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A number of potentially bioactive molecules can be found in nature . In particular , marine organisms are a valuable source of bioactive compounds . The activity of an α-galactosylceramide was first discovered in 1993 via screening of a Japanese marine sponge ( Agelas mauritanius ) . Very rapidly , a synthetic glycololipid analogue of this natural molecule was discovered , called KRN7000 . Associated with the CD1d protein , this α-galactosylceramide 1 ( KRN7000 ) interacts with the T-cell antigen receptor to form a ternary complex that yields T helper ( Th ) 1 and Th2 responses with opposing effects . In our work , we carried out molecular dynamics simulations ( 11 . 5 µs in total ) involving eight different ligands ( conducted in triplicate ) in an effort to find out correlation at the molecular level , if any , between chemical modulation of 1 and the orientation of the known biological response , Th1 or Th2 . Comparative investigations of human versus mouse and Th1 versus Th2 data have been carried out . A large set of analysis tools was employed including free energy landscapes . One major result is the identification of a specific conformational state of the sugar polar head , which could be correlated , in the present study , to the biological Th2 biased response . These theoretical tools provide a structural basis for predicting the very different dynamical behaviors of α-glycosphingolipids in CD1d and might aid in the future design of new analogues of 1 .
Compound 1 , [1] , [2] also referred to as α-GalCer , is a synthetic glycolipid that has shown promising bioactivity against diverse pathologies ( atherosclerosis , malaria , auto-immune diseases… ) . [3]–[7] This compound is presented to the iNKT cells via a MHC class 1-like protein , named CD1d , associated to β2-microglobulin . 1 can be readily loaded onto both mouse and human CD1d . The resulting binary complex is carried by Antigen-Presenting Cells ( APCs ) such as dendritic cells and macrophages . Upon recognition of the CD1d-glycolipid complex by the T Cell Receptor ( TCR ) ( Figure 1 ) , the iNKT cells rapidly initiate response that leads to a release of cytokines implied in Th1 ( interferon-γ , IFN-γ ) and Th2 ( Interleukin-4 , IL-4 ) immune response profiles , which yields opposing results from a medicinal point of view . Much research has been focused on being able to control the cascade by attempting to bias the cytokine release profile Th1/Th2 . Many biological and synthetic studies have been undertaken by a variety of research groups aimed at understanding the mechanism of 1 recognition in regards to both CD1d and TCR proteins with the hope of finding novel analogues with improved biological response ( magnitude and profile selectivity of the iNKT cell stimulation ) . [8]–[10] But , for the time being , the relationship between glycolipid pharmacomodulation and cytokine polarization is not completely understood . However , principles were established from earlier studies , based on the stability of the CD1d-ligand-TCR trimolecular complex . Mc Carthy et al . demonstrated experimentally that modifications of the lipid chain buried in the F′ channel of human CD1d molecules ( Figure 1 ) can modulate the TCR affinity . [11] However , they also showed that even though the length of the acyl chain controls the stability of the binary complex it does not automatically affect the CD1d-glycolopid complex affinity to TCR . In order to affect the binding affinity for TCR , it seems that a ligand chemical variation must additionally induce conformational changes of CD1d , which propagate to the TCR recognition surface . For example , these authors demonstrated that the incomplete occupation of the human CD1d F′ channel by the chain-shortened analogue 2 ( OCH ) [12] results in a less stable binary complex but also suggested that this causes conformational differences at the TCR recognition surface . In other respects , Porcelli et al . [13] have shown that the sugar head group of the ligand contacts the TCR in the initial phase whereas CD1d contacts with the TCR contribute to the stability of the whole complex . Since the IL-4 production was shown to require shorter TCR stimulation than IFN-γ , it has been thought to generate less stable CD1d-ligand complexes in order to impair the interaction at the ternary interface and then to elicit the cytokine profile toward a Th2 response . Conversely , a biased Th1 response was predicted through increasingly stable CD1d-glycolipid complexes . Hence , all attempts to design new ligands that polarize the cytokine profile were based on this principle of stability of the binary and ternary complexes , however not taking into account directly CD1d conformational changes induced by ligand modulations . Many modulations have been envisaged . Derivatives were obtained by changing at least one of the four distinct portions describing 1: the sugar part , the osidic bond , the polar linker , and the two lipid chains . Throughout our manuscript , the term “polar head” will refer to the distinct fragment of the ligand that is ( α-anomerically ) linked to the ceramide , regardless of the analogue . This designates the group that protrudes out the binding groove of the CD1d , towards the TCR , in contrast to the two more deeply anchored alkyl chains . In order to explain observed biological evaluation of analogues of 1 , molecular modeling supplements have sometimes been given by authors . However , these theoretical approaches are often limited to molecular docking or local optimizations of the ligand into the CD1d pockets . According to the huge number of degrees of freedom of 1 and its analogues such docking simulations are not appropriate to understand the mechanisms involved in such complex recognition process . Pipelier et al . [14] recently employed ab initio QM/QM′ level of theory to estimate electron withdrawing effect induced by the introduction of mono or difluoro substituent at C3 . Such CPU extensive quantum mechanical study is however limited to a part only of the entire system and to a single structure . In order to explore the impact of a single-amino acid variation at position 93 of iNKT on the conformational stability of Complementarity Determining Region ( CDR ) 3α , Gadola et al . [15] recently carried out molecular dynamics ( MD ) simulations of the ternary complex . Though very interesting , several questions arise from such simulation . Can tools for measuring conformational stability of CDRs be restrained to a single Cα-Cα distance probability distribution function ? Will the expected conformational change be observed during a unique 10 ns simulation ? Unlike experimental studies , only a few molecular modeling studies were fully dedicated to the investigation of the binary ( CD1d-glycoliplid ) or ternary ( CD1d-glycolipid-TCR ) complexes . To our knowledge only two previous studies have been fully devoted to the theoretical study of these systems . Nadas et al . [16] performed molecular dynamics of the ternary complex that allowed for the in-depth statistical and visual analysis of the H-bond network between CD1d , TCR and a set of 12 ligands during the simulation . The study was however limited to a single 3 ns simulation of a truncated complex , and tools for analysis were limited to hydrogen bond monitoring and visual inspection . In their theoretical study , E . Henon et al . [17] addressed the influence of three modulations on the dynamic behavior of the CD1d-glycolipid complex . However , only one 10 ns trajectory was produced for each of the four envisaged binary systems . In this previous study , the influence of the ligand modulations on the dynamic behavior of the CD1d-glycolipid complex was addressed by distance analysis and mainly focused on the so-called OTAN H-bond network built up from 2-OH , Thr154 , Asp151 , and NH . To be able to predict the strength of the Th1/Th2 polarization , very recently , De Spiegeleer et al . have presented multi-linear regression ( MLR ) and partial least squared ( PLS ) models based on a set of chemical descriptors of the ligand . [18] Though simple and easy to implement , these statistical methods partially failed to explain Th2 biased responses in vitro , and the use of numerous chemical descriptors prevents us from truly understanding the underlying correlation between chemical alterations and the cytokine-responses . Besides , for now , no MD simulations have been performed for characterizing differences between recognition of glycolipid by human or mouse CD1d . This point is important since there may be difference between antigen recognition by mouse and human iNKT cell . Nor is there any study of the influence of spacer lipids on the conformational behavior of the protein . Actually , sometimes , the CD1d protein has got non-specific lipid into its pockets , even in presence of a ligand ( for instance the shortened glycolipid 2 ) . Clearly , molecular dynamics is one of the most appropriate tools to study interactions in these complexes and to examine how chemical variation can affect their properties . However , as previously explained , since the ligand binding affinity to CD1d is not systematically correlated to the affinity of TCR to the binary complex , this reduces considerably the interest of ligand binding affinity predictions ( such as relative MMGB-SA calculations [19] ) . Moreover , relative binding free energy calculations via alchemical transformations [20] were ruled out due to the very large number of degrees of freedom in the two lipid chains in 1 . Simulating the ternary TCR-ligand-CD1d complex would be a very interesting study , but it would require still larger sampling compared with the binary system . Indeed , such a ternary complex is a very different system from the binary one . The TCR binding involves many additional interactions , compared to the binary complex , some of which stabilize the polar head at the binding interface ( Phe29 , Ser30 of CDR1alpha , and Gly96 of CDR3alpha ) . Thus , the impact of chemical alterations of the ligand involved in the ternary “lock and key” recognition might be observed but at a much larger time scale . Therefore , we have chosen another route . Since the TCR recognition process requires that the binding footprint onto CD1d to be maintained , instability of the ternary complex can occur only if this binding footprint is deteriorated . Figure 1 shows the non-covalent interactions[21] , [22] at this interface in the X-ray structure of human CD1d-1-TCR ternary complex ( PDB reference 2PO6 ) . Any deformation of this interface may disable the interaction with TCR , or at least makes it less effective . Hence , the idea is to focus on the binary complex ( CD1d-ligand ) and to determine how a chemical modulation of the ligand loaded into CD1d affects the interface part of this binary complex . Since binary complex-TCR contacts involve both the ligand polar head and the α1/α2 helices of CD1d , these two portions of the complex have to be particularly monitored during the simulations . Most of the SAR approach assumes that the structure of the ligand alone contains the features responsible for its biological properties . Here , using molecular dynamics , we took another step forward by studying the propagation of conformational changes ( induced by a chemical alteration ) from within the binding grove to the surface of the binary complex . In other words , in our study , we consider the whole binary complex as a “ligand” in correlating biological activity to chemical space . The reason why the TCR recognition process is altered may be due to an irreversible structural deformation of a portion of the interface or it may also result from an unusual dynamical behavior of this interface caused by abnormal fluctuations with larger amplitude for example . From MD trajectories , detecting these fluctuation deviations can be quite difficult because they can occur at different scales: small scale ( hydrogen-bond , residue fluctuation , polar head rocking ) or at even a larger scale ( secondary structure motions ) . That is the reason why , beyond simple distance monitoring , employing additional appropriate analyzing tools is important to reveal such unusual dynamic behavior . The question is whether chemical modulations known to induce a Th2 profile ( or Th1 ) will give MD simulations with similar features and readily detectable with post processing tools . This methodological and interpretative task is made more difficult since some ligands generally induce simultaneously both Th1 and Th2 responses ( only a bias is experimentally observed ) and also because experimental protocols that measure this bias can be quite different making it difficult to rigorously compare the Th1/Th2 bias values . Biological evaluations from different data sources can also sometimes be contradictory . [23] Furthermore , other factors such ligand solubility , biodisponibility , or stability in biological systems , may also play a role , which cannot be handled with our simple MD models . In our work , we carried out 48 MD simulation ( 11 . 5 µs in total ) involving eight different ligands ( conducted in triplicate ) ( Figure 2 ) in an effort to probe if a ligand modulation , which is known to lead to a Th2 bias , impacts on the conformational stability of the system , and how this ligand alteration is reflected in the dynamic behavior of the whole molecular structure . To what extent computational tools are able to predict a Th2 bias is very challenging for the design of new ligands . The main aim is then to test whether such a simple rule: complex instability-Th2/complex stability-Th1 , is really reliable or not . From our simulations , human and mouse CD1ds are found to exhibit different structural dynamics . Moreover , specific dynamical features haven been identified , which could be correlated here to Th2-biased systems exclusively .
Overall , 16 systems have been simulated and analyzed ( Table 1 , Figure 2 ) . Whenever it was possible , the short name chosen by the authors for the ligand has been followed . But additionally , the prefixes “H” or “M” have been inserted and stand for human or mouse , respectively . This set has been established in order to allow three types of comparison: human CD1d against mouse CD1d simulations , Th1 versus Th2 response and simulations with or without spacer lipid . The 2PO6 and 3SDA PDB structures[24] , [25] were used for the human and mouse CD1ds , respectively . Seven analogues of 1 have been chosen so as to account for modifications on the four portions of the glycolipid: the sugar part , the osidic bond , the polar linker , and the two lipid chains ( Figure 2 ) . The ligand 4 ( 7DW8-5 ) has got a phenyl group at the end of the shortened acyl chain . This analogue was shown to induce a Th1 biased response against human iNKT cells in vitro with binding affinity to human and mouse CD1d molecules . [26] The H_LIP designates simulations where the ligand has been replaced by two free lipid chains in the pockets F′ ( C12 ) and A′ ( C16 ) of the CD1d protein , thus , with no polar head present . These lipid structures have been taken from PDB files 3ARB [27] and 1Z5L . [28] The analogue 6 [29] has its acyl lipid chain truncated to eight carbon atoms and a Th2 polarization response of iNKT cells has been determined for this glycolipid . The 5 ( NU-α-GalCer ) ligand presents an ureido-naphtyl-group at position 6″ and exhibits pronounced Th1-biased cytokine production . [30] No interaction is observed between this ureido-naphtyl-group and the TCR part in the X-ray structure ( PDB 3QUZ ) . The analogue 2 is a glycolipid with a shortened sphingosin chain ( 9 carbon length ) and was found to induce a pronounced Th2-biased cytokine release compared to 1 . The molecule 3 ( OCH9 ) is almost identical to 2 , only differing from it by the addition of two methylene groups on the acyl chain . In the study by Mac Carthy et al . [11] the ratio of IL-4/IFN-γ found for this compound showed clearly a Th2-bias compared to the ratio obtained for 1 . 7 ( α-S-GalCer ) is a thioglycoside analogue of 1 and did not activate murine iNKT cells in vivo . [23] , [31] , [32] But , there are conflicting studies for the biological evaluation of 7 for human iNKT cells that is predicted to elicit a preferential Th2-biased response [32] or no real bias compared to 1 . [23] Substitution of the amide function by a 1 , 2 , 3- triazole group , compound 8 , induces Th2 cytokine production . [33] Finally , the human CD1d alone has been simulated ( H_CD1d ) without any ligand and free lipid chains in its pockets . A crystal structure is not available for each of the 16 studied systems . For some of them , the X-ray data are available but unfortunately they leave some protein structures incomplete . That is the reason why we selected only two CD1d structures: 2PO6 ( human CD1d ) and 3SDA ( mouse CD1d ) with full CD1d structures . Then , starting from the geometry of the KRN7000 ligand from PDB file 2PO6 we generated the OCH9 , AZOL , SaGAL , and 7DW analogues . For this , the program molden [34] was used to achieve chemical alterations . Truncating the sphingosine chain to obtain the OCH9 compound was straightforward . Using the Z-matrix editor of Molden allowed us substituting the amide function by a 1 , 2 , 3-triazole group ( AZOL compound ) , substituting an oxygen atom by a sulfur atom ( SaGAL ) and adding a phenyl group at the end of the shortened acyl chain ( analogue 7DW ) . In this way , the derived analogues fitted naturally into the hydrophobic pockets of human CD1d ( 2PO6 ) . In order for these analogues to fit also in the mouse ( 3SDA ) CD1d we performed the superposition of the 3SDA structure on the 2PO6 one ( using sequence alignment ) . The geometries of the analogues GOF , NUaGAL and OCH were taken from X-ray structures 1Z5L , 3QUZ and 3ARB , respectively . These protein structures were previously aligned to the 2PO6 one in order for the associated ligands to fit in the two binding pockets . Concerning the NUaGAL ligand , we had to modify the ureido-naphtyl group position in order to avoid steric clash with Trp153 in human CD1d . All these generated structures were then minimized in a first step before molecular dynamics simulations . Whenever a spacer lipid was added , it was taken from crystal structures 3ARB ( spacer lipid simultaneously present with the sphingosine chain ) and 1Z5L ( spacer lipid simultaneously present with the acyl chain ) . In the primary sequence of CD1d , the mouse protein contains an insertion of two residues between residues 89 and 90 of human CD1d . This does not concern the binding domain . The preparation of the protein ( disulfide bond linkages , protonation state of ionisable side chains ) was achieved using the same protocol as in our previous study . [17] In particular , as specified in the X-Ray structures , three disulfide covalent bonds were set between cysteine residues . We employed the package program xLeap of the AMBER11 package [35] to add the hydrogen atoms to the protein structure . The Propka [36] application was used to examine the protonation state of ionizable side chains with a focus on residues asparte , cysteine , histidine and glutamate in proximity to the ligand . No protonation state change was required compared to the state proposed by xLeap . Counterions ( Na+ ) were added such that to neutralize the unit system . The ff99SB force field was used for the protein . The general amber force field GAFF was used in conjunction with the antechamber program to describe the ligands . [37] The respgen procedure was employed to derive atomic charges from HF/6–31G* electrostatic potential calculations obtained with the Gaussian package [38] . The ligand and protein CD1d were fully explicitly solvated in a truncated octahedral box using TIP3P water molecules with a buffer distance of 7 . 0 Å and under periodic boundary conditions . We have carefully checked that the initial water molecules buffer remains during our simulations , and the CD1d protein does not interact with its neighbors in periodic images . The entire system consisted of about 40700 atoms ( depending on the ligand ) . All the dynamics calculations were carried out with the programs sander and pmemd of the AMBER11 package . The particle mesh Ewald procedure was employed to handle long-range electrostatic interactions . The default value of 8 . 0 Å for the non-bonded cutoff was set to calculate van der Waals and electrostatic energies . No switching function was used for the van der Waals interactions . The system was then carefully prepared . At first , the energy of the entire system was minimized with 1000 cycles of steepest descent followed by 1000 cycles of conjugate gradient minimization . This process was repeated twice . Classical Langevin NVT molecular dynamics simulations ( collision frequency = 2 ps−1 ) employed a 2 fs integration time step ( bonds involving hydrogen atoms were constrained ) . Firstly , the water molecules were heated from 0 to 300K during 20 ps , and equilibrated for 20 ps . A force constant of 100 kcal . mol−1 . Å−2 was used to restrain all other atoms during these steps . After cooling the solvent molecules to 0 K during 20 ps , this heating-equilibrating procedure was re-run twice for the entire system with no constraint and followed by 240 ns of data collection . Prior to production , in order to allow the density to equilibrate , our system has been equilibrated using the NPT ensemble ( isothermal-isobaric ensemble ) at 300K and 1 atm for 40 ps . Three 240 ns trajectories have been produced in parallel for each of the 16 systems ( 0 . 72 µs each ) . Coordinates of the system were written every 1 ps . As said above , the polar head is known to protrude out the binding groove of the CD1d and is a key element in the TCR recognition . Its orientation is characterized by three dihedral angles: φx , φy , φz . Therefore the ability of the GAFF force field to reproduce static ab initio quantum chemistry calculations was tested on these three degrees of freedom . Focusing on these three parameters , rigid potential energy scans for internal rotations about the three axes φx , φy , φz in the 8 compounds were performed to compare GAFF energies to electronic structure calculations ( at the DFT/6-31G* level of theory using the M06 hybrid functional , which is recommended by Truhlar and col . [39] for non-covalent bonds descriptions ) . Single points energy calculations were performed every 5° . It can be clearly seen from Figure S1 that the potential energy profiles for these three rotational degrees of freedom are reproduced in a satisfactory manner by the force field GAFF . The rotations around the two first angles ( φx , φy ) emphasize wide regions of steric hindrance ( several tens or even several hundreds of kcal/mol ) corresponding to steric clashes between the head group and the osidic bond , the sphingosine and acyl chains . Outside these very repulsive zones , GAFF correctly describes the minimum energy regions . Our tests were limited to these three internal coordinates . Indeed , it is to be noticed that in these binary complexes , the lipid anchors and the hydrogen bonds considerably reduce the other internal degrees of freedom of the ligand . A 2D-RMSD graph represents the root mean square deviation ( RMSD ) of every conformation to all other conformations of a simulation , as a function of time during a 240 ns simulation . Each point of the two-dimensional plot corresponds to the RMSD between two trajectory structures , and its value is encoded into a color . The diagonal elements ( black ) represent self-comparison ( zero RMSD ) and the yellow dots show the largest pairwise RMSD . RMSD values have been computed based on the binding region , i . e . , using an atom selection including the alpha carbons of helices α1 and α2 only ( residues in the range 58–92 and 137–184 in human and in the range 58–92 and 139–186 in mouse ) . The average of all RMSD values of this matrix was also computed for each graph . The resulting number represents the level of fluctuation of the whole system during the simulation . In parallel , the root mean square fluctuation ( RMSF ) of the CD1d protein was computed as a measure of the average atomic mobility . It was calculated on a residue basis using the RMSF of the positions of the Cα atoms of all the protein . A so-called dihedral footprint was computed , based on 9 dihedral angles made by the Cα atoms of 9 CD1d residues that form a contact with TCR . The considered residues are: 76 , 79 , 80 , 83 , 84 , 87 , 99 , 147 ( 149 in mouse ) and 150 ( 152 in mouse ) . Sine and cosine transformed dihedral angles were used to avoid problems arising from the circularity of angles . The human 2PO6 X-ray structure was chosen as the reference in all simulations for the calculation of the dihedral values . For one given dihedral angle θi , the squared deviation from its reference position θ0 is measured as follows: . This formula derives from the sum of the two squared differences for sine and for cosine . The final index was obtained by calculating the root mean square deviation over all the 9 dihedral angles . This index varies in the range 0–2 and the percentage change is reported in the figures . The change in inter-helix distance was monitored by computing the distances between centroid pairs along the two portal helices α1 and α2 . Each centroid is formed by four successive residues . Helices α1 and α2 consist of 7 and 10 centroids , respectively . The chosen procedure is based on a modified Hausdorff distance calculation . For every centroid of helix α1 we determine the smallest distance to any centroid of helix α2 . The sum of all these distances is computed . The procedure is repeated for every centroid of helix α2 relative to all points of helix α1 and a second sum is deduced . Finally , the inter-helix separation was assessed by summing these two distances and by averaging over the total number of centroids of helices α1 and α2 . Each dihedral angle θi formed by 4 bonds joining 4 successive Cα atoms along the main chain of the protein CD1d is a probe of the free-energy landscape ( FEL ) along the primary sequence . The 1D Free Energy Landscape ( 1D_FEL ) [40] of these coarse-grained dihedral angles are obtained based on the logarithmic relation at 300K: G = −RT ln P ( θi ) using the one-dimensional probability distribution function P ( θi ) derived from our simulations . For a given dihedral angle , in order to compare the 1D_FEL between two simulations i and j , the following procedure was carried out . First , the 1D_FEL curve j was shifted on the energy axis so as to align the minima of i and j . Next , the curve j was shifted on the angle axis so as to minimize the Hausdorff-like distance between the two curves i and j . In this way , the resulting distance value ( with unit mixing the energy and angle axes ) measures shape dissimilarity between the two 1D_FELs . Points with energy above 20 kBT in the 1D_FEL were excluded from this procedure . Similarly , for the polar head , three-dimensional histograms were constructed from values of dihedrals φx , φy , φz and converted to free energies ( 3D_FEL ) based on an analogous logarithmic relation at 300K using the probability distribution function P ( φx , φy , φz ) given by our simulations . Each of the isosurfaces shown in our paper corresponds to points of the 3D-space ( φx , φy , φz ) with a constant free energy isovalue ( in kcal mol−1 ) . Nine isovalues were considered from 1 to 9 kBT . Our study disclosed the existence of specific states with lifetime ranging from a few nanoseconds to 30ns . It takes only a few picoseconds to switch from one of these states to the other . Due to this very short timescale , no dihedral principal component analysis ( dPCA ) could be carried out to correlate the occurrence of these transitions to specific structural and dynamical features of the system ( coordinates of the system were written every 1 ps during the MD ) .
To achieve our objectives , a large conformational sampling is required . Such a large amount of data is difficult to analyze . Our trajectory analyses use a wide range of tools to extract the most relevant and unanticipated events . Since we are interested in detecting conformational behavior differences between systems , these tools are now exemplified in the case of the two systems Sy1 and Sy16 , expected to behave quite differently . First , 2D-RMSD ( α1/α2 interface ) can be helpful to detect different conformational “substates” . While replicas I and II of H_aGAL show a relative homogenous 2D-RMSD plot ( Figure 3 ) , replica III appears to move into two “wide” different conformations . Trajectories of H_CD1d give more contrasted patterns , with replica III showing three dissimilar clusters . The matrix average of RMSD values accurately reflects the level of granularity observed by visual inspection ( numbers reported in Figure S2 ) . These plots clearly show that the two CD1d helices can be very stable during 240 ns or in contrast go through several distinct conformational states with a life of a few tens of nanoseconds . Therefore , it seems that one cannot just perform a single 240 ns MD simulation but rather running multiple MD with different starting initial conditions is better to study the interface of the binary complex . Surprisingly , at this stage , though H_CD1d displays slightly more contrasted 2D-RMSD figures , the α1/α2 interface of H_aGAL and H_CD1d does not appear to have greatly differing dynamical behavior . Despite the presence of ligand 1 in the case of H_aGAL , a comparison of the per-residue RMSF calculated from the binary complex trajectories shows that the two systems ( with or without ligand ) undergo very similar fluctuations ( Figure 4 , panel A ) , in particular no appreciable difference is observed in the ligand-binding pocket . For both systems the linker domain ( amino acid sequences separating the helices domain from the beta sheet part of the CD1d protein ) is the most flexible region , as expected . The extremities of the helices show the highest mobility , beta sheets are very stable . The same conclusions arise for the three replicas . The advantage of this tool over 2D-RMSD is to localize the regions of high mobility . However , it does not permit to distinguish between two situations: ( a ) regular but larger fluctuations due to higher mobility of some residues at the local scale in specific region of the interface but maintaining the secondary structure or ( b ) direct loss of secondary structure elements occurring at one point of the simulation , involving a larger amplitude motion and impacting RMSF values . The analysis of the 1D Free Energy Landscape ( 1D-FEL ) of the Coarse-Grained Dihedral Angles of the protein ( CGDA , defined by four successive alpha carbon atoms ) was used with a view to detecting the presence of such possible structure deformation . This methodology has been recently applied to studies of proteins . [40] In order to capture the largest deformations in the protein resulting from the absence of ligand we decided to compute a Hausdorff-like distance ( see Materials and methods section ) that measures how far two Free Energy Profiles ( FEP ) are from each other for a given dihedral angle in H_aGAL or in H_CD1d . The deformations can be well appreciated in panel B of Figure 4 where the color of the ribbons is directly proportional to this distance acting as a dissimilarity index . We report at the bottom of Figure 4 the FEP of the six residues the most influenced by the presence of 1 . As can be seen , significant anharmonicity appears at the end of the helix α1 ( on the side towards the F′ pocket ) when the ligand is lacking . This comes in conjunction with the middle of the helix being more rigid . The lack of ligand clearly produces a bend in the middle of helix α1 combined with the destructuration of its extremity . One may now question how this deformation will affect the binding footprint between the TCR and CD1d . The evolution of this interface during the simulation was monitored according to two complementary indexes calculated with reference to the X-ray structure ( PDB 2PO6 ) . In Figure 5 , the first index ( the distance between the centroids of α1 and α2 helices ) reveals the closure of the cavity entrance in the lipid-free system ( H_CD1d ) . Secondly , a so-called dihedral footprint was computed , based on the dihedral angles made by the successive alpha carbons of the 9 CD1d residues that are known to form a contact with TCR . This index varies in the range 0–2 and the percentage change is also reported Figure 5 ( right ) . According to this index , the ligand-free CD1d interface greatly deviates from the reference ( X-ray structure ) , by about 50% in comparison with the H_aGAL system ( 35% ) . All these results are in agreement with the theoretical results of Garzón et al . [41] who observed the same trend . Finally , the conformational space explored by the polar head of the ligand during the simulations of H_aGAL was described using the three torsion angles of the three successive rotatable bonds shown in Figure 6 . In the following , the first one ( φx ) will be referred as the anomeric pivot , the second one ( φy ) as middle pivot and the last one ( φz ) will be denoted the amide axis . Theoretically , rotations around φx and φz yield conformations in which the polar head has rotated horizontally at the top of the cavity entrance . In the CD1d environment , these two motions should be hardly sterically hindered by the two helices . In contrast , rocking about the middle pivot will get the polar head striking the helices . In all cases , such individual rotations would require the loss of the OTAN H-bond network . The free energy landscape of the MD trajectory along these three coordinates is illustrated in Figure 6 for the system Sy1 . The top panel shows all points in the ( φx , φy , φz ) space with isovalues of G being one to nine kBT ( 0 . 6 to 5 . 3 kcal . mol−1 ) for replica I of H_aGAL . For all simulations , the conformational space does not grow any more for energies above 9 kBT . For replica I , the 3D-FEL emphasizes only one conformational state , showing that the OTAN network is strong enough to maintain the orientation during all the 240ns simulation . This state , hereafter referred to as “OTAN state” , is centered about the φx , φy , φz coordinates: ( 50° , 157° , 51° ) in replica I . Comparison with the three replicas of H_aGAL at G = 5 . 3 kcal . mol−1 ( 9 kBT , bottom panel of Figure 5 ) reveals the presence of the OTAN state in every case . But in addition , two secondary conformational states can be visited , mainly limited to the ( φx , φz ) plane . It is very important to note that , as with the OTAN state , these two complementary states maintain the polar head interacting with helix α2 . Actually , the second state observed in replica II is a combination of two rotations about φx and φz that limits the displacement of the sugar ring ( see Figure S3 ) . The third state observed in replica III corresponds to a rotation of about 180° around φz , which brings again the polar head in contact with helix α2 ( see Figure S4 ) . In this last state , the Asp151 residue is now hydrogen-bonded to the 4′-OH group ( sphingosine chain ) and the Trp153 side chain is again in van der Waals ( VDW ) contact with the hydrophobic side of the polar head . But most importantly , no conformations are observed involving rotations about the middle pivot φy , points that would lie inside the 3D-FEL box , involving the “y” axis . Considerable structural similarities are apparent between mouse and human CD1d molecules . Focusing on the α1 and α2 helices-binding domain , human and mouse amino acid sequences show a similarity of 81 . 2% and an identity rate of 65 . 2% in this portion of the protein . The amino acid sequence is highly conserved in particular the residues Asp80 , Asp151 ( 153 in mouse ) and Thr154 ( 156 in mouse ) , which are of crucial importance to bind the ligand through the OTAN network , are present in both proteins . There are 25 amino-acid variations located in the TCR-interface domain . One of these seems to be particularly important . At position 153 , the crystal structures show the presence of a bulky tryptophan side chain in human CD1d ( Figure 1 ) in contrast with the glycine ( no side chain ) in mouse CD1d . This Trp153 side chain is in VDW contact with the hydrophobic side of the sugar in a face-to-face configuration ( see Movie S1 ) and one may question whether the absence of this residue in the mouse CD1d may exert an indirect effect on TCR binding or not . Actually , as can be seen in Figure 1 , the galactose head group acts as a mechanical stop restricting the TCR approach to only one side: the F′ part of the CD1d groove . Both human and mouse CD1d proteins are able to induce a balanced Th1/Th2 response depending on the loaded ligand . However , the biological activities of analogues of 1 loaded into mouse or human CD1d can be sometimes quite different . [14] , [32] Hence , four “human versus mouse” comparisons are conducted for systems: Sy1/Sy2 , Sy3/Sy4 , Sy6/Sy7 and Sy8/Sy9 . These systems were chosen because , with ligand unchanged , human and mouse CD1ds produce the same polarization ( Th1 or Th2 ) . Moreover , to ensure a thorough comparison , the ligand 2 is supplemented in both human and mouse simulations with a “spacer” , i . e . a linear hydrophobic compound taken from the CD1d-2 PDB ( 3ARB ) . From the analyses of these 24 trajectories , the outstanding results are the following . From a structural point of view , in all CD1d mouse simulations , we clearly observe an increased inter-helix distance localized on the A′ pocket side . On average , the inter-helix distance is about 1 . 3 Å larger in mouse simulations than in human CD1d simulations ( see Table S1 ) . This is not surprising since this portion of the two helices concentrates ten amino acid variations ( 8 residues on α2 helix and 2 on α1 helix ) involving residues with physico-chemical properties very different between human and mouse proteins . This effect is however counterbalanced on the F′ pocket side where the portions of helices α1 and α2 come closer such that overall , the total inter-helix distance is almost the same for human and mouse CD1ds during the simulations ( see Figure 7 and Table S1 ) . Curiously , the M_NUaGAL/H_NUaGAL comparison exhibits a still larger increase of the inter-helix distance: 2 . 1 Å larger in mouse simulations than in human . This is likely to be correlated with the fact that the naphthyl group introduced on the head part of this analogue facilitates the interaction with two residues in a small pocket between helices α1 and α2 of CD1d ( as demonstrated by Trappeniers et al . [30] ) . One of these residues is Ile69 in humans , replaced by Me69 in mice . Finally , it is to be noted that this inter-helix variation observed between mouse and human CD1ds is not accompanied by a dihedral footprint deviation ( measured as a percentage value from our analysis tool based on CD1d contacts ) . From a dynamical point of view , a higher mobility is found for the human protein CD1d compared to mouse CD1d . This is slightly noticeable from the 2D-RMSD ( see Figure S2 ) and from RMSF pictures where more fluctuations are observed for the human linkers . From the 3D-FEL analysis tool , comparing the motions of the polar head in mouse or human CD1d , all simulations emphasize more flexibility when the ligand is loaded into the human CD1d rather than in the mouse CD1d . Whether for human or mouse , there is predominantly only one conformational free energy well explored during the simulations , which we term the “OTAN state” ( Figure 6 ) . However , the conformational space sampled within the mouse simulations is significantly smaller than the one for human simulations . This is evidenced by estimating the corresponding volumes enclosed by the free energy isosurface ( 9 kBT ) in the 3D representation ( φx , φy , φz ) for both mouse and human simulations ( see Table S2 ) . Unexpectedly , we observe a very intriguing free energy landscape for the replica II simulation of human 2 , indicating an ensemble of five conformational states . This will be discussed in more details in the next section . The goal is now to find out correlation at the molecular level , if any , between chemical modulation of the ligand and the orientation of the known biological response , Th1 or Th2 . Analogue 1 ( Th1 ) is compared to 2 ( Th2 ) , 7 ( Th2 ) and 8 ( Th2 ) within three comparisons . Firstly , two comparisons are made with the ligand loaded into the human CD1d: ( a ) H_aGAL/H_OCH or ( b ) H_aGAL/H_SaGAL . Additionally , in mouse CD1d , the compared behavior ( c ) M_aGAL/M_AZOL is then addressed . This study focuses on the systems Sy1 , Sy2 , Sy3 , Sy12 and Sy14 of Table 1 . The key results are the following . From a structural point of view , H_OCH and M_AZOL , simulations revealed significant structural changes of the CD1d protein with regard to the other simulations . The replica II ( mainly ) of the H_OCH simulation shows a modification of the α1 helical structure involving residues 74 to 82 ( on the F′ pocket side ) as revealed and evidenced by the 1D-FEL analysis ( it can be seen on Figure 8 , middle panel ) . Overall , human CD1d in complex with 2 appears to be slightly more fluctuating compared to H_aGAL simulations . More specifically , the residues on the F′ pocket side display a higher mobility in the RMSF analysis of H_OCH . All these changes are very likely due to the truncated sphingosin chain of 2 , even though a spacer lipid complements the F′ pocket in this case . The presence of the ligand 8 in the human CD1d protein causes a pronounced enlargement of the 1D-FEL for dihedrals around the residue 153 ( residues 151 to 155 of helix α2 ) . This was strongly observed for all three replicas of the M_AZOL system , compared to the M_aGAL one . This clearly shows that the replacement of an amide function with a triazole group significantly increases the flexibility of the α2 helix and consequently disturbs the OTAN hydrogen bond network , which involves the residues Asp151 and Thr154 ( helix α2 , human numbering ) . A polar head destabilization is then expected ( discussed hereafter ) . Concerning the ligand 7 , no CD1d structural change has been observed here . In spite of the two aforementioned structural changes , absolutely no CD1d difference has been observed concerning the binding footprint and the inter-helix distance between all these systems , which could have explained a Th2 bias . We turn now to the discussion about the dynamical features of the polar head . Very interestingly , the three ligands ( 2 , 7 , 8 ) , which are known to induce a Th2 bias , display multiple well 3D-FEL ( Sy3 , Sy12 , Sy13 and Sy14 on Figure 8 ) compared with ligand 1 ( Th1 bias in human and mouse CD1d , Sy1 and Sy2 on Figure 8 ) . H_OCH simulations exhibit this feature only once , for replica II . This suggests that at least three trajectories or more are needed to reveal and confirm such a conformational behavior . A common pattern to these three ligands is a new conformational state , which appears about 1 . 8 kcal . mol−1 above the OTAN state , designated as the “aside” state in Figure 8 . The polar head has rotated by about 110° relative to the φz axis in the resulting conformations . In these conformations , the OTAN network and the hydrogen bond with Asp80 are lost , or partially lost . The polar head points now toward the α1 helix but no direct contact has been observed between the sugar and this helix . In fact , the two residues Val72 and His68 of helix α1 , which face the polar head , are positioned too far away to attract the ligand . In other words , the source of the new observed state is not helix α1 . Thus , it seems that a chemical alteration is able to make accessible the “aside” state , thanks to the CD1d interaction . It should be noticed that the VDW contact initially made by the hydrophobic side of the sugar with Trp153 in the OTAN state ( Figure 1 ) , is also lost in the “aside” state . The new polar head orientation clearly penalizes a TCR recognition process . But this reorientation towards helix α1 is found to be reversible . The lifetime of this state ranges from a few nanoseconds to 30 ns . It takes only a few picoseconds to change from the OTAN state to the “aside” state and vice versa . It is difficult to correlate the occurrence of this transition to specific structural and dynamical features at such a short scale , but obviously , the new state arises in conjunction with the partial or total loss of the OTAN network and the lost of hydrogen-bond between 3′-OH and Asp80 . Also , rare and slight rotations around the middle pivot φy can occur . From an energetic point of view , the OTAN state remains the ground state in all our simulations ( except in the case of M_SaGAL that will be discussed below ) . For the H_SaGAL simulations , the “aside” state is also present . But moreover , the free energy landscape shows unstructured features above 2 kcal . mol−1 , indicating that all conformations are frequently visited along the “x” axis in a broad basin ( Figure 8 ) . In other words , in these high-energy states , the polar head is almost free to move around φx . Extending this 3D-FEL analysis of the polar head dynamics to all studied systems leads to very interesting results . All the binary systems known to have a Th1 biased response ( Sy1 , Sy2 , Sy6 , Sy7 , Sy8 , Sy9 ) never show the “aside” state , nor such multiple-well energy landscapes in the ( φx , φy , φz ) space , for any replica . In contrast , all the other seven loaded CD1d systems ( but Sy4 and Sy10 ) for which a Th2 biased polarization has been demonstrated , are characterized ( at least once ) by a multiple-well landscape including the specific state above-mentioned . This concerns the systems Sy3 , Sy5 , Sy11 , Sy12 and Sy14 in Table 1 . One may question whether it is a pure coincidence . Obviously , despite our very large-scale MD simulations , a more representative statistical sample of MD trajectories is required to further reinforce this trend ( typically , more than three replicas would be needed ) . But , our results are consistent with the accepted model that correlates a Th2 biased response to chemical modulations yielding a less stable CD1d-glycolipid complex . More precisely , we show here that the complex instability results from increased sugar head fluctuations above the CD1d binding groove that will hinder TCR recognition . All the simulations showing an “aside” state are associated with a Th2 response exclusively . More interesting is the simulation of the M_SaGAL system , which displays a very particular 3D-FEL illustrated at the bottom of Figure 8 . All three replicas also reveal multiple energy wells with broad basins and the so-called “aside” specific state is present . But it is the only system for which the OTAN state is not the ground state . Actually , the specific “aside” state is observed to be the lowest one in the 3D-FEL analysis of M_SaGAL , the OTAN state being about 1 . 2 kcal . mol−1 above it . Furthermore , in our study , it is the only system that displays conformations involving large rotations of the polar head around the middle pivot φy , resulting in points distinctly inside the 3D-FEL box . A typical conformation is illustrated in Figure 8 . It is associated to a third distinctive state we call the “flip” state in which the polar head hydrogen bonds to the α1 helix . Let us recall that rotations about this φy axis would normally drive the polar head in contact with the helices . Such motions are clearly hindered in all other studied systems . This means that in this case , the polar head of the thio-galactoside derivative slightly pulls out of the CD1d host during the M_SaGAL simulation . Relative to the C–O , the C–S bond is longer . Combined with a greater separation inter-helix distance observed on the A′ pocket side of mouse CD1d , this is probably the reason why we observe this specific dynamical behavior for the M_SaGal simulation . Obviously , these slightly “extricated” conformations will prevent the TCR binding . This theoretical result fully agrees with biological evaluations [23] , [31] , [32] of this compound that show no activity against mouse iNKT cells . In this general analysis , it is to be noted that , although they are known to give a Th2 biased response , the two binary systems Sy4 ( M_OCH ) and Sy10 ( H_GOF ) do not display the “aside” state . Additional replicas might be necessary to observe such behavior . However , in our simulations , these two systems with a truncated glycolipid chain ( acyl or sphingosin ) involve a strong change in the 1D-FEL of dihedrals on the helix α1 bearing the contacts , which are critical for CD1d-TCR recognition . Clearly , anharmonic flat or double-wells appear in the 1D-FEL of these dihedral angles . This suggests that under chemical modulation not only the polar head flexibility but also the deformation of helix α1 itself can deteriorate the TCR recognition process . When short chain lipids ( in analogues ) are bound to the protein , spacer lipids may be simultaneously present in the pockets of CD1d . For example , two X-ray structures ( PDB references 3ARB and 1Z5L ) show the presence of A′ and F′ pockets spacer lipids when CD1d is partially occupied by the sphingosin truncated 2 and the acyl truncated 6 analogues , respectively . In the absence of the glycolipid ligand , endogenous ligands can also fill the entire volume in order to maintain stability and prevent protein denaturation [28] . It was then interesting to examine how the presence or the lack of spacer lipid impacts the polar-head dynamics and the conformations of the CD1d surface . Firstly , the influence of the presence of a spacer is addressed by comparing the trajectories of the systems Sy3 ( with 2+ lipid ) and Sy5 ( with 3 ) . The two ligands are almost identical , the molecule 3 having only two CH2 more in its acyl chain . The tremendous difference is that in the system Sy3 , an additional linear hydrophobic compound C12H26 is present in the F′ pocket in addition to 2 . As expected , 2D-RMSD and RMSF analyzing tools indicate a higher fluctuation for the system lacking the spacer lipid . This increased flexibility concerns the CD1d residues in the vicinity of the F′ pocket . Also , in the absence of spacer lipid ( Sy5 ) the inter-helix distance becomes slightly larger ( by about 0 . 3 Å , see Table S1 ) . In addition , the absence of a spacer lipid causes a slightly larger conformational space of the polar head in the 3D representation ( φx , φy , φz ) of 3 compared to 2 ( see Table S2 ) . Both systems reveal the specific “aside” state on their 3D-FEL figure , but the simulation without complementary free lipid displays broad basins with the polar head almost free to move around the φx axis ( see H_OCH and H_OCH9 3D-FELs in Figure S5 ) . All these results are consistent with the experimental findings of Garcia et al . [42] who concluded that the spacer lipid appears to work in concert with the ligand to stabilize the binding groove . How the presence of the polar head impacts on the molecular dynamics was addressed based on the comparison between simulations Sy1 and Sy16 ( human CD1d with two headless lipids filling simultaneously pockets A′ and F′ ) . As expected , the observation of RMSF figures shows that fluctuations are more important in the middle of helix α2 when the polar head is missing . But further , fluctuations also tend to affect helix α1 in this case . This shows the importance of the presence of the OTAN hydrogen bond network for stabilizing the binding groove and then the CD1d surface in view of recognition by TCR . From the analysis of 48 trajectories , it appears that the α1/α2 inter-helix distance differs in mouse and human loaded-CD1d simulations . A greater separation distance is observed on the A′ pocket side of mouse CD1d where strong residue dissimilarities appears between human and mouse helices . This point may be interesting in view of the known differences in cytokine profile production that sometimes appear between human and mouse systems . For the lipid-free CD1d simulations , we observe the spontaneous closure of the binding domain entrance , accordingly with previous theoretical results . [41] In complement , a spacer lipid simultaneously present with the ligand stabilizes the F′ pocket . In a similar manner , we show the key role of the polar head in stabilizing the binding groove at the CD1d surface . The goal of this study was to get insight into the impact of a chemical variation of molecule 1 on the structure of the binary complex formed between the ligand and protein CD1d . A crucial point was how this could affect the CD1d binding footprint with possible deterioration of the TCR recognition . The major result of our study is that the dynamical behavior of the polar head seems to be a key factor when trying to correlate a ligand modulation with the orientation of the known biased biological response , Th1 or Th2 . Considering three successive dihedral degrees of freedom ( φx , φy , φz ) , which govern the polar head rotation above the CD1d binding groove , our simulations permitted to identify three model situations . In the first one , the conformations visited by the polar head during the simulation mainly fall in a portion of the free energy landscape we call the “OTAN” state . It corresponds to the polar head hydrogen-bonded to the CD1d through the well-known H-bond network built up from 2-OH , Thr154 , Asp151 , and amide-NH . Only a few higher free energy states can appear , but all of these maintain the polar head in contact with helix α2 . Sampled conformations are exclusively restricted to well-separated ( φx , φz ) minima corresponding to rather structured states . A second situation corresponds to the emergence of a specific conformational state in the energy subspace ( φx , φz ) , about 1–2 kcal . mol−1 above the OTAN state . This new “aside” state is characterized by the polar head pointing toward the α1 helix , but without direct interaction with CD1d . It arises in conjunction with the partial or total loss of the OTAN network and the loss of the hydrogen bond between 3′-OH and Asp80 . The new polar head orientation clearly penalizes the presentation to TCR . The lifetime of this state ranges from a few nanoseconds to 30 ns . The ligands associated with Th1 biased response never displayed this “aside” state in their free energy landscape in any simulation replica . By contrast , all the simulations showing an “aside” state are associated with a Th2 response exclusively . Obviously , the previous 10 ns simulations of Henon et al . [17] were missing this conformational space . Sampling has been improved here with longer trajectories but also mainly by running several independent simulations , thus exploiting different starting conditions . Three 240 ns trajectories have been produced for each of the 16 systems ( 0 . 72 µs each ) . Only on this time scale and using multiple replicas could the emergence of these specific states be disclosed . But a still more representative statistical sample of MD trajectories would be required to further reinforce our findings . The interesting thing is that our model holds for very different chemical modulations affecting the anomeric bond as well as the polar linker , or either the sphingosin lipid chain . A third model situation arises when the specific “aside” state become the ground state , below the OTAN state . Then , at higher energies , new conformations appear in which the polar head turns upside-down and hydrogen bonds to the helix α1 , a situation incompatible with TCR recognition . We observe then broad basins in the 3D free energy landscape of the polar head that must necessarily involve the slight extrication of the sugar head from the cavity entrance , correlated with no biological activity . In this case ( thio-analogue of 1 ) , our findings indicate that mouse simulations behave differently than human ones . The existence of a high-energy but populated “aside” state in the simulations of some analogues of 1 very likely contributes to reduce the stability of the ligand-CD1d binary complex . Binding free energy calculations using molecular dynamics tools could have potentially provide information . However , we presume that the very large number of degrees of freedom in these glycolipids would have prevented obtaining accurate results . Moreover a change in the binary complex stability does not systematically affect the affinity to TCR . Therefore , such binding affinity calulations are certainly not the best way to find out relationships here . The route we have chosen allowed unambiguous identification of these states . Of course , it would be naive to believe that a molecular model can capture such a complex biological response . The mechanisms by which analogues govern the cytokine profile are multifactorial . For example , Sullivan et al . [43] showed that a critical parameter for a glycolipid to influence the cytokine response is its stability in cells . Overall , our results are consistent with the often-invoked model that correlates a Th2 biased response to chemical modulations yielding a less stable CD1d-glycolipid complex and hence a less stable ternary complex . Additionally , the 1D free energy landscape analysis tool permitted to show that not only the polar head but also modifications of α1 and α2 helical structures could result from chemical variations of molecule 1 . Even though the chemical alterations seem large and significant , the set of molecules studied here have common structural features , what could limit the application of our methodology to other class of analogues . First , chemical alterations that prevent defining the three dihedral angles φx , φy , φz cannot be studied within our procedure . This concerns analogues that derive from specific osidic link variations . Moreover , it is clear that our results here only apply to analogues having a galactose residue . Another sugar group ( glucose , … ) would likely change the free-energy profiles in a way that cannot be predicted by our results obtained with the galactose component . Furthermore , our methodology only allows checking that preconditions for interaction of the binary complex with the TCR exists . From our study , these requirements for an efficient association are: a polar head dynamics with significantly populated OTAN state , and a limited deformation of helices α1 and α2 . But our model ( based on the CD1d-ligand system ) cannot explicitly handle the interactions between TCR and the binary complex . However , our polar head 3D-FEL tool combined with the 1D-FEL analysis of CD1d dihedrals in the binary complex provides a structural basis for predicting the very different dynamical behaviors of α-glycosphingolipids in CD1d and might aid in the future design of new analogues of 1 . | To modulate the natural immune response toward aggressive ( Th1 ) or protective ( Th2 ) profiles remains a difficult challenge , but can also offer great therapeutic opportunities , particularly for the treatment of cancer or auto-immune diseases . It has been demonstrated that a particular type of cells , named invariant Natural Killer T ( iNKT ) cells , are able to induce both protective and aggressive response profiles , depending on the antigen that is presented to it by CD1d proteins . Since this discovery , efforts have been made to find synthetic compounds that would selectively induce Th1 or Th2 immune response . KRN7000 was the first to selectively induce a Th1 response , and for two decades many analogues of this compound were synthesized . Some of them effectively induce Th1- or Th2-biased responses . But , unfortunately , the Th1/Th2 selectivity mechanism remains unclear . That is the reason why we have undertaken large-scale molecular modeling ( molecular dynamics ) simulations of various CD1d-ligand systems with the aim to find out correlation between chemical modulation and the orientation of the biological response for a variety of known ligands . | [
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] | 2014 | Relationships between Th1 or Th2 iNKT Cell Activity and Structures of CD1d-Antigen Complexes: Meta-analysis of CD1d-Glycolipids Dynamics Simulations |
Plant defense responses need to be tightly regulated to prevent auto-immunity , which is detrimental to growth and development . To identify negative regulators of Resistance ( R ) protein-mediated resistance , we screened for mutants with constitutive defense responses in the npr1-1 background . Map-based cloning revealed that one of the mutant genes encodes a conserved TPR domain-containing protein previously known as SRFR1 ( SUPPRESSOR OF rps4-RLD ) . The constitutive defense responses in the srfr1 mutants in Col-0 background are suppressed by mutations in SNC1 , which encodes a TIR-NB-LRR ( Toll Interleukin1 Receptor-Nucleotide Binding-Leu-Rich Repeat ) R protein . Yeast two-hybrid screens identified SGT1a and SGT1b as interacting proteins of SRFR1 . The interactions between SGT1 and SRFR1 were further confirmed by co-immunoprecipitation analysis . In srfr1 mutants , levels of multiple NB-LRR R proteins including SNC1 , RPS2 and RPS4 are increased . Increased accumulation of SNC1 is also observed in the sgt1b mutant . Our data suggest that SRFR1 functions together with SGT1 to negatively regulate R protein accumulation , which is required for preventing auto-activation of plant immunity .
To protect themselves from infections by microbial pathogens , plants have evolved a large number of immune receptors to sense pathogen-derived molecules and trigger defense responses [1] . Resistance ( R ) proteins with nucleotide-binding ( NB ) and Leucine-rich repeat ( LRR ) domains constitute the main type of intracellular plant immune receptors . In animals , similar nucleotide-binding domain and LRR-containing ( NLR ) proteins also function as intracellular immune receptors [2] . In plants , activation of NB-LRR R proteins often results in localized programmed cell death known as hypersensitive response ( HR ) , accumulation of defense hormone salicylic acid ( SA ) , and high expression of resistance marker genes termed Pathogenesis-Related ( PR ) genes [3] . Among the components that are required for R protein triggered immune responses , RAR1 , HSP90 and SGT1 are three conserved proteins that function in correct folding and stabilization of NLR R proteins [4] . Loss of RAR1 function leads to compromised resistance mediated by multiple R proteins [5] , [6] , [7] , [8] , [9] . Accumulation of barley MLA proteins , potato Rx , and Arabidopsis RPM1 and RPS5 was reduced when RAR1 function was compromised [7] , [10] , [11] . Compromising the activity of HSP90 also caused reduced accumulation of several R proteins including RPM1 , RPS5 and Rx [11] , [12] , [13] . The functions of SGT1 appear to be more complex . Silencing of SGT1 in Nicotiana benthamiana resulted in reduced accumulation of Rx , suggesting that similar to RAR1 and HSP90 , SGT1 is required for maintaining the protein level of Rx [14] . On the other hand , reduced accumulation of RPS5 , but not RPM1 or RPS2 , in the rar1 mutant background can be suppressed by the sgt1b loss-of-function mutation . It was suggested that SGT1b antagonize RAR1 in regulating the accumulation of certain R proteins [11] . SGT1 contains three domains including the TPR ( tetratricopeptide repeat ) domain , the CS ( present in CHP and SGT1 proteins ) domain and the SGS ( SGT1 specific ) domain [4] . RAR1 contains two conserved cysteine and histidine rich domains named CHORD-I and CHORD-II [5] . Both SGT1 and RAR1 function as cochaperones of HSP90 [15] , [16] , [17] . The CS domain of SGT1 and CHORD-I domain of RAR1 bind to HSP90 . The CHORDII domain of RAR1 binds to SGT1 . In Arabidopsis genome , there are two copies of SGT1 genes , SGT1a and SGT1b . Loss of the function of both genes lead to lethality [14] . Both plant and animal NLR proteins are substrates of the HSP90-RAR1-SGT1 chaperone complex [4] . Binding of SGT1 to these substrates is probably through the SGS domain in SGT1 and LRRs in NLRs [10] . Arabidopsis SNC1 encodes a TIR-NB-LRR type of R protein [18] . In the snc1 mutant , a gain-of-function mutation located in the region between NB and LRR constitutively activates downstream defense responses . snc1 mutant plants exhibit dwarf morphology , accumulate high levels of salicylic acid ( SA ) , and constitutively express pathogenesis-related ( PR ) genes and resistance to pathogens [19] . Overexpression of SNC1 also results in constitutive activation of defense responses [20] . A recent report showed that the expression of SNC1 is regulated at chromatin level by MOS1 , which encodes a large protein with a conserved BAT2 domain [21] . Because autoimmunity is detrimental to plant growth and development , R protein mediated immunity is subjected to tight control . Since overexpression of R genes often leads to constitutive activation of defense responses [20] , [22] , transcription of R genes need to be controlled properly to keep R protein levels below a threshold to avoid constitutive activation of R protein-mediated immune responses . At protein level , without the presence of the microbial pathogens , R proteins are kept in an auto-inhibited conformation through intramolecular interactions [23] . Here we report that an SGT1-interacting protein negatively regulates R protein accumulation to prevent auto-activation of immune responses .
In Arabidopsis , NPR1 ( Nonexpresser of PR genes 1 ) is an essential signaling component downstream of SA [24] . To search for negative regulators of defense responses independent of NPR1 , an npr1-1 suppressor screen was previously conducted [25] . A mutant named snc5-1 npr1-1 was found to constitutively express the BGL2 ( PR2 ) Promoter-GUS reporter gene in the npr1-1 mutant background ( Figure S1 ) . snc5-1 npr1-1 exhibited a dwarf morphology ( Figure 1A ) similar to snc1 , an auto-activated TIR-NB-LRR R gene mutant identified in an independent npr1-1 suppressor screen [19] . Plants heterozygous for snc5-1 npr1-1 displayed wild type morphology , indicating that the snc5-1 mutation is recessive . In snc5-1 npr1-1 mutant plants , both PR1 and PR2 were constitutively expressed ( Figure 1B and 1C ) . To test whether snc5-1 npr1-1 over-accumulates SA , SA levels in snc5-1 npr1-1 and wild type plants were measured with high-performance liquid chromatography ( HPLC ) . As shown in Figure 1D , both free and total SA ( free SA plus glucose-conjugated SA ) levels in snc5-1 npr1-1 plants were much higher than in wild type controls . Since the defense marker PR genes were activated in snc5-1 npr1-1 , we tested whether snc5-1 npr1-1 has enhanced pathogen resistance . snc5-1 npr1-1 seedlings were challenged with Hyaloperonospora arabidopsidis Noco2 ( H . a . Noco2 ) , an oomycete downy mildew pathogen virulent on Arabidopsis Col-0 ecotype . As shown in Figure 1E , sporulation of H . a . Noco2 on snc5-1 npr1-1 plants was much less than on wild type plants , indicating that defense responses are constitutively activated in snc5-1 npr1-1 . To map the snc5-1 mutation , snc5-1 npr1-1 ( in the Col-0 ecotype ) was crossed with the wild type Ler ecotype to generate a segregating F2 population . In the F2 progeny , plants homozygous at the snc5-1 locus were identified based on the dwarf morphology of snc5-1 . Interestingly , the percentage of plants with dwarf morphology in the F2 population was less than one quarter , suggesting that there may be a natural modifier of snc5-1 in Ler . Crude mapping using 24 dwarf plants suggested that two loci are required for the mutant phenotype: one is closely linked to the lower arm of chromosome 4 ( marker F19F18 at 17 . 7 MB ) and the other is linked to the middle of chromosome 4 ( marker FCA5 , at 9 MB ) . For fine mapping of the locus on the lower arm of chromosome 4 , we first identified F2 plants homozygous for the Col-0 sequence at marker FCA5 and heterozygous at marker F19F18 . About 500 F3 plants from these F2 lines were genotyped with the markers T16L1 and F19F18 . The snc5-1 mutation was further mapped to a 92 kb region between markers F6G17 and F19F18 after analyzing the recombinants between T16L1 and F19F18 . Sequence analysis of the genes in this region identified a single G to A mutation in At4G37460 , which introduces an early stop codon in the middle of the protein ( Figure 2A ) . At4G37460 was predicted to encode a TPR domain-containing protein . Analysis of At4G37460 expression using the microarray database at The Arabidopsis Information Resource found that it is expressed in all tissues . To confirm the mutation in At4G37460 causes the activation of defense responses , we analyzed two additional T-DNA knockout alleles of At4G37460 , snc5-2 ( SAIL_412_E08 ) and snc5-3 ( SAIL_216_F11 ) , both carrying T-DNA insertions in exons of At4g37460 ( Figure 2A ) . These two mutants showed similar dwarf morphology as snc5-1 npr1-1 ( Figure 2B ) . RT-PCR analysis showed that full length At4G37460 was no longer expressed in the two T-DNA mutants ( Figure S2 ) . Both mutants accumulated high levels of SA ( Figure 2C ) . Consistent with previous reports that NPR1 functions in negative feedback regulation of SA accumulation [19] , [26] , the snc5-1 npr1-1 double mutant accumulated higher levels of SA than the snc5-2 and snc5-3 single mutants . Like snc5-1 npr1-1 , snc5-2 and snc5-3 also constitutively expressed PR1 ( Figure 2D ) and PR2 ( Figure 2E ) and exhibited enhanced resistance to H . a . Noco2 ( Figure 2F ) , suggesting that the mutations in At4G37460 cause the activation of defense responses . It also indicates that the locus in the middle of chromosome 4 is probably a natural modifier of snc5-1 . Recently it was reported that mutants of At4g37460 named srfr1 ( suppressors of rps4-RLD ) in the RLD ecotype background exhibited enhanced resistance against Pseudomonas syringae pv . tomato DC3000 expressing avrRps4 [27] . Unlike the snc5 mutants in Col background , defense responses are not constitutively activated in the srfr1 mutants identified in RLD ecotype and these mutants remain fully susceptible to the virulent P . s . t . DC3000 strain without avrRps4 [28] . To be consistent with the literature , we renamed snc5-1 , snc5-2 and snc5-3 in the Columbia background as srfr1-3 , srfr1-4 and srfr1-5 , respectively . The protein encoded by At4g37460 is referred to as SRFR1 . Sequence analysis revealed that SRFR1 is conserved in plants and vertebrates ( Figure S3 ) , but not present in yeast and invertebrates such as C . elegans and D . melanogaster . The biochemical function of the protein is unknown . To further map the modifying locus affecting srfr1-3 npr1-1 mutant morphology , we identified F2 plants that are homozygous for Col-0 at marker F19F18 ( close to SRFR1 ) and heterozygous at marker FCA5 ( close to the modifier ) . About 500 F3 plants from these lines were genotyped using the markers FCA5 and F1N20 . The modifier was further mapped to the region between marker FCA6 and FCA8 after analyzing the recombinants between FCA5 and F1N20 . This region contains the RPP4 R-gene cluster ( Parker et al . 1997 ) , which SNC1 is a member of . To identify the modifier required for the mutant phenotypes of srfr1-3 npr1-1 , we mutagenized srfr1-3 npr1-1 with EMS and looked for suppressors of srfr1-3 npr1-1 . Because the SNC1 locus is highly polymorphic in different ecotypes [29] , we hypothesized that it may be the natural modifier . When we sequenced the SNC1 locus in four of the suppressor mutants , we found that two of them contained mutations in SNC1 ( Figure S4 ) . To confirm that SNC1 is indeed the modifier of srfr1-3 npr1-1 , we crossed snc1-r1 , a known null mutant allele of SNC1 containing a deletion of 8 bp in the first exon [18] , into srfr1-3 npr1-1 . We found that the snc1-r1 srfr1-3 npr1-1 mutant plants displayed wild type morphology ( Figure 3A ) , a stronger suppression compared to mutant alleles with point mutations identified from the srfr1-3 suppressor screen . Further analysis of the triple mutant showed that the elevated SA levels ( Figure 3B ) , constitutive expression of PR genes ( Figure 3C–3D ) and resistance to H . a . Noco2 ( Figure 3E ) in srfr1-3 npr1-1 were also blocked by the snc1-r1 mutation , suggesting that srfr1-3 activates SNC1-mediated resistance pathways . To test whether activation of defense responses in srfr1-3 npr1-1 was caused by overexpression of SNC1 at transcription level , the expression level of SNC1 was determined by real-time RT-PCR . As shown in Figure 3F , SNC1 expression in srfr1-3 npr1-1 is only slightly higher than that in wild type and npr1-1 plants . The small increase in SNC1 transcript level probably is not the cause of the dramatic phenotypes observed in srfr1-3 npr1-1 . Interestingly , the snc1-r1 srfr1-3 npr1-1 triple mutant is less susceptible to H . a . Noco2 than the snc1-r1 npr1-1 double mutant ( Figure 3E ) , suggesting that srfr1-3 may also affect SNC1-independent resistance responses . To test whether srfr1-3 affects resistance specified by additional R genes , we analyzed resistance mediated by RPP4 , RPS2 and RPS4 in snc1-r1 srfr1-3 npr1-1 . As shown in Figure S5A , the snc1-r1 srfr1-3 npr1-1 triple mutant displayed enhanced resistance to H . a . Emwa1 comparing to the snc1-r1 npr1-1 double mutant , suggesting that the srfr1-3 mutation enhances RPP4-mediated resistance . In addition , snc1-r1 srfr1-3 npr1-1 exhibited enhanced resistance to P . s . t . DC3000 carrying avrRpt2 or avrRps4 comparing to npr1-1 ( Figure S5B and S5C ) , indicating that resistance mediated by RPS2 and RPS4 is also enhanced by the srfr1-3 mutation . SRFR1 contains a TPR domain at its N-terminal half and a conserved C-terminal domain with unknown function . Since TPR domains are often involved in protein-protein interactions , SRFR1 probably functions through association with other proteins . To identify interacting partners with SRFR1 , we performed a yeast two-hybrid screen using the full-length SRFR1 as bait . Seven positive cDNA clones were identified on synthetic dropout plates lacking Histidine ( data not shown ) . Sequence analysis showed that one clone contained SGT1a ( encoding amino acid 1-351 ) and another contained SGT1b ( encoding amino acid 6-358 ) cDNA . To confirm the interactions between SRFR1 and SGT1a/b , the cDNA clones were recovered from yeast and used for additional assays . As shown in Figure 4A , both SGT1a and SGT1b interact with SRFR1 but not the empty vectors in the yeast two-hybrid assays . β-Gal assays were also performed to confirm the interactions ( data not shown ) . To determine which parts of SRFR1 and SGT1a/1b interact with each other , we created a series of deletion constructs of SRFR1 and SGT1a/1b ( Figure 4B ) . As shown in Figure 4C and 4D , the N-terminal TPR domain but not the C-terminal half of SRFR1 interacted with SGT1a and SGT1b , suggesting that SRFR1 interacts with SGT1 through its TPR domain . When the TPR domain of SRFR1 was expressed together with the truncated SGT1a/1b proteins , it was found to interact with the TPR domains of SGT1a and SGT1b ( Figure 4E ) , but not with the CS plus SGS domains in the yeast two-hybrid assay ( Figure 4F ) . These interactions were further confirmed by β-Gal assays ( data not shown ) . We also tested whether the TPR domain of SRFR1 self-associates in the yeast two-hybrid assays . As shown in Figure S6 , the TPR domain of SRFR1 interacts with the TPR domain of SGT1b but not itself . To test whether SRFR1 and SGT1 associate with each other in planta , we conducted co-immunoprecipitation ( co-IP ) analysis . First , we generated a polyclonal antibody against SRFR1 , which has a predicted size of 118 kD . The anti-SRFR1 antiserum detected a protein around 120 kD present in wild type but not the srfr1-3 npr1-1 or srfr1-4 mutant plants ( Figure S7 ) , indicating that the antibody specifically detects SRFR1 . Next we performed IP experiments using an anti-SGT1 antibody that can detect both SGT1a and SGT1b . As a control , we also performed IP using an anti-MPK4 antibody . Both SRFR1 and MPK4 were localized to cytosol and nucleus ( Figure S8 ) . Proteins that were immunoprecipitated by the antibodies were subsequently detected by western blot analysis using the SGT1 , MPK4 or SRFR1 antibodies . As shown in Figure 5 , SRFR1 co-immunoprecipitates with SGT1 , but not with MPK4 , indicating that SRFR1 and SGT1 associate with each other in planta . Since SRFR1/SNC5 interacts with SGT1 and SGT1 has been shown to regulate R protein stability through its association with RAR1 and HSP90 , we tested whether the accumulation of SNC1 is affected in the srfr1 mutants . We generated a SNC1-specific antibody against a peptide unique in the SNC1 protein . SNC1 has a predicted size of 147 kD . The anti-SNC1 antibody detected a protein around 150 kD in the wild type , but not in the snc1-r1 deletion mutant ( Figure 6A ) , indicating that the antibody is specific against SNC1 . In the srfr1-3 npr1-1 , srfr1-4 and srfr1-5 mutant plants , SNC1 protein levels are much higher than that in the wild type plants , suggesting that loss of the function of SRFR1 results in over-accumulation of SNC1 . To test whether mutations in SGT1b and SGT1a affect the accumulation of SNC1 , we also analyzed the SNC1 protein levels in the sgt1b deletion allele edm1-1 [30] and sgt1a-3 , a T-DNA knockout allele of sgt1a . Real-time RT-PCR showed that the expression of SGT1a was dramatically decreased in sgt1a-3 ( Figure S9 ) . We observed increased accumulation of SNC1 protein in edm1-1 , but not in sgt1a-3 ( Figure 6B ) . Taken together , both SRFR1 and SGT1b contribute to the negative regulation of SNC1 stability . To test whether srfr1 mutations affect the accumulation of RPS2 and RPS4 proteins , we crossed RPS2-HA or RPS4-HA transgenic lines , expressed under their native promoters [31] , [32] , into snc1-r1 srfr1-3 and snc1-r1 srfr1-3 npr1-1 backgrounds . The snc1-r1 mutation was included in the analysis to avoid the effect of constitutive activation of defense responses on the accumulation of the R proteins . In the snc1-r1 srfr1-3 plants , the transcript level of RPS2 was similar to that in wild type plants whereas the transcript of RPS4 was about twice as much as that in wild type plants ( Figure 7A and 7B ) . As shown in Figure 7C and 7D , both RPS2-HA and RPS4-HA accumulated to higher levels in snc1-r1 srfr1-3 than in wild type plants . In the snc1-r1 srfr1-3 npr1-1 triple mutant , the transcript levels of RPS2 and RPS4 were similar to those in wild type plants ( Figure 7E and 7F ) . As shown in Figure 7G , RPS2-HA accumulated to a higher level in snc1-r1 srfr1-3 npr1-1 than in wild type . Accumulation of RPS4-HA was also increased in the triple mutant ( Figure 7H ) , but the increase was not as dramatic as that observed in the snc1-r1 srfr1-3 double mutant , suggesting that the increased RPS4-HA protein level in snc1-r1 srfr1-3 was partly due to increased transcription of RPS4 . These data suggest that SRFR1 contributes to the regulation of RPS2 and RPS4 protein levels .
In a suppressor screen of npr1-1 to search for negative regulators of immune responses , we identified snc5-1/srfr1-3 that constitutively expresses PR genes and pathogen resistance . Since loss-of-function mutations in SNC1 block activation of defense responses in srfr1-3 npr1-1 , the resistance activated by srfr1-3 is mediated by the R protein SNC1 . In addition , SNC1 protein over-accumulated in srfr1 mutants , suggesting that SRFR1 regulates the stability of SNC1 and over-accumulation of SNC1 caused the activation of immune responses . A previous study showed that srfr1 mutants in the RLD ecotype background do not activate constitutive defense responses [28] . The lack of constitutive defense responses in the srfr1 mutants is probably due to the absence of a functional SNC1 gene in the RLD background , whereas the enhanced resistance to DC3000 with avrRps4 may be caused by increased accumulation of an unidentified R protein that recognizes AvrRPS4 . From a yeast two-hybrid screen , we found that SRFR1 interacts with SGT1a and SGT1b . In planta interactions between SGT1 and SRFR1 were confirmed by co-IP experiments . Like in srfr1 mutants , elevated SNC1 protein level was also observed in edm1-1 , the deletion mutant allele of sgt1b . This is consistent with SRFR1 and SGT1 function together to regulate the stability of SNC1 . Interestingly , the over-accumulation of SNC1 in sgt1b mutant plants does not cause constitutive activation of defense responses , suggesting that SNC1 protein over-accumulated in sgt1b mutant may have reduced activity . Since SGT1 may have dual functions in negative regulation of R protein accumulation as well as positive regulation of R protein folding [11] , it is likely that the over-accumulated R proteins in sgt1b mutant are not folded correctly without the assistance of SGT1b , thus not able to trigger immune responses . SGT1 contains three domains , the N-terminal TPR domain , the central CS and C-terminal SGS domain . The CS domain interacts with both RAR1 and HSP90 while the SGS domain may form contacts with the LRRs of R proteins [10] , [16] . The function of the TPR domain is unclear . Interestingly , the TPR domain of SGT1 is missing in some non-plant species such as C . elegans [4] , suggesting that the TPR domain may have a specialized function . Our study showed that the TPR domain of SGT1 interacts with SRFR1 , suggesting that this domain may function in negative regulation of R protein accumulation , which is consistent with the association of SGT1 with components of the SCF ( SKP1 , Cullin , F-box protein ) ubiquitin ligase complex [33] , [34] and SGT1 is required for SCF-mediated auxin responses [34] . The TPR domain of SGT1b has previously been shown to be dispensable for the function of SGT1b in regulating R protein mediated resistance as well as auxin signaling when it was overexpressed [14] . It remains to be determined whether a truncated SGT1b without the TPR domain under its own promoter is able to complement the phenotypes of sgt1b as well as the embryo lethality phenotype in the sgt1a sgt1b double mutant . Analysis of SGT1 functions in Arabidopsis has been complicated by the presence of two closely related SGT1 proteins with overlapping functions [14] , [35] . STG1a is expressed at a lower level than SGT1b , but it has intrinsic activity to complement the sgt1b mutant when its expression is increased to a certain level . Thus the mutant phenotypes of sgt1b are probably results of partial loss of SGT1 functions . While SGT1b has been shown to be required for the function of a number of R proteins ( reviewed by Shirasu [4] ) , RPS5 function is not affected in sgt1b . The SGT1a activity may be sufficient for proper folding of RPS5 . An unexpected result is that a loss-of-function mutation in SGT1b suppresses the reduced accumulation of RPS5 and loss of RPS5 function in rar1 , implicating that SGT1b may also play a role in the negative regulation of R protein accumulation [11] . Our data support the model proposed by Azevedo et al . [14] that SGT1 has dual functions in regulating R protein-mediated immune responses . In addition to its function as a co-chaperone of HSP90 in positively regulating R protein folding , it may also be involved in the negative regulation of R protein stability by association with SRFR1 through its N-terminal TPR domain . In addition to SNC1 , SRFR1 may regulate the accumulation of other R proteins . In the srfr1-3 mutant plants , both RPS2-HA and RPS4-HA fusion proteins accumulate to higher levels than in wild type plants . Because knockout of SNC1 is sufficient to block the constitutive defense responses in the srfr1-3 mutant , the increased accumulation of other R proteins such as RPS2 and PRS4 probably has not reached the threshold levels that would cause activation of these R proteins . Since SRFR1 and SGT1 are both conserved in plants and animals and SGT1 is required for the functions of animal NLR proteins such as NOD1 , NOD2 and NLRP3 [36] , [37] , it will be interesting to test whether the homologs of SRFR1 in animals also function as negative regulators of NLR protein-mediated immune responses .
All plants were grown under 16 hour light at 23°C and 8 hour dark at 20°C . srfr1-3 npr1-1 was identified from an EMS-mutagenized mutant population in the npr1-1 mutant background as previously described [25] . snc5-2/srfr1-4 ( SAIL_412_E08 ) , snc5-3/srfr1-5 ( SAIL_216_F11 ) and sgt1a-3 ( SALK_122139C ) were obtained from the Arabidopsis Biological Resource Center ( ABRC ) . Homozygous plants for snc5-2/srfr1-4 were identified by PCR using primers 5′-tcatcactaattccgcaacg-3′ and 5′-cgacttatgtaacggatcag-3′ . Homozygous plants for snc5-3/srfr1-5 were identified by PCR using primers 5′-ctatggttctactgagctcg-3′ and 5′-tgctcatggtttagttagcc-3′ . The RPS2-HA and RPS4-HA transgenic lines were described previously [31] , [32] . snc1-r1 npr1-1 is a deletion mutant of snc1 described previously [18] . The snc1-r1 srfr1-3 npr1-1 triple mutant was generated by crossing snc1-r1 npr1-1 with srfr1-3 npr1-1 and genotyping the F2 population . srfr1-3 mutation were identified by PCR using primers 5′-caggggaagtaatcttatcggatatcac-3′ and 5′-caattttcctgtcttgaccagggttcg-3′ followed by digestion with TaqI . Plants homozygous for snc1-r1 were identified by PCR using primers 10C-WT-F ( 5′-cctggtgcctgaatgaattg-3′ ) and 10C-R ( 5′-atcatccgatggtgtcatag-3′ ) . Infection of H . a . Noco2 was carried out on two-week-old seedlings by spraying with spore suspensions at a concentration of 50 , 000 spores per ml of water . The plants were kept at 18°C in 12 h light/12 h dark cycles with 95% humidity . Infections were scored seven days post inoculation by counting the number of spores with a hemocytometer . RNA was extracted from the 12-day-old seedlings grown on MS plates using the RNAiso reagent ( Takara ) . Reverse transcription ( RT ) was performed using the M-MLV reverse transcriptase from Takara . For gene expression analysis , real-time PCR was carried out using the Perfect Real Time kit ( Takara ) . The sequences of primers used for amplification of PR-1 , PR-2 and Actin1 were described previously [38] . SA was extracted as previously described and measured using HPLC [39] . Markers used for mapping were designed based on the Monsanto Arabidopsis polymorphisms and Landsberg sequence collections [40] . The primer sequences for AP20 are 5′-gtcattttctaaaatccaatatgaccg-3′ and 5′-gacgacatattgcacattttcatattg-3′ . Primers for F6G17 are 5′-cacttccctggtgcgtccaa-3′ and 5′-ggacagaagatacaggtgag-3′ . The primer sequences for F19F18 are 5′-aatcaatgattctatatacacatg-3′ and 5′-gacgaagattgcttggtgag-3′ . The primer sequences for FCA5 are 5′-aatgcggtgttacccatggc-3′ and 5′-actcttccgataaacttcctc-3′ . The primer sequences for FCA8 are 5′-gtcttcctctgccatttcac-3′ and 5′-gttgcgaaaagcagagattg-3′ . All the markers are based on Indel polymorphisms . About 0 . 9 g of 12-day-old seedlings were ground in liquid nitrogen to fine powder and 0 . 9 ml of grinding buffer with 50 mM Tris-HCl ( pH 7 . 5 ) , 10 mM MgCl2 , 150 mM NaCl , 0 . 1% NP40 , 1 mM PMSF , and 1 x Protease Inhibitor Coctail ( Roche , 11873580001 ) was added to the powder . The sample was resuspended , transferred to 1 . 5 ml tubes and spun at 21 , 000 g for 10 min at 4°C . The supernatant was transferred to a tube containing 20 µl Protein A agarose beads ( GE Healthcare , 17-1279-03 ) for pre-cleaning . After rotating for 25 minutes , the sample was spun at 21 , 000 g for 5 min at 4°C . 40 µl of the supernatant was saved as input . Antibody was added to the rest of the supernatant and the sample was kept at 4°C with continuous rotation for 2–3 hours . 20 µl of Protein A agrose beads was subsequently added to the sample and kept at 4°C with continuous rotation for 1 hour . The beads were spun down at 4 , 000 rpm for 30 sec at 4°C . The beads were washed with 1 ml of grinding buffer for three times before immunoprecipitated proteins were eluted with 40 µl 2 x SDS loading buffer . SGT1b and the TPR domain of SRFR1 ( a . a . 1-567 ) were expressed in E . coli and used to generate the anti-SGT1b and anti-SRFR1 antibodies in rabbit . The Anti-SNC1 antibody was generated against an SNC1-specific peptide ( KAKSEDEKQS ) . The anti-MPK4 antibody was from Sigma ( A6979 ) . The anti-HA antibody was from Roche ( REF#11867423001 ) . Nuclei-depleted ( ΔN ) and nuclear ( N ) protein extracts of wild type plants were prepared as previously described [41] . To create the SRFR1 bait plasmid , SRFR1 cDNA was amplified by primers 5′-aaaactgcagggcccatgaggcctcaatcgttgtaagtgctaag-3′ and 5′-cgcggatccggccgtcaaggccaatggcgacggcgacggcgaca-3′ and cloned into pGBKT7 ( Clontech ) . The plasmid was sequenced and transformed into the yeast strain Y1348 . The Arabidopsis prey library in pGADT7 was kindly provided by Dr . Qi Xie . 40 µg of the library DNA were transformed to yeast strain containing the bait plasmid . The transformed yeast cells were plated on the SD-Leu-Trp-His containing 3 mM 3AT . DNA inserts from the positive clones were amplified by PCR using primers T7 and AD-seq-R ( 5′-agatggtgcacgatgcacag-3′ ) . The DNA fragments from PCR were digested with HinfI to group the positive clones into different classes . DNAs from representative clones were sequenced . The plasmids from selected positive clones were extracted and transformed into E . coli to amplify the DNA for further analysis . For yeast growth assays , overnight yeast cultures were diluted to different concentration and plated on SD-Leu-Trp and SD-Leu-Trp-His dropout plates . To make the bait plasmid containing the N-terminal half of SRFR1 ( a . a 1-567 ) , the cDNA fragment was amplified using 5′-cgcggatccggccgtcaaggccaatggcgacggcgacggcgaca-3′ and 5′-aaaactgcaggcccatgaggcctcatgcatcaagttccacgtcaa-3′ . To make the bait plasmid containing the C-terminal half of SRFR1 ( a . a . 568-1052 ) , the cDNA fragment was amplified using 5′-gcgggtacccatatggggccgtcaaggccagtggagaaatttgttcttc-3′ and 5′-aaaactgcagggcccatgaggcctcaatcgttgtaagtgctaag-3′ . The DNA fragments were cloned into the pGBKT7 . SGT1 fragments were amplified by PCR and cloned into the prey vector pGADT7 . SGT1a-TPR1-120 was amplified using 5′-ccggaattcatggcgaaggagcttgctga-3′ and 5′-gccgaattctcgagtcattctgtgattagaaaattgc-3′ . SGT1b1-120 was amplified using 5′-ccggaattcatggccaaggaattagcaga-3′ and 5′-gccgaattctcgagtcattcttctgcaatacgaagat-3′ . SGT1a121-351 was amplified using 5′-ccggaattcgaagagaaagatttggttca-3′ and 5′-cgcggatcctcagatctcccatttcttga-3′ . SGT1b121-358 was amplified using 5′-ccggaattcgagaaagatttggttcagcc-3′ and 5′-cgcggatcctcaatactcccacttcttga-3′ . The bait and prey vectors expressing the SRFR1 and SGT1 fragments were co-transformed into the Y1348 strain for yeast two-hybrid assays . | The nucleotide-binding domain and leucine-rich repeats-containing ( NLR ) proteins are structurally conserved immune receptors found in both animals and plants . Correct folding of NLR proteins requires two conserved proteins , SGT1 and HSP90 . We showed that another evolutionarily conserved protein , SRFR1 , interacts with SGT1 in both yeast two-hybrid assays and co-immunoprecipitation analysis . Loss-of-function mutations in SRFR1 result in constitutive activation of immune responses . The constitutive activation of immune responses in the srfr1 mutants is dependent on the NLR Resistance ( R ) protein SNC1 . In srfr1 mutant plants , levels of multiple R proteins including SNC1 , RPS2 and RPS4 are elevated . Consistent with previous findings that SGT1b is involved in the negative regulation of protein levels of certain NLR R proteins , increased accumulation of SNC1 is also observed in the sgt1b mutant . Our data suggest that SRFR1 functions together with SGT1 to negatively regulate NLR R protein accumulation to prevent autoimmunity in plants . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
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"and",
"Methods"
] | [
"plant",
"biology/plant-biotic",
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] | 2010 | SRFR1 Negatively Regulates Plant NB-LRR Resistance Protein Accumulation to Prevent Autoimmunity |
African green monkeys ( AGM ) and other natural hosts for simian immunodeficiency virus ( SIV ) do not develop an AIDS-like disease following SIV infection . To evaluate differences in the role of SIV-specific adaptive immune responses between natural and nonnatural hosts , we used SIVagmVer90 to infect vervet AGM and pigtailed macaques ( PTM ) . This infection results in robust viral replication in both vervet AGM and pigtailed macaques ( PTM ) but only induces AIDS in the latter species . We delayed the development of adaptive immune responses through combined administration of anti-CD8 and anti-CD20 lymphocyte-depleting antibodies during primary infection of PTM ( n = 4 ) and AGM ( n = 4 ) , and compared these animals to historical controls infected with the same virus . Lymphocyte depletion resulted in a 1-log increase in primary viremia and a 4-log increase in post-acute viremia in PTM . Three of the four PTM had to be euthanized within 6 weeks of inoculation due to massive CMV reactivation and disease . In contrast , all four lymphocyte-depleted AGM remained healthy . The lymphocyte-depleted AGM showed only a trend toward a prolongation in peak viremia but the groups were indistinguishable during chronic infection . These data show that adaptive immune responses are critical for controlling disease progression in pathogenic SIV infection in PTM . However , the maintenance of a disease-free course of SIV infection in AGM likely depends on a number of mechanisms including non-adaptive immune mechanisms .
Although it is not known when SIV was first introduced into African nonhuman primates , it is widely believed that African monkey and ape species coevolved with SIV infection probably for tens of thousands of years [1] , [2] . In contrast , Asian nonhuman primates and humans encountered the virus much more recently [2] , [3] . Despite these differences , SIV infections in nonhuman primates and HIV in humans follow a similar pattern of viremia: an initial burst of viremia during primary infection followed by a partial containment and establishment of a plateau or set point viremia [4] , [5] , [6] . Additionally , the level of viremia in African monkeys , natural hosts of SIV , and Asian monkeys , nonnatural hosts of SIV infection is similar [7] , [8] , [9] , [10] . Given the similarities in viral load , however , the course of infection and its consequences differ between natural and nonnatural hosts [11] , [12] , [13] . Most natural hosts such as AGM appear to peacefully coexist with the SIV infection while macaques generally develop overt signs of illness , immune failure and AIDS [14] . However , recent findings indicate that some natural hosts like chimpanzees may develop an AIDS-like disease when infected with SIV [15] . These differences in pathogenic consequences of infection prompt speculation about the mechanisms that enable African primate species to cope with SIV infection without developing disease . AGM provide a dramatic contrast to the apparently irrevocable pathway to immune failure seen in SIV-infected macaques and HIV-infected humans . At least two fundamental characteristics of SIV infection of natural host species that appear to distinguish them from pathogenic infections include the lack of chronic immune activation and the paucity of CCR5+ CD4+ target cells [11] , [16] , [17] . These differences suggest that natural hosts may have developed a complex arsenal of protective mechanisms to cope with the pathogenic consequences of SIV-infection . Adaptive immune responses , such as SIV-specific CD8+ T cells and humoral immune responses , have also been observed in SIV-infected natural hosts either at comparable or lower magnitude than in pathogenic SIV and HIV infection [18] , [19] , [20] , [21] , [22] , [23] , [24] . However , the ultimate role of adaptive immune responses in the protection against disease progression in AGM and other natural hosts of SIV remain elusive . An ideal setting to study the role of adaptive immune responses is to utilize the same virus strain of SIV in two different host species that would respond with similar dynamics of viremia but disparate disease outcome . Previously , it was shown that SIVagmVer90 can induce AIDS in pigtailed macaques ( Macaca nemestrina ) but not in vervet AGM ( Chlorocebus pygerythrus ) [25] . In fact , SIVagmVer90 infection induces an AIDS-like disease in PTM , similar to that observed in SIVmac251-infection in rhesus monkeys . Critically for the present study , set point viremia in SIVagmVer90-infection of PTM and AGM is similar . This observation confirms a characteristic finding in natural hosts: disparate pathogenic outcomes despite a similar magnitude of viremia as seen in nonnatural hosts . In fact , in natural hosts the magnitude of viremia varies widely , without any clinical consequences [7] . In contrast , the extent of viremia is an excellent predictor of disease progression in pathogenic models such as macaques and humans [26] , [27] , [28] . Here , we utilized the administration of antibodies to deplete both CD8+ lymphocytes and B cells during primary SIVagmVer90 infection in AGM and PTM to delay cellular and humoral SIV-specific immune responses . These studies underlined the critical role of adaptive immune responses in viral control in nonnatural hosts like PTM . In contrast , the absence of clinical signs of disease in AGM suggested that the maintenance of a disease-free course of infection in natural hosts does not solely depend on adaptive immune responses .
To better understand the role of adaptive immune responses during the early stages of SIV infection in pathogenic and non-pathogenic models of SIV infection , we initiated the depletion of CD8+ and CD20+ lymphocytes prior to infection with SIV . Six vervet AGM and six PTM received five doses of humanized anti-CD8α cM-T807 monoclonal antibody ( mAb ) on days 0 , 3 , 7 , 10 and 14 and three doses of anti-CD20 human mAb on days −7 , 14 and 35 . Four lymphocyte-depleted animals of each species were also inoculated intravenously with SIVagmVer90 [25] on day 0 , and two AGM and PTM served as uninfected controls . The treatment with lymphocyte depleting mAb resulted in a transient depletion of both CD8+ T cells and CD20+ B cells from peripheral blood in the AGM ( Fig . 1A and C ) . A comparable period of lymphocyte depletion , 6 and 14 weeks for CD8+ T cells and B cells , respectively , was also observed in the uninfected control AGM ( A9 and A23 ) . The SIV-infected AGM had a median CD8+ T cell depletion of 3 . 5 weeks ( range: 2–6 weeks ) and a median B cell depletion of 12 weeks ( range: 4–18 weeks ) . AGM A7 showed the earliest resurgence of both CD8+ T and B cells ( 3 and 4 weeks , respectively ) . Vervet AGM harbor two distinct subsets of CD8+ T cells: CD8αα homodimer and CD8αβ heterodimer expressing cells [18] . Despite a lower expression of the CD8 molecule on CD8αα T cells , administration of the cM-T807 mAb affected both CD8+ T cell subsets ( data not shown ) . The cells that first reappeared after CD8+ T cell depletion were mainly CD8αα+ T cells . Since depletion of peripheral blood lymphocyte subsets does not reflect depletion in tissues , we performed flow cytometric analyses for CD8+ and CD20+ lymphocyte subsets in bronchoalveolar lavage samples ( BAL ) and lymph node biopsies . A shorter duration of CD8+ T cell depletion was observed in BAL and lymph nodes of SIV-infected AGM where CD8+ T cells rebounded at week three ( Fig . 1B and data not shown ) . This was associated with a transient increase in double negative ( CD4− CD8− ) T cells in BAL consistent with down-modulation or masking of the CD8 molecule on T cells ( data not shown ) . The SIV negative control animals were CD8+ lymphocyte-depleted in BAL and lymph nodes throughout week four post depletion . Four of the lymphocyte-depleted AGM had a long lasting depletion of B cells in peripheral blood for 13–16 weeks and two AGM ( A7 and A13 ) had a shorter depletion of 4 and 10 weeks post infection ( p . i . ) ( Fig . 1C ) . A similar transient depletion of B cells was also observed in lymph node sections at one and four weeks p . i . ( data not shown and Fig . 2A–C ) . Four of the six lymphocyte-depleted PTM showed an efficient and long lasting depletion of CD8+ T cells and B cells ( P31 , P23 , P27 , P35 ) ( Fig . 1D , E and F ) . Depletion of both CD8+ T cells and B cells was irreversible in three of the SIV-inoculated PTM ( P23 , P27 , and P35 ) . Each of these PTM rapidly developed disease and had to be euthanized by 6–7 weeks . Transient depletion was observed in one of the SIV-infected PTM , P24 , and one uninfected animal , P33 . Both PTM had a depletion of CD8+ T cells for two weeks and a partial depletion of CD20 cells with a reappearance of B cells at week 8 post depletion ( Fig . 1D and F ) . The uninfected PTM P31 had a long lasting B cell depletion of 20 weeks and a CD8+ T cell depletion of 5 weeks . Analysis of CD20 expression in peripheral lymph node sections correlated with the flow cytometric analysis of peripheral blood . Depletion of B cells in the long-term depleted PTM was very efficient in lymph node sections ( Fig . 2D–F ) . This contrasted with incomplete depletion in lymph node biopsies collected at one and four weeks post depletion from P24 ( Fig . 2G–I ) , the one SIV-infected PTM with incomplete peripheral depletion . CD8+ and CD20+ lymphocyte depletion had only a brief effect on the plasma RNA viral load in AGM . The viral load followed a course comparable to that observed in SIV-infected historical control AGM that were inoculated with the same virus ( Fig . 3A ) . The peak SIV viral load was similar between CD8+ and CD20+ lymphocyte-depleted AGM and control AGM ( median: 0 . 79×107 SIV RNA copies/ml in the depleted AGM versus 1 . 47×107 SIV RNA copies/ml in the control AGM; P = 0 . 200 Fig . 3B ) . There was however a trend towards a prolongation of peak viremia in the CD8+ and CD20+ lymphocyte depleted AGM . The median viral load was higher at three weeks p . i . in the antibody-treated AGM than in the historic controls ( lymphocyte-depleted: 7 . 22×105 SIV RNA copies/ml versus control: 0 . 35×105 SIV RNA copies/ml; P = 0 . 057 ) . This trend was not maintained and differences in viremia between the two groups of AGM vanished at week six p . i . ( median: 1 . 14×105 SIV RNA copies/ml versus 0 . 645×105 SIV RNA copies/ml; P = 0 . 688 ) . To confirm the plasma viral load results , we assessed SIV expressing cells by in situ hybridization of peripheral lymph nodes sampled from AGM at one and four weeks p . i . ( Fig . 3C and 4 ) . As shown in Fig . 3C , the number of SIV positive cells in lymph node biopsies from control or antibody-treated AGM at one or four weeks p . i . did not differ significantly ( P = 0 . 486 and P = 0 . 183 ) . As reported previously [29] , the kinetics of viremia in PTM and vervet AGM inoculated with SIVagmVer90 is similar . As expected , all control PTM experienced a peak of viremia at 7–10 days p . i . followed by a decline to setpoint viremia ( Fig . 3D ) . In contrast to the AGM , we detected a significantly higher SIV plasma viral RNA copy number in CD8+ and CD20+ lymphocyte-depleted PTM than in control SIV infected PTM ( median; lymphocyte-depleted: 8 . 79×108 versus control: 0 . 66×108 , P = 0 . 029; Fig . 3E ) . Plasma viral load remained significantly higher throughout the remainder of their disease course ( P = 0 . 029 at 3 and 6 weeks p . i . ) . The viral load in the inefficiently-depleted PTM ( P24 ) decreased to a level seen at the high end of the range of the historic control PTM . The higher viral load in the lymphocyte-depleted PTM was confirmed by analysis of SIV expression in lymph node sections . As shown in Fig . 3F and 4 , there was a trend to higher levels of SIV+ cells in PTM lymph nodes collected at one week p . i . ( P = 0 . 057 ) and a significantly higher number of SIV+ cells at four weeks p . i . ( P = 0 . 029 ) . All of the SIV-infected AGM remained healthy throughout the original observation period of 50 weeks p . i . and beyond despite efficient lymphocyte depletion in the mAb-treated group ( Fig . 5A ) . In striking contrast to the AGM , CD8+ and CD20+ lymphocyte depletion in PTM resulted in an accelerated disease progression compared with historical control PTM infected with the same inoculum ( Fig . 5B; log rank test; P = 0 . 007 ) . Three of the four PTMs with almost complete lymphocyte depletion developed respiratory distress that necessitated euthanasia by six weeks p . i . The fourth animal had only a transient CD8+ and CD20+ lymphocyte depletion and experienced similar clinical signs during the primary stages of infection but made a partial clinical recovery . This animal subsequently experienced episodes of vasculitis associated with infarction of the skin , weight loss , poor appetite and diarrhea that eventually led to euthanasia at 18 weeks p . i . Pathologic evaluation of the three PTM euthanized early in the infection were remarkably similar , and included severe lymphoid depletion , severe vasculitis with pulmonary edema and cytomegalic cells in the lung , pulmonary edema , and nuclear inclusions consistent with disseminated cytomegalovirus ( CMV ) infection . SIV-specific in situ hybridization showed high levels of SIV-expression in all lymphoid tissues and in the brain or meninges consistent with uncontrolled SIV replication ( data not shown ) . To confirm the pathologic findings and to examine the effect of CD8+ and CD20+ lymphocyte depletion on CMV reactivation , we assayed CMV DNA in the plasma of both the AGM and PTM by quantitative PCR . As shown in Fig . 6B and D , SIV infection alone did not result in significant activation of CMV either in AGM or PTM . However , CMV activation was observed in the majority of the animals that were CD8+ and CD20+ lymphocyte-depleted as indicated by detectable CMV DNA in plasma ( Fig . 6A and C ) regardless of whether they were also infected with SIV . Reactivation of CMV was transient in the SIV infected and CD8+ and CD20+ lymphocyte-depleted AGM . In contrast , massive reactivation of CMV ( up to 106 copies/ml of plasma ) was observed in three of the CD8+ and CD20+ lymphocyte depleted and SIV-inoculated PTM . The PTM with the shortest duration of CD8+ T cell and B cell depletion transiently controlled CMV replication by week 12 but CMV DNA in plasma was detectable again prior to death . Reactivation of CMV in lymphocyte-depleted monkeys shows that control of CMV is dependent on functional CD8+ and CD20+ lymphocytes , as observed in AGM . PTM however appeared to be too compromised either by high level SIV viremia and/or lack of CD8+ and CD20+ lymphocytes to mount an effective immune response against CMV . The majority of CD4+ T cells in vervet AGM coexpress the CD8αα homodimer [18] . Administration of the anti-CD8α mAb therefore had a potential depleting effect on CD4+ T cells . Absolute CD4+ T cell counts in the blood declined with a median of −46% ( range: −59% to +6% ) following administration of the anti-CD8α mAb , regardless of inoculation with SIV ( Fig . 7A ) . Interestingly , CD4+ T cell levels did not return to pre-treatment values , but remained relatively stable in the AGM with exception of A346 . This animal experienced an abrupt decline in peripheral blood CD4+ T cell numbers after week 14 that coincided with a slight increase in plasma viremia . Viremia subsequently decreased and the animal remained free from clinical signs of disease throughout one year of follow up , despite a very low frequency of CD4+ T cells ( <5 cells/µl ) . In contrast to the vervet AGM , CD4+ T cells in PTM do not express the CD8αα homodimer . Therefore , administration of the anti-CD8α antibody did not affect CD4+ T cell counts in the non-infected mAb treated PTM ( Fig . 7C ) . The relatively stable number of peripheral blood CD4+ T cells in AGM was not observed for the lymphocyte-depleted PTM where SIV infection resulted in an abrupt decline in peripheral blood CD4+ T cells in the first 2 weeks of infection ( Fig . 7C ) . CD4+ T cell levels continued to decline in three of the animals ( P24 , P27 , and P35 ) . PTM P23 showed a less dramatic loss of CD4+ T cells than the other three lymphocyte-depleted PTM ( Fig . 7C ) . Similar kinetics and extent of CD4+ T cell decline were observed in untreated control PTM infected with SIV ( Fig . 7D ) . CD4+ T cell decline was less severe in the two PTM with lower viremia ( P9665 , P9663 ) . These two animals also showed the longest survival ( >105 weeks ) [13] . The decline of CD4+ T cells in pathogenic models of AIDS infected with a CCR5-tropic virus is mainly due to a loss of memory CD4+ T cells [6] , [30] . To assess the extent of memory CD4+ T cell depletion , we evaluated the ratio of naïve to memory CD4+ T cells in PTM and AGM . We observed an initial loss of memory CD4+ T cells at peak viremia , as indicated by a higher ratio of naïve to memory CD4+ T cells than before infection ( Fig . 8A , B ) in all but one SIV-infected AGM . The non-infected lymphocyte-depleted AGM experienced a similar increase in the ratio of naïve to memory CD4+ T cells as SIV-infected AGM ( Fig . 8A ) . In AGM , memory CD4+ T cells express higher levels of CD8α than naive CD4+ T cells ( data not shown ) and therefore may be preferentially depleted by the anti-CD8 mAb . After the transient loss of memory CD4+ T cells , the naïve to memory CD4+ T cell ratio recovered to levels comparable to pre-infection ratios , with the exception of A7 . A7 recovered from the initial loss of memory CD4+ T cells to a higher , but nevertheless stable ratio of naïve to memory CD4+ T cells . As described above , one of the AGM ( A346 ) suffered an almost complete loss all of its peripheral blood CD4+ T cells ( Fig . 7A ) . The loss of CD4+ T cells also included a precipitous decline of naive CD4+ T cells as indicated by the decline in the naive to memory CD4+ T cell ratio indicated ( Fig . 8A ) . In contrast to the effects on the CD4+ T cell subset in vervet AGM , a much more obvious but also transient increase in the naive to memory CD4+ T cell ratio was observed in three of four CD8+ and CD20+ lymphocyte-depleted , SIV-infected PTM ( Fig . 8C ) . The short term depleted PTM , P24 , only showed a minor increase in the naïve to memory CD4+ T cell ratio with a subsequent slow decline to low levels just prior to death . In contrast , a much more muted decline in memory CD4+ T cells was observed in SIV-infected control PTM ( Fig . 8D ) . A more severe pathogenic SIV infection is generally associated with an increased turnover of CD4+ T cells . The increased proliferation of CD4+ T cells can be directly assessed by an increase in Ki-67 expression on memory CD4+ T cells . We therefore evaluated the proliferation of memory CD4+ T cells in both AGM and PTM ( Fig . 9 ) . As expected , a vigorous proliferation of memory CD4+ T cells was seen in both the lymphocyte-depleted and the historical control SIV-infected PTM ( Fig . 9C and D ) . In contrast to the pathogenic SIV infection , we only observed a marginal increase in proliferation of memory CD4+ T cells in both of the two SIV-infected groups of AGM ( Fig . 9A and B ) . The brief increase of memory CD4+ T cell proliferation in both SIV negative AGM and PTM was likely the result of compensatory homeostatic mechanisms in response to the depletion of CD8+ T cells ( Fig 9A and B ) . Even low numbers of remaining B cells in lymphoid tissue after CD20+ lymphocyte depletion may support the generation of SIV-specific antibodies . We therefore evaluated the efficacy of the inhibition of humoral immune responses by determining the generation of SIV-specific antibody responses by Western blot and neutralization assays . Western blot assays of AGM plasma against whole SIVagmVer90 virus lysate revealed a delay in the development of SIV-specific antibodies in three of the four lymphocyte-depleted AGM compared to historical non-depleted control AGM inoculated with the same virus ( Fig . 10A and C ) . All control AGM developed SIV-specific antibodies by four to six weeks p . i . Similarly the inefficiently CD20+ lymphocyte-depleted AGM ( A7 ) developed SIV-specific antibodies by six weeks p . i . The three long-term B cell-depleted AGM only seroconverted after week six , and two animals showed only a weak response to SIV antigen even at 24 weeks post infection . A more dramatic effect on seroconversion was observed in PTM that were depleted of CD8+ T cells and CD20+ cells ( Fig . 10B ) . Only the PTM ( P24 ) transiently depleted of CD8+ T cells and B cells developed SIV-specific antibody responses at four weeks p . i . The three other B cell-depleted PTM did not develop any SIV specific antibodies . All of the historic control PTM developed variable levels of SIV-specific antibody responses by four to six weeks p . i . ( Fig . 10D ) . We attempted to confirm these data using SIVagmVer90 envelope-pseudotyped HIV particles in a single round neutralizing antibody ( Ab ) assay [31] . However , SIVagmVer90 appeared to be highly resistant to neutralization and therefore we were unable to detect neutralizing Ab in any of the AGM in this study . However , using a tissue culture lab-adapted SIVmac251 strain , we observed a delay in the generation of neutralizing Ab in AGM that had been well-depleted of B cells compared to the historic non-depleted SIV infected control AGM ( Fig . 11A ) . The appearance of neutralizing Ab had no consistent effect on the magnitude of plasma viremia in either of these AGM ( Fig . 11B and C ) .
Soon after the discovery of AIDS viruses it became apparent that natural hosts of SIV do not generally develop immunodeficiency in association with SIV infection , whereas these viruses readily induce disease in Asian nonhuman primates and humans [8] , [12] , [32] , [33] , [34] . However , the mechanisms employed by these primates to avoid the pathogenic consequences of SIV-infection remain unclear . In the present study , we made a direct comparison of the role of SIV-specific adaptive immune responses in a nonnatural host and natural host of SIV infection , PTM and vervet AGM , respectively . To do this , we evaluated the effect of antibody-mediated temporal inhibition of cellular and humoral immune responses during primary infection with the uncloned SIV virus , SIVagmVer90 , in PTM and AGM . Recent investigations have shown that this virus does not induce an AIDS-like disease in AGM but is not inherently nonpathogenic as infection studies in PTM have shown [25] . Here in this study , temporal inhibition of adaptive immune responses in primary SIV infection of PTM resulted in an increased peak and set point viremia and accelerated disease progression similar to observations recently made in CD8+ lymphocyte-depleted rhesus macaques infected with pathogenic SIV [35] , [36] , [37] . Interestingly , in the present study and in unpublished observations evaluating sabaeus AGM ( R . C . Zahn et al . ) , peak viremia was not increased in lymphocyte-depleted AGM but only a relatively brief prolongation of peak viremia was observed during primary infection . The delay in resolution of primary viremia was very likely due to the inhibition of cellular immune responses since primary viremia had resolved before the appearance of humoral immune responses . Also , the eventual generation of humoral immune responses in B cell-depleted animals following reappearance of these cells did not appear to have a significant influence on the magnitude of viremia . This observation was recently confirmed by others when B cell depletion during primary and chronic SIV infection of AGM did not result in an increased viremia or clinical signs of illness ( personal communications with Ivona Pandrea ) . Thus , the data presented here and unpublished observations using sabaeus AGM ( R . C . Zahn et al . ) suggest that cellular immune responses contribute to viral containment in AGM but humoral immune responses appear to be less critical . However , in contrast to rhesus monkeys the absence of CD8+ lymphocytes in AGM resulted in a much more subdued impact on viremia , similar to observations recently made in sooty mangabeys [38] . Although no overt signs of SIV disease were seen in the lymphocyte-depleted AGM , the depletion of these cells was associated with reactivation of CMV . A similar transient reactivation of CMV without clinical signs was observed in one of the two PTM that were lymphocyte-depleted but not challenged with SIV . The most significant signs of pathogenicity were seen in PTM that were depleted of CD8+ and CD20+ lymphocytes and inoculated with SIV: in these animals , we observed a massive increase in plasma CMV DNA copies , precipitous loss of CD4+ T cells and an increase in naive/memory CD4+ T cell ratio , indicating a rapid loss of memory CD4+ T cells . These observations raise a number of questions . Is it possible that the impairment of adaptive immune responses in AGM was not of sufficient duration to negatively impact the health of these animals ? Or , is the inherent ability to suppress immune activation in SIV-infected AGM the critical factor that helps AGM to cope with chronic SIV infection ? CD8+ lymphocyte depletion in rhesus macaques results in a significantly enhanced disease progression . However , as recently shown [35] , [39] , [40] and observed here in the PTM depleted of CD8+ lymphocytes , the fastest disease acceleration is seen in nonnatural hosts when CD8+ lymphocytes are depleted for at least the first 4 weeks during primary SIV infection . However , the CD8+ lymphocyte depletion in most AGM in this study was of fairly short duration . But even the one relatively long-term CD8+ lymphocyte-depleted AGM ( A13; about 6 weeks ) did not develop an AIDS like-disease with rapid disease progression as we have seen in all rhesus macaques studied so far with a similar length of CD8+ lymphocyte-depletion [39] , [40] . In addition , PTM P24 in this study also was only depleted for 2 weeks , but succumbed to AIDS within 18 weeks p . i . A number of recent investigations have shown that natural hosts exhibit a much lower level of immune activation during chronic viremia compared to nonnatural hosts [16] , [32] . The low level immune activation may protect the natural host species from more aggressive virus replication and the development of an AIDS-like disease . Recent investigations have shown that short-term immune activation using LPS or an IL-2/diphtheria toxin fusion protein in AGM can result in an increased viremia , supporting the notion that hyperactivation of the immune system plays a role in virus replication and disease progression [41] . However , these brief in vivo manipulations had no apparent effect on the health of the animals . Thus , in vivo manipulations in AGM that are capable of suppressing adaptive immune responses for a longer duration than in the present study and/or induce a prolonged immune activation may result in a different outcome . In addition , there may be a number of possible caveats in our study . ( 1 ) . Since CD4+ T cells in vervet AGM dimly coexpress the CD8α molecule , administration of the anti-CD8α antibody may have also affected CD4+ T cell targets and thus limited virus replication . However , a similar result was recently observed in sabaeus AGM that did not coexpress the CD8α molecule on CD4+ T cells ( R . C . Zahn et al . , unpublished observations ) . We also cannot clearly rule out that NK cells that express the CD8α molecule may contribute to viral containment as these cells are also depleted by the anti-CD8α antibody . It is also possible that some of the differences observed in the control group and the antibody-treated group may be due to utilizing historical controls for this study . However , both the historical controls and antibody-treated group were treated identically except for receiving lymphocyte-depleting antibodies . Finally , it is conceivable that the combined depletion of CD8+ and CD20+ lymphocytes may affect AGM and PTM differently . However , to formally rule out that the antibody treatment may have a more significant pathogenic effect on PTM we have performed the lymphocyte depletion experiments as well in SIV-negative AGM and PTM which both did not exhibit any signs of disease following the antibody administrations . Recent investigations have shown that evolutionary adaptations in natural hosts ( paucity of CCR5+ cells , decreased immune activation , and ability to down modulate the CD4 molecule on CD4+ T cells ) may assist adaptive immune responses or may even render SIV-specific adaptive immune responses unnecessary [32] , [42] , [43] . In contrast , if the AIDS virus can bypass restriction factors in nonnatural hosts , adaptive immune responses appear to be the major defense against uncontrolled virus replication . However , the eventual failure of viral control is due to inevitable viral immune escape [44] , [45] . A sign of the incredible plasticity of the immune system of natural hosts to cope with SIV infection was seen in one of the lymphocyte-depleted AGM ( A346 ) . This animal eventually lost all of its peripheral blood CD4+ T cells ( both memory and naïve cells ) , suggesting that the virus in this animal might have changed coreceptor usage ( characterization of coreceptor usage is still ongoing ) . Even with an almost complete loss of peripheral blood CD4+ T cells the animal showed no signs of disease . Recently , a similarly abrupt decline in CD4+ T cells was observed in another natural host of SIV , sooty mangabeys , upon emergence of a CXCR4-tropic SIV variant without inducing disease [46] . This abrupt decline of CD4+ T cells in sooty mangabeys does not necessarily always depend on switching the tropism of the virus to CXCR4 [47] . AGM may be capable of utilizing a large fraction of CD4- T cells , which can be found in peripheral blood and tissues , as surrogate T helper cells [43] , [48] . Investigations into natural hosts of SIV , including AGM , will allow us to understand how these animals can coexist with SIV without developing disease . The observations made here and in sabaeus AGM ( R . C . Zahn et al . , unpublished observations ) suggest that CD8+ T cell responses participate to some degree in controlling viral replication in natural hosts . However , the effects were considerably more limited than observations made in macaques and it is not clear whether a more long-term increase in viremia would precipitate disease progression in AGM . Further investigations are required to assess the relative contribution of adaptive immune responses versus non-adaptive mechanisms in the maintenance of an AIDS-free course of infection in natural host species . Our aim is that these investigations will provide clues how pathogenic AIDS virus infections could be limited , identify new therapeutic approaches , and contribute to the development of a successful HIV vaccine .
All animals were maintained in accordance with the guidelines of the Committee on the Care and Use of Laboratory Animals under a NIAID-approved animal study protocol [49] , and all studies and procedures were reviewed and approved by the Institutional Animal Care and Use Committees of the NIH and Harvard Medical School . Animals were inoculated intravenously with SIVagmVer90 , an isolate from a naturally-infected vervet AGM ( Chlorocebus pygerythrus ) imported from Kenya in 1987 [7] . The virus ( SIVagmVer90 ) was isolated from the mesenteric lymph nodes of monkey AGM90 by coculture of viably frozen mononuclear cells with pigtailed macaque peripheral blood mononuclear cells ( PBMC ) . The vervet AGM utilized for this study were imported from Tanzania and screened for SIV infection by Western blotting , virus isolation from PBMC , and plasma viral RNA ( vRNA ) loads . PTM were colony bred in North America . All study animals were seronegative for SIV , respiratory syncytial virus ( SRV ) , and simian T-cell leukemia virus ( STLV-1 ) . A total of six adult vervet AGM and six adult PTM were recruited for combined CD8+ and CD20+ lymphocyte depletion studies . The chimeric anti-human CD8α monoclonal antibody ( mAb ) , cM-T807 ( NIH Nonhuman Primate Reagent Resource ) was administered at 10 mg/kg of body weight subcutaneously on day 0 ( the day of SIV infection ) followed by 5 mg/kg intravenous injections on days 3 , 7 , 10 and 14 . The anti-human CD20 mAb , Rituxan® ( Rituximab ) , purchased from Genentech , Inc . ( South San Francisco , CA ) , was administered intravenously at 50 mg/kg of body weight on days −7 , 14 and 35 . For lymph node biopsies , animals were sedated with Telazol® . For all other procedures including brochoalveolar lavage ( BAL ) , phlebotomy and Ab injections , animals were sedated with ketamine hydrochloride . Of these twelve treated animals , four AGM and four PTM were inoculated intravenously with 1 , 000 50% tissue culture infectious doses ( TCID50 ) of SIVagmVer90 on day 0 . The remaining antibody-treated animals ( two AGM and two PTM ) were not infected . Animals were monitored for 50 weeks following inoculation by plasma viral load , SIV-specific antibody responses by Western blot , lymphocyte subsets in the blood , BAL and lymph node biopsies ( −2 , 1 , and 4 weeks p . i . ) , and clinical evidence of disease . Animals showing weight loss of greater than 10% of body weight , diarrhea , or evidence of pneumonia that was unresponsive to antibiotic or supportive therapy were humanely euthanized and tissues collected for pathology . An additional four AGM and four PTM previously inoculated with the same SIVagmVer90 stock and dose served as historic , untreated controls [7] , [29] . Plasma levels of viral SIV RNA in PTM and AGM were measured by a quantitative real-time RT-PCR assay as previously described [7] , using methodology based on the 7700 sequence detection system ( Applied Biosystems , Foster City , CA ) . Plasma samples were collected from EDTA-anticoagulant whole blood and were stored in a −80°C freezer until analysis . Plasma viral RNA was isolated using a QIAmp viral RNA kit ( QIAGEN , Valencia , CA ) , and RT-PCR reactions were performed in 96-well plates . CMV DNA was quantitated in plasma using real-time PCR as previously described [50] . DNA was extracted from plasma with the QIAmp DNA Mini Kit ( Qiagen , Inc . , Valencia , CA ) . The rhesus CMV specific primers amplify a 108-bp amplicon in the exon 1 region of the immediate-early gene of rhesus CMV [51] and are reactive with the published AGM CMV [52] . The forward primer ( 5-GTTTAGGGAACCGCCATTCTG-3 ) corresponds to residues 4847 to 4867 of AGM CMV , the reverse primer ( 5-GTATCCGCGTTCCAATGCA-3 ) corresponds to residues 4936 to 4954 , and the probe ( 5-FAM-TCCAGCCTCCATAGCCGGGAAGG-tamra-3 ) corresponds to residues 4908 to 4930 . The PCR was run on an ABI-Prism 7700 Sequence Detection System ( PerkinElmer , Foster City , CA ) [50] . Nonradioactive in situ hybridization ( ISH ) for SIV expression was performed in formalin-fixed , paraffin-embedded lymph nodes utilizing sense or antisense digoxigenin labeled riboprobes that spanned the entire SIVagm9063-2 genome as previously described [25] . The number of SIV-expressing cells was measured as follows: Six random fields of view were selected for each of the ISH stained lymph nodes and the AxioVision automated segmentation measurement program was used to calculate the number of SIV+ cells per high powered field ( HPF ) . Lymph node biopsies were also evaluated for CD20 positive cells by using a mouse anti-human CD20 antibody ( M0755 , DAKO Cytomation , Carpenteria , CA ) , a mouse IgG avidin biotin complex-peroxidase kit ( Vector Laboratories , Ltd . , Burlingame , CA ) , and diaminobenzidine ( DAB ) substrate . Serology for antibodies to SIVagm was performed by Western blot analysis , as previously described [25] . Briefly , virus was pelleted from cell-free supernatant of CEMss cells infected with SIVagmVer90 . Virus particles were disrupted in Laemmli sample buffer , viral proteins were separated by SDS/polyacrylamide gel electophoresis and transferred onto nitrocellulose membranes . Individual strips containing SIVagm viral proteins were reacted with diluted PTM and AGM plasma and washed to remove unbound material . The bound SIV specific antibodies were visualized by subsequent reaction with ImmunoPure A/G protein conjugated with alkaline phosphatase ( Pierce Biotechnology , Rockford , IL ) , followed by nitroblue tetrazolium-5-bromo-4-chloro-3-indolylphosphate ( BCIP/NBT ) substrate system ( KPL , Laboratories , Gaithersburg , MD ) . Neutralization was measured as a function of reduction in luciferase reporter gene expression after a single round of infection in TZM-bl cells as described [31] . TZM-bl cells were obtained from the NIH AIDS Research and Reference Reagent Program , as contributed by John Kappes and Xiaoyun Wu . Briefly , 200 TCID50 of virus was incubated with a serial 3-fold dilution of test sample in duplicates in a total volume of 150 µl for 1 h at 37°C in 96-well flat-bottom culture plates . Freshly trypsinized cells ( 10 , 000 cells in 100 µl of growth medium containing 75 µg/ml DEAE dextran ) were added to each well . One set of control wells received cells and virus ( virus control ) and another set received cells only ( background control ) . After a 48 h incubation , 100 µl of cells were transferred to a 96-well black solid plate ( Corning , Lowell , MA ) for measurement of luminescence using the Britelite Luminescence Reporter Gene Assay System ( PerkinElmer ) . Neutralization titers are the dilution at which relative luminescence units ( RLU ) were reduced by 50% compared to virus control wells after subtraction of background RLUs . Assay stocks of molecularly cloned Env-pseudotyped viruses were prepared by transfection in 293T cells and were titrated in TZM-bl cells as described [31] . All antibodies were purchased from BD Biosciences ( San Jose , CA ) , BD Pharmingen ( San Jose , CA ) , Caltag ( Carlsbad , CA ) , R&D Systems ( Minneapolis , MN ) or Beckman Coulter ( Miami , FL ) . The antibodies used in this study were anti-CD95-Allophycocyanin ( DX2; BD Pharmingen ) , anti-CD28-PerCP-Cy5 . 5 ( L293; BD Biosciences ) , anti-CD4-AmCyan ( L200; BD Biosciences ) , anti-CD3-Pacific blue ( SP34-2; BD Biosciences ) , anti-CD3-Alexa Fluor 700 ( SP34; BD Pharmingen ) , anti-CD8α-Allophycocyanin-Cy7 ( SK1; BD Biosciences ) , anti-CD8α-Phycoerythrin ( DK25; Dako , Carpenteria , CA ) , anti-CD8α-PerCP-Cy5 . 5 ( SK1; BD Biosciences ) , anti-CD8α-Allophycocyanin ( SK1; BD Biosciences ) , anti-CD8αβ-Energy-Coupled Dye ( ECD ) ( 2ST8 . 5H7; Beckman Coulter ) , anti-CD20-Allophycocyanin-Cy7 ( L27; BD Biosciences ) , CD79a-PerCP-Cy5 . 5 ( HM47; BD Pharmingen ) , CD20-Phycoerythrin-Cy7 ( L27; BD Biosciences ) , Ki-67-Fluorescein Isothiocyanate ( B56; BD Biosciences ) . In order to determine the efficacy of lymphocyte depletion , whole blood was stained with anti-CD3 , anti-CD4 , anti-CD8 , anti-CD8αβ , anti-CD20 , and anti-CD79a antibodies . The use of the anti-CD8 clone DK25 ( coupled to PE ) and anti-CD79a permits detection of CD8+ lymphocytes and B cells with the best sensitivity in lymphocyte-depleted animals treated with the antibodies cM-T807 and Rituximab [53] , [54] . For detection of maturation-associated T cell subsets , whole blood samples were stained for 15 min with anti-surface antibodies ( CD3 , CD4 , CD8α , CD8αβ , CD28 and CD95 ) . Red blood cells were lysed by a TQ-prep instrument ( Beckman Coulter ) and the cells were washed with PBS . For determination of proliferation , cells were then fixed and permeabilized with Cytofix/Cytoperm solution ( BD Biosciences ) according to the manufacturer's description and stained with anti-Ki-67 mAb . Labeled cells were fixed in 1 . 5% formaldehyde-phosphate-buffered saline . Samples were collected on an LSR II instrument ( BD Biosciences ) and analyzed using FlowJo software ( TreeStar Inc . , Ashland , OR ) . Mononuclear cells were purified from BAL samples and lymph node biopsies and viably frozen in media consisting of 20% DMSO and 80% FCS , and flow cytometry was performed on thawed suspensions . Statistical analyses and graphical presentations were computed with GraphPad Prism 5 . 02 ( GraphPad Prism Software , La Jolla , CA ) . P values of <0 . 05 were considered significant . Mann-Whitney tests were applied for comparison of two groups . Kaplan-Meier graphs were used to compare survival , and log-rank tests were applied for statistical comparison . | Simian immunodeficiency virus ( SIV ) is a naturally occurring infection in a wide range of African nonhuman primates , including African green monkeys ( AGM ) , which generally results in a clinically inapparent infection . In contrast , SIV infection of Asian nonhuman primates such as macaques can result in an AIDS-like disease similar to that observed in humans infected with human immunodeficiency virus ( HIV ) . This different pathogenic outcome occurs despite similar levels of viremia . In order to evaluate the contribution of adaptive immune responses to these different outcomes , we transiently inhibited the generation of CD8+ and CD20+ lymphocyte-mediated immune responses in vervet AGM and pigtailed macaques ( PTM ) during primary SIV infection . PTM experienced higher viremia and accelerated progression to disease , whereas AGM showed only a short prolongation of peak viremia but exhibited no signs of illness . These results demonstrate that protection against development of disease in AGM does not solely rely on adaptive immune responses . Future efforts should aim to determine the underlying mechanisms that enable natural hosts to cope with SIV infection and to apply these findings to develop new treatment modalities for humans infected with HIV . | [
"Abstract",
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"virology/immunodeficiency",
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] | 2009 | Inhibition of Adaptive Immune Responses Leads to a Fatal Clinical Outcome in SIV-Infected Pigtailed Macaques but Not Vervet African Green Monkeys |
Quorum sensing is a chemical communication process that bacteria use to coordinate group behaviors . Pseudomonas aeruginosa , an opportunistic pathogen , employs multiple quorum-sensing systems to control behaviors including virulence factor production and biofilm formation . One P . aeruginosa quorum-sensing receptor , called RhlR , binds the cognate autoinducer N-butryl-homoserine lactone ( C4HSL ) , and the RhlR:C4HSL complex activates transcription of target quorum-sensing genes . Here , we use a genetic screen to identify RhlR mutants that function independently of the autoinducer . The RhlR Y64F W68F V133F triple mutant , which we call RhlR* , exhibits ligand-independent activity in vitro and in vivo . RhlR* can drive wildtype biofilm formation and infection in a nematode animal model . The ability of RhlR* to properly regulate quorum-sensing-controlled genes in vivo depends on the quorum-sensing regulator RsaL keeping RhlR* activity in check . RhlR is known to function together with PqsE to control production of the virulence factor called pyocyanin . Likewise , RhlR* requires PqsE for pyocyanin production in planktonic cultures , however , PqsE is dispensable for RhlR*-driven pyocyanin production on surfaces . Finally , wildtype RhlR protein is not sufficiently stabilized by C4HSL to allow purification . However , wildtype RhlR can be stabilized by the synthetic ligand mBTL ( meta-bromo-thiolactone ) and RhlR* is stable without a ligand . These features enabled purification of the RhlR:mBTL complex and of RhlR* for in vitro examination of their biochemical activities . To our knowledge , this work reports the first RhlR protein purification .
Quorum sensing is a process of intercellular communication that bacteria use to coordinate group behaviors [1–4] . Quorum sensing relies on the production , release , and group-wide detection of signaling molecules called autoinducers [5–7] . At low concentrations of autoinducer , bacteria act as individuals . At high concentrations of autoinducer , bacteria act as collectives , initiating behaviors that are beneficial when undertaken in unison by the group . Many species of Gram-negative bacteria use LuxR-type quorum-sensing receptors to orchestrate group behaviors [8–10] . LuxR-type receptors are transcription factors that , as they fold , typically bind to and are stabilized and activated by cognate homoserine lactone ( HSL ) autoinducers [6 , 11] . The opportunistic pathogen Pseudomonas aeruginosa employs two LuxR-type quorum-sensing receptors , LasR and RhlR , that interact with the cognate autoinducers N-3-oxo-dodecanoyl-L-homoserine lactone ( 3OC12HSL ) and N-butyryl-L-homoserine lactone ( C4HSL ) , respectively [8 , 10] . 3OC12HSL and C4HSL are produced by the LasI and RhlI synthases , respectively . LasR activates the genes encoding RhlR and RhlI , in addition to its own regulon , so the two quorum-sensing systems function in tandem [12 , 13] . RhlR also responds to a second autoinducer , designated the “alternative autoinducer” , whose identity remains unknown [14] . The alternative autoinducer is produced by PqsE [15] , a thioesterase involved in alkylquinolone synthesis [16] . When bound to either C4HSL or the alternative autoinducer , RhlR activates transcription of many genes , including those required for virulence factor production and biofilm formation [17 , 18] . LasR has been studied extensively; multiple LasR structures have been solved and the activities of wildtype and mutant LasR variants have been characterized [8 , 19–22] . RhlR , by contrast , is understudied , primarily as a consequence of its biochemical intractability . The C4HSL autoinducer does not stabilize recombinant RhlR , which has precluded purification of the protein [23] . One possible explanation underlying these difficulties is that RhlR does not bind C4HSL particularly tightly , as evidenced by a micromolar EC50 [24] . We contrast that value to the nanomolar EC50 that LasR , which can be purified , exhibits for 3OC12HSL [21] . A synthetic ligand called meta-bromo-thiolactone ( mBTL ) has been used to successfully solubilize RhlR , enabling some preliminary analyses of activity in recombinant E . coli [23] . We use mBTL in some of the studies in the present work . To accelerate studies of RhlR , here , we identify a RhlR mutant , RhlR Y64F W68F V133F , which we call RhlR* , that is stable and displays constitutive activity in the absence of any ligand . Threading analyses predict that all three of the RhlR* mutations reside in the ligand binding site , presumably allowing RhlR* to adopt a conformation mimicking the ligand-bound state [25] . RhlR* properly regulates quorum-sensing-controlled traits , including virulence factor production and biofilm formation . RhlR and PqsE function together to regulate the virulence factor called pyocyanin . RhlR* requires PqsE to produce pyocyanin in planktonic cultures but PqsE is dispensable for RhlR* to control pyocyanin production on surfaces . Finally , we show that the negative regulator , RsaL , prevents RhlR* from hyper-stimulating quorum-sensing-controlled genes . RhlR* represents a valuable tool for exploring RhlR structure and function .
To overcome issues with RhlR biochemical intractability , we took a genetic approach to identify RhlR mutants amenable to purification that might , moreover , provide insight into the RhlR structure , ligand binding mechanism , and regulation of transcriptional activation . Toward this goal , we performed a screen for mutants of RhlR that could function in the absence of a ligand . We used our previously reported E . coli reporter assay that harbors rhlR on one plasmid , and a RhlR-activated prhlA-lux transcriptional fusion on a second plasmid [26] . rhlA encodes a rhamnolipid biosynthetic enzyme required for virulence [27 , 28] . The logic underlying the screen is as follows: wildtype RhlR requires its cognate autoinducer C4HSL for activation . Therefore , E . coli carrying wildtype rhlR and prhlA-lux produces no light unless exogenous C4HSL autoinducer is provided . To identify autoinducer-independent RhlR variants , we assessed E . coli transformed with a rhlR mutant library for those clones that produced light in the absence of any supplied autoinducer , reasoning that such transformants must harbor RhlR variants that function independently of a ligand . We identified two RhlR mutants , RhlR Y64F and RhlR W68F , that produced 37-fold and 2 . 5-fold more light , respectively , than the background level produced by E . coli carrying wildtype RhlR and prhlA-lux ( Fig 1A ) . In neither case did the mutants elicit maximal luciferase activity comparable to that produced by E . coli carrying wildtype RhlR and prhlA-lux in the presence of saturating ( 10 μM ) C4HSL ( Fig 1A , dotted line ) . Furthermore , increased light production occurred when C4HSL or mBTL was provided to the E . coli reporter strain harboring RhlR Y64F or RhlR W68F ( S1 Fig ) . Therefore , RhlR Y64F and RhlR W68F , while harboring intrinsic autoinducer-independent activity , remain capable of ligand-driven activation . We wondered whether a RhlR mutant could be obtained that was capable of high level transcriptional activation and was , moreover , impervious to stimulation by a ligand . One possibility was the double RhlR Y64F W68F mutant , which we constructed , but its phenotype was similar to the single RhlR Y64F mutant ( Fig 1A ) . Thus , we sought additional mutations in RhlR that could be tested for enhancement of the ligand-independent phenotypes of the RhlR Y64F , RhlR W68F , or RhlR Y64F W68F mutants . We have previously reported that mutations at LasR A127 alter LasR responses to HSLs , and our companion structural analyses revealed that the A127 residue lies in the LasR ligand binding pocket and interacts with the autoinducer acyl tail [19 , 21] . Based on protein sequence alignments and threading analyses using the LasR structure as the model , V133 is the residue in RhlR equivalent to A127 in LasR , so we explored its role in ligand-driven activation of RhlR [29] . We constructed RhlR V133F and found that , without a ligand , it stimulated 177-fold more luciferase production than wildtype RhlR in the prhlA-lux assay ( Fig 1A ) . However , in this assay , RhlR V133F did not promote emission of as much light as that elicited by wildtype RhlR in the presence of saturating ligand ( Fig 1A ) . Combining the RhlR V133F mutation with the Y64F or W68F mutation further enhanced RhlR ligand-independent activity to approximately that made by wildtype RhlR in the presence of saturating autoinducer ( Fig 1A ) . The RhlR Y64F W68F V133F triple mutant exhibited the highest activity of all mutants tested , exceeding the activity produced by wildtype RhlR in the presence of saturating autoinducer . Specifically , in the absence of autoinducer , the triple mutant produced approximately 10 , 000 times more light than did wildtype RhlR in the absence of autoinducer ( Fig 1A ) . Provision of C4HSL or mBTL did not further increase the activity of RhlR Y64F W68F V133F ( Figs 1B and S1 ) . Thus , RhlR Y64F W68F V133F appears to be fully active with no ligand bound . In the remainder of this work , we refer to RhlR Y64F W68F V133F as RhlR* . Amino acid sequence alignments show that residues that , when altered in RhlR , confer ligand independence , are well conserved among LuxR-type receptors [30] . To investigate whether the residues we pinpointed as driving ligand-independent activity in RhlR also promote ligand-independence in LasR , we constructed the analogous set of single , double , and triple LasR mutants . These variants are: LasR Y56F , LasR W60F , LasR A127F , LasR Y56F W60F , LasR Y56F A127F , LasR W60F A127F , and LasR Y56F W60F A127F . We examined the activities of these LasR mutants along with wildtype LasR in our previously reported E . coli lasR plasB-lux reporter system [31] . All of these mutants responded , at least partially , to exogenous 3OC12HSL , mBTL , or both agonists . ( S2 Fig ) , and none of the LasR variants stimulated luciferase activity in the absence of added ligand ( Fig 1C ) . Thus , these alterations do not confer ligand independence on LasR even though two of the residues are identical in LasR and RhlR ( RhlR Y64 = LasR Y56 and RhlR W68 = LasR W60 ) [30] . The residue at RhlR V133 ( LasR A127 ) is not as well conserved among LuxR family members . At this position , the residue is typically hydrophobic ( A , I , L , F , M , or V ) [21] . We characterized different RhlR* biochemical activities to learn how RhlR* functions without a ligand . First , as a proxy for folding , we compared the solubility of RhlR* to that of wildtype RhlR bound to mBTL , the only ligand known to be capable of solubilizing RhlR ( Fig 2A ) [23] . We expressed wildtype rhlR and rhlR* in E . coli . In the case of wildtype RhlR , we grew the recombinant strain in the absence and presence of 100 μM of mBTL . In the case of RhlR* , we did not add any ligand . As reported previously , RhlR was insoluble in the absence of the mBTL ligand [23] and in the presence of mBTL , a substantial portion of the RhlR protein was present in the soluble fraction ( Fig 2A ) . RhlR* was soluble at levels comparable to that of the RhlR:mBTL complex ( Fig 2A ) showing that unlike wildtype RhlR , RhlR* can fold when it is not bound to a ligand . Addition of mBTL to E . coli expressing RhlR* did not enhance its solubility ( Fig 2A ) , further indicating that RhlR* folds without a ligand . We purified the RhlR:mBTL complex ( Fig 2B shows the final fractions; S3A Fig shows the preceding purification step ) using a protocol similar to one we developed for purification of LasR bound to HSLs and analogs ( see Materials and Methods and [21] ) . We confirmed the presence of RhlR protein by immunoblotting with a RhlR-specific antibody ( Fig 2B ) . We confirmed that mBTL was present by heating the purified RhlR:mBTL complex to 95°C to denature the protein and allow release of the ligand . We assayed the released ligand using the E . coli rhlR and prhlA-lux reporter strain ( Fig 2C ) . Released mBTL was also verified by mass spectrometry ( S3B Fig ) . We used the identical protocol to purify RhlR* with no ligand added ( Fig 2B ) . To our knowledge , this is the first report of the purification of a functional RhlR:ligand complex , and also , of course , the first time a RhlR variant has been purified without a ligand . The yield of RhlR* was low , and its purity in the peak fraction was approximately 70% compared to >95% purity for the wildtype RhlR:mBTL complex ( Fig 2B ) . These issues hindered our ability to perform multiple biochemical analyses for comparison of RhlR* to RhlR:mBTL . To overcome this issue , we next purified maltose binding protein-tagged RhlR: mBTL and RhlR* ( called MBP-RhlR:mBTL and MBP-RhlR* , S4A Fig ) . MBP-RhlR required the presence of mBTL to become soluble and enable purification , while MBP-RhlR* did not . MBP-RhlR* solubility was enhanced ~2-fold by mBTL ( S4A Fig ) and we return to this point below . Thus , MBP-RhlR and MBP-RhlR* are governed by principles similar to those of the native proteins , but , in the case of MBP-RhlR* , with markedly increased yield . To test whether the MBP tag interfered with RhlR function , we compared the DNA binding capabilities of RhlR:mBTL and MBP-RhlR:mBTL using a gel-shift assay to assess binding to rhlA promoter DNA . rhlA expression is RhlR-dependent and the promoter contains a rhl-box sequence that is required for RhlR promoter binding in vivo ( S4B Fig ) [32 , 33] . Both RhlR:mBTL and MBP-RhlR:mBTL bound to the rhlA promoter in a concentration dependent manner and , moreover , there were no differences between MBP-RhlR:mBTL and RhlR:mBTL DNA binding ( S4C Fig ) . Addition of unlabeled competitor DNA blocked RhlR:mBTL and MBP-RhlR:mBTL binding to the labeled rhlA promoter ( S4D Fig ) . These results gave us confidence that the MBP tag does not interfere with RhlR activity , and thus MBP-RhlR* would be suitable for assessment of its function . Indeed , exactly like MBP-RhlR:mBTL , MBP-RhlR* bound to the rhlA promoter and to two other RhlR-dependent rhl-box containing promoters , rhlI and hcnA ( Figs 3A and S4B ) . Neither MBP-RhlR:mBTL nor MBP-RhlR* bound to control DNA amplified from an intergenic region of the P . aeruginosa chromosome ( S4E Fig ) . Using isothermal titration calorimetry and the rhl-box consensus sequence [34] , we determined the Kd for MBP-RhlR:mBTL and MBP-RhlR* for DNA to be 23 nM and 34 nM , respectively ( Fig 3B ) . Thus , RhlR* functions essentially identically to RhlR bound to ligand , at least with respect to DNA binding . RhlR* functions in our E . coli reporter assay and it can bind DNA in vitro with no ligand present . We thus wondered whether RhlR* can , in fact , bind a ligand . To test this possibility , we purified MBP-RhlR* in the presence of mBTL . As mentioned , MBP-RhlR* solubility was enhanced ~2-fold when mBTL was present ( S4A Fig , right side ) . For comparison , wildtype MBP-RhlR solubility was enhanced at least 10-fold by mBTL ( S4A Fig , left side ) . Mass spectrometry showed that mBTL was present in MBP-RhlR* when mBTL was supplied during purification ( S4F Fig ) . Thus , while the RhlR* variant activates gene expression in a ligand-independent manner that is not enhanced by mBTL ( Figs 1 and S1B ) , it can bind mBTL ( S4A and S4F Fig ) . Our in vitro analyses show that unliganded-RhlR* functions identically to wildtype RhlR bound to an autoinducer or an autoinducer mimic . To examine the consequences of RhlR* on quorum sensing in vivo , we engineered P . aeruginosa with rhlR* on the chromosome at its native location in an otherwise wildtype strain and in a ΔrhlI ΔpqsE strain . Our rationale for the second strain is that by deleting rhlI and pqsE , we eliminate endogenous production of both of the RhlR autoinducers; C4HSL ( synthesized by RhlI ) and the alternative autoinducer whose identity is not known ( synthesized by PqsE ) . We measured the effect of RhlR* on colony biofilm formation in both strains . Wildtype P . aeruginosa produces colony biofilms with rugose centers and smooth peripheries on Congo red plates ( Fig 4 ) [14 , 15] . By contrast , the P . aeruginosa ΔrhlI ΔpqsE strain forms hyper-rugose colony biofilms because it is defective for phenazine production ( Fig 4 ) [14 , 15] . Both the wildtype and the ΔrhlI ΔpqsE P . aeruginosa strains harboring RhlR* produced colony biofilms with morphologies similar to the wildtype ( Fig 4 ) . These results suggest that , in vivo , RhlR* is active , ligand independent , and capable of promoting normal colony biofilm formation . Furthermore , the presence of autoinducers has no effect on this RhlR*-driven phenotype as shown in Fig 4 by the similar colony biofilms made by the rhlR* and the rhlR* ΔrhlI ΔpqsE strains . The colony biofilm assay takes place over 120 hours . To confirm that RhlR* also functions analogously to wildtype in short time-course assays , we measured RhlR- and RhlR*-directed activation of a chromosomal prhlA-mNeonGreen transcriptional fusion in ΔrhlI P . aeruginosa . We supplied DMSO or 10 μM C4HSL to the strains . At every time point , prhlA-mNeonGreen expression in the RhlR* strain to which either DMSO or C4HSL had been added was within ~15% of that in the strain carrying wildtype RhlR supplied with C4HSL ( S5 Fig ) . Taken together , these results show that RhlR and RhlR* are functionally equivalent for gene expression and in complex phenotypes such as colony biofilm formation . RhlR is a crucial regulator of P . aeruginosa virulence . Unlike wildtype RhlR , RhlR* activity is not subject to the cell-density-dependent accumulation of autoinducer . For this reason , we wondered if RhlR* could properly regulate virulence factor production . To investigate this issue , we measured pyocyanin production , which depends on RhlR [10] . Wildtype and rhlR* P . aeruginosa strains produced , respectively , 26-and 21-fold more pyocyanin than the ΔrhlR strain ( Fig 5 ) . Thus , RhlR* can substitute for RhlR to control pyocyanin production . Interestingly , the ΔrhlI ΔpqsE and rhlR* ΔrhlI ΔpqsE strains produced almost no pyocyanin ( Fig 5 ) . This result suggested that , unlike for colony biofilm formation and rhlA transcription , RhlR* may require an autoinducer to promote pyocyanin production . To explore this possibility , we examined the reliance of RhlR* on RhlI and on PqsE for pyocyanin production . The ΔrhlI strain produced almost no pyocyanin while the rhlR* ΔrhlI strain produced pyocyanin at a level equivalent to the rhlR* strain ( Fig 5 ) . These results show that C4HSL is not required for RhlR* to activate pyocyanin production . The ΔpqsE strain produced almost no pyocyanin , a phenotype that has been reported previously [35 , 36] , and likewise , the rhlR* ΔpqsE strain also did not make pyocyanin ( Fig 5 ) . Thus , RhlR* requires PqsE to drive pyocyanin production in this assay . One interpretation for the above results is that , to promote pyocyanin production in liquid cultures , RhlR* requires the alternative autoinducer that is synthesized by PqsE . However , evidence already exists suggesting this cannot be the case: PqsE thioesterase activity is required for alternative autoinducer synthesis [15] but not for pyocyanin production in liquid culture [37] . An alternative interpretation is that PqsE plays a second role in the regulation of pyocyanin production in liquid beyond that of alternative autoinducer synthesis , and RhlR* cannot bypass this additional PqsE function . We offer some ideas to underpin this second hypothesis in the Discussion . To explore RhlR* function in the context of an animal infection model , we employed the Caenorhabditis elegans fast kill assay [38] . In this assay , P . aeruginosa rapidly kills C . elegans in a pyocyanin-dependent manner . The C . elegans fast kill assay steps are as follows: P . aeruginosa cells are incubated for 48 hours on petri plates , enabling them time to produce pyocyanin , after that , nematodes are added , and killing is subsequently assessed [39 , 40] . To test the potential of our strains in this assay , we first preliminarily examined their pyocyanin production profiles on surfaces . Wildtype and rhlR* P . aeruginosa produced ample pyocyanin on plates ( S6 Fig ) . The rhlR* ΔrhlI ΔpqsE strain also produced pyocyanin on surfaces , albeit less than the wildtype and rhlR* strains , and the ΔrhlI ΔpqsE strain did not produce detectable pyocyanin ( S6 Fig and [15] ) . Thus , unlike in liquid culture , all of the strains containing rhlR* make pyocyanin on surfaces and therefore could have the capacity to be virulent in this nematode infection model . In the nematode fast-kill assay , wildtype and rhlR* P . aeruginosa killed over 95% of the C . elegans within 24 hours ( Fig 6 ) . The rhlR* ΔrhlI ΔpqsE P . aeruginosa strain killed 75% of the C . elegans , consistent with our finding that the strain produces pyocyanin on surfaces , however , less than the wildtype and rhlR* strains ( Figs 6 and S6 ) . By contrast , the ΔrhlI ΔpqsE strain was highly attenuated , killing only 2% of the nematodes . ( Fig 6 ) . Again , this result tracks with the inability of this mutant to make detectable pyocyanin on plates ( S6 Fig ) . Together , these virulence phenotypes show that RhlR* functions in vivo and , moreover , the phenotype of the rhlR* ΔrhlI ΔpqsE strain implies that no autoinducer is required for the strain to be highly virulent . Many RhlR-controlled products are public goods that are energetically expensive to produce . Thus , one could imagine that it would be detrimental for P . aeruginosa to harbor a ligand-independent RhlR variant that hyper-stimulates quorum-sensing-controlled gene expression . However , curiously , all of our above results show that P . aeruginosa containing RhlR* is essentially wildtype for colony biofilm formation ( Fig 4 ) , pyocyanin production ( Fig 5 ) , and virulence in nematodes ( Fig 6 ) . While our experiments do not address survival of P . aeruginosa carrying RhlR* in the wild , they nonetheless suggest that some component exists that caps RhlR* activity to normalize RhlR-controlled traits . The obvious candidate is RsaL , a transcriptional regulator that represses quorum-sensing-activated genes [38 , 41] . To test this hypothesis , we measured pyocyanin production in late stationary phase ( RsaL accumulates during stationary phase [42] ) in wildtype , rhlR* , ΔrsaL , and rhlR* ΔrsaL strains . Both strains containing the ΔrsaL mutation produced significantly more pyocyanin than did the corresponding wildtype and rhlR* P . aeruginosa strains ( Fig 7A ) . We also tested the role of RsaL in curbing RhlR* activity in colony biofilms . Unlike wildtype and rhlR* P . aeruginosa , both the ΔrsaL and rhlR* ΔrsaL strains produced colony biofilms that were smooth ( Fig 7B ) . These colony biofilms resemble those made by the ΔrhlI mutant suggesting that the ΔrsaL and rhlR* ΔrsaL strains over-produce phenazines [14] . Additionally , the biofilms made by the ΔrsaL and rhlR* ΔrsaL contained voids at the centers , which we do not understand ( Fig 7B ) . Our results show that RhlR* promotes higher pyocyanin production and drives altered colony biofilm formation in the absence of RsaL , demonstrating that RsaL prevents RhlR* from excessively stimulating quorum-sensing-controlled gene expression . Furthermore , the ligand-independent nature of RhlR* does not interfere with this RsaL regulatory role . Together , these results explain why RhlR* behaves similarly to wildtype RhlR in vivo and support our suggestion that RhlR* can be used as a tool to study RhlR regulation .
RhlR , a central component of the P . aeruginosa quorum-sensing system , controls many genes , including those required for biofilm formation and virulence factor production . Here , we report RhlR* , a constitutive RhlR allele that is stably produced and that functions without an agonist bound . There are dozens of studied LuxR-type receptors , of which RhlR is one . Almost all are unstable and inactive absent a ligand . We note that EsaR and a few other LuxR-type receptors are exceptions in that they operate by a mechanism distinct from the vast majority of LuxR-type receptors , RhlR included . Specifically , EsaR binds DNA and activates transcription when no ligand is bound and EsaR is inactive when bound to an autoinducer [43 , 44] . Amongst the ligand-dependent LuxR-receptors , RhlR* represents a new type of mutant and its lack of ligand-dependence enables previously inaccessible possibilities for its study . RhlR* contains three mutations: Y64F , W68F , and V133F . Currently , there is no RhlR crystal structure , but the locations of the RhlR* mutations provide potential insight into the RhlR structure . Based on threading , each of the RhlR* mutations resides in the putative RhlR ligand binding site and we suspect that the three hydrophobic phenylalanine residues fill and stabilize the hydrophobic ligand binding pocket , essentially mimicking the bound ligand , and in so doing , stabilize the protein [25] . This idea is supported by our previous work with LasR demonstrating that a phenylalanine substitution at LasR L130 ( RhlR L136 ) in the LasR ligand binding pocket made the LasR L130F protein overall more stable than wildtype LasR , but not ligand independent [21] . Furthermore , mutation of the autoinducer acyl-tail binding LasR residue A127 to tryptophan prevented binding of 3OC12HSL and enhanced binding to HSLs possessing shorter tails suggesting that the large residue partially occupied the ligand binding site [21] . However , neither of these LasR substitutions conferred ligand-independent activity to LasR , nor did the LasR Y56F W60F A127F mutant made here ( Fig 1C ) . We suggest that one reason RhlR may be more amenable to stabilization by bulky substitutions than is LasR is , because RhlR , to accommodate C4HSL , possess an intrinsically smaller binding pocket than LasR ( which naturally accommodates 3OC12HSL ) , and a smaller binding pocket is more easily filled and stabilized by bulky groups . Our analyses of in vivo RhlR* phenotypes show that the protein is functional with no autoinducer present , and that in this state , it can drive colony biofilm formation and nematode killing ( Figs 4 and 6 ) . The role of RhlR* in activating pyocyanin production was less straightforward concerning its reliance on PqsE ( Fig 5 ) . On surfaces , the rhlR* ΔrhlI ΔpqsE P . aeruginosa strain produces some pyocyanin ( S6 Fig ) , and indeed , an amount sufficient to kill nematodes ( Fig 6 ) , so PqsE is not required for P . aeruginosa harboring RhlR* to produce pyocyanin on plates . In contrast , the P . aeruginosa rhlR* ΔrhlI ΔpqsE strain does not produce detectable pyocyanin in liquid culture ( Fig 5 ) , so PqsE is required . We know that one role of PqsE is in alternative autoinducer production . However , RhlR* appears to be autoinducer-independent , so we propose that PqsE must therefore have another role in pyocyanin production that RhlR* can bypass on surfaces but not in liquid culture . We do not yet understand the nature of this PqsE activity . We can imagine some possibilities: Two nearly identical but distinctly regulated phz ( phenazine ) operons , phz1 and phz2 , exist in P . aeruginosa . Either operon can be employed to produce the phenazine precursors required for pyocyanin biosynthesis [45 , 46] . With respect to regulation , phz2 plays the major role on surfaces while phz1 plays a substantial role in planktonic cultures [45] . The differential regulation of these two operons mimics the differences in pyocyanin production we observe in liquid versus surface conditions . Perhaps RhlR and PqsE physically interact to activate expression of the phz1 operon while RhlR bound to the alternative autoinducer drives expression of phz2 . If RhlR* cannot bypass the need to interact with PqsE but can , as we have shown , function in the absence of any ligand , such a mechanism could explain the differences in pyocyanin production in our mutants on surfaces and in liquid . Alternatively , PqsE functions in production of an alkylquinolone precursor to the PQS signal molecule [16] , and PQS quorum sensing is required for pyocyanin production in liquid culture [46] . Perhaps the PqsE contribution to pyocyanin production is through this alternative biosynthetic route and this pathway operates in liquid but is not required on surfaces . While further investigation is needed , our results , combined with earlier ones [15 , 46] , provide increasing evidence that P . aeruginosa virulence products are regulated differently under particular environmental conditions . RhlR* behaved similarly to wildtype RhlR in all of our assays . Most surprising to us was that the high-level activation of RhlR exhibited by RhlR* did not cause increased gene expression or hyper-production of quorum-sensing-controlled products . These findings suggested to us that evolution has built checks into the P . aeruginosa quorum-sensing system that protects it against excessive stimulation . We suggest that system brakes exist both upstream and downstream of RhlR . First , the upstream brake is LasR , which is required for activation of rhlR expression . Thus , ligand-independent RhlR* is incapable of prematurely activating target gene expression because its own expression depends on LasR , and LasR only functions at high cell density when its cognate autoinducer , 3OC12HSL , has accumulated . This idea is supported by previous work demonstrating that provision of excess C4HSL to P . aeruginosa cultures does not prematurely activate expression of RhlR target genes [47] . Although , LasR directs the proper timing of RhlR ( and RhlR* ) activity , RhlR* , once made , could drive excessive activation of its target genes , but our results show this does not happen . We propose that this cap on activity is due to RsaL , that acts as a second , downstream brake on RhlR* ( Fig 7 ) . RsaL represses transcription of RhlR-activated target genes preventing their overproduction [48] . Our results combined with earlier ones [47 , 48] demonstrate that while RhlR is responsible for activating a large regulon of genes in P . aeruginosa , two buffering mechanisms are present and ensure that RhlR ( and RhlR* ) activity is constrained to a proper window so it does not exceed the tolerable range . Our discovery of RhlR* and its characterization provide initial insight into its biochemical activities , how it functions in conjunction with PqsE , and possibly the shape of the ligand binding pocket . The RhlR* protein offers an unparalleled opportunity for crystallization , given that wildtype RhlR and RhlR mutants reported to date have been intractable to structural analysis . Furthermore , because there is a connection between RhlR activity and PqsE activity , RhlR* could be a useful tool to discover the mechanisms underlying PqsE functions . Finally , because RhlR* is ligand-independent and active , it could be used to identify RhlR inhibitors , possibly fostering development of anti-quorum-sensing therapeutics for P . aeruginosa , fulfilling an urgent medical need .
Random mutations in rhlR were generated using the Diversify PCR Random Mutagenesis Kit ( Takara; mutagenesis level 5 protocol ) with the primers ARM289 and ARM290 ( S1 Table ) . Mutagenized DNA was digested with XhoI and SacI ( NEB ) and ligated into pBAD-A using T4 ligase ( NEB ) . The resulting plasmids were transformed into One-shot TOP10 E . coli chemically competent cells ( Invitrogen ) along with prhlA-luxCDABE . Reactions were plated on LB agar rectangular plates containing ampicillin ( 100 mg/L ) and kanamycin ( 50 mg/L ) . Colonies were arrayed into black clear-bottom 96-well plates ( Corning ) using a BM3-BC colony handling robot ( S&P Robotics Inc . ) and screened for luciferase production . Hits were sequenced using primers ARM209 and ARM210 . Candidate rhlR mutants were re-engineered in pBAD-A-rhlR using a previously reported site directed mutagenesis protocol [21] . Primers and strains used in this work are listed in S1 and S2 Tables , respectively . LasR variants containing mutations homologous to those studied here in RhlR were constructed using pBAD-A carrying lasR and a previously reported site directed mutagenesis protocol [21] . Mutations were sequenced using primers ARM203 and ARM204 [21 , 31] . In-frame , marker-less rhlR mutations were engineered onto the chromosome of P . aeruginosa PA14 as previously described [14] . Briefly , the rhlR gene and 500 base pairs of upstream and downstream flanking regions were cloned into pUCP18 [49] . rhlR mutants were constructed using pEXG2-suicide constructs with gentamicin selection and sacB counter selection [50 , 51] . Candidate rhlR constructs were sequenced with rhlR forward and reverse primers ( ARM209 and ARM210 ) . We have previously described a method to assess RhlR activity in response to exogenous ligands , which relies on luciferase as a reporter [26] . In brief , 2 μL of overnight cultures of Top 10 E . coli carrying a plasmid harboring prhlA-luxCDABE and the pBAD-A plasmid carrying either wildtype or mutant rhlR alleles were back diluted into 200 μL LB medium and aliquoted into clear-bottom 96-well plates ( Corning ) . The plates were shaken at 30°C for 4 hours , at which time 0 . 1% arabinose was added to each well . To measure responses to a single concentration of autoinducer , either 2 μL of DMSO or 10 μM of C4HSL in DMSO was added to each well . To measure responses to different concentrations of ligands , ten 3-fold serial dilutions of 10 mM C4HSL or 10 mM mBTL were made into DMSO , and 2 μL of each dilution was added to appropriate wells . In all assays , the plates were shaken at 30°C for 4 hours . Bioluminescence and OD600 were measured using a Perkin Elmer Envision Multimode plate reader . Relative light units were calculated by dividing the bioluminescence measurement by the OD600 nm measurement . The assay to measure LasR and mutant LasR activity is identical to that for RhlR except the reporter plasmids contain lasR and plasB-luxCDABE and 3OC12HSL ( serially diluted from a 100 μM stock ) was used as the autoinducer instead of C4HSL . Full-length RhlR/RhlR* ( cloned into pET23b ) and MBP-RhlR/MBP-RhlR* ( cloned into pMALC2x ) were overexpressed in BL21 E . coli cells using 1 mM IPTG at 25°C for 4 hours in the presence ( for wildtype RhlR ) or absence ( for RhlR* ) of 100 μM mBTL . Cells were pelleted at 16 , 100 x g and resuspended in lysis buffer ( 500 mM NaCl , 20 mM Tris-HCl pH 8 , 20 mM imidazole , 1 mM EDTA , 1 mM DTT , 5% glycerol ) . Resuspended cells were lysed using sonication ( 1 second pulses for 15 seconds ) . The soluble fraction from each preparation was isolated using centrifugation at 32 , 000 x g . For RhlR:mBTL and RhlR* , protein was prepared for heparin column binding by diluting the samples 5-fold in buffer A ( 20 mM Tris-HCl pH 8 , 1 mM DTT ) . Protein was loaded on a heparin column ( GE Healthcare ) and eluted using a linear gradient from buffer A to buffer B ( 1 M NaCl , 20 mM Tris-HCl pH 8 , 1 mM DTT ) . Peak fractions were assessed by SDS PAGE analysis and pooled . Pooled fractions were concentrated for size exclusion chromatography using a Superdex-200 ( GE Healthcare ) column in 200 mM NaCl , 20 mM Tris-HCl pH 8 , and 1 mM DTT . Pooled fractions were concentrated to 2 mg/mL , flash frozen , and stored at -80°C . To confirm the presence of mBTL , 100 μL aliquots of fractions 7–12 from Superdex-200 columns were heated to 95°C for 15 minutes . Denatured protein was removed by centrifugation at 20 , 000 x g and 100 μL of the clarified supernatants were added to 900 μL of the reporter strain . For MBP-RhlR:mBTL and MBP-RhlR* , soluble fractions were applied to amylose resin ( NEB ) and incubated at 4°C for 1 hour . Bound protein was eluted from the resin using 10 mM maltose in lysis buffer and collected via gravity flow . Elution was repeated 10 times using 1 mL elution volumes . Fractions were pooled and concentrated . Concentrated protein was applied to a Superdex-200 column as described above . 600 μL of acetonitrile was added to 20 μg of RhlR:mBTL , MBP-RhlR:mBTL , or MBP-RhlR* and heated at 40°C for 1 hour to extract ligand from the protein . The sample was concentrated , and an equivalent of 2 μg was injected on an LTQ Orbitrap XL coupled to a Shimadzu HPLC ( Thermo Scientific ) for analysis as reported previously [52] . The rhlA , rhlI , and hcnA promoter sequences were amplified using PCR . The 5’-end of the forward primer for each pair was labeled with biotin ( IDT ) . The labeled probe was incubated with 0 , 10 , 20 , 30 , 50 , 100 , 200 , 500 ng of purified RhlR:mBTL , MBP-RhlR:mBTL , or MBP-RhlR* in binding buffer ( 20 mM Tris-HCl pH 8 , 50 mM KCl , 1 mM EDTA , 1 mM DTT , 1 . 5 mg/mL poly-IC , 50 μg/mL BSA , and 10% glycerol ) at room temperature for 15 minutes . DNA-protein complexes were subjected to electrophoresis on 6% DNA retardation gels ( Invitrogen ) . DNA was visualized using the chemiluminescent nucleic acid detection module ( Thermo Scientific ) . Briefly , DNA was transferred to a membrane , crosslinked , and incubated with blocking buffer for 15 minutes with shaking . The membranes were next incubated in stabilized streptavidin-horseradish peroxidase conjugate in blocking buffer for 15 minutes with shaking . The membranes were then washed 4 times for 5 minutes with wash buffer followed by incubation in substrate equilibration buffer for 5 minutes with shaking . Chemiluminescent substrate working solution was prepared by mixing equal parts luminol solution and stable peroxide solution . The membrane was removed from substrate equilibration buffer and incubated with the prepared chemiluminescent solution for 5 minutes without shaking . After incubation , the excess liquid was decanted and the blot was imaged on an Image Quant LAS4000 gel dock using the luminescence setting ( GE Healthcare ) . Isothermal titration calorimetry ( ITC ) was performed using a MicroCal PEAQ-ITC instrument ( Malvern ) . 20 μM of rhl-box consensus sequence DNA ( ACCTGCCAGATTTCGCAGGT ) was titrated into a cell containing 1 μM of MBP-RhlR:mBTL or MBP-RhlR* at 25°C with a stirring speed of 1 , 000 rpm . Initial injection volume for the DNA was 0 . 4 μL and every subsequent injection was 2 μL . Consensus sequence DNA was resuspended in buffer to match the MBP-RhlR* and MBP-RhlR:mBTL S200 buffer . Data fitting was performed with the PEAQ-ITC Analysis software ( Malvern ) . The protocol for this assay was adapted from [14] . In brief , 1 . 5 μL aliquots of overnight cultures of P . aeruginosa strains grown in 1% tryptone broth were spotted onto 60 x 15 mm plates containing 10 mL of 1% tryptone medium , 1% agar , 40 mg/L Congo red dye , and 20 mg/L Coomassie brilliant blue dye . Colony biofilms were grown for 120 hours at 25°C . Images were acquired using a Leica stereomicroscope M125 mounted with a Leica MC170 HD camera at 7 . 78x zoom . Overnight cultures of P . aeruginosa strains grown in LB medium were diluted 1:500 into 25 mL of LB medium and grown for an additional 9 hours at 37°C . One ml aliquots were collected every 1 hour starting 4 hours post-dilution . The cell density ( OD600 nm ) of each sample was measured using a Beckman Coulter DU730 Spectrophotometer . The aliquots were subjected to centrifugation at 16 , 100 x g for 2 minutes and the supernatants were discarded . The cell pellets were resuspended in 1 mL of PBS , and 200 μL of each resuspended sample was placed into clear-bottom 96-well plates ( Corning ) and fluorescence was measured using a Perkin Elmer Envision Multimode plate reader . Relative fluorescence units were calculated by dividing the fluorescence measurement by the OD600 nm measurement . Overnight cultures of P . aeruginosa strains grown in LB medium were diluted 1:50 into 25 mL of LB medium and agitated for 8 hours at 37°C . 1 mL aliquots were removed from the cultures and cell density ( OD600 nm ) was measured using a Beckman Coulter DU730 Spectrophotometer . The aliquots were next subjected to centrifugation at 16 , 100 x g for 2 minutes and the clarified supernatants were removed and filtered through 2 μm filters . The OD695 nm of each supernatant was measured . Pyocyanin activity was determined by plotting the OD695 nm/OD600 nm over time for each strain . Pyocyanin assays on stationary phase cultures were performed as above , except the cultures were incubated for 24 hours prior to analysis . This procedure was adapted from [39] . Briefly , 10 μL aliquots from overnight cultures of the P . aeruginosa strains under study were spread onto 3 . 5 cm peptone-glucose-sorbitol agar medium plates ( PGS ) and grown for 24 hours at 37°C followed by 24 hours at 25°C . Thirty age-matched L4 C . elegans nematodes were placed onto each plate containing the bacteria . C . elegans were scored as live or dead at 4 , 6 , 8 , and 24 hours by stroking each animal with a pick and assessing signs of movement . The percentage of live nematodes was calculated by dividing the number of live worms by the total number of worms tested for each P . aeruginosa strain and multiplying by 100 . Visual inspection of pyocyanin production by P . aeruginosa strains on PGS solid medium was performed as described previously ( 14 ) . In brief , strains were grown overnight in LB medium with shaking at 37°C . A 10 μL volume of each stationary phase culture was plated on PGS agar medium . Plates were incubated at 37°C for 48 hours at which time images were acquired . | The human pathogen Pseudomonas aeruginosa uses a chemical communication process called quorum sensing to orchestrate group behaviors including virulence factor production and biofilm formation . Thus , quorum sensing is essential for P . aeruginosa to be a pathogen . Quorum sensing relies on the production , release , and detection of extracellular signal molecules called autoinducers . Autoinducers are bound by partner receptor proteins , and together , autoinducer-receptor complexes control gene expression . Here , we identify , purify , and characterize a mutant version of the P . aeruginosa RhlR quorum-sensing receptor that we call RhlR* , which , remarkably , does not require its partner autoinducer to function . We show that P . aeruginosa carrying RhlR* can properly form biofilms , produce virulence factors , and infect a nematode animal used as a model for pathogenesis . Because RhlR* does not rely on an autoinducer to function , biochemical and genetic analyses that were previously not possible with RhlR could be performed with RhlR* . Indeed , our studies of RhlR* provide new insight into the workings of other P . aeruginosa quorum-sensing components , most notably , the PqsE enzyme that functions together with RhlR to control virulence factor production . We propose that RhlR* is an especially valuable tool for learning about cell-cell communication and virulence in P . aeruginosa , a pathogen of high clinical relevance . | [
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"d... | 2019 | An autoinducer-independent RhlR quorum-sensing receptor enables analysis of RhlR regulation |
Jaagsiekte sheep retrovirus ( JSRV ) is a unique oncogenic virus with distinctive biological properties . JSRV is the only virus causing a naturally occurring lung cancer ( ovine pulmonary adenocarcinoma , OPA ) and possessing a major structural protein that functions as a dominant oncoprotein . Lung cancer is the major cause of death among cancer patients . OPA can be an extremely useful animal model in order to identify the cells originating lung adenocarcinoma and to study the early events of pulmonary carcinogenesis . In this study , we demonstrated that lung adenocarcinoma in sheep originates from infection and transformation of proliferating type 2 pneumocytes ( termed here lung alveolar proliferating cells , LAPCs ) . We excluded that OPA originates from a bronchioalveolar stem cell , or from mature post-mitotic type 2 pneumocytes or from either proliferating or non-proliferating Clara cells . We show that young animals possess abundant LAPCs and are highly susceptible to JSRV infection and transformation . On the contrary , healthy adult sheep , which are normally resistant to experimental OPA induction , exhibit a relatively low number of LAPCs and are resistant to JSRV infection of the respiratory epithelium . Importantly , induction of lung injury increased dramatically the number of LAPCs in adult sheep and rendered these animals fully susceptible to JSRV infection and transformation . Furthermore , we show that JSRV preferentially infects actively dividing cell in vitro . Overall , our study provides unique insights into pulmonary biology and carcinogenesis and suggests that JSRV and its host have reached an evolutionary equilibrium in which productive infection ( and transformation ) can occur only in cells that are scarce for most of the lifespan of the sheep . Our data also indicate that , at least in this model , inflammation can predispose to retroviral infection and cancer .
Retroviruses have been instrumental in understanding the genetic basis and the fundamental molecular mechanisms leading to cancer [1] . Studies on the pathogenesis of retrovirus induced malignancies have also contributed to our understanding of the cells that give origin to cancer and the role played by stem and progenitor cells in these processes [2] . The “cancer stem cell” ( CSC ) hypothesis postulates that cancer is initiated and sustained by adult stem cells [3]–[4] . A growing body of experimental evidence is supporting the presence of CSCs in haematological malignancies and in some solid tumours . However , the presence and significance of CSCs is object of considerable debate particularly in slow turnover organs such as the lungs [5]–[7] . Identifying the cells that give origin to cancer is critical both to understand the basic carcinogenetic processes but also to devise appropriate therapeutic strategies . Most retroviruses induce transformation of hematopoietic cells but there are a few notable exceptions causing sarcomas , nephroblastomas , mammary carcinomas , nasal and lung adenocarcinomas in a variety of animal species [8] . Ovine pulmonary adenocarcinoma ( OPA ) is a naturally occurring ( and experimentally inducible ) lung cancer of sheep caused by a retrovirus known as Jaagsiekte sheep retrovirus ( JSRV ) [9]–[11] . OPA is a common disease of sheep in most geographical areas of the world . Interestingly , the disease shares several clinical and histological features with some forms of human lung adenocarcinomas . Therefore , OPA represents an excellent animal model with great potential to contribute significantly to our understanding of retroviral pathogenesis , lung tumorigenesis and pulmonary biology [9] , [12]–[13] . JSRV is the only oncogenic virus that causes a naturally occurring lung adenocarcinoma . Interestingly , in contrast to the overwhelming majority of oncogenic retroviruses , JSRV is a replication-competent virus that possesses a structural protein ( the viral envelope , Env ) that acts as a dominant oncoprotein [14]–[16] . Expression of the JSRV Env is sufficient to induce cell transformation in vitro in a variety of cell lines [13]–[15] , [17]–[22] and importantly in vivo in both experimental mice models and in lambs [23]–[24] . Thus , productive virus infection and cell transformation are mutually dependent in OPA and this creates an “evolutionary dilemma” as , at face value , abundant viral replication is entirely dependent on tumor development in the host . The JSRV Env is believed to induce cell transformation via the activation of a variety of signal transduction pathways including the PI-3K/Akt and Ras-MEK-MAPK [13] , [20] , [22] , [25]–[27] . Experimentally , intratracheal inoculation of concentrated JSRV viral particles in young lambs induces OPA in the overwhelming majority of animals with a very short incubation period ( varying from a few weeks to a few months ) [28]–[29] . There is a clear age-dependent susceptibility to experimentally induced OPA in lambs while it is not possible ( or extremely difficult ) to reproduce the disease in adult sheep [29] . These data suggest that there is a different availability of the target cells of JSRV transformation in animals of a different age . The age-susceptibility to OPA induction does not appear to be related to expression of the receptor in target cells or to a differential immune response towards the virus . Indeed , the cellular receptor for the virus ( Hyaluronidase-2 , Hyal-2 ) is ubiquitously expressed [16] , [29] and this virus can infect several cell types in vitro and in vivo [30]–[33] . In addition , JSRV naturally or experimentally-infected animals do not mount a significant immune response , likely as a result of tolerance induced by expression of JSRV-related endogenous retroviruses ( enJSRVs ) which are present in the genome of all domestic and wild sheep [34]–[37] . In OPA affected sheep , abundant expression of JSRV proteins are confined to the tumor cells although viral RNA and DNA can be detected by sensitive PCR assays in a variety of cells of the lymphoreticular system [30]–[31] , [38] . In sheep naturally infected with JSRV and with no neoplastic lesions , JSRV can be detected only in lymphoid tissues [39] . OPA tumours , similar to some human lung adenocarcinomas , are formed by secretory cells of the distal pulmonary tract; predominantly alveolar type 2 pneumocytes and less commonly the non-ciliated bronchial cells of the terminal bronchioli ( Clara cells; see note at the end of the text on the usage of this term ) [40]–[42] . Interestingly , a putative bronchioalveolar stem cell ( BASC ) has been identified in mice lungs although its presence in other species , including humans , has not been established with certainty [43] . It has been proposed that BASCs have the capacity to originate both Clara cells and type 2 pneumocytes and to be the cell origin of lung adenocarcinoma in mice in response to oncogenic K-ras [43] . However the significance of BASCs in physiological and pathological processes and the origin of lung adenocarcinoma are under debate [44]–[45] . In order to identify the target cells of JSRV infection and transformation we performed a series of in vivo studies in experimentally infected lambs and adult sheep . Furthermore , we derived a JSRV-based vector in order to assess the ability of this virus to infect non-dividing cells in vitro . In this study we identified the cells target of JSRV infection and transformation and provide important insights into lung biology , pulmonary carcinogenesis and retroviral pathogenesis .
All experimental procedures carried out in this study are included in Project Licence 60/3905 approved by the Home Office of the United Kingdom in accordance to the “animals ( scientific procedures ) act 1986” . Experiments carried out at the Istituto G . Caporale were also detailed in protocol number 3315 approved by the Italian Ministry of Health ( Ministero della Salute ) in accordance with Council Directive 86/609/EEC of the European Union . Viral stocks used in all these experiments were produced in rat 208F . JSRV21 cells as already described [46] . Briefly , 208F . JSRV21 derive from 208F cells [47] stably transfected with a plasmid expressing the JSRV21 infectious molecular clone [11] . 208F . JSRV21 cells were plated at 80% confluence and supernatants were collected after 24 , 48 and 72 h . Virus was concentrated by ultracentrifugation [300×] as previously described [11] and resuspended in 1×TNE buffer ( 100mM NaCl , 10 mM Tris , 1 mM EDTA ) . The infectious titer for JSRV cannot be easily calculated in vitro , because of the lack of a convenient tissue culture system for this virus . In order to infect animals with the same amount of JSRV , pellets from various virus preparations were pooled into a single stock , divided into 1 ml aliquots and stored at −80°C until use . In all the experiments described below , each animal received the same amount of virus stock . In a related study , the same JSRV preparation used here , induced OPA in 4 of 4 experimentally infected lambs within 5 months after inoculation ( Caporale and Palmarini , unpublished ) . Animal studies were performed at the Istituto G . Caporale ( Teramo , Italy ) and at the University of Glasgow . Prior to experimental infections all animals were anaesthetised with sodium pentobarbital anesthesia , and all efforts were made to minimize suffering . To facilitate the detection of infected cells , JSRV ( 1 ml ) was inoculated directly into the accessory bronchus of the cranial lobe of the right lung by fiber-optic bronchoscopy . Sheep used in this study were females between 3 and 5 year old of either bergamasca cross-breed ( study 1 , 2 & 4 ) or blackface breed ( study 3 ) unless otherwise indicated . Three independent studies were performed as follow . Formalin-fixed , paraffin-embedded OPA tumour samples from naturally occurring ( n = 6 ) and experimentally induced ( n = 2 ) cases were obtained from the Department of Veterinary Pathology , University of Zaragoza . All tumour samples were previously diagnosed as JSRV positive by immunohistochemistry as already described [23] , [38] , [48] . Four serial sections for each tumour were analysed by immunofluorescence as described below . Tissue sections were deparaffinised and hydrated using standard procedures . Antigen retrieval was performed using citrate buffer ( pH6 ) and pressure cooker heating . To quench endogenous peroxidase , sections were incubated in 3% H2O2 diluted in methanol or PBS for 30 minutes . Sections were incubated overnight at 4°C with the following primary antibodies: polyclonal rabbit anti pro-SP-C ( Seven Hills Bioregagents or Chemicon , dilution 1∶4000 ) , monoclonal mouse anti Ki67 ( DAKO , 1∶2000 ) , mouse monoclonal anti JSRV Env ( 1∶200 , kindly provided by Dusty Miller ) [24] , [49] . For CC10 detection we used either a polyclonal rabbit ( Proteintech ) or mouse ( Dundeecell products ) antisera generated against full length recombinant bovine CC10 . Mouse CC10 was detected using goat anti-mouse CC10 clone T18 ( Santa Cruz; 1∶200 ) . Immunofluorescence detection was performed using the following labelled secondary antibodies: goat anti-mouse Alexa488 , donkey anti-rabbit Alexa-555 , donkey anti-rabbit Alexa 488 . SP-C was detected using horseradish peroxidase ( HRP ) -conjugated donkey anti-rabbit secondary antibody ( 1∶6000 ) by tyramide signal amplification ( TSA; Perkin-Elmer Life Science Products ) while Ki67 was detected using donkey anti-mouse Alexa488 or Alexa-555 . Slides were mounted with medium containing DAPI ( Vectashield; Vector Laboratories ) . Immunohistochemistry was performed with Dako supervision system ( DAKO ) and slides were counterstained with haematoxylin . Confocal images were analysed and merged using Image-pro analyser 7 software ( MediaCybernetics ) . Histological images were captured using cell∧D software ( Olympus ) . Proliferation analysis was performed by counting SP-C/Ki67 double positive cells in the entire 10 lung sections for each animal using a Leica TCS SP2 confocal microscope . Numbers of double positive cells were normalized to the sectioned area using Image-pro analyser 7 Software . Bronchiolar cell proliferation was determined by counting the number of CC10+/Ki67+ cells in 100 terminal bronchioli for each animal . The JSRV-based vector employed in this study was derived from the JSRV21 infectious molecular clone pCMV2JS21 [11] and was termed pCJS-EfGFP-mC . Most of the JSRV gag and pol have been deleted and replaced by a cassette containing the promoter of the human elongation factor 1 α ( EF1α ) driving the enhanced green fluorescent protein ( eGFP ) . The EF1α-eGFP cassette was derived from pDRIVE5-GFP-3 ( InvivoGen ) . In addition , pCJS-EfGFP-mC also contains the woodchuck hepatitis post-transcriptional regulatory element ( WPRE; before the env splice acceptor ) [50]–[51] derived from pCCLcPPTPGKEGFPLTRH1shSOD1 ( Addgene Inc . ) . In pCJS-EfGFP-mC , the JSRV env has also been deleted and replaced with the cDNA expressing the mCherry fluorescent protein , followed by two copies of the Mason-Pfizer constitutive transport element ( CTE ) [52]–[53] . The packaging plasmid pCMVGPP-MX-4CTE expresses the JSRV Gag , Pro and Pol genes and derives from plasmid pGPP-MX by the addition of 3 additional CTE copies . pGPP-MX has been already described [23] . pCMV-SX2 . JS-env expresses the JSRV Env under the control of the CMV immediate early promoter and was derived from the pSX2 . Jenv ( a gift by Dusty Miller ) [33] , [54] . pCDNA3-HA-Sam68 is an expression plasmid for the RNA binding protein Sam68 and was a gift from David Shalloway [55] . Plasmids pCSGW-GFP ( HIV-based vector ) , p8 . 2 and pMD . G have been described previously [56] . 293T cells and sheep choroid plexus ( SCP ) cells were grown in Dulbecco's modified Eagle's medium and Iscove's modified Dulbecco's medium respectively supplemented with 10% fetal bovine serum at 37°C , with 5% CO2 and 95% humidity . Particles of a JSRV-based viral vector ( JS-EeGFP-mCherry ) were produced by co-transfecting 293T cells with pCJS-EfGFP-mC , pCMVGPP-MX-4CTE , pCMV-SX2 . JS-env and pCDNA3-HA-Sam68 plasmids essentially as described previously [23] . Viral particles were collected from supernatants of transfected cells , 24 and 48 h post-transfection , filtered through 0 . 45 µm filters ( Millipore ) and concentrated [200×] by ultracentrifugation as described previously [23] . A lentiviral vector ( HIV-GFP ) was used as control and prepared exactly as above by co-transfecting 293T cells with pCSGW-GFP , p8 . 2 and pMD . G . Target cells synchronization was established by culturing SCP cells in the presence of 0 . 2% fetal bovine serum ( FBS ) for 72 h . Synchronized SCP cells were then seeded at 5×104 cells/well in 6 well plates and treated for 25 h with 5 µg aphidicolin ( Sigma ) . Target cells were infected with serial dilutions of the JSRV or HIV-based vector in presence of polybrene [57] , [58] . Transduction controls included infection with heat-treated vector preparations ( 65°C/30′ ) . 12 h post-infection , cells were washed three times with phosphate-buffered saline and incubated for further 48 h in the presence or absence of aphidicolin . Viral titers were expressed as fluorescence forming foci/ml and were determined by counting foci of GFP positive cells 48 h post-infection . Cellular DNA content was determined by staining cells with 7-Aminoactinomycin D ( 7AAD , Invitrogen ) and measuring fluorescence in a Beckman Coulter flow cytometer . SCP cells were harvested by trypsinization and incubated for 1 h with 25 µg/ml 7AAD , 0 . 03% saponin ( Sigma ) and 1% BSA ( Sigma ) . Cells were then transferred in 500 µl of 1×PBS and the proportion of cells in G0/G1 , S and G2/M phases was estimated using expo32 software ( Beckman Coulter ) and counting 20000 events .
Ultrastructural , histological and immunophenotyping studies have shown that OPA tumours , similarly to some forms of human adenocarcinomas , are formed by type 2 pneumocytes and to a lesser extent by Clara cells [40] , [42] , [59]–[62] . No data are available in the literature on whether JSRV is expressed in both these cell types in the OPA tumours . Here , we analysed by immunofluorescence and confocal microscopy serial tumor sections collected from six sheep with late stages of naturally occurring OPA and two lambs with experimentally induced disease , in order to characterize both the phenotype of the cells forming the neoplasm and viral expression . Type 2 pneumocytes and Clara cells can be easily identified by the expression of surfactant protein-C ( SP-C ) and the Clara cell 10 protein ( CC10 ) respectively [63]–[64] . As expected , our confocal microscopy analysis revealed that all the neoplastic foci were composed mainly by SP-C+ cells ( Fig . 1 ) . In all cases the SP-C+ cells co-expressed the JSRV Env that was localized mainly at the apical surface of the cell ( Fig . 1A–C ) . Despite multiple optical serial section ( z stacks images ) were analysed for each section , we found that the majority of tumor lesions were formed by cells that did not express CC10 ( Fig . 1D ) . Areas with CC10+ cells were detected in 2 of the 6 natural OPA tumours analyzed . However , in both of these cases CC10+ positive cells did not show clear expression of the JSRV Env ( Fig . 1E–F ) . Experimentally , OPA can be easily induced in lambs but not in adults [28]–[29] , [65] . The incubation period of experimentally induced OPA is directly related to the age of the infected animals [29] . These data can be explained by hypothesizing a differential abundance of the cell targets for viral infection in lambs compared to adult sheep . Alternatively , the target cells for JSRV infection may be present both in lambs and in adults but only in the former , infection is able to progress to neoplastic transformation . In order to begin to address this issue we experimentally infected four newborn lambs and four adult sheep with JSRV and analysed virus-infected cells 10 days post-infection . Virus was inoculated directly in the accessory bronchus via bronchoscopy in order to facilitate subsequent detection ( Fig . 2A ) . Animals were euthanized 10 days post-infection and lung samples collected from either 8 ( in lambs ) or 16 ( in adult sheep ) regions of the cranial lobe of the lungs to maximise the chances of detecting a small number of virus infected cells and in order to compensate the differences in size between the lambs and adult lungs . We detected JSRV infected cells by immunohistochemistry using monoclonal antibodies against the viral Env [24] , [49] . We were not able to detect any JSRV-infected cells in all the sections derived from the adult sheep used in this experiment ( Fig . 2B–C ) . In contrast , all sections analyzed from each lamb showed JSRV-infected cells ( Fig . 2B , D–E ) . On average , in each lamb we detected 32 clusters of JSRV infected cells ranging in size from 1 to 36 cells ( mean 4 . 9±6 . 5 ) with some of them clearly displaying a neoplastic phenotype . Overall these data strongly suggest that the age related susceptibility to OPA is due to the ability of JSRV to infect cells that are much more abundant in the lungs of lambs compared to adult sheep . We then characterized the phenotype of viral infected cells in the lungs of experimentally infected lambs . We analyzed by immunofluorescence and confocal microscopy lung sections incubated with both antibodies towards SP-C or CC10 and the JSRV Env . In all cases , JSRV Env+ cells were also SP-C+ ( Fig . 2F , G ) . We were not able to detect any JSRV Env+ cell that was also CC10+ . Some early neoplastic lesions were observed in the respiratory bronchioli but in these cases they were always CC10 negative ( Fig . 2H–I ) . Overall , the data obtained in experimentally infected lambs at the early stages of viral infection are in accordance with the observations made in naturally occurring OPA cases and indicate that cells of the type 2 pneumocytes lineage are infected and transformed by JSRV . So far , our results showed that lambs are more susceptible to experimentally induced OPA due to the ability of the virus to infect type 2 pneumocytes in lambs but not in adults . Obviously , mature type 2 pneumocytes are present abundantly both in lambs and adults . Therefore , we reasoned that JSRV was able to infect a sub-population of SP-C+ that was abundantly present in lambs but not in adult sheep . The normal developed lung is a relatively quiescent organ , with low levels of cell division in the bronchioalveolar epithelium [66] . For a variety of mammals , lungs are not yet mature at birth but continue to develop during a period ( “alveolar” stage ) where the number of alveoli increases dramatically [67]–[68] . Thus , we hypothesised that JSRV infected lung alveolar proliferating cells instead of post-mitotic type 2 pneumocytes . In order to test this hypothesis , we first analysed by immunofluorescence the mitotic status of type 2 pneumocytes and Clara cells in lambs and adults sheep lungs using antibodies towards the proliferation marker Ki67 [69] in conjunction with either antisera towards SP-C or CC10 ( Fig . 3 ) . We found that proliferating type 2 pneumocytes ( SP-C+/Ki67+ ) , addressed here as lung alveolar proliferating cells ( LAPCs ) , were up to 50 times more abundant in newborn lambs compared to adult sheep ( p<0 . 001 ) ( Fig . 3A–B ) . Also proliferating Clara cell ( CC10+/Ki67+ ) in the terminal bronchioli were more abundant in lambs compared to adult sheep . We detected 94 . 5±39 CC10+/Ki67+ per 100 terminal bronchioli in lambs while there were only 5 . 5±2 . 1 CC10+/Ki67+ per 100 terminal bronchioli in adult sheep ( p = 0 . 004 ) ( Fig . 3C–D ) . A subset of SP-C+/CC10+ putative pulmonary stem cells ( known as bronchioalveolar stem cells or BASCs ) was identified at the bronchioalveolar junction in mice [43] . We analysed the localization of the proliferating Clara cells in the terminal bronchioli of lambs and sheep and found that they were not localised in a specific area of the terminal bronchioli but randomly distributed . In addition , we could not detect SP-C+/CC-10+ double-positive cells by confocal microscopy in either lambs or adult sheep , while we were able to identify cells with this phenotype in mice ( Fig . S1 ) . So far our data suggested that the presence of LAPCs in lambs is the main factor determining the susceptibility of young animals to JSRV infection as opposed to the resistance observed by adult sheep . Indeed , in the adult lungs , the proliferation rate of the respiratory epithelium is very low [68] . However , the lung has a significant reparative capability and after an injury the LAPC proliferate and play an important role in the tissue regenerative process . We therefore reasoned that we would be able to render adult sheep susceptible to experimental JSRV infection by previous induction of a mild lung injury that would stimulate LAPCs . 3MI is an organ-selective pneumotoxicant that affects specifically type I pneumocytes and bronchiolar epithelial ( Clara ) cells and it is especially effective in ruminants [69] , [70] . Here , to assess the ability of 3MI to induce lung injury and repair we exposed two sheep to this pneumotoxicant and we then assessed lung injury after 48 hours . Histological examination showed diffuse pulmonary edema with scattered hemorrhagic foci ( Fig . 4A–B ) . Next , we assessed the proliferation status of type 2 pneumocytes and Clara cells by verifying co-expression of SP-C or CC10 with the proliferating marker Ki67 by immunofluorescence as described above ( Fig . 4C–F ) . The number of SP-C+/Ki67+ cells was 90 fold higher in sheep after lung injury as opposed to normal control sheep ( p<0 . 001 ) ( Fig . 4H ) . The examination of the terminal bronchioli in sheep after 3MI administration revealed that almost 100% of terminal bronchioli contained CC10+/Ki67+ ( Fig . 4G ) . The total number of CC10+/Ki67+ cells was more than 100 fold higher in adult sheep after lung injury compared to healthy controls ( p = 0 . 009 ) ( Fig . 4H ) . Also in adult sheep after lung injury we were not able to identify any SP-C+/CC10+ double-positive cells ( data not shown ) . Overall , the data presented above indicate that the number of LAPCs , that we identified as target cells of JSRV infection , increase dramatically after mild lung injury . In order to determine whether lung injury may render adult sheep susceptible to JSRV infection , we treated five sheep with 3MI and after 48 h we infected them with JSRV ( Group I ) . Five additional sheep were infected with JSRV without pre-treatment with 3MI ( Group II ) . 10 days after infection animals were euthanized ( Fig . 5A ) . As expected , post-mortem examination revealed no signs of lesions attributed to lung injury . In each animal , the presence of JSRV infection was assessed in 15 sections collected from the cranial lobe by immunohistochemistry . JSRV Env expression was only detected in lung cells of animals that were infected after treatment with 3MI ( Fig . 5B , D–F ) . On average , 10 clusters of JSRV Env+ cells ( ranging from 1 to 80 cells ) were detected in each animal while no JSRV infected cell was detected in those animals that were infected without 3MI pre-treatment ( Fig . 5C ) . By immunofluorescence and confocal microscopy we found that all JSRV infected cells were SP-C positive ( Fig . 6A–C ) . None of the JSRV Env+ cells were CC10+ ( Fig . 6D–F ) , despite the high number of proliferating Clara cells induced by 3MI and the presence of numerous infected cells localized in the terminal bronchioli . Our data have shown that JSRV infects LAPCs but not the overwhelming majority of type 2 pneumocytes which divide very slowly . These data could be explained mechanistically by the fact that the majority of retroviruses , with the exception of lentiviruses [71] , infect more efficiently cells that are in mitosis [72]–[73] . The proliferation rate of type 2 pneumocytes is very low in adults under normal conditions . On the other hand the higher proliferative rate of LAPCs during post-natal development or tissue repair in the adult would facilitate JSRV infection . Experiments with JSRV in vitro are hindered by the lack of a convenient tissue culture system for the propagation of this virus [32] . Therefore , we constructed a convenient JSRV-derived viral vector ( JS-EeGFP-mCherry ) in order to easily quantify JSRV infection in proliferating and non-proliferating cells . JS-eGFP-mCherry was derived by transiently transfecting 293T cells with ( i ) a packaging plasmid ( pGPP-MX-4CTE ) devoid of the JSRV packaging signal ( Ψ ) and expressing the viral Gag , Pro and Pol; ( ii ) a plasmid providing the JSRV Env in trans ( pC-ML-JSenv , also devoided of Ψ ) , and ( iii ) the packaged JSRV vector ( pCJS-EFGFP-MC ) that upon infection and integration expresses eGFP under the control of an internal promoter ( Fig . 7A ) . JS-eGFP-mCherry viral particles were then used to infect synchronized SCP cells in the presence or absence of a drug that , at the concentration used in this study , arrests cells in the G1 phase ( aphidicolin ) ( Fig . 7B ) . Consistently , JS-eGFP-mCherry was able to transduce actively dividing SCP cells approximately 200 times more efficiently ( p = 0 . 002 ) than the same cells where mitosis was arrested with aphidicolin while only minor differences between treated and untreated cells were observed with the lentivirus vector HIV-GFP ( Fig . 7C ) .
In this study we have investigated the pathogenesis of a unique virus-induced lung adenocarcinoma and obtained data that have a broad significance in pulmonary biology , carcinogenesis and retroviral pathogenesis . Most adenocarcinomas in humans display cells expressing type 2 pneumocytes or Clara cell markers but it is not completely clear whether the neoplasm arises from a stem cell that is able to differentiate into both cell types , or from a committed progenitor or from the fully differentiated cell compartments [74] . In this study , we identified the target cells of JSRV infection and transformation in vivo as proliferating cells of the type 2 pneumocytes lineage ( SP-C+/Ki67+ , LAPC ) . In addition , we showed that the age-related susceptibility to experimental OPA induction is directly related to the abundance of LAPCs . Importantly , induction of mild injury to the respiratory epithelium increased dramatically the number of LAPCs in adult sheep and rendered these animals susceptible to JSRV infection and transformation . We have not found evidence that CC10+/Ki67+ cells are infected and transformed by JSRV . Furthermore , we found that the CC10+ cells that are found in a proportion of late stages OPA tumours are not expressing JSRV proteins and may therefore not be true tumour cells , at least in the cases we examined . Our data provide important consideration for pulmonary biology and carcinogenesis . We infer from our study that at least in sheep , type 2 pneumocytes and Clara cells have two distinct populations of proliferating progenitor cells committed to the alveolar and the bronchiolar lineages . From this study , we cannot determine whether the LAPCs are progenitor committed solely to type 2 or type 1 pneumocytes . We showed that lung adenocarcinoma can originate from an alveolar proliferating cell of the alveolar lineage , rather than from a bronchioalveolar stem cell postulated to originate both type 2 pneumocytes and Clara cells . Studies in mice have identified a population of putative stem cells that are both SP-C+ and CC10+ ( bronchioalveolar stem cells , BASCs ) located at the bronchioalveolar duct junction [43] . Based on in vitro analysis , BASCs were hypothesised to give rise to Clara cells , alveolar type 2 cells and be the cell originating lung adenocarcinoma [43] . On the other hand , studies using genetic lineage-labelling experiments in mice , supported a model where bronchioli and alveoli are maintained and repaired distinctively by Clara cells and LAPCs respectively [44] , [75] . The presence of BASCs in humans has not been confirmed and in general the biological relevance of BASCs is object of debate [44]–[45] . In our study , by confocal microscopy , we have not been able to detect SP-C+/CC10+ in sheep while we were able to detect cells with this phenotype in mice ( Fig . S1 ) . We cannot rule out the presence of a rare bronchioalveolar stem cell ( SP-C+/CC10+ ) able to differentiate in both type 2 pneumocytes and Clara cell progenitors in sheep . We also cannot rule out the presence in sheep of phenotypically uncharacterized pulmonary stem cells . However , if these cells exist in the sheep , they are very rare and unlike LAPCs they do not appear to play a major role in OPA . Interestingly , from the anatomical and histological point of view the human lungs are more comparable to the sheep lungs as opposed to the mice lungs [76]–[77] . We showed with experiments in vitro that JSRV , similarly to other retroviruses , infects preferentially cells in active mitosis . These experiments provide a mechanistic explanation to the observation that JSRV infects readily LAPCs but not mature type 2 pneumocytes . As mentioned before , JSRV is a unique oncogenic virus as it possesses the viral Env ( a structural protein ) that behaves as a functional dominant oncoprotein both in vitro and in vivo . In general , viral oncoproteins are non structural proteins whose expression is not linked to productive infection . It would be detrimental from an evolutionary point of view of the virus , to have productive viral infection and carcinogenesis as strictly mutually dependent events ( viral replication would in this case lead to the death of the infected host ) . Onset of lung adenocarcinoma in JSRV-infected animals could therefore be viewed as either “accidental” ( similarly to other retrovirus-induced tumors ) or “essential” in order to allow virus spread among susceptible hosts . Although these two alternative hypotheses are not necessarily mutually exclusive , the data obtained in this study and accumulated over the years on JSRV/OPA , strongly suggest that tumor induction plays an important part in the evolutionary strategies used by the virus to persist in the sheep population . In previous studies we have shown that development of OPA in the field occurs only in a minority of the JSRV-infected sheep [39] . On the other hand , animals with OPA produce lung secretions containing abundant amounts of infectious JSRV particles that pour freely from the nostrils of the affected sheep [41] , [78]–[79] . The data from this paper strongly suggests that clinical OPA develops in natural conditions as a result of viral infection only when LAPCs are available to the virus: in young lambs during post-natal development or in the presence of an injury to the bronchioalveolar epithelium . Importantly , as mentioned in the introduction , JSRV proteins are detected readily only in the tumour cells of OPA affected animals ( and in the LAPCs as shown in this study ) [38] although low levels of virus infection and protein expression are detectable in cells of the lymphoreticular system of animals with or without clinical OPA . We and others have shown that the JSRV LTRs are the main determinants regulating the tight cell-specific expression pattern displayed by this virus . The JSRV LTRs contains lung-specific enhancer binding motifs that are preferentially active in cell lines derived from transformed type 2 pneumocytes [80]–[83] . In addition , in transgenic mice , reporter gene expression driven by the JSRV LTR has been detected specifically in type 2 pneumocytes [84] . Thus , JSRV-host equilibrium has been reached by a combination of factors . JSRV has evolved a structural protein that is a powerful oncoprotein but only when expressed at high levels in the LAPCs , which are relatively rare cells in the adult healthy sheep . Therefore , JSRV has a limited window of opportunity to infect the target cells of the host that allow high level of viral expression ( and that can be consequently transformed ) . At the same time , onset of lung adenocarcinoma in a minority of the infected animals allows an amplification of the cells that can produce infectious virus and therefore it is a likely evolutionary mechanism that helps JSRV to persist in the population . It is important to note that in natural conditions , sheep with OPA present consistently a variety of other parasitic , bacterial or viral infections [9] . Classically , these infections were considered as “secondary” to JSRV infection . We suggest instead that in the adult , the induction of an injury to the respiratory epithelium by various pathogens substantially increases the number of LAPCs and renders adult sheep susceptible to JSRV-induced transformation , similarly to what we have shown experimentally in this study with the pneumotoxicant 3MI . Thus , inflammation induced by different pathogens is the “primary” event for OPA induction . It is feasible that in animals already infected with JSRV the virus present in lymphoreticular cells is able to spread to injured tissues where it can infect and transform alveolar progenitor cells actively involved in repairing the epithelium . In conclusion , this work provided unique insights into pulmonary physiology , lung cancer , and retrovirus pathogenesis and is another telling example where viruses have helped us to understand fundamental aspects of host biology . | The identification of cells that give origin to cancer is critical in order to design effective therapeutic strategies . To this end , the early stages of cancer are the most informative but they are seldom associated with clinical symptoms and therefore pass unnoticed in human patients . Studies on animal tumors are invaluable to this research area . In this study , we determined the cells originating an infectious lung cancer of sheep ( ovine pulmonary adenocarcinoma , OPA ) that is similar to some forms of human pulmonary adenocarcinoma . OPA is caused by a virus known as Jaagsiekte sheep retrovirus ( JSRV ) . We show that OPA is caused by JSRV infection of proliferating type 2 pneumocytes ( lung alveolar proliferating cells , LAPCs ) . We show that young animals possess abundant LAPCs and are highly susceptible to JSRV infection while healthy adult sheep exhibit a relatively low number of LAPCs and are resistant to OPA induction . However , adult sheep were susceptible to JSRV infection when the presence of LAPCs was stimulated by induction of a mild injury to the respiratory epithelium . Thus , our study identifies the cells originating lung adenocarcinoma in OPA and shows that inflammation to the respiratory epithelium can predispose to retrovirus infection and cancer . | [
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] | 2011 | Lung Adenocarcinoma Originates from Retrovirus Infection of Proliferating Type 2 Pneumocytes during Pulmonary Post-Natal Development or Tissue Repair |
A variety of obstacles including bureaucracy and lack of resources have interfered with timely detection and reporting of dengue cases in many endemic countries . Surveillance efforts have turned to modern data sources , such as Internet search queries , which have been shown to be effective for monitoring influenza-like illnesses . However , few have evaluated the utility of web search query data for other diseases , especially those of high morbidity and mortality or where a vaccine may not exist . In this study , we aimed to assess whether web search queries are a viable data source for the early detection and monitoring of dengue epidemics . Bolivia , Brazil , India , Indonesia and Singapore were chosen for analysis based on available data and adequate search volume . For each country , a univariate linear model was then built by fitting a time series of the fraction of Google search query volume for specific dengue-related queries from that country against a time series of official dengue case counts for a time-frame within 2003–2010 . The specific combination of queries used was chosen to maximize model fit . Spurious spikes in the data were also removed prior to model fitting . The final models , fit using a training subset of the data , were cross-validated against both the overall dataset and a holdout subset of the data . All models were found to fit the data quite well , with validation correlations ranging from 0 . 82 to 0 . 99 . Web search query data were found to be capable of tracking dengue activity in Bolivia , Brazil , India , Indonesia and Singapore . Whereas traditional dengue data from official sources are often not available until after some substantial delay , web search query data are available in near real-time . These data represent valuable complement to assist with traditional dengue surveillance .
With an estimated 500 million people infected each year [1] , dengue ranks as one of the most significant mosquito-borne viral human diseases , and one of the most rapidly emerging vector-borne diseases [2] , [3] . Considered to be endemic in over 100 countries , mostly in South-East Asia , the Americas and Western Pacific islands [3] , recent estimates according to the Pediatric Dengue Vaccine Initiative put the population at risk , at 3 . 6 billion , or 55% of the world population . Most national surveillance systems for dengue in endemic countries currently depend on passive or sentinel site surveillance of hospitalizations with some countries also monitoring outpatient clinics . However , weaknesses in these systems including non-streamlined bureaucratic structuring , politics and lack of funding for skilled personnel and equipment at local level laboratories have been cited as interfering with timely reporting and confirmation of cases [1] , [4] . Alternative approaches to surveillance have turned to data outside of the virological or clinical domains with the hope of capturing health-seeking behavior at the earlier stages of disease progression , as well as capturing the population of the ill who do not seek medical care formally . Examples of these data include telephone triage calls [5] , sales of over-the-counter drugs [6] , school/work absenteeism [7] , and online activity [8]–[12] . These data could complement traditional surveillance by potentially facilitating earlier detection , though results with respect to correlation and timeliness have been variable [13] . Even if the signals in one data source are no earlier than in another , there is benefit in using data that provide access to information on a more real-time or near real-time basis . The value of "predicting the present" for situations where data for the present may theoretically be available but not be accessible until the future is discussed in [14] . These novel approaches have so far for the most part been narrowly focused and validated on influenza-like and gastrointestinal illness . One example of such an effort is Google Flu Trends ( http://www . google . org/flutrends/ ) . The system mines Google search query data to estimate influenza activity in near real-time , developed by matching trends in queries for flu-related search terms to seasonal trends in the Centers for Disease Control and Prevention's ( CDC ) data for sentinel physician visits for influenza-like illnesses in the United States [9] . While the system has been successfully expanded to other nations to provide a near global picture of influenza activity , there is clearly value in applying these efforts to other pathogens where morbidity and mortality are more significant , where clinical outcomes are more severe or where a vaccine may not exist . Though one study has provided evidence for this broader potential application [15] , in general few have evaluated the utility of web behavior data for other diseases and in non-English speaking countries . In this paper , we describe the extension of the Google Flu Trends methodology to dengue surveillance . We provide initial results for Bolivia , Brazil , India , Indonesia , and Singapore and assess whether web search query data is a viable data source for the early detection and monitoring of dengue epidemics .
Our objective was to build models that are able to estimate a disease activity indicator for a significant high-burden disease by using data on Google search patterns . In building these models , time series of the fraction of Google search query volume for an appropriate disease from a particular country ( both chosen by specific inclusion/exclusion criteria ) were fit to a time series of case counts from official data sources . Our model fitting and query selection approach closely follows the precedent established by Google Flu Trends [9] . Statistical analyses were conducted using the statistical software R , version 2 . 10 . 1 ( Vienna , Austria ) . Several factors had to be taken into consideration in selecting a specific disease and country around which a web query based surveillance tool would be developed . Such a tool would be most useful and successful for a high prevalence disease , in that the benefit of prevented cases gained by early detection would be maximized , but would work only where there is sufficient web searching behavior for information about the disease . However , concurrently , the disease should not be prone to “panic-induced searching” that would lead to spurious spikes in the data for our purposes . Our list of candidates was narrowed down further by the fact that model building would require a time series of official case counts against which web search query data could be fit and validated . Therefore , a further requirement was the availability of a corresponding official source dataset of case counts of at least a monthly but ideally weekly temporal resolution , dated 2003 or later ( the time frame for which Google query data are available ) , and of at least three years in length . A final consideration was that the disease must exhibit fluctuations , via either a seasonal pattern or occasional upsurges , in order to better assess the match in trends in search data . Initial disease and country candidates were identified based on considerations of annual national data reported by the World Health Organization ( WHO ) provided through its Global Health Atlas platform ( http://apps . who . int/globalatlas/ ) to gauge the burden of a disease , and Google search query volume for queries about the disease in the country of interest to determine whether there was sufficient search interest . Attempts to find official case count data involved searching through various official websites including those of national Ministries of Health and the WHO , as well as scientific publications . We determined that endemic diseases were particularly suitable candidates because of their high burden , lesser susceptibility to panic-induced searching , and greater likelihood of available official data as they are often monitored by a national surveillance system . Ultimately , taking into consideration the above criteria , we decided to focus on dengue in Bolivia , Brazil , India , Indonesia , and Singapore . We fit a univariate linear model to the weekly or monthly official case count time series for each country independently:where O is the official dengue case count , S is the dengue-related Google search query fraction , β0 is the intercept , β1 is the multiplicative coefficient , and ε is the error term . We split the official case count time series O into two sets: a training set Ot and a holdout set Oh of a complete outbreak season that spanned one year but not necessarily a calendar year . Oh was used only for testing the final model . For Oh , we generally selected the last full dengue season that was available in the time series; Singapore was the one exception because there had not been a significant outbreak that would be valuable to track from the point of view of the public health community since its 2007 season . Queries to include in the set of dengue-related Google search queries were selected separately for each country . This selection process started with first ranking individual search queries ( from the total pool of all queries ) according to their correlation with Ot . Starting with the most correlated query , and discarding queries that were obviously unrelated to dengue , each query was sequentially added to the variable S . With each new addition , if the fit of the new model with Ot improved , the query was kept in the set of queries , otherwise , the query was removed from the model and the query selection process was stopped at that point . We did not consider it necessary to utilize a cross-validation methodology during query selection given the small number of candidate queries that correlated well with Ot , and given that we were estimating just two parameters , the intercept and the multiplicative coefficient . Therefore , model overfitting was not a major concern . Spikes in the time series indicate an increase in interest in dengue , but it is important to determine whether they are “true spikes” representative of the burden of illness in the population or “spurious spikes” not reflective of population health impact . For example , spurious spikes may be caused by panic-induced searching when media attention about a particular outbreak triggers amplification of search activity that is disproportionate to the actual extent of the outbreak . These spurious spikes occur rarely but can be distinguished from true spikes when the rate of growth of the values in the time series S exceeds the normal rate of spread of the disease as determined by the basic reproduction number R0 . In the absence of precise data about R0 , we used a statistical approach to detect spurious spikes . Given a version of S based on daily data and a candidate spike point p that belongs to S , we computed the daily mean value and standard deviation using the previous four weeks' of daily data , and if p was found to exceed five standard deviations from the mean , we considered it to be a spike that was not driven by normal transmission of the disease . In such a case , we replaced p with a daily value imputed from the past data by simply continuing the trend of the last two weeks . We continued imputing subsequent points until the candidate points fell below the five standard deviation threshold . We chose such a high threshold to ensure that S will be modified only in extremely rare situations . Removal of spurious spikes was performed subsequent to query selection and prior to model fitting . Lastly , the predictive performance of the final model for each country was assessed by testing each model fit to the training set Ot against the holdout set Oh as well as the overall set O .
Dengue was determined to be a suitable candidate for search query-based disease surveillance since it generates over a million Google search queries every month . We found that the models contained up to ten queries for each country when built using the query selection approach described earlier . The queries were generally directly about dengue , expressed predominantly in Spanish , Portuguese , English , Indonesian and English for Bolivia , Brazil , India , Indonesia , and Singapore respectively . Some queries showed that the user was looking for more information about the disease , while others were looking for symptoms or treatments . Some of the queries contained misspellings of the word “dengue” . A few queries were related to mosquitoes and their control . There would be significant overlap between queries from different countries if translated to the same language . Training the models using different time periods of the truth data sometimes resulted in small changes to the list of selected queries , suggesting some elasticity in the query selection process . Model-fitted “expected” epidemic curves generally matched official case counts “observed” epidemic curves quite well for all five countries in most seasons , with the exception of Bolivia in 2007 when the model over-estimated the activity in that season , and India in 2005 for which it under-estimated ( Figure 1 ) . More formally , the correlation between values predicted by models fit to the training data and the holdout set as well as the overall dataset was generally quite high , ranging from 0 . 82 to 0 . 99 ( Table 1 ) .
Although there is a trend towards modernizing surveillance of infectious diseases , dengue surveillance is still very much traditional , mostly based on passive routine reporting or sentinel site surveillance , which is a preferable active but more costly approach [4] . The current standard approaches to dengue surveillance have recognized shortcomings including low sensitivity and accuracy and lack of timeliness . Therefore , the need to take steps to improve dengue surveillance has been well acknowledged [1] , [4] , [16] , but cost and feasibility remain major obstacles . The results of this study show that in general , models built on the fraction of Google search volume for dengue-related queries were able to adequately estimate true dengue activity according to official dengue case counts reported by national ministries of health or the WHO for five selected countries for the majority of the seasons during the time-frame analyzed . To our knowledge , few have explored non-traditional clinical/laboratory settings for monitoring dengue epidemics . Our results provide evidence of the availability of a novel data source that could supplement traditional surveillance . Furthermore , a web data based approach would be a low-cost option as it is passive and would require minimal resources to run . The main added benefit in monitoring web-searching behavior is the potential for earlier detection . While notifications by doctors or laboratories to ministries of health are often delayed until there is a confirmed diagnosis [17] , it is believed that individuals , especially at earlier stages of illness , may seek health information on the Internet before or even instead of making medical visits . One study evaluating a community-based surveillance system in rural Cambodia found that 67% of cases of hemorrhagic fever were treated at home as opposed to a health facility [18] . While rural areas are less likely to be served by Internet access , in other more developed areas , the Internet could be a source of information for those who do not actively seek clinical care . These data could therefore have the potential to provide earlier signals of epidemics in the community than clinical or laboratory data . Several studies have already demonstrated that web access logs and search query data work well for tracking influenza [9]–[12] , although whether these data are actually timelier than traditional data is uncertain , with differing results depending on the study and gold standard of comparison . However , even if the signals in web query data are no timelier than in traditional laboratory/clinical surveillance data , a tool built on the presented models could still provide a time advantage in that it would provide immediate access to an indicator of dengue activity that could help illustrate the dengue situation as it is currently . This idea reflects the concept of “now-casting” as opposed to forecasting , to predict the present rather than the future [14] . Official case counts are not always made publicly available in all countries , or if they are , there is a broad spectrum in the timeliness of when these data become available , ranging from only a couple days ( as in the case of Singapore ) to as much as months , or even years ( as in case of the WHO's DengueNet system which collects data for all countries ) . This tool is not meant to serve to fill in these gaps with actual estimates of case counts , but by estimating an indicator of dengue activity that would be available in near real-time , it could serve as a stepping stone to prompt further investigation if warranted . The lack of data stems from a variety of factors , including under-reporting . Even with mandatory reporting of dengue , under-reporting is prevalent [1] , [4] , [16] . Field investigations , sero-surveys and capture-recapture methods have yielded some remarkably low estimates for the sensitivity of dengue case notification , reflecting under-reporting [17] , [19]–[21] . Reasons for under-reporting include lack of resources ( both personnel and equipment ) , motivation and leadership , in addition to misunderstandings about or unfamiliarity with case definitions , complicated reporting procedures , a tendency to report only the most severe cases , lack of reporting from the private health sector [4] , [16] and the reality that a proportion of the ill do not seek clinical care whether because they self-treat at home [18] or because their infection is asymptomatic or subclinical [21] . Unfortunately , the problem of under-reporting extends to our models as well as they were built on official data that are precisely affected by these problems . Therefore , it is not sensitivity but the ability to capture the same trends as the official data at a potentially earlier time point that is the value that a tool built on such models would be trying to capitalize . A main challenge remains that rural areas and developing nations tend to lack or have limited Internet access currently . Web-query based surveillance depends on sufficient web search volume from any country of interest in order to both generate signals and drown out noise . In fact , it was this limitation of sufficient search volume that turned out to be a significant limiting factor in our process of identifying appropriate disease/location candidates . Another limitation to be kept in mind with respect to expanding to different countries is that inter-country comparisons may be difficult due to differences in case definition for the official time series to which models were fitted . Unfortunately , because data using a consistent case definition across all countries do not exist ( to our knowledge ) , each presented country and model must be considered independently . Lack of Internet access may also be a potential explanation for the discrepancy between the fitted and actual values for the 2005 season in India . Though the gap is narrower today , there is a tremendous amount of regional variation in Internet penetration in India , a reflection of the country's economic disparity , especially between rural and urban areas [22] . The 2005 season was predominantly driven by a major outbreak that occurred in the state of West Bengal which includes the city of Kolkata , where per-capita Google searches at that time were much less than in cities like Delhi and Mumbai . Correspondingly , a model that fits aggregate national-level search data to national official case count data could underestimate true activity in regions with limited Internet usage . If state level data becomes available , future improvements to the model could include the addition of state-level adjustments . Another limitation is that not everyone who submits a dengue related search query is actually ill with dengue . Indeed , a prevailing concern in such uses of web-searching behavior data for monitoring epidemic signals is the susceptibility of these data to panic-induced searching; the announcement of a novel outbreak , especially if compounded by media sensationalism , usually leads to increased online searching activity , and while a proportion of that behavior may be spurred by legitimate personal medical concern , a larger proportion is likely driven by fear or curiosity . By training the models over multiple years of data we are able to filter for terms that might be popular at a specific point in time during one season , but not over the multiple seasons . For example , when the first wave of H1N1 swine influenza emerged in 2009 , there were large increases in search activity for “swine flu” , but this term was not included in Google Flu Trends models since it was not used significantly prior to 2009 . Additionally , dengue is probably somewhat shielded from mass panic-induced searching; being an endemic disease in the regions we have focused on , dengue is less likely to receive the same degree of attention as would happen with a novel or rare disease . This hypothesis is confirmed by our results which demonstrate that dengue-related search queries are generally not as influenced by news coverage . For example , despite more severe and newsworthy outbreaks for Bolivia in 2009 , Brazil in 2008 , Indonesia in 2004 , and Singapore in 2005 , the models were able to handle these high levels of dengue activity without any significant overestimation . The one exception occurred in 2006 in India , when news about members of the prime minister's family being hospitalized for suspected dengue caused an unusually large spike in dengue queries . However , adjusting this spike prior to model fitting as described in our methods proved to be an effective way of retaining model fit . As with Google Flu Trends , despite strong historical correlations , our system remains susceptible to false alerts that could be caused by a sudden increase in dengue-related queries [9] . Incorrect self-diagnosis is another instance where dengue related search queries may not correspond to true illness . Notably , chikungunya and dengue are particularly difficult to distinguish because they manifest with similar symptoms and share the same vectors [23] . It has been made even more difficult since late 2005 , when chikungunya re-emerged and led to a major outbreak in the Indian Ocean region , resulting in its current co-circulation with dengue in India [24] . Misdiagnosis is an obvious limitation for this tool , but it should be noted that in the case where it would be difficult for even doctors to make that distinction based on clinical symptoms alone , it is one that afflicts clinical data used in traditional surveillance of dengue as well . Therefore , misdiagnosis should be an acknowledged problem , but search query data could nonetheless be useful for evidence-based decisions , providing earlier signals on the basis of which more formal epidemiological investigation and coordination with diagnostic laboratories could be initiated . Mining Google search query data raises obvious privacy concerns and it must be ensured that policies to protect personal information are extended to the application of this tool in public health practice . The main safeguard is that such a tool only presents query volume at the aggregate level where the unit of analysis prevents any re-identification of patients . The product of this work is freely available at www . google . org/denguetrends . The presented tool is not intended to replace traditional dengue surveillance , but by taking advantage of readily available data essentially provided by millions of individuals , it could be a useful and low-cost complement . These data can help mitigate some of the many gaps that exist in the current dengue surveillance landscape . More broadly , these results also contribute to a growing pool of evidence demonstrating the capability of relatively novel sources such as web-based data to assist with public health goals . | A variety of obstacles , including bureaucracy and lack of resources , delay detection and reporting of dengue and exist in many countries where the disease is a major public health threat . Surveillance efforts have turned to modern data sources such as Internet usage data . People often seek health-related information online and it has been found that the frequency of , for example , influenza-related web searches as a whole rises as the number of people sick with influenza rises . Tools have been developed to help track influenza epidemics by finding patterns in certain web search activity . However , few have evaluated whether this approach would also be effective for other diseases , especially those that affect many people , that have severe consequences , or for which there is no vaccine . In this study , we found that aggregated , anonymized Google search query data were also capable of tracking dengue activity in Bolivia , Brazil , India , Indonesia and Singapore . Whereas traditional dengue data from official sources are often not available until after a long delay , web search query data is available for analysis within a day . Therefore , because it could potentially provide earlier warnings , these data represent a valuable complement to traditional dengue surveillance . | [
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"te... | 2011 | Using Web Search Query Data to Monitor Dengue Epidemics: A New Model for Neglected Tropical Disease Surveillance |
How social groups and organisms decide between alternative feeding sites or shelters has been extensively studied both experimentally and theoretically . One key result is the existence of a symmetry-breaking bifurcation at a critical system size , where there is a switch from evenly distributed exploitation of all options to a focussed exploitation of just one . Here we present a decision-making model in which symmetry-breaking is followed by a symmetry restoring bifurcation , whereby very large systems return to an even distribution of exploitation amongst options . The model assumes local positive feedback , coupled with a negative feedback regulating the flow toward the feeding sites . We show that the model is consistent with three different strains of the slime mold Physarum polycephalum , choosing between two feeding sites . We argue that this combination of feedbacks could allow collective foraging organisms to react flexibly in a dynamic environment .
Many social or gregarious living organisms are effective decision-makers , in the sense that they are able to select the best of several available options [1]–[9] . Extensive experimental work and mathematical modelling suggest that a basic feature underlying this phenomenon is a symmetry-breaking bifurcation . That is , there is a transition from a “homogeneous” exploitation of the resources ( all options are equally exploited ) to an “inhomogeneous” mode where a focus on a particular option is occurring after a certain critical value of a parameter , typically the number of individuals [3] , [10]–[13] . A key factor in the emergence of such patterns of exploitation is the amplification of an initial asymmetry arising through a fluctuation . For example in social insects , an individual discovering a food source will produce a signal that will be followed and reinforced by recruited individuals [14] . If the number of individuals is large enough , a slight initial imbalance of the fraction of individuals visiting one or the other source will entrain the majority of foragers to focus on a particular food source resulting in a collective decision . Such collective decision-making has been seen in predator avoidance [15] , shelter selection [16] and has even been interpreted in terms of rationality [17] , [18] . The idea of a symmetry-breaking depending on the number of individuals have also inspired other fields of research focusing on human behaviour [19]–[21] or economics [22] , [23] . In all these examples , symmetry is broken when a critical number of individuals is exceeded . While symmetry breaking is important , we also know that symmetry can be restored when the system size ( e . g . number of individuals ) becomes very large . For example , direct contacts resulting from crowding in foraging ants lead to the exploitation of two routes to food , despite the fact that only one route is chosen when there is no crowding [24] . More intricate situations can arise in , for example , ant species using two pheromones [25] or in social caterpillars Malacosoma disstria displaying behavioural polymorphism [26] , [27] . Here exploitation patterns are shown to arise in which past a first symmetry-breaking transition there is coexistence of inhomogeneous and homogeneous modes the latter becoming even the rule under certain conditions . The interplay between symmetry breaking and symmetry restoring is also a basic issue in statistical and condensed matter physics [28] , [29] and in high energy physics [30] when more than two phases of matter can coexist . In this paper , we analyse decision-making at the cellular level , on the paradigmatic case of the true slime mold Physarum polycephalum . We show that non-trivial decision patterns , including a symmetry restoring bifurcation may arise depending on the mass of the slime mold . P . polycephalum is a unicellular , multinucleate protist . Its vegetative phase is a multi-nucleate plasmodium . It is during this stage that the organism searches for food . Depending on the strains of the organism considered , the plasmodium sets out pseudopodia in all directions for a certain distance and then builds one or few extended search fronts ( Fig . 1 ) during exploration . The plasmodium is able to sense various stimuli from a distance and move toward them via chemotaxis [31] . When the plasmodium comes into contact with a food source , it completely surrounds it and resumes exploration while remaining in physical contact with the initial food source . The plasmodium can grow to cover large area ( up to 900 cm ) , and is capable of moving at relative high speed ( up to 5 cm/hr ) [32] and of building efficient transportation networks [33] . In most of these studies reported in the literature , a single strain was used to reveal the decision-making patterns of P . polycephalum . In this paper we develop a model based on [34] and [35] , along with experiments carried out on three strains of the true slime mould P . polycephalum to test our predictions and reveal the differences between these three strains in decision-making outcome . The model describes how commitment to two identical options evolves in time . We let and be the number of units within the system committed to options 1 and 2 , respectively . We further assume a pool of uncommitted units of size where is the system size . We express the build up of commitment to the options with respect to time as ( 1 ) Here is the rate per individual unit time to choose between one of the options , accounts for the feedbacks present in the decision-making and is the rate at which commitment decays . A number of authors [1] , [13] , [24] have analysed a similar model – particularly in the context of foraging in ants – under the hypothesis that rate of decision-making is constant , i . e . is replaced by a constant . This hypothesis is reasonable in the limit where the initial system size is large and the number of units committed to the options remains small . However , in many natural systems the initial mass is significantly depleted as time goes on . This is certainly the case in our current experiment on foraging by P . polycephalum where a substantial part of the initial mass ends up covering one or both the food sources . The system we study here can thus be viewed as having a “passive” negative feedback of , , whereby depletion of units reduces the rate of recruitment . We turn next to the positive feedback functions . Several possible forms have been proposed for these ( see [35] and [36] for recent reviews ) . One of the dominant ideas has been that an individual bases its decision on previous decisions made by others , i . e . , on the numbers of units having already committed the different options . For example , [13] use ( 2a ) while , [37] argue , on the basis of Bayesian estimation , that the form ( 2b ) gives a form of optimal decision-making , being a sensitivity parameter . Both the above forms assume that information about commitment to both of the options is available to the decision-making units . An alternative view is the quorum model [34] . Here one assumes that the probability of accepting an option is simply an increasing function of the number of units that have already accepted this particular option independent of the number of units choosing the other option . In this paper we model this phenomenon using ( 2c ) This form follows [34] , albeit without an additional spontaneous probability of adopting an option . A similar form has also been derived by [36] within a Bayesian framework . They found that ( 2d ) provided a good match to decisions made by zebrafish . As it turns out the use of either ( 2c ) or ( 2d ) is not essential in what follows . Both these functions have the same sigmoidal form , which produces the sequence of bifurcations we now describe . In the case of P . polycephalum feedback is in the form of the growth of tubes as a result of protoplasmic flow . There is evidence that there is an upper limit of tube thickness in real organisms [38] . The parameter then stands for the threshold beyond which this feedback becomes effective or , alternatively the threshold flow for tube construction . Nakagaki et al . [39] consider the sigmoidal function of the form to account for these effects but , again , the results reported below are not affected qualitatively by the choice of exponents greater than 2 . Summarising , model ( 1 ) for two equal food sources can be written as ( 3 ) It captures two essential properties of a class of decision-making systems of which Physarum polycephalum constitutes a prototypical example . First , decisions are local in the sense that each of the two positive feedback functions depends only on the fraction of system's mass attracted to the particular option . In particular , in P . polycephalum tubes are being built to food sources on the basis of only local information . Second , for any given value of initial mass the portion of the system not yet committed to the options is decreasing as , are increasing . In order to investigate the role of randomness in the model and to fit it to data , we also implemented a Monte Carlo version of this model . See Materials and Methods for details .
Fig . 2 shows the bifurcation diagram of the steady-state solutions of eqs . ( 3 ) , i . e . , how the steady-sate level of commitment to an option changes for initial system sizes . Three bifurcation points can be identified . Before the first bifurcation there is one stable steady state corresponding to no decision ( trivial steady state ) . After the first bifurcation point ( see Material and Methods , eq . ( 6 ) ) the system has three stable states , one corresponding to no decision and the other two corresponding to the exclusive exploitation of one or the other of the two options ( semi-trivial steady state ) . In terms of the behavior of Physarum polycephalum , the trivial steady state describes a situation where the plasmodium did not find food or never moved from the starting point . The semi-trivial steady state describes the situation where the plasmodium exploits just one option . For larger initial mass values a second bifurcation occurs and unstable homogeneous solutions appear . In terms of the decision-making of Physarum polycephalum the instability of these symmetric solutions means that the plasmodium does not have enough mass to exploit two options at the same time and thus moves to just one . After a critical value ( see Materials and Methods , eq . ( 10 ) ) , corresponding to a third bifurcation , the upper branch of the homogeneous solutions becomes stable . This corresponds to the plasmodium equally exploiting both food sources . We label the bifurcation at a symmetry restoring bifurcation , since a stable , nontrivial symmetric solution appears at this point . This stabilisation coincides with the appearance of two non-homogeneous ( asymmetric ) unstable solutions , characteristic of a subcritical pitchfork bifurcation . Here we have tristability such that , depending on initial conditions , the plasmodium will exploit either none of the options , one of the two or both . The asymptotic analysis of these solutions for shows that the distance between the inhomogeneous solutions and the stable upper branch of the semi-trivial steady state decreases as increases . This means that for large mass these two solutions are approximately equal . As a result , the stable upper branch of the semi-trivial solution ( see Material and Methods , eq . ( 5 ) ) can never be reached in the sense that the set of initial conditions in its attraction basin decreases in size with . The biological conclusion is that a plasmodium of very large mass nearly always spreads between two options rather than moving to one . We now study the role of the threshold and flux parameters and . Fig . 3 depicts critical values of parameter as function of parameter for the fixed mass . The three lines correspond to the three types of bifurcations identified above . The bold solid line corresponds to the condition of the first bifurcation to occur and thus , to the existence of semi trivial solutions ( see eq . ( 6 ) in Materials and Methods ) . The solid line corresponds to the condition of the second bifurcation to occur and to existence of a non-trivial unstable homogeneous solution ( see eq . ( 8 ) in Material and Methods ) Finally , if parameters and are chosen under the dashed line in Fig . 3 the existence of all types solutions and all bifurcation points is secured . We next turn to the experimental results . Fig . 4a , b , c shows the probability to move to a food source as a function of the size of plasmodium . For very small size , there is a non-negligible probability to select none of the food sources . Plasmodia of small masses exploit more often only one source , while larger ones exploit both food sources at the same time . For example , the smallest Japanese plasmodia ( cm ) exploit only one food in 95 of the cases while for the largest size ( cm ) , this frequency decreases to 54 ( see Fig . 4a ) . Similar results are observed for the other strains ( see Fig . 4b , c ) . We notice however that there are some quantitative differences of exploitation patterns between strains: The largest Australian plasmodia ( cm ) exploit two food sources in 75 of the cases , a value which is larger than for the two other strains . Decision making by Physarum polycephalum depends thus on the size of the plasmodium as well as on the different exploration patterns of the strains . The experimental results are qualitatively consistent with the model predictions . Indeed , for small values of the parameter , there is no option chosen . For larger , there is coexistence between a state where one option is chosen and a state where no option is selected . Finally , for still larger , there is coexistence between three states corresponding to the selection of one option , to the simultaneous selection of two options and no selection at all . In terms of Physarum polycephalum , an organism with a small mass exploits one or no options , while a large mass endows it with the possibility to select simultaneously two options , one option or none . In order to compare the predictions of the model to the experimental outcome , we identified the best fit model in terms of the parameters and for each strain . For each mass used in the experiment we performed a Monte Carlo simulation of the model ( Materials and Methods ) for different parameter combinations . We run the Monte Carlo simulation 1000 times for each pair of ranging with the step 0 . 1 from 0 . 5 to 3 . 5 and ranging from 0 . 5 to 2 , and identified the best fit parameters ( see eq . ( 12 ) in Materials and Methods for details of model fitting ) . The best-fit parameters identified for each strain of plasmodium are given in Table 1 , along with the goodness of fit parameter ( see Model fitting in Materials and Methods section ) . The fitting parameter can be roughly interpreted as the proportion of data explained by our Monte Carlo simulation model . It varies for each strain between 0 . 84 and 0 . 92 , indicating that the simulation model accounts for the large majority of observed variation , supporting the validity of the inferred values of and . Fig . 4d , e , f shows the probability of selecting an option as a function of the mass , resulting from an average of 1000 realisations for every value of the mass considered and from the best fit parameters shown in Table 1 . This is to be compared with the experimental probabilities ( Fig . 4a , b , c ) . The model captures adequately the different patterns of exploitation for the masses and the strains considered in the experiment . Fig . 5 shows the bifurcation diagrams corresponding to the best-fit parameters for each of the three strains . We now identify the positions of the symmetry-restoring bifurcation point beyond which a simultaneous exploitation of the two options becomes possible . We notice that the critical value of the mass is different for the three strains , the Japanese one occurring at ( cf . Fig . 5a ) while the Australian and American ones occur at smaller values ( and respectively , Fig . 5b , c ) . These differences can be explained in biological terms and the exploration patterns of the slime mold ( Fig . 1 ) . The exploratory pattern of the Japanese strain is directional , forming thick tubes during its displacement . A larger mass is then needed to be able to exploit two options . In contrast , the Australian strain explores its environment more uniformly by forming thin tubes . A smaller mass is then needed to be able to exploit two options . As for the American strain , its exploration pattern combines both Japanese and Australian ones and an intermediate value of the mass is then needed . These exploration pattern differences are taken into account by the differences between two parameters that we used in our model . can be viewed as the speed of displacement of the plasmodium while reflects a threshold beyond which a tube can be built , and therefore is related to the way the different strains are moving: a small value of means that a tube is more easily constructed , even with a low mass . The function in eq . ( 4a ) saturates therefore more quickly and favours the homogeneous solution . On the contrary , a large value of this parameter implies that a large mass will be needed to build a tube and that saturates more slowly , favouring the semi-trivial inhomogeneous solution ( 6 ) .
We have presented a generic mathematical model for how different patterns of exploitation of two identical resources depend on the size of the system . The model takes into account two important features . Firstly , owing to the finite size of the system , the number of uncommitted units is limited by that already committed to the feeding sites . Secondly , the amplification process is local in that no direct comparison is made between the two options . The combination between local positive feedback and regulation of the traffic revealed a symmetry restoring bifurcation beyond which the system was able to select simultaneously two options , one of two options , or none of them . Past this bifurcation point , for increasingly larger initial system sizes , this tristability was still present but the symmetric solutions had an increasing basin of attraction . This was due to the existence of nearby unstable inhomogeneous states masking the other stable states . Most of the studies investigating decision-making patterns in Physarum polycephalum were conducted using a single strain ( the Australian strain obtained from Southern Biological Supplies: [40]–[42]; the Japanese strain: [43] ) . In order to test the model , we conducted experiments on three strains of Physarum polycephalum , each of them having different pattern of exploration . In our experimental set-up we took single individuals of different masses and let them choose between two identical food sources on a Petri dish . The different types of exploitation patterns obtained were similar to those predicted by the model , with the model capturing around 90% of the data . Symmetry-restoring is a generic phenomenon resulting from the coexistence of positive and negative ( regulatory ) feedbacks . In addition to the case considered in this work , it is also encountered in social insect foraging [24] , [25] . Beyond the case of decision-making in biological organisms , symmetry restoring is known to be also present in physical sciences , including phase transitions [29] and pattern formation in reaction-diffusion systems [44] . Our study highlights an important difference between local and global information in decision making . In slime mould , flow is a function of the thickness of the tube between the organism and a specific food source [38] , [39] . As a result , tube growth is a local process in the sense that tubes oriented along different directions are not inhibiting growth . In many experiments on ant and fish decision-making there is a predetermined decision point , at for example a Y-shaped branch [3] , [15] , where animals compare the two options directly . This choice point provides global information . It would be interesting to investigate situations in ants and other social organisms in a natural environment where groups are still offered two options ( two food sources ) but there is no pre-determined choice point . A setup of this kind for ants could consist of colonies of variable sizes connected to an open arena containing two identical food sources placed equidistant to the nest . The traffic that will eventually be established will still privilege paths leading to the food sources , but the information held by individuals will be purely local . In these conditions , we predict that beyond a critical size of the colony , individuals will display the three exploitation patterns seen in this paper . In particular , we predict a symmetry restoration at large colony sizes . Notice that symmetry restoring should be possible even in a maze type experiment provided that returns to the main branch of the maze can occur . A full analysis of this problem would require to incorporate in the description the navigation strategies employed . This is beyond the scope of the present work . The coexistence of multiple steady states in our model is expected to enhance flexibility . In nature , food sources are not constantly available and colonies focussing on one source can take a long time to switch to another [45] . However , in the region of coexistence between many solutions , a colony may quickly switch to another option [35] . Previously this was shown to be the case in the presence of crowding [24] or in the presence of more than two options [18] . We suggest that this may also happen in an open environment in the presence of only two options and a regulation of traffic of the kind considered in this paper .
We start by studying steady-state ( time-independent ) solutions of the system ( 3 ) . Setting time derivatives to zero and denoting by and the steady state solutions we arrive at the following system of algebraic equations ( 4 ) By solving this system we can determine how the decision to choose one , two or zero options depends on the total mass . We notice that eqs . ( 3 ) – ( 4 ) secure positivity of , as well as the property whatever the values of , and might be , provided that these conditions are satisfied initially . Indeed , as approaches starting from smaller values the first ( positive ) term in the rhs of eq . ( 4 ) will become increasingly small and the second ( negative ) term will dominate . As a result the time derivatives in eq . ( 3 ) will be negative and , and their sum will be led to lesser values . By evaluating the Jacobian at the steady states we can also determine their stability . In the general case , the Jacobian iswhere and Thus the characteristic equation determining the eigenvalues of the Jacobian has the form The steady states are stable as long as the real parts of the two ( possibly complex ) eigenvalues are negative . Equations ( 3 ) admit four types of steady states . We now discuss the existence and stability of each of these in turn . In order to incorporate the fluctuations inherent to the experiments , we developed a Monte Carlo approach by simulating directly the equations ( 3 ) . We describe the main principles of our Monte-Carlo simulation implementation in the following steps: In the light of the model results , we conducted a series of experiments to determine how the mass of Physarum polycephalum plasmodium influences the foraging decision process when the individual is confronted with two identical food sources . Physarum polycephalum is a unicellular , true slime mold , typically yellow in colour , and inhabits shady , cool , moist areas such as decaying leaves and logs . It belongs to the supergroup Amoebozoa . The main vegetative phase of P . polycephalum is the multi-nucleate plasmodium ( the active , streaming form ) that consists of networks of protoplasmic veins and pseudopods . It is during this stage that the organism searches for food . In the wild , the plasmodium eats bacteria and dead organic matter and in the laboratory they are fed oat flakes . We cultivated Physarum polycephalum on a 10 oat medium in a Petri dish ( diameter: 145 mm ) . The rolled oat were grained and set in 1 agar solution for presentation to Physarum polycephalum . To compare the foraging solution predicted by the model with those of P . Polycephalum , we measured the foraging solutions produced by three different strains: Australian strain ( Southern Biological Supplies , Victoria ) , American strain ( Carolina Biological Supplies ) and from Japanese strain ( Strain HU192 x HU200 ) that exhibit different exploration patterns . The Japanese strain is fast , forming only a few thick tubes to explore the substrate covering a long distance but a small surface . The Australian strain spreads in all direction by forming multiple thin tubes , covering a large surface but a small distance . The American strain combines both exploration patterns . It forms both thick and thin tubes ( see Fig . 1 for a snapshot of the three different exploration patterns by these three strains ) . In each trial one single plasmodium was confronted with two identical food sources . The food consisted in a 10 oatmeal-agar mixture similar to the one used for rearing the plasmodia . The foraging arena were made by filling 90-mm diameter Petri dishes with plain 1 agar . Once the agar set , we punched two circular holes ( diameter: 1 . 7 cm , 2 . 5 cm away from each other ) into the agar and filled them with food . Then we punched a third circular hole placed 2 . 5 cm away from each source which we filled with a plasmodium . The diameter of that last hole varied depending on plasmodium size . We tested 10 plasmodium sizes ( by extension , 10 plasmodium masses ) corresponding to the following diameters: 4 cm , 3 . 2 cm , 2 . 6 cm , 2 . 3 cm , 2 cm , 1 . 8 cm , 1 . 7 cm , 1 . 3 cm , 1 cm and 0 . 8 cm . The distance between the border of the plasmodium and the food was kept at a fixed value equal to 2 cm , whatever the diameter tested . We replicate each experiment 65 times for each plasmodium size and each strain ( 1950 experiments in total: 65 replicates 3 strains 10 plasmodium sized ) . All the experiments were conducted in the dark at temperature and 70 humidity . Experiments were run for 48 hours and pictures were taken every 5 min with a digital camera canon 60D . Throughout the experiment the plasmodium explores its environment by deploying a network of protoplasmic tubes until a food source is discovered , whereupon a link between the food source and its initial position is built . We consider that a given source is chosen if the plasmodium moves toward it through the link and fully covers it . If on the other hand the plasmodium does not completely cover the food source and moves to the other one at the same time to eventually cover it in part , we consider that both sources are chosen . We recall that both experiment and theory concern the steady state behaviour . Transients are likely to be of interest as well , but are not addressed here . Finally , if after exploring the environment the plasmodium did not succeed in finding any food source during the time of experiment we consider that no choice has been made . Summarising , we differentiated three distinct foraging patterns – the plasmodium exploits both food sources simultaneously , a single source and none of them – and calculated the proportion of replicates that ended up in these three states . We expect that our Monte Carlo simulation will capture a large proportion , but not all of the details of the real process . For example , for certain parameter values and masses our model predicts that the plasmodium will always move to exactly one option . In the data however , there is always some non-vanishing probability of a slime mould encountering two food sources . Acknowledging that our simulation model will not fully describe the many effects that could cause variation in the slime moulds behaviour , we must adapt our model fitting to allow for this in order to make our eventual fitted estimates of the simulation parameters robust . We thus modify our model fitting to account for variation that is not explained by the simulations , by fitting a mixture model comprising the simulation predictions , and a uniform distribution that represents all of the variation that is not accounted for in the simulation model . We thus introduce a new parameter , , that controls the mixing proportion of the simulation predictions , and therefore represents the proportion of the experimental variation explained by the simulation model [46] . Mathematically , to do the fitting , we let be the proportion of times the simulation with mass and parameters and chooses food options . We denote by the experimental proportion of times a plasmodium of mass chose food sources . Let be this uniform distribution over the options , such that . Introducing as the proportion of variation explained by our simulation and therefore the mixing ration of , we have a prediction for the distribution of : ( 12 ) where we infer and for each strain by finding the values that minimises the error term between this prediction and the experimental results . Identifying the best-fit values of the parameters is done by an exhaustive search over all combinations of , and with steps of , and 0 . 01 respectively . While the inferred parameters and are the best estimates for the internal processes of the slime mould described above , the inferred value of indicates what proportion of the experimental variation can be attributed to the processes specified in the simulation model , rather than to all other factors accounted for by the uniform distribution . It is therefore encouraging that the inferred values of in our study are typically on the order of 0 . 9 ( see Table 1 ) . As seen , the large values of inferred indicate that our simulation predictions are a substantial improvement upon a null hypothesis that the slime mould chooses randomly between the three options . | Collective decision making is ubiquitous in group-living organisms allowing them to select between several competing resources . It is a self-organized process involving positive feedback mechanisms , whereby the preference for a particular option is reinforced if the option has already been accepted by a part of the group's constituting units . The generally accepted paradigm of collective decision-making is a transition from an exploitation mode where all options are on equal footing , to one in which groups of sufficiently large size are led to focus on a particular option , a phenomenon referred to as symmetry-breaking bifurcation . In the present work we report results based on mathematical modeling in parallel with experiments carried out on the unicellular plasmoidal organism Physarum polycephalum showing that , contrary to the classical paradigm , symmetry is eventually restored for individuals of sufficiently large size ( here the plasmodium mass ) . This possibility , arising from the combination of positive feedbacks and a regulation of the flow by the fraction of system's mass already committed to the options , allows the organism to react flexibly . We argue that , beyond the case of P . polycephalum , this paradigm should apply to many systems possessing the aforementioned feedback and regulatory mechanisms . | [
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] | 2014 | Symmetry Restoring Bifurcation in Collective Decision-Making |
Malaria remains one of the greatest burdens to global health , causing nearly 500 , 000 deaths in 2014 . When manifesting in the lungs , severe malaria causes acute lung injury/acute respiratory distress syndrome ( ALI/ARDS ) . We have previously shown that a proportion of DBA/2 mice infected with Plasmodium berghei ANKA ( PbA ) develop ALI/ARDS and that these mice recapitulate various aspects of the human syndrome , such as pulmonary edema , hemorrhaging , pleural effusion and hypoxemia . Herein , we investigated the role of neutrophils in the pathogenesis of malaria-associated ALI/ARDS . Mice developing ALI/ARDS showed greater neutrophil accumulation in the lungs compared with mice that did not develop pulmonary complications . In addition , mice with ALI/ARDS produced more neutrophil-attracting chemokines , myeloperoxidase and reactive oxygen species . We also observed that the parasites Plasmodium falciparum and PbA induced the formation of neutrophil extracellular traps ( NETs ) ex vivo , which were associated with inflammation and tissue injury . The depletion of neutrophils , treatment with AMD3100 ( a CXCR4 antagonist ) , Pulmozyme ( human recombinant DNase ) or Sivelestat ( inhibitor of neutrophil elastase ) decreased the development of malaria-associated ALI/ARDS and significantly increased mouse survival . This study implicates neutrophils and NETs in the genesis of experimentally induced malaria-associated ALI/ARDS and proposes a new therapeutic approach to improve the prognosis of severe malaria .
Malaria is one of the most common infectious diseases and is an enormous public-health problem . In some individuals , a Plasmodium infection results in severe malaria . The main complications associated with this severe disease are cerebral malaria , metabolic acidosis , severe anemia , placental malaria , renal and hepatic insufficiency and acute lung injury/acute respiratory distress syndrome ( ALI/ARDS ) , which can occur alone or in combination [1 , 2] . Patients infected with Plasmodium falciparum , Plasmodium vivax , and Plasmodium knowlesi can develop ALI or ARDS , with a mortality rate close to 80% [3] . Neutrophils are one of the key cells in the pathophysiology of ALI/ARDS driven by various conditions [4] . They are recruited to lung tissue where they release reactive oxygen ( ROS ) and nitrogen species ( RNS ) , cationic proteins , such as myeloperoxidase ( MPO ) ; lipid mediators; inflammatory cytokines; elastase and matrix metalloproteinases . Although these molecules are toxic to invading pathogens , they also promote epithelial and endothelial damage [5–8] . The accumulation of proteinaceous substances [7 , 9] and the inefficient phagocytosis of apoptotic neutrophils also promote tissue injury [10] . Post-mortem examinations of the lungs of patients with malaria-associated ALI/ARDS have shown the presence of pulmonary edema , inflammatory infiltrates and accumulated inflammatory cells , including neutrophils , in the interstitial and alveolar spaces [11 , 12] . Moreover , a recent report showed higher neutrophil numbers in the peripheral blood of patients with severe malaria compared with numbers in uncomplicated cases in an Indian cohort [13] . Thus , evaluating the contribution of neutrophils to malaria associated-ALI/ARDS may help clarify the cellular and molecular mechanisms involved in the pathogenesis of this disease , which is essential for the development of new therapeutic approaches . There are several mouse models of pulmonary pathologies associated with Plasmodium infections with a wide range of severity [14–18] that can be used to investigate the relevance of neutrophils in malaria associated-ALI/ARDS . C57BL/6 mice infected with Plasmodium berghei NK65 showed evidence of damage in their alveolar epithelia , mixed inflammatory infiltrates containing macrophages , neutrophils and lymphocytes , as well as hemorrhages , severe edema and , in some cases , the development of hyaline membranes [19] , which were also found in DBA/2 mice infected with P . berghei ANKA ( PbA ) showing symptoms of ALI/ARDS [18] . However , CD8+ T lymphocytes have been demonstrated to be important in the induction of ALI/ARDS in C57BL/6 mice infected with P . berghei NK65 [19] . Here , we used a previously reported mouse model in which 30–60% of DBA/2 mice infected with PbA die as a result of ALI/ARDS symptoms between 7–12 days post-infection ( dpi ) [18 , 20] . DBA/2 mice suffering from ALI/ARDS show a loss of integrity of the alveolar-capillary barrier , including increased vascular permeability , pulmonary edema , hemorrhaging and leukocyte infiltration . Moreover , in this mouse model , we are able to identify mice that will likely die from ALI/ARDS using predictive criteria based on respiratory parameters and the extent of parasitemia [18] . Our data highlight the important potential of understanding the molecular mechanisms of malaria-associated ALI/ARDS as a way to identify new therapeutic targets .
As in our previous study [18 , 20] , a proportion of DBA/2 mice died during the second week of PbA infection with relatively low parasitemia levels ( Fig 1A and 1B ) . Using enhanced respiratory pause ( Penh ) , respiratory frequency ( RF ) and parasitemia values as predictive criteria , we have previously shown that these mice develop ALI/ARDS and that the remaining group dies after developing hyperparasitemia ( HP ) [18] . Based on these parameters , mice were divided into two groups on the 7th dpi ( S1 Fig ) . The mice with ALI/ARDS showed a significantly increased Penh and decreased RF compared with the values in mice developing HP ( Fig 1C and 1D ) , but both groups presented similar levels of parasitemia on the 7th dpi ( Fig 1E ) . We verified parasite distribution and adhesion in various organs via bioluminescence analysis using DBA/2 animals infected with PbA expressing luciferase . Luciferin injections were made on the 7th dpi , and perfused mice showed parasite loads , especially in the lungs and spleen . Moreover , mice that developed ALI/ARDS ( with hydrothorax ) showed more parasites in their lungs than mice developing HP ( Fig 1F ) . To investigate the mechanism responsible for the development of malaria-associated ALI/ARDS , leukocytes in the lungs and bronchoalveolar lavage fluid ( BALF ) were analyzed on the 7th dpi . Histological sections of lungs from mice with ALI/ARDS revealed an intense inflammatory infiltrate , along with numerous neutrophils ( Fig 2A ) . Flow cytometry analysis of the inflammatory cells from the lungs showed a significantly greater increase in the Ly6G+CD11b+ neutrophil population in mice with ALI/ARDS than in those developing HP ( Fig 2B ) . Accordingly , the mRNA expression of Ncf2 , a neutrophil-specific marker , was upregulated in the lungs of mice with ALI/ARDS compared with its expression in those developing HP ( Fig 2C ) . Consistent with neutrophil trafficking into the lungs of mice with ALI/ARDS , chemoattractants known to be produced by macrophages [21] and associated with ALI/ARDS-related injuries [22] , such as the chemokines KC ( CXCL-1 ) and MIP-2 ( CXCL-2 ) , were found at higher concentrations in sera of mice with ALI/ARDS than in that of mice with HP on both the 3rd and 5th dpi ( Fig 2D and 2E ) . Additionally , on the 7th dpi , neutrophils from the lungs of mice with ALI/ARDS showed increased ROS production ( DHR+ ) compared with those from mice developing HP ( Fig 2F and S2 Fig ) . Likewise , we found increased MPO activity in the lungs ( Fig 2G ) and BALF ( Fig 2H ) of mice with ALI/ARDS on the 7th dpi , indicating neutrophil activity within the alveolar space . In addition , macrophage/monocyte populations were prevalent in the BALF on the 7th dpi , and they did not differ between the different groups . In contrast , the number of neutrophils was significantly higher in mice with ALI/ARDS than in those developing HP ( Fig 2I ) , and more iRBCs were visualized in the BALF of mice with ALI/ARDS ( Fig 2J ) . All together , these data indicate that neutrophils are recruited in higher numbers and are more active in mice with ALI/ARDS than in mice developing HP . To investigate the relevance of neutrophils in the development of malaria-associated ALI/ARDS , DBA/2 mice infected with PbA received a single dose of anti-GR1 IgG antibody ( RB6-8C5 ) or an isotype control IgG ( control group ) on the 1st dpi . Consistent with a key role of neutrophils in the establishment of ALI/ARDS , none of the anti-GR1-treated mice developed the syndrome , and their survival rate was higher than that of the control group , in which , as expected , 60% of the mice died with signs of ALI/ARDS between 7 to 12 dpi ( Fig 3A ) . No differences in parasitemia were observed between the anti-GR1-treated mice and isotype-control-treated mice ( Fig 3B ) . Accordingly , on the 7th dpi , the anti-GR1-treated mice presented a decrease in Penh and an increase in RF compared with values in the isotype-control-treated mice that developed ALI/ARDS ( Fig 3C and 3D ) . Severe pulmonary edema and alveolar hemorrhaging were observed in histological lung sections of the isotype-control-treated mice , while the anti-GR1-treated mice showed only a thickening of the interstitium on the day of death ( Fig 3E ) . The depletion of neutrophils in the anti-GR1-treated mice was effective from the 2nd to 7th dpi ( 1st to 6th day post-antibody treatment ) ( Fig 3F and 3G ) . However , on the 9th dpi ( 8th day post-antibody treatment ) , the neutrophil population in the blood returned to control levels . On the 1st day post-anti-GR1 treatment , a small and transient decrease in blood monocytes was also observed , followed by an increase in monocytes on the 5th dpi ( S3A and S3B Fig ) . An increase was also observed in blood lymphocytes from the 2th to 7th dpi ( S3C and S3D Fig ) , which might be a compensatory mechanism in response to the lack of neutrophils . The CXCR4/CXCL12 signaling pathway is central to the migration of neutrophils and fibroblasts to the lung tissue in response to lung injuries due to different causes [23–26] . Hypothesizing that the CXCR4/CXCL12 axis would be important in this model of malaria-associated ALI/ARDS , we investigated its role . We used a plerixafor , AMD3100 , which is a non-peptide bicyclam derivative compound that antagonizes CXCR4 and inhibits its binding to CXCL12 and thus its function [27 , 28] , preventing neutrophil accumulation . DBA/2 mice infected with PbA were treated with four doses of AMD3100 , on the 1st , 3th , 5th and 7th dpi . Surprisingly , between the 7th and 12th dpi , 60% of untreated mice died with signs of ALI/ARDS , whereas only 10% of the mice treated with AMD3100 developed the disease , and 90% survived until the end of the experiment ( Fig 4A ) , despite there being no differences in parasitemia between the groups ( Fig 4B ) . The untreated mice that developed ALI/ARDS presented pleural effusion , hemorrhaging and intense inflammatory infiltration on the day of death ( Fig 4C ) ; however , AMD3100 treated-mice showed only minimal thickening of the alveolar septa on the day of death , indicating that blocking the action of CXCR4 with AMD3100 was effective in reducing the pathological responses associated with the decrease in neutrophils in the lungs of AMD3100-treated mice , on the 7th dpi ( Fig 4D ) . In addition , bone marrow cellular density was higher in the AMD3100-treated mice than in the untreated mice on the day of death , indicating greater cellular retention ( S4 Fig ) . The respiratory parameters on the 7th dpi were also altered: Penh was decreased , and RF was increased in the AMD3100-treated mice compared with values in the control mice ( Fig 4E and 4F ) . Our previous results show increases in neutrophil recruitment and in ROS and MPO production in the lungs of mice developing ALI/ARDS , all of which are favorable conditions for NET formation . The generation of ROS and the release of MPO are , respectively , the initial and later steps of NET generation [27 , 29 , 30] . Hypothesizing that NETs contribute to the development of malaria-associated ALI/ARDS , we investigated if P . falciparum and PbA could induce NETosis ex vivo . Indeed , we observed NET formation following the stimulation of human neutrophils with P . falciparum-iRBCs ( Fig 5A ) and mouse neutrophils with PbA-iRBCs and an iRBC lysate ( Fig 5B ) . In addition , we quantified NETosis ex vivo in mouse neutrophils using Sytox Green over 60 , 120 , and 180 minutes ( Fig 6 ) . The neutrophils stimulated with iRBCs showed a significant increase in fluorescence intensity from 120 minutes ( confirming more NETosis ) when compared with RBC-stimulated neutrophils ( Fig 6B ) . In vivo , we identified NETs in the lungs of PbA-infected mice on the day of death ( Fig 7A ) and also in the peripheral blood of PbA-infected mice ( S5 Fig ) , suggesting that this mechanism is involved in malaria-associated ALI/ARDS . To ascertain the effect of NETs on the pathogenesis of ALI/ARDS , we used Pulmozyme ( Roche , USA ) , a DNA disrupting drug , to treat DBA/2 mice on the 3th and 6th dpi . We observed that while 40–60% of the untreated mice died with signs of ALI/ARDS , fewer than 20% of the mice treated with Pulmozyme showed lung complications on the day of death , and none died of ALI/ARDS until the 20th dpi ( Fig 7B ) . We found no differences in parasitemia associated with or without the drug treatment ( Fig 7C ) , but Pulmozyme-treated mice had decreased Penh and increased RF values on the 7th dpi . ( Fig 7D and 7E ) . In addition , we treated the mice with Sivelestat , an inhibitor of neutrophil elastase , and observed an increase in survival , with just 15% of mice showing pulmonary involvement ( compared with the 75% of untreated mice that died of ALI/ARDS ) ( Fig 7F ) . There was no difference in parasitemia between groups ( Fig 7G ) : however , Sivelestat-treated mice showed decreased Penh and increased RF values compared with untreated mice on the 7th dpi ( Fig 7H and 7I ) . As with Pulmozyme treated mice , elastase inhibitor-treated mice did not show histological signals of ALI/ARDS , instead they showed only minimal interstitial thickening , whereas mice in the control group died of ALI/ARDS and presented a phenotype characterized by edema , hemorrhaging , and a high influx of inflammatory cells ( Fig 7J ) . All together , these results show that preventing NET formation using Pulmozyme or the inhibitor elastase Sivelestat improved respiratory parameters and no signs of ALI/ARDS , such as edema , hemorrhaging , and the high influx of inflammatory cells . In Fig 8 , we summarize the events leading to lung tissue damage associated with ALI/ARDS . During PbA infections , DBA/2 mice that develop ALI/ARDS show a higher number of neutrophils migrating into the lung tissue . Neutrophils from the microcirculation enter the interstitium and alveoli where they produce ROS , release enzymes ( MPO ) and form NETs , resulting in damage to epithelial tissue in the lungs associated with cytokine release , the death of endothelial and epithelial cells and increased vascular permeability and , consequently , edema . The course of the infection leads to hypoxemia and respiratory failure , which suggests that the use of drugs to inhibit the chemotaxis of neutrophils and the production of their inflammatory mediators may have a positive effect .
This study demonstrates the pivotal role of neutrophils in the establishment of malaria-associated ALI/ARDS . Using the PbA-infected DBA/2 mouse model previously established in our laboratory [18] , we have shown that Penh and RF values on the 7th dpi can predict whether mice will die earlier with ALI/ARDS or later with HP . Here , we show that during the development of ALI/ARDS , but not HP , neutrophils migrate and accumulate in lung inflammatory infiltrates , where they actively produce ROS and MPO , which are known to contribute to lung pathogenesis . The depletion of neutrophils , inhibition of neutrophil trafficking or inhibition of NET formation prior to the appearance of ALI/ARDS symptoms improves respiratory parameters , histopathological findings and mouse survival , thus confirming the dependency on neutrophils for establishing this syndrome . Our data indicate that lung pathologies in this model of malaria-associated ALI/ARDS are orchestrated by neutrophils and that CXCR4/CXCL12 are the receptor/chemokine responsible for their trafficking . CXCL12 is mainly produced by bone marrow stromal cells , including vascular endothelial cells , and this receptor/chemokine complex has been associated with the trafficking of immune cells in other infectious diseases [23 , 30–32] and has been shown to modulate neutrophils with only minimal effects on the monocyte compartment [31] . Various diseases , especially those involving the lungs , are improved by treatments that block CXCR4 [23 , 33 , 34] . A specific CXCR4 antagonist has been shown to inhibit neutrophil accumulation into air spaces and attenuate the increase in lung permeability during LPS-induced lung injury [23] . Furthermore , it has been demonstrated that AMD310 releases neutrophils from the marginal pool in the lung into the blood but does not change the output of bone marrow neutrophils [35] , as shown in our findings . We show here that , once in the lungs , neutrophils in mice developing ALI/ARDS produce ROS and MPO , whereas those in mice developing HP do not . In other models of lung injury , it has been shown that treatment with immunoregulatory drugs decreases the production of ROS and MPO [36 , 37] . We hypothesize that the same effect would occur in PbA-induced ALI/ARDS , predicting that without ROS and MPO , NET formation would not occur; however , this remains to be demonstrated . In a model of ALI/ARDS associated with E . coli , it has been observed that sick animals show an increase in neutrophils in the lungs , a decrease in neutrophil apoptosis and an increase in the production of ROS and MPO by neutrophils . Moreover , animals treated with resolvin E1 , a lipid mediator that reduces inflammation , showed an increase in apoptosis and a decrease in ROS , MPO , and IL-6 production by neutrophils , promoting disease resolution [38] . Previous studies showed that parasites such as Eimeiria spp , Toxoplasma gondii , Besnoitia besnoiti , and Leishmania amazonensis , among others , are able to stimulate neutrophils to form NETs [39–43] , and fungal infection of Candida albicans hyphae and Aspergillus fumigatus induce NET formation in the lung of mice [44] . In addition , the presence of circulating NETs in the blood has been reported in children with uncomplicated P . falciparum malaria [45] . Here , NET formation was implicated for the first time in the development of malaria-associated ALI/ARDS . We observed NET formation ex vivo by stimulating human and mouse neutrophils with P . falciparum and PbA iRBCs , respectively . Most importantly , we showed that the inhibition of NET formation by treating mice with recombinant human DNase ( rhDNase , Pulmozyme ) or elastase inhibitor ( Sivelestat ) greatly reduced lung pathologies and increased mouse survival . Accordingly , it has been shown that rhDNase treatment prevents NET formation in the alveoli and , as a consequence , improves pulmonary function and diminishes hypoxia in a transfusion-related model of acute lung injury [29] . It also decreases neutrophil accumulation and activation in cystic fibrosis patients [27] . The neutrophil elastase is a serine protease present in azurophilic granules that contributes to tissue injury when released during the inflammatory process [46 , 47] . However , elastase inhibitor treatment in patients with SIRS has been shown to improve the symptoms of this disease , decreasing ventilation times without adverse effects during and after treatment [8 , 46 , 48] . For more than 10 years , drugs such as Pulmozyme , Sivelestat , and AMD3100 have been used in patients as adjuvant treatments of various diseases [8 , 46 , 48–52] , and they are commercially available . However , the main criticism of studies conducted in Japan with elastase inhibitors is that they did not include patients with severe lung disease such as ALI/ARDS [53 , 54] . Therefore , our data indicate that Pulmozyme , AMD3100 and elastase inhibitors could be considered as adjuvant treatments to prevent malaria-associated ALI/ARDS in patients . High serum levels of KC and MIP-2 , selective chemoattractants for neutrophils , lead to the accumulation of these cells in the lungs . Moreover , various inflammatory factors , such as C5a , PAF , IL-8 and TNF-α , induce neutrophil activation [55] . However , it remains unclear what promotes the activation of neutrophils in the lungs of mice developing ALI/ARDS and not in those of mice developing HP . It is possible that the sequestration of iRBCs in the lungs promotes the release of different immune mediators from lung endothelial and epithelial cells . One such cytokine , IL-33 , has recently been associated with pulmonary edema in severe malaria cases in Southeast Asian patients and was found to be positively correlated with neutrophils and activated monocytes [56] . It will be of interest to use the mouse model of malaria-associated ALI/ARDS to investigate if IL-33 indeed has a role in PbA-induced lung pathologies and to examine what the molecular and immune mechanisms underlying the changes may be and how they can be prevented or controlled . Studies investigating allergies and auto-immunity in the context of lung mucosa [56 , 57] are likely to be informative in showing how Plasmodium infections can develop into lung pathologies and in helping to clarifying the host-pathogen interactions that mediate these changes . Our experimental model offers a unique view of the regulation and plasticity of the immune system in response to PbA infections , with an emphasis on lung pathology that may help understanding malaria-associated ALI/ARDS and contribute to early diagnoses and effective treatments to prevent ICU admissions and death due to ALI/ARDS , which are not yet attainable [9 , 18] .
Ten to twelve DBA/2 mice per group ( survival group and euthanatized groups ) were infected with 106 Plasmodium berghei ANKA ( PbA ) -infected red blood cells ( iRBCs ) at the same time . In the survival group , mice showing pleural effusion or red and congested lungs at necropsy , the cause of death was designated as ALI/ARDS . For mice without pleural effusion that died after 13 days post-infection ( dpi ) with pale lungs and high levels of parasitemia , the cause of death was designated as hyperparasitemia ( HP ) . By using respiratory patterns ( enhanced pause and respiratory frequency ) and the degree of parasitemia as predictive criteria , we established cut-off values using receiver operating characteristic ( ROC ) curves for these parameters measured on the 7th dpi based on data from mice whose cause of death was known ( survival group ) . Afterwards , we retrospectively diagnosed the euthanized mice as suffering from ALI/ARDS or HP by comparing their respiratory patterns and parasitemia measured on the 7th dpi with the cut-off values from the survival group at the end of each experiment ( 20th dpi ) , as previously described [18] and as illustrated in S1 Fig . Samples ( lung tissue , blood and bronchoalveolar lavage fluid ( BALF ) ) were collected from mice on the 7th dpi from the euthanized group . To measure chemokines , samples were collected on the 3rd and 5th dpi from the survival group , and lung tissues for histological analyses used to verify the cause of death were collected on the day of death . All experiments were performed in accordance with the ethical guidelines for experiments with mice , and the protocols were approved by the Animal Health Committee of the Biomedical Sciences Institute of the University of São Paulo ( CEUA n° 003 , page 98 , book 2 ) , of the Tropical Medicine Institute of the University of São Paulo ( n° CPE-IMT 2011/123 ) and of the Federal University of São Paulo ( CEP 1712/09 ) . The guidelines for animal use and care were based on the standards established by The Brazilian College of Animal Experimentation ( COBEA ) . Ethical approval for obtaining blood from healthy adult human volunteers was provided by the Committee for Research of the University of São Paulo ( Plataforma Brasil , CAAE: 11150612500005467 ) . All the study participants gave written informed consent . Male DBA/2 mice between 6–10 weeks old ( purchased from the Department of Parasitology , University of São Paulo , Brazil ) were infected with 1x106 PbA ( clone 1 . 49 L ) -iRBCs , as previously described [18] . Parasitemia and mortality were monitored daily . Parasitemia was determined via Giemsa staining and expressed as the percentage of iRBCs . Mice were euthanized using ketamine ( 150 mg/kg ) /xylazine ( 15 mg/kg ) . Respiratory patterns ( respiratory frequency [RF] and enhanced pause [Penh] ) were monitored on the 7th dpi using an unrestrained whole-body plethysmography chamber ( WBP , Buxco Electronics , USA ) for 10 minutes ( basal level ) , as previously described [18] . DBA/2 mice were infected with PbA expressing luciferase . On the 7th dpi , mice were injected with luciferin ( VivoGlo Luciferin , In Vivo Grid , Catalog #: P1041 , Promega ) , which result in the parasites becoming luminescent . Parasite localization was analyzed via an IVIS Spectrum instrument ( PerkinElmer ) . Mice were sedated with isoflurane to take pictures ( approximately 6 minutes after the injection of luciferin ) . Later , they were euthanized and perfused with 20 ml of PBS 1X . After perfusion , new images of the mice were captured , and their organs were then collected and placed in sterile petri dishes for observations of the bioluminescence of each tissue . Lung tissues from the day of death were fixed with 10% buffered formalin for 24 hours and kept in 70% ethanol until embedding in paraffin , and sections ( 4–5 μm ) were stained with hematoxylin-eosin ( HE ) . Quantitative RT-PCR was performed for the relative quantification of gene expression in the lungs of non-infected and infected mice on the 7th dpi . RNA extraction was performed according to the "Animal Cell I" protocol from the RNeasy Mini kit ( Qiagen , USA ) . cDNA synthesis was performed with a 1 μg RNA sample using the First Strand cDNA Synthesis RT-PCR kit ( Roche , USA ) according to manufacturer's instructions . Finally , for gene expression , SYBR Green PCR Master Mix ( Applied Biosystems , USA ) and the 2 ( -ΔΔCT ) relative quantification method were used as described previously [58] . The qRT-PCR reactions were performed in a 7500 Fast system ( Applied Biosystems , USA ) with the following oligonucleotides: Ncf2 ( forward—5’ gcagtggcctacttccagag 3’; reverse- cttcatgttggttgccaatg ) and HPRT ( forward—5’ aagcttgctggtgaaaagga 3’; reverse- 5’ ttgcgctcatcttaggcttt 3’ ) . Lungs were collected on the 7th dpi , washed with PBS 1X , and the extracellular matrix was removed with collagenase IV ( Sigma-Aldrich , USA ) as previously described [59] . Lung inflammatory cells were stained with fluorochrome-conjugated monoclonal antibodies ( BD Pharmingen or eBioscience , USA ) to the following surface molecules: CD3 ( 145-2C11 ) , CD19 ( 1D3 ) , Ly6G ( 1A8 ) , F4/80 ( BM8 ) , CD11c ( N418 ) , CD11b ( MI/70 ) , and Ly6C ( AL-21 ) . Cells were then incubated for 30 min at 4°C ( 1 μg Ac/1x106 cells ) . Data collection was performed using a FACSCantoII cytometer ( BD Bioscience , USA ) , and analyses were performed with FlowJo VX-10 software . Blood leukocytes were measured using the same methods described above and/or in fixed blood smears stained with Instant-Prov ( Newprov , Brazil ) . Lung inflammatory cells ( 1x106 ) from the 7th dpi were stained with antibodies for Ly6G ( 1A8 ) , CD11b ( MI/70 ) , and Ly6C ( AL-21 ) ( BD Pharmingen , USA ) . Intracellular levels of ROS were detected in neutrophils using dihydrorhodamine 123 [ ( DHR123 - ( 1 μg/ml ) ] . Cells were incubated sequentially with the antibodies and DHR123 at 37°C for 30 minutes . Data collection was conducted using a FACScantoII cytometer ( BD Bioscience , USA ) and analyzed with FlowJo VX-10 software . BALF and lungs were collected on the 7th dpi and sonicated for 60 seconds at 40 Hz with a TissueRuptor ( Biospec Products Inc , USA ) , and the supernatant was collected . To measure myeloperoxidase levels , 100 μl of the supernatant and the substrate solution were used . The substrate solution contained citrate buffer ( 10 mM citric acid + 10 mM sodium citrate ) , 5 mg of o-phenylenediamine dihydrochloride ( OPD; Sigma-Aldrich , USA ) and 5 μl of H2O2 ( 8 , 8 mM ) . A standard curve was established with 100 μl of type II horseradish peroxidase ( Sigma-Aldrich , USA ) at 500 ng/ml + 100 μl of the substrate . The stop solution was made with 4N H2SO4 . Sample reading was performed with a spectrophotometer ( Epoch-Bio Tek , USA ) at a wavelength of 492 nm . The quantities of keratinocyte-derived chemokine ( KC/CXCL1 ) and macrophage inflammatory protein 2 ( MIP-2 ) were determined in the serum using an ELISA kit ( Sigma-Aldrich , USA ) according to the manufacturer's protocols , on the 3rd and 5th dpi among the survival group , for which the cause of death was known . For BALF collection , the trachea was cannulated on the 7th dpi , and lungs were washed once with 1 . 0 ml of PBS 1X . Total and differential cell counts from the BALF were determined from slides prepared in a cytospin and stained with Instant-Prov ( Newprov , Brazil ) . The control group received IgG1 antibodies ( 0 . 2 mg/mouse ) , and the anti-GR1 group received anti-GR1 antibodies ( RB6-8C5 isotype IgG1 ) ( 0 . 2 mg/mouse ) on the 1st dpi . Mouse blood was collected from the submandibular vein for leukocyte quantification using blood smears and flow cytometry . The ALI/ARDS phenotype was confirmed via necropsies . The AMD group received 5 mg/kg of AMD3100 in a DMSO solution ( 20% DMSO in 80% saline solution ) , and the control group received just the DMSO solution on the 1st , 3rd , 5th and 7th dpi . Respiratory parameters of the mice were evaluated on the 7th dpi . The ALI/ARDS phenotype was confirmed via necropsies . Cultures of the P . falciparum clone 3D7 were grown as described previously [60] , except that human serum was replaced with Albumax I ( 0 . 5%; Thermo , USA ) . Parasite multiplication was monitored via microscopic evaluations of Giemsa-stained thick blood smears . Schizont stages were purified using magnetic columns ( Magnetically Activated Cell Sorting MACS Separation Columns; Miltenyi Biotec , USA ) [61] . Column stabilization , washing , and elution all were carried out at room temperature with RPMI 1640 ( Sigma-Aldrich , USA ) . To obtain mature PbA , iRBCs were synchronized as described previously [60] . Briefly , iRBCs were collected from infected mice exhibiting 10 to 20% parasitemia through a cardiac puncture and transferred to RPMI 1640 culture medium ( Gibco-Thermo , USA ) supplemented with 25% fetal bovine serum ( FBS ) . The iRBCs were subsequently maintained in vitro at 37°C for 14 h in an atmosphere containing 5% CO2 , 85% N2 , and 10% O2 . The parasitized erythrocytes were then enriched using a magnetic separation column ( Miltenyi Biotec , USA ) to generate cell populations consisting of approximately 95% iRBCs , as assessed based on thick blood smears . P . berghei extracts were obtained from iRBCs subjected to several freeze-thaw cycles . The femur and tibia of DBA/2 mice were removed , all muscles and tendons were dissected away , and the bones were placed in PBS 1X with 2% FBS and kept on ice . Bone marrow from each bone was washed with ( PBS+2% FBS ) and filtered through a 0 . 70-μm cell strainer . Cells in suspension were centrifuged at 500 x g for 5 minutes at 4°C , and the pellet was suspended in ice-cold distilled water for 30 seconds to lyse the erythrocytes . Then , a solution of PBS+2% FBS was used to stop the action of the distilled water , and the cells were centrifuged again . The pellet was resuspended in 1 ml PBS+2% FBS and placed on the surface of a Ficoll gradient ( Sigma-Aldrich Ficoll -1119 and 1077 ) . The samples were then centrifuged at 500 x g for 30 minutes at 4°C ( acceleration = 5 and deceleration = 0 ) . Neutrophils were recovered from the Ficoll ring between 1119 and 1077 and then washed with PBS+2% FBS . Finally , the neutrophils were centrifuged again , resuspended in 1 ml PBS+2% FBS , counted , and checked for purity based on Giemsa staining . Human neutrophils were obtained from peripheral blood via Ficoll gradient centrifugation followed by RBC lysis . These cells were stimulated with synchronized P . falciparum-iRBCs and phorbol-12-myristate-13-acetate ( PMA , 90 nM; Sigma-Aldrich , USA ) for 4 hours at 37°C in a humidified atmosphere containing 5% CO2 . The cells were washed with PBS 1X , fixed with 4% paraformaldehyde ( PFA; Sigma-Aldrich , USA ) and then permeabilized with 1% Triton X-100 ( Sigma-Aldrich , USA ) . Afterwards , we performed the NET labeling protocol . Neutrophils isolated from the bone marrow of femurs and tibias from naïve DBA/2 mice were resuspended in PBS+2% FBS at a final concentration of 2x105 cells per well . Neutrophils were stimulated with synchronized P . berghei-iRBCs , P . berghei lysate , non-infected red blood cells ( RBCs ) and PMA ( 50 nM; Sigma-Aldrich , USA ) for 3 hours at 37°C in a humidified atmosphere containing 5% CO2 . The wells were washed twice with PBS 1X , fixed with PFA ( Sigma-Aldrich , USA ) and permeabilized with 0 . 1% Triton X-100 ( Sigma-Aldrich , USA ) . To stain NETs in human neutrophils , they were incubated with rabbit anti-human-neutrophil elastase antibodies ( 1:1000; Santa Cruz , USA , ) and mouse anti-human-H2A/H2B antibodies ( 1:1000; Max Planck Institute , Germany ) . The secondary antibodies used were donkey anti-rabbit-IgG Alexa 488 ( 1:200; Invitrogen , USA ) and donkey anti-mouse-IgG Cy3 ( 1:100; Invitrogen , USA ) . Nuclei were stained with Hoechst 33342 ( 100 ng/mL; Invitrogen , USA , ) . To stain NETs from DBA/2 mice , neutrophils were incubated with histone H3 goat polyclonal IgG ( C-16 ) antibodies ( 1:200; Santa Cruz , USA ) and myeloperoxidase polyclonal rabbit anti-human antibodies ( 1:400; DAKO , Denmark ) . Nuclei were stained with Hoechst-33342 ( 100 ng/mL; Invitrogen , USA ) . The secondary antibodies used were Alexa Fluor 488 donkey anti-rabbit and Alexa Fluor 568 donkey anti-goat ( 1:200; Invitrogen , USA ) . To stain NETs in DBA/2 mice peripheral blood from , thin smears were made on glass slides and fixed with methanol . Immunofluorescence staining was performed using the antibodies described above_ anti-histone H3 ( 1:250 ) , anti-myeloperoxidase ( 1:500 ) , and the secondary antibodies ( 1:500 ) . Nuclei were stained with Hoechst-33342 . Lungs from mice with ALI/ARDS or HP were collected on the 7th dpi and fixed with 10% buffered formalin for 24 hours and then transferred to 70% ethanol . Tissues were embedded in paraffin , cut into sections ( 4–5 μm ) , and after deparaffinization , antigen retrieval and immunofluorescence were assessed as described previously [62] using the same antibodies as described from the ex vivo protocol . To confirm the ability of the PbA to promote NETosis , Sytox Green ( Invitrogen ) imaging was performed . Sytox Green is a fluorescent dye that binds to the nucleic acids of dead cells . Approximately 5 x 105 mouse neutrophils ( from the bone marrow ) were distributed into 96-well black flat plates ( Corning ) . Neutrophils were incubated with iRBCs or non-infected RBCs for 60 , 120 and 180 minutes . As a negative control , we used Hank’s buffered salt solution ( Thermo ) , and the positive control was established with 50 nM PMA ( Sigma-Aldrich ) . After incubation , the supernatant was removed , and 5 mM Sytox Green ( 50 mL ) was added . After 10 minutes , plate readings were taken at 488–523 nm in a SpectraMAX fluorimeter ( Molecular Devices ) . Mice were anesthetized briefly with approximately 4% halothane and 96% oxygen and then administered 50 μg/mouse ( 5 mg/kg ) of DNAse 1 ( Pulmozyme , Roche , USA ) or a saline solution via intranasal spray on the 3rd and 6th dpi as describe previously [63] . Respiratory parameters of the mice were evaluated on the 7th dpi . Sivelestat ( Sigma-Aldrich ) , an elastase inhibitor , was administered to mice ( 30 mg/kg ) diluted in a saline solution , and the control group received just the saline solution on the 3rd and 6th dpi . Respiratory parameters of the mice were evaluated on the 7th dpi . Statistical analyses and graphing were performed using GraphPad Prism 5 . 0 software . The data were analyzed for normality using Kolmogorov-Smirnov or Shapiro-Wilk normality tests , and variance was assessed using Bartlett’s test . Non-parametric variables were compared using Mann-Whitney tests between the groups with ALI/ARDS and HP . For the analysis of three groups , we used a Kruskal-Wallis test followed by Dunn’s post-hoc tests . For the survival curves , log-rank and Wilcoxon-Gehan-Breslow tests were used . The differences between the groups were considered significant at p≤0 . 05 ( 5% ) . To establish cut-off values from the data , ROC curves were generated in MedCalc version 8 . 2 . 1 . 0 using the results from the infected control group ( survival group ) . | A deeper understanding of the pathogenesis of malaria-associated ALI/ARDS may help in the development of new therapeutic approaches to improve the prognosis of severe cases of malaria . Using the Plasmodium berghei ANKA-infection mouse model of ALI/ARDS , which resembles the human disease in many aspects , this study reports the critical role of neutrophils in the pathogenesis of this syndrome . Mice developing ALI/ARDS showed abundant lung-infiltrating neutrophils in association with the increased production of neutrophil-attracting chemokines , myeloperoxidase and reactive oxygen species . The parasites Plasmodium falciparum and P . berghei ANKA both induced the formation of neutrophil extracellular traps ex vivo . By targeting neutrophils and neutrophil extracellular traps with specific drugs , we succeeded in preventing the development of malaria-associated ALI/ARDS and significantly increased mouse survival . | [
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"... | 2016 | Targeting Neutrophils to Prevent Malaria-Associated Acute Lung Injury/Acute Respiratory Distress Syndrome in Mice |
The highly expressed D7 protein family of mosquito saliva has previously been shown to act as an anti-inflammatory mediator by binding host biogenic amines and cysteinyl leukotrienes ( CysLTs ) . In this study we demonstrate that AnSt-D7L1 , a two-domain member of this group from Anopheles stephensi , retains the CysLT binding function seen in the homolog AeD7 from Aedes aegypti but has lost the ability to bind biogenic amines . Unlike any previously characterized members of the D7 family , AnSt-D7L1 has acquired the important function of binding thromboxane A2 ( TXA2 ) and its analogs with high affinity . When administered to tissue preparations , AnSt-D7L1 abrogated Leukotriene C4 ( LTC4 ) -induced contraction of guinea pig ileum and contraction of rat aorta by the TXA2 analog U46619 . The protein also inhibited platelet aggregation induced by both collagen and U46619 when administered to stirred platelets . The crystal structure of AnSt-D7L1 contains two OBP-like domains and has a structure similar to AeD7 . In AnSt-D7L1 , the binding pocket of the C-terminal domain has been rearranged relative to AeD7 , making the protein unable to bind biogenic amines . Structures of the ligand complexes show that CysLTs and TXA2 analogs both bind in the same hydrophobic pocket of the N-terminal domain . The TXA2 analog U46619 is stabilized by hydrogen bonding interactions of the ω-5 hydroxyl group with the phenolic hydroxyl group of Tyr 52 . LTC4 and occupies a very similar position to LTE4 in the previously determined structure of its complex with AeD7 . As yet , it is not known what , if any , new function has been acquired by the rearranged C-terminal domain . This article presents , to our knowledge , the first structural characterization of a protein from mosquito saliva that inhibits collagen mediated platelet activation .
Hematophagous arthropods produce a varied mix of salivary proteins , peptides , and small molecules aimed at overcoming the hemostatic and inflammatory responses of the host . In order to successfully take a meal , the blood feeder must prevent host vasoconstrictive responses and the clotting of blood as it travels through the mouthparts to the gut [1] , [2] . The inhibition of immediate inflammatory responses is also essential , in that the swelling , itching , and pain resulting from arthropod bites may themselves interfere with the ingestion of blood or elicit defensive behavioral responses from the host [1]–[4] . Additionally , inflammation in the skin at the site of feeding has been shown to influence the establishment of infection by arthropod-vectored pathogens , making the anti-inflammatory components of saliva important from this standpoint as well [5] , [6] . In fact , several pathogens take advantage of the biological properties of the salivary mixture to infect their hosts and cause disease . It has been demonstrated that immunity against salivary components from different mosquito species is able to reduce disease transmission by these vectors [7]–[10] . In addition , the mosquito life cycle is affected by immunization against salivary molecules [11] . Wounding as a result of a mosquito bite exposes collagen and other matrix proteins that act to initiate the activation of platelets . The stimulation of TXA2 biosynthesis and the release of dense granules containing small molecule mediators of platelet activation and inflammation such as ADP and serotonin potentiate the activation response . In sensitized hosts , IgE antibodies recognizing salivary proteins activate mast cells in the skin , leading to the release of large amounts of histamine and the synthesis of CysLTs [1] , [2] . These compounds cause rapid swelling , pain , increases in vascular permeability , and itching in the host . Numerous proteins have now been identified in the salivas of blood feeders that act to limit the responses of platelets and mast cells to arthropod bites [12]–[19] . An important functional theme in the physiology of blood feeding is the use of specific salivary binding proteins to sequester small-molecule agonists of inflammation and platelet activation [14] , [17] , [18] , [20] . Since hematophagy has evolved independently many times in insects and other arthropods , proteins from different structural families act to perform these functions in the various blood-feeding species [1] , [2] , [13] . To generate the molecular diversity needed to bind small molecule effectors of widely varying structure , multigene families have arisen from gene duplication events , with the resulting gene products being expressed specifically in the salivary glands of blood feeders [21] . Individual members of these families have diverged in sequence and structure , resulting in an array of protein forms with different ligand binding specificities . In some instances , salivary proteins have acquired the ability to form specific interactions with host proteins while maintaining the ability to bind small molecule effectors . The diversity of these binding protein families may reflect an evolutionary arms race between the arthropod blood feeders and the sophisticated hemostatic , inflammatory , and immune systems of their vertebrate hosts . Two protein families have thus far been implicated as scavengers of small molecule modulators of inflammation and platelet aggregation in blood feeding arthropods . The lipocalins serve this function in ticks and triatomine bugs , while members of the D7 family serve the function in mosquitoes [14] , [20] , [22] . D7 proteins are structurally related to the arthropod OBPs and come in two forms . The long form proteins , as exemplified by AeD7 from the saliva of Aedes aegypti , have two OBP domains , with each domain binding a single ligand molecule [14]–[16] . Single-domain D7 proteins are found in mosquitoes and other members of the Nematocera suborder of flies , with those from An . gambiae ( referred to as D7r proteins ) being extensively characterized and found to bind a single ligand molecule per protein [14] . A group of proteins orthologous to D7r is found in An . stephensi , and one of these has also been found to function as an inhibitor of coagulation and inflammation pathways by binding factor XII ( a ) and high molecular weight kininogen [23] . The functionally equivalent ortholog of this molecule has been identified in An . gambiae as the protein D7r1 [14] . Both AeD7 and the D7r proteins bind the biogenic amines serotonin , norepinephrine , and histamine with high affinity . The C-terminal domain of AeD7 is responsible for biogenic amine binding and is homologous to the single domain D7r proteins , while the N-terminal domain is distinct in sequence and structure and is a scavenger of CysLTs [15] . Despite the presence of the highly expressed , biogenic amine-binding , short form D7 proteins in all species of Anopheles examined , the two-domain long forms of D7 have not been lost , suggesting that they may play , at least in part , a different role in these species . In this study we examine the ligand binding specificity , physiological function , and three dimensional structure of AnSt-D7L1 , a two-domain D7 protein from An . stephensi , a vector of the malaria parasite . We found that unlike other members of the D7 family , this protein functions as a TXA2-binding protein , thereby acting to inhibit the activation of platelets during feeding . We also describe the crystal structures of ligand complexes that provide , to our knowledge , the first view of the molecular interactions involved in TXA2 binding . We ask whether evolution of the short D7 proteins in Anopheles sp . and their assumption of the biogenic amine binding function otherwise seen in the long form of Aedes has resulted in the evolution of functional changes in the protein . We find that AnSt-D7L1 has acquired the ability to bind the vasoactive platelet aggregation and proinflammatory agonist TXA2 in addition to maintaining the ability to bind CysLTs . Additionally , the C-terminal domain has undergone extensive structural rearrangements resulting in a loss of the biogenic amine binding function .
The amino acid sequence of AnSt-D7L1 is 31% identical to that of AeD7 , the two-domain D7 from Ae . aegypti ( Figure 1 ) . AeD7 contains binding sites for both CysLTs and biogenic amines , with the CysLT binding site lying in the N-terminal domain and the biogenic amine binding site in the C-terminal domain . Residues lining the CysLT binding pocket in the N-terminal domain of AeD7 are conserved to a large degree in AnSt-D7L1 and other two-domain D7 proteins from Anopheles sp . ( Figure 1 ) . The C-terminal domain of AnSt-D7L1 also shows conservation of most but not all of the residues from the biogenic amine binding pocket in AeD7 and the D7r proteins from Anopheles species . Notably , the position of His 189 in AeD7 contains alanine ( Ala 190 ) in AnSt-D7L1 and other two-domain D7 proteins from Anopheles species ( Figure 1 ) . This residue is highly conserved in biogenic amine-binding D7 proteins where it forms a hydrogen bond with the phenolic hydroxyl groups of serotonin and catecholamines [15] , [16] . In order to determine the role of AnSt-D7L1 in blood feeding , we examined its ligand binding properties . A series of ITC experiments were performed to screen potential candidate ligands , including bioactive lipids , biogenic amines , and nucleotides that are known to be involved in inflammation and hemostasis ( Figure S1 ) . AnSt-D7L1 bound the CysLTs LTC4 , LTD4 , and LTE4 with a stoichiometry of one ligand molecule per molecule of protein ( Figure 2A–C ) . The binding affinities for CysLTs were approximately 10 times higher than those previously reported for the related protein AeD7 [15] . As in AeD7 , the affinities for the three CysLTs are similar to one another , suggesting that the protein recognizes the lipid portion of the ligand , rather than the peptide portion . AnSt-D7L1 did not bind LTB4 , a ligand previously shown to bind with AeD7 [15] with low affinity ( unpublished data ) . The eicosanoid TXA2 is an important mediator of platelet activation and vascular tone . Because of its instability , TXA2 binding could not be evaluated directly using ITC . In solution , it undergoes rapid hydrolysis to form TXB2 , a stable but physiologically inactive compound . Binding with stable analogs could be measured , however , with U46619 and carbocyclic TXA2 exhibiting dissociation constants of approximately 98 nM and 38 nM , respectively ( Figure 2D , E ) . This suggested that TXA2 itself may be a physiological target of AnSt-D7L1 . The binding affinity for TXB2 , the major hydrolysis product of TXA2 , was approximately 13-fold lower than for U46619 , demonstrating that the protein may be able to discriminate between the active and inactive thromboxane forms in vivo ( Figure 2D , F ) . AeD7 and the single-domain D7r proteins of An . gambiae have been characterized as scavengers of the biogenic amines serotonin , norepinephrine , and histamine [14]–[16] . AnSt-D7L1 showed no detectable binding of biogenic amines , however , suggesting that its C-terminal domain is structurally distinct from the comparable , biogenic amine-binding C-terminal domain of AeD7 ( unpublished data ) . We have also tested the binding of AnSt-D7L1 to the platelet activating phospholipid derivative PAF and also to the nucleotide ADP . Neither showed any detectable binding ( unpublished data ) . To determine if AnSt-D7L1 is specific in its binding for CysLTs and TXA2 , we screened a number of additional eicosanoid compounds using ITC . AnSt-D7L1 showed no detectable binding to AA ( unpublished data ) but bound the prostaglandins PGD2 , PGE2 , and PGF2α with affinities much lower than those seen with CysLTs and TXA2 analogs ( Figure 3 ) . The PGH2 analog U51605 also showed detectable but much weaker binding than U46619 ( Figure 3D ) . This compound is also similar in structure to U46619 and carbocyclic TXA2 but lacks the hydroxyl group at the ω-5 position of the hydrocarbon chain , suggesting that this moiety plays an important role in the binding of TXA2 analogs . To test for a hydrolytic or enzymatic function of AnSt-D7L1 , LTC4 was incubated with the protein at 25°C and the mixture was analyzed by HPLC and mass spectrometry . Analytical gel filtration chromatography revealed only one peak corresponding in molecular size to the protein , indicating the formation of a leukotriene complex ( Figure S2 ) . Fractions containing the complex were then applied to a C18 HPLC column , eluted with methanol , and analyzed by mass spectrometry . The spectrum of the bound ligand was essentially identical to that of the free ligand , indicating that the protein binds but does not chemically modify LTC4 ( Figure S3 ) . One of the well-characterized physiological effects of CysLTs and TXA2 is the induction of smooth muscle contraction [24] , including pulmonary vascular smooth muscle [25] , guinea pig ileum [26] , and aorta [27] . AnSt-D7L1 effectively abrogated LTC4-induced contraction ( Figure 4A ) of ileum preparations , demonstrating the ability of the protein to sequester ligand molecules and prevent them from interacting with their cognate receptors . When administered to a preparation of rabbit aorta , AnSt-D7L1 also inhibited U46619-induced contraction , increasing by approximately 3-fold the amount of U46619 needed to promote contraction in the absence of the protein ( Figure 4B ) . AnSt-D7L1 was also able to reverse contraction induced by U46619 when added after the agonist ( Figure 4C ) . In order to verify that the protein had no additional effect on the integrity of aorta preparations , phenylephrine ( PE ) , an α1-adrenergic receptor agonist , was added to the preparation after relaxation by AnSt-D7L1 . The aorta contracted normally , further verifying that the effect of AnSt-D7L1 was due only to its ability to bind U46619 ( Figure 4C ) . Exposure of collagen from the subendothelial matrix at the site of a wound plays a key role in triggering platelet adhesion and activation . Platelet interaction with collagen may be indirect , due to binding of the VWF-collagen complex with glycoprotein Ib-IX-V ( GPIb-IX-V ) or αIIbβ3 , or direct , via interaction with the platelet collagen receptors α2β1 ( or glycoprotein Ia/IIa ) and glypoprotein VI ( GPVI ) [28]–[32] . These events lead to the synthesis of TXA2 and release of ADP , which act together with collagen to amplify pro-aggregatory signals resulting in “inside out” activation of integrin αIIbβ3 , the receptor for fibrinogen and fibrin , and consequent platelet aggregation [29] , [32] . At higher concentrations , collagen acts as a strong agonist of GPVI leading to platelet activation and aggregation in a manner that is independent of secretion of TXA2 or ADP [31] , [32] . At low concentrations of collagen , however , aggregation depends on amplification of the response by TXA2 and ADP [31] . This being the case , we hypothesized that binding of TXA2 by AnSt-D7L1 should inhibit platelet activation by low concentrations of collagen and have no effect at higher collagen concentrations . When we incubated stirred platelets with AnSt-D7L1 and stimulated with a low concentration ( 1 . 6 µg/mL ) of collagen , we observed a delay in the onset of shape change and a diminished extent of platelet aggregation ( Figure 5A ) . The degree of inhibition was dependent on the concentration of AnSt-D7L1 , and under these conditions , aggregation was almost completely inhibited by a concentration of 1 µM AnSt-D7L1 ( Figure 5A ) . Conversely , when platelets were stimulated by collagen at high concentration ( Figure 5B ) or by the potent GPVI agonist convulxin ( Figure 5C ) , the inhibitory effect of AnSt-D7L1 was lost . Platelet aggregation induced by collagen is also affected by apyrase , indicating an important role for ADP . Shape change induced by lower concentrations of ADP is a TXA2-independent process , however , and should not be limited by an inhibitor targeting TXA2 [33] . When we administered the minimal dose of ADP needed to elicit shape change to stirred platelets , preincubation with AnSt-D7L1 had no inhibitory effect ( Figure 5D ) . This indicates that AnSt-D7L1 does not affect ADP signaling directly . Conversely , RPAI1 , a specific ADP-binding protein from Rhodnius prolixus saliva [22] , [34] , was able to completely inhibit the shape change response under these conditions ( Figure 5D ) . AnSt-D7L1 also showed no effect on platelet aggregation induced by the protein kinase C activator PMA ( Figure 5E ) or on ristocetin-induced platelet agglutination , which is dependent on VWF ( Figure 5F ) . Both of these pathways are independent of TXA2 , suggesting that the inhibition of collagen-mediated aggregation by AnSt-D7L1 depends only on its ability to bind TXA2 . When platelets were activated by collagen in the presence of SQ 29 , 548 , an antagonist of TXA2 receptor ( TP ) , or were pre-treated with indomethacin , an inhibitor that prevents TXA2 biosynthesis , aggregation was attenuated ( Figure 6A ) . The effect obtained with both treatments was very similar to that seen with 3 µM AnSt-D7L1 ( Figure 6A ) , further supporting the idea that the activity of the protein is due to its ability to bind TXA2 . This result is important in showing that AnSt-D7L1 is able to bind TXA2 itself , since in ITC experiments we were limited to the testing of stable analogues of TXA2 . AnSt-D7L1 inhibited U46619 ( 1 . 3 µM ) -induced platelet aggregation in a concentration-dependent manner ( Figure 6B ) . At low concentrations of AnSt-D7L1 ( less than a 1∶1 ratio of protein to inhibitor ) , the protein delayed but did not prevent platelet aggregation . As the ratio approached 1∶1 ( at 1 µM AnSt-D7L1 ) , the protein dramatically inhibited aggregation , an observation consistent with the 1∶1 binding stoichiometry seen in ITC experiments ( Figure 2D ) . Although higher concentrations ( 2 and 3 µM ) of the protein completely prevented aggregation of platelets , shape change was not completely inhibited and could only be prevented by blockade of the TP receptor with the antagonist SQ 29 , 548 ( Figure 6B ) . This is possibly due to the fact that TP-mediated shape change is coupled to a Gα12/13 protein signaling cascade , which requires only small amounts of U46619 ( EC50 around 13 nM ) [27] , . Larger amounts of U46619 are necessary to promote aggregation , which is dependent on Gαq/11-coupled signaling [27] , [35] . Since AA is a biosynthetic precursor of TXA2 , as well as of prostaglandins , we tested the effect of AnSt-D7L1 on platelet aggregation induced by this compound . AnSt-D7L1 drastically decreased platelet aggregation induced by AA , showing a similar effect to that observed when platelets were pre-treated with indomethacin ( Figure 6C ) . Since ITC data indicated that this protein does not bind AA itself ( unpublished data ) , we conclude that the observed effect is due to AnSt-D7L1 binding of newly synthesized TXA2 . In order to characterize the ligand binding sites and understand the relationships and evolution of proteins in the D7 family , we determined the crystal structure of AnSt-D7L1 in the absence of ligands and in the presence of U46619 and LTC4 ( Table 1 ) . The ligand-free form of the protein crystallized in the space group P212121 with one protein molecule in the asymmetric unit . The structure revealed two OBP domains with the N-terminal domain containing three disulfide bonds and the C-terminal domain containing two ( Figure 7A , B ) . The interface between the domains contains a number of residues that interact by hydrogen bonding or cation pi interactions . In its overall structure , the protein is similar to AeD7 with an RMS deviation of 1 . 82 Å over 239 Cα positions ( Figures 1 , 7 ) . The N-terminal domain of AnSt-D7L1 consists of seven α-helices oriented around a solvent-accessible hydrophobic channel ( Figure 7A , B ) . Superposition of the N-terminal domains of AeD7 and AnSt-D7L1 shows the two to be quite similar in structure , with an RMS positional deviation for 144 Cα positions of 1 . 36 Å ( Figure S4 ) . Like AeD7 , the apparent entry point to the ligand-binding channel is surrounded by a positively charged electrostatic surface that would be attractive to the anionic eicosanoid ligands ( Figure 8D ) [15] . In AnSt-D7L1 the C-terminal domain also contains seven α-helices and is less similar in overall structure to AeD7 than is the N-terminal domain ( Figures 7A , B and S4 ) . The C-terminal domain of AeD7 is made up of seven α-helices in the ligand-free form and an eighth helix ( H2 ) forms in response to the binding of norepinephrine ( Figure 7C , D ) [15] . This helix corresponds to the seventh α-helix ( H2 ) of AnSt-D7L1 ( Figure 7A–D ) [15] . In AnSt-D7L1 , the second α-helix of AeD7 ( B2 ) is not present ( Figure 7A , B ) . Rather , this region forms a predominantly coil structure extending between Lys 169 and Ser 184 containing a β-turn between residues Trp 173 and Gly 176 . This portion of the C-terminal domain also lacks a cysteine residue found in AeD7 ( Cys 173 ) and other D7 proteins , which forms a disulfide bond with a second cysteine ( Cys 301 in AeD7 ) located at or near the C-terminal end of the protein ( Figure 7C , D ) [15] , [16] . As a result of these changes , the terminal α-helix of the C-terminal domain ( H2 ) is positioned differently than the corresponding α-helix H2 in AeD7 . Many of the residues forming the C-terminal domain ligand binding pocket in AeD7 are conserved in AnSt-D7L1 , but some occupy different positions , giving a completely different architecture to the structure of the region . Arg 177 in AnSt-D7L1 is equivalent to Arg 176 in AeD7 but is positioned such that its side chain partially occupies the same space as the ligand in the AeD7-norepinephrine complex ( Figure 9A , B ) . Along with other changes , including the presence of tryptophan rather than leucine at position 173 in AnSt-D7L1 , this modification acts to further fill the space equivalent to the biogenic amine binding pocket of the AeD7 C-terminal domain ( Figure 9A , B ) . Although the identities of most of the residues forming hydrogen bonds with biogenic amines in AeD7 are conserved in AnSt-D7L1 , some changes are apparent . Most notably , a histidine residue ( position 189 in AeD7 ) that forms hydrogen bonds with the phenolic hydroxyl groups of serotonin and norepinephine is mutated to alanine ( Ala 190 ) in AnSt-D7L1 ( Figure 9A , B ) . These positional rearrangements and amino acid substitutions clearly explain the loss of the biogenic amine binding function in AnSt-D7L1 and indicate that the C-terminal domain in AnSt-D7L1 performs a different function than its counterpart AeD7 . This novel function has not yet been identified . Anst-D7L1 was crystallized in the presence of a 1 . 3-fold molar excess of either U46619 or LTC4 using otherwise identical crystallization conditions as for the ligand-free form . Both ligand complexes crystallized in the space group P21 rather than P212121 , with a single protein molecule in the asymmetric unit . Rather than binding in the separate domains of AnSt-D7L1 , both ligands were found to bind in the hydrophobic pocket of the N-terminal domain of the protein . The structure of the U46619 complex showed excellent electron density for the ligand , allowing a complete analysis of its binding interactions ( Figure 8A , B ) . U46619 is bound with the unmodified end of the hydrocarbon chain projecting into the hydrophobic pocket , while the carboxyl group is positioned near the surface of the protein ( Figure 8A ) . The hydroxyl group at the ω-5 position of the hydrocarbon chain of the ligand is stabilized by hydrogen bonds with the phenolic hydroxyl of Tyr 52 and the carbonyl oxygen of Trp 37 , while the oxygen atom contained in the bicyclic ring system participates in a hydrogen bonding network with the carbonyl oxygen of Leu 13 via an intervening water molecule ( Figure 8A ) . The carboxyl group of the ligand forms hydrogen bonds with the side chain of Lys 152 , as well as with an ordered water molecule near the entry to the ligand binding channel , while the ω-end of the fatty acid chain sits in a hydrophobic pocket formed in part by the side chains of Leu 42 , Val 56 , and Leu 57 ( Figure 8A ) . The LTC4 complex of AnSt-D7L1 is similar in structure to the LTE4 complex of AeD7 with the ligand being bound at essentially the same site as U46619 ( Figure 8C ) . The quality of the electron density for LTC4 was somewhat lower than for U46619 , probably reflecting the relative instability of the ligand over the 2–3-week crystallization period . Nevertheless , the fatty acid portion of the molecule could be positioned in the ligand binding channel ( Figure 8C ) . The peptide portion of LTC4 was not well ordered , consistent with the fact that similar thermodynamic parameters for the three CysLTs were observed in ITC experiments . The carboxyl group of the ligand is positioned similarly to U46619 and also forms a hydrogen bond or salt bridge with the side chain of Lys 152 ( Figure 8C ) . The longer unsaturated hydrocarbon chain of LTC4 projects further into the ligand binding channel than does that of U46619 . Near the position occupied by the ω-methyl group of U46619 , the hydrocarbon chain of LTC4 is bent approximately 90° and the terminal four carbon atoms are accommodated in a hydrophobic cavity lined by the side chains of Tyr 117 , Ile 62 , Leu 60 , Trp 40 , and Leu 57 ( Figure 8C ) . The structure of the C-terminal domain in the ligand complexes is quite similar to the ligand-free protein and shows no evidence of interaction with either U46619 or LTC4 . The position of helix H2 and the structure of the region corresponding to helix B2 in AeD7 are nearly identical to those seen in the ligand-free form of the protein . This again demonstrates that these differences between AnSt-D7L1 and AeD7 are not the result of crystal packing interactions . However , the region to the C-terminal side of helix H2 takes on a different conformation in the ligand complexes than in the ligand-free protein . In the absence of ligands , the segment between Leu 291 and the C-terminus ( Phe 297 ) extends away from the surface of the protein and forms a β-turn between Thr 293 and His 296 . In the ligand complexes the segment between Leu 291 and Val 295 packs against the surface of the protein , where it participates in a number of intramolecular hydrogen bonds ( Figure S4 ) . It is not clear whether the change in the C-terminal conformation is attributable to crystal packing differences or is a direct result of leukotriene binding in the N-terminal domain binding pocket .
The binding site for eicosanoid ligands lies in a pocket in the N-terminal domain of AnSt-D7L1 , which is lined with mostly hydrophobic residues that accommodate a large portion of the fatty acid chain . CysLTs are substituted at the ω-14 position of the chain while TXA2 and its analogs contain a hydroxyl group at the ω-5 position ( Figure S1 ) . Binding of TXA2 analogs by AnSt-D7L1 appears to result from its ability to accommodate this substitution pattern . AnSt-D7L1 contains a tyrosine residue at position 52 , while AeD7 has phenylalanine at the equivalent position . Consequently , AeD7 is unable to form one of the hydrogen bonds that stabilize U46619 in the AnSt-D7L1 binding pocket and does not bind TXA2 analogs [15] . The PGH2 analog U51605 is very similar in structure to U46619 but lacks the ω-5 hydroxyl group and binds with approximately 10-fold lower affinity to AnSt-D7L1 , further demonstrating the importance of this functionality in binding . The sequences of the N-terminal domains of two-domain D7 proteins from all mosquitoes show a high degree of sequence conservation , particularly with regard to residues lining the binding pocket that are involved with ligand binding . Tyrosine-phenylalanine polymorphism at the equivalent of AnSt-D7L1 position 52 is found in both anopheline and culicine D7s . This suggests that mosquito salivary secretions contain D7 protein forms that bind both CysLTs and TXA2 , as well as forms that bind only CysLTs , and that there may be an adaptive significance to differences in TXA2 binding observed in AeD7 and AnSt-D7L1 . Limitation of mast cell responses in host skin is essential for successful blood feeding , and scavengers of small-molecule mediators are apparently present in saliva to accomplish this task . Immediate cutaneous reactions to mosquito bites lead to release of histamine and LTC4 , potent mediators of acute allergic processes and inflammation [36] . Leukotrienes are produced by activated mast cells , stimulated leukocytes , endothelial cells , and epithelial cells through conversion of AA to 5-HPETE catalyzed by 5-lipoxygenase [24] , [37] , [38] . The most physiologically active leukotrienes are LTB4 and the CysLTs . LTC4 , the primary CysLT product , is secreted by cells and converted extracellularly to LTD4 and LTE4 by successive cleavages of its glutathione moiety . In human skin it has been demonstrated that intradermal injection of nanomolar amounts of LTC4 , LTD4 , and LTE4 are able to elicit erythema and wheal formation [36] , [39] . Although CysLTs promote smooth muscle contraction [24] , [26] and consequent vasoconstriction in other tissues such as the pulmonary vasculature [25] , they elicit a vasodilatatory response in human skin , increasing blood flow in a manner similar to histamine [40] , [41] . Moreover , CysLTs , as well as histamine , cause increased vascular permeability and interstitial transport in the skin , favoring edema formation [36] , [42] . The CysLT receptors , CysLT1 and CysLT2 , are distributed in numerous tissues . In some endothelial populations , CysLT1 is much more abundant than CysLT2 and has affinities for LTD4 and LTC4 of approximately 1 nM and 10 nM , respectively . CysLT2 binds both LTC4 and LTD4 with an affinity of approximately 10 nM , and both receptors bind LTE4 with affinities near 100 nM [24] . The affinities ( ranging from ∼4 to 6 nM ) of AnSt-D7L1 for all the three CysLTs are similar to one another and are equal to or lower than those described for CysLT receptors , making it likely that AnSt-D7L1 can compete with CysLT receptors for ligands if present at sufficient concentration . Unlike the previously described AeD7 , AnSt-D7L1 also binds TXA2 analogs , and evidence from platelet aggregation assays strongly suggests that it binds TXA2 itself . Besides being a potent platelet activation agonist , TXA2 induces smooth muscle contraction in vascular tissue [27] , and like the CysLTs is able to cause itching [43] . Therefore , TXA2 interferes with mosquito feeding by promoting hemostasis ( vasoconstriction and platelet aggregation ) , as well as by causing inflammatory skin responses . Mosquito bites cause injury to the skin , leading to the exposure of collagen present in subendothelial extracellular matrix [44] . Exposed collagen interacts directly or indirectly ( via VWF ) with different receptors present on the platelet surface triggering platelet activation , aggregation , and thrombus formation . Among these receptors is GPVI , a central collagen receptor that is able to bind collagen both in high and low shear conditions , promoting inside out activation of integrin receptors α2β1 and αIIbβ3 , thereby increasing the affinities for their respective ligands , resulting in aggregation of platelets . Activated platelets release granules containing small molecule agonists such as ADP and begin synthesizing TXA2 . These secondary mediators are able to diffuse and activate circulating platelets that do not have contact with collagen , resulting in potentiation of the pro-aggregatory signal and an increase in the size of the platelet plug . Studies comparing the effects of collagen with other GPVI agonists , such as collagen-related peptide ( CRP ) [45] , and platelets lacking protein Gq have shown that ADP and TXA2 are essential for collagen-induced platelet aggregation . The effect of AnSt-D7L1 on collagen-induced aggregation is similar to that obtained when platelets are treated with indomethacin or SQ 29 , 548 , strongly suggesting that this protein is able to scavenge the TXA2 generated in response to collagen exposure . Moreover , similar effects have been shown in previous studies where platelets lacking Gαq and Gα13 , G proteins coupled to TP and to ADP receptors , were exposed to collagen [46] . Binding of TXA2 or its analogs to TP receptors on the platelet surface activates the platelet , leading to shape change followed by aggregation [27] . When the analog U46619 is used to promote aggregation , the presence of AnSt-D7L1 at near equimolar concentrations is enough to completely inhibit the platelet aggregation response . AnSt-D7L1 also abrogates AA-induced aggregation , strongly suggesting that it scavenges TXA2 being produced as a result of stimulation by its biosynthetic precursor . A recently described mutation in the human TP receptor causes platelet dysfunction and lack of responsiveness to AA and U46619 [47] at similar doses as used in the present work and has similar effects as those described here for AnSt-D7L1 . In order for this binding mechanism to be effective in vivo , the protein concentration must be sufficient to remove a large fraction of the eicosanoid ligand from the feeding site . Calvo et al . [14] have estimated the quantities of a biogenic amine-binding protein that is necessary to accomplish this task to be 0 . 03–0 . 3 µg per feeding site . Mosquito salivary glands contain approximately 1–3 µg of protein , and a mosquito injects about half of this protein during a single feeding . Injection of 1 nmol of CysLT at a concentration of 50 µM into a small site on the skin has been shown to result in the appearance of large erythemas measuring over 20 mm in diameter and persisting for many hours [36] . The far less severe response to mosquito feeding suggests that the CysLT concentrations at the feeding site would be much lower than this . Likewise , the data presented here indicate that a concentration of AnSt-D7L1 of 0 . 03 µM is sufficient to remove a significant fraction of the TXA2 secreted by platelets in response to collagen stimulation and that 0 . 1 µM eliminates most of the aggregation response ( Figure 5 ) . This would suggest that the TXA2 concentration in uniformly activated platelet-rich plasma is near 0 . 1 µM . Based on the size of a blood meal , Calvo et al . [14] estimate the feeding volume of a mosquito to be maximally 10 µL , and considering the relative concentration of two-domain D7 proteins in the salivary secretion of An . gambiae [48] , it appears that approximately 5–10 ng of these two-domain proteins are injected during a single feeding period , giving a final concentration of approximately 0 . 1 µM in the feeding volume . The highly expressed single-domain D7 proteins in Anopheles species are known to bind biogenic amine ligands including serotonin , norepinephrine , and histamine . Comparisons of these sequences with the C-terminal domains of the two-domain D7s from culicine species show a high degree of sequence conservation of the residues directly involved with ligand binding ( Figure 1; [15] ) The crystal structures of AeD7 ( two-domain ) from Ae . aegypti and D7r4 ( one-domain ) from An . gambiae also show very similar binding modes for biogenic amine ligands , with most hydrogen bonding interactions being highly conserved between the two . Phylogenetic analyses of D7 sequences suggest that the two-domain forms are ancestral and that the single domain proteins found in both culicine and anopheline mosquitoes are derived from an apparent duplication of the C-terminal domain of a two-domain D7 protein [14] . In culicine mosquitoes , the function of the single-domain proteins is not known , but a lack of conservation of residues involved with biogenic amine binding suggests that biogenic amines are not the target ligand [16] . Sequence comparisons of apparently orthologous two-domain D7s from culicine and anopheline species initially suggested that the C-terminal domain of the anopheline proteins lack some important determinants of biogenic amine binding , while maintaining a high overall degree of similarity with the culicine forms . The work presented here shows that the biogenic amine binding function has indeed been lost in the anopheline proteins and that the loss of function is due to rearrangements that dramatically affect the structure of the binding pocket . The loss of α-helix B2 that is found in both AeD7 and D7r results in Arg 177 taking on a different conformation in AnSt-D7L1 . Along with the bulky side chain of Trp 173 , Arg 177 fills most of what would be the biogenic amine binding pocket in the D7 forms that bind these ligands ( Figure 9A , B ) . Two crystal forms of AnSt-D7L1 are described in this study . The orthorhombic form is obtained in the absence of eicosanoid ligands , while the monoclinic form is obtained in their presence . In the two forms , the structure of the C-terminal domain binding pocket region is nearly identical ( Figure S4 ) , indicating that interactions in the crystal play no role in producing these differences between AnSt-D7L1 and AeD7 . It appears that the cluster of single-domain D7 proteins in anopheline mosquitoes has taken over the function of the C-terminal domain of the two-domain D7s of culicine ( Aedes and Culex ) mosquitoes , making it unnecessary for AnSt-D7L1 and other anopheline forms to maintain the biogenic amine-binding function . Apparently , another function has been acquired by the C-terminal domain of these proteins that may be entirely unrelated to the binding of small-molecule ligands . This case seems to be an example of extensive duplication of salivary protein genes allowing structural and functional diversification within protein families . The D7 protein family represents a case where a duplication of one domain of an ancestral two-domain protein to form a one-domain form has allowed the ancestral protein to lose its original function and almost certainly acquire a new one . We are currently working to determine the more recently acquired function of the C-terminal domain in this group of proteins .
UltraPure guanidinium hydrochloride was obtained from Invitrogen . L-arginine , serotonin , norepinephrine , histamine , ADP , PMA , and indomethacin were obtained from Sigma-Aldrich . All leukotrienes and prostaglandins as well as U46619 , carboxyclic TXA2 , TXB2 , U51605 , AA ( for ITC experiment ) , PAF , and SQ 29 , 548 were obtained from Cayman Chemical . Native collagen fibrils ( type I ) from equine tendons , AA , and ristocetin used in platelet experiments were purchased from Chrono-Log Corporation . Convulxin and RPAI1 were prepared as described previously [22] , [49] . The AnSt-D7L1 cDNA , minus its signal sequence , was cloned into the expression vector pET17b and was expressed in BL21 ( DE3 ) pLysS cells grown for 3 h after induction with 1 mM IPTG [50] . After expression , inclusion bodies were washed in Triton X-100 as previously reported [50] and denatured in 100 mL of 6 M guanidinium HCl and 20 mM Tris-HCl pH 8 . 0 containing 10 mM DTT . This solution ( 50 mL ) was refolded by adding dropwise to 4 L of 0 . 3 M L-arginine in 50 mM CAPS buffer pH 10 . 0 . The solution was stirred for 1 h at 25°C and transferred to 4°C overnight . The protein was concentrated and purified by gel filtration chromatography on Sephacryl S-100 , followed by anion exchange chromatography on SP sepharose . The protein was further purified by a final step of gel filtration chromatography on Superdex 75 . Purity was assessed by SDS-PAGE ( Figure S5 ) . AnSt-D7L1 was prepared for ITC experiments by dialysis against 20 mM Tris-HCl 0 . 15 M NaCl pH 7 . 4 for 1 h . Binding experiments were performed on a MicroCal VP-ITC instrument . Aliquots of lipid stock solutions in ethanol or methyl acetate were dried under a stream of nitrogen in a glass vial , then dissolved in 20 mM Tris HCl , 0 . 15 M NaCl pH 7 . 4 , vortexed , and sonicated for 8 min . Non-lipidic ligands were dissolved in 20 mM Tris HCl , 0 . 15 M NaCl pH 7 . 4 . All solutions were degassed prior to use . Assays were performed at 35°C with successive 10 µL injections , with a spacing interval of 180 s and a syringe stirring speed of 290 rpm . In all the cases , after subtraction of the heats of dilution , the measured heats were converted to enthalpies and analyzed by fitting to a single-site binding model using the Microcal Origin software . Guinea pig ileum contraction in response to LTC4 was measured isotonically with an initial load of 1 . 0 g tension , and rat aorta ring contraction in response to U46619 was measured isometrically after a distension of 2 . 5 g . Tissue preparations were bathed in modified Tyrode solution ( with 10 mM HEPES buffer , pH 7 . 4 ) during the course of the experiment , and the solutions were kept oxygenated by bubbling air into the bath [51] . Platelets were prepared as described previously [52] . Human platelet-rich plasma ( ∼2×105/µL final density ) and Tyrode-BSA buffer [52] in the presence or absence of AnSt-D7L1 ( final volume 300 µL ) were placed in an aggregometer [52] and stirred at 1 , 200 rpm at 37°C for 1 min prior to the addition of different agonists . In experiments using the human TP ( TXA2 receptor ) antagonist SQ 29 , 548 or made in the presence of proteins ( AnSt-D7L1 or RPAI-1 ) , those compounds were added to the platelet suspension and Tyrode mix prior to addition of agonists . In experiments in which indomethacin , a general cycloxygenase inhibitor , was used , platelets were pre-incubated with the compound for 5 min prior to addition of agonists . AnSt-D7L1 was crystallized using the hanging drop vapor diffusion method from 0 . 1 M Tris pH 8 . 5 , 0 . 2 M lithium sulfate , 30% PEG 3000 . The crystals were frozen for data collection in the crystallization buffer described above , containing 10% glycerol . To prepare a selenomethionine derivative of AnSt-D7L1 , the expression plasmid construct was transformed into BL834 ( DE3 ) pLysS cells and grown in SelenoMet media ( Molecular Dimensions Ltd . ) as per the manufacturer's instructions . In order to obtain crystals with the protein bound to its ligands , either LTC4 or U46619 prepared in 10 mM Tris-HCl pH 8 . 0 buffer was pre-incubated with AnSt-D7L1 for 10 min but in a 1 . 3 molar excess when compared to the protein concentration . Prior to data collection , the crystals were frozen using the cryoprotectant described above . Data collection was performed at beamlines 22-BM at the Southeast Regional Collaborative Access Team ( SER-CAT ) and 19-BM of the Structural Biology Center ( SBC ) , Advanced Photon Source ( APS ) , Argonne National Laboratory . Crystals of the ligand-free form of the protein belong to the space group P212121 and contain one monomer per asymmetric unit ( Table 1 ) . Crystals of the LTC4 and U46619 complexes belong to the space group P21 and also contain one monomer per asymmetric unit . Four data sets were collected from a ligand-free selenomethionine crystal ( 2 . 00 Å resolution ) , a ligand-free crystal ( 1 . 77 Å resolution ) , a U46619-complexed co-crystal ( 1 . 45 Å resolution ) , and a LTC4-complexed co-crystal ( 1 . 43 Å resolution ) . The structure of AnSt-D7L1 was determined using a combination of single wavelength anomalous dispersion ( SAD ) methods with data collected at the selenium absorption edge , and molecular replacement using the N-terminal domain of AeD7 from Ae . aegypti as the search model ( Table 1 ) [15] . The data were indexed , integrated , and scaled using HKL2000 or HKL3000 [53] . Initial phases were obtained from the selenium data using SHELX-C , D , and E [54] , [55] . After molecular replacement using PHASER [56] with the selenomethionine data set , a model of the N-terminal domain of AnSt-D7L1 was refined using REFMAC [57] including the phase information from the SAD experiment . After this procedure , electron density for some of the helical segments in the C-terminal domain could be observed , allowing manual building of this portion of the model in Coot [58] . The complete model was refined using REFMAC [57] , with a TLS model being applied in the later stages utilizing a single TLS group [57] . The structures of the ligand complexes were determined by molecular replacement using PHASER , with the ligand-free protein as a search model [59] . The structures were rebuilt using Coot and refined using REFMAC . Since little electron density was observed for the peptidyl portion of LTC4 , the ligand was modeled as only its lipid portion , 5 ( S ) -hydroxy- ( E , E , Z , Z ) -7 , 9 , 11 , 14-eicosatetraenoic acid . The structures of ligand-free AnSt-D7L1 ( 3NGV ) , its U46619 complex ( 3NHT ) , and its LTC4 complex ( 3NHI ) have been deposited with the RCSB protein data bank . | When feeding , a female mosquito must inhibit the blood clotting and inflammatory responses of the host . To do this , the insect produces salivary proteins that neutralize key host molecules participating in clotting and inflammation . Here , we describe a salivary protein AnSt-D7L1 that scavenges both thomboxane A2 and cysteinyl leukotrienes , two substances involved in blood vessel constriction , platelet aggregation , and inflammatory responses to an insect bite . We produced this protein in bacteria and showed that it tightly binds both these molecules , inhibiting the processes in which they are involved . We then determined its structure using X-ray crystallography and showed that there is a single binding site in one domain of the protein , accommodating both thromboxane A2 and cysteinyl leukotrienes , and that this site is responsible for the scavenging effect of the protein . These studies reveal the structural features of proteins needed to bind to key molecules of potential pharmacological importance and add to our understanding of the process of mosquito blood feeding , which is essential for transmission of the malaria parasite . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [
"biochemistry/protein",
"chemistry"
] | 2010 | The Function and Three-Dimensional Structure of a Thromboxane A2/Cysteinyl Leukotriene-Binding Protein from the Saliva of a Mosquito Vector of the Malaria Parasite |
Recent studies have shown that virally encoded mRNA sequences of genome maintenance proteins from herpesviruses contain clusters of unusual structural elements , G-quadruplexes , which modulate viral protein synthesis . Destabilization of these G-quadruplexes can override the inhibitory effect on self-synthesis of these proteins . Here we show that the purine-rich repetitive mRNA sequence of Epstein-Barr virus encoded nuclear antigen 1 ( EBNA1 ) comprising G-quadruplex structures , limits both the presentation of MHC class I-restricted CD8+ T cell epitopes by CD11c+ dendritic cells in draining lymph nodes and early priming of antigen-specific CD8+ T-cells . Destabilization of the G-quadruplex structures through codon-modification significantly enhanced in vivo antigen presentation and activation of virus-specific T cells . Ex vivo imaging of draining lymph nodes by confocal microscopy revealed enhanced antigen-specific T-cell trafficking and APC-CD8+ T-cell interactions in mice primed with viral vectors encoding a codon-modified EBNA1 protein . More importantly , these antigen-specific T cells displayed enhanced expression of the T-box transcription factor and superior polyfunctionality consistent with the qualitative impact of translation efficiency . These results provide an important insight into how viruses exploit mRNA structure to down regulate synthesis of their viral maintenance proteins and delay priming of antigen-specific T cells , thereby establishing a successful latent infection in vivo . Furthermore , targeting EBNA1 mRNA rather than protein by small molecules or antisense oligonucleotides will enhance EBNA1 synthesis and the early priming of effector T cells , to establish a more rapid immune response and prevent persistent infection .
The interaction of a peptide-MHC class I ( pMHC-I ) complex on antigen presenting cells ( APCs ) with a T cell receptor ( TCR ) on CD8+ T cells , initiates the activation of antigen-specific CD8+ T cells [1] . Recent in vitro studies from many groups have revealed that endogenously processed MHC class I-restricted epitopes are predominantly generated from rapidly degraded defective ribosomal products ( DRiPs ) rather than from the degradation of full-length , stable viral proteins [2] , [3] , [4] , [5] , [6] . This process suggests that by regulating the production of antigen or DRiPs in host cells during viral infection we could beneficially influence the generation and presentation of MHC class I-restricted epitopes and the induction of antigen-specific immune responses . Indeed , earlier studies by Ryan and colleagues have shown that the magnitude of CD8+ T cell activation during mycobacterial infection is determined by the level of antigen first encountered by naïve T cells [7] . Furthermore , modulation of antigen expression by slowly replicating pathogens may facilitate their persistence by delaying the development of acquired immune responses [8] , [9] . Epstein-Barr virus ( EBV ) is a classic example of a persistent infection in which down-regulation of viral protein synthesis limits antigen presentation to CD8+ T cells through the MHC class I pathway . EBV encoded nuclear antigen 1 ( EBNA1 ) is a critical viral genome maintenance protein expressed in all EBV-associated malignancies . Constraints on EBNA1 self-synthesis limit the presentation of T cell epitopes on the surface of virus-infected cells [10] , [11] . Extensive studies have shown that this restricted presentation is due in part to an internal glycine-alanine repeat ( GAr ) domain within EBNA1 [12] , [13] , [14] . Although it has been reported that the GAr encoded domain impedes translation of the EBNA1 mRNA [6] , [15] , [16] , [17] , [18] , [19] , [20] , the mechanism causing this has remained unclear . There are reports that the EBNA1 GAr polypeptide sequence delays the initiation of EBNA1 mRNA translation [15] , [21] . However , other studies have clearly demonstrated that the purine-rich , GAr mRNA structure limits EBNA1 synthesis , resulting in decreased presentation of EBNA1 to specific CD8+ T cells [19] , [22] . Indeed , recent studies from our group have revealed that the GAr mRNA includes cis-regulatory , G-quadruplex structures that inhibit EBNA1 synthesis and thereby modulate the endogenous presentation of EBNA1-specific CD8+ T cell epitopes [23] . Considering the importance of CD8+ T cells in controlling primary and latent EBV infection , we hypothesized that the translational efficiency of the EBNA1 mRNA may also influence the priming of antigen-specific T cells in vivo . To test this hypothesis we used two sequences of the EBNA1 gene encoding identical proteins but with differential rates of translation of their respective mRNAs to assess the impact of translational efficiency on the induction of effector and memory CD8+ T cell responses . A native EBNA1 GAr mRNA inhibits translation due to the presence of G-quadruplex structures , whilst a codon-modified EBNA1 GAr mRNA enhances translation due to destabilization of the G-quadruplex structures [23] . These studies demonstrated that the translational efficiency of the EBNA1 mRNAs directly correlated with the MHC class I antigen presentation in vivo and early priming of antigen-specific effector CD8+ T cells , while the generation of a memory T cell response was not impacted . Furthermore , the translational efficiency of EBNA1 mRNAs also impacted on the functional profile of antigen-specific effector CD8+ T cells , suggesting that changes in their activation are likely related to the amount of antigen available .
To determine the impact of EBNA1 mRNA translational efficiency on MHC class I-restricted antigen presentation in vivo , we constructed both EBNA1-pcDNA3 ( Fig . 1A–B ) and adenoviral EBNA1-GFP expression vectors ( Fig . 1C–D ) to generate mRNAs with differential translational efficiency but encoding identical proteins . These EBNA1 vectors were designed to express either 400 nucleotides of a native GAr mRNA ( E1-GArN and Ad-E1-GArN ) or 400 nucleotides of a codon-modified GAr mRNA ( E1-GArM and Ad-E1-GArM ) . In addition , we also generated two additional adenoviral EBNA1-GFP expression vectors encoding full-length EBNA1 ( Ad-E1-GFP; Fig . 1E ) or EBNA1 with a deleted GAr domain ( Ad-E1-ΔGAr-GFP; Fig . 1F ) . The above EBNA1 adenoviral expression vectors all demonstrated similar adenovirus transduction efficiencies ( Table S1 ) . To assess the endogenous loading of MHC class I molecules , the adenoviral EBNA1-GFP expression constructs also encoded a model H-2kb- restricted CD8+ T cell epitope SIINFEKL , comprising OVA257–264 from the ovalbumin protein . Recent studies by our group have demonstrated that the native purine-rich EBNA1 GAr mRNA contains G-quadruplexes and these structures have been shown to inhibit EBNA1 self-synthesis [23] . Following codon-modification to reduce this purine-bias we demonstrated that destabilization of the RNA G-quadruplex structures resulted in enhanced EBNA1 synthesis [19] , [22] ( Fig . 1G ) . Initially , we challenged C57BL/6 mice with Ad-E1-GArN-GFP or Ad-E1-GArM-GFP . Two days post-infection , CD11c+ DCs were enriched from draining inguinal lymph nodes and incubated with B3Z T cells , a CD8+ T cell hybridoma cell line that expresses lacZ upon activation of its SIINFEKL-specific T cell receptor ( Fig . 2A ) . CD11c+ DCs isolated from mice infected with Ad-E1-GArM-GFP , the more efficiently translated EBNA1 mRNA , demonstrated a significantly higher level of ex vivo presentation of the H-2Kb-restricted SIINFEKL epitope ( Fig . 2 , B–C ) , which remained consistent at different effector to target ratios ( Fig . 2C ) . These observations indicated that the translation efficiency of viral mRNAs could influence the in vivo presentation of CD8+ T cell epitopes by professional antigen presenting cells . To further delineate the potential impact of viral mRNA translational efficiency on the modulation of CD8+ T cell immunity in vivo , we used confocal imaging of draining lymph nodes to visualize the interaction of antigen presenting cells with SIINFEKL-specific CD8+ T cells and the recruitment of these effector cells . CFSE-labeled CD8+ OT-1 T cells were adoptively transferred into C57BL/6 mice two hours prior to infection with adenoviral expression vectors Ad-E1-GArN-GFP encoding native EBNA1 , or Ad-E1-GArM-GFP encoding codon-modified EBNA1 . Draining lymph nodes were harvested on day 2 for frozen section and stained with anti-CD11c , anti-H-2Kb-SIIN ( 25-D1 . 16 ) and DAPI . Mice infected with the vector encoding native EBNA1 , demonstrated a significantly reduced number of CFSE+CD8+ OT-1 cells and H-2Kb-SIIN+ APCs in draining lymph nodes when compared to mice infected with the vector encoding codon-modified EBNA1 which generates a faster translating EBNA1 mRNA due to destabilization of the native G-quadruplex structures ( Fig . 3A–D ) . Additionally , we observed that mice infected with the vector expressing native EBNA1 also demonstrated a significantly lower number of H-2Kb-SIIN+ APCs within 3 µm distance of CFSE+CD8+ OT-1 cells compared to mice challenged with the vector expressing the codon-modified EBNA1 , suggesting enhanced interactions between APC and CD8+ T cells in mice immunized with a vector encoding a codon-modified EBNA1 ( Fig . 3E–G ) . These observations further emphasize the critical role of translational efficiency of viral mRNAs in not only modulating antigen presentation in vivo but also influencing the number of effector T cells and in the interaction of APCs and antigen-specific T cells in draining lymph nodes . Having established a direct impact of mRNA translational efficiency on in vivo antigen presentation , APC-T cell interactions and antigen-specific T cell numbers in draining lymph nodes , we next assessed the impact of differential translation efficiency on antigen-specific CD8+ T cell proliferation and activation . C57BL/6 mice were adoptively transferred with CFSE-labelled CD8+ OT-1 cells ( 5×106 cells/mouse ) and subsequently challenged with Ad-E1-GArN-GFP or Ad-E1-GArM-GFP ( 1×106 or 1×108 pfu/mouse ) . Mice were sacrificed on days 2 and 3 post-infection and the proliferation , activation and functional properties of the adoptively transferred OT-1 cells were evaluated from draining inguinal lymph nodes . Proliferation of OT-1 cells was significantly lower in mice challenged with an adenoviral vector encoding native EBNA1 , Ad-E1-GArN-GFP , ( Fig . 4A–C ) . Interestingly , the kinetics of proliferation of these effector cells correlated with the dose of viral infection . We confirmed these results by infection with a full-length native EBNA1-GFP adenoviral expression construct , Ad-E1-GFP , which also showed low T cell proliferation , whilst infection with an adenoviral EBNA1-GFP expression vector where the GAr was deleted , Ad-E1-ΔGA-GFP , resulted in enhanced proliferation of antigen-specific CD8+ T cells ( data not shown ) . As the ( IL-2/IL-2R ) pathway is crucial for T-cell activation , proliferation and differentiation [24] , [25] we next assessed the expression of IL-2 receptors on CD8+ T cells . Antigen-specific CD8+ T cells from mice challenged with an adenoviral vector encoding codon-modified EBNA1 , Ad-E1-GArM-GFP , led to a significantly higher proportion of these cells being CD25+ ( IL-2Rα ) and CD122+ ( IL-2Rβ ) ( Fig . 4D ) . In addition , as CD27 plays a pivotal role in the generation , maintenance and differentiation of cytotoxic T lymphocytes [26] , [27] , the expression of CD27 was also assessed and we observed that the majority of SIINFEKL-specific CD8+ T cells isolated from mice challenged with an adenoviral vector encoding codon-modified EBNA1 , Ad-E1-GArM-GFP , were also CD27+ ( Fig . 4D ) , suggesting that T cells primed with this vector are less differentiated and are more likely to respond to IL-2 . Consistent with the data presented above , we also observed a significant difference in the activation profile of SIINFEKL-specific CD8+ T cells . Mice infected with an adenoviral vector encoding EBNA1 with a codon-modified GAr domain , Ad-E1-GArM-GFP , demonstrated a significantly higher proportion of activated antigen-specific CD8+ T cells ( Fig . 5 ) . These T cells included CD44+CD62L−CD69− and CD44+CD62L−CD69+ populations . Interestingly , mice infected with an adenoviral vector encoding EBNA1 with a native GAr domain , Ad-E1-GArN-GFP , showed a significantly higher number of CD44−CD62L+CD69− antigen specific T cells in the DLNs , further emphasizing the impact of G-quadruplex structures on the activation of T cells in vivo ( Fig . 5 ) . It should be noted that the kinetics of T cell activation correlated with the dose of viral infection . Infection with high doses of adenoviral vectors ( 1×108 pfu/mouse ) was co-incident with early activation of antigen-specific T cells ( day 2 ) , while the peak of activation in mice challenged with a lower dose of virus ( 1×106 pfu/mouse ) was not observed until day 3 ( Fig . 5 ) . Previous reports have demonstrated that the T-box transcriptional factors , T-bet and Eomesodermin ( Eomes ) , play crucial roles in regulating T cell differentiation and function including expression of cytokines and cytotoxicity [28] , [29] , [30] , [31] . Ex vivo analysis of SIINFEKL-specific effector T cells demonstrated that mice infected with Ad-E1-GArM-GFP showed significantly higher levels of T-bet expression on days 2 and 3 post-infection compared to mice infected with Ad-E1-GArN-GFP ( Fig . 6A–B ) . In contrast , the levels of Eomes in antigen-specific effector T cells were not significantly different in mice infected with Ad-E1-GArM-GFP or Ad-E1-GArN-GFP ( Fig . 6A–B ) . To investigate further the potential impact of T-bet expression , we assessed the polyfunctional potentiality of antigen-specific T cells . For these analyses , T cells from draining lymph nodes were stimulated in vitro with SIINFEKL peptide and assessed for expression of the anti-viral cytokines IFNγ and TNFα and the cytotoxicity degranulation marker CD107 . T cells from the Ad-E1-GArM-GFP-infected mice displayed significantly higher polyfunctional potentiality ( IFNγ+ , TNFα+ and CD107α+ or IFNγ+ and CD107α+ ) when compared to Ad-E1-GArN-GFP-infected mice ( Fig . 6C ) . Similarly , infection with Ad-E1-ΔGA-GFP , where the GAr domain has been deleted resulting in improved translation of the E1-ΔGA-GFP mRNA , also showed significantly enhanced expression of activation markers ( Fig . 6D ) and polyfunctional antigen-specific T cells ( Fig . 6E ) compared to infection with Ad-E1-GFP , a construct expressing full-length native EBNA1 . Mice infected with a control recombinant EBNA1-GFP expression vector not encoding SIINFEKL showed no antigen-specific T cell responses when stimulated in vitro with SIINFEKL peptide ( Fig . S1 ) . To confirm that these results were not due to an artifact of adoptive T cell transfer , we repeated these studies in C57BL/6 mice without cell transfer . Naïve mice were challenged with Ad-E1-GArN-GFP or Ad-E1-GArM-GFP and the expression of early activation markers and polyfunctional potentiality of primary SIINFEKL-specific effector T cells were assessed on day 7 using an H-2Kb-SIIN pentamer . Similar to the results demonstrated in the adoptive T cell transfer setting , we observed a significantly higher proportion of T cells from naïve C57BL/6 mice infected with Ad-E1-GArM-GFP , which were of the activated phenotype CD44+CD69+CD62L− and which displayed polyfunctional potentiality compared to the T cells from naïve C57BL/6 mice infected with Ad-E1-GArN-GFP ( Fig . 7A–B ) . We also investigated whether the impact of mRNA translational efficiency on an early effector T cell response also extends to the generation and establishment of a memory response . C57BL/6 mice were challenged with Ad-E1-GArN-GFP and Ad-E1-GArM-GFP and SIINFEKL-specific CD8+ T cell responses were assessed on days 14 and 28 . Antigen-specific T cells from mice infected with Ad-E1-GArN-GFP and Ad-E1-GArM-GFP demonstrated similar levels of activation markers ( Fig . 8 ) . Furthermore , these T cells also showed comparable levels of the T-box transcription factors T-bet and Eomes and a similar capacity to express IFNγ following stimulation with SIINFEKL peptide . Taken together , these data clearly demonstrate that the native EBNA1 GAr mRNA comprising G-quadruplex structures limits the availability of peptide/MHC complexes on the cell surface of antigen presenting cells and selectively impacts on the functional quality of an early antigen-specific T cell response in vivo .
Although the innate immune response is crucial in controlling early stages of viral infection , rapid priming of an effective adaptive cellular immune system can determine the outcome of primary viral infection [32] , [33] . In particular , recruitment of virus-specific CD8+ T cells and their maturation as effector cells is achieved through an interaction between T-cell receptors and MHC class I-peptide complexes on professional antigen presenting cells [34] . Following activation , these effector T cells scan the surface of virus-infected cells to detect viral peptides bound to MHC class I molecules and eliminate these cells either by direct lysis or by secreting cytokines/chemokines [35] . To counter this effector mechanism , viruses have evolved multiple strategies to limit the endogenous processing and presentation of viral peptides [36] , [37] . Indeed , human herpes viruses including EBV , which are known to establish persistent infection , have developed specific strategies to suppress the expression of immunodominant antigens [38] , [39] . While limiting the supply of viral peptides by controlling the synthesis of viral proteins can prevent T cell recognition , this strategy can also impact on viral fitness and compromise the ability of viruses to establish persistent infection [40] . EBV-encoded EBNA1 is a good example of a viral protein , which has successfully evolved unique strategies to overcome this dilemma . This protein includes an internal glycine-alanine repeat domain that not only limits self-synthesis but also blocks proteasomal degradation [6] , [13] . While restricted expression of this protein limits the availability of peptide epitopes , the blockade of degradation provides sufficient protein for maintenance of the viral genome in virus-infected B cells . A number of studies published over the last decade have shown that in spite of the inhibitory effect of the internal GAr domain , CD8+ T cell responses directed towards EBNA1 can be readily detected in EBV seropositive individuals [2] , [3] , [41] . This paradox was resolved following extensive in vitro molecular analysis of the endogenous processing of EBNA1 which showed that CD8+ T cell epitopes from this protein were predominantly generated from newly synthesized RDPs rather than from the long-lived pool of stable EBNA1 in EBV-infected B cells [2] , [3] , [6] , [15] , [17] , [19] , [21] , [22] , [40] . These observations have subsequently been further extended to demonstrate that the generation of RDPs is intrinsically linked to the rate at which proteins are synthesized [17] . It has been reported that EBNA1 with its native GAr domain generates RDPs less efficiently compared to EBNA1ΔGA , which is more efficiently synthesized [20] . As a consequence , CD8+ T cell epitopes generated from EBNA1ΔGA were more efficiently processed and cells expressing EBNA1ΔGA were lysed in vitro at higher levels by EBV-specific CTLs compared to cells expressing a poorly translated full-length EBNA1 . Based on these observations , we hypothesized that an EBNA1 GAr-mediated inhibitory effect on mRNA translation and RDP generation may be one of the crucial mechanisms by which EBV modulates the kinetics of antigen presentation and the priming of virus-specific CD8+ T cell responses in vivo . Indeed , it has been recently revealed that the EBNA1 GAr mRNA exploits G-quadruplex structure to inhibit translation elongation by impeding ribosome transit , thereby down-regulating EBNA1 synthesis and limiting the availability of peptide epitopes . The identification of inhibitory G-quadruplex structures within EBNA1 has helped elucidate an important EBNA1 translational regulatory mechanism . Earlier studies had proposed that the GAr peptide sequence may interfere with translation initiation to down-regulate EBNA1 synthesis [15] , however toe-printing experiments performed by the Shastri group demonstrated that inhibition of EBNA1 synthesis was most likely not due to interference of translation initiation [20] . Results from recent EBNA1 polysome profiling experiments demonstrated that G-quadruplex structural elements within the EBNA1 GAr mRNA act as steric blocks to cause a stalling/dissociation of ribosomes [23] . This result confirmed previous findings that reducing the purine-bias within the EBNA1 GAr mRNA through codon-modification , whilst maintaining the encoded protein sequence results in increased EBNA1 mRNA translation [22] , [23] . We have more recently demonstrated that codon-modification of the repeat sequence leads to destabilization of the G-quadruplex structures within the GAr , which in turn leads to increased EBNA1 mRNA translation . In the present study , EBNA1 variants displaying distinct translational efficiencies for their respective native or codon-modified mRNAs have been used to assess the influence of mRNA translational efficiency on both in vivo antigen presentation and priming of virus-specific CD8+ T cell responses . Comparison of the ex vivo antigen presentation by CD11c+ DCs from the DLNs of mice infected with adenoviral vectors encoding E1-GArN-GFP or E1-GArM-GFP revealed that CD8+ T cell epitopes from these proteins were differentially presented on the cell surface and this presentation correlated with their translational efficiency . These observations extend previously published data on the impact of translational efficiency on T cell recognition of EBNA1 expressing virus-infected cells in vitro . While EBNA1 mRNA in humans is primarily expressed in B cells in vivo , previous studies have suggested that dendritic cells may play an important role in the priming of naïve T cells , which recognize EBV latent antigens [42] , [43] . This dendritic cell-mediated priming may be mediated through either direct infection of these cells with EBV [44] , [45] , [46] or through cross-presentation [47] . Having established that mRNA translational efficiency is intrinsically linked to in vivo antigen presentation by professional APCs , we further demonstrated the impact of mRNA translational efficiency on CD8+ T cell priming by ex vivo imaging of draining lymph nodes which showed enhanced antigen-specific T cell-APC interactions in mice infected with an adenoviral vector expressing a rapidly translated EBNA1 mRNA ( Ad-E1-GArM-GFP ) . More importantly , these antigen-specific T cells displayed superior polyfunctionality and increased expression of the T-box transcription factor , T-bet . Earlier studies , primarily in animal models , have demonstrated the critical role of T-box transcription factors in regulating effector function and the establishment of CD8+ T cell memory . Thus antigen-specific T cells with high T-bet expression display long-term resilience and protection from CD8+ T cell exhaustion . Recent studies have demonstrated that the level of T-bet expression in virus-specific CD8+ T cells is associated with the efficiency of endogenous antigen presentation , clonal expansion and the phenotypic and functional profiles of antigen-specific T cells [48] . Data presented in this study further extend these observations and provide evidence for a potential link between mRNA translational efficiency and antigen presentation in vivo and its impact on the functional programming of effector T cells . We note that in spite of a dramatic impact of mRNA translational efficiency on early priming of CD8+ T cells , we observed only a minimal impact on the generation of memory CD8+ T cell responses . The above observations provide an important insight into how persistent viruses like EBV exploit mRNA translational efficiency to modulate antigen presentation in vivo . In such a setting , viruses would restrict early priming of antigen-specific T cells , thereby escaping immune surveillance and allowing the establishment of a successful latent infection . Furthermore , the techniques utilized here may provide a general method to improve the immunogenicity of poorly immunogenic viral proteins which restrict T cell priming by limiting the availability of epitopes on the surface of virus-infected cells . Enhanced mRNA translation through codon-modification can dramatically enhance the endogenous presentation of immunodominant epitopes by professional APCs and induce a strong effector T cell response . We predict that these effector cells will recognize virus-infected cells more efficiently compared to naturally-induced anti-viral T cells . These findings also suggest a novel and alternate platform for designing anti-viral strategies that focus on targeting RNA structure rather than protein within gammaherpesviral ORFs . Such strategies may include antisense oligonucleotides to enhance viral protein synthesis and the early priming of effector T cells , to establish a more rapid immune response and prevent persistent infection .
This study was performed under strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Health and Medical Research Council ( Australia ) . The Animal Ethics Committee of the QIMR Berghofer Medical Research Institute approved the protocol [Protocol approval number: P353 ( A0610-612 ) ] . All viral infections were performed under gaseous ( isoflurane ) anaesthesia and every effort was made to minimize suffering . HEK293 cells were cultured in Dulbecco modified Eagle medium supplemented with 10% fetal bovine serum , 2 mM Glutamax , and 100 IU/ml penicillin-streptomycin . The SIINFEKL-specific CD8+ T-cell hybridoma ( B3Z ) was maintained in RPMI 1640 supplemented with 2 mM L-glutamine ( Gibco , Life Technology ) , 1 mM sodium pyruvate ( Gibco , Life Technology ) , 50 µM 2-mercaptoethanol ( Gibco , Life Technology ) , 100 IU/ml penicillin , and 100 µg/ml streptomycin plus 10% FCS ( R-10 ) . APC-anti-CD3e , PE-Cy7-anti-CD3e , FITC-anti-CD3e , PE-anti-CD8a , PerCp-anti-CD8a , Alex700-anti-CD19 , FITC-anti-CD44 , APC-anti-CD44 , V450-anti-CD44 , PE-anti-IFN-γ , PE-Cy7-anti-TNF-α were purchased from BD Biosciences ( Australia ) ; PE-Cy7-anti-CD25 , FITC-anti-CD27 , APC-anti-CD27 , Alexa647-anti-CD107a , eFluo450-anti-CD122 , PE-anti-T-bet and Alexa700-anti-Eomes and purified anti-mouse MHC I-SIINFEKL complex ( clone 25D ) were purchased from eBioscience ( Jomar Bioscience , Kensington , SA . , Australia ) ; PerCp-Cy5 . 5-anti-CD62L , PE-Cy7-anti-CD69 and purified anti-CD11c were purchased from BioLegend , ( Australian Biosearch , Karrinyup , WA . , Australia ) ; APC-H-2Kb-SIINFEKL pentamer was purchased from ProImmune ( Oxford , UK ) . C57BL/6 mice were purchased from Animal Resource Centre ( Perth , WA , Australia ) . OT-1 mice were bred and maintained under conventional conditions in the animal facility at the Queensland Institute of Medical Research . The Queensland Institute of Medical Research Animal Ethics Committee approved and monitored all animal procedures . Full-length EBV-encoded EBNA1 ( E1 ) , EBNA1 with a deleted GA repeat ( E1-ΔGAr ) , EBNA1 expressing 400 nucleotides of native GAr ( E1-GAr400N ) referred to as E1- ( GArN ) and EBNA1 expressing 400 nucleotides of codon-modified GAr ( E1-GAr400M ) referred to as E1- ( GArM ) had been previously subcloned in-frame with a sequence coding for GFP ( pEGFP-N1; Clontech ) to generate E1-GFP , E1-ΔGAr-GFP , E1-GArN-GFP and E1-GArM-GFP , respectively [2] , [17] . To enable the analysis of endogenous processing of these proteins , a sequence encoding a previously defined H-2Kb–restricted epitope SIINFEKL ( referred to as SIIN ) was inserted into the EBNA1-GFP expression constructs between the 3′ end of the EBNA1 sequence and the start of the GFP sequence . Recombinant adenovirus encoding E1-SIIN-GFP , E1-ΔGAr-SIIN-GFP , E1-GArN-SIIN-GFP and E1-GArM-SIIN-GFP were generated by a highly efficient , ligation-based protocol of Adeno-X System ( Clontech ) [2] , [49] . Briefly , E1-GArN-SIIN-GFP was cloned into the pshuttle plasmid between NheI and XbaI restriction enzyme sites and transformed with dam negative cells ( SCS110 ) . E1-GArM-SIIN-GFP , E1-ΔGAr-SIIN-GFP and E1-SIIN-GFP were all digested with BspE1 and XcmI enzymes and cloned into E1-GArN-SIIN-GFP-pshuttle 2 ( replacing the 400 nucleotides of native GAr sequence with either the full-length GAr , no GAr or 400 nucleotides of codon-modified GAr ) to generate Ad-E1-SIIN-GFP , Ad-E1-ΔGAr-SIIN-GFP , Ad-E1-GArN-SIIN-GFP and E1-GArM-SIIN-GFP , respectively . Viral titers were verified using an end-point dilution assay . The viral infection efficiency of all constructs was assessed with varying dilutions into HEK293 cells and by measuring GFP fluorescence using flow cytometry . EBNA1-pcDNA3 constructs expressing 400 nucleotides of either native or codon-modified GAr ( E1-GArN; E1-GArM ) were transcribed and translated in vitro with T7 RNA polymerase using a coupled transcription/translation reticulocyte lysate system ( Promega , Madison WI ) supplemented with 10 µCi 35[S]-methionine ( Perkin-Elmer Pty Ltd . , Boston , MA . ) . Lysates were subjected to SDS-PAGE followed by autoradiography and band intensities were quantified by densitometric analysis using ImageJ64 software . B3Z is a T-cell hybridoma expressing a TCR that is specifically activated by the Ovalbumin ( 257–264 ) peptide , ( SIINFEKL ) , in the context of H-2Kb . The cells express the beta-galactosidase ( lacZ ) gene under the control of the nuclear factor of activated T-cell ( NF-AT ) element of the interleukin 2 enhancer , thereby allowing the activation of B3Z T-cells to be measured by β-galactosidase activity in single cells [50] . SIINFEKL-expressing EBNA1 transfectants were incubated with B3Z cells at varying effector to target cell ratios for 18 h . B3Z cells were harvested , stained with anti-mouse CD3 and anti-mouse CD8 antibodies , followed by osmotic loading of FDG ( fluorescein di-β-galactoside; Invitrogen ) , as previously described [51] . Briefly , B3Z cells were resuspended in 25 µl staining buffer ( PBS containing 4% FBS and 10 mM HEPES , pH 7 . 2 ) , incubated for 10 minutes at 37°C followed by the addition of 25 µl pre-warmed FDG ( 2 mM in de-ionized water ) . After a further incubation at 37°C for 1 minute , 450 µl ice-cold staining buffer containing 1 µg/ml 7-Aminoactino-mycin D ( 7-AAD ) was added to each sample to stop osmotic loading . Cells were kept on ice until assessment by flow cytometry on a FACSCanto ( BD Biosciences ) . Live B3Z cells ( 7-AAD−CD3+CD8+ cells ) were gated to analyze their activation by measuring intracellular β-galactosidase activity . SIINFEKL-specific B3Z hybridoma cells were used to detect cells presenting SIINFEKL peptide as previously described [50] , [52] . Briefly , C57BL/6 mice were immunized with either E1-GArM-GFP or E1-GArN-GFP at 1×108 pfu/mouse . DLNs were collected 2 days post-infection and DCs enriched from DLNs of immunized mice and incubated with B3Z cells at different ratios overnight in R-10 . The cells were then harvested , loaded with FDG and analyzed for LacZ activity on a FACSCanto . CD8+ T cells were enriched from the spleens of OT-1 mice using a mouse CD8+ T cell isolation kit II ( Miltenyl Biotec Australia ) . The purified CD8+ OT-1 cells were labeled with 0 . 5 µM carboxyfluorescein succinimidyl ester , CFSE , ( Sigma , Mo . USA ) and adoptively transferred intravenously into C57BL/6 mice ( 5×106 cells/mouse ) . Two hours following adoptive transfer , the mice were immunized intramuscularly with either Ad-E1-GArN-SIIN-GFP or Ad-E1-GArM-SIIN-GFP at a dose of 1×108 pfu/mouse ( 3 mice/group ) . Draining inguinal lymph nodes were removed 48 hours later and snap frozen in an optimal cutting temperature ( OCT ) buffer ( ProSci Tech , Qld . Australia ) . Frozen sections ( 7 µm ) were fixed in 75% acetone 25% ethanol for 5 minutes , washed in PBS and blocked with Vector Biotin Blocking kit for 2×10 minutes , followed by 60 min block in Biocare Medical Mouse Block plus donkey anti-mouse Fab fragments . Sections were washed in PBS before a further block in 10% normal donkey serum in PBS for 30 minutes . Slides were stained with anti-CD11c and anti-H2Kb SIIN or isotype control antibodies for 60 min at room temperature followed by biotinylated goat anti-Armenian hamster for 30 min . MACH1 Mouse Probe was applied for 15 minutes . Sections were stained with Alexa donkey anti-rabbit 647 , streptavidin-555 applied for 30 minutes and incubated with DAPI for 10 minutes before mounting with Dako Fluorescent mounting media . Slides were examined on a Zeiss 512 Meta confocal microsope with a ×25 oil emersion objective lens , taking 2 µm Z-sections , or ×60 objective with 2 µm Z-sections . Tiling was used for whole-section imaging . Images for publication were cropped , minimally adjusted for brightness and contrast , and a 3×3 median filter applied using ImageJ and Photoshop . Raw images were analyzed using Imaris 7 . 6 . 4: determining baseline fluorescence parameters from controls , identifying cell types by fluorescence and size , and using spot-analysis to calculate XYZ intercellular distances . Parameters were saved and applied to all images within an experiment to maintain objective consistency . At least 3 fields of view per slide of each mouse were used for data analysis . Experiments were repeated at least twice . Data were exported into Excel and Graphpad Prism for statistical analysis . One-way ANOVA was applied to compare groups , which we considered statistically significant if p<0 . 05 . CD8+ OT-1 T cells were purified from the spleens of OT-1 mice using a mouse CD8a+ T cell isolation kit II ( Miltenyi Biotec Australia , Cat# 130-095-236 ) according to the manufacturer's instruction . The isolated CD8+ OT-1 T cells were then labeled with 5 µM CFSE as previously described [53] and adoptively transferred to female C57BL/6 mice by intravenous injection . Recipient mice were immunized with recombinant adenovirus two hours following adoptive transfer . CD8+ OT-1 T cells were surface stained with APC-H-2Kb-SIINFEKL pentamer for 20 minutes then with anti-CD8a , anti-CD19 before fixation and permeabilization and intracellular staining for IFN-γ and TNF-α . CFSE+CD8+ OT-1 T cells were first surface stained with anti-CD8a and anti-CD3e mAbs , fixed and permeabilized using cytofix/cytoperm ( BD Biosciences , San Diego , CA ) and then labeled with anti-IFN-γ and anti-TNF-α mAbs . Pluripotent CTL responses were evaluated by ICS as previously described [54] . Briefly splenocytes or local draining lymph node ( DLN ) cells were restimulated with SIINFEKL peptide ( 0 . 1 µg/ml ) for 6 hours at 37°C in complete DMEM ( high glucose , Invitrogen , Grand Island , NY , USA ) medium supplemented with 10% FCS , 1 mM sodium pyruvate ( Gibco , Life Technology ) , MEM non-essential amino acids ( Gibco , Life Technology ) , 50 µM 2-mercaptoethanol , 100 U/ml penicillin and 100 U/ml streptomycin ( D-10 ) . Anti-CD107a antibody was added to the culture at the beginning . Brefeldin A and monensin ( BD Biosciences , San Diego , CA ) were added 1 hour later to prevent cytokine release . Cells were harvested after 6 hours for staining . To determine the activation status of T cells after adoptive transfer , splenocytes and local DLN cells were stained with anti-CD8a , anti-CD44 , anti-CD62L , anti-CD69 , anti-CD25 , anti-CD27 and anti-CD122 . In other experiments splenocytes and local DLN cells were stained with APC-H-2Kb-SIINFEKL pentamer for 20 minutes , followed by staining with anti-CD8a , anti-CD19 , anti-CD44 , anti-CD62L , anti-CD69 , or anti-CD25 , anti-CD27 and anti-CD122 . Transcriptional factor expression was determined by intracellular immunofluorescent staining . Cells were first surface stained , then fixed and incubated with anti-T-bet and anti-Eomes antibodies in permeabilization buffer ( eBioscience , Cat# 00-5521 ) before analysis by flow cytometry . For the statistical analysis of the IVT and antigen presentation experiments , a two-tailed paired Student's t test was used . A P-value<0 . 05 was considered significant . | Maintenance proteins of viruses establishing latent infections regulate their synthesis to levels sufficient for maintaining persistent infection but below threshold levels for host immune detection . The Epstein-Barr virus maintenance protein , EBNA1 , has recently been shown to contain unusual G-quadruplex structures within its repeat mRNA that reduces its translational efficiency . In this study we assess how modification of the EBNA1 mRNA repeat sequence to destabilize the native G-quadruplex structures and thereby increase translation , impacts on the activation of EBNA1-specific T cells in vivo . Mice primed with viral vectors encoding a more efficiently translated EBNA1 mRNA revealed increased trafficking of EBNA1-specific T cells , an enhanced functional profile and increased expression of transcription factors providing evidence for a potential link between mRNA translational efficiency and antigen presentation in vivo and the resultant impact on the functional programming of effector T cells . These findings suggest a novel approach to therapeutic development through the use of antisense strategies or small molecules targeting EBNA1 mRNA structure . | [
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"infection"... | 2014 | mRNA Structural Constraints on EBNA1 Synthesis Impact on In Vivo Antigen Presentation and Early Priming of CD8+ T Cells |
Autosomal recessive congenital ichthyosis ( ARCI ) is a rare genetic disorder of the skin characterized by abnormal desquamation over the whole body . In this study we report four patients from three consanguineous Tunisian families with skin , eye , heart , and skeletal anomalies , who harbor a homozygous contiguous gene deletion syndrome on chromosome 15q26 . 3 . Genome-wide SNP-genotyping revealed a homozygous region in all affected individuals , including the same microdeletion that partially affects two coding genes ( ADAMTS17 , CERS3 ) and abolishes a sequence for a long non-coding RNA ( FLJ42289 ) . Whereas mutations in ADAMTS17 have recently been identified in autosomal recessive Weill-Marchesani-like syndrome in humans and dogs presenting with ophthalmologic , cardiac , and skeletal abnormalities , no disease associations have been described for CERS3 ( ceramide synthase 3 ) and FLJ42289 so far . However , analysis of additional patients with non-syndromic ARCI revealed a splice site mutation in CERS3 indicating that a defect in ceramide synthesis is causative for the present skin phenotype of our patients . Functional analysis of patient skin and in vitro differentiated keratinocytes demonstrated that mutations in CERS3 lead to a disturbed sphingolipid profile with reduced levels of epidermis-specific very long-chain ceramides that interferes with epidermal differentiation . Taken together , these data present a novel pathway involved in ARCI development and , moreover , provide the first evidence that CERS3 plays an essential role in human sphingolipid metabolism for the maintenance of epidermal lipid homeostasis .
Autosomal recessive congenital ichthyosis ( ARCI ) is characterized by abnormal desquamation over the whole body due to a dysfunctional skin permeability barrier and an altered lipid composition of the skin . To date , in our collection of about 550 families presenting with ARCI we identified mutations in seven different genes , which can cause non-syndromic forms of ARCI: ABCA12 , ALOXE3 , ALOX12B , CYP4F22 , ICHTHYIN , PNPLA1 , and TGM1 [1]–[6] in about 80% of the patients; the remaining 20% of patients are expected to carry mutations in other genes , which remain to be identified [7] . Here we present a new contiguous gene deletion syndrome affecting the sequences of ADAMTS17 , FLJ42289 , and CERS3 in four patients from three consanguineous families from our collection . The clinical phenotype of the affected individuals partly corresponds to the characteristic manifestation of Weill-Marchesani ( WM ) -like syndrome ( MIM 613195 ) that has been found to be caused by loss-of-function mutations in the ADAMTS17 ( a disintegrin-like and metalloproteinase with thrombospondin type-1 motif 17 ) gene [8] , [9] . However , the present ichthyosis skin phenotype of our patients has never been reported in WM-like syndrome patients , suggesting that mutations in FLJ42289 and/or CERS3 ( ceramide synthase 3 ) could be associated with this unusual form of ARCI . We therefore performed sequence analyses of the affected individuals and functional studies on mutant skin samples and keratinocytes , which were differentiated in vitro . In this way , we were able to characterize a new type of ichthyosis and to provide evidence for the involvement of CERS3 mutations in the development of ARCI in humans .
We performed genome-wide SNP-array based homozygosity mapping in 34 consanguineous families with ARCI including three Tunisian families with a syndromic form of ARCI . The clinical features in the four patients ( D1 , D2 , C , and S ) include collodion membrane at birth evolving to generalized ARCI , but also short stature , brachydactyly with joint stiffness , microspherophakia , ectopia lentis , mitral valve defects , and multiple nevi ( Table 1 , Figure 1 , and Text S1 ) . These patients all shared a homozygous region on chromosome 15q26 . 3 with an identical haplotype in the smallest common interval of 1 . 67 Mb ( Figure 2A ) . Within this region , a homozygous deletion of about 100 Kb was observed between the SNP markers rs1080492 and rs7179355 that encompasses the first three exons of ADAMTS17 , the complete sequence of the non-coding RNA FLJ42289 , and exon 13 of CERS3 including the 3′UTR ( Figure 2B ) . We confirmed the homozygous deletion in these patients using FISH ( Figure 2C ) and array CGH ( comparative genomic hybridization ) analysis ( data not shown ) . A breakpoint spanning PCR followed by sequencing defined the genomic deletion encompassing 106 , 960 bp ( Figure S1 ) . Moreover , sequencing of all exons and exon/intron boundaries of the CERS3 gene showed the absence of PCR amplification of exon 13 and therefore confirmed the genomic deletion in the patients ( D1 , D2 , C , and S ) . ADAMTS17 was not sequenced . One additional Tunisian individual ( H ) with isolated ARCI also showed a homozygous region on 15q26 . 3 , but did not carry the genomic deletion described above ( Figure 2A ) . However , sequencing of the CERS3 gene in this patient revealed a homozygous transversion of guanine to thymine affecting the exon 9 splice donor site ( c . 609+1G>T ) ( Figure 2D ) . To analyze the functional effect of this mutation event we performed reverse transcription of mRNA from patient H isolated from in vitro differentiated keratinocytes followed by PCR amplification of the corresponding CERS3 region using specific primers . Separation by agarose gel electrophoresis as well as sequencing of the PCR fragment demonstrated a reduced length of the PCR product due to skipping of exon 9 resulting in an in-frame deletion of 93 bp in the CERS3 coding transcript ( Figure S2 ) . MutationTaster software calculated a result score of 0 . 999 for a probable disease causing mutation event [10] . In addition , this sequence variation was not found in 96 unaffected population-matched control individuals . To investigate the role of CERS3 mutations in the development of ichthyosis we performed histological and biochemical studies using a skin sample of patient H carrying the splice site mutation in the CERS3 gene . Since we could not exclude that mutations in ADAMTS17 and/or FLJ42289 interfere with skin physiology , we did not include samples from the patients with the gene deletion syndrome in the following experiments . Histological analysis of the skin biopsy from patient H showed acanthosis with thickening of the stratum granulosum , psoriasiform epidermal hyperplasia ( Figure 3A ) , and normal size of the detached stratum corneum ( inset Figure 3A ) . To examine CERS3 distribution in skin we performed immunofluorescence staining of paraffin as well as frozen sections from human control biopsies . Using an antibody targeting an epitope near the N-terminus of CERS3 ( amino acid 59–120 ) we demonstrated that the protein localizes at the interface between the stratum granulosum and the stratum corneum in the epidermis ( Figure 3B and Figure S3 ) in accordance with data of the Human Protein Atlas ( http://www . proteinatlas . org ) . In contrast , the patient's skin biopsy did not show CERS3 staining suggesting that functional protein is not present in mutant epidermis ( Figure 3B ) . We verified these results by immunoblotting of lysates from in vitro differentiated control and patient keratinocytes using an antibody targeting amino acids 370–383 at the C-terminus of CERS3 . Immunoblots revealed expression of the protein in control cells at the basal stage ( day 0 ) and increased levels during progression of differentiation ( Figure 3C ) . Concordant with the results of immunofluorescence staining , we did not detect full-length CERS3 or a truncated version of the protein in mutant keratinocytes under basal conditions as well as at later stages of keratinocyte differentiation . Since CERS3 generates epidermis-specific ceramides by N-acylating dihydrosphingosine with acyl-CoAs ranging from long to very long aliphatic chains ( C18–C28 ) [11] , [12] ( Figure 4A ) , we examined whether mutated CERS3 affects the localization and concentration of ceramides in human epidermis using a commercially available antibody targeting ceramides [13] . Immunofluorescence analysis on frozen sections of a control skin biopsy demonstrated the presence of ceramides in the stratum granulosum and stratum corneum , consistent with the localization of CERS3 . In the skin biopsy of the patient carrying the CERS3 splice donor site mutation , however , we detected a massive reduction of ceramides in these layers ( Figure 4B ) . To study the disturbed sphingolipid profile of the patient keratinocytes in detail , we performed TLC analysis of lipid extracts from differentiated control and mutant cells ( Figure 4C and Figure S4 ) . Compatible with the results of immunofluorescence staining , lipid extracts of patient keratinocytes compared to control samples exhibited a marked decrease of very long-chain ( VLC ) ceramides with sphingosine ( −48 . 2% ) and phytosphingosine ( −47 . 9% ) as sphingoid base as well as significantly decreased levels of acylceramides ( −49 . 9% ) , glucosylacylceramides ( −95 . 9% ) , and glucosylceramides ( −60 . 2% ) . In contrast , levels of ceramides with middle to long-chain acyl moieties ( C16–20 ) were slightly but significantly increased ( 1 . 4-fold for sphingosine and 1 . 2-fold for phytosphingosine as sphingoid base ) in patient keratinocytes compared to control samples . To examine the effect of CERS3 mutations on epidermal differentiation , we performed immunofluorescence and immunohistochemical analysis using established differentiation markers for keratinocytes . In healthy control skin , immunohistochemical staining showed that K14 , a marker of undifferentiated keratinocytes , was almost exclusively present in the stratum basale arranged as a one- or two-cell layer ( Figure 5A , upper panel ) . In a skin sample of patient H , however , K14 staining expanded to upper cell layers . During differentiation , keratinocytes from the basal layer gradually migrate upwards forming the upper layers of the epidermis . Thus , an expansion of the basal layer in mutant skin could be a result of an increased proliferation and/or delayed terminal differentiation of keratinocytes . However , immunolabeling of the proliferation marker Ki-67 in control and patient skin corresponded to the K14 expression pattern , indicating a delayed epidermal differentiation and an increased number of proliferating cells in mutant skin ( Figure 5A , lower panel ) . Immunofluorescence staining for involucrin , loricrin , and filaggrin , markers for terminally differentiated keratinocytes , revealed a thickening of the upper stratum spinosum and stratum granulosum in patient skin compared to control samples . Together , these observations suggest that mutated CERS3 affects the terminal differentiation process in human skin ( Figure 5B ) .
We report four patients with a genomic microdeletion on chromosome 15q26 . 3 that partially affects the sequences of CERS3 and ADAMTS17 and abolishes the sequence of the non-coding RNA FLJ42289 . We observed the same haplotype with an identical genomic deletion in these patients and since they originate from the same geographical region in Tunisia , we concluded that the present contiguous gene deletion syndrome is due to a founder effect . The loss of exon 13 in CERS3 with the 3′UTR and the first three exons of ADAMTS17 including the 5′UTR and the start codon predict a reduced mRNA transcript stability of both genes that renders protein translation unlikely . Moreover , the genomic deletion could lead to a fusion protein of CERS3 with ADAMTS17 resulting in a stop codon in exon 4 of ADAMTS17 . If so , the premature termination codon in the predicted fusion gene suggests an enhanced transcript instability triggered by nonsense-mediated mRNA decay [14] . Exon 13 of CERS3 corresponds to the C-terminal amino acids 334–383 that are predicted to form a coiled-coil structure ( amino acids 335–355 , http://www . ensembl . org ) . This domain is found in many other proteins involved in important biological functions such as gene regulation ( e . g . transcription factors ) or vesicular transport [15] , [16] . Moreover , because of their specific interaction , coiled-coil structures are essential for protein-protein interactions thereby facilitating dimerization ( e . g . leucine zipper ) [17] , [18] . Whether CERS3 interacts with DNA or with other proteins via its coiled-coil motif is not known so far . However , the C-terminal 50 amino acids of CERS3 are evolutionary highly conserved among mammals ( homology 62–96% ) indicating an important role of this domain for protein function . Since the partial deletion of ADAMTS17 and CERS3 seems to have a pathologic effect only when both alleles are affected , and since the parents of our patients have no obvious disease symptoms , we conclude an autosomal recessive mode of inheritance . Thus , the present contiguous gene deletion syndrome leads to two independent diseases ( ARCI and WM-like syndrome ) . Currently , it is unclear whether the deletion of the non-coding RNA FLJ42289 contributes to the phenotype of the syndrome . Recently , Morales et al . [8] described a related WM-like syndrome phenotype in eight individuals from Saudi Arabian families with mutations in ADAMTS17 , who displayed many of the key features of WM-like syndrome , including lenticular myopia , ectopia lentis , glaucoma , spherophakia , and short stature , but none of these patients had the characteristic brachydactyly or decreased joint flexibility of WM-like syndrome . However , in our four patients with the homozygous 15q26 . 3 microdeletion in which the first three exons of ADAMTS17 are missing , three of them show a brachydactyly and two of them have reduced joint flexibility ( Table 1 , Figure 1 , and Text S1 ) . This observation is coherent with phenotypic variability found in most genetic syndromes and underlines the importance of clinical reports in rare genetic disorders . The identification of the CERS3 splice donor site mutation , c . 609+1G>T , in an additional patient ( H ) with isolated ARCI confirmed that mutations in CERS3 are causative for the skin anomalies in this form of contiguous gene deletion syndrome . The splice site mutation leads to the loss of exon 9 in the CERS3 coding transcript . This sequence region corresponds to a transmembrane domain ( amino acid 174–194 ) of CERS3 that is thought to be essential for proper membrane topology of the protein . Thus , the loss of this structure would most likely affect protein localization as well as stability . Immunohistochemistry using an antibody that recognizes an N-terminal epitope of CERS3 demonstrated the presence of the protein at the interface between the stratum granulosum and the stratum corneum in control skin but was not detectable in the patient H . CERS3 belongs to a family of enzymes encoded by the CERS genes ( CERS1–6 in mammals ) that were originally referred to as LASS 1–6 ( longevity assurance homolog 1–6 ) based on their homology to the yeast protein , longevity assurance 1 ( LAG1p ) [19]–[21] . All mammalian CERS are integral membrane proteins of the endoplasmic reticulum that catalyze the acylation of the free amine nitrogen of the sphingoid long chain base to form an amide bond ( N-acylation , Figure 4A ) [22] , [23] . In this reaction each CERS prefers acyl-CoAs of specific carbon chain length to synthesize ceramides [11] , [12] , [19]–[21] , [24]–[26] . Of the six known mammalian CERS , CERS3 shows the broadest substrate spectrum utilizing acyl-CoAs of 18 to 28 carbon chain lengths [11] , [12] . Quantitative RT-PCR revealed that CERS3 mRNA is mainly expressed in testis and epidermis , and its expression in these tissues strongly increases upon differentiation [27] , [28] . Thus , CERS3 contributes to the fatty acid composition and concentration of ceramides in these tissues . In skin sections of the patient carrying the splice site donor mutation we did not detect ceramides in the epidermis by immunohistochemistry using a commercially available antibody ( Figure 4B ) . Thus , we conclude that the patients' ichthyosis skin phenotype results from mutations in CERS3 that significantly impair the epidermal ceramide synthesis , in particular the synthesis of ( glucosyl ) acylceramides . Using TLC analysis , however , we identified VLC ceramides in in vitro differentiated patient keratinocytes ( Figure 4C ) suggesting that the mutated CERS3 may harbor residual enzymatic activity . In addition , some limited synthesis of VLC ceramides may occur in patient keratinocytes by the enzymatic activity of other members of the CERS family that compensate for the CERS3 defect . Indeed , CERS2 as well as CERS4 show epidermal expression and substrate specificities toward acyl-CoAs with acyl chain lengths of 22 to 26 carbon atoms [12] , [29] . In mammalian epidermis , ceramides represent the most abundant components of the stratum corneum lipid , which forms a barrier against the penetration of chemicals and pathogenic microorganisms as well as the unregulated loss of water [30] . There are at least eleven different ceramide species in human skin , differing in their fatty acid composition as well as their sphingoid base [29] . To date , the molecular details of sphingolipid metabolism resulting in this huge structural diversity of epidermal ceramides as well as their role in terminal differentiation of keratinocytes have not been extensively studied . However , profound knowledge of these pathways and their regulation is of great interest for the understanding of skin physiology and to provide novel targets and strategies for the treatment of ichthyosis and possibly other lipid-associated disorders of the skin . In this context , the metabolism of ( glucosyl ) acylceramides may play a central role in epidermal lipid pathways [31] . Acylceramides are epidermis-specific sphingolipids carrying amide-linked VLC fatty acids with a terminal hydroxyl group that is further esterified with linoleic acid . In mammalian skin , these ceramides are an absolute prerequisite for the formation of an intact stratum corneum and the water permeability barrier [31] . Accordingly , loss-of-function of enzymes involved in acylceramide metabolism result in cutaneous barrier abnormalities such as those found in human diseases and corresponding mouse models like ELOVL4-deficiency ( MIM 614457 ) [32]–[34] or Chanarin-Dorfman syndrome ( MIM 275630 ) [35] , [36] . The skin of these patients and mutant mice does not exhibit detectable levels of acylceramides and displays a delayed terminal differentiation process that is similar to the one observed in CERS3-deficient skin , arguing for a fundamental role of acylceramides in keratinization . The importance of ceramides and their metabolism for cellular proliferation and differentiation is also evident in other organs and cell types . Very recently , Jennemann et al . [37] demonstrated that glucosylceramides are essential for intestinal epithelial differentiation to maintain the reabsorption function of enterocytes . Our data resemble in many ways the skin phenotype of mice with targeted disruption of the Cers3 gene [12] . In contrast to affected patients of our families , however , Cers3-null mice die shortly after birth due to drastically reduced levels of VLC ceramides leading to a dysfunctional water permeability barrier and rapid dehydration of the animals [12] . This interesting phenotypic difference suggests that mice are more sensitive to barrier defects than humans probably due to a disadvantageous ratio of body volume to skin surface provoking increased dehydration . Notably , similar skin barrier defects associated with early postnatal death are also present in other mouse models for human skin disorders like Chanarin-Dorfman syndrome [36] or NISCH syndrome ( MIM 607626 ) [38] . Future detailed studies addressing skin integrity and barrier recovery of patients with CERS3 mutations will be required to shed light on the mechanisms involved in disease development in humans . In summary , our study reports a contiguous gene deletion syndrome that identifies CERS3 as another ARCI-associated gene in humans . We present functional evidence demonstrating that CERS3 is crucial for the synthesis of VLC ceramides in human skin to maintain epidermal lipid homeostasis and terminal differentiation . Therefore , we suggest that the application of lotions supplemented with VLC ceramides , especially acylceramides onto the skin of affected patients would be a promising therapeutic approach to treat skin symptoms in patients with keratinization disorders .
We obtained blood samples from 34 consanguineous ARCI families in collaboration with clinicians and the support of Généthon ( Evry , France ) . DNA was extracted from whole blood according to standard procedures after written informed consent from all patients and family members who participated in the study . The medical ethics committee of AFM/Généthon approved the study . Genome-wide SNP-genotyping was carried out in a total of 34 consanguineous families ( 120 individuals ) using a human SNP array ( Illumina 370k Quad , San Diego , CA ) . After quality control , the genotyping data were filtered for homozygous regions larger than 1 Mb . Both DNA strands from all subjects and controls were sequenced for the entire coding region and the exon/intron boundaries using standard protocols . Primers for CERS3 flanking the coding exons were designed with primer3 . Genomic DNA from 4 individuals of family C ( one patient , one non-affected brother , and parents ) was analyzed on Microarray Sure Print G3 Human CGH+SNP chip 4x180K ( Agilent , Santa Clara , CA ) . The probes were annotated against NCBI Build 37 ( UCSC hg19 , February 2009 ) . The fragmentation , labelling , and purification of test DNA ( reference DNA: HapMap sample of known genotype ) as well as hybridization and washing was performed according to Agilent's protocol . The scanning step was performed with Agilent high resolution C scanner ( 3μ ) and Agilent Feature Extraction software . Agilent Cytogenomics software 2 . 0 . 6 . 0 was used for imaging . Deletion-specific PCR was performed using Phusion High-Fidelity DNA Polymerase ( Finnzymes Espoo , Finland ) according to the manufacturer's instructions ( annealing temperature 60°C ) . The following primer pair D . fwd = 5′-AAT GCC TCT GAG GAG CAA GG-3′ and D . rev = 5′-GGA ATG TGA ATT AGT TTG GCC A-3′ was used to obtain a breakpoint spanning 1 . 2 kb PCR-product . The PCR-product was sequenced using PCR primers . For histology , samples were collected in PBS , fixed in 4% PFA , embedded in paraffin , sectioned to 7 µm , and stained with hematoxylin and eosin . Immunostaining was performed using the Vectastain ABC Kit and the Avidin/Biotin Blocking Kit ( both from Vector Laboratories ) following the manufacturer's guidelines . Antigen retrieval was performed at pH 9 . 0 in a pressure cooker . A rabbit monoclonal antibody to cytokeratin 14 ( 1∶300 dilution , AC-0058 , Epitomics , Burlingame , CA ) and rabbit monoclonal antibody to Ki-67 ( 1∶300 , AC-0009 , Epitomics ) were used as primary antibodies and a biotinylated goat anti-rabbit IgG antibody ( 1∶200 , BA-1000 , Vector Laboratories ) as secondary antibody . Stained samples were examined using a Zeiss Axioskop 40 microscope with a Zeiss CCD camera . Skin biopsies were fixed in 4% PFA , embedded in Tissue-Tek O . C . T . Compound ( Sakura Finetek , Torrance , CA ) , shock frozen in liquid nitrogen , and sectioned to 8 µm . For double immunofluorescence staining , the skin biopsy was fixed in 4% PFA and embedded in Paraplast Plus ( Leica Microsystems , Wetzlar , Germany ) followed by sectioning to 8 µm . Antigen retrieval was performed at pH 6 . 0 in a pressure cooker . The following commercial antibodies were used: rabbit polyclonal antibody to an N-terminal epitope of CERS3 ( 1∶100 , HPA006092 , Sigma-Aldrich ) , mouse monoclonal antibody to ceramide ( 1∶100 , MAB_0011 , Glycobiotech , Kükels , Germany ) , rabbit polyclonal antibody to loricrin ( 1∶500 , ab24722 , Abcam , Cambridge , UK ) , mouse monoclonal antibody to involucrin ( 1∶200 , I9018 , Sigma-Aldrich ) , and mouse monoclonal antibody to filaggrin ( 1∶200 , SPM181 , Abcam ) as primary antibodies and Alexafluor 488 donkey antibody to mouse IgG ( 1∶200 , 715-545-150 , Jackson ImmunoResearch , West Grove , PA ) , Alexafluor 594 donkey antibody to rabbit IgG ( 1∶200 , 711-585-152 , Jackson ImmunoResearch ) , DyLight 488 donkey antibody to rabbit IgG ( 1∶150 , 711-485-152 , Jackson ImmunoResearch ) , and Alexafluor 546 goat antibody to mouse IgM ( 1∶200 , A21045 , Invitrogen , Carlsbad , CA ) as secondary antibodies . Confocal images were captured and analyzed with an Olympus Fluoview FV1000 laser scanning confocal microscope or with a Carl Zeiss Axioplan 2 and a Photometrics CCD camera for non-confocal images . Primary cultures of keratinocytes were prepared according to standard protocols from skin biopsies of a control individual and patient H carrying the splice site mutation . Cells were cultured at 37°C in a humidified atmosphere with 5% CO2 in defined keratinocyte serum-free medium ( EpiLife , Invitrogen ) containing human keratinocyte growth supplement ( HKGS , Invitrogen ) , 100 IU/ml penicillin , and 100 µg/ml streptomycin . Epidermal differentiation was induced in keratinocyte cultures according to Breiden et al . [42] with minor changes to promote epidermal lipid synthesis . In brief , confluent cultures were maintained in medium supplemented with 1 . 1 mM CaCl2 , 30 µM palmitic acid , 25 µM oleic acid , 15 µM linoleic acid , and 10 µM lignoceric acid for 14 days with medium changes every second day . Fatty acids ( Sigma-Aldrich ) were complexed to fatty acid-free BSA ( Sigma-Aldrich ) using a ratio of 3∶1 . Total RNA was extracted from keratinocytes before differentiation and at day 4 , 7 and 14 after induction of differentiation with TRIzol Reagent ( Invitrogen ) according to manufacturer's protocol . 1 µg of RNA was transcribed into cDNA using M-MuLV Reverse Transcriptase ( Biozym Scientific , Hessisch Oldendorf , Germany ) , poly d ( T ) primers ( Sigma-Aldrich ) and random hexamers ( Invitrogen ) according to manufacturer's guidelines . A PCR was performed using Taq Polymerase ( Qiagen , Hilden , Germany ) and primers localized in exon 8 and 10 of CERS3 ( forward: GGA ATG GCT ATC CCA AAC AG; reverse: GAC TCC AGC CAA ATG TCA GC ) . PCR fragments were separated by 2% TAE agarose gel electrophoresis according to standard laboratory protocols . PCR primers were used to sequence DNA fragments . At day 0 , 4 , 7 and 14 after induction of keratinocyte differentiation , cells were collected in RIPA buffer ( 150 mM NaCl , 10 mM Tris-HCl , pH 7 . 4 , 0 . 1% SDS , 1% Triton X-100 , 1% sodium deoxycholate and 5 mM EDTA ) and lysed by sonication with a Branson Sonifier Cell disruptor B15 ( output control 1 , duty cycle 10% ) . After centrifugation at 1 , 000×g for 5 min to pellet nuclei and unbroken cells , the protein content was measured using BCA reagent ( Pierce/Thermo Scientific , Waltham , MA ) and BSA as standard . 50 µg of protein were separated by 10% SDS-PAGE according to standard laboratory protocols , blotted onto polyvinylidene difluoride membrane ( Carl Roth , Karlsruhe , Germany ) and hybridized with a goat polyclonal antibody raised against the C-terminus of CERS3 ( 1∶500 dilution , AP16822PU-N , Acris Antibodies , Herford , Germany ) or a rabbit polyclonal antibody raised against actin ( 1∶1 , 000 dilution , A2066 , Sigma-Aldrich ) . Specifically bound immunoglobulins were detected in a second reaction using HRP-conjugated anti-goat or anti-rabbit IgG antibodies ( 1∶10 , 000 dilution ) and visualized by enhanced chemiluminescence detection ( ECL , Amersham Biosciences , Buckinghamshire , UK ) . Total lipids were extracted from differentiated keratinocytes with chloroform/methanol/glacial acetic acid ( 66∶33∶1 v/v/v ) and collected from the organic phase after addition of 1/5 volume of water and centrifugation at 2 , 400×g for 15 min . To prepare an epidermal lipid reference standard for TLC , epidermis from a healthy control individual was separated from dermis by incubating full thickness skin ( 15×15 mm ) dermis-side down in 0 . 25% Trypsin-EDTA ( PAA Laboratories , Pasching , Austria ) at 4°C over night and total lipids were extracted from epidermis as described above . For TLC , total lipids were dried in a stream of nitrogen , reconstituted in chloroform , and spotted onto a thin-layer silica gel 60 plate ( Merck , Whitehouse Station , NJ ) . Epidermal ceramide species were separated twice using chloroform/methanol/glacial acetic acid ( 190/9/1 v/v/v ) as solvent system [43] . To separate polar lipids ( glucosyl ( acyl ) ceramides ) chromatograms were developed using the solvent system chloroform/methanol/water ( 70/30/5 v/v/v ) [42] . Lipid spots were visualized by carbonization after spraying the chromatograms with 10% CuSO4 ( w/v ) and 10% H3PO4 ( v/v ) and heating them to 150°C for 20 min . Developed chromatograms were photographed and signals were quantified using Quantity One 1-D Analysis software ( Bio-Rad Laboratories , Hercules , CA ) . Lipid spots of acylceramides and glucosyl ( acyl ) ceramides were identified according to Breiden et al . [42] using the epidermal lipid reference standard . After lipid extraction , cells were solubilized in 0 . 1% ( w/v ) SDS and 0 . 3 N NaOH at 65°C over night , and the protein content was determined using BCA reagent ( Pierce/Thermo Scientific ) and BSA as standard . | Autosomal recessive congenital ichthyosis ( ARCI ) is a heterogeneous group of human keratinization disorders mainly characterized by generalized abnormal scaling of the skin . To date , positional cloning and homozygosity mapping of families with ARCI have identified disease-associated mutations in seven genes: ABCA12 , ALOX12B , ALOXE3 , CYP4F22 , ICHTHYIN , PNPLA1 , and TGM1 . The reported molecular mechanisms underlying disease development are related to defects in epidermal lipid pathways that interfere with terminal keratinocyte differentiation and skin barrier function . In this study we used genome-wide SNP mapping , which identified homozygous mutations in the CERS3 ( ceramide synthase 3 ) gene that cause a new type of ARCI . Functional analysis of a skin sample and in vitro differentiated keratinocytes from one patient demonstrated that mutated CERS3 impairs the synthesis of ceramides with very long-chain acyl moieties . The defect in sphingolipid metabolism disturbs the epidermal lipid profile , which leads to an abnormal terminal differentiation process . In summary , mutations in CERS3 are causative for ARCI and illustrate the important role of ceramide synthesis in human skin physiology . | [
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"dermatology",... | 2013 | Mutations in CERS3 Cause Autosomal Recessive Congenital Ichthyosis in Humans |
Pestiviruses express their genome as a single polypeptide that is subsequently cleaved into individual proteins by host- and virus-encoded proteases . The pestivirus N-terminal protease ( Npro ) is a cysteine autoprotease that cleaves between its own C-terminus and the N-terminus of the core protein . Due to its unique sequence and catalytic site , it forms its own cysteine protease family C53 . After self-cleavage , Npro is no longer active as a protease . The released Npro suppresses the induction of the host's type-I interferon-α/β ( IFN-α/β ) response . Npro binds interferon regulatory factor-3 ( IRF3 ) , the key transcriptional activator of IFN-α/β genes , and promotes degradation of IRF3 by the proteasome , thus preventing induction of the IFN-α/β response to pestivirus infection . Here we report the crystal structures of pestivirus Npro . Npro is structurally distinct from other known cysteine proteases and has a novel “clam shell” fold consisting of a protease domain and a zinc-binding domain . The unique fold of Npro allows auto-catalysis at its C-terminus and subsequently conceals the cleavage site in the active site of the protease . Although many viruses interfere with type I IFN induction by targeting the IRF3 pathway , little information is available regarding structure or mechanism of action of viral proteins that interact with IRF3 . The distribution of amino acids on the surface of Npro involved in targeting IRF3 for proteasomal degradation provides insight into the nature of Npro's interaction with IRF3 . The structures thus establish the mechanism of auto-catalysis and subsequent auto-inhibition of trans-activity of Npro , and its role in subversion of host immune response .
Cells sense RNA virus infections by pattern recognition receptors ( PRR ) such as Toll-like receptors and the cytosolic RIG-I and MDA5 that recognize different forms of single-stranded and double-stranded viral RNA [1] , [2] . Engagement of these PRR triggers a signaling cascade leading to phosphorylation and subsequent activation of the interferon regulatory factor-3 ( IRF3 ) . Activated IRF3 then translocates into the nucleus where it induces transcription of the interferon-α/β ( IFN-α/β ) genes . This activation is essential for the host to mount innate and adaptive anti-viral responses [3] . Viruses have evolved a multitude of strategies to counter the initial steps of the host's innate immune activation [4] , [5] . IRF3 is targeted by many different viruses that use virus-encoded proteins to counteract IRF3 functions . A few examples of viral proteins targeting IRF3 are NSP1 of rotavirus , ICP0 of herpes virus , the leader protein of mengovirus and of Theiler's murine encephalomyelitis virus , the ML protein of Thogoto virus , and the NS1 and NS2 proteins of bovine and human respiratory syncytial virus [6] , [7] , [8] , [9] , [10] , [11] , [12] , [13] . The mechanisms of IRF3 antagonism employed by these viral proteins vary , and include inhibition of phosphorylation , nuclear translocation , and assembly of the transcription complex , as well as targeting IRF3 for proteasomal degradation . Pestiviruses , such as bovine viral diarrhea virus ( BVDV ) and classical swine fever virus ( CSFV ) use a virally encoded protein , the N-terminal protease ( Npro ) , to suppress the transcriptional activation of the IFN-α/β genes by interacting with IRF3 and inducing its ubiquitination and proteasome-dependent degradation [14] , [15] , [16] , [17] , [18] . Npro also interferes with the activity of IRF7 in plasmacytoid dendritic cells [19] . Unlike the other viral proteins encoded by the pestivirus genome , Npro has no counterpart in the other members of the Flaviviridae family . The Npro protein is a leader cysteine autoprotease that cleaves itself from the nascent polyprotein during translation of the viral mRNA , freeing itself for innate immune suppression activities . Self-cleavage of Npro releases the core protein that becomes a structural component of the virion , probably by associating with the viral RNA genome and forming a nucleocapsid [20] , [21] , [22] . Npro is not associated with virions and is dispensable for virus replication [23] . Interestingly , following the first self-cleavage reaction , Npro does not possess any proteolytic trans-activity [24] . Sequence comparison with other known protease families showed that Npro has a unique sequence and a novel arrangement of catalytic residues , and hence it is classified as its own C53 protease family [25] . The predicted catalytic triad of Npro is Glu22 , His49 and Cys69 , which differs from the known catalytic triads in serine and cysteine proteases . For example , the catalytic triad in papain-like cysteine proteases is Cys25-His159-Asn175 , and that in subtilisin-like serine proteases is Asp32-His62-Ser245 . Additionally , the catalytic activity of Npro is not inhibited by typical cysteine protease inhibitors such as antipain dihydrochloride and by the serine protease inhibitor aprotinin [21] . There is strong evidence that the function of Npro in IRF3 degradation and inhibition of IFN-α/β induction is independent of its autoproteolytic activity , since mutation of the catalytic Cys69 to Ala had a minimal effect on inhibition of IFN-α/β induction by Npro [26] , [27] . However , mutation of His49 resulted in a loss of IFN-antagonistic activity , indicating that there is spatial overlap of regions that are involved in proteolysis and those responsible for IRF3 interactions [15] , [16] , [26] . We previously reported that Npro has two domains , a catalytic N-terminal domain and a zinc-coordinating C-terminal domain , and that a zinc-binding TRASH motif in the C-terminal domain is required for binding IRF3 and subverting IFN-α/β induction [28] . Here , we report the crystal structures of CSFV Npro and a C168A cleavage site Npro mutant to 1 . 6 Å resolution . To our knowledge , this is the first structure of an IRF3 antagonist . Npro has a unique ‘clam shell’-like protease fold that is distinct from other known proteins including all known proteases . As predicted , Npro consists of two domains , a cysteine protease domain and a zinc-binding domain . The active site of Npro's cysteine protease is formed by a catalytic dyad , Cys69 and His49 . Contrary to previous reports , Glu22 is not in the active site . The C-terminus of the protein that constitutes the self-cleavage site is not only bound in the protease active site , but also contributes an integral β-strand to the central β-sheet that makes up the active site . Thus , the C-terminus of Npro occludes the catalytic site following cleavage , inhibiting any trans-activity of the protease and limiting the activity of the enzyme to a single catalytic turnover . The C-terminal domain contains the zinc-binding TRASH motif that is indispensable for binding IRF3 and targeting it for proteasomal degradation . Taken together , the Npro structures presented here establish the mechanism of auto-catalysis and subsequent auto-inhibition of Npro , and provide insight into its interaction with IRF3 in subversion of host innate immune responses .
Both crystal structures of Npro were determined using deletion mutants that lack the first 17 amino acids ( Npro-Δ17N ) . The first 19 amino acids are not essential for proteolytic activity of Npro and can be deleted without affecting the in vitro protease activity [21] , [26] . The 19 residue deletion also does not interfere with the ability of Npro to block the IFN-α/β induction in cell culture [26] . Thus the structures represent biologically relevant forms of Npro . The C168A protein was expressed as Npro-Δ17N protein that contains a Cys168 to Ala mutation along with an additional four residues at the C-terminus , 169Ser-Asp-Asp-Gly172 , a sequence that corresponds to the first four amino acids of the core protein . This construct was intended to trap a substrate-bound form of Npro; by mutating the cleavage-site residue , Npro should not be able to catalyze self-cleavage at its C-terminus . Unexpectedly , the C168A mutant was active and the SDDG peptide at the C-terminus was cleaved , as confirmed by mass spectrometry ( data not shown ) . Introduction of the Cys168 to Ala mutation resulted in different packing in the crystal lattice . The C168A Npro crystals belong to the spacegroup P212121 with one molecule per asymmetric unit and a solvent content of 54% . In contrast , wild-type Npro crystals were of spacegroup P21212 also with a monomer in the asymmetric unit , but with a solvent content of 35% ( Table 1 ) . Although it is not entirely clear why the C168A mutation resulted in such a dramatic change in packing , new crystal contacts at the active site contributed to the stabilization of the helix carrying the nucleophilic Cys69 , which was disordered and not visible in the native structure ( Figure 1a–b ) . In the C168A structure , the side chains of Cys69 , His49 and the C-terminal carboxyl group of one molecule , along with the side chain of His74 from a neighboring molecule , coordinated a zinc atom ( Figure 1c ) . Since His74 is not conserved among pestiviral Npro proteins , coordination of zinc near the active site is most likely a result of crystal packing interactions and may not be physiologically relevant . Presence of zinc was confirmed by determining the anomalous difference map from single wavelength anomalous dispersion ( SAD ) data collected at the zinc absorption edge . The distances between zinc and the coordinating groups are 1 . 9 , 2 . 1 , 2 . 1 and 2 . 3 Å for the carboxy-terminus , two histidines ( His74' and His49 ) , and cysteine ( Cys69 ) residues , respectively , all of which are consistent with distances reported for tetrahedral zinc coordination [29] . The structure of the C168A mutant can be superimposed on the wild type structure with a root-mean square deviation ( R . M . S . D . ) of 0 . 38 Å for 136 Cα atoms . Thus , there is no gross structural difference between the wild-type and C168A mutant . Npro is composed predominantly of β-sheets that adopt a unique ‘clam shell’-like fold . The protein can be divided into two distinct domains , the catalytic protease domain and the zinc-binding domain ( Figure 1 ) . The protease domain spans the N-terminus through residue 100 and also includes C-terminal residues 157 to 168 . The domain harbors the protease active site along with the C-terminal protease cleavage site Cys168 . The protease domain contains mostly coils without regular secondary structure and a single β-sheet formed by strands β1 , β2 , and β8 . The first two β-strands of the sheet are contributed by the first 100 residues in the sequence . The last 6 residues at the C-terminus ( 163–168 ) form the final β-strand , and fold back into the protease active site , positioning the C-terminus Cys168 for cleavage ( see the next section ) . The Npro protease domain was predicted to be disordered , perhaps due to the abundance of proline residues; the domain contains twelve prolines corresponding to an average of one proline for every 7 residues . Most prolines are located in the loops on the surface of the protein , contributing to the unique fold of the protein . A search for similar folds using the DALI server resulted in zero instances , indicating that the catalytic domain of Npro has a new fold . The zinc-binding domain of Npro spans residues 101 through 156 and forms an anti-parallel β-sheet consisting of five β-strands , β3 , β4 , β5 , β6 , and β7 ( Figure 1 ) . This domain carries a conserved metal binding TRASH motif consisting of Cys112-Cys134-Asp136-Cys138 that coordinates a single zinc atom [28] . The TRASH motif is located at one end of the β-sheet . The interface between the protease and zinc-binding domains is mostly hydrophobic , and the C-terminal domain partially covers the final β-strand in the protease domain ( see below ) . A cysteine protease triad in Npro was predicted to include Glu22 , His49 and Cys69 by site-directed mutagenesis in a cell-free translation system [21] . The active site of Npro is solvent exposed on one end of the protease domain ( Figure 2a ) . Cys69 is part of a single-turn helix formed by residues 68–71 in the C168A protein , while it is disordered in the native structure . Among the proposed protease triad , only Cys69 , the nucleophile , and His49 , the general base , are present to form a catalytic dyad flanking the C-terminal cleavage site . The sulfur atom of Cys69 is 3 . 8 Å away from the epsilon nitrogen of His49 , and 3 . 5 Å away from the terminal carboxylate of Ala168 . These distances are comparable to those seen in crystal structures of papain-like cysteine proteases , although the arrangement of the dyad ( His49-Cys69 ) is different from that of papain ( Cys25-His159 ) and other cysteine proteases . Since a zinc atom is present in the active site ( figure 1C ) , this could lead to small artifacts in the observed active site geometry . Cysteine proteases often contain a stabilizing Asn/Asp residue in the vicinity of the catalytic His . No stabilizing anion group in the vicinity of His49 is apparent . However , the main chain carbonyl group of Asp50 is within a hydrogen-bonding distance of 2 . 8 Å of the delta nitrogen of His49 , and thus could orient the imidazolium ring of His49 during catalysis ( Figure 2b ) . Contrary to previous predictions , Glu22 does not complete a catalytic triad since its spatial location is approximately 23 Å from the nucleophilic Cys69 ( Figure 2a ) . Instead , Glu22 forms a salt bridge with the conserved Arg100 . Since mutation of Glu22 , either a deletion or an Ala-substitution renders the protease inactive , breakdown of the salt bridge between Glu22 and Arg100 likely destabilizes the structure of the protease domain , resulting in the observed loss of proteolytic activity . Both Npro structures represent a product-bound form of the enzyme , providing the geometry of the catalytic residues around the scissile bond of Cys168 . The C-terminal β-strand ( β8 ) provides substrate specificity by positioning the C-terminal cleavage site residue 168 for hydrolysis near the protease dyad . The C-terminal carboxylate of residue 168 , either Cys in the wild-type structure or Ala in the C168A mutant structure , has a clear density with planar geometry ( Figure 2b ) . The terminal carboxylate forms hydrogen bonds with the main chain amides of Gly67 , Asp68 and Cys69 . These hydrogen bonding interactions would also help stabilize the tetrahedral intermediate during catalysis and thus form the oxyanion hole . Npro cleaves the peptide bond between Cys168 and Ser169 in the viral polyprotein such that Ser169 then becomes the N-terminus of the core protein . The residues at the C-terminus of Npro ( the P sites ) are reported to be essential for a functional Npro protease , while the residues following the cleavage site ( P' sites ) can tolerate many amino acid substitutions [20] , [24] , [30] . The cleavage site for substrates is defined as …P3-P2-P1- P1'-P2'-P3'… , where a cleavage occurs between the P1 and P1' residues . The last seven C-terminal residues Pro162-Leu-Trp-Val-Thr-Ser-Cys168 ( P7 to P1 ) form the final β-strand ( β8 ) which is an integral part of a β-sheet . The β-strand is partially occluded by the C-terminal domain , such that the P7 to P4 site is not solvent accessible and enclosed in a hydrophobic environment . In addition to the typical main chain hydrogen bonding with β1 , the β8-strand is stabilized by side-chain interactions , most notably hydrophobic interactions , involving Leu163 , Trp164 , and Val165 . For example , Trp164 ( P4 ) shown to be critical for protease activity is located in a hydrophobic environment consisting of the conserved residues Leu45 , Leu47 , Arg51 , Tyr82 , Val97 , and His99 ( Figure 2c ) . This is consistent with the highly conserved nature of the C-terminal residues and the mutational studies in which Trp164 to Ala substitution renders the protease inactive and prevents the release of Npro from the BVDV-encoded polyprotein [20] , [24] . The W164A mutation would likely destabilize the β-sheet and , by extension , the catalytic site of Npro such that the enzyme is no longer able to carry out catalysis . Cys168 is absolutely conserved in pestiviruses , and thus Npro has been thought to be highly specific for Cys at the P1 site . Consistent with this prediction , Cys168 to Glu substitution abrogates the protease activity [30] . In our experiment , however , the recombinant C168A protein that contains the additional four residues ( SDDG ) from the core protein was proteolytically active , and the four C-terminal residues were cleaved by the protein . In the C168A structure , the side chain of Ala168 is located in a shallow hydrophobic pocket formed by Thr166 , Pro64 , Val78 and Gly80 ( S1 subsite ) ( Figure-2c ) . The S1 subsite can only accommodate amino acids with small side chains . A long negatively charged Glu in the C168E protein thus would not fit in the subsite due to steric hindrance . Thus , although Npro does not require Cys at the cleavage site , Cys168 is conserved in pestiviruses , suggesting that the residue may have an additional function other than participating in the protease catalysis . Following auto-proteolysis at the C-terminus , the catalytic activity of Npro is completely lost [24] . The structures presented here show that the C-terminal β-strand ( one half of the product peptide ) remains buried in the active site pocket , indicating that once cleaved , the C-terminus of Npro acts as an intramolecular inhibitor and thus prevents trans-activity , i . e , the enzyme is inactive toward additional substrates . This is consistent with limited proteolysis results showing that the C-terminus of Npro is protected from proteolytic degradation [28] . Additionally , the C-terminal β-strand ( substrate ) is also a part of the central β-sheet . Thus , no other peptide substrate can bind in the substrate binding site without disrupting the fold of the protease . In this way , Npro has evolved to carry out only a single catalytic event . An analogous autoprotease mechanism , viz . , intramolecular product inhibition , has been reported for several proteins . For example , pestivirus NS2 is an autoprotease that cleaves its own C-terminus from the NS2-3 protein . Although the full-length NS2 is limited to a cis-cleavage reaction , deletion of at least four amino acids from the C-terminus was sufficient to allow the protein to cleave a substrate in trans [31] , indicating that the C-terminal residues ( substrate ) do not participate in either the fold or the activity of the protease . In contrast , Npro is unlikely to possess trans-cleavage activity even if the C-terminal residues are deleted from the protein because the C-terminal β-strand is critical for the fold and activity of the protease domain . Deletion of the C-terminal residues would result in an unstable protease rather than an active protease with an unoccupied substrate binding site . We have indeed observed that the deletion of the terminal 5 amino acids results in an insoluble protein , likely due to instability of the protein and the resultant formation of inclusion bodies upon expression in E . coli ( unpublished data ) . The C-terminal zinc-binding domain ( residues 101 to 156 ) forms an anti-parallel β-sheet consisting of five β-strands ( β3 , β4 , β5 , β6 , and β7 ) . Though the domain is not directly involved in the proteolytic mechanism , it serves as a structural scaffold for the N-terminal protease domain and shields the C-terminal β-strand . The C-terminal domain likely maintains the structural integrity of the protein until the final β-strand carrying the cleavage site ( Cys168 ) is translated , which then enables the catalytic domain to acquire its active conformation , thus allowing cleavage of the peptide bond at the C-terminus of Npro . We have shown that this domain carries a conserved metal binding TRASH motif with the consensus sequence C-X19–22-C-X3-C ( X being any amino acid ) [28] . Npro has a modified TRASH motif that consists of Cys112-Cys134-Asp136-Cys138 , which coordinates a single zinc atom . Individual mutations of C112A/R , C134A , D136N , and C138A in the TRASH motif resulted in loss of zinc-binding , and also abolished IRF3 binding and subsequent inhibition of IFN-α/β induction when introduced into the virus . In the crystal structure , all four residues of the TRASH motif are located at one end of the β-sheet , consistent with previous biochemical data [28] ( Figure 2d ) . The zinc-binding site consists of a loop that contributes the ligand Cys112 and a β-hairpin that contributes the other three ligands Cys134 , Asp136 , and Cys138 , respectively . However , neither the wild-type nor the C168A structures contain a bound zinc atom at this site . Instead , a disulfide bridge was formed between Cys112 and Cys134 . We surmise that the zinc atom escaped the binding site in the absence of a stable reducing agent in the crystallization conditions , which in turn allowed formation of a disulfide bridge . This displaced zinc atom could then be salvaged in the C168A protein , and coordinated by the secondary coordination site formed between two molecules of Npro as a result of crystal packing ( see above ) . The distance between Cys112 and Cys138 , the furthest two residues in the proposed zinc-binding site , is 7 . 7 Å , which is too long to form a zinc coordination site . Since both residues are located in flexible loop regions , they may come closer upon zinc binding without the need for major conformational changes . Alternatively , one of the Cys residues may be required to maintain the geometry of the other residues in the zinc-binding site , and may not be directly involved in zinc binding . A water molecule could then occupy the fourth coordination site . The TRASH motif was first described as a novel sequence motif for genes involved in copper homeostasis , and was predicted to have a treble clef fold [32] . The treble clef fold consists of a β-hairpin at the N-terminus and an α-helix at the C-terminus that contribute two ligands each for zinc-binding [33] . However , the zinc-binding site in Npro does not resemble the treble clef fold or any other common zinc-finger motifs . It is close to a zinc ribbon in that the zinc-binding site contains a three-stranded anti-parallel β-sheet . Unlike a typical zinc ribbon that consists of two zinc knuckles ( short β-strands connected by a turn ) that each contribute two ligands , in Npro one ligand comes from the loop connecting β3 and β4 , and the other three from the strands β5 and β6 and the loop connecting them ( Figure 2d ) . Since the zinc-binding residues in Npro constitute a modified form of the TRASH motif , i . e . , C-X21-C-X-D-X-C , it is not clear whether the zinc-binding motif in Npro forms a subset of the TRASH motif or a new zinc coordinating sequence motif . An intact zinc-binding site in Npro is required for binding IRF3 and targeting it for proteasomal degradation in the host cell [28] . Similar to pestivirus Npro , rotavirus NSP1 and herpes virus ICP0 also inhibit IRF3 activation by binding to IRF3 and targeting it for proteasomal degradation [8] , [34] . Both proteins also contain a conserved zinc-binding RING-finger motif ( Cys3HisCys4 ) at their N-termini , and have been suggested to act as an E3 ubiquitin ligase . The E3 ligase transfers ubiquitin from the E2 conjugating enzyme to the substrate protein via direct interaction with the substrate protein . Although Npro contains a zinc-binding motif , the structure of the zinc-binding site is rather different from the classical zinc-fingers and does not resemble the RING-finger motif , the typical fold of E3 ubiquitin ligase . Thus , it seems unlikely that Npro functions as an E3 ubiquitin ligase and Npro may regulate the IRF3 degradation via a mechanism different from that of rotavirus NSP1 and herpes virus ICP0 . The role of Npro in the regulation of IRF3-dependent IFN-α/β induction is well-established in the pestiviral disease pathogenesis . Interaction of CSFV Npro with IRF3 has been shown in cell-based and in vitro binding assays , and interaction between BVDV Npro and IRF3 has been shown by immunoprecipitation , all of which were used to identify residues that affect its ability to interfere with IFN induction [15] , [16] , [26] , [27] , [28] . Mutations of the catalytic Cys69 had a minimal effect on IFN induction for both BVDV and CSFV Npro , indicating that the protease activity is not related to IRF3 binding [15] , [26] , [27] . However , mutations of His49 to Val or Leu resulted in a loss of IFN-antagonistic activity , suggesting at least partial structural overlap between the protease and anti-IFN functions of Npro [15] , [16] , [26] . Point mutations of Glu22 to Leu or Val also abolished the anti-IFN activity of Npro [15] , [16] , [26] . Cys112 , Cys134 , Asp136 and Cys138 in the zinc-binding domain were also required for the anti-IFN activity , as described previously [28] . N-terminal mutations of BVDV and CSFV Npro have different consequences on the suppression of IFN-α/β production in infected cells [15] , [16] , [26] . In BVDV Npro Leu8 to Pro substitution impaired its IFN-α/β antagonistic function . Although the mutant displayed binding to IRF3 , it could no longer promote its ubiquitination and proteasomal degradation [16] . In contrast , CSFV Npro that contains a deletion of the N-terminal 19 amino acids maintained its ability to inhibit IFN-α/β response [26] . Deletion of 24 or more amino acids at the C-terminus of Npro also abolished the anti-IFN activity of Npro [16] , [26] , [27] . To determine if the residues involved in the anti-IFN response form a localized IRF3-binding surface , we mapped the above mentioned residues on the 3D structure of Npro , along with the conserved residues ( Figure 3 ) . Large deletions of the N-terminal 19–22 amino acids or the C-terminal 24 amino acids were not included in the surface mapping , since their loss of function may be caused by the disruption of protein folding . The residues form two spatial clusters on the opposite sides of the protein surface; one cluster is on a face of the protease domain , and the other on the zinc-binding domain ( Figure 3 ) . Whether IRF3 could simultaneously interact with both surfaces is not known . However , since the mutation on the N-terminus of BVDV Npro ( L8P ) only disrupted ubiquitination of IRF3 and not its binding , the two surface clusters of conserved residues in each domain may account for different functions in anti-IFN activity; one for direct interaction with IRF3 and the other for interaction with cellular proteins in a downstream response leading to ubiquitination and degradation of IRF3 [16] . Based on previous experimental data and the surface distribution of residues involved in IRF3 binding , we speculate that the C-terminal Zn binding domain interacts with IRF3 , whereas the protease domain would bind to a cellular protein involved in the ubiquitination reaction .
Cysteine proteases fall into one of two major groups , or clans based on their structural homology and evolutionary relationship . Clan PA proteases are evolutionarily related to the chymotrypsin family and have the common double β-barrel fold with catalytic residues located between the two β-barrels . The catalytic nucleophile can be either serine or cysteine arranged similar to His57-Asp102-Ser195 in the chymotrypsin sequence . The other clan , CA , comprises all papain-like cysteine proteases which consist of an N-terminal α-helical domain and the C-terminal β-barrel domain with the active site located in the cleft between the two domains . The arrangement of the catalytic residues in papain is Cys25-His159- ( Asn175 ) ; Asn helps to orient the imidazolium ring of the catalytic His [35] . Npro does not share sequence homology with any other known proteases , and thus was assigned to its own family of cysteine proteases , C53 [25] . The newly established catalytic His49-Cys69 dyad does not align in either sequence or structure with either type of cysteine protease , and the unique fold of the protein reported here supports this classification . One of the unique features of the protease is that the C-terminal residues , the substrate of its own protease activity , form a β-strand that contributes to the overall fold of the protein . This β-strand is further blocked by the zinc-binding domain , and the substrate binding site is partially enclosed in a hydrophobic environment . Such an arrangement of substrate peptide would prevent further access of any other endogenous substrates to the active site for cleavage , indicating that Npro evolved to catalyze a single cleavage event . After self-cleavage , the product peptide remains bound in the active site pocket , making the protease permanently inhibited by its own C-terminus . In fact , the β-strand would not be able to be released without distorting the structure , resulting in the loss of protease activity . Additionally , the short α-helix containing the catalytic Cys69 is disordered in the wild-type Npro structure , which may be an additional measure to deactivate the protease function after initial cleavage . While our manuscript was under review , BVDV Npro structures that lack the first 21 amino acids have been published [36] . The overall fold is similar to the fold presented here , and BVDV Npro ( PDB 3zfr ) can be superimposed with an rmsd of 0 . 86 Å for the common 134 Cα atoms with CSFV Npro . The greatest deviations between CSFV and BVDV Npro and among BVDV Npros lie in the short helix containing the catalytic Cys69 and the loop preceding the helix ( residues 63–69 ) . This also contributes to two major differences in the structures and in their interpretation . First , the catalytic Cys69 and Cys168 forms a disulfide bond in BVDV Npro . Since this is an inactive state of the enzyme , an active form of the enzyme with reduced Cys69 was proposed to be in equilibrium with the non-productive form . Second , a bound hydroxide ion near Gly67 amide was proposed to deprotonate the catalytic Cys69 sulfhydryl for the nucleophilic attack . His49 would then function as oxyanion hole and polarize the scissile bond , instead of forming an imidazolium ( His49 ) -thiolate ( Cys69 ) ion pair . In comparison , CSFV Npro structures do not have a disulfide bond between Cys69 and Cys168 because the active site-containing helix is disordered in the wild-type Npro and Cys168 is replaced in the C168A Npro . Since C168A is as active as the wild-type Npro in our hands , disulfide bond formation is not a required step in catalysis . In addition , no water molecule was observed near the Gly67 amide . The Gly67 amide , along with Asp68 and Cys69 amides , is within hydrogen-bonding distance to the C-terminal carboxylate ( Figure 2 ) . Thus , the CSFV Npro structure supports the classical cysteine protease mechanism rather than the catalytic mechanism proposed for BVDV Npro . Although differences in crystallization conditions and protein preparations ( native vs refolding ) could have led to the observed differences in the catalytic site , it seems unlikely that BVDV and CSFV Npro utilize a different mechanism to catalyze the cleavage reaction . Since both proteins could have a distorted active site geometry either from the disulfide bond formation between Cys69 and Cys168 in BVDV Npro or zinc coordination in CSFV Npro , the measurement of pKa of the Cys69 and His49 may be required to distinguish between the two mechanisms . The release of Npro from the polyprotein subsequently sets the stage for suppression of innate immune responses . Pestivirus Npro binds and degrades IRF3 via ubiquitination and the proteasomal degradation pathway , and thus subverts the IFN-α/β induction in host cells [16] , [17] , [18] , [27] . However , following the initial binding to IRF3 , the mechanism of IRF3 degradation is still unknown . In addition , although many residues have been indicated to be involved in IRF3 binding and subsequent IFN subversion , it is not known whether the mutations directly affect IRF3 degradation or simply decrease protein stability . For example , Glu22 was proposed to be important for both proteolytic activity and IFN subversion functions of Npro [15] , [16] , [21] , [26] . In light of the crystal structures presented here , it is likely that the mutation would destabilize the protein folding leading to loss of function . Nonetheless , the Npro residues involved in the anti-IFN function cluster into two patches on opposite sides of the protein surface ( Figure 3 ) , suggesting there might be distinct functions for each of the patches . Since Npro is unlikely to ubiquitinate IRF3 directly , other cellular proteins probably need to bind to the Npro-IRF3 complex for ubiqutination and degradation to occur . This could also explain the observations that the N-terminal mutations of CSFV and BVDV Npro have different consequences in subversion of interferon induction . Although the same cellular proteins are likely recruited to CSFV and BVDV Npro , specific residues involved in the interaction between Npro and the protein partner may be different . Several Npro-binding proteins including IRF-7 , HAX-1 , IκBα , and TRIM56 have been identified [19] , [37] , [38] , [39] . IRF7 is a transcription factor for interferon-α genes and induced by type I interferon . Npro also interferes with the function of IRF7 in pDC and thus dampens interferon-α induction during viral infection . Similar to IRF3 and Npro interactions , the IRF7 interactions with Npro rely on the zinc-binding domain of Npro . In particular , individual mutations of TRASH motif residues ( C112R , C112A , C134A , D136N , and C138A ) in Npro abolished the IRF7 interaction in mammalian two-hybrid assays [19] . However , interaction between IRF7 and Npro does not induce proteosomal degradation of IRF7 , suggesting a different mechanism of Npro-mediated IRF7 antagonism . The significance of Npro interactions with HAX-1 , IκBα , and TRIM56 in viral pathogenesis is less clear . HAX-1 and IκBα are involved in controlling cell survival , while TRIM56 is involved in antiviral response . Interestingly , the consensus sequence for HAX-1 binding site was suggested to be present in Npro between residues 110 and 135 . The peptide corresponding to Npro residues 106–143 interact with HAX-1 in co-precipitation assays [37] . This Npro peptide contains an intact TRASH motif , and it is likely that HAX-1 binds to the zinc-binding surface as with IRF3 and IRF7 . Several additional proteins interacting with Npro were identified in random screens , but the functional relevance of these interactions have not yet been characterized [39] , [40] . Identification of cellular proteins that interact with Npro and their interaction studies are essential next steps towards understanding how binding of Npro to IRF3 leads to the degradation of IRF3 and Npro-mediated viral pathogenesis .
The Npro gene of CSFV strain vA187-1 ( Alfort/187 , GenBank accession number X87939 ) [41] was amplified by PCR from pA187-1 and cloned into pCR4-TOPO ( Invitrogen ) . The DNA fragment containing the Npro gene was then subcloned into the NdeI and XhoI restriction sites of pET-15b vector to obtain pET-6H-throm-Npro ( Alf ) [28] . The N-terminal deletion mutants were designed based on limited proteolysis results [28] . The Npro construct lacking the first 17 amino acids ( Npro-Δ17N ) was amplified from the full-length construct using the oligonucleotide primers 5′ ggcagccatatgggagtggaggaaccggtatac 3′ ( forward ) and 5′ cggatcctcgagttagcaactggtaacccacaatgg 3′ ( reverse ) . The PCR product was again sub-cloned into the pET15b expression vector between the NdeI and XhoI restriction sites . The C168A mutant with the additional four residues of the core protein ( NproΔ17N-C168A-SDDG ) was cloned similarly using the reverse primer 5′ gtggtgctcgagttagccatcatcagaggcactggtaac 3′ . All constructs were verified using DNA sequencing . The resulting proteins have a hexa-histidine tag ( His-tag ) and the thrombin cleavage sequence ( LVPRGS ) on the N-terminus of the protein . The Npro mutants were expressed and purified as described in ref . 28 . His-tagged Npro proteins , purified using Talon metal affinity chromatography resin ( Clontech ) were pooled and dialyzed in buffer A ( 20 mM Tris pH 8 . 0 , 100 mM NaCl and 5 mM β-mercaptoethanol ) overnight , and the N-terminal His-tag cleaved using thrombin protease immobilized on agarose beads ( ThermoScientific ) . The cleavage reaction was performed with 1% thrombin ( w/w ) at room temperature in buffer A for 4 hrs . Cleaved Npro-Δ17N was separated by passing the mixture through the Talon resin equilibrated in buffer A . Npro-Δ17N-C168A was purified similarly except that 10% glycerol was added during thrombin cleavage of the His-tag . Glycerol was necessary to stabilize the protein during the cleavage reaction at room temperature . The protein was >95% pure judged by SDS-PAGE . Both proteins were monomers in solution as judged by size-exclusion chromatography . Proteins were concentrated to ∼4 . 5 mg/ml . Initial crystallization trials were conducted using the sitting drop vapor diffusion method in 96-well plates using a Phoenix RE liquid handling robot ( Rigaku ) . 200 nL protein solution was mixed with equal volumes of a range of precipitants obtained from commercially available crystal screens . Crystals appeared in several conditions within a week . Diffraction quality crystals of Npro-Δ17N grew in 25% PEG3350 , 0 . 2 M MgCl2 ( or 0 . 2 M ( NH4 ) 2SO4 ) and 0 . 1 M Hepes pH 7 . 4 . Npro-Δ17N-C168A crystallized in 25% PEG3350 0 . 2 M ( NH4 ) 2SO4 ( or 0 . 2 M Li2SO4 ) and 0 . 1 M Hepes pH 7 . 5 . The Npro-Δ17N crystals were cryo-cooled at 100 K using paratone as cryo-protectant . High redundancy data was collected using Bruker's Microstar microfocus X-ray Source equipped with a Platinum135 CCD detector . The data were indexed and merged using the Bruker AXS PROTEUM2 software suite for X-ray crystallography ( Bruker AXS ( 2010 ) . PROTEUM2 , Version 2010 . 5 , Bruker AXS Inc . , Madison , Wisconsin , USA ) . The crystals diffracted to 1 . 6 Å resolution and belonged to the space group P21212 with a = 60 . 1 , b = 62 . 6 , c = 30 . 8 Å . The solvent content was 35% with a monomer in the asymmetric unit . The structure of Npro-Δ17N was solved via the single wavelength anomalous dispersion method ( SAD ) using the anomalous signal present in sulfur atoms illuminated by a copper K-α home X-ray source . Determination of the positions of sulfur atoms , phasing , and calculation of electron density maps were performed using AutoSol wizard in the Phenix package [42] , [43] . The initial atomic model was obtained using the Autobuild wizard in Phenix [44] . The final model was achieved using manual model building with the program O [45] followed by iterative cycles of refinement with phenix . refine . All residues from Glu21 to Cys168 were visible in the electron density map except residues 65–71 , which encompasses the catalytic Cys69 . Diffraction data for Npro-Δ17N-C168A crystals was collected to 1 . 6 Å using a Rigaku FRE++ X-ray source and an RAXIS-IV™ detector at UTMB . Data was indexed in the space group P212121 with unit cell dimensions of a = 41 . 5 , b = 58 . 3 , and c = 75 . 5 Å , different from the Npro-Δ17N protein . The solvent content of the crystals was 54% . The structure of Npro-Δ17N-C168A was determined using molecular replacement with the Npro-Δ17N structure as a model . An atomic model was built using Auto-Build , and phenix . refine was used for refinement of the final model . All residues from Met18 to Cys168 were visible except amino acids 145–149 . New crystal packing interactions involving the active site contributed to the stabilization of the helix carrying the nucleophilic Cys69 . Strong density ( visible at >8σ ) at the center of the coordination complex at the active site indicated the presence of a metal ion at the site . SAD data at the zinc absorption edge were collected at the Center for Advanced Microstructures and Devices ( CAMD ) synchrotron macromolecular crystallography beamline at Louisiana State University . An anomalous difference Fourier map was calculated to confirm the presence of zinc . Ramachandran plots for both structures were generated using the program PROCHECK [46] in CCP4 . Data collection and refinement statistics are given in Table 1 . The coordinates and associated structure factors for this publication have been deposited into the Protein Data Bank and assigned the following accession codes: 4H9J and 4H9K for the Npro-Δ17N and Npro-Δ17N-C168A , respectively . | Mammalian cells respond to viral infection by inducing an innate immune response involving interferon-α/β that mediates cellular antiviral defenses . Viruses , in turn , have evolved mechanisms to counter the host's innate immune response by inhibiting the interferon response . Pestiviruses use the virally encoded N-terminal protease ( Npro ) to suppress interferon-α/β induction . Npro first cleaves itself off from the viral polyprotein using its own cysteine protease activity . Released Npro then interacts with interferon regulatory factor-3 ( IRF3 ) , a transcriptional activator of interferon-β , and induces proteasome-mediated degradation of IRF3 . We have determined the crystal structure of Npro from classical swine fever virus . Npro has a unique protease fold consisting of two domains . The N-terminal domain carries the protease active site and has the C-terminus , the auto-cleavage site , bound in the active site . Thus , following auto-cleavage at the C-terminus , Npro obstructs the catalytic site preventing further activity , making the protease active only once in its lifetime . The C-terminal domain carries a zinc-binding site that is required for interaction with IRF3 . Surface mapping of the Npro residues essential for subversion of interferon induction provides insight into the interaction with IRF3 and its subsequent degradation . To our knowledge , this is the first structure of a direct IRF3 antagonist . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [] | 2013 | The Structure of Classical Swine Fever Virus Npro: A Novel Cysteine Autoprotease and Zinc-Binding Protein Involved in Subversion of Type I Interferon Induction |
Partial mosquito-proofing of houses with screens and ceilings has the potential to reduce indoor densities of malaria mosquitoes . We wish to measure whether it will also reduce indoor densities of vectors of neglected tropical diseases . The main house entry points preferred by anopheline and culicine vectors were determined through controlled experiments using specially designed experimental huts and village houses in Lupiro village , southern Tanzania . The benefit of screening different entry points ( eaves , windows and doors ) using PVC-coated fibre glass netting material in terms of reduced indoor densities of mosquitoes was evaluated compared to the control . 23 , 027 mosquitoes were caught with CDC light traps; 77 . 9% ( 17 , 929 ) were Anopheles gambiae sensu lato , of which 66 . 2% were An . arabiensis and 33 . 8% An . gambiae sensu stricto . The remainder comprised 0 . 2% ( 50 ) An . funestus , 10 . 2% ( 2359 ) Culex spp . and 11 . 6% ( 2664 ) Mansonia spp . Screening eaves reduced densities of Anopheles gambiae s . l . ( Relative ratio ( RR ) = 0 . 91; 95% CI = 0 . 84 , 0 . 98; P = 0 . 01 ) ; Mansonia africana ( RR = 0 . 43; 95% CI = 0 . 26 , 0 . 76; P<0 . 001 ) and Mansonia uniformis ( RR = 0 . 37; 95% CI = 0 . 25 , 0 . 56; P<0 . 001 ) but not Culex quinquefasciatus , Cx . univittatus or Cx . theileri . Numbers of these species were reduced by screening windows and doors but this was not significant . This study confirms that across Africa , screening eaves protects households against important mosquito vectors of filariasis , Rift Valley Fever and O'Nyong nyong as well as malaria . While full house screening is required to exclude Culex species mosquitoes , screening of eaves alone or fitting ceilings has considerable potential for integrated control of other vectors of filariasis , arbovirus and malaria .
Houses are the main site for contact between humans and night biting mosquito vectors [1] , [2] . The impact of improved housing on indoor malaria vector densities [3]–[6] and transmission [7] is well established . In Africa , the primary malaria vectors are nocturnal , endophilic and endophagic mosquitoes of the Anopheles gambiae species complex [8] , [9] . These vectors prefer to enter houses via open eaves [2] . Therefore , houses with open eaves or those lacking ceilings have higher numbers of mosquitoes and a greater malaria burden compared to those with closed eaves or with ceilings [3] , [4] , [7] , [10] . Regardless of evidence that improved housing provides protection from Anopheles malaria vectors , its potential to reduce indoor biting densities of other mosquito genera has received little attention , despite the fact that several of these species are known vectors of diseases which cause significant morbidity and mortality . These diseases include lymphatic filariasis , several arboviruses such as Chikungunya , O'Nyong nyong , Rift Valley Fever ( RVF ) and West Nile Virus ( WNV ) ( Table 1 ) . An . gambiae sensu stricto and An . arabiensis are the most abundant malaria vectors in rural tropical African countries and are also the main vectors of filariasis [11] as well as O'Nyong nyong [12] . Mansonia africana and Ma . uniformis are vectors of RVF and filariasis , although the latter predominantly transmits Brugian filariasis in Asia . Integrated control of filariasis and malaria is feasible [13] , [14] due to their co-occurrence in rural areas , where they are often co-endemic and transmitted by the same vectors [15] . Though the main control measure against filariasis is chemotherapy , achieved through mass drug administration , a more holistic approach which integrates other proven interventions may be feasible in many endemic areas [16] . Culex quinquefasciatus is a vector of Wuchereria bancrofti causing lymphatic filariasis in Africa . It is the main vector in urban areas [17] but also contributes to rural transmission . Cx quinquefasciatus is also a vector of other arboviruses such as Chikungunya and West Nile Virus ( Table 1 ) . Several other Culex species transmit other arboviruses in East Africa; these are shown in Table 1 . Crucially , culicines are also the major cause of nuisance biting in rural and especially urban areas [18] . Several studies have shown that the community is sensitive to changes in biting nuisance related to changes in mosquito densities . Uptake of several control measures such as use of house screens [19] and mosquito coils [20] is dependent upon the desire to prevent mosquito bites in addition to preventing diseases . Similarly , use of insecticide treated nets ( ITNs ) is motivated by the desire to prevent nuisance bites [21] , [22] , as shown by reduction in the use of ITNs when mosquito densities are lower due to seasonal decline , [23] , [24] even when mosquito numbers are sufficient for disease transmission to continue . Unfortunately , efficacy of insecticide based interventions declines when resistance develops , as has already been seen in Tanzania [25] , [26] . If people continue to be bitten by nuisance mosquitoes due to development of insecticide resistance , it undermines public acceptance of ITNs as an intervention [27] , [28] . Therefore , there is need to develop supplementary tools for control of nuisance mosquitoes . Reduction in nuisance mosquitoes will increase users' confidence in the available mosquito control measures and therefore also encourage use of other measures . The aim of the study was to evaluate preferential points of entry of different mosquito species into houses . This was determined by indoor densities of different species of mosquitoes when a specific entry point was screened , precisely , eaves , windows and doors compared to an unscreened control . Our overall goal was to evaluate the optimal method needed for house screening in order to provide integrated control of filariasis , arboviruses and malaria vectors .
The experimental hut study was carried out at Lupiro village ( 8 . 01°S and 36 . 63°E ) located in Ulanga district , in the south eastern part of Tanzania . The village lies 300 meters above sea level on the flood plain of Kilombero River , approximately 26 km south of Ifakara town . The climate is hot and humid , experiencing annual rainfall ranging between 1200–1800 mm and annual mean temperature between 20–32°C . This climate and the clearance of a perennial swamp for rice farming creates ideal conditions for perennially abundant populations of both An . gambiae s . s . and An . arabiensis and many species of culicine mosquitoes [29] . Malaria transmission intensity in this village is exceptionally high , averaging between 474 and 851 infectious bites per person per year , despite mosquito net coverage which consistently exceeds 75% [30] . In addition , there have been several cases of RVF and filariasis ( E . Mossdorf pers comm ) . In Ulanga and Kilombero DSS ( Demographic Surveillance System ) areas , most of the local houses have mud walls ( 56% ) , while the remainder are made of baked mud bricks . The roofs are mostly thatched ( 70% ) or of corrugated iron . The houses chosen for these experiments therefore had mud walls and thatched roofs with open eaves and one or two windows ( Figure 1 ) . Cooking was mainly done outside of the hut and each of the local houses selected had two or three people living in them . Several prototypes of a new design of experimental huts ( Figure 2 ) ( Moore et al . , Submitted ) were built in Lupiro with the intention of representing , as closely as possible , the key structural features of local housing in southern Tanzania ( i . e . brick or mud huts with corrugated iron or thatched roofing ) . These huts were designed in kit form for ease of portability , with a galvanized piping framework so that the entire hut could be flat packed . The roof is corrugated iron covered with grass thatch on the top , to simulate the temperature of local houses with thatched roofing . The outer walls are constructed from wooden planks or canvas . The inner walls are removable panels coated with mud , to simulate local mud walls . Two huts were constructed to mimic average local huts in the village . These were 6 . 5 m long , 3 . 5 m wide and 2 m high , ( the size of these huts was determined by measuring 100 houses in Lupiro and calculating the average dimensions ) . The remaining two were smaller , at 3 m long , 3 . 5 m wide and 2 m high . The height of each structure measured 2 . 5 m at the roof apex . Each experimental hut had one door and two window openings as this was the median number seen in local houses . Two blocks of four huts were used for these experiments: one block of four local houses and one block of four experimental huts . The selected houses were located nearest to the experimental huts and were selected to be approximately 50 m apart from each other . Two male volunteers slept in each experimental hut . The volunteers were not rotated between huts but remained in the same hut for the duration of the study . The bias created by variation in human attractiveness to mosquitoes and spatial variation between huts were therefore combined and treated as a single source of bias in the statistical analysis . For each of the two blocks of four houses , the following sequence of experimental treatments was completed . In each block , four repetitions of four experimental treatment arrangements were completed between 4th December and 19th December 2007 . This is the peak of short rains and therefore there is wide spread flooding leading to high densities of mosquitoes of all genera . Each repetition included three nights during which three of the four houses had the same one of the three potential entry points screened while the remaining fourth house was completely unscreened . On the first night of each repetition , all the four huts remained completely unscreened . For the subsequent three nights of each repetition , all the three treatments were changed each night from screening the eaves to windows and then doors , in that order . For each night , a different hut was chosen within each block to have no entry point screened , so that at the end of the four repetitions , all four huts had acted as these contemporaneous controls . The treatments were rotated across all the huts systematically . Rotation of treatments reduced the bias of mosquito collections between the huts . PVC-coated fibreglass netting material ( Elastic Manufacturing , Tanzania ) was used to screen specific entry points each particular night . The netting was cut to fit each of the entry points ( doors windows and eaves ) . In the experimental huts , the size of the windows , eaves and doors was uniform for all the huts . Screens were fitted on the experimental huts by hook and loop fasteners . In the local houses , the screens were nailed onto the wall ( mud wall ) . The nails could be removed easily each morning at the end of the experiments . Due to uneven wall surfaces of the local huts , small gaps were found between the netting and the wall . These gaps were blocked with cotton wool to create a complete barrier . CDC light trap is an appropriate tool for sampling mosquito vectors that would otherwise bite humans , thus being comparable to human landing catches [31]–[34] . A CDC miniature light trap ( model 512 ) was positioned approximately 1 m above the ground . It was placed next to the bed ( at the foot end ) occupied by an adult male volunteer , under an untreated bed net [32] . Volunteers operated light traps from 19:00 to 07:00 hrs each night . Although no attempt was made to control times at which occupants slept , this period typically approximated 19:00 hrs to 07:00 hrs . Traps were collected from each house every morning at 07 . 00 . Collection bags were then placed in a plastic bucket , and mosquitoes were killed using cotton wool treated with chloroform . The mosquitoes were morphologically identified to genus level each morning in the field while they were still fresh . Mosquitoes were stored in small centrifuge tubes which contained tissue paper with silica gel beneath , then transported to the laboratory where they were stored at −20°C , until further identification . Further identification was done to species level using polymerase chain reaction ( PCR ) for An . gambiae s . l . [35] . Mosquitoes allocated for PCR were sampled randomly from An . gambiae s . l . , mosquitoes collected from different trap nights by placing labelled tubes in a box and picking them at random . Morphological identification of culicines was done using a key [36] . Volunteers were recruited only if they agreed to participate in the study and signed a written informed consent form . To minimize risk of infection of mosquito borne diseases , participants were provided with untreated nets . In addition , they were offered free malaria screening and treatment . Ethical approval was granted by Ifakara Health Institute ( IHI ) ( IHRDC/IRB/No . A-014-2007 , IHRDC/IRB/No . A-019-2007 ) and the National Institute of Medical Research ( NIMR/HQ/R . 8a/Vol . W710 ) . Centre for Disease Control ( CDC ) ethical review deemed the work non-human subjects research . Generalized estimating equations were used with SPSS 15 to estimate the effect of screening specific entry points , which was treated as a categorical independent variable , on indoor mosquito densities relative to unscreened controls . House number was fitted as a subject effect and day as the within-subject variable , with an exchangeable working correlation matrix , to account for spatial and temporal heterogeneity in the dependent variable , namely number of mosquitoes of a given mosquito taxon caught in each house on each night . Note that , each species was analyzed separately using generalised estimating equation model . An . gambiae s . l . mosquito catch had a normal distribution and was fitted to an identity link . All the other species were negatively skewed and were therefore fitted with a negative binomial and a log link function . The model was used to derive the relative rates and their 95% confidence intervals . Binary logistic regression was used to test the strength of the influence of different treatments on the proportion of An . arabiensis and An . gambiae s . s caught , that were identified to sibling species by PCR . The independent variables fitted in the model were treatment and house number . The outcome variable was binomial; An . arabiensis and An . gambiae s . s were coded as 1 and 0 respectively and the effect of treatment on the odds ratio of finding An . arabiensis relative to An . gambiae s . s . was calculated .
During the cumulative 16 nights of sampling , with the CDC light traps , 77 . 9% ( 17 , 929 ) of the total catch were Anopheles gambiae s . l . This species complex comprised 66 . 2% ( 738 ) An . arabiensis and 33 . 8% ( n = 377 ) An . gambiae s . s ( n = 1115 successful PCR amplifications ) . There were only 0 . 2% ( n = 50 ) An . funestus species complex caught in the entire study . One tenth ( 10 . 2% , n = 2359 ) of all mosquitoes collected were various Culex spp . Three quarters ( 76 . 9% ) of Culex spp . were identified as Cx . pipiens complex of which four fifths ( 80 . 3% , n = 875 ) were Cx pipiens quinquefasciatus while the remainder ( 19 . 7% , n = 214 ) were Cx . pipiens pipiens . Other culicines included Cx . univittatus and Cx . theileri ( 20 . 0% of the total Culex spp ) . Just over one tenth ( 11 . 6% ) of all mosquitoes collected were Mansonia spp . , of which more than half ( 58 . 3% n = 1038 ) were Ma . uniformis and the remaining 41 . 6% ( n = 742 ) were Ma . africana . Other species of culicines caught in smaller numbers were , Cx . horridis ( n = 7 ) , Cx . andersanius ( n = 11 ) , Cx . acrostichalis ( n = 43 ) , Cx . rubinotus ( n = 30 ) , Cx . sitiens ( n = 5 ) , Cx . simpsoni ( n = 18 ) , and Cx . aureus ( n = 69 ) . A summary of the median indoor density species collections when each entry point was screened is presented in Table 2 and a statistical estimate of the impact of screening is presented in Table 3 . An . gambiae s . l . mosquitoes were less likely to be found in houses with screened eaves ( Table 3 ) . Binary logistic regression revealed that both treatment ( screening of various entry points ) and house did not affect the proportion of An . gambiae s . s . versus that of An . arabiensis mosquitoes , ( Treatment , Odds Ratio [95% confidence interval] = 1 . 06 [0 . 94 , 1 . 20]; Wald Chi square = 0 . 87; P = 0 . 35 ) , indicating that the effect of treatment on the two sibling species was similar . Screening eaves also reduced both Ma . africana and Ma . uniformis mosquito densities by almost half ( Table 3 ) . Screening windows and the door reduced indoor densities of Cx . quinquefasciatus , Cx . theileri and Cx . univittatus mosquito densities by a quarter or more although this was not significant ( Table 3 ) . The relative densities of Cx . univittatus and Cx . theileri mosquitoes were increased when eaves were screened respectively ( Table 3 ) .
More than three quarters of the mosquitoes caught during the study were An . gambiae s . l . a major vector of both lymphatic filariasis as well as malaria in this area and across most of Africa [11] . An . funestus complex mosquitoes caught in this study were not identified to species level . However , other studies from Tanzania have shown that this species complex shows distinct behavioural differences . An . funestus s . s . mosquitoes are mainly endophagic while others like An . rivulorum are mainly exophagic [37] . Therefore , since mosquitoes were collected indoors we assume that most of the mosquitoes caught were An . funestus s . s . Culicine mosquitoes collected in this study contribute to the transmission of filariasis and arboviruses ( Table 1 ) . Cx . quinquefasciatus was the most abundant Culex species caught . Significant numbers of Cx . univittatus and Cx theileri mosquitoes were also caught . Ma . africana has been incriminated as a vector of RVF [38]–[40] , and was present in high densities during an outbreak of RVF among humans at the field site ( E . Mossdorf pers comm ) . Most of the mosquitoes caught were unfed , and therefore considered to be caught in the act of host seeking [31] , [34] . Studies carried out previously in the same experimental huts ( unpublished data ) indicated that there were very low densities of indoor resting mosquitoes . Only 0 . 35% of the mosquitoes caught in that particular study were caught resting . Therefore it may be assumed that indoor resting mosquitoes were present in insufficient numbers to bias the outcome of the screening experiments . Consistent with previous reports [3]–[5] , Anopheles gambiae s . s . and An . arabiensis mosquitoes were noted to prefer eaves as the main entry point , demonstrated by reduced indoor densities when this particular entry point was screened . Both Ma . africana and Ma . uniformis also preferred entry via eaves as exhibited by reduced indoor densities when eaves were screened . This data indicates that transmission of the diseases these vectors transmit could be prevented by blocking eaves [2] . A study carried out in the Gambia showed a reduction in culicine indoor densities in houses with closed eaves but in association with horses tethered outside and with increased room height [41] . Indoor Cx . pipiens s . l . densities were reduced by 38% when eaves were closed [41] . On the contrary , a second study recently carried out in The Gambia measured the impact of closing eaves in addition to screening the doors in houses with no windows . The same study indicated that there was no additional reduction in culicine mosquito densities when eaves were blocked [42] . In the present study , we have shown that Cx . quinquefasciatus , Cx . univittatus and Cx . theileri mainly prefer windows and doors as their main point of entry . It is also important to note that when eaves were screened and windows and doors were left open , indoor densities of Cx . univittatus and Cx . theileri mosquitoes were increased in comparison to when all the three entry points were left unscreened . This indicated the importance of screening all the three entry points to achieve control of Culex spp . mosquitoes . Effectiveness of house proofing on mosquito vectors depends on the interaction between their feeding behaviour and human behaviour especially when and where people eat and sleep [43]–[45] . House screening will only reduce exposure to endophagic mosquito vectors . Several anophelines in Africa are endophagic; therefore , house screening would be highly effective . Since most Culex spp . mosquitoes are commonly thought to be predominantly exophagic , then it raises concerns of whether house screening would be effective against them . However , varying levels of both endophagy and exophagy observed in different species; differ from one region to another . In East and West Africa Cx quinquefasciatus is more endophagic [46] . Cx . univittatus and Cx theileri exhibit both exophagy and endophagy in some areas [47]–[49] . In addition , our study also demonstrates endophagy by these Culex species . Our findings suggest that screening eaves reduces indoor densities of Anopheles gambiae s . l . as well as Mansonia spp . both of which are vectors of several neglected tropical diseases in rural areas of Africa and some parts of Asia . Blocking eaves and full house screening , as a control tool against mosquito vectors may reduce nuisance mosquitoes and thus encourage uptake of control interventions which rely on acceptance , participation and even investment by the community . Screening of eaves and/or installation of ceilings may prove to be practical and affordable where existing house designs prove amenable to such modifications . While most of the African population does not live in houses as uniform as our experimental huts , it is encouraging that mosquito proofing of houses by screening the eaves or installing ceilings has proven equally effective for anophelines and some culicines in rural settings in both East and West Africa . Blocking the eaves of the mud-walled , thatch-roofed village houses included in this Tanzanian study yielded results which are remarkably consistent with those observed when netting ceilings and screened eaves were installed into typical houses in The Gambia despite the wide geographical separation between them [3] . Recent evidence from urban Dar es Salaam [19] suggests that communities perceive closed ceilings and window screening as successful means to prevent house entry by mosquitoes . They demonstrate high levels of acceptance , uptake and even investment , despite the fact that this intervention has never been specifically promoted on this basis . We suggest that the true full potential of protecting houses against house entry by culicine and anopheline mosquitoes , could be better achieved through insecticide treated screening material for targeted killing by placing them on either eaves , windows and doors . | Mosquito vectors that transmit filariasis and several arboviruses such as Rift Valley Fever , Chikungunya and O'Nyong nyong as well as malaria co-occur across tropical Africa . These diseases are co-endemic in most rural African countries where they are transmitted by the same mosquito vectors . The only control measure currently in widespread use is mass drug administration for filariasis . In this study , we used controlled experiments to evaluate the benefit of screening the main mosquito entry points into houses , namely , eaves , windows and doors . This study aims to illustrate the potential of screening specific house openings with the intention of preventing endophagic mosquitoes from entering houses and thus reducing contact between humans and vectors of neglected tropical diseases . This study confirms that while full house screening is effective for reducing indoor densities of Culex spp . mosquitoes , screening of eaves alone has a great potential for integrated control of neglected tropical diseases and malaria . | [
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] | [
"infectious",
"diseases/neglected",
"tropical",
"diseases",
"infectious",
"diseases/epidemiology",
"and",
"control",
"of",
"infectious",
"diseases"
] | 2010 | Screening Mosquito House Entry Points as a Potential Method for Integrated Control of Endophagic Filariasis, Arbovirus and Malaria Vectors |
Periodontitis is a common human chronic inflammatory disease that results in the destruction of the tooth attachment apparatus and tooth loss . Although infections with periopathogenic bacteria such as Porphyromonas gingivalis ( P . gingivalis ) and Fusobacterium nucleatum ( F . nucleatum ) are essential for inducing periodontitis , the nature and magnitude of the disease is determined by the host's immune response . Here , we investigate the role played by the NK killer receptor NKp46 ( NCR1 in mice ) , in the pathogenesis of periodontitis . Using an oral infection periodontitis model we demonstrate that following F . nucleatum infection no alveolar bone loss is observed in mice deficient for NCR1 expression , whereas around 20% bone loss is observed in wild type mice and in mice infected with P . gingivalis . By using subcutaneous chambers inoculated with F . nucleatum we demonstrate that immune cells , including NK cells , rapidly accumulate in the chambers and that this leads to a fast and transient , NCR1-dependant TNF-α secretion . We further show that both the mouse NCR1 and the human NKp46 bind directly to F . nucleatum and we demonstrate that this binding is sensitive to heat , to proteinase K and to pronase treatments . Finally , we show in vitro that the interaction of NK cells with F . nucleatum leads to an NCR1-dependent secretion of TNF-α . Thus , the present study provides the first evidence that NCR1 and NKp46 directly recognize a periodontal pathogen and that this interaction influences the outcome of F . nucleatum-mediated periodontitis .
Chronic inflammatory periodontal disease is initiated by several bacterial pathogens . The infection leads to an inflammatory process which results in the destruction of the dental attachment apparatus associated with tooth loss in adults over the age of 35 . As such , it affects about one-half of working American adults [1] . The health risks of periodontal disease are not limited to the dentition . Increasing evidence suggests that periodontitis may be an aggravating factor which significantly enhances the risk for developing bacterial endocarditis , aspiration pneumonia , osteomyelitis in children , preterm low birth weight , coronary heart disease , cerebral infarction , atherosclerosis and diabetes mellitus [2]–[7] . Recently , several reports also showed a strong association between rheumatoid arthritis and periodontitis [8] . This correlation may have a causative nature due to protein citrullination by P . gingivalis [9] . Nevertheless , although the presence of a periodontal pathogen is prerequisite for periodontitis development , the progression of the disease is dependent on the host innate and adaptive immune responses [10] . NK cells , which are part of the innate immunity , are able to directly kill tumor and virus-infected cells and are also a source for immune mediating cytokines [11] . The function of NK cells is controlled by both inhibitory and activating receptors [12] , [13] . When the activity of NK cells is balanced towards activation , it leads to enhanced killing , enhanced production of cytokines , or both [14] , [15] . The activating NK receptors includes: the NKp44 , NKp30 and NKp46 receptors collectively known as NCR ( Natural Cytotoxicity Receptors ) , 2B4 , NKp80 , CD16 and NKG2D . The ligands recognized by these receptors are either induced by stress ( ligands for NKG2D , see [11] , [16] ) , are viral proteins such as hemagglutinin ( ligands for NKp44 and NKp46 , see [17] , [18] ) and pp65 ( ligands for NKp30 , see [19] ) , are self-ligands [20] or are unknown tumor ligands . Among the NK activating receptors , the NKp46 receptor ( NCR1 in mice ) is the only receptor that is expressed specifically by NK cells of both human and mice [11] , [21] . The direct in vivo role played by NKp46 in the killing of some tumors , influenza virus-infected cells and even self-beta cells was demonstrated using mice in which the NKp46 receptor is “knocked-out” ( Ncr1gfp/gfp mice , see [20] , [21] ) . Importantly , with regard to the current research , NKp46 is not only involved in NK cytotoxicity , but also in production of cytokines [15] , [22] . The activity of NK cells in periodontitis has been scarcely studied and to the best of our knowledge , the involvement of the NK killer receptors in the disease was not investigated at all . This is quite surprising since impaired NK cells cytotoxicity has been described in several genetic and acquired conditions associated with periodontal involvement [23]–[26] . It has also been well documented that the local inflammatory response to periodontal bacteria is maintained and amplified by the production of pro-inflammatory cytokines , including TNF-α , IFN-γ and IL1-β [10] , [27] , [28] , the former two being produced by NK cells [29] , [30] . In addition , a role for antimicrobial peptides , which are also secreted by NK cells [31] , [32] , has been also implicated in the pathogenesis of periodontal disease [33] , [34] . The present study aimed to address the role of NK cells in general , and of their activating receptor NKp46 , in particular , in the pathogenesis of periodontal disease . We demonstrate that F . nucleatum , a major etiologic bacteria involved in the pathogenesis of periodontal disease , is directly recognized by the mouse NCR1 and by the human NKp46 receptors and we show that the interaction between NCR1 and F . nucleatum probably leads to a rapid and specific secretion of TNF-α , resulting in alveolar bone loss . Collectively our results demonstrate that NK cells through their killing receptor NKp46 play a critical role in the pathogenesis of F . nucleatum-mediated periodontal disease .
The important clinical outcome of oral inflammation that is induced by periodontal pathogens is the degradation of gingival connective tissue and the loss of alveolar bone which supports the teeth . Although the mechanisms underlying the inflammatory process which leads to the destruction of the supporting apparatus are not fully understood , TNF-α was demonstrated to be critical for disease induction [35]–[37] . Because TNF-α is secreted by NK cells and because NKp46 triggering can lead to TNF-α secretion we wondered whether NCR1 is involved in alveolar bone loss . To investigate this , we induced experimental periodontitis in wild type C57BL/6 mice and in the NCR1 knockout mice ( Ncr1gfp/gfp , C57BL/6 background ) that were generated in our laboratory by replacing the Ncr1 gene with GFP [21] . Mice were orally infected with F . nucleatum and with P . gingivalis and the levels of alveolar bone loss were quantified by micro-CT ( [38] , [39] , Figure 1A ) . Around 20% bone loss was observed in the Ncr1+/+ wild type C57BL mice infected with F . nucleatum , compared to the Ncr1gfp/gfp KO mice in which bone loss was not detected at all ( Figure 1B ) . Infection with P . gingivalis also resulted in alveolar bone loss which was similar to that of F . nucleatum . However , this bone loss was observed in both wild type and Ncr1gfp/gfp KO mice and no statistically significant differences were observed between the mice ( Figure 1B ) . The experimental periodontis model is not suitable for investigating NK cell activities because of technical problems , tissue limitations and due to ethical restrictions . Therefore , to further investigate the role played by NK cells in F . nucleatum infection we used subcutaneous chambers which were implanted into mice in the dorsolumbar region [40] , [41] . This model allows the direct quantification of inflammatory cells and mediators in the inflammatory exudates following bacterial challenge [40] . Subcutaneous chambers were implanted in Ncr1gfp/gfp KO mice . Two weeks after the implantation , when the outer incision healed completely and the chambers became encapsulated by a thin vascularized layer of fibrous connective tissue , the chambers were inoculated with the two periodontal pathogens F . nucleatum , P . gingivalis , or with Escherichia coli ( E . coli , used as a non–periodontal gram negative bacterial control ) . In agreement with previous reports [41] , [42] , a rapid and massive leukocyte infiltrate was observed in the chamber exudates following bacterial inoculation ( Figure 2 ) . NK cells ( GFP-positive ) were detected in the chambers as early as 2 hours post inoculation ( Figure 2 , left quadrates ) . The percentages and the numbers of NK cells increased at 24 hours following the inoculation , except for the E . coli-inoculated group ( Figure 2 ) . To further characterize the NK population that accumulated in the chambers following bacteria inoculation , we stained the cell content of the chambers with antibodies directed against NK cell receptors; NKG2D , DX5 and NK1 . 1 . As can be seen in Figure 2 , all of the GFP labeled NK cells were NK1 . 1 positive and CD3 negative ( not shown ) and most of them , at 2 hours post infection , were DX5 and NKG2D positive . A reduction in the expression of DX5 and of NKG2D on NK cells was observed twenty-four hours following the inoculation of F . nucleatum and P . gingivalis ( Figure 2 ) . Notably , NK cells ( GFP positive ) were the minor immune cell population present in the chambers ( Figure 2 ) as most of cells that express NK cell markers such as NKG2D , DX5 and NK1 . 1 , were actually GFP negative , ( Figure 2 ) . The presence or absence of NKp46 did not affect bacterial loads in the chambers ( data not shown and figures below ) . Furthermore , both P . gingivalis and F . nucleatum bacteria were detected in the chambers 2 hours following inoculation and little or no bacteria was detected at 24 hours following inoculation ( Figure 3 depicting the Ncr1gfp/gfp mice , and data not shown ) . In contrast , the E . coli load was significantly increased during the tested period ( Figure 3 ) . Thus , we conclude that the vast majority of lymphocytes in the chambers are not NK cells , that the in vivo accumulation of lymphocytes in the chambers is rapid , that low percentages and numbers of NK cells are observed in the chambers and that the NK cell percentages and numbers increase with time concomitantly with the disappearance of the two periodontal pathogens . NKp46/NCR1 is an activating receptor involved in the killing of virus-infected , tumor cells and self-cells [20] , [21] and in the secretion of IFN-γ and of TNF-α in response to various stimulations [29] . We therefore next examined whether the absence of NCR1 will affect the cytokines milieu that is present in the chambers exudates . The exudates of all chambers were collected at time 0 ( before inoculation ) , at 2 and at 24 hours post inoculation and IFN-γ and TNF-α levels were measured . Under the tested experimental conditions , the levels of IFN-γ in the chambers could hardly be detected ( data not shown ) . In contrast , a significant and rapid increase in the levels of TNF-α was observed in the Ncr1+/+ WT mice , 2 hours following the challenge with F . nucleatum ( Figure 4 ) . This elevation was NCR1 dependent , since the levels of TNF-α in the F . nucleatum-challenged Ncr1gfp/gfp KO mice were only modestly increased ( Figure 4 ) . In agreement with the above results , twenty four hours post inoculation of F . nucleatum , concomitantly with the disappearance of the bacteria ( Figure 3 ) , the TNF-α amounts in the exudates dropped to minimal in both the Ncr1+/+ WT and the Ncr1gfp/gfp KO mice ( Figure 4 ) . Interestingly , P . gingivalis did not induce TNF-α secretion . Increase in TNF-α secretion was also observed following E . coli inoculation however this increase was NCR1 independent and was less pronounced as compared with F . nucleatum-mediated secretion ( Figure 4 ) . Furthermore , in agreement with the presence of E . coli in the chambers during the entire tested time period ( Figure 3 ) , the increased TNF-α secretion observed following E . coli inoculation did not significantly changed between 2 hours and 24 hours . We also tried performing an intracellular staining for TNF-α in the NK cells isolated from the chambers . However , these NK cells did not survive the 5 hours Brefeldin A treatment , and without this treatment we could not detect TNF-α . To better characterize the immune cell populations present in the inflamed chambers and to investigate whether in the absence of NCR1 the percentage and the number of immune cells present in the chambers will be altered , we implanted chambers in the NCR1 knockout , Ncr1gfp/gfp mice ( KO ) and in the heterozygous , Ncr1+/gfp mice ( HET , we used the Ncr1+/gfp mice because the heterozygous mice behaves similarity to the WT mice , but have an additional advantage as all NK and NK-like cells are GFP-positive , [21] ) . Since the NCR1 effect was observed 2 hours following F . nucleatum injection ( see above figures ) we inoculated the HET and KO mice with F . nucleatum and assayed for the presence of various immune cells two hours post infection . Surprisingly , as can be seen in Figure 5 , more lymphocytes had accumulated in the F . nucleatum infected chambers in the absence of NCR1 ( the reasons for this are currently unknown ) . The T cell numbers ( CD3+ ) were , in general , twice as large as the NK cell numbers and most of these T cells were helper CD4+ cells ( Figure 5A ) . Macrophages ( detected by F4/80+ staining ) and DC ( detected by CD11c staining ) were also present in the chambers more or less at equal levels , irrespectively of whether NCR1 is present or is absent ( Figure 5B ) . To test whether live bacteria is required for triggering the NCR1-mediated TNF-α secretion we repeated the in vivo chamber model experiments with heat-treated F . nucleatum . As seen in Figure 6A , 2 hours after inoculation with heat-killed F . nucleatum , the percentages of NK cells in the chambers were similar to those observed with the untreated , viable F . nucleatum ( compare Figures 2 and 6 ) . In contrast , 24 hours post inoculation , the percentages of NK cells in the chambers inoculated with the heat-killed F . nucleatum were not elevated ( as observed with the untreated F . nucleatum , Figure 2 ) , but rather stayed constant ( Figure 6A ) . We next tested whether the TNF-α production will be affected by heat treatment . As can be seen in Figure 6B , a significant secretion of TNF-α was still detected following the inoculation of a heat-killed F . nucleatum bacteria ( compared with the KO mice ) , however this TNF-α secretion was significantly less pronounced as compared with the F . nucleatum live bacteria . Thus , we concluded that heat treatment of the bacteria affects NK cell accumulation in the chamber and that it also slightly affects the NCR1-dependent TNFα secretion . To test whether the mouse NCR1 and the human NKp46 directly interact with F . nucleatum we used fusion proteins ( generated as previously described [17] ) , in which the extracellular domains of NCR1 and of NKp46 are fused to the Fc portion of human IgG1 . As a negative control we used an Ig fusion protein made of the membrane proximal domain of NKp46 ( named D1 ) , that does not include the NKp46 site required for its binding [17] , [21] , [43] . Importantly , as can be seen in Figure 7A , a specific , dose dependent , binding of NCR1-Ig and NKp46-Ig was observed to F . nucleatum , whereas little or no binding was observed to P . gingivalis ( Figure 7B ) . We have previously showed that NKp46 and NCR1 recognize influenza virus hemagglutinins [17] , [21] , [43] . To compare the efficiency of the interactions of NKp46 and NCR1 with F . nucleatum to that of hemagglutinin , we infected 721 . 221 cells with the PR8 influenza virus . As can be seen in Figure 7C , in the absence of infection little or no binding was observed when either NKp46-Ig or NCR1-Ig were used . In agreement with previous reports [17] , [21] , [43] , following influenza infection , the binding of NKp46-Ig and NCR1-Ig was substantially increased ( Figure 7D ) . The increased binding was dose-dependent ( Figure 7 ) and was noticed with similar concentrations of fusion proteins that were used to detect binding to F . nucleatum . For unknown reasons the P . gingivalis staining is sometimes observed as a smeared peak ( Figure 7B ) and sometimes appeared as a single peak ( Figure 7E ) . Thus , to further demonstrate that the F . nucleatum recognition by NKp46/NCR1 is specific and that P . gingivalis is indeed not recognized by NKp46/NCR1 we stained the P . gingivalis and the F . nucleatum bacteria with various killer receptors fused to Ig . As can be seen in Figure 7E little or no staining of the Ig-fusion proteins ( NKp46D1-Ig , NCR1-Ig , NKp46-Ig , NKG2D-Ig , NKp44-Ig , NKp30-Ig and CD16-Ig ) was observed with the P . gingivalis , whereas F . nucleatum was recognized only by the human NKp46-Ig and its mouse orthologue NCR1-Ig ( Figure 7E ) . We have previously shown that the recognition of influenza hemagglutinin by NCR1 and by NKp46 requires the sialylation of these receptors and that it is sensitive to digestion with neuroaminidase ( NA ) [17] , [21] , [43] . We therefore tested whether binding NCR1 and NKp46 to the unknown F . nucleatum ligand also involves sialic acid residues . For this , we treated the proteins with bacterial neuraminidase and observed that such treatment did not affect the binding to F . nucleatum ( data not shown ) , suggesting that binding of NCR1 and NKp46 to the fusobacterial ligand is mechanistically different from the binding to viral hemagglutinins . To further delineate the nature of the fusobacterial ligand , we tested the binding of NCR1-Ig and NKp46-Ig to heat-killed F . nucleatum , or to F . nucleatum that was treated with enzymes ( proteinase K or pronase ) known to modify proteins on bacterial surfaces . Because the proteinase K or pronase enzymes are active at 55°C we also tested whether NCR1-Ig and NKp46-Ig interact with F . nucleatum after heating the bacteria at 55°C for 1 hour and observed efficient binding ( data not shown ) . Furthermore , as shown in Supplementary Figure S1 , all treatments did not affect the integrity or the presence of the bacteria . Figure 8 shows that the F . nucleatum ligand is either a protein or a modification found on a protein , as heat , proteinase K and pronase treatments significantly reduced the binding of both the NCR1-Ig and the NKp46-Ig fusion proteins . Next , we tested whether the direct interaction of F . nucleatum and NCR1 is functional . For this purpose , we initially used a reporter system in which we fused the NCR1 receptor to mouse CD3ζ chain and expressed this chimeric receptor in mouse BW cells . Triggering of this chimeric receptor will lead to the secretion of mouse IL-2 , thus reporting for functional interaction of NCR1 with its ligand . However , upon generating this reporter system , a substantial secretion of IL-2 was observed , even without the addition of the bacteria ( Figure 9A ) . A possible explanation to this observation is that the mouse BW cells express an unknown tumor ligand for the mouse NCR1 which consistently triggers IL-2 secretion as BW cells are specifically recognized by NCR1-Ig ( data not shown ) . Because we demonstrated above that both the mouse NCR1 and the human NKp46 receptors directly interact with F . nucleatum , we next examined whether we could use the human NKp46 protein fused to zeta as our reporter system . Importantly , as can be seen in Figure 9A , the self-secretion of IL-2 from the BW-46 cells was much lower than that of BW-NCR1 . Furthermore , the NKp46 reporter system was functional as triggering of NKp46-zeta on BW cells by using plate bound anti-NKp46 resulted in a dose dependent IL-2 secretion ( Figure 9B ) . Therefore , BW-46-zeta transfectants were incubated with viable F . nucleatum , with heat-killed F . nucleatum and with F . nucleatum treated with proteinase K or with pronase . PR8 influenza virus infected 721 . 221 cells were used as positive control ( Figure 9C ) . Incubations were performed for 48 hours in the presence , or in the absence of anti-NKp46 mAb and IL-2 levels were measured in the supernatants . Figure 9C reveals that F . nucleatum induced a significant secretion of IL-2 from BW-NKp46 cells and this secretion was almost completely blocked by the anti-NKp46 mAb . Furthermore , ( in agreement with the above binding results ) , heat-killed bacteria , or bacteria treated with proteinase K or with pronase induced little or no IL-2 secretion . The activation of this reporter system by hemagglutinin seems to be more efficient as compared with F . nucleatum as incubation of the BW-NKp46 cells with infected 721 . 221 cells resulted in pronounced IL-2 secretion . Our final effort was to demonstrate that the direct interaction between NCR1 and F . nucleatum will lead to TNF-α secretion . For this purpose we isolated ( using the autoMACS instrument ) mouse NK cells from Ncr1gfp/gfp and Ncr1+/gfp mice , incubated them with F . nucleatum or with P . gingivalis and tested the supernatants for the presence of TNF-α . As shown in Figure 10 , no TNF-α secretion was observed when NK derived from the Ncr1gfp/gfp mice were incubated with F . nucleatum , while a significant secretion was detected when the Ncr1+/gfp mice were used . The TNF-α secretion was F . nucleatum-specific since P . gingivalis had no effect ( Figure 10 ) .
Periodontitis is a bacterial-induced inflammatory process that leads to the destruction of the tooth-supporting tissues and to tooth loss . It is one of the most common chronic inflammatory diseases in humans [44] and has been suggested as a risk factor for variable systemic conditions including rheumatoid arthritis , atherosclerosis and preterm births [45]–[47] . Here we investigated whether NK cells are involved in periodontitis through the interaction between their specific NK receptor NKp46 with periodontal bacteria . We used two complementary animal models . In the first model we induced experimental periodontitis by orally infecting the Ncr1+/+ and Ncr1gfp/gfp animals with periodontal pathogenic bacteria . We show that in the absence of NCR1 , when mice are infected with F . nucleatum , no loss of alveolar bone around the teeth is observed , while when mice were infected with P . gingivalis bone loss was observed independent of NCR1 . Due to technical and ethical limitations additional experiments could not be investigated in this model and we therefore used the subcutaneous chamber model [40] , [41] to study the NKp46/NCR1 activity with regard to periodontal pathogens . Interestingly , we noticed that a large fraction of immune cells present in the inflamed chambers express NK cell markers such as NKG2D , DX5 and NK1 . 1 , however these cells were not NK ( GFP− ) , or T cells ( CD3− ) . The identity and the function of these cells will be elucidated in future studies . We show that in response to challenge with F . nucleatum and P . gingivalis , NK cells accumulate in the inflamed chambers , that F . nucleatum trigger the secretion of TNF-α and that the presence of TNF-α in the chambers is NCR1-dependent . The interactions of NK cells with the bacteria probably renders them sensitive to in vitro manipulations and therefore we were not able to directly demonstrate that , in the chambers , NK cells are the main producers of TNF-α . Nevertheless , it is likely that TNF-α is indeed secreted by NK cells , in vivo , in response to F . nucleatum because upon incubation of isolated NK cells with F . nucleatum , an NCR1-dependent TNF-α secretion is observed . Because alveolar bone loss is observed following P . gingivalis infection and since TNF-α could hardly be detected in the chambers following P . gingivalis infection we suggest that TNF-α has little role in the induction of the P . gingivalis-mediated bone loss in the system we used . TNF-α is a very potent proinflammatory cytokine having pleotropic effects on both the immune and the skeletal systems . Its role and its contribution to the pathogenesis of chronic periodontitis , tissue destruction and bone loss has been clearly documented [48]–[50] and administration of anti-TNF-α antibodies resulted in reduced alveolar bone loss [51]–[54] . Previous studies demonstrated that the direct recognition of tumor cells [21] , [43] , viral infected cells [17] , [43] and beta cells [20] by NKp46 ( NCR1 ) lead to killing and to the secretion of TNF-α and IFN-γ [22] , [55]–[57] . In our experimental system TNF-α , but not IFN-γ was present in the chambers . Similar observations were noted in other studies and it was proposed that NK cells shape their functional phenotype depending on the nature of the stimuli . For example , some tumors were able to induce TNF-α , but not IFN-γ secretion when co-cultured with naïve NK cells and only when NK cells were activated with IL-2 , a significant increase in IFN-γ could be seen [58] . Another study showed that IL-4 compromised the ability of stimulated NK cells to release IFN-γ , without affecting the secretion of TNF-α [15] and interestingly IL-4 was detected in the chambers' exudates ( data not shown ) . The TNF-α response to F . nucleatum was NCR1-dependant , however , in the chamber experiments , in the absence of NCR1 , the TNF-α secretion was markedly reduced but not totally abrogated . In contrast , no TNF-α secretion was observed from purified NK cells lacking NCR1 that interacted with F . nucleatum . This suggests that in the chambers , cells other than NK cells probably provide additional source for TNF-α . Indeed , previous studies showed that F . nucleatum-derived lipopolysaccharide up-regulated the secretion of the TNF-α by macrophage-like cells [59] . As shown here , macrophages and DCs are also present in the F . nucleatum-inflamed chambers and therefore we can speculate that the low level of TNF-α observed in the chambers implanted in the NCR1gfp/gfp animals is released either by macrophages recruited into the chambers , or by other immune cells . Twenty four hours following bacteria inoculation , the TNF-α levels dramatically dropped to almost baseline levels , in spite of the continuous accumulation of NK cells in the chambers . This transient nature of TNF-α response has been reported previously [60] , [61] and we assume that the TNF-α levels decline due to the elimination of F . nucleatum ( the stimulating antigen ) from the chambers during the study period . In summary , we provide here the first evidence that NKp46 and NCR1 directly recognize a periodontal pathogen and we show that this recognition is heat , proteinase K and pronase sensitive , suggesting that the bacterial ligand is a protein or modifications of protein . Our data support the idea that periodontal pathogens initiate the disease by activating host mechanisms that consequently contribute to the destruction of the supporting apparatus of the periodontium by releasing inflammatory mediators , such as TNF-α .
The generation of the Ncr1gfp/gfp knockout mice has been previously described [21] . All experiments were performed in the specific pathogen–free unit of Hadassah Medical School ( Ein-Kerem , Jerusalem ) according to guidelines of the ethical committee . Ethics statement: This study was carried out in strict accordance with the Law for the Prevention of Cruelty to Animals ( 1994 ) and the regulations of the Hebrew University of Jerusalem Ethics Committee for Maintenance and Experimentation on Laboratory Animals . The protocol was approved by the Committee on the Ethics of Animal Experiments of the Hebrew University of Jerusalem ( Permit Number: 11-5413 ) . All surgery was performed under sodium pentobarbital anesthesia , and all efforts were made to minimize suffering . P . gingivalis strain ATCC3327 and F . nucleatum strain PK1594 were grown in an Bactron II anaerobic ( N2∶CO2∶H2 , 90∶5∶5 ) chamber ( Sheldon Manufacturing Inc . , Cornelius , OR ) at 37°C in Wilkins-Chalgran anaerobic broth ( Fluka , Spain ) anaerobic chamber . E . coli strain ATCC25922 was grown in LB broth ( Lennox , BD , Maryland , USA ) . Bacterial purity was determined by phase contrast microscopy . Bacteria were harvested during the logarithmic phase , washed by centrifugation and resuspended in phosphate-buffered saline ( PBS ) at 107 bacteria/ml [40] , [62] . Heat-killing was performed at 100°C for 10 min . Infection was carried out as described by Baker at al . 2000 and Wilensky et al . 2009 [63] , [64] . In brief , four to five-week-old Ncr1+/+ ( WT ) and Ncr1gfp/gfp ( KO ) mice were given sulfamethoxazole/trimethoprim 0 . 08% and 0 . 016% respectively , in drinking water , ad libitum for 10 days . Three days following the withdrawal of antibiotics ( day 14 ) , the animals were infected with F . nucleatum or with P . gingivalis ( 2×108 CFU in 0 . 2 ml of PBS and 2% carboxymethylcellulose ) or vehicle only . The infection was carried out by gavage into the esophagus and oral cavity 3 times , once every other day . Forty two days after the last infection , the mice were sacrificed and the hemi-maxillae were collected and prepared for bone loss measurements using the micro computerized-tomography ( μCT ) technique [38] . At the end of the experiments mice were killed by CO2 . For quantitative 3-dimensional analysis of the alveolar bone loss , the hemi-maxillae were examined by a desktop micro-CT system ( μCT 40 , Scanco Medical AG , Bassersdorf , Switzerland ) . The sagittal plan of the specimens was set parallel to the X-ray beam axis . The specimens were scanned at a resolution of 12 µm in all 3 spatial dimensions . The scans were Gaussian-filtered and segmented using a multi-level global thresholding procedure for the segmentation of enamel , dentin and bone . Residual supportive bone volume ( RSBV ) was determined separately for either root ( bucco-mesial and bucco-distal ) using a direct 3-dimensional approach [65] . The measured mesio-distal length of the alveolar bone was 204 µm and 120 µm for the mesio-buccal and the disto-buccal roots , respectively . The apical basis of the measured volume was set mesio-distally parallel to the cemento-enamel junction ( CEJ ) and bucco-palatinally parallel to the occlusal plane . The results represented the residual bone above the reference plane in mm3 [38] . Two titanium coil chambers were inserted subcutaneously into anesthetized 6–8 week-old male mice as previously described [41] . After 10–14 days , the chambers were thoroughly emptied of their exudates and P . gingivalis , F . nucleatum and E . coli ( 106 bacteria in 100 µl of PBS ) were immediately injected into each chamber . The exudates were collected at 2 and 24 h post-infection ( each chamber was sampled only once ) . After centrifugation at 4000 rpm for 20 min , the supernatants were collected for bacterial counts and cytokine analysis . To remove red blood cells the pellets were re-suspended in 3 ml of cold lysis buffer containing NH4Cl ( 1 . 55M ) , KHCO3 ( 0 . 138M ) and NaEDTA ( 0 . 684 mM ) at pH 7 . 3 for 3 min , after which the cells were washed and re-suspended in 0 . 5% BSA/PBS for flow cytometry analysis . Antibodies specific for NK cells ( DX5; Caltag Laboratories , Burlingame , CA , USA ) , NKG2D ( CX5; eBioscience , San Diego , CA , USA ) were conjugated to phycoerythrin . DC were identified by CD11c ( eBioscience , San Diego , CA , USA ) , macrophage with F4/80 ( eBioscience , San Diego , CA , USA ) and T cells were stained with CD3 , CD4 and CD8 ( BD Pharmingen , San Diego , CA , USA ) . NK1 . 1 antibody was produced in PK136 hybridoma cell line , as previously described [66] . Staining of NK1 . 1 was visualized with a secondary Cy5-conjugated strepavidin ( Jackson ImmunoResearch Laboratories , West Grove , PA , USA ) . For intracellular staining cells were washed with Perm Wash ( BD Pharmingen , San Diego , CA , USA ) , fixed and treated with Brefeldin A ( Cell Signaling Technology ) for 5 hours at 37°C . Cells were then incubated with antibodies to TNF-α ( BD Pharmingen , San Diego , CA , USA ) . The levels of TNF-α in chamber exudates were determined by ELISA as previously described [67] . Ten microliters of chamber exudates was serially diluted in duplicates in PBS and plated on tryptic soy agar containing sheep blood ( Hylabs , Rehovot , IL ) . Plates with exudates from chambers challenged with P . gingivalis and F . nucleatum were grown under anaerobic conditions for 5–7 days at 37°C , while plates with exudates from E . coli challenged mice were grown in aerobic conditions at 37°C for 24 hours . The bacteria in the different colonies were identified by phase contrast microscopy . In addition , P . gingivalis colonies were confirmed by their black pigment . The generation of NCR1-Ig , NKp46-Ig , NKp46D1-Ig , NKp44 , NKG2D , NKp30 and CD16 was previously described [17] , [18] . Proteins were purified on protein A/G columns as previously described [17] , [18] . 2×105 bacteria were stained with 5 µg fusion proteins ( unless indicated otherwise ) . Staining was performed in the absence of azid and was visualized using a Phycoerythrin or Allophycocyanin conjugated anti-human Ig antibody . Generation of the stable transfectants BW-NCR1 and BW-NKp46 was previously described [17] . 105 treated and untreated F . nucleatum and 5×104 influenza PR8-infected or uninfected 721 . 221 cells were incubated with 5×104 BW-NKp46 cells in the presence and in the absence of 0 . 5 µg/well anti-NKp46 mAb ( generated in our laboratory ) . All assays were performed in medium that do not contain antibiotics , at 37°C for 48 hours . The presence of IL-2 was measured by ELISA kit ( BD Pharmingen , San Diego , CA , USA ) . NK cells were isolated from splenocytes obtained from Ncr1+/gfp and from the Ncr1gfp/gfp mice by using an NK isolation kit ( Miltenyi Biotech , Auburn , CA ) . The percentage of GFP+ cells was assessed by FACS and 5×104 NK cells were cultured with 105 F . nucleatum and P . gingivalis bacteria for 48 hours at 37°C . The presence of TNF-α was determined by ELISA . | Periodontal disease is a common bacterial-induced inflammatory process in which F . nucleatum and P . gingivalis infections lead to the destruction of the teeth supporting attachment apparatus . Previous reports demonstrated that immune cells aggravate the severity of the disease . However , whether NK cells in general and NKp46 ( a major killer receptor expressed by NK cells ) in particular , play a protective or destructive role in this disease is unknown . Using mice deficient in NCR1 ( the mouse orthlogue of NKp46 ) , we demonstrate that oral infection of mice with F . nucleatum , but not with P . gingivalis results in an NCR1-dependent alveolar bone loss . In addition , we show that F . nucleatum is recognized by NCR1 and NKp46 directly and that this recognition leads to the secretion of TNF-α , a central cytokine critically involved in the pathogenesis of periodontal destruction . Collectively , we show that NCR1 and NKp46 play a critical role in the pathogenesis of F . nucleatum-mediated periodontitis . | [
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"biology"
] | 2012 | Direct Recognition of Fusobacterium nucleatum by the NK Cell Natural Cytotoxicity Receptor NKp46 Aggravates Periodontal Disease |
In this study , we found that a subpopulation of CD4+CD25+ ( 85% Foxp3+ ) cells from persons with latent tuberculosis infection ( LTBI ) inhibits growth of M . tuberculosis ( M . tb ) in human monocyte-derived macrophages ( MDMs ) . A soluble factor , Rho GDP dissociation inhibitor ( D4GDI ) , produced by apoptotic CD4+CD25+ ( 85% Foxp3+ ) cells is responsible for this inhibition of M . tb growth in human macrophages and in mice . M . tb-expanded CD4+CD25+Foxp3+D4GDI+ cells do not produce IL-10 , TGF-β and IFN-γ . D4GDI inhibited growth of M . tb in MDMs by enhancing production of IL-1β , TNF-α and ROS , and by increasing apoptosis of M . tb-infected MDMs . D4GDI was concentrated at the site of disease in tuberculosis patients , with higher levels detected in pleural fluid than in serum . However , in response to M . tb , PBMC from tuberculosis patients produced less D4GDI than PBMC from persons with LTBI . M . tb-expanded CD4+CD25+ ( 85% Foxp3+ ) cells and D4GDI induced intracellular M . tb to express the dormancy survival regulator DosR and DosR-dependent genes , suggesting that D4GDI induces a non-replicating state in the pathogen . Our study provides the first evidence that a subpopulation of CD4+CD25+ ( 85% Foxp3+ ) cells enhances immunity to M . tb , and that production of D4GDI by this subpopulation inhibits M . tb growth .
Tuberculosis ( TB ) causes an estimated 1 . 7 million deaths world-wide annually . Reducing morbidity and mortality from TB hinges on developing an improved vaccine , which in turn depends on understanding the immune response . T cells play a crucial role in protective immunity against Mycobacterium tuberculosis ( M . tb ) and other intracellular pathogens [1] in part through production of IFN-γ , which is required for resistance to infection [2] . However , uncontrolled T-cell responses can cause tissue damage , which can be reduced by regulatory CD4+ T-cells ( Tregs ) that express CD25 and Foxp3 [3] . It is generally believed that CD4+CD25+Foxp3+ T-cells inhibit effective immunity to microbial pathogens . CD4+Foxp3+ T-cells accumulate at sites of infection [4] and prevent efficient clearance of infection in mice infected with M . tb [5] . Recently we found that Tregs expand in response to M . tb in healthy tuberculin reactors and that M . tb mannose-capped lipoarabinomannan converts some CD4+CD25-Foxp3- cells to CD4+CD25+Foxp3+ cells [6] . We also found that the programmed death-1 receptor ( PD-1 ) and cytokine inducible SH2-containing protein ( CISH ) control expansion of M . tb-induced Tregs [7] . Furthermore , human CD4+CD25+Foxp3+ cells produce TGF-β and IL-10 , and inhibit IFN-γ production by CD4+ and CD8+ cells [6] , suggesting that they may limit tissue inflammation and destruction . Other studies have found increased number of CD4+Foxp3+ T-cells in TB patients , which inhibit immune responses [6] , [8] , [9] . However , in humans , some activated T-cells express Foxp3 transiently and these cells lack classical regulatory function [10]–[12] . In the current report , we found that M . tb-activated CD4+CD25+ ( 85% Foxp3+ ) T-cells from individuals with latent tuberculosis infection ( LTBI ) can inhibit growth of M . tb in human monocyte-derived macrophages ( MDMs ) through production of Rho GDP dissociation inhibitor ( D4GDI ) , a small GTP-binding protein . In addition , D4GDI reduced the bacillary burden in mice infected with M . tb . These findings demonstrate that human CD4+CD25+ ( 85% Foxp3+ ) T-cells can contribute to immune defenses by enhancing antimicrobial activity .
To determine the effect of M . tb-activated CD4+CD25+Foxp3+ cells on intracellular mycobacterial growth , freshly isolated CD4+ cells and CD14+ monocytes from 6 LTBI were cultured with γ-irradiated M . tb H37Rv . After 4 days , CD4+CD25+ ( 85–90% Foxp3+ ) and CD4+CD25- ( <5% Foxp3+ ) cells were isolated , as outlined in the methods . MDMs from the same donors were infected with M . tb H37Rv at a MOI of 1:2 . 5 , as detailed in the methods , and M . tb-expanded CD4+CD25+ ( 85% Foxp3+ ) or CD4+CD25-Foxp3- cells were cultured in Transwells , or directly in the same wells containing infected macrophages . On day “0” ( 2 hr after infection ) the number of CFU per well were 1 . 2 ± 0 . 38× 106 . After 7 days , 16 . 5 ± 1 . 2 × 106 CFU per well were present in MDMs cultured without T-cells . Addition of CD4+CD25+ ( 85% Foxp3+ ) cells to the same well or in Transwells reduced CFU to 0 . 4 ± 0 . 2 × 106 ( >95% inhibition , p = 0 . 001 for both comparisons , Fig . 1A ) . Addition of CD4+CD25-Foxp3- cells had no effect ( Fig . 1A ) . This surprising result indicates that soluble factors produced by CD4+CD25+ ( 85% Foxp3+ ) cells strongly inhibit M . tb H37Rv growth in macrophages . This finding was unlikely to be due to contamination of CD4+CD25+ cells with activated CD4+ cells because very few cells expressed IFN-γ ( Fig . 2D ) . Furthermore , we added a very low ratio of T-cells to macrophages ( 1:9 ) , whereas published data indicate that much higher ratios of activated CD4+ cells are needed to reduce M . tb growth by 50–80% [13] , [14] . Even though we used low numbers of CD4+CD25-Foxp3+cells for the above study , it is possible that the effects seen in the above experiment may be due to small numbers of contaminating IFN-γ- or IL-22-producing activated T-cells or NK cells . However , in 5 LTBI+ individuals , when CD4+CD25+Foxp3+ cells were cultured in Transwells with M . tb-infected MDMs , addition of anti-IFN-γ or anti-IL-22 , alone or together , did not reduce inhibition of M . tb growth in MDMs by CD4+CD25+ ( 85% Foxp3+ ) cells ( Fig . 1B ) . To identify the soluble factor/s produced by M . tb-expanded CD4+CD25+Foxp3+ cells that inhibit M . tb H37Rv growth in macrophages , CD4+ cells and autologous monocytes from 6 persons with LTBI were cultured with γ-irradiated M . tb H37Rv . After 4 days , CD4+CD25+Foxp3+ and CD4+CD25-Foxp3- cells were isolated by immunomagnetic sorting , and cultured overnight in serum-free medium . The supernatants were concentrated and proteins in the supernatants were resolved by 2D gel electrophoresis . Only supernatants from CD4+CD25+Foxp3+ cells showed strong expression of a protein that was identified as D4GDI ( 100% match by LC MS/MS analysis , S1 Fig . ) . We next found that D4GD1 was abundant in supernatants from M . tb-expanded CD4+CD25+ ( 85% Foxp3+ ) cells but not those from CD4+CD25-Foxp3- cells , using Western blotting ( Fig . 2A ) . As additional confirmation , we isolated CD4+ cells from 6 individuals with LTBI , and cultured them with autologous monocytes and γ-irradiated M . tb for 4 days . We found that 33 ± 4% of CD4+Foxp3+ cells were D4GDI+ , compared to only 3 . 2 ± 0 . 7% of CD4+CD25+Foxp3- cells ( p = 0 . 0003 , Figs . 2B and C ) . This suggests that a subpopulation of CD4+Foxp3+ cells produce D4GDI . In 5 individuals with LTBI , we measured IL-10 , TGF-β and IFN-γ-positive CD4+CD25+Foxp3+D4GDI+ cells in γ-irradiated M . tb-stimulated PBMC . As shown in Fig . 2D , CD4+CD25+Foxp3+D4GDI- but not CD4+CD25+Foxp3+D4GDI+ cells are the source for IL-10 ( 5 ± 1 . 2% vs . 0 . 7 ± 0 . 3% , p = 0 . 02 ) and TGF-β ( 3 . 6 ± 2 . 1% vs . 0 . 5 ± 0 . 5% , p = 0 . 01 ) . CD4+CD25+Foxp3- cells but not CD4+CD25+Foxp3+D4GDI- cells or CD4+CD25+ Foxp3+D4GDI+ cells are the major source or IFN-γ ( 1 . 2 ± 0 . 2% vs . 0 . 4 ± 0 . 2% , and 0 . 64 ± 0 . 1% , p = 0 . 06 ) . We next wished to determine if D4GDI inhibits M . tb H37Rv growth in human MDMs . Recombinant D4GDI had no effect on uninfected MDM viability ( S2 Fig . ) . Recombinant D4GDI reduced CFU in MDMs by 75–84% ( p = 0 . 04 , Fig . 3A ) . Next , we treated M . tb-expanded CD4+CD25+ ( 85% Foxp3+ ) cells with D4GDI siRNA , which inhibited D4GDI mRNA expression by 70% to 80% , as quantified by real-time PCR . In contrast , D4GDI siRNA did not affect Foxp3 expression . In 5 donors with LTBI , CD4+CD25+ ( 85% Foxp3+ ) cells treated with scrambled siRNA reduced M . tb growth in MDMs by 84% ( p = 0 . 002 , Fig . 3B ) . In contrast , CFU were 3-fold higher in MDMs exposed to D4GDI siRNA-transfected CD4+CD25+Foxp3+ cells ( p = 0 . 01 , Fig . 3B ) . CD4+CD25- cells treated with D4GDI or scrambled siRNA did not reduce CFU in MDMs . These findings indicate that D4GDI produced by M . tb-expanded CD4+CD25+ ( 85% Foxp3+ ) T-cells inhibits intracellular growth of M . tb . Our data in humans ( Fig . 3 ) suggest that CD4+CD25+ ( 85% Foxp3+ ) cells inhibit growth of M . tb through production of D4GDI . To determine if these cells express D4GDI during M . tb infection in vivo , we infected C57BL/6 mice with M . tb H37Rv . After 30 days , we quantified CD4+CD25+Foxp3+D4GDI+ cells in the lungs of uninfected and M . tb H37Rv-infected mice . Immunolabeling and flow cytometry showed that the total number of CD4+ cells increased 4 . 5 fold ( p = 0 . 04 , Fig . 4A ) , CD4+CD25+Foxp3+ cells increased around 9 fold ( p = 0 . 009 , Fig . 4B ) and CD4+CD25+Foxp3+D4GDI+ cells increased more than 6-fold , compared to uninfected mice ( p = 0 . 04 , Fig . 4C ) . Further , we asked whether recombinant D4GDI can reduce bacterial burden in M . tb-infected mice . We infected C57BL/6 wild type mice with M . tb H37Rv by aerosol . Some infected mice were given recombinant D4GDI ( 10 ng/ml ) through tail vein injection 0 , 4 , 8 , 12 , 16 , 20 , 24 and 28 days after infection . Thirty days later , we measured CFU in the lungs . Recombinant D4GDI reduced CFU by 4 fold ( p = 0 . 0001 , Fig . 4D ) . These findings suggest that D4GDI produced by M . tb-expanded CD4+CD25+Foxp3+ T-cells inhibits M . tb growth in mice . Our findings above suggest that T-cell supernatants contain D4GDI , which inhibits growth of M . tb in MDMs ( Fig . 1 and S1 Fig . ) . However , in humans , D4GDI is expressed primarily by T and B cells [15] and is not a secreted protein . We asked whether D4GDI is released when terminally differentiated Foxp3+ cells undergo apoptosis . CD4+ cells and autologous monocytes from 6 persons with LTBI were cultured with γ-irradiated M . tb H37Rv . After 4 days , annexinV expression by CD4+CD25+Foxp3+ , CD4+CD25+Foxp3- and CD4+CD25-Foxp3- cells was determined by flow cytometry . Among CD4+ cells exposed to γ-irradiated M . tb , 7 . 2 ± 1 . 9% of CD25+FoxP3+D4GDI+ , 4 . 7 ± 0 . 3% of CD25+FoxP3+D4GDI- and 1 . 5 ± 0 . 6% of CD4+CD25+ FoxP3-D4GDI- cells are annexinV+ ( Figs . 5A and C ) . As an alternative measure of apoptosis , we determined caspase 3 expression in cultured cells . Similar to the above findings , among CD4+ cells exposed to γ-irradiated M . tb , 15 . 8 ± 3 . 3% of CD25+Foxp3+D4GDI+ and 0 . 82 ± 0 . 1% of CD25+Foxp3+D4GDI-cells were caspase 3+ ( S3 Fig . ) . Among CD4+CD25+Foxp3- cells 3 . 5 ± 2 . 1% of them were caspase 3+ ( S3 Fig . ) and none were D4GDI+ , suggesting that only a subpopulation of CD4+Foxp3+D4GDI+ cells that undergo apoptosis release D4GDI . To further determine if D4GDI is specifically released by apoptotic CD4+Foxp3+ cells but not by CD4+Foxp3- cells , we cultured the latter cells in the presence of cyclosporin A ( 10 μg/ml ) , a known inducer of CD4+ T-cell apoptosis . As shown in S4 Fig . , apoptotic CD4+Foxp3- cells did not express D4GDI despite induction of apoptosis . We next determined whether MDMs can take up D4GDI . MDMs from 6 healthy donors were infected with GFP- M . tb H37Rv as described in the methods , and some of the uninfected and infected MDMs were cultured with N-terminal-tagged GST-D4GDI fusion protein . Using confocal microscopy , as described in the methods , we found significant amounts of internalized D4GDI fusion protein in M . tb H37Rv-infected MDMs ( S5 Fig . ) . To identify molecules that control D4GDI-mediated inhibition of M . tb growth in MDMs , we cultured M . tb H37Rv-infected MDMs from 5 to 6 healthy donors , with or without recombinant D4GDI . After 6 hr , culture supernatants were collected , and levels of 27 different cytokines and chemokines were measured , using a multiplex ELISA system . Recombinant D4GDI increased levels of interleukin-1 beta ( IL-1β ) from 43 ± 33 pg/ml to 193 ± 104 pg/ml ( p = 0 . 02 , Fig . 6A ) , tumor necrosis factor-alpha ( TNF- α ) from 88 ± 126 pg/ml to 129 ± 111 pg/ml ( p = 0 . 03 , Fig . 6B ) , and granulocyte colony-stimulating factor ( G-CSF ) from 122 ± 67 pg/ml to 223 ± 135 pg/ml ( p = 0 . 02 , Fig . 6C ) . Recombinant D4GDI had no effect on cytokine production by uninfected MDMs ( Fig . 6 ) . To identify additional molecules that are involved in D4GDI-mediated inhibition of M . tb growth , we compared gene expression profiles of M . tb-infected MDMs , cultured with or without recombinant D4GDI , using microarray analysis for 40 , 000 genes . MDMs from 4 healthy donors were infected with M . tb H37Rv and some of the infected MDMs were cultured with recombinant D4GDI . After 6 hr , total RNA was extracted from control , infected and D4GDI-treated infected MDMs . In all 4 donors , mRNA expression was >1 . 25-fold higher for 42 genes <1 . 25-fold lower for 4 genes in D4GDI-treated cells ( S1 Table ) . Because the focus of our study is to identify the molecules that are involved in D4GDI-dependent inhibition of M . tb H37Rv growth , we selected four upregulated genes , IL-1β , TNF-α , MMP-12 and IL-27 , for further study , because these molecules have been shown to play important roles in M . tb infection . D4GDI induced G-CSF production ( Fig . 6C ) but we did not find differences in mRNA expression . We also included G-CSF and a downregulated gene called SIVA ( proapoptotic molecule ) for further study . Transfection of M . tb-infected MDMs with IL-1β and TNF-α siRNAs reduced mycobacterial growth inhibition by D4GDI by 80% ( p<0 . 05 , Fig . 6H ) and G-CSF siRNA decreased D4GDI-induced growth inhibition by 30% ( p<0 . 05 , Fig . 6H ) . In contrast , MMP-12 , SIVA and IL-27 siRNAs had no effect on D4GDI-dependent M . tb H37Rv growth inhibition ( Fig . 6H ) . Because D4GDI increases production of ROS by mononuclear phagocytes in other experimental systems [15] , [16] , we wished to determine if D4GDI-induced IL-1β- , TNF-α- and G-CSF-dependent growth inhibition depended on ROS production . ROS production by MDMs was enhanced by infection with M . tb H37Rv , and this was further increased by addition of D4GDI ( MFI of 1286 . 8 ± 501 . 9 vs . 598 . 4 ± 158 . 3 , p = 0 . 01 , Fig . 7A ) . ROS levels were similar with addition of D4GDI and hydrogen peroxide ( Fig . 7A ) . To determine if D4GDI-dependent ROS production inhibits growth of M . tb H37Rv , we used N-acetylcysteine ( NAC ) , a scavenger of ROS . D4GDI reduced CFU in infected MDMs by 84% and NAC completely abrogated this effect ( p = 0 . 02 , Fig . 7B ) , suggesting that D4GDI inhibits M . tb H37Rv growth by inducing M . tb-infected MDMs to produce ROS . We also found that transfection of M . tb-infected MDMs with IL-1β , TNF-α and G-CSF siRNAs reduced D4GDI-induced ROS production ( p<0 . 05 Fig . 7C ) . D4GDI increased the production of IL-1β , TNF-α , G-CSF and ROS by M . tb H37Rv-infected MDMs to inhibit M . tb growth . We next asked whether D4GDI-dependent growth inhibition is due to enhanced ROS-induced apoptosis of infected MDMs . M . tb H37Rv infection increased the percentage of apoptotic MDMs and this was further increased by addition of D4GDI ( 5 . 6 ± 0 . 9% vs . 1 . 7 ± 0 . 9% , Fig . 8 ) . Addition of NAC , a scavenger of ROS , inhibited D4GDI-mediated apoptosis . We also found that D4GDI-induced apoptosis was reduced by transfection of M . tb-infected MDMs with siRNAs for IL-1β or TNF-α ( p<0 . 05 ) but not by G-CSF siRNA ( Fig . 8 ) . To characterize the physiologic state of M . tb in MDMs during exposure to M . tb-expanded CD4+CD25+Foxp3+ T-cells , we used real-time PCR to measure expression of dosR , which encodes a transcription factor that is upregulated in response to hypoxia and nitric oxide [17]-[19] . DosR activates expression of multiple genes when M . tb enters a nonreplicative state , including dormancy induced by anaerobic conditions [20] . MDMs from 7 healthy tuberculin reactors were infected with M . tb H37Rv and cultured with autologous M . tb-expanded CD4+CD25+ ( 85% Foxp3+ ) or CD4+CD25- cells in Transwells . After 7 days , dosR expression was increased 4-fold in MDMs exposed to CD4+CD25+ ( 85% Foxp3+ ) cells ( p = 0 . 04 , Fig . 9A ) , but not in those exposed to CD4+CD25-Foxp3- cells . Expression of Rv3130c and hspX , which are part of the DosR regulon , was also markedly increased in MDMs exposed to CD4+CD25+ ( 85% Foxp3+ ) cells ( p<0 . 07 , Fig . 9A ) . Addition of D4GDI to M . tb-infected MDMs also induced dosR expression two-fold ( p = 0 . 004 , Fig . 9B ) . Because DosR can be activated by multiple stresses [21] , we evaluated other stress-associated regulators to determine whether D4GDI induced a generalized mycobacterial stress response that was not associated with non-replicating persistence . Expression of these genes ( trcR , sigE and sigH ) was not increased after exposure to CD4+CD25+ ( 85% Foxp3+ ) cells ( Fig . 9A ) . A M . tb dosR deletion mutant showed no growth defect in MDMs , compared to wild type M . tb H37Rv , but addition of CD4+CD25+ ( 85% Foxp3+ ) cells reduced CFU of wild type M . tb H37Rv by 80% , compared to only 40% for the dosR mutant ( Fig . 9C ) . The dosR complemented strain behaved similarly to wild type M . tb H37Rv , confirming that this difference was due to dosR and not to effects on adjacent M . tb genes . These findings demonstrate that M . tb-expanded CD4+CD25+Foxp3+ T-cells and D4GDI inhibit intracellular mycobacterial growth through mechanisms that upregulate expression of dosR , and may induce M . tb to enter a state of non-replicating persistence . To investigate the potential contribution of D4GDI in vivo at the site of disease , we studied patients with tuberculous pleuritis , as the pleural immune response usually leads to clearing of local infection [22] , [23] . Western blotting showed that D4GDI expression was significantly higher in pleural fluid than in serum of 10 patients with tuberculous pleuritis ( Fig . 10A ) , suggesting that D4GDI is part of an effective local human immune response to M . tb infection . In contrast to tuberculous pleurtis , systemic immunity is reduced in patients with pulmonary TB , whose PBMC show decreased production of IFN-γ in response to mycobacterial antigens , compared to healthy persons with LTBI , who have protective immunity to M . tb [8] . We stimulated PBMC from TB patients and donors with LTBI with γ-irradiated M . tb , and measured D4GDI levels in culture supernatants by Western blotting . Expression of D4GDI was significantly reduced in TB patients , compared to findings in donors with LTBI+ ( Fig . 10B ) . When CD4+ cells from 5 TB patients and 5 donors with LTBI+ were cultured with autologous monocytes and γ-irradiated M . tb for 4 days , the percentages of CD4+CD25+Foxp3+D4GDI+ cells were higher in persons with LTBI+ ( p = 0 . 0004 , Fig . 10C ) compared to TB patients , suggesting reduced expansion of D4GDI+ cells in TB patients .
In the current study we found that human CD4+CD25+ ( 85% Foxp3+ ) cells inhibit growth of M . tb in macrophages , providing the first evidence that CD4+CD25+ ( 85% Foxp3+ ) cells contribute to effective immunity against an intracellular pathogen . These salutary effects were mediated through production of D4GDI , which enhanced apoptosis of MDMs to inhibit M . tb growth through the production of IL-1β , TNF-α and reactive oxygen species . D4GDI was concentrated at the site of disease in tuberculosis patients , D4GDI+ cells were expanded in mice infected with M . tb , and recombinant D4GDI inhibited M . tb growth in mice , suggesting that this molecule contributes to immune defenses in vivo . Furthermore , CD4+CD25+ ( 85% Foxp3+ ) cells and D4GDI upregulated the mycobacterial gene DosR which activates expression of multiple genes when M . tb enters a nonreplicative state . The sum of these data suggest a novel role for human CD4+CD25+Foxp3+ cells in protection against infection and identify a new molecule , D4GDI , through which such protection is mediated . Tregs influence the immune response to parasitic , bacterial , viral and fungal pathogens . The effects may be favorable or harmful to the host , depending on the pathogen and stage of infection . In Leishmania infection , Tregs persist at the site of infection , are essential for parasite persistence but favor host immunity to exogenous reinfection [24] , [25] . In human Plasmodium falciparum infection , the percentage of Tregs correlates directly with parasitic growth [26] and depletion of Tregs enhances survival of mice infected with P . yoelii [27] , indicating the negative effects of Tregs on the host in malaria . In contrast , Tregs suppress Helicobacter pylori-specific T cell responses [28] , reducing gastric inflammation and ulceration [29] . Tregs negatively affect host immune responses to viral infections , such as HIV [30] , cytomegalovirus [31] , Epstein-Barr virus and hepatitis B and C [32]–[35] . We found that a subpopulation of CD4+CD25+Foxp3+ T-cells enhance immunity by producing D4GDI , which inhibits M . tb growth in human macrophages . Our studies are further supported by recent findings that in Candida albicans infected mice , Tregs enhance Th17 cytokine production to clear the fungal infection [36] . Recent studies have shown that human CD4+CD25+ cells express Foxp3 transiently and do not have classical regulatory function . Previously we found that M . tb-expanded CD4+CD25+Foxp3+ cells produce IL-10 and TGF-β to inhibit IFN-γ production by T-cells [6] , [7] . Our findings in Fig . 2D indicate that the subpopulation of CD4+CD25+Foxp3+ cells that express D4GDI do not express IL-10 and TGF-β , suggesting that they are not immunosuppressive . Our current findings suggest that subpopulations of M . tb-expanded human Tregs differ in their function . D4GDI is one of the Rho GDP dissociation inhibitors , small GTP-binding proteins that stabilize the GDP dissociation inhibitor-bound form of Rho GTPases , sequestering Rho GTPases at the plasma membrane [15] , [37] . In humans , D4GDI is expressed primarily by T and B cells [15] and is involved in diverse cellular functions , including proliferation , cell signaling , cytoskeletal organization and apoptosis [15] , [38] , but there is limited information available on the role of D4GDI in microbial infection . Overexpression of D4GDI in T-cells reduces HIV replication through inactivation of RhoA , which reduces viral receptor clustering and lowers the efficiency of virus-cell membrane fusion [39] . However , given the differences in intracellular replication strategies of HIV and M . tb , this mechanism would not explain our current results . We found that silencing of IL-1β and TNF-α gene expression reduces D4GDI-dependent inhibition of M . tb growth ( Fig . 6 ) . IL-1αβ-/- and IL-1R-/- mice are highly susceptible to M . tb infection [40] , [41] and IL-1β inhibits M . tb growth in macrophages through caspase-3 activation [42] , suggesting an important role for IL-1β in innate immune responses against M . tb infection . In humans , M . tb induces IL-1β production through its interaction with TLR2 , TLR6 and NOD2 receptors [43] . In addition , TLR2/1-induced antimicrobial responses against M . tb depend on convergence of the IL-1β and vitamin D receptor activation pathways [44] , [45] . In mice , caspase-1-independent IL-1β production is critical for host resistance to M . tb but does not require TLR signaling [41] . Similarly , TNF-α is essential for control of infection with M . tb in animals [46] and inhibits growth of M . tb in human monocytes and alveolar macrophages [11] , [47] , [48] . IL-1β inhibits M . tb growth in macrophages by enhancing TNF-α production and through caspase-3 activation [42] , suggesting the vital role of these two molecules in M . tb infection . In the current study we found that a subpopulation of Tregs produce a novel molecule , D4GDI , which induces IL-1β and TNF-α production by human macrophages to inhibit M . tb growth . We found that IL-1β and TNF-α produced by MDMs in response to D4GDI enhance ROS production , and inhibition of ROS reverses D4GDI-dependent inhibition of M . tb growth in macrophages ( Fig . 7 ) . ROS are vital in eliminating many pathogens , including M . tb [49] , [50] and patients with chronic granulomatous disease , whose phagocytic cells fail to generate superoxide , are highly susceptible to infections with fungi and bacteria , including mycobacteria [51] , [52] . D4GDI is recruited to the phagosome of RAW macrophages after infection with Listeria monocytogenes [53] , but its role in ROS production is controversial . Some investigators concluded that D4DGI inhibited ROS production in response to Listeria [53] , whereas others showed that phagocytic cells from D4GDI-deficient mice produce less superoxide [15] , [16] . Our current findings suggest that D4GDI produced by CD4+CD25+Foxp3+ T-cells increases IL-1β and TNF-α production which enhance ROS production by human macrophages in response to M . tb infection , reducing bacillary replication . ROS can induce apoptosis , enhance autophagy and elicit production of antimicrobial peptides in M . tb-infected macrophages [54] , [55] , all of which can inhibit intracellular mycobacterial growth [56]–[58] . We found that ROS generated by D4GDI increase M . tb-infected macrophage apoptosis and mycobacterial killing ( Fig . 8 ) . Apoptosis is a potent mechanism for elimination of mycobacteria . More virulent strains of the M . tb complex inhibit apoptosis and grow more rapidly in macrophages , whereas attenuated strains such as H37Ra and BCG elicit greater apoptosis and show reduced intracellular growth [59] , [60] . The M . tb nuoG gene inhibits macrophage apoptosis and a nuoG deletion mutant has reduced virulence in SCID mice [61] . ROS generated during M . tb infection induce signaling molecules , such as signal-regulating kinase , which induce apoptosis [62] . We found that D4GDI enhances apoptosis of M . tb infected macrophages through the production of IL-1β , TNF-α and ROS to inhibit M . tb growth . Disease manifestations in human TB result not only from uncontrolled bacillary proliferation , but also from tissue inflammation due to a vigorous immune response . In this setting , the role of Tregs in the pathogenesis of TB remains controversial . Elegant experiments in mice suggest that Tregs inhibit immunity to M . tb by delaying trafficking of effector T cells to the site of infection [5] , [63] , but studies in macaques show that the frequency of Tregs is higher in animals that developed LTBI than in those that developed active disease , suggesting that Tregs do not cause progression to active disease [64] . Tregs are well known to downregulate immune responses in many experimental models , and CD4+Foxp3+ cells expand in response to inflammation during early TB in macaques [64] , suggesting that they limit tissue destruction . We found that CD4+CD25+Foxp3+ cells that expand upon exposure to M . tb produce D4GDI , which inhibits mycobacterial growth in macrophages . D4GDI was selectively concentrated in pleural fluid of patients with tuberculous pleuritis ( Fig . 10A ) , who have an effective immune response that clears local infection . In addition , PBMC from TB patients with ineffective immunity have reduced production of D4GDI ( Fig . 10B ) . Furthermore , recombinant D4GDI reduced the bacillary burden in M . tb infected mice ( Fig . 4B ) . Because CD4+Foxp3+ cells are enriched in pleural fluid of TB patients [65] and in mycobacterial granulomas [66] , we speculate that CD4+CD25+ cells that express Foxp3 transiently at the site of disease release D4GDI , which inhibits M . tb growth . The sum of our studies in humans and murine models of infection suggest that D4GDI produced by CD4+CD25+Foxp3+ T-cells has a previously undescribed positive effect on immunity by enhancing host antimicrobial activity . Our results suggest that D4GDI is part of an effective local human immune response to M . tb infection in LTBI individuals . Previous studies have found increased Foxp3+cells at the site of TB disease [65] , [67] . We found that apoptotic CD4+CD25+Foxp3+ cells express D4GDI and that high D4GDI levels are present at the site of disease , suggesting high turnover of CD4+CD25+FoxP3+ cells at the site of active disease . Further studies to understand the mechanisms that induce D4GDI+ cell expansion , production and turnover will provide new insight into the pathogenesis of TB , and identify strategies to enhance immune responses in TB patients . We found that D4GDI causes intracellular M . tb to increase expression of DosR and DosR-regulated genes ( Fig . 9 ) . DosR controls expression of a suite of genes required during dormancy induced by anaerobic conditions , when M . tb enters a hypometabolic state with minimal replication [20] , [68] , [69] . DosR is activated by two sensor kinases , DosT and DosS , that fine-tune the response to changes in oxygen , nitrous oxide and carbon monoxide levels , and that appear to modulate the entry of M . tb into dormancy in a step-wise fashion [19] , [20] , [70] . Further work is required to determine the conditions that induce the DosR regulon following macrophage exposure to D4DGI . Mycobacterial growth inhibition by CD4+CD25+Foxp3+ cells was reduced in the M . tb dosR deletion mutant ( Fig . 9B ) , suggesting that the growth inhibition depends in part on activation of the DosR regulon . Our results suggest that macrophage exposure to D4GDI triggers conditions that induce DosR , followed by entry of the bacteria into a nonreplicative state . These findings may aid in understanding the factors that induce LTBI . In summary , our study demonstrates that D4GDI inhibit growth of M . tb in macrophages , providing the first evidence that D4GDI contribute to effective immunity against an intracellular pathogen . We are currently determining whether D4GDI can be used as an immunologic marker to detect persons at greatest risk of progression of LTBI to TB , so that this subpopulation can be targeted to receive isoniazid , reduce TB morbidity and improve public health . Additional studies are needed to determine if D4GDI can be used as an immunostimulatory treatment for TB and other infectious diseases .
After obtaining informed consent , blood was obtained from 20 healthy persons with positive QuantiFERON-TB Gold tests , indicative of LTBI , 12 healthy persons with negative QuantiFERON-TB Gold tests and 15 HIV-seronegative patients with culture-proven TB who had received antituberculosis therapy for <4 weeks . All donors were between the ages of 18 and 65 . Individuals with LTBI did not have a history of TB or HIV infection , and were not receiving therapy with immunosuppressive drugs . Pleural fluid was obtained from 10 patients with tuberculous pleuritis who had received antituberculosis therapy for <5 days . All patients had unilateral exudative effusions , and the diagnosis was confirmed by culture of M . tb from pleural fluid or tissue , or by histologic evidence of granulomatous pleuritis , combined with a response to antituberculosis therapy . All animal studies were performed on specific-pathogen-free 4–6-week-old female C57BL/6 mice and approved by The Institutional Animal Care and Use Committee of the University of Texas Health Science Center at Tyler . All studies were approved by the Institutional Review Boards of the University of Texas Health Science Center at Tyler ( Protocol #640 ) and the University of Southern California School of Medicine . All the human subjects were in between 18 to 65 years and written informed consent was obtained before enrolling in the study . The Institutional Animal Care and Use Committee of the University of Texas Health Science Center at Tyler approved the animal work ( Protocol #488 ) . All animal procedures involving the care and use of mice were in accordance with the guidelines of NIH / OLAW ( Office of Laboratory Animal Welfare ) . H37Rv , a virulent laboratory strain of M . tb , was used in most experiments . A dosR mutant , its complemented strain , and its parental strain of H37Rv , were used in some experiments [68] . For flow cytometry , we used FITC anti-CD4 , allophycocyanin ( APC ) anti-CD4 , APC anti-CD25 , PE anti-Foxp3 , PE-Cy5 anti-Foxp3 ( all from eBioscience ) , FITC anti-CD14 , FITC anti-CD8 , PE anti-PD1 , FITC anti-D4GDI ( Pierce ) , PE anti-IL-10 , PE anti-TGF-β and PE anti-IFN-γ and PE anti-CD127 ( e-Bioscience ) , APO-Direct TUNEL kit ( e-Bioscience ) , Caspase-3 staining kit ( BD Pharmingen ) and DCFDA—Cellular Reactive Oxygen Species Detection Assay Kit ( Abcam ) . γ-irradiated M . tb H37Rv was obtained from BEI Resources . In some experiments recombinant D4GDI ( Cell Sciences ) and cyclosporin A ( Sigma ) were used . For neutralization experiments , anti-IFN-γ ( BD Pharmingen ) and anti IL-22 ( e-Biosciences ) antibodies were used . PBMC were isolated by differential centrifugation over Ficoll-Paque ( Amersham Pharmacia Biotech ) . CD4+ and CD14+ cells were isolated by positive immunomagnetic selection ( MiltenyiBiotec ) , and were >95% CD4+ and CD14+ , respectively , as measured by flow cytometry . CD4+ cells were cultured in 12-well plates at 2 ×106 cells/well in RPMI 1640 containing 10% heat-inactivated human serum , with 2 × 105 autologous CD14+ monocytes/well and γ-irradiated M . tb ( 10 µg/ml ) at 37°C . After 4 days , CD4+CD25+ and CD4+CD25- cells were isolated , using the Treg isolation kit ( MiltenyiBiotec ) , as described [11] . Eighty five-90% of isolated CD4+CD25+ cells expressed Foxp3 , and <1% of CD4+CD25- cells were Foxp3+ , as determined by intracellular staining . For surface staining , 106 cells were resuspended in 100 μl of staining buffer ( PBS containing 2% heat-inactivated FBS ) and Abs . Cells were then incubated at 4°C for 30 min , washed twice and fixed in 1% paraformaldehyde , before acquisition using a FACS Calibur ( BD Biosciences ) . In some experiments , intracellular staining for Foxp3 , IL-10 , TGF-β , IFN-γ and D4GDI was performed , according to the manufacturer’s instructions . Controls for each experiment included cells that were unstained , cells to which APC-conjugated goat or rat IgG or PE-conjugated rat IgG had been added and cells that were single stained , either for the surface marker or for intracellular molecules . For Foxp3 , IL-10 , TGF-β and IFN-γ analysis , we gated on CD4+ lymphocytes , and determined the percentages of CD25+ and Foxp3+ cells . For D4GDI , IL-10 , TGF-β and IFN-γ analysis , we gated on CD4+Foxp3+ cells to identify D4GDI+ cells . CD14+ monocytes ( 106/well ) were plated in 12-well plates in 1 ml of antibiotic-free RPMI 1640 containing 10% heat-inactivated human serum , and incubated at 37°C in a humidified 5% CO2 atmosphere for 4 days to differentiate into macrophages . At the same time , CD4+ cells and CD14+ monocytes were cultured with γ-irradiated M . tb for 4 days , and CD4+CD25+ and CD4+CD25- cells were isolated , as outlined above . In some experiments cells were cultured with Cyclosporin A ( 20μg/ml ) . MDMs were infected with M . tb H37Rv at a MOI of 1:2 . 5 ( 2 . 5 M . tb to one MDM ) , incubated for 2 hr at 37°C , washed to remove extracellular bacilli , and cultured in RPMI 1640 containing10% heat-inactivated human serum . To some wells , CD4+CD25+ or CD4+CD25- cells were added in Transwells or in the same well , at a ratio of 1 CD4+ cell:9 MDMs . To some wells anti-IFN-γ or anti-IL-22 or both , or isotype control antibodies were added on days 0 and 3 . Infected macrophages were cultured for 7 days , at which point macrophage viability was >90% . The supernatant was aspirated , and macrophages were lysed . The supernatant was centrifuged to pellet bacteria , and the pellets were added to the cell lysates . Bacterial suspensions were ultrasonically dispersed , serially diluted , and plated in triplicate on 7H10 agar . The number of colonies was counted after 3 weeks . CD4+ cells and autologous monocytes were cultured with γ-irradiated H37Rv , as outlined above . After 4 days , CD4+ CD25+ cells ( 85–90% Foxp3+ ) and CD4+CD25- cells ( <5% Foxp3+ ) were isolated by immunomagnetic sorting , and cultured in medium overnight . In some experiments , the supernatants were concentrated and 2D gel electrophoresis was performed , followed by LC-MS/MS analysis of differentially expressed proteins ( Kendrick Laboratories , Madison , WI ) . In other experiments , supernatants were collected and 10μg from each sample was separated by 10% SDS-PAGE , transferred to nitrocellulose and probed with Abs to D4GDI or β-actin ( Santa Cruz Biotechnology ) . After washing , the membranes were incubated with HRP-conjugated secondary Ab ( Santa Cruz Biotechnology ) and binding was detected by ECL ( GE Healthcare ) . The effect of recombinant D4GDI on the viability of MDMs was studied in 96-well plates using the MTT cell proliferation assay kit ( ATCC ) . Briefly , after 7 days of D4GDI treatment , 10 µl of MTT reagent was added in the wells and incubated for 3 hr for the development of purple precipitates . Cells were then lysed in 100 μl of detection reagent and the plate was read at 570 nm after 2 hr of incubation . For blank wells , cells were first lysed and then MTT reagent was added . H37Rv-infected MDMs were cultured with or without recombinant D4GDI . After 6 hr , culture supernatants were collected and RNA was isolated from MDMs , using TRIzol reagent ( Life Technologies ) , and pooled RNA was converted to cDNA , followed by microarray analysis ( UT , Southwestern , Dallas , TX , USA ) . In the culture supernatants , the following 27 cytokines and chemokines were measured using multiplex ELISA kit ( Bio-Rad ) . The cytokines and chemokines analyzed were IL-1β , IL-1ra , IL-2 , IL-4 , IL-5 , IL-6 , IL-7 , IL-8 , IL-9 , IL-10 , IL-12 ( p70 ) , IL-13 , IL-15 , IL-17 , basic FGF , Eotaxin , G-CSF , GM-CSF , IFN-γ , IP-10 , MCP-1 ( MCAF ) , MIP-1α , MIP-1β , PDGF-BB , RANTES , TNF-α , and VEGF . MDMs were infected with H37Rv at a MOI of 1:2 . 5 ( 2 . 5 M . tb to one MDM ) , as outlined above , and treated with medium alone or recombinant D4GDI . In some experiments , CD4+CD25+ or CD4+CD25‑ cells were added in Transwells . After 3 days , RNA was isolated from 106 MDMs , and reverse transcribed , using the Clone AMV First-Strand cDNA synthesis kit ( Life Technologies ) . For analysis of M . tb mRNA , host cells were lysed , bacteria were recovered by centrifugation , and then RNA was extracted by bead-beating in Trizol , followed by further purification . Mycobacterial primer and probe sets were designed with primer express software ( Applied Biosystems ) ; probes were labeled with 5’-fluorescein phosphoramidite and 3’-TAMRA . The primers used to amplify human and M . tb cDNA are shown in S2 Table . Real-time PCR was performed using the Quantitect SYBR Green PCR kit ( Qiagen ) in a sealed 96-well microtiter plate ( PE Applied Biosystems ) on a spectrofluorometric thermal cycler ( 7700 PRISM , Applied Biosystems ) . PCR reactions were performed in triplicate as follows: 95°C for 10 min , and 45 cycles of 95°C for 15 s , 60°C for 30 s , and 72°C for 30 s . Expression of human and M . tb genes were normalized to the amount of GAPDH and 16S rRNA transcripts in each sample , respectively . Freshly isolated CD4+ cells were transfected with siRNA for D4GDI or scrambled siRNA . The next day , CD4+ cells were washed , and cultured with autologous monocytes and γ-irradiated M . tb H37Rv . CD4+CD25+ and CD4+CD25- cells were isolated after 5 days . The efficiency of siRNA knockdown was measured by real-time PCR of D4GDI expression . MDMs were transfected with siRNA for IL-1β , TNF-α , IL-27 , G-CSF , SIVA or MMP12 , or control siRNA ( all from Santa Cruz Biotechnology ) . The efficiency of siRNA knockdown was measured by real-time PCR to detect the relevant mRNA . Briefly , 106 MDMs were resuspended in 500 µl of transfection medium , and transfected with siRNA ( 6 pmoles ) . After 6 hr , an additional 250 µl of 2X RPMI complete medium was added , and cells were cultured overnight in a 24-well plate . The next day , MDMs were washed and infected with H37Rv , as outlined above , and CFU were measured after 3 days . Confocal microscopy was performed to detect intracellular D4GDI , as described previously [71] . MDMs on chamber slides ( Lab Tek ) were uninfected or infected with GFP expressing M . tb H37Rv at a multiplicity of infection of 1:2 . 5 ( 2 . 5 M . tb to one MDM ) for 2 hr , washed thoroughly , and cultured overnight with GST-D4GDI . After overnight incubation , for intracellular staining , cells were first fixed in 2% paraformaldehyde in PBS ( pH 7 . 2 ) , permeabilized and nonspecific binding was blocked by incubating in blocking buffer . Cells were then incubated overnight with goat polyclonal anti-GST ( 5 mg/ml ) in blocking buffer . As a control , monocytes were incubated with either blocking buffer alone or isotype control antibody ( 5 mg/ ml ) . Then , cells were stained with secondary antibody and DAPI ( Molecular Probes ) to identify the primary signal and nuclei . The cells were washed and mounted with aqueous gel mounting media ( Biomedia ) containing antifading agent . Confocal images were obtained , using an LSM 510 Meta confocal system ( Carl Zeiss ) equipped with an inverted microscope ( Axio Observer Z1; Carl Zeiss ) . Immunostained cells were viewed through a Plan-APOCHROMAT 633/1 . 4 NA oil objective lens , with 2 . 53 digital magnification , to detect green fluorescence ( GFP-expressing M . tb H37Rv ) , blue ( DAPI ) and red fluorescence ( GST-D4GDI ) . Images were acquired with Zen 2007 software ( Carl Zeiss ) , and scanned images were exported and processed using Adobe Photoshop version 7 . 0 software ( Adobe Systems ) . The effect of recombinant D4GDI on apoptosis of M . tb-infected MDMs was measured by using the APO-Direct TUNEL kit . Briefly , MDMs were infected with M . tb H37Rv at a MOI of 1:2 . 5 ( 2 . 5 M . tb to one MDM ) . Some MDMs were cultured with D4GDI ( 10ng/ml ) . After 72 hr , cells were isolated using trypsin-EDTA and fixed in 1% paraformaldehyde and 70% ethanol in PBS . After overnight incubation at -20°C , cells were washed in washing buffer , resuspended in 50 μl of DNA labeling solution ( provided in the kit ) and incubated at 37°C . After 60 min , cells were washed twice in rinsing buffer and 500 μl of propidium iodide/RNAse A solution was added and incubated in the dark . After 30 min , cells were analyzed by FACS . Wild type C57Bl/6 mice were infected with H37Rv , using an aerosol exposure chamber , as described previously [72] , [73] to deposit ~50–100 bacteria in the lungs . To measure lung CFU , serially diluted lung homogenates were plated on 7H11 agar , supplemented with OADC . CFU were enumerated after 14–22 days incubation at 37°C . Results are shown as the mean ± SE . Comparisons between groups were performed by a paired or unpaired t test , as appropriate . | Most people who are infected with Mycobacterium tuberculosis ( M . tb ) have latent tuberculosis infection ( LTBI ) with protective immunity . Patients with active tuberculosis have severe disease and ineffective immunity . Understanding how LTBI individuals control infection without developing disease provides important insight into the mechanisms of protective immunity against tuberculosis , and this information is essential for development of an effective vaccine . It is known that a lymphocyte population called T-cells contributes significantly to protective immunity against tuberculosis infection . In the current study , using human and murine models of M . tb infection , we found that a soluble factor , Rho GDP dissociation inhibitor ( D4GDI ) , produced by a subpopulation of T-cells ( CD4+CD25+Foxp3+ ) inhibits M . tb growth . We also found that D4GDI induces M . tb genes that are expressed during the non-replicative state . Our results suggest that D4GDI has a previously undescribed positive effect on immunity by enhancing host antimicrobial activity . These findings also may aid in understanding the factors that induce LTBI . Further , this information will facilitate development of improved vaccines and immunotherapeutic strategies to prevent and treat tuberculosis , respectively . | [
"Abstract",
"Introduction",
"Results",
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"Materials",
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"Methods"
] | [] | 2015 | A Rho GDP Dissociation Inhibitor Produced by Apoptotic T-Cells Inhibits Growth of Mycobacterium tuberculosis |
The dimensionality of a network’s collective activity is of increasing interest in neuroscience . This is because dimensionality provides a compact measure of how coordinated network-wide activity is , in terms of the number of modes ( or degrees of freedom ) that it can independently explore . A low number of modes suggests a compressed low dimensional neural code and reveals interpretable dynamics [1] , while findings of high dimension may suggest flexible computations [2 , 3] . Here , we address the fundamental question of how dimensionality is related to connectivity , in both autonomous and stimulus-driven networks . Working with a simple spiking network model , we derive three main findings . First , the dimensionality of global activity patterns can be strongly , and systematically , regulated by local connectivity structures . Second , the dimensionality is a better indicator than average correlations in determining how constrained neural activity is . Third , stimulus evoked neural activity interacts systematically with neural connectivity patterns , leading to network responses of either greater or lesser dimensionality than the stimulus .
A fundamental step toward understanding neural circuits is relating the structure of their dynamics to the structure of their connectivity [4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14] . However , the underlying networks are typically so complex that it is apriori unclear what features of the connectivity will matter most ( and least ) in driving network activity , and how the impacts of different connectivity features interact . Recent theoretical work has made progress in identifying rich and distinct roles for several different features of network connectivity: local connection structures [15 , 16 , 17 , 18 , 19 , 20] , spatial profiles of coupling [21] , low-rank connection structures [22] , subnetwork statistics [23 , 24] , clustered organization [25] ( addressing connectivity properties in a complementary fashion from our present focus ) . Here we focus on linking network connectivity to collective activity as quantified by the dimensionality of the neural response . This dimensionality summarizes the number of collective modes , or degrees of freedom , that the network’s activity explores . We use the “participation ratio” dimension , which is directly computable from the pairwise covariances among all cells in a population [2 , 3 , 26 , 27 , 28] . This connection is useful because the structure of pairwise covariance has been linked , in turn , to the fidelity of the neural code , both at the single neuron [29] , and at the population levels [30 , 31 , 32 , 33 , 34] . Overall , the participation ratio has proven useful in interpreting properties of multi-units neuronal recordings [27] , and has yielded a remarkable perspective on neural plasticity and how high dimensional responses can be optimal for general computations [3 , 2] . Two factors arise in our efforts to understand what it is about a network’s connectivity that determines the dimensionality of its activity . First , this process requires untangling two leading contributions to collective spiking: the reverberation of internal activity within the circuit , and its modulation by external inputs [35 , 36 , 37] . Experiments point out that both have strong effects [21 , 38 , 39 , 40] , and they interact in rich ways that our analysis will begin to dissect . Second , beyond providing general formulas , the understanding we seek demands that we identify relatively simple “observables” of complex network connectivity that systematically determine the dimensionality they produce . A natural approach is based on connection paths through networks , and how these can in turn be decomposed into local circuit micro-circuits , or “motifs” [16 , 17 , 18 , 19 , 20 , 23 , 41 , 42] . This is attractive because such local connectivity structures can be measured in tractable “multi-patch” type experiments , are limited in their complexity , and are controlled by local plasticity mechanisms . The prevalence of motifs , characterized in terms of connection probabilities and strengths , has achieved success in predicting the average levels of pairwise correlation among spiking cells—a measure of coordinated activity related to dimensionality in interesting ways that we will further explore below ( [17 , 18 , 20]; see also [43] ) . Here we deploy this framework to compute the dimensionality of spontaneous and stimulus-driven neural activity . We find that expressions based on just the details of small ( and hence local ) connection motifs give correct qualitative , and in some ( but not other ) cases quantitative , predictions of trends in dimensionality of global activity patterns . This underlines the utility of local network motifs as building blocks in bridging from network connectomics to network dynamics . Our main findings are threefold: First , the dimensionality of global activity patterns can be strongly , and systematically , regulated by local connectivity structures . Second , for a wide range of networks this dimensionality can be surprisingly low ( indicating strongly coordinated activity ) even when the average correlations among pairs of neurons are very weak , cfr . [44] . Third , the dimensionality of stimulus evoked neural activity is controlled systematically by neural connectivity , leading to network responses that have either expanded or reduced the dimension of the original stimulus . In what follows we will start by introducing the underlying theoretical framework . We describe the mathematical model , a spiking network of linearly interacting point process cells ( a “Poisson linear network” , linearized GLM , or Hawkes process ) , together with the measure of dimensionality we use . We show how this dimensionality can be expressed in terms of connectivity motifs . We continue by analyzing the dimensionality of the spontaneous ( internally generated ) activity of an excitatory randomly connected network , and move to stimulus-driven networks of this type . Finally , we generalize our results to consider different connectivity topologies as well as excitatory-inhibitory balanced networks . We hinge the discussion around the question of how a network can modulate the dimensionality of its response to external stimuli by leveraging its local connectivity .
Consider a recurrent neural network of N neurons where the activity yi ( t ) of neuron i at time t occurs around a baseline rate of irregular firing , which is set by the internal connectivity of the network W and an external input ξ ( t ) . The spike train of neuron i is given by s i ( t ) = ∑ j δ ( t - t j i ) where each spike is sampled from a Poisson distribution with instantaneous mean rate ( intensity ) yi ( t ) . The response of the whole network y ( t ) can then be captured by linearizing its dynamics around the baseline rates , giving the equation: y ( t ) = y 0 + ∫ - ∞ ∞ A ( t ′ ) ( W s ( t - t ′ ) + ξ ( t - t ′ ) ) d t ′ = y 0 + ( A * ( W s + ξ ) ) ( t ) , ( 1 ) where each entry of the vector y ( t ) is the instantaneous firing rate of neuron i at time t with baseline firing rate y0 . Here Wij is the synaptic strength between neuron i and neuron j , and A is a diagonal matrix where Aii is the postsynaptic filter which encapsulates the timecourse of the postsynaptic response . Thus , Gij = Aii ⋅ Wij defines an effective connectivity matrix . Finally , ξ is the external input to the network . This model is pictured in Fig 1a , where the input ξ contributes to the baseline activity of each neuron , and the recurrent feedback is linearized . The stochastic spiking dynamics induced by Eq 1 leads ( cfr . Supp . Mat . ) to an equation for the covariance matrix C of the network response . For simplicity we present the result as a matrix of spike train auto- and cross-spectra at frequency ω , C ( ω ) . This is the matrix of the Fourier transforms of the familiar auto- and cross-covariance functions; its zero mode C ( 0 ) is the the usual covariance matrix on which we will focus for the rest of this work [48 , 49] . Very usefully , this mode has been shown to yield an accurate approximation of correlations over any time window that is long enough to encompass the structure of neural correlograms [50] . The linearized dynamics , Eq 1 give rise to the covariance matrix as: C ( ω ) = ⟨ y ( ω ) y ( ω ) * ⟩ = = Δ ( ω ) ⟨ y 0 ( ω ) y 0 ( ω ) T ⟩ Δ ( ω ) * + Δ ( ω ) ( A ( ω ) ⟨ ξ ( ω ) ξ ( ω ) T ⟩ A ( ω ) * ) Δ ( ω ) * = Δ ( ω ) C 0 ( ω ) Δ ( ω ) * ︸ internally generated + Δ ( ω ) ( A ( ω ) C i n p ( ω ) A ( ω ) * ) Δ ( ω ) * ︸ externally induced = C i n t + C e x t . ( 2 ) The first term of Eq 2 expresses how the variability in the activity of single neurons ( the baseline covariance C0 ) propagates through the network to induce internally-generated covariability . Similarly , external inputs with covariance Cinp give rise to covariances ( ( A ( ω ) Cinp ( ω ) A ( ω ) * ) in the externally induced term ) , which then propagate through the network . ( External inputs with low-rank correlations could reflect global fluctuations due to shifts in attention , vigilance state , or motor activity [39 , 51] . ) Above we also introduced Δ ( ω ) = ( I - G ( ω ) ) - 1 , where Δij is called a propagator as it reflects how a spike in neuron j propagates through the network to affect the activity of neuron i . Eq 2 has been extensively studied in a number of frameworks [45 , 52 , 53 , 54 , 55 , 56] . We aim to characterize the dimensionality of the distribution of population vector responses . Across many trials , these population vectors populate a cloud of points . The dimensionality is a weighted measure of the number of axes explored by that cloud: D i m ( C ) = ( Tr C ) 2 Tr C 2 = ( ∑ i λ i ) 2 ∑ i λ i 2 . ( 3 ) where λi is the ith eigenvalue of the covariance matrix C . The eigenvectors of the covariance matrix C are the axes of such cloud of points as in Fig 1c . If the components of y are independent and have equal variance , all the eigenvalues of the covariance matrix have the same value and Dim ( C ) = N . Alternatively , if the components are correlated so that the variance is evenly spread across M dimensions , only M eigenvalues would be nonzero and Dim ( C ) = M ( Fig 1d ) . For other correlation structures , this measure interpolates between these two regimes ( Fig 1e ) and , as a rule of thumb , the dimensionality can be thought as corresponding to the number of dimensions required to explain about 80% of the total population variance in many settings [3 , 26 , 27] . Previous works have shown that the average correlation between neurons depends strongly on the motif structure of their connectivity [17 , 18 , 20] . We began by asking whether the same is true for the dimensionality . To do this , we generated random networks with a range of connection probabilities and , for each connection probability , a wide range of two-synapse motif frequencies ( SONET networks; Methods c and e , and References [41 , 57] ) . In Fig 1d we plot the dimensionality of the network’s activity against the average probability of connection p ( 0 ≤ p ≤ 1 ) for an ensemble of SONET networks ( cfr . Methods e for network details ) . The first notable observation from Fig 1f is that the dimensionality for such networks is strongly influenced by p: as p increases , the dimensionality decreases towards 1 . Importantly , Fig 1f also shows a high range of variability in the dimension produced by networks with the same value of average connectivity p , indicating that the way that a given number of connections is arranged across the network also plays a strong role in determining the dimension of its activity Fig 1f . The dimensionality decreases in a narrow range of values of p around p = 0 . 08 ( near the value p = 0 . 10 for which the spectral radius of the network approaches one ) . The wide span of dimensionality values produced in this narrow range points to the importance of predicting dimensionality and possibly of mechanisms that control it . Our next major goal is to describe how the statistics of connectivity motifs gives rise to this variability . We review the main ideas of the theoretical framework that allows for an expansion of Eq 2 in terms of connectivity motifs . For a more comprehensive description see Suppl . Mat . S1 File and [17 , 18] . This framework aims to model the complexity of connectivity structures in real world networks , in terms of motif statistics . We first provide an intuitive idea and then a mathematical description of the framework . A network with recurrent connections , as in Fig 2a , can be characterized in terms of connectivity motifs . These building blocks quantify the amount of structure in the network by measuring the abundance of a specific connectivity features , or patterns . For example , in Fig 2a we highlighted in red a pattern made from two diverging branches of length 2 and 1 , respectively , beginning from one neuron . This is called a ( 2 , 1 ) divergent motif , and its abundance , or probability of occurring in four randomly sampled cells in the network , is indicated by μ 2 , 1 d i v . The abundance of this pattern can also be measured relative to the probability of observing it given the abundance of its own building blocks: in this case , single connections , double connections ( chains ) and smaller divergent motifs ( μ 1 , 1 d i v ) . Expressing the total probability of μ 2 , 1 d i v in terms of its building blocks is analogous to rewriting a moment μ in terms of its cumulants κ [17 , 18] . This is illustrated in Fig 2b . Importantly , this procedure of translating moments into cumulants turns out to be more than a simple “change of variables , ” and allows one to resum the contributions of relatively small ( or “low order” ) motifs to abundance of motifs of any higher order . For example , it is possible to account for the contribution of chains of order 2 ( two consecutive links ) to any higher order motif . This is the key property identified in [17 , 18] that we will use in developing predictions for global network activity based on local , low-order motifs . To provide intuition on how different motifs appear at different order we show in Fig 2c examples of motifs and their cumulant description . This intuition translates into three main mathematical steps to highlight . We will introduce them in the case where the network does not receive any external input so that C ( ω ) = Δ ( ω ) C0 ( ω ) Δ ( ω ) * but they can be extended ( cfr . S1 File Sec . S2 ) to the more general case where such an input is present . The first step is to expand the propagator: Δ = ( I - G ) - 1 = ∑ m = 0 ∞ G m . ( 4 ) By expressing Δ in this form we can then write C ( dropping the dependency on w ) via an expansion: C i j= ∑ m = 0 ∞ ∑ n = 0 ∞ ∑ k = 1 N ( G m ) i k ( C 0 ) k k ( G * n ) k j , ( 5 ) where from now on we will consider the case where C0 is diagonal C 0 = c 0 I—as for the standard assumption and model of initially independent Poisson neurons that are then coupled together into a network . Then Eq 5 cum provides an intuitive description of the spike train cross-spectra in terms of paths through the network . This captures contributions to the cross-spectrum for paths that fork out of neuron k and end on one side in neuron i after m connections , and on the other side in neuron j after n connections . An example of such a path for m = 2 and n = 1 , with corresponding i , j , k indices , is shown in red in Fig 2a . The expression in Eq 5 cum has been studied extensively in previous works [20 , 53 , 54 , 55 , 59] . The framework in which we cast our theory relies on a second conceptual step , based on rewriting a function of the covariance C , Eq 5 , in terms of motifs . In the case of the where this function is the average covariance 〈C〉 , this takes the form [17]: ⟨ C ⟩ c 0 = 1 N 3 ∑ m , n = 0 ∞ ( N ) m + n μ m , n , μ m , n = ∑ k , i , j = 1 N G i k m ( G k j T ) n / N m + n - 1 = ⟨ G m ( G T ) n ⟩ / N m + n - 3 . ( 6 ) Here , we assumed that cellular response properties are homogeneous A = g I , and C 0 = c 0 I . The motif moment μm , n measures the average strength of a ( m , n ) -motif composed of two paths ( respectively of length m and n ) connecting any neuron k with neuron i and j . The example of a ( 2 , 1 ) -motif is shown in Fig 2a and 2b . Motifs of this kind , where paths originate from a common neuron , are called divergent motifs . We consider five kinds of motifs: convergent , divergent , chain , reciprocal and trace , depending on the direction of edges to the common node as illustrated in Fig 2c . These motifs correspond to similar definitions to the one for μm , n in Eq 6 ( cfr . S1 File Sec . S2 . 1 for additional details ) . In networks where all synaptic weights have the same value , then μm , n is proportional to the frequency of the motif . We can also define weighted motif statistics . For example: μ m , n u = ∑ k , i , j = 1 N u i G i k m ( G k j T ) n u j / N m + n - 1 = u T G m ( G T ) n u / N m + n - 3 , ( 7 ) where u is a vector of norm 1 ( ||u|| = 1 ) . For example , u could contain neuron’s firing rates , or be the eigenvectors of W . The case of Eq 6 corresponds to choosing the unit norm vector of constant entries , u = ( 1 , 1 , 1 …1 ) T / N . Ultimately the choice of u depends on the desired function of the covariance to compute ( e . g . 〈C〉 , Tr ( C ) , Dim ( C ) … ) , on the structure of G , and on the presence or absence of inputs . In what follows this choice will be motivated in each case . The last and crucial conceptual step of the theoretical framework is to re-sum the motif moments by rewriting them in terms of cumulants . The idea is to approximate the probability of finding a specific motif μn , m by iterative approximations built through the probabilities of finding the building blocks of that motif . For example , in Fig 2b we see how the probability of motif μ1 , 2 to occur in the network can be subdivided in the probabilities of finding its building blocks: three synapses κ 1 3 , one synapse and one chain of length two κ1 κ2 and so on . The general relationship between moments and cumulants is [18]: μ m , n = ∑ { n 1 , . . . , n t } ∈ C ( n ) { m 1 , . . . , m s } ∈ C ( m ) ( ∏ i = 2 t κ n i ) ( κ n 1 , m 1 + κ n 1 κ m 1 ) ( ∏ j = 2 s κ m j ) . ( 8 ) where each κn , κn , m is a cumulant ( respectively for chains and divergent motifs ) and C ( n ) is the collection of ordered sets whose elements sum up to n . This step removes redundancies and improves the rate of convergence of the expansion , so that only relatively smaller motifs need to be measured and included . This is accomplished by “resumming , ” via the identity: ∑ n , m = 1 ∞ ∑ { n 1 , . . . , n t } ∈ C ( n ) { m 1 , . . . , m s } ∈ C ( m ) [ ( ∏ p = 1 t x n p ) z n p m q ( ∏ q = 1 s y m q ) ] = [ ∑ i = 0 ∞ ( ∑ n = 1 ∞ x n ) i ] ( ∑ n , m = 1 ∞ z n m ) [ ∑ j = 0 ∞ ( ∑ m = 1 ∞ y m ) j ] ( 9 ) that allows one to resum the contribution of each cumulant to any order in the expansion of Eq 5 . In this way the expression for a function of the covariance matrix assumes a closed form as a function of the cumulants ( e . g . Eq 6 for the mean covariance ) . Through the resumming procedure we are computing the contribution of any cumulant κ not to a specific term Gm ( GT ) n but to the full sum ∑ m , n = 0 ∞ G m ( G T ) n . In summary , this approach allows us to remove redundancies in motif statistics , and to isolate the impact solely due to higher order motif structures [17 , 18] . The framework outlined above results in the ability to write any function of the covariance in terms of motif cumulants . Specifically , according to our interest here , the expressions for 〈C〉 and Dim ( C ) can be written in terms of a small subset of cumulants . In the following ( cfr . S1 File Sec . 2 . 4 ) we will explain how this framework can be deployed in computing Dim ( C ) for different networks , first in the absence of inputs , and then in their presence . In our results we will include cumulants up to second order , although the expansion and theory can be taken to higher order . Second order cumulants correspond to chains κ n c h , convergent paths κ n , m c o n v , divergent paths κ n , m d i v , reciprocal paths κ n , m r e c i p and trace motifs κ n , m t r as shown in Fig 2c . Mathematical definitions and more detailed explanations of the meaning of these cumulants can be found in the S1 File Sec . 2 . 1-2 . 4 . The expansion in terms of cumulants leads to the expression for the average covariance 〈C〉 ( [18] ) : ⟨ C ⟩ = c 0 N ( 1 - ∑ n = 1 ∞ ( N ) n κ n ) - 2 ( 1 + ∑ n , m = 1 ∞ ( N ) n + m κ n , m d i v ) . ( 10 ) Notably , the contributions of chains and divergent motifs factor out in Eq 10 . The expression for the dimensionality Dim ( C ) is the ratio between Tr ( C ) 2 and Tr ( C2 ) , and these two quantities are general functions of the cumulants so that D i m ( C ) = F ( N , k n c h , κ n , m d i v , κ n , m c o n v , κ n , m T r , κ n , m , p , q T r ) ( 11 ) where F is a function whose full expression is shown in Methods a , in terms of its numerator Tr ( C ) 2 and denominator Tr ( C2 ) . This full expression also shows that the dimensionality is directly related to the average covariance 〈C〉 . Specifically , it turns out that the dependency of Dim ( C ) on k n c h , κ n , m d i v is the same as that of 〈C〉 , so that we can rewrite Eq 11 as: D i m ( C ) = F ^ ( N , ⟨ C ⟩ , κ n , m c o n v , κ n , m T r , κ n , m , p , q T r ) ( 12 ) highlighting the role of convergent and trace motifs in regulating the relation between the average covariance and the dimensionality ( a detailed expression of Eq 12 can be found in S1 File Sec . 2 . 3 ) . The trace cumulants κ n , m T r , κ n , m , p , q T r in Eq 11 represent the statistics of motifs corresponding to patterns of connectivity that originate in one neuron and converge to a second neuron ( Fig 2c ) . We will show later how these statistics are highly correlated with reciprocal connections . We next interpret and apply the formulas just described , which predict the dimension of network-wide activity in terms of localized connectivity motifs . We first use two classes of networks as examples: “purely random” Erdos-Reyni networks , and an exponential family of random graphs parameterized by second order motif statistics . While these are quite natural ( but by no means automatic ) cases for our theory , which is based on localized connectivity statistics , to succeed , we later apply it to different types of complex networks . We begin by analyzing an interesting limit of Eq 11: an Erdos-Reyni network . For a Erdos Reyni network all cumulants except for k 1 c h = p ( where p is the probability for each edge to be present in the graph ) and the trace cumulants k 0 , 0 , 0 , 0 T r = k 0 , 0 T r = ( 1 - 1 / N ) are zero . In this limit Eq 3 becomes: D i m ( C ) = ( ( 1 - N p ) - 2 + ( N - 1 ) ) 2 ( 1 - N p ) - 4 + ( N - 1 ) . ( 13 ) From this expression we see that when p → 1 N we obtain Dim ( C ) → N − 1 . This behavior can be interpreted in the following way: for p small enough that the structure of C is fully diagonal and all the elements are equal to c0; in this regime all the neurons in the network act independently and contribute equally to Dim ( C ) . As p increases more and more neurons start interacting and the dimensionality decreases until we obtain Dim ( C ) = 1 . In Fig 3a we see how Eq 13 ( red dashed line ) is in agreement with the full expression for Dim ( C ) ( green line ) where Eq 2 has been used for the internally generated covariance in spite of the cumulant approximation . To show the efficacy of Eq 11 in capturing the dimensionality of network responses , we use this expression to compute Dim ( C ) in an ensemble of SONET networks [41] . These ( cfr . Methods f ) are random networks where the probability of having a second order motif can be arbitrarily modified; such networks can therefore assume a wide range of values for second order motifs and cumulants . In Fig 3b and 3c we show the dimensionality and average correlation values ( given by 〈C〉/c0 ) for a wide range of SONET networks , with a network’s dimensionality plotted against its connection probability p . Here , for each network we plot both the dimension computed via the full covariance formula Eq 3 , as well as via the cumulant truncation via Eq 11 ( red dots ) . Although the dimensionality varies strongly across networks with different motif statistics even at a fixed value of p ( as was already pointed out in Fig 1f ) , the cumulant theory matches this variability closely across the range of SONET networks . This is shown in Fig 3b in two ways: for each network ( every green dot ) the corresponding theoretical approximation ( corresponding red dot ) lies right on top or closeby; the inset in Fig 3b confirms this by plotting dimension calculated via the cumulant approximation against the true values from the full covariance expression . Together Fig 3b shows that second order motifs contribute to the dimensionality of the response according to Eq 11 . However , from Fig 3b it is not possible to single out the contribution of each motif . To address this question we consider an ensemble of SONET networks centered in their statistics around an Erdos-Renyi network with p = 0 . 08 , corresponding to the orange dot in Fig 3b and 3d ( see Methods f for details ) . The dimensionality for the response of each network in this ensemble is plotted against p in Fig 3d . Then we carry out a multilinear regression ( see Methods f ) of the dimensionality of this ensemble of networks against the values of each cumulant . The regression coefficients express how each cumulant influences the dimensionality ( r2 = 0 . 994 ) ( Fig 3e ) so that: D i m ( C ) = D i m ( C | E R ) + α p k p + α c h k c h + α c o n k c o n + + α d i v k d i v + α T r ( C ) k T r ( C ) + α T r ( C 2 ) k T r ( C 2 ) ( 14 ) where the α′s are the regression coefficients for each cumulant ( green bars in Fig 3d ) . An increase of most cumulant , but not all , types of cumulants appears to lead to a decrease in dimensionality as most coefficients in Fig 3e are negative . This is important as it suggests that adding most types of connectivity structure to a circuit generally lowers the dimensionality of the response . In more detail , this analysis shows that , while increasing the average connectivity , chains , diverging and converging motifs leads to a decrease in dimensionality , terms contributing to the trace motifs may play a role in expanding the dimensionality . Complicating matters is that κ n , m T r and κ n , m , p , q T r are , in general , highly correlated in their values . This correlation is shown in Fig 3f and it limits the applicability of the regression to the ensemble with respect to the trace cumulants , as can be seen in Fig 3e . Regressing against two regressors which are highly correlated , like κ n , m T r and κ n , m , p , q T r , is known to lead to opposite regression coefficients—as occurs in our case . We note that orthogonalizing the two regressors leads to qualitatively similar results ( figure not shown ) , in line with the results to which we turn next . To get a theoretical handle on this , we analytically compute the Taylor coefficients of the expansion of the dimensionality formula Eq 11 in terms of motifs , expanded around the Erdos-Renyi case ( orange point in Fig 3d ) . The Taylor coefficients are the α′ s in the first order theoretical expansion of Eq 14 of the dimensionality formula . To ease reading of the resulting formulas we first define: r = ( 1 - ∑ n = 1 ∞ N n k n c h ) - 1 . ( 15 ) The expressions for Tr ( C ) and Tr ( C2 ) in the Erdos-Renyi case have then the form: ( Tr C ) | E R = c 0 ( r 2 + N - 1 ) ∼ c 0 ( r 2 + N ) ( Tr C 2 ) | E R = c 0 2 ( r 4 + N - 1 ) ∼ c 0 2 ( r 4 + N ) . ( 16 ) The expressions for the Taylor coefficients of second order motifs are: α c h = ∂ k c h | E R D i m ( y ) = 4 r 3 ( r 2 + N ) r 4 + N - ( r 2 + N ) 2 ( 4 r 5 ) ( r 4 + N ) 2 α d i v = ∂ k d i v | E R D i m ( y ) = 2 r 2 ( r 2 + N ) r 4 + N - ( r 2 + N ) 2 ( 2 r 4 ) ( r 4 + N ) 2 α c o n = ∂ k c o n | E R D i m ( y ) = 2 r 2 ( r 2 + N ) r 4 + N - ( r 2 + N ) 2 ( 2 r 4 ) ( r 4 + N ) 2 α T r ( C ) = ∂ k Tr ( C ) | E R D i m ( y ) = 2 N ( r 2 + N ) r 4 + N α T r ( C 2 ) = ∂ k Tr ( C 2 ) | E R D i m ( y ) = - ( r 2 + N ) 2 N ( r 4 + N ) 2 . ( 17 ) A derivation with more details is available in the S1 File Sec . 2 . 5 . These expressions represent the corresponding theoretical quantities for the regression coefficients of Fig 3e and are shown as red dots . As we see the Taylor coefficients provide a direct understanding of the effect of increasing different cumulants on the dimensionality . Moreover , as we show analytically in the S1 File , αch < 0 , and αdiv = αconv < 0; thus , the effects of adding chain , diverging , or converging motifs to a given network is to drive down the dimension of the activity that it produces . Although the regression fails to capture the right quantitative expressions for the trace motifs ( see Fig 3e ) , it does suggest that these terms play a key role in regulating the dimensionality . The two corresponding Taylor coefficients are opposite in sign and their sum is positive pointing to Trace motifs as the only factor which enables the dimensionality to increase , this results are in line with the regression analysis . Trace motifs appear as critical features in regulating dimensionality , so we now elucidate more clearly their structure . The key contribution to trace motifs are reciprocal motifs . At second order the two are in tight one to one correspondence , as can be observed in Fig 3g where the high correlation between the two is highlighted . At higher orders trace motifs may have more complicated forms ( cfr . Fig 3g right side ) , but reciprocal connections maintain their key role as building blocks of such motifs . Thus a good intuition for trace motifs may simply be derived by thinking them at first as reciprocal connections . Our results point to such reciprocal connections as major players in determining the overall behavior of the dimensionality . In Eq 2 we highlighted two contributions to the total covariance of the network activity . The first is due to the internally generated activity ( the reverberation of the stochastic Poissonian spiking through the network ) , and the second is due to the inputs to the network . While in the previous sections we have analyzed the dimensionality of the network response in the absence of inputs , here we generalize the results to include their contribution . The interplay between the connectivity of the network and the inputs can be captured by Eq 3 def where we expressed C as C = Cint + Cext: D i m ( C ) = ( Tr C i n t + Tr C e x t ) 2 Tr ( C i n t + C e x t ) 2 = ( Tr C i n t ) 2 + ( Tr C e x t ) 2 + 2 ( Tr C i n t · Tr C e x t ) Tr ( C i n t 2 ) + Tr ( C e x t 2 ) + 2 Tr ( C i n t · C e x t ) . ( 18 ) We decompose the input covariance Cinp into Ninp orthogonal unitary factors ξ , so that C i n p = ∑ i N i n p c ξ , i ξ i ξ i T . The external input to the network might arise from the spontaneous or evoked activity of other areas; regardless , it can be modeled as a sum of independent contributions where the number of factors Ninp and the individual strength of these factors cξ , i has to be determined . The theory introduced in previous sections needs to be extended to reflect a crucial fact: the input may target different neurons in the network to a different degree . This is typically modeled with an input matrix to the network . In our model this is part of Cext , because its effect can be included in the input by redefining ξ → Winput ξ in Eq 1 . In turn , connections from and to specific neurons will be more important than others in driving network-wide activity . In previous sections Fig 2 , we introduced motif moments and cumulants by specifying that weights from different neurons were equally taking part to the computation of the dimensionality . This idea was rendered mathematically by using a uniform weight vector u = ( 1 , 1 , 1 … 1 ) T / N in defining and resumming motif cumulants . In the following we will also employ a set Ninp of vectors uξ , i = ξi to properly resum different contributions to the input structure and their reverberation through the network . In S1 File Sec . 3 . 2 we show how all these contributions can be dealt with and re-summed simultaneously via proper handling of weighted motifs and cumulants , building from [17 , 18] . Here , each motif simply carries a weight corresponding to the product of input strengths for each of the neurons that compose it . The resulting equations have function forms similar to the one of Eq 11 , but with weighted cumulants . Denoting with κext the set of input weighted cumulants and with κint the set of internal cumulants employed in Eq 11 , we have: D i m ( C ) = F ( N , c 0 , c ξ , κ i n t , κ e x t ) ( 19 ) The full expression for this equation , in terms of its building blocks of Eq 18 , is given in Methods b . This equation formalizes the interplay between stimuli , connectivity , and internally generated activity in creating network activity with a particular dimension . This interplay is crucial to the understanding of network dynamics . Nevertheless , we emphasize that Eq 19 does not capture transient or dynamical features of the activity , as this equation ( as our entire paper ) focuses on the zero mode of the covariance matrix C thus pertains to the stationary features of the response . In what follows , we illustrate one aspect of this: how the strength and dimensionality of inputs to a network modify the “total” dimensionality of the network responses . While the limiting trends are exactly what one would expect—stronger inputs increasingly entrain the network response , and higher dimensional inputs lead to higher dimensional responses—both the limiting values of dimensionality and the approach to them depend on details of network connectivity . To better illustrate this process , we study the response of two different networks: a weakly and a strongly connected network . These two cases correspond to the two points highlighted in Fig 3b: the green point ( p = 0 . 03 ) to a weakly connected network , while the orange one ( p = 0 . 08 ) to a more strongly connected one . In both cases the internally generated activity is uniformly weak or strong across all neurons . To gain more insight on how skewed distributions of intrinsic variances would affect our analysis we refer the reader to [26] . To begin , consider a weakly connected random network receiving Ninp input factors , each with the same strength cξ , so that C i n p = c ξ ∑ i N i n p ξ i ξ i T . We examine the dimensionality of the network response as a function of Ninp in Fig 4a . Note that as Ninp grows , both the dimension of the input ( Ninp ) and its overall strength ( variance Ninpcξ ) grow . The initial dimensionality in the absence of any input is close to 100% , then it decreases as more and more inputs are fed into the network , eventually growing with the number of inputs as these entrain the network activity . Both the extremes have dimensionality close to 100% , as shown in Fig 4a , and in between there is a trade-off region where the low dimensionality of the input and the high dimensionality of the internal activity interact non-linearly as shown in Eq 18 . To better understand these trends we rewrite Eq 18 by using Eq 2 with C 0 = c 0 I , A = g I and C i n p = c ξ C ¯ i n p where we have highlighted the scaling factor of Cinp . The resulting expression is: D i m ( C ) = ( Tr C i n t ) 2 + ( Tr C e x t ) 2 + 2 ( Tr C i n t · Tr C e x t ) Tr ( C i n t 2 ) + Tr ( C e x t 2 ) + 2 Tr ( C i n t · C e x t ) = c 0 2 Tr ( Δ Δ * ) + ( g c ξ ) 2 Tr ( Δ C ¯ i n p Δ * ) 2 + 2 c 0 c ξ g Tr ( Δ Δ * ) Tr ( Δ C ¯ i n p Δ * ) c 0 2 Tr ( Δ Δ * ) + ( g c ξ ) 2 Tr ( Δ C ¯ i n p Δ * ) 2 + 2 c 0 c ξ g Tr ( Δ Δ * Δ C ¯ i n p Δ * ) . ( 20 ) In this formula we recognize that the limits highlighted above ( absence of input regime and input dominated regime ) correspond to the cases where either the terms in c 0 2 or in c ξ 2 dominate , while intermediate cases are trading-off the contribution due to internal dynamics or external input . The distance of the full dimensionality from the diagonal ( green region ) measures the dimensionality expansion , where the input distribution is “inflated’ by the network’s noisy internal dynamics , Fig 4b . The non-monotonic behavior displayed in Fig 4a can be explained as a trade-off of the two input properties introduced above: the input strength and dimensionality . The effect of the former can be understood in Fig 4c , where we show how the dimensionality of the response decreases as a function of a gradually stronger unidimensional input ( Ninp = 1 and increasing cξ ) . This behavior can be compared to established properties of stimulus driven dynamics in cortical circuits [26 , 61] where it has been observed that evoked activity suppresses the dimensionality of spontaneous activity . The influence of the latter factor , input dimensionality , is displayed in Fig 4d where we provide the network an input of overall constant strength , of standard deviation ∑ i N i n p c ξ , i 2 = 2 . 5 c 0 ( cfr . Methods g ) , with increasing number of factors ( dimensions ) . In this case , as the inputs fully entrain the network response , the dimensionality constantly increases . The trend in Fig 4a can be interpreted as a trade-off between these two trends , again recalling that stimulus dimension and strength increase together in that plot Fig 4c and 4d . If we describe Fig 4a as passing stimuli into weakly coupled networks leading to an expansion of the input dimensionality , then Fig 4e shows that strongly coupled networks lead to a more complex trend . At first the input dimensionality is expanded , but then it is compressed; overall , the network response never achieves the full dimensionality of the input . In other words , the response is always constrained by the network dynamics: a first phase of dimensionality expansion is followed by a second phase of dimensionality reduction ( Fig 4f ) . These two phases can both be understood qualitatively in terms of the propagator Δ in Eq 2 , that restrains the total network dynamics . In Fig 4e the theoretical prediction made by the second order cumulant framework ( red line ) agrees with the exact dimensionality from formula Eq 18 def inp ( green line ) only for a low dimensional input , but then departs . This can be attributed to the many ways with which the inputs can interact with the internal modes of the network: as the number of input factors increases , evidently , the term Cint ⋅ Cext in Eq 20 can no longer be captured by low order motif cumulants . In particular the motif cumulant approximation tends to overweight the importance of the input: the predictions for high Ninp in both Fig 4a and 4e are similar . To weaken this limitation we show ( pink line in Fig 4e ) a second theoretical approximation , where the terms arising from the internal modes are disengaged from the input contribution in Eq 18 . See Methods g for more details . This approximation captures more closely the properties of the network when , in the case of high dimensional input Ndim the activity is mainly constrained by the internal modes . We denote the two approximations , red and pink lines in Fig 4e to 4h , respectively as the low and high dimensional input approximation . These two limits taken together show how low order cumulants are able to predict general trends in the dimensionality of driven responses . Altogether we have shown in Fig 4 how the interaction between the input and the network dynamics gives rise to a number of scenarios where the input dimensionality can be expanded , reduced or somehow controlled through the internal recurrent dynamics . Specifically we point out three different scenarios: These points , as illustrated in Fig 4 , will be revisited in the Discussion . Our results so far have shown a variety of phenomena in which the connectivity of a recurrent spiking network , and its resultant internal dynamics , shape its dimensionality . We have shown how this spectrum of behaviors can be interpreted in terms of the statistics of connectivity motifs: the theoretical framework introduced and illustrated in Figs 3 and 4 points to motif cumulants as the logical building blocks . Moreover , truncating motif cumulant expansions at second order , so that only very localized connectivity data enters , can lead to quantitatively accurate predictions of dimension of intrinsic network activity and qualitative predictions of trends in the presence of stimulus drive . This said , above we have tested these results only for fully excitatory random networks , and for those that are either fully random ( Erdos-Reyni ) or are generated according to low order connectivity statistics ( SONET networks ) . It is possible that either the theoretical framework proposed ( cfr . Fig 3 ) or the dimensionality phenomena analyzed ( cfr . Fig 4 ) , may not generalize to more complex networks . To attest this , in this section we generalize the results to complex networks with other structures , and with both inhibitory and excitatory neurons . We also introduced weighted cumulants to account for an input that was fed unevenly into different neurons within a networks . This is necessary as the cumulants originating in some neurons may have more impact on the network dynamics than others . The same argument holds true for the way internal activity in a recurrent network is generated intrinsically in a network , as some neurons , and their connectivity patterns , are known to have a stronger influence [62 , 63] . Thus , we make use of generalized motifs for the internal activity of the network to account for input effects , by using weight vectors u in Eq 7 that are chosen to be the eigenvectors of the connectivity matrix G . This choice is justified by the same logic as in the case of the input: the directions identified by the eigenvectors are the ones where the activity propagates , so that neurons which participate more to the dynamical mode of the network are weighted more in computing the cumulants . Weighting neurons and thus motifs in such a way therefore handles the relative importance of cumulants in propagating activity through the network in the directions of eigenmodes with eigenvalues near one ( see S1 File Sec . 3 . 2 and appendix of [17] for further details ) . To generalize our results we start by showing that the findings in Fig 3 hold true for a wider class of complex networks . Specifically we compare three different network topologies: the Erdos-Renyi case studied before , together with Small World and Free Scale ( Albert-Barabasi model ) networks . For each case , we vary a single common parameter ( cfr . Methods h ) , the density ( probability ) of synapses in the network p . In Fig 5a to 5c we show three examples of the underlying weight matrices , one for each topology . We find that the dimensionality of the network response for the different connection topologies follows the same general trend: it decreases as a function of the average connectivity p ( cfr . Fig 5b ) , until it reaches the boundary of instability for the dynamics . Interestingly , the relation between the average correlation and the dimensionality appears to be very tightly stereotyped as shown in Fig 5c . Such a tight relationship suggests that one may be able to interpret average correlations observed in a circuit in terms of their dimensionality , at least across some classes of network connectivity . Overall , these results suggest that the framework and results given so far do generalize to a more general class of excitatory networks . In Fig 6 we move beyond excitatory networks to consider the case of excitatory/inhibitory networks To do so we analyze a random Erdos-Renyi network where 10% of the neurons are randomly selected to be inhibitory and balance out , on average , the excitatory connection weight in the network ( see Methods l for more details ) . The result of this process is a block Erdos-Renyi network with a non-trivial statistics of motifs and cumulants . The sign of the motifs reflects their excitatory , inhibitory or mixed nature . Importantly E-I networks tend to be more stable , which allows for stronger synapses overall . Taking advantage of this , we increase the average synaptic strength by changing its scaling from 1/N to 1 / N [60 , 64] . We see that the resulting relationship between the dimensionality of the network and the average synaptic connectivity p in Fig 6a is even stronger that in the fully excitatory case of Fig 3a . Specifically , Fig 6a shows that the dimensionality rapidly decreases as a function of the average connectivity , and—different from the purely excitatory case—does so with a very steep initial slope . Moreover , the dimensionality decreases very quickly as a function of average correlations Fig 6c , so that , once again , E-I networks whose activity might at first appear to be ( at least on average ) independent due to low values of average pairwise correlations actually show very tightly coordinated dynamics . We also find that the theoretical approximation ( red dots ) , despite capturing the overall steeply decreasing trend , is in poor agreement with the full ( exact ) values of dimensionality . This is due to the fact that the theory shown is perturbative ( we keep terms only up to second order cfr . Fig 2 ) and that excitatory/inhibitory networks require more resumming directions u due to their spectral properties . While these matters will be the focus of future work , at the price of increasing the complexity of our analysis [18] , we here wish to highlight the underlying limitations at second order , at least in our hands , while pointing out important trends in the relationship between the dimensionality of the response and other network properties . For example Fig 6b and 6c show that , in the balanced case , the theory approximates to a better extent the average correlations ( Fig 6b ) than the dimensionality [17 , 18] . To highlight the role of cumulants in controlling these effects we carry out a similar analysis to the one illustrated in Fig 3d to 3g . We compute the dimensionality for an ensemble of 500 SONETS networks of 1000 neurons each ( see Methods m ) with excitatory connectivity p = 0 . 03 . The average connectivity between inhibitory neurons , together with the motif content , varies perturbatively around p = 0 . 03 . How the dimensionality varies as a function of the probability of connection between inhibitory neurons is shown in Fig 6f , for each network in the ensemble . We then carry out a multilinear regression where the dimensionality of the network is regressed against all the values of the cumulants between neurons in the inhibitory population ( r2 = 0 . 420 ) . The result is shown in Fig 6d . This result is similar to the one shown in Fig 4e and shows how different motifs may lead to a dimensionality increase or decrease . One of the main characteristics of E-I balanced networks is the cancellation between strong excitatory and inhibitory contributions . This , in turn , means that the network tends to be in a strongly coupled regime where the internal dynamics is strong and the inputs , rather than driving the network , are entrained to its dynamics . This is shown in Fig 6d , where the dimensionality of the network varies with the input dimensionality but the span over which the former is modulated by less than 30% , from a dimensionality of roughly 30% to a dimensionality of roughly 60% , over a wide range of input dimensions . If we imagine the input to itself vary in a reasonable range of , say , 30% then the network acts to equalize the dimensionality of its response across this range . Specifically , this seems to be achieved optimally at the minimum of the green line in Fig 6e , where the contribution of the input and internal network dynamics appears to be of similar strength . This may be an important working point for the network , as we will further cover in the Discussion .
We have introduced a theory of dimensionality in linear , spiking recurrent networks , which predicts the dimensionality of a network’s response from basic features of its internal connectivity and the stimuli it receives . The theory builds on the existing framework of motif cumulants [17 , 18 , 19 , 43] , which identified the significance of connectivity motifs in leading a number of other effects in the network dynamics . We single out three important results from our analysis for further discussion here . First , we find that the statistics of highly local “second order” connectivity motifs—subnetworks of just two or three cells at a time—can be used to predict several ( but not all ) global aspects of the dimensionality of network-wide activity . These are as follows: for purely excitatory , autonomously spiking networks , the values of connection probability and the prevalance of second order connectivity motifs provides highly accurate quantitative predictions of dimension—and hence dimension appears to be regulated by these connection features alone . For excitatory-inhibitory networks , we can use these localized motifs to make qualitative predictions about trends in dimension with connectivity , but quantitative estimates have large errors . The same is true about the network response to strong inputs: trends can be captured from local motif cumulants , but quantitative accuracy demands a fuller description of network connectivity . The ability , when it occurs , of local circuit features to regulate global activity patterns is important because local activity dependence appears as one of the major constraints in biological learning paradigms [65 , 66 , 67] . Thus , when it succeeds , expressing neural dynamics in terms of local connectivity motifs may reveal the function of learning rules , and how they target the dynamics of specific connectivity patterns [68 , 69] . Second , our results show that the dimensionality of the network activity has the tendency to assume low values , even when the average pairwise correlations in a network are themselves so low that it might be tempting to consider them as neglibible . In Figs 3h , 5e and 6c we have shown that , across a number of different connectivity regimes , the network response has low dimensionality when the average correlation is lower than 0 . 025 . This effect is important , it may point to the dimensionality , rather than the often reported statistic of average pairwise correlations ( see review in [35] ) , as a better metric for describing how strongly network activity is coordinated [27 , 44] . Moreover , our theory suggests that specific connectivity motifs , i . e . reciprocal motifs , have a prominent role in influencing the activity dimensionality over and above its average correlation . Third , depending on stimulus properties and network connectivity , the network response may have a higher or lower dimensionality than the stimulus; in this way , feeding a stimulus to a network results in either an expanded or contracted dimensionality in the response ( cfr . Figs 4 and 6e ) . Which of these occurs depends strongly on the network connectivity . Here , stronger coupling leads to a more restricted range of dimensionalities with which the network operates . This restricted range—produced in response to a wide range of stimuli—may be interpreted as a type of “dimensionality equalization:” the network reduces or expands the stimulus dimensionality to lie in a relatively tight range Figs 4e and 6e . Moreover , when inputs assume a fixed strength in each dimension , there is a specific stimulus dimensionality where the network response assumes minimum value . This point is of interest as it marks the transition from a dynamical regime dominated by the internal network response to one governed by the stimulus: thus , near the minimum , the network is entrained by the stimulus but not dominated by it , with the internal dynamics serving as scaffold for the activity that is produced . All these results are currently of high relevance to experimental efforts to quantify connectivity structures in neural networks . Because low-order connectivity motifs involve connections among only a few cells at a time , they can be measured with the techniques such as multi-patch recordings , with each new recording viewed as a sample from the network; in fact , [16 , 70] used exactly this approach and quantified synaptic motif motifs in cortical networks in vitro . While structural connectomics data [71] does not currently include precise estimates of synaptic strengths , it can be used to estimate the abundance of motif structures . Another approach begins by fitting “GLM” type models of functional connectivity directly to large-scale recordings of neural activity [72 , 73] . This results in an effective interaction matrix among all neurons that , while not a direct description of synaptic connections [74 , 75] , still defines a network whose connection structures produce activity patterns in the same way that our theory describes . Altogether , we hope that our theory will be an important tool in interpreting the large scale data on neural activity and connectivity that is increasingly becoming available . We close by considering three future research directions that our work here has helped to define . The first is the question of finding efficient , readily measurable features of network connectivity that drive key aspects of neural network dynamics . Here , we demonstrated some substantial new successes , and failures , of local connectivity motifs in this regard . Further research across our field will be important to understand the relevance of specific connectivity patterns and their statistics , including how they vary across space and cell types [21 , 76] . This will be especially interesting in relation to next generation connectomics data , which may unlock new roles and new forms of connectivity structures . The second is the extension to nonlinear network of this link between connectivity structure and activity dimension . While the theory in this study is for networks that are linearized around their working point , recent work [77 , 78] has developed an expansion that predicts correlations of arbitrary orders in similar Poisson-type networks , for increasing orders of nonlinearity . Further work to elucidate their influence in shaping the dimensionality of neural response would extend the scope of the present analysis beyond linear circuits , possibly bridging our framework with others that have been recently advanced [79] . The third and final direction for future study is analysis of the stimulus entrainment of network dynamics highlighted above . Specifically , neural representations , i . e . the encoding of stimulus-specific information by neural networks , may involve circuitry that either increases , decreases , or equalizes the dimensionality of neural responses , but further work is needed to understand the implications for neural coding [2 , 3 , 27] .
The expression for the dimensionality Dim ( C ) is the ratio between Tr ( C ) 2 and Tr ( C2 ) . In terms of cumulants the functions of Eq 11 can be written as: Tr ( C ) = c 0 ( 1 - ∑ n = 1 ∞ N n k n c h ) - 2 ( 1 + ∑ n , m = 1 ∞ N n + m k n , m d i v ) ( 1 + ∑ n . m = 1 ∞ N n + m k n , m c o n v ) + c 0 N ∑ n , m = 1 ∞ N n + m κ n , m T r Tr ( C 2 ) = c 0 2 ( 1 - ∑ n = 1 ∞ N n k n c h ) - 4 ( 1 + ∑ n , m = 1 ∞ N n + m k n , m d i v ) 2 ( 1 + ∑ n . m = 1 ∞ N n + m k n , m c o n v ) 2 + N c 0 2 ∑ n , m , p , q = 1 ∞ N n + m + p + q κ n , m , p , q T r . ( 21 ) These two expressions are both tightly linked to the average covariance Eq 10 . In particular they can be written as follows to highlight this connection: Tr ( C ) = N ⟨ C ⟩ · ( 1 + ∑ n . m = 1 ∞ N n + m k n , m c o n v ) + c 0 N ∑ n , m = 1 ∞ N n + m κ n , m T r Tr ( C 2 ) = N ⟨ C ⟩ 2 · ( 1 + ∑ n . m = 1 ∞ N n + m k n , m c o n v ) 2 + N c 0 2 ∑ n , m , p , q = 1 ∞ N n + m + p + q κ n , m , p , q T r . ( 22 ) The full expression for Eq 19 is: Tr ( C e x t ) = c ξ ( 1 - ∑ n = 1 ∞ N n κ e x t - n ) - 2 ( 1 + ∑ n . m = 1 ∞ ( g N ) n + m κ e x t - n , m c o n v ) Tr ( C e x t 2 ) = c ξ 2 ( 1 - ∑ n = 1 ∞ N n κ ˜ e x t - n ) - 4 ( 1 + ∑ n . m = 1 ∞ N n + m κ e x t - n , m c o n v ) 2 Tr ( C i n p · C e x t ) = c 0 c ξ ( 1 - ∑ n = 1 ∞ N n κ ˜ e x t - n ) - 4 ( 1 + ∑ n . m = 1 ∞ N n + m κ ˜ e x t - n , m d i v ) 2 ( 1 + ∑ n . m = 1 ∞ N n + m κ ˜ e x t - n , m c o n v ) . ( 23 ) These formulas can be resumed with different choices of cumulants . In particular both κint and κext can be employed simultaneously ( cfr . S1 File Sec . S3 . 2 ) . In Eq 23 we show the expression used to generate figures in the main text; this choice is best motivated in the case of low dimensional input . The SONET model for random graphs can be seen as an extension of the Erdos-Renyi model . In an Erdos-Renyi graph two nodes are randomly connected with probability p ( 0 ≤ p ≤ 1 ) . In SONET networks also second order connection motifs ( convergent , divergent , etc . ) appear with controlled statistics ( see [41 , 57] for further details ) . The total number of parameters for the generation of a network is five: the average connectivity and the relative aboundance of convergent , divergent , reciprocal , chains motifs statistics . As an extension of the Erdos-Renyi model , the algorithm we use ( provided by the authors of [41] ) generates a W with binary entries by maximizing a maximum likekelihood for the maximum entropy of the connectivity entries . To each binary connectivity state , the algorithm associates a probability under the 5 parameters of the model ( average connectivity p and probability of convergent , divergent , reciprocal and chain motifs ) . For further details we point the reader to [80] . The ensemble of networks used for Fig 3b , 3c and 3h consists of 500 networks with N = 1000 neurons each . All networks share the parameters c0 = 1 , Aii = 10 ∀i ∈ {1‥N} while the connectivity graph W is generated through the SONET algorithm with the same set of parameters ( α’s ) used in [41] . Such parameters regulate the statistics of convergent , divergent , reciprocal and chain motifs . They are uniformly sampled in the ranges p ∈ [0 . 01 , 0 . 1] , αrecip ∈ [−1 , 4] , αconv ∈ [0 , 1] , αdiv ∈ [0 , 1] and αchain ∈ [−1 , 1] . The ensemble of networks used for Fig 3d to 3g has exactly the same parameters as the one above , except that the range for p is different: p ∈ [0 . 078 , 0 . 082] . The dimensionality for each network is computed and the difference in dimensionality from an Erdos-Renyi network with p = pER = 0 . 08 is regressed against 6 different variables: p − pER , and the value of chain , convergent , divergent and the two trace cumulants . The coefficients of the regression are displayed in Fig 3e . These figures display the full covariance dimensionality expression Eq 3 and the motif reduction Eq 11 for a SONET network with p = 0 . 03 and a random choice of second order motifs . An input of varying strength and number of factors is fed onto the network . This is captured by C i n p = ∑ i N i n p c ξ , i ξ i ξ i T where each ξ is a random vector of unit norm . In the case of Fig 4a the number of factors Ndim is increased and cξ = 0 . 05 . In Fig 4c the number of factors is one while cξ is increased . In Fig 4d the number of factors is increased but the total strength constrained to ∑ i N i n p c ξ , i 2 = 2 . 5 c 0 . The procedure for obtaining these figures is equal to the one used for Fig 4a , 4c and 4d except that the initial network is a SONET network with p = 0 . 08 and random second order motifs . The pink line in these figures corresponds to a theoretical approximation of the formula in Eq 18 . The term in the denominator Tr ( Cint ⋅ Cext ) is the only term in the expression with the product Cint and Cext . We used the following inequality to build an upper bound for this term: Tr ( C i n t · C e x t ) 2 ≤ Tr ( C i n t 2 ) · Tr ( C e x t 2 ) ≤ 1 2 ( Tr ( C i n t ) + Tr ( C e x t ) ) 2 . ( 24 ) By substituting the rightmost side of this expression into Eq 18 we obtain the expression for the pink line displayed in Fig 4a , 4c and 4d . The figures use the same values and techniques of Fig 3b and 3c . The different network architectures are all generated using the package NetworkX in Python 3 . 6 . The Erdos-Renyi network is a randomly connected network , the small world network has a number of nodes denoted by p ⋅ N and probability of rewiring 0 . 3 , the scale-free network is obtained through a Barabasi-Albert graph where the number of number of edges to attach from a new node to existing nodes ( parameter m ) is derived as a function of the final number of connections p ⋅ N and the number of nodes N ( m = ( N + N 2 - 2 N 2 p ) / 2 ) . The networks displayed in these figures are 500 SONET networks with average synaptic strength g = 1 . 25 / N that scales with N rather than N . For each network a random 10% of the neurons is selected to be inhibitory and their strength rescaled so that 〈GEE〉 = 〈GII〉 where GEE and GII denote respectively the part of the connectivity graph G in between the excitatory and the inhibitory population . We checked that the network so obtained respects the constraints for a balanced state determined in [81] . We generate 500 SONET networks with connectivity p = 0 . 03 . Upon balancing the network 10% of the neurons are inhibitory . The dimensionality of this ensemble of networks is regressed against the values of the connectivity cumulants computed on the inhibitory part of the network . | New recording technologies are producing an amazing explosion of data on neural activity . These data reveal the simultaneous activity of hundreds or even thousands of neurons . In principle , the activity of these neurons could explore a vast space of possible patterns . This is what is meant by high-dimensional activity: the number of degrees of freedom ( or “modes” ) of multineuron activity is large , perhaps as large as the number of neurons themselves . In practice , estimates of dimensionality differ strongly from case to case , and do so in interesting ways across experiments , species , and brain areas . The outcome is important for much more than just accurately describing neural activity: findings of low dimension have been proposed to allow data compression , denoising , and easily readable neural codes , while findings of high dimension have been proposed as signatures of powerful and general computations . So what is it about a neural circuit that leads to one case or the other ? Here , we derive a set of principles that inform how the connectivity of a spiking neural network determines the dimensionality of the activity that it produces . These show that , in some cases , highly localized features of connectivity have strong control over a network’s global dimensionality—an interesting finding in the context of , e . g . , learning rules that occur locally . We also show how dimension can be much different than first meets the eye with typical “pairwise” measurements , and how stimuli and intrinsic connectivity interact in shaping the overall dimension of a network’s response . | [
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"in... | 2019 | Dimensionality in recurrent spiking networks: Global trends in activity and local origins in connectivity |
Transcriptome-wide time series expression profiling is used to characterize the cellular response to environmental perturbations . The first step to analyzing transcriptional response data is often to cluster genes with similar responses . Here , we present a nonparametric model-based method , Dirichlet process Gaussian process mixture model ( DPGP ) , which jointly models data clusters with a Dirichlet process and temporal dependencies with Gaussian processes . We demonstrate the accuracy of DPGP in comparison to state-of-the-art approaches using hundreds of simulated data sets . To further test our method , we apply DPGP to published microarray data from a microbial model organism exposed to stress and to novel RNA-seq data from a human cell line exposed to the glucocorticoid dexamethasone . We validate our clusters by examining local transcription factor binding and histone modifications . Our results demonstrate that jointly modeling cluster number and temporal dependencies can reveal shared regulatory mechanisms . DPGP software is freely available online at https://github . com/PrincetonUniversity/DP_GP_cluster .
The analysis of time series gene expression has enabled insights into development [1–3] , response to environmental stress [4] , cell cycle progression [5 , 6] , pathogenic infection [7] , cancer [8] , circadian rhythm [9 , 10] , and other biomedically important processes . Gene expression is a tightly regulated spatiotemporal process . Genes with similar expression dynamics have been shown to share biological functions [11] . Clustering reduces the complexity of a transcriptional response by grouping genes into a small number of response types . Given a set of clusters , genes are often functionally annotated by assuming guilt by association [12] , sharing sparse functional annotations among genes in the same cluster . Furthermore , regulatory mechanisms characterizing shared response types can be explored using these clusters by , for example , comparing sequence motifs or other features within and across clusters . Clustering methods for time series transcription data partition genes into disjoint clusters based on the similarity of expression response . Many clustering methods , such as hierarchical clustering [11] , k-means clustering [13] , and self-organizing maps [14] , evaluate response similarity using correlation or Euclidean distance . These methods assume that expression levels at adjacent time points are independent , which is invalid for transcriptomic time series data [15] . Some of these methods require a prespecified number of clusters , which may require model selection or post hoc analyses to determine the most appropriate number . In model-based clustering , similarity is determined by how well the responses of any two genes fit the same generative model [15 , 16] . Model-based methods thus define a cluster as a set of genes that is more likely to be generated from a particular cluster-specific model than other possible models [17] . Mclust , for example , assumes a Gaussian mixture model ( GMM ) to capture the mean and covariance of expression within a cluster . Mclust selects the optimal number of clusters using the Bayesian information criterion ( BIC ) [18] . However , Mclust does not take into account uncertainty in cluster number [19] . To address the problem of cluster number uncertainty , finite mixture models can be extended to infinite mixture models using a Dirichlet process ( DP ) prior . This Bayesian nonparametric approach is used in the Infinite Gaussian Mixture Model [20] and implemented in the tools Gaussian Infinite Mixture Models , or GIMM [21] and Chinese Restaurant Cluster , or CRC [22] . Using Markov chain Monte Carlo ( MCMC ) sampling , GIMM iteratively samples cluster-specific parameters and assigns genes to existing clusters , or creates a new cluster based on both the likelihood of the gene expression values with respect to the cluster-specific model and the size of each cluster [21] . An advantage of nonparametric models is that they allow cluster number and parameter estimation to occur simultaneously when computing the posterior . The DP prior has a “rich get richer” property—genes are assigned to clusters in proportion to the cluster size—so bigger clusters are proportionally more likely to grow relative to smaller clusters . This encourages varied cluster sizes as opposed to approaches that encourage equivalently sized clusters . Clustering approaches for time series data that encode dependencies across time have also been proposed . SplineCluster models the time dependency of gene expression data by fitting non-linear spline basis functions to gene expression profiles , followed by agglomerative Bayesian hierarchical clustering [23] . The Bayesian Hierarchical Clustering ( BHC ) algorithm performs Bayesian agglomerative clustering as an approximation to a DP model , merging clusters until the posterior probability of the merged model no longer exceeds that of the unmerged model [24–26] . Each cluster in BHC is parameterized by a Gaussian process ( GP ) . With this greedy approach , BHC does not capture uncertainty in the clustering . Recently , models combining DPs and GPs have been developed for time series data analysis . For example , a recent method combines the two to cluster low-dimensional projections of gene expression [27] . The semiparametric Bayesian latent trajectory model was developed to perform association testing for time series responses , integrating over cluster uncertainty [28] . Other methods using DPs or approximate DPs to cluster GPs for gene expression data use different parameter inference methods [25 , 27 , 29] . However , several methods similar to DPGP lack software to enable application of the methods by biologists or bioinformaticians [27 , 29] . Here we develop a statistical model for clustering time series data , the Dirichlet process Gaussian process mixture model ( DPGP ) , and we package this model in user-friendly software . Specifically , we combine DPs for incorporating cluster number uncertainty and GPs for modeling time series dependencies . In DPGP , we explore the number of clusters and model the time dependency across gene expression data by assuming that gene expression for genes within a cluster are generated from a GP with a cluster-specific mean function and covariance kernel . A single clustering can be selected according to one of a number of optimality criteria . Additionally , a matrix is generated that contains estimates of the posterior probability that each pair of genes belongs to the same cluster . Missing data are naturally incorporated into this GP framework , as are observations at unevenly spaced time points . If all genes are sampled at the same time points with no missing data , we leverage this fact to speed up the GP regression task in a fast version of our algorithm ( fDPGP ) . To demonstrate the applicability of DPGP to gene expression response data , we applied our algorithm to simulated , published , and original transcriptomic time series data . We first applied DPGP to hundreds of diverse simulated data sets , which showed favorable comparisons to other state-of-the-art methods for clustering time series data . DPGP was then applied to a previously published microarray time series data set , recapitulating known gene regulatory relationships [30] . To enable biological discovery , RNA-seq data were generated from the human lung epithelial adenocarcinoma cell line A549 from six time points after treatment with dexamethasone ( dex ) for up to 11 hours . By integrating our DPGP clustering results on these data with a compendium of ChIP-seq data sets from the ENCODE project , we reveal novel mechanistic insights into the genomic response to dex .
We tested whether DPGP recovers true cluster structure from simulated time series data . We applied DPGP and the fast version of DPGP , fDPGP , to 620 data sets generated using a diverse range of cluster sizes and expression traits ( S1 Table ) . We compared our results against those from BHC [25] , GIMM [21] , hierarchical clustering by average linkage [11] , k-means clustering [13] , Mclust [18] , and SplineCluster [23] . To compare observed partitions to true partitions , we used Adjusted Rand Index ( ARI ) , which measures the similarity between a test clustering and ground truth in terms of cluster agreement for element pairs [31 , 32] . ARI is 1 when two partitions agree exactly and 0 when two partitions agree no more than is expected by chance [31 , 32] . ARI was recommended in a comparison of metrics [33] and has been used to compare clustering methods in similar contexts [21 , 34–36] . Assuming GPs as generating distributions , we simulated data sets with varied cluster size distributions , length scale , signal variance , and marginal variance ( S1 Table ) . Across simulations , DPGP generally outperformed GIMM , k-means , and Mclust , but was generally outperformed by BHC and SplineCluster , and performed about as well as hierarchical clustering ( Fig 1 and S2 Table ) . fDPGP performed nearly as well as DPGP ( Fig 1C ) . The performance of hierarchical clustering and k-means benefited from prespecification of the true number of clusters—with a median number of 24 clusters across simulations—while the other methods were expected to discover the true number of clusters with no prior specification . In scientific applications , a priori knowledge of the optimal number of clusters is unavailable , necessitating multiple runs and post hoc analyses for hierarchical clustering and k-means . Methods that do not model temporal dependencies in observations—GIMM , k-means , and Mclust—performed worst in our evaluations , suggesting that there is substantial value in explicitly modeling temporal dependencies . We simulated an additional 500 data sets with t-distributed errors ( df = 2 ) , which is a heavier-tailed distribution than the Gaussian and may more realistically reflect the distribution of quantified gene expression levels in RNA-seq data [37] . Again , we varied cluster size , length scale , and signal variance ( S1 Table ) . In these simulations , DPGP outperformed BHC , SplineCluster , Mclust , and hierarchical clustering , and was outperformed by GIMM and k-means clustering ( S1 Fig and S2 Table ) . DPGP and fDPGP performed nearly the same ( Wilcoxon two-sided signed-rank , p = 0 . 12 ) . Across all simulations , performance depended on the assumptions of the simulated data and no algorithm outperformed all others across all data sets . DPGP performed well under both Gaussian- and t-distributed error models , which demonstrates robustness to model assumptions . DPGP successfully recovered true cluster structure across a variety of generating assumptions except in cases of a large number of clusters each with a small number of genes ( data sets 4 and 5 ) or a small signal variance ( data set 16 ) and a high marginal variance ( data set 31; Fig 1 ) . It is possible that DPGP performed poorly on data sets with many clusters , each with a small number of genes , because this kind of cluster size distribution poorly matches the DP prior . The DP prior may not be appropriate for all clustering applications . However , BHC , which also assumes a DP prior , performed quite well on these data sets . Moreover , clustering a large number of genes ( 500 ) into a large number of clusters ( 100 ) might best be performed using other types of methods [38] For each gene , DPGP can optionally estimate a probability of inclusion to its assigned cluster based on the weighted mean frequency of co-occurrence with all other genes in that cluster across Gibbs samples . Performance of DPGP on the data sets with Gaussian-distributed error improved after omitting genes with low probability cluster assignments both across all data sets and across the ten data set classes for which DPGP performed worst ( Wilcoxon two-sided signed-rank , including only genes with probability of inclusion of , e . g . , ≥ 0 . 7 versus all genes , p ≤ 2 . 2 × 10−16; S2A and S2C Fig ) . Performance did not improve when cluster assignment probabilities were permuted across genes ( p > 0 . 21 , S2B and S2D Fig ) . After excluding genes with cluster inclusion probabilities < 0 . 9 , there was an improvement in performance for data sets with small signal variance ( data sets 16 and 17 ) or high marginal variance ( data sets 30 and 31 ) , but minimal improvement on data sets with a large number of clusters , each with a small number of genes ( data sets 4 and 5; S2E Fig ) . These results imply that DPGP generates useful cluster assignment probabilities . The algorithms tested varied greatly in speed . On moderately sized data sets ( ≲ 1 , 000 genes ) , fDPGP was substantially faster than GIMM and BHC , but slower than hierarchical clustering , k-means , Mclust , and SplineCluster [S3A Fig; Wilcoxon two-sided signed-rank ( WSR ) , DPGP versus each method , p ≤ 8 . 86 × 10−5] . On larger data sets of up to 10 , 000 genes , fDPGP again was faster than BHC and GIMM ( S3B Fig; WSR , DPGP versus each method , p ≤ 5 . 06 × 10−3 ) . BHC failed to cluster data sets with ≥ 2 , 000 genes within 72 hours . Because of the speed and reliable clustering performance of fDPGP , we use this version in the biological data applications below . An important advantage of DPGP , as a probabilistic method , is that uncertainty in clustering and cluster trajectories is captured explicitly . Some implications of the probabilistic approach are that cluster means and variances can be used to quantify the likelihood of future data , to impute missing data points at arbitrary times , and to integrate over uncertainty in the cluster assignments [39] . Using these same data simulations , we clustered expression trajectories while holding out each of the four middle time points of eight total time points . We computed the proportion of held-out test points that fell within the 95% credible intervals ( CIs ) of the estimated cluster means . For comparison , we also permuted cluster membership across all genes 1 , 000 times and recomputed the same proportions . We found that DPGP provided accurate CIs on the simulated gene expression levels ( S4 Fig ) . Across all simulations , at least 90% of test points fell within the estimated 95% CI , except for data set types with large length-scales or high signal variances ( both parameters ∈ {1 . 5 , 2 , 2 . 5 , 3} ) . The proportion of test points that fell within the 95% CIs was consistently higher for true clusters than for permuted clusters [Mann-Whitney U-test ( MWU ) , p ≤ 2 . 24 × 10−6] , except for data with small length scales ( {0 . 1 , … , 0 . 5} ) when the proportions were equivalent ( MWU , p = 0 . 24 ) . This implies that the simulated sampling rates in these cases were too low for DPGP to capture temporal patterns in the data . For the simulations with Gaussian-distributed error , in which DPGP performed worse than BHC or SplineCluster with respect to recovering the true cluster structure , the clusters inferred from the data provided useful and accurate CIs for unseen data . For example , DPGP performed decreasingly well as the marginal variance was increased to 0 . 4 , 0 . 5 , and 0 . 6 . However , the median proportions of test points within the 95% CIs were 93 . 4% , 92 . 6% , 91 . 9% , respectively ( S4 Fig ) . This suggests that DPGP provides well calibrated CIs on expression levels over the time course and can theoretically be used for reliable imputation at arbitrary time points . DPGP may also be used to evaluate the confidence in a specific clustering with respect to the fitted model , which can be important for revealing instances when many different partitions model the data nearly as well as one another . For example , across our simulated datasets , when DPGP did not precisely recover the cluster structure , we found there was also substantial uncertainty in the optimal partition . Specifically , the posterior probability of the oracle clustering with respect to the simulated observations was greater than both the posterior probability of the DPGP MAP partition and than the mean posterior probability across all DPGP samples in only 1 . 6% of cases ( Z-test , p < 0 . 05 ) . This suggests that , in nearly all simulated examples , the posterior probability was not strongly peaked at the true partition . Given the performance of DPGP on simulated data with minimal user input and no prespecification of cluster number , we next sought to assess the performance of DPGP on biological data . As a test case , we applied DPGP to published data from a single-celled model organism with a small genome ( Halobacterium salinarum; 2 . 5 Mbp and 2 , 400 genes ) exposed to oxidative stress induced by addition of H2O2 [30] . This multifactorial experiment tested the effect of deletion of the gene encoding the transcription factor ( TF ) RosR , which is a global regulator that enables resilience of H . salinarum to oxidative stress [40] . Specifically , transcriptome profiles of a strain deleted of the rosR gene ( ΔrosR ) and control strain were captured with microarrays at 10–20 minute intervals following exposure to H2O2 . In the original study , 616 genes were found to be differentially expressed ( DEGs ) in response to H2O2 , 294 of which were also DEGs in response to rosR mutation . In previous work , the authors clustered those 294 DEGs using k-means clustering with k = 8 ( minimum genes per cluster = 13; maximum = 86; mean = 49 ) [30] . We used DPGP on these H . salinarum time series data to cluster expression trajectories from the 616 DEGs in each strain independently , which resulted in six clusters per strain when we consider the maximum a posteriori ( MAP ) partition ( Fig 2 ) . The number of genes in clusters from DPGP varied widely across clusters and strains ( minimum genes per cluster = 2; maximum = 292; mean = 102 . 7 ) with greater variance in cluster size in trajectories from the mutant strain . To assess how DPGP clustering results compared to previous results using k-means , we focused on how the deletion of rosR affected gene expression dynamics . Out of the 616 DEGs , 372 moved from a cluster in the control strain to a cluster with a different dynamic trajectory in ΔrosR ( e . g . , from an up-regulated cluster under H2O2 in control , such as cluster 5 , to a down-regulated cluster in ΔrosR , such as cluster 3; Fig 2 and S3 Table ) . Of these 372 genes , 232 were also detected as differentially expressed in our previous study [30] [significance of overlap , Fisher’s exact test ( FET ) , p ≤ 2 . 2 × 10−16] . Comparing these DPGP results to previous analyses , similar fractions of genes were found to be directly bound by RosR according to ChIP-chip data from cells exposed to H2O2 for 0 , 10 , 20 , and 60 minutes [40] . When all RosR binding at all four ChIP-chip time points were considered together , 8 . 9% of DPGP genes changing clusters were bound , similar to the 9 . 5% of DEGs that were bound in the previous analysis [30] . Genes most dramatically affected by deletion of rosR were those up-regulated after 40 minutes of H2O2 exposure in the control strain . For example , all 141 genes in control cluster 5 changed cluster membership in the ΔrosR strain ( Fig 2; FET , p ≤ 2 . 2 × 10−16 ) . Of these 141 genes up-regulated in the control strain in response to H2O2 , 89 genes ( 63% ) exhibited inverted dynamics , changing to down-regulated in the ΔrosR strain . These 89 genes grouped into two clusters in the ΔrosR strain ( ΔrosR clusters 3 and 5; Fig 2 and S3 Table ) . The transcriptional effect of rosR deletion noted here accurately reflects previous observations: 84 of these 89 genes showed differential trajectories in the control versus ΔrosR strains previously [30] . RosR is required to activate these genes in response to H2O2 [30] . These results suggest that DPGP analysis accurately recapitulates previous knowledge of RosR-mediated gene regulation in response to H2O2 with reduced user input . Given the performance of DPGP in recapitulating known results for biological data , we next used DPGP for analysis of novel time series transcriptomic data . Specifically , we used DPGP to identify co-regulated sets of genes and candidate regulatory mechanisms in the human glucocorticoid ( GC ) response . GCs , such as dex , are among the most commonly prescribed drugs for their anti-inflammatory and immunosuppressive effects [41] . GCs function in the cell primarily by affecting gene expression levels . Briefly , GCs diffuse freely into cells , where they bind to and activate the glucocorticoid receptor ( GR ) . Once bound to its ligand , GR translocates into the nucleus , where it binds DNA and regulates expression of target genes . The induction of expression from GC exposure has been linked to GR binding [42 , 43] . However , while there are a plethora of hypotheses regarding repression and a handful of well-studied cases [44 , 45] , it has proved difficult to associate repression of gene expression levels with genomic binding on a genome-wide scale [42 , 43] . Further , GC-mediated expression responses are far more diverse than simple induction or repression , motivating a time course study of these complex responses [46–50] . To characterize the genome-wide diversity of the transcriptional response to GCs and to reveal candidate mechanisms underlying those responses , we performed RNA-seq in the human lung adenocarcinoma-derived A549 cell line after treatment with the synthetic glucocorticoid ( GC ) dex at 1 , 3 , 5 , 7 , 9 , and 11 hours , resulting in six time points . This data set is among the most densely sampled time series of the dex-mediated transcriptional response in a human cell line .
We developed a Dirichlet process Gaussian process mixture model ( DPGP ) to cluster measurements of genomic features such as gene expression levels over time . We showed that our method effectively identified disjoint clusters of time series gene expression observations using extensive simulations . DPGP compares favorably to existing methods for clustering time series data , is robust to non-Gaussian marginal observations , and , importantly , includes measures of uncertainty and an accessible , publicly-available software package . We applied DPGP to existing data from a microbial model organism exposed to stress . We found that DPGP accurately recapitulated previous knowledge of TF-mediated gene regulation in response to H2O2 with minimal user input . We applied DPGP to a novel RNA-seq time series data set detailing the transcriptional response to dex in a human cell line . Our clusters identified four major response types: quickly up-regulated , slowly up-regulated , quickly down-regulated , and slowly down-regulated genes . These response types differed in TF binding and histone modifications before dex treatment and in changes in TF binding following dex treatment , indicating shared biological processes among genes in the same response cluster . As with all statistical models , DPGP makes a number of assumptions about observations . In particular , DPGP assumes i ) cluster trajectories are stationary; ii ) cluster trajectories are exchangeable; iii ) each gene belongs to only one cluster; iv ) expression levels are sampled at the same time points across all genes; and v ) the time point-specific residuals have a Gaussian distribution . Despite these assumptions , our results show that DPGP is robust to certain violations . In the human cell line data , exposure to dex resulted in a non-stationary response ( at time point lag 1 , all dex-responsive genes had either Augmented Dickey-Fuller p < 0 . 05 or Kwiatkowski—Phillips—Schmidt—Shin p > 0 . 05 ) , and the residuals did not follow a Gaussian distribution ( Schapiro-Wilk test , p ≤ 2 . 2 × 10−16 ) , violating assumptions ( i ) and ( v ) . However , despite these assumption violations , we found that DPGP clustered expression trajectories in a robust and biologically interpretable way . Furthermore , because DPGP does not assume that the gene expression levels are observed at identical intervals across time , DPGP allows study designs with non-uniform sampling . Our DPGP model can be readily extended or interpreted in additional ways . For example , DPGP returns not only the cluster-specific mean trajectories but also the covariance of that mean , which is useful for downstream analysis by explicitly specifying confidence intervals around interpolated time points . Given the Bayesian framework , DPGP naturally allows for quantification of uncertainty in cluster membership by analysis of the posterior similarity matrix . For example , we could test for association of latent structure with specific genomic regulatory elements after integrating over uncertainty in the cluster assignments [39] . DPGP can also be applied to time series data from other types of sequencing-based genomics assays such as DNase-seq and ChIP-seq . If we find that the Gaussian assumption is not robust for alternative data types , we may consider using different distributions to model the response trajectories , such as a Student-t process [71] . When DPGP was applied to RNA-seq data from A549 cells exposed to GCs , the clustering results enabled several important biological observations . Two down-regulated response types were distinguished from one another based on histone marks and TF binding prior to GC exposure . The rapidly down-regulated cluster included homeobox TFs and growth factor genes and was enriched for basal enhancer regulatory activity . In contrast , slowly down-regulated cluster included critical cell cycle genes and was enriched for basal promoter regulatory activity . More study is needed to resolve how GCs differentially regulate these functionally distinct classes of genes . GR tends to bind distally from promoters [42] so that rapid down-regulation may be a direct effect of GR binding , while slower down-regulation may be secondary effect . We also found that down-regulated genes lost binding of transcriptional activators in distal regions , while up-regulated genes gained binding . This result links genomic binding to GC-mediated repression on a genome-wide scale . With increasing availability of high-throughput sequencing time series data , we anticipate that DPGP will be a powerful tool for characterizing cellular response types .
We developed a Bayesian nonparametric model ( S9 Fig ) for time series trajectories Y∈RP×T , where P is the number of genes and T the number of time points per sample , assuming observations at the same time points across samples , but allowing for missing observations . In particular , let yj be the vector of gene expression values for gene j ∈ {1 , … , P} for all assayed time points t ∈ {1 , … , T} . Then , we define the generative DP mixture model as follows: G∼DP ( α , G0 ) ; ( 1 ) θh∼G; ( 2 ) yj∼p ( ·|θh ) . ( 3 ) Here , DP represents a draw G from a DP with base distribution G0 . G , then , is the distribution from which the latent variables θh are generated for cluster h , with α > 0 representing the concentration parameter , with larger values of α encouraging more and smaller clusters . We specify the observation distribution yj ∼ p ( ⋅|θh ) with a Gaussian process . With the DP mixture model , we are able to cluster the trajectory of each gene over time without specifying the number of clusters a priori . Using exchangeability , we can integrate out G in the DP to find the conditional distribution of one cluster-specific random variable θh conditioned on all other variables θ¬h , which represent the cluster-specific parameter values of the observation distribution ( here , a GP ) . This allows us to describe the distribution of each parameter conditioned on all others; for all clusters h ∈ {1 , … , H} we have p ( θH|θ1 , … , θH-1 ) ∝αp ( θH|G0 ) +∑h=1H-1δθh ( θH ) , ( 4 ) where δθh ( ⋅ ) is a Dirac delta function at the parameters for the hth partition . A prior could be placed on α , and the posterior for α could be estimated conditioned on the observations . Here we favor simplicity and speed , and we set α to one . This choice has been used in gene expression clustering [19] and other applications [72 , 73] and favors a relatively small number of clusters , where the expected number of clusters scales as αlogP . Our base distribution for the DP mixture model captures the distribution of each parameter of the cluster-specific GP . A GP is a distribution on arbitrary functions mapping points in the input space xt—here , time—to a response yj—here , gene expression levels of gene j across time t ∈ {1 , … , T} . The within-cluster parameters for the distribution of trajectories for cluster h , or θh={μh , ℓh , τh , σh2} , can be written as follows: μh∼GP ( μ0 , K ) ( 5 ) ℓh∼lnN ( 0 , 1 ) ( 6 ) τh∼lnN ( 0 , 1 ) ( 7 ) σh2∼InverseGamma ( αIG , βIG ) ( 8 ) where αIG captures shape and βIG represents rate ( inverse of scale ) . The above hyperparameters may be changed by the user of the DPGP software . By default , αIG is set to 12 and βIG is set to 2 , as these were determined to work well in practice for our applications . For data with greater variability , such as microarray data , the shape parameter can be decreased to allow for greater marginal variance within a cluster . The base distributions of the cluster-specific parameters , which we estimate from the data , were chosen to be the conjugate prior distributions . The positive definite Gram matrix K varies by cluster and quantifies the similarity between every pair of time points x , x′ in the absence of marginal variance using Mercer kernel function Kh , t , t′ = κh ( xt , xt′ ) . We used the squared exponential covariance function ( dropping the gene index j ) : κh ( xt , xt′ ) =τh2exp{-||xt-xt′||22ℓh2} . ( 9 ) The hyperparameter ℓh , known as the characteristic length scale , corresponds to the distance in input space between which two data points have correlated outputs . The hyperparameter τh2 , or signal variance , corresponds to the variance in gene expression trajectories over time . The model could be easily adapted to different choices of kernel functions depending on the stimulating conditions and the smoothness of the trajectories used in the analysis , such as the Matérn kernel [74] , a periodic kernel [75] , or a non-stationary kernel [76] . Including marginal ( i . e . , time point-specific ) variance , σh2 ( Eq 8 ) , the covariance between time points for trajectory yj becomes Kh+σh2I . Thus , yj∼N ( μh , Kh+σh2I ) , ( 10 ) where the marginal variance , σh2 , is unique to each cluster h . This specifies the probability distribution of each observation yj in Eq ( 3 ) according to a cluster-specific GP . Given this DPGP model formulation , we now develop methods to estimate the posterior distribution of the model parameters . We use MCMC methods , which have been used previously in time series gene expression analysis [19 , 22] . MCMC allows the inference of cluster number and parameter estimation to proceed simultaneously . MCMC produces an estimate of the full posterior distribution of the parameters , allowing us to quantify uncertainty in their estimates . For MCMC , we calculate the probability of the trajectory for gene j belonging to cluster h according to the DP prior with the likelihood that gene j belongs to class h according to the cluster-specific GP distribution . We implemented Neal’s Gibbs Sampling “Algorithm 8” to estimate the posterior distribution of the trajectory class assignments [77] . More precisely , let cj be a categorical latent variable specifying to what cluster gene j is assigned , and let c¬j represent the class assignment vector for all trajectories except for gene j . Using Bayes’ rule , we compute the distribution of each cj conditioned on the data and all other cluster assignments: Pr ( cj=h|yj , c¬j , θh , α ) ∝Pr ( cj=h|c¬j , α ) Pr ( yj|cj=h , θh ) ( 11 ) where the first term on the right-hand side represents the probability of assigning the trajectory to cluster h and the second term represents the likelihood that the trajectory yj was generated from the GP distribution for the hth cluster . According to our model specification , the probability Pr ( cj = h|c¬j , α ) in Eq ( 11 ) is equivalent to the Chinese restaurant process in which: Pr ( cj=h|c¬j , α ) ∝{α/mα+n−1ifhisemptyorgenejassignedtosingletoncluster . ∑j=1n1 ( cj=h ) α+n−1otherwise . ( 12 ) In the above , m is the number of empty clusters available in each iteration . Similarly , the likelihood Pr ( yj|cj = h , θh ) in Eq ( 11 ) is calculated using our cluster-specific GPs: Pr ( yj|cj=h , θh ) ={N ( yj|μ0 ( x ) , K0+σ02I ) ifhisemptyorgenejassignedtosingletoncluster . N ( yj|μh ( x ) , Kh+σh2I ) otherwise . ( 13 ) We draw μ0 ( x ) as a sample from the prior covariance matrix , and we put prior distributions on parameters τh2 , ℓh , and σh2 ( Eqs 6–8 ) and estimate their posterior distributions explicitly . In practice , the first 48% of the prespecified maximum number of MCMC iterations is split into two equally sized burn-in phases . At initialization , each gene is assigned to its own cluster , which is parameterized by its mean trajectory and a squared exponential kernel with unit signal variance and unit length-scale [after the mean time interval between sampling points has been scaled to one unit so that the length scale distribution remains reasonable ( Eq 6 ) ] . The local variance is initialized as the mode of the prior local variance distribution . During the first burn-in phase , a cluster is chosen for each gene at each iteration where the likelihood depends on the fit to a Gaussian process parameterized by the cluster’s mean function and the covariance kernel with initial parameters defined above . Before each iteration , m empty clusters ( by default , 4 ) are re-generated , each of which has a mean function drawn from the prior mean function μ0 with variance equivalent to the marginal variance described above . These empty clusters are also assigned the initial covariance kernel parameters described above . After the second burn-in phase , we update the model parameters for each cluster at every sth iteration to increase speed . Specifically , we compute the posterior probabilities of the kernel hyperparameters . To simplify calculations , we maximize the marginal likelihood , which summarizes model fit while integrating over the parameter priors , known as type II maximum likelihood [76] . The updated mean trajectory and covariance , respectively , then become: μh=K ( x , x ) h[K ( x , x ) h+σn , h2I]-1y¯hwherey¯h=y1+⋯+yk∑j=1n1 ( cj=h ) , ( 14 ) Kh*=K ( x′ , x′ ) h-K ( x′ , x ) h[K ( x , x ) h+σn , h2I]K ( x , x′ ) h , ( 15 ) for all expression trajectories {y1 , … , yk} ∈ cluster h . We do this using the fast quasi-Newton limited-memory Broyden-Fletcher-Goldfarb-Shanno ( L-BFGS ) method implemented in SciPy [78] . After the second burn-in phase , the cluster assignment vector c is sampled at every sth iteration to thin the Markov chain , where s = 3 by default . By default , the algorithm runs for 1 , 000 iterations . The algorithm can also check for convergence based on squared distance between the sampled partitions and the posterior similarity matrix and by change in posterior likelihood . The version of statistical inference for DPGP is fully general in that it allows observations at different time points and missing data , which is a desirable feature of GP models . However , when the data are fully observed and the observations of the genes are made at identical time points , we can exploit the structure in the data for additional computational gains , as in related work [79] . In particular , we can use the marginal likelihood by gene to perform posterior inference instead of the marginal likelihood by cluster . This approach changes the model in that we now have separate estimates of the mean function for a cluster based on each gene , with those mean functions being drawn from a cluster-specific shared GP prior , as we make explicit in the generative model above . We refer to this version of inference for the DPGP as fDPGP . This marginalized approach reduces the complexity of the matrix inversion from O ( ( MT ) 3 ) for DPGP to O ( M3 ) for fDPGP for M genes and T time points . Note that in our application to the H . salinarum and dex exposure data we use fDPGP to scale to the data . Our MCMC approach produces a sequence of states drawn from a Gibbs sampler , where each state captures a partition of genes into disjoint clusters . In DPGP , we allow several choices for summarizing results from the Markov chain . Here , we take the maximum a posteriori ( MAP ) clustering , or the partition that produces the maximum value of the posterior probability . We also summarize the information contained in the Gibbs samples into a posterior similarity matrix ( PSM ) , S , of dimension P × P , for P genes , where S[j , j′] = the proportion of Gibbs samples for which a pair of genes j , j′ are in the same partition , i . e . , 1Q∑q=1Q1[cjq=cj′q] , for Q samples and cjq representing the cluster assignment of gene j in iteration q . This PSM avoids the problem of label switching by being agnostic to the cluster labels when checking for equality . In order to test our algorithm across a wide variety of possible data sets , we formulated more than twenty generative models with different numbers of clusters ( 10–100 ) and with different generative covariance parameters ( signal variance 0 . 5–3 , marginal variance 0 . 01–1 , and length scale 0 . 5–3 ) . We varied cluster number ( data sets 1–5 ) and covariance parameters both across models and within models . For each model , we generated 20 data sets to ensure that results were robust to sampling . We simulated 620 data sets with Gaussian-distributed error and 500 data sets with t-distributed error for testing . To generate each data set , we specified the total number of clusters and the number of genes in each cluster . For each cluster , we drew the cluster’s mean expression from a multivariate normal ( or multivariate t-distribution ) with mean zero and covariance equivalent to a squared-exponential kernel with prespecified hyperparameter settings , then drew a number of samples ( gene trajectories ) from a multivariate normal ( or multivariate t-distribution ) with this expression trajectory as mean and the posterior covariance kernel as covariance . We compared results of DPGP applied to these simulated data sets against results from six state-of-the-art methods , including two popular correlation-based methods and four model-based methods that use a finite GMM , infinite GMM , GPs , and spline functions . Hierarchical clustering and k-means clustering were parameterized to return the true number of clusters . All of the above algorithms , including our own , were run with default arguments . The only exception was GIMM , which was run by specifying “complete linkage” , so that the number of clusters could be chosen automatically by cutting the returned hierarchical tree at distance 1 . 0 , as in “Auto” IMM clustering [21] . We evaluated the accuracy of each approach using ARI . To compute ARI , let a equal the number of pairs of co-clustered elements that are in the same true class , b the number of pairs of elements in different clusters that are in different true classes , and N the total number of elements clustered: RI=a+b ( N2 ) ( 16 ) ARI=RI-E[RI]max ( RI ) -E[RI] ( 17 ) For a derivation of the expectation of RI above , see [32] . Gene expression microarray data from our previous study [30] ( GEO accession GSE33980 ) were clustered using DPGP . In the experiment , H . salinarum control and ΔrosR TF deletion strains were grown under standard conditions ( rich medium , 37°C , 225 r . p . m . shaking ) until mid-logarithmic phase . Expression levels of all 2 , 400 genes in the H . salinarum genome [81] were measured in biological duplicate , each with 12 technical replicate measurements , immediately prior to addition of 25 mM H2O2 and at 10 , 20 , 40 , 60 , and 80 min after addition . Mean expression across replicates was standardized to zero mean and unit variance across all time points and strains . Standardized expression trajectories of 616 non-redundant genes previously identified as differentially expressed in response to H2O2 [30] were then clustered using DPGP with default arguments , except that the σn2 hyperprior parameters were set to αIG = 6 and βIG = 2 to allow modeling of increased noise in microarray data relative to RNA-seq . Gene trajectories for each of the control and ΔrosR strains were clustered in independent DPGP modeling runs . Resultant clusters were analyzed to determine how each gene changed cluster membership in response to the rosR mutation . We computed the Pearson correlation coefficient in mean trajectory between all control clusters and all ΔrosR clusters . Clusters with the highest coefficients across conditions were considered equivalent across strains ( e . g . , control cluster 1 versus ΔrosR cluster 1 , ρ = 0 . 886 in Fig 2 ) . Significance of overrepresentation in cluster switching ( e . g . , from control cluster 1 to ΔrosR cluster 2 ) was tested using FET . To determine the degree of correspondence between DPGP results and previous clustering results with the same data , we took the intersection of the list of 372 genes that changed cluster membership according to DPGP with genes in each of eight clusters previously detected using k-means [30] . Significance of overlap between gene lists was calculated using FET . A549 cells were cultured and exposed to the GC dex or a paired vehicle ethanol ( EtOH ) control as in previous work [42] with triplicates for each treatment and time point . Total RNA was harvested using the Qiagen RNeasy miniprep kit , including on column DNase steps , according to the manufacturer’s protocol . RNA quality was evaluated using the Agilent Tape station and all samples had a RNA integrity number > 9 . Stranded Poly-A+ RNA-seq libraries were generated on an Apollo 324 liquid handling platform using the Wafergen poly-A RNA purification and RNA-seq kits according to manufacturer instructions . The resulting libraries were then pooled in equimolar ratios and sequenced on two lanes 50 bp single-end lanes on an Illumina HiSeq 2000 . Data are available at GEO under study accession GSE104714 . RNA-seq reads were mapped to GENCODE ( v . 19 ) transcripts using Bowtie ( v . 0 . 12 . 9 ) [82] and quantified using samtools idxstats utility ( v . 1 . 3 . 1 ) [83] . Differentially expressed ( DE ) transcripts were identified in each time point separately using DESeq2 ( v . 1 . 6 . 3 ) [84] with default arguments and FDR ≤10% . We clustered only one transcript per gene , in particular , the transcript with the greatest differential expression over the time course among all transcripts for a given gene model , using Fisher’s method of combined p-values across time points . Further , we only clustered transcripts that were differentially expressed for at least two consecutive time points , similar to the approach of previous studies [7 , 85] . We standardized all gene expression trajectories to have zero mean and unit variance across time points . We clustered transcripts with DPGP with default arguments . To query the function of our gene expression clusters , we annotated all transcripts tested for differential expression with their associated biological process Gene Ontology slim ( GO-slim ) [51] terms and performed functional enrichment analysis using FET with FDR correction [86] as implemented in GOAtools [87] . We considered results significant with FDR ≤ 5% . We compared DPGP clusters in terms of TF binding and histone modification occupancy as assayed by ChIP-seq ( S5 Table ) . For each of the ENCODE BAM files whose root names are listed in S5 Table , we tallied read counts in flanking regions of the transcription start site ( TSS ) of the gene from which each transcript derived . Flanking regions were split into the following bins: within 1 kb of the TSS , 1–5 kb from the TSS , and 5–20 kb from the TSS; reads were quantified in those bins using the software featureCounts ( v . 1 . 4 . 6 ) [88] . For data sets in which two replicates were available , we merged mapped reads across replicates . We normalized counts by the total number of mapped reads . TF binding tends to be correlated ( in enhancers and promoters , for example ) , as does histone modification occupancy . In order to determine the features relevant to the prediction of cluster membership , we chose to apply elastic net logistic regression , which combines lasso ( ℓ1 ) and ridge ( ℓ2 ) penalties . Elastic net tends to shrink to zero the coefficients of groups of correlated predictors that have little predictive power [59] . We ran regression models to predict cluster membership from log10 normalized counts of TF binding and histone modifications in control conditions ( 2% EtOH by volume and untreated ) and , separately , from log10 fold-change in normalized TF binding from 2% EtOH by volume to 100 nM dex conditions . We used stochastic gradient descent as implemented in SciKitLearn [80] to efficiently estimate the parameters of our model . We searched for optimal values for the ℓ1/ℓ2 ratio and the regularization multiplier ( λ ) by fitting our model with 5-fold stratified cross-validation across a grid of possible values for both variables ( ℓ1/ℓ2 ∈ {0 . 5 , 0 . 75 , 0 . 9 , 0 . 95 , 1} , λ ∈ {10−6 , 10−5 , 10−4 , 10−3 , 10−2 , 1} ) . We selected the sparsest model ( least number of non-zero coefficients ) with mean log-loss within one standard error of the mean log loss of the best performing model [89] . We performed principal components analysis ( as implemented in SciKitLearn [80] ) on the standardized log10 library size-normalized binned counts of TF binding and histone modifications in control conditions only for the observations that corresponded to transcripts in the four largest DPGP clusters . | Transcriptome-wide measurement of gene expression dynamics can reveal regulatory mechanisms that control how cells respond to changes in the environment . Such measurements may identify hundreds to thousands of responsive genes . Clustering genes with similar dynamics reveals a smaller set of response types that can then be explored and analyzed for distinct functions . Two challenges in clustering time series gene expression data are selecting the number of clusters and modeling dependencies in gene expression levels between time points . We present a methodology , DPGP , in which a Dirichlet process clusters the trajectories of gene expression levels across time , where the trajectories are modeled using a Gaussian process . We demonstrate the performance of DPGP compared to state-of-the-art time series clustering methods across a variety of simulated data . We apply DPGP to published microbial expression data and find that it recapitulates known expression regulation with minimal user input . We then use DPGP to identify novel human gene expression responses to the widely-prescribed synthetic glucocorticoid hormone dexamethasone . We find distinct clusters of responsive transcripts that are validated by considering between-cluster differences in transcription factor binding and histone modifications . These results demonstrate that DPGP can be used for exploratory data analysis of gene expression time series to reveal novel insights into biomedically important gene regulatory processes . | [
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"... | 2018 | Clustering gene expression time series data using an infinite Gaussian process mixture model |
Elevated blood CXCL10/IP-10 levels during primary HIV-1 infection ( PHI ) were described as an independent marker of rapid disease onset , more robust than peak viremia or CD4 cell nadir . IP-10 enhances the recruitment of CXCR3+ cells , which include major HIV-target cells , raising the question if it promotes the establishment of viral reservoirs . We analyzed data from four cohorts of HIV+ patients , allowing us to study IP-10 levels before infection ( Amsterdam cohort ) , as well as during controlled and uncontrolled viremia ( ANRS cohorts ) . We also addressed IP-10 expression levels with regards to lymphoid tissues ( LT ) and blood viral reservoirs in patients and non-human primates . Pre-existing elevated IP-10 levels but not sCD63 associated with rapid CD4 T-cell loss upon HIV-1 infection . During PHI , IP-10 levels and to a lesser level IL-18 correlated with cell-associated HIV DNA , while 26 other inflammatory soluble markers did not . IP-10 levels tended to differ between HIV controllers with detectable and undetectable viremia . IP-10 was increased in SIV-exposed aviremic macaques with detectable SIV DNA in tissues . IP-10 mRNA was produced at higher levels in the small intestine than in colon or rectum . Jejunal IP-10+ cells corresponded to numerous small and round CD68neg cells as well as to macrophages . Blood IP-10 response negatively correlated with RORC ( Th17 marker ) gene expression in the small intestine . CXCR3 expression was higher on memory CD4+ T cells than any other immune cells . CD4 T cells from chronically infected animals expressed extremely high levels of intra-cellular CXCR3 suggesting internalization after ligand recognition . Elevated systemic IP-10 levels before infection associated with rapid disease progression . Systemic IP-10 during PHI correlated with HIV DNA . IP-10 production was regionalized in the intestine during early SIV infection and CD68+ and CD68neg haematopoietic cells in the small intestine appeared to be the major source of IP-10 .
Chronic immune activation is a hallmark of HIV infection [1] . Effective combined-antiretroviral therapy ( cART ) reduces HIV viremia to undetectable levels , but milder chronic immune activation nonetheless persists and is associated with onset of both AIDS and non-AIDS illnesses [2 , 3] . The mechanisms fuelling chronic inflammation in HIV infection are poorly understood and probably multifactorial . Translocation of microbial products from the gastrointestinal tract may be an important driving factor [4–6 , 7 , 8] . Studies of SIV+ non-human primates ( NHP ) such as Asian macaques ( MAC ) and natural hosts of SIV such as African green monkeys ( AGM ) support a role of immune activation and microbial translocation in HIV pathogenesis [1 , 5 , 6 , 7 , 8–15] . SIV infection in natural hosts is characterized by high viral load but does not result in chronic inflammation [1 , 15 , 16] . Strong inflammatory responses are only transient in natural hosts and by the end of the primary phase of infection , they are dampened to pre-infection levels [1 , 9–15] . We thus asked whether HIV-infected individuals with only weak inflammation near the end of primary HIV infection ( PHI ) have better outcomes [17] . High inflammation level at Fiebig stages III and IV of PHI was indeed associated with rapid loss of CD4+ T-cells . Among 28 pro-inflammatory factors tested , CXCL10/IP-10 was a strong and independent predictive marker of rapid CD4+ T-cell loss [17] . During PHI , IP-10 was even a more robust predictive marker than viremia or the CD4+ T-cell nadir . Many cells can produce and release IP-10 [18] . During HIV-1 infection , circulating myeloid cells are the main source of IP-10 in blood [19] . In secondary lymphoid organs from SIV+ macaques , IP-10 is mainly produced by CD3+ T-cells , but also by CD14+ and CD3-CD14- cells [18 , 20 , 21] . IP-10 is a pro-inflammatory chemokine and a ligand of CXCR3 . As CXCR3+ CD4+ T-cells are the main cellular targets of HIV [22 , 23] , it is conceivable that IP-10 enhances the trafficking of HIV target cells to lymphoid tissues , thereby promoting new rounds of infection and helping to establish viral reservoirs [24] . Here we attempted to gain further insights into the role of IP-10 during HIV-induced inflammation and its relationship with the levels of infected cells .
We raise the hypothesis that IP-10 attracts target cells for HIV . First , we tested if IP-10 pre-infection levels impact on infection outcome . We quantified IP-10 in blood from 136 patients before HIV infection , during PHI , 3 months ( M3 ) after seroconversion ( SC ) and/or 6 months ( M6 ) after SC in the Amsterdam cohort ( ACS ) ( characteristics described in Table A in S1 Text ) . Plasma IP-10 levels were higher during PHI ( p<0 . 05 ) than before infection , and remained elevated at M3 and M6 , albeit at lower levels ( p<0 . 01 ) ( Fig 1A ) . Similar IP-10 profiles were observed in the subset of 16 patients from whom samples were available at every time point ( Fig 1B ) . IP-10 levels correlated negatively with the CD4 T-cells count [r = -0 . 19 ( p = 0 . 04 ) and r = -0 . 39 ( p<0 . 001 ) at M3 and M6 , respectively] , and positively with viremia in PHI ( Fig 1C ) , at M3 ( Fig 1D ) . Strikingly , elevated IP-10 levels before infection were associated with rapid progression ( OR = 3 . 24 p = 0 . 01 ) ( Table B in S1 Text ) , CD4+ T-cell counts falling below 350/mm3 more rapidly in individuals with pre-infection IP-10 levels above the median ( Fig 1E ) . In contrast , CD4 T-cell counts before infection had no impact on the rate of progression . Of note , only IP-10 levels measured less than 24 months before infection had such an impact: IP-10 levels measured between 24 and 60 months before infection did not influence the rate of CD4 T-cells loss . IP-10 concentrations in blood before infection were not correlated to canonical immune activation markers ( Table C in S1 Text ) . Elevated IP-10 levels at M3 post-SC were also associated with rapid CD4+ T-cell decline to below 350/mm3 ( Fig 1F ) and with an increased risk of rapid progression toward AIDS ( OR = 2 . 54 p = 0 . 02 ) before any treatment ( Table B in S1 Text ) . However , at M3 , the CD4 T-cell count was a more robust predictor of rapid progression than were IP-10 levels , while both the IP-10 level and the CD4 T-cell counts were more robust predictors than viremia ( Table B in S1 Text ) . In order to compare the robustness of IP-10 in predicting rapid disease onset to other systemic markers of HIV-induced immune activation , we also measured soluble CD163 ( sCD163 ) , a monocyte-macrophage activation marker associated with disease progression in HIV+ individuals [25 , 26] . sCD163 concentrations in blood were strongly correlated to IP-10 concentrations at all times studied here ( Fig 2 ) . However , sCD163 concentrations before and after infection failed to be associated with rapid disease progression ( Table B in S1 Text ) , in contrast to IP-10 . Thus , by analyzing the time course of IP-10 levels , starting before infection , we found that they rose markedly upon HIV infection . Strikingly , pre-existing elevated IP-10 levels were associated with rapid CD4 T-cells loss upon HIV-1 acquisition . To further test the hypothesis that IP-10 , by promoting CXCR3+ cell trafficking , attracts HIV target cells and thereby increases the number of infected cells , we examined the relationship between the IP-10 level and the number of infected cells . We measured cell-associated total viral DNA in order to include both latently infected cells and cells supporting active viral replication . These HIV DNA levels in PBMC from 134 subjects with PHI from the ANRS PRIMO cohort have previously been reported [17] . IP-10 levels strongly correlated with cell-associated HIV-1 DNA ( Fig 3 ) . We also compared the levels of 27 additional inflammatory molecules with the amount of infected cells in the same patients . These markers had been previously analyzed [17] . Among the 27 markers , only IL-18 also positively correlated with total HIV DNA in PBMC ( r = 0 . 3 p = 0 . 045; Table D in S1 Text ) , but to a lesser extent than IP-10 ( r = 0 . 35 p<0 . 0001 , Fig 3B ) . RANTES was the only factor , which had a negative association with total HIV DNA ( r = -0 . 4 p = 0 . 007; Table D in S1 Text ) . Altogether Blood IP-10 levels positively correlate with cell-associated viral DNA during in PHI . We then examined IP-10 levels in various groups of patients with controlled viremia ( Fig 4A and 4B ) . We first studied HIV controllers ( n = 82 ) , divided into two groups: individuals with strong viral control at the time of IP-10 assay ( <50 copies of viral RNA/ml ) and individuals displaying a moderate viral “blip” at this time point ( >50 copies ) . IP-10 levels in all 82 controllers together were similar to those in the patients on successful cART . However , IP-10 levels tended to be lower in the HIV controllers with <50 copies/ml than in the HIV controllers with >50 copies/ml and cART-treated patients . Next , we evaluated IP-10 before and during cART ( n = 41 ) ( Table E in S1 Text ) . IP-10 levels fell significantly during cART as compared to pre-treatment levels , but remained higher than in uninfected controls ( Fig 4A ) . Before treatment , IP-10 levels correlated positively with viremia ( r = 0 . 32 p<0 . 001 ) and negatively with the CD4 T-cell counts ( r = -0 . 26 p = 0 . 003 ) . During cART , IP-10 levels correlated negatively with the CD4 T-cell counts ( Fig 4C ) , as strongly as in viremic patients . The recent TEMPRANO and START trials demonstrated that AIDS and non-AIDS events can occur even in patients with high CD4 counts ( >500/mm3 ) [27] . When we considered only patients with CD4 T-cells counts above 500/mm3 , there was still a trend towards a negative correlation between IP-10 and CD4 T-cell counts ( Fig 4D ) . To further determine the relationship between IP-10 and viral replication in a context of viral control , we quantified IP-10 in SIVmac-exposed aviremic macaques . We chose a non-human primate model because it allowed us to investigate viral load in tissues . We studied 34 MAC exposed to moderate doses of SIVmac251 . Twenty-seven MAC displayed an expected viremic phenotype . From 3 of these viremic animals , we FACS-sorted the LN cells into four subsets: CD4+ and CD4- T cells expressing or not CXCR3 ( Figure A in S1 Text ) . The viral DNA copy numbers in CD4+ LN cells were high as expected ( Figure A in S1 Text ) . No significant difference could be observed between CXCR3+ and CXCR3neg CD4+ T cells . The samples that were positive for viral DNA were also those positive for IP-10 gene expression ( Figure A in S1 Text ) . Surprisingly , 7 of these 34 animals remained aviremic ( < 12 copies of SIVmac RNA/ml ) during the chronic phase of infection ( follow up until 1 year p . i . ) , despite the fact that the viral doses used resulted in 100% of infection in previous experiments [28] . None of the aviremic animals seroconverted during follow-up . We quantified total SIV DNA in total LN cells from the SIV-exposed aviremic macaques . PCR amplification of cell-associated DNA on total LN cells was negative in 5 of the 7 aviremic animals , while positive ( 4–35 copies/106 cells ) in 2 animals ( AX414 and 30845 ) on day 14 p . i . We then compared plasma IP-10 dynamics in three groups of animals ( viremic , aviremic with or without detectable viral DNA in tissues ) . IP-10 levels were elevated in viremic animals , as expected ( Fig 5A ) . Viremia and IP-10 levels correlated positively with one another ( r = 0 . 69 , p<0 . 0001 ) . In the 5 aviremic animals with no detectable viral DNA in tissues ( LN ) , IP-10 levels remained low during primary infection ( Fig 5B ) . In contrast , IP-10 levels increased in the 2 animals ( AX414 and 30845 ) with detectable SIV DNA during primary infection ( Fig 5B ) . We then compared levels in the aviremic animals with those in 3 MAC in which cART was initiated 4 h after infectious challenge [29] . The animals were treated until day 14 p . i . and then sacrificed . None of these animals had detectable viral DNA in lymphoid tissues during follow-up [29] . These cART-treated animals displayed a weaker induction of IP-10 during follow-up as compared to viremic animals ( Fig 5C ) . Together , these observations support a strong association between blood IP-10 levels and active viral reservoirs in lymphoid tissues . Since IP-10 triggers the trafficking of cells expressing its ligand , CXCR3 , we sought to address the dynamics of CXCR3+ CD4+ T cells in vivo in parallel to the IP-10 response upon SIV infection . We first determined the levels of CXCR3 expression by flow cytometry on distinct haematopoietic cells in blood before SIV infection in rhesus macaques and AGMs . Strikingly , CXCR3 was mostly expressed on CD4+ T cells when compared to other immune cells ( Fig 6A ) . CXCR3 expression was also significantly higher on CD4+ T cells than on CD8+ T cells . We then assessed the dynamics of CXCR3+ within the naïve ( CD28+ CD95neg ) and memory ( CD28+CD95+ and CD28-CD95+ ) CD4+ T cells in LN . This memory cell fraction typically contains the vast majority central memory CD4+ T cells . We found that the frequency of CXCR3+ cells was higher within the memory subset than within naïve CD4+ T cells . Both in macaques and AGM , these cell subsets quickly exhibited changes in their frequencies upon infection ( Fig 6C and 6D ) . The frequencies of CXCR3+CD4+ T cells tended to increase at day 2 p . i . in macaques ( p = 0 . 0625 ) . In the contrary , AGMs exhibited decreased frequencies of CXCR3-expressing cells in memory CD4+ T cells at days 2 and 9 p . i . ( p = 0 . 0313 ) ( Fig 6C and 6D ) . All AGMs and one macaque displayed a peak of IP-10 at days 2 and 9 p . i . ( Fig 6B ) . We therefore wondered whether decreases in CXCR3 expression could be related to internalization of the receptor as described for the IL-7R in HIV/SIV infections [30] . To address this hypothesis we evaluated the rate of CXCR3 internalization in LN CD4 T cells from 3 SIVmac-infected macaques and 3 SIVagm-infected AGMs ( Fig 6E and 6F ) . In both species , we observed in the infected animals high proportion of LN CD4 T cells having internalized CXCR3 . The levels of CXCR3 in the permeabilized cells varied between 72 and 92% in macaques and between 45 and 60% in AGMs . Altogether , CXCR3 was mostly expressed on CD4+ T cells when compared to other immune cells and within CD4+ T cells , more frequently expressed on memory than on naïve cells . Modulations in the frequencies of CXCR3+ CD4+ T cells were observed upon infection . Significant decreases might in part be explained by internalization of the CXCR3 receptor in response to the increased production of its ligands ( IP-10 or other CXCR3 ligands ) during infection . To determine the origin of IP-10 in blood , we measured IP-10 expression in the largest lymphoid tissue: the intestine . The latter is also the largest site of HIV/SIV replication . We analyzed intestinal IP-10 production in 5 SIVmac-infected rhesus macaques . We also compared the IP-10 expression pattern in a non-pathogenic model ( 5 SIVagm-infected AGMs ) . AGMs were used because they are known to display a high level of viral replication in the gut , in the absence of chronic inflammation [7 , 31] . Furthermore , as the intestine is regionalized into several sections with specific functions [32] , and as we found higher infection rate of the small intestine than in the large intestine in SIVmac-infected cynomolgus macaques ( Figure B in S1 Text ) , we analyzed the IP-10 gene expression in 4 distinct sections , i . e . jejunum , ileum , colon and rectum . During SIVmac infection , IP-10 was strongly expressed by CD4+ cells in the small intestine ( jejunum/ileum ) ( Fig 7A ) , and more strongly than by CD4- cells in the small intestine or both CD4+ and CD4- cells in the large intestine . No such regionalization of IP-10 was seen in AGMs . Likewise , CXCR3 expression was the strongest in CD4+ cells of the small intestine during SIVmac infection , whereas this profile was not observed in AGMs ( Fig 7B ) . IP-10 expression correlated with CXCR3 expression ( r = 0 . 66 , p = 0 . 0009 ) . IP-10 expression levels in CD4+ cells of the small intestine correlated with plasma levels when the two species were grouped for analysis ( Fig 7C ) . When we considered only MAC , which reduced the statistical power , there still was a trend towards a positive correlation ( Fig 7C ) . No such correlation was found in the colon/rectum . Thus , the strongest IP-10 expression was detected in the CD4+ fraction in the small intestine in SIVmac-infected macaques . Moreover , IP-10 levels in plasma tended to correlate with those in the small intestine . We then sought to determine which CD4+ cell subset was responsible for elevated IP-10 expression in the small intestine . It has been described that IP-10 is produced by monocytes and macrophages during HIV/SIVmac infection [19 , 33–35] . We therefore quantified the expression of genes associated with macrophages ( CD14 , CD68 and CD163 ) in the same samples as those analyzed above for IP-10 mRNA . All three macrophage markers ( CD14 , CD68 and CD163 ) were more strongly expressed in small-intestinal CD4+ leukocytes from MAC than from AGM , or in any other gut section from MAC ( Fig 7D–7F ) . IP-10 expression levels correlated strongly with these gene expression levels ( Fig 7G–7I ) . To address whether IP-10 is produced at the protein level in gut macrophages , we performed immunohistochemistral stainings in jejunum fragments of macaques harvested at necropsy ( day 240 p . i ) . IP-10 expression was detected throughout the jejunum in cells that had a shape and localization distinct from epithelial/endothelial cells ( Fig 8A ) . We found a massive expression of IP-10 from small and round CD68neg cells , which ressembled in their shape lymphocytes ( Fig 8B ) and to a lesser extent from large CD68+ cells ( Fig 8C ) . Very often CD68+IP-10+ cells were found in clusters at top of villi ( Fig 8D ) . These data demonstrate that IP-10+ is produced by macrophages in the jejunum . However many smaller , CD68neg cells produced IP-10 as well . To further analyze the link between IP-10 , macrophages and intestinal inflammation , we quantified the expression of ISGs such as MX1 and IFI30 . IP-10 expression was positively correlated to MX1 and IFI30 gene expression . ( Figure C in S1 Text ) . Although these ISGs were also correlated with the macrophage markers , these correlations were less robust than with IP-10 ( Figure C in S1 Text ) . During HIV-1/SIVmac infections , mucosal immunity in the intestine is generally gradually impaired , notably with a characteristic loss of Th17 cells , which is absent in natural hosts of SIV [5 , 36 , 37] . As a read-out for gut damage , we quantified the expression of RORC , the master transcription factor for Th17 cells , in enriched CD4+ leukocytes from the intestinal sections . We detected stronger RORC expression in CD4+ leukocytes from AGM than MAC ( Fig 7J ) . RORC and IP-10 expressions correlated negatively with one another in small-intestinal CD4+ leukocytes ( r = -0 . 74 , p = 0 . 0034 ) from all the studied NHP . There was also a trend towards a negative correlation when we considered only MAC ( Fig 7K ) . A negative correlation between RORC in the small intestine and plasma IP-10 ( Fig 7L ) was observed . Pathogenic SIVmac infection is characterized by a skewed Th response towards a Th1 phenotype in the gut at the detriment of Th17 cells , in contrast to natural hosts [38–40] . To determine if this negative correlation between IP-10 and RORC were associated with a particular profile of Th differentiation in the analyzed CD4+ cell population , we went on evaluating the IP-10 expression in Th subsets . We sorted circulating primary human Th subsets . We observed that primary human circulating Th17 cells are devoid of a strong IP-10 gene expression in sharp contrast to primary Th1-like cells which express the highest levels of transcriptional IP-10 gene activity ( Figure D in S1 Text ) . Altogether these data indicate that IP-10 is associated with inflammation in the small intestine and suggest a negative association between the levels of IP-10 and Th17 cells .
Here , we studied the relevance of IP-10 as a marker of disease progression before infection , and examined why IP-10 is so strongly associated with HIV pathogenesis . We found that pre-existing elevated IP-10 levels were associated with an increased risk of rapid CD4+T-cells loss upon HIV infection in the ACS . Elevated levels of IP-10 prior to infection may be multifactorial: ( i ) resulting from co-infections with viruses although we excluded co-infections with HIV-2 , HBV and HCV but we couldn’t exclude a co-infection with TB [41] . Indeed this latter report showed that during reactivation of latent TB infection IP-10 is found at elevated concentrations in blood . We couldn’t completely rule out ( ii ) elevated immune activation [42] . However , when we analyzed additional immune activation/inflammation markers , such as Ki-67 , CD8+DR+CD38+ , CD8+CD70+ , CD4+DR+CD38+ , CD4+CD70+ , before infection , we couldn’t see any significant impact of such markers on the rate of CD4+ T cells upon HIV-infection and none of them were significantly correlated to IP-10 pre-infection levels in blood ( Table C in S1 Text ) . The caveat was the very low number of patients with documented immune activation markers before infection . In addition , we analyzed sCD163 levels . They were significantly correlated to those of IP-10 but sCD163 levels failed to predict rapid disease onset in contrast to IP-10 pre-infection levels . Lower IP-10 levels had been reported in the genital mucosa of highly HIV-exposed-seronegative women than in HIV-seronegative and -seropositive women [43 , 44] . Blood IP-10 levels were recently reported to be higher in transmitting HIV-1–infected individuals and in their HIV-1–seroconverting partners than in HIV-1–infected and uninfected partners [45] . This suggested that elevated IP-10 increased the risk of HIV-1 acquisition . It is possible that this increased risk of HIV-1 acquisition , and the more rapid CD4+ T-cells loss observed here in individuals with higher IP-10 levels before infection , is due to IP-10 enhancement of the infection . We indeed found a strong correlation between IP-10 and the amount of cell-associated HIV DNA . Recently we have analyzed plasma IP-10 levels in the ANRS OPTIPRIM study , where patients received mega-ART therapy starting from PHI [46] . IP-10 , but not IL-6 , sCD14 nor sCD163 was positively correlated with blood HIV-DNA at inclusion ( r = 0 . 53 , p = 0 . 018 ) and only IP-10 levels among 5 inflammatory markers assessed in plasma correlated with total HIV DNA in semen ( A . Cheret , personal communication ) . In our animal models , IP-10 levels helped to discriminate between SIV-exposed aviremic animals with and without detectable tissue infection . Several studies have shown that elevated IP-10 levels contribute to excessive recruitment of CXCR3+ T-cells into lymphoid tissues during pathogenic SIVmac infection [47 , 48] . This was also described in important sites of viral entry , notably the foreskin of sexually active men with a high risk of acquiring HIV [49] . CXCR3 expression is highest in activated memory CD4+ T-cells [22] . It is possible that IP-10 attracts not only CXCR3+ immune cells with potential antiviral activity but also major HIV target cells , indirectly enhancing viral dissemination and the establishment of viral reservoirs . Recent studies have shown a high infection rate among CXCR3+ CD4+ T-cells [22] , which are also preferentially enriched for HIV DNA in HIV-infected individuals on cART [23] . IP-10 has also been shown to enhance the susceptibility of resting naïve CD4 T-cells to HIV infection [50] . Here we observed distinct dynamics of CXCR3+ CD4 T cells on LN from SIV-infected macaques and natural hosts . These increased frequencies of CXCR3+ memory CD4 T cells in macaque LN versus reduced frequencies of CXCR3+ memory CD4 T cells in AGM LN during the acute phase of infection may be due to mobilization of these cells in the context of a strong pro-inflammatory context ( CXCR3-ligands ) in macaques . We could not see such dramatic increases in AGM and we can’t exclude that the CXCR3 was either internalized or that the CXCR3+ memory CD4+ T cells are migrating to another tissue in natural hosts . In macaques , we didn’t detect a higher rate of infection in CXCR3+ versus CXCR3neg CD4+ cells . As CXCR3 might be dramatically internalized upon recognition of its ligands during infection ( Fig 6E and 6F ) , the interpretation of the viral distribution in the context of increased production of IP-10 ( and other CXCR3 ligands ) in vivo is complex . More animals and more studies need to be done at critical time points and in animals with distinct levels of CXCR3 ligands . Though , when we looked at the intestinal mucosa , we found a significant higher rate of infection in the small intestine where the expression of IP-10 and CXCR3 were the highest . Overall , our findings further demonstrate that elevated IP-10 levels are a strong predictive marker of disease progression but raise the question whether it might , directly and/or indirectly , also promote the establishment of viral reservoirs . Our data in animals suggest that IP-10 in plasma derives in large part from the gut , the largest lymphoid tissue . Unexpectedly , the IP-10 response was regionalized in macaques , being higher in the small intestine than the large intestine . CXCR3 expression showed the same regionalization . Previous studies have shown marked regional variations in the abundance of infected cells in the gut , but most focused on specific compartments and not the entire gut [51 , 52] . In cART-treated patients , the small intestine also seems to harbor more active viral reservoirs than the periphery or the rectum [53 , 54] . Here we also observed a higher infection rate in the small intestine than in the large intestine , correlating with the IP-10/CXCR3 regionalized expression . Further , IP-10 mRNA expression in MAC small intestine positively and strongly correlated with the expression of macrophage-associated markers ( CD14 , CD68 and CD163 mRNA ) . This association can have several explanations . It might have an indirect cause as both IP-10 and macrophage levels in the gut might be the consequence of higher inflammation . It might also be explained by a higher number of macrophages in the gut or finally by an increase in production of IP-10 in the gut . IP-10 levels correlate with expression of the activation markers CD11b and CD38 on monocytes [55] . In the latter report , the sCD14 levels did not correlate with any of these molecules . The same authors suggest that IP-10 , but not sCD14 , is a robust and easier tool to measure monocyte activation [55] . Further , an accumulation of CD68+ and CD163+ macrophages in the duodenal mucosa of HIV-infected patients was reported in parallel to increased levels of pro-inflammatory molecules such as IP-10 [20] . By studying patients in the COPANA cohort , we found that plasma IP-10 correlated with the concentrations of monocytic activation markers sCD163 ( r = 0 . 57 p<0 . 001 ) , sCD14 ( r = 0 . 35 p = 0 . 008 ) and TFN-α ( r = 0 . 43 p<0 . 001 ) , but not with CRP , IL-6 , MCP1 , sTNFR1 or sTNFR2 ( Figure E in S1 Text ) . Infiltration of the small intestine ( duodenum ) of HIV-infected individuals by inflammatory CD68+/CD163+ macrophages has been reported in HIV+ individuals in absence of cART [20] . Thus , elevated IP-10 production in the small intestine might derive from infiltrating activated macrophages during progressive HIV/SIV infections . The IP-10 , CD14 , CD68 and CD163 gene expression in the small intestine of SIVmac-infected rhesus macaques seem to be in line with these observations in HIV+ individuals . We show here that macrophages are indeed one important source of IP-10 production in the jejunum SIV-infected rhesus macaques ( Fig 7 ) . This is consistent with previous reports in humans . During acute HIV-1 infection , IP-10 production in blood was found to be associated with circulating myeloid cells [19] . However , many other cells produced IP-10 as well , consistent with data in lymph nodes [18 , 20 , 21] . Indeed , IP-10 was also more often confined to CD68neg small and rounded-shape cells ( Fig 8 ) . These might include predominantly CD4+ lymphocytes since IP-10 mRNA expression levels where highest in the CD4+ cell fraction . However , we cannot exclude differences in the profiles of mRNA and cellular sources due to fact that the PCR and IHC analyses were performed in distinct animals and distinct time points ( Day 65 p . i and D240 p . i . , respectively ) . Finally IP-10 increases might result from both increases in cell numbers as well as from intra-cellular upregulations . Altogether , we determined the cellular source of IP-10 and demonstrate a regionalization of IP-10 production in the gut . The small intestine in particular is remarkably enriched in IL-17 producing T cells [56] . A gradient of T-cell IL-17 production has indeed been reported along the intestinal tract , with the small intestine being enriched in such lymphocytes [56] . We found that IP-10 levels in both blood and the small intestine correlated negatively with the presence of Th17 in the small intestine , suggesting that blood IP-10 levels mirror the extent of gut damage . RORC expression in the small intestine was stronger in AGMs than in MAC , which supports the relevance of our model . We found that IP-10 mRNA expression in MAC small intestine negatively correlated with the presence of gut Th17 cells ( Fig 7 ) . IP-10 expression might be indirectly associated to intestinal inflammation and gut damage . Our observations from primary human Th subsets clearly confirm a confinement of IP-10 gene expression in genuine Th1 cells rather than Th17 . Thus the negative correlation between IP-10 and RORC in our study could be due to the biased Th1 response at the detriment of Th17 response , which has been described in pathogenic SIVmac infection in contrast to natural hosts of SIVs [38–40] . Persistently moderate IP-10 levels were observed in HIC , as reported elsewhere [57 , 58] . IP-10 seems to distinguish between HIC who experience viral blips ( Fig 3B ) and rapid loss of CD4+ T-cells [57 , 58] , and could prove useful for identifying those patients with controlled viremia , including HIC , who need therapeutic interventions to further delay disease progression . In summary , this study of IP-10 in four cohorts of HIV-infected patients and in two non-human primate models provides new information on the tissue source of this pro-inflammatory mediator , reveals its regionalization in gut and indicates an association with the cell infection rate during HIV-1 infection .
Studies were conducted with ethical agreements and with the informed consent of each patient . Patient enrollment respects European guidelines and established guidance promulgated by the World Medical Association in its declaration of Helsinki . All patients were adult subjects . The scientific board of the Amsterdam cohort studies and of the French ANRS cohorts PRIMO C06 , COPANA C09 and CODEX C21 approved this study . Institut Pasteur “Comité de recherché Clinique” CoRC #2013–05 approved this study . Animals were housed in the facilities of the CEA ( “Commissariat à l'Energie Atomique” , Fontenay-aux-Roses , France ) IDMIT facilities ( Center for Infectious Disease Models and Innovative Therapies ) , Fontenay-aux-Roses , France ( permit number A 92-032-02 ) or the Pasteur Institute , Paris , France ( permit number A 78-100-3 ) . All experimental procedures were conducted in strict accordance with the European guideline 2010/63/UE for the protection of animals used for experimentation and other scientific purposes ( French decree 2013–118 ) and with the recommendations of the Weatherall report . The monitoring of the animals was under the supervision of the veterinarians in charge of the animal facilities . All efforts were made to minimize suffering , including efforts to improve housing conditions and to provide enrichment opportunities ( e . g . , 12∶12 light dark schedule , provision of monkey biscuits supplemented with fresh fruit and constant water access , objects to manipulate , interaction with caregivers and research staff ) . All procedures were performed under anesthesia using 10 mg of ketamine per kg body weight . For deeper anesthesia required for lymph node removal a mixture of ketamine and xylazine was used . Paracetamol was given after the procedure . Euthanasia was performed prior to the development of any symptoms of disease ( e . g . , for macaques when the biological markers indicated progression towards disease , such as significant CD4+ T cell decline and increases of viremia ) . Euthanasia was done by IV injection of a lethal dose of pentobarbital . A large serum library derived from cART-naïve patients is available , including pre-infection samples from many patients enrolled in the Amsterdam Cohort Studies ( ACS ) of HIV infection and AIDS . None of the 136 subjects studied here had started antiretroviral therapy when samples were collected . These patients had an estimated date of seroconversion ( SC ) defined as the midpoint between the date of the last visit with a negative HIV test and the first visit with a positive HIV test ( complete or incomplete western blot ) [59] . None of the 136 subjects had started antiretroviral therapy when samples were collected . Patients were categorized as rapid progressors ( RP ) or slow/normal progressors as previously described [17] . Basically , rapid progressors had CD4 T cell counts below 350/ml 12 months post-SC . PHI ( M0 ) was defined by an incomplete WB , with detectable HIV RNA load and/or p24 ( Fiebig stage III/IV ) . Samples collected before infection were obtained at least 3 months before the estimated date of SC . Patients co-infected with other bloodborn pathogens ( HIV-2 , HBV , HCV ) were excluded . The viremic cART-naive subjects ( VIR , n = 121 ) were part of the French ANRS C09 COPANA cohort ( See supplementary materials and Table C in S1 Text ) . A subgroup of 41 patients was submitted to cART ( >24 months on cART and >12 months with VL < 50 copies/mL ) . The HIV controllers ( HIC , n = 82 ) were enrolled in the French ANRS C021 CODEX ( See supplementary materials and Table C in S1 Text ) . The samples collected at PHI M0 ( n = 126 ) and PHI M6 ( n = 35 ) were from subjects enrolled in the French ANRS C06 PRIMO cohort , who are thoroughly described in [17] . The viremic cART-naive subjects ( VIR , n = 121 ) were part of the French ANRS C09 COPANA cohort . The main objective of this ongoing cohort created in 2004 is to prospectively evaluate the impact of HIV infection and ART on morbidity and mortality in recently diagnosed ( <1 year ) HIV-1-infected cART-naive adults in France . The Paris-Cochin Ethics Committee approved the study protocol and all the participants give their written informed consent . Among the 800 patients enrolled in the COPANA cohort , 214 joined the metabolic sub-study [60] . The 121 VIR patients corresponded to patients with available CRP , IL-6 , MCP1 , TNFα , sCD14 , sCD163 , sTNFR1 and TNFR2 values and who initiated cART at enrollment or during follow-up . The 121 VIR patients were enrolled within a median of 6 months ( range 3 . 8–9 . 1 ) after HIV-1 diagnosis . IP-10 was measured at cART initiation . A subgroup of 41 patients on sustained successful cART ( >24 months on cART and >12 months with VL < 50 copies/mL ) was identified . They were enrolled in the COPANA cohort less than 6 months after diagnosis of HIV infection . None of the subjects enrolled in our study received immunosuppressive drugs , IFN therapy or chemotherapy , and none had cancer , autoimmune diseases or HIV-unrelated chronic inflammatory metabolic disorders at enrollment . The HIV controllers ( HIC , n = 82 ) were enrolled in the French ANRS C021 CODEX cohort with their written informed consent . This French multicenter cohort was created in 2009 . To be enrolled , patients had to be diagnosed as HIV-infected for more than 5 years , to remain cART-naive with viremia below 400 copies/ml in five consecutive assays , regardless of their CD4 cell count . After enrollment , some patients started to exhibit viral blips and/or a slight loss of CD4 T cells [57 , 58] . The samples collected at PHI M0 ( n = 126 ) and PHI M6 ( n = 35 ) were from subjects enrolled in the French ANRS C06 PRIMO cohort , who are thoroughly described in [17] . We used plasma leftovers for this study . We used data from the ANRS PRIMO cohort to address the relationship between IP-10 and the amount of infected cells , because viral reservoir size has been extensively studied in these patients from PHI onwards [61–64] . Frozen sera collected on EDTA were obtained from the ACS study , while frozen plasma collected on EDTA was obtained from the ANRS cohorts . EDTA plasma from HIV/HBV/HCV-seronegative individuals ( n = 87 ) were obtained from Etablissement Français du Sang ( EFS , Paris , France ) for research purposes . All animals were housed in the CEA IDMIT facilities ( Center for Infectious Disease Models and Innovative Therapies ) , Fontenay-aux-Roses , France ( permit number A 92-032-02 ) or the Pasteur Institute , Paris , France ( permit number A 78-100-3 ) . All experimental procedures were conducted in strict accordance with the European guideline 2010/63/UE for the protection of animals used for experimentation and other scientific purposes ( French decree 2013–118 ) . CEA complies with Standards for Human Care and Use of Laboratory Animals of the U . S . Office for Laboratory Animal Welfare under OLAW assurance number A5826-01 . The animal experimentation ethics committee approved all experimental protocols ( CETEA-DSV , IDF , France; notification numbers 10-051b and 12–006 ) . Twenty-three ( Chlorocebus sabaeus ) were infected by intravenous inoculation with 250 TCID50 of purified SIVagm . sab92018 [13 , 14 , 15] . Nineteen rhesus macaques ( Macaca mulatta ) and eleven cynomolgus macaques ( Macaca fascicularis ) were infected i . v . with 50 AID50 of an uncloned SIVmac251 isolate ( provided by A . M . Aubertin , Université Louis Pasteur , Strasbourg , France ) . Twenty-nine cynomolgus macaques were inoculated intra-rectally with 5 ( n = 10 ) or 50 AID50 ( n = 13 ) of the same uncloned SIVmac251 isolate . In addition , 3 cynomolgus macaques were treated with AZT ( 4 . 5 mg/kg ) and 3TC ( 2 . 5 mg/kg ) subcutaneously twice daily and oral indinavir ( 60 mg/kg ) twice daily . The treatment was initiated as early as 4 hours post-challenge and continued until day 14 , when the animals were killed . These animals are described in [29] . We used plasma leftovers collected on D9 and D14 . Blood and intestinal samples were obtained from AGM . Blood and lymph node samples were obtained from Cynomolgus macaques . The latter tissues were used for viral load quantification . Blood and intestinal samples were collected from Rhesus macaques , and the tissues were used to measure cellular gene expression . Whole blood collected on EDTA was used to prepare plasma or serum . IP-10 and sCD163 concentrations were determined in stored plasma or sera samples ( −80°C ) by specific enzyme-linked immunosorbent assay , human Quantikine CXCL10 and human CD163 Duoset ( R&D Systems , Minneapolis , Minnesota ) according to the manufacturers' instruction as previously performed . At necropsy ( day 65 post-infection ) , a fragment ( 5/7cm in length ) was collected from each of 4 sections of the intestine ( jejunum , ileon , colon and rectum ) of 5 SIVmac251-infected rhesus macaques and 5 SIVagm . sab92018-infected AGM . The ileum fragment was not collected from 2 rhesus macaques and 2 AGMs . The fragments were enzymatically dissociated in RPMI culture medium ( Life Technologies ) containing collagenase ( Collagenase II-S , Sigma-Aldrich ) and DNAse ( Sigma-Aldrich ) for 1 h with agitation ( 80 rpm ) at 37°C . Total leukocytes were separated from epithelial/endothelial cells through a Percoll gradient . CD4-positive and -negative leukocytes were purified on Miltenyi columns and with a CD4 cell purification kit . Cryopreserved lymph node cell samples were stained with LIVE/DEAD Fixable Aqua Dead Cell Stain Kit ( Thermo Fisher ) , then labeled with anti-CD45-PerCP , anti-CD4 Pacific Blue and anti-CXCR3-PE-Cy7 . Viable CD45+CD4+CXCR3- , CD45+CD4+CXCR3+ , CD45+CD4-CXCR3- and CD45+CD4-CXCR3+ cells were sorted using a FACS Aria cell sorter ( BD Biosciences ) equipped to handle biohazardous material . Human primary Th1 ( CD25neg , CXCR3high , CCR4neg , CCR6neg ) , Th1/Th17 ( CD25neg , CXCR3high , CD161+ , CCR6+ ) , Th17 CD161+ ( CD25neg , CXCR3neg , CD161+ , CCR4+ CCR6+ ) and Th17 ( CD25neg , CXCR3neg , CD161neg , CCR4+ CCR6+ ) were isolated as described [65 , 66] from HIV negative blood cytapheresis . Total RNA was extracted and reverse-transcribed as previously described [15] . qPCR ( Taqman chemistry ) and commercial kits were used to quantify the expression levels of genes of interest ( CXCL10 Rh02788358_m1 , CD14 Rh03648680_s1 , CD68 Hs02836816_g1 , CD163 Hs00174705_m1 ) . The expression of each gene was normalized to that of 18S rRNA , and relative expression levels were calculated using the ΔΔCT method . The relative gene expression levels were determined by using as the internal reference the raw value for each gene in rectal CD4+ leukocytes from one rhesus macaque , allowing direct comparison between each species ( Fig 7A , 7B , 7D–7F and 7J ) . Alternatively , relative expression levels were determined by normalizing each value against the raw value of each gene in CD4+ leukocytes enriched from the rectum of each animal . This reduces inter-individual differences and highlights differences between the small and large intestine ( Fig 7C , 7G–7I , 7K and 7L ) . HIV-1 DNA load in PBMC was measured in the laboratory of Prof . C . Rouzioux [67] . SIV viremia and SIV DNA load in lymphoid tissues were determined as previously described [15 , 28] . The cut-offs for cynomolgus macaques were 12 copies/ml of plasma and 12 copies/million cells , respectively . Fresh jejunum fragments were obtained from SIVmac251-infected cynomolgus macaques within 30 min of necropsy ( Day 240 p . i . ) . These fragments were embedded and snap frozen at optimum cold temperature compound ( OCT ) and 10 μm frozen sections were stained using unconjugated primary antibodies ( CD68 clone KP1 from Santa Cruz , IP-10 clone ab47045 from Abcam ) followed by appropriate secondary antibodies conjugated to Alexa 488 ( green ) , Alexa 568 ( red ) ( Molecular Probes , Eugene , OR ) . Prior to staining , slides were incubated with 100–200 μL of ice cold methanol and 5% acetic acid , allowed to rest at -20°C for 10 min then washed 3 times with PBS . Confocal microscopy acquisition was performed using a Leica TCS SP8 confocal microscope ( Leica Microsystems , Exton , PA ) . Individual optical slices were collected at 512 × 512 pixel resolution . Image J software were used to assign colors to the channels collected . ( See supplementary materials ) | Chronic immune activation is a hallmark of HIV infection and contributes in multiple ways to HIV persistence . Here , we gained insights on the association between a pro-inflammatory chemokine , CXCL10/IP-10 and HIV infection in four cohorts of HIV+ individuals , studied at distinct stages of infection ( before , primary and chronic stage with spontaneous- and treatment-controlled infection ) . We further analyzed pathogenic and non-pathogenic SIV infections to address IP-10 levels and the presence of infected cells in tissues ( lymph nodes , small and large intestine ) . We found that elevated systemic IP-10 levels before HIV-1 infection associate with a more rapid disease progression . During primary infection , IP-10 in blood strongly correlated with the amount of infected cells in blood . The animal model showed that IP-10 expression was regionalized in the intestine and highest in the small intestine . Studies of aviremic animals suggest that high IP-10 is indicative of viral replication in lymphoid tissues . Haematopoietic cells rather than epithelial/endothelial cells mainly contributed to the IP-10 production in small intestine ( jejunum ) . The receptor of IP-10 was highly expressed on memory CD4+ T cells , i . e . major target cells for the virus . This study contributes to our understanding of the establishment of HIV reservoirs and why IP-10 associates with HIV/AIDS . | [
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"primates"... | 2016 | Elevated Basal Pre-infection CXCL10 in Plasma and in the Small Intestine after Infection Are Associated with More Rapid HIV/SIV Disease Onset |
Cholesteryl ester transfer protein ( CETP ) mediates the reciprocal transfer of neutral lipids ( cholesteryl esters , triglycerides ) and phospholipids between different lipoprotein fractions in human blood plasma . A novel molecular agent known as anacetrapib has been shown to inhibit CETP activity and thereby raise high density lipoprotein ( HDL ) -cholesterol and decrease low density lipoprotein ( LDL ) -cholesterol , thus rendering CETP inhibition an attractive target to prevent and treat the development of various cardiovascular diseases . Our objective in this work is to use atomistic molecular dynamics simulations to shed light on the inhibitory mechanism of anacetrapib and unlock the interactions between the drug and CETP . The results show an evident affinity of anacetrapib towards the concave surface of CETP , and especially towards the region of the N-terminal tunnel opening . The primary binding site of anacetrapib turns out to reside in the tunnel inside CETP , near the residues surrounding the N-terminal opening . Free energy calculations show that when anacetrapib resides in this area , it hinders the ability of cholesteryl ester to diffuse out from CETP . The simulations further bring out the ability of anacetrapib to regulate the structure-function relationships of phospholipids and helix X , the latter representing the structural region of CETP important to the process of neutral lipid exchange with lipoproteins . Altogether , the simulations propose CETP inhibition to be realized when anacetrapib is transferred into the lipid binding pocket . The novel insight gained in this study has potential use in the development of new molecular agents capable of preventing the progression of cardiovascular diseases .
Cholesteryl ester transfer protein ( CETP ) is a 476-residue-long hydrophobic glycoprotein that transports cholesteryl esters ( CEs ) , triglycerides , and phospholipids between high density lipoprotein ( HDL ) and other lipoprotein fractions in human blood plasma [1] . To be more specific , CETP exchanges CEs of HDL particles to triglycerides of very low density lipoproteins ( VLDL ) and low density lipoproteins ( LDL ) , thus increasing the amount of triglycerides in HDL , leading to more rapid catabolism of HDL particles . CETP ( Figure 1 ) carries CEs within a 6-nm-long hydrophobic tunnel that traverses the core of the molecule [2] . The tunnel has two distinct openings , and in the crystal structure [2] both of them are plugged by a dioleoylphosphatidylcholine ( DOPC ) molecule ( Figure 1A ) . The lipid exchange mechanism of CETP is poorly understood . One plausible mechanism is the so-called shuttle mechanism [1] , [3] , in which CETP binds only one lipoprotein at a time . CETP attaches to the surface of a lipoprotein via its concave surface where also the two tunnel openings reside [2] , [4] . The openings are expected to serve as passages to the flow of neutral lipids ( CEs and triglycerides ) between the particles , and their location supports the view that the concave surface is the only site able to bind lipoproteins , since other surfaces of the protein lack direct access to the tunnel . Further , the inherent curvature of CETP matches well with the curvature of HDL particles that may result from the fact that a major part of CETP has been shown to be associated with HDL due to higher binding affinity compared with plasma LDL or VLDL [1] . However , the molecular details driving the diffusion of lipids into and out from CETP require further elucidation . Previous experimental studies indicate that helix X located at the C-terminal domain of CETP is detrimental for the neutral lipid exchange , but not for the exchange of phospholipids [5] , [6] . Helix X has been proposed to act as a lid conducting the exchange of lipids by alternating its open and closed states [2] , [4] . In a recent molecular dynamics simulation study it was shown that after the attachment of CETP to lipoprotein surface , helix X is able to fold into the hydrophobic tunnel and interact with the CETP-bound CE [4] . After the lipids have been exchanged , the tunnel openings are plugged by phospholipids followed by the detachment of CETP from the lipoprotein surface . Meanwhile , in addition to the shuttle mechanism , another transportation mechanism has also been suggested . Here , CETP forms a ternary complex with two lipoprotein particles , and lipids somehow diffuse from one lipoprotein to another through the hydrophobic tunnel [7] . The interest towards CETP and its lipid transfer functions came to the forefront after notable associations between decreased CETP activity , decreased LDL-cholesterol level , increased HDL-cholesterol level , and resistance to atherosclerosis [8] . Atherosclerosis is a leading cause of morbidity and mortality in Western societies , and several clinical trials have shown that low HDL levels correlate with the risk of atherosclerosis due to antiatherogenic properties of HDL to remove cholesterol from atherosclerotic plaques back into liver to be recycled or secreted into bile [9] , [10] . Pharmacological CETP inhibition has therefore emerged as a prime target to modulate HDL levels , with an objective to become a potential treatment strategy for preventing various cardiovascular diseases . Unfortunately , the road of CETP inhibition has had a turbulent beginning due to the failure of its two first compounds , torcetrapib and dalcetrapib . Torcetrapib increased the level of HDL as was hoped , but additionally it also increased the blood pressure as well as the mortality rate [11] . Due to these reasons , all clinical trials concerning torcetrapib had to be terminated . In the case of dalcetrapib , the trials were halted for futility as only modest increases in HDL levels were reached [12] . However , subsequent studies indicate that CETP remains a valid target since the lethal side effects seen with torcetrapib are unrelated with CETP inhibition and may not be shared by the other members of CETP inhibitors . A real breakthrough was reached at the end of 2010 when a new variant of the drug , anacetrapib ( Figure 1B ) , was found to inhibit CETP with an acceptable side-effect profile [13] . In addition to anacetrapib , a competing inhibitor currently under phase III clinical development , evacetrapib , has already been shown to dose-dependently inhibit CETP and to increase HDL without severe cardiovascular events [14] . Despite the promising start achieved in the anacetrapib-based CETP inhibition , the precise inhibitory mechanism behind the agent is yet to be proven , regardless of the extensive research efforts its clarification has demanded . Classically , drugs inhibit or promote the functions of an enzyme or a receptor by binding e . g . to the active site thus blocking the binding of a ligand . However , in the case of CETP inhibitors , it has been demonstrated that they promote the formation of CETP-HDL complex , indicating that the current inhibitors do not only compete with CEs and triglycerides in CETP-binding but , additionally , they also hamper the detachment of CETP from HDL surface [15] , [16] . The reported ability of anacetrapib , torcetrapib and dalcetrapib to increase the binding affinity between CETP and HDL , and hereby to promote the inhibition of lipid exchange between the particles , does not clarify the actual mechanism of action nor the possible structural changes required . However , explanations concerning especially the role of phospholipids and helix X in this regard have been proposed but the details at an atomistic level are largely unknown , and thus the understanding of the molecular basis of inhibition is quite limited . Recently , the X-ray structures of CETP were published with bound torcetrapib and one of its analogs [17] . Surprisingly , the structure showed that torcetrapib is able to bind CETP even if both CEs are bound to CETP . However , the C-terminal phospholipid was not present in the structure suggesting that torcetrapib abolishes the binding of a phospholipid to the C-terminal tunnel opening . This , again , could make the detachment of CETP from the surface of a lipoprotein more unfavorable , thus stabilizing the CETP-HDL complex . It remains to be seen if this holds for anacetrapib , since it has a similar chemical structure compared with torcetrapib [18] . Another mechanism that has been suggested to stabilize the CETP-lipoprotein complex is the ability of anacetrapib to act as glue between the particles [16] . The above findings and suggestions are insightful and encouraging , but call for better understanding of the inhibitory mechanism of anacetrapib , as well as of the lipid transfer functions related with CETP inhibition . In this regard , our objective is to perform atomistic molecular dynamics simulations to obtain detailed information linking the two processes . Here we have studied the interactions between anacetrapib and CETP with different lipid compositions to gather novel information regarding the inhibition of CETP . Previous studies of HDL-like lipid droplets [4] , [19] , HDL [20] , and LDL [21] have shown that atomistic and coarse-grained simulations of lipoproteins and related transfer proteins can provide significant insight into their nanoscale properties and the mechanisms associated with lipid transfer . Understanding the lipid transfer functions of the protein , as well as the mechanisms behind CETP inhibitors , are important to realize in order to develop safe and efficacious treatment methods for the pharmacological raising of HDL cholesterol levels . We find that anacetrapib has a strong affinity for the region of the N-terminal tunnel opening . The primary binding site of anacetrapib turns out to reside in the tunnel inside CETP , near the residues surrounding the N-terminal opening . Free energy calculations show that when anacetrapib resides in this area , it hinders the ability of CE to diffuse out from CETP . The simulations further bring out the ability of anacetrapib to regulate the structure-function relationships of phospholipids and helix X , the latter representing the structural region of CETP important to the process of neutral lipid exchange with lipoproteins . Altogether , the simulations propose CETP inhibition to be realized when anacetrapib is transferred into the lipid binding pocket . The present study serves as a solid foundation for future studies concerning interactions between anacetrapib and CETP-lipoprotein complexes .
To find the most probable sites from the crystal structure of CETP where anacetrapib would favor to attach , we used the energy-minimized and flexible structure of anacetrapib together with the crystal structure of CETP . Here , the aim was not to identify the possible binding poses of anacetrapib , but rather to show the most probable binding sites of the drug molecule . The results are illustrated in Figure 1C and show that , according to the docking calculations , the most favorable binding site for anacetrapib resides in the hydrophobic tunnel of the protein . For ligands colored with red , brown , cyan , and green , the respective binding energies are −47 . 7 kJ mol−1 , −46 . 4 kJ mol−1 , −48 . 5 kJ mol−1 , and −46 . 9 kJ mol−1 . In order to further validate the binding site of anacetrapib , the recently published X-ray structure of CETP with bound torcetrapib [17] was matched with the most probable binding site of anacetrapib gained from the docking calculations , see Figure 1D . The binding sites are in good accordance with each other , although CEs were absent from our calculations . In conclusion , docking calculations suggest that anacetrapib could either compete with CETP-bound CEs or phospholipids in binding , or lock them to reside more tightly inside CETP . Below we discuss this topic in more detail based on the free energy calculations that we have carried out to unlock this issue . We carried out ten 20 ns atomistic simulations for fully hydrated systems containing CETP with anacetrapib placed outside but in a close proximity with the protein ( S1-helix , S2-1nm , S3-2nm , S4-3nm , S5-4nm , S6-convex , S7-1N , S8-2N , S9-1C , S10-3C; see Table 1 and Materials and Methods ) to study the self-assembly process as well as the interactions between anacetrapib and the concave surface of CETP . The initial configurations were constructed to reflect random initial conditions to better correspond to the biological environment of the particles . We also performed five 200 ns simulations involving CETP with different interior lipid and anacetrapib compositions ( L1 , L2 , L3 , L4 , L5; see Table 1 and Figure 2 ) to investigate the effects of anacetrapib to the conformational properties of CETP and bound phospholipids . The simulations without anacetrapib ( L1 , L3 ) served as control simulations to enable a more elaborate specification of the structural changes induced by the drug . In addition to the molecular dynamics simulations , we conducted eight umbrella sampling ( free energy ) simulations where both anacetrapib ( U1 , U2 , U3 , U4; see Table 1 and Figure 2 ) and the N-terminal CE ( U5 , U6 , U7 , U8; see Table 1 and Figure 2 ) were pulled out from the hydrophobic tunnel of CETP through the N-terminal opening . The purpose was to determine whether the anacetrapib located inside the tunnel has an influence on the diffusion of CE out from CETP , and to see the effect of helix X in this process . Root mean square deviation ( RMSD ) profiles of 20 ns simulations indicate that the structures do not deviate considerably from the corresponding X-ray structure ( Figure 3 ) . The radii of gyration fluctuated between 3 . 33 and 3 . 54 nm in each simulation ( Figure 3 ) . The spatial density maps illustrated in Figure S1 ( see Supporting Information ( SI ) ) reveal a disordered motion of the drug molecule around CETP . The distance between the particles ranged from 1 to 2 nm in the simulations S1-helix , S2-1nm , S3-2nm , S7-1N , S8-2N , and S9-1C , and from 3 to 4 nm in the simulations S4-3nm , S5-4nm , S6-convex , and S10-3C . A change in the distance from 2 to 3 nm weakens considerably the interactions between the CETP and anacetrapib and , as a consequence , anacetrapib experiences random movement due to thermal fluctuations . These findings are supported by the interaction energies calculated between the particles ( Table 2 , Figure 4 ) . Table 2 presents the interaction energies averaged over the course of the simulations , whereas Figure 4 depicts the energies as a function of simulation time . It is apparent that the main force to drive the binding of anacetrapib to CETP in S1-helix , S2-1nm , S3-2nm , S7-1N , S8-2N , and S9-1C is the weak van der Waals interactions . In the remaining simulations both the van der Waals electrostatic interaction forces are substantially weaker . It is worth to notice that in S1-helix , S2-1nm , S3-2nm , S7-1N , S8-2N , and S9-1C , the movement of anacetrapib is highly similar , since the drug moves at the N-terminal tunnel opening mainly around residues Arg197 , Ser431 , Lysh432 , Gly433 , Ser435 , and Hisb462 , which is in good agreement with our results based on molecular docking , concerning especially the binding site of the red ligand ( Figure 1C , Figure S1 ) . The visualization of the simulation trajectories also revealed that while the drug moved at the N-terminal opening , the trifluoromethyl- and methyl groups of the drug oriented close to each other ( Figure 1E ) . This indicates that the drug aligned itself to a tighter conformation suggesting a possible movement into the tunnel . The observed finding is supported by the interaction energies calculated from the simulations where anacetrapib was transferred into the hydrophobic tunnel of CETP ( L2 , L4 , L5; Table 2 , Figure 4 ) . The strength of van der Waals interactions between the particles is two to two-and-a-half times stronger inside the tunnel than at the N-terminal opening , or at the N- and C-terminal ends of the protein . This strongly suggests that CETP inhibition is enabled when the drug enters the protein , and the drug interacts with the structural regions of CETP important to lipid exchange from the hydrophobic cavity . The proposed movement is further supported by the lack of a significant number of hydrogen bonds between the protein and the drug . Anacetrapib was noticed to form separate hydrogen bonds with CETP while moving at the N-terminal tunnel opening , implicating that when a new bond was formed , the previous one was broken . This implies a weak attachment to CETP , and thus an unobstructed movement of the drug . The present findings based on a self-assembly process highlight the importance of thermal diffusion together with electrostatic and van der Waals interactions during the formation of CETP-inhibitor complexes . Thermal motion predominates for distances above 3 nm between anacetrapib and the tunnel opening of CETP , and only for shorter scales the direct interactions between the molecules become strong enough to drive the complex formation process . Furthermore , the affinity of anacetrapib towards the concave surface of CETP is evident when the distance between the particles is taken into consideration . On the basis of the above findings , we propose that the primary binding site of anacetrapib resides inside the hydrophobic tunnel of the protein , near the residues surrounding the N-terminal tunnel opening , including helix X . Computation of free energy profiles is a major computational challenge in general . The case considered here is not an exception . To get the free energy profiles shown in Figure 5 through umbrella sampling simulations required substantial computer resources ( see Materials and Methods ) . Despite this , the obtained profiles are not fully converged . This issue typically arises from inadequate sampling of regions of conformational space that are likely separated by a large barrier . While the data presented here represents largely the state of the art , we yet wish to stress that the best we can extract from the data are suggestive trends . The obtained free energy profiles ( Figure 5 ) indicate strong attachment between anacetrapib and CETP . They further point towards the possibly hindered ability of the CE molecule to diffuse from CETP to the water phase when both the drug molecule and two CE lipids reside in the hydrophobic tunnel ( Figure 5 ) . The corresponding free energy barriers range up to 65 kJ mol−1 for anacetrapib , and between 184 and 197 kJ mol−1 for CE ( when anacetrapib blocks the path ) . The free energy barriers found here , as CE is pulled out from CETP , are profoundly high . This results from the transition path that takes CE completely into the water phase . Importantly , Figure 5 also suggests that the increase in free energy is rather modest at short distances when CE is still inside the hydrophobic environment of CETP . Consequently , the free energy barriers are expected to become lower when CETP binds to a lipoprotein surface , hence facilitating the diffusion and exchange of lipids between the particles . It is worth to notice that the presence of helix X seems to have an influence on both the binding strength of anacetrapib and the diffusion ability of CE , since both molecules are pulled out from the hydrophobic tunnel more easily when helix X is removed from the structure of CETP . Additionally , when also the drug molecule is removed , the free energy barrier of CE movement towards the water phase appears to be the lowest , 153 kJ mol−1 . The results point towards the important role of helix X in assisting the lipid exchange , and highlight the possible inhibitory mechanism of anacetrapib as the movement of CE outside from CETP could be hindered in the presence of the drug molecule . There are two thermodynamic cycles for binding and unbinding both anacetrapib and CE present in the free energy calculations , namely , the one with the absence of helix X from the structure of CETP ( U1/U6/U2/U5 ) and the other with the presence of helix X in the structure of the protein ( U3/U8/U4/U7 ) . With the current data , these cycles result in values of −28±20 kJ mol−1 for the first and −30±20 kJ mol−1 for the latter cycle , where one is tempted to expect for a value of zero . However , the binding site of anacetrapib is not identical in systems where the hydrophobic tunnel is empty ( U1 , U2 ) or contains two CEs ( U5 , U6 ) . To be more specific , the binding site of anacetrapib resides deeper in the hydrophobic tunnel of CETP as the tunnel does not include lipids , while in the presence of these lipids the binding site of the drug molecule resides closer to the N-terminal tunnel opening . Hence , with the present systems , it is not possible to obtain a thermodynamic cycle that would result in a value of zero , and the values of the thermodynamic cycles given above therefore partly stem from this fact , and partly from inadequate sampling . Given the considerable computing resource to generate the data in Figure 5 ( see Materials and Methods ) , we consider it quite unfeasible to reduce the systematic error , but this is not an issue since the main conclusions that can be drawn from Figure 5 are evident based on the data shown . RMSD profiles of atomistic 200 ns simulations indicate that the protein structures do not deviate considerably from the corresponding X-ray structures ( Figure 6 ) . The RMSD values of DOPCs are also plotted in Figure 6 , and the profiles depict increased conformational alterations of DOPCs when the drug molecule is transferred into the hydrophobic tunnel of CETP: the RMSD fluctuates between 0 . 27 and 0 . 47 nm without the drug ( L1 , L3 ) , and between 0 . 26 and 0 . 61 nm with the drug ( L2 ) . This finding is further supported by the atomic RMS fluctuations and spatial density maps calculated for DOPCs ( Figure 7 ) . Maps confirm that DOPCs , especially their head groups and sn-2 chains , experience considerable wobbling in the presence of anacetrapib ( L2 ) compared with the absence of the drug ( L1 ) . However , there is a contradiction when comparing the RMSD and RMSF curves of DOPC in simulations L1 and L3 . The RMSD appears more stable in L3 ( Figure 6 ) , but the RMSF is more stable in L1 ( Figure 7 ) . A reason for this could be that DOPC shifts from its initial position in L1 and is then stabilized there . Nonetheless , the results are in good accordance with the interaction energies calculated between CETP and the associated lipids ( DOPCs and CEs ) , as well as between the lipids and anacetrapib ( Table 3 ) . As Table 3 illustrates , the strength of interactions between CETP and DOPCs are the strongest in the absence of anacetrapib ( L1 ) . Furthermore , as the interactions between DOPCs and CEs ( L3 ) seem to be stronger than between the lipids and anacetrapib ( L2 , L5 ) , it is evident that anacetrapib induces high fluctuations to phospholipids . This provides compelling evidence that the drug interacts with phospholipids , and , as a consequence , could hinder the binding of DOPCs to the tunnel openings , which could play a role in the stabilization of the CETP-lipoprotein complex . As the interaction energies between DOPC and CE molecules imply ( Table 3 ) , the fluctuations of the same order of magnitude were observed also when two CEs filled the tunnel ( Figures 6 and 7 ) . The spatial density maps reveal a high similarity for the trajectories of DOPCs regardless the type of the tunnel-filling particle . The observed movement could be caused by the residence of neutral lipids inside the hydrophobic tunnel of CETP , since in order for CEs to properly accommodate the cavity , a conformational rearrangement of DOPCs would be required . Nonetheless , the wobbling of phospholipids with CETP-bound CE molecules indicates the structure of CETP to be rather unstable during the transportation of neutral lipids . This could highlight the importance of helix X needed to prevent the structure of the protein from collapsing , as was suggested also previously [4] . The RMS fluctuations of CETP backbone were analyzed in order to find the regions that fluctuated the most during the simulations . This method of analysis can give valuable information regarding the functioning of a protein by highlighting the regions of protein backbone with low and high mobility . First , for comparison , CETP has previously been reported to have mobile structures with elevated B-factors near tunnel openings including the hinge region of helix X ( Gly458-Pro460 ) , and in the N- and C-terminal ends including the loop regions represented with omegas one and two [2] , [4] . As expected , these regions showed high mobility also in our simulations ( Figure 8 ) , with the conformational fluctuation of helix X peaking near the residue 462 . In addition , four other regions in the backbone of the protein were found to fluctuate highly during each simulation . These regions were Ω3 ( residues 380–400 ) , Ω4 ( residues 40–50 ) , Ω5 ( residues 90–110 ) and Ω6 ( residues 150–170 ) which were also earlier shown to have high mobility [4] . All these regions are found in the loops and therefore the high fluctuations can be expected . The results imply that the structure of CETP is elastic , facilitating the binding to lipoprotein surfaces with varying curvatures . In addition , the observed flexibility of the hinge region of helix X ( Glu 461-Ser472 ) suggests that helix X could play a crucial role in assisting the lipid exchange process . During the lipid exchange process helix X may partly move into the N-terminal CE-binding pocket of CETP to facilitate the export of CE out from CETP [4] . Another possibility is that helix X moves aside from the N-terminal tunnel opening , thus generating a wider pathway that facilitates the diffusion of CE out from CETP [22] . The above described free-energy calculations point to this direction . Interestingly , it became apparent based on DSSP calculations that the secondary structure of the helix encountered notable fluctuations between turn ( unfolding of the helix ) and 310-helix ( extension of the helix ) when the drug molecule interacted with the concave surface of CETP ( S1-helix , S2-1nm , S3-2nm , S7-1N , S8-2N , S9-1C ) , and when either CEs ( L3 , L5 ) or anacetrapibs ( L2 , L4 ) were present in the hydrophobic tunnel ( Figure 9 , Table 4 ) . For comparison , helix X maintained its α-helical form during the simulation L1 where the hydrophobic tunnel was empty ( Table 4 ) . The visual inspection of the simulation trajectories revealed that in L1 , the N-terminal DOPC maintained 1 nm distance from helix X over the course of simulation , while in L2 these two structures oriented themselves close to each other at the time when helix X experienced conformational fluctuations . The results imply that anacetrapib induces conformational alterations to the helix , and hence affects its stability , by interacting with the N-terminal DOPC . This , in turn , could indicate drastic effects on the lipid transfer functions of CETP .
On the basis of earlier clinical trials , both anacetrapib and the flawed torcetrapib were shown to increase the binding affinity of CETP towards lipoproteins , especially towards HDL [1] , [15] , [19] . They induced a tight reversible binding on the lipoprotein surface stabilizing the HDL-CETP complex , and hereby preventing the capability of CETP to transport neutral lipids between different lipoprotein fractions . Despite the appealing start achieved in the anacetrapib-based CETP inhibition , the actual inhibitory mechanism of the drug remained unknown . In the present study , our objective was to reveal the mechanism of action behind anacetrapib , shed light on its ability to inhibit CETP-mediated lipid transfer , and to unravel the dynamics of related processes . The results showed an evident affinity of anacetrapib towards the concave surface of CETP , especially towards the N-terminal tunnel opening where also helix X resides , and highlighted the importance of electrostatic and van der Waals interactions during the process once the drug was able to migrate to a close enough distance from the tunnel opening . However , the distance between the particles should be taken into consideration in the complex formation , since with too large distances ( above about 3 nm ) the movement of the drug was noticed to be dominated by thermal motion , eventually resulting in disordered motion . Hence , the question is how the affinity between the particles could be ensured in order to secure the interactions and speed up the complex formation process , as otherwise anacetrapib may experience random motion and may not be suitable for CETP inhibition purposes . For comparison , the formation of CETP-lipoprotein complex has been reported to be modulated by pH , surface pressure , and the introduction of positive divalent ions , such as Ca2+ and Mn2+ , into the solution [23] , [24] . In this spirit it is justified to assume that at least ion mediated interactions could foster the complex formation process , as electrostatics in terms of charged centers is an integral factor in both molecules but in the present case that we simulated in the absence of salt the screening effects were quite strong , resulting in predominance of thermal motion at long distances . In addition to the observed affinity , anacetrapib was noticed to align itself to a tighter conformation while moving near the N-terminal opening . This finding together with the evidence of stronger interactions prevailing between the particles when the drug was transferred inside the hydrophobic cavity , indicate the primary binding site of anacetrapib to reside in the tunnel , particularly near the residues surrounding the N-terminal opening , including helix X . Hence , we propose CETP inhibition to be realized when the drug is transferred into the lipid binding pocket . The regulatory role of helix X has been identified to play an important role in the lipid exchange process , since it has been suggested to act as a lid that conducts the exchange by alternating its open and closed states [4] . The structure of helix X has been proposed to undergo conformational changes during lipoprotein binding by moving aside from the N-terminal tunnel opening through an oblique penetration into the monolayer [22] , or by rearranging and becoming buried inside the hydrophobic pocket [4] . Thus helix X is proposed to be locked in the “open” state for the time of lipid exchange . Considering the detachment as well as the transportation of lipids , helix X is needed to shield the corresponding tunnel opening to make CETP more compatible with the aqueous environment [2] , hence the nomination “closed” state . The inhibitory mechanism of anacetrapib has been speculated to be in connection specifically with this regulatory property of helix X . One proposition suggests that CETP-bound anacetrapib alters the conformation of helix X to favor the open state , thus stabilizing the HDL-CETP –complex [4] . The above described findings disclose the flexible nature of helix X ( the hinge region ) that is essential in assisting the exchange of lipids . Our results are in agreement with these observations , as in the present simulations the hinge region of helix X was noticed to have elevated B-factors and , additionally , the secondary structure of the helix was shown to experience fluctuations between turn and 310-helix while anacetrapib moved near the residues that surround the N-terminal tunnel opening . The results provide compelling evidence about the ability of anacetrapib to induce conformational changes to helix X in order to achieve the needed flexibility . How helix X behaves in the presence of the entire HDL-CETP-anacetrapib complex is a question left for additional simulations to be resolved . Another crucial component in the process of neutral lipid exchange are the phospholipids due to their central role both in the binding and detachment of CETP from lipoprotein surfaces . During binding , phospholipids have been proposed to merge into the monolayer followed by a migration away from the tunnel openings to their edges [2] , [4] . The molecular simulation data is strongly in favor of this view [4] . This process induces the formation of a hydrophobic pathway under the concave surface of the protein , which permits the access of lipids into the tunnel . Considering the detachment , the tunnel openings will need to be refilled with phospholipids before the dissociation since otherwise the protein would not be able to return to aqueous environment , or at least it would be much more unfavorable [2] . Hence , changes in the structure of phospholipids could possibly hinder their binding to CETP and the dissociation of CETP from lipoprotein surfaces , further resulting in a weaker capability of the protein to transport neutral lipids . Our results pointed to this direction , since phospholipids were noticed to experience increased structural fluctuations , in addition to the declined electrostatic and van der Waals interactions with CETP when anacetrapib was transferred into the hydrophobic tunnel of the protein . The corresponding interactions were stronger between phospholipids and CE molecules , suggesting the capability of the drug to destabilize the binding of phospholipids to CETP . This view is in accordance with the crystal structure of CETP published in complex with torcetrapib [17] . The structure indicates that the binding of torcetrapib to CETP abolishes the binding of phospholipids to the N-terminal tunnel opening . It is possible that torcetrapib together with CE excludes enough volume inside the hydrophobic tunnel of CETP rendering the binding of a phospholipid to the corresponding tunnel opening impossible , as the hydrophobic acyl chains of the phospholipid can no longer be buried inside CETP . The primary binding site of anacetrapib to reside inside the hydrophobic tunnel is further supported by the free energy profiles that reveal strong attachment between the drug molecule and CETP , especially when two CEs fill the length of the tunnel as shown also previously [17] . When attached as described , anacetrapib hinders the ability of CE to diffuse out from the structure of CETP , thus pointing towards the possible inhibitory mechanism of the drug . The presence of helix X has a strong influence during this process , as both anacetrapib and CE were shown to move into the water phase more easily when the helix was removed from the structure of CETP . The results highlight the crucial role of helix X in assisting the lipid exchange during which helix X could possibly move aside from the N-terminal tunnel opening thus generating a wider pathway for CEs to diffuse out from CETP . It is reasonable that the hinge region of helix X enables the movement of the helix aside from the corresponding tunnel opening . In conclusion , our results show an evident affinity of anacetrapib towards the concave surface of CETP , especially towards the region of N-terminal tunnel opening . The primary binding site for the drug turns out to reside inside the hydrophobic tunnel , near the residues surrounding the N-terminal opening . When residing in this area , anacetrapib was shown to hinder the ability of CE to diffuse out from the structure of CETP . Additionally , the results point towards the encouraging capability of anacetrapib to influence the molecular interactions between phospholipids and helix X , both of which represent the structural regions of CETP important for lipid exchange between lipoproteins , thus giving support for the competency of pharmacological CETP inhibition . The view presented in this article paves the way for extending the scope of computational studies to gain a deeper understanding concerning the pharmacological ways to inhibit CETP and to modulate HDL levels . In this regard , simulations concerning the interactions between HDL-CETP-inhibitor –complex are ongoing ( work in progress ) . The novel understanding could be used in the development of new molecular agents in the fight against the progression of cardiovascular diseases .
Here we consider systems where anacetrapib interacts with CETP , which is either empty or carries a number of lipids in its transfer pocket . First , anacetrapib ( Figure 1B ) is an orally active , potent , and selective agent identified by high-throughput screening to belong to the 1–3-oxazolidin-2-one series of CETP inhibitors developed by Merck [15] . The medicinal chemistry behind the discovery of anacetrapib is described in [25] . The coordinate file for CETP in the PDB format was acquired from the RCSB Protein Databank with an accession code 2OBD . In addition to the protein , the file provides information of the atomic positions of the lipids involved in CETP: there are two CEs located inside the hydrophobic tunnel of CETP , and two DOPCs that cover the two openings of the tunnel . A detailed explanation of the protein structure is given elsewhere [2] . For all molecules considered in this study ( CETP , DOPC , CE , anacetrapib ) , we used the official distribution force field OPLS-AA [26]–[33] . In addition , an extension of OPLS was used for the long hydrocarbon tails of DOPC and CE [34] . Concerning the partial charges , for DOPC molecules they were derived in compliance with the OPLS methodology [35] , while for anacetrapib they were fitted to the electrostatic potential by applying the RESP software [36] . Here , the Merz-Kollman molecular electrostatic potential ( MEP ) was computed for the optimized structure of anacetrapib [37] . The MEP calculations were performed by applying the Gaussian 09 package at the Hartree-Fock level by employing the 6-31G* basis set [38] . The charges were fitted automatically by the RESP and ESP charge derived ( R . E . D . ) software version III . The derived charges can be found from the topology file Dataset S1 ( see SI ) . Water molecules were described with the TIP3P model since it is compatible with the parametrization of OPLS-AA [39] . Prior to molecular dynamics simulations , we used molecular docking calculations to determine the initial configurations for the simulated systems . The purpose of the calculations was not to identify the possible binding poses of anacetrapib , but rather to explore the most probable sites from the crystal structure of CETP where the drug would desire to attach in terms of the lowest binding energy . The constructed box covered the two tunnel openings and the hydrophobic tunnel of CETP . CETP-bound lipids were not present . A flexible anacetrapib molecule with 9 rotatable bonds was used in the calculations . In total , 1000 runs were carried out with default settings , namely , the maximum number of binding modes to generate/export was set to 9 , and the maximum energy difference between the best ligand pose and other ligand poses was set to 12 . 6 kJ mol−1 . Four conformations with the highest binding free energy for anacetrapib are shown in Figure 1C . For ligands colored with red , brown , cyan , and green , the respective binding free energies were found to be −47 . 7 kJ mol−1 , −46 . 4 kJ mol−1 , −48 . 5 kJ mol−1 , and −46 . 9 kJ mol−1 . More detailed technical information for the applied program , AutoDock Vina , can be found in [40] . Based on the docking data ( see Results for details; Figure 1C ) , we constructed initial simulation systems as divided into three groups . The first group consisted of 10 systems with lipids removed from CETP , and anacetrapib placed outside the protein but in the vicinity of its lipid binding pocket , to characterize the self-assembly process as well as to elucidate the interactions between the drug and the concave surface of the protein . In the first simulation ( S1-helix ) , anacetrapib was placed 1 nm away from helix X , whereas in the four following systems ( S2-1nm , S3-2nm , S4-3nm , S5-4nm ) the drug was placed 1 , 2 , 3 , and 4 nm from the tunnel openings , respectively . The sixth simulation ( S6-convex ) included anacetrapib at a distance of 3 nm from the convex back of the protein . The remaining four simulations ( S7-1N , S8-2N , S9-1C , S10-3C ) involved the drug at 1 and 2 nm distances from the N-terminal end , as well as 1 and 3 nm distances from the C-terminal end of the protein , respectively . All of the simulations in the first group were simulated for 20 ns each , thus “S” here in the system name stands for “short” . The second group consisted of five systems with anacetrapib placed inside the lipid binding pocket to study the conformational changes of CETP induced by the drug . In the first simulation system ( L1 ) , the two CEs and anacetrapib were removed from CETP , thus only the two DOPC molecules remained inside the protein ( Figure 2A ) . In the second simulation ( L2 , Figure 2B ) , two anacetrapib molecules were placed inside the empty hydrophobic tunnel based on the binding sites of cyan and green ligands presented in Figure 1C . Compared with L2 , the drug molecules were replaced by two CEs in the third simulation ( L3 ) , the one being placed in the N-terminal domain and the other in the C-terminal domain of the protein ( Figure 2C ) . Both L2 and L3 included DOPCs to plug the tunnel openings . All the lipids were removed from CETP in the fourth simulation ( L4 , Figure 2D ) , with one anacetrapib located in the empty tunnel between the binding sites determined by the cyan and green ligands ( Figure 1C ) . In the fifth simulation ( L5 ) , the N-terminal DOPC was removed from CETP , with two CEs and one anacetrapib filling the length of the hydrophobic tunnel ( Figure 2E ) . CEs were placed as in L3 , while the location of anacetrapib was determined by the binding site of the cyan ligand ( Figure 1C ) . Each of these systems , “L” standing for “long” ones , was simulated for 200 ns . The third group consisted of eight systems directed to umbrella sampling simulations . In the first four systems , one anacetrapib molecule was pulled out from CETP through the N-terminal tunnel opening . The interior lipid composition and the presence of helix X in the structure of CETP were varied between the systems . In the first two systems , helix X was removed and the tunnel was either empty ( U1 , Figure 2F ) or contained two CEs ( U2 , Figure 2G ) . Helix X was returned to CETP in the following two simulations and the tunnel was both empty ( U3 , Figure 2H ) and filled with two CEs ( U4 , Figure 2I ) . In all the remaining four systems , two CEs resided inside the hydrophobic tunnel , the N-terminal CE being the molecule pulled out from the structure of CETP with the varying presence of helix X and one anacetrapib . Both of these were absent in the fifth simulation ( U5 , Figure 2J ) , while in the sixth simulation ( U6 ) anacetrapib was added inside the tunnel , near the N-terminal tunnel opening ( Figure 2K ) . Helix X was returned to CETP in the last two simulations without ( U7 ) and with ( U8 ) one anacetrapib locating near the N-terminal tunnel opening ( Figure 2L and 2M ) . The N-terminal DOPC molecule was removed in all eight systems , whereas the C-terminal DOPC plugged the corresponding tunnel opening . Each of these systems , “U” standing for umbrella sampling ( see below ) , were first equilibrated for 100 ns , and then simulated for 60 ns . The systems belonging to the first group were solvated with ∼100 , 000–160 , 000 water molecules with counter ions , while in the second and third groups about 100 , 000 and ∼30 , 000–60 , 000 water molecules , respectively , were used for solvation . Altogether , the systems included ∼125 , 000–500 , 000 atoms . The number of water molecules used in the simulations depends on the size of the simulation box: the greater the distance between CETP and anacetrapib , the greater the size of the simulation box and , hence , the number of water molecules . The size of the simulation box originates from the requirement of periodic boundary conditions . Before any simulation was started , energy minimization was performed for each system using the steepest descent method with 500 steps [41] . Prior to conducting umbrella sampling simulations , eight pulling simulations were performed in order to generate a series of configurations that served as the starting configurations for umbrella sampling . In the pulling simulations , either anacetrapib or the N-terminal CE , depending on the system , was pulled out from the structure of CETP through the N-terminal tunnel opening . Residues Cysh9 , Arg10 , Ile11 , and Thr12 were used as the reference pull group due to their parallel location with the N-terminal tunnel opening . The force constant applied either to the center of mass of anacetrapib or to the last carbon atom in the acyl chain of CE was 2000 kJ mol−1 nm−2 with a pull rate of 0 . 003 nm ns−1 . After pulling simulations , umbrella sampling was conducted with a total of 25 and 47 umbrella windows when the pulled molecule was anacetrapib and CE , respectively . The umbrella windows were selected at 0 . 1 nm intervals from the original location of the molecules inside the hydrophobic tunnel towards the water phase . Each window was simulated for 160 ns where the first 100 ns were used for equilibration . These parameters were chosen based on a systematic study for increasing equilibration and simulation times . Altogether , the umbrella sampling simulations required about 600 core-years of computing time . In these simulations , both molecules were restrained to the middle of every umbrella window by a harmonic potential with the same force constant as used in the pulling simulations . The restraints were applied only along the reaction coordinate defined by the vector connecting the reference pull group and the pulled molecule , and the molecules were free to move in the other directions . In order to keep the reaction coordinate along the vector and to prevent CETP from rotating and tilting , position restraints were applied to a carbon atom of Ser115 and to a carbon atom Gly413 . These atoms reside in the N- and C-terminal ends of the protein , respectively . The simulations were performed under NpT conditions ( constant number of particles , pressure , and temperature ) with the GROMACS software package using the version 4 . 5 . 4 for the first and second simulation groups and version 4 . 6 . 1 for the third simulation group [41] . The reference temperature for all simulated systems was 310 K , and each component of the systems was separately coupled to a temperature bath using the Nόse-Hoover coupling method with a time constant of 0 . 1 ps [42] . The Parrinello-Rahman barostat was applied to couple the pressure , with a coupling constant of 1 ps and a reference pressure of 1 bar [43] . A time step of 2 fs was used in all simulations , with the LINCS algorithm applied to constrain all the bonds in the system [44] . The van der Waals interactions were calculated up to a cutoff radius of 1 nm and the particle mesh Ewald technique was utilized for long-range Coulombic forces , with a real space cutoff of 1 nm [45] , [46] . As mentioned above , the ten systems associated with the first simulation group ( “S” standing for short ) were simulated for 20 ns , the systems in the second group ( “L” standing for long ) for 200 ns , and the systems in the third group ( “U” standing for umbrella sampling ) for 160 ns where the first 100 ns were used for equilibration . DSSP ( define secondary structure of proteins ) [47] was applied to determine the most likely secondary structure of CETP as a function of time . DSSP was calculated by applying the do_dssp tool of GROMACS . The root mean square deviation ( RMSD ) was used to evaluate the deviation of the structure of the simulated system from the initial starting structure over the course of simulation . RMSD was calculated by applying the g_rms tool of GROMACS . The radius of gyration was used to measure the size and compactness of a molecule . It is defined as the mean square distance of each particle in the structure with respect to its center of mass . The radius of gyration was calculated by applying the g_gyrate tool of GROMACS . The root mean square fluctuation ( RMSF ) of atomic positions was used to discover and evaluate the most flexible regions of CETP . RMSFs were calculated by fitting the simulated structure to a reference structure followed by the calculation of the average distance deviation from the reference structure . Typically , the residues of a protein that fluctuate the most can be found in loop regions . For purposes of comparison with experimental data , the RMSFs can be converted into B-factor values . RMSF was calculated by applying the g_rmsf tool of GROMACS . Interaction energies between different molecules were calculated by applying the g_energy tool of GROMACS . The tool calculates the contributions of the energies automatically from the simulation trajectory . Weighted histogram analysis method ( WHAM ) is a standard technique to compute the potential of mean force ( PMF ) along the reaction coordinate for a molecule [48] , [49] . It estimates the statistical uncertainty of the probability distribution obtained from the umbrella histograms and iteratively computes the PMF that corresponds to the smallest uncertainty in the form of global free energy of the molecule [49] . WHAM was calculated by applying the g_wham tool of GROMACS . Statistical uncertainty of the PMF can be estimated by applying the bootstrap analysis . The idea is to generate new hypothetical observations , that is , a bootstrapped trajectory for each umbrella histogram , thus yielding a new set of histograms for the corresponding umbrella window that are subsequently applied in WHAM to calculate a bootstrapped PMF . The process is repeated for each bootstrapped trajectory when a large number of bootstrapped PMFs can be obtained . The applied bootstrapped sample size was 200 . Hydrogen bond formation has a remarkable role , e . g . , in the stabilization of the secondary structure of a molecule . In this study the formation of hydrogen bonds is analyzed between CETP and anacetrapib in order to see where and how tightly anacetrapib binds . The formation of hydrogen bonds is analyzed between all possible donors D and acceptors A . OH and NH groups are regarded as donors while O is always an acceptor . The determination for the existence of a hydrogen bond is done by using a geometrical criterion ( based on the distance between donor-acceptor rDA ) and a criterion for the angle α ( between acceptor-donor-hydrogen triplet αADH ) , ( 1 ) ( 2 ) Hydrogen bonds were calculated by applying the g_hbond tool of GROMACS . | Cardiovascular disease is a leading cause of morbidity and mortality in Western societies . One of the most encouraging treatment methods to prevent the generation and progression of cardiovascular disease is the elevation of high density lipoprotein ( HDL ) levels in circulation , as high HDL levels have been found to correlate negatively with the risk of cardiovascular disease . HDL elevation is attainable through inhibition of cholesteryl ester transfer protein ( CETP ) . A novel molecular agent , anacetrapib , fulfills the requirements with an acceptable side-effect profile . In this study , our objective is to gain more detailed information regarding the interactions between CETP and anacetrapib in order to unlock the inhibitory mechanism of the drug that has , to date , remained unclear . Our results point out the primary binding site of anacetrapib and highlight the ability of the drug to regulate the structure-function relationship of those structural regions of CETP that are considered important in CETP inhibition . Our findings could be exploited in the development of new and more efficient molecular agents against cardiovascular disease . | [
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] | 2014 | How Anacetrapib Inhibits the Activity of the Cholesteryl Ester Transfer Protein? Perspective through Atomistic Simulations |
Cellular immune responses require the generation and recruitment of diverse blood cell types that recognize and kill pathogens . In Drosophila melanogaster larvae , immune-inducible lamellocytes participate in recognizing and killing parasitoid wasp eggs . However , the sequence of events required for lamellocyte generation remains controversial . To study the cellular immune system , we developed a flow cytometry approach using in vivo reporters for lamellocytes as well as for plasmatocytes , the main hemocyte type in healthy larvae . We found that two different blood cell lineages , the plasmatocyte and lamellocyte lineages , contribute to the generation of lamellocytes in a demand-adapted hematopoietic process . Plasmatocytes transdifferentiate into lamellocyte-like cells in situ directly on the wasp egg . In parallel , a novel population of infection-induced cells , which we named lamelloblasts , appears in the circulation . Lamelloblasts proliferate vigorously and develop into the major class of circulating lamellocytes . Our data indicate that lamellocyte differentiation upon wasp parasitism is a plastic and dynamic process . Flow cytometry with in vivo hemocyte reporters can be used to study this phenomenon in detail .
Blood cells are the central players in the cellular immune response , and evolutionarily conserved signaling pathways control their hematopoiesis . Three main types of blood cells or hemocytes have been described for Drosophila melanogaster; plasmatocytes , crystal cells , and lamellocytes . Plasmatocytes , the main hemocyte type in healthy larvae , are professional phagocytes , and they are functionally similar to mammalian monocytes , macrophages , and neutrophils . Lamellocytes are formed in response to wasp infection , when they are needed for the encapsulation and killing of parasitoids . Finally , crystal cells , are required for the melanization of wounds . Together with lamellocytes , crystal cells probably also contribute to the melanization of capsules , a presumed effector mechanism of the immune defense [1–5] . A variety of parasitoid hymenopteran wasp species , including the genus Leptopilina [6] , deposit their eggs in the hemocoel of fly larvae . This triggers a melanotic encapsulation reaction that comprises a fixed sequence of events . After the egg is injected , a thin electron-dense layer of unknown material is deposited on the chorion . Then plasmatocytes attach to and spread on the egg . Several layers of lamellocytes encapsulate the egg , the capsule is sealed by septate junctions between the cells , and finally melanin is deposited by the action of the enzyme phenol oxidase [7 , 8] . Both crystal cells and lamellocytes participate in the melanization reaction [5 , 9] . Parasitoid wasp species , in turn , deploy several virulence strategies , which incapacitate the host´s cellular immune system in different ways and visibly affect hemocytes [10] . Drosophila larval hemocytes originate from two embryonic sources; the procephalic and the cardiogenic mesoderm anlagen [11] . The cardiogenic anlage gives rise to two rows of hematopoietic organs , called lymph glands , which are situated on each side of the dorsal vessel . The paired primary lobes of the lymph glands consist of a medullary zone with progenitor cells , a cortical zone with differentiated hemocytes , and a posterior signaling center that supervises the maintenance and differentiation of progenitor cells [12–14] . Prior to pupariation , the lymph glands disintegrate and release mature hemocytes . In response to wasp infection the primary lobes can disintegrate earlier and release differentiated plasmatocytes and lamellocytes [15 , 16] . The hemocytes of procephalic origin give rise to the peripheral hemocyte population , which is distinct from the lymph glands . Peripheral hemocytes colonize a second hematopoietic compartment of sessile hemocyte islets , which are arranged in segments under the skin [15 , 17 , 18] . These hemocytes proliferate in contact with peripheral neurons [19] and alternate between sessile positions in the islets and circulation in the open body cavity of larvae [4 , 19] . In healthy larvae , all hemocytes are of procephalic origin until the onset of metamorphosis , when hemocytes are released from the lymph glands . Procephalic hemocytes also persist into adulthood [4] . Although research during the past 15 years has highlighted the lymph glands as the source of lamellocytes , Rizki suggested already in 1957 that peripheral plasmatocytes give rise to lamellocytes [20] . This idea was more recently corroborated by lineage tracing in three studies [21–23] . After a wasp attack , a main fraction of the hemocytes participating in the encapsulation reaction originates from the peripheral population [18 , 21] . Nevertheless , the origin of lamellocytes remains ambiguous , and the dynamics of the cellular immune system in the encapsulation reaction is unclear . Initially , hemocytes were classified by their morphology [20] . The development of the enhancer trap system in Drosophila enabled the production of the first generation of genetic hemocyte markers [24 , 25] . Later , hemocyte-specific antibodies provided pan-hemocyte antibodies [26] as well as specific antibodies for the different hemocyte classes [27 , 28] . These antibodies were also instrumental in the discovery of new hemocyte-specific proteins . Hemocyte-specific GAL4 constructs and fluorescent enhancer-reporter fusions further diversified the genetic toolbox , allowing the observation of hemocytes or specific hemocyte subclasses in vivo [17 , 29–33] . These , and other markers used to study embryonic hemocytes and lymph glands , are reviewed in [34] . Despite these advances , peripheral hemocytes are mainly counted with hemocytometers , which is labor-intensive and error-prone . So far , the use of flow cytometry in the differential cell counting and sorting of Drosophila hemocytes has been minimal . Here we present a combined approach of flow cytometry and microscopy to investigate the dynamics of hematopoiesis after a wasp infection . We took advantage of the previously developed enhancer-reporter constructs eater-GFP ( here called eaterGFP ) [30] , which is specific for plasmatocytes , and MSNF9MO-mCherry ( msnCherry ) , which is specific for lamellocytes [32] . We chose three species of the parasitoid wasp genus Leptopilina , each with different well-established effects on the immune response of Drosophila larvae , to better understand the origin of lamellocytes and the dynamics of the hemocyte compartments during the encapsulation reaction . We show that flow cytometry , combined with fluorescent enhancer-reporter constructs , is an effective way to distinguish different hemocyte classes . A wasp infection induces several novel hemocyte classes that belong to two major lineages , the plasmatocyte and the lamellocyte lineage . These lineages give rise to two types of lamellocytes and activated plasmatocytes in a demand-adapted response .
To simultaneously monitor plasmatocytes and lamellocytes , we recombined X chromosome insertions of the msnCherry and eaterGFP reporters to generate a dual reporter chromosome , here referred to as Me . We will refer to the corresponding expressed phenotypes as mCherry and GFP , respectively . We chose three wasp species of the genus Leptopilina to study the encapsulation and killing response in Me/w1118iso ( Me/w ) heterozygous larvae . L . boulardi is a specialist for D . melanogaster that kills approximately half of the infected host larvae after interfering with hemocyte spreading [35 , 36] and the melanization reaction [37 , 38] . L . heterotoma is a generalist species that kills almost all infected larvae [39] by lysing lamellocytes [40 , 41] . D . melanogaster is not a host species for L . clavipes , and eggs of this species are efficiently killed by the larval immune system [6] . We assumed that the different life styles of these wasp species would be reflected in differences in the immune responses of Drosophila larvae . As expected , the eggs and larvae of the three wasp species were melanized and killed with different efficiencies ( S1A Fig ) . L . boulardi eggs were melanized at a low rate ( examples are shown in S1B–S1B”“Fig ) . Most of the wasp larvae hatched 30–32 h after infection . Thereafter the Drosophila larval cellular immune system mounted a melanotic encapsulation response and killed about 40% of the wasp larvae ( examples of living or killed wasp larvae are shown in S1C and S1C” Fig ) . L . clavipes eggs were more readily encapsulated and living wasp larvae of that species were rarely found in the hemocoel . In contrast , a melanotic encapsulation response never developed against L . heterotoma eggs or larvae . After we had confirmed the unequal encapsulation responses against these wasp species , we set out to characterize the dynamics of the cellular immune response with flow cytometry and microscopy . Our first approach was a time line experiment where we let L . boulardi females lay eggs in heterozygous Me/w larvae for two hours . Then we bled infected and age-matched control larvae every second hour during a time course of 50 h and analyzed hemocyte numbers and types by flow cytometry . A detailed gating strategy can be found in Fig 1A and S2 Fig . In S3 Fig , we illustrate the morphology of the different cell types after cell sorting , thereby verifying our gating strategy . As expected , we detected only a single well-defined population of GFP-positive plasmatocytes in the hemolymph of uninfected animals by flow cytometry ( Fig 1C , upper row ) . In contrast , a L . boulardi infection induced drastic changes producing an increased diversity of hemocyte phenotypes ( Fig 1A , 1B and 1C , second row ) . Besides the typical plasmatocytes , a second heterogeneous population of plasmatocytes appeared . This class , which we named activated plasmatocytes , expressed high levels of GFP together with varying amounts and variable sizes of cytoplasmic mCherry-positive foci ( Fig 1B’ ) . In addition to the pre-existing plasmatocytes , we found a separate population of cells with plasmatocyte-like morphology , but with 10-fold lower GFP fluorescence ( Fig 1B and 1C , second row , S4A and S4A’ Fig ) . We will tentatively refer to these cells as lamelloblasts because they appear to be a major source of circulating lamellocytes . Apart from differences in GFP expression levels , lamelloblasts were less granular and slightly smaller than plasmatocytes ( S4C and S4C’ Fig ) . A fourth class gradually appeared , with increasing mCherry expression and correspondingly decreasing GFP expression . Morphologically these were intermediates between lamelloblasts and lamellocytes , and we will refer to them as prelamellocytes ( Fig 1B”‘ ) . The fifth class , the fully differentiated lamellocytes , represented the end result of this development . They were large cells that only expressed mCherry throughout the cytoplasm ( Fig 1B”‘ ) . A sixth class included large cells with homogeneous expression of mCherry throughout the entire cytoplasm , however , unlike circulating lamellocytes , they also expressed strong nuclear GFP ( Fig 1B” and 1B”‘ ) . These cells were rarely observed in circulation . To distinguish them from circulating lamellocytes ( lamellocytes type I ) , we will refer to them as lamellocytes type II . Finally , there was also a highly variable number of cells or particles , defined as the "negative population" , that did not express either of the two reporter constructs ( Fig 1A ) . This fraction may include crystal cells and prohemocytes as well as cell fragments and other debris . Due to the lack of good markers we did not further investigate these cells . A time line experiment revealed the dynamics of the cellular immune response ( Fig 2 ) . Total cell numbers in L . boulardi-infected larvae were higher than in uninfected larvae . The increase of total cell numbers started eight to ten hours after infection ( S5A and S5B Fig ) . Most of the circulating blood cells in uninfected larvae were plasmatocytes . Only in late third instar larvae a few activated plasmatocytes developed . Plasmatocyte numbers increased steadily but never reached much more than 1000 cells per larva , until a sudden increase prior to pupariaton ( Fig 2A ) . Plasmatocytes of larvae infected by L . boulardi followed the same dynamics as those of uninfected larvae , but without the sudden increase late during infection . Activated plasmatocytes were present in the circulation already ten hours after infection . Their numbers stayed low until the 30 h time point . Then their count started to rise above the number of plasmatocytes and thereafter steadily increased . This coincided with the hatching of wasp larvae . After this time point , activated plasmatocytes were the predominant plasmatocyte population in circulation ( Fig 2B ) , as well as in the sessile compartment ( Fig 3 ) . The final peak of activated plasmatocytes observed in infected larvae corresponded well to a similar increase in plasmatocytes in uninfected larvae ( Fig 2A and 2B ) . Lamelloblasts , prelamellocytes , and lamellocytes were rarely seen in uninfected larvae , but eight hours after infection lamelloblasts appeared for the first time , and during the following six hours their count rose to over 1000 cells per animal . Later , their numbers decreased and thereafter stayed more or less constant until the end of the time line experiment . Interestingly , the dynamics of prelamellocytes and lamellocytes followed that of lamelloblasts but with a delay of six and 16 h , respectively . Unlike lamelloblasts , the numbers of prelamellocytes and lamellocytes started to rise again 40 h after infection ( Fig 2B’ ) . In addition , we tested if temperature influences the induction of different blood cell types . The immune reaction of larvae grown at 25°C was similar to that of larvae grown at 29°C , however it was time-delayed due to the lower temperature ( S6 Fig ) . We used a reduced time line approach for L . clavipes- and L . heterotoma-infected Me/w larvae , focusing on the time points when a L . boulardi infection had the largest effects . In larvae infected by L . clavipes , the increase in total cell number was comparable to that after a L . boulardi infection ( S5 Fig ) . Also the dynamics of the different cell types was similar , albeit delayed by four hours . The average numbers of prelamellocytes and lamellocytes never reached those after L . boulardi infection ( S7B and S7B’ Fig ) . The total cell number of L . heterotoma-infected larvae was lower than after L . boulardi or L . clavipes infection ( S5 Fig ) . Shortly after infection , it rose above the level of controls , but stayed relatively low thereafter . At the 48 h time point , the total cell count was lower than in controls . Lamelloblasts appeared in the circulation , but their numbers were low . Also the counts of activated plasmatocytes , prelamellocytes , and lamellocytes were reduced in comparison to larvae infected by the other wasp species . Activated plasmatocytes were not observed in the circulation until the 48 h time point ( S7C and S7C’ Fig ) . Flow cytometry plots and representative microscopic images of hemocytes at selected time points after infection by the three wasp species and uninfected controls are presented in Fig 1C and S8 Fig . It is noteworthy that oviposition by all wasp species induced all blood cell populations with similar dynamics . This implies that the melanotic encapsulation response is stereotypical , and only shaped by the virulence factors of the infecting wasp species . The outcome of a L . boulardi infection varied between individual Drosophila larvae . Thus , we recovered either living or killed wasp larvae from the hemocoel when we dissected fly larvae 36 to 50 h after infection . Similarly , melanized and non-melanized wasp eggs were present 24 h after a L . clavipes infection . This gave us the opportunity to test if the total cell number varied according to the outcome of the infection , thereby explaining the resistance to the parasite . However , in neither case did we see a significant difference in cell numbers ( S5B and S5C Fig ) . It was reported previously that hemocytes leave the sessile islets and start circulating after a wasp infection [17 , 18] . We therefore imaged control larvae and larvae infected by the three wasp species at different time points after infection to have a closer look at the pattern of sessile cells and the lymph glands ( Fig 4 ) . The fluorescent signals of the eaterGFP and msnCherry reporters were weak until approximately 22 h after infection , presumably due to the combination of a long maturation time of the fluorophores and a comparatively low magnification . The signal was stronger when we expressed UAS-GFP with the hemocyte-specific HmlΔ-GAL4 driver ( HmlΔ>GFP ) , which is expressed from an early time point in development [12 , 42] . For this reason , we imaged the offspring of crosses of msnCherry to HmlΔ>GFP ( msnCherry;HmlΔ>GFP ) at 8 and 16 h after infection . At all other time points , we used heterozygous Me/w reporter larvae . In uninfected larvae , we were able to detect HmlΔ>GFP in the lymph glands of only one out of five cases at the 8–10 h time point and in two out of five cases at the 16–18 h time point ( Fig 4A–4A”“ ) . Different wasp species had varying effects on the lymph glands . Early after parasitization by L . boulardi and L . clavipes , the primary lymph gland lobes disappeared while the secondary lobes were enlarged later . This was best visible before the application of structured illumination as described in Materials and Methods ( see numbers in Fig 4A”“‘ , 4B”“‘ and 4C”“‘ ) . In contrast , the primary lobes were always visible after a L . heterotoma infection , and they contained lamellocytes starting from the 22 h time point , whereas the secondary lobes disappeared ( Fig 4D”“‘ ) . This was in contrast to a previously published report where a L . heterotoma infection induced apoptosis in the lymph glands [43] . We did not observe any major effect on the sessile hemocyte population 8 or 16 h after infection by any of the three wasp species . 48–50 h after L . boulardi and L . clavipes infections , the number of sessile plasmatocytes seemed to increase and mCherry-positive nodules of lamellocytes became visible ( Fig 4B”–4B”“ and 4C”–4C”“ ) . Under these conditions , the previously observed mobilization of sessile cells [17 , 18] was not apparent . A L . heterotoma infection induced a progressive loss of sessile plasmatocytes , and lamellocytes were rarely seen among sessile cells ( Fig 4D”–4D”“ ) . As noted previously [44] the msnCherry reporter was also ectopically expressed in the pharyngeal musculature , in one to three adjacent lateral transverse muscles on each side of most segments , and in the alary muscles . After infection by L . boulardi and L . clavipes , mCherry expression became activated in pericardial cells , while its expression in the lateral transverse musculature abated ( Fig 4B–4B”“ and 4C–4C”“ ) . A similar effect was previously observed in the Toll10b gain-of-function mutant [44] . No change was observed after an infection by L . heterotoma ( Fig 4D–4D”“ ) . Next we imaged wasp eggs of the different wasp species at various time points after infection . The events on the wasp egg differed depending on the wasp species . After a L . boulardi infection , plasmatocytes and activated plasmatocytes were found attached to wasp eggs eight to ten hours after infection ( Fig 5A ) . Their numbers increased 12–14 h and type II lamellocytes formed and started to spread ( Fig 5B ) . Type II lamellocytes were fully spread 28–30 h after infection . No melanotic encapsulation reaction had occurred yet , and type I lamellocytes were rarely present on wasp eggs at this point ( Fig 5C ) . Approximately 32 h after infection , L . boulardi larvae hatched and the cellular immune system mounted a melanotic encapsulation response against the wasp larvae . Fig 5D and 5D’ show an encapsulated wasp larva 48–50 h after infection , with lamellocytes and plasmatocytes participating in the formation of the capsule . In L . clavipes-infected larvae , hemocytes did not attach to the wasp egg early during infection ( Fig 5E ) . Instead , they formed loose networks around wasp eggs . These networks were too delicate to dissect and therefore difficult to image . As soon as lamellocytes were present , 22–24 h after infection , melanotic encapsulation ensued rapidly . Both lamellocytes and plasmatocytes were involved in forming the capsule . Wasp eggs were fully encapsulated 28–30 h after infection ( Fig 5F and 5F’ ) and the capsule became darker with time ( Fig 5G and 5G’ ) . The immune system of fly larvae was not able to attack wasp eggs or larvae after a L . heterotoma infection at any time point ( Fig 5H–5J ) . The sudden appearance of lamelloblasts was the most striking observation in the time line experiment . Their numbers increased from zero to over 1000 cells per larva within only six hours ( Fig 2B’ ) . This increase was most likely due to the proliferation of lamelloblasts or their precursors . We therefore devised experiments to investigate cell division after infection . We placed Me/w larvae together with L . boulardi females for two hours for infection and then applied different 5-ethynyl-2′-deoxyuridine ( EdU ) feeding schemes to test which cell types were capable of division early and late after a wasp infection ( Fig 6A ) . The gating strategy of EdU-Alexa647 combined with GFP and mCherry expression can be found in S9 Fig . Eight hours after infection , total cell numbers were slightly elevated in infected larvae ( S5 Fig ) , lamelloblasts were seen in the circulation for the first time ( Fig 2B’ ) , and type II lamellocytes appeared on the wasp eggs ( Fig 5A ) . Therefore we fed larvae with EdU at different early time intervals and then analyzed EdU incorporation eight hours after infection to find out the earliest time point of infection-induced cell division ( Fig 6A ) . After the first EdU feeding scheme , two to six hours on EdU food , approximately half of the hemocytes of control and infected larvae had incorporated EdU ( Fig 6C ) . After the second feeding scheme , four to eight hours on EdU food , a larger number of hemocytes of infected larvae were EdU positive than of controls ( Fig 6B and 6C ) . We observed the highest number of lamelloblasts 14 h after infection ( Fig 2B’ ) . Therefore , we predicted that just prior to that time point , lamelloblasts would be dividing at their highest rate . Thus , we fed larvae on EdU two to 12 h and dissected hemocytes 12 h after infection ( Fig 6A ) . At this time point , lamelloblasts and all plasmatocyte subtypes had incorporated EdU at a high rate ( Fig 6B’ , 6C , and 6D ) . Thus , a demand-adapted increase in hemocyte proliferation was already well under way at eight hours after infection , and most plasmatocytes and lamelloblasts had undergone division at least once by 12 h ( Fig 6C ) . As type II lamellocytes were scarce in circulation , we investigated if these cells were able to divide on wasp eggs . We used UAS-S/G2/M-Green under the control of the combined hemocyte-specific drivers HmlΔ-GAL4 and He-GAL4 to mark dividing cells . S/G2/M-Green is an in vivo cell cycle reporter that labels cells in the S- , G2- , and M-phases [45 , 46] . Fig 7A–7A”‘ show that plasmatocytes and type II lamellocytes were dividing while attached to a wasp egg . At 48–50 h after infection , sessile plasmatocyte numbers seemed to have increased after a L . boulardi and a L . clavipes infection in comparison to controls ( Fig 4A”“ , 4B”“ and 4C”“ ) . We used S/G2/M-Green in combination with eaterDsRed to assess whether sessile plasmatocytes were dividing . Within the sessile population of controls and infected larvae a large proportion of plasmatocytes divided ( Fig 7B and 7B’ ) . Because genetic tools have not yet been developed for the newly discovered cell types , we deduced the relationships between these classes by a different approach . We reasoned that changes in marker expression must be gradual . By sampling the population at close enough time points , we expected all hemocyte classes to be linked to their precursors via intermediate forms . In this way we could trace hematopoiesis to two parallel lineages , the plasmatocyte and lamellocyte lineages , each originating from a different class of plasmatocyte-like cells . In addition to changes in the expression levels of fluorescent markers , both forward and side scatter increased the further advanced the cells were in each lineage , suggesting that they became larger and more granular ( S4E–S4E” Fig ) . In the plasmatocyte lineage plasmatocytes gave rise to two infection-induced cell types; activated plasmatocytes and type II lamellocytes . The continuity of the cell population from the plasmatocyte gate into the activated plasmatocyte gate ( Fig 1C ) suggested that plasmatocytes developed into activated plasmatocytes by retaining GFP expression and gradually accumulating cytoplasmic mCherry-positive foci . 30–32 h after infection , activated plasmatocyte counts increased in synchrony with the hatching of wasp larvae , whereas plasmatocyte numbers remained constant ( Fig 2B ) . This implied that both cell types are able to proliferate . Feeding larvae on EdU-containing food 28–32 h after infection and dissecting them 16 h later ( Fig 6A ) revealed that plasmatocytes and activated plasmatocytes had incorporated EdU at the same rate ( Fig 6B”‘ and 6D ) . In addition , we compared the granularity and the size of plasmatocytes and activated plasmatocytes 48 h after infection . The plasmatocytes of infected larvae were smaller and less granular than activated plasmatocytes and the plasmatocytes of non-immune challenged larvae ( S4D–S4G’ Fig ) . Therefore , we concluded that plasmatocytes matured into activated plasmatocytes , both cell types proliferated , and these cell types differed in size and granularity . In addition , soon after plasmatocytes adhered to the parasite , they started to express mCherry , increased in size , and turned into type II lamellocytes by transdifferentiation ( Fig 8A–8C , S1 Video ) . At this stage , their shape became reminiscent of lamellocytes , but they never lost their plasmatocyte identity , as defined by the expression of the GFP marker ( Figs 5C and 8A–8C ) . We noted that lamelloblasts appeared eight hours after oviposition , followed by prelamellocytes at 14 h and finally lamellocytes at 22 h ( Fig 2B’ ) . These three hemocyte populations formed one contiguous streak in the two-dimensional scatter plots ( Fig 1C ) . This suggested that lamelloblasts were precursors of lamellocytes . Therefore , early feeding of EdU would generate EdU-positive precursors that in turn would give rise first to EdU-positive prelamellocytes and then to lamellocytes . To test this prediction , we fed larvae with EdU at two early time points after infection ( 4–8 h and 2–12 h ) , put them back on normal food , and analyzed hemocytes 28 h after infection ( Fig 6A ) . At 28 h , approximately half of all hemocytes of infected larvae had incorporated EdU ( Fig 6B” and 6C ) . Because the effects of feeding with EdU in these two experiments were similar , we pooled the results when looking at individual cell types . Indeed , 50–75% of prelamellocytes and 80–100% of lamellocytes were EdU-positive . The fraction of EdU-positive plasmatocytes , activated plasmatocytes , and lamelloblasts was reduced in comparison to the previous time point ( Fig 6B” and 6D ) . Lamellocytes have so far been regarded as terminally differentiated and non-dividing cells [47] , but we found that most lamellocytes were EdU-positive ( Figs 6D and 7A ) . To ascertain that the incorporation of EdU was due to an earlier cell division event in precursor cells , namely lamelloblasts and prelamellocytes , we double-labeled hemocytes with EdU and HmlΔ;He>S/G2/M-Green , using the same feeding scheme as described above . No lamellocyte ever expressed Green alone or in combination with EdU while almost all lamellocytes had incorporated EdU . This indicated that lamellocytes themselves were not dividing nor replicating DNA , but did indeed develop from dividing precursor cells . As shown before , lamelloblasts and all plasmatocyte subtypes , but also prelamellocytes were proliferating ( Fig 7A–7C ) . We also found EdU-positive prelamellocytes during a later feeding scheme ( Fig 6A , 6B”‘ and 6D ) . This suggests that prelamellocytes were still dividing 28–32 h after infection , giving rise to non-dividing lamellocytes . We corroborated our FACS results by imaging EdU-labeled hemocytes of three feeding schemes and obtained similar results ( S10 and S11 Figs ) . We recently showed that the peptide Edin is required for the normal wasp-induced recruitment of plasmatocytes into the circulation from the sessile compartment . When we suppressed edin expression in the fat body , total cell numbers were reduced 14 h after infection , and at 48 h total plasmatocyte numbers did not rise above control levels [48] . We now explored in detail how the different hemocyte classes were affected when we manipulated edin expression . We suppressed or overexpressed edin in the fat body and assessed blood cell numbers by flow cytometry 14 h after infection by L . boulardi . As expected , total blood cell numbers were significantly reduced when an edin RNAi construct was expressed in the fat body , while the effect of edin overexpression , if any , was not statistically significant ( Fig 9A ) . The effect of edin RNAi was most evident with lamelloblasts . Their number was reduced to less than half ( Fig 9B’ ) . Also prelamellocytes were reduced in edin-depleted larvae ( Fig 9B’ ) , but few prelamellocytes had formed at this time point and the effect of edin suppression was not statistically significant . Activated plasmatocytes were slightly reduced when edin was suppressed ( Fig 9B ) . Monoclonal antibodies have been widely used to define different Drosophila hemocyte populations , as well as to identify proteins with hemocyte-specific functions [28] . The P1 antibody recognizes a phagocytosis receptor , NimC1 , which is known to be expressed by cells with plasmatocyte morphology . Several antibodies , Atilla/L1 , L2 , Myospheroid/L4 , and L6 ( the L-antibodies ) , detect different proteins on lamellocytes [4 , 49 , 50] . We were therefore interested to see how these antigens were distributed among the hemocyte classes described here . We used these antibodies to stain hemocytes from uninfected and L . boulardi-infected Me/w larvae at different time points . As expected , NimC1 was expressed by all eaterGFP-positive cells derived from uninfected larvae . A small proportion of these cells also expressed the L2 and L4 antigens at the 28 and 48 h time points ( Fig 10A ) . In infected animals , lamellocytes were always NimC1-negative and were stained with all L-antibodies . All other hemocyte types consistently expressed NimC1 ( Fig 10A and S12 Fig ) , but the tempo-spatial patterns of L-antigen expression in them were more complex . Generally only a minority of plasmatocytes and lamelloblasts expressed these antigens ( < 30% ) . L6 was previously exclusively detected in mature lamellocytes [21] . In our experiments , L6 was also the least prevalent L-antigen to be expressed in hemocyte types other than lamellocytes , but we did observe some L6-positive activated plasmatocytes and prelamellocytes ( Fig 10A , S12L–S12O Fig , Table 1 ) . L4 was expressed in more than 50% of plasmatocytes , activated plasmatocytes , and lamelloblasts already 18 h after infection . At 28 h after infection , half of the activated plasmatocytes were positive for all L-antigens , but the number of stained cells decreased at the 48 h time point ( Fig 10A ) . A high but variable fraction of prelamellocytes stained with L-antibodies . Except for L2 , the expression of these markers all dropped at 48 h . A similar trend was obvious in the different plasmatocyte lineage cells . Prelamellocytes and type II lamellocytes were scarce in the circulation , and were detected in sufficient numbers only 18 h after infection . All type II lamellocytes were P1- and L4-positive , while being negative for L2 and L6 , and 83% expressed L1 ( Table 1 , S12K–S12O’ Fig ) . Also on the wasp egg type II lamellocytes expressed P1 ( Fig 10B–10B”‘ ) , L1 ( Fig 10D–10D”‘ ) , and L4 ( Fig 10C–10C”‘ ) . Plasmatocytes on the wasp eggs showed varying expression of L1 and L4 and expressed P1 ( Fig 10B–10D”‘ ) . Prelamellocytes were L1 and L4 positive , and a large majority of them expressed also NimC1 ( 83% ) . L2 and L6 were expressed in 50% and 30% of prelamellocytes , respectively ( Table 1 ) . In conclusion , L1 , L2 , L4 , and L6 were detected in all lamellocytes , and to a variable extent in their likely precursors . However , they were also detected in activated plasmatocytes and could therefore be regarded as general indicators of hemocyte activation rather than specific markers of lamellocytes . The same could be said for the msnCherry in vivo marker .
The switch from steady-state to infection-induced hematopoiesis in Drosophila melanogaster is marked by the generation of a new blood cell type , the lamellocyte . Three different models for lamellocyte hematopoiesis have been proposed . Firstly , prohemocytes in the lymph glands self-renew and directly transform into lamellocytes that are released into the circulation [15 , 16 , 51] . Secondly , prohemocytes from the lymph glands [52] , or putative prohemocytes in the circulation [20] , develop into plasmatocytes , which transdifferentiate via so-called podocytes into lamellocytes [20 , 52] . Thirdly , peripheral plasmatocytes of procephalic origin transdifferentiate directly into lamellocytes [21–23] . Nonetheless , the dynamics of lamellocyte hematopoiesis remain largely elusive . Here we present a two-lineage model for lamellocyte hematopoiesis , where one type of lamellocytes is generated from the plasmatocyte lineage , by direct transdifferentiation of plasmatocytes on the surface of the parasite , and the other from a designated lamellocyte lineage , with infection-induced lamelloblasts that differentiate into circulating lamellocytes ( Fig 11 ) . Lamelloblasts are characterized by the expression of the plasmatocyte markers eaterGFP and NimC1 , albeit the eaterGFP expression level is ten times lower in lamelloblasts than in plasmatocytes . Therefore , we first assumed that lamelloblasts might be generated from plasmatocytes by downregulating eaterGFP or via the cell division of plasmatocytes , which would dilute the GFP fluorescence . But several arguments speak against these ideas . Firstly , as GFP is a highly stable molecule with a half-life of 24 hours or more [53 , 54] , it seems unlikely that downregulation would result in such a large difference in GFP expression after just one round of cell division . Secondly , lamelloblasts appear suddenly 8 h after infection , without the presence of obvious precursors among the circulating cells . The lamelloblast count increased from zero to more than 1000 cells in only six hours , whereas plasmatocyte numbers remained at a constant level . Producing this many lamelloblasts in one cell division would entirely deplete the plasmatocyte pool . Asymmetric cell division could in principle have generated cells with reduced levels of GFP expression , but we never observed mitotic plasmatocytes with unequal distribution of nuclear GFP expression . Furthermore , lamelloblasts are a uniform population of small cells with lower granularity than observed in plasmatocytes . Several other studies attribute similar features to prohemocytes [15 , 20 , 21 , 52] . Taken together , these features establish lamelloblasts as a population that is clearly distinct from plasmatocytes and suggest a non-plasmatocyte origin for these cells . Several of our findings imply that lamelloblasts derive directly from sessile prohemocytes . We showed that knocking down the cytokine Edin in the fat body reduced the number of lamelloblasts in the circulation . Furthermore , we previously found that sessile cells are not released into the circulation in response to a wasp infection in edin knockdown larvae [48] . This indicates that the precursor cells of lamelloblasts likely reside in the sessile tissue . In addition , the Eater protein was originally described as a phagocytosis receptor on plasmatocytes [55] , but recently it was shown that it is also required for the attachment of hemocytes to the sessile compartment [56] . This might suggest that the low expression level of eaterGFP in lamelloblasts induces their release from the sessile islets . Márkus et al . [18] found that cells expressing neither plasmatocyte nor lamellocyte antigens were lost from the sessile population after a wasp infection and that transplanting sessile hemocytes into recipient larvae triggered lamellocyte hematopoiesis in the transplanted cells . This shows that sessile hemocytes can be a source of lamellocytes . The relative contribution of lymph glands to circulating hemocytes during the immune response is still uncertain . Lymph glands release prohemocytes , plasmatocytes , and lamellocytes into the circulation [21] , but only after the immune response against the wasp egg has already started [18] . Furthermore , we show that even though the primary lymph gland lobes stay intact after a L . heterotoma infection , all hemocyte types of the lamellocyte lineage develop normally . Still , the lymph glands likely contribute to the population of lamellocytes or their precursors at later time points after an infection . We confirmed that lamellocytes are terminally differentiated and non-mitotic [15 , 20 , 47] , but nevertheless we detected EdU-positive lamellocytes after a wasp infection . Biosynthetically active cell types are known to undergo endocycles characterized by the uncoupling of DNA-replication from mitosis . Endoreplicating cells typically go through the S- and G1-phases of the cell cycle [57] . Therefore EdU-incorporation in lamellocytes could be due to endoreplication , but the absence of >S/G2/M-Green expression in lamellocytes indicates that DNA-synthesis is quiescent . Although we cannot entirely exclude that lamellocytes endoreplicate , we suggest that they originate from mitotically active precursor cells , namely lamelloblasts and prelamellocytes . The plasmatocyte lineage originates from procephalic plasmatocytes . At the time point when the wasp eggs hatch , activated plasmatocytes appear in large numbers . This suggests that plasmatocytes play an important role in the defense response , although we did not see them on the wasp egg . When plasmatocytes are activated they become more granular , grow in size , and accumulate cytoplasmic mCherry-positive foci . The granular mCherry fluorescence in activated plasmatocytes may indicate the phagocytosis of lamellocyte-derived material , but the expression of lamellocyte antigens might also signify the general activation of the immune system . An important question is how the hemocyte classes in Drosophila can be homologized to the blood cells of other species . Unfortunately , the naming of Drosophila hemocytes is not congruent with the generally accepted terminology for other insect orders , including other dipterans . Drosophila plasmatocytes are structurally and functionally very similar to the professional phagocytes of other insects , usually called granulocytes or granular cells , and these cell types are considered homologous [3 , 58] . On the other hand , general insect terminology reserves the term plasmatocyte for a granulocyte-like , but agranular , class of cells that actively participate in the encapsulation of parasites , much like the Drosophila lamellocytes [3 , 58] . Our observation that Drosophila lamellocytes actually originate from a group of round cells of low granularity , the lamelloblasts , suggests that the lamellocyte lineage may indeed be homologous to the plasmatocytes of other insects . Notably , hemocytes of lamellocyte morphology are only found among the Drosophila species of the melanogaster subgroup [59] , although lamellocyte-like cells have been described in several other drosophilids [59 , 60] . Instead of lamellocytes , some drosophilids have evolved other bizarre hemocyte types that participate in the encapsulation of parasitoid wasps , such as the hairy pseudopodocytes of the obscura group [61] and the highly motile multinucleated giant hemocytes of the ananassae subgroup [62] . In the drosophilid Zaprionus indianus and several Drosophila species , spindle- or thread-shaped nematocytes appear together with lamellocyte-like cells [60] . A parsimonious interpretation of these observations is that an ancestral hemocyte class , specialized in the encapsulation of parasites , has undergone rapid and diversifying evolution in the Drosophila lineage . Homologies between Drosophila and human blood cells remain entirely speculative . Indeed , it is not unlikely that different types of blood cells evolved independently in vertebrates and arthropods . Still , the activation of plasmatocytes in the plasmatocyte lineage can be seen as an interesting analogy to the transformation of monocytes into macrophages . Peripheral plasmatocytes proliferate by self-renewal [19] and their numbers increase during larval development [20 , 49] . Hemocyte numbers have also been shown to increase after a wasp infection [20 , 63 , 64] . This increase has been linked to the release of cells from the sessile compartment [17 , 18] and from the lymph glands [3 , 15 , 21] . Our results show that the demand-adapted hematopoiesis of the lamellocyte and plasmatocyte lineages is reason for the increase in cell counts after a wasp infection . Moreover , hemocytes divide on the wasp egg and in the sessile compartment . Infection-induced mitosis has been observed in Anopheles gambiae [65 , 66] , but to our knowledge this has not previously been demonstrated for immune-induced cell types in Drosophila . In mammals , on the other hand , demand-adapted hematopoiesis is a well described trait of the immune response and is characterized by the increase of cell numbers several-fold over the steady-state levels of blood cell production [67–69] . Recently , subpopulations of tissue macrophages derived from embryonic cells were also found to divide in situ rather than being replenished by myelopoiesis [70 , 71] . Taken together , the immune response after wasp infection is reminiscent of the demand-adapted hematopoiesis in mammals . Antibodies have been instrumental in defining blood cell populations in Drosophila larvae , where the expression of the P1/NimC1 antigen marks plasmatocyte identity and the expression of the L-antigens lamellocyte identity [28] . eaterGFP and msnCherry have been introduced as specific markers for plasmatocytes and lamellocytes respectively [30 , 32] . However , after immune activation , cells with plasmatocyte morphology express varying levels of L-antigens , indicating that they represent intermediate cell types [4 , 21] . Similarly , we show that the expression of eaterGFP and msnCherry is not restricted to plasmatocytes or lamellocytes , but that cell populations expressing both reporter constructs exist . Available plasmatocyte and lamellocyte markers unambiguously define unchallenged plasmatocytes and fully differentiated lamellocytes , respectively , but because of the dynamic nature of the immune response a combination of reporter constructs , or the corresponding plasmatocyte and lamellocyte antibodies , have to be used in order to define the blood cell lineages . In conclusion , flow cytometry in combination with fluorescent hemocyte markers is an accurate and fast method for the differential counting of Drosophila blood cell populations from single larvae , and is potentially useful for the high throughput analysis of hemocyte phenotypes in genetic screening , or drug testing in vivo . Overall , our findings show that lamellocytes are generated in parallel by the transdifferentiation of plasmatocytes and de novo from lamelloblasts . However , the origin of lamelloblasts remains uncertain . The challenge is now to create appropriate genetic tools to track and experimentally manipulate individual hemocyte populations and to understand how the as yet elusive signals from different tissues , like the fat body and somatic muscles [44 , 48 , 72] , integrate to shape a functional immune response .
We maintained the wasp strains Leptopilina boulardi G486 ( L . boulardi ) , Leptopilina heterotoma strain 14 ( L . heterotoma ) on D . melanogaster Canton S , and Leptopilina clavipes ( L . clavipes ) on D . virilis . Wasps were collected into vials containing apple juice agar . All fly cultures were maintained on mash potato food . We generated a double reporter line , which we refer to as Me , by meiotically recombining the X chromosome-linked eaterGFP with a nuclear localization signal and cytoplasmic MSNF9MOmCherry ( msnCherry ) constructs . Crosses of Me with w1118iso ( Me/w ) were used for most experiments . We recombined the second-chromosome-linked eaterDsRed and HmlΔ-GAL4 ( HmlΔ> ) constructs and combined these flies with msnCherry to create msnCherry;eaterDsRed , HmlΔ> . In addition , we recombined the third-chromosome-linked UAS-S/G2/M-Green with He-GAL4 ( He> ) to create w;He>S/G2/M-Green . For the edin experiments , we used the fly lines published in [48] . The hemocyte double reporter was always homozygous for the edin RNAi and its control ( Me;Fb-GAL4 crossed to Me;edinKK109528 and Me crossed to Me ) and heterozygous for UAS-edin ( Me;Fb-GAL4 crossed to UAS-edin and Me crossed with UAS-edin as control ) . All wasp species and fly stocks used in this study as well as their origins are summarized in S1 and S2 Tables . For all experiments , we crossed 20 female and ten male flies . When the fly cultures started to produce eggs , the flies were tipped daily and the vials containing eggs were moved to a 25 or 29°C temperature controlled incubator , whereas the parental crosses were kept at room temperature . On the third day after egg laying , we added twenty female and male wasps to the fly larvae cultures and allowed the wasps to infect fly larvae at room temperature for 2 h , removed the wasps and placed the fly vials back into 25 or 29°C . In order to determine whether the cellular immune system of Drosophila larvae had mounted an encapsulation response , we dissected larvae 27–29 h after infection in water on twelve well slides and scored the degree of encapsulation according to the following phenotypes: type 1: no melanin deposit on the wasp egg; type 2: melanin deposit on the wasp egg on less than 50% of wasp egg length; type 3: melanin deposit on wasp egg 50–99% of wasp egg length; type 4: wasp egg completely melanized and black . We pooled type 2 , 3 and 4 and referred to them as infection type melanized wasp eggs and to type 1 as infection type non-melanized wasp eggs . Correspondingly , we investigated if the larval immune system had killed wasp larvae 48–50 h after infection . We dissected fly larvae as described above and scored the phenotypes according to the following categories: L ( living , non-melanized wasp larvae or eggs ) : living wasp larvae in the body cavity of the fly larvae , no melanization present; LM ( living , melanized ) —living wasp larvae and remnants of melanized capsules or melanized wasp eggs or wasp larvae; M ( dead , melanized ) –killed and melanized wasp eggs or wasp . We grouped L and LM under the infection type category living wasp larvae , and M under killed wasp larvae . We determined the encapsulation and killing ability of the Drosophila immune system with all three Leptopilina species . For the encapsulation as well as the killing experiments we scored 50 infected larvae of three independent crosses . In order to detect changes in hemocyte types and numbers during the cellular immune response to a wasp infection on a narrow time scale , we analyzed hemocyte samples of at least ten individual L . boulardi-infected larvae of each available infection type and ten age-matched uninfected control larvae every second hour until 50 h after infection . Furthermore , we analyzed hemocyte samples of age-matched control and L . boulardi-infected larvae at 20 , 30 , and 48 h after infection raised at 25°C to control for temperature effects . Finally , we analyzed hemocyte samples of at least ten larvae infected by L . heterotoma and L . clavipes and age-matched uninfected control larvae 8 , 12 , 14 , 18 , 20 , 22 , 24 , 28 , 38 , and 48 h after infection . We collected larvae and washed them carefully in water with a brush until they were clean , dried them on tissue paper before we placed individual larvae into 20 μl sterile filtered ( 0 . 45 μm , ministart syringe filter ) phosphate-buffered saline ( PBS: 0 . 14 M NaCl , 0 . 0027 M KCl , 0 . 01 M Phosphate pH 7 . 4 ) with 8% bovine serum albumin ( BSA , Sigma ) on 12-well slides ( Thermo Scientific ) . Then , we dissected the larvae with biology tip forceps ( Fine Science Tools ) , careful not to puncture the intestinal tract , gently shaking the carcasses to bring more lose blood cells into suspension . At this point , the infection status of the larvae was visually inspected . We removed the carcasses and pipetted the hemocyte samples into earlier prepared tubes containing 80 μl PBS with 8% BSA and analyzed the samples with a flow cytometer . For imaging , the blood cells remained on the 12-well slides and were allowed to spread in a humidified chamber for one hour . We used a Zeiss LSM 780 laser scanning confocal microscope mounted on a Cell Observer microscope for imaging DAPI ( pulsed diode laser 405 nm ) , GFP ( multiline Argon laser 488 nm ) , DsRed ( multiline Argon laser 514 nm ) , mCherry ( HeNE-laser 594 nm or diode laser 561 nm ) , Alexa Fluor 647 ( InTune-tunable pulsed laser 628 nm ) , and Alexa Fluor 680 ( InTune-tunable pulsed laser 628 nm ) . A Zeiss AxioImager M2 equipped with an ApoTome 2 and COLIBRI LED was used to image Alexa Fluor 405 ( LED 380 nm ) , GFP ( LED 470 nm ) , mCherry ( LED 555 nm ) , and DIC with an AxioCam HRm CCD camera . A BD Accuri C6 flow cytometer was used to analyze cell numbers and cell types . We analyzed 30 μl of the hemocyte suspension . GFP-positive cells were recorded by the FL1 detector equipped with a 510/15 BP filter and mCherry-positive cells by the FL3 detector with a 610/20 BP filter . Both channels were excited using a 488 nm blue laser . In order to control fluorescence spill over , we pooled hemocytes of three to five late L3 w larvae as a negative control , hemocytes of eaterGFP females crossed to w males as a GFP-only control , and hemocytes of wasp-infected larvae ( 48 h pi ) of a cross of msnCherry females to w males as a mCherry-only control . We corrected the spillover of GFP into the FL3 detector by subtracting 8% of FL1 . mCherry did not spill into FL1 . A description of the gating strategy can be found in S2 Fig . We used hemocytes of ten pooled late L3 w larvae that were previously fed with EdU and had undergone the Click-iT Plus EdU Flow Cytometry Assay protocol with Alexa Fluor 647 picolyl azide as Alexa647-only control . EdU-Alexa647 was detected by FL4 equipped with a 675/25 filter . We corrected the spillover of Alexa647 by subtracting 1 . 61% of FL3 . For a detailed description of the gating strategy see S9 Fig . To estimate hemocyte size , we used a standard kit of Polystyrene particles with the diameters of 2 . 1 μm , 3 . 4 μm , 5 . 1 μm , 7 . 4 μm , 10 . 5 μm , and 14 . 7 μm ( Spherotech Inc . ) . We diluted the particles according to the manufacturer’s instructions in PBS and ran 5000 events per bead size . A BD FACSAria II instrument with the FACSDiva v8 . 0 software was employed to sort the different fluorescent hemocyte populations . Hemocytes of w were used as a negative control , hemocytes of infected msnCherry/w as an mCherry-only control , and hemocytes of uninfected Me/w served as the GFP-only control to set the gates for cell sorting . Hemocytes of Me/w infected by L . boulardi and L . clavipes collected 28 h pi were used to retrieve all hemocyte populations . Yield was favored over specificity in the sorting process . After sorting , the cells were pipetted onto 12-well slides to spread for 1 h in a humidified chamber and treated accordingly to the immunohistochemistry protocol ( see below ) . Finally the cells were mounted with ProLong Gold Antifade Mountant with DAPI ( Life Technologies ) and imaged with a Zeiss LSM 780 confocal microscope . We used uninfected and infected Me/w larvae , carefully cleaned them in water with a brush , and mounted them with their dorsal side facing upwards in a drop of ice-cold 100% glycerol on a glass slide . Double-sided sticky tape was used to attach the cover slip tightly onto the larvae . MsnCherry/w; HmlΔ>GFP/+ larvae were used instead of Me/w larvae at early time points due to low fluorescence of the Me reporter in whole larval mounts . The mounted larvae were kept at -20°C for 20 minutes or at 4°C for four to eight hours prior to imaging in order to make sure the larvae were not moving during the imaging . Larvae were imaged with a Zeiss Apotome . 2 microscope with an EC Plan Neofluar 5x/0 . 16 objective ( pixel size 6 . 45 μm2 ) or with an EC Plan Neofluar 10x/0 . 30 objective ( pixel size 6 . 45 μm2 ) . We processed all whole mount larval images with and without structured illumination to ascertain the presence of lymph glands . Primary lymph gland lobes are often covered by the fat body . Optical sectioning causes imaging artifacts that result in erasing lymph gland lobes in the apotomized image . We therefore determined the presence of primary lymph gland lobes by analyzing the raw data Z stacks . We dissected out wasp eggs at several time points after infection , fixed them in 4% paraformaldehyde , washed and mounted them in 50% glycerol in PBS . Then wasp eggs were imaged with a Zeiss Apotome . 2 microscope with an EC Plan Neofluar 20x/0 . 50 objective ( pixel size 12 . 90 μm2 ) . We used the Click-iT Plus EdU Alexa Flour 647 Flow Cytometry Assay Kit and the Click-iT EdU Alexa Fluor 647 Imaging Kit ( Life technologies ) to mark hemocytes in the S-Phase of the cell cycle . The preparation of EdU-containing food was identical for imaging and flow cytometry . We melted the fly food , added red food coloring , and let the food cool down to below 70°C before adding EdU with a final concentration of 0 . 2 mM . When the food had cooled down entirely , age-matched control and infected larvae were allowed to feed on it for 4 or 12 h at room temperature . Feeding of EdU food was ensued by the following incubation schemes on normal food until the larvae were dissected . Feeding from 2–6 h , 4–8 h , and 2–12 h pi and analyses at 8–10 h , 8–10 h , and 12–14 h pi , respectively , answered the question , which cell types divided at early time points . Feeding from 4–8 h and 2–12 h and analyses at 28–30 h pi helped to find out if any population would give rise to lamellocytes . And finally , feeding from 28–32 h pi and analysis at 48 h pi shed light on whether activated plasmatocytes and lamellocytes divided . Only larvae with red food coloring in their intestinal tract were dissected to ensure that they had consumed EdU . For imaging , we pooled hemocytes of two larvae per well . The cells were treated and mounted as described above . Instead of adding the primary antibody , we proceeded according to the protocol of the manufacturer’s instructions with the following exception: We reduced the amount of the reaction cocktail to 1/8 of the suggested amount . For flow cytometry , 40 to 60 larvae were dissected for the early feeding and dissection schemes and about 20 for the late . We proceeded according to the manufactures instruction with the following exceptions: We pooled hemocytes and centrifuged them at 2500 x g for 5 min . We washed the cells with 500 ul of 1% BSA in PBS . We used 50 μl of Click-iT fixative . We re-suspended the cells in 100 μl of Click-iT saponin-based permeabilization and wash reagent , and analyzed the cells by flow cytometry as described previously . In order to further investigate the development of lamellocytes type II on wasp eggs , we infected Me/w by L . boulardi , dissected out the eggs 16 h after infection , and imaged them every 25 min for 14 h to record changes in hemocyte populations . Glass bottom culture dishes ( MatTek ) were coated with 1% Gelatine ( Sigma ) in PBS for one hour . The culture medium was Schneider´s medium ( Sigma ) with 25% FBS ( Sigma ) [73] . The eggs were carefully placed into glass bottom dishes and allowed to settle for 30 min before they were imaged with a Zeiss LSM 780 confocal microscope using a 20x/0 . 8 Apochromat objective equipped with DIC M27 . 3D stacks with 1 μm slice intervals were acquired every 25 min for 14 h . The time lapse series was then processed with ImageJ and iMorph to assemble a time lapse movie . NimC1/P1 , Atilla/L1 , L2 , L4 and L6 hemocyte-specific antibodies [28] were used to stain hemocytes of five to six individual infected and age-matched uninfected larvae at 8 , 18 , 20 , 28 and 48 h after infection . The infections and dissections of the larvae were done as described above , and each antibody was applied on a separate set of samples . Dissected hemocytes were allowed to spread on glass slides in humidified chambers for approximately 1 h . The cells were fixed with ice-cold 4% paraformaldehyde in PBS for 10 min and washed three times with ice-cold PBS , followed by permeabilization with 0 . 1% Triton X-100 for 5 min . After washing three times with PBS , cells were blocked with 3% BSA in PBS for 1 h at room temperature . After removing the blocking solution , 20 μl of the primary antibody supernatant was added for an overnight incubation at 4°C . Cells were again washed three times with PBS and incubated with a goat anti-mouse Alexa Fluor 680 secondary antibody ( Life Technologies ) in 1% BSA in PBS ( 1:500 ) for 1 h at room temperature in the dark . Finally , the cells were washed and mounted with ProLong Gold Antifade Mountant with DAPI ( Life Technologies ) and high precision cover glasses ( Zeiss ) . The cells were imaged using a Zeiss LSM 780 confocal microscope with a Plan Apochromat 63 x/1 . 4 oil immersion objective . The images were processed using ImageJ . The negative controls ( either missing primary or secondary antibody ) were used to set a threshold level for positive antibody staining . On each image , we manually classified the cells into five different subtypes based on their GFP and mCherry expression and morphology as described above ( Fig 1 ) . Then we calculated the ratio of cells stained with a specific antibody to total number of that cell type at each time point . The amount of different cell types based on eaterGFP and msnCherry expression varied considerably among the time points after infection ( Fig 5 ) . The total number of cells analyzed per antibody per time point was between 69 and 256 ( generally over 100 ) , except for the 8–10 h time point , where the cell numbers were generally low , around 20 . Antibody—time point—cell type combinations with less than ten cells were excluded from the analysis . Wasp eggs were dissected 14–16 h after infection by L . boulardi in PBS . Eggs were stained with NimC1/P1 , L4 , and Atilla/L1 antibody as described for antibody staining of bled hemocytes . Alexa Fluor 405 was used as the secondary antibody . Wasp eggs were imaged with a Zeiss Apotome . 2 microscope with a EC Plan Neofluar 20x/0 . 5 objective ( pixel size 12 . 90 μm2 ) . For all statistical analysis we used R ( version 3 . 1 . 3 ( 2015-03-09 ) —"Smooth Sidewalk" Copyright ( C ) 2015 The R Foundation for Statistical Computing ) . We used statistics to find out whether the infection type affected the total number of blood cells . The only time points after L . boulardi infection when more than one infection type was present were 36 to 50 h after infection , and for L . clavipes 24 h after infection . We also wanted to know if edin-knock down affected total number of blood cells and the number of individual blood cell types . Finally , we compared the size and granularity of the different hemocyte types . First , we tested the data for normality and homoscedasticity . When these requirements were met , we used two-way ANOVA with an interaction term followed by Tukey´s HSD test . If the requirements were not met regardless of transformation , we used the non-parametric Kruskal-Wallis rank sum test and the independent two-group Mann-Whitney U Test for pairwise testing . In the edin experiments our data contained two or three independent replicates for each genotype . Therefore , we separately tested if replicates and if genotypes differed significantly . Then we made pairwise comparisons between edin knockdown and overexpression to their respective controls . For plotting we used ggplot2 [74] . | Hematopoiesis is regulated by a conserved set of signaling pathways in flies and men . While the implication of multiplex flow cytometry has led to the discovery of a plethora of new human blood cell types , it has not routinely been used to study fly hematopoiesis . We present here the application of flow cytometry with in vivo blood cell reporter constructs to study infection-induced hematopoiesis in blood samples from single fly larvae . We put forward a new perspective on Drosophila hematopoiesis , based on our discovery of new blood cell types . We show a switch from steady-state to demand-adapted hematopoiesis in fly larvae , which corresponds well to the described demand-adapted hematopoiesis after infection and inflammation in humans . Our results provide new insights into the dynamics of infection-induced hematopoiesis in fly larvae and increase the versatility of the fly as a model system to study the cellular innate immune system . | [
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"biol... | 2016 | Transdifferentiation and Proliferation in Two Distinct Hemocyte Lineages in Drosophila melanogaster Larvae after Wasp Infection |
The human malaria parasite Plasmodium vivax infects red blood cells through a key pathway that requires interaction between Duffy binding protein II ( DBPII ) and its receptor on reticulocytes , the Duffy antigen/receptor for chemokines ( DARC ) . A high proportion of P . vivax-exposed individuals fail to develop antibodies that inhibit DBPII-DARC interaction , and genetic factors that modulate this humoral immune response are poorly characterized . Here , we investigate if DBPII responsiveness could be HLA class II-linked . A community-based open cohort study was carried out in an agricultural settlement of the Brazilian Amazon , in which 336 unrelated volunteers were genotyped for HLA class II ( DRB1 , DQA1 and DQB1 loci ) , and their DBPII immune responses were monitored over time ( baseline , 6 and 12 months ) by conventional serology ( DBPII IgG ELISA-detected ) and functional assays ( inhibition of DBPII–erythrocyte binding ) . The results demonstrated an increased susceptibility of the DRB1*13:01 carriers to develop and sustain an anti-DBPII IgG response , while individuals with the haplotype DRB1*14:02-DQA1*05:03-DQB1*03:01 were persistent non-responders . HLA class II gene polymorphisms also influenced the functional properties of DBPII antibodies ( BIAbs , binding inhibitory antibodies ) , with three alleles ( DRB1*07:01 , DQA1*02:01 and DQB1*02:02 ) comprising a single haplotype linked with the presence and persistence of the BIAbs response . Modelling the structural effects of the HLA-DRB1 variants revealed a number of differences in the peptide-binding groove , which is likely to lead to altered antigen binding and presentation profiles , and hence may explain the differences in subject responses . The current study confirms the heritability of the DBPII antibody response , with genetic variation in HLA class II genes influencing both the development and persistence of IgG antibody responses . Cellular studies to increase knowledge of the binding affinities of DBPII peptides for class II molecules linked with good or poor antibody responses might lead to the development of strategies for controlling the type of helper T cells activated in response to DBPII .
Plasmodium vivax infects human reticulocytes through a major pathway that requires interaction between an apical parasite protein , the Duffy binding protein ( DBP ) , and its cognate receptor on reticulocytes , the Duffy antigen/receptor for chemokines ( DARC ) [1–3] . Although most individuals lacking DARC on their red blood cells ( RBCs ) are naturally resistant to P . vivax [1] , some infections occur in DARC-negative individuals living in vivax malaria endemic areas [4–6 , 70] . So far , no alternative ligand facilitating the binding of P . vivax to reticulocytes has been identified , which makes the DBP one of the most promising P . vivax vaccine targets [8] . The importance of the interaction between DBP ( region II , DBPII ) and DARC to P . vivax infection has stimulated a significant number of studies on DBP antibody responses ( reviewed in [8] ) . The available data demonstrate that naturally occurring antibodies to DBP are prevalent amongst individuals living in P . vivax endemic areas , and that these antibodies can inhibit the DBPII-DARC interaction [7 , 9–12] . Even though DBPII-specific binding inhibitory antibodies ( DBPII BIAbs ) seem to confer a degree of protection against blood stage infection [11] , the majority of people naturally exposed to P . vivax do not develop a DBPII BIAbs response [8] . In the Amazon Basin , for example , this inhibitory activity was detected in only one third of malaria-exposed subjects [8 , 13] . Similarly , less than 10% of children from Papua New Guinea ( PNG ) with immunity to malaria had acquired high levels of DBPII BIAbs [11] . Given the significant differences in epidemiology and parasite genetics between the Amazon Basin and PNG , the fact that the DBPII BIAbs response is relatively low but also remarkably stable over time is particularly intriguing . The reasons for the low immunogenicity of DBPII are not clear , but may be linked to a complex immune response driven by genetic diversity in both the parasite and human populations . Several studies have demonstrated the existence of variant specificity in the natural immune response against DBPII , which has been attributed to allelic diversity [12 , 14] . On the host side , recent evidence suggests that host genetic polymorphisms might also affect humoral immunity against DBP [15 , 16] , with DARC polymorphisms thought to affect the ability of DBP antibodies to block parasite invasion [16] . In a previous study , we demonstrated that the naturally acquired BIAbs response tended to be more frequent in heterozygous individuals carrying a DARC-silent allele ( FY*BES ) , which suggested that gene-dosage effect occurred [7] . In this context , we were interested in determining if DBPII non-responsiveness could be associated with variation in the major histocompatibility complex . While malaria infection represents a key selection pressure for the human leukocyte antigen ( HLA ) , and has left clear evolutionary footprints on the alleles observed in different countries [17] , the association between HLA gene expression and responsiveness ( or non-responsiveness ) to defined malaria antigens has produced contradictory results [18–21] . Beyond the extreme genetic diversity of HLA class II , which hinders interpretation of the role of HLA on antibody responses elicited during malaria , most studies rely on antibody prevalence data collected at a single time-point in cross-sectional analysis of a population . Since malaria transmission is intermittent and seasonal in many endemic areas , it is possible that antibody levels fluctuate over time such that individuals could appear to be non-responders on some occasions and responders on others [20] . In the current study , we present data of the first ongoing population-based study of the relationship between HLA class II genes and DBPII immune response . The methodological approach included a community-based open cohort study in an agricultural settlement of the Brazilian Amazon , in which 336 unrelated volunteers were genotyped for HLA class II ( DRB1 , DQA1 and DQB1 loci ) , and their DBP immune responses were monitored over time by conventional serology ( DBPII IgG ELISA-detected ) and functional assays ( DBPII BIAbs ) .
The study was carried out in the agricultural settlement of Rio Pardo ( 1°46’S—1°54’S , 60°22’W—60°10’W ) , in the Presidente Figueiredo municipality , located in the Northeast of Amazonas State in the Brazilian Amazon . The Rio Pardo settlement is located approximately 160 km from Manaus , the capital of Amazonas , along the main access to a paved road ( BR-174 ) that connects Amazonas to Roraima ( Fig 1 ) . The settlement was officially created in 1996 by the National Institute of Colonization and Agrarian Reform ( INCRA ) as part of a large-scale colonization project focused on agriculture and wide-ranging human settlement in the Amazon area [22] . The mean annual temperature is 31°C with a humid climate and an average annual rainfall of 2 , 000 mm per year . The rainy season extends from November to May , and the dry season from June to October . According to a census conducted between September and October 2008 , Rio Pardo has 701 inhabitants , most of whom live on subsistence farming and fishing along the tributaries of the Rio Pardo River . The study population was quite stable . Most residents were native to the Amazon region , and their average age of 28 years roughly corresponded to the time of malaria exposure in the Amazon area [7] . In the study area , migration rates were relatively low , as only 28 ( 8% ) of 336 individuals moved out of the village during the follow-up period . Based on the spleen size of the local children and parasite infection rates , the study area was classified as hypo- to mesoendemic , which is consistent with the general profile of malaria infection for well-established frontier settlements in the Amazon region [23] . The study site and malaria transmission patterns have been described in detail elsewhere [7] . Although P . vivax and P . falciparum are transmitted year round , P . vivax is responsible for about 90% of malaria cases in the region . Similar to other parts of the Brazilian Amazon area [24] , a continuous decrease in the number of malaria cases has been reported in the Rio Pardo community; in 2008 , the local Annual Parasitological Index ( API ) was 131 cases per 1000 inhabitants , while in 2009 the API was 54 . 6 ( Health Surveillance Secretariat of the Brazilian Ministry of Health , SVS/MS ) . In the study area , precarious living conditions , including houses with partial walls and roofs made of tree leaves , increase human-vector contact and reduce indoor residual spraying efficacy [23] . However , while the availability of curative services is limited , a government outpost in the area provides free malaria diagnosis and treatment . The ethical and methodological aspects of this study were approved by the Ethical Committee of Research on Human Beings from the Centro de Pesquisas René Rachou ( Reports No . 007/2006 , No . 07/2009 , No . 12/2010 and No . 26/2013 ) , according to the Resolution of the Brazilian Council on Health-CNS 466/12 . In November of 2008 , 541 of the 701 residents of the settlement ( 77 . 2% ) invited to participate in the study accepted by giving written informed consent , which was also obtained from the next of kin , caregivers , or guardians on the behalf of participating minors . A population-based open cohort study was initiated in November of 2008 , with the following procedures: ( i ) administration of a structured questionnaire to all volunteers to obtain demographical , epidemiological , and clinical data; ( ii ) physical examination , including body temperature and spleen/liver size , recorded according to standard clinical protocols; ( iii ) venous blood collection for individuals aged five years or older ( EDTA , 5 mL ) , or blood spotted on filter paper ( finger-prick ) for those aged <5 years; and ( iv ) examination of Giemsa thick blood smears for the presence of malaria parasites via light microscopy . The geographical location of each dwelling was recorded using a hand-held 12-channel global positioning system ( GPS ) ( Garmin 12XL , Olathe , KS , USA ) with a positional accuracy of within 15 m . At the time of initial enrollment in the study , 222 out of 541 volunteers had no familial relationships with other volunteers , and were consequently selected for HLA genotype and serological assays . Six and twelve months after the initial survey , two similar cross-sectional surveys were carried out . In total , 336 unrelated subjects were enrolled in the study , with 222 examined in the baseline cohort , 249 examined during the 2nd survey ( June , 2009 ) , and 239 during the 3rd survey ( October-November , 2009 ) . A total of 244 ( 72 . 6% ) subjects had consecutive samples taken , and 156 of these ( 64% ) had samples taken in all cross-sectional surveys ( baseline , 6 and 12 month follow-up ) . Malaria infections were diagnosed by microscopy of Giemsa-stained thick blood smears , and by Real-Time PCR amplification of a species-specific segment of the multicopy 18SSU rRNA gene of human malaria parasites . The Giemsa-stained smears were evaluated by experienced microscopists , according to the malaria diagnosis guidelines of the Brazilian Ministry of Health . For Real-Time PCR , genomic DNA was extracted from either whole blood samples collected in EDTA , or from dried blood spots on filter paper using the Puregene blood core kit B ( Qiagen , Minneapolis , MN , USA ) or the QIAmp DNA mini kit ( Qiagen ) , respectively , according to manufacturers’ instructions . Real-Time PCR was performed as previously described [25] . Molecular amplification of the alleles of HLA-DRB1 , HLA-DQB1 and HLA-DQA1 were performed by the PCR-SSO ( polymerase chain reaction , specific sequence of oligonucleotides ) technique , with Luminex technology ( One Lambda Inc . , Canoga Park , CA , USA ) . Briefly , target DNA was PCR-amplified using group-specific primer sets , after the amplified product was biotinylated , which allowed later detection using R-Phycoerythrin-conjugated Streptavidin ( SAPE ) , and hybridized with microspheres linked to specific conjugated fluorescent probes for each HLA allele group ( One Lambda , Canoga Park , CA , USA ) . The fluorescent intensity varied based on the reaction outcome , with an expected intensity of 1000 or more for positive control probes . Reaction readings were carried out by flow cytometry using Luminex technology ( One Lambda ) . Samples were analyzed through the HLA FUSION software ( One Lambda Inc . , San Diego , CA , USA ) . A conventional enzyme-linked immunosorbent assay ( ELISA ) for total IgG antibodies to DBPII was carried out using a recombinant protein that included amino acids 243–573 ( region II ) of the Sal-1 DBPII variant , which is highly prevalent in the study area [23]; the recombinant protein was expressed as a 39 kDa 6xHis fusion protein , as previously described [26] . ELISA was carried out as previously described [27] , with serum samples at 1:100 and DBPII at a final concentration of 3 μg/ml . The results were expressed as reactivity index ( RI ) , calculated by dividing the reading values of the test ( OD values ) by the cut-off ( mean reading for the unexposed group plus 3 SD , n = 30 ) . Values of RI > 1 . 0 were considered positive . COS7 cells ( green monkey kidney epithelium , ATCC , Manassas , VA ) were transfected with the plasmid pEGFP-DBPII , which coded for a common DBPII sequence circulating in the Amazon area [13] . Transfections were performed with lipofectamine and PLUS-reagent ( Invitrogen Life Technologies , Carlsbad , CA ) according to manufacturer’s protocols . Forty-eight hours post-transfection , erythrocyte-binding assays were performed as previously described [10] . Briefly , plasma samples were added at 1:40 , and plates were incubated for 1 hr at 37°C in 5% CO2 . Human O+ DARC+ erythrocytes in a 10% suspension were added to each well ( 200 μl/well ) , and plates were incubated for 2 h at room temperature . After incubation , unbound erythrocytes were removed by washing the wells three times with phosphate buffered saline ( PBS ) . Binding was quantified by counting rosettes observed in 10–20 fields of view ( x200 ) . Positive rosettes were defined as adherent erythrocytes covering more than 50% of the COS cell surface . For each assay , pooled plasma samples from Rio Pardo residents characterized as non-responders by ELISA were used as a negative control ( 100% binding ) . For this purpose , only plasma that did not inhibit erythrocyte binding was pooled for use as the negative control ( usually , 10 plasma samples/pool ) . The positive control included a pool of plasma from individuals with long-term exposure to malaria in the Amazon area . The percent inhibition was calculated as 100 x ( Rc—Rt ) /Rc , where Rc is the average number of rosettes in the control wells , and Rt is the average number of rosettes in the test wells . Plasma samples with more than 50% of binding inhibition were considered positive . To predict HLA-DR/-DQ binding affinities ( IC50 ) we used the P . vivax DBP sequence ( XP_001608387 . 1 ) from the NCBI database . Each potential 15-mer sequence frame was scored using the NetMHCIIpan-3 . 1 server ( http://www . cbs . dtu . dk/services/NetMHCIIpan-3 . 1/ ) , an improved version of the tool that permits a much more accurate binding core identification [28] . Binding affinity was given as the log IC50 value in nanomolar ( nM ) , and the defined thresholds for strong and weak binders were <1 . 7 nM and <2 . 7 nM , respectively . Homology models of the three DRB1 variants were generated using Modeller and Macro Model ( Schrodinger , New York , NY ) using an ensemble of previously solved X-ray crystal structures of the HLA II beta chain ( PDB IDS: 1IEB Chain D , 3LQZ Chain B and 1SEB Chain B; 76% , 67% and 90% sequence identity respectively ) . The alpha chain was modelled using an ensemble of available X-ray crystal structures including PDB IDs: 2Q6W and 4AEN ( Chain D and A respectively , 100% sequence identity ) . As previously described [29 , 30] , the models were then minimized using the MMF94s forcefield in Sybyl-X 2 . 1 . 1 ( Certara L . P . , St Louis , MO ) , with the final structure having more than 95% of residues in the allowed region of a Ramachandran plot . The quality of the models was confirmed with Verify3D . The models of the HLA II complex of the alpha and beta chains were built using X-ray crystal structures of the complex ( PDB ID: 1IEB , 3LQZ , 1SEB , 2Q6W , 4AEN ) to guide protein docking [31] . Two representative DBPII antigenic peptides ( H1: FHRDITFRKLYLKRKL; H3: DEKAQQRRKQWWNESK ) were modelled into each HLA II complex variant using the available crystal structures of the HLA II complexes to guide docking . Binding affinities were predicted using CSM-lig [32] . Model structures were examined using Pymol . The structural consequences of each amino acid difference between the DRB1 variants were analyzed to account for all the potential effects of the mutations [33] . The effects of the variations on the stability of DRB1 and the HLA II complex were predicted using DUET [34] , an integrated computational approach that optimizes the prediction of two complementary methods ( mCSM-Stability and SDM ) . The effect of the differences on the protein-protein binding affinity between the alpha and beta chains to form the HLA II complex were predicted using mCSM-PPI [35] . The effect of the changes on the binding affinity of the HLA II complex for a model peptide were also analysed using mCSM-PPI , as previously described [36] , mCSM-lig [37] , and mCSM-AB [38] . These computational approaches represent the wild-type residues structural and chemical environment of a residue as a graph-based signature in order to quantitatively determine the change upon mutation in Gibb’s Free Energy of stability or binding . A database was created using Epidata software ( http://www . epidata . dk ) . Linear correlation between two variables was determined by using the Spearman’s correlation coefficient . Differences in proportions were evaluated by chi-square ( Χ2 ) test and , differences in medians were tested using either the Mann-Whitney or Kruskal–Wallis tests , with Dunn’s post hoc test , as appropriate . For allelic group comparison , differences in proportion were performed by Z-test or chi-square tests , or Fisher’s exact tests , as appropriate . Alleles frequencies for each locus ( DRB1 , DQA1 , and DQB1 ) were summarized descriptively using frequencies and percentage for immunological categorical variables . Overall associations with immunological responses and alleles from each locus of HLA class II were evaluated by comparing the allele frequencies between seronegative individuals and seropositive individuals from the baseline study using standard contingency tables . Based on the humoral immune response to DBPII from the three cross-sectional surveys , the long-term immune responses against DBPII were grouped into three categories: ( i ) Persistent non-responder ( PNR ) —absence of antibodies against DBPII in all three cross-sectional surveys; ( ii ) transient responder ( TR ) —antibodies detected in at least one cross-sectional survey; ( iii ) Persistent responder ( PR ) —individuals with detectable DBPII antibodies in all three cross-sectional studies . The association between HLA class II alleles ( or haplotypes ) and long-term immune response ( PR or PNR groups ) was analyzed by standard contingency tables ( Chi-square and Fisher’s exact test , as appropriate ) , with two observations per subject ( one for each allele ) . Alleles with a frequency of less than 0 . 01 were not included in the analysis . Additionally , multiple logistic regression models with stepwise backward deletion were built to describe independent associations between covariates and HLA class II alleles or haplotypes and antibodies to DBPII . Covariates were selected for inclusion in the logistic models if they were associated with the outcome at the 15% level of significance in exploratory unadjusted analysis . Logistic regression models included the following covariates: age , gender , exposure to malaria ( time of residence in the endemic area ) , self-reported malaria episodes , recent malaria infection and household location within the study area . Multivariate logistic regression was performed using Stata software version 10 ( Stata Corporation , College Station , TX ) . Only variables associated with statistical significance at the 5% level were maintained in the final models . To avoid type II errors due to overly severe correction , statistical adjustment for multiple tests were not used [39 , 40] . Type I errors were reduced by using multiple logistic regression models with stepwise backward deletion . Estimated genotype distribution between the observed and expected allelic frequencies was tested using the method described by Guo and Thompson [41] to verify Hardy-Weinberg equilibrium . Because the gametic phase was unknown , maximum-likelihood estimates of haplotype frequencies were obtained from multilocus genotype data and computed using the expectation-maximization ( EM ) algorithm [42] . Both procedures were performed using Arlequin software version 3 . 5 ( http://cmpg . unibe . ch/software/arlequin35/ ) [43] .
We evaluated DBPII antibody responses in 336 unrelated subjects with a median of age 41 years and a 1 . 3:1 male-female ratio ( Table 1 ) . Age was significantly associated with a subject’s time of malaria exposure in the Amazon area ( r = 0 . 82; p<0 . 0001 , Spearman’s correlation test ) . At the time of the first blood collection , the overall prevalence of malaria was 5% , with 14 out of the 17 ( 82% ) infections caused by P . vivax and 3 ( 18% ) by P . falciparum . No P . malariae or mixed Plasmodium infections were diagnosed by either microscopy or Real-Time PCR . The 336 participants were followed up for an average of 7 . 5 months ( 10 days to 12 months ) , thus representing 2 , 514 person-months of follow-up . Based on parasitological-confirmed cases , the incidence rates of P . vivax malaria were 1 . 03 episodes per 100 person-months ( 95% confidence interval [CI] of 0 . 69–1 . 49/100 person-months ) and 0 . 19 per 100 person-months for P . falciparum ( 95% CI of 0 . 03–0 . 32/100 person-month ) . One hundred and twenty-two ( 36% ) of the individuals enrolled in the study had ELISA-detected IgG antibodies to the main variant of DBPII circulating in the study area ( Sal-1 ) ( Table 1 ) . Because not all DBPII IgG antibodies are able to block the interaction between the ligand ( DBPII ) and its receptor on the RBC surface ( DARC ) , we evaluated the functional properties of the anti-DBPII antibodies . Due to the methodological constraints of performing functional assays , measurement of DBPII binding inhibitory antibodies ( BIAbs ) was performed on a representative subset of the study population comprising 164 individuals , matched for age , sex , malaria exposure and DARC alleles; 58 ( 35 . 4% ) of these individuals showed BIAbs response against a predominant DBPII variant circulating in the study area ( Table 1 ) . Since the number of malaria cases varied during the course of the study ( Fig 2A ) , we evaluated the long-term antibody response at different levels of malaria transmission . Over three cross-sectional surveys , at 6-month intervals , between 38 to 40% of individuals developed DBPII IgG antibodies , as detected by conventional serology ( Fig 2B ) . Considering the inhibitory antibody response , there was a slight decrease in the frequency of BIAbs at the time of the 3rd cross-sectional survey ( 34–35% to 25% ) ( Fig 2C ) . Finally , the 12-month follow-up study allowed individuals to be classified as persistent non-responders ( PNR ) , transient responders ( TR ) , or persistent responders ( PR ) for either conventional serology or BIAbs immune response ( Fig 2D ) . For conventional and inhibitory antibody responses , the frequency of acute malaria infections was similar between the PNR , TR or PR groups ( p>0 . 05 for all comparisons ) . Of the HLA class II loci that were genotyped in the study population , we found 13 HLA-DRB1 , 6 HLA-DQA1 , and 5 HLA-DQB1 allele groups . As expected , HLA-DRB1 was the most polymorphic locus with 46 alleles identified; there were 21 and 13 DQB1 and DQA1 alleles , respectively . For each HLA class II locus , the predominant alleles ( frequency ≥ 0 . 01 ) were listed in the S1 Fig . In a preliminary analysis , the effect of HLA class II genes on conventional DBPII antibody response was evaluated at the time of the first blood collection ( S1 Table ) . While three HLA class II alleles ( DRB1*13:01 , DQA1*01:03 , DQB1*06:03 ) were positively associated with anti-DBPII antibody response , six alleles ( DRB1*10:01 , DRB1*14:02 , DQA1*01:01 , DQA1*05:03 , DQB1*03:01 , DQB1*05:01 ) were negatively associated . Nevertheless , using multiple logistic regression models , only the DRB1*13:01 ( presence ) and DRB1*14:02 ( absence ) alleles were significant predictors of anti-DBPII antibodies ( Fig 3A ) . Since combinations of HLA alleles are inherited together in the genome more often than expected , we further evaluated the association between ELISA-detected DBPII-specific antibodies and HLA class II haplotypes . In total , 126 combinations of specific DRB1 , DQA1 , DQB1 haplotypes were found , and for 27 of them ( frequency ≥ 0 . 01 ) it was possible to estimate the individual probability of developing DBPII antibodies . Adjusted logistic regression analysis identified a single haplotype associated with poor production of DBPII antibodies , with individuals carrying the haplotype DRB1*14:02-DQA1*05:03-DQB1*03:01 5-times less likely to develop a conventional DBPII antibody response ( Fig 3A ) . In addition , for each HLA class II locus analyzed ( DRB1 , DQA1 , and DQB1 ) , the genotype frequencies were confirmed to be in Hardy-Weinberg equilibrium ( for the responder vs . non-responder groups ) . Next , we investigated whether the status of persistent responder ( PR ) or non-responder ( PNR ) was HLA class II-linked at the time of the 12-month follow-up collection . The frequencies of some HLA class II alleles were significantly different between the PR and PNR groups ( S2 Table ) . An adjusted odds ratio analysis confirmed that two alleles were associated with the status of long-term responder , and a single allele was associated with the absence of an antibody response ( Fig 3B ) . More specifically , while individuals carrying either the DRB1*13:01 or DQA1*01:03 alleles had an increased probability of a sustained antibody response , the DQA1*05:03 allele carriers were associated with the status of persistent non-responders ( Fig 3B ) . It is noteworthy that the DQA1*05:03 allele aggregated in a specific haplotype ( DRB1*14:02-DQA1*05:03-DQB1*03:01 ) that was primarily associated with the absence of an antibody response ( Fig 3A ) , and this haplotype was in strong linkage disequilibrium ( Δ = 1 . 0; P = 0 ) . Further experiments investigated whether HLA class II polymorphisms interfered with the functional proprieties of DBPII antibodies . The three cross-sectional measures of DBPII BIAbs responses were performed on a subset of the study population comprising 164 individuals ( Table 1 ) , with responders ( n = 58 ) and non-responders ( n = 106 ) matched for age , sex , and malaria exposure . Three alleles ( DRB1*07:01 , DQA1*02:01 , and DQB1*02:02 ) were overrepresented in DBPII BIAbs responders ( S3 Table ) , and these same alleles aggregated in a haplotype ( Fig 4A ) , which was in linkage disequilibrium ( Δ = 0 . 90 and 0 . 94 , for responders and non-responders , respectively ) . Interestingly , the long-term persistence of anti-DBPII responses ( determined at the 12 month follow-up analysis ) was also associated with those same three HLA class II alleles ( Fig 4B ) . Unfortunately , the small size of the sample precluded use of adjusted odds ratio analyses . Nonetheless , responder and non-responder groups were matched by the confounding variables ( age , sex , malaria exposure , and dwelling localization ) . Since persistence and functional properties of DBPII antibodies were influenced by class II allelic variants , we investigated whether differences in the affinity of DBPII peptides for class II molecules might contribute to the observed difference in responses . Based on predicted binding affinity between DBPII peptides and HLA-DR/DQ alleles , we found unexpected differences in affinity in favor of the non-responder allele carriers . Actually , the HLA-DR allele linked to non-responders ( DRB1*14:02 ) appeared to have a higher binding affinity for the peptides ( low IC50 values ) than the HLA–DR alleles that were associated with responders ( DRB1*07:01 and DRB1*13:01 ) ( S2 Fig ) . In spite of that , different HLA-DR binding profiles were found for previously identified DBPII epitopes [44–47] . Of note , the recently described broadly neutralizing DBPII epitopes ( 2D10/2H2 and 2C6 ) had low binding affinity for all of the Class II molecules analyzed ( S2B Fig ) . Considering HLA-DQ , the model also showed a higher predicted binding affinity for HLA-DQA1/B1 molecules linked to non-responders . Structural analysis of the three HLA-DRB1 variants revealed a number of interesting differences in the peptide-binding groove ( S3 Fig ) , with significant alterations to its electrostatic potential , and reduced affinity for the model peptides ( Fig 5A–5C ) , which we propose as an explanation for the differences in subject responses . The antigenic surface of DBPII has a strong positive charge ( S4 Fig ) , which is suggestive of a binding preference for antibodies targeting positively charged epitopes such as those that will be preferentially bound by the DRB1*07:01 and DRB1*13:01 variants . Interestingly , while the DRB1*14:02 and DRB1*13:01 variants are the closest in sequence identity , the docked peptides were most similar between the two responder variants ( rmsd of the peptides < 3 . 8 Å ) , whilst the non-responder did not dock in a similar way ( rmsd of the peptides > 8 Å ) . This supports the suggestion that the non-responder variant leads to reduced antigen presentation . Overall , while the non-responder-associated variant ( DRB1*14:02 ) shares 81 . 2% and 95 . 5% sequence identity to DRB1*07:01 and DRB1*13:01 , respectively , the sequence identity is lower in the groove region within 5 Å of the presented antigen ( DRB1*07:01–73 . 3%; DRB1*13:01–89 . 6% ) . While the majority of the differences between the variants are located within the peptide-binding domain , this change in the nature of the antigen-binding groove is evident in differences between their isoelectric points , with DRB1*07:01 and DRB1*13:01 having slightly acidic pI’s ( 6 . 5 and 7 . 0 respectively ) , and DRB1*14:02 being basic ( 7 . 7 ) . It was also reflected in the energy calculations , with DRB1*14:02 having an overall Coulomb energy approximately 1 . 5% lower than either of the responder variants . One significant difference between the good and poor responder variants was the presence of a glutamine residue at position 99 ( 247 according to the Protein Data Bank , PDB ) in DRB1*14:02 , compared to aspartic acid in DRB1*07:01 and DRB1*13:01 . This residue side-chain points into the peptide-binding groove and is located approximately 5 Å from the antigen peptide backbone , making a key hydrogen bond ( Fig 5D and 5E ) . Here , loss of the acidic residue in the peptide-binding groove was predicted to reduce the H1 and H3 peptide binding affinity ( ΔΔG < -0 . 8 kCal/mol ) , and is likely to lead to altered antigen binding and presentation profiles , and hence the poor response seen for DRB1*14:02 variant carriers .
The HLA molecules encoded by MHC class II genes are responsible for presenting peptide epitopes to CD4+ T helper cells . Consequently , it is reasonable to postulate that polymorphism in the HLA class II region may account for the variation in DBPII antibody responses . Unfortunately , most antibody prevalence data on malaria have been collected by cross-sectional analysis at a single time point , which might led to misclassification of individual immune responsiveness . Therefore , in this study we conducted a longitudinal study , collecting serum from the same individuals over a period of 12 months , to obtain a reliable estimate of DBPII antibody prevalence . The genetic profile of HLA class II in the study population was similar to other populations of the Brazilian Amazon [48] , which are characterized by an interethnic admixture with high proportions of European and Amerindian groups [49] . Accordingly , in the study population 44% had European ancestry , followed by 38% Amerindian , and 18% African ancestry . For other Brazilian regions , the contribution of European ancestry has ranged from 40% in the Northeast to >70% in the Southeast and South [50 , 51] . As expected , the Native-American ancestry in the study area ( 38% ) was representative of the Amazonian region , where Amerindian ancestry is much higher that in other Brazilian regions ( <10% ) [50] . Our current study confirms the heritability of antibody responses to DBPII , with genetic variation in HLA class II molecules influencing both the development and persistence of an individual’s anti-DBPII IgG antibody response . Accordingly , multivariate analyses adjusted for potential confounding variables showed effects of alleles linked to the DR and DQ loci on the presence ( DRB1*13:01 ) and persistence ( DRB1*13:01 and DQA1*01:03 ) of ELISA-detected DBPII IgG antibodies . On the other hand , two alleles were associated with DBPII-non-responsiveness , DRB1*14:02 and DQA1*05:03 , and these comprised a single haplotype ( DRB1*14:02-DQA1*05:03-DQB1*03:01 ) that significantly reduced the development of anti-DBPII IgG at any time during the follow-up study ( baseline , 6 and 12 months later ) . Interestingly , the alleles in the aforementioned haplotype were in strong linkage disequilibrium , which demonstrated that these poor-responder alleles are inherited together more often than expected by chance . So far , only a single study has investigated the association between HLA and DBPII antibodies [52] . Although in that case the authors were unable to demonstrate an association between HLA type and ELISA-detected DBP IgG antibodies , and the relatively limited number of responders did not allow any final conclusions about the highly polymorphic HLA class II and DBP antibodies . Here , the assessment of long-term antibody response was essential to strengthen the conclusion that there was an increased susceptibility of DRB1*13:01 carriers to develop and sustain their anti-DBPII IgG antibody response . Furthermore , these data confirmed that individuals harboring the haplotype DRB1*14:02-DQA1*05:03-DQB1*03:01 were persistent non-responders . Due to the overall scarcity of data combining analysis of HLA and immune responses to P . vivax , further confirmation of these associations in other malaria endemic areas is needed . Despite the remarkable lack of data on this subject , systematic review and meta-analysis studies have identified a link between the DRB1*13:01 allele and increased antibody responses to vaccines for other microbial infections , including hepatitis B , influenza virus , serogroup C meningococcus , and MMR-II ( measles and rubella virus ) [53 , 54] . Additionally , the DRB1*14 allelic group has been associated with a poor humoral response to HBsAg vaccination [55] . Many field studies examining the immune response to malaria have focused on measuring the concentrations of antibodies to vaccine candidate antigens , while less attention has been paid to complementary approaches defining the functional relevance of these antibodies . By using an in vitro assay to quantify inhibition of DBPII–erythrocyte binding [9 , 56] , we demonstrated that DBPII binding inhibitory antibodies ( BIABs ) were associated with three alleles ( DRB1*07:01 , DQA1*02:01 and DQB1*02:02 ) , which are in linkage disequilibrium and were found to be part of a single haplotype . Notably , these three alleles were associated with the presence of BIAbs antibodies and were also associated with the persistence of this inhibitory response . Therefore , our observations may explain previous results showing that the majority of people who are naturally exposed to P . vivax do not develop antibodies that inhibit the DBPII-DARC interaction , but once they are acquired these BIAbs seem to be stable under continuous exposure to malaria transmission [11 , 13] . Intriguingly , a significant number of pharmacogenetic studies have identified HLA-DRB1*07:01 carriers ( in less extension , DQA1*02:01 and DQB1*02:02 ) as being more susceptible to side effects of biological therapy due to the activation of immune response drug-induced [57–59] . Notably , part of the side effect could be explained by the higher production of neutralizing antibodies against drugs ( or their metabolites ) in the HLA-DRB1*07:01 and/or DQA1*02 carriers [59 , 60] . Although drug-specific antibodies are undesirable in therapies involving biological proteins , these findings reinforce our results of a much higher frequency and persistence of DBPII neutralizing antibodies in individuals harboring those alleles HLA class II . In future studies , functional analysis of a greater number of individuals might allow for more robust statistical comparisons . It is noteworthy that the class II alleles associated with DBPII inhibitory activity were not associated with the conventional IgG antibody responses . Likewise , alleles ( or haplotypes ) associated with ELISA-detected IgG antibodies were not associated with DBPII BIAbs . These results are not completely unexpected because quantitative receptor binding assays distinguish between antibodies that recognize DBPII and those that inhibit binding to DARC receptor . Here , the DBPII/DARC interaction was assessed by using an established cytoadherence assay based upon multivalent interactions between DBPII on the surface of COS-7 cells and DARC expressed in RBCs [56] . As a consequence , we and others have demonstrated a moderate correlation between DBPII BIAbs and ELISA anti-DBPII antibodies ( revised in [8] ) . Overall , our results emphasize the relevance of examining functional aspects of the immune response , particularly in the case of immunogens such as DBPII , in which the goal of vaccination would be to enhance broadly neutralizing antibodies targeting invasion-blocking epitopes . To gain insights into the difference between good and poor HLA responders , we sought to investigate whether natural HLA-DR/DQ allelic differences could be explained with respect to binding affinity of DBPII epitopes . While predicted DBPII epitopes have a unexpected moderate-to-high affinity for non-responder alleles , the binding affinity of previously described DBPII epitopes [44–47] was much more variable , including low binding affinities of recently described DBPII B-cells epitopes associated with strain-transcending immunity [47] . However , it seems inappropriate to extrapolate our findings to conformational B cell epitopes because the prediction analyses used here were largely determined by the primary amino acid sequence of the peptide-binding core . In this context , the development of tools for reliably predicting B-cell epitopes , particularly for predicting conformational epitopes , remains a major challenge in immunoinformatics [61] . Although the predicting peptide-HLA binding affinity method used here ( NetMHCIIpan—www . cbs . dtu . dk/services/NetMHCIIpan-3 . 1 ) [62] seems to be a suitable predictive algorithm for T cell epitopes [28] , we performed a further detailed structural in silico analysis of the HLA-DRB1 variants . Significantly , the majority of the differences between HLA-DRB1 variants ( good vs . poor responders ) were located within the peptide-binding domain , leading to significant changes in the nature of the antigen-binding groove . A striking structural difference between HLA-DRB1 variants was the presence of a glutamine residue at position 99 in the poor responder allele ( DRB1*14:02 ) , as compared to aspartic acid in the good responder alleles ( DRB1*07:01 and DRB1*13:01 ) . Remarkably , mutation of the corresponding residue has previously been shown to result in loss of the ability of HLA-DP2 to present the metal beryllium to T cells , in genetically susceptible to chronic beryllium- disease [63] . Notably , this single mutation seems to drive helper CD4 T cells in susceptible individuals to secrete Th1-type cytokines , such as gamma-interferon , but not IL-4 , leading to beryllium-induced hypersensitivity and chronic beryllium-disease [64 , 65] . Consequently , we speculate that the mutation found here in the peptide-binding groove ( D247 vs . Q247 ) is likely to change the outcome of the CD4+T cells immune response . Accordingly , the loss of the acidic residue in the peptide binding groove was predicted to reduce DBPII-specific peptide binding affinity ( H1 and H3 ) , which is expected to lead to altered antigen binding and presentation profiles , and hence poor response of carriers of the DRB1*14:02 variant . It strengthens the findings that DRB1*14:02 could be more frequently involved with a poor antibody production [55] , while the DRB1*13:01 allele produces a much more robust antibody response [53 , 54] . Future studies are required to determine differences in the functionalities of DBPII epitopes in the context of different HLA molecules . Notwithstanding the relevance of our results , the current study has some limitations . As we focused on the highly variable HLA class II genes it may not have been possible to discriminate between causal alleles and variation that is due to the linkage disequilibrium ( LD ) between alleles . In fact , in most association studies it has been difficult to pinpoint the causal variants within this genetic complex due to strong LD , population heterogeneity , and the high density of immune-related genes [66] . Such studies have proven most successful for diseases with one prominent predisposing genetic factor mapping to either the class I or class II region [67] . In addition , the associations described in the present study are most likely multifactorial , and depend on several additional factors related to the parasite and host environment . Although the structural analysis of DRB1 variants described here suggested that specific alleles might influence anti-DBPII antibody responses , these results indicate a first step towards the understanding of DBPII immune response in the context of different HLA class-II variants . We are confident that future cellular assays can be pursued to confirm and identify mechanisms associated with good and poor antibody responders . Finally , knowledge of the relative binding affinities of DBPII peptides for class II molecules associated with good and poor responses to this major P . vivax blood-stage vaccine candidate might lead to strategies for controlling the type of helper T cells activated in response to DBPII . | Vaccines are a crucial component of the current efforts to eliminate malaria , and much of the vaccine-related research on P . vivax has been focused on the Duffy binding protein II ( DBPII ) , a ligand for human blood stage infection . A high proportion of individuals who are naturally exposed to P . vivax fail to develop neutralizing antibodies , but the host genetic factors modulating this immune response are poorly characterized . We investigated whether DBPII responsiveness was dependent on the variability of human leucocyte antigen ( HLA ) class II cell surface proteins involved in the regulation of immune responses . To obtain a reliable estimate of DBPII antibodies , we carried out a longitudinal study , collecting serum from the same individuals over a period of 12-months . The results confirmed the heritability of the DBPII immune response , with genetic variation in HLA class II genes influencing both the development and persistence of the antibody response . HLA class II genotype also influenced the ability of DBPII antibodies to block the ligand-receptor interaction in vitro . Computational approaches identified structural specificity between HLA variants , which we propose as an explanation for differences between a good or poor antibody responder . These results may have implications for vaccine development , and might lead to strategies for controlling the type of immune response activated in response to DBPII . | [
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"apicomp... | 2016 | The Presence, Persistence and Functional Properties of Plasmodium vivax Duffy Binding Protein II Antibodies Are Influenced by HLA Class II Allelic Variants |
Leishmaniasis is a parasitic infection affecting ∼12 million people worldwide , mostly in developing countries . Treatment options are limited and no effective vaccines exist to date . Natural Killer T ( NKT ) cells are a conserved innate-like lymphocyte population with immunomodulating effects in various settings . A number of reports state a role of NKT cells in different models of Leishmania infection . Here , we investigated the effect of NKT cells in a physiologically relevant , intradermal low dose infection model . After inoculation of 103 infectious-stage L . major , comparable numbers of skin-immigrating NKT cells in both susceptible BALB/c mice and resistant C57BL/6 mice were noted . Compared to their wild type counterparts , NKT cell-deficient mice on a C57BL/6 background were better able to contain infection with L . major and showed decreased IL-4 production in cytokine analysis performed 5 and 8 weeks after infection . Low doses of the NKT cell stimulating αGalCer analog PBS57 applied at the time of infection led to disease exacerbation in C57BL/6 wild-type , but not NKT-deficient mice . The effect was dependent both on the timing and amount of PBS57 administered . The effect of NKT cell stimulation by PBS57 proved to be IL-4 dependent , as it was neutralized in IL-4-deficient C57BL/6 or anti-IL-4 antibody-treated wild-type mice . In contrast to C57BL/6 mice , administration of PBS57 in susceptible BALB/c mice resulted in an improved course of disease . Our results reveal a strain- and cytokine-dependent regulatory role of NKT cells in the development of immunity to low dose L . major infections . These effects , probably masked in previous studies using higher parasite inocula , should be considered in future therapy and immunization approaches .
Leishmaniasis is a parasitic disease which is caused by a variety of Leishmania spp . and affects about 12 million people worldwide . There are approximately 2 million people newly infected every year . Transmitted by a sand fly , it primarily affects people in ( sub- ) tropical climates . Depending on the genetic background and the immune status of the patient , the disease can have various clinical presentations . It can be primarily cutaneous , mucocutaneous , multilocular , chronic , or recurrent and in severe cases develop visceral forms . About 90% of infected individuals suffer from cutaneous leishmaniasis ( CL ) , which often heals with disfiguring scars [1] . Primarily affecting poorer populations , there is little incentive for drug and vaccine development . Leishmaniasis is considered a neglected disease by the WHO . Experimentally , leishmaniasis has long been used as an immunologic model . Infected mouse strains can either develop a Th1/Tc1-driven immune response successfully containing infection or a Th2/Th17/Treg response , ultimately succumbing to uncontrolled parasite loads . A better understanding of the disease and the immunologic mechanisms involved will hopefully result in improved treatment options and an effective vaccine . Natural killer T ( NKT ) cells are a subset of T cells first identified in the early 90s2 . Obtaining their name because they express a subset of receptors primarily expressed on natural killer ( NK ) cells , they also have a number of other unique properties which distinguish them from conventional T cells . They harbor a restricted set of T cell receptors and recognize endogenous and exogenous lipid antigens presented by a MHC class 1b molecule named CD1d [2] , [3] . They also have an effector phenotype and function , readily able to secrete considerable amounts of both IL-4 and IFNγ upon stimulation [4] . They have been shown to regulate and influence the immune response to a variety of infectious agents being activated either by direct recognition of bacterial lipid antigens or in a CD40- , IL-12-dependent manner by dendritic cells ( DC ) presenting endogenous lipids [5] . The strongest known ligand activating NKT cells is αGalactoysl-Ceramide ( αGalCer ) [6] . Stimulation of NKT cells by αGalCer can lead to considerable cytokine secretion when applied in small quantities and has been used as a modulator of immune responses in a variety of antitumor , autoimmune and infectious experimental models [7]–[9] . A number of studies have addressed the role of NKT cells in the immune response to Leishmania [10]–[17] . In visceral leishmaniasis , NKT cells were shown to recognize a L . donovani lipophosphoglycan and an impaired immune response in NKT deficient CD1d−/− BALB/c mice was noted [18] . L . donovani infection causing IFNγ secretion by NKT cells through liver SIRP ( signal regulatory protein α ) upregulation was also reported [10] . In cutaneous leishmaniasis , infections with >106 L . major parasites ( s . c . or i . v . ) showed delayed parasite clearance in NKT cell-deficient CD1d−/− and Jα18−/− mice [13] . In summary , the results of these studies are variable and do not provide a coherent understanding of the role of NKT cells in leishmaniasis . All in vivo studies reported , with the exception of vaccine trials by Dondji et al . [19] , used supraphysiological high dose parasite inocula , applying >106 promastigotes at the time of infection . In our study we analyzed the effect of NKT cells in a physiologically relevant model of cutaneous leishmaniasis applying 103 infectious stage L . major promastigotes intradermally into the ear . Our results differ considerably from prior high dose inocula studies and show effects that point toward an important influence of NKT cells on the development of protective immunity against Leishmania . This clear role of NKT cells for parasite clearance could be important for the development of new treatment options or an effective vaccine .
C57BL/6 , Jα18−/− , CD1d−/− , and IL-4−/− mice ( all C57BL/6 background ) , and BALB/c mice were housed under specific pathogen-free conditions in the animal care facility in Mainz . All animal experiments were conducted in accordance with federal guidelines and approved by the ethical committee of the state of Rheinland Pfalz ( according to §8 Abs . 1 des Tierschutzgesetzes , Landesuntersuchungsamt , approval #LUA 23 170–07/G07-1-022 ) . Metacyclic promastigotes of L . major clone VI ( MHOM/IL/80/Friedlin ) were prepared as described previously [20] . Groups of three to five mice were infected with low-dose ( 103 ) inocula in a volume of 20 µl by intradermal injection into ear skin applying 0 . 3 mm diameter needles . Lesion volumes were measured weekly in three dimensions and are reported as ellipsoids: [ ( a/2×b/2×c/2 ) ×4/3π] . Parasite burdens were enumerated using a limiting dilution assay [20] . All experiments used an artificial variant of αGalCer termed PBS57 [21] . It was applied i . p . after dilution in 200 µl PBS at the time of treatment or as referred to in the manuscript . Control groups received 200 µl PBS i . p . IL-4 neutralizing antibodies ( clone 11B11 ) were applied i . p . at 1 mg/200 µl , one day before and one day after infection . To measure antigen-specific cytokine production , retroauricular LNs were isolated and single cell suspensions prepared . One million LN cells in 200 µl complete RPMI 1640 medium ( BioWhittaker ) were cultured in the presence of 25 µg/ml SLA . Supernatants were harvested 48 h after stimulation and analyzed with ELISAs specific for IFNγ ( R&D Systems ) , IL-4 and IL-10 ( BD ) . IFNγ and IL-4 levels in serum samples were measured the same way . The livers were harvested , minced , and the tissue pieces strained through 70-µm mesh and pelleted by centrifugation . The cell pellet was resuspended and lymphocytes isolated by Percoll gradient , spun at 200 g . Spleen and lymph node cells were isolated by mechanically grinding the tissue through 70-µm cell strainers . Ears infected with L . major were excised , soaked in 70% ethanol , and washed with PBS . The ears were split into halves and placed in 0 . 5 mg/ml liberase ( Sigma-Aldrich ) diluted in RPMI 1640 with 5% penicillin/streptomycin for 1 . 5 h at 37°C . Liberase was inactivated by adding complete RPMI 1640 containing 5% FCS . The ears were put into 50 µM Medicon homogenizers ( BD ) with 1 ml of complete RPMI 1640 and homogenized in a Medimachine ( BD ) for 7 min . This was then passed through a 70 µm-pore size filter and centrifuged at 200 g for 8 min . Cells were resuspended in PBS and labeled with antibodies for flow cytometry . The following antibodies were purchased from BD: PerCP-Cy5 . 5 rat anti–mouse CD8α ( 53–6 . 7 ) , PE rat anti–mouse CD4 ( L3T4 ) . NKT cells were stained with APC-labeled , αGalCer analog PBS57-loaded CD1d tetramers as previously described [22] . Flow cytometry analysis was performed using a FACSCalibur or LSRII cytometer ( BD ) and FlowJo software ( Tree Star ) . Cells were gated via FSC/SSC for viable cells , concentrating on lymphocytes . Statistical analysis was performed using StatView software and Students t-test .
Post intradermal inoculation of 1 , 000 L . major in the ear pinna of C57BL/6 and BALB/c mice , we assessed the number of NKT cells at different time points in the lymph nodes , spleen and liver ( Figure 1 , additional statistical information in Table S1 ) . As expected , at later time points of infection , significant increases in the amount of CD4 and CD8 T cells in the lymph nodes and ears of C57BL/6 and BALB/c groups were noted . NKT cell numbers were measured applying CD1d-PBS57 tetramers . Interestingly , in parallel to conventional T cells , NKT numbers were also increased at later time points in infected skin sites , the draining lymph nodes and the liver . Strain-dependent differences were not apparent . The course of infection in Jα18−/− and CD1d−/− compared to C57BL/6 wild-type mice was analyzed post intradermal injection of 1 , 000 L . major in the ear pinna . Both Jα18−/− and CD1d−/− mice lack the majority of NKT cells , with slight differences: Jα18−/− lack those containing the invariant Vα14-Jα18 T cell receptor ( TCR ) alpha chain , CD1d−/− lack all T cells selected by and recognizing CD1d . Both mouse strains showed a less severe course of infection than wild-type C57BL/6 controls as assessed by significantly decreased lesion volumes at different time points ( Figure 2A ) . Parasite burdens assessed in the ear and spleen showed a similar trend with lower parasite levels in NKT cell-deficient mice . Differences between Jα18−/− and C57BL/6 groups reached statistical significance ( Figure 2B and 2C ) . Antigen-specific cytokine production was assessed after restimulation of draining LN cells ( Figure 2D , 2E , and 2F respectively ) . A consistent decrease of IL-4 secretion in both Jα18−/− and CD1d−/− LN cells compared with C57BL/6 cells was noted in both weeks 5 and 8 . To analyze the effect of NKT cell stimulation on the course of infection , we injected 100 ng of αGalCer analog PBS57 at the time of infection . Interestingly , this led to a dramatic worsening of the course of disease , with lesion sizes reaching twice the size of the control group . Healing was also considerably delayed , prolonging the course of disease ( Figure 3A ) . The effects correlated with parasite burdens over time , which were higher in the PBS57-treated group both in the ear ( week 5 ) and spleen ( week 8 ) ( Figure 3B+C ) . Consistent with a primarily CD1d-mediated effect , PBS57 administration had only minor effects on the course of infection in CD1d−/− mice ( Figure 3D ) , where parasite burdens assessed in week 5 and 8 demonstrated only smaller changes ( Figure 3E+F ) . Although not significant , antigen-specific cytokine levels showed a trend to a decrease of IL-4 production by CD1d−/− LN cells than wild type counterparts and to an increase of IL-4 production in the C57BL/6 mice which had received αGalCer analog PBS57 ( Figure 3G ) . Interested in assessing potential dose-dependent effects on the course of disease after intradermal L . major infection , αGalCer analog PBS57 was applied in doses of 10 ng , 100 ng , and 2 µg . Disease exacerbation upon PBS57 administration did show dose dependency with lesion size increases and prolongation of resolution being highest in the 2 µg-treated group and weakest in the 10 ng-treated group ( Figure 4A ) . Administration of a subsequent dose of 100 µg at 6 weeks elicited a considerable effect with a rapid increase in lesion sizes and additional delay in healing . Finally , the control group treated with PBS57 only 6 weeks after infection showed a similar effect , considerably worsening the course of disease compared to the untreated group ( Figure 4B ) . To further delineate the time variable of PBS57 effects , an additional experiment with groups where 100 ng of PBS57 was applied 1 week before and 3 weeks after infection was initiated . Interestingly , while giving PBS57 one week before injection did slightly influence the course of infection , the effect was stronger in mice receiving PBS57 3 weeks after infection ( Figure 4C ) . This confirmed the result of earlier experiments indicating that effects of αGalCer analog PBS57 were strongest if applied at the time of or post infection . In contrast to resistant C57BL/6 mice , susceptible BALB/c mice routinely develop a Th2/Th17 response to L . major not allowing them to contain the parasite and ultimately leading to death due to extremely high visceral parasite loads . To analyze if αGalCer analog PBS57 administration in BALB/c mice has similar effects as in C57BL/6 mice , a range of concentrations were tested . Unexpectedly , the dose of 100 ng of PBS57 led to an improvement of disease . It did not allow the mice to contain infection , but significantly delayed the growth of lesions , resulting in prolonged survival ( Figure 5A ) . This effect was not only seen in terms of lesion size , but also mirrored in parasite burdens , which were measured again at week 5 and 8 in ear and spleen ( Figure 5B ) . IFNγ , IL-4 , and IL-10 cytokine levels showed no significant differences ( Figure 5C ) . Application of a second dose of 100 ng of PBS57 led to a slight worsening of disease . In contrast , a single dose of 2 µg given at the time of infection showed only a small window of improvement from week 3–5 in terms of lesion sizes . At week 6 , the lesion sizes were once again comparable to untreated controls ( Figure 5A ) . To determine if the differences seen in C57BL/6 and BALB/c infected mice were due to variations in the early cytokine response , we measured these in the serum shortly after L . major infection in PBS57 and untreated controls . PBS57 treatment led to an acute increase of serum levels of IFNγ and IL-4 at 6 hrs , which was not observed in untreated , infected controls . PBS57-treated mice also showed higher IL-10 levels 3 days post infection . The only clear observed strain-specific difference was a higher IFNγ level 6 hrs post infection in BALB/c than in C57BL/6 serum ( Figure 6 ) . To further analyze the role of early cytokine secretion in the observed αGalCer analog PBS57-mediated effects on infection , experiments were performed eliminating IL-4 . In one set of experiments , IL-4−/− mice were infected with L . major and subsequently treated with PBS57 . However , whereas controls showed the known exacerbation of disease after application of PBS57 , this was not seen in IL-4−/− mice ( Figure 7A [23] ) . In another set of experiments , IL-4 neutralizing antibodies were applied to infected C57BL/6 mice . Here , similar results were observed , with PBS57 application no longer changing the course of infection ( Figure 7B ) . Anti-IL-4-treated mice also exhibited significantly lower parasite loads . PBS57 administration no longer affected the course of infection in these mice ( Figure 7C ) , supporting an important role of IL-4 in αGalCer analog PBS57-mediated disease exacerbation .
In the present study we demonstrated that NKT cells influence the course of L . major infection in a physiological low dose infection model . Mice on a C57BL/6 background lacking NKT cells showed an improved course of disease . Correspondingly , NKT cell stimulation with αGalCer analog PBS57 worsened the course of disease . Effects of stimulation were time , dose , and strain dependent . The effect of PBS57-stimulated NKT cells appeared to be IL-4 mediated , as neutralizing this cytokine abrogated the observed effects in vivo . Our results show that NKT cells should be considered both when treating active Leishmania infection as well as in the development of vaccines . The reported effects of L . major-activated NKT cells observed in various models of Leishmania infection have been variable and often conflicting [10]–[16] . Most of this is probably due to both different infection models and Leishmania strains applied . In our model , 103 infectious stage parasites are inoculated intradermally in the ear . This is considerably lower than in most other studies using L . major , which additionally often infect the foot pads instead of ear skin . Studies by Mattner et al . [13] and Ishikawa et al . [12] presented very different effects of NKT cells on the course of L . major infection than those we observed . In their hands , high doses of parasites ( 106–108 ) given intradermally or even intravenously showed a protective effect of NKT cells , with C57BL/6 mice having lower parasite loads than their NKT cell-deficient counterparts . We and others [24] argue that such high parasite doses are far removed from the actual real life scenario , where infection is initiated by small amounts of parasites leaving the sand fly during its feeding on the host . We therefore believe our findings might be more representative of most infection settings in humans . Both NKT cell deficient mice strains on a C57BL/6 background controlled L . major infection significantly better than wild-type counterparts . CD1d−/− mice lack all NKT cells . Jα18−/− mice do not have the larger invariant Vα14-Jα18 TCR subset , however still maintain a smaller NKT cell subset which recognizes CD1d with a different TCRs . Although there was a trend toward better disease control for Jα18−/− than CD1d−/− mice ( Figure 2 ) this was not statistically significant , nor were substantial differences in cytokine secretion between the two strains noted . Future studies would be needed to elucidate the role of different NKT cell subsets in Leishmania infection . Stimulating NKT cells by applying αGalCer analog PBS57 significantly altered the course of disease . The effect was time- and dose-dependent . As initiating a Th1 immune response is critical for the control of Leishmania infection , we hypothesized that the mechanism through which NKT cells have a negative effect on the course of infection in C57BL/6 mice , could be through secretion of Th2 cytokines , in particular IL-4 . When IL-4 was neutralized , either in IL-4 deficient mice or by applying IL-4 binding antibodies , the effect of PBS57 on the course of infection was alleviated . We believe this proves IL-4 secretion by NKT cells is the relevant factor negatively influencing control of L . major in C576BL/6 mice . It is noteworthy that αGalCer analog PBS57 administration showed strain-dependent differences . While leading to disease exacerbation in C57BL/6 , it improved the course of disease in BALB/c mice ( at least in smaller doses of 100 ng ) . The higher amount of IFNγ secretion in the serum of PBS57-treated BALB/c we noted compared to C57BL/6 mice might play a relevant role . Additionally , we assume the effect could be strongly context-dependent , with the same cytokines ( IFNγ and IL-4 , both secreted by NKT cells ) , resulting in a slight Th1 shift in the developing Th2 response of BALB/c , compared to a Th2 shift in the Th1 setting of C57BL/6 . The strain specific observations are important to consider when trying to extrapulate what effect administration of αGalCer or its analogs might have in a human infection setting . Generally , it is believed that the course of infection seen in C57BL/6 mice better mirrors the situation seen in most humans with cutaneous leishmaniasis . As such , NKT cell activation through αGalCer analog PBS57 during the course of infection is most likely non-beneficial to the host and should be avoided . On the other hand , αGalCer has shown a very beneficial effect as an adjuvant in L . major vaccination studies [19] . This could mean that while applying αGalCer in a vaccination setting appears very promising , one should be careful before applying such a vaccine in the setting of an existing infection , as it could potentially lead to disease worsening . A potential additional strategy would be to test other NKT cell stimulating glycolipids . PBS57 , the compound used in our study , was shown to stimulate slightly higher amounts of IL-4 and IFN-γ secretion than the original αGalCer compound , KRN7000 [21] . Several versions of αGalCer and other glycolipids have been synthetically generated and vary in terms of cytokine response generated , favoring more of a Th-1 or Th-2 response [7] , [25] . Potentially applying other αGalCer variants or glycolipid compounds which elicit a more pronounced Th1 profile cytokine stimulation could prove valuable , both in terms of treatment and vaccination for Leishmania infections . In summary , our findings demonstrate that NKT cells influence the course of L . major infection in a physiological low dose model . The effects were strain-dependent and could be augmented through αGalCer analog PBS57 stimulation , leading to disease worsening in Leishmania resistant C57BL/6 mice . Our results make it apparent that immune response modulating effects of NKT cells should be considered both when treating active Leishmania infection as well as developing vaccines . | Cutaneous leishmaniasis is a disease affecting about 12 million people worldwide . It is transmitted by a sand fly and primarily affects people in developing countries . To date there are no effective vaccines . Many of the treatments available have serious side effects and resistance mechanisms are becoming an increasingly prevalent problem . Natural killer T ( NKT ) cells are a unique T cell population recognizing glycolipids . Their role in immune processes , especially in infectious diseases , is incompletely understood . In the current study , we investigated the role of NKT cells in Leishmania infections in detail . We found that NKT cells can significantly alter the development of immunity , however in different directions depending on the host's genetic background . Their natural effect on infection can be increased when applying the stimulating antigen alpha-Galactosyl-Ceramide ( αGalCer ) or its analogs ( in our study PBS57 ) . Our results show that the effect of these cells in resistant mice ( which are generally reminiscent of the situation in humans ) is largely mediated by cytokine secretion , in particular IL-4 , a Th2 cytokine . We conclude that NKT cells influence the course of Leishmania infection and that therapeutically modulating their function could be beneficial both to treat existing infections , as well as potentially develop desperately needed , effective vaccines . | [
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"protozoans"... | 2014 | Immune Modulating Effects of NKT Cells in a Physiologically Low Dose Leishmania major Infection Model after αGalCer Analog PBS57 Stimulation |
The pattern recognition receptor RIG-I is critical for Type-I interferon production . However , the global regulation of RIG-I signaling is only partially understood . Using a human genome-wide RNAi-screen , we identified 226 novel regulatory proteins of RIG-I mediated interferon-β production . Furthermore , the screen identified a metabolic pathway that synthesizes the inositol pyrophosphate 1-IP7 as a previously unrecognized positive regulator of interferon production . Detailed genetic and biochemical experiments demonstrated that the kinase activities of IPPK , PPIP5K1 and PPIP5K2 ( which convert IP5 to1-IP7 ) were critical for both interferon induction , and the control of cellular infection by Sendai and influenza A viruses . Conversely , ectopically expressed inositol pyrophosphate-hydrolases DIPPs attenuated interferon transcription . Mechanistic experiments in intact cells revealed that the expression of IPPK , PPIP5K1 and PPIP5K2 was needed for the phosphorylation and activation of IRF3 , a transcription factor for interferon . The addition of purified individual inositol pyrophosphates to a cell free reconstituted RIG-I signaling assay further identified 1-IP7 as an essential component required for IRF3 activation . The inositol pyrophosphate may act by β-phosphoryl transfer , since its action was not recapitulated by a synthetic phosphonoacetate analogue of 1-IP7 . This study thus identified several novel regulators of RIG-I , and a new role for inositol pyrophosphates in augmenting innate immune responses to viral infection that may have therapeutic applications .
The innate immune system , a primordial yet highly organized defense mechanism , plays critical roles in the host response against RNA viruses . The first step in the innate immune response involves recognition of pathogen-associated molecular patterns by several host encoded pattern recognition receptors ( PRR ) . A key mediator of antiviral immunity is the type-I interferon family of cytokines , which are transcribed upon detection of RNA viruses by the pattern recognition receptors [1]–[3] . Cells have developed PRRs that are specialized for detecting pathogens in the cytosol , the site where many RNA viruses replicate . One such PRR is the retinoic acid inducible gene - I ( RIG-I ) [1]–[3] . RIG-I recruits the adaptor protein MAVS to activate a signaling pathway that causes TBK1 to phosphorylate the latent transcription factor IRF3 [4]–[7] . Signaling cascades triggered by multiple PRRs indeed converge to activate IRF3 . Once phosphorylated , IRF3 dimerizes and translocates to the nucleus , where it forms a complex with the transcriptional coactivators CBP/p300 , which together stimulate the expression of type-I interferon [1] . This initiates the antiviral immune responses [8]–[10] . An optimal interferon response is essential to control viral infections; however , excessive interferon exposure is detrimental to the human body [11] . Significant research effort has been invested in determining the nature of the positive and negative signaling pathways which regulate the responses that RIG-1 elicits following viral infection [1] , [2] , [5] , [6] , [12]–[18] . Yet , there are significant gaps in our understanding of how an appropriate interferon response is regulated . For example , the regulation of the coupling of RIG-I stimulation to the activation of IRF3 is not completely understood . In particular , it has not previously been well determined if any diffusible second messenger molecules have signaling roles in this pathway . In addition , a comparative understanding of the regulation of the unique RIG-I specific upstream and the conserved ( across PRRs ) downstream steps of interferon production is still lacking . In any case , the innate immune system is a complex , multifactorial network of interconnected pathways that exhibit combinatorial effects and emergent properties [19]; this is an entity that is much more than the sum of its individual components . Systems-level analysis therefore offers the most promising approach to a comprehensive understanding of the regulation of innate immune pathways such as the interferon response; this information can also be exploited for the development of novel therapeutic targets [20] . Some previous studies used proteomics and gene expression profiling approaches to understand the global regulation of innate immune response during several RNA viral infections [21] , [22] . However , a systematic interrogation of the role of all of the annotated genes of human genome in the RIG-I signaling and interferon production is yet to be reported . In this study , through a systems level approach using human genome wide RNA-interference ( RNAi ) screen , bioinformatics analysis and mechanistic validations , we generated an expanded understanding of the regulation of RIG-I mediated interferon response . We have identified 226 novel components of the RIG-1 pathway . In particular , the approach we took in the current study led us to identify that a class of kinases that synthesizes inositol pyrophosphates are important positive regulators of the type-I interferon response . The inositol pyrophosphates ( also known as diphosphoinositol polyphosphates ) are a specialized subgroup of the inositol phosphate signaling family that is distinguished by the presence of high-energy diphosphate groups [23]–[25] . The inositol pyrophosphates are known to regulate DNA damage repair [26] , apoptosis [27] , [28] , insulin exocytosis [29] , and insulin signaling [30] . Although a role for inositol pyrophosphates in regulating neutrophil function has also recently emerged [31] , it has not previously been reported whether they play any role in antiviral immunity . Now , we demonstrate for the first time that the synthesis of inositol pyrophosphates is critical for type-I interferon transcription and antiviral immunity .
To discover novel genes regulating the RIG-I mediated interferon response , we performed a human genome wide RNA-interference ( RNAi ) screen . A quantitative fluorescence microscopy based assay was adopted for the screen using human interferon-β ( IFNβ ) promoter- driven green fluorescent protein reporter ( IFNβ-GFP ) ( Figure 1A ) . The assay used human embryonic kidney ( HEK ) 293 cell line , a widely used model system to dissect RIG-I signaling [15] , [32] , [33] . As HEK293 cells do not have a robust TLR3 expression , the use of this cell line would minimize the effects from non-RIG-I pathways [34] . As reported earlier [33] , because HEK293 cells express only moderate levels of RIG-I , transfection of IFNβ-GFP reporter along with the RIG-I ligand Polyinosinic:polycytidylic acid ( poly ( I:C ) ) into these cells leads to only a modest increase in the GFP signal ( Figure S1A ) . However , transfection of RIG-I expression plasmid into these cells leads to a very robust activation of GFP signal , both with and without poly ( I:C ) stimulation ( Figure S1A ) . In control experiments , silencing of RIG-I , MAVS and IRF3 , drastically reduced the RIG-I transfection mediated IFNβ-GFP signal , but there was no effect upon silencing either TRIF ( TLR3 adaptor ) or MDA5 ( another cytosolic PRR of viruses ) ( Figure S1B ) . These experiments prove that the observed reporter activity was originating specifically through RIG-I . For the RNAi screen , we selected a condition where , 24 hr after the transfection of a RIG-I expression plasmid ( with poly ( I:C ) stimulation ) , IFNβ-GFP transcription was observed in approximately 25% of the cells . In comparison , only 1–2% of the total cells were GFP-positive after silencing of the positive control genes MAVS and IRF3 , representing a 26 . 5- and 14 . 3-fold decrease in IFNβ-GFP reporter activity respectively ( Figure S1B ) . High content microscopy based imaging was used to detect and quantify the degree of activation of the IFNβ reporter . For every image , we calculated the GFP intensity per cell ( defined as a DAPI stained nucleus ) , after setting an intensity threshold to identify the GFP expressing cells . The final readout of the assay was the percent of GFP-positive cells per well . The screen was conducted in two stages ( Figure 1A ) . The primary screen involved silencing 18 , 120 human genes using a pool of four unique siRNAs ( from Dharmacon ) targeting each gene . Later , the “hit genes” from the primary screen were further validated for on-target specificity by testing each of the four individual siRNAs of the pool separately , and only those for which at least two independent siRNAs impacted on reporter signal were selected . A Z-score of ( −/+ ) 2 . 5 was taken as cut-off for putative positive or negative regulators , respectively . The analytic parameters for the siRNA screen including the signal intensity and Z-score distributions are given in the Figures S2A–D . We re-identified several previously known regulators of RIG-I pathway such as RIG-I , IRF3 , TRIM21 , PRKR and MAVS as hits , validating the ability of the screen to discover proteins that regulate the interferon response [35] , [36] . More importantly , the RNAi screen led to the identification of a total of 226 additional novel regulators of RIG-I mediated IFNβ response ( Table S1 ) . Out of these , 220 and 6 genes respectively were positive and negative regulators of RIG-I signaling . We subsequently performed detailed bioinformatics analysis to mine the information contained within the RNAi screen results . A meta-analysis using the Gene Expression Omnibus database revealed that 33 of the identified RNAi hits were previously observed as host genes upregulated upon exposure to various RNA viruses , interferon or poly ( I:C ) [21] , [37]–[40] ( Table S1 ) . Network analysis of the obtained hit genes revealed that several proteins previously implicated to interact with components of interferon response , but not determined yet to serve a regulatory role in interferon response , ( e . g , ADAP2 [41] ) are indeed needed for optimal interferon induction ( Figure 1B ) . In addition , genes serving different functions such as those regulating nuclear transport ( RAN , XPO1 ) , ubiquitin like proteins ( UBQLN2 , UBL5 ) and transcription ( e . g . , DLX3 ) were also among the identified hits ( Table S1 ) . Gene ontology ( GO ) analysis identified several statistically significant cellular functional categories of genes regulating interferon production ( Figure 1C ) . Most of the top-ranked GO categories identified were those related to antiviral innate immune signaling . Remarkably , gene ontology analysis also identified the pathway involving biosynthesis of inositol pyrophosphates as a novel cellular process associated with interferon response regulation ( Figure 1C ) . Overall , our functional genomics interrogation revealed that genes and pathways from diverse functional categories are regulators of RIG-I mediated interferon production . In order to begin to generate a global mechanistic understanding of the newly discovered regulators of IFNβ response , we attempted to place these genes in the known framework of RIG-I signaling . It is known that ectopic expression of MAVS , TBK1 and a constitutively active mutant of IRF3 ( termed IRF3-5D ) can stimulate IFNβ transcription , independent of RIG-I [9] , [17] , [42] . By coupling the ectopic expression of these genes with individual silencing of the newly identified regulators , we generated a detailed map of the functional localization of their action within the RIG-I pathway . The results of the “stage determination assays” are shown in Figure 1A ( displayed inside the brown box ) and Table S1 . Among the 226 hit genes , the greatest number ( 55% ) was identified to serve a regulatory role upstream of MAVS . Among the rest , 5 . 5% , 11 . 3% and 25% of the total hit genes were found to function between MAVS and TBK1 , between TBK1 and IRF3 , and downstream of IRF3 , respectively . In summary , this forward genetics study revealed a global picture of the stage wise distribution of 226 novel regulators of RIG-I signaling cascade . Bioinformatics analysis of the RNAi screening results identified the kinase PPIP5K2 as a positive regulator of RIG-1 signaling ( Figure 1A , and 1B ) . PPIP5K2 is one of the enzymes that directly synthesizes inositol pyrophosphates ( Figure 1D ) . In relation to this , IPPK is another kinase that was also identified in the screen as a positive regulator of RIG-1 signaling; IPPK synthesizes IP6 , which serves as the common precursor material for inositol pyrophosphate synthesis . The key steps and enzymes involved in inositol pyrophosphate biosynthesis are shown in Figure 1D . The best studied inositol pyrophosphates in mammals are the two IP7 isomers ( 1-IP7 and 5-IP7 ) and IP8 [43] . These are synthesized by two classes of enzymes , the IP6Ks and the PPIP5Ks [44]–[49] . The inositol pyrophosphate pathway has not previously been implicated as participating in antiviral responses , so we set out to further characterize its role in innate immunity . We first validated that the siRNAs against IPPK efficiently knocked down gene expression ( Figure 2A ) . Moreover , Following stimulation of these cells by transfection with RIG-I ligand poly ( I:C ) , the knock-down of IPPK expression was confirmed to cause a major reduction of IFNβ-promoter driven luciferase activity ( Figure 2A ) . We also used q-RTPCR based quantification of IFNβ transcripts to verify the role of IPPK in influencing IFNβ transcript synthesis ( Figure 2B ) . Finally , transfection of siRNA resistant IPPK cDNA expressing plasmid into endogenous IPPK silenced cells using 3′-UTR targeting siRNA led to the recovery of the IFNβ response to a level comparable to that in normal cells , indicating the on-target specificity of gene silencing ( Fig . S3A ) . The silencing of IPPK will not only reduce the formation of IP6 but also the synthesis of the inositol pyrophosphates 1-IP7 , 5-IP7 and IP8 ( Figure 1D ) . The kinases PPIP5K1 and PPIP5K2 catalyze the synthesis of 1-IP7 and IP8 , but not 5-IP7 ( Figure 1D ) . Indeed , the RNAi screen also identified PPIP5K2 , but not PPIP5K1 , as a RIG-1 regulator ( see above ) . So we next investigated if the inositol pyrophosphates play roles in innate immunity . Silencing of the PPIP5K2 gene strongly reduced RIG-I driven IFNβ transcription and IFNβ promoter driven luciferase activity ( Figure 2B , C ) . We also retested PPIP5K1 since it was possible that the latter was missed in the primary screen . Notably , PPIP5K1 gene silencing also reduced the IFNβ reporter activity . Gene silencing was verified by both Western blot ( Figure 2C ) and q-RTPCR ( Figure S3B ) . The q-RTPCR based quantification also showed a notable decrease in the IFNβ transcript production in PPIP5K2 silenced cells ( Figure 2B ) . As shown in Figure S3A , ectopic expression of siRNA resistant PPIP5K2 rescued the loss of IFNβ response caused by ablation of endogenous PPIP5K2 using 3′-UTR targeting siRNA , confirming the on-target specificity of the knockdown . The knockdown of IPPK and PPIP5Ks did not significantly affect basal-level IFNβ or IFNα production when HEK293 cells were not stimulated by either RIG-I ectopic expression or transfection with poly ( I:C ) or infection with virus ( Figure S3C , S3D ) . Using JAK1 silenced cells , it was further determined that the observed effects of IPPK , PPIP5K1 and PPIP5K2 silencing on interferon response are independent of the autocrine amplification of the pathway ( Figure S3E ) . We next investigated the possible roles of the IP6Ks ( IP6K1 , IP6K2 and IP6K3 ) which participate in the synthesis of 5-IP7 and IP8 , but not 1-IP7 Figure 1D ) . Although none of these genes were identified from our genome-wide RNAi screen , we re-investigated their role in RIG-I signaling with validation of gene silencing . It was observed that both individual and simultaneous silencing of IP6K1 , IP6K2 and IP6K3 genes did not affect the interferon transcription ( Figure 2D ) . Furthermore , consistent with the gene knockdown data , fibroblasts from IP6K1 gene deficient mouse did not show any defect in the IFNβ response ( Figure S3F ) [50] . The fact that the IFNβ response is inhibited by knock-down of PPIP5Ks but not IP6Ks ( Figure 2 ) suggests that 1-IP7 , but not 5-IP7 ( Figure 1D ) , has functional significance in the innate immune response . Complete loss of expression of murine IP6K1 ( or the Kcs1 homologue in yeast ) was previously shown to adversely affect the functioning of mitochondria , and alters ATP levels [51] . However , no significant general cytotoxicity , mitochondrial toxicity or change in the levels of cellular ATP was found in cells transiently silenced for IPPK , PPIP5K1 and PPIP5K2 ( Figure S4A ) . The experiments described above used poly ( I:C ) in order to mimic a cellular viral infection . It is therefore significant that we also found silencing of IPPK , PPIP5K1 and PPIP5K2 dampened IFNβ transcription during infection of HEK293 cells by Sendai virus ( SeV ) , a known stimulator of RIG-I [52] ( Figure 2E ) . To further validate the physiological relevance of IPPK , PPIP5K1 and PPIP5K2 in IFNβ production , we also silenced the expression of these kinases in human primary monocyte derived macrophages , and then challenged them with Sendai virus . We found a significant decrease in IFNβ transcription in these RNAi-targeted human primary macrophages ( Figure 2F ) . No notable difference in SeV induced IFNβ response was observed when IP6K1-3 genes were silenced ( not shown ) . These experiments further indicate that the expression of the kinases involved in the synthesis of 1-IP7 is important for an effective interferon response . In addition to the transcriptional induction of IFNβ , signaling from several of the PRRs that sense RNA viruses also result in the production of another class of type-I interferons , the IFNα , as well as activation of the transcription factor NFκB [5] . Therefore it was important to determine whether inositol pyrophosphate-synthesis-pathway kinases are also required for the IFNα and NFκB response from RIG-I . We observed that silencing of IPPK , PPIP5K1 and PPIP5K2 in HEK293 cells led to a reduction in RIG-I mediated transcription of IFNα , determined using a luciferase reporter driven by the IFNα4 promoter ( Figure 2G ) . However , inositol pyrophosphate-synthesis-pathway kinases were not required for RIG-I triggered NFκB activation ( Figure 2H ) . This data indicated that these kinases regulate a step of RIG-I signaling that happens after the bifurcation of interferon and NFκB branches . In addition to RIG-I , there are several other PRRs such as TLR3 ( an endosomal PRR ) and MDA5 ( another cytosolic PRR ) , which also induce IFNβ transcription [1] . Therefore we investigated the specificity of the inositol pyrophosphates-synthesis-pathway kinases with regards to signaling by other PRRs . We found that repression of the expression of either IPPK , PPIP5K1 or PPIP5K2 attenuated the IFNβ response elicited by both TLR3 and MDA5 , to a level comparable to that observed in the case of RIG-I ( Figure 2I ) . These results demonstrated that inositol pyrophosphates-synthesis-pathway kinases play a broader role as a positive regulator of several major antiviral pathways . The identification of inositol pyrophosphate-synthesis-pathway kinases as positive regulators of the interferon response initiated by multiple PRRs ( Figure 2I ) indicates that this pathway acts at or downstream of the point in the signaling cascade where the actions of these particular PRRs converge: activation of the kinase TBK1 , which phosphorylates IRF3 , or further downstream . Indeed , the IFNβ induction arising from ectopic expression of MAVS and TBK1 , two key downstream components of RIG-I pathway , was diminished when IPPK , PPIP5K1 and PPIP5K2 were silenced ( Figure 3A ) . These data further indicate that the inositol pyrophosphates most likely regulate a step at the level or immediately downstream of TBK1 . Because activation of IRF3 happens immediately downstream of TBK1 , we next investigated the effect of interference with inositol pyrophosphate synthesis pathway gene expression on IRF3 functioning . The IRF3 exists as a monomer in its unstimulated state in the cytosol . When PRRs are stimulated , the phosphorylation of monomeric IRF3 leads to its homo-dimerization , followed by nuclear migration . We first investigated whether inositol pyrophosphate synthesis was needed for the nuclear translocation of activated endogenous IRF3 . In control experiments , the negative control siRNA treated HEK293 cells were stimulated with poly ( I:C ) , which led to a prominent nuclear accumulation of phosphorylated IRF3 ( pIRF3; Figure 3B ) . In additional control experiments , silencing of MAVS , the key adaptor of RIG-I , reduced the nuclear levels of pIRF3 ( Figure 3B ) . Notably , there was also a major reduction in the intra-nuclear levels of endogenous pIRF3 following silencing of IPPK , PPIP5K1 and PPIP5K2 ( Figure 3B , 3C ) . Next , we investigated whether the depletion of IPPK , PPIP5K1 and PPIP5K2 altered endogenous IRF3 dimerization . The knockdown of all three of these genes strongly reduced the degree of IRF3 dimerization that was induced by poly ( I:C ) ( Figure 3D , E ) , compared to that observed in negative control siRNA treated cells . The levels of GAPDH and Tubulin proteins were unaffected by the knockdown of these kinases , indicating there was not a global perturbation of protein expression ( Figures 3B , 3F ) . We finally determined whether poly ( I:C ) induced phosphorylation of endogenous IRF3 was affected by silencing of inositol pyrophosphate-synthesis-pathway kinases . Notably , it was found that knock-down of the expression of IPPK , PPIP5K1 and PPIP5K2 caused a reduction in the phosphorylation of endogenous IRF3 ( Figure 3F , 3G ) . In summary , the experiments described above argue that the expression of inositol pyrophosphate-synthesis pathway kinases is required for the TBK1-IRF3 axis to function; the absence of inositol pyrophosphate synthesis compromised IRF3 phosphorylation and dimer formation . Having established the involvement of the inositol pyrophosphate-synthesis-pathway as a regulator of antiviral response , we further sought to identify the mechanism by which this pathway modulates interferon signaling . We first investigated whether enhancing the cellular expression of these kinases has any effect on the interferon response . Indeed it was determined that the ectopic expression of IPPK , PPIP5K1 and PPIP5K2 induced a significant dose dependent enhancement of RIG-I driven IFNβ promoter reporter activity , in both the cells that were either stimulated or unstimulated with poly ( I:C ) ( Figure 4A ) . However , the enhancing effect of ectopic expression of these genes on the IFNβ reporter activity in cells pre-transfected with RIG-I and poly ( I:C ) was greater than that in the unstimulated cells ( Figure 4A ) . Both PPIP5K1 and PPIP5K2 ectopic expression caused a greater enhancement of the IFNβ response than did by IPPK . Even though silencing of IP6Ks did not affect IFNβ response , we also investigated whether the ectopic expression of IP6K1-3 has any effect on IFNβ response . Interestingly , the ectopic expression of IP6K1 , IP6K2 and IP6K3 also enhanced the IFNβ response significantly , although to a lesser degree than that promoted by overexpression of either PPIP5K1 or PPIP5K2 ( Figure 4B ) . These data revealed that the interferon response could be augmented by over-expression of any of the tested kinases in the inositol pyrophosphate synthesis pathway . In order to determine whether the kinase activity of these proteins is important for the interferon transcription , we next transfected cells with catalytically-inactive mutants . These mutant proteins were found to express at levels comparable to the corresponding wild type kinases . Remarkably , the kinase deficient mutants of IPPK , PPIP5K1 and PPIP5K2 all exhibited a decreased ability to facilitate the interferon response upon over expression , when compared with the corresponding wild type proteins ( Figure 4C ) . In addition , we noted an earlier report that the kinase domain of PPIP5K1 ( PPIP5K1-KD ) and PPIP5K2 ( PPIP5K2-KD ) was able to catalyze the formation of 1-IP7 , with greater efficiency than the full-length protein [47] . As shown in Figure 4D , indeed we found that over expression of both PPIP5K1-KD and PPIP5K2-KD enhanced the IFNβ reporter activity to an extent greater than that induced by full length PPIP5K1 and PPIP5K2 . We also found that inactivation of the catalytic activity of IP6K1 significantly diminished its ability to enhance IFNβ response upon ectopic expression ( Figure 4C ) . However , consistent with the gene knockdown data showing no role for endogenous IP6Ks in RIG-I signaling , HEK293 cells treated with IP6K kinase inhibitor TNP ( N2-[m-Trifluorobenzyl] , N6-[p-nitrobenzyl] purine ) did not show any defect in IFNβ response ( Figure S3G ) [53] . These experiments demonstrated that the inositol pyrophosphate-synthesis-pathway kinases regulated IFNβ transcription through their catalytic activities . That is , one or more of the soluble inositol pyrophosphates products are required for IFNβ production . The ability of ectopically expressed PPIP5K1/2 to stimulate interferon transcription ( Figure 4A ) could result from increased synthesis of either 1-IP7 and/or IP8 ( Figure 1D ) . For IP8 to be involved , IP6K activity would also be required . However , the stimulatory effects of over-expressed PPIP5K1/2 were not affected by either individual or simultaneous silencing of IP6K1-3 ( Figure 3E ) . Moreover , in control experiments , silencing of IPPK nearly completely abolished the ability of ectopically expressed PPIP5K1 and PPIP5K2 to enhance interferon transcription ( Figure 4F ) . That result is consistent with the requirement for IP6 as the precursor molecule for phosphorylation by PPIP5K1/2 to synthesize 1-IP7 ( Figure 1D ) . It was also observed that the diminished interferon response caused by PPIP5K1 silencing could be compensated by over expressed PPIP5K2 , or vice versa ( Figure 4G ) . These data indicate that 1-IP7 mediates the interferon transcriptional effects of the PPIP5K1/2 . Nevertheless , even though the aforementioned experiments identify 1-IP7 as being more important for enhancing interferon transcription than IP8 , the ectopic expression of IP6K1 , IP6K2 and IP6K3 also enhanced the IFNβ response significantly ( Figure 4B ) . These results raise the possibility that , at elevated IP6K1-3 expression levels , IP8 ( and/or possibly even 5-IP7 ) might substitute for 1-IP7 in regulating IFNβ expression . However , enhanced IFNβ reporter activity induced by ectopic expression of IP6K1-3 was mostly lost in the absence of expression of PPIP5K1 and PPIP5K2 ( Figure 4H ) . Thus , it is more likely that , at high levels of expression of IP6K1-3 , it is IP8 rather than 5-IP7 that substitutes for the actions of 1-IP7 . In this respect , it is notable that one of the diphosphate groups on IP8 is also attached to the 1-position . To further establish the role of inositol pyrophosphates in the immune response , we also studied a class of enzymes that dephosphorylates inositol pyrophosphates . In humans , the hydrolysis of short-lived inositol pyrophosphates has been attributed to three classes of diphosphoinositol-polyphosphate phosphohydrolase proteins ( DIPPs ) encoded by four genes belonging to the Nudix hydrolase family [44] , [54] , [55] . These hydrolases remove the terminal phosphate from inositol pyrophosphates . If inositol pyrophosphates regulate RIG-I signaling , then removal of their diphosphate would inhibit the interferon response . To test this prediction , we determined the effect of over expression of DIPP1 , DIPP2α and DIPP3α on RIG-I induced IFNβ promoter driven reporter activity . In agreement with our hypothesis , cells ectopically expressing either DIPP1 , DIPP2α or DIPP3α indeed showed a significantly attenuated interferon response ( Figure 4I; the rank order of efficacy of the DIPPs followed their reported rank order of catalytic activity ( DIPP1>DIPP3α>DIPP2α [54] . These data also further argued that the synthesis of inositol pyrophosphates is critical for the induction of IFNβ . In summary , the experiments described in this section argue that inositol pyrophosphates –particularly 1-IP7 - are important for the interferon response . The data described above , obtained from experiments using gene silencing and catalytically inactive mutants of IPPK , PPIP5K1 and PPIP5K2 , provided strong yet indirect evidence for the involvement of inositol pyrophosphates themselves in the interferon response . To further test this hypothesis , we employed a cell-free , virus-dependent assay for IRF3 activation . This was developed in an earlier study which reported that a purified mitochondrial fraction from Sendai virus infected cells could induce IRF3 phosphorylation in a cytoplasmic fraction prepared from uninfected cells [56] . We reproduced these results ( Figure 5A ) using similar subcellular fractions ( Figure S4B ) . It was significant that the degree of IRF3 phosphorylation was strongly reduced when the cytoplasmic fraction was prepared from PPIP5K2-silenced cells ( Figure 5A ) . Next , we reasoned that if inositol pyrophosphates were directly involved in IRF3 phosphorylation , their addition to the in vitro assay system would rescue the loss of IRF3 activation caused by the silencing of PPIP5K2 . For these experiments we added samples of either 1-IP7 , 5-IP7 or IP8 that were prepared enzymatically and purified electrophoretically [57] , to the cell free IRF3 phosphorylation assays . Remarkably , 5 min after the addition of 1-IP7 in the range of its projected physiological concentration ( 0 . 5 uM [54] ) the loss of IRF3 phosphorylation that resulted from PPIP5K2 silencing was rescued to a level that was equivalent to that in wild type cells ( Figure 5B ) . At this time point , IP8 had no significant effect ( Figure 5C ) . , However , IP8 was found to substitute for 1-IP7 in promoting IRF3 phosphorylation , at the 10 min time point ( Figure 5C , E ) . The effect of 1-IP7 on IRF3 phosphorylation is consistent with the conclusions drawn from the above described kinase silencing and ectopic expression experiments . Next , we tested 5-IP7 which from genetic experiments ( see above ) was predicted not to regulate the interferon response . Indeed , we found that 5-IP7 did not promote IRF3 phosphorylation ( Figure 5D ) . The observation that IP8 acted less efficiently than 1-IP7 in supporting IRF3 phosphorylation in vitro , is consistent with that activity in intact cells only emerging in an over-expression paradigm ( Figure 4 ) . In the latter case , IRF3 phosphorylation was stimulated upon ectopic expression of IP6Ks in a manner that was also dependent upon endogenous PPIP5Ks ( Figure 4H ) , and hence the synthesis of IP8 ( Figure 1D ) . In conclusion , these cell free system based experiments considerably strengthened our hypothesis ( see above ) that among the inositol pyrophosphates , it is 1-IP7 that is the more physiologically-relevant mediator of IRF3 phosphorylation and activation . Earlier studies had indicated that one mechanism by which the inositol pyrophosphates regulates signaling pathways involves the transfer of the β-phosphoryl of their diphosphate group to phosphorylated serine residues on target proteins ( termed protein pyrophosphorylation ) [58] , [59] . We therefore investigated whether the mechanism of action of inositol pyrophosphates in the interferon response could be dependent on the transfer of their β-phosphate . For these experiments we used synthetic analogues of 1-IP7 and IP8 , in which the diphosphate was replaced with a phosphonoacetic acid ( PA ) ester [60] . Although the PA ester resembles a diphosphate group in several respects , its terminal phosphonate group ( equivalent to the β-phosphate of a diphosphate ) cannot be transferred , due to the stability of the P-C bond it contains . Interestingly , we found that addition of the PA analogues of 1-IP7 and IP8 failed to recapitulate the actions of the natural 1-IP7 and IP8 molecules ( Figure 5F , 5G ) . These data are consistent with potential phosphoryl transfer underlying the mechanism of action of inositol pyrophosphates in regulating interferon signaling . We also investigated whether inositol pyrophosphate-synthesis-pathway kinases contribute to the immune resistance of human cells to viral infection . For this , we used Sendai virus to infect HEK293 cells in which either IPPK , PPIP5K1 or PPIP5K2 was knocked-down . In each case , the kinase knock-down led to an increased viral load , as determined by q-RTPCR ( Figure 6A ) . Furthermore , we also found that HEK293 cells were more resistant to infection with influenza A virus upon over expression of either IPPK , PPIP5K1 or PPIP5K2 ( Figures 6B and 6C ) . Interestingly , ectopic expression of IP6K1 also enhanced the cellular immunity to influenza A virus infection , in agreement with their ability to increase the interferon response upon ectopic expression ( Figures 6B and 6C ) . We further investigated whether interference with inositol pyrophosphate-synthesis-pathway kinases can affect viral infection dependent induction of ISG15 ( a major interferon stimulated antiviral gene ) in Sendai virus challenged HEK293 cells . As shown in Figure 6D , knock-down of either IPPK , PPIP5K1 or PPIP5K2 attenuated the induction of ISG15 . This was specifically due to a defect in interferon production or indirect induction of ISG15 by IRF3 , because the inositol pyrophosphate-synthesis-pathway did not show any role in exogenous IFNβ induced , JAK/STAT signaling mediated ISRE activation ( not shown ) . Furthermore , we also found that both p ( I:C ) stimulation and Sendai virus infection moderately enhanced the transcription of IPPK , PPIP5K1 and PPIP5K2 in HEK293 cells ( Figure 6E ) . In summary , these results further confirmed that inositol pyrophosphate-synthesis-pathway kinases are required for interferon mediated antiviral innate immunity .
Our manuscript provides important new information concerning the regulation of the interferon-mediated innate immune response to infection by RNA viruses . For example , our human genome-wide RNAi screen identified 226 novel regulators of RIG-1 mediated IFNβ transcription . A particularly significant finding of this genomic study was the identification of the pathway synthesizing inositol pyrophosphate 1-IP7 as being essential for the interferon response . Moreover , this is the first time that a specific function for 1-IP7 has been identified in mammalian cells , thereby opening up a new area of research in the inositol pyrophosphate field . The importance of a genome-wide , systems-biology approach to understanding the innate immune response was outlined in the Introduction . Among these newly identified genes , several may be “pan-regulators” of interferon induction . Indeed , our secondary assays revealed that 36 . 3% of the identified genes act downstream of TBK1 , a common component of several antiviral PRR pathways . It is interesting to note that more than half ( 60 . 5% ) of the hit genes regulated a segment of the signaling chain that is likely unique to RIG-I pathway ( upstream of TBK1 ) , and not common with other interferon inducing PRR pathways . This indicates that the regulation of the proximal steps of PRR signaling leading to interferon induction is more complex than the commonly shared steps . Given their distinct compartmentalized cellular localizations , it is not surprising that the PRRs undergo more intricate regulation at their proximal signaling steps , than the downstream conserved steps . The meta-analysis demonstrated that at least 33 of the obtained hit genes were previously reported to show transcriptional up-regulation during challenge with various immune stimuli that activates interferon response . However the functional relevance of the differential expression of these 33 genes during interferon response was not known previously . Our identification of these genes as important regulators of the interferon response demonstrates that the current systems biology based approach to study RIG-I signaling also helps to functionally interpret genomics studies of host responses to infection . We further anticipate that our data-set will facilitate future studies in this field . Given that PRRs also recognize damage-associated molecular patterns produced by endogenous stress signals [61] , it is intriguing that inositol pyrophosphates have also been implicated in mediating responses to a variety of stress responses , including osmotic stress , thermal challenges and metabolic stress [43] . Our study opens up possible new directions for identifying the mechanisms of action of inositol pyrophosphates in combating these stresses . Our study characterized an essential regulatory role for inositol pyrophosphates in the interferon production . Although an earlier study had identified PPIP5K2 as an interferon inducible gene [39] , inositol pyrophosphates themselves have not been shown before to play any direct role in antiviral innate immune response . Structural analysis of PPIP5K2 [62] has revealed that it has an exquisitely specific active site that can only phosphorylate IP6 and 5-IP7 , to yield 1-IP7 and IP8 respectively . The in vitro reconstituted RIG-I signaling assay using purified inositol pyrophosphates identified that both 1-IP7 and IP8 are capable of regulating the interferon response . However , based on the comparative analysis of the results of experiments involving silencing of the key enzymes in this pathway along with effects of over-expression of wild-type kinases , we propose that 1-IP7 would most likely be the physiologically-relevant regulator of IFNβ transcription ( among inositol pyrophosphates ) . The results of the virus-dependent cell free reconstitution assays ( Figure 5 ) provided additional direct evidence that 1-IP7 is needed for the functioning of TBK1-IRF3 axis leading to the phosphorylation of IRF3 , a precondition for its competence to stimulate IFNβ transcription . Currently it is proposed that inositol pyrophosphates may regulate cellular pathways either by β-phosphoryl transfer to host proteins ( protein pyrophosphorylation ) , or as cofactors that may bind to target proteins [43] , [58] , [59] , [63]–[65] . We found that synthetic , metabolically stable analogues of 1-IP7 and IP8 failed to recapitulate the effects of the physiological isomers ( Figure 5 ) , consistent with a mechanism of action involving phosphoryl transfer . Nevertheless , given that in earlier studies [59] all of the inositol pyrophosphates were equally competent at β-phosphoryl transfer to proteins , it is intriguing that 5-IP7 did not support IRF3 phosphorylation , suggesting that the potential target protein may also exhibit stereo-selective recognition . It is also interesting that the phosphatidylinositol 5-phosphate , a member of the separate inositol-lipid signaling family , was recently reported to stimulate IRF3 phosphorylation [66] . Thus , the distinct regulatory properties of both membrane-restricted signals ( inositol lipids ) and soluble , diffusible signals ( inositol pyrophosphates ) , may converge upon the innate immune response to viral invasion . Lastly , our study may seed the discovery of novel drug targets and drugs that can be used to manipulate the interferon response , thereby improving therapy for viral infection . For example , it might be possible to develop cell permeable small molecules that are capable of imitating the role of 1-IP7 . Conversely , inhibitors of PPIP5Ks may find useful application to control excessive interferon response observed during various medical conditions such as autoimmune diseases . In summary , this study provided valuable insights into the global regulation of interferon response , and identified a novel role for inositol pyrophosphates in antiviral immunity .
The RNAi screening employed a siRNA library from Dharmacon/ThermoFischer scientific ( human whole genome siGENOME siRNA Library , Cat#GU-005005-02 ) targeting 18 , 164 annotated human genes was used the RNAi screening . The screen was performed in 384 well imaging compatible plates ( Corning cat#3712 ) . Briefly , 2500 HEK293 cells ( in 20 µl of DMEM with 10% fetal bovine serum ) were seeded in each well having 50 nM siRNA complexed with 0 . 05 µl lipid Dharmafect1 ( in 20 µl of serum free DMEM ) ( ThermoFischer scientific ) . At 46 hr , 40 ng RIG-I and 50 ng human IFNβ-GFP reporter plasmids ( in 5 µl of serum free DMEM ) were transfected with Fugene ( Roche ) . At 52 hr , 2 µl of a 10 µg/ml stock of poly ( I:C ) complexed with the lipid Fugene ( Roche ) in serum free DMEM was added to each well . At 72 hr , the cells were fixed with 3% paraformaldehyde , followed by washing with phosphate buffered saline and nuclear staining with DAPI . Using high content fluorescence microscopy ( ImageXpress Micro , Molecular Devices Corporation ) , images of each well was captured at 4× magnification . The number of cells , and number of GFP positive cells were determined by algorithm-driven data analysis using the MetaXpress software ( Version 3 , Molecular Devices Corporation ) . Any gene silencing that reduced cell number by greater than approximately 50% was eliminated for potential toxicity . siRNAs targeting IRF3 and MAVS were used as positive controls , and a non-targeting ( NT ) siRNA served as the negative control . The bioinformatics analysis of the siRNA screen was facilitated by the RNAither package of Bioconductor in R [67] . The screen was performed in duplicate . The mean percent GFP-positive cells was calculated for each gene ( the screen was performed in duplicate ) , and then a Z-score normalization was performed by subtracting the median of the plate and dividing by the median absolute deviation per plate . Gene ontology enrichment analysis and network analysis was conducted on the 226 novel regulators that were identified in the secondary siRNA screen using Ingenuity Pathway Analysis ( IPA ) software . Gene expression datasets were accessed from the NCBI Gene Expression Omnibus in series matrix file format from five previous studies [21] , [37]–[40] . Raw expression values were log2-transformed . Two-group comparisons were made between sample sets using Student's t-test followed by the false-discovery rate ( FDR ) method to correct for multiple hypothesis testing , setting the cut-off at FDR<0 . 05 . Significantly differentially expressed genes from each study were then queried against the list of 226 genes identified from the RNAi screen . The reporter assays were performed as previously reported [9] , [42] . Briefly , HEK293 cells were transfected with expression plasmids of human PRRs ( RIG-I or TLR3 or MDA5 ) , human IFNα4 promoter , or human IFNβ promoter or NFκB-target promoter driven luciferase reporters ( pGL2 vector , Promega ) and a constitutively transcribed Renilla luciferase reporter ( p-RL-TK , Promega ) for 24 hr . Cells were then either directly assayed for luciferase activity , or were stimulated with poly ( I:C ) by either transfecting ( 500 ng/ml for RIG-I assay ) or by adding to the medium ( 20 µg/ml for TLR3 ) for additional 18 hr , and luciferase reading was performed using Dual-Glo assay kit ( Promega ) . For ectopic expression assays , HEK293 cells grown overnight were transfected with the indicated plasmids for 24 hr with or without RIG-I and poly ( I:C ) , and luciferase assays were performed . Values were normalized to that of Renilla luciferase internal control . HEK293 cells or primary macrophages were infected with Sendai virus ( Cantell strain , Charles River Laboratories ) at 30–80 HA units for 18 hr , and processed for q-RTPCR . A genetically modified Influenza A virus ( IAV ) ( A/Puerto Rico/8/34 ) with green fluorescent protein insertion was propagated in MDCK cells and used for the studies [68] . The HEK293 cells were infected with IAV at an MOI of 2 for 12 hr , fixed and microscopy was performed . The IRF3 activity was determined using previously reported protocols [42] , [69] , [70] . Detection of IRF3 phosphorylation: Overnight grown 5×105 HEK293 cells in 6-well plates were transfected with 500 ng of RIG-I for 24 hr , and stimulated with 4 µg of poly ( I:C ) for 4 hr . The clarified cell lysate in RIPA buffer ( 50 mM TrisHCl pH 7 . 4 , 150 mM NaCl , 2 mM EDTA , 1% NP-40 , 0 . 1% SDS , protease and phosphatase inhibitors ) ( pooled from three wells , for each condition ) were separated by Sodium dodecyl sulphate polyacrylamide gel electrophoresis ( SDS-PAGE ) , and probed with anti-pIRF3 ( Serine 396 ) and anti-IRF3 antibodies . For the detection of IRF3 dimers , after 4 hr stimulation , the cells were lysed in mild cold lysis buffer ( 50 mM Tris-HCl , 150 mM NaCl , 1 mM EDTA and 1% NP-40 ) , and the protein was separated on native acrylamide gel , with 1% sodium deoxycholate in the cathode buffer . The IRF3 dimer was visualized by Western blot . For the detection of IRF3 nuclear migration by Western blot , after 4 hr stimulation , nuclei were isolated using Nuclear extraction Kit ( Activemotif ) , and cytoplasmic and nuclear proteins were separated by SDS-PAGE and detected by Western blot . For the Western blot , the proteins were transferred on to nitrocellulose membranes using Transblot ( Biorad ) , and detected by immuno-detection with appropriate primary antibodies . The transferred proteins of interest were visualized using Licor infrared imaging system , with IRDye 800CW and 680RD as secondary antibodies ( Licor ) . This assay was performed as reported earlier [56] . Briefly , cytoplasm from uninfected cells was incubated with isolated mitochondrial fraction from Sendai virus infected cells at 30°C , and pIRF3/IRF3 were detected by Western blot ( visualized using HRP conjugated secondary antibody ) at different time points . The assay buffer was 20 mM HEPES-KOH ( pH 7 . 0 ) , 2 mM ATP , 5 mM MgCl2 , and 0 . 25 M D-mannitol . The methodology was reported previously [57] . The inositol pyrophosphates were prepared enzymatically , using 1 . 2 mM InsP6 as starting substrate . The synthesis of 1-InsP7 , 5-InsP7 and InsP8 were carried out by incubating ( at 37°C ) IP6 with respectively 0 . 12 mg/ml PPIP5K2KD for 22 . 5 h , 0 . 17 mg/ml IP6K1 for 3 h or 0 . 17 mg/ml IP6K1 and 0 . 11 mg/ml PPIP5K2KD together for 3 h . The reaction buffer composition was 20 mM Hepes , pH 6 . 8 , 50 mM NaCl , 6 mM MgSO4 , 1 mM DTT , 6 mM phosphocreatine , 24 unit/ml creatine kinase and 5 mM ATP disodium salt . The reactions were quenched and neutralized with , respectively , 0 . 2 volumes 2 M HClO4 and 0 . 34 volumes 1 M K2CO3 , 40 mM EDTA or placed at 100°C for 3–5 min . The synthesized inositol pyrophosphates were purified using a previously reporter polyacrylamide gel electrophoresis-based method that was modified for scale up [71] . The inositol pyrophosphates were detected by staining with Toluidine Blue [71] , and quantified through mass assay of the released orthophosphate upon complete hydrolysis by wet-ashing at 120°C for 48 h [72] . The phosphonoacetic acid ( PA ) analogues of 1-IP7 and IP8 were chemically synthesized using a similar strategy to that previously reported for 5-IP7 [60] . The IP8 analogue was used as a racemic mixture , i . e . a 1∶1 mixture of 1 , 5-[PA]2-IP4 and 3 , 5-[PA]2-IP4 . IPPK , NM_022755 , PPIP5K2 , NM_015216; PPIP5K1 , NM_014659; IP6K1 , NM_001006115; IP6K2 , NM_001005911; IP6K3 , NM_054111 . Data are expressed as mean ± SD of one representative experiment performed in triplicates . Statistical significance of differences in mean values was analyzed using unpaired two-tailed Student's t-tests; and p-values<0 . 05 were be considered statistically significant . *p<0 . 05; **p<0 . 01 . Additional descriptions of the general reagents , experimental procedures , siRNA and DNA primer sequences that were used in the study are provided in Supplementary Methods S1 . | The innate immune system is critical for viral infection control by host organisms . The type I interferons are a family of major antiviral cytokines produced upon the activation of innate immune pattern recognition receptors ( PRRs ) by viruses . The RIG-I is a major PRR that uniquely detects RNA viruses within the cytoplasm . In this study , we aimed to discover cellular genes and pathways that play regulatory roles in the transcriptional induction of type I interferon-β ( IFNβ ) . Using a human genome wide RNA interference ( RNAi ) screening , we identified 226 genes whose expression is important for proper IFNβ production . Through bioinformatics-based mining of the RNAi screen results , we identified that the cellular pathway synthesizing inositol pyrophosphates , a class of inositol phosphates with high-energy diphosphates , is a key positive regulator of RIG-I mediated IFNβ production . The kinases IPPK , PPIP5K1 and PPIP5K2 , that synthesize inositol pyrophosphate 1-IP7 , regulated IFNβ response in a catalytically dependent manner . Mechanistic studies identified that 1-IP7 synthesis pathway was needed for efficient phosphorylation of IRF3 . The DIPP family of inositol pyrophosphate hydrolases negatively regulated the IFNβ response , upon ectopic expression . In summary , this study generated a global view of the regulation of RIG-I signaling , and identified inositol pyrophosphates as important regulators of antiviral response . | [
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] | 2014 | Human Genome-Wide RNAi Screen Identifies an Essential Role for Inositol Pyrophosphates in Type-I Interferon Response |
In human cells , DNA double-strand breaks are repaired primarily by the non-homologous end joining ( NHEJ ) pathway . Given their critical nature , we expected NHEJ proteins to be evolutionarily conserved , with relatively little sequence change over time . Here , we report that while critical domains of these proteins are conserved as expected , the sequence of NHEJ proteins has also been shaped by recurrent positive selection , leading to rapid sequence evolution in other protein domains . In order to characterize the molecular evolution of the human NHEJ pathway , we generated large simian primate sequence datasets for NHEJ genes . Codon-based models of gene evolution yielded statistical support for the recurrent positive selection of five NHEJ genes during primate evolution: XRCC4 , NBS1 , Artemis , POLλ , and CtIP . Analysis of human polymorphism data using the composite of multiple signals ( CMS ) test revealed that XRCC4 has also been subjected to positive selection in modern humans . Crystal structures are available for XRCC4 , Nbs1 , and Polλ; and residues under positive selection fall exclusively on the surfaces of these proteins . Despite the positive selection of such residues , biochemical experiments with variants of one positively selected site in Nbs1 confirm that functions necessary for DNA repair and checkpoint signaling have been conserved . However , many viruses interact with the proteins of the NHEJ pathway as part of their infectious lifecycle . We propose that an ongoing evolutionary arms race between viruses and NHEJ genes may be driving the surprisingly rapid evolution of these critical genes .
DNA double-strand breaks are a particularly toxic form of DNA lesion . Such breaks are repaired through several pathways , the most well-studied being homologous recombination and non-homologous end joining ( NHEJ; reviewed in [1] ) . NHEJ is also required for V ( D ) J recombination , which generates immunoglobulin and T cell receptor diversity . Accordingly , mutations in NHEJ genes have been linked to both cancer and immune deficiencies . Given the central importance of these processes , NHEJ genes are expected to have a low tolerance for mutations . Such a hypothesis would be supported if sequences of NHEJ genes are stable and relatively unchanging over evolutionary time . In contrast to this expectation , a genome-wide analysis uncovered NHEJ as one of the two functional pathways most enriched for positive selection during Saccharomyces evolution [2] . Positive selection occurs when natural selection operates on an advantageous mutation , driving an increase in its prevalence over time , and sometimes leading to fixation of this mutation in the species in which it arose . Because advantageous mutations commonly involve a change in protein sequence , recurrent rounds of positive selection can lead to relatively rapid protein sequence evolution over time . Positive selection has been found to predominantly affect genes in three functional classes: reproduction , immunity , and environmental perception ( smell , taste , etc ) , presumably because these processes are under strong selection for constant adaptive change [3]–[10] . The intriguing observation of positive selection in the NHEJ genes of Saccharomyces remains unexplained , but could potentially be attributed to the fact that NHEJ is not the major pathway for the repair of double-strand breaks in yeast [11] . Relaxation of evolutionary constraints on NHEJ genes in yeast species , due to their reliance predominantly on the homologous recombination pathway , could have made NHEJ genes vulnerable to competing evolutionary forces . In this study , we have analyzed the molecular evolution of NHEJ genes in primates , including humans , where NHEJ is the major pathway for DNA double-strand break repair . NHEJ is activated upon detection of DNA double-strand breaks . After detection , NHEJ proteins enzymatically process broken DNA ends to allow for efficient end joining . Repair is then completed through the action of repair-specific DNA polymerases and the NHEJ ligation complex , which fill in and seal the break [1] . To analyze the selective pressures that have shaped the genes of the human NHEJ pathway , we generated sequence datasets of primate orthologs from twenty simian primate species . We find support for positive selection in five NHEJ genes: NBS1 , CtIP , Artemis , XRCC4 and POLλ . Analysis of human polymorphism data indicates that positive selection has also operated on XRCC4 in modern humans . Crystal structures are available for the Nbs1 , XRCC4 , and Polλ proteins , and in all cases we find that amino acid sites targeted by positive selection fall on protein surfaces . It is well-established that rapidly evolving amino acid residues tend to be found on the surfaces of proteins [12]–[14] . In previous studies where the significance of these residues has been structurally or functionally investigated , it has been shown that they modulate protein-protein , protein-ligand , or protein-DNA interactions [15]–[24] . However , we demonstrate biochemically that positive selection in Nbs1 at one of the three residues identified has not affected its physical interactions with other DNA repair components . In the discussion , we propose that the positive selection of NHEJ genes may be explained by the diverse viruses and genetic parasites that interact with these proteins to promote their own lifecycle .
We utilized primate sequence datasets to study the evolutionary history of human NHEJ genes . With human population genetic data , evolutionary pressures can usually only be summarized for chromosomal regions larger than a single gene . However , with inter-species divergence data , resolution of evolutionary signatures can be increased to the level of a single gene , and it is sometimes possible to see the serial fixation of mutations in particular gene regions or even codons . The limitation in these studies is the number of available primate sequences . We first performed a preliminary survey of the selective pressures that have shaped all of the major genes of the NHEJ pathway ( Figure 1A ) , so that we could generate appropriate primate datasets for candidate genes containing signatures suggestive of positive selection . Five nearly complete primate genome projects are publicly available: human , chimpanzee , orangutan , rhesus macaque , and marmoset . Ten possible pairwise gene comparisons can be made between these five species , but three pairwise comparisons ( human-orangutan , human-rhesus , and rhesus-marmoset ) were chosen that maximize divergence and minimize phylogenetic re-sampling ( Figure 1B ) . For each NHEJ gene , these three pairwise gene alignments were constructed and analyzed with a custom algorithm that calculates dN/dS in sliding windows along the length of each gene [25] . The dN/dS ratio captures the ratio of non-synonymous ( dN; changing the encoded amino acid ) to synonymous ( dS; silent ) DNA mutations that have accumulated since two genes last shared a common ancestor [26] . For most protein-encoding genes , the observed number of non-synonymous mutations is far less than the number of synonymous mutations observed ( dN/dS<1 ) [5] . This is because mutations which cause an alteration in amino acid sequence are more likely to be detrimental to proper protein folding and function , and are therefore typically selected against ( purifying selection ) . As expected in a typical gene , dN is less than dS ( dN/dS<1 ) for all windows along the length of the NHEJ gene KU70 ( Figure 1C ) . Under positive selection , non-synonymous mutations are swept through populations more quickly than neutral or nearly-neutral synonymous mutations due to a selectable advantage that they convey . After many such rounds , such a regime gives rise to the dN>dS signature that is indicative of positive selection ( dN/dS>1 ) . Sliding window analysis of dN/dS is useful when making pairwise gene comparisons , as positive selection may be limited to specific regions that are buried within a gene that is otherwise conserved . In the case of XRCC4 , sliding window analyses of human-rhesus and rhesus-marmoset pairwise alignments highlight the 3′ end of the gene as having signatures of dN/dS>1 ( p<0 . 001 and p<0 . 005 , respectively; Figure 1C ) . In this region , human and rhesus XRCC4 sequences differ by nine non-synonymous DNA mutations and zero synonymous mutations . In the human–orangutan comparison , a different region in the 5′ end of the gene shows a significant inflation of dN/dS above 1 ( p<0 . 05 ) . The different location of this signal may indicate a unique selective force that is operating specifically in the great apes . Sliding window analyses have an inherent multiple testing problem that is difficult to correct because of the non-independence of tests ( windows overlap ) [27] . Nevertheless , we have successfully utilized sliding window analysis as a pre-screening tool in several previous studies [2] , [28] . As an ad hoc method for eliminating some false positive signatures , we sought genes with regions of dN/dS significantly>1 in at least two out of three different pairwise primate comparisons made . All pairwise comparisons for each NHEJ gene are shown in Figure S1 , and the maximum dN/dS value found in each comparison is summarized in Figure 1D . We find that five out of thirteen NHEJ genes bear significant regions of dN/dS>1 in at least two out of the three primate comparisons made ( highlighted in gray in Figure 1D ) . Thus , we have identified preliminary signals of positive selection in five candidate NHEJ genes: NBS1 , Artemis , CtIP , POLλ , and XRCC4 . In order to verify positive selection with greater statistical rigor , larger sequence datasets are required . We sequenced all five candidate genes from 15 additional hominoid , old world monkey , and new world monkey species . Despite the fact that no significant windows of dN/dS>1 were observed in any of the pairwise comparisons of XLF ( Figure 1D ) , we also included this gene because positive selection was previously reported in an analysis of mammalian XLF sequences [29] . In total , 90 primate genes were sequenced ( 6 genes , each from 15 species ) . We also re-sequenced all genes that were incomplete in the available primate genome projects ( chimpanzee , orangutan , rhesus macaque , or marmoset ) . Details of primate cell lines , cell culture , mRNA extraction , cDNA library construction , and divergent-species PCR are given in the materials and methods section and in Tables S1 , S2 , S3 . The resulting dataset for each gene is comprised of orthologs from 20 primate species that represent approximately 35 million years of primate evolution [30] . The multiple sequence alignment generated for each gene was analyzed for positive selection with the “codeml” program in PAML [31] . The codeml program provides a maximum likelihood framework for estimating dN/dS rates over the entire history of primate evolution by integrating over all ancestral gene sequences in the context of a phylogeny [32] , [33] . This program offers several models for gene evolution , some where no codons are allowed to evolve with dN/dS>1 ( NSsites models M1a , M7 and M8a ) , and others where positive selection of some codons is allowed ( NSsites models M2a and M8 ) . A likelihood ratio test allows comparison of positive selection models to null models . Results of all model comparisons for each gene are provided in Tables S4 , S5 , S6 , S7 , S8 , S9 , and the results of the M8a vs . M8 comparisons , using the f61 model of codon usage , are summarized in Table 1 . The null model ( M8a ) is rejected ( p<0 . 05 ) in favor of the model of positive selection ( M8 ) in four of these six genes: CtIP , Artemis , XRCC4 , and POLλ . For NBS1 , the null model was very nearly rejected ( p = 0 . 056 ) . This analysis did not support a model of positive selection in primate XLF ( p = 0 . 59 ) . As mentioned above , sliding window analysis did not detect domains of positive selection in XLF . In conclusion , we find strong support for positive selection in four genes of the primate NHEJ pathway , a surprising finding given the critical role that these proteins play in DNA repair . Analysis of the 20-species NBS1 dataset yielded marginal support for positive selection ( p = 0 . 056; Table 1 ) . However , we noticed that several amino acid positions in the NBS1 protein alignment had changed multiple times exclusively in hominoid species ( humans , great apes , and gibbons ) . Based on this , we considered that positive selection of NBS1 may be specific to hominoids . Indeed , analysis of NBS1 from only the hominoid species resulted in improved statistical support for positive selection ( p = 0 . 048; Table 1 ) , despite the fact that the analysis of only eight sequences should greatly reduce statistical power . To formally test the hypothesis of hominoid-specific positive selection , we analyzed our datasets with “branch-site” models of evolution [34] . This test allowed us to determine whether there are codon positions evolving under positive selection specifically in the hominoid clade . NBS1 was the only one of the six NHEJ genes for which this hypothesis was supported ( p<0 . 005; Table S10 ) , and support is robust under all models of codon usage ( Table S11 ) . Because three total tests were performed on the NBS1 dataset , a Bonferroni-corrected p-value can be calculated for the rejection of the null hypothesis in the branch-sites test ( p<0 . 015 ) . Thus , hominoid-specific positive selection is supported in NBS1 . Interestingly , the yeast ortholog of NBS1 ( XRS2 ) was also identified as being under positive selection during Saccharomyces evolution [2] . Specific codon sites that have been the target of recurrent positive selection could be identified in the dataset for each NHEJ gene ( Table 1 ) . Posterior probabilities of codons included in the dN/dS>1 site class are commonly considered highly significant at cutoffs as low as P = 0 . 90 , and potentially even lower [35] . The positions of these amino acid sites are summarized in Figure 2 . Crystal structures have been solved for Polλ , XRCC4 , and Nbs1 , allowing us to further analyze the patterns of positive selection in these three proteins . Polλ is one of two DNA polymerases involved in the filling of gaps formed during NHEJ [36] . Approximately 5% of the codons in this gene were identified as evolving under positive selection , with an average dN/dS value of 3 . 2 ( Table 1 ) . Eight specific codons could be assigned to this class with high posterior probability ( P>0 . 90 ) , and these sites are scattered across the linear protein sequence ( Figure 2 ) . The crystal structure of the 39 kDa Polλ catalytic domain has been solved in complex with substrate DNA , and this catalytic core is comprised of the fingers , palm , thumb , and 8 kDa subdomains ( Figure 3 ) [37] . Four of the eight amino acid sites identified as being positively selected are part of this catalytic core domain . All four ( E330 , S381 , R441 , and R484 ) map to the outer surface of the three-dimensional structure ( red balls in Figure 3 ) , with none of the sites being found within the enzyme active site . Thus , residues under recurrent positive selection fall on the protein surface , and mutations at these sites are not predicted to directly affect catalytic activity . The NHEJ-specific ligase complex is composed of DNA ligase IV ( Lig4 ) along with the regulatory molecules XLF and XRCC4 [1] . The dN/dS>1 site class in XRCC4 is assigned a value of dN/dS = 15 , nearly double the value seen for any other NHEJ gene ( Table 1 ) . Given the extreme value , only one codon , L243 , can be supported as a member of this class with high posterior probability ( P>0 . 99 ) . To uncover more codons that may be evolving under positive selection , a secondary analysis was performed on the three XRCC4 structural domains: the N-terminal head domain , which is involved in DNA binding , the coiled-coil stalk domain , which includes the ligase binding domain , and the unstructured C-terminal domain ( residues 204–336 ) . Positive selection is supported only in the C-terminal domain ( p<0 . 001; Table 1 ) . Because four tests were performed on the XRCC4 dataset , the Bonferroni-corrected p-value for the observation of positive selection in the C-terminal domain is p<0 . 004 . In this domain , six codon sites , including L243 identified previously , were identified as evolving under positive selection ( P>0 . 90 ) , with support for five of these being P>0 . 95 . These codons were now collectively assigned a dN/dS value of 8 . 7 . All of these codons were also identified , albeit with lower confidence , in the full-length XRCC4 analysis ( Table S7 ) . The partial crystal structure of the XRCC4 dimer in complex with its binding partner , Lig4 , has been solved [38] . All six of the identified codons map just downstream of the Lig4-binding domain ( red dots in Figure 4A ) , in a region of the protein where the structure is predicted to transition from an alpha-helix to an unstructured domain . This unstructured domain is not included in the crystal structure , but has been represented in schematic form for illustration . Strikingly , of the five sites supported at the 95% confidence level , the first four ( R205 , Q211 , A216 , and C218 ) lie within a 14 amino acid stretch of the protein ( 4% of the length of the protein ) , and the fifth site ( L243 ) lies just 25 residues downstream of this cluster . We assessed the significance of this clustering on the linear protein sequence by determining how many times a random sampling of five sites fell in a cluster equal to or smaller than the 39 amino acid region that contains the sites under positive selection . Comparing this observed distance to a null distribution ( 100 , 000 permutations ) lends statistical support to the hypothesis that these positively selected sites are clustered ( p = 0 . 0005 ) . The functional significance of this “patch” of positive selection is unknown . A protein alignment of primate XRCC4 in this region is shown in Figure 4B . To the left , a cladogram shows the relationship of the twenty primate species used in this study . Amino acid positions evolving under positive selection are shown in the alignment in gray . This unstructured C-terminal domain has been shown to be dispensable for repair and V ( D ) J recombination [39] , [40] . However , this domain also contains a number of regulatory sites including a SUMOylation site and several DNA-PKcs phosphorylation sites [41] , [42] , as well as a known cancer-linked mutation [43] ( Figure 4B ) . We investigated whether the NHEJ genes that have been subject to ancient recurrent positive selection in simian primates are also under recent local adaptation in humans . We examined the five genes POLλ , XRCC4 , Artemis , NBS1 , and CtIP for signals of selection in the HapMap Phase II [44] data using a recently published method , the Composite of Multiple Signals ( CMS ) [45] . By combining multiple tests , CMS increases resolution for localizing signals of selection by up to 100-fold , and has a lower false-positive rate than the component individual tests . We examined SNPs within and surrounding each gene of interest , with a window size of 100kb upstream and 100kb downstream of each gene ( see Materials and Methods ) . In the European population , the CMS signal for XRCC4 is significant at a threshold that yields a 0 . 1% false positive rate in simulations , and is one of the top 60 strongest signals in the genome ( Table S12 ) . Applying CMS to fine-map the region , we localized the signal to 83kb entirely within the gene , suggesting that XRCC4 is a target of recent local adaptation ( Figure 5 ) . In the other four genes , we did not observe any signals significant at the same level as XRCC4 , but we do observe suggestive signals by the individual tests ( in the top 1–5% tail genome-wide ) in POLλ and XRCC4 in the West African population , and Artemis in the European population ( Table S12 ) . As CMS is optimized to detect recent local adaptation in a single population , these signals by individual tests may reflect selective events outside of this model ( e . g . , selection on standing variation , or selection of the same allele in multiple populations ) . Indeed , a single allele of POLλ has previously been reported to be under positive selection in both Asian and Sub-Sahara African populations [46] . Thus we find that several of the genes that have been evolving under positive selection during primate evolution also show evidence suggestive of recent positive selection in human populations , with an especially strong signature identified in XRCC4 . Nbs1 is part of the MRN complex , containing Mre11 , Rad50 , and Nbs1 . This complex is involved in DNA break detection , end processing , and cellular signaling [47] . Mutations in NBS1 lead to the autosomal recessive disease , Nijmegen breakage syndrome , which is characterized by chromosomal instability . Three amino acid positions were identified as evolving under positive selection ( Table 1 ) . G9 , Q185 , and I531 are identified with P>0 . 90 , with support for I531 being P>0 . 99 . A partial Nbs1 structure is available [48] , and two of the amino acid sites targeted by positive selection ( residues 9 and 185 ) fall on the protein surface ( Figure 6A ) . The third site , residue 531 , is not included in this partial structure . The positive selection of NHEJ genes suggests that certain mutations are providing a fitness advantage in an unknown context . While the essential DNA repair functions of these genes would be expected to remain conserved , there is a formal possibility that adaptive evolution of NHEJ genes could come at the cost of DNA repair . We wished to consider this hypothesis because a human SNP at a site of positive selection in NBS1 ( Q185E; SNP ID rs1805794 ) has been linked to increased risk of renal , skin , and lung cancer in multiple association studies [49]–[52] . This SNP is found at high frequencies in human populations ( Figure 6B ) . While Q185E has been linked to cancer , association studies are limited in that they may identify either a causal SNP , or a SNP that is linked to a causal SNP . We wished to test whether amino acid substitution in this codon changes the performance of Nbs1 in DNA repair , as the association with cancer might suggest . We constructed NBS1 alleles encoding either an E or a Q at position 185 , and expressed these proteins in insect cells using a baculovirus system . We then tested the effects of this mutation on several of the known activities of Nbs1 . The Nbs1 N-terminus , including the BRCT domain in which this SNP is located , is known to bind to the checkpoint protein Mdc1 [53]–[56] . We produced and purified MRN complexes containing both versions of Nbs1 and find that both interact equally well with purified Mdc1 in an in vitro binding assay ( Figure 6C ) . Thus the Nbs1 E/Q polymorphism is not expected to affect the association of MRN with Mdc1 at sites of DNA damage in vivo . The MRN complex is also required for the activation of the checkpoint protein ATM [57] , [58] . We find that MRN complexes containing both versions of Nbs1 are equally efficient in stimulating ATM-dependent phosphorylation of one of the downstream targets of ATM , p53 ( Figure 6D ) . Nbs1 is also known to bind XRCC4/Lig4 [59] and we find that both versions of Nbs1 interact equally well with this complex in vitro ( data not shown ) . Therefore , we conclude that positive selection of this codon , regardless of what is driving it , has not affected the repair-related physical interactions of Nbs1 . However , it should be noted that laboratory-based assays may not be sensitive enough to detect subtle defects that could cause a minor fitness effect in nature .
The NHEJ pathway is over 3 billion years old , and is found in bacteria , archaea , and eukaryotes . Despite the ancient conservation of the pathway , we have identified five NHEJ genes that have evolved under positive selection during the evolution of simian primates: NBS1 , CtIP , Artemis , XRCC4 , and POLλ . An analysis of polymorphism data supports positive selection of XRCC4 in modern humans as well . Interestingly , the yeast ortholog of NBS1 ( XRS2 ) was also identified as one of the two Saccharomyces NHEJ genes with the most extreme signatures of positive selection [2] . One hypothesis is that these signatures of positive selection are reflective of natural selection for more efficient DNA repair . As certain NHEJ components evolve , compensatory mutations may arise in other NHEJ components to re-optimize protein-protein interactions between the various components . We feel that this model is unlikely . In the absence of an antagonizing force , there is no reason that recurrent adaptive change should be required of any member of this pathway , which would then need to be followed by compensatory change . Four observations from our study additionally argue against this model . First , our biochemical experiments with Nbs1 suggest that positive selection of at least one of the three sites identified has not altered interactions with other repair proteins . Second , although there are several core complexes involved in NHEJ ( the MRN complex and the Lig4/XRCC4/XLF complex ) , only one component of each of these was identified as evolving under positive selection . Third , the clustered sites of positive selection in XRCC4 fall within the C-terminal protein domain that is not essential for DNA repair . Fourth , the positive selection of the NHEJ pathway is not a primate specific phenomenon , but is also found in Saccharomyces yeast [2] , arguing against a model where some novel role for DNA repair during primate evolution has driven this selection . The finding of multiple primate NHEJ components evolving under positive selection , supported by parallel findings in Saccharomyces yeast , indicates a systematic perturbation of the NHEJ pathway . With positive selection observed in two highly divergent eukaryotic clades , a model for the cause of this rapid evolution must span such diverse species groups . We propose that NHEJ genes may be antagonized by genetic parasites , which in primates are comprised of viruses and retrotransposons . Proteins of the NHEJ repair pathway have been shown to act as antiviral factors in the lifecycle of human adenovirus , a linear double-stranded DNA virus . Adenoviruses are a major cause of upper respiratory and other infections in humans . During infection , components of the NHEJ pathway join together viral genome ends , causing “dead-end” viral genome concatenation [60] . To counteract this antiviral tactic , adenovirus proteins ( encoded by the E4 genes ) sequester and target for degradation a number of components of the NHEJ pathway , including components of the Mre11/Rad50/Nbs1 and Lig4/XRCC4/XLF complexes [60]–[63] . CtIP has also been implicated in the adenovirus lifecycle through its interaction with the adenovirus early region 1A ( AdE1A ) protein [64] . If primate NHEJ genes are continually selected to encode variants that can evade interaction with these adenoviral antagonists , while the viral antagonists continually counter-evolve , this could drive positive selection of primate NHEJ genes . Adenovirus has been found in stool samples from great apes and macaques [65] , indicating a possible long-standing co-evolution between this virus and primates . Retroviruses like HIV may also provide the selective pressure that shapes the recurrent positive selection of NHEJ genes . There is abundant genetic evidence suggesting a role for NHEJ in the retroviral lifecycle [66]–[70] . Upon cellular entry , the retroviral RNA genome is reverse transcribed into double-stranded DNA . The ultimate destination for this retroviral cDNA is integration into the genome of the host , but it must first survive passage through the nucleus without being detected as broken DNA by the cell . NHEJ proteins have been found to physically associate with retroviral proteins , cDNA , and pre-integration complexes in vivo and in two-hybrid interactions [67] , [71]–[74] . There are several models which have been proposed to explain this . In one model , NHEJ proteins are recruited by the viral complex to protect free viral cDNA ends from degradation or from triggering apoptosis . In another model , the viral complex recruits host NHEJ proteins to promote the repair of breaks created at sites of retroviral cDNA integration into the host genome . In a third model , NHEJ proteins act as antivirals , joining the two long-terminal repeat ( LTR ) ends of the viral cDNA into dead-end “2-LTR circles . ” These 2-LTR circles are ubiquitously observed in the nuclei of infected cells [67] . Regardless of the model , allelic variants of NHEJ genes that result in lower infection rates would be selectively advantageous to the host . Should such alleles go to high frequency or fixation , retroviruses would be expected to counter-evolve , and the back-and-forth interplay would drive recurrent positive selection of NHEJ genes . Retroviruses and primates have co-evolved for tens of millions of years , as illustrated by the fact that all sequenced primate genomes contain the remnants of hundreds of thousands of integrated retroviruses [75] . It is unknown whether the positive selection observed in NHEJ genes represents a response to a single selective force , or whether multiple forces are shaping their evolution . At least eight additional viral families have been shown to evade or exploit the host DNA damage response [76] . Several NHEJ proteins include one or more “BRCT” domains , which have been linked to viral infection in multiple instances . The Epstein-Barr viral protein Zta has been shown to interact with the BRCT domains of 53BP1 , a component of the DNA damage response , to prevent apoptosis that is activated in response to viral replication [77] . HIV-1 Tat has also been shown to interact with the BRCT domain of the human replication protein FCP1 [78] . In both Polλ and Nbs1 , we find an amino acid position at the C-terminal end of the BRCT domain to be evolving under positive selection ( Q185 in Nbs1 and Q102 in Polλ ) . The single site found to be under positive selection in Saccharomyces Xrs2 also falls near the end of the BRCT domain ( site 298 ) [2] . BRCT domains could be a critical link in the interaction between viruses and the NHEJ pathway . Antagonism of host NHEJ proteins by genetic parasites may be a universal feature of cellular life , as yeast Ty retrotransposons also interact genetically and physically with NHEJ machinery [79] , [80] . LINE-1 retrotransposons are major drivers of primate genome evolution , and LINE-1 retrotransposition rates are reduced in the absence of NHEJ genes [81] . The Corndog and Omega bacteriophages of mycobacteria have even incorporated the first gene in the bacterial NHEJ pathway , Ku , into their own genome [82] . This viral Ku now evolves under the selective pressures of the virus in order to recruit the bacterial NHEJ ligase , LigD , to circularize phage DNA . In summary , we have documented abundant signatures of positive selection in genes of the NHEJ pathway , which is the major pathway for repairing double-strand chromosomal breaks in mammalian cells . We propose the hypothesis that these signatures result from the long-term co-evolution between NHEJ genes and genetic parasites . While it is well known that genetic parasites shape genome architecture through insertion and subsequent inter-element recombination , the present study may indicate that selective pressures imposed by genetic parasites can drive the evolution of protein sequence in critical human proteins .
Chimpanzee , orangutan , rhesus macaque , and marmoset gene sequences were obtained from the UCSC genome database ( http://genome . ucsc . edu/ ) using the BLAT alignment tool [83] . NBS1 , CtIP , Artemis , XRCC4 , POLλ , and XLF were sequenced from 15 additional primate species , and poor-quality regions of chimpanzee , orangutan , rhesus and marmoset genes were also re-sequenced . Primary and immortalized primate cell lines ( sources and individual primate identifiers are listed in Table S1 ) were grown in standard media supplemented with 15% fetal bovine serum at 37°C and in 5% CO2 . Total RNA was harvested from cell lines using the AllPrep DNA/RNA kit ( Qiagen ) . PCR was performed from total RNA and/or cDNA with OneStep RT-PCR kit ( Qiagen ) or PCR SuperMix High Fidelity ( Invitrogen ) , respectively . Details of the PCR and sequencing strategy , along with primer sequences , can be found in Tables S2 and S3 . Primate NHEJ gene sequences have been deposited in GenBank ( accession numbers HM486750–HM486849 ) . Alignments between orthologous gene pairs were performed using ClustalX2 . 0 [84] . Sliding-window dN/dS calculations for each alignment were performed with the SLIDERKK program [25] . Human-orangutan , human-rhesus and rhesus-marmoset alignments were analyzed with standard window sizes of 450bp , 306bp and 153bp , respectively , to reflect the increasing level of divergence in these species pairs ( window size must be a multiple of nine in this program ) [2] , [28] . In order to generate confidence values for windows with dN/dS>1 , the K-estimator program [85] was utilized to generate a null distribution through Monte Carlo simulation of randomly derived dN/dS values in the gene region of interest . Multiple alignments were created with ClustalX2 . 0 [84] . Maximum likelihood analysis was performed with codeml in the PAML 4 . 1 software package [31] . To detect selection , multiple alignments were fitted to the NSsites models M1a ( neutral model , codon values of dN/dS are fit into two site classes , one with value between 0 and 1 , and one fixed at dN/dS = 1 ) , M2a ( positive selection model , similar to M1a but with an extra class of dN/dS>1 allowed ) , M7 ( neutral model , codon values of dN/dS fit to a beta distribution , dN/dS>1 disallowed ) , M8a ( neutral model , similar to M7 except with a fixed codon class of at dN/dS = 1 ) and M8 ( positive selection model , similar to M7 but with an extra class of dN/dS>1 allowed ) . Simulations were run with multiple seed values for dN/dS ( ω ) and assuming either the f61 or f3x4 model of codon frequencies . Likelihood ratio tests were performed to assess whether permitting codons to evolve under positive selection gives a significantly better fit to the data ( model comparisons M1a vs . M2a , M7 vs . M8 , M8a vs . M8 ) . In situations where the null model could be rejected ( p<0 . 05 ) , posterior probabilities were assigned to individual codons belonging to the class of codons with dN/dS>1 . Residues under positive selection were mapped onto existing crystal structures using MacPyMol ( v . 0 . 99; http://pymol . sourceforge . net/ ) . The branch-site test allows identification of positive selection that might be limited to a subset of codons along only a subset of the branches being analyzed [34] . To implement this test , multiple alignments were fitted to the branch-sites Model A ( positive selection model , codon values of dN/dS along background branches are fit into two site classes , one ( ω0 ) between 0 and 1 and one ( ω1 ) equal to 1 , on the foreground branches a third site class is allowed ( ω2 ) with dN/dS>1 ) , and Model A with fixed ω2 = 1 ( null model , similar to Model A except the foreground ω2 value is fixed at 1 ) . Hominoids were defined as the “foreground” clade , with all other branches in the tree being defined as background branches . The likelihood of Model A is compared to the likelihood of the null model with a likelihood ratio test . Simulations were run with multiple seed values for dN/dS and assuming either the f61 or f3x4 models of codon frequencies . The “Fequal” codon model was also tested in the branch-site analysis of NBS1 . To test the significance of clustering of the codons under positive selection in XRCC4 , the statistical program R was utilized to perform a permutation test . The observed span of the positively selected codons on the primary sequence was compared with a null distribution created by calculating the span resulting from randomly generated sets of equivalent numbers of codons . We generated 100 , 000 random distances . To examine evidence for recent positive selection in humans , we implemented a previously published method that combines multiple tests for selection , the Composite of Multiple Signals ( CMS ) [45] . We have adapted the method to detect genomic regions under selection by examining the fraction of high scores in 100kb sliding windows . To determine the significance threshold , we used the cosi coalescent simulator to simulate 1 , 000 1MB autosomal regions , evolving neutrally under a previously validated demographic model [86] . We set thresholds that yielded a 0 . 1% false positive rate in simulations . Two long-haplotype tests , XP-EHH and iHS , were used to examine evidence for selection in or around the genes of interest . iHS was calculated as described in [10] for all SNPs with a minor allele frequency greater than 5% . iHS was analyzed independently in the European ( CEU ) , East Asian ( JPT and CHB ) , and West African ( Yoruban; YRI ) populations . XP-EHH was calculated as in [9] for the each of the three populations . For each SNP , we found the maximum score of the comparisons with the two other populations . In each 100kb window along the gene regions , the fraction of SNPs with |iHS|>2 or the maximum XP-EHH score was used as the test statistic . To calculate empirical P-values for each window w , we calculated the test statistics for each 100kb window across the genome and found the fraction of genomic windows with values of the test statistic greater than that found for window w . The ancestral state for each SNP was determined by comparison to the chimpanzee genome . We calculated Fst for each SNP in the regions using the Weir-Cockerham estimator [87] . Three pairwise comparisons were made between the African ( Yoruban ) , European , and East Asian populations . For each population , we compared the allele frequency in that population to the average frequency in the other two populations . For each 100kb window across the region , the maximum Fst was used as the test statistic . To generate the null distribution , we performed the same procedure on each 100kb window in the genome and derived an empirical p-value based on this distribution . A biotinylated human MRN ( E185 ) complex was expressed in a baculovirus system from the transfer vectors pTP11 ( Rad50 ) , pTP814 ( Mre11 ) , pTP1014 ( Nbs1 ) , and pTP1016 ( BirA ) as described earlier [88] . To make biotinylated human MRN ( Q185 ) complex , the E to Q point mutation at Nbs1 position 185 was introduced into pTP994 , whose bacmid form is pTP1014 , by primer-based mutagenesis ( QuikChange Kit , Invitrogen ) . Flag-tagged Mdc1 ( amino acids 1–740 ) was expressed using bacmid construct pTP1188 , which was made from the corresponding transfer vector pTP1187 . Expression constructs for Flag-tagged and HA-tagged ATM were gifts from M . Kastan and R . Abraham . The E . coli expression construct for GST-p53 was described earlier [89] . Purification procedures for the biotinylated MRN complex were the same as for the non-biotinylated MRN complex as described earlier [90] . Dimeric ATM was made by transient transfection of expression constructs into 293T cells using calcium phosphate and purified as described earlier [91] . Mdc1 ( aa 1–740 ) was expressed in Sf21 insect cells using the Bac-to-Bac system ( Invitrogen ) and was purified identically to 53BP1 as described earlier [88] . The GST-p53 was purified identically to the GST–Brca1 fragments as described earlier [92] and was further purified by separation on a Superdex 200 gel filtration column ( GE ) in buffer A ( 100 mM NaCl , 25 mM Tris pH8 , 10% glycerol , and 1 mM DTT ) . Protein concentrations were determined by quantification of protein preparations with standards on colloidal Coomassie-stained SDS–PAGE gels using the Odyssey system ( LiCor ) . 20 nM biotinylated MRN complex was incubated with 45 nM Mdc1 ( aa 1–740 ) in buffer A for 1 hour at 30°C in a final volume of 100 µl , then incubated with streptavidin-coated magnetic beads ( Dynal ) and 0 . 2% CHAPS ( Sigma ) while rotating at 4°C for 15 min . Beads with associated proteins were washed three times with buffer A containing 0 . 2% CHAPS , and bound proteins were eluted by boiling the beads in SDS loading buffer . Proteins were analyzed by SDS–PAGE and western blotting using antibodies directed against the Flag epitope ( Sigma , F3165 ) and Nbs1 ( Genetex , MSNBS10PX1 ) . ATM kinase assays were performed with 0 . 2 nM dimeric ATM , 50 nM GST–p53 substrate , and varying amounts of MRN complex ( concentrations of MRN = 1 . 25 , 2 . 5 , 5 , and 10 nM ) . Kinase assays were performed in kinase buffer ( 50 mM HEPES , pH 7 . 5 , 50 mM potassium chloride , 5 mM magnesium chloride , 10% glycerol , 1 mM ATP , 1 mM DTT , and 10 ng DNA ) for 90 min at 30°C in a volume of 40 microliters as described earlier [91] . Phosphorylated p53 ( ser15 ) was detected as described earlier [91] using phospho-specific antibody from Calbiochem ( PC461 ) . | Because all cells experience DNA damage , they must also have mechanisms for repairing DNA . When the proteins that repair DNA malfunction , mutation and disease often result . Based on their fundamental importance , DNA repair proteins would be expected to be well preserved over evolutionary time in order to ensure optimal DNA repair function . However , a previous genome-wide study of molecular evolution in Saccharomyces yeast identified the non-homologous end joining ( NHEJ ) DNA repair pathway as one of the two most rapidly evolving pathways in the yeast genome . In order to analyze the evolution of this pathway in humans , we have generated large evolutionary sequence sets of NHEJ genes from our primate relatives . Similar to the scenario in yeast , several genes in this pathway are evolving rapidly in primate genomes and in modern human populations . Thus , complex and seemingly opposite selective forces are shaping the evolution of these important DNA repair genes . The finding that NHEJ genes are rapidly evolving in species groups as diverse as yeasts and primates indicates a systematic perturbation of the NHEJ pathway , one that is potentially important to human health . | [
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] | [
"infectious",
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] | 2010 | Ancient and Recent Adaptive Evolution of Primate Non-Homologous End Joining Genes |
The survival motor neuron ( SMN ) protein , the determining factor for spinal muscular atrophy ( SMA ) , is complexed with a group of proteins in human cells . Gemin3 is the only RNA helicase in the SMN complex . Here , we report the identification of Drosophila melanogaster Gemin3 and investigate its function in vivo . Like in vertebrates , Gemin3 physically interacts with SMN in Drosophila . Loss of function of gemin3 results in lethality at larval and/or prepupal stages . Before they die , gemin3 mutant larvae exhibit declined mobility and expanded neuromuscular junctions . Expression of a dominant-negative transgene and knockdown of Gemin3 in mesoderm cause lethality . A less severe Gemin3 disruption in developing muscles leads to flightless adults and flight muscle degeneration . Our findings suggest that Drosophila Gemin3 is required for larval development and motor function .
Spinal muscular atrophy ( SMA ) is an autosomal recessive disorder characterised by degeneration of spinal cord motor neurons , as well as progressive muscular weakness , dysphagia , dyspnoea , and in severe cases , death [1] , [2] . The majority of SMA patients harbour deletions or mutations in the survival motor neuron ( SMN1 ) gene , which encodes an RNA-binding protein , SMN . In mammalian cells , the SMN protein is stably complexed with a group of proteins including Gemin2 [3] , Gemin3 [4] , [5] , Gemin4 [6] , Gemin5 [7] , Gemin6 [8] , Gemin7 [9] , and Gemin8 [10] . Biochemical studies in vertebrate systems suggested that the SMN complex plays an essential role in small nuclear ribonucleoprotein ( snRNP ) assembly . The SMN complex binds directly to small nuclear RNAs ( snRNAs ) and ensures that a set of seven Sm or Sm-like ( Lsm ) proteins are assembled onto snRNAs [11] . Gemin3 , the only RNA helicase in the SMN complex , contains nine conserved motifs including the Asp-Glu-Ala-Asp motif ( or DEAD box in one-letter code ) . The RNA helicase activity of Gemin3 is ATP-dependent with a 5′ to 3′ direction [12] . RNAi-mediated knockdown studies indicated a role for Gemin3 in the assembly of snRNP complexes as an integral component of the macromolecular SMN complex [13] , [14] . Furthermore , a recent study demonstrated that intracellular Gemin3 proteolysis by a poliovirus-encoded proteinase led to reduced Sm core assembly activity in poliovirus-infected cells [14] . In addition to snRNP biogenesis , Gemin3 was also implicated in transcriptional and microRNA regulation . Gemin3 was originally isolated as a cellular factor that associates with the Epstein-Barr virus nuclear proteins EBNA2 and EBNA3C , which play a role in the transcriptional regulation of both latent viral and cellular genes [15] . The non-conserved C-terminal domain of Gemin3 has been shown to interact with and modulate a variety of cellular transcription factors including steroidogenic factor 1 [12] , [16] , early growth response protein 2 [17] , forkhead transcription factor FOXL2 [18] , and mitogenic Ets repressor METS [19] . Although the majority of Gemin3 and its associated protein , Gemin4 , are found in the SMN complex , a less abundant Gemin3-Gemin4 complex has been isolated from HeLa and neuronal cells . The Gemin3-Gemin4 complex contains Argonaute 2 and numerous microRNAs , co-sedimenting with polyribosomes [20]–[22] . Despite the detailed studies in vertebrate systems and a recent study in Drosophila culture cells [23] , the function of Gemin3 in Drosophila development remains elusive . Here we identify the orthologue of Gemin3 in Drosophila melanogaster and demonstrate that Drosophila Gemin3 , like its vertebrate counterpart , associates with SMN . Loss-of-function gemin3 mutants are lethal as third instar larvae and/or prepupae . Before they perish , gemin3 mutants exhibit dramatic loss of mobility and neuromuscular junction ( NMJ ) defects . Tissue-specific expression of a dominant-negative transgenic construct and RNAi studies suggest that the function of Gemin3 in mesoderm , particularly in muscles , is essential for animal survival . Furthermore , disruption of Gemin3 in muscles causes flight muscle degeneration and loss of flight . Thus our study demonstrates that Drosophila Gemin3 plays a critical role in development and motor function .
We carried BLAST searches of the Drosophila melanogaster genome using human and mouse Gemin3 sequences , and found that the DEAD/DEAH RNA helicase 1 ( Dhh1 ) or CG6539 is the putative Drosophila Gemin3 orthologue . This gene , renamed for the present studies as gemin3 , is located on the third chromosome in region 67E3 , and is composed of 2 exons separated by a short intron . The Drosophila melanogaster Gemin3 protein is composed of 1028 amino acids and shows 33% identity and 55% similarity ( BLASTP ) to the respective human orthologue ( Figure 1A , B ) . This level of conservation is quite similar to that observed between the Drosophila and human SMN , which have an overall identity and similarity of 31% and 49% , respectively . The N-termini of Gemin3 , in which all nine DEAD-box helicase motifs reside , are more conserved than the C-termini . A region in the middle ( 451–573aa ) of Drosophila melanogaster Gemin3 corresponds to the SMN-binding domain identified in higher eukaryotes [5] . Aiming to test whether the physical interaction between SMN and Gemin3 reported in higher eukaryotes [24] is conserved in Drosophila , a co-immunoprecipitation approach was pursued . We have generated a transgenic line expressing CFP::Gemin3 . The CFP::Gemin3 gene is functional as it can rescue gemin3 mutants , which we describe later . In extracts derived from CFP::Gemin3 transgenic larvae , anti-SMN antibodies co-immunoprecipitate CFP::Gemin3 ( Figure 2 ) . Two recessive lethal gemin3 alleles were identified: PBac{RB}e03688 ( gemin3W ) and P{PZ}Dhh1rL562 ( gemin3R ) . We used PCR to confirm that the transposon insertion site of the gemin3W allele is located at 92 nt upstream of the transcription start site ( Figure 3A; Figure S1 ) . Part of the 5′ and 3′ piggyBac ends in the gemin3W allele were found to have been lost during the insertion . In the gemin3R allele , the P element inserted at 108 nt downstream of the transcription start site ( Figure 3A; Figure S1 ) . Since the P{PZ}-element insert sequence generates several premature stop codons , gemin3R is hypothesised to be an amorph . Several studies were pursued to demonstrate that the recessive lethality of both transposon insertions is specific to gemin3 disruption , thereby confirming that gemin3 is an essential gene . First , complementation crosses revealed that both gemin3 alleles retain their recessive lethality in trans to each other and to a chromosomal deficiency that completely eliminates the gemin3 gene ( Df[3L]ED4457 ) . Second , a re-mobilisation screen of the P-element in the gemin3R allele , which is the only transposon that could be excised , recovered homozygous viable precise excision alleles or revertants . Third , both low ubiquitous gemin3 and CFP::gemin3 transgenic expression driven by 1032-GAL4 [25] rescued the lethality of gemin3R homozygotes and gemin3R/gemin3W transheterozygotes . However , neither of the above gemin3 transgenes can rescue the lethality of homozygous gemin3W , suggesting that a non-specific mutation may be causing the lethality associated with the gemin3W allele . Since the lethality observed in gemin3 heteroallelic mutants was specific to the loss of gemin3 , further analysis concentrated on this genotype . Expression of the CFP::gemin3 transgene under the control of tissue-specific drivers such as G7-GAL4 ( muscle ) , elav-GAL4 ( neuron ) , or the combination of both could not rescue the lethality of gemin3R homozygotes and gemin3R/gemin3W transheterozygotes , suggesting that animal survival also depends on the basal level of Gemin3 in tissues not covered by the expression of G7-GAL4 or elav-GAL4 drivers . Homozygous gemin3R mutants survive to the third instar larval stage , while the transheterozygotic gemin3R/gemin3W animals survive to the prepupal stage after both genotypes experience a prolonged wandering third instar larval stage . The expression of gemin3 at different developmental stages was compared by two-step RT-PCR . Essentially gemin3 mRNA was expressed at all developmental stages ( Figure 3B ) . Supporting the amorphic allele hypothesis , we observed that expression of gemin3 mRNA was dramatically reduced in transheterozygous animals throughout their entire larval life , whereas the housekeeping control Tat-binding protein-1 ( Tbp-1 ) transcripts remained detectable ( Figure 3B ) . Heterozygous gemin3R adults have approximately half of the gemin3 mRNA transcript as that in wild-type animals ( Figure 3B ) . Although showing no dramatic mobility changes throughout the first and second larval stages , the gemin3R/gemin3W transheterozygotes exhibit a significantly decreased contraction rate at the third instar larval stage ( Figure 4A and Video S1 ) . The puparium formed by gemin3 heteroallelic mutants exhibited failed eversion of the spiracles and a large axial ratio ( Figure 4B , C ) , the latter of which is most probably the result of a failure in body wall muscle contraction . Ubiquitous expression of the CFP::gemin3 transgene within this mutant background rescues the defects in mobility , spiracle eversion and abnormal axial ratio , confirming that the CFP::gemin3 transgene is functional and the above phenotypes exhibited by gemin3R/gemin3W transheterozygotes are specifically due to the disruption of Gemin3 function ( Figure 4A–C ) . Mobility failure is probably not secondary to compromised muscle structure since gemin3 mutant larval fillets have an ordered pattern of muscle fibres without obvious muscle losses . In addition , there are no gross defects in the sarcomeric organisation in the gemin3 mutants ( Figure 4D ) . The obvious larval contraction defects of the gemin3 transheterozygotic mutants directed the research focus on the larval neuromuscular junction ( NMJ ) . The present studies focus on the highly characterised type I NMJ innervating ventral longitudinal muscles 6 and 7 , and aim at unveiling the presence of any morphological abnormalities in a gemin3 mutant background . To this end , larval muscle fillets were dissected and double-labelled with anti-HRP antibodies , which allow visualisation of the neuronal membrane , and an antibody against Discs-large ( Dlg ) , a primarily postsynaptic scaffold protein localised to the subsynaptic reticulum that surrounds each bouton . Although no obvious motor neuron denervation was detected , gemin3 heteroallelic mutants exhibit an appreciative synaptic overgrowth before pupariation ( Figure 5A ) and a significantly increased synaptic area even when normalised to muscle size ( Figure 5B ) . Expression of a gemin3 transgene in a mutant or wild-type background resulted in an increase in both NMJ and muscle area ( data not shown ) . When normalized to muscle area , the NMJ area and branches in rescued gemin3 mutants restore to the wild-type range , whereas normalized NMJ area and branch numbers within single NMJs are significantly decreased when gemin3 was overexpressed ( Figure 5B , C ) . A truncated gemin3 transgene ( gemin3ΔN ) , which lacks 424 amino acid residues from the N-terminus of Drosophila melanogaster Gemin3 and hence lacks the helicase core ( Figure 3A ) , causes lethality on ubiquitous expression . Whilst highlighting the importance of the helicase domain to the function of Gemin3 , the N-terminal truncated Gemin3 isoform is hypothesized to be a dominant-negative mutant . We used various drivers to investigate the effect on animal survival when gemin3ΔN is expressed in various temporal and spatial expression patterns ( Table 1 ) . No dramatic effect is observed when gemin3ΔN is expressed at 25°C under the control of elav-GAL4 , nrv2-GAL4 , D42-GAL4 , OK6-GAL4 , mef2-GAL4 , or C57-GAL4 drivers ( Figure 6A ) . However , expression of gemin3ΔN at 25°C by Act5C-GAL4 , how-GAL4 or C179-GAL4 driver results in lethality , and that by the G7-GAL4 driver leads to a significant decrease in viability ( Figure 6A ) . When the temperature shifted to 29°C to allow for maximal GAL4 activity , expression of gemin3ΔN by Act5C-GAL4 , C179-GAL4 , how-GAL4 , or G7-GAL4 driver causes lethality , while that by mef2-GAL4 and C57-GAL4 drivers results in decreased viability ( Figure 6B ) . Co-expression of an extra full-length gemin3 transgene but not a control gene such as GFP with the gemin3ΔN transgene significantly alleviates the driver-associated lethality ( Figure 6 and data not shown ) . These experiments indicate that the lethality or low viability associated with the expression of gemin3ΔN in the mesoderm and larval muscles is specifically due to the disruption of Gemin3 function . To confirm the driver-specific lethality pattern induced by the gemin3ΔN transgene , several gemin3 RNAi transgenic flies were isolated and tested to establish whether lethality can be induced when gemin3 knockdown occurs ubiquitously throughout the entire organism . Two RNAi transgenes , gemin3dwejra and gemin3munxar , fit this criterion . Reducing gemin3 gene activity using elav-GAL4 , nrv2-GAL4 , or D42-GAL4 has no effect on fly viability ( Figure 7 ) . In contrast , Gemin3 knockdown at both 25°C and 29°C via C179-GAL4 resulted in lethality . The how-GAL4 driver gave a similar effect when the gemin3dwejra and gemin3munxar RNAi transgene was expressed at both temperatures or at a temperature of 29°C , respectively ( Figure 7 ) . The lethality induced by gemin3munxar could be rescued by co-expressing a functional gemin3 transgene , thus excluding the possibility that lethality is the result of ‘off-target’ effects ( Figure 7A , B ) . Knockdown of gemin3 in the mesoderm and larval somatic musculature results in lethality at the late pupal stage , that is , pharate adults enclosed in pupae fail to eclose . Animals expressing gemin3ΔN under the control of the how-GAL4 driver often lead to pupariation and puparia have increased axial ratios , similar to the defects exhibited by the gemin3R/gemin3W transheterozygotes . In addition , how-GAL4≫gemin3ΔN pupae exhibited several morphological abnormalities , including head eversion defects , short legs , and short wings , although segmentation of the abdomen and mature eye pigments appear normal ( Figure 8 ) . While they can walk and jump normally , eclosed flies with an mef2-GAL4-driven gemin3ΔN expression have a reduced ability to fly . In a flight assay , those flies show defective flight ability , similar to wild-type flies with clipped wings , which are flightless ( Figure 9A and Video S2 ) . The indirect flight muscles ( IFMs ) in mef2-GAL4≫gemin3ΔN flies are shrunken , resulting in increased spacing , and breakages are obvious between the muscle fibers . Frequently , large tears within the indirect flight muscles are observed in mef2-GAL4≫gemin3ΔN flies but not in wild-type flies ( Figure 9B ) .
Gemin3 or DP103 was first identified in mammalian culture cells through biochemical approaches [5] , [15] . The Gemin3 protein has three critical features . First , the N-terminus of Gemin3 contains multiple helicase motifs including a DEAD-box . Second , Gemin3 interacts with SMN in vitro and in vivo [24] . Third , the Gemin3 and SMN proteins have a similar subcellular localization pattern [5] , [26] . In Drosophila there are 29 DEAD-box RNA helicases [27] . Using human and mouse Gemin3 to BLAST the Drosophila melanogaster genome , CG6539 , previously identified as DEAD/DEAH RNA helicase 1 ( Dhh1 ) , is the top hit . In the N-terminus , CG6539 contains 9 conserved RNA helicase motifs including a DEAD-box . A segment in the middle of CG6539 , which corresponds to the SMN-binding domain in human Gemin3 , is less conserved . Moreover , co-immunoprecipitation experiments using Drosophila larval muscle extracts show that Gemin3 binds to SMN in vivo . We have also carried localization assays , which demonstrate that Gemin3 co-localizes with SMN in the cytoplasm and nucleus [28] ( RJC , KED , and JLL , unpublished data ) . Taken together , we feel confident that we have identified the Drosophila orthologue of vertebrate Gemin3 . Recently , an independent study by Fischer and colleagues also identified CG6539 as Drosophila Gemin3 through bioinformatic and biochemical approaches using Drosophila culture cells [23] . Both their study in Drosophila culture cells and this study in Drosophila tissues have shown that Gemin3 interacts with SMN , suggesting that Gemin3 is a bona fide component of the SMN complex in fruit flies , similar to that in vertebrate systems . In this study , we have multiple lines of evidence demonstrating that Drosophila Gemin3 is essential for animal development and survival . Firstly , homozygous loss of gemin3 through a specific transposon insert ( gemin3R ) or a transheterozygous combination of two transposon inserts which do not complement each other ( gemin3R/gemin3W ) results in lethality at the larval and/or prepupal stage . Secondly , a functional gemin3 transgene specifically rescues the lethality and developmental defects caused by loss of gemin3 . Thirdly , expression of a dominant-negative allele of gemin3 ( gemin3ΔN ) or Gemin3 knockdown by RNAi ubiquitously or even in a tissue-specific pattern results in lethality or reduced viability . Gemin3-null mutants have recently been described in the mouse [29] . Heterozygous gemin3 mutant mice are healthy and fertile , with minor defects in the female reproductive system , whereas homozygous gemin3 knockout in mice leads to death at the 2-cell embryonic stage [29] . Thus , the lethality caused by loss of Gemin3 in Drosophila is consistent with the findings in Gemin3-null mice . However , while Gemin3-null mice died at an early embryonic stage , gemin3 mutant flies exhibit delayed lethality , which probably results from maternal contribution of the gemin3 transcript . In a separate study in female ovaries , we observed severe defects in nurse cells and oocytes when gemin3 is disrupted in germline cells ( RJC , KED , and JLL , unpublished data ) . The earliest clues pointing towards a motor function were a progressive loss of mobility and consequent long and thin puparia when Gemin3 function is lost . Similar phenotypes have previously been observed in mutants with disrupted Mlp84B , a muscle sarcomeric protein [30] , or Tiggrin , an extracellular matrix ligand for the position-specific 2 integrins [31] . We also observe that gemin3 mutants have an overgrown NMJ though these could be a secondary response to the progressive loss of muscle power . The size ratio of NMJs to muscles is reduced when gemin3 is overexpressed raising the possibility that Gemin3 might also play a role in synaptic growth . The requirement of Gemin3 in mesoderm and larval muscles for adult viability suggests a function of Gemin3 at the post-synaptic side . Based on the tissue-specific phenotypes uncovered , such a function is critical for pupal metamorphic changes and flight muscles . However , another possible explanation is that an earlier and wider disruption of Gemin3 by mesodermal-related drivers is responsible for the lethality , while late and local disruption of Gemin3 by neuroectodermal-related drivers causes milder phenotypes . More studies on the expression details of Gemin3 in pre- and post-synaptic tissues would help to distinguish those views . Studies in vertebrate systems , in vitro and in vivo , have shown that Gemin3 directly binds to SMN [24] . A recent study in Drosophila culture cells [23] and this study in fly tissues confirm that the interaction between Gemin3 and SMN is conserved from fly to human . This study raises the possibility of a functional interaction between Gemin3 and SMN . Loss of gemin3 phenocopies the larval mobility phenotypes observed in smn mutants [32] . Strong Gemin3 disruption in mesoderm and muscles led to striking developmental defects during metamorphosis , similar to those reported on disruption of SMN in a similar expression pattern [33] . A less severe gemin3 disruption in the developing musculature results in viable but flightless adult flies , which have flight muscle degeneration , similar to the phenotype in a hypomorphic smn mutant [34] . We observed that gemin3 mutants exhibit an overgrown NMJ before puparation and overexpression of gemin3 leads to a significant decrease in NMJ area and branches relative to muscle size . Interestingly , two studies describe a range of NMJ phenotypes for smn mutants [32] , [35] . It is still not clear whether smn and gemin3 mutants have similar morphologic defects at the NMJ as the parameters and the segments used for NMJ analysis vary in different studies . Comparison of smn and gemin3 mutant NMJs with the same standard , as well as analysing the NMJ phenotype in smn and gemin3 double mutants would help to address this question . The motor defects unravelled on disruption of Gemin3 function in Drosophila are very intriguing in view of its association with SMN , and the possible link to SMA . More studies are necessary to clarify the roles of SMN-Gemin3 interaction in development , which may help us to understand the molecular mechanisms of the devastating neurodegenerative disorder SMA .
The y w stock was used as the wild-type control . Transposon insertion alleles gemin3R ( P{PZ}Dhh1rL562 ) and gemin3W ( PBac{RB}e03688 ) were obtained from the Bloomington Drosophila Stock Centre ( BDSC ) at Indiana University and the Exelixis collection at Harvard Medical School , respectively . Complementation tests , transposon remobilisation and rescue studies were carried out according to standard genetic crossing schemes . The RNAi transgenic constructs UAS-gemin3dwejra ( 49505 ) and UAS-gemin3munxar ( 49506 ) were obtained from the Vienna Drosophila RNAi Center and their generation was described in Dietzl et al . [36] . GAL4 lines used in this study included 1032-GAL4 , Act5C-GAL4 ( BDSC ) , elav-GAL4 ( BDSC ) , nrv2-GAL4 ( gift from Paul Salvaterra , City of Hope National Medical Center , Duarte , California , USA ) , D42-GAL4 ( BDSC ) , OK6-GAL4 ( gift from Cahir O'Kane , University of Cambridge , Cambridge , UK ) , C179-GAL4 ( BDSC ) , how-GAL4 ( BDSC ) , mef2-GAL4 ( gift from Barry Dickson , Research Institute of Molecular Pathology , Vienna , Austria ) , G7-GAL4 ( gift from Aaron DiAntonio , Washington University , St . Louis , Missouri , USA ) and C57-GAL4 ( gift from Vivian Budnik , University of Massachusetts , Worcester , Massachusetts , USA ) ; the spatial and temporal expression patterns are described in the Results . All stocks were cultured on standard molasses/maizemeal and agar medium in plastic vials or bottles at 25°C . For the generation of the P{CFP::gemin3} transgenic construct , the PCR-amplified full-length coding sequence of gemin3 was ligated into the KpnI and XbaI restriction sites of the pUAST vector . The NotI and KpnI restriction sites of the resulting recombinant vector were then used to insert the cyan fluorescent protein ( CFP ) coding portion of the pECFP-C1 vector ( BD Biosciences Clontech , Palo Alto , California , USA ) upstream of the gemin3 sequence . The P{UAS-gemin3} construct was produced by ligating the gemin3 cDNA ( Drosophila Genomics Resource Centre , Indiana University ) in the pUAST vector using the KpnI and NotI restriction sites . The generation of the P{UAS-gemin3ΔN} involved PCR-amplification of the C-terminus of gemin3 followed by ligation into the KpnI and XbaI restriction sites of the pUAST vector . In both cases , the ligation products were used to transform E . coli competent cells using standard protocols . Correct transformants were further propagated and their harbouring plasmids were purified ( Qiagen HiSpeed Plasmid Midi Kit , Qiagen Ltd . , West Sussex , UK ) prior to microinjection in y w embryos ( BestGene Inc . , Chino Hills , California , USA ) . RNA was first extracted using the RNeasy kit ( Qiagen Ltd . ) and then reverse transcribed into cDNA using the QuantiTect Reverse Transcription Kit ( Qiagen Ltd . ) following manufacturer's instructions . PCR amplification of mRNA transcripts was performed using primers specific to gemin3 ( forward: 5′-CACTGGCCAAAATGGATCTAA-3′ and reverse: 5′-GGCATTGCCTCAATGAGTTT-3′ ) and Tbp-1 ( forward: 5′-CACCGAAAAGATCAAGGTCAA-3′ and reverse: 5′-CTTTGTTGACTCCGACCAGA-3′ ) mRNAs . RT-PCR products were resolved by electrophoresis on a 1 . 7% agarose gel containing ethidium bromide and bands were visualized by ultraviolet light . Measurement of larval mobility involved placing age-matched larvae individually at the centre of a 0 . 7% agar plate and measuring the forward body wall contractions exhibited by each larva for 1 minute . Puparial axial ratios were calculated by dividing the length by the width of the puparia , both of which were measured from still images . Adult viability assays were conducted by crossing GAL4 driver stocks to lines harbouring knockdown or truncated gemin3 transgenes . A week following eclosion , adult flies were screened and counted . Adult viability was calculated as the percentage of the number of adult flies with the appropriate genotype divided by the expected number for the cross . The flight assay was done according to a modified protocol originally designed by Benzer [37] . In brief , a 1000 ml-graduated cylinder divided into 5 sectors was coated internally with mineral oil . Flies were introduced into the top of the cylinder through a funnel and the flies stuck in each sector were counted . The height flies stick in the cylinder is indicative of their flight capabilities . Protein A beads washed and suspended in protein lysis buffer ( 2× protein lysis buffer [50 mM Tris pH8 , 150 mM NaCl , 1 mM EDTA , and 1% v/v NP-40]+21× protease inhibitor cocktail [complete , Mini; Roche Diagnostics Ltd . ] ) were incubated with preimmune serum or an antigen-specific antibody , including rabbit anti-GFP ( Abcam plc . , Cambridge , UK ) and rabbit anti-SMN ( gift from Marcel van den Heuvel , University of Oxford ) . Sample lysates were prepared by dissecting body wall larval muscle fillets ( ∼30/IP ) into cold 1× PBS followed by grinding into cold 2× protein lysis buffer . Following pre-clearing , lysates were incubated with beads coated with the appropriate target antigen-specific antibody . The beads were then washed in lysis buffer , and mixed with 4× NuPAGE LDS Sample Buffer ( Invitrogen Ltd . , Paisley , UK ) , 10× NuPAGE Reducing Agent ( Invitrogen Ltd . ) and deionised water . The mixture was then heated at 70°C in order to dissociate the immunoprecipitated antigen and any other macromolecules bound to it , followed by a brief spin . The bead-free supernatant was loaded onto a 4–12% NuPAGE Novex Bis-Tris pre-cast gel ( Invitrogen Ltd . ) , resolved and probed for GFP according to standard Western blotting procedures . Larvae were dissected in 1× PBS , fixed in 4% paraformaldehyde in PBS and then washed in 1× PBS+0 . 1% ( v/v ) Triton X-100 ( PBT ) . The tissues were next subjected to overnight staining at 4°C by mouse anti-Discs large antibodies ( 1∶100; Developmental Studies Hybridoma Bank , University of Iowa , Iowa , USA ) . The next day , tissues were washed in PBT and stained for ∼2 hours at room temperature with anti-rabbit Alexa Fluor 488-conjugated secondary goat antibodies ( 1∶50 ) , and anti-HRP goat antibodies conjugated to TRITC ( 1∶50; Jackson ImmunoResearch Laboratories Inc , West Grove , Pennsylvania , USA ) . Samples were then counterstained with nuclear-staining Hoechst 33342 ( 1∶500 ) and Cy5-conjugated actin-binding phallodin ( 1∶200 ) and mounted in Vectashield medium ( Vector Laboratories Ltd . , Peterborough , UK ) prior to viewing with a Zeiss LSM 510 META confocal microscope . ImageJ software ( NIH ) was used to quantify branch number , NMJ area , and muscle area from z-projections of confocal image stacks capturing ventral longitudinal muscles 6 and 7 ( Segment A1 ) . NMJ area constituted the presynaptic region stained by the anti-HRP antibody whereas branch number calculates the number of arborisations containing at least two boutons within a single NMJ . Both NMJ area and branch numbers were normalised through dividing each by the total muscle area of ventral longitudinal muscles 6 and 7 . Adult flies were fixed overnight in 4% ( v/v ) paraformaldehyde+2 . 5% ( v/v ) glutaraldehyde+0 . 1 M phosphate buffer pH7 . 2 . The flies were then washed in 0 . 1 M phosphate buffer pH7 . 2 and post-fixed with 2% ( w/v ) osmium tetroxide for 2 hours at room temperature . Following a wash in water , the samples were subjected to a series of progressive dehydration steps in ethanol : water mixtures prior to embedding in Spurr's resin . Ultrathin sections were then made with a diamond knife , stained with Toluidine Blue and viewed under a light microscope . | The childhood disease spinal muscular atrophy ( SMA ) has a drastic impact on motor neurons and muscles . The cause has been linked to a deficiency in the survival motor neuron ( SMN ) protein . SMN interacts with various proteins termed Gemins to form the SMN complex , among which Gemin3 is the only one with an RNA unwinding activity . Here , we study the function of D . melanogaster Gemin3 in the context of development . The association of Gemin3 with SMN , which had been reported previously in humans , is conserved in flies . Loss of Gemin3 resulted in death at larval stages . Before they die , gemin3 mutant flies become sluggish and develop large synapses , which are the contacts between motor neurons and muscles . Disruption of Gemin3 in mesodermal tissues , especially muscles , causes development defects , degeneration of flight muscles , and flies that are unable to fly . This study demonstrates that Gemin3 plays a critical role in fruit fly development , especially in motor function , which raises the question of whether disruption of Gemin3 contributes to SMA . | [
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"gen... | 2008 | A Motor Function for the DEAD-Box RNA Helicase, Gemin3, in Drosophila |
Patterning the neuroectoderm along the anterior–posterior ( AP ) axis is a critical event in the early development of deuterostome embryos . However , the mechanisms that regulate the specification and patterning of the neuroectoderm are incompletely understood . Remarkably , the anterior neuroectoderm ( ANE ) of the deuterostome sea urchin embryo expresses many of the same transcription factors and secreted modulators of Wnt signaling , as does the early vertebrate ANE ( forebrain/eye field ) . Moreover , as is the case in vertebrate embryos , confining the ANE to the anterior end of the embryo requires a Wnt/β-catenin-dependent signaling mechanism . Here we use morpholino- or dominant negative-mediated interference to demonstrate that the early sea urchin embryo integrates information not only from Wnt/β-catenin but also from Wnt/Fzl5/8-JNK and Fzl1/2/7-PKC pathways to provide precise spatiotemporal control of neuroectoderm patterning along its AP axis . Together , through the Wnt1 and Wnt8 ligands , they orchestrate a progressive posterior-to-anterior wave of re-specification that restricts the initial , ubiquitous , maternally specified , ANE regulatory state to the most anterior blastomeres . There , the Wnt receptor antagonist , Dkk1 , protects this state through a negative feedback mechanism . Because these different Wnt pathways converge on the same cell fate specification process , our data suggest they may function as integrated components of an interactive Wnt signaling network . Our findings provide strong support for the idea that the sea urchin ANE regulatory state and the mechanisms that position and define its borders represent an ancient regulatory patterning system that was present in the common echinoderm/vertebrate ancestor .
Wnt signaling pathways play fundamental roles in many developmental processes . One of the earliest and most crucial of these roles is the activation of gene regulatory programs that specify different cell fates along the embryo's primary anterior–posterior ( AP ) axis . Recent comparative analyses suggest that Wnt/β-catenin signaling is an ancient AP patterning mechanism that establishes posterior identity in most metazoan embryos [1]–[9] . In invertebrate deuterostome embryos , which include cephalochordates , urochordates , hemichordates , and echinoderms , localized determinants cause stabilization of β-catenin in posterior blastomeres . This stabilized β-catenin enters nuclei in which it activates genes that specify endomesoderm , marking the site of gastrulation at what corresponded to the vegetal pole of the egg and forming the posterior end of the developing embryo [2] , [4] , [10] , [11] . In the sea urchin embryo , in which the molecular mechanisms of endomesoderm specification are best understood [12] , the first evidence of Wnt signaling after fertilization is the presence of β-catenin in the nuclei ( nβ-catenin ) of posterior cells , beginning at the 16- to 32-cell stage . During the next few cleavages , a detectable gradient of nβ-catenin forms in the posterior half of the embryo , with the highest concentration at the posterior pole [4] . This gradient of Wnt/β-catenin signaling is both necessary and sufficient to activate the gene regulatory networks that establish mesoderm and endoderm cell fates in a posterior-to-anterior wave during late cleavage stages [13] , [14] . Wnt/β-catenin signaling also transforms the initial regulatory state that specifies anterior neuroectoderm ( ANE ) development in those deuterostome embryos in which it has been examined [15]–[22] . In the sea urchin embryo , we refer to this neuroectoderm as ANE because it becomes restricted to a region derived from the animal pole of the egg , which is located opposite to the posterior end of the embryo ( see [23] ) . The initial regulatory state of early sea urchin embryos activates ANE specification by the 32-cell stage , when genes encoding the earliest ANE regulatory proteins are expressed broadly throughout the anterior half of the embryo [22] , [24] . These early factors include Six3 , which is expressed at the anterior end of bilaterian embryos [25] and has been shown by functional studies to be critical for the specification of anterior-most neuroectoderm in diverse embryos including Tribolium castaneum [26] , sea urchins [24] , zebrafish , and mouse [27] . Beginning around the 60-cell stage , a progressive posterior-to-anterior down-regulation of ANE factor gene expression in most of the anterior half of the embryo occurs by an unknown mechanism that requires posterior Wnt/β-catenin signaling [22] . This process continues during blastula stages until the ANE regulatory state is confined to a disk of cells around the anterior pole of the mesenchyme blastula [24] . Interestingly , an unknown signal from posterior Wnt/β-catenin signaling also appears to be necessary to pattern the anterior ectoderm along the AP axis in Saccoglossus kowalevskii [2] , which belongs to the hemichordates , a sister clade to echinoderms . Remarkably , Six3 activates a large cohort of genes in the sea urchin ANE that are orthologs of genes expressed in the vertebrate ANE ( forebrain/eye field ) ( Figure 1A ) , raising the possibility that the common ancestor of sea urchins and vertebrates may have shared this ANE regulatory program [24] . Similar to the sea urchin embryo , an initial widespread regulatory state in late blastula/early gastrula stages of vertebrate embryos supports expression of genes encoding early anterior forebrain/eye field factors throughout the presumptive neuroectoderm , including six3 [28] , [29] . Simultaneously , secreted antagonists from the organizer block bone morphogenetic protein ( BMP ) signaling on the dorsal side and a high-to-low , posterior-to-anterior gradient of nβ-catenin forms in the presumptive neuroectoderm . This Wnt/β-catenin signaling gradient is part of a mechanism that activates genes encoding posterior neuroectoderm factors while down-regulating anterior ( forebrain/eye field ) factors in the posterior neuroectoderm [16] , [18] , [21] . By these mechanisms , the neural plate is formed and expression of the presumptive forebrain/eye field factors is restricted to cells at its anterior end , where Wnt antagonists protect them from posteriorization [30]–[33] . Multiple Wnts , Fzl receptors , and Wnt antagonists ( i . e . , Wnt8 , Wnt3a , Wnt1 , Fzl8 , and Dkk1 ) have been implicated in posteriorization of the neuroectoderm in vertebrate embryos , as well as members of the fibroblast growth factor ( FGF ) , retinoic acid ( RA ) , and transforming growth factor–beta ( TGF-β ) signaling pathways [28] , [30] , [34] , [35] . However , the exact functions of these pathways in AP neuroectoderm patterning have been difficult to determine because of their earlier functions as well as the complex cell movements of gastrulation during this process [28] , [30] , [36] . Moreover , the interactions among these various pathways in AP neuroectoderm patterning are not well understood . Recent studies suggest that early AP neuroectoderm patterning in vertebrate embryos is independent of information from the dorsal organizer . In both Xenopus and zebrafish , the initial widespread regulatory state promotes neuroectoderm specification throughout most of the embryo in the absence of β-catenin , which blocks dorsal organizer formation , as well as BMP2 , BMP4 , and BMP7 . Expression of neuroectoderm markers is radialized around the AP axis in these embryos , but remarkably they retain normal AP neuroectoderm patterning , and the ANE expands posteriorly when both maternal and zygotic Wnt/β-catenin function is blocked [20] , [21] . Interestingly , in the sea urchin embryo , the action of Wnt/β-catenin signaling in early patterning of the neuroectoderm along the AP axis [22] is also separate and distinct from the dorsal-ventral patterning mechanism because it occurs before Nodal and BMP signaling are activated and is required for their expression [37]–[40] . The inhibition of Wnt/β-catenin signaling , and consequently the loss of expression of Nodal and BMP , causes a large majority of cells to differentiate into ANE [22] , [24] , [41] . Thus , the developmental regulatory mechanisms used by vertebrate embryos for ANE development have striking similarities to those used by sea urchin embryos and may therefore represent an ancestral deuterostome mechanism . Here we show that the Wnt-dependent restriction of neuroectoderm to the anterior pole involves not only Wnt/β-catenin but also a series of linked steps mediated by Wnt/JNK signaling through Wnt1 , Wnt8 , and Fzl5/8 , the homolog of vertebrate Fzl8 . Coordinated progression of signaling through these Wnt pathways and activation of the secreted Wnt antagonist Dkk1 in anterior-most blastomeres establish the definitive ANE around the anterior pole . Signaling through a second Wnt receptor , Fzl1/2/7 , and its activation of PKC suppress Wnt/β-catenin and Wnt/JNK ANE restriction activities to coordinate the correct temporal progression of ANE restriction . Collectively , signaling through three different Wnt signaling pathways provides precise spatiotemporal control of neuroectoderm AP patterning along the AP axis .
FoxQ2 and Six3 are essential for the specification of the ANE and are the earliest ANE regulatory genes to be expressed . Their transcripts accumulate in the anterior half of the 32-cell embryo but are never detectable in the posterior half ( Figure 1B , C ) [22] , [24] . We reasoned that posterior repression might depend on Wnt/β-catenin signaling because this pathway is activated in posterior blastomeres by the 16-cell stage [4] , [14] , [42] , [43] . To test this possibility , we blocked nβ-catenin by injecting embryos with mRNA encoding either Tcf-Engrailed ( Tcf-Eng ) [42] or Axin [44] and examined foxq2 expression at the 32-cell stage ( Figure 1B , F; Figure S1 ) . In both cases , foxq2 and six3 were expressed in every blastomere during early cleavage stages ( 32-cell , Figure 1F; 120-cell , Figure 1G ) and ubiquitous expression persisted until late mesenchyme blastula stage ( 24 hpf ) ( Figures 1G , H and S1Ae–g ) . As expected , each perturbation resulted in formation of dauer blastulae with a thickened neuroepithelium covering most of the embryo that produced greatly increased numbers of serotonergic neurons throughout ( Figure 1I versus E; Figure S1Ah versus Ad ) . These 4-d embryos phenocopied ΔCadherin mRNA-injected embryos , which previously were shown to lack nβ-catenin in all but the four vegetal-most blastomeres , the small micromeres during cleavage stages [24] . Together , these data indicate that the factors that activate ANE specification operate in all early blastomeres in these Wnt/β-catenin-deficient embryos and likely are part of a ubiquitous maternal regulatory state . Moreover , these observations indicate that the first step in suppressing the ANE in the posterior half of the embryo depends on the repression or rapid down-regulation of ANE regulatory gene transcription by Wnt/β-catenin signaling . Previous studies have shown that restriction of foxq2 expression to the anterior pole depends on posterior Wnt/β-catenin signaling . However , Wnt/β-catenin signaling has never been detected in the anterior half of the embryo ( the presumptive ectoderm , blue in Figure 1Ja ) , suggesting that an intermediate signal ( s ) downstream of posterior Wnt/β-catenin signaling must mediate this second phase of ANE restriction ( Figure 1Jb versus Jc; the gray region in this and subsequent figures represents the posterior ectoderm and the orange arrows indicate the second phase of restriction ) . We hypothesized that this intermediate signal ( Figure 2C , signal X ) might also involve Wnt signaling , and we tested this idea by exploring the functions of the Wnt [Frizzled ( Fzl ) ] receptors in ANE restriction . Two of the four sea urchin receptors , Fzl5/8 and Fzl1/2/7 , were expressed during ANE restriction ( Figure S2A ) and also in the appropriate cells to mediate this process ( Figure S2Ba–h ) , making them excellent candidates for transducing Wnt signals that eliminate the ANE regulatory state from the posterior ectoderm ( Figure S2Bi–Bl ) . To determine whether Fzl5/8 signaling has a role in neuroectoderm AP patterning , we injected embryos either with morpholinos targeting Fzl5/8 or with mRNA encoding a C-terminal truncated form of the receptor ( ΔFzl5/8 ) that acts as a dominant negative by competing for Wnt ligands [45] . In contrast to embryos injected with Axin or Tcf-Eng mRNA , those expressing ΔFzl5/8 mRNA had normal foxq2 transcript levels and distributions at the 32-cell stage ( cf . , Figure 2Aa , Af ) , suggesting that Fzl5/8 signaling is not required for the initial Wnt/β-catenin-dependent down-regulation of foxq2 mRNA in the posterior half of the embryo . Further evidence that Fzl5/8 is not required for early Wnt/β-catenin activity is provided below . However , at mesenchyme blastula stage ( 24 hpf ) , ΔFzl5/8-injected embryos expressed foxq2 ectopically throughout the anterior half of the embryo , indicating that the second phase of its restriction to the anterior pole requires Fzl5/8 function ( cf . , Figure 2Ab , Ag ) . Expression of foxq2 also was not correctly restricted in two different Fzl5/8 morphants , although the phenotype was less pronounced ( cf . , Figure 2Ab , Ag versus Figure S3D , E ) . We used ΔFzl5/8 for further studies because it gave the more penetrant phenotype , likely because it blocked signaling through both maternal and zygotic Fzl5/8 . Importantly , eliminating expression of six3 , the critical upstream ANE regulator , from the posterior ectoderm also required functional Fzl5/8 signaling ( Figure 2Ad , Ai ) . Furthermore , the transcript levels per embryo for genes in the 24 hpf Six3-dependent ANE regulatory network ( Figure 2B ) were significantly elevated in ΔFzl5/8-containing mesenchyme blastula embryos . Interestingly , one of these was zygotic fzl5/8 mRNA itself ( Figure 2Ac , Ah ) , indicating that Fzl5/8 function is required to down-regulate fzl5/8 mRNA levels in the posterior ectoderm . Finally , 3-d pluteus larvae injected with ΔFzl5/8 had an expanded thick neuroepithelium with a greatly increased number of serotonergic neurons ( Figure 2Aj ) . In contrast , the thickened neuroepithelium in normal pluteus-stage embryos was restricted to a small region that produced only 4–6 serotonergic neurons ( Figure 2Ae ) . These observations indicate that a Fzl5/8 signaling-dependent process eliminates the ANE regulatory state required for serotonergic neural development from the posterior ectoderm ( Figure 2C ) . In addition to the ubiquitous maternal and anterior zygotic expression of fzl5/8 at mesenchyme blastula stage ( Figure S2e–h ) , it was also expressed in a ring of nonskeletogenic mesenchyme cells ( 24 hpf ) ( Figures 2Ac and S2Bh ) . Previously , Croce et al . ( 2006 ) [46] showed that Fzl5/8 signaling in these posterior cells works through the c-Jun N-terminal kinase ( JNK ) pathway to initiate primary invagination movements later during gastrulation . This observation raised the possibility that the earlier ANE restriction process mediated by Fzl5/8 in posterior ectoderm may also depend on the JNK pathway . jnk mRNA was present ubiquitously during ANE restriction ( Figure S2C ) , and indeed , foxq2 failed to restrict to the anterior pole in embryos injected with a splice-blocking JNK morpholino ( Figure S3A ) . This JNK morphant phenotype was weaker than the ΔFzl5/8 phenotype ( cf . , Figure 2G and Figure S3A ) , probably because some normal JNK transcripts persisted in the embryo ( Figure S3J ) . It is also possible that maternally synthesized JNK protein persisted in these embryos . As an additional test , we treated embryos with the specific JNK inhibitor , ( L ) -JNKI1 [46] , [47] , beginning at fertilization , which produced embryos expressing foxq2 throughout the anterior half of the embryo , mimicking exactly the ΔFzl5/8 phenotype ( Figure 2 , cf . Ag , Al ) . Moreover , fzl5/8 and six3 expression was not restricted to the anterior pole ( Figure 2Am , An ) , and these embryos also had an expanded , thickened neuroepithelium and an increased number of serotonergic neurons , as seen in ΔFzl5/8-injected embryos ( Figure 2Aj ) . These results indicate that the second phase of ANE restriction that down-regulates the ANE regulatory state in the anterior half ( i . e . , the posterior ectoderm ) depends on Fzl5/8 function . Moreover , they suggest that JNK activity transduces a Wnt signal X through this Wnt receptor , the production of which depends on Wnt/β-catenin activity in the posterior half of the embryo ( signal X , Figure 2C ) . To identify the link between Wnt/β-catenin signaling and Fzl5/8 , we first searched for genes encoding Wnt ligands that are expressed by the 60-cell stage ( i . e . , the beginning of the second phase of ANE restriction ) in posterior blastomeres and that also depend on Wnt/β-catenin activity . We confirmed the previously reported expression profile of wnt8 , which is activated by Wnt/β-catenin [48] , [49]: At the 60-cell stage , wnt8 was expressed in both the micromeres and the adjacent blastomere tier ( veg2 ) ( Figure 3Aa ) . Similarly , wnt1 expression was first detected midway through the 60-cell stage ( 9 hpf ) in the micromeres , and it also depended on nβ-catenin ( Figures 3Aa and S4A , C ) . As development progressed , wnt8 expression first moved into the next most anterior tier of blastomeres ( veg1 ) and then , during late blastula stages ( 18 and 24 hpf ) , into both veg1 and overlying posterior ectoderm cells ( Figure 3Ac , Ad ) . wnt1 expression continued in the micromeres until midblastula stages ( 15 hpf ) after which it , too , progressively moved to more anterior blastomeres until it reached the endoderm/ectoderm boundary during later blastula stages ( 24 hpf ) ( Figures 3Ac , Ad and S4A ) . Thus , genes encoding the secreted ligands Wnt1 and Wnt8 were expressed in posterior cells when the second phase of ANE restriction begins in the posterior regions of the anterior hemisphere . As restriction proceeded , wnt8 continued to be expressed near cells expressing ANE marker genes , whereas wnt1 expression was more posterior . In order to evaluate whether these secreted ligands were required for ANE restriction in posterior ectoderm , we performed knockdown experiments by injecting either of two different morpholinos designed against each . As shown in Figure 3B , embryos injected with either Wnt1 or Wnt8 morpholinos failed to down-regulate foxq2 expression in posterior ectoderm . ANE restriction was more strongly perturbed in Wnt1 morphants , even though the cells producing it were more distant from the site of action than those producing Wnt8 . This raised the possibility that Wnt1 is necessary for later Wnt8 expression . However , this was not the case because , at blastula stage ( 16 hpf ) , Wnt8 expression was normal in Wnt1 morphants ( Figure S4D ) . The converse was also true: wnt1 expression did not depend on Wnt8 ( Figure S4E ) . We conclude that production of each of these ligands depends on Wnt/β-catenin signaling , but they do not depend on each other but act in parallel in ANE restriction . These results suggest that Wnt1 and Wnt8 spatiotemporally link posterior Wnt/β-catenin signaling to Fzl5/8-mediated down-regulation of ANE factors in the posterior ectoderm . To test this hypothesis , we first showed that overexpressed Wnt1 or Wnt8 completely eliminated foxq2 expression in the ANE ( Figure 3Cb , Cd ) . We then tested whether this foxq2 down-regulation required active Fzl5/8 . Strikingly , ΔFzl5/8 strongly blocked the suppression of foxq2 expression mediated by either Wnt1 or Wnt8 ( 100% rescue of Wnt1 or Wnt8 misexpression phenotype; n = 63 and 67 , respectively ) ( Figures 3Cc , Ce and S5Bb , Bd ) . These results strongly support the conclusion from the Wnt1 and Wnt8 loss-of-function analyses that Fzl5/8-mediated ANE restriction in the posterior ectoderm requires these ligands . Furthermore , suppression of foxq2 expression by both Wnt 1 and Wnt8 also required JNK activity , since the JNK inhibitor rescued the loss-of-ANE phenotypes produced by misexpression of Wnt8 ( 81% of embryos rescued; n = 126 ) ( Figure 3Ca versus Cf ) and , to a lesser extent , Wnt1 ( 55% of embryos had low to normal foxq2 expression; n = 83 ) ( Figure S5A ) . These data indicate that Wnt1 , Wnt8 , and Fzl5/8 function in a Wnt/JNK signaling pathway to effect the second phase of ANE restriction . The expression pattern of the gene encoding the other early Wnt receptor , fzl1/2/7 , suggests that Fzl1/2/7 signaling also could affect neuroectoderm restriction ( Figure S2Ba–Bd ) . We tested this possibility by morpholino knockdown . We were surprised to find that neither six3 nor foxq2 was activated at the 32- to 60-cell stage ( Figure 4Aa versus Ah and Figure 4C ) and neither mRNA was detectable throughout the normal time of ANE restriction ( Figure 4Ah–k , Af- versus Am ) . As expected , zygotic fzl5/8 expression , which depends on Six3 [24] , also required Fzl1/2/7 ( Figure 4Ae versus Al ) . As well , the expression of all other known regulatory factors that depend on Six3 at mesenchyme blastula stage ( 24 hpf ) also required Fz1/2/7 function ( Figure 4D ) . Moreover , the ectoderm in 3- to 4-d Fzl1/2/7 morphants lacked a thickened columnar epithelium corresponding to the ANE in normal embryos ( Figure S3F ) . In 4-d pluteus larvae , which normally have well-established neurons in the ANE , the large majority of Fzl1/2/7 morphants had none ( 37/41 embryos ) ( Figure 4Ag versus An , green ) . They also had a severely reduced number of ciliary band neurons , as assayed by the pan-neural marker SynaptotagminB ( Figure 4An , 1e11 antibody , magenta ) . These results indicate that Fzl1/2/7-mediated signaling is essential for establishment and maintenance of the early neuroectoderm regulatory state , which in turn subsequently is required for the specification and differentiation of all neurons ( Figure 4Ag ) . The Fzl1/2/7 morphant phenotype is opposite to the Axin or Tcf-Eng misexpression phenotypes as well as those produced by ΔFzl5/8 misexpression or treatment with the JNK inhibitor or JNK morpholino . These observations raise the possibility that Fzl1/2/7 transduces a different Wnt signal , possibly through the Ca2+ pathway . Although the architecture of the Ca2+ pathway downstream of Fzl receptors is not yet well established , one important player in other systems is conventional Protein Kinase C ( PKC ) [50] , [51] . In the sea urchin embryo , genes encoding conventional PKC isoforms are expressed maternally and throughout development and at least one is activated by the 60-cell stage ( Figure 4B ) [52] . To test the hypothesis that pPKC , like Fzl1/2/7 , is necessary for maintaining ANE specification , we treated embryos with the specific PKC inhibitor , Bisindolylmaleimide 1 , which blocks activation through phosphorylation of most Ca2+-dependent PKC isoforms by competing for the ATP binding site [53] . Treatment with this inhibitor at 1–3 µM strongly reduced the level of pPKC ( Figure 4B ) , but had no detectable deleterious effects on the morphology of embryos during ANE restriction . Importantly , the level of pPKC in Fzl1/2/7 morphants was as low as that produced by the PKC-specific inhibitor ( Figure 4B ) , indicating that Fzl1/2/7 function is required for activation of this kinase . Similar to Fzl1/2/7 morphants , foxq2 expression was never initiated in embryos treated with the inhibitor continuously from fertilization to mesenchyme blastula stage ( 24 hpf ) ( Figure 4Ao–r ) . Moreover , six3 and fzl5/8 were not expressed ( Figure 4As , At ) , and in a large majority of embryos ( 36/39 ) serotonergic neurons did not develop ( Figure 4Au and Figure S3Ia versus Ic ) , showing that neural differentiation was severely compromised in treated embryos . While these experiments demonstrate that activation of PKC is required for the ANE regulatory state and that Fzl1/2/7 is required for that activation , they do not conclusively prove that Fzl1/2/7 signals through the Ca2+ pathway because PKC activation can occur by other mechanisms . We conclude that Fzl1/2/7 signaling and PKC activity are each essential for early neuroectoderm specification . Our findings that a Wnt signaling branch utilizing Fzl1/2/7 and PKC activity is necessary for initiating expression of upstream ANE regulatory factors was entirely unexpected because at early stages , Wnt signaling is thought to antagonize this process . We hypothesized that Wnt signaling through this receptor is necessary either for the expression of regulatory genes that specify the ANE or for antagonizing the ANE restriction mechanism from the very earliest stages . To distinguish between these alternatives , we first asked whether Fzl1/2/7 signaling is part of the maternal mechanism that can drive ubiquitous expression of ANE regulatory genes in the absence of Wnt/β-catenin signaling . Within each of three batches of embryos , we injected one set of fertilized eggs with Axin mRNA , a second set with Fzl1/2/7 morpholino , and a third with both Fzl1/2/7 morpholino and Axin mRNA ( Figure 5A ) . As shown above , foxq2 was expressed throughout the embryo in the absence of nβ-catenin , whereas it was completely undetectable in more than 90% ( 52/57 ) of embryos lacking Fzl1/2/7 . However , it was expressed at high levels throughout all Fzl1/2/7-deficient embryos ( 47/47 ) when Wnt/β-catenin signaling was also blocked . These results indicate that maternal factors are still capable of activating foxq2 in embryos lacking Fzl1/2/7 and that the loss of foxq2/ANE fate in Fzl1/2/7 morphants requires a functional Wnt/β-catenin pathway . Thus , Fzl1/2/7 signaling is not a positive regulator of the initial maternal regulatory state that supports ANE specification , but rather it inhibits the Wnt/β-catenin-dependent ANE restriction mechanism . To test if Fzl1/2/7 also antagonizes the Fzl5/8-JNK-dependent second phase of ANE restriction , we asked whether blocking Fzl5/8 or JNK function could rescue ANE specification in embryos lacking Fzl1/2/7 signaling ( Figure 5B , C ) . Similar to the above experiments , in three different batches of embryos , we found that blocking the function of either Fzl5/8 or the JNK pathway rescued the expanded expression of foxq2 in 99% ( n = 72 ) or 93% ( n = 70 ) , respectively , of embryos also lacking Fzl1/2/7 . These results suggest that Fzl1/2/7 antagonizes Fzl5/8-JNK-mediated ANE restriction . In the final set of experiments , we tested whether PKC signaling also antagonizes Fzl5/8-JNK-mediated ANE restriction ( Figure 5D ) . Using the same approach , we injected one set of fertilized eggs with ΔFzl5/8 , treated a second with the PKC inhibitor , and a third was treated with PKC inhibitor and injected with ΔFzl5/8 . Blocking the function of Fzl5/8 in these embryos rescued the expression of foxq2 in a large majority of embryos ( 77% rescue; n = 83 ) , demonstrating that , like Fzl1/2/7 , PKC antagonizes the ANE restriction mechanism by antagonizing Fzl5/8 signaling . Collectively , these results support the idea that the Fzl1/2/7-dependent suppression of Fzl5/8-mediated ANE restriction works through PKC ( Figure 5G ) . The data suggest that Fzl1/2/7 signaling antagonizes Fzl5/8-JNK-mediated down regulation of genes necessary for ANE specification . Because Fzl1/2/7 functions as early as the 32-cell stage to maintain expression of ANE markers , it might also antagonize Fz5/8 indirectly by down-regulating Wnt/β-catenin activity . To test this possibility , we measured the level of Wnt/β-catenin signaling in 120-cell embryos ( 12 hpf ) during the early stages of ANE restriction using the TCF-luciferase reporter plasmid , TopFlash [54] . Three different batches of embryos that had been injected with ΔFzl5/8 or treated with PKC inhibitor showed no significant difference in TopFlash activity when compared to controls ( Figure 5E ) , suggesting that neither of these proteins affects early Wnt/β-catenin signaling . In contrast , TopFlash activity increased ∼2 . 5-fold on average in embryos lacking Fzl1/2/7 compared to controls ( Figure 5E ) , indicating that signaling through Fzl1/2/7 negatively regulates Wnt/β-catenin activity in cleavage-stage embryos . Recently published experiments showed that introduction of mRNA encoding a dominant negative form of Fzl1/2/7 caused a reduction in TopFlash activity in cleavage-stage embryos and a loss of endoderm specification [55] . While this appears to conflict with our results , it is important to realize that interference with Fzl1/2/7 activity by misexpression of ΔFzl1/2/7 can interfere with the function of maternal Fzl1/2/7 , whereas Fzl1/2/7 morpholino cannot . In keeping with this , embryos in which zygotic Fzl1/2/7 synthesis was blocked with a morpholino still expressed Wnt1 and Wnt8 ( Figure 5F ) , whereas these are not expressed in embryos injected with ΔFzl1/2/7 [55] . Thus , in Fzl1/2/7 morphants , these Wnt ligands up-regulate Wnt/β-catenin- and Wnt/Fzl5/8-mediated ANE restriction , whereas the absence of these ligands in ΔFzl5/8-containing embryos leads to a reduction in Wnt/β-catenin activity . Collectively , these data suggest that Fzl1/2/7 signaling and PKC activity provide a buffer that limits the rate of ANE down-regulation by both of these Wnt signaling pathways ( Figure 5G ) . A possible concern in the ΔFz5/8 and ΔFz1/2/7 experiments is that elevating the levels of these proteins might influence the balance of signaling between the Wnt signaling pathways , for example , by competing for common components . To test this possibility , we overexpressed either wild-type Fzl5/8 or Fzl1/2/7 mRNA . In both cases , embryos developed normally and had normal foxq2 expression patterns ( Figure S6A ) . Next we showed that elevating the levels of Fzl1/2/7 mRNA did not change ΔFzl5/8's ability to prevent ANE restriction ( Figure S6B ) or prevent elimination of the ANE by excess Wnt1 mRNA ( Figure S6C ) . Taken together these data indicate that the levels of endogenous Fzl receptors are not limiting . These data contrast with the Wnt1 and Wnt8 misexpression results , which showed that excess ligand can dramatically up-regulate ANE restriction ( Figure 3Cb , d ) , suggesting that it is the levels of Wnt ligand in time and space and not those of the Wnt receptors that control the ANE restriction mechanism Around the mesenchyme blastula stage ( 24 hpf ) , restriction of the ANE is complete and it constitutes a separate regulatory domain at the anterior end of the embryo with well-defined borders . Expression of fzl5/8 is also restricted to this domain ( Figure 2 ) , raising the question of why Fzl5/8-mediated signaling does not continue to down-regulate the ANE regulatory state there . We hypothesized that the secreted Wnt antagonist , Dkk1 , might play a role because , in most of the major clades , competition between anterior Wnt antagonism by Dkk1 and posterior Wnt signaling has been shown to regulate cell fates along the primary ( AP ) axis [8] . Very low-level dkk1 expression was detectable as early as the 120-cell stage by qPCR ( Figure 6A ) , and increased during the time of ANE restriction , reaching maximal levels by the mesenchyme blastula stage ( 24 hpf ) . At this time dkk1 expression could be detected by in situ hybridization at the anterior end of the embryo as well as in a ring of cells surrounding the future site of gastrulation ( Figure 6A , inset ) . Thus , dkk1 was expressed at the right time and place to prevent anterior Wnt-mediated ANE down-regulation . Interestingly , expression of dkk1 depended on Fzl5/8 signaling ( Figure 6B ) , raising the possibility that Fzl5/8 signaling limits its own activity in anterior cells by promoting a negative feedback mechanism through this Wnt antagonist . To test whether Dkk1 protects the ANE regulatory state from Wnt-mediated down-regulation , we monitored the expression of a set of genes encoding ANE regulatory factors in Dkk1 morphants at mesenchyme blastula stage by in situ hybridization . Each of the genes tested was severely down-regulated in these embryos ( Figures 6Cg–k and S3H ) , and no serotonergic neurons developed in 4-d plutei ( Figure 6Cl ) . Furthermore , overexpression of Dkk1 mRNA prevented restriction of foxq2 expression ( Figure 6Db ) and rescued foxq2 expression in embryos also overexpressing wnt1 mRNA ( 88% rescue; n = 65 ) ( Figure 6Dc versus d ) . Together these results indicate that Dkk1 can block the Wnt1/Fzl5/8-JNK-dependent ANE restriction mechanism . Interestingly , overexpression of Dkk1 also rescued foxq2 expression in Fzl1/2/7 morphants ( 98% rescue; n = 64 ) ( Figure 6Ec , Ed ) , suggesting that it may interfere with either Wntβ-catenin or Fzl5/8 signaling or both . There is some support for both possibilities . First , Dkk1 likely inhibits Fzl5/8 activity because the morphological phenotype ( unpublished data ) and foxq2 expression pattern ( cf . , Figures 1F , 2Ag , and 6Db ) of Dkk1 mRNA-injected embryos were more similar to those of embryos lacking functional Fzl5/8 than to those lacking Wnt/β-catenin signaling ( cf . , Figure 6Db and Figures 1H and 2Ag ) . Second , misexpressed Dkk1 can also interfere with endomesodermal gene expression , which depends on the Wnt/β-catenin pathway ( Figure S4B ) .
The data presented here show that patterning the neuroectoderm along the AP axis of the early sea urchin embryo depends on an elegant spatiotemporal coordination and integration of the activities of three different Wnt signaling pathways . Throughout this process , a balance is achieved between the initial regulatory mechanisms that can specify the ANE ubiquitously , those that subsequently suppress it in posterior regions , and those that limit ANE suppression . The consequence is that ANE tissue is stably positioned only at the anterior pole of the embryo by the mesenchyme blastula stage . To summarize our current model ( Figure 7 ) , the first phase of ANE restriction requires Wnt/β-catenin and occurs very rapidly in posterior blastomeres by the 32- to 60-cell stage . Wnt/β-catenin signaling simultaneously activates expression of Wnt1 and Wnt8; these cells and these ligands initiate the second phase of ANE down-regulation in the posterior ectoderm ( non-ANE ectoderm in the anterior hemisphere ) by activating the Fzl5/8-JNK pathway , beginning around the 60-cell stage . As development progresses , Wnt1 and Wnt8 mRNAs accumulate in more anterior blastomeres , behind the front of ANE down-regulation . Whether these secreted ligands diffuse to the overlying ectoderm to directly activate Fzl5/8 or whether they act indirectly to stimulate production of other Wnt ligands that signal through this receptor is not known . Regardless , it is clear that Wnt1 , Wnt8 , Fzl5/8 , and JNK are all required for full ANE down-regulation in the posterior ectoderm and suppression of transcription of fzl5/8 itself . Clearly , Fzl5/8 plays a pivotal role in the ANE restriction process because it is necessary not only for the second phase of ANE restriction but also to stop that process in the third phase of ANE patterning when Fzl5/8 signaling leads to the expression of the Wnt receptor antagonist Dkk1 at the anterior pole . Thus , the coordination between the timing of auto-repression of fzl5/8 transcription and activation of Dkk1 by Fzl5/8 ensures that this negative feedback loop reproducibly defines the ANE at the anterior pole of the embryo by mesenchyme blastula stage ( 24 hpf ) . The relative timing of Dkk1 production in the anterior ectoderm and ANE restriction in the rest of the embryo is critical and carefully controlled by a third Wnt pathway working through Fzl1/2/7 and PKC activities that limit Wnt/β-catenin and Wnt/JNK functions during the first two phases of ANE clearance . Because all of these Wnt pathways affect the same developmental process ( i . e . , the specification of ANE versus non-ANE fates along the primary axis ) , they may function as components of an interactive Wnt signaling network rather than as separate pathways with different roles . Yet it appears that posterior Wnt/β-catenin and anterior Wnt/JNK signaling define two adjacent early regulatory domains in the sea urchin embryo . While our data suggest that these two signaling pathways activate different downstream regulatory programs in order to down-regulate ANE factors , both pathways are linked spatially and temporally by the activities of at least two common signaling components , Wnt1 and Wnt8 [49] , [56] . These results are in keeping with recent evidence that individual Wnt ligands are able to activate distinct Wnt signaling branches , often in the same or adjacent territories [57]–[59] . However , it remains to be determined whether Wnt1 and/or Wnt8 act directly on cells in the anterior hemisphere in the ANE restriction process , although it is interesting that wnt8 expression moves into posterior ectoderm cells as ANE factors move out . Alternatively , Wnt1 and Wnt8 may act indirectly by reinforcing the nβ-catenin gradient in the anterior-most cells of the posterior half of the embryo ( i . e . , near the equator ) , activating production of an unidentified intermediate Wnt ligand that is secreted from even more anterior cells and that activates Fzl5/8 signaling . We found that the cardinal ANE regulatory genes , six3 and foxq2 , are not expressed in Fzl1/2/7 knockdowns . This unexpected phenotype is the exact opposite of the ANE expansion produced by interference with Wnt/β-catenin , Fzl5/8 , and JNK signaling . The function of Fzl1/2/7 begins as early as the 32-cell stage , around the time that nβ-catenin is first detectable in posterior blastomeres [4] and at least 2 h before the ANE restriction process mediated by Fzl5/8 and JNK is observed . Since Fzl1/2/7 signaling significantly suppresses Wnt/β-catenin signaling during early cleavage stages , we propose that it reduces Wnt/β-catenin-dependent Fzl5/8 and JNK activities . This model suggests that Fzl1/2/7 signaling is essential for controlling the rate of progression of the ANE restriction mechanism along the AP axis , providing a “timing buffer” that prevents premature elimination of the ANE regulatory state during the early cleavage and blastula stages . We propose that one function of this Fzl1/2/7 “timing buffer” is to allow sufficient Fzl5/8-dependent accumulation of Dkk1 in the ANE by later blastula stages to protect it from Wnt signals and define its borders . Since Fzl1/2/7 does not appear to signal through either the Wnt/JNK or the Wnt/β-catenin pathways during ANE restriction , we propose that it transduces signals through the Wnt/Ca2+ pathway . This mechanism may be similar to the situation in several other systems where Wnt/Ca2+ signaling affects early development either through the intracellular messengers CamKI , Calcineurin , and the transcription factor , NF-AT , or through PKC [60] . Similar to what we report here , the Wnt/Ca2+ pathway has been shown to antagonize Wnt/β-catenin signaling during vertebrate D/V axis specification [61] , [62] . Interestingly , we found that blocking PKC activity with either an inhibitor or with Fzl1/2/7 morpholino had exactly the same effect on phosphorylated PKC levels and on the Fzl5/8-JNK-dependent re-specification of ANE to ectoderm fate . However , inhibiting the function of Fzl1/2/7 elevated Wnt/β-catenin activity , whereas loss of PKC activity did not . This result suggests that Fzl1/2/7 signaling activates two branches that affect ANE restriction , one that antagonizes early Wnt/β-catenin activity and another , mediated by pPKC , that blocks Fzl5/8-mediated ANE restriction in the anterior hemisphere . Thus , if Fzl1/2/7 mediates Wnt/Ca2+ signaling in the sea urchin embryo , it could affect several different downstream parallel pathways , any or all of which are necessary to prevent premature and complete elimination of the ANE regulatory state . Moreover , the involvement of Wnt/Ca2+ signaling in AP neuroectoderm patterning would be a first . These considerations suggest that the function of Fzl1/2/7 in the early embryo is context-dependent , and we propose that the balance of information sent by this receptor through different Wnt signaling pathways is essential for correct specification and patterning . Recent data from several laboratories suggest that the same Fzl receptors can activate different Wnt signaling pathways , even in the same cells [50] , [60] , [63] . For example , the sea urchin Fzl1/2/7 homologue , Fz7 , activates Wnt/β-catenin signaling and D/V axis specification in the early Xenopus embryo [63] , but it also later activates Wnt/JNK and possibly the PKC signaling pathways that are required in the same general territory for convergent extension movements during gastrulation [57] , [64] , [65] . In the sea urchin embryo , our results and those of Lhomond et al . ( 2012 ) [55] are consistent with two early roles for Fzl1/2/7 – one stimulating endoderm specification via nβ-catenin through maternal Fzl1/2/7 in posterior blastomeres and another produced by zygotic Fzl1/2/7 that antagonizes early Wnt/β-catenin and subsequent Wnt/JNK signaling through an alternative Wnt pathway ( Ca+2 ) that operates throughout the embryo . The balance between these pathways may favor Wnt/β-catenin signaling in the posterior half of the cleavage stage embryo because of localized Wnt/β-catenin pathway-specific co-factors in that part of the embryo [66] , [67] . Striking parallels are emerging in the regulatory mechanisms that sea urchin and vertebrate embryos use to establish neural regulatory states at the anterior pole . Both embryos require Six3 for anterior neural development and share many homologous factors [24] , [27] . Moreover , as shown here , in the absence of Wnt/β-catenin , and consequently of Nodal , BMP , and all other known signaling pathways , the regulatory state of all of the cells in the sea urchin embryo supports development of ANE from the very beginning of its specification . These data indicate that an initial ubiquitous maternal regulatory state activates ANE specification and that one of the most important roles of posterior Wnt/β-catenin signaling is to break the symmetry of this neural-promoting state . Similarly , in vertebrate embryos , an initial regulatory state is capable of activating ANE markers throughout the embryo in the absence of Wnt , Nodal , and BMP signaling [15] , [20]–[22] , [68] . Thus , this initial , broad activation of ANE specification , and its subsequent down-regulation , could be a widely shared property of deuterostome embryos . The Wnt-dependent mechanism used for AP neuroectoderm patterning is still incompletely understood in vertebrates , in part because complex cell movements during patterning and the involvement of Wnt signaling in earlier specification events obscure the spatial and temporal relationships among the individual players [28] , [30] , [36] . In vertebrates , the only known Wnt pathway involved in the early restriction of ANE factors to the anterior pole is Wnt/β-catenin signaling [16]–[18] . Here , we show for the first time , to our knowledge , that the anterior Dkk1-posterior Wnt/β-catenin neuroectoderm patterning mechanism observed in vertebrates exists in a nonchordate deuterostome . These data strongly suggest the general Dkk1-Wnt/β-catenin AP patterning mechanism present in extant pre-bilaterian embryos was likely co-opted to pattern the neuroectoderm along the AP axis in the deuterostome ancestor . In addition to a posterior-to-anterior gradient of Wnt/β-catenin signaling , AP neuroectoderm patterning in the sea urchin embryo also requires Wnt/JNK signaling and an additional pathway mediated by Fzl1/2/7 that may function in Wnt/Ca2+ signaling . At present these are completely novel findings , but the fact that orthologs of several Wnt signaling components that function in these additional pathways in sea urchins ( Fzl8 , Wnt1 , Wnt8 , Dkk1 ) ( Figure 8A , C ) also are involved in posteriorizing the neural plate of vertebrate embryos ( Figure 8A ) [17] , [31] , [69] raises the possibility that this entire multistep mechanism was present in the common echinoderm/vertebrate ancestor and still operates to specify anterior neural identity in deuterostome embryos . Supporting this view , recent studies in hemichordates indicate that expression of homologues of sea urchin foxq2 , sfrp1/5 , and six3 demarcate an anterior-most region of the embryo that is homologous to the vertebrate anterior neural ridge secondary patterning center [19] . Interestingly , these factors are initially broadly expressed and restricted to this region by an unknown mechanism that depends on posterior Wnt/β-catenin signaling and appears to require Fzl5/8 function in the anterior part of the embryo ( Figure 8D ) . Moreover , there are similarities in the expression patterns of ANE genes ( dkk1 , dkk3 , six3 , foxq2 ) and those specifying endomesoderm ( wnt1 and wnt8 ) between the invertebrate chordate amphioxus and the sea urchin embryo ( Figure 8B ) . For example , foxq2 is initially expressed in a broad region and subsequently restricted to the anterior-most region . It can be completely cleared from this region of the embryo by LiCl treatment , which can elevate Wnt/β-catenin signaling [11] , raising the possibility that amphioxus also uses the same ANE patterning mechanism . Thus , there is accumulating evidence that the ANE clearance mechanism described here may be used in a wide variety of deuterostomes . However , to date , only the work reported here reveals the intricate , interdependent Wnt signaling mechanisms that are required to confine the ANE regulatory state to the anterior end of the embryo .
Strongylocentrotus purpuratus sea urchins were obtained from Point Loma Marine Invertebrate Lab , Lakeside , CA; The Cultured Abalone , Goleta , CA; or Marinus , Garden Grove , CA . Embryos were cultured in artificial seawater at 15°C . For drug treatments , eggs attached to a protamine sulfate-coated plate were fertilized in the presence of 2 mM 4-Aminobenzoic acid ( PABA ) , and fertilization envelopes were removed by shear force . Treatments with the cell-permeable JNK Inhibitor 1 , ( L ) -form , ( EMD/Calbiochem ) and the PKC inhibitor , Bisindolylmaleimide 1 ( EMD/Calbiochem ) , were performed by diluting the stock solution to 50 µM or 3 µM , respectively . JNK Inhibitor 1 , ( L ) -form is a specific inhibitor that blocks interactions between JNK and its transcriptional substrates , such as c-Jun and c-Fos , resulting in a knockout phenotype [46] , [47] . Bisindolylmaleimide 1 is a selective inhibitor that specifically competes with the ATP binding site of most PKC isoforms [53] . As controls for the PKC inhibitor experiments , DMSO was added alone . These experiments were repeated with at least three different embryo batches , and each produced the same results . The 24-h blastula total cDNA was used to obtain full-length clones for dkk1 , frizzled5/8 , frizzled1/2/7 , wnt1 , and a partial clone of jnk by PCR . The following primers were based on the sea urchin genome sequence: Sp-dkk1 Forward 5′-AGAATGGCGGCTCCTTCTGC-3′ , Reverse 5′-TCATAATACAGTTAACTGGC-3′; Sp-frizzled5/8 Forward 5′-AGAATGGCTGCCTTCAGTGGAAC-3′ , Reverse 5′-TCACACCTGTACATTTGGTA-3′; Sp-frizzled1/2/7 Forward 5′-AGAATGGGTTGGTTGGTGAGA-3′ , Reverse 5′-TCATACATTGGCTGGTGCAC-3′; Sp-wnt1 Forward 5′-AGAATGAAACTTGAGTGGTTTG-3′ , Reverse 5′-CTACAAGCATCTGTGCACG-3′; Sp-jnk Forward 5′-GAATGTGACGCATGCCAAGC-3′ , Reverse 5′-GATCACCGCCGTCGTCTATTG-3′ . Full-length dkk1 and wnt1 cDNA sequences were inserted into pCS2+ vector for mis-expression studies . ΔFzl5/8-pCS2 and Wnt8-pCS2 were obtained from Jenifer Croce ( CNRS/Villefranche sur Mer , France ) and Christine Byrum ( College of Charleston , Charleston , SC ) , respectively . pCS2 constructs were linearized with Not1 and mRNA was synthesized with mMessage Machine kit ( Ambion ) , purified by LiCl precipitation and ∼20 pl injected at the following concentrations: Fzl1/2/7 mRNA = 1 . 0–1 . 5 µg/µL; Fzl5/8 mRNA = 2 . 0 µg/µL; ΔFzl5/8 mRNA = 2 . 0 µg/µL; Wnt1 mRNA = 0 . 01–0 . 1 µg/µL; Wnt8 mRNA = 0 . 5–1 . 0 µg/µL; Dkk1 mRNA = 3 . 0 µg/µL; Axin mRNA = 1 . 0 µg/µL; Tcf-Eng mRNA = 0 . 5–1 . 0 µg/µL . S . purpuratus EST sequences for wnt1 , fzl1/2/7 , and fzl5/8 as well as sequence information from 5′ RACE on dkk1 were used to generate translation-blocking morpholino oligonucleotides . A splice-blocking morpholino oligonucleotide was designed for the second exon–intron boundary of wnt8 , which produces transcripts encoding a protein lacking sequence from the second exon , which was verified by PCR ( Figure S2A ) . The morpholinos were produced by Gene-Tools LLC ( Eugene , OR ) . The sequences and injection concentrations were: Wnt1 MO1: 5′-ACGCTACAAACCACTCAAGTTTCAT-3′ ( 1 . 8 mM ) ; Wnt1 MO2: 5′-ATCCTCATCAAAACTAACTCCAAGA-3′ ( 0 . 4 mM ) ; Wnt8 splice MO: 5′-GTAAAGTGTTTTTCTTACCTTGGAT-3′ ( 0 . 7 mM ) ; Wnt8 MO2: 5′-GTACACTCCAATAAAAGAAATCAAA-3′ ( 0 . 6 mM ) [49]; Fzl1/2/7 MO1: 5′-CATCTTCTAACCGTATATCTTCTGC-3′ ( 1 . 3 mM ) ; Fzl1/2/7 MO2: 5′-ACAGATCTCCTTTAACAAGGGTAGA-3′ ( 2 . 2 mM ) ; Fzl5/8 MO1: 5′-GGATTGTTCCACTGAAGGCAGCCAT-3′ ( 2 . 25 mM ) ; Fzl5/8 MO2: 5′-ATGTTTATGGTCTGATGGCAATCGC-3′ ( 0 . 6 mM ) ; Dkk1 MO1: 5′-GCGTCTAAATCCTAAATTCCTTCCT-3′ ( 1 . 5–1 . 6 mM ) ; Dkk1 MO2: 5′-ATCGTTGGTAGTTGCAGAAATTCGT-3′ ( 0 . 7–0 . 85 mM ) ; and JNK splice MO: 5′-CCTCATCGTTCTAGACTCACCGTTC-3′ ( 1 . 0–1 . 25 mM ) . Embryos were injected immediately after fertilization with solutions containing FITC , 20% glycerol , and mRNA and/or morpholino oligonucleotides . All injected embryos were cultured at 15°C . Microinjection experiments were performed using at least three different batches of embryos , and each experiment consisted of 50–150 embryos unless otherwise stated . Experiments were scored only if a change in phenotype or marker expression was seen in at least 85%–90% of the manipulated embryos . qPCR was performed as described previously [24] . Each experiment was repeated with embryos from at least three different mating pairs , and each PCR reaction was carried out in triplicate . The primer set information can be found in Table S1 . For developmental expression analysis , the number of transcripts per embryo was estimated based on the Ct value of the z12 transcript [70] . The probes for each gene analyzed correspond to the full-length cDNA sequence . Alkaline phosphatase and three-color fluorescent in situ hybridization were carried out as previously described [24] , [71] . For the three-color in situ hybridization , foxq2 was labeled with fluorescein and detected with Cy5-TSA , wnt1 was labeled with DNP and detected with Cy3-TSA , and wnt8 was labeled with DIG and detected with fluorescein-TSA . Embryos were fixed in 2%–4% paraformaldehyde in artificial seawater at RT for 20 min and washed 5 times in phosphate-buffered saline containing 0 . 1% Tween-20 . Embryos were incubated with primary antibodies at 4°C overnight at a dilution of 1∶1 , 000 for serotonin ( Sigma , St . Louis , MO ) and synaptotagminB/1e11 [72] . Primary antibodies were detected by incubating embryos with Alexa-coupled secondary antibodies for 1 h at RT . Nuclei were stained with DAPI . Protein extracts were prepared by adding 30 µL of lysis buffer ( 25 mM Tris-HCL pH 7 . 4; 150 mM NaCl; 5 mM EDTA; with PhosSTOP phosphatase and Complete Mini protease inhibitor cocktails; Roche , Indianapolis , IN ) to a pellet of 300 injected embryos . Embryos were crushed 4–5 times with a pestle , immediately spun at 16 , 000 RCF for 15 min at 4°C , and the supernatant was stored at −80°C until use . Samples were thawed on ice and 4× NuPage Running Buffer containing 4% SDS and 10% 2-ME was added . Samples were heated at 80°C for 3–5 min and 20 µL of each sample was run on 4%–12% NuPage Bis-Tris gradient gel ( Invitrogen , Grand Island , NY ) , transferred to nitrocellulose . Membranes were probed overnight at 4°C in Phosphate Buffered Saline+0 . 1% Tween-20 ( PBST ) +3% BSA with a poly-clonal Phospho-PKC ( pan ) ( β11 Ser660 ) antibody ( Cell Signaling Technology , Danvers , MA ) ( 1∶250 ) that recognizes a region that includes serine 660 and detects endogenous levels of phosphorylated PKC α , β1 , β11 , δ , ε , η , and θ . The recognition sequence is conserved in S . purpuratus PKC isoforms . Membranes were washed 3–5 times in room temperature PBST and probed for 1 h at room temperature in PBST+3% Bovine Serum Albumin with an enhanced chemiluminescent anti-rabbit IgG horseradish peroxidase secondary antibody ( GE Healthcare , Piscataway , NJ ) . After 3–5 more washes in PBST , the membranes were developed and imaged . Promega Dual Luciferase Reporter System ( Promega ) was used to perform dual luciferase assays . Embryos ( 350–400 ) were injected with linearized TopFlash-Firefly Luciferase ( REF ) and Endo16-Renilla Luciferase plasmids at concentrations of 20 ng/µL and 10 ng/µL , respectively , along with 10 ng/µL of linearized genomic DNA carrier . The Firefly and Renilla luciferase signals were recorded with a plate style luminometer using Promega's suggested protocol . The level of luciferase activity was normalized to the level of Renilla activity for each experiment . All experiments were repeated three times using separate batches of embryos . | The initial regulatory state of most cells in many deuterostome embryos , including those of vertebrates and sea urchins , supports anterior neural fate specification . It is important to restrict this neurogenic potential to the anterior end of the embryo during early embryogenesis , but the molecular mechanisms by which this re-specification of posterior fate occurs are incompletely understood in any embryo . The sea urchin embryo is ideally suited to study this process because , in contrast to vertebrates , anterior–posterior neuroectoderm patterning occurs independently of dorsal-ventral axis patterning and takes place before the complex cell movements of gastrulation . In this study , we show that a linked , three-step process involving at least three different Wnt signaling pathways provides precise spatiotemporal restriction of the anterior neuroectoderm regulatory state to the anterior end of the sea urchin embryo . Because these three pathways impinge on the same developmental process , they could be functioning as an integrated Wnt signaling network . Moreover , striking parallels among gene expression patterns and functional studies suggest that this mechanism of anterior fate restriction could be highly conserved among deuterostomes . | [
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"kinase",
"s... | 2013 | Integration of Canonical and Noncanonical Wnt Signaling Pathways Patterns the Neuroectoderm Along the Anterior–Posterior Axis of Sea Urchin Embryos |
Innate immune response against Brucella abortus involves activation of Toll-like receptors ( TLRs ) and NOD-like receptors ( NLRs ) . Among the NLRs involved in the recognition of B . abortus are NLRP3 and AIM2 . Here , we demonstrate that B . abortus triggers non-canonical inflammasome activation dependent on caspase-11 and gasdermin-D ( GSDMD ) . Additionally , we identify that Brucella-LPS is the ligand for caspase-11 activation . Interestingly , we determine that B . abortus is able to trigger pyroptosis leading to pore formation and cell death , and this process is dependent on caspase-11 and GSDMD but independently of caspase-1 protease activity and NLRP3 . Mice lacking either caspase-11 or GSDMD were significantly more susceptible to infection with B . abortus than caspase-1 knockout or wild-type animals . Additionally , guanylate-binding proteins ( GBPs ) present in mouse chromosome 3 participate in the recognition of LPS by caspase-11 contributing to non-canonical inflammasome activation as observed by the response of Gbpchr3-/- BMDMs to bacterial stimulation . We further determined by siRNA knockdown that among the GBPs contained in mouse chromosome 3 , GBP5 is the most important for Brucella LPS to be recognized by caspase-11 triggering IL-1β secretion and LDH release . Additionally , we observed a reduction in neutrophil , dendritic cell and macrophage influx in spleens of Casp11-/- and Gsdmd-/- compared to wild-type mice , indicating that caspase-11 and GSDMD are implicated in the recruitment and activation of immune cells during Brucella infection . Finally , depletion of neutrophils renders wild-type mice more susceptible to Brucella infection . Taken together , these data suggest that caspase-11/GSDMD-dependent pyroptosis triggered by B . abortus is important to infection restriction in vivo and contributes to immune cell recruitment and activation .
Inflammasomes are multiprotein complexes that assemble in response to pathogen- and damage-associated molecular patterns ( PAMPs and DAMPs ) . The NLRP3 inflammasome , via the adaptor molecule ASC , leads to caspase-1 activation and release of proinflammatory cytokines such as IL-1β and IL-18 [1 , 2] . An extensive range of stimuli can trigger the canonical activation of this inflammasome such as damage and stress indicative signals [3–5] , environmental insults [6–9] , microbial products [10 , 11] and bacterial pore-forming toxins [12] . However , recent studies have shown that Gram-negative bacteria can trigger the NLRP3 inflammasome in a non-canonical manner , that depends on caspase-11 [13 , 14] . In this process , caspase-11 , which was shown to be critical during septic shock [15–19] , recognizes bacterial LPS in the cytoplasm , dependent on mouse chromosome 3 GBPs [20–22] . More recently , studies unveiled a pyroptosis mechanism in which active caspase-11 cleaves a protein named Gasdermin D ( GSDMD ) in its C-terminal p20 and N-terminal p30 fragments [23 , 24] . The p30 N-terminal domain inserts and oligomerizes into the plasma membrane forming pores with a diameter of 15–20 nm [25 , 26] . Osmotic imbalance triggered by membrane pore formation thereby culminates in membrane rupture and cell death termed pyroptosis [27] . Through the membrane pore , products such as IL-1β [28] , ions as potassium , eicosanoids and other proinflammatory molecules can be released [27 , 29] . Potassium efflux from the cells is one of the mechanisms believed to trigger NLRP3 inflammasome activation leading to caspase-1 activation and proinflammatory cytokine maturation [30–35] . Furthermore , cytokines and eicosanoids released through the pores might contribute to restricting infection as they drive the recruitment of neutrophils to the local of the infection in order to remove pyroptotic macrophages by efferocytosis [29 , 36] . Brucella abortus is a Gram-negative facultative intracellular bacterium that causes in humans and cattle a disease termed brucellosis . In humans , it causes pathological manifestations such as arthritis , endocarditis , and meningitis , while in cattle it leads to abortion and infertility , resulting in serious economic losses to the livestock industry [37] . This pathogen infects primarily antigen-presenting cells ( APCs ) , such as dendritic cells and macrophages [38 , 39] . These phagocytes act both as an initial replicative niche as well as vehicles for the systemic dissemination of this pathogen , which will then infect myeloid lineage as liver and spleen macrophages , besides remaining in granulomatous lesions [40] . Once inside host cells , B . abortus develop an intracellular sophisticated replicative cycle [39] . It delivers effector proteins into macrophages cytoplasm through the virB type IV secretion system in order to subvert the normal intracellular traffic and establish a replicative niche inside phagocytes termed rBCV ( replicative Brucella containing vacuole ) [41–43] . The innate immune response against B . abortus begins upon interaction with APCs through recognition by pattern recognition receptors such as TLRs and NLRs [44] . MyD88 and IRAK4 are critical molecules involved in TLRs signaling pathway which results in the activation of NF-κB , MAPKs and production of inflammatory cytokines . These molecules play an essential role for production of proinflammatory cytokines by macrophages and control of B . abortus infection in mice [45–47] . Although B . abortus modified LPS is a weak activator of TLR4 , unlipidated outer membrane protein ( OMP ) 16 ( U-OMP16 ) derived from B . abortus is able to trigger TLR4-dependent inflammatory cytokine production [45 , 48] . Furthermore , L-Omp19 triggers TLR2-dependent TNF-α and IL-6 production in mouse peritoneal macrophages [49] . While TLR2 and TLR4 play no role controlling B . abortus infection in mice , TLR9 correlated to restricting infection , and recently TLR9 was shown to be activated by B . abortus DNA-derived CpG motifs [45 , 50] . Previously published studies from our group revealed that B . abortus can also be recognized by NLR proteins . NOD1 and NOD2 contribute to NLR signaling in response to B . abortus as NOD1- and NOD2- deficient BMDMs produced reduced levels of TNF-α [51] . Nevertheless , the absence of these molecules was not critical to control B . abortus infection [51] . Additionally , B . abortus can trigger activation of ASC-dependent inflammasomes such as NLRP3 and AIM2 , leading to caspase-1 activation and IL-1β secretion [44 , 52 , 53] . In this study , we demonstrated that Brucella LPS is sensed by caspase-11 and triggers GSDMD-dependent pyroptosis leading to control of bacterial infection in vivo .
Previously , we demonstrated that B . abortus infects macrophages leading to caspase-1 activation and IL-1β secretion dependent on NLRP3 [52] . Recently , Kayagaki and collaborators described a non-canonical NLRP3 inflammasome activation pathway dependent on caspase-11 [13] . However , the role of caspase-11 during B . abortus infection was still unknown . Thus , we investigated whether NLRP3 inflammasome activation in response to B . abortus required caspase-11 . We infected LPS-primed C57BL/6 , Casp11-/- , Nlrp3-/- and Casp1/11-/- BMDMs with B . abortus and measured IL-1β secretion and caspase-1 cleavage . We also infected BMDM from Casp1/11−/− mice expressing a functional caspase-11 allele to generate single caspase-1-deficient mice ( hereafter termed Casp1−/−Casp-11Tg ) [13] . After 17 hours of infection , secretion of IL-1β into the supernatant was evaluated . We observed that Casp11- , Nlrp3- and Casp1-single-deficient BMDMs reduced the levels of IL-1β released in comparison to C57BL/6 ( Fig 1A ) . The remaining IL-1β release observed in Casp11-deficient macrophages is probably due to canonical NLRP3 inflammasome activation . As expected , non-infected macrophages did not release significant levels of IL-1β . To evaluate the importance of the B . abortus type IV secretion system for IL-1β secretion , we also infected these macrophages with type IV secretion system deficient B . abortus ( ΔvirB2 ) and observed that all macrophages secreted reduced levels of IL-1β in response to B . abortus ΔvirB2 in comparison to WT B . abortus . As a control , these macrophages were treated with nigericin , a canonical NLRP3 agonist . As expected , we observed that primed C57BL/6 and Casp11-deficient BMDMs secreted similar levels of IL-1β , whereas primed Casp1-/-Casp11Tg , Casp1/11-/- and Nlrp3-/- were unable to secrete IL-1β in response to nigericin ( Fig 1A ) . We also decided to investigate whether IL-1α release induced by B . abortus required caspase-11 . We infected BMDMs from C57BL/6 , Casp11-/- , Casp1-/-Casp11Tg , Nlrp3-/- and Casp1/11-/- with B . abortus and after 17 hours of infection , we collected supernatant and measured IL-1α release . We observed that C57BL/6 and Casp1-/-Casp11Tg and Nlrp3-/- secreted similar levels of IL-1α ( Fig 1B ) . However , BMDMs from Casp11-/- and Casp1/11-/- released reduced levels of this cytokine suggesting the importance of caspase-11 but not caspase-1 promoting IL-1α release in response to B . abortus . As expected , non-infected controls did not secrete significant levels of this cytokine . Next , we assessed if caspase-11 is required for caspase-1 cleavage . We infected primed C57BL/6 , Casp11-/- and Nlrp3-/- BMDMs with B . abortus . After 17 hours of infection , cell supernatants were collected and subjected to Western blotting using a specific Ab against the p20 subunit of caspase-1 . We observed that Casp11-deficient BMDMs showed reduced levels of caspase-1 activation in comparison to C57BL/6 macrophages which were fully able to activate caspase-1 ( Fig 1C ) . The minor caspase-1 processing observed in Casp11-deficient macrophages is probably due to canonical NLRP3 inflammasome activation . As a control , we infected Casp1-/-Casp11Tg and Casp1/11-/- which did not express caspase-1 . These macrophages were also infected with the B . abortus type IV secretion system mutant ΔvirB2 and they were not able to activate caspase-1 . As a control for cell viability and the ability to cleave caspase-1 in response to a known stimulus , macrophages were treated with nigericin . We observed that C57BL/6 and Casp11-/- were fully able to activate caspase-1 , as expected ( Fig 1D ) ; however , Nlrp3-/- BMDMs were unable to activate caspase-1 and Casp1-/-Casp11Tg and Casp1/11-/- did not express caspase-1 . In order to assess whether these BMDMs properly express caspase-11 , we infected primed C57BL/6 , Casp11-/- , Casp11-/-Casp11Tg and Casp1/11-/- BMDMs with B . abortus and analyzed caspase-11 expression . Caspase-11 was efficiently upregulated in response to infection with B . abortus in C57BL/6 and Casp1-/-Casp11Tg BMDMs . As expected , BMDMs from Casp11-/- and Casp1/11-/- did not express caspase-11 ( S1 Fig ) . Further , to investigate whether lack of caspase-11 or caspase-1 could interfere in inflammasome-independent cytokines , levels of IL-12 and TNF-α were measured in the supernatants of Brucella-infected KO macrophages . As observed in Fig 1E , infected Casp11-/- and Casp1/11-/- macrophages produced similar levels of these cytokines when compared to cells of wild-type mice . Taken together , these data suggest that caspase-11 is required for caspase-1 activation , IL-1β and IL-1α secretion in response to B . abortus . Previous study suggested that caspase-11 is an intracellular LPS receptor [17] . Once it recognizes LPS in the cytosol , caspase-11 is activated triggering pyroptosis and IL-1α secretion . Moreover , caspase-11 is able to trigger NLRP3/ASC inflammasome activation , leading to caspase-1 processing and IL-1β secretion [15–17] . Thus , we analyzed whether B . abortus LPS directly transfected into macrophage cytosol was able to trigger caspase-1 activation and IL-1β secretion . BMDMs from C57BL/6 , Nlrp3-/- , Casp1/11-/- , Casp1-/-Casp11Tg and Casp11-/- mice were transfected with purified B . abortus LPS and after 17 hours of transfection , we measured IL-β production and caspase-1 activation in the cell supernatant . We observed that C57BL/6 BMDMs were able to produce high levels of IL-1β in response to cytoplasmic LPS ( Fig 2A ) . In contrast , BMDMs from Casp11-/- , Casp1-/-Casp11Tg , Casp1/11-/- and Nlrp3-/- mice secreted low levels of IL-1β similar to control cells treated only with transfection reagent FuGENEHD . These data suggested that B . abortus LPS is recognized by caspase-11 in the macrophage cytosol and leads to IL-1β secretion dependent on NLRP3 , caspase-1 and caspase-11 . Also , we investigated whether B . abortus LPS was able to trigger caspase-1 activation in a caspase-11-dependent manner . BMDMs from C57BL/6 , Nlrp3-/- , Casp1/11-/- , Casp1-/-Casp11Tg and Casp11-/- mice were transfected with B . abortus LPS . After 17 hours of transfection , cell supernatants were collected and lysates were prepared for immunoblotting using specific Ab . We observed that wild-type macrophages directly transfected with B . abortus LPS activates caspase-1 ( Fig 2B ) . In contrast , BMDMs from Nlrp3-/- and Casp11-/- mice were not able to activate caspase-1 in response to B . abortus LPS . As expected , Casp1-/-Casp11Tg and Casp1/11-/- BMDMs did not express caspase-1 . Moreover , caspase-1 activation was not observed in non-treated and FuGENEHD-treated BMDM controls , as expected . These data suggested that caspase-1 activation in response to B . abortus LPS is dependent on caspase-11 and NLRP3 . Collectively , these data demonstrated that B . abortus LPS is the PAMP responsible for non-canonical caspase-11 inflammasome activation when recognized by caspase-11 in the macrophage cytosol . Once caspase-11 is activated , it triggers an inflammatory form of cell death termed pyroptosis , which is independent of NLRP3/caspase-1 axis [13] . Therefore , we asked whether B . abortus is able to trigger pore formation and pyroptosis . BMDMs from C57BL/6 , Nlrp3-/- , Casp1/11-/- , Casp1-/-Casp11Tg and Casp11-/- mice were infected with B . abortus in a medium containing propidium iodide . To assess pore formation , we quantified the influx of propidium iodide into the nuclei of the cells in real time during 8 h of infection . We observed that B . abortus was able to trigger pore formation in C57BL/6 , Casp1-/-Casp11Tg and Nlrp3-/- BMDMs , but failed to trigger pore formation in Casp11-/- and Casp1/11-/- BMDMs ( Fig 3A–3E ) . Thus , B . abortus is able to trigger pore formation in macrophages dependent on caspase-11 but independently of caspase-1 or NLRP3 . When we stimulated the cells with nigericin as control , Casp11-deficient BMDMs were as able to form pores as C57BL/6 BMDMs , whereas Casp1-/-Casp11Tg , Nlrp3-/- and Casp1/11-/- failed to trigger pore formation in response to nigericin ( Fig 3F ) . Taken together , these data suggest that B . abortus triggers pore formation in macrophages dependent on caspase-11 but independent of caspase-1 . Guanylate-binding proteins ( GBPs ) are IFN-inducible GTPases which act both in the membrane disruption of vacuolar pathogens and facilitating intracellular LPS interaction with caspase-11 to activate non-canonical inflammasome , mainly when LPS is within liposomal membranes and within bacterial outer membranes [20–22] . We therefore hypothesized that GBPs participate in the activation of the non-canonical inflammasome by B . abortus . Thus , we asked whether GBPs are involved in pore-formation in response to B . abortus . To assess the role of GBPs , we infected BMDMs from C57BL/6 , Gbpchr3-/- ( deficient for the locus on mouse chromosome 3 encoding GBP1 , GBP2 , GBP3 , GBP5 , and GBP7 ) , Gbp2-/- and Casp1/11-/- with B . abortus . By evaluating propidium iodide uptake in real time during 8 h of infection , we found that Gbp2-/- BMDMs were able to form pores similar to C57BL/6 BMDMs whereas Gbpchr3-/- BMDMs failed to form pores in response to B . abortus as observed for Casp1/11-/- ( Fig 4B ) . As expected , non-infected controls failed to trigger pore formation ( Fig 4A ) . As a control , we treated BMDMs from C57BL/6 , Gbpchr3-/- , Gbp2-/- and Casp1/11-/- with nigericin and evaluated propidium iodide uptake in real time during 2 h of treatment . We observed that Gbp2- and Gbpchr3-deficient BMDMs form pores at the same level as C57BL/6 BMDMs in response to nigericin whereas Casp1/11-/- BMDMs failed to replicate this phenotype ( Fig 4C ) . These data suggest that GBP2 seems to be dispensable but other GBPs on mouse chromosome 3 are critical to pore formation in response to B . abortus . Because caspase-11 activation is required for pore formation , we asked whether GBPs on mouse chromosome 3 are important to caspase-11 activation . Therefore , BMDMs from C57BL/6 and Gbpchr3-/- mice were pre-treated with a biotin-labeled caspase inhibitor ( Biotin-VAD-FMK ) which only binds to the active site of activated caspases . After 15 min , cells were infected with B . abortus for 17 h and subsequently , cell lysates were submitted to pulldown with streptavidin-coupled beads . Then , the pulldown product was subjected to western blotting using specific Ab against caspase-11 . We found that in the absence of GBPs from chromosome 3 , caspase-11 could not be activated while in wild-type BMDMs caspase-11 was strongly activated ( Fig 4D ) . Altogether , these data suggest that GBPs on mouse chromosome 3 are essential for Brucella-driven caspase-11 activation and consequently to non-canonical inflammasome activation . Our data suggest that B . abortus LPS is the PAMP responsible to activate the non-canonical pathway . Previous studies suggested that caspase-11 acts as an intracellular LPS receptor [17] . However , recent study demonstrated that GBPs have a notable function mediating LPS interaction with caspase-11 [20] . Hence , we asked whether GBPs are important to activation of the non-canonical caspase-11 inflammasome also in response to purified B . abortus LPS . To test that , we transfected BMDMs primed with PAM3CSK from C57BL/6 , Gbp2-/- and Gbpchr3-/- mice with B . abortus LPS using FuGENEHD and evaluated propidium iodide uptake in real time during 8 h of infection . We observed that C57BL/6 and Gbp2-/- BMDMs were able to form pores in response to B . abortus LPS whereas Gbpchr3-/- BMDM failed to form pores in response to bacterial LPS ( Fig 5A–5C ) . Moreover , we investigated whether GBPs on mouse chromosome 3 were crucial to caspase-11 activation also in response to B . abortus LPS . We previously primed C57BL/6 and Gbpchr3-/- BMDMs with PAM3CSK during 6 hours . Then , we pretreated these BMDMs with biotin-labeled caspase inhibitor ( Biotin-VAD-FMK ) and after 15 min transfected them with B . abortus LPS . After 17 h , cells lysates were submitted to pulldown with streptavidin-coupled beads . To observe caspase-11 activation levels , the pulldown product was subjected to western blotting using specific Ab against caspase-11 . As we previously observed to whole bacteria , C57BL/6 BMDMs were able to activate caspase-11 in response to purified B . abortus LPS whereas Gbpchr3-deficient BMDMs failed to activate caspase-11 ( Fig 5D ) . To investigate which GBPs contained on mouse chromosome 3 ( GBPchr3 ) would be involved in LPS sensing by caspase-11 , we first performed qPCR analysis of GBP1 , GBP2 , GBP3 , GBP5 and GBP7 expression on macrophages transfected with Brucella LPS . We observed that GBP2 , GBP3 , GBP5 and to less extent GBP7 had increased mRNA transcripts in macrophages transfected with bacterial LPS compared to cells transfected with FuGENEHD alone ( S2 Fig ) . We then treated wild-type BMDMs with GBP1 , GBP3 , GBP5 and GBP7 siRNA and transfected them with B . abortus LPS and measured IL-1β and LDH release . As shown in Fig 6A and 6C , only GBP5 siRNA treated cells reduced IL-1β secretion and LDH release when compared to other knockdowned GBPs . Simultaneously , we also performed similar experiments with GBP2 and GBPchr3 KO macrophages and these experiments demonstrated that GBP2 plays no role in IL-1β secretion and LDH release as a result of Brucella LPS recognition by caspase-11 ( Fig 6B and 6D ) . Collectively , our data suggest that GBPs on mouse chromosome 3 , more specifically GBP5 , mediates caspase-11 activation and consequently triggers non-canonical inflammasome in response to purified B . abortus LPS . Recently , the identification of a protein termed Gasdermin-D ( GSDMD ) contributed to the elucidation of the mechanism of pore formation involved in pyroptosis [23 , 24 , 28 , 54–56] . Gasdermin-D acts as a substrate of caspase-11 , and once it is cleaved , the N-terminal fragment is recruited to the cell membrane forming pores . Thus , as we observed that B . abortus is able to trigger pyroptosis in macrophages , we assessed the requirement of GSDMD for pore formation in response to B . abortus . First , BMDMs obtained from C57BL/6 , Casp11-/- , Gsdmd-/- and Casp1/11-/- mice were left uninfected or infected with B . abortus . By evaluating propidium iodide uptake in real time during 8 h of infection , we found that BMDMs from C57BL/6 mice formed pores whereas BMDMs from Gsdmd-/- , Casp11-/- and Casp1/11-/- mice failed to form pores in response to B . abortus ( Fig 7B ) . As expected , non-infected cells were unable to form pores ( Fig 7A ) . It suggests that GSDMD is important to pore formation in response to B . abortus . Once the GSDMD pore is formed , osmotic pressure leads to water influx inducing cell swelling and consequent membrane disruption , releasing cytosolic content as LDH . Thus , to further evaluate GSDMD role during pyroptosis induced by B . abortus , we quantified the release of LDH in cell culture supernatants . BMDMs obtained from C57BL/6 , Casp11-/- , Gsdmd-/- and Casp1/11-/- mice were infected with B . abortus and after 8 h LDH was measured in supernatants . We found that B . abortus triggered higher percentage of LDH release in C57BL/6 BMDMs compared to Gsdmd-/- , Casp11-/- and Casp1/11-/- cells ( Fig 7C ) . These data support the pore formation assay results , suggesting that GSDMD and caspase-11 are essential to pyroptosis in response to B . abortus . Active caspase-11 cleaves GSDMD to separate the regulatory p20 subunit from the cytotoxic p30 subunit , which oligomerizes into the lipid cell membrane forming a pore that culminates in a pyroptosis event . As we observed that B . abortus triggers pyroptosis dependent of GSDMD , we asked whether caspase-11 was able to cleave GSDMD in response to B . abortus infection . We infected BMDMs from C57BL/6 , Casp11-/- , Gsdmd-/- , Nlrp3-/- and Casp1/11-/- mice with B . abortus and after 17 h , supernatant was harvested and submitted to western blotting . We found that C57BL/6 and Nlrp3-/- BMDMs were fully able to cleave GSDMD in its active p30 subunit ( Fig 7D ) . However , in Casp11-/- and Casp1/11-/- cells GSDMD cleavage was abrogated . As expected , Gsdmd-/- BMDMs did not express GSDMD protein . Thus , this result indicates that caspase-11 is pivotal to GSDMD cleavage in response to B . abortus . In addition , NLRP3 was dispensable to GSDMD cleavage . Next , we investigated the role of GSDMD in IL-1β secretion and caspase-1 activation . We infected BMDMs from C57BL/6 , Gsdmd-/- , Casp11-/- and Casp1/11-/- mice with B . abortus for 17 hours . The secretion of IL-1β and caspase-1 activation was evaluated in the supernatant of these cells . We observed that Gsdmd-deficient BMDMs further resembled Casp11-deficient cells presenting reduced levels of IL-1β secretion and the active form of caspase-1 ( p20 ) in comparison to C57BL/6 macrophages ( Fig 7E and 7F ) . As expected , Casp1/11-/- BMDMs did not secrete IL-1β or express caspase-1 . As indicated in the literature , GSDMD pores allow the efflux of ions such as potassium as well as limited secretion of small cytosolic proteins that fit through these pores , such as IL-1β [27] . Despite the wide variety of stimuli that trigger NLRP3 ( e . g . , reactive oxygen species , release of oxidized mitochondrial DNA , lysosomal cathepsins and bacterial RNA ) potassium efflux has emerged as a point of convergence essential to NLRP3 inflammasome activation [30–35] . Thus , we decided to investigate the requirement of potassium efflux for NLRP3 activation in response to B . abortus . We submitted BMDMs from C57BL/6 , Gsdmd-/- , Casp11-/- and Casp1/11-/- mice to a medium containing high K+ concentration and after 1 h , cells were infected with B . abortus . After 17 h , secretion of IL-1β in the supernatant was evaluated . We observed a significant reduction in the secretion of IL-1β in C57BL/6 , Casp11-/- and Gsdmd-/- BMDMs when cells were incubated in high-K+ media ( Fig 7G ) . As expected , IL-1β was not processed in BMDMs from Casp1/11-/- mice . Increased extracellular [K+] prevented NLRP3 activation , suggesting a great importance of potassium efflux to inflammasome activation in response to B . abortus . Next , we tested whether GSDMD and caspase-11 were required for potassium efflux in response to B . abortus . We found that intracellular potassium concentration decreased inside C57BL/6 BMDMs in response to B . abortus infection whereas in Casp11-/- , Gsdmd-/- and Casp1/11-/- macrophages it remained at similar levels as observed in the non-infected controls ( Fig 7H ) . In summary , these data suggest that pyroptosis which is dependent on caspase-11 and GSDMD are central to potassium efflux and , consequently , to NLRP3 inflammasome activation in response to B . abortus . Since GSDMD triggered pyroptosis was associated to bacterial clearance [36] , we investigated the role of GSDMD in controlling B . abortus infection . We infected C57BL/6 , Gsdmd-/- and Casp11-/- mice intraperitoneally with B . abortus and after 72h , 1 and 2 weeks , bacterial CFU in spleens were evaluated . Bacterial load recovery was higher in Gsdmd-/- and Casp11-/- mice in comparison to C57BL/6 at 1 and 2 weeks postinfection ( Fig 8A ) . However , no difference in bacterial counts was observed at 72h following Brucella infection . Further , we measured Brucella intracellular replication in C57BL/6 , Gsdmd-/- and Casp11-/- macrophages at 2 , 24 and 48 hrs in vitro . No difference in intracellular CFU was detected among macrophages from tested mouse groups ( S3 Fig ) . This finding suggests that lack of caspase-11 and GSDMD does not affect Brucella entry in macrophages at the initial colonization stage . Additionally , we infected C57BL/6 , Casp11-/- , Casp1-/-Casp11Tg , Casp1/11-/- and Nlrp3-/- mice intraperitoneally with B . abortus . After 2 weeks of infection , bacterial CFU were determined from spleen homogenate . Casp1-/-Casp11Tg and Nlrp3-/- were as resistant as C57BL/6 mice ( S4 Fig ) . In contrast , bacterial loads were approximately 1 log higher in Casp11-/- and Casp1/11-/- mice compared with C57BL/6 animals . These results demonstrate that GSDMD and caspase-11 deficiency but not caspase-1 are important to B . abortus control in mice . As we observed that Gsdmd-/- mice are more susceptible and that GSDMD is involved in pyroptosis in response to B . abortus , we decided to investigate the mechanism involved in the susceptibility of GSDMD mice . To further evaluate that , we assessed whether GSDMD- and caspase-11- deficient mice have a deficiency in the recruitment of immune cell populations . C57BL/6 , Casp11-/- and Gsdmd-/- mice were infected with B . abortus and after 2 weeks we analyzed the numbers of neutrophils , macrophages and dendritic cells by flow cytometry . We observed higher numbers of neutrophils , dendritic cells and macrophages in the spleen of C57BL/6 mice infected with B . abortus compared to non-infected mice ( Fig 8B–8D ) . However , when we analyzed these cells populations in the spleens of Gsdmd-/- and Casp11-/- mice infected with B . abortus , we observed a reduction in numbers of neutrophils , dendritic cells and macrophages compared to C57BL/6 mice . Additionally , we submitted splenic homogenates from C57BL/6 , Casp11-/- and Gsdmd-/- mice infected with B . abortus to a myeloperoxidase ( MPO ) activity assay and measurement of KC levels to corroborate whether Gsdmd- and Casp11- deficient mice showed less neutrophil recruitment . We observed MPO reduced activity ( Fig 8E ) and diminished KC levels ( S5 Fig ) in Gsdmd-/- and Casp11-/- splenic homogenates from mice infected with B . abortus compared to homogenates from C57BL/6 mice . To confirm this deficiency in neutrophil recruitment , we performed confocal microscopy analysis ex vivo of mouse spleens 72 h after B . abortus infection . Clearly , we observed a reduced influx of neutrophils in Gsdmd-/- and Casp11-/- spleens labeled with anti-Ly6G antibody when compared to wild-type animals ( Fig 8F ) . These findings support the hypothesis that GSDMD and caspase-11 play a role in neutrophil recruitment in response to B . abortus . To determine whether these neutrophils are activated , we measured CD62L surface expression levels in Gsdmd-/- and Casp11-/- mice by flow cytometry , a L-selectin marker of neutrophil activation . The levels of CD62L on Ly6G+ cells were higher in Gsdmd-/- and Casp11-/- infected animals compared to C57BL/6 , what is related to less activated neutrophils ( Fig 8G ) . Down-regulation of CD62L surface expression in neutrophils is characteristic of cell activation [57] . Additionally , we measured the number of IL-17 expressing Ly6G+ cells in mouse spleens . Two-weeks post-infection , Gsdmd-/- and Casp11-/- animals showed reduced production of IL-17 within the Ly6G+ cell population compared to C57BL/6 animals ( Fig 8H ) . To determine the role of neutrophils in the control of Brucella infection , we treated mice with anti-Ly6G antibody for one week . Depletion of neutrophils in wild-type animals infected with Brucella renders mice more susceptible to bacterial replication in vivo ( Fig 8I and S6 Fig ) . Taken together , these data suggest that caspase-11 and GSDMD play a role in B . abortus infection restriction in mice and mediate neutrophil , macrophage and dendritic cell recruitment and activation .
Lipopolysaccharides ( LPS ) of Gram-negative bacteria are the major component of its outer membrane and crucial to the recognition of bacteria by immune cells [58] . They are recognized by TLR4 , drive the induction of proinflammatory cytokines such as tumor necrosis factor ( TNF-α ) [59] and are great inductors of septic shock [58] . However , pathogenic bacteria developed strategies to escape the recognition by the immune system to establish an infection inside the host . One of these strategies is the modification of its LPS to avoid effective recognition by TLR4 [60] . B . abortus is an example among Gram-negative bacteria that contains a low immunostimulatory LPS with long-chain fatty acid , being an important virulence factor [61–63] . In that context , caspase-11 arises as a second barrier for LPS recognition acting as an intracellular receptor to promote cytoplasmic surveillance [15–17] . Once activated , it leads to pyroptosis and NLRP3 inflammasome activation and consequent caspase-1 activation and proinflammatory cytokines release , being critical to innate immunity against Gram-negative bacteria [13 , 15 , 16 , 18] . Therefore , in this study , we investigated whether B . abortus were able to activate this non-canonical caspase-11 inflammasome . Here , we demonstrated that caspase-11 is important to caspase-1 activation and IL-1β and IL-1α secretion in response to B . abortus . We also evaluate if B . abortus LPS was the PAMP responsible for activation of the non-canonical inflammasome . Surprisingly , we observed that purified B . abortus LPS was sufficient to drive caspase-11 non-canonical inflammasome activation . Although B . abortus LPS escapes cell surface surveillance by TLR4 , it cannot escape caspase-11 cytoplasmic control . This is distinct from other bacteria , such as Francisella novicida , that modify their LPS , and escape immunosurveillance by both TLR4 and caspase-11 [15] . Hence , the caspase-11 pathway seems to be important to control B . abortus infection . The recognition of LPS by caspase-11 occurs when this molecule is hexa-acylated [16] . B . abortus LPS contains long-chain fatty acid , nevertheless it is hexa-acylated [64] . Moreover , it is already reported that Legionella pneumophila , whose LPS is hexa-acylated with long-chain fatty acid , activates the non-canonical inflammasome [65] , likewise we observed here for B . abortus . Even though we used in this study E . coli LPS primed-macrophages to show caspase-11 activation and pyroptosis induced by B . abortus , unprimed cells also showed similar phenotype . However , once these cells are primed prior to the moment of infection , inflammasome proteins are already highly expressed , cells are synchronized and ready to respond to a second signal , thus inducing higher levels of pore formation and caspase-11 activation compared to unprimed cells . Regarding macrophages transfected with Brucella LPS , PAM3CSK priming was required to activate the caspase-11/pyroptosis pathway . This fact makes sense , since during infection other Brucella PAMPs such as lipoproteins may deliver the first signal to activate the cell and when bacterial LPS is release into the cytoplasm caspase-11 is ready to recognize it . Pilla et al . suggested that mouse chromosome 3 GBPs possibly act in collaboration with caspase-11 in the recognition of bacterial LPS with structural differences in the lipid A moiety of L . pneumophila [21] . Furthermore , Santos et al . , confirmed that GBPchr3 proteins facilitate the interaction of LPS with caspase-11 [20] . In addition , previous studies including one from our group demonstrated that GBPs can associate with pathogen-containing vacuoles contributing to its lysis and resulting in the release of bacterial PAMPs in the cytoplasm [22 , 66] . Here we observed that GBPchr3 proteins are required for caspase-11 activation and pyroptosis upon macrophage infection with whole B . abortus or transfected with its purified LPS . Accordingly , our data support the idea that GBPs contribute to BCV lysis , as previously shown by our group , but also these molecules can contribute to the recognition of bacterial LPS by caspase-11 . Additionally , Santos et al . showed that the role of Gbpchr3 proteins mediating interaction of LPS with caspase-11 are especially observed when LPS is incorporated within liposomal membranes [20] . Indeed , here we used FuGENEHD reagent in the transfections which incorporates LPS in liposomal vesicle which mimics the LPS-containing membranes . Additionally , to determine which GBP from the mouse chromosome 3 would be involved in caspase-11 sensing of Brucella LPS , we knocked down GBP1 , GBP3 , GBP5 , GBP7 by siRNA in C57BL/6 macrophages and used GBP2 KO cells . Lack of GBP5 expression but not other GBPs resulted in reduced IL-1β secretion and LDH release in macrophages transfected with Brucella LPS . These findings suggest that GBP5 is the molecule responsible for the phenotype observed in GBPchr3 KO mice related to caspase-11 recognition of Brucella LPS . More recently , our research group identified that miR-21a-5p led to downregulation of GBP5 expression in macrophages infected with Brucella and increased bacterial counts in macrophages [67] . This study highlights the importance of GBP5 regulation by a miRNA in macrophage susceptibility to Brucella infection . In the last few years , great progress in comprehension of the pyroptosis mechanism was achieved . Studies demonstrated that once caspase-11 is activated , it cleaves GSDMD into two domains: a C-terminal p20 domain and an N-terminal p30 domain which oligomerizes and inserts into the membrane forming a pore [23 , 24 , 27 , 28] . Since water can enter into cells through these pores , an osmotic imbalance is created leading to cell death [27] . In the case of Brucella , previous reports established that smooth virulent Brucella inhibit macrophage cell death whereas rough attenuated strain induces apoptosis via caspase-2 activation [68–71] . In contrast , another study observed that smooth B . melitensis induced apoptosis in Raw264 . 7 macrophage cell lines via ROS production [72] . Additionally , several reports have observed that B . abortus smooth strain 2308 induced apoptotic cell death in dendritic cells , astrocytes and T lymphocytes [73–75] . In our study , we observed pore formation and confirmed cell death using LDH release assay suggesting that B . abortus triggers caspase-11/GSDMD-dependent pyroptosis . Here , we infected BMDMs using opsonized B . abortus in order to increase phagocytosis and synchronize the infection , a different protocol used by other Brucella investigators . Notably , this strategy is the one which better mimics the in vivo infection and has been extensively used in other studies involving other pathogens and pyroptosis [76–80] . Hence , it may explain these discrepancies observed in our study in comparison to previous reports . More recently , Lacey et al . studying the role of inflammasomes in Brucella-induced arthritis concluded that the smooth Brucella strain induces pyroptosis in macrophages via caspase-1/caspase-11 pathway , confirming our results [81] . Furthermore , the pyroptosis event also seems to be strongly related to restricting infection in vivo . We observed that mice deficient in caspase-11 and GSDMD that are involved in pyroptosis are more susceptible to Brucella infection compared to wild-type animals , suggesting that B . abortus triggers pyroptosis and this event is important to control infection . Recently others reported that pyroptosis leads to secretion of molecules such as IL-1β , IL-1α and eicosanoids which recruit neutrophils to the site of infection promoting phagocytosis of infected cells and contributing to restricting infection [29 , 36] . Indeed , here we observed lower neutrophil , macrophage and dendritic cell recruitment in the spleen of Casp11-/- and Gsdmd-/- mice infected with B . abortus . We hypothesize that this cell recruitment and activation deficiency could be one of the mechanisms to explain the increased bacterial burden observed in Casp11-/- and Gsdmd-/- mice in response to this bacterium . To confirm that , we depleted neutrophils from infected wild-type animals and our results demonstrated that neutrophil depletion enhanced mouse susceptibility to Brucella infection . Therefore , we speculate that caspase-11/GSDMD-dependent pyroptosis contributes to immune cell recruitment and activation in response to B . abortus and this process may promote infection control in mice , although formal validation is still required . Additionally , in a previous study from our group we have shown that lack of IL-1R renders mice more susceptible to Brucella infection [52] . So , reduced production of IL-1β in Casp11-/- and Gsdmd-/- mice is another possible mechanism to enhance susceptibility to infection . IL-1α release has also been related to neutrophil recruitment and infection control in response to other bacteria such as L . pneumophila [82] . However , although we observed here that Casp11-/- BMDMs released reduced IL-1α levels , IL-1α-deficient mice did not show increased bacterial load after 2 weeks of infection when compared to wild-type animals in response to B . abortus ( S7 Fig ) . Thus , IL-1α does not seem to be linked to infection control in response to B . abortus . In summary , caspase-11 and GSDMD KO susceptibility to Brucella is triggered by a multifaceted inflammatory response against this bacterial infection . Overall , our results lead to a model in which B . abortus is phagocytized by macrophages and establishes its BCV ( Brucella containing vacuole ) to replicate . GBPchr3 proteins , mainly GBP5 , contributes to BCV lysis and recognition of B . abortus LPS by caspase-11 leading to cell activation . Once activated , caspase-11 cleaves GSDMD into its p20 and p30 forms . Cleaved p30 GSDMD subunit drives pyroptosis promoting K+ efflux which contributes to NLRP3 inflammasome activation leading caspase-1 activation and IL-1β secretion . Furthermore , the pyroptosis event possibly contributes to proinflammatory molecule secretion that drives neutrophil , dendritic cell and macrophage recruitment and activation , which participate to restrict B . abortus infection in mice ( Fig 9 ) . The results of this study provide relevant information to the elucidation of a pathway of bacterial sensing involved in the recognition of B . abortus LPS and potential mechanisms of host protection against this stealthy pathogen . Furthermore , these findings advance in the comprehension of bacterial pathogenesis and contribute to the future development of drugs or vaccines to control brucellosis .
Brucella abortus strain 2308 was obtained from our laboratory collection . The ΔvirB2 B . abortus mutant strain used in this study was obtained by allelic exchange of the virB2 gene , generating a polar deletion of virB2 and it was kindly provided by Dr . Renato de Lima Santos from the Federal University of Minas Gerais ( UFMG ) , Brazil [83] . All bacteria were grown in Brucella broth medium ( BD Pharmingen , San Diego , CA ) for 1 d at 37°C under constant agitation . The culture OD at 600 nm was measured in a spectrophotometer to determine the bacterial number in the solution . This study was carried out in strict accordance with the Brazilian laws 6638 and 9605 in Animal Experimentation . The protocol was approved by the Committee on the Ethics of Animal Experiments of the Federal University of Minas Gerais ( Permit Number: CETEA #128/2014 ) . Wild-type C57BL/6 mice were purchased from the Federal University of Minas Gerais ( UFMG ) . Nlrp3-/- and Casp1/11-/- were described previously and backcrossed to C57BL/6 mice for at least eight generations [3 , 84] . Casp11-/- , Gsdmd-/- , Gbp2-/- and Gbpchr3-/- mice were generated in the C57BL/6 background [13 , 23 , 85 , 86] . Casp1−/−Casp-11Tg mice are Casp1/11−/− mice expressing a transgene encoding a functional copy of the caspase-11 allele as previously described [13] . The animals were maintained at UFMG and used at 6–9 wk of age . Macrophages were derived from bone marrow of indicated mice in L929 cell–conditioned medium as previously described [80] . Briefly , bone marrow cells were harvested from femurs and differentiated with DMEM ( Life Technologies , Carlsbad , CA ) containing 20% fetal bovine serum ( Life Technologies , Carlsbad , CA ) and 30% L-929 cell-conditioned medium ( LCCM ) , 15 mM Hepes ( Life Technologies , Carlsbad , CA ) and 100 U/ml penicillin-streptomycin ( Life Technologies , Carlsbad , CA ) at 37°C with 5% CO2 [80] . BMDMs were seeded at 5 x 105 cells/well in 24-well plates and cultivated in DMEM supplemented with 1% FBS and 15 mM Hepes . BMDMs were seeded into 24-well plates ( 5 × 105 cells/well ) . The cells were primed with PAM3CSK ( 1 μg/ml ) for 6 h . Two solutions were made to perform the B . abortus LPS transfection one containing DMEM medium without FBS and with FuGENEHD ( Promega , Madison , USA ) ; and other containing DMEM medium without FBS and with B . abortus LPS ( kindly provided by Dr . Ignacio Moriyón at Universidad de Navarra , Pamplona , Spain ) . These solutions were mixed and kept for 15 min at room temperature before the addition to the cells . After 17 h of transfection , supernatant and lysates were collected to be submitted to Western blotting and ELISA . Pore formation in BMDMs was determined by quantifying propidium iodide uptake as previously described [76] . BMDMs were seeded into black 96-well plates ( 1 × 105 cells/well ) and pre-stimulated with E . coli LPS ( 1 μg/ml ) or PAM3CSK ( 500 ng/ml ) during 4 or 6 h , respectively . The cells were submitted to RPMI 1640 media lacking phenol red with 15 mM HEPES and 0 . 38 g/l NaHCO3 supplemented with 10% ( v/v ) FBS and 6 μg/ml propidium iodide . BMDMs were immediately infected or transfected . Infections were performed with Brucella abortus wild-type at an MOI of 100 for 8 h . Transfections with B . abortus LPS were performed using FuGENEHD ( Promega , Madison , USA ) as described above and propidium iodide uptake was measured at 24 h . Throughout infection/transfection , the plates were incubated at 37°C in a FlexStation 3 microplate reader ( Molecular Devices , Sunnyvale , CA ) , and propidium iodide fluorescence was measured every 1 h . During the infections , bacteria were opsonized with a mouse polyclonal Ab ( anti-B . abortus , 1:1000 dilution ) in order to ensure greater efficiency of bacterial phagocytosis . This polyclonal Ab was generated by injecting 1x106 heat-killed bacteria/mouse . Animals were injected three times during a 15-d interval; then , the serum of each mouse was tested for the presence of the specific Ab and stored at −80°C . BMDMs were seeded into 24-well plates ( 5 × 105 cells/well ) and infected with B . abortus at an MOI of 100 . Infections were performed in DMEM media lacking phenol red . After 8 h of infection , supernatants were harvested for analysis of lactate dehydrogenase ( LDH ) release by dying cells . Total LDH was determined by lysing the cultures with Triton X-100 . LDH was quantified using the CytoTox 96 LDH-release kit ( Promega , Madison , WI ) , according to the manufacturer’s instructions . BMDMs were seeded into 6-well plates ( 1 × 107 cells/well ) . The media of BMDMs were replenished with fresh media containing 20 μM biotin-VAD-FMK ( Enzo ) , a pan-caspase inhibitor , 15 min before infection . BMDMs were infected with B . abortus at an MOI of 100 or transfected with B . abortus LPS as described above . Infected/transfected BMDMs were lysed in RIPA buffer ( 10 mM Tris-HCl ( pH 7 . 4 ) , 1 mM EDTA , 150 mM NaCl , 1% Nonidet P-40 , 1% ( w/v ) sodium deoxycholate and 0 . 1% ( w/v ) SDS ) supplemented with a protease inhibitor cocktail ( Thermo-Fisher ) . Cleared lysates were incubated overnight with streptavidin–agarose beads ( Novex ) and thoroughly rinsed with RIPA buffer . Bound proteins were eluted by re-suspension in Laemmli sample buffer , boiled for 5 min and subjected to SDS-PAGE analysis and Western blotting as described above . RNA was extracted from BMDMs with TRIzol reagent ( Invitrogen , Carlsbad , CA ) to isolate total RNA in accordance with the manufacturer’s instructions . Reverse transcription of 2 μg of total RNA was performed using Illustra Ready-To-Go RT-PCR Beads ( GE Healthcare , Chicago , IL ) according to the manufacturer’s directions . Real-time RT-PCR was performed using 23 SYBR Green PCR master mix ( Applied Biosystems , Foster City , CA ) on a QuantStudio3 real-time PCR instrument ( Applied Biosystems , Foster City , CA ) . The appropriate primers were used to amplify a specific fragment corresponding to specific gene targets as follows: β-actin , forward , 5’- GGCTGTATTCCCCTCCATCG-3’ , reverse , 5’-CCAGTTGGTAACAATGCCATGT-3’; GBP1 , forward , 5’-GAGTACTCTCTGGAAATGGCCTCAGAAA-3’ , reverse , TAGATGAAGGTGCTGCTGAGGAGGACTG-3; GBP2 , forward , 5’-CTGCACTATGTG ACGGAGCTA-3’ , reverse , 5’-CGG AATCGTCTACCCCACTC-3’; GBP3 , forward , 5’-CTGACAGTAAATCTGGAAGCCAT-3’ , reverse , 5’-CCGTCCTGCAAGACGATT CA-3’; GBP5 , forward , 5’-CTGAACTCAGATTTTGTG CAGGA-3’ , reverse , 5’-CATCGACATAAGTCAGCACCAG-3’; GBP7 , forward , 5’-TCCTGTGTGCCTAGTGGAAAA-3’ , reverse , 5’-CAAGCGGTTCATCAAGTAGGAT-3’ . All data are presented as relative expression units after normalization to the β-actin gene , and measurements were conducted in triplicate . BMDMs were previously primed with PAM3CSK ( 500 ng/ml ) and after 6 hours , they were transfected with siRNA from siGENOME SMARTpools ( Dharmacon , Lafayette , CO ) with the GenMute siRNA transfection reagent according to the manufacturer’s instructions ( SignaGen , Rockville , MD ) . siGENOME SMARTpool siRNAs specific for mouse GBP1 ( M-040198010005 , GBP3 ( M-063076-01-0005 ) , GBP5 ( M-054703-01-0005 ) , and GBP7 ( M-061204-01-0005 ) were used in this study . A control siRNA pool was used ( D-001206-14-05 ) . Forty-six hours after siRNA transfection , cells were transfected with B . abortus LPS ( 5 μg/ml ) as described above . After 17h , supernatant was collected to measure IL-1β by ELISA and LDH release using the CytoTox 96 LDH-release kit ( Promega , Madison , WI ) , according to the manufacturer’s instructions . Five mice from each group ( C57BL/6 , Casp11-/- and Gsdmd-/- ) were infected i . p . with 1 × 106 CFU B . abortus virulent strain S2308 and sacrificed at 2 weeks postinfection . Spleen cells were harvested and washed twice with sterile PBS . After washing , the cells were adjusted to 1x106 cells in RPMI medium supplemented with 10% fetal bovine serum , 150 U penicillin G sodium and 150 μg streptomycin sulfate per well in a 96-well plate . After , the cells were centrifuged at 1500 rpm for 7 min at 4°C and washed with PBS containing 1% bovine serum albumin ( PBS/BSA ) . The cells were incubated with anti-CD16/CD32 ( FcBlock ) ( 1:30 diluted in PBS/BSA ) for 20 min at 4°C . The cells were then centrifuged and washed in PBS/BSA and incubated for 20 min at 4°C with a mixture of the following antibodies: rat IgG2a anti-murine F4/80 conjugated to biotin ( clone BM8; 1:200 ) ; rat IgG2b anti-murine CD11b conjugated to APC-Cy7 ( clone M1/70; 1:200 ) ; hamster IgG1 anti-murine CD11c conjugated to FITC ( clone HL3; 1:200 ) ; rat IgG2a anti-murine Ly-6G conjugated to PE ( clone 1A8; 1:200 ) and rat IgG2a anti-murine CD62L conjugated to APC ( clone MEL-14; 1:400 ) . All antibodies were obtained from BD Bioscience . The cells were centrifuged and washed again with PBS/BSA and incubated with streptavidin conjugated to PerCP Cy5 . 5 ( 1:30 ) for 20 min at 4°C . To measure IL-17 , the cells were centrifuged and washed again with PBS/BSA and fixed and permeabilized using BD Cytofix/Cytoperm reagent ( BD Bioscience , San Diego , CA , USA ) according to the manufacturer’s instructions . The cells were then incubated with rat IgG2a anti-murine IL-17 conjugated to PE ( clone eBio 18F10; 1:30; eBioscience ) for 30 min at 4°C . Finally , the cells were washed three times , suspended in PBS buffer and evaluated using Attune Acoustic Focusing equipment ( Life Technologies , Carlsbad , CA , USA ) . The results were analyzed using FloWJo software ( Tree Star , Ashland , OR , USA ) . For cytokine determination , BMDMs were seeded at a density of 5 × 105 cells/well in 24-well plates . BMDMs were infected with B . abortus or virB2 mutant strain at an MOI of 100 or transfected with B . abortus LPS , as described above , for 17h . As a positive control , cells were primed with 1 μg/ml of E . coli LPS ( Sigma-Aldrich , St . Louis , MO , USA ) for 4h and stimulated with 20μM nigericin sodium salt ( Sigma-Aldrich ) for 30 minutes . Supernatants were harvested and cytokines were measured with mouse IL-1β , IL-1α , TNF-α and IL-12 ELISA kits ( R&D systems , Minneapolis , MN ) according to the manufacturer’s instructions . For measurement of KC , five mice from each group ( C57BL/6 , Casp11-/- and Gsdmd-/- ) were infected intraperitoneally with 1 × 106 CFU B . abortus virulent strain S2308 and sacrificed at 2 weeks postinfection . Fragments with approximately 100 mg from the harvested spleens were homogenated in 1 ml of cytokines extraction solution ( Phosphate-Buffered Saline ( PBS ) containing an anti-proteases cocktail ( 0 . 1 mM PMSF , 0 . 1 mM benzethonium chloride , 10 mM EDTA e 20 KI aprotinin A ) and 0 , 05% Tween-20 ) using a tissue homogenator ( T10 basic ULTRA-TURRAX , IKA , Germany ) . Next , homogenates were centrifuged at 10000 rpm for 10 min at 4°C . The supernatants were immediately collected and kept at 80° C to posterior cytokine measurement . KC was measured using ELISA kit ( R&D systems , Minneapolis , MN ) according to the manufacturer’s instructions . BMDMs were seeded at a density of 5 × 105 cells/well in 24-well plates . BMDMs were infected with B . abortus or virB2 mutant strain at an MOI of 100 or transfected with B . abortus LPS , as described above , for 17h . As a positive control , cells were primed with 1 μg/ml of E . coli LPS ( Sigma-Aldrich , St . Louis , MO , USA ) for 4h and stimulated with 20μM nigericin sodium salt ( Sigma-Aldrich ) for 30 minutes . Culture supernatants were collected and cells were lysed with M-PER Mammalian Protein Extraction Reagent ( Thermo Fisher Scientific ) supplemented with 1:100 protease inhibitor mixture ( Sigma-Aldrich ) . Cell lysates and supernatants were subjected to SDS-PAGE analysis and western blotting . The proteins were resuspended in SDS-containing loading buffer , separated on a 15% SDS-PAGE gel , and transferred to nitrocellulose membranes ( Amersham Biosciences , Uppsala , Sweden ) in transfer buffer ( 50mM Tris , 40mM glycine , 10% methanol ) . Membranes were blocked for 1 hour in TBS with 0 . 1% Tween-20 containing 5% nonfat dry milk and incubated overnight with primary antibodies at 4°C . Primary Abs used included a mouse monoclonal against the p20 subunit of caspase-1 ( Adipogen , San Diego , CA , USA ) , a mouse monoclonal against caspase-11 ( Adipogen , San Diego , CA , USA ) and a rat monoclonal against GSDMD ( Genentech , cell line GN20-13 ) , both at a 1:1000 dilution . Loading control blot was performed using mAb anti–β-actin ( Cell Signaling Technology , Danvers , MA ) at a 1:1000 dilution . The membranes were washed three times for 5 min in TBS with 0 . 1% Tween 20 and incubated for 1 h at 25°C with the appropriate HRP-conjugated secondary Ab at a 1:1000 dilution . Immunoreactive bands were visualized using Luminol chemiluminescent HRP substrate ( Millipore ) and analyzed using the ImageQuant TL Software ( GE Healthcare , Buckinghamshire , United Kingdom ) . C57BL/6 , Casp11-/- and Gsdmd-/- mice were infected with B . abortus as previously described , and 3 days post-infection they were inoculated i . v . with a single dose of 8μg of Ly-6G PE antibody ( clone 1A8; 1:200 , BD Bioscience ) to each 20g mice . After 2h , spleens were extracted , and whole organ ex-vivo confocal microscopy analysis was performed using a Nikon A1 confocal system . Three animals per group were analyzed , and images were taken using a 4x objective for ten random fields per mice . The percentage of red fluorescent pixels was analyzed per organ area per field using ImageJ . To increased extracellular [K+] assay , BMDMs were seeded at a density of 5 × 105 cells/well in 24-well . We incubated BMDMs in a medium containing 80 mM KCl 1 h before infection . Then , BMDMs were infected with B . abortus at an MOI of 100 in the same medium for 17 h and IL-1β was measured in the supernatant . Intracellular concentration of K+ was determined by fluorescence emission of Asante Potassium Green-2 ( APG-2 , TEFLabs , Austin , EUA ) . Briefly , BMDMs ( 2 × 104 ) were seeded in black , clear-bottom 96-well plates , infected with B . abortus at an MOI of 100 . After 6 h of infection , cells were incubated with 5 μM APG-2 in RPMI without FBS and phenol red for 30 min . BMDMs were washed with PBS , and the media was replaced with RPMI without phenol red . Four images per well were recorded at 40× magnification with the ImageXpress Micro High-Content Imaging System and processed with MetaXpress High-Content Image Acquisition and Analysis ( Molecular Devices ) . The images were analyzed using ImageJ , and the concentration of intracellular K+ in each cell was calculated as a percentage: MFI540nm ( inquired cell ) / Σ MFI540nm ( control cells ) ×100 . Five mice from each group ( C57BL/6 , Casp11-/- and Gsdmd-/- ) were infected i . p . with 1 × 106 CFU B . abortus virulent strain S2308 and sacrificed at 72 h , 1 or 2 weeks postinfection . For Nlrp3-/- , Casp11-/- , Casp1-/-Casp11Tg , Casp1/11-/- , the bacterial load was evaluated at 2 weeks after infection . The spleens were harvested and macerated in 10 ml saline ( NaCl 0 . 9% ) , serially diluted , and plated in duplicate on Brucella Broth agar . After 3 d of incubation at 37°C , the number of CFU was determined as described previously [46] . To measure intracellular multiplication in macrophages , BMDMs were seeded at a density of 5 × 105 cells/well into 24-well tissue culture plates . Cultures were infected at B . abortus MOI of 10 , followed by incubation at 37°C in a 5% CO2 atmosphere . For CFU determination , the cultures were lysed in sterile water after 2 , 24 , and 48 h of infection . Lysates from each well were diluted in water , plated on Brucella broth ( BB ) agar plates , and incubated for 3 d at 37°C for CFU determination . Neutrophils were depleted by intraperitoneal injection of 100 μg of anti-mouse Ly6G ( clone 1A8 , BioXcell , West Lebanon , NH , USA ) 24 hours before infection i . p . with 1 × 106 CFU B . abortus virulent strain S2308 . The neutrophils depletion was maintained with applications of anti-mouse Ly6G antibodies at intervals of 2 days each dose for 7 days . In these experiments , 100 μg of an isotype control antibody ( IgG from rat serum , Sigma-Aldrich , St . Louis , MO , USA ) was administered as control . After 1 week of infection , mice were sacrificed , spleens were harvested and CFU counting was performed as described above . Neutrophil depletion was confirmed by flow cytometry analysis of spleen cells from depleted and control mice . The neutrophil population was analyzed by staining 1x106 cells for 30 min on 4°C with fluorescent antibodies against Ly6G ( PE , clone 1A8 , BD Biosciences ) . Stained cells were acquired in Attune Flow Cytometer ( Applied Biosystems , Waltham , MA , USA ) and analyzed using FlowJo software ( Tree Star , Ashland , OR , USA ) . Statistical analysis was performed using Prism 5 . 0 software ( GraphPad Software , San Diego , CA ) . The unpaired Student t test was used to compare two groups . One-way ANOVA followed by multiple comparisons according to Tukey procedure was used to compare three or more groups . Unless otherwise stated , data are expressed as the mean ± SD . Differences were considered statistically significant at a p value < 0 . 05 . | Brucella abortus is the causative agent of brucellosis , a zoonotic disease that affects both humans and cattle . In humans , it is characterized by undulant fever and chronic symptoms as arthritis , endocarditis , and meningitis , while in cattle it causes abortion and infertility . Due to its difficult diagnosis and treatment , it leads to severe economic losses and human suffering . Recently , a novel non-canonical inflammasome pathway was described that involves sensing of bacterial LPS by an intracellular receptor termed caspase-11 and leads to pyroptosis and non-canonical NLRP3 inflammasome activation . Here , we show that B . abortus or its purified LPS is able to activate the non-canonical inflammasome . In this process , activated caspase-11 leads to GSDMD-dependent pyroptosis . Moreover , this pathway was dependent of IFN-induced GBP proteins , mainly GBP5 . To analyze the role of caspase-1 , caspase-11 and GSDMD in controlling B . abortus infection , we infected knockout ( KO ) mice for these molecules and we observed that caspase-11 and GSDMD KO animals were more susceptible to infection compared to wild-type animals . Casp11-/- and Gsdmd-/- animals also recruited less immune cells in mouse spleens compared to wild-type animals in response to B . abortus . Thus , caspase-11 and GSDMD are major components of the innate immune system to restrict B . abortus in vivo . This pathway of bacterial sensing by the host immune system is important to future development of drugs and vaccines that may contribute to the control of brucellosis worldwide . | [
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"p... | 2018 | Guanylate-binding protein 5 licenses caspase-11 for Gasdermin-D mediated host resistance to Brucella abortus infection |
Defensins are effectors of the innate immune response with potent antibacterial activity . Their role in antiviral immunity , particularly for non-enveloped viruses , is poorly understood . We recently found that human alpha-defensins inhibit human adenovirus ( HAdV ) by preventing virus uncoating and release of the endosomalytic protein VI during cell entry . Consequently , AdV remains trapped in the endosomal/lysosomal pathway rather than trafficking to the nucleus . To gain insight into the mechanism of defensin-mediated neutralization , we analyzed the specificity of the AdV-defensin interaction . Sensitivity to alpha-defensin neutralization is a common feature of HAdV species A , B1 , B2 , C , and E , whereas species D and F are resistant . Thousands of defensin molecules bind with low micromolar affinity to a sensitive serotype , but only a low level of binding is observed to resistant serotypes . Neutralization is dependent upon a correctly folded defensin molecule , suggesting that specific molecular interactions occur with the virion . CryoEM structural studies and protein sequence analysis led to a hypothesis that neutralization determinants are located in a region spanning the fiber and penton base proteins . This model was supported by infectivity studies using virus chimeras comprised of capsid proteins from sensitive and resistant serotypes . These findings suggest a mechanism in which defensin binding to critical sites on the AdV capsid prevents vertex removal and thereby blocks subsequent steps in uncoating that are required for release of protein VI and endosomalysis during infection . In addition to informing the mechanism of defensin-mediated neutralization of a non-enveloped virus , these studies provide insight into the mechanism of AdV uncoating and suggest new strategies to disrupt this process and inhibit infection .
Defensins are an evolutionarily conserved family of antimicrobial peptides that are an important effector component of the innate immune response . Humans express two classes of defensins , α- and β-defensins . There are six human α-defensins ( HNP1–4 , HD5 , and HD6 ) and multiple β-defensins , which differ in their tissue distribution and expression patterns [1] , [2] . Both α- and β-defensins are small peptides with three intramolecular disulfide bonds and are potent antibacterial agents . There is substantial evidence that a major bactericidal mechanism of defensins is through membrane disruption [3] , and lipid bilayer interactions are facilitated by their amphipathicity and net positive charge . A growing body of evidence suggests that certain defensins are also potent antivirals . For enveloped viruses , direct disruption of the viral lipid envelope bilayer has been proposed as a mechanism for neutralization [4] . In addition , several defensins have been shown to be lectins and to block human immunodeficiency virus and Herpes simplex virus binding to cellular receptors [5]–[7] . Defensins have also been shown to neutralize several non-enveloped viruses , including human adenovirus ( HAdV ) , human papillomavirus ( HPV ) , adeno-associated virus ( AAV ) , and polyomavirus , despite the absence of a lipid target [8]–[14] . We have chosen HAdV as a tractable model system to analyze this process at the molecular level . AdV is a dsDNA virus with an icosahedral capsid composed primarily of 240 trimers of hexon . Each of the twelve icosahedral vertices contains a penton complex comprised of the non-covalently associated fiber and penton base proteins . The capsid is stabilized by proteins IIIa , VI , VIII , and IX . There are 52 serotypes of HAdV divided into 7 species , A–G [15] , [16] . Three additional types ( HAdV-53 , -54 , and -55 ) have also recently been described [17] , [18] . The mode of cell entry is best understood for the HAdV-C serotypes in cultured epithelial cells and is initiated by a high affinity interaction between the distal knob of the fiber and one of several cell surface receptors [19] . Internalization via clathrin-mediated endocytosis is triggered by the interaction between an RGD motif in penton base and cellular integrin co-receptors [20] . Uncoating , which is the removal of the protective protein shell from the viral genome , occurs in a stepwise fashion beginning with dissociation of the fiber from the capsid at or near the cell surface [21] , [22] . Additional uncoating events , including release of the endosomalytic protein VI , occur in the endosome in response to cellular triggers such as acidification [23] . Upon escape from the early endosome , the partially uncoated capsid travels along microtubules and docks at the nuclear pore complex , where the viral genome enters the nucleus [24] . Our previous studies revealed the stage in the virus entry pathway that is blocked by defensins [13] . We found that the α-defensins HNP1 and HD5 significantly inhibit HAdV-5 infection at low micromolar concentrations . Although receptor binding and virus internalization were unaffected , virus escape from the endosome was blocked . Moreover , defensin binding stabilized the virus capsid in thermal denaturation assays . These observations are consistent with a mechanism by which defensins neutralize AdV infection by blocking uncoating and release of the endosomalytic protein VI . We have now extended these studies to determine the specificity of defensin binding to HAdV , to approximate the stoichiometry and affinity of this interaction , and to identify the neutralization determinants on the virus capsid . These studies not only contribute to an understanding of the mechanism of defensin-mediated neutralization of non-enveloped virus infection but also provide insight into the process of HAdV uncoating during infection .
In our previous studies we showed that a small subset of HAdVs , including HAdV-5 , -12 , and -35 ( species C , A , and B2 , respectively ) are neutralized by α-defensins [13]; however , the underlying molecular mechanisms were not delineated . To determine whether sensitivity to α-defensins is a general property of HAdVs , serotypes representative of HAdV species A–F were tested for infectivity in the presence of 15 µM HD5 or HNP1 ( Figure 1 ) . Wild type HAdVs rather than vectors were used for these studies , and infectivity was assessed by staining for hexon production . We found that each of HAdV types belonging to species A , B1 , B2 , C , and E is sensitive to HD5 . Strikingly , the HAdV-D and F serotypes are completely resistant to HD5-mediated neutralization and , in most cases , infection is actually enhanced . Serotypes sensitive to HD5 are also generally sensitive to HNP1 , although only modest inhibition was observed for HAdVs-3 , -12 , -14 , and -16 . One exception is HAdV-4 ( species E ) , which is moderately sensitive to HD5 but resistant to HNP1 . None of the tested serotypes is sensitive to the β-defensin HBD2 ( data not shown ) . These studies indicate that sensitivity to α-defensins is species specific . In addition , particular HAdV serotypes are not equally sensitive to all defensins , indicating defensin sequence specificity as well . Neutralization of HAdV by α-defensins is dependent upon binding to the virus capsid , which can be disrupted in the presence of elevated concentrations of sodium chloride [13] . To perform a more quantitative assessment of this interaction , increasing concentrations of HD5 were incubated with Ad5 . eGFP to allow binding , and the virus/HD5 complex was then separated from unbound HD5 on a nycodenz gradient . Bound defensin was visualized after SDS-PAGE using a sensitive fluorescent total protein stain and quantified against a standard curve . These experiments showed that defensin binding to the HAdV-5 capsid is saturable , suggesting specificity , and that at saturation approximately 2750 HD5 molecules are bound to each virus particle ( 95% confidence interval = 1603–3919 HD5 molecules ) ( Figure 2A ) . In addition , the KD of this interaction is approximately 14 . 5 µM ( 95% confidence interval = 2 . 8–26 . 2 µM ) , which correlates reasonably well with the IC50 of HD5 for HAdV-5 infection ( 3–4 µM ) [13] . We assessed HD5 binding to additional serotypes after incubation with 20 µM HD5 ( Figure 2B ) . The sensitive serotype HAdV-7p bound 69 . 3±15 . 9% of the amount of HD5 bound to HAdV-5 in parallel samples; whereas , the corresponding values for the resistant serotypes HAdV-19c , -25p , and -51p were 32 . 5±7 . 5% , 3 . 3±5 . 8% , and 24 . 6±12 . 0% , respectively . These studies demonstrate reduced binding of HD5 to resistant serotypes , suggesting that binding of α-defensins to species-specific features on the HAdV capsid correlates with neutralization . To gain further insight into the defensin-HAdV interaction , we assessed the requirement for two conserved structural elements on the anti-AdV activity of HD5 . All defensins have three disulfide bonds ( Figure 3A ) . In addition , all α-defensins possess a conserved salt bridge , such as that comprised of glutamic acid 14 ( E14 ) and arginine 6 ( R6 ) in HD5 , which has been shown to increase defensin protease resistance [25] , [26] . The antibacterial properties of defensins , which are dependent upon protein-lipid interactions , are not uniformly conformation dependent [27]–[29] . In some cases , incorrectly folded analogs are more potent antibacterial agents than the correctly folded defensin molecule . In contrast , defensin-related chemokine activity , which relies on protein-protein interactions , is dependent on defensin conformation [28] . We hypothesized that the defensin-capsid interaction for sensitive serotypes would likely be dependent upon defensin conformation , as this would be more typical for protein-protein interactions . To test this hypothesis , HD5 derivatives in which the six cysteines were replaced with L-α-aminobutyric acid ( HD5-Abu ) , to prevent the formation of disulfide bonds , or containing a substitution of glutamine for glutamic acid 14 ( HD5-E14Q ) , to disrupt the conserved salt bridge , were tested for their activity against Ad5 . eGFP ( Figure 3B ) . Disruption of the R6-E14 salt bridge had no effect on antiviral activity . In contrast , HD5-Abu failed to inhibit Ad5 . eGFP infection , and no detectable binding of HD5-Abu was observed upon incubation at 20 µM with HAdV-5 ( data not shown ) . Therefore , HAdV neutralization does not merely require an amphipathic molecule with a net positive charge . Rather , specific interactions mediated by the correctly folded α-defensin molecule are required . Previously we observed that HD5 enhances binding of HAdV-5 to cells despite an almost complete block to productive infection [13] . In order to determine the receptor-dependence of this effect , we pre-incubated cells with recombinant fiber knob from HAdV-5 ( 5FK ) to block receptor ( CAR ) interactions and measured cell binding of fluorescently labeled HAdV-5 that was pre-incubated with or without HD5 or HD5-Abu ( Figure 3C ) . Cells incubated with fiber knob from HAdV-16 ( 16FK ) , which binds CD46 , served as a control . We observed that virus binding to cells was reduced 5 . 2-fold in the presence of 5FK compared to 16FK . This confirms the receptor-dependence of the normal interaction of HAdV-5 with cells . Pre-incubation with HD5 increased virus binding to cells . In this case the presence of 5FK reduced binding 1 . 6-fold compared to 16FK , indicating some receptor-dependence of the virus/cell interaction even in the presence of HD5 . Virus pre-incubated with HD5-Abu was equivalent to virus alone , consistent with the failure of HD5-Abu to bind to virus . These studies confirm that HD5 binding to HAdV-5 does not completely block the interaction with CAR receptor . To obtain structural insight into the mechanism of α-defensin-mediated neutralization of HAdV infection , we studied a complex of Ad5 . F35 ( Ad35F ) and HD5 by cryoelectron microscopy ( cryoEM ) . This chimeric virus construct was chosen because of its short fiber and the availability of a cryoEM structure of Ad5 . F35 in the absence of defensin for comparison [30] , [31] . The sensitivity of Ad5 . F35 to HD5 is comparable to that of HAdV-5 and HAdV-35 ( data not shown ) . Ad5 . F35 was incubated with a saturating concentration of HD5 ( 20 µM ) then applied to grids and flash frozen for cryoEM . A dataset of 2 , 611 cryoEM particle images of the Ad5 . F35+HD5 complex was collected and processed as performed earlier for Ad5 . F35 [31] . The resolution of the icosahedral portion of the Ad5 . F35+HD5 reconstruction is estimated as 12 Å by the FSC 0 . 5 threshold criterion , compared to 6 . 9 Å for the Ad5 . F35 reconstruction . Both cryoEM structures are shown filtered to 12 Å resolution in Figure 4A . The most noticeable difference between the two structures is the presence of more density on top of penton base and around the fiber shaft in the Ad5 . F35+HD5 structure . In addition , while the fiber knob is visible in the Ad5 . F35 structure , it is only weakly reconstructed in the Ad5 . F35+HD5 structure ( Figure 4A inset ) . In order to identify the binding regions for HD5 on the surface of Ad5 . F35 , we performed a difference map analysis using the available crystal structure of the HAdV-5 hexon ( PDB 1P30 ) [32] and the co-crystal structure of HAdV-2 penton base bound to a peptide derived from the N-terminus of fiber ( PDB 1X9T ) [33] . Difference mapping with the crystal structures was preferable to direct subtraction of the Ad5 . F35 structure from the Ad5 . F35+HD5 structure because of ringing in the cryoEM density maps due to incomplete correction for the contrast transfer function of the microscope . There are multiple flexible loops with a total of 51 residues per monomer at the top of hexon ( hexon towers ) that are missing from the crystal structure . Density for these loops ( yellow ) is clearly visible in the Ad5 . F35 difference map and nearly identical for each of the four unique hexons within the icosahedral asymmetric unit ( Figure 4B , left panel ) . The Ad5 . F35+HD5 difference map shows density ( red ) on the hexon towers that is attributable to both HD5 and the missing hexon loops ( Figure 4B , middle and right panels ) . This density is variable for each unique hexon and greatest above the peripentonal hexon ( position 1 ) . The variability in the Ad5 . F35+HD5 difference map suggests that HD5 interacts with and induces additional conformational heterogeneity in the flexible loops of hexon . HD5 difference density is also found within the central depression of the hexon trimers in the same location identified for binding of Factor X [34] , [35] . This central depression contains multiple negatively charged residues that are likely to form a binding site for the positively charged HD5 molecule . The difference map analysis reveals multiple binding sites for HD5 on the penton complex ( penton base and fiber ) . The Ad5 . F35 difference map clearly reveals the flexible RGD loop of penton base ( 78 residues ) as well as the shaft and knob of fiber ( yellow ) , which are missing from the penton base/fiber peptide co-crystal structure ( Figure 4C , left panel ) . The Ad5 . F35+HD5 difference map shows significant additional density attributable to HD5 ( red ) on top of the penton base and around the fiber shaft ( Figure 4C , middle and right panels ) . The conformation of the flexible RGD loop of penton base appears to be perturbed in the presence of HD5 . The position of the fiber knob relative to the fiber shaft also seems to be modified such that the knob is no longer reconstructed . The cryoEM analysis of the Ad5 . F35+HD5 complex indicates that HD5 interacts with the exposed surfaces of the three major capsid proteins: hexon , penton base , and fiber . Previously , we observed that HD5 does not prevent HAdV-5 from entering host cells [13] , [36] . In addition , we observed that HD5 binding stabilizes the capsid and prevents dissociation of capsid proteins , including fiber , upon exposure to heat . Therefore , we considered which of the multiple binding sites visualized by cryoEM might lead to enhanced virion stability . We reasoned that we might find a negatively charged region of the capsid that was present within the protein sequences of sensitive serotypes and not present in resistant serotypes and that was also in the vicinity of HD5 cryoEM difference density . In particular , we were looking for a possible binding site for HD5 that might bridge adjacent capsid subunits and stabilize the capsid . By comparing the N-terminal sequences of fibers from HAdV types that are either sensitive or resistant to HD5 we identified one negatively charged region that is present in all of the sensitive serotypes ( i . e . , 18-DTET-21 in HAdV-5; DPFD in HAdV-12; EDES in HAdV-3; DADN in HAdV-4 ) ( Figure 5A ) . In resistant serotypes of species D the corresponding region of the fiber is non-polar and positively charged ( i . e . , 18-GYAR-21 in HAdV-19c ) . Serotype HAdV-41 is resistant to HD5 , despite having a single negatively charged residue in this region; however , it is different from all of the other serotypes we examined in that it has both a short and a long fiber , which could affect the mechanism of HD5 neutralization . The variable fiber region , which is conserved within species but varies between species , precedes the fiber shaft repeats and directly follows a conserved motif ( FNPVYPY ) that binds at the interface of adjacent penton base monomers [33] . The difference density analysis of Ad5 . F35+HD5 ( Figure 5B and C ) suggests a possible explanation for fiber stabilization by HD5 , as strong difference density ( mesh ) appears to cover the variable fiber sequence ( EDES in HAdV-35 or DTET in HAdV-2 , partially shown in space filling representation ) , effectively pinning the N-terminus of fiber ( green ribbon ) against penton base ( gold ribbon ) . Therefore , this variable region of the fiber may form part of a critical binding site for HD5 neutralization of HAdV . We propose a model for HD5 neutralization of HAdV-5 in which HD5 binds to the interface of penton base and fiber and prevents fiber dissociation , consequently blocking downstream uncoating events that are required for infection . The availability of sensitive ( e . g . , HAdV-5 ) and resistant ( e . g . , HAdV-19c ) serotypes provided a means to test this HD5 neutralization model by generating virus chimeras . Initially , virus chimeras were constructed by replacing the sequences for fiber , penton base , and hexon in the HAdV-5 genome with the corresponding sequences from HAdV-19c . Consistent with previous studies [37] , [38] , the virus chimera containing the HAdV-19c hexon is not viable; however , constructs containing the HAdV-19c fiber ( 19cF ) or penton base ( 19cPB ) are capable of replicating . When each of these viruses was tested for sensitivity to HD5 , we found that the 19cF virus is completely resistant to neutralization ( Figure 6 ) . In contrast , the 19cPB virus has an intermediate phenotype . It is partially neutralized by HD5 but only at the higher concentration tested ( 10 µM ) . Together , these results indicate that both fiber and penton base are involved in HD5 neutralization . Based on these results , we created an additional construct in which only the four residues in the HAdV-5 fiber variable region ( DTET ) were replaced by the corresponding residues from HAdV-19c ( GYAR ) . Compared to HAdV-5 , the GYAR virus is less sensitive to 5 µM HD5 . We then combined the GYAR substitution with the PB substitution in a single construct ( PB/GYAR ) . This construct , like 19cF and wild type HAdV-19c , is completely resistant to neutralization by HD5 . This result confirms a role for the DTET/GYAR variable fiber region in HD5 neutralization , as the PB/GYAR chimera is even more resistant to HD5 then 19cPB alone . Additional studies using a higher concentration of HD5 ( 20 µM ) confirmed the defensin-resistance of HAdV-19c , 19cF , and PB/GYAR ( data not shown ) . Equivalent results were obtained using a FACS-based assay that requires 100-fold lower moi , indicating that variations in particle to pfu ratios among the virus preparations could not account for the differences in phenotype ( data not shown ) . Studies equivalent to those in Figure 2B to measure HD5 binding to both 19cF and PB/GYAR did not detect a reduction in the amount of HD5 bound to these viruses compared to HAdV-5 ( data not shown ) . Taken together , these studies demonstrate that HD5-mediated inhibition of HAdV infection is determined by species-specific sequences in the virus capsid and that critical neutralizing determinants are found in both fiber and penton base; however , the lack of reduction in overall HD5 binding to the resistant chimeric viruses suggests that additional , non-neutralizing binding determinants remain intact .
These studies extend our understanding of the mechanism of α-defensin-mediated neutralization of HAdV . We observed species-specific neutralization of HAdVs , which is dependent upon defensin binding to the virus capsid . Thousands of defensin molecules bind to each virus particle with an approximate KD that correlates well with the IC50 for virus infection , and antiviral activity is dependent upon the tertiary structure of a correctly folded α-defensin molecule . Structural analysis by cryoEM indicates that defensins bind to all of the exposed major capsid proteins . Based on sequence analysis and cryoEM studies , we proposed that potential critical sites for defensin binding are located at the point of contact between penton base and fiber . The importance of these sites for defensin neutralization was confirmed by an analysis of virus chimeras comprised of sequences from sensitive and resistant HAdV serotypes , indicating that neutralization determinants are found in both fiber and penton base . In conjunction with our previous studies , this observation suggests a model in which defensin binding to these critical neutralization sites prevents fiber dissociation , thereby blocking subsequent steps in HAdV uncoating that are required for release of protein VI , endosomalysis , and infection . Differential susceptibility to defensin was previously observed in studies of cutaneous and genital serotypes of HPV [9] , suggesting that there are specific determinants on the HPV capsid that dictate defensin neutralization . To investigate whether this is also the case for HAdV , we tested the sensitivity of representative serotypes from 6 of the 7 HAdV species to defensins HD5 and HNP1 . Consistent with more limited previous studies [12] , we found that sensitivity to defensins is species specific . Because the defensin-capsid interaction is at least in part based on electrostatic interactions [13] , a simple hypothesis is that defensin sensitivity would correlate with net hexon charge . However , this is not the case , even though the major electrostatic property of the AdV is from hexon [39] . This observation supports a model in which specific binding determinants dictate defensin sensitivity . This conclusion is bolstered by the observation that only correctly folded HD5 has antiviral activity . Previous studies showed that the chemokine activity of some defensins is dependent upon defensin conformation [28] . α-defensin inhibition of bacterial toxins is also significantly reduced in defensin derivatives that cannot form disulfide bonds , as in the HD5-Abu used here [29] , [40] . As HD5-Abu retains the same net positive charge as the correctly folded HD5 , a purely charge-dependent mechanism cannot explain the neutralizing activity of this antimicrobial peptide . Similarly , although all natural defensins have a net positive charge , not all defensins ( e . g . , HBD-2 ) neutralize HAdV infection [8] , [12] , [13] . Therefore , these studies support the hypothesis that the HAdV capsid-defensin interaction is due to specific recognition of the virus capsid by defensins . We used an equilibrium-binding assay to measure the affinity and stoichiometry of the defensin-capsid interaction . We found that as many as 2750 HD5 molecules are bound to each virus particle at saturation ( Vmax ) with an apparent affinity ( KD ) that approximates the IC50 for infection . The use of surface plasmon resonance to more accurately measure the capsid-defensin interaction would have been preferable for these studies; however , the large mass difference between HD5 ( 3 . 6 kDa ) and the virus particle ( 150 MDa ) precludes this approach . Although our analysis likely approximates the binding parameters of the system , there are some limitations . First , it is semi-quantitative because of the methods used to estimate both the number of virus particles in each sample and the amount of defensin bound . Second , there is no estimation of non-specific binding . Nonetheless , the data more closely fits a specific binding curve . Our binding studies suggest one possible explanation for the enhancement of infectivity that is commonly observed for resistant serotypes . We observe specific binding of HD5 to the sensitive HAdV-5 and HAdV-7 serotypes but only a low level of binding to the resistant HAdV-19c , -25p , and -51p . Therefore , both neutralizing and non-neutralizing binding sites are likely present on the capsid . Defensin binding to non-neutralizing sites may neutralize electronegative surface charges and facilitate virus binding to the cell surface , functionally analogous to the enhancing effect of polybrene on retrovirus infection [41] . Consistent with this hypothesis , we showed that receptor-dependent and -independent binding of HAdV-5 to cells is enhanced by HD5 , but not HD5-Abu , despite a complete block of productive infection . Moreover , mutation of critical neutralization determinants in the 19cF and PB/GYAR chimeras did not result in a noticeable reduction in overall HD5 binding . Thus , the capsid-defensin interaction is complex , and the presence or absence of critical neutralization determinants dictates the outcome ( inhibition or enhancement ) . The extensive difference density attributable to HD5 in our cryoEM analysis of Ad5 . F35+HD5 is consistent with our estimated stoichiometry . HD5 binding sites were found on all of the major proteins of the capsid . Our studies do not address a physiologic role for hexon binding , although this binding may contribute to enhancement of infection due to charge neutralization . The accumulation of HD5 difference density was not equal among the four unique hexon positions in the asymmetric unit but rather was greatest on the peripentonal hexons . Since the possible binding sites presented by each hexon are equivalent , this may be due to multimerization of HD5 at the vertices , potentially creating bridges between the peripentonal hexons and the penton base . In crystal structures , α-defensins form dimers [42] , [43]; however , it is unclear whether or not defensin dimerization plays a physiologic role . HD5 has been shown to form dimers and tetramers at concentrations below 5 µM , defensin self-association is greatly enhanced by binding to target proteins , and mutations that disrupt the ability of HD5 to form dimers also reduce target protein binding [40] , [44] . Therefore , defensin dimerization or multimerization may also contribute to AdV binding and antiviral activity . Similarly , we observed extensive binding of HD5 to the fiber . The fiber shaft was substantially thicker in the presence of HD5 , and the fiber knob was poorly reconstructed . Either HD5 induces greater conformational flexibility in the fiber shaft leading to greater averaging of the fiber knob density , or HD5 affects the linker region between the shaft and the knob . Both the RGD loops and the fiber shaft contain multiple negatively charged residues that might serve as binding sites for the positively charged HD5 molecule . Nonetheless , the capacity of fiber to bind to CAR was not compromised by HD5 binding based on our previous studies showing HAdV-5 cell entry in the presence of HD5 and the observed reduction in cell binding of HAdV-5/HD5 in competition with 5FK [13] , [36] . Our virus chimera studies support the existence of multiple binding determinants in the penton complex that are critical for neutralization . Disruption of a single binding determinant ( e . g . DTET in fiber ) is insufficient to completely abrogate neutralization . Rather , two or more sites must be simultaneously disrupted , as in the PB/GYAR chimera , to generate defensin resistance . Because resistance was also observed in the 19cF construct , at least two separate determinants are likely found in fiber . In each case , disruption of the neutralization sites led not only to resistance , but also to enhancement of infection . This finding supports the notion that enhancement and neutralization are competing processes mediated by defensin binding . Analysis of additional virus chimeras to map the neutralization determinants may provide a more detailed description of the binding sites important for inhibition and enhancement . They may also help explain the resistance of HAdV-41 to HD5 despite the presence of one acidic residue in the identified fiber neutralization determinant of both the short and long HAdV-41 fibers . Based on our combined functional and structural studies , we propose a model for neutralization in which α-defensins bind to critical capsid determinants at the point of contact between fiber and penton base , thereby preventing fiber release . One implication of this model is that fiber dissociation is absolutely required for subsequent uncoating events . This model cannot distinguish between the dissociation of fiber and penton base from the capsid independently or together as a complex . In the first case , defensin may actively lock the fiber onto the penton base . Alternatively , HD5 may obstruct a conformational change in penton base that is required for its release with fiber still attached . Our studies provide strong support for a mechanism of neutralization of HAdV-5 by HD5 and , in combination with our previous report demonstrating stabilization of HAdV-5 , -12 , and -35 capsids by HD5 [13] , suggest that other sensitive serotypes are neutralized by HD5 by a similar mechanism . However , detailed studies of additional HAdV/defensin combinations may reveal differences in the mechanisms . Although the temporal order of uncoating events suggests that fiber release is a critical step [21] , [22] , no previous example of a specific inhibitor of this step leading to a block to infection has been described . Therefore , our studies not only provide insight into the mechanism of defensin-mediated neutralization of non-enveloped virus infection but also provide a new rationale for the design of entry inhibitors . In addition , our results shed further light on the earliest events of HAdV disassembly occurring during cell entry . Because other non-enveloped viruses ( e . g . , HPV ) are also inhibited by defensins , studies of defensin neutralization may also provide insight into the entry mechanisms of these viruses . The role of defensins in vivo against adenovirus or other non-enveloped viruses has not been demonstrated; however , several observations suggest that the neutralization model studied here could be relevant for antiviral immunity . HD5 concentration in the intestinal lumen has been estimated at 14–69 µM ( 50–250 µg/ml ) [45] , which is greater than that required to neutralize HAdV infection . Many HAdVs , including those that cause respiratory infections , have been shown to infect and replicate in the bowel and have been detected upon shedding in the feces . Thus , sensitive HAdV serotypes may encounter HD5 secreted by Paneth cells during natural infection . It is intriguing that HAdV-F serotypes , which cause primarily gastrointestinal infections , are resistant to HD5 . The alpha-defensins of human neutrophils are found at high concentration in azurophil granules [46] , [47] . Although measured at low concentrations in plasma , these molecules can be secreted or found in phagocytic vacuoles at high local concentrations ( >10 mg/ml ) [47]–[49] . These cells home to the site of infection where they could encounter HAdV in many tissues , including the ocular , oral , and pulmonary mucosa . AdVs have also been shown to interact directly with neutrophils and to be engulfed [50] . Additional studies are required to assess the role of defensins in antiviral immunity in vivo .
Tissue culture reagents were obtained from Invitrogen ( Carlsbad , CA ) . Human A549 cells ( ATCC ) were propagated in DMEM supplemented with 10% FBS . Stable 293 cells over-expressing the human β5 integrin subunit ( 293β5 ) were created by transfecting 293 cells ( ATCC ) with the human β5 gene ( pCDNA3/β5 , a gift from David Cheresh , University of California , San Diego; San Diego , CA ) . Transfected cells were selected for high integrin expression . Stable 293 cells over-expressing the V-protein of the paramyxovirus Simian virus 5 ( 293-SV5/V ) were a gift of Kenneth Mellits ( University of Nottingham , Loughborough , UK ) [51] . HAdV-2p , -3p , -4p , -11p , -12p , -25p , -35p , -37p , -41p , and -51p were from ATCC . HAdV-7p and -14p were gifts of David Metzgar ( Naval Health Research Center , San Diego , CA ) . HAdV-16p and -23p were gifts of Adriana Kajon ( Lovelace Respiratory Research Institute , Albuquerque , NM ) . HAdV-19c was a gift of James Chodosh ( Harvard Medical School , Boston , MA ) [52] . The replication-defective HAdV-5 vector used in these studies ( Ad5 . eGFP ) is E1/E3-deleted and contains a CMV promoter-driven enhanced green fluorescent protein ( eGFP ) reporter gene cassette . Ad5 . F35 was constructed by replacing the entire fiber gene from a HAdV-5-based vector expressing β-galactosidase with that of HAdV-35p [53] . Virus chimeras were created by replacing the entire open reading frames of the HAdV-5 penton base or fiber with that of HAdV-19c by recombineering [54] in a BAC construct ( pAd5-GFPn1 ) containing the entire genome of an E1/E3-deleted HAdV-5 vector expressing eGFP [55] . The GYAR and PB/GYAR constructs were created by replacing the codons for DTET in the HAdV-5 fiber gene with those for GYAR from HAdV-19c in the original pAd5-GFPn1 plasmid or in the previously constructed PB chimera plasmid , respectively . The fidelity of the chimera constructs was verified by sequencing the recombineered region and by restriction digest . To generate virus , 293β5 cells were transfected with the large Pac I restriction fragment of these BACs . Transfected cells were cultured until visible plaques formed . The identity of the final virus stock was confirmed by restriction digest . PCR was used to verify purity and absence of cross-contamination . The GYAR substitution in the fiber protein was confirmed by sequencing a PCR product from the final virus stock . All wild type viruses were propagated in 293β5 or A549 cells except for HAdV-41p , which was propagated in 293-SV5/V . All AdV vectors were propagated in 293β5 cells . Cultures were infected with 300 particles/cell of purified viruses or from cleared lysates of original virus stocks . When complete cytopathic effect was observed , cells were harvested and concentrated by low speed centrifugation . For some serotypes , virus was precipitated from supernatant using 8% PEG [56] . Cell pellets were disrupted by three cycles of freezing and thawing . Mature virus was purified from the cleared lysate or PEG precipitate by two consecutive rounds of centrifugation [2–3 h at 111 , 000×g ( avg . ) ] through continuous 15% to 40% CsCl gradients , dialyzed against three changes of A195 buffer [57] , flash frozen in liquid nitrogen , and stored at −80°C . Synthetic HNP1 , HBD2 , and HD5 were obtained from Peptides International , Inc . ( Louisville , KY ) . HD5 derivatives containing the E14Q substitution or L-α-aminobutyric acid in place of cysteine were produced by solid phase chemical synthesis as described [25] , [58] . The ribbon representation of HD5 ( PDB 1ZMP ) was generated with PyMOL [59] Prior to use in this assay , each virus stock was titrated on A549 cells . A virus concentration was chosen to produce 50–70% maximal signal in the absence of defensin as described below . To measure the effect of defensins on infectivity , purified virus was incubated with HD5 or HNP1 for 1 h on ice in serum-free DMEM ( SFM ) . Confluent A549 cells in black wall , clear bottom 96-well plates were washed twice with SFM , and virus/defensin mixtures were added in a final volume of 35 µl/well . In parallel , wells were infected with two-fold serial dilutions of each virus to establish a standard curve for quantification with an upper limit of 200% . After 2 h , wells were washed twice and replaced with DMEM/10% FBS . Samples were incubated for approximately 48 h , fixed with paraformaldehyde , permeabilized in 20 mM glycine/0 . 5% Triton X-100 in PBS , and stained with an anti-hexon primary antibody ( 8C4 , Fitzgerald Industries International , Acton , MA ) and an Alexa Fluor 488-conjugated anti-mouse secondary antibody ( Invitrogen , Carlsbad , CA ) . Plates were scanned for Alexa Fluor 488 signal using a Typhoon Trio variable mode imager ( GE Healthcare , Piscataway , NJ ) . Total well fluorescence above background was quantified with ImageJ software [60] . For each virus , samples were quantified by nonlinear regression against the standard curve using Prism software ( GraphPad Software , Inc . , La Jolla , CA ) . To test the activity of HD5 derivates , Ad5 . eGFP was incubated with 15 µM of HD5 , HD5-Abu , or HD5-E14Q . Infectivity was assessed by enumerating eGFP-positive cells by flow cytometry as described [13] . To measure HD5 binding to HAdV-5 and -51 , HD5 was serially diluted in PBS and mixed with 5 µg purified virus . After 1 h incubation on ice , one half of each sample was separated by ultracentrifugation [209 , 000×g ( avg . ) for 2 hrs at 4°C] on a discontinuous gradient consisting of 300 µl of 30% nycodenz and 200 µl of 80% nycodenz in 50 mM NaCl , 20 mM HEPES pH 7 . 4 using an SW55ti rotor with adaptors ( Beckman Coulter , Inc . ) . The visible virus band was collected . The other half of each sample was used to make a standard curve for quantification . All samples were boiled in reducing loading buffer and separated using a 16% PAGEgel ( Expedeon , Inc . , San Diego , CA ) or 10–20% Tris-Tricine gel ( Bio-Rad , Hercules , CA ) . The gels were stained with Deep Purple ( GE Healthcare ) and imaged on a Typhoon Trio . Virus bands were quantified using ImageQuant NT software ( GE Healthcare ) . The amount of HD5 in each sample was normalized to protein V and hexon . The amount of HD5 in the centrifuged samples was then quantified against the standard curve using Prism software . Affinity and stoichiometry were estimated from the average data of at least three independent experiments using Prism software . Recombinant HAdV-5 fiber knob ( 5FK ) comprising residues 387–581 of the HAdV-5 fiber and HAdV-16 fiber knob ( 16FK ) comprising residues 151–353 of the HAdV-16 fiber , each containing an N-terminal hexahistidine tag , were expressed in BL21 ( DE3 ) cells ( Invitrogen , Carlsbad , CA ) and purified using TALON Metal Affinity Resin ( Clontech , Palo Alto , CA ) as previously described [61] , [62] . Alexa Fluor 448 labeled-Ad5 . eGFP [13] ( 4 . 2×109 particles/sample ) was incubated with or without 20 µM HD5 or HD5-Abu for 45 min on ice . In parallel , 1×105 A549 cells in PBS+0 . 2% sodium azide were incubated with or without 200 nM 5FK or 16FK for 45 min on ice . The virus/defensin mixtures were combined with the cell/FK mixtures ( final volume 100 µl/sample ) and incubated for 45 min on ice . Samples were washed 2 times with cold PBS+1% FBS , fixed with 1% paraformaldehyde , and analyzed by flow cytometry for Alexa Fluor 488 . Purified Ad5 . F35 ( 160 µg/ml ) was combined with HD5 ( 20 µM ) and incubated for 45 min on ice . CryoEM grids were produced with an FEI Vitrobot . Electron micrographs were collected on an FEI Polara microscope ( 300 kV , FEG ) operated at 300kV with the grids at liquid nitrogen temperature using the SAM semi-automatic data collection routine [63] . The defocus values of the micrographs ranged from 0 . 5 µm to 4 µm . The absolute magnification of the digital micrographs collected on a Gatan UltraScan 4000 ( 4000×4000 pixel ) CCD camera was 397 , 878× , corresponding to a pixel size of 0 . 4 Å on the molecular scale . Individual particle images were selected from micrographs with in-house scripts and computationally binned to produce particle image stacks with various pixel sizes suitable for image processing ( 4 . 8 Å , 2 . 4 Å , and 1 . 6 Å ) . Particle images with a pixel size of 4 . 8 Å were used for initial CTF parameter determination with CTFFIND3 [64] and orientational parameter determination with FREALIGN [65] . A cryoEM structure of Ad5 . F35 [31] was used as the starting three-dimensional model for FREALIGN refinement . Intermediate refinement rounds were performed using particle images with a 2 . 4 Å pixel and the final rounds of refinement were performed using particle images with a 1 . 6 Å pixel . Magnification refinement for the previously acquired Ad5 . F35 and the new Ad5 . F35+HD5 cryoEM particle images was performed together on a per particle basis in FREALIGN . Separate three-dimensional structures were generated for Ad5 . F35 and for Ad5 . F35+HD5 based on 3 , 040 and 2 , 611 particle images , respectively . The pixel size of the final structures was determined to be 1 . 61 Å by optimizing the agreement between the docked HAdV-5 hexon crystal structure ( PDB 1P30 ) [32] and the cryoEM density maps with UCSF Chimera [66] . The resolution of the icosahedral capsid ( radii 300–463 Å ) of the Ad5 . F35 reconstruction estimated by Fourier shell correlation is within the range of 6 . 9–5 . 3 Å; 6 . 9 Å ( FSC 0 . 5 threshold ) ; 6 . 1 Å ( FSC 0 . 3 ) ; and 5 . 3 Å ( FSC 0 . 143 ) . The resolution of the icosahedral capsid of the Ad5 . F35+HD5 reconstruction is 12 . 3–8 . 2 Å; 12 . 3 Å ( FSC 0 . 5 threshold ) ; 10 . 9 Å ( FSC 0 . 3 ) ; and 8 . 2 Å ( FSC 0 . 143 ) . Both the Ad5 . F35 and Ad5 . F35+HD5 reconstructions were sharpened with a temperature factor of B = −450 Å2 and filtered to 12 Å resolution with cosine edge filtering using the BFACTOR program ( http://emlab . rose2 . brandeis . edu/software ) . Difference mapping was performed by docking the HAdV-5 hexon ( PDB 1P30 ) and HAdV-2 penton base/fiber N-terminal peptide crystal structure coordinates ( 1X9T ) [33] within one facet of each reconstruction . The docked coordinates were converted to a density map with the pdb2mrc routine of EMAN v1 . 7 [67] , filtered to 12 Å resolution , normalized , and subtracted from the Ad5 . F35 and Ad5 . F35+HD5 reconstructions . | Defensins are effectors of the innate immune response with antibacterial and antiviral activity . A major bactericidal mechanism of defensins is membrane disruption; however , their mechanism against non-enveloped viruses , such as human adenovirus , is poorly understood . This work shows that sensitivity of human adenovirus to defensins is species specific and that neutralization is dependent upon defensin tertiary structure . A cryoEM structural study of an adenovirus vector in complex with a neutralizing defensin , HD5 , led to a neutralization model in which defensin binds to the interface of two capsid proteins , preventing dissociation of the fiber protein . We propose that binding at this site blocks downstream uncoating events required for infection . Infectivity studies using virus chimeras comprised of capsid proteins from sensitive and resistant human adenovirus serotypes support this model . This functional and structural study provides insight into the mechanism of human adenovirus neutralization by defensins and suggests new strategies to inhibit infection . | [
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] | 2010 | Insight into the Mechanisms of Adenovirus Capsid Disassembly from Studies of Defensin Neutralization |
Cryptococcosis is a neglected and predominantly opportunistic mycosis that , in Brazil , poses an important public health problem , due to its late diagnosis and high lethality . The present study analysed cryptococcosis mortality in Brazil from January 2000 to December 2012 , based on secondary data ( Mortality Information System/SIM-DATASUS and IBGE ) . Out of 5 , 755 recorded deaths in which cryptococcosis was mentioned as one of the morbid states that contributed to death , two distinct groups emerged: 1 , 121 ( 19 . 5% ) registered cryptococcosis as the basic cause of death , and 4 , 634 ( 80 . 5% ) registered cryptococcosis associated with risk factors , mainly AIDS ( 75% ) , followed by other host risks ( 5 . 5% ) . The mortality rate by cryptococcosis as the basic cause was 6 . 19/million inhabitants , whereas the mortality rate by cryptococcosis as an associated cause was 25 . 19/million inhabitants . Meningitis was the predominant clinical form ( 80% ) , males were the more affected ( 69% ) , and 39 . 5 years old was the mean age . The highest mortality rate due to cryptococcosis as basic cause occurred in the state of Mato Grosso ( 10 . 96/million inhabitants ) . Mortality rates due to cryptococcosis as associated cause were highest in the states of Santa Catarina ( 70 . 41/million inhabitants ) and Rio Grande do Sul ( 64 . 40/million inhabitants ) , both in the South Region . Southeast , Northeast and South showed significant time trends in mortality rates . This study is relevant because it shows the magnitude of cryptococcosis mortality linked to AIDS and removes the invisibility of a particular non-AIDS-related disease , accounting for almost 20% of all cryptococcosis deaths . It can also contribute to control and surveillance programs , beyond highlighting the urgent prioritization of early diagnosis and proper treatment to reduce the unacceptable mortality rate of this neglected mycosis in Brazil .
Encapsulated yeasts of the Cryptococcus neoformans/Cryptococcus gattii species complexes are the causative agents of cryptococcosis , a systemic mycosis of humans and animals , acquired by inhalation of their spores—desiccated yeast cells or basidiospores—from the environment [1 , 2] . Although usually regressive , some cases develop cryptococcal lung injury , which can spread to other sites or organs . On reaching the central nervous system , it may cause meningoencephalitis , the most severe form of cryptococcosis that , without early diagnosis and proper treatment , is highly lethal or disabling [3 , 4] . Cryptococcus neoformans infection predominates in immunocompromised hosts , being globally a threat to people living with HIV/AIDS , causing approximately 15% of AIDS-related annual mortality [5 , 6] . Cryptococcosis by C . gattii occurs mainly in otherwise immunocompetent hosts , but some immune deficiency not detected by routine tests may predispose individuals to this infection [7 , 8] . It is estimated that more than 300 million people worldwide , of which about 3 . 8 million in Brazil , suffer from a serious fungal infection every year , resulting in more than 1 , 350 , 000 deaths [9 , 10] . Among these diseases is cryptococcosis , with an overall incidence varying from 0 . 04 to 12% per year among people with HIV [5] . The global incidence of cryptococcosis in people living with HIV/AIDS in 2008 was estimated in approximately 1 million meningitis cases annually ( range 371 , 700–1 , 544 , 000 ) causing around 625 , 000 deaths [5] . The highest number of yearly cases was estimated to occur in sub-Saharan Africa ( 720 , 000 ) , followed by South–East Asia , and Latin America as the second and third regions with the most cases of cryptococcal meningitis ( 54 , 400 ) [5] . Since then , due to extensive antiretroviral therapy ( ARVT ) expansion , AIDS-related deaths have been reduced by 45% [6] . In 2014 , the global incidence cases of cryptococcal meningitis was estimated at 223 , 100 ( 95% CI 150 , 600–282 , 400 ) and the annual global deaths were estimated at 181 , 100 , with 135 , 900 ( 75%; [95% CI 93 , 900–163 , 900] ) deaths in sub-Saharan Africa [6] . Latin America’s annual burden of cryptococcal meningitis estimate was 5300 ( 2600–8900 interval ) and deaths from cryptococcal meningitis were 2400 ( 1100–4400 ) [6] . But , even so , cryptococcosis is not on the WHO neglected tropical diseases list [5 , 11] . Besides the well-known outbreak in North America [12 , 13] , cryptococcosis by C . gattii presents a peculiar epidemiological profile in South America , especially in Brazil , where it is endemic in large areas of the Amazon region and the semi-arid Northeast region [14–19] . However , data available on cryptococcosis in Brazil is fragmented and circumscribed , mostly based on indirect data on AIDS programs and some based on analyses of series of cases , diagnosed in regional centres . According to studies regarding mortality related to systemic mycoses in the nationally , cryptococcosis is the second cause of mortality among them [20] . Moreover , cryptococcosis is highlighted as the most frequent among the systemic mycoses associated with AIDS [21] , assuming its essentially opportunistic character . The cryptococcosis lethality rate in Brazil is substantial , reported in the range of 45% to 65% [22] , independent of the presence of risk factors , dominated by association with AIDS , as well as the primary form of the disease . A different scenario is seen in developed countries , as for example in Canada , in non-HIV hosts , where the diagnosis of pulmonary forms is more frequent than meningitis , the overall lethality is about 8% and there is a control program and surveillance for primary cryptococcosis [23] . Cryptococcosis is a major public health problem in Brazil , most cases are diagnosed as central nervous clinical forms , mainly meningitis . Only a few cases are diagnosed in a pulmonary form , which usually disseminates to meningoencephalitis , increasing hospitalizations and lethality . Late diagnosis of cryptococcosis slows crucial therapeutic measures to reduce sequelae and avoid lethal outcomes . Nevertheless , cryptococcosis is not a reportable disease in Brazil , and the real magnitude of its mortality is unknown [15] . In order to improve epidemiological surveillance , regional strategies and priorities for early diagnosis and treatment of cryptococosis in HIV as well as in non-HIV groups , this study aims to characterize the mortality by cryptococcosis as a health problem with a diverse geographical pattern in Brazil . This paper shows the magnitude of cryptococcosis mortality and points to cryptococcosis as a severe and often fatal neglected mycosis in Brazil . The vast majority of deaths are hidden by several immunosuppressive conditions .
This is a descriptive epidemiological Brazialian study , based on secondary data for the period 2000 to 2012 , covering a historical series of 13 years . The study was approved by the Ethics Research Committee of the Sérgio Arouca Brazilian National School of Public Health , number 37353614 . 5 . 0000 . 5240 . The research used secondary data from the DATASUS/Ministry of Health ( MS ) Mortality Information System ( SIM ) and the Brazilian Institute of Geography and Statistics ( IBGE ) . Therefore , the individuals whose information was extracted were not identified individually . Furthermore , there was no direct intervention with the patient and / or relatives , ensuring anonymity . The DATASUS/Ministry of Health ( MS ) SIM is the official source of death data for infectious and parasitic diseases ( IPDs ) . SIM compounds the National Epidemiological Surveillance System ( NESS ) , providing data about deaths in Brazil through information registered on death declaration ( OD ) , including basic and associated cause , based on the 10th International Classification of Disease ( ICD ) . This data is collected by Municipal Health Secretaries ( MHS ) and registered in a national database and available for consultation . SIM data collection methodology did not change during the study period . Demographic data of the population and cartographic bases of the Brazilian federal units and regions were obtained from IBGE . The following variables were considered: cryptococcosis as basic or associated cause of death , gender , age , and place of residence . Data was distributed and analyzed according to country , regions and states . Deaths were studied according to their frequency by place of residence and their temporal and spatial distribution , estimating mortality and trend coefficients and analyzing their geographical distribution . Basic cause of death was defined as a disease or condition that initiated the chain of pathological events that led directly to death . Associated cause of death was defined as a pathological condition that had an unfavourable effect and contributed to death , mentioned in the death certificate . The classification between basic or associated cause was attributed by the physician who completed the death certificate . Only recently , data on deaths according to multiple causes is available in the mortality database . The mean mortality rate was estimated taking as numerator the number of basic cause of death by cryptococcosis at specific locations during the study period ( 2000–2012 ) . The utilized denominator was the mean size of the Brazilian population , in the same period , multiplied by 1 , 000 , 000 inhabitants . The same methodology was used for cryptococcosis as an associated cause . The mean mortality rate for all mentions was also estimated in the death certificates , that is , by the sum of both conditions above . To highlight the particularity of cryptococcosis , the total number of times cryptococcosis was mentioned , either as the basic or associated cause , that is , the total number of mentions among the diseases that contributed to death , was used . The ratio was then estimated by dividing the frequency of cryptococcosis as a mentioned cause by frequency as the basic cause ( ratio: total mentions/basic cause ) [24] . In order to analyze association between gender and associated or basic cause , we used a chi-square test , with significance level of 5% . We used a Poisson model with offset term to model the mortality rate by cause ( associated or basic ) , age groups and gender . The incidence density ratios ( IDR ) and 95% confidence intervals ( 95% CI ) were obtained from this model . The information on mortality by cryptococcosis with reference to each region or federated unit was analyzed according to its geographic distribution and presented through tables and thematic maps . We analyzed the time trends of mortality rate by Joinpoint analysis for basic and total cause of death . For this , we modelled the rates by Poisson model with quasilikelihood estimation , in order to solve the overdispersion problem . After , we used a segmented regression to determine the breakpoints in which we observed a significant change in trend of mortality rate . The Annual Percentage Change ( APC ) in each trend was obtained , with a 95% confidence interval ( CI ) . Graphs of mortality rates observed ( squared points ) and of mortality rates predicted by the Poisson segmented regression ( lines ) were provided . Tabwin , Microsoft Excel 2010 , R 3 . 5 . 1 and package segmented and QGIS were used to obtain the database , tabulation , trends and graphing .
From 2000 to 2012 , a total of 5755 deaths were recorded in Brazil in which cryptococcosis was mentioned . Of these , cryptococcosis was recorded as the basic cause of death in 1121 deaths ( 19 . 5% ) , representing a mean mortality rate of 6 . 09/ million inhabitants . The remaining 4634 ( 80 . 5% ) deaths from cryptococcosis were recorded as an associated cause with a mortality rate of 25 . 19/million inhabitants . Male deaths were more common in both the basic and associated causes ( Table 1 ) . The frequency rate of basic cause ( mentions/basic cause ) was 5 . 13 ( 5755/1121 ) . Of the 4314 cases associated with AIDS , 71 . 5% of deaths occurred in males , prevailing in the age range of 20 to 59 years old , accounting for 95 . 8% ( n = 4133 ) of the deaths . In the group of other risk factors ( n = 320 ) , males represented 66 . 9% of the deaths ( Table 1 ) . The IDR found corroborates the increased risk of death in males , the age group of 20 to 59 years and associated cause ( Table 2 ) . Among deaths of those younger than 20 years of age , ( 2 . 9% of the total ) , cryptococcosis mentioned as basic cause accounted for 6 . 7% ( n = 76 ) , and 5 . 3% ( n = 17 ) of deaths by cryptococcosis due to other risk factors , excluding HIV+ , as compared to 1 . 5% ( n = 68 ) of cryptococcosis AIDS-related deaths . In the basic cause group , cryptococcosis deaths among those older than 60 represent 51% of total mentions in this age group ( 225/445 ) and among those younger than 20 years old , represent 47% of total mentions in this group ( 76/161 ) ( Table 1 ) . Several known immunosuppressive conditions were recorded as basic cause in 80% ( n = 4634 ) of the deaths where cryptococcosis was mentioned as associated cause . AIDS was the major immunosuppressive disorder with 75% ( n = 4314 deaths ) , followed by other immunodeficiency conditions or risk factors with 5 . 5% ( n = 320 ) of deaths: non-Hodgkin lymphoma ( 27 ) , unspecified immunodeficiency ( 17 ) , lymphoid leukemia ( 13 ) , chronic renal failure ( 12 ) and other causes ( 251 ) , reflecting the opportunistic face of this mycosis . All clinical presentations of registered cryptococcosis have pointed to a severe disease , especially cryptococcal meningitis . Cerebral cryptococcosis–ICD ( International Classification of Diaseases ) B45 . 1 - ( cryptococcal meningitis ) predominated as by far the most frequent form , with 4743 deaths ( 82 . 4% ) of the total mentions . In the AIDS group , this form occurred in 83 . 6% ( 3609 ) of deaths , whereas where cryptococcosis was the underlying cause of death , it was 79 . 9% ( 895 ) . It is worth noting that the pulmonary form was diagnosed with cryptococcosis as a basic cause of death in 65 cases ( 5 . 8% ) , when associated with other risk factors 18 ( 5 . 7% ) and when associated with AIDS it was recorded only in 31 deaths ( 0 . 7% ) ( Table 3 ) . The distribution of deaths and the mean mortality rate by other infectious meningitides , according to the basic cause , were also analyzed in order to assess the relevance of the central nervous system in cryptococcosis among the other meningitides . During the study period , 21 , 333 meningitis deaths occurred , with a mortality rate of 115 , 97/million inhabitants . Among meningitis with specified cause , the meningococcal etiology was responsible for 8 . 6% ( 1 , 830 ) , with a mortality rate of 9 . 95/million inhabitants , being the most frequent , followed by cryptococcal meningitis , with 895 deaths ( 4 . 2% of the total ) and mortality rate of 4 . 87/million inhabitants . Also relevant were toxoplasma meningitis with 806 deaths ( 3 . 8% ) and a mortality rate of 4 . 38/million inhabitants; viral meningitis with 753 deaths ( 3 . 5% ) and a mortality rate of 4 . 09/million inhabitants; and tuberculous meningitis with 624 deaths ( 2 . 9% ) and a mortality rate of 0 . 26/million inhabitants . Meningites of unknown cause were included as “other meningites” ( Table 4 ) . In the same period , there were 608 , 314 deaths from other infectious diseases listed in Chapter 1 from ICD 10 . Cryptococcosis was the thirteenth cause of death between chronic and recurrent infectious disease , 1121 by basic cause . The proportion of cryptococcal deaths in the study period compared to the other infectious diseases was 0 . 18% ( S1 Table ) . Deaths from cryptococcosis were recorded in all Brazilian states , but their distribution was not homogeneous . Thematic maps show the geographic profile of cryptococcosis mortality rates in the period , as basic cause as well as an associated cause of death ( Table 5 ) ( Figs 1 and 2 ) . Total mentioned cause of death by cryptococcosis shows that the South Brazilian region has the highest rates , followed by the Midwest and Southeast . The North and Northeast had the lowest rates ( Fig 3 ) . The Southeast , Northeast and South showed significant time trends in mortality rates ( S2 Table ) . The Southeast region showed a decreasing trend of mortality rate ( -4 . 82% ) in years 2000–2006 . The Northeast region showed 105 . 20% of increasing trend in 2001 and 10 . 35% of increasing between 2005 and 2012 . Meanwhile , the South region showed decreasing trends of mortality rates in 2000–2005 ( -2 . 89% ) and 2009–2012 ( -7 . 27% ) . The basic cause of death by cryptococcosis show that the Northeast region had the lowest rates ( Fig 4 ) . The North and Northeast showed significant time trends in mortality rates ( S3 Table ) . The North region showed a decreasing trend of mortality rate ( -64 . 28% ) between years 2009–2010 . The Northeast region showed 12 . 42% of increasing trend between 2000 and 2008 and 43 . 92% of increasing between 2009 and 2012 .
This study points to cryptococcosis as a neglected , severe and often fatal opportunistic condition , since the vast majority of deaths ( 80% ) is hidden by a serious immunosuppressive disease , especially AIDS . In fact , Two patterns of infection were revealed: 1 ) primary cryptococcosis and 2 ) opportunistic cryptococcosis , both expressed mainly in the form of meningoencephalitis , indicating late diagnosis , ineffective treatment and difficult access to the national care network . The study of cryptococcal mortality considering only the basic cause presented limitations , since the presence of underlying immunodeficiencies predominates in the scenario . Thus , when the total causes mentioned in the death certificates was considered , a broad picture of the mycosis in Brazil was revealed , leading to an important reflection on the neglected diseases associated with a host with immunodeficiency . Eighty percent of cryptococcosis deaths were revealed through this approach [25] . In addition , the poorer regions of the north and northeast of Brazil still have high proportions of deaths due to ill-defined causes , which may hide both cryptococcosis and other AIDS-related infectious causes of death [25–27] . The distribution of cryptococcosis deaths according to gender and by all mentioned causes showed a preponderance among males . When associated with AIDS ( 71 . 2% ) , crypto mortality was greater than the mortality due to cryptococcosis as basic cause ( 62 . 3% ) , which corresponds with data from the literature [16 , 21] . We observed in primary cryptococcosis an age-matched progressive curve from childhood to adulthood , consistent with progressive environmental exposure to the agent . However , the age-related pattern of cryptococcosis associated with AIDS reflects the predominance of this risk factor , specially in the age group of 20 to 59 ( Tables 1 and 2 ) . In the over 60 age group within the total number of deaths an important differential was also revealed: AIDS-related deaths accounted for 2 . 7% of the total , while deaths due to cryptococcosis as basic cause represented about 20% , i . e . about seven times higher and , deaths due to cryptococcosis associated with other risk factors represented 33 . 6% , that is , twelve times higher . This set of evidence seems to corroborate the double profile of cryptococcosis ( Table 1 ) . This age-related profile is consistent with recent reports showing individuals affected by cryptococcal meningitis caused by C . gattii , with high lethality rates ( 30 up to 50% ) and frequent relapses in the North and Northeast regions of Brazil , along with increased frequency of cryptococcosis in AIDS in young male adults , the involvement of immunocompetent children , adolescents and young adults and the involvement of elderly individuals [15 , 16 , 28 , 29] . The mortality rate of infectious diseases which are difficult to diagnose and that require specialized care , usually expresses the tip of an iceberg . This study hypothesized cryptococcosis as an underestimated causa mortis , because the laboratory resources for timely agent identification and with the needed accuracy are often unavailable . The lack of extensive diagnostic laboratory coverage is evident , given that 75% of all meningitis-related deaths had no defined etiology [27] . In this study , the vast majority of cryptococcosis deaths , according to the total number of mentions , was due to cryptococcal meningitis ( 82 . 4% ) , and when associated with AIDS , caused 83 . 6% of deaths . In Brazil , studies have shown the relevance of cryptococcosis as the main mycosis associated with AIDS death [21] , and as the second cause of mortality among systemic mycoses [20] . Cryptococcal meningitis was the second most frequent opportunistic neurological infection in HIV/AIDS [28–30] , only surpassed by neurotoxoplasmosis [31–33] . Further , between 1980 and 2002 , about 13 , 000 individuals had cryptococcosis at the time of diagnosis of HIV infection , six percent of the 215 , 810 registered cases of AIDS in Brazil [22] . Brazilian autopsy studies of the Central Nervous System of AIDS patients showed high cryptococcal involvement: 12% ( 17/138 ) , 13 . 5% ( 34/252 ) and 15 . 8% ( 45/284 ) , respectively [31–33] . The high lethality of cryptococcal meningitis in Brazil results from the convergence of factors such as late suspicion and diagnosis , difficult access to care network , unavailability of rapid laboratory tests , together with inadequate or unavailable antifungals . The screening of Cryptococcal Antigen ( CrAg ) in HIV infected persons with CD4 count below 100 cells/mm3 is highly recommended by the WHO [34–36] . According to international advised protocol to reduce mortality by cryptococcosis , another important issue regarding treatment is to associate 5-flucytosine with amphotericin as a combined initial therapy [37 , 38] , but is as yet unavailable in the national therapeutic arsenal , despite institutional efforts to import this drug [39] . It is worth noting that the mortality rate related to cryptococcal meningitis was higher than that of Toxoplama CNS infection ( neurotoxoplasmosis ) , as well as higher than meningitis caused by all viral infections and by tuberculosis . In Africa , cryptococcal meningitis is the most common cause of meningitis in adults [6] . In the US , cryptococcal meningitis hospitalizations were more frequent than all bacterial meningitides combined , with an incidence of 1 . 1 per 100 , 000 inhabitants versus 0 . 728 per 100 , 000 respectively [38] . This study detected two patterns for cryptococcosis in Brazil: the first , a primary cryptococcosis drawn by deaths recorded as the basic cause , an emerging disease and the second , a cryptococcosis registered as an associated cause of death , an opportunistic infection affecting individuals who present some immunodepression , mainly AIDS-related patients [8 , 40] . C . gattii species complex occurs in tropical , subtropical and temperate areas , affecting mainly apparently healthy hosts in contact with environmental sources of infection [8] . C . neoformans complex is cosmopolitan and affects mainly individuals who present some immunodepression [8 , 40] . The geographic distribution of C . gattii in Brazil shows a higher prevalence in the North and Northeast regions compared with the other regions [18 , 19] , while C . neoformans is more prevalent in the South and Southeast regions [14] . In our study , we did not find significant differences between cryptococcal deaths in the North and Northeast regions , but we found a great difference in the South , Southeast and Central-West regions , where crypto deaths as associated cause were more frequent than basic cause . Furthermore , the majority of individuals infected by HIV in Brazil were concentrated in the South and Southeast regions [41] , reinforcing the two profiles of cryptococcosis: the South , Southeast and Central-West with predominant opportunistic infection by C . neoformans and the North and Northeast with , side by side , the opportunistic infection by C . neoformans and the primary infection by C . gattii [14 , 18 , 19] . The geographic distribution and joinpoint analysis show that the highest mortality rates due to cryptococcosis reported as basic cause was observed in the North , folowed by the Central West and the South . The state of Mato Grosso , Pará , Mato Grosso do Sul , Amazonas and Santa Catarina showed the highest rates by state . These regions are economically heavily based on agricultural activity . The North and Central West are the new Brazilian agricultural frontiers with intensive population mobility [42 , 43] . As previously pointed out , recent studies documented the presence of an endemic primary cryptococcosis in the Amazon region , the north , and northeast of Brazil [15–17 , 19] . The geographic distribution of mortality rates due to cryptococcosis as associated cause evidenced that the highest mortality rates occurred in the most economically dynamic regions of the country . These rates occurred in the South , Central West and Southeast . The highest rates were reported in the states of Santa Catarina , Rio Grande do Sul and Mato Grosso do Sul . This distribution is analogous to the distribution of AIDS deaths in the period , which it is also consistent with the interiorization spreading of the AIDS epidemic in Brazil [41] . The major limitation of this study is in relation to the use of secondary data , which underestimates the true number of deaths related to neglected diseases . The lack of specialized laboratories and medical resources in the poorest regions of the country result in a large number of deaths of indeterminate cause . Furthermore , the SIM does not have access to medical records , only to diagnoses reported on death certificates . Therefore , it is impossible to know how the diagnosis of cryptococcosis was made .
This study is the first one to apply a holistic approach to cryptococcosis mortality in Brazil . It provides needed visibility to cryptococcosis , revealing two distinct profiles , one primary and the other opportunistic associated mainly with AIDS . The high frequency of deaths by cryptococcosis meningitis and other severe clinical presentations indicates late diagnosis , unavailability of rapid diagnostic methods , lack of effective antifungal treatments , and difficult access to the care network in the country . This study can support surveillance and improvement actions aimed at preventing many avoidable deaths by this neglected systemic mycosis . | Cryptococcosis is an invasive , global , and neglected mycosis . Species of the Cryptococcus neoformans complex cause opportunistic infections in immunosuppressed hosts , particularly AIDS patients , while infections by species of the C . gattii complex predominate as a primary endemic mycosis in tropical and subtropical areas . In Brazil , it is an important and hidden public health problem , mainly in its meningitis form , whose lethality ranges from 45 to 65% , but remains as a not-notifiable disease . Brazilian studies placed it as the first cause of mortality among all AIDS-associated systemic mycoses and the second cause of mortality among systemic mycoses in general . This national study used data from the Brazilian Mortality Information System ( SIM ) in which all mentioned causes were considered , allowing the analysis of the associated causes of deaths and showing two different patterns of infections: a primary and an opportunistic cryptococcosis . Primary cryptococcosis presented a peculiar epidemiological regional profile and the opportunistic cryptococcosis was hidden by several immunosuppressive conditions . The authors expect that this study can support a better understanding of this infection and encourage more research and public health initiatives to prevent and control the cryptococcosis , both primary and opportunistic . | [
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"t... | 2019 | Mortality by cryptococcosis in Brazil from 2000 to 2012: A descriptive epidemiological study |
Epithelial morphogenesis involves a dramatic reorganisation of the microtubule cytoskeleton . How this complex process is controlled at the molecular level is still largely unknown . Here , we report that the centrosomal microtubule ( MT ) -binding protein CAP350 localises at adherens junctions in epithelial cells . By two-hybrid screening , we identified a direct interaction of CAP350 with the adhesion protein α-catenin that was further confirmed by co-immunoprecipitation experiments . Block of epithelial cadherin ( E-cadherin ) -mediated cell-cell adhesion or α-catenin depletion prevented CAP350 localisation at cell-cell junctions . Knocking down junction-located CAP350 inhibited the establishment of an apico-basal array of microtubules and impaired the acquisition of columnar shape in Madin-Darby canine kidney II ( MDCKII ) cells grown as polarised epithelia . Furthermore , MDCKII cystogenesis was also defective in junctional CAP350-depleted cells . CAP350-depleted MDCKII cysts were smaller and contained either multiple lumens or no lumen . Membrane polarity was not affected , but cortical microtubule bundles did not properly form . Our results indicate that CAP350 may act as an adaptor between adherens junctions and microtubules , thus regulating epithelial differentiation and contributing to the definition of cell architecture . We also uncover a central role of α-catenin in global cytoskeleton remodelling , in which it acts not only on actin but also on MT reorganisation during epithelial morphogenesis .
Epithelial polarisation involves a coordinated series of events resulting in the asymmetric segregation of plasma membrane into apical and basolateral domains . The establishment of apico-basal polarity is also accompanied by asymmetric distribution of intracellular organelles , cytoskeleton reorganisation , and polarised membrane trafficking [1] . How the intracellular redistribution of organelles and the establishment of plasma membrane domains are coupled to define the spatial orientation of cell polarity is , however , not well understood . The MT cytoskeleton undergoes a profound reorganisation during epithelial polarisation [2] . In many epithelia , MTs are prominently organised in bundles aligned along the apico-basal axis with their minus ends oriented toward the apical membrane and plus ends toward the basal membrane and as networks of mixed polarity underneath the apical and basal membranes . The molecular events underlying MT reorganisation and their contribution to epithelial morphogenesis remain unclear . In addition , these mechanisms seem to be different depending on the tissue . For instance , in the stratified epidermis , proliferative basal cells have a radial array of MTs organised around the centrosome ( CTR ) , while differentiated cells have acentrosomal cortical MTs . During epidermal differentiation , desmosomes appear to be essential to organise MTs around the cell cortex . The centrosomal proteins Ninein , Lis1 , and Ndel1 are recruited to desmosomes by desmoplakin [3–5] , and both desmoplakin and Lis1 are required to organise MTs at the cortex . In simple epithelia , lateral intercellular junctions are largely composed of cadherin-based cell–cell contacts or adherens junctions ( AJs ) . AJs consist of cadherin-adhesion receptors and associated cytoplasmic proteins , collectively called catenins . Cadherins form an adhesive interface all along the lateral domain but are also organised into special complexes known as zonula adherens ( ZA ) that are localised at the apical end . AJs are enriched in MTs , and MT bundles aligned along the apico-basal axis have their minus ends in close proximity to the ZA [6] . The molecular players underlying the AJ–MT connection remain , however , mostly unknown . Although cadherins are known to cooperate with the actin cytoskeleton [7 , 8] , a growing body of evidence also links cadherins to MTs . Indeed , it has been shown that MT disruption either by overall depolymerisation or by freezing the dynamic activity of MT plus ends perturbs cadherin-based cell-cell contacts [9] . Furthermore , the expression of exogenous cadherins in CTR-free cytoplasts increased the number of MTs [10] . This effect , which was dependent on the formation of cell–cell contacts , was mimicked by application of beads coated with stimulatory anti-cadherin antibody and suppressed by overexpression of the cytoplasmic cadherin tail [10] . Moreover , targeting α-catenin , but not p120-catenin or β-catenin , to the plasma membrane reproduced the MT-stabilising activity of E-cadherin in this assay [11 , 12] . In mammalian epithelial cells , a protein complex containing Plekha7 , the minus-end MT-binding protein Nezha/CAMSAP-3/Patronin , and KIF3C was reported to be recruited to ZA by interaction of Plekha7 with p120-catenin [13] . In nonpolarised individual cells , CAMSAP-3 is localised at the CTR and at minus ends of noncentrosomal MTs [14] . Whether CAMSAP-3 regulates the orientation of MTs in polarised epithelial cells remains to be elucidated . p120-catenin was also shown to interact with the MT plus-end binding protein CLASP2 in progenitor epidermal cells , suggesting that , depending on the cell context , p120-catenin could recruit opposite MT-binding activities [15] . CAP350 is a large and highly conserved cytoskeleton-associated protein-glycine-rich ( CAP-Gly ) domain-containing protein that directly binds MTs through its N-terminal domain . It localises at the CTR , where it might play a role in MT anchoring [16 , 17] . CAP350 also participates in MT stabilisation at both the Golgi area and centrioles [17 , 18] . It was reported that CAP350 interacts with the centrosomal protein FOP and recruits it to the CTR [16] . Interestingly , a novel protein superfamily , the TON1 Recruiting Motif ( TRM ) protein family , has been identified in plants [19] . An archetypal member of this family , TRM1 , is a MT-associated protein that localises to cortical MTs . TRM1 interacts in vivo with the TON1 protein that shares similarity with human FOP and is essential for MT organisation at the cortex [19] . Three motifs of TRMs ( M3 , M4 , and M2 ) are found in CAP350 . The M2 motif of CAP350 is responsible for FOP recruitment and was shown to interact with plant TON1 protein in yeast . These results suggest a conservation of CAP350-FOP centrosomal components in plant cells where they bind cortical MTs . CAP350 also targets the deubiquitinating enzyme cylindromatosis ( CYLD ) to the CTR in mammalian cells . This targeting is required for proper ciliogenesis , supporting an indirect role of CAP350 in primary cilium formation [20] . Studies on CAP350 have been generally performed in cells that do not make adhesive contacts with one another or do not express E-cadherin , such as Hela cells [16–18] . Intriguingly , a stable isotope labelling by amino acids in cell culture ( SILAC ) -mass spectrometry ( MS ) -based proteomic analysis of isolated adherent surfaces of epithelial MDCKII cells identified CAP350 as one of the most enriched cellular proteins [21] . This study suggested both the existence of a membrane-bound fraction of CAP350 in polarised kidney cells as well as a previously unknown role of this protein at the cell periphery . In this work , we report that CAP350 localises at the cell cortex in a cadherin-adhesion-dependent manner . A two-hybrid screen for centrosomal protein partners revealed a consistent high-confidence interaction of CAP350 with the adhesion protein α-catenin . By using MDCKII cells grown either as polarised epithelia or as cysts , we show that CAP350 is required for epithelial morphogenesis .
By using a previously characterised goat polyclonal antibody ( Fig . 1A , CAP350g ) , we found that in methanol- or paraformaldehyde ( PFA ) -fixed MDCKII epithelial cells , CAP350 is essentially detected at the CTR ( Fig . 1B , left panel ) . However , when cells were extracted with Triton before fixation , an additional cell peripheral CAP350 labelling was observed ( Fig . 1B , right panel ) . As shown in Fig . 1C , CAP350 clearly co-localised with α-catenin at cell-cell contacts but it was absent from cell-substrate adhesion sites ( Fig . 1C , arrows ) . These results suggested that CAP350 accumulated at cell-cell adhesions . Similar results were also obtained in human epithelial MCF10A cells ( S1A Fig . ) . To confirm this peripheral localisation , we performed additional immunofluorescence ( IF ) experiments by using two other antibodies ( Fig . 1A ) : a rabbit polyclonal antibody recognising the N-terminal part of the protein ( CAP350r , Novus Biologicals ) and a mouse monoclonal antibody raised against the central part of the protein ( CAP350m , this work ) . Both antibodies revealed a fraction of CAP350 co-localising with α-catenin at cell-cell junctions , which was more conspicuous when cells became fully polarised ( Fig . 1D ) . Double labelling for CAP350 and the adhesion proteins E-cadherin or β-catenin further indicated that , in addition to the CTR , CAP350 localised at cell-cell adhesion sites in epithelial cells ( Fig . 1E ) . In order to verify the specificity of the peripheral labelling , we developed three short hairpin RNA ( shRNA ) lentiviruses targeting different CAP350 sequences ( shCAP1 , shCAP2 , and shCAP3 ) and infected MDCKII cells . As controls , we generated lentiviruses containing either empty vectors or shRNAs against CAP350 but including four point mutations ( shm4 ) . Four days post-infection , cells infected with any of the shCAP-lentiviruses showed reduced CAP350 expression when compared with either noninfected or control lentivirus-infected cells , as revealed by WB ( S1B Fig . ) . When cells were infected with a mix of the three lentiviruses ( hereafter shCAP-lentiviruses ) , CAP350 was almost undetectable by western blot ( WB ) ( Fig . 1F ) . Immunofluorescence experiments showed that under these conditions cortex-associated CAP350 fraction disappeared , thus confirming the specificity of the staining ( Fig . 1G ) . Similar phenotypes were observed in cells infected with any of the lentiviruses ( S1C Fig . ) . Since lentiviruses targeted different CAP350 sequences , the possibility that the observed phenotypes were due to off-target effects is very unlikely . Under these conditions , however , the CTR-associated fraction was still present in most cells , suggesting a slower turnover of the protein at this location ( Fig . 1G and S1C Fig . ) . These partially depleted cells appeared enlarged and displayed disorganised cell–cell contacts ( Fig . 1G and S1C Fig . ) . Similar results were obtained in MCF10A cells ( S1D Fig . ) . Seven days post-infection , CAP350 centrosomal fraction was also exhausted ( S1E Fig . ) . In order to preserve the centrosomal function of CAP350 , all our experiments were carried out in cells infected with shRNA lentiviruses for four days , after which CAP350 was still maintained at the CTR . Indeed , quantification of CAP350 fluorescence intensity of more than 800 cells proved similar amounts of centrosomal CAP350 in shCAP- and shm4-infected cells 4 d post-infection ( Fig . 1H ) . To further assess the integrity of the CTR , the presence of specific centrosomal markers such as FOP , whose recruitment to the CTR is CAP350-dependent , γ-tubulin , and pericentrin ( PCNT ) was analysed in cells transduced with specific or control lentiviruses for four days . Once again , no significant differences in the distribution of any of these centrosomal proteins were observed ( Fig . 1I and Fig . 1J ) . Altogether , these analyses indicated that the experimental conditions we had set up would allow us to investigate the role of CAP350 at the cell periphery without severely affecting its function at the CTR ( see below for CTR functionality ) . To further substantiate that CAP350 is a cell-cell junction protein in epithelial cells , we examined the distribution of CAP350 in cells lacking E-cadherin . As shown in Fig . 1K , in human dermal fibroblasts ( HDF ) CAP350 was exclusively detected at the CTR by IF and hardly detectable by WB in whole-cell extracts , as expected for a strict centrosomal protein . Similar results were obtained in the MCF10A-derived cell line NeuT that expresses a constitutively active form of the oncogene ERBB2/HER/neu ( S1F Fig . ) . In these cells , loss of E-cadherin and cell-cell adhesion was accompanied by loss of CAP350 labelling at the cell periphery but not at the CTR . A significant reduction of CAP350 expression was also detected by WB ( S1F Fig . ) . These results , and those by others [17] , suggest that whereas CAP350 is ubiquitously localised at the CTR , the presence of CAP350 at cell-cell contacts is a feature of E-cadherin-expressing epithelial cells . To examine if the peripheral localisation of CAP350 depends on cell-cell adhesion , we first applied the calcium chelation method with ethylene glycol tetraacetic acid ( EGTA ) ( Fig . 2A ) . As expected , under calcium chelation condition , cells detached from each other and rounded up . E-cadherin and α-catenin stainings disappeared from the plasma membrane ( Fig . 2A , 0 min ) . Similarly , CAP350 peripheral labelling was abolished by EGTA treatment ( Fig . 2A , 0 min ) . Calcium addition allowed de novo formation of cell-cell contacts . Sixty minutes after calcium addition , E-cadherin and α-catenin , but not CAP350 , were detected at most of the cell-cell contacts ( Fig . 2A , 60 min ) . By 2 h , CAP350 was also recruited to cell adhesions ( Fig . 2A , 120 min ) . Then , we wondered whether cadherin-based cell-cell adhesion was responsible for junctional CAP350 localisation . To address this issue , we specifically inhibited E-cadherin homophilic binding by using a blocking antibody against its extracellular domain DECMA-1 and examined the distribution of either E-cadherin , α-catenin , and CAP350 . Cells were allowed to polarise for three days in the presence of either an irrelevant antibody ( immunoglobulin G [IgG] control ) or the DECMA-1 antibody . Contrary to the control , cells were unable to form confluent layers in the presence of DECMA-1 and appeared as isolated groups containing a variable number of cells ( Fig . 2B ) . Cell morphology and cadherin-based contact integrity were also compromised . As shown in Fig . 2C , distribution patterns of either E-cadherin or α-catenin were altered or even abolished at some cell-cell contacts . Changes in CAP350 distribution completely paralleled those of E-cadherin or α-catenin ( Fig . 2C ) . By contrast , the distribution of the zonula occludens protein 1 ( ZO-1 ) remained intact ( Fig . 2D ) , indicating that changes in CAP350 localisation were not due to nonspecific alterations at the plasma membrane . Remarkably , we observed severe modifications of MT network in the presence of the blocking antibody , pointing out the relevance of E-cadherin-based adhesion in the organisation of the MT cytoskeleton ( Fig . 2E ) . Taken together , these results indicate that during cell-cell adhesion formation , the centrosomal protein CAP350 localises to cell-cell contact sites and that this localisation is dependent of E-cadherin-mediated adhesion . To identify possible partners of CAP350 , a two-hybrid screening was carried out using several fragments of the protein as baits . This screening identified a high-confidence interaction of CAP350 with α-catenin ( Fig . 3A ) . Seven independent α-catenin clones were isolated with the CAP2 fragment ( Fig . 3A , dark red ) , corresponding to the middle part of CAP350 , and three with the CAP4 fragment ( Fig . 3A , dark yellow ) , corresponding to the C-terminus of the protein . To confirm these interactions , we first performed co-immunoprecipitation ( co-IP ) experiments from A293T cells co-expressing a green fluorescent protein ( GFP ) -α-catenin fusion protein and myc-tagged versions of either CAP2 or CAP4 fragments of CAP350 ( as represented in Fig . 3B , top panel ) . A CAP1A fragment was also included in the assay as a negative control . The results of these co-IP assays showed that GFP-α-catenin precipitated with both CAP2 and CAP4 fragments but not with the CAP1A fragment ( Fig . 3B , bottom panel ) , suggesting that CAP350 contains two α-catenin binding sites . All isolated clones contained a sequence that is included in the vinculin homology domain 1 ( VH1 ) domain of the protein . To ascertain CAP350 binding to the VH1 domain of α-catenin , we generated two α-catenin-truncated mutants , VH1Cat consisting of the VH1 domain and VH2Cat roughly corresponding to the VH2 domain , to be used as a negative control ( Fig . 3C , top panel ) . VH1 domain of α-catenin co-precipitated in the presence of both fragments , whereas no interaction was detected with the VH2Cat construct ( Fig . 3C , bottom panels ) . Next , we used a lysate of GFP-α-catenin transfected cells to examine whether GFP-α-catenin co-immunoprecipitated with endogenous CAP350 . As shown in Fig . 3D ( top panel ) , anti-CAP350 antibodies co-immunoprecipitated both CAP350 and GFP-α-catenin . Finally , the presence of endogenous CAP350-α-catenin complexes was demonstrated by co-IP experiments in nontransfected MDCKII cells ( Fig . 3D , bottom panel ) . These results reveal the existence of endogenous CAP350 and α-catenin complexes in MDCKII cells . To assess the contribution of α-catenin in CAP350 recruitment to cadherin-based cell-cell contacts , cells treated with small interfering RNA ( siRNA ) against α-catenin were examined by IF 36 h and 72 h after transfection ( Fig . 4A ) . Thirty-six hours after transfection , cells began to detach from each other , but some cell-cell contacts still remained . Under these conditions , both junctional α-catenin and CAP350 stainings were significantly diminished , and only residual α-catenin-CAP350 co-localisation was detected at the remaining cell-cell contacts . Seventy-two hours after α-catenin siRNA transfection , when most cell-cell contacts were disrupted , CAP350 peripheral localisation was completely abolished . WB of α-catenin siRNA transfected cell extracts confirmed almost full depletion of α-catenin after 72 h ( Fig . 4B ) . The amount of CAP350 in α-catenin-depleted cells did not change , indicating that disappearance of CAP350 peripheral labelling was not due to degradation ( Fig . 4B ) . Interestingly , loss of α-catenin and subsequent dissociation of CAP350 resulted in the loss of the polarised pattern of MT cytoskeleton , further supporting the role of cadherin junctions in defining MT network architecture ( Fig . 4C ) . These findings demonstrate that CAP350 is recruited to the AJs in an α-catenin-dependent manner . To characterise the molecular basis of CAP350 function in cell-cell adhesion , we ectopically expressed myc-CAP350 in MDCKII cells ( Fig . 5A ) . As also reported in other cell types [17] , at a low expression level CAP350 targeted the CTR ( S2A Fig . ) . When the expression level increased , myc-CAP350 also associated with MTs , mostly in the pericentrosomal area ( Fig . 5B ) . At a high expression level , the protein covered the whole MT network . Under these conditions , MTs did not arise from the CTR , and some unusually thick , bended MT bundles were observed ( Fig . 5C ) , thus indicating that CAP350 is able to bind to the lattice of cytoplasmic MTs when present in excess . It must be noted that ectopic CAP350 was not detected at cell-cell contacts . Contrary to the endogenous protein , transfected myc-CAP350 was only detected in the insoluble fraction after detergent extraction ( Fig . 5D ) in agreement with the IF results . To investigate whether MT binding could prevent ectopic CAP350 targeting to cell-cell contacts , we expressed a truncated mutant lacking the MT-binding N-terminal domain but containing both α-catenin binding domains and the CTR targeting site ( Fig . 5A ) . Unfortunately , results from these experiments were inconclusive since the truncated mutant was not detected either at cell-cell contacts or at the CTR , probably because of improper folding ( S2B Fig . ) . An even stronger MT-bundling effect was detected when a construct consisting of only the N-terminal MT-binding domain CAP1 was expressed ( Fig . 5E ) . In vitro assays had previously shown that the N-terminal domain of CAP350 directly binds MTs through two independent regions [17] . To provide support to the MT-bundling activity of CAP1 domain , we generated two shorter N-terminal constructs ( Fig . 5A ) corresponding to the two independent MT-binding sites [17] . As shown in Fig . 5F , both truncated mutants were able to decorate MTs ( although with different affinities ) , but none of them exhibited MT-bundling ability , indicating that these two domains have to form part of the same molecule to display this capacity . These experiments suggested that , in addition to its known MT-binding and stabilising properties , CAP350 might possess a genuine MT-bundling capacity . Since CAP350 is able to bind both α-catenin and MTs , we then wondered whether CAP350 could recruit α-catenin to MTs . To answer this question , we carried out in vitro MT co-sedimentation assays . Soluble fractions from control or CAP350-depleted cells were incubated with taxol and assembled MTs sedimented by centrifugation through a sucrose cushion . As a negative control , guanosine-5’-triphosphate ( GTP ) and taxol were not added in parallel assays . As shown in Fig . 5G , α-catenin associated with MTs in a CAP350-dependent manner . Quantification of the ratio of α-catenin and tubulin in MT pellets from control- or CAP350-knockdown cells showed a 2 . 5-fold reduction of the amount of MT-bound α-catenin in the absence of CAP350 ( Fig . 5H ) . Altogether , our results support a model in which CAP350 could bridge adhesion complexes at the plasma membrane to MTs: CAP350 would be recruited to the AJs by interaction between its CAP2 and CAP4 domains and the VH1 domain of α-catenin and , in turn , would bind MTs via its CAP1 domain ( see below ) . In order to evaluate the role of CAP350 in epithelial morphogenesis , MDCKII cells were allowed to polarise for four days in the presence or in the absence of junctional CAP350 . Cells transduced with control lentivirus showed a fully polarised phenotype including ( i ) defined AJs as revealed by staining for either α-catenin ( Fig . 6A ) or E-cadherin ( S2C Fig . ) , ( ii ) an apically located CTR ( Fig . 6A , top ) , and ( iii ) a MT-network with prominent cortical MTs ( Fig . 6B , left ) . In contrast , in cells lacking junctional CAP350 , AJs were strongly perturbed and became wide and undefined ( Fig . 6A and S2C Fig . ) . The CTR remained close to the nucleus ( Fig . 6A , bottom ) , and the apico-basal array of MTs was absent ( Fig . 6B , right ) . Indeed , the MT network of CAP350-knockdown cells resembled that of nonpolarised cells . Tight junctions persisted under these conditions ( see Fig . 6C ) , indicating a selective effect of CAP350 knockdown on AJs . Strikingly , cells lacking junctional CAP350 appeared bigger and flatter than control cells ( see also Fig . 1G ) . To quantify this phenotype , we measured the apical surface enclosed by the ZO-1 signal in mosaic images of confluent layers ( Fig . 6C ) . Quantification of more than 20 , 000 cells revealed a 25% increase in the mean apical surface of knockdown cells ( Fig . 6D ) . This percentage is probably underestimated since a number of cells may not be transduced . The distribution profile of cells ranked by apical area clearly showed a shift towards higher apical area values in depleted cells: the number of cells with the smallest area decreased , whereas the number of cells with highest area increased ( Fig . 6E ) . To find out whether this increase in size is due to defective cell-cell adhesion or to increased cell-substrate adhesion , we also compared the surface occupied by control or depleted cells when they grew isolated . Data indicated no significant differences among them ( Fig . 6F ) . Finally , fluorescence-activated cell-sorting ( FACS ) analysis revealed that the total volume of the cells remained unchanged after CAP350 depletion , suggesting that the increase in the apical area was accompanied by a decrease in height ( S2D Fig . ) . Indeed , flattening of the cells was evident from vertical confocal images ( Fig . 6G ) . Overall , these data demonstrate that CAP350 plays a key role in both AJ and MT-network reorganisation occurring during epithelial polarisation and , in this way , contributes to generate columnar epithelial cell architecture . To gain further insights into CAP350 contribution to epithelial cell morphology , we performed live-imaging analysis of AJ formation and MT dynamics in control or CAP350-knockdown cells . First , we monitored calcium-induced AJ reassembly in GFP-α-catenin expressing cells infected with either control shm4 ( Fig . 7A , left panels , and S1 Movie ) or shCAP lentiviruses ( Fig . 7A , right panels , and S2 Movie ) . Under calcium chelation , α-catenin dissociated from the plasma membrane ( time 0 ) . In cells expressing CAP350 , 30 min after calcium addition α-catenin was already detected at the cell surface , and by 60 min contacts between cells were re-formed . In cells lacking junctional CAP350 , α-catenin accumulated at spotlike junctions at the tips of cellular processes between neighbouring cells . However , these primordial contacts seemed to be unstable and disappeared . By 4 h , stable contacts between CAP350-knockdown cells were not yet established . Extended cell-cell contacts between depleted cells were clearly observed 7 h after calcium addition , although cells still occasionally detached from each other and appeared more mobile than control cells ( S3A Fig . , S3 Movie , and S4 Movie ) . Thus , the absence of junctional CAP350 delays the establishment of cell-cell contacts , probably by interfering with the ability of the cells to extend nascent cadherin-based adhesive contacts , and affects their stability . Then , we performed MT regrowth experiments after nocodazole treatment in the control ( Fig . 7B , top panels ) and junctional CAP350-depleted cells ( Fig . 7B , bottom panels ) that had been allowed to polarise for four days . At 8 min after drug washout , prominent MTs were observed to emanate from the CTR under both conditions . No significant differences were detected either in density or length of CTR-growing MTs . These results indicated that not only the integrity but also MT nucleation activity at the CTR were preserved under our shRNA conditions . By 40 min a dense MT network occupying the whole cytoplasm had been formed in both the control and junctional CAP350-depleted cells . Four hours after drug washout , however , MT organisation was strikingly different: whereas MT network had acquired a polarised phenotype with conspicuous cortical MTs in control cells , the MT network of CAP350-knockdown cells resembled that of nonpolarised cells with long and mostly straight MTs . In order to follow MT dynamics and/or growth during cell polarisation , we generated a tetracycline-inducible MDCKII cell line expressing the microtubule plus-end binding protein 3 ( EB3 ) fused to the fluorescent protein Ruby ( Ruby-EB3 ) . Control or shCAP lentivirus-transduced Ruby-EB3 cells were recorded 12 h after tetracycline addition ( Fig . 7C ) . Alternatively , they were allowed to polarise for four days before recording ( Fig . 7D ) . In nonpolarised cells , both the distribution and the number of EB3 comets were similar either in the presence or in the absence of junctional CAP350 ( Fig . 7C , Fig . 7E , S5 Movie , and S6 Movie ) . MT-nucleating activity of the CTR was also comparable in control or partial CAP350-knockdown cells . By contrast , the pattern of EB3 comet distribution dramatically changed in control cells after polarisation ( Fig . 7D and S7 Movie ) . In fully polarised cells , CTR activity was hardly distinguishable and the EB3 comets decreased in number and acquired a cortical distribution ( Fig . 7E ) . This reduction in centrosomal activity and MT dynamics is in agreement with the increase in MT stability that has been described in fully polarised cells [2 , 22] . In the absence of cortical CAP350 , however , this shift of MT arrangement from a nonpolarised to a polarised state did not take place ( Fig . 7D and S8 Movie ) . Indeed , the number of EB3 comets per cell was similar to that of control nonpolarised cells and four times higher than control polarised cells ( Fig . 7E ) . Taken together , these data support that CAP350 plays an important role in both the AJ formation and MT remodelling that occur during acquisition of columnar epithelial morphology . CAP350 thus emerges as a good candidate to mediate the reciprocal relationship between cadherin-based adhesion and MT cytoskeleton . The effect of CAP350 depletion on epithelial architecture prompted us to study the function of CAP350 on cystogenesis . Consistent with 2-D-cultured cells , CAP350 staining was found at both the CTR , which localises at the apical pole , and the cell-cell junctions in MDCKII control cysts ( Fig . 8A ) . In contrast , FOP exclusively localised at the CTR ( magnifications in Fig . 8A ) . A more careful examination showed that CAP350 labelling intensity inversely correlated with the distance to the apical pole , and therefore , CAP350 overlapped with α-catenin mainly at the most basal half of lateral cell surfaces ( Fig . 8B ) . Knockdown of CAP350 profoundly affected the number , the size , and the morphology of MDCKII cysts . The number of cysts formed from the same number of control- or shCAP-transduced cells plated on Matrigel was reduced by about 50% . Measurement of the diameter of more than 150 cysts revealed a 20% reduction in CAP350-knockdown cyst size compared to control cysts ( Fig . 8C ) . These figures could reflect individual differences in the reduction of CAP350 expression level . It should be noted that successfully formed cysts from shCAP-transduced cells lacked cortical CAP350 but retained CAP350 and FOP at the CTR , which maintained its apical localisation ( Fig . 8D ) . GP135/podocalyxin , an apical marker used to monitor lumen formation [23] , showed that almost 70% of control cysts contained a single lumen ( Fig . 8E ) . However , only 37% of CAP350-knockdown cysts were able to form a single lumen , while the rest contained multiple small lumens ( 42% ) or consisted of cell aggregates without any obvious lumen ( 21%; Fig . 8D and Fig . 8E ) . Since defective cystogenesis can be attributed to cell polarity defects and subsequent mis-segregation of apical/basolateral membranes , we compared the localisation of several polarity markers in control and CAP350-knockdown cysts . In both cases , F-actin and GP135 were enriched at the apical membrane of all lumens , ZO-1 was restricted to the apical cell–cell contact region , and E-cadherin , α-catenin , and β-catenin were located at lateral cell–cell contacts . However , we could occasionally observe intracellular lumens ( yellow arrows in Fig . 8F ) , co-localisation of α-catenin and β-catenin with apical markers ( arrowheads in Fig . 8F ) , and cells containing two apical poles . Furthermore , cadherin-based cell-cell junctions appeared wider and disorganised in CAP350-knockdown cysts . We conclude that the global cell polarisation is taking place in CAP350-knockdown cysts , although a series of minor defects could be observed . Reorganisation of the MT cytoskeleton and the alignment of MTs along the apico-basal axis could be observed by confocal microscopy in the MDCKII cyst ( Fig . 9A ) . In addition , a conspicuous MT network in the basal pole and a meshwork of short MTs at the apical pole of cells could be observed . Strikingly , cysts obtained from CAP350-knockdown cells contained less MTs . Both apical and basal MT networks persisted , but very few vertical MTs could be observed throughout the whole cyst ( Fig . 9B ) . Acetylated tubulin labelling that usually lines the lumen under the F-actin ring maintained its distribution in CAP350-depleted cysts , further suggesting that the apical MT network is retained in CAP350-depleted cysts ( Fig . 9C ) . These results demonstrate that CAP350 is required for organising the apico-basal arrangement of MTs in 3-D-cultured MDCKII cells and is therefore necessary for epithelial architecture . Finally , we aimed to understand the cellular role of CAP350 in the context of a developing organism . To this end , we employed morpholinos to knockdown Cap350 gene expression in medaka fish ( Oryzias latipes ) embryos [24] . A splicing morpholino directed against the exon5-intron5 junction ( MCap350 ) was designed and injected ( 150 μM ) into two-cell medaka embryos ( Fig . 10A ) . The ability of the morpholino to interfere with the splicing of the zygotic Cap350 transcripts was assayed by reverse transcription polymerase chain reactions ( RT-PCRs ) in samples taken from wild-type as well as mock and MCap350-injected stage 15 embryos . Molecular analysis of morphant embryos showed a number of exon5-intron5 aberrant splicing events , which are consistent with the expected retention of intron 5 and the use of alternative ( i . e . , cryptic ) donors of splicing at exon 5 and intron 5 ( Fig . 10B ) . All the anomalous transcripts generated upon MCap350 interference include premature stop codons and hence yield exon-5 truncated forms of Cap350 ( i . e . , including only the first 340 N-terminal amino acids [aas] ) . To evaluate the efficiency of the microinjections , the RNA of the membrane-tagged tracer Lyn_tdTomato was injected alone ( mock injection ) or co-injected with MCap350 . Only those embryos expressing significant levels of Lyn_tdTomato at blastula stage ( stage 11 ) were scored and analysed further . Strikingly , while epiboly progressed normally in mock-treated embryos at stage 15 ( n = 56 ) , in 100% of the MCap350-injected embryos ( n = 76 ) , the blastoderm cells failed to properly migrate and accumulated at the animal pole ( Fig . 10C and Fig . 10D ) . Later during development , MCap350-injected embryos failed to gastrulate and degenerated before neurulation ( stage 18 ) . This observation indicates that CAP350 is required for embryo morphogenesis very early during development , shortly after the onset of zygotic transcription , and suggests that this loss-of-function phenotype corresponds to a severe cellular defect . In agreement with data obtained from MDCKII cells , both MT network and cell contacts , as revealed by α-tubulin and α-catenin immunostainings , appeared disorganised in morphant embryos ( Fig . 10E–J ) .
Our findings identify CAP350 as an essential regulator of the MT architecture during epithelial differentiation . Recruitment of CAP350 to AJs by α-catenin confers to cells the capacity to develop apico-basal MT arrays and thus to acquire a columnar shape . Our data also indicate that , in addition to MT ends anchoring at the ZA , formation of cortical MTs would require MT stabilisation . Finally , they unveil a previously unknown role of α-catenin in coordinating actin and MT cytoskeleton remodelling during epithelial differentiation . We show here that in E-cadherin-expressing cells CAP350 localised at both the CTR and AJs , whereas it was restricted to the CTR in nonepithelial cells or in cells that had lost E-cadherin expression because of oncogenic transformation . Interestingly , the total amount of CAP350 was also significantly reduced under these conditions , suggesting a coordinated regulation of either transcription or stability of both proteins . We also show that CAP350 recruitment to cell-cell contacts depends on both E-cadherin-based adhesion and α-catenin . On the other hand , CAP350-mediated binding of α-catenin to MTs could be demonstrated by MT-sedimentation experiments . Altogether , these results strongly support a role of CAP350 and α-catenin complexes at the AJ–MT interface . Remarkably , blocking of cadherin homotypic binding as well as depleting either α-catenin or junctional CAP350 led to similar perturbations on MT reorganisation during cell polarisation , highlighting the relevance of cadherin-based adhesion in MT regulation . Biochemical approaches together with two-hybrid screening demonstrated that CAP350 could bind the N-terminal VH1 domain α-catenin directly . This domain has been reported to mediate α-catenin binding and α-catenin homodimerisation , which are mutually exclusive interactions [25–27] . Since the VH1 domain is engaged in α-catenin binding at the AJs , the question as to how CAP350 binds to these complexes is intriguing and remains unresolved . Several other proteins , including merlin , centralspindlin , Ajuba , and DLC1 , have been also reported to interact with the VH1 domain of α-catenin , but the mechanism responsible for their targeting to the ZA has not been investigated further [28–30] . CAP350 contains two VH1-binding sites , suggesting that it may bind either two α-catenin monomers or one α-catenin homodimer . However , the asymmetric nature of the recently reported α-catenin dimer structure [31] suggests that CAP350 probably binds α-catenin monomers . Interestingly , a recent work has demonstrated that the complex formed by E-cadherin , β-catenin , and α-catenin is able to bind directly to F-actin under force application [32] . Anchoring of E-cadherin , β-catenin , and α-catenin complexes to actin filaments in polarised cells mainly occurs at the apical-basolateral boundary , where the actin ring develops , and probably involves a set of additional actin-binding or regulatory proteins [33] . We showed in the present work that CAP350 was absent from this region and instead co-localised with a fraction of basolateral E-cadherin , β-catenin , and α-catenin complexes . Indeed , whereas E-cadherin , β-catenin , and α-catenin stainings in MDCKII cells forming cysts extended from the apical ZA to the basal membrane , CAP350 localisation was restricted to the basal half of the lateral contacts , being excluded from the ZA . This suggests that , in addition to α-catenin , other , as-yet-unknown factors should collaborate to confer this differential localization . This spatial segregation also suggests that α-catenin may participate in different cadherin-based complexes located at specialised membrane regions , where it may perform specific functions: ZA-located α-catenin could regulate actin dynamics , whereas basolateral α-catenin could participate in MT reorganisation . Further supporting this view , junctional CAP350-depleted cells exhibited perturbed AJs but an apparently intact ZA . Cell-cell junction formation and MT reorganisation are multistep and interdependent processes . Our data point out a role for CAP350 in several steps of the process . Recruitment of CAP350 to the cell surface occurred shortly after membrane contact formation between neighbour cells both in normal growth conditions and after calcium addition . The binding of α-catenin to E-cadherin and β-catenin complexes preceded CAP350 recruitment , thus suggesting that CAP350 binds to preassembled E-cadherin , β-catenin , and α-catenin complexes . Accordingly , CAP350 depletion did not prevent α-catenin association to cell-cell contacts nor did it induce its dissociation . However , our in vivo experiments demonstrated that CAP350 participates in the formation of AJs . This agrees with previous data showing that MTs are required for AJ assembly in tumour cell lines [9] and for AJ turnover in polarising epithelial cells in Drosophila [34] . A role for β-catenin-bound dynein in capturing MTs in developing cell-cell contacts has been reported [35] . It is worth keeping in mind that , in addition to its N-terminal MT-binding domain , CAP350 contains a CAP-Gly domain and two putative end binding protein 1 ( EB1 ) -interacting sites that could mediate binding to MT plus ends . It could be speculated that two different complexes containing either β-catenin and dynein or α-catenin and CAP350 cooperate during AJ assembly by providing both tethering and stabilising activities . Interestingly , α-catenin and CAP350 complex properties and behaviour clearly contrast with those of the p120-catenin , Pleka7 , and CAMSAP-3 system [13] . CAMSAP-3 specifically localises at the ZA , whereas CAP350 localises at the basolateral membranes . In addition , CAMSAP-3 is recruited to cell junctions only in the mature cell-cell contacts and therefore appears to be more important for their maintenance than for their formation . While CAMSAP-3 may function by anchoring MT minus ends to the ZA once the apico-basal MT array has been established , its potential role in MT reorganisation during polarisation remains still to be investigated [14] . Taken together , this evidence suggests complementary roles for these two MT-regulatory systems during apico-basal polarisation . Alpha-catenin and CAP350 complexes would act earlier , regulating AJ formation and the concurrent transition from a radial mesenchymal array to an apico-basal epithelial architecture . In the latter stages of the differentiation process , recruitment of CAMSAP-3 and KIFC3 to ZA could serve to anchor MT minus ends at the ZA . Based on the perturbations induced by full CAP350 depletion on MT organisation , a role for CAP350 in MT-minus-end anchoring at the centrosome was proposed [16] . However , CAP350 also associated with MTs in the Golgi area [17] , and its related plant protein TRM1 was found to bind to cortical MTs [19] . These results , together with the present work , argue against a restricted role in MT-minus-end anchoring . More work is necessary to clarify whether CAP350 is a specific MT-minus-end-binding protein or if it plays a more general role in MT dynamics . The presence of two tandem MT-binding sites in the N-terminal domain of CAP350 , both of which are required for its putative MT-bundling activity , provide mechanistic insights on how CAP350 could participate in the formation of apico-basal MT arrays . Interestingly , junctional CAP350-depleted cysts contained few cortical apico-basal MTs , whereas the apical and basal MT networks were preserved . This supports the hypothesis that junctional CAP350 depletion does not affect global MT dynamics but does affect the stabilisation of cortical MTs specifically . Indeed , junctional CAP350-depleted-cells exhibited a robust MT-nucleating activity at the CTR and were able to develop a dense MT network , as shown by Ruby-EB3 live-imaging experiments during MT regrowth . However , contrary to control cells , CAP350-depleted cells lacked cortical MTs . The absence of cortical MTs may contribute to defective lumen formation . Only a few studies about the contribution of MTs to spatial orientation of apico-basal polarity are available [36 , 37] . Notably , our results indicate that CAP350-dependent stabilisation of cortical MTs is not essential for segregation of apical and basolateral domains nor for CTR or Golgi Apparatus ( GA ) relocation to the apical pole , which is in agreement with the fact that these relocations take place before MT reorganisation is completed . Indeed , analysis of apical exocytosis in polarising MDCKII cells revealed that efficient secretion of apical proteins occurs well before completion of MT array rearrangement [38] . Strikingly , knockdown of CAP350 in medaka embryos blocked epiboly . Epiboly , the spreading of the blastoderm over the large yolk cell , is considered the first morphogenetic movement of the teleost embryo . Given that epiboly occurs shortly after the onset of zygotic transcription at stage 12 and that the morpholino only interferes with spliced zygotic transcripts , it is likely that CAP350 has an essential and general role in tissue morphogenesis . This early arrest of development in epiboly prevented further analysis of CAP350 during embryogenesis but allowed us to confirm in a developing organism the results obtained in polarised kidney cells . CAP350-depleted blastoderm cells exhibited defects in cell-cell adhesion and MT organisation . These defects can account for the block in epibolic movement , since both E-cadherin and MTs have been shown to be essential for epiboly; however , the underlying molecular mechanism remains to be elucidated . In conclusion , this work reveals an essential role of the CAP350-α-catenin complex in defining the polarised columnar architecture of epithelial cells . Epithelial polarity and tissue architecture are compromised at early stages of epithelial-to-mesenchymal transition , a critical step in carcinoma progression and metastasis . Whether the CAP350-α-catenin complex somehow participates in this transition deserves further analysis .
Medaka experiments were performed in accordance with the guidelines of the “Comité de Ética CSIC” . MDCKII cells were cultured in MEM containing 10% FBS or grown in 3-D Matrigel cultures ( BD ) , as previously described [39] . Briefly , cells were trypsinized to a single suspension at 5 x 103 cells/ml in complete medium containing 2% Matrigel . Suspensions were plated into chamber glass slides ( BD Falcon ) precoated with 100% Matrigel . MDCK cysts were grown for four days , and the medium was renewed every two days . Human embryonic kidney A293T cells were cultured in DMEM supplemented with 10% FBS , l-glutamine , and penicillin-streptomycin . MCF10A and the MCF10A-derived cell line NeuT were grown in DMEM/F12 medium supplemented with 5% horse serum , 0 . 5 μg/ml hydrocortisone , 10 μg/ml insulin , 100 ng/ml cholera toxin , 20 ng/ml epidermal growth factor , l-glutamine , and penicillin-streptomycin . HDFs were grown in basal medium supplemented with 10% FBS , Fibroblast Growth Supplement ( FGS , Innoprot ) , and penicillin-streptomycin . All cells were maintained in a 5% CO2 humidified incubator at 37°C . Yeast two-hybrid screening was performed on a random-primed cDNA library from human PAZ-6 cell line . The library was transformed into the Y187 yeast strain . The cDNAs encoding N-terminal ( 1–983 aa ) , C-terminal ( 2590–3118 aa ) , or internal ( 985–1929 aa ) regions of hCAP350 were inserted into the pB27 bait plasmid . Forty-five , 87 , and 46 million interactions were tested , and 294 , 322 , and 357 positive clones , respectively , were picked and analysed . The corresponding prey fragments were amplified by PCR and sequenced at their 5ʹ and 3ʹ junctions . These sequences were used to identify the corresponding gene in the GenBank database ( National Center for Biotechnology Information ) using a fully automated procedure . Cells were treated with 4 mM EGTA ( Sigma-Aldrich ) for 2 h or 10 M Nocodazole ( Sigma-Aldrich ) for 3 h . Monoclonal anti-α-tubulin , anti-γ-tubulin , anti-acetylated-tubulin , anti-vinculin anti-c-myc , rat monoclonal anti-E-cadherin ( DECMA-1 ) , rabbit polyclonal anti-α-catenin , anti-β-catenin , and anti-α-tubulin antibodies were purchased from Sigma-Aldrich . Mouse monoclonal anti-α-catenin was obtained from Santa Cruz Biotechnology . Mouse monoclonal anti-E-cadherin and anti-β-catenin antibodies were from BD Biosciences . Rabbit polyclonal anti-ZO-1 was from Invitrogen . Rabbit polyclonal anti-GFP and anti-myc were purchased from ICL . Mouse monoclonal anti-GFP was purchased from Roche . Rabbit polyclonal anti-pericentrin was purchased from Covance . Mouse monoclonal anti-Hsp70 antibody was obtained from Abcam . Rabbit polyclonal anti-CAP350 antibodies ( 450–500 and 3066–3116 aa ) were from Novus Biologicals . Rhodamine-phalloidin used to label F-actin was purchased from Sigma-Aldrich . Rabbit anti-GMAP210 has been previously characterised [40] . Goat polyclonal anti-CAP350 and rabbit polyclonal anti-FOP were kindly provided by E . Nigg ( Biozentrum , University of Basel , Switzerland ) . Rabbit anti-GM130 and mouse anti-GP135 were kind gifts from Y . Misumi ( Fukuoka University , Japan ) and G . Ojakian ( New York , United States ) . All secondary antibodies conjugated to DyLight fluorophores were from Jackson ImmunoResearch . Anti-IgG peroxidase-labelled secondary antibodies were from Amersham . To generate CAP350 monoclonal antibodies , a construct containing amino acids 1875–2055 of human CAP350 was inserted into the expression vector pET28a ( + ) , expressed in Escherichia coli strain BL21 , and affinity purified using HIS-Select Nickel Affinity Gel according to the manufacturer's protocol . CAP350 monoclonal antibodies were generated by Protein Tools Unit , CNB/CSIC ( Madrid , Spain ) . Stable RNAi was achieved by lentiviral shRNA . RNAi sequence against human CAP350 was 5ʹ-GTTACTCAGATGAACGATA-3ʹ . RNAi sequences against canine CAP350 ( shCAP1 5ʹ-TTAAGAAGCAACCTGGAACAGTTGA-3ʹ , shCAP-2 5ʹ-GCAGCAAGAGAAGGCAGAAATTAAA-3ʹ , and shCAP3 5ʹ-AAGAGATGGAGCTAATTTCTTTGTG-3ʹ ) were designed by using the BLOCK-iT RNAi Designer ( Invitrogen ) . As controls , a shRNA containing four point mutations was used . Sequences were submitted to BLAST search to ensure targeting specificity . Complimentary oligonucleotides containing the shRNA sequences were synthesized with BglII and HindIII overhangs and were purchased from Sigma-Proligo . Oligonucleotides were annealed and cloned into pSUPER . Next , the H1 polymerase promoter-shRNA sequence cassette was removed with EcoRI/ClaI and ligated into the lentiviral vector pLVTHM ( Addgene plasmid 12247 ) . Two different versions of each lentivirus were generated: +GFP and −GFP . All inserts were sequenced . Experiments in MDCKII cells were carried out by infection with a mix of the three lentiviruses ( named shCAP ) , unless otherwise indicated . Virus production was performed according to standard protocols . 293T cells were plated the day before transfection to ensure them to be in the exponential growth phase at the moment of transfection . The pLVTHM vector , the packaging ( psPAX2 ) plasmid , and the envelope plasmid ( pMD2 . G ) ( proportion 3:2:1 ) were co-transfected , and after 48 h and 72 h , viral supernatants were collected , combined , filtered through 0 . 45 μm PVDF filter ( Fisher Scientific ) , and concentrated by ultracentrifugation ( Beckman Coulter ) . For biochemical experiments , cells were extracted by incubating with 0 . 02% saponin and 0 . 02% BSA or 1% Triton X-100 in Pipes-Hepes-EGTA-MgCl2 ( PHEM ) buffer containing protease inhibitors for 5 min at room temperature ( RT ) . Soluble fractions were centrifuged at 16 , 000 g for 20 min and supernatant collected . Insoluble fractions were solubilized with Laemmli sample buffer . SDS-PAGE , WB , IPs , and MT-pelleting assays were performed as described [41] . Densitometric analysis was performed on scanned images using Image Quant 5 . 2 software ( GE Healthcare ) . All CAP350 fragments ( 1–900 , 1–560 , 555–900 , 976–1931 , 2468–3117 aas ) were obtained by PCR using pCS2-MT-CAP350 full length as template and EcoRI and XhoI restriction sites onto their 5ʹ and 3ʹ respectively to allow subclone into pCS2-MT 6 Myc vector . To generate ΔNCAP350 ( 976–3117 ) a fragment corresponding to 1720–3117 aas was obtained by PCR introducing StuI and XhoI restriction sites and by using pCS2-MT-CAP350 full length as template . Subsequently , pCS1-MT-CAP2 ( 976–1931 ) was digested with StuI and XhoI and the resulting vector was isolated and fused to 1720–3117 fragment . peGFP-CEP1 ( 1–900 aa ) was generated by PCR by introducing EcoRI and BamHI sites . peGFP-α-catenin was a gift from Prof . J . Nelson . Both constructs of α-catenin ( 1–291 and 219–730 aa ) were obtained by PCR introducing EcoRI and SalI sites and subcloned into peGFP-C2 . Cells were transfected with either Lipofectamine2000 or by using Neon Transfection System ( Invitrogen ) according to the manufacturer's instructions . To deplete α-catenin in MDCKII cells , we used the following siRNA: 5ʹ AUAACCUGAGGACAGAGGGCUUCUA 3ʹ . Scrambled siRNA was used as the control . Duplexes were obtained from Life Technologies and Sigma-Aldrich . siRNA transfection was performed with Neon Transfection System ( Invitrogen ) by following instructions from the supplier . Assays were performed 36 h and 72 h after transfection . Cell size analysis was done by flow cytometry . Measures were performed on a BD FACSCalibur flow cytometer ( Becton Dickinson , US ) . Forward scatter height ( FSC-H ) was used as a measure of the cell size and was determined in MDCKII cells expressing either control or CAP350 shRNAs . For immunofluorescence experiments , cells were grown on coverslips and fixed in either 100% methanol at −20°C for 6 min or 4% paraformaldehyde for 10 min at RT and permeabilised with 0 . 5% Triton X-100 . Alternatively , cells were extracted with 0 . 3% Triton X-100 for 30 s at 37°C before fixation . Then , cells were incubated with primary antibodies for 1 h at RT , washed with 0 . 1% PBS-Tween , and incubated with the appropriate fluorescent secondary antibody for 40 min . Nuclei were counterstained with DAPI ( 1 μg/ml ) after secondary antibody labelling . MDCKII cysts were processed for immunofluorescence as follows: cysts were rinsed twice with DPBS ( Sigma ) containing CaCl2 and MgCl2 , fixed with shaking for 30 min with 4% paraformaldehyde in DPBS , and permeabilised for 15 min with 0 . 5% triton in DPBS . To improve the staining of some centrosomal proteins , samples were treated with 0 . 5% SDS in DPBS for 10 min . After washing , nonspecific binding sites were blocked by rocking for 30 min in DPBS , 0 . 025% saponin , and 3% BSA . Samples were incubated overnight with primary antibodies at 4°C . Cysts were then rinsed three times with blocking buffer and incubated with secondary antibodies conjugated to DyLight fluorophores for 90 min at RT . Nuclei were counterstained with DAPI . Finally , samples were extensively washed with blocking buffer and DPBS and mounted in ProLong ( Molecular Probes ) . Stage 15 embryos were fixed in 4% paraformaldehyde in PBS overnight at 4°C . After chorion removal , embryos were washed in PBS and blocked for 2 h in PBS containing 0 . 2% Tween ( PBT ) , 1% DMSO , and 10% FCS ( blocking solution ) . Whole embryos were incubated overnight at 4°C with primary antibodies diluted in blocking solution . After washing in PBT , samples were incubated with Alexa-conjugated ( Molecular Probes ) secondary antibodies for 3 h at RT . After final rinses , embryos were counterstained with DAPI ( 5 μg/ml ) and mounted with PBS/glycerol . A Ruby-EB3-inducible cell line was generated using the Flp-In T-REx system ( Invitrogen ) according to the manufacturer's instructions . Briefly , a MDCKII host cell line was obtained in a two-step procedure . In the first step , MDCKII cells were transfected with pFRT/lacZeo2 followed by selection with 500 μg/ml Zeocin ( Invitrogen ) . Single-copy integrants were identified by Southern blot analysis and β-galactosidase expression was analysed to identify clones with integration of the pFRT/LacZeo2 plasmid into a high-expression site ( β-Gal Staining Kit , Invitrogen ) . In a second step , MDCKII cells were transfected with pcDNA6/TR and selected with 10 μg/ml Blasticidin ( InvivoGen ) until colonies formed . To generate stable Flp-In T-REx MDCKII cells containing Ruby-EB3 , EB3 was excised from mCherry-EB3 and inserted into pcDNA5/FRT/TO-neo-Ruby ( kindly provided by Dr . J . Pines ) between BamHI and NotI sites to create the plasmid pcDNA5/FRT/TO-neo-Ruby-EB3 . This was co-transfected with pOG44 ( 1:9 ) into MDCKII host cells , and proper recombination events were selected with 500 μg/ml G418 ( InvivoGen ) . To induce Ruby-EB3 expression , cells were treated with 0 . 1 μg/ml tetracycline for 12 h before the assay . Stable cells were maintained in culture with tetracycline-free FBS ( Clontech ) to avoid background expression of the protein . Confocal images were captured using either TCS SP5 or TCS SPE confocal Leica laser scanning systems equipped with DMI60000 and DM 2500 microscopes , respectively , and a HCX PL APO Lambda blue 63x 1 . 4 OIL objective at 22°C . Images correspond to maximal projections or optical sections according to each experiment . Mosaic images were automatically acquired with a Nikon eclipse Ti-e microscope controlled by NIS-Elements imaging software ( Nikon ) and using the scan-large-image tool . For in vivo imaging experiments of AJ reassembly , cells expressing either control or CAP350 shRNAs ( GFP- ) were plated onto 35-mm glass-bottom dishes ( IBIDI ) , transfected with peGFP-α-catenin and cultured in phenol red–free MEM . Two hours after EGTA addition , cells were washed , and transfected cells were identified and recorded at 37°C every 8 or 15 min for 5 or 12 h ( as indicated ) with an inverted microscope ( DM16000; Leica ) equipped with a camera ( ORCA-ER; Hamamatsu Photonics ) and using an HCX Plan Apochromat CS 63×/1 . 4 NA oil objective . For time-lapse experiments to visualise MT dynamics , Ruby-EB3-inducible MDCKII cells were plated three days after infection with shCAP lentivirus ( GFP+ ) . Noninfected Ruby-EB3-inducible MDCKII cells were also plated . The day after , Ruby-EB3 expression was induced for 12 h , and cells were recorded every 24 s for 288 s . For quantification of the area covered by isolated cells , cells were plated at a density of 10 , 000–20 , 000 cells/ml and analysed the day after seeding . Image processing was carried out using the Leica ( LAS ) and Adobe Photoshop softwares . For presentation , whole images were adjusted for intensity level , contrast , and/or brightness . Quantification of cell surface was performed using the multiwave length cell-scoring module of Metamorph Offline software . Cyst diameter was calculated with ImageJ and the command Multimeasure . The cyst section with the widest transverse diameter was chosen for image analysis . For quantification of lumen formation , MDCKII cysts were phenotypically classified into three groups based on GP135 staining: single-lumen cyst ( single central lumen ) , multiple-lumen cyst ( ≥two lumens ) and aberrant cyst ( cell aggregate without visible lumen ) . More than 200 cysts from randomly selected fields were examined under each condition . For quantification of centrosomal CAP350 fluorescence intensity , mosaic images were processed with Metamorph Offline software . After background subtraction , resulting objects were detected by using the “create regions around objects” command and objects’ intensities were estimated with the “region measurements” tool . For calculation of the number of EB3 comets , cells with comparable levels of Ruby-EB3 expression were selected and processed with the ImageJ software . Regions were created around selected cells , and image background fluorescence was corrected . The number of Ruby-EB3 comets per cell was calculated by using the “analyse particles” command . Frame 5 of each movie was selected for quantification . Between ten to fifteen cells of each group were quantified . To inhibit E-cadherin-mediated junction formation , we incubated MDCKII cells with 48 μg/ml anti-E-cadherin antibody ( Monoclonal Anti-Uvomorulin/E-Cadherin clone DECMA-1 , Sigma-Aldrich , U3254 ) in complete medium for 72 h; control experiments were run with cells incubated with a control IgG under the same conditions . Medaka fish ( O . latipes ) from the wild-type line Cab were kept as a closed stock . Embryos were staged as described [42] . A splicing morpholino ( Gene Tools ) directed against the medaka cap350 exon5-intron5 junction was designed using as a template the medaka EST m010—E1_007 ( Genebank: FM166216 ) . The following morpholino was synthetized and injected: MCap350E5-I5: 5′-AATCCTTGAGACCAAATACCTTTAT-3′ . Morpholino-induced splicing interference was monitored by RT-PCR in samples from wild-type and morpholino-injected embryos . To this end , total RNA was extracted from stage 15 embryos ( TRIzol , Invitrogen ) , and RT reactions were performed ( Super Script III , Invitrogen ) . The following primers were used in RT-PCR experiments: Ctrl_ MCap350E5_fw: 5′- CAGAGGCAACATCTGGAGGAGG- 3′ Ctrl_ MCap350E7_rv: 5″- CGAGTCTATGGACCTTCCTAACTG- 3′ The vector pCS2+:Lyn_tdTomato was used as a template to synthesize capped RNA for the membrane-tagged tracer Lyn_tdTomato . Capped RNA was synthesize using the mMessage Machine Kit ( Ambion ) and column purified ( Qiagen RNeasy ) . To monitor the success of the morpholino injection , the tracer was co-injected ( 50 ng/μl ) with the morpholino ( 150 μM ) into two-cell stage medaka embryos . Microinjected embryos were then examined under the fluorescence binocular ( Olympus SZX16 ) and processed for immunofluorescence . Quantitative data are expressed as mean ± SD . Significant differences were evaluated by Student’s t test or ANOVA as appropriate ( GraphPad Prism software ) . | Epithelia cover all the surfaces of and the cavities throughout the body and serve as barriers between the organism and its external environment . Epithelial differentiation requires the coordination in space and time of several mechanisms that ultimately lead to the acquisition of distinctive epithelial features , including apical-basal polarity , specialised cell-cell junctions , and columnar shape . Epithelial differentiation also induces the reorganisation of three cytoskeletal networks: actin filaments , intermediate filaments , and microtubules . In simple epithelia , cadherins and their cytoplasmic binding partners catenins play a crucial role in connecting cell-cell junctions to the actin cytoskeleton . The cadherin extracellular domain forms adhesive contacts between adjacent cells , and their cytoplasmic tail indirectly binds the actin-binding protein α-catenin , thus linking cell-cell junctions to the underlying actin cytoskeleton . We report here an additional role of α-catenin in remodelling microtubules during epithelial differentiation . In most epithelial cells , microtubules are organised as parallel bundles aligned along the apico-basal axis and as apical and basal plasma membrane-associated networks . We demonstrate that the microtubule-binding protein CAP350 , which is only localised at the centrosome in most cells , is also recruited at cell–cell junctions in epithelial cells through its binding to α-catenin . In the absence of junctional CAP350 , microtubules are unable to reorganise in bundles , and cells do not acquire columnar shape . Our results suggest that recruitment of centrosomal proteins to cell-cell junctions could be a general mechanism to control microtubule reorganisation in neighbour cells during epithelial differentiation . | [
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] | [] | 2015 | Alpha-catenin-Dependent Recruitment of the Centrosomal Protein CAP350 to Adherens Junctions Allows Epithelial Cells to Acquire a Columnar Shape |
Carbon Catabolite repression ( CCR ) allows a fast adaptation of Bacteria to changing nutrient supplies . The Pseudomonas aeruginosa ( PAO1 ) catabolite repression control protein ( Crc ) was deemed to act as a translational regulator , repressing functions involved in uptake and utilization of carbon sources . However , Crc of PAO1 was recently shown to be devoid of RNA binding activity . In this study the RNA chaperone Hfq was identified as the principle post-transcriptional regulator of CCR in PAO1 . Hfq is shown to bind to A-rich sequences within the ribosome binding site of the model mRNA amiE , and to repress translation in vitro and in vivo . We further report that Crc plays an unknown ancillary role , as full-fledged repression of amiE and other CCR-regulated mRNAs in vivo required its presence . Moreover , we show that the regulatory RNA CrcZ , transcription of which is augmented when CCR is alleviated , binds to Hfq with high affinity . This study on CCR in PAO1 revealed a novel concept for Hfq function , wherein the regulatory RNA CrcZ acts as a decoy to abrogate Hfq-mediated translational repression of catabolic genes and thus highlights the central role of RNA based regulation in CCR of PAO1 .
The opportunistic human pathogen Pseudomonas aeruginosa causes acute as well as chronic infections in immunocompromised individuals . Moreover , airway epithelia of patients suffering from cystic fibrosis are frequently colonized by the pathogen [1] . P . aeruginosa is a metabolically versatile organism with the ability to utilize numerous carbon sources , which allows the bacterium to thrive in different environments such as soil , marine habitats as well as on/in different organisms [2] . In Bacteria , the uptake and utilization of carbon compounds is controlled in a hierarchical manner by a mechanism known as carbon catabolite repression ( CCR ) . Generally speaking , CCR prevents the utilization of less preferred carbon sources until the preferred one is consumed . In Escherichia coli CCR prevents the expression of catabolic genes , the transcription of which requires the transcriptional activator CRP ( cyclic AMP receptor protein ) in conjunction with cAMP , whereas in Bacillus subtilis CCR is mediated by the transcriptional repressor CcpA ( catabolite control protein A ) . In both organisms CCR is regulated by a signal transduction pathway inherent to the phosphoenolpyruvate-carbohydrate phosphotransferase system [3] . In most studied Pseudomonas spp . the presence of organic acids ( for example succinate ) results in CCR , which leads to repression of catabolic genes required for the consumption of other carbon sources . During CCR catabolic genes were deemed to be down-regulated by the translational repressor Crc ( catabolite repression control protein ) [4] . It has been suggested that Crc binds to CA-rich motifs within or adjacent to ribosome binding sites ( RBS ) of multiple target mRNAs , and thereby prevents their translation [5]–[7] . Upon relief of CCR , the regulatory RNAs , CrcZ in PAO1 [7] , CrcZ/CrcY in P . putida [8] and CrcZ/CrcX in P . syringae [9] were proposed to bind to and to counteract Crc by trapping the protein . This hypothesis was in line with the observation that the CrcZ levels increase in the presence of poor carbon sources , and that they are reduced in the presence of a preferred carbon source [7] . However , our recent structural and biochemical studies challenged the role of Crc as a direct translational repressor of genes governed by CCR in PAO1 . Recombinant Crc purified to homogeneity did neither bind to amiE mRNA , encoding aliphatic amidase , nor to CrcZ RNA [10] , [11] . Rather , the previously reported RNA binding activity of His-tagged Crc purified by nickel affinity chromatography [6] , [7] was attributed to a contamination of the Crc-His preparations with the RNA chaperone Hfq [10] , [11] . In Enterobacteriaceae Hfq is pivotal for riboregulation [12] , [13] , which results on the one hand from binding to and protection of sRNAs from nucleolytic decay [14] , and on the other hand from accelerating base-pairing between sRNAs and their target mRNAs [15]–[17] . E . coli Hfq hexamers have dedicated RNA binding sites , preferably binding uridine-rich stretches of sRNAs around the central pore of the proximal surface [18] , [19] and A-rich sequences on the distal surface [20] . In addition , the lateral surface of the hexamer can as well contribute to sRNA binding [21] . The dedicated sRNA and mRNA binding surfaces on either site of the Hfq-hexamer may serve to transiently increase the local concentration of two RNA substrates . Moreover , the inherent capacity of Hfq to induce conformational changes in RNAs together with the observed structural flexibility of RNA ligands bound to Hfq could stochastically facilitate base-pairing [22] , [23] . Although many sRNA candidates have been identified in PAO1 [24]–[27] , the function of only a few has been revealed . The sRNAs PhrS [28] and PrrF [29] have been shown and inferred , respectively , to act by base-pairing with target mRNAs , whereas the protein binding RNAs RsmY and RsmZ are known to antagonize the function of the translational regulator RsmA [30] . PAO1 Hfq was shown to stabilize the protein binding RNA RsmY [31] , [32] and to affect expression of some sRNAs including PhrS [25] . In PAO1 , Hfq acts as a pleiotropic regulator , impacting on growth , virulence , motility , and quorum sensing [31] , [33] . A transcriptome analysis of a PAO1hfq- strain revealed that ∼15% of all genes were de-regulated . These included a number of genes encoding proteins involved in carbon compound catabolism , which were up-regulated in the absence of Hfq [31] . Here , we studied the impact of Hfq on CCR in PAO1 . In vivo and in vitro studies revealed that Hfq acts as a translational repressor of several catabolic genes . Moreover , we present evidence that the regulatory RNA CrcZ binds to and sequesters Hfq , which in turn results in translation of Hfq-regulated mRNAs . Hence , this study revealed a novel mechanistic twist on post-transcriptional regulation by Hfq and highlights its role in regulating the central metabolism in P . aeruginosa .
Several observations suggested a link between Hfq and CCR in PAO1 . A comparative transcriptome analysis of a PAO1 wt and a PAO1hfq- strain disclosed transcripts encoding functions related to carbon compound and amino-acid catabolism that were up-regulated in the absence of Hfq ( [31]; Table S1 ) . Many of these transcripts comprise A-rich stretches ( Table S1 ) within or adjacent to the RBS , which could serve as recognition motifs for the distal poly-A binding site of Hfq [20] , [34] . Mutations within these A-rich stretches in certain mRNAs abrogated CCR [7] , [35] . Crc was deemed to act as a translational regulator in PAO1 CCR [5]–[7] . However , Crc was recently shown to be deficient in binding to CrcZ and to the CCR regulated amiE mRNA [10] . In fact , these studies identified Hfq as a contaminant RNA binding activity in Crc preparations [10] , [11] . This observation prompted us to test ( i ) whether Hfq serves as the principle post-transcriptional regulator of CCR in PAO1 , and ( ii ) whether the regulatory RNA CrcZ , displaying several A-rich motifs [7] , might abrogate Hfq-mediated regulation by sequestering Hfq . We first revisited post-transcriptional regulation of amiE mRNA , encoding an aliphatic amidase . Strain PAO1 ( pTCamiE ) and strain PAO1 ( pME9655 ) harboring a plasmid borne transcriptional amiE-lacZ and a translational amiE::lacZ fusion , respectively , were grown in BSM medium either in the presence of succinate/acetamide ( CCR ) or mannitol/acetamide ( no CCR ) . Acetamide was added to induce transcription of the chimeric amiE genes , i . e . to mimic CCR . As shown in Figure S1A ( left panel ) , the β-galactosidase activities conferred by the transcriptional fusion was comparable in either medium , i . e . in the presence and absence of CCR . However , when compared with growth in the presence of mannitol/acetamide ( no CCR ) , amiE::lacZ translation was repressed in strain PAO1 ( pME9655 ) ( Figure S1A; right panel ) during cultivation in the presence of succinate/acetamide , i . e . when CCR was in place . We next tested whether amiE mRNA and CrcZ RNA associate with Hfq upon induction of amiE transcription during CCR . Strain PAO1hfq- harboring plasmid pMMBhfqFlag ( encodes flag-tagged Hfq ) and the control plasmid pMMB67HE , respectively , was grown to an OD600 of 1 . 5 in BSM medium supplemented with succinate . In addition , acetamide was added to induce transcription of the amiE gene , i . e . to mimic CCR . Then , cell lysates were prepared and Hfq-associated RNAs were co-immunoprecipitated ( CoIP ) with Hfq-specific antibodies . As revealed by RT-PCR both , amiE and CrcZ , were found in complex with Hfq ( Figure S2 ) . In contrast RsmZ , which does not bind to Hfq [7] , could not be detected among the RNAs that co-immunoprecipitated with Hfq ( Figure S2 ) . Taken together , these initial studies validated amiE as a model mRNA to scrutinize the hypothesized role of Hfq in CCR . To obtain first hints whether Hfq is involved in post-transcriptional regulation of amiE during CCR , the strains PAO1 , PAO1hfq- , PAO1Δcrc and PAO1hfq-Δcrc were transformed with plasmid pTCamiE harboring the transcriptional amiE-lacZ fusion and with plasmid pME9655 harboring the translational amiE::lacZ fusion , respectively . The strains were grown in BSM medium in the presence of succinate to establish CCR , and in the presence of acetamide to induce amiE-lacZ/amiE::lacZ transcription . The β-galactosidase activity conferred by the transcriptional amiE-lacZ fusion was comparable in the presence and absence of Hfq and/or Crc in either strain ( Figure S1B ) . In contrast , the β-galactosidase activity conferred by the translational amiE::lacZ fusion differed in strains PAO1 , PAO1hfq- , PAO1Δcrc and PAO1hfq-Δcrc when grown in BSM medium containing succinate and acetamide ( CCR ) . In contrast to PAO1 , amiE::lacZ translation was greatly increased in the PAO1hfq- strain and in the PAO1hfq-Δcrc double mutant , respectively ( Figure 1A ) . The absence of Crc resulted as well in marked amiE::lacZ translation , albeit at a lower level when compared with the hfq- mutant or the hfq-Δcrc double mutant , suggesting that Hfq exerts a more pronounced negative effect on amiE translation during CCR than Crc . To verify these experiments , we tested whether Hfq likewise affects translation of the estA and the phzM genes , which are also known to be regulated by CCR [7] , [35] , [36] . The impact of Hfq was again monitored using translational lacZ reporter gene fusions . The results obtained mirrored those obtained with the amiE::lacZ reporter gene . Their translation was repressed during growth of PAO1 in BSM medium containing succinate , whereas in the absence of Hfq , Crc or both , the synthesis of the encoded fusion proteins increased ( Figures 1B and C ) . In contrast , the expression of the heterologous lacZ gene ( variation control ) , was comparable in strains PAO1 , PAO1hfq- , PAO1Δcrc and PAO1hfq-Δcrc ( Figure S1C ) . Taken together , these initial studies supported our hypothesis that Hfq is involved in post-transcriptional regulation of CCR regulated genes . As shown in Figure 1A–C , both , Crc and Hfq , were required for full repression of all three CCR regulated genes . Although translation occurred in the absence of Crc , a pronounced increase in translation only required the absence of Hfq , i . e . the observed de-repression was comparable in the hfq- strain and in the hfq-Δcrc double mutant . We interpreted this as showing that Hfq acts as the principal translational repressor , whereas Crc seemed to act as an auxiliary factor , somehow amplifying the negative regulation exerted by Hfq . To further test this hypothesis , amiE::lacZ translation was monitored in the PAO1hfq-Δcrc double mutant complemented with a plasmid borne crcFlag and hfqFlag gene , respectively . In consideration that crc could impinge on hfq expression and vice versa , the plasmid pMMBcrcFlag and pMMBhfqFlag borne crcFlag and hfqFlag genes , respectively , were equipped with the same expression signals , i . e . their expression was controlled by the Ptac promoter and identical translation initiation signals . The different strains used in this experiment were grown in BSM medium supplemented with succinate and acetamide ( CCR ) . At an OD600 of 1 . 0 , IPTG was added to induce ectopic expression of the crcFlag and hfqFlag genes , respectively . Three hours thereafter , amiE::lacZ translation was monitored by determination of the β-galactosidase activities and the Crc-Flag and Hfq-Flag levels were determined by quantitative western-blot analysis . As shown in Figure 1D ( blue bar ) , under these conditions amiE::lacZ translation was repressed in strain PAO1Δcrc ( pMMBcrcFlag; pME9655 ) . In contrast , translation of the amiE::lacZ fusion gene was de-repressed in the absence of Hfq in the double mutant PAO1hfq-Δcrc ( pMMBcrcFlag; pME9655 ) ( Figure 1D; red bar ) . Moreover , when compared with the control strain PAO1hfq-Δcrc ( pMMB67HE; pME9655 ) ( Figure 1D , purple bar ) , ectopic expression of crcFlag in strain PAO1hfq-Δcrc ( pMMBcrcFlag; pME9655 ) did not affect amiE::lacZ translation in the absence of Hfq . Next , amiE::lacZ translation was monitored in strains PAO1hfq- ( pMMBhfqFlag , pME9655 ) and PAO1hfq-Δcrc ( pMMBhfqFlag; pME9655 ) after growth in BSM succinate/acetamide medium ( CCR ) and 3 h after ectopic expression of the hfqFlag gene . The absence of Crc in the double mutant strain PAO1hfq-Δcrc ( pMMBhfqFlag; pME9655 ) ( Figure 1D; green bar ) resulted in an increased de-repression of amiE::lacZ translation when compared with strain PAO1hfq- ( pMMBhfqFlag; , pME9655 ) ( Figure 1D; blue bar ) despite comparable levels of HfqFlag in both strains . Taken together , these experiments showed that Crc only impacts on amiE::lacZ translation in the presence of Hfq . Hence , they corroborate the idea that Crc does not act per se as a translational regulator but functions as an ancillary factor in Hfq-mediated repression of target genes . Next , we tested whether Hfq directly represses translation of amiE mRNA by binding to the translation initiation region ( TIR ) . First , a filter binding assay was performed with purified PAO1 Hfq and an amiE mRNA fragment encompassing nucleotides ( nt ) from position −134 to +20 with regard to the A ( +1 ) of the start codon . This experiment revealed that Hfq binds to amiE−134–+20 with a Kd of ∼67 . 0±1 . 4 nM ( Figure S3 ) . Next , the Hfq binding site ( s ) were mapped on amiE RNA . Enzymatic probing was performed with riboendonucleases T1 ( G-specific cleavage ) and A ( C/U-specific cleavage ) in the absence and presence of Hfq . As shown in Figure 2 , Hfq protected the segment of amiE RNA extending from G−28 to U−5 . This region includes the Shine and Dalgarno sequence ( SD ) sequence of amiE mRNA . Thus , Hfq binding to this region would readily explain the observed translational repression of amiE::lacZ mRNA ( Figure 1A , D , E ) . To further test whether Hfq acts as a translational repressor of amiE mRNA , the PURExpress system was employed . The in vitro translation system was programmed with amiEFlag mRNA , encoding a Flag-tagged amidase . As shown in Figure S4 , translation of amiEFlag mRNA was already impeded at a 1∶1 molar ratio of Hfq to mRNA . As the in vitro system is reconstituted from purified components of the translation machinery of E . coli , no additional PAO1 component was apparently required for repression . To further demonstrate that Hfq directly interferes with ribosome binding , a toeprinting assay was performed with amiE−134–+76 mRNA in the presence and absence of Hfq . Briefly , in the presence of tRNAfMet , 30S ribosomes form a stable ternary complex at the RBS of mRNAs , which can be visualized by inhibition of cDNA synthesis primed downstream of the start codon [37] . A toeprint signal usually occurs at position +15 to +17 with regard to the A ( +1 ) of the start codon . As shown in Figure 3 , lane 7 , a toeprint signal at the amiE RBS was observed in the absence of Hfq , whereas the addition of Hfq to amiE−134–+76 mRNA inhibited ternary complex formation ( Figure 3 , lanes 8 and 9 ) . In contrast , the presence of Hfq alone did not result in a stop signal ( Figure 3 , lane 6 ) , which is in accordance with earlier observations that translational repressors do not always provide a roadblock for cDNA synthesis by reverse transcriptase under these conditions [38] . Taken together , these in vitro studies strongly supported the idea that Hfq acts as a translational repressor that prevents ribosome loading on amiE mRNA . Link et al . [20] reported a crystal structure of E . coli Hfq in complex with poly ( A15 ) , wherein the poly ( A ) tract is bound to the distal face using tripartite binding motifs . They consist of an adenosine specific site ( A- site ) , a purine nucleotide selectivity site ( R-site ) and a sequence-non-discriminating E-site . The amino-acids involved in building the A-R-N motifs are fully conserved in the Hfq protein of PAO1 [34] . As the hexamer Hfq could accommodate the entire A-rich stretch from nt −26 to −8 of amiE mRNA ( Figure 2 ) in the six binding pockets , we next tested whether the distal binding site of Hfq is required and sufficient for translational repression of amiE mRNA . We therefore engineered the PAO1 hfq variants hfqY25DFlag and hfqK56AFlag as the corresponding E . coli mutant proteins were shown to be deficient in binding to polyA- and polyU-tracts [18] , respectively . In contrast to the PAO1 hfqFlag gene and the PAO1 hfqK56AFlag allele , ectopic expression of the hfqY25DFlag allele did not result in repression of amiE::lacZ translation , albeit all three proteins , HfqFlag , HfqY25DFlag and HfqK56AFlag , were present at comparable levels ( Figure 4A ) . Basically the same results were obtained when translation of the estA::lacZ ( Figure 4B ) and phzM::lacZ ( Figure 4C ) fusion genes was monitored in the presence of HfqFlag , HfqY25DFlag and HfqK56AFlag , respectively . Hence , translational repression of these reporter genes apparently required an intact distal polyA binding site of Hfq . To verify these in vivo data , the PAO1 Hfq variants HfqY25D and HfqK56A were purified , and binding to amiE−134–+20 mRNA was assessed using electrophoretic mobility shift assays ( EMSA ) . As shown in Figure S5A , while PAO1 Hfq and HfqK56A bound to the mRNA fragment , the HfqY25D protein failed to bind . With increasing concentrations of either Hfq or HfqK56A two shifted bands were observed ( Figure S5A ) , suggesting that Hfq binds at two sites of the amiE−134–+20 fragment . This observation can be explained by the Hfq binding site mapped between nucleotides G−28 to U−5 ( Figure 2 ) and by a probable second binding site , comprising an A-rich region ( nucleotides −92 to −71 ) , which was inferred from an RNomics approach after CoIP with Hfq-specific antibodies [25] . Taken the in vivo and in vitro studies together , these experiments strongly suggested that Hfq binds with its distal face to the RBS of amiE , and by inference most likely also to estA and phzM mRNA . To further corroborate the idea that Hfq directly represses amiE translation the experiment was also performed in the heterologous E . coli hfq- strain JW4130 . The strain was transformed with the control plasmid pME4510 and derivatives thereof harboring the PAO1 hfqFlag gene , the PAO1 hfqY25DFlag allele and the PAO1 hfqK56AFlag allele , respectively . In addition , these strains were transformed with plasmid pME9658 , wherein the amiL terminator preceding the amiE gene was deleted . As shown in Figure S5B , the experimental results paralleled that performed in PAO1 . The translation of the amiE::lacZ gene was repressed in the presence of HfqFlag and HfqK56AFlag , whereas the reporter gene was translated in the presence of HfqY25DFlag . Thus , the presence of Hfq was apparently necessary and sufficient for repression of amiE translation in E . coli . The regulatory RNA CrcZ is present at lower levels during CCR , when compared to conditions when CCR is not in place , e . g . in BSM medium containing mannitol as the sole carbon source [7] . The 407 nt long CrcZ RNA contains six A-rich stretches ( Figure S6A ) to which Hfq can potentially bind with its distal surface , i . e . with the same binding surface as it binds to the RBS of amiE ( Figure S5A ) . Binding of Hfq to the first 151 nt of CrcZ , containing 3 A-rich stretches ( Figure S6A ) was confirmed using EMSA assays ( Figure S6B ) . Three shifted bands could be discerned ( Figure S6B , lane 2 ) , which would be consistent with one Hfq-hexamer binding to either A-rich stretch . As anticipated , the PAO1 HfqY25D mutant protein was defective in binding to CrcZ151 , whereas the HfqK56A variant bound to the CrcZ fragment like native Hfq . Thus , CrcZ binds to the distal face of Hfq like amiE mRNA , and therefore has the potential to titrate Hfq , which in turn would explain the observed increase in translation of amiE::lacZ mRNA in BSM mannitol medium , i . e . in the absence of CCR ( see Figure S1A ) . In the next set of experiments we therefore asked whether CrcZ can abrogate Hfq-mediated translational repression in vitro . First , a mobility shift assay was performed with radioactively labeled amiE−134–+20 RNA in the presence of unlabelled specific CrcZ151 and non-specific RsmZ competitor RNAs , respectively . As shown in Figure 5A , CrcZ151 competed with amiE−134–+20 for binding to Hfq ( Figure 5A , lanes 5 and 6 ) , whereas the addition of RsmZ RNA , which does not bind to Hfq [7] , did not result in a downshift of labeled amiE−134–+20 RNA ( Figure 5A , lane 7 ) . When compared with the addition of unlabelled amiE−134–+20 RNA , the addition of an equimolar concentration of CrcZ151 resulted already in a significant downshift , i . e . loss of Hfq binding to amiE−134–+20 . Hence , CrcZ151 acted as a better competitor for Hfq than amiE−134–+20 , which is anticipated as the used CrcZ151 has three Hfq binding sites , whereas the amiE fragment has only two . Next , amiEFlag mRNA was translated in vitro in the presence of Hfq as well as in the presence of Hfq and CrcZ mRNA . As shown before ( Figure S4 ) , Hfq inhibited translation of amiEFlag , ( Figure 5B , lanes 2–4 ) . In contrast , the mRNA was translated in the presence of CrcZ ( Figure 5B , lanes 5 and 6 ) , whereas the Hfq-mediated translational repression was not relieved in the presence of the non-specific competitor RNA RsmZ ( Figure 5B , lane 7 ) . Similarly , the addition of CrcZ RNA to the Hfq-amiE complex , under conditions that inhibited translation initiation complex formation , resulted in reappearance of a toeprint signal ( Figure 3 , lanes 10 and 11 ) . Thus , CrcZ counteracted the function of Hfq . Taken together , these in vitro experiments indicated that CrcZ can titrate Hfq , and that it can prevent it from binding to the amiE RBS . In our model titration of Hfq by CrcZ would result from increased CrcZ levels [7] in the presence of non-preferred carbon sources , which in turn would lead to de-repression of Hfq-regulated genes . Hence , it would be anticipated that ectopic over-expression of CrcZ would cause de-repression of Hfq-regulated genes even during CCR , i . e . under conditions when the CrcZ levels are low [7] . With this line of reasoning , we next asked whether ectopic expression of crcZ during CCR results in increased expression of the estA gene , which was assessed by monitoring the esterase activity . To avoid any interference of Crc , the experiments were performed in a PAO1Δcrc strain . The control strain PAO1Δcrc ( pMMB67HE ) and the crcZ over-expressing strain PAO1Δcrc ( pMMBcrcZ ) were grown in BSM medium supplemented with 40 mM succinate to an OD600 of 1 . Then , crcZ expression was induced and samples were taken 60 minutes thereafter . Esterase was produced even without induction of crcZ , which can be reconciled with the absence of Crc ( see Figure 1B ) and by endogenous background expression of crcZ in strain PAO1Δcrc ( pMMB67HE ) ( Figure 6A , upper panel ) . Nevertheless , ectopic over-expression of crcZ ( Figure 6A , upper panel ) resulted in elevated activities of esterase ( Figure 6A ) , reflecting de-repression of estA translation . Similarly , over-expression of crcZ in PAO1 resulted in de-repression of amiE::lacZ translation during CCR in BSM succinate/acetamide medium ( Figure S7A ) , which is in agreement with our model wherein CrcZ titrates Hfq . In contrast to strain PAO1 ( pMMBcrcZ;pME9655 ) ( Figure S7A ) , ectopic expression of crcZ did not affect translation of amiE::lacZ in the hfq- strain PAO1hfq- ( pMMBcrcZ;pME9655 ) ( Figure S7B ) , clearly showing that CrcZ-mediated regulation requires Hfq . The model would further specify that a deletion of the crcZ gene should increase repression of amiE::lacZ during CCR . As shown in Figure 6B , when compared with strain PAO1 ( pME9655 ) , amiE::lacZ translation was even further repressed in strain PAO1ΔcrcZ ( pME9655 ) when grown in BSM medium supplemented with succinate and acetamide ( CCR ) . Moreover , amiE::lacZ translation during CCR was indistinguishable in the absence of Hfq in strain PAO1hfq- ( pME9655 ) and in the double mutant PAO1hfq-ΔcrcZ ( pME9655 ) . Taken together , these experiments showed that the hfq deletion is epistatic to crcZ , in other words that CrcZ exerts regulation on amiE::lacZ only in the presence of Hfq . Hence , these in vivo experiments lend further support to the hypothesis that CrcZ titrates Hfq , and thereby abrogates Hfq-mediated translational repression .
In this study , we provided evidence that Hfq represses three CCR regulated genes , amiE , estA and phzM . Given that Hfq blocked translation initiation of amiE mRNA by binding to A-rich stretches encompassing the RBS , we revisited catabolic and transport genes that were found to be up-regulated in a comparative transcriptome analysis of a PAO1 and a PAOhfq- mutant [31] . Out of 126 putative target mRNAs , 72 transcripts contained A-rich stretches in the TIR ( Table S1 ) . Out of the latter , 28 transcripts contain several single non-consecutive A-R-N motifs , whereas 44 transcripts contained consecutive ( A-R-N ) n repeats with n≥3 either within or in close proximity to the RBS ( Table S1 ) , indicating that Hfq could interfere with ribosome binding . Although it remains to be tested for either candidate transcript it is tempting to speculate that Hfq is involved in translational regulation of several genes controlled by CCR . In addition , it is conceivable that several CCR controlled genes , which do not contain A-rich regions in the TIR [39] , are indirectly controlled by Hfq . Based on our in vivo and in vitro studies with the amiE model mRNA , we suggest that Hfq acts as a translational repressor of transcripts subjected to CCR in PAO1 ( Figure 7 ) . As there appear to be several Hfq regulated genes ( Table S1 ) and our preliminary results show that Hfq levels are more or less constant during growth in different carbon sources ( E . Sonnleitner , unpublished ) , the question arises how Hfq can regulate numerous mRNAs . Many if not all catabolic genes including the corresponding transporter genes are primarily regulated at the transcriptional level [4] , [40] , and their transcription usually requires the presence of the respective catabolite . Therefore , it is rather unlikely that many of the putative target genes ( Table S1 ) are concomitantly induced at the same time . Thus , in the presence of a preferred carbon source , e . g . succinate , only a few other catabolites may induce concomitant transcription of the corresponding catabolic genes . Moreover , translational repression most likely leads to degradation of mRNAs [41] , [42] encoding catabolic enzymes other than those required for the breakdown of succinate , and thus to recycling of Hfq . Therefore , CCR control may not require vast amounts of Hfq . This hypothesis is supported by the experiment shown in Figure S8 . When compared with the absence of CCR ( presence of acetamide only ) or with the PAO1hfq- strain , amiE mRNA was faster degraded in PAO1 during CCR in the presence of succinate and acetamide . In addition , we have estimated the number of Hfq hexamers/cell in BSM- succinate medium with 2160+/−56 per PAO1 cell ( Figure S9 ) , which might suffice to silence “a few catabolic transcripts” that are induced during CCR ( Figure 7 ) . In the presence of non-preferred carbon sources , the two component system CbrAB is activated; phosphorylated CbrB binds to the RpoN-dependent promoter of crcZ and stimulates CrcZ synthesis [7] , [43] . Our data ( Figures 5 and 6 ) suggest that CrcZ then binds to and titrates Hfq by virtue of its A-rich binding motifs . This in turn would allow translation of transcripts that are induced by available catabolites , and thus synthesis of the cognate degradative enzymes ( for example aliphatic amidase ) ( Figure 7 ) . For the following reasons we favor the hypothesis that no other sRNAs are required for regulation of the catabolic genes examined in this study . Most E . coli sRNAs bind to the proximal site of Hfq , and binding is usually abrogated in the HfqK56A mutant protein [13] . However , in contrast to the HfqY25D variant , the HfqK56A mutant protein was still capable to repress the fusion genes governed by CCR in PAO1 ( Figure 4 ) and in E . coli ( Figure S5B ) . It seems therefore reasonable to suggest that regulatory sRNAs other than CrcZ are not involved in Hfq-mediated regulation of these catabolic genes . Although binding of E . coli Hfq to A-rich stretches in mRNA has been demonstrated in several model systems ( see below ) , Hfq seems to work predominantly in conjunction with sRNAs [44]–[46] . Hfq-mRNA binding may recruit the sRNA to the target mRNA and stimulate sRNA-mRNA pairing . In this scenario , the sRNA competes with initiating 30S ribosomes , whereas Hfq has a rather indirect function . Some deviations from the canonical model of Hfq assisted and sRNA-mediated regulation of target mRNAs have been reported . In E . coli evidence has been provided that Hfq acts as an autogenous repressor on its own mRNA . As for PAO1 amiE mRNA ( Figure 2 ) , E . coli Hfq was shown to bind to an A-rich sequence encompassing the SD sequence of hfq mRNA [47] . Another example for translational repression by Hfq entails regulation of the E . coli sdhC mRNA by the sRNA Spot 42 . Desnoyers and Massé [48] reported that Spot 42 binds upstream of the RBS and recruits Hfq , which then directly represses translation . Moreover , E . coli Hfq was recently shown to act as a repressor of cirA mRNA translation in the absence of a sRNA [49] . Interestingly , the translational block exerted by Hfq was shown to be abrogated by RyhB RNA pairing to cirA mRNA [49] . Similarly , the model shown in Figure 7 entails direct repression of target mRNAs by PAO1 Hfq . However , in contrast to Spot 42 [48] and RyhB [49] RNA , which recruit Hfq to and abrogate Hfq-mediated translational repression of the target mRNA , respectively , CrcZ RNA acts as a decoy for Hfq . The CrcZ RNA contains six ( A-R-N ) n repeats ( n≥4 ) ( Figure S6A ) that can potentially be exploited for binding to the distal face of Hfq . Thus , in the absence of CCR Hfq is most likely sequestered by CrcZ , and therefore not available to act as a translational repressor on target mRNAs . In this way the Hfq/CrcZ regulatory system is reminiscent to the Pseudomonas RsmA/RsmY/RsmZ system and the CsrA/CsrB system of several Gram-negative Bacteria [30] , [50] , [51] . The ability of Hfq to bind to RsmY [31] in fact poses the question whether the regulatory systems are interlinked . This could provide an explanation why different carbon sources can affect virulence traits such as biofilm formation and antibiotic resistance [39] , [52] . Moreover , given its constellation with Hfq , it seems possible that CrcZ on the one hand can interfere with any mRNA-dependent role of Hfq . On the other hand , the role of Hfq in sRNA-mediated riboregulation remains ill defined in PAO1 . Although Hfq appears to be required for the PAO1 sRNAs PrrF1/PrrF2 to regulate target mRNAs [53] , it is unclear whether Hfq exerts this function by stabilizing the sRNAs and/or by stimulating sRNA-mRNA pairing . As CrcZ binds to the distal site of Hfq it is conceivable that Hfq might even still be able to bind sRNAs such as PrrF at the proximal site , and thus to protect them from degradation . In any case it will be interesting to study whether sequestration of Hfq by CrcZ indirectly affects other Hfq-mediated processes in P . aeruginosa . We have recently shown that the Crc protein is devoid of RNA binding activity [10] , and that the previously observed RNA binding activity of Crc could be attributed to Hfq [11] . However , Crc contributes to Hfq-mediated repression during CCR ( Figure 1 ) . In addition , Crc was shown to impact on biofilm formation [54] , [55] , virulence and antibiotic susceptibility [52] , traits which are also affected by Hfq [31] , [33] . This raises the question how Crc impacts on Hfq function . Crc appears not to interfere with hfq expression . The translation of a hfq::lacZ reporter gene , whose transcription is driven by the authentic hfq promoter , was indistinguishable in PAO1 and in the isogenic PAO1Δcrc strain ( Figure S10A ) . In addition , the levels of Hfq , as determined by quantitative western-blot analysis , were not significantly altered in PAO1Δcrc when compared with the wild-type strain ( Figure S10B ) . Conversely , Hfq seems not to affect the cellular concentration of Crc ( Figure S10B ) . Thus , Crc seems not to impact on the Hfq levels , and vice versa Hfq seems not to affect that of Crc . RelA was recently shown to enhance multimerization of E . coli Hfq , and thereby to stimulate binding to sRNAs [56] . We therefore considered the possibility that Crc might interact with Hfq to increase the specificity of Hfq for A-rich sequences . However , as revealed by EMSA assays , the presence of Crc did not increase the affinity of PAO1 Hfq for amiE−134–+20 RNA ( E . Sonnleitner , unpublished ) , making it less likely that Crc acts similar to RelA . Nevertheless , we are currently exploring the possibility whether Crc is associated with Hfq in vivo .
The strains and plasmids used in this study are listed in Table S2 . Unless indicated otherwise , the cultures were grown at 37°C in BSM minimal medium supplemented with 40 mM succinate . The strains PAO1hfq-Δcrc and PAO1hfq-ΔcrcZ were constructed by homologous recombination . Briefly , plasmid pME9672 and plasmid pME9673 , respectively , were mobilized into strain PAO1hfq- with the aid of E . coli strain HB101 ( pRK2013 ) , and then chromosomally integrated through selection for tetracycline resistance . Excision of the vector by a second crossover event was achieved by enrichment for tetracycline-sensitive cells [57] . If required E . coli and PAO1 were grown in the presence of 100 µg ml−1 ampicillin , 25 µg ml−1 tetracycline or 25 µg ml−1 kanamycin and 50 µg ml−1 gentamicin , 100 µg ml−1 tetracycline or 250 µg ml−1 carbenicillin , respectively . Details on the construction of plasmids used in this study are provided in Text S1 . The β-galactosidase activities were determined as described by Miller [58] . The cells were permeabilized with 5% toluene . The β-galactosidase units in the different experiments were derived from three independent experiments . The error bars in the different Figures represent standard deviations . The protein levels of Hfq and Crc fused to C-terminal Flag-tags ( DYKDDDDK ) were determined in the respective strains and under the growth conditions as specified in the legends to the Figures . 1 ml aliquots of the respective cultures were withdrawn; the cells were harvested by centrifugation , resuspended and boiled in protein sample buffer . Equal amounts of total protein were separated on 12% SDS-polyacrylamide gels and then electro-blotted to a nitrocellulose membrane . The blots were blocked with 5% dry milk in TBS buffer , and then probed with rabbit anti-DYKDDDDK polyclonal antibody ( Roth ) . The antibody-antigen complexes were visualized with alkaline-phosphatase conjugated secondary antibodies ( Sigma ) using the chromogenic substrates nitro blue tetrazolium chloride ( NBT ) and 5-Bromo-4-chloro-3-indolyl phosphate ( BCIP ) . Hfq protein , HfqY25D and HfqK56A protein were produced in the hfq deficient E . coli strain AM111F′ harboring plasmid pHfqPae , pHfqPaeY25D or pHfqPaeK56A . Protein purifications were performed as described in detail by Beich-Frandsen et al . [59] . For in vitro transcription of amiE ( 1172 nt ) , CrcZ ( 426 nt ) and RsmZ ( 141 nt ) RNAs the AmpliScribe T7-Flash Transcription Kit ( Epicentre Biotechnologies ) was used according to the manufacturer's instructions . First , PCR fragments were generated with the primer pairs ( see Table S3 ) A5/A75 ( amiE ) , E6/C6 ( crcZ ) and W26/X26 ( rsmZ ) , whereby the forward primers contained T7 promoter sequences . Primer A75 encoded in addition a Flag-tag sequence . For the filter binding and gel mobility shift assays truncated versions of amiE−134–+20 ( first 154 nt ) and crcZ151 ( first 151 nt ) were used . The corresponding PCR fragments were amplified with the primers A5/C1 ( amiE−134–+20 ) and E6/E2 ( crcZ151 ) . For the toeprint assay the amiE−134–+76 fragment was in vitro transcribed using oligonucleotides A5 and Q99 ( Table S3 ) . Five pmol of in vitro transcribed full length amiE RNA was incubated in RT-buffer ( 50 mM Tris pH 8 . 3 , 60 mM NaCl , 6 mM Mg-acetate , 10 mM DTT ) at 37°C for 30 min in a 10 µl reaction with 0 , 5 and 20 pmol of purified Hfq protein . Then 2 U RNase T1 ( 1 µl ) , 10 pg RNase A ( 1 µl ) or 1 µl of RNase free H2O was added and incubated for additional 10 min followed by phenol/chloroform extraction and precipitation . 200 fmol RNase treated or untreated RNAs were further used for the primer extension reaction with AMV reverse transcriptase ( Promega ) , which was primed with the 5′-[32P]-labeled C78 oligonucleotide to test for protection by Hfq of the proximal part of amiE mRNA . For sequencing amiE RNA and ddNTPs ( Fermentas ) were used in primer extension reaction ( s ) . The amiE−134–+76 RNA used for toeprinting was obtained as described above . The [32P]-5′-end labeled oligonucleotide Q99 was annealed to amiE mRNA ( +57 to +76 with regard to the A ( +1 ) of the start codon ) and used to prime cDNA synthesis by MMuLV reverse transcriptase ( Thermo Scientific ) . The toeprinting assay was carried out with purified E . coli 30S ribosomal subunits and E . coli initiator-tRNA ( tRNAfMet ) as described by Hartz et al . [37] . The mRNA ( 0 . 05 pmol ) was pre-incubated at 37°C for 10 min with or without 4 pmol 30S subunits and 16 pmol tRNAfMet before reverse transcriptase was added . To test whether Hfq interferes with translation initiation , 0 . 05 pmol amiE−134–+76 mRNA was pre-incubated at 37°C for 10 min with 4 pmol 30S subunits , 16 pmol tRNAfMet and Hfq-hexamer ( 1 or 2 pmol , respectively ) before the reverse transcriptase reaction was performed . To test whether CrcZ can abrogate the Hfq mediated repression of amiE translation initiation , 0 . 05 pmol amiE−134–+76 mRNA was pre-incubated at 37°C for 10 min with 4 pmol 30S subunits , 16 pmol tRNAfMet and equimolar amounts of Hfq-hexamer and CrcZ ( 1 or 2 pmol , respectively ) before reverse transcriptase was added . The amiE−134–+20 and crcZ151 RNAs ( see above ) were dephosphorylated with FastAP thermo sensitive alkaline phosphatase ( Thermo Scientific ) and subsequently 5′-end labeled using [γ-32P]-ATP ( Hartmann Analytic ) and polynucleotide kinase ( Thermo Scientific ) . The labeled RNAs were gel-purified and dissolved in diethylpyrocarbonate-treated water . Labeled RNA ( 10 nM ) was incubated with increasing amounts of purified Hfq , the HfqY25D or HfqK56A mutant proteins in 10 mM Tris-HCl ( pH 8 . 0 ) , 10 mM MgCl2 , 60 mM NaCl , 10 mM NaH2PO4 , 10 mM DTT , and 25 ng tRNA in a total volume of 10 µl . Unlabeled RNA was used as competitor as stated in the legend to Figure 5A . The reaction mixtures were incubated at 37°C for 30 min to allow protein–RNA complex formation . The samples were mixed with 4 µl loading dye ( 25% glycerol , 0 . 2 mg/l xylencyanol and bromphenol blue ) immediately before loading and separated on 4% polyacrylamide gels using Tris-borate buffer . The radioactively labeled bands were visualized with a PhosphorImager ( Molecular Dynamics ) and quantified with ImageQuant software 5 . 2 . In vitro translation was performed with the PURExpress in vitro protein synthesis kit ( New England BioLabs ) . 5 pmol in vitro transcribed amiEFlag mRNA was used in a 12 . 5 µl reaction . Increasing amounts of purified Hfq protein ( as specified in legends of Figures 5B and S4 ) were added . For competition CrcZ ( 5 and 10 pmol ) or RsmZ ( 10 pmol ) RNA were added . After 1 h of incubation at 37°C , 5 µl of the reaction was mixed with 5 µl protein loading buffer and a western-blot was performed using anti-Flag antibodies as described above . Esterase activity was assayed as described previously [60] . Briefly , the cells were harvested by centrifugation and washed in 100 mM potassium phosphate buffer pH 7 . 2 . The substrate ( 25 µl p-nitrophenyl-caproate dissolved in 5 ml ethanol ) was added to 100 ml potassium phosphate buffer ( 100 nM; pH 7 . 2 ) containing MgSO4 to a final concentration of 10 mM . 1 ml of the test solution and 50 µl of cells were used to determine esterase activity by monitoring the change in absorbance at 410 nM min−1 , which was normalized to the optical density ( OD600 ) of the culture . Total RNA of the respective strains as specified in the legends to the Figures was purified using hot phenol . The steady state levels of CrcZ and 5S rRNA ( loading control ) was determined by Northern-blotting using 4 µg of total RNA . The RNA samples were denatured for 5 min at 65°C in loading buffer containing 50% formamide , separated on a 8% polyacrylamide/8 M urea gel , and then transferred to a nylon membrane by electroblotting . The RNAs were cross-linked to the membrane by exposure to UV light . The membranes were hybridized with gene-specific 32P-end-labelled oligonucleotides ( CrcZ: K3; 5S rRNA: I26; Table S3 ) . The hybridization signals were visualized using a PhosphorImager ( Molecular Dynamics ) . | Carbon assimilation in Bacteria is governed by a mechanism known as carbon catabolite repression ( CCR ) . In contrast to several other bacterial clades CCR in Pseudomonas species appears to be primarily regulated at the post-transcriptional level . In this study , we have identified the RNA chaperone Hfq as the principle post-transcriptional regulator of CCR in P . aeruginosa ( PAO1 ) . Hfq is shown to act as a translational regulator and to prevent ribosome loading through binding to A-rich sequences within the ribosome binding site of mRNAs , which encode enzymes involved in carbon utilization . It has been previously shown that the synthesis of the RNA CrcZ is augmented in the presence of non-preferred carbon sources . Here , we show that the CrcZ RNA binds to and sequesters Hfq , which in turn abrogates Hfq-mediated translational repression of mRNAs , the encoded functions of which are required for the breakdown of non-preferred carbon sources . This novel mechanistic twist on Hfq function not only highlights the central role of RNA based regulation in CCR of PAO1 but also broadens the view of Hfq-mediated post-transcriptional mechanisms . | [
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"science... | 2014 | Regulation of Hfq by the RNA CrcZ in Pseudomonas aeruginosa Carbon Catabolite Repression |
Though Nepal declared leprosy elimination in 2010 , its burden is constantly rising in Terai communities for the past 2 years with 3000 new leprosy cases being diagnosed annually . Community’s perception is important for prevention and control of leprosy and enhancing quality of life of leprosy patients . Poor knowledge , unfavorable attitude and stigma create a hindrance to leprosy control . The main objective of this study was to assess the knowledge , attitude and stigma of leprosy amongst the community members living in Dhanusha and Parsa districts of Southern Central Nepal . A total of 423 individuals were interviewed using a structured questionnaire in Dhanusha and Parsa districts . Data was analyzed using both descriptive ( frequency , percentage , median ) and statistical inferences ( Chi-square test , Kruskal Wallis H test , Mann Whitney U test , binary logistic regression ) using SPSSvs20 . All respondents had heard about leprosy . Source of information on leprosy was mainly found to be health workers/hospitals ( 33 . 1% ) . Only 62 . 6% reported bacteria being its cause followed by other myths such as bad blood/curse/heredity/bad deeds ( 36% ) . Only 43 . 8% responded that leprosy is transmitted by prolonged close contact with leprosy patients and 25 . 7% reported religious rituals as the treatment . Only 42 . 1% had good knowledge and 40 . 9% had favorable attitude . Good knowledge of leprosy was highly associated with favorable attitude towards leprosy ( P<0 . 001 ) . The outcome variables- knowledge , attitude and EMIC score were found to have highly significant association with age , sex , ethnicity , religion , education and occupation of the respondents ( P<0 . 001 ) . Having knowledge on leprosy transmission was positively associated with favorable attitude towards leprosy ( P<0 . 001 ) . Strategizing the awareness programmes according to socio-demographic characteristics for enhancing the knowledge regarding leprosy cause , symptoms , transmission , prevention and treatment , can foster the positive community attitude towards leprosy affected persons . Enhancing positive attitude towards leprosy affected persons can reduce the community stigma , thus may increase their participation in the community . Positive attitude may further increase their early health seeking behaviour including their quality of life .
Leprosy , also known as Hansen’s disease , is a chronic infectious disease caused by bacteria Mycobacterium leprae [1] . It generally affects epidermis and peripheral nerves of the affected ones [2] . The disease is basically transmitted via prolonged close contact with untreated multibacillary leprosy patients through inhalation of bacilli [2; 3] . However , it is still an unequivocal issue regarding transmission of leprosy from one person to another [1] . Leprosy is more than a biological disease and is featured by stigma in the society leading to treating the affected ones with negative attitude [4] . Higher the associated stigma , lesser will be the chance to detect the new cases of leprosy early . Despite being curable , each year globally around 200000 new cases of leprosy are detected [5] . Leprosy remains to be one of the neglected tropical diseases of developing countries in Africa and Asia with its burden being concentrated in Indonesia , Brazil and India . These three countries respectively contributed to 8% , 13% and 60% of the global new cases burden in 2015 while Nepal contributed to 1 . 3% [5; 6] . According to WHO factsheet , globally 210 , 758 new leprosy cases were detected in 2015 with prevalence rate of 0 . 29/10000 population [6] . However , the prevalence rate of leprosy in South-East Asian Region was 0 . 61/10000population [6] . Many countries have some areas of high endemicity showing high notification rates for new cases and witnessing continued transmission of leprosy [7] . Moreover , the open border between Nepal and India allows free migration of the population including leprosy affected persons . This may impede the early case detection and treatment . Unfortunately , disability , disfigurement and the stigma associated with the leprosy have sustained and enhanced the stigma towards leprosy which in turn leads the affected ones to isolation , status concealment , delayed diagnosis and treatment . Leprosy affected ones in the early phase of the disease are generally suspicious of the diagnosis but fearing social isolation , leading to hesitancy towards seeking the advice and health care services [8] . A study done in Lalitpur Nepal in 1993 to 1995 showed that 6% ( 10/166 ) of leprosy affected persons reported of not seeking treatment earlier due to fear and social consequences including isolation [9] . Similarly , a quantitative study conducted in western Nepal in 2013 revealed that 66% of 135 leprosy affected persons intended to conceal their disease [10] . Moreover , in-depth interviews showed that 70% of 20 leprosy affected individuals intended to conceal their disease status with the major reasons being the fear of transmission , fear of exclusion , separation and rejection from the society [11] . Additionally , it has been observed that the social integration of people diagnosed of having leprosy is threatened when other people in the community come to know about it which results into applying the principle of silence and concealment of the disease status [12] . However , it is a serious public health problem since the multidrug therapy treatment should be initiated as soon as possible to prevent the disease progression resulting grade-2 disability which can pose further burden and severity condition in the lives of affected individuals [8; 13] . In order to control the cycle of concealment that leads to delayed health seeking and may lead to development of impairment and disability , early identification and treatment is critical . Under leprosy control programme , Nepal declared that leprosy is no longer a public health problem in 2010 with the achievement of leprosy elimination in 2009 [14; 15] . However , there remain the challenges of sustaining this achievement and reducing the disease burden through quality services including early detection and prompt treatment [14] . On the contrary to decreasing incidence and prevalence of the disease , it has increased from 0 . 77 to 0 . 79 , 0 . 84 , 0 . 82 , and 0 . 83 respectively during 2010 to 2014 . Moreover , the country has been detecting more than 3000 new cases of leprosy annually [14] . Additionally , 18 districts of the nation have still prevalence above elimination level ( prevalence rate of <1 case per 10000 population ) and these districts contribute to 75% of the total incidence and accounts for around 3200 new cases of leprosy each year [15] . Most of these high prevalent districts are located in terai region of Nepal . Despite the World Health Organization’s ( WHO ) target to eradicate leprosy by 2020 , in the fiscal year 2016/2017 , 19 . 77 leprosy affected individuals were diagnosed in every 10 , 000 population in the high prevalent districts of Terai regions of Nepal that are worst-hit by the burden of leprosy [16] . Towards increasing burden of leprosy in these regions , it has been argued that lack of awareness , poor personal hygiene , poor sanitation and low economic status of the people may be the reasons [17] . Additionally , people visit hospitals when the disease conditions get too worse; may it be due to inadequate awareness or lack of awareness towards skin-related diseases and its mode of transmission [17] . So , in order to address leprosy , better understanding about its cause , means of transmission and nature , and associated stigma is required . In addition , to better understand leprosy and its social consequences it is important to study it in context , may it be the socio-cultural factors , belief systems , geography , economy , available resources or services [12] . The study done in Eastern Nepal revealed that leprosy affected individuals still encounter many constraints and restraints in their social life making them left out [4] . This fear of getting isolated may result in delayed in health care seeking [4] . Furthermore , a study in Nepal showed that majority of the respondent did not understand the cause of leprosy and were not aware of the duration of its treatment [18] . The study also emphasized the need of strengthening public/community awareness program towards leprosy [18] . According to a study done in Myanmar , it was found that community members were not sure about the cause of leprosy [19] . A study conducted in Pakistan revealed that more than one-fifth of the doctors did not have good knowledge regarding leprosy [20] . One of the major contributing factors towards the late diagnosis of leprosy is communities’ lack of knowledge regarding leprosy ultimately leading to increased likelihood of physical disability [2] . The available literatures have indicated that though leprosy is an old disease in terms of human civilization , it remains to be misunderstood and stigmatized . The knowledge and attitude of community towards leprosy remains poor which is mirrored by the study done in Cameroon which showed that less than one-fifth of the respondents knew the cause of leprosy and only about two-fifth of the respondents would shake hands with someone who is affected with leprosy [21] . A recent increase in new cases of leprosy from the Terai districts of Nepal has implications for the community where they live . How community members perceive leprosy affected persons and their attitude can affect their disease confession and health seeking at the hospital . Although studies in past have explored factors affecting community stigma towards leprosy in western and eastern Nepal , none in our knowledge has explored the community’s knowledge and attitude towards leprosy in Central southern Nepal . The main objective of this study was to assess the knowledge , attitude and stigma of leprosy amongst the community members living in Dhanusha and Parsa districts of Southern Central Nepal .
This was a cross-sectional study carried out amongst the community members living around teaching hospital ( National Medical College and Teaching Hospital ) of Parsa and Lalgadh Leprosy Hospital of Dhanusha district of state 2 of Nepal . Respondents of both sexes aged between 18 years and 60 years were involved in the survey . However , individuals who were having hearing impairment and mental illness were excluded from the survey . The sample size was calculated by using StatCalc Epi-Info . With prevalence 50% and margin of error 5% , the sample size was 384 . Assuming the non-response of 10% , the final sample size calculated was 423 . The data was collected in two priority districts of state 2 of Nepal viz Parsa and Dhanusha . From both districts the communities ( Bhediyahi and Mithila ) surrounding the teaching hospital and leprosy hospital of Parsa and Dhanusha respectively were chosen for data collection . From Bhediyahi 212 and from Mithila 211 households were taken systematically . From each selected household one eligible respondent of age in between 18 and 60 years who gave his/her consent to participate in the study were selected for interview . Structured questionnaire consisting of four parts was prepared after review of relevant literatures . The first part of the questionnaire was related to socio-demographic characteristics of the study participants , the second part was related to assessment of community member’s knowledge regarding leprosy , the third part was related to assessment of community member’s attitude towards leprosy and leprosy patients , and the fourth part was related to assessment of stigma attached in community towards leprosy and leprosy patients . The fourth part , EMIC scale ( The Explanatory Model Interview Catalogue ) is a reliable and validated tool to assess the community stigma towards leprosy ( Rensen et al ) [24] . The Nepali version of EMIC scale has been used in the past by one study conducted in western Nepal [25] . The other parts of the structured questionnaire in English were translated into Nepali language so that it can be relevantly used in the Nepalese context . A back-translation was then done to English language . The back translation of the tool from Nepali to English language was blind to the original questionnaire . Then the translated questionnaire in Nepali and back-translated questionnaire in English and the original questionnaire were all reviewed by assessing the meaning of each word to ensure the accuracy of the translation and the final questionnaire in Nepali was prepared . Data was collected by the researchers themselves through face to face interview . The data was collected from the members of each selected household whose age was greater than 18 years old and less than 60 years and who gave his/her voluntary consent . The purpose of data collection was explained first to respondents to increase their awareness about the study before the start of the interview . They were informed regarding their voluntary participation in the study and their right to not answer any questions they did not want to . They were also ensured about regarding maintaining confidentiality of the information they provided as the researchers neither asked their name nor recorded any kind of respondent personal identity which could identify their name . Knowledge of leprosy- Based on reported response each correct response towards each item of the knowledge questionnaire; the level of knowledge towards leprosy was assessed . Altogether sixteen self-reported items were considered for assessing level of knowledge which included questions with one correct answer as well as questions of dichotomous response ( Yes/No ) like hearing about leprosy , knowing its cause , sign and symptoms , leprosy as very infectious disease , its transmission , is it treatable , and its treatment . The level of knowledge was categorized as having good knowledge or poor knowledge . Good knowledge of leprosy- Respondents who were able to answer 75% or more of knowledge questions correctly were regarded as having good knowledge of leprosy . Poor knowledge of leprosy- Respondents who were able to answer less than 75% of knowledge questions correctly were regarded as having poor knowledge of leprosy . Additionally , the source of information on leprosy , knowledge regarding leprosy being a severe disease , and knowledge regarding first sign and symptoms of leprosy were also assessed . Attitude towards leprosy- It referred to community member’s perception towards leprosy and/or leprosy affected individuals . Attitude was assessed through 13 statements ( 10 positive statements towards leprosy and 3 negative statements towards leprosy ) with response either ‘Yes’ or ‘No’ . A response with ‘Yes’ towards each positive statement was given a score of 1 and a response with ‘No’ towards each positive statement was given a score of 0 . Similarly , a response with ‘No’ towards each negative statement was given a score of 1 and a response with ‘Yes’ towards each negative statement was given a score of 0 . Attitude was categorized as either having favorable attitude towards leprosy or unfavorable attitude towards leprosy based on individual respondent’s attitude score . Favorable attitude towards leprosy- Respondents who scored attitude score 7 or more ( >50% of maximum attitude score ) were regarded as having favorable attitude towards leprosy . Unfavorable attitude towards leprosy- Respondents who scored attitude score less than 7 ( <50% of maximum attitude score ) were regarded as having unfavorable attitude towards leprosy . Level of stigma towards leprosy- The level of stigma towards leprosy was assessed based on respondent’s individual EMIC score . The EMIC score was calculated based on individual responses towards 15 items of the EMIC scale which is a standard tool to assess stigma towards leprosy . Each item/question in the scale was scored on the basis of response as “Yes = 2 , Possibly = 1 , No or Don’t know = 0” . Further , the level of stigma was assessed based on calculated individual respondent’s EMIC score and was categorized as high level of stigma , moderate level of stigma and low level of stigma . The category of the level of stigma towards leprosy was adapted . Respondents who scored EMIC score greater than 20 were regarded as having high level of stigma towards leprosy , respondents who scored EMIC score in the range of 10–20 were regarded as having moderate level of stigma towards leprosy , and respondents who scored EMIC score in the range of 0–10 were regarded as having low level of stigma towards leprosy . The collected data were checked daily for completeness and consistency before data processing and analysis . The collected data was cleared , checked and analyzed by using tally sheet and computer . Data was entered and analyzed in SPSS version 20 . Both descriptive and statistical inferences were used to analyze the data . Descriptive statistics like frequency , percentage , and median were used to describe the socio-demographic characteristics , level of knowledge , level of attitude and level of stigma of the study participants . Proportions were calculated , and the Chi-square test was used to examine relationship between socio-demographic characteristics and level of knowledge; socio-demographic characteristics and level of attitude; and level of knowledge and level of attitude . Mann Whitney U test and Kruskal Wallis H test were used to analyze the difference in total perceived stigma score using EMIC between different socio-demographic characteristics of the community . Further , binary logistic regression analysis was carried out to determine predictors of unfavorable attitude towards leprosy . Ethical clearance was obtained from Institutional Review Committee ( IRC ) of National Medical College ( FNMC-310-074-075 ) . Further , for each study participants , the purpose of the study was stated by the researchers prior to data collection . In addition , participants were informed that they have full right to refuse participating in the study and can interrupt the interview if not comfortable with it . However , they were informed that their participation in the study is very important . Participation of each respondent in this study was voluntary and data was collected from each participant once they gave an informed consent . Confidentiality of the information was maintained , and anonymity of the study participants was respected during data processing and analysis .
Four hundred and twenty-three ( 423 ) individuals were contacted and interviewed in the survey with age ranging between 18 years and 60 years , with around 36% above 40 years and 29% below 24 years . They were 58 . 6% males , 34 . 8% Brahmin/Chhetri ( considered to be higher class as per ethnicity in Nepal ) and 69 . 7% married . Almost half of the respondents ( 49 . 9% ) were from nuclear family . More than one-third of the participants ( 40 . 9% ) had bachelors level or higher degree of education . Most of them were service holder ( 45 . 6% ) followed by farmer ( 24 . 3 ) and with monthly income more than Nepalese Rupees twenty thousand ( 49 . 2% ) . All the study participants had heard about leprosy . More than 4/5th of the participants ( 88 . 4% ) reported of knowing the cause of leprosy . More than 3/4th of the study participants ( 79 . 4% ) believed leprosy to be highly infectious disease . Similarly , 69% of them reported of knowing how leprosy is transmitted . Also , 81 . 1% of the study participants reported of knowing the signs and symptoms of leprosy . With regards to the first sign and symptom of the disease , 46 . 8% of the participants reported skin involvement , 3 . 1% reported nerve involvement and 31 . 2% reported both skin and nerve involvement as the first sign of the disease . Although 88 . 4% responded of knowing the cause of leprosy , only 62 . 6% of them reported of bacteria being the cause of leprosy . Surprisingly , 21 . 1% of them reported bad blood as the cause of leprosy , followed by curse by god ( 8 . 8% ) , heredity ( 3 . 2% ) , bad deeds ( 2 . 7% ) , and unclean environment ( 1 . 6% ) . However , only 43 . 8% responded that leprosy is transmitted by prolonged close contact with leprosy affected individuals . Majority of the participants ( 87 . 7% ) thought leprosy to be a curable disease . But , 25 . 7% of them reported religious rituals as the treatment for leprosy . In addition , most of the participants ( 65 . 2% ) thought leprosy to be a severe disease . Nevertheless , only 62 . 2% , 48 . 9% , 30% , and 66 . 7% of them reported skin patches , loss of sensation , deformity and ulcer respectively to be the signs and symptoms of the disease . Surprisingly , 28 . 4% and 31 . 2% of the participants also responded tingling and skin irritation respectively to be the signs and symptoms of leprosy . Around 2/5th of the study respondents ( 38 . 8% ) said that they would not go to hospital or doctor if they get to know of having leprosy . Based on correct response towards the questions related to knowledge , it was found that 57 . 9% of the study participants had poor knowledge of leprosy and remaining ( 42 . 1% ) of them had good knowledge of leprosy . The major source of information about leprosy for the community people was found to be hospital and health worker comprising ( 33 . 1% ) followed by media ( 30 . 7% ) . The knowledge of leprosy among community people were influenced by socio-demographic characteristics ( Table 1 ) . It was found that there was highly significant association between the level of knowledge of leprosy among study participants with age , sex , ethnicity , religion , educational status , occupation and monthly income ( P< 0 . 001 ) . Most of the study participants from older adult age group ( >45 years ) had good knowledge of leprosy while majority of female had poor knowledge of leprosy as compared to male . Most of the respondents from Dalit or Janajati background had poor knowledge of leprosy . Majority of the non-Hindu respondents had good knowledge of leprosy . Respondents with higher education including bachelor or master or higher degree were having good knowledge of leprosy . Respondents with occupation service had good knowledge of leprosy . Most of the individuals with monthly income more than Nepali Rupees 20000 ( Nepali Rupees 20000 approximately equivalent to USD 178 as of 29 November 2018 ) had good knowledge of leprosy . The level of knowledge of leprosy was also significantly associated with type of family of the study participants where individuals from joint family had good knowledge of leprosy ( P = 0 . 034 ) . However , marital status was not found to influence the level of knowledge of leprosy ( P = 0 . 101 ) . Around 3/5th of the study participants ( 59 . 1% ) had unfavorable attitude towards leprosy and 40 . 9% had favorable attitude . Most of the participants ( 51 . 8% ) responded they would sit together with leprosy affected individuals in public conveyance , 51 . 3% said that they would not avoid having food or other activities with leprosy patients , would agree to work in the same environment with leprosy affected ones ( 52 . 5% ) , would not feel shame to share the status to others if anyone in the family had leprosy ( 53 . 4% ) . More than 4/5th ( 96 . 2% ) reported that they would support leprosy affected ones if they would need it . However , only 12 . 5% reported that they would share foods with leprosy patients , only 32 . 6% would take cooked foods by the leprosy affected individuals , and majority of them reported that they would not marry individuals from family with history of leprosy ( 82% ) . Similarly , majority of them ( 84% ) reported that it is difficult for anyone with leprosy to get married . The level of attitude towards leprosy among community members were found to be influenced by socio-demographic variables ( Table 2 ) . It was found that there was highly significant association between level of attitude towards leprosy and age , sex , ethnicity , religion , marital status , educational status and occupation ( P<0 . 001 ) . Most of the study participants from older adult age group ( >45 years ) had favorable attitude towards leprosy while majority of female had unfavorable attitude towards leprosy as compared to male . Most of the respondents from Dalit or Janajati background had unfavorable attitude towards leprosy . All of the non-Hindu respondents had favorable attitude towards leprosy . Majority of the married respondents had unfavorable attitude towards leprosy . Respondents with higher education including bachelor or master or higher degree were having favorable attitude towards leprosy . Majority of the housewives were found to have had unfavorable attitude towards leprosy . The binary logistic regression showed that the individuals who knew how leprosy is transmitted are likely to have 3 . 35 times favorable attitude of sitting together with leprosy affected individuals in the public conveyance ( Table 3 ) . Also , those who think leprosy to be very infectious would have 2 . 1 times higher chance of staying far away from leprosy patients . In addition , those who know it is transmitted by prolonged close contact only would have 13 times higher chance of letting own child to play with children of leprosy affected individuals . The Chi-square test showed that the attitude was highly influenced by the knowledge of leprosy among the community members ( Table 4 ) . There was highly significant association between level of attitude and level of knowledge of leprosy among the study participants ( P<0 . 001 ) . The finding revealed that better the knowledge of leprosy among individuals , more the chance of having positive attitude towards leprosy and leprosy patients . The EMIC profile of the study participants revealed that 44% were having high stigma , 33 . 3% were having moderate level of stigma and 22 . 7% were having low stigma towards leprosy and leprosy patients . The assessment of EMIC score was done to measure the perceived stigma towards leprosy and leprosy patients in community members . The median score was calculated to analyze the difference of stigma between various groups . It was found that 43 . 7% of the study participants would keep others from knowing leprosy status if possible , 32 . 2% would think less of self due to leprosy affected individual in the family , 24 . 8% think that leprosy has caused shame or embarrassment in the community , 29 . 3% feel others think less of a person with leprosy , 39 . 7% think that there would be adverse effect on others if they know someone’s status of leprosy , and 29 . 6% think that others would avoid a person with leprosy ( Fig 1 ) . It was found that there was highly significant association between EMIC score and age , ethnicity , marital status , educational status , occupation , monthly income , knowledge of leprosy transmission , knowledge of cause of leprosy , sex , religion , and income sufficiency for living , knowledge regarding leprosy is treatable , Knowledge of sign and symptoms of leprosy ( P<0 . 001 ) ( Table 5 , Table 6 , Table 7 ) . The finding showed that perceived stigma towards leprosy ( EMIC score ) was lower at increasing age > 40 years . EMIC score was high among Dalit/Janajati , unmarried , female , Hindu participants , and participants with insufficient income for living . Similarly , study participants who did not have knowledge of leprosy transmission and who did not know the cause of leprosy had high EMIC score . Further , the study participants who thought leprosy as not curable disease were found to have had high EMIC score . Furthermore , respondents who knew loss of sensation , deformity and ulcer as sign of leprosy had low EMIC score while respondents who knew skin patch as sign of leprosy had high EMIC score . Respondents who though skin itchiness as sign and symptom of leprosy had high EMIC score . Additionally , the study participants who correctly knew bacteria as the cause of leprosy and prolonged close contact being the means to transmit leprosy had low EMIC score . Similarly , respondents with higher educational status ( Bachelor’s degree and above ) , engaged in service and with monthly income of >20000 NRs were found to have had low EMIC score . However , there was no association between EMIC score and type of family ( P = 0 . 177 ) , residence or district ( P = 0 . 56 ) , knowledge regarding leprosy being an infectious disease ( P = 0 . 551 ) , knowledge regarding leprosy being a severe disease ( P = 0 . 51 ) and knowing tingling as a sign of leprosy ( P = 0 . 133 ) . These factors ( type of family , residence , knowledge regarding leprosy being a severe disease and knowing tingling as a sign of leprosy ) were found to have no influence on perceived stigma towards leprosy in community people .
The overall findings of the study revealed that only 42 . 1% of the community people had good knowledge of leprosy with major source of information being local health worker and media ( 63 . 8% ) . Similarly , only 40 . 9% of the study respondents were found to have favorable attitude towards leprosy . Additionally , it was also found that the community-based stigma towards leprosy and leprosy affected persons is still prevalent among study participants living in the study districts- Dhanusha and Parsa . The findings of this community-based study showed that still around 3/5th of the study participants had poor knowledge of leprosy . This result is supported by the study done in eastern Nepal [4] . Similarly , the study done in western Nepal also showed similar result with almost half having some kind of knowledge on leprosy cause , transmission and clinical manifestation [25] . This finding is also congruent to the study done in community members of Andhra Pradesh and Orissa which showed that 35–50% of the respondents had high level knowledge of leprosy [26] . However , a study done in Indian rural community to assess knowledge and attitude towards leprosy after post elimination phase showed that 78 . 94% of the respondents had good knowledge and 69% had positive attitude towards leprosy [27] . Similarly , a study done in Ethiopia also revealed worse scenario with around 80% of the respondents having low level of knowledge of leprosy [28] . The reason for this difference in knowledge and attitude may be due to the different socio-cultural context in relation to Terai districts of Nepal . This study and Ethiopian study resembles in relation to the response that 100% of the participants had heard about leprosy [28] . However , the study done in Cameroon showed that only 82 . 4% of the respondents had heard about leprosy [21] . Apart from responding bacteria as the cause of leprosy , participants also responded wrongly citing god’s sin , bad deeds , bad blood , and heredity as the causes of leprosy which is similar to the findings of the study done in Cameroon and Ethiopia [21; 28] . This finding has also been supported by the study done in Uttar Pradesh , India [29] . These myths are rooted in the socio-cultural context of the communities in Asia , Africa and South America as evident in the literature written by Wong and Subramaniam [30] . The current study revealed that around 3/5th of the respondents had unfavorable attitude towards leprosy . The findings related to prevalence of unfavorable attitude such as eating limitation and negative behavior in the community are consistent to the study done in eastern Nepal [4] . One of the reasons behind this unfavorable attitude may be overall poor literacy rate and more specifically poor literacy rate of female of the study region . The level of attitude among the community members towards leprosy is also similar in the study done in Ethiopia [28] . The study findings showed that knowledge and attitude of leprosy among community are influenced by various socio-demographic characteristics of the community members . This finding is supported by the study done in community members in western region of Nepal [25] . This result is also congruent with the studies done in Cameroon and Ethiopia [21; 28] . This study showed that stigma is still prevalent in communities of Terai districts of Nepal . The study identified various kinds of stigma/myths such as participants preferring to hide their leprosy status , thinking less of self if any of the family member is affected by leprosy , thinking that leprosy has caused shame , feeling others think less of a person with leprosy , thinking that others would avoid a person with leprosy , and reporting that it would cause problem in marriage . This indicated that preference to concealment towards leprosy status is still prevalent due to grounded stigma of leprosy in communities of Nepal . This finding is similar to study done in Western region of Nepal [25] . Such finding relating to prevalence of preference towards concealment of the disease and feeling of shame towards leprosy is also congruent to studies done in eastern Nepal [4; 31] . The finding regarding stigma related to leprosy causing problem in marriage was similar to the qualitative study done in South East Nepal [32] . The results regarding the nature of perceived stigma towards leprosy and leprosy patients among community people was similar in the study conducted in Thailand [33] . The finding is also supported by the study done in Indonesia [34] . The level of stigma is high among high proportion of study participants in this study and this finding is supported by the studies done in western Nepal [25] and rural India [34] , example around 47% and 22% of the respondents with response of not preferring to buying foods from leprosy affected individuals in western Nepal and rural India respectively which is quite similar to this study ( 29% ) . In this study , socio-demographic variables like age , ethnicity , marital status , education , occupation , etc . and knowledge were found to influence stigma and EMIC score among community members . The finding is supported by the findings of the study done in Pokhara [25] . Nevertheless , unlike the finding of the study done in Pokhara , there was no association between perceived stigma of leprosy and residence ( districts ) of the study participants [25] . The reason for this dissimilarity may be the effect of teaching hospital and leprosy hospital raising similar kind of consciousness towards leprosy among the people . Knowledge and beliefs about leprosy has been found to be associated with stigma in leprosy in many studies conducted in China [35] and Nepal [4] . Myths such as not allowing child to play with children of leprosy affected individuals , not sitting together with leprosy affected ones , not preferring to marry with one with family history of leprosy , and not sharing foods with leprosy affected individuals suggest how deep-rooted misconceptions of leprosy are prevalent in the communities . It was also found that study participants reported that leprosy affected ones would get difficulty in getting job . There were various unfavorable attitudes towards leprosy prevalent in the communities of Terai districts of Nepal . Similarly , knowledge regarding leprosy causes , transmission , sign and symptoms and treatment were also not adequate for breaking the transmission of the disease and early identification for prompt treatment . Also , different myths and misconceptions are still present in the communities in different socio-demographic groups of the population . Progress towards leprosy eradication is only possible by making people to better understand its transmission . So , to make the leprosy control programme a success by eliminating and eradicating this old disease , the first and foremost thing to do is to strategize the programmes as per strata according to socio-demographic characteristics of the population for enhancing their knowledge regarding leprosy , its cause , symptoms , transmission , prevention and treatment and thereby changing the attitude to make it more favorable towards leprosy . Furthermore , advocacy programmes should be developed engaging people affected with leprosy , local health workers , and deep-rooted traditional healers of the rural communities and local media to provide information about leprosy to the community people . Also , empowerment workshops should be organized for the leprosy affected individuals including unaffected females of the community who can further help to aware other people once empowered . Additionally , more information , education and communication materials need to be developed and made accessible to the general public in both the least and the most affected communities . Further studies are needed to develop new diagnostic and screening tools which can identify leprosy at earlier and hidden stage at the community level . As state 2 of Nepal lies adjacent to communities of India which is one of the countries with concentrated burden of leprosy , further studies on communities of state 2 of Nepal bordering to Bihar state of India is recommended which might show the issue of inadequate knowledge , negative attitude and high stigma at more worse scenario . These communities need to be addressed in terms of strengthening their capacity to prevent and control this growing burden of leprosy with sufficient supporting evidence . Further study on the issues of this neglected tropical disease in a larger scale both in rural and urban areas of Nepal is recommended to bring forth clearer picture . | Though Nepal declared leprosy to be no more a public health problem in 2010 , its burden is constantly rising in Terai communities for the past 2 years with 3000 new leprosy cases being identified annually . With the fact that community’s knowledge and perception is important for prevention and control of leprosy this study aimed at assessing the community knowledge , attitude and stigma of leprosy amongst the community members living in Dhanusha and Parsa districts of Southern Central Nepal . The study was conducted in the communities of Dhanusha and Parsa by interviewing 423 individuals using structured questionnaire . All study respondents had heard about leprosy with main source of information to be health workers/hospital . A good proportion had myths such as bad blood/curse/heredity/bad deeds as the cause of leprosy and reported religious rituals as its treatment . Although more than half had good knowledge , only 2/5th had favorable attitude . The attitude was found to be influenced by knowledge . Also , knowledge , attitude and stigma score were found to be influenced by age , sex , ethnicity , religion , education and occupation . Strategizing the awareness programmes according to socio-demographic characteristics for enhancing the knowledge regarding leprosy cause , symptoms , transmission , prevention and treatment , could change the attitude to make it more favorable and thereby would help in reducing leprosy burden and enhancing the quality of life of leprosy patients . | [
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... | 2019 | Community knowledge, attitude, and perceived stigma of leprosy amongst community members living in Dhanusha and Parsa districts of Southern Central Nepal |
N-Methyl-d-aspartic acid ( NMDA ) receptors are widely expressed in the brain and are critical for many forms of synaptic plasticity . Subtypes of the NMDA receptor NR2 subunit are differentially expressed during development; in the forebrain , the NR2B receptor is dominant early in development , and later both NR2A and NR2B are expressed . In heterologous expression systems , NR2A-containing receptors open more reliably and show much faster opening and closing kinetics than do NR2B-containing receptors . However , conflicting data , showing similar open probabilities , exist for receptors expressed in neurons . Similarly , studies of synaptic plasticity have produced divergent results , with some showing that only NR2A-containing receptors can drive long-term potentiation and others showing that either subtype is capable of driving potentiation . In order to address these conflicting results as well as open questions about the number and location of functional receptors in the synapse , we constructed a Monte Carlo model of glutamate release , diffusion , and binding to NMDA receptors and of receptor opening and closing as well as a model of the activation of calcium-calmodulin kinase II , an enzyme critical for induction of synaptic plasticity , by NMDA receptor-mediated calcium influx . Our results suggest that the conflicting data concerning receptor open probabilities can be resolved , with NR2A- and NR2B-containing receptors having very different opening probabilities . They also support the conclusion that receptors containing either subtype can drive long-term potentiation . We also are able to estimate the number of functional receptors at a synapse from experimental data . Finally , in our models , the opening of NR2B-containing receptors is highly dependent on the location of the receptor relative to the site of glutamate release whereas the opening of NR2A-containing receptors is not . These results help to clarify the previous findings and suggest future experiments to address open questions concerning NMDA receptor function .
Excitatory synapses onto hippocampal CA1 pyramidal cells are a well-studied model system for understanding synaptic transmission and plasticity in the central nervous system [1] . These synapses contain two types of ionotropic receptors activated by the neurotransmitter glutamate: the fast α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid ( AMPA ) receptor and the slower N-methyl-d-aspartate ( NMDA ) receptor [2] . The NMDA receptor ( NMDAR ) is permeable to Ca2+ , which in turn drives multiple forms of synaptic plasticity [3]–[6] thought to underlie forms of learning and memory [1] . In addition to its role in plasticity , slow NMDAR currents help shape the dynamic activity of neurons and neural networks [7] , [8] . The NMDAR is a multimer , composed of two obligatory NR1 subunits and two ( or more ) NR2 subunits [9] . The NR2 subunit exists in multiple isoforms . In the mammalian forebrain , the majority of NR2 subunits are of the NR2A or NR2B subtype [9] . The expression levels of the NR2 subtypes is developmentally regulated [10] . At birth , the NR2B subtype is dominant and there is very little NR2A expression . During the course of development , NR2A expression gradually rises to adult levels . NR2A- and NR2B-containing receptors may exhibit differences in their spatial localization [11]–[14] and may also vary in relative numbers across synapses [15]–[17] . NR2 subunit identity can also confer very different biophysical properties onto the NMDA receptor [9] , [18] . Differences in subunit composition could thus have important consequences for synaptic plasticity and neuronal function . Notwithstanding the importance of these issues , fundamental questions concerning the activation properties of NMDA receptors containing different NR2 subtypes remain open . One question concerns the fidelity with which NMDARs of distinct subunit composition at the synapse respond to glutamate release . Some studies have suggested that the open probabilities of NR2A- and NR2B-containing receptors are similar [19] , while others indicate that they are dramatically different [20] , [21] . Pharmacological isolation of each receptor subtype could potentially resolve this issue , but the available drugs for blocking NR2A-containing receptors are not specific enough [22]–[24] . A second question concerns the number of functional NMDARs at a synapse . Measurement of NMDAR activation at single spines using two-photon glutamate uncaging and calcium imaging has begun to address this issue [17] , [25] , [26] . However , it is not known how these measurements would be affected by differences in NR2 subunit composition . Other open questions concern the spatial distribution of NMDARs containing different NR2 subtypes in and out of synapses and the response of receptors at different locations to glutamate release . These may have particular bearing on experiments that suggest spontaneously released vesicles activate a different population of synaptic receptors from those activated by vesicles released due to action potentials [13] , [27] . The role of NR2 subunit identity in long-term potentiation is also an open question , as the experimental evidence is contradictory [23] , [28] . Computational models with parameters well-constrained by experimental measurements can shed light on these issues . Previous models examining the role of the NMDA channel in synaptic transmission [29]–[31] have not included NR2 subtype differences and therefore have been unable to address how different subtypes could contribute to the synaptic response . To better understand the potential role of differential NR2 subunit-dependent NMDAR kinetics in synaptic transmission and plasticity , we have constructed a biophysically-realistic model of a CA1 excitatory synapse , incorporating glutamate release , diffusion and binding , and NMDAR opening and closing . We then used this model to address each of the open questions mentioned above . The model allowed us to interpret and integrate previous experimental results , as well as to suggest experiments to address remaining open questions .
Previous models of NMDA receptors [30]–[33] have been based on the kinetic schemes derived from recordings by Lester and Jahr [29] . Since then , genetic techniques have allowed for a more detailed understanding of the biophysics of NMDA channel gating [21] , [34] , [35] . Erreger et al . [21] measured single-channel NMDAR kinetics of recombinant diheteromeric NMDARs by expressing NR1 with either NR2A or NR2B . These recordings were used to fit kinetic schemes for each receptor type ( Figure 1E ) and predicted the average behavior of the channels in response to brief glutamate pulses . The surprising result from this study was that the kinetics of previous models of NMDA receptors were similar to those observed for NR2B-containing receptors , with slow opening , closing and glutamate unbinding . The NR2A-containing receptors , on the other hand , showed markedly faster kinetics , with an on-rate constant for glutamate ( ∼3×107/M·sec ) similar to that of the AMPA receptor ( ∼2×107/M·sec ) . These results also implied that NR2A-containing receptors were better suited to sense rapid glutamate transients in the synaptic cleft and would open with a high probability , while NR2B receptors appeared to be tuned to sense ambient levels of glutamate and would open with much lower probability . However , the study used simplified models of glutamate concentration in the cleft and therefore may not inform us about how NMDA channels open in response to synaptically released glutamate . We have previously developed a stochastic model of AMPA receptor transmission [36] using standard Monte Carlo techniques [31] , [37] , [38] , which accounted for channel structure , activation and desensitization [39]–[42] . By implementing the kinetic schemes fit for NMDA receptors [21] within this biophysically-realistic Monte Carlo framework , we were able to simulate individual NMDA receptor responses to realistic glutamate signals . The model tracked the diffusion of individual glutamate molecules in a structurally-constrained model of the synapse . The simulated synapse had dimensions corresponding to an average nonperforated synapse on a mushroom or stubby spine [43] . Glutamate was released from a vesicle and diffused through a fusion pore out into the cleft , where it diffused out into the extrasynaptic space , potentially interacting with the receptors on its way . Parameters used for the simulation of glutamate diffusion are listed in Table 1 . The temperature-adjusted rate constants of the NMDAR model are listed in Table 2 . NR2A-containing receptors ( NR2A-NMDARs ) were about three times as likely as NR2B-containing receptors ( NR2B-NMDARs ) to open in response to the release of a single vesicle ( P = 0 . 73 vs . 0 . 25 ) . NR2A-NMDARs opened and closed much more quickly , and their peak open probability was more than 10 times greater ( 0 . 34 vs . 0 . 03 , Figure 1B–E ) . On the other hand , NR2B-NMDARs closed more slowly than NR2A-NMDARs ( τw = 14 . 4 vs . 130 msec , τ1 = 12 . 7 vs . 47 . 9 msec , τ2 = 505 vs . 964 msec , Figure 2A and 2B ) . The weighted time constant of decay , τw , was calculated by taking an average of the two time constants ( τ1 and τ2 ) derived from a double exponential fit , weighted by their coefficients in that fit . When NR2B-containing NMDARs opened , they spent twice as much time open ( 8 . 0 vs . 16 msec ) as NR2A-containing receptors . Thus , the overall time open and average open probability were only about 50 percent greater for NR2A-NMDARs ( time open = 5 . 9 vs . 4 . 1 msec , Figure 2D ) . Single-channel measurements of cloned channels have shown that , as in our model , NR2A-containing receptors have a greater probability of opening than NR2B-containing receptors [21] , [22] . However , the results of another study suggests that this may not be the case for receptors expressed in neurons . Prybylowski et al . [19] overexpressed either the NR2A or the NR2B NMDAR subunit in cultured cerebellar granule neurons and recorded NMDAR currents from nucleated patches in response to brief applications of glutamate and MK-801 , a very high affinity open-channel NMDAR blocker . The decrease in current over successive stimulations , which reflected the open probability during the previous applications , was essentially the same in the control and in both of the overexpression conditions . This is an indirect measurement of open probability however , and the lack of observed differences between conditions could be explained by a number of other factors . First , the affinities of MK-801 with channels containing different subtypes are not the same . Dravid et al . [44] reported that the IC50 for NR2A-containing NMDA receptors was 4 . 5 times greater than for NR2B-containing receptors , while fitted kinetic schemes showed similar off-rate constants for the two receptor types . Thus , the on-rate constant should be about 4 . 5 times faster for NR2B-NMDARs , so they will be blocked faster for the same open probability . Second , the measure of open probability chosen to quantify the response , peak current , will produce a measurement that disproportionately reflects the opening of NR2A-containing receptors , due to their much faster opening and higher peak open probability . To examine how these factors may have affected the results of Prybylowski et al . [19] , we constructed a simulation of their experiment ( Figure 3 ) , using a modified version of our NMDAR kinetic schemes and the kinetic parameters from Dravid et al . [44] for the block of NMDARs by MK-801 . The kinetic scheme was essentially a doubled version of the eight-state kinetic scheme , with a blocked and unblocked version of each of the eight states and a single , reversible connection between the blocked and unblocked open states . When MK-801 is bound to the receptor and the receptor is no longer in the open state , MK-801 becomes trapped , so both blocking and unblocking are glutamate-dependent . We used IC50 values ( 18 and 4 nM for NR2A- and NR2B-NMDARs , respectively ) for resting membrane voltage [44] , and ran the simulation at 23°C [19] . We applied a single , 4 msec pulse of 1 mM glutamate , followed ten pulses of 200 µM MK-801 and 1 mM glutamate [19] , spaced 10 seconds apart . We set the single free parameter , the off-rate constant for MK-801 ( 0 . 25/sec ) , so as to produce a block after the first stimulation similar to what was observed experimentally . The simulation was deterministic , and reproduced the probabilistic time evolution of receptor state . As expected , the open probabilities were quite different , with peak open probabilities of 0 . 42 for NR2A-NMDARs and 0 . 11 for NR2B-NMDARs ( Figure 3C ) . The average percent block from one stimulation to the next was also quite different ( 19 vs . 8 . 4 percent ) . When plotted relative to the peak open probability of the control stimulus , the slope of the change in peak open probability is initially higher for NR2A-containing receptors , but tapers off to a level similar to that of NR2B-containing receptors ( Figure 3D ) . To approximate the overexpression cases of Prybylowski et al . [19] , we considered the case of 80 percent NR2A-NMDARs and 20 percent NR2B-NMDARs versus 80 percent NR2B-NMDARs and 20 percent NR2A-NMDARs . The relative expression of the different subunit types in the experiment were unknown , so these cases were chosen to represent high and low expression cases; other choices yielded similar results . The normalized decline in peak open probability was very similar in the two cases ( Figure 3H ) . As in the experimental results , the slope of the decline was initially steeper for the NR2A “overexpression” case ( −0 . 11 vs . −0 . 086/stimulation for stimuli 1–4 ) , but similar later ( −0 . 039 vs . −0 . 038 for stimuli 5–10 ) . The one feature observed by Prybylowski et al . [19] that our simulations did not reproduce was a larger relative block of NR2B-containing receptors after the first stimulation , impossible given the steeper initial decline for NR2A-containing receptors . However , Monte Carlo simulations of the experiment showed a high degree of trial-to-trial variability , so it is possible this feature was simply due to random trial-to-trial variation in the experiments ( Prybylowski et al . [19] did not report the number of trials or show error bars for their data ) . Multiple lines of evidence have shown that multivesicular release , the release of more than one glutamate vesicle in response to a single action potential , may occur at central synapses [25] , [45] , [46] . However , little is known about the consequences for neural function . We have previously shown that AMPA receptors can respond in a nearly linear fashion to multivesicular release [36] . In order to extend these results to NMDA receptors , and compare the response of receptors with different subunit composition , we simulated multivesicular release by allowing glutamate to diffuse out of two vesicles . Results at this spatial and temporal spacing were representative of a variety of spacings; changing these parameters did not alter the results significantly . Figure 4A and 4B summarize the results . NR2B-NMDARs responded linearly , with the probability of success for two vesicles 2 . 1 times what it was for one ( 0 . 52 vs . 0 . 25 ) , while NR2A-NMDARs showed only a modest increase in success probability ( 0 . 87 vs . 0 . 73 , ratio = 1 . 2 ) . Success probability was still 67 percent greater for NR2A- than for NR2B-NMDARs , but time open was 15 percent longer for NR2B-NMDARs ( Figure 4B ) . Chavis and Westbrook [47] found a population of synapses expressing NR2B-containing NMDARs early in development that showed a high probability of NMDA receptor activation . These responses may have been due to an increased probability of multivesicular release at these synapses , or to an increase in the number of glutamate molecules per release event [48] , typically denoted as the quantal size , q . The reason NR2B-containing receptors are able to respond linearly to multivesicular release and NR2A-NMDARs are not is relatively intuitive . Since 75 percent of NR2A-NMDARs open in response to a single vesicle release , not many receptors are available to respond to the additional glutamate . NR2A-NMDARs , on the other hand , have a low probability of opening , so there are enough receptors available to produce a graded response . This may seem counterintuitive given the higher affinity of NR2B-NMDARs , but the conditions simulated are far from steady state , so the dynamic properties of the receptors , rather than their steady-state properties , determine their behavior . To further explore how receptor saturation shaped the NMDAR responses , we released a glutamate from a single vesicle and varied q from 1000 to 20000 molecules . While this is not a physiological value for q , it does illustrate how NR2B-NMDAR responses saturate at much higher glutamate levels . Figure 4C and 4D show how success probability and time open increase with the number of glutamate molecules released . NR2A-containing NMDAR success probability reaches 90 percent of its saturated level with only 4000 glutamate released , but NR2B-containing receptors do not reach 90 percent until 10000 glutamate , or the equivalent of five vesicles , are released . This is in agreement with experimental results showing that NMDA responses were not saturated by single release events [49] and previous simulations where only a single receptor subtype ( NR2B ) was considered [31] . Our results suggest that at synapses where multivesicular release can occur , or even where the glutamate content of single vesicles is variable , NR2B-containing NMDARs could be very important for the transduction of graded glutamate signals . We next studied the location-dependence of NMDAR activation relative to the site of glutamate release . When glutamate is released from a vesicle in the active zone , a very short-lived , high-concentration “hot spot” is produced in the synaptic cleft . AMPA receptors are very sensitive to this , and their probability of opening shows a similar hot spot around the site of release [36] . We would expect NMDARs , which have a higher affinity and lower desensitization , to open in response to more distant glutamate release , but we would also expect distinct differences between receptors containing different NR2 subtypes , due to their different kinetics . To investigate this , we compared the response of receptors in our model located close to the release site with the response of those located farther away . We held the site of release constant , close to the center of the synapse , and randomly varied the locations of the receptors . Figure 4E and 4F show the probability of receptor opening as a function of position in the cleft . NR2B-containing receptors showed an activation hot spot similar to that of AMPA receptors , while NR2A-NMDARs were almost indifferent to location . The NR2B-NMDARs closest to the release site ( mean distance = 44 nm , P = 0 . 46 ) were more than three times as likely to open as those farthest away ( mean distance = 228 nm , P = 0 . 14 ) . For NR2A-NMDARs , the difference was less than 10 percent . The intuitive explanation of these response properties depends , again , on the dynamic properties of the receptors . While under steady-state conditions NR2B-NMDARs respond to lower concentrations of glutamate , under the conditions of a short-lived , high concentration glutamate signal the fast on-rate constant of NR2A-NMDARs that allows them to respond to lower concentrations of glutamate . Given the observed differences in location-dependence , regulation of the location of NR2B-containing receptors could have a profound effect on NMDAR transmission and synaptic plasticity . Indeed , an electrophysiological study in knockout mice showed that the location of NR2B-NMDARs may indeed be developmentally regulated [13] . NMDA receptors , primarily of the NR2B-containing subtype , can also be found extrasynaptically [50] . Recent studies have shown that the extrasynaptic pool of NMDARs activate signaling pathways that are distinct from and even opposite to the ones activated by the synaptic pool [51] . We simulated the effect of synaptic glutamate release on NMDA receptors located outside of the synaptic cleft but adjacent to the synapse , at distances of 300–750 nm from the release site . The results are summarized in Figure 4G . The probability of success of extrasynaptic NR2A-NMDARs fell off rapidly at the edge of the synapse , but was still 0 . 3 at 750 nm . Extrasynaptic NR2A-containing receptors have been reported recently [14] , but they are probably quite rare , and a function has not been proposed for them . Our results suggest that if they are located in the vicinity of synapses , they should be fairly sensitive to single release events . NR2B-containing receptors , on the other hand , already had a low probability of opening at the edge of the synapse , which dropped to 0 . 04 at 750 nm . Individual extrasynaptic NR2B-NMDARs would be unlikely to open in response to glutamate release , and significant activation of extrasynaptic receptors would require that glutamate diffuse over an area of membrane large enough to contain a number of receptors . A number of studies have shown evidence of extrasynaptic NMDAR activation [33] , [52] , [53] , suggesting that this may be the case . Our estimates of NR2B activation by efflux of glutamate from the cleft after the release of a single vesicle are similar to previous simulations [31] , [54] but somewhat lower than other models where glutamate diffusion occurs in a neuropil modeled as a porous medium [33] , [55] . This difference is due to assumptions about the amount of glutamate released by a single vesicle . The number of NMDARs at individual synapses has been estimated from electron microscopy studies [56] . More recently , a tissue preparation technique which provides near one-to-one labeling of receptors present has provided approximate lower and upper bounds ( 10 and 100 ) for this number [57] . However , these anatomical techniques cannot distinguish functional receptors [58] . Physiological measurements [2] can in principle yield the number of active NMDAR by comparing miniature EPSCs to single channel currents . However , dendritic spines are far too small to record from individually , and techniques such as minimal stimulation do not reliably isolate single synapses [59] , so an alternative approach must be used . Two-photon glutamate uncaging [17] , [60] , [61] or calcium imaging [17] , [26] can be used to record synaptic activity at single dendritic spines . Nimchinsky et al . [26] used calcium imaging to estimate the number of NMDARs at hippocampal synapses . They measured the frequency of synaptic failures in the presence and in the absence of D-CPP , a competitive NMDA antagonist , and calculated M , the number of NMDARs present at the synapse ( see Methods ) . However , they did not differentiate between receptors containing different NR2 subtypes . We ran our simulations at 30°C [26] and determined the probabilities of opening for NR2A-NMDARs ( 0 . 70 ) and NR2B-NMDARs ( 0 . 20 ) . Using the values of vesicle release probability , mean number of receptors opening and failure rate from Nimchinsky et al . [26] , and measurements of NR2 subtype-dependent D-CPP block from Lozovaya et al . [62] , we estimated MNR2A and MNR2B , the average number of receptors per synapse containing NR2A and NR2B subtypes ( see Methods ) . We arrived at estimates of 0 . 63 NR2A- and 11 NR2B-NMDARs , on average , per synapse . Because these estimates depend on opening probability , and because the probability of opening of NR2B-containing NMDARs varies so dramatically with location , assumptions about the distribution of receptors will have a strong impact on the results . We calculated the number of receptors as above , but under the assumption that NR2B-NMDARs were located either near the release site , or at the periphery of the synapse . At 30°C the success probability for NR2B-containing receptors close to the release site was 0 . 40 , and our calculations yielded an average of 0 . 44 NR2A- and 4 . 9 NR2B-NMDARs . If NR2B-containing receptors were located at the periphery , as proposed by Tovar and Westbrook [50] , probability of opening dropped to 0 . 11 and the number of receptors rose to 0 . 69 NR2A- and 19 . 2 NR2B-NMDARs . Our estimates compare well with the limits placed by structural [56] and two-photon imaging measurements [26] . Moreover , given the differences in Popen for the two subtypes , our models predict that blocking NR2B receptors would result in a mean reduction of 50 percent in peak current , which is consistent with experimental data [17] . Our kinetic models so far have been restricted to channels that exclusively contain NR2A or NR2B subunits . However , multimeric channels that contain both subunits are known to be present at hippocampal synapses [12] , [63] , although a recent study indicated that the majority of receptors are diheteromeric [64] . Up to this time , no kinetic model exists for a triheteromeric channel , as isolation of these channels for recording would be extremely difficult , though it may be possible by exploiting differential sensitivity to antagonists such as ifenprodil and zinc [12] , [65] , [66] . Without a kinetic scheme , it is difficult to estimate the number of these channels at synapses . As a first-pass approximation , we constructed a kinetic scheme derived from the schemes of the diheteromeric channels ( Figure 5A ) . We assumed that glutamate bound and unbound from each subunit independently , so there were two single-bound states ( 1A and 1B ) . The rate constants for these steps were the same as the rates for NR2A and NR2B in the diheteromer models . For the other kinetic transitions , which are proposed to be due to conformational changes in the NR1 subunits , we set the forward and reverse rate constants of each state transition such that the ratio between these rates and the sum of the magnitudes of the rates were the mean of those in the NR2A- and NR2B-NMDAR models . We used this kinetic scheme in our model to estimate the kinetics and probability of opening of these simulated triheteromeric receptors ( Figure 5B ) . The triheteromer kinetics were intermediate between those of NR2A- and NR2B-NMDARs , but closer to those of NR2A-NMDARs . The weighted time constant of decay was 19 . 0 msec ( τ1 = 15 . 8 msec , τ2 = 695 msec ) , the probability of success was 0 . 41 , and the time open given a success was 7 . 8 msec , yielding an overall time open of 3 . 1 msec . If triheteromeric receptors behave similarly to those in our model , then in mature animals , where NR2A expression levels are high , a significant fraction of the NMDA receptors would have kinetics significantly faster than those assumed by most previous models , even if the majority of NR2A subunits were incorporated in triheteromeric receptors . This would have significant consequences for the results of many previous models . Using the results from this simulation , we repeated the calculation of the mean number of receptors per synapse from the data of Nimchinsky et al . [26] ( Figure 5C ) . We assumed that inhibition constant for D-CPP for the triheteromeric channel was the geometric mean of those for the diheteromers . To solve for the number of receptors of three species ( MNR2A , MNR2B , MNR2AB ) , we needed an additional constraint . We calculated solutions under four different assumptions . The first , that only NR2A and NR2B receptors were present , is what we calculated earlier ( MNR2A = 0 . 63 , MNR2B = 11 ) . The second , that only triheteromeric and NR2B receptors were present , yielded MNR2AB = 3 . 0 and MNR2B = 8 . 3 . Under the assumption that only NR2A and NR2A/B receptors were present there was no positive solution . Finally , we assumed that all three types were present and that they combined randomly ( that is , ) . Under these conditions , MNR2A = 0 . 29 , MNR2AB = 1 . 7 and MNR2B = 9 . 4 . Overall , these results indicate that NR2A subunits made up somewhere between 5 and 15 percent of the total NMDA subunits present in functional receptors . This is not particularly surprising given the developmental age of the animals , but a similar approach could be used to estimate the number of receptors present at different developmental time points . Such estimates would be valuable in understanding the role of NMDARs in adult synapses , and in understanding the role of the developmental NR2 subunit switch . Synaptic NMDARs are incorporated into multiprotein complexes and are in close proximity to many calcium-sensitive enzymes , such as Ca2+-Calmodulin-dependent Kinase-II ( CaMKII ) [67] and protein phosphatases [68] . These enzymes are ideally positioned to detect the time-varying calcium concentration changes due to influx through NMDARs and transduce these signals by altering the phosphorylation state of their various substrates . The ensuing signaling events can lead to rapid alteration in the number of AMPARs in the synapse [61] , [69]–[71] , activation of protein synthesis machinery in dendrites [72] and gene transcription in nucleus important for long-term maintenance of neuronal plasticity [73] . A number of recent studies have suggested that NR2A- and NR2B-containing NMDA receptors selectively induce potentiation and depression , respectively , of hippocampal synapses [28] , [74] , [75] . However , other studies have suggested that either subtype can be sufficient for the induction of long-term potentiation [23] , [76] , that NR2B-containing receptors can drive LTP [77] , [78] , or that either subtype can drive long-term depression [79] . In many of these studies , differences were seen depending on developmental age and induction protocol . The differences in the ability of the receptor subtypes to induce plasticity could arise due to their distinct kinetics , which result in distinct spatiotemporal pattern of calcium concentration in the postsynapse . The rapid , reliable opening of NR2A-containing NMDA receptors , would produce large rapid increases in internal Ca2+ concentrations , which has been shown to selectively lead to LTP [80] . On the other hand , the much longer-lived activation of NR2B-containing NMDARs could lead to enhanced potentiation in situations where depolarization occurs over a long period of time , such as during bursts . On average , NR2B-containing NMDA receptors let in as much or more Ca2+ than NR2A-containing NMDARs , but they also fail much more often . Therefore , the variability in the Ca2+ signal through NR2B-containing NMDARs is very high . This variability could have significant effects on LTP induction . We next explored these questions by coupling our model of NMDAR activation to a postsynaptic model of LTP . We calculated calcium influx from receptor opening data from our Monte Carlo simulation and used it as the input to a model of a CaMKII switch [81] . This latter model is deterministic , and assumed that all reactions are taking place in a single , well-stirred compartment . Each molecular species was represented by a single , time-varying concentration , and the model was a system of differential equations relating those concentrations . In the model , CaMKII activation was bistable between an unphosphorylated state and an activated state where a large fraction of CaMKII subunits are phosphorylated ( see Methods ) . Its activation is set by the balance of the rates of calcium-dependent phosphorylation and autophosphorylation with the rate of dephosphorylation by Protein Phosphatase 1 ( PP1 ) . Under baseline conditions , dephosphorylation is faster than phosphorylation and activity tends towards a low level . Once calcium-dependent phosphorylation pushes the level of activation above a threshold , autophosphorylation begins to out-compete dephosphorylation , and CaMKII activity tends towards a high level . Calcium current was determined by a simple model , based on the Goldman-Hodgkin-Katz equations [26] . Conductance and calcium permeabilities were the same in NR2A- and NR2B-NMDARs , as has been measured experimentally [82] , [83] . We assumed the block of NMDARs by Mg2+ was an instantaneous , voltage-dependent process , and modeled by fitting a sigmoidal curve to fractional block versus voltage data [83] . Our LTP induction protocol ( Figure 6A and 6B ) consisted of a train of 100 stimuli delivered at 100 Hz . The synapse had 60 percent release failure and both facilitation and depression were modeled [84] , based on measured values [85] , [86] . We modeled postsynaptic voltage using a simple , single exponential approximation of the results of a detailed simulation [87] . For each stimulus , the voltage exponentially approached −10 mV for 1 msec with a time constant of 0 . 1 msec and fell back towards the resting voltage with a time constant of 9 msec . NR2A-containing NMDARs let in more calcium per receptor than NR2B-NMDARs ( Figure 6C–F ) , and were more effective at driving LTP ( Figure 7A–E ) . The probability of a synapse to potentiate after tetanic stimulation exceeded 99 percent with only 3 NR2A-NMDARs present , while the same required 9 NR2B-NMDARs ( Figure 7C ) . Even if we set the number of receptors such that the total time open was the same , NR2A-NMDARs showed a greater rate of potentiation . This is because the time they spent open was mostly right after glutamate release , while the postsynaptic cell was depolarized . The total time open during the one second tetanic stimulation period , however , predicted the probability of potentiation well ( Figure 7D and 7E ) . This quantity was about three times longer per receptor for NR2A-NMDARs than for NR2B-NMDARs ( 87 . 4 vs . 26 . 1 msec ) . We ran the simulation using our hypothetical kinetic scheme for triheteromeric receptors . Again , the behavior of the NR2A/B receptors was intermediate between the diheteromers but more similar to that of NR2A-NMDARs ( Figure 7F ) . Reaching a 99 percent probability of potentiation required 4 receptors , and the time open during the tetanus also predicted the probability of potentiation well . The precise timing of postsynaptic spikes relative to presynaptic glutamate release can have drastic effects on the magnitude and direction of synaptic potentiation [88] . Because the opening of NR2A- and NR2B-containing NMDARs have very different time courses , they may show great differences in this kind of precise timing-dependent plasticity . To test this , we paired 50 presynaptic glutamate release events with 50 postsynaptic voltage spikes , and varied the relative timing between them ( Figure 7G ) . NR2B-NMDARs showed a much broader window in which paired stimuli could still drive LTP , while NR2A-NMDARs required relatively precise timing . The width at half height for NR2B-NMDARs was twice that of NR2A-NMDARs ( ∼36 vs . 18 msec ) . This suggests that the NR2 subunit may play an important role in determining the spike timing-dependent properties of LTP .
We found that NR2A-containing receptors were about three times as likely as NR2B-containing receptors to open in response to a single glutamate vesicle release . This is in agreement with previous , in vitro studies [20] , [21] . In addition , when NR2B receptors opened , their total time open was about twice as long on average as NR2A-containing receptors , so the trial-to-trial variability in time open was much greater . The kinetics of the NR2B-containing receptors were much slower , however , and receptor opening was spread out over a much longer time . The peak open probability was more than 10 times greater for NR2A-containing receptors than for NR2B-containing receptors , while the weighted time constant of decay was almost 10 times slower . This distinction between different measures of open probability is important for the interpretation of experimental results . For example , a number of studies have used progressive blockade of NMDAR excitatory post-synaptic currents ( EPSCs ) by MK-801 to estimate open probability [19] , [33] , [47] . MK-801 is an irreversible open channel blocker , so progressive blockade reflects prior NMDAR opening . Typically , it is interpreted to indicate success probability , or even the number of receptors activated . However , blockade is usually measured relative to a baseline , and blockade is not instantaneous , so in the case of a chronic application of MK-801 , blockade is actually indicative of mean time open . Thus , our results agree with Scimemi et al . [33] , who showed that MK-801 blocked NR2B-containing NMDARs faster than NR2A-containing NMDARs . In a study where MK-801 is applied briefly [19] , blockade should better indicate peak open probability , although it may not if washout is incomplete . Our results were based on receptor kinetics measured in a heterologous system . However , it has proved much more difficult to determine the properties of NMDA receptor subtypes natively expressed by neurons . One study that attempted to do so [19] implied that there was no difference in average open probability between NR2A- and NR2B-containing receptors . However , other studies suggest that the differences in activation kinetics between the two receptor subtypes measured in situ were similar to those measured in vitro . Our simulations of the Prybylowski et al . [19] experiment predicts that this result could potentially have arisen despite a difference in open probability , due to differences in antagonist affinity and the way receptor block was quantified . The presence of triheteromeric receptors could further complicate this situation . To finally resolve the question of the open probabilities and kinetics of NMDA receptors in synapses , direct measurements will have to be made . However , this has proved elusive , primarily due to the lack of a selective blocker for NR2A-containing receptors . However , genetic methods can be used to isolate receptor subpopulations [66] , [89] . In combination with two-photon uncaging and/or imaging [17] , [26] , these methods should allow the properties of NMDA receptors to be measured in situ and the predictions of our model to be tested . The slower opening kinetics of NR2B-containing receptors could have important consequences for calcium influx during miniature excitatory postsynaptic events . Due to the small size of the dendritic spine and the high resistance of the spine neck [90] , AMPA mEPSCs should be sufficient to depolarize the spine head and relieve the NMDAR Mg2+ block . As the peak open probability of the NR2A-containing receptor is much greater than that of the NR2B-containing receptor , the Ca2+ influx during the brief AMPA mEPSC would be much greater . It has been shown that NMDA miniature excitatory currents can stabilize synaptic strength [72] . One prediction of our model is that the homeostatic stabilization of AMPA receptors at the synapse is preferentially mediated by NR2A-containing NMDARs . This prediction could be tested by studying whether homeostatic stabilization in the presence of ifenprodil ( which blocks NR2B containing receptors ) differs from that in NR2A knockout animals . We studied the differences in receptor activation as a function of the amount of neurotransmitter released . Such differences can arise either due to variation in the amount of neurotransmitter contained in vesicles [31] , [91] or differences in the number of vesicles released [25] , [45] , [46] . We found that synapses with predominantly NR2A-containing receptors were nearly insensitive to differences in the amount of neurotransmitter , while those with predominantly NR2B-containing receptors responded in graded fashion ( Figure 3 ) . We next considered the impact of distance from the release site on the activation of NMDA receptors containing different subtypes . While NR2A-containing receptors responded about equally regardless of where they were in the synapse , NR2B-containing receptors were highly location-sensitive , with the receptors located closest to the release site opening three times as often as the receptors located farthest away . Receptors located perisynaptically , outside the synapse but less than 1 µm from the release site , showed a very low probability of opening . These results have important implications for the hypothesis that , over the course of development , NR2B-containing receptors at the center of synapses are displaced by NR2A-containing receptors , such that NR2B-containing receptors end up preferentially located at the periphery of synapses . This idea is based on the finding that miniature excitatory post-synaptic currents ( mEPSCs ) progressively declined with age in NR2A knockout animals , while evoked activity , which could result in multivesicular release , could still produce an NMDA current [13] . Our results suggest that NR2B-containing receptors located at the periphery of synapses would be very unlikely to open , even under evoked activity . This is difficult to reconcile with the experiments of Townsend et al . [13] . One potential explanation is that the mEPSCs of single NR2B-containing receptors are difficult to distinguish from noise , due to the extended , rapidly opening and closing nature of their activation . In the knockout experiments , the number of NR2B-NMDARs decreased over development . If the number of NR2B-NMDARs per synapse is relatively low , spontaneous release would be likely to open only one , or zero , NR2B-containing receptors , making mEPSCs nearly impossible to detect . On the other hand , action potential evoked release , might be multivesicular , leading to the activation of a detectable number of receptors ( Figure 4 ) . Once again , further experiments are needed to test the hypothesis . Our simulations suggest one such experimental test . NR2B-NMDAR exhibit a sharp location-dependence of opening probability , implying that they require a very high concentration of glutamate to open . NR2A-NMDARs are essentially location-independent , suggesting their response is essentially saturated at low concentrations . Thus , a low-affinity antagonist such as L-AP5 or D-AA would have a much more dramatic effect on NR2B-containing receptors . Similarly , the antagonist would be much more effective at blocking NR2B-NMDARs located at the periphery of the synapse . If , later in development , NR2B-containing receptors are not just decreasing in number but are preferentially located at the periphery , we would expect a proportionally much stronger block of evoked activity when applying a low-affinity antagonist . A related prediction of our model is that in addition to the progressive decline in the spontaneous NMDA current in the knockout animal , the variance of the evoked NMDA response should increase . It has also been shown that glutamate spillover from adjacent synapses can activate NMDA receptors [33] , [52] , [92] . Whether or not this happens depends upon the activity of glutamate transporters , the rate of glutamate diffusion , temperature , the geometry of the extracellular space and the extent of sheathing of synapses by glia . We did not address those factors here , but they have been considered elsewhere [31] , [93] . However , the very low opening probability of perisynaptic NR2B-containing receptors in our simulations suggests that the excitation of these NMDA receptors by spillover from a single vesicle is quite difficult . Thus , if significant activation by spillover does occur , glutamate must diffuse far enough to potentially interact with a large number of receptors . We note that our model of the NR2B-containing receptors are similar to those used in Scimemi et al . [33] , and our results on activation probabilities of these receptors are similar . However , it remains to be shown whether under normal in vivo conditions glutamate release at a single synapse ( the conditions we simulate ) can cause significant activation of extrasynaptic NMDARs . It could be that these extrasynaptic NR2B-containing NMDARs instead detect changes in ambient glutamate concentration related to average synaptic activity over longer timescales or to events that cause large amounts of glutamate to be released . Another possible function for these receptors could be to detect signals originating extrasynaptically , such as glutamate release by astrocytes , which may play a role in synchronizing hippocampal pyramidal cell activity [94] . We studied the potential impact of NMDAR subunit composition on postsynaptic long-term potentiation by coupling our model of receptor opening driven by tetanic stimulation to a model of activation of calcium-sensitive enzymes in the postsynapse known to be critical for induction of LTP . We found that either NR2A- or NR2B-containing receptors could drive persistent CaMKII autophosphorylation , but more NR2B receptors were required to reliably drive autophosphorylation . Similarly , the majority of experimental studies in adult animals using concentrations of NMDA receptor blockers small enough to be selective for NR2 subtype have shown that either receptor type can drive LTP [23] , [95] , [96] , though some reports contradict this [28] . That either receptor type could drive LTP stands to reason , as the conductance and calcium permeability of both types would allow large Ca2+ currents to enter the postsynaptic cell while it was depolarized . We note that while our simulations suggest that given nearly equal Ca2+ permeabilities of the two receptor-subtypes [10] , [97] , NR2A-containing receptors let in more calcium than NR2B-containing NMDARs . This is compatible with experimental findings [17] which suggest that synaptic NR2B-containing receptors can have greater or smaller fractional calcium current due to post-translational modifications depending on synapse size and history [58] . In our simulation , the most important variable for determining the probability of LTP was the total time open during the period of tetanic stimulation , which was more than three times greater for NR2A-containing receptors . We would expect the advantage of NR2A-containing receptors in driving LTP to diminish in a low frequency pairing protocol where the postsynaptic cell is held at a depolarized voltage for the entire period of receptor opening , during which NR2A-containing receptors are only open for about 50 percent longer . Still , the advantage of NR2A-containing NMDARs in driving LTP is surprising , considering that NR2B-NMDARs are the dominant receptor type during early , critical periods of development [10] . It could be that early in development other forms of synaptic plasticity are dominant , or that multivesicular release is more common , there is a posttranslational modification that allows more calcium to enter [17] , [58] , or there is a difference in postsynaptic biochemical signaling [98] . Barria and Malinow [78] showed that in slices taken from young animals , LTP was dependent upon interaction between NR2B subunit intracellular C tails and CaMKII . This interaction may be important in allowing NR2B-containing receptors to drive LTP despite their slow kinetics . It is also interesting to note that Harris and Teyler [99] were first able to observe hippocampal LTP at P7 , and that LTP was maximal at P15 , time points which correspond well with the expression of NR2A . We also found a distinct difference between the receptor types in a protocol in which glutamate release was paired with depolarization of the postsynaptic cell at different temporal offsets , similar to experiments used to assess spike timing-dependent plasticity [88] . When presynaptic glutamate release was nearly concurrent with or preceded postsynaptic depolarization by a small offset , calcium entered the postsynapse and CaMKII was autophosphorylated . But , the range of temporal offsets over which CaMKII phosphorylation occurred was about twice as wide for NR2B- as for NR2A-containing receptors , suggesting that the temporal properties of spike timing-dependent plasticity ( STDP ) could vary greatly with subunit composition . STDP is a competitive plasticity mechanism and could play a role in the formation and refinement of neuronal networks [100] , [101] . The more permissive temporal filter of NR2B-containing receptors could allow potentially informative connections to be strengthened and stabilized initially . Later , as the network settles into a more mature state , the more precise temporal filtering of NR2A-containing receptors would allow the circuit to be refined , strengthening only the fastest and most informative of the initially stabilized connections . Another interesting temporal property of NR2B-containing NMDARs was recently reported [102] . Repeated stimulation of the receptors caused a downregulation in Ca2+ permeability . In combination with a permissive temporal filter , this property could allow inputs that are loosely correlated to be stabilized , while guarding against spurious connections by requiring that correlations persist over a long period of time . The same process of early , temporally-permissive filtering and later refinement could also be acting in the adult brain , where smaller , more plastic spines have longer EPSC decay times , consistent with higher NR2B content [17] . The subunit shift seen in development [10] could act as a form of temporal metaplasticity . Such a change has also been shown to take place in the visual cortex during development [103] . A recent study showed that NMDA receptor turnover was rapid and that shifts in NR2 subunit composition could occur within seconds to minutes after LTP induction [104] . Thus , the subunit shift could serve to stabilize the synaptic potentiation and as a bridge between short-term and long-term potentiation . The NMDA receptor is , without question , one of the most important determinants of synaptic plasticity in neuronal systems , and its NR2 subunit can drastically alter its biophysical properties and determine its binding to other components of the postsynaptic density . It is surprising then , that basic pieces of information , such as the relative open probabilities of NR2A- and NR2B-containing receptors at the synapse are still unknown . Our work has attempted to address some of the ambiguities in the in the experimental data , and suggests that the open probabilities of the two receptor might indeed be quite different . In addition , it shows that the receptors are likely to vary greatly in their spatiotemporal response to glutamate release . However , these conclusions still await characterization the basic response properties of the receptors in vivo . Once these basic properties are characterized , many more questions will be able to be addressed , by both experimental and theoretical methods . Understanding , for example , the localization of NMDA receptors , or the role of interactions with signaling molecules in the postsynaptic density , will provide us with valuable insight into the development of neural circuits and neuronal plasticity .
Glutamate was modeled as discrete particles , each occupying a position in 3-dimensional space not restricted to a grid . At each time step each particle took a random step , drawn from a 3-dimensional Gaussian distribution . For each dimension , the standard deviation , σ , was , where D is the diffusion coefficient and dt is the time step . Particles moved to the endpoint of the step unless they collided with a boundary . Boundaries represented cell membranes and collisions at the boundaries were elastic , unless the particle bound to a glutamate receptor or transporter . The space containing the synapse was modeled as two adjacent 500 nm cubes , representing the presynaptic and postsynaptic cells , contained within a larger rectangular prism . The distance across the synaptic cleft was 15 nm , as was the width of the space around the cubes . The active zone was a 350 nm square patch in the center of the cleft face of the postsynaptic cube . 121 possible receptor locations were arranged in a 35 nm-spaced grid across the active zone . On each simulation , receptors were placed randomly at these sites . The release site of the vesicle was always the same , located 18 nm from the center of the presynaptic face of the cleft . The vesicle was a 25 nm cube connected to the cleft by a fusion pore 8 nm wide and 15 nm long . Before release , the glutamate molecules were randomly placed within the vesicle . At release , they were simply allowed to begin diffusing . The diffusion coefficient of glutamate in the neuropil has been recently estimated to be ∼3×10−6 cm2/s at the mossy fiber-granule cell synapse [105] , which is 3× lower than the measured value in free solution [106] . This value was estimated by measuring the reduction of the slow AMPA-mediated EPSC , presumably activated by glutamate spillover from neighboring synapses when slices are loaded with high molecular weight dextran , a crowding agent . This reduction was then fit to a battery of glutamate receptor kinetic models to extract the best fit value of D that matched the observed reduction . We note that this number is an estimate , that depends on the particular kinetic model used , the amount of glutamate released per vesicle and the geometry . Direct measurements of glutamate diffusion have not been made at hippocampal synapses . Therefore , we used a similar procedure to estimate the diffusion constant of glutamate . As a constraint , we used the waveforms of sucrose-evoked AMPA miniature EPSCs measured close to the synapse [107] . We then simulated a battery of kinetic models of AMPAR activation at hippocampal synapses [36] , [42] , [108] in response to synaptic release of glutamate and matched the amplitude , rise-time and decay times of the mEPSC . The AMPAR model of Jonas et al . [108] assumed that the binding of two glutamate molecules to the receptor was sufficient to activate the receptor and postulated that the binding was cooperative . This has been ruled out by subsequent experiments [39] , [40] , but we included it since it is the only published model of hippocampal AMPARs . The AMPAR model of Raghavachari and Lisman [36] was based on validated fits of fast glutamate application to AMPARs to outside out patches pulled from CA1 pyramidal neurons [109] . The model of [42] , although originally formulated for cerebellar AMPARs , was included for completeness as it is the only kinetic scheme that accounts for multiple glutamate binding and conductance states of the receptor . The free variables were the diffusion constant of glutamate and the number of glutamate molecules in a vesicle . The best fit values for these parameters resulted in a diffusion coefficient of 5 . 0×10−6 cm2/sec at 37°C . We note that these values lie at the upper end of the estimates of Nielsen et al . [105] . Moreover , the higher values of D in that study correlated with independent subunit models of AMPAR activation . Since our model of AMPAR activation is also an independent subunit model with multiple sub-conductance states [36] , our estimate of D is slightly higher than that reported . Varying this value by 20 percent did not affect the simulation results qualitatively . We used a fixed time step of 0 . 01 µsec . Receptors were represented by discrete 10 nm square patches on the postsynaptic membrane . When a particle hit one of these patches , a random number was generated to determine whether or not it would bind to the receptor . The probability of binding for a collision was determined by dividing kon , the number of binding events per second per M of ligand , by the expected number of collisions per second , given a ligand concentration of 1 M . The expected number of collisions per time step dt is half the number of particles in the volume defined by the area of the receptor and the mean step size for a particle in one dimension . So , the probability of binding was equal to . The kinetic scheme for the NMDA receptors was as in Erreger et al . [21] ( Figure 1A ) . There were eight states: zero bound ( 0 ) , one bound ( 1 ) , two bound ( 2 ) , two desensitized states ( D1 , D2 ) , two intermediate closed states ( C1 , C2 ) and one open state ( O ) . The rate constants were taken from Erreger et al . [21] and adjusted for temperature ( Table 2 ) . We scaled the rate constants using Q10 = 1 . 4/10°C for diffusion-limited processes and Q10 = 3/10°C for non-diffusion-limited processes [110] . Our simulations were run at 33°C , so our kinetics were significantly faster than those observed by Erreger et al . [21] , whose experiments were conducted at room temperature . A simulation where we fixed the temperature to 23°C , and applied a glutamate pulse of 1–4 mM for 1 msec , exactly reproduced the results of Erreger et al . [21] , as it was , in fact , the same model . Extrasynaptic membranes contained glutamate transporters . They did not have a fixed location on the membrane . Instead , we assumed the density of transporters available to bind glutamate was 10000/µm2 [111] and assumed that the fraction of extrasynaptic membrane was 0 . 1 so that when a particle hit the extrasynaptic membrane it collided with a transporter with probability 0 . 1 . Upon collision , the probability of binding was calculated as above . On subsequent time steps a bound particle could either unbind or be transported and removed from the simulation . The rate constants of the binding , unbinding and transport steps were as in Grewer et al . [112] , adjusted for temperature ( Table 1 ) . The opening and closing of individual NMDARs was independent of the other receptors in the synapse , as assessed by varying the number of NMDARs included . The average success probability and time open of the receptors was the same whether there was one receptor present or 20 . We normally included 20 receptors , and combined the receptors from each simulation into a single pool for analysis . We calculated the average number of receptors of each per synapse based on the data of Nimchinsky et al . [26] , using their equations ( 1 ) ( 2 ) where f is failure probability with no antagonist , f′ is failure probability in the presence of the antagonist , Pr is the probability of neurotransmitter release , pro is the probability a receptor will open given neurotransmitter release , I′/I is the ratio of the NMDA current amplitude in the presence of the antagonist to the amplitude in the absence of the antagonist , and M is the total number of receptors present at the synapse . They could not measure Pr directly , so they used the approximation and solved ( 3 ) numerically , where n = MPro . Nimchinsky et al . [26] report that n = 3 . 1 , and by inspecting their data , we can observe that their mean f = 0 . 43 , f′ = 0 . 58 , and I′/I = 0 . 41 , and that the concentration of D-CPP that will produce an I′/I of 0 . 41 is 240 nM . We can then calculate that Pr = 0 . 60 by Pr = ( 1−f ) / ( 1−e−n ) . From Lozovaya et al . [62] we know that the inhibition constants ( Ki's ) for NR2A- and NR2B-containing NMDARs are 41 and 270 nM . We then ran our simulation at 30°C , the temperature used by Nimchinsky et al . [26] , and determined that Pro for NR2A- and NR2B-containing NMDARs were 0 . 70 and 0 . 20 . We then solved for MNR2A and MNR2B , the number of NR2A- and NR2B-containing NMDARs at the synapse , by ( 4 ) ( 5 ) where fNR2X = 1−Pro and , where D-CPP is 240 nM . The equations could also be solved for the case where three receptor species were present , given an additional equation to constrain the number of each species present . We calculated the average effect of applying 4 msec pulses of 1 mM glutamate and 200 µM MK-801 to NR2A or NR2B-containing receptors using a deterministic , explicit model . We used a doubled version of our NMDAR model , with the second set of states representing having MK-801 bound to the receptor . There was a single , reversible transition between the open and MK-801-bound open states , with forward rate constants of 5 . 0×107 and 1 . 39×107/M·sec [44] . To calculate the time-varying probabilities of being in each of the 16 possible states , we constructed a matrix of state-to-state transition probabilities , P , for a small time step dt . Given , a row vector of the probability distribution over all states at time t0 , we calculated the probability distribution at time t0+t , where t = ndt by . We used a time step of 0 . 1 µsec for the first 200 msec after simulation and 10 µsec between stimulations . We simulated the effect of applying tetanic stimulation to a synapse containing either NR2A- or NR2B-containing receptors . It was assumed that the presynaptic cell was firing at a rate of 100 Hz for 1 second , but that vesicle release at the synapse was stochastic , with an adapting release probability , modeled using the method of Maass and Zador [84] . For each presynaptic spike , the probability of release , Prelease = 1−e−CV . The value of C , the facilitation parameter , was initially set to C0 . After every presynaptic spike C was incremented by α and then decayed back towards C0 exponentially with time constant τC . The depletion parameter , V , was initially set to V0 . Every time a vesicle was released V was decreased by 1 , or , if V<1 , set to 0 . V then decayed back towards V0 with time constant τV . The parameters C0 , V0 , τC , τV , and α were set to 0 . 26 , 3 . 5 , 20 msec , 50 msec , and 0 . 25 , respectively , based on recordings in hippocampal slices using minimal stimulation [85] , [86] . For these simulations , rather than simulate the trajectories of 120 , 000 glutamate particles , we computed the time-varying average collision rate at each of the 121 possible receptor locations following a single vesicle release by counting collisions and averaging 1000 Monte Carlo runs , and used these averages to randomly determine whether a collision occurred at each time step . Receptor open probability using this technique was indistinguishable from that of the full Monte Carlo simulation ( reduced χ2 was 1 . 004 for NR2A- and 0 . 9617 for NR2B-NMDARs , and p values for a paired t tests were 0 . 9950 and 0 . 9983 , respectively ) , but the simulations ran ∼2000 times faster . We modeled internal calcium concentration using the same parameters and model as Nimchinsky et al . [26] . Current was calculated by the Goldman-Hodgkin-Katz equation and concentration showed fast buffering and single exponential decay kinetics . We added a voltage-dependent Mg2+ block , fitted to the data of Monyer et al . [83] . Conductance , G , was equal to G0/1+e−0 . 08 ( V+20 ) , where G0 is the conductance at 0 mM Mg2+ and V in voltage in mV . The conductance was half-maximal at −20 mV and increased from 10 to 90 percent over a 54 . 9 mV range . Calcium concentration was calculated by ( 6 ) ( 7 ) where ICa is calcium current , GM is the conductance of the channel in the presence of 2 mM Ca2+ ( 46 pS ) , PCa/PM is the ratio of NMDAR permeability to calcium to permeability to monovalent ions ( 3 . 6 ) , Caex is external calcium concentration ( 2 mM ) , M is the concentration of monovalent ions ( 130 mM ) , F is Faraday's constant , R is the gas constant , T is temperature , Ca is internal calcium concentration , v is spine volume ( 0 . 08 fL ) , kex is the decay rate constant of internal calcium concentration ( 1 . 6 msec−1 ) , Carest is the resting internal calcium concentration ( 0 . 1 µM ) and κ is the buffer capacity ( 20 ) . ICa was maximal at −14 . 2 mV . The postsynaptic spine was modeled as a single compartment with uniform concentration throughout . Conductance and calcium permeability were assumed to be the the same for NR2A- and NR2B-NMDARs [10] , [82] , [97] . The calcium influx through NMDARs leads to the activation of CaMKII which is a significant component of the PSD [113] . The enzyme is activated by the binding of Calcium-Calmodulin ( Ca-CaM ) . When two adjacent subunits bind Ca-CaM , the subunits become autophosphorylated . The kinase then becomes autonomous , that is it retains enzymatic activity even after CaM unbinding . CaMKII is dephosphorylated by Protein phosphatase I ( PPI ) in a calcium-dependent manner . High levels of calcium can trigger the autophosphorylation of all 12 holoenzymes , which can overcome phosphatase action to dephosphorylate the enzyme . It has been proposed that the dynamics of CaMKII phosphorylation could then function as a bistable “switch” , and that this switch could underly long-term synaptic potentiation [67] . Introduction of active CaMKII in hippocampal neurons mimics LTP [114] , and animals with genetic mutations of CaMKII show severe deficits in learning and memory [67] . Based on this evidence , experimental and theoretical efforts have focused on understanding the properties of the CaMKII switch [81] , [115]–[118] . We used a bistable model of Ca2+/Calmodulin-dependent kinase II ( CaMKII ) activation [81] as a model of LTP . This was a single-compartment , deterministic model of several interacting chemical processes , driven by the free calcium concentration . For details of the model , and parameter values , see Miller et al . [81] . Essentially , there are two , competing calcium-dependent processes , which phosphorylate and dephosphorylate CaMKII . If the phosphorylation process outcompetes the dephosphorylation process , [CaMKII*] moves towards a high , stable value . We denoted such synapses as potentiated . We ran the simulation for 30 minutes , after which point it was possible to separate the potentiated synapses from those that were not by simply checking whether [CaMKII*] was above a threshold ( 84 µM ) . | Information processing in the brain is carried out by networks of neurons connected by synapses . Synapses can change strength , allowing these networks to adapt and learn , in a process known as synaptic plasticity . At a synapse , an electrical signal in one neuron is converted into a chemical signal , carried by a neurotransmitter , which is in turn converted into electrical and chemical signals in another neuron by specialized proteins called receptors . One such protein , the N-methyl-d-aspartic acid ( NMDA ) receptor , is particularly important for plasticity , due to its ability to detect the voltage of the cell receiving the neurotransmitter signal and to the fact that it allows calcium , an important signaling molecule , to enter the cell . Here we use computational modeling to investigate the role of one part of the NMDA receptor: the NR2 subunit . The subunit has various forms , and which of these forms are present in the NMDA receptor can strongly affect the kinetics and other properties of the receptor . We show that , along with changing the kinetics of the receptor , changing the NR2 subunit affects the reliability of the receptor , its ability to respond to large stimuli , and its spatial response properties . These results have implications for synaptic transmission and plasticity . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] | [
"neuroscience/neuronal",
"signaling",
"mechanisms",
"neuroscience/theoretical",
"neuroscience"
] | 2008 | The Effects of NR2 Subunit-Dependent NMDA Receptor Kinetics on Synaptic Transmission and CaMKII Activation |
Calcium-dependent protein kinases ( CDPKs ) are conserved in plants and apicomplexan parasites . In Toxoplasma gondii , TgCDPK3 regulates parasite egress from the host cell in the presence of a calcium-ionophore . The targets and the pathways that the kinase controls , however , are not known . To identify pathways regulated by TgCDPK3 , we measured relative phosphorylation site usage in wild type and TgCDPK3 mutant and knock-out parasites by quantitative mass-spectrometry using stable isotope-labeling with amino acids in cell culture ( SILAC ) . This revealed known and novel phosphorylation events on proteins predicted to play a role in host-cell egress , but also a novel function of TgCDPK3 as an upstream regulator of other calcium-dependent signaling pathways , as we also identified proteins that are differentially phosphorylated prior to egress , including proteins important for ion-homeostasis and metabolism . This observation is supported by the observation that basal calcium levels are increased in parasites where TgCDPK3 has been inactivated . Most of the differential phosphorylation observed in CDPK3 mutants is rescued by complementation of the mutants with a wild type copy of TgCDPK3 . Lastly , the TgCDPK3 mutants showed hyperphosphorylation of two targets of a related calcium-dependent kinase ( TgCDPK1 ) , as well as TgCDPK1 itself , indicating that this latter kinase appears to play a role downstream of TgCDPK3 function . Overexpression of TgCDPK1 partially rescues the egress phenotype of the TgCDPK3 mutants , reinforcing this conclusion . These results show that TgCDPK3 plays a pivotal role in regulating tachyzoite functions including , but not limited to , egress .
Apicomplexan parasites like Toxoplasma gondii and Plasmodium species contain a number of plant-like calcium-dependent protein kinases ( CDPKs ) [1] . These have been shown to be druggable targets that are distinct from their mammalian hosts . For that reason and for their suggested role in regulating calcium-dependent processes in apicomplexan parasites , CDPKs have been the object of intense study . For example , several reports have used either direct , conditional or chemical knock-out strategies to investigate the function of CDPKs in T . gondii and Plasmodium [2]–[11] . In T . gondii , two CDPKs have been investigated in detail . TgCDPK1 ( TGGT1_059880 ) has been shown to be essential for the secretion of micronemes [5] and in three independent studies , TgCDPK3 ( TGGT1_041610 ) has recently been shown to be important for regulating the rapid egress from the host cell upon treatment with the calcium ionophore A23187 [6]–[8] , [12] . TgCDPK3 mutants show retarded microneme-secretion and ionophore-induced egress although they still extrude the conoid , a complex structure in the apical part of the parasites , with the usual kinetics [13] [6] , [7] . These results show that the mutant parasites can sense the calcium signal induced by the ionophore to some extent but fail to transduce that signal in the normal way . The fact that egress does still occur in the TgCDPK3 mutants , albeit with a delay , indicates that other signaling pathways can operate in the absence of this enzyme [6] . A second phenotype that is associated with TgCDPK3 malfunction is resistance to ionophore-induced death ( IID ) [13] . IID describes the sensitivity of extracellular tachyzoites to prolonged treatment with a calcium-ionophore . All parasite lines identified harboring mutations in the TgCDPK3 gene show resistance to IID , but the biochemical basis for this is not yet known . TgCDPK3 also appears to be necessary for producing latent stages in mice [14] , but the mechanism is also not yet understood . To understand the role of TgCDPK3 during both normal conditions and ionophore-induced egress , we performed a quantitative phosphoproteome and proteome study of wild type and TgCDPK3 mutants using stable isotope labeling with amino acids in cell culture ( SILAC ) . Our study revealed clues to the role played by this enzyme in normal physiology and induced egress .
To identify the pathways controlled by TgCDPK3 , we infected human foreskin fibroblasts ( HFFs ) with wild type ( WT ) or TgCDPK3-mutant tachyzoites previously grown in either “heavy” ( H ) or “light” ( L ) conditions . “Heavy” indicates the presence of 13C , 15N-Lys in place of the naturally-occurring ( 12C or 14N ) amino acids in “light” media [15] , [16] ) . Approximately 24 h after continued growth in either “heavy” or “light” media , the infected cells were incubated for 30 seconds in the presence of 1 µM calcium-ionophore or DMSO as a control ( Figure 1A ) . These samples are called “intracellular” . We also compared WT and mutant parasites grown under “heavy” or “light” conditions and then exposed to ionophore after being released from the host cells by syringe lysis . These samples , called “extracellular , ” were used to examine the role of TgCDPK3 in ionophore-induced death and gliding motility , a process by which the parasites use their own motor-proteins to glide over a surface . In total , we generated 6 datasets ( experiments 1–6 , see Supplemental Figure S1 and Supplemental Table S1 ) . These compared WT and mutant parasites under each of three conditions in technical duplicate: 1 ) intracellular parasites without ionophore ( “IC/ION−” ) ; 2 ) intracellular parasites with ionophore ( “IC/ION+” ) ; and 3 ) extracellular parasites with ionophore ( “EC/ION+” ) . We measured each condition with forward and reverse labeling; that is , we labeled WT parasites with “light” amino acids and the TgCDPK3-mutant parasites with “heavy” in one experiment and reversed this labeling for the replicate experiment ( Figure 1A and Supplemental Figure S1 ) . This strategy ensured that host-cell peptides , which are abundantly present in the “intracellular” samples , did not introduce quantification errors; reverse labeling effectively removes false positives resulting from misidentified host-derived peptides , since they will show the same heavy/light ratio , irrespective of the labeling . True , parasite-derived quantifications will have reciprocal log2 H/L ratios for the reverse-labeled experiment . Knock-out mutants of TgCDPK3 ( RH:Δcdpk3 [8] ) , but not the point mutants resulting from chemical mutagenesis ( e . g . , MBE1 . 1 [13] ) , show impaired growth relative to WT parasites . This phenotypic difference led us to use Δcdpk3 and MBE1 . 1 in different experiments ( see Supplemental Figure S1 ) in our study as phosphorylation sites that differ between WT and both Δcdpk3 and MBE1 . 1 are unlikely to be caused by either the growth defect observed for Δcdpk3 or a mutation in the chemical mutants outside of the TgCDPK3 gene . To ensure that any change in phosphorylation site abundance is not simply a result of a change in the general abundance of that protein , we also measured non-phosphorylated peptides ( for the remainder of the manuscript called the “proteome” ) from two experiments . We analyzed 192 LC-MS/MS runs from 6 different experiments under three different conditions to identify signaling pathways that are differentially regulated between WT and TgCDPK3 mutant parasites: 72 phosphoproteome samples , and 24 proteome samples from two experiments ( “IC/ION−” and “EC/ION+” ) , all analyzed in two independent runs ( i . e . , in “technical duplicate”; Supplemental Table S1 ) . We identified differences in protein levels and phosphorylation site usage between WT and TgCDPK3 mutant strains using a phosphopeptide-enrichment strategy [17] which we previously applied to Toxoplasma parasites [18] . All datasets were initially filtered to a false discovery rate ( FDR ) of <1% on the peptide and <3% on the protein level . In total , we identified 32 , 147 phosphorylation sites ( Figure 1C ) , 69 . 4% of which we previously identified in phosphoproteomic studies of WT tachyzoites [18] . Primary analysis of the data obtained revealed up to 50% FDR of “decoy” hits ( obtained by searching a fictional decoy database consisting of reversed protein sequences [19] ) in phosphorylation sites with a very high or low H/L SILAC ratio even though the total set FDR was well below 1% across all datasets . To largely eliminate false positives from these “tails” ( high or low SILAC ratios ) , we further filtered all quantifications for the signal to noise ratio , spectral counts and MS1-elution parameters of the SILAC pairs ( see materials and methods ) . After such filtering , 19 , 257 sites remained which were considered quantified with a site FDR of 0 . 41% and a protein FDR of 1 . 61% ( see Supplemental Table S1 ) . Note that the FDR refers to the estimated number of incorrect identifications of phosphopeptides in the dataset as a whole and does not estimate the correctness of all quantifications , so additional filtering , as described above , is required for highly reliable quantifications . We include all quantifications after the above-mentioned filtering in this manuscript ( Table S1 ) because these represent a resource that can inform the interpretation of complementary approaches to identify targets of TgCDPK3 . 78 . 5% of all quantified sites identified have an ASCORE >19 , indicating a 99% probability of being correctly localized to an S , T or Y residue within the peptide they were found [20] . The median-centered SILAC ratios of all quantified sites show a normal Gaussian distribution with a median standard deviation of ∼0 . 5 for each experiment ( Figure 1D ) , showing that the presence of mostly unlabeled host-cell material in our samples did not skew the expected distribution of SILAC ratios at a detectable level . We identified a subset of phosphorylation sites as reliably different between WT and mutant parasites by applying two additional criteria: 1 ) the site was identified in at least two datasets without conflicting ratios for different experiments ( e . g . , they must have a positive log2 H/L ratio in a forward and a negative log2 H/L ratio in the reverse experiment ) ; 2 ) the log2 H/L ratio was >0 . 75 or <−0 . 75 , ( ∼1 . 5 times the average standard deviation of any given experiment ) ; sites were designated as “not different” if the log2 ratios were between 0 . 5 and −0 . 5 . Sites were considered dependent on TgCDPK3 if they differed between WT and mutant parasites under one or more of the three experimental conditions , “IC/ION−” , “IC/ION+” or “EC/ION+” . Given that treatment with ionophore was for 30 s followed by a wash , minor differences in the timing of the wash could contribute to considerable phosphorylation state variation between datasets . Thus , we allowed one unexpected value in any of the conditions . Using this filtering , we obtained a list of 156 phosphorylation sites that are different between WT parasites and TgCDPK3 mutants with a final FDR of 0 . 5% ( Supplementary Table S2 ) . The criteria above yielded 156 phosphosites with abundances that differed between wild type and mutant parasites under any of the three conditions; for 130 of these we also obtained protein-level data ( i . e . , SILAC ratios for nonphosphorylated peptides from the same protein; Figure 2A ad 2C1 and Table S2 ) . Pearson-correlation analysis of the forward and reverse experiment for each condition showed significant correlation ( p-values <0 . 0001 for all comparisons ) ( Figure 2B ) . These results allowed us to identify which differences in phosphopeptide abundance can be explained simply by a difference in the abundance of that protein ( Figure 2C ) ; only ∼14 . 9% of the 130 phosphosites where we also had proteome data correlated with protein abundance , showing that the vast majority of sites identified as different in the mutants are likely a result of differences in the degree of phosphorylation ( Figure 2C2 and Supplemental Figure S2 ) . For a majority ( ∼58% ) of the 156 phosphorylation sites discussed above we did not obtain high-confidence SILAC ratios for the untreated samples ( “IC/ION−”; Figure 2A and 2C3 ) , precluding any conclusion about their regulation in the absence of ionophore . In the 65 phosphosites where we did obtain such data , however , we observed the following: only 2 of the proteins on which one or more of these phosphosites were detected showed a difference in protein levels and both these were in the set that was different in the “IC/ION−” conditions . 51 of the 65 phosphosites showed a significant difference between wild type and mutant parasites even in the absence of ionophore ( Figure 2C3 ) and only 14 were not significantly different in these latter conditions . These results indicate that TgCDPK3 likely regulates biological processes during the normal function of intracellular parasites , independent of egress and ionophore treatment . Among the phosphorylation sites that are already different in the absence of ionophore are some on proteins important for ion-homeostasis ( P-type ATPase , putative , TGGT1_103910 ) and a dense granule protein GRA22 ( TGGT1_125960 ) that has recently been shown to play a role in egress [21] . Importantly , many of the differences were observed in the two independently derived TgCDPK3 mutant lines ( MBE1 . 1 and RHΔcdpk3 ) indicating that these changes are a consequence of TgCDPK3 inactivation and not a consequence of the genetic modification of the parasites independent of TgCDPK3 function ( Figure 2D ) . The two datasets for “EC/ION+” contained most of the 156 differing phosphorylation sites , but these experiments involved comparisons between RH ( wild type ) and the same mutant strain ( MBE1 . 1 ) . Thus , we could not exclude the possibility that some of the observed differences in phosphorylation state are due to secondary mutations carried by this strain ( i . e . , are not dependent on TgCDPK3 ) . To address this , we made use of a complemented MBE1 . 1 cell line which expresses wild type TgCDPK3 under its endogenous promoter [8] and compared the phosphoproteome and proteome of WT and MBE1 . 1::CDPK3 from extracellular , ionophore-treated parasites in a new experiment “COMP/EC/ION+” using the methods described above . We then retrieved all SILAC ratios of this experiment for the 156 phosphorylation sites that we identified as different between WT and CDPK3 mutant parasites ( Supplemental Table S2 ) . As expected , we observed a significant difference ( P-value <0 . 0011 Kolmogorov-Smirnov test ) between the distributions of SILAC ratios of all 156 differing phosphorylation sites of the “EC/ION+” datasets for the mutant ( MBE_RH_EC_ION+_forward or reverse ) when compared to the SILAC ratios observed for “COMP/EC/ION+” ( Figure 3A ) . Overall , 68 ( 72 . 3% ) of the 94 phosphorylation sites for which we obtained SILAC ratios from the complementation experiments showed complementation ( Figure 3B ) . Of the 26 sites that were not rescued in the complemented strain , the vast majority ( 80 . 8% ) appeared different because of differences in protein-levels compared to only 1 . 5% of the sites that were complemented . These data show that differences in the efficiency of phosphorylation at a given site in the TgCDPK3 mutant are largely complemented and differences that occur at the protein-level are not . While these latter differences in protein abundance could be an indicator of MBE1 . 1-specific effects due to undetected mutations or passage history , we observed that ∼25% of the sites that were not complemented were also identified as differentially phosphorylated in RHΔcdpk3 vs . WT parasites , indicating a dependence of TgCDPK3 function . A primary aim of this study was to identify phosphorylation sites that differ in their usage between the WT and TgCDPK3 mutant parasites upon ionophore treatment . Within this set of 156 changing sites , two classes are most interesting: “Class A” where the phosphosite was detected in both WT and mutant parasites in the absence of ionophore-treatment but whose usage did not differ between these two strains; and “Class B” where the phosphosite was not detected in one or other or both of the strains in the absence of ionophore-treatment . This latter class likely represents phosphorylation sites that are substantially phosphorylated only during ionophore-induced egress , assuming the absence of detection in the “IC/ION-“ condition is not caused by technical reasons , as explained below . In Class A , we identified 14 phosphorylation sites on a total of 11 proteins ( Figure 4A ) . Seven of the 11 proteins are more phosphorylated in the mutants relative to WT in the presence of ionophore and 5 of these were predicted or shown to be secreted into the host cell [18] . The preponderance of secreted proteins in this group is discussed further below . To understand more about TgCDPK3's role , we looked for proteins in our dataset that were already known or predicted to play a role in egress or motility ( Figure 4B ) . Among the identified proteins in Class B are several that are associated with actin regulation ( cyclase associated protein ( CAP , TGGT1_086070 ) [22]–[24] ) , putative motor-proteins ( Myosin A ( TGGT1_070410 ) , F ( TGGT1_103490 ) and G ( TGGT1_092070 ) [25] ) , proteins of the inner membrane complex ( IMC [26] ) and a recently discovered protein that associates with cortical microtubules ( TrxL-1 ( TGGT1_115220 ) [27] ) . Although IMC and microtubule-associated proteins are not directly implicated in egress or motility , rapid rearrangements of the cytoskeleton prior to egress could be part of such a process . Also two uncharacterized kinases ( TGGT1_043160 , TGME49_053450 ) were identified , although nothing about their function is known . Whether TgCDPK3 inactivation leads to a motility phenotype in the presence of ionophore remains unclear . Whereas Lourido and colleagues reported significant differences in the types of motility that TgCDPK3 mutants could perform , McCoy and colleagues observed only a slight , but not significant trend toward such differences [6] , [7] . Both groups reported no differences in the speed of the parasites while gliding over a surface . Several members of the motor-complex ( MyoA , GAP45 ( TGGT1_078320 ) and MLC1 ( TGGT1_013010 ) ) are known to be phosphorylated in a calcium-dependent manner in Toxoplasma and Plasmodium [28]–[33] . Thus , we specifically looked for differences in the relative abundance of phosphopeptides in such proteins as well as other members of the motor complex: GAP40 , GAP50 , GAP70 and aldolase [34] , [35] . Many previously identified phosphosites in these proteins were identified in our datasets but only MyoA and Aldolase ( TGGT1_069710 ) showed a difference in relative phosphorylation between the TgCDPK3 mutants and WT parasites: on MyoA we observed increased phosphorylation of S518 and decreased phosphorylation of S20/S21 in extracellular , ionophore-treated mutants vs . WT ( we cannot differentiate which of the two adjacent serines is phosphorylated based on the spectra ) . The latter site was less phosphorylated in the mutants in the absence of ionophore but this difference decreased in the “EC/ION+” condition . These data suggest that while TgCDPK3 activity is essential for processes that regulate egress-related events , it is not the main kinase regulating phosphorylation of the motor complex components . Among the proteins that were differentially phosphorylated between wild type and mutant parasites were some that contain EF-hands , proteins that are regulated directly by calcium ( Figure 4B ) . We identified a differentially regulated phosphorylation site on a small EF-Hand protein that contains no other recognizable domain and is annotated as a putative calmodulin ( TGGT1_042450 ) . The phosphorylation site was identified just adjacent to the EF-hands themselves . In addition to the putative calmodulin , we identified two calcium-dependent kinases ( TgCDPK2a ( TGGT1_062170 ) and TgCDPK3 itself ) as differentially phosphorylated in the MBE1 . 1 mutant vs . WT . For both kinases , the sites were hyperphosphorylated in the mutant parasites and were located within the ATP-binding loop of the kinase domain , a region where phosphorylation can play a regulatory role [36] , [37] . It is worth noting that the mutation ( T239I ) in the activation loop of TgCDPK3 in the mutant MBE1 . 1 [8] functionally inactivates the kinase and so a different kinase must be involved in the hyperphosphorylation . Interestingly , our dataset also indicated that two of several phosphorylation sites on proteins recently identified as targets of TgCDPK1 ( TGGT1_059880 ) . PRP ( TGME49_005320 ) and DRPB ( TGGT1_064650 ) [38] are , surprisingly , more phosphorylated in TgCDPK3 mutant vs . WT parasites upon ionophore treatment . Although TgCDPK1 itself did not emerge from our stringently filtered datasets as differentially phosphorylated in the mutants vs . WT , these results indicate that there might be an increase in activity of TgCDPK1 in the TgCDPK3 mutants . Hence , we specifically looked for evidence of differences in the phosphorylation state of TgCDPK1 in our datasets and found several phosphopeptides with high-quality quantifications in the “EC/ION+_FW” condition that corresponds to the activation loop threonine ( T200 ) of TgCDPK1 [39] , [40] . The phosphorylation site identified in TgCDPK1 showed a higher level of phosphorylation ( 2 . 9-fold ) in the mutant vs . WT parasites ( Figure 4c ) , while the protein levels of TgCDPK1 appear similar between WT and TgCDPK3 mutants in our proteomic dataset ( Supplemental Table S1 ) and by Western blot ( data not shown ) . This phosphorylation is a prerequisite for activity of the kinase and supports the model that the TgCDPK3 mutants have a higher level of activated TgCDPK1 . It was identified in no other dataset which is why it is not included in the set of 156 phosphorylation sites discussed above ( all of which were seen in at least two datasets ) , but all peptides containing quantitative information for TgCDPK1:T200 were identified in the heavy and the light version in two different fractions giving confidence in its identification and quantification . All phosphopeptides were identified as a missed cleavage form , which is often the case for phosphopeptides [41] . We did not identify the activation-loop phosphosite in the dataset from the complemented mutants and so could not assess whether such complementation rescued its phosphorylation; however , we did observe hyperphosphorylation of the above-mentioned targets of TgCDPK1 in the MBE1 . 1 mutant and all showed phenotypic rescue upon TgCDPK3 complementation . Hence , TgCDPK3 plays a role in the phosphorylation of these proteins through another kinase , presumably , TgCDPK1 . TgCDPK3 mutants egress in the presence of ionophore with much slower kinetics than WT parasites [8] , [13]: whereas after 2 minutes 100% of WT parasites have exited in the presence of ionophore , TgCDPK3 mutants only start to slowly egress after 3–4 minutes , reaching near 100% egress levels by 10 minutes [13] . The increased amount of phosphorylated TgCDPK1 and its targets in the TgCDPK3 mutants prompted us to test whether accumulation of active TgCDPK1 might eventually reach levels necessary for this enzyme to take the place of TgCDPK3 , thereby explaining the ability of the TgCDPK3 mutant parasites to respond , albeit slowly , to the ionophore . To test this hypothesis , we over-expressed TgCDPK1 in MBE1 . 1 parasites using a strong promoter ( from the GRA2 gene ) and measured the ability of MBE1 . 1::TgCDPK1 parasites to egress in the presence of ionophore . We tested the level of overexpression using an antibody specific to TgCDPK1 , which recognizes a single band at around 55kD in MBE1 . 1 parasites ( Figure 5A ) . The product of the introduced TgCDPK1 transgene is HA-tagged and showed the expected size-shift on gel electrophoresis with an expression level that was ∼10× higher than the slower migrating , endogenous TgCDPK1 ( Figure 5A ) . Immunofluorescence imaging of TgCDPK1::HA showed a concentration of TgCDPK1::HA toward the periphery of MBE1 . 1::TgCDPK1 parasites whereas WT parasites showed a more general cytosolic staining; biochemical fractionation assays , however , revealed no difference in membrane association of TgCDPK1 in the two strains ( data not shown ) . While we saw no difference in growth or number of parasites/vacuole in the MBE1 . 1::TgCDPK1 parasites ( data not shown ) , they were substantially but not fully rescued in their ionophore-induced egress phenotype ( Figure 5B ) : at 2 minutes , most WT ( RH ) parasites had egressed but MBE1 . 1 and MBE1 . 1::TgCDPK1 remained mainly inside; however , at 6 minutes ∼50% of MBE1 . 1::TgCDPK1 had egressed while MBE1 . 1 were still almost entirely intracellular . This shows that over-expression of TgCDPK1 can partially overcome the block seen in mutants lacking active TgCDPK3 , supporting the implication of the SILAC data that the function of these two kinases is directly or indirectly linked . We have previously shown that the egress phenotype of TgCDPK3 mutants can be rescued by overexpressing an engineered form of TgCDPK3 that has mutations in its predicted myristoylation and pamitoylation sites but only when using a strong promoter ( SAG1 ) , not when using the endogenous promoter [8] . This was likely because overexpressing TgCDPK3 allows a fraction of it to reach the plasma membrane [8] where it can phosphorylate its targets . To test whether the increased levels of activated TgCDPK1 observed in MBE1 . 1 mutants might similarly be rescuing the egress delay observed by phosphorylating TgCDPK3 targets , we directly compared the TgCDPK1 and TgCDPK3 substrate specificity . We incubated peptide microarrays spotted with ∼500 defined but random 13-mer peptides containing a central serine residue with recombinant TgCDPK1 or recombinant TgCDPK3 and compared their ability to phosphorylate the arrayed peptides ( Figure 5C ) . We ranked the peptides according to the phosphorylation intensity with the highest phosphorylated peptide being 1st . A comparison of the ranking for each given peptide incubated with either CDPK1 or CDPK3 shows that a majority of the peptides are equally well phosphorylated by the two kinases although some are predominantly phosphorylated by one , but not the other . We did not obtain significantly enriched amino acids in any position for either TgCDPK1 or TgCDPK3 , but that might be related to the technical limitation of these arrays . They sometimes contain more than 1 phosphorylatable residue per peptide; i . e . , an additional serine , threonine or tyrosine residue in addition to the central serine . Since we cannot distinguish whether the central serine , or another phosphorylatable residue is phosphorylated , they have limited value for a motif analysis . However , it still allowed us to directly compare TgCDPK1 and TgCDPK3 in their linear motif analysis with the result that TgCDPK1 appears likely able to phosphorylate at least a subset of TgCDPK3 targets . In addition to the calcium-dependent proteins mentioned earlier , we identified a putative calcium-transporting ATPase ( TGGT1_103910 ) that showed differential phosphorylation between mutant and WT parasites in the “IC/ION−” condition . These results suggested a putative role for TgCDPK3 in regulating calcium levels . To test this , we measured calcium levels in the absence of ionophore in WT , MBE1 . 1 , MBE1 . 1 complemented with a functional copy of TgCDPK3 ( MBE1 . 1::CDPK3 ) and , as a control , MBE1 . 1 complemented with a nonfunctional copy of TgCDPK3 ( MBE1 . 1::CDPK3 ( T239I ) ) . Both , MBE1 . 1 and MBE1 . 1::CDPK3 ( T239I ) showed elevated calcium levels ( ∼150% ) compared to MBE1 . 1 complemented with a functional copy of CDPK3 ( 100% ) , supporting the notion that TgCDPK3 plays a role in maintaining normal intracellular calcium levels ( Figure 6 ) . To rule out that integration of the TgCDPK3 WT copy into MBE1 . 1 lowered basal calcium levels because of an off- target effect , we also measured basal calcium levels in MBE1 . 1 parasites complemented with the Plasmodium falciparum orthologue of TgCDPK3 , PfCDPK1 ( PF3D7_0217500 ) , that has recently been shown to complement the egress phenotype of MBE1 . 1 [42] . Complementation with the WT PfCDPK1 version , but not a kinase dead mutant ( T231I ) decreases calcium levels similar to those of MBE1 . 1::CDPK3 . No significant differences in the change of calcium levels were observed in the response to the calcium ionophore itself ( data not shown ) . This suggests that inactivation of CDPK3 causes a reproducible elevation of basal calcium levels that are directly dependent on TgCDPK3 .
The aim of this study was to identify phosphorylation events that are dependent on TgCDPK3 . Based on previous publications , we hypothesized that the signaling pathways controlled by TgCDPK3 might be most easily detected during ionophore-induced egress . Among the proteins that fulfilled this prediction were several that are known to be secreted into the parasitophorous vacuole ( PV ) , the PV-membrane ( PVM ) or into the host cell . Some of the phosphopeptides in these proteins showed a decreased abundance in the WT samples which could be due to dephosphorylation or degradation of these proteins resulting from breakdown of the PVM . We have not further investigated these events here , but they are consistent with the fact that breakdown of the PVM , normally an early event in egress , is defective in the TgCDPK3 mutant parasites [6]–[8] , [13] . Despite the low number of phosphorylation sites for which we obtained SILAC ratios in untreated samples as discussed above , we identified several significant differential phosphorylation events on proteins that are either known or predicted to play a role in egress or associated processes , and these are discussed further below . In addition to sites that are differentially phosphorylated , those that show no change in phosphorylation status in the mutants relative to WT can be equally informative . For example , our results indicate that TgCDPK3 is not the major regulator of key phosphorylation sites observed on the components of the machinery that drives parasite motility including GAP45 , one of the key “glideosome” proteins known to be regulated by phosphorylation [28] , [30] . The only known part of the motor for which we confidently saw differences in the phosphorylation state between WT and TgCDPK3 mutants was MyoA . The differences observed for MyoA could explain some of the observed phenotypic differences in TgCDPK3 mutants with regards to motility , but given that at least one site ( S20/S21 ) was already differentially phosphorylated in intracellular parasites not treated with ionophore ( “IC/IONO−” ) , it appears that this phosphorylation site has a function independent of , or in addition to , egress . A recent report on a conditional knock-out of MyoA , where loss of this protein has no effect on parasite egress ( or invasion [43] ) supports the notion that phosphorylation of MyoA and other proteins by TgCDPK3 can serve functions other than egress . Interestingly , two other myosin isoforms ( MyoG and MyoF ) show up as differentially phosphorylated in the TgCDPK3 mutants vs . WT , one of which , MyoF , was recently described as playing a role in apicoplast segregation [44] . The role that these myosin isoforms play during ionophore-induced egress requires further analysis . One protein strongly indicated as a potential regulator of motility is CAP , a regulator of actin dynamics [45] , which we found to be ∼2-fold less phosphorylated in the TgCDPK3 mutants relative to WT in the presence of ionophore . In tachyzoites , CAP has been shown to be localized in the apical end , rapidly redistributing into the cytosol when becoming extracellular [46] . Thus , CAP could regulate actin dynamics during egress and motility in a location-dependent manner . In Plasmodium berghei , deletion of CAP showed a defect in oocyst development but the function of CAP and actin regulation in this process is not understood [23] . The identification of TgCDPK3-dependent phosphorylation of calcium-regulated proteins , including TgCDPK1 , TgCDPK2a , and an EF-hand containing protein is a strong indicator that TgCDPK3 , in addition to being regulated by calcium , controls other calcium-regulated processes . Furthermore , the identification of two proteins that are known phosphorylation targets of TgCDPK1 , and indications that loss of TgCDPK3 may result in a more active TgCDPK1 itself , indicate that the pathways controlled by TgCDPK1 are , at least in part , activated in TgCDPK3 mutants treated with ionophore . While this suggests that TgCDPK3 might be a negative regulator of TgCDPK1 , we have no direct evidence for this and understanding their precise roles will require further investigation . Overexpression of TgCDPK1 partially rescues the egress phenotype . This indicates that 1 ) either active TgCDPK1 can phosphorylate targets of TgCDPK3 , or 2 ) that active TgCDPK1 can activate egress and microneme secretion independent of TgCDPK3 , but with much slower kinetics . Both kinases appear to have overlapping substrate specificity and the dominant localization of the overexpressed TgCDPK1 at the periphery and the increased rescue of egress supports the first option where TgCDPK1 may be phosphorylating TgCDPK3 targets at the plasma membrane . However , we cannot exclude the alternative , in which egress in the TgCDPK3 mutants is facilitated via a TgCDPK3-independent pathway . In both scenarios , the elevated levels of TgCDPK1 we observed in MBE1 . 1 parasites that are phosphorylated in the autophosphorylation loop might explain how TgCDPK3 mutant parasites egress slowly over time when treated with ionophore . A possible explanation for how CDPK1 might be activated is via a PKG ( TGGT1_087710 ) controlled pathway . Lourido et al . , have shown that activation of PKG is partially CDPK3 dependent as inhibition of CDPK3 decreases egress triggered by Zaprinast [6] . PKG has also been shown to be important for egress in Plasmodium falciparum as a key-regulator for calcium levels thought to be important for regulation of the TgCDPK1 orthologue in P . berghei , PbCDPK3 [47] , [48] . While we consistently identified the phosphorylated activation loop of TgPKG ( Threonine 837 , Supplementary table S1 ) under all conditions , we did not observe CDPK3- dependent differences . But it is possible that other phosphorylation sites of the protein , which we might not have detected for technical reasons , or other regulatory mechanisms are mainly involved in regulation of PKG . Whatever the mechanism by which TgCDPK3 and PKG are connected , our data support a broader role of TgCDPK3 and the pathways it controls . This is evident from the proteins that are differentially phosphorylated , including proteins that are important for metabolism , transcription and ion homeostasis in addition to the proteins important for egress , several of which are differentially phosphorylated even in the absence of ionophore . This is in line with our observation that basal calcium levels are elevated in TgCDPK3 mutants in the absence of ionophore . This allows for a model in which altered calcium fluxes in TgCDPK3 mutants have a profound effect on the homeostasis of the cell , which could dictate how a cell behaves under conditions of stress . The fact that CDPK3 mutant parasites don't show a measurable phenotype in cell culture points towards compensatory mechanisms that allow for normal growth . The fine balance the parasites have to strike might be easily tipped as in the case of calcium ionophore treatment , when the egress phenotype becomes evident . While this phenotype was only observed in vitro , CDPK3 mutant parasites also have a phenotype in vivo . Type I Toxoplasma parasite strains lacking TgCDPK3 ( as used in this study ) are still highly virulent in mice whereas Type II strains lacking TgCDPK3 activity are attenuated with severely reduced latent stages ( tissue cysts ) being found in the brain of chronically infected animals [8] , [49] . We previously hypothesized that this could be due to an egress phenotype but the data we present here would suggest that the phenotypic changes are due to alterations in TgCDPK3-dependent functions unrelated to egress . Our observation that there are differences in protein abundance in the TgCDPK3 mutants relative to WT resembles a recent study of the closest orthologue of TgCDPK3 in the malaria parasite Plasmodium berghei , PbCDPK1 , that showed a role for PbCDPK1 in translational repression [10] . However , our results differ in two ways: 1 ) we observe differences in the absence of environmental triggers and 2 ) complementation of the TgCDPK3 mutants with a WT copy of the gene restores protein levels in only one case . The fact that we identified a substantial fraction of non-complemented phosphorylation sites in both the TgCDPK3 point mutant ( MBE1 . 1 ) and knock-out clearly indicates that the effect is due to TgCDPK3 . Several of these sites can be explained by changes in protein level indicating that phosphorylation state and proteome changes occur in the absence of TgCDPK3 and their non-complementation suggests that an epigenetic event “locks in” some of the effects . While it is possible that genetic effects in the chemical mutants are partially responsible for the observed static changes of protein levels , an epigenetic effect seems more likely as the only protein coding mutation identified in MBE1 . 1 using whole genome sequencing was in TgCDPK3 . In addition to that , several of the changes that do not revert are identified in the chemical mutant and the TgCDPK3 knock-out strain , strongly arguing for a TgCDPK3 specific effect . Among the proteins and phosphorylation sites that are not complemented are some that are important regulators in glycolysis and other metabolic pathways , suggesting loss of TgCDPK3 could lead to long-lasting phenotypic changes that will not be reversed upon complementation . The results presented here , therefore , present a new insight into how the protein kinases of Toxoplasma interact to regulate several key functions , extending well beyond ionophore-induced egress .
Parasites lines and labeling of parasites was achieved as previously described [15] , [16] . Briefly: parasites were grown in heavy ( 146 mg/l 13C6- , 15N2-L-lysine , 84 mg/l 13C6-L-arginine , 40 mg/L unlabeled L-Proline ) or light media ( 146 mg/l unlabeled L-lysine , 84 mg/l unlabeled L-arginine , 40 mg/l unlabeled L-Proline ) . After 4 complete lytic cycles , parasites incorporated between 96% and 98% of heavy amino acids . For the comparative analysis parasites were seeded onto confluent human foreskin fibroblast in 150 mm dishes with an MOI of 5 in either heavy or light media . 24 hours post-infection the cells were washed once with fresh media and incubated in the presence of 1 uM A23187 or DMSO for 30 seconds . After the incubation time , the parasites were immediately placed on wet ice and quickly washed once with pre-chilled , ice-cold PBS prior to lysis in ice-cold 8 M urea containing protein and phosphatase inhibitors ( Roche ) . We performed each experiment using 5 individual 15 cm dishes in order to monitor an average of the signaling events that take place during the first 30 seconds of ionophore treatment . Peptide and phosphopeptide samples were prepared as previously described [17] , [18] using SCX and IMAC chromatography for phosphopeptide enrichment . Briefly , samples were lysed , reduced , alkylated , and digested with trypsin . After desalting , the peptides were fractionated using strong cation exchange chromatography ( SCX ) and phosphopeptides were further enriched using IMAC ( immobilized metal affinity chromatography ) and the phosphorylated and non-phosphorylated flow-through peptides were analyzed by LC_MS/MS on a LTQ-Velos Orbitrap in technical duplicates in a total of 196 MS/MS runs . In addition , we analyzed the phosphoproteome and proteome of RH vs . the MBE1 . 1 mutant complemented with a WT copy of TgCDPK3 ( MBE1 . 1::CDPK3; [8] ) in technical duplicate in comprised of a total of 36 runs . This was done using parasites “EC/ION+” . Phosphorylated and non-phosphorylated ( flow-through ) peptides were resuspended in 4% formic acid , 5% acetonitrile and analyzed by LC-MS/MS in technical duplicate on a system consisting of a MicroAS autosampler ( Thermo Scientific ) , binary HPLC pumps ( Agilent 1200 series ) with flow-splitting , an in-house built nanospray source , and an LTQ Orbitrap Velos ( Thermo Scientific ) . 2 µg of sample was loaded onto a 100 µm ID fused silica capillary packed with 18 cm of 5 µm Magic C18AQ resin ( Michrome Bioresources ) . Peptides were eluted using a gradient of water:acetonitrile with 0 . 1% formic acid from 7% to 25% acetonitrile over 120 min , and then 25–40% B over 30 minutes . A top 10 method was run consisting of one MS1 scan ( resolution: 6×104 AGC: 5×105 , maximum ion time: 500 ms ) followed by ten data dependent MS2 scans ( AGC: 1×10 , maximum ion time: 100 ms ) of the most abundant ions . Dependent scans were configured with the following settings: 2 . 0 m/z isolation width , dynamic exclusion width: −0 . 52 , 2 . 02 , exclusion duration: 60 seconds , normalized collision energy: 35 , activation time: 5 ms . Charge state screening was employed to reject ions with unassigned or +1 charge states . HFFs were cultivated in 96 well plates and each well infected with 500 parasites . After 24 hours of growth , the parasites were incubated in HBSS containing 1 µM A23187 calcium ionophore for time periods ranging from 0 to 10 minutes , in triplicates , after which the cells were fixed in 100% methanol and subsequently stained with Giemsa . All assays have been done on at least three independent occasions . Spectra were searched against a concatenated database of Human ( IPI , version 3 . 66 ) and Toxoplasma ( toxoDB , release 6 . 1 ) proteins using SEQUEST [50] , with 15 ppm precursor mass tolerance , trypsin specificity with up to two missed cleavages , static modification of cysteine ( carbamidomethylation , +57 . 0215 ) and variable modification of serine , threonine , and tyrosine ( phosphorylation , +79 . 9663 ) , methionine ( oxidation , +15 . 9949 ) lysine ( SILAC 13C ( 6 ) 15N ( 2 ) , +8 . 0142 ) , and arginine ( SILAC 13C ( 6 ) , +6 . 0201 ) . Phosphorylation site localization was assessed using the Ascore algorithm [20] . All datasets were filtered using the target-decoy method [19] , [51] to a false discovery rate ( FDR ) of <1% on the peptide and <3% on the protein level . Phosphopeptides were combined into phosphosites based on their localization probabilities , and phosphosites were further filtered to an FDR of <1% for each phosphorylatable residue ( S , T , Y ) using the peptide score provided by Ascore . All peptides matching to the human proteome were removed to exclude peptides from the parasite that are identical with the host and where quantification is thus not reliable . SILAC quantification was achieved by analysis of the MS1-intensity peaks using the VISTA algorithm [52] . Quantifications were scored using: closeness of log2 H/L to 1∶1 , signal to noise of each isotopic partner , and a VISTA confidence metric that accounts for chromatography quality . Weighted averages were calculated using these scores for sites and proteins for which more than one identification was made . These weighted averages are intentionally conservative , in an attempt to eliminate false-positives from the tails of the distribution . Unweighted average and standard deviation calculations have been included as well . Phosphopeptides were categorized as either mono- , bis- , or tris-phosphorylated , and separate averages were calculated for sites found in peptides of each type . The resulting data was further filtered for a minimum of 2 quantifications in each respective experiment , a minimum VISTA confidence score of 88 for the best quantification and a minimum signal to noise ratio for the best peptide of 8 . SILAC log2 ratios were centered on “0” based on the median SILAC ratio for each dataset . Differentially phosphorylated sites were identified by using the following criteria: a minimum log2 fold change of 0 . 75 ( + or − ) , which is ∼1 . 5 times the standard deviation across the experimental datasets , and a consistent change of phosphorylation site abundance in one or more of the conditions . Note , one mismatch was allowed to capture phosphorylation sites that are just at the threshold , or missing in a single sample due to a bad SILAC quantification , to be included in the dataset . Phosphorylation site quantifications were manually curated by analyzing the MS1 elution profiles and removed if they originated from low-quality quantifications . Protein SILAC ratios were calculated by using the median SILAC ratio for all identified peptides . Pearson correlation was calculated using a two-tailed test with a 95% confidence interval ( Prism6 ) . The open reading frame of TgCDPK1 was cloned into pGRA [53] using the restriction sites NsiI and NcoI . The plasmid was linearized using HindIII and transfected into MBE1 . 1 parasites and selected with MPA/XAN as previously described [53] . Random peptide library kinase arrays ( KIN-MA-RLYS , JPT , Germany ) with a central serine were incubated according to the manufacturer's instructions . Briefly , 100 nM recombinant CDPK1 or CDPK3 was incubated with 50 µM Ca and 10 µM cold ATP to allow for autophosphorylation and activation of the kinase . This mix ( 400 µL ) was then supplemented with 10 µCi of 32P-ATP and added to the peptide arrays for 4 h at 30 degrees Celsius . After washing and drying a high-resolution phosphor-imaging screen ( Fujifilm , BAS-SR ) was exposed . Images were acquired using a Typhoon scanner using 25 µM resolution and spot intensity values were analyzed using microarray software . Median spot intensities were generated after manual verification of each spot . Contaminations were manually removed and excluded from the analysis . Each median intensity was plotted as a rank from highest ( 1st rank ) to the lowest observed phosphorylation . Naturally egressed parasites were resuspended in intracellular buffer ( 5 mM NaCl , 142 mM KCl , 2 mM EGTA , 1 mM MgCl2 , 5 . 6 mM glucose , 25 mM HEPES , pH 7 . 2 ) and labeled with Fluo-4 AM ( 2 . 5 µM ) at room temperature with shaking for 30 minutes . Parasites were then pelleted , washed and resuspended in intracellular buffer followed by incubation at room temperature with shaking for 30 minutes to allow de-esterification . The parasites were then loaded onto 96-well plates ( 107 per well ) and fluorescence ( excitation 496 nm and emission 516 nm ) was quantified using a Synergy H1 plate reader ( BioTek ) . Recombinant full length TgCDPK1-HIS6 was generated by cloning the open reading frame into the expression vector pET28 . Recombinant TgCDPK1 was purified using the HIS-tag with NI-NTA agarose ( GE-Healthcare ) . 200 µg of purified TgCDPK1 was injected with an equal volume of Freunds incomplete adjuvant into 6–8 week old pre-screened BALB/c mice from Charles Rivers . None of the mice showed reactivity in the pre-bleeds . Mice were boosted 3 times with 100 µg of recombinant protein every 3 weeks . Test bleeds were taken at week 6 and all mice were sacrificed at week 10 for the terminal bleed . Final bleed serum was screened for selectivity by Western blot and used in this study . Statistical analysis and graphs were made using GraphPad Prism6 . Data handling was performed using Excel and MySQL using Python scripts . Heat-maps were generated using Cluster 3 ( unclustered , k-means ) , and visualized by Treeview . | Calcium-dependent protein kinases are plant-like enzymes of apicomplexan parasites that regulate a variety of biological processes including stage-conversion , post-translational repression and egress from the host cell . In this study , we analyzed Toxoplasma CDPK3 , which has recently been shown to regulate rapid egress from the host cell . The specific pathways that TgCDPK3 regulates , however , have not previously been known and so we used a quantitative phosphoproteome approach to determine phosphorylation site usage in wild type and TgCDPK3 mutant parasites before , during and after egress . This revealed >150 novel phosphorylation sites that are differentially phosphorylated between WT and TgCDPK3 mutant parasites . Some of these sites are on proteins predicted to play a role in parasite egress . However , we also identified many phosphorylation sites on proteins not thought to be involved in egress , as well as many proteins of unknown function . We confirm that basal calcium levels are affected by CDPK3 inactivation and observed a link between TgCDPK3 and another calcium-dependent kinase ( TgCDPK1 ) . Known targets of TgCDPK1 were hyperphosphorylated in the TgCDPK3 mutants , and overexpression of TgCDPK1 partially rescued the observed egress phenotype of TgCDPK3 mutants . | [
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] | 2014 | The Calcium-Dependent Protein Kinase 3 of Toxoplasma Influences Basal Calcium Levels and Functions beyond Egress as Revealed by Quantitative Phosphoproteome Analysis |
Sequence variation can affect the physiological state of the immune system . Major experimental efforts targeted at understanding the genetic control of the abundance of immune cell subpopulations . However , these studies are typically focused on a limited number of immune cell types , mainly due to the use of relatively low throughput cell-sorting technologies . Here we present an algorithm that can reveal the genetic basis of inter-individual variation in the abundance of immune cell types using only gene expression and genotyping measurements as input . Our algorithm predicts the abundance of immune cell subpopulations based on the RNA levels of informative marker genes within a complex tissue , and then provides the genetic control on these predicted immune traits as output . A key feature of the approach is the integration of predictions from various sets of marker genes and refinement of these sets to avoid spurious signals . Our evaluation of both synthetic and real biological data shows the significant benefits of the new approach . Our method , VoCAL , is implemented in the freely available R package ComICS .
The immune system consists of a remarkable collection of immune cell subpopulations with complex interconnections . To gain a better understanding of immune processes at the cellular level , such as cell proliferation , differentiation , activation and migration , researchers have systematically quantified the abundance of particular immune cell types in health and disease . This approach has provided insights into the role of immune cells during both homeostasis and disease progression; for example , recruitment and accumulation of macrophages in adipose tissue are associated with obesity [1]; the presence of eosinophils in the airway lumen and lung tissues is considered a defining feature of asthmatic disease [2]; recruitment of monocytes to arterial vessel walls is an early step in the development of atherosclerosis [3]; and an increase in CD4+CD28null T cells is detectable in patients with complications of rheumatoid arthritis [4] . There is a strong need for workable methodological approaches that can identify the underlying molecular mechanisms determining the physiological state of the immune system . A major goal in this endeavor is to identify genetic variants that lead to inter-individual variation in the abundance of particular immune cell types . In studying the genetic basis of immune physiology , both genotyping and immune-cell quantification must be performed and analyzed in concert . Direct measurement of the abundance of a large number of immune cell types remains a challenge because of the relatively low throughput of cell-sorting technologies . Such direct quantification is particularly laborious when a large number of individuals is studied , and as a result , most association studies are restricted to only a few immune-cell types [5–17] , with few exceptions [18–20] . Thus , a simplified approach is required . With the advent of immune deconvolution methods , it is now possible to infer the relative abundance of immune cell subpopulations without the need for experimental cell sorting . Specifically , deconvolution methods take as input expression profiles of isolated immune cell types ( in short , a 'reference data'; e . g . , [21–24] ) and an expression profile from a complex tissue . The expression of each gene in a tissue is modeled as a linear combination of its expression in each cell type , where the weights stand for the unknown abundance of each immune cell type . This abundance can be resolved by solving a set of linear equations , one for each gene . Previous studies have shown that using only a subset of carefully selected genes ( rather than the whole expression signature ) typically reduces the signal-to-noise ratio and stabilizes the solution ( e . g . , [24 , 25] ) . For example , 360 , 61 , 240 and 547 genes were selected for immune cell type deconvolution in [24–27] , respectively . The selected genes , which are used as observations during the deconvolution process , are referred to as 'markers' . Deconvolution techniques have been successfully applied to predict the composition of immune cell types , but have not yet been applied in the context of genetic studies . We describe here a method for revealing the genetic basis of inter-individual variation in the abundance of immune cell types . Our method relies on a deconvolution algorithm that receives as input expression profiles from a complex tissue across a population of individuals , and uses this data to calculate relative cell type abundance values in each individual . The underlying genetic variants are then identified on the basis of the predicted cell type abundance levels , without the need for experimental cell quantification . In our framework , the predicted abundance of a particular cell type across a certain cohort of individuals is termed an 'immune trait'; the associated DNA variant is referred to as an 'immune quantitative trait locus' ( iQTL ) ; and the genetic association is termed an 'immune trait association' . Since we use predicted traits ( rather than direct measurements ) , special care has to be taken to ensure the reliability of the identified immune trait associations . To that end , we resample several disjoint sets of marker genes and then repeat the pipeline using the different marker sets . An association is considered reliable if it attains high significance , on average , based on several different sets of marker genes . We also realized that part of the reason for false positive iQTLs is the presence of genetic control on the expression levels of marker genes ( such genomic loci are typically termed 'expression QTLs' [eQTLs] ) . To overcome this difficulty , we filter out marker genes that are associated with potentially misleading eQTLs . Our rationale is to discriminate between true iQTLs and spurious ones: a false positive iQTL ( due to an eQTL ) can be eliminated by removing the relevant eQTL targets from the marker set; true iQTLs , in contrast , are generally robust to such alterations in the set of marker genes . We refer to this approach as the VoCAL ( Variation in Cell Abundance Loci ) algorithm . We used synthetic data to assess the performance of the VoCAL algorithm in a controlled setting . Using these data , we start by demonstrating the increasing complexity of the iQTL-identification problem with increasing numbers of eQTLs in a tissue . We next show the utility of VoCAL over a large range of data parameters , and demonstrate the benefits of discarding potentially misleading eQTLs while combining evidence from multiple sets of markers . As a proof of principle , we applied VoCAL to genotyping and lung expression profiles from recombinant inbred BXD mouse strains , thereby demonstrating the ability of VoCAL to identify significant iQTLs while removing spurious associations .
In the following we consider how to find , in the absence of direct cell-sorting measurements , the genetic basis of immune traits . To address this we rely on a computational inference of cell type abundance levels from gene expression data . We begin with an illustrated example to explain the basic rationale of this approach and follow with the actual pipeline of the VoCAL methodology . Consider a simplified reference data consisting of transcriptional profiles from three immune cell types ( c1-c3 ) , assuming that each cell type contains only five genes ( g1-g5; Fig 1A ) . In this reference data , each plot describes the RNA levels of each gene in each cell type . For example , the plots indicate the cell type-specific expression of gene g1 in cell type c3 . The scenario in Fig 1B ( left ) considers a certain genomic locus v that has an effect on the abundance of cell type c3 within a given tissue . This locus is therefore an iQTL . In accordance , Fig 1B ( left ) demonstrates the higher level of cell type c3 in TT-carrying compared to GG-carrying individuals . The plots of total RNA levels in the tissue are shown in the middle panel of Fig 1B; these RNA levels reflect the composition of cell types in the tissue and the RNA levels within each cell type . As can be seen in the figure , if a TT-carrying individual has an increased abundance of cell type c3 , then its level of the c3-specific gene g1 is also elevated ( Fig 1B , middle ) . Mathematical deconvolution methods take as input a certain list of marker genes , and then use the total RNA levels of these markers in the complex tissue to calculate the abundance of each cell type . In our example , the inferred ( deconvolved ) cell type quantities are shown in the right panel of Fig 1B , for each genotype and for two potential sets of marker genes ( marker sets g1-g4 [top] and g2-g4 [bottom] ) ; this prediction relies on the total RNA levels in the tissue from Fig 1B ( middle panel ) and the reference data from Fig 1A . It can be clearly seen that each of the two marker sets can be utilized to correctly predict ( i ) a higher abundance of cell type c3 in TT-carrying individuals , and ( ii ) a similar amount of cell types c1 and c2 in different genetic backgrounds ( Fig 1B , right ) . Thus , by repeating the same deconvolution process in multiple individuals , it is possible to identify true immune trait associations ( e . g , v-c3 ) and to reject false ones ( e . g . , v-c1 and v-c2 ) ; furthermore , we expect that the identification of true associations will be generally robust to the selection of marker genes . This observation is key to the success of the VoCAL algorithm . While studying the system , we discovered a potential pitfall of this approach—the existence of eQTLs acting on the intracellular RNA levels of genes . To gain some intuition about why this is the case , consider the presence of an eQTL acting in locus v ( instead of an iQTL in this genomic position ) . For instance , Fig 1C shows an effect of eQTL acting on the expression of gene g1 . We see that the TT- and GG-carrying individuals differ only in their RNA level of gene g1 ( Fig 1C , middle ) but not in their composition of cell types ( Fig 1C , left ) . Yet , when a marker set g1-g4 is used , a deconvolution algorithm may output an erroneous increased abundance of cell type c3 in TT-carrying individuals , which might be interpreted as an association between locus v and cell type c3 ( a false positive iQTL; Fig 1C , top right ) . We note that the spurious association stems from g1 ( a c3-specific marker and an eQTL target ) and can be eliminated by excluding g1 from the marker set ( e . g . , marker set g2-g4 , Fig 1C , bottom right ) . Thus , the inclusion of eQTL targets in the set of marker genes may interfere with our algorithm and lead to spurious iQTLs at the same genomic positions . Following this rationale , construction of marker sets that do not include eQTL targets can , in principle , be used to avoid spurious predictions . The VoCAL algorithm relies on this idea , as discussed below . We devised the VoCAL method with the specific object of using deconvolution to identify significant associations between cell type abundance traits and polymorphic DNA loci . The input of the VoCAL algorithm is the gene expression profiles of a given complex tissue across a population of genetically distinct ( genotyped ) individuals , as well as a large 'reference data' of transcriptional profiles from isolated immune cell subsets ( Fig 2A , top ) . The output is a collection of significant iQTLs ( Fig 2A , bottom ) . As we discussed , VoCAL relies on two observations . First , we expect noisy predictions to be weakly reproducible between marker sets , but true iQTLs to be consistently identified by multiple different marker sets . Based on this rationale , VoCAL combines iQTL predictions from multiple marker sets to produce a reliable model . Second , eQTL targets may lead to spurious iQTL associations . Naively , VoCAL could filter all eQTL targets in a pre-processing step . However , a potential caveat of this strategy is that the removal of many informative markers might reduce the ability to detect iQTLs . To address this , VoCAL leverages the observation that the expression of misleading markers likely associates with eQTLs located within the inferred iQTLs ( e . g . , locus v in Fig 1C ) . The problem is a challenging one , as the identification of iQTLs requires the selection of markers , and the selection of markers requires knowledge about the genomic positions of iQTLs . This necessitates the identification of both the iQTLs and the gene markers simultaneously . To address this , VoCAL applies an iterative approach . In each iteration , VoCAL uses the sets of selected markers to identify iQTLs and then uses the identified iQTLs to filter out confounding markers . In particular , VoCAL consists of five steps ( Fig 2B ) . In step 1—initialization—VoCAL constructs an initial collection of k marker sets . In this stage we do not yet have the inferred iQTLs . Thus , each set of markers is selected based on the ability of the genes to discriminate well between immune cell types in the reference data . This strategy has been proven useful in deconvolution of immune cell types [24–27] . Steps 2 and 3 are repeated k times , each time with a different set of markers . In step 2—Deconvolution—VoCAL relies on a mathematical deconvolution algorithm to predict cell type abundance levels . The input to this procedure is ( i ) the expression data of a complex tissue across individuals , ( ii ) the reference data , and ( iii ) a single set of marker genes . The output is a collection of immune traits , each consisting of inferred cell abundance values for a single cell type across the individual samples . In step 3—genome-wide association testing ( GWAS ) —VoCAL applies a statistical association test on each immune trait , producing association scores between each genomic locus and each immune trait . We term such a collection of association scores as an association map . Altogether , steps 2 and 3 provide a collection of k association maps ( a single map for each marker set ) . In step 4—aggregation—VoCAL combines the k association maps to produce a reliable model . In particular , for each given locus and each given immune trait , VoCAL calculates a single association P-value based on the relevant scores in the collection of k maps . Significantly associated loci are referred to as iQTLs . In step 5—filtration—VoCAL refines the k sets of marker genes by filtering out eQTL targets . Specifically , the filtration step tests whether any of the current marker genes is associated with an eQTL that coincides with an inferred iQTL . If such markers are found , VoCAL filters them out and returns to step 2 . In summary , the VoCAL procedure starts with an initial selection of k marker sets ( step 1 ) and then iterates between two tasks: a reliable identification of significant iQTLs relatively to a given collection of k marker sets ( steps 2 , 3 , and 4 ) , and the filtration of marker sets relatively to the collection of significant iQTLs ( step 5 ) . The algorithm terminates when there are no more changes to the marker genes . A detailed description of the VoCAL algorithm appears in the Methods section . The associated R package ComICS is available at https://cran . r-project . org/web/packages/ComICS/index . html and csgi . tau . ac . il/VoCAL/ . To evaluate the performance of VoCAL , it was necessary to simulate iQTLs and eQTLs in synthetic complex tissues . To do this over a population of individuals , we used genotyping of the recombinant inbred BXD mouse strains ( 102 individuals ) and a reference data containing expression profiles of isolated immune cell types ( taken from the ImmGen project [23] ) . First we randomly selected one or a few cell types from this reference data and a polymorphic locus ( an iQTL ) for each of these cell types; groups of co-expressed genes sharing the same eQTL hotspots were selected in a similar manner . Next , assuming an initial equal abundance of cell types for each individual , we altered the fractions of the chosen cell types according to the DNA allele of the selected iQTL . The magnitude of the change in cell type fractions is termed the iQTL effect size . Lastly , we generated the final expression values of each tissue sample by ( i ) mixing the signatures from the reference data according to those fractions , and ( ii ) introducing the effect of the selected eQTLs on their target groups of genes ( the magnitude of this effect is termed the eQTL effect size ) . To account for the common scenario in which the cell types that are used during the deconvolution process are not exactly the same as the cell types in the complex biological tissue , we used two disjoint sets of cell types: one set is used for synthetic data generation ( the 'data-generation cell types' ) , while the VoCAL algorithm—particularly the deconvolution process—was applied based on another set of cell types ( the 'deconvolution cell types'; Fig 3A ) . Each cell type in one set is closely related to a cell type in the other set ( for example , the same cell type isolated from different tissues; S1 Table ) , allowing us to use the ground truth immune-trait associations to evaluate the predictions of the VoCAL algorithm . Although the simulation may not perfectly mirror a real tissue , it can still provide a model for a tissue that is ( i ) affected by iQTLs and by eQTL hotspots leading to variation in specific cell types and genes , and ( ii ) characterized by cell types that are similar but not identical to the cell types given as input to the VoCAL algorithm ( see Methods and S1 Fig ) . Here we examine and demonstrate four different initialization methods ( used in step 1 of the VoCAL algorithm ) : ( i ) choosing sets of gene markers carrying the highest variability in expression between cell types ( top varying ) ; ( ii ) choosing representative marker genes that can discriminate well between cell types ( cell tagging; 24 ) ; ( iii ) using the cell-tagging strategy but adding a predefined set of cell surface markers that were used in the cell-isolation process ( cell tagging with FACS; 36 ) ; and ( iv ) using an unbiased selection of gene markers ( random sampling ) . We note that the three former methods ( but not random sampling ) are based on the cell type signatures in the reference data . The ability to identify the correct iQTLs was evaluated as the area under the receiver operating curve ( AUC score ) . Notably , the results are robust to variation in the parameters of the VoCAL algorithm ( S2 Fig ) . For example , different significance cutoff of the identified iQTLs ( varying between 0 . 05 and 10−12 ) had a little effect on the eventual AUC scores . Motivated by these results , we analyzed the effect of different data parameters and the benefits of the VoCAL algorithm , as discussed below . We first investigated how the complexity of the problem is affected by the presence of eQTLs and iQTLs in a tissue . To assess this , we generated synthetic datasets with varying numbers of iQTLS and eQTLs , each of which acts through a fixed size of its genetic effect . Overall , we tested a total of 15 such combinations of different numbers of QTLs . First , we applied VoCAL without the 'filtration step' ( using steps 1–4 only ) , allowing us to trace the effect of eQTL targets within the marker sets . As expected , predictions in datasets with smaller numbers of iQTLs were more accurate ( Fig 3B ) . Furthermore , consistent with our expectation ( Fig 1C ) , the ability to identify iQTLs depended not only on the number of iQTLs , but also on the number of eQTLs: the AUC scores were lower in datasets with higher numbers of eQTLs . For example , AUCs were significantly higher for datasets with no eQTL hotspots than for those with 2 eQTL hotspots for the same number of iQTLs ( average AUC = 0 . 7 vs . 0 . 39; P < 2∙2−16 ( t-test ) , in the presence of 4 iQTLs , effect sizes = 0 . 05 , cell-tagging and k = 1; Fig 3B ) . These results were quantitatively similar when using a larger number of association maps ( k = 10; Fig 3C ) and for different initialization methods and data parameters ( S3 Fig , left and middle panels ) . We conclude that the iQTL-identification problem becomes more complex with increasing amounts of different genetic effects; without applying the filtration step , the presence of eQTLs results in relatively low performance values . Next we were interested in the effect of applying the filtration step ( step 5 , Fig 2B ) . We found that the iterative filtration of marker sets improved the prediction of iQTLs . In particular , without filtration of eQTL targets , the presence of eQTLs in a tissue resulted in a drastic reduction in AUC scores ( Fig 3B and 3C ) ; in contrast , in the presence of the filtration procedure , there was little or no reduction in AUC scores when more eQTLs were added ( Fig 3D ) . The same was true when different initialization methods and data types were used ( e . g . , Figs 3E and S3 ) . Notably , marker filtration brought no improvement when the complexity was increased by multiple iQTLs ( Fig 3D and 3E ) ; this is consistent with the primary goal of the filtration procedure , which is to tackle the problem of confounding eQTLs ( rather than the problem of interactions among multiple iQTLs ) . To gain additional insights into the filtration step , we analyzed 2-dimensional plots of AUC scores for the same synthetic datasets with ( x-axis ) and without ( y-axis ) this step ( S4A Fig ) . In the case of 2 eQTL hotspots , all datasets appear above the diagonal line , indicating that the filtration step resulted in improved performance ( e . g . , using the top-varying initialization method , P < 2∙10−34 ( t-test ) ; S4A Fig , left panel ) . In contrast , the AUC scores remained nearly unchanged when eQTLs were not introduced into the simulation ( e . g . , using cell-tagging with FACS and 10 iQTLs , P > 0 . 15 ( t-test ) ; S4A Fig , right panel ) . The patterns were similar when we used false positive rate ( FPR ) and true positive rate ( TPR ) metrics instead of the AUC ( e . g . , S4B and S4C Fig ) . Taken together , these results indicated that the filtration procedure successfully reduces the amount of spurious associations derived from the effects of eQTLs in a tissue . We next investigated the added value of generating k association maps rather than a single map . To that end , we compared the performance of VoCAL with 10 association maps to its performance with a single map . We found that the power to detect iQTLs increased drastically when using 10 association maps ( Figs 3B and 3C , S3 and S5A ) . For example , using 1 eQTL and 6 iQTLs , the usage of 10 association maps is significantly better than using one selected map ( P <2∙10−16 , paired t-test; assuming effect size of 0 . 05 , the cell-tagging method , without filtration ) . In fact , the AUC scores were quantitatively correlated with the number of association maps ( Fig 3F ) . These results were qualitatively similar when using different initialization methods and different numbers of iQTLs ( Figs 3F and S5B–S5D ) . We further tested the possibility of pooling the k marker sets into a single large set . As a proof of principle , we focus on two alternative strategies . In the first strategy , VoCAL was applied using k association maps , where each map relies on a marker set consisting of Ψ markers . Alternatively , VoCAL was applied with a single marker set that was generated by pooling the k disjoint marker sets of the former method . Since we use the cell-tagging initialization method , the resulting pooled set is the same as direct selection of Ψ∙k cell-tagging markers . This way , both strategies were initialized with exactly the same list of markers . We find better performance with multiple marker sets as compared to a single pooled set ( S6 Fig ) . For example , when we use k = 6 and 2 iQTLs , P < 5∙10−11 ( t-test ) for multiple sets over the pooled set . Taken together , our results demonstrate the benefit of testing reproducibility in association signals when relying on multiple non-overlapping marker sets . We also compared the reference-based initialization methods—the top-varying and two tagging-based methods—with random sampling of marker sets . The reference-based selection of marker genes showed a striking improvement in performance over the random sampling of markers , especially when the number of iQTLs was large ( e . g . , S7 Fig ) . For example , when we used 8 iQTLs and 1 eQTL hotspot , P < 6∙10−91 ( t-test ) for cell-tagging over the random sampling approach . The results for different parameter settings were similar ( e . g . , S3 Fig ) . Thus , the current study clearly supports a rationalized initialization of marker sets . Notably , since one method of reference-based initialization did not seem to consistently outperform the others , we could not find a convincing reason to prefer one method over another . We applied the VoCAL algorithm to identify iQTLs in the lung gene expression dataset of Alberts et al . [28] , which was measured across a collection of ( genotyped ) naive BXD mouse strains ( a cross of C57BL/6J [B6] and DBA/2J [D2] strains ) . The analysis was conducted using the 'cell-tagging with FACS' initialization method on the basis of the ImmGen reference data [23] , which carries 207 immune cell types . VoCAL converged after three iterations , with removal of 13 and 3 markers in the first two iterations , respectively , and no additional filtration in the third . In the absence of marker filtration , 7 significant iQTLs were apparent , associated with the abundance of murine cytomegalovirus ( MCMV ) -stimulated natural killer ( NK ) cells , lung macrophages , mucosal Langerhans cells , non-classical MHC class IIint monocytes , effector T cells , transitional type 2 B cells , and B1a cells ( permutation FDR < 0 . 05; see Fig 4A and full details in S2 and S3 Tables ) . However , only the Langerhans cells exhibited significant association when we applied VoCAL with the iterative filtration of marker genes ( Fig 4A ) . On the assumption that our study with synthetic data was realistic , the six remaining associations probably indicate false positives , since they appeared only in the presence of a few eQTLs that could have stemmed from any of the cell populations in the tissue . The subpopulation of MCMV-stimulated NK cells demonstrates VoCAL's ability to address the eQTL-confounding problem . In the absence of marker filtration step , these cells were found to be significantly associated with a 25 . 6-Mb region on chromosome 6 , with a peak between 129 . 56–133 . 8 Mbp ( Fig 4A , top left ) . The RNA levels of three marker genes—Klrc3 , Klrk1 and Klra8—were associated with an eQTL residing in the same iQTL region . In accordance , the three markers were removed during the filtration step and the association completely vanished ( Fig 4A , top left ) . Consistent with our predictions , all three markers have a known role as NK-specific receptors , with a specific role of Klra8 in MCMV infection [29–31] . Brown et al . [30] reported that ( i ) splenic NK cells are abundant in both the B6 and D2 strains ( the parental strains of BXD lines ) ; and ( ii ) in NK cells , the Klra8 gene is expressed in B6 but not D2 mice . Furthermore , Lee et al . [31] showed that , using spleen and liver tissues , the Klra8 gene could be amplified from the B6 strain but not from the D2 strain . Thus , our predictions in NK cells agree well with previous studies . Additional experiments are required to test the NK hypothesis in the lung tissue . The mucosal Langerhans cells provide a clear example of a predicted iQTL ( Fig 4B ) . In lung tissue , mucosal Langerhans cells act as the first line of defense against invading pathogens . Using VoCAL , the Langerhans cells were significantly associated with a 1 . 2-Mb region iQTL on chromosome 12 ( from 59 . 05 to 60 . 24 Mbp ) with permutation-based FDR < 0 . 025 . The predicted iQTL interval consisted of 9 genes ( Fig 4B , left ) , none of these genes had any cis-association . Notably , 2 of these 9 genes located at the peak of this interval—somatostatin receptor 1 ( Sstr1 ) and C-type lectin domain receptor ( Clec14a ) —have documented roles in Langerhans cells ( e . g . , [32–34] ) . The association with Langerhans cells also demonstrates the advantages of aggregating k association maps , as the results consisted primarily of consistent association pattern ( 8 out of 10 independently derived maps; Fig 4B , left ) . These maps were in agreement with the overall prediction of the VoCAL algorithm ( Fig 4B , left , black line ) . Furthermore , in all of these cases strains carrying the D2 allele showed higher predicted quantities of Langerhans cells than strains carrying the B6 allele ( Fig 4B , right and S4 Table; based on the rs3705833 locus located at chromosome no . 12 at 59 . 05 Mbp ) . This highlights a major advantage of our approach: true iQTLs are expected to be revealed on the basis of distinct subsets of markers . The independent support of the iQTL interval from different marker sets and the lack of eQTLs in this region are in agreement with our hypothesis of an iQTL acting on Langerhans cells in chromosome no . 12 .
In this work we developed a novel method , which we call VoCAL , to reveal the genetic basis of variation in immune cell traits based on gene expression data . Whereas existing methods for genetic mapping require direct measurement of immune traits across a large population of individuals , VoCAL avoids cell quantification by inferring these immune traits indirectly . To address this , VoCAL utilizes a mathematical deconvolution technique , which relies on a set of marker genes , to calculate the abundance of a variety of immune traits; it then applies genome-wide association methods to uncover the causal loci for these traits ( iQTLs ) . By consolidating hypotheses from different marker sets we avoid errors from noisy predictions ( Fig 2B ) . This technique relies on the observation that true signals are generally robust to the choice of a marker set , as demonstrated in Fig 1B . Our analysis indeed demonstrates the improved performance of this approach ( Figs 3F , S5 and S6 ) and the consistency between predictions derived from distinct marker sets in the murine lung-tissue dataset ( Fig 4B ) . Suspecting that the existence of eQTL targets may lead to spurious iQTL associations ( as demonstrated in Fig 1C ) , the VoCAL pipeline refines the selected sets of markers by filtering out potentially confounding eQTL targets ( Fig 2B ) . Our analysis in synthetic data confirms the increased complexity of the problem with increasing number of eQTLs ( Figs 3B–3D and S3 ) and the improved performance when using the filtration step ( Figs 3D and 3E and S4 ) . Analysis of a biological dataset from the lung complex tissue further underscores the utility of the filtration step: of the seven putative associations found , only one still holds after filtration of eQTL targets ( Fig 4A ) , suggesting that the remaining associations are purely due to confounding eQTLs . For example , we discovered that the association of a subpopulation of NK cells was eliminated when the Klra8 gene was removed from the set of marker genes . This prediction is in agreement with previous in vitro measurements [30 , 31] . Taken together , our results emphasize VoCAL's ability to eliminate spurious associations that do not reflect an actual change in quantity of an entire cell subpopulation , but rather an inter-individual variation in expression of particular genes . Our findings point the way to several avenues of research . First , additional methods capable of dealing with biological tissues of high genetic complexity will have to be developed; for example , joint analysis of several iQTLs and eQTLs may enhance predictive power and make it possible to distinguish immune cell-cell and gene-cell interactions . Second , it will be important to extend VoCAL to human data . For example , we should use a human reference data ( such as [35] ) ; account for different confounding effects such as population structure and gender; and extend the association tests ( Eq 2 ) to handle heterozygous populations . Third , taking into account the correlations between the different marker genes might enhance our predictive power . Fourth , manipulation of the reference data ( as in [36] ) would allow us to explore genetic loci that lead to a shift of an immune cell to its inflammatory state . Fifth , it would be important to incorporate environmental effects , thereby highlighting the role of non-heritable factors in physiological immune responses . Finally , the ability to predict iQTLs provides plausible hypotheses for future experimental investigations . For example , this study suggests an iQTL acting on immune Langerhans cells located at the lung mucosa . The association holds when using multiple different marker sets and after applying the marker filtration step ( Fig 4B ) . Langerhans cells play a key role in innate defense against pathogens , suggesting a framework for understanding the genetic and immune cell interactions underlying susceptibility to respiratory infections . Additional investigations are needed to explore the functionality of changes in the abundance of these cells in the lung tissue . Overall , the methodology is general and can be applied with other deconvolution tools ( e . g . , [27] ) , and for other applications in the mammalian immune system .
VoCAL takes as input the following information: The VoCAL pipeline involves five steps: initialization , deconvolution , GWAS , aggregation and filtration . In the following we first describe the details of the different steps and then provide the overall VoCAL algorithm . A brief summary of the VoCAL framework is provided in S8 Fig . We analyzed the gene-expression profiling of whole lung tissue samples obtained from 47 BXD recombinant inbred mouse strains ( E-MTAB-848 [28] ) . These strains were originally generated by crossing the B6 and D2 inbred strains , which are also included in this dataset . Using log-transformed data , we normalized each strain by subtracting the expression profile of the B6 strain . We used the 207 cell type profiles that are part of the ImmGen reference data ( log-transformed; [23] ) . Genotyping data were reported and released in the GeneNetwork website ( http://www . genenetwork . org ) . The genome annotations were based on UCSC Mouse Genome Browser NCBI37/mm9 assembly ( RefSeq mm9 ) . We applied VoCAL using the 'cell-tagging with FACS' initialization method with k = 10 , Ti = 5 and Te = 10 . We used 100 permutations of the labeling of strains in the lung expression data to assess the empirical FDR , defined as the ratio of the average number of associations found in the permuted data to the number of associations in the real lung data ( denoted 'permutation FDR' ) . We note that VoCAL utilizes permutations tests in addition to the resampling of markers ( as detailed in step 1 ) . The two procedures were designed to address two distinct challenges: whereas the selection of markers addresses the problem of noisy associations due to confounding eQTLs , the permutations aims to account for the multiple testing problem . | Quantitative trait locus ( QTL ) studies have identified a plethora of genetic variants that lead to inter-individual variation in the abundance of immune cell subpopulations , both in normal and disease states . Cell sorting is an effective method of monitoring immune cell type quantities; however , owing to the large number of possible immune cell subsets , it can be difficult to apply this method to each cell type over multiple individuals . Recent QTL studies dealt with this difficulty by focusing on an a priori selection of one or a few cell subsets . Here we introduce VoCAL , a deconvolution-based method that utilizes transcriptome data to infer the quantities of immune cell types , and then uses these quantitative traits to uncover the underlying DNA loci . Our results in synthetic data and lung cohorts show that the VoCAL method outperforms other alternatives in revealing the genetic basis of immune physiology . | [
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"cel... | 2016 | Exploiting Gene-Expression Deconvolution to Probe the Genetics of the Immune System |
The mechanism by which homologous chromosomes pair during meiosis , as a prelude to recombination , has long been mysterious . At meiosis , the telomeres in many organisms attach to the nuclear envelope and move together to form the telomere bouquet , perhaps to facilitate the homologous search . It is believed that diffusion alone is not sufficient to account for the formation of the bouquet , and that some directed movement is also required . Here we consider the formation of the telomere bouquet in a wheat-rye hybrid both experimentally and using mathematical modelling . The large size of the wheat nucleus and wheat's commercial importance make chromosomal pairing in wheat a particularly interesting and important process , which may well shed light on pairing in other organisms . We show that , prior to bouquet formation , sister chromatid telomeres are always attached to a hemisphere of the nuclear membrane and tend to associate in pairs . We study a mutant lacking the Ph1 locus , a locus ensuring correct homologous chromosome pairing , and discover that bouquet formation is delayed in the wild type compared to the mutant . Further , we develop a mathematical model of bouquet formation involving diffusion and directed movement , where we show that directed movement alone is sufficient to explain bouquet formation dynamics .
Meiosis , an integral component of the mechanism of sexual reproduction , is a crucial process in eukaryotes , resulting in a halving of the number of chromosomes . Such a process allows genetic material to be shared during fertilisation , whilst maintaining the same amount of DNA per cell . Diploid cells that undergo meiosis must first pair homologous chromosomes so that gametes can be formed containing only one copy of each pair . The mechanism by which pairing occurs has long been an outstanding problem [1] , [2] since thermally-driven diffusion of chromosomes is probably much too slow to ensure pairing in the observed time scale of hours [2] . Many organisms attach telomeres to the nuclear membrane before pairing , although how this is achieved is largely mysterious . Further , many of these organisms then move the telomeres together , until they form one cluster on the membrane producing the telomere bouquet [3] , [4] , [5] , [6] , [7] , [8] . This is in contrast to the Rabl configuration , seen in some organisms during interphase , where centromeres and telomeres occupy opposite sides of the nucleus . In addition there is often complex motion of the entire chromatin as , for example , has been observed in maize [9] . It has been suggested that the telomere bouquet facilitates homologous pairing , perhaps by reducing the search space to a much smaller region . The method by which the bouquet forms is not well understood . However , it is known that numerous organisms contain pairs of SUN-KASH proteins , which link chromosomes to cytoskeletal motors , and potentially these motors could pull the telomeres around the nuclear membrane [10] . Although chromosome motion has been much studied during mitosis , there are far fewer mathematical and computational models of chromosome organisation during meiosis . A purely mathematical model of homology searching was performed in [11] where , along with comparing a 2D search along the nuclear membrane with a 3D full nucleus search , the effect of the number of homology recognition sites per chromosome was analysed . Recently , the effect of the telomere bouquet on homologous pairing has been modelled , in an attempt to understand the reason for bouquet formation [12] . Another recent paper studied the spatial organisation of meiotic chromosomes after pairing is complete , when homologous chromosomes are arranged in synaptonemal complexes [13] . A combination of experiments and modelling in rye were used in [14] where it was argued that directed movement of telomeres is required to form the bouquet in the observed time . However , diffusion was also needed to explain all their experimental data . Here we significantly extend this earlier work and our general understanding of meiosis both experimentally and theoretically , demonstrating the novel result that directed movement alone ( without diffusion ) can in fact explain bouquet formation dynamics . We also examine the degree of variation in this directed movement , presumably due to disorder in the appropriate underlying cytoskeletal elements . In addition we determine for the first time the initial arrangement of telomeres on the nuclear envelope , before telomere bouquet formation begins . The problem of chromosome pairing in wheat is particularly acute due to both the large nuclear radius ( ∼8 µm ) and the relatively large chromosomes ( average of ∼800 Mb each ) . These should be compared to typical values in , say , the yeast S . cerevisiae , where the nuclear radius is around 1 µm and the average chromosome size is less than 1 Mb . Although it might be thought that the much larger nuclear volume in wheat would drastically increase the pairing time , wheat is able to complete pairing in times similar to those for other organisms . Wheat may achieve this feat by utilising a greater level of meiotic chromosome organisation . In addition to clustering all telomeres in a bouquet as in many organisms , wheat carefully controls the centromere positions , both by maintaining the Rabl configuration during interphase and by forming seven centromere clusters shortly before the telomere bouquet is formed [15] . However , since these centromere clusters form when the telomere bouquet is almost complete , it is unlikely that they significantly influence the dynamics of bouquet formation . Similar features are found in bouquet formation in maize , where centromeres and telomeres are both organised during meiosis [8] . Pairing in bread wheat is further complicated by its hexaploid nature where , due to hybridisation of diploid ancestors , the genetic material consists of three closely related genomes . With each nucleus containing six related copies of each chromosome , it is important to ensure that pairing only occurs between homologous pairs . This pairing specificity has been shown to involve the Ph1 ( Pairing homeologous 1 ) locus , a region located on chromosome 5B . Deletion of this region leads to homeologous pairs ( i . e . related but non-homologous pairs ) , chromosome rearrangements , and eventually infertility . The Ph1 locus has been defined to a cluster of defective Cdk-like genes that have been shown to suppress Cdk-2 type activity and hence histone H1 phosphorylation [16] . To examine homologous chromosome pairing and bouquet formation we studied two wheat-rye hybrids: a wild type containing the Ph1 locus and a mutant where Ph1 has been deleted . Sexual hybridization between wheat and a wild relative generally produces an interspecific hybrid containing a haploid set of related but non-homologous chromosomes ( homeologues ) , in which chromosome pairing is largely prevented as a result of the presence of Ph1 [17] . Although non-homologous pairing is prevented , the telomere bouquet still forms even in a wheat-rye hybrid containing Ph1 [16] . Since pairing is normally prevented , wheat-rye hybrids are ideal for studying the Ph1 locus: the presence of paired chromosomes can then be used as an easily identified phenotypic signal of unusual Ph1 behaviour . Further , understanding the basis for pairing suppression may lead to the important practical application of being able to switch the pairing on and off , thereby enhancing breeding strategies [18] . In this study , we analyse both the initial distribution of telomeres ( after telomeres have moved to the nuclear envelope but prior to bouquet formation ) and their dynamics as they form the bouquet . We show that , before bouquet formation , sister chromatid telomeres are always attached to a randomly-orientated hemisphere of the nuclear envelope and tend to associate in pairs . We combine fluorescence microscopy with mathematical modelling to shed light on how telomeres move along the nuclear membrane , how the bouquet forms and the relative roles of diffusion and directed movement . Further , we study the differences between plants with and without the Ph1 locus , showing that bouquet formation is delayed in the presence of Ph1 .
Wheat–rye hybrids have a haploid set of 21 wheat chromosomes and seven rye chromosomes . Replication of the rye heterochromatin knobs can be easily visualized in these lines . Previous data showed that in wheat-rye hybrids , either with or without Ph1 , DNA replication is initiated in the meiocytes as the tapetal cells are finishing their replication , and all meiocyte replication is completed within a 4 hr period before the telomeres form the bouquet [16] . Therefore , DNA replication in the meiocytes is a good guide for identifying the onset of telomere dynamics and bouquet formation . In this work , DNA replication in wheat–rye anthers was analyzed by diffusing in 5-ethynyl-2′-deoxyuridine ( EdU ) , a nucleoside analog of thymidine that is incorporated into DNA during active DNA synthesis . In EdU , the terminal methyl group is replaced with an alkyne group , which allows detection using a fluorescent azide compound that covalently binds to the alkyne group in a “click chemistry” reaction [19] . This technology is quick , very specific , and does not require DNA denaturation . It therefore provides good structural preservation and is compatible with dual labelling with telomere probes . After EdU treatment for 4 hr , anthers of wheat-rye hybrids ( see Figure 1A ) , both with and without the Ph1 locus in the wheat genome , were labelled with a telomere probe by fluorescence in situ hybridization ( FISH ) and chromosomes were counterstained with 4′ , 6-diamidino-2-phenylindole ( DAPI ) , as described in detail in Materials and Methods . Thus , anthers undergoing or just after DNA replication in the meiocytes were identified via EdU incorporation and labelling , while telomeres in the same meiocytes were labelled by FISH . Anther sections were then imaged using fluorescence microscopy . Our method offers a series of snapshots of in vivo states rather than potentially perturbing the normal progression by in vitro anther culture . These images were taken at essentially random times during ( or just after ) meiotic DNA replication . Each section gave rise to three stacks of 2D images: one stained with DAPI , one labelled with telomere probes and one labelled with EdU . The images include both meiocytes ( which undergo meiosis to form gametes ) and tapetal cells ( which aid nutrient transportation within the anther and do not undergo meiosis ) ; see Figure 1B . Figures 2A–C show example snapshots of the different stages of bouquet formation , ranging from dispersed telomere clusters to a tight telomere bouquet . From the raw dataset of images we first extracted the positions of the telomere signals . In each case this involved using the DAPI image to determine the extent of the nucleus and the FISH telomere image to locate the telomeres . For each telomere signal we extracted its 3D position , its size and its intensity . Further , we recorded the point within each nucleus that was furthest from the centre of the anther , i . e . the point on the “outside” of the anther ( Figure 1B ) . For details see Materials and Methods and the Supporting Information . Figure 2D shows a representative example of the cluster positions ( extracted from the data in Figure 2A ) . Wheat-rye hybrid cells contain 21+7 chromosomes and so , after undergoing DNA replication , a meiocyte nucleus contains 112 telomeres , which , as telomeres at the same end of sister chromatids are close ( or attached ) , would appear as 56 telomere signals . However , it is never possible ( at least with our resolution ) to even see 56 separate telomere signals . This is due to sister chromatid telomeres being close together ( and perhaps even attached ) , forming sister chromatid telomere clusters . From now on we will often refer to sister chromatid telomeres , namely the pairing of the two telomeres at the same end of sister chromatids . When we refer to pairing/clustering of sister chromatid telomeres , we mean the pairing/clustering of these pairs of telomeres . So , for example , a pair of sister chromatid telomeres would involve a cluster of four telomeres in total . From the positions and intensities of the telomere signals , we constructed three measures of the telomere distribution . First , we simply counted the number of telomere clusters in a given nucleus , which we call N . As telomere bouquet formation proceeds , N will gradually decrease as more and more telomeres join the bouquet . Second , we determined which point on the surface of the nucleus lies furthest from the telomere clusters ( by maximising the sum of the 3D distances to the telomere clusters weighted by their intensities ) and then recorded the average telomere distance from this point ( again weighted by intensities ) . Figure 3A shows a sketch of the definition of dmax . This distance , dmax , always takes values above 1 . 2R ( see Supporting Information ) and , as bouquet formation proceeds , telomeres move closer to each other and dmax increases , reaching a maximum after bouquet formation has completed . Finally , we calculated dout , which is the average 3D distance from the telomere clusters to the “outside” pole of the nucleus weighted by intensity , where the “outside” pole of the nucleus is the point on the nuclear membrane furthest from the anther centre ( Figure 1B ) . Figure 3B shows a sketch of how dout is defined . Unlike dmax which increases with time , dout decreases as bouquet formation proceeds , equalling zero only if the bouquet forms exactly on the outside of the nucleus . See Supporting Information for detailed definitions of dmax and dout . Since our data are noisy , useful information can only be extracted by analysing many nuclei . We therefore considered the histogram of the number of telomere clusters , N , the histogram of the maximum average telomere cluster distance , dmax , and the histogram of the average telomere cluster distance from the outside pole , dout . Although we do not have time-lapse images and so cannot track individual telomeres as they move towards the bouquet site , we can still extract information on bouquet formation dynamics by studying these histograms . For example , the cluster number histogram shows the proportion of time that nuclei spend with a given number of clusters , which is directly related to the telomere dynamics . From the 3D positions of the telomere clusters , we checked that telomeres are attached to the nuclear envelope . To do so we calculated the distance of clusters from the centre of the nucleus as a fraction of the nuclear radius , and found that , in both meiocytes and tapetal cells ( both with and without the Ph1 locus ) , this normalised distance has average 0 . 9 and standard deviation 0 . 1 . This supports the idea that telomeres are associated with the nuclear envelope , not just in meiocytes , but in tapetal cells and potentially , therefore , in many diverse cell types . We also examined the position of the final bouquet in Ph1− meiocytes relative to the anther centre . To do this we studied images where the bouquet has completely or very nearly formed . In each case we measured the angle , from the centre of the nucleus , between the bouquet and the “outside” pole and plotted the histogram of these angles ( Figure S1 ) . If the bouquet formed at random positions on the nuclear membrane this would give a flat histogram . However , since Figure S1 is heavily weighted to small angles , this shows that , in the majority of cases , the bouquet tends to form close to the outside pole of the nucleus , the point on the nuclear membrane furthest from the centre of the anther ( Figure 1B ) . During meiosis , meiocytes start with their telomeres attached to the nuclear membrane , and then gradually form the telomere bouquet by moving all telomeres to a small region on the membrane . However , before we study the dynamics of forming the bouquet , it is important to study the initial distribution of telomeres ( after telomeres have attached to the nuclear envelope but before bouquet formation has started ) . This distribution can then be used to inform the initial condition for our mathematical model . Since it is not possible to determine from a still image whether a meiocyte has started bouquet formation , we instead use tapetal cells ( both from Ph1+ and Ph1− plants ) to study the initial telomere distribution in meiocytes . We also checked , as explained below , that the initial telomere distribution in meiocytes is indeed similar to the telomere distribution in tapetal cells . As discussed previously , we never observed as many as 56 telomere clusters . In fact combining all our tapetal data we find , on average , only 27±1 telomere clusters ( n = 133 ) , where the error is the standard error of the mean number of telomere clusters . This suggests that there is always some association between sister chromatid telomeres . Furthermore , strikingly , 27 is close to half of 56 , which suggests that the sister chromatid telomeres may be associating in pairs . We also confirmed this result separately for Ph1+ and Ph1− tapetal cells . There are three possibilities for how telomeres might pair together: sister chromatid telomeres on opposite ends of the same chromosome may pair , homeologous chromosomes may pair , or any two sister chromatid telomeres may pair non-specifically . It would be interesting to label individual chromosome telomeres to determine which of these associations occurs . It is also revealing to study the distribution of the number of clusters . This distribution is approximately normal with a standard deviation of about 8 ( see Figure 4A ) . This implies that , although sister chromatid telomeres on average form pairs , this is not always the case: sometimes fewer than 28 pairs form , and in other cases telomeres form clusters containing more than two sister chromatid telomeres . Potentially this could be because the association between nearby telomeres is transient , with only weak forces holding clusters together , so that telomeres can easily dissociate from existing clusters . It is also possible that the association is not between telomeres but between the chromosomes themselves , perhaps between subtelomeric regions . The exact region of the chromosomes that are associated would impact the distance that telomeres could move from each other , which could also explain the potential movement of telomeres in and out of clusters . Further , the fact that there are clusters containing more than two sister chromatid telomeres disfavours a model where the clusters are solely due to associations between opposite ends of single chromosomes . However , it would still be interesting to know whether pairings between telomeres at opposite ends of a chromatid pair are preferential . Again , labelling individual telomeres would help to answer this question . In addition to the initial number of telomere clusters , we can also study the initial telomere cluster distribution in space . As before , the initial distribution refers to the distribution once the telomeres are attached to the nuclear envelope , but before bouquet formation has started . When chromosomes are in the Rabl configuration , with centromeres biased towards one side of the nucleus , it is often observed that the telomeres , being the regions on the chromosomes furthest from the centromeres , inhabit regions of the nucleus opposite to the centromeres . In wheat , the Rabl configuration persists through all stages of the cell cycle , and so we expect a bias in the initial distribution of telomeres . To study this we plot the histogram of the maximum average telomere cluster distance , dmax , for tapetal cells ( combining both Ph1+ and Ph1− cells; see Figure 4C ) . If telomere clusters were randomly distributed on the nuclear membrane , a computer simulation ( see Supporting Information ) shows that we would expect a histogram centred on 1 . 51R . Conversely if the telomere clusters were confined to a hemisphere the histogram would peak at 1 . 72R . Since the maximum in Figure 4C occurs at 1 . 74R , this suggests the telomere clusters are , on average , initially distributed within a region slightly more restricted than a hemisphere ( which has an opening angle of 180° ) . This agrees with the examination of individual images , where it is often obvious that telomere clusters are preferentially grouped within some hemisphere ( for example , see Figure 2D ) . In fact , simulations ( see Supporting Information ) show that this data fits well with telomere clusters confined to a cap subtending an opening angle that follows a normal distribution with mean <Θ0> = 170° and standard deviation δΘ0 = 30° . This result is not changed if Ph1+ or Ph1− tapetal cells are analysed separately . To determine whether this initial cap has any preferred orientation with respect to the centre of the anther ( as suggested in previous models [14] ) , we calculated the distribution of average distances of telomere clusters from the “outside” pole for tapetal cells , i . e . the distribution of dout ( Figure 4D ) . If , for example , telomere clusters sit in the “outside” cap , then the average value of dout will be lower than for other distributions . In fact , computer simulations ( see Supporting Information ) show the average value of dout would then be 0 . 93R . Conversely a random orientation for the telomere cap would give a distribution with an average of 1 . 31R . The data ( combining Ph1+ and Ph1− cells; Figure 4D ) , with average 1 . 30R , matches much better with this second case , showing that the initial cap containing the telomeres does not have a preferred orientation . This result is unchanged if we separately analyse Ph1+ and Ph1− cells . This conclusion is important for our mathematical model , as we explain below . Although the average of dout matches well between the experimental data and our cap distribution , the full experimental distribution is still somewhat broader ( Figure 4D ) . Nevertheless , the width of the distribution for a randomly-orientated cap is much closer to the experimental value than that for an “outside” cap ( see Supporting Information ) . The Rabl configuration may also influence the position of telomere clusters within the randomly-orientated cap . For example , chromosomes with similar arm lengths may tend to lie closer to each other than to other chromosomes . This may help explain the spread in initial cluster size , with some sister chromatid telomeres grouped in pairs and others grouped in larger clusters . In principle it would be possible to explicitly model the position of the full length of each chromosome , via a semiflexible polymer model ( as in [20] and [12] ) , in order to determine the initial telomere positions . However , such an analysis is beyond the scope of this work and instead we assume , for simplicity , that the telomere clusters are initially placed randomly within the randomly-orientated cap . Since the Ph1 locus has been implicated in preventing homeologous pairing , it may well affect the dynamics of telomere bouquet formation . To study this issue we considered telomere data both from a wheat-rye hybrid with the Ph1 locus ( Ph1+ ) and in a mutant where the locus has been deleted ( Ph1− ) . As expected , we found a wide range in the number of telomere clusters in the Ph1− meiocyte images , ranging from many separate clusters to a single large cluster after the bouquet has formed ( see below ) . However , interestingly , when we plotted the histogram of the number of telomere clusters for Ph1+ meiocytes ( Figure 4B ) , we found little evidence of bouquet formation . In fact we found a distribution that is remarkably similar to the distribution for tapetal cells ( Figure 4A ) . The bouquet eventually forms even in Ph1+ meiocytes [16] , but since our images ( from around the time of meiocyte replication ) do not show any noticeable change from the tapetal telomere distribution , we conclude that the onset of bouquet formation is delayed in the presence of Ph1 . Since it is not clear whether homologous pairs form before or after formation of the bouquet , perhaps the purpose of this delay in the presence of Ph1 is to facilitate correct pairing of homologues , allowing more time to check potential pairings and dissociate incorrectly-paired homeologous chromosomes . To further confirm our conclusion that bouquet formation has apparently not started in our Ph1+ meiocyte dataset , we also compared the dmax and dout distributions from Ph1+ meiocytes with those from the tapetal ( both Ph1+ and Ph1− ) data . Histograms for dmax and dout ( Figure S2 ) are , as with tapetal cells , consistent with telomere confinement to a randomly-orientated cap , whose opening angle is slightly less than that of a hemisphere ( ∼170° on average ) . Further the average number of telomere clusters is 26±1 , again agreeing with the tapetal data ( the error is the standard error in the mean ) . The width of the cluster number histogram , 9 , is similar again to that for tapetal cells . The fact that both tapetal cells ( with and without Ph1 ) and Ph1+ meiocytes share the same telomere cluster distribution , both in terms of number and position , buttresses our hypothesis that Ph1− telomeres also start in the same configuration . In contrast , Ph1− meiocytes do exhibit intricate bouquet-forming telomere dynamics . This is seen in the histogram of the number of telomere clusters ( Figure 5 ) , which now has a second peak at the origin , representing nuclei that are close to completing bouquet formation , with only a few remaining clusters . Although the dynamics of bouquet formation is clearly visible in the histogram for small numbers of clusters , the large peak around 28 clusters seen in Ph1+ meiocytes and tapetal cells ( in both Ph1+ and Ph1− ) is still visible , supporting the idea that telomere clusters in Ph1− meiocytes also start in the same configuration . We believe the presence of two peaks is due to our imaging dataset capturing not only the dynamic formation of the bouquet , but also the period before bouquet-formation onset , when the telomere clusters are arranged in their initial configuration . This leads to the superposition of the initial telomere cluster distribution and the bouquet dynamics distribution ( as seen in Figure 5 ) . It is an interesting question as to how multicellular organisms coordinate meiosis amongst their constituent cells . In wheat , for example , meiosis within different meiocytes could be coordinated at various levels , including that of single meiocytes , locules , anthers , florets or even spikelets ( see Figure 1A ) . Our Ph1− meiocyte data originates from anthers within 12 separate florets and so we were also able to study whether individual florets showed synchrony in the time that bouquet formation started , i . e . whether all meiocytes in a given floret begin to form the bouquet at the same time . In fact it may be that the synchrony is not within florets , but at a lower level , say within anthers . However , since our dataset is only split into florets , we can only test synchrony within florets . To investigate this question we split our data into separate florets and considered the cluster number distribution for each . If florets are synchronous then we would expect a tighter distribution , i . e . smaller variance , for individual florets compared to that for all the florets combined . We found the mean variance in the number of clusters for individual florets was only 66±18 ( this error is the standard error in the mean variance ) , compared to 160 for the whole data set ( see Supporting Information ) . To test whether this was significant we repeatedly randomly partitioned the complete dataset into 12 appropriately-sized sub-datasets , finding that the mean variance followed a distribution with mean 160 and standard deviation 18 ( see Supporting Information ) . Since a mean variance of 66 is far from the randomly-partitioned mean variance of 160 , we conclude that individual florets do indeed show synchrony , with meiocytes within many florets starting bouquet formation at similar times . However , it is worth noting that the distribution of the variances in cluster number for individual florets , with mean 66 , has a relatively large standard deviation of 61 , which suggests that , although many florets show synchrony , this may not be true of all florets . This may be because the synchrony is not within florets , but within anthers . It would be interesting to test whether synchrony is only at the anther level by studying images from individual anthers . To understand better the mechanics of telomere bouquet formation , we constructed a mathematical model incorporating the dynamics of telomere clusters moving along the nuclear membrane . We then used the model to simulate bouquet formation . To do this we idealised the nuclear membrane as a sphere of radius R , with each telomere cluster represented by a position on the surface of the sphere . Although nuclei are never exactly spherical , they are frequently close to this ideal ( with the centre-to-edge distance , on average , varying by only about 10% ) and so we do not expect a spherical approximation to substantially affect our results . First , we considered a pure diffusional model , with no drift . Although this can lead to bouquet formation in the correct total time it is unable to capture only an 8% variation in this time . In fact , with D = 0 . 025 µm2 s−1 , we found Tbouq = 6 . 6±2 . 6 hr , with an approximately 40% variation . Further , such a model cannot capture the cluster number histogram shown in Figure 5 , since the minimum around N = 12–16 is too pronounced . Thus a pure diffusion model is unlikely , which agrees with the same conclusion in [14] . Next we considered a pure drift model , without any diffusion . In [14] this was excluded since it could not match the observed variation in Tbouq , producing far too small a variation . However , our initial conditions are different: our telomeres are initially contained in a randomly-orientated cap , rather than in an outwardly-pointing hemisphere as in [14] . This makes a crucial difference since now the dominant source of variation in Tbouq is due to the initial cap orientation . With v = 8 . 5×10−4 µms−1 we found that Tbouq = 5 . 6±1 . 0 hr . This is in good , although not perfect , agreement with the observed value in [14] ( although we note that the standard deviation in [14] is for rye and is based on only four measurements ) . Thus , by appreciating that the initial cap containing the telomeres is not necessarily on the outside of the anther , a pure drift model can explain the data . Figures 6A and 6B shows examples of the evolution of dmax and dout for the pure drift model . Further , the pure drift model appears to match well with the cluster number histogram ( Figure 5 ) . To test this more rigorously we performed a chi-squared goodness of fit test , which gave a test statistic of 2 . 1 , a value that is well below that required to doubt the model at the 5% confidence limit ( which is 9 . 5 ) . Thus there is no reason to reject the null hypothesis that our experimental data is well-described by our pure drift model . See Supporting Information for more details . This good match between model and data would not have been the case if the telomere clusters had started in the outside hemisphere rather than a randomly-orientated cap . In this latter case ( as in the experimentally measured data ) the histogram contains an extra peak at small numbers of clusters that is caused by the few telomere clusters that start on the side of the nucleus opposite to the bouquet and take a relatively long time to move towards the bouquet site . It is these final few telomere clusters that are the last to join the bouquet and , since they are few in number ( due to the decreasing area near the poles ) , there are relatively long gaps between the final few telomere clusters joining the bouquet , leading to the extra peak for small cluster numbers . We also considered the behaviour of dmax and dout as a function of the number of telomere clusters for Ph1− meiocytes . Despite the noise in the data , the pure drift model still captures the overall telomere dynamics ( Figures 6C and 6D ) . Another way of quantifying telomere dynamics is via the average telomere cluster distance , dpairs , which is defined as the mean distance between all pairs of telomere clusters ( without intensity-weighting ) . As the bouquet forms and all telomeres approach a point close to the outside pole , this distance tends to zero . If we plot dpairs as a function of time for our pure drift model we find two categories of behaviour ( Figure S5 ) . Firstly , for cases where the initial cap is mostly facing the outside of the nucleus ( nearest where the bouquet forms ) , dpairs is monotonically decreasing . Secondly , however , there are cases where the initial cap is partially facing inwards , where we find that dpairs initially rises before eventually dropping to zero . This initial rise is due to telomere clusters that start near the inside pole of the nucleus and must first diverge from each other as they proceed through the equator , until they form the bouquet near the outside pole . When we average over all initial cap orientations we find , after the initial period of T0 , a slight rise in dpairs , followed by a relatively gentle decrease , before dpairs finally drops to zero ( Figure S5 ) . This effect was also noted in [14] , where its origin was mysterious , and was suggested to be due to a short period between relaxation of the Rabl configuration and directed movement towards the bouquet site , when telomere clusters were able to diffuse freely . Our model , however , provides a natural explanation for this behaviour without the need to postulate an extra period of free diffusion before bouquet formation starts . As we have seen , a pure directed movement model can fit our data , and hence there is no necessity for diffusive motion . The effect of adding such diffusion is to increase the peak at small cluster numbers ( since the final few telomere clusters take a relatively long time to find the bouquet due to partially random rather than directed movement ) . This effect can be compensated for by increasing the waiting time , T0 , although then the trough at N = 12–16 is more pronounced . Small amounts of diffusion still match the experimental data and so cannot be excluded . However , the important point is that diffusion is not required in our model to fit our data and since , as we discuss below , global diffusion may be negligible , we predict that pure drift is the relevant mechanism in our system . In the simplest version of the model , telomere clusters move with constant drift speed directly towards the bouquet site . Although we do not know which component of the cytoskeleton is responsible for causing this drift , such a model would require a perfectly ordered cytoskeleton , with all cytoskeletal elements near the nucleus pointing directly towards the bouquet site . Although there is some evidence that microtubules in plants lie tangential to the nucleus during prophase [22] , it is not clear to what extent there is variation within this arrangement . In fact , in rye there is evidence that , during bouquet formation , there is significant disorder to the microtubules near the edge of the nucleus [23] , with perhaps only the overall average direction pointing towards the bouquet site . To model this , we introduce a random element to the drift direction in the model . Unless the drift direction varies enormously , we emphasise that this is not the same as simply adding diffusion since telomeres still almost always head roughly towards the bouquet site . Rather this situation is more like constant drift directed towards the bouquet site , with a small amount of transverse diffusion . Telomere clusters are assumed to drift in some direction ( not necessarily directly towards the bouquet site ) for some distance , LR , called the run length . Without knowing the details of the cytoskeletal elements involved in telomere movement , it is difficult to estimate the run length . However , motivated by studies of kinesin [24] , we use LR = 1 µm . The drift direction , ψ , is chosen ( independently for each telomere cluster ) from a truncated normal distribution , with mean centred on the direction towards the bouquet site and with standard deviation , δψ . After a telomere cluster has moved the run length in this drift direction , a new independent drift direction is chosen . The standard deviation of the drift direction , δψ , is thus a measure of the directionality of the cytoskeleton . See Supporting Information for more details . It is worth noting that , even with a random element to the drift direction , a randomly-orientated initial cap is still required to produce a good match with the experimental cluster number histogram . To fit with the experimental data it is necessary , for each value of δψ , to refit both the drift speed , v , and the waiting time , T0 . After doing this it is notable that a non-zero variation in the drift direction can produce a slightly better match with the experimental cluster number histogram ( Figure 5 ) . To quantify this , we use the chi-squared test-statistic as a measure of the goodness-of-fit . As δψ increases from zero the value of the statistic decreases , reaching a minimum of 1 . 6 at around δψ = 40° , with similar results obtained if the run length is reduced to LR = 0 . 5 µm . So although we do not know the relevant run length for telomere movement , for reasonable values we predict that even a relatively large variation in the cytoskeletal directionality does not seem to interfere with bouquet formation .
The arrangement of chromosomes within the nucleus is far from random , with radically different arrangements required during interphase , mitosis and meiosis . Even during interphase there is significant chromosomal order , with ribosomal DNA localising to the nucleolus , actively transcribed genes often present in transcription factories , and discrete chromosome territories for individual chromosomes . Further , during mitosis sister chromatids must be segregated , which involves kinetochores forming at the centromeres and being pulled apart by microtubules to opposite ends of the cell . A different arrangement again is required during meiosis , with telomeres often grouped together on the nuclear membrane and homologous chromosomes forming bound pairs , often accompanied by complex motions of the entire chromatin [9] . Although the process of chromosome segregation during mitosis is well-studied , much less is known about how the telomere bouquet forms during meiosis . In fact the bouquet itself is not a universal feature in all organisms . For example , Arabidopsis thaliana lacks a bouquet , with the telomeres instead associating with the nucleolus [25] . Further , some organisms do not even use the telomeres to facilitate pairing . C . elegans , for example , attaches special pairing centres to the nuclear membrane rather than telomeres [26] . In fact , organisms seem to display substantial variation in exactly how chromosomes are organised during meiosis . Despite this variation , in general terms , almost all organisms associate specific regions of the chromosomes ( telomeres or pairing centres ) to some relatively small region of the nucleus ( nuclear envelope or nucleolus ) and often use cytoskeletal elements to move chromosomes around this region , sometimes gathering all telomeres in an even smaller bouquet region . Again , there is variation as to which component of the cytoskeleton is used , with animals and fission yeast tending to use microtubules and budding yeast instead employing actin . For example , it seems that dynein motors are used by C . elegans to move the pairing centres along microtubules [27] , [28] . From a meiotic viewpoint , wheat is in many ways an extreme case . Partly due to being hexaploid and partly due to many repetitive DNA elements , the wheat genome is over a thousand times larger than that of yeast . Necessarily this then implies a large nucleus and in fact the wheat nucleus has several hundred times the volume of a typical yeast nucleus . Thus with very large ( and hence potentially slow moving ) chromosomes needing to search relatively large nuclei to find their homologous partner , the problem of homologous pairing is much more pronounced in wheat than in many other organisms . Further , the problem of partner identification is compounded by the presence of related but non-homologous ( i . e . homeologous ) chromosomes and large amounts of repeated DNA . So perhaps it is not surprising that , as meiosis progresses and the telomere bouquet is almost formed , centromeres in wheat associate into homeologous clusters , such that seven centromere groups can be seen per nucleus [15] . This centromere clustering , which is in addition to the telomere clustering modelled in this paper , is another level of chromosome organisation that wheat employs , perhaps to overcome problems related to the large chromosome and nuclear size . In addition to this grouping of centromeres shortly before bouquet formation is complete , we have shown that even prior to the initiation of bouquet formation , after telomeres have moved to the nuclear envelope , wheat also groups sister chromatid telomeres together . Interestingly , this occurs not only in meiocytes , but also in tapetal cells , which at no point undergo meiosis . Unlike centromere clusters , where each of the seven centromere groups is likely to be composed of six homeologous chromosomes , sister chromatid telomeres tend to cluster , on average , in pairs , so that each cluster contains , on average , four telomeres . Such initial telomere association has also been observed in other organisms , such as rye [14] and a maize mutant [29] . Since wheat-rye contains only homeologous rather than homologous chromosomes , the sister chromatid telomeres cannot be homologous pairs . Given this , it would be interesting to determine whether the association is between sister chromatid telomeres at opposite ends of a chromatid pair , between homeologous chromosomes or whether any set of sister chromatid telomeres can cluster together . Once on the membrane , the telomere clusters move together to form the bouquet . Interestingly , this bouquet normally forms at the pole of the nucleus furthest from the centre of the anther . A similar result was found in rye [23] . Pure diffusion is not sufficient to explain the variation in the bouquet formation time and our model confirms that directed movement is also required , agreeing with the result in [14] . As such we predict that there must be significant organisation to the cytoskeleton ( or some other similar structure ) , forming a directed network along which telomeres can move towards the bouquet patch . Since no SUN/KASH proteins linking telomeres through the nuclear membrane have yet been discovered in wheat , it is unclear which structural elements are involved . Possibilities include microtubules ( as in animals ) , actin ( as in S . cerevisiae ) , nuclear envelope structural proteins ( similar to the nuclear lamins in animals ) , or perhaps even the controversial idea of a nuclear matrix . Potentially relevant is the fact that the process in rye has been shown not to involve microtubules [30] . Although a mixture of diffusion and directed movement can form the bouquet , we have shown that diffusion is not required . Our data can be explained by a pure drift model , with telomere clusters moving directly towards the bouquet site near the outside pole . Although there must always be some diffusion , we believe that such diffusion is unlikely to play any significant role in forming the bouquet . This is because chromosomes are effectively confined to small regions potentially due to the barriers formed by other chromosomes . Chromosomes do diffuse , but only within these small regions [31] , such that diffusion is unlikely to be relevant in moving telomere clusters all the way to the bouquet site . For example , during interphase in S . cerevisiae it has been shown that chromosomes freely diffuse , but only within a region of radius 0 . 3 µm , which is considerably smaller than the radius of the yeast nucleus [32] . Similarly , results in Drosophila suggest that chromosome regions are confined within a 0 . 5 µm radius [33] . Thus any diffusional component may well be irrelevant , further supporting our pure drift model . Although we favour a pure drift model , this does not imply that the telomeres need always drift directly towards the bouquet site . In fact , a model where the drift direction varies , with a relatively large standard deviation of around 40° fits the data slightly better . This model is similar to one with constant drift towards the site of bouquet formation together with transverse diffusion ( as distinct from diffusion in any direction discussed above ) . Interestingly , this version of the model predicts that bouquet formation dynamics is robust to significant cytoskeletal disorder . This issue could potentially be investigated in the future by imaging the relevant cytoskeletal component ( s ) . The Ph1 locus seems to have evolved in wheat in order to ensure that only homologous chromosomes pair during meiosis . Since wheat originated from the hybridisation of three related diploid species , each chromosome occurs in six similar copies , and so pairing must be carefully controlled to restrict the formation of homeologous pairs . If the Ph1 locus is deleted then both homologous and homeologous pairs form , which eventually leads to infertility . Our analysis has shown that Ph1− mutants complete telomere bouquet formation at earlier times . Reduced Cdk2 activity during mammalian meiosis affects telomere behaviour and their attachment to the nuclear membrane [34] . The presence of the Ph1 locus has recently been shown to reduce Cdk2-type activity in wheat-rye hybrids [16] . Thus the modified telomere behaviour with and without Ph1 observed here is entirely consistent with altered Cdk2-type activity . Formation of the telomere bouquet is an important step during meiosis in many organisms [2] , [35] and the relative roles played by drift and diffusion in this process is an important question . We have shown that the arrangement of telomere clusters prior to bouquet formation is of vital importance for understanding later telomere dynamics , with telomere clusters initially positioned in a randomly-orientated cap whose size is slightly smaller than that of a hemisphere . We have argued that a pure drift model , which is probably the simplest possible mechanism , may well be the most appropriate . This is distinct from previous models where a diffusional component was required . Although our results were obtained in a wheat-rye hybrid , the confined nature of diffusion suggests that similar mechanisms may be used in many organisms , and it is quite possible that the formation of most telomere bouquets is best understood as due to purely directed movement .
The plants used came from crosses between rye ( Secale cereale cv . Petkus ) and hexaploid wheat ( Triticum aestivum cv . Chinese Spring ) . Two crosses were used: one from wild-type wheat and one with the wheat lacking the Ph1 locus [36] . Seeds from both genotypes were germinated on petri dishes for 3–4 days . The seedlings were vernalized for 3 weeks at 4°C and then transferred to a controlled environmental room with the following growth conditions: 16 hours at 20°C ( day ) and 8 hours at 15°C ( night ) with 85% humidity . Plants were collected after 6–7 weeks . EdU treatment was carried out as described previously [16] . Briefly , tillers containing immature pre-meiotic spikes were detached after an 8 hr period in the dark and immediately transferred to a solution of 100 mM sucrose and 1 mM EdU ( Invitrogen: A10044 ) . The cut tillers in individual tubes were left in the light for four hours , after which the spike was dissected out and fixed in 4% formaldehyde solution , freshly made from paraformaldehyde [37] . The fixed samples were placed in biopsy cassettes and embedded in wax using a Tissue-tek vacuum infiltrator processor ( VIP ) machine [38] . They were then sectioned using a microtome [25] to produce sections of 10 µm thickness . EdU detection was carried out using a Click-iT EdU Alexa Fluor 488 Imaging Kit , according to the manufacturer's instructions ( Invitrogen: C10337 ) . Fluorescence in situ hybridization was carried out as previously described [39] . Telomeric probes were labelled with biotin-16-dUTP by nick translation of PCR-amplified products using the oligomer primers ( 5′-TTTAGGG-3′ ) 5 and ( 5′-CCCTAAA-3′ ) 5 in the absence of template DNA [40] , and detected using streptavidin-Cy3 conjugate . Chromosomes were counterstained with DAPI ( 4′ , 6-diamidino-2-phenylindole ) and mounted in Vectashield ( H-1000 ) medium . To carry out dual labelling with both EdU and telomere probes , samples ( sections ) were first digested in 2% cellulose , 2% pectolyase in 1×TBS for 3 hours at 37°C . Then , the telomere probe was hybridised to the sample , incubated overnight at 37°C and washed according to the usual protocol [39] . Samples were then blocked in 3% BSA and followed by the EdU detection protocol . Before staining with DAPI , samples were incubated with the required antibodies for the telomere probe , and then finally mounted in Vectashield . Images were acquired with a Nikon Eclipse E600 epifluorescence microscope equipped with a Hamamatsu Orca-ER cooled CCD camera and a Prior Proscan x , y , z stage . Stack images of individual cells were collected by using MetaMorph ( Universal Imaging ) software . Deconvolutions of images were processed with AutoDeblur ( AutoQuant Imaging ) . Projections of 3D pictures were performed with ImageJ . These images were also used in [16] to study the possible Cdk2-type activity of the Ph1 locus . However , the work described here is the first detailed analysis of this data , where the actual telomere cluster positions are determined and analysed . From each DAPI image we first identified the nucleus by generating ellipses that fit around the DAPI stain . Then , from the equivalent telomere FISH image , we identified telomeres within the nucleus by searching for discrete pixels with an elevated FISH signal . Pixels were only counted as part of a telomere if their intensity was greater than some threshold , which , for each image , was chosen as 0 . 12 of the maximum pixel intensity . This value was chosen since it gave consistently-sized clusters: larger values missed some telomere clusters and smaller values sometimes led to large regions being incorrectly identified as a single cluster . After imposing the threshold , clusters were defined such that adjacent pixels ( including diagonally adjacent ) were considered part of the same cluster . In order to remove spurious background signals , clusters were only counted if their total intensity was greater than 2 ( where each pixel had a maximum intensity of 1 ) . We tried various other values for the minimum total intensity , although this did not affect our results . See Supporting Information for more details . | The appearance of sexual reproduction over a billion years ago led to a revolution in how organisms pass on genetic material to their offspring . In sexually reproducing organisms parental diploid cells , containing two nearly identical copies of each chromosome ( homologues ) , produce gametes containing only one copy of each chromosome . This in turn requires the pairing of the related homologous chromosomes to ensure their subsequent segregation into the gametes . How this pairing is achieved is poorly understood since chromosomes must search the entire nucleus for their homologous partner . Many organisms move the ends of each chromosome ( the telomeres ) along the periphery of the nucleus into a small patch forming the telomere bouquet . We show here that direct movement of telomeres towards the bouquet site , potentially driven by molecular motors , can explain bouquet formation dynamics . We focus in particular on a wheat-rye hybrid since understanding homologous pairing in wheat could have profound implications for breeding resistant crops by aiding the production of hybrids . We also show that wheat seems to have evolved a mechanism to delay the onset of telomere bouquet formation , perhaps in order to ensure chromosomes find their correct homologous partners . | [
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"computa... | 2012 | Quantitative Dynamics of Telomere Bouquet Formation |
Accumulating evidences have assigned a central role to parasite-derived proteins in immunomodulation . Here , we report on the proteomic identification and characterization of immunomodulatory excretory-secretory ( ES ) products from the metacestode larva ( tetrathyridium ) of the tapeworm Mesocestoides corti ( syn . M . vogae ) . We demonstrate that ES products but not larval homogenates inhibit the stimuli-driven release of the pro-inflammatory , Th1-inducing cytokine IL-12p70 by murine bone marrow-derived dendritic cells ( BMDCs ) . Within the ES fraction , we biochemically narrowed down the immunosuppressive activity to glycoproteins since active components were lipid-free , but sensitive to heat- and carbohydrate-treatment . Finally , using bioassay-guided chromatographic analyses assisted by comparative proteomics of active and inactive fractions of the ES products , we defined a comprehensive list of candidate proteins released by M . corti tetrathyridia as potential suppressors of DC functions . Our study provides a comprehensive library of somatic and ES products and highlight some candidate parasite factors that might drive the subversion of DC functions to facilitate the persistence of M . corti tetrathyridia in their hosts .
Cestodes in general and the metacestode larval stages in particular are of major etiological importance for both human and domestic animal diseases . Currently available therapies against the deadliest metacestode-mediated diseases are still limited . Major life-threatening human cestodes such as T . solium , E . granulosus and E . multilocularis cause serious diseases due to the unique ability of their metacestode larvae to persist within the host tissues for decades , gradually impairing the function of the colonized organ [1 , 2] . Metacestodes dwell in the host tissues where they confront the immune system and modulate the immune response to enable their survival and the establishment of a chronic infection [3] . Therefore , severe pathology in mammalian hosts occurs late after long asymptomatic or subclinical infection periods , with little inflammatory responses or overt tissue destruction [1 , 2] . Cestodes , as most of the helminths , induce modified T-helper ( Th ) 2 immune responses that are accompanied by various immunoregulatory mechanisms to control excessive Th1 immunity that would prevent parasite colonization [2– 6] . The major factor instructing Th1 cell generation is the cytokine IL-12p70 released by dendritic cells ( DCs ) [4] . Thus , for tissue-dwelling metacestodes , interference with IL-12 production by DC is critical for limiting pro-inflammatory Th1 immunity and allowing parasite persistence [2 , 5–10] . However , how metacestodes modulate DC functions is largely unclear [2] . Excretory-secretory ( ES ) products of metacestodes are instrumental in the mitigation of IL-12 production by host DCs [2 , 11] . As such , metacestode ES products are attractive targets to understand the mechanisms governing host-parasite interactions since these products directly interact with host immune cells where they drive immunoregulation [2 , 7 , 9 , 11–14] . Proteomic analytical tools including mass spectrometry have helped the identification of ES products from in vitro cultures of parasitic helminths and led to the identification of candidate host protective antigens and immunomodulators alike [15–21] . As for the disease-mediating larvae of parasitic cestodes i . e . metacestodes , a major drawback was the dependency of all established culture systems on supplements from mammalian hosts [22] making it difficult to perform downstream proteomic analyses on metacestode culture supernatants . We recently developed an in vitro cultivation system for metacestodes ( tetrathyridia ) of the parasitic cestode Mesocestoides corti [22] . Our cultivation system enabled the collection of M . corti tetrathyridia ES products in medium devoid of host cells and other supplements such as serum [22] . Although axenic ES products of M . corti tetrathyridia isolated from our cultivation system sufficiently recapitulated M . corti tetrathyridia ability to suppress LPS-driven IL-12 production by DC in vitro [22] , the molecular bases of DC suppression by ES products of M . corti tetrathyridia in particular and metacestodes in general still remains unknown . In this study , we took advantage of our M . corti tetrathyridia cultivation system to characterize the DC suppressing effect of M . corti tetrathyridia ES products ( McES ) . In vitro exposure of BMDCs to McES impaired their subsequent responsiveness to other pathogen products including ligands for TLRs and C-type lectins . The production of IL-12p70 from LPS-activated BMDCs was significantly reduced upon exposure to McES whereas exposure to M . corti tetrathyridia homogenates ( McH ) could not impair BMDC activation . Biochemical analyses of M . corti tetrathyridia ES products ( McES ) narrowed down the immunosuppressive activity to glycoproteins . Further analyzing McES by bioassay-guided fractionation assisted with liquid chromatography-mass spectrometry , we identified a set of candidate proteins that might mediate M . corti tetrathyridia suppression of DCs . Once functionally tested , this comprehensive library of metacestode-derived candidate immunomodulatory proteins should improve our understanding of how tissue-dwelling metacestodes subvert the host DC response .
Having previously shown that M . corti impairs DC responsiveness to stimuli [22] , we now sought to ascertain the in vivo relevance of DCs in the host response to M . corti tetrathyridia . To address this , we injected either live , heat-killed M . corti tetrathyridia or the PBS carrier solution ( mock , negative control ) into the peritoneum of BALB/c mice ( Fig 1A ) and analyzed the frequency of host CD11c+ cells within the total peritoneal exudate cells ( Fig 1B ) . We found that viable tetrathyridia significantly recruited cells within the peritoneum at day 7 p . i . when compared to dead tetrathyridia or to the mock control ( 3-fold more than the dead larvae and 15-fold more than the mock injections ) ( Fig 1C ) . Further analyses showed that live M . corti tetrathyridia recruited growing proportion of CD11c+ ( 12% of the peritoneal exudate cells at day 3 p . i . and 27% at day 7 p . i . ) ( Fig 1D and 1E ) . In contrast , cells recruited less efficiently by heat-killed M . corti tetrathyridia harbored fewer CD11c+ host cells over time ( 10% of the peritoneal exudate cells at day 3 p . i . and 4% at day 7 p . i . ) ( Fig 1D and 1E ) . These results indicate that only live M . corti tetrathyridia massively attracted host CD11c+ cells up to day 7 post-infection whereas dead ( ametabolic ) larvae recruited CD11c+ cells just for the 3 days that followed injection . Given the ability of live helminths to excrete-secrete molecules which directly interact with host immune cells [11 , 23] and considering the reported predominance of dendritic cells within murine peritoneal CD11c+ cells , our data suggest a central role for ES products of M . corti ( McES ) in the modulation of host DC responses in vivo . To characterize the mechanisms of DC modulation by McES , BMDCs were exposed to a wide range of McES concentrations ( 0 . 5–50μg/ml ) for 24h before subsequent stimulation with LPS for another 24h . After incubation , the culture supernatants were harvested and IL-12p70 production was measured by ELISA . As shown in Fig 2A , we found that all tested McES concentrations significantly inhibited LPS-driven release of IL-12p70 by BMDCs in a dose-dependent manner . To rule out the possibility that McES bind to TLR-4 receptors to prevent the subsequent binding of LPS by steric hindrance , we assessed how the timing of exposure of host DCs to McES might influence the inhibitory effect on IL-12p70 production . In a first series of experiments , we simultaneously stimulated BMDCs with McES and LPS for 24h in vitro and measure the levels of LPS-driven IL-12p70 production . We noted that LPS-driven IL-12p70 production by BMDCs was significantly reduced in culture concomitantly supplemented with McES plus LPS ( Fig 2B ) . In a second series of experiments , BMDCs were first activated with LPS for 24h and different doses of McES were then added to the activated BMDCs cultures for another 24h . We noted a significant and dose-dependent ability of McES to neutralize IL-12p70 release by LPS-activated BMDCs ( Fig 2C ) . Fig 2D shows that BMDC upregulation of surface activation markers ( MHCII and CD86 ) in response to LPS treatment was not affected by McES . To rule out any cytotoxic effect as a result of dual stimulation [24] , BMDCs dually stimulated with different doses of McES and LPS were analyzed by Annexin-V/Propidium Iodide dual staining to identify viable cells with uncompromised cell membranes ( Annexin-V-/Propidium Iodide- ) . BMDCs dually exposed to McES and LPS did not show any reduction in cell viability ( Fig 2E ) ruling out cell death as a possible cause of the reduced IL-12p70 production by BMDCs . These results demonstrated that McES limited LPS-driven BMDC activation independently of the time of exposure and also diminished the effector response ( IL-12p70 production ) of LPS-activated BMDCs in vitro . Conclusively , these findings indicate that McES suppressive effect is not merely a result of steric hindrance of the TLR-4 receptor on DCs . We extended our studies by investigating the effect of McES on BMDC ability to respond to other activation stimuli i . e . Staphylococcus aureus lipoteichoic acid ( LTA ) , a TLR-2 agonist; Alcaligenes faecalis Beta-1 , 3-glucan ( Curdlan ) , a Dectin-1 agonist; Saccharomyces cerevisiae cell wall extract ( Zymosan A ) , a dual TLR-2 and dectin-1 agonist and phorbol 12-myristate 13-acetate ( PMA ) , an activator of protein kinase C and NF-κB by measuring the release of IL-12p70 , IL-10 , IL-6 and IL-23 into the culture supernatants . Since activation of immature DCs via different routes leads to distinct cytokine profiles [25 , 26] , we used the cytokine ( s ) most abundantly produced by each stimulus to better capture the possible suppressive effect of McES . As shown in Fig 3 , pre-exposure of BMDCs to McES significantly reduced LTA-driven IL-12p70 release ( Fig 3A ) , curdlan-driven IL-6 and IL-10 secretions ( Fig 3B ) , PMA-driven IL-10 secretion ( Fig 3C ) and zymosan-driven IL-12p70 , IL-6 , IL-23 and IL-10 secretions ( Fig 3D ) . These results indicated that McES broadly impair BMDCs activation by various stimulatory ligands . To better understand the molecular nature of the immunomodulatory component within McES mixture , biochemical assays for the selective depletion of major classes of biomolecules were applied . To determine the role of free lipids , we comparatively tested the ability of McES and lipid-free McES or McESΔAS ( i . e . ammonium sulphate precipitated as described in [27 , 28] ) to impair BMDC activation . As shown in Fig 4A , similarly to McES , lipid-free ES significantly diminished the production of LPS-driven IL-12p70 by BMDCs indicating that parasite released lipids are not required for McES-mediated BMDC suppression . Next , we appraised the role of parasite proteins contained in McES by comparative testing of heat-inactivated McES ( hiMcES ) and mock-treated McES ( Mock hiMcES ) . As expected , pre-exposure to Mock hiMcES significantly impaired BMDC ability to release IL-12p70 in response to LPS ( Fig 4B ) . In contrast , hiMcES completely failed to show such an ability ( Fig 4B ) indicating that parasite proteins are important for McES-driven BMDC suppression . To determine the role of parasite-derived carbohydrates in the ability of McES to impair BMDC activation , we cleaved carbon bonds that bear hydroxyl groups using metaperiodate yielding carbohydrate-free McES ( McESΔCHO ) or performed a mock cleavage of McES using buffer without addition of metaperiodate ( Mock ΔCHO ) . Predictably , Mock McESΔCHO impaired LPS-driven IL-12p70 release by BMDCs whereas McESΔCHO failed to show such an effect ( Fig 4B ) . These results indicated that parasite carbohydrates are important for the suppressive effect of McES . Together , these findings demonstrated that both parasite proteins and carbohydrates are necessary for the immunosuppressive effect of McES . Whether McES-driven immunosuppression requires a concerted action of a separate protein and carbohydrate entity or whether single or multiple entities combining carbohydrate and protein parts are responsible for the observed McES potency to suppress DC function remained unclear . To address this , we combined protein-depleted with carbohydrate-depleted McES and tested for their ability to impair LPS-driven BMDCs activation . As shown in Fig 4B , the mixture of protein-depleted McES ( hiMcES ) and carbohydrate-depleted McES ( McESΔCHO ) failed to inhibit LPS-driven IL-12p70 production by BMDCs whereas the mixture of mock controls ( mock hiMcES and mock McESΔCHO ) mediated this suppressive effect . These results indicated that one or several intact parasite glycoproteins , but not separate protein and carbohydrate entities , mediate ( s ) DC suppression by McES . To identify the distribution of the DC-suppressing protein ( s ) in M . corti tetrathyridia products , we comparatively evaluated the ability of M . corti homogenates ( McH ) and McES to impair LPS-driven IL-12p70 production by BMDCs ( Fig 5 ) . As expected , as little as 5 μg/ml of McES reduced LPS-driven IL-12p70 production by 50% in BMDC cultures whereas a similar amount of McH failed to show any suppressive effect on LPS-driven IL-12p70 release by BMDCs ( Fig 5 ) . Our data therefore suggested that the DC-suppressing glycoprotein ( s ) from M . corti tetrathyridia is/are specifically secreted by the larva and not that somatic products were leaking from the larval soma . We next reasoned that the differential suppressive activity of McES when compared to McH might be the result of a differential expression of the immunomodulatory glycoprotein ( s ) in both parasite preparations . We therefore examined proteins differentially expressed between McH and McES to identify candidate DC suppressors . To this end , a 1D SDS-PAGE with three different batches of McH and McES was performed and proteins revealed by silver staining ( Fig 6A ) . Visual inspection of the gels showed a general consistency in the protein composition and concentration across batches of each set of parasite products , although minor differences were evident ( Fig 6A ) . Even though shared protein bands between McH and McES were visible , differentially represented protein bands were detected ( Fig 6A ) . All protein bands were excised and processed for LC-MS/MS analysis to complement the visual comparison of McH and McES proteomes ( S1–S3 Tables ) . We identified 115 M . corti proteins in McH and 55 M . corti proteins in McES ( Fig 6B; S1–S3 Tables ) thereby greatly extending the database of cestode proteomes beyond previously available information [18] . Of the 55 identified McES proteins , 27 ( 49% ) were also detected in McH ( Fig 6B , S3 Table ) leaving 28 ( 51% ) of the identified proteins exclusive to McES ( Fig 6B , S1 Table ) . Notably , 88 ( 76 . 5% ) of the 115 proteins identified in the McH were found to be exclusive to the parasite homogenates ( Fig 6B , S2 Table ) . These results show that McES is markedly less complex than McH ( in excess of 60 proteins ) consistent with the observation that M . corti tetrathyridia differentially secrete a defined set of proteins ( Fig 6B ) . Among the 55 McES proteins identified were a selection of enzymes ( i . e . proteases , phosphatases , enolases , lipases , aldolases , hydroxylases , fucosidases , isomerases , hydrolases , dehydrogenases and kinases ) , ion-binding proteins , protein transporters , fatty acid-binding proteins , conserved structural proteins ( actins , heat shock protein , collagen and actin-binding proteins ) and conserved regulatory proteins ( ubiquitins , 14-3-3 proteins and endophilins ) . Protease inhibitors ( cystatins , serpins ) and annexins were also detected as were a high number of proteins with unknown functions with homologues in other cestodes ( conserved cestode proteins ) and novel proteins as yet unidentified in other helminths ( S1 and S3 Tables ) . All McES proteins were functionally annotated according to the Gene Ontology Consortium ( http://geneontology . org/ ) . GO terms analysis was performed to identify terms that were represented in the McES ( S1 Fig ) . GO terms were assigned to the identified proteins on the basis of similarity using Blast2GO . In this analysis , ≥1 GO terms were assigned for 41 protein sequences ( 74 . 5% ) of the total of McES product set . In total , 70 GO terms were returned ( S1 Fig ) . These encompassed the three organizing categories of the GO database: biological process , molecular function and cellular component ( S1 Fig ) . Only 12 cellular component ontologies were returned ranging from intracellular , membrane components to extracellular terms ( S1 Fig ) . There were 40 biological process terms represented predominantly by terms for metabolic process , single organism process and cellular process ( S1 Fig ) . There was an intermediate number of molecular function terms returned ( 18 ) , representing a variety of terms with the most returned terms being ion binding , protein binding and hydrolase activity , respectively ( S1 Fig ) . Of the 55 proteins identified in the McES , 15 ( 27% ) contained a predicted N-terminal signal peptide ( S2 Fig ) . Nine ( 60% ) of these classically secreted proteins did not correspond to any annotated gene in the NCBI database , and of these 5 ( 33% of classically secreted proteins ) were novel proteins with no database match other than that of M . corti predicted genes ( http://www . sanger . ac . uk/resources/downloads/helminths/; 01/29/2015 version ) . Of the identified 15 classically secreted proteins , 4 ( 27% of classically secreted proteins ) matched predicted or hypothetical proteins of unknown function from other parasitic cestodes ( S2 Fig ) . These results further illustrate the presence of a novel set of secreted proteins in McES . We also compared the relative abundance of proteins in McES and McH by their NSAF values ( normalized spectral abundance factors , [29] ) . We were able to infer that the relative concentration of a number of proteins differed substantially between McES and McH ( S1–S3 Tables ) . To narrow down the database of most likely immunomodulatory proteins within McES , we searched for proteins with exclusive to over-representation in the immunomodulatory McES but absent or present in poorly detectable levels in the non-active McH ( Fig 7 ) . Specifically and by descending order of magnitude , the 5 most represented McES protein entities identified were: a novel hypothetical protein ( MCOS_959401 , exclusively detected in McES ) , an annexin homologue ( Number 1 , MCOS_561301 , exclusively detected in McES ) , a hypothetical protein conserved among parasitic cestodes ( Number 2 , MCOS_155201 , ~3-fold enrichment in McES ) , a cystatin ( MCOS_775601 , exclusively detected in McES ) and an endophilin ( MCOS_968201 , 2 . 4-fold enrichment in McES ) ( S4 Table ) . Column-based chromatographic analyses were used to further isolate the active fractions of McES . First , McES were fractionated by anion-exchange chromatography ( IEX ) , dialyzed against PBS and tested for the immunosuppressive activity of the isolated fractions by IL-12p70 suppression ( Fig 8 ) . This first line of McES fractionation generated 13 detectable protein-containing fractions , as judged by the absorbance at 280nm ( Fig 8A ) . The collected fractions were further dialyzed against PBS to minimize interference from the salty elution buffers on the downstream immunological assays . The protein concentrations in all fractions were determined ( Fig 8B ) tightly aligning to the previously obtained chromatogram ( Fig 8A ) . To assess the immunomodulatory potency , IL-12p70 production by BMDCs pre-exposed to 5 μg/ml of each of the purified fractions before LPS stimulation was measured . As a positive control of DC-suppressing fraction , 5μg/ml of total McES , resuspended in elution buffer and further dialyzed against PBS was used . As expected , exposure of BMDCs to total McES reduced the LPS-driven production of IL-12p70 by close to 50% ( Fig 8C ) . The activity was different across McES fractions . Whereas fractions E1 , E3 , E4 , E5 , E6 and E7 displayed a considerable ability to impair LPS-driven BMDC production of IL-12p70 , fractions E2 , E8 , E9 , E10 , E11 , E12 and E13 failed to do so ( Fig 8C ) . To have a visual appraisal of the protein composition of the various McES fractions , we performed a one-dimensional SDS-PAGE of 11 μg from each fraction ( Fig 8D ) . A complex but rather dissimilar banding pattern was apparent in the major protein-containing fractions of McES . We failed to clearly detect a differential banding pattern between active and non-active fractions as both group of fractions revealed protein bands spanning the entire MW range ( <15 to >130kDa ) . Notably , in the minimally active fraction E1 ( around 12% inhibition ) , only proteins of MW higher than 40kDa were visible . To further characterize the protein entity ( ies ) that mediate the immunosuppressive potential of McES , fractions E4 , E5 , E6 and E7 , representing the most active fractions ( Fig 8C ) with the highest protein content ( Fig 8B ) were pooled and the mixture was subjected to gel filtration chromatography ( GFX , Fig 9 ) . This second line of McES fractionation generated 3 detectable protein-containing peaks as judged by the absorbance at 280 nm ( Fig 9A ) . These peaks were further subdivided under refined elution profile of 40 fractions ( Fig 9A ) to increase the resolution of our analyses . The protein concentration in all fractions was determined ( Fig 9B ) tightly reflecting chromatogram ( Fig 9A ) . To assess the immunomodulatory potency , IL-12p70 production by BMDCs pre-exposed to 5 μg/ml of each of the fractions before LPS stimulation was measured . As a positive control , 5 μg/ml of active McES fractions from IEX were used . As expected , exposure of BMDCs to the pool of active McES fractions after IEX reduced the LPS-driven production of IL-12p70 by close to 75% ( Fig 9C ) . The activity was different across McES fractions after GF revealing A10 , A11 , A12 , A13 , A14 , A15 , B15 , B14 as the most active fractions mediating at least a 50% reduction of LPS-driven IL-12p70 release by BMDCs ( Fig 9C ) . Fractions B11 , B10 , B9 , B8 , B7 , B6 , B5 , B4 , B3 , B2 , B1 , C1 , C2 , C3 , C4 , and C5 were poorly to non-active mediating less than 50% of reduction of LPS-driven IL-12p70 release by BMDCs ( Fig 9C ) . To have a visual appraisal of the protein composition of the various McES fractions , we performed a one-dimensional SDS-PAGE of each fraction ( Fig 9D ) . A clear clustering of the protein banding pattern along three definable MW groups was observed for the major protein-containing fractions ( Fig 9D ) . These groups of proteins were arbitrarily defined as group i ( >130kDa to 25kDa ) , group ii ( 60kDa to 20kDa ) and group iii ( < 20kDa ) . Active fractions were principally found within the MW group ( i ) suggesting that the active principle within McES might be of a MW >20kDa since fractions from group ii and iii showed minimal to no activity ( Fig 9C and 9D ) . Taken together , our bio-activity based fractionation analyses suggest that ( a ) protein ( s ) of MW higher than 20 kDa might mediate the immunosuppressive activity of McES . Having now isolated refined fractions of McES with differential DC-suppressing activity , we reasoned that a comparative proteomic analysis of active and non-active McES fractions could provide us with a list of candidate DC-suppressing proteins preferentially represented in active fractions . To address this , fractions A14 , A15 and B15 as the most active fractions ( Fig 9C ) with highest protein content ( Fig 9D ) and fractions B6 , B7 , B8 and B9 as the non-active fractions ( Fig 9C ) with high protein content ( Fig 9D ) were individually lyophilized and analyzed by mass spectrometry for their protein composition . Overall , 37 different proteins were detected in the analyzed McES fractions ( S5 Table ) . To assess the differential profile of active and non-active fractions of McES , the relative abundance of each protein defined by the NSAF values ( normalized spectral abundance factors , [29] ) , was plotted revealing a mutually exclusive distribution of the majority of proteins to either active or non-active McES fractions ( Fig 10 ) . Close to 77% ( 27/37 ) of all identified proteins were exclusive to the active fractions ( Fig 11 ) of which 40% ( 11/27 ) , not detectable in the parasite somatic extracts , were associable to McES immunomodulatory potential i . e . never detected in non-active parasite products and frequently/always present in active parasite products ( Fig 11 , S6 Table ) . Those are by descending order of representation in M . corti ES products , a hypothetical protein ( number 1 , MCOS_959401 ) , another hypothetical protein ( number 4 , MCOS_110601 ) , an ectonucleotide pyrophosphatase/phosphodiesterase family member 7 ( ENPP7 , MCOS_794301 ) , a ferritin ( MCOS_381601 ) , an alkaline phosphatase ( MCOS_274401 ) , an annexin ( MCOS_561201 ) , a hypothetical protein ( Number 6 , MCOS_428801 ) , another hypothetical protein ( number 5 , MCOS_1039801 ) , an epidermal growth factor ( EGF ) -domain protein homologue ( MCOS_1031401 ) , a calpain ( MCOS_208601 ) and the cestode antigen B ( MCOS_36601 ) .
The infectious cestode larvae intimately dwell within their mammalian host organs , mitigating the host immune response [1–3] . Their longevity in mammalian hosts raises a growing interest in the molecular basis of host immunomodulation by these parasitic larvae [30] . Generally , immunosuppression by helminths results from prior interaction with innate immune cells–such as DCs–and relies on viable parasites and their released products [13 , 31] . However , much on the mechanisms of host immunomodulation by released products of cestode larvae remains to be elucidated . In the current study , we have characterized the immunomodulatory potential of ES products from the tissue-dwelling metacestode larva of M . corti at the level of IL-12p70 production by BMDCs . Our results show that secreted glycoproteins from M . corti tetrathyridia impaired the IL-12p70 secretion of BMDCs in response to a wide-range of pro-inflammatory or microbial stimuli . We performed an extensive proteomic analysis of these products and provided a comprehensive library of M . corti tetrathyridium-derived proteins that might suppress DC functions . DCs play a sentinel role in the sensing and recognition of invading pathogens [32] . These cells initiate immune response through several signals: ( i ) antigen presentation via MHC-II molecules , ( ii ) the expression of co-stimulatory molecules such as CD86 and ( iii ) cytokine production [32–34] . Beside quantitative and qualitative importance of each signal , IL-12 is a key inflammatory cytokine for the development of a parasite-limiting Th1 immune response [32–34] . By injecting M . corti tetrathyridia into the peritoneum of mice , we first demonstrated an early role for DCs in the interactions between the mammalian host and M . corti tetrathyridia in the course of an infection . A central role for live larvae-released products ( ES products ) in the interaction of M . corti with the host immune system was uncovered here as live but not dead larvae continuously recruited DCs to the peritonea of injected mice throughout the first 7 days post-infection . Our subsequent observation of a persistently heightened recruitment of host immune cells within the peritonea of animals injected with live , but not dead M . corti tetrathyridia further supported the critical role of M . corti tetrathyridia ES products in facilitating the parasite persistence in vivo . This is consistent with an increasingly appraised role of helminth ES products as the most physiologically relevant parasite-derived products that mediate the fine-tuning of hosts by parasites [11 , 35] Indeed , we reported earlier that ES products from M . corti tetrathyridia inhibit DC activation [22] similar to ES products identified from other metacestodes [7 , 8 , 13 , 14 , 36–38] . As oppose to our previous observations on ES products from Echinococcus multilocularis larvae [7] , we failed to detect any DC-killing activity in M . corti ES preparations . This demonstrates that although phenotypically similar , the mechanisms of host immunomodulation by products of parasitic cestodes might not be redundant from one species to another . As an example , the most exposed structure of the closely related Echinococcus spp , the laminated layer rather promotes DC maturation [39] . Contrarily in our study , LPS-driven DC maturation was not affected by M . corti ES products or homogenates and this was also inconsistent with the widely reported ability of secretions from tissue-dwelling larvae of other parasitic cestodes like E . multilocularis [7] , E . granulosus [38] or T . crassiceps [8 , 14] to impair LPS-driven dendritic cell maturation . Our study shows that McES not only limited DC activation independently of the timing for stimulation after exposure to the parasite products as they also suppressed IL-12p70 release by BMDCs that had already been activated with LPS . The ability to refrain BMDCs from LPS-driven activation by simultaneous exposure to released products is a rather common ability of ES products of parasitic helminths [31] , but the impairment by M . corti tetrathyridia ES products of the immune effector functions of DCs that had already been activated is interesting . In fact , such products that can refrain IL-12 production by inflammatory DCs are clearly encouraging in the quest for novel and more effective approaches to counteract IL-12-dependent inflammatory diseases like sepsis [40] . Moreover , we also observed that McES mediated a general DC unresponsiveness to several TLR ligands and non-TLR ligands , which activate pathways that are instrumental for the pathogenesis of sepsis [41] further supporting the robust anti-inflammatory potential of McES . Such a potential of McES could both serve the silent establishment of the parasite in the course of an infection with M . corti tetrathyridia but could equally help preserve the host from tissue destruction by a frustrated and uncontrolled anti-tetrathyridia immune response . Our work also uncovered a glycoprotein nature of the mediator ( s ) of the DC-suppressing effect in McES . This is not uncommon since glycoproteins have already been widely reported to play a crucial role in the priming of the host immune cells by products of cestode larvae [13 , 42] . The suppressive activity of McES could not be detected in the somatic products of M . corti tetrathyridia , a quite intuitive observation given the large representation of glycoproteins among helminth-released products when compared to somatic products [11 , 17 , 19–21 , 30] . Proteomic analyses of M . corti tetrathyridia products enabled us to identify 143 proteins of which 55 were detected in the ES products and 88 in the somatic products . Comparisons between the two sets of proteins indicated a considerable lack of overlap supporting the purity of our McES preparations and excluding the leakage of somatic antigens from degenerating tetrathyridia as the primary source of the identified McES proteins . Moreover , since only 23% of the proteins detected in the McH could also be found in the McES , a selective and regulated transit of proteins from the parasite soma to the exterior milieu under our serum-free cultivation conditions is also strongly supported . Additionally , gene ontology analyses of the proteins identified within the McES could only ascribe stress response to 2 of the detected proteins ( out of 41 proteins annotated ) further indicating that ES products collected under our culture conditions were not from metabolically impaired/stressed larvae . Since in vitro generated ES products of M . corti can be recognized by IgG antibodies from chronically infected mice [43] and some composing entities of these products can be detected in the serum of infected mammals [19 , 44] , we expect that our McES collected in vitro reflects an analogical release by M . corti tetrathyridia in vivo . In this regard , it is noteworthy to point out the abundance in our McES of previously characterized immunomodulatory proteins . Many of them perform biological function necessary for the parasite survival . For example , proteases known to participate in the establishment and maintenance of infections [45] . Similarly , we detected fatty acid binding proteins which are involved in the transport of hydrophobic molecules , generally used as substrates for energy metabolism and signaling and capable of inducing alternative activation of macrophages ( AAM ) [46] . Another group of molecules , the glutathion-transferases , important in the detoxification of reactive oxygen species released from the host cell and in the inhibition of inflammatory responses were also identified in our McES [47] . Overall , M . corti tetrathyridia aided by their ES products might support energy supply , protect from the hardship of the host immune effector responses and help tame anti-parasitic host immune responses , all supportive of the parasite survival and the progression of the infection . Our findings on the comparative proteomic profiling of McH and McES then further revealed a set of proteins that were highly or exclusively present in the DC-suppressing McES as compared to the non-active McH . Intriguingly , 2 out of the 5 most represented of these proteins ( hypothetical protein 1 , MCOS_959401 and hypothetical protein 2 , MCOS_155201 ) were of unknown function and harbored secretory motif suggesting their active release by M . corti tetrathyridia at the host parasite interface . Such proteins with unknown functions , if proven to be immunosuppressive , might provide novel insights on how to regulate DC responses but more investigations are clearly required at this level . A cysteine-rich secretory protein-3 ( CRISP-3 ) containing a CAP domain was also exclusively detected in McES . CRISP-3 shares similarities with Venom Allergen-Like ( VAL ) proteins , which are dominant in ES products of nematodes where they represent interesting candidates for vaccine development [16] . Whether this host-protective function is relevant in M . corti tetrathyridia-mediated infections still remains to be determined . The most represented proteins in McES include annexin , cystatin and endophilin . Cestode annexin hold the highest homology with annexin A13 , a member of the annexin family that has not been functionally characterized yet [48] . Although present in the genome of most classes of parasitic helminths [49] , cystatins from nematodes are the most functionally characterized helminth cystatins shown to inhibit , among others , proteases involved in antigen processing and presentation , which diminishes T cell responses [49 , 50] . M . corti endophilin is considerably similar to Echinococcus spp . P29 proteins , which were shown to be highly efficient host protective antigens when used as vaccines [51 , 52] . A similar role for M . corti endophilin might therefore be supposed but would require experimental validation . The overall goal in the present study was to identify the M . corti-derived immunomodulatory glycoprotein ( s ) which suppress IL-12 pro-inflammatory cytokine release by DCs . Sequential bioassay-guided chromatographic fractionation of McES helped pin down a list of M . corti proteins exclusively present in the McES fractions that were suppressive to BMDCs . Moreover , a visual analysis of one-dimensional protein gels of McES fractions further helped narrow down the likely DC-suppressing factor ( s ) to a molecular weight higher than 20kDa . Therefore , focusing on the differential proteome between active vs . non-active McES fractions and eliminating candidates detected in the non-active parasite somatic extracts and keeping in mind the glycosylated nature of the DC-suppressive principle ( s ) , we identified 11 candidates DC-suppressing proteins . Of these , several appear not to match any protein of known function further indicating the potential of the current library of proteins in uncovering novel scheme ( s ) of metacestode interactions with their mammalian hosts . The functional characterization of these factors is currently underway and will be greatly facilitated by the commendable recent efforts in the sequencing and annotation of the genome of the major parasitic cestodes [53 , 54] In conclusion , we have dissected the ES products of the tissue-dwelling tetrathyridium of the model cestode M . corti . Importantly , the extension of these findings to more clinically/economically relevant metacestodes and the potential of the identified proteins as anti-cestode vaccines and/or controllers of unwanted host immune responses altogether re-emphasize the value of the library of candidates provided in the present work .
Animals handling , care and all experiments were carried out in compliance with Slovakian ( Law No . 23/2009 ) regulations on the protection of animals . All in vivo experiments were performed at Institute of Parasitology , Slovak Academy of Sciences ( Slovakia ) following ethic approval of the protocol 1359/14-221a under the law 39/2007 as amended by the local ethics committee of the State Veterinary Administration of the Slovak Republic in agreement with the Slovak Republic Government regulation number 377/2012 . ICR and BALB/c mice were bred and housed at the animal facilities of the Institute of Parasitology , Slovak Academy of Sciences ( Slovakia ) under specific pathogen-free conditions . C57BL/6 mice were purchased from Charles River/Wiga ( Sulzfeld , Germany ) and bred within the animal facility of the Institute of Virology and Immunobiology , University of Würzburg ( Germany ) under specific pathogen-free conditions . Mice were used at the age of 6–10 weeks . M . corti tetrathyridia were maintained in experimental hosts and cultivated essentially as described by Vendelova et al . [22] . Briefly , tetrathyridia were maintained in ICR mice ( 6–8 week old ) by the serial passage upon oral infection of larvae obtained from the peritoneal cavity of mouse with chronic infection . Host cells were removed from parasite material by axenic cultivation as previously described [22] . Tetrathyridia were maintained for 14 days in serum-free tissue culture medium ( DMEM+Glutamax , GIBCO ) containing antibiotics ( 100 U/ml of penicillin , 100 μg/ml of streptomycin ) ( Biochrom , Berlin , Germany ) , 20 μg/ml Levofloxacin ( Tavanic , Sanofi-Aventis ) and 50 μM 2-mercaptoethanol ( Merck , Darmstadt , Germany ) . Larvae viability was assessed by motility . Culture medium conditioned with parasite products from M . corti cultures which remained viable throughout the observed period was collected every 24 h and processed as previously defined [22] . Briefly , for a preparation , supernatants were pooled together , sterile-filtered through 0 . 22 μm pore-size filter ( Minisart Sartorius , Gottingen , Germany ) , concentrated 30 times and the buffer exchanged to phosphate-buffered saline ( PBS ) ( Sigma , St . Louis , USA ) using a 3 kDa concentrating column ( Merck Millipore , Tullagreen , Carrigtwohill Co . , Cork , Ireland ) . To obtain the somatic homogenate ( McH ) , M . corti tetrathyridia from in vitro cultures were extensively washed and mechanically squeezed with glass tissue grinder in cold PBS . The supernatant from homogenized larvae was collected and sterile-filtered through 0 . 22 μm pore-size filter . All procedures were performed under strict aseptic conditions . Protein concentration was determined using BCA Protein Assay Kit ( ThermoFisher Scientific ) and samples were stored at -80°C until required . Independent aliquots ( from different parasite isolates ) of McH and McES were lyophilized for LC-MS/MS analysis . The involvement of intact protein in immunomodulation was investigated upon heat-inactivation ( hiMcES ) in water bath at 100°C for 15 min . Mock-treated ES were kept 15 min at room temperature ( Mock hi ) . To test the carbohydrates involvement , sodium metaperiodate-mediated modification of glycan moieties was performed . Briefly , 0 . 5 mg/ml of ES mixture was treated with 100 mM ( vol/vol ) of sodium acetate ( pH 5 . 5 ) at room temperature . The tube content was divided to obtain test sample with addition of sodium metaperiodate ( 10mM ) in sodium acetate buffer ( McESΔCHO ) or control mock-treated ES products ( Mock ΔCHO ) treated with the equivalent amount of sodium acetate buffer without sodium metaperiodate . The samples were incubated in the dark at room temperature with gentle shaking for 1h . Desalting and buffer exchange to PBS was accomplished using the Amicon Ultra-0 . 5 ( 3K MWCO; Merck Millipore ) as per manufacturer instructions . To selectively precipitate proteins , ES products were saturated with ammonium sulfate up to a concentration of 80% ( McESΔCHO ) . The precipitated proteins were obtained by centrifugation ( 6500g , 20 min ) and dissolved in 100μl PBS and buffer-exchanged using Amicon-Ultra 0 . 5 ( 3K MWCO; Merck Millipore ) as per manufacturer instructions . Axenic M . corti tetrathyridia were washed 3 times and 60 larvae in 1 ml PBS were injected i . p . in Balb/c mice . Control mice received 60 dead larvae ( heat killed by treatment at 100°C for 15 min ) or 1 ml of PBS as a mock control . At day 3 and 7 p . i . , mice were sacrificed by CO2 asphyxiation and peritoneal exudate cells were collected by flushing the peritonea with 5 ml of complete medium i . e . RPMI 1640 ( Biochrom , Berlin , Germany ) supplemented with 10% heat-inactivated fetal calf serum ( Biochrom , Berlin , Germany ) , 100 U/mL of penicillin ( Biochrom , Berlin , Germany ) , 100 μg/mL of streptomycin ( Biochrom , Berlin , Germany ) , 2 mM L-glutamine ( Sigma , St . Louis , USA ) and 50 μM 2-mercaptoethanol ( Merck , Darmstadt , Germany ) . The suspensions of peritoneal cells were sieved through a 40 μM nylon filters ( BD Biosciences , Durham , NC , USA ) . Red blood cells were lysed using 1 . 4% NH4Cl for 5 min at 37°C and then washed with the complete RPMI medium . Viable cells were counted using a Neubauer chamber by trypan blue exclusion . BMDCs were generated from mice bone marrow precursors of C57BL/6 mice by GM-CSF as previously described [55] . Briefly , 2–3 x 106 precursor cells were cultured in complete RPMI medium supplemented with GM-CSF at 37°C , 5% CO2 . Cultures were fed with GM-CSF on days 3 and 6 . On day 8 , non-adherent and semi-adherent cells representing differentiated DCs ( 80–90% CD11c+ ) were harvested and washed in complete medium prior to in vitro stimulation assays . 1 x 106 BMDCs were plated in 24 well-plates ( Nunc , Roskilde , Denmark ) in complete RPMI medium . 5 , 20 or 50 axenically maintained larvae were washed thrice and added directly into DC cultures . In another series of experiments , larvae were separated from BMDCs using trans-well inserts ( 0 . 4 μm , BD Falcon ) . Alternatively , larva ES products were used instead of whole larvae . Lipopolysacharide ( LPS; 0 . 1 μg/ml , E . coli 0127:B8 ) was used as a positive control for DC activation . After 24h of DC stimulation at 37°C under 5% CO2 , supernatants were collected for cytokine detection and cells were stained for flow cytometric analysis . For re-stimulation experiments , larvae were removed 24 h post stimulation and BMDCs were further stimulated with LPS ( 0 . 1 μg/ml , E . coli 0127:B8 ) for an additional 24 h . In some experiments , BMDCs were treated with different doses ( 0 . 5 μg/ml up to 50 μg/ml ) of M . corti ES products or McH prior to , at the same time with , or 18 h after LPS stimulation . In several experiments different stimuli were used instead of LPS for restimulation i . e . : Zymosan A ( Saccharomyces cerevisiae; 50 μg/ml , Sigma ) , Curdlan ( 50 μg/ml , Wako ) , Lipotechoic acid ( LTA , 10 μg/ml , InvivoGen ) or phorbol 12-myristate 13-acetate ( PMA; 0 . 5 μg/ml , Sigma ) . Control BMDC wells were treated in a similar way without exposure to parasite larva samples . Expression of cell surface markers on BMDCs was measured using anti-mouse fluorochrome-conjugated antibodies specific for CD11c lineage marker ( clone N418; PE , APC , Pacific blue , FITC; eBioscience ) , MHC-II ( M5/114 . 15 . 2; I-A/I-E; PE , Alexa fluor700; eBioscience ) and CD86 ( clone GL1; FITC , PE; eBioscience ) . For staining , cells were incubated with anti-CD16/CD32 , stained with CD11c and thereafter washed in FACS buffer ( 1x PBS supplemented with 0 . 1% BSA and 0 . 1% NaN3 ) . To exclude cell debris , DRAQ5 ( Abcam ) ( 5 μM ) was added . In vitro-generated BMDCs were stained for 30 min with a cocktail of CD11c , MHC-II and CD86 antibodies and washed in FACS buffer . To analyze the cell death , BMDCs were stained for 20 min with a staining mix composed of 1x annexin-V binding buffer ( BD Pharmingen ) containing annexin-V ( roman 5; FITC , BD Pharmingen ) and Propidium Iodide ( PI; BD Pharmingen ) . Cells were acquired on a FACSCalibur ( Beckton Dickinson ) or BD LSRII equipped with DIVA software ( BD Biosciences , San Jose , USA ) . Analyses were done on FlowJo software ( Tree Star , USA ) . Culture supernatants were harvested and stored at -20°C . The production of IL-6 , IL-10 , IL-12p70 and IL-23 was assessed using sandwich ELISA ( OptEIA kits , BD Biosciences or Ready-SET-Go , eBioscience ) according to the manufacturer´s instructions . The kit detection limits were 15 pg/ml for IL-12p70 and IL-23 and 19 pg/ml for IL-10 and IL-6 . The concentrated ES products ( resuspended in PBS ) were dialyzed twice against 20 mM Tris-HCl ( pH 8 ) using Thermo Scientific Slide-A-Lyzer G2 Dialysis Cassettes ( 3K MWCO; Life Technologies ) . The dialysate was centrifuged at 30 000 g for 20 min at 4°C to remove precipitates . Approximately 10 mg of ES products were subsequently loaded onto an anion-exchange HiTrap-Q HP column ( GE Healthcare ) , which was connected , to an ÄKTA Purifier FPLC system ( GE Healthcare ) and equilibrated with a low-salt buffer . To determine the best conditions for separation of the ES products , pH scounting was performed using a triple pKa buffer/HCl system ( CIEX: 30 mM di-sodium phosphate , 30 mM sodium formate and 60 mM sodium acetate; IEX: 50 mM 1-methyl-piperazine , 50 mM BisTris base , and 25 mM Tris-base ) as suggested by GE Healthcare and using a 1 ml HiTrap Q/S ion exchange column for separation in analytical scale . From these ion exchange runs , pH 6 provided the best resolution and was adopted for subsequent preparative IEX . Preparative IEX of the dialysate of McES was performed at pH 6 using the triple IEX pKa buffer/HCl system . Practically , before loading the sample , the 1 ml HiTrap Q column was equilibrated with 15 column volume 20 mM MES buffer ( pH 6 ) . Fractionated elution of bound ES proteins/components was performed employing a linear gradient 0 to 1 M NaCl ( 25 column volumes ) . Loading and elution was done using a flow rate of 1 mL/min . Protein elution was monitored by measuring the absorption at 280 nm , and fractions of 1ml each were collected . The obtained fractions were ultra-dialyzed extensively against PBS using Amicon-Ultra 0 . 5 ( 3K MWCO; Merck Millipore ) before protein quantification by Bicinchoninic acid assay and functional assessment in the in vitro DC stimulation assay . IEX fractions of highest DC-suppressive activity were pooled for Gel filtration chromatographic fractionation . The gel filtration was performed on an Äkta Explorer machine ( GE Healthcare ) using a Superdex 200 10/300 column ( GE Healthcare ) equilibrated with 2 column volumes PBS ( pH 7 ) . Approximately 500 μl of 2 . 5 mg/ml protein solution was applied . Loading and elution was done in the same buffer using a flow rate of 0 . 4 ml/min . Protein elution was monitored by measuring the absorption at 280 nm and 400 μl fractions were collected . The eluted fractions were probed by Bicinchoninic acid assay for protein quantification before testing in the in vitro DC stimulation assay . The tested fractions were analyzed by SDS-PAGE . Immunosuppressive fractions ( 3 ) and non-active fractions ( 4 ) were lyophilized and the protein composition analyzed by LC-MS/MS . Protein samples were diluted in denaturing buffer ( 25 mM NH4HCO3/8 M urea , pH 8 . 0 ) , reduced by adding DTT ( 1 μg/50 μg protein ) , and carboxyamidomethylated with iodoacetamide ( 5 μg/50 μg protein ) . Samples were then diluted to 1 M urea with 25 mM NH4HCO3 ( pH 8 . 0 ) , and trypsin ( Trypsin Gold , Mass Spectrometry Grade , Promega ) was added at a ratio of 1 μg/ 100 μg protein . After digestion for 4 h at 37°C , an additional aliquot of enzyme was added , and samples were further incubated for 16–20 h at 37°C . The resulting peptides were desalted using OASISs HLB Cartridge ( Waters , USA ) and lyophilized . Peptides were analyzed using a Q-Tof Premier API mass spectrometer ( MicroMass/Waters ) , attached to a nanoACQUITY ultra performance liquid chromatography ( UPLC ) system ( Waters ) . Ten micrograms of each peptide sample were injected in an analytic ACQUITY UPLC peptide BEH C18 nanoACQUITY column ( 130 Å , 1 . 7 μm , 100 μm ×100 mm ) with a 2–90% acetonitrile gradient in 0 . 1% formic acid , at a 200 nL/min flow rate , for 45 or 60 min , for ES products samples or tetrathyridium somatic products sample , respectively . An ACQUITY UPLC Symmetry C18 nanoACQUITY trap column ( 100 Å , 5 μm , 180 μm × 20 mm ) was used for sample desalting at a flow rate of 5 μl/min over 2 min . The MS spectra between m/z 100 to 2000 Da were recorded , with 1-second search time spaced by 0 . 1-second interval . The MS/MS spectra were acquired on m/z 100–2000 Da mass range with the same search time and interval mentioned for the MS mode , using the MassLynx software system ( Waters ) . The samples were analyzed at data dependent acquisition mode , in which every full MS mode run was followed by three consecutive MS/MS runs of the three most intense multiple charged ions with a count higher than the threshold ( 30 counts/s ) . The collision energy values necessary for the peptide fragmentation were adjusted according to the +2 , +3 and +4 ion charges recognition files available by the MassLynx system . The raw MS/MS data were processed using the Mascot Distiller v . 2 . 2 . 1 ( Matrix Science , Boston , MA , USA ) to generate the * . mgf peak list files . Each sample was independently analyzed two or three times ( as indicated ) by LC-MS/MS ( technical replicates ) . The MS/MS peak list data files were run through the Mascot ion search engine version 2 . 3 . 0 , using carbamidomethylation of cysteine as a fixed modification ( monoisotopic mass 57 . 0215 Da ) , methionine oxidation as a variable modification ( monoisotopic mass 15 . 9949 Da ) , and a peptide and MS/MS fragment ion mass tolerance of 0 . 1 Da . Other parameters were set to include up to one missed cleavage , and the Mascot automatic decoy database search was selected . All protein searches were performed using the deduced amino acid sequences from the M . corti genome , available at ftp://ftp . sanger . ac . uk/pub/pathogens/bh4/ ( version 29/01/15 09:48:00 ) . The * . dat files ( obtained by Mascot platform ) were merged ( the LC–MS/MS technical replicates ) and processed by ScaffoldQ+ version 4 . 4 . 1 . 1 ( Proteome Software , Portland , OR , USA ) as follows . Mascot ion scores of 30 or higher ( for +2 , +3 and +4 charges ) , a minimum of two identified peptides , 90% peptide identification probability ( using the Scaffold Local FDR algorithm ) , and 99% protein identification probability were required to improve the reliability of protein identifications , resulting in a calculated FDR of <1% . The normalized spectral abundance factor ( NSAF ) [56] was calculated for each protein , and quantitative differences were statistically analyzed by a t-test using Scaffold Q+ version 4 . 4 . 1 . 1 . Differences with p values lower than 0 . 05 were considered statistically significant . Differential proteins from t-test were submitted to hierarchical clustering analysis in Perseus software package ( version 3 . 15 ) . Gene ontology ( GO ) functional classification of McES proteins was performed using Blast2GO [57] , in which a BLASTP search using NCBI non-redundant protein database with a cut-off of 30 for homology annotation was applied . McES proteins were also investigated for the presence of signal peptide using SignalP 4 . 1 [58] , and presence of non-classical signals using SecretomeP 2 . 0 [59] . A protein was considered to contain a signal peptide if the D-score was >0 . 5 and to be non-classically secreted if the NN score was higher than 0 . 6 ( unless a signal peptide has been already predicted to a given protein ) . All results were expressed as mean ± standard deviation ( SD ) . Differences observed were analyzed with nonparametric test that does not assume normality of the measurements . When only two groups were compared , a Mann-Whitney test was used . When 3 groups or more were compared , Kluskal-Wallis with Dunn post hoc comparison was used . Values of p<0 . 05 were considered statistically significant . Statistical analyses were performed with GraphPad Prism 6 . 00 for Windows ( GraphPad Prism Software ) . Most of the reported sequences are not yet available on publicly stable and available databases but can be retrieved from the “50 helminth genomes database” of the Wellcome Trust Sanger Institute at http://www . sanger . ac . uk/resources/downloads/helminths/ | The metacestode larval stages of life-threatening tapeworms grow within the organs of its mammalian hosts , thus causing severe and long-lasting morbidity . Immunosuppression , which mainly depends on factors that are released or leaking from the parasite , plays an important role in both survival and proliferation of the larvae . These parasite-derived molecules are potential targets for developing new anti-parasitic drugs and/or improving the effectiveness of current therapies . Moreover , an optimized use of such factors could help to minimize pathologies resulting from uncontrolled immune responses , like allergies and autoimmune diseases . The authors herein demonstrate that larvae from a parasitic cestode release factors that sufficiently support the suppression of dendritic cells , a set of innate immune cells that recognizes and initiates host immune responses against invading pathogens . Employing modern analytic proteomic tools combined with immunological bioassays , several cestode-derived candidate immunomodulators were identified . This is the first bioassay-guided comprehensive library of candidate immunomodulators from a tissue-dwelling cestode larva . This work validates the unmet value of the Mesocestoides corti system in characterizing the mechanisms of host immunomodulation by metacestodes and reveals the largest database of candidate metacestode-derived immunomodulators until date . | [
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"gen... | 2016 | Proteomic Analysis of Excretory-Secretory Products of Mesocestoides corti Metacestodes Reveals Potential Suppressors of Dendritic Cell Functions |
How interactions between neurons relate to tuned neural responses is a longstanding question in systems neuroscience . Here we use statistical modeling and simultaneous multi-electrode recordings to explore the relationship between these interactions and tuning curves in six different brain areas . We find that , in most cases , functional interactions between neurons provide an explanation of spiking that complements and , in some cases , surpasses the influence of canonical tuning curves . Modeling functional interactions improves both encoding and decoding accuracy by accounting for noise correlations and features of the external world that tuning curves fail to capture . In cortex , modeling coupling alone allows spikes to be predicted more accurately than tuning curve models based on external variables . These results suggest that statistical models of functional interactions between even relatively small numbers of neurons may provide a useful framework for examining neural coding .
One of the central tenets of systems neuroscience is that the functional properties of neurons , such as receptive fields and tuning curves , arise from the inputs that each neuron receives from pre-synaptic neurons . Over the past few decades , a number of experimental techniques have been developed to study exactly how interactions between neurons determine receptive field structure , including in vivo intracellular or paired recording [1]–[6] and pharmacological or electrophysiological interventions [7]–[10] . As electrophysiologists record from increasing numbers of neurons simultaneously [11]–[13] , statistical approaches that estimate interactions between neurons have the potential to explain the functional properties of neurons as network effects using only passive spike observations [for review see 14] . To understand how interactions between neurons drive neural activity , recent model-based statistical methods attempt to predict the activity of each neuron based on the activity of other simultaneously observed neurons in addition to any external variables , such as the orientation of a visual stimulus or the direction of hand movement [15]–[19] . This type of inferential approach provides estimates of potential interactions between neurons and allows us to assess how much external variables or interactions between neurons may have contributed to the observed spiking . It is important to note that these models provide only an approximation to the true underlying network structure . Since the vast majority of pre-synaptic inputs to any given neuron are unobserved , the interactions that these approaches describe reflect many different factors including common input in addition to direct and indirect synaptic connections [14] , [20] . However , due to the fact that neurons are not independent , these models can improve both encoding accuracy ( how well neural responses can be predicted ) as well as decoding accuracy ( how well external variables can be predicted from neural responses ) . Statistical models of interactions between neurons have been used to describe many different aspects of multi-electrode data in retina [21] , LGN [22] , primary visual cortex [23] , [24] , motor cortices [17] , [25] , [26] , and hippocampus [27] , [28] . Here we present a unified analysis of data from six different brain areas with a particular view towards three questions: 1 ) How are estimated interactions between neurons related to apparent tuning properties ? , 2 ) How do traditional tuning curve models change as interactions between neurons are included in the model ? and 3 ) How does our ability to predict and decode neural activity improve as increasing numbers of simultaneously recorded neurons are observed ? To make our analysis as broad as possible , we collected ten multi-electrode spike train datasets with at least 30 simultaneously recorded neurons . Datasets were obtained from six different brain areas across four different species performing a variety of tasks . By modeling typical tuning curves for neurons in each area as well as interactions between neurons we determine how much these two factors contribute to spike prediction . We find that including information about the activity of other observed neurons improves both spike prediction and decoding accuracy substantially . By capturing noise correlations and unmodeled features of the external world models of interactions between even a relatively small number of recorded neurons can complement and , in some cases , surpass , models of tuning curves alone .
Although neurons are often characterized by how their firing rate relates to external stimuli or movement variables , the functional properties of most neurons are byproducts of the input they receive from other neurons ( Fig . 1A ) . By modeling typical tuning curves as well as coupling between neurons we aim to determine how well each of these factors explains spiking ( Fig . 1B ) . We fit three , time-instantaneous , generalized linear models ( GLMs ) to recorded spike trains from 10 different datasets and attempt to predict spiking given: 1 ) external variables , 2 ) the activity of other observed neurons , or 3 ) both external variables and the activity of other observed neurons . After fitting these models to spike data the estimated parameters correspond to a typical tuning curve model , a phenomenological model of interactions between neurons , and a full model that allows functional interactions between neurons to provide an alternative explanation for the spiking that is traditionally attributed to tuning to external variables ( see Methods ) . Tuning curves can be “explained away” if the other observed neurons provide a better explanation for spiking than the external variables ( Fig . 1C ) . For instance , in a toy network where neuron 1 is tuned to external variables and projects to neurons 2 and 3 . Neurons 2 and 3 will appear tuned , despite having no direct relationship to the external world ( Fig . 1C , middle ) . By using the activity of neuron 1 to predict the spiking of neurons 2 and 3 , the tuning properties can be explained away by the more direct interactions between neurons ( Fig . 1C , bottom ) . Apparent tuning can appear in any number of network configurations , but given a set of simultaneously recorded neurons the models used here aim to explain spiking as directly as possible . In physiological data , it is unlikely that we are recording from synaptically connected pairs of neurons . The estimated couplings that we observe are likely to be strongly influenced by common input from outside of the recording area and do not necessarily reflect local , recurrent effects . However , tuning curves can still be “explained away” if the activity of the other observed neurons allows better spike prediction . We fit spike count data from multi-electrode recordings in 6 different brain areas using maximum a posteriori ( MAP ) estimation for each of the three models ( see Methods ) . Data from motor cortices were recorded during reaching movements to measure tuning to hand direction ( Fig . 2A , top ) . Data from visual cortex were recorded during the presentation of drifting gratings ( Fig . 2B , top ) . Data from auditory cortex were recorded during the presentation of pure tones ( Fig . 2C , top ) . Data from primary somatosensory cortex were recorded during reaching ( Fig . 2D , top ) . Data from hippocampus were recorded during free foraging ( Fig . 2E , top ) . Details of the experiments as well as model fitting and validation procedures are included in the methods . In the full model , most , but not all , neurons showed decreased modulation to external variables ( Fig . 2 , bottom ) . That is , spiking that was previously attributed to tuning properties was more directly explained by functional interactions with other neurons . However , the structure of the tuning curve ( i . e . the preferred direction , frequency , or place ) remained relatively unchanged . The tuning modulation ( minimum-to-maximum ) decreased 34–82% , with hippocampus showing the smallest decrease and primary auditory cortex the greatest decrease ( Fig . 3A ) . On the other hand , typical tuning preferences are generally well-preserved ( Fig . 3B ) . Preferred direction , frequency , and place are consistent between the tuning curve model and the full model ( correlation coefficient R = 0 . 34–0 . 86 , circular correlation coefficient where appropriate ) . To quantify how coupling in the full model relates to tuning properties we measured the overlap between tuning curves for each pair of neurons in each dataset using the angle between the tuning curve parameter vectors ( cosine similarity ) . An overlap of zero corresponds to orthogonal tuning ( i . e . cosine tuned neurons with preferred directions of 0 and 90 deg ) , an overlap of one corresponds to identical tuning , and an overlap of negative one corresponds to exactly opposite tuning ( i . e . cosine tuned neurons with preferred directions of 0 and 180 degrees ) . We find that tuning curve overlap is clearly related to the bulk spike-count correlation across all stimulus/movement conditions ( Fig . 3C ) . However , coupling strength is only indirectly related to tuning curve overlap ( Fig . 3D ) . Two neurons having similar tuning curves will not necessarily have strong coupling in the full model . This suggests that the explaining away of tuning curves by coupling is not a straight-forward byproduct of stimulus correlation and that including other observed neurons in spike prediction provides information that is not present in the tuning curves alone . The structure of the coupling terms , particularly the number of connections that each neuron makes with the other observed neurons ( the “degree” ) provides some insight into how tuning curves are explained away . In contrast to theories of scale-free neural connectivity [29] – which predict power-law degree distributions – the estimated functional interactions in these datasets , under the full model , have uni-modal degree distributions ( Fig . 4A ) . Interestingly , across all datasets , it seems that out-degree ( how many outputs a neuron drives ) is more narrowly distributed than in-degree ( how many inputs a neuron receives ) . The exact structure of the functional connectivity graphs may be affected by electrode spacing and geometry [24] . However , in-degree is correlated with how well coupling can explain tuning ( Fig . 4B ) . In general , neurons whose tuning curves are well explained by coupling receive input from more neurons compared to neurons whose tuning curves are not well explained by coupling . How these models behave as the number of simultaneously recorded neurons grows is an important consideration for future modeling . Here we fit the coupling alone and the full model , varying the number of neurons used to predict spikes . Under the full model , we find that , in good approximation , the fraction of variance explained by tuning decreases logarithmically as the number of observed neurons increases ( Fig . 5 ) . Place fields in hippocampus are explained away slowly , while tuning curves in motor and sensory cortices are explained more rapidly . In general , 10–70% of the variance initially attributed to tuning curves is explained by coupling between neurons in the full model . A second metric for studying how these methods scale with the number of observed neurons is spike prediction accuracy ( see Methods ) . As the number of neurons included in the model increases we find that spike prediction accuracy scales , to a good approximation , hyperbolically ( Fig . 6A ) . Note that the full model begins providing the same accuracy as the tuning curve model . As more neurons are included in the model , spike prediction accuracy increases and appears to converge towards a maximum . Interestingly , modeling coupling alone shows this same hyperbolic behavior , beginning at zero and converging towards a maximum . Once 10–30 neurons are included in the model , coupling alone provides more accurate spike prediction that traditional tuning curve models in most datasets . Hippocampal neurons appear to differ from cortical recordings in that spike prediction accuracy increases approximately linearly . Moreover , modeling coupling alone does not provide more accurate spike prediction than the basic place field model . This may be due to the low correlations between HC neurons . Electrode spacing may also be a factor , since , unlike the 400 µm electrode spacing used in almost all of the intra-cortical arrays , HC recordings had 20 µm vertical electrode spacing . However , the coupling model for spontaneous activity in V1 shows the same hyperbolic behavior despite data being recorded using a polytrode with 50 µm electrode spacing . Scaling of spike prediction accuracy in hippocampus appears to be qualitatively different from that in cortex . In addition to examining how encoding accuracy scales with the number of recorded neurons , we also examined decoding accuracy for several datasets ( Fig . 6B ) . For the V1 , M1 , and PMd datasets , we infer which of eight different reach targets or stimuli was presented given the observed spiking on a given trial . Here we use Bayesian decoding under either the tuning curve encoding models or the full encoding model described above ( see Methods for details ) . As with spike prediction accuracy , decoding accuracy grows approximately hyperbolically as more neurons are included in the models . Including coupling between neurons in addition to tuning improves decoding by a small but significant amount: 4 . 8±0 . 3% , 7 . 8±0 . 4% , 10 . 3±0 . 4% , and 7 . 9±0 . 3% for the two M1 datasets , PMd , and V1 , respectively . Many studies have illustrated how dependencies between neurons can reduce decoding accuracy [30] . By simulating from the tuning curve model we can examine how well we could decode external variables if the neurons were conditionally independent . In this case , decoding from such an independent population of neurons would be ∼25% more accurate than decoding the observed data with the tuning curve model . It is important to consider what factors may be driving these scaling phenomena . Although the coupling terms are regularized during estimation and the spike prediction accuracy is cross-validated , it may be the case that tuning curves are explained away as a result of over-fitting or , alternatively , as a simple side effect of stimulus correlations . To test for this possibility we simulated spike counts from the tuning curve model , where the neurons are conditionally independent given the external variables . That is , although there may be stimulus correlations , spiking can be completely predicted by external variables . Here we find that no matter how many neurons are included in the full model , tuning explains between 90–100% of the variance ( Fig . 7A ) . This suggests that the results for the full model in real data are not driven by over-fitting or stimulus correlation alone . Additionally , we can quantify how much stimulus correlation contributes to explaining away by shuffling the data to remove noise correlations . Where possible ( M1 , PMd , and V1 ) we shuffle the spike counts within each trial condition ( target or grating direction ) independently for each neuron . This manipulation retains stimulus correlations while destroying any structure unrelated to the stimulus . Here we find that , in the full model , tuning explains between 85–95% of the variance ( Fig . 7B ) . Furthermore , the spike prediction accuracies of the full and coupling models do not exceed the accuracy of the tuning curve model in shuffled data ( Fig . 7C ) . These two controls demonstrate that the observed explaining away is not simply a byproduct of stimulus correlations or of a poor tuning curve model . Explaining away can only occur when the other observed neurons provide a more direct explanation of spiking than the external variables . Finally , to examine what drives the shape of these spike prediction accuracy curves we simulated a linear-nonlinear-Poisson neuron receiving sparse , correlated input . As input correlation increases spike prediction accuracy converges more quickly to its maximum ( Fig . 8A ) . When the inputs are strongly correlated , neurons added later are only providing redundant information . However , when the inputs are independent , each additional neuron contributes to more accurate spike prediction . If the inputs are sparse and some of them are irrelevant to the prediction , information added by each neuron is simply smaller on average ( Fig . 8B ) . That is , if only 10% of the inputs are non-zero then it takes 10 times as many neurons to reach a given spike prediction accuracy compared to the case where all of the inputs were non-zero . For input correlation and probability of a given input being non-zero , the simulations are well-approximated by a hyperbolic function where is the maximum spike prediction accuracy and the maximum number of neurons . Linking the strength of common input and sparseness to the spike prediction accuracy curves observed in real data is difficult . Both a weakly correlated , highly connected network and a highly correlated , highly sparse network will have near-linear growth . However , here we find that neurons in cortex ( particularly V1 and A1 ) tend to be more strongly correlated than neurons in hippocampus ( Fig . 3C ) . This may partially explain the rapid growth in spike prediction accuracy for the cortical datasets and , in comparison , the near-linear growth for hippocampal datasets . Especially in cortex , the fact that neural activity traditionally attributed to tuning curves is more directly explained by interactions between neurons appears to be a byproduct of unobserved common input .
Neurons receive pre-synaptic input from tens of thousands of other neurons , and each of these inputs , presumably , plays a role in determining the tuning properties of a post-synaptic neuron . How is it possible then that models of interactions between <100 neurons are able to explain spiking more directly than traditional tuning curve models without any guarantee that the neurons are even anatomically connected ? Ultimately , explaining away can only occur when neural activity is not independent . Many studies have examined correlated neural activity [38] , [44]–[48] as well as its potential functional roles [30] , [37] , [49] , [50] . Here correlations between neurons are essential in allowing tuning properties to be explained away by the functional interactions between small numbers of neurons . However , the fact that coupling terms do not explain away tuning curves in simulated or shuffled data , suggests that our results are not simply a byproduct of stimulus correlation . Rather , the estimated coupling between neurons is likely to reflect a combination of direct and indirect interactions [e . g . 51] as well as additional unobserved common input [14] and internal processes [52]–[54] . Several studies have made progress in attempting to infer unobserved common input related to the external world [34] as well as internal processes [35] , [55] . Here we simply note that unobserved common input may allow more accurate spike prediction in models of interacting neurons by creating correlations that cannot be attributed to the observed external variables . Modeling these dependencies improves decoding by a small , but significant , amount and may be useful for improving brain-machine interfaces [56] . Moreover , the correlations induced by unobserved common input appear to allow neural activity traditionally attributed to tuning properties to be more directly explained by interactions between neurons . It is important to note , however , that the statistical approaches used here are unlikely to capture anatomical information about the underlying circuitry . These methods still only provide a sketch of the underlying circuit that best explains the observed spiking . The hyperbolic scaling of spike prediction accuracy observed here , for instance , may be a general property of correlated prediction problems [57] . found a similar hyperbolic scaling in accuracy using the firing rates of neurons in motor cortex for linear prediction of hand position . For many years , studies of the relationship between neural interactions and tuning properties have been based on detailed electrophysiology [58] , [59] , experimental intervention , or simulation [32] , [60] . Most of these studies have addressed data collected in sensory cortices or peripheral areas . However , understanding the response properties of neurons in other areas , such as motor and association cortices , in terms of neural circuits has been difficult . Here we used simultaneous neural recordings and a model-based statistical approach to ask how well tuning properties can be explained , in a statistical sense , by functional interactions between neurons . While these models are able to explain a surprisingly large fraction of the variation in neural spike counts in a variety of brain areas with a relatively small number of observed neurons , they only provide a rough picture of how network architecture might give rise to commonly observed tuning properties . Understanding how interactions between neurons give rise to tuning properties , will ultimately mean understanding the relative contributions of feed-forward , local , and top-down pre-synaptic inputs , as well as how different subtypes of neurons and neurons with different types of tuning interact . One area where statistical approaches have revealed this type of detailed architecture is in the retina . By recording from dense populations of retinal ganglion cells ( RGCs ) , recent work has shown that RGC receptive fields arise directly and clearly from input received from rods and cones [61] . Moreover , functional interactions between retinal ganglion cells appear to have a strong , local structure [21] . Although photoreceptors are the only elements in the retinal circuit that have direct responses to the external world , the receptive fields of RGC responses can be understood as a byproduct of indirect interactions with photoreceptors , mediated by intermediate neurons , such as horizontal , amacrine , and bipolar cells . In most areas of the brain , beyond the retina , recording from a complete neural circuit is experimentally infeasible and the complete network of neurons is immensely under-sampled . In these cases , it is difficult to determine whether potential interactions between neurons are direct ( mono-synaptic ) or indirect ( poly-synaptic ) , and the estimated interactions are likely to be strongly influenced by unobserved common input [14] . What is ultimately estimated by the statistical approaches is a phenomenological model of the circuitry that best describes the observed spikes [20] . For this reason it is difficult to draw conclusions about detailed architecture in current multi-electrode datasets . Here we have examined how modeling interactions between small numbers affects neural coding and how model-based estimates of interactions relate to stimulus and noise correlation . As electrophysiologists record from increasing numbers of neurons [13] these approaches have the potential to reveal more detailed information about the structure of these cortical and sub-cortical areas .
Spike count data were fit using either external variables , the activity of the other recorded neurons , or both [14] , [17] , [21] , [28] . In each case we used a class of generalized linear model [71] - a linear non-linear Poisson ( LNP ) model with exponential nonlinearity [15] , [16] . The model and estimation methods have been previously described in detail elsewhere [21] . Briefly , LNP models assume that the covariates ( tuning to stimulus/movement or activity of other neurons ) are linearly combined , then passed through an exponential nonlinearity such that the firing rate is non-negative . The estimated firing rate for each neuron is then a function of the external variables during each trial and the activity of the other neurons :where denotes one of basis functions that describe the shape of the tuning curve , and the parameters and capture tuning , coupling to other neurons , and a baseline firing rate . The basis functions , described below , will depend on the brain area we are trying to model and the stimulus/task . The spike count is then assumed to be drawn from a Poisson distribution with this rate:where represents the spike count for neuron on trial . Using this same framework , tuning curves alone were modeled bywhile coupling between neurons was modeled by Note that , for the coupling model , the spike count for the neuron whose firing rate we are estimating was always excluded . Using this framework we examined the effect of network size on spike prediction accuracy by varying the total number of neurons included in the model and using a random subset of all recorded neurons , again excluding neuron . For each of these three models – the full model , tuning curve model , and coupling model – we estimated the parameters and directly from the observed spike count data using maximum likelihood estimation ( MLE ) or maximum a posteriori ( MAP ) estimation with an L1-penalty to prevent over-fitting [see 21] . Here we compute ML estimates using iterative reweighted least squares ( IRLS ) with the Matlab package glmfit and compute MAP estimates using path-wise , cyclical coordinate descent [72] with the R package glmnet . Where regularization is used we optimized the regularization hyperparameter via the cross-validated ( 10-fold ) log-likelihood , and in all cases we evaluated the “spike prediction accuracy” of the models using the cross-validated log likelihood ratio relative to a homogeneous Poisson process . For a firing rate , the log-likelihood is given byand the log likelihood ratio relative to a homogeneous Poisson process ( spike prediction accuracy ) is given by In this case , a spike prediction accuracy of zero corresponds to a model that does no better than predicting the mean spike count . Values were calculated in base-2 and rescaled by time to give units of bits/s [see 21 , 27] . We find that spike prediction accuracy scales approximately hyperbolically , following where is the number of neurons in the model and and are parameters determining the shape of the curve [see 57] . An important component of these models is the choice of basis functions for the external variables . Here we have attempted to choose common tuning models , appropriate for each dataset . For M1 and PMd neurons , for instance , where denotes the target direction on each center-out trial . This linear component of the model corresponds to the traditional cosine tuning models of motor cortical neurons [73] , [74] . We used the same model to capture direction tuning in visual cortex [75] . While activity in M1 has also been shown to covary with speed [76] , we elected to use the simpler direction tuning model here , and model speed tuning only in S1 neurons , which show direction tuning [77] as well as clear tuning to hand speed [64] . In this case we use Place fields of the neurons in hippocampus have been well described [78]–[80] . To model these localized response properties we use a set of radial basis functions that tile the foraging area . Specifically we use K = 25 isotropic Gaussian radial basis functions equally spaced on a 5×5 grid with means and covariance , = 9 cm . Finally , for neurons in A1 [81]–[83] , we again use radial basis functions . In this case K = 7 Gaussians were equally spaced along the log-frequency of the stimulus with standard deviation = 0 . 64 octaves . In most cases ( TC dimensionality <4 ) , regularization was only applied to the coefficients modeling coupling between neurons . To avoid convergence problems [84] the models using radial basis functions ( A1 and HC ) included weak regularization on the tuning curve coefficients ( with 20% of the L1-penalty used for the coupling coefficients ) . The tuning curve parameters do not change substantially for penalties ranging from 1–20%; however , there may be unintended shrinkage in these models , and the decrease in modulation observed for these neurons may be somewhat over-estimated . It is important to note that the models used here differ from previous approaches in that they are time-instantaneous — we model coupling between neurons at the same time . This does not pose any difficulties during fitting , since we are modeling only the conditional distributions for each neuron . However , simulating from the joint spiking distribution is no longer straight-forward . The usual assumption , , does not hold , but , since the conditionals are know , we can use Gibb's sampling to simulate from this joint distribution if necessary ( see section on Decoding below ) . To quantify the changes in tuning under the full model we evaluate the tuning modulation , tuning preference , and tuning curve overlap between pairs of neurons . Tuning modulation is simply the peak-to-peak difference in firing rate for the tuning curve component of the model , reported in Hz . Tuning preference is defined differently for each dataset: for M1 , V1 , PMd , and S1 we use the preferred direction , for A1 we use the preferred frequency , and for HC we use the preferred place along the x-axis . Finally , to measure similarity between the tuning curves for pairs of neurons we evaluate the tuning curve overlap between neurons and , . Accordingly , a tuning curve overlap of 1 suggests that the two neurons have identical tuning ( up to a constant baseline ) , while a tuning curve overlap of 0 suggests that the two neurons have orthogonal tuning . To quantify network properties we also report the spike count correlation ( Pearson's correlation ) . For two neurons with trial-by-trial spike count observations and the correlation is given by . Although the spike count correlation between pairs of neurons is known to increase with both firing rate [85] and time interval [86] , [87] , we do not attempt to correct for these effects here . In most cases the bin-size is determined by the task and the traditional periods used to measure tuning curves , such as stimulus duration . To quantify the relative contributions of the tuning curve and coupling components in the full model we summarize the fit using the fraction of variance explained by tuning . For each neuron we calculate A value of 1 suggests that the coupling terms provide no additional information , while a value of 0 suggests that any tuning information is explained completely by coupling to other observed neurons . It is important to note that there is considerable heterogeneity in how well tuned neurons are to the external variables . Here we analyze all recorded neurons , even those that might be considered un-tuned . In contrast to the encoding models above , which aim to predict spikes given a stimulus , we can also examine how coupling affects decoding , which aims to predict a stimulus given a set of spike observations . Here , we use Bayesian decoding [88] , [89] based on the same encoding models described above . Assuming the stimuli are equally probable For the tuning curve models , we assume that the neurons are conditionally independent given the stimulus , However , for the full model , since we assume that coupling is instantaneous , we cannot make this assumption . In this case we use a variation of Gibb's sampling [90]–[92] to approximate the joint distribution . Briefly , in Gibbs sampling we generate samples from by iterating over all neurons and sampling a spike count for each neuron based on the conditional distributionwhere denotes the iteration . Here we use a method know as ordered over-relaxation [93] to improve mixing . This makes the sampler much more efficient for large networks of neurons with strong coupling . In this case we generate samples from the conditional distribution at each update , sort the samples along with , and if is the -th largest value we take the -th sample . After many iterations the set of samples - ignoring a burn-in period - provides an approximation to the joint likelihood that we can then use , via Bayes rule , to approximate the posterior over possible stimuli . For each model we initialize the sampler with , initialize each successive sample using , and update the spike counts for each neuron in a random order using the conditional distribution with ordered over-relaxation . We then take 5000 samples after a burn-in period of 500 samples to use as an approximation to the joint density . In practice , it is non-trivial to estimate the probability for each trial given a set of samples from the distribution . When the number of neurons become large the curse of dimensionality makes histogram estimation impossible . We would need samples where is the number of neurons to construct an accurate histogram . Here we use an approximation based on the chain rule of probability Although we cannot write down the full joint probability analytically , we can approximate each of the marginal distributions in the chain rule using the set of Gibbs sampleswhere denotes the random variables for all other neurons not yet taking a specific value , and the expectations are taken over the set of Gibbs samples . Importantly , each probability in each expectation can now be evaluated analytically based on the conditional Poisson likelihoods of the full model . This approach allows us to approximate the posterior over stimuli and assess the Bayesian decoding accuracy of the tuning curve model with instantaneous coupling . To examine how the scaling of spike prediction accuracy relates to the underlying structure of the inputs we simulated spikes from a linear-nonlinear-Poisson neuron receiving correlated inputwhere the baseline firing rate parameter was fixed and denotes a set of correlated Poisson random variables . The connection strengths were drawn from a sparse , binary random vector with entries randomly set to zero with probability . Correlated inputs were each assumed to have mean 1 and were drawn from a multivariate Poisson distribution with the covariance matrix where denotes the specified correlation , denotes the mean , denotes the unit matrix , and the identity matrix . Under this covariance matrix all pairs of neurons have correlation and we set the variance of each neuron equal to the mean . In general , producing correlated Poisson random variables with specific marginal distributions and covariance structure is difficult . Here we use a simplified family of covariance matrices where all neurons have the same correlation and simulate spike counts following [94] . After simulating and fitting the LNP model , we can examine how input correlations and sparseness affect spike prediction accuracy . | The number of simultaneous neurons that electrophysiologists can record is growing rapidly , and a central goal of computational neuroscience is to develop statistical methods that can make sense of this growing data . Here we present a unified statistical analysis of 10 different datasets recorded from several different species and brain areas . We show how functional interactions between neurons may be used to predict spiking in each of these different areas , and find that , in many cases , modeling interactions between a small number of neurons yields better spike predictions than modeling each neuron's relationship to the outside world using tuning curves . Although these statistical results cannot be linked to specific network architectures , since the measured interactions between neurons are purely functional rather than anatomical , they suggest that modeling interactions between neurons will be a useful approach to understanding neural coding as electrophysiologists record from increasing numbers of neurons . | [
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] | 2012 | Functional Connectivity and Tuning Curves in Populations of Simultaneously Recorded Neurons |
Animal locomotion is mediated by a sensory system referred to as proprioception . Defects in the proprioceptive coordination of locomotion result in uncontrolled and inefficient movements . However , the molecular mechanisms underlying proprioception are not fully understood . Here , we identify two transient receptor potential cation ( TRPC ) channels , trp-1 and trp-2 , as necessary and sufficient for proprioceptive responses in C . elegans head steering locomotion . Both channels are expressed in the SMDD neurons , which are required and sufficient for head bending , and mediate coordinated head steering by sensing mechanical stretches due to the contraction of head muscle and orchestrating dorsal head muscle contractions . Moreover , the SMDD neurons play dual roles to sense muscle stretch as well as to control muscle contractions . These results demonstrate that distinct locomotion patterns require dynamic and homeostatic modulation of feedback signals between neurons and muscles .
Animal locomotive behaviors , which include crawling , walking , swimming , and running , are mediated by a sensory system referred to as proprioception [1–3] . Specialized proprioceptive neurons sense body and limb movements and send signals to the brain , in which the proprioceptive signals are integrated and processed to coordinate motor activity [2–4] . In invertebrates , proprioceptive signals are detected by proprioceptive neurons and proprioceptors , which are located within the body wall muscles or mechanosensitive organs and orchestrate the movement of each body segment [5–9] . Similarly , in mammals , proprioceptors are located in their muscles , ligaments , and joints to coordinate the movements of the limbs [3 , 10] . Defects in the proprioception-mediated coordination of locomotion cause uncontrolled and inefficient movements such as ataxic gait [7 , 8 , 11] , but the precise molecular mechanisms by which proprioception occurs and how it modulates sensorimotor coordination remain unclear . Specifically , the cells and stretch-sensitive molecules that mediate proprioception need to be fully identified . Mechanosensitive channels , including transient receptor potential ( TRP ) channels , degenerin/epithelial sodium channels ( DEG/ENaC ) , and Piezo have been implicated as putative proprioceptors that transduce the mechanical signals derived from muscle and limb movements into electrical signals [8 , 12–15] . TRP channels have been well characterized in animal models and in vitro expression systems as cellular sensors that detect a variety of mechanical forces . For example , Drosophila transient receptor potential no mechanical potential C ( TRPN/NompC ) channels are expressed in the bipolar dendrite ( bd ) and class I dendritic arborization ( da ) proprioceptive neurons of chordotonal organs , in which they are involved in both larval crawling and adult locomotion [8 , 12 , 16] . In addition , heterologously expressed transient receptor potential ankyrin ( TRPA ) , transient receptor potential mucolipin ( TRPM ) , transient receptor potential cation ( TRPC ) , and transient receptor potential vanilloid ( TRPV ) channel isoforms can be activated by membrane stretch [17–24] , but their precise functional role in proprioception remains unclear . The nematode C . elegans is a genetically tractable animal model in which to dissect the sensorimotor feedback system’s underlying locomotion . Its complete synaptic wiring of motor circuits [25 , 26] and a broad spectrum of locomotive behaviors , including forward and backward crawling and swimming [27 , 28] , provide a unique opportunity to study molecular and neuronal mechanisms underlying locomotive behaviors at single-synapse resolution . C . elegans moves in a sinusoidal wave pattern via a periodic bending of its head and body . These movements are thought to be generated and shaped by proprioception [29] . Two putative types of proprioceptive neurons have been identified: the B-type cholinergic neurons , which may respond to local body bending and propagate proprioceptive signals along the body , and the DVA neurons , which regulate the extent of body bending via activation of trp-4 TRPN channels [13 , 30] . However , the molecular nature of the stretch-sensitive proprioceptive receptors and the mechanism by which these neurons direct proprioceptive feedback systems have not yet been identified . Here , we show that the C . elegans TRPC channels trp-1 and trp-2 are both necessary for the proprioception-mediated steering of forward locomotion and sufficient for stretch-induced neuronal responses upon expression . trp-1 trp-2 double-mutant animals show defects in steering during forward movement , leading to ventral circling locomotion . Both TRP-1 and TRP-2 are expressed in the SMDD proprioceptive neurons , the ablation of which also causes ventral circling locomotion . The activity of the SMDD neurons induced by head bending is not abolished but instead misregulated in trp-1 trp-2 mutants , and optogenetic manipulation of the activity of SMD neurons similar to that observed in trp-1 trp-2 double mutants also results in ventral circling locomotion . Moreover , expression of the proprioceptive receptors C . elegans trp-4 or Drosophila trpγ rescues the locomotive defects of trp-1 trp-2 double mutants , and ectopic expression of TRP-1 or TPR-2 causes robust Ca2+ responses to head bending in a C . elegans chemosensory neuron . Together , these results reveal that sensorimotor coordination of head steering locomotion in C . elegans is mediated by two TRPC channels trp-1 and trp-2 in the SMDD proprioceptive neurons .
To identify the factors that mediate proprioception to modulate the sinusoidal waveforms of C . elegans , we performed a candidate mutant screen of mechanosensitive TRP channels and DEG/ENaC genes [31–33] . We measured 44 mutant strains , including 19 TRP channels and 25 DEG/ENaC channel genes , for three values of the sinusoidal locomotive waveforms including wave width , wave length , and turning angle ( Fig 1A , S1–S3 Figs ) . We found several mutant strains with altered values ( S1–S3 Figs ) . Since the defects were mild , however , we decided not to pursue these mutants further . Instead , we began to generate double mutants for genes examined in the first screening . The C . elegans genome contains three TRPC channel genes ( i . e . , trp-1 , trp-2 , and trp-3/spe-41; Fig 1B ) , of which trp-3 is expressed exclusively in sperm [32–34] . To determine whether remaining TRPC family members regulate locomotion , we used genetic recombination to create trp-1 trp-2 double mutants . In the trp-1 ( sy690 ) allele , the promoter and the majority of the N-terminus of the TRPC channel are missing; in the trp-2 ( sy691 ) allele , half the transmembrane domain is lost along with the TRP box domain . The nature of these molecular lesions suggests that they are likely null alleles ( Fig 1C ) . We found that trp-1 trp-2 ( sy690 sy691 ) double mutants exhibited continuous circular sinusoidal locomotion ( Fig 1D , S1 and S2 Videos ) . To quantitate this circling behavior , we measured their turning angle and found it to be significantly higher than that of wild-type animals ( trp-1 trp-2: 31 . 9° ± 5 . 1° , n = 20; wild type: 1 . 71° ± 1 . 1° , n = 20; Fig 1E ) . We call this phenotype “ventral circling locomotion . ” In contrast to the double mutants , trp-1 or trp-2 single mutants did not exhibit ventral circling locomotion ( Fig 1E ) . While the wave width of the trp-1 trp-2 double mutants is similar to that of wild-type animals , their wave length is slightly reduced ( S4 Fig ) . The ventral circling locomotion of trp-1 trp-2 double mutants persists in the absence of bacterial food ( S5 Fig ) . However , we did not find any differences of turning angles between wild-type and trp-1 trp-2 mutant animals during reversals ( S6 Fig ) . Together , these results suggest that trp-1 and trp-2 regulate the turning angle of forward movement . Next , we generated transgenic animals expressing trp-1p::gfp or trp-2p::mCherry transgenes under the control of 2 . 6-kb and 3-kb promoter regions , respectively [35–37] . We found that trp-1 and trp-2 were coexpressed in several head neurons , including the putative proprioceptive SMD neurons ( Fig 1F ) [26] . The SMD neurons include two left and right pairs of neurons ( i . e . , the dorsal SMDDL/R and ventral SMDVL/R ) with cell bodies in the head that extend processes sublaterally from head to tail to innervate the muscles of the head . The SMDV cell bodies are located dorsally , and they send processes subventrally , whereas the SMDD cell bodies are located in the ventral ganglion , and their processes follow other dorsal sublateral cords ( Fig 1A ) [26] . To verify the expression of trp-1 and trp-2 in the SMD neurons , we compared the expression of the trp-1 and trp-2 reporters to that of the flp-22p-Δ4 and flp-22 SMD reporters ( Fig 1F ) . The flp-22p-Δ4 promoter resides upstream of the flp-22 promoter , which drives transgene expression in several head neurons , including ASG and CEP ( or URX ) , as well as in SMD ( S7A and S7B Fig ) [38] . In this study , we used the flp-22p-Δ4 promoter to express transgenes in the SMD neurons , except when otherwise noted . We observed strong overlap between the trp-1 or trp-2 transgene and SMD reporter expression ( Fig 1F ) . We also found colocalization of trp-1 expression with trp-2 in the SMD neurons ( Fig 1F ) , indicating that both trp-1 and trp-2 are indeed expressed in the SMD neurons . To determine whether the ventral circling locomotion is caused by loss of trp-1 and trp-2 function in SMD , we expressed the trp-1 cDNA or trp-2 cDNA under the control of the flp-22p-Δ4 promoter in the trp-1 trp-2 double-mutant background . We found that expression of either trp-1 cDNA or trp-2 cDNA rescued the locomotion defects of the trp-1 trp-2 double mutants ( Fig 1G , S8A Fig ) . We further dissected their relative contributions of the dorsal and ventral SMD neurons by expressing the trp-1 cDNA or trp-2 cDNA specifically in the SMDD and/or SMDV neurons under the control of the glr-1p-Δ1 and flp-7 promoters , respectively . The glr-1p-Δ1 promoter drives transgene expression in SMDD and some ventral nerve cord neurons but not in SMDV neurons; the flp-7 promoter drives expression consistently in several neurons , including SMDV but also weakly and occasionally in SMDD ( S8B Fig ) [38 , 39] . Interestingly , glr-1p-Δ1 promoter–driven expression of either TRP-1 or TRP-2 fully rescued the ventral circling phenotype of the trp-1 trp-2 double mutants , but flp-7 promoter–driven expression produced a weaker rescue ( Fig 1G , S8A Fig ) . These results suggest that TRP-1 and TRP-2 act in SMDD to regulate turning angle of forward locomotion . To investigate the physiological roles of TRP-1/TRP-2 in the SMD neurons during forward locomotion , we first generated transgenic animals expressing GCaMP3 in the SMD neurons and recorded the Ca2+ transients of all the SMDD and SMDV somas as the animals moved freely . We observed oscillating Ca2+ transients in SMD during movement; the SMDD calcium activity was increased during dorsal head bending and reduced during ventral head bending , whereas the SMDV calcium transients were increased during ventral head bending and reduced during dorsal head bending ( Fig 2A and 2B , S9 Fig , S3 Video ) [40 , 41] . These results indicate that the SMDD and SMDV oscillating Ca2+ waves are in antiphase ( Fig 2B ) . A cross-correlation analysis of the SMD calcium dynamics and head bending showed a strong correlation between SMDD calcium activity and dorsal head bending and between SMDV activity and ventral head bending ( Fig 2B and 2F ) . Next , we found that the SMDV and SMDD neurons of trp-1 trp-2 double mutants also exhibited oscillating Ca2+ transients during forward movement . However , although we did not see any changes in the calcium activity of the SMDV neurons , the Ca2+ transients of SMDD in trp-1 trp-2 double mutants were reverse-correlated with dorsal head bending and positively correlated to ventral head bending . This leads to two oscillating Ca2+ waves in SMDV and SMDD with phases similar to each other ( Fig 2C , 2D and 2F , S9 Fig , S4 Video ) . We also noted that SMDD activity is a little lower than SMDV activity in trp-1 trp-2 double mutants ( S10A Fig ) . The glr-1p-Δ1 promoter–driven expression of the trp-1 cDNA fully rescued this defect in the SMDD calcium dynamics ( Fig 2E and 2F ) . The SMD activities of the trp-1 or trp-2 single mutants showed strong correlations with head bending like wild-type animals ( S10B Fig ) , consistent with no apparent phenotype in forward locomotion upon each single mutation . These results suggest that TRP-1 and TRP-2 play a role in coordinating the activity of the SMDD neurons with dorsal head movement . Since the oscillatory calcium transients of SMDD and SMDV are synchronized in the trp-1 trp-2 mutants , we next asked whether the simultaneous activation of SMDD and SMDV can induce a locomotion pattern that mimics the defect of the trp-1 trp-2 mutants . We performed optogenetic experiments using transgenic animals that express the channelrhodopsin variant ReaChR::mKate2 in the SMDD/V neurons under the control of the lad-2p-Δ1 promoter [42 , 43] . The lad-2p-Δ1 promoter is expressed in ALN , PLN , SAA , SDQ , and SMDD/V ( S7C Fig ) . Previous studies have shown that optogenetic activations of the PLN , ALN , and SDQ neurons do not affect forward movement [44] , nor do ablations of the SAA neurons [37] . Upon green light stimulation in the presence of retinal , transgenic worms instantly began ventral bending , which led to a ventral circling phenotype like that of the trp-1 trp-2 mutants ( Fig 2G , S5 Video ) . Upon termination of the light stimulation , the animals immediately reverted to normal forward movement . These results suggest that the ventral circling phenotype of the trp-1 trp-2 double mutants is due to the synchronization of the activities of SMDV and SMDD neurons . SMDD and SMDV innervate the dorsal and ventral head muscles near the nerve ring region ( Fig 2H ) [26] . Previously , it was shown that a set of cholinergic marker genes are expressed in the SMD neurons and that a few excitatory nicotinic acetylcholine receptors are expressed in muscle [45 , 46] , suggesting that synaptic transmission from the SMD neurons to muscle is excitatory [47 , 48] . To verify that synaptic transmission between SMD and neck muscles is excitatory , we performed the calcium imaging and optogenetic experiments by expressing ReaChR channelrhodopsin in the SMD neurons and measuring Ca2+ transients in dorsal and ventral muscles upon light exposure . Upon light exposure , Ca2+ transients in both dorsal and ventral muscles near the neck were strongly increased ( S11 Fig ) , indicating that synaptic transmission from the SMD neurons to neck muscles is indeed excitatory . Then , we speculated that the uncoordinated SMDD calcium dynamics with head movement in the trp-1 trp-2 mutants impair dorsal head muscle contractions , leading to the ventral circling locomotion phenotype . Using transgenic animals expressing GCaMP3 . 35 in body wall muscles [49] , we measured GCaMP intensity in the head muscles while observing SMD Ca2+ dynamics with head bending ( Fig 2H , S12 Fig ) . We found that Ca2+ levels in the dorsal head muscles of trp-1 trp-2 double mutants during dorsal bending , when the SMDD GCaMP fluorescence is brightest , were reduced compared to those of wild-type animals , whereas the ventral muscle levels are unaltered ( Fig 2H , S12 Fig ) . In addition , we examined the general morphology of the body wall muscles of wild-type , trp-1 trp-2 double-mutant , and unc-89 mutant animals , using label-free coherent anti-Stokes Raman scattering microscopy [50] . unc-89 gene encodes a component of the M-line and organizes the myosin filament structure of muscles in C . elegans [51] . Compared to disorganized muscle structure of unc-89 mutants , wild-type and trp-1 trp-2 mutant animals exhibit linearized and well-organized sarcomere structure ( S13 Fig ) , indicating that the reduced Ca2+ activity in the dorsal head muscles is not a result of structural defects in the muscles . Consistent to this observation , trp-1 and trp-2 genes are not expressed in muscles ( Fig 1F ) . Together , these results suggest that TRP-1 and TRP-2 in SMDD are involved in linking head bending to head muscle contractions . We next asked whether TRP-1 and TRP-2 function as stretch-sensitive receptors to detect head bending–driven mechanical stretches due to the contraction of head muscles . First , we performed rescue experiments by expression of the previously identified stretch receptors C . elegans TRP-4 and Drosophila TRPγ [8 , 13] . trp-4 encodes a TRPN subfamily member that is expressed in the DVA putative proprioceptive neuron and that regulates body bending [13]; trpγ is a TRPC homolog gene expressed in femoral chordotonal proprioceptive organs that regulate fine leg coordination during walking [8] . The expression of the trp-4 or trpγ cDNAs in the SMD neurons fully rescued the ventral circling locomotion defect of trp-1 trp-2 mutants ( Fig 3A ) . In addition , we expressed the trp-1 or trp-2 cDNAs in the DVA neuron of trp-4 ( sy695 ) mutants . trp-4 mutants exhibit exaggerated wave width during forward movement due to defects in body stretch–mediated proprioception [13] . As with the expression of TRP-4 , the expression of TRP-1 or TRP-2 in the DVA neuron rescued the altered locomotion of trp-4 mutants . In addition , the wave width for these animals was even smaller than that of wild-type animals ( Fig 3B ) . These results indicate that the stretch sensitive TRP-4 and TRPγ channels can functionally substitute for TRP-1 and TPR-2 . Furthermore , the role of the TRPC channels is evolutionarily conserved between C . elegans and Drosophila [8] . To further investigate the stretch-sensitive functions of TRP-1 and TRP-2 , we first ectopically expressed the trp-1 or trp-2 cDNAs in the AWC chemosensory neurons of transgenic animals also expressing GCaMP3 . We then monitored Ca2+ transients in the AWC somas during freely moving conditions . Previous studies have shown that the AWC neurons elicit Ca2+ transients upon odor removal [52] . In addition , ultrasound-induced mechanical deformation also induces Ca2+ responses in the AWC neurons expressing TRP-4 [53] . We detected weak and inconsistent Ca2+ responses in the AWC neurons of forward-moving animals ( Fig 3C and 3D ) [53] . However , misexpression of either TRP-1 or TRP-2 in the AWC neurons caused the AWC neurons to additionally produce strong and consistent Ca2+ responses , depending upon dorsoventral nose bending ( Fig 3C and 3E ) . We observed increases of the AWC Ca2+ signal during dorsal nose bending that fell back to baseline during ventral bending , resulting in a strong correlation between the Ca2+ transients in the AWC neurons and dorsal nose bending ( Fig 3F ) . Next , we tested two other chemosensory neurons , AWA and ASI , and found that , similar to those in TRP-1-expressed AWC , Ca2+ transients in TRP-1-expressed ASI were increased only upon dorsal nose bending but not ventral nose bending ( S14 Fig ) . However , we did not see significant difference of Ca2+ transients in TRP-1-expressed AWA ( S14 Fig ) . These results suggest that ectopic expression of TRP-1 or TRP-2 is sufficient to confer neuronal responses upon mechanical deformation of head muscles in a context-dependent manner and support a role for TRP-1 and TRP-2 as putative stretch-sensitive receptors . To determine whether the SMD neurons are stretch-sensitive proprioceptive neurons that mediate forward locomotion , we first performed laser microsurgery to individually ablate pairs of SMDD or SMDV cell bodies . Ablation of the SMDD cell bodies resulted in a ventral circling phenotype similar to that observed with the trp-1 trp-2 mutants , confirming that the ventral circling phenotype of the trp-1 trp-2 double mutants is due to a functional defect in the SMDD neurons ( Fig 4A and 4C ) . Furthermore , ablation of the SMDV neurons induces dorsal circling locomotion ( Fig 4B and 4C ) . Because ctbp-1 mutants show defects in the neuronal processes of SMDD but not SMDV neurons [39] , we examined the locomotion of ctbp-1 mutants . C-terminal binding protein 1 ( CTBP-1 ) is a transcriptional repressor of C-terminal binding protein , which regulates neuronal development [39] . We found that ctbp-1 ( ok498 ) mutant animals exhibited the ventral circling phenotype like the trp-1 trp-2 double mutants ( Fig 4D ) . These results indicate that the SMD neurons play a role in steering forward locomotion—SMDD for the dorsal direction and SMDV for the ventral direction . Because SMD neurons have pre- and postsynaptic connections with several sensory neurons , motor neurons , and interneurons in the head region [26] , we asked whether Ca2+ transients in the SMD neurons are elicited by transmissions from presynaptic neurons or by direct sensing of head muscle contractions . We first measured Ca2+ transients in the SMD neurons of unc-13 ( e1091 ) and unc-31 ( e928 ) , which have defects in synaptic vesicle release and dense core vesicle release , respectively [54 , 55] . We found that although these mutant animals have uncoordinated movements , the correlation between head bending and the activity of their SMD neurons was quantitatively unaltered compared to wild type ( Fig 4E ) . This suggests that SMD Ca2+ signals could be induced by direct mechanical sensory stimuli or electric synaptic transmission rather than by chemical synaptic transmission from other cells . We next asked whether the head muscle contractions upon head bending indeed generate SMD calcium activity . When we tested unc-54 ( e1092 ) myosin heavy chain mutants , which are paralyzed because of severe defects in muscle contractions [56] , we found a complete absence of SMD calcium transients ( Fig 4F ) . We did observe SMDD and SMDV calcium activity in these animals , however , when we physically induced head bending by gently pushing the head with a platinum wire in the dorsal and ventral directions , respectively ( Fig 4F ) . To validate that head muscle contractions are sufficient to generate SMD calcium dynamics further , we generated transgenic animals expressing ReaChR channelrhodopsin in the body wall muscle and calcium sensor GCaMP in the SMD neurons , respectively . The worms were placed into the 4% agar pad to be immobilized . Then , we activated both dorsal and ventral body wall muscles simultaneously by exposing light to animals and observed the SMD Ca2+ transients . We found that upon light exposure , Ca2+ level was increased in the SMDD and SMDV neurons ( Fig 4G ) , suggesting muscle contractions are indeed sufficient to activate the SMD neurons . Taken together , these results indicate that head muscle contractions are sufficient to directly generate SMD calcium dynamics .
The motor circuits and neural mechanisms underlying the sinusoidal forward and backward movements of C . elegans have been extensively studied [57 , 58] . Little is known , however , about how worms steer their head to maintain a straight path overall . Here , we have determined that the proprioceptive receptor SMD neurons and TRP-1/TRP-2 TRPC channels are required for the proprioceptive feedback that regulates head steering during forward movement . The SMD cholinergic neurons were suggested to be proprioceptive receptor neurons because of their morphology , including their extension of synapse-free processes along the body and their innervation of head muscles [26 , 47] . With several lines of evidence , we demonstrated that the SMD neurons do indeed function as proprioceptive neurons that control head steering locomotion . First , laser ablations of the SMD neurons cause severe defects in steering during forward movement . Killing either the SMDD or the SMDV neurons results in ventral or dorsal circling locomotion , respectively . In addition , the ctbp-1 mutants , which have defects in their SMDD processes , also exhibit ventral circling locomotion . Second , optogenetic activation of the SMD neurons results in head steering locomotion . When we stimulate all four SMD neurons together , producing a synchronized calcium dynamic similar to that observed in trp-1 trp-2 double mutants , the animals exhibit ventral circling movements . Third , we found that SMD neurons are activated by head/neck muscle stretching . Forced head/neck bending in the dorsal or ventral directions elicits robust Ca2+ transients in SMDD or SMDV neurons , respectively . Finally , disruption of chemical synaptic transmission does not affect the oscillating Ca2+ transients produced in the SMD neurons upon head bending . Together , these results indicate the SMD neurons are necessary and sufficient to generate head steering locomotion and strongly support that the SMD neurons are bona fide proprioceptive neurons in C . elegans . The DVA neuron , which was previously identified as a proprioceptive neuron , is stimulated by body bending and expresses a stretch receptor , the TRP-4 TRPN channel [13] . Rather than innervating any muscles , however , the DVA neurons appear to send sensory signals to the ventral nerve cord motor neurons to modulate the locomotor circuitry [13 , 26] . Additionally , laser ablation of the DVA neurons only mildly affects body bending [13] . Unlike the DVA neurons , the SMD neurons directly sense head/neck muscle stretch and regulate muscle contractions , suggesting head steering locomotion in C . elegans is regulated mainly by a feedback system utilizing only a single neuronal cell type . In addition , recent studies have shown that SMD regulates the activity of other interneurons , including postsynaptic RIAs and extrasynaptic RMEs via cholinergic neurotransmission to set the amplitude of head bending [40 , 41] . This indicates dual roles for SMD in head locomotion: the regulation of steering via direct muscle contractions and the modulation of head bending amplitude via synaptic transmission to other postsynaptic target neurons . Previously , the TRP-1 and TPR-2 TRPC channels were shown to modulate nicotine-dependent behaviors by acting in command interneurons as receptor-operated channels [36] . Here , we identified a novel role for the TRP-1 and TRP-2 channels as putative stretch-sensing molecules in the proprioceptive SMDD neurons that regulate the proprioceptive feedback system that directs forward locomotion in C . elegans . First , trp-1 and trp-2 are coexpressed in the SMDD proprioceptive receptor neurons . Second , trp-1 trp-2 double mutants , but not single mutants , exhibit a ventral circling phenotype similar to that of SMDD-ablated animals . This indicates that TRP-1 and TRP-2 are redundant but necessary for SMDD-mediated head steering locomotion . Third , either TRP-1 or TRP-2 is sufficient to confer head/neck bending–dependent Ca2+ signals in the AWC chemosensory neuron . Fourth , TRP-1 and TRP-2 are functionally interchangeable with the two known proprioceptors C . elegans trp-4 or Drosophila trpγ . Although we could not completely rule out the possibility of an indirect and modulatory role of TRP-1/TRP-2 in stretch sensation [59–61] , we suggest that TRP-1 and TRP-2 are putative proprioceptor channels that act redundantly to detect head/neck bending in the SMDD proprioceptive neurons responsible for regulating dorsal head muscle contractions . What physiological role do TRP-1 and TRP-2 play in the SMDD neurons ? In general , TRP channels are nonselective Ca2+-permeable ion channels that permit Ca2+ influx in response to various stimuli [62] . In our Ca2+ imaging results , the SMDD neurons of trp-1 trp-2 double mutants still show oscillating calcium dynamics , but rather than being synchronized with dorsal head/neck bending , they are synchronized with ventral head/neck bending . This means that the SMDD and SMDV neurons fire synchronously upon ventral head/neck bending . Thus , in contrast to TPR-4 , which is required for the increased Ca2+ signals that appear in DVA neurons upon body bending , TRP-1 and TRP-2 are not required for Ca2+ signals in the SMDD neurons . Since the oscillating Ca2+ transients in the SMD neurons are completely abolished in the paralyzed unc-54 mutants , SMD Ca2+ signals obviously originate from body movements . These Ca2+ influxes may arise from a yet unidentified proprioceptor in the SMD processes that run along the body . This proprioceptor would detect body bending/body muscle stretch and generate Ca2+ transients . In Drosophila , the TRP channels Nanchung , Inactive , and NompC are coexpressed in the auditory neurons of both the chordotonal and Johnston’s organs to detect and transduce sound vibrations [63–65] . Although these channels are all expressed in the auditory neurons and all function in hearing , the activities of NompC and the Nanchung–Inactive complex are independent of one another [63] . It is also possible that putative proprioceptors among the ventral nerve cord motor neurons detect body bending and cause waves of body muscle contractions [66 , 67] . The VB1 ventral motor neurons are electrically coupled to the SMD neurons , and thus Ca2+ influx may propagate from these ventral motor neurons to the SMD neurons via gap junctions [26] . Recently , Fouad and colleagues showed that during forward locomotion , a midbody rhythmic signal or wave propagates from the midbody to the head via nonproprioceptive coupling [68] . Thus , we speculate that during forward locomotion , a rhythmic signal is transmitted from the VB1 motor neuron to the SMDV neurons . Moreover , the SMDV and SMDD neurons are also electrically coupled . Our working model is that during the forward movement , the oscillating calcium wave generated by midbody rhythm–generating units reaches at VB1 and causes ventral neck muscle contraction , and this calcium wave then transmits to the SMDV and SMDD , which synchronize the states of SMDV and SMDD together with that of VB1 , and elicits ventral head/neck muscle contractions . Then , SMDD detects dorsal head/neck bending via TRP-1/TRP-2 and changes phase of SMDD calcium transients from those of SMDV , which initiates dorsal head muscle contractions via cholinergic transmission from SMDV to dorsal head muscles . TRP-1 and TRP-2 in SMDD neurons thus seem to play a role in detecting head/neck bending , and the SMDD neurons themselves seem to integrate information about head/neck bending and body bending . They separate the SMDD neurons from the circuit of the SMDV neurons and ventral muscle contractions , orchestrating dorsal head muscle contractions so the animal can steer straight ( Fig 4H ) . In mice , ablation of proprioceptive systems also causes synchronized activation of muscles in the hip , knee , and ankles [69] . Together , we propose that synchronization of the locomotion circuits is a general consequence of the loss of function of proprioceptive neurons and receptor molecules , and distinct locomotion patterns require dynamic , homeostatic modulation of feedback signals between proprioceptive neurons and muscles .
All strains were maintained at 20°C [29] . The N2 Bristol strain was used as a wild-type strain . To generate the trp-1 trp-2 double mutants , trp-1 ( sy690 ) males were mated with trp-2 ( sy691 ) hermaphrodites , and the genomic deletion was confirmed by PCR ( trp-1-deletion_1_F: GGCTAAGTTCCTGTCTACCAC , trp-1-deletion_2_F: TCTGCTACTCGTAGGGGCTT , trp-1-deletion_R: CTGTTGACAATGAGGATGAGAG; trp-2-deletion_1_F: CTACGCACTGATGACGTGGA . trp-2-deletion_2_F: AGTCACTGCTCAGAGCTACC , trp-2-deletion_R: AGTACGCAAACAACGACTACAG ) . All the mutants and transgenic strains used in this study are listed in Table 1 . All the constructs created in this study were inserted into the pPD95 . 77 vector [70] . For the flp-22 and lad-2 promoter analysis , 2 . 7-kb and 7 . 3-kb promoter regions were amplified by PCR from N2 genomic DNA and used to generate flp-22p::gfp and lad-2p::gfp as previously described [38 , 71] . Deletions in the flp-22 and lad-2 promoter reporter constructs were generated by using various enzymes or PCR fusions . To generate transgenic worms , 50 ng of each reporter construct was injected , with 50 ng of unc-122p::dsRed as an injection marker . Among the various flp-22 promoter fragments , flp-22p-Δ4 was used as an SMD neuronal marker . A 2 . 6-kb fragment of the trp-1 promoter and a 2 . 9-kb fragment of the trp-2 promoter from the start codon were amplified by PCR and inserted into the pPD95 . 77 vector . For the rescue experiments , glr-1p-Δ1 ( for SMDD; a gift from Hannah Nicholas ) [39] , flp-7p ( for SMDV ) [38] , flp-22p-Δ4 ( for SMDD/V ) , and twk-16p ( for DVA; a gift from Shawn Xu ) [13] were fused with a trp-1 cDNA , a trp-2 cDNA , a trp-4 cDNA ( gift from Shawn Xu ) [36] , and a trpγ cDNA ( a gift from Craig Montell ) [8] . The trp-1 cDNA and the trp-2 cDNA were amplified by PCR from a cDNA library . With 50 ng of unc-122p::dsRed as an injection marker , 0 . 5 ng of the trp-1 , trp-2 , trp-4 , and trpγ cDNAs under the control of various promoters were injected into trp-1 trp-2 double mutants or trp-4 mutants . For ectopic expression of trp-1 cDNA or trp-2 cDNA in AWC , ceh-36p-Δ1 ( a gift from Piali Sengupta ) was fused with the trp-1 cDNA or trp-2 cDNA in the pPD95 . 77 vector , and gpa-4p was fused with the trp-1 cDNA in the pPD95 . 77 vector for ectopic expression in AWA , and ASI . 0 . 5 ng of each transgene was injected with 50 ng of unc-122p::dsRed as an injection marker . lad-2p-Δ1 and myo-3p were inserted into the ReaChR::mKate2 vector ( a gift from Henrik Bringmann ) [42 , 43] , and 100 ng of each transgene was injected with 50 ng of unc-122p::dsRed or unc-122p::gfp as an injection marker , respectively . To record animal locomotion , NGM agar plates were coated with 600 μl of Escherichia coli OP50 , incubated for 3 h , and allowed to fully dry . Bacterial lawn plates were prepared the day before behavior recordings . Well-fed young adult hermaphrodite worms were used to leave trajectories on bacterial lawn plates and recorded under a Leica High-performance Fluorescence Stereomicroscope ( M205FA ) using the Leica Application Suite Advanced Fluorescence Lite 3 . 5 software . To quantify the turning angle of the worm paths , 5 min of behavior video were collected into 30 s–interval images . A total of 10 images from each worm were used to measure the dorsal or ventral angles from the dorsoventral body positions during forward movement . From each image , at least 3 ventral and dorsal angles were measured using Image J , and the angle values were averaged . The averaged dorsal angles were then subtracted from the averaged ventral angles to obtain a turning angle . The turning angles were then color-coded along a brown-to-blue scale . Ventral circling was defined as dark brown , and dorsal circling was defined as dark blue . Twenty worms for each strain were analyzed to generate a locomotion pattern heat map . To measure wave length and wave width , the Leica Application Suite Advanced Fluorescence Lite 3 . 5 software was used to capture images of worm tracks on the bacterial lawn . Wave width was defined as the peak-to-trough distance of the sine wave , and wavelength was defined as the peak-to-peak distance of the sine wave . The average of 6 consecutive wave widths and wave lengths from each worm track was quantified . At least 50 worms for each strain were measured and analyzed . Well-fed young adult–stage worms were used to observe SMD and head muscle calcium activities . For freely moving conditions , each worm was transferred onto a 2% agarose pad on a glass slide and placed on a coverslip . Fluorescence time lapse images were acquired over the course of 80 s under a Zeiss Axio observer A1 with a 20× objective using the Image J software . At least 100 frames ( 20 s ) of continuous forward movement from each worm were selected and analyzed with a customized program that automatically normalizes SMD fluorescence intensity and subtracts the background . Head muscle activities were obtained together with SMD neuronal activities and analyzed as described above . To quantify SMD neuronal activity in the unc-54 mutants induced by head bending , a platinum wire was used to manually bend the heads of worms on the NGM agar plate . The resulting calcium intensities were observed under a Zeiss SteREO Discovery V8 . Young adult–stage flp-22p-Δ4::mCherry; flp-12p::gfp transgenic worms were anesthetized with 1 M sodium azide on the 2% agar pad . Transgenic worms coexpressing markers of both the SMD and SMB neurons ( flp-22p-Δ4::mCherry; flp-12p::gfp ) were used for precise ablation of the SMD cell bodies because the SMD and SMB neurons are so close to one another . After ablation , animals that exhibited GFP expression in the SMB neurons were selected [27 , 37] . A commercial femtosecond ( approximately 120 fs ) pulse laser system ( Insight Deepsee Dual , Spectra physics ) , employed as a light source ( 790 nm ) for nonlinear imaging in an Olympus IX83 microscope platform , was also used to kill the SMDD or SMDV neurons ( 56 mW illumination during 35 s ) . After these ablations , the worms were transferred to NGM agar plates immediately and allowed to recover for 14 h at 15°C . Mock-ablated worms were placed on the same agar pad to expose them to light and allowed to recover on separate NGM agar plates . Locomotion was observed and recorded over 5 min with the Leica High-performance Fluorescence Stereomicroscope M205FA using the Leica Application Suite Advanced Fluorescence Lite 3 . 5 software . After the behavioral recordings , the expression of flp-22p-Δ4::mCherry in the SMD neurons and flp-12p::gfp in the SMB neurons were confirmed under a Zeiss Axio observer A1 with a 40× objective . Only worms that specifically lost fluorescence of flp-22p-Δ4::mCherry in their SMD neurons but exhibited expression of flp-12p::gfp in the SMB neurons were counted as ablated worms . Young adult stage of wild-type and trp-1 trp-2 double-mutant animals were anesthetized with 100mM sodium azide on the 2% agar pad and placed on a top of an agarose pad . The label-free images were obtained under the coherent anti-Stokes Raman scattering microscopy , followed by the setting of the microscopy as previously described [50] . L4 transgenic worm larvae expressing ReaChR::mKate2 transgenes under the control of indicated promoters were transferred 12 h before the assay to either normal OP50 plates or OP50-retinal plates containing 1 mM all-trans-retinal ( ATR , Sigma ) . OP50-retinal plates were prepared by seeding 200 μl OP50 with 2 μl 100 mM ATR ( Sigma ) in 100% ethanol . To stimulate ReaChR , we illuminated the NGM plates with 565 nm LED at roughly 0 . 05 mW/mm as measured with an optical power/energy meter . We recorded at least 40 young adult hermaphrodites per strain in the presence or absence of ATR under a custom automated worm-tracking system . The animals were allowed to move on the NGM agar plates for at least 1 min . Then , the recordings began with 10 s in the absence of green light , followed by 10 s of green light stimulation , and finally another 10 s without green light . Circling behavior was determined within 1 s after supplying the green light stimulus . The JMP10 software ( SAS ) was used as described to analyze time series of head bending angles and calcium fluorescence intensities for a cross-correlation analysis [40] . The time lag was 20 s , and head position was used as an input . Peak correlations are the correlation values between head bending and SMD activity at lag 0 s and are compared using the ANOVA test . | Proprioception provides the nervous system with feedback about body posture in animals and is essential for the generation of coherent locomotive behaviors , such as walking , running , or crawling . However , little is known about the identity of proprioceptive receptors that sense body movement to regulate locomotion and the extent to which proprioception modulates sensorimotor coordination . Here , we analyze the molecular mechanisms that control head steering locomotion of Caenorhabditis elegans . We show that this movement is regulated by the transient receptor potential cation ( TRPC ) channels TRP-1 and TRP-2 and the SMDD proprioceptive neurons . We observe that mutant animals for both channels are defective in head steering locomotion and that ectopic expression of TRP-1 or TPR-2 in a C . elegans chemosensory neuron confers head bending–dependent responses , suggesting roles for these channels in proprioception . We also find that SMDD neurons are both necessary and sufficient to generate head steering locomotion via the two channels . Moreover , we demonstrate that the proprioceptive system mediates locomotion coordination by desynchronizing activities in motor systems . We conclude that two TRPC channels in collaboration with the proprioceptive receptor SMDD neurons control head steering in worms during forward locomotion . | [
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"i... | 2018 | A sensory-motor neuron type mediates proprioceptive coordination of steering in C. elegans via two TRPC channels |
Invasive candidiasis , mainly caused by Candida albicans , is a serious healthcare problem with high mortality rates , particularly in immunocompromised patients . Innate immune cells express pathogen recognition receptors ( PRRs ) including C-type lectin-like receptors ( CLRs ) that bind C . albicans to initiate an immune response . Multiple CLRs including Dectin-1 , Dectin-2 and Mincle have been proposed individually to contribute to the immune response to C . albicans . However how these receptors collaborate to clear a fungal infection is unknown . Herein , we used novel multi-CLR knockout ( KO ) mice to decipher the individual , collaborative and collective roles of Dectin-1 , Dectin-2 and Mincle during systemic C . albicans infection . These studies revealed an unappreciated and profound role for CLR co-operation in anti-fungal immunity . The protective effect of multiple CLRs was markedly greater than any single receptor , and was mediated through inflammatory monocytes via recognition and phagocytosis of C . albicans , and production of C . albicans-induced cytokines and chemokines . These CLRs were dispensable for mediating similar responses from neutrophils , likely due to lower expression of these CLRs on neutrophils compared to inflammatory monocytes . Concurrent deletion of Dectin-1 and Dectin-2 , or all three CLRs , resulted in dramatically increased susceptibility to systemic C . albicans infection compared to mice lacking a single CLR . Multi-CLR KO mice were unable to control fungal growth due to an inadequate early inflammatory monocyte-mediated response . In response to excessive fungal growth , the multi-CLR KO mice mounted a hyper-inflammatory response , likely leading to multiple organ failure . Thus , these data reveal a critical role for CLR co-operation in the effective control of C . albicans and maintenance of organ function during infection .
Fungal infections including invasive candidiasis are a serious healthcare problem particularly for patients who are immunocompromised , have undergone invasive clinical procedures or have suffered from a major trauma . Invasive candidiasis has unacceptably high mortality rates of 46–75% [1] . Candida albicans is the main cause of hospital acquired bloodstream Candida infections [2] . These infections frequently arise from gastrointestinal colonisation and migration through the mucosal barrier or from colonisation of an intravenous catheter . The early inflammatory response to systemic Candida infections is dominated by innate immune cells such as inflammatory monocytes , neutrophils , macrophages and dendritic cells ( DCs ) [3] . These cells express pathogen recognition receptors ( PRRs ) including C-type lectin-like receptors ( CLRs ) , Toll-like receptors ( TLRs ) , nucleotide-binding oligomerization domain ( NOD ) -like receptors ( NLRs ) and retinoic acid-inducible gene-I ( RIG-I ) -like receptors ( RLRs ) that bind C . albicans and initiate an immune response [4] . Multiple CLRs such as Dectin-1 , Dectin-2 and Mincle have individually been proposed to participate in the immune response to C . albicans . All three receptors bind carbohydrates in the fungal cell wall , with Dectin-1 binding β-glucans and Dectin-2 and Mincle binding mannosylated ligands . All three CLRs signal through a Syk-PKCδ-Card9-NFκB pathway and through Syk-MAPK pathways [5–7] . In addition , Dectin-1 can activate NFAT , IRF1/5 and a non-canonical NFκB pathway via Raf-1 and Syk [8–10] . Dectin-1 induces multiple anti-fungal responses such as phagocytosis , cytokine production , cell recruitment , reactive oxygen species ( ROS ) production , canonical and non-canonical inflammasome activation and Th1 and Th17 responses [6 , 9 , 11–14] . In addition , Dectin-1 can prevent damaging neutrophil extracellular trap ( NET ) release by enhancing the phagocytosis of small yeasts , thereby minimizing pathology [15] . Dectin-1 KO mice exhibit decreased survival and increased fungal burdens during systemic C . albicans infection [14] . This protective anti-fungal effect is strain specific due to in vivo adaptation of the fungal cell wall [16 , 17] . The importance of Dectin-1 for controlling fungal infections was confirmed by the discovery of a premature stop codon polymorphism in human Dectin-1 ( CLEC7A ) , which was identified in a family with a high prevalence of mucocutaneous candidiasis and onychomycosis . This polymorphism is also associated with increased Candida colonisation in stem cell transplant patients and increased susceptibility to invasive aspergillosis [18–20] . Dectin-2 plays a role in phagocytosis , cytokine production , cell recruitment and Th1 and Th17 responses during systemic infection with C . albicans [6 , 7 , 21] . Dectin-2 KO mice display decreased survival and increased fungal burdens during systemic infection with C . albicans [7] . In addition , various polymorphisms in human Dectin-2 ( CLEC6A ) , either alone or in combination with additional genes , are associated with aspergillosis and pulmonary cryptococcosis [22–24] . The function of Mincle during C . albicans infection is currently under debate . Wells et al showed that C . albicans induced Mincle expression , recruited Mincle to the phagocytic cup , promoted TNF production in a Mincle-dependent manner and Mincle KO mice displayed increased fungal burdens during systemic C . albicans infection [25] . However , another study showed that Mincle did not bind C . albicans or any other Candida spp . [26] . The Card9 pathway downstream of these three CLRs is important for C . albicans-induced cytokine production , but not zymosan internalisation [27] . In addition , C . albicans-induced Th1 and Th17 responses were defective in splenocytes from Card9 KO mice [28] . Card9 KO mice display dramatically decreased survival and increased fungal burden compared to WT controls during systemic infection with C . albicans [27] . Further , an early stop polymorphism in human CARD9 was identified in a family where several family members suffered from recurrent fungal infections , and at least 2 family members had previously died from invasive Candida infection of the brain . These patients had reduced circulating IL-17+ T cells [29] . In addition , in a CARD9 deficient patient suffering from a chronic invasive Candida infection of the brain , there was a lack of Candida-induced cytokines from monocytes , a defect in neutrophil Candida killing that was independent of respiratory burst generation and reduced CD4+ Th17 lymphocytes [30] . Finally , Card9 has been shown to mediate neutrophil recruitment to the brain and subsequent fungal clearance during systemic infection with C . albicans in mice and in a CARD9 deficient patient [31] . The dramatic effects in Card9 KO mice and CARD9 deficient patients are likely due to the loss of signalling in response to multiple receptors including various CLRs , NLRs and TLRs . In consideration of these findings , it is likely that the three CLRs Dectin-1 , Dectin-2 and Mincle both collaborate to maintain effective CARD9 signalling and have collective independent signalling roles to control the innate immune response to C . albicans infection . Here we decipher the individual , collaborative and collective roles of Dectin-1 , Dectin-2 and Mincle during systemic infection with C . albicans . Using novel multi-CLR KO mice , we found that all three receptors collaborate to bind C . albicans . Dectin-1 and Dectin-2 collaborate to induce the protective effect of inflammatory monocytes during systemic C . albicans infection while they are dispensable for various neutrophil-mediated anti-fungal responses . This is likely due to the different expression pattern of these CLRs on inflammatory monocytes and neutrophils . In the absence of Dectin-1 and Dectin-2 together or all three CLRs , these multi-CLR KO mice are unable to control fungal growth due to an inadequate early innate response . These mice then mount an excessive inflammatory response likely resulting in kidney immunopathology and multi-organ failure . Together these CLRs mediate the various immune responses required for clearance of C . albicans and to maintain organ function during infection .
CLR KO mice used in this study are shown in Table 1 . Dectin-1 KO mice [14] generated on a 129 background were backcrossed for a total of 11 generations to the C57BL6/J background . Mincle KO mice [25] were obtained from the Mutant Mouse Resource and Research Center ( MMRRC ) . Dectin-2 KO mice [7] were sourced from Tokyo University of Science . As the Dectin-2 gene cluster ( Clec4n , Clec4d and Clec4e ) and Dectin-1 ( Clec7a ) are located on mouse chromosome 6 , ~6cM apart ( S1 Fig ) , a unique targeting strategy involving cross-breeding to identify rare recombination events and Crispr-Cas9 technology was employed to generate double ( DKO ) and triple ( TKO ) KO mice . The various multi-CLR KO mouse strains were then bred to homozygosity . Mincle-Dectin-1 DKO1 mice were generated by crossing Mincle KO with Dectin-1 KO mice . Sigma Advanced Genetic Engineering ( SAGE ) generated Mincle-Dectin-2 DKO2 mice by targeting Dectin-2 in Mincle KO mice using Crispr-Cas9 technology . Briefly , SAGE designed donor plasmids with homologous arms and an insert sequence containing 3-frame stop codons upstream of a LoxP site . The following sequence ( GAGTGACTGATAACTTCGTATAGCATACATTATACGAAGTTATCGAT ) was inserted into exon 3 of Clec4n ( Dectin-2 ) in Mincle KO mice ( S1 Fig ) . Dectin-1-Dectin-2 DKO mice were generated by crossing Dectin-1 KO with Dectin-2 KO mice . Mincle-Dectin-2-Dectin-1 TKO1 mice were generated by crossing Mincle-Dectin-2 DKO2 mice with Dectin-1 mice ( Table 1 ) . Mice were age and gender matched for experiments . Female mice were co-housed for 1–3 weeks prior to in vivo experiments . For various experiments where male mice were used , bedding was swapped between cages for 3–7 days prior to experiments . The mice were maintained and handled according to institutional and UK Home Office guidelines . This study was performed in strict accordance with the Project License ( 30/2938 , P05D6A456 ) and procedures that were approved by Cardiff University Animal Welfare and Ethical Review Body and the UK Home Office . The animal care and use protocol adhered to the Animals ( Scientific Procedures ) Act 1986 . Flow cytometry antibodies against Ly6C , Ly6G , CD11b , F4/80 , CD11c , MHCII , B220 , CD19 , CD3 , CD4 , CD8 , CD49b , TLR2 , TLR4 , mannose receptor ( MR ) , IFN-γ , IL-17 , TNF and isotype controls were purchased from Biolegend . Dectin-1 antibody ( AbD Serotec ) , Dectin-2 antibody D2 . 11E4 [32] and Mincle/Clec4e antibody ( Abnova ) were used in this study . IFN-γ , IL-17 , G-CSF , MIP2 , MIP1α and MCP1 ELISAs were purchased from R&D while IL-1β , IL-6 , IL-10 , IL-12p40 and TNF ELISAs were purchased from Invitrogen . Candida albicans SC5314 ( ATCC ) was plated on YPD agar , cultured for 16–20 h in YPD broth , washed three times with PBS and resuspended at the required concentration in PBS . Age matched ( 8–12 weeks old ) female mice were injected i . v . with 100μl of C . albicans in PBS . Mice were monitored and weighed daily . Experiments were continued for a maximum of 30 days post-infection . Kidneys , brains and spleens were harvested . The left kidney was placed in PBS , homogenised and serial dilutions were plated on YPD agar containing 50μg/ml chloramphenicol . The plates were cultured for 24 h and CFU were calculated per g organ . Alternatively , the left kidney was diced into small pieces , incubated at 37°C for 30 min in DMEM/F12 medium ( Gibco ) including 0 . 2mg/ml Liberase TL ( Roche ) and 100U/ml DNase I ( Invitrogen ) . Following digestion , DMEM/F12 medium containing 10% fetal bovine serum ( FBS ) was added , filtered through 40μm cell strainers ( BD ) and then centrifuged at 4°C , 500g for 5 min . The pellet was resuspended with ice-cold PBS as a single cell suspension for further staining procedures . The right kidney was placed in 10% formalin , embedded in paraffin wax blocks , processed using an automated tissue processor , sectioned at 4μm , deparaffinised and stained for H&E and PAS according to standard protocols . The spleens were homogenized , red blood cells were lysed with ACK lysis buffer and the cells were washed with PBS and IMDM . Cells were resuspended in IMDM containing 10% FBS , 2mM L-glutamine , penicillin/streptomycin , 50μM 2-mercaptoethanol plated and restimulated with C . albicans for 48 h in the presence of Amphotericin B or with PMA ( 50ng/ml ) and Ionomycin ( 0 . 5μg/ml ) in the presence of 0 . 2% Brefeldin A for 4 h . IFN-γ and IL-17 levels were measured by ELISA in C . albicans-stimulated cells while PMA/Ionomycin-induced IFN-γ and IL-17A producing cells were analysed by flow cytometry . Alternatively , the splenocytes were fixed in 1% paraformaldehyde for 20 min after the red blood lysis and the PBS wash . The cells were centrifuged and resuspended in PBS . The cells were then stained with antibodies for myeloid cell markers and analysed by flow cytometry . Kidneys were examined at 4μm and the cortex and medulla individually assessed for the presence of inflammatory cells including neutrophils and lymphocytes / plasma cells and scored as follows: Score 0 = no inflammation , Score 1 = < 3 foci of inflammation , Score 2 = 4 to 6 foci of inflammation , Score 3 = > 6 foci of inflammation , but less than 25% of kidney affected , Score 4 = > 25% of kidney affected . Scoring was performed by a pathologist blinded to the experimental groups . To recruit primary myeloid cells , mice were injected intraperitoneally with 0 . 5ml 2% ( w/v ) BIOgel P-100 polyacrylamide beads ( BIO-Rad ) , 16–18 h prior to peritoneal lavage . Inflammatory cells were collected after sacrifice by peritoneal lavage with ice-cold RPMI containing 10% FBS and 1% penicillin/streptomycin . To remove BIOgel beads from cells , the cells were filtered through 40μm cell strainers . Cells were washed twice with RPMI containing 10% FBS and 1% penicillin/streptomycin . C . albicans was washed three times with PBS and resuspended at 1x108/ml in PBS . Candida was labelled with cell trace far red ( Invitrogen ) at a concentration of 3 . 4μg/ml for 30 min while rotating at RT . Candida was washed three times with PBS and resuspended at the desired concentration in RPMI containing 10% FBS and 1% penicillin/streptomycin . 4x105 BIOgel recruited inflammatory cells were plated in 100μl RPMI containing 10% FBS and 1% penicillin/streptomycin in ultra-low attachment 96 well round bottom plates . 4x105 cell trace far red labelled C . albicans in 100μl RPMI containing 10% FBS and 1% penicillin/streptomycin were added to the inflammatory cells and incubated at 37°C for 15 min . Cells were centrifuged and supernatants were removed . 100μl of 5μM dihydrorhodamine 123 ( DHR-123 ) ( Invitrogen ) in warmed PBS was added to cells and incubated at 37°C for 15 min . Cells were centrifuged , supernatants were removed , and cells were washed once with ice-cold PBS . Cells were stained with antibodies for Ly6G and CD11b and analysed by flow cytometry or Amnis Imagestreamx MkII . BIOgel recruited inflammatory cells were recovered by peritoneal lavage and washed as described above . Cells were stained with antibodies against Ly6G , CD19 and CD11b . Ly6G-CD11b+CD19- inflammatory monocytes/macrophages and Ly6G+CD11b+CD19- neutrophils were purified by cell sorting on a FACS Aria cell sorter . To opsonise C . albicans , 5x107 C . albicans were placed in a 1 . 5ml Eppendorf tube and resuspended in 200μl mouse serum . This was incubated at 37°C for 15 min with frequent mixing . Opsonised C . albicans was washed 3x with PBS prior to use . For the luminol assay , purified cells were seeded at 1x105 cells per well in a 96-well luminescence plate in 100μl DMEM with no phenol red containing 10% FBS , 2mM L-glutamine and 800μM luminol . The plate was incubated for 30 min at 37°C , after which 100μl media , 1x105 C . albicans , opsonised C . albicans or PMA ( 400ng/ml ) was added . The plate was immediately placed in a luminescence plate reader at 37°C and luminescence readings were measured every 8 . 7 min for 3 . 5 h . For the candidacidal assay , purified cells were seeded at 1x105 cells per well in a 96-well round bottom plate in 100μl DMEM with no phenol red containing 10% FBS and 2mM L-glutamine . 100μl media , 1x105 C . albicans or opsonised C . albicans was added . The plate was incubated for 3 h at 37°C . Cells were lysed with 200μl 1% Triton X-100 , and Candida were plated on YPD agar and incubated at 37°C for 24 h . The percentage of Candida killed by monocytes/macrophages or neutrophils was determined by [1- ( number of C . albicans incubated with cells ) / ( number of C . albicans incubated without cells ) ]x100 . 4x105 BIOgel recruited inflammatory cells were plated in 100μl RPMI containing 10% FBS and 1% penicillin/streptomycin in ultra low attachment 96 well round bottom plates . 4x105 cell trace far red labelled C . albicans in 100μl RPMI containing 10% FBS and 1% penicillin/streptomycin were added to the inflammatory cells and incubated at 37°C for 3 h in the presence of 0 . 2% Brefeldin A . Cells were stained with live/dead fixable aqua dead cell stain kit ( Invitrogen ) , antibodies against Ly6G , CD11b and CD19 and intracellular TNF levels were measured by flow cytometry . BIOgel recruited inflammatory cells were stained with antibodies against Ly6G and CD11b . Cells and cell trace far red labelled C . albicans were mixed at 1:1 ratio and analysed by Amnis Imagestreamx MkII over 1 . 5 h at RT . An object mask on CD11b and a morphology mask on C . albicans was applied on pre-gated neutrophils or monocytes which were best in focus ( Gradient RMS_M01_BRF ) using Ideas software 6 . 2 . An internalisation feature was used [Internalisation_Object ( M02 , CD11b , Tight ) _C . albicans] to differentiate between cells that had internalised C . albicans versus cells that had C . albicans bound externally . BIOgel recruited inflammatory cells were recovered by peritoneal lavage and washed as described above . Cells were stained with antibodies against Ly6G , CD4 , CD8 , Ly6C , F4/80 , CD19 , DX5 and CD11b . Ly6ChiLy6G-CD11b+F4/80+CD4-CD8-DX5-CD19- inflammatory monocytes were purified by cell sorting on a FACS Aria cell sorter . Inflammatory monocytes were incubated at 37°C with C . albicans at 3:1 Cells:Candida ratio for 3 h in RPMI containing 10% FBS , 1% penicillin/streptomycin , 1% L-glutamine , 0 . 5% HEPES and 50μM 2-mercaptoethanol . Cell pellets were snap frozen and stored in -80°C . RNA was extracted using a RNeasy mini kit ( Qiagen ) . Total RNA quality and quantity was assessed using Agilent 2100 Bioanalyser and a RNA Nano 6000 kit ( Agilent Technologies ) . Total RNA with a RIN value >7 was depleted of ribosomal RNA using the NEBNext rRNA Depletion Kit ( Human/Mouse/Rat ) , ( New England BioLabs , NEB ) and the sequencing libraries were prepared using the NEB Ultra II Directional RNA Library Prep Kit for Illumina ( NEB ) . Libraries were normalised to 10nM , pooled and sequenced using a 75-base paired-end ( 2x75bp PE ) dual index read format on the Illumina HiSeq4000 according to the manufacturer’s instructions . Reads from sequencing were trimmed with Trimmomatic [33] and assessed for quality using FastQC ( https://www . bioinformatics . babraham . ac . uk/projects/fastqc/ ) , using default parameters . Reads were mapped to the mouse GRCm38 reference genome using STAR [34] and counts were assigned to transcripts using featureCounts [35] using the GRCm38 . 84 Ensembl gene build GTF . Both the reference genome and GTF were downloaded from the Ensembl FTP site ( http://www . ensembl . org/info/data/ftp/index . html/ ) . RNAseq data has been deposited to ArrayExpress ( https://www . ebi . ac . uk/arrayexpress/ ) under accession number E-MTAB-8030 . Differential gene expression analyses used the DESeq2 Bioconductor package [36] . Genes were filtered from the analysis where read count < 10 over all replicates and conditions . Normalised gene expression values ( FPKM ) , used for downstream cluster analysis , were calculated for all significantly differentially expressed genes ( significance: adjusted p value < 0 . 05 , Benjamini-Hochberg correction for multiple testing ) . Cluster analysis were performed in Genesis [37] where FPKM count data were z-score transformed over genes . Pathway term-enrichment analyses of each cluster was performed in Ingenuity IPA ( QIAGEN: Inc . https://www . qiagenbioinformatics . com/products/ingenuity-pathway-analysis ) Bone marrow cells were flushed out of the femurs and tibiae of mice . Red blood cells were lysed with ACK lysis buffer and the cells were washed with PBS . Monocytes were magnetically sorted using a negative selection bone marrow monocyte isolation kit . Cells were incubated with C . albicans at 3:1 Cells:Candida ratio for 24 h . 2 . 5μg/ml Amphotericin B was added 2 h after stimulation . Cell culture supernatants were recovered and assayed for cytokine/chemokine by ELISA ( Invitrogen/R&D ) . Age matched male mice were injected i . p . with 1x105 CFU of C . albicans in 100μl PBS , 4 h prior to peritoneal lavage . Inflammatory cells were collected after sacrifice by peritoneal lavage with 1ml ice-cold PBS . Cells were counted using a MUSE cell counter , cells were centrifuged and lavage fluid was removed and placed in a fresh 1 . 5ml eppendorf tube and frozen at -80°C . Cells were stained with antibodies against Ly6G , Ly6C , CD11b , F4/80 , CD11c , MHCII and CD19 . Myeloid cell recruitment was measured by flow cytometry . Cytokine/chemokine levels in the lavage fluid were measured by ELISA . Bone marrow cells were flushed out of the femurs and tibiae of mice . Red blood cells were lysed with ACK lysis buffer and the cells were washed with PBS . Monocytes were magnetically sorted using a negative selection bone marrow monocyte isolation kit . Monocytes were further purified to Ly6ChiLy6G-CD11b+CD4-CD8-CD19-CD49b-Cd11c- cells by FACS sorting on a FACS Aria cell sorter . Cells were 93–99% viable post-sort . 3-4x106 Ly6Chi monocytes from wildtype ( WT ) or Min-D2-D1 TKO1 mice were injected intravenously into Ccr2 KO mice followed by i . v . injection of 1 . 5x105 CFU of C . albicans in PBS . Mice were weighed and monitored daily for 3 days . Kidneys and brains were placed in PBS , homogenised and serial dilutions were plated on YPD agar containing 50μg/ml chloramphenicol . The plates were cultured for 24 h and CFU were calculated per g organ . Bone marrow cells were flushed out of the femurs and tibiae of mice . Red blood cells were lysed with ACK lysis buffer and the cells were washed with PBS . Monocytes were magnetically sorted using a negative selection bone marrow monocyte isolation kit . Cells were labelled with 5μM CFSE in PBS containing 0 . 1% BSA for 10 min at 37°C . RPMI containing 10% FBS was added to the cells and cells were incubated on ice for 5 min . Cells were washed with PBS and 2 . 5x106 monocytes from WT or Min-D2-D1 TKO1 mice were injected intravenously into Ccr2 KO mice followed by i . v . injection of 1 . 5x105 CFU of C . albicans in PBS . After 24 h , kidneys were placed in PBS . The left kidney was diced into small pieces , incubated at 37°C for 30 min in DMEM/F12 medium including 0 . 2mg/ml Liberase TL and 100U/ml DNase I . Following digestion , DMEM/F12 medium containing 10% FBS was added , filtered through 40μm cell strainers and then centrifuged at 4°C , 500g for 5 min . The pellet was resuspended with ice-cold PBS as a single cell suspension for further staining procedures . The right kidney was homogenised and serial dilutions were plated on YPD agar containing 50μg/ml chloramphenicol . The plates were cultured for 24 h and CFU were calculated per g organ . Chemokine levels in the kidney homogenates were determined by ELISA . Data are presented as means +/- s . e . m . and are representative or cumulative data from the indicated number of independent experiments . Data was tested for normality and if data followed a Gaussian distribution then one-way ANOVA followed by Bonferroni’s post-test or 2-way ANOVA was used for statistical analysis when multiple groups were analysed or Student’s t test was used for statistical analysis when two groups were analysed . A Gaussian distribution was assumed for experiments with small sample numbers . When data did not follow a Gaussian distribution , it was transformed by Y = sqrt ( Y+0 . 5 ) for data containing zeros or by Y = logY for other data [38] and analysed by Student’s t test or one-way ANOVA followed by Bonferroni’s post-test if it then followed a Gaussian distribution . If data still did not follow a Gaussian distribution it was analysed by non-parametric Mann-Whitney test or Kruskal-Wallis test followed by Dunn’s post-test . Statistical significance was set at *p<0 . 05 **p<0 . 005 ***p<0 . 001 .
As Dectin-1 , Dectin-2 and Mincle have individually been proposed to play roles in response to C . albicans [7 , 14 , 25] , we aimed to identify collaborative and redundant roles of these CLRs . To this end we generated mice deficient in different combinations of these CLRs ( Table 1 ) . We confirmed appropriate loss of CLR protein expression in bone marrow derived dendritic cells ( BMDCs ) ( S1 Fig ) , inflammatory monocytes/macrophages ( S1 Fig ) and neutrophils ( S1 Fig ) from the multi-CLR KO mice generated in this study . Inflammatory monocytes/macrophages displayed higher expression of Dectin-1 and Dectin-2 than neutrophils while Mincle expression was higher on neutrophils ( S1 Fig ) . As expected , expression of additional receptors such as MR , TLR2 , TLR4 and CD14 was unaffected on inflammatory monocytes/macrophages from the various multi-CLR KO mice ( S1 Fig ) . The multi-CLR KO mice were viable , had no gross abnormalities and had normal differential splenocyte counts ( S1 Table ) . In order to determine the collective and contributing roles of these three CLRs during systemic infection with C . albicans , we injected groups of WT and multi-CLR KO mice intravenously with low ( 1 . 5x104 CFU ) , medium ( 5x104 CFU ) or high ( 1 . 5x105 CFU ) doses of C . albicans SC5314 . Dectin-1-Dectin-2 DKO and Mincle-Dectin-2-Dectin-1 TKO1 mice displayed marked susceptibility to systemic infection with C . albicans with both medium ( Fig 1A ) and high ( Fig 1B ) dose infection . All Dectin-1-Dectin-2 DKO and Mincle-Dectin-2-Dectin-1 TKO1 mice infected with a medium or high dose of C . albicans succumbed to the infection by day 6 ( by humane end-point ) and some Dectin-1-Dectin-2 DKO and Mincle-Dectin-2-Dectin-1 TKO1 mice infected with a low dose of C . albicans even succumbed within 6 days of infection ( Fig 1C ) . Dectin-1 and Mincle-Dectin-1 DKO1 mice showed significant susceptibility to systemic infection with C . albicans with both medium ( Fig 1A ) and high ( Fig 1B ) dose , however this effect was much less profound than that observed in Dectin-1-Dectin-2 DKO and Mincle-Dectin-2-Dectin-1 TKO1 mice . Dectin-2 and Mincle-Dectin-2 DKO2 mice only showed increased susceptibility to systemic infection with C . albicans with high dose infection ( Fig 1B ) but not with medium dose infection ( Fig 1A ) . In comparison , Mincle KO mice did not show substantial susceptibility to systemic infection with C . albicans with any of the tested doses ( Fig 1A and 1B ) . The CLR KO mice with highest susceptibility ( Dectin-1-Dectin-2 DKO and Mincle-Dectin-2-Dectin-1 TKO1 ) to systemic infection with C . albicans ( Fig 1A and 1B ) displayed the highest fungal burden in the kidneys and brains with low dose infection 6–7 days post-infection ( Fig 1C and 1D ) . Similar effects were observed in mice infected with medium dose ( S2 Fig ) or high dose ( S2 Fig ) infection at humane end point or 30 days post-infection . Nodules of Candida were visibly evident on the kidneys of Dectin-1-Dectin-2 DKO and Mincle-Dectin-2-Dectin-1 TKO1 mice ( Fig 1E ) . These data indicate that of the single KO mice , Dectin-1 is most important for C . albicans clearance followed by Dectin-2 , and loss of both of these receptors severely diminishes control of systemic C . albicans infection . Mincle deficiency alone or in combination with Dectin-1 , Dectin-2 or Dectin-1 and Dectin-2 had limited impact indicating that Mincle is dispensable for clearance of systemic infection . As the Dectin-1-Dectin-2 DKO and Mincle-Dectin-2-Dectin-1 TKO1 mice displayed increased susceptibility to systemic C . albicans infection and increased fungal burden , we next examined immune cell recruitment to the kidneys of these mice . We observed increased numbers of myeloid cells including Ly6Chi monocytes/macrophages and neutrophils in the kidneys of Dectin-1-Dectin-2 DKO and Mincle-Dectin-2-Dectin-1 TKO1 mice compared to WT mice as early as 20 h post-infection ( S3 Fig ) and also at 4 days post-infection ( Fig 2A ) . In agreement with this , the total number of CD45+ cells was increased in the kidneys of the multi-CLR KO mice compared to WT mice ( Fig 2B ) . By day 6 post-infection , we observed that WT mice almost completely cleared low dose C . albicans from their kidneys while Dectin-1-Dectin-2 DKO and Mincle-Dectin-2-Dectin-1 TKO1 mice displayed large areas/abscesses of Candida growth , sometimes in hyphal form ( Fig 2C–2E ) . While kidneys from WT mice displayed limited and predominantly dispersed chronic inflammation with sparse neutrophils 6 days post-infection , kidneys from Dectin-1-Dectin-2 DKO and Mincle-Dectin-2-Dectin-1 TKO1 mice displayed extensive mixed inflammation affecting the cortex , medulla and renal pelvis with focal extension into surrounding adipose tissue ( Fig 2F–2H ) . These multi-CLR KO kidneys showed multi-focal suppurative granulomatous inflammation containing central neutrophilic microabscesses with frequent Candida identification , surrounded by macrophages and chronic inflammatory cells . In some multi-CLR KO cases , occasional kidneys developed cystic degeneration . Similarly , at 4 days post-infection , we observed increased numbers of splenic myeloid cell populations including Ly6Chi monocytes and neutrophils and total splenocytes in the susceptible mice strains compared to WT mice ( S4 Fig ) . By 6 days post-infection , splenocyte numbers in the multi-CLR KO mice continued to increase compared to WT mice ( S4 Fig ) . This was not observed in the other single or double KO strains ( S4 Fig ) . At 6 days post-infection the total number of T cells , CD8+ T cells and/or NK cells were also increased in these multi-CLR KO mice ( S4 Fig ) . We then restimulated splenocytes from these infected mice with PMA and Ionomycin , to examine the ability of these cells to produce IFN-γ and IL-17 . This mainly induced an IFN-γ response with a much smaller IL-17 response . Due to the splenomegaly in Dectin-1-Dectin-2 DKO and Mincle-Dectin-2-Dectin-1 TKO1 mice , the total number of IFN-γ producing cells were increased ( S4 Fig ) . Upon restimulation of the splenocytes with live C . albicans , the multi-CLR KO mice displayed a trend towards increased IFN-γ production although this did not always reach significance ( S4 Fig ) . These kidney and splenic data indicate that uncontrolled fungal growth in Dectin-1-Dectin-2 DKO and Mincle-Dectin-2-Dectin-1 TKO1 mice is associated with persistent/prolonged inflammatory cell recruitment which may contribute to tissue immunopathology and organ failure . As inflammatory monocytes , macrophages and neutrophils contribute to protection during the early stages of systemic infection with C . albicans [39 , 40] , we examined the collective and contributing roles of Dectin-1 , Dectin-2 and Mincle to C . albicans recognition by myeloid cells . BIOgel polyacrylamide beads were injected intraperitoneally to elucidate inflammatory myeloid cells including neutrophils and monocytes/macrophages [41] . The different KO strains demonstrated similar recruitment of inflammatory monocytes/macrophages ( Fig 3A ) and neutrophils ( Fig 3B ) in response to BIOgel . These cells were recovered from the peritoneal cavity of WT and multi-CLR KO mice and incubated ex vivo with cell trace far red-labelled live C . albicans . The percentage of inflammatory monocytes/macrophages ( Ly6G-CD11b+ ) and neutrophils ( Ly6G+CD11b+ ) interacting with C . albicans were measured by flow cytometry . The inflammatory monocyte/macrophage cell population is Ly6G-CD11b+Ly6Chi/loF4-80+ ( S5 Fig ) . Inflammatory monocytes/macrophages lacking Dectin-1 , Dectin-2 or Mincle individually showed no major defects in C . albicans recognition after 15 min incubation . However , inflammatory monocytes/macrophages lacking any two or all three of these CLRs showed significant defects in C . albicans recognition/binding compared to WT cells ( Fig 3C and S5 Fig ) . In addition , Mincle-Dectin-2 DKO2 cells , Dectin-1-Dectin-2 DKO and Mincle-Dectin-2-Dectin-1 TKO1 inflammatory monocytes/macrophages showed significant defects in C . albicans binding compared to Dectin-2 KO cells , while Dectin-1-Dectin-2 DKO and Mincle-Dectin-2-Dectin-1 TKO1 inflammatory monocytes/macrophages showed significant defects in C . albicans binding compared to Dectin-1 KO cells ( Fig 3C ) . In contrast , neutrophils deficient in expression of individual or multiple CLRs showed no major defects in C . albicans binding ( Fig 3D and S5 Fig ) suggesting the involvement of additional receptors . Using an Amnis Imagestreamx MkII , we confirmed a similar trend towards reduced recognition and internalisation of C . albicans by Mincle-Dectin-2-Dectin-1 TKO1 inflammatory monocytes/macrophages over 1 . 5 h ( Fig 3E and S6 Fig ) . In addition , we found that the mean number of C . albicans yeast particles internalised per WT inflammatory monocyte/macrophage is ~4 times greater than the mean number of C . albicans yeast particles internalised per Mincle-Dectin-2-Dectin-1 TKO1 inflammatory monocyte/macrophage ( Fig 3E ) . However , no major differences were found for recognition or internalisation by neutrophils ( Fig 3F and S6 Fig ) . Some of the differences between inflammatory monocytes/macrophages and neutrophils are likely due to differences in expression of the CLRs ( S1 Fig ) and other receptors between these cell types . These data indicate that while Mincle is not required for clearance of C . albicans in vivo , it still contributes to recognition of C . albicans by inflammatory monocytes/macrophages in addition to the main CLRs , Dectin-1 and Dectin-2 , while additional receptors are likely to be important for this function in neutrophils . ROS production is considered important for protecting against Candida infections [42] . Therefore , we also examined the collective and contributing roles of Dectin-1 , Dectin-2 and Mincle to C . albicans-induced ROS production by inflammatory monocytes/macrophages and neutrophils . We found that cells lacking Dectin-1 , Dectin-2 or Mincle individually showed no major defects in C . albicans-induced ROS production by measuring Dihydrorhodamine 123 ( DHR-123 ) fluorescence . However , inflammatory monocytes/macrophages lacking two or all three of these CLRs showed significant defects in C . albicans-induced ROS production ( Fig 4A and 4B and S5 Fig ) . Dectin-1 KO neutrophils displayed a moderate reduction in C . albicans-induced ROS production however , additional loss of Mincle or Dectin-2 did not substantially increase this defect ( Fig 4C and 4D and S5 Fig ) . As DHR-123 fluorescence only measures some reactive oxygen species ( hydrogen peroxide , hypochlorous acid , peroxynitrite anion ) , we also purified the BIOgel-elicited inflammatory monocyte/macrophage and neutrophil populations from WT and Mincle-Dectin-2-Dectin-1 TKO1 mice to measure a broader spectrum of reactive oxygen species using a luminol assay . Using this assay , we did not observe any significant defects in ROS production by Mincle-Dectin-2-Dectin-1 TKO1 monocytes/macrophages ( Fig 4E ) or neutrophils ( Fig 4F ) . We next measured the ability of WT and Mincle-Dectin-2-Dectin-1 TKO1 monocytes/macrophages and neutrophils to kill C . albicans and opsonised C . albicans . We did not observe any significant defect in the candidacidal ability of the multi-CLR KO cells ( Fig 4G and 4H ) . These data indicate that while these CLRs minimally contribute to C . albicans-mediated induction of some specific reactive oxygen species , ROS production in general and Candida killing are largely independent of these CLRs . As cytokine production is important for the clearance of systemic C . albicans infections [43] , we examined TNF production from monocytes/macrophages in response to C . albicans . Inflammatory myeloid cells recovered after BIOgel injection into WT and multi-CLR KO mice were incubated ex vivo with cell trace far red-labelled live C . albicans for 3 h . TNF production in the monocytes/macrophages that interacted with live C . albicans was measured by flow cytometry . Dectin-1 KO and Dectin-2 KO monocytes/macrophages displayed reduced C . albicans-induced TNF production , while Dectin-1-Dectin-2 DKO and Mincle-Dectin-2-Dectin-1 TKO1 cells displayed a more marked reduction in TNF production ( Fig 5A and 5B and S7 Fig ) . The defect in TNF production appears to be independent of Mincle . We next examined whether CLRs collaborated to more broadly influence inflammatory monocyte gene expression . Thus , we stimulated BIOgel-elicited monocytes isolated from WT , Dectin-1-Dectin-2 DKO and Mincle-Dectin-2-Dectin-1 TKO1 mice with C . albicans for 3 h and examined global gene expression using RNASeq analysis . We applied a filter to remove low expression transcripts ( <10 reads ) which revealed 177 significantly different ( adjusted p value of <0 . 05 ) protein coding transcripts . Following Z transformation across genes , genes were clustered by K means into 3 clusters using Genesis software ( S8 Fig ) . Cluster 1 consisted of genes that were higher basally and/or upregulated with C . albicans stimulation in WT cells compared to Dectin-1-Dectin-2 DKO and Mincle-Dectin-2-Dectin-1 TKO1 cells ( Fig 5C ) . Ingenuity Pathway Analysis ( IPA ) revealed that these genes are important for the inflammatory response , cellular movement and cell-to-cell signalling . As many of the genes in this cluster were chemokines , we searched for the GO terms chemokine activity ( GO:0008009 ) , cytokine activity ( GO:0005125 ) and growth factor activity ( GO:0008083 ) for transcripts that showed 10 or more reads ( Fig 5D ) . Many of these genes were present or induced in WT cells by C . albicans while they were absent or not induced in Dectin-1-Dectin-2 DKO and Mincle-Dectin-2-Dectin-1 TKO1 cells . The defect in the inflammatory response in Mincle-Dectin-2-Dectin-1 TKO1 monocytes was validated by ELISA measurement of chemokines and cytokines in cell supernatants 24 h after stimulation with C . albicans ( Fig 5E ) . The ELISA results validated the findings in Fig 5C and 5D . These data indicate that Dectin-1 and Dectin-2 are vitally important for mediating C . albicans-induced chemokine and cytokine production from inflammatory monocytes . As C . albicans recognition and cytokine/chemokine production were highly defective in inflammatory monocytes and macrophages from multi-CLR KO mice , we hypothesised that early innate cell recruitment would be delayed in response to C . albicans . In addition , Taylor et al previously demonstrated that Dectin-1 KO mice displayed reduced inflammatory cell recruitment in response to C . albicans [14] . Using a peritoneal infection model , we therefore explored whether this defective inflammatory cell recruitment also occurred in the highly susceptible multi-CLR KO mice . We injected mice intraperitoneally with 1x105 CFU C . albicans and 4 h later , we examined inflammatory cell recruitment to the peritoneum . In response to C . albicans , we observed reduced neutrophil recruitment to the peritoneum of Dectin-1 KO , Dectin-1-Dectin-2 DKO and Mincle-Dectin-2-Dectin-1 TKO1 but not Dectin-2 KO mice ( Fig 6A and 6B ) . These same mice also demonstrated reduced resident macrophage emigration ( Fig 6A and 6B ) and reduced levels of Ccl2 in the lavage fluid . These data confirm that Dectin-1 is highly important for early neutrophil recruitment to the C . albicans-infected peritoneum . As we identified highly defective cytokine/chemokine responses by multi-CLR KO monocytes ex vivo ( Fig 5 ) and reduced chemokine production and neutrophil recruitment in vivo ( Fig 6 ) , we wanted to further examine the role of these CLRs in monocytes in vivo . Ccr2+ Ly6Chi inflammatory monocytes have been proposed to be important during the first 48 h of systemic infection with C . albicans and Ccr2 KO mice are highly susceptible to systemic C . albicans infection [39 , 40] . To confirm the protective effect of Ccr2+ Ly6Chi monocytes in our facility during systemic infection with C . albicans , we infected WT and Ccr2 KO mice intravenously with 1x105 CFU C . albicans SC5314 . Similar to previous findings , we observed increased fungal burden in the kidneys of Ccr2 KO mice ( Fig 7A ) . As inflammatory monocytes from Dectin-1-Dectin-2 DKO and Mincle-Dectin-2-Dectin-1 TKO1 mice display severely deficient responses ( Figs 3–5 ) and these mice are highly susceptible to systemic C . albicans infection ( Fig 1 ) , we performed adoptive transfer experiments to determine whether these CLRs are responsible for the protective effect of monocytes during C . albicans infection ( Fig 7B ) . Since Mincle was involved in recognition of C . albicans by inflammatory monocytes , we adoptively transferred Ly6Chi monocytes from Mincle-Dectin-2-Dectin-1 TKO1 mice . We found that Ccr2 KO mice that received Ly6Chi monocytes from WT mice displayed lower kidney fungal burden than mice that received Ly6Chi monocytes from TKO1 mice , 72 h post-infection ( Fig 7C ) . We then performed further adoptive transfer experiments to examine cell recruitment to the kidney , 24 h post-infection . We found significantly reduced numbers of adoptively transferred Mincle-Dectin-2-Dectin-1 TKO1 monocytes than WT monocytes in the kidneys of infected mice ( Fig 7D and 7E ) . We also observed a subtle reduction in neutrophil recruitment to the kidneys ( Fig 7D and 7E ) and Cxcl2 production in the kidneys ( Fig 7F ) of mice who received Mincle-Dectin-2-Dectin-1 TKO1 monocytes compared to WT monocytes . These data indicate that these receptors mediate the protective effect of inflammatory monocytes during systemic infection with C . albicans .
Dectin-1 , Dectin-2 and Mincle have been proposed to play various roles during anti-fungal immune responses , however how these receptors work together to respond to a systemic infection with C . albicans has not previously been determined . Here using novel multi-CLR KO mice , we identified individual , collaborative and redundant roles for Dectin-1 , Dectin-2 and Mincle during systemic infection with C . albicans . We found that mice lacking two ( Dectin-1 and Dectin-2 ) or three ( Dectin-1 , Dectin-2 and Mincle ) CLRs exhibited dramatic susceptibility to systemic infection with C . albicans compared to WT or the other single or double KO mice strains . These multi-CLR KO mice displayed an excessive inflammatory response associated with uncontrolled fungal growth which likely resulted in immunopathology and organ failure . Surprisingly , all three CLRs were dispensable for neutrophil recognition/phagocytosis and killing of C . albicans . However , inflammatory monocytes/macrophages utilise all three CLRs for recognition/phagocytosis , but not for Candida killing . Furthermore , Dectin-1 and Dectin-2 are vitally important for the early C . albicans-induced cytokine and chemokine response from inflammatory monocytes , and Dectin-1 is required for early inflammatory cell recruitment likely mediated by resident macrophages . Our data indicates that these CLRs are important for mediating recognition and/or anti-fungal immune responses in inflammatory monocytes/macrophages in the following order: Dectin-1 , Dectin-2 , Mincle . We also found that the protective effect of inflammatory monocytes during systemic infection with C . albicans is mediated by these CLRs . Together these CLRs mediate recognition of C . albicans and the various immune responses required for clearance of C . albicans and therefore , maintain organ function during infection by controlling fungal growth . Based on our data , we believe that Dectin-1 and Dectin-2 are important to mediate various anti-fungal responses by inflammatory monocytes/macrophages while they are largely dispensable for neutrophil anti-fungal responses . These data extend our knowledge of anti-fungal roles for Dectin-1 and Dectin-2 and we confirm that Mincle plays a subtle role in recognition of C . albicans . Interestingly , we found that C . albicans-induced recognition and phagocytosis is severely attenuated in inflammatory monocytes/macrophages from Mincle-Dectin-2-Dectin-1 TKO1 mice while these responses are mostly normal in neutrophils lacking these CLRs . Dectin-1 and Dectin-2 are expressed at higher levels on inflammatory monocytes/macrophages than on neutrophils which may help to explain the greater dependence on these CLRs by inflammatory monocytes/macrophages than neutrophils . In agreement with these data , Ferwerda et al showed that neutrophils from Dectin-1 deficient patients displayed normal phagocytosis of opsonised C . albicans [18] . However , it was also reported that murine Dectin-1 KO neutrophils displayed reduced recognition of non-opsonised zymosan and C . albicans , while recognition of opsonised particles was normal [41] . Similarly , an additional report showed that unopsonised C . albicans binding to human neutrophils could be partially blocked with the addition of soluble β-glucan or anti-Dectin-1 , while the binding of opsonised C . albicans was not affected [44] . We did not exogenously opsonise the C . albicans in this study for the recognition assay , however it is possible that some opsonins were present in the cell preparations . In addition , the timing and ratio of cells:Candida differed between our experiments and the previously published data [41] , which could potentially explain some of the discrepancies in our data . Another report found that CR3 was important for recognition of zymosan and ROS production by human neutrophils and that this was independent of Dectin-1 [45] . In addition , CR3 binds iC3b on opsonised C . albicans and it can also bind Pra1 and β-glucan on the cell surface/wall of C . albicans [46 , 47] , indicating that CR3 could potentially mediate neutrophil recognition of C . albicans and ROS production in the absence of these CLRs . However , as the inflammatory monocyte/macrophage population expresses higher levels of CD11b than neutrophils ( S1 Fig ) , it is also possible that additional receptors expressed on neutrophils such as FcγR are involved in partially mediating these responses . While we have not determined here which receptors mediate neutrophil recognition of C . albicans it is clear from our data that Dectin-1 , Dectin-2 and to a lesser extent Mincle mediate early recognition of C . albicans by inflammatory monocytes/macrophages . In addition to reduced recognition of C . albicans , we hypothesised that the defective inflammatory monocyte response by TKO1 monocytes may affect neutrophil-mediated killing of C . albicans . A report recently showed that type I IFN from inflammatory monocytes induced IL-15 production which led to activation of NK cells and GM-CSF release to boost the candidacidal potential of neutrophils [39] . Furthermore , the neutrophils from a CARD9 deficient patient showed normal recognition and ROS production similar to our TKO1 neutrophils , however Candida killing was defective in the CARD9 deficient neutrophils [30] . However , we did not observe any defects in Candida killing in our TKO1 cells suggesting that the CARD9-dependent killing is mediated by different receptors than these CLRs for murine neutrophils , or that dependence on these CLRs for Candida killing differs between mouse and human neutrophils . As neutrophil functions were largely normal , we then questioned why Mincle-Dectin-2-Dectin-1 TKO1 mice were so susceptible to systemic Candida infection . We hypothesised that the early innate response was severely defective in the susceptible multi-CLR KO mice . In fact it has previously been shown that the early inflammatory response including neutrophil recruitment was reduced in Dectin-1 KO mice compared to WT mice [14] , and similarly , we found that neutrophil recruitment was also defective in the Dectin-1-Dectin-2 DKO and Mincle-Dectin-2-Dectin-1 TKO1 mice , 4 h after infection in a peritoneal model of C . albicans infection . This was likely due to the loss of Dectin-1 on resident macrophages resulting in defective activation of these cells [14] . Resident macrophages express Dectin-1 but not Dectin-2 [32] , which fits with the normal neutrophil recruitment that we observed in Dectin-2 KO mice . In addition , our observation that the inflammatory response is largely absent in monocytes from the multi-CLR KO mice further indicates that the immune response to C . albicans during the first 24 h of infection is likely severely defective . We and others have shown that Ccr2 KO mice displayed increased susceptibility to systemic infection with C . albicans ( Fig 7A ) [39 , 40] . Trafficking of Ly6Chi inflammatory monocytes to infected organs including the kidney and spleen was severely reduced 24 h post-infection in Ccr2 KO mice . This was accompanied by a moderate reduction in the monocyte-derived DC population and reduced neutrophil recruitment to these organs [39] . These inflammatory monocytes were shown to be essential during the first 48 h post-infection to control fungal growth [40] . Here , we have shown that Dectin-1 , Dectin-2 and Mincle mediate recognition and/or various anti-fungal responses of inflammatory monocytes and that these CLRs mediate the protective effect of inflammatory monocytes during systemic infection with C . albicans . Using an adoptive transfer model , we found reduced Mincle-Dectin-2-Dectin-1 TKO1 monocytes compared to WT monocytes in the kidneys of infected CCR2 KO mice . This could be due to reduced recruitment , survival or retention of these cells in the kidneys of infected mice . This was associated with a near significant reduction in Cxcl2 production in the kidney and a subtle reduction in neutrophil recruitment to the kidney of mice that received Mincle-Dectin-2-Dectin-1 TKO1 monocytes compared to WT monocytes . In line with this data , we observed defective chemokine production including neutrophil-recruiting chemokines by TKO1 inflammatory monocytes following incubation with C . albicans ( Fig 5 ) . Drummond et al recently showed that neutrophil recruitment to the brain during systemic infection with C . albicans was significantly impaired in Card9 KO mice due to reduced production of neutrophil-recruiting chemokines ( Cxcl1 , Cxcl2 , Cxcl5 ) resulting in fungal invasion of the central nervous system [31] . These data indicate that these CLRs are vitally important for early innate chemokine/cytokine production and resulting inflammatory cell recruitment during the early stages of infection with C . albicans . Due to the inability of Dectin-1-Dectin-2 DKO and Mincle-Dectin-2-Dectin-1 TKO1 mice to mount an appropriate early innate response to infection with C . albicans , these mice develop uncontrolled fungal growth particularly in the kidneys . In a model of invasive candidiasis , it has previously been shown that the spleen recruits large numbers of neutrophils and monocytes in response to the infection and successfully clears the pathogen from the spleen early during infection , which then results in a decline in myeloid cell numbers in the spleen . However , the kidney recruits much lower numbers of these myeloid cells and this correlates with increased fungal burden , persistent neutrophil accumulation and immunopathology in the kidney [48] . In our susceptible multi-CLR KO mice we observed a hyper-inflammatory response in the kidneys and spleen in association with the excessive fungal outgrowth in these mice . This inflammatory response did not resolve by 6 days post-infection . However , the inflammatory response in WT mice was much less pronounced and fungal burden was almost completely cleared in the WT mice at this time . We observed splenomegaly only in the highly susceptible Dectin-1-Dectin-2 DKO and Mincle-Dectin-2-Dectin-1 TKO1 mice , likely due to the excessive fungal growth in these mice . Patients who have survived candidemia while neutropenic can develop chronic disseminated candidiasis or hepatosplenic candidiasis . Following recovery of their neutrophil counts , these patients present with various symptoms including splenomegaly [49] . As mentioned above , in our highly susceptible multi-CLR KO mouse strains , we observed increased recruitment of myeloid cells , particularly monocytes and neutrophils , to the spleen and kidneys . In addition , the total number of T and NK cells and the total number of IFN-γ producing T/NK cells were increased the spleen of the multi-CLR KO mice . Furthermore , the slightly increased ability of multi-CLR KO splenocytes to produce IFN-γ following restimulation with C . albicans differs from previous reports with Dectin-1 KO , Dectin-2 KO or Card9 KO T cells [6 , 7 , 28] , however these differences could be due to the use of live C . albicans in the presence of Amphotericin B versus heat killed C . albicans as this changes the ligand availability . The increased IFN-γ production is also likely due to the excessive fungal burden in these mice and these high levels of IFN-γ likely contribute to immunopathology in these mice . Taken together , these data indicate that failure to control fungal growth early during the infection due to defective early activation of monocytic cells and macrophages resulted in rapid excessive fungal outgrowth in Mincle-Dectin-2-Dectin-1 TKO1 mice , from which these mice were unable to recover . In conclusion , we have shown that Dectin-1 , Dectin-2 and to a lesser extent , Mincle mediate inflammatory monocyte/macrophage recognition of C . albicans . We have shown for the first time that the protective effect of inflammatory monocytes during systemic infection with C . albicans is mediated by these CLRs , while loss of these receptors did not have a direct effect on C . albicans recognition or ROS production by neutrophils . Loss of early control of C . albicans infection in the absence of these CLRs resulted in excessive fungal outgrowth and hyper-inflammation likely leading to multi-organ failure . The co-ordinated immune response through these CLRs to clear C . albicans infections could provide the basis for the design of novel immunotherapies for fungal or other pathogens that only naturally engage one of these receptors . | Fungal infections including invasive candidiasis are a serious healthcare problem particularly for immunocompromised patients . Mortality rates for invasive candidiasis are very high and complex anti-fungal immune responses are poorly understood , hindering the development of novel immunotherapies . Dectin-1 , Dectin-2 and Mincle are three cell surface receptors that are proposed to be involved in the immune response to fungal pathogens . However , if or how these receptors work together during infection is currently unknown . Here we demonstrate that these receptors , in particular Dectin-1 and Dectin-2 , work together to promote fungal clearance by a group of innate immune cells called inflammatory monocytes . Furthermore , we found that mice lacking these three receptors are dramatically susceptible to systemic Candida albicans infection due to defective early innate immune responses . These mice develop hyper-inflammation to try to control excessive fungal growth likely resulting in multi-organ failure . Our work helps explain how these receptors work together to clear/control invasive candidiasis . Our improved knowledge of the interactions between these receptors could be used to help design novel anti-fungal immunotherapies . | [
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... | 2019 | The protective effect of inflammatory monocytes during systemic C. albicans infection is dependent on collaboration between C-type lectin-like receptors |
Organisms like Dictyostelium discoideum , often referred to as DNA damage “extremophiles” , can survive exposure to extremely high doses of radiation and DNA crosslinking agents . These agents form highly toxic DNA crosslinks that cause extensive DNA damage . However , little is known about how Dictyostelium and the other “extremophiles” can tolerate and repair such large numbers of DNA crosslinks . Here we describe a comprehensive genetic analysis of crosslink repair in Dictyostelium discoideum . We analyse three gene groups that are crucial for a replication-coupled repair process that removes DNA crosslinks in higher eukarya: The Fanconi anaemia pathway ( FA ) , translesion synthesis ( TLS ) , and nucleotide excision repair . Gene disruption studies unexpectedly reveal that the FA genes and the TLS enzyme Rev3 play minor roles in tolerance to crosslinks in Dictyostelium . However , disruption of the Xpf nuclease subcomponent results in striking hypersensitivity to crosslinks . Genetic interaction studies reveal that although Xpf functions with FA and TLS gene products , most Xpf mediated repair is independent of these two gene groups . These results suggest that Dictyostelium utilises a distinct Xpf nuclease-mediated repair process to remove crosslinked DNA . Other DNA damage–resistant organisms and chemoresistant cancer cells might adopt a similar strategy to develop resistance to DNA crosslinking agents .
DNA interstrand crosslinks are complex lesions that covalently link the two complementary strands of DNA . Agents that cause this type of lesion can originate from an endogenous source such as reactive species generated by lipid peroxidation , or as a consequence of exposure to exogenous mutagens [1]–[5] . For this reason the cytotoxicity of DNA crosslinks is exploited in cancer chemotherapy , where drugs such as cisplatin , mitomycin C and melphalan are administered as potent DNA crosslinking agents . DNA crosslinks are extremely cytotoxic because they form an absolute barrier to replication [6] . In addition , a crosslink present in a gene coding sequence , will also block transcription . Apart from cell death , DNA crosslinks can also lead to cell senescence and dysfunction [7] , [8] . These features are observed in humans born with defective crosslink repair as such individuals exhibit growth retardation , stem cell attrition and symptoms consistent with premature aging [9] . These phenotypic features may be due to the accumulation of unrepaired crosslinks in genomic DNA Crosslinks can also form between adjacent bases on the same DNA strand , which are referred to as intrastrand crosslinks . Of the two classes of crosslinks , interstrand crosslink is believed to be the more cytotoxic . Crystal structures of lesions formed by reacting cisplatin with DNA have now been solved showing that these lesions cause substantial helix distortion . In terms of DNA repair , genetic and biochemical studies have shown that intrastrand crosslinks are largely repaired by nucleotide excision repair [10] . Repair of interstrand crosslinks is much more complex and poorly understood . Much of the work here is underpinned by genetic studies of classes of mutants that in certain organisms render cells selectively or generally sensitive to chemical crosslinking agents . Four clear repair gene groups in vertebrates stand out in this manner: the Fanconi anaemia ( FA ) genes , the translesion DNA polymerases Rev1 and Rev3 , homologous recombination ( HR ) repair genes and finally the structure-specific nucleases subcomponents XPF and Mus81 [11]–[13] . Taking this knowledge into account a replication-coupled model for interstrand crosslink repair has been proposed . This model suggests that replication pausing at or near a crosslink initiates a cleavage ( a step commonly referred to as unhooking ) , which is followed by lesion bypass over the crosslinked base by translesion DNA synthesis ( TLS ) . An intact chromatid is therefore created and can now be used as a template to complete repair by HR [11] , [13] . Not all the gene groups that function in vertebrate crosslink repair are conserved in yeast . Apart from FANCM none of the other 12 Fanconi anaemia genes appears to have orthologues in this organism [14] , [15] . This limits the use of yeast in understanding crosslink repair in higher eukaryotes . Crosslink repair has therefore been largely studied in immortalised vertebrate cell lines ( such as chicken DT40 cells or Chinese hamster ovary cells ) . A drawback of some of these systems is however that they contain mutations in other genes such as p53 that may influence repair . For these reasons some workers have turned to worms and flies [16] , [17] , as both organisms are genetically tractable and have some of the vertebrate crosslink repair groups conserved . A potential limitation of these model systems is that they are multicellular organisms and consequently DNA repair cannot be easily studied at the level of a single cell . All these factors led us to develop Dictyostelium discoideum as a new model for eukaryotic crosslink repair . Dictyostelium is a simple , soil-dwelling organism , which under optimal growth conditions exists as a unicellular amoeba , feeding on bacteria and dividing by binary fission . However , upon starvation , a precisely regulated developmental program is triggered , leading individual amoebae to aggregate and form a multicellular fruiting body [18] . Dictyostelium is easy to culture as axenic strains can be grown under standard laboratory conditions [19] . It possesses a small , compact genome that is fully sequenced [20] , thereby greatly facilitating genomic and bioinformatics analyses . In addition to this , the organism is genetically tractable as it is straightforward to knock genes out [21] , [22] and to carry out random mutagenesis screens [23] , [24] . However , an unusual feature of Dictyostelium is that it is highly resistant to DNA-damaging agents . Significant numbers of cells can survive exposure to 300 kilorads of ionising radiation , a striking observation that makes Dictyostelium one of the most radioresistant organisms known and places it on par with Deinococcus radiodurans [25] . This resistance is not just restricted to radiation . Dictyostelium also shows resistance to UV light [26] and to many chemical mutagens [27] , some of which are produced by bacteria in the soil [28] . Highly efficient DNA repair responses might therefore have evolved in Dictyostelium to enable it to survive in such a highly mutagenic environment . We believe that studying how this organism responds to DNA crosslinks provides us with a unique opportunity to see how a DNA damage resistant organism can deal with these important lesions .
The Fanconi anaemia ( FA ) genes are a particularly important class of DNA crosslink repair genes in vertebrates . Their inactivation in humans leads to Fanconi anaemia – an illness that leads to developmental defects , stem cell attrition and cancer predisposition [5] , [29] , [30] . There are 13 known FA genes in humans . Most of them ( FANCA , B , C , E , F , G , L , M , FAAP100 and FAAP24 ) assemble into a nuclear complex – hitherto referred to as the FA core complex . This complex interacts with the E2 enzyme Ube2t [31] , [32] , and monoubiquitinates two other FA proteins FANCD2 and FANCI . Both proteins form a complex and co-localise at sites of DNA damage with FANCD1 ( BRCA2 ) , FANCN ( PALB2 ) and the FANCJ helicase [30] . All the FA proteins are highly conserved in vertebrates . As a first step to dissect crosslink repair in Dictyostelium we delineated the pattern and depth of their conservation in all eukaryotes . A clear picture emerges from this analysis ( Figure 1A ) : a minimal FA pathway consists of FANCD2 ( FncD2 ) , FANCI ( FncI ) , FANCL ( FncL ) , FANCM ( FncM ) , FANCJ ( FncJ ) , Ube2T ( Ube2T ) and FancD1/BRCA2 ( FncD1 ) ; the later appears to have evolved in the ancestral eukaryote . Additional components , including most of the FA core complex proteins , evolved later in the ancestral metazoan . With respect to Dictyostelium , this analysis suggests a simplified FA pathway may operate in this organism ( Figure 1B ) . Next , we proceeded to establish a functional role for the ‘minimal’ FA pathway in Dictyostelium . We bioinformatically identified the genomic loci of the Dictyostelium FA genes and using these information generated knockouts of orthologues of FANCD2 , I , L , M , J and Ube2t ( Figures S1 , S2 , and S3 , and Table S1 ) . To study the response to DNA crosslinks , the various Dictyostelium strains were exposed to cisplatin . After one hour exposure to a range of doses , the amoebae were diluted , plated out onto bacterial lawns and allowed to grow for 4 days . Surviving amoebae form distinct plaques on the bacterially coated agar plates , each of which represents a colony arisen from a single cell . The number of plaques was counted and survival was expressed as a percentage of plaques formed by mock-treated cells . This assay is very much like the standard colony survival assay used in toxicity studies with vertebrate cell lines . The data in Figure 2 shows that most of the FA knockout strains show a moderate sensitivity to cisplatin . A notable exception is the fncJ knockout , which does not seem to be sensitive . Also of note is the dose of mutagen required to compromise wild type cells , which is in the range of 300 µM . This is a very large dose considering that human and chicken cells show sensitivities in the 1–40 nM range . This difference becomes even more striking when comparing the chicken fancL knockout , which has a D50 value of 5 nM ( 8 fold more sensitive compared to wild type ) , to its Dictyostelium counterpart , which has a D50 value of 165 µM ( 2 fold more sensitive than wild type ) . We can conclude that , firstly , Dictyostelium is much more resistant to cisplatin than vertebrate cells . Secondly , the identifiable FA genes are functionally required for this resistance , though unlike in vertebrates their overall contribution is much less marked . The monoubiquitination of FANCD2 is a key biochemical step in the FA pathway . In vertebrates this step requires the complete FA core complex , with FANCL and Ube2t forming the catalytic core of this reaction [33] . Studies in at least two non-vertebrate model organisms ( flies and worms ) confirm that FANCD2 monoubiquitination is conserved [16] , [17] . Both these organisms appear to have lost many core complex genes , once again raising the possibility of a minimal FA pathway operating in simpler organisms . Dictyostelium provides a unique opportunity to test if this is true since it lacks obvious orthologues of so many FA genes . Our first step was to establish whether FncD2 is monoubiquitinated and then to determine the genetic requirements for this . To facilitate detection of endogenous FncD2 we developed a FncD2 reporter strain where a YFP-tag was knocked in frame after the penultimate codon in the last exon of this gene ( Figure 3A ) . Western blot analysis ( Figure 3B ) and cisplatin survival data ( Figure S5 ) confirm that this strain expresses functional FANCD2-YFP and is not sensitive to cisplatin . In order to detect monoubiquitinated FncD2 we expressed HA-tagged ubiquitin in the FncD2-YFP strain . Cell extracts prepared from cisplatin or mock-treated cells were immunoprecipitated with an anti-YFP antibody and Western blotted for the HA-tag . A single DNA damage-inducible band , which corresponded to the size of FncD2-YFP was detected ( Figure 3C ) . We then knocked out fncL in this strain and found that monoubiquitinated FncD2-YFP was no longer detectable ( Figure 3D ) . Our next step was to determine if FncL acted alone or as part of a complex . Our bioinformatics analysis presented in Figure 1 revealed a possible FANCE orthologue - FncE ( Figure S4 ) . FANCE is an essential component of the vertebrate FA nuclear complex . We deleted this gene and found that the resultant ΔfncE strain was moderately sensitive to cisplatin ( Figure 2 ) and that monoubiquitinated FncD2-YFP was no longer detectable ( Figure 3D ) . Finally , we needed to determine if any one of these FA core complex proteins exists in a complex . To assay for this , we generated a strain that expresses N-terminal TAP-tagged FncL ( Figure S5 ) . Whole cell extract from this strain was subjected to size exclusion chromatography and fractions were blotted for TAP-FncL . The data in Figure 3E clearly show that TAP-FncL is present in two large molecular size peaks of approximately 800 kDa and 140 kDa respectively ( Figure 3E ) . In summary , this data shows that FncL and FncE are required for FncD2 monoubiquitination ( Figure 3F ) . Since FncL appears to reside in a protein complex it is unclear whether a truly ‘minimal’ FA pathway operates in this simple organism . A recent study surveyed the relative sensitivity of a large number of DNA repair mutants generated in the isogenic chicken cell line DT40 [34] . This comparison revealed that the most sensitive mutants are those that lack the translesion polymerases Rev1 and Rev3 , followed closely by mutants that lack the FA genes . Analysis of double mutants within these two groups of genes in DT40 shows that they participate in a common process to repair crosslinks [11] . These observations prompted us to establish the role of TLS in Dictyostelium crosslink repair . The Dictyostelium genome appears to contain a smaller complement of TLS enzymes than vertebrates . However a Rev3 orthologue ( rev3 ) was easy to identify . We disrupted the rev3 locus , the ensuing Δrev3 strain ( Figure 4A and 4B ) was viable , grew normally in culture and showed normal development ( Figure 5B ) . We then tested the Δrev3 for sensitivity to cisplatin and were surprised to see that it was only moderately sensitive to this agent ( 3 fold over WT ) ( Figure 4C ) . We then disrupted fncD2 in this strain to test the genetic interaction between these two crosslink repair genes . fncD2 deficiency makes no additional or synergistic impact in the Δrev3 strain ( Figure 4C and 4D ) , indicating that both genes function in a common process to repair crosslinks . However , notably the Δrev3 strain ( like the FA mutants ) was not strongly sensitive to crosslinks , once again contrasting with the corresponding sensitivities seen for this mutant in vertebrate cells . The fact that Dictyostelium mutants of FA and TLS genes are only moderately sensitive to cisplatin surprised us . This organism may be resistant to cisplatin because of reduced bioavailability of the drug ( reduced uptake/enhanced breakdown ) . In addition , it is noteworthy that the Dictyostelium genome is very AT-biased [20] . Since cisplatin crosslinks form at mainly GC sequences , this could mean that very few lesions are produced . Alternatively , crosslink repair may be carried out by another process that does not use the FA and TLS genes studied here . One obvious pathway would be HR . However , to date we and others have not been able to knockout core genes in this pathway [35] , [36] . Perhaps this could be due to an essential role for HR in cell viability . Another candidate group of genes are those involved in nucleotide excision repair . Vertebrate cell lines lacking NER show differential requirements for crosslink repair . Certain genes like xpa and xpc play at best only a minor role [9] , [37] , whilst the nuclease subcomponent XPF appears to be very important . Indeed , all models of crosslink repair invoke the action of a nuclease in cutting on either side of the crosslink , a step referred to as unhooking . In addition to XPF/ERCC1 , the Mus81/EME1 nuclease complex is also believed to be important in vertebrate crosslink repair [12] , [38] , [39] . We therefore set out to disrupt XPF ( xpf ) , XPC ( xpc ) and Mus81 ( mus81 ) . The respective orthologues were identified , their loci mapped and disrupted ( Figure 6A–6D and Figure S6A and S6B ) . All three mutant cell lines were then tested for sensitivity to cisplatin . The Δxpc and Δmus81 strains were not sensitive ( Figure 6E and Figure S6C ) , in contrast to the Δxpf mutant , which was extremely sensitive to cisplatin . The D50 values reflect this with Δxpf giving a value of 4 µM , in contrast with Δxpc ( 342 µM ) and wild type ( 290 µM ) ( Figure 6F ) . In summary , the excision repair nuclease subcomponent xpf is essential for repairing crosslinks in Dictyostelium . This activity is not due to the role of this gene in global NER since the xpc mutant is not at all sensitised to cisplatin . The current models for crosslink repair all involve a nuclease ( s ) carrying out the excision step . Our discovery of an essential role played by xpf and not mus81 in crosslink repair makes xpf a very good candidate component for the nuclease implicated in such a step . In a Xenopus cell free system , a crosslinked plasmid was repaired in a replication process that involves excision and TLS [40] . This important study therefore raises the question regarding the identity of the nuclease ( s ) involved in this excision step . A genetic test to determine if XPF might be involved here is to generate a ΔxpfΔrev3 strain and to establish genetic epistasis between these genes . If the double mutant is as sensitive as the single Δxpf strain then this indicates that xpf functions with rev3 in crosslink repair . This is indeed what we see since disruption of rev3 does not impact further on the sensitivity to cisplatin in the Δxpf strain ( Figure 5A ) . In addition , we also demonstrated that xpf is epistatic with respect to fncD2 ( Figure 5A ) . The single Δxpf mutant is 20–30 fold more sensitive than either Δrev3 or ΔfncD2 strains , respectively , which indicates that most crosslink repair requires xpf but not rev3 or fncD2 . Finally there is considerable evidence for the role of XPF in HR repair [41]–[43] . To test whether HR repair is compromised in Δxpf we analysed gene targeting efficiency into two independent loci . The data in Table 1 clearly shows that homologous gene targeting is compromised to varying degrees in both loci analysed in the Δxpf strain compared to wild type AX2 .
The studies presented in this paper establish the genetic requirements for crosslink repair in Dictyostelium . This simple unicellular genotoxin-resistant eukaryote shares the important groups of crosslink repair genes that function in humans . In contrast to vertebrates , the FA proteins and TLS enzymes appear to play only a minor role in repairing crosslinks . However , the most striking discovery reported here is that the nucleotide excision repair gene xpf is essential for crosslink repair in Dictyostelium . So far our analysis has confirmed that at least two known proteins that are crucial for the function of the FA core complex , FANCE and FANCL , are conserved in this organism . FANCE links the FA complex to its main substrate FANCD2 [44] and FANCL is the E3 subunit in the complex [45] . An unresolved question is whether Dictyostelium has a truly simplified FA pathway . Certainly the FncL protein exists in a high molecular mass protein complex . Such a complex may consist only of FncL and FncE . Another possibility is that there are other proteins in this complex . Such proteins could be other FA core complex orthologues that have simply evaded detection by bioinformatics as they may have diverged at the amino acid sequence level but not at a structural level . Alternatively , both FncL and FncE could be embedded in a complex consisting of new proteins or into a known surrogate multiprotein E3 ligase complex . Purification and identification of components of the FncL complex should address these possibilities . It has long been appreciated that Dictyostelium is an unusually DNA damage-resistant organism . The work presented here further illustrates this . Conceivably factors such as reduced bioavailability of cisplatin and the number of crosslinks introduced into the genome may contribute towards this resistance . However , the profound cisplatin sensitivity as a result of xpf inactivation clearly showed that a sufficient number of crosslinks are formed to cause lethal damage . We were surprised that the FA and the TLS proteins seem to only contribute a minor activity towards this crosslink resistance . This finding contrasts with what has been observed with vertebrate cells , where both groups of genes are crucial for tolerance to DNA crosslinking agents . The profound sensitivity of the xpf-deficient strain raises the question how xpf contributes to tolerance to DNA crosslinking agents repair . The genetic interactions between xpf , fncD2 and rev3 show that there is a minor repair process involving all three genes , but the dominant mechanism of xpf-dependent crosslink repair remains to be determined . During vegetative growth , Dictyostelium displays a skewed cell cycle distribution . The vast majority of cells are found in the G2 phase of the cell cycle [46] , [47] . The G1 phase appears to be very short . This , in terms of DNA content , means that most of the vegetative cells possess a duplicated genome . Upon exposure to cisplatin , it is very likely that lesions form at only one copy per site . Under such conditions , the most straightforward means of repair would be to excise the crosslink creating a double strand break . The undamaged copy could then be used as the template for HR-mediated double strand break repair ( Figure 7 ) . Such a model predicts the requirement for HR genes in crosslink repair , a proposition that is currently difficult to address , since we and others thus far been unable to disrupt HR genes in Dictyostelium [35] , [36] . In addition , this model of crosslink repair may require additional nucleases to not only to create but also to process DNA double strand breaks , remove flaps or resolve secondary structures . All these activities would be quite distinct from the unhooking step itself . Considerable work in both yeast and vertebrates point to a critical role for XPF and its orthologues in homologous recombination repair [42] , [48] . ES cells and yeast knockouts appear to be defective at homologous gene targeting though it is important to appreciate that this is not always a consistent feature [41] , [43] . Recombinant XPF/ERCC1 also function in processing recombination intermediates as well as synthetic replication forks [49] . Indeed we also find a defect in gene targeting in the Δxpf strain indicating that like in other organisms , Xpf does play a role in HR in Dictyostelium . It is therefore possible that it is the HR functions of Xpf that determines why it is so crucial for the tolerance of crosslinks in Dictyostelium . Finally , it is noteworthy that there are many organisms that share resistance to DNA damaging agents with Dictyostelium . The dependence of an excision nuclease-based repair mechanism may be responsible for such resistance . Such a mechanism may not just be limited to such organisms but also to human cancers which develop resistance to cisplatin [50] . Induction of such an excision repair pathway may account for the acquired resistance to chemical crosslinking agents . Future work will aim to address the genetic requirements and elucidate the mechanism of the xpf-dependent crosslink repair pathway .
All targeting constructs were generated using pLPBLP as the backbone [51] . 5′ and 3′ homology arms were generated by PCR amplification from Ax2 genomic DNA using Pwo polymerase and inserted into the plasmid on either side of the blasticidin-resistance cassette ( bsr ) . The HA-ubiquitin overexpression construct was generated using pDXA-3C as backbone [52] . The wild-type strain and the parent of all strains generated in this study was the Kay laboratory version of Ax2 . Transformants were created by electroporation ( Genepulser Xcell Bio-Rad ) of 17 . 5 µg of the targeting cassette or 25 µg of the overexpression plasmid . Potential homologous recombinants were selected for blasticidin resistance ( 10 µg/ml ) at limiting dilution in 96-well plates , whereas overexpression lines were selected as a pool of transformants in the presence of 10 µg/ml G418 . After approximately 10 days , the content of positive wells were cloned out onto SM agar plates in association with K . aerogenes . Colonies were picked and analysed by PCR . Genomic DNA was prepared from approximately 3×106 cells using the GenElute Mammalian Genomic DNA Miniprep Kit ( Sigma ) according to manufacturer's protocol . Two screening primers were designed per strain , one placed just upstream of the 5′ homology arm ( primer X ) and another just downstream of the 3′ homology arm ( primer Y ) in the genomic sequence . Each of the two primers was paired with a primer of the appropriate sense that bound within the bsr cassette ( BSR1B and BSR2B ) . The generation of a product by primer X and BSR1B , and primer Y and BSR2B indicated that the bsr cassette had integrated into the correct genomic locus . BSR1B - 5′ – CATTGTAATCTTCTCTGTCGCTACTTCTAC – 3′ BSR2B - 5′ - GTGTAGGGAGTTGATTTCAGACTATGCACC – 3′ All disrupted strains were confirmed by Southern analyses according to standard protocol . Genomic DNA was extracted using a method adapted from a universal , rapid high-salt extraction protocol [53] . When further genetic manipulation ( either gene disruption or in situ tagging ) of a knockout strain was required , the bsr cassette was removed from the parental strain by transfection with pDEX-NLS-Cre [51] and selecting for G418 resistance ( 10 µg/ml ) . After approximately 10 days of selection , resistant cells were cloned out onto SM-agar plates in the presence of K . aerogenes and tested for blasticidin ( 10 µg/ml ) and G418 ( 10 µg/ml ) sensitivity in axenic media . All strains were routinely grown at 22°C in axenic medium [19] supplemented with vitamins ( 0 . 1 mg/l B12 , 0 . 02 mg/l Biotin , 0 . 2 mg/l Riboflavin ) in the presence of tetracycline ( 10 µg/ml ) and streptomycin ( 200 µg/ml ) , either in tissue culture plates or in conical flasks shaken at 180 rpm ( shaken suspension ) . Strains can also be cultured in association with Klebsiella aerogenes on SM agar plates . Strains carrying pDXA-3C-based neoR-expressing plasmids were grown in axenic medium supplemented with G418 ( 10 µg/ml ) . Axenically grown cells in log phase ( 2–5×106 cells/ml ) were harvested by centrifugation ( 200 g , 2 minutes ) and washed twice with KK2 buffer ( 16 . 5 mM KH2PO4 , 3 . 9 mM K2HPO4 , pH 6 . 1 ) . Cells were resuspended in KK2 plus 0 . 1 mM CaCl2 to 2 . 5×107 cells/ml and 4 ml ( 108 cells ) were plated per agar plate ( 1 . 5×106 cells/cm2 ) in duplicate . Cells were allowed to settle on the agar for 15 minutes before the buffer was aspirated . Plates were then incubated in a moist box at 22°C with light . Photographs were taken with a Nikon Coolpix 4500 camera mounted on a Wild M10 microscope at the indicated time points in development . Cells in logarithmic growth phase ( 2–6×106 cells/ml ) were harvested , resuspended at 1×106 cells/ml in Pt buffer ( 3 mM NaCl , 1 mM NaPO4 , pH 6 . 5 ) and treated with cisplatin ( Sigma ) or mock-treated for 1 hour at 22°C in shaken suspension in the dark . The cisplatin solution was prepared in the dark immediately prior to use by dissolving in Pt buffer to a concentration of 1 mg/ml ( 3 . 3 mM ) . After treatment , cells were serially diluted in KK2 buffer and 50 µl of two dilutions shown to contain approximately 50 viable cells in preliminary experiments were plated in triplicate on SM agar plates with 400 µl of two-day old K . aerogenes culture . The plates were incubated at room temperature and the number of plaques per plate was scored 4 days after plating . An average was taken between the triplicate plates . Viability was calculated as a percentage of the estimated number of cells plated , which was then normalised against that of the mock-treated culture . Typically , 108 cells were harvested by centrifugation and washed twice with 1 ml KK2 buffer . The cell pellet was resuspended in 500 µl NETN lysis buffer ( 20 mM Tris-HCl pH 8 . 0 , 150 mM NaCl , 1 mM EDTA , 1 mM DTT , 0 . 5% NP40 , 10% glycerol , 1× Protease Inhibitor Cocktail [Roche] , 5 mM NEM [Sigma] ) . The lysate was drawn through a 25G needle four times to ensure complete lysis of the cells and to shear the genomic DNA . The resulting whole cell extract was cleared by centrifugation and the protein concentration was determined by Bradford assay . Protein concentrations across all samples were equalised and the total extract volume was made up to 540 µl with NETN lysis buffer . 1 µl of rabbit polyclonal antibody to GFP ( Abcam ab6556 ) was added and mixed by rotation during an 1 hour incubation at 4°C . 200 µl of 50 mg/ml freshly prepared protein A-sepharose beads ( GE Healthcare ) were then added and the samples mixed and incubated as the previous step . The beads were then pelleted by centrifugation , washed four times with 1 ml NETN lysis buffer and finally resuspended in 100 µl 2× SDS loading buffer . Protein samples were run on 10% NuPAGE Bis-Tris pre-cast gels ( Invitrogen ) in 1× MOPS buffer ( Invitrogen ) . The separated proteins were transferred onto nitrocellulose membrane ( Millipore ) . After blocking with 5% milk/PBST , the blot was incubated with the appropriate primary and secondary antibody diluted in PBST ( PBS with 0 . 05% v/v Tween-20 ) for 1 hour each at room temperature . The following antibodies and dilutions were used: rabbit anti-GFP antibody ab6556 ( Abcam; 1∶2000 ) , goat anti-rabbit IgG HRP-conjugated antibody ( Southern Biotech; 1∶1000–1∶2000 ) , mouse monoclonal anti-HA ( clone 12CA5 ) HRP-conjugated antibody ( Roche; 1∶1000 ) , rabbit anti-TAP antibody ( Sigma-Aldrich; 1∶600 ) . 2×109 exponentially growing cells were harvested and washed three times with KK2 buffer before flash-freezing in liquid nitrogen and storing at −80°C until use . The cell pellet was resuspended in 10 ml high salt buffer ( 50 mM HEPES pH 7 . 9 , 5 mM MgCl2 , 420 mM NaCl , 0 . 2 mM EDTA , 25% glycerol , 2 mM DTT , 1× Protease Inhibitor Cocktail [Roche] ) on ice . The suspension was taken up in a syringe and forced through a 3 µm Nucleopore filter ( Whatmann ) and absorbant pad ( Millipore ) to complete cell lysis , and was subsequently passed through a 26G needle to lyse the nuclei . The resulting lysate was mixed gently at 4°C for 30 minutes to extract nuclear protein and cleared by centrifugation ( 16 , 000 g , 10 minutes at 4°C ) . 2 ml whole cell extract was filtered through a 0 . 2 µm filter and applied to a Superose 6 XK 16/70 column ( GE Healthcare ) equilibrated with high salt buffer . 4 ml fractions were collected and 25 µl of each fraction was resolved on 10% Bis-Tris polyacrylamide gels and analysed by Western blotting . Orthologue searches were done using two publicly available databases – NCBI BLAST Link ( BLink ) and Kyoto Encyclopaedia of Genes and Genomes ( KEGG ) Orthology . NCBI BLink – http://www . ncbi . nlm . nih . gov/sites/entrez KEGG Orthology – www . genome . jp/kegg/ PSI-BLAST searches were carried out using the NCBI Blastp suite . http://blast . ncbi . nlm . nih . gov/Blast . cgi Structure of the Dictyostelium FancE orthologue was predicted using Phyre . http://www . sbg . bio . ic . ac . uk/~phyre/ Sequence alignments were carried out using ClustalW [54] and displayed using JalView ( http://www . jalview . org/ ) . | Organisms are constantly exposed to environmental and endogenous molecules that chemically modify the DNA in their genomes . A particularly pernicious chemical modification is when the two strands of DNA are crosslinked . These crosslinks must be removed so that genomes can be copied , and the damage caused by their persistence is often exploited in cancer chemotherapy . It is also no surprise that all organisms have developed effective means to remove these lesions , and work in prokaryotes and eukaryotes has shown that crosslinks are removed by the concerted action of certain DNA repair pathways . Whilst the obvious route of accumulating crosslinks is by exposure to anti-cancer drugs , these lesions may also arise spontaneously in DNA . This could be why inherited inactivation of one of the crosslink repair pathways results in the catastrophic human illness Fanconi anaemia . Here we determine how the social amoeba Dictyostelium discoideum , an organism that is unusually resistant to DNA-damaging agents , removes crosslinks . Our results indicate that this organism has evolved a distinct strategy to remove these lesions . More specifically , we discover that a particular nuclease subcomponent removes the crosslinks by a distinct repair process . We postulate that this strategy to remove crosslinks could be used by other DNA damage–resistant organisms and also by cancer cells that have developed resistance to chemotherapy . | [
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] | 2009 | Xpf and Not the Fanconi Anaemia Proteins or Rev3 Accounts for the Extreme Resistance to Cisplatin in Dictyostelium discoideum |
Renal tumor heterogeneity studies have utilized the von Hippel-Lindau VHL gene to classify disease into molecularly defined subtypes to examine associations with etiologic risk factors and prognosis . The aim of this study was to provide a comprehensive analysis of VHL inactivation in clear cell renal tumors ( ccRCC ) and to evaluate relationships between VHL inactivation subgroups with renal cancer risk factors and VHL germline single nucleotide polymorphisms ( SNPs ) . VHL genetic and epigenetic inactivation was examined among 507 sporadic RCC/470 ccRCC cases using endonuclease scanning and using bisulfite treatment and Sanger sequencing across 11 CpG sites within the VHL promoter . Case-only multivariate analyses were conducted to identify associations between alteration subtypes and risk factors . VHL inactivation , either through sequence alterations or promoter methylation in tumor DNA , was observed among 86 . 6% of ccRCC cases . Germline VHL SNPs and a haplotype were associated with promoter hypermethylation in tumor tissue ( OR = 6 . 10; 95% CI: 2 . 28–16 . 35 , p = 3 . 76E-4 , p-global = 8E-5 ) . Risk of having genetic VHL inactivation was inversely associated with smoking due to a higher proportion of wild-type ccRCC tumors [former: OR = 0 . 70 ( 0 . 20–1 . 31 ) and current: OR = 0 . 56 ( 0 . 32–0 . 99 ) ; P-trend = 0 . 04] . Alteration prevalence did not differ by histopathologic characteristics or occupational exposure to trichloroethylene . ccRCC cases with particular VHL germline polymorphisms were more likely to have VHL inactivation through promoter hypermethylation than through sequence alterations in tumor DNA , suggesting that the presence of these SNPs may represent an example of facilitated epigenetic variation ( an inherited propensity towards epigenetic variation ) in renal tissue . A proportion of tumors from current smokers lacked VHL alterations and may represent a biologically distinct clinical entity from inactivated cases .
Von Hippel-Lindau ( VHL ) alteration leading to protein inactivation is considered a frequent , early event in renal carcinogenesis that can be used as a biomarker of tumor heterogeneity , to strengthen etiologic relationships with risk factors , and study mechanistic pathways of disease [1]–[4] . The most common established risk factors that are associated with approximately 50% of renal cell cancer ( RCC ) cases include obesity , hypertension , and tobacco smoking . Less-established risk factors include occupational exposure to pesticides and the organic solvent trichloroethylene ( TCE ) . Dietary intake of vegetables and fruits has been inversely associated with renal cancer , whereas intake of red meat and milk products have been associated with increased RCC risk , although not consistently [5] . Common genetic variation has also been shown to modify RCC risk [5] . Germline sequence alterations of the VHL gene were first identified and have been observed in almost all families with VHL disease , a hereditary cancer syndrome in which affected individuals are at risk for renal cysts and clear cell RCC ( ccRCC ) [1] . In sporadic ccRCC , alterations in the VHL gene have been reported in up to 91% of case tumors [6] . The VHL gene plays a role in tissue-specific responses to oxygen concentration and delivery . Under normal oxygen conditions , the VHL protein forms a complex with elongin B , elongin C , and cullin 2 which targets hydroxylated hypoxia inducible factor-alpha ( HIFα ) for ubiquitin-mediated degradation [7] , [8] . Under hypoxic conditions , the VHL complex cannot bind HIFα for degradation because it is in the non-hydroxylated form . Therefore , HIFα accumulates , resulting in transcription of additional genes that facilitate oxygen delivery , cellular adaptation to oxygen deprivation , and angiogenesis . Similarly , alteration of the VHL gene prevents formation of the protein complex required for HIF degradation , resulting in an excess of HIF and a similar gene expression pattern as that observed under hypoxic conditions . Recently , we applied sensitive and high-throughput mutation detection methods in a pilot study of 205 well-characterized sporadic ccRCC cases to comprehensively evaluate tumor DNA for VHL sequence alterations and promoter methylation , and to identify associations between the prevalence , type , and location of VHL alterations with etiologic and clinical factors [6] . In the current study , we expand upon our previous analysis [6] , and report findings from the entire case series of 507 sporadic RCC cases , including 470 ccRCC patients . The combined dataset has increased statistical power to identify associations between risk factors and heterogeneous subgroups of cases defined by the type of VHL alterations . Using questionnaire data on patient characteristics , nutritional intake , and occupational exposures known or suspected to modify risk , we attempted to replicate findings from previously published studies in which evidence of tumor heterogeneity had been reported [9]–[13] . A previously reported VHL polymorphism , rs779805 and epigenetic inactivation of the VHL gene were examined among these cases using a tag SNPs method that is routinely used in association studies . The VHL gene locus was examined using highly correlated SNPs to comprehensively evaluate common genetic variation across this gene region and risk of developing a specific type of VHL alteration [14] .
In Table S1 , sporadic RCC cases from the Central and Eastern European Case-Control study ( CEERCC ) that were included in this analysis are compared to cases not included in this analysis by their personal/clinical characteristics , and risk factors that have been previously associated with the prevalence of RCC or VHL alterations in tumor tissue . Cases not included in this study were those from whom we were unable to collect frozen tumor biopsy material for analyses . Collection of frozen tissue was most successful among cases from the Czech Republic than the other study regions . This analysis also included more cases with high body mass index ( BMI ) , with a lower level of education , and included more M0 compared to M1 cases compared to those not included in this analysis . The distribution of other factors was similar across groups . The prevalence of having any VHL alteration ( i . e . inactivating , silent , and intronic mutations , and promoter hypermethylation ) was 83 . 0% among all RCC cases , 88 . 3% among the subset of ccRCC cases , and 16 . 2% among non-ccRCC cases ( Table 1 ) . The higher percentage observed in ccRCC compared to all RCC cases was due to a greater proportion of cases with VHL inactivating alterations and a lower proportion of wild type ccRCC cases [i . e . cases without inactivating VHL gene alterations] , that were primarily observed among non-ccRCC cases . The overall prevalence of VHL promoter hypermethylation was similar in RCC , ccRCC , and non-ccRCC cases . Among all ccRCC cases , the highest alteration prevalence was located at codon 117 ( N = 13 ) . These included 5 deletions , 5 missense , 2 insertions , and 1 nonsense sequence alteration at Codon 65 had the second highest sequence alteration prevalence ( N = 11 ) , and included 6 missense , 4 nonsense , and one deletion ( data not shown ) . Thirty putative splice junction sequence alterations , ( intronic variants located within 3 bases of an exon ) were observed . VHL promoter epigenetic and genetic inactivation was mutually exclusive in all tumors analyzed . Because VHL genetic alterations were rarely observed among non-ccRCC cases , all additional analyses were restricted to confirmed ccRCC cases . From the univariate analysis ( Table S2 ) , risk factors with a p-value<0 . 20 were selected as adjustment variables in multivariate analyses . In addition to sex , age , and country , variables remained in models if their inclusion changed risk estimates by at least 10% . High blood pressure ( p = 0 . 16 ) , family history of cancer ( p = 0 . 12 ) , and fruit intake frequency ( p = 0 . 09 ) , were inversely associated with VHL promoter hypermethylation and were selected for initial inclusion in multivariate models . In addition to smoking ( p = 0 . 05 ) , family history of cancer ( p = 0 . 10 ) and fruit intake ( p = 0 . 14 ) were initially included the multivariate analysis of genetic inactivation prevalence . In M1 compared to M0 cases , a lower prevalence of genetic inactivation was observed in exon 1 [from 43 . 4% to 11 . 8% , p = 0 . 02] and a higher prevalence was observed in exon 3 [from 25 . 4% to 52 . 9% , p = 0 . 08] . Inactivating VHL alterations were found in 9/12 ( 75% ) patients with a self-reported family history of kidney cancer; 8 case tumors had inactivating alterations , and 1 had a hypermethylated VHL promoter . Specifically , two cases had deletions located at codons 137 and 180 , two had insertions located at codons 184 and 203 , and four had missense mutations , two A/G transitions at codons 120 and 147 , one T/A transversion at codon 158 , and one C/A transversion at amino acid 65 which resulted in a stop ( ATG ) codon ( data not shown ) . Of the three VHL wild type cases , one had an alteration within intron 2 ( -11 ) that was not considered as an inactivating alteration in this study . In Table 2 , Odds Ratios ( OR ) and 95% confidence intervals ( CI ) estimated from multivariate models of risk factors and VHL alteration prevalence among ccRCC case tumor DNAs are presented . Only tobacco smoking and fruit intake , were significantly associated with VHL genetic inactivation in tumor tissue , and/or were required for adjustment . Tobacco smoking was inversely associated with VHL genetic inactivation in ccRCC tumors . The OR associated with having a ccRCC tumor with a genetic VHL inactivating alteration decreased in a dose-dependent manner among former [OR = 0 . 70 ( 0 . 20–1 . 31 ) ] and current smokers [OR = 0 . 56 ( 0 . 32–0 . 99 ) ] compared to never smokers ( p-trend = 0 . 04 ) . The association in the adjusted analysis was very similar to that observed in the univariate analysis as was the association with fruit intake that was not statistically significant ( Table S2 ) . The association with fruit intake and genetic alterations in tumor DNA did not differ with respect to smoking status . The lower prevalence of genetically inactivated cases among current smokers was due to a higher prevalence of wild type cases ( ∼8% ) ( Table 2 ) . Low fruit intake frequency was associated with having a VHL promoter hypermethylated tumor ( p = 0 . 02 ) . Compared to cases with high fruit intake frequency , the association with promoter hypermethylation increased in a dose-dependent manner among cases with medium [OR = 1 . 37 ( 0 . 62–3 . 03 ) ] and low fruit intake [OR = 3 . 03 ( 1 . 16–8 . 33 ) ; p-trend = 0 . 02] . After stratification by smoking status ( ever/never ) , the association between fruit intake and promoter hypermethylation was observed among smokers when the high intake group was used as a referent [medium: OR = 1 . 72 ( 0 . 59–3 . 13 ) , and low: OR = 4 . 35 ( 1 . 09–16 . 67 ) ; p-trend = 0 . 03] . A significant trend was not observed among never smokers ( p-trend = 0 . 59 ) , however , the formal test for heterogeneity between models was not statistically significant ( p-interaction = 0 . 28 ) . In contrast , tumor histopathologic factors that are generally associated with disease progression ( i . e . stage , nuclear grade , node positivity , metastases ) were not associated with alteration prevalence . Likewise , occupational exposure to the solvent TCE was not associated with VHL alteration prevalence in tumor DNA , when compared to unexposed cases . In Table 3 , the association between chromosome 3p loss and specifically the 3p clone CTB110j24 , which harbors the VHL gene locus , were analyzed with respect to VHL gene inactivation through either epigenetic or sequence alterations . The proportion of both chromosome 3p loss , and loss of clone CTB110j24 were significantly higher among cases with VHL gene inactivation compared to cases without VHL inactivation ( 92 . 4%/93 . 9% vs 70 . 2%/61 . 7%; p<0 . 00001 ) . Visual examination of each array CGH profile among cases without and with VHL inactivation but for whom chromosome 3p loss was observed , did not differ with respect to loss of clone CTB110j24 , and did not support the hypothesis that biallelic loss of the VHL locus had occurred among cases without VHL inactivation ( i . e . wild type cases ) . In adjusted multivariate analysis , the only factor that was significantly associated with chromosome 3p loss was having a VHL gene alteration , and the association was highly significant ( OR = 1250; 95% CI:476–3125 , p<0 . 00001 ) . Additional analysis of array CGH data did not indicate that loss of chromosome 3p or clone CTB110j24 differed significantly in tumor DNA from never ( 92 . 1% ) , former ( 91 . 3% ) , or current smoking cases ( 92 . 3% ) , nor did we observe a significant trend with tobacco exposure ( data not shown ) . In Table 4 , associations between germline VHL tag SNPs and VHL gene promoter hypermethylation in tumor tissue were evaluated in an attempt to replicate a previously reported association between the presence of VHL SNP rs779805 ( Ex1+19G>A ) in germline DNA , and the prevalence of promoter hypermethylation in tumor DNA [15] . A tag-SNP method was used that relies upon linkage disequilibrium ( LD ) of highly correlated SNPs to identify gene regions that could be associated with disease susceptibility , or heterogeneous subgroups of cases [14] . A significant association was observed between cases with VHL promoter hypermethylation with SNP rs779805 , and six additional tag SNPs across the VHL gene region . Some associations between SNPs in germline and promoter hypermethylation in tumor DNA were stronger when analyses were restricted to ccRCC cases . Significant trends were observed in ccRCC cases that had germline minor alleles at VHL SNPs rs265318 ( −2872 A>G ) , rs779805 ( Ex1 +19 G>A ) , rs779812 ( IVS1 −1184 G>A ) , rs1678607 ( IVS2 +108 T>G ) , rs1642742 ( Ex3 +473 G>A ) , rs1642739 ( 3835 bp 3′ST ) , and rs457414 ( IRAK2 −3754 A>C ) . Examination of this region using Haploview revealed that some tag SNPs were highly correlated ( Figure 1 ) . To identify regional associations between germline variants with promoter hypermethylation in tumor DNA , a sliding window analysis was conducted with a fixed window size ranging from 2 to 9 consecutive SNPs . The most significant global association across all inherited haplotype variants and tumor-specific VHL promoter hypermethylation was observed when a 9-SNP window spanning across the entire VHL gene region was evaluated . This window spanned from tag SNP rs6442154 ( c3orf10 , Ex3 −90 , T>C ) through rs457414 ( IRAK2 −3754 A>C ) ( p-global = 8E-5 ) . When specific VHL haplotypes were evaluated individually and compared to the common 9-SNP referent haplotype T-A-A-A-G-G-A-C-A , two germline haplotypes were significantly associated with tumor-specific promoter hypermethylation , specifically T-A-C-G-A-T-G-A-C ( OR = 6 . 10; 95% CI:2 . 28–16 . 35 , p = 3 . 76E-4 ) and C-G-A-G-G-G-G-C-A ( OR = 4 . 65; 95% CI:1 . 75–12 . 32; p = 2 . 21E-3 , respectively ) . A similar association was observed with a 4-SNP haplotype , as rs779805 was able capture common variation across a highly correlated 6-SNP block , spanning from rs779805 through rs457414 . Haplotype analyses spanning a 3-SNP sliding window , conducted to capture smaller regional variations , suggested that two regions may be driving the association observed , one centered within the VHL promoter at rs265318 ( p = 0 . 005 ) and the other located 3′ of the VHL stop codon centered at rs457414 ( p = 0 . 0004 ) ( data not shown ) . No associations were observed between these inherited polymorphisms and ccRCC cases with genetically inactivated VHL or wild type tumors .
The prevalence of VHL inactivation in ccRCC tumor DNA from this large well-characterized case-series of sporadic RCC is one of the highest reported in the literature , and is consistent with recent publications including our previous report [6] , [9] , [13] , [15] , [16] . As in our previous study , VHL inactivation in ccRCC tumors occurred either through genetic or epigenetic mechanisms . Notably , VHL alteration prevalence was associated uniquely with etiologic risk modifiers such as tobacco use , fruit intake , and VHL tag SNPs that were examined to capture common germline genetic variation across this region . We observed a slightly higher prevalence of tumors without genetic or epigenetic inactivation of VHL gene among current and former smokers , compared to never smokers . The addition of array CGH analysis of this same case-series of chromosome 3p loss and specifically the clone that harbors the VHL locus , clone CTB110j24 , enabled us to evaluate the VHL gene region for evidence of biallelic loss among cases in which we did not detect sequence alterations or evidence of epigenetic inactivation . Multivariate analysis of chromosome 3p loss revealed that the only patient/tumor characteristic or RCC risk factor associated with 3p or clone CTB110j24 loss was inactivation of the VHL gene , and the association was highly significant . In addition , statistically significant associations between VHL promoter hypermethylation and low fruit intake frequency were observed , particularly in tumor DNA from smokers . Interestingly , associations were observed with several tag SNPs spanning the VHL gene in germline DNA and tumor-specific VHL promoter hypermethylation . Of the ten tag SNPs selected to capture common genetic variation across the VHL gene region and evaluate associations with heterogeneous case subgroups , seven were significantly associated with VHL promoter hypermethylation in tumors . Analysis of haplotypes revealed the strongest association was observed using a 9-SNP sliding window that spanned across the entire VHL gene region . Lastly , we did not observe an increased prevalence of inactivating alterations , multiple mutations , nor a specific “hot spot” among TCE exposed cases , compared to unexposed cases . The association between inherited VHL polymorphisms and promoter hypermethylation in sporadic ccRCC case tumor DNA observed in the current study was similar to a previous report of 97 sporadic RCC cases [15] in which germline SNP rs779805 ( Ex1 +19 A>G ) was significantly associated with tumor-specific VHL promoter hypermethylation . In the current study , along with rs779805 , nine additional SNPs were selected to capture ( tag ) common variation across the VHL gene region to evaluate associations with heterogeneous subgroups of cases . The global p-values indicated that germline variation across the VHL gene region was significantly associated with risk of having a VHL hypermethylated tumor . When compared to the most common SNP or haplotype as a common referent , subsequent analyses revealed that several individual SNPs and two high risk haplotypes were associated with tumor-specific VHL promoter hypermethylation . These findings are similar to several reports of other cancer types , in which associations between constitutional ( germline ) mutations were associated with gene specific hypermethylation and silencing in tumors . In one report , a MGMT germline polymorphism ( rs16906252 C>T ) located within the transcriptional enhancer element of the MGMT promoter was strongly associated with susceptibility to CpG island methylation and gene silencing in colorectal cancer ( OR = 18 . 0; 95% CI:6 . 2–52 . 1 , p< . 0001 ) [17] , [18] . Epigenetic silencing and transcriptional suppression of the death associated protein kinase 1 gene DAPK1 , an underlying factor in familial B cell chronic lymphocytic leukemia , was found to be attributable to a germline SNP [c . 1–6531 A>G] located upstream of the DAPK1 promoter . Presence of this SNP resulted in higher binding affinity for the HOXB7 protein [19] . Similarly , hypermethylation of the MLH1 and MLH2 genes , also referred to as “epimutations” in inherited cases , have been associated with germline variants in some cases [20] , [21] . In contrast , in Beckwith-Wiedemann syndrome , an IGF2 gene polymorphism has been associated with loss of imprinting of the maternal allele-specific methylation of the KCNQ1 gene [22] . The association observed in the current study between particular inherited VHL haplotypes and promoter hypermethylation in renal tumors may be an example of facilitated epigenetic variation , or an increased inherited propensity towards epigenetic variation with respect to a particular genotype [23] . Because we did not analyze VHL promoter hypermethylation in germline DNA ( or in normal somatic tissues ) , it is unknown whether this particular finding is an example of an epimutation , however additional studies are warranted . This observation could be important for future translational research , as identification of individuals with high risk haplotypes could benefit from increased surveillance . Also of note , haplotype analyses spanning a 3-SNP sliding window across the VHL gene suggested that two regions may be driving the association observed , one centered within the VHL promoter and the other located 3′ of the VHL stop codon . The first region of interest , which spanned the promoter region of the VHL gene , raises the possibility that SNP variants in the promoter region could directly influence gene expression [24] . The second region associated with promoter hypermethylation in tumor DNA was centered 3′ to the VHL stop codon . It is possible that this region could be in linkage disequilibrium with a cis-acting structural or copy number alteration that might permit a mechanistic explanation to the associations observed [25] . VHL inactivation in tumor tissue was not associated with any of the clinical parameters examined that are normally considered to reflect disease progression such as stage , grade , and the presence of metastases or positive lymph nodes . The lack of an association between VHL alteration prevalence and indicators of tumor progression was similar to some previous reports [26]–[31] . However , this finding was in contrast to our previous report of 205 sporadic cases [6] , and a recent study ( analyzing 177 patient tumors ) that reported an association between VHL promoter hypermethylation and tumor grade [13] . The mutational spectrum observed in our study was similar to others reporting that the majority of genetic alterations in RCC were located in exon 1 ( codons 54–114 ) ( an excellent summary of recent studies is provided in ref 13 ) . The prevalence of promoter hypermethylation observed among cases in our study was within the range observed in other studies ( ∼5–15% ) , and was lower than that observed in a recent large study ( a prevalence of 31% compared to ∼9% in our study ) [13] . Unlike Young et al . , [13] we did not observe a difference in the prevalence of alterations between tumors from male and female cases . These dissimilarities could be partially explained by differences in the laboratory methods used to detect promoter hypermethylation and/or the case selection criteria used in each study . Our case series came from a hospital-based case-control study that attempted to include all cases diagnosed at hospitals serving a specific geographic region per study center , and therefore may be more representative of the general study population of sporadic cases than those acquired through studies that uniquely include cases from tertiary care centers . We observed a higher prevalence ( ∼8% ) of VHL wild type cases among current smokers compared to never smokers in this study . The higher prevalence of VHL wild type cases among smokers had been previously observed in our study of 205 cases but was not statistically significant ( p = 0 . 07 ) . A Dutch study also observed more VHL wild type tumors among smokers [16] . A Swedish study did not observe more VHL wild type tumors among smokers overall , however , they observed that smoking modified the associations observed between VHL alteration prevalence and citrus fruit and vegetable intake [9] . Unlike the Swedish study , we observed an association between VHL promoter hypermethylation and low fruit intake frequency among smokers , rather than genetic alteration prevalence . One reason for these differences may be the use of formalin fixed tissues in both studies , compared to the use of frozen tissue in the current study . The 8% difference in the prevalence of VHL wild type tumors among current smokers compared to never smokers could be clinically meaningful as this subgroup is considered biologically distinct from those with an inactivated VHL protein . Molecular studies have shown that VHL wild type and VHL inactivated tumors demonstrate differential signaling pathways [32]–[35] and methylation profiles [36] . Clinical studies have reported mixed results with respect to disease progression and survival . VHL wild type tumors have shown reduced treatment response rates [37] and lower median progression free survival [35] . In contrast , other studies have reported that cases without VHL alterations had better cancer-free and overall survival [34] , [35] , [37]–[41] , with the exception of Stage IV disease , as found in one study [39] . However , two studies reported no differences [13] , [27] . Clearly , elucidation of the association between heterogeneous tumor subtypes with respect to progression and survival warrants further large studies of well-characterized cases to enable pooled analyses across studies . Follow-up of cases in the current study is ongoing . Occupational exposure to TCE was associated with an increased risk of RCC in this case-control study [42] , however we were unable to replicate previous findings from a German study of exposed workers in which a higher VHL mutation prevalence and a hotspot located at nt454 ( codon 81 ) was reported [11] . In the current study , only one unexposed case had a VHL mutation located at this location and the VHL mutation prevalence was similar in TCE exposed and unexposed cases . Although the German study result may have been a false-positive finding due to small sample size , it was unlikely that mutations were caused by artifacts introduced by formalin fixation , as each tumor DNA sample was analyzed in duplicate [11] . Another possibility was that the German workers may have been exposed to higher TCE levels than those in the current study . A second study of RCC tumor heterogeneity recently conducted among TCE-exposed workers in France , also did not replicate the high mutation prevalence and hotspot observed in tumors from the German exposed workers [43] . However , the French study reported an unusually low VHL alteration prevalence overall , which may have been due to the sensitivity of the laboratory methods applied and the use of DNA extracted from formalin fixed rather than frozen tumor material , as frozen tissue generally results in higher yields of good quality DNA . Both differences could cause misclassification of cases by their alteration status which would have biased results toward the null . Strengths of the current study include a large sample size , a high participation rate , histological confirmation of all cases and also the tumor tissue used for DNA extraction . The study also included a high number of subjects from most case centers . We applied accurate and sensitive , mutation detection methods in a large study of well-characterized RCC and ccRCC cases to provide a clear picture of VHL inactivation through sequence alteration and promoter hypermethylation in a study conducted in a region with the highest incidence of RCC world-wide [44] . CGH analysis of chromosome 3p and specifically the clone harboring the VHL locus enabled us to evaluate the VHL region for biallelic loss . The multivariate analysis provided additional evidence to support that the only patient characteristic or risk factor associated with 3p or VHL locus loss was inactivation of the VHL gene through either genetic or epigenetic mechanisms , and the association was highly statistically significant . To our knowledge , this study is one of the largest conducted to date . However , additional large studies , data pooling , and meta-analyses will be required to clarify many of the associations observed across study populations . Lastly , we did not observe an increased risk associated with smoking in this case-control study as would have been expected; however by conducting case-only analyses , biases caused by control selection were eliminated . Some weaknesses of this study included misclassification of fruit , vegetable , and alcohol intake frequency due to retrospective recall using a limited 23-item food frequency questionnaire . There may also have been misclassification of BMI and self-reported hypertension among cases , as this information was collected post- rather than prior to diagnosis . These qualities are strengths of the ongoing Dutch cohort study . Lastly , the prevalence of VHL gene epigenetic inactivation in tumor tissue was only about 9% . Therefore , this analysis relied upon few cases that were both heterozygous/homozygous for the VHL germline variants which also had promoter hypermethylation in tumor tissue . This resulted in unstable point estimates , and is reflected by some of the wide confidence intervals observed . In summary , this comprehensive analysis of 470 well-characterized ccRCC patient tumor DNA samples observed VHL inactivation through genetic or epigenetic mechanisms in 86 . 6% of cases . The remaining 13 . 4% of cases in which we did not observe evidence of VHL inactivation ( VHL wild type cases ) may represent a biologically distinct subgroup , one that was observed more frequently in tumor DNA from smokers than never-smokers . Moreover , common germline VHL SNPs and haplotypes were associated with promoter hypermethylation in RCC tumor tissue and may demonstrate an example of facilitated epigenetic variation with respect to inherited high risk genotypes [23] . These findings show for the first time in a well-defined ccRCC case series that somatic VHL gene alterations in tumors were uniquely associated with exposures ( i . e . tobacco smoking , diet ) and inherited VHL polymorphisms in germline DNA , rather than factors associated with disease progression . Additional work is required to elucidate the consequences in these VHL molecularly defined subtypes in terms of etiology , biological mechanisms , treatment , and survival .
The study protocol was approved by relevant ethics committees and institutional review boards of all participating centers , the International Agency for Research on Cancer ( IARC ) , and the U . S . National Cancer Institute ( NCI ) at the U . S . National Institutes of Health . All study subjects and their physicians provided written informed consent . Cases were from a hospital-based case-control study of sporadic RCC that was conducted between 1999 and 2003 in seven centers in four countries of Central and Eastern Europe ( Moscow , Russia; Bucharest , Romania; Lodz , Poland; and Prague , Olomouc , Ceske-Budejovice , and Brno , Czech Republic ) as previously described [45] , [46] . All newly diagnosed and histologically confirmed cases of sporadic kidney cancer ( ICD-O2 code C . 64 ) were identified at participating hospitals in each study region between 1999 and 2003 . Histological slides of renal tumor tissue from all cases were reviewed by an international renal cancer pathology expert at the U . S . National Cancer Institute for standardized confirmation and disease classification ( MM ) . Only confirmed cases of RCC and ccRCC were included in the analyses . There were 1097 cases included in the final case-control study: 524 of the 1097 cases ( 48% ) originally diagnosed with RCC from hospital reports that provided frozen tumor biopsies for genetic analysis . Of the 524 cases , 507 ( 97% ) cases were confirmed with RCC by review of their biopsy material provided , and 470 of the 507 ( 93% ) were confirmed with the ccRCC subtype . Questionnaires were administered in person by trained interviewers at each center . Subjects were asked about their lifestyle habits , in particular tobacco consumption , anthropometric measures one year before diagnosis , personal and familial medical history , and dietary habits . Lifetime occupational information for jobs of at least 12 months duration was also collected during interviews through the use of general occupational and job-specific questionnaires . Job-specific questionnaires covered ( 1 ) possible organic and chlorinated solvent exposures , ( 2 ) hours per week of solvent exposure , ( 3 ) source of solvent exposure , and ( 4 ) a description of solvent use as previously described [42] . All coding in the re-assessment was performed while blinded with respect to the previous assessment ( with respect to chlorinated solvents and TCE exposures ) as well as disease status . Frequencies of fruit , vegetable , and alcohol intake were examined as they have been inversely associated with the prevalence of VHL alterations and particular alteration subtypes [9] . The dietary questionnaire was comprised of 23 food items which the study investigators selected by consensus during the planning stage of the study , which had been validated as previously described [47] . The questionnaire was repeated for two different time periods: 1 ) the year prior to interview , and 2 ) prior to political and market changes in 1989 ( 1991 in Russia ) . A lifetime weighted average intake for the two time periods was calculated as previously described [47] . Frozen tumor biopsies were collected from a subset of cases enrolled in the case-control study in which detailed information on tumor pathology , patient characteristics , and occupational risk factors for RCC , had been collected ( Table S1 ) . Tumor DNA extraction was performed following an additional pathology review of each tissue sample ( FW ) followed by macrodissection to remove non-tumor tissue , as previously described [6] . Sample areas estimated to contain at least 70% tumor cells were removed for DNA extraction . For each sample , 5 mm3 of tissue was sectioned and digested with 0 . 4 µg Proteinase K per µl of digestion buffer ( 500 mM KCl , 100 mM Tris-HCl , 15 mM MgCl2 , 0 . 5% Tween 20 ) at 50°C overnight . A standard protocol1 was used to extract DNA from the digested samples . PCR of VHL coding sequences , endonuclease scanning , and sequencing were performed as previously described [6] . PCR primers for this study for exons 1–3 were the following: VHL Exon1- Forward:5′-CTACGGAGGTCGACTCGGGAG , VHL Exon 1- Reverse:5′-GGGCTTCAGACCGTGCTATCG ( amplicon length:495 bp ) ; Exon 2- Forward:5′-CCGTGCCCAGCCACCGGTGTG , Exon 2- Reverse:5′-GGATAACGTGCCTGACATCAG ( amplicon length:288 bp ) , Exon 3- Forward:5′-CGTTCCTTGTACTGAGACCCTAG , Exon 3- Reverse:5′-GAACCAGTCCTGTATCTAGATCAAG ( amplicon length:317 bp ) . Amplification was carried out in 50 µL reactions using 10 to 15 ng tumor DNA and HotMaster Taq DNA Polymerase ( Eppendorf ) . Thermal cycling was accomplished using a MJ Research ( Bio-Rad ) DNA Engine and a touchdown PCR program with an annealing temperature of 58C . PCR products were heteroduplexed using standard conditions . PCR products were analyzed on 2% agarose gels and electrophoresis . Heteroduplexed PCR samples were analyzed using SURVEYOR Nuclease ( Transgenomic , Inc . ) and standard non-denaturing HPLC conditions appropriate for DNA fragment sizing as previously described [6] . A 100-bp DNA ladder ( New England Biolabs ) was run as a size marker . Positive and negative controls were included with each plate of PCR products to monitor endonuclease cleavage efficiency . Excess PCR primers were removed using the AMPure PCR Purification system ( Agencourt Bioscience Corp . ) . Reaction chemistry using BigDye version 3 . 1 ( Applied Biosystems ) and cycle sequencing on an MJ Research thermal cycler were adapted from the manufacturer's recommendations . Sequencing products were purified using CleanSEQ reagents ( Agencourt Bioscience ) . Sequence chromatograms were analyzed using Sequencher ( GeneCodes , Ann Arbor , MI ) . Standard methods were used for bisulfite modification of 100 to 500 ng of tumor DNA ( Zymo Research Laboratories ) . Primers were designed to amplify both methylated and unmethylated alleles across 11 CpG dinucleotides of the VHL promoter . Primers for the methylation analysis were the following: wild-type ( WT ) amplicon: VHL WT-Forward-CTACGGAGGTCGACTCGGGAG , WT-Reverse-GCGATTGCAGAAGATGACCTG ( amplicon length:335 bp ) ; VHL nested primers: WT Forward-CGGGTGGTCTGGATCG , WT-Reverse AGTTCACCGAGCGCAGCA ( nested amplicon length:226 bp ) . Post-bisulfite modification primers that annealed to both methylated ( M ) and unmethylated ( U ) alleles were as follows: VHL M/U Forward-5′-TTAYGGAGGTYGATTYGGGAG , and VHL M/U Reverse- ACRATTACAAAAAATAACCTA , ( amplicon length:335 bp ) , nested primers VHL M/U Forward-YGGGTGGTTTGGATYG , VHL M/U Reverse AATTCACCRAACRCAACA , nested ( amplicon length: 226 bp ) . PCR was performed using an MJ Research PTC200 thermal cycler and a touchdown PCR program with an annealing temperature of 50°C . Nested PCR included 1 µL of a 1∶10 dilution of first-round product using cycling conditions as described above . PCR products were visualized in 2 . 0% agarose and bi-directionally sequenced . Cytosine positions in CpGs were inspected for thymine or cytosine signals in chromatograms , and scoring was conducted as follows: T only , not methylated; both cytosine and thymine , partially methylated; C only , fully methylated . Tumor samples with at least four of 11 methylated CpGs ( >36% ) were considered as hypermethylated . All analyses were run in duplicate , blinded to VHL mutation status , and with positive ( CpGenome Universal Methylated DNA , Chemicon/Millipore ) and negative ( K562 Human Genomic DNA , Promega ) controls . Each DNA sample from the same case-series was analyzed using Scanning and OncoBAC arrays . Scanning arrays were comprised of 2464 BACs selected at approximately megabase intervals along the genome as described previously [48] , [49] . OncoBAC arrays were comprised of 960 Pa , PAC or BAC clones . About three-quarters of the clones on the OncoBAC arrays contained genes and STSs implicated in cancer development or progression . All cones were printed in quadruplicate . DNA samples for array CGH were labeled as described previously [48] , [49] . Briefly , 500 ng each of cancer and normal female genomic DNA sample was labeled by random priming with CY3- and CY5-dUTP , respectively; denatured; and hybridized with unlabeled Cot-1 DNA to CGH arrays . After hybridization , the slides were washed and imaged using a 16-bit CCD camera through CY3 , CY5 , and DAPI filters [50] . Array CGH data image analyses were performed as described previously [51] , [52] . Genomic DNA was extracted from blood samples as described previously [42] . Single nucleotide polymorphisms ( SNPs ) were selected from the HapMap Project , using expected minor allele frequencies reported among Caucasians , to capture 80–90% of common genetic variation across the locus encompassing the VHL gene , covering an average of 15 kb upstream and downstream of the gene . This method relies upon linkage disequilibrium ( LD ) of highly correlated SNPs in order to identify gene regions that are associated with disease susceptibility , or in this case , specific heterogeneous subgroups of cases defined by their VHL alteration status [14] . SNPs selected ( from 5′ to 3′ included the following: rs6442154 ( c3orf10 , Ex3 −90 T>C ) , rs6796538 ( VHL , −5011 A>G ) , rs265318 ( VHL , −2872 A>C ) , rs779805 ( VHL , Ex1 +19 A>G ) , rs779812 ( VHL , IVS1 −1184 G>A ) , rs1678607 ( VHL , IVS2 +108 G>T ) , rs1642742 ( VHL , Ex3 +473 A>G ) , rs1642739 ( VHL 3835 bp 3′STP C>A ) , rs457414 ( IRAK2 , −3754 A>C ) , rs11465853 ( IRAK2 , IVS1 +249 G>C ) . Assays were validated at the NCI Core Genotyping Facility ( CGF ) in 280 control samples from the human diversity panel that included 76 African/African Americans , 66 Caucasians , 49 Native Americans/Hispanics , and 89 Pacific Rim Asians . Subsequently , minor allele frequencies ( MAFs ) were determined from the CGF panel among Caucasians . All selected SNPs had a minor allele frequency of at least 10% . Methods for assays can be found at: http://snp500cancer . nci . nih . gov . DNA samples were blinded and randomized on PCR plates to avoid any potential bias and duplicate genotyping was performed for a randomly selected 5% of the total series for quality control . Concordance rates were >99% for all SNPs . All SNPs analyzed were within the expected distributions of Hardy-Weinberg equilibrium ( p<0 . 05 ) . Tumor and patient characteristics including clinical stage , Fuhrman nuclear grade ( I–IV ) , node stage ( N0 , N1 , N2–3 ) , body mass index ( BMI ) ( <25 , 25–35 , >35 ) , and smoking status were considered as categorical variables . Smoking status ( never , former , or current smoker ) was defined as status 2 years prior to the interview . Specifically , participants who were smoking in the 24 months prior interview were classified as current smokers . Other variables such as metastasis ( M0 , M1 ) self-reported hypertension ( no/yes ) , family history of cancer or kidney cancer ( no/yes ) , sex , and age at diagnosis ( <50 , ≥50 years ) were analyzed as dichotomous variables . Additional exposures and risk factors were selected based upon previous published reports of renal tumor heterogeneity including our own [6] . These additional factors included fruit , vegetable , and alcohol intake frequency , and VHL tagging SNPs [9]–[13] . Because occupational trichloroethylene ( TCE ) exposure was positively associated with RCC risk in this population [42] and because TCE exposure had previously been associated with an increased prevalence of VHL mutation among occupationally exposed workers [11] , [12] , we also evaluated associations between occupational exposure to organic and chlorinated solvents and trichloroethylene with VHL alteration prevalence . For nutritional variables , intake frequencies of related foods were summed to form food group intake categories based on tertile cutoff points that were defined by consumption frequency among controls . Categories of consumption for food-specific items were grouped as low ( never to <once per month ) , medium ( ≥once per month but <once per week ) , and high ( ≥once per week to daily ) . Categories of alcohol consumption as grams per week of ethanol among weekly drinkers were none , low ( <36 . 5 ) , medium ( 36 . 5–137 . 5 ) , and high ≥137 . 5 ) as described previously [47] . The prevalences of VHL genetic ( sequence alterations ) and epigenetic alterations ( promoter hypermethylation ) observed in tumor DNA samples were considered as dichotomous variables per case ( no/yes ) . VHL gene nonsynonymous sequence alterations were considered as inactivating alterations if they were located within exons 1–3 and would lead to an altered amino acid sequence or a truncated VHL protein . Splice site mutations and promoter hypermethylation were also considered as inactivating alterations . DNA sequence alterations that were synonymous or SNPs were not considered as inactivating alterations . Similarly , sequence alterations that were located 5′ of codon 54 , which were very rare , were not considered as inactivating alterations unless they were nonsynonymous and also would cause an alteration in the coding sequence of both pVHL19 and pVHL30 translation products . These included alterations such as insertions , deletions , and nonsense mutations . As in our previous study , the P25L variant was only considered an inactivating alteration if the case also possessed a second VHL alteration that would be considered inactivating using the above criteria . The prevalence of cases with a particular type of alteration was calculated by dividing the number of cases with that type of alteration by the total number of cases analyzed in the group . Chi-square tests were applied to contingency table ( 2×2 ) analyses to test for differences between the proportion of cases with or without a particular alteration subtype within each group . Trend tests were used to analyze associations between categorical variables and cases with particular types of alterations . Ordered logistic regression was used for multivariate analyses to evaluate associations between categorical variables and case subgroups , initially adjusting for variables that were associated with the same alteration subtype in our univariate analyses ( p<0 . 20; Table S2 ) . With the exception of sex , age , and country , other variables remained in multivariate models if their inclusion modified risk estimates by at least 10% . For genotyping analyses , each SNP was assessed in three categories , ( G0 = homozygote for the major allele , G1 = heterozygote , G2 = homozygote for the minor allele ) using the most common allele as a referent . LD between SNPs was measured using Lewontin's D' statistic . Correlation ( r2 ) between tagged regions was evaluated in Haploview . To evaluate associations between SNPs and VHL promoter hypermethylation prevalence , logistic regression models were used to calculate odds ratios ( OR ) and 95% confidence intervals ( CI ) , adjusting for sex , age , country , and fruit intake . Risks were estimated using both additive and dominant models . Risk per allele and trends were calculated using unconditional logistic regression . Analyses were conducted using STATA 10 . 0 ( Stata Corporation , College Station , TX ) and all statistical tests were two-sided . Haplotype analysis was used to explore the combined contribution of consecutive VHL tagging SNPs . A sliding window analysis was first conducted in MatLab to identify regions of interest ( The MathWorks , Inc . , Natick , MA ) . For the 10 SNPs examined , sliding windows of 2–9 SNPs were evaluated , accounting for multiple testing and correlations between SNPs . The significance of haplotype-based associations was assessed using the score test [53] . Haplotypes of interest were analyzed using an R package Haplostats ( Version 1 . 3 . 1 ) in ( version 2 . 4 . 1 ) adjusting for sex , age , and country . The most common haplotype was used as the reference group and rare haplotypes with frequencies of <5% were combined into one group . Generalized linear models accounting for phase ambiguity were used to estimate haplotype-specific ORs per copy [54] , [55] . For array CGH analyses of these same cases , those with loss of chromosome arm 3p or clone CTB110j24 to those without , the presence of a loss was considered as a dependent variable in stepwise logistic regression models to first evaluate associations with clinical risk factors including: T stage ( T1 , T2 , T3–4 ) , Fuhrman nuclear grade ( 1–2 , 3–4 ) , node positivity ( N0 , N1 , N2–3 ) , and presence of metastases ( M0 , M1 , Mx ) . In addition , co-variates and etiologic risk factors ( described above ) that were previously associated with RCC risk were initially analyzed using univariate analyses , including the presence of a VHL inactivating alteration in tumor tissue ( no/yes-any ) . The criterion for initial inclusion of a variable into multivariate models was a p-value<0 . 20 . Frequency matching variables inherent to the study design ( i . e . country , sex and age ) were included into all of the models regardless of associations with outcome . Variables selected were then fitted in logistic models adjusted for sex , country , and age , to obtain odds ratios ( OR ) and 95% confidence intervals ( 95% CI ) as estimates of risk for both types of alterations . All analyses were conducted using SAS 9 . 1 . 3 software ( SAS Institute Inc . ) and STATA 10 . 0 and statistical tests were two-sided . | In a large case-series of 470 sporadic clear cell renal cancer ( ccRCC ) cases , we examined von Hippel-Lindau ( VHL ) inactivation as a biomarker of tumor heterogeneity . Germline alterations of the VHL gene were identified and have been found in most families with VHL disease , a hereditary syndrome associated with ccRCC . In sporadic disease , VHL alterations have been reported in up to 91% of cases . Here , we observed a high prevalence of VHL inactivation through both genetic and epigenetic mechanisms that were highly associated with ccRCC . VHL inactivation through promoter hypermethylation in tumors was associated with inherited polymorphisms selected to capture common variation across the VHL locus . A high-risk haplotype associated with promoter hypermethylation in tumor DNA was identified . These findings suggest that the presence of these polymorphisms and VHL promoter hypermethylation may represent an example of an inherited propensity toward epigenetic variation and potential silencing of the VHL gene in tumor tissue . This result could have translational implications , as individuals with the high-risk haplotype could be targeted for increased surveillance . Smokers had a higher prevalence of tumors without detectable VHL sequence alteration or epigenetic inactivation . Such tumors may be biologically distinct and have demonstrated a poorer prognosis compared to VHL inactivated cases . | [
"Abstract",
"Introduction",
"Results",
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] | [
"medicine",
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"cancers",
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... | 2011 | Von Hippel-Lindau (VHL) Inactivation in Sporadic Clear Cell Renal Cancer: Associations with Germline VHL Polymorphisms and Etiologic Risk Factors |
Animal African trypanosomosis ( AAT ) is a neglected tropical disease which imposes a heavy burden on the livestock industry in Sub-Saharan Africa . Its causative agents are Trypanosoma parasites , with T . congolense and T . vivax being responsible for the majority of the cases . Recently , we identified a Nanobody ( Nb474 ) that was employed to develop a homologous sandwich ELISA targeting T . congolense fructose-1 , 6-bisphosphate aldolase ( TcoALD ) . Despite the high sequence identity between trypanosomatid aldolases , the Nb474-based immunoassay is highly specific for T . congolense detection . The results presented in this paper yield insights into the molecular principles underlying the assay’s high specificity . The structure of the Nb474-TcoALD complex was determined via X-ray crystallography . Together with analytical gel filtration , the structure reveals that a single TcoALD tetramer contains four binding sites for Nb474 . Through a comparison with the crystal structures of two other trypanosomatid aldolases , TcoALD residues Ala77 and Leu106 were identified as hot spots for specificity . Via ELISA and surface plasmon resonance ( SPR ) , we demonstrate that mutation of these residues does not abolish TcoALD recognition by Nb474 , but does lead to a lack of detection in the Nb474-based homologous sandwich immunoassay . The results show that the high specificity of the Nb474-based immunoassay is not determined by the initial recognition event between Nb474 and TcoALD , but rather by its homologous sandwich design . This ( i ) provides insights into the optimal set-up of the assay , ( ii ) may be of great significance for field applications as it could explain the potential detection escape of certain T . congolense strains , and ( iii ) may be of general interest to those developing similar assays .
The Trypanosoma genus represents a diverse group of extracellular hemoflagellated parasites of which some members can infect and cause disease in humans and livestock . An infection with African trypanosomes generally leads to the development of pathologies called Human African Trypanosomosis ( HAT ) and Animal African Trypanosomosis ( AAT ) , respectively . In the case of AAT ( also called “Nagana” ) , the predominant causative agents are T . congolense and T . vivax . Estimates place 50 million animals at risk of infection in Sub-Saharan Africa and indicate that the annual AAT-driven economic losses to the local livestock industry are close to US$ 4 billion [1] . Evidently , AAT has a profound negative impact on the development of endemic regions . While drug treatments to combat AAT exist , these are deployed in an indiscriminate fashion on a large scale due to the lack of inexpensive , specific and easy-to-use diagnostic tests . These attributes are of great significance for the development of point of care tests ( POCTs ) for rapid detection of AAT in a low-income setting where the disease is endemic . Importantly , the practice of indiscriminate administration of anti-trypanosomal drugs to both healthy and diseased animals has led to the emergence of drug-resistant parasite strains [2 , 3] . For this reason , there are ongoing efforts by the research community to develop both DNA- and protein-based tests to improve diagnosis of AAT in the field . An important category of assays for the diagnosis of trypanosomosis is the one of immunodiagnostics such as enzyme-linked immunosorbent assays ( ELISAs ) and lateral flow assays ( LFAs ) [4–9] . Both the antibody- and antigen-based immunodiagnostics have their advantages and drawbacks . The antibody-based tests , which rely on the detection of circulating parasite-induced host antibodies , have two main disadvantages: ( i ) a low specificity due to antibody cross-reactivity [10] and ( ii ) the inability of differentiating between past and ongoing infections as a consequence of long lasting circulating antibodies after parasite clearance [11–13] . These problems are alleviated by antigen-based assays , which aim to detect circulating parasite antigens . However , antigen-based diagnostic tests face their own issues . First , during an active infection , antigen levels should be high enough in order to be detected [14] . Second , the detection and capturing antibodies of the assay should bind to different epitopes from the host antibodies , which usually form immuno-complexes with the circulating antigen or at least be able to outcompete them [15] . Finally , the assay’s antibodies should be species-specific , which is not straightforward given that some antigens are highly conserved among different Trypanosoma species . Recently , we described an antigen-based immunoassay for diagnosis of active T . congolense infections using Nanobody ( Nb ) technology [16] . The immunoassay is designed in the format of a homologous sandwich ELISA employing a single Nb ( Nb474 ) . The target of the assay was identified as T . congolense fructose-1 , 6-bisphosphate aldolase ( TcoALD ) and , hence , validates this enzyme as a diagnostic biomarker for T . congolense infections [16] . Fructose-1 , 6-bisphosphate aldolase is an enzyme involved in the glycolytic pathway and most members of this protein family occur in solution as tetramers . This is because of the low dissociation constants for the dimer-tetramer equilibria , resulting in stable tetramer formation [17] . In trypanosomatids , most glycolytic enzymes ( including aldolase ) are located in specialized organelles called glycosomes [18] . At first glance , the potential of an intracellular , glycosomal enzyme as an infection biomarker may seem counterintuitive . However , it has recently been discovered that , within the context of host-parasite interactions , trypanosomes produce extracellular vesicles containing many different proteins including fructose-1 , 6-bisphosphate aldolase [19] . As such , TcoALD is part of the T . congolense “secretome” , i . e . the collection of all molecules secreted/excreted by the parasite [20] , which is probably why it can act as a biomarker for active T . congolense infections . The Nb474-based ELISA is highly specific for T . congolense as infections with other trypanosomes such as T . brucei brucei , T . vivax , and T . evansi are not detected . Concomitantly , the Nb474 sandwich ELISA only yields a positive signal when incubated with TcoALD and is negative for the detection of TbALD and LmALD ( T . brucei brucei and Leishmania mexicana glycosomal fructose-1 , 6-bisphosphate aldolase ) [16] . This is remarkable given that glycolytic enzymes such as fructose-1 , 6-bisphosphate aldolase display a relatively high degree of sequence conservation , especially among different trypanosome species ( 94 . 1% for TcoALD and TbALD ) . These findings raise questions about the molecular details of the Nb474-TcoALD interaction determining the specificity of this particular assay . In this study , we present the structural basis for the high specificity of the Nb474-based T . congolense homologous sandwich ELISA . Using a combination of X-ray crystallography , site-directed mutagenesis , ELISA and surface plasmon resonance ( SPR ) , we demonstrate that the high specificity of the Nb474-based immunoassay is determined by its sandwich design . The results may serve as a basis for the improvement of the Nb474-based ELISA and the design of similar antigen-based diagnostic tests .
The generation of Nb474 by alpaca immunization , the recombinant production of its C-terminally His-tagged variant in E . coli and subsequent purification by IMAC and size exclusion chromatography ( SEC ) have been described recently [16] . The recombinant production of C-terminally His-tagged TcoALDWT in E . coli was performed as described [16] . To purify TcoALDWT from an overnight production culture , cells were first harvested by centrifugation ( 10 min; 8000 rpm , JLA-8 . 1000 rotor; 14°C ) . The bacterial pellets were resuspended in lysis buffer ( 50 mM Tris-HCl , 500 mM NaCl , pH 8 . 0 ) and aliquoted in volumes of 50 ml . The aliquots were flash-frozen using liquid nitrogen and stored at -80°C . Prior to purification , aliquots were thawed on ice . Cells were lysed using a sonicator ( Ultrasonic disintegrator MSE Soniprep 150; 5 sonication cycles of 1 min at 15 microns amplitude with a 2 min pause between each cycle ) and the cell lysate was centrifuged ( 20 min , 18000 rpm , JA-20 rotor , 4°C ) . The supernatant was collected and filtered ( 0 . 45 μm ) . The purification of TcoALDWT was performed on an AKTA Prime Platform ( GE Healthcare ) using IMAC and SEC . A 5 ml HisTrap HP nickel-sepharose column ( GE Healthcare ) was equilibrated with buffer A ( 50 mM Tris-HCl , 500 mM NaCl , pH 8 . 0 ) for at least five column volumes . The sample was loaded on the column using the same buffer at a flow rate of 1 ml min-1 . After loading , the column was further washed with 5 column volumes of the same buffer . TcoALDWT was then eluted by a linear gradient of buffer B ( 50 mM Tris-HCl , 500 mM NaCl , 1 M imidazole , pH 8 . 0 ) over 20 column volumes . The fractions containing TcoALDWT were pooled and concentrated to a final volume of 2 ml for the subsequent SEC step on a Superdex 200 16/60 column ( GE Healthcare ) , which was pre-equilibrated with at least one column volume of buffer C ( 50 mM MES , 500 mM NaCl , pH 6 . 7 ) . The sample was eluted at a flow rate of 1 ml min-1 . Fractions containing TcoALDWT were pooled and stored at 4°C . Each of the purification steps was monitored by SDS-PAGE and Western blot under reducing conditions . The purification and storage conditions for TcoALDWT were optimized via differential scanning fluorimetry ( DSF , see S2 Fig ) . The TcoALDA77E , TcoALDL106Y , and TcoALDA77E/L106Y mutants were generated by modifying the TcoALDWT sequence . Synthesis and cloning of the mutant sequences was outsourced to a commercial company ( GenScript ) . These mutants were produced and purified as described for TcoALDWT . The stoichiometry of the Nb474-TcoALD complex was determined by analytical SEC . The experiments were performed using a Superdex 200 HR 10/30 ( GE Healthcare ) column , pre-equilibrated with buffer C for at least one column volume . Five hundred μl samples containing 1 mg TcoALD mixed with varying molar ratios of Nb474 ( Nb474:TcoALD ratios of 1:4 , 2:4 , 3:4 , 4:4 , and 6:4 , respectively ) were allowed to incubate for at least 1 h prior to injection . The samples were eluted with a flow rate of 0 . 5 ml min-1 and the elution peaks of all chromatograms were subjected to SDS-PAGE analysis . The column was calibrated with the Bio-Rad molecular mass standard under the same conditions . The ( Nb474-TcoALD ) 4 complex was generated by mixing Nb474 and TcoALD in a Nb474:TcoALD ratio of 6:4 , allowing the sample to equilibrate for at least 1 h prior to purification on a Superdex 200 16/60 column ( GE Healthcare ) pre-equilibrated with at least one column volume of buffer C . The sample was eluted at a flow rate of 1 ml min-1 . Fractions containing the ( Nb474-TcoALD ) 4 complex were pooled and stored at 4°C . Differential scanning fluorimetry ( DSF ) experiments were performed to optimize the purification and storage conditions of TcoALD . DSF was performed on a CFX Connect Real-Time System Thermal Cycler ( Bio-Rad ) . Data were collected from 10°C to 95°C at a scan rate of 1°C min-1 . The fluorescence signal was recorded every 0 . 5°C . Experiments were carried out in 96-well plates and the total sample volume was 25 μl . To determine the optimal protein-dye ratio , a grid screen of various concentrations of SYPRO orange dye ( Life Technologies ) ( 0x , 5x , 10x , 50x , 100x ) and TcoALD ( 0 μM , 1 μM , 5 μM , 10 μM , 25 μM , 50 μM ) was carried out . After identification of a suitable condition ( 10x SYPRO orange dye and 5 μM of TcoALD ) , buffer and additive screens were performed as previously described [21] . All experiments were conducted in duplicate . The ( Nb474-TcoALD ) 4 complex was concentrated to 0 . 5 mg ml-1 using a 5 , 000 molecular weight cut-off concentrator ( Sartorius Vivaspin20 ) . Crystallization conditions were screened manually using the hanging-drop vapor-diffusion method in 48-well plates ( Hampton VDX greased ) with drops consisting of 2 μl protein solution and 2 μl reservoir solution equilibrated against 150 μl reservoir solution . Commercial screens from Hampton Research ( Crystal Screen , Crystal Screen 2 , Crystal Screen Lite , Index ) , Molecular Dimensions ( MIDAS , JCGS+ ) , and Jena Bioscience ( JBScreen Classic 1–10 ) were used for initial screening . The His-tags of both proteins were retained for crystallization . The crystal plates were incubated at 20°C . Diffraction-quality crystals of the complex were obtained in Crystal Screen Lite ( Hampton Research ) no . 18 ( 100 mM sodium cacodylate pH 6 . 5 , 200 mM magnesium acetate , 10% PEG 8000 ) and the crystals grew after approximately 14 days at 20°C . The ( Nb474-TcoALD ) 4 crystals were cryocooled in liquid nitrogen with the addition of 25% ( v/v ) glycerol to the mother liquor as a cryoprotectant in 5% increments . Data were collected on the PROXIMA2 beamline at the SOLEIL synchrotron ( Gif-Sur-Yvette , France ) and were processed with XDS [22] . The quality of the collected data sets was verified by close inspection of the XDS output files and through phenix . xtriage in the PHENIX package [23] . Twinning tests were also performed by phenix . xtriage . Analysis of the unit-cell contents was performed with the program MATTHEWS_COEF , which is part of the CCP4 package [24] . The structure of the ( Nb474-TcoALD ) 4 complex was determined by molecular replacement with PHASER-MR [25] using the structure of T . brucei aldolase ( PDB ID: 1F2J , [26] ) as a search model . This provided a single solution ( top TFZ = 96 . 4 and top LLG = 14236 . 4 ) . From here , refinement cycles using the maximum likelihood target function cycles of phenix . refine [27] were alternated with manual building using Coot [28] . The final resolution cut-off was determined through the paired refinement strategy [29] , which was performed on the PDB_REDO server [30] . The crystallographic data for the ( Nb474-TcoALD ) 4 complex are summarized in Table 1 and have been deposited in the PDB ( PDB ID 5O0W ) . Molecular graphics and analyses were performed with UCSF Chimera [31] . The amino acid sequences of trypanosomatid homologs of TcoALD were obtained by a protein BLAST search of the TriTrypDB [32] using TcoALD ( Uniprot ID: G0UWE7 ) as a query sequence . A total of 24 trypanosomatid aldolase sequences ( including TcoALD ) were employed to generate a sequence alignment with MAFFT [33] using the Geneious Pro program suite ( Biomatters Ltd ) . The amino acid sequences of TcoALD homologs from T . congolense MOSROM_ALL , T . congolense SA268 , T . congolense KAPEYA357 , and T . congolense ZER-AGRIUMBE were kindly provided by dr . Hideo Imamura . The details on these sequences and how they were obtained have recently been published [34] . Genomic DNA samples from T . congolense TSW103 , T . congolense WG84 , T . simiae Ban7 , and T . godfreyi Ken7 were kindly provided by Prof . dr . Wendy Gibson . More information concerning these sequences can be found in the work by Masiga et al . [35] . The gene encoding aldolase was extracted from these genomic DNA samples via PCR . Four different primers were designed to amplify the aldolase-coding genes based on the nucleotide sequence of the T . congolense IL3000 aldolase gene ( Genbank accession number CCC93713 . 1 ) : one set of primers to amplify the entire gene ( TcoALDcFwd: 5’-ATGTCCAGGCGTGTGGAAGTTC-3’; TcoALDcRev: 5'-CTAGTAGGTGTTGCCAGCAAC-3' ) , a short region from the gene encoding Met1 to L181 ( TcoALDcFwd: 5’-ATGTCCAGGCGTGTGGAAGTTC-3’; TcoALDOcshRev: 5'-CGAGCGTTTCAGCGTTGAA-3' ) , or a short region from the gene encoding Y162 to Y372 ( TcoALDcshFwd: 5-ACAAGATTCAGAACGGCAC-3'; TcoALDcRev: 5'-CTAGTAGGTGTTGCCAGCAAC-3' ) . The PCR mix contained the following components: 0 . 4 mM forward primer , 0 . 4 mM reverse primer , 0 . 4 mM dNTPs , 1x GoTaq G2 buffer ( Promega ) , 1 . 5 U GoTaq G2 DNA polymerase ( Promega ) , 5 ng genomic DNA . The PCR was performed according to the following protocol: ( i ) 30 cycles of denaturation ( 95°C , 5 min ) , denaturation ( 94°C , 1 min ) , annealing ( 55°C , 1 . 5 min ) , elongation ( 72°C , 1 min ) , ( ii ) elongation ( 72°C , 10 min ) , ( iii ) storage ( 4°C ) . Amplified PCR products were resolved by electrophoresis on 1% agarose ( Lonza ) in TBE buffer ( 90 mM Tris , 90 mM borate , 2 . 5 mM EDTA ) . Electrophoresis was conducted at 100V for 30 minutes . Amplicons were cleaned-up using the PCR clean-up kit ( Sigma-Aldrich ) following the protocol recommended by the manufacturer . Gene sequences were obtained through DNA sequencing with 50 pmol of each primer . Sequencing of the samples was outsourced to the VIB Genetic Service Facility . A total of 16 aldolase sequences were employed to generate a sequence alignment with MAFFT [33] using the Geneious Pro program suite ( Biomatters Ltd ) . The Nb474H/Nb474B homologous and Nb474B/mouse anti-His heterologous sandwich ELISAs were performed in similar manner as previously described [16] . Briefly , Nb474H ( homologous ELISA ) or Nb474B ( heterologous ELISA ) was coated on the plate as capture reagent by applying 100 μl ( diluted to a concentration of 0 . 02 μg ml-1 in PBS ) per well . The plate was incubated overnight at 4°C and the excess of non-coated Nb was removed by washing the plate three times with PBS containing 0 . 01% Tween20 ( PBS-T ) . Next , blocking of residual protein binding sites was performed by adding 300 μl blocking buffer ( 5% milk powder in PBS ) to each well and the plate was kept for 2 h at room temperature . Subsequently , the plate was washed three times with PBS-T , after which the TcoALD wild type and mutant variants were allowed to interact with the coated Nb by applying 100 μl ( diluted to a concentration of 1 μg ml-1 in blocking buffer ) per well . After incubation for 1 h at room temperature , the plates were subsequently washed three times with PBS-T . Then , 100 μl Nb474B ( diluted to a concentration of 0 . 02 μg ml-1 in blocking buffer ) or 100 μl mouse anti-His ( diluted to a concentration of 0 . 05 μg ml-1 in blocking buffer ) was added to the plate as a primary detection reagent for the homologous and heterologous ELISAs , respectively . After an incubation of 1 h at room temperature , the plate was washed 5 times with PBS-T . The conjugate , 100 μl of streptavidin-HRP ( diluted to a concentration of 1 μg ml-1 in rinsing buffer ) or 100 μl goat anti-mouse-HRP ( diluted to a concentration of 0 . 05 μg ml-1 in blocking buffer ) , was then added to the plate for the homologous and heterologous ELISAs , respectively , followed by incubation for 1 h at room temperature . After a final washing step ( 5 times with PBS-T ) , the ELISAs were developed by addition of 100 μl of 3 , 3’ , 5 , 5’-tetramethylbenzine ( TMB ) substrate and subsequent incubation for 25 min at room temperature . The enzymatic reaction was stopped by adding 50 μl 1 M H2SO4 to the reaction mixture . The plates were read at OD450 nm with a VersaMax ELISA Microplate Reader ( Molecular Devices ) . Surface plasmon resonance ( SPR ) experiments were performed on a BIAcore T200 system ( GE Healthcare ) . The interactions between Nb474 and the TcoALD variants were analyzed on a CM5 chip . Nb474 was immobilized in flow cell 2 using the following procedure . Using a flow rate of 5 μl min-1 the carboxylated dextran matrix was activated by a 7-min injection of a solution containing 0 . 2 M N-ethyl-N′- ( 3-diethylamino ) propyl carbodiimide ( EDC ) and 0 . 05 M N-hydroxysuccinimide ( NHS ) . A Nb474 solution of 1 μg ml-1 ( 50 mM sodium acetate pH 5 . 0 ) was subsequently injected until the desired amount of protein was immobilized ( approx . 50 R . U . ) . The surface immobilization was then blocked by a 7-min injection of 1 M ethanolamine hydrochloride . The surface in flow cell 1 was used as a reference and treated only with EDC , NHS and ethanolamine . Sensorgrams for different concentrations of the TcoALD variants expressed as monomer concentrations ( 0 . 02 nM , 0 . 05 nM , 0 . 10 nM , 0 . 20 nM , 0 . 35 nM , 0 . 50 nM , 0 . 75 nM , 1 . 00 nM , 2 . 00 nM , 5 . 00 nM , 10 . 00 nM for TcoALDWT; 0 . 78 nM , 1 . 56 nM , 3 . 12 nM , 6 . 25 nM , 12 . 50 nM , 25 . 00 nM , 50 . 00 nM , 100 . 00 nM , 125 . 00 nM , 250 . 00 nM , 500 . 00 nM for TcoALDA77E; 0 . 12 nM , 0 . 24 nM , 0 . 49 nM , 0 . 98 nM , 1 . 95 nM , 3 . 90 nM , 7 . 81 nM , 15 . 62 nM , 31 . 25 nM , 62 . 50 nM , 125 . 00 nM for TcoALDL106Y; 0 . 78 nM , 1 . 56 nM , 3 . 12 nM , 6 . 25 nM , 12 . 50 nM , 25 . 00 nM , 50 . 00 nM , 100 . 00 nM , 125 . 00 nM , 250 . 00 nM , 500 . 00 nM , 750 . 00 nM , 1 . 00 μM for TcoALDA77E/L106Y ) plus a 0 concentration ( injection of running buffer ) were collected at a flow rate of 30 μl min-1 and a data collection rate of 1 Hz . For the Nb474 binding/washing experiments , the ligand ( Nb474 ) was first saturated by an injection of an adequate concentration of the first analyte ( TcoALD variant; 10 nM for TcoALDWT , 125 nM for TcoALDA77E , 31 . 25 nM for TcoALDL106Y , and 750 nM for TcoALDA77E/L106Y ) . Immediately after injection of the first analyte ( i . e . , no dissociation phase ) , different concentrations of the second analyte ( Nb474; 0 . 5 nM , 1 . 0 nM , 1 . 5 nM , 5 . 0 nM , 10 . 0 nM , 100 . 0 nM , 500 . 0 nM , 1 . 0 μM ) plus a 0 concentration ( injection of running buffer ) were injected at a flow rate of 30 μl min-1 and a data collection rate of 1 Hz . All analytes were dialyzed into the running buffer ( 20 mM HEPES , 150 mM NaCl , 0 . 005% Tween , 3 . 4 mM EDTA , pH 7 . 4 ) prior to data collection . Analyte injections were performed with association and dissociation phases of 480 s and 660 s , respectively . This was followed by a 5 μl pulse injection of regeneration buffer ( 0 . 2% SDS ) . Prior to data analysis , reference and zero concentration data were subtracted from the sensorgrams . The data collected for Nb474 binding to the pre-formed Nb474-TcoALDWT and Nb474-TcoALDA77E complexes were analyzed with a 1:1 Langmuir binding model . All experiments were performed on the same sensor chip using the same flow channels .
The amino acid sequences of glycolytic enzymes such as fructose-1 , 6-bisphosphate aldolase are generally well conserved . Indeed , among trypanosomatids , the pairwise sequence identity for aldolase is 86 . 7% ( S1 Fig ) . For TcoALD and TbALD , the sequence identity is 94 . 1% . Nonetheless , the Nb474-based immunoassay is highly specific for TcoALD . Thus , we were interested in identifying the TcoALD epitope recognized by Nb474 . First , we produced TcoALD through recombinant protein production in E . coli and optimized its purification conditions via DSF . The details of these procedures are given in Materials and Methods and S2 Fig ( panels A-D ) . Next , we determined the stoichiometry of the Nb474-TcoALD complex via analytical SEC ( Fig 1 ) . An excess of Nb474 could only be detected at a molar ratio of 6:4 between Nb474 and the TcoALD monomer , and not at the other tested ratios 1:4 , 2:4 , 3:4 , and 4:4 . This suggests that one Nb474 binds a single TcoALD monomer . The analytical SEC reveals another interesting feature of the Nb474-TcoALD interaction . First , TcoALD appears to occur as a dimer in solution . The TcoALD monomer has a theoretical molecular mass of 42 . 6 kDa ( 170 . 4 kDa for a TcoALD tetramer ) . Instead , TcoALD migrates with a higher apparent molecular mass ( MMapp = ~66 kDa , Fig 1H ) , suggesting a dimer population ( TcoALD2 ) . Second , a comparison of the analytical SEC profiles recorded for the different ratios between Nb474 and the TcoALD monomer suggests that adding Nb474 to TcoALD promotes tetramer formation . Rather than shifting the TcoALD2 peak to the left , the titration of Nb474 reduces the intensity of the TcoALD2 peak and gives rise to a peak corresponding to an entity of larger molecular mass . At an estimated molecular mass of ~230 kDa for the peak at a 4:4 molar ratio ( Fig 1F ) , this complex likely corresponds to a hetero-octameric ( Nb474-TcoALD ) 4 complex in which four Nb474 occupy identical sites on the TcoALD tetramer ( TcoALD4 ) . Indeed , the theoretical molecular mass of such a complex is 233 . 52 kDa , which is in accordance with the molecular mass calculated based on the analytical SEC data ( Fig 1H ) . For crystallization purposes , the ( Nb474-TcoALD ) 4 complex was prepared using a 6:4 molar ratio as described above and purified by SEC . Crystals of the ( Nb474-TcoALD ) 4 complex and their diffraction are shown in S2 Fig ( panels E-F ) . The details of the crystallographic experiment are summarized in Table 1 . The crystal structure of the ( Nb474-TcoALD ) 4 complex confirms that TcoALD4 indeed contains 4 binding sites for Nb474 ( Fig 2 ) . Nb474 binds an epitope on the TcoALD surface that is located relatively far away from the aldolase A and B dimer interfaces . This results in large distances between the Nb474 epitopes on TcoALD4 relative to the A and B dimer interfaces ( ~ 69 Å and ~ 79 Å from one epitope to another , respectively ) . The Nb474-TcoALD interaction is mediated by residues from all three complementarity determining regions ( CDRs; Fig 2 ) . The bulk of the contacts are provided by CDR1 and CDR3 , while a single amino acid from CDR2 ( Arg53 ) is involved in TcoALD recognition . A detailed overview of all the interactions is given in S3 Fig and S1 Table . A superposition of the crystal structures of TbALD ( PDB ID: 1F2J , [26] ) , LmALD ( PDB ID: 1EPX , [26] ) , and the ( Nb474-TcoALD ) 4 complex allows to pinpoint those residues that are located in the vicinity of or on the TcoALD epitope recognized by Nb474 and are distinct between the three trypanosomatid aldolases ( Fig 3A ) . These residues are located at positions 76 , 77 , 96 , 98 , 99 , 101 , 109 , 328 , and 332 for TcoALD and TbALD . For LmALD , all positions are shifted by -1 . We reasoned that mutating some of these TcoALD residues to their TbALD/LmALD counterparts would influence Nb474 binding and provide a starting point to explain the assay’s specificity . Within the above-mentioned selection of amino acids , we first identified those residues that are conserved in both TbALD and LmALD , but differ in TcoALD . These amino acids would most likely contribute to a loss of binding energy given that the Nb474-based immunoassay does not provide a binding signal for both TbALD and LmALD [16] . This narrowed the selection of residues to mutate down to four positions: A77/E77 , R96/K96 , L106/Y106 , and S328/E328 for TcoALD/TbALD ( E76 , K95 , Y105 , and E327 for LmALD ) . Positions 96 and 328 were further omitted because , based on the structural comparison depicted in Fig 3B , these are too far from the Nb474 paratope to have any influence on Nb474-TcoALD interaction . This resulted in a final selection of two positions that were targeted for site-specific mutagenesis: A77/E77 and L106/Y106 for TcoALD/TbALD ( E76 and Y105 for LmALD ) . Hence , three TcoALD mutants ( TcoALDA77E , TcoALDL106Y , and TcoALDA77E/L106Y ) were generated . The different TcoALD variants were tested in the Nb474-based homologous sandwich ELISA and compared . As can be seen from Fig 4A , TcoALDA77E is still detected , although to a lesser extent compared to TcoALDWT , whereas TcoALDL106Y and TcoALDA77E/L106Y display no signal . Two hypotheses could be presented to explain these observations . The first poses that the lack of detection of the TcoALD mutants is caused by a loss of recognition by Nb474 due to the introduced mutations . The second explanation states that the mutations somehow weaken the Nb474-TcoALD interaction and that a “self-competition” or “washing” effect is at play because of the homologous sandwich design of the assay . In order to distinguish between both hypotheses , a second , heterologous ELISA was carried out with Nb474B as a capturing agent ( Fig 4B ) . Compared to TcoALDWT , the three mutants display a lower but clear signal , with TcoALDA77E/L106Y providing the lowest intensity . When combined , the results of both ELISAs suggest that Nb474 still interacts with the TcoALD mutants , thus favoring the second hypothesis . The interaction between Nb474 and each of the TcoALD variants was investigated further via SPR . For this experiment , Nb474 and the TcoALD variants were employed as ligand and analytes , respectively . From Fig 5 ( panels A-D ) , it is clear that all TcoALD mutants bind to Nb474 and that the kinetics of the Nb474-TcoALD interaction are affected by the A77E , L106Y , and A77E/L106Y mutations . Unfortunately , this could not be quantified by any interaction model , which is why the interpretation of the presented SPR data is performed in a semi-quantitative fashion . For TcoALDWT , saturation is readily observed at an enzyme concentration of 10 nM ( maximal binding signal Rmax of ~110 R . U . ; Fig 5A ) . This indicates that the affinity of the Nb474-TcoALDWT interaction is quite high ( nM to pM range ) , which is supported by the necessity of solutions containing 0 . 2% SDS to regenerate the Nb474-coated sensor chip surface . The three TcoALD mutants only attain a similar maximal binding signal at higher analyte concentrations ( Fig 5 , compare panels A-D ) , suggesting that the binding of Nb474 to the TcoALD mutants is weakened by the introduced mutations . Interestingly , although TcoALDA77E only reaches a binding signal of ~110 R . U . at a concentration of 500 nM ( Fig 5B ) , the dissociation phases for the Nb474-TcoALDWT and Nb474-TcoALDA77E interactions seem very similar . In the case of TcoALDL106Y , a signal of ~110 R . U . is attained at a concentration of 125 nM ( Fig 5C ) , while the dissociation of this complex appears to occur faster . Finally , binding of Nb474 to TcoALDA77E/L106Y does not reach the maximal signal observed for the other TcoALD variants , even at a concentration of 1 μM ( Fig 5D ) . An additional SPR experiment was designed to mimic the homologous sandwich ELISA ( Fig 5 , panels E-H ) . The basic set-up is the same as mentioned above: Nb474 and the TcoALD variants were selected as ligand and analytes , respectively . For each TcoALD variants , the analyte concentration was chosen to saturate the Nb474-coated sensor chip surface . Upon saturation , Nb474 was injected onto the sensor chip surface at different concentrations and allowed to interact with the pre-formed Nb474-TcoALD complex . For both TcoALDWT and TcoALDA77E , this results in additional binding of Nb474 and formation of Nb474-TcoALDWT-Nb474 and Nb474-TcoALDA77E-Nb474 sandwiches ( Fig 5 , panels E and F ) . Interestingly , these binding curves can be fitted with a 1:1 Langmuir binding model . It appears that the Nb474-TcoALD interaction is virtually unaffected by the A77E mutation as the affinity constants for both binding events are quasi identical ( Table 2 ) . In the case of TcoALDL106Y and TcoALDA77E/L106Y , the injection of additional Nb474 leads to dissociation of the pre-formed Nb474-TcoALD complex as evidenced by a reduction in RU signal over time ( Fig 5 , panels G and H ) . The ELISA data in conjuncture with the SPR results indicate that the high specificity for TcoALD displayed by the Nb474-based immunoassay is not determined by the initial interaction between TcoALD and the capturing Nb474 , but rather from its homologous sandwich design . The above-mentioned mutation studies imply that T . congolense strains carrying mutations at positions 77 and/or 106 would be detected less efficiently ( or not at all ) by the Nb474-based homologous sandwich ELISA . To probe the aldolase sequence variation within the Trypanosoma subgenus Nannomonas , of which T . congolense is a member , the aldolase amino acid sequences were determined for the following parasites: T . congolense ( Savannah type ) , T . congolense ( Forest type ) , T . congolense ( Kilifi type ) , T . simiae , and T . godfreyi . A sequence alignment reveals that the sequence identity of aldolase within Nannomonas is relatively high ( 90 . 6%; S4 Fig ) . Interestingly , while position 106 remains unaltered throughout all sequenced Nannomonas members ( Leu106 ) , position 77 displays a larger sequence variation: T . congolense Savannah and Kilifi subtypes contain an Ala77 , T . congolense Forest subtypes harbor a Val77 , and T . simiae and T . godfreyi both possess a Glu residue at position 77 ( S4 Fig ) .
Animal African Trypanosomosis is neglected on a global scale , yet it continues to impose a heavy societal and economic burden on Sub-Saharan Africa [1] . However , the disease can be contained provided that the necessary control and surveillance programs are put in place . For HAT , such multidisciplinary initiatives have “eliminated the disease as a public health problem” [36] , which means that in most areas HAT can be targeted for eradication . Together with vector control strategies and adequate treatment schemes , tools for rapid diagnosis of AAT are of utmost importance . Luckily , such assays targeting T . congolense and T . vivax infections ( the two important causative agents of AAT in livestock ) are under development [4–7 , 9] . Recently , we described the generation of a highly specific Nb-based homologous sandwich ELISA targeting TcoALD to detect active T . congolense infections [16] . Evidently , the principle of a homologous sandwich ELISA can only work if the target antigen is a multimer [37 , 38] . Members of the fructose-1 , 6-bisphosphate aldolase family usually occur in solution as stable tetramers [17] . Mutations at the A and B dimer interfaces influence the dimer-tetramer equilibria by destabilizing the tetramer , but , interestingly , without affecting the enzyme’s catalytic activity [17 , 39 , 40] . While aldolase dimers retain the same catalytic potential compared to tetramers , they appear to be less thermostable [39] . In the case of TcoALD , the analytical SEC data presented here indicates that the enzyme does not occur as a tetramer in solution , but rather seems to behave as a dimer . This suggests that the dissociation constants for the dimer-tetramer equilibria are higher for TcoALD compared to archetypal aldolases . This may also explain why TcoALD was observed to be labile during our first purification trials . Using DSF , we markedly improved the thermal stability of TcoALD ( melting temperatures Tm of ~40°C and ~50°C in the initial and final buffer conditions , respectively ) . Interestingly , in their work on rabbit muscle aldolase , Beernink and Tolan measured Tm values of ~45°C and ~60°C for aldolase dimers and tetramers , respectively [39] . Nb474 clearly influences the TcoALD dimer-tetramer equilibria . As shown by analytical SEC , the titration of Nb474 against TcoALD shifts the equilibrium towards the formation of an aldolase tetramer . The end-point of the titration is reached at a Nb474:TcoALD molar ratio of 4:4 , suggesting the formation of a hetero-octameric ( Nb474-TcoALD ) 4 complex , which is confirmed by X-ray crystallography . The crystal structure of the ( Nb474-TcoALD ) 4 complex provides a molecular basis as to why the homologous sandwich ELISA format works in the case of TcoALD . The Nb474 epitope is located on the extremities of the TcoALD tetramer , thereby easily allowing all four copies of Nb474 to bind their epitopes without mutual interference . A detailed analysis of the Nb474-TcoALD interface reveals a multitude of interactions between both proteins , mainly mediated by CDR1 and CDR3 residues . The SPR data demonstrate that these interactions result in a high-affinity recognition event ( KD in the pM range ) , which explains why Nb474 is such a good capturing agent [16] . In some cases , the mutation of a single residue on the antigen’s epitope can cause total loss of antigen recognition by the Nb [41] . In contrast , the mutation studies presented here indicate that this is not the case for the Nb474-TcoALD interaction . Changing specific TcoALD epitope residues to their TbALD/LmALD counterparts ( A77E , L106Y , A77E/L106Y ) does not result in a loss of TcoALD recognition by Nb474 . Instead , an interaction still takes place , albeit with different kinetics , suggesting that the mutations have a significant effect on TcoALD binding . Unfortunately , this could not be quantified by any interaction model . This indicates that the interactions taking place on the sensor chip surface are relatively complex . Indeed , based on the analytical SEC results , we suspect that multiple events occur simultaneously on the sensor chip surface . First , TcoALD occurs as a dimer in solution making it a bivalent analyte . Hence , this possibly leads to avidity effects on the sensor chip , whereby one TcoALD2 is able to bind two Nbs simultaneously . The use of an analysis model designed to take such effects into account was attempted [42] , but this did not improve the fit . Second , since Nb474 binding promotes TcoALD2 tetramer formation , this would mean that , on the sensor chip surface , binding of a TcoALD2 to a Nb allows the subsequent recruitment of an additional TcoALD2 onto a formed Nb474-TcoALD2 complex . Moreover , the effect of the introduced mutations on the TcoALD dimer-tetramer equilibria is unknown . Generally , in such complex cases , the ‘analyte’ should be immobilized on the sensor surface to become ‘ligand’ and the ‘ligand’ should be used in the mobile phase to become ‘analyte’ . However , employing the TcoALD variants as ligands is not an option as they do not survive the harsh regeneration condition used during the experiment ( 0 . 2% SDS ) . Given the complexity of the interactions on the sensor chip surface , we therefore prefer not to fit the data with any model to avoid overparametrization and misinterpretation of the real KD value describing the Nb474-TcoALD interaction . Hence , we interpreted the SPR data in a semi-quantitative manner . A determination of the dissociation affinity constants for the Nb474-TcoALDWT and Nb474-TcoALDA77E becomes possible when the SPR experiments are carried out according to the format of the homologous sandwich ELISA . Surprisingly , both interactions have very similar affinities ( 73 . 83 pM and 66 . 97 pM , respectively ) despite the mutation of an Ala to a bulkier , charged Glu residue . This can be explained by a closer examination of the Nb474 paratope ( S5A Fig ) . Nb474 contains a cavity , which is perfectly aligned with the position of Ala77 on the TcoALD epitope . Hence , given a local rearrangement , a Glu side chain could be easily accommodated . We hypothesize that Nb474 immobilized in an ELISA well or on a sensor chip surface has less conformational freedom to accommodate the Glu77 side chain , which leads to less efficient binding of TcoALDA77E . This explains why , during the SPR experiments , a 50-fold increase in analyte concentration was needed for TcoALDA77E compared to TcoALDAWT in order to reach the same binding signal . However , once bound , the Nb474-TcoALDA77E dissociation displays the same kinetics as for the Nb474-TcoALDWT interaction as evidence by the SPR data . In contrast , non-immobilized Nb474 has the conformational freedom to accommodate Glu77 on TcoALDA77E efficiently , thereby displaying very similar binding kinetics as observed for interaction with TcoALDWT . In the case of TcoALDL106Y and TcoALDA77E/L106Y , investigation of the homologous sandwich ELISA format with SPR reveals that non-immobilized Nb474 outcompetes immobilized Nb474 for antigen binding and thus washes the antigen off the Nb474-coated surface . Although the affinity constants for the Nb474-TcoALDL106Y and Nb474-TcoALDA77E/L106Y could not be measured directly , these observations suggest that these mutations weaken the Nb-antigen interaction . For the L106Y mutation , this can again be explained by examination of the structure . The presence of a Tyr residue at this position would disrupt the salt bridge between Asp106 of Nb474 and TcoALD Arg109 and Arg110 ( S5B Fig ) . The A77E/L106Y double mutant most likely experiences a combined effect of both mutations , which is why TcoALDA77E/L106Y yields the lowest binding signals in all experimental set-ups . Together , the SPR and crystallographic data explain the results of the Nb474-based homologous sandwich ELISA . Compared to TcoALDWT , a low signal was observed for TcoALDA77E , whereas TcoALDL106Y and TcoALDA77E/L106Y could not be detected . While the Nb474-based immunoassay is highly specific for diagnosing T . congolense infections , our mutations studies imply that the detection of all T . congolense strains may not be guaranteed . In our previous work [16] , we tested the Nb474-based ELISA on the sera of mice infected with different T . congolense strains of the Savannah subtype . While some infected sera gave rise to very high signals ( T . congolense strains TC13 , IL1180 , Ruko 14cl3 , and MF3cl2 ) , others displayed low binding ( T . congolense strains STIB68 , TRT55 , MF5cl4 ) . It is difficult to assess whether these differences arise from i ) varying expression levels of TcoALD between the distinct T . congolense strains , ii ) the occurrence of mutations on the epitope recognized by Nb474 with effects similar to the A77E , L106Y , and A77E/L106Y mutations studied in this paper , or iii ) a combination of both . Our results concerning the aldolase sequences within the Nannomonas subgenus seem to suggest the first hypothesis . The aldolase amino acid sequence conservation among all T . congolense subtypes tested in this work ( Savannah , Forest , Kilifi ) is very high ( 95 . 2% ) . Most importantly , the amino acids at positions 77 and 106 are relatively well conserved ( Ala77 and Leu106 for Savannah and Kilifi subtypes; Val77 and Leu106 for Forest subtype ) . While the T . congolense Forest subtype contains a Val at position 77 , this is not expected to severely impact detection in the Nb474-based immunoassay based on our findings . Given that Val and Ala are chemically and structurally much more similar than Glu and Ala , the Nb474-TcoALD interaction is likely to be much less perturbed by the Ala77Val than the Ala77Glu mutation . Hence , this would suggest that the Nb474-based immunoassay would detect all T . congolense infections . However , the potential occurrence of T . congolense strains carrying mutations that would escape detection in the Nb474-based ELISA is not unconceivable . This finding calls for an extensive and detailed molecular characterization of the different T . congolense strains and sequence their genomes . Finally , it is interesting to note that the pig-infective T . simiae and T . godfreyi parasites have an aldolase with an Ala77Glu and Leu106 genotype , suggesting that the Nb474-based could be employed to detect infections of these trypanosomes . The data presented here also provide insights into the practical set-up of the Nb474-based ELISA . The amounts of capturing and detecting Nb474 yielding the highest signal were determined using a checkerboard ELISA format without prior knowledge of the Nb474-target interaction and its affinity [16] . The outcome of this effort is shown as a heat map in Fig 6 . The highest ELISA signal is obtained when relatively low amounts of both capturing and detecting Nb474 are used ( ~ 2 ng for both , respectively ) . In the case where the optimal amount of capturing Nb474 is kept fixed ( ~ 2 ng ) , any deviation ( higher or lower ) from the optimal 2 ng amount of detecting Nb474 reduces the intensity of the observed ELISA signal . A decrease results in less detecting Nb474 binding to the Nb474-TcoALD sandwich , which is why a reduction in signal intensity is observed . Based on the results presented in this paper , an increase in the amount of detecting Nb474 above the optimal 2 ng would enhance the “self-competition” or “washing” effect , which was exacerbated in the case of the TcoALDL106Y and TcoALDA77E/L106Y mutants . Likewise , in the case where the optimal amount of detecting Nb474 is kept fixed ( ~ 2 ng ) , any deviation from the optimal 2 ng of capturing Nb474 reduces the signal intensity in the ELISA . Employing relatively low amounts of capturing Nb474 is possible due to the high affinity and slow dissociation kinetics of the Nb474-TcoALD interaction as evidenced by the SPR data . A decrease in the amount of capturing Nb474 compared to the optimal case leads to less antigen being captured , which is why a reduction in signal intensity is observed . An increase in the amount of capturing Nb474 would enhance the avidity effects in the ELISA wells , whereby one TcoALD multimer would be able to bind several Nbs simultaneously . Hence , no TcoALD epitopes would be available for binding of detecting Nb474 , which results in the observed lower ELISA signal with increasing amounts of capturing Nb474 ( Fig 6 ) . The main focus of this paper was to determine the molecular mechanisms underlying the high specificity of a Nb-based homologous sandwich ELISA that allows detection of T . congolense infections . As reported previously , the assay targets glycosomal aldolase [16] . While aldolase proteins are relatively well conserved throughout all domains of life , they seem to be immunologically sufficiently distinct , even within the same genus . In this and previous work [16] , we have demonstrated that the Nb474-based sandwich assay specifically detects the presence of T . congolense aldolase , while this is not so for aldolase from other trypanosomes . Coincidentally , a similar finding has been documented for the differential diagnosis of Plasmodium infections . A monoclonal antibody-based immunoassay targeting malarial aldolase results in the specific detection of Plasmodium vivax infections , while remaining negative for samples containing Plasmodium falciparum [43] . These examples demonstrate that parasite-encoded aldolases are suitable biomarkers for the stringent detection of parasite infections . This may present an interesting research avenue for the development of immunoassays for the specific detection of other pathogens . The results presented in this paper indicate that , while the concept and use of such assays are relatively simple , their underlying biochemistry can be quite complex . This may be of particular interest to those developing similar assays . | Sub-Saharan Africa is plagued by many diseases , which impede its socio-economical development . One of these diseases , Animal African Trypanosomosis , affects livestock and is caused by the parasites of the Trypanosoma genus ( T . vivax and T . congolense ) . Animal African Trypanosomosis leads to considerable economic losses and renders sustainable livestock industry in Sub-Saharan Africa very difficult . In order to proceed with the selective treatment of infected animals , they need to be properly diagnosed . We recently described the use of an assay to specifically detect T . congolense infections in both experimentally and naturally infected animals . The diagnostic assay employs a Nanobody ( Nb ) , which is the smallest antigen-binding unit derived from camelid heavy-chain only antibodies . Our previous results showed that the Nb-based diagnostic test specifically recognizes T . congolense fructose-1 , 6-bisphosphate aldolase , a glycolytic enzyme that is well conserved amongst other Trypanosoma species . In this paper , we studied the molecular mechanisms underlying the high specificity of the Nb-based diagnostic assay . The principles derived from this work may be important for the design and improvement of similar diagnostic tests . | [
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"crystallog... | 2017 | Structural basis for the high specificity of a Trypanosoma congolense immunoassay targeting glycosomal aldolase |
Even for simple perceptual decisions , the mechanisms that the brain employs are still under debate . Although current consensus states that the brain accumulates evidence extracted from noisy sensory information , open questions remain about how this simple model relates to other perceptual phenomena such as flexibility in decisions , decision-dependent modulation of sensory gain , or confidence about a decision . We propose a novel approach of how perceptual decisions are made by combining two influential formalisms into a new model . Specifically , we embed an attractor model of decision making into a probabilistic framework that models decision making as Bayesian inference . We show that the new model can explain decision making behaviour by fitting it to experimental data . In addition , the new model combines for the first time three important features: First , the model can update decisions in response to switches in the underlying stimulus . Second , the probabilistic formulation accounts for top-down effects that may explain recent experimental findings of decision-related gain modulation of sensory neurons . Finally , the model computes an explicit measure of confidence which we relate to recent experimental evidence for confidence computations in perceptual decision tasks .
Research in perceptual decision making investigates how people categorise observed stimuli . By presenting stimuli embedded in large amounts of noise , experimenters prolong the time it takes a subject to make a decision about the stimulus . This makes the decision making process observable for hundreds of milliseconds and enables experiments about the underlying mechanisms [1] . For example , in the well-known random dot motion task subjects typically have to categorise a cloud of moving dots according to whether it moves in one of two opposing directions [2–4] . By decreasing the fraction of coherently moving dots the task is made more difficult such that subjects respond slower and make more errors . Such increases in reaction time for more difficult categorisations motivated models that describe decision making as an accumulation of noisy evidence towards a bound [5 , 6] . One of the key findings is that such bounded accumulation models fit accuracy and reaction time distributions of decision makers well [6–8] . Furthermore , electrophysiological research has found support for an accumulation mechanism: neurons in different areas of monkey brains exhibit steadily increasing firing rates dependent on stimulus reliability , e . g . [1 , 9–12] . In humans , correlates of evidence accumulation have been found with functional magnetic resonance imaging [13 , 14] and magneto-/electroencephalography [15–19] . The two best-known models of perceptual decision making are drift-diffusion and attractor models . Drift-diffusion models implement accumulation to a bound using diffusion processes [7 , 20–22] and can be understood in terms of statistically optimal sequential decision making [20] . Bayesian models of perceptual decisions provide a direct link between the computation of evidence from the sensory input and the statistically optimal accumulation of this evidence [23–25] . In contrast , attractor models were developed as neurophysiologically inspired spiking-neuron models of perceptual decision making [26] , but can also be described by simpler firing rate models [27 , 28] . Attractor models use winner-take-all dynamics to implement accumulation which is nonlinear over time . This nonlinear accumulation is the key difference to drift-diffusion models , which are based on linear accumulation . Both types of models seem to make mostly the same predictions [29 , 30] , yet exhibit subtle differences in favour of attractor models when considering experimental evidence [31–33] but see [34] . Bayesian inference provides an optimal approach for combining noisy sensory evidence with internal dynamics and seems generally useful as a basic mechanistic principle for perceptual decision making . For example , drift-diffusion models are strongly connected to Bayesian models of perceptual decision making [23–25] . Therefore , the question arises what exactly a Bayesian inference approach would have to offer for attractor models . Here , we address this question by combining a variant of the nonlinear attractor model with Bayesian inference . The resulting new model , which we call the Bayesian attractor model ( BAttM ) , combines the neurophysiological motivation of the attractor model with the explicit evidence computation formalism of the Bayesian machinery . As we will show , the BAttM is a quantitative model and fits well to behavioural data ( reaction times and choice ) . Furthermore , we will highlight three key advantages of the BAttM that go beyond the standard features of both attractor and drift-diffusion models . First , the BAttM naturally models changes in decisions that reflect changes in the underlying category . Such changes of an already made decision are an important part of our environment , e . g . , a switching traffic-light , but have not been considered by previous models . Rather , drift-diffusion [35] and attractor models [26 , 31] have been adapted to model ‘changes of mind’ which are different from ‘re-decisions’ considered here ( for more details on the difference see Discussion ) . Second , the BAttM provides a natural explanation for top-down modulation of the sensory gain that controls evidence extraction during the decision making process . Such gain modulation has been implicated in attentional phenomena such as found in feature-based attention [36–38] . In addition , early sensory neurons have been found to exhibit within-trial gain modulation that appears to depend on the final choice in a trial [39 , 40] . The BattM explains these phenomena in terms of a state-dependent , top-down gain mechanism which is absent from both drift-diffusion and attractor models . Third , the BAttM provides an explicit measure of confidence that reproduces the experimentally established dependence of confidence ratings on decision outcome and task difficulty [41–43] . In particular and in contrast to both drift-diffusion and attractor models , the probabilistic formulation of the BAttM yields a quantitative measure of confidence that reflects the decision maker’s internal expectations and provides a meaningful quantitative interpretation of the bound .
Attractor models of perceptual decision making were originally proposed as neurophysiologically plausible implementation of noisy decision making [26] . In particular , [26] introduced a spiking neuron network which implements decisions through an attractor dynamics based on two mutually inhibiting pools of neurons . By using a mean-field approach this model has been reduced to a relatively small set of differential equations [28] , see also [27 , 32] . Apart from the neurobiological motivation , attractor models mainly differ from prevalent diffusion models of decision making by the nonlinear accumulation of evidence: The mutual inhibition between alternatives leads to faster accumulation for an alternative as more evidence for that alternative is accumulated , that is , decisions for an alternative are attracting . In the present work we capture this decisive property of attractor models with a simpler , more abstract Hopfield network [44] . The Hopfield dynamics describes how state variables zi ( the activities of units in the Hopfield network ) evolve through time . Each state variable corresponds to one decision alternative . Intuitively , large values of state variable zi indicate large amounts of evidence for decision alternative i . The Hopfield dynamics implements lateral inhibition between and self-excitation of state variables . As a result , it exhibits winner-takes-all dynamics which ensures stable and unambiguous decision making between alternatives . In particular , the Hopfield dynamics has stable fixed points ϕi , each identifying one decision alternative i . For further details see Methods . By abstracting from details of the particular attractor dynamics used in different models , previous attractor models of decision making may be formalised ( in discretised form ) as z t - z t - Δ t = Δ t f ( z t - Δ t ) + I t ( 1 ) where f ( z ) is a function defining an attractor dynamics for the vector of state variables z , which we also call decision state ( cf . Table 1 ) . The external input It varies with stimulus strength , includes noise , directly drives the attractor dynamics and reflects momentary evidence in decision making ( see Fig 1A ) . Typically , when one of the state variables zi reaches a certain threshold , the model indicates a decision for the corresponding alternative i . We refer to models of this type as ‘pure attractor models’ which include the attractor models described above [26–28] . Note that pure attractor models are not informed about the stimulus itself or its features . Rather , they presume that their noisy input carries some information about a stimulus which is interpreted as evidence for or against the considered alternatives . Therefore , these models implicitly postulate that evidence for a decision is extracted by lower level sensory processes which are independent of the state of an ongoing decision . Under this assumption , pure attractor models cannot exhibit top-down gain control as a mechanism , because the decision state cannot provide feedback to the lower sensory level , see Fig 1A . Bayesian models infer the state of an unobserved variable ( here the identity of a stimulus ) from realisations of an observed variable [24 , 45–47] . Here , we define these ‘observations’ and motivate them as feature representations in the brain . Even though the BAttM can model tasks with multiple alternatives , we here focus on two-alternative forced choice tasks , as most commonly employed when investigating perceptual decisions . For example , in typical random dot motion ( RDM ) tasks subjects have to judge into which of two opposing directions a randomly moving cloud of dots moves on average [2–4] . By varying the percentage of coherently moving dots the task difficulty can be controlled . We assume that the brain translates low-level sensory information , such as moving patters of light and dark spots on the retina , into stimulus feature vectors that are relevant for the current decision . In the RDM task a suitable feature may be the dominant motion direction in the stimulus , or a distribution over it . As the motion in the stimulus becomes less coherent , the dominant motion direction becomes more noisy . The precise feature representation that the brain uses when making decisions , including the particular distribution of feature vectors , is largely unknown . Consequently , we take a suitably parsimonious approach and model ( abstract ) feature vectors as samples from one of two Gaussian distributions which represent the two alternatives in the decision task . In particular , a feature vector at time t is xt ∼ 𝓝 ( μi , s2 I ) where s is the standard deviation of the noise , or noise level ( cf . Table 1 ) and μi is the feature vector that would result , if alternative i was presented without noise . We set μ1 = [0 . 71 , 0 . 71]T ( alternative 1 ) and μ2 = [−0 . 71 , −0 . 71]T ( alternative 2 ) , that is , the feature vectors of the two alternatives occupy opposite positions on the unit circle . This ( feature ) representation of the noisy stimulus has itself an interpretation as a perceptual decision making task . We use this interpretation here to illustrate the task that the brain , as decision maker , presumably solves when given noisy feature vectors as observations in a decision task: The feature vector x can be interpreted as the location of a single dot on a plane which moves randomly around one of two target positions . The single dot positions are sampled from an isotropic two-dimensional Gaussian with mean equal to one of the two targets . The task of the decision maker is to infer around which of the two target locations the single dot moves . Similarly to the RDM task , the difficulty of the task can be continuously varied by manipulating the ratio between the noise level and the distance between the two targets . In the two extremes , there is either no noise so that the correct target can be inferred easily , or the random movements are so large that one cannot infer the true target ( i . e . , the mean of the underlying Gaussian ) with sufficient certainty . In Fig 2 we illustrate the dot movements across an example trial in this task . The generative model of the decision maker implements its expectations about the incoming observations . More precisely , the generative model is a probabilistic model that defines the likelihood of observations under all possible hypotheses that the decision maker considers . Compared to pure attractor models the flow of information is reversed in the generative model: The generative model predicts a probability distribution over observations based on the current decision state and its winner-take all attractor dynamics . In contrast , in pure attractor models evidence extracted from the stimulus perturbs the decision state without any feedback from the decision state to the sensory evidence ( cf . Fig 1 ) . A previous Bayesian model of perceptual decision making [23] defined independent generative models for the different alternatives in the decision task . The Bayesian attractor model complements the generative model with a competition between alternatives as implemented by attractor dynamics . In particular , the generative model defines a change in decision state from one time step to the next as z t - z t - Δ t = Δ t f ( z t - Δ t ) + Δ t w t ( 2 ) where f ( z ) is the Hopfield dynamics ( Methods , Eq 9 ) . wt is a ( Gaussian ) noise variable with wt ∼ 𝓝 ( 0 , Q ) where Q = ( q2/Δt ) I is the isotropic covariance of the noise process and we call q ‘dynamics uncertainty’ . It represents the ( expected ) state noise at the attractor level which can be interpreted as the propensity to switch between decisions ( the higher the dynamics uncertainty , the more likely the state switches between the decision alternatives ) . Given a decision state z the generative model predicts a probability distribution over observations by interpolating prototypical observations that represent the different alternatives: x = M σ ( z ) + v ( 3 ) where M = [μ1 , … , μN] contains the mean feature vectors defined in the input model above . This choice implements the reasonable assumption that the decision maker has learnt the average representations of the stimuli in feature space either through experience with the task , or from a suitable cue in the experiment . σ ( z ) is the sigmoid-transformed decision state , that is , all state variables zj are mapped to values between 0 and 1 . Due to the winner-take-all mechanism of the Hopfield dynamics , its stable fixed points ϕi will map to vectors σ ( ϕi ) in which all entries are approximately 0 except for one entry which is approximately 1 . Hence , the linear combination M σ ( z ) associates each stable fixed point ϕi with feature vectors ( observations ) from one of the decision alternatives . When the Hopfield network is not in one of its stable fixed points , M σ ( z ) interpolates between mean feature vectors μi dependent on the sizes of individual state variables zj . Finally , v is a ( Gaussian ) noise variable with vt ∼ 𝓝 ( 0 , R ) where R = r2 I is the expected isotropic covariance of the noise on the observations and we call r ‘sensory uncertainty’ . It represents the expected noise level of the dot movement in the equivalent single dot decision task explained above ( the higher the sensory uncertainty , the more noise is expected by the decision maker ) . By inverting the generative model using Bayesian inference we can model perceptual inference . Specifically , we use Bayesian online inference to infer the posterior distribution of the decision state zt , that is , the state of the attractor dynamics at time t , from sensory input , that is , all the sensory observations made up to that time point: XΔt:t = {xΔt , … , xt} , given the generative model ( Eqs 2 , 3 ) . The generative model postulates that the observations are governed by the Hopfield dynamics . Hence , the inference must account for the assumption that observations of consecutive time points depend on each other . In this case , inference over the decision state zt is a so-called filtering problem which could be solved optimally using the well-known Kalman filter ( see , e . g . , [48] ) , if the generative model was linear . For nonlinear models , such as presented here , exact inference is not feasible . Therefore , we used the unscented Kalman filter ( UKF ) [49] to approximate the posterior distribution over the decision state zt using Gaussians . Other approximations such as the extended Kalman filter [48] , or sequential Monte Carlo methods [50] could also be used . We chose the UKF , because it provides a suitable tradeoff between the faithfulness of the approximation and computational efficiency . The UKF is based on a deterministic sampling technique called the unscented transform [51][52] , which provides a minimal set of sample points ( sigma points ) . These sigma points are propagated through the nonlinear function and the approximated Gaussian prediction is found by fitting the transformed sigma points . Following [49] , we use for the unscented transform the parameter values α = 0 . 01 , β = 2 , κ = 3−D where D is the dimension of the state representation inside the UKF . In the following , we provide an intuitive description of the UKF computations . For the mathematical details , we refer the reader to [49] . The unscented transform is performed twice . First , it is used to approximate the distribution over the decision state in the next time step , as predicted by the generative model from the current estimate based on previous observations , with a Gaussian: p ( z t ∣ X Δ t : t − Δ t ) ≈ 𝓝 ( z ^ t , P ^ t ) . Second , the unscented transform is used to approximate the predicted distribution of the corresponding next sensory observation: p ( x t ∣ X Δ t : t − Δ t ) ≈ 𝓝 ( x ^ t , Σ ^ t ) . The conceptual idea of Kalman filter algorithms is to compare the predicted distribution with the actual observation and update decision state estimate z ‾ t proportional to the observed discrepancy while taking the uncertainty over predictions into account . Practically , for the Gaussian approximation used in the UKF we compute a prediction error ϵ t = x t − x ^ t between predicted mean x ^ t and actual observation xt and then update the decision state prediction z ^ t via a Kalman gain Kt: z ¯ t = z ^ t + K t ϵ t . ( 4 ) The Kalman gain represents the relative importance of the prediction errors with respect to the predictions and is computed from the estimated covariance of the predicted observations and the cross-covariance between predicted observations and decision state: K t = C ^ t Σ ^ t - 1 ( 5 ) where C ^ t is the cross-covariance between predicted decision state z ^ t and predicted observation x ^ t which is strongly affected by dynamics uncertainty q ( larger q , larger cross-covariance ) and Σ ^ t is the covariance matrix of the predicted observations which is strongly affected by sensory uncertainty r ( larger r , larger variance ) . These relations mean that an increase in q mostly leads to an increase in gain whereas an increase in r leads to a reduction in gain . In addition to affecting the updates of the mean decision state , the Kalman gain is further used to estimate the posterior covariance P ‾ t of the state variables zi , t which completes the UKF approximation of the posterior distribution over the decision state p ( zt∣XΔt:t ) . Fig 3 illustrates the described Kalman filtering scheme . The final component of the Bayesian attractor model is its decision criterion . In decision models based on evidence accumulation the decision criterion implicitly sets a particular level of accumulated evidence that needs to be reached before the decision maker commits to a decision . In contrast , we here define the criterion directly on a measure of confidence in the decision . In particular , the model makes a decision for alternative i at time t , if p ( z t = ϕ i | X Δ t : t ) ≥ λ ( 6 ) where p ( zt = ϕi∣XΔt:t ) is the posterior density over the decision state evaluated at the stable fixed point ϕi corresponding to alternative i , that is , p ( zt = ϕi∣XΔt:t ) is the posterior belief of the decision maker that alternative i is the true alternative . Then the threshold λ can directly be interpreted as a confidence level . This decision criterion requires that all state variables are at their expected values as given by the stable fixed points ϕi . Note that this is different from pure attractor models which do not use a bound around the fixed point location , but rather threshold individual state variables zj , see below in results . Uncertainty parameters and the confidence bound interact: Larger dynamics uncertainty leads to wider posterior distributions , faster evidence accumulation and smaller density values ( Fig 4 ) . For reporting results we therefore fixed the bound to λ = 0 . 02 in all reported experiments which was sufficiently small to be reached for all considered settings of uncertainties . Note that p ( zt = ϕi∣XΔt:t ) is not a probability , but a probability density value , that is , it can be larger than 1 and should not be expressed in % . Technically , a probability density value is the slope of the cumulative distribution function of a probability distribution evaluated at a given point in the continuous space over which it is defined . In the standard , single decision experiments below we report the decision of the first time point for which the decision-criterion ( Eq 6 ) was met . In the re-decision experiment we report the fraction of time in which the criterion was met for the correct alternatives .
In the BAttM , the speed and accuracy of decisions are primarily controlled by the noise level of the sensory input ( s ) , the sensory uncertainty ( r ) and the dynamics uncertainty ( q ) . Additionally , the initial state uncertainty p0 ( see Methods ) influences the rate of evidence accumulation at the beginning of a trial . First , we demonstrate the effect of the sensory uncertainty r , i . e . , the decision maker’s internal expectation of how noisy the input is , on decisions . Fig 5 shows the dynamics of the decision state over time for three different settings of the decision maker’s sensory uncertainty r . After an initial non-decision time of 200ms , the decision variables start accumulating evidence . If the sensory uncertainty is too low , i . e . , the decision maker puts too much weight on the noisy input relative to the attractor dynamics ( Fig 5A ) , the decision state overshoots and initially misses the associated fixed point representing a decision . Only after hundreds of milliseconds the decision state relaxes back to a fixed point . This uncertainty setting leads to inaccurate decisions with rather long reaction times . If the sensory uncertainty is too high ( Fig 5C ) , decision making is accurate but relatively slow , because the decision maker expects a much higher noise level than the actual one . When using a suitable sensory uncertainty for the actual noise level of the input ( Fig 5B ) , decision making is fast and accurate as typically observed in subjects . To investigate the quantitative dependence of decision state trajectories on both the noise level s and the sensory uncertainty r we systematically varied these two parameters . We sampled single trial trajectories from each parameter combination while keeping the remaining parameters of the model fixed ( q = 0 . 1 , p0 = 5 ) . For more reliable results , we computed the accuracy and mean reaction time over 1 , 000 single trials for each parameter combination ( Fig 6 ) . As expected , the accuracy ( Fig 6A ) decreases from perfect to chance level as the noise level s increases . In general , below s < 2 , any setting of sensory uncertainty r leads to perfect accuracy whereas the mean reaction time ( RT ) increases with sensory uncertainty r ( with r > 10 RTs can become slower than 1000ms; we excluded these parameter settings from further analysis , see the light blue areas in Fig 6 ) . In contrast , when the noise is large ( s > 20 ) , the random movement of the dot is too large to recover the stimulus identity reliably , whatever the setting of the sensory uncertainty r . For intermediate values of s , 3 < s < 20 , a relatively high accuracy level can be maintained by increasing the sensory uncertainty appropriately; this is reflected by the diagonal gradient between the white and dark grey area in Fig 6A . In Fig 6B there is a narrow valley of fast mean RTs stretching from the lower left to the upper right of the image . Note that the slower RTs below this valley result from trajectories as in Fig 5A . Slower RTs above this valley are due to slow accumulation as seen in Fig 5C . Most importantly , both fast and accurate decisions can be achieved by appropriately adapting the sensory uncertainty r to the noise level s of the stimulus . The practical use of the results shown in Fig 6 is to fit subject behaviour , i . e . , to identify parameter settings which explain the observed accuracy and mean reaction time of a subject . As our environment is dynamic , a specific stimulus may suddenly and unexpectedly change its category . For example , traffic lights turn red and other people may suddenly change their intentions and actions . In these cases one has to make a ‘re-decision’ about the category of the attended stimulus . This is different from the typical ‘single decision’ forced-choice experiments considered in the previous section . These investigate the special case in which the underlying category of a single trial does not change . The corresponding models , like the drift-diffusion model , were designed to model precisely this case and focus on the tradeoff between speed and accuracy of decisions . With re-decisions , another tradeoff , between flexibility and stability in decisions , presents itself . This tradeoff stresses the dilemma of the decision maker to either explain away evidence for an alternative as noise ( stability ) , or rather switch to the alternative decision rapidly ( flexibility ) . Although one may consider extending the ‘single trial’ models so that re-decisions can be modelled ( see Discussion ) , we found that the BAttM is already an appropriate model of re-decisions . In particular , the sensory uncertainty r and dynamics uncertainty q are two well-interpretable parameters which control the balance between flexibility and stability . Therefore , the BAttM lends itself naturally as a quantitative analysis method for reaction times and accuracy of re-decisions , as we will demonstrate next . We investigated the re-decision behaviour for a range of parameter settings , see Fig 7 . In contrast to the above findings for single decisions , the dynamics uncertainty q here plays an important role because it enables the Bayesian attractor dynamics to display different behaviours: When q is large , the decision maker will switch readily between fixed points , i . e . decisions . When q is small , switching will occur only when sensory input very clearly indicates the alternative . As a proof of principle , we varied the sensory uncertainty r and the dynamics uncertainty q in logarithmic steps ( with fixed noise level s = 4 ) , over many ( 1 , 000 ) trials . In each trial , after showing noisy exemplars from one target location ( blue alternative ) for about 800ms , we switched to the other target ( orange alternative ) for the same duration ( cf . Fig 2 ) . As a measure for accuracy we report in Fig 7 the mean percentage of time spent in the correct decision state . There are three main regions in the plot: ( i ) uncertainty settings in the white region lead to extremely slow decisions , ( ii ) the grey region in which an initial decision ( first 800ms ) is made but not appropriately updated after a switch and ( iii ) the black region in which the decision dynamics is sufficiently flexible to make two appropriate decisions . As expected , and in congruence with Fig 6 , we find that the sensory uncertainty r must be set appropriately ( here approximately between 1 . 5 to 3 . 0 ) in relation to the sensory noise level ( here s = 4 . 0 ) to make fast and accurate initial decisions . For further analysis we focus on one of these values ( r = 2 . 4 ) , which is consistent with the behavioural data fitting reported below ( in our fitting results r = 2 . 4 roughly corresponds to noise level s = 4 . 0 and a coherence of about 25% ) . We selected three different settings of q ( 0 . 1 , 0 . 5 , 1 ) as a representative illustration of the results . We display samples of the corresponding trajectories of the decision state in Fig 7A–7C . To compare the impact of the dynamics uncertainty q , these samples are based on the same sensory input . For high dynamics uncertainty q = 1 . 0 ( Fig 7A ) both the initial decision and the re-decision are made appropriately . However , the decision maker sometimes changes its decision due to sensory noise , i . e . , without an underlying switch of stimulus ( see Fig 7A at 350ms ) , exhibiting a high level of flexibility . On average , as re-decisions are made correctly , the performance is relatively large ( 73% ) . Although a performance of 73% does not sound very high , it is an open experimental question how human participants would perform in the re-decision experiment . Like the model , a participant will require switching time and may experience transient false beliefs as seen in Fig 7A . In the model , the 73% performance compares well against the two other dynamics uncertainty settings . For example , for a smaller uncertainty ( q = 0 . 5 , Fig 7B ) spurious , noise-induced switches are greatly reduced , but re-decisions are slower . This leads to a reduction in time spent in the correct decision state ( 53% ) in exchange for an increased stability of the decisions . In the grey region ( point location and panel C in Fig 7 ) the dynamics uncertainty is too low ( 0 . 1 ) to make a re-decision based on the sensory input . Only 35% of the time was on average spent in the correct decision state with this setting of q , i . e . , decisions were detrimentally stable . In summary , the dynamics uncertainty q is a useful parameter for modelling the tradeoff between flexibility and stability of re-decisions . Importantly , similar to the fitting of the experimental data of [54] , the mapping of parameters s , r , and q ( i . e . , noise level , sensory uncertainty and dynamics uncertainty ) can be used to quantitatively analyse experimental data in re-decision tasks . The BAttM suggests an intuitive mechanism of re-decisions: Once an initial decision has been made , the decision state is located in a stable fixed point of the attractor dynamics . As long as sensory observations are consistent with the decision maker’s expectations , the fixed point location is held . When the underlying stimulus changes , however , violated expectations , i . e . , large prediction errors ( see Fig 1B ) , force the decision state to move away from the currently occupied fixed point and towards the fixed point representing the identity of the new stimulus , eventually leading to a re-decision . Both sensory uncertainty and dynamics uncertainty control the gain with which prediction errors influence the decision state ( cf . Eqs 4 and 5 in models ) : the sensory uncertainty primarily controls the overall amount of evidence extracted from sensory observations ( high uncertainty means low evidence ) while the dynamics uncertainty controls how sensory evidence is translated to the decision state ( high dynamics uncertainty usually means large effects of sensory evidence on the decision state ) . Similarly , the gain of the sensory evidence on the decision state is influenced by the decision state itself , implementing state-dependent top-down gain modulation of sensory information . We describe this effect next . There is growing evidence that higher level cognitive processes modulate neural responses already in early sensory areas [36–38 , 55–58] . More specifically , recent findings [39 , 40 , 53] indicate that neural activity in early sensory areas is modulated by the final choice of subjects in simple perceptual decision tasks . These findings suggest that top-down feedback influences sensory processing already on the temporal scale of single decisions , i . e . , within a trial of a perceptual decision making task . Pure attractor and drift-diffusion models , however , do not account for top-down feedback that modulates the extraction of evidence on the sensory level . In this section , we show that the BAttM offers such a top-down computational mechanism that leads to a stabilisation of the fixed points of the attractor dynamics and , consequently , allows the decision maker to make confidence-informed decisions . This mechanism can be best understood by comparing the within-trial dynamics of the decision state for both pure attractor models ( Eq 1 ) and the BAttM . Bayesian inference in the BAttM implements a predictive coding scheme ( Eq 4 ) in which state predictions z ^ t are updated with information from prediction errors ϵt dependent on a Kalman gain matrix Kt ( Eq 5 ) which embodies uncertainty and the relation between observations x and decision variables z . To compare the pure attractor model with the BAttM we first note that both models have the same form: After approximating the mean state prediction z ^ t with the ( expected ) attractor dynamics of the generative model , z ^ t ≈ z ¯ t - Δ t + Δ t f ( z ¯ t - Δ t ) , ( 7 ) we can plug this approximation into Eq ( 4 ) . The resulting Bayesian inference formalism replicates the form of the attractor model in Eq ( 1 ) : z ¯ t - z ¯ t - Δ t ≈ Δ t f ( z ¯ t - Δ t ) + K t ϵ t . ( 8 ) The critical difference of the BAttM formalism of Eq ( 8 ) to the pure attractor model in Eq ( 1 ) is that the BAttM prescribes an input consisting of a prediction error scaled by the gain . In particular , the input to the Bayesian attractor model depends on the last state z ‾ t − Δ t both through the gain matrix Kt and the mean prediction x ^ t ( see Models ) . This means that sensory observations pass through two processing steps which are applied in each time step: ( i ) Computation of prediction error using the top-down prediction , and ( ii ) modulation of the prediction error by the gain which also translates the sensory information ( prediction errors ) into the decision space ( through linear transformation by the gain matrix Kt ) . In this model , the effect of the gain is driven by two opposing components: In general , when predictions are more certain , the gain is increased . This effect is primarily mediated by the uncertainty r at the sensory level . Importantly , the gain is also driven by the cross-covariance of the predicted decision state z ^ t and predicted sensory observations x ^ t ( Eq 5 ) . The cross-covariance describes the information about changes in the decision state that can explain variation in sensory observations . It defines how prediction errors in sensory observations induce necessary changes in the decision state . This effect is largest in the space between fixed points of the attractor dynamics , because here a change in the decision state almost linearly maps to a change in sensory predictions . In contrast , the effect is relatively small close to the fixed points ( see Methods for details ) . As uncertainty in the decision state increases , it becomes more likely that the underlying distribution covers more of the space between fixed points , thereby increasing cross-covariance . Consequently and opposite to uncertainty at the sensory level , higher uncertainty at the decision level typically leads to larger top-down gain . Fig 8 demonstrates this within-trial gain modulation mediated by cross-covariance , for the empirically inferred parameters of point B of Fig 7 ( s = 4 , r = 2 . 4 , q = 0 . 5 ) . Fig 8A shows the inferred decision state as a function of time . After the switch of the stimulus , between 800 and 1 , 500ms , the decision state moved between fixed points of the attractor dynamics . As can be seen in Fig 8B , the predicted cross-covariances between decision state and sensory observations were large during this time period and became small again once the dynamics settled into a fixed point after 1 , 500ms , i . e . , when a decision had been made . Similar dynamics can be seen for the initial decision around 0 to 200ms . Fig 8C plots the elements of the gain matrix Kt over time . The trajectories follow those of the cross-covariance closely demonstrating that within-trial changes in gain were driven nearly exclusively by changes in the cross-covariance . Although the uncertainty over the decision state also varied within the trial ( Fig 8A , shading ) , the effect on the uncertainty of predicted observations was small in comparison to the effect exerted by the sensory uncertainty r , which remained constant throughout the trial . In summary , the within-trial , state-dependent modulation of gain is a useful mechanism when making decisions: It stabilises the representation of the stimulus category ( low gain close to fixed points , see below ) , but also implements fast accumulation of evidence , when needed ( high gain between fixed points ) . A graded feeling of confidence appears to be a fundamental aspect of human decision making . Corresponding confidence judgements can inform about underlying decision processes [42 , 43] . Through the probabilistic formulation , the BAttM directly provides a continuous measure of confidence that may be compared to experimentally measured confidence judgements . In the following we describe how confidence is computed in the BAttM , explain its use within the decision criterion and demonstrate that it conforms to experimental findings about confidence judgements [41 , 42] . The substantial and sudden decrease of gain close to a fixed point ( e . g . , Fig 8C , at 1 , 400ms ) contributes to an important feature of the BAttM: The location of fixed points is the same for different stimulus strengths . As we will show in this section , stable fixed point locations are the basis for defining a decision criterion directly on an explicit measure of confidence . Pure attractor models do not have stable fixed points: Because noisy evidence directly feeds onto the decision variable ( see Eq 1 and Fig 1A ) , the location of fixed points depends on the magnitude of the evidence , i . e . , stimulus strength . We show this effect in Fig 9A , see also [59] . Therefore , in pure attractor models , as long as stimulus strength is assumed to be unknown , one cannot tell how close the current decision state is to a fixed point , that is , fixed points have no particular meaning in pure attractor models except that the dynamics will eventually converge to them . In contrast , in the BAttM the speed of evidence accumulation , as caused by a particular , underlying stimulus strength , can vary without affecting fixed point locations ( Fig 9B and 9C ) . This is because the BAttM implicitly represents stimulus strength in its uncertainty parameters r and q such that expected stimulus strength is automatically taken into account during evidence computation from the stimulus . As a consequence of stable fixed point locations , a deviation of the decision state from a fixed point can be readily interpreted as violation of the expectations about the stimulus associated with that fixed point , irrespective of stimulus strength . In general , the more such expectations are violated , the less confident the decision maker should be about choosing one of the alternatives . We implemented this mechanism in the BattM by deriving the confidence in a decision alternative directly from the probabilistic model and using a threshold on it as decision criterion ( see Models , Eq 6 ) . In Fig 10 we illustrate how confidence values relate to the posterior density of the decision state ( Fig 10A ) , and how confidence-based decisions are made ( Fig 10B ) . Intuitively , the confidence for a specific alternative measures the distance of the current decision state ( blue and orange lines in Fig 10A ) from the stable fixed point of that alternative ( at [0 , 10] or [10 , 0] ) scaled by the posterior uncertainty of the decision state . Consequently , the confidence for all alternatives can be tracked across time ( cf . blue and orange lines in Fig 10B ) . Strikingly , the confidence dynamics are different from the decision variable dynamics: While the decision state gradually moves towards a fixed point , thus reflecting the relatively slow gradual accumulation of evidence ( e . g . , time period 800 to ∼ 1100ms ) , the confidence rises abruptly as soon as the posterior density of the decision state starts concentrating around a fixed point ( e . g . , from ∼ 1100ms onwards ) . How does the confidence-based decision making formalism compare with experimental findings ? Early behavioural work with humans [42] , indirect confidence judgements by rats [41] and general theoretical considerations [42 , 43] suggest that confidence in correct choices increases with stimulus strength whereas confidence in erroneous choices decreases with stimulus strength . At first glance , this seems at odds with a confidence-based decision criterion , as used by the BAttM , where the decision is made exactly when the confidence is at a specific level , independent of stimulus strength ( Fig 10B ) . This apparent contradiction can be resolved by noting that subjects , in the typical experimental setup , keep observing the stimulus for a short time after reaching the threshold , because of the delay between an internal decision and the production of the corresponding motor output , such as a button press . In standard models , this time period is usually considered to be part of the total non-decision time . Importantly , the same mechanism of continued accumulation of evidence in this time period is thought to contribute to ‘changes of mind’ observed in a reaching task [35] where subjects revise their internal categorization before being able to fully execute the reaching movement . We implemented this mechanism in the BAttM by continuing the accumulation of evidence after crossing the confidence threshold for about half of the estimated non-decision time of 200ms , i . e . , for 100ms . Critically , during this continued accumulation period , the confidence values evolve further and replicate the reported experimental results that show a dependence of confidence on stimulus strength and correctness of decision ( Fig 11 ) . To establish the validity of the proposed model and show that the model can be used to analyse data of decision making tasks , we fit behavioural macaque monkey data on the RDM two-alternative forced choice task presented in [54] . These authors used a drift-diffusion model to fit the average responses based on 15 , 937 trials . Stimuli were presented at eight different coherence levels ranging from 0% to 75% . We extracted the averages of the behavioural data from Figure 1 d , f in [54] and re-plotted the data in Fig 12B and 12C ( black dots ) . We obtained the model fit by stochastically minimising an objective function which quantified the discrepancy between values sampled from the model and the behavioural data ( cf . Methods ) . The sampled RTs contained a non-decision time which was reported in [54] ( see Methods for details ) . We plot the fits of mean reaction time and accuracy in Fig 12B and 12C . In Fig 12A , we show the fitted model parameters , noise level s and sensory uncertainty r , see also Table 2 . These results demonstrate that the model can fit the mean RTs and accuracy for different coherence levels by varying the sensory noise and the internal uncertainty of the decision maker . As can be seen in Fig 12A and Table 2 , we found , as expected , that both the sensory uncertainty and the noise level decrease as a function of coherence . The estimated posterior parameter variances indicate that parameters of the model can be estimated reliably for intermediate accuracies . When accuracy reaches its ceiling at 100% for coherences greater than 25% many different noise levels s can lead to equivalent predictions , simply because noise is not needed anymore to explain erroneous choices and can be set arbitrarily small . It has previously been found that the drift in a drift diffusion model scales linearly with coherence ( e . g . , [54] ) . We found an equivalent relation between the sensory uncertainty r and coherence ( Fig 12A , red line ) . In particular , it has been shown for a simple probabilistic model ( [23] , Eq 22 ) that sensory uncertainty r relates to drift v in the drift diffusion model as r2 = 2/ ( vΔt2 ) . If v = Kc as in [54] , r can be written as r2 = K′/c . We applied this relation to the BAttM and fitted K′ to the values of r reported in Table 2 ( see Methods for details ) . The result captures the previously reported relation between coherence and sensory uncertainty well for most coherences ( red line in Fig 12A ) and only deviates from the fitted parameter values for coherences greater than 25%; see Discussion for a potential , interesting reason . In all work presented here we fixed the confidence threshold λ to a constant value . This was necessary , because λ and sensory uncertainty r have very similar effects on mean RT and , thus , are interchangeable in many conditions ( cf . [23] ) . To verify this relationship we repeated fitting of the data used here , but fixed r = s and allowed λ to vary . With this parameterisation , we could fit behaviour for high and intermediate coherences equally well , but observed a drop in quality of fit for low coherences ( 0% and 3 . 2% , results not shown ) .
In typical perceptual decision making experiments , e . g . [54] , the response of the participant automatically ends a trial and the stimulus disappears . In natural conditions , however , an object typically does not disappear after the brain has made its categorisation and the object should be represented as long as it is behaviourally relevant . In addition , the brain has to be able to rapidly update a decision in response to a change in the environment , for example , when a green traffic light turns red . These decisions , which we called re-decisions , are currently rather not considered by perceptual decision making models . In particular , drift-diffusion and similar probabilistic models of perceptual decisions are not good models for behaviour in response to stimuli that switch occasionally . This is simply because the amount of accumulated evidence for a decision depends on the time the stimulus supporting the decision is observed: To switch to the alternative decision , this accumulated evidence must be overcome by an equal amount of evidence in favour of the alternative . This means that the reaction time in response to a switch would depend on how long the previous stimulus was shown . If the previous stimulus was present for several seconds , standard drift-diffusion and related models predict that the reaction time for a switch would be several seconds as well . This would clearly depart from the expected decision behaviour of participants with typical reaction times of several hundred milliseconds . Pure attractor models , on the other hand , provide a basis for successful re-decisions: Once the decision state is in a fixed point no additional evidence is accumulated . Consequently , only a fixed amount of evidence for the alternative category is required to reverse an initial decision by moving the decision state into a different attractor [26] . The BAttM enhances this property through its embedding in a probabilistic framework: It provides a single , interpretable parameter , the dynamics uncertainty q ( cf . Table 1 ) , that controls the timing of re-decisions independently of the timing of initial decisions and , thus , implements a tradeoff between flexible and stable decisions ( Figs 7 , 9C ) . Note that the drift diffusion model could be extended to allow for re-decisions that do not depend on the duration of the previous stimulus . In a neural model of a drift diffusion process this could be achieved by using neurons with a maximal firing rate . In mathematical formulations based on a stochastic differential equation [6 , 20] , such a maximal firing rate mechanism translates to a condition which would increasingly limit the size of state changes as the maximum state value is approached . To the best of our knowledge , such a mechanism has not been described yet and would reproduce a key feature of attractor models where state changes decrease as a fixed point is approached . So-called changes of mind [31 , 35] differ from re-decisions . In [35] a change of mind occurred very quickly to correct an initial decision , that is , without a change of stimulus subjects changed their decision , presumably , in response to stimulus information that was processed just after the initial decision had been made . In contrast , re-decisions can also occur long after a decision that was made with high confidence . Specifically , the model of changes of mind described in [35] extended a standard drift-diffusion model with an additional bound which only comes into effect after one of the initial bounds has been crossed , that is , after an initial decision has been made . This second bound is only defined for the initially unchosen alternative . Other than in the standard drift-diffusion model , accumulation of evidence continues after the decision . If the second bound is reached within a given deadline , a change of mind is executed . There are two properties of this model which prevent modelling re-decisions in response to a change in stimulus: 1 ) the deadline and 2 ) ( as described more generally for drift diffusion models above ) the dependence of re-decision times on the time of the underlying stimulus switch . The deadline in the change-of-mind model was designed to capture motor costs that prevent a change-of-mind too close to the end of the trial . The deadline , therefore , could simply be dropped in a re-decision experiment . However , the more general drawback of drift diffusion models , i . e . , the dependency of re-decisions on the duration of the previous stimulus , would have to be fixed more elaborately ( see previous paragraph ) . To investigate re-decisions in experiments , standard perceptual decision making paradigms need to be adapted . Especially , single trials need to be prolonged in order to present changing stimuli to the participants and allow them to react to these changes . As stated above , although there may be differences in detail , pure attractor models can , in principle , explain re-decisions as well . One question is what the BAttM can offer beyond what pure attractor models can do . An important advantage of a probabilistic formulation is that it allows to define confidence measures , as discussed further below . Another crucial advantage is that the BAttM explicitly models how evidence for a decision is extracted from the concrete features of a given stimulus . This means that the BAttM can in principle predict reaction times and choices of the subject given the stimulus features of the actual stimulus shown to the subject in each single trial . Although this may appear as a technical detail , we believe this input model ( see Fig 3 ) is a vital model component . For example , pure attractor models require that the modeller provides the evidence input . This ‘manual’ specification of the evidence input is not necessarily an advantage because the exact shape of the input is a key to explain the data . This would make the manual input specification an important but rather ill-constrained component of the model as there is no measure of the degrees of freedom spent on the input specification . In contrast , the BAttM explicitly constrains evidence computation via the Bayesian update equations . As a result , stimulus features shown to the subject enter the behavioural analysis in a highly constrained fashion . This formally described evidence computation also defines the top-down modulation predicted by the BAttM , as discussed next . In the BAttM , there are two different ways how top-down gain modulation of sensory processing emerges . The first depends on the sensory uncertainty r , which we implicitly assume here is a between-trial effect because most experiments keep the amplitude of the sensory noise constant over a trial , but see ‘Adapting stimulus expectations’ below for a discussion of this assumption . The second gain effect varies due to the dynamics of the internal decision state , which is a within-trial modulation . The between-trial gain modulation offers a novel understanding of variations in reaction times caused by varying stimulus noise level . In explanations of perceptual decision making it is generally assumed that stronger stimuli , i . e . , with higher signal-to-noise ratio , translate into larger pieces of evidence which lead to faster accumulation [1] . The BAttM makes this translation explicit and models higher stimulus strength by less observation noise s and correspondingly less sensory uncertainty r ( Table 2 , Fig 12 ) . A key prediction of the BAttM is that different speeds of evidence accumulation , e . g . , across task difficulty levels , are caused by different amounts of top-down gain modulation: the lower the sensory uncertainty , the higher the gain of sensory input ( Eq 5 ) . Such a top-down mechanism has been described in general by proponents of the Bayesian brain hypothesis [45 , 46 , 60] , the free energy principle [61] and predictive coding [62] . In particular , it has been suggested that internal uncertainty is tightly linked to neuronal modulator mechanisms [63–65] that implement attentional , top-down modulation of sensory areas [36–38 , 55–58] . In addition to these between-trial effects , experimental findings prompted the suggestion that sensory gain may be modulated within-trial by the state of an ongoing decision [39 , 40 , 53] . Drift-diffusion and pure attractor models do not account for such top-down modulation of gain , because there is no top-down connection from decision state to sensory input in these models . In the BAttM , however , this connection is provided by the state-dependent Kalman gain , see Eqs ( 8 , 5 ) . In particular , the BAttM predicts that sensory gain is large when transitioning between decision alternatives and small when the decision is imminent or has been made ( Fig 8 ) . This modulation is driven by the cross-covariance between predicted observations and decision states ( Fig 8 ) . Intuitively , this cross-covariance measures what changes can be expected on the observation level due to a change of the decision state , or , inversely , what changes in the decision state are likely to explain changes on the observation level . Therefore , the described formalism underlying within-trial gain modulation differs from the between-trial modulation which is purely based on changes in sensory uncertainty . Previous experiments [39 , 53] showed only coarse-grained evidence for decision-dependent modulation of activity in sensory areas , or are currently difficult to translate into our formalisation due to the type of measurement [40] . Therefore , further research is needed to test the hypothesis of specific temporal structure of gain modulation as predicted by the BAttM . Note that the BAttM was not designed by us to employ such a state-dependent top-down modulatory mechanism; rather , this property emerges from the Bayesian formulation in which decision states explicitly connect to particular sensory observations . Furthermore , the gain modulation in the BAttM has two functional benefits: First , it leads to a common , stable representation of the decision across task difficulties while still allowing decisions to be made with varying accuracy and timing . This is not the case for pure attractor models ( Fig 9 ) but is useful for a neuronal implementation because the next higher level can more easily read out a stable representation . Second , within-trial gain modulation facilitates rapid updating of decisions in response to a changed stimulus , because it quickly destabilises a made decision when sufficient evidence to the contrary is available . Consequently , the increased gain speeds up the transition to an alternative decision . Note that the initial movement out of a fixed point that represents a previously made decision is mediated by prediction errors ( Eq 8 ) which tend to be large when the decision deviates from the real stimulus and small otherwise . Although there are some reports of potential within-trial top-down gain modulation [39 , 40 , 53] , the formalism implemented by the BAttM is , at the current time point , a purely theoretical prediction which may be tested in future experimental work . Diffusion models often successfully explain decision behaviour without using top-down feedback mechanisms . Therefore , it may appear that the brain does not use top-down feedback when making simple perceptual decisions . However , a simple experiment testing the existence of top-down modulation may proceed as follows: Participants would be cued about the upcoming stimulus strength only in some trials but not in others . If the predictive cue had an effect on decisions , the BAttM would predict that this was partially due to between-trial top-down modulation through updated expectations of the participants . It is harder to test the existence of within-trial top-down modulation that discriminates the BAttM from pure attractor and diffusion models . Novel tasks may be required to elicit measurable effects of such within-trial top-down modulation . For example , the BAttM predicts that top-down modulation varies strongly in experiments with longer trials including re-decisions . In addition , the BAttM could be used to test this particular question by removing within-trial top-down gain modulation in the model and comparing choices predicted from this reduced model with those predicted from the full BAttM . “It has been definitely shown that the recognition process is attended by varying degrees of confidence; that the correctness of recognition tends to vary directly with the degree of confidence , and that our belief-attitudes appear with varying degrees of strength , or varying degrees of confidence , assurance , or certainty . ” [66] Since 1926 this account has been consolidated and given a theoretical basis [42] . More recently , behavioural paradigms were developed in which confidence could be measured from non-verbal responses [41 , 67] . These developments have been accompanied by extensions of drift-diffusion and attractor models that explain measured confidence ratings: For drift-diffusion models explicit confidence values can be computed as function of the decision variable and time [67] under the assumption that subjects’ confidence equals their true probability of making an error , but see [68] . Alternatively , the decision variable itself can be related to subjective confidence in the drift-diffusion model [23] . In pure attractor models , the decision state has been related to confidence judgements only indirectly: The increasing magnitudes of the decision state at the fixed point locations for increasing stimulus strengths ( cf . Fig 9A ) have been interpreted as increasing confidence in the decision [59] . This account assumes that the decision state continues to evolve towards the fixed points of the dynamics after the decision threshold has been reached . Other than both drift-diffusion and pure attractor models , the BAttM computes an explicit ( i . e . , in addition to the decision state ) and ongoing measure of confidence based on subjective uncertainties of the decision maker ( see Fig 10 and Fig 4 ) . This enables us to model confidence-based decisions using a threshold on the ongoing confidence ( Fig 10B ) which , in the BAttM , is defined as the posterior density that the decision state is in a stable fixed point of the generative model ( cf . Eq 6 in Methods ) . This posterior density can be interpreted as the decision maker’s internal belief that a category is the true category of the stimulus and can be easily computed from the estimated posterior over the decision state for an arbitrary number of alternatives . Note that the threshold on confidence may be implemented by a simple threshold on firing rates of neurons that represent the corresponding posterior density . As a density , however , it cannot be expressed in percent and , therefore , lacks an intuitive connection to typical measures of confidence in behavioural experiments . This connection may instead be provided by alternative measures of confidence that can also be derived from the posterior distribution over the decision state . For example , one can compute , as a measure of confidence , the probability that any one of the decision state variables exceeds all other state variables . This probability can be expressed in percent . It is possible that subjects compute such a measure when asked to explicitly report confidence after the decision , but it is an open experimental question how to identify forms of confidence judgements actually used by the brain . As the BAttM uses a threshold on the confidence to make a decision , the confidence at decision time is always equal to the threshold . This fact appears to contradict key experimental findings showing a dependence of confidence judgements on decision outcome and stimulus strength [42 , 43] . Yet , this apparent mismatch can be resolved ( Fig 11 ) simply by continuing accumulation of evidence during part of the non-decision time period . This continued accumulation is motivated by a corresponding assumption in [59] and by recent experimental findings regarding changes-of-mind in decision making [35] . It has also been shown that a wide range of findings about confidence ratings can be replicated under the assumption that evidence accumulation continues until the confidence rating [69] . In further congruence , potential neural correlates of continued processing of the stimulus after reaching a threshold were reported in [70] . Furthermore , the BAttM predicts direct , intuitive relations between the internal uncertainties of a decision maker and the absolute level of confidence that can be reached: Larger uncertainties lead to smaller confidence ( e . g . , see Fig 4 ) . As these uncertainties simultaneously control choices , response times and re-decision times , we propose to validate the consistency of these predicted relations in future experiments . We fitted the BAttM to average behaviour reported in [54] and found that the BAttM explains decision making behaviour well ( Fig 12B and 12C ) even though we assumed a simplified representation of the stimulus ( cf . section input ) . This was expected , because 1 ) a similar , abstract stimulus representation was sufficient to fit behavioural data ( of humans ) before [23] and 2 ) [54] originally used a similar computational representation to fit a drift-diffusion model to the data considered here . For the BAttM , estimates of the reliability of parameter fits indicate that fitted parameter values are highly reliable for experimental conditions in which subjects exhibit intermediate accuracy in response to coherences from 3 . 2% to 12% ( Fig 12A ) . In these conditions our fits suggest that the noise level s exceeded sensory uncertainty r in the subjects which would mean that the subjects’ generative model of the stimulus underestimated the amount of noise in the stimulus . In contrast , an optimal Bayesian decision maker should have a generative model in which , ideally , r would equal s . It has been proposed that variability in subjects’ responses may be due to suboptimal inference [71] , that is , inference based on suboptimal , or wrong assumptions about the underlying statistical structure of the inference problem . Our observation that s exceeds r suggests that subjects indeed perform suboptimal inference in the corresponding choice task . This finding , however , only holds under the assumption that the confidence threshold is set to a constant , low value ( λ = 0 . 02 ) , because r and λ have very similar effects on accuracy and mean RT . Indeed , we also found that behaviour in most conditions could be fit equally well , when r was constrained to be equal to s , but λ was allowed to vary freely . Although the drop in quality of fit for coherences 0% and 3 . 2% ( cf . results ) indicates a disadvantage of the constraint s = r compared to the constraint λ = 0 . 02 we cannot draw definite conclusions about whether subjects perform suboptimal inference , or not , from the present data . For coherences above about 25% parameter estimates became less reliable ( Fig 12A ) , because accuracy reached its ceiling of 1 and became uninformative . We expect that parameter estimates become more reliable in these experimental conditions , if reaction time distributions are used for fitting instead of only mean reaction times [54] . In the original fits of behaviour in [54] the drift was constrained to be a linear function of coherence ( [54] , Supp . Fig . 6 ) , where a single parameter , the slope of the linear function replaced coherence-specific drifts . In contrast , in our fits of the BAttM to the same data we allowed both , sensory uncertainty r and noise level s , to freely vary across coherences . Although this increased flexibility of the BAttM , in principle , could have led to overfitting , it is unlikely that this is the case for our results: The noise in the data is small compared to the effect of the coherence , because the data are averages based on 15 , 937 trials ( [54] , Fig 1 ) . The low variance of parameter estimates for intermediate coherences ( Fig 12A ) also indicates that our fitting method identified unique parameter values for these coherences . Furthermore , by relating the sensory uncertainty parameter in our fits to drift in the drift diffusion model [23] , we observed that the fitted values of sensory uncertainty r obey the linear constraint employed by [54] for coherences of up to 25% without explicitly using this constraint during fitting . It is currently unclear why the parameters for high coherences do not follow the previously assumed linear relation between drift and coherence . One possible explanation is that the urgency signal , which we did not model in the BAttM , has a larger effect for high coherences than for low ones . The estimated shape of the urgency signal ( [54] , Supp . Fig . 6b ) supports this speculation , because it exhibits a steep rise early in a trial such that its effect should be relatively large for fast decisions . However , clearly further research is required to substantiate this potential mechanism . The BAttM explains different behaviour in response to stimuli with different strength using particular combinations of input noise level s and sensory uncertainty r ( Table 2 , Fig 12 ) . It , therefore , appears that decision makers adapt their expectations about the stimulus ( r ) to stimulus strength even before they experience the stimulus ( we fixed r within trials ) . In experiments in which trials with the same stimulus strength are blocked , or in which stimulus strength is cued before onset of the stimulus , this is plausible . In experiments in which stimulus strength changes randomly across trials , this assumption seems flawed . This consideration has led others to discuss whether the brain implements Bayesian models [72] . Here , we speculate that decision makers rapidly adapt their expectations in parallel with decision making as they sample observations from the stimulus . Such adaptation is compatible with the timescale of short-term synaptic plasticity in the brain [73] . Also , it has previously been demonstrated that sensory reliability ( akin to r ) can be inferred together with stimulus identity in a Bayesian model [25] . Even though we believe that decision makers adapt their stimulus expectations within a trial , the BAttM currently does not employ such a mechanism . Nevertheless , assuming fixed r led to good fits of accuracy and mean RTs as recorded in [54] ( cf . Fig 12 ) . This is not very surprising: The behavioural data has originally been fit by a drift-diffusion model with constant drift throughout a trial [54] . Such constant drift implements the assumption that the average amount of evidence extracted from the stimulus at a given moment is constant throughout the trial . Critically , the ‘evidence’ is not a fundamental , sensory quantity , but needs to be computed by the brain specifically for the given decision problem . It can further be shown [23] that ‘evidence’ depends on sensory uncertainty in probabilistic models . Therefore , the assumption of a constant drift throughout a trial is , in the BAttM , equivalent to maintaining stable expectations about the stimulus throughout the trial . As a result , keeping r fixed in the BAttM is a simplification that follows previous approaches based on drift diffusion models and still allows to fit behaviour ( accuracy and mean RTs ) of subjects well ( see Fig 12 ) . Similar to within-trial effects of top-down gain modulation , however , future work may aim at elucidating potential effects of within-trial variations in expected sensory uncertainty r due to adaptation of stimulus expectations . In particular , experiments with longer re-decision trials and continuously changing stimulus reliability may induce strong adaptations of stimulus expectations that have measurable behavioural effects . One of the strengths of the original pure attractor models is their link to possible neurobiological implementations in networks of spiking neurons ( cf . Section: pattm ) . We have abstracted from this perspective and have embedded a pure attractor model in a dynamic Bayesian inference framework . Consequently , the question arises how this apparently more complicated construct may map to a neurobiological substrate . The BAttM is a probabilistic filter that recursively updates posterior beliefs by evaluating the likelihood of the state of a dynamic generative model given a stream of observations ( cf . models ) . A wide range of proposals have been made for how probabilistic filters can be implemented by networks of neurons [47 , 74–81] . For example , [80] discusses how computations defined by predictive coding approaches , which derive from probabilistic filters ( cf . Section Bayesinf ) , can map onto canonical microcircuits in cortex . More abstractly , [47 , 77 , 79] show how networks of rate neurons may implement probabilistic filters and [74–76 , 78 , 81] provide implementations based on spiking neuron networks . Given these proposals , it seems reasonable to assume that the computations defined by the BAttM can be implemented by the brain . We have presented a novel perceptual decision making model , the Bayesian attractor model , which combines attractor dynamics with a probabilistic formulation of decision making . The model captures important behavioural findings and makes novel predictions that can be tested in future experiments . In particular , we have highlighted a re-decision paradigm which can be used to investigate the tradeoff between flexibility and stability in perceptual decisions . Furthermore , the BAttM predicts particular , within-trial modulation of sensory gain which may explain recent experimental findings . Finally , the BAttM predicts experimentally testable links between choice , response times and confidence .
We used a Hopfield network as an example of a pure attractor model . Hopfield networks have originally been suggested as a neurobiologically plausible firing-rate models of recurrently connected neurons [44] . We define a general Hopfield network with N state variables as follows ( here summarised in one equation using matrix notation , see Fig 13 for a graphical representation of the binary case N = 2 ) : z ˙ = k ( L σ ( z ) + b l i n ( g 1 - z ) ) ( 9 ) where z ∈ ℝN is the decision state consisting of the state variables zi , k is a rate constant , σ ( ⋅ ) is a multidimensional logistic sigmoid function and blin is a parameter determining the strength of a goal state attractor g = g1 . Lateral inhibition for winner-take-all dynamics is implemented using σ i ( z ) = 1 1 + e - r ( z i - o ) and L = b l a t ( I - 1 ) ( 10 ) where r and o determine the slope and centre of the sigmoid function , respectively , blat determines the strength of the lateral inhibition , 1 ∈ ℝN×N is a matrix of ones , and I is the identity matrix . One can see that the fixed points with one state variable zm ≈ g , while all others are zj ≠ m ≈ 0 , are local minima of the underlying Lyapunov function and therefore stable [44] provided that o = g and blat/blin = 2g . We denote these stable fixed points as ϕm where m indicates the state variable that is equal to g . As parameter values we used k = 4 , g = 10 , r = 1 , o = g , blat = 1 . 7 , blin = blat/ ( 2g ) in all experiments , because these provided for numerically stable Hopfield dynamics which exhibited the desired fixed points and reasonably fast convergence to these . For interpolating observations in the generative model ( Eq 3 ) we use the same form of sigmoid as defined in Eq ( 10 ) , but with parameters r = 0 . 7 , o = g/2 . This choice increases the range of values for which the sigmoid is approximately linear and increases robustness of the inference with the generative model . When modelling perceptual decisions , we follow [26 , 28] and initialise the attractor dynamics in a neutral state . In particular , we set a prior distribution over the decision state as z0 ∼ 𝓝 ( μ0 , P0 ) where μ0 is an unstable equilibrium point of the Hopfield dynamics for which μ i = μ j and μ ˙ i = 0 ∀ i , j ∈ 1 , ⋯ , N . ( 11 ) This starting point ensures that a relatively long time is spent close to the equilibrium , while once the dynamics has sufficiently differentiated , the decision state will rapidly move to its closest stable fixed point . We set the covariance of the initial decision state to P 0 = p 0 2 I and call p0 the initial state uncertainty which is a parameter of the model that controls the susceptibility of the decision state to incoming evidence at the beginning of a trial . In Fig 6 we plotted contour lines . These were approximated from the noisy data points underlying the grey scale maps as follows . We defined four values for four contours for each map as reported in the caption of Fig 6 . For each value , e . g . , 500ms , we found all points in the parameter grid for which their own associated value lay within a limit to the chosen contour value ( limit of 0 . 01 fraction correct and of 10ms ) . We then fitted the hyperparameters of a Gaussian process [82] to the found points in logr-logs space ( one per contour line ) using the GPML Matlab toolbox ( http://mloss . org/software/view/263/ ) . In particular , the Gaussian process mapped the logarithm of the noise level , logs , onto the logarithm of the sensory uncertainty , logr and used a standard squared exponential covariance function with a Gaussian likelihood [82] . The contour lines in Fig 6 represent the mean predictions of sensory uncertainty obtained from the fitted Gaussian processes for the corresponding noise level . To fit the data from the experiment reported in [54] we defined a temporal scaling between our discrete model and the times recorded during the experiment . This scaling corresponds to Δt = 4ms in Eq ( 2 ) . It was chosen as a tradeoff between sufficiently small discretisation steps and computational efficiency and means that about 200 time steps are sufficient to cover the full range of reaction times observed by [54] . Furthermore , we used a non-decision time of T0 = 200ms which is roughly the value that was estimated by [54] ( cf . their Table 1 ) . The non-decision time captures delays that are thought to be independent of the time that it takes to make a decision . These delays may be due to initial sensory processing , or due to the time that it takes to execute a motor action . We used a form of stochastic optimisation based on a Markov Chain Monte Carlo ( MCMC ) method to find parameter values that best explained the observed behaviour in the experiment for each coherence level independently . This was necessary , because we could not analytically predict accuracy and mean reaction times from the model and had to simulate from the model to estimate these quantities . In particular , we simulated 1 , 000 trials per estimate of accuracy and mean RT , as done to produce Fig 6 . We then defined an approximate Gaussian log-likelihood of the parameter set used for simulation by using the estimated values as means: L ( s , r ) ∝ ( A - A ^ ) 2 σ A 2 + ( R T - R T ^ ) 2 σ R T 2 + P ( s , r ) ( 12 ) where A and RT are the accuracy and mean RT , respectively , measured in the experiment for one of the coherences and A ^ and R T ^ are estimates from the model . σA = 0 . 05 and σRT = 10ms are ad-hoc estimates of the standard deviation of the estimates which we chose large enough to account for the variability we observed in the data of Fig 6 . P ( s , r ) is a penalty function which returned values greater than 10 , 000 , when more than half of the simulated trials were timed out ( cf . light blue areas in Fig 6 ) and when the particular combination of s and r lead to too strong overshoots of a state variable ( cf . Fig 5A ) . We identified overshoot parameters as those which lay below a straight line from r = 0 . 47 , s = 1 . 45 to r = 3 . 66 , s = 80 in Fig 6 . We embedded the approximate likelihood of Eq ( 12 ) into the DRAM method of [83] ( Matlab mcmcstat toolbox available at http://helios . fmi . fi/~lainema/mcmc/ ) which implements adaptive Metropolis-Hastings sampling with delayed rejection . We log-transformed the parameters to ensure that only positive samples are generated and defined wide Gaussian priors in this log-space ( logs ∼ 𝓝 ( 0 , 102 ) , logr ∼ 𝓝 ( 0 , 102 ) ) , but also constrained s > 0 . 1 to ensure a minimum level of noise . We then ran the MCMC method for 3 , 000 samples , discarded the first 499 samples and chose every 5th sample to reduce correlations within the Markov chain . The resulting set of 501 parameter samples is a rough approximation of the posterior distribution over parameters for the given data . It is not statistically exact , because of the approximate likelihood , but it still indicates when parameter estimates become unreliable , as demonstrated in Fig 12 . The parameter values reported in Table 2 are those of the sample ( of the 501 ) which fitted the behaviour for a given coherence best , as determined by Eq ( 12 ) . Note that , different from [54] , we did not a priori assume a particular relationship between coherence and the parameters of the BAttM during fitting . In [54] coherence linearly scaled the drift in their drift-diffusion model using a scaling parameter K that was common across coherences ( [54] , Supp . Fig . 6 ) , that is , the average amount of momentary evidence accumulated in the model was determined from the coherence used in a trial . In the BAttM the fitted parameters , sensory uncertainty r and noise level s , determine how stimulus features are translated into momentary evidence . Since we did not want to assume , a priori , a specific relationship between the level of coherence and parameters s and r , we chose to let the parameters vary independently of coherence during fitting . However , we investigated whether an equivalent relation between r and coherence holds for the fitted values of r . As stated in the main text , this relation can be written as r2 = K′/c where c is coherence and K′ is an arbitrary constant . Consequently , we used a least-squares approach to estimate K′ from given pairs of coherence ( in % ) and sensory uncertainty r ( Table 2 ) . The best fitting value was K′ = 381 . 9 . As suggested by one reviewer , it may be useful to assume the above relation between r2 and c as a constraint when fitting noisy data . This can be easily done by fitting K′ to the data across coherences instead of directly fitting one r per coherence . | How do we decide whether a traffic light signals stop or go ? Perceptual decision making research investigates how the brain can make these simple but fundamentally important decisions . Current consensus states that the brain solves this task simply by accumulating sensory information over time to make a decision once enough information has been collected . However , there are important , open questions on how exactly this accumulation mechanism operates . For example , recent experimental evidence suggests that the sensory processing receives feedback about the ongoing decision making while standard models typically do not assume such feedback . It is also an open question how people compute their confidence about their decisions . Furthermore , current decision making models usually consider only a single decision and stop modelling once this decision has been made . However , in our natural environment , people change their decisions , for example when a traffic light changes from green to red . Here , we show that one can explain these three aspects of decision making by combining two already existing modelling techniques . This resulting new model can be used to derive novel testable predictions of how the brain makes perceptual decisions . | [
"Abstract",
"Introduction",
"Models",
"Results",
"Discussion",
"Methods"
] | [] | 2015 | A Bayesian Attractor Model for Perceptual Decision Making |
The role of biofilms in the pathogenesis of mycobacterial diseases remains largely unknown . Mycobacterium ulcerans , the etiological agent of Buruli ulcer , a disfiguring disease in humans , adopts a biofilm-like structure in vitro and in vivo , displaying an abundant extracellular matrix ( ECM ) that harbors vesicles . The composition and structure of the ECM differs from that of the classical matrix found in other bacterial biofilms . More than 80 proteins are present within this extracellular compartment and appear to be involved in stress responses , respiration , and intermediary metabolism . In addition to a large amount of carbohydrates and lipids , ECM is the reservoir of the polyketide toxin mycolactone , the sole virulence factor of M . ulcerans identified to date , and purified vesicles extracted from ECM are highly cytotoxic . ECM confers to the mycobacterium increased resistance to antimicrobial agents , and enhances colonization of insect vectors and mammalian hosts . The results of this study support a model whereby biofilm changes confer selective advantages to M . ulcerans in colonizing various ecological niches successfully , with repercussions for Buruli ulcer pathogenesis .
Mycobacterium ulcerans is the etiologic agent of Buruli ulcer , a necrotic skin disease affecting humans living close to wetlands in tropical countries . The natural history and transmission of this mycobacteria are still obscure . Epidemiological studies suggest that swampy areas , and more specifically , aquatic environments , are the main ecosystems inhabited by M . ulcerans [1–7] . Many aquatic insects in this environment are predators that feed on herbivorous organisms , such as snails , which , after grazing on plants covered by M . ulcerans , act as passive hosts . It is conceivable that , following ingestion of prey contaminated with M . ulcerans , certain carnivorous aquatic insects might then transmit the bacteria to humans . We previously demonstrated that predatory aquatic insects , such as Naucoris cimicoides , ingest M . ulcerans–containing prey under laboratory conditions and are both hosts and vectors of this mycobacterial species [8–11] . Indeed , they are able to deliver invasive bacteria to laboratory mice , whose tails were exposed to the infected insects , with lesions developing 30 to 90 d later precisely at the point where the bite occurred . M . ulcerans is the only Mycobacterium species that localized within the salivary glands of these aquatic insects , where it can both survive and actively multiply without damaging insect tissues [8 , 10] . Furthermore , it has recently been shown that the lipid toxin mycolactone , the sole known virulence factor responsible for Buruli ulcer [12] , is essential for the colonization of the salivary glands and that mycolactone-deficient mutants do not multiply in N . cimicoides [10] . Another striking feature of M . ulcerans is its ability to assemble into a biofilm , as first seen on the surface of aquatic plants [3] . Biofilms for human bacterial pathogens such as Pseudomonas aeruginosa , Haemophilus influenzae , and Vibrio cholerae have been well-studied [13] and consist of discrete bacteria surrounded by an extracellular matrix ( ECM ) [14 , 15] . Typically , the ECM shapes the bacterial network and can be crossed by channels , which play a critical role in water and nutrient circulation , as well as in interbacterial communication via quorum-sensing [16] . Biofilm formation confers a selective advantage for persistence under diverse environmental conditions and for resistance to antimicrobial agents , and also facilitates colonization of the host by the bacteria [13] . With regard to mycobacterial species , mutants of M . avium and M . smegmatis impaired in biofilm formation are less able to invade and translocate through bronchial epithelial cells and to form smegma in mice , respectively [17 , 18] . Molecular events involved in biofilm formation have already been reported in several studies undertaken on the genetically tractable M . smegmatis [19] . Recently , the GroEL1 chaperone was shown to be involved in mycolic acid biosynthesis during biofilm formation . Here , we show that the ECM of M . ulcerans differs from known biofilms since it is associated with only the outermost cell layer as opposed to classic biofilms in which all cells are surrounded by the matrix . Biochemical characterization of the ECM was performed and its role in pathogenesis at the different stages of the currently known life cycle investigated . Taken together , these findings provide insight into the factors that promote persistence in diverse environmental niches and infectivity of M . ulcerans to various hosts .
Given the complexity of the life cycle of M . ulcerans , systematic examination was undertaken of the ultrastructure of the bacterium by scanning electron microscopy . Large clusters of M . ulcerans that were covered with a biofilm-like structure were detected in biopsy samples from patients with confirmed Buruli ulcers ( Figure 1A ) . An analogous biofilm structure was also found in bacteria isolated from lesions from mice experimentally infected with M . ulcerans . According to the relative magnetic bead size , the surface of the recovered biofilm-like structure is estimated at about 200 μm × 50 μm , suggesting that one structure could harbor up to 105 bacteria . Further analysis of the same samples by Ziehl–Neelsen staining also revealed that , for each biofilm-like structure , there were less than ten free individual bacilli ( unpublished data ) . A biofilm-like structure was also seen with M . ulcerans cultured in 7H9 broth , with or without Tween 80 , and in 7H11 and 7H12 with or without PANTA ( antimicrobial mixture ) ( unpublished data ) . The same amount of ECM was recovered from bacteria grown under all these culture conditions . Strains 1615 and 1G897 were examined at different time points , and bacilli-containing clusters were evident as early as day 10 ( Figure 1B-1 ) . From days 35 to 45 , large cell aggregates measuring more than 100 μm were detected ( Figure 1B-3 ) . Higher-magnification micrographs revealed that entire clusters were surrounded by an abundant biofilm-like structure , the ECM ( Figure 1B-4 ) . All M . ulcerans clinical isolates that were cultured under the same conditions displayed the same biofilm-like structure , including the mycolactone-deficient mutant of 1615 , mup045 ( unpublished data ) . In contrast , other environmental or pathogenic mycobacteria , such as M . chelonei , M . fortuitum , M . kansasii , and M . tuberculosis , grew in vitro without displaying significant ECM despite their exhibiting large clusters of cells ( Figure S1 ) . M . marinum , the progenitor of M . ulcerans [20] , formed discrete packets of cells that were quite distinct from the clusters , but displayed no ECM ( Figure S1-3 ) . These data show that the ECM is a peculiar feature of M . ulcerans colonies . Subsequent analysis by transmission electron microscopy ( TEM ) revealed that the ECM covers only the outermost bacterial layer , its thickness was estimated to range between 4 and 40 μm ( Figure 2A , dotted circled area ) . Strikingly , very little matrix was found within the bacterial network ( Figure 2B , arrows ) . This contrasts with classical biofilm , in which the bacteria are each individually surrounded by the matrix [14 , 15] . Furthermore , scanning microscopic pictures of M . ulcerans strains revealed the presence of vesicles on the surface of the ECM after 35 to 45 d of incubation ( Figure 3A ) . The diameter of the vesicles varied between 50 and 200 nm ( Figure 3B ) . Vesicles were isolated by ultracentrifugation from the wild-type bacterial ECM as well as from the mycolactone-deficient mutant ( unpublished data ) . Together with ECM , vesicles could also be recovered from biopsies of mouse lesions by immunomagnetic separation ( Figure 3C ) . Furthermore , the vesicles could be isolated independently from the ECM fraction by performing ultracentrifugation and were thus considered separately in the following analysis . To determine whether this matrix influences bacterial phenotype , comparison of the growth rate of M . ulcerans either harboring ECM , or from which ECM was carefully removed , was undertaken . No difference in colony-forming unit ( CFU ) counts of bacteria using Löwenstein–Jensen slants , and in metabolic activity using the Bactec radiometric method , was found with or without ECM removal from M . ulcerans ( Figure 4 ) , suggesting that biofilm does not confer a selective advantage for bacterial growth in vitro . In our culture conditions , the ECM re-forms in 2 wk . The ECM fraction was isolated from broth-cultured M . ulcerans by mechanical disruption combined with Tween 80 detergent treatment , as typically used for other mycobacteria [21 , 22] . Fifteen seconds are sufficient for complete removal of ECM from bacteria ( Figure 4A ) . We then compared the effect of the treatment on the cultivability of the treated bacteria . The same amount of CFUs was obtained for M . ulcerans with or without ECM ( Figure 4B ) , showing that this mechanical disruption does not impair the cultivability of the bacteria . Furthermore , we checked whether this treatment modifies bacterial permeability . To this end , the level of potassium release by bacteria was monitored . No significant levels of potassium were released after mechanical vortexing for up to 60 s compared to untreated bacteria ( Figure 4C ) . In addition , the presence of KatG , a catalase-peroxidase that is cytosolic or membrane-associated , was not detected by Western blot analysis in samples that had been treated for 15 s and 30 s ( Figure 4D ) . Altogether , these data show that ECM can be efficiently isolated with a 15-s mechanical disruption , and this argues against major contamination of ECM by lysed bacteria . To determine whether ECM plays a role in protecting bacteria from toxic compounds in the environment , the susceptibility of M . ulcerans , with and without ECM , toward chlorine and two common antibiotics was tested . This could be done since removal of ECM did not alter the growth of M . ulcerans , as shown above ( Figure 4B ) . The minimum inhibitory concentration ( MIC ) of rifampin was <0 . 0625 μg/mL for M . ulcerans devoid of ECM compared to 0 . 5 μg/mL for M . ulcerans with ECM , a significant increase in susceptibility ( p = 0 . 01 ) . In contrast , the MIC for amikacin was identical under both experimental conditions . To test the susceptibility of M . ulcerans to chlorine , the bacteria were incubated in solutions of different concentrations . The concentrations of chlorine required to kill 108 M . ulcerans cells , with or without ECM , were 100 and 40 mg/l , respectively ( p = 0 . 05 ) . Taken together , these results suggest that the ECM protects the M . ulcerans population from noxious agents . Coomassie blue staining of an SDS-PAGE gel of the ECM fraction shows that the protein composition differs between isolated ECM and that of a whole bacterial lysate ( Figure 5 , lanes 1 and 2 ) . By subsequent use of two-dimensional ( 2-D ) gel electrophoresis or liquid chromatography combined with mass spectrometry ( LC/MS ) , 84 proteins were identified within the ECM fraction ( Table 1 ) and classified in seven out of 11 different functional categories used for pathogenic mycobacteria . As many as 70 ( 83% ) of the proteins fell into four classes: 14 in virulence , detoxification , and adaptation; 10 in lipid metabolism; 32 in intermediary metabolism and respiration , and 14 in the conserved hypothetical protein class ( Tables 1 and S1 ) . AhpC , AhpD , and SodA are major players in the oxidative stress defense , whereas DnaK , GroEL1 , GroEL2 , GroES , HtpG , Hsp18 , ClpB , ClpC1 , and Clp1 are specialized in heat shock responses . Of particular interest , the GroEL1 chaperone was recently shown to modulate synthesis of mycolates during biofilm formation [19] . Strikingly , a large number of proteins essential for intermediary metabolism and respiration were identified in the ECM , which has not been reported in other bacterial biofilm studies . Among them , pgi- , pgk- , gltA2- , and glcB-encoded proteins are involved in glycolysis , the tricarboxylic acid cycle , or even the glyoxylate shunt . Furthermore , the protein pattern of isolated ECM—as classified by class or molecular weight—is significantly different from that of the secreted proteins , indicating that the ECM is an independent and specific bacterial compartment . Interestingly , besides chaperones , common mycobacterial antigens such as the antigen 85 family ( FbpA , B , C , D ) , Mpt64 , and Wag31 were not identified in the ECM by the proteomic analysis . However , it is well known that Buruli ulcer patients develop humoral responses to several M . ulcerans antigens [23 , 24] . To further check for the presence of M . ulcerans antigens within the ECM , this fraction was probed with the serum of 30 patients diagnosed with Buruli ulcer . Using Western blotting , no ECM-reactive IgG antibodies were detected in the serum of all patients , irrespective of the disease stage ( Figure 5A ) . In contrast , the serum contained IgG antibodies that bound to many components of the bacterial lysate ( Figure 5A ) . A more sensitive ELISA method was used to search for IgG antibodies recognizing M . ulcerans proteins in different fractions . Sera from all patients reacted with the whole bacterial lysate , cytosolic , membrane , and vesicle fractions , but not with the ECM fractions ( Figure 5B ) . Indeed , no ECM-reactive IgG antibodies were detected in 53% ( 16/30 ) of the cases . Biochemical analysis of ECM revealed a complex mixture of carbohydrates and lipids , with the total amount of carbohydrates in the ECM estimated to be as high as 2 mg per 109 bacteria , a value 3-fold higher than that measured for the same number of bacterial cells lacking ECM but submitted to the same treatment . Fluorescence microscopy confirmed the abundance of carbohydrates , which are mainly localized in the ECM of the bacterial cluster ( Figure 6A ) Moreover , M . ulcerans aggregates have a high affinity for calcofluor , suggesting that β-glucans were a major component of ECM ( unpublished data ) . Thin-layer chromatography ( TLC ) analysis of the sugar constituents of the ECM showed that glucose and mannose were the main monosaccharides found in this fraction ( unpublished data ) . Strikingly , the ECM of M . ulcerans wild-type strain 1615 contained the bulk of the mycolactone , with as much as 0 . 2 mg per gram of bacteria ( Figure 6B-1 ) . In addition to the toxin , the lipid content of the ECM from M . ulcerans wild-type strain 1615 consisted mainly of phosphatidylinositol mannosides ( PIM2 , PIM5 , PIM6 ) , phospholipids ( phosphatidylethanolamine , phosphatidylinositol , cardiolipin ) , triacylglycerol , phthiodiolone diphthioceranates , and two unidentified apolar compounds ( Figure 6B-2 ) . Using the CS-35 monoclonal antibody , lipoarabinomannan was detected in ECM . Interestingly , in spite of their reported abundance in the outermost layers of the cell envelope of some M . ulcerans strains [25] , no trehalose dimycolates were detected in the matrix . Further comparative analysis show that the type and quantity of lipids of the ECM were similar in the transposon mutant mup045 , where they were impaired in mycolactone production , and the wild-type strain . The vesicles could be isolated independently of the ECM fraction by performing ultracentrifugation . By subsequent use of LC/MS , 57 proteins were identified within the purified vesicle fraction ( Table 2 ) . Among them , only six proteins were also found in ECM , whereas 51 were also present in the membrane fraction , suggesting that vesicles are more likely to derive from the membrane compartment . Strikingly , the polyketide synthases MlsA1 and MlsB required for mycolactone synthesis are also present in the vesicles , and further lipid analysis showed the presence of mycolactone there ( unpublished data ) . Surprisingly , vesicles recovered from wild-type bacteria displayed cytotoxic activity on bone marrow–derived mouse macrophage cultures . Indeed , 24 h after vesicle addition , 80% of the macrophages were lysed , and similar cytotoxicity was seen with HeLa and Cos cells ( Figure 7 ) . In parallel , mycolactone purified from M . ulcerans was noticeably much less cytotoxic than the vesicles that were prepared and purified from an equal amount of the same culture , suggesting that the supramolecular organization of mycolactone affects its biological activity ( Figure 7 ) . It has also been found that , owing to its hydrophobic nature , the toxin aggregates , thus giving non-linear dose-response curves [26] . In addition , vesicles isolated from mup045 did not cause cytotoxicity , regardless of the amount added ( unpublished data ) , demonstrating that the vesicles' toxicity is likely due to the presence of mycolactone . Altogether , these data suggest that vesicles trigger mycolactone export , thus enhancing toxicity . To determine whether the ECM affects bacterial virulence within the host , we infected mice in the tail with M . ulcerans , with or without ECM , and examined the inoculation site for bacterial load , the time of onset of clinical symptoms , and symptom severity . The clinical evolution was significantly different ( p = 0 . 008 ) using the two bacterial populations: lesions occurred much earlier in mice inoculated with 103 bacilli covered by ECM ( 35 ± 5 d versus 58 ± 7 d ) . In addition , all mice ( 10/10 ) inoculated with bacteria covered with ECM showed cutaneous lesions . In contrast , seven of ten mice inoculated with bacteria lacking ECM displayed similar lesions . The results are consistent with a role for the ECM containing vesicles as a reservoir of toxin . We investigated whether the ECM plays a role in the colonization of aquatic insects by M . ulcerans , as we have recently shown that the early trafficking events involve translocation of the bacillus from the head capsule to the coelomic cavity containing hemolymph [11] . To evaluate the role of ECM during the translocation , Naucoris aquatic insects were first fed with prey that had been inoculated with M . ulcerans , with or without ECM . After 6 h , the insect hemolymph was extracted and presence of M . ulcerans DNA was determined by real-time PCR . As shown in Table 2 , no M . ulcerans DNA could be detected in samples from insects infected with M . ulcerans lacking ECM , whatever the initial bacterial load . In contrast , in the case of bacteria with ECM , M . ulcerans DNA corresponding to up to 5 × 104 bacteria was readily detected . It should be recalled that both types of bacteria inoculated into the prey remain cultivable in this setting . Thus , in our experimental model of aquatic bug infection , M . ulcerans lacking ECM was apparently unable to colonize the insect vector , suggesting that the ECM is required during translocation . Using scanning electron microscopy , no sign of ECM was found on bacilli in the salivary glands of N . cimicoides that were previously infected with M . ulcerans covered by ECM ( Figure 8A ) . However , the latter was observed on insect setae , through which the infection occurs via penetration of the prey [10] . Furthermore , incubation of M . ulcerans having ECM with salivary gland extracts from N . cimicoides resulted in rapid and complete degradation of ECM [11] . A likely explanation is that hydrolytic enzymes interact with the ECM and trigger its disintegration . We have previously shown that M . ulcerans can be naturally recovered from the environment as a biofilm on the surface of aquatic algae [3] . However , this biofilm structure completely differs from that of the ECM as seen in in vitro culture in the absence of algal extract and host lesions ( Figure 8B ) . In the presence of algal extracts , ECM could still be present , though in amounts undetectable by electron microscopy . No proteins from the ECM fraction isolated from cultures performed in the presence of algal extracts were detected by LC/MS analysis . Additionally , biochemical composition analysis showed that while significant amounts of mycolactone and ( glyco ) phospholipids ( cardiolipin , phosphatidylethanolamine , phosphatidylinositol , and phosphatidylinositol mannosides ) were detected in the ECM from control bacteria , there was no evidence for the presence of such material in algae-treated bacteria ( unpublished data ) . Moreover , when these bacterial clusters were inoculated in fresh standard culture media , or when intermediate hosts , such as aquatic snails , were fed with these bacterial clusters , the ECM was synthesized within a few days ( unpublished data ) . Taken together , the absence of ECM in specific conditions , i . e . , in culture medium complemented by crude algal extract or in the salivary gland of water bugs , strongly suggests regulation of ECM formation by external factors .
We investigated the presence of the extracellular matrix within M . ulcerans biofilms in the different settings of the currently known lifecycle . We show that M . ulcerans forms biofilms on the surface of aquatic plants [3] , and , in addition , this is surrounded by an ECM in hosts such as snails , mice , and humans . We also demonstrated that M . ulcerans with ECM is more potent for insect and mammalian host colonization , which is typical for bacterial biofilms in general [13] . In contrast to other bacterial biofilms [14 , 15] , M . ulcerans ECM is devoid of bacteria and is a thick layer only in contact with the outermost layer of M . ulcerans . While scanning electron and fluorescence microscopy unambiguously showed the abundance of ECM on the external surface of the aggregates , no ECM could detected within the network of bacteria in aggregate . This observation could not be supported by a statistical analysis , as we encountered severe difficulties for generating a large number of sections for TEM analysis from the same sample . We observed that during the fixation step , the araldite resin penetrated inefficiently into the bacterial aggregates , even when high pressure fixation was used . This phenomenon is likely to be due to the thickness of the ECM , which may also create a microaerophilic atmosphere that has been found more suitable for M . ulcerans growth in hostile conditions [27] . Similar to other biofilms , the ECM of M . ulcerans seems to be crossed by channels , whose role requires further investigation [16] . Some of the lipids/lipoglycans identified in the M . ulcerans ECM , such as lipoarabinomannan , PIM , and phthiocerol diesters , are known to play important roles in the permeability barrier of the cell envelope , as well as in the virulence of other mycobacterial species [28–30] . The ECM also contains significant quantities of carbohydrates , with glucose being the main monosaccharide constituent . The abundance of this polysaccharide in M . ulcerans suggests that it might be structurally related to the capsular D-glucan of M . tuberculosis [31] . Assuming that the bacteria use the ECM as a source of carbon and energy , there may be a relationship between the presence of carbohydrates and enzymes involved in glycolysis and the tricarboxylic acid cycle in the ECM . It has already been shown that ectoenzymes or exoenzymes of biofilms could be involved in the complex process of conversion of non-assimilable into assimilable molecules , as seen in Cellulomonas flavigena [32] . One striking feature of the ECM is its large variety and abundance of proteins . It could be argued that the presence of such a large amount of proteins results from bacterial lysis . However , the method used for preparing the ECM has also been used to investigate the architecture of the cell envelope of other mycobacteria without causing significant lysis [21] , as confirmed by our control experiments ( Figure 4C and 4D ) . Among the abundant proteins in the ECM were several chaperones , and the genes encoding chaperones like DnaK , GroEL , GroES and other oxidative stress response proteins are known to be over-expressed in different biofilms ( Staphylococcus aureus , P . aeruginosa ) [33 , 34] , and GroEL1 was recently reported to be involved in biofilm formation in M . smegmatis [19] . Surprisingly , many enzymes required for the biosynthesis or catabolism of lipids and sugars were recovered from the ECM , whereas most of them are usually located exclusively in the cytoplasm of planktonic bacteria . Their presence within the M . ulcerans ECM suggests that they may participate in the formation or maturation of the ECM , although their functionality remains to be addressed . Another general feature of the biofilm matrix of bacteria is its role as a diffusional barrier interfering either with the transport kinetics or the modification of extracellular molecules . We showed that ECM-coated M . ulcerans bacteria are resistant to rifampin , but not to amikacin . Similarly , biofilm-grown cells of M . avium in catheters are also resistant to rifampin as well as to clarithromycin [35] . In contrast , rifampin activity was not reduced for slime producing S . epidermidis [36] . The difference in susceptibility of ECM-harboring M . ulcerans to amikacin and rifampin could be explained by ECM acting as a selective barrier or trap for rifampin , or it may even contain enzymes that hydrolyze rifampin . The ECM is likely to function as a resistance barrier to the host immune system . In Staphylococcus biofilms , the matrix was shown to interfere with macrophage phagocytic activity [37] and to prevent antibodies from reaching the bacterial cell surface [38] . On the one hand , M . ulcerans escaping from immune recognition could be due to the inaccessibility of the surface antigens to the host immune system . On the other hand , mycolactone has already been shown to limit phagocytic activity [26 , 39] as well as to cause the death of macrophages and other cells via apoptosis [12 , 40] . Uncoupling the specific effects of ECM from those of mycolactone at the cellular level is currently being investigated . Usually , toxins of Gram-positive bacteria accumulate in the cytoplasm in a precursor form or are secreted without accumulation . In Gram-negative bacteria , apart from the endotoxin lipopolysaccharide , the same processes are observed . The presence of mycolactone in an external reservoir was proposed previously when the toxin was found associated with suspended lipids [41] . We provide further evidence by showing that mycolactone accumulates mainly in the ECM , which may play the role of a reservoir and amplify the pathogenicity of the bacteria . Furthermore , the toxin is secreted in specialized vesicles , which are cytotoxic for a variety of cells , both phagocytic and non-phagocytic , suggesting that mycolactone-containing vesicles do not recognize a specific receptor . Similarly , vesicles have already been shown to be secreted by some bacteria and exported to reach their target for delivering virulence factors to host cells [42] . The fact that mycolactone is sequestered within vesicles suggests that treatment prospects based on the design of neutralizing antibodies against this polyketide toxin would likely be inefficient . Although we showed that ECM has an important role for insect vector colonization and M . ulcerans translocation to the coelomic cavity , no ECM is found on the bacteria in this particular compartment . This could be due to two different processes: either hydrolysis by salivary enzymes , or down-regulation of matrix production by external factors . For instance , no matrix was produced when M . ulcerans catabolized carbohydrates present in algal material , whereas growth in lipid-rich medium such as 7H9 with oleic acid induced copious amounts . Generating a mutant lacking ECM will help decipher the molecular mechanisms involved in ECM production , although inhibiting its synthesis with plant extracts may be a useful alternative . Unraveling the regulation of the production of the ECM together with the export of mycolactone will be an important step in developing new pharmacological approaches for the treatment of Buruli ulcer , which has been greatly handicapped by the lack of effectiveness of the current antibiotics .
The strains of M . ulcerans 1G897 [43] and 1615 [12] ( Trudeau Collection Strain ) were originally isolated from human skin biopsies from French Guyana and Malaysia , respectively . Each clinical isolate was inoculated in the mouse tail . Forty days later , M . ulcerans bacteria were recovered from the infected tissue and seeded onto Löwenstein–Jensen slants ( Bio-Rad , http://www . bio-rad . com ) for an additional 45 d before being aliquoted and stored at −80 °C [44] . The mup045 mutant ( MU1615::Tn118 ) has a transposon insertion located in the ketosynthase gene mup045 , leading to undetectable levels of mycolactone in culture [26 , 39] The mycobacterial strains M . chelonei ( 6B0139 ) , M . fortuitum ( 10B0345 ) , M . kansasii ( 11B0014 ) , M . marinum ( 8B0432 , clinical isolate from a French patient ) , and M . tuberculosis H37Rv were used as controls . Frozen aliquots of each strain were first inoculated onto 7H11 solid medium supplemented with 10% OADC ( oleic acid , dextrose , catalase; Difco , Becton-Dickinson , http://www . bd . com ) and Tween 80 0 . 05% ( Sigma , http://www . sigmaaldrich . com ) . Then , 35 d later , exponentially growing bacteria from agar plates were harvested in 7H9 broth supplemented with 10% OADC and Tween 80 0 . 05% ( Sigma ) at 105 bacteria/mL . Titration of the intitial inoculum was performed by the Shepard and Rae method [45] . The cultures were performed in 200 mL in a disposable polystyrene cell culture flask ( EasYFlask; Nunc , http://www . nuncbrand . com ) with gentle agitation ( 30 rpm ) at 30 °C for 35 d , which corresponds to the end of exponential phase of bacterial growth . Regarding the experiment performed with the algal extract , mycobacteria were inoculated at 105 bacteria/mL in 200 mL of 7H9 broth supplemented with 10% OADC , Tween 80 0 . 05% , and a crude extract of Rhizoclonium sp . algae obtained as previously described [3] . Samples were fixed for 30 min in 0 . 1 M cacodylate buffer ( pH 7 . 2 ) containing 2 . 5% glutaraldehyde for 1 h at 4 °C , then left to stand for 12 h at 20 °C in cacodylate buffer . Specimens were progressively dehydrated and then metallized prior to examination by scanning electron microscopy on a JEOL 6301F field emission microscope . For transmission microscopy , the bacteria were embedded in Araldite ( Fluka , St . Quentin Fallavier , France; http://www . sigmaaldrich . com/Brands/Fluka___Riedel_Home . html ) . After dehydration , thin sections were stained with uranyl acetate and Reynold's lead citrate and then examined on a JEOL 120 EX electron microscope . The fresh broth was incubated overnight and cells were harvested by centrifugation ( 8 , 000g for 10 min ) , and washed twice in PBS . The resulting pellets were fixed in 2 . 5% ( w/v ) glutaraldehyde , in cacodylate buffer for 2 h in the dark at room temperature . Cells were washed three times in cacodylate buffer ( 0 . 1 M [pH 6 . 8] ) , postfixed for 2 h in the dark in 1% ( w/v ) osmium tetroxide ( Sigma ) , 0 . 05% and then washed twice each in cacodylate buffer and in water . Bacteria were dehydrated through a graded ethanol series of 50% , 60% , 70% , 80% , and 95% for 5 min each , and then washed twice for 15 min each in 100% ethanol , then twice for 15 min each in propylene oxide . The bacteria were finally embedded in Araldite ( Fluka ) . Resin was replenished the next morning and samples were left to cure at 60 °C overnight . Blocks were thin-sectioned on a Reichert–Jung microtome and mounted on copper grids . Sections were poststained with uranyl acetate and Reynold's lead citrate . Microscopy was performed on a JEOL 120 EX electron microscope . A biopsy from an Ivory Coast patient and from mouse tail lesions were surgically excised from skin . The tissue specimens were minced with disposable scalpels in a Petri dish and ground with a Potter–Elvehjem homogenizer , size 22 ( Kimble/Kontes , http://www . kimble-kontes . com ) , in PBS/Tween 80 0 . 05% . For isolation of M . ulcerans , the human and mouse tissue specimens were processed by immunomagnetic separation to isolate bacilli . Two types of immunomagnetic particles were used: 2 . 8-μm-diameter immunomagnetic particles precoated with sheep anti-rabbit IgG ( Dynald ) for the human sample , and 1-μm-diameter immunomagnetic particles precoated with goat anti-rabbit IgG ( Interchim , http://www . interchim . com ) for the mouse sample . Firstly , coating of the immunomagnetic particles ( 104 ) was carried out for 2 h at 37 °C with agitation with a rabbit polyclonal antibody raised against whole PFA-fixed M . ulcerans [8] at 20 μg in a total volume 200 μl of PBS ( pH 7 . 2 ) containing Tween 80 0 . 05% . Secondly , 0 . 1 g/mL of tissue homogenate was added to the coated immunomagnetic particles and incubated with bidirectional mixing at 4 °C for 12 h . Finally , particles were washed six times for 3 min each with PBS containing Tween 80 0 . 05% . A 35-d-old M . ulcerans shaking culture ( 200 mL ) was washed three times with 20 mM Tris-HCl ( pH 7 . 5 ) ( 3 , 000g for 30 min at 4 °C ) . The mycobacterial pellet was then resuspended in the same buffer supplemented with antiprotease Complete EDTA free cocktail ( Roche , http://www . roche . com ) to obtain 109 bacilli/mL . Thirty glass beads ( 4 mm in diameter ) were added to the suspension and vortexed for 15 s . The mycobacterial suspension was then centrifuged at 8 , 000g for 10 min at 4 °C . The ECM fraction consists of the supernatant collected after centrifugation and filtration through a 0 . 45-μm filter . The supernatant was further fractionated into vesicles that were recovered in the pellet after ultracentrifugation at 40 , 000g for 3 h , then washed three times in 0 . 1 M Tris-HCl ( pH 7 . 5 ) with Tween 80 0 . 05% . The pellet containing whole bacteria was then suspended in the same buffer and the mycobacteria were broken with 106-μm acid washed glass beads ( Sigma ) for 5 min at speed 30 using a bead beater ( Mixer Mill MM301; Retsch GmbH , http://www . retsch . com ) at 4 °C . The bacterial lysate consisted of the supernatant obtained after removal of unbroken cells and cell debris by centrifugation at 8 , 000g at 4 °C . The soluble cytosolic proteins were subsequently obtained by ultracentrifugation of the bacterial lysate ( 70 , 000g , 90 min , 4 °C ) . The pellet , consisting of membrane proteins , was washed with 200 μl of 50 mM Tris-HCl ( pH 7 . 5 ) to remove residual cytosolic contaminants and then resuspended in 50 mM Tris-HCl ( pH 7 . 5 ) . For all fractions , quantification was performed by measuring protein concentration using a Bio-Rad protein assay . Regarding the secreted proteins , the shaking liquid culture was performed in the absence of albumin and prepared as previously reported [46] . Briefly , the culture filtrate was recovered after filtration through 0 . 22-μm-pore-size filters ( Millex GP; Millipore , http://www . millipore . com ) , followed by concentration using a filter with a 3-kDa cutoff ( Centricon; Millipore ) . Bacterial suspension preparation and ECM removal were carried out exactly as described above . After recovery by centrifugation at 5 , 000g for 10 min , the number of CFU was determined by inoculating 10-fold dilutions of the bacterial suspension onto three Löwenstein–Jensen slants ( Bio-Rad ) incubating for 6 wk at 30 °C . In addition , the bacterial dilutions were inoculated into Bactec 12B vials ( Becton-Dickinson ) containing Middlebrook medium with 14C-labeled palmitic acid as a carbon source . Substrate consumption generates 14CO2 in the airspace of the sealed vial . The BACTEC TB-460 instrument detects the amount of released radioactivity and records it as a growth index ( GI ) on a scale from 0 to 999 . The vials were incubated at 30 °C , and every 5 d the GI was recorded . To test bacterial permeability , kinetics of vortexing with glass beads for the ECM removal step was performed at 15-s intervals for up to 3 min . After removal of unbroken cells and debris by filtration ( 0 . 45 μm ) , quantification of K+ in the supernatant was monitored on BM/Hitachi 917 apparatus following manufacturer protocol . As a control , boiled M . ulcerans suspension was used for maximum K+ release . In addition , KatG detection was performed by Western blot analysis , as this enzyme is known to be localized in the membrane and cytosol . To this end , supernatant of bacterial culture pelleted after treatment by glass bead ( 60 μg ) was loaded on a sodium dodecyl sulfate ( SDS ) –polyacrylamide gel ( 4%–12% ) ( Bio-Rad ) and the separated bands were transferred onto a 0 . 45-μm nitrocellulose membrane ( Amersham , http://www . amersham . com ) . After blocking with 5% skimmed milk in PBS , the membrane was incubated with serum from rabbit anti-KatG 1:100 [47] in PBS containing Tween 80 0 . 05% ( Sigma ) for 90 min at 37 °C . After two washes with PBS containing Tween 80 0 . 05% , sheep anti-rabbit IgG ( heavy and light chains ) peroxidase-conjugated antibodies ( Amersham ) at 0 . 5 μg/ml and 0 . 5 μg/ml DAB ( Interchim ) was used for detection of the bands . Protein fractions were analyzed by 1- or 2-D gel electrophoresis followed by a combination of matrix-assisted laser desorption/ionization mass spectrometry peptide mass fingerprinting ( MALDI-MS PMF ) and liquid chromatography/electrospray ionization mass spectrometry ( LC-MS/MS ) . The spots or bands of interest were excised from the gel and treated automatically using a Probest/P50MS robotics system ( Genomics Solutions , http://www . genomicsolutions . com ) . The tryptic peptide mixture was then extracted by 10% formic acid , desalted using Micro C18 Zip Tips ( Millipore ) , and eluted with 0 . 5 μl of alpha-cyano-4-hydroxy-cinnamic acid ( Sigma ) . The samples were analyzed by MALDI-MS on a Voyager DE STR ( PerSeptive Biosystems , http://www . appliedbiosystems . com ) equipped with a nitrogen laser ( 337 nm ) . To search the M . ulcerans ORF database “BuruList” ( http://genolist . pasteur . fr/BuruList ) , monoisotopic masses were assigned using a local copy of the MS-Fit3 . 2 part of the Protein Prospector package ( University of California Mass Spectrometry Facility , San Francisco; http://prospector . ucsf . edu ) . The parameters were set as follows: no restriction on the isoelectric point of proteins , 50 ppm as the maximum mass error , and one incomplete cleavage per peptide . Eleven different samples were analyzed . Protein digest fractions of samples were also analyzed by reverse phase LC-MS/MS . As peptides eluted off the C18 Pepmap column ( LC-Packings , http://www . dionex . com ) , they were introduced on line into a QSTAR XL instrument ( MDS-Sciex; Applied Biosystems , http://www . appliedbiosystems . com ) and were analyzed using data-dependent switching between MS and MS/MS modes . The ProID ( MDS-Sciex; Applied Biosystems ) program was used to interpret the LC-MS/MS data by searching against BuruList [48] . The search parameters were as follows: 1 ) 0 . 2-Da mass error tolerance for both MS and MS/MS; 2 ) one missed cleavage of trypsin specificity was allowed . Peptide matches with significant homology ( confidence score > 95 ) were considered as identified peptides . Proteins identified by a single peptide were validated by manual inspection of the MS/MS spectra . The Buruli Patients group consisted of 30 patients recruited from the Centre de Diagnostic et de Traitement de l'Ulcère de Buruli in Pobè , Benin , and were included in a sero-epidemiological study , for which written consent had been obtained [9] . Nine out of 30 patients presented early clinical signs without ulceration ( four nodules , two oedema , three plaques ) , ten patients with limited ulceration ( <6 cm ) , and 11 with extensive ulceration ( >10 cm ) . Diagnosis of M . ulcerans infection was by Ziehl–Neelsen staining of material taken from swabs of the lesions or directly from the biopsy for the early form and confirmed by PCR for M . ulcerans–specific IS2404 DNA [6] . The participants , who had given their written consent , were enrolled as volunteers in the study , the protocols of which were approved by the Ministry of Health in Benin . Serum was prepared from 8 ml of blood from each participant and tested for potential HCV and HIV exposure using Access HIV-1/2 automated immunoassay ( MDA/98/58 ) and Sanofi Diagnostics Pasteur Access anti-HCV automated immunoassay ( plus update on five other anti-HCV assays [MDA/96/26] ) . Proteins ( 10 μg ) from ECM , bacterial lysate , membrane , and cytosolic fractions were coated onto 96-well Nunc Maxisorb plates by incubation overnight at 4 °C in 100 μl of PBS containing Tween 80 0 . 05% . The coated plates were then incubated with PBS containing 5% skimmed milk at room temperature for 2 h . After three washes in PBS/Tween 80 , the samples were incubated for 1 h at 37 °C with human serum diluted 1:200 in PBS/Tween 80 . After three further washes , plate-bound human immunoglobulins were detected using peroxidase-conjugated goat anti-human IgG ( γ chain ) antibodies ( Sigma ) and OPD ( Dako , http://www . dako . com ) . The diluted sera were tested in triplicate and the average absorbance at 650 nm was expressed in optical density units . Proteins ( 60 μg ) from lysates or ECM fractions were run in an SDS–polyacrylamide gel ( 4%–12% ) ( Bio-Rad ) , and the separated bands were transferred onto a 0 . 45-μm nitrocellulose membrane ( Amersham ) . After blocking with 5% skimmed milk in PBS , the membrane was incubated with serum from humans diluted 1:100 in PBS containing Tween 80 0 . 05% for 90 min at 37 °C . After two washes with PBS containing Tween 80 , anti-human IgG ( γ chain ) peroxidase-conjugated antibodies ( Sigma ) at 1:2 , 000 and 0 . 5 μg/ml DAB ( Interchim ) was used , respectively , to detect human IgGs bound to the different bands . Bacteria were fixed in 2 . 5% ( w/v ) formaldehyde in PBS buffer and surface carbohydrates labeled with Texas red hydrazide ( Molecular Probes , http://probes . invitrogen . com ) or with calcofluor white M2R ( Sigma ) . Bacteria were then stained by DAPI , and labeled carbohydrates were visualized directly using a Zeiss Axioskop 20 fluorescence microscope and the AxioVisionLE 4 . 2 SP1 program ( http://www . zeiss . com ) used to perform the 3-D reconstruction . ECM obtained by treating bacteria with Tween 80 0 . 05% and glass beads was extracted by phase partitioning . The aqueous layer from the H2O/CHCl3/CH3OH partition was concentrated , the polymers precipitated overnight at 4 °C with six volumes of cold ethanol , and the precipitates collected by centrifugation at 14 , 000g for 1 h . The lipoarabinomannan content of this fraction was analyzed by SDS-PAGE and immunoblotting using the CS-35 antibody as described [49] . The interphase derived from the partition experiment was extracted three times with water before precipitating the polymers with ethanol and submitting them to acid hydrolysis in 2 M trifluoroacetic acid for 2 h at 120 °C . The monosaccharide constituents of this fraction were then analyzed by TLC , and their migration profile was compared to that of known standards . Total lipids from bacterial cells treated with Tween 80 0 . 05% , or untreated , were extracted as described [50] and analyzed by TLC on silica gel 60–precoated plates F254 ( Merck , http://www . merck . de ) . Extraction of mycolactone and cytotoxicity tests was performed according to George et al . [40] either using the bacterial pellet ( cells without ECM ) or ECM [13] . The carbohydrate content of the ECM material was measured by a colorimetric method [51] . Bone marrow–derived macrophages were obtained by seeding 105 bone marrow cells from 8-wk-old C57BL/6 mice per well in RPMI 1640 supplemented with 10% heat-inactivated fetal calf serum and 10% L-cell-conditioned medium . Culture medium was changed at day 4 and just before adding mycolactone at day 7 . HeLa cells and Cos cells ( American Type Culture Collection , http://www . atcc . org ) were cultured in Dulbecco's modified Eagle's medium supplemented with 10% heat-inactivated fetal calf serum . Proliferating cells were seeded in 96-well microtitration plates at a density of 105 cells/well , which were further incubated for 24 h at 37 °C under 5% CO2 in air before each assay . Various concentrations of vesicles or mycolactone in ethanol were added ( 2 μl/well ) . The mycolactone used as reference was purified as previously reported [12] . After 24 h incubation in the above conditions , cytotoxicity was then assessed by addition of 20 μl of dimethylthiazolyl diphenyl tetrazolium bromide solution ( MTT , Sigma ) ( 7 . 5 mg/mL ) to each well and further incubated for 4 h at 37 °C to allow the formation of formazan . Formazan crystals were then dissolved with 100 μl of 10 % SDS in 10 mM HCl . The optical density of each well was measured at 595 nm using a Multiwell plate reader . The values given are the average of two replicates and are representative of four independent experiments . The 50% inhibition concentration was determined by curve fitting . Adult N . cimicoides water bugs were collected and housed as described previously , then fed with grubs of Phormia terrae novae ( Verminière de l'Ouest , http://www . verminieredelouest . fr ) that had been inoculated beforehand with M . ulcerans , with or without ECM , in 30 μl by using a 25-gauge needle . Six hours after feeding , the insect hemolymph was collected with an insulin syringe [10] . Pooled hemolymph ( 100 μl ) was added to 100 μl of cold distilled water . The samples were washed three times by centrifugation ( 14 , 000g for 15 min ) in distilled water and resuspended in 50 μl of 50 mM NaOH and heated at 95 °C for 15 min . Real-time PCR was performed using brilliant SybrGreen Q PCR mix ( Stratagene , http://www . stratagene . com ) containing Taq polymerase , 2 . 5 mM MgCl2 , 100 μM ( each ) deoxynucleoside triphosphate and 20 pM primers . The primers were MLF ( 5'- CCCTTCGACGTCATCAAGAAA −3′ ) and MLR ( 5'- CCGACTGACCGATGAGCAA −3′ ) , leading to amplification of a 63-bp region of the mls genes [52] . After 15 min at 95 °C , the DNA was amplified by 30 cycles of 45 s at 95 °C; 1 min at 61 °C , and 45 s of elongation at 72 °C on an MX3000P apparatus ( Stratagene ) . The dissociation curve was performed between 55 °C and 95 °C . The MIC of rifampin and amikacin , inhibiting >99% of the bacteria , was determined as previously described [53] . To measure chlorine susceptibility , ∼108 bacteria , with or without ECM , were suspended in solutions containing a range of chlorine concentrations ( 20–200 mg per liter ) . After 60 min at 25 °C , residual chlorine was neutralized with sodium thiosulfate [54] and bacterial viability determined by inoculation onto Löwenstein–Jensen slants . Suspensions ( 30 μl ) containing 5 × 103 bacteria , with or without ECM , were injected subcutaneously into the tail of ten female Balb/c mice ( Charles River Laboratories , http://www . criver . com ) . Mice tails were examined weekly over 6 mo . The non-parametric Mann-Whitney U test was used for statistics . A p-value of < 0 . 05 was considered significant . | Mycobacterium ulcerans is the etiologic agent of Buruli ulcer , a necrotic skin disease affecting humans living close to wetlands in tropical countries . This mycobacteria resides in water where it could colonize many ecological niches such as aquatic plants , herbivorous animals , and water bugs . The latter were shown to be able to transmit the bacteria to mammalian hosts . Here , we described that the bacilli could be structured with a thick envelope called the extracellular matrix ( ECM ) . This peculiar coat contains in small vesicles a toxin named mycolactone , the main virulence factor of M . ulcerans . The ECM confers to the mycobacterium increased resistance to antimicrobial agents and plays a role in virulence . Indeed , a bacteria with ECM is more potent for colonization of insect vectors and mammalian hosts compared to bacteria . Unraveling the regulation of the production of the ECM together with the export of mycolactone will be an important step in developing new pharmacological approaches for the treatment of Buruli ulcer , which has been greatly handicapped by the lack of effectiveness of the current antibiotics . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [
"physiology",
"eubacteria"
] | 2007 | Impact of Mycobacterium ulcerans Biofilm on Transmissibility to Ecological Niches and Buruli Ulcer Pathogenesis |
In the roadmap on the neglected tropical diseases ( NTD ) the World Health Organization ( WHO ) aims at attaining at least 75% coverage of preventive chemotherapy in pre-school and school-age children by 2020 . A randomized controlled trial was used to compare the effectiveness of praziquantel in treating Schistosoma haematobium in Africa using two different sources for the drug , Merck Limited Partnership ( KgaA ) , Germany and Nanjing Pharmaceutical Factory ( NPF ) , China . More than 6 , 000 participants testing positive for S . haematobium infection were enrolled from three villages ( shehias ) situated in the northern , middle and southern part of Pemba Island , Zanzibar . Applying criteria of inclusion and exclusion , resulted in a study population of 152 people ( 84 males , 68 females ) . A randomized controlled trial was conducted assigning participants to either praziquantel from NPF or Merck KGaA . After one month , the cure rate of S . haematobium and adverse events were compared to evaluate effectiveness . The ratio of male to female , the ratio of light/high infection intensity , and the average value of age were calculated between the two drug manufacturers . Chi-squared test and T-test were used for consistency analysis . Out of the total of 73 cases receiving praziquantel from NPF , the cure rate achieved was 97 . 3% ( 73/75 ) , while the 74 cases receiving the drug from Merck KgaA reached a similar cure rate ( 96 . 1% or 74/77 ) . There was no significant difference between the two outcomes ( χ2 = 0 . 003 , P = 0 . 956 ) . Among the 75 patients treat , only one ( a 16-years old female student ) , who had received the drug made in China had slight adverse reactions manifested as dizziness , headache and abdominal pain . The efficacy of China-made praziquantel does not differ significantly from praziquantel made by Merck KGaA in Germany . ClinicalTrials . gov , NCT03133832
In tropical and subtropical regions , schistosomiasis remains as an important public health problem . It is estimated about 800 million people are at risk of schistosomiasis infection and more than 200 million people are constantly infected [1 , 2] . The trematode digenetic parasites in the family Schistosomatidae ( phylum Platyhelminthes ) infect a wide range of vertebrates . Five major species of the genus Schistosoma are major medical importance: Schistosoma mansoni , S . japonicum , S . haematobium , S . intercalatum and S . mekongi [3 , 4] . S . haematobium is distributed in different area of Africa including Zanzibar and the Middle East [5] where it infects the genito-urinary tract of humans causing urinary schistosomiasis , whose many complication include the bladder cancer [6 , 7] . Praziquantel is an anthelmintic drug whose complete principle of action remains to be unraveled , but it is known that a main effect is paralysis of the function of the worm's sucker[8–11] . It is highly effective and remains the drug of choice for the treatment of all forms of schistosomiasis infection [12] , and is also active against a broad range of parasitic helminths , including clonorchiasis , opisthorchiasis , tapeworm infections , cysticercosis and hydatid disease [13] . Although safe and generally without serious side effects , praziquantel can still cause poor coordination , abdominal pain , vomiting , headache and allergic reactions . While it may be used in women during pregnancy for the second trimester , it is not recommended for the mother when breastfeeding [14] . The strategy of WHO to eliminate schistosomiasis involves a large-scale treatment for affected populations through periodic , targeted treatment of school-children with praziquantel [15] . In 2008 , Merck KgaA , Darmstadt , Germany started a program donating 20 million tablets ( 600mg ) annually , which is still ongoing [16] . The increased use of the drug is attributable to many factors , including improved availability of donated praziquantel , essentially from Merck , which has led to some countries implementing large-scale schistosomiasis control programmes and scale-up of praziquantel treatment [17] . The global target of WHO in the roadmap on neglected tropical diseases ( NTD ) is to attain at least 75% coverage of preventive chemotherapy in pre-school and school-age children by 2020 [18] . Praziquantel has been used to treat schistosomiasis for a long time in China and the experience demonstrates that preventive chemotherapy ( i . e . , large-scale treatment without individual diagnosis ) with high coverage significantly impacts infection indices and even reduces transmission [19] . In 2014 , WHO signed a tripartite memorandum of understanding ( MOU ) with China and Zanzibar , paving the way for the start of a pilot schistosomiasis elimination programme in Zanzibar . The objectives are to control and eliminated schistosomiasis based on the experience of schistosomiasis control in China . The project on Pemba Island is China’s first aid project focusing on schistosomiasis control . The early stage of the project was to carry out schistosomiasis prevention and control work in three villages ( shihias ) , named Mtangani , Kiuyu and Wingwi , using snail control , population investigation and treatment [20–23] . In a follow-up step , we proposed an open-label , randomized trial to evaluate the comparative efficacy China-made praziquantel in the treatment people infected with S . haematobium in Africa . This paper describes this approach .
The field studies did not involve endangered or protected species . All subject enrollment has been signed the informed consent of this study . For all participants who were not adult , a parent or guardian provided informed consent on their behalf . The China-made praziquantel used was certified by the Zanzibar foods and Drugs Board ( ZFDB ) . The study was approved by the local government of Pemba Island . In addition , the Ethics Review Committee of Zanzibar approved all studies described here ( ZAMREC/002/MAY/014 ) . The trial was registered with ClinicalTrials . gov , number NCT03133832 . Zanzibar is composed of two sister islands , Unguja and Pemba , situated off the eastern coast of Tanzania mainland between latitudes 4 and 5 degrees South [24] . Zanzibar is endemic for schistosomiasis haematobium . The intermediate host is Bulinus globosus [25 , 26] . In 2011 , a survey of 24 schools showed that the infection in Unguja and Pemba rates were 8% ( 0–38% ) and 15% ( 1–43% ) , respectively [26] . A randomized controlled trial was used for this study [27] . Three shehias , Mtangani , Kiuyu and Wingwi , situated in northern , central and southern Pemba , respectively , were selected as study area . Three pilot areas proceeded schistosomiasis control in the early stages of assistance . A series of meetings was held at the shehias and their schools to explain the objectives , procedures , and potential risks of the study . More than 6 , 000 participants were originally enrolled for the study . Applying criteria of inclusion and exclusion ( see below ) , resulted in a final study population of 152 people ( 84 males , 68 females ) . People were enrolled randomly into two groups: group A received praziquantel ( batch number: 20170303 ) from Nanjing Pharmaceutical Factory Co Ltd ( NPF ) , Nanjing , China and group B received praziquantel ( batch number: M50812 ) from Merck Limited Partnership ( Merck KgaA ) , Darmstadt; Germany donated from WHO for the treatment of schistosomiasis in Africa . The dose was 40mg/kg body weight of drug given in a single oral dose according to the instructions of the manufacturers . The Merck KgaA praziquantel was larger than that made by NPF . Nothing less than half a tablet was given . Thus , if the fraction calculated ended up as an amount less than that , half a tablet was still given [28–30] . The staff of the NTD office , Ministry of Health , Zanzibar would instruct the drug distributers after confirming the treatment allocation from the randomization sequence that had been generated by computer . The NTD staff and participants was unmasked to the treatment assignment , but the laboratory technicians were masked to samples examination throughout the study . Inclusion criteria were the following: people permanently living on the island including residents and students of ages between 5 and 60 years who had been shown to be infected by S . haematobium as confirmed by urine test ( worm eggs detected ) . Exclusion criteria were the following: people refusing chemotherapy of praziquantel; women pregnant or lactating at the time of the study; people with serious adverse drug reactions; patients with severe heart , liver or kidney problems; those with a history of mental illness; and patients who for various reasons did not take medication on time . The NTD staff recorded the exact time of drug ingestion . Participants were observed for 2 hours after taking the drug to see adverse events and were continually observed at home by the assistance of local public health community center ( PHCU ) staff . They followed up on the medications every day to see adverse events . If anybody was vomiting within 2 hours of drug ingestion , a second dose was given . Urine was collected and tested in April 2017 . Every participant provided a fresh urine sample used to detect the presence of S . haematobium . The NTD staff subjected all potential participants to physical examination and eligibility check . We used a 10 ml syringe to extract 10 ml and filtered the urine , repeatedly shaking the cup to include eggs that that has a tendency to collect at the bottom . The filter device was prepared according to WHO recommendations with the filter taken out and placed on a glass slide before microscopy . Only participants found positive and otherwise meeting the criteria were included in the study . After one month , follow-up was conducted with urine were collected and tested in the same way again . Signs and symptom indicating adverse effects , inter-current illness or abdominal pain was recorded for the preceding month . Quality control measure was used for inter-observation variability , and technician retested a random selection of 10% of slides in the laboratory . At end of the study , all participants who still excreted S . haematobium eggs ( i . e . , who had not been cured ) were again treated with praziquantel . The primary outcome was a comparison of the cure rates after either having received praziquantel from NPF or Merck KgaA . The secondary outcome was the rate of severe adverse events . Serial report forms were used to collect the data from the participants . Epi Info ( Centers for Disease Control and Prevention ) , SPSS 20 . 0 ( International Business Machines Corporation ) and PASS 16 ( NCSS ) were used for data entry and analysis . The sample size was calculated by cross-sectional survey , 95% confidence interval ( CI ) ( Zα/2 = 1 . 96 ) , 5% margin of error and design effect of 2 . 5 . According to previous study , the infection rate of schistosomiasis in Pemba was about 6 . 0% and following the function of N=Z1−α/22 ( 1−p ) /ε2p [31] . Therefore , the sample size calculation formula required approximately 6 , 019 cases . The outcome of power was 0 . 99975 , which met the requirements . For the estimation of sample size in the early stage , we set the accuracy to 10% of the expected incidence rate to estimate the sample size . In this study , S . heamatobium infection intensity was determined as light ( 1–49 egg/10ml urine ) and heavy ( ≥50 eggs/10ml urine ) [32] . The ratio of male to female , the ratio of light infection intensity to heavy , and the average value of age was firstly calculated between the NPF and Merck KgaA praziquantel groups , Chi-squared test and T-test were used to analysis the consistency . A two-sided of Chi-squared test was used to compare the cure rate of positive and adverse reactions between different groups . The size of the test or α level was set to 5% , with 95% CI , with exact binomial estimates when necessary . The number of eggs and logarithmic transformation was in a skewed state , so the median value was used to analysis the change of infection intensity between the NPF and Merck KgaA praziquantel groups after praziquantel treatment .
A total of 6000 people were enrolled from three shehias in Pemba Island Zanzibar , Urine samples were collected and tested in April 2017 ( Fig 1 ) . According to the criteria of inclusion and exclusion , 152 people ( 84 males , 68 females ) were included consisting of 45 participants from Mtangani , 76 participants from Kiuyu and 31 participants from Wingwi . Participants were randomly assigned to study groups and in May 2017 , 75 people received NPF praziquantel ( males: 37 , females: 38 ) and 77 Merck KgaA praziquantel ( males: 47 , females: 30 ) ( Table 1 ) . There was no significant difference of age in the two groups ( t = -0 . 424 , P = 0 . 672 ) with a median of 14 for both Merck KGaA and NPF . There was no significant difference of the number of eggs in the two groups ( t = -1 . 130 , P = 0 . 261 ) with the median value in Merck KGaA and NPF 8 and 9 , respectively . There was good consistency with respect to age and gender for S . haematobium infection and intensity between the two groups . Seventy-three of the 75 cases receiving the NPF praziquantel were all negative translating into a cure rate of 97 . 3% . With regard to the Merck KgaA praziquantel , treatment the cure rate was 96 . 1% ( 74/77 ) . There was no significant difference in the cure rate between the two groups ( χ2 = 0 . 003 , P = 0 . 956 ) . In Mtangani , 20 were people tested negative out of the 21 who had received the NPF praziquantel ( cure rate = 95 . 2% ) , while 21 of the 24 receiving the Merck KgaA praziquantel were cured translating into a rate = 87 . 5% . There was no statistically significant difference ( χ2 = 0 . 038 , P = 0 . 845 ) . In Wingwi , 16 patients received praziquantel from NPF and 15 were negative ( cure rate = 93 . 8% ) . With regard to Merck KgaA praziquantel , all 15 treated patients were negative , so the cure rate was 100 . 0% . Also here , there was no statistical significant differences between the two groups ( χ2 = 0 . 016 , P = 0 . 900 ) . In Kiuyu , finally , there were 38 people in both groups and they were all cured , so the cure rate was again 100 . 0% in two groups . As seen in Tables 2 and 3 , there was no statistical difference with respect to gender ( male: χ2 = 0 . 027 , P = 0 . 869; female: χ2 = 0 . 001 , P = 0 . 977 ) or the degree of infection ( light: χ2 = 0 . 0003 , P = 0 . 986; heavy: χ2 = 0 . 001 , P = 0 . 973 ) . One month after treatment , only two cases were found in the NPF group; the number of eggs was 1 and 6 , respectively , while three cases appeared in the Merck KGaA group with 3 , 12 and 20 eggs , respectively . The final egg reduction rate was thus 99 . 8% ( 4285/4292 ) in the NPF group and 98 . 7% ( 2620/2655 ) in the Merck KGaA group . The side effects included dizziness , headache , nausea , anorexia , abdominal pain , diarrhea , vomiting , body weakness , cough , itchy skin and skin rash . Among the 152 patients , only one 16-year old female student experienced slight adverse reactions , manifested as dizziness and headache of receiving the NPF product . No other adverse effects occurred .
Praziquantel is a heterocyclic isoquinolinazine derivative synthesized in 1972 by the two firms E . Merck and Bayer Pharmaceuticals [33] . Outside Germany , the drug was first synthesized by Shin Poong PharmaceuticaL Co . in South Korea and in 1977 also in a Chinese company in 1977 and subsequently was used in clinical practice there in 1978 . Due to a high curative effect , low side effects and high safety , praziquantel is not only used for clinical treatment on a large scale of various stages of schistosomiasis in China , but also used for prevention of schistosomiasis [34 , 35] . Although S . haematobium is widespread in Africa , no large amounts of China-made praziquantel made by NPF has been used on a large scale . Most praziquantel used in Africa comes is from Merck KgaA through the WHO donation mentioned above [36–38] . However , the actual demand over the last 5 years was about 400 million tablets , which above what can be met by the donation . It is thus important to find another source of effective praziquantel that is not expensive [16 , 39 , 40] . This study investigated the feasibility of China-made praziquantel to complement what is currently available . Non-inferiority margins limit the allowable range of clinically acceptable medicines and comparator drugs . From the perspective of clinical efficacy , and against the background of previous test results , it must be repeatedly demonstrated that a drug is superior to these margins . Sometimes , a cost-benefit analysis may be necessary . However , this study did not investigate the efficacy of praziquantel per se , but used traditional statistical methods to compare the differences in efficacy between the two products to prove the possibility of using Chinese praziquantel for the treatment and prevention of schistosomiasis haematobium . For non-inferiority margins , relevant studies will be conducted again in the future . This study may be limited in that the design of testing only relatively few people from three shehias . However , this was done to serve as a reflection of the overall situation on Pemba Island . The studies proved to be a strong indication there was no difference between the NPF praziquantel and that made by Merck KgaA . There was also no stratified study of Shehias in this study . In the results , the cure rates of different shehias were compared , and then the overall cure rates were compared , just to observe whether there were statistical differences in different shehias , and then make an overall comparison . In terms of drug prices , China-made praziquantel prices are cheaper , which is conducive to large-scale application in Africa [41–44] . Although praziquantel is effective in the treatment of schistosomiasis , side effects have been reported clinically and in the field [45 , 46] . We recorded only one adverse effect , which could be due to differences in drug manufacture [47] . However , this occurrence was to minor , and a large-scale trail would be needed to rule this out or put it on a better footing . The fact that the common side effects , mainly reactions from the neuromuscular , digestive , or cardiovascular system sometimes due to allergy , are generally light and disappear in a short time , makes a comparison difficult without reverting to large-scale trails . Even severe reactions may occur in individual cases , such as syncope , ataxia , angina pectoris and severe arrhythmia , might be easier to record but they are very rare [48] . Finally , what makes the study of side effects difficult is that they may be related to the dose , route , time , dosage form , physical properties of the drug , and individual differences in the drug administration [33 , 49 , 50] . Through studying of other researches , China-made praziquantel had also good effectiveness to treat schistosomiasis haematobium [51] . There were some confounding factors , such as re-infection after treatment . Since only 152 positive patients were collected in the first year of the project , the sample size may not be sufficiently large to study that . On the other hand , with one month period after treatment , there is hardly time for new infections to reach the maturity needed to produce eggs . There was no equivalence study , so in this study we used a traditional comparison of two drugs to prove the possibility of China-made praziquantel treatment of schistosomiasis . In conclusion , this study indicates that China-made praziquantel has good efficacy and minor side effects . China-made praziquantel can be used to treat S . haematobium infections in Africa on a large scale . | Schistosomiasis is a neglected tropical disease ( NTD ) with praziquantel the only effective drug available . It is estimated that about 800 million people are currently at risk for this disease with more than 200 million people infected . A large drug donation partnership between Merck , Darmstadt , Germany and the World Health Organization supports widespread , successful preventive chemotherapy programs , but the donated drugs does not meet the entire need , particularly not in Africa . The primary aim of our study was to evaluate the efficacy of China-made praziquantel to explore whether the drug could complement preventive chemotherapy programs in Africa . A randomized controlled trial was conducted assigning participants to two groups , one receiving praziquantel from NPF , the other from Merck KGaA . After one month , the cure rate of S . haematobium and were compared to evaluate effectiveness and document potential adverse events . The outcome showed that the two sources of praziquantel that did not differ significantly from each other . China-made praziquantel can thus be trusted to complement the current use of the drug from Merck KGaA in Africa making it possible to enlarge drug provision programs . | [
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] | [] | 2019 | Efficacy of China-made praziquantel for treatment of Schistosomiasis haematobium in Africa: A randomized controlled trial |
In schizophrenia , increased aberrant salience to irrelevant events and reduced learning of relevant information may relate to an underlying deficit in relevance detection . So far , subjective estimates of relevance have not been probed in schizophrenia patients . The mechanisms underlying belief formation about relevance and their translation into decisions are unclear . Using novel computational methods , we investigated relevance detection during implicit learning in 42 schizophrenia patients and 42 healthy individuals . Participants underwent functional magnetic resonance imaging while detecting the outcomes in a learning task . These were preceded by cues differing in color and shape , which were either relevant or irrelevant for outcome prediction . We provided a novel definition of relevance based on Bayesian precision and modeled reaction times as a function of relevance weighted unsigned prediction errors ( UPE ) . For aberrant salience , we assessed responses to subjectively irrelevant cue manifestations . Participants learned the contingencies and slowed down their responses following unexpected events . Model selection revealed that individuals inferred the relevance of cue features and used it for behavioral adaption to the relevant cue feature . Relevance weighted UPEs correlated with dorsal anterior cingulate cortex activation and hippocampus deactivation . In patients , the aberrant salience bias to subjectively task-irrelevant information was increased and correlated with decreased striatal UPE activation and increased negative symptoms . This study shows that relevance estimates based on Bayesian precision can be inferred from observed behavior . This underscores the importance of relevance detection as an underlying mechanism for behavioral adaptation in complex environments and enhances the understanding of aberrant salience in schizophrenia .
Reduced differentiation between relevance and irrelevance , a disruption of salience attribution , is the key component of the aberrant salience hypothesis of psychosis [1–3] . According to this theoretical framework , neurobiological noise in terms of increased striatal dopamine turnover may cause the subjective experience of salience or meaningfulness in the absence of relevant contextual events that usually cause dopaminergic saliency signaling . This experience of aberrant salience is then attributed to random , irrelevant events that coincide with it and , thus , these irrelevant events turn subjectively meaningful . At the same time , chaotic aberrant salience signaling was proposed to blur the signal-to-noise ratio leading to decreased processing of contextually relevant events and the formation and maintenance of negative symptoms [4 , 5] . This salience framework clearly renders the objective experimental measurement of ( aberrant ) salience challenging and highlights the subjective nature of relevance and salience attribution . This subjectivity aspect can be captured by modeling latent learning processes of individuals , which is a common approach for describing the processing of relevant information , for example , during reinforcement learning [6 , 7] . However , while computational modeling has already revealed decreased learning from task relevant events in schizophrenia patients [4] , this approach has not been applied to learning from relevant compared to irrelevant stimuli , which might shed further light on aberrant salience attribution . Both constructs , relevance and salience , are closely intertwined . In general , cues can be considered salient based on their physical characteristics , or cues are subjectively salient when they have been learned to be relevant in a certain context . For instance , neutral cues that are learned to predict reward can turn subjectively salient . Here , we define salient cues as those that have been learned to reliably predict important outcomes . These associations between cues and outcomes are learned via prediction error ( PE ) signals that code the surprise and unexpectedness of events; or computationally , the difference between observation and prediction . Thus , an unexpected event elicits a large unsigned prediction error ( PE; a directed PE would carry information about the valence/reward ) and the corresponding event would turn salient to the individual . Prediction errors are used to update the predictive value ( belief ) of the preceding stimulus . On the neural level , unexpectedness correlates with brain responses in the so-called salience network [8–11]; such as the ( dorsal ) anterior cingulate cortex and the insula [8 , 12–16] , while some studies also reported unsigned PE signaling in the striatum [for a review see 17] . In multidimensional environments , multiple cues are potentially important and individuals have to adapt to relevant cues that have proven to be reliable or precise predictors . A cue is precise when it announces a specific event with a high probability . Correspondingly , irrelevant cues that are experienced to be noisy and unreliable ( = uncertain ) should be dismissed . This was investigated by recent learning studies using multisensory cues [18–20] where subjects were either instructed to find out the relevant cue feature or were told which information they had to focus on in order to achieve the task of choosing the correct stimulus for reward maximization . While applying computational modeling , these studies provided behavioral and neural evidence for learning from multiple sources of information by integrating these according to their respective subjective relevance . According to the principles of Bayesian learning [21–23] , as incorporated in the Hierarchical Gaussian filter [HGF; 24] , Bayesian precision reflects the computational mechanism capturing the reliability of a stimulus . We use precision as our definition of subjective ( in the sense of learned ) relevance in multidimensional environments . Furthermore , we probe the influence of this subjective relevance on prediction errors , i . e . when the subject knows that the environment is irrelevant he/she should no longer experience a large prediction error as salient . In line with this approach , a theoretical account proposed that aberrant precision coding underlies psychosis formation [5 , 25–27] . In schizophrenia and presumably due to chaotic dopaminergic signaling , the detection of task relevant cues seems to be disturbed while irrelevant cues not carrying reliable information can gain high subjective salience [1 , 2 , 28] . This latter phenomenon of aberrant salience describes the subjective experience of patients characterized by random stimuli suddenly standing out and turning meaningful . According to the hypothesis , patients make sense of this aberrant salience experience by forming cognitive schemes that on the long run turn into delusional beliefs . However , though the aberrant salience concept offers high descriptive value and plausibility regarding clinical symptoms the behavioral quantification in experimental settings still remains challenging . So far , conclusions about increased aberrant salience attribution has been drawn from two kinds of findings both related to reinforcement learning: ( 1 ) heightened responses to cues that predicted ( affectively ) neutral outcomes and ( 2 ) increased responses to irrelevant , i . e . unreliable cues . Regarding the first operationalization , blunted differentiation between cues indicating either reinforcement or neutral outcomes were consistently found in schizophrenia patients . Whereas healthy individuals displayed enhanced responses to the reinforced over neutral cues , patients displayed the opposite pattern; increased responses ( reaction times , skin conductance as well as midbrain and striatal BOLD responses ) to stimuli that were followed by neutral outcomes [29–32] . With regard to the second operationalization , aberrant salience may further be reflected in a tendency or bias towards one over another equally irrelevant stimulus , as defined in the Salience Attribution Test [SAT; 33] . In the SAT , subjects have to speed up their responses to a target to increase their wins . Crucially , the target is preceded by conditioned stimuli with one feature being reliably informative about the following reward ( instrumental motivational salience ) and another feature being uninformative for predicting reward; being therefore relevant or irrelevant . Here , aberrant salience is reflected by the idiosyncratic bias inside the irrelevant dimension . This quantification of aberrant salience to irrelevant instead of neutral events circumvents instrumental learning deficits reported in schizophrenia [6] . So far , it has revealed mixed results in schizophrenia patients possibly pointing to differential expressions of aberrant salience across the stages of illness . The explicit ( = subjective judgment based ) aberrant salience measure was increased in first episode patients with delusions and individuals at ultra-high risk for psychosis [33–35] and striatal responses to irrelevant events correlated with positive symptoms [34] . The implicit ( = reaction time based ) aberrant salience measure was increased in a medicated and rather chronic schizophrenia patients sample [36] . However , other studies using the SAT in patients only found deficits in adaptive salience [37 , 38] . In a previous study [39] , we found that this idiosyncratic bias inside the irrelevant cue feature does not interfere with adaptive salience attribution that is needed to successfully solve the task . Hypothetically , this may imply that when schizophrenia patients are confronted with cues that are not associated with task-information and that are therefore imprecise they form a bias towards one of these cues in order to resolve this uncertainty . In other words , cues that are irrelevant within a particular ( task ) framework and that thereby are unreliable in serving instrumental aims may be inherently prone to capture aberrant salience . Thus , explicit task demands should be low in order to create an atmosphere where aberrant salience attribution can arise . A rather implicit task design would further reduce confounds by motivational , cognitive and stress-related deficits known in schizophrenia patients [40–43] . The aim of the current study was to test the idea of aberrant salience as an idiosyncratic bias to subjectively unreliable and thus task-irrelevant information . For that , we used computational modeling in order to assess relevance attribution on the subjective level . While we followed the idea of the SAT of having relevant and irrelevant cue dimensions , we used a more dynamic task design including contingency reversals in order to achieve ongoing learning that is better suited for computational modeling . Further , participants were not instructed to explicitly track contingencies between cues and outcomes in order to keep task demands low . In the current study , 42 schizophrenia patients and 42 healthy individuals performed an implicit salience paradigm during fMRI [ISP; 39] . In this paradigm , participants had to discriminate between two outcomes ( coin/circle ) via button press . The outcome could be predicted from preceding graphic cues with dynamically changing contingencies along two distinct features ( color and shape ) . By applying the Bayesian learning framework of the HGF , we used computational modeling to assess individual learning trajectories of these associations . Subjective relevance was formalized as Bayesian precision ( as a dynamic reliability measure ) and we compared different models , which varied in how subjective relevance affected learning and behavior . We hypothesized that participants would be more surprised by unexpected events and slow down their responses . On the computational level , this was defined via relevance weighted UPEs and we expected their neural correlates to be located in areas previously implicated in salience processing network and/or the striatum . Further , we defined aberrant salience as an idiosyncratic bias towards one unreliable and thus subjectively irrelevant cue feature . We hypothesized that this measure of aberrant salience would be increased in schizophrenia patients .
All participants gave written informed consent and received monetary compensation as well as the total wins of the task battery . The study was performed in accordance with the Declaration of Helsinki and was approved by the local ethics committee of Charité Universitätsmedizin . In total , 42 schizophrenia patients and a matched healthy control group of 42 individuals participated in this study . Healthy individuals reported no past or present psychiatric disorder according to the SKID-I . Patients were diagnosed with schizophrenia according to the DSM-IV and ICD-10 . Psychopathology was assessed using the Positive and Negative Syndrome Scale ( PANSS ) as well as the subscale for delusions and anhedonia of the Scale for the Assessment of Positive ( SAPS ) and Negative Symptoms ( SANS ) , respectively ( for information on demographics and psychopathology , see Table 1 ) . All patients were on antipsychotic medication ( for more details , see Table A in the Supplement ) . They were recruited from the inpatient and outpatient units of the Department of Psychiatry and Psychotherapy , Charité-Universitätsmedizin Berlin and the Psychiatric Department of the Schlossparkklinik Berlin . Aberrant salience raw data scores of a partially overlapping sample ( 37 healthy controls and 34 schizophrenia patients ) were reported in a previous publication [39] . This paradigm was explicitly instructed like a target-detection task though implicitly being a learning paradigm where features of neutral stimuli predicted certain outcomes . It consisted of 160 trials where subjects were told to discriminate the outcomes ( 10 Eurocent coin or blue circle ) of each trial . Therefore , their only task was to press a respective button when they saw a coin , versus another button when they saw the blue circle . Subjects were told that they would receive the amount of money they had seen during the task irrespective of whether they had pressed a button or not , though they were encouraged by the experimenters not to miss too many trials because this would impede the analysis . The outcomes were preceded by conditioned stimuli that differed in color and shape: gray or colorful squares or triangles ( see Fig 1A and 1B ) . During the instructions , subjects were told not to pay attention to these stimuli preceding the outcomes . However , prior to scanning , participants were primed with the stimulus features while they were asked to name the color and the shape of each of the four conditioned stimuli . Then , they practiced the outcome detection for 10 trials . In this practice session , all outcomes were preceded by a stimulus that was not presented during the main experiment in the scanner . In the main experiment , the conditioned stimuli predicted the outcome types in a probabilistic manner that reversed during the task . Importantly , only one stimulus feature reliably predicted the outcome ( eg , shape ) . For instance , 80% of all triangles were followed by the coin ( 20% circle ) , and 80% of all squares were followed by the blue circle ( 20% coin ) . Whether the square or the triangle predicted the coin reversed every 20 trials . In the meantime , the color of the stimuli was irrelevant in predicting the outcome; colorful and gray stimuli were equally followed by coins and circles ( 50% each ) . After the first half of the experiment this was reversed , and then the formerly irrelevant feature ( here: shape ) predicted the outcome , whereas the other feature turned irrelevant ( see Fig 2 ) . The relevant dimensions were counterbalanced across participants and coins and neutral outcomes were each displayed in 50% of all trials . In total , the experiment lasted 15 minutes and took place during fMRI scanning . Participants received the amount of coins seen in the experiment ( 8 Euro ) . In our raw data analysis of reaction times , we focused on two aspects: ( i ) learning of the regularly reversing relevant feature and ( ii ) aberrant salience towards one manifestation of the irrelevant feature . Extreme reaction times ( <150 ms and >1 . 5 s ) were excluded . For analyses of potential learning , reaction times ( in ms ) were log transformed to achieve normal distribution required for variance analyses . First , we tested whether subjects learned the cue-outcome contingencies and slowed down their responses if the outcome could not be predicted based on the preceding cues and thus violated their expectation . For that , log reaction times were compared for expected ( i . e . trials when the 0 . 8 rewarded feature was followed by reward and trials when the 0 . 8 non-rewarded feature was followed by a circle ) versus unexpected events ( i . e . trials when the 0 . 8 rewarded feature was followed by the circle and trials when the 0 . 8 non-rewarded feature was followed by a coin ) of the relevant condition in a repeated-measures ANOVA with group as between-subject factor ( HC versus patients ) and event type as within factor ( expected versus unexpected ) . Second , a change in reaction times over time following contingency changes inside the relevant cue feature was tested using a repeated-measures ANOVA . For all eight blocks with 20 trials each , log-reaction times of the 16 expected events ( ie , spanning those 8 trials when the rewarded feature was followed by reward and the 8 trials when the non-rewarded feature was followed by a circle ) were grouped for rewarded versus neutral outcome trials ( Condition factor ) and combined into 4 time bins each , consisting of 2 consecutive trials ( Time factor ) . For analyses targeting responses with regard to different cue features , please see the Supplement . For aberrant salience attribution , aberrant salience scores were calculated as in the previous literature [39] , and reflected an individual bias towards one of the two irrelevant cue manifestations based on the ground truth contingencies . For that , the mean reaction times ( in ms ) to each of the four cue features when they were irrelevant to the task were calculated . Then , aberrant salience was calculated as the absolute difference in reaction times between both manifestations of each condition ( eg , square over triangle when shape is irrelevant ) . Then , these two scores were collapsed across test halves . We used detailed computational modeling combined with model selection in order to assess the learning mechanisms driving the observed individual behavior . By that we tested if subjects learned the underlying cue-outcome associations and inferred the relevant cue feature . In keeping with our initial definition of relevance , a cue feature should be perceived as more relevant the more precisely it is believed to predict the outcome . In contrast , if the association between cue feature and outcome is very noisy , because the occurrence of reward and circle are equally probable this feature should be perceived as irrelevant . We set up novel response models that postulated slowing down of responses when the expectations were violated . Computationally , a violation was captured by the unsigned PE of each feature . In different models , we compared if unsigned PEs of the different cue features differentially affected behavior based on their current relevance . By the relevance weighted PE , we implemented increased adaptation to surprising events ( unsigned PE ) predicted by the most relevant cue feature as well as decreased adaptation to the irrelevant cue feature . Thereby , we tested if individuals adapted their behavior less to events when these had proven to be noisy and uninformative in the past . Instead , they would adapt their behavior to those unexpected events that were held to be informative because these may actually signal a real change in the environment ( as the contingency changes in our task ) . Our modeling analysis was guided by two aims: We modeled predictions for each of the two cue features , shape and color , in separate HGF learning models so that a trial-by-trial expectation was computed for each feature ( learning model ) . We did not model relevant and irrelevant conditions separately because of two reasons . First , the generative model was supposed to capture the subjects’ learning experience and they were not instructed about the task structure having relevant and irrelevant conditions . Instead they were only primed with the distinction by feature , color and shape , in the practice session . Second , after the first half of the experiment we switched the relevant dimension ( e . g . shape to color ) . Hence , modeling separately for relevance versus irrelevance would have introduced external information on the task structure that was not accessible to subjects and thus not generative . The resulting learning trajectories for shape and color were transformed into trial-by-trial predictors of reaction times ( response model ) . According to the ‘Bayesian brain’ hypothesis [21–23 , 46] , an agent forms a generative model of the world in part by increasing the precision of predictions ( μ ) to successfully adapt one’s behavior . The HGF offers a generic framework for Bayesian learning on multiple hierarchical levels . Crucially , the belief update at each level is comprised of a lower-level prediction error δi-1 ( k ) that is weighted according to a cross-level precision ratio ( Eqs 1 and 2; i for learning level , and k for trial number ) . The precision of each level’s prediction π^i ( k ) =1/σ^i ( k ) is defined as the inverse variance of the prediction . We used a “two branches” version of the HGF for parallel learning of the shape and color associations with the outcome . In our modelling , we focused on the reliability and thus undirected beliefs about associations . Thus , the direction of the learning trajectories ( association beliefs μ^1 ( k ) and prediction errors δ ) did not reflect the reward value but an arbitrarily determined relationship between cue feature manifestations and outcomes . A more detailed description of the HGF and its levels can be found in the Supplement . Since the core aim of this study was the dissociation between learning about relevant versus irrelevant cue features , the term relevance needs to be defined formally . In terms of the ISP , a cue feature should be perceived as more relevant the more precisely it is believed to predict the outcome . In contrast , if the belief μ^1 ( k ) of an association is 0 . 5 it should be perceived as irrelevant for outcome prediction ( because in this case reward and circle will occur with the same probability and cannot be reliably predicted ) . In the HGF framework , this interpretation of relevance is reflected in the estimated precision of prediction on the first level π^1 ( k ) ( see 4 ) . It is a function only of the first-level association prediction μ^1 ( k ) , which ranges between 0 and 1 . π^1 ( k ) has a minimum of 4 for μ^1 ( k ) =0 . 5 and increases symmetrically to infinity as μ^1 ( k ) approaches 0 or 1 . This relevance could affect how beliefs are updated ( for this implementation ( ‘precision feedback’ ) , see the Supplement ) and/or how learning signals affect behavior , which we implemented in four response models . Our learning model space contained 2-level and 3-level HGFs with and without precision feedback ( see Supplement ) , leading to four different hierarchical learning models: 2HGF , 2HGFprecfb , 3HGF , and 3HGFprecfb . Prediction errors relating to the cue feature that is thought to be more relevant might translate more strongly into reaction times , and the aberrant salience effect found in the raw data may be explained as a bias towards one of the irrelevant features on a trial-by-trial basis . Both aspects were formalized in the following four response models . The baseline response model ( see Eq 4 ) postulates that trial-by-trial reaction times are a linear function of the mean of the prediction errors of both features ( 4 . 1 . 1 ) , a constant bias towards one feature manifestation ( eg , triangles over squares ) and the outcome ( eg , slower for circles than for coin trials; 4 . 2 . 1 ) . The four cue manifestation vectors m reflect whether the respective manifestations were displayed for every trial ( eg , 1 for triangles and 0 for squares in mtriangle ) . This response model was modified in three ways . In a first modification ( 4 . 1 . 2 ) , the absolute prediction errors of each feature were weighted according to their respective relevance weight ( rel; 5 ) . The latter is formalized as the relative amount of each feature’s precision given the overall precisions of both features . In a second modification and in line with the aberrant salience effect , the constant bias was weighted according to its feature’s irrelevance ( irrel; see Eq 4 . 2 . 2 ) . The irrelevance weight of one feature was defined as the relevance weight of the opposing feature ( see Eq 5 ) . From the four cue feature parameters ( β2 , … , β5 ) one composite parameter was calculated in two steps . First , the individual absolute differences between the β2 and β3 for irrelevance weighted manifestations within color ( and between the β4 and β5 for shape manifestations ) were calculated . Then , they were collapsed across color and shape to achieve one parameter βirrelevance capturing the bias towards one cue feature manifestation that increased with subjective irrelevance . Thus , we compared four different response models: the baseline model ( Eq 4 ) , the baseline model with relevance weighted absolute prediction errors ( Eq 4 with modification term 4 . 1 . 2; RelPE ) , the baseline model with only the irrelevance bias ( Eq 4 with modification term 4 . 2 . 2; IrrelBias ) , and a full model with both modifications ( Eq 4 with modification terms 4 . 1 . 2 and 4 . 2 . 2; RelPE+IrrelBias ) . This led to a total model space of 16 model combinations ( see Figure S1 ) . All models were fitted using the HGF toolbox 4 . 15 [24 , 45] as part of TNU Algorithms for Psychiatry-Advancing Science ( TAPAS , http://www . translationalneuromodeling . org/tapas/ ) . For optimization , a quasi-Newton optimization algorithm was applied . We used random-effects Bayesian Model Selection [BMS , spm_BMS in SPM12 , www . fil . ion . ucl . uk/spm; 47] for each subject’s and each model’s negative free energy ( as an approximation to log-model evidence ) in order to identify which of the competing models best explained the subjects’ response time data . BMS takes into account accuracy of each model and also penalizes for complexity . It accounts for heterogeneity across subjects and treats each model as a random variable in the population . We report protected exceedance probabilities for each model ( PXP ) and posterior probabilities ( PP ) as well as exceedance probabilities ( XP ) for model families ( HGF vs . HGFprecfb; 2HGF vs . 3HGF; BL vs . RelPE vs . IrrelBias vs . RelPE+IrrelBias ) . The XP describes the relative probability that the model would better replicate the data in comparison with the other models . The PXP that governed our model selection protects against the ‘null’ possibility that there are no differences in the likelihood of models across the population . Based on the estimated individual parameters from the best-fitting model , we simulated trial-by-trial reaction time data . In addition to the Bayesian model comparison , we tested the model’s credibility by carrying out the same analyses as in the raw data section on the simulated data ( ( 1 ) Expectedness*Group ANOVA , ( 2 ) Condition*Time*Group ANOVA , ( 3 ) ‘ground truth’ aberrant salience group differences ) . Using this approach , we checked whether the model was capable of reproducing the meaningful effects and group differences that were evident in the data . For single and group statistics , an event-related analysis was applied using the general linear model ( GLM ) approach as implemented in SPM12 ( http://www . fil . ion . ucl . ac . uk/spm/software/spm12/ ) . On the single subject level , the outcome onsets were convolved with the hemodynamic response function and its temporal derivative . As parametric modulator , the mean of the relevance weighted absolute prediction errors of the best fitting model ( 2HGF-RelPe+IrrelBias ) was introduced , representing how unexpected and salient the observed outcome was based on the subjects’ learned expectations about the two cue features . Regressors of no interest were no response trials , trials with reaction times>1 . 5 seconds and <150 milliseconds , realignment parameters with their first temporal derivative of translational movement , and one regressor for scans with >1mm scan-to-scan movement . For random effects group-level analysis , the individual contrast images for mean relevance weighted PEs were used in a two-sample t-test for between-group comparisons ( controls vs . patients ) . Explorative analysis probed the association between model parameter βirrelevance and neural relevance weighted PE signals in schizophrenia patients . Hence , interindividual βirrelevance scores were introduced as a covariate in a one-sample t-test using the Mean relevance weighted PE contrast . Results are reported using FWE correction at the voxel level across the whole brain . Based on our hypothesis concerning activations in areas previously shown to code salience such as the ACC and insula , namely the so-called salience network [8–11] , and the nucleus accumbens , we applied small volume correction at the voxel level for the respective bilateral anatomical masks derived from the WFU PickAtlas ( http://fmri . wfubmc . edu/software/pickatlas ) . Thus , three VOIs were used for small volume correction at pFWE<0 . 05 and we indicate which results survive Bonferroni correction for three tests .
Participants displayed increased log reaction times observed for probabilistic ( unexpected ) events compared to non-probabilistic ( expected ) events ( Main effect of event type: F ( 1 , 82 ) = 5 . 9 , p = 0 . 018 , interaction event type*group F ( 1 , 82 ) = 0 . 02 , p>0 . 8 ) . The Reward*Time*Group ANOVA revealed that reaction times differed significantly between coin and circle ( main effect Condition: F ( 1 , 82 ) = 22 . 78 , p < . 001 , see Fig 1C ) and showed a trend-wise decrease following a reversal ( main effect Time: F ( 3 , 246 ) = 2 . 6 , p = . 053 ) . Participants took around 8 trials to decrease their reaction times after slowing down following a reversal in contingencies ( RT difference first time bin ( trials 1–4 ) vs . third time bin ( trials 8–12 ) , t = 2 . 72 , p = 0 . 048 , Bonferroni corrected ) . Groups did not significantly differ in their reaction times ( main effect of Group p> . 2 ) . The aberrant salience scores calculated based on the ground truth contingencies differed significantly from zero in both groups ( mean ( SD ) for HC = 17 . 98 ( 10 . 88 ) , t ( 41 ) = 10 . 7 , p < . 001; for Sz = 22 . 95 ( 14 . 46 ) , t ( 41 ) = 10 . 3 , p < . 001 ) . Schizophrenia patients displayed increased aberrant salience scores compared to healthy individuals ( Welch’s F ( 1 , 76 . 156 ) = 3 . 2 , p = 0 . 04 , one-tailed based on our a priori hypothesis ) . Across all subjects , the two-level HGF with the full response model was the best fitting model ( PP = 0 . 3755; PXP = 0 . 5155; see Table 2 ) . Among learning models there was clear evidence against the precision feedback model ( PPHGF = . 968; PPHGFprecfb = . 032; exceedance probability XPHGF = 1 ) , while there was only a very subtle advantage for two-level compared to three-level models ( PP2HGF = . 551; PP3HGF = . 449; XP2HGF = . 551; XP3HGF = . 449 ) . Concerning the response models , the full response model using the mean relevance weighted prediction error and the irrelevance weighted bias clearly explained the data best ( PPBL = . 015; PPirrelBias = . 037; PPrelPE = . 017; PPrelPE+irrelBias = . 93; XPrelPE+irrelBias = 1 ) . Therefore , we decided to do our fMRI analyses with the 2HGF model and the best response model relPE+irrelBias . We repeated the same analyses as for the raw reaction time data for the simulated log RTs based on the best fitting model . The ANOVAs revealed similar behavioral effects: faster responses for expected than for unexpected events ( F ( 1 , 82 ) = 296 . 8 , p < . 001 ) , faster responses for coins than for circles ( F ( 1 , 82 ) = 118 . 4 , p < . 001 ) , as well as faster reaction times across time bins ( F ( 1 . 6 , 133 . 3 ) = 216 . 3 , p < . 001; see Fig 1C ) . The aberrant salience difference score was again significantly increased in schizophrenia patients ( Mean = 14 . 4 , SD = 8 . 2 ) compared to healthy individuals ( Mean = 10 . 2 , SD = 5 . 9 ) ( Welch’s F ( 1 , 74 . 6 ) = 7 . 2 , p = . 009 ) and correlated with the aberrant salience score from the raw data ( Pearson’s r = 0 . 637 , p<0 . 001 ) . In line with that , βirrelevance reflecting the model based subjective bias towards irrelevant events differed significantly from zero in both groups ( HC: t ( 41 ) = 12 . 6 , p<0 . 001; Sz: t ( 41 ) = 12 . 1 , p<0 . 001 ) and correlated with the aberrant salience difference score from the raw data analysis ( HC: ρ = 0 . 523 , p<0 . 001; Sz: ρ = 0 . 612 , p<0 . 001 ) . We tested for group differences on three individual response parameters that weighted the influence of the relevance weighted prediction error ( β1 ) , the outcome ( β6 ) , and the irrelevance bias ( βirrelevance ) on reaction times . Schizophrenia patients showed an increased bias towards one of two equally irrelevant cue features as indicated by increased βirrelevance values ( t ( 74 . 2 ) = 2 . 7 , p = 0 . 036 , corrected for multiple comparisons , see Fig 3 ) . Both groups did not differ on β1 and β6 ( p>0 . 7 ) . For all fitted model parameters , see Table 3 . In an explorative approach , we investigated how the response model parameter βirrelevance related to psychopathology using Spearman’s correlations within groups . In schizophrenia patients , βirrelevance was associated with an increased negative symptoms score from the PANSS ( ρ = 0 . 334 , p = 0 . 031 ) but there was no significant correlation with the other PANSS scores ( all p-values>0 . 2; except p = 0 . 11 for total PANSS score ) . Across all participants , the relevance weighted prediction error correlated with increased BOLD response in the anterior cingulate cortex ( [12 32 22] , t ( 74 ) = 4 . 2 , pSVC for ACC VOI = 0 . 032 , pB corr = 0 . 096 , see Fig 4A ) . A negative correlation with relPE was observed in the left hippocampus ( [-32–18–14] , t ( 74 ) = 5 . 4 , pFWE whole brain = 0 . 041 , see Fig 4C ) . There was no group difference in relevance weighted PE response in any of the VOIs nor at the whole brain level . In order to probe the associations between model derived parameters and brain responses in patients , we focused on the model parameter βirrelevance that was increased in schizophrenia patients and related to psychopatholgy . In schizophrenia patients , there was an inverse correlation between βirrelevance values and relPE related bilateral nucleus accumbens response ( [-14 4–10] , t ( 36 ) = 5 . 21 , pSVC for nucleus accumbens<0 . 001; pBonferroni corr = 0 . 001; [14 6–8] , t ( 36 ) = 3 . 6 , pSVC for nucleus accumbens = 0 . 019 , pBonferroni corr = 0 . 057 , see Fig 5 ) .
In the current study , we established a novel definition of subjective relevance based on Bayesian precision of predictions . This computational mechanism was involved in implicit learning about multidimensional and changing environments , as well as in aberrant salience attribution in schizophrenia . To our knowledge , our study stands alone in investigating subjective beliefs during implicit learning in a dynamic appetitive Pavlovian conditioning task . We had three main findings: 1 ) Both groups learned the underlying associations equally well but patients showed more aberrant salience in terms of a bias towards task-irrelevant features; 2 ) in all participants unexpected outcomes as indicated by high relevance-weighted unsigned prediction errors were associated with increased dorsal ACC BOLD signal as part of the so-called salience network; and 3 ) heightened aberrant salience in patients in terms of a bias towards the currently task-irrelevant stimulus feature was associated with a lower neural salience signal in the nucleus accumbens and higher negative symptom severity . On the behavioral level , patients and controls both performed the target detection task with high accuracy and responded faster to the rewarding coin stimulus compared to the neutral circle . These two findings suggested that participants of both groups were engaged in the simple task of pressing one button upon seeing a coin and another for a circle , which had obviously minimal cognitive demands . We found that schizophrenia patients and healthy individuals seemed to use the preceding cues to speed up during the outcome discrimination task . Subjects were faster for expected than for unexpected events in terms of ground truth probabilistic contingencies . Detailed computational modeling combined with model selection revealed that participants learned and used the underlying cue-outcome associations and could determine the currently relevant feature . Thus , participants discriminated faster if the outcome was predicted based on the preceding cues but slowed down if the observed outcome violated the expectation , which was formalized in the relevance weighted PE . Responses to the most relevant cue feature were increased , whereas reactions to the irrelevant feature were decreased as implemented in the best-fitting response model . Hence , subjects adapted more to those unexpected events that were thought to be reliable and that thus signaled actual changes in the environment . Correspondingly , they downregulated responses to such information that was thought to be noisy and uninformative . To conclude , in our task the relevance weighted unsigned PE can be interpreted as subjective informative surprise that leads to subtle adaptation in behavior even in the absence of instrumental need . While relevance weights scaled the influence of prediction errors on reaction times , that is , behavioral adaptation , we had no evidence that updating of association beliefs was increased by the subjective relevance of a cue feature beyond the HGF implementation of a cross level precision ratio [24 , 45] . This may only hold for our implicit and dynamic paradigm and seems to be different when subjects are explicitly instructed to find out the steadily relevant aspect of a multidimensional learning cue [18] . The relevance weighted unsigned PE correlated with BOLD responses in the salience network comprising the dorsal ACC . This is in line with the theory of proximal salience , which proposes that activity of ACC and insula regulates higher order processing of external stimuli [16] . Especially the dorsal ACC/medial prefrontal cortex has been reported to respond to unexpectedness regardless of valence [48 , 49] . According to the response-outcome theory [50] , the dorsal ACC is crucial for detecting discrepancies between expectations and outcomes and thereby drives attentional and behavioral reallocation . Further studies that elaborated how individuals use those unexpectedness signals highlighted the ACC’s function in belief updating [51] and in predicting future cognitive load based on previous experience [14] . This can be related to the relevance weighted unsigned PE signal in our study that also comprised estimates of prior reliability of a cue feature . In line with our results , a recent study also used computational modeling of Bayesian conflict learning and reported similar UPE correlates in the dorsal ACC [12] . On the other hand , the hippocampus showed an opposite pattern in our study: high hippocampus activation was associated with low relevance weighted UPE . This stands in contrast to previous findings and theories describing hippocampal activation during mismatching events [for a review see 52] . In our task , low relevance weighted UPE occurred when the observed outcome was not surprising and would therefore be mostly present at the end of each block , after constantly changing contingencies have been learned . In other words , expected events elicit stronger BOLD response in the hippocampus which might indicate higher-order processes related to contextualizing and memorizing these learned contingencies [53 , 54] . Although participants were not incentivized for target detection , both groups performed well and no group differences emerged for learning contingencies indicating that patients and controls both used the cues for behavioral adaptation . Contrarily , there is sound evidence for learning deficits in schizophrenia patients mostly in more explicit and instrumental tasks [55–58] . Our study assessed implicit learning which might have led to the subtle behavioral and neural effects . In addition , the reversals inside the relevant condition appeared every 20 trials . Presumably , fewer reversals with longer stable periods for learning the implicit associations might have led to stronger task effects . Switching the relevant condition in the middle of the experiment did not affect learning significantly ( please see Supplement ) , though this seems to be different in tasks where such shifts happen more often and are explicitly instructed as during set-shifting . During these paradigms , schizophrenia patients are impaired [55] . Hence , whereas we focused on the rather implicit and prediction error driven learning about relevance with our paradigm and model space , schizophrenia patients might show more pronounced deficits when explicit reasoning about the structure of the task is required . It has been shown that when healthy individuals were explicitly asked to find out the relevant cue dimension they used explicit strategies reflecting the assumed underlying task structure [59] . Thus , group differences between schizophrenia patients and healthy individuals concerning the detection of relevance ( shifting ) might be better detectable and more pronounced in such more complex learning paradigms probing deliberative decisions that rely on the use of explicit task knowledge . In keeping with previous results in a partially overlapping sample [39] , schizophrenia patients displayed an increased bias for one of two equally task-irrelevant cue features as formalized using the ground truth contingencies of the task . This is in line with previous studies that reported increased responses in schizophrenia patients to neutral [29–32 , 60] or unreliable [33] information . We further elucidated this bias using computational modeling that took into account only subjective and dynamic relevance estimates . The response parameter capturing this irrelevance bias was increased in patients indicating that they attributed more aberrant salience to cues when they were subjectively irrelevant and thus thought to be less informative with regard to the task . This aberrant salience bias was associated with decreased striatal activation during relevance weighted PE signaling . Though this finding has to be treated with caution , since this region did not display a task effect per se , it might show that patients experiencing more idiosyncratic and task-unrelated saliency also showed a reduced striatal processing of relevant information . There is meta-analytic evidence for decreased striatal responses in schizophrenia patients to reward-predicting cues and rewarding feedback [61] . Also , ultra-high risk subjects who decreased their unusual thought content after treatment showed an amelioration of striatal response to relevant and reinforced stimuli in the SAT [35] . These studies focused on striatal reward anticipation , whereas the relevance weighted PE in our study was undirected , i . e . carried no information about reward , only about associability strength and the respective surprise when these associations were violated in both directions , good or bad . This striatal PE coding is in line with a recent study on explicit reasoning that elegantly decorrelated reward PEs from Bayesian surprise and the authors found that the latter was more strongly associated with striatal response [59] . Taken together , the processing of relevant ( not only rewarding ) and the bias towards irrelevant information seem to be interfering phenomena . We cannot make any claims on causality here and would argue that bidirectional influences are plausible and may appear at the same time . A possible interpretation may be that not being able to figure out the correct ( e . g . rewarding ) cues for behavioral adaptation may cause a compensatory clinging to random cues as seen in the aberrant salience bias to irrelevant events in our study . Note that this aberrant salience definition which is based on the SAT literature [33 , 35] targets increased responses to task-irrelevant and not to neutral events as often used in previous Pavlovian studies [30 , 31 , 62] . This different operationalization of aberrant salience could be important for associations with psychopathology . One study reported increased BOLD response towards cues reliably indicating neutral outcomes to be associated with positive symptoms [30] . Our aberrant salience measure to events that were learned to be uninformative of any outcome relates to negative symptoms . In the same vein , orientating behavior to unreliable , and thus irrelevant stimuli was proposed to underlie negative symptom formation [5] . Taken together , a biased focus on uninformative , irrelevant events by possibly limiting attention to relevant events relates to increased negative symptoms . Roiser and colleagues found a similar association between ( explicit ) aberrant salience to irrelevant events and negative symptoms in patients as well as with anhedonia in healthy individuals [33 , 63] . They interpreted this to result from ‘false negatives’ in phasic dopamine signaling to contextually relevant events contributing to reduced processing of reinforcing stimuli [33] . This view is supported by an animal study reporting decreased striatal dopamine transients to relevant , reward-predicting stimuli following amphetamine administration [64] . In the same vein , aberrant salience was related to increased tonic dopamine synthesis capacity and reduced responses to relevant events in the striatum in healthy individuals [65] . Transferred to our findings , processing unreliable information in schizophrenia patients may increase processing of irrelevant as well as decrease processing of relevant events while contributing to both , positive and negative symptoms [4 , 5] . Our association between the aberrant salience ( irrelevance ) bias and negative symptoms was found in a chronic patient sample on stable antipsychotic medication showing both negative and positive symptoms . Taken together , we provide evidence that schizophrenia patients show a bias towards irrelevant stimuli when confronted with an uncertain and changing environment . Future longitudinal studies should examine the time-wise formation of this bias as well as the process of relevance detection and their respective associations with psychopathology . Several limitations of our study need to be addressed . First , by keeping the contingency structure implicit , it possibly led to a high variance between subjects in how to solve the paradigm . We modeled reaction times and although there are notable exceptions [66–69] , modeling of choice data is more widely used . For reaction time based analysis , unlike choice-based analysis , there is no clear absolute model fit to compare against as in previous studies [56 , 57] . Second , because learning was not necessary for task performance , the implicit behavioral and neural learning effects were both very subtle and might need larger samples for the detection of group differences . Third , the two different cue features were initially chosen to be easily dissociable resulting in differences regarding their perceptual characteristics and presumably their saliency . As alterations of visual perception have been reported in schizophrenia patients , patients might have processed the cue features differently compared to controls [70] . However , in our supplementary analyses we neither found evidence that the cue features were learned differently nor that cue features were processed differently between groups . Fourth , with our current paradigm we cannot disentangle the saliency of cues from their rewarding valence since we did not include a punishment condition . Finally , future studies of learning about multidimensional information in schizophrenia should include additional methods to detect relevance attribution , such as skin conductance response [30] , eye-tracking , or MVPA [18] . In sum , we give a novel computational account of the use of subjective relevance estimates in implicit learning that is based on Bayesian precision . Furthermore , we provide quantitative , model-based evidence of an impairment in the formation and/or use of relevance estimates associated with schizophrenia . In a task probing the implicit learning of multidimensional and dynamic associations , relevance detection and neural learning correlates in the ACC seem to be intact in patients with schizophrenia , but aberrant salience to subjectively irrelevant events was increased in patients and related to negative symptoms and reduced striatal response to salient events . Our findings suggest that individual beliefs about relevance can be inferred from computational models and highlight the importance of relevance detection to complex environmental stimuli . | Schizophrenia patients display deficits in the appropriate attribution of meaningfulness to stimuli; such as aberrantly increased processing of irrelevant and insufficient processing of relevant information . We aimed to investigate the subjective nature of relevance detection and its deficit in schizophrenia and developed an implicit learning paradigm that allowed for parallel learning from relevant and irrelevant information . Based on the idea that subjective relevance might be captured by Bayesian precision we set up different computational models of how subjective relevance guides learning and behavioral adaptation . We found that subjects use Bayesian precision to estimate stimulus relevance in order to integrate multidimensional information and adapt more to the subjectively relevant stimuli . This relevance weighted adaptation correlated with brain activation within the salience network . Further , schizophrenia patients displayed an increased aberrant tendency to irrelevant events which related to decreased striatal coding of the relevant learning signal . To conclude , our findings demonstrate how individual beliefs about relevance can be inferred from computational models . Furthermore , we suggest that aberrant salience observed in patients with schizophrenia reflects an idiosyncratic bias in states of high subjective uncertainty . | [
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... | 2018 | Modeling subjective relevance in schizophrenia and its relation to aberrant salience |
In the skin and gill epidermis of fish , ionocytes develop alongside keratinocytes and maintain body fluid ionic homeostasis that is essential for adaptation to environmental fluctuations . It is known that ionocyte progenitors in zebrafish embryos are specified from p63+ epidermal stem cells through a patterning process involving DeltaC ( Dlc ) -Notch-mediated lateral inhibition , which selects scattered dlc+ cells into the ionocyte progenitor fate . However , mechanisms by which the ionocyte progenitor population is modulated remain unclear . Krüppel-like factor 4 ( Klf4 ) transcription factor was previously implicated in the terminal differentiation of mammalian skin epidermis and is known for its bifunctional regulation of cell proliferation in a tissue context-dependent manner . Here , we report novel roles for zebrafish Klf4 in the ventral ectoderm during embryonic skin development . We found that Klf4 was expressed in p63+ epidermal stem cells of the ventral ectoderm from 90% epiboly onward . Knockdown or knockout of klf4 expression reduced the proliferation rate of p63+ stem cells , resulting in decreased numbers of p63+ stem cells , dlc-p63+ keratinocyte progenitors and dlc+ p63+ ionocyte progenitor cells . These reductions subsequently led to diminished keratinocyte and ionocyte densities and resulted from upregulation of the well-known cell cycle regulators , p53 and cdkn1a/p21 . Moreover , mutation analyses of the KLF motif in the dlc promoter , combined with VP16-klf4 or engrailed-klf4 mRNA overexpression analyses , showed that Klf4 can bind the dlc promoter and modulate lateral inhibition by directly repressing dlc expression . This idea was further supported by observing the lateral inhibition outcomes in klf4-overexpressing or knockdown embryos . Overall , our experiments delineate novel roles for zebrafish Klf4 in regulating the ionocyte progenitor population throughout early stem cell stage to initiation of terminal differentiation , which is dependent on Dlc-Notch-mediated lateral inhibition .
Unlike terrestrial vertebrates , teleosts encounter and adapt to ionic , osmotic and acid-base fluctuations in aquatic environments . To maintain body fluid ionic homeostasis , specialized ionocytes ( previously called mitochondria-rich cells ) develop predominantly in the skin of embryos and gills of adult fish . These cells regulate osmotic homeostasis through transepithelial ion-transport [1 , 2] . Five types of ionocytes have been identified in the skin of zebrafish embryos , including H+-ATPase-rich ( HR ) cells , Na+ , K+-ATPase-rich ( NaR ) cells , Na+-Cl- cotransporter-expressing ( NCC ) cells , SLC26-expressing cells , and K+-secreting ( KS ) cells [3] . These ionocytes perform transepithelial H+ secretion/Na+ uptake/NH4+ excretion , Ca2+ uptake , Na+/Cl- uptake , Cl- uptake/HCO3- secretion , and K+ secretion , respectively , by utilizing various transporters located at the apical or basolateral cell surface [3–6] . In zebrafish embryos , ionocytes and keratinocytes are derived from common precursors in the ventral non-neural ectoderm and express a dominant-negative form of p63 ( ΔNp63 ) at the late gastrula stage [7] . ΔNp63 was shown to be a direct target of BMP signaling , which is essential to promote ectodermal cell differentiation into epidermal cells [8] . The functional consequences of ΔNp63 were revealed in a study that showed reduced expression of gata2 non-neural marker and enhanced expression of neuroectoderm markers ( six3 . 1 and pax2 . 1 ) during gastrulation , suggesting an early role for ΔNp63 as a repressor of neural specification in the ventral ectoderm . In addition , ΔNp63 morphants were reported to have lost fin fold and pectoral fins , which was attributed to defective p53 inhibition . Thus , ΔNp63 also plays a late role , after 20 hours post fertilization ( hpf ) , in the maintenance of epidermal proliferation [8 , 9] . Although ionocyte progenitors transiently express ΔNp63 from the bud to the 14 somite stage , knockdown of ΔNp63 does not abolish proliferation or differentiation of ionocytes [7 , 10] , indicating that p63 is unlikely to be a master regulator of proliferation control in ionocyte progenitors . Delta-Notch-mediated lateral inhibition determines whether cells from the p63+ ventral ectoderm will become ionocytes or keratinocytes [7 , 10] . Epidermal cells expressing high levels of Dlc ligand become ionocyte progenitors , and Dlc binding to Notch1a/3 receptors on neighboring epidermal cells prevents them from adopting the same cell fate . Without dlc expression , the neighboring cells develop into keratinocytes [10] . Lateral inhibition is widely known to be regulated by signaling strength , and a recent study on Drosophila sensory organ precursor ( SOP ) cells showed that cellular proliferation also plays a crucial role in determining lateral inhibition-controlled tissue patterning [11] . In addition to Notch signaling strength and proliferation rates , there are several other potential mechanisms by which lateral inhibition may be modulated . These mechanisms include effects on the extent of the lateral inhibition domain , or control of delta expression levels after cell division . These multiple control processes may be influenced by a master regulator that differentially modulates epidermal stem cells and ionocyte progenitors during lateral inhibition , however , such a master regulator has not yet been identified . After the progenitor cell fate is determined by lateral inhibition , expression of two winged helix/forkhead transcription factors ( foxi3a and foxi3b ) can be observed in ionocyte progenitors during late gastrulation . Knockdown of foxi3a abolishes the development of ionocytes , including HR and NaR cells , indicating a requirement for Foxi3a in the specification and differentiation of ionocytes . Furthermore , a positive feedback regulatory loop between Foxi3a and Foxi3b is thought to control specification into different ionocyte subtypes [10] . This loop creates individual expression profiles for the two proteins that differentially regulate downstream determination factors , such as glial cell missing 2 ( gcm2 ) , to specify ionocyte progenitors into HR cells or NaR cells [12 , 13] . Thus , a self-organized and evenly distributed pattern of ionocytes emerges in the epidermal tissue , and factors that influence ionocyte progenitor proliferation would be expected to affect all types of matured ionocytes . Mammalian krüppel like factor 4 ( KLF4 ) is a zinc-finger transcription factor [14] that is composed of an N-terminal activation domain , a central repression domain , and three zinc-finger DNA binding motifs at the C-terminus . The protein is expressed and functions in a variety of tissues , including intestinal epithelium and skin [15 , 16] . Interestingly , Klf4-/- mice die shortly after birth because of defects in the skin barrier function [17] . An epidermal permeability barrier consists of several layers , including the outer stratum corneum , which is composed of a cornified envelope and lipid bilayers; it is the development of the cornified envelope that is selectively affected in Klf4-/- mice [17 , 18] . Mechanistically , KLF4 positively regulates expression of Sprr2a , which encodes a proline-rich protein in the cornified envelope , and nine different Keratin genes , which form keratin filaments . Thus , KLF4 is known to be essential for terminal differentiation of skin epidermis [17 , 19] . KLF4 also acts as an oncogene or tumor suppressor in a context-dependent manner [20 , 21] . The tumor suppressor activity is related to induction of cell cycle arrest via transcriptional upregulation of the CDKN1A gene , which encodes p21Cip1 . Correspondingly , gastric epithelia in mice with Klf4 deficiency exhibit low levels of p21Cip1 expression , resulting in increased proliferation [22 , 23] . Conversely , KLF4 may act as an oncogene by binding to the promoter of p53 and suppressing transcription of the gene [24] . In cells expressing RASV12 , retroviral delivery of KLF4 promoted proliferation through repression of p53 and inactivation of p21Cip1 via Cyclin D1 inhibition [24] . In addition , KLF4 was shown to regulate embryonic stem cell self-renewal by directly enhancing Nanog expression to prevent differentiation [25] . Thus , the cellular functions of KLF4 are multifaceted , and it is still not clear how KLF4 regulates the balance of epidermal proliferation-differentiation . Here , we report novel roles for zebrafish Klf4 in the maintenance of the ionocyte progenitor population by regulating epidermal stem cell proliferation and modulating dlc-mediated lateral inhibition . In order to examine ionocyte development in zebrafish embryos , we generated dlc transgenic lines that recapitulate endogenous dlc expression . Strikingly , dlc+ ionocyte progenitor cells were absent in mutant lines with a defective KLF binding motif on the dlc promoter , which was identified by chromatin immunoprecipitation ( ChIP ) . Furthermore , we found that Klf4 is expressed universally in p63+ epidermal stem cells located in the ventral ectoderm from 90% epiboly . Knockdown or knockout of klf4 expression reduced the proliferation rate of p63+ stem cells , resulting in decreased numbers of p63+ stem cells , dlc+ p63+ionocyte and dlc-p63+ keratinocyte progenitors . These decreased numbers led to subsequent decreases in the densities of HR and NaR ionocytes , as well as col1a1a+ keratinocytes . We found that Klf4 modulated the ionocyte progenitor population through multiple mechanisms , including p53-mediated effects on proliferation of p63+ epidermal stem cells and ionocytes , regulating the range of lateral inhibition domain , repressing dlc expression and affecting dlc+ progenitor clustering .
Previously , we demonstrated that zebrafish Klf4 plays an evolutionarily conserved role in regulating the differentiation of intestinal goblet cells , much like its counterpart , KLF4 , in mouse [26] . Because mouse KLF4 also plays an essential role in the terminal differentiation of skin epidermis , we investigated whether zebrafish klf4 is expressed in the epidermis and affects the development of ionocytes in embryos . Immunofluorescence was conducted using an anti-zebrafish Klf4 antibody , and Klf4 was found to be universally expressed in the epiblast of the deep cell layer ( DEL ) , yolk syncytial layer ( YSL ) , and enveloping layer cells ( EVL ) during gastrulation . Moreover , Klf4 staining was observed in both ventral and dorsal ectoderm , and EVL cells during early somite stages ( Fig 1A ) . Epidermal stem cells are marked by p63 [27] , and are known to give rise to ionocyte progenitors [10] . We examined the distribution pattern of p63 and Klf4 by double immunofluorescence in stages ranging from late gastrulation to early somite . p63 expression was first observed in the ventral ectoderm of 90% epiboly and bud stage embryos , where it was highly colocalized with Klf4 ( 93 . 8 ± 8 . 6% in 90% epiboly and 85 . 5 ± 15 . 5% in bud , mean ± SEM ) ( Fig 1B ) . Expanded p63 expression in the dorsal ectoderm was found in 5s and 10s embryos , and some Klf4 positive cells did not colocalize with p63 epidermal stem cells in the ventral ectoderm region at the stages screened ( Fig 1B ) . Those cells that only express Klf4 are not expected to be ionocyte precursors , because p63 was consistently colocalized with ionocyte precursors until at least the 14s stage [10] . In addition , colocalization of Klf4 protein and dlc mRNA was observed beginning at 90% epiboly until the bud stage , and all dlc+ cells also stained positive for Klf4 ( Fig 1Ca-h ) . At the 5s stage , some dlc+ cells in the epidermal ionocyte domain ( yolk ball ) were not labeled by Klf4 staining ( Fig 1Ci-l ) . dlc+ ionocyte progenitor number reached a maximum at bud stage and was decreased at the 5s stage ( Fig 1Cm ) . This result suggests that the selection of dlc+ ionocyte progenitors via lateral inhibition occurs at the bud stage and that dlc degradation is initiated between the bud and 5s stage . Since mammalian KLF4 is known to regulate embryonic stem cell self-renewal , we wondered whether zebrafish Klf4 might modulate p63+ epidermal stem cell proliferation and dlc+ ionocyte progenitor number . Thus , we knocked out klf4 by CRISPR-Cas9 genomic editing [28] . Four sgRNAs were designed to target exon 4 at a position 5'-upstream of the first zinc finger motif , but only one of the sgRNAs efficiently generated a new mutant strain , which was named klf4d5i1 and contained an indel consisting of a 5-bp deletion and a 1-bp insertion . This mutant produces a truncated Klf4 protein that consists of 328 amino acids , 27 of which are misframed , and no functional zinc finger motif ( Fig 2A ) . We labeled 80% epiboly klf4d5i1 F3 embryos with BrdU and fixed the embryos at the bud stage . Immunofluorescence staining was performed , using anti-BrdU and anti-p63 antibodies , in combination with fluorescence in situ hybridization , using a dlc antisense RNA probe ( Fig 2B ) . Each klf4d5i1 F3 embryo was genotyped after imaging . The p63+ epidermal stem cell number was reduced by 13 . 1% in klf4d5i1 heterozygous mutants ( klf4+/+ 1222 . 5 ± 41 . 7 cells vs . klf4+/- 1062 . 3 ± 49 . 2 cells; t-test , p = 9 . 5 × 10−4 ) and 23 . 5% in klf4d5i1 homozygous mutant embryos ( klf4+/+ 1222 . 5 ± 41 . 7 cells vs . klf4-/- 935 ± 43 . 6 cells; t-test , p = 5 . 8 × 10−9 ) compared to sibling wild-type controls at the bud stage ( Fig 2Bf , k and 2Ca ) . These reductions were attributable to a decreased proportion of p63+ BrdU+ epidermal stem cells in klf4d5i1 heterozygous and homozygous mutant embryos at the bud stage ( Fig 2Bi , n and 2Ca ) , suggesting that Klf4 is required to maintain the proliferation rate of p63+ epidermal stem cells . Since p63+ epidermal stem cells can produce both keratinocytes and ionocytes , we then analyzed proliferation and numbers of dlc-p63+ cells ( keratinocyte precursors ) and dlc+p63+ cells ( ionocyte precursors ) in klf4d5i1 heterozygous , homozygous mutant and sibling wild-type embryos by analyzing merged images of embryos stained for p63 and dlc . dlc- p63+ keratinocyte progenitor cell number was decreased by 13 . 8% in klf4d5i1 heterozygous mutant embryos ( klf4+/+ 1165 . 1 ± 41 . 2 cells vs . klf4+/- 1004 ± 43 . 5 cells; t-test , p = 6 . 853 × 10−3 ) and 23 . 2% in klf4d5i1 homozygous mutant embryos ( klf4+/+ 1165 . 1 ± 41 . 2 cells vs . klf4-/- 894 . 25 ± 41 . 9 cells; t-test , p = 1 . 36 × 10−4 ) compared to sibling wild-type controls ( Fig 2Cb ) . The percentage of dlc- p63+ BrdU+ keratinocyte progenitor cells was decreased by 11 . 5% in klf4d5i1 heterozygous embryos ( klf4+/+ 87 . 3 ± 0 . 81% vs . klf4+/- 77 . 3 ± 2 . 26%; t-test , p = 1 . 06 × 10−3 ) and 25 . 3% in klf4d5i1 homozygous mutants ( klf4+/+ 87 . 3 ± 0 . 81% vs . klf4-/- 64 . 7 ± 1 . 5%; t-test , p = 2 . 18 × 10−10 ) compared to wild types ( Fig 2Cb ) . dlc+ p63+ ionocyte progenitor cell number was also decreased in klf4d5i1 homozygous mutant embryos compared to wild-type siblings ( klf4+/+ 57 . 41 ± 2 . 6 cells vs . klf4-/- 40 . 75 ± 3 . 28 cells; t-test , p = 6 . 31 × 10−4 ) , however , no reduction of dlc+ p63+ ionocyte progenitor cell number was detected in klf4d5i1 heterozygous mutants at bud stage ( Fig 2Cc ) . Consequently , a reduced ( 24 . 7% ) proportion of dlc+ p63+BrdU + cells was identified in klf4d5i1 homozygous ( klf4+/+ 72 . 5±2 . 66% vs klf4-/-54 . 7±3 . 79%; t-test , p = 7 . 93 × 10−4 ) mutant , but not in klf4d5i1 heterozygous mutant embryos at bud stage ( Fig 2Cc ) . Surprisingly , we also identified a small number ( < 5 ) of dlc+ p63- cells in all examined genotypes ( Fig 2Cd ) , which we suspect resulted from erroneous labeling ( Fig 2Cd ) . We also knocked down klf4 by antisense morpholino oligomers ( klf4 MO1 and klf4 MO2 ) , which have been previously validated for specificity and efficacy [26] . Significant decreases in the total number of p63+ epidermal stem cells , which may be attributed to reduced proliferation rate , were identified in klf4 morphants compared to control embryos at the bud stage ( S1Ca Fig ) . Similar declines in dlc- p63+ keratinocyte progenitor cell number and proliferation rate were detected in klf4 morphants compared to control embryos ( S1Cb Fig ) . A substantially reduced number of dlc+ p63+ ionocyte progenitor cells was found in klf4 morphants , however the proliferation rate was not altered ( S1Cc Fig ) . We also identified a small number ( < 5 ) of dlc+ p63- cells in control and klf4 morphants , which were probably the result of erroneous labeling ( S1Cd Fig ) . Together , these results indicate that Klf4 regulates the proliferation rate of p63+ epidermal stem cells and dlc- p63+ keratinocyte progenitor cells , as well as dlc+ p63+ ionocyte progenitor cell number . In order to confirm the effect of klf4 deficiency on the dlc+ ionocyte progenitor cell number , we knocked down klf4 by antisense morpholino oligomers ( klf4 MO1 and klf4 MO2 ) . We detected a significant decrease in the cell density of dlc+ ionocyte progenitors ( control 2 . 13 ± 0 . 067 cells μm-2 × 10−4; morphants 1 . 20 ± 0 . 058 cells μm-2 × 10−4; t-test , p = 1 . 42 × 10−17 ) in embryos co-injected with klf4 MOs as compared with control embryos . We further detected a substantial increase in dlc+ progenitor cell density ( LacZ-overexpression 1 . 78 ± 0 . 10 cells μm-2 × 10−4; klf4-overexpression 2 . 50 ± 0 . 14 cells μm-2 × 10−4; t-test , p = 1 . 15 × 10−4 ) in klf4-overexpressing embryos at the bud stage ( Fig 3A ) . Since the Foxi3a and Foxi3b winged helix/forkhead box transcription factors are master regulators of epidermal ionocyte specification in zebrafish embryos [10] , we further investigated whether expression of these genes is affected by perturbing klf4 levels . A significant reduction ( control 3 . 31 ± 0 . 13 cells μm-2 × 10−4; morphants 2 . 80 ± 0 . 12 cells mm-2 × 10−4; t-test , p = 4 . 51 × 10−3 for foxi3a+ cells; control 3 . 12 ± 0 . 087 cells μm-2 × 10−4; morphants 2 . 60 ± 0 . 09; t-test , p = 9 . 72 × 10−5 for foxi3b+ cells ) in the densities of ionocyte progenitors expressing either foxi3a or foxi3b was observed in embryos that were co-injected with klf4 MOs as compared to control embryos at the 5s stage . Conversely , statistically significant increases in cell density of foxi3a+ or foxi3b+ ionocyte progenitors were observed ( LacZ-overexpression 3 . 04 ± 0 . 071 cells μm-2 × 10−4; klf4-overexpression 3 . 61 ± 0 . 23 cells μm-2 × 10−4; t-test , p = 0 . 0279 for foxi3a+ cells; LacZ-overexpression 2 . 84 ± 0 . 07 cells μm-2 × 10−4; klf4-overexpression 3 . 87 ± 0 . 14 cells μm-2 × 10−4; t-test , p = 1 × 10−7 for foxi3b+ cells ) in 5s embryos that were injected with klf4 mRNA , as compared to embryos injected with LacZ mRNA ( Fig 3B and 3C ) . We also analyzed the densities of dlc+ and foxi3a+ ionocyte progenitor cells in klf4d5i1 homozygous mutant embryos . We observed a significant reduction in dlc+ ionocyte cell density ( control 2 . 17 ± 0 . 010 cells μm-2 × 10−4; mutants 1 . 51 ± 0 . 033 cells μm-2 × 10−4; t-test , p = 0 . 01396 ) of klf4d5i1 homozygous mutant embryos compared to wild-type controls at bud stage ( S2C Fig ) . Similarly , a substantial decrease of foxi3a+ ionocyte cell density ( control 2 . 07 ± 0 . 11 cells μm-2 × 10−4; mutants 1 . 77 ± 0 . 055 cells μm-2 × 10−4; t-test , p = 0 . 03901 ) was detected in klf4d5i1 homozygous mutant embryos compared to wild-type controls at 5s stage ( S2F Fig ) . Together these results confirm that defective klf4 expression affects ionocyte progenitors , as evidenced by expression of ionocyte regulators , dlc , foxi3a and foxi3b . Because NaR and HR cells have been studied most extensively among the five types of ionocytes , we next evaluated whether differentiation of NaR and HR cells was affected by perturbation of klf4 expression . Expression of relevant marker genes ( atp1a1a . 1 and atp6v1aa for NaR and HR cells , respectively ) at 24 hpf was measured by in situ hybridization . A substantial decrease in atp1a1a . 1+ NaR cell density ( control 3 . 58 ± 0 . 19 cells μm-2 × 10−4; morphants 2 . 40 ± 0 . 16 cells μm-2 × 102; t-test , p = 1 . 05 × 10−5 ) was found in 24 hpf embryos co-injected with klf4 MOs , as compared with wild-type and control embryos injected with klf4 5mm MO2 . Conversely , a significant increase in atp1a1a . 1+ NaR cell density ( 3 . 31 ± 0 . 16 cells μm-2 × 10−4 for LacZ-overexpression; 5 . 40 ± 0 . 28 cells μm-2 × 10−4 for klf4-overexpression; t-test , p = 5 . 08 × 10−9 ) was observed in embryos injected with klf4 mRNA at the same time-point ( Fig 4A ) . A similar effect on atp6v1aa+ HR cell density was observed in klf4 morphants ( control 9 . 87 ± 0 . 37 cells μm-2 × 10−4; morphants 6 . 16 ± 0 . 53 cells μm-2 × 10−4; t-test , p = 1 . 99 × 10−6 ) and klf4-overexpressing embryos ( 9 . 28± 0 . 34 cells μm-2 × 10−4 for LacZ-overexpression; 11 . 82 ± 0 . 47 cells μm-2 × 10−4 for klf4-overexpression; t-test , p = 2 . 93 × 10−5 ) at 24 hpf ( Fig 4B ) . We also analyzed whether the density of col1a1a+ differentiated keratinocytes was affected by knockdown of klf4 expression and found that col1a1a+ cell density was significantly reduced in klf4 morphants compared to control embryos ( S3 Fig ) . Co-injection with klf4-7mm mRNA completely rescued the cell densities of foxi3a+ expressing ionocytes in 24 hpf morphants , while co-injection with LacZ mRNA had no such effect ( S4A Fig ) . In addition , Klf4 protein was scarcely detected by immunofluorescence in bud embryos injected with klf4 MOs as compared with control embryos ( S4B Fig ) . Immunofluorescence with antibodies against Na+ , K+-ATPase or H+-ATPase further confirmed that klf4 knockdown significantly reduced the densities of NaR and HR cells in a dose-dependent manner at 72 hpf , as compared to uninjected wild types or embryos injected with control MOs ( S5 Fig ) . These results demonstrate that Klf4 affects the differentiation of NaR and HR ionocytes as well as col1a1a+ keratinocytes by regulating cell densities of their progenitors . Because klf4 deficiency resulted in reduced p63+ stem cell proliferation rate , we next explored the mechanism through which Klf4 modulates p63+ epidermal stem cell proliferation . A reduction in the percentage of p63+BrdU+ epidermal stem cells was detected in klf4 bud morphants compared to control embryos ( 66 . 52 ± 1 . 43% vs . 54 . 36 ± 1 . 04%; t-test , p = 2 . 71 x 10−7 ) ( Fig 5Aa-f , l ) . Furthermore , co-injection of klf4-7mm mRNA , but not klf4 lacking a C-terminal DNA binding domain ( klf4ΔC-7mm ) , completely restored the proportion of p63+ BrdU+ epidermal stem cells to a control level , indicating that reduced p63+ epidermal stem cell proliferation is due to klf4 deficiency ( Fig 5Aj-l ) . Because p53 is known to regulate the G1/S cell cycle checkpoint by transactivation of CDKN1A/p21 expression [29] , and mammalian KLF4 was shown to repress transcription of p53 , we evaluated p53 and cdkn1a/p21 expression in klf4 morphants [30] . Upregulated expression levels of p53 and cdkn1a/ p21 were found by RT-qPCR in klf4 morphants compared to control embryos at the 5s stage . Upregulation of p53 and cdkn1a/p21 was prevented in 5s embryos co-injected with klf4-7mm but not klf4ΔC-7mm mRNA , demonstrating that upregulation of p53 and cdkn1a/p21 is dependent on decreased klf4 expression ( Fig 5B and 5C ) . A lack of cdkn1a/p21 upregulation was further observed in 5s embryos co-injected with klf4 MOs and p53 MO ( Fig 5C ) . The decreased percentage of p63+ BrdU+ epidermal stem cells was also completely rescued in embryos co-injected with klf4 MOs and p53 MO or cdkn1a MO ( Fig 5Ah , i , l ) . Injection of p53 MO or cdkn1a MO also restored p63+ epidermal stem cell number and percentage of p63+ BrdU+ epidermal stem cells in klf4d5i1 heterozygous mutant embryos to levels comparable to klf4+/+ sibling wild types at bud stage ( S6 Fig ) . In addition , no apoptosis was observed in ventral ectoderm of klf4 morphants compared to wild-type and control embryos at 5s stage ( S7 Fig ) . In order to investigate whether Klf4 regulates p63+ epidermal stem cell proliferation in a cell-autonomous manner , we produced chimeric embryos by transplanting FITC dextran-labeled wild-type blastomeres into klf4-morphant hosts or FITC dextran-labeled klf4-morphant blastomeres into wild-type hosts . Chimeric embryos were labeled with BrdU at 80% epiboly and fixed at bud stage . Immunofluorescence was conducted with anti-FITC , anti-p63 and anti-BrdU antibodies . The difference in percentage of FITC+BrdU+p63+ cells in wild-type hosts transplanted with klf4-morphant cells compared to klf4-morphant hosts transplanted with wild-type blastomeres ( S8 Fig ) was greater than the difference in percentages of BrdU+p63+ cells detected in klf4-morphant embryos ( Fig 5l ) . This unequal difference between the percentages of FITC+BrdU+p63+ and BrdU+p63+ cells may be due to variations in wild-type response to morpholino injection . Nevertheless , this result demonstrates that Klf4 cell-autonomously regulates epidermal stem cell proliferation by repressing p53 expression . Thus , in klf4-deficient embryos , p53 activity is not inhibited and activates cdkn1a/p21 expression to prevent cell cycle progression . The haploinsufficiency of klf4d5i1 was found in p63+ stem cells but not in their direct downstream dlc+ ionocyte progenitors , suggesting there may be additional regulatory mechanisms in dlc+ cells . To investigate whether Klf4 binds directly to the dlc promoter in vivo , we used JASPAR , a sparse matrix multiplication benchmark for JAVA/F90/C , to identify four potential KLF binding motifs located in the 5′ upstream region of the dlc promoter . We then used Klf4 or Myc antibodies to immunoprecipitate cross-linked chromatin from 5s stage wild-type embryos or embryos injected with klf4-Myc mRNA . The KLF binding motif , located at -756 to -747 bp , was significantly enriched in the immunoprecipitated chromatin , as measured by qPCR ( Fig 6A ) . Moreover , we cloned the entire dlc coding gene , including nine exons and eight introns , as well as 7505 bp upstream of the transcription initiation site into a mini-Tol2-mCherry-based vector and established a stable Tg ( dlc11k:mCherry ) transgenic line . Expression of mCherry in the epidermal ionocyte domain , cranial ganglia , somites and presomitic mesoderm regions of Tg ( dlc11k:mCherry ) F1 embryos recapitulated expression patterns of endogenous dlc at the 5s stage ( Fig 6Bb-e ) . To create a mutated KLF binding motif between -756 and -747 , we cloned 296 bp of dlc exon 1 and 2840 bp upstream of the transcriptional initiation site of the dlc promoter containing a wild-type or a mutated KLF binding motif into a mini-Tol2-mCherry-based vector and established two stable transgenic lines , namely wild-type Tg ( dlc3k:mCherry ) and mutated Tg ( dlc3kM:mCherry ) . mCherry expression was observed in the epidermal ionocyte domain and in nonspecific ectoderm covering the entire trunk of Tg ( dlc3k:mCherry ) embryos ( Fig 6Bf , g ) . This observation suggests that the sequence between -7505 and -2840 bp upstream of dlc promoter is involved in proper patterning of dlc expression in the cranial ganglia , somite and presomitic mesoderm . In addition , more mCherry-expressing cells were detected in the epidermal ionocyte domains of Tg ( dlc3k:mCherry ) embryos compared to Tg ( dlc11k:mCherry ) embryos . This difference may be attributed to a shorter half-life for full-length Dlc-mCherry fusion protein based on ubiquitination and degradation events . In contrast , no mCherry expression was detected in the epidermal ionocyte domain , and low level mCherry expression was observed in the presomitic mesoderm region of the mutant Tg ( dlc 3kM:mCherry ) transgenic line at the 5s stage ( Fig 6Bh , i ) . Furthermore , increased mCherry protein was detected in klf4-overexpressing Tg ( dlc3k:mCherry ) but not Tg ( dlc3kM:mCherry ) transgenic embryos compared to LacZ-overexpressing Tg ( dlc3k:mCherry ) transgenic embryos at bud stage ( Fig 6Ca-g ) . Taken together , these findings suggest that Klf4 binds directly to the KLF binding motif at -756 to -747 bp to modulate dlc transcription . Mutation of the -756 to -747 upstream KLF binding motif abolished mCherry expression in the ionocyte domain , while knockdown of klf4 only resulted in decreased cell density of dlc+ ionocyte progenitors at the bud stage ( Figs 6Bh and 3Ac , d ) . These differing observations imply that additional transcription factors may bind to the KLF binding motif or act as essential cofactors for dlc expression in the ionocyte expression domain . The transcription factor , Suppressor of Hairless ( Su ( H ) ) , interacts with the intracellular domain of Notch to activate downstream genes , while Su ( H ) DBM contains a point mutation in the DNA binding domain and acts as dominant negative to inhibit Notch signaling [31] . To examine the influence of Notch signaling on dlc expression in ionocyte progenitors , we further injected dominant-negative X-Su ( H ) DBM RNA into 1-cell zygotes of Tg ( dlc3k:mCherry ) or Tg ( dlc3kM:mCherry ) transgenic lines and evaluated mCherry+ or endogenous dlc+ ionocyte progenitor cell numbers ( S9 Fig ) . We observed significant increases in cell numbers for both mCherry+ and endogenous dlc+ ionocyte progenitors in X-Su ( H ) DBM -injected Tg ( dlc3k:mcherry ) embryos with Notch inhibition . However , no mCherry+ ionocyte progenitors were detected in X-Su ( H ) DBM RNA-injected Tg ( dlc3kM:mCherry ) embryos , despite the increased number of endogenous dlc+ ionocyte progenitors . These results further demonstrate that the -756 to -747 KLF binding motif on dlc promoter is essential for lateral inhibition , and this motif might be additionally regulated by unknown transcription factor ( s ) that act downstream of Su ( H ) . In order to further investigate whether Klf4 acts as an activator or suppressor of dlc expression , we generated two chimeric constructs , which contained either a VP16 activator or an Engrailed repressor domain linked to a NLS sequence and Klf4 zinc finger DNA binding domain . At the 5s stage , similar foxi3a+ ionocyte cell densities were detected in embryos injected with 50 pg VP16-klf4 or 130 pg LacZ mRNA compared to embryos injected with 130 pg klf4 mRNA , suggesting that Klf4 is not likely to function as activator ( S10H Fig ) . However , abnormal embryonic development and decreased foxi3a+ ionocyte cell density were identified in embryos injected with 50 pg engrailed-klf4 mRNA ( S11 Fig ) . Based on preliminary tests of different doses , we injected a very low amount ( 0 . 1 pg ) of engrailed-klf4 mRNA and observed a significant increase in foxi3a+ ionocyte cell density at the 5s stage compared to LacZ-overexpressing embryos , which was similar to that seen in klf4-overexpressing embryos ( S10D Fig ) . Together , these results suggest that Klf4 functions as repressor of dlc expression . Klf4 modulation of dlc+ ionocyte progenitor cell number may be regulated by direct binding of Klf4 to the dlc promoter ( Fig 6 ) . Several potential explanations may account for the alteration of dlc+ ionocyte progenitor number that resulted from perturbation of klf4 expression . The first potential explanation is that the cell size may be altered . To examine this possibility , we compared cell diameters after making two assumptions: ( 1 ) the ionocyte domain is a two-dimensional single cell layer , and ( 2 ) dlc expression levels do not change cell size . We compared the normalized dlc+ cell diameters of klf4 morphants and klf4-overexpressing embryos ( S12A Fig ) . An approximately 5 . 2% larger cell diameter was measured in klf4 morphants compared to control embryos , leading us to estimate that 9 . 7% fewer cells should be found in the ionocyte domain . On the contrary , in klf4-overexpressing embryos , a 7 . 9% smaller cell diameter was observed , suggesting that 17 . 9% more cells should be contained in the ionocyte domain . However , the estimated cell density differences do not quantitatively match the observed reductions in dlc+ ionocyte progenitor numbers ( Fig 2Cc ) . The second possibility is that the output densities of lateral inhibition were changed by perturbation of klf4 expression . The average normalized nearest spacing between dlc+ cells ranged from 1 . 29 to 1 . 54 cell diameters in both klf4 morphants and klf4-overexpressing embryos , which is close to that found in in vitro synthetic lateral inhibition circuits [32] . This observation suggests that the range of ionocyte lateral inhibition is relatively short in comparison to Drosophila SOP [11 , 33] . Furthermore , the normalized nearest spacing between dlc+ cells is not different between klf4 morphants and klf4-overexpressing embryos ( S12B Fig ) . Thus , the output densities of lateral inhibition seem to be unaffected by klf4 knockdown or overexpression . The third possibility is that Klf4 controls the range in which precursor cells participate in lateral inhibition . The angle between two vectors that extend from the embryo centroid as the vertex to two points on the embryo edges which flank the dlc+ cell domain was measured [10] . This measurement is proportional to the total area of the ionocyte domain , and was 12 . 1% smaller in klf4 morphants and 36 . 3% larger in klf4-overexpressing embryos compared to controls ( S12C Fig ) . We anticipate that a combination of the effects on cell diameter ( S12A Fig ) and domain size ( S12C Fig ) is required to account for the experimentally determined differences in cell number that are presented in Fig 2Cc and Fig 3A . True quantitative comparisons are not possible due to the variation of embryo batches and sensitivity of in situ detection methods . However , future studies with live time-lapse analysis may be sufficient to fully describe the morphology of alterations induced by perturbation of klf4 expression . Nevertheless , we uncovered multiple routes by which Klf4 modulates ionocyte development , including controlling proliferation rates of epidermal stem cells , modulating precursor cell numbers prior to lateral inhibition , and influencing the range of ionocyte domain . In addition to the three possibilities discussed above , we observed some large dlc+ cell clusters in klf4 overexpressing embryos that were not observed in klf4 mutant or morphants . When we analyzed the clustering effect in klf4 morphants and klf4-overexpressing embryos , there was no difference in the percentage of dlc+ connected pairs between klf4 morphants and control embryos , however , klf4-overexpressing embryos showed a significantly increased percentage of dlc+ connected pairs ( S12D Fig ) . In both control and klf4 morphants , the average maximum dlc+ cluster size in an embryo was 2 . 1 cells , but in klf4-overexpressing embryos , the average maximum dlc+ cluster size was significantly increased to 4 . 1 cells with a highest observed value of 9 cells ( S12E and S12F Fig ) . Furthermore , the dlc+ cell clustering phenotype does not appear to be temporary , because we detected increased foxi3a+cluster size ( ranging from 4 to 6 cells ) in klf4-overexpressing embryos , compared to LacZ-overexpressing embryos ( 2 cells ) at 24 hpf ( S12G Fig ) . Since injection of p53 or cdkn1a MO rescued proliferation of p63+ epidermal stem cells in klf4 morphants at bud stage ( Fig 5 ) , we wondered whether injection of p53 or cdkn1a MO could rescue the reduction in differentiated atp6v1aa+ ionocyte cell density in klf4 morphants . Although the p53 MO-mediated rescue of atp6v1aa+ ionocyte cell density did not reach statistical significance , injection of downstream cdkn1a MO did produce a significant rescue effect on atp6v1aa+ ionocyte cell density of klf4 morphants at 24 hpf ( S13 Fig ) . This result suggests that cdkn1a expression is necessary to produce the reduction in differentiated atp6v1aa+ ionocyte cell density in klf4 morphants .
In the present study , we uncovered a novel role for Klf4 in zebrafish epidermis development . In zebrafish embryos , dlc+ ionocyte progenitors are specified and differentiate from epidermal stem cells during late gastrulation [10] . We showed that Klf4 is expressed in p63+ epidermal stem cells beginning at 90% epiboly ( Fig 1 ) . Knockout or knockdown of klf4 reduced epidermal stem cell proliferation , resulting in fewer stem cells , which in turn reduced the number of differentiated dlc+ p63+ ionocyte progenitors ( Fig 2 , S1 Fig ) . We further demonstrated that zebrafish Klf4 regulates the epidermal stem cell population by repressing p53 expression . A significant reduction in the percentage of BrdU+ epidermal stem cells was also observed in klf4 morphants and was accompanied by increased expression levels of p53 and cdkn1a/p21 . Co-injection of klf4 MOs with either p53 MO or klf4-7mm mRNA reversed cdkn1a/p21 upregulation and restored the percentage of BrdU+ epidermal stem cells to control level . Co-injection of cdkn1a MO also completely rescued the proportion of BrdU+ epidermal stem cells , owing to the fact that cdkn1a/p21 is an essential downstream target gene of P53 in cell cycle regulation [29] . Similar rescue effects on the percentage of BrdU+ p63+ epidermal stem cells were detected in klf4d5i1 heterozygous mutant embryos after injection of p53 MO or cdkn1a MO ( S6 Fig ) . In addition , injection of cdkn1a MO restored atp6v1aa+ differentiated ionocyte cell density in klf4 morphants at 24 hpf ( S13 Fig ) , indicating that the decreased dlc+ p63+ progenitor cell number and reduced cell density of differentiated ionocytes in klf4 morphants could be attributed to upregulation of p53 and cdkn1a/p21 expression . Maintenance of epidermal stem cell proliferation also requires an intact klf4 C-terminal DNA binding domain , suggesting that Klf4 may directly suppress p53 expression ( Fig 5 ) . Mammalian KLF4 was previously shown to suppress p53 expression through direct binding to a specific element within the p53 promoter . Moreover , this repression of p53 expression is one feature that transforms KLF4 from a tumor suppressor to an oncogene [24] . Therefore , zebrafish Klf4 may have a conserved function as a suppressor of p53 expression; further study will be required to analyze potential KLF binding motifs within the zebrafish p53 promoter . One of our especially intriguing discoveries , which stands in contrast to previous reports using different models , is that Klf4 maintains the ionocyte progenitor population by regulating epidermal stem cell proliferation [17 , 34] . Mammalian KLF4 suppresses keratinocyte proliferation by transcriptional activation of CDKN1A/p21 expression [35] . Nevertheless , some studies have shown that KLF4 can also facilitate cell proliferation [24 , 36 , 37] . For example , KLF4 plays an essential role in B cell development and in activation-induced B cell proliferation by regulating Cyclin D2 expression [36] . KLF4 also functions as an oncogene to promote proliferation of breast cancer and bladder cancer cells in the presence of RASV12-Cyclin-D1 signaling or the absence of p21CIP1 [24 , 37] . Altogether , our findings further support the idea that KLF4 may exert distinct functions to regulate stem cell proliferation in a context-dependent manner . The effects of cell proliferation on tissue patterning by lateral inhibition were largely ignored until two recent publications highlighted the issue . First , Akanuma et al . [38] showed that polarized localization of Dlc in developing zebrafish V2 neural progenitor cells determines an asymmetric fate of V2a and V2b daughter cells after cell division . Second , In Drosophila notum , Hunter et al . showed that Notch signaling-dependent cell cycle rate contributes to lateral inhibition-mediated microchaete patterning [11] . These findings demonstrated the essential role of the cell cycle in asymmetric fate and lateral inhibition-mediated tissue patterning . Similarly , we discovered that the proliferation rate of dlc+ cells is lower than that of dlc- cells during ionocyte determination . Although the underlying mechanisms of this proliferation rate difference remain unclear , our data suggest that klf4 might be a crucial factor , since our loss-of-function experiments showed closer proliferation rates between the two cell types ( Fig 2Cb , c , S1Cb , c Fig ) . In the present study , we describe an important role for Klf4 in regulating epidermal stem cell proliferation and the ionocyte progenitor population , which consequently affects the patterning of ionocytes through dlc-mediated lateral inhibition . Thus , we propose a model to describe Klf4 function in the maintenance of the ionocyte progenitor population ( Fig 7 ) . In wild-type embryos , Klf4 represses p53 expression to prevent induction of cdkn1a/p21 , thereby allowing proper proliferation of p63+ epidermal stem cells during late gastrulation . At the same time , Klf4 modulates Dlc-mediated lateral inhibition by repressing dlc expression via direct binding to the dlc promoter , thus maintaining proper ionocyte progenitor population and patterning . In klf4-deficient embryos , p53 expression is no longer suppressed and cdkn1a/p21 expression is activated . cdkn1a/p21 inhibits epidermal stem cell proliferation , and as a consequence , the ionocyte progenitor population is restricted . Conversely , when klf4 is overexpressed , the ionocyte progenitor population is increased , and an aberrant lateral inhibition pattern is produced by dlc+ cell clustering . These observations represent novel discoveries in tissue pattern formation by Delta-Notch signaling .
All animal procedures were approved by the Academia Sinica Institutional Animal Care & Use Committee ( AS IACUC ) ( Protocol ID: 15-12-918 ) . All methods were performed in accordance with the approved guideline . Zebrafish , including ASAB wild-type , klf4d5i1 , Tg ( dlc11k:mCherry ) as33 , Tg ( dlc3k:mCherry ) as34 , and Tg ( dlc3kM:mCherry ) as35 fish lines , were maintained as previously described [39] . Different stages of embryos were defined according to morphological criteria described previously [40] . To generate the expression vector encoding full-length klf4 with a C-terminal 5x Myc tag ( klf4-Myc ) , PCR was conducted using T7TS-klf4 plasmid DNA as template , and 5′-AACTCGAGATGAGGCAGCCTCCGACT-3′ and 5′-ATTCTAGAGGTAGATGGCGCTT-3′ primers ( restriction sites are underlined ) . PCR product was cloned into pCS2-PMTC2 vector digested with XhoI and XbaI . To generate klf4 full-length coding region with seven mismatched nucleotides at the N-terminus ( klf4-7mm ) , PCR with 5′-ATGAGaCAaCCgCCaACcGAaTTcGATAGCATGGCACTGAGCGGAA-3′ ( mismatched bases are in lowercase ) and 5′-TCACTAGTCTATAGATGGCGCTTCATGTG-3′ ( restriction site is underlined ) primers was conducted , and PCR product was cloned into pGEMT vector . This construct was used as template and 5′-TCACCGGTATGAGaCAaCCgCCaACcGAaTTcGA-3′ and 5′-TCACTAGTC TATAGATGGCGCTTCATGTG-3′ ( restriction sites are underlined ) primers were used to conduct a second round PCR . PCR product was first digested with AgeI and blunted with Klenow fragment , followed by digestion with SpeI . Digested PCR product was then cloned into a T7TS vector digested with EcoRV and SpeI . To generate klf4 lacking DNA binding domain with seven mismatched nucleotides at the N-terminus ( klf4ΔC-7mm ) , PCR was conducted using klf4-7mm plasmid as template , and 5′-AACTCGAGATGAGACAACCGCCAACCGAA-3′ and 5′-TTTCTAGACTAGTGTGTGGCGATCCGCTT-3′ ( restriction sites are underlined ) primers . PCR product was cloned into PCS2+ vector digested with XhoI and XbaI . To create the dlc11k-mCherry plasmid , a 3230 bp long upstream region of the dlc gene from -7245 to -4016 bp was amplified by a first PCR using genomic DNA as template and 5′-ATAGGGCCCCATTTGAGAAGAGTGGGACA-3′ and 5′-TCGCCTCACAGTAAGAAAGTCACTGG-3′ ( restriction site is underlined ) primers . A 4275 bp long upstream region of dlc gene from -4030 to +245 bp ( +1 corresponding to transcription initiation site ) was amplified by a second PCR using genomic DNA as template and 5′-CTTACTGTGAGGCGACAGTGCTAACC-3′ and 5′-TTTCCGCGGCTTTGCCTTCTTGTCTGCTA-3′ primers . A third PCR was conducted to merge these two fragments , which comprise 7505 bp upstream of dlc gene . The products of the first and second PCRs were used as templates , and 5′-ATAGGGCCCCATTTGAGAAGAGTGGGACA-3′ and 5′-TTTCCGCGGCTTTGCCTTCTTGTCTGCTA-3′ were used as primers . The PCR product was then cloned into a miniTol2-mCherry vector digested with ApaI and SacII [41 , 42] . A 3307 bp dlc coding gene region from +219 to +3525 bp was amplified by a fourth PCR using genomic DNA as template and 5′-CGTTCAGTAGCAGACAAGAAGGCAAAG-3′ and 5′-AACTCGAGTACCTGAGGAAGGACAGAA-3′ primers . The final dlc 11k gene was combined by PCR using plasmid DNA containing 7 . 5 kb dlc upstream region and the fourth PCR product of 3 . 3 kb dlc coding gene as template , and 5′-ATAGGGCCCCATTTGAGAAGAGTGGGACA-3′ and 5′-AACTCGAGTACCTGAGGAAGGACAGAA-3′ primers . PCR product was then cloned into a miniTol2-mCherry vector digested with ApaI and XhoI . To build the dlc3k-mCherry plasmid , a 3085 bp region upstream of dlc gene from -2840 to +245 bp was amplified by PCR using genomic DNA as template and 5′-ATGGGCCCTGCCACTGGATCACACCTCA-3′ and 5′-TTTCCGCGGCTTTGCCTTCTTGTCTGCTA-3′ primers and cloned into a miniTol2-mCherry vector digested with ApaI and SacII . To create the dlc3kM-mCherry plasmid , first and second PCRs were conducted using dlc3k-mCherry plasmid DNA as template and respective primer pair 1 ( 5′-ATGGGCCCTGCCACTGGATCACACCTCA-3′ and 5′-GGCTTTtttTGGAGGGGATTGGCACA-3′ ) ( restriction site is underlined and mutated KLF motif is italicized ) and primer pair 2 ( 5′-CCCTCCAaaaAAAGCCCCTCCGCGAT-3′ and 5′-TTTCCGCGGCTTTGCCTTCTTGTCTGCTA-3′ ) . The final PCR was conducted using the first and second PCR products as template , and 5′-ATGGGCCCTGCCACTGGATCACACCTCA-3′ and 5′-TTTCCGCGGCTTTGCCTTCTTGTCTGCTA-3′ primers . The final PCR product was then cloned into a miniTol2-mCherry vector digested with ApaI and SacII . To generate a chimeric plasmid ( VP16-klf4 ) , which contains the VP16 activation domain ( amino acids 410–490 ) linked to a Klf4 NLS and Zinc finger DNA binding domain ( amino acids 295–396 ) , a first PCR was conducted using T7TS-klf4 plasmid as template and 5′-CTTGGAATTGACGAGTACGGTGGGGGGTTGCCGGAAGAAT-3′ and 5′-TCTAGATCTAGACTATAGATGGCGCTTCATGTGCAG-3′ ( restriction site is underlined ) primers . A second PCR was conducted using pCS2+-NLS VP16AD plasmid as a template and 5′-GAATTCGAATTCCTGTCGACGGCCCCCCCGAC-3′ and 5′-TTTGGATTCTTCCGGCAACCCCCCACCGTACTCGTCAATTCC-3′ primers . The final PCR was conducted using 1st and 2nd PCR product as template , and 5′-GAATTCGAATTCCTGTCGACGGCCCCCCCGAC-3′ and 5′-TCTAGATCTAGACTATAGATGGCGCTTCATGTGCAG-3′ primers . The final PCR product was then cloned into PCS2+ vector digested with EcoRI and XbaI . To produce a chimeric plasmid ( engrailed-klf4 ) , which contains the engrailed repressor domain ( amino acids 1–298 ) linked to Klf4 NLS and Zinc finger DNA binding domain , a first PCR was conducted using T7TS-klf4 plasmid as template and 5′- CAGAGAAATCTGCTCTGGGATCCGGGTTGCCGGAAGAATCC-3′ and 5′-TCTAGATCTAGACTATAGATGGCGCTTCATGTGCAG-3′ ( restriction site is underlined ) primers . A second PCR was conducted using dENG-hoxa1a plasmid as template and 5′-GAATTCGAATTCATGGCCCTGGAGGATCGCTGCAG-3′ and 5′-TTTGGATTCTTCCGGCAACCCGGATCCCAGAGCAGATTTCTC-3′ primers . The final PCR was conducted using 1st and 2nd PCR product as template and 5′-GAATTCGAATTCATGGCCCTGGAGGATCGCTGCAG-3′ and 5′-TCTAGATCTAGACTATAGATGGCGCTTCATGTGCAG-3′ primers . The final PCR product was then cloned into PCS2+ vector digested with EcoRI and XbaI . Two translational morpholino oligonucleotides ( MOs ) previously designed to inhibit Klf4 protein synthesis were used [26] . The MO sequences were as follows: klf4 MO1: CATGAGTGGAAGGAACGCAAAAG; klf4 MO2: CAAACTCAGTCGGAGGCTGCCTCAT . The following two control MOs were designed: klf4 5mmMO1: CATGAcTGcAAGcAACcgAAAAG , and klf4 5mmMO2: CAAA gTCAcTCGcAGGCTGgCTgAT . A total of 1 . 5 or 3 ng each of klf4 MO1 and klf4 MO2 , 3 ng each of klf4 5mmMO1 and klf4 5mmMO2 , or 6 ng of klf4 5mmMO2 were diluted with Danieau solution , and microinjected into the cytoplasm of 1-2-cell zygotes using an IM300 microinjector ( Narishige , Tokyo , Japan ) . The sequence of p53 MO and cdkn1a MO was as described previously [43 , 44] . klf4 mutant was generated using a CRISPR-Cas9 system . CCTop was used to design four sgRNAs targeting exon 4 [45] . Aligned complementary oligomers of individual sgRNA was cloned into BsmBI-digested pT7-gRNA [46] . sgRNA was synthesized using BamHI-linearized pT7-gRNA and MEGAshortscript T7 Transcription Kit ( Ambion , Austin , TX , USA ) . klf4 sgRNA ( 250 pg ) and Cas9 protein ( 500 ng; Tools , Taipei , Taiwan ) were co-injected into 1-cell zygotes . Genomic DNA was isolated from pools of 10 injected embryos at 24 hpf . PCR was conducted using forward ( 5′-CGGCAGCCAGAAGAGAGAATAATGTC-3′ ) and reverse ( 5′-TTAACACTACAACCGTCTCACTCAAATGC-3′ ) primers , and amplified DNA was digested with T7 endonuclease I ( T7E1 ) to evaluate deletion and insertion ( indel ) efficiency . Only one out of four sgRNAs showed high indel efficiency and the injected embryos were reared to adulthood . Injected fish were designated as the F0 generation . To detect the DNA sequence alterations induced by klf4 sgRNA , genomic DNA was isolated from clipped tail fin of adult F1 fish , T7E1 digestion was performed and DNA sequencing was conducted to determine whether F1 adult fish carried DNA sequence alterations . klf4d5i1 F1 mutants containing a 5 bp deletion and 1 bp insertion in the sgRNA target site were crossed with wild-type fish to produce the F2 generation . A pair of primers ( forward: 5′-GCTCATTTCCCCAGCCGAGG-3′ and reverse: 5′-GTGTGTCCTGTGGTGGGCTTTCA-3′ ) were used for genotyping of F3 heterozygous or homozygous mutant embryos . Since klf4d5i1 homozygous embryos are viable , F4 homozygous adults were also maintained . Whole-mount in situ hybridization was conducted on embryos treated with 0 . 003% phenylthiocarbamide , using digoxigenin-labeled antisense RNA probes and alkaline phosphatase-conjugated anti-digoxigenin antibodies as previously described [47] . T7 RNA polymerase ( Thermal Fisher Scientific , Ambion Inc . , Waltham , USA ) was used to synthesize antisense RNA probes , using EcoRI- linearized foxi3a plasmid as a template . SP6 RNA polymerase ( Roche , Mannheim , Germany ) was used to synthesize antisense RNA probes , using NcoI-linearized atp1a1a . 1 , ApaI-linearized atp6v1aa , NcoI-linearized dlc , NcoI-linearized foxi3b , BamHI-linearized mCherry , or NcoI-linearized col1a1a . Whole mount immunofluorescence for Klf4 protein and fluorescence in situ hybridization for dlc mRNA was conducted on 3% H2O2 permeable embryos . Whole-mount in situ hybridization using a digoxigenin-labeled dlc RNA probe was conducted first at 60°C . After hybridization wash , embryos were blocked with 1% blocking reagent for 1 h before incubation with rabbit anti-Klf4 antibody ( 1:50 ) diluted in 1% blocking reagent at 4°C overnight . After PBST ( PBS + 0 . 1% tween 20 ) washes for 10 min four times , embryos were incubated with anti-rabbit Alexa-488 ( 1:200 , Thermal Fisher Scientific ) at room temperature for 3 h . Embryos were then washed with PBST and blocked with 2% blocking reagent for 1 h before incubation with anti-Digoxigenin-POD ( 1:500 , Roche ) diluted in 2% blocking reagent at 4°C overnight . After PBST washes , embryos were incubated with TSA-Cy3 ( 1:50 , Perkin Elmer ) diluted in Amplification buffer at 28°C for 1 h . Embryos were then washed with PBST , post fixation with 4% paraformaldehyde for 20 min , PBST washes and stored in 80% glycerol at 4°C . For labeling epidermal NaR and HR cells , 72 hpf-embryos were fixed with 4% paraformaldehyde at room temperature for 3 to 4 h . After two washes with solution ( PBS + 0 . 1% triton X-100 ) for 5 min each time , embryos were permeabilized with 100% ice-cold acetone at -20°C for 7 min . Embryos were then washed with dH2O and PBST several times , after which they were blocked with 10% serum for 1 h . Embryos were incubated with α5 monoclonal antibody against Na+-K+-ATPase ( 1:200 , Developmental Studies Hybridoma Bank , Iowa , USA ) or a polyclonal antibody against killifish H+-ATPase ( 1:200 ) [48] diluted with 10% serum at 4°C overnight . After PBST washes , embryos then treated with anti-mouse Alexa 488 antibody ( 1:200 ) or anti-rabbit Alexa 568 antibody ( 1:200 , Thermal Fisher Scientific ) diluted in 10% serum at room temperature for 3 h . Embryos were washed with PBST and stored in 80% glycerol at 4°C . Double immunofluorescence for Klf4 and p63 was conducted on embryos fixed with 4% paraformaldehyde for overnight at 4°C . After PBST washes and blocking with 1% blocking reagent ( Roche ) for 1 h , diluted anti-p63 ( 1:200 , Abcam ) antibody and anti-Klf4 ( 1:50 ) polyclonal antibody in 1% blocking reagent were added to embryos and incubated at 4°C overnight . Embryos were washed with PBST and incubated with diluted anti-mouse Alexa 488 antibody ( 1:200 ) in 0 . 5% blocking reagent at 4°C overnight . After PBST washes , embryos were incubated with anti-rabbit Alexa 568 antibody ( 1:200 ) in 0 . 5% blocking reagent at 4°C overnight . After PBST washes , embryos were stained with diluted Hoechst 33342 ( 1:1000 , Thermal Fisher Scientific ) in PBST for 30 min . After PBST washes , 4% paraformaldehyde fixation , and more PBST washes , embryos were stored in 80% glycerol at 4°C . Immunofluorescence on chimeric embryos was conducted on fixed BrdU-exposed bud embryos that had been stored in 100% methanol at -20°C . After rehydration and PBST washes , embryos were blocked with 2% blocking reagent for 1 h at RT . Embryos were then incubated with anti-fluorescein-POD in 2% blocking reagent ( 1:500 ) at 4°C overnight . After several PBST washes and a rinse with Plus Amplification Diluent ( Perkin Elmer ) , embryos were then incubated with TSA-fluorescein amplification reagent ( 1:100–1:150 ) in Plus Amplification Diluent at 28°C for 1 h . After PBST washes , embryos were incubated in 2N HCl for 20 min and washed with PBST several times . After blocking in 1% blocking reagent for 1 h at RT , embryos were incubated at 4°C overnight with rabbit anti-BrdU antibody ( 1:200; Abcam ) that was diluted in 1% blocking reagent . After several PBST washes , embryos were incubated with anti-rabbit Alexa-647 ( 1:200; Thermo Fisher ) in 0 . 5% blocking reagent at RT for 5 h . After PBST washes , embryos were incubated in mouse anti-p63 antibody ( 1:200 ) diluted in 1% blocking reagent at 4°C for one or two days . After several PBST washes , embryos were incubated in mouse Alexa-568 in 0 . 5% blocking reagent ( 1:200; Thermo Fisher ) at 4°C overnight . Embryos were then washed with PBST and incubated in Hoechst 33342 in PBST ( 1:1000 ) for 30 min at RT . After PBST washes , 4% paraformaldehyde fixation and more PBST washes , embryos were embedded in 1% low-melting agar for confocal imaging . Immunofluorescence for mCherry in Tg ( dlc11k:mCherry ) and Tg ( dlc3k:mCherry ) transgenic embryos was conducted on 4% paraformaldehyde fixed and dehydrated embryos . Embryos were rehydrated and washed twice with PBSTx ( PBS with 0 . 1% triton X-100 ) for 5 min . Embryos were then permeabilized with PBS containing 2% triton X-100 for 30 min at RT , after which the samples were washed twice with PBSTx for 5 min . After blocking in 1% blocking reagent for 1 h , embryos were incubated with rat anti-mCherry antibody ( 1:50–1:150; Thermo Fisher ) diluted in 1% blocking reagent at 4°C overnight . After several PBSTx washes , embryos were incubated with anti-rat Alexa-568 antibody ( 1:200 ) diluted in 0 . 5% blocking reagent at 4°C overnight . Embryos were then washed with PBSTx and fixed with 4% paraformaldehyde . Capped mRNA ( klf4 , klf4-7mm , klf4ΔC-7mm , klf4-Myc , X-Su ( H ) DBM , VP16-klf4 , engrailed-klf4 or LacZ ) was synthesized using either a T7 or SP6 mMESSAGE mMACHINE kit ( Thermal Fisher Scientific , Ambion Inc . ) . To ectopically express klf4 , klf4 mRNA ( 130–150 pg ) was injected into 1-cell zygotes , and the same amount of LacZ mRNA was injected for comparison . To rescue klf4 morphants , 1-cell zygotes were co-injected with klf4-MO1 and klf4-MO2 ( 3 ng each ) together with klf4-7mm ( 50 pg ) mRNA . Control embryos were co-injected with LacZ mRNA ( 50 pg ) and 3 ng each of klf4-MO1 and klf4-MO2 . To ectopically express X-Su ( H ) DBM , X-Su ( H ) DBM ( 1000 pg ) mRNA was injected into 1-cell zygotes of Tg ( dlc3k:mCherry ) or Tg ( dlc3kM:mCherry ) lines . Dechorionated embryos from 80% epiboly were incubated in egg water containing 10 mM BrdU and 15% DMSO for 20 min on ice and washed with egg water . BrdU treated embryos were allowed to grow to bud stage at 28°C before fixation with 4% paraformaldehyde at 4°C overnight . After washing with PBST , embryos were dehydrated through a methanol series and stored in 100% methanol at -20°C overnight . Embryos were incubated with 3% H2O2 in methanol for 30 min , rehydrated with a methanol series and washed with PBST . Whole-mount in situ hybridization using digoxigenin-labeled dlc antisense RNA was conducted first at 60 or 65°C . After hybridization washes , embryos were blocked with 2% blocking reagent at room temperature for 1 h before incubation with anti-digoxigenin-POD antibody ( 1:500 , Roche ) diluted in 2% blocking reagent at 4°C overnight . After PBST washes , embryos were incubated with TSA-Cy3 ( 1:50 , Perkin Elmer ) diluted in Amplification buffer at 28°C for 1 h . Once the reaction was completed , embryos were washed with PBST and incubated in 2N HCl for 20 min . Following PBST washes and blocking in 1% blocking reagent at room temperature for 1 h , embryos were treated with diluted anti-rabbit BrdU antibody ( 1:200 , Abcam ) and anti-mouse P63 antibody ( 1:200 ) diluted in 1% blocking reagent at 4°C overnight . Embryos were then washed with PBST and blocked in 1% blocking reagent at room temperature for 1 h before incubation with anti-rabbit Alexa-647 antibody ( 1:200 , Thermal Fisher Scientific ) and anti-mouse Alexa-488 antibody ( 1:200 ) diluted in 0 . 5% blocking reagent at room temperature for 5 h . After PBST washes , cell nuclei were stained with Hoechst 33342 ( 1:1000 ) in PBST for 30 min . Embryos were then washed with PBST , fixed with 4% paraformaldehyde , more PBST washes , and stored in 80% glycerol at 4°C . Rescue experiments were conducted by co-injection of 3 ng each of klf4-MO1 and MO2 with 50 pg klf4-7mm mRNA , 50 pg klf4ΔC-7mm mRNA , 9–12 ng of p53 MO or cdkn1a MO into 1–2 cell zygotes and embryos were allowed to develop to 80% epiboly stage before BrdU incubation . TUNEL staining was performed as described by the manufacturer’s protocol ( Roche ) with the following modifications . Embryos were permeabilized with 100% acetone at -20°C for 7 min . Embryos were incubated with alkaline phosphatase-conjugated anti-fluorescein antibody ( 1:5000 ) at 4°C overnight . After washing with PBST followed by NTMT solution ( 100 mM Tris-HCl , pH 9 . 5 , 100 mM NaCl , 50 mM MgCl2 , 0 . 1% Tween 20 ) , embryos were stained with NBT/BCIP in NTMT solution . Embryos were then stored in 80% glycerol . Images of embryos were taken using an AxioCam HRC camera on a Zeiss Axio Imager M1 microscope equipped with a DIC mode . High resolution fluorescent images were taken using a Leica TCS-SP5-MP confocal microscope ( Leica , Wetzlar , Germany ) . klf4-Myc ( 150 pg ) -injected or wild-type 5s stage embryos were dechorionated with pronase ( Sigma , Munich , Germany ) and washed with 1×PBS containing 1×proteinase inhibitor ( Roche ) , before being fixed with 37% formaldehyde ( final concentration of 1% ) at room temperature for 15 min . The embryos were then incubated with glycine ( final concentration of 125 mM ) for 10 min , and subsequently washed three times with ice cold PBS . Embryos were lysed by pipetting up and down in cell lysis buffer ( 10 mM Tris-HCl , pH 8 . 0 , 10 mM NaCl , 0 . 5% NP-40 and 1×proteinase inhibitor ) on ice for 15 min . After centrifugation , the nuclear pellet was resuspended in nuclei lysis buffer ( 50 mM Tris-HCl , pH 8 . 0 , 10 mM EDTA , 1% SDS and 1×proteinase inhibitor ) , and then pipetted up and down on ice for 10 min . Two volumes of IP buffer ( 16 . 7 mM Tris-HCl , pH 8 . 0 , 167 mM NaCl , 1 . 2 mM EDTA , 1 . 1% Triton X-100 , 0 . 01% SDS , and 1×proteinase inhibitor ) were added , and the resulting mixtures were aliquoted into tubes ( 200 μl per tube ) ; the aliquots were then sonicated using Bioruptor Pico sonicator ( diagenode , Seraing , Belgium ) with the following protocol: 3 repeats of 30 sec ON and 30 sec OFF for 5 cycles for six times . An average chromatin length of 300 bp was used . After sonication , sonicated lysates were centrifuged at 14 k rpm for 15 min , and supernatants were transferred to 1 . 5 mL tubes and incubated with 50 μl pre-cleaned Protein A agarose beads ( Invitrogen ) for 1 h at 4°C to remove nonspecifically-bound proteins . After centrifugation at 5 k rpm for 10 min , 50 μl supernatant was removed and used as input control . The rest of the supernatant was diluted 10-fold with IP dilution buffer , divided into two parts , and then incubated with either anti-Myc ( Cell Signaling , Beverly , USA ) , anti-Klf4 or anti-IgG antibody bound to Protein A agarose beads , at a 1:100 dilution at 4°C overnight . After centrifugation at 1500 rpm for 5 min , beads were washed sequentially for 15 min/buffer with ChIP wash buffer A ( 20 mM Tris-HCl , pH 8 . 0 , 2 mM EDTA , 1% Triton X-100 , 0 . 1% SDS , 150 mM NaCl ) , buffer B ( 20 mM Tris-HCl , pH 8 . 0 , 2 mM EDTA , 1% Triton X-100 , 0 . 1% SDS , 500 mM NaCl ) and buffer C ( 10 mM Tris-HCl , pH 8 . 0 , 1 mM EDTA , 0 . 5% NP-40 , 0 . 1% sodium deoxycholate , 0 . 25M LiCl ) , followed by two washes with TE solution at room temperature . Freshly prepared 200 μl elution buffer containing 0 . 1 M NaHCO3 and 1% SDS was added to beads , and then incubated for 15 min at 65°C . After centrifugation at 14 k rpm for 5 min , the elution step was repeated once more . Reverse cross-linking of eluted DNA and protein was performed by incubation in buffer containing final concentrations of 0 . 2 M NaCl and 0 . 2 μg/ μl RNase A ( sigma ) at 65°Covernight . Proteins were removed by a final 0 . 2 μg/ μl proteinase K ( Roche ) digestion at 65°C for overnight . After phenol/chloroform extraction , eluted DNA was precipitated using ethanol , and its concentration was determined using the Picogreen kit ( Invitrogen P7589 ) . The following primers were used for qPCR: dlc ( -296 to -287 ) forward primer: 5′-GTTGTGGTTAGCGTGGGTTTCCA-3′; dlc ( -296 to -287 ) reverse primer: 5′-GGGACTTTGGACCCTTCAGTTACG-3′; dlc ( -756 to -747 ) forward primer: 5′-TGCCGGTTTAACGACTCACACG-3′; dlc ( -756 to -7477 ) reverse primer: 5′-CGCGTGCCAAGCAATTCTCTAA-3′; dlc ( -998 to -989 ) forward primer: 5′-CACAAACCAAGATTGCGAAGCG-3′; dlc ( -998 to -989 ) reverse primer: 5′-GGTAAAGAGGGCGAAATGGTGG-3′; dlc ( -1101 to -1092 ) forward primer: 5′-AGAAAGCATGCAAGGTGTGGTGAT-3′; dlc ( -1101 to -1092 ) reverse primer: 5′-CGCTTCGCAATCTTGGTTTGTG-3′; the following primers were used for negative binding controls: dlc-nb forward primer: 5′- TCGTTCTGCTGGCGTGGG T-3′; dlc-nb reverse primer: 5′- TTACGCAACGCATGACCTTTCAG-3′ . To investigate the role of the KLF binding motif within -756 to -747 on dlc gene expression , 25 pg of dlc11k:mCherry , dlc3k:mCherry , or dlc3kM:mCherry plasmid and 25 pg of transposase mRNA were injected into 1 cell zygotes . Injected embryos were allowed to grow to adulthood . Positive F0 transgenic fish was screened by expression of mCherry and later crossed with wild type fish to generate F1 generation . F2 embryos of three transgenic fish lines obtained by crossing with wild-type fish were then analyzed for mCherry expression patterns at 5s stage . F2 embryos of Tg ( dlc3kM:mCherry ) were genotyping confirmed by sequencing . We produced chimeric embryos by transplantation as described [49] . A 3% solution of fluorescein-conjugated dextran ( MW 10 , 000 , Invitrogen ) alone or mixed with klf4 MO1 and MO2 was injected into 1-2-cell zygotes . Approximately 50 to 150 blastomeres from wild-type or both klf4 MO1 and klf4 MO2-injected embryos were transplanted into klf4-morphant or wild-type hosts at a region above the blastoderm margin at a developmental stage between sphere and 40% epiboly . The number of stained ionocytes or keratinocytes was determined using ImageJ software as follows: ( i ) an image was loaded in ImageJ; ( ii ) ‘Cell counter’ was selected from the ‘Analyze’ item in the Plugins menu; ( iii ) ‘Initialize’ was selected; ( iv ) the software output cell number was recorded . The ionocyte/keratinocyte domain areas in the yolk ball of bud embryos and in the yolk ball or yolk extension of 24 hpf embryos were quantified using ImageJ software as follows: ( i ) a scale bar image of appropriate magnification was loaded in ImageJ; ( ii ) a line was drawn over the scale bar to determine the conversion factor between pixel number and length; ( iii ) from the Analyze menu , ‘set scale’ was selected to define parameters , including distance in pixels , known distance , pixel aspect ratio and unit of length; ( iv ) a ‘polygon symbol’ was used to draw the outline of the yolk ball or yolk extension; ( v ) from the Analyze menu , ‘measure’ was selected to determine area . Values are presented as mean ± s . e . m . unless otherwise noted . Two-tailed Student’s t-test with unequal variance was performed in Microsoft Excel . | The skin epidermis of terrestrial vertebrates is composed of a stratified epithelium , and requires krüppel-like factor 4 ( KLF4 ) to establish a functional permeability barrier that protects animals from dehydration . In contrast , fish must tolerate variations in salinity and pH of the aquatic environment . As such , the fish skin epidermis is composed of keratinocytes and ionocytes , which transport ions and acid-base equivalents to maintain ionic and acid-base homeostasis of body fluids . In the present study , we used embryonic zebrafish as a model to investigate how Klf4 modulates the cell densities of matured ionocytes from early stem cell stages through the initiation of terminal differentiation by Dlc-Notch-mediated lateral inhibition . We showed that Klf4 promotes cell proliferation in epidermal stem cells , where it represses p53 expression and prevents cdkn1a/p21 induction . Additionally , Klf4 regulates the ionocyte progenitor population by directly repressing dlc expression and modulating lateral inhibition . Our findings describe novel roles for zebrafish Klf4 in ionocyte development and provide insights into the mechanism by which Klf4 regulates proliferation-differentiation balance in epidermal stem cells . | [
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"organisms",... | 2019 | Zebrafish Klf4 maintains the ionocyte progenitor population by regulating epidermal stem cell proliferation and lateral inhibition |
Candida albicans , a human fungal pathogen , undergoes morphogenetic changes that are associated with virulence . We report here that GAL102 in C . albicans encodes a homolog of dTDP-glucose 4 , 6-dehydratase , an enzyme that affects cell wall properties as well as virulence of many pathogenic bacteria . We found that GAL102 deletion leads to greater sensitivity to antifungal drugs and cell wall destabilizing agents like Calcofluor white and Congo red . The mutant also formed biofilms consisting mainly of hyphal cells that show less turgor . The NMR analysis of cell wall mannans of gal102 deletion strain revealed that a major constituent of mannan is missing and the phosphomannan component known to affect virulence is greatly reduced . We also observed that there was a substantial reduction in the expression of genes involved in biofilm formation but increase in the expression of genes encoding glycosylphosphatidylinositol-anchored proteins in the mutant . These , along with altered mannosylation of cell wall proteins together might be responsible for multiple phenotypes displayed by the mutant . Finally , the mutant was unable to grow in the presence of resident peritoneal macrophages and elicited a weak pro-inflammatory cytokine response in vitro . Similarly , this mutant elicited a poor serum pro-inflammatory cytokine response as judged by IFNγ and TNFα levels and showed reduced virulence in a mouse model of systemic candidiasis . Importantly , an Ala substitution for a conserved Lys residue in the active site motif YXXXK , that abrogates the enzyme activity also showed reduced virulence and increased filamentation similar to the gal102 deletion strain . Since inactivating the enzyme encoded by GAL102 makes the cells sensitive to antifungal drugs and reduces its virulence , it can serve as a potential drug target in combination therapies for C . albicans and related pathogens .
Candida albicans is a polymorphic fungus that causes infection of skin , nail , mucous membrane in healthy individuals and can lead to more severe infections of the vital organs in case of immune-compromised patients leading to death [1] . It is capable of growing in both yeast and hyphal forms and the yeast to hyphal transition has been reported to play a key role in virulence [2] . Environmental cues such as temperature , pH , serum , nutrient deprivation on solid media , etc . are known to trigger yeast to hyphal transition and in vitro studies have led to the identification of some of the key regulators such as CPH1 , EFG1 , INT1 , PRA1 , RBF1 , TUP1 , UME6 etc . [3]–[5] . In general , mutants of some of these regulators show reduced hyphal morphology that correlates with reduced virulence , suggesting a direct correlation of the hyphal form with virulence of C . albicans [6] . Surprisingly , mutations in genes like TUP1 and NRG1 ( global repressors of hyphal morphology ) also show reduced virulence in spite of increased hyphal morphology [7] . This observation has raised questions about the validity of the direct correlation of hyphal morphology and virulence [8] . The morphological forms also differ in the cell wall composition [9] . Cell wall is the first cell organelle that comes in contact with the host and plays an important role in determining the outcome of the host pathogen interaction . Therefore , alterations in the cell wall composition and the associated transcriptional program , than the shape of the cell , per se , that might be crucial to virulence of C . albicans . It has been reported that the cell wall architecture and virulence of microbial pathogens can be affected by presence of Galactose , a sugar that can act as a sole carbon source for many pathogens [10] . The effect of galactose on the biofilm development of C . albicans has been extensively studied . The rate of formation of biofilm is higher in the presence of galactose [11] . Further , galactose contributes to 3% of the dry weight of extra-cellular polymeric material of C . albicans biofilm [12] . Most organisms are able to metabolize galactose i . e . convert β-D-galactose to glucose 1-phosphate through four enzymes of the Leloir pathway which have been well characterized in E . coli and Saccharomyces cerevisiae [13] . The epimerase which catalyzes the third step in the Leloir pathway can clearly be an enzyme that may have a role beyond galactose metabolism , in that , the reversible reaction could be employed to generate galactose during growth on glucose as the sole carbon source . Indeed , various phenotypes are associated with mutations in this gene in different organisms [14] , [15] . In S . cerevisiae , lack of Gal10p prevents growth on galactose as the sole carbon source [16] although , it has no reported effect on growth in the absence of galactose . Previous work from our laboratory has shown that CaGAL10 ( orf19 . 3672 ) encodes a true homolog of UDP-galactose-4-epimerase and can functionally complement the S . cerevisiae gal10Δ [17] . We have shown that the ultrastructure of the biofilm of Cagal10 mutant is distinctly different from that of the wild type [17] . In Arabidopsis , the impairment results in root-specific phenotypes , including increased root hair elongation , decreased root length , and root epidermal bulging etc . [18] . In humans , impairment of galactose epimerase causes one of two clinically distinct forms of galactosemia , an autosomal recessive epimerase-deficiency syndrome [19] . The orf19 . 3674 which has been annotated as CaGAL102 in the Candida Genome Database , encodes a protein very similar to the epimerase domain of the CaGal10p . We have previously shown that the full length CaGal10p as well as its epimerase domain alone complements the S . cerevisiae gal10 deletion [17] . However , in light of a report [20] that Cryptococcus neoformans has two functional paralogs of GAL10 , we asked the following questions: Does CaGAL102 encode a functional galactose epimerase ? If yes , what is the significance of two Gal10 paralogs in C . albicans ? If it is not a functional epimerase what role does it play in C . albicans ? In the present study , we aimed to determine the role of this putative galactose epimerase in C . albicans using multiple experimental approaches . We found that the GAL102 actually encodes a UDP-glucose 4 , 6-dehydratase activity and its loss affects the composition of cell wall mannans . The mutant cells lacking the activity also showed several defects in phenotypes associated with virulence of C . albicans . The mutant cells elicited a differential cytokine response from host immune system cells in vitro as well as in vivo , which reflected in attenuated virulence in mouse model of systemic candidiasis . These observations are in agreement with the reports that cell wall mannans contribute to host responses elicited by fungal pathogens [21] , [22] . Our observations present a clear evidence for an enzyme activity that affects composition of cell wall mannans , cell morphology and contributes to virulence in C . albicans .
Orf19 . 3674/GAL102 in the Candida Genome Database has been annotated as a UDP-galactose 4-epimerase . Multiple sequence alignment of Gal102p with UDP-galactose 4-epimerase ( Gal10p ) homologs using the software ClustalW showed that the active site residues in the epimerase domain are highly conserved ( Figure 1A ) . Incidentally , CaGal10 shows 52% identity and ∼ 70% similarity to ScGal10p but Gal102p shows only 27% identity and 47% similarity . Most striking is the conservation of the YXXXK motif wherein the conserved tyrosine residue plays an important role during catalysis facilitating the transfer of a hydride from C4 of the sugar to C4 of NADH leading to a 4′-ketopyranose intermediate and NADH [23] . Most ORFs from C . albicans expressed in S . cerevisiae are able to complement loss of function mutants of corresponding homologs . To test whether GAL102 encoded protein has UDP-galactose 4-epimerase activity we sub-cloned the ORF under the constitutive TEF1 promoter on a multi-copy plasmid ( pMS643 ) . C . albicans uses an alternative genetic code with CUG codon encoding for Serine in place of Leucine of the universal genetic code . We replaced the only CUG codon with UCG to introduce Serine at the 314 position in the recombinant Gal102 ORF ( pMS861 ) and then tested its ability to complement the S . cerevisiae gal10 mutant strain PJB5 . The gal10 mutant is unable to grow in the presence of galactose as the sole carbon source . Transformants expressing the open reading frame grew on plates containing glucose as the sole carbon source but not in the presence of galactose ( Figure 1B ) . We tested the presence of this protein in cells transformed with pMS861 using Western blot analysis to confirm that the failure to complement was not due to poor or lack of expression of the heterologous protein ( Figure S1A ) . We further disrupted the GAL102 gene using a PCR based strategy as described earlier [24] and generated multiple isolate/mutants through independent transformations . We confirmed the deletion and the absence of the transcript by Southern and Northern analysis respectively ( Figure S1B ) . We tested these mutants for various phenotypes and have presented here representative data from one of these isolates . We found that the null mutant gal102Δ/Δ had growth rate similar to that of the WT in normal rich media ( YPD ) at 30°C ( data not shown ) . When spotted on YP glucose or YP galactose plates , the gal102Δ/Δ strain exhibited no growth defect ( Figure 1C ) while the gal10Δ/Δ mutant strain could not grow on galactose-containing medium [17] . This implied that the GAL102 gene does not play any significant role in galactose metabolism in C . albicans . It has been reported that the two paralogs of GAL10 in C . neoformans affect growth on galactose at different temperatures [20] . We saw no such difference in growth under suboptimal conditions such as high temperature or low galactose concentration in the absence of GAL102 ( data not shown ) . Since the deletion of GAL102 showed no effect on galactose metabolism and associated phenotypes , we repeated the homology search through NCBI databases . We found that Gal102p showed 32% identity to dTDP-glucose 4 , 6-dehydratase ( RmlB; Acc . No . AAB88398 ) of E . coli and 40% identity to the N-terminus of RHM2 ( 1–370 amino acids ) of A . thaliana . The latter has been biochemically shown to have UDP-glucose 4 , 6-dehydratase activity . The dTDP/UDP-glucose 4 , 6-dehydratase enzyme is known to be involved in rhamnose biosynthesis in bacteria as well as in plants [25] , [26] . Figure 2A shows the ClustalW alignment of Gal102p sequence with several other fungal homologs as well as those from E . coli and A . thaliana . The dTDP/UDP-glucose 4 , 6-dehydratase enzyme is a member of the SDR ( short chain dehydratase/reductase ) family of proteins , which have a highly conserved YXXXK motif , crucial for the enzyme activity . In case of A . thaliana , the RHM2K165A mutation completely abolishes UDP-glucose 4 , 6-dehydratase activity [26] . Lysine at position 159 in Gal102 lies within the putative catalytic motif , YXXXK . Therefore , we mutated it to alanine ( AAA to GCA codon ) as described in materials and methods section . We expressed the codon optimized Gal102p ( as described above ) and its mutant derivative Gal102pK159A in E . coli and purified the recombinant proteins . We assayed for the dehydratase activity by measuring NAD- NADH conversion at 340 nm using either UDP glucose or dTDP glucose as substrates . After 2 hr the native Gal102p showed significant activity with UDP glucose as the substrate but only very low activity with dTDP glucose as the substrate . This activity could not be detected with the same amount of Gal102K159A mutant protein ( Figure 2B ) . This confirmed that Gal102p actually encodes a UDP-glucose dehydratase activity and that the lysine ( Lys 159 ) in the conserved motif YXXXK , is essential for the activity of the enzyme . We observed that the cells of the gal102Δ/Δ strain were more elongated when grown in normal rich media ( YPD ) at 30°C as compared to the WT ( SC5314 ) strain ( Figure 3A ) . Thus , the deletion of GAL102 has an effect on cell morphology which is also reflected in the wrinkled colony morphology ( Figure S1C ) . When grown under hyphae inducing conditions , like growth in Lee's or Spider medium , the mutant showed much more enhanced filamentation as compared to the WT ( SC5314 ) . To establish that the loss of enzyme activity of the Gal102p is responsible for the phenotypes associated with the deletion , we replaced the gal102::HIS1 allele with either WT GAL102 or gal102K159A allele . All these strains thus have URA3 gene integrated at the GAL102 locus whose expression from non-native locus has been reported to be associated with attenuation of virulence . The morphology of these marker matched reintegrant strains was then tested in hyphal inducing media like Lee's medium and Spider medium . It was observed that ( Figure 3A ) WT GAL102 integrant at the gal102::HIS1 locus reduced the extent of filamentation close to that of the WT ( SC5314 ) strain . In contrast , the catalytically inactive gal102K159A integrant at the same locus continued to show high filamentation phenotype . This shows that the morphological phenotypes associated with the deletion are indeed due to the lack of the glucose dehydratase activity associated with the protein . We tested the sensitivity of gal102Δ/Δ strain to various cell wall damaging agents , e . g . SDS , Congo red and Calcofluor white as well as an antifungal antibiotic echinocandin . The mutant cells showed greater sensitivity to the cell wall damaging agents as compared to the WT ( SC5314 ) strain ( Figure 3B ) . The increased sensitivity to several cell wall damaging agents suggests that the cell wall composition of the mutant is altered in such a way as to affect the integrity of the cell wall . The antibiotic echinocandin specifically showed larger zones of inhibition as compared to the WT , signifying greater sensitivity of the mutant to this antibiotic supporting the observed cell wall integrity defect A bar graph consolidating three independent measurements of zone of inhibition at the indicated concentration underscores the significance of the observation ( Figure 3C ) . The above results indicated that the cell wall composition may be altered significantly in the gal102Δ/Δ mutant . Since the product of the Gal102 catalyzed reaction is a nucleotide sugar which might act as a sugar donor in cell wall protein glycosylation , we surmised , that the most likely target of the deletion was cell wall mannans which form the outermost layer of the C . albicans cell wall [9] . We analyzed the mannan composition of the mutant cell wall and compared it to that of the WT ( SC5314 ) . Earlier reports on NMR analysis of mannans from C . albicans cells have revealed differences among the yeast form and the hyphal form [9] . To ascribe the difference in mannan composition to the lack of Gal102 activity and not to the elongated cell morphology associated changes , we isolated mannans as described [9] from both the WT and the mutant cells grown at 25 °C at which the gal102Δ/Δ cells were much less elongated ( Figure S1D ) . In our studies we performed 1H NMR and 31P NMR to study presence/absence of linkages among the mannans , and TOCSY , ROESY and HSQC to study the details of gross defects in specific bonding . The anomeric region of the 1D 1H-NMR spectra of mannans from WT [ ( i ) ] , and gal102Δ/Δ [ ( ii ) ] are shown ( Figure 4A ) . A close observation of the corresponding proton NMR spectra revealed interesting differences in the structural assembly of mannan from the mutant as compared to WT . Both peaks #1 and #9 showed drastic reduction in the intensity . The former represents the loss or reduction of the entire β-1 , 2 link branched chain mannose units attached through phosphodiester linkage , and the latter , indicates the loss of considerable length of the α-1 , 6 backbone moiety . The internal change after the loss of α-1 , 6 backbone is reflected in the downfield shift of the peak 5 ( merged into peak 4 ) . The small , peak 3 which accounts for α-1 , 2 linked mannans in the acid-labile terminus is missing in the mutant . The mutant showed no change in the intensity of peak 10 suggesting the retention of the β-1 , 2 linked units ( in the side-chain of acid resistant- terminus ) . The analysis of 31P NMR spectra ( Figure S2 ) showed that the phosphodiester moiety in the side chain is absent in the mutant spectra implying that such linkage is either missing or substantially reduced . A comparison of 2-dimensional 1H-1H-total correlation spectra ( 2D-TOCSY ) of WT and the gal102Δ/Δ samples revealed significant difference in the spectra ( Figure 4B ) . The reduced peak a indicated the loss of phosphodiester linkage with the β-1 , 2 mannan moiety . Peaks b and c come from the correlations between β 1 protons on the PO4-linked mannans ( in the acid-labile region ) to their respective C-6 and C-2 protons which are reduced in the spectra of the mutant samples . Additionally , the loss of intensity in peaks d and e indicates lack or substantial loss of part of the α-1 , 6 backbone mannan skeleton ( revealing a reduction in the size of the α-1 , 6 backbone ) which was further supported by the analysis of 2D 1H-1H ROESY ( 2-dimensional 1H-1H Rotating-frame Overhauser Effect Spectroscopy ) spectra for both WT and the mutant ( Figure S3 ) . A detailed analysis of a 2-dimensional 1H-13C-Heteronuclear Single Quantum Coherence ( 2D 1H-13C-HSQC ) spectrum of WT and mutant samples revealed an interesting feature [Figure 4C ( i ) and ( ii ) ] . Peak a in Figure 4C ( i ) corresponds to α-1 proton ( δH 5 . 04 ppm; with its attached carbon , δC 101 . 73 ppm ) of the 1 , 3 , 6-trisubstituted mannan moiety in the α-1 , 3 linkage of the acid-resistant terminus . The absence of this peak in the spectra for mutant reveals that the mutation leads to the loss of α-1 , 3 mannan linkage in the acid-resistant terminus . Peak b belongs to α/β proton of the terminal mannan β-1 unit ( extreme left part of the α-1 , 6 backbone , see Figure 5 ) attached to α-1 , 2 mannose side-chain moiety missing in the mutant spectra , demonstrating the loss of entire α-1 , 2 side-chain in the acid-resistant terminal region of the mannan assembly . The significance of peak c has not been ascertained yet . The proton up-field region of the HSQC spectra [Figure 4C ( iii ) and ( iv ) ] indicates loss of a part of the α-1 , 6 backbone mannan assembly and highlighted peaks with red boxes indicate the appearance of new peaks in the spectra for mutant . These new peaks are attributed to C-2 , C-3 and C-6 protons/carbons of the β-1 , 2 mannose side-chain units in the acid-resistant terminus . The sharp and narrower peaks appearing in the anomeric proton regions of the HSQC spectra demonstrate reduction in chain length and other branching side-chains in the mutant sample . Thus , these observations offer details of the structure of the mannan assembly in C . albicans which corroborate published reports [9] and highlight the changes occurring in it upon deletion of GAL102 . Based on the above 1D as well as 2D NMR analyses we propose the mutant mannan structure to be much different than the WT mannan as shown in Figure 5 . The upper panel refers to the WT mannan structure as accepted in the literature [22] . Our study clearly shows that the length of the mutant mannan is substantially reduced and it lacks specific linkages in the branches including the phospho-mannans ( Figure 5 , lower panel ) . Significance of these alterations in relation to the other known mannosylation defective mutants is discussed below ( see discussion section ) . Since the mutant cells showed such distinct phenotypes as elongated cell morphology , and reduced cell wall integrity , we tested the genome wide expression profile of the mutant and compared it to that of the WT . Both WT and gal102Δ/Δ mutant were grown at 30°C in YPD till A600 = 1 . 2 and RNA was isolated from cells , labeled and used to probe the Agilent custom microarrays as described ( see Materials and Methods ) . In agreement with the filamentous morphology , the expression profile of the mutant cells showed several hyphal specific genes like HWP1 and a transcriptional regulator UME6 expressed at high levels while yeast phase specific genes like YWP1 were down regulated . Differential expression of some of the genes like HWP1 , YWP1 and GAL102 was validated using semi-quantitative RT PCR ( data not shown ) . The levels of transcripts encoding several ( characterized as well as putative ) GPI-anchored proteins , e . g . ALS7 , PGA31 , PGA37 , RBR1 etc . were high in the mutant . While a negative regulator of hyphal morphology NRG1 was also found to be up-regulated ( Table 1 ) ; several genes known to play a role in biofilm formation , along with genes like CHK1 , CRK1 , RRH2 , SOD4 etc . that contribute to virulence of C . albicans , were significantly down-regulated ( Tables S1 , S2 in Text S1 ) . While the gene expression profiling showed genes being expressed as expected from the observed phenotypes , it also provided hints that some of the other attributes associated with virulence such as biofilm formation and survival in disseminated candidiasis mouse model may be altered in the mutant . Apart from the GPI anchored protein coding genes and those involved in biofilm formation , several classes of genes also showed differential expression such as those encoding proteins intrinsic to membrane ( GO:31224 ) , α1 , 3 mannosyl transferase activity ( GO:331 ) , etc . Several genes associated with cell wall ( GO: 5618 ) were also highly overexpressed . Since the cell wall mannans constitute the outermost layer of the C . albicans cell wall we expected that the altered mannan composition might alter interactions with the host cells . The outcome of the interaction between phagocytic cells such as macrophages and pathogens such as C . albicans can be studied using cell viability assays in vitro [27] . To study the response of macrophages to gal102Δ/Δ strain , both WT and gal102Δ/Δ mutant cells were incubated with mouse resident peritoneal macrophages and their growth was monitored at indicated time points . At 6 hr , there was no difference in the growth as measured by the CFU numbers , in the presence or absence of macrophages . However , by 18 hr there was a slight reduction in the growth of gal102Δ/Δ strain in the presence of macrophages and by 30 hr there was a substantial reduction in the proliferation relative to cultures without macrophages . The WT strain , on the other hand , proliferated to the same extent in the presence or absence of macrophages ( Figure 6A ) . This inhibition of growth of the gal102Δ/Δ strain in the presence of macrophages is illustrated in micrographs ( Figure 6B ) . These observations demonstrate that resident macrophages suppressed the proliferation of the gal102Δ/Δ strain but not WT C . albicans . To determine cytokine response mediated by WT and gal102Δ/Δ in vitro , live and heat-killed C . albicans strains were incubated with resident peritoneal macrophages for varying time points . Incubation of macrophages with live WT Candida induced 3–4 fold higher levels of TNFα and IFNγ compared to the gal102Δ/Δ strain and the amounts steadily increased from 6 to 30 hr ( Figure S4A and B; left panel ) . In case of heat-killed Candida , the levels were reduced but differences in the cytokine amounts between WT and gal102Δ/Δ were still significant ( Figure S4A and B; right panel ) and reflected the same pattern as that induced by the live cells . Interestingly , the gal102Δ/Δ strain induced higher amounts of IL4 production compared to that induced by WT ( Figure S4C ) . These observations demonstrate that peritoneal macrophages elicit distinct cytokine patterns in response to WT and the gal102Δ/Δ strains . The problem in treating Candida infection becomes more complicated when it adheres to host surface or to the inner walls of catheters in patients and forms a biofilm , which is resistant to a variety of antifungal agents [28] . The biofilm formed by the WT strain is made up of both the yeast and the hyphal forms and the mutants that are unable to show yeast to hyphal transition , do not form effective biofilms [28] . The ability of gal102Δ/Δ , which shows predominantly elongated cell morphology , to form biofilm was determined using protocols described previously [17] . The WT SC5314 cells formed biofilm which consisted of a mixture of yeast form and filamentous cells which appear healthy and exhibit turgor ( Figure 7 ) . Although the ability of the gal102Δ/Δ to form biofilm was not affected , the ultrastructure observed under a scanning electron microscope was quite different ( Figure 7 ) . In case of the gal102Δ/Δ mutant strain , the biofilm consisted mainly of elongated cells that showed relatively less turgor , which could reflect weakened structure of the cell wall . The WT reintegrant biofilm showed presence of much higher proportion of yeast form cells as observed in case of biofilms formed by DAY286 WT strain ( data not shown ) . The mutant reintegrant showed biofilm comparable to that of the gal102Δ/Δ strain . To test the effect of alteration in the cell wall mannan composition on virulence of the gal102Δ/Δ , we performed intravenous injection into the lateral tail vein of female BALB/c mice with the WT and the gal102Δ/Δ strain . To ensure that high filamentation of gal102Δ/Δ strain does not lead to clogging of the tail vein during injection , or lead to inaccurate estimation of cell numbers we grew both WT and gal102Δ/Δ strain at 25°C . As mentioned earlier , at this temperature gal102Δ/Δ strain exhibited much less elongated cell morphology ( Figure S1D ) . The resulting survival curves demonstrate that virulence of gal102Δ/Δ strain is greatly reduced . At 5×106 cells of WT C . albicans per animal , 50% of the mice died within 3–4 days and the rest by 6 days ( Figure 8A ) . However , ∼80% or more of mice injected with the gal102Δ/Δ strain survived the entire 30 day duration of observation ( data not shown ) . As mentioned above , the gal102Δ/Δ and the WT and the gal102K159A reintegrant strains , all have URA3 gene integrated at the gal102 locus . We tested the virulence of these genotype matched strains in a mouse model of systemic candidiasis test as before . The clinical isolate SC5314 which is routinely used as the standard for virulence studies showed that it kills the host with faster kinetics than the DAY286 , a strain with URA3 reintegrated at the ARG4 locus . This is consistent with earlier reports that the DAY286 strain is ∼70% as virulent as compared to SC5314 [29] . As seen in the survival curve ( Figure 8A ) , the WT reintegrant showed virulence levels comparable to the WT DAY286 strain while the mutant gal102K159A reintegrant strain , as expected , showed low virulence , comparable to the gal102Δ/Δ parent strain . These results clearly show that the deletion/inactivation of GAL102 , is responsible for the alteration in morphology as well as compromised virulence and not the expression of URA3 gene from a non-native locus [30] . To evaluate whether reduced virulence of gal102Δ/Δ strain was due to its reduced multiplication in vivo , in a parallel set of experiment mice infected with both WT and mutant were sacrificed and fungal colonization of both , kidney and liver , the major target organs in systemic candidiasis , was determined . Increased fungal burden was observed in WT-infected mice from 24 hr to 60 hr after initiation of infection . On the other hand , CFUs recovered from the kidney and liver of mice infected with the gal102Δ/Δ strain were significantly lower than the WT and steadily decreased with time ( Figure 8B and C ) . Both the reintegrants showed expected phenotypes similar to the WT and gal102Δ/Δ strains respectively . The Candida cells isolated from kidneys of mice infected with the gal102Δ/Δ strain clearly showed the wrinkled colony morphology characteristic of the mutant strain ( data not shown ) confirming the presence of the mutant in the infected hosts . The other markers of kidney and liver damage namely elevated levels of serum urea [31] and of the enzyme alanine aminotransferase ( ALT ) [32] were also monitored in case of mice infected with either the WT ( SC5314 ) or the gal102Δ/Δ mutant and corroborated the damage to these organs by the WT but not the gal102Δ/Δ strain ( Figure S5A and B ) . The liver sections from the control ( PBS-treated ) mice revealed normal hepatic architecture whereas mice infected with WT C . albicans showed necrotic patches . Moreover , the kidney sections of WT infected mice showed damage probably due to an excessive inflammatory response . In WT kidney , massive sloughing of the tubular epithelial cells into tubular lumen and deposition of tubular casts was observed compared to PBS and gal102Δ/Δ . Intra-tubular infiltration of inflammatory cells was also high in WT compared to PBS and gal102Δ/Δ . In WT infected liver , significant infiltration of the inflammatory cells around the peri-arterial space was observed compared to the PBS and gal102Δ/Δ . The hepatocytes around the peri-arterial space also exhibited nuclear pycnosis and hydrophobic degeneration in WT compared to PBS and gal102Δ/Δ group . However , liver of mice infected with the mutant strain did not display any necrotic regions or infiltration in the kidney by cells involved in inflammatory response and was comparable to PBS treated mice ( Figure 8D and E; Figure S6A and B ) . These observations demonstrate that WT infection causes organ damage which is not seen upon infection with gal102Δ/Δ . The observation that the gal102Δ/Δ cells displayed reduced virulence led us to study their ability to elicit cytokine production . Mice were injected ( as above ) with equal number of cells of WT ( SC5314 and DAY286 ) , gal102Δ/Δ , and the GAL102 or the gal102K159A mutant reintegrants in gal102Δ/Δ strain and sacrificed at various intervals . The amounts of different cytokines in serum were monitored by ELISA . We observed that the amounts of the pro-inflammatory cytokines , TNFα and IFNγ were significantly higher in mice infected with WT than those infected with gal102Δ/Δ strain ( Figure 9A and B ) . It is interesting that IFNγ amounts were initially high and decreased later; however TNFα was induced early and remained high for the WT . At the later time points , the lowered IFNγ amounts correlated with increase in the anti-inflammatory cytokine IL-4 . In striking contrast , infection with the gal102Δ/Δ strain was characterized by a rapid and increased production of IL-4 ( Figure 9C ) . These experiments demonstrate that infection with the gal102Δ/Δ strain resulted in an altered cytokine response in the host . The WT cells elicited high levels of pro-inflammatory cytokines , such as TNFα and IFNγ , whereas these cells elicited much higher levels of anti-inflammatory cytokine response , e . g . IL-4 ( Figure 9A–C ) . This was also true with the WT and the mutant reintegrant indicating that the activity of the enzyme was restored in the WT reintegrant and lack of which in the mutant reintegrant is responsible for the observed opposing effects on cytokine production .
Cell wall is the major organelle of a pathogen that comes in contact with the host cells and plays an important role in the outcome of the host-pathogen interaction . Many studies have revealed that the major components of the fungal cell wall such as mannans , glycans and proteins all contribute to morphology as well as the host response elicited by the pathogen . The mutants of C . albicans which lack specific components of mannan , the outermost layer of the cell wall , show reduced virulence indicating subtle contributions of individual components to virulence [34] . The two morphological forms of C . albicans , the yeast and the hyphae , are known to differ in the proteins associated with the cell wall , as well as the mannans which greatly contribute to the host response [34] . Several mutants have been studied which show alterations in various features of the cell wall . It has been reported that the och1 mutant is defective in outer , branched N-linked glycans [35] . The mnt1 mnt2 mutant lacks all the 4 terminal O-linked α1 , 2-mannosyl residues , but has normal N-linked mannan [36] . The pmr1 mutant has defects in both N- and O-linked mannosylation [37] and the mnn4 mutant lacks phosphomannan [38] . While the gal102 mutant lacked the phosphomannan like the mnn4 mutant , it showed substantially reduced levels of the O-linked mannosyl residues and had less drastic effect on the N-linked mannan as compared to the pmr1 mutant . Thus , the gal102 mutant displayed a mannan profile that is distinct from any of these above mentioned known mannosylation defective mutants ( Figure 5 ) . Cell wall has been considered a dynamic rather than a static assemblage of macromolecules and recent studies have indicated that the Candida cells exhibit altered mannoprotein composition in response to environmental stimuli [39] . Our genome-wide differential gene expression studies of the mutant showed that a large number of hypha-specific genes were upregulated while yeast form-specific Ywp1 protein was clearly downregulated which is commensurate with the morphology of the cells and increased tendency of the mutant cells to show hyper-filamentation . Among the classes of downregulated genes , the most significant were membrane protein encoding genes as well as those involved in biofilm formation . Interestingly , among the over expressed genes under the categories like cell wall ( p = 4×10−8 ) hyphal cell wall , carbohydrate metabolism etc . were much higher and most significant . Some of the genes encoding cell-surface proteins such as ALS2 , ALS9 which are known to be expressed during infection were also found to be downregulated while ALS6/ALS7 appear to be upregulated . It has been suggested that in response to cell wall integrity defects some compensatory mechanisms cause increase in expression of several cell wall proteins [40] . In the gal102Δ/Δ mutant the genes coding for GPI-anchored cell wall proteins showed increased expression levels . It has been known from work based on S . cerevisiae system as well , that expression of GPI-anchored proteins is drastically altered when cell wall synthesis is defective [40] . It has been suggested through many studies that cell wall is an important organelle in fungi , whose complex structure is carefully managed by the cell and altered according to various environmental and internal cues . The cell wall composition in turn affects survival of the fungal cell in the host as it elicits specific response from host immune system . Mammalian hosts can respond to the presence of a pathogen by producing a variety of inflammatory molecules which help curtail the infection . These can be categorized into two broad groups: those involved in pro-inflammatory responses ( e . g . TNFα & IFNγ ) and anti-inflammatory responses ( e . g . IL4 & IL13 ) . The balance of pro- and anti-inflammatory response is thought to be important for the outcome of fungal infections . TNFα , a pro-inflammatory cytokine is a key mediator in protecting against disseminated candidiasis , as demonstrated by the fact that the lack of TNFα worsens the course of disseminated candidiasis [41] . Furthermore , IFNγ another pro-inflammatory cytokine is thought to play a dual role during candidiasis . On one hand , it is required for host resistance as shown in studies using Ifnγ−/− mice [42]; on the other hand , excess IFNγ production during infection leads to host damage leading in turn , to increased susceptibility to C . albicans [43] . Most importantly , dendritic cells pulsed ( ex vivo ) with yeast cells , when transferred into mice , protect them from challenge with C . albicans [44] . This protection was not observed with dendritic cells pulsed with hyphal cells . These studies clearly underscore the importance of pro-inflammatory cytokines in the host resistance to C . albicans infection . There are conflicting reports on the role of IL-4 during candidiasis . One report involving intra-peritoneal challenge with C . albicans blastoconidia showed that IL-4 was not involved in resistance [42] . However , the unrestrained IFNγ response during early stages of C . albicans infection in Il4−/− mice , leads to resistance and only at later stages are the Il4−/− mice susceptible due to failure in mounting a strong Th1 response . In fact , treatment with exogenous IL4 boosts immunity against C . albicans [45] . The gal102 mutant showed virulence defect in disseminated mouse model system and the same reflected in its inability to grow in the presence of macrophages in vitro . In vitro as well as in vivo studies showed that the mutant was unable to induce pro-inflammatory cytokine production in contrast to that observed with WT C . albicans infection . This was indeed surprising since reduced pro-inflammatory cytokine response could be expected to increase survival of the pathogen in the host . It is well known that C . albicans yeast and the hyphal forms elicit different responses from the host immune system with the yeast form inducing pro-inflammatory cytokines , and the hyphal form inducing anti-inflammatory cytokines [34] , [44] . The high pro-inflammatory cytokine response is required for host defence; however excessive inflammatory responses cause damage to the host [46] , [47] . The better survival and growth of the WT pathogen in the host leads to increased production of pro-inflammatory cytokines , resulting in excessive tissue damage . On the other hand , it is possible that the defective cell wall of gal102 mutant renders these cells susceptible to killing by host cells ( Figure 6 ) and at the same time lower levels of pro-inflammatory cytokines induced by the mutant cause reduced tissue damage ( Figure 8D and E ) resulting in increased host survival ( Figure 8A ) . The gal102 mutant induces increased production of IL4 , an anti-inflammatory cytokine which is responsible for the increased killing and reduced growth of mutant cells ( Figure 9 ) . These results clearly underscore the important roles of pro- and anti-inflammatory cytokines , which have major implications in terms of immunity against fungal pathogens . In C . albicans marker gene expression has been shown to be drastically affected depending on the locus of integration . Among the most favorite of the marker genes viz . URA3 gene in C . albicans has been shown to affect virulence attributes depending on its chromosomal location [30] . Re-integration of the WT ORF and the catalytically inactive mutant ORF in the native locus allowed us to compare the phenotypes of the deletion mutant irrespective of the URA3 expression levels since all the three strains , i . e . gal102Δ/Δ and the WT or mutant reintegrant carried the URA3 marker at the GAL102 locus . The WT reintegrant showed rescue of most phenotypes tested e . g . filamentous morphology , virulence attributes and the cytokine response elicited by the mutant , while the catalytically inactive mutant with only a single lysine to alanine change in the YXXXK motif showed phenotypes akin to the parent gal102Δ/Δ mutant . In summary , our characterization of gal102 , a putative paralog of UDP-galactose 4-epimerase in C . albicans , has led to the conclusion that it is not a galactose epimerase . Although sequence analysis reveals that it is a member of the Short chain dehydratase reductase ( SDR ) family , whose members have a conserved , glycine rich , NAD/NADP-binding motif as well as a catalytic YXXXK motif [48] . The present study for the first time has presented evidence that a fungal homolog actually possesses the UDP-glucose 4 , 6-dehydratase activity . Yet , the homologs of enzymes participating in the subsequent steps involved in rhamnose biosynthesis have not been identified and the product rhamnose has not been detected in C . albicans or other related fungi . This raises a distinct possibility that Gal102p may not be involved in the rhamnose biosynthetic pathway in these fungi . It is known that nucleotide sugar moieties are used as sugar donors in glycosylation reactions . Since we have observed significant differences in the mannosylation profile of the mutant , it is possible that this enzyme functions upstream of a variety of glycosylation reactions involved in cell wall protein mannosylation in C . albicans and many of the related fungal pathogens . We have shown here that in C . albicans , the absence of the activity affects cell wall mannans , cell wall integrity and morphology with consequences on survival in the host and virulence . The product of this enzyme activity likely acts as a donor of sugar residues in the synthesis of mannans and might affect GPI anchoring of proteins which are known to affect cell wall integrity and morphology of cells [49] , [50] . We speculate that loss of cell wall integrity might trigger over-expression of several GPI proteins as a salvage response . The mutant with reduced cell wall integrity is also more susceptible to extracellular killing in the host as compared to WT cells . At the same time altered mannan composition elicits weaker pro-inflammatory cytokine response reducing host tissue damage and further allowing host to survive longer to be able to overcome the infecting mutant cells . The WT cells , on the other hand , can cause greater mortality due to the increased tissue damage induced by high levels of pro-inflammatory cytokines . Hence , in spite of the elongated cell morphology , the gal102 mutant remains avirulent . Perhaps , it's not the cell morphology , but the composition of the cell wall that plays a key role in virulence . Interestingly , CaGAL102 was not included among the 674 target genes studied by Noble et al . [51] as those likely to be involved in virulence of C . albicans . It turns out that this study had excluded genes that had sequence homologs in either S . cerevisiae or S . pombe , two of the well-studied non-pathogenic yeasts . CaGal102p is highly homologous to the protein encoded by the S . pombe gene SPBPB2B2 . 11 and recent phylogenetic analysis of GAL cluster has indicated that S . pombe might have acquired the entire GAL cluster including CaGAL102 homolog from a Candida species [52] . Hence it is not surprising that the above interesting study [51] missed CaGAL102 as one of the genes affecting virulence of C . albicans . It is also well known that genes whose products contribute to virulence can have homologs in related non-pathogenic microorganisms and , thus , are not necessarily unique to the genomes of pathogens . Assigning the direct role of the biochemical activity of CaGal102p in virulence of the fungal pathogens will require further in-depth studies through biochemical , genetic and molecular analyses .
All experiments involving mice were conducted in compliance of the Ministry of Environment and Forests Act on breeding of and experiments on animals ( control and supervision ) rules , 1998 . Mice were housed in the Central animal facility of IISc and studies were performed as per the guidelines laid out by the institutional animal ethics committee , IISc ( permit no . CAF/Ethics/174/2009 ) . The Central animal facility is accredited to the Ministry of Environment and Forests , Government of India . The guidelines followed are approved in consultation with the Committee for the purpose and control and supervision of experiments on animals ( CPCSEA ) can be seen in detail in the following document: http://envfor . nic . in/divisions/awd/cpcsea_laboratory . pdf . The C . albicans strains used in this study are listed in Table 2 . Standard growth media were used for C . albicans . Details of composition are provided in supplementary methods section . Prior to challenge in the animal model , a suspension was made by transferring to YPD broth and incubating at 30°C with shaking for a period of 16–24 hr . The S . cerevisiae strain was transformed with the plasmid constructs listed in Table 3 to generate the appropriate strains assayed for various phenotypes in this study . In all assays such as mouse infection , etc . where number of cells is critical , the cells were counted using hemocytometer . Female BALB/c mice , aged 6–8 weeks and weighing ∼18–25 g , were obtained from the Central Animal Facility , Indian Institute of Science , Bangalore . All mice received care according to institutional guidelines and were maintained under controlled conditions and fed with a standard diet . GAL102 ( http://www . candidagenome . org/ ) was amplified with the CaputGAL10 ( f ) and CaputGAL10 ( r ) primers . The 963 bp fragment was cloned in pGEM-Teasy vector ( Promega ) to construct pVM602 . pVM603 ( pGAL1-ORF19 . 3674 ) was constructed by cloning of pYES2 ( Invitrogen ) . pMS643 ( pTEF1-ORF19 . 3674 ) was constructed by cloning BamHI/XhoI insert from pVM603 in the same sites in pPS189 . The construct thus obtained was used to transform S . cerevisiae gal10 deletion strain , PJB5 . Codon optimized CaGAL102 was also cloned in the same sites in pPS189 ( pMS861 ) and transformed in pJB5 . A list of all the plasmids generated during this study is provided in Table 3 . To generate K159A mutation in Gal102 , the first 490 bp of the wildtype open reading frame was amplified using Pfu ( Fermentas ) with primers CaputGAL10 ( f ) and Gal102 _int _r ( Table 4 ) harbouring the TTT to TGC change in the primer . The remaining 473 bp was amplified using Pfu ( Fermentas ) using primers Gal102 _int _f harbouring the AAA to GCA change and CaputGAL10 ( r ) . The final product was generated by overlap PCR using Pfu using primers CaputGAL10 ( f ) and CaputGAL10 ( r ) and cloned in pBSKS ( Promega ) in EcoRV site thus generating plasmid pMS833 The clone had K159A mutation in the Gal102 open reading frame and this was confirmed by sequencing . The Gal102 K159A open reading frame was released as a BamHI-XhoI fragment from pMS833 and subcloned in pSJ821 in BglII-XhoI sites thus generating plasmid pMS834 . In order to express CaGal102 in E . coli , the only CUG codon in Gal102 ( seventh codon from the C- terminus ) was converted to other serine encoding codon to compensate for the alternative genetic code in C . albicans . The ORF was amplified using Caput Gal10 ( f ) and a reverse primer Gal102 CTG* r using Pfu polymerase ( Fermentas ) and cloned in pBSKS . The mutant CaGal102 hereafter referred to as Gal102CTG* , was further subcloned in pET32 ( a ) to generate plasmid pMS836 . To express the catalytic mutant in E . coli , the mutant ORF was PCR amplified using primers Ca put Gal10 ( f ) and Gal102 CTG* r from pMS833 ( described above ) and cloned in pET32 ( a ) thus generating plasmid pMS838 ( Table 3 ) . The lithium acetate procedure as described previously was used to transform C . albicans [53] and S . cerevisiae [54] . For Nourseothricin based plasmids transformation was done by electroporation and selected on plates containing 200 µg/ml of nourseothricin at 30°C [55] . Protein extracts were prepared from PJB5 cells transformed with pPS189 and pMS643 by glass bead lysis method . Protein samples were quantified using Bradford Reagent ( Sigma ) and approximately 50 µg of total protein was electrophoresed in 12 . 5% SDS-PAGE transferred to ImmobilonTM-P Transfer Membrane ( Amersham ) , and probed with rabbit polyclonal 1° antibodies raised against bacterially expressed orf19 . 3674p . The blots were probed with HRP-conjugated anti-rabbit 2° antibody ( Sigma ) and developed using Western Lighting TMChemiluminescence Reagent plus ( Perkin Elmer ) and X-ray film reagents . Strains were grown in YPD and YPGal at 30°C . Overnight saturated cultures were diluted in their respective media to an A600 of 0 . 1 and were allowed to grow until the A600 reached 1 . 2 following which total RNA was extracted as described below . WT SC5314 cells were induced to form hyphae using various hyphae inducing media described above . RNA was isolated by hot phenol method using liquid nitrogen [56] . RNA samples were quantified by measuring the absorbance at 260 nm and equal amounts of RNA were run on a 1% agarose-formaldehyde gel to check the quality . Total RNA was used for Genome wide expression profiling through Genotypic technology . Agilent's C . albicans custom arrays ( AMADID 16356 ) were used and hybridized with the cDNAs that were labeled using the Agilent's RNA linear amplification kit following manufacturer's protocol . Two biological replicates were used for both WT and mutant NA samples and single color hybridization was performed on four independent arrays . The differentially expressed genes were identified using Genespring software based normalization methods ( Typically LOWESS method was applied for array wide normalization and only mutant/WT ratio of >2 or <0 . 5 was considered as significant differential expression ) . The entire data has been deposited at the GEO database and can be accessed at http://www . ncbi . nlm . nih . gov/geo/query/acc . cgi ? acc=GSE20883 . ( Text S2 ) . Biofilms were produced as described [57] and biofilm permeability assay was performed as described [17] . The concentration of echinocandin used for this assay was 300 µg/ml and 600 µg/ml . Biofilm developed was fixed with 4% ( v/v ) formaldehyde made in 1X phosphate buffer ( pH 7 . 5 ) for 15 min followed by washing with 1X phosphate buffer . Then the biofilm was treated with 1% osmium tetroxide made in 1X phosphate buffer for 1 hr in dark . Then the subsequent dehydration steps with ethanol were carried out as follows: 70% for 10 min , 95% for 10 min , 100% for 20 min , followed by air drying in a desiccator overnight prior to gold coating in a sputter . Cultures were grown in 5 ml of YPD medium until the exponential phase and then diluted to an optical density at 600 nm ( OD600 ) of 0 . 5 . Each undiluted culture and its four 10 fold serial dilutions were spotted onto YPD plates containing the following: Calcoflour White ( 10–40 µg/ml ) , sodium dodecyl sulfate ( SDS; 0 . 005–0 . 04% ) , Congo red ( 5–30 µg/ml ) . Growth differences were recorded after incubation of the plates at 37°C for 72 hr . Candida strains were grown at 30°C for 36 hr with shaking in YPD medium containing 1% yeast extract , 2% peptone and 2% dextrose . Mannan was extracted from the cells with water at 120°C in an autoclave for 3 hr [9] . Briefly , after centrifugation the supernatant was treated with equal volume of Fehling's reagent for a short term precipitation . The copper-mannan complex was dissolved in 3N HCl and further precipitated drop-wise in Methanol: Acetic acid ( 8∶1 ) solvent . The carbohydrate was dried , dissolved in water , purified and then lyophilized till further use . The mannans obtained so from the above mentioned procedure were then subjected to NMR analysis ( all NMR studies were carried at the NMR Facility , Piramal Life Sciences Ltd . , Mumbai , India ) . All NMR spectra were recorded for a solution sample of each ( purified and lyophilized ) mannan in 700 µl of deuterium oxide ( D2O ) at 40°C using BrukerAvance 500 MHz spectrometer equipped with z-gradient triple resonance ( 1H , 13C , X ) probe . Acetone ( δH 2 . 17 ppm ) was used as an internal standard for the spectral referencing . The 2D TOCSY spectra ( pulse , mlevphpr ) were recorded containing 256 increments , consisting of 64 scans . The mixing time for each spectrum was set to 100 ms . 2D 1H-13C HSQC ( pulse , hsqcetgp ) ) spectra were composed of 256 increments consisting of 64 scans . 2D ROESY spectra were acquired using a pulse sequence roesyphpr , with 256 increments consisting of 128 scans . 1D NMR spectra were recorded suing a standard pulse sequence , zg30 . The 31P NMR spectra were recorded on Bruker 300 MHz spectrometer equipped with a BBO probe at the Piramal Life Sciences Ltd . research facility , Mumbai . Orthophosphoric acid was used as an external standard ( δ31P 7 ppm ) for 31P NMR . All spectra were processed and analyzed using Topsin ( version 2 . 1 , Bruker , March 2007 ) program package . Cells were isolated from the peritoneal cavity of mice by flushing with 5 ml of ice-cold 0 . 32 M sucrose . 2×105 cells/well were seeded in 96-well flat-bottom tissue culture plates in 100 µl/well culture medium ( RPMI 1640 , 5% FBS , 2 mM L-glutamine , 100 U/ml penicillin , 100 µg/ml streptomycin , 10 µg/ml gentamycin , 10% nonessential amino acids , 10% HEPES , 10% sodium pyruvate , 50 µM 2-ME ) . After incubation for 2 hr at 37°C with 5% CO2 , wells were washed with medium to remove non-adherent cells and adherent cells were used for subsequent co-culture studies with C . albicans strains . Adherent resident peritoneal macrophages were incubated with 100 µl of various strains of live or heat-killed ( 30 min at 75°C ) C . albicans cells at a concentration 104 cells/ml . Supernatants were harvested at different time points ( 6 , 18 and 30 hr ) and stored at –80°C until analysis of cytokines . The experiments were performed in triplicate with samples from three mice . The differences between strains were analyzed by using the Student's t test , and the level of significance was set at p < 0 . 05 . Age-matched mice were challenged intravenously with 5×106 C . albicans WT ( SC5314/DAY286 ) , gal102Δ/Δ , or WT or gal102K159A re-integrants in gal102Δ/Δ per mouse via lateral tail vein injection in 100 µl PBS . Control mice were injected with 100 µl PBS as vehicle control . Cohorts of five mice per C . albicans strain were inoculated for survival study . Mice were monitored daily for signs of morbidity ( weight loss , ruffled fur , hunched appearance , and decreased activity ) . For the tissue burden assays same dose was injected as above ( five mice per strain per experiment ) and mice were sacrificed at varying time points ( 24 , 42 and 60 hr ) post-infection . Kidney and liver from individual mice ( three to five mice per group ) were removed aseptically , weighed and homogenized in 1X PBS buffer using homogenizer . CFU was determined by plating serial dilutions on YPD agar medium . The colonies were counted after 24 hr at 37°C , and results were expressed as log CFU/g tissue . These experiments were performed thrice with 5/6 mice per group . For histological examinations the kidney and liver tissues were dissected , fixed in 10% neutral formalin buffer and embedded in paraffin wax . The sections were mounted on slides and stained with haematoxylin-eosin ( H&E ) . Examination was performed under a light microscope and photographs were taken by Nikon camera fitted to the microscope . The mice injected with WT ( SC5314/DAY286 ) , gal102Δ/Δ , or WT or gal102K159A re-integrants in gal102Δ/Δ or PBS was sacrificed at 24 , 42 and 60 hr post-infection . Blood was collected by cardiac puncture , allowed to clot at room temperature and centrifuged ( 10 , 000 rpm for 10 min ) to separate serum for subsequent assays . Cytokine concentrations were measured by commercial ELISA kits from eBioscience , San Diego , USA according to the manufacturer's instructions using 96 well plates . The serum samples were diluted 1∶5 and the concentrations of cytokines were determined , using a standard curve . The linear range of detection for TNFα , IFNγ and IL-4 was 31 . 25–1 , 000 pg/mL , 62 . 5–2 , 000 pg/mL and 15 . 125–500 pg/mL respectively . This experiment was performed thrice with 5 mice per group-per time point . The enzyme activity was measured as described [26] . Briefly , the recombinant protein expressed in E . coli was purified using Ni-NTA column and 20 µg of protein was incubated at 37°C for 2 hr in reaction buffer containing 50 mM Tris-Cl ( pH-7 . 6 ) . At various time points the A340 nm was measured . The assay was repeated with two independent purified enzyme preps . The results include data from three replicates . Data were analyzed using commercial software ( GraphPad Prism 5 Software ) . Differences in C . albicans colonization of tissues and cytokine levels between two groups were analyzed by Student's t test and comparison between the survival curves were done using the Logrank test . | Candida albicans is an opportunistic fungal pathogen which infects individuals with debilitated immune system either due to old age , diseases such as AIDS or immune suppressive treatments . The cell wall of C . albicans , like most pathogens , mediates interaction of the pathogen with the host and determines the outcome of the host-pathogen interaction . We discovered that inactivation of GAL102 encoded UDP-glucose 4 , 6-dehydratase activity in C . albicans causes altered mannosylation of cell wall proteins and loss of cell wall integrity . The mutant cells thus show increased sensitivity to antifungal drugs that target cell wall . Importantly , these mutant cells show significantly lower virulence and reduced ability to elicit inflammatory cytokine responses from the host . Hence , inactivating the enzyme could significantly aid in controlling the infections by C . albicans . Since , the gene encoding the UDP glucose 4 , 6-dehydratase is also present in many other fungal genomes , inhibitors of this activity could be useful in effective treatment of candidiasis and other fungal infections . | [
"Abstract",
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] | 2011 | UDP-glucose 4, 6-dehydratase Activity Plays an Important Role in Maintaining Cell Wall Integrity and Virulence of Candida albicans |
Drosophila embryos are well studied developmental microcosms that have been used extensively as models for early development and more recently wound repair . Here we extend this work by looking at embryos as model systems for following bacterial infection in real time . We examine the behaviour of injected pathogenic ( Photorhabdus asymbiotica ) and non-pathogenic ( Escherichia coli ) bacteria and their interaction with embryonic hemocytes using time-lapse confocal microscopy . We find that embryonic hemocytes both recognise and phagocytose injected wild type , non-pathogenic E . coli in a Dscam independent manner , proving that embryonic hemocytes are phagocytically competent . In contrast , injection of bacterial cells of the insect pathogen Photorhabdus leads to a rapid ‘freezing’ phenotype of the hemocytes associated with significant rearrangement of the actin cytoskeleton . This freezing phenotype can be phenocopied by either injection of the purified insecticidal toxin Makes Caterpillars Floppy 1 ( Mcf1 ) or by recombinant E . coli expressing the mcf1 gene . Mcf1 mediated hemocyte freezing is shibire dependent , suggesting that endocytosis is required for Mcf1 toxicity and can be modulated by dominant negative or constitutively active Rac expression , suggesting early and unexpected effects of Mcf1 on the actin cytoskeleton . Together these data show how Drosophila embryos can be used to track bacterial infection in real time and how mutant analysis can be used to genetically dissect the effects of specific bacterial virulence factors .
Drosophila is now widely established as a useful genetic model for looking at microbial infection with recent studies now encompassing both bacterial [1] , viral [2] and even fungal infections [3] . Different Drosophila infection models have also begun to mimic different types of infections . For example , several groups are now developing systems in which to examine bacterial intestinal infections [4] as well as the more highly studied model of septic injury involving injection of bacteria directly into the open insect blood system or hemocoel . Within each of these infection models , three different aspects of infection can be examined [5] . First , the innate immune response , the mechanism whereby the fly attempts to kill , isolate or neutralize the invading microbe . Second , microbial virulence , the mechanism whereby the invading microbe seeks to evade or overcome the host immune response . Finally , third , changes in host pathology that can relate either to adverse effects generated by the invading microbe or indeed the host immune response itself [5] . Whilst it is easy to recognize these three aspects of infection it is often harder to examine the interactions between them . It is possible , for example , to examine the effects of a recombinant bacterial toxin on infection , but it is more difficult to examine the role of specific virulence factors in neutralizing specific elements of the immune system , such as phagocytes . Consequently , despite the extensive and highly successful efforts of many researchers to develop infection models in Drosophila , the outcomes of infection are often measured by end-points such as insect death ( survival of a cohort of insects over time ) or changes in cell morphology at fixed periods throughout infection ( often monitored by staining different elements of the cytoskeleton ) . Although this problem can , to some extent , be addressed by the use of reporter constructs ( e . g . Diptericin-LacZ ) that provide quantitative or visual read-outs from specific immune response genes , we still lack the ability to follow bacterial infections in real-time in the critical early stages of infection . We are therefore unable to visualise the outcome of the first interactions between insect phagocytes and invading microbes , interactions that will determine the future success of the infection itself . To address this need , here we use Drosophila embryos , specifically embryonic hemocytes , as models for studying the early stages of infection in real-time using time lapse confocal microscopy . Drosophila embryos and their development are extremely well documented and recent attention has focused on the role of the embryonic hemocytes in early embryonic development . Embryonic hemocytes are highly motile macrophage-like cells that migrate throughout the developing embryo following stereotypical routes to disperse from their point of origin to eventually distribute themselves equally throughout the animal by late embryonic stages [6] , [7] . During their migration hemocytes play many important roles in development including the phagocytic clearance of apoptotic cells within the embryo , as well as the production and secretion of many extracellular matrix proteins [8] . They are also essential for the proper development of many key structures such as the gut and Central nervous system [9] . Although these developmental roles are well documented it is less clear how competent these cells are to respond to infection and whether they play a significant role in the immune response of the embryo . Embryonic hemocytes lend themselves beautifully to live imaging studies since fluorescent probes can be expressed specifically in these cells using hemocyte specific promoters and their movements subsequently imaged within living embryos using confocal timelapse microscopy . Drosophila embryos therefore represent an easily injectable , containable and closed experimental system into which bacteria can be injected and their subsequent interactions with resident hemocytes observed in real time . Many of the studies developing Drosophila as models for bacterial infections have used bacteria pathogenic to man [5] . Thus several studies have used Pseudomonas aeruginosa , Salmonella typhimurium , Staphylococcus aureus or Vibrio cholera to look at insects as models for mammalian infection [10]–[15] . However , the role of insect specific pathogens , or pathogens capable of infecting both insects and man , has been less well studied . We have been developing the Gram-negative bacterium Photorhabdus asymbiotica as a model system in which to study cross-talk between virulence factors developed against insects that can also be deployed against mammalian immune responses . P . asymbiotica strains have been recovered from human wounds [16] and are vectored by nematodes that usually invade and kill insects [17] . We have recently catalogued the full range of virulence factors that this bacteria has at its disposal for infecting insects and humans [18] . Anti-insect virulence in Photorhabdus bacteria is associated with the dominant toxin Makes Caterpillars Floppy 1 or Mcf1 [19] . This toxin causes extensive apoptotic cell death in both the midgut epithelium and circulating hemocytes of caterpillar hosts . Access to both purified Mcf1 toxin and recombinant E . coli expressing the mcf1 gene makes this an ideal virulence factor in which to study early interactions between an insect pathogen and insect phagocytes . Here , we pioneer the use of Drosophila embryos as models to study bacterial infection in real time . We show that embryonic hemocytes both recognise and phagocytose non-pathogenic E . coli in a Dscam independent manner . In contrast , we show that the cells of the insect pathogen Photorhabdus instantly freeze the highly mobile phagocytes . This freezing phenotype can be phenocopied either by injection of recombinant E . coli expressing the mcf1 gene , or by injection of the purified toxin itself . The ability to image these first early stages of infection therefore facilitates a direct examination of the Mcf1 virulence factor neutralizing the phagocytic role of the embryonic hemocytes . Moreover , examination of the role of Mcf1 can be dissected genetically using mutants that either interfere with its endocytosis into target cells , or Rac signalling mutants that hint at early and unexpected Mcf1 mediated effects on the phagocyte cytoskeleton .
To enable in vivo detection of E . coli , strain BL21 ( DE3 ) was transformed with a high-copy vector pRSET expressing the monomeric red fluorescence protein . Protein expression was under the control of the T7 promoter; the leaky nature of this promoter allowed basal expression of the fluorescent protein without induction and successful detection of the bacteria within the embryo . The specificity of the bacterial-hemocyte interaction was initially tested by injecting stage 15 wild-type embryos containing unlabelled hemocytes with nl quantities of highly concentrated fluorescently-labelled bacterial suspension ( 1010 colony forming units/ml ) . At this embryonic stage , hemocytes are arranged into three characteristic lines that run anterior to posterior along the ventral aspect of the embryo ( Figure 1A ) . Monitoring of the injected embryos under fluorescence revealed that 20 minutes after injection , bacteria specifically localised to the hemocytes . Thus , although the cells themselves were not fluorescently labelled their pattern of distribution could be easily visualised as a result of their binding to the RFP labelled bacteria alone ( Figure 1B ) . The fact that the hemocytes can be seen in their normal positions within the embryo reveals that these cells do not have to actively migrate toward the invading bacteria but rather are able to recognize and bind the bacteria as they are washed over them in the extra-cellular space . To investigate this host-pathogen interaction in more detail hemocytes were labelled using the srpGAL4 driver to express GFP specifically in the hemocytes . These embryos , now with GFP labelled hemocytes , were then injected with a less concentrated fluorescently-labelled bacterial suspension ( 107 cfu/ml ) and subjected to timelapse confocal imaging . Confocal images show that hemocytes clearly locate and capture invading E . coli ( Video S1 ) and optical sections collected at different focal planes through one hemocyte show labelled bacteria within the cytoplasm of the phagocyte ( Figure 1D , E and F ) . Previous work has indicated the importance of the immunoglobulin ( Ig ) -superfamily receptor Down syndrome cell adhesion molecule ( Dscam ) for bacterial recognition in Drosophila third instar larvae [20] . Drosophila fat body cells and hemocytes have the potential to express more than 36 , 000 isoforms of Dscam , and soluble isoforms of Dscam have also been detected in the hemolymph [20] . Dscam binds E . coli and is thought to act both as a phagocytic receptor and an opsonin in both Drosophila [20] and the malaria vector Anopheles gambiae [21] . To determine whether Dscam acts as a receptor for bacterial recognition in embryos , we compared the ability of hemocytes in wild-type and dscam05518 mutant embryos [22] to bind E . coli . Surprisingly , in contrast to the above observations , dscam05518 mutants were still able to recognise and crosslink bacteria on the surface of their hemocytes with equal efficiency to their wild-type counterparts demonstrating that Dscam is dispensable for recognition of E . coli by embryonic hemocytes ( Figure 1C ) . Having shown that embryonic hemocytes can bind and engulf live non-pathogenic bacteria , we wanted to characterize the response of embryos upon infection with an insect pathogen . Photorhabdus is a Gram-negative , nematode-vectored bacterium that kills a wide range of insect species [23] . Injection of stage 15 wild-type Drosophila embryos containing RFP-labelled hemocytes with a GFP-labelled P . asymbiotica suspension ( 107 cfu/ml ) had a profound effect on embryonic hemocyte motility whereby hemocytes rapidly loose their ability to migrate and apparently freeze ( Figure 2 and Video S2 ) . All actin rich protrusions are retained in these cells but appear to loose their dynamism failing to extend or retract as would ordinarily be seen in a healthy untreated motile hemocyte . This dramatic effect occurs very rapidly and could be observed 20 minutes after injection of Photorhabdus . Consequently the hemocytes are unable to engulf the bacteria . Interestingly , despite this severe effect on the cell's migratory and phagocytic machinery , their ability to recognize and bind the bacteria was unaffected ( Figure 2B ) . During insect infection Photorhabdus replicates within the hemocoel and delivers toxins which rapidly kill the insect host . Expression of one such toxin , Mcf1 is sufficient to allow E . coli to survive within , and kill , Manduca caterpillars which are otherwise able to clear E . coli infection [19] . Mcf1 treated caterpillars show rapid loss of body turgor ( the “floppy” phenotype ) within 12 hours , associated with massive apoptosis of the midgut epithelium . Manduca hemocytes also undergo apoptosis when exposed to recombinant Mcf1 [19] . Mammalian cells treated with Mcf1 also display key features of apoptosis which is putatively mediated by a BH3-like domain and involves the mitochondrial pathway [24] , [25] . Injection of wild-type stage 15 embryos with E . coli constitutively expressing Mcf1 from the high-copy vector pUC18 causes rapid paralysis of embryonic hemocytes and inhibition of phagocytosis as observed following wild-type Photorhabdus infection ( Figure 3A and Video S3 ) . Micro-injection of purified Mcf1 ( 0 . 2 mg/ml ) into wild-type stage 15 Drosophila embryos containing GFP-moesin expressing hemocytes also triggers rapid freezing of hemocytes with ‘frozen’ cellular protrusions and phagosomes ( Figure 3B and Video S4 ) . This effect was not seen when embryos were injected with the same concentration of heat inactivated BSA demonstrating that it is indeed the presence of Mcf1 that causes the freezing phenotype ( Video S5 ) . To ascertain whether the hemocyte paralysis effect of Mcf1 occurs in a dose-dependent manner we injected embryos with half the concentration previously used ( 0 . 1 mg/ml ) . In these embryos the freezing effect on hemocytes was less pronounced with many cells displaying active lamellipodial ruffling . Despite this however , these cells were not as dynamic as untreated cells and were still unable to migrate ( Video S6 ) . The rapid paralysis of hemocytes in the presence of Mcf1 suggests that this phenotype is independent , or upstream of , apoptosis given that the earliest pro-apoptotic indicators are observed 3 hours following incubation with Mcf1 [24] . To investigate this we expressed the pro-apoptotic Bcl-2 family member Bax in hemocytes using a combination of srpGAL4 and crqGAL4 drivers . Confocal analysis revealed that apoptotic hemocytes are very different in morphology to those exposed to Mcf1 appearing hugely swollen and containing fluorescent puncta having engulfed their dying neighbouring hemocytes ( Figure 3E ) . Such obvious differences in morphology suggested that the early freezing effect of Mcf1 is independent of apoptosis but could not rule out a separate more long-term pro-apoptotic effect . In order to determine the long term effect of Mcf1 injection we left injected embryos overnight before scoring for lethality . We found that 70% of embryos injected with Mcf1 failed to develop to first larval instar compared with 26% of embryos injected with the same concentration of heat inactivated BSA ( Figure 3C ) . This was consistent with a long-term apoptotic effect of Mcf1 causing widespread cell death and ultimately death of the animal . To investigate this further we observed hemocytes in embryos 12 hours after injection and found that hemocyte number is greatly reduced in these dead animals ( Figure 3D ) . Additionally , high magnification confocal analysis revealed that the remaining hemocytes in these animals appeared morphologically identical to those overexpressing Bax ( Figure 3F ) . This suggests that long-term exposure to Mcf1 causes hemocytes to ultimately undergo apoptosis consistent with previous studies using Manduca caterpillars . We were curious to know whether the observed freezing effect of Mcf1 was specific for hemocytes or whether other cells might also be affected in the same way . To address this we analysed the paradigm morphogenetic tissue movement dorsal closure in embryos injected with Mcf1 and compared them to wildtype . Dorsal closure is a naturally occurring epithelial movement which requires the coordinated migration and fusion of two epithelial sheets to close the dorsal side of the embryo . Like hemocyte migration , dorsal closure requires the small GTPase Rac [26] and previous work has shown that the fusion of the migrating epithelial fronts is dependent on the formation of dynamic actin rich filopodia [27] . We found that Mcf1 injection into embryos expressing constitutively expressed GFP moesin had no effect on dorsal closure and that epithelial fronts migrated and fused at the same rate as wildtype ( Figure 4 and Video S7 ) . We therefore conclude that Mcf1 does not appear to affect all embryonic cell types in the dramatic fashion observed in hemocytes . One possible explanation for this result might be that epithelial cells are less endocytically active than hemocytes and therefore internalise less of the Mcf1 toxin . Mcf1 has been previously described as requiring internalisation for cytotoxicity in vitro [24] , [25] . To determine whether Mcf1 requires cellular internalisation for its freezing effect on hemocytes in vivo we tested whether Drosophila embryonic hemocytes attenuated in their ability to endocytose would still exhibit the freezing phenotype upon exposure to Mcf1 . Dynamin is a GTP-binding protein which controls formation of constricted coat pits and is involved in a late step of clathrin-dependent endocytosis . In order to disrupt dynamin function specifically in hemocytes we expressed a temperature sensitive allele of Drosophila dynamin ( shibirets1 ) [28] using the a combination of the hemocyte drivers srpGAL4 and crqGAL4 . We allowed embryos to develop to stage 14 before moving them to restrictive ( non-permissive ) temperature to allow activation of shits1 . When these embryos were microinjected with Mcf1 the hemocytes were immune to the paralytic effect of the Mcf1 and continued to produce large dynamic cytoplasmic extensions appearing indistinguishable from uninjected control embryos ( Figure 5A and Video S8 ) . This demonstrates that the toxin Mcf1 needs to be internalized to cause cellular paralysis . To further investigate internalization and paralysis , Mcf1 was directly labelled with Alexa-Fluor 555 ( Mcf1-555 ) and micro-injected into wild-type embryos . Embryos injected with Mcf1-555 show a punctate distribution of labelled Mcf1 within hemocytes appearing associated with phagosomal compartments ( Figure 5B ) . Mcf1-555 was also visible outside of hemocytes in a similar punctate pattern probably due to internalization of the labelled toxin by cells other than the GFP expressing hemocytes since Mcf1 is known to affect a wide variety of cell types other than insect hemocytes [24] . The rapid onset of the freezing phenotype led to the hypothesis that Mcf1 may be acting on a pre-existing eukaryotic molecular switch governing actin cytoskeletal dynamics such as the rho GTPases . The small GTPase Rac is a key factor known to be involved in phagocytosis and cell migration in mammals and has been shown to be essential for hemocyte migration within the embryo [29] , [30] . To investigate the potential involvement of Rac in Mcf1 mode of action we micro-injected Mcf1 into Drosophila embryos expressing either dominant- negative ( RacN17 ) or constitutively active ( RacV12 ) versions of the small GTPase , Rac , in hemocytes . It has been previously shown that hemocytes expressing dominant-negative RacN17 fail to undergo their normal developmental migrations and exhibit stunted lamellipodia formation [29] , [30] . However , despite these migratory defects , RacN17 expressing hemocytes were completely resistant to the effects of Mcf1 and injection of Mcf1 into these embryos failed to cause the freezing effect observed when administered to wildtype cells ( Figure 6A and Video S9 ) . Interestingly , expression of constitutively active RacV12 in hemocytes also led to complete resistance to Mcf1-mediated paralysis in the hemocytes ( Figure 6B and Video S10 ) . These results appear to indicate a role for Rac in Mcf1 mediated paralysis .
Adult Drosophila have been used extensively as infection models for a range of different microbes [1] . In this study , we have expanded this infection model to include the well studied Drosophila embryo . We have combined Drosophila genetics and real-time imaging to examine the very earliest stages of host-pathogen interaction , which are critical for the successful initiation of any infection . We have proven that embryonic hemocytes are indeed competent phagocytes when challenged with non-pathogenic E . coli and that the process of recognition and engulfment of these bacteria is , surprisingly , Dscam independent . In contrast , when injected with the insect and human pathogen P . asymbiotica , the highly motile embryonic hemocytes underwent a rapid paralysis , termed the ‘freezing’ phenotype . This phenotype could be phenocopied either by injection of the purified Photorhabdus toxin Mcf1 or by injection of recombinant E . coli expressing the mcf1 gene . Use of Drosophila mutants either deficient in endocytic machinery or with altered activity of their Rac GTPases shows that the freezing phenotype requires internalization of the Mcf1 toxin and may involve unexpected alterations in the actin cytoskeleton of the hemocytes . These studies demonstrate not only that Drosophila embryos are powerful systems for studying the early stages of infection but also that they can facilitate the genetic dissection of the underlying molecular mechanisms of virulence and immunity . Mcf1 is a single toxin which facilitates persistence of Photorhabdus bacteria in the hemocoel of an insect host in the face of the cellular immune response [19] . Previous studies have suggested that the massive apoptosis of the insect midgut epithelium , and destruction of insect hemocytes , associated with Mcf1 toxicity were related to its pro-apoptotic activity . However the rapid Mcf1 mediated hemocyte freezing phenotype described here suggests that this toxin may also have earlier effects on the actin cytoskeleton of host phagocytes . This early , anti-phagocytic , activity of Mcf1 may also be consistent with Mcf1 being the anti-phagocytic factor previously documented in other strains of Photorhabdus [31] . Mcf1 has previously been shown to require endocytosis for its pro-apoptotic activity and here we confirm that the freezing phenotype also requires internalisation of the toxin . The mechanism of how Mcf1 was freezing the actin cytoskeleton and preventing cellular migration was investigated by examining the effect of the toxin on embryonic hemocytes mutant in the small GTPase Rac . Drosophila embryonic hemocytes expressing dominant-negative or constitutively active Rac evaded the freezing phenotype caused by Mcf1 indicating a necessity for the presence of wild-type Rac in the freezing process . The Rho GTPases are a popular target for bacterial toxins as the manipulation of these molecules assists in virulence processes such as intracellular invasion and phagocytic avoidance [32] . A number of bacterial toxins inactivate Rho GTPases as a mechanism of avoiding phagocytosis . A group of such Rho inactivators act as Rho GTPase activating Proteins ( RhoGAPs ) which stimulate the intrinsic GTPase activity of the small GTPases hydrolysing them to their inactive GDP bound state . Examples of such toxins are ExoS and ExoT ( Pseudomonas aeruginosa ) , YopE ( Yersinia spp . ) and SptP ( Salmonella typhimurium ) [33]–[36] . Constitutive activation of the Rho GTPases counteracts the activity of most GAP toxins and does not effect those that directly target the actin cytoskeleton [37] , [38] . Whether Mcf1 is capable of inactivating Rac , and is doing so directly through a GAP-like activity or via other mechanisms remains to be explored . Previous studies using third instar Drosophila larvae have implicated the immunoglobulin ( Ig ) -superfamily receptor Down syndrome cell adhesion molecule ( Dscam ) as being an important player in the recognition of bacteria [20] . Here we demonstrate that , despite these previous results , Dscam mutant hemocytes can recognize and bind E . coli with equal efficiency to that seen in wild-type embryos . This result demonstrates an intriguing difference between the immune system operating in the embryo when compared with larvae . Embryonic hemocytes are very long lived cells that persist into larval stages and constitute the circulating population of hemocytes in a larva . Within the larva a second population of hemocytes develops in a specialised hematopoetic organ called the lymph gland . Lymph gland hemocytes are normally released from this organ during metamporphosis but can be released prematurely following parasitisation [39] . Within an infected larvae , bacteria are therefore cleared by a combination of both embryonic hemocytes that have persisted through to larval stages and larval lymph gland hemocytes released upon infection . Our results suggest that the mechanisms used for bacterial recognition by these two populations could be different . We cannot exclude the possibility that hemocytes within the embryo operate with a small subset of the receptors utilised by lymph gland hemocytes and that as they persist through to larval stages they begin to express the full complement of immune receptors including Dscam . It will be interesting to determine whether this is the case or whether embryonic hemocytes encode a completely different set of proteins for bacterial detection . Further work is also needed to determine at which stage of development embryonic hemocytes acquire their ability to recognise invading micro-organisms . The maturation of embryonic hemocytes as they progress through embryonic into larval stages of development is an interesting process that has received very little research attention . Recent studies have shown that when circulating within larvae , hemocytes appear substantially less motile than when they migrate throughout the embryo [40] , [41] This difference in morphology can be attributed to their being passively pumped around the larval hemocoel rather than actively migrating through the embryonic extracellular space . Their morphology could change drastically however , once they encounter a pathogen that needs to be engulfed . Here we show the effect of Mcf1 on the actin cytoskeleton of a hemocyte within an embryo which manifests itself as a block on cell migration . It would be interesting to see the affect of Mcf1 on hemocytes within larvae where its effect on cell migration would presumably be less pronounced but its effect on other actin dependent processes such as phagocytosis may be equally drastic . Here we have described an in vivo system for looking at a known population of phagocytes in a closed system , the Drosophila embryo . This system complements the use of tissue culture systems for several reasons . First , the real-time behaviour of phagocytes in their natural environment can be monitored . This overcomes the limitations of looking at immortal cell lines of uncertain origin ( eg Schneider cells ) or of looking at abnormal behaviour in primary cultures of phagocytes ( eg hemocytes recently bled from an insect ) . Second , we can use both genetic mutants and RNAi to look at effects in vivo . This contrasts to transfection experiments on cell cultures that are often transient and variable in their effects . Finally , although we cant precisely define the concentration of effector proteins delivered into the hemocyte via injection , we can say , in the case of Mcf1 , that both the purified protein , the recombinant protein expressed by E . coli and the native Mcf1 expressed by P . asymbiotica all had the same phenotypic effects on the in vivo system . Moreover , these effects were all very different to those previously described for Mcf1 protein applied to primary cultures of Manduca hemocytes recorded under time-lapse photography [19] . In recent years cultured Drosophila S2 cells have been used extensively as a model system to study infection and immune responses . These cells allow for large scale screening using RNAi and have been successfully used to identify proteins involved in host interactions with important human bacterial pathogens such as Escherichia coli , Staphylococcus aureus [42] , [43] , Mycobacterium spp . [44] , Legionella pneumophila [45] , Chlamydia spp . [46]–[48] and Listeria monocytogenes [49]–[51] . Whilst such studies provide a reservoir of genes involved in bacterial recognition and degradation in vitro the situation in vivo where hemocytes can interact with other immune cells to optimize immune responses is likely to be more complex . Ultimately , to have an impact on human and animal health , the results obtained by in vitro studies need to be verified in a whole organism . The assay we present here provides a perfect model to begin to fill these gaps and should lead to a better understanding of host-pathogen interactions in the complex setting of a multicellular organism .
P . asymbiotica ATCC 43949 was isolated from a human leg wound in San Antonio , Texas [52] and obtained from the ATCC culture collection . A spontaneous rifampicin mutant was created by common microbiology methods and used in all microinjection experiments . Escherichia coli S17-1λpir [53] was used as a conjugative donor of the pir-dependent suicide replicon pBamH7 ( a kind gift from Dr Leo Erbel ) which constitutively expresses green fluorescence protein ( GFP ) . E . coli BL21 was used for cloning and constitutive expression of Mcf1 from pUC18 ( as previously described [19] ) and green or red fluorescence protein ( RFP ) from pRSET ( Invitrogen ) . DNA fragments were cloned using standard cloning procedures . Bacterial strains were amplified in LB broth containing , as appropriate , ampicillin 100 µg ml−1; kanamycin 25 µg ml−1; rifampicin 25 µg ml−1 . For embryo microinjections , bacteria were grown to stationary phase at 37°C for 18–24 h , washed in phosphate-buffered saline ( PBS ) and adjusted to the appropriate density . pBamH7 was delivered to P . asymbiotica via conjugation with S17-1λpir by using a membrane filter mating technique . S17-1λpir pBamH7 was inoculated into 5 ml of LB broth containing kanamycin and grown at 37°C for 16–18 h with shaking ( 200 rpm ) . P . asymbiotica was grown at 28°C for 16–18 h with shaking ( 200 rpm ) but without antibiotic selection . 100 µl of each saturated bacterial culture was added to 3 ml of sterile 10 mM MgSO4 , mixed , and filtered through a 0 . 45-µm-pore-size nitrocellulose filter , using a 25-mm Swinnex filter apparatus ( Millipore ) . Control assays , using donor and recipient alone , were also performed . Filters were placed on LB plates supplemented with 10 mM MgSO4 and incubated for at least 8 h in a 37°C incubator . The filters were washed with 4 ml of sterile 0 . 85% NaCl , and 100 µl aliquots were spread onto LB plates containing 25 µg of rifampicin and 25 µg of kanamycin per ml . Rifampicin-resistant and kanamycin-resistant transconjugants were identified after 48 h incubation at 37°C . Purification and labelling of Mcf1 was carried out as described previously [24] . Mcf1 was diluted to required concentrations for micro-injection with sterile 1× phosphate buffered saline solution ( PBS ) . UAS constructs were expressed in hemocytes using either the hemocyte specific Gal4 line serpentHemoGAL4 ( srpGAL4; [54] ) or croquemortGAL4 ( crqGAL4; [30] . A w; srpGAL4 , UAS-GFP recombinant line was used to visualize wildtype hemocyte motility and bacterial engulfment . Actin dynamics were visualised in hemocytes using lines with recombined chromosomes carrying both srpGAL4 and either UASGFPmoesin ( UASGMA; [55] or UAS-RFP-Moesin [56] . Embryos containing the transgene sGMCA ( constitutively expressing GFP-Moesin ) [55] were used to visualise actin dynamics in epithelial cells during dorsal closure . To activate apoptosis in hemocytes w;srpHemoGAL4UASGFP;crqGAL4UASGFP flies were crossed to a w;UAS-bax stock . After egg laying at 25°C , embryos were transferred to 29°C to develop . To disrupt shibire function in hemocytes w;srpHemoGAL4UASGFP;crqGAL4UASGFP flies were crossed to a w;UASshits1 stock [28] generating w;srpHemoGAL4UASGFP/UASshits1; crqGAL4UASGFP/+ progeny . These embryos were then left to develop to late stage 13 before being incubated at 32°C for 2 h and returning to room temperature for 1 . 5 h before injection . Expression of dominant negative Rac constructs in hemocytes was achieved by crossing UAS-RacV12 or UAS-RacN17 flies to a w;srpHemoGAL4UASGFP;crqGAL4UASGFP stock . For the Dscam loss of function experiment the dscam05518 allele was used [22] . w; dscam/CTG flies were intercrossed and homozygous dscam05518 mutants were identified by their lack of a fluorescent balancer . Embryos were collected at stage 15 of development and prepared for micro-injection and confocal imaging . Embryos were dechorionated in bleach and mounted on a coverslip under Voltalef oil as previously described [57] . Micro-injection was carried out using an Eppendorf Femtojet injectman . The micro-injection needle was loaded with 4 µl of either E . coli RFP , E . coli GFP pUC-18 , GFP pUC-18mcf1 or purified Mcf1 for injection as required . The needle was then introduced into the anterior of the embryo and the embryo injected . Following injection a coverslip was mounted over the embryos ready for microscopy . For the survival study injected embryos were left uncovered in voltalef oil in a humid chamber overnight and scored for lethality the following day . Imaging was carried out on a Zeiss LSM-510 confocal laser-scanning microscope ( Zeiss LSM-510 system with inverted Axiovert 100 M microscope ) , equipped with a krypton-argon laser and helium-neon lasers , under 63× objective . For time-lapse movies images were obtained by taking four optical slices ( each slice averaged 2× ) through hemocytes collected at 120 s intervals . Compilation and processing of movies was carried out using ImageJ software . | The humble fruit fly has formed an important model for the study of bacterial infection both by insect specific and mammalian pathogens . However , many studies of bacterial infection rely upon death of the insect host , or actin cytoskeleton staining of specific host cells , at fixed end-points to look at infection or the mode of action of different bacterial toxins . Here , we use Drosophila embryos in a novel application to look at bacterial infection in real time . Contrary to popular belief , embryonic hemocytes both recognise and ingest injected Escherichia coli . This is a dynamic process in which the bacteria are recognised by , and adhere to , the phagocytes in a process that can be dramatically seen in real time using time-lapse confocal microscopy . In contrast , when cells of the insect pathogen Photorhabdus are introduced , the hemocytes become frozen and are unable to engulf the invading bacteria . Using both recombinant E . coli expressing the bacterial toxin Makes Caterpillars Floppy , and also purified toxin itself , we show how genetic mutants of Drosophila can be used to dissect the role of bacterial toxins in infection . Such approaches should provide a useful model in which to study infection by other pathogens and their associated toxins . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [
"developmental",
"biology",
"immunology/innate",
"immunity",
"cell",
"biology/cytoskeleton"
] | 2009 | Drosophila Embryos as Model Systems for Monitoring Bacterial Infection in Real Time |
Eukaryotic cells respond to environmental stimuli when cell surface receptors are bound by environmental ligands . The binding initiates a signal transduction cascade that results in the appropriate intracellular responses . Studies have shown that endocytosis is critical for receptor internalization and signaling activation . In the rice blast fungus Magnaporthe oryzae , a non-canonical G-protein coupled receptor , Pth11 , and membrane sensors MoMsb2 and MoSho1 are thought to function upstream of G-protein/cAMP signaling and the Pmk1 MAPK pathway to regulate appressorium formation and pathogenesis . However , little is known about how these receptors or sensors are internalized and transported into intracellular compartments . We found that the MoEnd3 protein is important for endocytic transport and that the ΔMoend3 mutant exhibited defects in efficient internalization of Pth11 and MoSho1 . The ΔMoend3 mutant was also defective in Pmk1 phosphorylation , autophagy , appressorium formation and function . Intriguingly , restoring Pmk1 phosphorylation levels in ΔMoend3 suppressed most of these defects . Moreover , we demonstrated that MoEnd3 is subject to regulation by MoArk1 through protein phosphorylation . We also found that MoEnd3 has additional functions in facilitating the secretion of effectors , including Avr-Pia and AvrPiz-t that suppress rice immunity . Taken together , our findings suggest that MoEnd3 plays a critical role in mediating receptor endocytosis that is critical for the signal transduction-regulated development and virulence of M . oryzae .
The rice blast fungus Magnaporthe oryzae produces an infectious structure called the appressorium that enables it to penetrate host plant cells and initiate infection [1] . During the interaction between the pathogen and the host , the fungus secretes numerous effectors into the host that suppress plant immunity [2–5] . Previous studies have shown that G-protein/cAMP signaling is important in the perception of host surface cues by M . oryzae and during invasion of host tissue [6 , 7] . M . oryzae contains three distinct Gα subunit proteins: MagA , MagB and MagC as well as a highly conserved cAMP-dependent signaling pathway , which consists of the adenylate cyclase Mac1 , the regulatory subunit of protein kinase A Sum1 , and the catalytic subunit of protein kinase A cPKA [6 , 8] . cPKA activation is responsible for appressorium differentiation . In addition , the non-canonical G-protein coupled receptor ( GPCR ) Pth11 is known to function upstream of G-protein/cAMP signaling [9 , 10] . Moreover , the MAP kinase cascade comprised of Mst11 ( MAPKKK ) , Mst7 ( MAPKK ) , and Pmk1 ( MAPK ) is also involved in the regulation of appressorium formation [11] . Furthermore , MoMsb2 and MoSho1 function as two upstream sensors of the MAP kinase cascade [12] . Deletion of either MoMSB2 or/and MoSHO1 resulted in a significant reduction in appressorium formation . Intriguingly , the expression of a dominant active MST7 allele partially suppressed the defects exhibited by the ΔMomsb2 mutant [12] . Recently , endosomal compartments were discovered to function as signaling platforms by anchoring the components of G-protein/cAMP signaling . The various signaling components then interact within the endosomal compartments for sustaining signaling [13] . Endosomal compartments contain early and late endosomes . Proteins internalized from the cell surface target early endosomes to undergo a sorting process , by which they are either recycled back to the plasma membrane or sent to late endosomes for degradation . Previous studies have shown that disruption of phosphoinositide PI3P synthesis on the endosomal membrane or inhibition of the conversion of early endosomes into late endosomes by MoVPS39 gene deletion disrupts the endosomal localization of Pth11 , MagA , Mac1 proteins , and a regulator of G protein signaling MoRgs1 thereby leading to an inhibition in appressorium formation [13] . However , despite these important findings , the mechanism by which Pth11 or other receptors proteins enter intracellular compartments to activate signal transduction in M . oryzae is still unclear . Endocytosis is a conserved intracellular transport process in which membrane proteins , lipids , or other macromolecules are transported to endosomal compartments . During endocytosis , endocytic proteins are recruited to endocytic sites and interact with actin cytoskeleton to drive vesicle maturation and scission [14] . In Saccharomyces cerevisiae , the Eps15 homolog ( EH ) domain-containing proteins Pan1p and End3p are important members of endocytic proteins and depletion of Pan1p or End3p severely impairs endocytosis and actin organization [15–17] . When vesicles are mature , endocytic proteins and actin components simultaneously dissociate from the vesicle membrane , thereby promoting efficient endocytosis [18] . The Ark1p/Prk1p actin-regulating kinases are implicated in this dissociation process [19 , 20] . Ark1p/Prk1p phosphorylates Pan1p and other proteins to promote their dissociation [20 , 21] . Deletion of Ark1p and Prk1p results in aggregation of endocytic proteins and actin cytoskeleton in the cytoplasm , which prevents endocytosis [22] . We previously found that MoArk1 has conserved functions in regulating endocytosis and that MoArk1 is required for appressorium turgor generation and penetration in M . oryzae . This study suggested that endocytosis plays an important role in the pathogenesis of the rice blast fungus [23] . Here we continued to investigate the mechanism that links MoArk1-regulated endocytosis to fungal pathogenesis . We identified a MoArk1-interacting protein MoEnd3 by mass spectrometry analysis and characterized its function . We found that MoEnd3 is an endocytic protein and mediates the endocytic transport of GPCR Pth11 and sensor MoSho1 . This transport could trigger downstream Pmk1 phosphorylation for autophagy , appressorium formation and penetration . In addition , we identified that MoEnd3 function is regulated by MoArk1-dependent phosphorylation at Ser-222 . Finally , we demonstrated that secretion of the MoEnd3-regulated effectors is directly linked to host immunity suppression .
MoArk1 is an actin-regulating kinase homolog required for endocytosis , growth , development , and full virulence of M . oryzae [23] . To explore the mechanism by which MoArk1 regulates these processes , we employed protein co-immunoprecipitation ( Co-IP ) to identify putative MoArk1-interacting proteins . By expressing the MoARK1:FLAG construct and using FLAG beads to isolate MoArk1:FLAG-interacting proteins followed by mass spectrometry analysis , we found several proteins potentially important for endocytosis and actin cytoskeleton , including homologues of the clathrin heavy chain , amylase-binding protein AbpA , Arp2/3 complex subunit proteins , endocytosis and cytoskeletal organization proteins , vesicular integral-membrane protein Vip36 , and F-actin-capping proteins ( S1 Table ) . Additional proteins co-precipitated with MoArk1 also include the dynamin-A homologue MoDnm1 that regulates peroxisomal and mitochondrial fission through interactions with MoFis1 and MoMdv1 [24] . We identified MGG_06180 . 6 as an endocytic protein homolog to S . cerevisiae End3p ( 30% amino acid sequence identity ) and characterized its function . To confirm the interaction between MoEnd3 and MoArk1 , we employed the yeast two-hybrid assay that demonstrated the interaction . Transformants expressing AD-MoEnd3 and BD-MoArk1 constructs showed β-galactosidase activity on SD-Leu-Trp-His-Ade plates ( Fig 1A ) . In addition , we performed in vitro protein binding and bimolecular fluorescence complementation ( BiFC ) assays that further substantiated the MoEnd3 and MoArk1 interaction ( Fig 1B and 1C ) . In the BiFC assay , fluorescence appeared in the cytoplasm of the conidia and 24 h appressorium of the strain co-expressing MoEnd3-YFPN and MoArk1-YFPC constructs , but not in controls ( Fig 1C ) . To characterize MoEnd3 functions , a ΔMoend3 mutant was obtained ( S1 Fig ) and characterized . No significant differences were observed between the ΔMoend3 mutant and the wild-type Guy11 strain in colony diameter ( on CM , MM , SDC and OM medium plates ) or conidia production ( S2 Table ) . However , when the ΔMoend3 mutant was crossed to the tester strain TH3 ( MAT1-1 ) , no perithecia were observed after 3 weeks ( S2 Fig ) , suggesting that MoEnd3 is dispensable for vegetative growth and conidiation but not sexual reproduction . To examine whether MoEnd3 is required for endocytosis , we stained the cells with the lipophilic dye FM4-64 and observed its internalization . After 1 min of staining , the dye appeared in the cytoplasm of hyphal tips in Guy11 and the complemented strain , but the dye remained at the plasma membrane of the ΔMoend3 mutant ( Fig 2A ) . At 15 min , the dye was most intense in the hypal tip of Guy11 and the complemented strain , while was near invisible in the cytoplasm of ΔMoend3 . Only at 30 min , when some dye internalization was observed in ΔMoend3 . The fluorescence intensity of the dye was quantified using the ImageJ software ( Fig 2B ) , and this quantification is consistent in suggesting that MoEnd3 is required for normal endocytosis . Since the End3 endocytic protein regulates endocytosis through the coordination of the F-actin assembly at endocytic sites in S . cerevisiae [25] , we examined whether MoEND3 deletion impairs F-actin organization using the Lifeact:RFP marker [26] . A toroidal-shaped F-actin network could be observed in 80 . 4% of the mature appressoria produced by wild-type Guy11 ( Fig 2C ) . By comparison , ΔMoend3 displayed an aberrant distribution of F-actin in 98 . 8% of appressoria , as demonstrated by a line-scan analysis . It is known that the actin patch that associates with plasma membrane corresponds to endocytic sites [27] . In the conidia of Guy11 , a lot of punctae-like cortical actin patches were observed in the cytoplasm of conidia ( Fig 2D ) . However , aggregated , instead of punctae-like , actin structures were observed in nearly 96 . 3% of ΔMoend3 conidia ( Fig 2D ) . In addition , many actin patches displayed polarized distributions at the hyphal tip regions of Guy11 , whereas they were rarely seen at the hyphal tip region of ΔMoend3 ( Fig 2E ) . To further examine whether MoEnd3 is associated with F-actin , the MoEnd3:GFP fusion protein and Lifeact:RFP were co-expressed in the ΔMoend3 mutant and localizations of the GFP and RFP fusion proteins were observed by confocal fluorescence microscopy . We found that MoEnd3:GFP co-localized with the F-actin network in appressoria after 6 and 12 h of incubation ( Fig 1D ) . In conidia and the hyphal tips , MoEnd3:GFP patches were found at the plasma membrane and were co-localized with actin patches ( Fig 1D ) . However , we still observed some regions only showed MoEnd3:GFP or Lifeact:RFP , likely due to that End3 protein arrives endocytic sites or disassembles from there earlier than F-actin , as suggested in studies involving S . cerevisiae End3p [16 , 27] . We then examined whether MoEnd3 interacts with F-actin protein MoAct1 by performing yeast two-hybrid and in vitro protein binding assays . Consistently , both assays demonstrated an interaction occurred between MoEnd3 and MoAct1 ( Fig 1E and 1F ) , supporting that MoEnd3 could coordinate actin assembly through a direct interaction with F-actin . On hydrophobic surfaces , the ΔMoend3 mutant showed delayed appressorium development compared with Guy11 and the complemented strain ( Fig 3A and 3B ) and this delay became indistinguishable after 24 h . However , the germ tubes of ΔMoend3 were elongated and the appressoria were smaller in size and not fully developed ( Fig 3C and 3D ) . The incipient collapse assay [28] showed that the collapse rate of appressoria of ΔMoend3 was significantly higher than Guy11 and the complemented strain ( Fig 3E ) , suggesting that MoEnd3 contributes to appressorial turgor generation . We further observed translocation and degradation of glycogen and lipid required for turgor generation during conidia germination and appressoria development . Iodine solution and Nile red were used to stain the glycogen and lipid bodies , respectively . At 0 h , the glycogen and lipids were abundant in conidia ( S3 Fig ) . In Guy11 , the glycogen and lipids were translocated from conidia to nascent appressoria and were rapidly degraded in conidia after 6 h . They were completely degraded in over 60% of conidia after 12 h and in 90% of the mature appressoria after 24 h . In ΔMoend3 , the degradation of glycogen in conidia and its translocation to appressoria occurred more slowly , and this was coupled with the delayed appressorium formation . After 12 h , glycogen and lipids in conidia were not translocated or degraded . After 24 h , they remained in almost 50% of conidia . These results suggested that MoEnd3 is required for an efficient translocation and breakdown of glycogen and lipids . To further test the role of MoEnd3 in pathogenesis , conidial suspensions were sprayed onto susceptible rice seedlings ( Oryza sativa cv . CO-39 ) . After 7 days of inoculation , ΔMoend3 produced significantly fewer lesions than control strains . The lesions produced by ΔMoend3 were also smaller and less expansive , in contrast to the fully expanded necrotic lesions produced by Guy11 and the complemented strain ( Fig 3F ) . Similar results were obtained in barley leaf infection assay after 5 days ( Fig 3F ) . To further validate the reduction in virulence of ΔMoend3 , we performed penetration assays using detached barley leaf . By observing 100 appressoria for each strain at 24 hpi and classifying their invasive hyphae ( IH ) into 4 types ( type 1 , no hyphal penetration; type 2 , IH with one or two branch; type 3 , IH with at least three branch , but the IH are short and less extended; type 4 , IH that has numerous branches and fully occupies a plant cell ) , we found that in Guy11 and the complemented strain , nearly 80% of appressoria were type 3 , in contrast to that 52 . 3% were type 1 and 38 . 1% were type 2 in ΔMoend3 ( S4 Fig ) . In the penetration assays using rice tissues , 90 . 2% of appressoria of Guy11 and the complemented strain displayed extended IH growth , whereas less than 10% of ΔMoend3 appressoria formed IH , which were arrested in individual rice cells and did not extend to neighboring cells ( Fig 3G ) . These results indicated that MoEnd3 is required for full virulence . Pth11 is a non-canonical GPCR that functions upstream of the G-protein/cAMP pathway for surface sensing in M . oryzae [9] . Once proper surface clues were sensed by M . oryzae , Pth11 and cAMP signaling components , such as MagA and MoRgs1 , are anchored on the endosomal compartments to sustain the transduction of cAMP signaling [13] . In addition , membrane sensors MoMsb2 and MoSho1 are responsible for recognition of surface signals and activation of the downstream MAPK cascade consisting of Mst11-Mst7-Pmk1 [12] . Both the cAMP pathway and the Pmk1-MAPK cascade are known to regulate appressorium formation and penetration . In mammalian cells , endocytosis transports membrane receptors or sensors to endosomes so that these receptors and sensors interact with signaling proteins to activate and amplify signal transduction [29] . We examined whether Pth11 , MoMsb2 , and MoSho1 are transported by endocytosis . We expressed Pth11:GFP , MoMsb2:GFP , and MoSho1:GFP in Guy11 and observed their co-localization with FM4-64 in germ tubes following conidia incubation on hydrophobic surfaces for 3 h . This stage is crucial for pathogen to sense surface clues and initiate appressorium development . We observed that signal of Pth11:GFP and MoSho1:GFP , but not MoMsb2:GFP , was primarily accumulated in regions also labeled by FM4-64 ( Fig 4A , 4B and 4C ) . Rab5 GTPase and Rab7 GTPase are known to bind with early endosomes and late endosomes , respectively [30] . To determine whether FM4-64 stained regions in germ tubes are endosomes or vacuoles , co-localizations of FM4-64 with GFP:Rab5 or GFP:Rab7 and vacuole marker CMAC were observed in germ tubes ( S5 Fig ) . We found that most of FM4-64 was localized to GFP:Rab5 labeled regions ( S5A Fig ) and rarely co-localized with GFP:Rab7 ( S5B Fig ) . In addition , CMAC-marked vacuoles did not appear in the germ tubes but only in the conidia . These observations revealed that internalized FM4-64 localizations in germ tube are likely to be early endosomes . Considering our finding that Pth11:GFP and MoSho1:GFP were co-localized with FM4-64 , we proposed that most of Pth11 and MoSho1 are localized to early endosomes of the germ tubes . To further demonstrate that Pth11 and MoSho1 are internalized by endocytosis , we used actin inhibitor Latrunculin B ( LatB ) that inhibits endocytosis [14] and determined the effect of LatB on Pth11 and MoSho1 . We found that LatB inhibited Pth11:GFP and MoSho1:GFP internalization and enriched them at plasma membrane ( Fig 4E and 4F ) . In addition , exposure to Lat B for 30 min resulted in 91 . 5% of germinated conidia being unable to form appressorium ( Fig 4D ) . Next we determined the role of MoEnd3 in endocytosis of Pth11:GFP and MoSho1:GFP . We found that most of the Pth11:GFP and MoSho1:GFP signals remained at the plasma membrane of the germ tubes in ΔMoend3 ( Fig 4G and 4H ) , and this pattern is similar to that of Pth11:GFP and MoSho1:GFP in Guy11 treated with LatB . We further compared ΔMoend3 and Guy11 in the endocytosis rate of Pth11 and MoSho1 by fluorescence recovery after photobleaching ( FRAP ) , a technique that measures the mobility of fluorescent proteins . We intended to bleach fluorescence from the regions where Pth11:GFP or MoSho1:GFP were accumulated in germ tubes and the recovery of fluorescence can reflect the rate of endocytosis . Considering newly synthesized proteins can be delivered from Golgi to endosomes , we treated germinated conidia ( 3 h ) with cycloheximide to inhibit protein biosynthesis , which may prevent Golgi resident Pth11:GFP or MoSho1:GFP from entering endosomes . We also treated germinated conidia with benomyl for 10 min to inhibit endosomes trafficking via microtubule [31 , 32] . In the FRAP assay , we bleached 90% of fluorescence of a region using 488 nm light . For Pth11:GFP , 72 . 7 ± 4% of fluorescence was recovered at post-photobleach 35 s in Guy11 , compared with 16 . 1 ± 0 . 8% in ΔMoend3 ( Fig 4I and 4J ) . In addition , the recovery level of MoSho1:GFP in ΔMoend3 ( 27 . 5 ± 3 . 1% ) was significantly lower than that in Guy11 ( 78 . 8 ± 7 . 9% ) at post-photobleach ( Fig 4K and 4L ) . Collectively , these results suggested that MoEnd3 is important for endocytosis of Pth11 and MoSho1 . It is clear that the Mst11-Mst7-Pmk1 MAPK pathway is required for appressorium formation and function [11] . Since ΔMoend3 showed defects in appressorium formation , penetration and endocytosis of Pth11 and MoSho1 , we tested the hypothesis that Mst11-Mst7-Pmk1 signaling could also be affected in ΔMoend3 . We extracted proteins and performed Western blot analysis and found that there was no difference in the expression of Pmk1 ( 42-kDa ) between ΔMoend3 and Guy11 ( Fig 3H bottom panel ) . By using the phosphor-MAPK antibody , Pmk1 phosphorylation was detected at all stages except conidia in Guy11 ( Fig 3H bottom panel ) . However , a reduced Pmk1 phosphorylation level was detected in the ΔMoend3 appressoria following 16 h of incubation . This finding suggested that MoEnd3 affects Pmk1 phosphorylation during appressorium development . Previous studies showed that the constitutively activated MST7S212D T216E allele restores normal Pmk1 phosphorylation and appressorium formation in the Δmst11 and Δmst7 mutant strains [11] . To confirm that MoEnd3 affects Pmk1 phosphorylation , we introduced the MST7S212D T216E allele into ΔMoend3 and found that it too suppressed the defect of ΔMoend3 in appressorium formation ( Fig 3H upper panel ) . Interestingly , 50% of conidia of the ΔMoend3/MST7S212D T216E strain appeared to form appressoria after 6 h of incubation on hydrophobic surfaces , whereas no appressoria were formed in ΔMoend3 . There were no significant differences in the formation rate between Guy11 and the ΔMoend3/MST7S212D T216E strain after 10 h ( Fig 3I and 3J ) . Moreover , ΔMoend3 only formed a small number of lesions on rice leaves ( Fig 3K and 3L ) . In contrast , the ΔMoend3/MST7S212D T216E strain produced many typical lesions ( Fig 3K and 3L ) . Further , penetration assays using rice tissues were conducted by observing 100 appressoria for each strain and classifying their IH into 4 types ( type 1 , no hyphal penetration; type 2 , IH with less than two branches; type 3 , IH with at least two branches , but the IH are short and less extended; type 4 , IH that fully occupies a plant cell and moves into neighboring cells ) . We found that 84 . 2% of appressoria from the ΔMoend3/MST7S212D T216E strain could penetrate the rice cells ( Fig 3M ) . In contrast , less than 10% of appressoria from ΔMoend3 could penetrate the host . These results suggested a function link between MoEnd3 and Pmk1 by showing that elevating Pmk1 phosphorylation level could significantly suppress the defect of ΔMoend3 in appressorium formation and infection . Nuclear degradation in conidia is essential for appressorium development and penetration , which is also the consequence of autophagy following mitosis and nuclear migration [33] . To test if MoEnd3 has a role in autophagy , an RFP-labeled H1 histone protein ( H1:RFP ) was expressed in both Guy11 and the ΔMoend3 mutant , and nuclei were visualized following conidia germination on the hydrophobic surface . ΔMoend3 displayed successive nuclear divisions , with no breakdown of nuclei in conidia or germ tubes at 24 h ( Fig 5A ) . We also expressed H1:RFP in the Δpmk1 mutant and found that nuclei failed to degrade ( Fig 5A ) , consistent with previous study [33] . Thus , it is likely that the defect in nuclear degradation in ΔMoend3 is due to the defective Pmk1 phosphorylation . We then determined whether deletion of MoEND3 affects autophagy by culturing mycelia in liquid minimal medium with reduced nitrogen ( MM-N ) in the presence of the proteinase B inhibitor phenylmethylsulfonyl fluoride ( PMSF ) for 4 h and observing hyphal vacuoles under a electron microscope . Autophagosomes were observed in the vacuoles of Guy11 but not ΔMoend3 ( Fig 5B ) . The GFP:MoATG8 construct can be used as a functional marker for monitoring the delivery of vesicles to vacuoles and the breakdown of autophagosomes , and normal autophagy cannot easily hydrolyze free GFP protein cleaved from GFP:MoAtg8 [24 , 34 , 35] . We monitored autophagy using GFP: MoAtg8 in both Guy11 and the ΔMoend3 mutant . GFP was observed in 76 . 7% of vacuoles of Guy11 , but 15 . 2% in ΔMoend3 ( Fig 5C and 5D ) . Interestingly , the expression of the MST7S212D S216E allele promoted GFP:MoAtg8 to enter the 68 . 3% of vacuoles in ΔMoend3 . This phenomenon was further examined by the GFP:MoAtg8 proteolysis assay . Total proteins were extracted from strains expressing GFP:MoAtg8 following 0 , 2 and 5 h of nitrogen starvation . The full-length GFP:MoAtg8 ( 41-kDa ) and cleaved free GFP were detected ( Fig 5E ) . In Guy11 , the level of full-length GFP:MoAtg8 decreased as the time of nitrogen starvation increases . This was not observed in the ΔMoend3 mutant . Meanwhile , the expression of the MoMST7S212D S216E allele accelerated the breakdown of GFP:MoAtg8 in ΔMoend3 ( Fig 5E ) . Based on these results , we concluded that MoEnd3 is important for autophagy , and autophagy defect in ΔMoend3 is possibly caused by a defect in Pmk1 phosphorylation . Given that MoEnd3 interacts with MoArk1 , a serine/threonine protein kinase , we tested whether the activity of MoEnd3 is regulated by MoArk1 through protein phosphorylation . Mn2+-Phos-tag SDS PAGE was thus performed to detect the phosphorylation of MoEnd3 . Phosphorylated proteins in Mn2+-Phos-tag SDS PAGE are visualized as slower migrating bands compared with the corresponding unphosphorylated proteins [36] . We extracted the MoEnd3:GFP protein from the ΔMoend3/MoEND3:GFP strain . Then the protein was treated with phosphatase or phosphatase inhibitor , and was separated in Mn2+-Phos-tag SDS PAGE followed by analysis with the GFP antibody . The band of MoEnd3:GFP treated with the inhibitor migrated slower than that treated with phosphatase ( Fig 6A ) , indicating that phosphorylation occurs in MoEnd3:GFP . In contrast , the band of MoEnd3:GFP from the ΔMoark1/MoEND3:GFP strain migrated as fast as that of the unphosphorylated MoEnd3:GFP protein treated with phosphatase ( Fig 6A ) , indicating that MoEnd3 phosphorylation is dependent on MoArk1 . Additionally , mass spectrometry was used to identify potential phosphorylated site ( s ) in MoEnd3 . In the strain expressing MoARK1 , one MoEnd3 peptide containing a phosphorylated Ser-222 was detected ( Fig 6B ) , in contrast to none found in the MoARK1 deletion strain . We expressed the MoEnd3 Ser-222 to Ala allele linked to GFP in ΔMoend3 and examined the phosphorylation level of MoEnd3S222A:GFP protein using Mn2+-Phos-tag SDS PAGE . The result showed that the band of MoEnd3S222A:GFP migrated as fast as the band of MoEnd3:GFP extracted from the ΔMoark1/MoEND3:GFP strain ( Fig 6C ) , suggesting that MoEnd3S222A:GFP is a unphosphorylated protein and MoEnd3 Ser-222 is a specific site for MoArk1-mediated phosphorylation . In S . cerevisiae , Ark1p/Prk1p kinases initiate phosphorylation to inhibit endocytic protein functions and promote disassembly of endocytic proteins at the late stage of endocytosis [19] . To further determine whether MoEnd3 function is regulated by MoArk1-mediated phosphorylation at Ser-222 , the constructs of the constitutively unphosphorylated MoEnd3 S222A and phosphomimetic MoEnd3 S222D mutants were introduced into ΔMoend3 , ΔMoark1 , and Guy11 , respectively . Endocytosis was observed following 5 min of hyphal exposure to FM4-64 . We found that MoEND3S222A and MoEND3S222D expressions could not restore endocytosis to ΔMoend3 and ΔMoark1 ( Fig 6D and 6E ) . However , we noticed that MoEND3S222A expression mildly promoted endocytosis . But the MoEND3S222D expression impaired endocytosis in Guy11 , and showed no rescue effect on endocytosis in ΔMoend3 and ΔMoark1 , suggesting the constitutively phosphorylated MoEnd3 interferes with normal MoEnd3 function . We further extracted proteins from appressoria or germinated conidia incubated for 8 h expressing MoEND3S222A and MoEND3S222D and performed Western blot analysis using the phosphor-Pmk1 antibody . We found that MoEND3S222A expression could elevate Pmk1 phosphorylation levels to some degree in ΔMoend3 and ΔMoark1 , in contrast to MoEND3S222D that was unable to induce Pmk1 phosphorylation in ΔMoend3 ( Fig 6F ) . In addition , the appressorium formation assay showed the ΔMoend3/MoEND3S222A strain , but not the ΔMoend3/MobEND3S222D strain , had a higher appressorium formation rate than ΔMoend3 after 10 and 16 h of incubation ( S6 Fig ) . Pathogenicity assay showed only MoEND3S222A expression could partially rescue virulence ofΔMoend3 and ΔMoark1 . Taken together , we concluded that the function of MoEnd3 is negatively regulated by MoArk1-dependent Ser-222 phosphorylation and that this regulation is important for endocytosis , Pmk1 phosphorylation , and virulence . Plants protect themselves against pathogens by evolving multiple layers of innate immunity , which is often associated with the hypersensitive response ( HR ) , reactive oxygen species ( ROS ) accumulation , and the induction of pathogenesis-related ( PR ) genes [37 , 38] . We hypothesized that small lesions and limited IH growth by ΔMoend3 are likely the results of the mutant being unable to suppress the host defense system . We thus measured host ROS production and HR induction using 3 , 3’-diaminobenzidine ( DAB ) and Trypan blue staining , respectively [39–41] and found significant ROS accumulation or HR occurring at 36 hpi in over 50% of rice cells infected by ΔMoend3 , compared with less than 20% by Guy11 and the complemented strains ( S7A , S7B , S7C and S7D Fig ) . Diphenyleneiodonium ( DPI ) functions as a flavoenzyme inhibitor that prevents the activation of NADPH oxidases necessary for ROS generation in plants [41 , 42] . When treated with DPI , 51 . 7% of rice cells infected by ΔMoend3 displayed improved IH grow that 36 hpi and these IH were able to spread to neighboring cells ( S7E Fig ) , indicating that IH growth of ΔMoend3 was arrested by strong plant defense reaction . We examined the transcript levels during the early stages of infection ( 0–36 hpi ) of four rice pathogenesis-related ( PR ) genes ( PR1a , PAD4 , CHT1 and AOS2 ) involved in the salicylic acid and jasmonic acid pathways [5 , 42 , 43] by qRT-PCR and results indicated significantly higher transcription levels of all PR genes elicited by ΔMoend3 infection than by Guy11 infection ( S7F Fig ) . During the early stages of infection , M . oryzae is believed to secrete effector proteins to suppress PTI and facilitate its own growth within rice tissues . The strong immunity triggered by ΔMoend3 led us to hypothesize that the mutant may be impaired in effector secretion . To test whether ΔMoend3 is defective in the secretion of AvrPib and AvrPi9 effectors , conidial suspensions were sprayed onto rice LTH ( a universally susceptible rice variety ) , LTH-Pib ( LTH harboring resistant gene Pib ) , and LTH-Pi9 ( LTH harboring resistant gene Pi9 ) . Guy11 produced many typical virulent-type lesions on LTH and tiny dark-brown HR-type lesions ( a highly resistant response ) in LTH-Pib and LTH-Pi9 ( Fig 7A and 7D ) . The virulent-type lesions are larger than 1 mm in diameter and are considered virulent because conidia will be produced from this type of lesions under high humidity condition [44] . In contrast , the HR-type lesions are smaller than 1 mm , cannot produce conidia , and considered avirulent . ΔMoend3 still could produce virulent-type lesions in LTH , but the lesions were much less than those produced by Guy11 , and ΔMoend3 induced the resistant response in LTH-Pib and LTH-Pi9 , similar to Guy 11 ( Fig 7A and 7D ) . These results suggested that MoEnd3 is dispensable for AvrPib and AvrPi9 triggered host immunity . To test other effectors that are not contained in Guy11 , such as Avr-Pia and AvrPiz-t , constructs containing genes encoding Avr-Pia and AvrPiz-t were introduced into Guy11 and ΔMoend3 . Conidial suspensions of Guy11/Avr-Pia and ΔMoend3/Avr-Pia were sprayed onto LTH and LTH-Pia ( LTH harboring resistant gene Pia ) . Guy11/Avr-Pia was found to have normal infection in LTH and induce aresistant response in LTH-Pia . However , ΔMoend3/Avr-Pia produced typical lesions in LTH-Pia and LTH , suggesting Avr-Pia secretion may be affected in ΔMoend3 ( Fig 7B and 7D ) . Similarly , ΔMoend3/AvrPiz-t was unable to cause a strong resistant response in LTH-Piz-t in comparison to Guy11/AvrPiz-t ( Fig 7C and 7D ) , suggesting that MoEND3 deletion also inhibits AvrPiz-t function . Avr-Pia and AvrPiz-t are cytoplasmic effectors that are preferentially accumulated in the biotrophic interfacial complex ( BIC ) and translocated to the rice cell cytoplasm [45] . We fused Avr-Pia and AvrPiz-t with GFP , expressed them in Guy11 and ΔMoend3 , and observed their localizations at the early stage of infection . In the cells infected by Guy11 , Avr-Pia:GFP and AvrPiz-t:GFP accumulated in over 95% of BIC structures adjacent to primary hyphae ( Fig 7E and 7F ) , in contrast to the cells infected by ΔMoend3 in which less than 10% of BICs contained Avr-Pia:GFP and AvrPiz-t:GFP ( Fig 7E and 7F ) . To further demonstrate the requirement of MoEnd3 for secretion of Avr-Pia and AvrPiz-t , but not AvrPib and AvrPi9 , we observed effector secretion with the strains co-expressing Avr-Pia:GFP and AvrPiz-t:GFP with AvrPib:RFP or AvrPi9:RFP . For Guy11 , we found about 95% of BICs containing AvrPib:RFP or AvrPi9:RFP appeared with Avr-Pia:GFP and AvrPiz-t:GFP ( S8A , S8B , S8C and S8D Fig ) . For ΔMoend3 , more than 90% of BICs showed the presence of AvrPib:RFP or AvrPi9:RFP , but less than 10% of BICs with AvrPib:RFP or AvrPi9:RFP containing Avr-Pia:GFP and AvrPiz-t:GFP . Moreover , RT-PCR analysis for Avr-Pia and AvrPiz-t during infection showed that MoEND3 deletion did not inhibit their expression ( S9 Fig ) , which ruled out the possibility that this secretion defect of ΔMoend3 was caused by the inhibition of effector gene expression . Interestingly , the expression of the MST7S212D S216E allele in ΔMoend3 was unable to induce a resistant response in rice harboring resistant genes ( Fig 7B , 7C and 7D ) and to enrich Avr-Pia:GFP and AvrPiz-t:GFP in BICs ( Fig 7E and 7F ) , suggesting that the two effector secretion may be not directly regulated by Pmk1-MAPK . Moreover , the DAB staining assay indicated that ΔMoend3/MST7S212D S216E failed to suppress ROS responses as effectively as Guy11 ( S10 Fig ) , implying that the expression of the MST7S212D S216E allele still cannot restore effector secretion required for suppressing rice innate immunity . Taken together , we concluded that MoEnd3 facilitates secretion of effectors such as Avr-Pia and AvrPiz-t , but not Avr-Pib and Avr-Pi9 , though a pathway independent of Pmk1 phosphorylation .
Endocytosis is employed by eukaryotic cells to constitutively internalize plasma membrane-associated proteins , lipids , and other molecules for regulating many key cellular functions . In M . oryzae , this process is closely linked to fungal physiology and pathogenicity [23 , 24 , 45–47] . Our current studies provide evidence further supporting this conclusion . Our results show that in addition to having an important role in mating and virulence , MoEnd3-mediated endocytosis is also important for transport of the GPCR Pth11 and the membrane sensor MoSho1 . Significantly , MoEND3 deletion delayed endocytosis of Pth11 and MoSho1 , resulting in delayed appressorium development . Similar to phenotypes in the strains lacking cPKA [48] , the appressoria produced by ΔMoend3 strains showed impaired turgor pressure , inefficient mobilization of glycogen and lipids , and a defect in host penetration . Additionally , we found that MoEnd3 function affects the Pmk1 MAPK signaling pathway . Collectively , our findings support that endocytosis is required for receptor-mediated signaling , development and pathogenesis in M . orzae . Our findings are consistent with observations in other model organisms . For example , in mammalian cells , activation of plasma membrane receptors including receptor tyrosine kinases and GPCR by external agonists is followed by the endocytic receptor transport to the endosome . In the endosome the internalized receptors can interact with key components of various signaling pathways to activate specific signal transduction pathways [49 , 50] . Furthermore , in the biotrophic plant pathogen Ustilago maydis , studies of tSNARE Yup1 revealed that endocytosis controls GPCR Pra1-mediated signaling . Yup1 is co-localized with Rab5-marked early endosomes . A temperature-sensitive mutation of yup1 blocked the fusion of endocytic vesicles with early endosomes and the endocytic recycling pathway [51] . These defects result in depletion of the pheromone receptor Pra1 from the plasma membrane and disruption in pheromone-mediated signal transmission to downstream effectors that would normally trigger pathogenic development [51] . Autophagic cell death in the conidium is necessary for appressorium formation and infection . Previous studies have shown that a Δpmk1 mutant is blocked in autophagic nuclear degradation [33] . We found that constitutively activated Mst7 could accelerate autophagy in the ΔMoend3 mutant . This supports the hypothesis that the severely delayed nuclear degradation and autophagy in ΔMoend3 was caused by a defect in Pmk1-MAPK signaling . This is in agreement with several other studies that also found that MAPK signaling is involved in the autophagic process . In mammalian cells , members of the MAPK family including MAPK1/ERK2 , MAPK8/JNK , MAPK14/p38a and MAPK15 are involved in the control of autophagy [52–54] . In S . cerevisiae , the Slt2-MAPK and Hog1-MAPK signaling pathways were found to be required for mitophagy and pexophagy [55] . Additionally , mammalian and yeast Ark1p/Prk1p serine/threonine kinases initiate phosphorylation of endocytic and actin cytoskeleton components to control endocytosis [19] . We previously reported that MoArk1 regulates endocytosis and pathogenicity and is localized to actin patches in M . oryzae [23] . Here , we demonstrated that MoEnd3 function is regulated by MoArk1 through protein phosphorylation . We further found that neither of the constitutively phosphorylated nor unphosphorylated form of MoEnd3 could properly function in endocytosis , Pmk1 phosphorylation or virulence . Strikingly , the unphosphorylated MoEnd3 could still function to partially suppress the defects of ΔMoend3 and ΔMoark1 . This is in contrast to the constitutively phosphorylated MoEnd3 , which was completely inactive . M . oryzae secretes effectors , such as Slp1 , into rice cells to suppress host immunity [56] . IH growth of ΔMoend3 was found to be arrested suggesting that it was inhibited by a robust host immune response . This could be due to ΔMoend3 being unable to secrete effector molecules . Indeed , we found that the secretion of Avr-Pia and AvrPiz-t was impaired in ΔMoend3 . This finding is in accordance with our earlier studies in which we found that Qc-SNARE MoSyn8 is required for Avr-Pia and AvrPiz-t secretion [45] . However , the secretion of AvrPib and AvrPi9 was not affected in ΔMoend3 , suggesting that secretion of these effectors may involve mechanisms independent of MoEnd3 . Moreover , when Pmk1 phosphorylation was activated by expressing the MST7S212D T216E allele in ΔMoend3 , the secretion of Avr-Pia and AvrPiz-t was still impaired , suggesting that these mechanisms are also independent of Pmk1 signaling . It would be interesting to identify such mechanisms in future studies . Previous studies indicated that there are two distinct effector secretion systems functioning in M . oryzae [2] . The cytoplasmic effectors such as Pwl2 are preferentially accumulated in BIC , and their secretion depends on the t-SNARE protein MoSso1 and exocyst components MoExo70 and MoSec5 . The secretion of apoplastic effectors , such as Bas4 , follows the Golgi-dependent secretion pathway [2] . Some studies also indicated that endocytosis and exocytosis/secretion are obligatorily coupled [57 , 58] . In S . cerevisiae , the perturbation of She4p affects endocytosis and defects in endocytosis result in a slow motion of exocytic vesicles during polarity establishment [59] . This decreased exocytosis could reflect in defects in endocytic recycling of components required for membrane fusion , including certain SNARE proteins [59] . Therefore , it is likely that MoEnd3-mediated endocytosis affects secretion of certain effector proteins and that delayed endocytosis in ΔMoend3 could also affect movement of certain exocytic vesicles required for transporting effector proteins . Ultimately , inhibition of effector secretion could attenuate M . orzae pathogenicity . In summary , our studies demonstrate that the endocytic protein MoEnd3 is required for blast fungus growth and development , endocytic transport of pathogenic GPCRs , interaction with the rice host , and pathogenicity . Together with MoArk1 , MoEnd3 exhibits a regulatory function for multiple processes , including appressorium development and function , autophagy , Pmk1 MAPK transduction , and signaling and regeneration of Pth11 and MoSho1 ( Fig 8 ) . Given that endocytosis is closely coupled with exocytosis , MoEnd3 could have additional roles in facilitating effector secretion to suppress host defenses .
M . oryzae Guy11 was used as the parental wild type strain in this study . All strains were cultured on complete medium ( CM ) agar plates . Liquid CM medium was used to prepare the mycelia for DNA and RNA extraction . For conidia production , strains were maintained on straw decoction and corn ( SDC ) agar media at 28°C for 7 days in the dark followed by 3 days of continuous illumination under fluorescent light [42] . Plugs of mutant and the wild type strain Guy11 ( MAT1-2 ) and the mating partner strain TH3 ( MAT1-1 ) were point inoculated 3 cm apart on oatmeal agar medium and incubated at 20°C under constant fluorescent light for 3 to 4 weeks [60] . The MoEND3 deletion mutant was generated using the standard one-step gene replacement strategy [61] . First , two approximate 1 . 0 kb of sequences flanking of MoEND3 ( MGG_06180 ) were amplified with two primer pairs MoEND3-F1/MoEND3-R1 , MoEND3-F2/MoEND3-R2 , the products of MoEND3 were digested with restriction endonucleases ( EcoRI and SalI , SpeI and SacII ) and ligated with the HPH cassette released from pCX62 . The protoplasts of wild type Guy11 were transformed with the vectors for targeted gene deletion by inserting the hygromycin resistance HPH marker gene cassette into the two flanking sequences of the MoEND3 gene . For selecting hygromycin-resistant transformants , CM plates were supplemented with 250 μg/ml hygromycin B ( Roche , USA ) . To generate complementary construct pYF11-MoEND3 , the gene sequence containing the MoEND3 gene and 1 . 0 kb native promoter was amplified with MoEND3-comF/MoEND3-comR . Yeast strain XK1-25 was co-transformed with this sequence and XhoI-digested pYF11 plasmid . Then the resulting yeast plasmid was expressed in E . coli . To generate the complementary strain , the pYF11-MoEND3 construct containing the bleomycin-resistant gene for M . oryzae transformants screen was introduced into the ΔMoend3 mutant [61] . EcoRV was used to digest the genomic DNA from wild-type strain Guy11 and the ΔMoend3 mutant . The digest products were separated in 0 . 8% agar gel and were hybridized with the MoEND3 gene probe . The probe was designed according to the disruption strategy and was amplified from Guy11 genomic DNA using primers MoEND3-InterF/MoEND3-InterR . To confirm MoEND3 replacements , labeled MoEND3 probe was used to hybridize the EcoRV-digested genomic DNA from the ΔMoend3 mutant and wild-type Guy11 . The copy number of HPH gene in the ΔMoend3 mutant was detected using labeled HPH fragments that amplified from the plasmid of pCB1003 with primers FL1111/FL1112 . The whole hybridization was carried out according to the manufacturer’s instruction for DIG-High Prime [61] . Conidia were harvested from 10-day-old SDC agar cultures , filtered through three layers of lens paper and re-suspended to a concentration of 5×104 spores/ml in a 0 . 2% ( w/v ) gelatin solution . Two-week-old seedlings of rice ( cv . CO39 ) and 7-day-old seedlings of barley ( Hordeum vulgare cv . Four-arris ) were used for pathogenicity assays . For spray inoculation , 5 ml of a conidial suspension of each treatment were sprayed onto rice with a sprayer . Inoculated plants were kept in a growth chamber at 28°C with 90% humidity and in the dark for the first 24 h , followed by a 12 h/12 h light/dark cycle . Lesion formation in rice and barley was observed after 7 and 5 days , respectively [60] . For infection assay with rice tissues , conidia were re-suspended to a concentration of 1×105 spores/ml in a 0 . 2% ( w/v ) gelatin solution . 3-week-old rice cultivar CO-39 was inoculated with 100 μl of conidial suspension on the inner leaf sheath cuticle cells and incubation under humid conditions at 28°C . The leaf sheaths were observed under Zeiss Axio Observer A1 inverted microscope at 36 hpi . For barley epidermis penetration assays , conidia were suspended to a concentration a concentration of 5×104 spores/ml in a 0 . 2% ( w/v ) gelatin solution . Droplets ( 10 μl ) of conidial suspension were placed on detached barley leaf epidermis . The barley epidermis was observed under Zeiss Axio Observer A1 inverted microscope at 24 hpi . Conidia were harvested from 10-day-old cultures , filtered through three layers of lens paper , and re-suspended to a concentration of 5×104 spores/ml in sterile water . For appressorium formation assay , droplets ( 30 μl ) of conidial suspension were placed on plastic cover slips ( Fisher Scientific , St Louis , MO , USA ) under humid conditions at 28°C [62] . Appressorium turgor was determined by cell collapse assay using a 1–4 molar concentration of glycerol solution . The percentages of conidia germinating and conidia forming appressoria were determined by microscopic examination of at least 100 conidia . To visualize glycogen and lipid , KI solution and Neil red were used as described [48] . All the samples were observed under Zeiss Axio Observer A1 inverted microscope ( 40× ) . For DAB staining assay , rice tissues infected by strains at 36 hpi were stained with 1 mg/ml DAB ( Sigma-Aldrich ) solution ( pH 3 . 8 ) for 8 h and destained with an ethanol/acetic acid solution ( ethanol/acetic acid = 98:2 , v/v ) for 1 h . For Trypan blue staining assay , rice tissues infected by strains at 36 hpi were stained with a 2 . 5 mg/ml Trypan blue solution for 1 h and destained in 2 . 5 g/ml lactophenol for 1 h . For evaluating the growth of IH in ROS-suppressed rice sheath , a conidial suspension ( 1×105 spores/ml ) treated with 0 . 5 μm DPI was inoculated into the rice sheath for 36 h . All the samples were observed under Zeiss Axio Observer A1 inverted microscope ( 40× ) . For detection of the rice PR gene transcription during infection stage , total RNA samples were extracted from plants inoculated with the wild-type strain or mutant at 0 , 24 , 48 , and 72 hpi . Transcription of elongation factor 1a gene ( Os03g08020 ) was used as endogenous control in O . sativa . For detection of AVR-Pia and AVRPiz-t transcription during infection stage , total RNA samples were extracted from the strains at 24 and 48 hpi . Transcription of actin gene ( XP 003719871 . 1 ) was used as endogenous control . The qRT-PCR was run on the Applied Biosystems 7500 Real Time PCR System with SYBR Premix Ex Taq ( Perfect Real Time , Takara , Japan ) . Normalization and comparison of mean Ct values were performed as previously described [42] . Bait constructs were generated by cloning MoARK1 and MoACT1 full-length cDNAs into pGBKT7 , respectively . MoEND3 full-length cDNA was cloned into pGADT7 as the prey construct . The prey and bait constructs were confirmed by sequencing analysis . The yeast strain AH109 was transformed with the bait and prey constructs as the description of BD library construction & screening kit ( Clontech , USA ) . The Trp+ and Leu+ transformants were isolated and assayed for growth on SD-Trp-Leu-His-Ade medium [63] . The MoEND3-YFPN plasmid was generated by cloning the MoEND3 gene with a native promoter into the vector pHZ65 containing hygromycin-resistant gene . The MoARK1 gene with a native promoter was cloned into the vector pHZ68 containing bleomycin-resistant gene to generate the MoEND3-YFPC plasmid . The two plasmids were introduced into protoplasts of wild type Guy11 . Transformants resistant to both hygromycin and bleomycin were isolated and examined using fluorescence microscopy ( Zeiss Axio Observer A1 inverted microscope , 40× ) . To construct the plasmids of GST-MoEND3 , His-MoARK1 and His-ACT1 , full-length cDNA of MoEND3 was amplified and inserted into the vector pGEX4T-2 , and full-length cDNAs of MoARK1 and MoACT1 were amplified and inserted into the vector pET-32a , respectively . Then these plasmids were expressed in E . coli strain BL21 ( DE3 ) and bacterial cells were collected and treated by lysis buffer ( 10 mM Tris-HCl [pH 7 . 5] , 150 mM NaCl , 0 . 5 mM EDTA , 0 . 5% Triton x-100 ) . To confirm expression of the GST or His fusion proteins , bacterial lysates were separated by SDS-PAGE gel followed by Coomassie blue staining . In the binding assay for His-MoArk1 and GST-MoEnd3 , bacterial lysate containing His-Ark1 protein was incubated with 30 μl Ni-NTA agarose beads ( Invitrogen , Shanghai , China ) for 1 h at 4°C . Then the beads were washed for five times , incubated with bacterial lysate containing GST-MoEnd3 for 1 h at 4°C , washed for five times again and boiled for elution . The elution was probed with His and GST antibodies ( Abmart , Shanghai , China ) . In the binding assay for His-MoAct1 and GST-MoEnd3 , bacterial lysate containing GST-MoEnd3 protein was incubated with 30 μl GST agarose beads ( Invitrogen , Shanghai , China ) for 1 h at 4°C . Then the beads were washed for five times , incubated with bacterial lysate containing His-MoAct1 for 1 h at 4°C and boiled for elution . The elution was probed with His and GST antibodies ( Abmart , Shanghai , China ) . To construct plasmids of MoARK1:FLAG , PTH11:GFP , MoMSB2:GFP , MoSHO1:GFP , MST7S212D T216E ( RP27 promoter ) , MoEND3:GFP , MoEND3S222A:GFP , MoEND3S222D:GFP , Lifeact:RFP ( RP27 promoter ) , H1:RFP , Avr-Pia:GFP , AvrPiz-t:GFP , AvrPi9:RFP and AvrPib:RFP , their gene fragments were amplified with primers listed in S3 Table and inserted into pYF11 plasmid by transformation with yeast XK1-25 strain . Yeast transformants were isolated from the SD-Trp plates and resulting constructs were amplified by expression in E . coli . FM4-64 ( Molecular Probes Inc . , Eugene , OR , USA ) was solved in distilled water to a final concentration 5 μg/ml . For assaying with hyphae , strains were grown on CM liquid medium for 16 h at 28°C . Before observation , hyphae were washed with distilled water and strained with FM4-64 on glass slide . For assaying with germinated conidia , conidia were inoculated on the coverslips with hydrophobic surface . After 3 h , the dye was added to the conidia for 10 min . Then samples were washed with distilled water . Latrunculin B ( LatB ) ( Cayman , USA ) is stocked in DMSO in a concentration of 25 mg/ml . Conidia incubated on the coverslips with hydrophobic surface were treated with LatB ( final concentration 0 . 1 μg/ml ) for 30 min , while the controls were treated with 5% DMSO . Then samples were washed with distilled water . Cycloheximide ( MedChemExpress , USA ) was solved in distilled water and the germinated conidia were treated with a final concentration 10 μg/ml for 10 min . Then samples were washed with distilled water . Benomyl ( Aladdin , Shanghai , China ) was solved in 0 . 1% DMSO and added to germinated conidia with a final concentration 1 μg/ml . Then the samples were washed with distilled water . All the samples were observed under a fluorescence microscope ( Zeiss LSM710 , 63× oil ) . The filter cube sets: GFP ( excitation spectra: 488 ± 10 nm , emission spectra: 510 ± 10 nm ) , FM4-64 ( excitation spectra: 535 ± 20 nm , emission spectra: 610 ± 30 nm ) . Exposure time: 800 ms . The conidial suspensions ( 1×105 conidia/ml in a 0 . 2% gelatin ) were injected into rice sheath from 3-week-old rice seedlings ( cv . CO39 ) . The BICs in the infected rice cells were observed using fluorescence microscopy ( Zeiss Axio Observer A1 inverted microscope , 40× ) at 24 hpi and the images were captured immediately . The filter cube sets: GFP ( excitation spectra: 488 ±10 nm , emission spectra: 510 ± 10 nm ) , RFP ( excitation spectra: 561 ± 10 nm , emission spectra: 610 ± 10 nm ) . Exposure time: 800 ms . About 150 to 200 mg of mycelia were ground into powder in liquid nitrogen and resuspended in 1 ml of extraction buffer ( 10 mM Tris-HCl [pH 7 . 5] , 150 mM NaCl , 0 . 5 mM EDTA , 0 . 5% Triton x-100 ) with fresh added 1 mM PMSF and 10 μl of protease inhibitor cocktail ( Sigma , Shanghai , China ) . Total proteins were separated on a 12% SDS-PAGE gel and transferred to nitrocellulose membranes . The p44/42 MAPK ( Erk1/2 ) antibody ( Cell Signaling Technology , USA ) was used to detect endogenous Pmk1 expression . The phospho-p44/42 MAPK ( Erk1/2 ) ( Thr202/Tyr204 ) antibody ( Cell Signaling Technology , USA ) was used to detect phophorylated Pmk1 . Thegerminated conidia with 3 h of incubation were treated with cycloheximide and benomyl as described . FRAP were performed using a fluorescence microscope Zeiss LSM710 . Regions containing Pth11:GFP and MoSho1:GFP in germ tube were selected for photo-bleaching . The photobleaching was carried out using an Argon-multiline laser at a wavelength of 488 nm with 90% laser power and 150 iterations in ROI . Images were acquired with 2% laser power at a wavelength of 488 nm every 5 sec . For quantitative analyses , fluorescence intensity was measured using the ZEISS ZEN blue software and fluorescence recovery curves were fitted using following formula: F ( t ) = Fmin + ( Fmax − Fmin ) ( 1-exp−kt ) , where F ( t ) is the intensity of fluorescence at time t , Fmin is the intensity of fluorescence immediately post-bleaching , Fmax is the intensity of fluorescence following complete recovery , and k is the rate constant of the exponential recovery [64] . Mobile Fraction was calculated as the following formula: Mf = ( Fend − F0 ) / ( Fpre − F0 ) , where Fend is the stable fluorescent intensity of the punctae after sufficient recovery , F0 is the fluorescent intensity immediately after bleaching , and Fpre is the fluorescent intensity before bleaching [65] . The MoEND3:GFP fusion construct was introduced into ΔMoend3 and ΔMoark1 mutants , respectively . The proteins extracted from mycelium were resolved on 8% SDS-polyacrylamide gels prepared with 50 μM acrylamide-dependent Phos-tag ligand and 100 μM MnCl2 as described [36] . Gel electrophoresis was run at 80 V for 3–6 h . Prior to transfer , gels were equilibrated in transfer buffer containing 5 mM EDTA for 20 min two times and then in transfer buffer without EDTA for 10 min . Protein transfer from the Mn2+-phos-tag acrylamide gel to the PVDF membrane was performed overnight at 80 V at 4°C , and then the membrane was analyzed by Western blotting using the anti-GFP antibody . To identify phosphorylation sites of targeted proteins , samples were separated on 10% SDS PAGE . The gel bands corresponding to the targeted protein were excised from the gel , reduced with 10 mM of DTT and alkylated with 55 mM iodoacetamide . In gel digestion was carried out with the trypsin/lys-c mix ( Promega , USA ) in 50 mM ammonium bicarbonate at 37°C overnight . The peptides were extracted using ultrasonic processing with 50% acetonitrile aqueous solution for 5 min and with 100% acetonitrile for 5 min . The extractions were then centrifuged in a speed to reduce the volume . A liquid chromatography–mass spectrometry ( LC–MS ) system consisting of a Dionex Ultimate 3000 nano-LC system ( nano UHPLC , Sunnyvale , CA , USA ) , connected to a linear quadrupole ion trap Orbitrap ( LTQ Orbitrap XL ) mass spectrometer ( ThermoElectron , Bremen , Germany ) , and equipped with a nanoelectrospray ion source was used for our analysis . For LC separation , an Acclaim PepMap 100 column ( C18 . 3 μm , 100 Å ) ( Dionex , Sunnyvale , CA , USA ) capillary with a 15 cm bed length was used with a flow rate of 300 nL/min . Two solvents , A ( 0 . 1% formic acid ) and B ( aqueous 90% acetonitrile in 0 . 1% formic acid ) , were used to elute the peptides from the nanocolumn . The gradient went from 5% to 40% B in 80 min and from 40% to 95% B in 5 min , with a total run time of 120 min . The mass spectrometer was operated in the data-dependent mode so as to automatically switch between Orbitrap-MS and LTQ-MS/MS acquisition . Survey full scan MS spectra ( from m/z 350 to 1800 ) were acquired in the Orbitrap with a resolution r = 60 , 000 at m/z 400 , allowing the sequential isolation of the top ten ions , depending on signal intensity . The fragmentation on the linear ion trap used collision-induced dissociation at a collision energy of 35 V . Protein identification and database construction were processed using Proteome Discoverer software ( 1 . 2 version , Thermo Fisher Scientific , Waltham , MA , USA ) with the SEQUEST model . MS/MS-based peptide identifications were accepted if they could be established at greater than 95 . 0% probability , as specified by the Peptide prophet algorithm . Gene sequences can be found in the GenBank database under the following accession numbers: MoEND3 ( MGG_06180 ) , MoARK1 ( MGG_11326 ) , MoACT1 ( MGG_03982 ) , PTH11 ( MGG_05871 ) , MoMSB2 ( MGG_06033 ) , MoSHO1 ( MGG_09125 ) and MST7 ( MGG_00800 ) . | During the interaction between the rice blast fungus Magnaporthe oryzae and the host , the pathogen employs a series of receptors and sensors at the plasma membrane to recognize host surface cues and to activate signal transduction pathways required for appressorium formation and pathogenicity . We found that MoEnd3-mediated endocytosis is responsible for internalization of non-canonical GPCR Pth11 and the sensor MoSho1 to endosomal compartments . This is important for activating the downstream Pmk1 MAPK pathway to control appressorium formation and penetration . MoEnd3 is regulated through phosphorylation by the actin-regulating kinase MoArk1 . In addition , MoEnd3 has a role in establishing effector secretion required for suppressing rice immunity . Our studies provide evidence that endocytosis is required for normal signaling and virulence in M . oryzae . | [
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... | 2017 | MoEnd3 regulates appressorium formation and virulence through mediating endocytosis in rice blast fungus Magnaporthe oryzae |
Cholera is a diarrheal disease causing significant morbidity and mortality worldwide . This study aimed to establish an adult mouse model of Vibrio cholerae-induced diarrhea and to characterize its pathophysiology . Ligated ileal loops of adult mice were inoculated for 6 , 9 , 12 and 18 h with a classical O1 hypertoxigenic 569B strain of V . cholerae ( 107 CFU/loop ) . Time-course studies demonstrated that the optimal period for inducing diarrhea was 12 h post-inoculation , when peak intestinal fluid accumulation ( loop/weight ratio of ∼0 . 2 g/cm ) occurred with the highest diarrhea success rate ( 90% ) . In addition , pathogenic numbers of V . cholerae ( ∼109 CFU/g tissue ) were recovered from ileal loops at all time points between 6–18 h post-inoculation with the diarrheagenic amount of cholera toxin being detected in the secreted intestinal fluid at 12 h post-inoculation . Interestingly , repeated intraperitoneal administration of CFTRinh-172 ( 20 µg every 6 h ) , an inhibitor of cystic fibrosis transmembrane conductance regulator ( CFTR ) , completely abolished the V . cholerae-induced intestinal fluid secretion without affecting V . cholerae growth in vivo . As analyzed by ex vivo measurement of intestinal electrical resistance and in vivo assay of fluorescein thiocyanate ( FITC ) -dextran trans-intestinal flux , V . cholerae infection had no effect on intestinal paracellular permeability . Measurements of albumin in the diarrheal fluid suggested that vascular leakage did not contribute to the pathogenesis of diarrhea in this model . Furthermore , histological examination of V . cholerae-infected intestinal tissues illustrated edematous submucosa , congestion of small vessels and enhanced mucus secretion from goblet cells . This study established a new adult mouse model of V . cholerae-induced diarrhea , which could be useful for studying the pathogenesis of cholera diarrhea and for evaluating future therapeutics/cholera vaccines . In addition , our study confirmed the major role of CFTR in V . cholerae-induced intestinal fluid secretion .
Cholera is a life-threatening disease caused by intestinal infections with a gram-negative bacterium Vibrio cholerae . It has been estimated that cholera affects millions of people and causes several hundreds of thousands of death each year , especially in developing countries [1] . Importantly , the number of cholera cases has increased steadily in recent years , probably due to climate change and more frequent occurrence of natural disasters [2] . The main symptoms of cholera are profuse watery diarrhea and vomiting , which could lead to severe dehydration , hypovolemic shock and , with no appropriate treatment , death . The current treatment of cholera is the use of oral rehydration solution ( ORS ) , with recommended use of antibiotics in moderate and severe cases [3] . However , these treatment strategies have some disadvantages . For instance , efficacy of ORS is reduced in children and elderlies , and even ineffective in severe cholera cases with excess intestinal fluid loss . Treatment benefit of antibiotics may be abated by the emergence of multidrug-resistant strains of V . cholerae [4] . Therefore , great efforts have been paid to develop novel adjunctive therapies of cholera , especially those that can reduce intestinal fluid loss by modulating intestinal fluid secretion and/or absorption processes [5] , [6] . Diarrhea in cholera results from both direct and indirect ( via enteric nervous system ) effects of V . cholerae-derived enterotoxins , especially cholera toxin ( CT ) , on intestinal epithelium [7] . Using cAMP as a second messenger , CT induces transepithelial Cl− secretion , which in turn provides a driving force for Na+ and water secretion [8] . Both in vitro and in vivo experiments demonstrated that cystic fibrosis transmembrane conductance regulator ( CFTR ) mediates CT-induced apical Cl− efflux into intestinal lumen and therefore represents a promising therapeutic target for treatment of cholera [9] . Interestingly , it was recently shown that , in addition to CFTR , unidentified inward rectifying Cl− channels ( IRC ) might help mediate cAMP-activated Cl− efflux across the apical membrane of intestinal epithelial cells [10] . To study the pathophysiology of diarrhea and to evaluate the potential anti-diarrheal therapies for cholera , most previous studies employed rodent and rabbit models of CT-induced intestinal fluid secretion [11] . However , extrapolation of the data obtained from these studies to explain the pathogenesis which would lead to therapeutic intervention of cholera in human proved difficult , since pathogenesis of cholera in human requires coordinated expression by V . cholerae of several other virulence factors other than CT [7] . Indeed , a number of investigations have recently suggested that other non-CT virulence factors produced by V . cholerae and inflammatory response induced by V . cholerae independently of CT may be involved in the pathogenesis of cholera [7] , [12] , [13] . To date , V . cholerae infection models have used both infant rabbits and infant mice [14] . Rabbit infants orally or intestinally inoculated with live V . cholerae have been shown to exhibit massive diarrhea and mucous secretion from goblet cells despite having intact microscopic architecture of intestinal epithelium , resembling pathology of cholera in human [15] . However , developing mouse models of cholera may be preferable to using rabbits for many reasons . Being small and with shorter lifespan , mice are relatively inexpensive , easy to handle and require smaller quantities of compounds/vaccines for therapeutic/preventive evaluation . Transgenic mice are also available for studying cholera pathophysiology . At present , the only established mouse model of V . cholerae infection is an infant mouse model of cholera induced by oral inoculation of V . cholerae . This infant mouse model has been used extensively for studying growth and colonization of V . cholerae in the intestine [16] . However , due to an absence of overt diarrhea and immature development of immune system , this model may not be suitable for studying pathogenesis of diarrhea or for evaluating anti-secretory therapeutics/vaccines of cholera [17] . With an attempt to establish adult animal models of cholera , Basu and Pickett [18] investigated fluid accumulation in ligated ileal loops ( 10-cm long ) inoculated with live V . cholerae ( Inaba strain 569B ) or CT in various laboratory animals including gerbil , rat , hamster , guinea pig , chinchilla , cat and mouse . It was found that other types of animals developed profuse and consistent intestinal fluid secretion , whereas mice showed little or no fluid accumulation at 16 h after intestinal injection of bacteria or CT , despite normal replication of V . cholerae in mouse intestine . Based on the fact that V . cholerae do replicate in adult mouse intestine as shown by Basu and Pickett [18] , and that CT has been found by a number of investigators including our groups to cause consistent and significant intestinal fluid secretion in closed 2–3 cm intestinal loops of adult mice [19] , [20] , we hypothesized that V . cholerae might induce diarrhea in adult mice under condition optimal for V . cholerae expression of their virulence factors , especially CT . In this study , we aimed to establish an adult mouse model of V . cholerae-induced diarrhea using a closed ileal loop approach , and to use it to investigate the underlying pathophysiology of diarrhea . A closed ileal loop approach was chosen because V . cholerae has been known to preferentially colonize distal small intestine particularly ileum [15] and secondly , a closed loop system allows direct and accurate quantitation of the intestinal fluid secretion , a pathophysiological hallmark of cholera . In this study , we demonstrated that V . cholerae ( Inaba strain 569B ) challenges into the ligated 2–3 cm ileal loops of adult ICR outbred mice consistently produced intestinal fluid accumulation in 12 h after inoculation in a CFTR-dependent manner .
This study has been approved by the Institutional Animal Care and Use Committee of the Faculty of Science , Mahidol University ( permit number 240 ) . This study was performed in accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health . Vibrio cholerae 569B Inaba ( classical , O1 strain ) was used in this study . Bacteria were grown in Thiosulfate-Citrate-Bile-Sucrose ( TCBS ) agar and then duplicated using Luria Broth ( LB ) plate . To prepare the inoculum , V . cholera were cultured at 37°C overnight in LB . The overnight culture were then subcultured into fresh LB at the ratio of 1∶100 and grown to a mid-log phase . V . cholerae cells were collected by centrifugation and the pellet was re-suspended in phosphate buffered saline to obtain the inoculum containing 108 CFU of V . cholera/ml . CT was purchased from List Biological Laboratories , Inc . ( Campbell , CA , USA ) . CFTRinh-172 was purchased from Calbiochem ( San Diego , CA , USA ) . Fluorescein isothiocyanate-linked dextran ( FITC-dextran; molecular weight of 4 . 4 kDa ) and other chemicals were obtained from Sigma-Aldrich ( St . Louis , MO , USA ) . Six-week-old ICR outbred mice ( weight 30–35 g ) were acquired from the National Laboratory Animal Center , Bangkok , Thailand . Before surgery , mice were fasted for 24 h and anesthetized by intraperitoneal injection of nembutal ( 60 mg/kg ) . While maintaining the body temperature at 37°C using a heating pad , a small abdominal incision was made and a loop of distal ileum was isolated by suture ( 2–3 cm in length ) . The closed ileal loop was instilled with 100 µl of phosphate buffered saline ( PBS ) or PBS containing V . cholerae ( 107 CFU/loop ) . After abdominal closure by suture , mice were allowed to recover from anesthesia . At specific time points after bacterial inoculation ( 6 , 12 , 18 , 24 h ) , the mice were re-anesthetized and ileal loops were exteriorized for measurements of weight/length ratio . Mice with intestinal weight/length ratio of al least 0 . 1 g/cm were considered as having positive diarrheal response . Diarrhea success rates ( % diarrhea ) were computed by dividing a number of surviving mice with intestinal loop weight/length ratio of at least 0 . 1 g/cm by a total number of surviving mice at a specific time point . In the study of CT-induced diarrhea , ileal loops were instilled with PBS or PBS containing CT ( 1 µg/loop ) , and loop weight/length ratio was quantified 4 h later . In some experiments , CFTRinh-172 ( 20 µg in 0 . 1 ml of DMSO ) was intraperitoneally administered every 6 h until euthanasia . For bacterial colonization assays , ileal loops at various time points after V . cholerae inoculation were homogenized in PBS , followed by serial dilutions and plating on LB agar for colony forming unit ( CFU ) counting . Amount of CT in fecal fluid was quantified using GM1 enzyme-linked immunosorbent assay . Briefly , 100 µl of sample , standard CT in PBS or PBS alone was added to GM1-coated 96-well plates in duplicate and incubated at 37°C for 1 h . The plate was then washed three times with PBS before addition of goat-anti CTb serum . An hour later , rabbit anti-goat globulin was added to the plate and incubated for 60 min . The substrate solution was then added and incubated for 30 min . The reaction was stopped by adding 50 µl of 3M NaOH and absorbance at 405 nm was measured using a microplate reader ( BMG LABTECH , Victoria , Australia ) . The amount of CT was calculated according to the manufacturer's instructions . Ileal loops were opened longitudinally , washed with PBS and mounted in the Ussing chamber system ( Physiologic Instruments Inc . , San Diego , CA , USA . ) . Both apical and basolateral hemichambers were filled with Kreb's bicarbonate buffer containing ( in mM ) 120 NaCl , 25 NaHCO3 , 3 . 3 KH2PO4 , 0 . 8 K2HPO4 , 0 . 5 MgCl2 and 10 glucose ( pH 7 . 4 ) . The solution was continuously bubbled with 5% CO2/95% O2 and maintained at 37°C . Electrical resistance of the intestinal tissues was calculated using values of passing current and transmembrane voltage recorded by a voltage/current clamp machine with Ag/AgCl electrodes and 1 M KCl agar bridges ( Physiologic Instruments Inc . , San Diego , CA , USA . ) . Intestinal paracellular permeability was estimated using the measurement of FITC-dextran ( molecular weight 4 . 4 kDa ) flux from the intestine to the blood as previously described [21] . Briefly , at 12 h after instillations of PBS , PBS containing V . cholerae ( 107 CFU/loop ) or PBS containing CT ( 1 µg/loop ) into ileal loops , mice were anesthetized and intestinal fluid was removed and replaced with 0 . 2 mL of PBS containing 20 mg of FITC-dextran . Thirty min afterwards , mice were sacrificed and blood was collected by cardiac puncture . Blood was centrifuged at 3 , 000 g for 10 min ( 4°C ) and the serum was collected for measurement of FITC-dextran using a fluorospectrophotometer ( Bio-Tek Instrument , Helsinki , Finland ) . The amount of FITC-dextran in the sample was estimated from the standard curve generated by fluorometric measurements of FITC-dextran at known concentrations . Intestinal tissues dissected from ileal loops were fixed for 24 h in 10% formaldehyde , followed by tissue dehydration using graded alcohol and paraffin embedding . The processed tissues were cut into 5 µm-thick sections and stained with hematoxylin and eosin ( H&E ) reagents or periodic-acid Schiff ( PAS ) reagent . Tissue slices were visualized under light microscope for histological analysis . Concentration of albumin in fluid in ileal loops was determined using a bromcresol purple ( BCP ) dye-binding method as previously described [22] . In brief , the obtained sample was mixed with the BCP reagent and the absorbance at 600 nm was measured using the automated Dimension RxL Max analyzer ( Siemens Healthcare Diagnostics Inc . , Tarrytown , NY , USA ) . The data were presented as mean ± standard error ( S . E . ) . Statistical analyses for two-group and multiple comparisons were performed using Student's t test and one-way analysis of variance ( ANOVA ) , followed by Bonferroni's post-hoc test , respectively . P value of <0 . 05 was considered statistically significant .
Vibrio cholerae 569B of classical O1 Inaba strains ( 107 CFU/loop ) , a bacterial strain known to possess high diarrheagenic potential [18] , was inoculated into the ligated ileal loop of 2–3 cm length . This length of intestinal loops was previously shown by our group to be optimal for detecting CT-induced excessive intestinal fluid secretion in adult mice [19] , [20] . We first sought to determine the optimal incubation periods for V . cholerae-induced intestinal fluid secretion by analyzing three parameters , i . e . , the amount of intestinal fluid secretion , percent of mice developing fluid accumulation ( loop weight/length ratio of at least 0 . 1 g/cm ) , and survival rate of mice at different time points ( 6 , 9 , 12 to 18 h ) after V . cholerae inoculation . As depicted in Fig . 1A , intestinal fluid secretion increased over time and reached its peak at 12 h after V . cholerae inoculation ( loop weight/length ratio = 0 . 203±0 . 037 g/cm ) . This level of intestinal fluid secretion was sustained until 18 h post-inoculation ( loop weight/length ratio = 0 . 192±0 . 042 g/cm ) . Diarrhea success rate , which indicated model reproducibility , and survival rate of mice were 90% and 80% at 12 h post-inoculation , and 68% and 50% at 18 h post-inoculation , respectively ( Fig . 1B ) . Therefore , an optimal incubation period for induction of diarrhea by V . cholerae was 12 h . It was also noted that higher inoculation doses of V . cholerae ( 108–109 CFU/loop ) caused lethality in more than 80% of mice within 6 h after bacterial challenge without inducing fluid secretion . We thought that circulatory failure resulting from V . cholerae-induced systemic inflammatory response might account for this death . Subsequent experiments were performed to characterize the pathophysiology of this cholera model . Pathogenesis of diarrhea in cholera required V . cholerae colonization and production of CT [14] . To gain insight into the mechanism of diarrhea in this model , the amount of V . cholerae in the intestinal loops ( intestinal fluid plus intestinal tissues ) and CT in intestinal fluid were determined . As shown in Fig . 2 , the number of V . cholerae recovered from the intestinal loops at all time points ( 6 h , 9 h , 12 h and 18 h ) after inoculation was ∼109 CFU/gram of tissues . This amount of V . cholerae was comparable to that recovered from the intestine of infant rabbit models of V . cholerae infection-induced diarrhea [15] , suggesting that V . cholerae was capable of colonizing the intestine in our mouse cholera model . Using GM1 ELISA assays , the amount of CT in intestinal fluid was found to be 1 . 688±0 . 563 µg/ml at 12 hour post-inoculation , whereas none was detected in the ileal loop instilled with PBS ( no V . cholerae ) . These data indicated that V . cholerae established colonization and expressed CT in the closed ileal loop in this mouse cholera model . It has been known that CFTR-mediated transepithelial Cl− secretion provides the driving force for CT-induced intestinal fluid secretion [9] . To estimate the relative contribution of CFTR-mediated Cl− secretion to the pathogenesis of diarrhea in this model , the effect of CFTRinh-172 , a CFTR inhibitor , on V . cholerae-induced intestinal fluid secretion was investigated . In this experiment , CFTRinh-172 ( 20 µg ) was intraperitoneally administered at the time of V . cholerae inoculation and 6 h thereafter , and mice were sacrificed for measurements of intestinal fluid secretion ( loop weigh/length ratio ) at 12 h after V . cholerae inoculation . This dosage regimen of CFTRinh-172 was used because it was previously shown to produce maximal degrees of inhibition of CT-induced intestinal fluid secretion in mice ( ∼90% inhibition ) [23] . Interestingly , we found that treatment with CFTRinh-172 completely prevented V . cholerae-induced intestinal fluid accumulation ( Fig . 3 ) . In addition , effects of CFTRinh-172 on V . cholerae growth were determined both in vitro and in vivo . Addition of V . cholerae for 24 h with CFTRinh-172 ( at 20 µM , a concentration at which CFTRinh-172 is maximally soluble in saline and fully inhibits CFTR-mediated Cl− secretion in intact intestinal epithelia ) to the 5×108 CFU/ml of V . cholerae in Mueller Hinton Broth did not affect V . cholerae growth as enumerated by a spread plate method ( data not shown ) . Moreover , amounts of V . cholerae recovered from V . cholerae-inoculated ileal loops of CFTRinh-172-treated mice were not statistically different from that of control ( V . cholerae inoculation with no CFTRinh-172 treatment ) ( data not shown ) . These data indicated that CFTRinh-172 inhibited V . cholerae-induced intestinal fluid secretion without affecting V . cholerae growth in ileal loops in vivo . Possibility of paracellular leakage as a cause of V . cholerae-induced intestinal fluid accumulation was investigated using both ex vivo measurements of transepithelial electrical resistance ( TEER ) of mouse intestine by Ussing chamber systems and in vivo FITC-dextran trans-intestinal flux assays . As shown in Fig . 4A , TEER of V . cholerae-inoculated intestinal tissues was not significantly different from that of saline-injected control and CT-injected groups ( 268 . 87±13 . 80 Ω·cm2 , 266 . 21±19 . 59 Ω·cm2 and 240 . 79±4 . 20 Ω·cm2 , respectively ) . In order to confirm that V . cholerae infection had no effect on the intestinal paracellular permeability , in vivo FITC-dextran trans-intestinal flux assays were performed . In this experiment , FITC-dextran was injected into the intestinal loops and serum level of FITC-dextran was measured 30 min thereafter . It was found that V . cholerae infection had no effect on serum FITC-dextran compared with saline control and CT-injected groups ( Fig . 4B ) . Taken together , our results suggested that paracellular permeability of the mouse intestine was unaltered by V . cholerae infection and CT exposure . To determine the contribution of vascular leakage to V . cholerae-induced intestinal fluid accumulation in this model , the amount of the plasma protein albumin was determined in fecal fluids of both control ( no V . cholerae ) and V . cholerae-inoculated mice . It was found that levels of albumin in fecal fluid of both control and V . cholerae-inoculated intestinal loops were under detection limit ( <0 . 3 g/dL ) . This result indicated that vascular leakage did not contribute to the development of diarrhea in this experimental model of cholera . To investigate the microscopic changes of the intestinal tissues after infection with V . cholerae , the V . cholerae-infected and normal saline-injected control loops were subjected to histological examination . As shown in Fig . 5A , V . cholerae-infected tissues showed diffuse edema of the submucosal area and marked enlargement of the internal structures of intestinal villi compared to control . Furthermore , vascular congestion ( arrows , Fig . 5A ) and inflammatory cell infiltration ( arrowheads , Fig . 5A ) were noted in V . cholerae-infected intestinal tissues . In addition , mucin secretion , a phenotypic response of mucin-containing goblet cells to V . cholerae infection , was analyzed by periodic acid-Schiff ( PAS ) staining , which detects mucin in tissues . As depicted in Fig . 5B , V . cholerae-infected intestine showed a marked reduction in PAS-positive goblet cells ( arrows ) compared with control , indicating empty goblet cells after secreting mucin in response to V . cholerae infection . These findings indicated that this animal model resembles human cholera in a histological context .
To date , several animal models have been developed for cholera research . Most of these models are generated using both live V . cholerae or its virulence factors especially CT . The only V . cholerae infection model that manifests severe watery diarrhea was the infant rabbit model [15] . In this study , we established a ligated ileal loop model of V . cholerae infection in adult mice . In this model , inoculation of 107 CFU of V . cholerae into closed ileal loops of 2–3 cm length led to massive intestinal fluid secretion , with the optimal period for induction of fluid secretion being 12 h after inoculation . Importantly , CT at the amount reported to elicit intestinal fluid secretion was detected in the intestinal fluid . Furthermore , we provided the evidence that this model might be beneficial for studying pathophysiology of fluid secretion during V . cholerae infection and for evaluation of anti-secretory therapy of cholera . More than four decades ago , it was reported that V . cholerae inoculation ( 5×107 CFU/loop ) into 10 cm-long ileal loops failed to cause fluid secretion [18] . Using the same strains of mice and V . cholerae , but shorter ileal loops , we successfully established a reproducible V . cholerae-induced diarrhea model in adult mice . Successful establishment of diarrhea model in the present study may be due to 1 ) optimal proportion of the amount of inoculated V . cholerae and length ( i . e . volume ) of ileal loops , and 2 ) optimal environment in distal ileum . Proportion between numbers of V . cholerae and volume of ileal loops determines the density of V . cholerae , which in turn affects V . cholerae expression of virulence factors including a colonizing factor toxin-coregulated pilus ( TCP ) and CT via quorum sensing mechanisms [24] . In addition , the shorter ileal loop mostly composed of distal ileum may create optimal environment for V . cholerae expression of virulence factors . These environmental factors include concentrations of bile and HCO3− in the ileal loops . V . cholerae expression of TCP and CT has previously been shown to be repressed and enhanced by unsaturated fatty acids in bile ( e . g . arachidonic , linoleic , and oleic acids ) and HCO3− , respectively [25] , [26] . The ability of V . cholerae to multiply and express CT in ileal loops in our study suggests the existence of environmental signals suitable for virulence expression of V . cholerae . Time course of intestinal fluid secretion in the established cholera model is in accord with the prior knowledge regarding pathogenesis of V . cholerae-induced diarrhea . In this study , we found that 12-h period of V . cholerae incubation was required to obtain maximal intestinal fluid secretion . Since it was previously reported that maximal fluid secretion of mouse ileum required at least 6 h of exposure to CT [23] , it is therefore estimated that V . cholerae colonized and expressed CT in the ileal loops within 6 h after inoculation in our model of study . In support of this notion , previous study demonstrated that V . cholerae expression of virulence factors including colonizing factors ( e . g . TCP ) and CT occurred within 4 h after bacterial inoculation [27] . Furthermore , attainment of the pathogenic amount of V . cholerae ( ∼109 CFU/g tissue ) at 6 h post-inoculation in our study affirmed that V . cholerae colonization and virulence expression had occurred within the first 6-h of V . cholerae exposure . Interestingly , time course of diarrhea in our model was similar to that in canine cholera model , in which diarrhea developed at 6–12 h after inoculation of V . cholerae into duodenal lumen [28] . Investigation of pathophysiological mechanisms underlying diarrhea in this new cholera model has highlighted CFTR as a therapeutic target for treatment of cholera . A number of previous investigations have demonstrated that CFTR inhibitors reversed CT-induced intestinal fluid secretion in both rats and mice [29] . However , the exact therapeutic value of CFTR inhibitor in the treatment of cholera has been elusive , since anti-diarrheal efficacy of CFTR inhibitors has never been investigated in animal models of V . cholerae-induced diarrhea . In fact , pathophysiology of diarrhea induced by CT and V . cholerae might be different , as V . cholerae can express several enterotoxins other than CT , which may participate in development of profuse diarrhea in cholera [7] . In support of this statement , some experimental therapeutics that were effective in mouse closed loop models of CT-induced fluid secretion such as racecadotril , an enkephalinase inhibitor , was subsequently found to produce no benefit in cholera patients , indicating the need to evaluate potential utility of anti-diarrheal therapeutics using V . cholerae-induced diarrhea models [30] . Of particular importance , a recent study in human intestinal epithelial ( T84 ) cells revealed the signaling crosstalk between cAMP and Ca2+ , which thus raised the possibilities that calcium-activated Cl− channel ( CaCC ) -mediated transepithelial Cl− secretion may contribute to fluid secretion in cholera [10] . In this study , we showed that CFTRinh-172 , a small molecule CFTR inhibitor which inhibits CFTR but not CaCC [31] , completely abrogated V . cholerae-induced intestinal fluid secretion . This finding indicates the predominant role of CFTR-mediated Cl− secretion in providing the driving force for intestinal fluid secretion during V . cholerae infection . In addition , we provided evidence that paracellular and vascular leakage were not involved in the pathogenesis of V . cholerae-induced intestinal fluid secretion in this cholera model . This observation , together with the inhibitory effect of CFTRinh-172 on V . cholerae-induced intestinal fluid secretion , suggests that CFTR-mediated Cl− secretion is the major pathophysiological event leading to secretory diarrhea at least in the early phase ( ∼12 h ) of V . cholerae infection and could be the important target of anti-secretory drug for cholera . In addition , this diarrhea model might be beneficial for cholera research , especially for further investigation of the underlying pathophysiology of secretory diarrhea in cholera , and for evaluation of anti-secretory therapy of cholera . Importantly , due to the maturation of immune system in the adult mice , this cholera model could be used for evaluating preventive efficacy of cholera vaccine In summary , we have established the ligated ileal loop model of V . cholerae-induced diarrhea in adult mice . Pathogenesis of diarrhea in this cholera model results from CFTR-mediated transepithelial Cl− secretion with no involvement of disrupted intestinal barrier function or vascular leakage . This animal model may be beneficial for studying pathogenesis of diarrhea and evaluating potential anti-secretory therapies as well as vaccines for cholera . | Cholera is a diarrheal disease causing significant morbidity and mortality worldwide . Vibrio cholerae , the causative agent of cholera , colonizes the intestine and induces massive intestinal fluid secretion through actions of its enterotoxins , especially cholera toxin . We have developed a ligated ileal loop model of V . cholerae-induced diarrhea in adult mice , in which inoculation of V . cholerae ( 107 CFU/loop ) consistently caused intestinal fluid secretion in 12 h . Interestingly , administration of CFTRinh-172 , a small molecule CFTR inhibitor , completely abolished V . cholerae-induced intestinal fluid secretion , indicating that CFTR plays a pivotal role in the pathogenesis of diarrhea in this model . Furthermore , we demonstrated that intestinal fluid accumulation in this model was neither caused by increased intestinal paracellular permeability nor enhanced vascular leakage . This adult mouse model of V . cholerae-induced diarrhea could be very useful in the studies of pathogenesis of V . cholerae infection-induced diarrhea and in the evaluation of potential therapies/cholera vaccines . | [
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] | [
"medicine",
"infectious",
"diseases",
"gastroenterology",
"and",
"hepatology",
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] | 2013 | An Adult Mouse Model of Vibrio cholerae-induced Diarrhea for Studying Pathogenesis and Potential Therapy of Cholera |
Infectious diseases have been paramount among the threats to health and survival throughout human evolutionary history . Natural selection is therefore expected to act strongly on host defense genes , particularly on innate immunity genes whose products mediate the direct interaction between the host and the microbial environment . In insects and mammals , the Toll-like receptors ( TLRs ) appear to play a major role in initiating innate immune responses against microbes . In humans , however , it has been speculated that the set of TLRs could be redundant for protective immunity . We investigated how natural selection has acted upon human TLRs , as an approach to assess their level of biological redundancy . We sequenced the ten human TLRs in a panel of 158 individuals from various populations worldwide and found that the intracellular TLRs—activated by nucleic acids and particularly specialized in viral recognition—have evolved under strong purifying selection , indicating their essential non-redundant role in host survival . Conversely , the selective constraints on the TLRs expressed on the cell surface—activated by compounds other than nucleic acids—have been much more relaxed , with higher rates of damaging nonsynonymous and stop mutations tolerated , suggesting their higher redundancy . Finally , we tested whether TLRs have experienced spatially-varying selection in human populations and found that the region encompassing TLR10-TLR1-TLR6 has been the target of recent positive selection among non-Africans . Our findings indicate that the different TLRs differ in their immunological redundancy , reflecting their distinct contributions to host defense . The insights gained in this study foster new hypotheses to be tested in clinical and epidemiological genetics of infectious disease .
Plants and animals have developed complex innate mechanisms to recognize and respond to attack by pathogenic microorganisms . The innate immune system is a universal and evolutionarily ancient mechanism at the front line of host defense against pathogens [1]–[3] . In vertebrates , invertebrate animals and plants , innate immunity relies on a diverse set of germline-encoded receptors referred to as pathogen- or pattern-recognition receptors ( PRRs ) , or microbial sensors , which recognize molecular motifs shared by specific groups of microorganisms ( often referred to as pathogen-associated molecular patterns or PAMPs ) [2]–[6] . The last decade has seen a number of key advances in the understanding of PRR-mediated immunity , with Toll-like receptors ( TLRs ) being one of the largest and best studied families of PRRs [7]–[9] . The prototype of the TLR family is the toll gene in Drosophila , first identified for its role in dorso-ventral embryo patterning [10] , [11] and later shown to be critical for effective immune responses in adult flies against fungi and Gram-positive bacteria [1] , [12] . Since then , homologs of the Drosophila toll have been identified in many other species , with vertebrates typically having a repertoire of 10 to 12 TLRs [13] , [14] . The role of mammalian TLRs in host defense has been studied mainly on the basis of their stimulation by different agonists in vitro , and knocked-out mice for one or several TLRs show variable susceptibility to various experimental infections [15]–[17] . Today , TLRs are known to respond to various pathogen-associated stimuli and transduce the signaling responses that are required for the activation of innate immunity effector mechanisms and the subsequent development of adaptive immunity [4] , [9] , [18] . In humans , the TLR family consists of 10 functional members ( TLR1-TLR10 ) [4] , [9] , [14] , [19] , [20] . Human TLRs can be classified based on subcellular distribution: TLR3 , TLR7 , TLR8 and TLR9 are typically located in intracellular compartments such as the endosomes , whereas TLR1 , TLR2 , TLR4 , TLR5 and TLR6 are generally expressed on the cell surface [4] . TLRs can be further classified based on known agonists . Intracellular TLRs sense nucleic acid-based agonists and are particularly specialized in viral recognition , whereas cell-surface expressed TLRs detect various other products , such as glycolipids , lipopeptides and flagellin , which are present in a large variety of organisms including bacteria , parasites and fungi [4] , [21] . TLR10 , which is expressed on the cell surface , remains the only orphan TLR member: its agonists and specific functions are currently unknown . The contribution of human TLRs to host defense in the course of natural , as opposed to experimental , infections has only recently begun to be deciphered . Patients with MyD88 or IRAK-4 deficiency , who do not respond to most TLR agonists with the exception of TLR3 and , to a lesser extent , TLR4 agonists , suffer from life-threatening infections caused by pyogenic bacteria [22]–[24] . Conversely , patients with UNC-93B deficiency , unresponsive to TLR3 , TLR7 , TLR8 , and TLR9 stimulation , and patients with TLR3 deficiency , present with an apparently selective predisposition to herpes simplex virus-1 infection [25] , [26] . Epidemiological genetics studies have investigated the contribution of genetic variation in TLRs , particularly for TLR2 , TLR4 and TLR5 , to susceptibility to infectious diseases ( for a review , see [27] ) . However , the clear involvement of these TLRs in the complex genetic control of infectious pathogenesis has not been unambiguously demonstrated in most cases . The evolutionary genetics approach has increased our understanding of the evolutionary forces that affect the human genome providing an indispensable complement to clinical and epidemiological genetics approaches [28]–[30] . In the context of infection , identifying the extent and type of natural selection acting upon genes involved in immunity-related processes can provide insights into the mechanisms of host defense mediated by them as well as delineate those genes being essential in host defenses with respect to those exhibiting higher immunological redundancy [31]–[33] . In humans , the evolutionary approach has been successfully used for loci principally involved in adaptive immune responses or encoding for erythrocyte surface proteins ( particularly malaria-related genes ) . For example , the excess of worldwide diversity at both HLA class I and II genes [34]–[37] and killer cell immunoglobulin-like receptors [38] , as well as the high frequencies of the HbS allele [39]–[41] and the DARC null allele [42] , [43] in Africa , clearly attest for the action of natural selection on host genes in response to pathogen presence . In the context of innate immunity , TLRs constitute the best characterized family of PRRs , yet the extent to which the different members of human TLR family have been subject to natural selection remains largely unknown . Furthermore , it has been speculated that the set of human TLRs could be redundant with other PRRs for protective immunity against most microbes [44] . Here , we investigated the evolutionary contribution of human TLRs to host defense by examining how natural selection has acted upon the different members of this family of microbial sensors in humans . We show that the different TLRs differ in their biological relevance and provide clues for their different contributions to host defense .
Our population-based resequencing effort allowed us to identify 457 single nucleotide polymorphisms ( SNPs ) , 103 of which corresponded to nonsynonymous mutations ( Table S3 ) . These extensive dataset provides with unbiased information on the number of tagging SNPs — the minimal set of SNPs needed to characterize haplotype diversity fully — required in each major population group in association studies concerning individual TLRs and infectious disease susceptibility ( Table S4 ) . In general , we observed large fluctuations in the overall levels of nucleotide diversity for the different TLR members ( Figure 1 , Table 1 ) . Worldwide , TLR4 , TLR7 and TLR9 were the least diverse , whereas TLR10 was by far the most diverse gene with a 2-fold increase of general diversity with respect to the mean values observed for the twenty noncoding regions . For all TLR family members , with the exception of TLR1 , genetic diversity was higher in Africans with respect to both Europeans and East Asians ( Figure 1 , Table 1 ) , in agreement with the recent African origin of modern humans [45] , [46] . At the haplotype level , we observed the same picture with Africans showing higher levels of haplotype diversity than non-African samples ( Table 1 ) . The only departure from this trend was observed at TLR5 , which exhibited higher levels of haplotype diversity in non-Africans with respect to African populations . To identify specific human TLR genes with evidence of selection since the divergence of the human and the chimpanzee lineages , we applied a statistical approach — the McDonald-Kreitman Poisson Random Field ( MKPRF ) test — that makes efficient use of McDonald-Kreitman ( MK ) contingency tables [47]–[49] . The MK contingency tables summarize the number of nonsynonymous and synonymous fixed differences between species ( i . e . , human and chimpanzee ) and the number of nonsynonymous and synonymous polymorphisms within humans . Under neutrality , the ratio of the number of fixed differences between species to polymorphisms within species is expected to be the same for both nonsynonymous and synonymous mutations . Deviations from this expectation are indicative of natural selection: weak negative and/or balancing selection will result in an excess of nonsynonymous polymorphisms with regard to nonsynonymous divergence , and positive selection will lead to an excess of nonsynonymous divergence with respect to nonsynonymous polymorphisms . By explicitly taking into account shared parameters across genes ( e . g . , species divergence time ) , the MKPRF increases the power of the classical MK test and allows a more explicit estimation of the strength and direction of selection acting on individuals genes [48] , [49] . The MKPRF enables the discovery of positive selection in evolutionarily constrained genes as well as the differentiation of weak from strong purifying selection . The parameters estimated by this method are ω , the ratio between the nonsynonymous and synonymous mutation rates , the species divergence time , and the selection coefficient ( γ ) of nonsynonymous polymorphisms ( for details , see Material and Methods ) . We first estimated ω on individual TLR genes; ω ( i . e . , ω = log[θR/θS] ) measures the selective constraint on amino-acid mutations . θR and θS are estimates of the rate of amino-acid replacement and silent mutations [47]–[50] . Under neutrality , ω is not significantly different from 1 . Lower values are consistent with selection against nonsynonymous variants ( purifying selection ) , whereas higher values reflect selection favoring amino-acid mutations ( positive selection ) . With the exception of TLR1 that presented an ω value of 1 . 11 , all other TLRs had a posterior mean ω estimate lower than 1 , suggesting that all these genes have been targeted by purifying selection to some extent . This type of selection eliminates almost all new nonsynonymous mutations from the population ( θR≪θS ) because their occurrence is not tolerated ( e . g . , lethal or strongly deleterious mutations ) [28] , [29] . Among the ten TLRs , TLR3 , TLR7 , TLR8 and TLR9 are those evolving under the strongest purifying selection , with ω values significantly lower than 1 ( Figure 2A , Table S5 ) . Interestingly , these four TLRs correspond to those receptors known to recognize nucleic acids and involved primarily in the recognition of viruses [21] , [51] . This observation clearly demonstrates that these four TLRs have been subject to stronger purifying selection in humans with respect to the other TLR genes . Next , we used the population selection parameter γ [47] , [49] to identify TLR genes subject to selection operating on nonsynonymous mutations that are polymorphic in humans ( i . e . , non lethal mutations , Material and Methods ) . The parameter γ is negative if a gene displays excess of amino acid polymorphism within humans with respect to amino-acid divergence between species ( weak negative and/or balancing selection ) . In contrast with purifying selection , weak negative selection does tolerate the occurrence of nonsynonymous mutations provided that they do not increase in frequency within the population ( non lethal but slightly deleterious mutations ) [28] , [29] . Conversely , positive γ values reflect an excess of amino-acid divergence with respect to that observed for silent sites ( positive selection ) [49] . The posterior means of the γ draws for the different TLRs ranged from −1 . 13 to 0 . 49 , with a clear tendency towards negative values ( Figure 2B , Table S6 ) . Nonetheless , only TLR1 , TLR4 and TLR10 had the 95% confidence intervals entirely lower than neutral expectations ( i . e . , γ = 0 ) . The excess of nonsynonymous polymorphism observed at these three genes could testify either an advantage to maintain functional diversity ( balancing or frequency-dependent selection . ) or the action of weak negative selection . However , most nonsynonymous variants are observed at very low population frequencies ( nonsynonymous vs . silent mutations; χ2 test , P = 2 . 7×10−3 , Figure S1 ) , suggesting that weak negative selection is the most likely force operating on mutations causing amino-acid changes at these three genes . Taken together , our results revealed differences in the evolutionary constraint acting on TLRs: nucleic acid sensors ( TLR3 , TLR7 , TLR8 and TLR9 ) , for which nonsynonymous mutations are most likely deleterious , and the remaining TLRs , which evolve to different extents under more relaxed selective constraints . This dichotomy was further supported by comparisons of joint estimates of the strength of purifying ( ω ) and negative ( γ ) selection between these two groups . Little overlap was found between the two distributions ( Figure 2C ) . For TLRs sensing nucleic acids , the mean estimates of ω and γ were 0 . 17 [95% CI 0 . 09 to 0 . 31] and 0 . 83 [95% CI −0 . 11 to 2 . 2] , respectively . For the cell-surface expressed TLRs , the mean estimates of ω and γ were 0 . 8 [95% CI 0 . 59 to 1 . 06] and −0 . 7 [95% CI −1 . 13 to −0 . 31] , respectively . These results are therefore consistent with major differences in the intensity of selection acting on intracellular nucleic acid sensors with respect to the cell-surface expressed TLRs . The signature of strong purifying selection obtained for the intracellular TLRs sensing nucleic acids suggests that the corresponding genes can accumulate only synonymous mutations or mutations with no major effect on protein function in their exonic regions . Conversely , function-altering mutations are more likely to be present in the population for cell-surface expressed TLRs . We tested this hypothesis , by assessing the phenotypic consequences of the 103 nonsynonymous mutations identified in the 10 TLR genes , using the Polyphen algorithm [52] ( Table S7 ) . This method predicts the impact of nonsynonymous variants ( benign , possibly damaging , or probably damaging ) on the structure and function of the protein , using comparative and physical considerations including the analysis of multiple-species sequence alignments and protein 3D-structures [52] . We found that the different types of exonic mutations — synonymous , nonsynonymous variants considered benign , possibly damaging or probably damaging , and stop mutations — were unevenly distributed between the group of intracellular nucleic acids sensors and that of cell-surface TLRs ( χ2-test , P = 1×10−4 ) . Specifically , among the different exonic mutations identified in each group of TLRs , the proportion of possibly or probably damaging mutations and stop mutations observed on nucleic acids sensors was much lower ( 8% ) than that observed for the remaining TLRs ( 32% ) ( Figure 3A ) . At the population level , we observed no probably damaging or stop mutations for nucleic acids sensors , with the exception of a single European individual presenting a probably damaging heterozygous TLR7 mutation . Conversely , the proportion of individuals presenting probably damaging or stop mutations affecting at least one of the cell-surface TLRs was remarkably high ( 23% and 16% , respectively ) ( Figure 3B ) . A high proportion of individuals in the general population presented stop mutations affecting TLR2 ( 0 . 6% ) , TLR4 ( 0 . 6% ) , TLR5 ( 10% ) or TLR10 ( 5% ) ( Figure 3C ) . The relatively high frequencies of probably damaging and stop mutations affecting cell-surface expressed TLRs most likely reflect their lesser essential role in protective immunity in the natural setting . The previous inter-species analyses have proven to be powerful to identify classes of genes evolving under strong evolutionary constraints , however they are very much limited regarding the detection of more recent events of positive selection in human populations [29] , [30] , [53] . As a positively selected mutation increases in frequency in a given population ( i . e . , selective sweep ) , it leaves a distinct signature ( e . g . , skew in the distribution of allele frequencies ) on the pattern of genomic variation in the immediate vicinity of the selected mutation [28] , [29] , [54] . To test for geographically varying selection among the different continental populations here studied , we first used several summary statistics of the within-population allele frequency distribution , including the commonly used Tajima's D , Fu and Li's F* and Fay and Wu's H . In total , we identified five TLRs in the African sample , three in the European sample and three in the East Asian sample , whose variation was not compatible with neutrality ( Table 2 ) . These observations could reflect selective pressures targeting different TLRs in different populations but could also result from the distinct demographic histories characterizing the different continental populations . To account for demographic influences on the robustness of neutrality tests , we considered a demographic model previously validated using a set of 50 unlinked noncoding regions sequenced in a set of populations similar to ours ( i . e . , African , European and Asian ) [55] . This model considers a bottleneck in non-African populations starting 40 , 000 years ago in an ancestral population of 9 , 450 individuals , and an exponential expansion in African populations ( Material and Methods , for details on the demographic parameters used ) . This external demographic model fitted perfectly the patterns of neutral diversity ( i . e . , 20 noncoding regions ) observed in our studied populations ( Table S8 ) . We thus reestimated the significance of all neutrality tests incorporating the demographic model of Voight et al . [55] into our neutral expectations . We found that TLR4 , TLR5 , TLR7 and TLR10 rejected neutrality for at least one statistical test ( Table 2 ) . Specifically , TLR4 in Africans and East-Asians and TLR7 in Europeans showed an excess of rare alleles , a pattern indicative of weak negative selection or a selective sweep . TLR5 showed a significant excess of high-frequency derived variants in all population groups , compatible with the occurrence of a selective sweep . Similarly , TLR10 showed a significant excess of high-frequency derived variants in East-Asians with the same trend observed for the European sample ( P = 0 . 053 ) . An additional analytical approach to detect population-specific positive selection involves the comparison of genetic distances among populations , using the FST statistic [56] , [57] . Specifically , local positive selection is known to increase the levels of population differentiation with respect to neutrally evolving loci [29] , [30] , [54] , [55] , [58] . We thus estimated the FST values for all SNPs identified in our study ( 457 SNPs ) and compared them with the genomewide empirical distribution of FST obtained from the analysis ∼2 . 8 million HapMap Phase II SNPs [59] . Because the HapMap FST distribution includes loci targeted by positive selection [58] , the comparison of TLRs FST against the HapMap distribution represents a highly conservative approach to detect selection ( i . e . , the “neutral” distribution also includes selected loci ) . In addition , we accounted for the differences in the allele frequency spectra between the sequence-based TLR dataset and the genotyping-based HapMap dataset , by comparing the FST values as a function of the expected heterozygosity ( i . e . , twice the product of allele frequencies ) . Our results revealed significantly high levels of population differentiation among several TLR variants , a large proportion of which corresponded to nonsynonymous mutations ( Figure 4 ) . Regardless of the populations' pairwise comparison , most TLR variants presenting high-FST were located in the cluster TLR10-TLR1-TLR6 ( 66% of all high-FST SNPs ) ( Table S9 ) . The TLR10-TLR1-TLR6 gene cluster is located in a ∼60 kb genomic region in chromosome 4p14 , the three genes being in strong linkage disequilibrium ( LD ) particularly in non-African populations ( Figure S2 ) . Because of the close vicinity of these genes , we performed a sliding-window analysis of nucleotide diversity π , Tajima's D and Fay and Wu's H across this region . These analyses revealed multiple windows in TLR1 and TLR10 showing significant deviations from neutral expectations , particularly among non-Africans ( Figure S3 ) . This observation , together with the high-FST values observed in this region , strongly suggests the occurrence of population specific events of positive selection . To identify more precisely the allele ( s ) /haplotype ( s ) being targeted by selection , we developed a new statistic — the Derived Intra-allelic Nucleotide Diversity ( DIND ) test — that makes maximum profit of resequencing data ( see Materials and Methods for details ) . The rationale of this test is that , under neutral conditions , a derived allele that is at high population frequencies should present high levels of nucleotide diversity at linked sites ( i . e . , high levels of diversity within the class of haplotypes defined by the presence of the derived allele ) . Conversely , a derived allele that is positively selected will increase in frequency much quicker than the time needed to accumulate diversity at linked sites; a derived allele targeted by positive selection will be at high population frequencies but associated with low nucleotide diversity at linked sites . We first evaluated the power of the DIND test with respect to other commonly used frequency- and LD-based neutrality tests ( i . e . , Tajimas's D , Fu and Li's F* , Fay and Wu's H and iHS ) . Our simulations revealed that the DIND test clearly outperformed the other tests , particularly when the selected allele is found at a population frequency <70% ( Figure 5A and Figure S4 ) . The power of the test drops only when the selected allele is observed at near-fixation . Thus , the DIND test is especially useful for the identification of ongoing sweeps . We applied the DIND test to our data by plotting for all SNPs identified in the TLR10-TLR1-TLR6 region , the ratio between the ancestral and the derived internal nucleotide diversity ( iπA/iπD ) against the frequencies of the derived alleles ( Figures 5B–5D ) . An elevated iπA/iπD associated with a high frequency of the derived allele is indicative of positive selection targeting the derived allelic state . Our analyses identified three mutations characterizing several TLR10-TLR1-TLR6 haplotypes showing clear signs of positive selection: the nonsynonymous mutation C745T in TLR6 ( P249S ) tagging a single haplotype in Europeans ( H34 ) ( Figure 5C ) , and the nonsynonymous mutation A2323G ( I775V ) and the non-coding mutation G-260A , both in TLR10 ( Figure 5D ) , defining three evolutionarily-related haplotypes in East-Asians ( H41 , 54 , 55 ) ( Figure S5 ) . The action of positive selection targeting this gene cluster is further reinforced by the fact that , when using the HapMap data [59] , [60] , the haplotypes containing the selected alleles are also associated with significantly high levels of LD , as measured by the Long Range Haplotype ( LRH ) test [61] ( Figure S6 ) . The high frequencies of H34 in Europe ( ∼26% ) and of H41-54-55 in Asia ( ∼40% ) and the depicted signatures of positive selection ( Figures 5 and Figure S6 ) suggest that these haplotypes harbor functional variation that has conferred a selective advantage among non-African populations . In Europe , H34 is characterized by three amino-acid changes: TLR1 S248N ( SNP G743A ) , TLR1 I602S ( T1805G ) and TLR6 P249S ( C745T ) . To assess the functional impact of each of these variants , we examined their respective effects on the activation of NF-κB signaling — the principal TLR-dependent pathway [62] . To do so , we generated by site-directed mutagenesis the three variants of H34 as well as the TLR1 P315L and the TLR6 P680H variants , which were shown to substantially diminish NF-κB activation [63]–[65] . All constructs were HA-tagged at the C-terminus . Since both TLR1 and TLR6 signal as heterodimers with TLR2 , we co-transfected in human embryonic kidney ( HEK ) 293T cells the different TLR1 and TLR6 variants along with TLR2 and an NF-κB luciferase reporter plamid . The expression levels of the four TLR1 variants ( 248S/602I , 248N/602I , 248S/602S , 248N/602S ) and the two TLR6 variants ( 249P , 249S ) were found to be comparable ( Figure 6A ) . Interestingly , variants containing the derived 602S allele migrated slightly faster most likely due to a polarity change ( I602S ) . We next stimulated cells with their corresponding TLR agonists: PAM3CSK4 , for the TLR1/2 heterodimer , or PAM2CSK4 , for the TLR6/2 heterodimer ( Figure 6B ) . In response to stimulation with PAM3CSK4 , the ancestral TLR1 248S-602I form , when cotransfected with TLR2 , mediated greater NF-κB activity than TLR2 alone ( P<0 . 001 ) . The ability of the 248N variant to mediate NF-κB signaling did not significantly differ from that of the ancestral form . By contrast , the derived 602S allele ( 1805G ) presented impaired signaling with a drastic decrease of ∼60% of NF-κB activity in comparison with the 602I allele ( Figure 6B ) , in agreement with previous studies [66] , [67] . Consistently , the 248S and 248N in combination with either variant of 602 did not influence the degree of NF-κB activation . When cells were stimulated with the TLR6 PAM2CSK4 agonist , both the ancestral 249P and the derived 249S forms were similarly capable of mediating maximal NF-κB signaling ( Figure 6B ) . Together , these results show that , among the three nonsynonymous variants of H34 ( TLR1 248N , TLR1 602S and TLR6 249S ) , only TLR1 602S has a functional impact leading to impaired signaling . In Asia , the putatively-selected haplotypes H41-54-55 are characterized by three aminoacid changes targeting TLR10 ( N241H , I369L and I775V ) . We first observed that the three TLR10 variants were expressed at comparable levels ( Figure S7 ) . TLR10 is the only orphan TLR member for which no specific agonist has been yet identified . Several authors have evaluated the functional impact of some TLR mutations by over-expressing them and measuring NF-κB activity in the absence of stimulation [64] , [68] . We found that neither the over-expression of TLR10 at different levels ( see Material and Methods for details ) nor the stimulation of transfected cells with TLR10 antibodies induce NF-κB activation for any of the variants tested nor for the wild-type haplotype ( data not shown ) . As previously reported for TLR2 [68] , our results showed that TLR10 do not induce NF-κB activation in the absence of stimulation , thus precluding us from evaluating the functional impact of TLR10 variants .
The study of the evolutionary dynamics of the innate immune system is an excellent approach to test hypotheses concerning the evolution of genes mediating the antagonistic interaction between the host and the microbial environment . Here , we examined whether and how natural selection has targeted innate immunity receptors in humans , using as a paradigm the TLR family . Characterizing how rapidly , or not , innate immune genes evolve can increase our understanding of the recognition properties of these genes and the nature of the host-pathogen interactions mediated by them . In this respect , contrasting findings have been obtained for immunity genes in different model organisms [69]–[71 , and references therein] . In the plant Arabidopsis thaliana , genes involved in the specific recognition of pathogen proteins ( R genes ) show little evidence of positive selection arguing against a coevolutionary arms race driving R gene evolution [72] . These genes display instead signatures of transient balancing selection causing high levels of protein variation maintained over intermediate periods of time [72] , [73] . Conversely , no evidence for an important role of balancing selection has been found in Drosophila immunity proteins [69] , [74] , [75] . PRRs triggering humoral immunity ( e . g . , peptidoglycan recognition proteins ) appear to evolve under purifying selection , while phagocytic receptors involved in cellular immunity ( e . g . , class C scavenger receptors ) show evidence of ongoing positive selection [69] , [75]–[77] . This observation suggests that , in Drosophila , the recognition properties of these two classes of immunity genes are quite distinct: PRRs recognize highly conserved microbial compounds and are therefore evolutionarily static , whereas phagocytic receptors may bind to evolutionarily labile pathogen molecules and are likely to coevolve with pathogens [69] . In humans , similarly to the data from Drosophila PRRs , we observed that TLRs , taken as a set , have evolved under the action of purifying selection . These results are consistent with a recent study that , based on a partially overlapping set of genes resequenced in an Indian population , proposes that purifying selection is the dominant signature among genes of innate immune system [78] . Conversely , our data do not support the notion that balancing selection is pervasive among human innate immunity genes , as it has been previously claimed [79] . Although strong evolutionary conservation is expected at PRRs that recognize conserved and essential molecular patterns of the microorganisms , our data revealed major differences in the intensity of selection acting upon the different members of the TLR family . The biological relevance of the various TLR members can be inferred from the intensity of evolutionary constraints on these molecules . Our analyses clearly showed that the group of intracellular TLRs has been subject to strong purifying selection , whilst such a selective constraint appears to be less pronounced among cell-surface TLRs . This dichotomy most likely reflects both the different nature of the microorganisms targeted by the two groups of TLRs and the diverse spectra of targeted molecules displayed by the different microbes . Intracellular TLRs are principally involved in viral recognition through the sensing of their nucleic acids — the most dominant mechanism by which viruses are detected [21] , [51] . Indeed , viral proteins serve as poor targets for innate recognition because they can rapidly evolve . To ensure effective viral detection , the host has bypassed this problem by using the intracellular TLR-mediated system , which targets various forms of viral nucleic acids ( essential molecules that are difficult for the microorganism to alter ) . Conversely , cell-surface TLRs target multiple molecules ( i . e . , PAMPs ) characterizing the structure or the metabolism of a plethora of microorganisms , mostly bacteria , parasites and fungi [4] , [21] . Because these microbes display each several , different PAMPs ( e . g . , lipopolysaccharide , flagellin , etc ) , they can be simultaneously detected by different cell-surface TLRs , in contrast with viruses that are almost uniquely recognized by their nucleic acids . In this view , it is tempting to speculate that the extreme conservation observed at intracellular viral-recognition TLRs results from the very narrow choice these sensors have for targeting viral molecules ( nucleic acids ) . More generally , this pattern of strong purifying selection suggests that viruses have globally exerted stronger selective pressure on these immunity sensors with respect to other microbes , consistent with the group of intracellular TLRs playing each a key role in host anti-viral defences . This hypothesis is supported by clinical genetics data indicating that TLR3 plays an essential role in natural immunity to herpes simplex virus-1 encephalitis [26] . With respect to TLR7 , TLR8 and TLR9 , although they have been proposed to be redundant against most common viruses [22]–[26] , [80] , individuals presenting TLR7 , TLR8 or TLR9 deficiencies have never been reported , so a direct role of these genes in host anti-viral defenses cannot be ruled out . Overall , our data suggest that one or a few viruses ( extinct and/or undiagnosed ) have exerted pressure on TLR7 , TLR8 , and TLR9 , but in a manner different from that of the ubiquitous herpes simplex virus-1 , which exerts selective pressure on TLR3 . Viruses may not be the only selective pressure driving the selective maintenance of TLR3 , TLR7 , TLR8 and TLR9 . Some TLRs appear to be involved in central nervous system development and maintenance [81] , [82] . TLR8 has been implicated in neurite outgrowth in mouse , as neurons in mouse embryos have been shown to produce larger amounts of TLR8 during embryonic stages [82] . Interestingly , the human TLR8 is the TLR under the strongest purifying selection ( Figure 2A ) . Another factor that may have further contributed to the strong protein conservation of the four nucleic acid sensors is autoimmune avoidance . Indeed , the intracellular localization of TLR3 , TLR7 , TLR8 and TLR9 represents a mechanism for the host to prevent self nucleic acid recognition while preserving the ability to detect viral nucleic acids within the acidic environment of endosomes and lysosomes . Nevertheless , these TLRs can be stimulated “inappropriately” by certain endogenous RNA- and DNA-containing ligands [83] , [84] . For example , plasmacytoid dendritic cells are activated , via TLR7 or TLR9 , in response to “immune complexes” containing self DNA or RNA [83] . Furthermore , mice with an extra copy of TLR7 have accelerated autoimmune reactions [85] . Conceivably , mutations increasing the reactivity of these TLRs to self nucleic acids or releasing them from the endosomal compartment would be highly detrimental , particularly during embryonic life , increasing selective constraints on these genes . Altogether , the strong purifying selection operating on TLR3 , TLR7 , TLR8 and TLR9 demonstrates their essential , non-redundant biological role in host survival . Unlike the TLRs sensing nucleic acids , the group of TLRs expressed at the cell surface — TLR1 , TLR2 , TLR4 , TLR5 , TLR6 and TLR10 — display higher evolutionary flexibility ( i . e . , lesser selective constraint on nonsynonymous mutations ) . The relatively high population-frequencies of nonsynonymous variants with probable effects on protein function or stop mutations on the corresponding genes ( Figure 3C ) suggest higher immunological redundancy . Similar patterns of segregating non-functional alleles have been reported in Arabidopsis R genes . Out of 27 R genes examined , 17 of them displayed high frequencies ( up to 33% ) of frameshift or stop codon mutations , reflecting complex episodes of balancing selection and relaxed constraint [72] . Likewise , the high prevalence of stop codons observed at some class-C scavenger receptors in Drosophila suggest higher redundancy , allowing increased frequencies of these non-functional alleles without compromising organismal fitness [77] . In humans , the higher redundancy we observed at cell-surface TLRs suggest that they have overlapping functions among them or with respect to other non-TLR sensors ( e . g . , C-type lectins ) . The most notable example of such redundancy is TLR5 . The loss-of-function TLR5 392stop mutation is present at high population-frequencies ( up to 23% in Europe and South Asia , see also [86] ) . Some stop mutations have been reported to confer a selectively advantage in humans [87] , [88] , with cases involved in immunity-related processes such as the truncated form of the caspase-12 gene [89] . However , no signal of recent positive selection was detected in the TLR5 coding region ( our data and [86] ) . This finding , as we previously reported for the innate immune receptor MBL2 [90] , is consistent with a largely redundant role of TLR5 and suggests that other accessory mechanisms of pathogen recognition provide sufficient protection against infection . Our results support the notion that duality in sensing microbes , and therefore redundancy , may be a common feature among innate immunity receptors [91] . However , the higher biological dispensability of cell-surface TLRs does not exclude their important role in protective immunity . Indeed , our data revealed that weak negative selection precludes increases in the frequency of nonsynonymous variants in the population , at least for TLR1 , TLR4 and TLR10 ( Figures 2B and Figure S1 ) . For TLR4 , the action of weak negative selection is further reinforced by an excess of rare alleles as revealed by the significant negative values of Tajima's D and Fu & Li's F* ( Table 2 ) . Taken together , the nonsynonymous mutations accumulated by these genes , although non lethal , may have at least mildly deleterious phenotypic effects , as previously proposed for TLR4 [92] . This prediction is further supported by the genetic association of some of these amino acid-altering mutations with susceptibility to a number of infectious diseases [27] . On the other hand , the higher evolutionary flexibility of the cell-surface TLRs can result in an increased number of potential targets for positive selection . In particular circumstances , mutations at these TLRs are not only tolerated but indeed positively selected either worldwide or in a population-specific manner . Consistent with a selective sweep at the worldwide level , TLR5 displayed a significant excess of high-frequency derived variants ( i . e . , significantly negative Fay and Wu's H ) , restricted to its 5′-UTR ( Figure S8 ) . Although population structure can also result in significantly negative Fay and Wu's H values [93] , this possibility is unlikely given that we observed a signal of selection in all studied populations . Given the present-day apparent redundant role of TLR5 , as attested by high frequency of the TLR5 392stop mutation , we speculate that this selective sweep occurred in a more distant past; probably in a period characterized by a different set of pathogens against which certain TLR5 variants were advantageous . TLR5 represents therefore a paradigm of the evolutionary dynamics that may characterize a large number of innate immune receptors; these genes may swing between being essential for protective immunity and becoming redundant in the natural setting depending on the temporally-varying microbial milieu . Finally , our analyses revealed that positive selection can also act locally at some cell-surface TLRs , leading to differential selection of resistance alleles in specific populations . Specifically , we identified two haplotypic backgrounds in the genomic region encompassing TLR10-TLR1-TLR6 showing clear signs of positive selection in Europeans and East-Asians ( Figures 5 and Figure S6 ) . Our data show that TLR1 , and more specifically the nonsynonymous T1805G variant ( I602S ) , is the genuine target of positive selection detected in the TLR10-TLR1-TLR6 gene cluster in Europeans . First , TLR1 is ∼2 times more diverse in non-African than in African populations , a pattern not compatible with the African origin of modern humans [45] . This pattern has been observed only once among the 323 genes ( 0 . 3% ) sequenced by the Seattle SNP consortium . Thus , the increased diversity observed in TLR1 among non-Africans probably results from ongoing hitchhiking between the selected allele and neutral variation at linked sites . Second , the 1805G ( 602S ) mutation presents the highest level of population differentiation ( FST = 0 . 54 ) of all SNPs located in this gene cluster ( Figure 4 , Table S9 ) . Third , among the three nonsynonymous variants composing the haplotype identified as being under positive selection in Europeans ( H34 , see Figure S5 ) , only the TLR1 1805G ( 602S ) variant has a remarkable impairment effect on agonist-induced NF-κB activation , showing a decreased signaling by up to 60% ( Figure 6B ) . These findings are consistent with previous studies showing that , homozygous , and to a lesser extent heterozygous , individuals for the 1805G allele present impaired TLR1-mediated immune responses after whole blood stimulation [66] , [67] , [94] . Taken together , it is tempting to speculate that an attenuated TLR1-mediated signaling , and a consequently reduced inflammatory response , has conferred a selective advantage in Europeans — a scenario that would explain the very high frequency ( 51% ) of the “hypo-responsiveness” T1805G mutation in Europe . This observation raises questions about the possible evolutionary conflict between developing optimal mechanisms of pathogen recognition by TLRs , and more generally PRRs , and avoiding an excessive inflammatory response that can be harmful for the host . Our study has revealed that the mode and intensity of natural selection differs among the different TLR members , both at the species-wide level ( all humans ) and in a population-specific manner . Our results indicate that TLRs sensing nucleic acids play an essential , non-redundant role in host survival , either via protective immunity against viral infections ( present or past ) , or because of their additional involvement in other non immunity-related processes of major biological relevance , or both . The strong selective constraints affecting these sensors suggest that mutations leading to impaired responses for these receptors are associated with severe clinical phenotypes . These genes are thus ideal candidates for involvement in individual Mendelian deficiencies ( monogenic inheritance ) , as already shown for TLR3 deficiency [26] . Conversely , the relaxation of the selective constraints affecting cell-surface expressed TLRs , as illustrated by the higher rates of nonsynonymous and stop mutations , shows a higher level of biological redundancy for these receptors . Despite impaired responses involving these receptors have a more modest impact on human survival , polymorphism in these genes is involved in fine-tuning host defenses and may , therefore , subtly modulate individual susceptibility to infectious disease in the general population . Moreover , we show that impaired TLR-mediated responses may be in some cases beneficial for human survival , as attested by the signature of positive selection targeting the hypo-responsiveness TLR1 1805G allele in Europeans . Taken together , our evolutionary findings provide clues onto how variation in human TLRs may result in different contributions to the outcome of infectious diseases . More generally , the paradigm of TLRs neatly illustrates the value of integrating evolutionary genetic data into a clinical and epidemiological framework , for better definition of the ecological relevance of host defense genes to past and present survival in natura .
Sequence variation for the 10 members of the human TLR family and for the 20 autosomal non-coding regions was determined for a total of 158 individuals ( 316 chromosomes ) representing major geographical regions . The descriptions of the specific population samples can be found in ALFRED ( http://alfred . med . yale . edu ) using the unique IDs given in parentheses . Sub-Saharan Africans were represented by Yorubans from Nigeria ( 31 individuals from UID “SA000036J” ) and Chaggas from Tanzania ( 32 individuals from UID “SA000487T” ) ; Europeans were represented by Danes ( 23 individuals from UID “SA000046K” ) and Chuvash from Russia ( 24 individuals from UID “SA000491O” ) , and East-Asians were represented by Han Chinese ( 24 individuals from UID “SA000009J” ) and Japanese ( 24 individuals from UID “SA000010B” ) . In addition , the orthologous regions of the TLR genes were sequenced in two chimpanzees , when the corresponding sequences were not publicly available . All individuals were healthy donors from whom informed consent was obtained . This study was approved by the Institut Pasteur Institutional Review Board ( n° RBM 2008 . 06 ) . For each TLR , the totality of the exonic region and an at least an equivalent amount of non-exonic regions , including ∼1 , 000 bp of their promoter regions ( i . e . , upstream of the first transcribed exon ) , were sequenced ( Table S1 ) . Intronless genes like TLR6 and TLR9 were sequenced in their totality including ∼1 , 000 bp of their promoter regions . The 20 autosomal non-coding regions dispersed throughout the genome ( ) and used as baseline of neutral diversity were chosen ( i ) to be independent from each other ( ii ) to be at least 200 kb apart from any known gene , predicted gene or spliced expressed sequenced tag ( EST ) , and ( iii ) not to be in LD with any known gene or spliced EST . All sequences were obtained using the Big Dye terminator kit and the 3730 automated sequencer from Applied Biosystems . Sequence files and chromatograms were inspected using the GENALYS software [95] . As a measure of quality control , and to avoid allele-specific amplification , when new mutations were identified in primer binding regions , new primers were designed and sequence reactions were repeated . All singletons or ambiguous polymorphisms were systematically reamplified and resequenced . Haplotype reconstruction was performed by means of the Bayesian statistical method implemented in Phase ( v . 2 . 1 . 1 ) [96] . We applied the algorithm five times , using different randomly generated seeds , and consistent results were obtained across runs . Tagging SNPs for each population were selected using Haploview's Tagger in pairwise tagging mode ( r2≥0 . 80 , minor allele frequency cut-off = 5% , and other settings at default value ) . To assess the ancestral allelic state for each SNP , we aligned the human sequence with genomes of other primates ( Pan troglodytes , Pongo pygmaeus , Macacca mullata; UCSC database ) and deduced by parsimony the ancestral state of each SNP . The different summary statistics such as the number of segregating sites ( S ) , haplotype diversity ( Hd ) , the average number of pairwise differences ( π ) , and the sequence-based neutrality tests , such as Tajima's D , Fu and Li's F* and Fay and Wu's H tests were performed using DnaSP package v . 4 . 1 [97] . The sliding-windows of nucleotide diversity levels ( π ) , Tajima's D , and Fay and Wu's H were also performed using DnaSP [97] . The size of each window was 1 , 500 nucleotides , and the step size was 500 nucleotides . P-values for the various tests of neutrality were estimated from 104 coalescent simulations under a finite-site neutral model and considering the recombination rate reported for the genes studied by deCODE map rates [98] . Coalescent simulations were performed using the program SIMCOAL 2 . 0 [99] . Each of the 104 coalescent simulations was conditional on the observed sample size and the number of segregating sites observed in each gene and each of the sliding windows . To correct for the effects of demography on diversity patterns , we considered a validated demographic model that used also resequencing data of non-coding regions in set of populations similar to ours ( i . e . , African , European and Asian ) [55] . Specifically , they estimated demographic parameters , based on 50 unlinked non-coding genomic regions resequenced in 45 individuals from three human populations ( 15 Hausa , 15 central Italians and 15 Han Chinese ) [55] . We simulated non-African bottlenecks , conditionally on our European and East-Asian sample sizes ( 48 and 47 individuals , respectively ) , using their combination of parameters — i . e . , a bottleneck starting 40 , 000 YBP in an ancestral population of 9 , 450 individuals with combinations of bottleneck duration and severity corresponding to the confidence region of parameter space with P-values of 0 . 05 ( Figures 2A and 2D of ref . [55] ) . In addition , we also used their combination of parameters to simulate an African expansion , conditionally on our African sample size ( 63 individuals ) — i . e . , combinations of start of growth and grow rate of the exponential expansion corresponding to the confidence region of parameter space with P-values of 0 . 05 ( Supporting Figure 3 of ref . [55] ) . To evaluate whether Voight et al . 's demographic model fitted our data , we simulated 1 , 000 sets of 20 regions each ( the number of non-coding regions sequenced herein ) . Each simulated fragment had 1 , 300 bp , corresponding to the mean size of non-coding regions sequenced in this study ( Table S2 ) , with a per site mutation rate ( μ ) sampled from a Gamma distribution with a mean of 2 . 0×10−8 and with 95% of the draws varying from 1 . 5×10−8 to 4 . 0×10−8 [ref . 55] . We then tested whether the observed mean values for the different statistics observed for our non-coding regions was in the 95% confidence interval of the mean values estimated through this simulation procedure . We showed that Voight et al . 's demographic model fits well the patterns of diversity observed for the 20 non-coding regions sequenced in this study ( Table S8 ) . Once the model was validated , P-values of the summary statistics for the different TLRs were then corrected for this demographic model [55] by counting the number of simulated values of the different summary statistics that did not fall into the range of observed values ( Table 2 ) . To model purifying/negative and directional positive selection operating on the different TLRs , we employed a Markov Chain Monte Carlo ( MCMC ) algorithm for the Bayesian analysis of polymorphism and divergence data under a Poisson random field setting [48] , [49] . The different parameters are estimated by means of MK contingency tables comparing the levels of human polymorphism and human-chimpanzee divergence at silent and nonsynonymous sites [100] . This method assumes that a fraction , 1−f0 , of the amino acid substitutions is lethal and never contributes to polymorphism or divergence . Consequently , the effective mutation rate at amino acid-altering sites after purifying selection is θr/2 = 2NeμLr f0 , where Lr is the number of nucleotide sites at which a mutation would generate an amino acid change , Ne the effective population size and μ the mutation rate per generation per site . Silent mutations are considered to be neutral , so that θs/2 = 2NeμLs , where Ls is the number of nucleotide sites at which a mutation would not generate an amino acid change . Thus , given the data , we can estimate the locus scaled mutation rate for both nonsynonymous ( θr ) and synonymous sites ( θs ) . The ratio θr/θs will be a direct proxy of the fraction , 1−f0 , of the nonsynonymous mutations that have been eliminated from the population ( i . e . , the rate of purifying selection ) . In addition , and for each gene , the method quantifies the extent and directionality of selection operating on non-lethal nonsynonymous mutations in terms of the population genetic selection parameter ( γ = 2Nes ) ( specific details on the method can be found in refs . [47]–[49] ) . The model equally estimates the parameter τ , which corresponds to the number of generations since humans and chimpanzees started to diverge . Thus , each gene has its own γ , θr and θs values while τ is a shared parameter across loci . To approximate the posterior distribution of the parameters given the observed data ( i . e . , the joint probability for parameter values given the data ) , we used the MCMC method as already reported [48] . Specifically , for each TLR , we ran 10 independent MCMC chains with overdispersed starting points for 110 , 000 iterations . We retained samples after the 1 , 000th step in each chain to allow for “burn-in” of the chain and used every 10th sample from the chain as a quasi-independent draw . Thus , all posterior probabilities reported here are from 10 , 000 retained draws from 10 MCMC chains . To measure convergence , we used the Gelman Rubin statistics that was close to 1 for all parameters , illustrating that the 10 chains had converged before we retained our samples . The fitness status of all amino acid-altering mutations ( i . e . , benign , possibly damaging and probably damaging ) was predicted using the Polyphen algorithm [52] . This method , which considers protein structure and/or sequence conservation information for each gene , has been shown to be the best predictor of the fitness effects of amino acid substitutions [101] . To independently assess the functional impact of these mutations , we replicated the analyses using the Panther algorithm [102] . Mutations predicted to be “probably damaging” ( i . e . , the most likely to affect protein function ) by Polyphen were also predicted to be “strongly deleterious” using the Panther algorithm with a mean P deleterious = 0 . 90 . The identification of the protein domains of the different TLR members was defined using the SMART program [103] . Population differentiation was estimated by using the FST statistics derived from the analysis of variance ( ANOVA ) [56] . To identify SNPs presenting extreme levels of population differentiation , we compared the observed FST values at the level of individual SNPs in TLRs against the FST distribution [58] computed for ∼2 . 8 million HapMap Phase II SNPs [59] . Because FST values depend on allele frequencies , and the frequency spectrum of HapMap data is known to present a lack of low-frequency variants with respect to resequencing data [104] , we compared FST values between TLRs and the HapMap data by comparing SNPs presenting similar allele frequencies ( i . e . , similar expected heterozygosity ) . Empirical P values for each SNP at the TLRs were estimated as follows: ( i ) we compared the FST values of each TLR SNP with those observed for HapMap SNPs presenting similar heterozygosity values ( i . e . , ±0 . 025 with respect to the observed value ) , ( ii ) among these frequency-matched SNPs , we estimated the proportion of HapMap SNPs presenting FST values higher than that observed for our data . The 95th and 99th percentiles for the HapMap genome-wide FST distribution were estimated by using heterozygosity sliding windows of size 0 . 05 with increasing steps of 0 . 01 . Because the commonly used sequence-based neutrality tests have low power to detect selection , particularly if the selective events are too recent , we developed a new statistics that takes maximum profit of extensive resequencing data . The rationale of this test is that , under neutral conditions , a derived allele that is present at high population frequency is by definition old and therefore , it should be associated with high levels of intra-allelic nucleotide diversity ( i . e . , high levels of diversity within the class of haplotypes defined by the presence of the derived allele ) . Conversely , under a scenario of positive selection , a derived allele will increase in frequency in the population much quicker than the time required to accumulate intra-allelic diversity . Thus , a positively selected allele will be at high frequency in the population but associated with low internal diversity at linked sites . To test for such scenarios , we proceed as follows . Let a given sample of n individuals be sequenced for a given locus , and let x be a given polymorphism identified at this locus , with an ancestral allele at frequency nA and a derived allele at frequency nD . Then , we calculate the intra-allelic nucleotide diversity iπ of both alleles at SNP x using the following formulas:with dij being the number of observed differences between the ith and jth haplotypes harboring the ancestral allele , dkl being the number of observed differences between the kth and lth haplotypes harboring the derived allele , and nAC2 and nDC2 the number of pairwise comparisons , respectively . The DIND test is based on the ratio iπA/iπD plotted against the frequency of the derived allele . A high iπA/iπD ratio ( i . e . , iπD≪iπA ) together with a high frequency of the derived allele points to the action of positive selection ( i . e . , the internal diversity of the haplotypes associated with the derived allele is too small given the frequency of this allele in the population ) . For the particular situation in which iπD = 0 , we attributed to the ratio iπA/iπD an arbitrary value corresponding to the maximal iπA/iπD value observed in the dataset plus 20 . This decision was taken to avoid missing signals of selection resulting from situations where a highly frequent derived allele was associated with null intra-allelic diversity . To define statistical significance , the values estimated for TLRs were then compared against the background neutral distribution obtained by means of 10 , 000 simulations of the TLR10-TLR1-TLR6 region , conditional on the number of segregating sites and the recombination rate of the region , and integrating the demographic model previously described . We used the program SelSim to simulate data with selection and recombination [105] . We simulated genomic regions of 60 kb and with 182 polymorphic sites — equivalent to the TLR10-TLR1-TLR6 gene cluster — and a per locus recombination rate ( 4Nr ) ρ = 1×10−3 . The model used assumes that a new positively selected mutation experiences a constant additive selection pressure σ = 2Ns , where N is the population size and s is the additive selective advantage per copy per generation . The data are sampled when the mutation reaches a specified frequency . For each combination of σ and frequency of the selected site , we performed 250 simulations of 100 chromosomes each . Critical values for each statistic at P = 0 . 05 were obtained using identical simulations but with σ = 0 . To perform the LRH test [61] , we retrieved from the HapMap data [59] , [60] the haplotypes corresponding to the genomic region encompassing the TLR10-TLR1-TLR6 gene cluster ( 1 Mb regions centered on TLR1 ) . Then , we selected core regions identified as haplotype blocks ( restricted to SNPs genotyped on these three genes ) , following the criteria of Gabriel et al . ( 2002 ) [106] , and we assessed , for each core haplotype , its relative extended haplotype homozygozity ( REHH ) 200 kb apart . The only exception was for the European sample , where we defined core haplotypes as clusters of four continuous SNPs . This is because the SNP745 in TLR6 ( identified as being positively selected by the DIND test ) was not included in any of the core haplotypes obtained using the criteria of Gabriel et al . ( 2002 ) [106] Thus , for this particular situation , we assessed , for each core haplotype , its REHH 300 kb apart to improve the power of the test . To test the significance of potentially selected core haplotypes , we compared the values obtained for our core regions with the empirical distribution of “core haplotype frequencies versus REHH” obtained from the screening of ∼50 , 000 core haplotypes from chromosome 4 in Yoruban , Asian and European-descent populations from HapMap data [59] , [60] NF-κB luciferase reporter construct containing the luciferase gene under the control of six thymidine Kinase NF-κB sites from the thymidine kinase gene was kindly provided by Oreste Acuto . The Renilla Luciferase construct was purchased from Promega ( Promega , Madison , WI ) . All TLRs constructs were purchased from Invivogen ( InvivoGen , San Diego , CA ) . Allelic variants of TLR1 , TLR6 , and TLR10 were made using the QuickChange Site Direct Mutagenesis system according to the manufacturer's instructions ( Stratagene , La Jolla , CA ) . All constructs were systematically verified by sequencing of the complete TLR gene with a 3130×l Genetic Analyzer ( Applied Biosystems , Foster City , CA ) . The HEK 293T cell line was cultured in DMEM supplemented with 10% FBS , 100 IU penicillin , 100 µg/ml streptomycin ( Invitrogen , Carlsbad , CA ) , at 37°C in a humidified incubator at 5% CO2 . HEK 293T cells were seeded in 24-well plates ( 5×104−1×105 cells/well ) . The day after , cells ( reaching 30–50% of confluency ) were transiently transfected with a NF-κB reporter construct pNF-κB -luc from Stratagene , along with constructs expressing the various TLRs using FuGene 6 reagent from Roche Diagnostics according to the manufacture's recommendations . All plasmids used in transfections were purified using the Endofree plasmid kit ( Qiagen , Chatworth , CA ) . Briefly , 100 ng of NF-κB reporter construct was cotransfected with TLR constructs and with 5 ng pRL-TK-Renilla luciferase construct ( Promega , Madison , WI ) as a control for transfection efficiency . For each transfection point , total DNA was adjusted to 300 ng with the use of the empty vector pcDNA3 . 1 . For TLR2/1 and TLR2/6 transfection studies , 5 ng of TLR2 was cotransfected with 100 ng of TLR1 or TLR6 . For TLR10 experiments , different concentrations of TLR10 variants were tested for the constitutive activation of NF-κB in the absence of stimulation ( from 25 ng to 300 ng TLR10/well ) . After 24 h of transfection , cells were stimulated for 4 h with 10 ng/ml of Pam3CSK4 for TLR2/1 or Pam2CSK4 for TLR2/6 ( EMC microcollections ) in triplicate . No stimulation was performed for TLR10 because the ligand remains unknown . Then , supernatants were discarded and cells were lysed in 100 µl of passive lysis buffer ( Promega , Madison , WI ) and assayed for dual luciferase activities ( Firefly and Renilla luciferase activities ) according to the manufacturer's instructions . Luciferase activity was normalized by Renilla luciferase activity to account for the transfection efficiency and expressed as the mean relative stimulation±SD of three replicates of a representative of three independent experiments ( each performed in triplicate ) . Cell lysates were subjected to SDS-PAGE ( 10% ) under reducing conditions . Membranes were probed with an anti-HA tag antibody ( Invivogen , San Diego , CA ) followed by HRP-conjugated rabbit antimouse IgG ( JacKson ImmunoResearch , West Grove , PA ) . Detection was performed with the Pierce Western blotting reagent ( Thermo Scientific , Rockford , IL ) . | The detrimental effects of microbial infections have led to the evolution of a variety of host defense mechanisms . A vast array of host innate immunity receptors , critical sensors of viruses , bacteria , and fungi , exist to achieve permanent surveillance of intruding pathogens . The best characterized class of microbial sensors is the Toll-like receptor ( TLR ) family , which elicits inflammatory and antimicrobial responses after activation by microbial products . Here we investigated how microbes have exerted selective pressure on the human TLR family to gain insights on the extent to which they are functionally important in the immune system . By resequencing the ten TLRs in different worldwide populations , we show that intracellular TLRs—principally specialized in viral recognition—evolve under strong purifying selection , indicating their essential role in host survival , while the remaining TLRs display higher levels of immunological redundancy . However , for this latter group of genes , we also show that mutations altering immune responses have been in some cases beneficial for host survival , as attested by the signature of positive selection favoring a reduced TLR1-mediated response in Europeans . Our findings taken together indicate that the different human TLRs differ in their biological relevance and provide clues to be experimentally tested in clinical , immunological , and epidemiological studies . | [
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] | 2009 | Evolutionary Dynamics of Human Toll-Like Receptors and Their Different Contributions to Host Defense |
The immune system depends on effector pathways to eliminate invading pathogens from the host in vivo . Macrophages ( MΦ ) of the innate immune system are armed with vitamin D-dependent antimicrobial responses to kill intracellular microbes . However , how the physiological levels of vitamin D during MΦ differentiation affect phenotype and function is unknown . The human innate immune system consists of divergent MΦ subsets that serve distinct functions in vivo . Both IL-15 and IL-10 induce MΦ differentiation , but IL-15 induces primary human monocytes to differentiate into antimicrobial MΦ ( IL-15 MΦ ) that robustly express the vitamin D pathway . However , how vitamin D status alters IL-15 MΦ phenotype and function is unknown . In this study , we found that adding 25-hydroxyvitamin D3 ( 25D3 ) during the IL-15 induced differentiation of monocytes into MΦ increased the expression of the antimicrobial peptide cathelicidin , including both CAMP mRNA and the encoded protein cathelicidin in a dose-dependent manner . The presence of physiological levels of 25D during differentiation of IL-15 MΦ led to a significant vitamin D-dependent antimicrobial response against intracellular Mycobacterium leprae but did not change the phenotype or phagocytic function of these MΦ . These data suggest that activation of the vitamin D pathway during IL-15 MΦ differentiation augments the antimicrobial response against M . leprae infection . Our data demonstrates that the presence of vitamin D during MΦ differentiation bestows the capacity to mount an antimicrobial response against M . leprae .
The MΦ is a sentinel of the innate immune system that serves as the first line of defense to recognize and destroy invading microbes . In human MΦ , activation by a toll-like receptor 2/1 ( TLR2/1 ) ligand or interferon-γ ( IFN-γ ) triggers a direct antimicrobial response that depends upon the level of available vitamin D [1–3] . The vitamin D-dependent antimicrobial pathway involves the induction of IL-15 and IL-32 , the conversion of 25D3 to bioactive 1 , 25-dihydroxyvitamin D ( 1 , 25D3 ) and subsequent activation of the vitamin D receptor ( VDR ) to induce the expression of the antimicrobial peptides including cathelicidin , autophagy and phagolysosomal fusion [2 , 4–8] . This antimicrobial pathway is not induced in MΦ if the levels of 25D are not sufficient . Macrophages demonstrate phenotypic heterogeneity which confer distinct functions in the innate immune system [9] . IL-15 MΦdemonstrate a vitamin D-dependent antimicrobial profile which includes the expression of CAMP mRNA [4 , 10] . In contrast , primary human monocytes treated with IL-10 differentiate into phagocytic macrophages ( IL-10 MΦ ) , which readily take up bacteria but weakly express the vitamin D-dependent antimicrobial pathway [10] . These MΦ subtypes can be identified by a specific cell surface phenotype , both IL-15 MΦ and IL-10 MΦ express CD209 but only IL-10 MΦ express CD163 . As such , IL-15 MΦ and IL-10 MΦ are differentially identified in the polar forms of leprosy caused by the intracellular bacterium M . leprae , correlating with the different outcomes of infection . In addition to its role in MΦ antimicrobial function , vitamin D has long been recognized to affect the differentiation of diverse cell types , including cells of the myeloid lineage [11] . Activation of the VDR converts malignant myeloid leukemia cells into non-proliferating monocytes or MΦ [12–15] . Dendritic cells differentiated in the presence of 25D3 or 1 , 25D3 demonstrate aberrant differentiation and decreased antigen presentation in vitro [16 , 17] . MΦ differentiated in vitamin D have also demonstrated a change in phenotype and phagocytic function in vitro [15 , 18] . Most of these studies were performed by adding non-physiological concentrations of the bioactive form of 1 , 25D3 , such that the ability of the differentiating cell to utilize physiologic concentrations of 25D3 has not been substantially investigated . Although controversy still exists on the normal concentrations of 25D , we used the Endocrine Society Clinical Practice Guidelines which define vitamin D deficiency as below 20ng/mL ( 50nM ) , insufficiency as 21–29 ng/mL ( 52 . 5nM-72 . 5nM ) , sufficient levels as more that 30ng/mL ( 75nM ) [19] . In humans , 1 , 25D levels are regulated to be constant , such that the available level of 25D determines the amount of bioactive 1 , 25D that is generated in an activated MΦ and is therefore key to innate immune function [3] . Therefore , the aim of our work is to study the effects of physiological levels of 25D3 during IL-15 MΦ differentiation , function and antimicrobial response against M . leprae .
Experiments with three or more measurements were analyzed using One Way ANOVA or with Student-Newman-Keuls Method ( *P<0 . 05 , **P<0 . 01 , ***P<0 . 005 , ****P<0 . 001 ) for pairwise analyses using GraphPad Prism 7 software . Error bars represent the standard error of the mean between individual donor values . A two-tailed student’s t-test was used to compare two different experimental conditions . This study was conducted according to the principles expressed in the Declaration of Helsinki and was approved by the Institutional Review Board ( IRB ) of the University of California at Los Angeles ( UCLA ) . Human peripheral blood from healthy donors was acquired with informed consent ( UCLA Institutional Review Board #11–001927 ) . All adult subjects provided written informed consent . Peripheral blood mononuclear cells ( PBMCs ) were isolated from the blood of healthy donors using Ficoll-Paque ( GE healthcare ) and monocytes were purified with plastic adherence as previously described [20] . Adherent monocytes were cultured in the presence of IL-15 ( R&D Systems , 200ng/ml ) or IL-10 ( R&D Systems , 10ng/ml ) for 48 hours using Serum Free MΦ media ( SFM ) ( Gibco ) at 37°C and 5% CO2 . Cell phenotypes were consistent with previously published data [10] . The following antibody clones were used per manufacturers’ protocol for flow cytometry: CD209 ( DCN46 ) , CD163 ( GHI/61 ) , CD16 ( 3G8 ) , CD14 ( M5E2 ) , and CAMP/LL37/FALL39/Cathelicidin Antibody ( OSX12 ) . Differentiated MΦwere harvested and stained as previously described [1 , 4 , 5 , 20] . RNA was harvested using TRIzol reagent ( Life Technologies ) via phenol-chloroform extraction , followed by RNA cleanup and DNase digestion using the RNeasy Miniprep Kit ( Qiagen ) as previously described [21] . cDNA was synthesized using iScript cDNA synthesis kit ( Bio-Rad ) and stored at -80°C . Primer sequences were used as follows: CYP27B1 F: ACC CGA CAC GGA GAC CTT C , CYP27B1 R: ATG GTC AAC AGC GTG GAC AC; CAMP F: TGG GCC TGG TGA TGC CT , CAMP R: CGA AGG ACA GCT TCC TTG TAG C H36B4 F: CCA CGC TGC TGA ACA TGC T , H36B4 R: TCG AAC ACC TGC TGG ATG AC . Real-time PCR was performed using SYBR Green ( Kapa Biosystems ) according to the manufacturers’ protocol . cDNA levels were normalized with H36B4 as the housekeeping gene . Relative CAMP mRNA levels were normalized to IL-15 MΦ differentiated in the absence of vitamin D and shown as fold-change ( FC ) . Relative CYP27B1 mRNA levels were normalized to IL-15 MΦ baseline levels and shown as fold-change ( FC ) as previously described [1 , 6 , 10 , 21] . Primary human monocytes were seeded onto chamber slides ( BD falcon ) and treated with IL-15 with or without the presence of vitamin D . The cells were fixed and permeabilized using fixation/permeabilization solution kit ( BD Bioscience ) as indicated by the manufacturer . Cells were blocked with 10% human serum for 20 minutes and stained with CAMP/LL37/FALL39/Cathelicidin Antibody ( OSX12 ) antibody at 10μg/mL overnight . The monolayers were washed three times with cold-PBS and stained with a biotinylated-horse anti-mouse antibody ( Bio-Rad ) at 10μg/mL at room temperature for one-hour . The monolayers were washed again three times with cold-PBS and stained with streptavidin-conjugated to Alexa Fluor 488 ( Invitrogen ) protected from light as previously described [1 , 5] . The cells were washed with PBS and sealed with ProLong Gold antifade reagent with DAPI ( Invitrogen ) . Microscopy images were analyzed with the SP8-SMD confocal microscope ( Leica ) at the Advanced Microscopy Laboratory Macro-Scale Imaging Laboratory , California Nanosystems Institute , UCLA [22] . IL-15 MΦwere differentiated in the presence or absence of vitamin D in a 24-well tissue culture plate ( Corning ) . The cells were harvested and fixed with 4% paraformaldehyde for 15 minutes at room temperature in a V-bottom plate ( Corning ) . After fixation , the MΦ were permeabilized with 0 . 5% saponin ( Sigma ) in PBS and quickly washed with a series of PBS washes . The cells were then stained using same staining protocol as described above . The cells were acquired with a BD LSRII in the Janis V . Gorgi Flow Cytometry Core Laboratory at UCLA . All analysis was done using FlowJo 10 . 4 . 2 software . Cells were infected with PE-labeled M . leprae and harvested 24 hours post infection ( PI ) . The cells were blocked with 10% human serum for 20 minutes at room temperature and stained with an anti-CD14 antibody as indicated by the manufacturer for 30 minutes on ice . The cells were then fixed with 4% paraformaldehyde for 15 minutes and analyzed by flow cytometry as previously described [4 , 20] . The cells were acquired with a BD LSRII in the Janis V . Gorgi Flow Cytometry Core Laboratory at UCLA . All analysis was done using FlowJo 10 . 4 . 2 software . The same samples were also analyzed using IdEAS Software , ImageStream ( Amnis ) as explained below . The ImageStreamX MarkII imaging flow cytometer from Amnis Corporation was used for acquisition at 60X magnification . Anti-human CD14 antibody conjugated to PacBlue channel 1 was detected on the 405 nm laser at 30 . 00 mW , and PE labeled M . leprae channel 3 was detected off the 488 nm laser set at 70 . 00 mW . Acquisition was set to collect 5000 objects from the single cell population ( Aspect Ratio Bright Field channel 4 vs . Area Bright Field channel 4 ) . Data was analyzed using the Amnis IDEAS software . A compensation matrix was first created using single-stained CD14 labeled macrophages and PE calibrite beads ( BD ) . Compensated data was then applied to a template with a gating hierarchy . Focused cells were first selected from the higher population of the Gradient RMS histogram; single cells were then chosen using the same gating strategy applied during acquisition and lastly , PE and PacBlue double positive cells were then applied to the Spot Count Wizard . Two populations containing 10 or more cells , each expressing high or low values of spots ( single PE labeled M . leprae bacterium ) were manually selected . The Spot Count Wizard has the ability to measure uptake and count spots , thus providing individual bacterial counts per cell . IL-15 MΦwere differentiated with or without the indicated amount of 25D for 48 hours . The MΦ were then infected with M . leprae overnight at an MOI of 10 . The cells were washed with SFM to remove extracellular bacteria and treated with IL-15 and the indicated amounts of 25D . The infection progressed for 24 hours , 48 hours and 120 hours and all the material in the well was harvested into a 15mL conical tube . To ensure that all the material in the well was harvested , each well was washed with a series of cold PBS-EDTA washes and accumulated into their respective 15mL conical tube . Each 15mL conical tube was placed into a centrifuge for 300xg for 10 mins at 4°C . The supernatants were carefully removed and the genomic DNA was isolated as previously described [21 , 23] . We compared RLEP DNA levels of M . leprae with the H36B4 levels of the IL-15 MΦto measure bacterial burden using real-time PCR using SYBR Green as indicated by the manufacturer ( Kapa Biosystems ) [24 , 25] . The following primers sequences were used: RLEP F: GCA GCA GTA TCG TGT TAG TGA A , RLEP R: CGC TAG AAG GTT GCC GTA T; H36B4 F: CCA CGC TGC TGA ACA TGC T , H36B4 R: TCG AAC ACC TGC TGG ATG AC . The bacteria burden at each time point was normalized to IL-15 MΦdifferentiated without vitamin D to quantify relative bacteria burden .
To investigate the effect of 25D3 on MΦ differentiation , we used SFM , allowing us to control the amount of 25D3 in the culture . SFM contains neither 25D3 nor any other vitamin D analogues , such that 25D3 can be added at defined concentrations . Thus , SFM has an advantage over fetal calf sera or human sera that have varying amounts of 25D3 . Previously , IL-15 and IL-10 were shown to induce the differentiation of monocytes into distinct MΦ populations , however , these experiments were performed using FCS , which contains low levels of 25D3 . Thus , it was unclear whether vitamin D status affects the differentiation of monocytes into IL-15 MΦ and IL-10 MΦ . All experiments here involve MΦs derived from cytokine treated monocytes as previously reported [10] . Monocytes were cultured with either IL-15 or IL-10 for 48 hours in SFM with or without the addition of 25D3 ( 10-8M 25D3 ) . This is equivalent to the physiologic concentration in vitamin D sufficient serum of 10-7M 25D3 , which is then diluted to 10% serum in cell cultures [1 , 26] . Both IL-15 and IL-10 induced CD209 expression as assessed by flow cytometry , but only IL-10 induced CD163 expression ( Fig 1A ) , similar to differentiation in FCS [10] . Examining co-expression of CD209 and CD163 , we found that IL-15 induced CD209+CD163- MΦ , whereas IL-10 induced CD209+CD163+ MΦ , accounting ~80% of cells . We also found that the IL-15 MΦand IL-10 MΦ derived in SFM express the MΦ specific marker CD16 . The average surface expression of CD16 increased in IL-15 MΦ when differentiated in 25D3 to similar levels seen on IL-10 MΦ , but was not significant ( p = 0 . 07 ) . In addition , we observed that 25D3 status did not significantly alter the surface expression of CD209 , CD163 , CD16 or the coexpression of CD209+CD16+ whether derived using IL-15 or IL-10 ( Fig 1A ) . The frequency of CD14 was expressed on IL-15 MΦ , with a small but significant enhancement by 25D3 , to the level expressed on IL-10 MΦ ( Fig 1A ) . This was also reflected in an increase in cellular abundance as measured by the change in mean fluorescence intensity ( ΔMFI ) for MΦ derived in IL-15 but not IL-10 ( Fig 1B ) . Overall , SFM supported the differentiation of monocytes by IL-15 and IL-10 into divergent MΦ phenotypes , which were generally similar whether differentiated in the presence or absence of 25D3 . Although 25D3 did not dramatically affect the differentiation of MΦ by phenotype , we next investigated whether the presence of 25D3 during differentiation affected MΦ function . The induction of the antimicrobial protein cathelicidin is essential for the vitamin D-dependent antimicrobial response against intracellular mycobacteria in infected MΦ [5 , 27] . To determine whether 25D3 status during MΦ differentiation results in activation of the vitamin D-dependent antimicrobial pathway , we treated monocytes with IL-15 and IL-10 in the presence of increasing concentrations of 25D3 during differentiation and measured CAMP mRNA levels after 48 hours by qPCR . Conditioning during differentiation of both IL-15 MΦ and IL-10 MΦ in SFM supplemented with increasing level of 25D3 resulted in a significant dose-dependent induction of CAMP mRNA ( Fig 2A ) . At all concentrations of 25D3 , the CAMP mRNA expression was more robust in IL-15 MΦ relative to IL-10 MΦ . We observed a ~315-fold induction of CAMP mRNA in SFM supplemented with 10-8M 25D3 as compared to media without 25D3 in IL-15 MΦ , and ~500-fold induction of CAMP mRNA in SFM containing 10-7M 25D3 ( Fig 2A ) . In comparison , we observed a ~80-fold induction of CAMP mRNA in SFM containing 10-8M 25D3 in IL-10 MΦ and a ~100-fold induction of CAMP mRNA in SFM containing 10-7M 25D3 ( Fig 2A ) . The baseline values of CYP27B1 mRNA expression was not significant between IL-15 MΦand IL-10 MΦ ( S1 Fig ) . We determined whether the induction of CAMP mRNA was associated with expression of cathelicidin protein using intracellular flow cytometry . The CAMP mRNA expression levels in IL-15 MΦ correlated with both the frequency of cathelicidin and the cathelicidin protein abundance as measured by ΔMFI ( Fig 2B and 2C ) . The average frequency of cathelicidin was ~13% in IL-15 MΦ derived in 10-8M 25D3 and ~30% in 10-7M 25D3 supplemented SFM ( Fig 2B ) . The ΔMFI was ~45 AU in IL-15 MΦ derived in 10-7M 25D3 and ~80 AU in 10-8M 25D3 supplemented SFM ( Fig 2C ) . Representative fluorescence microscopy images of IL-15 MΦ conditioned in 25D3 indicates that cathelicidin protein accumulates in the intracellular vesicles proximal to the host nucleus , but not in IL-15 MΦdifferentiated in no 25D3 ( Fig 2D ) . These data collectively indicate that cathelicidin mRNA and protein expression directly correlate with 25D3 status during IL-15 induced MΦ differentiation . An important function of antimicrobial MΦ is the phagocytosis of pathogens to contain microbes in the host in vivo . However , it is unclear how vitamin D status may alter the phagocytic function of the MΦ during M . leprae infection . To assess phagocytic function , IL-15 MΦwere conditioned with or without 25D3 , infected with PE labeled-M . leprae for 24 hours , stained for the MΦ specific marker CD14 and phagocytosis was analyzed by flow cytometry and image stream flow cytometry . The efficiency of M . leprae infection in IL-15 MΦdifferentiated in the absence of vitamin D or in the presence of either 10-8M 25D3 or 10-7M 25D3 , was not statistically different , although somewhat greater in culture in which no 25D3 was present ( Fig 3A ) . Image stream flow cytometry analysis of the same samples demonstrated a frequency of infection of CD14+mLEP+ cells ranging from 30% , 35% , to 25% , when conditioned with no vitamin D , 10-8M 25D3 or 10-7M 25D3 , respectively ( Fig 3B ) . Using an unsupervised spot counting function of image stream flow cytometry , we determined the frequency of CD14+ cells containing varying numbers of intracellular M . leprae and no effect of 25D3 was observed ( Fig 3C ) . Images from image flow cytometry analysis show the number of bacteria per MΦ ( Fig 3D ) . Cells that contained either 7 or 8 bacteria all showed large clumps of bacteria in which were difficult to interpret as an accurate number of bacteria . Overall no significant difference was observed in the number of bacteria per cell . These data indicate that vitamin D status does not alter the phagocytic capacity of IL-15 MΦ . After the phagocytosis of invading pathogens , a major function of MΦ is to effectively mount an antimicrobial response to defend the host . However , it is unclear whether sufficient levels of 25D3 will provide MΦ with the capacity to mount an antimicrobial response . To investigate whether 25D3 status during MΦ differentiation affects the antimicrobial response , we simultaneously measured the kinetics of CAMP mRNA induction and antimicrobial activity against M . leprae in IL-15 MΦ . IL-15 MΦ were conditioned with or without 25D3 , infected with M . leprae for 24 , 48 , and 120 hours , at which time both RNA and DNA were harvested . The levels of CAMP mRNA in M . leprae infected IL-15 MΦ at 24 hours were relatively low as compared to the previous experiments in which CAMP mRNA was measured in uninfected MΦ , to the extent that CAMP mRNA was not detectable in some donors at this time point . However , the cathelicidin protein colocalized with M . leprae in IL-15 MΦdifferentiated in 25D3 , but not in IL-15 MΦdifferentiated in no 25D3 24 hours post M . leprae infection ( Fig 4A ) . The low level of CAMP mRNA expression was not different whether the MΦ were differentiated in the presence or absence of 25D3 ( Fig 4B ) . One possibility for the absence of CAMP mRNA but presence of cathelicidin protein at 24 hrs post infection is that upon infection with M . leprae the CAMP mRNA is downregulated yet the protein was already synthesized during differentiation . At 48 hours after M . leprae infection , CAMP mRNA expression was approximately 1000 fold in the IL-15 MΦ differentiated in 25D3 , at either 10-8M 25D3 or 10-7M 25D3 ( Fig 4C ) . At 120-hours post infection , the relative CAMP mRNA remained significantly increased in the MΦ differentiated in 25D3 , approximately 200–330 fold greater than in MΦ differentiated in the absence of 25D3 ( Fig 4D ) . The M . leprae burden was measured in the infected IL-15 MΦ according to the level of bacterial DNA . The M . leprae burden in infected IL-15 MΦ was not affected by the presence of 25D3 during differentiation as assessed at 24 or 48 hours ( Fig 4E and 4F ) . In one of the five donors , we noted a reduction in bacterial burden at 48 hours . However at 120 hours post infection the relative bacteria burden significantly decreased to 0 . 67 and 0 . 44 in IL-15 MΦ differentiated in 10-8M and 10-7M 25D3 compared to no 25D3 , respectively ( Fig 4G ) . The decrease in viability of M . leprae at 120 hours was not due to differences in macrophage number , as H36B4 levels remained constant . Antimicrobial activity against M . leprae was detected in IL-15 MΦ differentiated in 25D3 in all five donors . These data indicate that the presence of 25D3 during the IL-15 MΦ differentiation program and throughout M . leprae infection contributes to the vitamin D-dependent antimicrobial response against by M . leprae .
The ability of human MΦ to mount an effective response against intracellular mycobacteria depends in part upon their ability to induce the vitamin D-dependent antimicrobial pathway [1 , 2 , 5 , 28] . Although sufficient levels of vitamin D are required for optimal MΦ effector function , previous studies have indicated that myeloid cell differentiation and function can be altered by vitamin D bioavailability . Here , we investigated whether the level of 25D influences MΦ differentiation and programming of an antimicrobial response against M . leprae . The distinct phenotypes of IL-15 MΦ and IL-10 MΦ were largely sustained during differentiation from monocytes regardless of 25D3 status , yet onlyIL-15 MΦdifferentiated in the presence 25D3 robustly triggered the expression of CAMP mRNA and cathelicidin protein levels in a dose-dependent manner . Vitamin D status did not alter the phagocytic function of IL-15 MΦ , but a significant decrease in bacteria burden against M . leprae was observed at 120 hours post-infection . These data indicate that 25D3 status during IL-15 MΦdifferentiation permits the induction of an antimicrobial response against intracellular M . leprae . It is important for the host to mount an antimicrobial response against intracellular mycobacteria before the bacteria employ evasion mechanisms that help establish infection and progress to clinical disease [22 , 23] . A key finding of the present study was that the addition of 25D3 during the IL-15 induced differentiation of monocytes into MΦ led to a robust induction of the vitamin D-dependent antimicrobial pathway , including the induction of cathelicidin and an antimicrobial response against M . leprae . We detected a 315-fold induction of CAMP mRNA in IL-15 MΦ differentiated in the presence 10-8M 25D3 as compared to SFM without 25D3 and a 1/3 reduction in the M . leprae burden in infected cells . Previously we have shown that IL-15 MΦ supplemented with 10-8M 25D3 post-differentiation demonstrated a 5-fold increase in CAMP mRNA and a ~50% reduction in avirulent M . tuberculosis ( H37ra ) viability [4] . However , these IL-15 MΦ were differentiated in 10% 25D insufficient FCS ( 16nM ) . These data collectively suggest that 25D levels during IL-15 MΦ differentiation facilitate their antimicrobial function as part of the innate immune response . There are situations that allow the pathogen to escape the vitamin D antimicrobial response . For example , genetic polymorphisms in the VDR have been associated with increased susceptibility to mycobacterial infection [29] . M . leprae evades the vitamin D antimicrobial response via the induction of a microRNA that targets the pathway [23] , and by induction of type 1 interferon leading to IL-10 and subsequent suppression of the vitamin D pathway [22] . These data imply that upon the onset of microbial challenge , monocytes that are recruited to the site of infection are dependent on the presence of sufficient levels of 25D to differentiate into powerful IL-15 MΦthat fend of M . leprae evasion mechanisms and effectively reduce bacterial viability [1 , 5 , 30] . The addition of 25D3 during the IL-15 induced differentiation of monocytes into MΦ affected antimicrobial function , but we observed little change in cell phenotype . Regardless if the MΦ were differentiated with or without 25D3 , we found that the distinct phenotypes of IL-15 MΦ and IL-10 MΦ were largely not affected . In particular , the IL-15 MΦ were CD209+CD163- and the IL-10 MΦ were CD209+CD163+ . Only IL-15 MΦ differentiated in 25D3 demonstrated both a significant increase in CD14 frequency and cellular abundance . Although CD14 is a marker that identifies VDR-activated MΦs [31] , we have no evidence that the differences in CD14 expression directly affected function as phagocytic capacity was not affected . In contrast to our findings , the addition of 1 , 25D3 during differentiation of monocytes into MΦ by macrophage colony-stimulating factor ( M-CSF ) decreased phagocytic function and the release of pro-inflammatory cytokines [18] . Similarly , the addition of 25D3 or 1 , 25D3 during differentiation of monocytes into dendritic cells by granulocyte-macrophage colony-stimulating factor ( GM-CSF ) plus IL-4 decreased the expression of DC-specific surface markers CD1a , CD80 , CD86 , and MHC class-II , as well as antigen presentation capacity [16 , 17] . In these experiments the levels of 1 , 25D3 were supraphysiologic , although 25D3 was added at physiologic levels . Taken together with our findings , these findings suggest that although physiologic levels of 25D may alter the differentiation of DC , it permits MΦ differentiation and enhances MΦ antimicrobial function . In the present study we determined that clinically sufficient levels of 25D3 led to a functional difference in IL-15 MΦ , relative to MΦ differentiated in the absence of 25D3 . In humans , there is a range of 25D levels that can be classified from deficient ( 45nM ) to sufficient ( 98nM ) [2] . Previously , we compared the ability of African American sera and Caucasian sera to induce the expression of the mRNAs encoding the antimicrobial peptides cathelicidin and beta-defensin 2 and found that African American sera was less capable to induce the antimicrobial peptides ex vivo due to the relatively lower 25D sera levels [1 , 2] . Both exogenous 25D supplementation to African American sera ex vivo and 25D supplementation to vitamin D deficient individuals in vivo significantly enhanced CAMP mRNA expression in activated monocytes and MΦ in vitro [1 , 2 , 32] . Our data suggest that people with higher levels of vitamin D will derive MΦ with more antimicrobial function that could prevent the establishment of infection; however , testing the effects of vitamin D status on the prevention of infection by M . tuberculosis is challenging . The ability to acquire a large enough population with differential 25D levels randomly will be difficult as 25D status strongly correlates with season [33] , as such there are few studies that investigate the interaction of 25D status with infection by the pathogen . Deficient levels of 25D in household contacts of TB patients demonstrated either increased latent TB incidence or positive tuberculoid skin tests [33 , 34]; however the number of patients that acquire active TB is unclear [35–37] . These data support continued and more thorough investigation into whether vitamin D supplementation of deficient and insufficient individuals in vivo can enhance the MΦ antimicrobial response against mycobacterial infections and contain the spread and outcome of disease . In conclusion , we found that vitamin D-dependent antimicrobial MΦ differentiated in the presence of sufficient levels of 25D3 sustain a MΦ phenotype and exhibit an antimicrobial response against M . leprae . Our model indicates that vitamin D-dependent antimicrobial MΦ differentiated in the presence of sufficient 25D are capable of intrinsic microbicidal activity against infection . In contrast , the same MΦ differentiated in the low levels of 25D require the addition of exogenous 25D to induce activity [1 , 2 , 5 , 32] . These data suggest that sufficient levels of 25D at the site of microbial infection allow recruited monocytes to differentiate into vitamin D-dependent antimicrobial MΦ with the capacity to effectively reduce the viability of intracellular bacteria . Future clinical trials that study the relationship between vitamin D supplementation and susceptibility to microbial infection will determine if the prophylactic effects of vitamin D are therapeutically beneficial . | A key function of MΦ is to recognize , phagocytose and mount an antimicrobial response against microbial pathogens to defend the host . In humans , monocytes are recruited to the site of infection and differentiate into MΦ upon the onset of microbial infection . The MΦ phenotype and function are determined by the cytokine profile of the microenvironment in which the monocyte enters . Additionally , vitamin D is known to trigger direct antimicrobial responses against invading pathogens in MΦ , but also disrupts the differentiation of immune subsets within the myeloid lineage . Therefore , we investigated whether vitamin D status during MΦ differentiation influenced either phenotype or function . Here , we found that the IL-15 MΦphenotype is sustained regardless of vitamin D status . In contrast , antimicrobial MΦ differentiated in the presence of vitamin D exhibited a robust expression of an antimicrobial peptide , relative to MΦ differentiated in the absence of vitamin D . The antimicrobial MΦ armed with cathelicidin prior to M . leprae challenge demonstrated a strong antimicrobial response against the invading pathogen . Our study reveals that the presence of sufficient levels of vitamin D prior to microbial infection contributes to effectively reduce the viability of the pathogen in MΦ . | [
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"a... | 2018 | Vitamin D status contributes to the antimicrobial activity of macrophages against Mycobacterium leprae |
The intensity categories , or thresholds , currently used for Trichuris trichiura ( ie . epg intensities of 1–999 ( light ) ; 1 , 000–9 , 999 epg ( moderate ) , and ≥10 , 000 epg ( heavy ) ) were developed in the 1980s , when there were little epidemiological data available on dose-response relationships . This study was undertaken to determine a threshold for T . trichiura-associated anemia in pregnant women and to describe the implications of this threshold in terms of the need for primary prevention and chemotherapeutic interventions . In Iquitos , Peru , 935 pregnant women were tested for T . trichiura infection in their second trimester of pregnancy; were given daily iron supplements throughout their pregnancy; and had their blood hemoglobin levels measured in their third trimester of pregnancy . Women in the highest two T . trichiura intensity quintiles ( 601–1632 epg and ≥1633 epg ) had significantly lower mean hemoglobin concentrations than the lowest quintile ( 0–24 epg ) . They also had a statistically significantly higher risk of anemia , with adjusted odds ratios of 1 . 67 ( 95% CI: 1 . 02 , 2 . 62 ) and 1 . 73 ( 95% CI: 1 . 09 , 2 . 74 ) , respectively . This analysis provides support for categorizing a T . trichiura infection ≥1 , 000 epg as ‘moderate’ , as currently defined by the World Health Organization . Because this ‘moderate’ level of T . trichiura infection was found to be a significant risk factor for anemia in pregnant women , the intensity of Trichuris infection deemed to cause or aggravate anemia should no longer be restricted to the ‘heavy’ intensity category . It should now include both ‘heavy’ and ‘moderate’ intensities of Trichuris infection . Evidence-based deworming strategies targeting pregnant women or populations where anemia is of concern should be updated accordingly .
The most recent comprehensive estimation of the prevalences of the soil-transmitted helminthiases ( STH ) documents a global prevalence of 17% for Trichuris trichiura infection , with approximately 800 million persons infected at any one time [1] , [2] . Community-wide prevalences are frequently over 30–40% and it is not uncommon to observe prevalences exceeding 80% in community sub-groups like school-age children and preschool-age children [3]–[7] . T . trichiura infections contribute to the STH-attributable burden of disease by adversely affecting the growth and cognitive development of children and the health and productivity of adults [8] , [9] . Because of its co-occurrence with other infections , malnutrition and poverty , it also diminishes the economic potential , not only of the infected individual , but also of the family and community as well [10] . In 1987 , an expert committee convened by the World Health organization ( WHO ) established infection intensity categories for STH , including T . trichiura , in order to inform the management of large-scale deworming programs [11] . T . trichiura infection was defined as light ( 1–999 epg ) or heavy ( >10 , 000 epg ) [11] . These categories were based primarily on expert opinion and little dose-response data from the field , and were described as “arbitrary” by this committee . [11] . A further category of ‘moderate’ ( i . e . for epg counts between 1 , 000 and 9 , 999 epg ) was subsequently added by WHO [12] . The original 1987 report had also mentioned that anemia attributable to T . trichiura infection reflected a ‘very heavy worm burden’ [11] . Since then , the association between T . trichiura ( prevalence and intensity ) and hemoglobin ( Hb ) levels or anemia , has been assessed in several epidemiologic studies mostly conducted in Africa and in Asia and of which the majority found no significant association [13]–[18] . However , four studies conducted in the Americas ( Jamaica , Panama , Mexico and Peru ) reported statistically significant associations [19]–[22] . In addition , T . trichiura infection has been associated with a lower increase of Hb in iron-supplemented pregnant women [22] . Mechanisms by which T . trichiura infection may cause anemia include ingestion of blood by the parasite , blood loss from parasite-induced lesions in the intestinal mucosa , and inflammatory responses such as tumor necrosis factor α ( TNFα ) leading to decreased appetite; the relative contributions of these factors being unknown [9] . Anemia is a major public health problem because it impairs the growth and cognitive development in children and because severe anemia increases the risk of maternal mortality . Its worldwide prevalence is estimated at 48 . 8% [23] . The importance of the cluster of STH to the global risk of anemia is relatively well known , but among helminth species , T . trichiura has received much less attention than hookworms . The objectives of this study were to determine a threshold for T . trichiura-associated anemia in pregnant women , and to describe the implications of this threshold in terms of the need for primary prevention and chemotherapeutic interventions .
Ethics approval was obtained for the original RCT from the following review committees: Research Institute of the McGill University Health Centre ( Canada ) , The “Comite Institucional de Etica de la Universidad Peruana Cayetano Heredia” ( Peru ) ; and the “Comite Etica de la Direccion General de Salud de las personas del Ministerio de Salud de Peru” ( Peru ) . The research procedures followed were in accordance with the ethical standards of these three ethics committees and with the Helsinki Declaration . Written informed consent was obtained from all women . The data source for this study originated from a randomized controlled trial on mebendazole during pregnancy and its effect on birth weight which had been conducted in the highly STH-endemic Amazon area of Peru whose methods have been described elsewhere [24] . Briefly , 1 , 042 pregnant women were recruited in their second trimester and randomly assigned to receive either a single dose of 500 mg mebendazole or a placebo . Women in both groups received daily iron supplements throughout their pregnancy . At enrolment ( second trimester ) and again in the third trimester , blood and stool specimens were collected from participants for hemoglobin ( Hb ) ascertainment by HemoCue and for STH determination by the Kato-Katz method . There was no statistically significant difference between intervention groups in the prevalence of anemia or in mean hemoglobin levels in the third trimester . However , women having Trichuris trichiura infection in the second trimester were at a higher risk of anemia in their third trimester [22] . To determine a threshold for the effect of T . trichiura infection intensity on hemoglobin and anemia , the 935 mothers for whom complete information was available ( i . e . on helminth infection and hemoglobin level in both the 2nd and 3rd trimester , plus covariates ) were divided into quintiles based on T . trichiura infection intensity in the second trimester . Mean hemoglobin concentrations and anemia prevalence in the third trimester were calculated for each group . Mean hemoglobin concentrations in the third trimester of each T . trichiura quintile were compared to the lowest quintile using generalized linear model ( GLM ) analysis . The prevalence of anemia , defined as hemoglobin <11 g/dL [23] , in the third trimester in each quintile was compared to that of the lowest quintile by logistic regression . Covariates found to be statistically significantly associated with the outcome were included in regression models: the model predicting hemoglobin levels included hookworm intensity and the model predicting anemia included hookworm intensity and the time interval between assessments for hemoglobin levels [22] .
Among the 935 pregnant women included in the analysis , 82% were infected with Trichuris trichiura , and 43% were co-infected with T . trichiura and hookworms . The highest T . trichiura infection intensity was 25 , 200 epg . Participants' characteristics are described in more detail elsewhere [22] . Women in the lowest three T . trichiura intensity quintiles had similar hemoglobin concentrations , with arithmetic mean levels of 11 . 53 , 11 . 55 and 11 . 58 g/dL , respectively . In contrast , the fourth and fifth quintiles had significantly lower mean hemoglobin concentrations than the reference group ( i . e . 11 . 24 and 11 . 05 g/dL , respectively ) ( Table 1 ) . The fourth and fifth quintiles also had a statistically significantly higher risk of anemia , with adjusted odds ratios of 1 . 67 ( 95% CI 1 . 02 , 2 . 62 ) and 1 . 73 ( 95% CI 1 . 09 , 2 . 74 ) , respectively ( Table 2 ) .
The fact that a statistically significant association between T . trichiura infection and anemia was found in this study , but not in any other study of pregnant women , can be explained , in part , by the fact that this time the association between T . trichiura and anemia was determined in a population of women who had received daily iron supplements . Therefore , the fraction of anemia attributable to an insufficient dietary intake may have been reduced in the study population , resulting in an increased fraction attributable to T . trichiura . This likely strengthened the association between T . trichiura and anemia in our study population , a finding that may not have been easily observable in other populations . The 601–1632 epg T . trichiura infection intensity category was the lowest epg category where a statistically significant association between hemoglobin and anemia was found . This indicates that the threshold for the T . trichiura effect on hemoglobin and the risk of anemia in iron-supplemented pregnant women appears to be somewhere between 601 and 1632 epg . In other words , iron-supplemented pregnant women with “light” or “moderate” T . trichiura infection intensities , based on the current classifications , may indeed be at an increased risk of morbidity from anemia as a result of the infection . This finding has implications for STH control programs , in particular , those programs targeting pregnant women , because the efficacy of the commonly used deworming regimens of single-dose albendazole or mebendazole against T . trichiura is not optimal [25] . This analysis also provides support for categorizing a T . trichiura infection ≥1 , 000 epg as “moderate” , as currently defined by WHO . In addition , for pregnant populations , even if they are receiving iron supplements during pregnancy , it may be that 601 epg should be considered a lower limit for this ‘moderate’ category . The most important implication of these analyses is that moderate T . trichiura infection in pregnant women is a significant risk factor for anemia which , in turn , increases the risk of adverse maternal and infant health outcomes . Therefore , in a pregnant population where there is a high prevalence of T . trichiura infection and where intensity levels exceed 600 epg , it may be that additional care options beyond the commonly used single-dose albendazole or mebendazole should be considered . | Infection by the soil-transmitted helminth Trichuris trichiura is defined as ‘light’ , ‘moderate’ and ‘heavy’ depending on its intensity . However , these intensity categories were developed in the 1980s , before any epidemiological data were available on the association between specific T . trichiura infection intensities and adverse health outcomes . Here , we re-analyzed data from a study of T . trichiura infection and anemia in pregnant women to determine the threshold ( i . e . the lowest infection intensity ) associated with an increased risk of anemia . Women with T . trichiura infections of intensities ranging from 601 to 1632 eggs per gram of feces ( epg ) ( ie . a ‘moderate’ level of intensity ) had a significantly higher prevalence of anemia and a significantly lower hemoglobin level than the reference group ( i . e . women with T . trichiura infections of intensities ranging between 0 and 24 epg ) . This finding contrasts with the common belief that only ‘heavy’ T . trichiura infection ( 10 , 000 epg and above ) can cause anemia . | [
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] | 2012 | Re-Visiting Trichuris trichiura Intensity Thresholds Based on Anemia during Pregnancy |
BCCIP is a BRCA2- and CDKN1A ( p21 ) -interacting protein that has been implicated in the maintenance of genomic integrity . To understand the in vivo functions of BCCIP , we generated a conditional BCCIP knockdown transgenic mouse model using Cre-LoxP mediated RNA interference . The BCCIP knockdown embryos displayed impaired cellular proliferation and apoptosis at day E7 . 5 . Consistent with these results , the in vitro proliferation of blastocysts and mouse embryonic fibroblasts ( MEFs ) of BCCIP knockdown mice were impaired considerably . The BCCIP deficient mouse embryos die before E11 . 5 day . Deletion of the p53 gene could not rescue the embryonic lethality due to BCCIP deficiency , but partially rescues the growth delay of mouse embryonic fibroblasts in vitro . To further understand the cause of development and proliferation defects in BCCIP-deficient mice , MEFs were subjected to chromosome stability analysis . The BCCIP-deficient MEFs displayed significant spontaneous chromosome structural alterations associated with replication stress , including a 3 . 5-fold induction of chromatid breaks . Remarkably , the BCCIP-deficient MEFs had a ∼20-fold increase in sister chromatid union ( SCU ) , yet the induction of sister chromatid exchanges ( SCE ) was modestly at 1 . 5 fold . SCU is a unique type of chromatid aberration that may give rise to chromatin bridges between daughter nuclei in anaphase . In addition , the BCCIP-deficient MEFs have reduced repair of irradiation-induced DNA damage and reductions of Rad51 protein and nuclear foci . Our data suggest a unique function of BCCIP , not only in repair of DNA damage , but also in resolving stalled replication forks and prevention of replication stress . In addition , BCCIP deficiency causes excessive spontaneous chromatin bridges via the formation of SCU , which can subsequently impair chromosome segregations in mitosis and cell division .
Loss of genomic integrity is a hallmark for tumorigenesis . Mammalian cells maintain genomic integrity by ensuring DNA replication fidelity in S-phase , equal chromosome distribution into daughter cells during mitosis , error-free repair of sporadic DNA damage throughout the cell cycle , and a coordinated cell cycle progression [1] . Homologous recombination ( HR ) plays roles not only in repair of DNA double strand breaks ( DSB ) but also in replication fidelity [2] , [3] . When the replication forks stall during S-phase , one-ended DSBs are produced on one of the sister chromatids at the stalled replication fork . Subsequently , the HR machinery uses the 3′-end of a single-stranded tail of the one-ended DSB to invade the intact double-stranded DNA at the collapsed replication fork , which leads to the resolution of the stalled fork . Failure to do so causes excessive replication stress , which is often defined as the inefficient progression of the replication forks . Replication stress is a status highly susceptible to genomic instability . The BRCA2 tumor suppressor gene plays critical roles in HR , mainly by mediating RAD51 function [4] , [5] , including the strand invasion step during the resolution of stalled replication forks . Although mutations of BRCA2 are involved in only a small percentage of human cancers , the germline BRCA2 mutations are of high penetrance in malignant neoplasms . This suggests that the entire molecular network of BRCA2 is critical for cancer prevention , and defects of other proteins related to BRCA2 may contribute to additional tumors [6] . Thus analyses of BRCA2-interacting proteins offers opportunities to identify additional genetic factors involved in tumorigenesis . BCCIP is a BRCA2- and CDKN1A ( p21 ) - interacting protein [7]–[10] . In human cells , two major isoforms are expressed due to RNA alternative splicing: BCCIPα and BCCIPβ [9] . Although the human BCCIPα isoform was originally identified as a p21 and BRCA2 interacting protein , later studies found that the BCCIPβ isoform also interacts with p21 and BRCA2 [10]–[12] . BCCIP down-regulation has been reported in cancers [9] , [13] , [14] . Human BCCIP is known to function in HR , G1/S cell cycle checkpoint , and cytokinesis [10]–[12] , [15]–[18] . Furthermore , BCCIP deficiency leads to accumulation of spontaneous DNA damage and single-stranded DNA in human cells [16] . The Ustilago maydis homologues of BCCIP and BRCA2 ( BCP1 and Brh2 ) also interact with each other , and BCP1 deficiency causes replication stress [19] . However , the in vivo function of BCCIP has not been determined . To determine the role of BCCIP in vivo , we established a conditional BCCIP knockdown transgenic mouse model . We show that developmental defects in the BCCIP-deficient embryos occurred before day E6 . 5 , and this was associated with a significant reduction of cell proliferation . In addition to an impaired repair of exogenous DNA damage , BCCIP deficiency significantly induced spontaneous chromatid aberrations that often associate with replication stress . The chromosome abnormalities in BCCIP-deficient mouse cells are characterized by the elevated formation of sister chromatid unions ( SCUs ) and chromatid breaks , yet a modest increase of sister chromatid exchange ( SCE ) . This suggests an essential role of BCCIP in maintenance of chromatid stability and embryonic development in mice .
Although human cells express two major isoforms ( BCCIPα and BCCIPβ ) due to alternative RNA splicing [9] , mouse tissues appear to express only the BCCIPβ isoform . In the previous studies , human BCCIP has been shown to function in DNA repair , cell cycle regulation , cytokinesis , and maintenance of chromosome stability [7] , [10]–[12] , [15]–[18] . Reduced or absence of BCCIP expression have been reported in human cancers [9] , [13] , [14] , [20] . To further understand BCCIP's role in development and tumorigenesis , we generated a mouse model with BCCIP deficiency . Similar to the human BCCIP gene structure [9] , the mouse uroporphyrinogen III synthase ( UROS ) is “head-to-head” with the BCCIP gene , and the UROS promoter is located in the intron of the BCCIP gene . The mouse DEAD/H box polypeptide-32 ( DDX32 ) gene is “tail-to-tail” with the BCCIP gene . We adapted the RNAi based conditional knockdown approach developed by Coumoul and colleagues [21]–[23] . Briefly , the U6 promoter that normally drives the expression of short hairpin RNAs ( shRNAs ) is disrupted by insertion of a LoxPneoLoxP cassette , thus is only functional upon the conditional deletion of the LoxPneoLoxP cassette ( Figure 1A ) . The conditional shRNA expression construct against BCCIP gene was integrated into the mouse genome using standard transgenic mouse techniques . Two founder homozygous transgenic mouse lines with the conditional expression cassette were generated . The two independent homozygous transgenic lines , designated LoxPshBCCIP+/+-4 and LoxPshBCCIP+/+-13 , were fertile , grow normally , and have the same lifespan as wild type mice . The LoxPshBCCIP+/+ transgenic mice were crossed with a mouse line expressing Cre recombinase to “pop-out” the LoxPneoLoxP segment . As reported elsewhere [23] , the single LoxP site left in the U6 promoter after Cre-recombination does not affect the U6 promoter activity . This reconstitutes the U6 promoter activity , leading to the expression of the anti-BCCIP shRNA ( Figure 1A ) , to achieve a Cre-dependent conditional knockdown of BCCIP . To verify the BCCIP knockdown , MEFs from the two founder lines were established . As predicted and shown in Figure S1 , mouse cells only express one isoform . Expression of Cre in the MEFs derived from both mouse founder lines cells efficiently knocked down BCCIP ( Figure S1 ) . These MEF cells , designated MEF4-LoxPshBCCIP and MEF13-LoxPshBCCIP , were used further in vitro studies . It should be pointed out that BCCIP can be knocked down in heterozygous LoxPshBCCIP+/− cells by expression of Cre because one copy of the LoxPshRNA cassette is able to express shRNA against BCCIP . In an attempt to generate mice with BCCIP knockdown , we bred the FVB/N LoxPshBCCIP+/+-4 , and LoxPshBCCIP+/+-13 with the FVB/N EIIaCre+/− mouse [24] that carries a Cre transgene under the control of the adenovirus EIIa promoter . The EIIa promoter drives the expression of Cre recombinase early in embryogenesis [24] . As shown in Table 1 , breeding between wild type with EIIaCre+/− mice resulted in approximately 1∶1 ratio of LoxPshBCCIP−/−;EIIaCre+/− and LoxPshBCCIP−/−;EIIaCre−/− mice . However , breeding of LoxPshBCCIP+/+ with EIIaCre+/− mice resulted in a significantly smaller number of LoxPshBCCIP+/−;EIIaCre+/− than LoxPshBCCIP+/−;EIIaCre−/− newborns . In addition , the litter size ( 5 . 1 for founder line-4 or 6 . 6 for founder line-13 ) from the breeding between LoxPshBCCIP+/+ and EIIaCre+/− was significantly smaller than that of wild type ( LoxPshBCCIP−/− ) mice ( 10 . 3/litter ) . These data suggest that down-regulation of BCCIP causes embryonic lethality . Although there were significantly less Cre positive mice with this breeding scheme , it was noted that some Cre positive mice were viable . However , further analyses confirmed that some of these viable LoxPshBCCIP+/−;EIIaCre+/− newborn mice had lost the LoxBCCIPshRNA cassette ( data not shown ) . This suggests that the LoxBCCIPshRNA cassette in mice is subject to spontaneous loss . To confirm that BCCIP knockdown causes embryonic lethality , embryos from crosses between LoxPshBCCIP+/+-4 and EIIaCre+/− were analyzed at day E11 . 5 . As exemplified by Figure 1B–1D , among a total of seven embryos of the same litter , four ( labeled as No . 1–4 in Figure 1B ) were abnormal and three ( labeled as No . 5–7 in Figure 1B ) were normal . The abnormal embryos have the EIIaCre-positive genotype , while the normal embryos are EIIaCre-negative ( Figure 1C ) . As expected , the expression of BCCIP in the abnormal embryos was clearly down-regulated , while the healthy embryos expressed normal levels of BCCIP protein ( Figure 1D ) . Analysis of Cre-dependent conditional knockdown embryos derived from another founder line ( LoxPshBCCIP+/+-13 ) is shown in Figure S2 . Altogether , these data suggest that down-regulation of BCCIP during embryogenesis causes embryonic lethality prior to day E11 . 5 . Figure 1 , Figure S1 , and Figure S2 also illustrate that our conditional knockdown strategy indeed achieved the anticipated down-regulation of BCCIP upon expression of Cre-recombinase in the conditional transgenic mice . Given our observations that BCCIP down-regulation causes developmental arrest at day E11 . 5 , we anticipate the anomaly in embryonic development initiates a few days prior . To define the precise timeframe for the effects of BCCIP knockdown in early embryogenesis , we analyzed embryos at different timepoints , including embryonic days E6 . 5 , E7 . 5 , and E8 . 5 . As shown in Figure 2A–2C , wild type embryos were well developed during this period . By E6 . 5 , wild-type embryos ( Figure 2A ) displayed normal growth and egg cylinder elongation , extraembryonic and embryonic ectoderm and pro-amniotic cavities . By day E7 . 5 ( Figure 2B ) , wild-type embryos underwent gastrulation; the amniotic cavity was sealed off and three distinct cavities ( amniotic cavity , exocoelom , and ectoplacetal cleft ) were well developed . The neural plate , a developed notochord , a confined head and tail folds were visible at day E8 . 5 in a wild type embryo ( Figure 2C ) . The mid-trunk region remained apparently attached to yolk sac , which is consistent with normal mouse embryo development [25] , [26] . However , in the BCCIP knockdown embryos , there was a significantly delayed and abnormally developed embryos as evidenced by the mass size of the embryonic tissues at day E6 . 5 ( Figure 2D ) . At day E7 . 5 and E8 . 5 ( Figure 2E and 2F ) , the BCCIP knockdown embryos were developmentally retarded . There was no apparent formation of amniotic cavity , and no mesoderm differentiation at day E7 . 5 ( Figure 2E ) . Also , development of the neural plate and notochord was not evident at day E8 . 5 ( Figure 2F ) . These morphological observations suggest that the developmental defects caused by BCCIP knockdown in the analyzed mouse embryos are likely initiated before day E6 . 5 . During mouse embryogenesis , mesoderm development occurs around day E6 . 5 . Brachyury can be used as a marker of the primitive streak , nascent mesoderm , the node and notochord [27]–[29] . To confirm that the developmental delay occurs prior to day E6 . 5 , we examined the expression of the Brachyury protein by immunohistochemistry ( IHC ) at day ∼E6 . 5 . As shown in Figure S3A , the Brachyury expression was readily detectable in the primitive streak and mesoderm in wild-type embryos , which is a sign of mesoderm differentiation ( Figure S3A ) . However , in BCCIP deficient embryos of the same age , little Brachyury expression was detected ( Figure S3B ) . This confirms that the embryonic development retardation in BCCIP deficient mice was likely initiated prior to day E6 . 5 . As shown in Figure 2 and Figure S3 , the BCCIP knockdown embryos display histological development defects around day ∼E6 . 5 . Ki67 expression is commonly regarded as a proliferation marker . To determine whether cellular proliferation is impaired in BCCIP deficient embryos at about the same time , Ki67 expression in embryonic tissues was assessed by IHC ( Figure 3A ) . A proliferative index , defined as the ratio of the number of Ki67-positive nuclei in the embryo tissue preparations over the total nuclei number , was determined ( Figure 3B ) . As shown in Figure 3A and 3B , there was only a slight reduction of Ki67 expression in BCCIP knockdown embryos when compared to wild type embryos at day E6 . 5 . However at day E7 . 5 , the proliferation index was significantly reduced , from ∼80% in wild type to ∼11% in the BCCIP knockdown embryos ( Figure 3B ) . To confirm the cell proliferation assessment data , incorporation of 5-bromo-2′-deoxyuridine ( BrdU ) into DNA during the S phase of the cell cycle was measured at days E6 . 5 and E7 . 5 . As shown in Figure 3C and 3D , there was little difference in labeling index at day E6 . 5 between wild type and BCCIP knockdown embryos . However at day E7 . 5 , wild type embryos had 52% BrdU-positive nuclear staining compared to 10% in BCCIP knockdown embryos ( Figure 3D ) . These results strongly suggest that the proliferation defects of BCCIP deficient embryos are initiated by day E6 . 5 , consistent with the data from histological analyses ( Figure 2 and Figure S3 ) . To determine if the growth defect of BCCIP deficient embryos is associated with an excessive level of programmed cell death , embryo serial tissue sections at days E6 . 5 and E7 . 5 were analyzed by terminal deoxynucleotidyl transferase ( TdT ) -mediated dUTP nick end labeling assay ( TUNEL ) and anti-cleaved caspase-3 staining . At day E6 . 5 , there was little apoptotic and caspase-3-positive cells in the wild type and the BCCIP deficient embryos ( Figure 4 ) . However , at day E7 . 5 , clear apoptotic signals were detected in BCCIP deficient but not in wild type embryos ( Figure 4 ) . This indicates that programmed cell death in BCCIP knockdown embryos is increased as early as day E7 . 5 , which is in strong agreement with the impaired embryo development around this time as shown in Figure 2 . In early mouse embryogenesis , prior to the implantation , the inner cell mass ( ICM ) inside the blastocysts forms one of the earliest structures of embryos , and eventually give rise to the definitive structures of the embryo . In vitro Blastocyst outgrowth offers an opportunity to observe ICM growth and to assess the early post-implantational development . To assess the role of BCCIP in embryonic development prior to day E6 . 5 , LoxPshBCCIP+/+ mice were bred with EIIaCre+/+ mice ( breeding between LoxPshBCCIP+/+ and with EIIaCre−/− as the control ) . Blastocysts were collected by uterine flushing at day E3 . 5 , and cultured in vitro . The growth of ICM from the blastocysts was monitored daily while in culture . The numbers of blastocysts analyzed are summarized in Table S1 . Among 71 BCCIP knockdown blastocysts , 28 ( or 39% ) successfully attached to the culture dish , which was a slightly lower frequency than the control blastocysts ( 28/58 , or 48% ) . For the attached blastocysts , there was little morphological difference between control and BCCIP deficient blastocysts after one day in culture ( equivalent to day E4 . 5 in vivo ) . Figure 5A illustrates the representative growth morphology of the blastocysts in culture at days 2 , 4 , and 5 . Normally , the blastocysts hatch from the zona pellucida around day 1 to 2 in culture . As shown in Figure 5A , there was little apparent morphological difference at day 2 shortly after blastocysts hatching in vitro . After day 2 in culture , growth of the ICM from the BCCIP deficient blastocysts was clearly defective , although the difference in trophoblast giant cell growth between control and BCCIP deficient cells appears to be less significant ( Figure 5A ) . To quantify the growth of the ICM in vitro , the relative areas of ICM were calculated using the ImageJ program . As shown in Figure 5B , the growth of BCCIP deficient ICM was significantly impaired when compared with wild type blastocysts starting at day 3 ( equivalent to day 6 . 5 in vivo ) in culture . These results imply that BCCIP defects affect the ICM growth , which is consistent with the in vivo observation of growth retardation in BCCIP knockdown embryos as described in Figure 2 . The in vivo and in vitro data above have shown growth retardation in BCCIP knockdown embryos , suggesting that the mouse BCCIP is essential for cell proliferation and growth . To investigate the underlying mechanism ( s ) , we used the MEF4-LoxPshBCCIP cells . At passage 1 , the MEF4-LoxPshBCCIP cells were infected with retroviruses expressing Cre-recombinase to reconstitute the functional U6 promoter in order to achieve BCCIP knockdown . The control groups were infected with retrovirus expressing the YFP . As shown in Figure 6A , the MEF4-LoxPshBCCIP cells infected with Cre-virus grew slower than those infected with YFP expressing virus ( Control ) . This slowed growth of BCCIP knockdown MEF cells is coincident with a reduced level of PCNA ( a proliferation marker ) and increased level of p21 ( Figure 6B ) . We also observed an increase of Ser-15-phosphorylated p53 in the BCCIP knockdown MEFs ( Figure 6B ) , suggesting a spontaneous activation of DNA damage signaling in the BCCIP deficient cells . We further assessed the roles of mouse BCCIP in DNA damage sensitivity . Because of poor colony formation by the primary MEF culture , a clonogenic survival assay was technically infeasible . Thus , we performed growth inhibition assay to assess the MEF's response to modest dose of irradiation . As shown in Figure 7A , BCCIP knockdown cells exhibited greater growth inhibition by irradiation compared to control MEFs . Irradiation with 1–4 Gy of γ-rays showed a similar trend of inhibition of cell growth ( Figure S4 ) . Under physiological conditions , without exogenous DNA damage , HR is thought to play a major role in relieving replication stress . We treated the MEF cells with low concentrations of alphidicolin ( APH ) . After washing off the APH , cells were immediately incubated with Bromodeoxyuridine ( BrdU ) in APH-free medium . At various time points , the fraction of cells with BrdU incorporation was scored after immunofluorescent staining ( see Materials and Methods ) , which reflects the recovery from replication blockage . As show in Figure 7B , when normalized to the un-treated cells , the re-incorporation of BrdU was less efficient among BCCIP knockdown cells than the control MEFs , reflecting a delayed recovery from replication stress . Figure 7C shows representative fields of BrdU-labeled cells . Together , these data suggest that the BCCIP deficient cells are not only more sensitive to DNA damage but also less efficient to recover from replication stress than control cells . To directly assess the DSB repair capability , we measured the kinetics of γH2AX removal following irradiation . As shown in Figure 8A , 15 min after irradiation , all cells have a similar level of γH2AX . However , at 4 and 8 hours after irradiation , the BCCIP knockdown MEFs have significantly more γH2AX nuclear foci than the control MEF cells . Similarly , the fractions of cells with 5 or more γH2AX foci were higher in the BCCIP knockdown cells than the controls ( Figure 8B ) . Figure S5 shows representative γH2AX foci at different times after irradiation . These observations indicate that the control cells remove DSBs more efficiently than BCCIP knockdown MEFs , and that down regulation of BCCIP impairs DSB repair after irradiation . In addition , an alkaline comet assay revealed more residual DNA damage at 4 hours after irradiation in the BCCIP deficient MEFs when compared to control cells ( Figure 8C and 8D ) . These data strongly suggest an impaired repair capability in the BCCIP deficient cells , consistent with the slower growth of the BCCIP knockdown MEFs after irradiation ( Figure 7A ) . Because human RAD51 focus formation is associated with BCCIP [10] , [30] , we further assessed the potential role of BCCIP in mouse Rad51 response to radiation . As shown in Figure 9A , BCCIP deficiency resulted in a significant reduction of Rad51 foci in response to radiation . Furthermore , there was a reduction of Rad51 protein level in BCCIP deficient cells compared to control cells ( Figure 9C ) . This is consistent with a role of BCCIP in HR dependent DSB repair . The human BCCIP interacts with BRCA2 , and BCCIP deficiency reduces endogenous level of Rad51 ( Figure 9 ) . Both BRCA2 and Rad51 are key proteins involved in HR . Under physiological condition , a key function of HR is to resolve stalled replication forks [2] , [3] , and impaired HR would cause spontaneous structural chromosome alterations . Thus , we investigated whether BCCIP deficiency would cause spontaneous chromosome abnormalities . First , Giemsa-stained chromosome metaphase spreads were prepared from control and BCCIP-deficient MEFs . As represented in Figure 10A–10B , we observed two types of spontaneous chromatid aberrations in BCCIP knockdown MEFs: single chromatid breaks with un-paired chromatid fragments , and SCU ( sister chromatid union ) . We also observed some paired sister chromatid fragments ( pSCF ) that may be companions with SCU ( when the SCU is formed by fusion of telomere-less broken chromatid arms ) . Figure 10G summarizes the spontaneous frequencies of the types of chromosome abnormalities caused by BCCIP-deficiency . BCCIP-deficiency results in a 3 . 5-fold increase on single chromatid breaks , and 3 . 4-fold increase in occurrence of paired sister chromatid fragments . The most dramatic increase is in SCU occurrence . While there was little SCU in the control cells , there was ∼20-fold increase of SCUs in BCCIP knockdown cells . Because the BCCIP knockdown MEF population has more polyploid cells than control MEF , the frequencies of chromosome abnormalities were normalized to the number of chromosomes . The frequency of abnormality , normalized to number of metaphase cells , can be found in Figure S6 . The chromatid break is indicative of failed restart of collapsed replication forks , which generates one-ended DSBs . We further measured whether BCCIP deficiency causes increased sister chromatid exchange ( SCE ) , which is seen in Bloom syndrome and several genetic disorder related to replication stress [31]–[33] . Consistent with the results from Giemsa-stained chromosome metaphase spreads , we observed the induction of SCUs alone with chromatid breaks in BCCIP-deficient cells ( Figure 10C and 10D ) . However , the increase of SCE in BCCIP deficient cells is modest ( Figure 10H ) . This may reflect a potential role of BCCIP in supporting Rad51-dependent strand invasion during the restart of replication forks ( see Discussion for details ) , which is consistent with the observation that BCCIP deficiency causes Rad51 down regulation ( Figure 9 ) . The formation of SCUs is a unique phenotype in BCCIP deficient cells . To our best knowledge , the earliest literature that described this form of chromatid alteration was in 1938 with Drosophila by Kaufmann [34] , but has been rarely described since then . We reasoned that SCUs may be produced by two mechanisms: telomere fusion between the sister chromatids; or the re-ligation of the broken sister chromatids . Although the second possibility is suggested by the presence of paired chromatid fragments in the BCCIP deficient cells , telomere FISH was performed to distinguish these possibilities . As can be seen in Figure 10E and 10F , the SCUs were associated with loss of telomere signals and were not caused by telomere fusion . We often observed paired telomere signals from the acentromeric chromatid fragments in the same cells with SCUs . These observations suggest SCU as a consequence of ligation of two broken telomere-less sister chromatids , and unlikely a fusion after telomere erosion . With the same telomere FISH experiments , we observed induction of chromatid breaks with single sister chromatid fragment ( sSCF ) in BCCIP deficient cells ( Figure 10F ) . We also found an increase in percentage of chromatids that have lost telomere FISH signals ( Figure 10I ) . Altogether , these data ( Figure 10 ) strongly suggest that BCCIP deficiency causes spontaneous chromatid aberrations associated with replication . We further analyzed chromosome abnormalities at 2 and 8 hours after 2 Gy of γ-irradiation . Again , there was a significant increase of spontaneous chromosome abnormalities , including SCU ( Figure 11 ) . At 2 hours after the irradiation , SCU frequency is significantly higher in the BCCIP knockdown cells than the control cells , but the other forms of damages are not significantly different between the BCCIP knockdown and control cells . The control cells exhibited significantly less chromosome abnormalities at 8 hours , than at 2 hours after irradiation , indicating repair of DNA damages associated with these forms of abnormalities . However , there remained a significantly higher level of chromosome abnormalities in the BCCIP knockdown cells than the control cells at 8 hours . Noticeably , the SCU level at 8 hours remains as high as at 2 hours , suggesting that the BCCIP deficient cells repaired little damages leading to SCU during the 2–8 hours following irradiation . These data support the notion that BCCIP is not only required to repair different forms of DNA damages but also has a significant role in protecting the cells against SCU . Because BCCIP deficiency spontaneously activates p53 Ser-15 phosphorylation in the MEFs ( Figure 6B ) , and it has been shown that p53 deficiency can partially delay the embryonic lethality conveyed by BRCA1 and BRCA2 deficiency in mice [35] , we measured the in vitro growth rates of the p53 mutant and wild type BCCIP deficient MEFs . As shown in Figure S7 , deletion of p53 can only partially rescue the growth retardation of BCCIP deficient cells . Next we asked whether p53 deficiency can completely rescue the embryonic lethality in BCCIP deficient mice . We used three different strategies to breed the constitutive p53 null mice originally generated by Jacks et al [36] . Table 2 shows the distribution of genotypes among viable newborns after breeding: 1 ) between ( p53+/+;LoxPshBCCIP+/+;EIIaCre−/− ) and ( p53+/+; LoxPshBCCIP−/−;EIIaCre+/− ) , 2 ) between ( p53+/−; LoxPshBCCIP +/+;EIIaCre−/− ) and ( p53+/−; LoxPshBCCIP −/−;EIIaCre+/− ) , and between ( p53+/−; LoxPshBCCIP +/−;EIIaCre−/− ) and ( p53+/−; LoxPshBCCIP −/−;EIIaCre+/− ) . As shown in Table 2 ( see Table S2 for detailed breeding data ) , p53 deletion retain approximate 1∶1 ratio between EIIaCre ( +/− ) and EIIaCre ( −/− ) mice in LoxPshBCCIP ( −/− ) background . The EIIaCre ( +/− ) and EIIaCre ( −/− ) ratio was significantly less than 1 ( 16∶86 ) in p53 wild type mice , and this reduced ratio was not increased in p53 deficient or p53 heterozygous background ( 0∶24 and 11∶72 respectively ) . These data suggest that p53 deletion failed to completely rescue the embryonic lethality induced by BCCIP knockdown , suggesting that DNA damage activated p53 signaling cannot fully account for the embryonic death completely .
In addition to DSB repair , a major function of the HR machinery is to preserve genomic integrity via resolving replication blockage to reduce replication stress , which is loosely defined as the inefficient progression or stalling of replication forks [3] , [37] , [38] . During replication , replication forks may be stalled by encountering single-strand breaks or damaged nucleotides that are not by-passed by DNA translesion synthesis . This often produces a one-ended DSB , which can be processed to yield a single stranded 3′-end to initiate a strand invasion and form a single Holliday junction at the stalled replication fork . After branch migration ( or replication fork regression ) and resolution of the Holliday junction , the stalled replication fork can be re-started . It is believed that many factors of the HR pathway , including BRCA2 and associated proteins , are required in this process . Replication stress is often manifested by excessive levels of spontaneous single-stranded DNA ( ssDNA ) , or DNA strand breaks . On the cytogenetic level , excessive level of chromatid breaks and SCEs is a signature of replication stress . It has been suggested that endogenous replication stress induced by HR defects may not be detected by the S-phase checkpoint machinery . Thus cells with excessive replication stress can enter mitosis to cause mitotic errors [37] . In a previous report , it was shown that BCCIP deficiency results in accumulation of spontaneous DNA strand breaks and single-stranded DNA in human cells [16] . In this study , we have observed an increase of spontaneous chromatid breaks and SCUs in BCCIP deficient cells ( Figure 10 ) , and impaired repair of radiation damages that lead to SCU formation ( Figure 11 ) . These results are consistent with a role of BCCIP in suppressing replication stress and repair of DNA damage . We have observed a significant spontaneous increase in sister chromatid breaks ( 3 . 5-fold ) yet a modest increase of SCE ( ∼1 . 5 fold ) in BCCIP deficient cells ( Figure 10 ) . These abnormalities have often been used as markers for genomic instability . Although the molecular mechanisms for SCE formation are complex , it is generally believed that the 3′-end of the one-ended DSB of the stalled replication fork initiates the process with strand invasion [31] . Once strand invasion is initiated to form the Holliday junction , branch migration ( or fork regression ) and resolution of the Holliday junction would produce a SCE ( Figure 12A ) . Therefore , factors that increase the production of one-ended DSBs ( e . g . excessive levels of SSBs or inability to carry out translesion synthesis ) have the potential to stimulate SCE [31] . Additionally , deficiencies in proteins involved in branch migration of the Holliday junction ( e . g . BLM and RecQL5 ) may favor SCE upon Holliday Junction resolution [31]–[33] . On the other hand , defects in proteins involved in strand invasion may have different consequences on SCE . It has been shown that BRCA2 and RAD51 defects do not significantly increase spontaneous SCE in mammalian cells [31] , [39]–[41] . Since strand invasion is a critical step to produce SCE , defective RAD51 and its accessory factors may reduce or only modestly increase SCE due to ineffective strand invasion even in the context of excessive one-ended DSB and replication stress . As a consequence , this would significantly increase chromatid breaks ( Figure 12B ) . In this study , we observed reduced basal level of mouse Rad51 protein and focus formation in the BCCIP deficient cells ( Figure 9 ) . This observation is consistent with the increase in chromatid breaks and formation of paired sister chromatids in BCCIP-deficient cells and the reduction of RAD51 focus formation in BCCIP deficient human cells [10] , [30] . A possible mechanism for the formation single chromatid breaks is illustrated in Figure 12B . A question is how BCCIP deficiency may cause reduced Rad51 protein level . It is known that Rad51 preferably expresses in S phase cells . A tempting explanation is that reduction of S-phase cell fraction may reduce the overall Rad51 level in the BCCIP deficient cell population . However , this is unlikely the case because BCCIP deficiency causes replication stress but did not cause overall reduction of S-phase fraction ( [11] and data not shown ) . Although we cannot rule out the possibility that Rad51 protein stability is altered in BCCIP deficient MEFs , we found that the BCCIP deficient MEF cells had reduced Rad51 mRNA level based on RT-PCR analysis ( data not shown ) , suggesting that a down-regulated Rad51 transcription may contribute to the Rad51 protein level . A characteristic structural chromosome alteration in the BCCIP deficient MEFs is SCU , which is not only induced spontaneously but also remains high 2–8 hours after irradiation ( Figure 10 and Figure 11 ) . The telomere FISH experiments have suggested that SCUs are likely the consequence of ligation between two broken sister chromatids . We envision that SCU may be caused by the following scenario ( Figure 12C ) . When one-ended DSB resection and subsequent strand invasion fails , an excessive level of single sister chromatid breaks and further collapse of the replication fork result in three one-ended DSBs ( as shown in Figure 12C ) . Then , SCU may occur upon re-ligation of the sister chromatid DSB ends . The proximate DNA fragment may resume replication due to the presence of multiple replication origin sites . This produces paired chromatid fragments . However , we would like to emphasize that alternative mechanisms to produce SCU are possible . For example , late S-phase cells with failed resolution of HR intermediates and/or replication termination structures may form DSB on sister chromatids , thus SCU . Although erosion of telomeres in telomerase deficient cells may expose the chromtid ends to form SCU , this scenario is unlikely to be the cause of SCU in BCCIP deficient MEF cells , because the BCCIP deficient cells were cultured in vitro for only a few passages . It would be interesting to investigate whether eroded telomere ends can form SCU in Tert deficient cells after long-term culture . Nevertheless , the SCUs will likely form chromatin bridges between daughter nuclei at anaphase . It is expected that this form of structural abnormality will result in chromosome segregation errors and numerical chromosome instability in daughter cells . The phenotypes of BCCIP deficient embryos are consistent with BCCIP's orthologs in lower eukaryotes , and its interaction partner BRCA2 [35] . Several BRCA2 knockout mouse models have been developed . Depending on the specific regions deleted in the knockout model , the embryonic phenotype of BRCA2 mutant mice varies [35] . However , most mouse models with large deletions on BRCA2 produce embryonic lethality [35] . In this study , we have established a LoxP-Cre based conditional BCCIP knockdown mouse model . Using this model , we have shown that the mouse BCCIP gene is essential for embryonic development . Although many mechanisms may contribute to embryonic abnormality of BCCIP-deficient mice , the accumulation of spontaneous DNA damage , excessive replication stress , and formation of lethal chromatid aberrations in BCCIP deficient cells are considered the major initiating factors . Down regulation of BCCIP has been shown to cause spontaneous DNA damage in human cells [16] . In this study , we observed spontaneous activation of p53 together with up-regulation of p21 in BCCIP deficient MEFs ( Figure 6B ) , and increased cell death through apoptosis at day E7 . 5 follows reduction in cell proliferation ( Figure 5 ) . These observations are consistent with the scenario that BCCIP deficiency leads to accumulation of spontaneous DNA damage , thus growth inhibition and cell death , which lead to embryonic lethality . However , the accumulation of spontaneous DNA damage along with activation of p53 may not fully account for embryo lethality , as the p53 deletion did not completely rescue the embryonic lethality of BCCIP deficiency despite that it can partially rescue the growth retardation of BCCIP deficient MEFs in vitro ( Figure S7 ) . Second , BCCIP deficiency may inhibit proliferation by disrupting cell division in mitosis . We found that BCCIP-deficient cells had significantly increased levels of spontaneous chromatid breaks and SCUs at metaphase ( Figure 10 ) . It is anticipated that the chromatid breaks will cause a net loss of chromosomal materials after mitosis , and the SCUs will evolve into chromatid bridges at anaphase and telophase to disrupt chromosome segregation , both scenarios are potentially lethal to the cells and can contribute to the embryo development defects . The conditional knockdown approach offers advantages over conventional knockout approach . It may avoid interference with the overlapping genes . Second , while the conventional knockout approach would only offer either homozygous or heterozygous gene ablation , the knockdown approach may grant us the ability of mimicking abnormal protein expression that might occur in human diseases . Down regulation of BCCIP has been shown in cancers [7] , [9] , [13] , [14] . Considering the strong genomic instability phenotype in BCCIP deficient cells and the multiple functions of BCCIP [10] , [11] , [15]–[18] . It is likely that BCCIP deficiency may contribute to tumorigenesis in mice . Because the EIIa-Cre mediated BCCIP knockdown causes embryonic lethality , tissue specific conditional knockdown is in process to address whether BCCIP down-regulation contribute to tumorigenesis . In summary , our study suggests a critical role of mouse BCCIP gene in maintaining genomic stability and embryonic development . The formation of characteristic sister chromatid union in BCCIP deficient cells may reflect a unique molecular function of BCCIP in resolving stalled replication forks , and may contribute significantly to embryonic development defects .
The animal works presented in this study were approved by Institutional Animal Use and Care Committee of Robert Wood Johnson Medical School-UMDNJ . We follow our institutional guideline regarding to animal welfare issues . The pBS/U6-pLoxPneo vector [23] was kindly provided by Dr . Chuxia Deng ( National Institute of Diabetes and Digestive and Kidney Disease , NIH ) . A pair of mouse BCCIP specific oligonucleotide ( 5′-GGATGAAGATGAGATCTTTGGTTCAAGAGACCAAAGATCTCATC TTCATCCTTTTTT-3′ and 5′-AATTAAAAAAGGATGAAGATGAGATCTTTGGTCTCTTGAACCAAAGATCTCATCTTCATCCGGCC-3′ ) were annealed , and then ligated into the pBS/U6-pLoxPneo vector digested with ApaI and EcoRI . This results in the conditional mouse BCCIP knockdown vector designated pBS/U6-pLoxPneo-shBCCIP . The effectiveness of this vector to knockdown mouse BCCIP was confirmed by stably transfecting vectors into mouse NIH3T3 cells , and then transiently expressing the Cre recombinase in the cells . The conditional BCCIP knockdown vector ( pBS/U6-pLoxPneo-shBCCIP ) was digested by KpnI and NotI . The linearized 2 . 3 kb DNA fragment containing the conditional LoxPshRNA expression cassette was injected into pronuclei of fertilized oocytes isolated from superovulated FVB/N mice . Then the injected oocytes were implanted into pseudopregnant recipient females . Genomic DNA was extracted from tail biopsies of the resulting litters and analyzed by PCR and Southern blot . Among the 27 mice obtained from the injections , 7 were found to be positive for the LoxPshBCCIP transgene cassette . The U6-LoxP-shBCCIP positive mice were crossbred with FVB/N wild type mice to identify the mouse lines capable of germline transmission . Through this procedure , two founder lines with high germline transmission were identified . They were designated as LoxPshBCCIP-4 and LoxPshBCCIP-13 , and both were successfully bred into homozygsity ( LoxPshBCCIP+/+ ) . By breeding with wild type mice , the homozygous transgenic mice ( LoxPshBCCIP+/+ ) is distinguished from heterozygous mice ( LoxPshBCCIP+/− ) because the homozygous transgenic mice are able to produce 100% of LoxPshBCCIP positive newborns while the heterozygous mice ( LoxPshBCCIP+/− ) can produce only 50% of LoxPshBCCIP positive mice . The PCR primer pairs used for genotyping were: 5′-TCTAGAACTAGTGGATCCGAC -3′ , and 5′-TCGTATAGCATACATTATACG-3′ . The probe used for Southern blot was generated by a PCR amplification of the conditional knockdown vector using the following primers: 5′-ATTGAACAAGATGGATTGCACGCA , and 5′-TCAGAAGAACTCGTCAAG AAGG-3′ . The homozygous FVB/N-Tg ( EIIaCre+/+ ) C5379Lmgd/J mice ( Lakso , 1996 ) , were purchased from Jackson Laboratory ( stock number: 003724 ) , and crossed with wild type FVB/N mice to obtain EIIaCre+/− heterozygous mice . Then the LoxPshBCCIP+/+ homozygous mice were bred with the EIIa-Cre+/− heterozygous mice . Theoretically , this will generate offspring with two genotypes: [LoxPshBCCIP+/−;EIIaCre+/−] with BCCIP knockdown , and [LoxPshBCCIP+/−; EIIaCre−/−] as a control at a 1∶1 ratio . If the knockdown of BCCIP is lethal during embryogenesis , reduced newborn ratio of [LoxPshBCCIP+/−; EIIaCre+/−] to [LoxPshBCCIP+/−; EIIaCre−/−] is anticipated . The PCR primers to genotype EIIaCre were 5′CCTGTTTTGCACGTTCACCG3′ and 5′ATGCTTCTGTCCGTTTGCCG3′ , which results in a PCR product of ∼270 bp . The animal works were approved by Institutional Animal Use and Care Committee of Robert Wood Johnson Medical School . To generate rabbit anti-mouse BCCIP antibodies , mouse cDNA coding for C-terminal 292aa was cloned into pET28 vector ( Novagen , Madison , WI ) . Recombinant ( 6×His ) -tagged mouse BCCIP protein was expressed and purified with BL21 ( DE3 ) cells , and the GST-mouse BCCIP protein was expressed and purified in BL21 cells using pGEX vector as previously described [42] , [43] . The HIS-tagged BCCIP was injected into rabbits to produce polyclonal antibodies , and GST-mouse BCCIP was used for affinity purification of polyclonal anti-BCCIP antibodies . Anti- PCNA ( PC-10 ) , p21 ( F-5 ) , p53 ( FL-393 ) , and c-myc monoclonal antibody were purchased from Santa Cruz Biotechnology ( Santa Cruz , CA ) . Anti- γH2AX , phospho-p53 ( Ser15 ) and anti-cleaved caspase-3 antibodies from Cell Signaling ( Danvers , MA ) ; anti-pericentrin antibody from Covance Research Products Inc ( Berkeley , CA ) , anti-γ tubulin antibody from Sigma ( St , Louis , MO ) , and anti-Brachyury and anti-Ki67 from Abcam ( Cambridge , MA ) . Western blots were performed with procedures as described previously [7] , [11] , [15] , [16] , [18] , [44] . Uteri from female mice were isolated at days E6 . 5–8 . 5 , the individual decidual swellings were isolated transversely according to the methods of Smith ( Smith , 1985 ) , rinsed with cold PBS , fixed overnight in 4% paraformaldehyde at 4°C , then embedded in paraffin . Serials of 5 µm sections were cut and stained with hemotoxylin and eosin . Anti-BCCIP polyclonal antibody ( 1∶100 ) , anti-Ki67 polyclonal antibody ( 1∶300 ) , anti-cleaved caspase3 polyclonal antibody ( 1∶100 ) , and anti-Brachyury ( 1∶100 ) antibodies were used for immuno-histochemical staining of the corresponding proteins using previously developed protocols [20] . To measure DNA synthesis in embryo mouse tissues , BrdU ( 100 µg/g of body weight ) was intraperitoneally injected into pregnant female mice . One hour later , the entire uteri were removed , and the individual decidual swellings were isolated , fixed in 4% paraformaldehyde at 4°C overnight , embedded in paraffin , and sectioned ( 5 µm ) . To stain incorporated BrdU , the sections were de-paraffinized , treated with 2 N HCl for 30 min at 37°C , incubated with anti-BrdU monoclonal antibody ( Becton Dickinson , Franklin Lakes , NJ ) at a 1∶500 dilution for 2 hr at 37°C , and then incubated with anti-mouse-HRP secondary antibody for 1 hr . 3 , 3′-Diaminobenzine tetrahydrochloride hydrate ( DAB ) color developed . BrdU positive cells are visualized by their brown color with DAB , and BrdU negative cells display blue color by hematoxylin . Paraffin embedded tissue sections ( 5 µm ) were used to detect apoptotic cells using DeadEnd Fluorometric TUNEL System ( Promega , Madison , WI ) . Briefly , sections were rinsed 3 times with distilled H2O , once in PBS , and permeabilized with 200 µg/ml of Proteinase K in PBS for 15 min . The permeabilized sections were incubated with equilibration buffer for 10 min at room temperature . DNA strand-break labeling and colorization were performed according to the manufacturer recommended procedures , mounted with VECTASHIELD fluorescent mounting media with DAPI , and the results were recorded with fluorescent microscope . Homozygous BCCIP female FVB/NJ mice ( 3 . 5–4 week old ) were given 5 IU of pregnant mare's serum gonadotropin by intraperitoneal injection between 3–4 pm . At 46–48 h post-PMSG injection , they were treated with 5 . 0 IU of human chorionic gonadotrophin ( hCG ) by intraperitoneal injection , and then mated with wild type and EIIaCre+/+ male mice individually . Next morning , the female mice with positive mating-plugs were separated from male mice . At embryo day 3 . 5 ( E3 . 5 ) , blastocysts were collected by flushing the uteri of female mice , and individually cultured for 5 days in 24-well plates in ES cell culture media without leukemia inhibitory factor ( Liu , 1996 , Suzuki , 1997 ) with 5% CO2 at 37°C . The growth of the cultured blastocysts was monitored daily and photographed . Primary mouse embryo fibroblast ( MEF ) cells were generated from day 13 . 5–14 . 5 embryos of LoxPshBCCIP+/+ female mice ( founder line 4 ) mated with LoxPshBCCIP+/+ homozygous male mice according to the protocols by Hertzog [45] . The MEF cells were counted and plated into 10 cm dishes at a density of 0 . 5–1×105 per cm2 in DMEM medium containing 10% FBS , and incubated at 37°C with 5% CO2 . After 24 hr , the medium , cellular debris , and any unattached cells were removed . The attached MEF cells were designated as passage 0 . After 2–3 days of culture , each 10 cm plate of cells was split into 3–5 of 10 cm plates , and the split cultures were then designated as MEF cell passage 1 . All in vitro experiments , except specifically noted , were carried out with the first passage MEF cells . A retroviral packaging cell line specific for mouse cell lines ( φEco ) , and mouse embryo fibroblast cells ( MEF ) , were cultured in DMEM medium supplement with 10% fetal bovine serum , 100 U/ml of penicillin , 100 µg/ml of streptomycin , and 1% of glutamine . The φEco cells were transfected with pLXSP-YFP and pLXSP-myc-Cre retrovirus vector separately . Forty eight hours after transfection , transfected cells were selected by puromycin ( 1 µg/ml ) for 2 days . Then the cells were grown to 80–90% confluence in regular culture medium . Virus suspensions were collected , filtered with 0 . 45 sterile syringe filters , and mixed with 8 µg/ml of polybrene ( Sigma , St , Louis , MO ) . The MEF cells were infected 3-times with the virus during a 2 day period , and then selected with 2 . 5 µg/ml puromycin for 2 days prior to phenotype analyses . For cell growth analysis , cells were counted using a Coulter counter ( Beckman Coulter , Fullerton , CA ) . Cells were initially seeded onto 6 cm dish at a density of 0 . 1×106 per dish , then cell number was determined daily for the next 5 days after the initial plating . Triplicates for each group at each time point were used in the measurements . To assess the ability of MEFs to recover from replication blockage , 0 . 1×106 MEF cells were grown on 18 mm cover slides in 6-well plate . Cells were treated with 0 . 4 µM APH in DMEM media for 37°C for 30 hours . After removing APH containing media by rinsing with sterile PBS , the recovery of replication of was measured by measuring Bromodeoxyuridine ( BrdU ) incorporation . Briefly , BrdU was added to each well to a concentration of 10 µM and slides were fixed at 0 , 2 , 3 , 4 , and 5 hours after adding BrdU using 4% paraformaldehyde for 10 minutes at room temperature . The fixative was removed by washing the cover slides three times with 1× PBS . The slides in the wells were treated with 1 M HCl for 10 min in ice , 10 min at room temperature , and 40 min at 37°C to denature DNA . Acid was removed and neutralized by washing the cover slides three times with borate buffer ( pH 8 . 5 ) . Cover slides were then washed three times in PBS+ 0 . 05% Tween 20 [PBS/T20] , blocked with 1 ml of PBS/T20/2% normal goat serum at 37°C for 30 minutes . Cells were immuno- stained with mouse anti-BrdU antibody ( 1∶200 in 0 . 1 ml of PBS/T20/2% normal goat serum ) and incubating at room temperature for 1 hour or at 4°C overnight . The cells were washed three times with PBS+ 0 . 05% Tween-20 and stained with donkey anti-mouse Rhodamine conjugate diluted to 1∶500 in 0 . 1 ml PBS+ 0 . 05% Tween-20 with 3% BSA and incubated at room temperature for 1 hour . Cover-slides were washed three times with PBS/T20 , and mounted on glass slides using Vecta shield+DAPI mounting media . Slides were evaluated using immunofluorescent microscopy and the percentage of BrdU positive cells were counted by counting BrdU positive and DAPI stained cells on each slide . To prepare metaphase chromosome spreads ( Brown , 2000; Ko , 2008 ) , cells at 80–90% confluence were subcultured into fresh medium , and incubated at 37°C for 24 hours . Colcemid ( Sigma , St . Louis , MO ) was added at final concentration of 0 . 2 µg/ml and incubated at 37°C for 4 hours . Cells were trypsinized , and suspended in 75 mM KCl hypotonic solution at 37°C for 15 minutes , and then fixed in fresh 3∶1 methanol/acetic acid . After 3–4 times of additional fixation , suspended cells were dropped onto cold wet slides , allowed to dry at room temperature , and stained with 1% Giemsa . At least 50 metaphase cells were analyzed under 1000× magnification with microscope for each group . Gross chromosome aberrations were scored . Statistical analyses for frequency of aberrations were performed using t-test , and a P value of <0 . 05 was considered significant . The methods developed by Williams et al were used [46] , [47] . In brief , after the MEF cells were subcultured into fresh medium and cultured for 24 hours , 0 . 2 µg/ml Colcemid was added for 6 hours to accumulate mitotic cells . Cells were trypsinized with Trypsin-EDTA ( Gibco , Carlsbad , CA ) and suspended in 75 mM KCl hypotonic solution at 37°C for 15 minutes before fixation . After four times of repeated fixation in fresh 3∶1 methanol/acetic acid , cells were dropped onto cold slides and allowed to dry slowly in a humid slide box . A probe to telomeric DNA was prepared by synthesizing an oligomer having the sequence ( CCCTAA ) 7 and was labeled by terminal deoxynucleotidal transferase tailing ( Roche , Florence , SC ) with SpectrumRed-dUTP ( Vysis , Des Plaines , IL ) according to the manufacturer's instructions . A hybridization mixture containing 0 . 4 µg/ml probe DNA in 30% formamide and 2×SSC ( 1×SSC is 0 . 15 M NaCl , 0 . 015 M sodium citrate ) was applied to slides that had been denatured in 70% formamide , and 2× SSC at 70°C for five minutes . Following an overnight hybridization at 37°C in a moist chamber , the slides were washed in 2× SSC at 42°C ( 5 times , 15 min each ) twice , and then placed in PN Buffer ( 100 mM Na2HPO4 , 50 mM NaH2PO4 , 0 . 1%Triton X-100 ) at room temperature for 5 minutes and mounted in fluorescence mounting medium with DAPI . Metaphase cells examined with a Zeiss fluorescence microscope and images were captured with HAL100 camera . At least 20 metaphase cells were analyzed for each group . Chromosome aberrations ( breaks , fragments , and sister chromatid union ) were scored . Statistical analyses for frequency of aberrations were performed using t-test . The method developed by Wang et al . was modified [48] . The MEF cells were cultured with medium containing 10 µM bromodeoxyuridine ( BrdU ) for 24 hour and then cultured in growth medium for another 24 hour , and treated with 0 . 2 µg/ml of colcemid 6 h before collection . The harvested cells were treated with 75 mM KCl hypotonic solution at 37°C for 15 minutes , and fixed with fresh 3∶1 methanol/acetic acid . The cell suspension were dropped onto slides and air-dried . The slides were incubated with 10 µg/ml Hoechst 33258 in ddH2O for 20 min , and rinsed with MacIlvaine solution ( 164 mM Na2HPO4 , 16 mM citric acid pH 7 . 0 ) for three times . The slides were mounted in MacIlvaine solution , and exposed to UV light for 45 min . After washing with PBS for 3 times , the slides were incubated in 2× SSC ( 0 . 3 M NaCl , 0 . 03 M sodium citrate ) solution at 62°C for 1 hour , and then stained with 1% Giemsa solution at pH 6 . 8 for 20 min . Metaphase cells were examined with Olympus microscope and images were captured with PictureFrame . At least 20 metaphase cells were analyzed for each group . Statistic analyses for frequency of aberrations were performed using t-test . The heterozygous p53 knockout mice [36] were crossed with LoxPshBCCIP+/+-4 mouse and EIIaCre+/+ mouse respectively to generate p53+/−;LoxPshBCCIP+/− , and p53+/−;EIIaCre+/− mice . The PCR primers used to genotype p53 are: p53ex6F: 5′-GTATCCCGAGTATCTGGAAGACAG-3′ , p53neoF: 5′-GCCTTCTATCGCCTTCTTGACG-3′ , p53ex7RN: 5′-AAGGATAGGTCGGCGGTTCATGC-3′ . The same PCR primer pairs as described earlier in this report were used for BCCIPshRNA and EIIaCre genotyping . The p53+/−;LoxPshBCCIP+/+ mice were obtained by crossing p53+/−;LoxPshBCCIP+/− females with p53+/−;LoxPshBCCIP+/− males . The p53+/−;LoxPshBCCIP+/+ or p53+/−;LoxPshBCCIP+/− mice were crossed with p53+/−;EIIaCre+/− mice respectively . | BCCIP is a BRCA2- and p21-interacting protein . Studies with cell culture systems have suggested an essential role of BCCIP gene in homologous recombination and suppression of replication stress and have suggested that BCCIP defects causes mitotic errors . However , the in vivo function ( s ) of BCCIP and the mechanistic links between BCCIP's role in suppression of replication stress and mitotic errors are largely unknown . We generated transgenic mouse lines that conditionally express shRNA against the BCCIP , and we found an essential role of BCCIP in embryo development . We demonstrate that BCCIP deficiency causes the formation of a unique type of structural abnormality of chromosomes called sister chromatid union ( SCU ) . It has been noted in the past that impaired homologous recombination and resolution of stalled replication forks can have detrimental consequences in mitosis . However , the physical evidence for this link has not been fully identified . SCU is the product of ligation between sister chromatids , likely formed as a result of unsuccessful attempt ( s ) to resolve stalled replication forks . Because the SCU will progress into chromatin bridges at anaphase , resulting in mitosis errors , it likely constitutes one of the physical links between S-phase replication stress and mitotic errors . | [
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] | 2011 | Essential Roles of BCCIP in Mouse Embryonic Development and Structural Stability of Chromosomes |
Myotubularin is a lipid phosphatase implicated in endosomal trafficking in vitro , but with an unknown function in vivo . Mutations in myotubularin cause myotubular myopathy , a devastating congenital myopathy with unclear pathogenesis and no current therapies . Myotubular myopathy was the first described of a growing list of conditions caused by mutations in proteins implicated in membrane trafficking . To advance the understanding of myotubularin function and disease pathogenesis , we have created a zebrafish model of myotubular myopathy using morpholino antisense technology . Zebrafish with reduced levels of myotubularin have significantly impaired motor function and obvious histopathologic changes in their muscle . These changes include abnormally shaped and positioned nuclei and myofiber hypotrophy . These findings are consistent with those observed in the human disease . We demonstrate for the first time that myotubularin functions to regulate PI3P levels in a vertebrate in vivo , and that homologous myotubularin-related proteins can functionally compensate for the loss of myotubularin . Finally , we identify abnormalities in the tubulo-reticular network in muscle from myotubularin zebrafish morphants and correlate these changes with abnormalities in T-tubule organization in biopsies from patients with myotubular myopathy . In all , we have generated a new model of myotubular myopathy and employed this model to uncover a novel function for myotubularin and a new pathomechanism for the human disease that may explain the weakness associated with the condition ( defective excitation–contraction coupling ) . In addition , our findings of tubuloreticular abnormalities and defective excitation-contraction coupling mechanistically link myotubular myopathy with several other inherited muscle diseases , most notably those due to ryanodine receptor mutations . Based on our findings , we speculate that congenital myopathies , usually considered entities with similar clinical features but very disparate pathomechanisms , may at their root be disorders of calcium homeostasis .
Myotubular myopathy is a severe , X-linked congenital myopathy with onset in infancy [1] . It is characterized by profound neonatal hypotonia and skeletal muscle weakness . It is associated with substantial mortality , with approximately half of all affected boys dying in the first year of life [2] . Surviving children have significant morbidity associated with respiratory compromise and difficulties with ambulation . Currently there are no treatments or disease modifying therapies available for this condition . The condition is defined by characteristic changes observed on muscle biopsy [1] . Biopsies show muscle fiber hypotrophy and an abundance of fibers with large , centralized nuclei of unusual appearance . These nuclei are distinct in appearance from those observed in degenerative conditions like Duchenne muscular dystrophy , and are the defining pathologic features of a group of congenital myopathies called centronuclear myopathies [3] . Myotubular myopathy is caused by mutations in the myotubularin gene [4] . Over 200 mutations have been reported in the myotubularin gene , the majority of which result in loss of functional gene expression [1] . Myotubularin is the only gene associated with myotubular myopathy . It is the canonical member of a large family of homologous proteins called the myotubularin related proteins ( MTMRs ) [5] . Of interest is the fact that several MTMRs are mutated in human neurologic diseases , including mutation of MTMR14 in an autosomal form of centronuclear myopathy [6] . Myotubularin was originally characterized as a protein tyrosine phosphatase , but was subsequently found instead to function primarily as a lipid phosphatase [7] , [8] . It acts specifically to remove phosphates from the 3-position of phosphoinositide rings . As demonstrated in cell free biochemical assays [7] , [8] and with forced exogenous expression [9] , [10] , myotubularin converts phosphoinositide-3-phosphate ( PI3P ) to phosphoinositide phosphate ( PIP ) and phosphoinositide-3 , 5-bisphosphate ( PI3 , 5P2 ) to phosphoinositide-5-phosphate ( PI5P ) . Most recently , Cao and colleagues have demonstrated using RNAi in A431 cells that knockdown of myotubularin results in a 60–120% increase in PI3P levels , thus substantiating the requirement for myotubularin in the regulation of endogenous PI3P [11] . Increased PI3P levels have also been observed in yeast lacking the myotubularin homolog ymr1 [8] , [12] . As yet , however , this activity has not been directly examined in whole vertebrates or in specific organ systems , including muscle . The functional importance of myotubularin's phosphatase activity is assumed from the fact that missense mutations that alter critical amino acids in the phosphatase domain without affecting protein stability result in myotubular myopathy [1] . Phosphoinositides are implicated in myriad cellular functions , chief among them the regulation of membrane traffic and vesicle/organelle movement [13] . Because it acts to modify certain PI residues , myotubularin is assumed to function as a regulator of membrane traffic and in particular the movements of vesicles between endosomal compartments [14] , [15] . Overexpression of myotubularin in cell culture delays traffic out of the endosomal compartment and causes vacuole accumulation . However , as with myotubularin phosphatase activity , a role for myotubularin in the regulation of membrane traffic in vivo and specifically in skeletal muscle has yet to be determined . In addition , unlike with other myopathies due to altered membrane traffic ( examples include Danon Disease due to LAMP2 mutation [16] ) , myotubular myopathy is not characterized by the pathologic accumulation of vesicles . Many critical questions remain unanswered concerning myotubularin function and myotubular myopathy pathogenesis . These include whether myotubularin truly functions as a lipid phosphatase and regulator of membrane traffic in vivo . Furthermore , the relationship between the proposed functions of myotubularin and disease pathogenesis is not clear . The same is true with the association between the unique histologic appearance of the muscle in myotubular myopathy patient biopsies and the etiology of muscle weakness and hypotonia . The lack of knowledge concerning these fundamental issues is a significant barrier in the development of therapeutic strategies for the disease . A murine model of myotubular myopathy exists , generated by targeted mutagenesis [17] . It recapitulates the clinical and histopathologic features of the disease , thus confirming the association between myotubularin and myotubular myopathy . However , due in part to technical limitations with the murine system , it does not address many of the fundamental questions mentioned above . To begin answering these questions , and to develop a model system amenable to rapid testing of therapeutic strategies , we report here the development of a zebrafish model of myotubular myopathy . Using antisense morpholino technology , we generated zebrafish embryos with reduced myotubularin protein expression . These embryos have severely impaired motor function , muscle fiber atrophy and the presence of large , abnormally located nuclei . These findings are reminiscent of those seen in myotubular myopathy . We also demonstrate that loss of myotubularin causes increased PI3P levels in muscle , thus confirming for the first time that myotubularin functions as a lipid phosphatase in a vertebrate model system . Using RNA-mediated rescue experiments , we show that the homologous myotubularin-related genes MTMR1 and MTMR2 are able to functionally compensate for the loss of myotubularin . Lastly , and most significantly , we identify alterations in the T-tubule and sarcoplasmic reticular networks in morphant zebrafish muscle . We confirm that similar disorganization of the tubulo-reticular network is present in biopsy samples from patients with myotubular myopathy . In all , we have successfully created a zebrafish model of myotubular myopathy , and have used this model to both answer fundamental questions concerning myotubularin function and to uncover a novel mechanism to explain the pathogenesis of the disorder .
To study the function of myotubularin ( MTM1 ) in zebrafish , we employed antisense morpholinos to achieve functional gene knockdown . We first identified the zebrafish homolog of MTM1 using the Ensembl genome browser ( ENSDARG00000037560 ) . By bioinformatics and RT-PCR from zebrafish embryonic RNA , we found that MTM1 and 12 of 14 of the MTM1-related gene products ( MTMRs ) are expressed in the developing fish ( Figure S1 ) . We then designed morpholinos to the translation start site ( ATG MO ) , to the splice donor site of exon 1 ( Ex1 MO ) , and to the splice acceptor site of exon 3 ( Ex3 MO ) . Both splice morphants were predicted to result in the loss of an exon and the introduction of a premature stop codon . These morpholinos were independently injected into 1–4 cell stage embryos and then embryos were phenotypically analyzed at 24 , 48 , and 72 hours post fertilization ( hpf ) . A control morpholino ( CTL MO ) designed to a random sequence of nucleotides not found in the zebrafish genome was used to control for injection related non-specific effects [18] . The efficacy of the ATG morpholino to interfere with translation was verified by the demonstration of reduced myotubularin protein levels by immunofluorescence and western blot analysis of samples from ATG MO injected embryos ( Figure S2A , B ) . The ability of the splice morphants to alter myotubularin RNA processing and stability was confirmed by RT PCR analysis using primers to flanking exons ( Figure S2C ) . Of note , all 3 morpholinos yielded indistinguishable phenotypes . The ATG morpholino was used for analysis and quantitation in all subsequent experimentation , with all phenotypic observations additionally verified using the two splice morpholinos . Zebrafish embryos undergo rapid skeletal muscle development , and multinucleated myotubes are present and easily recognizable by 24 hours post fertilization . We thus began our analysis at this time point . Live microscopic analysis of myotubularin morphant embryos revealed a subtle but reproducible abnormality in body shape . Specifically , knockdown embryos exhibited a dorsal curvature ( ** ) through the back and tail instead of the normal flat or C-shaped dorsum ( Figure 1A ) . A similar morphologic abnormality has been observed in other zebrafish models of congenital myopathies [19] , [20] . Myotubularin morphant zebrafish began exhibiting more distinct morphologic abnormalities starting at 48 hpf , with the most obvious changes present in embryos at 3 days post fertilization ( Figure 1B ) . The most consistent finding was thinning of the muscle compartment ( bracket , Figure 1B ) . Morphant embryos also frequently had bent and/or foreshortened tails , a feature commonly associated with abnormalities in muscle structure or function ( arrow , Figure 1B ) . Of note , the most severely affected embryos ( ex: bottom embryo , Figure 1B ) also exhibited changes consistent with an overall delay in embryonic development ( small heads , abnormally shaped yolk balls , and reduced body extension ) . In zebrafish , the first recognizable muscle dependent motor function , detected between 17 and 26 hpf , is spontaneous embryo coiling [21] . On average , control injected embryos had 10 . 2 ( +/−0 . 4 ) spontaneous muscle contractions per 15 second period ( Supplemental Video 1 ) . Conversely , embryos injected with myotubularin morpholinos had only 5 . 2 ( +/−0 . 5 ) contractions in the same period ( Figure 2A and Supplemental Video 2 ) . This abnormality was highly reproducible ( P<0 . 0001 ) , and marked the earliest observed functional abnormality in zebrafish with reduced myotubularin levels . In addition to a decrease in spontaneous coiling frequency , myotubularin morphants also displayed defective motor behaviors later in development . Normally bouts of muscle activity contribute to the hatching of larvae from their protective outer chorion between 48 and 60 hpf . Typically approximately 90% ( 87 . 2%+/−2 . 3% ) of control injected embryos by 60 hpf had hatched from their chorions ( Figure 2B ) . In contrast , only 35 . 3% ( +/−3 . 3% ) of age-matched myotubularin morpholino-injected embryos were found to have hatched ( Figure 2B ) , consistent with a continued decrease in muscle activity . In the most severe morphants , delayed embryonic development also likely contributed to the reduction in chorion hatching . Once hatched , the myotubularin morphant larvae also displayed profound abnormalities in touch-evoked escape behaviors . Typically , 72 hpf larvae respond to tactile stimuli with a rapid and vigorous escape contraction , followed by swimming , which often resulted in larvae swimming out of the field of view ( Figure 2C; Supplemental Video 3 ) . In contrast , myotubularin morphants displayed weak escape contractions , followed by diminished swimming that often failed to propel the larvae out of the field of view ( Figure 2C; Supplemental Video 4 ) . The delayed chorion hatching , diminished touch-evoked escape behaviors , and morphologic changes were highly indicative of decreased muscle function . Severe muscle pathology , observed at both the light and electron microscopic levels , underlied the functional defects described above . We focused our analysis on muscle from 72 hpf embryos , as the muscle structure at this age is mature and greatly resembles that of human muscle . Light microscopic analysis of hematoxylin/eosin stained myotubularin morphant muscle revealed thin myofibers with abnormally located nuclei ( ** , Figure 3B ) . Analysis of semi-thin sections more dramatically illustrated these abnormal nuclei , which were mislocalized , large and filled with nucleoli of unusual appearance ( Figure 3C ) . These findings are highly reminiscent of the nuclear abnormalities observed in human myotubular myopathy , shown in longitudinal section in Figure 3A . We further characterized the perinuclear compartment using electron microscopy ( Figure 4 ) . Nuclei from myotubularin morphants were again found to be unusual in appearance ( Figure 4B ) . The nuclei were surrounded by enlarged areas of disorganized cytoplasm which had a relatively paucity of normally appearing organelles . Higher magnification of the perinuclear compartment underscored the perinuclear changes , revealing abnormal mitochondria , areas lacking any organellar structure , and disorganized tubule-like structures ( Figure 4C ) In addition , some fibers contained large , bizarre , membranous structures of unclear origin ( Figure 4D ) . This perinuclear disorganization is commonly observed in human myotubular myopathy muscle biopsies , and similar membranous structures have also been reported [22] . Of note is that we did not observe obvious vacuoles in the perinuclear area of any myofibers examined , which is contrary to what might be expected for a defect in endosomal trafficking . The fact that myotubularin morphants had thin appearing muscle compartments by live image analysis ( Figure 2 ) suggested that the muscle fibers may be hypotrophic as compared to controls . To examine this , we isolated myofibers from 72 hpf control and myotubularin morpholino injected embryos . Myofiber size was determined by calculating the area of myofibers stained by immunofluorescence with a myosin heavy chain ( MHC ) antibody . Myofibers from myotubularin morphants were significantly smaller than those from controls , measuring only 50% of control area ( Figure 5A , B ) . The reduced size was not due to loss of myofiber structural integrity , as evidenced by the normal appearance of sarcomeric structures with MHC antibody labeling . Myofiber hypotrophy is an abnormality that is commonly observed in the muscle from myotubular myopathy patients [2] . One of the central questions related to myotubularin function is whether it has lipid phosphatase activity in vivo . To address this , we measured levels of PI3P , the primary lipid upon which myotubularin acts in vitro , in morpholino-injected embryos . For whole embryo measurements , we extracted total lipids and then used a lipid-protein-antibody overlay technique . When normalized to PI4P levels , the amount of PI3P detected in lipid preps from myotubularin morphants was not significantly different from the level in controls ( Figure S3 ) . The fact that overall PI3P levels were not changed was unsurprising considering that 7 other MTMRs with PI3P phosphatase activity are present in the fish embryo ( see Figure S1 ) . Given that myotubularin is specifically required for muscle function , we next wanted to measure PI3P levels in muscle only . To accomplish this , we performed quantitative immunofluorescence on isolated myofibers using a PI3P antibody . Myotubularin morphant myofibers had readily observable increases in PI3P antibody staining , in particular in the perinuclear area ( Figure 6A ) . We quantitated the pixel intensity of the perinuclear PI3P staining , and found that myotubularin morphants had levels 1 . 6 times higher than observed in controls ( Figure 6B ) . This was consistent with a loss of myotubularin's phosphatase activity in the muscle , and provided evidence that myotubularin functions to regulate PI3P levels in muscle in vivo . A potential explanation for the fact that PI3P levels are normal in the whole embryo but increased in muscle is that myotubularin is the sole or primary PI3P phosphatase in muscle while other MTMRs are expressed in other tissues . This question has been examined in murine myocytes by RT-PCR , and myotubularin was found to be the predominant phosphatase expressed in differentiated fibers [23] . We examined this question in the developing zebrafish using whole mount RNA in situ hybridization . We focused on the expression of myotubularin and its two most closely related homologs , MTMR1 and MTMR2 . We found that between 24 hpf and 72 hpf , only myotubularin was expressed in muscle ( Figure 7A and data not shown ) , supporting the idea that it is the primary PI3P phosphatase in that tissue . We thus hypothesized that myotubularin knockdown results specifically in abnormalities in muscle because other functionally similar MTMRs are not expressed in muscle . To test this , we performed a series of gene rescue experiments ( Figure 7B ) . We injected embryos with myotubularin morpholino and RNA from either myotubularin , MTMR1 , or MTMR2 and measured the ability of embryos to hatch from their chorions by 60 hpf . In these experiments , the morpholino and the RNA are expressed ubiquitously . As expected , injection of morpholino alone caused a significant reduction in hatching ( 35% hatched; see also Figure 2B ) , while co-injection with full-length zebrafish myotubularin RNA resulted in significant amelioration of this hatching defect ( 71% hatched ) . Interestingly , co-injection of morpholino with either MTMR1 or MTMR2 RNA also restored the ability to hatch from the chorion . MTMR1 rescued hatching nearly to control levels ( 82%hatched; Figure 7B ) , while MTMR2 resulted in more modest improvement ( 55% hatched; Figure 7B ) . Therefore , these functionally similar MTMRs can compensate for the lack of myotubularin function in skeletal muscle . A recent study on mouse myotubularin by Buj-Bello and colleagues reported localization of the protein to the T-tubule/sarcoplasmic reticulum junction [24] . We examined myotubularin subcellular localization in zebrafish myofibers , and determined by immunofluorescent analysis that the protein was expressed in a distinctive linear pattern that overlaps with that of the dihydropyridine receptor ( DHPR ) , a marker for T-tubules ( Figure 8 ) . This pattern is thus consistent with localization to T-tubules . As expected , this staining was essentially undetectable in myofibers derived from myotubularin morphants ( Figure S2 ) . Based on this localization , we were interested in the effect of myotubularin knockdown on T-tubule organization . We performed ultrastructural analysis using electron microscopy ( Figure 9 ) . Muscle from control morpholino injected embryos exhibited the normal pattern of T-tubules and sarcoplasmic reticulum ( SR ) , with the SR coursing tightly through the sarcomeres and the T-tubules forming triads at regular periods . Conversely , muscle from myotubularin morpholino injected embryos had grossly aberrant SR and T-tubule networks ( Figure 9 ) . The SR networks were irregular , disorganized , and often randomly interspersed throughout the sarcomere . The T-tubule triads showed a range of abnormalities , from mild changes in electron density of the triad ( arrow , upper right panel ) , to severe dilation of the triad structure ( arrows , lower right panel ) , to fibers with essentially unrecognizable SR/triad areas ( arrow , lower left panel ) . We next determined if these ultrastructural changes corresponded to alterations in T-tubule function . We focused on excitation-contraction coupling , a process that requires intact T-tubules . We first verified that nervous system output to muscle was normal by assaying touch-evoked fictive swimming . To examine this , whole-cell voltage recordings were made from myofibers in vivo . In both control and myotubularin morphants , tactile stimulus resulted in rhythmic membrane depolarization in skeletal muscle ( Figure S4 ) . These data are consistent with intact output from the nervous system and through the neuromuscular junction [25] , [26] . We then proceeded to study excitation-contraction coupling ( Figure 10 ) . This was accomplished by measuring the ability of myofibers to contract when exposed to depolarizing stimuli of progressively higher frequencies [27] . Employing this technique , we found that control myofibers consistently contracted at all stimuli up to 30 Hz , with the average maximal frequency equaling 27 . 0 Hz . Conversely , myofibers from myotubularin morphants exhibited increasing abnormalities above 10 Hz , with no myofibers able to contract to stimuli at 25 Hz and the average maximal frequency equaling only 11 . 5 Hz . This result is consistent with a defect in excitation-contraction coupling , and provides functional evidence to support the morphologic abnormalities observed in the T-tubules . We were interested to correlate our findings with muscle from myotubular myopathy patient biopsies . T-tubule abnormalities have not been specifically mentioned in previous pathologic analyses from myotubular myopathy patients . We examined T-tubule organization in human biopsy samples using immunohistochemistry and antibodies to DHPRa1 , a T-tubule marker , and to RYR1 , a marker of the adjacent sarcoplasmic reticulum . A similar technical approach was successfully utilized by Laporte and colleagues to examine T-tubule organization in centronuclear myopathy patients with BIN1 mutations [28] . As a staining control , we used muscle from an unaffected , age matched control sample . DHPRa1 and RYR1 staining in the control muscle were found in the expected pattern along the membrane and throughout the cytoplasm ( Figure 11A and Figure 11B , respectively ) . Conversely , samples from three patients revealed clear abnormalities in both DHPR and RYR1 staining patterns . T-tubules were found concentrated around the abnormally located central nuclei , or in irregular densities in the centers of several fibers . Importantly , other plasma membrane components were not found in this distribution ( Figure S5 ) , indicating that this disorganization is relatively specific for T-tubules . We lastly examined electron micrographs obtained from patient muscle biopsies ( Figure 12 ) . Age matched control muscle showed the typical tight triad structure with well-organized adjacent sarcoplasmic reticulum . In contrast , micrographs from 3 myotubular myopathy patients showed various degrees of dilatation and disorganization of the T-tubules and adjacent sarcoplasmic reticulum . In conjunction with the immunostaining , these data confirm that T-tubule abnormalities are present in both our zebrafish model and in patients with myotubular myopathy .
Myotubular myopathy is characterized clinically by the early onset of weakness and hypotonia , and pathologically by Type I fiber hypotrophy and the presence of centralized nuclei with abnormal appearance surrounded by areas of sarcoplasmic disorganization [1] . Zebrafish with reduced levels of myotubularin share all of these essential disease features . Embryos have defects in the earliest muscle dependent functional processes , including diminished spontaneous contractions and an inability to hatch from their chorions . The histopathology of myotubularin morphant fish closely mirrors the appearance of human myotubular myopathy muscle . Fibers are small ( 50% of control size ) and have large , unusual and mislocalized nuclei surrounded by areas of sarcoplasmic disorganization . The perinuclear area also often contains accumulation of abnormal membranous structures; such structures have been reported in human ultrastructural analyses [22] . The myotubularin morphant zebrafish described here are now the second model system that recapitulates the “clinical” and pathologic features of myotubular myopathy by knocking down myotubularin levels during development . The other model is a mouse gene knockout generated by Buj-Bello , Laporte , Mandel and colleagues [17] . One interesting difference between our model and the knockout mice is the timing of the muscle phenotype . Our phenotype is present at a very early time point ( essentially when primary myogenesis is completed ) , whereas the knockout mice have a period of normal development followed by precipitous degeneration . It is not clear which more accurately reflects the human disease , for while patients often have symptoms at birth , the ability to measure/detect in utero abnormalities in muscle function is difficult [1] . The difference between the two models may be reflective of the rapid and compacted development of the zebrafish . Conversely , it may be due to the fact that muscle maturation in the mouse continues for the first several postnatal weeks . Thus the difference may reflect the specifics of muscle development in the two organisms instead of intrinsic differences in myotubularin function in the species . Our zebrafish model joins a growing list of myopathies and dystrophies that are successfully modeled in zebrafish [19] , [20] , [25] , [29]–[32] . Given the large number of offspring that can be studied and the highly reproducible nature of our morphant phenotype , the myotubular myopathy zebrafish should provide an excellent springboard for high throughput testing of small molecule therapeutics . One of the fundamental questions regarding myotubularin function was whether it behaved as a lipid phosphatase in vivo . We were able to address this question using our zebrafish model . Using quantitative immunohistochemistry , we demonstrate that PI3P , the principal substrate for myotubularin phosphatase activity , accumulates in myofibers from myotubularin morphant embryos . This is the predicted result from loss of myotubularin expression if it acts as a 3-position phosphatase . Significantly , these data are very consistent with the previously reported changes in PI3P levels found when myotubularin protein levels are reduced in cell culture or in yeast . We observed a 1 . 6 fold increase in PI3P in skeletal muscle , while Cao et al detected a 1 . 6 to 2 fold increase using RNAi in A431 cells and Dixon and colleagues found a 2 fold increase in ymr1 null yeast . Of note , our results represent one of the first assessments of potential phosphatase activity for any myotubularin family member in vivo and the first specifically in muscle . Including myotubularin , 15 MTMRs are present in the vertebrate genome . All are expressed in zebrafish , mouse and man . Eight of the 15 have apparently identical phosphatase activity , with the remaining 7 are considered “phosphatase-dead” MTMRs [33] . Because myotubularin mutations result in severe muscle disease , it seems clear that none of the phosphatase active MTMRs compensate in myotubular myopathy patients [14] . It was not known whether this is due to unique non-phosphatase properties of myotubularin , or rather due to expression differences between MTMRs . Our data convincingly support the later conclusion . We show that MTMR1 and MTMR2 , the MTMRs with the highest homology to myotubularin , are not expressed in zebrafish muscle . Furthermore , exogenous ubiquitous expression of either gene rescued the myotubularin morpholino phenotype . Importantly , expression of these MTMRs in control fish did not result in obvious phenotypic abnormalities . This implies that increasing the expression of either MTMR1 or MTMR2 in patient muscle is a viable potential treatment strategy for myotubular myopathy . Perhaps the most significant finding from our study is that decreasing myotubularin expression or function results in both structural and functional abnormalities in the T-tubule network . This finding is significant for several reasons . The first is that it provides the first viable explanation for why patients ( and mice and zebrafish ) have significant weakness . T-tubules are critical for several aspects of muscle contractions and force generation , in particular for excitation-contraction coupling [34] . Impairment of this network should clearly lead to diminished force production and muscle weakness . We demonstrate this functionally in the zebrafish , as embryos with decreased myotubularin have excitation-contraction coupling abnormalities . A second significance to these data is that they provide a plausible hypothesis for myotubularin function in myofibers . T-tubules biogenesis and maintenance is dependent on the continuous recycling of its membranous contents [15] . Membrane recycling is in turn dependent on tight regulation of phosphoinositides . Therefore , one possible explanation for our results is that myotubularin functions to regulate the recycling of T-tubule membrane components via its ability to participate in the regulation of phosphoinositide levels . An association between T-tubule homeostasis and myotubularin is especially attractive given the potential functional similarities between T-tubule recycling and endosomal dynamics . Previous studies have shown that both endosomes and T-tubules share similar structural and regulatory components . Most notably , BIN1/amphiphysin2 and dynamin-2 are critical regulators of membrane trafficking at the endosome [35] , [36] , and both are expressed at the T-tubule [28] . In addition , BIN1 is required for T-tubule biogenesis in cultured myocytes and for T-tubule organization in Drosophila [37] , [38] . As discussed below , mutations in both BIN1 and dynamin-2 result in centronuclear myopathy [1] , a myopathy with similar pathologic features to myotubular myopathy . Such overlapping roles are also seen with caveoli , which are critical for both T-tubule formation/maintenance and for endocytosis [39] , [40] . Thus , given the many observations functionally linking T-tubule dynamics and the regulation of endosomes , it seems very likely that myotubularin's primary function in muscle is controlling T-tubule dynamics in a fashion analogous to that described for its regulation of endosomal trafficking in vitro [10] , [11] . A final importance relates to other congenital myopathies . Traditionally , congenital myopathies are considered a group of independent conditions , distinguished by their histopathologic features on muscle biopsy . However , they are in general similar in clinical presentation , characterized by neonatal hypotonia and non-progressive weakness [41] . The discovery of T-tubule abnormalities in myotubular myopathy now pathogenically links the three most prevalent groups of congenital myopathies . Core myopathies are caused by mutations in the ryanodine receptor ( RYR1 ) [42] , the calcium channel located at the T-tubule/sarcoplasmic reticulum border that is required for excitation-contraction coupling [25] , and by mutations in Selenoprotein-N [43] , a modifier of RYR1 [20] . Most nemaline myopathies are caused by mutations in the components of the thin filaments , proteins which function downstream of RYR1 and calcium release to initiate contraction [44] . Along with the centronuclear myopathies due to BIN1 ( where T-tubule abnormalities have already been documented ) and dynamin-2 mutation [1] , myotubular myopathy likely is an “upstream” defect , resulting in abnormalities in the underlying T-tubule and sarcoplasmic reticular structure upon which RYR1 function is dependent . In light of this commonality between congenital myopathies , the next important step is to see if modifiers of excitation-contraction coupling and T-tubule function can ameliorate the muscle weakness in the relevant disease models . We are currently at work developing and testing such agents in our zebrafish model of myotubular myopathy . We have developed a new vertebrate model of myotubular myopathy , which has allowed us to answer fundamental questions regarding myotubularin function , and to make novel insights into the pathogenesis of the human disease . In the future , this model may provide a valuable platform for developing and testing novel therapeutics based on our new insights .
Morpholinos were designed to the putative ATG , to the exon 1 splice donor site , and to the exon 3 splice acceptor site of the zebrafish myotubularin gene ( GeneTools , LTC ) . The control morpholino ( GeneTools ) was designed to random sequence with no homology by BLAST analysis in the zebrafish genome . The morpholino sequences are as follows: 1 . 5 nL of morpholino ( 0 . 08 mM ) was injected into the yolk of 1–4 cell stage zebrafish embryos as described previously [18] . Embryos were subsequently grown in egg water and then analyzed at various time points . Western blot and RT-PCR analysis for determining morpholino efficacy were described previously [18] . Embryos were examined by live image analysis using a Leica stereomicroscope and camera . Both photomicrographs and videos were obtained using this system . To measure spontaneous coiling , embryos were manually dechorionated at 24 hpf and recorded for 15 seconds . Records were obtained approximately 5 minutes after dechorionation . Touch-evoked motor behaviors were elicited by touching the head , yolk sac or tail with a pair of No . 5 forceps . Motor behaviors were recorded by video microscopy ( ∼20× ) using a Panasonic CCD camera ( wv-BP330 ) mounted on a Leica dissection microscope . Videos captured ( 30 Hz ) on a Macintosh G4 computer with a Scion LG-3 video card using Scion Image software ( www . scioncorp . com ) were processed with ImageJ . For hematoxylin/eosin sections , 72 hpf embryos were fixed overnight at 4°C in 4% paraformaldehyde , washed in PBS , dehydrated in alcohols and xylenes , and embedded in paraffin . Microtome sections were cut at 2 mm . H/E was done per standard protocol . For semi thin sections and electron microscopic analysis , 72 hpf embryos were fixed overnight at 4°C in Karnovsky's fixative and then processed for sectioning by the Microscopy and Imaging Laboratory ( MIL ) core facility . Semi-thin sections were stained with Toludine blue . Light microscopy was performed using an Olympus BX-51 microscope and images captured with an Olympus DP-70 digital camera . Electron microscopy was performed using a Phillips CM-100 transmission electron microscope . Mixed cell cultures from 72 hpf embryos were obtained as follows . Embryos were euthanised with tricaine and the dissociated in 10 mM collagenase type I ( Sigma ) for 60–90 min at room temperature . Embryos were triturated approximately every 30 min . Dissociated preps were pelleted by centrifugation ( 5 min at 3000 rpm ) , resuspended in CO2 independent media ( Invitrogen ) , passed through a 70 mm filter ( Falcon ) , and plated onto chamber slides ( Falcon ) precoated with poly-L-Lysine ( Sigma ) . Culture media was changed after one hour , after which cells were fixed for 15 min in 4% paraformaldehyde . Fixed cells were blocked in 10%NGS/0 . 3% Triton , incubated in primary antibody overnight at 4°C , washed in PBS , incubated in secondary antibody , washed in PBS , then mounted with ProLong Gold plus DAPI ( Invitrogen ) . For PI3P antibody staining , cells were processed according to manufacturers protocol ( Echelon Biosciences ) . The following primary antibodies and dilutions were used: mouse anti-myosin heavy chain ( MF20; 1∶20; Developmental Hybridoma Bank ) ; mouse anti-PI3P ( 1∶100; Echelon ) ; rabbit anti-myotubularin ( 1∶50; Stratagene ) ; and mouse anti-DHPR1a ( 1∶200; Abcam ) . Alexafluor conjugated secondary antibodies were used at 1∶250 ( Invitrogen ) . Images were obtained by confocal microscopy as described previously [18] . Myofiber area was measured from photomicrographs using Metamorph software . Myofibers were outlined using the freehand tool and analyzed for total two-dimensional area . PI3P antibody staining was performed as described above . Samples were analyzed on an Olympus IX-71 inverted confocal microscope and images captured using the FluoView v4 . 3 software . Fluorescent images were processed for quantitation using Metamorph ( Sunnyvale , CA ) . Identical regions ( immediate perinuclear area ) were selected from each fiber using the rectangle tool set to a constant area . Boxed areas were then analyzed for pixel intensity . 15 myofibers from control and myotubularin morphant myofibers were compared for each region ( 5 per single myofiber prep×3 independent preps ) . Statistical significance was determined using a Students one-tailed t-test ( Prism software ) [45] . The lipid overlay assay was performed per manufacturer protocol for PI3P and PI4P on lipids extracted from 72 hpf embryos ( Echelon Biosciences ) [11] . In situ hybridization was performed as described previously [18] . Probes were made by in vitro transcription from zebrafish cDNA plasmids ( all clones obtained from Open Biosystems ) . RNA for morpholino rescue was prepared by in vitro transcription using the mMessage mMachine kit ( Ambion ) . RNA was co-injected with morpholino at a concentration of 100 ng/ml . Rescue was determined by measuring the percentage of embryos hatched from their chorions at 60 hpf . For in vivo electrophysiological measurements [46] , larvae ( 72–80 hpf ) were pinned in a Sylgard-coated petri dish ( Dow Corning , Midland , MI ) containing extracellular recording solution with curare [in mM:134 NaCl , 2 . 9 KCl , 2 . 1 CaCl2 , 1 . 2 MgCl2 , 10 glucose , 10 HEPES , pH 7 . 8 and 3 µM d-tubocurarine] . Larvae were manually skinned on one side , exposing muscle tissue . Electrodes were pulled from borosilicate glass and filled with internal recording solution [in mM: 116 K-gluconate , 16 KCl , 2 MgCl2 , 10 HEPES , 10 EGTA , at pH 7 . 2 with 0 . 1% Sulforhodamine B for muscle cell type identification] . Whole-cell recordings were performed on individual adaxial myocytes using an Axopatch 200B amplifier ( Axon Instruments , Union City , CA ) , low pass filtered at 1 kHz and sampled at 2–10 kHz . For each patch-clamped myocyte , steps of depolarizing current ( 3–6 nA ) were injected to induce contraction . Current pulses were first delivered at a frequency of 1 Hz for 10 s . Frequency was increased by 5 Hz intervals until the myocyte reached tetanus . Contractions were recorded by video imaging and data acquired using a Digidata 1322A interface controlled by pClamp 8 software ( Axon Instruments ) . Data analysis was performed using Clampfit 10 . Touch-evoked fictive swimming was elicited with a fire-polished recording electrode ( ∼50 µm ) controlled by a Burleigh PCS-1000 piezoelectric manipulator and PCS-250 patch clamp driver ( EXFO Life Sciences ) as described previously [47] until fictive swimming was evoked . Cryosections from human muscle biopsies were incubated overnight at 4°C in primary antibody ( DHPRa1 , 1∶200; RYR1 , 1∶100; α-dystroglycan , 1∶50 ) , washed in TBS , and then processed using the kit ( Novacastra ) . Photomicrographs were obtained on an Olympus XL . Western blot analysis was performed as previously described [48] . Rabbit anti-myotubularin ( Stratagene ) was used at 1∶1000 and anti-rabbit secondary ( Santa Cruz Biotech ) at 1∶2000 . Goat anti-actin ( Santa Cruz Biotech ) was used at 1∶1000 and anti-goat secondary ( Santa Cruz Biotech ) at 1∶200 . Luminenscent detection was performed using the Lumiglo reagent ( Cell Signalling ) . All animals were handled in strict accordance with good animal practice as defined by national and local animal welfare bodies , and all animal work was approved by the appropriate committee ( UCUCA #09835 ) . | Congenital myopathies are inherited muscle conditions typically presenting in early childhood . They are individually rare , but as a group are likely as common as conditions such as muscular dystrophy . The zebrafish is an emerging experimental system for the study of myopathies . We have utilized the zebrafish to develop a model of myotubular myopathy , one of the most severe childhood muscle diseases and a condition whose pathogenesis is poorly understood . We have generated fish that have the characteristic behavioral and histological features of human myotubular myopathy . Using this model , we then made novel insights into the pathogenesis of myotubular myopathy , including the identification of abnormalities in the muscle tubulo-reticular system . We subsequently identified similar changes in muscle from patients with myotubular myopathy , corroborating the importance of our zebrafish findings . Because a functional tubulo-reticular complex is required for normal muscle contraction , we speculate that the weakness observed in myotubular myopathy is caused by breakdown of this network . In all , our study is the first to identify a potential pathomechanism to explain the clinical features of myotubular myopathy . Furthermore , by revealing abnormalities in the tubulo-reticular system , we provide a novel link between myotubular myopathy and several other congenital myopathies . | [
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] | 2009 | Loss of Myotubularin Function Results in T-Tubule Disorganization in Zebrafish and Human Myotubular Myopathy |
Pink1 is a mitochondrial kinase involved in Parkinson's disease , and loss of Pink1 function affects mitochondrial morphology via a pathway involving Parkin and components of the mitochondrial remodeling machinery . Pink1 loss also affects the enzymatic activity of isolated Complex I of the electron transport chain ( ETC ) ; however , the primary defect in pink1 mutants is unclear . We tested the hypothesis that ETC deficiency is upstream of other pink1-associated phenotypes . We expressed Saccaromyces cerevisiae Ndi1p , an enzyme that bypasses ETC Complex I , or sea squirt Ciona intestinalis AOX , an enzyme that bypasses ETC Complex III and IV , in pink1 mutant Drosophila and find that expression of Ndi1p , but not of AOX , rescues pink1-associated defects . Likewise , loss of function of subunits that encode for Complex I–associated proteins displays many of the pink1-associated phenotypes , and these defects are rescued by Ndi1p expression . Conversely , expression of Ndi1p fails to rescue any of the parkin mutant phenotypes . Additionally , unlike pink1 mutants , fly parkin mutants do not show reduced enzymatic activity of Complex I , indicating that Ndi1p acts downstream or parallel to Pink1 , but upstream or independent of Parkin . Furthermore , while increasing mitochondrial fission or decreasing mitochondrial fusion rescues mitochondrial morphological defects in pink1 mutants , these manipulations fail to significantly rescue the reduced enzymatic activity of Complex I , indicating that functional defects observed at the level of Complex I enzymatic activity in pink1 mutant mitochondria do not arise from morphological defects . Our data indicate a central role for Complex I dysfunction in pink1-associated defects , and our genetic analyses with heterologous ETC enzymes suggest that Ndi1p-dependent NADH dehydrogenase activity largely acts downstream of , or in parallel to , Pink1 but upstream of Parkin and mitochondrial remodeling .
Parkinson's disease ( PD ( OMIM #168600 ) ) is the most common neurodegenerative movement disorder [1] . While diverse processes including autophagy , apoptosis , oxidative stress and accumulation of protein inclusions have been implicated in the etiology of the disease , mitochondrial dysfunction appears to play a central role as well [2]–[4] . Mitochondrial toxins , such as MPTP ( 1-methyl-4-phenyl-1 , 2 , 3 , 6-tetrahydropyridine ) or rotenone , that block Complex I of the mitochondrial electron transport chain ( ETC ) cause clinical features reminiscent of PD in humans and are commonly used to create animal models of the disease [5] , [6] . Furthermore , Complex I deficiency is often observed in neurons of PD patients [7] and mutations in genes causing familial forms of PD , including pink1 ( PARK6 , OMIM #605909 , Gene ID: 65018 ) , parkin ( PARK2 , OMIM #600116 , Gene ID: 5071 ) and DJ-1 ( PARK7 , OMIM #606324 , Gene ID: 11315 ) result in defects in mitochondrial morphology and/or function in model organisms [8]–[14] . Molecular genetic analyses of PD-associated genes will thus yield important insights into the mechanisms of PD . Pink1 ( CG4523 Gene ID: 31607 ) is a serine/threonine kinase involved in maintaining mitochondrial integrity [8]–[10] and loss-of-function mutants show hallmark mitochondrial defects including male sterility , an inability of most flies to fly as well as an inability to maintain synaptic transmission during intense stimulation , a deficit that can be rescued by supplementing synapses with ATP [15] , [16] . The observation of larger clumped mitochondria in pink1 mutants suggests a model where Pink1 is involved in the clearance of dysfunctional mitochondria [17]–[21] . This is in line with experiments that show an alleviation of pink1-associated phenotypes by over-expression of Parkin ( CG10523 Gene ID: 40336 ) , an E3 ubiquitin ligase involved in mitophagy [8]–[10] and by the notion that loss-of-function pink1 trumps Parkin recruitment to mitochondria [18] . Furthermore , the morphological defects in pink1 mutants can be modulated by altering the levels of proteins involved in mitochondrial fusion or fission , and this is thought to facilitate mitophagy [17] , [19] , [21] , [22] . However , these studies are not conclusive as functional defects in pink1 mitochondria at the level of Complex I have been observed in the absence of severe morphological alterations [15] , [23] and such functional defects can eventually result in mitochondrial morphological alterations [24]–[26] . These results suggest an alternative model where functional defects in pink1 mutant mitochondria precede morphological alterations and mitophagy . To determine if Pink1 acts to regulate ETC function we performed genetic studies with heterologous alternative enzymes that can bypass either Complex I , or Complex III and IV . Although each of the ETC complexes in flies ( and humans ) comprise numerous proteins ( Complex I contains more than 40 subunits in humans and in flies ) , Saccharomyces cerevisiae Ndi1p ( Gene ID: 854919 ) ( UAS-NDI1 ) constitutes an alternative NADH oxidoreductase that transfers electrons from NADH to ubiquinone , delivering electrons to downstream complexes and therefore can be used to bypass electron transport in Complex I in higher order species [27] , [28] . Similarly , ‘Ciona intestinalis’ alternative oxidase AOX ( Gene ID: 3293227 ) is able to bypass the cytochrome c chain and Complexes III and IV by using electrons from ubiquinol to reduce oxygen [29] . While neither Ndi1p , nor AOX themselves transfer protons across the inner mitochondrial membrane , they may add to the proton motive force by facilitating the ubiquinone cycle , thus contributing to Complex III and IV mediated proton translocation upon expression of Ndi1p , or to Complex I mediated proton translocation upon expression of AOX . Illustrating this idea , expression of Ndi1p in Drosophila can rescue partial loss-of-function mutations in Complex I components and confers rotenone resistance [30] , [31] , and expression of AOX can rescue partial loss-of-function mutations in Complex III and IV components and confers cyanide resistance [32] . Hence , Ndi1p and AOX allow us to genetically dissect the ETC . Here , we assay the role of Complex I in pink1-associated defects and find that Ndi1p can rescue pink1 phenotypes while AOX cannot . Similarly , loss-of-function of a Complex I component phenocopies many of the pink1 mutant phenotypes and these defects can also be rescued by expression of Ndi1p . In contrast , expression of Ndi1p fails to rescue parkin mutants , indicating that Ndi1p acts downstream or in parallel to Pink1 but upstream of Parkin . Further supporting this model , we do not find reduced enzymatic activity of Complex I in parkin mutants , and while modulating mitochondrial remodeling using Drp1 ( CG3210 Gene ID: 33445 ) or Opa1 ( CG8479 Gene ID: 36578 ) can rescue the defects in mitochondrial morphology in pink1 mutants , these manipulations do not rescue decreased enzymatic activity of Complex I observed in pink1 mutants . Thus , our studies suggest that the defects at Complex I in pink1 mutants are upstream of several of the events that lead to pink1-associated phenotypes .
Electron transfer activity of the mitochondrial multi-protein Complex I , NADH:ubiquinone oxidoreductase ( EC 1 . 6 . 5 . 3 ) can be recapitulated by a single yeast protein , Ndi1p [31] , [33] , [34] . To determine whether the reduced respiratory chain activity in pink1 mutants reported previously [15] are an upstream defect in the mutants , we generated transgenic flies that harbor a UAS-Sacharomyces cerevisiae NDI1 construct allowing expression under the control of GAL4 . Quantitative RT-PCR using RNA from flies that harbor the UAS-NDI1 transgene and the ubiquitously expressing da-GAL4 driver indicates that NDI1 expression levels in such animals is similar to that of an endogenously expressed Complex I component CG3446 ( Figure S1A ) . In addition , quantitative RT-PCR using RNA of UAS-NDI1 bearing flies , in the absence of GAL4 also shows low but significant expression of NDI1 RNA , particularly in the male reproductive organ ( Figure 1A , blue ) . Ndi1p confers rotenone insensitive NADH oxidoreductase activity in flies as the enzymatic activity of isolated Complex I in the presence of rotenone , a Complex I inhibitor , remains high in mitochondria from flies expressing Ndi1p , but is dramatically reduced in rotenone-treated mitochondria from control flies ( Figure S1B ) [30] , [31] . Ndi1p expression in Drosophila is benign as ubiquitous expression ( da-GAL4 ) does not lead to obvious behavioral or developmental abnormalities ( Figure S1C , S1D ) . Ndi1p expression rescues lethality associated with RNAi-induced systemic loss-of-function of CG18624 ( Gene ID: 31697 ) , an evolutionary conserved Complex I component , and also the mitochondrial defects associated with loss of CG12079 ( Gene ID: 38378 ) , another conserved Complex I component ( below ) . These data confirm that Ndi1p is functional . Next , we generated pink1 mutant animals that express Ndi1p . While pink1 mutant males are sterile , low expression of Ndi1p is sufficient to completely revert this defect ( Figure 1B ) . Given that pink1 is located on the X-chromosome , homozygous pink1 females are never observed . However , in the presence of NDI1 , fertile homozygous pink1 female flies are obtained ( Figure S2A ) , whose genetic makeup we confirmed by genomic PCR ( Figure S2B ) . Furthermore , while in pink1 mutants morphological defects in spermatid mitochondria are apparent [10] , [31] , expression of Ndi1p also rescues these mitochondrial defects ( data not shown ) . Thus , expression of Ndi1p rescues pink1-associated male sterility and mitochondrial morphological defects in the germline to a level indistinguishable from wild type controls . Drosophila flight muscles require large amounts of metabolic energy supplied by mitochondria . In adult pink1 mutant flies , mitochondrial deficits lead to muscle degeneration and a severe defect to fly . While expression of Ndi1p using da-GAL4 does not affect flight ( Figure S1C ) , expression in pink1 mutants improves flight ( Figure 1C ) . Although expression of Ndi1p does not restore the pink1 flight defect to control levels , it is important to note that previous experiments demonstrating rescue of Pink1 phenotypes using over-expressed Parkin showed very similar results [9] . Ndi1p expression also rescues degeneration of the indirect flight muscles in pink1 mutants as evaluated by decreased indentations in the thoraces of the flies ( Figure S2C ) . As flight muscle degeneration correlates with an accumulation of enlarged mitochondria in pink1 mutants [8]– , we labeled the mitochondrial pool using mito-GFP ( Figure 1E ) . In adult pink1 flight muscles , the mitochondria appear enlarged and clumped when compared to controls ( Figure 1E , middle ) and Ndi1p expression in pink1 mutants partially trumps this defect ( Figure 1E , right ) . Finally , pink1 mutants that express Ndi1p have an increase in ATP levels compared to pink1 mutants not expressing Ndi1p ( Figure 1D ) . Thus , enhanced ATP levels in pink1 mutants that express Ndi1p may dampen mitochondrial dysfunction and diminish muscle degeneration . Previous data indicated that mitochondrial defects cause synaptic vesicle trafficking and neurotransmitter release defects at pink1 mutant synapses [15] , [23] . We therefore measured neurotransmitter release at the Drosophila third instar neuromuscular junction ( NMJ ) . Upon stimulation of the motor neuron at 1 Hz , pink1 mutants , pink1 mutants that express Ndi1p , as well as control animals that express Ndi1p , show normal neurotransmitter release as gauged by the amplitude of the excitatory junctional potential ( EJP ) ( Figure S3A ) . In contrast , when stimulated at high frequency ( 10 Hz ) , neurotransmitter release in pink1 mutants gradually declines , in line with a defect to mobilize ‘reserve pool’ ( RP , see below ) vesicles that are only used under such ‘stressed’ conditions [16] , [35] . Interestingly , pink1 mutants that express Ndi1p maintain normal levels of synaptic transmission during a 10 Hz 10 min stimulation paradigm ( Figure S3B ) . These data indicate that synaptic transmission defects at pink1 mutant NMJs are also rescued by expression of Ndi1p . As previously shown , this neurotransmission deficit is likely caused by a lack of mobilization of the reserve pool synaptic vesicles within NMJ boutons [15] . We used the fluorescent dye FM 1–43 to label vesicles loaded in the RP [36] using the stimulation paradigm depicted in Figure 1F [37] . While pink1 mutants show a significant reduction in RP vesicle labeling , pink1 mutants that express Ndi1p display labeling of RP vesicles very similar to controls ( Figure 1F , 1G ) . Thus , synaptic function deficits in pink1 mutants are alleviated by expression of yeast Ndi1p . In pink1 mutant motor neurons , mitochondria are morphologically normal but show only partial mitochondrial membrane depolarization [15] . We assessed the mitochondrial membrane potential in pink1 mutants rescued with Ndi1p using the ratiometric dye JC-1 . [16] , [38] . Interestingly , compared to pink1 mutants , mitochondria at synaptic boutons of pink1 mutants that express Ndi1p are significantly more polarized and show more intense red JC-1 labeling ( Figure 1H , 1I ) . Although Ndi1p itself is not involved in proton transfer over the inner mitochondrial membrane , our data indicate that expression of Ndi1p can restore a negative mitochondrial membrane potential in pink1 mutants . Potentially Ndi1p improves electron transfer from NADH to complex III/IV that in turn helps to restore the proton gradient in mitochondria at synapses . To further test the specificity of Ndi1p-dependent rescue of pink1-associated phenotypes , we also tested the ability of Ciona intestinalis AOX to bypass pink1 defects . Our rationale is that AOX can also transport electrons but at a different site within the ETC: AOX uses electrons from ubiquinol to reduce oxygen and thereby bypasses both Complex III and IV [29] , [32] . We confirm the functionality of AOX in flies because lethality induced by expression of RNAi to cyclope ( CG14028 Gene ID 46040 ) that encodes a Complex IV component , is rescued upon expression of AOX ( data not shown ) [32] . Similar to NDI1 we also find basal expression of AOX in the male reproductive organ that is much induced by the presence of da-GAL4 ( Figure 2A ) and ubiquitous expression of AOX also does not affect flight , muscle degeneration or the mitochondrial membrane potential ( Figure S4A , S4B; see below ) . In contrast to Ndi1p , expression of AOX completely fails to alleviate pink1-associated phenotypes such as male fertility , flight or mitochondrial morphology ( Figure 2B , 2C , 2E Figure S4C ) . AOX also does not revert the RP defects in pink1 mutant animals ( Figure 2F , 2G ) nor does it alleviate the reduced red JC-1 labeling observed in mitochondria at boutons of pink1 mutants ( Figure 2H , 2I ) . Finally , also the reduced ATP levels , observed in pink1 mutant animals , are not rescued by AOX ( Figure 2D ) . Thus , AOX expression does not rescue pink1 deficiency . Our work suggests that several pink1 mutant phenotypes stem from defects at the level of Complex I . To further test this hypothesis , we used RNAi mediated knock down of evolutionary conserved Complex I subunits ( Figure 3A ) . As expected , down regulation of Complex I subunits results in significantly lower Complex I enzymatic activity ( Figure 3B ) and expression of NDI1 in these flies results in an increased ATP concentration compared to RNAi of Complex I subunits in the absence of NDI1 expression ( Figure 3C ) . While expression of RNAi to some of the Complex I subunits results in developmental lethality , RNAi to other Complex I subunits yields adult flies , and we used one of those ( CG11455; Gene ID: 33179 ) to assess flight upon Complex I knock down . Under ‘standard testing conditions’ ( see methods ) RNAi to this Complex I subunit does not result in a strong defect to fly ( blue bar Figure 3D ) , however under more ‘stringent conditions’ ( see methods ) about half of the flies fail to fly , and this defect is rescued by expression of NDI1 ( red bars Figure 3D ) . Thus , while reduced Complex I activity results in a defect to fly , the flight deficit upon knock down of this Complex I subunit is milder than that observed in pink1 mutants ( Figure 3E ) . Next , we determined mitochondrial morphology using Mito-GFP in third instar larval muscles upon knock down of a Complex I subunit . Similar to mitochondria in pink1 mutants , mitochondria in muscles of animals that express RNAi to a Complex I subunit are swollen and clumped , but the defects we observe are in general less severe than those seen in pink1B9 null mutants . Interestingly , expression of NDI1 significantly alleviates these defects ( Figure 3F ) . To assess mitochondrial function in animals that express RNAi to a Complex I subunit with or without NDI1 , we assessed the mobilization of RP vesicles and we quantified red JC-1 labeling intensity within neuromuscular mitochondria . As indicated in Figure 3G–3J , reduced Complex I activity results in reduced RP vesicle mobilization and less red JC-1 labeling in boutonic mitochondria , and expression of NDI1 can significantly rescue these defects as well . Thus , similar to pink1 mutants , loss-of-function of a component of Complex I results in reduced ATP and functional defects in synaptic mitochondria , and these defects are alleviated by NDI1p . Furthermore , we also find that reduced Complex I activity leads to morphological defects in muscular mitochondria and a defect to fly in adult flies , but these defects are in general milder than those observed in pink1 null mutants . Pink1 has been suggested to act upstream of Parkin to regulate , in a linear pathway , mitophagy [8]–[10] , [39] , [40] . We therefore expressed Ndi1p in parkin mutant flies but we did not observe a rescue of male fertility , flight defects or muscular degeneration ( Figure 4A , 4B , 4D ) . In line with these observations , mitochondrial morphological alterations caused by Parkin deficiency are also not rescued by expression of Ndi1p ( Figure 4C ) . Thus , parkin mutants cannot be rescued by expression of Ndi1p . To determine if parkin mutants also display reduced enzymatic activity of Complex I we isolated mitochondria from parkin null mutant flies and from controls and measured Complex I enzymatic activity . In contrast to pink1 mutants , the isolated enzymatic activity of Complex I in parkin mutant mitochondria is similar to controls ( Figure 4E ) . These data are in further support of a model where Complex I defects in pink1 mutants occur upstream from the defects caused by loss of Parkin function . Previous reports indicate that genetic manipulation of the mitochondrial remodeling machinery using over expression of drp1 or loss-of-function of opa1 alleviates mitochondrial morphological defects , muscle degeneration and flight deficits both in pink1 and in parkin mutant flies [17] , [19] and we confirm these results ( Figure 5A , 5B , data not shown ) . In contrast however , sterility of pink1 mutant males is not rescued by increased drp1 or decreased opa1 ( Figure 5C ) , suggesting that manipulation of mitochondrial remodeling cannot rescue all pink1-related phenotypes . As mitochondrial morphological phenotypes may result from alterations in numerous biochemical pathways [26] , we assessed directly whether drp1 or opa1 affect the enzymatic activity of Complex I in pink1 mutant flies . However , as shown in Figure 5D , the enzymatic activity of Complex I is still reduced to a level similar to that observed in pink1 mutants . These data thus indicate that the enzymatic deficiency at the level of Complex I in pink1 mutants precedes mitochondrial morphological deficits , or that they in part occur independently .
In this work we present compelling evidence that the mitochondrial kinase Pink1 is critically required to maintain efficient Complex I enzymatic activity in mitochondria and that this function precedes mitochondrial remodeling or mitophagy ( Figure 5E ) . While Pink1 likely acts via multiple ( phospho- ) targets [41] , [42] , our data suggests a pathway in which many of the deficiencies in pink1 can be traced back to mitochondrial dysfunction [8]–[10] , [15] . Our experiments indicate that Pink1 acts at , or in parallel to , Complex I , in line with the reduced enzymatic activity of this complex in pink1 mutant mouse cells and flies [15] , [23] . Expression of Ndi1p alleviates many pink1-associated phenotypes , suggesting that more efficient electron transport between NADH and ubiquinone is mediated by Ndi1p ( bypassing the endogenous Complex I deficiency ) [30] in pink1 mutants that boosts formation of a proton gradient by Complex III and IV . Although AOX expression also improves ETC efficiency [32] , it does not rescue pink1-associated phenotypes , in contrast to AOX rescuing DJ-1β ( CG1349 Gene ID: 43652 ) and cyclope associated phenotypes [32] . The lack of rescue is likely not due to the fact that AOX is insufficiently activated as a result of low reduced ubiquinone concentrations [43] as expression of AOX in pink1 mutants results in premature death of pink1 animals such that only few pink1 mutants that express AOX emerge as adults ( data not shown ) . We surmise that the lower Complex I activity in pink1 mutants , which results in reduced proton transfer across the inner mitochondrial membrane [15] is further propagated by the presence of AOX , that transfers electrons to oxygen without pumping protons [29] . These data thus argue against general mitochondrial dysfunction in pink1 and a universal failing of the ETC [23] but reveals an important role for Pink1 upstream or in parallel to Complex I enzymatic activity [15] . Previous work indicates that loss of pink1 in some cell types results in mitochondrial fragmentation , a process preceding mitophagy [44] . Several lines of evidence now indicate that some of the mitochondrial morphological defects occur downstream of functional deficits in pink1 mutants . First , we show that expression of Ndi1p in pink1 mutants alleviates part of the mitochondrial morphological defects . Second , RNAi-mediated knock down of an evolutionary conserved Complex I component results in mitochondrial dysfunction but also mitochondrial swelling and clumping , indicating that functional mitochondrial defects can lead to morphological defects [24] , [26] , [45] . Third , mitochondrial functional defects in pink1 mutant flies and mice have been widely observed in neuronal populations where mitochondrial morphological defects are not ( yet ) prevalent [15] , [23] . Fourth , while facilitating mitochondrial fission in pink1 mutants alleviates mitochondrial morphological defects , a deficiency at the level of the enzymatic activity of Complex I persists . Previous results in pink1 knock out cells had also indicated that mitochondrial swelling defects in pink1 mutant cells can be rescued by modulating the levels of the mitochondrial fission machinery [46] , but also this manipulation failed to rescue the defect in mitochondrial membrane potential caused by loss of Pink1 [47] . Thus , our data indicate that the upstream molecular dysfunction in pink1 mutants on Complex I is a major culprit in the development of the pink1 mutant phenotypes ( Figure 5E ) . Our rescue experiments indicate that expression of NDI1 can significantly rescue numerous pink1 associated phenotypes , including male sterility , vesicle trafficking and mitochondrial membrane potential . Likewise , NDI1 also alleviates mitochondrial morphological defects in pink1 mutant muscles , but rescue of this morphological defect is only partial . Similarly , mitochondrial morphological defects observed in animals that express RNAi to a Complex I subunit and flight defects in such animals are in general less severe than those seen in pink1 null mutants . These results are consistent with Pink1 also acting in parallel to its role at the level of Complex1; however , we cannot exclude the possibility that the partial rescue of morphological defects in pink1 mutants upon expression of NDI1 originates from an incomplete reconstitution of ETC activity under these conditions , and that the pink1 mutant conditions at the level of Complex I may not be exactly recapitulated by knock down of the Complex I components . Furthermore , given that Complex I dysfunction results in mitochondrial morphological defects and mild flight defects that are rescued by NDI1 expression , and the observation that the enzymatic defects at the level of Complex I in pink1 mutants are not rescued upon expression of Drp1 or loss of opa1 function , the data are consistent with the pink1-associated Complex I defects to act at least in part upstream of remodeling and suggest an important and central role for Complex I in Pink1 induced mitochondrial pathology . Our work expands on previous genetic and cell biological studies , and indicates that Pink1 can act at a different level , upstream of Parkin , to control Complex I enzymatic activity ( Figure 5E ) . Indeed , unlike pink1 mutants , loss of parkin in flies does not cause significantly reduced enzymatic activity of Complex I seen in pink1 mutants , and in addition , parkin loss of function is not rescued by expression of Ndi1p . Our data indicate that Complex I deficiency in pink1 mutants is specific and that this defect is not a result of abnormal mitochondrial remodeling or mitophagy . This model is consistent with a role of Pink1 in controlling mitochondrial health and also does not exclude a downstream or parallel role where Pink1 can be triggered to recruit Parkin , facilitating mitophagy ( Figure 5E ) .
w; UAS-mito:GFP , w; da-Gal4 and w; P{lacW}opa1-like3475/CyO ( opa1S3 ) were obtained from Bloomington stock center ( Indiana , USA ) ; w pink1B9 and w pink1RV , parkin1 and parkinRV [48] were gifts from Jongkyeong Chung ( Korea , Advanced Institute of Science and Technology ) [9] and parkinΔ21 mutant flies were a gift from Graeme Mardon ( Baylor College of Medicine ) [11] . drp1+ genomic rescue constructs were provided by Hugo Bellen ( Baylor College of Medicine ) [16] and w1118; UAS-AOXF6 were a gift from Howard T . Jacobs [32] ( Finland , Institute of Medical Technology , Tampere University Hospital ) . w1118; UAS-CG12079RNAi ( w1118; P{GD5910}v13856 ) , w1118; UAS-CG11455RNAi ( w1118; P{GD4800}v12838 ) and cyclope ( CG14028 ) RNAi ( w1118; P{GD908}v13403 ) were from the Vienna Drosophila RNAi Center ( VDRC ) [49] . Flies were raised on standard cornmeal and molasses medium . The coding region of Saccaromyces cerevisiae NDI1 was amplified from yeast genomic DNA ( Patrick Van Dijck , VIB Leuven ) , with the following primers; CGG AAT TCC AAA ATG CTA TCG AAG and GGC GGC CGC CTA TAA TCC TTT A using 2 X BIO-X-ACT Short Mix ( BIOLINE ) , cloned in the EcoR1 and Not1 of pUAST-Attb ( 43 ) and sequenced . Transgenic flies were created at GenetiVision Inc . ( Houston , USA ) using PhiC31 mediated transgenesis in the VK1 docking site ( 2R , 59D3 ) [50] . Testis samples from w; daGal4/+ and w; UAS-NDI1 and w; UAS-NDI1/+; da-Gal4/+ and w; UAS-AOXF6 and w; UAS-AOXF6/+; da-Gal4/+ adult flies were micro-dissected in ice-cold PBS followed by snap-freezing on dry ice . Third instar larvae from w; daGal4/+ and w; UAS-CG12079RNAi/da-Gal4 were also snap-frozen on dry ice . Q-RT-PCR was performed using standard procedures , as outlined in Text S1 , and relative RNA levels were calculated according to the ΔΔCt method . Primers are listed in Table S1 . Single males ( 30 ) of the genotypes indicated in the figure legends were crossed to 1–3 day old w1118 virgins and a score of 1 was assigned when offspring was detected . For flight assays , batches of 5 freshly eclosed male flies grown at 18°C of the genotypes indicated in the figure legends were put at room temperature for 2 days and then transferred to an empty vial ( 5 cm D , 10 cm H ) . For ‘standard testing conditions’ , flies were allowed to climb above a marked line at 9 cm height , the vial was gently tapped and visually scored for flying flies over the next minute . For more ‘stringent testing conditions’ flies were allowed to climb above a marked line at 9 cm height , and flying flies were scored immediately following tapping of the vial . Flies at the bottom were removed and the remaining flies were retested . Flies that fly twice were assigned a score of 1 , the others a score of 0 . Student's t test was used to assess the statistical differences . Five third instar larvae or five thoraces from 2–3 days-old flies were dissected and homogenized in 50 µl of 6 M guanidine-HCl 100 mM Tris and 4 mM , EDTA , pH 7 . 8 . These homogenates were snap-frozen in liquid nitrogen and then boiled for 3 min . Samples were then centrifuged and the supernatant was diluted ( 1/50 ) in extraction buffer , mixed with luminescent solution ( ATP Determination Kit , Invitrogen ) and luminescence was measured on an EnVision Multilabel Reader ( Perkin Elmer ) . Luminiscence was normalized to protein amount ( mg ) ( Bradford ) and compared to ATP standards . n = 3 . Student's t test was used to assess the statistical differences . Thoraces of adult flies were viewed under an Olympus SZX12 microscope equipped with a DF PLAPO 1X PF lens and the pictures were captured with an Olympus U-CMAD3 camera . Mitochondrial morphology in adult flight muscles of flies grown at 18°C and reared at room temperature for 2 days or in wandering third instar larvae grown at 25°C was assessed by visualizing mitochondrial tagged GFP ( mito-GFP ) , excited using 488 nm laser light and imaged on a Zeiss LSM 510 META confocal microscope using a 63×oil NA 1 . 4 lens ( for adult muscles ) or a 40×oil NA 1 . 3 lens ( for larvae ) using a 500–530 band pass emission filter . RP vesicles of larvae were labeled by electrically stimulating motor neurons of third instar larval fillets in HL-3 with 2 mM Ca2+ for 10 min at 10 Hz and then leaving the preparation to rest for 5 min in the presence of the dye following stimulation . This protocol labels the entire vesicle pool; the exo-endo cycling pool ( ECP ) and the RP . To unload the FM 1–43 from the ECP , leaving RP labeling intact , preparations were subsequently incubated for 5 min in HL-3 with 90 mM KCl and 2 mM Ca2+ ( in the absence of FM 1–43 ) [16] . Following washing in Ca2+ free HL-3 , NMJs were imaged on a Nikon FN-1 microscope with a DS-2MBWc digital camera , 40×W NA 0 . 8 objective and quantification of labeling intensity was performed using NIS-Elements AR 3 . 10 . JC-1 ( Molecular Probes ) labeling was performed on wandering third instar larvae of the genotypes indicated in the figure legends as described previously [15] . Red and green fluorescence was captured on a Nikon FN-1 microscope with a Hamamatsu ORCA-R2 , 40W NA 0 . 8 objective . Quantification of red and green labeling intensity was performed using NIS-Elements AR 3 . 10 . Complex I activity measurements were performed as described [15] . Data represent at least 3 independent experiments where mitochondrial preparations from 50 animals were prepared for each independent experiment . The Complex I enzymatic activity was normalized to Citrate Synthase enzymatic activity . | Parkinson's disease is the most common neurodegenerative movement disorder , and mutations in several genes are known to cause the disorder . A common theme among several PD–associated genes is a link to mitochondria , organelles that use their electron transport chain to generate ATP . One of the PD–associated genes encodes a mitochondrial kinase Pink1 , but it is not known what the primary role of Pink1 is within the mitochondria . Indeed , loss of Pink1 function in cells and model organisms results not only in mitochondrial morphological defects but also in an enzymatic deficit at the level of the first protein complex in the electron transport chain . Here , we express yeast Ndi1p ( an enzyme that can bypass electron transport in Complex I ) and sea squirt alternative oxidase ( an enzyme that can bypass electron transport in Complex III/IV ) in pink1 mutant fruit flies and find that supplementing the mutants with Ndi1p , but not with alternative oxidase , results in significant rescue of multiple phenotypes . Conversely , mitochondrial morphological defects in pink1 mutants are rescued by genetically improving mitochondrial fission , but this manipulation fails to improve the enzymatic deficiency at the level of Complex I . Our data thus pinpoint an important mode of action of Pink1 at the level of Complex I , and this action at least in part precedes defects at the level of mitochondrial remodeling . | [
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] | 2012 | The Yeast Complex I Equivalent NADH Dehydrogenase Rescues pink1 Mutants |
Eumycetoma is a traumatic fungal infection in tropical and subtropical areas that may lead to severe disability . Madurella mycetomatis is one of the prevalent etiologic agents in arid Northeastern Africa . The source of infection has not been clarified . Subcutaneous inoculation from plant thorns has been hypothesized , but attempts to detect the fungus in relevant material have remained unsuccessful . The present study aims to find clues to reveal the natural habitat of Madurella species using a phylogenetic approach , i . e . by comparison of neighboring taxa with known ecology . Four species of Madurella were included in a large data set of species of Chaetomium , Chaetomidium , Thielavia , and Papulaspora ( n = 128 ) using sequences of the universal fungal barcode gene rDNA ITS and the partial LSU gene sequence . Our study demonstrates that Madurella species are nested within the Chaetomiaceae , a family of fungi that mainly inhabit animal dung , enriched soil , and indoor environments . We hypothesize that cattle dung , ubiquitously present in rural East Africa , plays a significant role in the ecology of Madurella . If cow dung is an essential factor in inoculation by Madurella , preventative measures may involve the use of appropriate footwear in addition to restructuring of villages to reduce the frequency of contact with etiologic agents of mycetoma . On the other hand , the Chaetomiaceae possess a hidden clinical potential which needs to be explored .
Eumycetoma is a subcutaneous disease with a high morbidity . It is prevalent in tropical and subtropical arid climate zones , with a focus in Northeastern Africa and particularly the Sudan [1] . Patients who develop advanced mycetoma of the extremities frequently become invalids due to the immobilizing nature of the disease ( Fig . 1 ) [2] . Due to lack of social programs and poverty , patients become perpetually dependent on their family . Mycetoma can be caused by a variety of both bacteria ( actinomycetoma ) and fungi ( eumycetoma ) and is chronically progressive [1] , [2] . eumycetoma is difficult to treat by chemotherapy , surgery frequently leads to mutilation , and relapse is common postoperatively . In the Sudan alone , 25% of the eumycetoma patients underwent amputation of the infected limb because of failure of therapy [3] . In order to reduce the morbidity of this disease , not only is an improvement in chemotherapy required , but also in the preventive measures . These might involve an efficient vaccine , as well as a reduction of contact with the causative agent . Gaining insight in the natural habitat of the prevalent Sudanese agent of mycetoma , Madurella mycetomatis , may lead to strategies to prevent introduction of causative agents into the skin and should reduce the burden of this disease in the endemic communities . However , the natural habitat of the prevalent Sudanese agent of mycetoma , Madurella mycetomatis , is unknown . The classical hypothesis is that aetiologic agents are traumatically introduced via thorn-pricks or with soil particles contaminated by the aetiologic agent , but M . mycetomatis has never been cultured from either thorns or soil . Madurella DNA was demonstrated in 17 out of 74 soil samples , and only in one out of 22 thorns tested [4] . Thus , the thorn-prick hypothesis seems less likely . Madurella mycetomatis is thus far only known as sterile , melanized mycelium isolated from symptomatic patients . Isolates from subcutaneous infections that consist of dark hyphae are therefore routinely referred to as ‘Madurella’ , while those forming compact clumps of cells are traditionally identified as ‘Papulaspora’ . Still no form of propagation , either sexual or clonal , is known for these fungi , except for some occasional , undiagnostic phialide-like cells [5] . There are many more causative agents of subcutaneous disorders which lack identifiable sporulation in culture . Today , identification options of such poorly structured fungi have increased with the development of molecular diagnostics . It has become clear that non-sporulating fungi are phylogenetically quite diverse . The melanized species causing black-grain mycetoma worldwide belong to at least two different orders of ascomycetes: the Sordariales and the Pleosporales [6] . In the present study we apply morphology-independent techniques to classify sterile agents of mycetoma in a phylogenetic scaffold of the fungi . This should lead to a better understanding of their ecology and pathology . Non-sporulating clinical isolates , provisionally deposited in two reference laboratories under the generic names Madurella and Papulaspora , were analyzed using the universal fungal barcode gene rDNA partial large subunit ( LSU ) and the internal transcribed spacer ( ITS ) regions . Since Madurella mycetomatis is a member of the order Sordariales , Madurella pseudomycetomatis , M . fahalii and M . tropicana most likely belong to the same order [7] . Phylogenies based on the mitochondrial genome confirmed the relationship to the Sordariales . Shared synteny was observed of genes and tRNAs in the mitochondrial genomes of M . mycetomatis and Chaetomium thermophilum [8] . Chaetomium is a large genus of Sordariales with more than 100 described species [9] , but only very few species have been sequenced yet . In the present study we sequenced reference and additional clinical isolates of Chaetomium ( ITS and LSU ) . Further members of the family Chaetomiaceae ( Sordariales ) , including representatives of the genera Achaetomium , Aporothielavia , Chaetomidium , and Thielavia were selected to build up a framework of neighboring species to Madurella . Notably nearly all these fungi are ascosporulating only , producing elaborate fruiting bodies which cannot be expressed in human host tissue . Loss of the fruiting body thus immediately leads to sterile , Madurella-like cultures , rather than to a conidial counterpart as is the case in the majority of filamentous fungi . Comparison of ecological habitats of Chaetomiaceae was done in order to predict aspects of possible sources and routes of transmission of Madurella species .
The analysis consists of 128 strains among which 60 strains of Chaetomiaceae contain presently available ex-type strains of described species deposited in the CBS culture collection . A total of 13 sterile filamentous isolates identified as Madurella , and one meristematic isolate , phenotypically identified as Papulaspora sp . were analyzed . The set was complemented with 54 clinical strains identified in this study ( Supporting information; table S1 ) . All clinical isolates included in our study were previously isolated from human sources and were taken from the CBS reference collection . Information on strains can be found at ( www . cbs . knaw . nl ) About 10 mm3 fungal mass grown on agar surface were scraped in 2 ml screw cap vial containing 490 µl CTAB-buffer ( 2% CTAB , 100 mM Tris-HCL , 20 mM EDTA , 1 . 4 M NaCl ) and 6–10 acid washed glass beads . In the subsequent step 10 µl of proteinase K ( 50 mg/ml ) were added and the extraction buffer containing the sample vortexed for 2–5 minutes . The vials were incubated at 60°C for 60 minutes and vortexed again to ensure homogeneity of the sample . 500 µl of SEVAG ( Chloroform∶Isoamylalcohol 24∶1 ) were added and the vials inverted repeatedly for at least two minutes . Vials were centrifuged at 14000 rpm ( Eppendorf 5417R , Hamburg , Germany ) for 10 minutes and the supernatant collected in new sterile vials with 0 . 55 volumes of ice cold 2-propanol and inverted several times . The precipitated total nucleic acids were centrifuged at 14000 rpm for 10 minutes . Finally , the pellets were washed with 70% ethanol , air- dried and re-suspended in 100 µl TE buffer . The internal transcribed spacer ( ITS ) was amplified using the primers V9G and LS266 [10] . The resulting amplicons were bidirectionally sequenced with primers ITS1 and ITS4 [11] . The partial large ribosomal subunit ( 28S ) was amplified with primer LR0R and LR5 and sequenced with the same primers [12] . A life Technologies Corp . 3730XL Sanger laboratory capillary electrophoresis system was used to retrieve the sequence data . Trace files retrieved from bidirectional sequencing , were assembled and manually edited using Lasergene Seqman ( DNASTAR , USA ) . A selection of 89 strains from the total data set was used for inferring the phylogenetic tree . Sequences were aligned with MUSCLE using the EMBL-EBI web server ( http://www . ebi . ac . uk/Tools/msa/muscle/ ) . A concatenated alignment was assembled for complete ITS ( ITS1-5 . 8S-ITS2 ) and partial LSU sequences . Bayesian and maximum likelihood analysis were performed with MrBayes v . 3 . 1 . 2 [13] , and RAxML 7 . 2 . 8 respectively [14] , [15] . MrBayes was run for 1 000 000 generations; one tree was saved per 100 of generations and burn-in was set for 25% of the saved trees . The 50% majority consensus tree was calculated and the final tree was edited using MEGA v . 5 . 05 [16] . Maximum likelihood was conducted using the CIPRES website ( www . phylo . org ) , and GTR ( General Time Reversible ) model of nucleotide substitution was used; it is the only nucleotide substitution model in the RAxML software .
The analyzed data set comprised representative strains of the Chaetomiaceae [Sordariales] of both clinical and environmental origins ( Supporting information; table S1 ) . Alignment of the combined genes sequences ( ITS , LSU ) consisted of 1 , 356 total characters in which 1029 were constant and 307 were variable . In our two-gene phylogeny most basal and internal branches show high Bayesian inference posterior probability values ( BII PP ) and maximum-likelihood bootstrap support ( ML BS ) respectively ( Fig . 2 ) . However , some internal branches of the Chaetomiaceae ingroup tree ( split 0 . 88/- ) comprising several clusters , e . g . for C . atrobrunneum and C . nigricolor ( 1 . 0/100 ) , Chaetomium “sp . 1” , C . lucknowense , C . variosporum , Thielavia terricola and T . fragilis ( 0 . 96/46 ) as well as C . errectum and C . funicola ( 1 . 0/100 ) , could not be fully resolved into dichotomies . The ingroup tree comprised a monophyletic cluster with four Madurella species with 1 . 0 , 85% BII PP and ML BS , respectively , basal to Thielavia subthermophila ( 0 . 93/66 ) . Madurella clustered within a large clade containing mostly environmental Chaetomium species which were distant from the type species of Chaetomium ( C . globosum; Fig . 2 ) . Madurella fahalii was identified as the closest taxon to the Chaetomiaceae at 6 . 0% ITS divergence from Chaetomium nigricolor . Papulaspora equi , known from three clinical isolates and identified by it is ex-type strain , was resolved basal to the grade comprising the Chaetomium/Chaetomidium/Thielavia/Madurella clades . The data set contained 38 ex-type and authentic strains . Twenty-two of these were usable to define each as OTU's ( Operational taxonomical unit ) , while 16 were found to be identical to other described species defined by an ex-type isolate . Seven species , as delimited by sequence data , comprised more than one ex-type strain having identical sequences , rendering these species as provisional synonyms . Groups of isolates identified as the classical species Chaetomium globosum , described in the 19th century without deposition of live material , did not contain an ex-type strain . In total , 29 Chaetomium species were judged to be distinct at the LSU/ITS level ( Fig . 2 ) , each being separated by several point mutations . Eight strains originating from clinical resources did not show identity to any known Chaetomium species and were therefore reported as ‘unknown Chaetomium sp . ’ Three clinical isolates described as ‘Chaetomium sp . 1’ , which had provisionally been identified as ‘Papulospora sp . ’ on the basis of phenotypic characters , were found within the Chaetomium grade ( Fig . 2 , Supporting information; table S1 ) . All Achaetomium species were found to be synonyms of known Chaetomium species including ex-type strains of Achaetomium nepalense , A . thermophilum , and A . strumarium . The origins of 128 strains analyzed are summarized in table S1 ( supporting information ) . A large quantity ( 40 . 6%; n = 52 ) , were of environmental origin; about 7 . 0% ( n = 9 ) were derived from animal dung , mainly of herbivores such as antelopes , goats , elephants , hares and rodents , but also of carnivores such as foxes . A percentage of 16 . 4% ( n = 21 ) originated from soil either mixed with dung or decayed plant material , or from rhizosphere; 10 . 9% ( n = 14 ) were derived from putrid plant material . Several species ( C . globosum , C . atrobrunneum ) were repeatedly isolated from indoor environments such as mouldy rugs and mattresses . A total of 54 . 7% ( n = 70 ) of the overall analyzed strains were from clinical samples . Forty-five out of 112 Chaetomiaceae strains of Chaetomium , Chaetomidium and Thielavia were infection-related , of which 49 strains originated from humans and 5 were veterinary isolates . Five out of eight strains identified as C . atrobrunneum were obtained from deep localizations including sputum , bronchial lavages and brain . Chaetomium globosum was frequently isolated from clinical or veterinary sources ( 24 strains where information about the origin was available ) . In general , the clinical isolates were predominately isolated from the respiratory tract ( 9 . 4% , n = 12 ) , possibly as asymptomatic colonizers . A large number of strains ( 22 . 7% , n = 29 ) were isolated from superficial samples including skin , hair , nails and eyes . Five isolates ( 3 . 9% ) were derived from brain of four humans and one horse , and five ( 3 . 9% ) strains were recovered from blood and lymph nodes . Infections reported as being subcutaneous were exceptional ( 0 . 78% , n = 1 from a wound ) ; none of these were associated with production of grains in tissue . Within the Chaetomium grade , one unnamed ‘Chaetomium sp . 1’ and four Madurella species were exclusively from clinical origin . Strains of ‘Chaetomium sp . 1’ were mainly associated with eye infections . All 13 strains identified as Madurella were derived from rural patients with subcutaneous eumycetoma with grain production .
The genus Madurella , comprising the species M . mycetomatis , M . pseudomycetomatis , M . fahalii and M . tropicana , was found to cluster within the Chaetomiaceae . In contrast to Madurella , most species of this family are able to produce elaborate fruiting bodies with characteristically shaped setae and ascospores . The impressive morphology of the ascomata suggests that species should be easily distinguishable by microscopic morphology , using the available classical , richly illustrated monographs [9] , [17] . However , judging from our phylogenetic data ( Fig . 2 ) , molecular taxonomy matches poorly with morphology . At the generic level , the distinction between Chaetomium , Achaetomium , Chaetomidium and Thielavia is ambiguous , since several species of these genera clustered amidst Chaetomium species . Sometimes several ex-type strains of described taxa were found to have identical ITS sequences , suggesting that names should be reduced to synonymy . It may be concluded that molecular classification of Chaetomiaceae is significantly different from conventional taxonomy and extensive revision is needed at generic as well as at species levels . The position of Madurella as a derived clade within the family is unambiguous , and unexpected . Most members of the Chaetomiaceae lack anamorph sporulation , or some scattered , undiagnostic phialides are present at most [9] . Thus , if strains lose the ability to produce their elaborate ascomata , they cannot be recognized as a Chaetomium species by morphological means , as in Madurella . Most of the clinical Chaetomium strains analyzed in the course of this study produced ascomata in culture , but some had remained sterile . The clinical strains of Chaetomium were responsible for cutaneous or systemic phaeohyphomycoses , but never produced eumycetoma . In contrast , strains of the Madurella subcluster , with four different molecular siblings , were consistently associated with eumycetoma . They were all sterile or produced some undiagnostic , phialide-like cells . Large structures resembling fruiting bodies were occasionally observed in Madurella ( Fig . 3 ) , but these did not have the ability to produce ascospores . The Madurella clade is morphologically not so far away from remaining Chaetomiaceae , and the position of Madurella within the Chaetomiaceae thus is explainable . The clade deviates however by producing grains in host subcutaneous tissue . A consistent human pathogen is thus introduced in the family Chaetomiaceae . Traditionally , most species of the family were considered to be insignificant as agents of human disease . Of the ∼100 Chaetomium species described to date only five have repeatedly been associated with infection [5] . The majority of Chaetomium clinical strains analyzed in this study were probably transient colonizers or agents of mild superficial disorders . Twenty seven were involved in onychomycosis or cutaneous and eye infections in otherwise healthy individuals . This matches with literature data [18] , [19] . In our data , Chaetomium globosum showed a definite bias towards superficial infection , with 17 out of 29 strains analyzed ( supporting information; table S1 ) . The species is able to degrade keratin by production of extracellular keratinases [20] . Fatal , disseminated and cerebral infections by Chaetomiaceae have also been reported . In the literature about 20 deep and disseminated cases were described , nearly all in immunocompromised and severely debilitated patients [21] , [22] . Several Chaetomium-like fungi thus show rather pronounced pathology , sometimes with species-specific predilections . Grain formation in tissue by Chaetomiaceae other than Madurella is not known . A single case of chromoblastomycosis by Chaetomium funicola was reported by Piepenbring et al . [23] . The few subcutaneous cases [24] all showed hyphae in tissue rather than the compact grains of Madurella eumycetoma . In contrast to Madurella , none of the infecting Chaetomiaceae was exclusively clinical; all contained environmental strains as well . If agents of black-grain mycetoma have a relatively limited distribution in the phylogeny of Sordariales , i . e . are clustered within a single family , Chaetomiaceae , one may hypothesize that these fungi are predisposed to human infection and thus are likely to share a set of fundamental virulence factors . Many members of Chaetomiaceae have their natural habitat in soil or on mammal dung . A possible explanation of their recurrent virulence may lie in physiological properties such as growth at the human body temperature of 37°C , and the production of secondary metabolites such as inhibitors of chemokines and TNF-α [25] , [26] . Particularly the fatal brain infections , which were repeatedly reported in Achaetomium strumarium ( synonym of Chaetomium strumarium ) [27] , [28] , in C . atrobrunneum [19] , and in Thielavia subthermophila [21] , all belonging to the Chaetomiaceae , are remarkable . The hidden clinical diversity of the Chaetomiaceae urgently needs to be explored . The role of mammal dung and dung-enriched soil is one of the prime ecological niches in the order Sordariales , and this also holds true for Chaetomium [29] ( supporting information; table S1 ) . Some species in the current study exclusively grow in dung , such as Chaetomium homopilatum . Multiple Chaetomium and Thielavia species have been isolated in East Africa from different kinds of dung , ranging from cow and horse to more exotic types of dung such as of elephant and wildebeest [30] . Conversely , the position of Madurella in Chaetomiaceae is informative for the natural habitat of this pathogen . In the highly endemic area in Sudan , M . mycetomatis has as yet not been cultured , whereas the isolation of some other causative agents of mycetoma , Nocardia brasiliensis , Actinomadura madurae , and Streptomyces somaliensis has been successful [31] . The causative agent of eumycetoma Leptosphaeria senegalensis has been recovered from thorns of Acacia species in West and Central Sub-Saharan Africa [32] . Pseudallescheria boydii has been recovered from polluted soil samples all over the world , including the endemic mycetoma regions [33] , [34] , [35] . For Madurella mycetomatis numerous isolation attempts from environmental sources were without success [4] , [36] . Thirumalachar et al . [37] reported M . mycetomatis from soil in India , but the identification was based on scant phenotypic characters only . The difficulty in recovering M . mycetomatis from soil might indicate that pure soil is not the natural habitat for this fungus . Other possible habitats were thorny plant thorns , as plant material was occasionally found in human tissue [36] , but this remains exceptional . Based on our study , association with cattle dung now seems to be an alternative option . Madurella mycetomatis apparently needs other culture media for isolation . Enrichment with dung might be a successful strategy . This hypothesis may be extended to Madurella fahalii , M . tropicalis and M . pseudomycetomatis , which are endemic in the arid climate zone of Northeastern Africa and are exclusively known from human mycetoma . Providing insight into the taxonomic position and possible natural habitat of Madurella species changes our view regarding routes of infection and prevalent risk factors for human mycetoma . The Gezira region in the Sudan is highly endemic for eumycetoma by M . mycetomatis [1] . Most inhabitants live on cattle and camel husbandry and agriculture [38] . Local villages are characterized by an abundance of cattle , goats , sheep , dogs , chickens and donkeys [39] . Cows are raised mainly for their milk and are kept in pens surrounded by walls made of mud or thorny bushes . The floors of the pens are paved with dry feces , thorns and trash [39] , and some human settlements are made of dried cow dung . The family house is usually in direct contact with the pen . Inhabitants of the villages mostly are barefoot among the thorny bushes . Traumatic introduction of coprophilic fungi via thorn pricks is thus a plausible scenario . Given the low frequency of Madurella on thorns , contamination of dung and its role as an adjuvant in inoculation seems likely . If cow dung is an essential factor in inoculation by M . mycetomatis , preventative measures may involve the use of appropriate footwear in addition to restructuring of villages by stricter separation of animal husbandry and human settlement to reduce the frequency of contact with mycetoma etiologic agents . | Eumycetoma caused by Madurella mycetomatis is a common subcutaneous , mutilating fungal infection endemic in arid climate zones . Still there are many controversies on the route of infection , but traumatic inoculation of the subcutaneous tissue with the thorn or soil causative organism through minor skin trauma is a popular theory . This is due to the fact that , the origin and natural habitat of Madurella species , the prevalent mycetoma agents are still unknown . In order to predict the natural habitat of M . mycetomatis we investigated its phylogenetic relationships to species with known ecology . Two genes phylogeny based on LSU and ITS was performed for the species of the genus Madurella and representative genera from the family of Chaetomiaceae . Our findings confirmed that Madurella species are phylogenetically member of the family Chaetomiaceae . Members of this family are often found in dung and manure-enriched soil . We therefore suggest that animal dung , abundantly present in endemic villages , could be a possible niche for Madurella and plays an essential role in the onset of eumycetoma . This will help in understanding the origin of the disease and could be a base for future in depth study to investigate the presence of Madurella in dung from endemic areas . | [
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] | [
"medicine"
] | 2013 | Phylogenetic Findings Suggest Possible New Habitat and Routes of Infection of Human Eumyctoma |
Mutant forms of the Plasmodium falciparum transporter PfCRT constitute the key determinant of parasite resistance to chloroquine ( CQ ) , the former first-line antimalarial , and are ubiquitous to infections that fail CQ treatment . However , treatment can often be successful in individuals harboring mutant pfcrt alleles , raising questions about the role of host immunity or pharmacokinetics vs . the parasite genetic background in contributing to treatment outcomes . To examine whether the parasite genetic background dictates the degree of mutant pfcrt-mediated CQ resistance , we replaced the wild type pfcrt allele in three CQ-sensitive strains with mutant pfcrt of the 7G8 allelic type prevalent in South America , the Oceanic region and India . Recombinant clones exhibited strain-dependent CQ responses that ranged from high-level resistance to an incremental shift that did not meet CQ resistance criteria . Nonetheless , even in the most susceptible clones , 7G8 mutant pfcrt enabled parasites to tolerate CQ pressure and recrudesce in vitro after treatment with high concentrations of CQ . 7G8 mutant pfcrt was found to significantly impact parasite responses to other antimalarials used in artemisinin-based combination therapies , in a strain-dependent manner . We also report clinical isolates from French Guiana that harbor mutant pfcrt , identical or related to the 7G8 haplotype , and manifest a CQ tolerance phenotype . One isolate , H209 , harbored a novel PfCRT C350R mutation and demonstrated reduced quinine and artemisinin susceptibility . Our data: 1 ) suggest that high-level CQR is a complex biological process dependent on the presence of mutant pfcrt; 2 ) implicate a role for variant pfcrt alleles in modulating parasite susceptibility to other clinically important antimalarials; and 3 ) uncover the existence of a phenotype of CQ tolerance in some strains harboring mutant pfcrt .
The massive use of chloroquine ( CQ ) in the 20th century heralded substantial gains in the global fight against malaria . These advances were later lost as CQ resistance ( CQR ) arose and spread throughout malaria-endemic areas [1] , [2] . Today , CQ and the alternative first-line antimalarial sulfadoxine-pyrimethamine have officially been mostly replaced by artemisinin-based combination therapies ( ACTs ) [3] . Nevertheless , CQ continues to be widely used in parts of sub-Saharan Africa at the household level , presumably because of its ability to provide temporary relief from symptoms for patients unable to afford ACTs or other expensive drugs [4] , [5] . Recent findings also suggest the possibility of reintroducing CQ-based combination therapies into African regions where an extended hiatus from CQ use has led to the dominance of CQ-sensitive Plasmodium falciparum parasites that have outcompeted the less-fit CQ-resistant strains [6] . At the cellular level , CQ is thought to act by accumulating to low millimolar concentrations in the acidic digestive vacuole of asexual intra-erythrocytic Plasmodium parasites , wherein it interferes with the detoxification of iron-bound heme moieties produced as a result of hemoglobin degradation [7] . Clinical and epidemiological studies reveal that CQR emerged on very few occasions despite its abundant use , leading researchers to initially posit a multigenic basis of resistance [8] . This theory was challenged by the finding that CQR was inherited as a single locus in a genetic cross between the CQ-resistant Dd2 ( Indochina ) and the CQ-sensitive HB3 ( Honduras ) clones [9] , [10] . The causal determinant in this locus was ultimately identified as the P . falciparum chloroquine resistance transporter ( pfcrt ) , whose 49 kDa protein product PfCRT resides on the DV membrane [11] , [12] . Comparison of the Dd2 and HB3 sequence revealed eight point mutations that all mapped to sites within or near several of the 10 putative transmembrane domains [11] . Quantitative trait loci analysis of the HB3×Dd2 cross has revealed that mutant pfcrt from the Dd2 parent accounts for >95% of the CQ response variation among the progeny [13] . Further evidence supporting pfcrt as the primary determinant of CQR has come from studies of culture-adapted field isolates , which show extensive linkage disequilibrium surrounding the pfcrt locus in CQ-resistant isolates [14] . These data suggest that strong selective sweeps drove mutant pfcrt through P . falciparum populations across the globe , a notion also supported by more recent studies of nucleotide diversity in geographically distinct strains [15] , [16] . The PfCRT K76T mutation , ubiquitous to CQ-resistant strains , has proven to be a highly sensitive marker of CQR in vitro and is associated with a significantly increased risk of CQ treatment failure in vivo [17]–[19] . While these studies have demonstrated the primary importance of pfcrt in CQR , other evidence suggests that additional genes might contribute to the CQR phenotype . Most notably , a strain-dependent association has been demonstrated between mutant pfcrt and point mutations in pfmdr1 . This may reflect parasite physiologic adaptations to counteract the fitness cost of mutant PfCRT , or an independent role for pfmdr1 in CQR [1] , [8] , [19]–[22] . Nevertheless , even with identical pfcrt and pfmdr1 alleles , large variations in response to CQ can exist , suggestive of a secondary effect of additional parasite factors [13] , [23]–[25] . Clinically , resistance to CQ is graded by the World Health Organization ETF-LTF-ACPR system ( corresponding to early treatment failure , late treatment failure , or adequate clinical and parasitological response ) , based on the time to manifest clinical or parasitological evidence of treatment failure [26] . Studies aimed at dissecting the roles of pfcrt and pfmdr1 mutations in modulating the different grades of in vivo resistance have shown an increased risk of early treatment failure with PfCRT K76T , which in some reports is augmented with PfMDR1 N86Y [27] , [28] . However , the PfCRT K76T molecular marker cannot reliably predict CQ treatment failure , revealing moderate specificity of this marker . Discordance between in vitro parasite responses and in vivo patient outcomes following CQ treatment can be as high as 20% [17] , [29] . This discordance can be partially attributed to host and environmental factors , including patient immunity , individual pharmacokinetic differences , polyclonal infections , and limitations in obtaining repeated measurements of drug susceptibilities with patient isolates [30] . An additional explanation could be the variable presence of additional parasite determinants . We have previously adopted allelic exchange strategies to show that different mutant pfcrt alleles could confer verapamil ( VP ) -reversible CQR in a single , defined genetic background , the CQ-sensitive strain GC03 [31] . A separate transfection-based study found that pfcrt-mediated CQR in two geographically distinct strains , Dd2 ( from Indochina ) and 7G8 ( from Brazil ) , was entirely dependent on the presence of the K76T mutation [32] . These strains were chosen as they encode a PfCRT haplotype frequently observed in Africa and Asia ( Dd2 ) or in Papua New Guinea , South America and India ( 7G8 ) . Both alleles have been documented in multiple clinical trials to be highly specific for CQ treatment failures , with repeated evidence of significant selection for mutant pfcrt of either allelic type in early or late treatment failures . Frequencies of mutant alleles in those cases often attained 100% [17] , [33]–[37] . Trials were conducted in Africa , Southeast Asia , South America or the Oceanic region . Here , we have assessed the effect of mutant pfcrt on the CQ response of three CQ-sensitive strains . We also describe two isolates from French Guiana that provide clinical validation of our genetic investigations . Our data reveal the existence of a mutant PfCRT-mediated CQ tolerance phenotype in some strains of P . falciparum .
To define the impact of mutant pfcrt on CQ response in diverse genetic backgrounds , we developed an allelic exchange strategy based on a single round of homologous recombination and single-site crossover integration ( Figure 1A ) , and applied this to the CQ-sensitive P . falciparum strains 3D7 ( isolated in the Netherlands ) , D10 ( Papua New Guinea ) , and GC03 ( a progeny of the HB3×Dd2 genetic cross ) . This strategy differed from an earlier approach that required two rounds of allelic exchange to generate the desired recombinants [31] . Briefly , we constructed selectable transfection plasmids that contained a 2 . 9 kb pfcrt insert consisting of 0 . 5 kb of the endogenous 5′ untranslated region ( UTR ) , exon 1 , intron 1 , and the remaining exons 2–13 ( Figure 1A ) . This truncated 5′ UTR fragment ( termed Δ5′ ) was previously observed by luciferase assays to give insignificant levels of activity ( A . Sidhu , unpublished data ) . Single-site crossover between the pfcrt insert and the homologous pfcrt sequence upstream of codons 72–76 was predicted to replace the endogenous pfcrt gene with a recombinant allele harboring all the single nucleotide polymorphisms from the 7G8 or Dd2 pfcrt allele . Expression of this recombinant allele was driven by the endogenous full-length ( 3 . 0 kb ) 5′ UTR and a previously characterized , functional 0 . 7 kb 3′ UTR ( termed Py3′ ) from the pfcrt ortholog in Plasmodium yoelii [31] . In addition to these pBSD-7G8 and pBSD-Dd2 constructs , we also generated the control pBSD-GC03 plasmid that encoded the wild type ( WT ) pfcrt sequence in order to obtain recombinant control parasites . 3D7 , D10 and GC03 parasites were transfected with the pBSD-7G8 , pBSD-Dd2 , or pBSD-GC03 plasmids and screened monthly by PCR for homologous recombination at the pfcrt locus . With the 7G8 and GC03 alleles , integration into the pfcrt locus was first detected within 60 days of electroporation , and subsequently cloned by limiting dilution . In contrast , the Dd2 allele failed to show PCR evidence of homologous recombination even after 200 days of continuous culture in 3 separate transfection experiments , suggesting that this allele was detrimental to the growth of 3D7 and D10 parasites ( data not shown ) . Repeated efforts failed to transfect 7G8 and Dd2 pfcrt alleles into the CQ-sensitive strains MAD1 and Santa Lucia ( from Madagascar and Santa Lucia , a kind gift of Drs Milijaona Randrianarivelojosia and Dennis Kyle respectively ) , as well as HB3 . Recombinant parasites either never appeared following plasmid electroporation and drug selection , or the plasmids never integrated into the pfcrt locus . Successful transfection of the 3D7 , D10 and GC03 strains produced the recombinant mutant clones 3D77G8-1 , 3D77G8-2 , D107G8-1 , D107G8-2 , GC037G8-1 and GC037G8-2 ( all generated from the plasmid containing the 7G8 pfcrt sequence ) or the recombinant control clones 3D7c , D10c and GC03c clones ( generated with the control plasmid harboring the WT pfcrt sequence; Table 1 ) . Southern hybridization of EcoRI/BglII-digested genomic DNA samples with a pfcrt probe confirmed the expected recombinant locus , as evidenced by the loss of a 3 . 9 kb band present in the WT lines and the acquisition of 4 . 4 kb and 6 . 7 kb bands consistent with recombination in pfcrt ( results shown for the 3D7 and D10 clones in Figure 1B ) . The 7 . 2 kb bands present in 3D7C , D107G8-1 , and D107G8-2 were indicative of integration of tandem plasmid copies into the pfcrt locus . We confirmed these recombination events using PCR analyses with a 5′ UTR-specific primer ( p1 ) and an exon 5-specific primer ( p2 ) , which revealed a change in size from the 1 . 8 kb WT-specific band to a shorter 1 . 5 kb band in the recombinant controls and mutants reflecting the loss of introns 2–4 ( Figure 1C ) . The recombinant controls and mutants also showed the acquisition of PCR bands specific for the full-length functional copy of the pfcrt locus ( 2 . 2 kb , p1+p3 ) and the downstream truncated copy ( 1 . 1 kb , p4+p5 ) ( Figure 1C ) . Sequencing of these PCR products ( data not shown ) confirmed that the integration event placed the K76T mutation in the functional locus , and that the WT allele was displaced to the downstream non-functional locus . Reverse-transcriptase ( RT ) -PCR assays on synchronized ring stage RNA with primers specific to exons 2 and 5 ( p6+p2 ) produced a single band corresponding to cDNA , with no evidence of genomic DNA contamination ( data not shown ) . Sequence analysis of those products detected transcripts only from the functional recombinant locus ( under the control of the 3 . 0 kb full-length 5′ UTR ) and not from the downstream truncated locus ( data not shown ) . No endogenous WT locus was detected in any recombinant clone . To precisely assess the transcriptional status of the functional vs . the truncated pfcrt copies , we performed quantitative real-time RT-PCR utilizing primers specific for transcripts containing the Py3′ vs . Pf3′ UTRs respectively . Quantification of pfcrt steady state transcript levels was made by extrapolation from a standard curve generated from genomic DNA of D10C , which has a single copy of the pBSD-GC03 plasmid integrated into the pfcrt locus ( Figure 1B ) . Results showed that transcription from the functional pfcrt allele with Py3′ accounted for 93–95% of the total pfcrt transcript within each line ( Figure 1D ) . Western blot analysis showed that PfCRT protein levels in the recombinant 3D7 and D10 lines were 55–66% and 45–63% those observed in the parental controls respectively ( Figures 1E and 1F ) . This finding of reduced pfcrt transcript and protein expression levels following allelic exchange is consistent with earlier pfcrt transfection studies [31] , [32] , [38] . Importantly , those studies have shown that reduced pfcrt expression in recombinant lines causes a concomitant reduction in CQ IC50 values , which thus become lower than the IC50 values observed in parasites harboring non-recombinant pfcrt . In our drug assays , the IC50 value refers to the drug concentration that inhibits incorporation of [3H]-hypoxanthine , a marker of in vitro parasite growth , by 50% . Once the desired integration events were confirmed , we assessed the effect of mutant pfcrt on the CQ response in the recombinant lines . In the 3D7 background , mutant pfcrt was found to confer a 2 . 7-fold increase in CQ IC50 values ( mean±SEM CQ IC50 values of 84±14 nM and 79±11 nM for 3D77G8-1 and 3D77G8-2 respectively ) compared to the 3D7 recombinant control ( 29±2 nM , P<0 . 001; Figure 2A , Table S1 ) . These values were 2 . 4-fold lower than the IC50 values for WT 7G8 ( 190±14 nM ) . For the D10 mutants , there was no significant increase in CQ IC50 values for D107G8-1 and D107G8-2 compared to D10C ( 63±11 nM , 71±16 nM , and 45±3 nM , respectively , P>0 . 05 ) . When tested against the primary in vivo metabolite monodesethyl-chloroquine ( mdCQ ) , a significant decrease in susceptibility was found in both genetic backgrounds . The 3D7 mutant clones demonstrated a 10-fold increase in mdCQ IC50 values compared to 3D7C ( P<0 . 001 , Figure 2B ) . In comparison , the IC50 values for the D107G8-1 mutant were 5-fold higher than D10C ( P<0 . 01 , Figure 2B , D107G8-2 was not tested ) . Nevertheless , the mdCQ IC50 values in both backgrounds were approximately 2–fold lower than those observed in WT 7G8 , suggesting that mutant pfcrt was insufficient to confer high-level mdCQ resistance to 3D7 and D10 parasites . These findings of a relatively moderate , strain-dependent decrease in CQ susceptibility in the 3D7 and D10 pfcrt mutants contrasted with our earlier observation that the introduction of 7G8 mutant pfcrt in the GC03 background resulted in CQ IC50 values >100 nM [31] . To directly compare the effects of mutant pfcrt between strains , and to assess for any potentially confounding differences in our transfection strategies , we generated recombinant control ( GC03C ) and mutant clones expressing the 7G8 allele ( GC037G8-1 and GC037G8-2 ) using our single-round transfection strategy . These clones were confirmed by PCR , sequencing , and Southern hybridization , and were found to have similar levels of pfcrt RNA and protein expression compared to the 3D7 and D10 clones ( data not shown ) . In the GC03 background , introduction of the 7G8 mutant pfcrt allele increased the CQ IC50 values 4 . 7-fold ( P<0 . 001 ) , from 27±3 nM for GC03C to ∼130±8 nM for both recombinant clones ( Figure 2A , Table S1 ) , and increased the mdCQ IC50 values by 9-fold ( P<0 . 01; Figure 2B ) . These determinations included four independent assays that directly compared GC037G8-1 and GC037G8-2 with the C67G8 line . The latter was produced using our earlier pfcrt modification strategy involving consecutive rounds of allelic exchange [31] . C67G8 also expresses the 7G8 pfcrt allele in the GC03 background , yet differs from the clones produced in the current study in that C67G8 contains both the human dihydrofolate reductase and the bsd selectable markers , and lacks the 0 . 5 kb 5′UTR present in the downstream pfcrt loci in the GC037G8-1 and GC037G8-2 clones ( see Figure 1A ) . Drug assays with these lines produced CQ IC50 values of 131±7 , 129±8 and 130±7 nM for GC037G8-1 , GC037G8 and C67G8 respectively ( Table S1 ) . These results are comparable to our published data with C67G8 ( 127±17 nM; [31] ) and are consistent with both allelic exchange strategies producing the same CQ responses . Our data from all three strains also provide clear evidence that the degree of CQR conferred by mutant pfcrt is strain-dependent . We also found that the genetic background influenced the degree of VP chemosensitization , a hallmark of P . falciparum CQR [39] . In 3D7 and D10 , expression of mutant pfcrt conferred a VP reversibility of 24±1% and 28±1% ( calculated as the mean±SEM of percent reversibility for all CQ and mdCQ values ) , compared to 44±2% for GC03 ( Figure S1 ) . Notably , significant VP reversibility occurred in the D10 mutants despite the lack of a significant increase in CQ IC50 values ( Figure 2D , Table S1 ) . By comparison , VP reversibility for 7G8 CQ and mdCQ responses was 46±3% ( Figure 2B ) . This is lower than the degree of VP reversibility that results from expression of the Dd2 pfcrt allele [31] , [40] . Analysis of the dose response curves generated during these studies revealed a more complex picture than was evident from the IC50 values alone . For all three genetic backgrounds , introduction of the 7G8 mutant allele into the CQ-sensitive strains caused a pronounced change in the slope of the dose-response profiles , with evidence of continued growth at high CQ concentrations ( Figures 2C–E ) . This was particularly pronounced for the recombinant D107G8-1 and D107G8-2 lines , whose CQ IC50 values were similar to those of D10 and D10C , yet whose IC90 values ( i . e . the drug concentrations that inhibited [3H]-hypoxanthine uptake into cultured parasites by 90% ) were greatly elevated . Indeed , analysis of the CQ IC90/IC50 ratios for the lines in each genetic background revealed significant increases in the mean ratios of the mutant lines ( Figure S2 ) . For the 3D7 and D10 backgrounds in particular , the relatively modest increase in CQ IC50 values appeared to be compensated by an increased ability of these parasites to withstand high CQ concentrations . We posited that these elevated IC90 values imparted by mutant pfcrt subtly reflected a CQ tolerance phenotype . To test this , we assayed our lines for the ability to survive treatment with 50 nM CQ , a concentration that was lethal after three generations of exposure for all three WT strains , and 80 nM CQ , which substantially exceeded each of their CQ IC90 values ( Table S1 ) . Parental , control , and mutant lines were assayed for in vitro recrudescence ( defined as 50% of cultures testing positive for growth ) after a six-day exposure to CQ . The parental and recombinant control lines from the 3D7 , D10 , and GC03 backgrounds showed no signs of growth at 30 days post-exposure to 50 nM CQ ( Figures 3A and 3B ) . In contrast , 3D77G8-1 recrudesced at 9 and 13 days post-treatment with 50 nM and 80 nM CQ respectively ( Figure 2A ) . We also tested 3D77G8-1 that had been pretreated with 50 nM CQ for 3 generations approximately 30 days earlier ( 3D77G8-1/preCQ ) , and observed similar rates of recrudescence . All untreated lines were positive at day 7 , as was WT 7G8 that showed no inhibition of growth with 80 nM CQ treatment . Although the introduction of mutant pfcrt resulted in no significant increase in CQ IC50 values in the D10 background , both D107G8-1 and pretreated D107G8-1/preCQ recrudesced at days 13 and 17 with treatment with 50 nM and 80 nM CQ , respectively ( Figure 3B ) . In the GC03 background , GC037G8-1 showed no inhibition of growth at 7 days with both 50 nM and 80 nM CQ treatments , reflecting the high-level CQR phenotype imparted by mutant pfcrt in this strain . Given the evidence that mutant pfcrt was insufficient to confer CQR in all genetic backgrounds , we asked whether there were CQ-sensitive parasites harboring mutant pfcrt in the field . After an extensive search , this led to the identification of two clinical isolates from French Guiana that express the PfCRT K76T marker for CQR but are sensitive to CQ . These isolates , G224 and H209 , were harvested in 2003 and 2004 , respectively , and were genotyped at the pfcrt and pfmdr1 loci . The PfCRT haplotype of G224 was found to be identical to that of 7G8 , whereas H209 possessed a C350R mutation that has not been previously described ( Table 1 ) . Both G224 and H209 possessed a single copy of pfmdr1 with the same haplotype that differed from 7G8 only at position 1034 . Western blot analyses revealed equivalent levels of PfCRT expression compared to 7G8 ( data not shown ) . Drug susceptibility assays using CQ and mdCQ showed that these strains had low IC50 values for CQ ( mean IC50 values of 52±8 nM and 35±7 nM for G224 and H209 , respectively ) and mdCQ ( mean IC50 values of 349±46 nM and 70±9 nM ) ( Figures 4A and 4B , Table S1 ) . Further , both G224 and H209 demonstrated VP reversibility of their CQ and mdCQ response ( averaging 37% and 35% , respectively; Table S1 , Figure S1 ) . Analysis of the CQ inhibition curves revealed that the IC90 values were skewed towards the IC90 of 7G8 ( Figure 4C ) , reminiscent of the effect seen in our 3D7 and D10 mutant pfcrt lines ( Figures 2C and 2D ) . This was particularly pronounced for G224 , whose IC90 for CQ was 123±27 nM . When tested for in vitro recrudescence after a 6-day exposure to CQ , G224 recrudesced at days 11 and 17 when treated with 50 nM and 80 nM CQ respectively ( Figure 3D ) . Interestingly , H209 showed recrudescence at days 21 and 25 for 50 nM and 80 nM CQ respectively , despite having a very low CQ IC90 value of 44±7 nM . To test whether the host strain also influenced the effect of mutant pfcrt on parasite response to other drugs , particularly those currently used in ACTs , we tested our lines against quinine ( QN ) , artemisinin ( ART ) , monodesethyl-amodiaquine ( mdADQ , the potent in vivo metabolite of amodiaquine ) , lumefantrine ( LMF ) , and piperaquine ( PIP ) . The responses of the French Guiana isolates G224 and H209 were also assessed . In the 3D7 , D10 and GC03 backgrounds , we observed no effect of mutant pfcrt on QN response ( Figure 5A , Table S1 ) . Interestingly , the highest QN IC50 values were observed with H209 , which showed a moderately high level of resistance ( 405±40 nM ) . When tested against ART , introduction of mutant pfcrt showed a significant 2–fold decrease in IC50 values in the D10 and GC03 backgrounds , when compared to recombinant clones expressing WT pfcrt ( P<0 . 05 and P<0 . 01 respectively; Figure 5B ) . 3D77G8-1 also yielded a 33% lower ART IC50 compared to the 3D7C control , however this did not attain statistical significance ( P = 0 . 06 ) . Again , the highest ART IC50 values were observed with H209 ( Table S1 ) . For mdADQ , 3D77G8-1 had a 1 . 5-fold increase in IC50 value compared to 3D7C ( P<0 . 05 ) , and GC037G8-1 showed an even more pronounced ( 2 . 6-fold ) increase compared to GC03C ( P<0 . 01; Figure 5C ) . There was no effect of mutant pfcrt on mdADQ response in the D10 background . With this drug , G224 and H209 were both moderately resistant , as was 7G8 . Introduction of mutant pfcrt was also found to confer significantly increased sensitivity to LMF in all three strains , equating to a 23% , 44% , and 35% decrease in IC50 values for the 3D7 , D10 , and GC03 backgrounds respectively ( Figure 5D ) . H209 was also found to be less susceptible to LMF than was G224 , mirroring their responses to QN and ART . Finally , we found that mutant pfcrt had a significant effect on PIP response only in the D10 background , in which D107G8-1 was 1 . 7-fold less sensitive than D10C ( P<0 . 05 ) . G224 and H209 were found to be 2 . 7- and 1 . 7-fold more sensitive to PIP when compared to 7G8 .
Here , we provide evidence that the genetic background of P . falciparum determines whether expression of mutant pfcrt allele confers a full CQR phenotype , as defined by CQ IC50 values that exceed the in vitro CQR threshold [30] , or instead mediates increased tolerance to CQ , as evidenced by dose-response shifts manifesting primarily at the IC90 level . All our recombinant clones expressing mutant pfcrt recrudesced in vitro after being exposed for three generations to concentrations of CQ that were uniformly lethal to CQ-sensitive parasites; however the rate of recrudescence varied with the genetic background . The GC03 mutant lines , which had the highest CQ IC50 values , showed no growth inhibition . In contrast , the pfcrt-mutant lines generated in the 3D7 and D10 backgrounds , as well as the clinical isolates G224 and H209 , required 1–3 weeks for the detection of recrudescent parasites . Based on our findings , we propose that IC50 values , which typically constitute the sole measurement of CQ response in vitro , adequately identify high-level CQR but are insufficient to detect strains that have low-level resistance or manifest tolerance to CQ . Instead , our data suggest that accurate determinations of IC90 values provide a more predictive measure of whether parasites can recrudesce in the presence of CQ concentrations that are lethal to drug-sensitive parasites , a trait that we here refer to as CQ tolerance . Tolerance is also apparent in decreased parasite susceptibility to the primary drug metabolite mdCQ . We posit that pfcrt-mediated CQ tolerance might be an important component of late treatment failures in patients . These are classified as cases where symptoms occur during a follow-up period of 4–28 days post CQ treatment , or asymptomatic infection appearing 7–28 days post-treatment ( see the WHO 2006 publication on malaria treatment: http://whqlibdoc . who . int/publications/2006/9241546948_eng_full . pdf ) . In contrast , early treatment failures might result more often from infections with parasites in which mutant pfcrt exerts a higher degree of CQR . Early treatment failures are classified as the development of clinical or parasitological symptoms during the first three days following CQ treatment . We note that clinically , care must be taken when evaluating early failures , as these can also include patients that respond relatively slowly to treatment yet progress to full cure . Moreover , the joint effects of low-level CQ resistance reported here and acquired protective immunity might help explain why CQ treatment can successfully cure some infections harboring mutant pfcrt parasites in semi-immune individuals [1] , [18] . The importance of immunity in shaping the host's ability to resolve drug-resistant infections harboring mutant pfcrt was first demonstrated in work from Mali that found that successful CQ treatment of pfcrt mutant parasites was strongly dependent on age , a known surrogate for protective immunity in endemic areas [18] . These data complement other observations in the malaria literature indicating that the immune response can allow a relatively ineffective drug to clear an infection , and even at times clear infections without therapy [41] , [42] . Our data extend these reports by suggesting that successful CQ treatment of drug-resistant parasites is dependent both on the level of host immunity and the strain-dependent extent to which mutant pfcrt imparts CQR . A review of our CQ IC50 data reveals a relatively weak effect of mutant pfcrt , which attained the widely used in vitro CQR threshold of 80–100 nM only for GC03 ( Figure 2 , Table S1 ) . This threshold , however , was based on studies with field isolates [30] and does not readily extrapolate to our pfcrt-modified parasite lines . Our data ( Figure 1 ) show that these lines underexpress pfcrt , a consequence of allelic exchange into this locus that was earlier shown to cause artificially low CQ IC50 values whose level of reduction was concordant with the degree of reduced expression [31] , [32] , [38] . In our current study , the importance is not the absolute levels of CQR that we measured , but rather the finding that the genetic background of CQ-sensitive strains dictates a spectrum of mutant pfcrt-mediated changes in CQ response that ranges from tolerance to high-level resistance . We note that our data were obtained with the 7G8 pfcrt allele , which is known to have appeared independently in South America and the Oceanic region in or near Papua New Guinea and has recently spread throughout India [43] . The 7G8 haplotype ( C72S/K76T/A220S/N326D/I356L ) shares only two mutations ( K76T/A220S ) with the Dd2 haplotype ( I74E/N75E/K76T/A220S/Q271E/N326S/I356T/R371I ) that is common to Africa and SE Asia [11] , [14] , [44] . Our earlier allelic exchange studies on recombinant lines generated in the GC03 strain found that the 7G8 pfcrt haplotype confers a lower degree of resistance than that imparted by the Dd2 allele ( averaging 15% and 45% less or CQ and mdCQ respectively ) . This was consistent with the intrinsic differences observed between the parental 7G8 and Dd2 strains [31] . It is possible that in the D10 and 3D7 strains , higher degrees of resistance might have been observed with the Dd2 allele , however we were unable to test this . We note that D10 originates from Papua New Guinea where the 7G8 allele is highly prevalent , and our lack of success with introducing the Dd2 pfcrt allele into either this strain or 3D7 suggests a physiologic context that precludes expression and normal viability . Other evidence of a fitness cost imparted by the Dd2 allele comes from studies in Malawi showing that this allele is progressively lost from the parasite population in the absence of sustained CQ pressure [45] , [46] . Field studies have sometimes reported discordance in the association of K76T and in vitro CQR , suggesting the contribution of other genetic loci [24] , [47]–[49] . However , the interpretation of these results has been confounded by potential inaccuracies stemming from measuring one-time drug responses from frequently polyclonal fresh patient isolates . Our study provides , to the best of our knowledge , the first report of culture-adapted , monoclonal isolates that harbor mutant pfcrt and that , based on multiple drug susceptibility assays , show low CQ IC50 values that fail to meet the standard criteria for CQR . These findings , obtained with the G224 and H209 isolates from French Guiana , therefore provide indisputable evidence that mutant pfcrt is insufficient to confer CQR to all genetic backgrounds . Nevertheless , both isolates exhibited tolerance to high CQ concentrations and recrudesced under CQ pressure . Microsatellite typing revealed a close genetic similarity between G224 and 7G8 ( Table 1 ) , with the exception of the residue at PfMDR1 position 1034 that could potentially affect CQ response [22] , [50] . Of particular interest , H209 was highly sensitive to CQ and yet demonstrated delayed recrudescence ( Figure 4 ) . This might in part be attributable to the PfCRT C350R charge substitution in transmembrane domain 9 , a region postulated to function in substrate binding and translocation [51] . Studies are underway to introduce the H209 pfcrt allele , encoding the C350R mutation , into GC03 parasites to compare these to the GC037G8 parasites whose expressed pfcrt allele differs only at codon 350 ( Table 1 ) . We note that an adjacent charge substitution at residue 352 ( Q352K/R ) was previously selected by QN pressure in a CQ-resistant line , with a concomitant reversion to CQ-sensitivity [52] . The H209 line also showed elevated IC50 values for QN , as well as ART , when compared to G224 and 7G8 ( Figure 4 ) . Of note , QN-doxycycline , and more recently artemether-LMF , have been implemented as first line antimalarials in French Guiana since the cessation of CQ use for the treatment of P . falciparum malaria in the mid 1990s [53] . Indeed , a recent report from French Guiana documented the existence of several field isolates with elevated artemether IC50 values ( >30 nM in 7 of 289 isolates ) , suggesting decreased susceptibility to this agent [54] . G224 was tested at that time and found to have an artemether IC50 value of ∼1 nM . H209 , which yielded artemisinin IC50 values two-fold higher than G224 ( Table S1 ) , was isolated one year later . Our subsequent studies reveal comparable IC50 values between these two lines with the more potent clinical derivatives artemether , artesunate and artemether ( values provided in Table S1 ) . ACTs are rapidly assuming the role of first line antimalarials around the world [55] . Our studies with isogenic pfcrt-modified lines confirm previous reports that mutations in PfCRT can significantly affect parasite susceptibility to many of the antimalarials that constitute these ACTs [19] , [56] , and provide evidence that for certain drugs this effect is strain-dependent ( Figure 5 ) . In the case of the fast-acting ART , all three strains displayed enhanced susceptibility upon introduction of mutant pfcrt . With the amodiaquine metabolite mdADQ , elevated IC50 values were noted in two of the three recipient strains , supporting earlier epidemiological evidence that mutant PfCRT might contribute to a multigenic basis of amodiaquine resistance ( [57]–[59]; see below ) . The opposite effect was observed with the bisquinoline PIP , which is highly effective against CQ-resistant strains of P . falciparum [60] , and for which we observed a strain-dependent increase in susceptibility . For LMF , significantly enhanced susceptibility was observed in all three genetic backgrounds , supporting recent field studies [59] , [61] . The generally enhanced potency of LMF and artemisinin derivatives against mutant pfcrt parasites bodes well for the widely used LMF-artemether co-formulation . The enhanced susceptibility conferred by the mutant pfcrt 7G8 allele to the ACT partner drugs LMF and PIP , but not amodiaquine , has potentially important implications in regional antimalarial drug policy . Our pfcrt and CQ data speak to a requirement for additional parasite factors that , at least in some strains , either augment the level of PfCRT-mediated CQR or on the contrary , create an intracellular physiologic environment in which PfCRT is unable to exert its full capacity to dictate CQR [62] , [63] . pfmdr1 would appear to be one gene that contributes to this strain-dependent effect . Transfection-based studies have shown that in CQ-resistant strains that harbor mutant pfcrt , mutations in pfmdr1 can contribute to elevated CQ IC50 values , but only in a subset of strains . Mutant pfdmr1 alone shows no effect on CQ response in sensitive parasites harboring wild-type pfcrt [19] , [20] . Evidence from CQ treatment trials in African , Southeast Asia and the Oceanic region show that mutant pfmdr1 is associated with an increased risk of CQ treatment failure , however this risk is usually substantially higher in the presence of mutant pfcrt [17] , [28] , [36] , [64] , [65] . Of note , while mutant pfcrt is virtually ubiquitous to CQ treatment failures , mutant pfmdr1 is often absent ( [65] and references therein ) . Functional assays have yet to be developed to test whether pfmdr1 can directly reduce drug toxicity , or instead is associated with CQR because of its non-random association with mutant pfcrt , which potentially could relate to improved parasite fitness [66] . We note that in our study , pfmdr1 cannot account for differences in the extent to which mutant pfcrt affects CQ response , as both the resistant 3D7 and the tolerant D10 mutants ( 3D77G8 and D107G8 respectively ) share the same wild-type pmfdr1 haplotype ( Table 1 ) . The highly resistant GC03 mutants ( GC037G8 ) differ in having the pfmdr1 N1042D mutation that in allelic exchange studies had no impact on CQ response ( although it did affect a number of other antimalarials including QN , mefloquine and ART; [21] ) . Clear evidence that mutant forms of PfCRT and PfMDR1 can combine in a region-specific manner to create higher levels of drug resistance comes from the recent study by Sa et al . [67] , showing that the 7G8 South American haplotypes of these two determinants produce high-level resistance to mdADQ . This study also found that the Asian/African Dd2 haplotype of PfCRT was associated with high level CQR with minimal apparent contribution from variant PfMDR1 haplotypes . Why has no gene other than pfmdr1 been found associated with CQR ? In the case of the HB3×Dd2 genetic cross where mutant pfcrt was clearly the primary determinant , evidence that modulatory factors must exist was provided by the 2 . 7-fold spread in CQ IC50 values observed among the CQ-resistant progeny [13] . Such factors may be present within the 36 kb CQR-associated linkage group harboring pfcrt [10] , [68] , or potentially might already be present in the HB3 parent , thereby rendering this competent for CQR and masking the inheritance of a secondary determinant [8] . To test the latter hypothesis , we attempted to introduce mutant pfcrt into the HB3 strain , but were unable to obtain integrants in three independent transfection experiments ( data not shown ) . Independent genomic approaches analyzing linkage disequilibrium in CQ-resistant isolates have also failed to identify any gene besides pfcrt [14]–[16] , [69] , as elaborated upon below . The genetic identity of these secondary determinants associated with CQR may reflect the geographic distribution of distinct PfCRT haplotypes around the globe [19] . Indeed , the PfCRT 7G8 haplotype found in South America and the Pacific is typically associated with PfMDR1 N1042D/D1246Y ( ±S1034C ) , whereas the PfCRT Dd2 haplotype common to Asia and Africa is often associated in CQ-resistant isolates with PfMDR1 N86Y [43] , [50] . Identifying additional genetic determinants has been complicated by the complexity of performing genome-wide association studies with large numbers of culture-adapted parasite lines from different geographic regions and comparing these to parasite drug responses [50] , [70] . Major advances have recently been achieved in a seminal study by Mu et al . [69] , who performed genome-wide association studies with a 3 , 000 single nucleotide diversity array probed with DNA from189 culture-adapted P . falciparum lines from Africa , Asia , Papua New Guinea and South America , and compared their genetic diversity with CQ response . When accounting for local population structures , the authors found associations between CQ response and changes in pfcrt , pfmdr1 , and surprisingly a putative tyrosine kinase ( PF11_0079 ) . These associations could only readily be discerned in African populations where a sufficient number of CQ-sensitive strains could be identified; as opposed to South American , Asian and Papua New Guinean strains where mutant pfcrt remained at a high prevalence . Of the genes listed above , pfcrt stood out as being one of handful of genes in the parasite genome that were apparently under very substantial selection pressure in all three populations studied - Asia , Africa and South America . No other genes were convincingly associated with CQR , even though a number of genes potentially involved in drug transport ( including the putative drug/metabolite transporter PF14_0260 , and the ABC transporters PF13_0271 and PFA0590w ) were found to be under lesser selection pressure in local populations . We note that evidence of selection was also observed in genes adjacent to pfcrt , although these may simply represent genetic hitchhiking and insufficient time for genetic recombination to have disrupted these associations . Our conclusion from these studies is that mutant pfcrt has been the dominant genetic force that has driven CQR across the globe , with some degree of participation from mutant pfmdr1 , and that even the phenotype of CQ tolerance observed herein in D10 parasites expressing mutant pfcrt would appear sufficient to confer substantial levels of viability during a course of CQ treatment . This level of protection against drug onslaught , while appearing modest in vitro , appears to have sufficed for selection and rapid mobility through parasite populations subjected to CQ treatment . Experiments to define secondary determinants that can augment CQR would require , as an example , deeper sequence coverage of the set of 189 genotypically and phenotypically characterized isolates mentioned above [69] , followed by quantitative trait loci analysis that computationally subtracted the dominant effect of pfcrt to identify potential residual associations in local parasite population structures . Other hypothesis-driven approaches to identify secondary parasite factors could involve investigations into the function of mutant PfCRT and the cellular basis of CQ mode of action . Recent studies based on heterologous expression of codon-harmonized , surface-expressed PfCRT in Xenopus laevis oocytes have recently provided compelling evidence that mutant PfCRT can transport CQ [71] , a finding consistent with earlier evidence from Pichia pastoris and Dictyostelium discoideum [72] , [73] . The Xenopus study also identified peptides that could interfere with transport of radiolabeled CQ through mutant PfCRT , raising the possibility that PfCRT is involved in transport of certain peptide sequences out of the DV and into the cytoplasm ( [74] and references therein ) . Secondary factors could potentially alter the kinetics of peptide production ( resulting from hemoglobin proteolysis in the DV ) or their translocation into the parasite cytosol and subsequent conversion into amino acids that can be incorporated into newly synthesized proteins . Other potential factors could relate to the tri-peptide glutathione ( GSH ) and redox regulation . Interestingly , an earlier study by Ginsburg and colleagues reported that altering the intracellular levels of GSH caused a corresponding shift in CQ susceptibility in P . falciparum [75] . Work from these authors led to the hypothesis that GSH could degrade iron-bound heme ( a toxic byproduct of hemoglobin degradation ) that might be released into the parasite cytosol as a result of CQ action [76] . Further support for a relationship between GSH and levels of CQR was recently obtained following the genetic disruption of the P . falciparum gene PfMRP ( PFA0590w ) , whose ABC transporter product has been localized to the parasite surface . These knockout parasites , generated in the CQ-resistant W2 strain , accumulated more radioactive GSH and CQ and became less resistant to CQ as well as several other antimalarials [77] . Indirect additional evidence of a potential link between CQR and GSH comes from the recent report that PfCRT homologs in Arabidopsis thaliana can mediate GSH transport when assayed in Xenopus oocytes [78] . Collectively , these data suggest that GSH homeostasis is related to CQR , and possibly to PfCRT , in a strain-dependent manner . A multifactorial , and potentially region-specific basis for these differences would have precluded their identification to date . Further investigations into parasite cell biology , employing genomic , proteomic and metabolomic studies to compare CQ response phenotypes within regional populations , are warranted to identify these molecules and their determinants . French Guinea may well provide an ideal set of geographically restricted isolates in which to define these factors , because of its complex history of antimalarial drug usage and the existence of mutant pfcrt strains with both resistance and tolerance phenotypes .
Informed consent was not required for this study as the collection of samples from malaria patients for drug susceptibility testing are part of the French national recommendations for the care and surveillance of malaria . As the Pasteur Institute French Guiana laboratory is the regional malaria reference center , blood samples are sent to the laboratory by practitioners ( from health centers , private medical offices and hospitals ) for drug susceptibility testing , as part of the national regular medical surveillance . This included in vitro drug susceptibility testing and assessments of molecular markers . This research is mandated by the French Ministry of Health , and has been approved by the Institutional Review Boards of the Pasteur Institute in Paris and in French Guiana . pfcrt plasmid inserts were assembled from two contiguous sequences . The first 800 bp sequence , spanning 0 . 5 kb of the pfcrt 5′ UTR ( denoted Δ5′ ) through to the intron 1/exon 2 junction ( nucleotides 22960–23747 of the GenBank accession number AF030694 ) , was amplified from Dd2 genomic DNA with the primers p251 and 10AE1-3′A ( a list of these and all other primers used in this study is provided in Table S2 ) . A 2 . 1 kb fragment corresponding to pfcrt exons 2–13 and the 3′ UTR of the P . yoelii ortholog pycrt ( termed Py3′ ) was released following AvrII/BamHI digestion of the plasmids pBSD/AE123 -7G8 , -GC03 , and -SC01 ( the latter has the Dd2 sequence ) [31] ) . These two sequences were assembled in pCR2 . 1 ( Invitrogen ) to generate a 2 . 9 kb pfcrt fragment containing Δ5′ , exon 1 , intron 1 , exons 2–13 , and Py3′ . This insert was subcloned as a SacII/BamHI fragment into the pCAM-BSD transfection plasmid . This plasmid expresses the bsd selectable marker , which is under control of a 0 . 6 kb P . falciparum calmodulin ( cam ) 5′ UTR and a 0 . 6 kb P . falciparum hrp2 3′ UTR . The resulting 7 . 2 kb plasmids were designated pBSD-7G8 , pBSD-GC03 , and pBSD-Dd2 . The P . falciparum 3D7 , D10 , and GC03 strains were cultured in human erythrocytes , transfected as described [21] , and selected with 2 . 0 mg/ml blasticidin HCl ( Invitrogen ) . Upon integration , recombinant parasites were cloned by limiting dilution and identified using Malstat assays [31] . The isolates from French Guyana were collected from malaria patients referred to the reference malaria laboratory of the Pasteur Institute of Guyana , in Cayenne , France . Each year this work was reviewed and approved by the Pasteur Institute Surveillance Committees of Guyana and Paris . The institutional review board of the Columbia University Medical Center also reviewed and approved the P . falciparum culture work . PCR-based detection of plasmid integration into transfected parasites ( Figure 1 ) used the pfcrt 5′ UTR-specific primer p1 , the pfcrt exon 5-specific primer p2 , the Py3′-specifc primer p3 , the pfcrt intron 2-specific primer p4 , and the plasmid-specific primer p5 . For Southern blot analysis , 1 µg of DNA was digested with EcoRI/BglII , electrophoresed , and transferred onto nylon membranes . Hybridizations were performed with a hexamer-primed [32P]-labeled probe prepared from the 0 . 8 kb fragment spanning Δ5′ , exon1 and intron 1 , and released following SacII/AvrII digestion of the transfection plasmid pBSD-Dd2 . The full-length sequence of pfcrt was determined from the complete coding sequence amplified from cDNA using the primers p251+BB116C and sequenced internally with the primers CF5C , BB84 , AF12 , AB22 , AB25 , and BB116B . For sequencing of the upstream pfmdr1 polymorphic residues at positions 86 and 184 , genomic DNA was amplified with the primers p423+p231 , and the resulting 0 . 7 kb products were sequenced with p231 . For the downstream polymorphic residues at positions 1034 , 1042 , and 1246 , the 0 . 8 kb amplification product of p426+p215 was sequenced with p238 . pfmdr1 copy number was measured by Taqman quantitative real-time PCR and quantified with the ΔΔCt method as described elsewhere [79] . Genomic DNA samples were run twice in triplicate . The expression of pfcrt in the recombinant clones was assessed by quantitative real-time PCR assays performed with the QuantiTect SYBR Green PCR Kit ( Qiagen ) on an Opticon2 ( BioRad ) . Expression from the different alleles ( endogenous and genetically introduced ) was analyzed utilizing primers specific for the two different 3′ UTRs , designated Py3′ and Pf3′ . For the loci containing Py3′ , the primers p1752 and p1753 were used to generate a 182 bp amplicon . For the locus containing Pf3′ , a 191 bp amplicon was generated using the primers p1754 and p1756 . PCR conditions were optimized so that the relative efficiencies of the Pf3′ and Py3′ amplifications were equal . Reactions were performed in 25 mL volumes with 300 nM of each primer , 3 mM Mg2+ , and 1/80th of the oligo ( dT ) primed cDNA generated from 1 . 5 µg of total RNA . As a control for each sample , a 150 bp amplicon of β-actin was amplified using the primers A129 and A130 , using the same conditions as for Py3′ and Pf3′ except that the Mg2+ concentration was 3 . 5 mM . All amplifications were performed with 15 minutes of hot start at 95°C , followed by 40 cycles of denaturing for 30 seconds at 95°C , annealing for 30 seconds at 49°C , and extension for 30 seconds at 62°C . Melting curve analysis was performed for each assay to verify that a single melting peak was produced , indicating a single specific PCR product for each reaction . A standard curve for each reaction was generated with 10-fold serial dilutions of genomic DNA , spanning the range of 5 to 5×105 genome copies ) . This genomic DNA was prepared from D10C , a recombinant clone shown by Southern hybridization to have a single copy of each locus ( Py3′ and Pf3′ , Figure 1B ) . Each sample was run in triplicate on three separate occasions . Protein extracts were prepared from sorbitol-synchronized trophozoite-stage parasites . For each sample , protein from ∼1×106 parasites was loaded per well , electrophoresed on 12% SDS-PAGE gels , and transferred onto polyvinylidene difluoride membranes . Membranes were probed with rabbit anti-PfCRT antibodies ( diluted 1∶2 , 500 ) [11] , followed by incubation with horseradish peroxidase-conjugated donkey anti-rabbit IgG ( 1∶10 , 000; Amersham Biosciences ) . Rabbit anti-PfERD2 antibodies ( diluted 1∶1 , 000 ) [80] were used as an independent loading control . Bands were visualized by enhanced chemiluminescence ( Amersham Biosciences ) and quantified by densitometric analysis of autoradiograph data using NIH ImageJ 1 . 38× ( http://rsb . info . nih . gov/ij ) . PfCRT band intensities were normalized against the PfERD2 bands to correct for minor differences in protein loading . Parasite susceptibilities to antimalarial drugs were measured in vitro by [3H]-hypoxanthine incorporation assays , as described [81] . Briefly , predominately ring-stage cultures were seeded in duplicate in 96-well plates at 0 . 4% parasitemia and 1 . 6% hematocrit . Parasites were exposed to a range of drug concentrations , or no drug controls , for 72 hr , with 0 . 5 µCi per well of [3H]-hypoxanthine added at the 48 hr time point . IC50 and IC90 values were extrapolated by linear regression , as described [81] . Compounds were tested in duplicate on 4–11 separate occasions for CQ and mdCQ and 3–12 separate occasions for the other drugs . In some assays , VP was included at 0 . 8 µM final concentration . Statistical analyses comparing mutant pfcrt-modified lines against recombinant control lines of the same genetic backgrounds were performed using one-way ANOVA with a Bonferroni post-hoc test for CQ and mdCQ , or unpaired student t tests for quinine ( QN ) , artemisinin ( ART ) , monodesethyl-amodiaquine ( mdADQ ) , lumefantrine ( LMF ) , and piperaquine ( PIP ) . Parasites were assayed for their ability to grow under short-term exposure to high CQ concentrations . Predominately ring-stage cultures were seeded in 96-well plates at 0 . 2% parasitemia and 1 . 6% hematocrit . Parasites were exposed for 6 days to no drug , 50 nM CQ , or 80 nM CQ , with daily media changes . Drug pressure was then removed on day 7 and parasite growth was measured using Malstat assays ( [31] ) . From days 7 through 30 , media changes and Malstat assays were performed every two days , and the cultures cut 1∶2 into fresh erythrocytes weekly until the detection of positive wells . As part of this experiment , cultures of 3D77G8-1 and D107G8-1 were exposed to 50 nM CQ for 6 days and maintained until parasites became microscopically detectable , at days 15 and 20 respectively . These CQ-pretreated cultures were assayed for recrudescence alongside 7G8 , 3D7C , 3D77G8-1 , D10C , D107G8-1 , GC03C , and GC037G8-1 . Data were pooled from two independent experiments in which each line was assayed in duplicate for the no drug controls and in triplicate for the 50 nM and 80 nM CQ treatments . These were performed as described [82] , with minor modifications . Briefly , 100 µL of Malstat reagent was added to 50 µL of culture supernatant and incubated for 1 hr . Absorbance at 595 nM was measured on a VICTOR3 Multilabel Plate Reader ( Perkin-Elmer ) . Wells positive for parasite growth were identified based on absorbance values greater than twice those obtained from control wells with uninfected erythrocytes . Positive wells were verified by microscopic evaluation of Giemsa-stained thin smears . pfcrt: MAL7P1 . 27; pfmdr1: PFE1150w; pycrt: PY05061; b-actin: PFL2215w . Pfmrp: PFA0590w . All numbers are from www . plasmodb . org . | Plasmodium falciparum resistance to the antimalarial drug chloroquine has been found to result primarily from point mutations in PfCRT , which provide a highly sensitive marker of in vivo treatment failure and in vitro resistance . Debate has nonetheless continued about the singular role of mutant PfCRT and the contribution of the parasite genetic background . To address this , we have generated recombinant P . falciparum lines expressing a mutant pfcrt allele , or the reference wild type allele , in three distinct chloroquine-sensitive strains . Their analysis reveals a spectrum of responses ranging from high-level resistance to a previously unrecognized tolerance phenotype . The latter is characterized by virtually unchanged chloroquine IC50 values , significantly elevated IC90 values , and the ability to recrudesce after exposure to drug concentrations that are lethal to chloroquine-sensitive parasites . This tolerance phenotype was also observed in an isolate from French Guiana , confirming its presence in malaria-endemic regions . Mutant PfCRT significantly affected parasite responses to other antimalarials , including ones used in artemisinin-based combination therapies , in a strain-dependent manner . Our data suggest that successful CQ treatment of drug-resistant parasites is dependent on both host immunity and the strain-dependent extent to which mutant pfcrt imparts resistance . | [
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] | 2010 | Identification of a Mutant PfCRT-Mediated Chloroquine Tolerance Phenotype in Plasmodium falciparum |
Cryptococcus neoformans is the most common cause of fungal meningoencephalitis in AIDS patients . Depletion of CD4 cells , such as occurs during advanced AIDS , is known to be a critical risk factor for developing cryptococcosis . However , the role of HIV-induced innate inflammation in susceptibility to cryptococcosis has not been evaluated . Thus , we sought to determine the role of Type I IFN induction in host defense against cryptococci by treatment of C . neoformans ( H99 ) infected mice with poly-ICLC ( pICLC ) , a dsRNA virus mimic . Unexpectedly , pICLC treatment greatly extended survival of infected mice and reduced fungal burdens in the brain . Protection from cryptococcosis by pICLC-induced Type I IFN was mediated by MDA5 rather than TLR3 . PICLC treatment induced a large , rapid and sustained influx of neutrophils and Ly6Chigh monocytes into the lung while suppressing the development of eosinophilia . The pICLC-mediated protection against H99 was CD4 T cell dependent and analysis of CD4 T cell polyfunctionality showed a reduction in IL-5 producing CD4 T cells , marginal increases in Th1 cells and dramatic increases in RORγt+ Th17 cells in pICLC treated mice . Moreover , the protective effect of pICLC against H99 was diminished in IFNγ KO mice and by IL-17A neutralization with blocking mAbs . Furthermore , pICLC treatment also significantly extended survival of C . gattii infected mice with reduced fungal loads in the lungs . These data demonstrate that induction of type I IFN dramatically improves host resistance against the etiologic agents of cryptococcosis by beneficial alterations in both innate and adaptive immune responses .
Cryptococcocal meningoencephalitis is one of the most important AIDS-associated opportunistic infections with an estimated global burden of nearly one million cases with more than 600 , 000 deaths annually [1] . In fact , the disease is an AIDS defining illness in patients with late-stage HIV infection , particularly in Sub-Saharan Africa and Southeast Asia [1 , 2] . It is thought that the susceptibility of HIV+ individuals to C . neoformans infection is primarily due to the depletion of CD4 T cells , which leads to defects in both innate and adaptive immunity [3–5] that predispose to opportunistic infections [6 , 7] . Indeed , more than 75% of AIDS associated cryptococcosis cases develop in the late-stage of HIV infection when the CD4+ T-lymphocyte count falls below 50 cells/μl [8] , and in experimental animal models CD4 T cell deficiency results in defective control of C . neoformans infection [9–11] . Apart from CD4 T cell depletion , there are many other immunological phenomena that may impact on the ability of the host to control opportunistic infections such as C . neoformans infection . In particular , large amounts of type I IFNs are produced in response to HIV or SIV infections , which are required to induce potent innate antiviral defense pathways to control viral replication [12–14] and modulate the function of a variety of immune cell types [15 , 16] . Type I IFN has also been demonstrated to have major effects on the outcomes of bacterial , parasitic and fungal infections [17] . Type I IFN induction , for example , enhanced the susceptibility of mice to infection with Listeria monocytogenes [18 , 19] Streptococcus pneumoniae [20] and Mycobacterium tuberculosis [21 , 22] while the opposite was reported for Mycobacterium avium infection [23] . Study of this cytokine pathway in fungal infection has been relatively limited , and the contribution of type I IFNs to antifungal immunity has been reported to be either beneficial or detrimental depending on the fungal species [24–28] . In Candida albicans infection , type I IFN signaling was reported as required for induction of reactive oxygen intermediates necessary for killing of yeast cells by phagocytic cells [29] , while in another study IFN signaling caused no change in fungal burden but resulted in lethal immunopathology [26] . In in vitro experiments , type I IFNs skewed Candida-induced inflammation from a Th17-response toward a Th1-response suggesting that the type I IFN pathway is a main signature of Candida-induced inflammation [30] . Type I IFN signaling was also reported to be detrimental for host defense against C . glabrata [27] and Histoplasma capsulatum [24] but protective in mice infected with Aspergillus fumigatus [25 , 31] . Therefore , the innate antiviral inflammatory response against HIV infection associated with type I IFNs could also dramatically impact on the ability of the host to contain opportunistic infections , but this possibility has received much less attention . Polyinosinic-polycytidylic acid ( poly-IC ) , a double-stranded RNA ( dsRNA ) virus mimic , can be used in experimental models to stimulate enhanced production of type I IFNs . Poly-IC condensed with poly-L-lysine and carboxymethylcellulose ( pICLC , Hiltonol ) is a stabilized version of poly-IC , which is designed to stimulate prolonged , high-level production of type I IFN [32 , 33] and is available for investigation in humans [34] . Ds RNA can be recognized by two major pattern recognition receptors , Toll-like receptor 3 ( TLR3 ) and the melanoma differentiation-associated protein-5 ( MDA5 ) [34] . TLR3 is located in the endosomal compartment and senses the dsRNA following its internalization through endocytosis , whereas MDA5 , which is a cytosolic sensor protein , recognizes the pICLC that penetrates into the cytosol [35 , 36] . Upon pICLC recognition , TLR3 signaling occurs by recruiting the adaptor protein TRIF ( Toll/IL1 resistance domain-containing adaptor inducing IFNβ ) , whereas MDA5 associates with the adaptor protein IPS1 ( IFNβ promoter stimulator 1 ) [37 , 38] . Both of these adaptors initiate downstream signaling via activation of the transcription factors , IRF3 and IRF7 , which in turn induce the expression of genes encoding type I IFN and various proinflammatory cytokines [39] . In this study , we investigated the effect of high type I IFN environments on the cellular innate and adaptive immune responses to C . neoformans and the outcome of infection . We found that type I IFN induced by pICLC was highly protective in C57BL/6 mice infected with C . neoformans via MDA5 and not TLR3 recognition . In addition , we demonstrated that pICLC combined with fluconazole ( FLC ) resulted in a synergistic anti-fungal effect reflected in reduction of fungal loads . At the cellular level , pICLC administration induced a massive influx of Ly6Chigh monocytes and neutrophils into the lung tissue parenchyma within 3 days and sustained their elevated numbers for weeks . Moreover , pICLC treated mice displayed diminished GATA3+ IL-5 producing CD4 T cells and dramatically reduced eosinophilia , but increased RORγt+ IL-17A producing CD4 T cells . Importantly , pICLC induced protection against C . neoformans required CD4 T cells , IFNγ , and to a lesser extent IL-17A . Lastly , we found that pICLC treatment also enhanced host resistance against C . gattii infection . These data show that the induction of high levels of type I IFN can reorganize the innate and adaptive immune responses against cryptococcal infection , illustrating how manipulation of specific inflammatory responses can dramatically improve resistance to infection with etiologic agents of cryptococcosis .
To investigate the impact of innate inflammation associated with viral infections on the outcome of cryptotococosis , C57BL/6 or mice deficient in type I interferon receptor signaling ( Ifnar1-/- ) were intrapharyngeally exposed to C . neoformans and treated twice weekly with pICLC , a stabilized dsRNA virus mimic . While all of untreated WT mice succumbed to infection by day 49 , 60% of treated WT mice were remaining at the end of the experiment on day 70 post-infection ( Fig 1A ) . On day 28 post-infection , the pulmonary fungal burden of pICLC treated WT mice was reduced in the lungs by ~0 . 5 logs ( Fig 1A ) . Strikingly , while the control mice had ~105 CFU in the brain , the CFU in the brains of treated mice was barely detectable ( Fig 1A ) . Untreated Ifnar1-/- mice succumbed to infection significantly earlier and had a nearly 2 log increase in fungal loads in the lungs and brain compared to untreated WT mice while pICLC administration had no effect on the survival or fungal control of H99-infected Ifnar1-/- mice ( Fig 1A ) . These results indicate that type I interferon plays a major role in normal host resistance to H99 infection and that inducing high levels of type I interferon via pICLC administration further enhances its potent protective effects . Histopathological analysis showed that ~70% of lung parenchyma of untreated mice was affected compared to 25–30% of lung parenchyma in pICLC-treated animals ( S1 Fig ) . PICLC did not affect fungal growth in YPD broth indicating that the antifungal effects in vivo were not due to direct activity against the yeast . Collectively , these results suggest that inflammation associated with innate recognition of dsRNA , which simulates a viral infection , leads to a profound resistance to invasive pulmonary cryptococcal infection . Pattern recognition receptors TLR3 and MDA5 have been implicated in the recognition of dsRNA , so we next treated C . neoformans H99 infected Tlr3-/- and Mda5-/- mice with pICLC and monitored survival and fungal growth . Administration of pICLC significantly extended survival of C . neoformans infected Tlr3-/- mice ( Fig 1B; P<0 . 05 ) , and similar to the WT mice , fungal growth was nearly undetectable in the brain of pICLC treated TLR3 KO mice ( Fig 1B ) . In contrast , pICLC treatment of H99 infected Mda5-/- mice had insignificant effects on survival and no detectable effect on fungal burden ( Fig 1C ) . Furthermore , we observed a significant induction of IFNα ( Fig 1D; P<0 . 01 ) and moderate induction of IFNβ ( Fig 1E ) in lung tissue homogenates of pICLC treated WT but not Mda5-/- mice . Collectively , these data indicate that MDA5 recognition of pICLC is required for the increased induction of type I IFN and the protective effects of pICLC against cryptoccocal infection . To differentiate between the roles of IFNα and IFNβ we investigated the effect of pICLC administration on survival of Ifnb-/- mice following infection with C . neoformans . Importantly , pICLC treatment protected IFNβ deficient mice infected with H99 ( Fig 1F ) , suggesting a possible role of IFNα in the pICLC induced protection against cryptococcal infection . Administration of recombinant mouse IFNα to H99-infected WT mice slightly extended survival ( Fig 1G ) while rIFNβ treatment did not delay mortality of the mice compared to the untreated control ( S2 Fig ) . Together , these data indicate that MDA5 mediated recognition of pICLC induces IFNα which signals through IFNaR1 to induce control of C . neoformans infection . We next asked if pICLC could enhance standard antifungal therapy of C . neoformans infection . Mice were intrapharyngeally infected with H99 and treated with pICLC , FLC , or both , and CFU were quantified in the lungs and brain on days 7 , 14 and 28 . While monotherapy with either FLC or pICLC had a significant effect on fungal growth , co-treatment with the antifungal drug and immunomodulatory therapy together further decreased fungal replication ( Fig 2 ) . Thus , the protective effects of IFNaR1 driven innate inflammation can further enhance standard antifungal therapy . We next examined the early and later changes in the cellular innate immune response in the lung following infection with and without pICLC treatment . To do so , we identified six major populations of pulmonary myeloid cells by multi-color flow cytometry: alveolar macrophages , neutrophils , eosinophils , Ly6Chigh monocyte/macrophages , Ly6Clow monocyte/macrophages , and CD103+ dendritic cells ( Fig 3A ) . To carefully quantify the migration of myeloid cell types into the lung tissue parenchyma , we employed the well-characterized intravascular staining approach that allows for the flow cytometric discrimination of parenchymal and intravascular cells [40] . Three minutes before euthanasia and lung harvest , the mice were intravenously ( iv ) injected with a fluorochrome labeled-mAb against CD45 . Cells staining positive for the iv injected antibody were located in the lung blood-associated vasculature , and the cells that were protected from the iv stain were localized to the lung parenchyma ( Fig 3B ) . In all groups of mice the alveolar macrophages and CD103+ dendritic cells were almost exclusively localized to the lung parenchyma as expected for these tissue resident cell types ( Fig 3C ) . The percentage of eosinophils that were iv stain negative also increased but due to their low abundance at this early time point this only resulted in a ~2 fold increase in the number of eosinophils in the lung parenchyma of infected mice following pICLC treatment ( Fig 3D ) . In contrast , the frequency of iv stain negative neutrophils increased dramatically in uninfected as well as pICLC treated mice , resulting in an ~120 fold increase in the number of neutrophils in the lung parenchyma ( Fig 3C and 3D ) . Consistent with the increased migration of neutrophils , pICLC treatment induced a large increase in KC and G-CSF expression compared to untreated controls , which was completely IFNaR1 dependent ( S3A and S3B Fig ) . Interestingly , the only cell type to appreciably change following infection alone at day 3 were the neutrophils , which increased ~8 fold in the lung tissue parenchyma ( Fig 3D ) . PICLC induced the most dramatic change in Ly6Chigh monocytes/macrophages . In naïve mice , <5% of these cells were iv stain negative , and infection with H99 did not significantly increase their localization into the lung parenchyma ( Fig 3C and 3D ) . Following administration of pICLC to naïve or H99 infected mice , ~70% of the Ly6Chigh monocytes/macrophages were now iv stain negative corresponding to an ~240 fold increase in the number of these cells in the lung tissue parenchyma ( Fig 3B–3D ) . Ly6Chigh monocytes are well understood to express high levels of CCR2 , and accordingly we observed a large induction of the ligand CCL2 in pICLC treated mice , which was also IFNaR1 dependent ( S3C Fig ) . In contrast to day 3 when there were few eosinophils and the majority were in the lung associated blood-vasculature , by day 20 post-infection ~30% of all live cells were eosinophils ( Fig 3E ) and >90% were within the lung parenchyma ( S4 Fig ) . In contrast , in pICLC treated mice fewer than 10% of the cells isolated from the lung were eosinophils . The percentage of eosinophils that were localized to lung tissue parenchyma , however , was not decreased ( S4 Fig ) , but the total number of eosinophils in the lung parenchyma was reduced by ~3 fold ( Fig 3F ) . These data suggest that pICLC treatment may have inhibited the production of eosinophils but not their ability to migrate into the lung tissue . Similar to what was observed at day 3 , on day 20 post-infection we found a large increase in the abundance of neutrophils and Ly6Chigh monocytes/macrophages along with a dramatic increase in the number of lung parenchymal cells ( Fig 3E and 3F ) . Collectively , these data show that intrapharyngeal administration of pICLC induces an extremely rapid and sustained influx of neutrophils and Ly6Chigh monocytes/macrophages into the lung parenchyma , and suppresses the development of eosinophilia . We next asked what role CD4 T cells play in the pICLC induced protection , by treating H99 infected I-Ab-/- mice with pICLC . While there was a tendency for delayed mortality in pICLC treated CD4 T cell deficient mice compared to untreated mice , this difference was not statistically significant and pICLC had no effect on fungal loads in the absence of CD4 T cells ( Fig 4A and 4B ) , indicating that CD4 T cells are required for protection in pICLC treated H99 infected mice . Therefore , we next analyzed the effects of pICLC treatment on the differentiation of CD4 T cells in infected mice . We found that pICLC suppressed the expression of the GATA-3 and enhanced the expression of RORγt in foxp3-CD44hi effector CD4 T cells ( Fig 4C ) , indicating that pICLC treatment skews the CD4 T cell response against H99 from a Th2 towards a Th17 response . To characterize the function of pulmonary CD4 T cells , we simultaneously measured the production of IL-17A , IL-4 , IL-5 , IL-13 , IFNγ , and TNF by polychromatic intracellular cytokine staining following re-stimulation with anti-CD3/28 in vitro . We found that the overall frequency of CD4 T cells capable of producing IL-17A was ~3 fold higher in the pICLC treated compared to untreated mice ( Fig 4D and 4E ) . Moreover , there was a trend towards a reduction in the frequency of IL-5 producing CD4 T cells just below statistical significance ( Fig 4D and 4E ) . In order to determine if the increase in IL-17A+ CD4 T cells was due to an increase in Th17 cells themselves or its production by Th1 or Th2 cells , we quantified the frequency of CD4 T cells producing all possible combinations of these six cytokines . We found that the increase in IL-17A+ CD4 T cells in pICLC treated mice was due to increases in cells producing IL-17A alone or cells making only IL-17A and TNF ( Fig 4F ) . Therefore , Th1 and Th2 cells did not begin to make IL-17A in pICLC treated mice , and the increase in IL-17A producing CD4 T cells in pICLC treated mice was likely due to the expansion of bona fide Th17 cells . We also measured the parenchymal localization of effector CD4 T cells using the intravascular stain . We found that pICLC increased the frequency of CD44highfoxp3- effector/memory phenotype CD4 T cells that were within the parenchyma from ~85% in the untreated to ~95% in the treated ( S5 Fig ) . Collectively , these results show that pICLC treatment of H99 infected mice skews the CD4 T cell response away from detrimental Th2 cells and towards protective Th17 cells enhancing the migration of effector T cells into lung tissue . Given the enhanced production of Th17 cells following pICLC administration to H99 infected mice , we asked if IL-17A itself was contributing to the protective effects of the treatment . H99 infected mice were treated with and without pICLC and with and without anti-IL-17A neutralizing mAb . We found that in two independent experiments IL-17A blockade increased the fungal loads in the pICLC treated mice ( Fig 5A ) . These data indicate that IL-17A is partially involved in the control of H99 infection in pICLC treated mice . Although there was no major increase in IFNγ-producing CD4 T cells after pICLC administration ( Fig 4E ) , we observed increased levels of IFNγ in BAL fluid on day 7 upon pICLC administration to H99 infected mice ( S3D Fig ) indicating that the increased levels of IFNγ in treated mice may have originated from other cellular sources . We also found that IFNγ-producing CD8 T cells were not significantly increased , indicating that an innate lymphocyte such as NK cells may be the cell type responsible for the elevated levels of IFNγ in the polyICLC treated mice . Since IFNγ is known to play a key role in host defenses against C . neoformans [41] , we examined the requirements for this cytokine in the protective effects of pICLC by treating H99 infected Ifng-/- mice . Indeed , we found that pICLC treatment did not rescue IFNγ deficient mice as the animals succumbed to infection at the same rate as untreated controls ( Fig 5B ) . In addition , there was little or no suppression of fungal growth in pICLC treated IFNγ deficient mice ( Fig 5C ) . Taken together , these data suggest that both IL-17 and IFNγ are required for pICLC mediated protection against C . neoformans . We next asked if pICLC treatment could also enhance host resistance to C . gattii , another etiologic agent of cryptococcosis . We chose strain R265 , which primarily induces lethal pneumonia in mice , as opposed to C . neoformans which causes lethal meningoencephalitis by hematogenous dissemination from the lungs and fulminating growth in the central nervous system [42] . Mice were infected with R265 and subjected to the same pICLC treatment regimen . We found that pICLC significantly increased host survival after infection , with all untreated mice succumbing by ~day 60 while 80% of the treated mice still remaining on day 70 ( Fig 6A ) . C . gattii grows much less in the brain compared to H99 , and pICLC treatment had little effect on fungal loads in the brain . However , there was close to a 2 log reduction in the fungal loads in the lungs of treated compared to untreated mice ( Fig 6B ) . These data show that the host-protective effects of pICLC triggered inflammation extend to both C . neoformans and C . gattii despite their difference in organ tropism and end-stage disease manifestation .
Cryptococcocal co-infections are among the most important AIDS-associated opportunistic infections . However , the underlying immunological mechanisms that predispose HIV+ patients to cryptococcosis might not solely be attributable to CD4 depletion . In the present study we investigated the effect of type I IFN induction , a type of innate inflammation typically associated with viral infections , on the outcome of cryptococcosis by employing a dsRNA homolog , pICLC , as the type I IFN inducing agent to mimic viral co-infection . PICLC treatment induced multiple changes in both innate and adaptive cellular immune responses in H99 infected mice . This is not unexpected since poly-IC challenge is known to elicit gene expression changes in innate and cell mediated immune pathways similar to acute viral infection [43 , 44] . In the first three days after infection , we observed very little recruitment of myeloid cells into the lungs with this strain , regardless of dose and route of C . neoformans inoculation . The only noticeable change at the early time point after infection was a minor increase in the number of neutrophils in the lungs . This suggested that the yeast cells were able to persist and replicate in the lungs for at least 3 days before appreciable numbers of circulating phagocytes are recruited to the site of infection . Of note , a single administration of pICLC into the airways induced an enormous recruitment of myeloid cells in this time period , even without any infection . We found a >100 fold increase in the number of neutrophils and Ly6Chigh monocytes in the lungs three days after pICLC treatment . Early studies have reported conflicting results regarding the effect of poly-IC in mice infected by C . neoformans . While it was protective in one study [45] , it had no effect on infection in the other [46] . The reason for these different results is unclear since both studies used a similar protocol and for obvious reasons , no immunological mechanisms were addressed . In addition , mice in those studies had been infected intravenously with at least a1000-fold higher inoculum of an uncharacterized or a serotype A C . neoformans strain and used poly-IC instead of pICLC . We did not observe a beneficial effect of pICLC in mice infected intravenously with H99 ( S6 Fig ) . Importantly , the route of infection and the size of inoculum , as well as the C . neoformans strains used are all critical for the outcome of experimental cryptococcosis in an animal model [42] . One could speculate that during infection , the events mediated by pICLC may help the host to keep cryptococci contained in the lung but once the fungus is blood borne these events are unable to confer protection . This notion is supported by the fact that pICLC protected mice from meningoencephalitis only if it was administered within 72 hours post intrapharyngeal inoculation of C . neoformans . Once the cryptococci inoculated intrapharyngeally enter the brain , which occurs by 72h [42] , pICLC fails to control cryptococcal growth . Poly-IC is recognized by both TLR3 [34 , 47] and MDA5 [34 , 48] but our results in this study indicate that pICLC administered to mice infected with cryptococci was recognized by MDA5 and not by TLR3 . However , our data do not rule out the possibility that specifically triggering TLR3 by other means might also be protective against cryptococcal infection . Interestingly , Jaeger and coworkers recently reported that MDA5 is directly involved in the host defense against Candida infection but the active ligands for MDA5 in this context are not clear [49] . Poly-IC has also been tested in mice infected with Candida albicans [50 , 51] and Aspergillus fumigatus [25] and shown to have either a detrimental or a beneficial effect in mice , respectively . Results obtained with poly-IC corroborated the differential effects of type I IFN signaling observed in Candida [26] and Aspergillus infected hosts [25] , respectively . Guarda and colleagues demonstrated that the poly-IC induced type I IFN increased susceptibility to C . albicans infection by diminishing IL-1β production [51] . In the case of pulmonary H . capsulatum infection , pre-treatment with poly-IC had no effect on early fungal growth [52] . The poly-IC recognition receptor has not been identified in these studies [25 , 50] . In fact , our study is the first to identify the pattern recognition receptor for a dsRNA virus mimic in a host co-infected with pathogenic fungi . It is important to point out that we used the intravascular staining approach to formally show that these myeloid cells had migrated out of circulation and were located in the lung tissue parenchyma , and the enhanced numbers of parenchymal neutrophils as well as monocytes in pICLC treated mice were sustained for at least 3 weeks post-infection . It has been shown that recruitment of Ly6Chigh monocytes into the lungs following exposure to C . neoformans is associated with control of the infection and is dependent on CCR2 [53 , 54] and mice deficient in CCR2 are much more susceptible to C . neoformans infection [55] . Future studies of individual contributions of each of these cellular changes in the anti-cryptococcal effect of pICLC may provide further insight into the qualities of a protective innate immune response against cryptococcosis . PICLC treatment of H99 infected mice also greatly altered the polyfunctional profile of the pulmonary CD4 T cell response . CD4 T cells in the lungs of these mice showed reduced IL-5 production and GATA-3 expression . It has been shown that IL-5 produced by CD4 T cells is required for eosinophilia in the context of cryptococcal infection [56] and IL-5 overexpressing mice are highly susceptible to C . neoformans infection [57] . Indeed , we found that pICLC treatment greatly suppressed the development of eosinophilia normally observed in C . neoformans infection , indicating that the effect on eosinophil numbers in the lungs may be due to the impact of pICLC on CD4 T cell effector polarization in C . neoformans infected mice . Interestingly , pICLC administration also greatly increased Th17 cell generation in H99 infected mice . Consistent with recent reports in mice infected with C . neoformans H99 [58] or the less virulent strains 52D [59] or H99γ [60] where some protective role for IL-17A was observed [59] , we found that IL-17A induction by pICLC was partly responsible for control of the infection . In addition to the known function of IL-17 in neutrophil recruitment [61] , Th17 stimulation may also enhance the ability of alveolar macrophages to phagocytize and control the intracellular proliferation of cryptococci , as reported using in vitro studies with human primary macrophages [62] . The mechanisms of pICLC induction of RORγt Th17 cells are not clear , but the increase in Th17 responses in treated mice may result from the decreased levels of counter-regulatory GATA-3 . More detailed studies are needed to specifically address the mechanisms of Th17 induction in this setting . The clinical evidence in AIDS associated cryptococcosis unequivocally demonstrates that CD4 T cell mediated immunity is paramount to the host resistance to cryptococcosis [8] . The susceptibility of HIV+ individuals to opportunistic C . neoformans infection , therefore , is thought to be primarily due to CD4 T cell depletion [4 , 8] . Recent studies , however , showed that high type I IFN environments can exacerbate bacterial and other fungal infections often associated with HIV+ , such as M . tuberculosis [21 , 63 , 64] histoplasmosis [24] and candidiasis [26] . These reports have led to the idea that the innate inflammation induced by the chronic viral infection might also be a major factor predisposing to both primary and opportunistic infections in which high level induction of type I IFN may be detrimental for infection outcome . Our results clearly indicate that type I IFN signaling plays an important role in defending the host from cryptococci and helps integrate early , innate immune responses with later events mediated by the adaptive immune system . We found that Ifnar1-/- mice are highly susceptible to H99 , and furthermore , triggering type I IFN through the administration of pICLC induced multiple immunological changes leading to a profound resistance to this fungal infection . In agreement with our findings , one previous study found that IFNα receptor knockout mice displayed defective Th-1 responses following exposure to C . neoformans [65] . These results initially seemed inconsistent with the well-established susceptibility of HIV infected individuals to C . neoformans . However , we also found that pLCLC-mediated protection was dependent on CD4 T cells . It is therefore possible that the type I IFN response induced by HIV infection is protective against C . neoformans only until CD4 T cells fall below a critical threshold after which the protective effects are lost and the lack of CD4 T cells results in uncontrolled infection . Indeed , cryptococcosis is usually observed in late stage HIV infection when CD4 T cell numbers are extremely low [8] . The critical role for CD4 T cells in the pICLC mediated protection may suggest limited therapeutic implications of type I IFN based therapies for cryptococcosis in AIDS patients , as the most of the HIV-associated cryptococcosis occur as the patients become deficient for CD4 T cells [8] . On the other hand , type I IFN based therapies may be a possibility for cryptococcosis caused by C . gattii since we found pICLC treatment to be very effective against C . gattii infection which occurs more frequently in immunocompetent individuals rather than CD4 T cell depleted immunocompromised patients [66] . PICLC treatment had synergistic effect with FLC , the most widely used azole for the treatment of cryptococcosis [67] . When administration of the dsRNA was initiated 24 hours post infection , the therapeutic efficacy of pICLC alone was higher than FLC alone; however , combination of the two was significantly more effective than either one of them alone . These results implicate a potentially prophylactic importance of FLC combined with pICLC in HIV+ patients prior to decrease in CD4 T cell count . Regardless of the prophylactic/therapeutic potential of type I IFN specifically , these data serve as a proof of concept that manipulation of innate inflammatory signals can dramatically improve host resistance to cryptococcal infections caused by both agents of cryptococcosis , C . neoformans and C . gattii .
WT C57BL/6 mice were purchased from DCT ( National Cancer Institute , NCI-Frederick , MD ) . Ifnabr ( Ifnar1-/- ) , Tlr3-/- , Ifng-/- and I-Ab-/- ( Taconic:C57BL/6NTac-[KO]AbB ) on a C57BL/6 background , were purchased from Taconic Farms ( Germantown , NY ) under the NIAID Animal Supply Contract . Mda5-/- mice were obtained from The Jackson Laboratory . Ifnb-/- mice [68] were kindly provided by Dr . Stephanie N . Vogel ( University of Maryland , Baltimore ) . Male and female mice between 8 and 12 weeks of age were used in all experiments . The strains H99 and R265 , both genome sequenced strains were chosen as representative strains of C . neoformans and C . gattii , respectively . Strains were stored in 25% glycerol at −80°C until use and were maintained on YEPD ( 1% yeast extract , 2% peptone , 2% glucose ) agar plates at 30°C . To induce respiratory infection , WT and knockout mice were anesthetized with isoflurane and inoculated with the designated number of yeast cells in 20 μl of phosphate-buffered saline ( PBS ) via intrapharyngeal ( i . p . ) aspiration ( inhalation method ) [69 , 70] . Each mouse received approximately 5000 colony forming units ( CFUs ) of C . neoformans or C . gattii . Survival was monitored for up to 80 days post inoculation . Mice were observed daily for signs of disease and lethality . Mice with signs of irreversible disease ( e . g . , persistent hunching , unsteady gait , lethargy , unable to eat or drink ) were euthanized . For quantification of fungal burden , organs ( lung and brain ) were weighted , homogenized , and diluted in 10-fold steps in PBS . Fungal CFUs were determined by plating serially diluted homogenates on YEPD agar plates . Lungs and brains from mice were subjected to histopathologic staining with hematoxylin and eosin ( H&E ) and Gomori methenamine silver ( GMS ) . PICLC ( Hiltonol ) , a synthetic analogue of viral dsRNA , was supplied by Oncovir Inc . Mice were inoculated intrapharyngeally with pICLC ( 5 μg in 20 μl/mouse ) twice weekly up to 10 weeks , starting at the same day of infection . To examine preventive or therapeutic effect pICLC was administered twice weekly up to 10 weeks , starting 3 days prior or 1 day after cryptococcal exposure , respectively . Recombinant mouse IFNα and IFNβ were generous gifts from PBL InterferonSource ( Piscataway , NJ ) . IFNα or IFNβ ( 1000 U ) was administered intrapharyngeally twice weekly up to 10 weeks , starting at the same day of infection . Fluconazole ( FLC ) was used along with pICLC to assess antifungal combination therapy . FLC was administered intraperitoneally at a concentration of 10 mg/kg of body weight/day , starting 24 h after infection and continued for 28 days . For IL-17A neutralization experiments , mice were injected with 200 μg of αIL-17A mAb clone 17F3 every three days . The intravascular staining was performed as described previously [71] . Briefly , mice were injected i . v . with 2 . 5 μg of αCD45 . 2-FITC mAb in a volume of 200 μl , and after 3 minutes the mice were euthanized and the lungs were harvested . To isolate pulmonary leukocytes lungs were minced with scissors and shaken in a cocktail of DNase , collagenase and hyaluronidase for ~30 minutes at 37°C . The leukocytes were then pelleted through 37% percoll , and red blood cells were lysed with ACK buffer . The Institutional Animal Care and Use Committee of the National Institute of Allergy and Infectious Diseases approved all animal studies ( #A4149-01 ) . Studies were performed in accordance with recommendation of the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health . For intracellular cytokine staining , isolated lung leukocytes were stimulated with soluble αCD3 and αCD28 ( both at 1 μg/ml ) in the presence of brefeldin A and monensin for 5 hours . Lung cells were stained with various combinations of the following mAb clones: αTNF MP6-XT22 , αCD8 53 . 67 , αIL-17A TC11-18H10 . 1 , αCD4 RM4-5 , αCD45 . 2 104 , αIL-5 TRFK5 , αCD44 IM7 , αIFNγ XMG1 . 2 , αIL13 eBio13A , αFoxp3 FJK-16S , αLy6G 1A8 , αCD11b M1/70 , αCD11c N418 , αCD103 2E7 , αCD68 FA11 , αLy6C HK1 . 4 , αSiglec F E50-2440 , αT-bet 4B10 , αPD-1 29F . 1A12 , αRORγt B2D , and αGATA-3 TWAJ . All FACS antibodies were purchased from eBioscience ( San Diego , CA ) and Biolegend ( San Diego , CA ) . Analysis of CD4 T cell cytokine polyfunctionality was performed using SPICE version 5 . 3 , downloaded from http://exon . niaid . nih . gov [72] . Lungs were homogenized in 1 ml PBS . The samples were then centrifuged at 16 , 000 g for 30 minutes at 4°C , and IFNα/β , IFNγ levels were determined in the supernatants using ELISA ( PBL InterferonSource and eBioscience , respectively ) according to the manufacturer’s recommendation . In some experiments , bronchoalveolar lavage fluid ( BAL ) was collected by lungs’ perfusion with 1 ml of cold PBS after partial tracheal resection using 22-gauge catheters . Mouse Cytokine Group I ( 23-Plex ) was measured to quantify cytokine and chemokine concentrations in the supernatants obtained from mice , as described above , using Bio-Plex assay ( Bio-Rad Laboratories , Inc . , USA ) following the manufacturer's instructions . Survival data from the animal experiments were analyzed using a two-group Wilcoxon test ( GraphPad Prism analysis software ) . An unpaired t test was used for evaluation of the CFU in tissue burden studies . Two-group comparisons were done with the Student’s t test . When P values of <0 . 05 were obtained , differences were considered statistically significant . | Meningoencephalitis due to Cryptococcus neoformans is the leading cause of mortality in AIDS patients in the developing world . It has been known that depletion of CD4 T cells is the most critical predisposing factor to cryptococcosis in HIV infected patients . What has not been clear is the effect of HIV-induced innate inflammation in susceptibility to cryptococcosis . We treated C . neoformans infected mice with poly-ICLC ( pICLC ) , a dsRNA virus mimic , to study the role of virus-induced type I IFN in host defense against cryptococcosis . PICLC treatment induced type I IFN in C . neoformans infected mice via MDA5 and significantly prolonged the survival of mice with reduced fungal burden in the brain . PICLC also protected mice from cryptococcosis caused by C . gattii . PICLC treatment recruited large numbers of neutrophils and Ly6Chigh monocytes into the lung parenchyma and suppressed eosinophilia . PICLC-mediated protection against C . neoformans required CD4 T cells and was associated with suppressed Th2 and enhanced Th17 responses . IFNγ and IL-17A were also important for pICLC-induced protection of infected mice . Our study demonstrates that induction of type I IFN dramatically improves host resistance against cryptococci by beneficial alterations in both innate and adaptive immune responses as long as CD4 cells are not depleted . | [
"Abstract",
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"Results",
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"Methods"
] | [] | 2015 | Type I IFN Induction via Poly-ICLC Protects Mice against Cryptococcosis |
In the global program for the eradication of yaws , assessments of the prevalence of the disease are used to decide where to initiate mass treatment . However , the smallest administrative unit that should be used as the basis for making decisions is not clear . We investigated spatial and temporal clustering of yaws to help inform the choice of implementation unit . We analyzed 11 years of passive surveillance data on incident yaws cases ( n = 1448 ) from Lihir Island , Papua New Guinea . After adjusting for age , sex , and trends in health-seeking , we detected three non-overlapping spatial-temporal clusters ( p < 1 × 10−17 , p = 1 . 4 × 10−14 , p = 1 . 4 × 10−8 ) . These lasted from 28 to 47 months in duration and each encompassed between 4 and 6 villages . We also assessed spatial clustering of prevalent yaws cases ( n = 532 ) that had been detected in 7 biannual active case finding surveys beginning in 2013 . We identified 1 statistically significant cluster in each survey . We considered the possibility that schools that serve multiple villages might be loci of transmission , but we found no evidence that incident cases of yaws among 8- to 14-year-olds clustered within primary school attendance areas ( p = 0 . 6846 ) . These clusters likely reflect transmission of yaws across village boundaries; villages may be epidemiologically linked to a degree such that mass drug administration may be more effectively implemented at a spatial scale larger than the individual village .
Yaws , a bacterial disease caused by Treponema pallidum subspecies pertenue , causes skin lesions and arthralgia , most commonly in school-age children [1] . Yaws spreads via direct skin-to-skin contact . While yaws was widespread in tropical areas in the first half of the twentieth century , the disease currently persists primarily in Melanesia and parts of west and central Africa [2] . The discovery that oral azithromycin treats yaws as effectively as injectable penicillin sparked renewed interest in eradicating this neglected tropical disease [3 , 4] . Yaws often enters a latent stage during which patients are no longer infectious or symptomatic but are still infected and at risk of the disease reactivating and once again being infectious . Eradicating yaws necessarily requires treating all infections , including latent ones . The World Health Organization ( WHO ) yaws eradication strategy calls for 1 or more rounds of mass drug administration ( MDA ) in all yaws-endemic areas; that is , treating with azithromycin nearly everyone in these areas , regardless of individuals’ disease status . MDA aims to cure yaws even in latently infected individuals thereby preventing them from later becoming infectious . Before implementing yaws elimination programs , public health officials need to decide the spatial scale at which to conduct MDA . They refer to the geographic level ( eg , province , district , sub-district or village ) with respect to which they decide to start and stop MDA as the implementation unit [5] . The implementation unit may differ between diseases . For example , districts typically serve as the implementation unit for lymphatic filariasis and trachoma elimination programs , while the implementation units for schistosomiasis mass treatment are often groupings of sub-districts that share similar environmental characteristics [6] . The WHO initially recommended that the village or community should be the implementation unit for yaws eradication [4] , which , to our knowledge , would be smaller than the implementation units used in any other mass treatment program . This recommendation was informed , in part , by research concluding that village-level yaws prevalence is a stronger risk factor for yaws than household-level prevalence [7 , 8] . A more recent review argued that conducting yaws prevalence surveys at the village level is impractical and that the implementation unit for the initial round of MDA should instead be a unit with a population of 100 000 to 250 000 people and that for subsequent treatment rounds the implementation unit could be lowered to the village [9] . The choice of implementation unit is an unresolved challenge in formulating yaws eradication strategy and reflects a lack of research on the spatial epidemiology of yaws . Understanding yaws transmission and clustering not only helps inform the choice of implementation unit but also is needed to design statistically rigorous assessments of yaws prevalence within each implementation unit . Because clustering of an infectious disease can occur at multiple spatial scales simultaneously [10] , research is needed on yaws spatial epidemiology at multiple scales . In this study we assess whether clusters ( ie , areas of disproportionately high prevalence or incidence ) of yaws extend across neighboring villages . Spatial-temporal clusters of disease extending across villages may indicate that appreciable levels of disease transmission occur between villages . While most yaws studies have relied on cross-sectional data , we leverage more than a decade of clinical records to include a temporal component in our analysis . Finally , given that yaws is predominantly a disease of school children and might be expected to be spread at schools , we investigate whether primary school attendance areas help explain the spatial distribution of yaws .
We conducted this study on Lihir Island , a 200 km2 tropical island in New Ireland Province , Papua New Guinea . Fig 1 shows that the island’s mountainous interior is largely uninhabited and the population of approximately 12 500 Lihirians lives in coastal villages linked by a road that encircles the island . Even the most geographically distant pair of villages are only 35 . 2 km apart by road . Driving the loop road around the island takes approximately 2 hours . Most villages are near beaches suitable for launching and landing small motorboats . Many adults travel occasionally to Londolovit in the northeast part of Lihir , which is the area where most formal economic activity is centered . There is an elementary school in most villages and children may travel up to a few kilometers to a neighboring village to attend primary school . Approximately 4680 migrants live on the island , primarily in villages in the northeast part of Lihir . The island houses a large-scale gold mine . The migrants are generally not mineworkers; the mine employs about 2000 people who mostly stay in camps separate from the rest of the population . They are not counted among the migrants . A network of government-run aid posts , a clinic at a Catholic mission station , and the Lihir Medical Centre ( LMC ) ( a hospital that serves both mine personnel and the public ) deliver health care services . Yaws has long been endemic in the region; Dr . Robert Koch visited Lihir in 1900 and subsequently reported that he observed yaws throughout the Bismarck Archipelago , the group of islands that comprise the northeastern part of present-day Papua New Guinea [11 , 12] . We queried the LMC’s electronic medical records system to identify all outpatients who had been diagnosed with yaws between early April 2005 and 29 May 2016 . Some patients were diagnosed with yaws multiple times over the course of the study period; each diagnosis was counted as a separate case . We included only those patients whose reported place of residence was a Lihir village . The LMC typically recorded migrants to Lihir ( even those living there indefinitely ) as being from their place of origin , not the Lihir village where they currently live . To be considered an incident yaws case at the LMC , patients must present with a skin lesion consistent with yaws and have positive results on both the Treponema pallidum hemagglutination assay ( TPHA ) and the rapid plasma reagin ( RPR ) test . TPHA is a highly specific biomarker that provides definitive diagnosis of prior or current treponemal infection , while RPR , despite being less specific , indicates that an individual still has a treponemal infection [15] . Starting in April 2013 , we implemented a round of mass drug administration with azithromycin on Lihir to demonstrate the feasibility of eliminating yaws [16] . All people older than 2 months were offered treatment regardless of symptoms . At the same time we administered azithromycin , we examined the participants to identify all suspected yaws cases . We subsequently screened the population every 6 months to identify and treat symptomatic yaws cases and their contacts . In this study , we analyze data through the seventh survey of active case finding , which took place in April and May 2016 . We collected venous blood samples from consenting individuals suspected of having yaws and performed TPHA and RPR testing on these samples . We swabbed the ulcers of all suspected yaws cases in surveys 3 through 7 . Polymerase chain reaction ( PCR ) tests were performed on these swabs . The test consists of amplifying three T . pallidum gene targets: tp0548 , tpN47 ( tp0574 ) , and a pertenue-specific region of the tprL ( tp1031 ) gene [17] . In contrast to individuals in the outpatient data from the LMC , we categorized screened individuals in the active case finding data by their current village of residence without regard to migrant status . We also included as a village in this analysis an informal migrant settlement . We excluded from the analysis cases in villages during surveys where the number of individuals screened was missing for that village . We defined a cluster as a set of 1 or more villages where we observed more incident yaws cases in a time period than expected , given the spatial and temporal distribution of all outpatient visits to the LMC by Lihir village residents and the age and sex distribution of these patients . To detect statistically significant non-spatially overlapping clusters of outpatient yaws diagnoses , we conducted a retrospective space-time analysis in SaTScan version 9 . 4 . 4 using the discrete Poisson model [18–20] . We defined the spatial relationships between villages by the road distances between village centroids ( distances were calculated using ArcGIS version 10 . 3 . 4959 [21] ) and we input this information into SaTScan as a non-Euclidean neighbors file . Geographic data on village boundaries and on the road network were provided by Newcrest Mining Limited . Following standard practice for using SaTScan , we set the maximum allowed cluster duration to be half the duration of the study period . Similarly , we constrained the maximum spatial size of a cluster to encompass villages accounting for no more than half the outpatient visits over the course of the study period . To assess spatial clusters based on data from active case finding with serological confirmation , we analyzed data from each survey separately using the spatial-only discrete Poisson model in SaTScan . Clusters were villages or groups of villages where the proportion of screened individuals who had yaws was greater than expected . Like in the spatial-temporal analysis of incident yaws cases , each village was represented as a single point located at that village’s centroid and we used the road network to define distances between villages . We constrained the maximum cluster size such that no cluster contained more than half of the screened population . Using data on the village of residence of students at each Lihir primary school in 2013 , we defined primary school attendance areas based on the most frequent primary school affiliation of primary school-enrolled children from each village . In this analysis , we restricted the outpatient visit data to 8- to 14-year-olds . We calculated for each village the number of incident yaws cases divided by the total number of outpatient visits . Next , we calculated the F-statistic from weighted analysis of variance ( ANOVA ) to quantify the degree to which primary school attendance areas account for between-village differences in the number of yaws cases per outpatient visit . We weighted each proportion by the inverse of its variance . Because the inverse of the variance is not defined when there are no yaws cases among 8- to 14-year-olds from a given village in a given year , following Agresti and Coull we added 2 yaws cases and 4 outpatient visits to every village only when calculating weights [22] . Finally , to test whether clustering of yaws cases in primary school attendance areas deviated from the null hypothesis ( that clustered cases in villages served by a given primary school result from their spatial clustering rather than attendance at the same school ) , we permuted the primary school attendance area assignments while maintaining the condition that each primary school serves a sequential set of villages along the circumference of the island and calculated the F-statistic for each permutation using weighted ANOVA , thereby constructing an empirical distribution from which we calculated p-values [23] . Analyses were conducted in R version 3 . 4 . 2 [24] . The protocol was approved by the National Medical Research Advisory Committee of the Papua New Guinea National Department of Health ( MRAC no . 12 . 36 ) . All participant data have been anonymized .
From 11 years of routinely collected clinical data on residents of Lihir villages , we identified 2365 distinct symptomatic yaws cases but excluded 917 . Our main analysis is based on 1448 cases of yaws among 1271 patients ( Fig 2A ) . During this period , Lihirians made a total of 288 729 outpatient visits to the LMC ( Fig 2B; S1 Fig ) . The median age at diagnosis of the yaws cases was 9 years ( interquartile range: 6–13 ) . The cumulative number of yaws patients per village varied widely , ranging from 4 yaws cases out of 1390 outpatient visits from Huniho and 4 out of 3156 from Lienbil to 234 out of 32 859 from Kunaye 1 ( Fig 1 ) . We detected 3 statistically significant spatial-temporal clusters ( Fig 3 , S2 Fig ) . The most statistically significant cluster ( p < 1 × 10−17 ) lasted from July 2009 into March 2012 and encompassed 6 villages at the southern tip of Lihir ( cluster 1 ) ; the most distant pair of villages in that cluster are 10 . 7 km apart by road . The next most statistically significant cluster ( p = 1 . 4 × 10−14 ) lasted from the beginning of the study period ( April 2005 ) until the beginning of March 2009 and occurred in 4 villages located along the east coast of Lihir ( cluster 2 ) and spanned over a road distance of 5 . 1 km . Finally , the third statistically significant cluster ( p = 1 . 4 × 10−8 ) lasted from January 2014 through the end of the study period in May 2016 . It comprised 4 villages located in the northeast corner of Lihir ( cluster 3 ) which are at most 7 . 4 kilometers apart by road . Our analysis of spatial-temporal clustering of incident yaws cases was robust to a range of assumptions , including restricting only to yaws cases for which a positive RPR result was recorded in the medical record ( S1 Table ) , not adjusting for age and sex ( S2 Table ) , and using SaTScan’s case-only space-time permutation method instead of the discrete Poisson method [25] ( S3 and S4 Tables ) . While the exact timing and duration of clusters varied somewhat between the different analyses , all found evidence of 3 highly statistically significant spatial-temporal clusters , and the temporal order and general locations of the clusters were unchanged . Out of 95 353 screenings during the 7 biannual active case finding surveys ( mean of 13 622 individuals screened per survey ) , we identified 568 serologically confirmed yaws cases , of which 36 were excluded ( Fig 4 ) . More than half of all serologically confirmed cases were identified during the first ( pre-MDA ) round of screening . The median age of the serologically confirmed cases was 12 years ( interquartile range: 8–14 ) . We detected 1 statistically significant cluster in each survey at the α = 0 . 05 level of significance ( Fig 5 ) . The number of villages in each cluster varied widely from 1 to 16 . In a supporting analysis we repeated our active-case finding analysis using PCR-confirmed cases only . S3 Fig lists 116 PCR-confirmed cases and 11 exclusions by survey , and results for PCR-confirmed cases are shown in S4 Fig . The results from PCR-confirmed and serologically confirmed yaws cases are broadly similar in that most clusters of serologically confirmed cases overlapped with a cluster of PCR-confirmed cases , but fewer of the clusters detected in the PCR-based analysis were statistically significant . Unlike in the analysis of serologically confirmed cases , there were no statistically significant clusters of PCR-confirmed yaws in the third or fifth surveys . We categorized each village into 1 of 7 primary school attendance areas . Four of the primary school attendance areas consisted of 4 villages , while the remaining 3 areas consisted of 1 , 3 , and 6 villages apiece ( Fig 6A ) . We identified a total of 643 incident cases of serologically confirmed yaws among 8- to 14-year-olds , out of 32 202 visits by outpatients age 8 to 14 . We did not find evidence for clustering of incident yaws cases among 8- to 14-year-olds within primary school attendance areas in individual years 2006 through 2015 ( p-values ranged from 0 . 0687 in 2006 to 0 . 9881 in 2009 ) , nor in the combined data ( p = 0 . 6846 ) ( Fig 6 ) .
We found highly statistically significant spatial-temporal clusters of incident yaws cases , which stretched over multiple years and multiple villages . These clusters likely reflect transmission of yaws across village boundaries . The overall incidence of yaws can be viewed as the sum of an endemic and an epidemic component . The transmission dynamics of yaws on Lihir may consist of repeated and overlapping “outbreaks” of yaws that , when aggregated at the scale of the entire island , create the appearance of a persistently high-level endemic disease . The results of our analysis of purely spatial clusters ( based on data from biannual surveys of active case finding ) correspond in some respects to the results of our analysis of spatial-temporal clusters . For example , in the period January 2014 to May 2016 we identified a spatial-temporal cluster in northeastern Lihir that coincided with purely spatial clusters identified in May and October 2014 in the same area . More generally , our analysis of active case finding data found multi-village clusters of yaws in nearly all 7 surveys . This provides further evidence that at least some of the mechanisms that govern the spatial and temporal distribution of yaws operate at a scale larger than the village level . We did not find evidence for clustering of yaws within primary school attendance areas . While yaws transmission could be rare in an absolute sense within primary schools , a plausible alternative is that outside-of-school transmission simply overwhelms any signal from within-school transmission . Our study has implications for yaws elimination: If the observed clustering is due to appreciable inter-village yaws transmission , we suggest that villages may be epidemiologically linked to such a degree that they may not effectively serve as implementation units . While our analysis indicates that villages are likely too small to serve as the implementation unit for yaws elimination , it does not , however , directly inform how large implementation units ought to be . Also , our finding in the post-MDA surveys that spatial clusters of yaws were centered in multiple different villages around the island suggests that the persistence of yaws following MDA cannot be attributed purely to a lack of control in a single location . We believe that the persistence of yaws cases post-MDA may be attributable to reactivation of yaws in individuals who were latently infected and not treated as part of MDA . The role of migrants in the persistence of yaws on Lihir is unclear . If reintroduction of yaws to Lihir by migrants were the primary cause of clusters post-MDA , we would expect to see clusters concentrated within the northeast part of the island where migrants are most common , which is not what we observed in our spatial-only analysis of the post-MDA surveys . However , the spatial-temporal cluster that was detected in the period following MDA was located in northeast Lihir . It is possible that the cluster arose because MDA was less impactful in this area , though we are not aware of a mechanism that explains such a phenomenon and we cannot rule out reintroduction of cases via migrants . Our results are in line with the previously reported finding that many of the cases of yaws that occurred following MDA were in people who were not treated during MDA and that comparatively few occurred in recently-arrived migrants or in residents with a history of travel [26] . Little prior research has addressed the spatial-temporal epidemiology of yaws , and , to our knowledge , no prior research focuses on the spatial scale that is the focus of our analysis . A recent study from the Solomon Islands sampled villages and then households within villages to assess the prevalence of yaws and identify risk factors . The study found that yaws clusters in villages more so than in households but did not address spatial patterns at the scale of multiple neighboring villages [7] . Earlier work on yaws suggests that geographically heterogeneous environmental factors such as humidity influence the prevalence of yaws [27] . Environmental or social factors may lead to consistently higher levels of yaws in some locations: Public health staff on Lihir anecdotally described Tumbuapil—a village at the southern tip of Lihir—as having a consistently high burden of yaws . Notably , Tumbuapil was part of statistically significant clusters in more active case surveys ( 4 of 7 ) than any other village and was part of the spatial-temporal cluster with the highest observed-to-expected ratio . We lack village-level data on risk factors , so we cannot assess what , if any , factors may contribute to higher prevalence in some villages rather than others . Our study has several limitations: First , our results could reflect patterns in health-care seeking specific to yaws . While our analyses account for trends in the total number of outpatient visits from each village and condition on age and sex , spatially and temporally localized interest in seeking care specifically for skin lesions could , in principle , generate such clusters . But we are unaware of any driver of this particular health-seeking behavior that operates on the relevant spatial and temporal scale . Second , an environmental or social risk factor for the transmissibility of yaws or people’s susceptibility to yaws could underpin the spatial-temporal clusters we observed . Multi-village spatial-temporal clusters in theory could form even in the absence of transmission between villages , but we are unaware of any risk factors that vary not only at the relevant spatial scale but also at the relevant temporal scale . Third , the number of outpatient visits varied greatly by village , with fewer visits from villages that are farther from the LMC; we may have lacked power in our spatial-temporal analysis to detect yaws clusters in areas such as the northwest part of Lihir where we identified a spatial-only cluster in the seventh survey . Fourth , directly comparing the spatial-temporal and spatial-only clustering results is difficult in part because the analyses focus on somewhat different underlying populations: We had to include migrants in the spatial-only clustering analysis but could not include them in the spatial-temporal analysis . Additionally , our primary school attendance area clustering analysis associated each village with a single primary school and does not account for the fact that students from a single village may attend different primary schools . We used school attendance records from a single year to define primary school attendance areas; our analysis would not capture changing school attendance patterns . Finally , our findings may not be generalizable to other yaws-endemic areas . Elsewhere , villages may differ substantially from those on Lihir in terms of population size , density , proximity to other villages , and other factors . While many yaws cases occur on tropical Pacific islands broadly similar to Lihir , it is uncertain whether our results would generalize well to non-insular settings such as yaws-endemic regions of Africa . Conducting research on the spatial epidemiology of yaws in multiple settings such as tropical islands with migration and human mobility patterns different from Lihir and non-insular areas reflecting a range of population densities , human mobility patterns , and social and environmental conditions would help identify phenomena that are contingent on a particular geography versus those that reflect general characteristics of yaws epidemiology . Future research should consider collecting data on and explicitly modeling human mobility and contact patterns at various spatial and temporal scales . Operational research in support of yaws eradication will need to continue to investigate the disease’s spatial epidemiology: Designing prevalence surveys that employ cluster sampling requires understanding the extent of spatial clustering of yaws . Moreover , a mechanistic understanding of the spatial and temporal scales at which yaws spreads and the extent to which transmission occurs in different settings ( eg , schools versus households ) can help inform intervention strategies , particularly contact tracing . Earlier generations of yaws epidemiologists did not have access to molecular epidemiology tools or to remotely sensed data on environmental risk factors . These approaches may advance our understanding of the spatial epidemiology of yaws but will not replace the ongoing need for high-quality and high-spatial-resolution descriptive epidemiological data collected in both research and programmatic settings . | The World Health Organization aims to eradicate yaws using mass drug administration ( MDA ) , which consists of treating everyone in an administrative unit with antibiotics . Prevalence assessments are used to identify endemic communities for mass treatment programs , but the spatial scale ( eg , village , sub-district , district , or province ) at which mass treatment should be implemented is currently unclear . The administrative unit which is used as the basis for making decisions about implementing MDA is called the implementation unit . For example , if the implementation unit is the sub-district , then public health officials must determine for each sub-district whether MDA is warranted . All villages in the same sub-district will necessarily have the same treatment status , whereas all sub-districts in the same district need not share a treatment status . The choice of implementation unit depends on many factors; one of these is the underlying transmission patterns of the disease . Using data from Lihir Island , Papua New Guinea , we found that geographic clusters of yaws often spanned multiple villages . These clusters likely reflect transmission of the disease across village boundaries and suggest that it may be best to implement MDA at a spatial scale larger than the individual village , for example at sub-district level . | [
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"bacte... | 2018 | Spatial-temporal clustering analysis of yaws on Lihir Island, Papua New Guinea to enhance planning and implementation of eradication programs |
Muscle-eye-brain disease ( MEB ) and Walker Warburg Syndrome ( WWS ) belong to a spectrum of autosomal recessive diseases characterized by ocular dysgenesis , neuronal migration defects , and congenital muscular dystrophy . Until now , the pathophysiology of MEB/WWS has been attributed to alteration in dystroglycan post-translational modification . Here , we provide evidence that mutations in a gene coding for a major basement membrane protein , collagen IV alpha 1 ( COL4A1 ) , are a novel cause of MEB/WWS . Using a combination of histological , molecular , and biochemical approaches , we show that heterozygous Col4a1 mutant mice have ocular dysgenesis , neuronal localization defects , and myopathy characteristic of MEB/WWS . Importantly , we identified putative heterozygous mutations in COL4A1 in two MEB/WWS patients . Both mutations occur within conserved amino acids of the triple-helix-forming domain of the protein , and at least one mutation interferes with secretion of the mutant proteins , resulting instead in intracellular accumulation . Expression and posttranslational modification of dystroglycan is unaltered in Col4a1 mutant mice indicating that COL4A1 mutations represent a distinct pathogenic mechanism underlying MEB/WWS . These findings implicate a novel gene and a novel mechanism in the etiology of MEB/WWS and expand the clinical spectrum of COL4A1-associated disorders .
Congenital muscular dystrophies ( CMDs ) involving ocular and cerebral malformations are devastating childhood diseases . Fukuyama congenital muscular dystrophy , Muscle-Eye-Brain disease ( MEB ) , and Walker-Warburg Syndrome ( WWS ) are clinically and mechanistically related forms of CMD [1]–[4] . Patients present at birth or as infants with muscle weakness , hypotonia or even severe myopathy leading to fatal respiratory insufficiency . Clinical presentation varies between patients but often includes myofiber necrosis and fibrosis , replacement by adipose tissue , split muscle fibers and the presence of non-peripheral nuclei . In addition , while most patients exhibit marked elevation of serum creatine kinase ( CK ) , others have CK levels within the normal range [5] . Ocular and cerebral phenotypes demonstrate variable penetrance and expressivity between individual patients . For instance , ocular dysgenesis can occur in either , or both , the anterior ( Peters' anomaly , Rieger syndrome , cataracts , buphthalmos and developmental glaucoma ) and posterior portions of the eye ( retinal dysplasia , retinal detachments and optic nerve hypoplasia ) [6]–[8] . Variable neurological manifestations , including mental retardation and epilepsy , may be at least partially explained by cerebral cortical malformations including cobblestone lissencephaly , cerebellar hypoplasia , hydrocephalus and encephalocele . Genetic and biochemical studies led to the identification of a number of genes involved in the etiology of CMDs and revealed that alterations in post-translational processing of dystroglycan underlie MEB/WWS [9]–[15] . In these ‘dystroglycanopathies’ , hypoglycosylation of dystroglycan disrupts ligand binding and impairs muscle fiber attachment to the extracellular matrix . Central nervous system pathology is proposed to be secondary to defective interactions between radial glial cells and the pial basement membrane [16]–[18] . Despite these major advances , over half of MEB/WWS patients do not have mutations in known genes encoding glycosyltransferases [19] , [20] , suggesting that other genes in this pathway contribute to disease or that independent mechanisms are responsible . Identifying new pathways involved in MEB/WWS will be an important breakthrough that could open new avenues for understanding and ultimately treating CMDs . We have recently discovered the first mutations in the gene coding for the ubiquitous basement membrane protein type IV collagen alpha 1 in mice ( Col4a1 ) and humans ( COL4A1 ) [21] . COL4A1 is the most abundant basement membrane protein and is ubiquitously present in basement membranes with few exceptions . The collagenous domain ( a long stretch of Gly-Xaa-Yaa repeats that forms a triple helix ) accounts for over 90% of the protein . Mutations in this triple helix-forming domain are well documented to be pathogenic in several types of collagens , including type IV collagens . The mutation we identified in mice ( referred to as Col4a1Δex40 ) disrupts a splice acceptor site , causing exon 40 to be skipped and concomitant deletion of 17 amino acids from the collagen triple helical domain which interferes with proper folding , assembly and secretion of heterotrimeric COL4A1 and COL4A2 [21] , [22] . To date , eleven out of twelve other Col4a1 mutations reported in mice [23] , [24] and seventeen out of twenty one COL4A1 mutations identified in humans [21] , [22] , [25]–[34] are missense mutations within the triple helical domain , demonstrating that alterations of this domain are highly pathogenic . In mice and humans , semi-dominant Col4a1/COL4A1 mutations are highly pleiotropic with variable expressivity . The tissue distribution and severity of pathology depends on genetic and environmental factors but commonly include cerebrovascular diseases , ocular and renal defects [21]–[24] , [35] . Here , we broaden this spectrum to include MEB/WWS . We show that , depending on the genetic context; Col4a1+/Δex40 mice recapitulate the pathophysiological hallmarks of MEB/WWS , including ocular anterior segment dysgenesis , optic nerve hypoplasia , cortical lamination defects and myopathy . In addition , we identify heterozygous mutations in the triple–helix-forming domain of COL4A1 in two MEB/WWS patients . Together , these findings support COL4A1 mutations as a novel genetic cause of MEB/WWS . Importantly , COL4A1 is not directly related to post-translational modification of dystroglycan . We show that the mechanism is independent of dystroglycan glycosylation and instead is probably due to decreased COL4A1 levels in basement membranes . COL4A1 mutations are pleiotropic and these data describe another clinically distinct group of diseases that can result from alterations in a single gene .
Ocular hallmarks of MEB/WWS include anterior segment dysgenesis and optic nerve hypoplasia . Depending on the genetic context , mutations in Col4a1 can cause both anterior segment dysgenesis and optic nerve hypoplasia although the underlying pathogenic mechanism ( s ) remain unexplored [23] , [24] , [35] . During development , COL4A1 is present in the inner limiting membrane of the retina [36] and inner limiting membrane disruptions can perturb retinal ganglion cell ( RGC ) localization and cause apoptotic death [37] . To determine if excess RGC death during development caused optic nerve hypoplasia , developing retinas were immunolabeled for Islet-1 ( ISL1 ) and Laminin , which mark newly specified RGCs [38] and basement membranes , respectively . At embryonic days ( E ) 14 , E16 and E18 , RGCs were located in the innermost part of the retina in Col4a1+/+ mice , with only occasional ISL1 immunoreactivity detected in the outer retina ( Figure 1D ) . In contrast , in Col4a1+/Δex40 mice , the thickness of the ISL1 positive layer was highly variable and there were more displaced ISL1 positive cells detected in the outer retina ( arrows in Figure 1H and 1L ) . Laminin immunoreactivity revealed focal disruptions in the inner limiting membranes of Col4a1+/Δex40 animals ( asterisks in Figure 1F ) that were not observed in Col4a1+/+ animals . Moreover , in contrast to Col4a1+/+ eyes where the vasculature is closely associated with the inner limiting membrane , the hyaloid vasculature in Col4a1+/Δex40 eyes is most often found in the vitreous ( Figure 1B and 1F ) and , in one extreme case , the posterior chamber was devoid of detectable vasculature ( Figure 1J ) . During normal retinal development , approximately 50% of RGCs undergo programmed cell death as the visual system matures [39] , [40] . Induced or genetic disruption of the inner limiting membrane perturbs RGC localization and leads to RGC apoptosis during embryogenesis [37] . Therefore , we hypothesized that Col4a1+/Δex40 mice might exhibit increased RCG apoptosis . To test this , we co-labeled retinal sections with antibodies against ISL1 and activated Caspase-3 ( Figure 2A–2F ) and calculated the apoptotic index by counting the number of ISL1/Caspase 3 double-labeled cells ( Figure 2G ) . As retinas from Col4a1+/Δex40 mice were smaller than retinas from Col4a1+/+ mice ( Figure 2H ) , we normalized the number of double-labeled cells to the retinal cross-sectional area . Col4a1+/+ mice had low levels of ganglion cell apoptosis at E14 and E16 that increased approximately 2-fold by E18 . Although apoptotic rates in Col4a1+/Δex40 mice at E14 and E16 were not significantly different from those observed in Col4a1+/+ mice , there was a significant increase in apoptosis of ISL1 positive cells in Col4a1+/Δex40 eyes compared to Col4a1+/+ eyes at E18 ( p<0 . 05 ) – especially among mislocalized ISL1 labeled cells ( Figure 2F ) . Of note , one E18 Col4a1+/Δex40 eye had an extremely high apoptotic index ( 12 . 9 ) that was considered an outlier and was removed from subsequent statistical analyses ( see Materials and Methods ) . Interestingly , we did not observe vasculature in the posterior chamber of this eye suggesting that retinal vasculature might directly contribute to the inner limiting membrane or affect ganglion cell viability in other ways . Together , our data support that Col4a1 mutation leads to focal disruptions of the inner limiting membrane and that optic nerve hypoplasia results both from reduced production of retinal neurons and from mislocalization and subsequent apoptosis of ganglion cells during development . Based on our observations in the retina , we predicted that Col4a1+/Δex40 mice might also show pial basement membrane disruptions and cerebral cortical lamination defects that model cobblestone lissencephaly seen in MEB/WWS . To test our hypothesis , we stained coronal brain sections from adult Col4a1+/+ and Col4a1+/Δex40 mice with cresyl violet and detected abnormalities in all of the Col4a1+/Δex40 but none of the Col4a1+/+ mice examined ( Figure 3 ) . All Col4a1+/Δex40 mice had focal and variable cerebral cortex lamination defects ranging from mild distortions and ectopias to severe heterotopic regions devoid of obvious lamination ( Figure 3B–3F ) . Occasionally , Col4a1+/Δex40 mice displayed enlarged ventricles or major structural abnormalities ( Figure 3G and 3H ) . Immunolabeling with the pan–neuronal marker NeuN confirmed the neuronal identity of the ectopic cells ( Figure 4 ) . Col4a1+/Δex40 mice also had subtle but consistent defects within the hippocampus ( Figure S1 ) . The CA1 , CA3 and dentate gyrus layers of Col4a1+/Δex40 mice were less tightly organized and generally more dispersed compared to Col4a1+/+ mice and local perturbations were common . As it is the case in other animal models of MEB/WWS [41] , [42] , enhanced glial fibrillary acid protein ( GFAP ) immunoreactivity , which is reflective of astrocytic gliosis , was observed in the hippocampus and cerebral cortex of Col4a1+/Δex40 mice ( Figure S2 ) . To determine if cortical malformations were congenital or acquired , we used bromodeoxyuridine ( BrdU ) pulse labeling in utero to evaluate the localization of neurons that underwent terminal cell division during defined stages of embryogenesis . The locations of cells labeled at E14 or E16 were determined at birth ( P0 ) . In all Col4a1+/+ mice , BrdU-labeled neurons were uniformly distributed primarily in the superficial cortex ( Figure 5A and 5F ) . In contrast , the distribution of BrdU-labeled cells in mutant animals demonstrated that cortical lamination was disorganized . Focal and variable lamination defects were completely penetrant in Col4a1+/Δex40 mice ( Figure 5B–5E and 5G–5J ) . Laminin labeling of basement membranes in P0 mice revealed discontinuous pial basement membranes in all mutant mice , notably in areas adjacent to ectopias ( Figure 6 ) . Together , these findings demonstrate that Col4a1+/Δex40 mice have abnormal neuronal localization typical of cobblestone lissencephaly observed in MEB/WWS patients and suggest that these congenital defects are secondary to breaches in the pial basement membrane . Because Col4a1+/ex40 mice display ocular and cerebral abnormalities characteristic of MEB/WWS , we hypothesized that they would also have myopathy . To test this , we first confirmed that COL4A1 was present in skeletal muscle basement membrane by immunolabeling ( Figure S3 ) and performed functional , biochemical and histological analyses of muscles from young and aged Col4a1+/+ and Col4a1+/Δex40 mice . At 3 months of age , Col4a1+/Δex40 mice performed significantly worse than controls in a test of peak grip force ( Figure 7A ) . Next , we analyzed serum CK activity before and after exercise . We found no significant difference in CK levels between control and mutant mice at baseline , however , Col4a1+/Δex40 mice had a significant elevation in CK activity following exercise compared to pre-exercise Col4a1+/Δex40 and post-exercise Col4a1+/+ mice ( Figure 7B ) . Consistent with these functional and biochemical data , we also detected histological differences between Col4a1+/+ and Col4a1+/Δex40 muscles . Compared to Col4a1+/+ littermates , Col4a1+/Δex40 mice had occasional split muscle fibers and a significant increase in the number of non-peripheral nuclei – a measure of myopathy ( Figure 7C–7E ) . Importantly , the severity of myopathy was not markedly affected by age . We have shown previously that ocular dysgenesis is genetic context–dependent and that mutant F1 progeny of C57BL/6J and CAST/EiJ crosses ( CASTB6F1 ) are morphologically rescued [35] . As shown in Figure 7C , in contrast to what is observed on the C57BL/6J background , the number of non-peripheral nuclei was not increased in CASTB6F1 Col4a1+/Δex40 mice compared to their Col4a1+/+ littermates . Moreover , there were significantly fewer muscle fibers with non-peripheral nuclei in CASTB6F1 Col4a1+/Δex40 mice compared to C57BL/6J Col4a1+/Δex40 mice ( p<0 . 05 ) , indicating that the CAST/EiJ strain has one or more loci that can also ameliorate Col4a1-induced myopathy . Col4a1+/Δex40 mice display multiple hallmarks of MEB/WWS raising the possibility that COL4A1 mutations might cause CMD-like diseases in human patients . To test this , we performed direct sequence analysis of genomic DNA from a cohort of 27 patients with CMD ( see Table S1 for primers ) . Fifteen patients had diagnoses of WWS , two had diagnoses of MEB , and nine were not specifically classified as either but had CMD with variable ocular and cerebral involvement . To enrich for patients that may have dominant or semi-dominant mutations , rather than recessive mutations , most of the patients ( 23 out of 27 ) were chosen from non-consanguineous families . Finally , all patients were negative for mutations in genes currently known to underlie MEB/WWS-like diseases including LARGE , POMT1 , POMT2 , POMGNT1 , FKTN and FKRP . We identified several coding and non-coding sequence variants in COL4A1 ( Tables S2 , S3 , S4 ) . Twelve coding variants were silent and were either observed in controls or were not predicted to be splice–site-altering variants [43] . We identified four non-synonymous coding variants . Two of the four non-synonymous variants were previously identified SNPs that were highly polymorphic in patients and in controls and therefore deemed unlikely to be pathogenic . The two remaining SNPs were rare , missense variants that have not been previously reported in dbSNP and were heterozygous in independent patients . The first mutation was identified in a patient diagnosed with WWS that had lissencephaly , hydrocephalus , Dandy-Walker malformation , optic nerve hypoplasia and was hypotonic with CMD ( see Figure S4 and Text S1 for clinical details ) . An adenine to guanine transition ( A3046G ) in exon 36 substituted a methionine residue for a valine residue within the triple helical domain at amino acid number 1016 ( p . M1016V ) and was not detected in 282 control chromosomes ( Figure 8A ) . The second mutation was identified in a patient with unspecified CMD with ocular and cerebral involvement . The patient had mild gyral abnormalities , hydrocephalus , retinal dysplasia , seizures and elevated CK ( see Figure S4 and Text S1 for clinical details ) . A cytosine to guanine transversion ( C3946G ) in exon 44 substituted a glutamine residue for a glutamate residue within the triple helical domain of the protein at amino acid number 1316 ( p . Q1316E ) ( Figure 8A ) . Although this cytosine to guanine transversion was not detected in 286 control chromosomes , it was present in the paternal DNA . The first variant , COL4A1M1016V , is a mutation of a methionine residue in the Y position of the Gly-Xaa-Yaa repeat in the triple helix-forming domain . This amino acid is highly conserved and the analogous residue is a methionine in all vertebrate orthologues analyzed ( Figure 8B ) and in the COL4A1 paralogues COL4A3 and COL4A5 ( data not shown ) . Moreover , there is precedence for a Y position methionine to valine mutation in COL4A5 causing Alport syndrome [44] . The second variant , COL4A1Q1316E , is a mutation of a glutamine in the Y position residue within the triple helix-forming domain . This glutamine residue is conserved in most vertebrates ( Figure 8B ) . There is a strong preference for basic residues in the Y position of the Gly-Xaa-Yaa repeat and the mutation represents a substitution from a neutral amino acid to an acidic amino acid . Pathogenic mutations within the collagenous domain often perturb triple helix assembly and mutations in regions of low thermal stability are predicted to be more disruptive [45] . According to an algorithm that predicts collagen stability [46] , both mutations modestly reduce the thermal stability of their respective region ( Figure 8C ) although the biological relevance of this is equivocal . Pathogenic mutations in the triple helix forming domain of several types of collagens impair secretion of the collagen heterotrimers and concomitantly , misfolded proteins accumulate within cells . To assess the functional significance of the COL4A1M1016V and COL4A1Q1316E mutations , we developed an assay to test the impact of the mutant proteins in a human cell line . We stably transfected HT1080 cells with wild–type or mutant COL4A1 cDNAs and determined the relative levels of intracellular and secreted COL4A1 . To validate the assay , we tested the effect of the COL4A1G562E mutant allele that is established to cause familial small vessel disease in human patients [22] , [26] . As we predicted , when compared to HT1080 cells transfected with wild–type COL4A1 , significant intracellular accumulation of COL4A1 and concurrent decrease in secreted COL4A1 was observed in cells transfected with the COL4A1G562E mutant cDNA ( Figure 8D ) . The two putative pathogenic mutations were functionally tested using the same assay . Overall , the ratio of secreted/intracellular COL4A1 for the COL4A1M1016V mutation was reduced , however the results were variable ( n = 9 ) and did not reach statistical significance . In contrast , and similar to the established COL4A1G562E mutation , the COL4A1Q1316E mutation clearly impaired COL4A1 secretion leading to intracellular accumulation ( p<0 . 001 ) , supporting the hypothesis that the COL4A1Q1316E mutation is pathogenic . Importantly , the accumulation of both the monomeric and heterotrimeric forms of COL4A1 suggests that the COL4A1G562E and COL4A1Q1316E mutations impaired triple helix assembly and/or stability . Biochemical analyses revealed that known MEB/WWS-causing mutations act via hypoglycosylation of dystroglycan [11] . Although COL4A1 is not directly involved in post-translational dystroglycan modification , misfolded COL4A1Δex40 proteins in the endoplasmic reticulum ( ER ) might indirectly impair dystroglycan post-translational modification . Similarly , ER stress can produce reactive oxygen species [47]–[50] and exposure to reactive oxygen species can result in dystroglycan de–glycosylation [51] . Thus , Col4a1-induced pathogenesis might still act indirectly via dystroglycan hypoglycosylation or de–glycosylation . To test for alterations in dystroglycan expression and/or post-translational processing , we performed Western blot analysis on wheat germ agglutinin ( WGA ) -enriched skeletal muscle extracts and compared the amount and mobility of α– and β– dystroglycan between Col4a1+/+ and Col4a1+/Δex40 mice using a polyclonal β–dystroglycan antibody and the IIH6 α–dystroglycan antibody that recognizes the fully glycosylated , functional form of α–dystroglycan [11] . Immunoreactivity to , and mobility of , the precursor dystroglycan protein ( WGA-unbound fraction ) and α– and β– dystroglycan ( WGA-bound , glycoprotein enriched fraction ) were indistinguishable between Col4a1+/+ and Col4a1+/Δex40 mice ( Figure 9 ) . Consistent with this finding , immunolabeling of muscle sections for α– and β– dystroglycan showed similar expression patterns in the sarcolemma membrane of Col4a1+/+ and Col4a1+/Δex40 mice . These data indicate that dystroglycan expression , localization and post-translational modification are not altered in Col4a1+/Δex40 mice and that myopathy arises via disruption of the basal lamina .
In this study , we show that COL4A1 mutations cause multiple pathophysiological hallmarks of MEB/WWS in mice and possibly MEB/WWS in human patients . Mice harboring a semi-dominant Col4a1 mutation have ocular dysgenesis , cerebral cortical lamination defects and myopathy . Optic nerve hypoplasia results , at least in part , from mislocalization and increased apoptosis of RGCs during development . Cerebral cortical malformations range from subtle lamination defects to large structural abnormalities . Myopathy is mild , but consistent and significant , and is exacerbated by exercise but not by age . Importantly , myopathy was genetic background-dependent , which implies that in resistant genetic contexts Col4a1- induced myopathy might not be detected but that on permissive genetic backgrounds , myopathy could be severe . Two out of 27 MEB/WWS patients tested had COL4A1 mutations and in at least one case the mutation interfered with protein secretion . Moreover , unlike all other known causes of MEB/WWS , the cellular mechanism underlying Col4a1-induced pathology is independent of dystroglycan post-translational modification . Until now , the precise pathogenic mechanism resulting from COL4A1 mutations in human patients was poorly characterized and was only presumed to impair protein secretion and cause intracellular accumulation . Here , we have established and validated a cellular assay that demonstrates this effect . However , the relative contribution of COL4A1 deficiency in the basement membrane versus toxic intracellular accumulation to pathogenesis is difficult to dissociate and other possible mechanisms exist . Although the ratio of secreted to intracellular protein for the COL4A1M1016V mutation was not statistically different from wild–type there was an overall reduction in the ratio . It is important to bear in mind that absence of statistical significance does not necessarily imply absence of biological relevance . For instance , more efficient intracellular degradation of some misfolded proteins could prevent detection of an altered ratio of secreted to intracellular COL4A1 for some mutations . Alternatively , these data could indicate a third pathogenic mechanism whereby mutant proteins are secreted and exert a detrimental extracellular effect . In support of such a mechanism , the COL4A1M1016V mutation occurs within a putative binding site for the matricellular glycoprotein SPARC ( secreted protein acid and rich in cysteine ) [52] and could therefore act by disrupting protein-protein interaction in the extracellular matrix . These variants represent the first heterozygous mutations in MEB/WWS patients . Although generally considered to be recessive , the inheritance pattern in many MEB/WWS patients is unknown . Phenotypic variability , reduced penetrance , and de novo mutations can all explain how dominant mutations might appear recessive in small families . Here , we observed non–penetrance of the COL4A1Q1316E mutation in the father of the affected child . Families with COL4A1 mutations are only now starting to be identified but apparent non-penetrance , and asymptomatic carriers have already been reported [29] , [53] . Importantly , Col4a1-associated phenotypes in mice are not only influenced by environmental factors but are also genetic context–dependent , and reduced penetrance could reflect modifier loci . Alternatively , genetic mosaicism of dominant collagen mutations can explain asymptomatic carriers [54] . We identified mutations in two out of 27 CMD patients tested . DNA was limiting and prevented us from also sequencing COL4A2; however , evidence from mice and C . elegans support that mutations in COL4A2 may cause phenotypes similar to those resulting from mutations in COL4A1 [24] , [45] , [55] . It will be very important in the future to determine whether the COL4A1 findings extend to COL4A2 . This could have an even broader relevance as COL4A1 mutations are pleiotropic with variable penetrance and expressivity from organ to organ . It is possible that COL4A1 mutations underlie CMD in patients with different , non-MEB/WWS-like , subclasses of the disease . Based on our current data , the most likely patients are those with mild myopathy and those with clinical manifestations that overlap with some of the other COL4A1-related phenotypes described in non-MEB/WWS syndromes including porencephaly , renal disease and cerebrovascular disease . Collectively , these findings provide the impetus for COL4A1 and COL4A2 mutation analysis in further cohorts of patients with CMD and/or congenital cerebral malformations . COL4A1 mutations have been identified in families with a spectrum of diseases affecting the cerebral vasculature , although pathologies of the eyes , kidneys and muscles have also been reported [21] , [22] , [25]–[29] , [31] , [33] , [56] , [57] . Notably , COL4A1 appears to be an important genetic cause of porencephaly – a condition usually diagnosed in infants and characterized by large cerebral cystic cavities that communicate with the ventricles . Importantly , the cortical malformations present in MEB/WWS and described in the current manuscript are clinically and mechanistically distinct from porencephalic cavities , which are predicted to result from pre– or peri–natal hemorrhages in the germinal matrix . Col4a1 mutations are pleiotropic and our findings expand the phenotypic spectrum resulting from Col4a1 mutations in mice . We propose that COL4A1 mutations in human patients will reflect the pleiotropy observed in mice and will be involved in the pathogenesis of diseases clinically distinct from those reported previously . Optic nerve hypoplasia and cortical neuronal migration defects have not been described in human patients with COL4A1 mutations and a role for COL4A1 or COL4A2 in MEB/WWS-like diseases was not previously suspected . Interestingly , six families with COL4A1 mutations and cerebrovascular disease also had muscle cramps and CK elevation [28] , [33] . Although the degree of CK elevation in Col4a1 mutant mice is less than that observed in dystrophin-glycoprotein complex related disorders , it is comparable to that seen in other types of dystrophies involving extracellular matrix proteins , including collagen VI -associated Bethlem myopathy and Ullrich CMD . While the exact mechanism underlying myopathy in collagen VI-related disorders is unclear , several lines of evidence suggest that mitochondrial dysfunction may be an important player [58] . We show that genetic context is an important factor contributing to the variable penetrance and severity of Col4a1-related diseases and that the CAST/EiJ strain can modify myopathy . These findings also imply that certain genetic contexts might exacerbate myopathy and that COL4A1 mutations could also cause severe CMD . Importantly , genetic modifiers can be general or tissue specific and tissue-specific modification could help explain how mutations in a single gene can contribute to such diverse phenotypes . We also demonstrate that gene–environment interactions contribute to phenotypic variability . We have previously reported that cesarean delivery can reduce the risk of perinatal intracerebral hemorrhages and here we show that elevation in CK activity is exercise–dependent . Allelic differences could also help explain variable expressivity and severity of COL4A1-associated diseases between patients . For instance , a mutation that affects heterotrimer assembly might have broader effects than a mutation that specifically affects interactions with cell surface receptors , growth factors or other extracellular matrix molecules . Interestingly allelic differences are already emerging pointing to genotype/phenotype correlations in some families [28] , [33] . Pial basement membrane integrity is critical for normal cortical development and insufficient COL4A1 in basement membranes renders them prone to disruption . Breaches in the pial membrane cause alterations in cortical neuronal distribution [17] , [59] , [60] . These are not intrinsic neuronal migration defects but are secondary to disorganization of the cortical marginal zone , and to defects in anchorage of glial endfeet and formation of the Cajal-Retzius cell layer [16] . Reactive gliosis and increased GFAP labeling may reflect broader breaches of the glia limitans including the blood brain barrier [11] , [42] . Thus , while some structural defects might be due to disruptions of the pial basement membrane , other pathology might be attributed to disruptions of vascular basement membranes and/or defects in blood brain barrier function . Understanding the precise mechanism underlying myopathy is complicated by the presence of COL4A1 in basement membranes of the sarcolemma , myotendonous junctions and neuromuscular junctions . Notably , Col4a1 mutant mice have transient neuromuscular junction abnormalities that reportedly resolve by 3 weeks of age [61] . Determination of the primary site of pathogenesis for myopathy will likely require conditional expression of the Col4a1 mutation . However , evidence from other model systems suggests that the primary mechanism is load-induced muscle fiber detachment . For instance , the most common form of CMD ( MDC1A ) is caused by mutations in the basement membrane component laminin alpha 2 ( LAMA2 ) [62] and in zebrafish with mutations in the LAMA2 ortholog , muscle contractions lead to muscle fiber detachment and loss [63] . This mechanism is consistent with exercise-induced CK elevation in Col4a1 mutant mice . This mechanism is also consistent with the observation that C . elegans Col4a1 mutants die with ruptured basement membranes shortly after muscle contractions begin [45] , [55] . A similar mechanism in alveolar basement membranes could also explain why newborn Col4a1 mutant mice have respiratory distress immediately after starting to breathe [22] . Thus , myopathy resulting from mutations in basement membrane components LAMA2 and COL4A1 might share a common pathogenic mechanism whereby contraction-induced load leads to muscle fiber detachment . Given this potential shared mechanism and the phenotypic variability of COL4A1 mutations , we propose that MDC1A patients that are negative for LAMA2 mutations are suitable candidates for screening for mutations in COL4A1 and COL4A2 . Importantly , if a component of the pathology is secondary to deleterious consequences of compromised blood brain barrier and load-induced myopathy , there is the potential for therapeutic interventions to blunt the severity of this devastating disease . For example , conditions that promoted protein folding and increased COL4A1 secretion in C . elegans mutants were able to rescue muscle contraction-induced basement membrane disruptions and promoted viability and survival [55] . Thus , chemical chaperones , or other methods to promote protein folding , might have therapeutic potential in human patients and improve the prognosis for MEB/WWS patients .
Heads were equilibrated in 20% sucrose in phosphate buffered saline ( PBS ) overnight at 4°C , embedded in OCT compound ( Sakura Finetek ) , and flash frozen using dry ice/ethanol . For each genotype we analyzed six eyes at E14 and E16 and eighteen eyes at E18 . For each eye , at least 3 position-matched , transverse sections ( 20 µm ) were co-labelled with antibodies against Islet-1 ( 1∶10 , Developmental Studies Hybridoma Bank 39 . 4D5sup and laminin ( 1∶1000 , Abcam ) , or Islet-1 and activated Caspase-3 ( 1∶1000 , R&D Systems ) . Sections were blocked ( Tris-buffered saline with 0 . 1% Triton-X ( TBST ) containing 5% normal goat serum ( Invitrogen ) ) for 1 hour at room temperature ( RT ) and washed twice for 2 min with TBS . Labeling was performed in TBS containing 3% BSA ( Sigma ) overnight at 4°C . Sections were incubated with Alexa Fluor 488 goat anti-mouse and Alexa Fluor 594 goat anti-rabbit secondary antibodies ( 1∶1000 , Invitrogen ) for 2 hours at RT and cover-slipped with Vectashield Hard Set with DAPI ( Vector Labs ) . Adult brains were fixed by trans-cardiac perfusion with 4% paraformaldehyde ( PFA ) in 0 . 1 M sodium phosphate , pH 7 . 4 then post-fixed in PFA at 4°C overnight and prepared for cryosectioning as described above . For Nissl staining , coronal sections ( 25 µm ) were hydrated for 5 min in buffer ( 0 . 2% sodium acetate , 0 . 3% glacial acetic acid ) then incubated for 10 min in Nissl stain ( 0 . 02% cresyl violet in buffer ) . Sections were washed in water ( 2×2 min ) and de-stained for 15 sec ( 0 . 3% glacial acetic acid in 70% ethanol ) before being dehydrated , cleared in xylene and cover-slipped with Permount ( Fisher ) . For GFAP and NeuN immunostaining , sections were incubated in 1% H202 in PBS for 15 min , washed in PBS , blocked in PBS containing 5% NGS , 0 . 1% Triton-X , and 1% BSA in PBS for 1 hour at RT . Sections were incubated with anti-GFAP antibody ( 1∶500 , Chemicon ) or anti-NeuN antibody ( Chemicon 1∶500 ) overnight at 4°C , washed in PBS containing 0 . 1%Triton-X , and incubated for 2 hr with biotinylated goat anti-rabbit or goat anti-mouse antibody ( 1∶500 , Vector Labs ) . Sections were then incubated in avidin-biotin solution ( Vector Labs ) for 90 min and immunoreactivity was visualized by treating sections with diaminobenzidine ( DAB , Vector Labs ) . Sections were dehydrated , cleared in xylene and cover-slipped with Permount ( Fisher ) . For BrdU labeling , pregnant mice were injected with BrdU ( 50 mg/kg ) at gestational days 14 , or 16 . At P0 , heads were fixed in 4% PFA for 4 hr , embedded in OCT , snap frozen in dry ice/ethanol bath . Cryosections ( 25 µm ) were incubated in sodium citrate buffer ( 10 mM sodium citrate , pH 6 . 0 , 0 . 05% Tween-20 ) for 30 min starting at 90°C and allowed to cool , rinsed in water , incubated in 1 M HCl containing 0 . 2 mg/ml pepsin for 10 min at RT , in 2 N HCl for 20 min at 37°C . Sections were then washed and labeled with anti-BrdU ( 1∶30 , Accurate Chemical ) and biotinylated goat anti-rat secondary ( 1∶500 , Vector Labs ) . For laminin immunolabeling of P0 brains , heads were processed as described in the retinal analyses section and 20 µm coronal sections were immunolabeled with anti- laminin antibody ( 1∶1000 , Abcam ) . Peak grip force was determined using a Grip Strength Meter ( Columbus Instruments ) and using the average from 3 consecutive trials on each animal . For CK measurements , blood was drawn before and after exercise from the tail vein in a hematocrit tube , centrifuged for 5 min , and the serum was collected . CK activity was measured using CK-NADP assay ( Raichem ) and a microplate reader ( Biorad ) . Exercise was 30 minutes with a 15° downhill grade on a treadmill equipped with a shock plate ( Columbus Instruments ) . Animals were started at 7 m/min and increased 3 m/min every 2 min until maximum of 16 m/min speed was reached . Non-peripheral nuclei were evaluated in quadriceps and tibialis anterior muscles dissected and frozen in liquid nitrogen-cooled isopentane . Cryosections ( 8 µm ) were stained with hematoxylin and eosin for histopathology or labeled with anti-pan laminin antibody ( Sigma ) , followed by an anti-rabbit AlexaFluor-488 secondary antibody , and the nuclei were labeled with DAPI . The observers were masked to genotypes and counted between 2000–5000 fibers per animal . For dystroglycan enrichment and immunoblotting , quadriceps muscle biopsy ( 100 mg ) was homogenized in TBS ( pH 7 . 5 ) containing 1% Triton-X and protease inhibitors ( Thermo Scientific Pierce ) . The soluble fraction was incubated overnight at 4°C with 200 ul of wheat germ agglutinin ( WGA ) -agarose beads ( Vector Laboratories ) to enrich for glycosylated proteins . Beads were washed three times with 1 ml TBS containing 0 . 1%Triton-X and protease inhibitors ( Thermo Fisher ) and were boiled in SDS-PAGE loading buffer for 5 minutes . Proteins ( 50 µl ) were separated on 10% SDS-PAGE and transferred to polyvinylidene fluoride ( PVDF ) membranes ( BioRad ) . Membranes were blocked for 2 hours at room temperature in 5% non-fat milk in TBS containing 0 . 1% Tween-20 , incubated overnight with a mouse monoclonal anti- α-dystroglycan antibody recognizing the glycosylated form of α-dystroglycan ( IIH6; 1∶1000 , Millipore ) , or rabbit polyclonal anti- β-dystroglycan antibody ( raised against the C-terminus of dystroglycan precursor; 1∶400 , Santa Cruz ) diluted in blocking buffer . Membranes were washed in TBS containing 0 . 1% Tween-20 , incubated 2 hours at room temperature with horseradish peroxidase-conjugated secondary antibody raised in donkey ( anti-mouse IgM , and anti-rabbit IgG , respectively; 1∶10 000 , Jackson Immunoresearch ) diluted in blocking buffer . Immunoreactivity was visualized using chemiluminescence ( SuperSignal West Pico Chemiluminescent Substrate , Thermo Scientific ) . For immunostaining , muscle cryosections ( 25 µm ) were incubated with either β-dystroglycan ( 1∶150 ) or with α-dystroglycan ( 1∶400 ) antibody diluted in blocking buffer ( 10% normal donkey serum , 0 . 2% BSA in PBS containing 0 . 1% Triton-X ) overnight at 4°C and incubated with Alexa Fluor 488 conjugated donkey anti-rabbit ( Invitrogen ) or cy5- conjugated donkey anti-mouse IgM ( Jackson Immunoresearch ) . For COL4A1 immunolabeling , muscle cryosections ( 25 µm ) were fixed in acetone for 10 min , rinsed in TT buffer ( 50 mM Tric-HCl , pH 7 . 4 , 0 . 1% Tween-20 ) , incubated in acid solution ( 0 . 1 M KCl/HCl , pH 1 . 5 ) , washed three times in TT buffer and incubated for an hour in blocking buffer ( 10% normal donkey serum and 2 mg/ml BSA in Tris buffer ) . Sections were then incubated with rat anti- COL4A1 ( H11 ) monoclonal antibody ( 1∶200 , Shigei Medical Research Institute , Japan ) diluted in TT buffer overnight at 4°C and for 1 hour with Alexa Fluor 488 conjugated donkey anti-rat secondary antibody ( Invitrogen ) and cover-slipped using mowiol mounting medium ( Calbiochem ) . Images were captured using an AxioImager M1 microscope equipped with an AxioCam MRm digital camera for fluorescence or AxioCam ICc3 for brightfield and AxioVision software ( Zeiss ) . Genomic DNA ( 10 ng/µL ) sequencing was performed using ABI BigDye v3 . 1 and analyzed using Sequencher software ( Gene Codes Corporation ) . Control samples are from ethnically matched adults with no history of neurological disease . HT1080 Human fibrosarcoma cells were transfected using Superfect reagent ( Qiagen ) with the expression vector pReceiver–M02 vector ( GeneCopoeia ) containing a CMV promoter upstream of GFP ( to evaluate transfection efficiency ) , wild-type Col4a1 or mutant Col4a1 cDNA cloned and a neomycin resistance cassette , allowing stably transfected cells to be selected using G418 ( Invitrogen ) . After 12 days of G418 selection ( 600 mg/ml ) , individual surviving clones were isolated and expanded in presence of 600 mg/ml of G148 . Stably transfected HT1080 cells were cultured in Dulbecco's modified Eagle's medium ( DMEM ) supplemented with penicillin , streptomycin , nonessential amino acids , glutamine , sodium pyruvate , G418 ( 250 mg/ml for maintenance ) , 10% Fetal Bovine Serum ( FBS ) and ascorbic acid ( 50 mg/ml ) at 37°C in 5% CO2 in a humid atmosphere until they reach 80–90% confluence . Then , cells were serum-deprived for 24 hours under the same culture conditions and harvested and protein were extracted from HT1080 cells using cell extraction buffer containing 0 . 05 M Tris-HCl pH 8 . 0 , 0 . 15 M NaCl , 5 . 0 mM EDTA , 1% NP-40 , and protease inhibitors ( Pierce ) at 4°C . After centrifugation ( 13000 rpm , 20 min at 4°C ) , the soluble fraction of the whole cell lysate was collected for subsequent Western blot analysis . The conditioned medium was collected at the same time and supplemented with protease inhibitors . Determination of protein concentration in the soluble fraction was performed using a DC protein assay ( BioRad ) and 45 ug of total protein were separated on a 4–15% gradient SDS-PAGE under non-reducing conditions and transferred to polyvinylidene fluoride ( PVDF ) membranes ( BioRad ) . For the conditioned medium , the volume loaded on the gel was adjusted based on the protein concentration of the soluble fraction , which is assumed to reflect the number of cells for a given sample . Membranes were blocked for 2 hours at room temperature in 5% non-fat milk in TBS containing 0 . 1% Tween-20 , and overnight at 4°C in 3% BSA in TBS . Membranes were then incubated with rat anti- COL4A1 ( H11 ) monoclonal antibody ( 1∶100 , Shigei Medical Research Institute , Japan ) in 1% BSA in TBS for 3 hours at room temperature and were washed in TBS containing 0 . 1% Tween-20 , incubated 2 hours at room temperature with horseradish peroxidase-conjugated secondary antibody raised in donkey ( anti-Rat IgG 1∶10 000 , Jackson Immunoresearch ) diluted in 5% non-fat milk in TBS containing 0 . 1% Tween-20 . Immunoreactivity was visualized using chemiluminescence ( SuperSignal West Pico Chemiluminescent Substrate , Thermo Scientific ) . Densitometric analysis was performed on low exposure images using the NIH Image J software ( National Institutes of Health ) . For quantitative analysis of the ratio of secreted to intracellular mutant COL4A1 protein , the amount of COL4A1 detected in the conditioned medium was divided by the amount of intracellular COL4A1 normalized with actin . In experiments where two groups were compared , samples were compared by a Student's T-test with p<0 . 05 considered significant . In experiments where more than two groups were compared , samples were analyzed by one-way ANOVA followed by a Tukey's post hoc test with p<0 . 05 considered significant . For calculation of apoptotic index , one E18 Col4a1+/Δex40 eye had an extremely high apoptotic index ( 12 . 9 ) that was considered an outlier by Grubbs' test ( p<0 . 01 vs . all mutants and Z = 2 . 93248; vs . all samples Z = 3 . 26997 ) and was removed from subsequent statistical analyses . | Muscle-eye-brain disease ( MEB ) and Walker-Warburg Syndrome ( WWS ) are devastating childhood diseases that belong to a subgroup of congenital muscular dystrophies ( CMDs ) characterized by ocular dysgenesis , neuronal migration defects , and congenital myopathy . Genetic studies have revealed a number of genes involved in the etiology of CMDs , and subsequent studies show that alterations in dystroglycan glycosylation underlie MEB/WWS . However , over half of MEB/WWS patients do not have mutations in known genes encoding glycosyltransferases , suggesting that other genes are involved . Here , we describe a novel and genetically complex mouse model for MEB/WWS and identify putative heterozygous mutations in COL4A1 in two MEB/WWS patients . We identify a novel gene implicated in the etiology of MEB/WWS , provide evidence of mechanistic heterogeneity for this subgroup of congenital muscular dystrophies , and develop an assay to test the functional significance of putative COL4A1 mutations . Our findings represent the first evidence for a dominant mutation leading to MEB/WWS–like diseases and expand the spectrum of clinical disorders resulting from Col4a1/COL4A1 mutations . | [
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"o... | 2011 | COL4A1 Mutations Cause Ocular Dysgenesis, Neuronal Localization Defects, and Myopathy in Mice and Walker-Warburg Syndrome in Humans |
Cytotoxic T lymphocytes ( CTLs ) are important agents in the control of intracellular pathogens , which specifically recognize and kill infected cells . Recently developed experimental methods allow the estimation of the CTL's efficacy in detecting and clearing infected host cells . One method , the in vivo killing assay , utilizes the adoptive transfer of antigen displaying target cells into the bloodstream of mice . Surprisingly , killing efficacies measured by this method are often much higher than estimates obtained by other methods based on , for instance , the dynamics of escape mutations . In this study , we investigated what fraction of this variation can be explained by differences in peptide loads employed in in vivo killing assays . We addressed this question in mice immunized with lymphocytic choriomeningitis virus ( LCMV ) . We conducted in vivo killing assays varying the loads of the immunodominant epitope GP33 on target cells . Using a mathematical model , we determined the efficacy of effector and memory CTL , as well as CTL in chronically infected mice . We found that the killing efficacy is substantially reduced at lower peptide loads . For physiological peptide loads , our analysis predicts more than a factor 10 lower CTL efficacies than at maximum peptide loads . Assuming that the efficacy scales linearly with the frequency of CTL , a clear hierarchy emerges among the groups across all peptide antigen concentrations . The group of mice with chronic LCMV infections shows a consistently higher killing efficacy per CTL than the acutely infected mouse group , which in turn has a consistently larger efficacy than the memory mouse group . We conclude that CTL killing efficacy dependence on surface epitope frequencies can only partially explain the variation in in vivo killing efficacy estimates across experimental methods and viral systems , which vary about four orders of magnitude . In contrast , peptide load differences can explain at most two orders of magnitude .
Adaptive immune responses exert important selective pressures on viral infections through various mechanisms , such as neutralization of virus particles by antibodies or killing virus-infected cells by cytotoxic T lymphocytes ( CTLs ) . Efforts to quantify the ability of CTLs to kill infected host cells have yielded results with considerable variation [1 , 2] . In fact , estimates of the efficacy of CTLs at recognizing and clearing infected viral target cells in vivo vary by several orders of magnitude between experimental designs and viral study systems [1 , 3 , 3–16] . In vivo CTL killing efficacy estimates exist for the following types of viral study systems: HIV/SIV [4–11] , lymphocytic choriomeningitis virus ( LCMV ) [3 , 12–15] , polyoma virus [16] , HTLV-1 [1] , and bovine leukemia virus ( BLV ) [1] . The killing efficacy of CTLs in HIV [5 , 6] , SIV [4 , 9 , 10] , HTLV-1 [1] , and bovine leukemia virus infection [1] yield distinct , relatively low estimates . These estimates capture the rate at which a target cell is cleared by the total CTL response , and range from 0 . 1d−1 to 10d−1 [1] . In contrast , polyoma virus and LCMV have been shown to yield high killing efficacy estimates of 20−500d−1 for epitope-specific clones in either acute or chronic infections [1 , 3 , 13–17] . Hence , compared to LCMV and polyoma virus , HTLV-1 and BLV yield much lower estimates . The variation in these estimates might be primarily due to the viral study systems . The experimental methods employed to obtain the estimates for HIV/SIV , HTLV-1 and BLV rely on distinct approaches . HIV estimates are based on two approaches: the injection of CTL [5] and on the observation of viral escape mutants [4 , 6] , with an almost hundredfold difference between some estimates [1] . In contrast , the HTLV-1 and BLV estimates are based on assessing the decay rate of labeled cells , in a similar fashion as employed for LCMV and polyoma virus [1] . Estimates for LCMV and polyoma virus rely on an experimental technique referred to as in vivo killing assay . This technique involves the injection of target cells , loaded with viral peptides on their surface , into the bloodstream of mice . The subsequent tracking of their disappearance in relation to unpulsed control cells allows for the estimation of the effect of killing by CTLs . In most of these assays , the number of viral peptides that each target cell displays is unnaturally high , three orders of magnitude higher than on naturally infected cells ( see Discussion ) . In part , the discrepancy between the in vivo CTL efficacy estimates across experimental methods and study systems is likely to arise from the unnaturally high peptide loads on target cells in in vivo killing assays . The highest per CTL killing efficacies have been measured in LCMV in vivo killing assays with high peptide loads [14] . When reducing peptide loads to very low levels which make target cells unrecognizable by CTL , we accordingly expect a decrease per CTL killing efficacies to almost zero . Hence , peptide load variation could theoretically explain the entire variation in CTL killing efficacies . In this study , we investigate to what extent CTL killing efficacies depend on peptide load on target cells , and what proportion of the entire CTL efficacy variation can be explained by this effect . To this end , we conducted CTL in vivo killing assays in mice acutely or chronically infected with LCMV Docile . During chronic infections , CTLs are assumed to become dysfunctional or exhausted , displaying poor effector function [18] . We estimated the killing efficacies of effector , memory and chronic-infection CTLs for different peptide loads using mathematical models that extend previous approaches [15] . The types of CTL were classified by the administered dose of the LCMV Docile and the time after infection ( see Materials and Methods ) . We find that the per cell killing efficacy first increases with peptide loads , and saturates above a peptide load of approximately 10−1 μg/ml . For physiologically reasonable peptide loads however , which we estimate to lie around 10−3 μg/ml ( see Discussion ) , the CTL efficacy is only one order of magnitude lower than at saturation for all three CTL types . This leaves most of the differences in in vivo CTL efficacy estimates unexplained . We also found that individual CTL during chronic infections kill cells with physiological peptide loads at a higher rate than effector or memory CTL . This result needs to be interpreted in the context of whether exhausted CTLs display reduced killing efficacies [18] . As in studies with high peptide loads [15] , we found no evidence that CTL killing in chronic infections is impaired .
We adopt a statistical framework which allows us to estimate the killing efficacy dependence on the pulsing concentration of peptides on target cells separately for each of the treatment groups ( acute , chronic and memory groups ) , and to obtain estimates for the combined data set of all groups . Following the notation established in [15] , we index mice with i = 1 , … , m , and label the time points tl , where l = 1 , ⋯ , L . Additionally , we have target cells pulsed at increasing concentration λd , where d = 1 , … , D . For each mouse i the experimental methods allow us to retrieve the proportions of transferred target cells pulsed at concentrations λd , F ˜ λ d , i ( t l ) , as well as for unpulsed cells , F ˜ u , i ( t ) in the blood at each time point . These data permit to estimate the probability of a target cell in mouse i pulsed with peptide concentration λd to be killed by the GP33-specific CTL response until time tl: p ^ i , λ d ( t l ) = 1 - F ˜ λ d , i ( t l ) f d F ˜ u , i ( t l ) , ( 1 ) where as in [15] , fd is used to correct for the different ratios that might arise in the inoculum . To estimate fd , we calculated the ratios of cells pulsed with concentration λd and unpulsed cells at each time point tl in naïve mice , and took the average of those values over all time points . The key assumption for this procedure is that CTLs do not affect the proportions of transferred target cells in naïve mice . To estimate CTL efficacies and other quantities of interest in the killing assay data , a mathematical model that predicts the fraction of killed target cells at time tl and peptide concentrations λd , p ( tl; λd ) ( see Results ) , is fitted to the data p ^ i , λ d ( t l ) . For such a mathematical model two assumptions need to be made for the killing . First , how peptide load λ affects the killing rate constant k of CTLs has to be specified . Here , we assume a model with two parameters kmax and λ 1 2: k ( k max , λ 1 2 , λ ) ( see Results for interpretation of these parameters ) . Second , a further assumption is required as to how the total killing efficacy is affected by the presence of other CTLs within the same compartment . Here , a general model might describe the net effect of the overall epitope-specific CTL frequency g ( C ) , where C denotes the proportion of CTLs specific to the pulsed epitope among all splenocytes . The total killing —usually denoted by f ( k , C ) [3]— is captured by a mathematical expression incorporating both killing dependence on pulsing load and CTL saturation: f ( k ( k max , λ 1 2 , λ d ) , g ( C i ) ) . Fitting is realized by employing a least square algorithm on the arcsin-square-root transformed data and probabilities [22] . The expected killing probabilities depend upon the model of choice , as shown in ( 3 ) . Hence , the algorithm minimizes: ∑ d = 1 D ∑ i ∈ I T ∑ l = 1 L ( arcsin ( p ^ ( t l ; f ( k ( k max , λ 1 2 , λ d ) , g ( C i ) ) ) ) - arcsin ( p i , λ d ( t l ) ) ) 2 , ( 2 ) where IT denotes the index set of mice over which the minimization is carried out . These data can stem from the mice within the same treatment group , or from a combined data set from all treatment groups . The parameters in the killing model f ( k , C ) , such as kmax and λ 1 2 , are estimated by incorporating the model into Eq ( 3 ) , and fitting it to the observed fraction of pulsed target cells ( 1 ) . We used the R language for statistical computing [23] for the mathematical analysis performed on the data .
The acute , chronic and memory groups differed in the overall frequencies of CD8+ T cells in the spleen four hours after the transfer of target cells ( Fig 3A . ) . We performed two-tailed t-tests on the log-transformed frequencies among all groups to assess the inter-group differences . Applying the Holm-Bonferroni correction , we found that only half of the group pairs differed significantly . Acute and memory groups ( p = 0 . 31 ) , as well as the naïve and memory groups ( p = 0 . 03 ) did not differ significantly in their total CD8+ T cell frequency . We also measured the GP33-specific CD8+ T cells in the spleen ( Fig 3B . ) . All groups differed significantly , with the exception of acute and memory groups ( p = 0 . 26 ) . For both , the overall frequency of CD8+ T cells and the frequency of GP33-specific CD8+ T cells in the spleen , the acute and memory groups attained the highest values , whereas the number of cells in the chronically infected groups was lower compared to the acute and memory group but above the naïve group . The level of pulsing of target cells heavily influenced their clearance by GP33-specific CD8+ T cells . The more peptides were loaded onto target cells before transfer , the faster the target cells disappeared relative to the total number of target cells . Fig 4 . shows that in the naïve group relative target cell frequencies stayed approximately constant over the whole time course of the observation . In contrast , target cell frequencies for the other three groups show a significant reduction of most pulsed target cells when compared to unpulsed cells . Target cells which were pulsed at concentrations of 10 − 4 μ g m l of GP33 epitope increase in frequency in a similar fashion as the unpulsed cells , indicating that these pulsed cells are killed at very low rates . The measurement of the target cell frequencies relative to control cells contains information about how fast these target cells are cleared by CD8+ T cells . To extract this information , mathematical modeling is required to synthesize the migration of cells between the blood and secondary lymphatic tissues with the dynamics of killing by CTL . The mathematical model we used extends the previous model [15] by explicitly describing the dependence of the killing rate on the peptide load on the target cells . To predict the proportions of killed target cells with a mathematical model , more detailed information is required as to how the target cells circulate in the blood and in which compartments they are killed . In previous work [15] , we conducted experiments in naïve mice to determine at what rates target cells migrate to different compartments , such as the spleen , lung , liver and blood of mice . In these experiments , the total fraction of transferred target cells had been measured in all compartments over time . In a first step , we had observed that the target cells are likely to exclusively home to the spleen . For this reason , we assume that all target cells are killed in the spleen only . In a second step , we had calculated the net flux rate of target cells into the spleen , μ ( t ) . In the present study , we use the the estimate of μ ( t ) from [15] . The calculation of μ ( t ) is based on the existence of two compartments , a risk compartment –the spleen– where target cells can be cleared , and a non-risk compartment where they are not actively cleared . The net flux μ ( t ) between these two compartments constitutes a simplification to fluxes employed for inference in earlier models [3 , 13] and should not be equated to such fluxes . How efficiently the target cells are killed in the spleen by CD8+ T cells is determined by how abundant GP33-specific CD8+ T cells are in the spleen and the peptide load λ . These effects are mathematically captured in an expression for the total killing rate of the target cell population , f ( k , λ , C ) . In this expression , k denotes the killing rate constant that describes the functional relationship between killing rate , CTL abundance C , and peptide load . The form of f ( k , λ , C ) will be specified below . We denote the proportion of killed target cells pulsed at concentration λ at time t by p ^ i , λ ( t ) . With the previously determined net flux rate μ ( t ) of cells between spleen and blood , and the total killing rate f ( k , λ , C ) we can derive the probability of a target cell to be killed by CTL’s until time t: p ( t ; k , λ , C ) = { 1 - ( e ( - ∫ 0 t μ ( s ) d s ) + ∫ 0 t e ( - ∫ 0 u μ ( s ) ds ) μ ( u ) e ( - f ( k , λ , C ) ( t - u ) ) d u ) if t ≤ t 0 p ( t 0 ; k , λ , C ) + ∫ 0 t 0 e ( - ∫ 0 u μ ( s ) d s ) μ ( u ) e ( - f ( k , λ , C ) ( t 0 - u ) ) d u ∫ t 0 t e ( ∫ t 0 u μ ( s ) - f ( k , λ , C ) d s ) f ( k , λ , C ) d u if t > t 0 , ( 3 ) where , t0 denotes the time at which the netflux rate μ ( t ) becomes negative [15] . The derivation of this expression is based on the assumption that the target cells’ probability to be killed in the spleen depends on the target cells’ transition rate through the spleen , which roughly corresponds to μ ( t ) . The dynamics of target cell circulation changes with the sign of μ ( t ) : If μ ( t ) is positive , the probability of a target cell to be located in the spleen , and hence to be killed by CD8+ T cells , increases . If μ ( t ) is negative , this risk decreases . A detailed derivation of Eq ( 3 ) is provided in the supplementary information of [15] . To fit Eq ( 3 ) to the observed frequencies of pulsed cells , p ^ i , λ ( t ) , we need to specify how the killing rate f ( k , λ , C ) depends on the level of GP33-specific CD8+ T cells in the spleen and the peptide load λ . Here , we assume this dependence to be given by: f ( k , λ , C ) = k ( k max , λ 1 2 , λ ) C = k max λ λ 1 2 + λ C , ( 4 ) This expression assumes that the killing rate linearly increases with the frequency of GP33-specific CD8+ T cells , known as the mass-action killing assumption [24] . The parameters kmax and λ 1 2 characterize how the killing rate constant depends on the peptide load on the target cells ( Fig 5 . ) . kmax is the maximal killing efficacy and λ 1 2 accounts for the sensitivity of CTL’s to the frequency of presented epitopes on the target cell surface . This model disentangles two aspects of the per cell killing efficacy k: the sensitivity parameter λ 1 2 determines the peptide loads required for a CTL to kill , while the parameter kmax describes the maximal killing capacity that can be reached per cell . In principle , it is possible that the hierarchy of killing abilities between CTL population depends on the peptide load on the target cells . For example , the CTL population described by the blue curve in Fig 5 . is less sensitive to the peptide concentration on target cells than the other CTL populations and is therefore less efficacious , except for very high peptide loads . We fitted function ( 3 ) assuming the killing efficacy dependence model defined in Eq ( 4 ) to the data . We found that the two parameters characterizing the killing rate in the mass-action killing model differed significantly between the acute , memory and chronic groups ( F-test , p = 2 ⋅ 10−33 ) . For this reason , we analyzed the three groups separately from this point onwards . The maximum likelihood estimates for the maximum killing parameter kmax and the sensitivity λ 1 2 , and their confidence intervals are listed in Table 1 and visualized in Fig 6 . The estimates for kmax and λ 1 2 show a marked dominance of the maximum killing rate for chronically infected mice . The estimated maximal killing efficacy for the acutely infected mice ( kmax = 1 . 71 min−1 ) is around three times smaller than the corresponding efficacy for chronically infected mice ( kmax = 4 . 88 min−1 ) , and about 1 . 4 times larger than the memory group mice ( kmax = 1 . 19 min−1 ) . We calculated the associated minimal half-lifes by factoring in the proportion of GP33-specific splenocytes . The half-lifes calculated are 10 . 64 min , ( 95% CI: ( 6 . 65 , 14 . 62 ) ) for the acute , 22 . 58 min , ( 95% CI: ( 18 . 82 , 26 . 33 ) ) for the chronic and 19 . 09 min , ( 95% CI: ( 16 . 11 , 22 . 08 ) ) for the memory groups . The decimal logarithm of the epitope recognition sensitivity was estimated to be highest for the acute group ( 10 − 2 . 24 μ g ml ) , and almost identical for the chronic and the memory groups ( 10 − 2 . 14 μ g ml , 10 − 2 . 13 μ g ml ( Table 1 ) ) . Fig 7 . shows the fits of function ( 3 ) incorporating ( 4 ) for each group . The five curves shown for each group correspond to five peptide loads inserted into function ( 3 ) , which is parametrized with the estimates in Table 1 . Note that to generate all curves within a group only two parameter values are required . The simple model ( 4 ) is capable to successfully capture the most pronounced features of the data remarkably well . By using bootstrapping , we were able to calculate 95% confidence bands for the per-cell efficacy profile across all peptide loads ( Fig 8 . ) . The CTL’s in the chronically infected mice show larger killing efficacies than the other groups . The acutely infected group reveals significantly larger killing efficacies for concentrations up to 10 − 1 μ g ml compared to mice from the memory group . Thus , although hierachies that change with peptide loads would be theoretically possible in our model , as shown in Fig 5 . , we infer a clear and unchanging hierarchy across peptide loads . According to the mass-action assumption the killing rate increases linearly with the frequency of CTL . At very high CTL frequencies , however , the killing rate will stop to increase and saturate . Recent studies based on cellular automata predict a threshold in CTL frequencies of 0 . 03 , above which saturation effects in CTLs should not be neglected [25] . Below this threshold , mass action dynamics is an appropriate approximation [26] . In our data , the threshold is exceeded in the acute group ( ⟨Ca⟩ = 0 . 042 ) and slightly in the memory group ( ⟨Cm⟩ = 0 . 031 ) , but not the chronic group ( ⟨Cp⟩ = 0 . 006 ) . For this reason , we relaxed the mass-action assumption and assumed that the killing rate saturates with increasing CTL frequencies . Saturation in CTL frequencies implies that the killing efficacy per CTL approaches an upper limit with increasing CTL numbers . The individual CTL killing efficacy is thus impaired by the presence of other CTLs in the same compartment . If we incorporate the saturation in CTL frequencies into our model for killing , we obtain the following killing rate: f ( k ( k max , j , λ 1 2 , j , λ ) , C 1 2 , j ) = k max , j λ λ 1 2 , j + λ · C j C 1 2 , j + C j ( 5 ) Here j ∈ {a , p , m} denotes the acute , chronic and memory groups , respectively . C 1 2 , j is the CTL frequency , at which the saturation effects in Cj are half-maximal , and is sometimes confusingly referred to as the saturation threshold . With the adoption of a saturation model , the meaning of the killing efficacy k , and with it of the parameter kmax changes . In the mass action model , k is the per cell killing efficacy induced by a peptide load λ . Therefore , kmax signifies the maximum per cell killing efficacy that can be attained by a CTL . However , in the saturation model , k and kmax have a less intuitive meaning . Here , k is the actual killing rate exerted by all peptide-specific cells at a particular peptide load λ accounting for CTL saturation effects . Hence , in the saturation model , kmax captures the maximum killing rate that can be reached by the entire CTL population specific to a particular peptide . While it is conceivable that the half-maximum CTL frequencies C 1 2 , j differ by group , we do not have the resolution in our experimental data to determine these parameters for each group individually . This is due to the very low variation of CTL frequencies in different mice within the groups . We therefore defined killing model variants of increasing complexity , starting with a variant in which all parameters are equal between groups , to variants in which increasing number of parameters differ . We refer to these model variants as Model A , B , C , and D . The choice of these models was biologically motivated , and represents a subset of all theoretically conceivable combinations of inequalities between group parameters . We performed F-tests between these four models . In model A we assume all maximum killing efficacies within treatment groups to be equal kmax , a = kmax , p = kmax , m , all sensitivities on concentration between groups to be equal , λ 1 2 , a = λ 1 2 , p = λ 1 2 , m , as well as the saturation levels for CTLs , C 1 2 , a = C 1 2 , p = C 1 2 , m . Model B is given by the assumption that sensitivities between the treatment groups are independent or not necessarily equal , λ 1 2 , a ≠ λ 1 2 , p ≠ λ 1 2 , m . Model C is given by assuming an difference between memory cell CTL saturation levels and effector cell saturation levels: C 1 2 , a = C 1 2 , p ≠ C 1 2 , m . Model D adds further complexity to model C by relaxing the assumption of equal maximum killing efficacies: kmax , a ≠ kmax , p ≠ kmax , m . We found that model B provides a significantly better fit than model A ( p = 3 . 53 ⋅ 10−9 , by F-test ) . Model C provides a significant improvement of a fit over model B ( p = 2 . 21 ⋅ 10−5 ) . Intriguingly , model C ( six parameters ) does also lead to a better fit of the data than the combination of all group-wise fits of the mass-action kinetics model with killing efficacy dependence on pulsing concentrations ( also six parameters , identical data ) . The mass action model leads to a residual sum of squares ( RSS ) of 3 . 43 , whereas model C leads to an RSS of 3 . 33 . Also when comparing these two models by the Akaike Information Criterion ( AIC ) , model C is associated with a smaller information loss ( AIC: 301 ) than the mass-action model ( AIC: 308 . 14 ) . Here , AIC was calculated as AIC = 2k + n log ( RSS ) [27 , 28] , where the number of parameters in the model is k = 6 and the number of observations is n = 240 , see S1 Text . The fit of model C to the data is shown in S1 Fig . Lastly , model D does not significantly improve the fit compared to model C ( p = 0 . 323 ) . In addition to models A , B and D , we tested several other alternatives to model C , and found that model C is statistically the best supported model ( see S1 Text and S2 Fig ) . The fact that model C comes out as the best model in our model selection scheme is consistent with biological observations and previous quantitative analyses . Studies which employed mass-action kinetics for low effector-target cell ratios , found no significant differences between the killing efficacy of CTLs in acute and chronic infections [15] , as well as between effector and memory CTL [3 , 29] . This is in line with the assumption of model C that the maximum killing efficacies of CTLs in all mice groups are equal kmax , a = kmax , p = kmax , m . The model assumption of unequal half-maximum CTL frequencies differ between memory and effector CTL is supported by the observation that memory CTL bind to target cells longer until they kill due to lower perforin and granzyme levels [30] . We fitted function ( 3 ) under model C to the combined data of all treatment groups . Confidence intervals were obtained by bootstrapping . The estimated values of the model parameters are shown in Table 2 . Estimated maximum killing efficacies are smaller compared to the mass-action kinetics estimates , because of a different gauging under the new saturation assumption . The estimates for the peptide load sensitivities are very similar to those in mass-action estimates ( shown in Table 1 ) . For the saturation threshold in C 1 2 , effector , we obtain values around 0 . 015 . This estimate is very similar to one obtained by different methods ( see S1 Text ) . The saturation threshold estimate for memory CTL is substantially higher than for CTL in acute and chronic infections .
In this study , we have estimated CTL-mediated killing efficacies using in vivo killing assays across a wide range of peptide loads . Assuming mass-action kinetics , a clear hierarchy emerged between acute , chronic and memory responses . The chronic group showed a larger killing efficacy per CTL than the acute group , which in turn was more effective than the memory group across the entire range of peptide loads . This clearly shows , consistent with previous studies [15 , 20] , that CTL during chronic infections are not impaired in their ability to kill . Neither do these cells require more peptide on their targets to kill ( λ 1 2 ) , nor do they have a lower killing efficacy for very large peptide loads . In contrast to our previous work [15] , the estimates of the maximal per CTL killing efficacies were around one order of magnitude smaller for the acutely infected mice . This mismatch for the acute group is likely due to CTL frequency saturation effects . Saturation effects are likely to play a smaller role in [15] , where due to later cell transfer times ( 15 days after infection ) the average GP33-specific CTL frequency is about 0 . 01 . In this study , the average GP33-specific CTL frequency in acutely infected mice was 0 . 042 ( 8 days after infection ) . As the frequencies of GP33-specific CTL increase , killing efficacies will inevitably enter a saturation regime . In the saturation regime , a further increase in CTL does not lead to more total killing , violating a core assumption of the mass-action model . Erroneously adopting the mass-action assumption under saturation will therefore lead to an underestimate of the per CTL killing efficacy . In contrast , GP33-specific CTL frequencies for chronically infected mice in the experiments presented in [15] were very similar to those in this study , and no inconsistencies between killing efficacy estimates arise . To account for possible saturation effects in CTL numbers we also investigated mathematical models accounting for the saturation in killing rates for high CTL levels . Such saturating effects arise when the duration of killing is the limiting factor in the dynamics [31] . By a variety of methods we estimate that GP33-specific CTL need to exceed a frequency of 1% among splenocytes for saturation in acute and chronic infection . This estimate is about two to three times lower than that obtained from cellular automata models [25] . The results for the estimated recognition sensitivities between groups are almost identical between mass-action kinetics and CTL saturation model fits . Irrespective of the mass-action assumption , we did not find significant differences in the recognition sensitivities between responses . These estimates are of the same order of magnitude as comparable estimates found for chronic infections of polyoma virus , but differ for acute infections [16] . This study relies on estimates of the net unpulsed target cell migration into the spleen μ ( t ) and target cell data from the blood obtained in previous work [15] . Hence , uncertainties regarding the migration of target cells into the spleen that are associated with the experimental approach will inevitably be inherited by our killing efficacy estimates . There exist other models for CTL killing , such as the refractory model , epitope decay and CTL exhaustion models [13] or a recently investigated double saturation model [32] , that could have been used to fit the data . In this study , we limited the analysis to the standard mass-action kinetics and CTL saturation models . The refractory and exhaustion models were found to contradict biological observations in [13] . The CTL epitope decay model accounts for the observation that peptide-MHC complexes have lifetimes on the order of hours [33] , and could be lost over the course of our experimental study . However , in our previous study , this model did not provide significantly better fits to standard models [15] . Furthermore , the model could not provide additional information as to the relative strengths of the responses in the different treatment groups . The double saturation model—which accounts for saturation in both target as well as CTL numbers– could capture the functional response of the killing in a variety of conditions simulated in a computer model of lymphoid tissue . However , the relatively low variance in the target cell numbers in the spleen ( 0 . 08−0 . 12 probability for a target cell to be in the spleen [15] ) as well as the low variance of CTL frequencies do not permit to resolve the quantitative details of saturation in our data . The main motivation for estimating CTL killing efficacies for lower peptide loads in the present study were the discrepancies between killing estimates in vivo across a broad range of study systems [1 , 3–16] . However , there are also inconsistencies across in vivo and in vitro studies . It is unresolved if CTL are equally able to kill during chronic and acute LCMV infection . Some studies report cytolytic impairment of CTLs in chronic infections [34–36] , while others find unchanged cytotoxic potential in chronic infection [20] . These inconsistencies were thought to arise because the study systems employ either different peptide-MHC densities or different cells [20] . Our study shows that lower peptide-MHC densities by themselves cannot explain the impaired killing ability that some studies found: the killing ability during chronic LCMV infection is at least as strong as during acute infection across all peptide loads we tested in our study . Our estimates do not completely resolve why there are discrepancies of many orders of magnitude in CTL killing efficacy estimates between HIV , SIV , BLV , HTLV-1 on one hand , and LCMV and polyoma virus on the other . The peptide loads on naturally infected cells correspond to a peptide pulse of approximately 10 − 3 μ g ml . This number is estimated from a comparison of the T-cell stimulation by LCMV-infected or peptide-pulsed macrophages . An identical activation level of macrophages is attained for T-cells pulsed at 10 − 9 M ≈ 10 − 3 μ g ml . The killing efficacies obtained in in vivo killing assays with for the commonly applied large pulses of 1 μ g ml and the physiologically more realistic pulse of 10 − 3 μ g ml differ by a factor 10 . Thus , lower peptide loads explain only up to two orders of magnitude difference in CTL killing rates , and alternative explanations for the remaining large discrepancies need to be sought . The discrepancies between the estimated killing efficacies could be due to specific differences between the host species and the viruses . For instance , differences in the distribution of MHC molecules on target cells between mice and primates could have important effects . Other important host features , such as size , might affect CTL killing . Virus features are also expected to impact CTL killing efficacy . For example , viral protein expression in infected cells might vary substantially between different viruses and the infected cell type . Additionally , epitopes from different pathogens might elicit differently strong immune responses , which could contribute to CTL killing efficacy variation . Other studies have previously shown that the peptide concentration employed for target cell pulsing can affect the killing efficacies of CTLs in polyoma virus ( PyV ) [16 , 37] . As in our own study , killing efficacies declined with decreasing pulsing concentrations , indicating that the CTL’s ability to recognize and kill infected target cells depends on the number of peptide/MHC molecules presented on the target cell surface . In contrast to our results , fits of mass-action models do not show a clear hierarchy of killing efficacies between CTLs in acute and chronic infections . Rather , the hierarchy of killing abilities of CTLs in acute and chronic infections is reversed when pulsing concentrations are varied . Although this study differs in scope and in the viral system from the study of [16] , it can be regarded as an extension of it . Here , we have additionally investigated saturation models by employing statistical methods established in recent studies ( arcsin transformations for adequate error minimization in frequency data [13] , estimation of net flux rates of target cells into spleen [15] ) . Compared to the primary response after encounter of a pathogen , memory T cells confer a faster and stronger immune response to the host upon re-encounter , granting increased protection [38] . As in previous studies [13] , we found that memory CTL do not kill at higher rates than CTL in acute and chronic infections , particularly at lower peptide loads . We therefore have no evidence for an increased sensitivity of memory CTL compared to acute or chronic CTL , as has been suggested [39] . The increased level of viral control that is observed upon re-exposure is better explained by higher initial number or a higher proliferative capacity of memory CTL as compared to naïve CTL . | The immune system reacts to the presence of a viral pathogen within the host by the elicitation of an immune response . This response is characterized by the activation and proliferation of specific cell types , which , for instance , produce neutralizing antibodies or kill cells infected by the virus . Cytotoxic T lymphocytes ( CTLs ) function as an important protecting element of the system by recognizing and clearing infected viral target cells . Surprisingly , estimates of the killing efficacy of CTLs vary about four orders of magnitude across experimental methods and viral systems . In some studies , CTL killing efficacies were estimated by employing pre-treated cells that mimick virus infected cells . In general , cells signal their infection by a pathogen to the immune system by presenting viral peptides on their cellular surface . For the experimentally pretreated cells , these peptides were artificially loaded onto the surface at very high densities . In this paper , we study to what extent the variation in peptide densities can explain the variation found in killing efficacy estimates across methods and viral systems . We found that peptide densities explain only up to two orders of magnitude in killing efficacy variation . The remaining variation must originate from other sources , which might be specific to the viral study system . | [
"Abstract",
"Introduction",
"Materials",
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"Methods",
"Results",
"Discussion"
] | [] | 2015 | Estimating the In Vivo Killing Efficacy of Cytotoxic T Lymphocytes across Different Peptide-MHC Complex Densities |
The olfactory bulb transforms not only the information content of the primary sensory representation , but also its underlying coding metric . High-variance , slow-timescale primary odor representations are transformed by bulbar circuitry into secondary representations based on principal neuron spike patterns that are tightly regulated in time . This emergent fast timescale for signaling is reflected in gamma-band local field potentials , presumably serving to efficiently integrate olfactory sensory information into the temporally regulated information networks of the central nervous system . To understand this transformation and its integration with interareal coordination mechanisms requires that we understand its fundamental dynamical principles . Using a biophysically explicit , multiscale model of olfactory bulb circuitry , we here demonstrate that an inhibition-coupled intrinsic oscillator framework , pyramidal resonance interneuron network gamma ( PRING ) , best captures the diversity of physiological properties exhibited by the olfactory bulb . Most importantly , these properties include global zero-phase synchronization in the gamma band , the phase-restriction of informative spikes in principal neurons with respect to this common clock , and the robustness of this synchronous oscillatory regime to multiple challenging conditions observed in the biological system . These conditions include substantial heterogeneities in afferent activation levels and excitatory synaptic weights , high levels of uncorrelated background activity among principal neurons , and spike frequencies in both principal neurons and interneurons that are irregular in time and much lower than the gamma frequency . This coupled cellular oscillator architecture permits stable and replicable ensemble responses to diverse sensory stimuli under various external conditions as well as to changes in network parameters arising from learning-dependent synaptic plasticity .
The mammalian main olfactory bulb ( OB ) plays a central role in processing and relaying olfactory information from the primary sensory epithelium to subcortical and cortical areas [1] . This processing transforms the information content of the primary representation , but also has been proposed to transform the underlying physical metric by which this information is encoded , from rate-coded population activity organized on a respiration timescale to a spike timing-based representation aligned to a faster timescale that is determined by the intrinsic dynamics of cortical neural ensembles [2] . Odor stimulus-evoked activation of the OB generates fast , gamma-band ( 30–80 Hz ) local field potential ( LFP ) oscillations that are thought to be largely synchronous across the extent of the OB [3] . Such oscillations reflect the tightly constrained synchronization of a large neural assembly , which in the OB ( and its arthropod analogues ) has long been believed to play some role in the encoding and processing of olfactory information [4–14] . It is generally accepted that OB gamma oscillations are intrinsic , and mediated by a fast negative feedback loop formed between principal output neurons ( mitral and projecting tufted cells; MCs ) and a class of inhibitory GABAergic interneurons ( granule cells; GCs ) , interacting via dendrodendritic synapses in the external plexiform layer ( EPL ) of the OB ( Fig 1A; [15–25] ) . However , the underlying mechanisms generating these oscillations remain elusive . Several different dynamical architectures have been proposed or assumed to mediate OB gamma oscillogenesis . First , a pyramidal-interneuron network gamma ( PING ) mechanism is often assumed [22 , 26] , inspired by the anatomical predominance of the excitatory-inhibitory reciprocal synapses that constitute the EPL network . Early theoretical modeling of OB network dynamics also was based on this anatomical architecture [27] . However , PING networks do not incorporate cellular resonance properties , such as the intrinsic subthreshold oscillations ( STOs ) of MCs [28] . Second , an interneuron network gamma ( ING ) mechanism has been theoretically proposed [29 , 30]; however , this mechanism relies on inhibitory interactions among granule cells , which were intimated by early EEG work [16] and by the discovery of GABAergic synaptic inputs onto granule cells [31] but since have been ruled out . The PING and ING architectures have been reviewed by [32] . Third , OB network oscillations have been proposed to be driven directly by the intrinsic subthreshold dynamics of MCs [33] . This model highlighted the dynamical capacities of intrinsic MC subthreshold oscillations ( STOs; [28] ) and resolved some limitations of the PING architecture regarding observed OB dynamics ( e . g . , it permitted stable gamma oscillation frequency in the presence of fluctuating afferent drive ) . However , this model required substantially higher-frequency MC STOs than have been experimentally described , and also was not clearly compatible with the sparse spiking behavior of GCs [34] . Fourth , a hybrid network based on inhibition-coupled intrinsic cellular oscillators has been proposed [35] , in which the intrinsic STOs of MCs are transiently coupled during afferent activation into a coherent oscillatory network [36] paced by GC-mediated inhibitory synaptic inputs that periodically reset the slower MC STOs . ( Pulsed inhibitory inputs , including shunting inhibition , have been demonstrated to effectively reset MC STOs [28 , 37–39] ) . During these active epochs , the network dynamics exhibit key PING-like properties ( e . g . , the population oscillation frequency depends on the decay time constant of the GABA ( A ) receptor conductance ) , but they also retain a dependence on the slower STO dynamics of mitral cells even when the STO frequency itself is superseded by the network oscillation . This dynamical mechanism , pyramidal resonance interneuron network gamma ( PRING ) , is consistent with a broad range of experimental data and is modeled here . It is important to clearly understand the specific dynamical mechanisms underlying OB field oscillations , for several reasons . These oscillations are likely to reflect the re-encoding of afferent odor information into timing-based representations for distribution to multiple postbulbar cortical and subcortical structures [40] . Therefore , in order to understand the formation and information content of these secondary representations , the dynamics of their creation must be clear . Moreover , ascending inputs from the anterior olfactory nucleus and piriform cortex , among other structures , must be integrated into this dynamical framework . Piriform cortical inputs , in particular , are understood to alter bulbar dynamics , transiently transforming the OB’s intrinsic gamma oscillations into slower beta-band oscillations coherent with those of the piriform cortex [13 , 41–44] . To understand how these ascending inputs are integrated into the secondary odor representation requires a correct , mechanistic model of bulbar gamma oscillogenesis and its subversion by piriform cortical activity . Finally , field potential oscillations at many different characteristic frequencies are found all over the brain , often interacting within particular neural structures [45] and potentially serving to select and route specific information between coherently activated brain regions [46] . Elucidation of the detailed mechanics of oscillations and their transitions in the OB and its associated networks hence also will pertain to broader questions surrounding interareal communication mechanisms in the brain . To address this question , we developed a conductance-based , dynamically detailed biophysical model of the OB network . The present model is based on our earlier two-layer model of cholinergic neuromodulation in the OB [25] , but embeds these glomerular layer and intercolumnar EPL computations within an explicit spatial framework . The results from this model favor the PRING mechanism described above [35] , and demonstrate that this inhibition-coupled cellular oscillator architecture supports the diverse phenomena observed in OB neurophysiological recordings . These phenomena include ( 1 ) patterned spiking activity in MCs and GCs that both is broadly heterogeneous and occurs at lower frequencies than the population rhythm , ( 2 ) tolerance to a wide range of afferent MC excitation levels , which is important for mediating the representation of different odor qualities , ( 3 ) tolerance for substantial changes in MC-GC synaptic weights , which underlie intrinsic odor learning within the OB [47–49] , ( 4 ) the broad coherence of gamma-band oscillations across a physically extensive network despite the incoherent activity of some neurons within that network , ( 5 ) the phase-constraining of spikes within each cycle of the gamma oscillation [10 , 13] , and ( 6 ) the persistence of LFP gamma oscillations at consistent frequencies despite sparse network connectivity ( connection probability p = 0 . 3 between MCs and GCs ) and sharply heterogeneous afferent activation levels . The explicit , multiscale nature of this dynamical model further enables the elaboration , explanation , and experimental testing of the underlying mechanistic details that may underlie these observed physiological phenomena .
Stimulation with simulated odorants induced gamma oscillations that were coherent across the entire OB network . Simulated odorants comprised heterogeneous levels of input delivered to the 25 MC/PGC pairs; each MC fired at a different mean rate corresponding to the strength of its afferent input ( including feedforward inhibition from its associated PGC; Fig 2A ) . The mean MC firing frequency in response to odor stimulation was 14 Hz ( min = 4 Hz; max = 38 Hz; standard deviation ( SD ) = 9 . 8 Hz ) . Despite these heterogeneous firing rates , a strong and broadly coherent oscillation emerged in the gamma band ( 32 . 4 Hz , Fig 2B ) , consistent with in vitro recordings from olfactory bulb [19 , 35] . Individual MCs responded in a mixed mode , usually spiking at mean frequencies substantially below the underlying STO frequency , but with odor-evoked spikes phase-constrained to the underlying sLFP oscillation , as observed experimentally [10 , 13] . Moreover , systemwide coherence was maintained; voltage timeseries depictions of different pairs of MCs confirmed that the STOs of different MCs were synchronized with one another ( Fig 2C , top panel ) , MC spikes were synchronized with STOs from other MCs ( Fig 2C , bottom panel ) , and MC spikes were also substantially synchronized with spikes from other MCs ( Fig 2D1 and 2D2 ) . GC subthreshold voltages also fluctuated rhythmically and were well synchronized with one another ( Fig 2E1 ) , as were GC spikes ( Fig 2E2 ) , despite GCs’ low mean firing rates ( 4 . 6 Hz ) . In contrast , no gamma-band synchrony was observed in the subthreshold voltage fluctuations ( Fig 2F1 ) or spiking activity of PGCs ( Fig 2F2 ) . Population spike histograms of MCs , GCs and PGCs with corresponding frequency power spectra are shown in Fig 2D3 , 2E3 and 2F3 respectively . The population spiking activities of both MCs and GCs exhibited gamma rhythmicity , and the frequency was the same as that measured from the sLFP ( 32 . 4 Hz; Fig 2D3 and 2E3 ) . By comparison , no rhythmicity was observed in the PGC population spike histogram , and the frequency power spectrum was flat ( Fig 2F3 ) . Examined in aggregate , MC spikes were phase-constrained within the common , coherent gamma cycle of the OB network . The majority of MC spikes were evoked near the crest of the oscillatory sLFP ( Fig 3A ) . GC spikes also were phase-constrained within the gamma cycle , occurring predominantly during the descending phase of the sLFP ( Fig 3B ) . In contrast , PGC spikes were not phase-constrained , but were distributed uniformly across the gamma oscillation cycle ( Fig 3C ) . Because of the tight phase-locking between MC/GC spikes and the sLFP cycle , the gamma rhythm also was evident in MC/GC population spiking activities ( Fig 3D ) . The tightly alternating relationship between MC and GC population spiking , but not PGC spiking , suggested that this temporal delimiting of MC activity arose from effective feedback inhibition delivered by granule cells . To illustrate this point , we plotted the voltage traces of a weakly-activated MC and a strongly-activated MC against their respective cumulative GC-mediated GABAA conductances ( Fig 3E ) . The weakly-activated MC STO depolarized directly as its inhibitory conductance decayed ( Fig 3E , upper panel ) and the strongly-activated MC fired only after release from inhibition ( Fig 3E , lower panel ) . Moreover , the inhibitory conductance increased again directly following the evocation of MC spikes , initiating the next excitation-inhibition cycle . Sufficiently strong inhibitory GC input also effectively reset the phase of MC STOs ( Fig 3E , upper panel , arrows ) , consistent with experimental observation and earlier cellular models [28 , 37–39] . In principle , such resets erase the history imposed by longer-timescale internal dynamics , thereby enabling afferent input levels across the MC population to determine the depolarization rates in each MC from a common starting state , potentially governing MC spike phase as well as spike probability [39 , 50] . Moreover , recurrent resets also serve to supersede the intrinsic frequency of MC STOs , enabling the network to oscillate at a frequency faster than that generated by intrinsic STO dynamics [35] . In aggregate , these reciprocal interactions between MCs and GCs synchronized MC internal dynamics and MC spikes , incorporating them into a coherent gamma oscillation in which MC spikes were reliably phase-constrained with respect to the common oscillatory sLFP of the network ( Fig 3F; [10 , 13] ) . Functional computations in the olfactory bulb are generally independent of the physical distance between columns [2 , 51–54] , though their underlying biophysical mechanisms often have proximity-dependent properties . We therefore asked whether the distance-dependent spike propagation delays along MC lateral dendrites were sufficiently heterogeneous to impair the global coherence of gamma oscillations across the OB circuit . To visualize the propagation delay as a function of distance , the membrane potentials of a representative MC ( MC[2][2] ) were recorded from the soma and from the locations of three reciprocal synapses distributed along the lateral dendrite ( at 80 μm , 235 μm , and 500 μm from the soma; Fig 4 ) . These three synapses connected , respectively , to an adjacent GC ( GC[5][4] ) , a GC connecting near the middle of the lateral dendrite ( GC[6][3] ) , and a GC connecting at the end of the lateral dendrite ( GC[0][1] ) . Subthreshold activity in the MC dendrite was slightly hyperpolarized as the recording site progressed away from the soma , but spikes propagated at essentially full amplitude ( Fig 4A ) . Spike propagation was rapid , with less than 1 ms delay from the soma to the end of the 500 μm dendrite ( Fig 4B ) , suggesting that heterogeneous spike propagation delays would have little effect on network synchronization . This reflects the experimental observation that spikes fully propagate along a MC lateral dendrite with little delay ( Fig 2 in [55] ) , and is consistent with previous computational work in which spike backpropagation along MC lateral dendrites activates granule cells independently of distance [56] . It has been proposed that gamma oscillations in the OB depend on MC STOs [28 , 33]; however , in the PING framework , the pyramidal ( excitatory ) neurons generally do not exhibit resonance . We therefore asked whether and how MC STOs contribute to the robustness , power , and regularity of gamma coherence and spike synchronization in the active OB network . To investigate this , we first removed STOs from model MCs and examined the effect of this change on network dynamics . Specifically , STOs were eliminated by replacing the persistent sodium current ( INaP ) in all MCs of the network with ohmic cation currents scaled to maintain the same MC firing rates under the same current injection levels ( Fig 5A and 5B; [39] ) . The cation current was modeled as ICAT = gCAT ( v−ECAT ) , where gCAT = 0 . 26 mS/cm2 and ECAT = 0 mV . Under this manipulation , the power and regularity of odor stimulus-induced network gamma were substantially reduced and sLFP oscillations became less coherent , as evidenced by reduced persistence in the autocorrelogram and a lower , flatter peak in the power spectrum ( compare Fig 5C with Fig 5D ) . An examination of membrane potential timeseries from two pairs of MCs revealed that , although MCs without intrinsic STOs could still display subthreshold voltage fluctuations owing to phasic inhibition from granule cells , these fluctuations had smaller amplitudes and were much less regular compared with intact STOs in control cells ( compare Fig 5E with Fig 5F ) . MC spikes also became less synchronized with one another in the absence of intrinsic STOs ( compare Fig 5E with Fig 5F , bottom panels ) , although the mean odor-evoked MC firing rates were essentially identical ( Control: 14 Hz; STO removed: 13 . 2 Hz ) . Finally , the synchronization index ( SI ) was reduced from 0 . 64 in controls to 0 . 53 when STOs were removed . Hence , MC resonance contributed substantially to the integrity and regularity of coherent gamma oscillations in the active OB network , even when the intrinsic STO frequency was superseded by the PING-like mechanisms of the network frequency ( see below ) . The added stability and robustness of OB gamma oscillations contributed by these MC resonance properties resembles the advantages of resonance-induced gamma ( RING ) oscillations [57] , with the important distinction that RING is described for resonant inhibitory interneurons , whereas in the OB network it is the excitatory principal neurons that are resonant . The mechanism of OB oscillations can be described as pyramidal resonance interneuron network gamma ( PRING ) , thereby acknowledging the PING-like properties of the activated gamma oscillation as well as the additional properties afforded by MC resonance . Intrinsic STO frequencies appear to yield to higher-frequency network-based oscillations owing to recurrent STO phase resets delivered by GC-mediated synaptic inhibition [28 , 35] . If this interpretation is correct , and MC resonance is an important contributor to network coherence and frequency stability , then this oscillatory coherence should be disrupted if the intrinsic STO frequency becomes faster than the natural frequency of the synaptically-based network oscillation . To test this , we increased the intrinsic MC STO frequency by reducing the time constant of the activation variable of the slow potassium current ( IKS ) [33] . Specifically , we reduced the activation time constant of IKS from 10 ms to 5 ms , and increased the conductance densities of the IKS and INaP currents by factors of 1 . 6 and 1 . 3 respectively to maintain approximately the same STO amplitudes and MC firing rates . These modifications increased the STO frequency in an isolated MC model cell from 29 Hz ( in controls ) to 44 Hz in response to a 200 pA depolarizing current injection ( Fig 6A and 6B ) . Without altering any other model parameters , this change in the intrinsic STO frequency seriously disrupted the sLFP gamma rhythm and sharply reduced gamma power in the OB network ( compare Fig 6C with Fig 5C ) . A comparison of STO voltage timeseries with the aggregated GABAA conductances in the same MCs confirmed that GC inhibition could no longer effectively regulate MC STOs , which became irregular ( Fig 6D ) . Phase locking between MC spikes and sLFP oscillations also was significantly reduced ( SI , controls: 0 . 64; increased STO frequency: 0 . 38 ) , although the average odor-evoked MC firing rate was virtually unchanged ( controls: 14 Hz; increased STO frequency: 14 . 4 Hz ) . If this disruption was due to a mismatch between intrinsic STO frequency and the natural frequency of the network oscillation , as predicted , rather than to some separate effect of the changes made to the model MCs , then the coherence of OB gamma oscillations should be restored if the natural frequency of the network oscillation was also increased so as to again be faster than those of the MC STOs . In PING and ING networks , the natural frequency of network oscillations depends strongly on the decay time constant of the inhibitory synapse [32 , 58] . Indeed , when the GABAA receptor decay time constant of the GC→MC synapses was reduced to 3 ms ( from the default 18 ms ) , in a network populated with MCs exhibiting the higher intrinsic STO frequency , a strong gamma oscillation re-emerged at 51 . 3 Hz ( Fig 6E ) –considerably faster than the 32 . 4 Hz frequency exhibited by control networks . Under these conditions , MC STOs again displayed rhythmicity and were entrained effectively by GC-mediated GABAA synaptic conductances ( Fig 6F ) ; network synchrony also was substantially restored ( SI , controls: 0 . 64; increased STO frequency alone: 0 . 38; increased STO frequency + 3 ms synaptic decay time constant: 0 . 56 ) . These simulations indicate that the decay rate of GC-mediated GABAA inhibition must be faster than the intrinsic MC STO frequency in order to be able to synchronize MC dynamics . To test whether it was important that the inhibitory synaptic decay time constant be closely matched to the MC STO frequency , or that it simply be faster , we tested a network in which we paired the faster ( 3 ms ) GABAA synaptic decay time constant with the default ( 29 Hz ) intrinsic MC STO frequency . Under these parameters , the network oscillation frequency increased from 32 . 4 Hz ( under control conditions; Fig 2B ) to 43 . 4 Hz ( Fig 7A ) . This increase in oscillation frequency was accompanied by a slight reduction in oscillatory power and coherence , as indicated by a wider spectral peak and less persistent periodicity , though the amplitudes of the two spectral peaks were comparable ( compare Fig 7A with Fig 2B ) . Additionally , under these conditions the GABAA conductance fluctuated regularly and decayed fully within every gamma cycle owing to its fast dynamics , effectively entraining MC STOs ( Fig 7B ) . In contrast , when the GABAA decay time constant was increased from 18 ms to 30 ms , there was no change in the peak frequency of the network oscillation ( 18 ms: 32 . 4 Hz; 30 ms: 33 Hz ) , though its power was reduced considerably ( compare Fig 7C with Fig 2B ) . Within individual MCs , the slowly decaying GABAA conductance accumulated across successive gamma cycles and lost much of its rhythmicity , resulting in inconsistent effects on MCs that failed to supersede their intrinsic STO frequency preferences ( Fig 7D ) . Accordingly , under control parameters , synaptic decay time constants faster than ~18 ms progressively increased network sLFP oscillation frequencies , whereas slower time constants had no effect ( Fig 7E ) . These faster kinetics also maintained relatively high power spectral peaks at the gamma frequency ( oscillation indices ) , whereas slower synaptic kinetics resulted in rapidly declining oscillation indices ( Fig 7F ) . Mean spiking frequencies in both MCs and GCs , however , varied monotonically with respect to the rate of GABAA decay ( Fig 7E ) , likely because slower decay rates produced an overall increase in the total integrated inhibition of MCs . Specifically , as the decay time constant was increased from 3 ms to 30 ms , the MC firing rate decreased from 21 . 6 Hz to 10 . 8 Hz , resulting in a concomitant decrease in GC firing rate from 6 . 9 Hz to 3 . 4 Hz . In sum , these results showed that a wide range of synaptic decay time constants generated reliable coherence from the OB network provided that they were lower ( faster ) than a threshold value determined by the intrinsic frequency of MC STOs . However , there also was a clear peak ( 15 ms; Fig 7F ) , indicating that the strongest network oscillatory power could be achieved by an optimal matching of the synaptic and STO timescales . Additionally , these results demonstrated that the network oscillation frequency was robust to substantial changes in mean spike frequencies in both MCs and GCs . Finally , we decided to increase the intrinsic MC STO frequency by increasing the excitation levels of all MCs , rather than by altering their IKS and INaP conductance parameters as above , in order to test whether similar dynamical effects resulted . Depolarizing MCs increases their intrinsic STO frequencies both experimentally [28] and in the present model . To broadly increase MC excitation while retaining the same heterogeneous odor inputs , we decreased the level of PGC-mediated inhibition on MCs by reducing the PGC→MC synaptic weight to half of the control value ( from 4 to 2 ) . The results largely conformed to those observed when STO frequencies were increased by adjusting cellular conductance parameters ( Fig 6 ) . Under default parameters ( with an 18 ms GABAA decay time constant ) , reducing PGC inhibitory weights by half had no effect on the network oscillation frequency ( controls: 32 . 4 Hz; 50%WPGC-MC: 33 . 6 Hz ) , but did impair the coherence and stability of field potential oscillations and reduce the oscillation index ( peak spectral power; compare Fig 8A with Fig 2B ) . In contrast , when using a faster GC synaptic decay time constant of 3 ms , this reduced PGC inhibition produced a coherent gamma oscillation at a higher peak frequency ( controls: 32 . 4 Hz; 3 ms decay time constant only: 43 . 4 Hz; 3 ms decay time constant + 50%WPGC-MC: 51 . 3 Hz; Fig 8B ) , because the faster synaptic decay was again able to effectively reset the intrinsic MC STOs on every cycle . This result further suggests that higher overall levels of MC excitation , which generate faster intrinsic STO dynamics , would require correspondingly faster synaptic inhibition kinetics in order to maintain network stability , and thereby demonstrates the importance of maintaining a limited range of mean MC activity levels via global afferent activity normalization ( [59]; corrected mechanism in [54] ) . The synaptic weight of GC→MC inhibition also is an important factor in determining the stability of network gamma oscillations . To assess this effect , we varied the GC→MC synaptic weight ( WGC→MC ) from zero ( full blockade ) up to five times the default value . Under full blockade conditions , MC spikes and STOs were desynchronized ( Fig 9A ) and network sLFP oscillations were dramatically reduced ( compare Fig 9B with Fig 2B ) . Whereas overall spike rates increased substantially ( average odor-evoked spike rate , controls: 14 Hz; no GC inhibition: 24 Hz ) , synchronization among MC spikes was sharply reduced ( SI , controls: 0 . 63; no GC inhibition: 0 . 30 ) . These results further confirm that GC-mediated feedback inhibition is necessary for the synchronization of mitral cells into a coherent gamma rhythm in the OB . In contrast , when WGC→MC was increased threefold ( from 2 to 6 ) , MC spiking activity was reduced substantially ( controls: 14 . 0 Hz; 300% WGC→MC: 8 . 4 Hz ) and STOs were corrupted by an irregular mixture of shorter and longer oscillation periods , though MC membrane potential fluctuations were still moderately well-coordinated ( Fig 9C ) . The frequency power spectrum reflected this disruption , presenting a number of low-power peaks ( Fig 9D ) ; two of these ( at 18 . 3 Hz and 29 . 9 Hz ) were somewhat more distinct , though both remained well below control amplitudes ( compare Fig 9D with Fig 2B ) . These results indicate that excessive inhibition of MCs by large GC→MC synaptic weights impairs network gamma oscillations by disrupting STO periodicity . The frequency of the network sLFP oscillation and the mean spike rates of both MCs and GCs declined as WGC→MC increased from 0 to 6 and remained stable thereafter ( Fig 9E ) . In contrast , the synchronization index rose substantially as WGC→MC increased from 0 to 2 and maintained this level for all larger synaptic weights measured ( Fig 9F ) . The oscillation index ( spectral peak amplitude ) also increased greatly as WGC→MC grew from 0 to 2 , but then progressively decreased once WGC→MC exceeded 3 ( Fig 9F ) . This pattern of results indicates that the degradation of gamma oscillatory power at larger GC→MC weights was not a result of reduced phase coupling , but of disrupted STO periodicity ( Fig 9C ) . In sum , while sufficient GC inhibition is required to reset and synchronize MC STOs , excessive GC synaptic weights are detrimental to the stability of the gamma rhythm; an optimal level of GC inhibition is required to sustain a strong and coherent gamma oscillation . To understand in detail why larger GC→MC synaptic weights impaired gamma rhythmicity , we plotted spike time histograms for both MCs and GCs alongside the membrane potential timeseries of a representative MC and the aggregate GC-mediated GABAA conductance of that MC , all under the disruptive conditions of a 3-fold increase in WGC→MC ( Fig 10A; same parameters as Fig 9C and 9D ) . At a timepoint marking a surge of synchronous MC spiking activity , GCs responded in turn with higher-than-average activity ( Fig 10A , top and second panels , leftmost vertical line ) . Because of the large WGC→MC , this surge in GC activity evoked a particularly enlarged ( and correspondingly persistent ) GABAergic chloride conductance in MCs ( Fig 10A , third panel , leftmost vertical line ) , which substantially hyperpolarized MC membrane potentials ( Fig 10A , bottom panel , leftmost vertical line ) and , in aggregate , noticeably suppressed MC firing across the network ( Fig 10A , top panel , second vertical line ) . This reduced level of MC activity , in turn , did not induce any GC spiking in that cycle ( Fig 10A , second panel , second vertical line ) . As the GABAergic chloride conductance continued to decay ( Fig 10A , third panel , second vertical line ) , marginally increased numbers of spikes were generated from the MC population ( Fig 10A , top panel , third vertical line ) , which evoked weak responses in GCs ( Fig 10A , second panel , third vertical line ) and hence much smaller GABAergic conductances that only minimally hyperpolarized MC membrane potentials ( Fig 10A , third and bottom panels , third vertical line ) . After a few such “small” cycles , the MCs recovered from the effects of accumulated inhibition and a high-activity cycle occurred again ( Fig 10A , all panels , rightmost vertical line ) . The irregularity of this recurrent process substantially distorted MC subthreshold activity and gamma rhythmicity ( Fig 9D; Fig 10A , bottom panel ) . If this disruption of gamma oscillations indeed resulted from an oversuppression of MCs by excessive GC inhibition , as hypothesized , then boosting MC excitability should restore the rhythmicity . To test this , we increased MC mean firing rates back to the control level by reducing the PGC→MC inhibitory synaptic weight ( WPGC→MC ) to 50% of its default value ( controls: 14 . 0 Hz; 300% WGC→MC: 8 . 4 Hz; 300%WGC→MC + 50%WPGC→MC: 14 . 4 Hz ) . GC firing rates also were restored to control levels by this change ( controls: 4 . 6 Hz; 300%WGC→MC: 2 . 8 Hz; 300%WGC→MC + 50%WPGC→MC: 4 . 5 Hz ) . Under these restored excitability conditions , MC spikes again reliably drove substantial GC responses in every gamma cycle , the GABAergic synaptic conductance changes became more regular , and the periodicity of MC subthreshold activity was substantially improved ( compare Fig 10B with Fig 10A ) . Moreover , MC STOs were again well synchronized , and exhibited greater stability and regularity than under conditions of elevated GC inhibition but default PGC inhibition ( compare Fig 10C with Fig 9C ) . As a result , the second spectral peak observed in Fig 9D was eliminated and a single coherent gamma peak again appeared at 34 . 2 Hz , comparable to the control value of 32 . 4 Hz ( compare Fig 10D with Fig 2B ) . The above simulation demonstrates that the detrimental effect of excessive GC inhibition on gamma rhythmicity can be ameliorated by reduced PGC inhibition , indicating that an overall balance of excitation and inhibition is required for coherent , stable network gamma oscillations . Finally , the synaptic weights and decay time constants of GABAA synapses are not functionally independent of one another; shorter decay time constants generate less total MC inhibition and a weaker and shorter suppressive effect , all else being equal . We therefore asked whether the optimal inhibitory synaptic weights for robust oscillations and synchronization would differ depending on the synaptic time constant . We generated a network in which the GABAergic decay time constant was reduced from 18 ms ( in controls ) to 3 ms ( as depicted in Fig 7A and 7B ) , and measured network oscillation and spike frequencies and the oscillation and synchronization indices as functions of GC→MC synaptic weight . As predicted , the oscillation index ( OI ) peak and the SI plateau both occurred at substantially higher inhibitory synaptic weights when using the faster decay time constants ( compare Fig 10E and 10F to Fig 9E and 9F ) . The inhibitory synaptic decay time constant therefore also must be factored into the balance between excitation and inhibition that enables stable and coherent gamma oscillations across the OB network . The functional efficacy of feedback inhibition in the OB EPL depends on the synaptic weights of both the inhibitory GC→MC and the excitatory MC→GC synapses . If a balance between excitation and inhibition is required for strong and stable gamma oscillations across the OB , then an optimal range of excitatory MC→GC synaptic weights may also exist . However , because MC→GC synapses onto adult-born GCs are plastic [47 , 48] , the EPL network would be expected to tolerate a substantial range and heterogeneity among these synaptic weights . To examine the functional range of synaptic weights for the excitatory MC→GC synapses in this network , we varied the MC→GC synaptic weight ( WMC→GC ) from 0 up to 8 times the default value . When these synapses were blocked ( i . e . , WMC→GC = 0 ) , GCs were largely inactive ( 0 . 9 Hz spontaneous background activity ) ; other simulation results were similar to those obtained when blocking GABAergic synaptic transmission ( i . e . , WGC→MC = 0; Fig 9A and 9B ) and are not separately reported here . When WMC→GC was reduced to 50% of the default value ( from 1 to 0 . 5 ) , the GC subthreshold potential was substantially hyperpolarized and lost much of its rhythmicity compared with controls ( Fig 11A , upper panel ) , leading to significantly smaller and arrhythmic GABAergic chloride currents in MCs ( Fig 11A , lower panel ) . Because of this reduced phasic GC inhibition , MC activity increased , but both MC spikes and STOs were relatively desynchronized ( Fig 11B ) , and gamma oscillations were greatly impaired ( compare Fig 11C with Fig 2B ) . In contrast , when WMC→GC was increased to 8 times the default value ( from 1 to 8 ) , GCs were strongly excited , spiking in response to many incoming EPSPs and maintaining a level of rhythmicity comparable to controls ( Fig 11D , upper panel ) , but delivering much larger phasic GABAergic chloride conductances onto MCs ( Fig 11D , lower panel ) . The increased level of phasic inhibition suppressed MC spikes , but retained the synchrony and periodicity of MC STOs ( Fig 11E ) . Accordingly , a robust and coherent gamma oscillation persisted even with an 8-fold increase in the MC→GC synaptic weight , with little change in frequency ( controls: 32 . 4 Hz; 800%WMC→GC: 35 . 4 Hz; Fig 11F ) . To break this effect down further , we generated raster plots of MC and GC firing under these two conditions . When WMC→GC was reduced by 50% , the mean odor-evoked GC firing rate was reduced from 4 . 6 Hz ( in controls ) to 2 . 6 Hz , resulting in a slight increase in the mean MC firing rate from 14 Hz ( in controls ) to 17 . 7 Hz . As noted above , network synchrony was reduced substantially ( SI , controls: 0 . 63; 50%WMC→GC: 0 . 40 ) , because neither MC nor GC spike trains were well coordinated ( Fig 12A and 12B ) . In contrast , with an eightfold increase in WMC→GC , GC firing rates were greatly increased ( controls: 4 . 6 Hz; 800%WMC→GC: 12 . 8 Hz ) and GC spikes became remarkably well synchronized; this strong GC activation substantially suppressed MC firing ( controls: 14 Hz; 800%WMC→GC: 3 . 3 Hz; Fig 12C and 12D ) . This substantially different balance of MC and GC activity was stable because one MC input was strong enough to produce correlated discharges in many postsynaptic GCs . Notably , under these conditions the mean MC firing rate ( 3 . 3 Hz across all MCs ) was much lower than the oscillation frequency ( 35 . 4 Hz ) and a majority of MCs exhibited no odor-evoked spikes ( Fig 12C ) . The spikes of the remaining active MCs were effectively entrained by the highly synchronous GC activity , and exhibited elevated levels of synchrony ( SI , controls: 0 . 63; 800%WMC→GC: 0 . 92 ) ; i . e . , coherent gamma oscillations persisted despite substantial increases in lateral excitatory synaptic weights . This is a particularly important stabilizing property given that the intrinsic OB synaptic plasticity underlying odor learning relies on the potentiation of excitatory synapses [47 , 48] . The average odor-evoked MC/GC firing rates and sLFP oscillation frequencies across a range of MC→GC synaptic weights are depicted in Fig 12E . As WMC→GC was increased , MC firing rates decreased while GC firing rates increased , eventually crossing . In contrast , the sLFP oscillation frequency remained stable ( though unreliable at weights below 1 owing to very low spectral power; Fig 12E ) . The OI grew rapidly from its arrhythmic values at MC→GC synaptic weights below 1 up to a strong peak value that persisted across a fourfold range of excitatory synaptic weights , decreasing moderately thereafter ( Fig 12F ) . This eventual decline arose as the increased activation of GCs began to impose tonic , as well as phasic , feedback inhibition that further reduced MC activation levels . In contrast , the SI increased steadily as WMC→GC increased , gradually approaching unity at higher synaptic weights ( Fig 12F ) . Heterogeneity in population activity levels , whether across the neurons of an active ensemble or within a given population over time , poses a challenge to the stability and consistency of dynamical systems [60–65] . For example , the frequencies of gamma oscillations driven by pure PING mechanics vary directly with the activation levels of the excitatory neurons [58] , which in the olfactory bulb are strongly heterogeneous ( indeed , heterogeneity in MC activation levels is the fundamental basis of olfactory sensory representations ) . Notably , systems of coupled oscillators often are robust to reasonable heterogeneities in excitation levels [66]; indeed , the essence of coupled oscillator systems is a dynamics by which intrinsic differences in the natural frequencies of constituent oscillators are drawn together into a common limit cycle . To assess the robustness of the OB network gamma oscillation to variance across the afferent input levels of MCs , we altered the ranges of excitation generated across the MC population by simulated odorant stimuli . By default , steady-state odor input intensities us ( nA ) were drawn from a uniform distribution within a bounded range ( US1 , US2 ) . We first varied the upper input bound US2 from 0 . 4 nA to 1 . 0 nA with increments of 0 . 2 nA , with the lower input bound US1 fixed at 0 . 2 nA ( Fig 13 ) . When the upper input bound was reduced from 1 . 0 nA ( in controls ) to 0 . 4 nA , the odor-evoked MC firing rate dropped from 14 Hz to 8 . 8 Hz and the MC firing rate variance was markedly reduced ( SD , us ∈ ( 0 . 2 , 1 . 0 ) : 9 . 8 Hz , us ∈ ( 0 . 2 , 0 . 4 ) : 1 . 6 Hz; Fig 13A ) . Because of the reduced MC drive , the odor-evoked GC firing rate also declined from 4 . 6 Hz to 2 . 4 Hz , and the reduction in GC excitation generated much smaller GABAA conductance fluctuations on MCs ( Fig 13B ) ; this feedback response limited the overall change in the balance of excitation and inhibition . Despite these changes in firing rates and the amplitudes of synaptic interactions , MC oscillations remained highly synchronized under both conditions ( Fig 13C ) , and the synchronization index was essentially unchanged ( SI , us ∈ ( 0 . 2 , 1 . 0 ) : 0 . 63; us ∈ ( 0 . 2 , 0 . 4 ) : 0 . 62 ) , and the frequency of the dominant sLFP spectral peak was only slightly reduced ( us ∈ ( 0 . 2 , 1 . 0 ) : 32 . 4 Hz; us ∈ ( 0 . 2 , 0 . 4 ) : 28 . 7 Hz; compare Fig 13D with Fig 2B ) . The mean odor-evoked neuronal firing rates and sLFP oscillation frequencies across a range of upper input bounds are depicted in Fig 13E . As the upper input bound increased from 0 . 4 nA to 1 . 0 nA , the mean MC firing rate increased 58 . 6% ( from 8 . 7 Hz to 13 . 8 Hz ) and that of GCs increased 76 . 9% ( from 2 . 6 Hz to 4 . 6 Hz ) . In contrast , there was only a 14 . 3% increase in oscillation frequency ( from 28 . 6 Hz to 32 . 7 Hz ) , demonstrating the relative robustness of OB gamma frequency to input variance . The synchronization and oscillation indices for the same range of upper input bounds are shown in Fig 13F . Both indices also demonstrated considerable stability in response to changes in the upper input bound . We next fixed the upper input bound US2 at 1 . 0 nA , and varied the lower input bound US1 from 0 . 2 nA to 0 . 8 nA with increments of 0 . 2 nA ( Fig 14 ) . Increasing the lower input bound reduced input heterogeneity , as in Fig 13 , but potentiated rather than reducing the average MC excitation level . When US1 was increased from 0 . 2 nA to 0 . 8 nA , the odor-evoked MC firing rate increased from 14 Hz to 24 . 6 Hz , with markedly reduced variance ( SD , us ∈ ( 0 . 2 , 1 . 0 ) : 9 . 8 Hz; us ∈ ( 0 . 8 , 1 . 0 ) : 3 . 6 Hz ) , leading to highly synchronized MC spikes ( SI , us ∈ ( 0 . 2 , 1 . 0 ) : 0 . 63; us ∈ ( 0 . 8 , 1 . 0 ) : 0 . 7; Fig 14A and 14D ) . Accordingly , a strong , coherent sLFP gamma oscillation was generated with a higher-amplitude spectral peak than that exhibited by controls ( Fig 14D; also compare Fig 14B with Fig 2B ) . However , despite this large increase in the mean MC firing rate , the sLFP oscillation frequency remained remarkably stable ( us ∈ ( 0 . 2 , 1 . 0 ) : 32 . 4 Hz; us ∈ ( 0 . 8 , 1 . 0 ) : 31 . 1 Hz; Fig 14C ) . Coupled-oscillator networks are able to synchronize oscillators with nonuniform natural frequencies , but this robustness has limitations [61 , 62 , 66] . The large differences in input activation that can be generated by primary sensory receptor populations ( responding to stimuli varying by orders of magnitude in physical intensity and receptive-field optimality ) require regulation if they are to be constrained within the limited permissive range of the EPL’s oscillatory regime . Specifically , the range of absolute physiological variability generated in primary sensor populations must be compressed into a dynamic range that does not disrupt the functional dynamics of subsequent sensory system computations . This need is met in the early olfactory system by a series of concentration tolerance mechanisms ( reviewed in [67] ) , culminating in a global normalization computation in the deep glomerular layer ( [59]; corrected mechanism in [54] ) ; this computation is mediated by the heterogeneous periglomerular/short-axon cell population [68 , 69] and modeled herein by PGCs . To demonstrate the importance of these intensity compression mechanisms and examine the role of PGC-mediated inhibition in enabling OB gamma oscillations , we varied the PGC→MC synaptic weight ( WPGC→MC ) from 0 to 250% of its default value . When PGC inhibition was entirely removed ( WPGC→MC = 0 ) , the average odor-evoked MC firing rate increased markedly , from 14 Hz ( in controls ) to 32 . 2 Hz , inducing a concomitant increase in the mean GC firing rate ( from 4 . 6 Hz to 9 . 5 Hz; compare Fig 15A with Fig 3D ) . Firing rates within the MC ensemble also displayed a much larger variance when PGC inhibition was removed ( SD , controls: 9 . 8 Hz; No PGC inhibition: 19 . 3 Hz; compare Fig 15B with Fig 2A ) . Importantly , the removal of PGC inhibition significantly degraded MC spike synchrony ( SI , controls: 0 . 64; No PGC inhibition: 0 . 39 ) ; this reduction in SI arose because of the substantial increase in asynchronous background or noisy spiking in MCs ( compare Fig 15A , upper panel , with Fig 3D , upper panel ) . Nevertheless , GC population activity still retained a high level of rhythmicity comparable to controls ( compare Fig 15A , lower panel , with Fig 3D , lower panel ) , and imposed strong phasic inhibition on MCs . Examination of MC and GC population activities indicates that GCs spiked only in response to peak MC spike rates ( Fig 15A , dashed vertical lines ) , and the resulting phasic inhibition from GCs only partially suppressed MC spikes ( i . e . , MC spikes persisted during peak phasic inhibition ) , in contrast to the complete periodic suppression of MC spikes by GC inhibition in controls ( compare Fig 15A with Fig 3D ) . Moreover , spike rates in the most strongly driven MCs exceeded the frequency of the underlying STOs , violating the restrictions of coupled oscillator-derived synchrony and consequently wholly desynchronizing with the remainder of the MC population ( Fig 15C , lower panel; Fig 15J ) . Because of the loss of these highly-activated MCs from the synchronous population , the oscillatory power was considerably reduced in the absence of PGC inhibition ( compare Fig 15D with Fig 2B ) , although a sizable spectral peak arising from the less-active MC population still persisted , exhibiting little change in frequency ( controls: 32 . 4 Hz; No PGC inhibition: 34 . 2 Hz ) . This result supports two important points: First , although PGC inhibition improves global synchrony–specifically , it improves global participation in the synchronous ensemble by limiting the absolute activation levels of MCs to within a permissive range–it is not required for the generation of the OB gamma rhythm ( Fig 15D ) , whereas GC inhibition is clearly required for OB gamma oscillogenesis ( Fig 9B ) . Second , and critically , these results make clear that this coupled-oscillator mechanism is capable of sustaining coherent oscillations among participating MCs–i . e . , those that are both within the permissive band of afferent activation levels and adequately coupled via MC/GC synaptic weights–irrespective of the additional presence of substantial numbers of active MCs that are non-participants in the coherent assembly ( Fig 15C ) . As MCs are known for high levels of background spiking activity , both in vitro and in vivo but especially in awake/behaving animals [70] , it is critical to determine the extent to which this activity is likely to interfere with the transmission of neural information . Experimental studies and theoretical models of gamma-timescale coincidence detection in the piriform cortex have suggested that such postsynaptic temporal selectivity will naturally exclude most uncorrelated background activity in MCs from affecting third-order neuronal representations of odor information [71 , 72] . However , the present model is the first to demonstrate that timing-based odor representations in the OB can persist in the presence of high levels of uncorrelated background spiking . Increased PGC inhibition also disrupted OB oscillations ( Fig 15E–15H ) . When the PGC→MC synaptic weight was increased twofold ( from 4 to 8 ) , the average odor-evoked MC firing rate decreased from 14 Hz to 4 . 5 Hz ( compare Fig 15F with Fig 2A ) , reducing the mean GC firing rate from 4 . 6 Hz to 1 . 3 Hz . Because of the paucity of activity under this tonic inhibitory suppression , the MC-GC feedback loop was functionally disrupted; GCs responded sparsely and weakly ( compare Fig 15E with Fig 3D ) , evoking weak and irregular GABAergic synaptic conductances onto MCs . MC STOs thereby began to desynchronize and become irregular ( compare Fig 15G to Fig 2C ) , and both gamma rhythm and power were seriously impaired ( compare Fig 15H with Fig 2B ) . Both the MC and GC mean firing rates decreased rapidly as WPGC→MC increased further , whereas the sLFP oscillation frequency was stable below the control value and declined modestly at higher levels of PGC inhibition ( Fig 15I ) , from 34 . 5 Hz at WPGC→MC = 0 to 24 . 2 Hz at WPGC→MC = 10 . The synchronization index increased along with the strength of PGC inhibition up until the control value , and remained largely stable under stronger PGC→MC inhibitory weights ( Fig 15J ) . In contrast , the oscillation index peaked around the control value and declined rapidly at higher PGC weights ( Fig 15J ) . The discrepancy between SI and OI at large WPGC→MC values arises largely from the fact that decreasing the numbers of spiking MCs does not reduce the SI , whereas the OI is sensitive to the desynchronization of driver currents and other subthreshold activity occurring among less strongly activated neurons . This highlights the fact that a correspondence between MC spikes and LFP deflections alone does not suffice to ensure coherent gamma oscillations . These results show that PGC-mediated inhibition can serve to constrain the majority of MCs within a permissive range of activation . This constraint both protects the relational activation differences among MCs that underlie odor quality encoding and enables these odor-activated MCs to participate in a globally coherent gamma-oscillatory ensemble that constrains MC spike timing . Moreover , this globally coordinated oscillation , and the underlying phase-constraint of STOs and spikes in a majority of MCs , is robust to the potentially disruptive impact of highly active but uncorrelated MCs , whether uncorrelated owing to overstimulation or to inadequate coupling . Our OB network model contained 25 MCs , 25 PGCs and 100 GCs , a small fraction of the number of neurons in the biological OB; additionally , the ratio between the numbers of GCs and the numbers of MCs and PGCs is far greater than is represented in the model [1] . To test whether gamma oscillation in our model was robust to variations in this ratio , we increased the number of GCs ( NGC ) from 100 to 225 ( 15*15 array in Fig 1B ) and 400 ( 20*20 ) respectively , while maintaining the number of MCs and PGCs at 25 each . To correct for the increased total inhibition that would be delivered onto MCs , we scaled down the maximal conductance of individual GC→MC synapses by the same factor such that the total GABAA conductance received by each MC remained relatively constant . When NGC was increased to 225 , the mean odor-evoked MC and GC firing rates remained relatively unchanged ( controls , MC: 14 Hz , GC: 4 . 6 Hz; NGC = 225 , MC: 13 Hz , GC: 4 . 2 Hz ) . Both MC and GC spikes displayed clear synchronization , and MCs displayed appropriately sparse spiking activity ( Fig 16A and 16B ) . A dominant spectral peak in the sLFP power spectrum persisted at almost the same frequency and power as controls ( controls: 32 . 4 Hz; NGC = 225: 33 . 6 Hz; compare Fig 16C with Fig 2B ) . When NGC was increased to 400 , the mean odor-evoked MC and GC firing rates also remained stable ( controls , MC: 14 Hz , GC: 4 . 6 Hz; NGC = 400 , MC: 14 . 2 Hz , GC: 5 . 2 Hz ) , and MC activity remained reasonably sparse ( Fig 16D and 16E ) . A strong coherent gamma oscillation again persisted at approximately the same frequency and power as in controls ( controls: 32 . 4 Hz; NGC = 400: 33 Hz; compare Fig 16F with Fig 2B ) . While this variance does not encompass either the absolute size or the MC-GC ratio of the biological system , it does indicate that gamma oscillations are not highly sensitive to variations in network size .
The olfactory bulb transforms not only the information content of the primary sensory receptor input that it receives , but also its underlying coding metric . Large variance in absolute input amplitudes across receptor populations , varying on a slow respiratory timescale of encoding , are transformed by OB neural circuitry into patterns of ensemble spiking activity among OB principal neurons ( mitral cells and projecting tufted cells ) that are constrained in their amplitude variance and regulated on a fast gamma-band timescale . This emergent fast timescale for signaling is reflected in the gamma-band sLFP oscillations across the OB that are evoked by afferent activation of OB principal neurons , and presumably serves to efficiently integrate olfactory sensory information into the temporally regulated information networks of the central nervous system . However , the physiological mechanism underlying this transformation has not been clear . Field potential oscillations at many frequencies are ubiquitous across the brain , and have been attributed to several different underlying dynamical frameworks . Each such theoretical framework imposes predictable relationships and limitations upon the activities of its constituent neurons , and defines the capacities and vulnerabilities of the network to changes in input statistics or internal parameter values . Multiple such frameworks–including PING , ING , STO-driven gamma oscillations , and the PRING hybrid mechanism described herein–have been proposed to underlie OB dynamics; among these , the PRING framework best corresponds to experimental observations of OB circuit neurophysiology [28 , 35 , 38] . The diagnostic elements of this PRING framework are ( 1 ) resonant principal neurons that receive external excitation ( unpatterned on the gamma timescale ) and exhibit intrinsic STOs , ( 2 ) reciprocal connectivity of these principal neurons with spiking inhibitory interneurons that do not separately receive afferent input , ( 3 ) a PING-like network oscillation that emerges under afferent activation; its frequency is determined principally by the decay time constant of the GABA ( A ) receptor conductance and must be higher than that of the STOs , thereby enabling a recurrent reset of STO phase in participating principal neurons , and ( 4 ) a continued dependence on principal neuron resonance properties during these network oscillations . In the present simulations , excitatory synapses were spike-mediated; inhibitory synapses were realistically graded but also compatible with GC spiking . Using a biophysically elaborated multiscale computational model of the OB , we here assessed the capacities and limitations of this PRING framework with respect to the observed properties of the OB circuit and the requirements of the olfactory sensory modality . First , MCs converge onto piriform cortical pyramidal neurons from positions dispersed across the OB; there is no topographical organization to their projection patterns [73] . Coincidence detection in piriform pyramidal neurons [71 , 72] requires that spike timing relationships among converging MCs be regulated by a common clock , so that incoming information is not dominated by random variance . Therefore , even physically distant MCs must be regulated by this common clock , indicating that EPL oscillations would need to be coherent across the entire layer , with negligible phase differences among regions . Such spatially extensive zero-phase coherent networks are nontrivial to construct , particularly in the presence of heterogeneous levels of activity among principal neurons . Coupled-oscillator networks in general , and our model here in particular , can yield robust coherence among excitatory neurons with negligible phase drift and across a wide range of physical scales , provided that there is sufficient direct long-distance synaptic coupling between distant columns ( as provided here by the long MC lateral dendrites ) . When long-distance synaptic coupling is reduced in density , the spatial extent of coherence regions in the OB is correspondingly reduced [35] , consistent with theoretical predictions [74–76] . Second , the mechanisms generating gamma oscillations should serve to phase-constrain informative MC spike timing , presumably with respect to a timescale appropriate for the synaptic integration time constants of postsynaptic follower neurons . Indeed , MC spikes are phase-constrained at the gamma/beta timescale [10 , 13] , and their follower neurons in piriform cortex exhibit key properties of coincidence detectors [71] . However , MCs also exhibit high levels of uninformative background spiking , and are particularly active in awake/behaving animals [70] . It is therefore equally important that the oscillogenic mechanism of the OB be robust to high levels of uncorrelated MC spiking . In our model , MC spikes are phase-constrained by virtue of intrinsic STO dynamics [28] , which are periodically reset by GABA ( A ) -ergic synaptic inputs . The dynamical coordination and synchronization of these STOs and spikes across the full OB model is remarkably robust to the impact of high levels of uncoordinated MC spiking input ( Fig 15; see also [77] ) . This robustness , together with the need for multiple convergent inputs to activate piriform pyramidal neurons [78] , enables postsynaptic coincidence detectors to selectively respond to informative , temporally-coordinated MC inputs while disregarding MC background activity . Third , this common frequency and zero-phase coherence must withstand substantial heterogeneity in afferent input levels , both across the network and over time . Heterogeneous networks are a challenge to synchronize [63–65] , and , under many mechanisms , differentially-activated local regions of a heterogeneously-activated , spatially extensive network will exhibit different preferred frequencies [28 , 33 , 35] . Weak coupling has the capacity to pull such regions into a common oscillation , though it is generally effective only across a limited range of preferred frequencies and typically requires several , sometimes many , cycles to achieve synchronization [66 , 79–81] . Stronger coupling , such as the STO phase-reset phenomenon of our coupled-oscillator model , enables a rapid , history-independent coordination among diverse local ( columnar ) oscillators across a range of activation levels [79] . The afferent activation-dependent differences among MCs in the rate of their recovery from synchronous GC-mediated synaptic inhibition have been proposed to generate the spike phase code exported from the OB [49 , 72]; however , for present purposes , the important factor is that this coupling mode renders global sLFP synchronization robust to the large differences in afferent activation levels that together constitute the primary sensory representation ( Figs 2 , 13 and 14 ) . Some dynamical frameworks also are not robust to inhibitory neurons that spike , or to networks in which excitatory or inhibitory neurons fire at dissimilar rates , or at rates far below the common oscillatory frequency . All of these phenomena are features of the OB network , and are robustly supported by the present model . Finally , global synchronization across the OB must also be robust to sparse network connectivity , and to substantial differences in synaptic weights across the EPL , particularly the excitatory synaptic weights that are modified during the process of odor learning [47 , 48] . The present model maintains stable oscillations and global synchronization with sparse connections and a wide range of excitatory synaptic weights ( Figs 11D–11F and 12 ) . Fourth , notwithstanding the above , there clearly are limits to the range of absolute input amplitudes that a dynamical system can withstand . The effects of afferent input intensity ( concentration ) are mitigated in animals by a series of compensatory mechanisms [67] capped by a global normalization network embedded in the OB glomerular layer , essentially feeding back a global average of input intensity as inhibition onto all MCs . This global normalization function was proposed a decade ago [51 , 59] , but the underlying circuit mechanism has only recently been determined [54] . In the model , as predicted , reduction of this circuit-based concentration tolerance by modifying PGC inhibition increased mean activity and variance across the MC population and disrupted spike synchronization ( Figs 8 and 15 ) . PRING oscillations exhibit these diverse and computationally important properties by virtue of their integration of PING and STO mechanics . Two prior conductance-based network models of OB gamma oscillations also have incorporated both synaptic and STO dynamics [22 , 33] , but each reached different conclusions owing to differences in implementation . The earlier of these models , by Bathellier et al . [22] , incorporated STO dynamics in single-compartment MCs , but did not include explicit GCs; instead , MC spikes directly generated recurrent and lateral inhibition , and there was no graded contribution to synaptic inhibition . In this model , the resonant properties of MCs were found to play little role in the gamma oscillation , and the population frequency depended on the rising time constant ( rather than the decay time constant ) of lateral synaptic inhibition . The second such model , by Brea et al . [33] , incorporated explicit MCs and GCs , and exhibited both MC STO dynamics and graded synaptic inhibition . The Brea model demonstrated that STOs can be synchronized by graded inhibition , exhibited some STO resetting by this inhibition , and allowed mean MC firing rates to be much lower than the population oscillation frequency . However , it also differed from the present PRING model in several ways . First , in the Brea model , intrinsic STO frequencies directly drove the population oscillation frequency; the time constants of synaptic inhibition played little role . To accomplish this , MC STO frequencies were raised to 60–90 Hz , significantly higher than the 20–40 Hz that has been observed experimentally [28] and implemented in the present model . In principle , these high-frequency STOs could prevent the slower synaptic inhibition from determining the population frequency of the active network , as illustrated above ( Fig 7E ) ; however , in the Brea model , the STOs directly determined network frequency even when slowed to 35 Hz ( Fig S5 in [33] ) . Differences in the properties of synaptic inhibition and GC spiking are more likely to be the main differentiating factors . Second , synaptic inhibition in the Brea model was activated at relatively hyperpolarized potentials ( -66 mV ) , exhibited a relatively hard threshold ( activated between -66 . 5 mV and -65 . 5 mV; Fig 1A of [33] ) , and was delivered directly to the single somatic compartment of the model cell . In contrast , in the present model , half-activation of the graded inhibitory synapses occurred at -40 mV , the threshold was much softer ( activated between -50 mV and -30 mV ) , and incoming inhibitory synapses were distributed along an electrotonically extensive lateral dendrite . Third , the Brea model was not readily compatible with sparse GC spiking ( i . e . , GCs that spike at substantially lower frequencies than the population oscillation ) ; in contrast , the present PRING model robustly supports sparse GC spiking during population oscillations . In sum , the present model demonstrates that the PRING mechanism elucidated in the OB network by [35] , when embedded in a multiscale , dynamical biophysical model of MC circuit function , exhibits the full set of dynamical properties that either have been experimentally demonstrated in the OB or are critical theoretical predictions based on experimental data . These experiments demonstrate that OB dynamics can be best described as independent columnar oscillators , coupled by pulsed inhibition , with a network topology based on long-distance , non-topographically organized connections . This elucidation of the essential dynamics of OB oscillogenesis will substantially constrain the plausible mechanistic hypotheses for interareal dynamics , such as the transient coherence in the beta band between OB and piriform cortex that characterizes particular phases of olfactory investigation .
The “default” OB network model contained 25 mitral cells ( MCs ) , 25 periglomerular cells ( PGCs ) cells and 100 granule cells ( GCs; [25] ) . Each MC , together with an associated PGC , represented a separate OB column , each of which was associated with a particular glomerulus and hence a distinct olfactory receptor type . The number of GCs in the model was increased substantially in certain simulations . The MC , PGC and GC single-cell models were Hodgkin-Huxley type conductance-based compartmental models based on those in [25] . In contrast to the 2013 model , the present OB network incorporated physical locations for each OB column in order to model the problems of distance-dependent lateral interactions , such as the differing propagation delays of spikes along MC lateral dendrites [50] . Specifically , the OB surface was modeled as a two-dimensional ( 2D ) space ( 1 mm x 1 mm ) , upon which MCs and PGCs ( together ) and GCs ( separately ) were arranged in grid arrays with equal spacing in the horizontal and vertical directions ( Fig 1B ) . To avoid edge effects , the 2D network was mapped onto a torus . Each neuron was labeled with its column and row numbers in the 2D space starting from 0 ( i . e . , MC[i][j] denoted the MC in the ith column and the jth row ) . In some figures , model neurons were denoted by a single index to enable their distribution along a single axis ( e . g . , in raster plots ) . In such cases , that single index z was related to the two indices i and j as follows: z = N * i + j + 1 , where N was 5 for MCs and PGCs and 10 for GCs . Both MC-PGC and MC-GC connections incorporated dendrodendritic synapses ( Fig 1A; [25] ) . In the model , each MC formed reciprocal synapses with its local PGC ( associated with the same glomerulus ) ; i . e . , the MC excited the PGC dendritic spine whereas the PGC inhibited the MC tuft compartment via graded inhibition ( Fig 1A ) . MCs also interacted bidirectionally with GCs along the lengths of the MCs’ lateral ( secondary ) dendrites , which extend for long distances across the olfactory bulb [55 , 82] . Specifically , MCs delivered synaptic excitation onto GC dendritic spines while receiving feedback and lateral inhibition from these same spines ( Fig 1A ) . Each MC connected reciprocally to a random selection of GC dendrites with a connection probability p = 0 . 3 . To model the cable effects of distance , the location of the dendrodendritic contact along the length of the seven-compartment MC lateral dendrite [25] was determined by the distance between the MC soma and the GC in question ( Fig 1B ) . The MC→PGC and MC→GC synapses were mediated by both AMPA and NMDA receptors , whereas the PGC→MC and GC→MC synapses were mediated by GABAA receptors . Postsynaptic currents were modeled as in [25]: Isyn=WgsynsB ( V ) ( V−Esyn ) ( 1 ) where gsyn is the maximal synaptic conductance ( prior to weighting ) and Esyn is the reversal potential ( 0 mV for AMPA/NMDA currents and -80 mV for GABAA currents; [25] ) . The maximum synaptic conductances were: gAMPA = 2 nS and gNMDA = 1 nS for both MC→PGC and MC→GC synapses , and gGABA = 2 nS for both PGC→MC and GC→MC synapses [25] . W denotes the synaptic weight , which scaled the maximum preweighting synaptic conductance so as to generate final maximum synaptic conductances of W*gsyn . The synaptic weight was varied systematically in simulations; default synaptic weights were: WMC→PGC = 1 , WMC→GC = 1 , WPGC→MC = 4 , and WGC→MC = 2 ( arbitrary units ) . The function B ( V ) implemented the Mg2+ block for the NMDA current , and was defined as B ( V ) = ( 1 + [Mg2+]exp ( −0 . 062V ) /3 . 57 ) −1 83] . For AMPA and GABAA currents , B ( V ) = 1 . The gating variable s represented the fraction of open synaptic ion channels and obeyed first-order kinetics [84 , 85]: dsdt=αF ( Vpre ) ( 1−s ) −βs ( 2 ) where F ( Vpre ) was an instantaneous sigmoidal function of the presynaptic membrane potential , F ( Vpre ) = 1/ ( 1 + exp ( − ( Vpre –θsyn ) /σ ) ) . The half-activation potential ( θsyn ) of the synapse was set to 0 mV for AMPA/NMDA receptor synapses and -40 mV for GABAA synapses; the parameter σ was set to 0 . 2 for AMPA/NMDA currents and 2 . 0 for GABAA currents [25] . Consequently , synaptic excitation was triggered mostly by spikes ( high threshold ) , whereas synaptic inhibition occurred below spiking threshold and depended on presynaptic voltage in a graded manner . The channel opening rate constants ( α and β ) were expressed as α = 1/τα and β = 1/τβ , where τα and τβ were the synaptic rise and decay time constants respectively . For AMPA receptor currents , τα = 1 ms , τβ = 5 . 5 ms; for NMDA receptor currents , τα = 52 ms , τβ = 343 ms; and for GABAA receptor currents , τα = 1 . 25 ms , τβ = 18 ms [25] . Such first-order synaptic models naturally simulate the interactions of successive presynaptic events , enabling the saturation of slow synapses [85] . Specifically , with a slow rising time constant of 52 ms , the NMDA conductance increased only slightly in response to a single presynaptic spike , but accumulated over multiple synaptic inputs owing to its slow decay time constant of 343 ms , limited by the maximum synaptic conductance . Different synaptic decay time constants have been reported by experimental studies in the OB [20 , 23 , 86]; importantly , the modeled time constants represent in part the “functional time constants” generated by a quasisynchronously activated population of presynaptic synapses affecting the same postsynaptic neuron . Some of these parameters were varied for purposes of particular simulations as described in the Results; in those cases , the parameter values specified above are referred to as “default” or “control” values . Odor stimulation was modeled as in [25] . A sigmoidal function was used to model OSN inputs [33]: IOSN=u0+0 . 5 ( us−u0 ) [tanh ( 3 ( t−tORN ) r−3 ) +1] ( 3 ) where u0 was the pre-odor value ( simulated pure air input ) and us the steady-state value after odor excitation . The parameter r determined the transition rate from u0 to us ( set to 100 ) and torn the time of odor onset . Different MCs ( representing separate , independently-tuned glomeruli ) received different levels of afferent activation; the corresponding values of u0 and us were drawn from uniform distributions u0 ∈ ( 0 . 1 , 0 . 2 ) and us ∈ ( 0 . 2 , 1 . 0 ) . Additionally , all cells in the network received random excitatory inputs representing intrinsic and extrinsic sources of uncorrelated background noise . These nonspecific inputs were modeled as uncorrelated Poisson spike trains mediated exclusively by AMPA receptors; specifically , they comprised instantaneous steps followed by exponential decays with a time constant of 5 . 5 ms [25] . When plotting major network measures ( e . g . , MC/GC firing rates , oscillation frequencies , synchronization and oscillation indices ) under variable parameter sets , the data reported were averaged across 10 instantiations of the network with different random seeds for these Poisson spike trains . A simulated local field potential ( sLFP ) was constructed by filtering the mean ( somatic ) membrane potentials across all MCs [25] . Filtering was carried out numerically using a band-pass filter ( 10–100 Hz ) with the MATLAB functions FIR1 and FILTFILT [33] . The power spectrum of the signal was obtained by a fast Fourier transform ( FFT ) of the filtered sLFP . MC somatic spike times were converted to spike phases using the method detailed in [25] . The synchronization ( or phase-locking ) index was calculated as follows [22]: κ=1/N[∑i=1Nsin ( φi ) ]2+[∑i=1Ncos ( φi ) ]2 ( 4 ) where φi was the phase of each MC spike in the network relative to the sLFP peak . This synchronization index ( SI ) measures the degree of phase locking between MC spikes and sLFP oscillations rather than the absolute synchrony of MC spikes in time . Nevertheless , when substantial numbers of MC spikes are evoked , the SI also is a good measure of absolute spike synchrony . When all MC spikes have identical phases , the index achieves its maximal value of unity . The oscillation index ( OI ) corresponded to the peak of the frequency power spectrum of the sLFP , which was normalized to the largest peak value generated from ten sets of simulations with different random seeds . The oscillation frequency was determined from the position of the spectral peak in the power spectrum [25] . The model was implemented in the neuronal simulator package NEURON , version 7 . 3 [87] , using the Crank-Nicholson integration method and a fixed timestep of 2 μsec ( 0 . 002 ms ) . Shorter timesteps did not change the results . Simulations were run both on a workstation under CentOS Linux and on Linux clusters provided by the Cornell Computational Biology Service Unit’s High Performance Computing laboratory ( BioHPC ) . Simulation output data were saved in files and analyzed using custom Matlab scripts . | The mammalian olfactory bulb responds to odor stimulation by generating fast oscillations in its electrical field potential . Such oscillations are indications that a substantial number of principal neurons in the olfactory bulb are coordinating their activities in time , which often means that their action potentials are synchronized , or partly synchronized , such that the pattern of small differences in their spike times contains olfactory sensory information . We are interested in the mechanisms by which olfactory bulb circuitry can transform sensory information from the temporally unsophisticated spike rates of primary sensory neurons into this sophisticated cortical format . We present a biophysically explicit , multiscale dynamical model of the olfactory bulb network that generates these oscillations . The elements of this model are designed to adhere to experimental findings from individual neurons , membrane currents , and synapses as well as the functional network . Together , these elements generate gamma oscillations exhibiting the full range of properties of those in the biological system . We show that these dynamics arise from an inhibition-coupled oscillator framework , a type of dynamical system with some established mathematical properties . This finding enables us to understand how the olfactory system translates sensory information for distribution in the central nervous system , and how different areas of the brain can mechanistically coordinate with one another so as to regulate the flow of sensory information to appropriate target structures . | [
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"... | 2017 | A coupled-oscillator model of olfactory bulb gamma oscillations |
The parental feeding practices ( PFPs ) of excessive restriction of food intake ( ‘restriction’ ) and pressure to increase food consumption ( ‘pressure’ ) have been argued to causally influence child weight in opposite directions ( high restriction causing overweight; high pressure causing underweight ) . However child weight could also ‘elicit’ PFPs . A novel approach is to investigate gene-environment correlation between child genetic influences on BMI and PFPs . Genome-wide polygenic scores ( GPS ) combining BMI-associated variants were created for 10 , 346 children ( including 3 , 320 DZ twin pairs ) from the Twins Early Development Study using results from an independent genome-wide association study meta-analysis . Parental ‘restriction’ and ‘pressure’ were assessed using the Child Feeding Questionnaire . Child BMI standard deviation scores ( BMI-SDS ) were calculated from children’s height and weight at age 10 . Linear regression and fixed family effect models were used to test between- ( n = 4 , 445 individuals ) and within-family ( n = 2 , 164 DZ pairs ) associations between the GPS and PFPs . In addition , we performed multivariate twin analyses ( n = 4 , 375 twin pairs ) to estimate the heritabilities of PFPs and the genetic correlations between BMI-SDS and PFPs . The GPS was correlated with BMI-SDS ( β = 0 . 20 , p = 2 . 41x10-38 ) . Consistent with the gene-environment correlation hypothesis , child BMI GPS was positively associated with ‘restriction’ ( β = 0 . 05 , p = 4 . 19x10-4 ) , and negatively associated with ‘pressure’ ( β = -0 . 08 , p = 2 . 70x10-7 ) . These results remained consistent after controlling for parental BMI , and after controlling for overall family contributions ( within-family analyses ) . Heritabilities for ‘restriction’ ( 43% [40–47%] ) and ‘pressure’ ( 54% [50–59%] ) were moderate-to-high . Twin-based genetic correlations were moderate and positive between BMI-SDS and ‘restriction’ ( rA = 0 . 28 [0 . 23–0 . 32] ) , and substantial and negative between BMI-SDS and ‘pressure’ ( rA = -0 . 48 [-0 . 52 - -0 . 44] . Results suggest that the degree to which parents limit or encourage children’s food intake is partly influenced by children’s genetic predispositions to higher or lower BMI . These findings point to an evocative gene-environment correlation in which heritable characteristics in the child elicit parental feeding behaviour .
The home and family environment has been studied for decades with the assumption that it is a crucial determinant of children’s health and development . Since the onset of the childhood obesity crisis at the turn of the century , the spotlight has turned onto environmental factors associated with variation in adiposity , in the hope that modifiable elements may be identified as intervention targets . Perhaps unsurprisingly , parental behaviours have received a great deal of attention . Parents are widely considered to be the ‘gatekeepers’ to their children’s food , and powerful shapers of their developing eating behaviour[1–3] . Two types of parental feeding practices ( PFPs ) in particular have been hypothesised to play a causal role in children’s ability to develop good self-regulation of food intake and consequently determine their weight . Excessive restriction of the type and amount of food a child is allowed to eat ( ‘restriction’ ) has been hypothesised to lead to overeating when parental restriction is no longer in place , because the child will potentially then hanker after the foods he or she is not usually allowed to eat–the so-called ‘forbidden fruit effect’[1 , 4 , 5] . On the other hand , overly pressuring a child to eat , or to finish everything on the plate ( ‘pressure’ ) , is thought to be anxiety-provoking for a child with a poor appetite , and serves only to increase undereating further , and compromise weight gain[6 , 7] . A wealth of cross-sectional findings are consistent with these hypotheses[8] , but another plausible explanation for the observed correlations is that parents are responding to their child’s emerging characteristics , not simply causing them . Parents may only adopt restrictive strategies when a child shows a tendency toward overeating , or gains excessive weight; and they may pressure their child to eat only if he or she is a poor eater , or has underweight . The few longitudinal studies testing bidirectionality have shown that children’s weight prospectively predicts PFPs[9–13] . Furthermore , three studies showed no prospective association from PFPs to child weight[10] , and the studies reporting bidirectional relationships found stronger associations from child weight to parental behaviour than the reverse direction[9 , 11] . Although these findings point towards children’s weight eliciting PFPs , the possibility of residual confounding in observational studies hinders conclusions about causation–temporality does not necessarily mean causality . Testing whether children genuinely cause their parents’ behaviour presents challenges . It is not possible–practically or ethically–to randomise children to have overweight or underweight , and examine how parents respond . Genetic approaches provide a powerful alternative method of interrogating the role of children in causing their parents’ behaviour towards them , especially for child characteristics with an established genetic basis . To date , no study has applied genetically sensitive methods to test for gene-environment correlation in parental feeding behaviour . Family and twin studies have shown that Body Mass Index ( BMI ) , is highly heritable in both adulthood and late childhood ( ~70% ) [14–16] . Twin designs can also be used to test if parental behaviour has a heritable component , by comparing within-pair resemblance for identical and fraternal twin pairs in childhood . If found , this indicates that parental behaviour is explained to some extent by variation in children’s genotype–termed evocative gene-environment correlation[17] . Twin designs can also be extended to the analysis of multiple variables to establish if genetic influence on a particular child characteristic ( e . g . weight ) also predicts the parental behaviour of interest ( e . g . PFPs ) . If such analyses show that a child characteristic is genetically correlated with parenting traits , it indicates that these child characteristics influence parenting behaviours . A meta-analysis of 32 twin studies of different types of parenting behaviour reported an average heritability estimate of 24% , indicating that children’s genotype is predictive of a moderate amount of variation in parental behaviour[18] . Children’s DNA can also be used to test for gene-environment correlation . Genome-wide meta-analyses have made great progress in identifying common single nucleotide polymorphisms ( SNPs ) that are associated with body mass index ( BMI ) in adults and children[19] . These can be combined to calculate a genome-wide polygenic score ( GPS ) that indexes individual-specific propensity to higher or lower BMI , along a continuum , although in the aggregate the GPS explains only a small proportion of variance in BMI ( approximately 3% ) [20] . Nevertheless , children’s BMI GPS can therefore be used to test the hypothesis that parents develop their feeding practices specifically in response to their child’s weight , as indicated by a correlation between child BMI GPS and PFPs . A caveat to this is that a parent’s feeding practices may reflect their own genetic predisposition to be of a higher or lower BMI , rather than that of their children . In this way , a correlation between child BMI GPS and PFPs may simply reflect a child’s genetic predisposition to be of a higher or lower BMI , which they inherit from their parent with whom they share 50% of their DNA . In addition , genetic effects related to adult BMI discovered in genome-wide association studies could potentially incorporate effects of PFPs if they were to causally influence child BMI , and its trajectory into adulthood . However , within-family designs can circumvent both of these limitations to some extent . Studying variation in PFPs according to variation in BMI GPS within non-identical co-twins accounts for both genetic and environmental shared effects within families ( e . g . parental genetic predisposition to be of higher or lower BMI ) . By applying both quantitative and molecular genetic methods , and utilising statistical approaches to account for shared family effects , we intended to address the various limitations presented by the individual methods . The goals of this study were to test for gene-environment correlation between children’s BMI and PFPs , using a twin design and a BMI GPS . We hypothesised that: ( i ) children’s BMI GPS would be positively associated with parental restriction and negatively associated with parental pressure , even after accounting for shared genetic and environmental family influences; and ( ii ) parental restriction and parental pressure would be moderately heritable , and that genetic influence on PFPs would be partly explained by genetic influence on children’s BMI .
Child BMI-SDS was significantly positively correlated with ‘restriction’ ( β = 0 . 19 , t ( 4004 ) = 12 . 09 , p = 4 . 45x10-33 , R2 = 0 . 035 ) , such that parents were more restrictive over their child’s food intake if the child had a higher BMI . In contrast , child BMI-SDS was significantly negatively correlated with ‘pressure’ ( β = -0 . 24 , t ( 4058 ) = -15 . 59 , p = 3 . 14x10-53 , R2 = 0 . 056 ) , such that parents exerted higher amounts of pressure on their child to eat , if their child was leaner . ‘Restriction’ and ‘pressure’ were significantly positively correlated ( β = 0 . 15 , t ( 4207 ) = 9 . 51 , p = 3 . 08x10-21 , R2 = 0 . 021 ) , suggesting that parents who tend to exert higher levels of ‘restriction’ also exert a more pressuring feeding style , to some extent . In our sample of unrelated individuals , child BMI GPS was positively correlated with child BMI-SDS ( β = 0 . 20 , t ( 4226 ) = 13 . 08 , p = 2 . 41x10-38 , R2 = 0 . 039 ) . Mirroring phenotypic results for child BMI-SDS , children’s BMI GPS was significantly positively correlated with ‘restriction’ ( β = 0 . 05 , t ( 4255 ) = 3 . 53 , p = 4 . 19x10-4 , R2 = 0 . 003 ) , and significantly negatively correlated with ‘pressure’ ( β = -0 . 08 , t ( 4315 ) = -5 . 15 , p = 2 . 70x10-7 , R2 = 0 . 006 ) ( Fig 1 ) . These findings indicate that children’s genetic predisposition to higher BMI , elicits , to some extent , restrictive feeding behaviours in the parent; whereas children’s genetic predisposition to lower BMI elicits greater pressure to eat by parents . Parental BMI correlated positively with child BMI-SDS ( β = 0 . 26 , t ( 3761 ) = 17 . 00 , p = 1 . 57x10-62 , R2 = 0 . 071 ) and ‘restriction’ ( β = 0 . 08 , t ( 3711 ) = 4 . 64 , p = 3 . 65x10-6 , R2 = 0 . 005 ) , but was not significantly associated with ‘pressure’ ( β = -0 . 03 , t ( 3757 ) = -1 . 68 , p = 0 . 09 , R2 < 0 . 001 ) . The magnitude and direction of effects remained identical after controlling for parental BMI in ‘restriction’ ( β = 0 . 05 , t ( 3711 ) = 2 . 92 , p = 3 . 48x10-3 , R2 = 0 . 003 ) and in ‘pressure’ ( β = -0 . 08 , t ( 3757 ) = -4 . 62 , p = 3 . 97x10-6 , R2 = 0 . 005 ) . To establish the association between children’s BMI GPS and PFPs entirely without confounding by genetic and environmental family factors shared by twin pairs , we performed family fixed-effect analyses in dizygotic ( DZ ) co-twins . This analysis examined the extent to which parents vary their ‘restriction’ and ‘pressure’ across twin pairs in response to differences in their BMI GPS . As shown in Fig 2 , beta coefficients for BMI GPS predicting PFPs remained largely stable when comparing unrelated individuals ( Model 1 ) and DZ twin pairs ( Model 2 ) . For unrelated individuals ( Model 1 ) child BMI-SDS significantly positively predicted ‘restriction’ and significantly negatively predicted ‘pressure’ , as previously reported . The magnitude of the within-family estimates for the combined ( same-sex and opposite-sex ) DZ co-twins ( Model 2 ) were virtually the same as those for the unrelated individuals for the relationships between BMI GPS and ‘restriction’ ( t ( 2054 ) = 3 . 50 , p = 7 . 10x10-3 , Adj . R2model = 0 . 724 ) and BMI GPS and ‘pressure’ ( t ( 2103 ) = -4 . 82 , p = 1 . 52x10-6 , Adj . R2model = 0 . 641 ) ( R2 magnitudes for Model 2 are large because all shared factors among family members , including genetic and environmental influences , are accounted for ) . These findings indicate that even when shared family effects are completely accounted for , children’s BMI GPS is significantly associated with PFPs , providing additional evidence that children’s genetic predisposition to BMI evokes certain parental feeding responses . When repeating Model 2 analyses separately for same-sex and opposite-sex DZs , magnitudes of effect sizes ( Fig 2 ) remained consistent for the prediction of ‘pressure’ in same-sex DZ pairs ( t ( 1118 ) = -3 . 36 , p = 8 . 02x10-4 , Adj . R2model = 0 . 607 ) and opposite-sex DZ pairs ( t ( 984 ) = -3 . 49 , p = 5 . 12x10-4 , Adj . R2model = 0 . 678 ) . Although BMI GPS in opposite-sex DZs was a significant predictor of within-family differences in ‘restriction’ ( t ( 966 ) = 3 . 76 , p = 1 . 82x10-4 , Adj . R2model = 0 . 731 ) , same-sex DZ data did not show a significant within-family association ( t ( 1087 ) = 1 . 21 , p = 0 . 23 , Adj . R2model = 0 . 719 ) , indicating that within a family environment , GPS differences in BMI between same-sex DZ twins are not related to differences in parental ‘restriction’ . We performed multivariate genetic analyses ( a correlated factors model ) to establish the heritability of ‘restriction’ and ‘pressure’ and to test the extent to which genetic influence on child BMI-SDS elicited PFPs as indicated by the magnitude of genetic correlations between BMI , ‘restriction’ , and ‘pressure’ . Fig 3 shows the variance components ( A , C and E ) for each measured phenotype , as well as the genetic , shared environmental and non-shared environmental correlations between phenotypes derived from the correlated factors model ( see Supplementary S1 Table for fit statistics and model comparisons , and Supplementary S2 Table for intra-class correlations ) . Heritability estimates ( A ) were moderate to high for parental ‘restriction’ ( 43% , 95% CI [40% , 47%] ) and parental ‘pressure’ ( 54% , 95% CI [50% , 59%] ) ; heritability of child BMI-SDS was high ( 78% , 95% CI [72% , 84%] ) . Consistent with the findings from the GPS analyses , there was a significant , positive moderately sized genetic correlation between child BMI-SDS and parental ‘restriction’ ( rA = 0 . 28 , 95% CI [0 . 23 , 0 . 32] ) , indicating that some of the genetic effects that predispose a child to a higher BMI also elicit more food restriction by their parent . A sizeable significant negative genetic correlation was observed between child BMI-SDS and parental ‘pressure’ ( rA = -0 . 48 , 95% CI [-0 . 52 , -0 . 44] ) , indicating that many of the genetic effects that predispose a child to a lower BMI elicit greater parental pressure on the child to eat . As shown in the twin analyses ( Fig 3 and Supplementary S3 Table ) , variation in child BMI-SDS is partly caused by non-shared environmental influences , which correlate significantly with non-shared environmental influences for ‘restriction’ ( rE = 0 . 20 ) and ‘pressure’ ( rE = -0 . 29 ) . We therefore performed MZ twin difference analyses to examine these relationships more closely . In contrast to child BMI-SDS MZ difference scores , most twins did not differ in their PFP ( Supplementary S1 Fig ) . Nevertheless , we found that child BMI-SDS difference scores predicted both differences in ‘restriction’ ( β = 0 . 14 , t ( 1484 ) = 7 . 98 , p = 2 . 88x10-15 , R2 = 0 . 041 ) and ‘pressure’ ( β = -0 . 25 , t ( 1498 ) = -12 . 26 , p = 5 . 12x10-33 , R2 = 0 . 09 ) . These findings suggest that there are common non-shared environmental sources of variance for both PFP and child BMI; within identical twin pairs who share 100% of their genetic and shared environmental influence , parents apply more restrictive feeding practices on the twin with the higher BMI , and more pressuring feeding practices on the twin with the lower BMI score .
We describe the first study to test for gene-environment correlation for parental feeding behaviour in relation to child weight , using a twin design and children’s DNA . Results support our hypothesis that parents’ feeding practices are evoked , in part , by their children . Parental ‘restriction’ and ‘pressure’ were positively and negatively associated with child BMI respectively , in keeping with many previous cross-sectional studies[8] . We applied novel genetic methods to show , for the first time , that children’s BMI GPS was significantly positively associated with ‘restriction’ and negatively associated with ‘pressure’ , even after accounting for the potentially confounding shared familial effects ( both genetic and environmental ) . This suggests that children’s genetic influence on weight explains part of the observed phenotypic associations . Our twin analysis provided quantitative estimates of the total variance in parental feeding practices explained by children’s genotype . Heritability was substantial for both ‘restriction’ ( 43% ) and ‘pressure’ ( 54% ) , indicating that children’s genes explain about half of the variation in parental feeding behaviour . Multivariate twin analysis established the extent to which parental feeding behaviour was determined by children’s genetic influence on BMI specifically . The genetic correlations between children’s BMI and both ‘restriction’ ( rA = 0 . 28 ) and pressure ( rA = -0 . 48 ) were moderate , indicating overlap between the genes that influence parental feeding behaviour and children’s BMI . A potential confounder of the association between child GPS and parental feeding behaviour , was the parent’s own genetic propensity to a higher or lower BMI . Children inherit half of each of their parents’ genetic material , so the expected correlation between a child’s GPS with that of their parent’s is 0 . 50 . A parent’s genetic predisposition to be of a higher or lower BMI may also influence the way they feed their children , which could introduce a passive ( rather than ‘evocative’ ) gene-environment correlation . For example , a parent with a higher BMI may be more restrictive over their child’s food intake , but their child also inherits their parent’s susceptibility to be of a higher BMI . Restrictive feeding may therefore simply be a marker for a child’s genetic predisposition to be of a higher BMI that is transmitted to them by their parent , rather than a causal risk factor ( the same could be true for a more pressuring feeding style and lower BMI ) . In line with this , parental BMI ( indexing parental GPS ) was significantly positively associated with parental restriction indicating that parents of a higher weight exert greater restriction over their children’s food intake ( β = 0 . 08 ) ; although the association with parental pressure was not significant . Adjustment for parental BMI did not attenuate the associations between child GPS and either restriction or pressure , suggesting it was not confounding the relationship between parental feeding behaviour and child BMI GPS . Nevertheless , adjustment for parental BMI cannot completely remove confounding from parental BMI , nor can it account for the potential effect of longer-term BMI on parental feeding behaviours . However , in order to rule out confounding by any parental characteristics ( both genetic and environmental ) , we took advantage of a family fixed-effect design , which held the effects of family constant while testing the association between the child BMI GPS and parental feeding practices in DZ co-twins . The within-family analysis allowed us to demonstrate that even after accounting for all genetic and environmental familial effects , parents vary their feeding behaviour for each child depending on their GPS–larger GPS differences between pairs were associated with more pronounced differences in parental feeding behaviour . The magnitudes of the between- and within-family associations between parental feeding behaviour and child GPS were virtually the same , with the exception of the relationship between child GPS and ‘restriction’ in same-sex twins , strengthening the evidence that children evoke parental responses based on their genetic predispositions for BMI . Nevertheless , as expected , and consistent with the small amount of variance explained in BMI by the GPS , the size of the associations between the BMI GPS and PFPs were small . The findings from this study accord with those from twin studies of many other types of parenting behaviours that have also tended to show moderate heritability . A meta-analysis of 32 child twin studies on maternal positivity , negativity , affect and control in relation to parenting showed an average heritability of 24%[18] , indicating widespread , child-driven genetic influences on parental behaviour . The heritability estimates for ‘restriction’ ( 43% ) and ‘pressure’ ( 54% ) were somewhat higher than the average heritability estimate for the parenting styles considered in the meta-analysis ( 24% ) , but in keeping with the magnitude of the heritability of negative parenting styles observed across early childhood ( ~55% ) [21] . In addition to providing evidence for gene-environment correlation , results from the MZ discordance design also indicated that non-shared environmental influences for child BMI and PFPs are correlated as well . This suggests that child BMI and PFPs are also related due to common non-shared environmental influences . However , the MZ discordance design was not able to shed light on the causal direction–i . e . if child BMI causes PFPs or if PFPs cause child BMI–because our variables were measured at the same time . The few prospective studies that have attempted to establish the cause-effect relationship in the parent-child dynamic using bidirectional analyses have suggested either only a small effect of restriction and/or pressure on child weight , or none[9–11 , 13] . Prospective studies therefore suggest that PFPs may be less important than is commonly assumed . The well-established strong genetic influence on children’s weight–in the order of 70–80%[15 , 16]–also supports the hypothesis that parents influence child weight via genetic inheritance more than by creating an ‘obesogenic’ family environment . However , it cannot be ruled out that genetic effects related to BMI in the parents also contribute to an obesogenic environment if gene-environment correlation was at play , further passively reinforcing the child’s inherited genetic propensities . The shared environmental influence on BMI in late childhood is also low[15 , 16] . In the current study , the shared environmental influence on parental feeding behaviour was the proportion of variance that was common to both twins in a pair ( invariant within families ) . It therefore likely reflects variation in feeding behaviour that was parent-driven rather than child-directed . These estimates indicated that a substantial proportion of variation in both ‘restriction’ ( C = 43% ) and ‘pressure’ ( C = 37% ) also originated in the parent . Experimental studies in the form of large well-designed randomised controlled trials ( RCTs ) are needed to truly test the hypothesis that PFPs causally modify children’s weight gain trajectories . Very few of these have been conducted to date , and they have focused on the preschool years . Nevertheless , two landmark studies have indicated that parental behaviour may , in fact , be influential in early life . NOURISH[22] was an Australian RCT that randomised 352 parents and infants to receive a feeding intervention ( including using low amounts of pressure , and employing child-responsive methods of food restriction ) during the period of complementary feeding; 346 families were randomised to the standard care control group . At three to four years of age , children in the intervention group had better appetite control than those in the control group , and there were fewer children with overweight; although this did not reach statistical significance[23] . INSIGHT[24] , a US RCT , randomised 145 new mothers to a responsive parenting intervention that focused on feeding infants only in response to their hunger and satiety signals ( but neither pressuring nor restricting their milk and food intake ) , during milk-feeding and complementary feeding; 145 mothers were randomised to a control group . At one year significantly fewer infants in the intervention group had overweight ( 6% ) compared to the control group ( 13% ) . These RCTs indicate that parental feeding behaviour can modify young children’s eating behaviour and weight gain . However , these studies were conducted in infants and young preschool children so it is unclear whether these findings are generalisable to older children . The genetic correlations between children’s BMI and parental feeding behaviour were modest , and were far from complete ( i . e . less than 1 . 0 ) , indicating that other genetically-determined child characteristics are also influencing parental feeding behaviour . Children’s appetite is under strong genetic control; twin studies–including this sample–have shown high heritability for appetite[25 , 26] and shared heritability with BMI[27] . Appetite is associated with the BMI GPS in this sample and has been shown to mediate part of the GPS-BMI association[28] . It is therefore likely that child appetite also influences parental feeding behaviour[25 , 26] . In support of this , prospective and within-family studies have provided evidence that within the context of parental feeding , parents respond not only to their child’s weight but also to their eating styles . A large prospective population-based study used bidirectional analyses to show that parents whose children were excessively fussy at baseline increased their pressure over time[29] . A reverse relationship also pertained , but the temporal association from child to parent was stronger . A large within-family study of preschool twins showed that parents varied their pressuring feeding style when their twins were discordant for food fussiness[30] . The fussier twin was pressured more than their co-twin , also in support of a child-driven model of parental feeding behaviour . It stands to reason that a child who is a picky eater is pressured to try some of their vegetables or to eat more overall . Along the same lines , a natural response from a parent who has a child who shows a tendency toward excess intake and a relatively pronounced preference for foods rich in sugar or fat , is to enforce some restriction . We also found a positive phenotypic correlation between ‘restriction’ and ‘pressure’ ( β = 0 . 15 ) , indicating that parents who exert higher levels of restriction on their children also tend to pressure them more . This suggests that some parents have a more controlling feeding style in general . The relationship between parental behaviour and children’s emerging characteristics appears to be reciprocal and complex . The current findings suggest that parents’ natural feeding responses to child weight are to exert greater restriction of food intake on children with a higher BMI , and to pressure a thinner child to eat . However , these strategies may not be effective in the long run . RCTs have suggested that PFPs can have a lasting and important impact on children’s weight and eating behaviour in the early years , although whether or not these findings apply to older children has yet to be determined . It is well established that genetic influence on BMI in younger children is lower , and the shared environmental effect is higher , than it is in older children[15 , 16] . This suggests that parental influence diminishes as children grow older , gain independence and spend increasing time outside the home with peers rather than parents[31] . Large RCTs that follow children from early life to later childhood are needed to establish if PFPs influence the weight of older children . A strength of this study is that we used several genetically sensitive methodological approaches to explore the directionality of relationships between child BMI and PFPs , yielding consistent results . PFPs were measured using the Child Feeding Questionnaire , which has well established criterion and construct validity , as well as good internal and test-retest reliability[32] . This instrument has been used widely in previous research into child weight , allowing the findings from this study to be directly compared to a wealth of existing results . A potential limitation is that heritability estimates from twin studies rely on the assumption that MZs and DZs share their environment in terms of the trait in question to the same extent , so-called the ‘equal environments assumption’; if this is violated , the findings are invalid . Therefore if parents feed MZs more similarly than DZs simply because they are identical , this would artificially inflate the MZ correlation and , consequently , heritability . However , if MZs are fed more similarly than DZs because parents are responding to their genetically determined BMI or traits that share genetic influence with BMI such as appetite , differences in feeding experience across MZs and DZs do not constitute a violation of the equal environments assumption because these differences in feeding practices are being driven by greater genetic similarity between MZs than DZs . In addition , if parents’ reports of how similarly they fed their twins were biased by their perceived zygosity ( i . e . reported treatment was not a true reflection of actual treatment , but related to the twins being MZ or DZ ) , this would also render the heritability estimates unreliable . However , this seems unlikely given previous findings that parents’ reports about their twins’ are not biased by their beliefs about their zygosity , using the ‘mistaken zygosity’ design[33] . Another limitation was the lack of parental genotypes assessments . Parental BMI is by no means a perfect proxy for their genotypic predisposition to higher or lower BMI; the most powerful approach would be to have parental genotypes whereby the non-transmitted alleles from the parents ( which relate to their own BMI and behaviour , but not to that of their child ) can be entirely separated from the child’s genotype[34] . Nevertheless , the within-family analysis controlled for all family-level genetic and environmental effects , and the magnitudes of the relationships between child BMI and PFPs were unaffected . A further limitation is that we were unable to validate self-reported parental BMI , which may have been inaccurate and could potentially bias our results . Additionally , it may be possible that PFPs are largely explained by environmental factors that influence children’s BMI . As the BMI GPS is not yet strong enough to be a sufficient proxy to separate genetic and environmental effects on child BMI , we were unable to test this question empirically . However , considerable genetic correlations between child BMI and PFPs derived from the twin model renders this explanation unlikely . Lastly , BMI was only reported at one time point , but PFPs are likely to be driven by the child’s emerging BMI throughout the developmental years . However , BMI-associated SNPs and BMI GPS are associated with weight gain trajectories from infancy throughout childhood , so the BMI GPS in fact captures a long window of child BMI[14 , 35] . This study provides new evidence for gene-environment correlation in parental feeding practices . We have shown that parental feeding practices are substantially heritable and appear to be partly elicited by the common genetic variants that influence children’s BMI . Genome-wide polygenic scores that index children’s genetic propensities for their BMI significantly predicted their parents’ feeding practices , even after potentially confounding shared family effects were taken into account . The findings of this study provide a new perspective on the nature of the associations between parental feeding practices and child BMI .
Participants were drawn from the Twins Early Development Study ( TEDS ) . Between 1994–1996 TEDS recruited over 15 , 000 twin pairs born in England and Wales , who have been assessed in multiple waves across their development up until the present date . Despite some attrition , about 10 , 000 twin pairs still actively contribute to TEDS , providing genetic , cognitive , psychological and behavioural data . TEDS participants and their families are representative of families in the UK[36] . Written informed consent was obtained from parents prior to data collection . Project approval was granted by King’s College London’s ethics committee for the Institute of Psychiatry , Psychology and Neuroscience ( 05 . Q0706/228 ) . This study included 4 , 445 unrelated individuals with genotyping for the GPS analysis , 2 , 164 genotyped dizygotic ( DZ ) twin pairs ( 1 , 151 same-sex DZ pairs , 1 , 013 opposite-sex DZ pairs ) , and 4 , 375 twin pairs for the twin analysis ( 1 , 636 monozygotic ( MZ ) pairs , 1 , 441 same-sex DZ pairs , and 1 , 298 opposite-sex DZ pairs ) . Two different genotyping platforms were used because genotyping was undertaken in two separate waves , five years apart . AffymetrixGeneChip 6 . 0 SNP arrays were used to genotype 3 , 665 individuals at Affymetrix , Santa Clara ( California , USA ) based on buccal cell DNA samples . Genotypes were generated at the Wellcome Trust Sanger Institute ( Hinxton , UK ) as part of the Wellcome Trust Case Control Consortium 2 ( https://www . wtccc . org . uk/ccc2/ ) . Additionally , 8 , 122 individuals ( including 3 , 607 dizygotic co-twin samples ) were genotyped on HumanOmniExpressExome-8v1 . 2 arrays at the Molecular Genetics Laboratories of the Medical Research Council Social , Genetic Developmental Psychiatry Centre , using DNA that was extracted from saliva samples . After quality control , 635 , 269 SNPs remained for AffymetrixGeneChip 6 . 0 genotypes , and 559 , 772 SNPs for HumanOmniExpressExome genotypes . Genotypes from the two platforms were separately phased using EAGLE2[37] , and imputed into the Haplotype Reference Consortium ( release 1 . 1 ) through the Sanger Imputation Service[38] before merging genotype data from both platforms . Genotypes from a total of 10 , 346 samples ( including 3 , 320 dizygotic twin pairs and 7 , 026 unrelated individuals ) passed quality control , including 3 , 057 individuals genotyped on Affymetrix and 7 , 289 individuals genotyped on Illumina . The final data contained 7 , 363 , 646 genotyped or well imputed SNPs ( for more details , see Supplementary S1 Methods ) . We performed principal component analysis on a subset of 39 , 353 common ( MAF > 5% ) , perfectly imputed ( info = 1 ) autosomal SNPs , after stringent pruning to remove markers in linkage disequilibrium ( r2 > 0 . 1 ) and excluding high linkage disequilibrium genomic regions so as to ensure that only genome-wide effects were detected . The samples used for the analyses differed by necessity in order to accommodate the different methodological approaches: unrelated genotyped individuals ( UG ) ; dizygotic genotyped co-twins ( DG ) ; twin sample ( TS ) for quantitative genetic analysis . For the classical twin model approach , only phenotypic data from genotyped twins and their co-twins were selected for comparability across the study samples . Descriptive statistics for all phenotypic measures are reported in Supplementary S4A Table for unrelated genotyped individuals , in Supplementary S4B Table for genotyped DZ twin pairs and in Supplementary S4C Table for samples used for twin modelling . Children’s body mass index ( BMI ) was calculated from parent-reported weight ( kg ) divided by the square of parent-reported height ( metres ) : kg/m2 . The 1990 UK growth reference data[39] were used to create BMI standard deviation scores ( BMI-SDS ) which take account of the child’s age and sex , and represent the difference between a child’s BMI and the mean BMI of the reference children of the same age and sex . BMI-SDS are used rather than BMI itself because BMI varies substantially by age and sex until early adulthood . Reference BMI-SDS have a mean of 0 and a SD of 1: a value greater than 0 indicates a higher BMI than the mean in 1990; a value less than 0 indicates a lower BMI than the mean in 1990 . The validity of parent-reported height and weight was tested through home-visits of researchers in a subset of 228 families . Correlations between measurements taken by parents and researchers were high ( height: r = 0 . 90; weight: r = 0 . 83 ) [40] . BMI-SDS were available for 4 , 259 ( UG ) , 4 , 134 ( DG ) , and 8 , 406 ( TS ) individuals . Children had a mean age of 9 . 91 years ( SD = 0 . 87 ) when anthropometric measures were assessed . Parental BMI was calculated for 4 , 112 individuals using self-reported weight ( kg ) and height ( metres ) of the responding parent ( kg/m2 ) , which was assessed at the same time as childhood height and weight . To account for the gender of the responding parent ( 97% mothers , 3% fathers ) , we used the z-standardized residuals of gender-corrected BMI in analyses . To assess PFPs , we used the Child Feeding Questionnaire[41] , which parents completed when their twins were approximately 10 years old ( mean = 9 . 91 years , SD = 0 . 87 ) . To measure the degree to which parents restricted their children’s food intake ( ‘restriction’ ) , we calculated a mean composite score based on 6 items ( Cronbach’s alpha = 0 . 78 ) , such as “I intentionally keep some foods out of my child’s reach“ , or “If I did not guide my child’s eating , he/she would eat too many junk foods” . Data were available for 4 , 386 ( UG ) , 4 , 228 ( DG ) and 8 , 582 ( TS ) children . Similarly , we created a mean composite score to assess the amount of pressure parents exerted on their children to increase their food intake ( ‘pressure’ ) , including 4 items ( Cronbach’s alpha = 0 . 61 ) such as “If my child says “I’m not hungry” , I try to get him/her to eat anyway” , or “I have to be especially careful to make sure my child eats enough” . Data were available for 4 , 445 ( UG ) , 4 , 328 ( DG ) and 8 , 750 ( TS ) children . All items were scored on a 5-point Likert scale ( Disagree , Slightly disagree , Neutral , Slightly agree , Agree ) . For child and parent anthropometrics we removed extreme outliers with implausible values that were deemed to be errors . For children we excluded values based on the following criteria: -/+ 5 standard deviations above or below the mean of height SDS , weight SDS or BMI-SDS; shorter than 105 cm or taller than 180cm; lighter than 12 kg or heavier than 80 kg . After removing outliers , child BMI-SDS had a mean of 0 and a standard deviation of 0 . 99 , showing that the sample is representative of the UK reference population for BMI in 1990 ( mean = 0; SD = 1 ) . For parental BMI , we removed individuals with values that fell -/+ 3 . 5 standard deviations above or below the mean , as well as individuals that weighed below 35 kg . To account for the positive skew , we log transformed this variable . As all variables showed age or sex effects ( described in Supplementary S4A , S4B and S4C Table ) , we controlled for these variables by applying the regression method , using z-standardized residuals for all further analyses . Supplementary S5A , S5B and S5C Table show descriptive statistics for all clean measures ( regressed onto age and sex ) in unrelated samples , for DZ twin pair samples , and individuals used for twin modelling , respectively . We created Genome-wide Polygenic Scores ( GPS ) for BMI , using summary statistics from a genome-wide meta-analysis of BMI including 339 , 224 participants[19] . We calculated a GPS for each individual as the sum of the weighted count of BMI-increasing alleles: GPSBMI=∑i=1kβiSNPi where i ∈ {1 , 2 , . . , k} and indexes SNPi and the i number of the k BMI increasing alleles included in the score is determined by the p-value threshold of the SNP–phenotype association in the discovery GWAS , the β-coefficients for each respective genetic variant is used as a weight , and the count of each reference allele is represented by genotype dosage ( 0 , 1 , or 2 alleles ) of SNPi . We used the software PRSice[42] to calculate GPS in our sample . To account for multicollinearity among SNPs in Linkage Disequilibrium ( LD ) , which can upwardly bias GPS predictions[43] , genome-wide clumping was performed ( r2 = 0 . 1 , kb = 250 ) . Using the clumped , independent SNPs , we created eight GPS for 10 , 346 individuals ( 7 , 026 unrelated individuals; 3 , 320 DZ twin pairs ) using increasingly liberal GWAS p-value thresholds ( pT: 0 . 001 , 0 . 05 , 0 . 1 , 0 . 2 , 0 . 3 , 0 . 4 , 0 . 5 , 1 ) . Diagonals in Supplementary S2 Fig show the number of SNPs included in each respective GPS . As all thresholds performed similarly well ( Supplementary S2 Fig ) , we used a GPS based on the smallest p-value threshold of 0 . 001 for all further analyses . Potential effects due to population stratification and genotyping were accounted for by regressing the first ten principal components , and factors capturing genotyping information ( microarray , batch and plate ) onto the child BMI GPS , subsequently using the z-standardised residuals in our analyses . To obtain broad estimates of the extent to which individual differences in PFPs are determined by children’s genotypes , we used a multivariate ‘correlated factors’ twin model . This allowed us to estimate: ( 1 ) the heritability of PFPs , which provided an indication of the extent to which PFPs are caused by children’s genotypes in general; and ( 2 ) the extent of common genetic influence on both child BMI-SDS and PFPs , which provided an indication of the extent to which PFPs are caused by children’s genetic propensity to higher or lower BMI , specifically . Based on biometrical genetics theory[44] , it is possible to decompose variance in a single trait into three components: additive genetic ( A; heritability ) , shared environmental ( C; all environmental effects that make family members more similar ) and non-shared environmental ( E; all environmental effects that contribute to dissimilarities across family members , including random error measurement ) . The basis of the method is to compare resemblance for a single trait between monozygotic ( MZ ) and dizygotic ( DZ ) twin pairs , who share 100% and 50% ( on average ) of their segregating genetic material , respectively , while both types of twins are correlated 100% for their shared environmental influence . The observed covariation between MZ and DZ pairs is compared with the expected covariation , based on the knowledge of different degrees of allele sharing ( or identity by descent ( IBD ) ) of MZ ( IBD = 1 . 0 ) and DZ pairs ( IBD = 0 . 5 on average ) . The twin method therefore assumes that MZ and DZ twins share their environments in terms of the trait in question to the same extent ( so-called the ‘equal environments assumption’ ) , and the only difference between the two types of twins is the extent of their genetic relatedness . Using the same principles , comparison of MZ and DZ covariation across traits ( so-called cross-twin cross-trait covariance , e . g . the covariation between twin 1 BMI-SDS and twin 2 ‘restriction’ ) provides an indication of the extent to which the genetic and environmental influences on multiple traits are the same . The key pieces of information provided are the aetiological correlations , which indicate the extent to which child BMI and PFPs are caused by the same additive genetic ( genetic correlation; rA ) , shared environmental ( shared environmental correlation; rC ) , and non-shared environmental influences ( non-shared environmental correlation; rE ) . In this analysis we were primarily interested in the genetic correlation , which indicates the extent to which the additive genetic influences on child BMI cause PFPs . The aetiological correlations range from -1 to 1 and can be interpreted similarly to Pearson’s correlations . For example , a high positive genetic correlation between ‘restriction’ and BMI would indicate that many of the DNA variants that cause higher child BMI are the same as those cause higher levels of ‘restriction’ , while a high negative genetic correlation would indicate that many of the DNA variants causing higher child BMI are the same as those causing lower levels of ‘restriction’ . Maximum likelihood structural equation modelling was used to estimate intra-class correlations across the zygosities , the A , C and E parameter estimates and aetiological correlations ( with 95% confidence intervals ) , and goodness-of-fit statistics . Sex differences in the parameter estimates were also tested for using a sex-limitation model . Analyses were implemented in the R package OpenMx[45] . | It is widely believed that parents influence their child’s BMI via certain feeding practices . For example , rigid restriction has been argued to cause overweight , and pressuring to eat to cause underweight . However , recent longitudinal research has not supported this model . An alternative hypothesis is that child BMI , which has a strong genetic basis , evokes parental feeding practices ( ‘gene-environment correlation’ ) . To test this , we applied two genetic methods in a large sample of 10-year-old children from the Twins Early Development Study: a polygenic score analysis ( DNA-based score of common genetic variants associated with BMI in genome-wide meta-analyses ) , and a twin analysis ( comparing resemblance between identical and non-identical twin pairs ) . Polygenic scores correlated positively with parental restriction of food intake ( ‘restriction’; β = 0 . 05 , p = 4 . 19x10-4 ) , and negatively with parental pressure to increase food intake ( ‘pressure’; β = -0 . 08 , p = 2 . 70x10-7 ) . Associations were unchanged after controlling for all genetic and environmental effects shared within families . Results from twin analyses were consistent . ‘Restriction’ ( 43% ) and ‘pressure’ ( 54% ) were substantially heritable , and a positive genetic correlation between child BMI and ‘restriction’ ( rA = 0 . 28 ) , and negative genetic correlation between child BMI and ‘pressure’ ( rA = -0 . 48 ) emerged . These findings challenge the prevailing view that parental behaviours are the sole cause of child BMI by supporting an alternate hypothesis that child BMI also causes parental feeding behaviour . | [
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"sc... | 2018 | Evidence for gene-environment correlation in child feeding: Links between common genetic variation for BMI in children and parental feeding practices |
The development of bacteria on abiotic surfaces has important public health and sanitary consequences . However , despite several decades of study of bacterial adhesion to inert surfaces , the biophysical mechanisms governing this process remain poorly understood , due , in particular , to the lack of methodologies covering the appropriate time scale . Using micrometric colloidal surface particles and flow cytometry analysis , we developed a rapid multiparametric approach to studying early events in adhesion of the bacterium Escherichia coli . This approach simultaneously describes the kinetics and amplitude of early steps in adhesion , changes in physicochemical surface properties within the first few seconds of adhesion , and the self-association state of attached and free-floating cells . Examination of the role of three well-characterized E . coli surface adhesion factors upon attachment to colloidal surfaces—curli fimbriae , F-conjugative pilus , and Ag43 adhesin—showed clear-cut differences in the very initial phases of surface colonization for cell-bearing surface structures , all known to promote biofilm development . Our multiparametric analysis revealed a correlation in the adhesion phase with cell-to-cell aggregation properties and demonstrated that this phenomenon amplified surface colonization once initial cell-surface attachment was achieved . Monitoring of real-time physico-chemical particle surface properties showed that surface-active molecules of bacterial origin quickly modified surface properties , providing new insight into the intricate relations connecting abiotic surface physicochemical properties and bacterial adhesion . Hence , the biophysical analytical method described here provides a new and relevant approach to quantitatively and kinetically investigating bacterial adhesion and biofilm development .
Bacterial growth on surfaces and interfaces leads to the formation of three-dimensional communities called biofilms [1] . Biofilm-specific tolerance to different biocidal treatments used in health care facilities stimulated the investigation of key molecular events in biofilm formation , and molecular factors promoting bacterial adhesion have been characterized , including surface-exposed adhesins and polysaccharidic polymers . However , initial cell surface attachment itself is still poorly understood , and many questions remain regarding biophysical aspects of the adhesion process due to lack of appropriate investigation tools [2 , 3] . Physico-chemical approaches based on the Derjaguin-Landau-Verwey-Overbeek ( DLVO ) [4] theory , although reliable in predicting interactions between well-controlled model hard spheres , have often proven inappropriate for modeling bacterial adhesion [5] . This is likely due to the multiplicity of parameters involved in the adhesion process , influenced both by biological and environmental factors . On the other hand , most biological approaches to surface colonization rely on procedures that develop on an hourly or daily scale . Hence , interpretations are often made at the final adsorption stage or at equilibrium , when initial adhesion is blurred by subsequent biofilm development steps , thus preventing precise kinetic analysis of the adhesion process [3] . Alternative short-term approaches are therefore needed to provide quantitative and kinetic information on the early stage of bacterial interaction with a surface . We introduced a new methodology which takes advantage of advanced flow cytometry ( FCM ) analyses [6] to characterize initial bacterial cell surface attachment . Only a few studies monitoring bacterial attachment to mammalian cells using FCM have been published [7 , 8] . Thus far , stream techniques involved in FCM have appeared incompatible with the study of bacterial adhesion usually studied on macroscopic plane surfaces . We have overcome this apparent antagonism by choosing dispersed surfaces in the form of well-characterized micrometric particles as adhesion substrates in order to explore initial events of surface colonization by the bacterium Escherichia coli . We used charged particles as adhesion substrates , representing the most widespread situation for surfaces immerged in aqueous media due either to their inherent ionization state or to the water ion structure at the interfaces . Then , we examined the contribution of three well-characterized E . coli adhesion factors with a time resolution of a few seconds and the precision of one bacterium per particle . This revealed several phases leading to surface colonization , and evidenced clear-cut differences strongly dependent on the nature of the adhesin expressed at the cell surface . We also explored the contribution of cell-to-cell aggregation properties and particle surface physicochemical property changes throughout the colonization process . This analytical procedure therefore opens up new perspectives in the understanding of bacterial adhesion to abiotic surfaces .
To develop a short–time scale method for studying early bacterial adhesion , we used spherical micrometric colloidal particles as adhesion substrates , both positively charged ( aminated , NH3+ ) and negatively charged ( carboxylated , COO– ) with zeta potentials of +45 mV and −55 mV , respectively . Suspensions of 10-μm particles were resuspended in phosphate-buffered saline ( PBS ) and examined by microscopy and FCM . 80% of the events detected with the two types of particles were concentrated in scattering value region R1 ( free particles scattering region ) , corresponding to a monodispersed population ( Figure 1A and unpublished data ) . Particle surface charge properties were traced using an anionic dye ( pyranine , PYR ) and a cationic dye ( propidium iodide , PI ) , the fluorescent labeling of which was detected by microscope imaging ( Figure 1B ) and FCM ( Figure S1 ) . Both probes displayed fast ( adsorption half-time < 1 s ) and selective electrostatic adsorption onto particles carrying opposite charges . PYR was emitted in the FL1 channel [mean fluorescence intensity in channel 1] ( 525 ± 10 nm ) and PI in the FL3 channel [mean fluorescence intensity in channel 3] ( >670 nm ) . Labeling properties were conserved in M63B1 medium , the rather high ionic strength ( ≈200 mM versus 150 mM , e . g . , for PBS ) medium used in this study both for growth of the bacteria and the adhesion assay ( see below ) , indicative of strong and irreversible association , which demonstrated that the chosen pairs of dyes were flexible surface-charge reporters in the heterogeneous context of a bacterial suspension . To determine optimal recording conditions for bacterial adhesion in the colloidal system , we analyzed samples composed of planktonic cultures of fluorescent and non-fluorescent E . coli K-12 strains MG1655 and MG1655gfp , respectively , mixed at various proportions . Due to their smaller size , bacteria had to be analyzed with higher scattering photomultiplier gains than colloidal particles and appeared in a distinct acquisition window . We isolated a bacterial signal in scattering region Rb containing at least 98% of the recorded events ( Figure 2A ) . Depending on sample composition , fluorescence plots FL1/forward scattering ( FSC ) stemming from Rb events displayed one or two subsets , each with a characteristic mean fluorescence FL1 value conserved in the whole sample series ( Figure 2B–2D ) . The ratio of the number of cells counted in high and low fluorescence subsets accurately matched values expected from the mixtures ( Figure S2 ) , indicating that the recorded signals originated from single cells . Indeed , if more than one cell was detected in a single event , then higher number of subsets depending on the number of detected cells would have appeared with intermediate fluorescence intensities . This enabled us to determine a cell unitary fluorescence value fli from the mean FL1 fluorescence of an Rflb gate ( bacteria region ) containing the fluorescent bacteria ( Figure 2B ) . When green fluorescent protein ( GFP ) -labeled cells were allowed to rest at room temperature for 2 h , we observed the formation of cell aggregates that produced higher scattering and a fluorescence signal defining a new gate , Rflag ( bacterial aggregates fluorescence ( channel 1 ) region in bacteria records ) ( Figure 2E ) . The aggregate scattering parameters were sufficiently different from those of colloidal particles to avoid any confusion between the two types of objects even when aggregate sizes increased . Therefore , the Rflag number of events ( N ( Rflag ) ) , mean fluorescence ( FL1 ( Rflag ) ) , and mean forward scattering ( FSC ( Rflag ) ) enabled us to report the dispersion state of the cell suspension . To study bacterial adhesion onto colloidal substrates , GFP-labeled E . coli cells were brought into contact with cationic particles under gentle stirring , producing mild shear stress on the order of a few tens of piconewtons per contact . While this stirring abolished gravity effects , it also screened cell motility . Therefore , although bacterial motility has been shown to play a role in surface colonization under static conditions [9] , its effect is here masked by velocity gradients due to stirring-induced hydrodynamic shear . The question of the role of bacterial self-propulsion through flagellar motility is thus not addressed here . The FCM signal was recorded on aliquots taken at different times from the cell-particle sample using a sample flow speed of 1 μl/s and an acquisition time equal to 5 s . Direct microscopic observation showed that bacteria adhered to colloidal particles , leading to the emergence of a new cluster of higher fluorescence on particle FL1/FSC cytograms , corresponding to particles carrying at least one bacterial cell ( Figure 3A and B ) . Bare ( R2 ) and colonized particles ( R3 ) were thus easily discriminated on the basis of their fluorescence intensity and described by the two particle subsets stemming from the R1 gate ( Figure 3B ) . As shown in an experiment performed using a 200-fold excess of colloidal particles over bacteria ( Figure S3 ) —which ensured that only rare but single cell adhesion events would statistically appear—bacterial fluorescence was not affected by adhesion to particles . Therefore , the mean number of particle-bound bacteria ( nF ) could be obtained simply by dividing mean particle fluorescence ( FL1 ( R1 ) ) by bacterial unitary fluorescence ( fli = FL1 ( Rflb ) ) . Adhesion in the colloidal system could be regarded as the sum of discrete efficient collisions occurring between one particle and one cell , and could then be adequately described by Poisson's law as follows: where P ( k ) was the probability of finding a particle bearing k bacteria when the mean of the distribution was . For a given acquisition , the experimental value of was nF . fc , the colonized particle fraction , was experimentally given by fc = N ( R3 ) /[N ( R2 ) + N ( R3 ) ] and was linked to P ( 0 ) , the probability of finding a particle free of bacteria by fc = ( 1 – P ( 0 ) ) , which gave . For any value of fc , we could thus calculate the mean of the corresponding statistical distribution nP= –ln ( 1 – fc ) . This provided a direct means of characterizing adhesion distribution and detecting eventual cooperative effects by comparing nP to experimental value nF calculated from mean fluorescence . This also enabled the definition of a cooperative index λ , given by the ratio nF/nP . To achieve a complete description of the cell particle suspension , 5 μl of a 10−6 M PI solution were added to each aliquot taken from the incubation sample . Labeling performed just before the FCM analysis and after the cell–particle interaction allowed us to characterize the particle surface charge . It did not , however , affect cell–particle association , as checked by parallel recordings of unlabeled and labeled samples ( unpublished data ) . The complete analysis enabled us to determine , for each sample test , the free-floating cell aggregation state , the cell particle surface association degree , as well as the particle surface charge state . It also reported the potential cooperative character of cell to particle surface binding . The colloidal system approach therefore enabled full quantification of the early bacterial adhesion process . Moreover , the sensitivity of signal recording enabled us to determine adhesion kinetics taking place within the range of few seconds after cell–particle contact . Curli are thin aggregative fimbriae assembled at the cell surface of most Enterobacteriaceae , in which they have been shown to promote adhesion to abiotic surfaces [10] . They form 6–12-nm-diameter structures whose length varies between 0 . 5 and 1 μm [11] . To explore the contribution of curli to early steps in bacterial adhesion , we used fluorescent E . coli either overexpressing curli due to a mutation in ompR , the positive regulator of curli expression ( MG1655gfpompR234 ) [10] , or deprived of curli ( MG1655gfpΔcsgA ) . We compared the adhesion profiles of mid-exponential phase growth cultures on aminated particles using a cell-to-particle ratio close to 200 . FCM analyses of 10 μl aliquots taken from both cultures at ∼30 s intervals revealed that the presence of curli strongly modified early initial attachment of bacteria to an abiotic surface . The adhesion kinetics of the strain constitutively expressing curli displayed two distinct binding phases ( Figure 4A ) . After 20 min of adhesion , the extent of particle surface colonization , as reported by the mean number of bound bacteria per particle nF , was more than a hundred times higher than that of the curli-deficient mutant strain ( Figure S4 and Figure 4A and 4B ) . In contrast , strain MG1655gfpΔcsgA exhibited single-phase kinetics characterized by a steady state corresponding to a low level of binding reached within the first seconds after particle contact ( Figure 4B ) . To quantitatively analyze these cell surface adhesion profiles , we considered the first adhesion phase ranging from 10 s to 10 min after particle/bacteria initial contact . Dynamics of early surface binding , nF ( t ) was adjusted to the first-order–like kinetics equation nF ( t ) = Nmax ( 1 – exp ( -kat ) ) for both types of bacterial cells , with Nmax the maximum mean colonization level displayed at plateau and ka the apparent time constant of the adhesive process . The colonization plateau was obtained in both cases in the presence of a large fraction of free-floating cells . For MG1655gfpΔcsgA , the steady state was characterized by an Nmax value equal to 0 . 25 ± 0 . 3 bacteria per particle ( bact part−1 ) , which corresponded to the attachment of one cell for every four particles . This very restricted binding occurred rapidly after cell–particle contact , with an initial colonization rate reported by Nmaxka equal to 1 . 3 bact part−1 min−1 . The rapid establishing of this low-level steady state ( t1/2 = 0 . 13 min ) indicated that cell and particle surfaces were essentially repulsive to each other under the conditions of the experiment , contrary to what could have been expected from opposite charge ( negative cells and positive particles ) surfaces . This point is further investigated below . The curli producer strain MG1655gfpompR234 displayed , in phase I , a ten times higher colonization level than the curli-defective strain ( Nmax = 3 . 2 ± 0 . 5 bact part−1 ) and exhibited a longer characteristic time ( t1/2= 2 . 8 min and an initial binding rate of 0 . 8 bact part−1 min−1 ) ( Figure 4A and 4B ) . This indicated that , in the presence of curli , cell and particle surfaces did not experience the repulsive potential observed between curli-defective cells and particle surfaces . Nevertheless , in this phase I , MG1655gfpompR234 cells exhibited a colonization plateau in between three and four attached cells per particle , which represented a rather sparse surface occupation . This could be due to particle surface heterogeneity—of molecular nature or concentration—resulting in a low density of adhesive sites for bacteria in this first adhesive phase . Fresh particles added at the plateau to the cell–particle suspension displayed the same colonization kinetics as those initially present at t = 0 ( Figure 4C ) , demonstrating that remaining floating bacteria still had the capacity to adhere to freshly added particles . On the other hand , no additional colonization occurred ( stable nF ) when additional bacteria were added at the colonization plateau ( unpublished data ) . These results suggest establishment , on the particle surface , of a repulsive potential that limits MG1655gfpΔcsgA adhesion but is partially overcome by the presence of curli adhesion to the surface of MG1655gfpompR234 . To investigate the possible origin of the repulsive potential , we monitored particle surface charge during colonization using the cationic dye PI labeling procedure ( see above ) . As shown above ( Figure S1 ) , aminated particles suspended in PBS or M63B1 fresh medium did not adsorb the dye . Their FL3 intensity remained at the level of the background , corresponding to particles in the absence of dye . In contrast , when PI was added to the analysis test tubes taken from the incubation sample in the presence of exponentially grown bacteria , we measured a rapid increase in the PI labeling signal both with curli producer and nonproducer bacteria ( Figure 4D ) . This indicated that the particle surface—initially positively charged—had turned into a negative surface potential , which enabled PI adsorption . This PI labeling affected both cell-free and colonized particles in the suspension ( Figure S5A ) , suggesting that soluble species present in the bacterial supernatant were responsible for this effect . Consistently , aminated particles resuspended in filter-sterilized culture supernatants were labeled with PI , confirming production by bacterial cultures of anionic molecules . Furthermore , labeling intensity increased when supernatant stemmed from a longer overnight culture ( unpublished data ) . No significant bacterial cell death was observed within the culture before or after incubation , as indicated by the absence of noticeable number of red-labeled bacteria on fluorescence microscopy images . Indeed , in case of cell death , the dye contained in our samples would cross cell membrane and accumulate inside the cell through DNA association . Thus , only a small , naturally occurring bacterial lysis , which releases bacterial products in the medium , is expected to take place in our experiments , suggesting that this phenomenon could contribute only marginally to the surface properties changes observed . When COO– particles were tested , we observed that PI labeling , initially high with such anionic surface functionalization , slightly decreased , suggesting that these surfaces were also modified by cell supernatant , which finally set the exposed surfaces to similar potentials ( Figure S5B ) . Zeta potential measurements were performed on particles first incubated in bacterial culture media coming from cultures of the F plasmid-bearing strain and then suspended at 10% v/v in water for measurements . Value shifted for cationic particles from +36 mV in unspent medium ( +45 in pure water ) to −32 mV after 15 min incubation in 12-h culture spent medium . Anionic particles displayed slightly reduced negative charge , shifting from −65mV in unspent medium to −42 mV after medium conditioning , completely corroborating the behavior reported by dyes labeling . Very similar results were obtained with supernatant from MG1655 strain ( unpublished data ) . This surface charge conversion to a negative potential was thus likely to explain the repulsive potential observed against bacteria . To further investigate this , MG1655gfpompR234 or MG1655gfpΔcsgA bacteria were placed in contact with both positively ( NH3+ ) and negatively ( COO– ) charged particles , simultaneously and in the same sample . PI labeling enabled us to differentiate both types of particles within the sample ( Figure S5C ) . For both strains , COO– particle colonization was only slightly reduced compared to colonization on NH3+ particles , as if cells sensed very similar surfaces ( unpublished data ) . These results indicate that negative surface charge conversion induced by bacterial supernatants determines the surface potential of the interaction with cells independently of the initial surface state . In the absence of curli , this negative and thus repulsive potential dominates the interaction . Expression of curli at the cell surface obviously enabled overcoming this repulsion either by superimposing a much stronger binding force or by allowing the interaction to occur at a longer surface separation distance where the electrostatic potential had dropped . Indeed , in this high ionic strength medium , the Debye length is short and the electrostatic interactions quickly vanish with distance . After the initial binding phase , the MG1655gfpompR234 colonization kinetics profile systematically displayed a sudden increase about 10–12 min after cell–particle contact ( Figure 4A and 4E ) . Concomitantly , we observed a drastic increase in the population contained in the gate characteristic of bacterial aggregates ( Rflag ) , along with the appearance in the colloid plot of a new population collected in gate R5 ( bacterial aggregates fluorescence ( channel 1 ) region in particles records ) , corresponding to larger size particle-free bacterial aggregates ( Figure 5A–5C ) . The kinetics curve showed that MG1655gfpompR234—but not MG1655gfpΔcsgA—aggregation started after a 10-min lag , suggesting that aggregation could result from a biological shift in curli production . Indeed , when cells were incubated 15 min in the presence of 100 μg/ml of the translation inhibitor chloramphenicol before adhesion test , the second adhesive phase was abolished as well as the drastic cell-cell aggregation increase ( unpublished data ) . During this second phase , we also observed a rapid exponential increase in the cooperative index ( Figure 5D ) , which indicated that already occupied particles were preferentially but not exclusively colonized . In addition , a synchronized increase in PI labeling of colonized particles ( Figure 4D ) , but no change in cell-free particle labeling ( unpublished data ) , showed that this second phase colonization induced an increase in the negative potential of the colonized surfaces . Cell-cell aggregation also occurred when the experiment was conducted in the absence of particles , therefore ruling out the hypothesis of a surface-induced process ( Figure 5C ) . To evaluate the specificity of our observations with curli-expressing bacteria , we tested the adhesive properties of E . coli strains expressing other well-characterized adhesion factors . We first analyzed the adhesion profile of an E . coli strain that constitutively produces the autotransported adhesin Ag43 , a short , 10-nm , surface-exposed adhesin known to promote cell-cell interactions and biofilm formation [12–14] . Ag43-mediated cell-to-cell association was confirmed by the presence of a significant number of events in aggregate-characteristic gates ( Figure 6A ) . However , interestingly , the adhesion profile of Ag43+ cells ( MG1655gfpPcLflu ) was very close to that of the Ag43-depleted strain ( MG1655gfpΔflu ) ( Figure 6B ) . This shows that , by contrast with curli expression , the strong cell-to-cell aggregation induced upon Ag43 expression did not correlate with surface attachment . This is probably due to lack of efficient initial bacterial adhesion enabling further anchoring of bacterial aggregates . Next we examined the adhesive behavior of an E . coli strain expressing the F-conjugative pilus , which promotes both initial adhesion and biofilm maturation [15] . We compared colonization of the F-free strain ( MG1655gfp ) with an F-carrying strain ( MG1655gfpF ) . We observed that F expression supported a significant one-phase surface attachment the kinetics of which could be approximated to a first-order-like process ( Figure 6C ) . The plateau was obtained at Nmax=2 . 7 bact part−1 with a time constant ka = 0 . 16 min−1 , indicating an initial adhesion rate of Nmaxka = 0 . 45 bact min−1part−1 , close to that of curli-expressing strain MG1655gfpompR234 in phase I ( see Figure 4C ) . Meanwhile , the F pilus-expressing cells did not exhibit significant self-association properties under these conditions ( Figure 6D ) , indicating that this appendage did not support strong cell-to-cell interactions as curli or Ag43 did . Moreover , no second adhesive phase was observed and the cooperative index of F-carrying strains displayed no significant deviation from the unit ( Figure 6E ) , which is consistent with the idea of a second adhesive phase correlated with both initial phase one association and strong cell-to-cell association . Taken together , these results show that the kinetics of particle colonization are dependent on the nature of the expressed adhesion factor .
While bacterial adhesion genetics is being actively explored and produces increasing information on molecular factors that promote biofilm , the precise mechanism by which bacteria adhere to inert surfaces is not well understood [16 , 17] . We analyzed initial steps in bacterial attachment to abiotic surfaces by developing a new methodological approach that combined the use of a colloidal micrometric bead suspension as adhesion substrate and FCM . This strategy enabled the design of a real-time , multiparametric analysis to simultaneously monitor surface attachment , free-floating bacteria , and the surface physico-chemical state in the same sample , with the precision of a single cell and a time resolution of a few tens of seconds , without any separation step . Previous original attempts to assess initial binding kinetics used quartz microbalance equipment [18] . Although quartz resonance microbalance provides online monitoring of the physical state of the adsorbed cell layer reported by frequency shifts , it cannot be directly related to the numbers of attached cells . In contrast , FCM using colloids as adhesion substrates enabled us to directly monitor adhesion kinetics , providing initial binding rates that are unequivocal parameters of cell-surface association . These parameters are unaffected by bacterial features that are not part of initial adhesion , such as the division rate or resistance to shear or gene-dependent transition leading to biofilm . Moreover , the multi-parametric nature of FCM offered the opportunity of correlating initial adhesion with surface property changes and free-floating cell aggregation shifts , two phenomena involved in surface colonization . FCM kinetics are obtained on large cell populations with high statistical weight even for small subsets ( >1% ) . However , unlike microscope imaging , this technique does not allow monitoring the fate of a single bacterial cell over time [19 , 20] . We showed that expression of several well-defined adhesion factors induced significant differences in early adhesion profiles recorded after cell surface exposure . We first demonstrated the direct implication of curli and F-conjugative pilus in cell surface attachment within the first minutes of contact . In contrast , the strain constitutively expressing short surface adhesin Ag43 displayed no significant rapid initial surface binding . Yet this appendage was implicated in abiotic surface colonization in various models [9 , 21] . This suggests that the Ag43 adhesin does not contribute to early steps in interactions between bacteria and the surface; rather , it may participate in subsequent steps of biofilm maturation not investigated in our short–time scale approach . Kinetic characteristics of this initial surface binding support the hypothesis of the formation of a finite number of links between cell and particle surfaces rather than a physicochemical surface interaction , which would saturate either at cell population exhaustion or at surface overcrowding . Binding could occur either from the formation of a molecular complex between bacterial appendages and binding sites exposed at the particle surface after adsorption of surface active molecules produced by the cell suspension , or from hydrophobic interactions enabling cell strong adhesion on sparse and limited zones distributed over the particle surface . On the other hand , we show here , for all strains studied irrespective of the nature of exposed surface appendages , that surfaces undergo significant charge changes immediately when placed in contact with bacterial suspensions . The surface conditioning of host or environmental origin has been frequently addressed [2 , 22 , 23] . However , bacteria themselves produce macromolecules with sufficient surface activity to play a role in bacterial adhesion . This surface conversion induced by anionic surface-active molecules contained in the bacterial suspension could be one of the main reason why no clear relationship between initial surface physicochemical properties and bacterial adhesion has been established up to now [24] , and that it might also partially explain why the DLVO theory has been generally unsuccessful in describing bacterial colonization . We have no information as yet on the nature of the anionic biomacromolecule involved in the observed fast surface conversion , although bacterial surface polysaccharides such as released capsule fragment or LPS might be good anionic macromolecular candidates [25 , 26] . This surface conditioning accounts for the repulsive potential observed between MG1655gfpΔcsgA and the particle surface . This phenomenon is of particular interest in elucidating bacterial adhesion mechanisms , since it might constitute a mechanism by which nature selects the adhesive organisms , by first setting a repulsive surface potential . In addition to initial surface contact , curli-expressing bacteria exhibited a second kinetic phase that correlated with the onset of significant bacterial self-aggregation . This second colonization phase could be due to the accumulation of curli subunits at the surface of the bacteria and developed cooperatively . Suppression of this second phase by chloramphenicol treatment known to stop translation suggests that de novo synthesis of curli during the adhesion process is responsible for curli accumulation ( unpublished data ) . Consistently , when curli genes were placed under the control of an anhydrotetracyclin inducible promoter , ptetO [27] , both aggregation and adhesion increased with increasing concentration of the inducer ( unpublished data ) . Interestingly , although the strain constitutively expressing adhesin Ag43 displayed a strong aggregation phenotype , as expected from previous reports , it did not display secondary surface colonization [13 , 27 , 28] . Consistently , no second colonization phase was observed with E . coli expressing the F-pilus , which exhibited no rapid free-floating self-association in our experimental conditions using dispersed exponentially grown bacteria . Altogether , this demonstrates that early surface-bound cells could serve as anchors initiating cell associations , in good agreement with the role played by curli in biofilm maturation [10 , 29 , 30] and suggests that extensive cell-cell aggregation can amplify surface colonization , provided sufficient initial surface binding has occurred . Many reviews on bacterial adhesion have contributed to spreading the notion of a general two-step mechanism comprising primary reversible adhesion , in which most bacteria leave the surface on-and-off to join the planktonic phase , followed by secondary irreversible attachment [2 , 20 , 22 , 31] . This so-called reversible-to-irreversible transition actually describes differential resistance to shear due to contact maturation in an out-of-equilibrium process . In experiments presented here , we monitored only irreversible adhesion in the thermodynamic sense; indeed no spontaneous binding shift upon dilution of suspension was observed . We show here that these irreversible interactions could take place during the first seconds of the contact independently of a prior reversible step . It is very likely that in our experiments , reversible events such as those described by Agladze et al . are instantaneously discarded by exposure to hydrodynamic flow ( stirring and FCM shear flow ) [32] . In conclusion , we have introduced a new short–time resolution tool for quantitative and statistical analysis of cell-surface adhesion . It enables determination of initial cell-surface binding kinetics and analysis of initial adhesive behaviors conferred by different bacterial cell surface structures . Beyond initial adhesion , we show that cell–cell aggregation properties held by several surface appendages amplify surface colonization once initial adhesion is established . This suggests a biofilm development scenario in which various adhesion factors contribute to different but complementary tasks to colonize the abiotic surface . During this process , micrometric structures such as curli and F-pilus support the formation of initial contact with the surface , the properties of which are strongly influenced by surface-active biomacromolecules . Further elucidation of molecular interactions behind initial steps in bacterial adhesion might help to elaborate original approaches to limiting biofilm development . Finally , we believe that quantitative and kinetic dissection of early adhesion events could also represent a powerful way to investigate other aspects of biofilm development , including evaluation of potential antiadhesive compounds , gene expression upon surface contact or strain competition and cooperation during surface colonization .
Constitutive curli producers ( MG1655gfpompR234 ) were obtained by transducing , into gfp-tagged MG1655 ( MG1655gfp ) , the ompR234 mutation that specifies a gain of function allele of ompR , a gene encoding an activator of the curli operon [10] . MG1655gfpF carries a derivative of the F-conjugative plasmid . Non-curli producers ( MG1655gfpΔcsgA ) , non-Ag43 producers ( MG1655gfpΔflu ) , as well as constitutive Ag43 ( MG1655gfpPcLflu ) producers were constructed by a three-step PCR procedure as described in [33 , 34] . The latter strains were constructed by introducing , in front of the flu gene , the kmPcL cassette , which enables constitutive expression of chromosomal target genes [27] . Primers used to perform , verify , and sequence the different constructions are listed in Table S1 . All strains were grown in lysogeny broth ( LB ) medium or , for adhesion experiments , in defined M63B1 medium with 0 . 4% glucose ( M63B1Glu ) at 30 °C for curli experiments or 37 °C for other experiments . Antibiotics were added when required: kanamycin ( Km , 50 μg/ml ) , chloramphenicol ( Cm , 25 μg/ml ) , ampicillin ( Amp , 100 μg/ml ) , spectinomycin ( Spec , 50 μg/ml ) , and tetracycline ( Tet , 7 . 5 μg/ml ) . 10-μm-diameter polystyrene latex particles functionalized with carboxyl groups ( COO– ) were purchased from Polysciences . Particles were used either with their initial carboxyl functionalization after extensive washing and re-suspension in M63B1 minimal medium , or after surface treatment with polyethylenimine permethobromide a cationic , 6 , 300 molecular weight , branched polymer according to the principle initially introduced by Decher [35] . Briefly , particles were washed in pure water by filtration over 0 . 60 μm of diameter filter , adjusted to a concentration close to 106/ml and gently stirred for 5 min in the presence of 3 × 10−3 M polyethylenimine ( monomer concentration ) , which corresponds to an excess of positive charges compared to the negative charges of the colloidal particles . The permethylated amine polymer adsorbed rapidly onto the negatively charged particle , producing a net charge inversion and providing a cationic amino-functionalization ( NH3+ particles ) . Particles were then washed four times before being concentrated five times in the experiment buffer , usually PBS or M63B1 . The quality and stability of the deposit were checked by measuring the zeta potential in water using a Malvern zetasizer nano ZS Malverninstrument: −55 mV and +45 mV for COO– and NH3+ particles , respectively . The deposit remained stable for several weeks , therefore confirming the robust adsorption already mentioned by other authors [36] . The colloid particles used in this study did not display any bactericidal activity against E . coli cells . FCM analyses of bacteria and colloid suspensions were performed using a Becton-Dickinson flow cytometer ( Facscalibur ) . GFP and green dye PYR emissions were recorded in fluorescence channel FL1 ( band pass centered on 530 nm ) . The PI signal was collected in channel FL3 ( >650 nm ) . Two different acquisitions were performed on each sample to collect either the bacterial signal or the colloid signal ( lower FSC and SSC ( side scattering ) amplifications were used for colloids , but the same fluorescence gain settings were used for both objects ) . At least 1 , 500 events were recorded in colloid acquisition and 15 , 000 in that of bacteria . Data were analyzed using CellQuest ( BDIS ) and FlowJo ( Tree Star ) multivariate analysis software . Cells and particles were brought into contact in a round-bottom tube . An adequate volume of exponentially growing bacterial suspension—DO590 = 0 . 5–0 . 6 in M63B1Glu—was usually injected at time t = 0 into a particle suspension adjusted to the appropriate concentration in M63B1 and stirred at room temperature on a soft vortex ( 1 , 000 rpm min−1 ) . Total volume of this incubator was usually equal to 500 μl . Aliquots of 5–20 μl were taken at given incubation times for immediate analysis in FCM in 300 μl PBS supplemented with 5 picomoles PI or microscope imaging . | When bacteria grow on solid surfaces , they can form three-dimensional communities called biofilms . Within these complex structures , bacteria can develop specific tolerance to different microbiocides , causing serious health and economic problems . Investigations of the key molecular events involved in biofilm formation have shown that surface-exposed adhesin proteins promote this process , but many questions remain regarding the mechanisms and biophysics of surface adhesion . We introduced an original approach to investigating the very early steps in bacterial adhesion that uses dispersed colloidal surfaces as microbial adhesion substrates . Using flow cytometry , we performed a quantitative real-time analysis of adhesion kinetics of several strains of the bacterium Escherichia coli , which were genetically engineered to produce well-characterized cell-surface adhesins that are known to promote biofilm development . We provide evidence for previously unknown adhesin-dependent behaviors , such as clear-cut differences in the very initial phases of surface colonization . We also demonstrate that initial adhesion correlates with almost instant surface property changes , and that cell-to-cell association might serve as an amplification mechanism for surface colonization . We therefore provide a new understanding of the intricate relationships between the physico-chemistry of abiotic surfaces and bacterial adhesion . | [
"Abstract",
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"Results",
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] | [
"biophysics",
"microbiology"
] | 2008 | A Short–Time Scale Colloidal System Reveals Early Bacterial Adhesion Dynamics |
The innate immune response provides the first line of defense against viruses and other pathogens by responding to specific microbial molecules . Influenza A virus ( IAV ) produces double-stranded RNA as an intermediate during the replication life cycle , which activates the intracellular pathogen recognition receptor RIG-I and induces the production of proinflammatory cytokines and antiviral interferon . Understanding the mechanisms that regulate innate immune responses to IAV and other viruses is of key importance to develop novel therapeutic strategies . Here we used myeloid cell specific A20 knockout mice to examine the role of the ubiquitin-editing protein A20 in the response of myeloid cells to IAV infection . A20 deficient macrophages were hyperresponsive to double stranded RNA and IAV infection , as illustrated by enhanced NF-κB and IRF3 activation , concomitant with increased production of proinflammatory cytokines , chemokines and type I interferon . In vivo this was associated with an increased number of alveolar macrophages and neutrophils in the lungs of IAV infected mice . Surprisingly , myeloid cell specific A20 knockout mice are protected against lethal IAV infection . These results challenge the general belief that an excessive host proinflammatory response is associated with IAV-induced lethality , and suggest that under certain conditions inhibition of A20 might be of interest in the management of IAV infections .
Viruses are a class of highly diverse pathogens which depend on the host cell for their replication . The initiation of a protective innate antiviral immune response involves the action of specialized pattern recognition receptors ( PRR ) , which detect conserved molecular structures of the invading pathogen . Triggering of PRRs induces the production of host proinflammatory cytokines ( e . g . TNF , IL-6 and IL-1 ) and type I interferons ( interferon-α ( IFN-α ) and IFN-β ) through activation of downstream signaling pathways that control various transcription factors such as NF-κB , AP-1 , IRF3 and IRF7 [1] , [2] . The presence of viral nucleic acids , such as viral RNA and DNA , viral replication intermediates and viral transcription products , can be sensed by specific intracellular PRRs [3] . Endosomal Toll-like receptors ( TLRs ) and cytoplasmic RNA helicase RIG-I-like receptors ( RLRs ) or Nod-like receptors ( NLRs ) detect the presence of viral single stranded ( TLR7 , TLR8 , Nod2 ) or double stranded RNA ( TLR3 , RIG-I , MDA5 ) . Intracellular DNA sensors that mediate antiviral immune responses to DNA viruses include TLR9 , DAI [4] and the PYHIN domain containing proteins AIM2 [5] , [6] , [7] and IFI16 [8] . TLR mediated antiviral responses are restricted to specialized type I IFN producing plasmacytoid dendritic cells ( pDC ) , while most other cell types , including conventional DC ( cDC ) , macrophages and fibroblasts , depend on the cytosolic RNA and DNA sensors for the production of antiviral proteins [9] . Influenza A virus ( IAV ) is the etiological agent of a contagious acute respiratory disease that causes considerable mortality , which is generally believed to be due to an excessive host inflammatory response . Emergence of drug-resistant strains of influenza viruses with pandemic potential underscores the importance of developing novel antiviral strategies . In this context , understanding of the mechanisms that regulate IAV-induced immune responses is critical . IAV infection leads to the exposure in the host cell of single-stranded genomic RNA and double stranded RNA , the latter being an intermediate of viral replication . TLR3 and RIG-I have been implicated as sensors of IAV infection [10]–[12] . Both receptors contribute to the proinflammatory response to IAV , but the initiation of the innate antiviral immune response largely depends on RIG-I mediated signaling [13] . Interestingly , RIG-I deficient mice are highly susceptible to IAV [14] , [15] , whereas TLR3 deficient mice have a survival advantage to acute infection [16] . These results indicate that an imbalance between the beneficial and harmful effects of mediators released by immune cells is likely to contribute to the pathogenesis of influenza . RIG-I contains a C-terminal DExD/H box helicase domain , which is required for ligand recognition , and two N-terminal CARD domains . Upon ligand binding , the CARD domains of RIG-I associate with the CARD domain of the MAVS ( also termed IPS-1 , VISA , Cardif ) adaptor protein , which subsequently translocates to and inserts in the outer mitochondrial membrane via its C-terminal transmembrane domain [17]–[20] . Signaling downstream of MAVS requires the action of various ubiquitin modifying enzymes , which both positively and negatively regulate RIG-I mediated signal transduction [21] . K63-specific ubiquitin ligases ( E3s ) , such as TRIM25 [22] and Riplet [23] , [24] , have been shown to directly promote RIG-I activation . In addition , well characterized ubiquitin ligases such as TRAF6 [25] , [26] and TRAF3 [27] mediate respectively NF-κB and IRF3 activation upon RIG-I stimulation . On the other hand , deubiquitinating enzymes ( DUBs ) , such as DUBA [28] , CYLD [29] , [30] and OTUB1/2 [31] have been shown to negatively regulate RLR signaling by specifically removing K63-linked polyubiquitin chains from several signaling molecules . Furthermore , various K48-specific ubiquitin ligases , such as AIP4 [32] and TRIAD3A [33] mark respectively MAVS and TRAF3 for proteasome mediated degradation , thus inhibiting further downstream signaling . Additionally , the attachment of K48-specific polyubiquitin chains to the IRF3 and IRF7 transcription factors by E3s such as RAUL [34] , TRIM21 [35] and RBCK1 [36] further dampens antiviral signal transduction . A20 is an ubiquitin-editing enzyme belonging to the OTU-domain family of DUBs . Interestingly , A20 also harbors atypical zinc finger dependent K48-specific E3 ubiquitin ligase activity . Both catalytic and noncatalytic mechanisms were previously shown to be involved in the negative regulation of proinflammatory signaling by A20 in response to multiple receptors such as TNF receptor I [37]–[39] , TLR4 [40] , and IL-1R [41] . The anti-inflammatory role of A20 is clearly demonstrated by the fact that A20 deficient mice die early after birth due to severe multi-organ inflammation and cachexia [37] . More recently , gene targeting of A20 in specific cell types was shown to be associated with autoimmunity and chronic inflammation [42]–[48] , further illustrating that A20 is an important brake on the inflammatory response . The relevance of these findings for human disease has recently been illustrated through the identification of polymorphisms in the A20 locus that are associated with several autoimmune diseases and chronic inflammation [45] . In contrast to its well established function in the regulation of proinflammatory responses , the role of A20 in the regulation of antiviral immune responses is less well described and limited to a number of in vitro studies using overexpression or silencing in specific cell lines , indicating that A20 may regulate RIG-I- and TLR3-induced signaling to NF-κB and IRF-3 [49]–[52] . However , the precise in vivo role of A20 in the response to viral infection remains to be clarified . Using myeloid cell specific A20 knockout mice ( A20myel-KO ) that were recently generated in our lab and primary cells derived of these mice , we here provide evidence that A20 is a crucial negative regulator of IAV-induced proinflammatory and antiviral signaling in macrophages . Interestingly , A20myel-KO mice show enhanced survival and reduced morbidity in response to IAV lung infection compared to wild type mice . Protection against IAV in A20myel-KO mice is associated with increased cytokine and chemokine production , augmented recruitment of innate immune cells such as neutophils and alveolar macrophages , and enhanced viral clearance . These results suggest that boosting the innate immune response to IAV by targeting A20 activity in myeloid cells might have therapeutic potential .
RIG-I signaling induces the activation of NF-κB , IRF3 and IRF7 transcription factors , which promote the expression of proinflammatory cytokines and type I IFNs that restrict further viral propagation . Previous studies have shown that ectopically expressed A20 negatively regulates NF-κB and IRF3 activation upon RIG-I stimulation [50]–[52] . Similarly , we show that A20 overexpression in HEK293T cells prevents NF-κB- and IRF3-dependent luciferase reporter gene activation induced by transfection of a truncated constitutive active form of RIG-I [53] , corresponding to only the two N-terminal CARD domains of RIG-I [RIG-I ( 2CARD ) ] ( figure 1A , left and middle graph ) . We next investigated whether A20 also inhibits IRF7 activation . Unlike IRF3 , IRF7 is not or weakly expressed under naïve conditions and IRF7 protein levels are rapidly upregulated upon virus-induced IRF3 activation [54] , [55] . To determine the effect of A20 on IRF7 activation , we therefore transfected minor amounts of an IRF7 expression plasmid together with plasmids encoding RIG-I ( 2CARD ) , A20 and an IRF7-specific IFNα4 luciferase reporter construct . RIG-I ( 2CARD ) expression in the absence of IRF7 co-expression showed negligible IFNα4 promoter activation ( grey bar , figure 1A , right graph ) , whereas significant reporter gene expression was observed in the presence of IRF7 . Similar to its inhibitory effect on NF-κB and IRF3 activation , A20 also prevented RIG-I-induced IRF7 activation ( figure 1A , right graph ) . These results demonstrate the potential of A20 to inhibit RIG-I-induced NF-κB and IRF3/7 activation . To study the effect of endogenously expressed A20 on RIG-I-induced signaling in a more immunological relevant context , we performed further experiments in A20 deficient primary macrophages . Since A20 full knockout mice die prematurely as a result of severe multi-organ inflammation [37] , we generated mice carrying a conditional A20 allele in which exon IV and exon V were flanked by two loxP sites [56] . Crossing these mice with transgenic mice expressing Cre recombinase under control of the lysozyme M promoter leads to specific deletion in myeloid cells and allowed us to generate myeloid cell specific A20 knockout mice [48] . To stimulate the RIG-I receptor , we transfected A20myel-KO BMDM and wild type control cells with minimal amounts of low molecular weight ( LMW ) poly ( I:C ) , which is known to preferentially bind and activate RIG-I rather than MDA5 [57] . Of note , this concentration of poly ( I:C ) was unable to induce significant TLR3 dependent NF-κB and IRF3 activation or cytokine production ( data not shown ) . As expected , poly ( I:C ) transfection induced the rapid expression of A20 in wild type , but not in A20myel-KO BMDM ( figure 1B , upper panel ) . At early time points , slightly slower migrating forms of A20 were observed , indicating that A20 undergoes a yet unknown modification upon poly ( I:C ) transfection . Compared to wild type BMBM , A20 deficient cells showed enhanced NF-κB activation as indicated by increased phosphorylation and sustained degradation of IκBα ( figure 1B ) . Furthermore , nuclear translocation of the p65 NF-κB subunit was enhanced in poly ( I:C ) transfected A20myel-KO BMDM , reaching a maximum at earlier time points compared to wild type cells ( figure 1C ) . IRF3 is known to be activated upon phosphorylation of a series of carboxyl terminal serine residues by the IKK-like kinases TBK1 and IKKε [58] , leading to its dimerization and subsequent translocation to the nucleus [59] . Using immunoblotting with an antibody directed against phosphorylated Ser396 , maximum IRF3 phosphorylation was detected at earlier time points in A20myel-KO BMDM compared to wild type BMDM ( figure 1B ) . Similar to p65 , IRF3 nuclear translocation reached its maximum at an earlier time point in A20 deficient BMDM compared to wild type cells ( figure 1C ) . NF-κB controls the expression of IL-6 and TNF , and NF-κB and IRF3 control the expression of IFNβ . In line with the enhanced activation of NF-κB and IRF3 as described above , A20myel-KO BMDM secreted increased amounts of IL-6 , TNF and IFNβ ( figure 1D ) . Similar results were obtained using peritoneal macrophages ( data not shown ) . Together , these results demonstrate that A20 plays an important role in the negative regulation of RIG-I-induced NF-κB and IRF3 activation in primary macrophages . To investigate the role of A20 in the IAV-induced proinflammatory and antiviral innate immune responses , we infected A20 deficient and control BMDM with IAV X-47 ( H3N2 ) . A20 mRNA levels were rapidly induced in wild type BMDM , but not in A20 deficient BMDM , upon viral infection ( figure 2A ) . Furthermore , A20myel-KO BMDM show enhanced expression of IL-6 and IFNβ mRNA after IAV infection compared to control cells ( figure 2A ) . In accordance with these data , cell culture supernatant collected from these cells contained higher levels of TNF and IFNβ ( figure 2B ) . Upon host infection with IAV , alveolar macrophages are an important source of cytokines and chemokines , attracting innate immune cells to the lung during the primary phase of infection . To test whether A20 directly controls IAV-induced gene expression in alveolar macrophages , we isolated these cells from lungs of A20myel-KO and control littermates and infected them in vitro with IAV X-47 . Expression and secretion of the proinflammatory cytokines IL-6 and TNF , the type-I IFN IFNβ and IFNα4 and the chemokines MCP-1 ( ccl2 ) and KC ( cxcl1 ) was significantly higher in IAV infected cells lacking A20 compared to infected wild type cells ( figure 2C and figure S1 ) . Taken together these results demonstrate that A20 negatively regulates IAV-induced proinflammatory and antiviral gene expression in alveolar macrophages , consistent with the inhibitory effect of A20 seen on RIG-I-induced NF-κB and IRF3 activation . To determine the role of A20 expression in myeloid cells during an IAV infection in vivo , we intranasally inoculated both A20myel-KO mice and control littermates with a sublethal dose of the mouse adapted IAV X-47 ( H3N2 ) strain and monitored morbidity in terms of weight loss . A20myel-KO mice showed reduced weight loss compared to wild type control littermates and recovered faster from the viral challenge ( figure 3A ) . Also , total protein concentration in BAL fluid , which reflects lung damage and vascular leakage , was increased significantly at 7 and 10 days post infection in both wild type and A20myel-KO mice , and was slightly lower in A20myel-KO mice ( data not shown ) . Next , we measured pulmonary viral titers at 4 , 7 and 10 days post infection . No differences in viral titers were observed in A20myel-KO mice versus wild type mice at day 4 and 7 post infection . However , after 10 days , almost no virus could be detected in the lungs of A20myel-KO mice while abundant infectious viral particles could still be isolated from lungs of all wild type mice ( figure 3B ) . This indicates that loss of A20 in myeloid cells does not affect early viral replication but contributes to viral clearance at later stages during infection . To verify if A20 deficiency in myeloid cells affects IAV-induced gene expression in the lung , we analyzed the levels of several chemokines and cytokines in the bronchoalveolar lavage ( BAL ) at day 4 , 7 and day 10 following infection . Levels of KC and MIP-2 chemokines , as well as IL-6 were significantly higher at day 7 p . i . in BAL from IAV infected A20myel-KO mice compared to IAV infected wild type mice ( figure 3C ) . Unlike our observations with in vitro stimulated primary macrophages we could not detect a significant increase in MCP-1 or IFNα production in the lungs of A20myel-KO animals ( figure 3C ) . KC is the murine orthologue of IL-8 and serves together with MIP-2 as a chemoattractant for neutrophils , while MCP-1 is mainly known as a chemoattractant for monocytes , which eventually develop into macrophages upon entering the alveolar lumen [60] . Consistent with the higher KC and MIP-2 levels in A20myel-KO mice , the number of neutrophils ( CD11b+ Ly6C+ Ly6G+ F4/80− ) that were recruited in the bronchoalveolar spaces upon IAV infection was clearly higher throughout infection in A20myel-KO mice compared to control animals ( figure 3D ) . Although we could detect a significant increase in monocyte ( CD11b+ Ly6C+ ) recruitment at day 4 post infection , this was not evident at later time points after infection ( figure 3D ) , which is consistent with the equal expression of MCP-1 in both groups of mice . The number of resident alveolar macrophages ( autofluorescent+ CD11c+ F4/80+ CD11b− ) was also elevated in A20myel-KO mice but did not differ significantly between IAV infected or mock infected mice ( figure 3D ) . Elimination of IAV infected cells depends on the clonal expansion of virus specific cytotoxic CD8+ T cells ( CTL ) [61] , [62] , [63] . To test whether A20 expression in myeloid cells regulates the antiviral CTL response , total CD8+ T cells and virus specific Granzyme B ( GrB ) and IFNγ expressing CD8+ T cells were measured in BAL and lung parenchyma of wild type and A20myel-KO mice . A clear increase in CD8+ T cells could be detected at day 7 and 10 post infection , but no differences were observed between A20myel-KO and wild type mice ( figure S2A and figure S2C ) . Also , the number of GrB and IFNγ CD8+ T cells as well as IFNγ expression levels in the lungs were not altered by the absence of A20 in myeloid cells ( figure S2A–C ) . Protection against IAV infection is also provided by the humoral immune response . To test whether loss of A20 in myeloid cells affects B cell mediated immunity , we determined hemagglutinin ( HA ) antibody titers in the serum of A20myel-KO and wild type littermates . However , no differences could be detected between wild type and A20myel-KO animals ( figure S2D ) , indicating that humoral immunity is not affected by A20 expression in myeloid cells . Together , these data suggest that mechanisms other than adaptive immunity , such as an increased innate immune response , characterized by an increased influx of neutrophils and increased numbers of alveolar macrophages , contribute to the better viral clearance in A20myel-KO mice . It is generally believed that IAV-induced mortality is due to an excessive proinflammatory response in the lung . We therefore analyzed whether the increased proinflammatory cytokine production and infiltration of proinflammatory cells in A20myel-KO mice affects mortality induced by intranasal infection with a lethal dose of IAV X-47 . Surprisingly , almost all A20myel-KO mice survived ( 10/11 ) , while all control mice succumbed ( 0/11 ) within 16 days after infection ( figure 4A ) . A20myel-KO mice still showed significant weight loss and lung damage ( as reflected by increased total protein concentration in the BAL; data not shown ) during the course of infection but were able to recover , in contrast to wild type mice that succumbed ( figure 4B ) . Similar to our observations with sublethal IAV infection , pulmonary KC and MIP-2 production was stronger in A20myel-KO animals compared to wild type mice following lethal IAV infection ( figure 4C ) , which correlates with the increased numbers of neutrophils in the lungs of these mice ( figure 4C ) . Also levels of the proinflammatory cytokines IL-6 , TNF and IL-1β , which are often associated with immunopathogenesis in humans [64] , were increased in the lungs of A20myel-KO mice compared to control animals ( figure 4C and figure S3A ) . Again , MCP-1 production was not increased and even lower in A20myel-KO mice ( figure 4C ) , and also monocyte recruitment was not different between both groups of mice . We could also not detect any differences in viral clearance or antiviral adaptive immunity at 6 h post infection ( figure S3B–F ) . Collectively these data indicate that A20 deficiency in myeloid cells is associated with an increased innate immune response and protection against a lethal IAV infection .
In the present study we have investigated the contribution of A20 expression in myeloid cells in the innate immune response to IAV lung infection . In the pulmonary environment , macrophages populate both lung parenchyma and the alveolar lumen where they are referred to as alveolar macrophages . Under naïve conditions , alveolar macrophages exert important immunomodulatory functions [65] , [66] . However , alveolar macrophages are also crucial in the innate immune response against IAV as they are one of the first cells that encounter infectious IAV particles [67] , [68] . They are an important source of proinflammatory cytokines and chemokines that attract innate immune cells to the lung during the primary phase of infection [69] , and they are the primary producers of type I IFNs [70] . Alveolar macrophages are also known to phagocytose virus infected apoptotic cells and antibody coated viral particles , further contributing to viral clearance . We could show that BMDM or alveolar macrophages derived from A20myel-KO mice express higher amounts of chemokines , cytokines and type I IFNs compared to wild type mice in response to in vitro infection . Similarly , in vivo infection with IAV resulted in higher levels of primarily neutrophil attracting chemokines such as KC and MIP-2 and several proinflammatory cytokines such as IL-6 , TNF and IL-1β in the lungs of A20myel-KO mice compared to wild type mice . This was associated with a selective enhancement of neutrophil recruitment to the bronchoalveolar compartment , and resulted in improved viral clearance later on during infection . Although the role of neutrophils during viral infection is still under debate , recent evidence supports a protective function of these cells during IAV infection [71] , [72] . MCP-1 levels were not affected by the absence of A20 in myeloid cells , which is consistent with the notion that airway epithelial cells are the primary source of MCP-1 production during IAV infection [73] . Mice deficient for the MCP-1 receptor CCR2 , which is expressed on a subset of circulating monocytes , are protected against IAV infection and display reduced signs of immunopathology [74]–[76] . During IAV infection these monocytes develop into inflammatory dendritic cells or proinflammatory macrophages [77] and are considered major contributors to IAV-induced immunopathology [78] . A20myel-KO mice were protected against a lethal IAV infection , which is rather surprising since an excessive proinflammatory cytokine response and an excessive influx of inflammatory cells is generally believed to be associated with increased lethality [64] , [79] . However , the selective effect of A20 deficiency on neutrophil recruitment , without altering inflammatory monocyte ( Ly6C+ CD11b+ ) recruitment , further support the idea that monocytes and not neutrophils are major contributors to IAV-associated immunopathology and lethality [78] . We show that A20 deficient BMDM display enhanced NF-κB and IRF3 activation in response to RIG-I stimulation by synthetic LMW double stranded RNA . RIG-I has previously been shown to play a key role in the innate immune response to IAV [13] , suggesting that the increased immune response of A20myel-KO mice to IAV lung infection reflects enhanced RIG-I signaling . We propose that A20 inhibits IAV-induced proinflammatory gene expression ( as shown in our manuscript for TNF , IL-6 , KC , MIP-2 , and IFNβ ) by negatively regulating NF-κB and IRF3 activation , which are the major pathways controlling these genes . However , this does not exclude an additional effect of A20 on other signaling pathways that may contribute to proinflammatory gene expression . A20 is believed to exert its NF-κB and IRF3 inhibitory functions by modulating the ubiquitination status of different signaling proteins [80] . In this context , it was recently shown that A20 cooperates with the ubiquitin-binding proteins TAX1BP1 and ABIN1 to to disrupt the TRAF3-TBK1-IKKε complex , thereby negatively affecting K63-polyubiquitination of TBK1 and IKKε , and their ability to activity IRF3 [81] , [82] . Whether similar mechanisms are involved in the regulation of RIG-I induced NF-κB activation is still unclear . So far we were unable to clearly detect ubiquitination of TBK1 and IKKε in primary macrophages , preventing us from studying the effect of A20 deficiency on their ubiquitination status . It cannot be excluded however that A20 also targets other substrates that mediate NF-κB and IRF3 activation in myeloid cells . The identification of these substrates will be the topic of future investigations in our laboratory . Multiple other deubiquitinating enzymes ( DUBs ) , such as DUBA [28] , CYLD [29] , [30] , OTUB1/2 [31] , and A20 [49]–[52] have been shown to negatively regulate RIG-I signaling to NF-κB and IRF-3 , implicating possible redundancy . However , evidence so far was limited to in vitro data and was obtained under non-physiological conditions . The clear protective phenotype of A20myel-KO mice that we here describe indicates that A20 expression in myeloid cells is a central gatekeeper of RIG-I induced signaling in response to IAV infection and that other DUBs cannot substitute for A20 deficiency under physiological conditions . If A20 has a similar non-redundant role in other cell types that are implicated in the response to IAV , such as lung epithelial cells , remains to be investigated . Understanding and controlling the activation of innate antiviral immune responses is an important step toward novel therapies . About a fifth of world's population is infected by IAV annually , leading to high morbidity and mortality , particularly in infants , the elderly and the immunocompromised . The high mutation rate of IAV turns all attempts of vaccine and antiviral design into a never ending battle . In recent years , RNA interference , triggered by synthetic short interfering RNA ( siRNA ) , has rapidly evolved as a potent antiviral regimen . Properly designed siRNAs have been shown to function as potent inhibitors of influenza virus replication . Although specificity and tissue delivery remain major bottlenecks in the clinical applications of RNAi in general , intranasal application of siRNA against respiratory viruses including , but not limited to influenza virus , has experienced significant success and optimism [83] . Our results suggest that not only siRNA targeting IAV components , but boosting the antiviral immune response by intranasal administration of siRNA against A20 might be a valid therapeutic approach . Also small compound inhibitors of A20 might be an interesting alternative . Finally , similar targeting of A20 might be of interest in the battle against other viral infections including RSV and SARS coronavirus .
All experiments on mice were conducted according to the national ( Belgian Law 14/08/1986 and 22/12/2003 , Belgian Royal Decree 06/04/2010 ) and European ( EU Directives 2010/63/EU , 86/609/EEG ) animal regulations . Animal protocols were approved by the ethics committee of Ghent University ( permit number LA1400091 , approval ID 2010/001 ) . All efforts were made to ameliorate suffering of animals . Mice were anesthetized by intraperitoneal ( i . p . ) injection of a mixture of ketamine ( 12 mg/kg ) and xylazine ( 60 mg/kg ) . A20fl/fl mice were generated as previously described [56] . A20fl/fl mice were crossed with LysM-Cre mice [84] ( provided by I . Förster , Institute of Genetics , University of Cologne , Germany ) to generate A20fl/fl LysMCre transgenes and are described in detail elsewhere [48] . Mice were housed in individually ventilated cages at the VIB Department of Molecular Biomedical Research in specific pathogen-free animal facilities . Influenza infections were performed on age- ( between 7 and 9 weeks old ) and sex-matched littermates . A20fl/fl LysM-Cre animals were backcrossed three times to the C57Bl/6 background . A20fl/fl mice expressing or lacking the LysM-Cre transgene were termed A20myel-KO and wild type ( A20myel-WT ) respectively . Mouse adapted IAV X-47 ( H3N2; PR8×A/Victoria/3/75 ) was propagated in MDCK cells . For viral inoculation , mice were anesthetized by i . p . injection with ketamine ( 12 mg/kg ) and xylazine ( 60 mg/kg ) and 50 µl X-47 diluted in PBS was administered intranasally . For lethal and sublethal infection , mice received respectively 2-LD50 or 0 . 05-LD50 X-47 . To determine pulmonary viral titers , median tissue culture infectious dose ( TCID50 ) was measured as follows: lungs were homogenized with a Polytron homogenizer ( Kinematica ) in PBS . Eight-fold serial dilutions of lung homogenates were incubated on MDCK cells for 5 days in DMEM supplemented with trypsin ( 1 µg/ml ) , 2 mM L-glutamine , 0 . 4 mM sodium pyruvate and antibiotics . For read-out , 0 . 5% chicken red blood cells ( RBC ) were added and end-point dilution of hemagglutination was monitored . TCID50 titers were then calculated according to the method of Reed and Muench [85] . To determine the HAI titers in infected mice , sera of these were treated with receptor-destroying enzyme ( RDE/Cholera filtrate; Sigma ) to remove sialic acids from serum proteins capable of aspecific inhibition of agglutination . After incubation overnight at 37°C , the RDE was inactivated by addition of 0 . 75% sodium citrate in PBS and heating to 56°C for 30 min . To remove sialic acid binding proteins , sera were cleared with 1/10 volume 50% chicken RBC . Titration was done by incubating a two-fold dilution series of sera with 4 HA units of X-47 virus for 1 hour at room temperature in 96-well U-bottom plates . Finally , an equal volume of 0 . 5% chicken RBC was added and titers were read 30 min later . Negative controls included PBS instead of immune serum ( agglutination control ) or PR8 instead of X-47 virus ( control for agglutination effect of sera ) ; as positive control , serum from a mouse infected twice with a sublethal dose of X-47 was used . Granzyme B ( GrB ) and IFNγ expressing CD8+ T cells were determined by treating the mice intranasally with 50 µg Brefeldin A ( Sigma ) as previously described [86] . 6 h later , BAL and lungs were isolated and single cell suspensions were prepared from the lung in the presence of 3 µg/ml Brefeldin A . Cells were stained , fixed and permeabilized ( Cytofix/Cytoperm , BD Biosciences ) according to the manufacturer's instructions . Activated CD8+ T cells were analyzed by flow cytometry based on CD62lo CD3+ and CD8+ expression . Live/Dead fixable aqua dead cell stain kit ( Molecular Probes ) was used to discriminate live from dead cells . HEK293T and MDCK cells were grown in DMEM ( Gibco ) supplemented with 10% FCS , 2 mM L-glutamine , 0 . 4 mM sodium pyruvate and antibiotics . HEK293T cells were transfected using the calcium phosphate precipitate transfection method with specific expression vectors ( pCAGGS-E-hA20 ( LMBP 3778 ) , pCAGGS-E-RIG-I-CARD ( LMBP 6517 ) , pEF-HA-IRF-7 ( kindly provided by T . Taniguchi , Graduate School of Medicine and Faculty of Medicine , University of Tokyo ) ) , NF-κB , IRF3 , IRF7 reporter plasmids ( respectively pConLuc ( LMBP3248 ) , pISRE-luc ( LMBP4011 ) , pGL3-IFNα4-luc ( kindly provided by J . Hiscott , McGill University , Montreal , Quebec , Canada ) , and pACTbetagal ( LMBP4341 ) for transfection efficiency normalization . Details of plasmids are presented along with detailed sequence maps at the BCCM-LMBP plasmid databank http://bccm . belspo . be/index . php . For the generation of BMDM , bone marrow cells were cultured 7 days in RPMI 1640 ( Gibco ) supplemented with 10% FCS , 2 mM L-glutamine , 0 . 4 mM sodium pyruvate , antibiotics and 40 ng/ml recombinant M-CSF . BMDM were of ≥95% purity as measured by flow cytometry using F4/80 and CD11b specific antibodies . For the isolation of alveolar macrophages , the trachea was canulated and the lung was flushed 4 times with HBSS containing 1 mM EDTA . Alveolar macrophages were cultured in RPMI 1640 ( Gibco ) supplemented with 1% FCS , 2 mM L-glutamine , 0 . 4 mM sodium pyruvate and antibiotics . For total lysates , cells were lysed at 4°C for 15 min in lysis buffer ( 200 mM NaCl , 1% NP-40 , 10 mM Tris-HCl pH 7 . 5 , 5 mM EDTA , 2 mM DTT ) supplemented with protease and phosphatase inhibitors . Nuclear and cytoplasmic lysates were prepared by resuspending cells in B1 ( 10 mM Hepes pH 7 . 5 , 10 mM KCl , 1 mM MgCl2 , 5% glycerol , 0 . 5 mM EDTA and 0 . 1 mM EGTA supplemented with protease and phosphatase inhibitors ) for 15 min at 4°C . Next , NP-40 detergent was added to a final concentration of 0 . 65% and cells were centrifuged at 500 g for 5 min . The nuclear fraction containing pellet was lyzed in B2 ( 20 mM Hepes pH 7 . 5 , 1% NP-40 , 400 mM NaCl , 10 mM KCl , 1 mM MgCl2 , 20% glycerol , 0 . 5 mM EDTA and 0 . 1 mM EGTA supplemented with protease and phosphatase inhibitors ) for 15 min at 4°C . The lysates were subsequently separated by SDS-PAGE and analyzed by western blotting and ECL detection ( Perkin Elmer Life Sciences ) . Immunoblots were revealed with anti-A20 , anti-IκBα , anti-p65 , and anti-histon H1 ( Santa Cruz ) , anti-IRF3 ( Invitrogen ) , anti-phospho-IRF3 and anti-phospho-IκBα ( Cell Signaling ) and anti-actin ( MP Biomedicals ) . The density of the bands was quantified ( fold induction ) with the ImageJ ( http://rsbweb . nih . gov/ij ) Gel analyzer tool . All intensities were calculated relative to the first lane ( = time 0 ) . Lungs were dissected and incubated with collagenase type IV ( 1 mg/ml; Sigma ) and DNAse ( 100 U/ml; Roche ) at 37°C for 30 min . Subsequently , samples were filtered through a 70 µm and 40 µm nylon mesh . For the preparation of BAL , trachea were canulated and airway lumen was flushed 4 times with HBSS with 1 mM EDTA . Cells were stained with monoclonal antibodies directed against MHC-II ( I-A/I-E ) FITC ( M5/114 . 15 . 2 ) , CD11c PerCP-Cy5 . 5 ( N418 ) , F4/80 APC ( BM8 ) , CD62L PE ( MEL-14 ) , Granzyme B FITC ( NGZB ) from eBiosciences and CD3 Molecular Complex Horizon v450 ( 17A2 ) , Ly6C Horizon v450 ( AL-21 ) , Ly6G PE ( 1A8 ) , CD11b APC-Cy7 ( M1/70 ) , CD8α PerCP ( 53-6 . 7 ) , IFNγ Alexa 647 ( XMG1 . 2 ) and CD16/32 ( 2 . 4G2 ) from BD Pharmingen . Samples were acquired on a LSRII Cytometer and analyzed using FACSDiva software ( BD Biosciences ) . Propidium iodide was used to discriminate between live and dead cells . For TNF ELISA , 96-well plates were coated with TNF coating ( TN3-19 , eBioscience ) and detection ( R4-6A2 , eBioscience ) antibodies . IFNα and IFNβ protein levels were determined with an ELISA kit ( PBL Biomedical Laboratories ) . For IFNγ ELISA , 96-well plates were coated with IFNγ coating ( XMG1 . 2 ) and detection ( R4-6A2 ) antibodies ( eBiosciences ) . Detection of MCP-1 , KC , TNF , IL-1β and IL-6 in BAL fluid was performed using Bioplex ( BioRad ) technology according to the manufacturer's instructions . Milliplex technology ( Millipore ) was used for the detection of MIP-2 in BAL fluid . Total RNA was extracted using Aurum Total RNA mini kit ( BioRad ) and reverse transcribed into cDNA with iScript cDNA synthesis kit ( BioRad ) according to the manufacturer's instructions . qPCR was performed by using SYBR Green I master mix I ( Roche ) in the Lightcycler 480 detection system ( Roche ) with the following primers: HPRT: 5′-AGTGTTGGATACAGGCCAGAC-3′ and 5′CGTGATTCAAATCCCTGAAGT-3′; IL-6: 5′-GAGGATACCACTCCCAACAGACC-3′ and 5′-AAGTGCATCATCGTTGTTCATACA-3′; IFNβ: 5′-TCAGAATGAGTGGTGGTTGC-3′ and 5′-GACCTTTCAAATGCAGTAGATTCA-3′; A20: 5′-AAACCAATGGTGATGGAAACTG-3′ and 5′-GTTGTCCCATTCGTCATTCC-3′; CCL2: 5′-TTAAAAACCTGGATCGGAACCAA-3′ and 5′-GCATTAGCTTCAGATTTACGGGT-3′; CXCL1: 5′-GAGCCTCTAACCAGTTCCAG-3′ and 5′-TGAGTGTGGCTATGACTTCG-3′ and IFNα4: 5′-TGATGAGCTACTACTGGTCAGC-3′ and 5′-GATCTCTTAGCACAAGGATGGC-3′ . Primers were designed with PerlPrimer ( http://perlprimer . sourceforge . net ) . Quantification was performed using the comparative CT method ( ΔΔCT ) . Results are expressed relative to HPRT values . Results are expressed as the mean ± SEM . Statistical significance between groups was assessed using two-way ANOVA . The differences for in vivo experiments ( at least 5 mice per group ) were calculated using the Mann-Whitney U-test for unpaired data . Statistical significance of differences between survival rates was analyzed by comparing Kaplan-Meier curves using the log-rank test ( GraphPad Prism version 5 , GraphPad , San Diego , CA ) . | Influenza virus or flu epidemics represent a recurrent threat to the public health , especially for individuals which are part of a high-risk group such as children , elderly or immune-compromised people . Sporadic pandemic flu outbreaks , such as the Spanish flu of 1918 , may cause high grades of mortality among healthy persons . A better understanding of how the immune system deals with these pathogens is of key importance . The protein A20 is an important negative regulator of both innate and adaptive immune responses . We show that the specific deletion of A20 in myeloid cells , such as macrophages and neutrophils , improves the resistance against otherwise lethal influenza infections . This protective effect is mediated by an enhanced innate immune response following respiratory challenge with influenza virus . Although exaggerated pulmonary immune responses are believed to be the primary cause of often life threatening influenza virus induced pneumonia , we demonstrate that boosting the innate immune response by selectively targeting the functionality of A20 in myeloid cells is beneficial for the host survival . This finding provides us with a novel valuable approach for treating influenza and potentially other respiratory viral infections . | [
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"biology"
] | 2012 | A20 (Tnfaip3) Deficiency in Myeloid Cells Protects against Influenza A Virus Infection |
The immediate-early ( IE ) BZLF1 gene of Epstein-Barr virus ( EBV ) regulates the switch between latent and lytic infection by EBV . We previously showed that the cellular transcription factor ZEB1 binds to a sequence element , ZV , located at nt −17 to −12 relative to the transcription initiation site of the BZLF1 promoter , Zp , repressing transcription from Zp in a transient transfection assay . Here , we report the phenotype in the context of a whole EBV genome of a variant of EBV strain B95 . 8 containing a 2-bp substitution mutation in the ZV element of Zp that reduced , but did not eliminate , ZEB1 binding to Zp . Strikingly , epithelial 293 cells latently infected with the EBV ZV mutant spontaneously produced IE- , early- , and late-gene products and infectious virus , while wild-type ( WT ) -infected 293 cells did not and have never been reported to do so . Furthermore , treatment with the chemical inducers sodium butyrate and 12-O-tetradecanoyl-phorbol-13-acetate ( TPA ) led to an additional order-of-magnitude production of infectious virus in the ZV mutant–infected 293 cells , but still no virus in the WT-infected 293 cells . Similarly , ZV mutant–infected Burkitt's lymphoma BJAB cells accumulated at least 10-fold more EBV IE mRNAs than did WT-infected BJAB cells , with TPA or sodium butyrate treatment leading to an additional 5- to 10-fold accumulation of EBV IE mRNAs in the ZV mutant–infected cells . Thus , we conclude that ZEB1 binding to Zp plays a central role in regulating the latent-lytic switch in EBV-infected epithelial and B cells , suggesting ZEB1 as a target for lytic-induction therapies in EBV-associated malignancies .
Epstein-Barr virus ( EBV ) is a human gamma herpesvirus estimated to infect 90% of the world's population . It is a causative agent of or associated with infectious mononucleosis and several B-cell and epithelial-cell cancers including Burkitt's lymphoma ( BL ) , Hodgkin's disease , nasopharyngeal carcinoma , and some gastric carcinomas ( reviewed in [1] ) . EBV can infect and immortalize primary B lymphocytes , leading to a latent form of infection in which its genome is maintained as an episome replicating via its viral origin of replication , ori-P , in synchrony with its host cell's DNA . EBV can also infect epithelial cells , leading to a latent or lytic form of infection depending upon the specific cell type and state of cellular differentiation . Only a few of the ∼100 genes in EBV are expressed during latency unless reactivation occurs , leading to lytic replication with production of infectious virus ( reviewed in [2] ) . Understanding regulation of the switch between latency and lytic replication is a central problem in herpes virology . EBV provides an excellent system to address this problem . Reactivation of EBV out of latency is usually initiated via activating expression of the immediate-early ( IE ) BZLF1 gene [3] which encodes a sequence-specific DNA-binding protein , Zta ( also called Z , Zebra , and EB1 ) , a member of the bZIP family of leucine-zipper transactivators . The activities of Zta include directly participating in EBV replication via binding to the viral DNA origin of lytic replication , ori-Lyt , down-regulating the latency-associated promoters Cp and Wp , and serving as a transcriptional transactivator of its own promoter , other IE and early ( E ) viral promoters including the BRLF1 promoter , Rp , and several cellular promoters . The BRLF1 gene encodes a second viral transactivator , Rta ( also called R ) . Acting together , Zta and Rta play multiple roles in lytic replication of EBV . While highly quiescent during latency , expression of the BZLF1 promoter , Zp , can be activated in some cells by treatment with various inducers including phorbol esters such as 12-O-tetradecanoyl-phorbol-13-acetate ( TPA ) , calcium ionophores such as ionomycin , sodium butyrate , transforming growth factor β ( TGF-β ) and anti-immunoglobulins ( anti-Igs ) ( reviewed in [4] ) . Transcription of the BZLF1 gene can be initiated from either its proximal promoter , Zp , or the more distal promoter , Rp . However , most Zta protein is synthesized from mRNA initiated at Zp . The cis-acting elements of Zp sufficient for both basal and induced activity lie within the nucleotide ( nt ) −221 to +12 region relative to the promoter's transcription initiation site ( reviewed in [4 , 5] ) ( Figure 1 ) . Four AT-rich motifs , named ZIA through ZID , can bind the transcription factors Sp1 , Sp3 , and the myocyte enhancer factor 2D ( MEF2D ) [6 , 7] . ZII is a CRE-like motif that binds CREB , ATF family members , C/EBPs , and the AP-1 family of transcription factors [8–11] . ZIII contains multiple binding sites for the Zta protein itself [12] . Binding sites in Zp for Smads have also been identified [13] . Three elements involved in transcriptional silencing have also been identified within the nt −221 to +12 region of Zp: ZIIR [14] , HIɛ [15] , and ZV [16] . Other silencing elements , termed ZIV [17] and HIα-HIδ [15] , lie within the nt −551 to −222 region of Zp . We have identified ZEB1 ( also called δEF1 , TCF8 , AREB6 , ZFHEP , NIL-2A , ZFHX1A , and BZP ) as the main cellular factor in B-lymphocytes repressing transcription from Zp via binding the ZV element [18] . While repressors that recognize silencing elements upstream of nt −221 have been identified [19 , 20] , ZEB1 and MEF2D are the only ones known to bind functionally within the nt −221 to +12 region of Zp . Here , we report the effects of a 2-bp substitution mutation in the Zp ZV element in the context of a whole EBV genome . Quite strikingly , this ZV mutant ( mt ) of EBV spontaneously reactivated out of latently infected human epithelial 293 cells into lytic replication with production of infectious virus under conditions in which its WT parental virus never does . Burkitt's lymphoma BJAB cells latently infected with the ZV mutant also exhibited spontaneous synthesis of Zta mRNA under culture conditions in which WT-infected BJAB cells did not . Furthermore , treatment of the ZV mutant-infected BJAB cells with TPA led to high-level synthesis of Zta and Rta mRNAs while these IE viral genes remained silent in the WT-infected BJAB cells . Others have previously reported that ZEB1 is also a transcriptional repressor of the cellular E-cadherin promoter [21] , with reduction in E-cadherin expression linked to tumor invasion , metastasis , and unfavorable prognosis [22] . ZEB1 represses by functioning as a molecular beacon for recruitment to promoters of CoREST-CtBP co-repressor complexes [23] . Taken together , we conclude that ZEB1 plays a central role in maintaining EBV infection in a latent form in both epithelial and B cells and , thus , is an excellent target for lytic-induction therapy for EBV-associated malignancies .
Substitution mutations in the Zp ZV element of either ( i ) A to C at nt −12 or ( ii ) A to C at nt −12 plus T to C at nt −13 relative to the Zp transcription initiation site were shown previously to partially relieve both ( i ) binding of ZEB1 and ( ii ) repression of Zp by ZEB1 in transient transfection assays [16 , 18] and mini-EBV replicons [24] . To examine the role of the Zp ZV element in establishing and maintaining EBV in a latent form of infection , we introduced this −12C , −13C 2-bp substitution mutation in the ZV element ( ZVmt ) into an intact EBV genome using a bacmid , p2089 . Plasmid p2089 contains a wild-type copy of the complete genome of the B95 . 8 strain of EBV along with a mini F plasmid and expression cassettes for hygromycin phosphotransferase , green fluorescence protein ( GFP ) , and chloramphenicol acetyl transferase [25] . The parental p2089-WT and two completely independent isolates of p2089-ZVmt were transfected in parallel into 293 cells , and the cells were grown thereafter in the presence of hygromycin . Numerous hygromycin-resistant , GFP-positive colonies were visible within 3–4 weeks after transfection with either p2089-WT or p2089-ZVmt . Independent clones of latently infected cells were grown out into cell lines . Virus stocks of WT and ZVmt EBV were generated by co-transfection of these cell lines with pCMV-BZLF1 and p2670 , plasmids expressing the EBV-encoded proteins Zta and glycoprotein 110 , respectively , to induce lytic replication and production of infectious virus [26] . The titers of these virus stocks were determined by a Raji cell assay [27] . Multiple independent cell lines containing p2089-WT or p2089-ZVmt which consistently yielded infectious virus with titers of 104 to 105 green Raji units ( GRUs ) per ml of medium following induction were chosen for further analysis . To determine whether extraneous mutations might have arisen during either construction of the mutant plasmid or establishment and passage of the cell lines , p2089 DNA was extracted from each cell line . First , the nt −600 to +500 region of the BZLF1 gene in each plasmid was PCR-amplified and resequenced to make sure no extraneous mutations were present in the promoter region of this gene; only the expected −12C , −13C substitution mutations were observed . Second , Southern blot analyses of BamHI-digested plasmid DNA were performed with a variety of EBV DNA probes; no gross alterations in the EBV genomes were observed ( e . g . , Figure 2A; data not shown ) . The p2089 DNAs rescued from these cell lines were also digested with EcoRI , SalI , and HindIII restriction endonuclease; again , no differences were observed in any of the restriction fragment digestion patterns compared to those of the original p2089 DNA ( data not shown ) . Third , we also constructed a WT revertant , p2089-ZVmtRev , by introducing back into p2089-ZVmt DNA the original −12A and −13T sequence of Zp and isolated and extensively characterized three independent 293 cell lines latently infected with p2089-ZVmtRev . The phenotype of this revertant was found to be indistinguishable from that of the original p2089-WT in all assays performed on the latently infected 293 cells ( see below ) . Thus , the EBV genomes present in these cell lines probably do not differ in any significant way from the B95 . 8 strain of EBV except for the 2-bp substitution mutation in the ZV element of Zp . Three independent lines each of WT- , ZVmt- , and ZVmtRev-infected 293 cells were chosen for further detailed study . Two of the ZVmt-infected 293 cell lines were grown out from independent clones derived from cells transfected with one isolate of p2089-ZVmt DNA; the third was derived from cells transfected with p2089-ZVmt DNA obtained from a second , completely independent mutagenesis of p2089-WT DNA . Likewise , one of the three WT-infected 293 cell lines was the one originally described by Hammerschmidt and colleagues [25] . The other two were independent clones isolated from 293 cells transfected by us with p2089-WT DNA processed in parallel with the p2089-ZVmt DNAs constructed here . 293 cells latently infected with the B95 . 8 strain of EBV never spontaneously produce infectious virus because expression of the BZLF1 and BRLF1 genes is strongly repressed [28] ( M . Altmann and W . Hammerschmidt , personal communication ) . Only one laboratory has reported observing WT-infected 293 cells spontaneously producing EBV [29]; even in this case , only 2% of over 250 clones examined produced any EBV , and the cells had been infected with the Akata strain of EBV , not the B95 . 8 strain . As expected , we , too , failed to detect expression of the EBV IE , E , or late ( L ) genes in any of our WT-infected 293 cell lines ( Figures 2B , 2C , and 3 ) . Strikingly , both Zta and Rta mRNAs were readily detected in all three ZVmt-infected 293 cell lines , present at levels at least 20-fold higher than in the WT-infected 293 cell lines ( Figure 2B , lanes 4–6 vs . lanes 1–3 ) . Immunoblot analyses confirmed expression of the IE genes , with each of the ZVmt-infected cell lines containing at least 30-fold more Zta , Rta , and BMRF1 protein than the WT- and ZVmtRev-infected cell lines ( Figure 2C , lanes 5–7 vs . lanes 2–4 and lanes 8–10 ) . BMRF1 , an EBV E gene product , is only synthesized after Zta and Rta are present at sufficient levels to induce the later stages of the EBV lytic replication cycle . Immunofluorescence staining confirmed that Zta , Rta , and BMRF1 proteins were abundantly present in approximately 3% of the cells adhering to the dishes in each of the these three ZVmt-infected cell lines ( Figure 3; data not shown ) . IFS also indicated the presence of gp350 , a glycoprotein encoded by a late gene of EBV , in ∼1% of the cells ( Figure 3; data not shown ) . Likely , once any ZVmt-infected cell expressed Zta at a level detectable in our IFS assay , it was destined to proceed on through the entire EBV lytic cycle of replication , eventually dying , detaching from the dish , and , thus , no longer being measured in our assay; we observed only one-third as many gp350-positive cells as Zta-positive cells because the former had fewer hours remaining before they detached from the dish . Our finding 3% Zta-positive cells is not a measurement of the percent of these mutant-infected cells able to reactivate; rather , it indicates these cells were spontaneously reactivating at a rate of ∼1% per day if one assumes the time from reactivation of the BZLF1 promoter to cell death was ∼3 days . In contrast , we failed to detect any Zta- , Rta- , BMRF1- , or gp350-positive cells in any of the three WT-infected and three ZVmtRev-infected cell lines ( Figure 3; data not shown ) . Thus , the 2-bp substitution mutation in the ZV element of Zp led to greatly increased expression of IE , E , and L genes of EBV in 293 cells . Therefore , we conclude that ZV mutant-infected 293 cells spontaneously reactivate into lytic replication under culture conditions in which 293 cells infected with the WT B95 . 8 strain of EBV have never been reported to do so . We also assayed the cell lines for production of infectious virus . Strikingly , all three ZVmt-infected cell lines spontaneously produced at least 102 green Raji units ( GRUs ) per ml of medium ( Figure 4A; Table 1 ) . As expected , infectious virus was not detected in any of the three WT-infected and three ZVmtRev-infected cell lines unless the cells were transfected with an expression plasmid encoding Zta or Rta protein ( e . g . , Figure 4A and Table 1; data not shown ) . To confirm that the results observed with the Raji cell assay were truly due to encapsidation of replicated viral DNA into infectious virion particles , we also examined the termini of the EBV genomes present in these cell lines . When EBV exists solely in a latent state as a circular episome , the ends of its linear viral genome are fused together; cleavage with BamH1 restriction endonuclease generates large terminal EBV DNA fragments , somewhat heterogenous in size due to variability in the number of copies of a tandem repeated sequence present in this region of the EBV genome [30] . However , in lytically infected cells in which the EBV DNA has been linearized during packaging into virion particles , cleavage with BamH1 generates smaller terminal EBV DNA fragments , also heterogeneous in size . As expected , the EBV DNA terminal BamHI fragments isolated from the ZVmt-infected cell lines had sizes consistent with the presence of both circular and linear EBV genomes ( e . g . , Figure 4B; data not shown ) ; no small EBV DNA terminal fragments were detected with the DNA isolated from the WT-infected cell lines ( e . g . , Figure 4B; data not shown ) . Therefore , we conclude that presence of the 2-bp mutation in the Zp ZV element led not only to derepression of Zp , but also to the entire subsequent series of events in the EBV lytic replication cycle necessary for production of infectious virus . Transfection of cells with a Zta expression plasmid is the standard method for reactivating EBV-infected 293 cells into lytic replication for virus production [3] ( Table 1 ) . Exogenous expression of Rta can also reactivate EBV out of latency in some cell lines [31 , 32] . To determine whether ZVmt-infected 293 cells might be more susceptible to Rta induction than WT-infected ones because of partial derepression of Zp , we transfected them in parallel with a weak Rta expression plasmid , pEBV-RIE [31] . Both the WT- and ZVmt-infected 293 cell lines produced infectious virus following exogenous addition of Rta ( Table 1 ) . However , the virus titers obtained from the three ZVmt-infected cell lines were approximately 20-fold higher than they were from the three WT-infected cell lines . Immunoblot analysis indicated that these pEBV-RIE-transfected cells contained similar levels of Rta protein ( data not shown ) . Thus , the significant difference in virus production was probably due to differences in endogenous expression of the BZLF1 gene given that Zta and Rta function together in reactivation to lytic replication [33] . TPA and sodium butyrate are two well-known chemical inducers of latently infected B-lymphocytes . However , their presence , either individually or in combination , is not sufficient to reactivate the EBV B95 . 8 strain out of latency in 293 cells ( M . Altmann and W . Hammerschmidt , personal communication; Table 1 ) . Nevertheless , treatment of the ZVmt-infected 293 cell lines with these two chemicals in combination led to an additional ∼10-fold increase in production of infectious virus over the spontaneous rate observed with these cell lines ( Table 1 ) . Therefore , these two inducers synergized with the ZV mutation to yield a significantly higher frequency of reactivation of EBV than any of these three factors could accomplish by themselves or pairwise . Thus , TPA and sodium butyrate are probably primarily affecting positive and negative regulatory factors other than ZEB1 that also play roles in regulating Zp activity ( e . g . , c-Jun , MEF2D ) . Reduction in ZEB1 binding to Zp , in combination with changes in these other regulators , is necessary to efficiently reactivate EBV to lytic replication in 293 cells . However , ZEB1 is a key , essential regulator since the ZV mutation , by itself , led to some reactivation , while treatment with TPA plus butyrate failed to lead to any virus production in WT-infected 293 cells . BJAB is a human Burkitt's lymphoma cell line that can be efficiently infected by the B95 . 8 strain , with the EBV genome usually maintained as an episome [34 , 35] . To study whether our 2-bp substitution mutation in the ZV element also led to derepression of Zp in B-cells , we infected BJAB cells in parallel with WT and ZVmt virus . Hygromycin-resistant , GFP-positive clones were isolated and grown into cell lines . EBV DNA was isolated from each cell line and tested as described above by Southern blot analyses for ( i ) maintenance as an episome , ( ii ) average copy number per cell , and ( iii ) absence of gross sequence rearrangements ( Figure 5A; data not shown ) . Two independent lines each of WT- and ZVmt-infected BJAB cells with similar episomal copy number were selected for further study . As observed in 293 cells , the ZVmt-infected BJAB cell lines accumulated at least 10-fold more Zta mRNA than the WT-infected ones ( Figure 5B , lanes 2 and 4 vs . lanes 1 and 3 ) . Treatment of the mutant-infected cells with either TPA or sodium butyrate led to an additional 5- to 10-fold accumulation of Zta mRNA; treatment in combination led to a synergetic , 15- to 20-fold increase in accumulation ( Figure 5C , lanes 5–8 ) . On the other hand , treatment of the WT-infected BJAB cells with either TPA or sodium butyrate did not significantly affect accumulation of Zta mRNA; rather , significant activation of the WT promoter was only observed when these cells were treated concurrently with both inducers ( Figure 5C , lane 4 vs . lanes 1–3 ) . Immunofluorescence staining showed that Zta-positive and Rta-positive cells were readily detectable in the ZVmt-infected BJAB cell lines with or without TPA treatment , but not in the WT-infected BJAB cell lines ( Figure 5D; Table 2 ) . Synthesis of Zta protein in the ZVmt-infected BJAB cells led to derepression of Rp , with significant synthesis of both Rta mRNA ( Figure 5C , lane 1 vs . lane 5 ) and protein ( Figure 5D ) as well . Nevertheless , we failed to detect linear EBV DNA termini indicative of packaging of replicated viral DNA into virion particles in the ZVmt-infected BJAB cell lines ( Figure 5A ) . However , given that neither over-expression of Zta nor treatment with chemical inducers leads to lytic replication in WT-infected BJAB cells [35] , failure of the ZVmt-infected BJAB cells to undergo a complete lytic cycle of infection was expected . Regardless , we conclude that the 2-bp substitution mutation in the ZV element led to significant derepression of Zp in B-lymphocytic BJAB cells , with the ZVmt-infected BJAB cells being significantly more susceptible to additional induction of Zp by TPA and sodium butyrate than the WT-infected BJAB cells . These findings are very similar to the ones obtained with the WT- versus ZVmt-infected 293 cell lines ( Figures 2 and 3; Table 1 ) . We performed quantitative chromatin immunoprecipitation ( ChIP ) assays to test directly whether ZEB1 is associated with Zp via the ZV element in 293 cells latently infected with EBV . Chromatin was isolated from formaldehyde-fixed 293 , WT-infected 293 , ZVmt-infected 293 , and 293 cells infected with the wild-type revertant of the ZV mutant , ZVmtRev . The chromatin was sheared by sonication to fragments with an average length of ∼500 bp , and subjected to immunoprecipitation with a ZEB1-specific antibody . DNA extracted from the precipitated chromatin was used as template for quantitative PCR amplification with a pair of primers specific for Zp . As positive and negative controls , the PCR amplification was also performed with pairs of primers specific for ( i ) Rp , which also contains a ZEB1-binding site [18] , ( ii ) the interleukin 2 promoter ( IL-2p ) , a cellular promoter with a known ZEB1-binding site [36] , and ( iii ) an EBV sequence located 4 . 8-kbp upstream of the Zp transcription initiation site . The ZV mutant exhibited a 2- to 3-fold reduction in ZEB1 binding to Zp compared with the parental WT and the revertant , i . e . , the 2-bp mutation reduced but did not abolish ZEB1 binding ( Figure 6A , lane 3 vs . lanes 2 and 4; see Figure 6B for quantitation ) . This finding was expected given our recent identification of a second consensus ZEB1-binding element in Zp , named ZV' , located at nt +5 through +10 relative to the Zp transcription initiation site ( Figure 1A; Yu , Wang , and Mertz , unpublished data ) . Also as expected , the ZV mutation had no effect on binding of ZEB1 to either Rp or IL-2p ( Figure 6A , lane 3 vs . lanes 2 and 4; Figure 6B ) , and the assay was specific for ZEB1 antibody ( Figure 6D ) and DNA containing a ZEB1-binding site ( Figure 6E ) . Thus , we conclude that the ZV element of Zp is a functional ZEB1-binding site . When ZEB1 is present in cells , it binds concurrently with very high affinity to both the ZV and ZV' elements of Zp via its two zinc-finger domains [37] , thereby maximally silencing expression of the BZLF1 gene to ensure latency is maintained . Mutation of the ZV element weakens binding of ZEB1 to Zp , enabling occasional transcription initiation from Zp and , thus , synthesis of Zta mRNA and protein , leading to reactivation and the subsequent cascade of events that result in lytic replication with synthesis of infectious virions .
We examined here the effects of mutating the ZV element of Zp on maintaining latency and reactivating EBV in epithelial and BL cell lines . This is the first report of a systematic analysis of the role of a cis-acting transcriptional regulatory element of EBV within the context of a whole genome . We show that a 2-bp substitution mutation in the ZV element can have dramatic effects on the EBV life cycle . While this particular ZV mutant established latency in epithelial 293 cells at a frequency similar to WT EBV , it was defective in maintaining this latency . All three of the ZV mutant-infected cell lines we examined in detail spontaneously synthesized Zta mRNA and protein at levels sufficient to reactivate the virus into its lytic cycle , with synthesis of Rta , early proteins including BMRF1 , late proteins including gp350 , linear viral genomes , and infectious virus ( Figures 2–4; Table 1 ) . Neither we nor anyone else to the best of our knowledge has ever observed spontaneous reactivation of the WT B95 . 8 strain of EBV in laboratory-infected 293 cells . We also did not observe any spontaneous reactivation in 293 cells infected with the WT revertant of the ZV mutant ( Figure 2C; data not shown ) . Strikingly , the ZV mutant-infected cell lines were also more susceptible to induction by either ( i ) over-expression of Rta , or ( ii ) treatment with TPA and sodium butyrate ( Tables 1 and 2; Figure 5C ) . Quite likely , the phenotype of the ZEB1-binding site mutant would have been even more dramatic if the ZV element mutation had been combined with a ZV' element mutation to further reduce or completely eliminate ZEB1 binding to Zp . Furthermore , preliminary data indicate that the ZV mutant virus is at least an order-of-magnitude defective relative to WT EBV in establishing colonies of proliferating lymphocytic cells following infection of primary human B cells ( Yu and Mertz , unpublished data ) . Thus , we conclude that the ZV element is a key component of Zp , playing a central role in regulating the switch in the EBV life cycle between latency and lytic replication . We have recently published in collaboration with the Kenney laboratory that exogenous addition of ZEB1 represses Zp activity from both a Zp reporter plasmid and whole EBV genomes in gastric carcinoma ZEB1-negative AGS cells that are normally highly lytic for EBV [38] . Taken together with previously published data showing that numerous different mutations in the ZV element exhibit a similar effect on Zp activity in a transient transfection reporter assay [16 , 18] , this finding provides strong evidence that the phenotype of the ZV mutant studied here is , indeed , due to it altering ZEB1 binding rather than fortuitously creating a binding site for another transcription factor . Our finding that the ZV mutant can establish a latent form of infection in 293 cells rather than being a constitutive lytic mutant suggests that , although the ZEB1-binding ZV element is a physiologically important silencer of Zp , other negative regulatory elements ( e . g . , ZEB1-binding ZV' element , MEF2D-binding ZI elements , ZIIR element [14] ) also contribute to the very tight repression of Zp observed in 293 cells . In addition , for efficient reactivation of EBV from latency into lytic replication , positive transcriptional regulatory factors ( e . g . , ZII-binding proteins such as ATFs , CREBs , and AP-1 ) are required as well . Thus , while ZEB1 binding to Zp plays a central role in regulating EBV's switch between latency and lytic replication , it functions in coordination with other cellular regulators of Zp to determine whether the BZLF1 gene is expressed in a specific cell type under specific growth conditions . Consistent with this conclusion , we have recently published in collaboration with the Kenney laboratory data that indicate the following: ( i ) ZEB1 levels range from very high to moderate to absent among a variety of epithelial and B-cell types that are physiologically relevant to EBV; ( ii ) The correlation between ZEB1 abundance and whether infection by EBV is latent or lytic is fairly good , but far from perfect; and ( iii ) The abundance of activated c-Jun also contributes to how a cell responds to EBV infection [38] . In addition , loss of Zp repression via ZEB1 binding to the ZV/ZV' elements might also occur via changes in ZEB1 interactions with cellular co-regulators leading to ZEB1 , itself , switching from a repressor binding CtBPs to an activator binding Smads , p300 , and other co-activators [39] . Sodium butyrate inhibits the activity of histone deacetylase complexes ( HDACs ) , leading to acetylation of histone proteins and , subsequently , promoters becoming more accessible to transcriptional activators and the cellular transcription machinery [40] . TPA is a multi-functional inducer . It activates the cellular protein kinase C pathway in B cells [41] , inducing phosphorylation of Zta protein [42] which can then activate Rp [43] leading to synthesis of Rta protein and subsequent activation of Zp [44] . Nevertheless , treatment of WT-infected 293 cell lines with TPA plus sodium butyrate fails to induce reactivation of EBV ( e . g . , Table 1 ) . In contrast , identical treatment of the ZVmt-infected 293 cell lines led to a 10-fold increase in virus production above that observed spontaneously ( Table 1 ) . Thus , high-affinity binding of ZEB1 to the ZV/ZV' elements of Zp directly over the transcription initiation site is sufficient to maintain repression of the BZLF1 gene expression in 293 cells even when inducers make Zp much more accessible to its positive regulators . With the 2-bp mutation in the ZV element studied here partially alleviating binding of ZEB1 to Zp ( Figure 6 ) , the addition of these inducers increased the probability that transcription from Zp would reach the threshold level at which Zta protein was produced in sufficient quantity to irreversibly activate transcription from Zp and Rp , leading to full-blown reactivation with lytic replication . Binding of ZEB1 to Zp was also found to be important in B cells . Zp expression was tightly repressed and not inducible by either TPA or sodium butyrate in the WT-infected B-lymphocytic BJAB cells . Only treatment of the WT-infected BJAB cells with both inducers in combination led to significant accumulation of Zta mRNA ( Figure 5C ) . On the other hand , Zp was spontaneously expressed in the ZV mutant-infected BJAB cells . Moreover , either TPA or sodium butyrate was sufficient to further activate Zp expression , with significant accumulation of Rta as well as Zta mRNA , presumably due to Zta protein activating Rp expression . Unfortunately , since BJAB cells do not support EBV late gene expression and viral DNA replication , up-regulation of Zp and Rp in the mutant-infected BJAB cells did not lead to production of infectious virus . Nevertheless , our recent preliminary finding that the ZV mutant virus is at least an order-of-magnitude defective relative to the parental WT EBV in establishing colonies of proliferating lymphocytic cells following infection of primary human B cells ( Yu and Mertz , unpublished data ) provides strong evidence that ZEB1 binding to the ZV element of Zp is , indeed , important for establishing a stable latent infection in B cells as well as epithelial cells . We found that the ZV mutant exhibited only a 2- to 3-fold reduction in ZEB1 binding to Zp ( Figure 6 ) , yet a 20-fold or more increase in accumulation of Zta mRNA and protein ( Figures 2 and 5 ) . These two sets of data are quite compatible given the fact that a small initial increase in expression of the BZLF1 gene in the context of cells infected with whole EBV genomes can lead to a large change in expression because Zta protein activates expression of the BRLF1 gene , with the Rta protein then up-regulating BZLF1 gene expression to high levels . These findings also provide an explanation for why we chronically observe a small percentage of the ZVmt-infected 293 cells to have spontaneously reactivated into full-blown EBV lytic replication while most of the cells in the population still score as Zta-negative in our IFS assay ( Figure 3 ) , i . e . , once a cell manages to synthesize Zta mRNA and protein above a critical threshold level , it irreversibly switches into the lytic cycle . On the other hand , transcription of Zp remains tightly repressed in the WT-infected 293 cells , with infectious virus never produced without exogenous addition of Zta or Rta ( e . g . , Table 1 ) . Amon et al . [45] noted little difference by immunoblot analysis between wild-type and the 2-bp ZV mutant of Zp studied here in BZLF1 gene expression before versus after anti-Ig induction in Akata cells . This seeming discrepancy with our results could be due to epigenetic ( e . g . , methylation status of Zp ) or structural ( e . g . , Zp's distance from OriP ) differences between the p2089 bacmid used by us and the mini-EBV plasmid used in their study . Alternatively , their use of more sensitive assays ( e . g . , qRT-PCR , different method for extraction and detection of Zta protein ) likely would have revealed that the ZV mutant actually did over-express Zp , leading to higher accumulation of Zta mRNA and protein at earlier times after anti-Ig induction , consistent with the large difference in Zp expression they had reported earlier between wild-type and the ZV mutant using a luciferase reporter assay [24] . In summary , we show that a mere 2-bp substitution mutation in the ZEB1-binding site in Zp in the context of a whole EBV genome can lead to expression of EBV IE , E , and L genes and production of infectious virus under conditions in which the B95 . 8 strain of WT EBV has never been observed to reactivate out of latency . Given this finding , we speculate that loss of ZEB1 binding to Zp as a repressor by ( i ) mutation of the ZV' as well as the ZV element of Zp , ( ii ) knock down of synthesis of ZEB1 in the host cell , or ( iii ) switching ZEB1 from a repressor to activator of transcription ( e . g . , via TGF-β signaling of Smads [39] ) could lead to efficient reactivation into lytic EBV replication in latently infected cells , especially if combined with loss as well of other repressors of BZLF1 gene expression ( e . g . , MEF2D , the ZIIR element-binding protein ) and activation of transcriptional activators ( e . g . , c-Jun ) . Thus , ZEB1 is a novel candidate target for lytic-induction therapies for some EBV-associated malignancies [46] . In addition , an EBV strain containing mutations in the ZV/ZV' elements in combination with a mutation in another negative regulatory element of Zp ( e . g . , ZIIR ) may provide the basis for development of a constitutively lytic strain of EBV that could serve as a vaccine for immunization against EBV infection .
293 , a human embryonic kidney cell line , was obtained from W . Hammerschmidt . Raji and BJAB are EBV-positive and -negative human BL cell lines , respectively . They were maintained at 37 °C in RPMI1640 medium supplemented with 10% fetal bovine serum ( FBS ) . Plasmid pCMV-BZLF1 [47] , encoding Zta protein , and plasmid p154 . 13 , containing nt ∼101 , 000 through ∼113 , 000 of EBV strain B95 . 8 , were obtained from B . Sugden . Plasmid p2089 [25] , containing the complete genome of EBV B95 . 8 strain , and plasmid p2670 [26] , encoding EBV glycoprotein gp110 , were obtained from W . Hammerschmidt . Plasmid pGS284 , containing an ampicillin cassette and the levansucrase gene for positive and negative selection , respectively , and E . coli strains GS500 ( RecA+ ) and S17λpir [48] were provided by S . Speck . Plasmid pEBV-RIE [31] , encoding Rta protein , was obtained from S . Kenney . Plasmids containing the XhoI and EcoRI subfragments of EBV for termini assays were provided by N . Raab-Traub [30] . The 2-bp substitution mutation , ZVmt , was introduced into the Zp ZV element in p2089 by allelic exchange in E . coli as described by Smith and Enquist [49] and Moorman et al . [48] . Briefly , the mutation was generated by a two-step , PCR-based site-directed mutagenesis of plasmid p154 . 13 . A 1 , 100-bp EBV DNA fragment containing the mutated ZV element near its center was cloned into pGS284 and transformed into S17λpir by electroporation ( Bio-Rad ) . Plasmid p2089 was transformed by electroporation into GS500 . The resulting S17λpir and GS500 cells were mated . Integration of pGS284 into p2089 and its subsequent excision via homologous recombination were sequentially selected using the markers present in these two plasmids . PCR screening indicated 5% of the p2089 revertants had lost the WT Zp and retained the ZVmt one . The desired mutation in p2089 and nowhere else throughout the entire BZLF1 promoter region was confirmed by DNA sequence analysis . The p2089-ZVmt clones were also digested with a variety of restriction enzymes including EcoRI , BamH1 , HindIII , and SaII . Only ones with digestion patterns identical to the parental p2089 were retained . A wild-type revertant of p2089-ZVmt , p2089-ZVmtRev , was constructed by mutagenesis of p2089-ZVmt and thoroughly characterized likewise . The p2089-WT and p2089-ZVmt DNAs were purified by equilibrium centrifugation in CsCl-ethidium bromide gradients , introduced into 293 cells with Lipofectamine 2 , 000 ( Invitrogen ) , and selected by incubation in the presence of 100 μg/ml hygromycin as described by Neuhierl et al . [26] . GFP-positive colonies were picked 4- to 6-weeks later and grown into cell lines . To make virus stocks , these EBV-infected cells were co-transfected with pCMV-BZLF1 ( 5 μg/100-mm dish ) and p2670 ( 5 μg/100-mm dish ) using Lipofectamine 2000 . The culture medium was harvested 72 h later , passed through a 0 . 8-μm filter , and stored at 4 °C . BJAB cells were infected with WT and ZV mutant virus stocks at a multiplicity of infection of 0 . 1 GRUs per cell as described by Marchini et al . [35] , plated at 100 cells per well in 96-well plates , and grown in the presence of 300 μg/ml hygromycin until GFP-positive colonies emerged . The EBV genomes in each of the numerous 293 and BJAB cell lines were extensively characterized by DNA sequence analysis of the entire BZLF1 promoter region and restriction fragment patterns as described above . Whole-cell polyadenylated RNA was isolated with oligo ( dT ) cellulose [50] . In Figure 5C , mRNA was harvested after incubation of the cells with TPA and sodium butyrate for 48 h . Northern blot analysis was performed as previously described [51] . Radiolabeled probes were prepared using a random primer labeling system ( Amersham ) . A 311-bp fragment from nt +8 to +318 relative to the Zp transcription initiation site , generated by PCR , was used as template for making the probe for detection of both Zta and Rta mRNAs . A 177-bp human β-actin fragment [52] , a gift from S . Guang , was used as template for making a β-actin probe . Southern blot analysis was performed as previously described [53] . The p2089 DNA was digested with BamHI prior to electrophoresis in a 0 . 8% agarose gel . Plasmid p154 . 13 was used as template for making a probe that detects EBV's BamHI fragments Z , R , K , and B . EBV termini assays were performed as previously described [30] . To detect Zta , Rta , and BMRF1 proteins by immunoblotting , cells in 100-mm dishes were lysed in SUMO lysis buffer [54] . EBV proteins were separated by SDS-12% PAGE and detected by incubation with monoclonal anti-Zta ( Argene , 1:200 dilution ) , anti-Rta ( Argene , 1:100 dilution ) , anti-BMRF1 ( Capricorn , 1:100 dilution ) , or anti-β-actin ( Sigma , 1:5000 dilution ) antibodies , followed by incubation with goat anti-mouse IgG horseradish-conjugated secondary antibody ( Pierce , 1:5 , 000 dilution ) . The bound secondary antibody was visualized using a chemiluminescence kit ( Roche ) . For IFS , the cells were fixed with methanol:acetone ( 1:1 ) for 10 min at room temperature , pre-incubated with phosphate-buffered saline ( PBS ) containing 20% FBS , incubated with monoclonal anti-Zta ( 1:40 dilution ) , anti-Rta ( 1:40 dilution ) , anti-BMRF1 ( 1:40 dilution ) , or anti-gp350 ( Chemicon , 1:100 dilution ) antibody , washed with PBS , incubated with a Texas Red-conjugated , anti-mouse IgG secondary antibody ( Jackson Laboratories , 1:100 ) , washed with PBS , embedded in mounting medium ( Vector Laboratories ) , and examined with a fluorescence microscope ( Zeiss ) . To assay for spontaneous reactivation , latently infected 293 cells were plated in 100-mm dishes and incubated for 3 days until ∼80% confluent . The medium was harvested , passing through a 0 . 8-mm filter , and adjusted to 8 ml total volume . For chemical induction , the cells were incubated for 48 h with TPA ( 20 ng/ml ) , sodium butyrate ( 3 mM ) , or both before the medium was processed as above . For induction with Rta , the cells were transfected with pEBV-RIE ( 5 μg per 100-mm dish ) with Lipofectamine 2000 . The relative virus titers were determined by a Raji cell assay , with the number of GFP-positive cells being counted in a hemocytometer by ultraviolet microscopy [27] . This assay underestimates the concentration of infectious virus by a factor of at least 10 [27] . When virus titer was low , the virus particles were concentrated by centrifugation in an 80Ti Beckman rotor for 2 h at 17 , 500 rpm prior to infection of the Raji cells . Quantitative ChIP analysis was performed as described by Aparicio et al . [55] . Briefly , 293 cells latently infected with WT , ZV mutant , or ZVmtRev along with uninfected 293 cells as a negative control were fixed with formaldehyde and used to prepare chromatin . After sonication to shear the chromatin to average size of ∼500 bp , antibody to ZEB1 ( Santa Cruz Biotechnology ) and protein A/G plus-agarose beads ( Santa Cruz Biotechnology ) were added to immunoprecipitate the ZEB1-containing chromatin . The beads were collected by centrifugation and washed extensively . The cross-linked protein-DNA complexes were eluted and heated at 67 °C to reverse the crosslinking . The resulting DNA was subject to 25 cycles of PCR using the following primers: Zp , forward 5′-TGATGTCATGGTTTGGGA-3′ , reverse 5′-CTGCATGCCATGCATA-3′; Rp , forward 5′-GGGTGGTGATGTAGCTATAC-3′ , reverse 5′-CCTAGGGATTTCATAAAGGCC-3′; IL-2p , forward 5′-CTACATCCATTCAGTCAGTC-3′ , reverse 5′-AACTCTTGAACAAGAGATGC-3′; and negative control EBV sequence located 4 . 8-kbp upstream of the Zp transcription initiation site , forward 5′-AGAAGGGAGACACATCTGGA-3′ , reverse 5′-AACTTGGACGTTTTTGGGGT-3′ . Controls included the following: ( i ) The PCR condition used ( 94 °C 30 sec , 55 °C 30 sec , 72 °C 1 min for 25 cycles ) was one experimentally determined to yield products falling within the linear range of the assay ( Figure 6C ) ; ( ii ) Normal preimmune rabbit IgG immunoprecipitated at most one-fifth of the level of Zp DNA ( Figure 6D ) ; and ( iii ) ZEB1 antibody failed to immunoprecipitate EBV sequences located 4 . 8-kbps upstream of the Zp transcription initiation site ( Figure 6E ) . The PCR products were resolved by electrophoresis in a 2 . 5% NuSieve 3:1 agarose gel ( Cambrex ) and the resulting DNA bands obtained from three independent sets of experiments were quantified using a PhosphorImager ( Figure 6B ) .
Accession numbers at the NCBI ( http://www . ncbi . nlm . nih . gov/ ) database for human ZEB1 ( TCF8 ) and the EBV genome strain B95 . 8 are U12170 and V01555 , respectively . | Ninety percent of people in the world become infected with Epstein-Barr virus ( EBV ) . The virus can infect both epithelial and B cells , either making more virus and killing the cell or establishing a latent form of infection where it is stably maintained in the host . EBV infection is associated with the development of some types of cancer . We show here that a mere 2-bp substitution mutation in the silencer element , ZV , of the promoter of EBV's immediate-early BZLF1 gene in the context of a whole EBV genome can lead to spontaneous reactivation of EBV out of latency into lytic replication , with production of infectious virus in some cells . The presence of the mutation also ( i ) made the virus more responsive to reactivation following treatment with chemical inducers , and ( ii ) disrupted binding of a cellular transcriptional repressor protein , ZEB1 , to the BZLF1 promoter . Our work suggests a method to kill EBV-infected cancer cells by treating them with agents that lower the repressor activity of ZEB1 . It also suggests one may be able to generate a vaccine against EBV infection using a constitutively lytic EBV strain made by knocking out the silencer elements of the BZLF1 promoter . | [
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] | 2007 | ZEB1 Regulates the Latent-Lytic Switch in Infection by Epstein-Barr Virus |
The meiotic recombination checkpoint is a signalling pathway that blocks meiotic progression when the repair of DNA breaks formed during recombination is delayed . In comparison to the signalling pathway itself , however , the molecular targets of the checkpoint that control meiotic progression are not well understood in metazoans . In Drosophila , activation of the meiotic checkpoint is known to prevent formation of the karyosome , a meiosis-specific organisation of chromosomes , but the molecular pathway by which this occurs remains to be identified . Here we show that the conserved kinase NHK-1 ( Drosophila Vrk-1 ) is a crucial meiotic regulator controlled by the meiotic checkpoint . An nhk-1 mutation , whilst resulting in karyosome defects , does so independent of meiotic checkpoint activation . Rather , we find unrepaired DNA breaks formed during recombination suppress NHK-1 activity ( inferred from the phosphorylation level of one of its substrates ) through the meiotic checkpoint . Additionally DNA breaks induced by X-rays in cultured cells also suppress NHK-1 kinase activity . Unrepaired DNA breaks in oocytes also delay other NHK-1 dependent nuclear events , such as synaptonemal complex disassembly and condensin loading onto chromosomes . Therefore we propose that NHK-1 is a crucial regulator of meiosis and that the meiotic checkpoint suppresses NHK-1 activity to prevent oocyte nuclear reorganisation until DNA breaks are repaired .
Meiosis is a specialised form of cell division that differs from mitosis in many respects , particularly during the exchange of genetic information between homologous chromosomes in recombination . In early meiotic prophase , DNA double-strand breaks ( DSBs ) are introduced into meiotic chromosomes by the conserved enzyme Spo11 to initiate recombination [1]–[4] . An elaborate structure , the synaptonemal complex , then forms between homologous chromosomes stabilising their pairing and recombination [5] . Once recombination is complete and DSBs have been repaired , the synaptonemal complex is disassembled . As these events are meiosis-specific , molecular mechanisms of meiotic prophase progression need to be established beyond our understanding of mitotic cell cycle control . Eukaryotes have a surveillance-signalling system , the so-called meiotic recombination checkpoint ( hereafter referred to as the meiotic checkpoint ) , which prevents meiotic progression until DSBs generated during recombination are repaired [6]–[8] . Many advances have been made recently in determining the mechanisms involved in the detection of and signalling downstream from DSBs [9] . In contrast , little is known about how the checkpoint signal blocks meiotic progression , except in yeast . In yeast , the Cdc28 ( Cdk1 ) -Cyclin complex is suppressed in various ways by the meiotic checkpoint to delay or block meiotic division [10]–[12] . In Drosophila , the meiotic checkpoint was first revealed by the study of a class of mutants collectively called spindle ( spn ) mutants . These spn mutants were originally identified based on their abnormal dorsal-ventral oocyte polarity [13]–[16] . They also share abnormalities in a meiosis-specific organisation of chromosomes called the karyosome [14] , [17] , [16] . The meiotic checkpoint pathway is activated in spn mutants by persistent DSBs caused either by defects in DNA repair during recombination [18] , [19] or in processing of repeat-associated siRNA that suppress germline retrotransposition [20]–[22] . Signalling downstream of DSBs in the meiotic checkpoint requires the successive activation of two conserved kinases , Mei-41 ( an ATM/ATR homologue ) and Mnk/Chk2 [17] , [23] . Their activation blocks both oocyte polarisation and karyosome formation . Vasa was proposed to act downstream of the meiotic checkpoint to mediate both oocyte polarisation and karyosome formation [17] , [23] , but a more recent study suggests that Vasa acts upstream of the checkpoint through involvement in processing of repeat-associated siRNA [24] . Gurken has been shown to be a downstream effector required for oocyte polarisation which is inhibited by the meiotic checkpoint [25] , [16] , but an effector required for karyosome formation has not been identified . The karyosome is a compact cluster of meiotic chromosomes formed within the Drosophila oocyte nucleus [26] and similar structures are also found in human oocytes [27] . In addition to the successful completion of recombination , recent studies by us and others have shown that nucleosomal histone kinase-1 ( NHK-1 ) is essential for karyosome formation [28] , [29] . NHK-1 is a Histone 2A kinase conserved from nematodes to humans ( Vrk-1 in C . elegans , and Vrk1-3 in mammals ) [30] . We showed that NHK-1 also phosphorylates Barrier-to-Autointegration Factor ( BAF ) to release meiotic chromosomes from the oocyte nuclear envelope during karyosome formation [31] . However nothing is known about how NHK-1 activity itself might be controlled during meiosis . In this report , we have investigated the functional relationship between NHK-1 and the meiotic checkpoint . We found that the meiotic checkpoint suppresses NHK-1 activity to prevent reorganisation of the oocyte nucleus , including karyosome formation , synaptonemal complex disassembly and condensin loading , until DNA breaks are repaired . Therefore , we propose that NHK-1 is a critical meiotic regulator controlled by the meiotic checkpoint .
In the wild-type oocyte nucleus , meiotic chromosomes are clustered together to form a spherical body called the karyosome [26] ( Figure 1C ) . Female sterile nhk-1 mutations show an abnormal morphology of the karyosome , which is less compact and often attached to the nuclear envelope [28] , [29] , [31] ( Figure 1B and Figure S1 ) . A similar karyosome abnormality is also observed in the spn class of mutants , which were originally identified based on their abnormal oocyte polarity [13] , [14] , [16] , [17] ( Figure 1A and Figure S1 ) . Most spn mutants contain persistent DNA double stranded breaks ( DSBs ) in meiotic chromosomes and activate the meiotic checkpoint pathway [18]–[22] . Both the karyosome and polarity defects in these spn mutants can be rescued by inactivation of the meiotic checkpoint [17] , [21] , [23] ( Figure 1D ) . A possible explanation for this similarity in the karyosome defects between nhk-1 and spn mutants is that nhk-1 mutations lead to an activation of the meiotic checkpoint pathway . To test this possibility , we assessed the activation of the meiotic checkpoint pathway in an nhk-1 mutant by examining for the persistence of DSBs on meiotic chromosomes and the presence of oocyte/embryo polarity defects . The nhk-1Z3-0437 mutant has been previously shown to have no delay in DSB repair or polarity defects [28] . However , as this allele contains a mis-sense mutation in a residue with unknown function in the kinase domain , the phenotype may be due to the specific nature of this allele . To exclude this possibility , we examined another female sterile allele , nhk-1E24/Df , that expresses a reduced amount of wild-type NHK-1 protein and shows karyosome defects [29] , [31] . To assess oocyte polarity , we examined the dorsal appendages of eggs laid by females , whose formation depends on correct dorsal-ventral axis specification in the oocyte [32] . Dorsal appendages of eggs laid by the nhk-1E24/Df mutant did not show abnormalities , indicating that oocyte polarity was properly established . Furthermore , immunostaining using an antibody against the phosphorylated form of the Drosophila H2AX variant ( γ-H2Av ) which accumulates at DSB sites [33] showed no detectable DSB foci at late oogenesis stages , indicating DSBs were repaired in the nhk-1E24/Df mutant ( Figure S2 ) . These results indicated that , unlike spn mutants , the meiotic checkpoint pathway is not activated in the nhk-1E24/Df mutant , despite the clear karyosome defect observed in this mutant . To further confirm that the karyosome defect in the nhk-1E24/Df mutant arises without meiotic checkpoint activation , we examined whether inactivating the checkpoint rescues the karyosome defect in the nhk-1E24/Df mutant . The meiotic checkpoint signalling pathway contains two kinases , Mei-41 and Mnk , which are homologues of ATM/ATR and Chk-2 respectively ( Figure 1G ) . A mutation in either of these genes has been shown to rescue the karyosome defect caused by unrepaired DSBs in spn mutants ( Figure 1D ) [17] , [21] , [23] , although mei-41 mutations have been shown to be less proficient at rescuing the karyosome defect probably due to the presence of a second ATM/ATR homologue [21] . We constructed a double mutant between nhk-1E24/Df and mnk by successive genetic crosses , and immunostaining of oocytes was carried out to visualise the oocyte nucleus and the karyosome . This showed that inactivation of the meiotic checkpoint failed to rescue the karyosome defect in the nhk-1E24/Df mutant ( Figure 1E and 1F ) . In an mnk nhk-1 double mutant , 86% of oocytes showed deformed karyosome morphology , similar to the nhk1 single mutant in which 95% of oocytes showed deformed karyosomes ( p>0 . 3 ) . In a control analysis done in parallel , no oocytes from an mnk spnA double mutant showed deformed karyosome morphology ( Figure 1D and 1F ) , in comparison to 85% of oocytes from a spnA single mutant ( p<0 . 01 ) . In conclusion , these results demonstrated that the karyosome defect in the nhk-1E24/Df mutant is not caused by activation of the meiotic checkpoint pathway . The above results demonstrated that the nhk-1E24/Df mutation induces karyosome defects without activation of the meiotic checkpoint pathway . Therefore , this places NHK-1 function either downstream or in parallel to the meiotic checkpoint pathway . One way to distinguish between these two possibilities would be to examine the kinase activity of NHK-1 in oocytes under conditions activating the meiotic checkpoint pathway ( ie . in spn mutants ) . It is known that NHK-1 directly phosphorylates Histone 2A ( H2A ) at threonine 119 ( T119; 30 ) , and this phosphorylation in the oocyte nucleus has been shown to depend on NHK-1 activity [28] . Therefore we decided to examine the level of H2A T119 phosphorylation in the oocyte nucleus as a readout of NHK-1 activity in vivo by immunostaining using a phospho-specific antibody ( anti-dH2ApT119 ) [30] . Ovaries from spn mutants ( spnA , spnB , spnD and vasa ) were dissected and immunostained with the anti-dH2ApT119 antibody . As a control , we also examined wild type and the nhk-1E24/Df mutant in parallel . Compared to wild type , we found that the H2ApT119 signal was greatly reduced on meiotic chromosomes in oocytes from spn mutants , as well as in oocytes from the nhk-1E24/Df mutant ( Figure 2A and Figure S3A ) . To quantify the level of the H2ApT119 signal reproducibly and comparably between different oocytes , we measured the H2ApT119 signal in the oocyte nucleus relative to that in follicle cell nuclei , in which H2A T119 phosphorylation has been shown to be independent of NHK-1 activity [28] . H2ApT119 signals in spn mutants were significantly reduced ( p<0 . 01; Figure 2B ) . We considered the possibility that the reduction of H2ApT119 signal under meiotic checkpoint activation was simply due to abnormal karyosome morphology itself ( and we were in fact measuring an artefact or a secondary consequence ) . First of all , this is unlikely because H2ApT119 signals were also reduced in karyosomes which retained relatively normal morphology in the spn mutants ( Figure 2A and Figure S3A ) . To exclude this possibility further , we took advantage of our previous study showing that expressing a non-phosphorylatable version of BAF ( a substrate of NHK-1 ) disrupts the karyosome in these oocytes [31] . Under these conditions , although the karyosome was disrupted , the level of H2ApT119 signal in the oocyte nucleus was comparable to that in oocytes expressing wild-type BAF ( that show normal karyosome morphology ) or wild-type oocytes ( Figure 2B and Figure S3B ) . Furthermore , to exclude the possibility that the apparent reduction in H2ApT119 was simply due to reduced chromosome condensation or DNA density , we re-quantified H2ApT119 signal intensity relative to DNA staining signal intensity in oocyte nuclei ( Figure S3C ) . The H2ApT119 signal in the oocyte nucleus relative to that in follicle cell nuclei was divided by the DNA staining signal which had been measured using the same method . The result still showed a significant reduction in the H2ApT119 signal relative to DNA signal in spn mutant oocytes . The possibility that a simple reduction in H2A levels or its occupancy on DNA accounted for the decrease in H2Ap119 signal was further excluded by immunostaining using a phospho-independent antibody against H2A which did not show reduction in H2A signal in spn mutant oocytes ( Figure S3D , S3E ) . These results confirm the genuine suppression of H2A T119 phosphorylation ( which infers the suppression of NHK-1 activity ) in these mutants . Therefore we conclude that , judged by the phosphorylation level of one of its substrates , unrepaired DSBs in spn mutants suppress NHK-1 kinase activity in the oocyte nucleus . To confirm whether this suppression of NHK-1 activity by unrepaired DSBs is mediated by the meiotic checkpoint , we tested whether inactivation of the checkpoint ( as shown in Figure 1 ) could abolish this suppression . Inactivation of the checkpoint was achieved by introduction of a mutation in mnk , which encodes the crucial checkpoint kinase Chk2 . Examination of double mutants between mnk and spnA and between mnk and spnD showed that the H2ApT119 signal on meiotic chromosomes in spn mutants is restored by inactivation of the checkpoint ( Figure 3 and Figure S4 ) . This confirmed that the suppression of NHK-1 activity in the presence of DSBs is mediated by the meiotic checkpoint . Our cytological study showed that DSBs suppress the kinase activity of NHK-1 , judged by phosphorylation of its substrate H2A at T119 . We wished to confirm this suppression of NHK-1 activity by biochemical means . As biochemical measurements of oocyte-specific NHK-1 activity is challenging , we wondered whether similar suppression of NHK-1 may be observed when DSBs are induced in Drosophila cultured cells , without involvement of meiosis-specific factors . To aid purification of NHK-1 from cultured cells ( S2 cells ) , the NHK-1 gene was fused to GFP in frame and placed under the control of the metallothionein promotor . After transfection into S2 cells , a stable cell line inducibly expressing NHK-1-GFP was established . These cells were irradiated with X-rays at 1 Gy/min for 5 minutes . Immunostaining using a γ-H2Av antibody confirmed that this dose of X-rays efficiently induced DSBs without damaging the ability of cells to repair DSBs ( data not shown ) . Fifteen minutes after X-ray irradiation , cells were collected and NHK-1-GFP was immunoprecipitated from cell extract using a GFP antibody in the presence of phosphatase inhibitors . The kinase activity of immunoprecipitated NHK-1-GFP was assayed in vitro by adding radioactive ATP without inclusion of exogenous substrates , as the NHK-1 substrate BAF is co-immunoprecipitated with NHK-1 [31] . Interestingly , we found that in vitro phosphorylation of co-immunoprecipitated BAF was greatly reduced in irradiated cells in comparison to non-irradiated cells processed in parallel ( Figure 4A ) . This phosphorylation was dependent on NHK-1 kinase activity , as it was abolished by a mutation in NHK-1 [31] that eliminates its kinase activity but does not interfere with its binding to BAF ( Figure 4A ) . Immunoblotting confirmed that comparable amounts of NHK-1 were immunoprecipitated from irradiated and non-irradiated samples ( Figure 4A ) . When cells were collected 15 minutes after irradiation , their mitotic indexes were comparable ( 1 . 2% irradiated vs 1 . 4% non-irradiated ) , their nuclei still had unrepaired DSBs and nuclear localisation of NHK-1 was unaffected ( Figure 4B ) . This indicates that the reduction in NHK-1 kinase activity in irradiated cells was not due to a reduction of mitotic cells or a change in NHK-1 localisation . The suppression of NHK-1 kinase activity after X-ray irradiation was observed in three independent experiments . These biochemical results in S2 cells give further support to our observation in oocytes that NHK-1 kinase activity is suppressed in response to DSBs . In addition to karyosome formation , NHK-1 has been shown to be required for the disassembly of the synaptonemal complex and loading of the condensin complex onto chromosomes during meiosis [28] . Our results showed that the meiotic checkpoint suppresses NHK-1 activity when DSBs are not repaired . From these observations , a prediction is that these other NHK-1 dependent events would also be blocked or delayed when the meiotic checkpoint pathway is activated . Indeed , a previous report showed that disassembly of the synaptonemal complex is delayed in a spnA mutant [18] . To test how universal this is , we examined the disassembly of the synaptonemal complex during oogenesis in various spn mutants . Immunostaining using an antibody against the synaptonemal complex protein C ( 3 ) G [34] showed that synaptonemal complex disassembly was significantly delayed in spn mutants . In wild-type oocytes , synaptonemal complex disassembly was completed by oogenesis stage 6 . However , the characteristic filamentous structure of the synaptonemal complex or its remnants were still detected by the C ( 3 ) G antibody on meiotic chromosomes even at stage 6 or later in most oocytes of spn mutants ( spnA , spnB , spnD; Figure 5A and Figure 4B ) . This delay in synaptonemal complex disassembly in spn mutants , but not in the nhk-1Z3-0437/Df mutant , was reversed by inactivation of the meiotic checkpoint using an mnk mutation ( Figure S5 ) . Next we examined condensin loading onto meiotic chromosomes in wild type and spn mutants by immunostaining . In wild-type oocytes , the conserved condensin subunit CAP-D2 [35] is fully recruited onto meiotic chromosomes by stage 6 of oogenesis . In spn mutants , the protein had not fully accumulated onto meiotic chromosomes in most oocytes even at stage 6 or later ( Figure 5C and 5D ) , indicating that the condensin complex was not fully loaded onto meiotic chromosomes . These results showed that unrepaired DSBs not only disrupt karyosome formation but also other NHK-1 dependent events . This suggests that suppression of NHK-1 activity plays wider roles in delaying meiotic progression in response to DSBs . These NHK-1 dependent events , disassembly of the synaptonemal complex , loading of condensin and karyosome formation , represent an important transition in oocyte nuclear organisation during meiosis . Temporally karyosome formation takes place at the transition between oogenesis stage 2 and 3 [26] and in fact our quantitative study of synaptonemal complex disassembly and condensin loading in wild-type meiosis ( Figure 5B and 5D ) indicated that the initiation of these other two NHK-1 dependent events also occurs between oogenesis stage 2 and 3 . As these events depend on the presence of a functioning NHK-1 kinase [28] , it suggests that NHK-1 is a key meiotic regulator of this important transition in nuclear organisation in oocytes . It has long been known that activation of the meiotic recombination checkpoint disrupts karyosome formation , and additionally we show here that synaptonemal complex disassembly and condensin loading are delayed by the presence of unrepaired DSBs and an activated checkpoint . It has previously been shown that the meiotic checkpoint blocks oocyte polarisation by suppressing Gurken translation or localisation [16] , [17] , [23] , but it was not previously known how the checkpoint affects karyosome formation or any other nuclear events in oocytes . Our study has shown that the meiotic checkpoint suppresses phosphorylation of an NHK-1 substrate , H2A , when DSBs are not repaired . Furthermore , we found that DSBs induced by X-rays suppress the kinase activity of NHK-1 in S2 cells . These results indicate that NHK-1 is a downstream effector of the meiotic recombination checkpoint , whose suppression is responsible for blocking karyosome formation and other meiotic events until DSBs are repaired . Based on this evidence , we propose a model in which DSBs formed during recombination suppress the activity of the conserved kinase NHK-1 through the meiotic recombination checkpoint to delay oocyte nuclear reorganisation from a recombination to a post-recombination phase ( Figure 6 ) . Although the evidence is mostly genetic or cytological , all data are so far consistent with this model . Nevertheless , the model is likely to be too simplistic and to represent only a part of the whole picture . For example , we do not exclude the possibility that other checkpoint effectors are also involved in delaying meiotic progression . We hope that our proposed model will prompt further investigation to fully uncover how the meiotic checkpoint is linked to meiotic progression . How does NHK-1 kinase control this critical transition in meiosis ? Our previous study showed that NHK-1 directly controls karyosome formation through phosphorylation of BAF , a linker between the nuclear envelope and chromatin [31] . Phosphorylation of BAF by NHK-1 releases meiotic chromosomes from tethering at the nuclear envelope to allow karyosome formation . Expression of non-phosphorylatable BAF disrupts karyosome formation , but not synaptonemal complex disassembly or condensin loading ( Figure S6 ) . Therefore , NHK-1 appears to control two independent pathways during nuclear reorganisation . This is consistent with a recent study [36] showing that condensin is required for synaptonemal complex disassembly but not for karyosome formation . Karyosome formation and condensin loading are therefore likely to be two primary targets of NHK-1 activity . Finally , this study in Drosophila is likely to have significant implications for our understanding of meiotic regulation at a molecular level in other organisms , since the processes we studied here are conserved among eukaryotes . The meiotic checkpoint that coordinates recombination events with meiotic progression is universally found across eukaryotes . Furthermore , NHK-1 is well conserved among animals , and karyosome-like clustering of meiotic chromosomes , as well as synaptonemal complex disassembly and condensin loading , is widely found in oocytes of various species including humans . In addition , this study has also suggested an involvement of NHK-1 in the DNA damage response during the mitotic cell cycle .
Standard techniques of fly manipulation were followed [37] . All stocks were grown at 25°C on standard cornmeal media except in some case where females were matured at 18°C . General details of mutations , chromosome aberrations and common vectors can be found in [38] or at Flybase [39] . w1118 was used as wild type . The following mutant alleles were used in this study: nhk-1E24 and nhk-1Z3-0437 analysed as a hemizygote over the deficiency Df ( 3R ) ro-80b [29] , [28]; spnA1 [13] , spnB1 [13] analysed as a hemizygote over the deficiency Df ( 3R ) red3I and spnD2 [13] that were obtained from the Bloomington Drosophila Stock Centre; vas4 [40]; mnkp6 [21] . Flies containing both spnA1 and mnkp6 mutations were obtained by standard successive genetic crosses . BAF and non-phosphorylatable BAF-3A were expressed from pUASp-BAF and pUASp-BAF-3A transgenes using a maternal Gal4 driver ( V2H ) under the α-tubulin67C promotor , as previously described [31] . Standard immunological techniques were used throughout [41] . Drosophila ovaries were immunostained essentially as described [42] . Briefly , ovaries were dissected from mature females in Robb's medium ( 100 mM HEPES , pH7 . 4 , 55 mM sodium acetate , 40 mM potassium acetate , 100 mM sucrose , 10 mM glucose , 1 . 2 mM MgCl2 , 1 mM CaCl2 ) before being fixed in formaldehyde ( 8% paraformaldehyde , 100 mM potassium cacodylate , pH7 . 2 , 100 mM sucrose , 40 mM potassium acetate , 10 mM sodium acetate , 10 mM EGTA ) . Following a blocking and permeabilization step ( in PBS containing 10% foetal bovine serum and 1% Triton X-100 ) , ovaries were successively incubated in primary and secondary antibody solutions before mounting on coverslips in mounting medium ( 85% glycerol , 2 . 5% propyl gallate ) . The primary antibodies used in this study were those against H2ApT119 [30] ( 1/200 ) , γ-H2Av ( this study; 1/100 ) , H2A ( Ab13923 , Abcam; 1/250 ) , Lamin [43] ( 1/250 ) , C ( 3 ) G [44] ( 1/3000 ) and CAP-D2 [35] ( 1/5000 ) . The antibody against γ-H2Av was generated by Eurogentec using a phospho-peptide ( CQRKGNVILpSQAY-COOH ) , and differentially purified using the phospho-peptide and an equivalent non-phospho-peptide . The antibody gave punctate staining in oocyte nuclei during early oogenesis and in X-ray irradiated nuclei in S2 cells , but not during late oogenesis or non-irradiated S2 nuclei . Secondary antibodies conjugated with Cy3 or Alexa488 ( Jackson Lab or Molecular Probes ) were used at a 1/100 dilution . DNA was counterstained with DAPI ( 0 . 4 µg/ml; Sigma ) or propidium iodide ( 2 µg/ml , Sigma ) . A series of 1 µm optical sections were taken using a Plan-Apochromat lens ( 63X , 1 . 4NA; Zeiss ) attached to an Axiovert 200M ( Zeiss ) with a confocal scan head ( LSM510meta; Zeiss ) or to an Axioimager ( Zeiss ) with an LSM5 Exciter ( Zeiss ) . A single mid-section of the oocyte nucleus has been presented . All digital images were imported to Photoshop ( Adobe ) and adjusted for brightness and contrast uniformly across entire fields . The culture and transfection of S2 cells were performed as previously described [45] . NHK-1-GFP under the metallothionein promoter was generated by a Gateway-based method ( Invitrogen ) and NHK-1 ( K77R ) -GFP was made by site-directed mutagenesis . Stable cell lines were created through selection by inclusion of blasticidin in the culture medium . Untransfected S2 cells were used as a control . NHK1-GFP expression from the metallothionein promoter was induced by culturing in medium containing 0 . 7 mM copper sulfate for 72 h . Aliquotes of cells were adhered to coverlips coated with Concanavalin A for immunostaining for γ-H2Av and GFP . Cells , together with adhered cells , were irradiated with X-rays ( 1 Gy/minute ) for 5 minutes . Subsequently , 2 . 5×107 cells were lysed in 500 µl of buffer ( 20 mM Tris pH 7 . 5 , 150 mM NaCl , 5 mM EGTA , 1 mM DTT , 1 mM PMSF , Complete EDTA-free protease inhibitor cocktail ( Roche ) ) supplemented with 10× Protein Phosphatase Inhibitor Cocktail 2 ( Sigma ) . The cleared lysate was then incubated with 5µl of mouse-anti-GFP antibody ( 3E6 , Molecular Probes ) for 1h at 4°C before the addition of 50 µl of 1∶1 protein G beads ( Invitrogen ) in lysis buffer for 1h at 4°C . The beads were washed with the lysis buffer and kinase reaction buffer ( 10 mM HEPES pH 7 . 6 , 50 mM KCl , 5 mM MgCl2 , Complete EDTA-free protease inhibitor cocktail ( Roche ) ) supplemented with 10× Protein Phosphatase Inhibitor Cocktail 2 ( Sigma ) . In a typical kinase reaction , the suspension of beads and kinase buffer was mixed with 5 µCi of γ-[32P]ATP ( EasyTides , Perkin Elmer ) and incubated at room temperature ( 20°C ) for 60 min before the addition of 20 µl of 2× protein sample buffer . The samples were analyzed by SDS-PAGE , and dried gels were exposed to x-ray films ( high performance autoradiography films , GE Healthcare ) . Analysis of karyosome morphology was performed for images of oocytes stained for lamin and DNA . For each series of images through an oocyte nucleus , the optical sections within which the karyosome was visible were determined . Of these , the mid-optical section was selected for analysis ( or the lower of the middle two optical sections where this was the case ) , and the karyosome morphology categorised . Relative intensities of H2ApT119 or H2A signal on the karyosome in the oocyte nucleus were calculated using images of oocytes stained for H2ApT119 or H2A and DNA . As described above , the mid-optical section within which the karyosome was visible was selected for analysis . Using ImageJ software ( NIH ) , the area corresponding to the karyosome was selected and the maximum H2ApT119 signal intensity on the karyosome was obtained and divided by that in surrounding follicle cell nuclei ( an average of maximum signal intensity measurements in three nuclei at similar focal planes ) after both intensities had been normalized by subtracting the background maximum signal intensity for a randomly selected area in the oocyte cytoplasm . Relative intensities of DNA staining signal on the karyosome were obtained using the same analysis method , and a measurement of H2ApT119 or H2A signal relative to DNA staining signal on the karyosome was made by dividing the two values for each image . We always compare samples processed in parallel or within a short time frame , as the exact values can vary over time due to a change in various factors including the conditions of the fixative and antibodies . Karyosome staining patterns for oocytes stained for C ( 3 ) G or CAP-D2 and counterstained for DNA were categorised as described in ‘Results and Discussion’ and Figure 5 . A student t test or χ2 test was used for statistical analysis . | Meiosis is a specialised form of cell division that produces haploid gametes from diploid cells . Failures or errors in meiosis can lead to infertility , miscarriages , or birth defects . In meiosis , chromosomes first swap genetic information during recombination and then undergo two rounds of segregation . Temporal separation of these distinct meiotic events is essential for successful meiosis . To ensure this correct temporal order , the meiotic recombination checkpoint blocks meiotic progression when recombination is not completed . Adding to our understanding of this process , we here report that the conserved Drosophila protein kinase NHK-1 is a crucial regulator of meiosis that is controlled by the meiotic recombination checkpoint . The meiotic recombination checkpoint suppresses the activity of NHK-1 to block transitional remodelling of meiotic chromosomes in the oocyte nucleus until recombination is completed . | [
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"cell... | 2010 | The Meiotic Recombination Checkpoint Suppresses NHK-1 Kinase to Prevent Reorganisation of the Oocyte Nucleus in Drosophila |
Campylobacter jejuni is a major source of foodborne illness in the developed world , and a common cause of clinical gastroenteritis . Exactly how C . jejuni colonizes its host's intestines and causes disease is poorly understood . Although it causes severe diarrhea and gastroenteritis in humans , C . jejuni typically dwells as a commensal microbe within the intestines of most animals , including birds , where its colonization is asymptomatic . Pretreatment of C57BL/6 mice with the antibiotic vancomycin facilitated intestinal C . jejuni colonization , albeit with minimal pathology . In contrast , vancomycin pretreatment of mice deficient in SIGIRR ( Sigirr−/− ) , a negative regulator of MyD88-dependent signaling led to heavy and widespread C . jejuni colonization , accompanied by severe gastroenteritis involving strongly elevated transcription of Th1/Th17 cytokines . C . jejuni heavily colonized the cecal and colonic crypts of Sigirr−/− mice , adhering to , as well as invading intestinal epithelial cells . This infectivity was dependent on established C . jejuni pathogenicity factors , capsular polysaccharides ( kpsM ) and motility/flagella ( flaA ) . We also explored the basis for the inflammatory response elicited by C . jejuni in Sigirr−/− mice , focusing on the roles played by Toll-like receptors ( TLR ) 2 and 4 , as these innate receptors were strongly stimulated by C . jejuni . Despite heavy colonization , Tlr4−/−/Sigirr−/− mice were largely unresponsive to infection by C . jejuni , whereas Tlr2−/−/Sigirr−/− mice developed exaggerated inflammation and pathology . This indicates that TLR4 signaling underlies the majority of the enteritis seen in this model , whereas TLR2 signaling had a protective role , acting to promote mucosal integrity . Furthermore , we found that loss of the C . jejuni capsule led to increased TLR4 activation and exaggerated inflammation and gastroenteritis . Together , these results validate the use of Sigirr−/− mice as an exciting and relevant animal model for studying the pathogenesis and innate immune responses to C . jejuni .
Campylobacter jejuni is one of the leading bacterial causes of gastroenteritis in the world . Although responsible for the majority of food-borne bacterial infections in developed countries , and compared to many other common enteric bacterial pathogens , our understanding of the mechanisms underlying C . jejuni's pathogenesis remains poorly defined [1] . One reason for our limited understanding is that C . jejuni appears to utilize unique pathogenic strategies , as it lacks many of the common toxins , effector proteins and virulence factors found in other pathogenic bacteria [1] . For example , cytolethal distending toxin is the only toxin so far identified within Campylobacter strains [1] , [2] yet its potentially toxic role in vivo remains unclear [2] . Furthermore , a number of bacterial factors such as capsular polysaccharides [3] , [4] , lipo-oligosaccharides [4] and proteins such as CadF [5] , Peb1 [6] , [7] , JlpA [8] and the Campylobacter invasive antigens ( Cia ) [1] , [9]–[11] , have all been studied in vitro for roles in C . jejuni cell adhesion and invasion , and in the existing commensal colonization models , however whether they play any role in pathogenicity in vivo is largely unknown . Indeed , the study of C . jejuni pathogenicity has largely been limited by the lack of relevant and convenient animal models that can be used to replicate human disease [12] . While C . jejuni readily colonizes poultry , it does so in a commensal fashion , causing no disease and thus not providing significant insight into C . jejuni pathogenesis or how the host defends against these microbes . Galleria mellonella larvae , which are a common animal model used for the study of several bacterial pathogens have been applied to C . jejuni [13] , [14] , but their relevance in modeling vertebrate enteric infection is limited . While colostrum-deprived piglets [15] , as well as ferrets [16] have been used to model C . jejuni infection with some success , their use is limited by the difficulty obtaining and maintaining these animals , and a lack of immunologic and genetic tools to aid in studying the host response to infection . Mice would normally provide a preferred infection model system; however , they have repeatedly proven resistant to pathogenic infection by C . jejuni , and many strains are unable to even be reliably colonized [17] . The basis for their resistance to C . jejuni colonization appears to at least partially reflect active competition from the resident intestinal microbiota , thereby preventing C . jejuni from establishing a niche within the murine gut [17]–[19] . Secondly , the murine immune system has proven very tolerant to the presence of C . jejuni and in wild-type ( WT ) mice , their presence only rarely elicits any overt intestinal inflammation [20] , [21] . To overcome this tolerance , several groups have tested genetically manipulated mice that develop exaggerated inflammatory responses to bacteria , such as IL-10-deficient ( Il-10−/− ) mice [20] . While Il-10−/− mice can be colonized by C . jejuni , resulting in severe enterocolitis , the loss of IL-10 dramatically alters the murine immune system . As a result , their immune system is unable to effectively clear C . jejuni from the GI tract , leading to chronic colonization rather than the acute infections seen in humans . Moreover the immune systems of Il-10−/− mice are so sensitive that the presence of any commensal microbe can potentially trigger spontaneous enterocolitis [21] . The oral gavage and intraperitoneal injections of MyD88-deficient mice , have also been employed for the study of C . jejuni colonization and dissemination in mice [22]–[24] , but encounter the reverse limitation of Il-10−/− mice , where the immune response is attenuated , allowing for colonization of the intestine or systemic sites with limited host responses . This provides utility for the study of colonization , but not immunity and the development of inflammation in response to C . jejuni . Recently we showed that mice deficient in Single IgG IL-1 Related Receptor ( SIGIRR ) exhibit increased susceptibility to infection by two natural enteric bacterial pathogens of mice , namely Citrobacter rodentium and Salmonella enterica serovar Typhimurium [25] . In both mice and humans , SIGIRR is highly expressed by intestinal epithelial cells and acts as a negative regulator of MyD88-dependent signaling , thus acting to dampen signaling by most Toll-like receptors as well as interleukin ( IL ) -1R [25]–[27] . In the absence of SIGIRR , when these receptors are activated , their downstream signaling is increased , resulting in increased innate inflammatory responses [26] , [27] . In the context of C . rodentium and S . Typhimurium infections , we found that Sigirr−/− mice not only developed exaggerated forms of infectious colitis , but they were also infected much more rapidly and with much lower infectious doses than WT mice . This heightened susceptibility was shown to reflect exaggerated antimicrobial responses by Sigirr−/− mice that were surprisingly ineffective against pathogens , but instead depleted the competing commensal microbes [25] , dramatically reducing the microbiota based resistance to intestinal pathogen colonization . Based on their heightened susceptibility to natural bacterial pathogens of mice , we examined whether Sigirr−/− mice could potentially serve as an infection model for the human pathogen C . jejuni . Although orally delivered C . jejuni were able to sporadically colonize Sigirr−/− mice , antibiotic pretreatment was found to facilitate pathogen colonization , leading to acute gastroenteritis in infected Sigirr−/− mice . We confirmed that C . jejuni primarily activates the innate receptors TLR2 and TLR4 [28]–[31] , and found that TLR4 signaling was responsible for most of the inflammatory changes seen during infection . In addition to the requirement for innate signaling , the development of gastroenteritis was also dependent on the activity and pathogenicity of C . jejuni . In infections with C . jejuni mutants deleted for flaA ( flagella ) [32] or kpsM ( capsular polysaccharide ) [31] , [33] , [34] , the ability of C . jejuni to cause gastroenteritis was significantly altered . Together , these results validate the use of Sigirr−/− mice as an exciting and relevant animal model for studying innate immune responses to C . jejuni , as well as for the study of pathogenicity factors governing infection by this microbe .
The murine intestine is thought to be highly resistant to oral infection by C . jejuni , based primarily on the ability of the resident gut microbiota to outcompete any incoming C . jejuni [17] , [35] . Our experiments support this concept , as we found infrequent and inconsistent C . jejuni colonization of conventionally housed WT C57BL/6 mice following oral inoculation with our wild-type C . jejuni strain 81–176 ( 107 CFU ) ( data not shown ) . To overcome this barrier to colonization , we pretreated WT C57BL/6 mice with vancomycin by oral gavage prior to inoculation with C . jejuni . Previous research by Russell et al . [36] showed that oral vancomycin treatment depleted Bacteroidetes and Clostridia from the intestines of mice while promoting the overgrowth of Lactobacilli [36] . Vancomycin pretreatment has also been shown to promote S . Typhimurium colonization and colitis in a fashion similar to streptomycin pretreatment [37] . Following oral inoculation with C . jejuni , we found the vancomycin pretreated WT mice exhibited consistent and robust pathogen colonization in their ceca ( Figure 1a ) and colons ( Figure S1a ) . Despite their high levels of colonization , minimal signs of inflammation were observed ( Figure 1b and c ) , consistent with previously published analyses of C . jejuni-colonized immunocompetent mice . Considering that Sigirr−/− mice exhibit impaired colonization resistance against several murine enteric bacterial pathogens , we tested their susceptibility to C . jejuni infection/colonization . We again saw only sporadic colonization in some mice , but in contrast to WT mice , we also saw occasional signs of intestinal inflammation and other forms of pathology but the results were insufficiently reproducible to provide a reliable model ( data not shown ) . We therefore tested the impact of pretreating Sigirr−/− mice with vancomycin , as previously described for WT mice . We noted that vancomycin induced a similar change in the intestinal microbiota of Sigirr−/− mice as we had found for WT mice ( Figure S2 ) . Four hours after vancomycin pretreatment , we orally infected Sigirr−/− mice along with WT mice with approximately 107 CFU of C . jejuni 81–176 . We euthanized the mice at 3 and 7 days post-infection , assessing pathogen burden in the cecum ( Figure 1a ) , colon , ileum , mesenteric lymph nodes ( MLN ) , spleen and feces ( Figure S1a–e ) . Both WT and Sigirr−/− mice were quickly colonized , with both strains of mice reaching cecal colonization levels of approximately 109 CFU/g within 3 days . In Sigirr−/− mice , colonization numbers usually peaked within 7–9 days , and began to drop significantly by 2–3 weeks post-infection , with low levels of C . jejuni ( <104 CFUs/g ) found beyond 3 weeks ( Figure S3a ) . WT mice maintained high and relatively unchanging pathogen burdens for at least 25 days ( Figure S3a ) . Colonization in the colon was similar to the cecum , whereas relatively fewer C . jejuni were recovered from the ileum ( Figure S1b ) . Fecal samples taken just prior to euthanization , and throughout the infection , proved to be largely representative of the colonization of both the cecum and colon , with the numbers more closely resembling the numbers recovered from the colon ( Figure S1e and f ) . C . jejuni were also occasionally recovered in low numbers from the MLN and rarely from the spleen ( Figure S1c , d ) , indicating that even with a high pathogen burden in the gut , C jejuni did not readily go systemic . Despite carrying similar pathogen burdens , the macroscopic pathology resulting from C . jejuni colonization was dramatically more severe in the Sigirr−/− mice as compared to WT mice . Although neither mouse strain exhibited significant weight loss ( >10% ) ( Figure S3b ) or other severe signs of morbidity , the ceca and proximal colons of the Sigirr−/− mice were overtly inflamed and often devoid of stool contents . In mice at the height of infection , the stool itself often became noticeably softer and sticky . Significant enlargement of the mesenteric lymph nodes was also noted in infected Sigirr−/− mice ( Figure S4 ) . In comparison , control mice treated with vancomycin , but not receiving C . jejuni , exhibited no significant signs of intestinal pathology 3 or 7 days post antibiotic treatment ( Figure 1c and data not shown ) . As expected , histology revealed few , if any , signs of cecal inflammation in WT mice at 3 DPI ( Figure 1b ) , and only very mild signs of inflammation at 7 DPI , despite their heavy pathogen burden . In contrast , the cecal pathology and inflammation observed in infected Sigirr−/− mice was very severe at both 3 and 7 DPI , including submucosal edema , crypt hyperplasia and widespread immune/inflammatory cell infiltration ( Figure 1c ) . In some cases , the Sigirr−/− mice developed focal cecal ulcers , accompanied by bleeding into the lumen ( Figure 1b ) . The severe damage was focused within the cecum and proximal colon , with only minimal signs of inflammation appearing elsewhere in the intestine . When we measured gene transcript levels of several key cytokines , we found that despite the lack of overt inflammation in the infected WT mice , they still showed upregulated gene transcript levels for a number of cytokines compared to uninfected mice , most notably TNFα , indicating that the WT mice were not completely unresponsive to the presence of C . jejuni . However these responses were insufficient to trigger overt signs of inflammation ( Figure 2 ) . The infected Sigirr−/− mice also showed elevated cytokine gene transcripts at levels significantly higher than those seen in WT mice . Notably , at both 3 and 7 DPI , the Sigirr−/− mice showed significantly higher mRNA levels for IL-17A , TNF-α and Interferon gamma ( IFNγ ) , indicative of a stronger inflammatory response . We also observed higher transcription of the neutrophil chemoattractant KC , as well as the cytokines IL-1β , IL-18 and IL-22 , though the variability between mice prevented the demonstration of statistical significance . To better define the cause of the exaggerated tissue pathology suffered by infected Sigirr−/− mice , we explored the localization of the colonizing C . jejuni and whether it differed with that in WT mice . Staining for C . jejuni in intestinal tissue sections of WT mice at both 3 and 7 DPI revealed the bacteria were largely limited to the intestinal lumen , with rare C . jejuni found in only 26 . 5% ( 70/264 ) of crypts . We also noted C . jejuni accumulating in the mucus layer , whereas relatively few microbes were found in direct contact with the intestinal epithelium or penetrating the cecal or colonic crypts ( Figure 3 ) . Conversely , in the Sigirr−/− mice , C . jejuni were not only found within the intestinal lumen and the mucus layer , but large numbers were also seen penetrating deep within cecal and colonic crypts ( Figure 3 ) . In these mice , 56 . 2% ( 82/146 ) of crypts were found to be heavily colonized by C . jejuni . When we examined the localization of C . jejuni within Sigirr−/− tissues more closely , we observed that large numbers of the bacteria were in direct contact with the intestinal epithelium , particularly within crypts ( Figure 3a ) . By co-staining for C . jejuni antigens along with either β-actin or cytokeratin 19 , we could clearly visualize the cytoskeleton of the epithelial cells , relative to the localization of the C . jejuni . In addition to adherent C . jejuni , we also visualized C . jejuni co-localizing with and potentially within the epithelial layer ( Figure 4a ) . To address whether these C . jejuni were intracellular , we examined the stained cells using confocal microscopy , to determine whether they were in fact internalized ( Figure 4b and c ) . Indeed , in the X , Y and Z axes , labeled C . jejuni were present inside epithelial cells , often organized into spherical foci , suggesting their localization within a vesicle or phagosome ( Figure 4b and c ) . Previous studies have identified Lamp-1 , a lysosome-associated membrane protein as a marker for intracellular S . Typhimurium containing vacuoles [38] , [39] as well as for phagosomes containing C . jejuni [40] , [41] inside cultured epithelial cells . To address whether a similar structure was present in vivo , we stained for Lamp-1 [42] , and clearly observed internalized C . jejuni within epithelial cells to be surrounded by Lamp-1 positive membrane structures ( Figure 4d ) . Although the precise numbers of internalized C . jejuni present in a tissue section varied , we observed intracellular C . jejuni in all infected Sigirr−/− mice tested . While our data showed that SIGIRR deficiency facilitated the ability of C . jejuni to adhere to and infect intestinal epithelial cells in vivo , resulting in overt gastroenteritis , it was unclear whether the resulting pathology depended on C . jejuni pathogenicity factors . To test this , we inoculated our WT and Sigirr−/− mice with two previously well-characterized C . jejuni mutants: ΔkpsM and ΔflaA , as well as the complemented strains for each mutant . The kpsM gene encodes the permease of the capsule polysaccharide ABC transporter . This gene deletion results in the loss of the entire capsule surrounding the microbe , which is thought to be a key virulence-associated cellular structure [33] , [43] . The ΔflaA flagellar mutant lacks the primary flagellin protein , and although expression of the secondary FlaB flagellin continues , the result is a truncated flagellum and a significant loss of motility [44] . This phenotype has been previously associated with an inability to invade epithelial cells in vitro [32] , and defective colonization of chicks [45] . We initially observed significant shifts in colonization for each of the mutant strains tested . Whereas wild-type C . jejuni readily colonized the intestines of Sigirr−/− mice , each of the mutant strains suffered colonization defects ( Figure 5a and b , Figure S5a ) . The ΔkpsM mutant was significantly impaired at 3 DPI , but approached WT numbers by 7 DPI . The complemented version of this mutant was significantly less impaired for colonization at 3 DPI , and more closely resembled the colonization potential of the wild-type strain . Conversely , the ΔflaA flagellar mutant was severely impaired in colonization and was completely lost from the intestine by 3 DPI and remained absent at 7 DPI . The mutant and complemented strains were also assessed for growth in vitro , and neither mutant exhibited growth defects ( Figure S5b ) . In terms of pathology , each mutant exerted a substantially different effect on the gastroenteritis seen in infected Sigirr−/− mice . As might be expected given the severe colonization defect , the ΔflaA mutant did not elicit any significant inflammation or pathology ( Figure 5c ) . In contrast , despite the ΔkpsM mutant suffering delayed colonization , it still caused overt gastroenteritis at 7 DPI that was in fact significantly worse than that seen following infection with wild-type C . jejuni ( Figure 5d ) . To explore the basis for this exaggerated pathology , we next examined how the immune system is stimulated during in vivo C . jejuni infection . Previous research has shown that C . jejuni activates several Toll-like receptors ( TLR ) including TLR2 and TLR4 , and that TLR activation may play a key role in regulating host inflammatory responses to C . jejuni [21] , [28]–[31] . To confirm that our wild-type C . jejuni strain ( 81–176 ) stimulated these TLRs , we used HEK-TLR2 and HEK-TLR4 reporter cells with a NF-κB/AP-1 inducible reporter- SEAP to measure stimulation of TLR2 and TLR4 in vitro . We observed significant stimulation of both receptors by C . jejuni 81–176 , consistent with previously published results by Maue et al . [31] ( Figure 6 ) . To explore the impact that this activation might play in our infection model , we infected Tlr2−/−/Sigirr−/− and Tlr4−/−/Sigirr−/− mice . Although the Tlr4−/−/Sigirr−/− mice were heavily colonized by C . jejuni , ( Figure 7a ) they proved largely unresponsive to the pathogen , exhibiting few if any signs of the gastroenteritis seen in infected Sigirr−/− mice ( Figure 7b ) . Notably , these mice showed little response to infection even at the gene transcriptional level . While these mice did exhibit significantly elevated expression of TNFα and IFNγ at 3 DPI , by 7 DPI , their expression of these , and other pro-inflammatory cytokines had decreased to levels similar to those in uninfected controls ( Figure 2 ) . Conversely , the Tlr2−/−/Sigirr−/− mice were significantly more sensitive to C . jejuni infection , even compared to infected Sigirr−/− mice ( Figure 7b and c ) , suffering exaggerated gastroenteritis by 3 DPI that involved worsened edema , crypt hyperplasia and inflammatory cell infiltration , including large numbers of neutrophils . Moreover , there were frequent signs of ulceration in these mice , along with loss of crypt structure and overall loss of epithelial integrity . Pathological scoring of tissues confirmed that the damage suffered by the Tlr2−/−/Sigirr−/− mice was significantly more severe than that seen in WT mice , and even more than that of Sigirr−/− mice at 3 DPI , though the severity of their inflammation was reduced by 7 DPI , leaving it similar in severity to that seen in Sigirr−/− mice at this time point . Consistent with their severe pathology , we observed a dramatic induction of inflammatory cytokine genes within the ceca of Tlr2−/−/Sigirr−/− mice at 3 DPI ( Figure 2 ) . This included significantly elevated levels of IL-1β , IL-6 , IFNγ , KC , IL-22 , IL17 and TNF-α gene transcripts , particularly at 3 DPI , although expression of many of these cytokines dropped by 7 DPI ( Figure 2 ) . Interestingly , the localization of C . jejuni was similar amongst all three SIGIRR-deficient mouse strains , with the C . jejuni seen in large numbers deep within cecal and colonic crypts , as well as inside intestinal epithelial cells ( Figure 7c and data not shown ) . C . jejuni colonization of crypts in the Tlr2−/−/Sigirr−/− and Tlr4−/−/Sigirr−/− strains was comparable to the Sigirr−/− mice , with 41 . 7% ( 50/120 ) and 47 . 1% ( 66/140 ) of observed crypts being positively colonized , often with high numbers of bacteria in each crypt ( Figure 7c ) . This indicates that the significant differences in pathology amongst the three SIGIRR deficient mouse strains were governed by the stimulation of the TLRs instead of by changes in the localization of the bacteria . We also assessed Tlr2−/− and Tlr4−/− single mutants for colonization and inflammation . Once again , pathogen burden was not affected by the mouse strain so long as it was accompanied by vancomycin pretreatment ( data not shown ) . Unsurprisingly , Tlr4−/− were completely unresponsive to the presence of C . jejuni , exhibiting no inflammation ( Figure S6 ) . Tlr2−/− were much less responsive than Tlr2−/−/Sigirr−/− mice , but did show modest signs of inflammation by 7 DPI ( Figure S6 ) . Together , these results demonstrate that the majority of the inflammation seen in this model is driven by TLR4 , whereas TLR2 signaling appears to play a protective role . Based on previous data published by Rose et al . [34] and Maue et al . [31] we expected the capsule to play a role in modulating TLR responses to C . jejuni . To further explore the impact of TLR signaling during C . jejuni infection , we tested the effect of the ΔkpsM mutant on our TLR2 and TLR4 reporter cell lines . The ΔkpsM mutant stimulated both TLR2 and TLR4 to a significantly higher degree than the wild-type 81–176 strain with the complemented ΔkpsM+kpsM strain completely or nearly completely rescuing the mutant phenotype ( Figure 6 ) . To test whether these results translated to increased inflammation in vivo , we infected our different mouse strains with this mutant . As shown in Figure 8a , the ΔkpsM mutant elicited a very significant inflammatory response in the Sigirr−/− mice by 7 DPI . Moreover , it also caused exaggerated inflammation and pathology in Tlr2−/−/Sigirr−/− mice as compared to the effects of wild-type C . jejuni , yet once again there was little response in the Tlr4−/−/Sigirr−/− mice ( Figure 8a ) . The localization of the ΔkpsM mutant in vivo was similar to that of wild-type C . jejuni , as it was frequently found in direct contact with the epithelium and deep within crypts ( Figure 8b ) . These results were confirmed when cytokine transcript levels were assessed ( Figure S7 ) Together , these data support previously published in vitro results [31] , [34] , and for the first time demonstrates that the C . jejuni capsule limits the host innate responses to this pathogen during the course of infection .
A lack of animal models , and in particular mouse models that replicate the gastroenteritis caused by C . jejuni infection in humans , has long been an impediment to the study of C . jejuni pathogenesis . Moreover , improved preclinical models of C . jejuni infection are a necessity to better define those host factors that protect against this pathogen . Here we demonstrate that the antibiotic vancomycin facilitates C . jejuni's colonization of the mouse intestine , presumably through the removal of commensal microbes that promote resistance against C . jejuni colonization . Moreover , our studies validate the use of vancomycin pretreated Sigirr−/− mice as a model for C . jejuni infection and pathogenesis , as these mice develop acute gastroenteritis following infection . We were able to define the role of innate signaling in this model through the testing of Tlr2−/−/Sigirr−/− and Tlr4−/−/Sigirr−/− mice as well as clarify specific aspects of C . jejuni pathogenesis through the testing of mutant strains . Taken together , we demonstrate that by modulating the gut microbiota as well as the innate sensitivity of the murine intestine , we have been able to develop a reliable and exciting new animal model of C . jejuni infection . WT mice , including the C57BL/6 strain used in this study , have in the past proven resistant to infection by C . jejuni , limiting their utility as an infection model [17] , [35] . This limitation in the ability to colonize mice has been linked to the intestinal microbiota , and its ability to out-compete invading C . jejuni . Previous studies have explored how to overcome this barrier by using mice with a “humanized” microbiota [17] , as well as germ-free mice and mice carrying a limited microflora [19] , [21] , [46] . In the current study , we used an approach successfully employed with other bacterial pathogens [37] , using a single pre-treatment of the antibiotic vancomycin to disturb the murine microbiota sufficiently to allow C . jejuni to establish in the intestine . This colonization was , however , insufficient to produce an effective model of inflammation , as the colonized mice remained highly tolerant to the presence of C . jejuni , displaying few if any signs of inflammation , even in the presence of a high pathogen load . Our previous studies identified Sigirr−/− mice as displaying increased susceptibility to infection by the natural mouse pathogens S . Typhimurium and C . rodentium in terms of both the severity of disease as well as pathogen burden [25] . Normally highly expressed by the intestinal epithelium , SIGIRR acts to dampen signaling through MyD88-dependent receptors such as most TLRs as well as IL-1R [26] . Thus SIGIRR expression is thought to help maintain the relative innate hypo-responsiveness of the intestinal epithelium . While the absence of SIGIRR does not lead to spontaneous intestinal inflammation , it does leave the epithelium more sensitive to microbial stimulation through TLRs . Previous studies identified TLR2 and TLR4 as being stimulated by C . jejuni in vitro [31] , [34] and our study confirmed these two TLRs actively respond to C . jejuni . Moreover , TLR4 has been identified as being a major driver of inflammation in C . jejuni-infected IL-10−/− mice [21] and the present study found the gastroenteritis seen in infected Sigirr−/− mice is almost completely TLR4 dependent . In contrast , TLR2 signaling was found to protect the intestine from exaggerated injury , potentially by promoting responses in the epithelium that limit the damage caused by the TLR4 driven inflammation . Taken together , there are several advantages to the use of the Sigirr−/− mouse over other models of C . jejuni infection . While C . jejuni readily colonizes the intestines of newborn chickens , it only does so in a commensal fashion , thus providing little insight into its pathogenesis or how it triggers gastroenteritis . While neonatal piglet and ferret models have been used successfully as models for infection [15] , [16] , both have significant limitations as these animals are difficult to acquire as well as handle , and there are few immunological or genetic tools available for these species . To circumvent these issues , mice remain one of the preferred animal species for use in research , but their resistance to C . jejuni colonization and disease has limited their utility in the field . The most successful mouse model of C . jejuni infection to date has been the Il-10−/− mouse , which has several features in its favor , including a very strong and reproducible inflammatory response [20] , [21] , [46] . However , it also suffers from several complications , notably the propensity of the Il-10−/− mice to develop spontaneous colitis as a reaction against their own microbiota [47] , forcing researchers to use more inconvenient and costly germ-free conditions [21] , [46] . Additionally , IL-10 has been shown to be a key cytokine in the resolution for inflammation following infection , meaning that C . jejuni infection in IL-10−/− mice is ultimately chronic and lethal to the mice , as opposed to the acute , self-limiting infection observed in humans . Our use of Sigirr−/− mice addresses most of these issues . When orally inoculated with a relatively low dose of C . jejuni , the vancomycin pre-treatment allowed for reliable colonization , while only causing a temporary disruption in the microbiota . Although our previous research has identified a higher inflammatory “tone” in the Sigirr−/− mice , characterized by slightly higher expression of several pro-inflammatory cytokines [25] , the Sigirr−/− mice themselves do not develop spontaneous colitis in response to their own microbiota as often occurs in IL-10−/− mice . When infected with C . jejuni they developed only an acute gastroenteritis , in keeping with the clinical effects of C . jejuni infection . Moreover , the gastroenteritis bears several hallmarks of C . jejuni infection , including prominent neutrophil infiltration into the infected tissues and lumen . Our assessment of Tlr4−/−/Sigirr−/− mice determined that the vast majority of the inflammation seen in this model is TLR4 dependent , which is in agreement with previous observations in gnotobiotic IL-10−/− mice [21] . In contrast to the modest responses seen in infected Tlr4−/−/Sigirr−/− mice , when we infected Tlr2−/−/Sigirr−/− mice , we observed a significantly exaggerated and accelerated form of gastroenteritis , especially at the early stages of infection ( 3 DPI ) . Correspondingly , these mice suffered increased pathology , including widespread loss of epithelial integrity , loss of crypt structure and frequent ulceration . This was accompanied by substantially increased pro-inflammatory cytokine expression . The most severe pathology was apparent at 3 DPI , with both cytokine expression and pathology dropping substantially by 7 DPI to the point where it was no longer significantly more severe than that seen in Sigirr−/− mice . These findings are intriguing as they suggest that TLR2 plays a protective role , at least during the early stages of C . jejuni infection . Previous studies have identified roles for TLR2 in the maintenance of epithelial tight junctions in the intestine , for example by increasing the production of Trefoil Factor 3 [48] , along with other barrier protective proteins [49] , [50] . As recently described by our laboratory , innate inflammatory responses in the GI tract appear to reflect a tenuous balance between damaging inflammatory signals and concurrent protective or tolerance inducing innate responses that limit the resulting tissue damage . It appears this is also the case during C . jejuni infection , with TLR2 playing a key role in limiting damage suffered by the host as its immune system tries to clear C . jejuni from the intestine [51] . Aside from exploring the host response to infection , an optimal C . jejuni infection model must be able to distinguish subtle aspects of C . jejuni pathogenicity . To address this issue , we infected our Sigirr−/− mice with C . jejuni strains lacking the ability to form a capsule , as well as a flagellar mutant . Regarding the ΔflaA flagellar mutant , previous studies have found C . jejuni mutants that are non-motile or suffer reduced motility are unable to effectively colonize the intestines of chicks [45] , piglets [15] , or wildtype mice [52] , [53] . We therefore expected the ΔflaA strain to be impaired in colonization , and indeed , the ΔflaA mutant was unable to colonize the Sigirr−/− mice or cause any level of gastroenteritis . Precisely why this mutant was unable to colonize is an interesting question . We predominantly observe C . jejuni colonization in the mucus layer and into the crypts . Both leaving the lumen of the intestine and migration through the mucus layer would presumably require fully motile bacteria . It would appear that the inability of C . jejuni with reduced motility to reach and move through these niches results in a loss of colonization potential , even in mice with reduced microbiota competition . In the case of the ΔkpsM mutant , it exhibited a delay in colonization as assessed at 3 DPI , but by 7 DPI , its pathogen load had increased to levels similar to WT C . jejuni . This could indicate a greater sensitivity of this mutant to the innate defenses in the gut . Previous work has already linked the loss of capsule to increased sensitivity to environmental factors such as osmotic stress [54] , as well as antimicrobial factors [55] . However , the reduced colonization of ΔkpsM was transient , as the mutant quickly recovered to WT levels . Despite this initial delay , the ΔkpsM strain was able to elicit significantly more severe gastroenteritis than that seen with the wild-type C . jejuni . When we tested the ΔkpsM mutant in our in vitro reporter system , we found it stimulated both TLR2 and TLR4 to a significantly higher degree than that seen with WT C . jejuni . This result is consistent with previous findings [31] , [34] , suggesting a role for the capsule in reducing the exposure of pathogenic bacteria to the host's immune system by masking some of the TLR activating PAMPs . For example , Rose et al . determined that the presence of a capsule reduces cytokine expression by dendritic cells exposed to C . jejuni in vitro [34] , and a similar observation was made by Maue et al . in an epithelial reporter cell line [31] . Here , for the first time in vivo , we demonstrate that the capsule does help conceal C . jejuni from the host's immune system , potentially as a means to limit host driven defenses as well as perhaps limit collateral tissue damage to the host . One of the most intriguing findings from our study involved the localization of C . jejuni in the intestines of the Sigirr−/− mice . In WT mice , C . jejuni were found predominantly in the lumen , along with a clustering at the luminal surface of the mucus layer . Notably , relatively few C . jejuni were found in direct contact with the cecal or colonic epithelium , and few were seen penetrating the crypts . In contrast , in the Sigirr−/− mice we found large numbers of C . jejuni , not only within this mucus layer , but also penetrating and accumulating in large numbers at the base of the intestinal crypts . Similar observations were made in infected Tlr2−/−/Sigirr−/− mice , although in these mice , the exaggerated damage they suffered often left C . jejuni mixed within sloughed epithelial cells as well as phagocytosed inside neutrophils at sites of ulceration . This phenotype of crypt colonization was not restricted to mice developing severe inflammation , since Tlr4−/−/Sigirr−/− mice also displayed large numbers of bacteria within their cecal crypts . Thus the factor within Sigirr−/− mice that permits C . jejuni to colonize the crypts is not a result of overt inflammation , in contrast to recent studies of S . Typhimurium colonization of the murine intestine [56] , but may be due instead to more subtle differences in the microenvironment of the crypts . Aside from penetrating intestinal crypts , we also determined that C . jejuni could invade the intestinal epithelial cells of our Sigirr−/− mice . Intracellular C . jejuni were observed in both the cecum and colon of infected mice , and were usually seen in the more mature epithelial cells , at the top of crypts rather than at their base . Co-staining with β-actin or cytokeratin 19 confirmed that the C . jejuni were inside epithelial cells , while staining for LAMP-1 localized the internalized bacteria within LAMP-1 positive vesicles . Interestingly , the presence of intracellular C . jejuni did not on its own drive significant inflammation as internalized bacteria were also found in infected Tlr4−/−/Sigirr−/− mice , which exhibited no significant signs of inflammation . This indicates that intracellular C . jejuni can exist without causing overt inflammation or pathology; however , it remains possible that this cellular invasion can play a triggering role for the overt inflammation seen in infected Sigirr−/− and Tlr2−/−/Sigirr−/− mice . Together , these studies provide new insight into the pathogenicity of C . jejuni , and how colonization by this microbe triggers an inflammatory reaction by its host . In conventional WT mice , the commensal microbiota provide colonization resistance against C . jejuni by outcompeting the invading pathogen . Through vancomycin treatment , we were able to readily disrupt this protection , but the WT mice remained substantially tolerant to the presence of C . jejuni , resulting in almost no inflammatory response . In contrast , in the absence of SIGIRR , the murine immune system proved dramatically more responsive to C . jejuni , potentially by increasing the sensitivity of epithelial expressed TLRs . Overall , the degree of inflammation that developed in the infected intestines of the Sigirr−/− mice appeared to correlate with the invasion by C . jejuni of the intestinal crypts , and appeared almost totally dependent on the actions of TLR4 . In conclusion , we present the Sigirr−/− mouse as an effective and exciting new model for the study of C . jejuni infection and pathogenesis . We speculate that our demonstration that Sigirr−/− mice can indeed be infected in a relevant fashion by C . jejuni will provide an impetus for further study , to better elucidate both the host factors and pathogenesis that drive gastroenteritis .
The wild-type C . jejuni strain used in this study is the commonly used 81–176 lab strain and all mutant and complemented strains were constructed on this background . The bacteria were routinely grown on Mueller-Hinton agar plates or broth , supplemented with the selective antibiotics Chloramphenicol and/or Kanamycin as required . Additionally , during mutant and complement construction , plates and broth were routinely supplemented with vancomycin ( 10 µg/mL ) and trimethoprim ( 5 µg/mL ) to prevent contamination . Cultures were routinely grown under microaerophilic conditions using anaerojars and CampyGen sachets ( Oxoid ) at 42°C . To construct deletion mutants in the genes flaA and kpsM , each gene was PCR amplified with iProof ( Bio-Rad ) from C . jejuni 81–176 with the appropriate primers listed in Table S1 . The product was polyA tailed and ligated to pGEM-T ( Promega ) . Inverse PCR was performed on the resulting plasmid , deleting 1248 bp or 514 bp from the flaA or kpsM genes respectively . The flaA and kpsM inverse PCR products were digested with KpnI and SpeI , or KpnI and XbaI respectively , then ligated to the non-polar kanamycin resistance cassette ( aphA-3 ) digested out of pUC18K-2 [57] . The construct was verified by sequencing and naturally transformed to C . jejuni 81–176 . Mutant strains were selected by kanamycin resistance , and verified by sequencing . To complement each of these mutants , flaA or kpsM was PCR amplified from C . jejuni 81–176 genomic DNA , digested with SpeI and MfeI , or XbaI and MfeI respectively , and inserted into pRRC [58] digested with XbaI and MfeI . The resulting construct was verified by PCR and sequencing , and naturally transformed into the corresponding mutant . Complemented strains were selected on chloramphenicol and verified by PCR and sequencing . Additional confirmation of the phenotypes of both mutant and complemented strains were undertaken to ensure they corresponded to previously published data for these mutants . The ΔflaA mutant and complement were tested for motility , indicating the mutant was only approximately 25% as motile as the WT or complemented strain [59] . The ΔkpsM mutant was tested for NaCl sensitivity [54] and hyper-biofilm formation [60] , and the complement was confirmed to restore the wild-type phenotype for both . In vitro growth curves to confirm equal growth potential between both ΔflaA and ΔkpsM mutant and complemented strains were conducted in MH broth , at 37°C under microaerophilic conditions with samples taken at 6 , 24 , and 48 hours post inoculation . The C57BL/6 ( WT ) , Sigirr−/− , Tlr2−/− , Tlr2−/−/Sigirr−/− , Tlr4−/− , and Tlr4−/−/Sigirr−/− mouse strains used in this study were all bred in-house and kept under specific pathogen-free conditions at the Child and Family Research Institute ( CFRI ) . The combined TLR and SIGIRR deficient mice were created by cross breeding single knockout strains as described previously [25] . Mice at 6–10 weeks of age were orally gavaged with 100 µl of a 50 mg/ml vancomycin solution suspended in PBS ( dose per mouse of ∼5 mg ) . Four hours later , each mouse was inoculated with an overnight culture of ∼107 CFUs of C . jejuni 81–176 or one of the above mentioned mutant strains . The weight of each mouse was recorded before antibiotic treatment and inoculation , and each mouse was weighed again every two days to check for weight loss/gain . Fecal samples were collected 1 , 3 , 5 and 7 DPI , were weighed , homogenized , serially diluted and plated onto Campylobacter agar plates containing Karmali selective supplements ( Oxoid ) . Three and seven days post infection , mice were anaesthetized with isofluorane and euthanized by cervical dislocation . The mice were immediately dissected and their ileum , cecum , colon , mesenteric lymph nodes and spleen were isolated . Cecal and proximal colonic tissues were fixed in 10% neutral buffered formalin ( Fisher ) . Cecal tissues were also washed to remove luminal contents and then suspended in RNAlater ( Qiagen ) for subsequent RNA extraction . The remainder of the cecum ( including luminal contents ) , and other isolated tissue sections were suspended in 1 ml sterile PBS ( pH 7 . 4 ) for viable cell counts . Tissue samples were homogenized , serially diluted and plated onto Campylobacter agar plates containing Karmali selective supplements ( Oxoid ) . Following 48 hours incubation , at 42°C under microaerobic conditions colonies were enumerated , and the pathogen burden ( CFUs/g of tissue ) was calculated . Statistically significant differences were determined using a non-parametric Mann-Whitney test , with a p value below 0 . 05 used as the threshold for significance . To monitor colonization of C . jejuni over a 25 day timeframe , three experimental groups comprising 13 WT and 15 Sigirr−/− mice total were inoculated with C . jejuni 81–176 . Weights and fecal samples were taken every two days from 1 DPI to 25 DPI . CFUs present within the fecal samples were enumerated as described above and statistical significance was determined using multiple t-tests ( p<0 . 05 ) . All animal experiments were performed according to protocol number A11-290 , approved by the University of British Columbia's Animal Care Committee and in direct accordance with the Canadian Council of Animal Care ( CCAC ) guidelines . Mice were monitored for mortality and morbidity throughout their infection and euthanized if they showed signs of extreme distress or more than 15% body weight loss . Tissues previously fixed in 10% formalin were paraffin embedded and cut for further histological analysis . The paraffin embedded tissue sections were stained with haematoxylin and eosin , and then photographed , and then used for pathological scoring . The scoring was done by two blinded observers according to previously established criteria [25] . Each tissue section was assessed for: ( 1 ) submucosal edema ( 0-no change , 1- mild , 2- moderate , 3- severe ) , ( 2 ) crypt hyperplasia ( 0-no change , 1: 1–50% , 2: 51–100% , 3: >100% ) , ( 3 ) goblet cell depletion ( 0-no change , 1-mild depletion , 2-severe depletion , 3-absence of goblet cells ) , ( 4 ) epithelial integrity ( 0-no pathological changes detectable , 1-epithelial desquamation ( few cells sloughed , surface rippled , 2-erosion of epithelial surface ( epithelial surface rippled , damaged ) , 3-epithelial surface severely disrupted/damaged , large amounts of cell sloughing , 4-ulceration ( with an additional score of 1 added for each 25% fraction of tissue in the cross-section affected up to a maximum score of 8 ( 4+4 ) for a tissue section that had entirely lost its crypt structure due to epithelial cell loss and immune cell infiltration , ( 5 ) mucosal mononuclear cell infiltration ( per 400× magnification field ) ( 0-no change , 1- <20 , 2- 20 to 50 , 3- >50 cells/field ) , ( 6 ) submucosal PMN and mononuclear cell infiltration ( per 400× magnification field ) ( 1- <5 , 2- 21 to 60 , 3- 61 to 100 , 4- >100 cells/field ) . A maximum score under this scale is 24 . Statistical significance ( p<0 . 05 ) was determined using a two-way ANOVA , with a Bonferroni post-test . The paraffin embedded , formalin-fixed tissue sections were also used for immunofluorescent staining using variations on established protocols [25] , [61] . Briefly , tissue sections were deparaffinized by heating for 8 minutes , clearing with xylene , rehydrating with 100% , 95% , and 70% ethanol , followed by dH2O . Antigen retrieval of the tissue sections was conducted with sodium citrate buffer ( pH 6 . 0 ) , in a steam bath for 30 minutes . Blocking was done with an endogenous Biotin-blocking kit ( Molecular Probes ) following manufacturer protocols , followed by 1 hour blocking with donkey serum blocking buffer ( donkey serum in PBS containing 1% bovine serum albumin ( BSA ) , 0 . 1% Triton-X100 , 0 . 05% Tween 20 , and 0 . 05% sodium azide ) . The primary antibodies used were for Actin ( goat polyclonal , Santa Cruz Biotechnology ) , Cytokeratin 19 ( goat polyclonal , Santa Cruz Biotechnology ) , and Campylobacter jejuni ( Biotin-rabbit polyclonal , Abcam ) . Each was visualized using Alexa Fluor 488-conjugated donkey anti-goat IgG ( Invitrogen ) or Alexa Fluor 568-conjugated streptavidin ( Molecular Probes ) . The tissues were mounted using ProLong Gold antifade reagent containing DAPI ( Invitrogen ) . The stained slides were viewed using a Zeiss AxioImager Z1 , photographed using an AxioCam HRm camera with AxioVision software . Confocal imaging was conducted with a Leica TCS SP5 system , using the Leica Application suite software . Slides stained for C . jejuni and DAPI were used to assess crypt colonization . We used slides of formalin fixed , 7 day infected cecal tissues from WT , Sigirr−/− , Tlr2−/−/Sigirr−/− , and Tlr4−/−/Sigirr−/− mice to count the number of crypts containing visible numbers of C . jejuni . In total , 264 , 146 , 140 , and 120 crypts were counted for each mouse strain respectively , from three slides each , each of which contained at least three tissue sections . Tissue samples previously isolated from infected or control mice were preserved in RNAlater at −20°C for later use . RNA was extracted using a Qiagen RNeasy kit ( Qiagen ) according to the manufacturer's protocol . The final RNA samples were eluted from the columns in sterile , RNAse free dH2O and quantified using an ND-1000 spectrophotometer ( Nanodrop ) . cDNA was synthesized from the RNA using an Omniscripts RT kit ( Qiagen ) and Oligo-dT ( Applied Biological Material Inc . ) . Quantitative real-time PCR was carried out using an MJ mini-opticon Real-Time PCR system ( Bio-Rad ) using IQ SYBR Green Supermix ( Bio-Rad ) . The primers used have been described previously [25] and are listed in Table S1 . Quantification of the qPCR results was performed using Gene Ex Macro OM 3 . 0 software ( Bio-Rad ) and ANOVAs were used to determined statistical significance of the results . HEK TLR reporter cell lines , HEK-Blue hTLR2 and HEK-Blue hTLR4 , were purchased from InvivoGen ( San Diego , CA , USA ) . HEK-Blue hTLR2 were obtained by co-transfection of hTLR2 and hCD14 co-receptor genes into HEK 293 cells , while HEK-Blue hTLR4 were obtained by co-transfection of hTLR4 and hMD-2/CD14 co-receptor genes . The cells were transfected with the secreted embryonic alkaline phosphatase ( SEAP ) gene and stably express SEAP under the control of a promoter inducible by NF-κB and activator protein 1 ( AP-1 ) . Thus , stimulation of hTLR2 or hTLR4 will lead to the production of extracellular SEAP in the culture medium proportional to the level of NF-κB/AP-1 activation . Cells were grown in High Glucose DMEM ( HyClone , Logan , UT , USA ) with 2 mM L-glutamine , 10% heat-inactivated FBS ( HyClone ) , 100 µg/ml Normocin ( InvivoGen ) and selective antibiotics ( 1×HEK-Blue selection , InvivoGen ) according to the manufacturer's instructions . The activation of TLR2 or TLR4 was assessed by measuring the SEAP activity using QUANTI-Blue ( InvivoGen ) colorimetric assay . The reporter cells ( 5×104/well ) were seeded in a 96-well plate ( BD Bioscience , Mississauga , ON , Canada ) . The next day , cells were treated with fresh media ( without selective antibiotics ) containing wild type , ΔkpsM , or ΔkpsM+kpsM C . jejuni strains for 4 h . Cells treated with culture medium only , TLR2 ligand Pam3CSK4 ( 100 ng/mL , InvivoGen ) and TLR4 ligand lipopolysaccharide ( LPS , Escherichia coli K-12 , 100 ng/mL , InvivoGen ) serve as the negative and positive controls , respectively . For each experiment , all conditions were done in triplicate . After 4 h incubation , culture media were collected and centrifuged to remove bacteria . The supernatants ( 20 µl ) were then incubated with QUANTI-Blue solution ( 180 µl ) in a 96-well flat-bottom plate at 37°C for 16–18 h to allow the color development . The color change of the substrate solution corresponds to the activation of NF-κB/AP-1 , which can be quantified by optical density ( λ = 655 nm ) measurement using a SpectraMax 384 Plus plate reader ( Molecular Devices , Sunnyvale , CA , USA ) . | Research into the key virulence strategies of the bacterial pathogen Campylobacter jejuni , as well as the host immune responses that develop against this microbe have , in many ways , been limited by the lack of relevant animal models . Here we describe the use of Sigirr deficient ( −/− ) mice as a model for C . jejuni pathogenesis . Not only do Sigirr−/− mice develop significant intestinal inflammation in response to colonization by C . jejuni , but the ability of this pathogen to trigger gastroenteritis was dependent on key virulence factors . We also found that the induction of the inflammatory and Th1/Th17 immune responses to infection in these mice depended on specific Toll-like receptors , principally TLR4 , which we identified as the main driver of inflammation . In contrast , TLR2 signaling was found to protect mucosal integrity , with Tlr2−/−/Sigirr−/− mice suffering exaggerated mucosal damage and inflammation . Notably , we found that C . jejuni's capsule helped conceal it from the host's immune system as its loss led to significantly increased activation of host TLRs and exaggerated gastroenteritis . Our research shows that the increased sensitivity of Sigirr−/− mice can be used to generate a unique and exciting model that facilitates the study of C . jejuni pathogenesis as well as host immunity to this enteric pathogen . | [
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"... | 2014 | A Novel Mouse Model of Campylobacter jejuni Gastroenteritis Reveals Key Pro-inflammatory and Tissue Protective Roles for Toll-like Receptor Signaling during Infection |
Head and neck squamous cell carcinomas ( HNSCCs ) are characterized by outstanding molecular heterogeneity that results in severe therapy resistance and poor clinical outcome . Inter- and intratumoral heterogeneity in epithelial-mesenchymal transition ( EMT ) was recently revealed as a major parameter of poor clinical outcome . Here , we addressed the expression and function of the therapeutic target epidermal growth factor receptor ( EGFR ) and of the major determinant of epithelial differentiation epithelial cell adhesion molecule ( EpCAM ) in clinical samples and in vitro models of HNSCCs . We describe improved survival of EGFRlow/EpCAMhigh HNSCC patients ( n = 180 ) and provide a molecular basis for the observed disparities in clinical outcome . EGF/EGFR have concentration-dependent dual capacities as inducers of proliferation and EMT through differential activation of the central molecular switch phosphorylated extracellular signal–regulated kinase 1/2 ( pERK1/2 ) and EMT transcription factors ( EMT-TFs ) Snail , zinc finger E-box-binding homeobox 1 ( Zeb1 ) , and Slug . Furthermore , soluble ectodomain of EpCAM ( EpEX ) was identified as a ligand of EGFR that activates pERK1/2 and phosphorylated AKT ( pAKT ) and induces EGFR-dependent proliferation but represses EGF-mediated EMT , Snail , Zeb1 , and Slug activation and cell migration . EMT repression by EpEX is realized through competitive modulation of pERK1/2 activation strength and inhibition of EMT-TFs , which is reflected in levels of pERK1/2 and its target Slug in clinical samples . Accordingly , high expression of pERK1/2 and/or Slug predicted poor outcome of HNSCCs . Hence , EpEX is a ligand of EGFR that induces proliferation but counteracts EMT mediated by the EGF/EGFR/pERK1/2 axis . Therefore , the emerging EGFR/EpCAM molecular cross talk represents a promising target to improve patient-tailored adjuvant treatment of HNSCCs .
Head and neck squamous cell carcinomas ( HNSCCs ) are the sixth-most-common carcinomas worldwide , with a poor 45% survival rate at 5 y [1] , owing to early recurrence due to treatment failure and to the frequent presence of locoregional lymph node metastases at initial diagnosis [2] . Therefore , the requirement to control metastatic spread and to overcome therapy resistance represents major challenges and promises in HNSCC treatment . Furthermore , improvements of stratification options for patients beyond the current tumor , node , metastasis ( TNM ) classification and human papillomavirus ( HPV ) infection status are in high demand , in order to deliver patient-tailored precision medicine . In-depth knowledge of molecular processes that underlie metastasis formation and therapy resistance is thus of paramount importance to achieve best possible adjustment of adjuvant and palliative treatment of HNSCC patients who experience recurrences and metastases and , eventually , to improve clinical outcome . A mechanism central to metastatic spread and treatment resistance is referred to as epithelial-mesenchymal transition ( EMT ) , which is a differentiation program that allows cells to acquire the migratory capacity initially described in embryonic development [3] . Cancer cells undergo a partial phenotypic EMT shift to progeny with enhanced mesenchymal features , i . e . , gain of migratory and invasive potential , improved resistance to radiation and chemotherapeutic drugs , and development of cancer stem cell ( CSC ) features [4–6] . Accordingly , the use of multigene transcriptomic EMT signatures as a scoring system was demonstrated to have predictive value in a variety of carcinomas [7] . HNSCCs are characterized by strong genetic heterogeneity [8] , with an average of 130 mutations per tumor [9 , 10] . High intratumoral heterogeneity correlates with decreased overall survival ( OS ) [11] and provides cellular diversity , which fosters the emergence of cellular subpopulations equipped with enhanced EMT traits and treatment resistance [12–15] . Specifically , HNSCCs are composed of heterogeneous tumor cells with individual RNA transcript signatures related to cell cycle , stress response , hypoxia , epithelial differentiation , and partial EMT ( pEMT ) [16] . Malignant pEMT cells were preferentially located at leading edges of tumor areas , and their signature was reciprocal to that of the epithelial differentiation , which was codefined by high expression of the pan-carcinoma epithelial cell adhesion molecule ( EpCAM ) [16] . The identified pEMT program correlated with metastases formation and poor prognosis and was suggested to result from interactions of tumor cells with cancer-associated fibroblasts of the tumor microenvironment [16] . Despite such highly encouraging innovative data on molecular features of HNSCCs , therapeutic options to cope with metastasized and progressing HNSCCs at the molecular target level remain unsatisfying . Currently , epidermal growth factor receptor ( EGFR ) is the major target for therapeutic antibodies and inhibitor-based palliative treatment regimens aiming at controlling recurrent and metastatic disease in HNSCC patients . EGFR is frequently and strongly expressed in HNSCCs [9] , has prognostic and predictive value [17] , and serves as an anchor for Food and Drug Administration ( FDA ) -approved therapeutic antibodies and inhibitors targeting EGFR , including monoclonal antibody Cetuximab , which is primarily implemented into palliative treatment of metastatic head and neck , colon , and non-small-cell lung cancer patients [18–20] . However , clinical benefits deployed by inhibition of EGFR in HNSCCs remain insufficient because of highly advanced stages of disease , the development of multiple resistances [21] , and pleiotropic cellular functions of EGFR in proliferation and cell differentiation , including the regulation of EMT [22–27] . Therefore , deepening the understanding of EGFR signaling towards proliferation and EMT in HNSCCs is advisable to improve treatment regimens . In the present study , we describe a strong impact of differential EGFR and EpCAM expression on the clinical outcome of HNSCC patients . Low expression of EGFR combined with high expression of EpCAM correlated with substantially improved survival . We further defined a molecular basis for this disparity in outcome , in which the soluble extracellular domain of EpCAM ( EpEX ) acts as a ligand for EGFR , which induces signaling to extracellular signal–regulated kinase 1/2 ( ERK1/2 ) and AKT . Unlike EGF , which has a concentration-dependent dual function in HNSCCs as an inducer of proliferation or EMT , EpEX induces EGFR-dependent proliferation but represses EGF-mediated EMT through reduction of ERK1/2 phosphorylation and of EMT transcription factors ( EMT-TFs ) Snail , zinc finger E-box-binding homeobox 1 ( ZEB1 ) , and Slug expression . Accordingly , phosphorylation of ERK1/2 and/or expression of Slug further defined HNSCC patients with dismal outcome . Hence , we disclose a regulatory signaling cross talk between EGFR and EpCAM in cancer cells that impacts proliferation and EMT and may thus have substantial repercussions on disease progression and outcome . As such , the EGFR/EpCAM axis represents a novel and promising candidate to further develop patient-tailored therapeutic approaches .
EGFR and EpCAM expression was assessed in serial cryosections of primary HNSCCs within a cohort of the head and neck department at the Ludwig-Maximilians-University ( LMU ) of Munich , Germany ( LMU cohort; n = 180; S1 Table ) . EGFR and EpCAM were expressed in suprabasal layers of normal mucosa and were strongly expressed in primary carcinomas , with a frequent coexpression at the single-cell level ( Fig 1A ) . Expression levels of EGFR and EpCAM were assessed with an immunohistochemistry ( IHC ) scoring ( IHC score 0–300 ) [28] , and EGFR levels served to stratify patients . With the third quartile as the cutoff threshold , EGFRhigh defined patients with reduced OS across all patients ( n = 180 ) ( Fig 1B ) . Chronic infection with high-risk HPV predicts improved outcome of HNSCC patients [29] and is therefore an accepted clinical factor that has recently been implemented in the American Joint Committee on Cancer ( AJCC ) 8th Edition of the TNM classification of patients [30 , 31] . In order to determine the predictive capacity of EGFR independently of HPV status as a potential confounder , OS was calculated for the HPV-negative LMU subcohort ( n = 87 ) . Similar to the entire cohort , EGFRhigh predicted poor survival of HNSCCs in HPV-negative cases ( Fig 1B ) . Stratification of patients from the Cancer Genome Atlas ( TCGA ) HNSCC cohort [9] , using reversed-phase protein atlas data on EGFR expression , confirmed similar clinical outcome and poor OS of EGFRhigh patients , comparable with the LMU cohort ( Fig 1B ) . EpCAM has been described as a sensitive marker for an epithelial differentiation signature in HNSCCs [16] , which prompted us to analyze its expression in relation to EGFR . Besides tumors with a concurrent strong expression of both antigens , HNSCCs with reciprocal expression patterns of EGFR and EpCAM were identified as EGFRhigh/EpCAMlow and EGFRlow/EpCAMhigh ( Fig 1C ) . Subgroups of patients with EGFRhigh/EpCAMlow , EGFRlow/EpCAMhigh , EGFRhigh/EpCAMhigh , and EGFRlow/EpCAMlow expression patterns were classified based on IHC scoring using a cutoff threshold of 150 . EGFRhigh/EpCAMhigh ( n = 72 ) represented 40 . 00% of primary tumors , EGFRlow/EpCAMlow ( n = 31 ) 17 . 20% , and differential EGFRlow/EpCAMhigh ( n = 37 ) and EGFRhigh/EpCAMlow ( n = 40 ) expression 20 . 56% and 22 . 22% , respectively ( Fig 1D ) . OS and disease-free survival ( DFS; median follow-up 23 mo ) were analyzed in EGFR/EpCAM subgroups of patients . EGFRlow/EpCAMhigh patients displayed significantly improved OS and DFS , as compared to all other subgroups ( Fig 1E ) . Comparison of the two opposite subgroups of EGFRlow/EpCAMhigh and EGFRhigh/EpCAMlow patients disclosed OS above 90% and below 10% , respectively . EGFR/EpCAM subgroups of patients were tested for associations with the clinical parameters tumor localization , grading , T stage , N stage , age , and p16 status , which is a surrogate marker for HPV infection [32] . Although statistically not significant ( p = 0 . 055 ) , HPV-positive patients , which associates with improved prognosis [33–35] , were slightly enriched within the subgroup of EGFRlow/EpCAMhigh tumors ( S1A Fig ) . Therefore , OS and DFS ( median follow-up 19 mo ) were analyzed in HPV-negative patients within the LMU cohort by censoring p16-positive and not-determined cases ( n = 87 ) . Repartition of HPV-negative patients into all four EGFR/EpCAM quadrants was similar to the full cohort ( Fig 1F ) and confirmed a significantly improved OS and DFS of EGFRlow/EpCAMhigh over EGFRhigh/EpCAMlow ( Fig 1G ) . Additionally , the subgroup of EGFRhigh/EpCAMlow tumors was comprised of significantly more HNSCCs of the oral cavity , whereas EGFRlow/EpCAMhigh tumors comprised significantly fewer HNSCCs of the oral cavity ( S1B Fig ) . In order to exclude a confounding impact of sublocalizations of tumors on the clinical outcome of the four EGFR/EpCAM patient subgroups , we analyzed the most prominent entity , i . e . , oropharyngeal carcinomas ( n = 105 ) . Quadrant repartition was comparable to the full LMU cohort ( S1C Fig ) . In confirmation of all results so far , EGFRlow/EpCAMhigh patients with oropharyngeal HNSCCs displayed considerably and significantly improved OS and DFS compared to EGFRhigh/EpCAMlow patients ( S1D Fig ) . It must be noted that these differences in outcome remain present even in the case of oropharyngeal HNSCCs with a generally better prognosis . Hence , low expression of EGFR and high expression of EpCAM are markers of improved clinical outcome in HNSCC patients . Induction of EGFR signals through EGF and further ligands results in the activation of major pathways rat sarcoma gene ( Ras ) /rapidly accelerated fibrosarcoma kinase ( Raf ) /MAPK–ERK kinase ( MEK ) /ERK and phosphoinositide-3 ( PI3 ) kinase/AKT . Single and combinations of these pathways differentially promote proliferation , anti-apoptotic features , induction of EMT , and , as reported recently , activation of EpCAM regulated intramembrane proteolysis ( RIP ) [17 , 24 , 36 , 37] . EGF-mediated RIP of EpCAM was reported to lead to the release of the intracellular domain of EpCAM ( EpICD ) that , aside from fostering proliferation [38 , 39] , induces an EMT program in endometrial carcinoma cells [36] . This prompted us to investigate potential functional interactions of EGFR and EpCAM that could provide a molecular rationale for the observed disparity in clinical outcome , including the improved survival of HPV-associated HNSCCs . In order to address whether EGF/EGFR signaling induces EMT in HNSCC cells , FaDu and Kyse30 cells were treated with low and high concentrations of EGF ( 1 . 8 nM and 9 nM ) . EGFlow ( 1 . 8 nM ) corresponded to concentrations reportedly inducing EMT in endometrial carcinoma cells [36] . No signs of morphological changes along the EMT were observed after 72 hr of treatment with EGFlow; however , EGFhigh ( 9 nM ) induced strong loss of cell–cell contact and the adoption of a spindle-shape morphology in FaDu and Kyse30 cells ( Fig 2A ) . Immunofluorescence staining and confocal imaging of the major cell adhesion molecule and EMT target E-cadherin confirmed a shift to a mesenchymal appearance and partial loss of E-cadherin expression in both cell lines ( Fig 2B ) . Reduction of E-cadherin expression , which is considered a hallmark of an EMT shift [3 , 40 , 41] , was also observed in whole-cell extracts of EGFhigh-treated FaDu and Kyse30 cells ( Fig 2C ) . Hence , EGF induces morphological changes reminiscent of EMT and loss of E-cadherin in HNSCC cell lines . EGF treatment of endometrial carcinoma cells was reported to induce an EGFR-dependent RIP of EpCAM , resulting in complete EpEX shedding from the membrane and in release of EpICD , which serves as a nuclear transcriptional inducer of an EMT program [36] . EpICD was furthermore described as a regulator of proliferation and stem cell differentiation [38 , 39 , 42 , 43] . Therefore , we aimed at evaluating a potential contribution of EGFR-mediated RIP of EpCAM to the differential clinical outcome defined in Fig 1 and S1 Fig . EGFR and EpCAM were highly coexpressed at the cell surface of HNSCC/esophageal lines ( FaDu , Cal27 , Kyse30 ) and colon cell line HCT8 ( S2A Fig ) . Membranous colocalization of EGFR and EpCAM was confirmed with dual immunofluorescence staining of FaDu and Cal27 cells ( S2B Fig ) . First , we analyzed the potential of EGF to induce RIP of EpCAM at the level of ectodomain shedding ( EpEX ) , C-terminal fragment ( CTF ) , and EpICD generation ( see scheme in Fig 2D ) . Kyse30 and HCT8 cells stably expressing a human fusion of EpCAM with yellow fluorescence protein ( EpCAM-YFP ) were untreated or treated with EGF ( 9 nM , 72 hr ) . Treatment of Kyse30 and HCT8 with EGF did promote neither EpEX shedding in cell supernatants ( Fig 2E ) nor formation of a membrane-associated CTF-EpCAM-YFP ( Fig 2F ) . EGF treatment also did not foster the formation of EpICD in whole-cell lysates or in cytoplasmic and nuclear extracts of Kyse30 and HCT8 cells ( Fig 2G and 2H ) , so we conclude that EGFR-dependent RIP of EpCAM is not a common process in carcinoma cells . In order to certify that concentrations used by Hsu and colleagues would not induce RIP of EpCAM , despite no effects on EMT in the cell lines studied here , we repeated treatment of HCT8 cells with 1 . 8 nM EGF for 24 hr . Similarly , we could not observe any increase in ectodomain shedding ( S3A Fig ) , CTF formation ( S3B Fig ) , and EpICD release ( S3C Fig ) . To further test effects of EGF on EpCAM expression/RIP in a broader panel of cell lines , cell surface expression of EpCAM was assessed in HNSCCs ( FaDu , Kyse30 , Cal27 , Cal33 ) and in colon ( HCT8 ) , breast ( MCF7 , MDA-MB-231 ) , endometrial ( RL95-2 ) , and prostate ( Du145 ) cancer cells following EGF treatment . Independently of initial expression levels of EGFR and EpCAM , quantification of EGF effects on cell surface expression of EpCAM did not disclose any significant difference ( Fig 2I , S4A–S4C Fig ) . Treatment of Kyse30 , Cal27 , Cal33 , FaDu , HCT8 , and RL95-2 cells with 1 . 8 or 18 nM EGF for 24 hr or a second ligand of EGFR transforming growth factor alpha ( TGFα ) ( 1 . 8 nM , 24 hr ) did not reduce EpCAM cell surface expression ( Fig 2I , 2J , S4B , S4C Fig ) . Treatment of cells with TGFα was conducted to ensure that the lack of EpCAM reduction following activation of EGFR through EGF was not due to requirements for different EGFR ligands in HNSCC cell lines . Treatment with a 10-fold-higher concentration of EGF ( i . e . , 18 nM ) , as compared to Hsu and colleagues [36] , was used in order to rule out dosage effects in HNSCCs as compared to endometrial carcinoma cells . Furthermore , prolonged treatment with 9 nM for 72 hr did not affect EpCAM expression in the cell lines tested , with the exception of a slight induction of cell surface expression of EpCAM in RL95-2 cells ( Fig 2I , right panel ) . Effects of 1 . 8 nM and 18 nM EGF treatment for 24 hr and 9 nM for 72 hr on EpCAM protein expression were analyzed in lysates of FaDu , Cal27 , Cal33 , Kyse30 , MCF7 , HCT8 , Du145 , and RL95-2 cells . Quantification of immunoblot results did reveal an induction of EpCAM expression levels in Du145 cells treated with 1 . 8 and 18 nM EGF and RL95-2 endometrial carcinoma cells with 9 nM EGF for 72 hr , and a slight reduction of EpCAM expression following 1 . 8 and 18 nM EGF treatment of Cal33 ( Fig 2J , S4D and S4E Fig ) . Visualization of EpCAM at the cell surface of FaDu , Cal27 , Kyse30 , RL95-2 , and HCT8 carcinoma cells using immunofluorescence staining with EpEX-specific antibodies and confocal laser scanning microscopy confirmed a retention of EpCAM at the cell surface after treatment with EGF 9 nM for 72 hr ( Fig 2K ) or with EGF 1 . 8 nM or 18 nM for 24 hr ( S3D Fig ) . Finally , in order to assess the impact of EGFR on EMT through regulation of EpCAM , we chose Kyse30 cells , which showed the highest EGFR and EpCAM expression and strong EMT phenotype following EGFhigh treatment . Wild-type Kyse30 , a stable transfectant expressing EpCAM-YFP , two different short hairpin RNA ( shRNA ) EpCAM knockdown clones , and an shRNA control clone were treated with EGF ( 1 . 8 and 9 nM ) . Initial expression levels of EpCAM and EpCAM-YFP were assessed by immunoblotting and confirmed a lack of EpCAM in knockdown clones and exogeneous expression of EpCAM-YFP ( S5A Fig ) . Wild-type Kyse30 cells displayed concentration-dependent EMT , with morphological changes towards spindle-shaped cells lacking cell–cell contact after EGF treatment ( S5B Fig ) . Overexpression of EpCAM-YFP reduced the extent of EMT , whereas knockdown of EpCAM rather promoted a minimal increase in EMT changes observed after EGF treatment and in controls after 48 hr ( S5B Fig ) . Hence , EpCAM is dispensable for EGF-induced EMT , and consequently , RIP of EpCAM to generate EpICD , as an inducer of EMT-specific genes , does not appear as a major determinant of EMT induction by EGF . To further address potential interactions of EGFR and EpCAM , bidirectional coimmunoprecipitation of endogenous proteins was performed . Precipitation of EpCAM in FaDu , Cal27 , and HCT8 cells allowed for the coprecipitation of EGFR and vice versa ( Fig 3A ) . As was repeatedly reported , RIP of EpCAM is a process that occurs in cancer cells [38 , 39 , 44 , 45] and results in the presence of EpEX in the serum of cancer patients [46] . Immunoprecipitation of supernatants of Cal27 , FaDu , Kyse30 , and HCT8 cells with antibodies targeting EpEX confirmed the presence of EpEX ( Fig 3B , left panel ) . In its native form , the EpEX forms heart-shaped homodimers [47] , which was also observed for recombinant EpEX and soluble EpEX in cell culture supernatants of HCT8 cells [46] . Separation of immunoprecipitated EpEX from Cal27 , FaDu , Kyse30 , and HCT8 supernatants under nonreducing , native conditions confirmed the presence of EpEX mono- , di- , and oligomers ( Fig 3B , right panel ) . To test a potential binding of EpEX to EGFR , EpEX was fused to the constant region of human immunoglobulin 1 as described [48] , to generate EpEX-Fc ( S6A Fig ) . EpEX-Fc was expressed in human embryonic kidney 293 ( HEK293 ) cells and enriched from supernatants with high purity ( S6B Fig ) . Specificity , the oligomeric state and N-glycosylation of recombinant EpEX-Fc were confirmed ( S6C–S6E Fig ) . Oligomerization through the fragment crystallizable region ( Fc ) mimics the dimeric/oligomeric state of EpEX , with mono- , di- , and oligomers as observed in cell culture supernatants ( See Fig 3B and [46] ) . EpEX-Fc and Fc served as baits to isolate interacting proteins from FaDu and Cal27 cell lysates . EpEX-Fc , but not Fc , interacted with full-length EGFR , suggesting that EpEX-Fc can act as a ligand for EGFR ( Fig 3C ) . To further determine whether EpEX directly binds to the extracellular domain of EGFR ( EGFRex ) , cross-linking experiments were performed with purified recombinant EGFRex and EpEX . Cross-linking of EGFRex resulted in the generation of EGFRex dimers , which was further increased through addition of EGF ( Fig 3D ) . Cross-linking of EpEX induced dimerization as described [47] . Incubation of EGFRex and EpEX induced the formation of a protein complex of approximately 120 kDa , corresponding to a 1:1 stoichiometry of EGFRex and EpEX and a second , weaker band of approximately 155 kDa , corresponding to a 1:2 stoichiometry of EGFRex and EpEX ( Fig 3D; lane 6 ) . The intensity of the approximately 120 kDa band was reduced upon further addition of EGF , and the second band of approximately 155 kDa disappeared ( Fig 3D; lane 7 ) , indicating a competitive binding of EpEX and EGF to EGFRex . Next , we assessed whether treatment of intact cells with EpEX-Fc as a ligand induces classical EGFR signaling pathways resulting in ERK1/2 and AKT phosphorylation . Treatment with EpEX-Fc ( 10 nM ) induced phosphorylation of ERK1/2 in serum-starved FaDu , Cal27 , and Kyse30 cells within minutes , which was inferior in intensity as compared to EGF treatment ( 1 . 8 nM ) ( Fig 3E ) . EpEX-Fc-induced activation of AKT at the indicated concentrations was similar to EGF , although time points of maximal induction varied between both ligands ( Fig 3F ) . Treatment with therapeutic anti-EGFR antibody Cetuximab completely blocked EpEX-Fc- and EGF-mediated activation of ERK1/2 and AKT ( Fig 3E and 3F ) , demonstrating an EGFR dependency of signaling . Activation of ERK1/2 and AKT phosphorylation by EpEX-Fc and EGF was further validated by immunofluorescence staining of FaDu and Cal27 cells . Imaging of ERK1/2 phosphorylation confirmed higher activation through EGF than EpEX-Fc , whereas AKT activation by EGF or EpEX-Fc was similar ( Fig 3G ) . Owing to differential voltage adjustments , comparison across cell lines was not feasible . Furthermore , activation of ERK1/2 through EpEX-Fc and EGF in FaDu , Cal27 , and Kyse30 cells was entirely blocked by an inhibitor of the upstream kinase MEK1 ( AZD6244 ) , whereas tyrosine kinase inhibitor ( TKI ) AG1478 entirely ( Cal27 ) or partially ( FaDu , Kyse30 ) blocked ERK1/2 activation by EpEX-Fc and EGF ( Fig 3H ) . Hence , EpEX-Fc specifically activates phosphorylation of ERK1/2 through induction of EGFR signaling and MEK activity . A requirement for EGFR expression to induce ERK1/2 by EpEX-Fc was analyzed in HEK293 cells , which do not express detectable amounts of EGFR [49] . Treatment of HEK293 cells with EpEX-Fc or EGF did not result in activation of ERK1/2 ( Fig 3I ) . However , transient expression of EGFR restored signaling of EGF and EpEX-Fc to activate ERK1/2 , confirming a specificity for EGFR for the observed effects of EpEX-Fc ( Fig 3I ) . A possible involvement of full-length EpCAM in ERK1/2 activation by EpEX-Fc was addressed in clustered regularly interspaced short palindromic repeat/CRISPR-associated 9 ( CRISPR-Cas9 ) EPCAM-knockout HCT8 cell lines [48] . HCT8 knockout cells entirely lacked EpCAM expression but retained EGFR levels comparable to wild-type and CRISPR-Cas9 control cell lines ( Fig 3J ) . Treatment of EpCAM knockout with EpEX-Fc induced ERK1/2 phosphorylation within minutes ( Fig 3K ) , demonstrating a requirement for EpEX but not for full-length EpCAM for ERK1/2 induction . Hence , EpEX-Fc is a ligand that induces specific activation of classical EGFR signaling pathways . EpEX induces classical EGFR signaling pathways , which activate proliferation [22] but also promote EMT-characteristic phenotypic changes [50–53] . Therefore , we first compared effects of EGF and EpEX treatment on proliferation . Effects of EGF and EpEX-Fc on cell proliferation were assessed following treatment of FaDu and Kyse30 cells after 24 , 48 , and 72 hr . In order to delineate EGF and EpEX-Fc effects distinct from further growth factors , all cell lines were serum starved and maintained in the absence of serum throughout the experiment . Treatment of FaDu with low-dose EGF ( 1 . 8 nM ) and high-dose EpEX ( 10 nM ) induced a 2- and 1 . 5-fold increase in cell numbers , respectively , after 72 hr , whereas high-dose EGF ( 9 nM ) did not induce proliferation ( Fig 4A ) . EpEX-induced proliferation was entirely blocked upon cotreatment with Cetuximab ( Fig 4A ) . Treatment with low-dose EGF , high-dose EGF , or high-dose EpEX-Fc ( 10 nM ) induced a 2 . 5- , 2 . 2- , and 2-fold increase of Kyse30 cells , respectively , after 72 hr , whereas low-dose EpEX-Fc did not have significant mitogenic effect ( Fig 4A ) . Similarly , EpEX-Fc-induced proliferation of serum-starved cells was blocked upon cotreatment with Cetuximab ( Fig 4A ) . Proliferation-inducing effects of high-dose EpEX were additionally assessed through bromodeoxyuridine ( BrdU ) incorporation following treatment of serum-starved Kyse30 and FaDu cells . In line with cell counting results , treatment with high-dose EpEX ( 10 nM ) induced a significant 50% and 30% increase in BrdU uptake after 72 hr in Kyse30 and FaDu cells , respectively . BrdU incorporation induced by EpEX was blocked by cotreatment with Cetuximab ( Fig 4B ) . Next , effects of high-dose EGF ( 9 nM ) and EpEX ( 10 nM ) on cell migration were assessed in scratch assays . EGF treatment at concentrations inducing EMT resulted in enhanced relative migration of serum-starved FaDu and Kyse30 cells , which was significantly reduced by cotreatment with EpEX-Fc and by Cetuximab ( Fig 4C ) . Relative migration was quantified and corrected for proliferation rates , demonstrating substantially increased migration following EGFhigh treatment and inhibitory effects of Cetuximab and EpEX-Fc ( Fig 4D ) . Thus , EGF has dual capacities to induce proliferation and migration in HNSCC cell lines in a dosage-dependent manner , whereas EpEX-Fc induces proliferation at high concentration and counteracts EGF-induced migration . Since EpEX partially inhibited EGF-induced migration , we next addressed whether this is associated with a capacity of EpEX to generally repress EGF-dependent EMT in HNSCC cell lines . Serum-starved FaDu , Kyse30 , and Cal27 cells were treated with an increasing dose of EpEX-Fc ( 1–50 nM ) or EGF at 1 . 8 and 9 nM for 48 to 72 hr . Treatment with an increasing amount of EpEX-Fc had no detectable effect on epithelial morphology ( Fig 5A and S7A Fig ) . In contrast , treatment of FaDu and Kyse30 cells with high-dose EGF ( 9 nM ) , but not low dose ( EGF 1 . 8 nM ) , reproducibly induced EMT with the generation of spindle-shaped cells and loss of cell–cell contact ( Fig 5A ) . EMT induced by high-dose EGF was blocked upon simultaneous treatment with EpEX-Fc in a dose-dependent manner ( Fig 5A ) . Treatment of Cal27 cells under the same conditions or with 2-fold-higher EGF concentration ( 18 nM ) did induce neither EMT-related phenotypic changes nor loss of E-cadherin , which points at differences in cellular response ( S7A and S7B Fig ) . Next , regulation of E-cadherin , N-cadherin , vimentin , and EMT-TFs Snail , Zeb1 , Slug , and Twist was assessed at the transcriptional levels after 6 and 72 hr following treatment . Treatment of cells with control media , Fc , or EpEX-Fc ( 10 nM ) did not regulate the expression of any of the genes analyzed . Treatment of Kyse30 cells with EGFhigh resulted in a transient up-regulation of vimentin mRNA after 6 hr , which was reduced to background after 72 hr ( S7C Fig ) . E-cadherin , N-cadherin , and Twist expression was unaffected . Treatment of FaDu cells under the same conditions induced an early induction of N-cadherin after 6 hr that persisted until 72 hr ( S7C Fig ) and a decrease of E-cadherin and increase of Twist after 72 hr ( S7C Fig ) . Inductions and repressions of gene expression following EGF treatment were all counteracted by cotreatment with high-dose EpEX . Treatment with EGF 9 nM resulted in substantial induction of Snail , Zeb1 , and Slug in FaDu and Kyse30 cells at 6 hr and was maintained until 72 hr ( Fig 5B ) . Simultaneous treatment of both cell lines with EGF ( 9 nM ) and EpEX-Fc ( 10 nM ) repressed Snail , Zeb1 , and Slug induction ( Fig 5B ) . Thus , EGFhigh induces EMT changes with the recurrent expression of the EMT-TFs Snail , ZEB1 , and Slug and partial loss of E-cadherin , whereas soluble EpEX-Fc counteracts EMT via repression of the abovementioned EMT-TF activation . So far , we have shown that EGF and EpEX-Fc both induce ERK1/2 and AKT phosphorylation , however , with differing intensities and cellular outcome . In order to shed light on signaling pathways implicated in EGF-dependent EMT and on mechanisms of EpEX-Fc-mediated inhibition , EMT-responsive FaDu and Kyse30 cells were treated with high-dose EGF in combination with Cetuximab , Erlotinib ( TKI ) , AZD6244 ( MEK1 inhibitor ) , and MK2206 ( pan-AKT inhibitor ) . High-dose EGF induced pronounced EMT , which was completely blocked by Cetuximab , Erlotinib , and AZD6244 but not by AKT-inhibitor MK2206 in both cell lines , demonstrating that induction of ERK1/2 but not of AKT integrates EGF signals to mediate EMT ( Fig 6A ) . Since ERK1/2 was determined as the major mediator of EGF-induced EMT , we assessed potential differences in ERK1/2 activation in EMT-responsive FaDu versus nonresponsive Cal27 cells . Both cell lines were serum starved and treated with high-dose EGF ( 9 nM ) , and activating phosphorylation of ERK1/2 was assessed by immunoblotting after 10 , 60 , and 180 min . EGF treatment of FaDu cells induced a rapid and strong activation of ERK1/2 , whereas Cal27 cells were only moderately and more transiently activated ( Fig 6B ) . Signal quantification showed that the integrated pERK1/2 signal strength , incorporating intensity and duration , was 3-fold higher in FaDu cells than Cal27 cells ( Fig 6C ) . Thus , integrated signal strength of pERK1/2 after EGF treatment represents a major switch in decision-making towards EMT induction . Next , we assessed whether differential effects of EGF and EpEX-Fc on cell fate , i . e . , EMT and proliferation , were related to the integrated signal strength of ERK1/2 . FaDu cells were kept untreated or were treated with high-dose EGF ( 9 nM ) or EpEX-Fc ( 10 nM ) , and phosphorylation levels of ERK1/2 were analyzed over time . ERK1/2 activation after EGF treatment was higher than with EpEX-Fc ( Fig 6D ) . This translated in significantly enhanced pERK1/2 signal strength at all time points of treatment , with high-dose EGF compared to high-dose EpEX-Fc , and a 3-fold-enhanced integrated pERK1/2 signal strength ( Fig 6E ) . In contrast , low-dose EGF ( 1 . 8 nM ) and high-dose EpEX-FC ( 10 nM ) , which both trigger proliferation , induced a comparable average integrated pERK1/2 signal strength that was only significantly higher at late time points of EGF treatment ( Fig 6F and 6G ) . Hence , high-dose EGF , but not high-dose EpEX-Fc , induces EMT through enhanced ERK1/2 activation intensity and duration . Following , we addressed whether modulation of ERK1/2 activation is underlying the ability of EpEX-Fc to inhibit EMT induced by EGF . EMT-responsive FaDu cells were treated with high-dose EGF , high-dose EpEX-Fc , or a combination of both , and ERK1/2 phosphorylation was analyzed by immunofluorescence staining . Treatment with high-dose EGF induced a strong activation of pERK1/2 , whereas activation by EpEX-Fc was more moderate ( Fig 6H ) . Combinatorial treatment with EGF and EpEX-Fc resulted in reduced ERK1/2 activation , compared to only EGF ( Fig 6H ) . Quantification of pERK1/2 disclosed a 3-fold-reduced ERK1/2 activation by EpEX-Fc compared to EGF and a 2-fold reduction of activity upon combinatorial treatment with EGF and EpEX-Fc , compared to strong induction by EGF alone ( Fig 6I ) . Thus , EpEX-Fc potently inhibits EGF-dependent EMT through modulation of the ERK1/2 activation . EGFR and EpCAM levels correlated with the clinical outcome of HNSCCs ( see Fig 1 and S1 Fig ) . In order to address the impact of EGFR and EpCAM expression on tumor cell behavior at the mechanistic level , we established an in vitro mimic of the clinical situation . Kyse30 cells were treated with an EGFR-specific small interfering RNA ( siRNA ) pool , an EpCAM-specific shRNA , and the cognate controls . Double knockdown of EGFR and EpCAM was performed in EpCAM-knockdown Kyse30 cells with an EGFR-specific siRNA pool . EGFR and EpCAM expression levels were confirmed by immunoblotting ( Fig 7A ) . Based on these expression levels , EGFR-knockdown Kyse30 cells mimicked quadrant 1 of the clinical cohort ( EGFRlow/EpCAMhigh ) . Wild-type Kyse30 cells ( EGFRhigh/EpCAMhigh ) , EpCAM-knockdown Kyse30 cells ( EGFRhigh/EpCAMlow ) , and double-knockdown Kyse30 cells ( EGFRlow/EpCAMlow ) mimicked quadrant 2 , 3 , and 4 , respectively . Next , all cell lines were treated with EGFlow ( 1 . 8 nM ) and EGFhigh ( 9 nM ) , and induction of EMT was assessed based on the cell morphology at 72 hr . In EGFRhigh/EpCAMhigh wild-type cells ( Q2 equivalent ) , we confirmed the induction of EMT following treatment with EGFhigh but not EGFlow ( Fig 7B ) . Knockdown of EGFR in Kyse30 cells ( EGFRlow/EpCAMhigh , Q1 equivalent ) abolished EMT induction at both EGF concentrations . Double knockdown of EGFR and EpCAM ( EGFRlow/EpCAMlow , Q4 equivalent ) also resulted in a lack of EMT induction following EGF treatment ( Fig 7B ) . Knockdown of EpCAM in the presence of high levels of EGFR ( EGFRhigh/EpCAMlow , Q3 equivalent ) resulted in a 5-fold-reduced level of EGF required for the induction of EMT , with strong EMT induction at EGFlow concentrations ( Fig 7B ) . We have determined modulation of ERK1/2 activation strength as a major molecular switch to regulate proliferation versus EMT ( see Fig 6 ) . Therefore , serum-starved Kyse30 cell variants representing clinical quadrants 1–4 were treated with EGFlow ( 1 . 8 nM ) , and activating phosphorylation of ERK1/2 was assessed by immunoblotting . In EGFRhigh/EpCAMhigh wild-type cells ( Q2 equivalent ) , EGFlow induced intermediate ERK1/2 phosphorylation , which was strongly reduced in EGFR-knockdown Kyse30 cells ( EGFRlow/EpCAMhigh , Q1 equivalent ) ( Fig 7C ) . Double knockdown of EGFR and EpCAM ( EGFRlow/EpCAMlow , Q4 equivalent ) entirely abolished ERK1/2 activation ( Fig 7C ) . Knockdown of EpCAM in the presence of high levels of EGFR ( EGFRhigh/EpCAMlow , Q3 equivalent ) resulted in enhanced ERK1/2 activation ( Fig 7C ) . This increased activation of ERK1/2 in EGFRhigh/EpCAMlow Kyse30 cells was paralleled by induction of EMT-TF Slug following EGFlow treatment , whereas all other cells variants did not induce mRNA expression of Slug under these conditions ( Fig 7D ) . Treatment of all Kyse30 cell variants with EGFhigh induced Slug expression in EGFRhigh/EpCAMhigh wild-type cells ( Q2 equivalent ) , which was significantly reduced following EGFR knockdown ( Q1 and 4 equivalents ) and enhanced following EpCAM knockdown ( Q3 equivalent ) ( Fig 7D ) . Accordingly , EGFhigh treatment induced a higher relative migration rate in quadrant 2 and 3 mimics ( wild-type and EpCAM-knockdown Kyse30 cells ) than in quadrant 1 and 4 mimics ( EGFR-knockdown and EGFR/EpCAM-double-knockdown Kyse30 cells ) ( Fig 7E ) . Hence , loss of EGFR abolished—whereas loss of EpCAM facilitated—EGF-induced EMT through modulation of ERK activation and Slug expression . These differences further impacted the cellular behavior , with increased migration rates in quadrant 2 and 3 mimics . As reported for breast cancer , high ERK1/2 activity results in enhanced transcription and expression of Slug to foster cell migration [55] . Slug in turn was the only EMT-TF that was up-regulated in the single-cell transcriptomic pEMT-signature of HNSCCs ( termed SNAIL 2 in that publication ) [16] and appears as an early EMT-inducing factor compared to other EMT-TFs [56] . Based on these reports and on the findings from our own in vitro study , we addressed whether ERK1/2 and Slug levels in vivo reflected the abovementioned regulation mechanisms in HNSCCs . EGFRlow/EpCAMhigh ( n = 37 ) and EGFRhigh/EpCAMlow specimens ( n = 39 ) were stained for the expression of pERK1/2 and Slug in consecutive sections . EGFRhigh/EpCAMlow specimens were characterized by high average pERK1/2 and Slug expression , whereas EGFRlow/EpCAMhigh specimens displayed low to moderate expression of both antigens ( Fig 8A ) . Quantification using IHC scoring revealed an average 2 . 14-fold-enhanced level of ERK1/2 activation and an average 2 . 1-fold increase in Slug expression in EGFRhigh/EpCAMlow tumors compared to EGFRlow/EpCAMhigh tumors ( Fig 8B ) . In order to test overall correlations of pERK1/2 and Slug , consecutive sections of all available patients’ specimens of the HNSCC cohort ( n = 169/180 ) were stained for pERK1/2 and Slug expression . Expression levels of both proteins were quantified using the IHC scoring system . Spearman correlation analysis of IHC scores confirmed a robust positive correlation of pERK1/2 and Slug expression in the HNSCC cohort ( Fig 8C , r = 0 . 5784 , p < 0 . 0001 ) . Concurrent expression of pERK1/2 and Slug at the edges of tumor areas was observed ( Fig 8A ) and corroborated the preferential positioning of EMT cells at the leading edges of HNSCCs [16] . Next , expression levels of pERK1/2 and Slug were tested for their prognostic value . To do so , patients with EGFR and EpCAM IHC scores below 125 or above 175 were included . High expression of pERK1/2 and/or Slug ( cutoff threshold IHC score median ) defined HNSCCs with poor OS ( n = 98 ) and DFS ( n = 97 ) ( Fig 8D ) . Hence , EGF/EGFR/pERK1/2/Slug represents a signaling axis that impacts cell differentiation towards EMT and defines HNSCC patients with poor clinical performance .
HNSCC patients have dismal clinical outcome , with overall death rates above 55% at 5 y [2] . Recent publications disclosed an outstandingly high genetic and cellular heterogeneity of HNSCCs at the inter- and intratumoral level that may account for therapy resistance and poor clinical performance [8–11 , 16] . Especially , shifts towards mesenchymal phenotypes of carcinoma cells emerged as central to metastases formation , therapy resistance , and , ultimately , poor prognosis in several carcinoma entities [4 , 5 , 57–60] , including HNSCCs [16] . EGFR is currently the major therapeutic target in palliative treatment regimens for recurrent and metastatic HNSCCs and colon and lung cancer [17–20 , 26 , 61–65] , with signaling capacities to induce a broad range of cellular outcomes such as proliferation and EMT [15 , 24–27 , 53 , 65–68] . EpCAM in turn has been described as a cell adhesion molecule and , more recently , as a signaling membrane protein that regulates cell proliferation and differentiation in cancer and stem cells [38 , 39 , 43 , 69–72] . EpCAM defines the degree of epithelial differentiation of HNSCCs , and its expression at the single cell RNA-sequencing level was opposite to genes composing a pEMT signature including vimentin and Slug [16] . Loss of EpCAM was observed during EMT [73 , 74] , but a causal role in EMT is not fully understood [54 , 73 , 75–79] . Recently , Hsu and colleagues provided a link between EGF-induced EMT and RIP of EpCAM in the endometrial carcinoma cell line RL95-2 . In their model , EGF/EGFR signaling induced a complete loss of EpCAM because of cleavage that released EpICD . Together with lymphoid enhancer-binding factor 1 ( Lef-1 ) , EpICD then served as an inductor of EMT upon nuclear translocation and activation of an EMT gene program [36] . Although the presented mechanism would theoretically provide a compelling molecular basis for EGF/EGFR-dependent EMT and concurrent loss of EpCAM , unexpected results from the use of γ-secretase inhibitors raised questions on the actual molecular mechanism [36 , 80] . In the present study , RIP of EpCAM through EGF/EGFR signaling could neither be observed in an array of carcinoma cell lines nor be reproduced in RL95-2 endometrial carcinoma cells , independently of time points and EGF concentrations used ( Fig 2 ) . We conclude that EGF-induced RIP of EpCAM is neither a common nor a frequent mechanism in carcinoma cell differentiation along the EMT . The molecular background for such contradicting findings on the role ( s ) of EpCAM in EMT regulation has , to the best of our knowledge , not been elucidated yet . In accordance with such discrepancies , high expression of EpCAM is frequently associated with poor clinical outcome of breast , colorectal , pancreatic , and nasopharyngeal carcinomas and ovarian and bladder cancers [79 , 81–89] but with a good prognosis of colonic , gastric , and renal cancer [90–92] and of HNSCCs , as shown in the present study . Alternatively to Hsu and colleagues , we describe a novel functional cross talk of EGFR and EpCAM that regulates proliferation and EMT ( Fig 9 ) , which provides a molecular basis for differences in clinical outcome of subgroups of HNSCC patients . EGFRhigh HNSCCs were associated with poor OS in our cohort and in the HNSCC TCGA cohort [9] , including both HPV-negative subcohorts . Combination of EGFR and EpCAM as biomarkers for HNSCCs demonstrated that EGFRlow/EpCAMhigh HNSCCs were characterized by improved OS and DFS , whereas EGFRhigh/EpCAMlow tumors were characterized by strongly reduced OS and DFS ( Fig 1 ) . A tendency of an enrichment of oropharyngeal carcinoma associated with chronic HPV infection within the EGFRlow/EpCAMhigh group conforms with better survival [2 , 29 , 32 , 93–96] . However , analyses of HPV-negative patients within the LMU cohort confirmed results of the full cohort , arguing that the observed disparities in clinical outcome were not dependent upon the HPV status . Furthermore , effects were not related to differing sublocalizations of HNSCC specimens in our cohort . Analyses of the more abundant group of patients of oropharyngeal carcinomas , which are generally associated with improved survival , still demonstrated a significantly improved OS and DFS of EGFRlow/EpCAMhigh versus EGFRhigh/EpCAMlow tumors . Hence , an EGFR/EpCAM cross talk might generally be instrumental in the regulation of malignant differentiation in HNSCCs and thus impact clinical outcome . Functionally , we demonstrate that activation of EGFR through EGF in HNSCC cells results in a dosage-dependent dual capacity to activate proliferation or EMT through differential ERK1/2 activation strength and duration . Intermediate ERK1/2 activation correlated with induction of proliferation , whereas strong and sustained ERK1/2 activation was required to induce EMT ( Fig 9 ) . This is in accordance with reported differential integration of ERK signaling to modulate cell fates in PC12 and 3T3 cells [97 , 98] . Inhibitors of AKT did not impact EGF-induced EMT , defining ERK1/2 as a major integrator of EGFR-mediated signals into proliferation or EMT . In line with a role of ERK1/2 in EGF-mediated EMT , nonresponsive cells were characterized by substantially lower ERK1/2 induction rates . A central role of ERK1/2 , rather than AKT , in EGF-induced EMT induction conforms with earlier reporting [50–52 , 99] but is in contradiction to the published role of AKT in prostate cancer cell lines [53] , nasopharynx carcinoma [79] , and mammary MCF7 cells [100] . Direct involvement of ERK1/2 in EMT regulation has been reported to function through transcriptional silencing of E-cadherin expression [52] . Despite a loss of E-cadherin protein expression in both HNSCC lines FaDu and Kyse30 following EGF treatment , E-cadherin mRNA levels remained unaffected in Kyse30 cells , suggesting additional posttranslational effects of EGF/EGFR/ERK1/2 on E-cadherin expression . Additionally , EGF/EGFR/ERK1/2 robustly affected the expression of Snail , Zeb1 , and Slug in all cell lines addressed , but not as consistently Twist , N-cadherin , and vimentin ( Figs 2 , 4 and S7 Fig ) . Selective regulation of EMT-associated genes has been reported and contributes to the fluxionary and gradual nature of EMT in cancer [4 , 60 , 101] . Our results further provide a molecular mechanism in support of ERK1/2 as potential target ( s ) in HNSCCs ( Figs 3–8 ) , the inhibition of which was reported to enhance antitumor therapy in clinical approaches [102 , 103] . Induction of EMT through EGF/EGFR/ERK1/2 entailed functional consequences , as cells were equipped with enhanced migration capacity and might thereby impact local and distant tumor cell dissemination . Induction of migration and invasion through EMT might generate multifocal nests of therapy-resistant cells that have delaminated from the primary tumor , evade surgery , and could give rise to subsequent relapse . Accordingly , EMT was implicated in the generation of tumor cells with stem-like capacity ( CSCs ) , which represent the source of tumor recurrences and metastases [6 , 15 , 104] . Phenotypic plasticity along the EMT allows subpopulations of HNSCC-CSC to switch between epithelial/proliferative and mesenchymal/migratory/invasive states [105] . Post-EMT HNSCC-CSC , characterized as CD44high/EpCAMlow/neg . /CD24pos . , have enhanced resistance towards therapeutic drugs [106] . In accordance with a central role for pERK1/2 in induction of EMT in HNSCCs , we demonstrate a correlation of pERK1/2 with the EMT-TF Slug within clinical samples and with substantially decreased OS and DFS ( Fig 8 ) . Hence , the elucidation of a novel EGFR/EpCAM cross talk in HNSCCs additionally defined pERK1/2 and Slug as biomarkers for the stratification of HNSCC patients . Induction of Slug through the effect of pERK1/2 has been reported for breast cancer migration [55] , and Slug emerged as the only EMT-TF significantly associated with a pEMT signature in single cells of HNSCCs [16] . In analogy to the published intratumoral localization of pEMT-signature genes LAMB3 and LAMC2 [16] , pERK1/2 and especially Slug were frequently expressed in cells of the leading edge of tumor areas in our cohort . Thus , modulation of differential strength and quality of EGFR downstream signaling by EGF and EpEX might considerably impact key processes of local invasion and eventually recurrence . Increased activation of EGFR at the edges of tumor areas to induce EMT might be fulfilled by cancer-associated fibroblasts , myeloid-derived cells [107] , or , as recently reported , endothelial cells secreting EGF and inducing EMT- and stem-like properties in HNSCCs [108] . Using a cellular system , we recapitulated in vitro the distribution of EGFR and EpCAM expression observed in clinical samples . By doing so , we corroborated a regulatory potential of EGFR and EpCAM in the induction of EMT in HNSCC cells . Knockdown of EGFR expression inhibited EMT induction by EGF and was paralleled by a lack of activation of ERK1/2 and Slug and by reduced migration , hence demonstrating a central role of EGFR . Knockdown of EpCAM expression facilitated EGF-mediated induction of EMT , with EGF concentrations required for activation of EMT , pERK1/2 , and Slug that were reduced 5-fold . We therefore suggest that EGFR and EpCAM levels in vivo impact the strength of ERK and Slug activation through stimulation of EGFR . Reduced levels of EpCAM facilitate induction of EMT through a release from the competitive effects of EpEX on EGF and a resulting decrease in EGF concentrations required for strong ERK1/2 activation towards EMT . Hence , EpCAM emerges not only as a surrogate marker for epithelial differentiation of HNSCCs [16] but also as a modulator of epithelial differentiation with functional implication in tumors and stem cells [70] . High expression of EpCAM can be positive for treatment outcome based on its role in cell–cell adhesion [69 , 109] , in proliferation [38 , 39] , in endomesodermal differentiation [70] , and , as first described here , as a regulatory molecular determinant of tumor cell differentiation along the EMT axis through modulation of EGFR-dependent pERK1/2 . Furthermore , we provide evidence that the soluble ectodomain EpEX , which is produced upon RIP of EpCAM [39 , 48 , 110] including HNSCC cell lines ( Fig 3 ) , is a regulatory ligand of EGFR that induces ERK1/2 and AKT signaling ( Fig 9 ) . The definition of EpEX as a ligand for EGFR is in line with recent reports on the activation of EGFR signaling after treatment with EpEX in mouse embryonic fibroblasts and in colon carcinoma cell lines [71 , 111] . In colon carcinoma cells , EpEX induced mild proliferation and regulated proteolysis of intact EpCAM molecules through the activation of ADAM17 and γ-secretase [111] . However , experimental evidence for the binding of EpEX to EGFR was lacking . Additionally , activation of migration of colon carcinoma cells through EpEX is in contradiction with our findings in Kyse30 and FaDu HNSCC cell lines . Serum levels of EpEX in tumor patients revealed low [46 , 110 , 112–114] but represent systemic levels , which suggests substantially higher intratumoral levels at the interface of tumor cells , where EpEX is actively shed [115] . Hence , production of EpEX by carcinoma cells could locally impact the regulation of EGFR-dependent proliferation and EMT . Activation of signaling by EpEX was specific , as it depended on the expression of EGFR and was blocked by Cetuximab , TKIs , and ERK- and AKT-specific inhibitors . Unlike EGF , EpEX induces EGFR and ERK1/2 less potently and eventually promotes mild proliferation rather than EMT . Cotreatment of HNSCC cells with EpEX led to a dose-dependent repression of EGF-mediated EMT , which was accompanied by reduction of ERK1/2 activation and Snail , Zeb1 , and Slug transcription . We suggest that EpEX directly binds EGFR , as shown by cross-linking of recombinant proteins , but activates ERK1/2 less efficiently than EGF . Thereby , EGF and EpEX compete for binding to EGFRex , and EpEX modulates the strength of EGFR signaling to pERK1/2/Slug , repressing EMT in cancer cells ( Figs 5 and 9 ) . Inhibition of EGF-mediated ERK activation by full-length EpCAM has been reported in carcinoma cells , including breast cancer lines [73] . Down-regulation of EpCAM resulted in increased ERK activity following treatment with EGF and enhanced Slug expression . Oppositely , forced expression of EpCAM was shown to reduce ERK activation and Slug expression [73] . In concordance , knockdown of EpCAM in Kyse30 cells resulted in enhanced ERK1/2 activation by EGF in our in vitro experiments . A priori , our findings of an activating effect of EpEX on ERK activation are contradicting the report by Sankpal and colleagues [73] . However , our findings demonstrate that EpEX can compete with the strong activation of ERK , Slug , and eventually EMT following activation of EGFR by EGF ( Figs 5–8 ) . Hence , in addition to an inhibitory role of EpEX on the strong activation of ERK1/2 , Snail , Zeb1 , and Slug by EGF , EpEX has itself an intermediately activating effect on ERK activation in serum-starved HNSCC lines that results in proliferation . Work by Lin and colleagues in colon cancer cells demonstrated a function of EpCAM in the activation of pluripotency genes and EMT regulators [42] , which is contradictory to our findings . Once again , cellular systems and especially the molecules addressed are differing . Whereas Lin and colleagues concentrated on EpCAM in the regulation of transcription factors , our study addresses the cross talk of EGFR with EpCAM—more specifically , with the soluble ectodomain EpEX . From our cellular system , we conclude that EpEX binding to EGFR does not induce EMT-TFs or EMT but can induce proliferation and compete with EGF to hamper EMT induction . Thus , a cross-regulatory role of EGFR and EpCAM appears as a general regulatory mechanism that is instrumental in carcinoma cells and includes negative and positive feedback loops to control ERK1/2 and , ultimately , cell fate . In summary , we describe a novel molecular cross talk of EGFR and EpCAM that provides a rationale for substantial differences in survival of HNSCC patients . Stratification of HNSCC patients based on EGFR , EpCAM , pERK1/2 , and Slug expression levels represents a promising tool to define patients at increased risk of clinical relapse , with the future aim to improve therapeutic intervention including EGFR and EpCAM as targets .
The LMU of Munich , Germany , HNSCC cohort included tumor specimens from 180 patients . Distant normal mucosa was available for 87 patients . Clinical samples were obtained after written informed consent during routine surgery , based on the approval by the ethics committee of the local medical faculties ( Ethikkommission der Medizinischen Fakultät der Ludwig-Maximilians-Universität; #087–03; #197–11; #426–11 ) and in compliance with the WMA Declaration of Helsinki and the Department of Health and Human Services Belmont Report . FaDu , Kyse30 , Cal27 , Cal33 , HCT8 , RL95-2 , HEK293 , Du145 , MCF7 , and MDA-MB-231 cell lines were obtained from ATCC and DSMZ and were confirmed by STR typing ( Helmholtz Center , Munich , Germany ) . Kyse30-shRNA lines were described in [54] . Kyse30 and HCT8 cells were stably transfected with EpCAM-YFP fusion in the 141-pCAG-3SIP vector as described [39 , 48] . Cells were maintained in RPMI 1640 or DMEM , 10% FCS , 1% penicillin/streptomycin , in a 5% CO2 atmosphere at 37 °C . Treatment with EGF ( PromoCell PromoKine , Heidelberg , Germany ) , EpEX-Fc , Cetuximab ( Merck Serono , Darmstadt , Germany , 10 μg/mL ) , AZD6244 ( Selleckchem , Munich , Germany; 1 μM ) , AG1478 ( Selleckchem , 10 μM ) , Erlotinib ( Selleckchem , 1 μM ) , MK2206 ( Selleckchem , 1 μM ) , ß-lactone ( Santa Cruz , Heidelberg , Germany , 50 μM ) was conducted in medium . Recombinant EpEX-Fc was produced as described [48] . Briefly , HEK293 cells were stably transfected with human EpEX-Fc fusion in the 141-pCAG-3SIP vector and cultured in ultralow IgG DMEM for EpEX-Fc purification . EpEX-Fc was purified from supernatant of transfected cells after 3–5 d of culture according to the protocol by Savas and colleagues [116] . Recombinant Fc was purchased from Jackson ImmunoResearch , Baltimore , MD , United States . Migration was assessed as described [54] . Quantification of scratches was performed using ImageJ and MRI wound healing tool . Relative migration was adjusted for proliferation rates . For cell proliferation , 1 × 105 cells were plated in 12-well plates before treatment . At indicated time points , cells were counted in an EVE automatic cell counter ( NanoEntek , VWR , Munich , Germany ) . BrdU proliferation assay was performed with the Cell Proliferation ELISA BrdU kit ( Roche , Penzberg , Germany ) following the manufacturer’s protocol . Cells were plated at a density of 5 , 000 cells/well into a 96-well plate before treatment . After serum starvation , cells were treated as indicated in figure legends for 72 hr . BrdU ( 10 μM ) was then added to the cells and incubated for 12 hr . BrdU was detected with a peroxidase-labeled anti-BrdU antibody , and substrate turnover was measured at 405 nm on an ELISA reader . On-TARGETplus siRNA pools specific for EGFR and a nontargeting pool ( control ) from DharmaFECT were used ( Dharmacon , Lafayette , CO , US ) . Kyse30 cells were transfected with 50 nM final siRNA concentration using Dharmafect reagent 1 for 24 hr . Media were then changed to normal medium without siRNA and Dharmafect , and cells were subjected to further assays . EpEX- ( VU1D9 , Cell Signaling Technology , NEB , Frankfurt , Germany , #2929 , 1:100 ) , EGFR- ( Dianova , Hamburg , Germany , #DLN-08892 , 1:200 ) , pERK1/2Thr202/Tyr204- ( Cell signaling technology; #4370; 1:200 ) , and pAKTSer473-specific antibodies ( Cell Signaling technology; #4060; 1:400 ) were used for IHC and immunofluorescence staining in combination with the avidin-biotin-peroxidase method ( Vectastain , Vector laboratories , Burlingame , CA , US ) or Alexa Fluor-488- and Alexa Fluor-594-conjugated secondary antibodies . Confocal microscopy images were recorded with a TCS-SP5 system ( Leica Microsystems; Wetzlar , Germany ) . IHC intensity scores were calculated as described [28] . EpCAM and EGFR were stained with EpCAM- ( CD326; BD Biosciences; Heidelberg , Germany , 1:50 dilution in PBS-3% FCS ) or EGFR-specific antibodies ( Dianova , Hamburg , Germany , #DLN-08892 , 1:200 ) , 15 min on ice , washed 3 times in PBS-3% FCS , and stained with FITC-conjugated secondary antibody ( Vector Laboratories/Biozol , Eching , Germany; FI-4001; 1:50 ) . Measurement of cell surface expression was performed in a FACSCalibur ( BD Pharmingen , Heidelberg , Germany ) . Immunoblotting of EpCAM ( DAKO/Biozol; Eching , Germany; #M7239; 1:5 , 000 ) , EGFR ( Cell signaling technology; #2232s; 1:1 , 000 ) , ERK1/2 ( Cell signaling technology; #137f5; 1:1 , 000 ) , pERK1/2Thr202/Tyr204 , Akt ( Cell signaling technology; #9272; 1:1000 ) , pAkt-Ser473 ( Cell Signaling Technologies; #92725 and #4060 ) , and actin ( Santa Cruz , Santa Cruz , CA , US , #sc-47778; 1:5 , 000 ) was performed with 10–50 μg of lysate ( PBS , 1% triton X-100 , Roche complete protease inhibitors ) as described [48] . Immunoprecipitation was conducted with precleared cell lysates’ ( 16 , 000 rcf , 15′ ) incubation with EGFR- or EpCAM-specific antibodies ( 10 μg ) , EpEX-Fc , or Fc ( 50 μg ) overnight at 4 °C before protein A agarose beads ( Thermo scientific Pierce , Munich , Germany , #20333; 100 μl ) were added for 2 hr at room temperature . Immunocomplexes were washed 5 times in 25 mM tris , 150 mM NaCl , pH 7 . 2 , boiled in Laemmli sample buffer [117] , and loaded on SDS-PAGE . EpEX ( aa 24–265 ) was expressed in Sf9 insect cells ( Thermo Scientific ) and purified as described [47] . EGFRex ( aa 25–642; gift from Matthew Meyerson; Addgene plasmid #11011 ) was expressed and purified as reported [118] . For cross-linking , EpEX and EGF ( Sigma ) ( 250 pmol ) and EGFRex ( 50 pmol ) were mixed in final volumes of 9 μl of 20 mM HEPES pH 8 . 0 , 100 mM NaCl for 1 hr at 37 °C at 1 , 000 RPM on a thermomixer . Afterwards , 3 . 6 μg of BS3 cross-linker ( Sigma ) was added for 30 min at 37 °C at 1 , 000 RPM on a thermomixer . Reaction was stopped by adding 1 μl of 1 M Tris pH 8 . 0 and an additional incubation of 15 min . Migration was assessed as described [54] . Quantification of scratches was performed using ImageJ and MRI wound healing tool . Relative migration was adjusted for proliferation rates . For cell proliferation , 1 × 105 cells were plated in 12-well plates before treatment . At indicated time points , cells were counted in an EVE automatic cell counter ( NanoEntek , VWR , Munich , Germany ) . Measurement of BrdU incorporation was performed as follows . Total RNA was extracted using RNeasy Mini kit coupled with RNase-free DNase set ( Qiagen ) and reverse transcribed with Reverse transcription kit ( Qiagen ) . The resulting cDNAs were used for PCR using SYBR-Green Master PCR mix in triplicates . PCR and data collection were performed on LightCycler480 ( Roche ) . All quantifications were normalized to an endogenous control GAPDH . The relative quantitation value for each target gene compared to the calibrator for that target is expressed as 2- ( Ct-Cc ) ( Ct and Cc are the mean threshold cycle differences after normalizing to GAPDH ) . E-cadherin-FW 5′-TGC CCA GAA AAT GAA AAA GG-3′ E-cadherin-BW 5′-GTG TAT GTG GCA ATG CGT TC-3′ N-cadherin-FW 5′-GAC AAT GCC CCT CAA GTG TT-3′ N-cadherin-BW 5′-CCA TTA AGC CGA GTG ATG GT-3′ Vimentin-FW 5′-GAG AAC TTT GCC GTT GAA GC-3′ Vimentin-BW 5′-GCT TCC TGT AGG TGG CAA TC-3′ Snail-FW 5′-GCG AGC TGC AGG ACT CTA AT-3′ Snail-BW 5′-CCT CAT CTG ACA GGG AGG TC-3′ Slug-FW 5′-TGA TGA AGA GGA AAG ACT ACAG-3′ Slug-BW 5′-GCT CAC ATA TTC CTT GTC ACA G-3′ Zeb1-FW 5′-TGC ACT GAG TGT GGA AAA GC-3′ Zeb1-BW 5′-TGG TGA TGC TGA AAG AGA CG-3′ Twist-FW 5′-ACA AGC TGA GCA AGA TTC AGA CC-3′ Twist-BW 5′-TCC AGA CCG AGA AGG CGT AG-3′ GAPDH-FW 5′-AGG TCG GAG TCA ACG GAT TT-3′ GAPDH-BW 5′-TAG TTG AGG TCA ATG AAG GG-3′ Results represent means with standard deviations . Significance of differences of two groups was calculated with Student t tests in Excel . Significance of differences between more than two groups was calculated with one-way or two-way ANOVA tests and multiple comparisons including Bonferroni or Tukey correction in GraphPad Prism . OS and DFS were calculated in months from the date of diagnosis to death due to any cause ( OS ) or to first observations of any recurrence or death ( DFS ) . In the absence of an event , patients were censored at the date of the last follow-up visit . Analysis was performed in R ( R: A Language and Environment for Statistical Computing , R Foundation for Statistical Computing , 2017; 3 . 4 . 0 ) together with R-survival package ( CRAN ) . For univariate analysis , IHC scores were included into cox-proportional hazard models after stratification into high and low expressers . Hazard ratios , 95% confidence interval ratios , median survival times , and log-rank p-values were included in Kaplan-Meier plots . | Head and neck squamous cell carcinomas ( HNSCCs ) display poor survival , with death rates above 55% . Major factors affecting survival are metastases’ formation and therapy resistance . Phenotypic changes during partial epithelial-mesenchymal transition ( EMT ) provide tumor cells with increased migration , invasion , and therapy resistance . Understanding molecular mechanisms of EMT , as a central process of the metastatic cascade and the development of therapy resistance , is therefore important . In the present work , we identified molecular cross talk between epidermal growth factor receptor ( EGFR ) and epithelial cell adhesion molecule ( EpCAM ) as a novel determinant of clinical outcome in HNSCCs . Low levels of EGFR but high levels of EpCAM ( EGFRlow/EpCAMhigh ) were associated with favorable prognosis , with survival rates above 90% , whereas EGFRhigh/EpCAMlow correlated with poor survival , below 10% . EGFR was shown to have a concentration-dependent capacity to induce proliferation and EMT . Proteolytic cleavage of the extracellular domain of EpCAM ( EpEX ) produces a ligand of EGFR that induces EGFR-dependent proliferation but counteracts EGF-induced EMT . We delineate an EGFR/extracellular signal–regulated kinase 1/2 ( ERK1/2 ) /EpCAM signaling axis that may be a promising therapeutic target for HNSCCs . | [
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"dev... | 2018 | EpCAM ectodomain EpEX is a ligand of EGFR that counteracts EGF-mediated epithelial-mesenchymal transition through modulation of phospho-ERK1/2 in head and neck cancers |
Gene discovery , estimation of heritability captured by SNP arrays , inference on genetic architecture and prediction analyses of complex traits are usually performed using different statistical models and methods , leading to inefficiency and loss of power . Here we use a Bayesian mixture model that simultaneously allows variant discovery , estimation of genetic variance explained by all variants and prediction of unobserved phenotypes in new samples . We apply the method to simulated data of quantitative traits and Welcome Trust Case Control Consortium ( WTCCC ) data on disease and show that it provides accurate estimates of SNP-based heritability , produces unbiased estimators of risk in new samples , and that it can estimate genetic architecture by partitioning variation across hundreds to thousands of SNPs . We estimated that , depending on the trait , 2 , 633 to 9 , 411 SNPs explain all of the SNP-based heritability in the WTCCC diseases . The majority of those SNPs ( >96% ) had small effects , confirming a substantial polygenic component to common diseases . The proportion of the SNP-based variance explained by large effects ( each SNP explaining 1% of the variance ) varied markedly between diseases , ranging from almost zero for bipolar disorder to 72% for type 1 diabetes . Prediction analyses demonstrate that for diseases with major loci , such as type 1 diabetes and rheumatoid arthritis , Bayesian methods outperform profile scoring or mixed model approaches .
Genome wide association studies ( GWAS ) have been used for three different purposes—to map genetic variants causing variation in a trait , to estimate the genetic variance explained by all the single nucleotide polymorphisms ( SNPs ) that have been genotyped , and to predict the genetic value or future phenotype of individuals . These analyses are usually performed using different statistical models and methods . To map causal variants usually the SNPs are analyzed one at a time , consequently the failure to account for the effects of other SNPs increases the error variance and thus decreases the power to detect true associations [1 , 2] . The effects of the SNPs are treated as fixed effects and , to account for the multiple testing , a stringent p-value is used , resulting in many false negatives but typically over-estimating the effects of SNPs declared significant [3] . For most traits the significantly associated SNPs only explain a fraction of the heritability , and thus have low predictive power , even when considered in aggregate [4] . To estimate the variance explained by all the SNPs together , all genotyped or imputed SNPs can be included in the model simultaneously with their effects treated as random variables all drawn from a normal distribution with zero mean and constant variance . This gives an unbiased estimate of the variance explained , but all the estimated SNP effects are non-zero [5] . The most accurate method to predict genetic value or phenotype based on the SNP genotypes is to fit all SNPs simultaneously treating the SNP effects as drawn from a prior distribution that matches the true distribution of SNP effects as closely as possible [4 , 6] . We do not know the true distribution of effect sizes but a mixture of normal distributions can approximate a wide variety of distributions by varying the mixing proportions [7] . Erbe et al . [8] used this prior and included one component of the mixture with zero variance . A similar model was proposed by Zhou et al . [9] but with a mixture of two normal distributions , one with a small variance and one with a larger variance . The models used for prediction can also be used to map variants associated with phenotype and to estimate the total variance explained by the SNPs . Because they fit all SNPs simultaneously and account for LD between SNPs , they should have greater power to detect associations , find less false negatives and give unbiased estimates of the larger SNP effects . They can also provide information about the genetic architecture of the trait from the hyper-parameters of the distribution of SNP effects . Here we use a Bayesian mixture model ( called BayesR [8] ) to dissect genetic variation for disease in human populations and to construct more powerful risk predictors . We show how this method can shed light on the genetic architecture underlying complex diseases as well as demonstrating its ability to map SNPs associated with disease and estimate the genetic variance explained by the SNPs collectively . The approach was evaluated on simulated and real data of seven case-control traits from the Welcome Trust Case Control Consortium . We assessed the power to correctly identify causal and associated variants , to estimate SNP-based heritability and the accuracy to predict future outcomes . Results from BayesR are compared with a traditional single-SNP GWAS analysis , a linear mixed-effects modeling approach [5 , 10–12] and a Bayesian sparse linear mixed model [9] .
In most GWAS studies the number of markers is very large and notably p>>n . This requires some kind of variable selection , either by discarding unimportant predictors or by shrinking their effects to zero . We used a Bayesian mixture model and a priori assumed a mixture of four zero mean normal distributions of SNP effects ( β ) , where the relative variance for each mixture component is fixed [8]: p ( βj|π , σg2 ) =π1×N ( 0 , 0×σg2 ) +π2×N ( 0 , 10−4×σg2 ) +π3×N ( 0 , 10−3×σg2 ) +π4×N ( 0 , 10−2×σg2 ) . Here , π are the mixture proportions which are constrained to sum to unity and σg2 is the additive genetic variance explained by SNPs . Sparseness is included into the model by setting the effect and variance of the first mixture component to zero . Instead of fixing σg2 at a pre-specified value [8] , we estimate a hyper-parameter for the genetic variance from the data . We compare BayesR with traditional single-SNP GWAS analyses [13] , a linear mixed-effects modeling approach ( LMM ) [5 , 10–12] and a Bayesian sparse linear mixed model ( BSLM ) [9 , 14] . We used real genotype data of 287 , 854 SNPs measured on 3 , 924 individuals to simulate quantitative phenotypes with heritabilities equal to 0 . 2 , 0 . 5 , and 0 . 8 . Causal effects were drawn from three groups of effect sizes , the first containing 10 SNPs with moderate effects , the second containing 310 SNPs with smaller effect , and a large group of 2 , 680 SNPs representing a polygenic component ( S1 Fig . ) , where the definitions of moderate , small and polygenic effect size match those of the prior assumptions of BayesR . Note that the contribution of each mixture to heritability is not known a priori ( S2 Fig . ) . In additional simulations , under models that ranged from very sparse to polygenic and using alternate parametric models for the effect-size distribution , we assessed how our prior assumption may affect parameters estimates and interpretation of results ( S2 Text ) . To cover a wide range of architectures from very sparse to polygenic , we sampled 10 , 100 , 1 , 000 , 10 , 000 , and 20 , 000 causal SNPs either from a standard normal distribution or a gamma distribution with shape 0 . 44 and scale 1 . 66 [15 , 16] . In general estimates of heritability from all methods were robust across the wider range of settings ( S1 Table ) . Heritability estimates of LMM were unbiased , even under scenarios where its modeling assumptions were not met . BayesR and BSLMM showed a small upward bias under very sparse scenarios and BayesR slightly underestimated heritability under highly polygenic models . BayesR estimates had the smallest variance in the very sparse setting ( 10 causative variants ) despite prior specifications that did not closely correspond to the true model . Similar to the previous results using real genotype data , where the prior model closely matched the analysis model of BayesR , prediction accuracies from BayesR and BSLMM were highest and both methods performed almost the same across all the scenarios ( S2 Table ) . LMM was the least accurate method with the exception of scenarios including 10 , 000 and 20 , 000 SNPs . BayesR and BSLMM outperformed GPRS , with the exception of the scenarios involving 10 causative SNPs . These results show that the mixture models are more powerful than GPRS , even in the case of LE markers where the single SNP method might be expected to do very well . Inferences of BayesR about the genetic architecture were consistent with the underlying model and provided insights into the genetic architecture ( S4–S5 Figs . ) . Posterior inference of the BayesR model for the scenario including 10 causative SNPs , which is poorly supported by the BayesR prior , provided strong evidence to revise the prior model . As for the 287K data , BayesR and BSLMM outperformed LMM and GRPS in finding causal variants in all scenarios ( S6 Fig . ) . In addition to simulated data we assessed the performance of BayesR for seven diseases of the Welcome trust case control consortium ( WTCCC [17] ) . These data were previously used to estimate heritability [18 , 19] and for risk prediction [14 , 20–22] .
We have presented a single model for analysis of GWAS that maps associated variants , estimates the genetic variance explained by the SNPs collectively , describes the genetic architecture of the trait and predicts phenotype from SNP genotypes . The framework we present applies a Bayesian hierarchical model to human complex traits based on the assumption of a prior distribution that SNP effects come from a mixture of more than two normal distributions . The procedure clusters markers in groups with distinct genetic values where each SNP explains 0 . 01 , 0 . 1 , or 1% of σg2 and a group of SNPs with zero effect . Instead of fixing the variance component σg2 to a pre-specified value as in Erbe et al . [8] we treat σg2 as unknown and estimate it from the data . This is because the shrinkage of SNP effects is affected by σg2 and determining the amount of shrinkage a priori can have negative impact on performance [9 , 16] . BayesR showed good performance in estimating the SNP-based heritability across a wider range of simulated genetic architectures ( Fig . 2A , S1 Table ) and estimates were similar to BSLMM and LMM for diseases of the WTCCC study ( Fig . 4A ) . If the primary interest is to estimate SNP based heritability , LMM is faster and approximately unbiased under different disease architectures [9 , 11 , 18] . BayesR can provide more accurate estimates under certain architectures , for example when effect sizes follow skewed distributions , which is the case for many human diseases[4] . For phenotype prediction BayesR was as accurate as BSLMM which outperformed various other approaches in the study of Zhou et al . [9] . Qualitatively , the main difference between the methods considered here is that the BayesR model is sparse , which seems intuitively appealing , as not every genotyped SNP is likely to be in LD with causative variants . For example , often in GWAS the primarily focus is not on estimating the relative contribution of each genetic variant , but whether or not a particular variant contributes at all . Sparseness and good performance make BayesR an attractive alternative to currently available methods . The Bayesian framework incorporates model uncertainty by averaging over many different competing models [25] , and this allows for more robust inferences about the genetic architecture . The posterior inclusion probability can be directly interpreted as the probability that a variant is an risk factor with a certain effect size [26] , which is more intuitive to interpret than an association of zero or one based on a p-value from single-SNP analysis . Our simulations showed that SNPs with high inclusion probabilities have a high probability of being a causal or associated variant ( Figs . 1 , S3 , S6 ) and an increase in performance of BayesR to identify smaller SNPs that are currently difficult to detect in single SNP GWAS [1 , 27 , 28] . Predictions of phenotypes from BayesR , BSLMM and LMM were unbiased ( Table 1 ) . Unbiasedness of a disease predictor is important for practical implementations [29 , 30] , yet often ignored when developing GPRS derived from GWAS summary statistics . We applied BayesR directly to the WTCCC data treating the binary outcome coded 0/1 as the response in an ordinary linear regression . The predicted phenotypes can then be taken as the probability of being a case and heritability estimates can be transformed to liability of disease scale [11] . The model can be extended to binary or ordered categorical traits by fitting a liability model [31] , but improvements are expect to be negligible [27 , 32] . By quantifying the contribution of SNPs and their effect sizes , BayesR can be used to make inferences about the underlying genetic architecture of complex phenotypes ( Figs . 3 , 5 , 6 , S4 ) . In our analysis of WTCCC , we found that most of the SNPs had a zero effect ( >96% ) , inconsistent with the ‘infinitesimal model’ [33] , but that thousands each explain a small proportion of the total genetic variance and these estimates suggest a substantial contribution of a polygenic component to these common diseases . However inferences did vary between diseases , with fewer loci contributing to the genetic variance for T1D and RA than for the other traits . This difference is mainly a result of large effects associated with variants in the MHC for T1D and RA . Furthermore the variance explained by larger SNPs ( effect size 10−2×σg2 ) varied markedly between chromosomes and between diseases , ranging from 73% of hg2 for T1D to 0 . 6% for BD . Consistent with other studies the variance explained by individual chromosomes was largely related to its length [34–36] , although chromosomes of similar length showed large variability across diseases , which was due to SNPs with larger effects . We caution against over-interpretation of our results as they relate to genetic architecture [37] . Inevitably the specified mixture model that effect sizes come from four mixture distributions is very simplistic . Nonetheless , since the WTCCC diseases all utilize the same control samples , the differences between diseases allows comparative interpretation and the genetic architectures agree well with the findings in the original [17] and subsequent studies [11 , 18 , 22] . However , in practice the true effect size distribution is unknown . We used the same mixture distribution as prior as Erbe et al . [8] , where it showed good mixing between SNPs , but alternative prior distributions may lead to better performance . Priors may be influential , however , simulating a large number of different genetic architectures , we found that in general results were not very sensitive to our modeling assumptions and that inferences of BayesR about the genetic architecture were consistent with the underlying simulated genetic architecture ( S4 Fig . ) . Using a distribution with variance 10−4×σg2 seemed a reasonable choice for the effect size of ‘polygenic’ SNPs ( S5 Fig . ) . How much of the heavier tail of the distribution can be distinguished from zero effects depends on sample size . For much larger data sets adding more classes , for example one with variance 10−5×σg2 , might help to interpret the data . In addition to the caveats relating to the specific mixture model we emphasize that the inference drawn on SNP effects and genetic architecture is from observed SNPs and not on the causal variants directly . The true but unknown pattern of correlation between unobserved causal variants and genotyped SNPs will impact the inference about genetic architecture . Nevertheless , the comparison across the seven diseases , for which the genotyped SNPs are the same , demonstrates large differences in SNPs effects , variance explained and prediction accuracy , reflecting real differences in the distribution of effect sizes at causal variants . Incorporating markers beyond the small number of risk variants identified at genome wide significance has the potential to increase the predictive performance of risk models [4 , 38] . Our results on predicting disease risk in WTCCC are consistent with recent analysis [9 , 20–22] that demonstrated that predictive ability of polygenic models is trait specific , depending on heritability and genetic architecture . Furthermore , our results extend beyond previous reports of the impact of genetic architecture on genetic risk prediction , most of which have relied on hypothetical effect-size distributions or used results from risk predictions to inform about genetic architecture [38 , 39] . Here we infer genetic architecture directly from entire GWAS data , which can contribute to our understanding of complex disease and our ability to assess the power of future GWAS depending on the underlying disease architecture . We observed that the pattern of SNP-based heritability did not follow the same pattern as those of AUC . In particular , heritability was not a good indicator of prediction performance for BayesR and BSLMM . For traits where common SNP account for a large proportion of the SNP based heritability ( T1D , RA , CD ) , predictive accuracy was much higher for the two Bayesian methods compared to LMM and GPRS . BayesR has proved feasible in the WTCCC data set with ∼300 , 000 markers , but much larger data sets are currently being collected . Computing time increases linearly with the number of SNPs , however , runtime for large SNP sets can be reduced by avoiding redundant computations through filtering of SNPs that are in perfect or high linkage disequilibrium with at least another SNP . The savings can be quite substantial , ranging from 9–22% ( r2 = 1 ) to 34–58% ( r2>0 . 80 ) for the Hapmap3 panel [40] , depending on the ancestry of the population [41] . Computing performance can further be improved by running multiple MCMC chains instead of a single long chain . Moreover , computing time of the ‘500 SNPs’ implementation does not increase linearly with the number of SNP after the first 5 , 000 cycles , thus reducing computational burden even more for larger data sets . However , less arbitrary approaches should be developed . For very large datasets Bayesian-like estimation using MCMC might be infeasible altogether , and fast alternative Bayesian estimation procedures are required [42 , 43] . On the other hand , the use of a simple Gibbs sampling scheme provides great flexibility in effects size distributions by selecting the number and the variances of the mixture . We illustrated the flexibility of the method by partitioning the genetic variance into contribution of SNPs with different effect sizes by chromosomes . This model can easily be extended to allow for different prior probabilities of the mixture distribution for each chromosome [44] , to include dominant genetic variation [28] , to partitioned variance attributable to SNPs by annotation [34] , or to include prior biological knowledge in genomic analysis and prediction [45] . We found little difference between BayesR and BSLMM in prediction performance , however , differences seem likely when individual effects sizes can be estimated more accurately with increase in sample size . For instance , as sample size increases and genome sequence data is analyzed , causal variants explaining only 0 . 1% of genetic variance will be identified . An advantage of BayesR is that most SNPs have near zero effect and so could be deleted from prediction of future phenotype in practice . Improvements can also be expected when the prior induced mixture distribution more closely captures the actual distribution of effect sizes . It has been shown in simulation studies [46] that models that include all genetic variants do not take full advantage of high-density marker data if the number of causal SNPs is small , while approaches with an implicit feature selection do . In conclusion , we proposed and applied a flexible Bayesian mixture model that simultaneously estimates effect size of all SNPs , the genetic variation captured by SNPs and maximizes prediction accuracy . We demonstrate the ability of such a model to dissect genetic architecture and partition genetic variation . The method is highly flexible , can be applied to sequence data and can incorporate prior biological knowledge .
Phenotypes are related to markers with a standard linear regression model y=1nμ+Xβ+ε , where y is a n-dimensional vector of phenotypes , 1n is a n-dimensional vector of ones , μ is the general mean , X is an n×p matrix of genotypes encoded as 0 , 1 or 2 copies of a reference allele . The vector β is a p-dimensional vector of SNP effects and ε is a n-dimensional vector of residuals , ε∼N ( 0 , Iσe2 ) with I being a n×n identity matrix . The BayesR model assumes that the SNP effects come from a finite mixture of K components so that the probability of the β effects conditional on the variance of the components σ2= ( σ12 , … , σK2 ) and the mixture proportions π = ( π1 , … , πK ) which are constrained to be positive and to sum to unity: p ( β|π , σ2 ) =∑k=1KπkN ( β|0 , σk2 ) , where N ( β|0 , σk2 ) denotes the density function of the univariate normal distribution with mean 0 and variance σk2 . The Bayesian approach requires the assignment of prior distributions to all unknowns in the model . We followed Erbe et al . [8] and a priori assumed a mixture of four zero mean normal distributions , where the relative variance for each mixture component is fixed: p ( βj|π , σg2 ) =π1×N ( 0 , 0×σg2 ) +π2×N ( 0 , 10−4×σg2 ) +π3×N ( 0 , 10−3×σg2 ) +π4×N ( 0 , 10−2×σg2 ) . Here , σg2 is the additive genetic variance explained by SNPs . Sparseness is included into the model by setting the effect and variance of the first mixture component to zero . A key difference in our implementation of BayesR from previous application [8] is that we estimate a hyper-parameter for σg2 from the data , rather than fixing the marker variance at a pre-specified value . MCMC estimation of the unknown parameters ( μ , π , β , σg2 , σe2 ) used a Gibbs scheme to sample values from each unknown parameter’s conditional posterior distribution . Details of the sampling procedure are outlined in S1 Text . Simulations were used to assess the accuracy of estimates of model parameters and of inferences provided by BayesR . The first study represents a typical genome-wide association study and uses real genotype data to capture the correlation between SNPs . Moreover , in GWAS most SNPs are not in LD with causative variants and effect size distribution of causative variants is skewed toward smaller effects . Here we used genotype data of 3 , 924 Australian individuals [5] . After quality control , imputation of missing genotypes at each loci and removal of SNPs with a minor allele frequency less than 1% , 287 , 854 measured SNPs remained . The effects sizes of causal SNPs were assumed to come from a series of three zero mean normal distributions with the number of SNPs in each class falling in inverse proportion to the size of the effect . First we randomly selected 3 , 000 SNPs to be causal . Large effect sizes were drawn for 10 SNPs by sampling from a normal distribution with variance σ2 = 10−2 , moderate effect sizes were generated for 310 SNPs by sampling from a N ( 0 , 10−3 ) distribution and the effects of the remaining 2 , 680 SNP were generated from a N ( 0 , 10−4 ) distribution . Residual effects for each individual ( ei ) were obtained by sampling from a normal distribution with mean 0 and with variance chosen to accomplish heritabilities of 0 . 2 , 0 . 5 or 0 . 8 . The simulated phenotype for a single individual was then obtained as follows: yi=∑j=110wij×βj+∑j=11310wij×βj+∑j=3112968wij×βj+ei , where wij= ( xij−2pj ) /2pj ( 1−pj ) the centered and scaled genotype and xij is the number of copies of the reference allele ( 0 , 1 , 2 ) at SNP j for individual i with pj being the frequency of the reference allele in the sample . Sampling from this mixture distribution resulted in a fat-tailed distribution of effect sizes ( S1 Fig . ) , where large , moderate and small effects contributed around 14% , 46% and 40% of the total genetic variance . Fifty replicates were analysed for each of the three heritabilities and a different set of 3 , 000 SNPs was selected for each replicate . In each replicate the sampled 3 , 000 SNP effects were randomly assigned to the selected markers . Note that the contribution of each causal SNP to heritability depends on its frequency , so that the true number of SNPs in each mixture component of the BayesR model and the contribution of each mixture to heritability are not known a priori ( S2 Fig . ) . In the simulation using real genotype data , phenotypes were generated under a model that very closely matched the prior specifications for BayesR . To investigate how the prior assumption may affect parameters estimates and interpretation of results we performed additional simulations , including scenarios where we created mismatches between modeling assumptions and simulated genetic architectures . To avoid the problem of differentiating between causal variants and non-causal SNPs in LD with causal variants we simulated 20 , 000 independent SNPs in a sample of 5 , 000 individuals . Genotypes of SNP j were generated by sampling from a binomial distribution with n = 2 ( number of successes ) and success probability pi , where pi was sampled from a univariate distribution with interval [0 . 05 , 0 . 5] . We simulated 10 , 100 , 1 , 000 , 10 , 000 , and 20 , 000 causal SNPs to cover a wide range of architectures from very sparse to polygenic . Effect sizes were sampled either from a standard normal distribution or a gamma distribution with shape 0 . 44 and scale 1 . 66 as in [15 , 16] and residual effects were added to achieve a heritability of 0 . 5 . Sampling from a gamma distribution generates fewer large and more small effects than the standard normal [16] . We analyzed 7 traits of the Welcome Trust Case Control Consortium ( WTCCC ) study [17] . Following previous analyses of the data [11 , 18] we performed strict QC on SNP data using PLINK [13] . First , we removed individuals with > 2% missing genotypes . For each of the 7 case and the two control data sets we removed loci with frequency of the minor allele < 0 . 01 and SNP with missingness > 1% . After combining each case and the two control sets into 7 trait case/control studies , SNPs significant at 5% for differential missingness between cases and controls and SNP significant at 5% for Hardy-Weinberg equilibrium were removed . Relatedness testing was performed using a pruned set of SNPs with LD of r2 <0 . 05 , pairs of subjects with estimated relatedness > 0 . 05 were identified and one member of each relative pair was removed at random . Principal components of the genomic relationship matrix were estimated with the same set of pruned SNP using the software GCTA [10] and all phenotypes analyzed were the residuals of case-control status following linear regression on the first 20 principal components . After QC the data included 1 , 851 cases of bipolar disorder ( BD ) , 1 , 906 cases of coronary artery disease ( CAD ) , 1 , 731 cases of Crohn’s disease ( CD ) , 1 , 905 cases of hypertension ( HT ) , 1 , 837 cases of rheumatoid arthritis ( RA ) , 1 , 953 cases of type 1 diabetes ( T1D ) , 1 , 902 cases of type 2 diabetes ( T2D ) , and 2 , 910 to 2 , 918 controls depending on the trait . The number of genotypes ranged from 296 , 718 for BD to 305 , 967 for CD . We compared the ability of BayesR , BSLMM and LMM and single-SNP to identify causal variants . For the simulated 287K data we focused on the SNPs with large and moderate effect sizes sampled from N ( 0 , 10−2 ) and N ( 0 , 10−3 ) , respectively . Although , small effects together contributed ∼40% to genetic variance , power to identify ‘polygenes’ with our sample size was expected to be effectively zero . Similar to Guan and Stephens [27] we computed a measure of evidence of association between a genome segment and phenotype . This was done because the multi-SNP methods have the tendency to dilute a QTL effect across SNPs in LD with the QTL . For single-SNP analyses we used the minimum of the p-values of the SNPs within a region as evidence of association . The sum of the absolute effect sizes of SNPs within a region was used for LMM . The GEMMA software that implements BSLMM outputs the posterior probability of a SNP to have an effect above the polygenic background and we summed these probabilities over the SNPs within a segment . BayesR provides separate inclusion probabilities for an individual SNP to fall in each mixture component . We used the sum of the posterior inclusion probabilities that SNPs are allocated to effect size classes 10−2×σg2 and 10−3×σg2 as evidence measure . In BayesR the polygenic component is ‘mimicked’ by SNPs assigned to the mixture class with small effects size ( 10−4×σg2 ) and was therefore not included in the calculation . We divided the genome in non-overlapping segments of ∼ 250kb size . For each method we selected a series of cutoff values for the evidence measure and considered all segments containing a causative variant that exceed the cutoff value as true positives and all other regions exceeding the cutoff value as false positives . We then plot the true positive rate against the false positive rate averaged over two different starting positions for the first window ( 0 , 125kb ) . In the simulations using uncorrelated SNPs we assessed the methods on their ability to identify individual SNPs rather than regions . We used similar measures of evidence of association , except for BayesR where we used the posterior probability of the SNP being included in the model ( i . e . 1- posterior inclusion probability of class 0×σg2 ) . We assessed predictive performance in the simulated data and the WTCCC data . In the simulated data , each replicate was randomly split into a training sample containing 80% of individuals and a validation sample containing the remaining 20% . For the WTCCC data we generated 20 random 80/20 splits for each trait . We use Pearson’s product moment correlation statistic as measure of predictive ability in the simulated data . The accuracy of risk prediction in WTCCC was assessed by the area under the curve ( AUC ) [23] . We also report the slope of the regression of phenotypes on the predictions . A slope different from one indicates bias in the prediction . A slope of unity from a regression of phenotype on predictor implies that the predictor is calibrated correctly on the scale of absolute risk , which matters in genomic medicine applications , in particular when the genetic predictor is combined with non-genetic factors ( e . g . gender , smoking status , BMI etc . ) for risk prediction . For BayesR , BSLMM and LMM we centered and scaled each column of the genotype matrix to have mean zero and unit variance in all analyses . The data was analyzed using our BayesR software implemented in Fortran . The software is available at http://www . cnsgenomics . com/software/ . Prior assumptions for BayesR were as described above ( see also S1 Text ) . For all analyses a chain length of 50 , 000 was used with the first 20 , 000 samples as burn-in . Posterior estimates of parameters are based on 3 , 000 samples drawing every 10th sample after burn-in . GEMMA was run with its default setting of 1 , 000 , 000 sampling steps using the first 100 , 000 as burn-in . The only default parameter we changed was lowering the minor allele frequency threshold to 0 . 001 , to ensure that no SNP was deleted from the model when 80% of the data was used for training . The URLs for data presented herein are as follows: BayesR , http://www . cnsgenomics . com/software/ GCTA , http://www . cnsgenomics . com/software/ GEMMA , http://home . uchicago . edu/xz7/software . html PLINK , http://pngu . mgh . harvard . edu/∼purcell/plink/ | Most genome-wide association studies performed to date have focused on testing individual genetic markers for associations with phenotype . Recently , methods that analyse the joint effects of multiple markers on genetic variation have provided further insights into the genetic basis of complex human traits . In addition , there is increasing interest in using genotype data for genetic risk prediction of disease . Often disparate analytical methods are used for each of these tasks . We propose a flexible novel approach that simultaneously performs identification of susceptibility loci , inference on the genetic architecture and provides polygenic risk prediction in the same statistical model . We illustrate the broad applicability of the approach by considering both simulated and real data . In the analysis of seven common diseases we show large differences in the proportion of genetic variation due to loci with different effect sizes and differences in prediction accuracy between complex traits . These findings are important for future studies and the understanding of the complex genetic architecture of common diseases . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [] | 2015 | Simultaneous Discovery, Estimation and Prediction Analysis of Complex Traits Using a Bayesian Mixture Model |
Control of chromosome replication involves a common set of regulators in eukaryotes , whereas bacteria with divided genomes use chromosome-specific regulators . How bacterial chromosomes might communicate for replication is not known . In Vibrio cholerae , which has two chromosomes ( chrI and chrII ) , replication initiation is controlled by DnaA in chrI and by RctB in chrII . DnaA has binding sites at the chrI origin of replication as well as outside the origin . RctB likewise binds at the chrII origin and , as shown here , to external sites . The binding to the external sites in chrII inhibits chrII replication . A new kind of site was found in chrI that enhances chrII replication . Consistent with its enhancing activity , the chrI site increased RctB binding to those chrII origin sites that stimulate replication and decreased binding to other sites that inhibit replication . The differential effect on binding suggests that the new site remodels RctB . The chaperone-like activity of the site is supported by the finding that it could relieve the dependence of chrII replication on chaperone proteins DnaJ and DnaK . The presence of a site in chrI that specifically controls chrII replication suggests a mechanism for communication between the two chromosomes for replication .
Eukaryotes invariably have many chromosomes , whereas one chromosome is the norm in bacteria . Bacteria with more than a single chromosome , although amounting to only about ten percent of known bacterial species , belong to diverse phyla and include important human and plant pathogens [1] . How diverse chromosomes are maintained in individual bacteria is only beginning to be understood . The bacteria with a multipartite genome have one main chromosome containing most of the housekeeping genes [2] . Replication of this chromosome , which is analogous to the chromosome of monochromosome bacteria , is controlled by the initiator protein , DnaA . DnaA is not only well-conserved in bacteria but also has structural homology to eukaryotic initiators , Cdc6 and Orc proteins [3] , [4] . The secondary chromosomes in these bacteria appear to have originated from plasmids . Although plasmids often use DnaA as a replication factor , they do not depend on it to control their copy number; this is accomplished by initiators that they encode themselves . The secondary chromosomes also encode their own initiators to control replication and , like other chromosomes , initiate replication once at a particular time of the cell cycle [2] , [5]–[7] . Plasmid replication has no such constraints . Bacteria with multipartite genomes also differ from eukaryotes in that eukaryotic regulators of replication are not chromosome-specific [8] . In all organisms chromosome replication and segregation must be completed prior to cell division . Although the individual chromosomes of bacteria with multipartite genome use different replication and segregation systems , some coordination among the processes that maintain them is to be expected [9]–[11] . We argue that since segregation initiates soon after replication initiation , the coordination is more likely to be at the stage of replication initiation . Our knowledge of replication control in bacteria comes primarily from the study of the E . coli chromosome and plasmids . Multiple modes of control are used , but they all operate primarily through binding of the initiator protein to its sites in the origin of replication , as was originally proposed in the replicon model [12] . It was later found that the initiator also binds outside of the origin and plays important roles in the regulation of replication [13] . In E . coli , the initiator , DnaA , has more than 300 near-consensus binding sites distributed over the entire chromosome [14] . As sites are duplicated during replication elongation , their increased number results in titration of free initiators and reduces their availability for binding to the origin , which is important for preventing premature initiation [15] . Subsequent studies showed that some sites play more active roles in controlling replication . For example , the datA locus , although originally appeared to be titrating a significant fraction of total DnaA molecules of the cell [16] , promotes hydrolysis of DnaA-ATP , the active form of the initiator , to DnaA-ADP , the inactive form [17] . Another mechanism for promoting DnaA-ATP hydrolysis , called RIDA ( regulatory inactivation of DnaA ) , operates during the entire elongation phase as the replication fork passes through the DnaA binding sites [18] . Two other binding sites , called DARS ( DnaA reactivating sequence ) , do the opposite by facilitating the conversion of DnaA-ADP to DnaA-ATP , thus promoting replication [19] . DnaA is also the central mediator of control in other bacteria , but the details of the control can be species specific [20]–[23] . In plasmids , extra binding sites can also be present outside of the origin and they play only inhibitory roles through initiator titration and higher order interactions with the origin sites [6] , [24] . Plasmids , being orders of magnitude smaller than the chromosomes , have short elongation periods , and are not known to actively utilize the elongation phase for regulatory purposes . The importance of initiator binding sites outside of the origin in regulation of chromosomal replication , led us to ask whether plasmid-like secondary chromosomes might also employ such sites for regulation of their replication . Genome-wide distribution of such sites could also provide a mechanism for communication among the individual chromosomes . Among the bacteria with divided genome , chromosome maintenance has been studied mostly in Vibrio cholerae . The bacterium has two circular chromosomes ( chrI and chrII ) of 2 . 96 and 1 . 07 Mb , respectively [25] . They initiate replication at different times and use different initiators , DnaA and RctB for controlling replication of chrI and chrII , respectively [6] , [7] . The replication system of chrI appears identical to that of the E . coli chromosome , whereas that of chrII is similar to those of plasmids with repeated initiator binding sites ( iterons ) [9] , [24] . The chrII system is more elaborate in that the RctB initiator binds to iterons ( 12-mers ) as well as a second kind of site ( 39-mers ) [26] . The iterons are essential for replication initiation whereas the 39-mers play only inhibitory role that prevents over replication . The iterons antagonize 39-mer activities , thus playing only positive roles . Whether chrII also uses extra RctB binding sites outside the origin , like the DnaA binding sites in other bacterial chromosomes , has not been studied . Here , we have screened for new RctB binding sites using a genome-wide DNA binding analysis ( ChIP-chip ) . We report the identification of a new region containing additional RctB binding sites ( multiple iterons and a 39-mer ) in chrII , reminiscent of the E . coli datA locus . When provided in multiple copies , these sites were capable of titrating RctB and inhibiting chrII-specific replication . Additionally , a novel RctB binding site was found on chrI . In contrast to the chrII sites , the chrI site enhanced chrII-specific replication , reminiscent of the E . coli DARS . These results imply that providing regulatory sites outside the origin could be a general means to exploit the elongation phase for regulating chromosomal replication in bacteria . The chrI site appears to function like a DNA chaperone as it modulates DNA binding of RctB , and by controlling chrII replication , could provide a way to coordinate replication of the two V . cholerae chromosomes . The additional layers of chrII control that we reveal here indicate the extent of adaptation required for a ( plasmid-like ) random mode of replication to become cell cycle regulated .
We analyzed genome-wide binding of RctB in wild type ( WT ) V . cholerae strain N16961 ( CVC209 ) using a chromatin immuno-precipitation and microarray ( ChIP-chip ) assay . To compensate for the possible heterogeneity in hybridization efficiency of the microarray probes , the hybridized signals from the DNA immunoprecipitated ( IP ) with RctB antibody was divided by the corresponding signals from the total DNA before immunoprecipitation ( input DNA ) . To avoid non-specific signals , the IP DNA/input DNA values were determined from an rctB-deleted strain , MCH1 ( CVC2099 ) . MCH1 is a monochromosome mutant of N16961 , in which the fusion of chrII to chrI results in deletion of the chrII origin region , including the rctB gene [27] . When the difference in IP DNA/input DNA values between the two strains was plotted across the whole genome , a significant enrichment of the IP DNA from the origin region was apparent ( Figure 1A ) . We take this result as validation of the ChIP-chip assay because the origin region is known to have several iterons and 39-mers , the specific binding sites of RctB [26] . A few regions outside of the chrII origin were also enriched . Five regions were selected for which the difference in signal between the WT and MCH1 strains was two or more . Four of the regions were from chrII ( Figure 1B ) and one from chrI ( Figure 1C ) . The DNA fragments from these regions were tested for their ability to affect RctB-dependent replication in vivo and RctB binding to DNA in vitro . Sequence analysis of the ChIP-chip peak regions for homology to iterons and 39-mers , revealed homologous sites at 12 places . These putative binding sites were named chrII-1 to chrII-12 ( Figure 1B and Table S1 ) . The ability of these sites to influence chrII-specific replication was tested in a three-plasmid system as described [26] ( Figure 2A , top ) . The sites were cloned into a pBR322-derived vector and the resultant plasmids were introduced into E . coli with resident poriII and prctB plasmids . The copy number of poriII in the transformants was reduced by six of the sites: chrII-1 , -5 , -6 , -9 , -10 and -11 , with no significant change by the others ( Figure 2A and Table S1 ) . At least one of these six sites is present in each of the four peaks in Figure 1B , which again validated that the ChIP-chip method reported specific binding of RctB . The sites presumably reduced poriII copy number by titrating RctB since increasing the supply of RctB alleviated that reduction ( High RctB , Figure 2A and Table S1 ) [26] . In the case of chrII-10 , which has an iteron nested within a 39-mer , increasing the amount of RctB failed to alleviate poriII copy-number reduction . We showed earlier that when the two kinds of site are present in the same fragment , a more potent inhibition of replication results that can not be overcome by increasing RctB [26] . We show below that both the 39-mer and its nested iteron could bind RctB ( Figure 2B ) . A region centered on the chrII coordinate 1025 kb contains two iterons ( the ones present in chrII-5 and -6 ) , several GATC sites and a DnaA box with three mismatches to the consensus sequence , TTATCCACA ( Figure S1A ) . These elements being present in the chrII replication origin motivated us to test whether the region can confer origin function . The cloned fragment did not show origin activity ( Figure S1C ) ( Text S1 ) . The results suggest that the newly recognized chrII sites serve only replication inhibitory activity . The newly identified sites ( five iterons and a 39-mer ) that could inhibit chrII replication are present in a span of about 74 kb ( coordinates 956828–1 , 030773 ) , only about 40 kb away from the chrII origin . The locus will thus be duplicated early and be particularly effective in preventing premature initiation by providing additional titration sites . E . coli datA is similarly located close to oriC at 94 . 7 min [28] . By electrophoretic mobility shift assay ( EMSA ) , the six chrII sites that could reduce poriII copy number were the only ones proficient in binding RctB in vitro ( Figure 2B ) . These sites are also the ones that contained the fully conserved iteron bases , TGATCA ( Table S1 ) . The results of ChIP-chip analysis , poriII copy number measurements and EMSA are thus fully consistent . The EMSA pattern of the chrII-10 site appeared as expected for a composite of an iteron and a 39-mer , as the fragment sequence suggested . Since RctB binding to iterons requires the site to be methylated [26] , [29] , it was possible , using an un-methylated chrII-10 fragment ( made by PCR ) , to test whether its 39-mer could bind RctB on its own . It did ( chrII-10PCR , Figure 2B ) . This indicates that the chrII-10 site can function both as an iteron and a 39-mer . The region of chrI that by ChIP-chip evidence binds RctB ( Figure 1C ) contains only one iteron-like sequence with the conserved hexamer , TGATCA . However , a 24 bp fragment containing the hexamer marginally inhibited chrII replication in the three-plasmid assay system used above , suggesting that the hexamer by itself it not a strong RctB binding site ( chrI-1; Table S2 ) . When a fragment covering the entire peak region ( chrI-2 , spanning coordinates 817200–818899 ) was tested , it significantly increased poriII copy number ( Figure 3A ) . Serial deletion of the fragment from either side ( resulting in fragments chrI-3 to -10 ) showed that the replication-enhancing activity could be narrowed down to 70 bp ( as in chrI-9 , spanning coordinates 818000–818069 ) . Comparison of chrI-5 and -6 indicates that the leftmost 10 bp sequence of chrI-5 is important for activity . Trimming of the other end had a less dramatic effect ( chrI-7 to -10 ) . The 70 bp replication enhancer bore no sequence similarity to either the iterons or the 39-mers . Thus , the enhancer appears to be a new kind of RctB binding site , possibly a 70-mer . Western blotting analysis showed that the level of RctB synthesized in the presence of chrI-4 was comparable to that in the absence of chrI-4 ( Figure S3A ) , indicating that chrI-4 is increasing the activity of RctB and not its concentration . The replication-enhancing activity of the chrI site was also evident by monitoring the growth of cells dependent on poriII function ( Figure 3B ) . In the three-plasmid system used above , the rctB gene in prctB was under the control of an arabinose-inducible promoter , PBAD , and when the presence of poriII was selected with appropriate antibiotics , cells grew only in the presence of arabinose . When chrI-4 was present , cells grew in media lacking arabinose but did not increase further upon addition of arabinose . The level of RctB in the absence of arabinose was too low to be detected by Western blotting , indicating that the improved growth by chrI-4 is not due to significant increases in RctB concentration . Comparison of growth curves of cells with chrI-4 , -5 and -6 showed that while cells with chrI-4 and -5 grew similarly , cells with chrI-6 grew similarly to cells with the empty vector ( data not shown ) . Since chrI-6 shows little replication enhancer activity ( Figure 3A ) , these results confirm that the enhanced growth owes to the presence of an active enhancer fragment . The chrI-4 enhancer fragment contains an AT-rich stretch , several GATC sites and a DnaA box with three mismatches to the consensus sequence ( Figure S1B ) . The fragment , however , failed to show origin function ( Figure S1C ) . It appears that DnaA protein is also not important for the chrI-4 enhancer activity because poriII copy number increased in dnaA ( ts ) 204 strain ( BR4433 ) even at the non-permissive temperature of 42°C . Taken together , these results indicate that a 70-mer site in chrI can significantly enhance the initiator activity of RctB in E . coli . Its importance is further suggested by its conservation in the Vibrio genus ( Figure S4 ) . Here we asked whether the enhancer site could bind purified RctB in vitro , as would be expected from the ChIP-chip results . When the chrI-4 DNA was used as a linear fragment , no binding could be detected by EMSA ( data not shown ) . Linear fragments of chrI-4 DNA also failed to inhibit RctB binding to a 39-mer site ( data not shown ) . The effect on RctB binding to iterons was ambiguous because the binding was weak to start with [30] . However , when the chrI-4 sequence was present in a supercoiled plasmid ( pBJH170 ) , although we could not detect RctB binding to the plasmid itself by EMSA ( Figure S5A ) , the plasmid caused a reduction in RctB binding to a 39-mer ( Figure S5B ) . These results indicate that RctB can interact with the chrI site only in the supercoiled form . This conclusion was supported by DNase I footprinting of RctB , where a footprint could be detected only when the chrI-4 sequence was in a supercoiled plasmid ( Figure 3C ) . The bases protected from DNase I cleavage were distributed within a stretch of 18 bp ( coordinates 818020–818037 ) in the middle of the 70-mer site . When the specific protected bases ( shown in bold here and in Figure S6A ) were mutated from GAAATGCAGAATATGTAAC to AGGATGCAGAACGTGTGGC , RctB essentially failed to protect the mutant site ( chrI-9m ) from DNase I cleavage . The chrI-9m also lost its replication enhancer activity ( Figure S6B ) . As will be discussed later , extra copies of the enhancer site decreases growth of V . cholera . The growth inhibition was not seen when the chrI-9m was used instead of chrI-9 ( Figure S6C ) . These results indicate that RctB directly interacts with the replication enhancer site in chrI . Since the chrI site enhances replication through interactions with RctB without affecting RctB concentration , the mechanism of enhancement is likely to be by altering the regulatory activity of the initiator . To begin to understand the mechanism , we tested the effect of the replication enhancer on the activity of poriII plasmids that have different copy numbers because of differing numbers of iterons and 39-mers they carry ( Figure 4A ) . If the mechanism of replication enhancement is by lowering the inhibitory activity , then a copy number increase is expected to be significant only in 39-mer carrying poriII plasmids , since 39-mers are the primary inhibitors of chrII replication . However , the presence of chrI-4 in trans increased copy number of poriII whether or not the 39-mers were present in poriII plasmids , although the increase was more pronounced in 39-mer carrying plasmids . Replication enhancement was also seen with the RctB mutant , ΔC157 , which is defective in 39-mer binding [30] ( Figure 4B ) . From what follows , it appears that the enhancer can promote replication directly by promoting iteron binding of RctB and indirectly by reducing 39-mer binding of RctB . To assay the effect of the enhancer on RctB binding to iterons and 39-mers , we took advantage of the presence of two natural promoters in the origin of chrII . One promoter , PrctA , is associated with two iterons , and the other promoter , PrctB , with an operator that is naturally a truncated 39-mer ( a 29-mer ) but can also be replaced with a 39-mer without changing the operator activity [30] . The promoter activities were measured after fusing them to the lacZ reporter gene ( of a multicopy plasmid , pMLB1109 ) . RctB represses the activity of both the promoters , and this repression has been utilized as a convenient proxy for RctB binding to its specific sites in vivo [30]–[32] . When the chrI-4 site was present , RctB could more effectively repress PrctA ( the promoter activity decreased from 65±4 to 35±5% at low RctB concentration ) , suggesting that chrI-4 improves RctB binding to iterons ( Figure 4C ) . In the case of PrctB , chrI-4 had the opposite effect; here the promoter repression was less in the presence of chrI-4 ( the promoter activity increased from 62±7 to 79±6% at low RctB concentration ) , suggesting that chrI-4 makes 39-mer binding less effective . The decreased binding of RctB to a 39-mer in the presence of chrI-4 was also seen in vitro ( Figure S5B ) . When chrI-4 was replaced with chrI-6 , which is defective in enhancer activity , repression for both the promoters did not change significantly from those seen with the empty vector . Since 39-mers inhibit replication and iterons activate replication [26] , reduced binding to the former and increased binding to the latter are both consistent with the observed replication enhancement by chrI-4 . Together , these results suggest that the enhancer remodels RctB to alter its DNA binding activities . RctB binding to both iterons and 39-mers are greatly stimulated in the presence of DnaJ and DnaK chaperones in vitro and in E . coli [30] . As shown in Figure 4D , when the presence of poriII was selected in an E . coli ΔdnaKJ host ( BR4392 ) , the cells growth was negligible whether RctB was supplied at basal or induced levels ( using 0 . 002% arabinose ) . In contrast , even the basal level of RctB allowed near maximal growth in the presence of chrI-4 . We confirmed that the increased growth was due to increased oriII activity; the copy number of poriII , measured by qPCR , increased 3 . 1±0 . 5 fold in the presence of chrI-4 . The induced level of RctB used in these experiments was undetectable by Western analysis . Using quantitative RT-PCR , we confirmed that upon rctB induction , the gene was expressed at similar levels in cells with and without chrI-4 ( 8 . 2±2 . 1 and 7 . 6±1 . 9 , respectively ) . When induced with 0 . 2% arabinose , RctB could be detected by Western analysis and its level was similar in cells with and without chrI-4 ( Figure S3A , lanes 7 , 8 ) . The results support the earlier inference that the enhancer is increasing the activity of RctB and not its concentration . The altered binding of RctB to iterons and to a 39-mer in the presence of chrI-4 was also seen in a dnaK7 strain ( BR4390 ) ( Figure S7 ) . These results suggest that chrI-4 could be functioning like a DNA chaperone to remodel RctB . The remodeling , however , appears to be different in the two cases because the chaperones improve binding to both iterons and the 39-mer ( tested in vitro; [30] ) , whereas chrI-4 improved binding only to the iterons but decreased binding to the 39-mer . We note that RctB binding to chrI-4 could be seen in vitro only in the presence of chaperones ( Figure 3C , Figures S5B and S6A ) . It appears that in vitro , chrI-4 remodels RctB after it has been acted upon by chaperones . The apparent dnaKJ independence could be due to the presence of other chaperones that substitute for DnaJ and DnaK activities . Alternatively , the purification of RctB from overproducing cells could have affected its activity , imparting to it a form different from that present in a ΔdnaKJ or dnaK7 host . To test whether the newly identified RctB binding sites have a replication phenotype in the native host ( V . cholerae ) , we chose the chrII-10 site , which contains both an iteron and a 39-mer and showed the strongest replication inhibitory activity , and the chrI-4 site , which showed the maximal replication enhancer activity . Plasmids carrying these sites were used to transform WT V . cholerae cells ( CVC209 ) . The colony size of the transformants was significantly smaller in the presence of either chrII-10 or chrI-4 ( Figure 5A ) . The reduction in the case of chrII-10 was expected because the iterons and 39-mers are known to titrate RctB , which could reduce V . cholerae growth by reducing chrII replication [26] . In fact , when additional iterons were added to the chrII-10 plasmid , no viable transformants were recovered . However , deletion of the chrII-10 site alone from the V . cholerae chromosome did not affect viability and did not show a growth phenotype ( Figure S2A ) . The reduction of colony size in the case of chrI-4 is also expected due to over-activity of oriII . Increased chrII copy number due to overexpression of RctB or due to a copy-up rctB mutation reduced cell growth previously [33] , [34] . That over activity of oriII could be the cause of growth reduction was confirmed by measuring oriI/terI , oriII/terII , and oriII/oriI marker ratios using qPCR ( Figure 5B ) . The difference in oriI/terI ratios in cells with and without chrII-10 or chrI-4 sites was insignificant , suggesting that these newly identified RctB sites do not affect initiation of chrI replication . As expected , both chrII-10 and chrI-4 oppositely affected chrII replication: In the presence of extra copies of chrII-10 , the oriII/terII ratio decreased , and in the presence of chrI-4 , the ratio increased ( pchrII-10/vector and pchrI-4/vector , Figure 5B ) . Deletion of the sites showed the opposite effect , also as expected ( ΔchrII-10/WT and ΔchrI-4/WT , Figure 5B ) . These results are consistent with the inference from poriII copy number measurements in E . coli that indicated that the chrII sites inhibit and the chrI site enhances oriII-specific replication . The chrI-4 site could be deleted without causing a significant growth change in V . cholerae ( WT/vector vs . ΔchrI-4/vector , Figure S2B ) . When the chrI-4 deleted host was transformed with a medium copy number plasmid carrying the chrI-4 sequence , pchrI-4 ( pBJH188 , pACYC177-derived ) , there was no significant reduction in the growth of the transformants either ( ΔchrI-4/pchrI-4 ) . The same plasmid however reduced the growth of the WT V . cholerae host ( WT/pchrI-4 ) . Thus , a change of chrI-4 copy number by one ( that exists between the WT and the chrI-4 deleted hosts ) can cause a detectable growth phenotype in the presence of pchrI-4 . Although the chrI-4 deleted host did not show a growth phenotype , a reduction in oriII copy number compared to that in WT was evident by marker frequency analysis using qPCR ( ΔchrI-4/WT , Figure 5B ) . These results indicate that the activity of the chrI-4 site although modest is physiologically relevant . E . coli deleted for regulators like SeqA does not show a strong growth phenotype but replication initiation timing becomes heterogeneous in such cells [35] . When duplication timing of the oriI and oriII loci were determined by fluorescence microscopy , it was delayed in ΔchrI-4 cells specifically for oriII ( Figure 5C ) . Normally , the origins duplicate ( and segregate ) at a particular cell length . Cells with one oriII focus could be longer in ΔchrI-4 background compared to such cells in the WT . The modal cell length also increased and the separation between the duplicated foci became heterogeneous upon chrI-4 deletion ( Figure S8A and B , respectively ) . ChrII-less cells that are frequently found in ΔparAB2 mutants were not found in ΔchrI-4 mutants [36] ( Figure S2C ) . These results suggest that the chrI-4 site normally functions in controlling the timing of chrII replication initiation .
Communication among chromosomes is an open question in bacteria with divided genomes . In V . cholerae , the possibility of communication was suggested by the finding that replication of both chrI and chrII involves common factors such as DnaA and Dam [9] . To the extent studied , these factors appear to be unlikely candidates for coordinating replication , since DnaA is not a regulator of chrII replication and Dam is essential only for chrII replication [7] , [27] , [29] . Moreover , blocking chrII replication specifically did not disturb the timing and initiation rate of chrI [37] . The influence of chrI replication on chrII replication was heretofore unknown . As discussed in the Introduction , DnaA binding sites outside of the origin serve as major regulators of E . coli chromosomal replication . This motivated us to search for extra binding sites of RctB outside the chrII origin region . In iterons of chrII , only the hexamer TGATCA is fully conserved . The hexamer includes the Dam methylation site , GATC , and methylation at the adenine residue is required for efficient RctB binding and chrII replication [27] , [29] . The importance of the less conserved flanking sequences of the hexamers has not been tested . If the hexamer were to be sufficient for RctB binding , then the occurrence of about 1000 copies of such hexamers genome-wide would suggest that RctB titration to those sites could have a major regulatory consequence to chrII replication initiation , analogous to how the genome-wide presence of DnaA binding sites contribute to E . coli replication control . ChrI , being three times the size of chrII , could then play a proportionately larger role in controlling chrII replication . However , the TGATCA is not sufficient for RctB binding ( foot note ‘a’ , Table S2 ) and ChIP-chip experiments revealed only five titration sites and they were all in chrII . ChrI thus cannot be regulating chrII replication by titrating RctB . All the five titration-sites being located close to the origin duplicate shortly after chrII replication initiation . The early increase in the number of sites would maximize initiator titration and , like several previously described mechanisms , could contribute to prevention of premature reinitiation of chrII replication . This role being reflexive , can serve only indirectly in inter-chromosome coordination . The implication is that the intrinsic chrII replication control system needs to be efficient for an external signal from chrI to be effective in precisely timing the replication of the two chromosomes . By contributing to the overall replication control of chrII , the five sites could also be contributing indirectly to coordinate replication initiation . So far , we have deleted only the chrII-10 site without significant effect on oriII activity ( Figure S2A ) . A possible reason could be that the site is one of 22 regulatory sites of chrII: 16 iterons ( 11 in the origin and five identified in this work , Table S1 ) , four 39-mers ( three in the origin and one identified in this work , Table S1 ) , one parS2-B [38] and the chrI enhancer , and the deletion of one out of 22 sites may not be expected to have a strong effect . ChrI also contains one of the parS2 sites that bind the chrII-specific segregation protein ParB2 [39] . The functional significance of this finding has not been determined and it is not clear whether the two chromosomes communicate for segregation . Both chromosomes also encode a dimer resolution system that monomerizes chromosomal dimers that can form by homologous recombination between replicated sisters [40] . Dimer resolution before cell division is required for proper segregation of sister chromosomes . Although in V . cholerae the resolution sites ( dif ) are chromosome-specific , the same set of proteins ( XerC , XerD and FtsK ) act on those sites and they are all encoded in chrI . It is possible that at the time of cell division the final stages of segregation of the two chromosomes are coordinated through these proteins . However , there is no evidence that completion of segregation dictates the timing of replication initiation . Whereas plasmids generally initiate replication throughout the cell cycle [41] , chrII despite its presumed plasmid origin initiates replication at a particular time of the cell cycle , like other chromosomes [6] . The chrII replication system appears to have retained not only the characteristics of the replication system of its presumed progenitor-plasmid , but also added several , if not all , mechanisms used by the E . coli chromosome to time its replication initiation , as detailed below . The E . coli chromosome origin has abundant Dam methylation sites at which Dam and SeqA proteins act , and extra initiator ( DnaA ) titration sites outside of the origin , including special DnaA binding sites called datA and DARS that inhibit and activate replication , respectively [17] , [19] . The chrII origin is also equally enriched for Dam methylation sites and depends upon Dam and SeqA for replication initiation and its control . As we report here , extra titration sites are present in chrII . The 39-mers , which are special replication inhibitory sites of chrII not found in plasmids , can be thought of as functional equivalents of datA . Similarly , the enhancer of chrII replication present in chrI can be likened to DARS . The extra features of chromosomal replication might have been necessary to accomplish once per cell cycle replication and proper timing of replication initiation , which are apparently less critical requirements for plasmid replication . One requirement for the tighter control of chrII replication versus plasmid replication appears to be prevention of over-replication of chrII , which is detrimental to V . cholerae growth ( [33]; this study ) . It seems also possible that the deleterious effect of extra copies of chrI-4 is not due to the extra copies of chrII per se , but rather to improperly timed initiation of chrII ( Figure 5C ) such that simultaneous termination of the two chromosomes is compromised and some sort of partitioning problem arises . Here we find that the chrI enhancer site increases RctB binding to iterons , and decreases RctB binding to a 39-mer . The increase in iteron binding can promote replication initiation directly and the decrease in 39-mer binding can do so indirectly . The two activities could be seen as independent; the presence of a 39-mer was not required to see the stimulation of iteron binding , and vice versa ( Figure 4C ) . Replication stimulation activity was also seen using an oriII plasmid devoid of 39-mers ( Figure 4A ) and using an RctB mutant , ΔC157 , which is defective in 39-mer binding [30] ( Figure 4B ) . It is possible that the chrI site remodels RctB in such a way that it alters its binding to both the iteron and the 39-mer . As was reported earlier , we find that the absence of the chaperones DnaJ and DnaK greatly inhibited the growth of cells that are dependent on the functioning of the chrII origin [30] . This inhibition was relieved when the chrI site was provided in trans in a ΔdanKJ host ( Figure 4D ) . These results can be understood if the enhancer promotes RctB activity by remodeling the protein in the absence of DnaJ and DnaK . It is common among DNA binding proteins to change their conformation upon interaction with their cognate DNA binding sites [17] , [19] , [42]–[45] . The remodeling activity of the enhancer was also suggested by determination of the RctB level in V . cholerae . Upon deletion of the chrI-4 site , the initiator level increased by 58±24% compared to that in the WT cell ( Figure S3B ) . There was also increase in rctB transcription , although the increase was less significant: the ratio of rctB transcripts in ΔchrI-4/WT was 1 . 28±0 . 34 by qRT-PCR and 1 . 23±0 . 22 by promoter fusion to lacZ ( Figure S3C ) . The altered expression of rctB is expected considering that it is an autorepressed gene and chrI-4 site alters RctB DNA binding ( Figure 4C ) [31] , [46] . Since in ΔchrI-4 cells chrII replication tends to decrease ( Figure 5B ) , the results suggest that , in spite of the increase in RctB concentration , the initiator activity can decrease in the absence of chrI-4 site . In the presence of pchrI-4 , however , there was no significant increase in RctB concentration either in V . cholerae or in E . coli ( Figure S3A and B ) . Together , the results suggest that changing the initiator activity is the main role of the chrI-4 site . The E . coli sites datA and DARS that inhibit and activate replication , respectively , possibly also remodel DnaA . The initiator DnaA is an ATPase and to serve as initiator DnaA needs to be bound to ATP . The datA site inhibits initiation by converting DnaA-ATP to DnaA-ADP and the DARS sites promote initiation by doing the opposite conversion of DnaA-ADP to DnaA-ATP [17] , [19] . These conversions probably require structural changes in DnaA to increase the ATPase activity and release the bound ADP , respectively . The datA and DARS sites may be remodeling the cognate initiator like the chrI enhancer site . Like DnaA , RctB has been reported to be a weak ATPase [34] . In the same study , ATP was found to strongly inhibit RctB binding to the chrII origin DNA , although in our hands ATP showed only a nominal inhibitory effect ( Figure S9A , lanes 2 and 6 ) . On the contrary , ATP was required to promote the robust stimulatory activity of the chaperones on RctB binding to 39-mers ( lanes 10 and 12 ) . In the presence of chaperones , which are naturally present in vivo , ATP stimulated binding even in the presence of vast excess of ATP ( 5 mM as opposed to the optimal concentration of 0 . 1 mM ) . These results indicate that the chaperones override any inhibitory activity of ATP . In the absence of chaperones , the nominal inhibitory activity of ATP on DNA binding of RctB was also not affected significantly in the presence of the chrII-10 or the chrI-4 site ( Figure S9B ) . In the presence of these sites , the ATPase activity of RctB also did not change significantly ( Figure S9C ) . We also tested a mutant RctB ( R269S ) whose DNA-binding was reported not to be inhibited by ATP [34] . The mutant , as reported , conferred a higher copy number to a mini-chrII plasmid in E . coli ( Figure S9D ) . The mutant however remained sensitive to replication inhibition by the chrII-10 site and replication enhancement by the chrI-4 site . Together the results suggest that the enhancer is unlikely to be functioning by altering the ATPase activity of RctB . In iteron-based plasmids , dissociation of initiator dimers is the main mechanism by which chaperone proteins stimulate replication [47]–[49] . RctB binds to iterons both as monomer and dimer . The monomer binding is thought to be conducive to replication initiation since copy-up mutants of RctB were more proficient in binding as monomer [30] , [50] . However , using a bacterial two-hybrid system and a second assay based on λPR repression by the λ repressor [51] , [52] , the chrI-4 site did not appear to affect RctB dimerization ( Figure S10A and B , respectively ) . The mechanism of enhancement appears unlikely to be by reduction of RctB dimerization . Remodeling of RctB that leads to increased iteron binding and decreased 39-mer binding appears to be the primary mechanism of the chrI-4 enhancer function . The chrI site is a new kind of RctB binding site , as it has no homology to the sites present in the chrII origin . The site size is also large , ∼70 bp , whereas typical protein binding sites in bacteria are seldom even half that long . The requirements for an AT rich stretch and supercoiling suggest that the site needs to be in the single-stranded state to be active . We tried RctB binding individually to two complimentary single strands of the chrI site ( as 70-mer oligonucleotides ) by EMSA but without success ( data not shown ) . Both the strands are apparently required for the site to assume proper conformation driven by supercoiling . We considered whether transcriptional activity of the site could effect this change . A promoter is present within the minimal sequence required for enhancer activity , chrI-9 , spanning coordinates 818000–818069 ( Figure S11A ) . This promoter was not active in a longer fragment , chrI-4 . The extra sequences ( 817947–818000 ) present in chrI-4 upstream of chrI-9 apparently repress the promoter by a mechanism that remains to be explored . In any event , when the promoter region was mutated at the −35 ( m1 ) or −10 ( m2 ) , or at both sites in chrI-4 and chrI-9 , the promoter activity decreased in m2 and in the double mutant , but the replication enhancer activity was not significantly affected ( Figure S11B and C ) . These results indicate that the promoter activity internal to the chrI site is not critical for the replication enhancer activity . Passage of the replication fork across the chrI site might also cause the conformational switch to the single-stranded state . Moreover , by the passage of the fork the enhancer site concentration would double , which should increase the fraction of remodeled RctB and thus help time the chrII replication initiation more effectively . About 55% of the 2 . 97 Mb chrI will have duplicated before a replication fork reaches the replication enhancer site it carries . Since the two chromosomes terminate at about the same time [19] , by the time chrII replication starts , the chrI replication have proceeded even further by about 10% on each replichore , which would allow ample opportunity for RctB to interact with the nascent enhancers . It is tempting to speculate that the duplication of the replication enhancer site in chrI shortly before the time at which chrII must initiate if the two chromosomes are to terminate simultaneously , is important for this coordination of replication of the two chromosomes . RctB-enhancer interaction possibly stimulates chrII replication in one of two ways . The enhancer-bound RctB might directly engage with the initiation complex at oriII , so as to stimulate replication , analogous to the functioning of cis-acting transcriptional enhancers in bacteria and eukaryotes . The interactions can also happen in trans between chromosomes as in “chromosome kissing” [53] , [54] . However , so far we have failed to detect direct engagement of the enhancer with the initiation complex by the chromosome conformation capture ( 3C ) assay . Alternatively , interactions with the enhancer might lead to a conformational change , which is stable enough for the remodeled initiator to reach the chrII origin by diffusion . In addition to E . coli DARS , replication enhancer sites have been found in plasmids pT181 and pSC101 [55] , [56] . In both cases , the enhancer sites , like the chrI enhancer site , bear no similarity to initiator binding sites in the origin . In pSC101 , the enhancer has gyrase binding sites , which promote replication by increasing the negative superhelicity of the plasmid , particularly near the replication origin , that favors initiator-origin interaction . The cmp locus of pT181 is also believed to promote initiator-origin interaction , but the mechanism is not known . On the other hand , DARS and datA both have recognizable DnaA binding sites , which are essential for their function . A deeper mechanistic understanding of the chrII replication enhancer function will require more structural probing of RctB and its likely alternation in presence of the enhancer .
E . coli and V . cholerae strains , and plasmids used in this study are listed in Table S3 . ChIP-chip assay was performed exactly as described [38] . Cells used here were V . cholerae WT ( CVC209 ) and MCH1 ( CVC2099 ) . As before , ChIP ( Cy5 ) signals were divided by corresponding input DNA ( Cy3 ) from three independent experiments . The difference in mean Cy5/Cy3 signals between the WT and MCH1 strains was plotted in Figure 1 . The copy number of poriII was measured using a three-plasmid system as described [26] . E . coli ( BR8706 ) cells harboring the poriII ( pTVC25 , 31 , 35 , 210 or 524 ) and prctB ( pTVC11 ) that supplies the initiator from an arabinose inducible promoter , was transformed with a pBR322-derived plasmid containing one of the newly identified RctB binding sites . The plasmid copy number was determined by harvesting overnight grown cells directly from transformation plates containing either 0 . 002 or 0 . 2% arabinose , the conditions referred to in the text as supplying RctB at low or high levels , respectively . EMSA was performed as described [57] . A total of 1 . 2 pmol of DNA fragment , carrying one copy of a binding site with 100 bp of vector sequences ( pTVC243 ) at both flanks , was end-labeled with 32P and reacted with RctB at two different concentrations ( 2 and 20 nM ) . The binding was monitored using a 5% polyacrylamide gel and autoradiography . For competitive binding assay ( Figure S4 ) , DNA was not radiolabeled and visualized after staining with SYBR Green EMSA nucleic acid gel stain at 10 , 000× dilution for 30 min at room temperature ( Molecular Probes ) . The binding of RctB was performed under the same condition as was used for EMSA . The binding reactions were treated with 0 . 01 unit of DNase I ( Promega ) for 1 min at room temperature . DNaseI was inactivated by adding 15 mM EDTA followed by heating ( 95°C , 10 min ) . The DNA was purified using Qiaquick PCR purification kit ( Qiagen ) . Primer extension was performed using 6 FAM-labeled primer and Thermo Sequenase polymerase ( USB ) according to the manufacturer's protocol . Amplified products were purified using Qiaquick PCR purification kit . The purified products along with GeneScan 500-ROX size standard ( Applied Biosystems ) were denatured by adding Hi-Di formamide ( Applied Biosystems ) followed by heating ( 75°C , 10 min ) and immediately chilled on ice . The single stranded DNA was analyzed on an ABI 3130×l Genetic Analyzer ( Applied Biosystems ) and data was analyzed using GeneMapper ( v . 3 . 7 ) software . The deletion was achieved in two steps . First , the chrI-4 sequence was substituted with an FRT-Zeo-FRT cassette by the allele-exchange method [29] . Second , the Zeo cassette was excised , leaving one FRT site in place of the chrI-4 sequence . To provide homology for the allele exchange , ∼one kb natural flank of chrI-4 followed by a FRT site was cloned upstream of the Zeo cassette in pEM7-Zeo vector that resulted in pBJH242 . Likewise , another FRT site followed by ∼one kb of natural sequences at the other flank chrI-4 was cloned downstream of the Zeo cassette of pBJH242 that resulted in pBJH245 . The cloned region of pBJH245 ( upstream flank of chrI-4-FRT-Zeo cassette-FRT-downstream flank of chrI-4 ) was amplified by PCR and the linear product was introduced by natural transformation to CVC1121 , a hapR+ derivative of N16961 . The transformants were selected for Zeocin resistance , and the replacement of the chrI-4 sequences by the Zeo cassette was confirmed by PCR amplification of the region and sequencing of the PCR product . The Zeo cassette of the resulting ΔchrI-4::FRT-Zeo-FRT strain ( CVC2540 ) was excised by further transformation with an unstable plasmid supplying the Flp recombinase ( pBLO1218 ) . The plasmid , when not selected , was lost spontaneously from the final strain ΔchrI-4::FRT ( CVC2542 ) . The desired deletion/substitution was confirmed by PCR amplifying the mutated region and DNA sequencing . The same strategy was used to make ΔchrII-10::FRT-Zeo-FRT strain ( CVC2565 ) . The fragment used for natural transformation was a PCR product that had ∼one kb homology to the left flank of chrII-10 ( coord . 1026995–1027995 ) -FRT-Zeo-FRT- ∼one kb homology to the right flank of chrII-10 ( coord . 1028034–1029033 ) . Frequencies of four markers , oriI , oriII , terI and terII , in exponentially growing cells in L broth were determined by qPCR using a PTC-200 Peltier Thermal Cycler ( MJ Research ) and a LightCycler 480 SYBR Green I Master ( Roche ) mix , as described [29] . Fragments containing putative promoters were cloned into a promoter-less lacZ containing plasmid ( pMLB1109 ) . The resultant plasmids were used to transform E . coli BR8706 carrying prctB ( pTVC11 ) . Cells harboring these two plasmids were cultivated in L broth containing 0 , 0 . 002 or 0 . 2% arabinose at 37°C to exponential phase and β-galactosidase activity was measured , as described [58] . To localize oriI and oriII , P1parS as a P1parS-Km cassette and pMTparS as a pMTparS-Sp cassette were integrated at approximately +135 kb region on chrI and +40 kb region on chrII , respectively [58] . Both cassettes were inserted into WT ( CVC1121 ) and ΔchrI-4 ( CVC2542 ) strains , and the resulting strains ( CVC2553 and CVC2554 ) were transformed with a plasmid expressing mCherry-pMTparB and gfp-P1parB ( pRN010 ) . Cells were grown in M9+glycerol medium at 37°C to log phase and observed under a fluorescence microscope , as described [58] . Locations of fluorescent foci were measured using the ImageJ ( rsb . info . nih . gov/ij/index . html ) . | Genome maintenance in dividing cells requires that the chromosomes replicate reliably once per cell cycle , and that this replication be timed to allow for proper segregation of the daughter chromosomes before cell division . In organisms with divided genomes , eukaryotes and a significant class of bacteria , the chromosomes must avoid interference with one another . They exhibit disciplined chromosome choreography , involving several regulators and control circuits that , even in the simplest organisms , are poorly understood . Here we examine the regulatory processes involved in maintaining the two chromosomes of the well-studied and medically important pathogen Vibrio cholerae . We provide evidence that a site in chromosome I can control the frequency and timing of replication of chromosome II . The mechanism involves a DNA-mediated remodeling of the chromosome II-specific initiator of replication by the chromosome I site . The site enhances the activity of the protein by differentially affecting its affinity for inhibitory and stimulatory sites on chromosome II . Our results provide the groundwork for determining whether coordination of replication might be a conserved feature that maintains chromosomes in proliferating cells of higher organisms . | [
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] | 2014 | Chromosome I Controls Chromosome II Replication in Vibrio cholerae |
Nutrition is a key factor in host–pathogen defense . Malnutrition can increase both host susceptibility and severity of infection through a number of pathways , and infection itself can promote nutritional deterioration and further susceptibility . Nutritional status can also strongly influence response to vaccination or therapeutic pharmaceuticals . Arthropod-borne viruses ( arboviruses ) have a long history of infecting humans , resulting in regular pandemics as well as an increasing frequency of autochthonous transmission . Interestingly , aside from host-related factors , nutrition could also play a role in the competence of vectors required for transmission of these viruses . Nutritional status of the host and vector could even influence viral evolution itself . Therefore , it is vital to understand the role of nutrition in the arbovirus lifecycle . This Review will focus on nutritional factors that could influence susceptibility and severity of infection in the host , response to prophylactic and therapeutic strategies , vector competence , and viral evolution .
Defined as any imbalance resulting in a deficiency or excess , malnutrition is the principal source of immunodeficiency worldwide [1] . Globally , as of 2014 , it is estimated that 1 . 9 billion adults ( >18 years of age ) are overweight or obese by Body Mass Index ( BMI ) —18 . 5 kg/m2 to 24 . 9 kg/m2 = healthy weight , 25 . 0 kg/m2 to 29 . 9 kg/m2 = overweight , and ≥30 kg/m2 = obese—while 462 million are underweight . In children ( <5 years of age ) , around 225 million are undernourished , around 42 million are overweight/obese [2 , 3] , and approximately 45% of deaths are linked to malnutrition , mainly in developing countries [3] . In lower- to middle-income countries , the rate of increase of childhood obesity is more than 30% higher than in developed countries . Greater than 65% of the global population lives in countries where overweight and obesity kill more people than underweight [2] . Undernutrition is also rampant throughout developed nations [4] . Overall , it is estimated that greater than one-third of the global disease burden could be eliminated by correcting malnutrition [5] , and feeding children an adequate diet could prevent approximately 2 . 5 million deaths per year from pneumonia , diarrhea , malaria , and measles combined [6] . Malnutrition increases host susceptibility and severity of infection through several pathways , including weight loss , immune dysfunction , decreased epithelial integrity , and inflammation . In addition , infection itself can impact host nutritional status through infection-associated anorexia , altered metabolic rate , and altered dietary absorption , further complicating susceptibility and severity [1 , 7 , 8] . Indeed , frequency of exposure to infectious diseases increases the risk of poor nutrition in a vicious malnutrition–infection–malnutrition cycle [9 , 10] . Overall , it is apparent that the interactions between nutrition and infectious disease are complex , with interplay between host , pathogen , and diet . This Review will discuss what is currently known ( and unknown ) about the relationship between nutritional status and arboviruses in both the vector and the human host .
Arboviruses are spread to vertebrate hosts by hematophagous arthropod vectors . Transmission occurs via biological transfer , requiring successful replication in vector species as well as adequate viremia in the host before transmission is achievable . As of 1992 , 535 virus species belonging to 14 virus families are registered in the International Catalog of Arboviruses [11] , and new viruses are being described on a regular basis [12] . Of these species , greater than 100 are known to cause zoonotic diseases , mainly in four virus families: Togaviridae , Flaviviridae , Bunyaviridae , and Reoviridae [11] . While the majority of arboviruses circulate in tropical and subtropical regions , many arboviruses also have been introduced and thrive within temperate regions . Indeed , these viruses , along with their vector species , have spread exponentially in their geographical distributions in accordance with global trade routes and industrialization [13 , 14] . This Review targets arboviruses transmitted by mosquitoes that have high public health importance and risk , namely chikungunya virus ( CHIKV; Togaviridae ) , dengue virus ( DENV; Flaviviridae ) , Zika virus ( ZIKV; Flaviviridae ) , yellow fever virus ( YFV; Flaviviridae ) , Japanese encephalitis virus ( JEV; Flaviviridae ) , and West Nile virus ( WNV; Flaviviridae ) . Combined , these viruses account for hundreds of millions of clinical/symptomatic infections globally , resulting in tens of thousands of deaths per year . However , symptoms in humans and animals range from mild to subclinical infection all the way to encephalitic or hemorrhagic , so the total number of cases per year may be underestimated ( Table 1 ) . In addition , due to the paucity of data on nutrition and arbovirus infection , other viruses of concern will also be mentioned where literature is available , including La Crosse virus ( LACV; Bunyaviridae ) , Sindbis virus ( SINV; Togaviridae ) , Ross River virus ( RRV; Togaviridae ) , Western equine encephalitis virus ( WEEV; Togaviridae ) , Rift Valley Fever virus ( RVFV; Bunyaviridae ) , and St . Louis encephalitis virus ( SLEV; Flaviviridae ) .
To review what is known on nutrition and arbovirus infection , a comprehensive search was conducted of the peer-reviewed literature available on Pubmed using a number of search terms . Combinations of terms for nutrition ( nutrition , diet , feeding , obesity , body mass index , vitamin , micromineral ) were used in combination with general and specific terms for arboviruses ( arbovirus , alphavirus , flavivirus , bunyavirus , dengue , zika , chikungunya ) and/or mosquito-associated terms ( mosquito , Culex , Aedes , vector competence ) to find papers related to the Review . All papers were included in the study as long as they pertained to nutritional influences on arboviruses .
The interplay of transmission cycle , host range , and evolution of arboviruses is a complex process . Arboviruses require a natural host as well as a vector for transmission [25] . While arthropod vectors abound , mosquitoes and ticks carry the most known virus species [11 , 25 , 26] . Further , of the 300 types of mosquitoes known to transmit arboviruses , female mosquitoes of the genera Aedes or Culex are most frequently associated with transmission [11 , 25] . Arboviral diseases are generally associated with a specific vector and natural host species in rural epizootic and enzootic cycles . Humans and other large mammals tend to be accidental dead-end hosts for many of these cycles; however , spillover transmission to humans can lead to urban epidemic cycles where enzootic amplification is no longer required [25] . Since nutrition is essential for all organisms , numerous factors could be affected by changing nutritional status in reservoir and secondary amplification hosts as well as enzootic and/or endemic and epidemic vectors ( Fig 1 ) .
Few prospective studies have been conducted on nutritional status and arbovirus susceptibility . Therefore , seroprevalence remains the primary means of associating nutrition , infection susceptibility , and arbovirus infection in human hosts ( Table 2 ) . Several studies show a strong association between high body weight and obesity and previous arboviral infection . In Madagascar , overweight pregnant women had significantly increased risk for CHIKV seroconversion [27] . On the island of La Réunion , overweight and obese individuals were also at increased risk during the 2006 outbreak [28 , 29] . Obesity and increased body weight has also been associated with seropositivity for SINV in Sweden [30] , DENV in Thailand [31] , arboviruses of the genus Phlebovirus ( family Bunyaviridae ) , and Toscana virus ( TOSV; family Togaviridae ) [32] . Overall , further prospective studies in arbovirus-endemic areas are crucial to define the relationship between infection susceptibility and nutritional status . In addition to body weight , the role of micronutrients on arbovirus infection susceptibility is understudied . Vitamins and minerals play a crucial role in immune function and are therefore essential to a proper antiviral defense . Vitamin D can reduce DENV infection and alter proinflammatory cytokine production in vitro [33 , 34] , and associations between vitamin D receptor gene polymorphisms and risk for DENV infection have been observed in host genetic studies [35] . Vitamin A levels ( retinol and β-carotene ) have been found to be decreased in DENV patients compared to healthy controls [36] . Zinc has also been shown to be an effective antiviral against many viruses [37]; however , little is known about its role in arbovirus infection aside from antiviral roles in vitro [38 , 39] . Overall , further research is needed to scrutinize the relationship between micronutrient status and arbovirus susceptibility . Aside from host susceptibility , nutrition could also play a vital role in the ability and desire of mosquitoes to bite a given host . In fact , biting rate figures heavily into vectorial capacity , a measurement of the efficiency of vector-borne transmission [40] . Mosquitoes rely on olfaction for locating food sources . Several compounds commonly secreted in human skin , sweat , and breath , such as lactic acid and CO2 , are potent mosquito attractants [26–28] . While host genetics plays a major factor in mosquito attractiveness [29] , diet has also been suggested as a possible factor for altering individual body odors associated with attraction [41] . Indeed , before the scientific understanding of heritability of attraction , diet was ( and possibly still is ) the most cited cause of differential susceptibility to mosquito bites . Homeopathic and complementary medicine have suggested several bioactive dietary components that may prevent or encourage mosquito bites to augment traditional preventions and treatments; however , scientific evidence appears to be controversial . Garlic has been touted as a mosquito repellent since before recorded history , possibly seeding the belief that garlic repels the vampiric behavior of blood consumption . In addition , garlic supplementation has long been used by dog and horse owners to prevent bites from blood-feeding insects . Scientifically , protection is suggested to be linked with the potent antimicrobial compound allicin [42] . While previous studies suggest some beneficial effect of garlic consumption , a more recent randomized , double-blind , placebo-controlled crossover study found no difference in bites or feeding behaviors of A . aegypti [43] . Consumption of vitamin B is also commonly prescribed for prevention of mosquito bites , especially vitamin B-1 ( thiamine ) ; however , no studies have shown any reduction in mosquito attraction with vitamin B supplementation [44] . Several other dietary ingredients have been purported to reduce mosquito attacks , such as onions , citrus fruits , lemongrass , chilies , apple cider vinegar , and vanilla . While compounds and/or essential oils found in these foods may prove to be effective mosquito repellants [45] , no scientific literature is currently available on consumption of these foods in regards to reduction of mosquito attacks or feeding behavior . Conversely , certain dietary components and nutritional states may increase host “attractiveness” and thereby increase bites . Similar to pregnant woman and individuals performing high-intensity exercise , obese and overweight individuals have increased CO2 production , increasing risk of mosquito bites [46] . Indeed , increased host body mass has been associated with increased and repeat feeding within groups of varied individuals [47] . Alcohol consumption may also alter susceptibility . Several studies have shown that consumption of alcohol as low as a single bottle of beer can increase host attractiveness to several mosquito species [48 , 49] . Consumption of potassium-rich and salty foods increases lactic acid production , thereby increasing attractiveness . High-sugar foodstuffs could also increase attractiveness due to the need for nectars and/or plant sugars in the mosquito diet . These claims are currently scientifically unsubstantiated , and further work is necessary to define the role of host nutrition in attraction or prevention of mosquito bites [50] . Once the host has been bitten and become infected , infection severity is a significant factor in potential outcome . Compared to susceptibility , more studies have observed a relationship between disease severity and nutrition ( Table 3 ) . Obese individuals have an increased risk for inflammatory CHIKV sequelae [51] , and diabetic status increases CHIKV severity and complications [52 , 53] . Severity of WNV , including mortality , has also been associated with diabetes both during the initial outbreak of WNV in the Americas in 1999 [54] and later studies [55] . Furthermore , diabetic mice infected with WNV have increased mortality and impaired viral clearance as compared to healthy controls [56] . Perhaps most is known about the association between nutritional status and DENV severity . Early observational studies suggested no association between poor nutrition and DENV hemorrhagic disease in Thailand [64] . However , later reports showed that malnourished children experience less severe cases of DENV versus those that are well nourished [65 , 66] . Further reports provided evidence for these anecdotes [57 , 58] , and subsequently , this association has also been observed in children in the Philippines and Vietnam [59 , 60] . Conversely , obesity has been associated with increased severity of dengue hemorrhagic fever and unusual disease presentation , such as encephalopathy and fluid overload , in several [31 , 61 , 62] ( but not all [63] ) studies . Unfortunately , many of these studies do not use consistent definitions for malnutrition or obesity and therefore can be difficult to compare . A large multinational study with consistent parameters for assessment of nutritional status is necessary to truly settle this debate . Possible links between micronutrients and arbovirus disease severity have also been examined in several studies . Associations between vitamin D levels ( measured by overall vitamin D status or vitamin D-binding protein ) and outcome of dengue fever are mixed [67–69] . Other micronutrients such as zinc [70–72] , vitamin A [36] , iron [73 , 74] , copper [73] , chromium [75] , and vitamin E [76] have also been reported to be associated with development of severe DENV disease . High doses of intravenous vitamin C have been used to treat infection with CHIKV , although more work is needed for confirmation [77] . While more research must be done to improve our understanding of the role of micronutrients and arbovirus disease , there are promising results that suggest ameliorating these nutrient deficiencies or excesses may reduce disease burden and severity . Prophylactic and therapeutic strategies are crucial for preventing infection and mitigating disease severity . Nutrition can play a crucial role in these vital strategies . Several arbovirus vaccines are now available or currently in development [78–81] and are critical for many arbovirus-endemic areas of the world , many of which have high rates of one or more nutritional deficiencies ( Fig 2 ) . The live-attenuated YFV vaccine , 17D , is by far the most widely administered arbovirus vaccine and has the only vaccine study with nutritional components . Children with kwashiorkor ( severe protein deficiency ) had a significantly lower seroconversion rate to 17D ( 12 . 5% ) versus healthy controls ( 83 . 3% ) [82] . To date , no studies have looked at arboviral vaccines in the obese host; however , several studies have shown obesity can reduce vaccine response or vaccine effectiveness against other pathogens [83–85] . Micronutrients , especially vitamins A and D , are also crucial for vaccination [86–89] . Unfortunately , there is a paucity of information on micronutrients and arbovirus vaccine response . One study showed vitamin A deficiency did not reduce response to YFV 17D vaccine [90] . However , individuals deficient in vitamin A had reduced lymphocyte and cytokine proliferation following vaccination , which could affect long-term vaccine efficacy . Further work is necessary on these crucial nutrients , especially since these viruses are endemic in areas of the world with significant micronutrient deficiencies [3] . In addition to vaccination , the use of antivirals as a therapeutic strategy against arboviruses is critical . During the 1873 YFV epidemic in Memphis , Tennessee , iced champagne was recommended as a curative [91] with negligible effect . Despite research efforts , antiviral treatment for arboviruses has not significantly progressed since that time . While a few antiviral compounds have been tested , few have shown success outside of small-animal laboratory models , and no specific antivirals are currently available for arboviruses [92–94] . Due to the lack of antivirals currently available , several groups have been investigating natural products and medicinal plants as a resource for combating these viruses . These products have a long history as part of traditional medicines and diets [95 , 96] . While not necessarily predictive of actual consumption , in vitro studies have revealed potential antiviral effects associated with several common food items . Curcumin , a principal component of the turmeric root , inhibits cell binding of DENV , ZIKV , and CHIKV [97 , 98] . Polyphenols such as delphinidin ( found in cranberries , grapes , and pomegranates ) and epigallocatechin gallate ( found in green tea and bananas ) have been investigated for their strong antiviral effects against WNV , ZIKV , DENV , and CHIKV in vitro [99 , 100] . Papaya leaf and garlic extracts alter the immune response during dengue infection , presumably reducing symptoms during infection without directly affecting viral replication [101 , 102] . Additional studies should be performed to assess the antiviral efficacy of these plant-derived compounds . Another issue to consider is the effect of malnutrition on pharmacokinetic processes , drug responses , and toxicity . Diet and nutrition are extremely important to the pharmatoxicological properties of chemicals and malnutrition has been shown to generate therapeutic inadequacies and changes in drug toxicity [103–105] .
Changes in larval nutritional status can directly affect adult mosquitoes and therefore arbovirus infection in the vector or host . Insufficient diet or starvation during larval development leads to smaller , often weaker adult mosquitoes with fewer reserves and a shorter life span , thereby decreasing chances of transmission and/or infection [128–131] . Restricted larval diet can affect the sex ratio ( more males versus females ) of C . molestus , resulting in fewer mosquitoes searching for a blood meal [132] . Larval nutrition also has a potential effect on adult host-seeking behavior . A . aegypti females originating from nutrition-deprived larvae are smaller and show less host-seeking behavior [131] . Interestingly , smaller Aedes females also probe more often and take multiple blood meals during one gonotrophic cycle ( life cycle of feeding and laying of eggs ) [118 , 133–136] . This increased contact could enhance the potential of single-host transmission by smaller females despite seeking a host less frequently . On the other hand , larger females have increased host-seeking behavior to cover higher energy requirements [137 , 138] , increased survival , and more reserves [139] , resulting in extended flights [134 , 140] and thereby increasing the possibility for transmission to multiple hosts . Adult nutrition can also impact potential transmission . Feeding on sugar ( carbohydrates ) prolongs the life span of mosquitoes [119 , 141–143] . Indeed , a nutrient-rich adult diet can compensate for life-shortening effects of nutrient deprivation during larval stages in Aedes [144–146] and Culex [147] species . Sugar deprivation leads to starvation and death [141 , 143 , 148–152] . Sugar-seeking behavior can also affect propensity of the vector to seek a blood meal . Generally , sugar feeding inhibits the search for a vertebrate host [120 , 145 , 153–155] . C . restuans females feed on nectar when they are unfed ( not blood-fed ) and when they are carrying eggs ( gravid ) , whereas A . vexans females take nectar only while unfed ( not blood-fed and/or not gravid ) . However , both species rarely feed on sugar while digesting a blood meal [156] . Interestingly , females of C . nigripalpus show enhanced host-seeking behavior following sucrose feeding , while starved females preferentially feed on honey [157] . For A . aegypti females , field observations show infrequent consumption of sugar [158]; however , regular sugar intake is observed under laboratory conditions leading to higher fecundity [121] . In carbohydrate-deprived A . aegypti , gravid females attempt to obtain blood meals more often [159] . In contrast to sugar consumption , protein components of blood , specifically amino acids , are necessary for development of the ovarian follicles and oviposition [109] . As such , the host species greatly influences egg number and , subsequently , number of mosquitoes able to transmit arboviruses . C . quinquefasciatus females show a higher fertility and fecundity when fed with chicken blood compared to bovine [160] . A . aegypti females preferentially feed on humans but will produce more eggs if they feed from other animals , possibly due to the low isoleucine content in human blood [161 , 162] . Indeed , A . aegypti have adapted to feeding on protein-rich , isoleucine-poor human blood by taking additional blood meals [118 , 133 , 138 , 163–166] . The importance of amino acids for initiation of egg development has been demonstrated by several feeding experiments utilizing artificial diets . A . aegypti fed a meal containing only 12 amino acids , including isoleucine , were able to produce eggs [167] . Similarly , feeding of isoleucine-rich globulins versus isoleucine-poor human hemoglobin induced the development of the ovaries and eggs [168 , 169] . Interestingly , arbovirus infection itself can also alter feeding behavior of mosquitoes under laboratory conditions . A . aegypti females infected with DENV feed longer [170] and LACV infected A . triseriatus females probed more but took less amount of blood than uninfected mosquitoes [171] . Nutrition could also affect vector competence itself ( Table 4 ) . For the purposes of this Review , vector competence describes the ability of the vector to become infected with an arbovirus and to show potential to transmit the virus to a host . Overall , existing data on nutritional impacts on vector competence are limited and extremely controversial . Several studies have found that smaller adult females raised from nutrient-deprived larvae showed an increased vector competence . The most extensive studies have been performed using A . triseriatus and LACV . Smaller females originating from nutrient-deprived larvae had significantly higher viral titers and increased oral transmission versus normal-sized ( control ) or large ( overfed ) mosquitoes [172 , 173] , possibly through higher dissemination rates within the mosquito itself [174] . Inverse correlation between mosquito size and vector competence has been further confirmed with LACV in field-caught A . triseriatus , DENV and SINV in A . albopictus , and DENV and RRV in A . aegypti [175–178] . Similar results are observed with Culex mosquitoes . C . tritaeniorhynchus reared with a low nutrient diet as larvae had higher JEV titers [179] , and smaller females are slightly more susceptible to WNV infection [180] . Other studies have shown opposite or no effect of mosquito size on vector competence . Larger mosquitoes have been shown to be more susceptible to arbovirus infection , particularly A . aegypti and DENV [186] and A . albopictus and CHIKV [187] , possibly due to increased viral receptors in the gut [176] . Some studies have shown no correlation between mosquito size and vector competence [185] . Overall , these studies do suggest that nutrition during larval stages can affect vector competence of the adult mosquito; however , further work is necessary to elucidate the exact mechanism associated with these changes . Aside from mosquito size , mosquito microbiome may also play an important role in vector competence . Elimination of endogenous bacteria in A . aegypti mosquitoes increases susceptibility to DENV [188] , and probiotic transfer of Proteus bacteria into the midgut increases resistance . Mechanistically , microbiomes may protect mosquitoes from certain arbovirus infections by production of secondary antiviral metabolites [189] . In contrast , microbiota can also decrease the expression of immune genes and therefore increase the susceptibility [188] . Prevention of host infection is highly dependent on effective vector control . Most strategies aim to kill larvae directly , interfering with development or sterilizing the adults . Most commonly , these efforts are achieved with chemical growth regulators [190] . However , these hormone analogs can also affect benevolent insect species , and resistance is already found worldwide [191 , 192] . Therefore , there is an urgent need for novel vector control strategies , such as nutritional components . As stated above , the mosquito microbiome is necessary for reproduction and can influence vector competence . The most popular vector control strategy utilizing bacteria is based on endosymbiotic Wolbachia . Wolbachia are not ingested directly but are maternally transmitted from infected females to their offspring . Introduction of new Wolbachia species into field populations reduces the mosquito reproduction as well as infection susceptibility and transmission potential for several arboviruses such as DENV [193–196] , CHIKV [193–197] , and YFV [197] . The mechanism is not completely understood; however , direct competition between the endosymbiotic bacteria and arbovirus is postulated [195 , 196 , 198] . Specific Wolbachia strains can also decrease mosquito lifespan , reducing the likelihood of arbovirus transmission [199] . Another strategy for vector control is to introduce larvicidal components that are ingested by larvae in situ . Several bacteria produce larvicidal proteins that have been successfully applied for vector control [200 , 201] , and several plant extracts and leaf litter also demonstrate larvicidal activity [202 , 203] . Algae ingested by mosquito larvae can also have larvicidal effects [204] , mainly through production of toxins [205] or starvation [126 , 206 , 207] . More work is necessary to identify other dietary components or interventions that are more effective in panspecies mosquito population reduction .
RNA viruses , such as arboviruses , intrinsically exist as heterogeneous , highly mutable populations that can quickly take advantage of environmental conditions [208] . It is by this mechanism that arboviruses can quickly adapt to new vectors and hosts [209] . Since nutritional status has such a profound influence on the host and/or vector , it can also act as a driving force in the emergence of new viral variants [210] . Nutritional status has been found to directly influence virulence in several RNA viruses , including coxsackievirus [211] and influenza virus [212 , 213] . Overall , changes in nutritional status can result in point mutations , increasing virulence and/or adaptation when reintroduced to a new host . These mutations could result from reduced viral population bottlenecks due to compromised immune responses or novel viral mutations from increased exposure to inflammation and reactive oxygen species [210] . While no studies have directly observed the influence of nutrition on arbovirus mutation and population dynamics , future work will focus on these factors in different nutritional states in both host and vector species .
The number of arbovirus infections increases steadily on a yearly basis and the exact causes for the increased frequency of arboviral outbreaks are not fully understood . Combining the global prevalence of malnutrition with continual arbovirus pandemics , increasing frequency of autochthonous transmission , and the paucity of adequate vaccination and antiviral strategies , it is essential to understand the connection between arbovirus susceptibility and severity and host and vector nutrition . Nutritional status is known to play a major role in immune status and in the development , physiology , and behavior of several mosquito species . Taken together , modulation of nutritional status or amelioration of malnutrition seems to be a targetable method of interrupting transmission as well as reducing susceptibility and disease severity . | As the old adage goes , you are what you eat . Proper nutrition is a cornerstone of health , and malnutrition can seriously impair the function of the immune system , resulting in increased infections or a more severe disease . Imbalanced or inadequate nutrition can also affect responses to vaccines or drugs that are vital for protection and treatment against viruses . A mosquito is also a product of what it eats . Nutrition during development and adult lifecycle can affect the feeding behavior of mosquitoes , thereby affecting transmission of viral diseases . Arthropod-borne viruses ( arboviruses ) are a major global health concern , especially in areas impacted by malnutrition . Understanding how nutrition can affect both humans and mosquitoes in the context of these viruses is vital to combating these diseases . | [
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"obesi... | 2018 | Taking a bite out of nutrition and arbovirus infection |
A national baseline mapping of schistosomiasis and soil-transmitted helminthiasis ( STH ) was performed in Sierra Leone . The aim was to provide necessary tools for the Ministry of Health and Sanitation to plan the intervention strategies in the national integrated control program on neglected tropical diseases according to the World Health Organization ( WHO ) guidelines for preventative chemotherapy ( PCT ) and for future monitoring and evaluation . 53 primary schools were randomly selected through a two-staged random sampling throughout the country . Approximately one hundred children aged 5–16 years of age were systematically selected from each school and their stool samples examined in a field laboratory . A total of 5 , 651 samples were examined . Data were analyzed with multivariable logistic regression models using model-based geostatistics . Spatial analysis predicted that S . mansoni infection was positively associated with population density and elevation and that there was a large cluster of high risk of S . mansoni infection ( prevalence >70% ) in the north and most of the eastern areas of the country , in line with the observed prevalence in Kono ( 63 . 8–78 . 3% ) , Koinadugu ( 21 . 6–82 . 1% ) , Kailahun ( 43 . 5–52 . 6% ) , Kenema ( 6 . 1–68 . 9% ) and Tonkolili ( 0–57 . 3% ) . Hookworm infection was negatively associated with population density and land surface temperature , and was high across Sierra Leone with a large cluster of high infection risk ( prevalence >70% ) in the north-eastern part of the country . Remarkably low prevalence of Ascaris lumbricoides ( 7 . 2% ) and Trichuris trichiura ( 3 . 3% ) was recorded when compared with results published in the 1990s . Results justify PCT for schistosomiasis for school age children and at-risk adults every year in high-risk communities in five districts and every two years in moderate-risk communities in one more district . The high prevalence of STH , particularly hookworm , coupled with widespread anemia according to a national report in Sierra Leone , suggests all but one district justifying biannual PCT for STH for pre-school children , school age children , and at-risk adults . PCT for STH in the remaining district , Kono is justified annually .
Schistosomiasis and soil-transmitted helminthiasis ( STH ) , two of the most important neglected tropical diseases , cause serious public health problems in sub-Saharan Africa [1] . There are two main forms of human schistosomiasis in sub-Saharan Africa , intestinal schistosomiasis caused by Schistosoma mansoni and urinary schistosomiasis caused by S . haematobium . STH is caused by a group of nematodes , most importantly , hookworms , Ascaris lumbricoides , and Trichuris trichiura . It is estimated that over 200 million people are infected with schistosomes worldwide and about two billion with STHs [2] . These together cause significant morbidity worldwide , with 39 million disability adjusted life years ( DALYs ) lost each year [3] . With growing global attention on control of the neglected tropical diseases in the last few years , control of these diseases is gathering pace in sub-Saharan Africa with several countries implementing national control programs with financial support from external donors and technical assistance from international organizations [4] , [5] . In Sierra Leone , both intestinal and urinary schistosomiasis is known to be prevalent in the northern and eastern regions [6] , [7] . STH is endemic throughout the country [6] , [8] , [9] , [10] , [11] , and the hookworm species present in the country was identified as Necator americanus [12] . These diseases , together with the country's other neglected tropical diseases e . g . onchocerciasis and lymphatic filariasis ( LF ) , pose a great threat to the wellbeing of the population , particularly children . Children acquire infections typically from the weaning period as they become mobile and inquisitive , play barefoot and bathe in infected fresh water . Infected children on the marginal level of adequate nutrition will be at risk of growth retardation [13] , [14] , [15] , impaired cognition , and micronutrient deficiencies [16] , [17] , [18] . Despite the high burden of these diseases in the country , there has never been a national control program on schistosomiasis and STH . However , there has been de-worming activities for STH by non-governmental organizations and the United Nations agencies with albendazole or mebendazole to school age children and pre-school children since 2004 and 2006 respectively . There has also been treatment for lymphatic filariasis added to the existing onchocerciasis control program in six districts bordering Guinea and Liberia since 2007 . In 2008 , a national integrated NTD Control Program targeting onchocerciasis , LF , schistosomiasis , STH and trachoma was initiated with financial support from the United States Agency for International Development and technical support from Helen Keller International and other partners , using the integrated control strategy according to the preventive chemotherapy ( PCT ) guidelines recommended by the World Health Organization ( WHO ) [19] . A national survey of schistosomiasis and STHs was conducted in 2008 to determine the geographical distribution of these diseases in Sierra Leone . We conducted spatial analysis of the disease distribution and provided the disease distribution maps in the country to enable the national integrated NTD control program to plan the integrated control strategy and to determine the disease-specific PCT strategy in each district . The paper presents the prevalence distribution of intestinal schistosomiasis and STH , estimation of at-risk population and corresponding PCT strategy for each district .
The national program of NTD control is managed and implemented by the Ministry of Health and Sanitation ( MoHS ) , Sierra Leone . The program involved a national survey on the prevalence of each NTD in order to plan the implementation strategy . The ethical approval for data collection in school children was obtained from the Ethics Committee of the MoHS . Upon arrival at the selected schools , the investigating team met with the community teachers associations in each school , and explained the nature of the survey . Informed consent was verbally given by guardians/parents and recorded by the team leader , as literacy rates are low in Sierra Leone . Once data were collected , the results were anonymized and computerized . No individual identity can be revealed upon publication . Sierra Leone is in West Africa bordered by Guinea , Liberia and the Atlantic Ocean . It has an area of 71 , 740 km2 , a projected population of 5 , 473 , 530 , a growth rate of 1 . 8% , a life expectancy of 41 years and an adult literacy rate of 36% in 2008 [20] . The country is administratively divided into 12 districts which are also subdivided into 149 chiefdoms and the Western Area ( WA ) which is subdivided into 30 zones . A national cross-sectional survey was conducted in 2008 in order to facilitate the planning of mass drug administration for both schistosomiasis and STH . Although it is known that schistosomiasis is prevalent in Sierra Leone , particularly , in the northern and eastern regions , data were not available in terms of detailed distribution and level of risk of the disease throughout the country . It was decided that all 12 districts including cities plus the Western Area ( excluding the capital Freetown ) were subjected to survey to provide an up-to-date map of geographical distribution and level of risk of schistosomiasis and STH in the country . The sample size was determined according to the WHO guide ( 50 children per school ) [21] , but was increased to 100 per school considering the fewer sites used in this survey and the low prevalence data recorded previously within the country [7] . The survey sites ( schools ) were selected according to administrative districts ( four schools per district ) using a two-staged random sampling method to avoid two schools being selected from the same chiefdom to ensure a relatively even geographical coverage throughout the country . Therefore , in each district a list of chiefdoms was used as the sampling frame and four chiefdoms were first randomly selected . Within each selected chiefdom , a list of all primary schools was used as the sampling frame and one primary school was randomly selected . In total , 53 schools were selected for survey throughout the country . In Tonkolili which is ecologically heterogeneous with high altitude in the east and low altitude in the west , relevant chiefdoms were selected to represent the two ecological zones . Within each selected school , systematic sampling of children started from high grade classes and proceeded down through the grades with a view of balancing for sex . Approximately around 100 children aged 5 to 16 years per school ( range: 36–134 ) were examined [22] , [23] . In a few schools , due to large numbers of children present in the classes selected , up to 134 children were examined , while in one school , only 36 children were examined due to the small size of the school . Following community sensitization and selection of school children , each pupil was supplied with a bottle for stool sample collection and an identification number was assigned . One stool sample from each selected pupil was collected . After collection of stool samples these were processed immediately and one slide per sample was prepared and examined in the field laboratory by the Kato-Katz thick smear technique using a 41 . 7mg template [24] . S . mansoni and STH infections were identified under light microscopes by experienced examiners . The survey received technical supervision from the WHO and the University of Sierra Leone . Survey results were entered into Microsoft Excel . Prevalence of each parasite infection and corresponding differences between ages and sex was estimated taking into account the clustered design of the sampling , using the chiefdom as a primary sampling unit and including adjustments for the probability of sampling and finite population corrections for sampling without replacement in the Stata/SE 10 . 0 statistical package ( StataCorp , College Station , Texas , USA ) . The coordinates of each sample site were recorded using hand-held units of global positioning system ( GPS ) . The survey data were summarized as prevalence of infection by survey location . These summary data were plotted in a geographical information system ( GIS ) ( ArcView version 9 . 3 , ESRI , Redlands , CA ) ( Figure 1 ) . Electronic data for land surface temperature ( LST ) and normalised difference vegetation index ( NDVI ) for a 5 km×5 km grid cell resolution were obtained from the National Oceanographic and Atmospheric Administration's ( NOAA ) Advanced Very High Radiometer ( AVHRR; see Hay et al . [25] for details on these datasets ) and the location of large perennial inland water bodies was obtained from the Food and Agriculture Organization of the United Nations ( http://www . fao . org/geonetwork/srv/en/main . home ) and the distance to the nearest perennial water body ( DPWB ) was extracted for each survey location in the GIS . A 5km resolution population surface derived from the Global Rural-Urban Mapping Project ( GRUMP ) beta product was obtained from the Center for International Earth Science Information Network ( CIESIN ) of the Earth Institute at Columbia University ( http://sedac . ciesin . columbia . edu/gpw/global . jsp ) . Elevation data with a 5 km×5 km grid resolution , generated by a digital elevation model ( DEM ) from the Shuttle Radar Topography Mission ( SRTM ) , were obtained from the Global Land Cover Facility ( http://glcf . umiacs . umd . edu/index . shtml ) . All environmental datasets were linked to survey locations and values at each survey location were extracted in the GIS . The initial candidate set of predictor variables included population density , NDVI , LST , DPWB and elevation . Fixed-effects binomial logistic regression models of prevalence of infection for each parasite were developed in a frequentist statistical software package ( Stata version 10 . 1 , Stata Corporation , College Station , TX ) . In the preliminary multivariable models , elevation was not found to be significantly associated with hookworm infection risk . Population density , DPWB and LST were not found to be associated with A . lumbricoides infection; these variable were excluded from further analysis in the respective models ( Wald's P>0 . 2 ) . A quadratic association between LST and prevalence of infection was assessed for all models and was not found to improve model fit using the Akaike's Information Criterion . We developed model-based geostatistical spatial prediction models [26] using the Bayesian statistical software , WinBUGS version 1 . 4 ( Medical Research Council Biostatistics Unit , Cambridge , United Kingdom and Imperial College London , London , United Kingdom ) . All models had the covariates plus a geostatistical random effect , in which spatial autocorrelation between locations was modeled using an exponentially decaying autocorrelation function . Statistical notation of Bayesian geostatistical models , spatial interpolation and model validation procedures are presented in an additional file ( Text S1 ) . After analysis of the data from each school and according to the geographical distribution ( observed prevalence range ) of the diseases within the country , endemic areas were categorized as high , moderate or low risk areas according to the prevalence thresholds ( for details , see the WHO PCT guidelines [19] ) . As the PCT implementation was to be organized at each district level , the at-risk population was estimated for each district according to the endemicity category in the district and the projected population for 2009 from the 2004 National Census [20] . All the rural populations of the districts identified as having schistosomiasis in all survey sites are considered to be at-risk as they have occupations involving contact with infested water: fishermen , farmers , irrigation workers , artesian miners , women doing their domestic tasks and bathing . For PCT strategies , all school age children in endemic communities as well as those adults considered at high risk of infection were regarded as target population and to be treated according to the WHO PCT guidelines [19] , [27] .
A total of 5691 school children were selected and examined throughout the country . Among the total , 5069 school children had valid age , gender and parasitological data entries . There were 2563 males ( 50 . 6% ) and 2506 females ( 49 . 4% ) . The mean age ( ± standard deviation ) of pupils studied was 8 . 34±2 . 80 years ( male 8 . 36±2 . 80 years and female 8 . 32±2 . 81 years ) . There was no significant difference in mean age between gender ( p>0 . 05 ) . The overall point prevalence of S . mansoni infection in 5–16 year-old school children within the country was 18 . 4% ( 95% confidence interval ( CI ) : 14 . 8–22 . 1% ) . There was no significant difference in overall prevalence between boys ( 18 . 5% , 95% CI: 14 . 9–22 . 2% ) and girls ( 18 . 4% , 95% CI: 14 . 4–22 . 3% ) ( p>0 . 05 ) . However , there is a significant difference between ages ( p<0 . 001 ) . In general , prevalence in children of 8–16 years old ( 25 . 1% , 95% CI: 20 . 1–30 . 1% , n = 2777 ) was significantly higher than that in 5–7 years old ( 10 . 4% , 95% CI: 8 . 1–12 . 7% , n = 2292 ) ( p<0 . 001 ) . The overall point prevalence of hookworm infection in 5–16 year-old school children was 32 . 5% ( 95% CI: 28 . 7–36 . 3% ) within the country . The overall prevalence was significantly higher in boys ( 34 . 6% , 95% CI: 30 . 7–38 . 5% ) than in girls ( 30 . 4% , 95% CI: 26 . 4–34 . 3% ) ( p<0 . 001 ) . Prevalence of hookworm in children of 8–16 years old ( 38 . 5% , 95% CI: 34 . 1–43 . 0% , n = 2777 ) was significantly higher than that in 5–7 years old ( 25 . 2% , 95% CI: 21 . 0–29 . 5% , n = 2292 ) ( p<0 . 001 ) . Low levels of infection were recorded for A . lumbricoides with an overall prevalence of 7 . 2% ( 95% CI: 5 . 8–8 . 6% ) . There was also overall low prevalence of T . trichiura ( 3 . 3% , 95% CI: 2 . 5–4 . 2% ) . A . lumbricoides and T . trichiura infections were not analyzed in detail . Overall prevalence of any STHs was 39 . 1% ( 95% CI: 37 . 8–40 . 5% ) in 5–16 year-old school children within the country . To represent the level of endemicity of intestinal schistosomiasis and STHs , according to the above analysis , the prevalence in 8–16 years in each school was used in the following analysis to illustrate the geographical distribution of these NTDs within the country . The average number of 8–16 years old examined per school was 52 ( range 28–87 ) . Model results ( Table 3 ) indicated that: prevalence of S . mansoni was positively associated with population density and elevation; prevalence of hookworm infection was negatively associated with population density and LST; prevalence of A . lumbricoides was negatively associated with elevation; and prevalence of T . trichiura was negatively associated with LST and elevation and positively associated with DPWB . Phi ( φ ) indicates the rate of spatial decay of spatial autocorrelation and varied from 11 . 98 and 4 . 72 for T . trichiura and A . lumbricoides . This indicates that , after accounting for the effect of covariates , the radii of the clusters were approximately 70km in case of A . lumbricoides and 28km in case of T . trichiura ( note , φ is measured in decimal degrees and 3/φ determines the cluster size; one decimal degree is approximately 111 km at the equator ) . The tendency for spatial clustering was the strongest for S . mansoni and the weakest for T . trichiura ( the higher value the spatial variance parameter the higher the tendency for spatial clustering ) . We found a large cluster of high risk of S . mansoni infection ( prevalence >70% ) in a region covering the north and most of the eastern areas of the country ( Figure 2A ) . The predicted prevalence of hookworm infections was high across Sierra Leone with a large cluster of high infection risk ( prevalence >70% ) in the north-eastern part of the country ( Figure 2B ) . The risk of A . lumbricoides ( Figure 2C ) and T . trichiura ( Figure 2D ) was predicted to be highest ( prevalence >20% ) in western , central and southern areas of the country . All models showed acceptable predictive ability ( i . e . AUC>70% ) . According to the current S . mansoni prevalence distribution and the WHO PCT guidelines [19] which is now widely implemented in several countries in sub-Saharan Africa [27] , [28] , communities in the high-risk endemic areas in Koinadugu , Kono , Kailahun and part of Kenema and Tonkolili are justified for annual PCT for schistosomiasis in school age children and adults at high risk with an estimated target population of around 1 . 5 million ( Table 1 ) . About 730 , 000 people are estimated in the moderate-risk endemic areas in Bombali , Kenema and Tonkolili , where treatment for school age children and at-risk adults once every two years is justified . A further 330 , 000 school age children are in the low-risk endemic areas , who may require treatment twice during their primary education . According to the STH prevalence maps , the entire population in the country is at risk of STH . In particular , those in five coastal districts , Koinadugu and part of Bo , about 2 . 84 million people , are at high risk of STH infection ( Table 2 ) , justified for PCT twice a year to pre-school children , school age children and adults at high risk . Another 2 . 6 million people in the remaining areas are at moderate risk of STH infection , therefore justified for annual treatment to pre-school children , school age children and at-risk adults . A total target population was 5 . 44 million .
Based on the results of this survey , PCT with praziquantel for schistosomiasis was performed for the first time in Sierra Leone in June 2009 and was focused in the northeast districts . As this was the first round of such large scale treatment , significant side effects in heavily parasitized children were anticipated: headaches , stomach aches , nausea , vomiting and diarrhea . To ease this concern , PCT was phased in , and only school-going children in these districts ( including district cities ) were treated in the first round ( a total of 562 , 980 ) . Rural adult populations of the districts identified as having a high risk of S . mansoni infection are to be targeted in 2010 . All school age children in the high prevalence districts , Kono and Koinadugu , will be targeted again in the second round in 2010 . STH distribution is widespread in the country , particularly with high prevalence of hookworm infection ( Figures 1B and 2B ) . A government report suggests that there was a high prevalence of anemia in children in the country [33] . Considering these two factors , it was decided that 12 out of 13 districts require PCT twice a year at the beginning of the control program . The decision took into consideration the prevalence range observed in each district and the likely underestimation of one Kato-Katz slide used in the survey on the actual prevalence . The existing de-worming programs for school age children in the country funded and organized by UN agencies and NGOs have now been fully coordinated and integrated under the National School and Adolescent Health program . The LF elimination commenced with ivermectin and albendazole distribution for all persons over 5 years of age in 2007 , scaling up to national coverage in 2010 , including the capital Freetown and other cities . This provides the first round of PCT for STHs . The second round of PCT with mebendazole for STHs in 2009 was included in PCT for schistosmiasis in the districts receiving praziquantel , 6 months after PCT-LF . The National School and Adolescent Health program plans to scale up to national coverage of the second round of PCT for school age children and to integrate this activity into the Mother and Child Health Weeks . The MoHS has also included the provision of anthelminthic to pregnant women at the first visit in the second trimester into their basic ante-natal care package and district health indicators . It is noted that given the predominant hookworm infection among STHs it would be desirable to use albendazole as the drug of choice in de-worming in the country [34] . In conclusion , the first national survey on distribution of intestinal schistosomiasis and STH in Sierra Leone was carried out in 2008 . The results showed that school age children in Sierra Leone suffer from high prevalence of STH throughout the country and high prevalence of S . mansoni infection in the northeast half of the country , highlighting the need of control on these NTDs . It provided a platform for the Ministry of Health and Sanitation to plan the implementation strategies in the national NTD control program . The first round of pilot PCT campaign in school children was conducted in the moderate and heavy endemic areas in 2009 and the plan is made for the second round of treatment to expand the PCT coverage to a larger population including adults at high risk in the northeast areas . | The common intestinal roundworm , whipworm and hookworm ( together known as soil-transmitted helminthes - STHs ) together with schistosomes or bilharzia are responsible for extensive ill health , reduced life expectancy and death in sub-Saharan Africa . These diseases are transmitted in areas of poor water supply and sanitation . In order to implement an appropriate national control program , knowledge of the prevalence and geographical distribution of these diseases is required . A national survey was performed in Sierra Leone in 2008 . Overall prevalence of intestinal schistosomiasis was 18 . 4% and that of STHs was 39 . 1% . Intestinal schistosomiasis was mainly prevalent in the northern and eastern regions while STH is widespread in the country . The results justify routine de-worming for pre-school children , school age children , women of childbearing age , and adults at high risk twice a year . The results also justify using anti-schistosomiasis drug ( praziquantel ) in school age children , all women of childbearing age , and adults at high risk annually or biennially depending upon the prevalence in the areas . | [
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"infecti... | 2010 | Geographical Distribution of Intestinal Schistosomiasis and Soil-Transmitted Helminthiasis and Preventive Chemotherapy Strategies in Sierra Leone |
We are attempting to develop cost-effective control methods for the important vector of sleeping sickness , Glossina fuscipes spp . Responses of the tsetse flies Glossina fuscipes fuscipes ( in Kenya ) and G . f . quanzensis ( in Democratic Republic of Congo ) to natural host odours are reported . Arrangements of electric nets were used to assess the effect of cattle- , human- and pig-odour on ( 1 ) the numbers of tsetse attracted to the odour source and ( 2 ) the proportion of flies that landed on a black target ( 1×1 m ) . In addition responses to monitor lizard ( Varanus niloticus ) were assessed in Kenya . The effects of all four odours on the proportion of tsetse that entered a biconical trap were also determined . Sources of natural host odour were produced by placing live hosts in a tent or metal hut ( volumes≈16 m3 ) from which the air was exhausted at ∼2000 L/min . Odours from cattle , pigs and humans had no significant effect on attraction of G . f . fuscipes but lizard odour doubled the catch ( P<0 . 05 ) . Similarly , mammalian odours had no significant effect on landing or trap entry whereas lizard odour increased these responses significantly: landing responses increased significantly by 22% for males and 10% for females; the increase in trap efficiency was relatively slight ( 5–10% ) and not always significant . For G . f . quanzensis , only pig odour had a consistent effect , doubling the catch of females attracted to the source and increasing the landing response for females by ∼15% . Dispensing CO2 at doses equivalent to natural hosts suggested that the response of G . f . fuscipes to lizard odour was not due to CO2 . For G . f . quanzensis , pig odour and CO2 attracted similar numbers of tsetse , but CO2 had no material effect on the landing response . The results suggest that identifying kairomones present in lizard odour for G . f . fuscipes and pig odour for G . f . quanzensis may improve the performance of targets for controlling these species .
Between 1931 and 1961 , the annual number of recorded Human African Trypanosomiasis ( HAT ) cases was reduced by >90% , from >60 , 000 reported cases/year to <5000 cases/year , through the systematic screening and treatment of millions of individuals across sub-Saharan Africa [1] . When the incidence of HAT across the continent dropped to such low numbers , the newly-independent nations of sub-Saharan Africa reduced their efforts to monitor and control the disease . This reduction , combined with political and economic turbulence in some of the countries most affected by the disease ( e . g . , Uganda , Sudan , Angola , Democratic Republic of Congo ) led to a resurgence in HAT across the continent , such that by the late 1990s there were >30 , 000 recorded cases/year . Consequently , the World Health Organization ( WHO ) revived a major programme of disease surveillance and treatment which has now reduced the annual number of reported cases to <15 , 000/year [1] . Thus , over the past 80 years , programmes against HAT have been based largely on the detection and treatment of disease in humans and this continues to be the case [1] . Interventions against tsetse flies ( Glossina spp . ) [2] , the vector of the Trypanosoma spp which cause HAT , have , with some exceptions normally based on the rodesiense form of the disease [3] , played a minor role . This emphasis on tackling the trypanosome rather than the tsetse is due to a variety of humanitarian , socio-economic [4] , [5] , [6] and epidemiological [7] , [8] factors . By contrast , tsetse control has played a major role in the control of animal trypanosomiasis [4] . Should vector control play a greater role in tackling HAT ? More than 90% of HAT cases are caused by T . brucei gambiense transmitted by Palpalis-group species of tsetse found in Central and West Africa [1] . Moreover , modern methods of tsetse control , based on the use of natural ( insecticide-treated cattle ) or artificial ( traps or insecticide-treated targets ) baits to lure and kill tsetse , have the particular advantage that they can be applied and afforded by local people . Such interventions could overcome the present dependence on outside agencies to deploy survey teams and provide drugs and medical personnel . Against this advantage , the application of baits against HAT faces two important problems . First , the use of insecticide-treated cattle [9] depends on cattle being present and forming a significant part of the diet of the local tsetse . In many of the HAT-affected areas of West Africa , cattle are not abundant ( e . g . , Guinea , southern Côte d'Ivoire , DRC [10] and/or cattle do not seem to be an important component of the diet of Palpalis-group tsetse [11] . Second , the use of artificial baits has been more successful with Morsitans- ( e . g . , G . pallidipes and G . m . morsitans ) rather than Palpalis-group species of tsetse [12] . Morsitans-group species , especially G . pallidipes , are highly responsive to host odours . Insecticide-treated targets and traps , baited with synthetic blends of these odours and deployed at densities of ∼4 targets/km2 , can eliminate populations of tsetse rapidly [13] , [14] , [15] . By contrast , there are no artificial attractants effective against important vectors of T . b . gambiense and thus baits must be deployed at densities of 30–40 km−2 [12] making the method prohibitively expensive [6] . In the period 1997–2006 , 92% of the reported ∼242 , 000 cases of HAT caused by T . b . gambiense were in Angola , DRC , Sudan or Uganda . In these countries , either G . f . fuscipes ( northern DRC , Uganda , Sudan , ) or G . f . quanzensis ( northern Angola , southern DRC ) are the only significant vectors [16] . Over the same period ( 1997–2006 ) , 51% of the ∼6000 reported infections caused by T . b . rhodesiense were in southern Uganda where G . f . fuscipes is the main vector . Thus , nine out of ten cases of HAT probably start with a bite from a subspecies of G . fuscipes . The chemicals used to attract Morsitans-group tsetse are not effective for G . f . fuscipes [17] . However , there is evidence that there are novel attractants present in the natural odour from monitor lizard [18] , [19] , an important host for this species . It has also been reported that oil of Pinus pumilionis , octenol and decyl formate is an attractant for these flies [20] . For G . f . quanzensis , there are no data beyond Frezil & Carnevale's [21] very limited observation that carbon dioxide increases the catch of tsetse from traps . As a starting point for any programme to identify attractants , we need to assess whether a species uses odours to locate its hosts . Humans , pigs , cattle and lizards are important hosts for G . fuscipes spp [11] but , with the exception of the studies of lizard odours , there are no data to indicate whether these species use odours to locate hosts . Accordingly , this paper reports the results from field studies undertaken in Kenya and the DRC to assess the responses of G . f . fuscipes and G . f . quanzensis , respectively , to natural odours from humans , cattle , pigs and lizards . Following the successful approaches used in the identification of attractants for Morsitans-group species [22] , [23] , [24] , we did not confine ourselves to assessing the effect of odours on the catch of tsetse from traps but , rather , used various arrangements of electric nets [25] to quantify the effects of odours on the specific behavioural responses of: ( i ) long-range attraction , ( ii ) landing and ( iii ) trap entry .
In each country , local cattle , pigs or humans were used as sources of host odours ( baits ) . In Kenya only , studies were also made of odours from monitor lizards . The baits were placed in PVC-coated tents ( ∼2×2×3 m in Kenya; 2×1 . 5×2 m in DRC ) from which the air was exhausted at ∼2000 L/min using a 12 v co-axial fan connected to a flexible PVC-coated tube ( 0 . 1 m dia . ) with a net-covered outlet placed at ground level , ∼15 m away , where various catching devices were placed . In this way , cattle , humans and pigs were not visible nor could they be bitten by approaching tsetse flies . Lizards were unable to bask in a tent and , being poikilothermic , the absence of basking would reduce their metabolic rate and , perhaps , the odours they produce . Accordingly , they were placed in a chamber ( ∼2 . 4×2 . 4×2 . 5 m ) with stainless-steel walls and a partially shaded glass roof which allowed the lizards contained within it to move freely in and out of shade during the course of an experiment . Studies with Morsitans-group flies suggest that the effectiveness of odours from particular host species is related to their gross weight . Accordingly , to match the weights of different mammalian host species , tents contained a single ox , two men or three-to-four pigs . Given the average weight of the cattle ( ∼150 kg ) , humans ( ∼75 kg ) and pigs ( ∼50 kg ) the gross weight of mammalian baits within the tent was 150–200 kg unless reported otherwise . Lizards are considerably smaller and 5–6 lizards ( ranging in individual weight from 2 . 5–7 kg and sex undetermined ) with a total , combined weight of ∼30 kg were placed in the tent . Cows and pigs were from local farms and maintained under normal local conditions . Lizards were trapped near the lake when required , held in cages and provided with fish or beef on the evening of every third day and were used in experiments over a period of 12–14 days . In Kenya only , studies were also made of the responses to urine from lizards collected and dispensed following the methods of Mohamed-Ahmed [18] . Bacterial fermentation of host urine seems to have an effect on their efficacy and so studies were made of the responses to fresh urine and urine that had been fermented for two weeks . In some experiments , studies were made of the responses of tsetse to chemicals known to be present in cattle odour and to be effective for some species of tsetse . These chemicals included: acetone ( ∼500 mg/h ) , 1-octen-3-ol ( octenol; ∼0 . 1 mg/h ) , 4-methylphenol ( ∼0 . 4 mg/h ) and 3-n-propylphenol ( ∼0 . 01 mg/h ) for G . f . quanzensis only and carbon dioxide ( 1–4 L/min ) for both . The chemicals were dispensed individually or in various combinations following the methods of Vale & Hall [23] and Torr et al . [31] . To measure the dose of carbon dioxide produced by different hosts , the concentration ( ppm ) of carbon dioxide in the air being exhausted from the tents was measured using an infra-red gas analyser ( EGM-1 , PP Systems , Hitchin , UK ) . The velocity of air ( m/s ) being exhausted from the tent's exhaust pipe was also measured , using a hot wire anemometer , and hence the absolute volume of carbon produced by the test animals could be estimated . To assess the numbers of tsetse attracted to various host odours , an electric net ( either 0 . 5 m wide ×1 . 0 m high or 1×1 m ) was placed downwind of the source . Tsetse do not orientate precisely to an odour source unless it is marked by a visual stimulus [22] . Accordingly , a target , consisting of a panel of black cloth ( 0 . 75×0 . 75 m ) was placed 0 . 5 m upwind of the electric net ( 1×1 m ) . Alternatively , an electric target ( 1×1 m or 0 . 5 m high×1 m wide ) was placed adjacent to the smaller ( 0 . 5 m wide×1 m high ) electric net . For experiments where an electric net and electric target were used in combination , the catch from the target , expressed as a proportion of the total ( i . e . , net+target ) catch , provided an index of the strength of the landing response . Henceforth , an electric net operated singly is referred to as an ‘E-net’ and the combination of an electric target+flanking electric target is termed an ‘E-target’ . To assess the effect of host odours on trap-oriented responses , odours were dispensed at the base of the trap . The catch from a trap is the product of ( i ) the number of tsetse attracted to the vicinity of the trap and ( ii ) the proportion that subsequently enter it and are retained – i . e . , the so-called ‘trap efficiency’ [35] . Odours can have effects on attraction and/or trap efficiency . To measure these effects independently , experiments were performed with an electric net ( 0 . 5 m wide×1 m high ) placed adjacent to the trap . The total catch ( electric net+trap ) provided a measure of the numbers of tsetse attracted to the trap with or without host odours , and the catch from the trap , expressed as a proportion of the total catch , provided an index of trap efficiency . All field experiments were carried out for 4 h between 08:00 h and 14:00 h local time when Palpalis-group species are most active [26] , [36] . In general , odour baited devices ( e . g . , traps , electric nets , electric targets and combinations thereof ) were compared with an unbaited device over 6–12 days in a series of replicated Latin squares of days×sites×treatments . Sites were between 100 m and 200 m from each other . The daily catches ( n ) were normalized and variances homogenized using a log10 ( n+1 ) transformation and then subjected to analysis of variance using GLIM4 [37] . In general , the detransormed means are reported accompanied by their transformed means and standard errors of the difference ( SED ) between means [37] . To provide a common index of the effect of odours on catches , the detransformed mean catch of tsetse from an odour-baited device was expressed as the proportion of that from an unbaited one . The value is termed the catch index; odours which , say , double or halve the catch from a trap would have catch indices of 2 and 0 . 5 , respectively . Logistic regression was used to analyse the effects of odours on the proportions that were caught landing on a target or entering a trap as opposed to colliding with a flanking electric net . Following Crawley [37] , the total daily catches from a particular device ( e . g . , target+flanking net , trap+flanking net ) were specified as the binomial denominator and the catches from the accompanying target or trap as the y-variable . Days , sites and treatments were specified as factors and the statistical significance of differences in the proportion of tsetse landing on the target or entering a trap was assessed by removing the treatments factor from the full model ( i . e . , days+sites+treatments ) . The significance of changes in deviance was assessed by either χ2 or , if the data were overdispersed , an F-test following re-scaling [37] . The SE is asymmetric about the mean and thus mean percentages are accompanied by the larger SE . For all analyses , the term “significant” implies P<0 . 05 .
The results for G . f . fuscipes ( Fig . 1 ) show that odours from humans , cattle and pigs had no significant effect on the proportion of tsetse that were caught as they landed on the cloth panel of the large ( 1×1 m ) E-target ( Fig . 1A ) : for all treatments , ∼30% of males and ∼50% of females landed on the target . In one experiment ( Experiment 12 ) , carbon dioxide dispensed outside a tent increased significantly the proportion of female G . f . fuscipes that landed on the target ( Fig . 1B ) ( 48% vs . 23% ) and had a similar effect , albeit not statistically significant , for males ( 40% vs . 26% ) . In a second experiment ( Experiment 13 ) where the effect of dispensing carbon dioxide inside or outside a tent was assessed , there was no significant effect , although the trend was similar: 43% ( ±3 . 5 ) of females landed when carbon dioxide was dispensed outside , 34% ( ±3 . 8 ) when it was dispensed inside and 30% ( ±4 . 4 ) for an unbaited target . These results from Experiment 13 also suggest that carbon dioxide was more effective when dispensed outside a tent ( landing response = 40–48% ) than within ( 34% ) which is consistent with the indications ( above ) that carbon dioxide attracted more tsetse when it was dispensed outside a tent rather than within it . Baiting a small ( 1 . 0 m wide×0 . 5 m high ) target with lizard odour increased the landing response for males and females significantly ( Fig . 1C ) . Baiting the small target with mammalian host odours also had a significant effect: human and cattle odour increased the landing response for males significantly whereas cattle odour decreased the response for females significantly . The mean daily catches of G . f . quanzensis from an E-target were much smaller than the catches of G . f . fuscipes in Kenya; the geometric mean of the total ( males+females ) daily catches of G . f . fuscipes shown in Table 1 is 23 tsetse/day compared to 5 tsetse/day for the catches of G . f . quanzensis shown in Table 2 . The small daily catches of G . f . quanzensis prevented analysis of landing rates from individual experiments . Accordingly , the data from all experiments were pooled and subjected to logistic regression . The results ( Fig . 2 ) show that there was no significant effect of host odours on the landing response . However , the landing rate of females was consistently higher in the presence of pig odours; in the three experiments where pig-baited and unbaited E-targets were compared directly , the landing rates with pig odour were 43% ( n = 176 ) , 46% ( n = 156 ) and 52% ( n = 84 ) compared to 19% ( n = 86 ) , 35% ( n = 68 ) and 37% ( n = 38 ) , respectively , for an unbaited E-target . By contrast , there was no indication that carbon dioxide increased the landing rate . Experiments conducted when Stomoxys was abundant showed that cattle odour increased the landing response significantly . For instance , the landing response of Stomoxys on a small E-target baited with cattle ( 58±3 . 0% ) was significantly greater than that from lizard- ( 37±7 . 6% ) , human- ( 38±8 . 8% ) or unbaited ( 31±7 . 8% ) E-targets . Baiting a large E-net with odour from four cattle increased the landing response significantly from 21±9 . 8% to 55±4 . 9% . Studies of the effect of odours on trap efficiency were made for G . f . fuscipes only . The results ( Fig . 3 ) show that in one experiment ( Fig . 3A ) conducted on Chamaunga , host odours had no significant effect for males or females . In a second experiment ( Fig . 3B ) , lizard odour increased the percentage of males and females entering the trap . The difference in effects for lizard odour may merely reflect differences in the sample sizes which allowed us to detect relatively small ( ∼10% ) increases in trap efficiency . The total catches of males and females from the lizard-baited trap for experiment A , where no statistically significant effects were apparent , were 207 and 192 , respectively , compared to 505 and 811 for experiment B . Host odours had no significant effect on trap efficiency for Stomoxys .
Baiting an E-target with odours from cattle , human or pig odours had no significant effect for G . f . fuscipes and only pig odour increased the catch significantly for G . f . quanzensis . For Morsitans-group species by contrast , cattle odour increases the catch ten-fold [22] , [39]; pig ( warthog and bushpig ) odours are also highly effective [22] , and human odour seems to contain a mixture of attractants and repellents [35] . The present experiments were performed at a variety of sites with various sampling devices and host animals and hence it seems unlikely that the absence of any marked response is an experimental artefact . Moreover , the absence of any response to cattle odour is consistent with previous studies showing that cattle kairomones effective for Morsitans-group tsetse ( i . e . , acetone , octenol and phenols ) are ineffective for G . f . fuscipes [17] . The present results show that these odours are also ineffective for G . f . quanzensis . Carbon dioxide is present in the odours produced by all living hosts and is commonly claimed to be a universal kairomone for biting flies , including tsetse . Carbon dioxide dispensed alone , doubles the catch of both sexes of G . m . morsitans and G . pallidipes [22] and acts synergistically with other host kairomones [40] . Thus it is surprising that the natural odours that contained this gas were ineffective for G . f . fuscipes whereas carbon dioxide dispensed alone , at 2 L/min , did have a significant effect , albeit slight ( 2× ) and only when the gas was dispensed outside the tent . Dispensing carbon dioxide within a tent will dilute the concentration of the odour at the source; the 2 L/min of gas released is diluted in ∼2000 L of air being exhausted from the tent giving a source concentration of ∼0 . 1% compared to 100% at the point where carbon dioxide is released from a tube connected to a gas cylinder outside the tent . However , for Morsitans-group species at least , this difference does not seem to affect catches significantly [22] , [41] , probably because the diluting effects of atmospheric turbulence on the odour plume as it travels downwind , obscures the differences in source concentration [42] . G . f . quanzensis was responsive to carbon dioxide dispensed within a tent , but the increase was relatively slight ( ∼2× ) and only significant for females . Natural host odours that included carbon dioxide ( e . g . , human odour ) were not , however , consistently effective and G . f . quanzensis also seems to display only a slight and variable response to carbon dioxide . These results accord with those of Mohamed-Ahmed & Mihok [43] who also reported variable responses of G . f . fuscipes to carbon dioxide . They baited traps with carbon dioxide dispensed directly from a concealed cylinder placed nearby ( i . e . , the gas was dispensed outside a tent ) . In one experiment they found that carbon dioxide dispensed at 5 L/min had no significant effect whereas in a second experiment , with the carbon dioxide dispensed at a lower dose of 2 . 5 L/min , the catch of females , but not males , was doubled . Stomoxys is considered to be highly responsive to carbon dioxide [23] , [38] . Given that all host odours contain carbon dioxide , it is surprising that , in the present study , cattle odour was highly effective for Stomoxys whereas pig and human odours were not . Thus for the populations of Stomoxys studied here , the olfactory response to cattle odour seems to be elicited by kairomone ( s ) other than carbon dioxide , whereas studies conducted elsewhere suggest that carbon dioxide is the major kairomone that attracts Stomoxys produced by cattle [23] , [38] , [44] . It is therefore remarkable that in this part of western Kenya , carbon dioxide is not as effective as expected for two genera of biting flies . While G . fuscipes spp . seem unresponsive to mammalian odours , the present results show that there is a clear and consistent response to natural lizard odour , according with the findings of Gouteux [19] and Mohamed-Ahmed [18] . However , in the present study , lizard urine had no significant effect whereas Mohamed-Ahmed [18] found that urine doubled the catch of female G . f . fuscipes attracted to an electrocuting cylinder and increased the catch of tsetse from a trap 1 . 5× . However even his results are marginal: the increase with the electrocuting cylinder are not significant for either males or females analysed separately , and the increase with traps is only significant for males . Mwangelwa et al . [17] found that aqueous washings of monitor lizard had no significant effect on the catch of a trap . However , given that monitor lizards are semi-aquatic , it would be surprising if tsetse evolved responses to odours that could be readily washed off . The effect of lizard odour is unlikely to be explained by a response to carbon dioxide as the lizard biomass in the tents was only 20% of the mamalian hosts . Accordingly lizards increased the concentration of carbon dioxide by only ∼100 ppm above background , compared to 2000 ppm above background for a carbon dioxide dispensed at 2 L/min within a tent . Since the latter did not have a significant effect , and that carbon dioxide is more effective at higher concentration , it seems unlikely that the small amount of carbon dioxide produced by lizards accounts for their attractiveness . The present results show that while G . f . fuscipes is responsive to lizard odour the fly does not respond to odour in the same way as Morsitans-group species . We carried out experiments that can produce large effects for Morsitans-group species , but perhaps these experiments are not appropriate for the particular host-location strategies of Palpalis-group species . Indeed , the small hosts ( e . g . , lizards ) and dense vegetation that often characterises the ecology of riverine flies might lead us to expect that strategies based on responses to olfactory cues would be particularly advantageous . By contrast , the large hosts ( e . g . , buffalo , antelope , warthog ) and open savannah habitats typical of Morsitans-group species suggests that visual cues should be more important . The paradigm for the odour-orientated behaviour of ‘tsetse’ is based largely on the responses of G . pallidipes . For this species , the large catches produced by odours arise because tsetse are recruited to the source from distances of up to 100 m by upwind anemotaxis ( see review by [45] and references therein ) . However , several factors might suggest that this paradigm does not apply to Palpalis group species . First , the variable responses to carbon dioxide obtained by Mohamed-Ahmed & Mihok [43] were attributed to the linear nature of the habitat: carbon dioxide was ineffective in a ‘linear forest’ because the odour plume extended into areas outside the forest where tsetse were absent . While this might limit responses to host odours in some situations , we do not think that this is a universal explanation for the unresponsiveness of Palpalis-group flies . We carried out the experiments in a variety of habitats , where the distribution did not appear to be markedly linear , and yet mammalian odours were always ineffective for G . f . fuscipes . Second , studies of the odour-orientated responses of Morsitans-group flies have shown that low wind speeds caused , for example , by dense vegetation acting as a windbreak , can reduce the effectiveness of host odours [46] . Moreover , in densely vegetated habitats with low wind speeds and high photosynthetic activity , the background noise of atmospheric carbon dioxide can be 10× greater than that observed in dry savannah woodland [42] . Both these factors would limit the effective range of host odour plumes , especially those that relied on anemotactic responses to carbon dioxide . Mohamed-Ahmed & Mihok's [43] finding that carbon dioxide was effective in one experiment but not another may not have been due to the topography of the forest ( see above ) but , rather , the time of year when the experiments were performed . They found that carbon dioxide was effective in the dry season but not in the wet . Work conducted in southern Africa suggests that the background noise of atmospheric carbon dioxide is higher during the wet season . At the field sites in Kenya , atmospheric carbon dioxide levels will be affected by the lake , and high resolution measurements of carbon dioxide [42] would be required to test this hypothesis . Ironically , it may be that the places where host odours might be most useful are also those where carbon dioxide produced by hosts is harder to detect and track . If host odours do not elicit long-range anemotaxis in Palpalis-group flies , might they play other roles ? The observation that carbon dioxide is effective whereas natural host odours containing equivalent doses of carbon dioxide are not , might suggest that the host odours contain repellents . The apparent reduction in the landing response of female G . f . fuscipes on small targets is also in accordance with this notion . Perhaps therefore , Palpalis flies do make important use of odours but in a distinctive strategy that we have yet to discern . Might , for instance , odours have orthokinetic or orthotactic effects ? In the course of conducting the experiments in Kenya , we frequently observed tsetse resting on the ground near the host for extended periods; behaviour that we have not seen during our studies of Morsitans tsetse . Other studies have reported that lizard urine is effective [18] – might the residues of lizards cause tsetse to congregate in areas where lizards are common , such as basking points along the lake shore ? Discerning the behavioural basis of these effects is important in two respects: first , understanding the effects of odours will allow us to design more sensitive bioassays of putative kairomones and , second , show how to develop strategies to make best use of these odours to control and monitor tsetse . In conclusion , the present findings suggest that unidentified chemicals present in lizard odour can double the numbers of G . f . fuscipes attracted to traps or killed by insecticide-treated targets . And the results for G . f . quanzensis suggest that pig odour contains chemicals that increase the landing response and hence the performance of targets . The present results , and experience with other species of tsetse ( e . g . , [47] ) , further suggest that larger doses of host kairomones produce larger catches of tsetse . Accordingly , we might reasonably expect that super-normal doses of synthetic attractants will produce even greater improvements in the efficacy of baits for controlling vectors of HAT . But if these improvements are to be realised , or even exceeded , we need to increase our understanding of the specific behavioural effects of these novel odours . | Human African Trypanosomiasis ( sleeping sickness ) remains a serious threat to many of the poorest people in Africa . The trypanosomes causing the disease are transmitted by tsetse flies . There are no vaccines or prophylactic drugs to prevent people from contracting the disease . So the disease is dealt with after it has been contracted using often ineffective curative drugs with unpleasant and sometimes fatal side effects . Prospects for the development of effective vaccines or prophylactic drugs are poor . One certain means of preventing disease transmission is to remove tsetse flies , either at a local level ( e . g . , a group of villages ) or regionally ( covering large parts of a country or region ) . However , a major problem is the cost and logistical difficulty of implementing such fly control programmes . To overcome this , we are trying to develop cost-effective insecticide-treated targets by identifying chemicals that will increase the numbers of tsetse that will be lured to a target and killed . Here we show that two major vectors , G . f . fuscipes and G . f . quanzensis , are attracted to the odour of monitor lizards and pigs , respectively . This opens the way for further work to identify the attractants present in these natural odours which can be simply and cheaply incorporated into targets to reduce the cost of control . | [
"Abstract",
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] | [
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] | 2009 | Prospects for Developing Odour Baits To Control Glossina fuscipes spp., the Major Vector of Human African Trypanosomiasis |
The organization of eukaryotic genomes is characterized by the presence of distinct euchromatic and heterochromatic sub-nuclear compartments . In Saccharomyces cerevisiae heterochromatic loci , including telomeres and silent mating type loci , form clusters at the nuclear periphery . We have employed live cell 3-D imaging and chromosome conformation capture ( 3C ) to determine the contribution of nuclear positioning and heterochromatic factors in mediating associations of the silent mating type loci . We identify specific long-range interactions between HML and HMR that are dependent upon silencing proteins Sir2p , Sir3p , and Sir4p as well as Sir1p and Esc2p , two proteins involved in establishment of silencing . Although clustering of these loci frequently occurs near the nuclear periphery , colocalization can occur equally at more internal positions and is not affected in strains deleted for membrane anchoring proteins yKu70p and Esc1p . In addition , appropriate nucleosome assembly plays a role , as deletion of ASF1 or combined disruption of the CAF-1 and HIR complexes abolishes the HML-HMR interaction . Further , silencer proteins are required for clustering , but complete loss of clustering in asf1 and esc2 mutants had only minor effects on silencing . Our results indicate that formation of heterochromatic clusters depends on correctly assembled heterochromatin at the silent loci and , in addition , identify an Asf1p- , Esc2p- , and Sir1p-dependent step in heterochromatin formation that is not essential for gene silencing but is required for long-range interactions .
The eukaryotic nucleus tends to be organized so that active and inactive sub-nuclear domains are spatially separated [1]–[4] . For instance , active genes co-localize in a limited number of transcription factories , while heterochromatic regions are found clustered in silenced nuclear compartments . Examples of the latter are found in Drosophila melanogaster and Arabidopsis thaliana where the large heterochromatic regions encompassing the centromeres associate to form a single “chromocenter” , and in mammalian cells where centromeres cluster in a small number of foci [5]–[7] . In most cases heterochromatin is found clustered near the nuclear envelope [1] , [8] , [9] . In the yeast Saccharomyces cerevisiae , heterochromatin is found at and near the 32 telomeres , and at the two silent mating type loci , HML and HMR , located near the left and right telomere of chromosome III , respectively [10] , [11] . These 34 loci co-localize in 4–8 clusters at the nuclear periphery [12]–[16] . A similar phenomenon is observed in Schizosaccharomyces pombe in which the heterochromatic centromeres , telomeres , and mating type loci cluster in silent foci at the nuclear periphery [17] . Heterochromatic clusters are thought to represent nuclear sub-compartments that are enriched in silencing proteins , while the rest of the nucleus is depleted in such factors [14] , [18] , [19] . Although the importance of association of genes with silent compartments in the process of silencing is well established , the mechanisms that drive these interactions are poorly understood . Formation of heterochromatin at HM loci has been characterized in detail ( for reviews see [11] , [20] , [21] ) . Silencing at HML and HMR requires cis-acting silencer elements [11] . Protein complexes , such as Rap1p and the Origin Recognition Complex ( ORC ) , bind to these silencer elements and help recruit Silent Information Regulator ( Sir ) proteins . Sir1p associates with Orc1p . Subsequently , Sir4p is recruited to the silencers via its interaction with Rap1p and Sir1p . Sir4p likely recruits Sir2p and is also required to recruit Sir3p to the silencer . Sir2p is a NAD-dependent histone deacetylase that deacetylates H4 K16 at nearby nucleosomes , which provides a binding site for additional SIR2-4 complexes [22] , [23] . This positive feedback loop allows spreading of the SIR2-4 complex throughout the mating type loci , resulting in positioned nucleosomes and gene silencing throughout the region [24] , [25] . Thus , histones and appropriate nucleosome assembly contribute to formation of heterochromatin , perhaps due to the fact that binding and spreading of the Sir complex occurs through direct interactions with histones . In addition , genetic evidence indicates that the histone chaperone Asf1p and the CAF-1 and HIR nucleosome assembly complexes have partially overlapping functions in heterochromatin formation [26] , [27] . Finally , previous work has indicated that silencer elements can cooperatively silence HMR in a manner that may involve direct interactions between HMR-E and HMR-I [28] . The clustering of Sir-bound loci in a limited number of sub-nuclear domains has been used as a model to study the processes that drive nuclear compartmentalization . Formation of silent nuclear compartments results in limiting Sir proteins to only a small number of locations in the nucleus [14] . In that situation , only loci located in these compartments will have access to silencer proteins and become heterochromatic , thereby preventing SIR complex-mediated silencing at inappropriate locations . A major unanswered question is how compartmentalization is established and maintained . Is clustering of loci driven by association of individual loci to a common sub-nuclear structure , e . g . sites on the nuclear envelope , or is clustering an intrinsic property of heterochromatin that depends on local assembly of silencing complexes at these loci ? Answers to this question can have important implications for our understanding of causal relationships between nuclear organization and gene regulation . To address this issue we have used chromosome III as a model for clustering of silent loci . This chromosome contains 4 heterochromatic loci: two telomeres and the nearby silent mating type loci , HML and HMR . We employ live cell 3D imaging to show that HML and HMR frequently co-localize both at the nuclear periphery as well as at more internal locations of the nucleus , indicating that anchoring to the nuclear envelope ( NE ) is not required for HML-HMR interactions . Using chromosome conformation capture ( 3C ) [29] we find that HML and HMR frequently and specifically interact with each other . Interactions are most frequent around the HML-E and HMR-I silencers . Analysis of a series of mutants reveals that clustering of these loci critically depends on silencer proteins , but that it is independent of proteins that contribute to anchoring silent loci at the nuclear periphery . Furthermore , silencing is not sufficient for the HM loci interaction to occur . Based on these observations we propose that silent compartments are not pre-assembled to facilitate subsequent recruitment of heterochromatic proteins . Instead we propose that long-range interactions between HM loci depend on a particular step in local heterochromatin assembly , which requires at least Asf1p , Esc2p and Sir1p .
Next , we employed chromosome conformation capture ( 3C ) to further analyze co-localization of the heterochromatic loci HML and HMR in more detail and at higher resolution [29] . Previous 3C analyses of yeast chromosomes used purified nuclei , which may result in loss of some interactions due to the rather disruptive nuclei isolation protocol . Therefore , we adapted 3C for use with intact yeast cells [32] . In this method , the cell wall is removed by zymolyase treatment and intact spheroplasts are treated with formaldehyde to induce cross-links between proteins and DNA and proteins and other proteins thereby trapping interacting chromatin fragments throughout the yeast genome . Cross-linked spheroplasts are then solubilized by SDS and Triton X-100 . From here the conventional 3C protocol is followed including restriction digestion , DNA ligation , and reversal of cross-links . The identities of interacting fragments are determined through detection of 3C ligation products by semi-quantitative PCR using locus specific primers . In addition , a randomized ligation control is generated which serves as a control for primer efficiency . This template is generated by digesting purified yeast genomic DNA followed by random intermolecular ligation which results in a DNA sample in which every possible ligation product is present in equal molar amounts . The cross-linking frequency of two loci is determined by PCR using the 3C and the control libraries as templates . Primers are designed that recognize the corresponding ligation product and PCR products are quantified by ethidium bromide staining of agarose gels . We have found that this quantification method reliably measures the relative abundance of ligation products as long as the PCR is performed within the linear detection range [29] , [33]–[36] . Figure S1A and B show examples of determination of the linear range of PCR by titrating the template concentration . The ratio of the amount of PCR product obtained with the 3C library and the control library is a direct measure ( though in arbitrary units ) for the frequency with which two loci interact ( extensively described in [29] , [32] , [37] , [38] ) . Each crosslinking frequency is determined in triplicate and averaged . In general , sites that are located close together ( within up to 20 kb ) will give relatively high 3C crosslinking frequencies while sites that are located far apart will show increasingly lower crosslinking frequencies [29] , [33] , [38] . Specific long-range interactions between two loci are apparent when their crosslinking frequency is significantly over this background level of interaction [38] . We first determined whether HML and HMR interact more frequently with each other than with other loci on chromosome III . We performed 3C on exponentially growing haploid MATa-cells and determined crosslinking frequencies between the EcoRI fragment that contains HML and a number of EcoRI fragments along the length of chromosome III including the fragment containing HMR ( Figure 1B ) . Primer sequences and positions of EcoRI restriction fragments are listed in Table S1 and depicted in Figure S1C . As expected , we found that HML interacts frequently with sites very close to it and that this crosslinking frequency decreases for restriction fragments located progressively closer to the right arm of the chromosome , similar to what has been observed in other studies ( Figure 1B; [29] , [33] , [34] , [36] , [38] , [39] ) . Interestingly , we observed a clear peak of crosslinking frequency corresponding to the EcoRI fragment containing HMR . This indicates that the interaction with HML is more frequent than with any other locus in that chromosomal region and thus suggests that the interaction is specific . To further confirm the interaction between HML and HMR , we performed the reverse experiment , in which crosslinking frequencies were determined between the EcoRI fragment that contains HMR and the same EcoRI fragments including the fragment containing HML ( Figure 1B ) . Again , a peak of crosslinking frequency corresponding to the EcoRI fragment containing HML is observed . Furthermore , specific and prominent interactions were also determined between HML and HMR in MATα cells ( Figure S2A and B ) , indicating the HM-interactions are not specific to one mating type . Further , 3D imaging in MATα cells did not reveal a difference in HML-HMR interactions , nor did 3C analysis of strains deleted for the Recombination Enhancer [40] ( Figure S2 Panels C and D ) . Given the lack of any mating type specific differences in HML-HMR interactions we consider it not likely that any mating type specific proteins or the MAT locus itself plays a role in the interaction between silent mating type loci . Interestingly , we do note that there appears to be a loss of frequent interactions between HML and sites close to it specifically in MATα cells . Although the reason for this is unclear , future comprehensive and chromosome-wide studies can be aimed at analyzing mating type specific differences in the conformation of chromosome III . Here we focused specifically on HML-HMR interactions , which are unaffected by mating type . Next we tested whether the HM loci also interact with the telomeres of chromosome III . We performed 3C with primers annealing immediately adjacent to the left or to the right telomere ( Figure S2E and F ) . Interactions between the left telomere and other EcoRI fragments along chromosome III revealed frequent interactions between the left telomere and HML ( Figure S2E ) . This is most likely due to the fact that these loci are located close to each other on the chromosome , which typically results in very frequent background interactions [29] , [38] . Interactions along the length of the chromosome between the left telomere and other EcoRI fragments were generally lower than observed for HML or HMR . Interestingly , the left telomere interacted also relatively frequently with HMR . The same is true for the right telomere ( Figure S2F ) : this telomere interacted frequently with nearby fragments , including HMR , and with HML . Although the telomeres interacted preferentially with the HM locus located on the opposite side of the chromosome , these interactions are clearly less frequent than the HML-HMR interaction . Contacts between the two telomeres were also less frequent than the interaction between the HM loci ( Figure S2F ) . 3C is used to determine the relative crosslinking frequency in a population of cells , but 3C does not directly reveal the percentage of cells that are engaged in a certain configuration , just like chromatin immunoprecipitation experiments do not provide insight in absolute occupancy levels of proteins at specific loci . Our live cell imaging ( Figure 1A ) allows direct comparison of 3C crosslinking frequencies to the probability with which loci colocalize in living cells . We find that HML and HMR are co-localized in 21% of cells and closely juxtaposed in an additional 38% of cells . In contrast HML and MAT are co-localized in only 12% of cells and closely juxtaposed in another 17% . These different levels of in vivo co-localization closely correspond to relative 3C crosslinking frequencies detected for HML-HMR and HML-MAT ( Figure 1B ) . Thus , the quantitative agreement between fluorescence microscopy results and data obtained by 3C confirm that the HM loci are co-localized in a significant fraction of cells at any given moment . Combined , our results indicate that 3C data provide an accurate proxy for frequency with which loci are closely juxtaposed in vivo . We wished to firmly rule out the possibility that the observed interaction between the HM loci could be indirect and a consequence of contacts between other sub-telomeric elements . We used several approaches . First , we repeated the 3C analysis by including additional primers that detect interactions with EcoRI fragments directly flanking HML and HMR in MATa cells . We find that the peak of crosslinking frequency of HML and HMR corresponds to the precise location of these loci and that the crosslinking frequencies decrease dramatically immediately upstream and downstream of the fragment containing the HM loci ( Figure 1D left two panels ) . We observed the same in cells of the opposite mating type ( MATα , not shown ) . As a second approach we created a MATα strain in which the HMR locus was replaced with the KanMX cassette . We determined crosslinking frequencies between the fragment containing HML and fragments along the length of chromosome III including the EcoRI fragments containing and directly flanking the KanMX cassette ( Figure 1D third panel ) . We find that the peak of interaction is no longer observed and that the crosslinking frequency of HML with the fragments containing the KanMX cassette is similar to that of its neighbors . Likewise , when we analyzed interactions between the fragments containing the KanMX cassette with fragments along chromosome III including the fragment containing HML , we no longer detected the peak of interaction at HML ( Figure 1D fourth panel ) . These results indicate that the frequent interaction at HML observed in wild type cells requires the presence of HMR . In addition , this experiment rules out that the interaction is due to the presence of another genomic element in the sub-telomeric region located outside HMR but within the interacting EcoRI fragment . As a third approach , we determined the role of specific parts of HML and HMR in mediating their interaction . We analyzed the interaction between the heterochromatic loci using a different restriction enzyme , XbaI , as this enzyme cuts inside of HML and HMR to create fragments in which the left and right ends of HML and HMR are contained on separate restriction fragments . 3C primer sequences are listed in Table S1 . Interestingly , we find that the XbaI fragment containing the 5′ end of HML interacts preferentially with the fragment containing the 3′ end of HMR ( Figure 2A ) . Similarly , the fragment containing the 3′ end of HML preferentially interacts with the fragment containing the 5′ end of HMR ( Figure 2B ) . Furthermore , the interaction between the 5′ end of HML and the 3′ end of HMR is clearly the most frequent . These results point to the possibility that the interaction between HML and HMR involves the E- and I-silencer elements that flank HML and HMR on their 5′ and 3′ side , respectively . To test this we repeated the 3C analysis with a frequently cutting restriction enzyme AciI that cuts at multiple locations within the HM loci . We find that the small 814 bp AciI fragment containing the HMR-I element ( genomic position 294510–295324 ) most strongly interacts with the 821 bp fragment containing the HML-E silencer ( genomic position 10815–11636 ) , and significantly less frequently with other parts of HML ( Figure 2C ) . Conversely the fragment containing the HML-E silencer interacts most prominently with the HMR-I fragment , as compared to other regions of HMR ( Figure 2D ) . As a control we determined crosslinking frequencies between an AciI fragment located in the middle of HML . This fragment ( genomic position 11679–11906 ) interacted most prominently with the HMR-I fragment and the neighboring AciI fragment located within HMR , but the crosslinking frequencies were lower than that observed between HML-E and HMR-I ( Figure 2D ) , which is as expected for a fragment located just next to the site of interaction . These results strongly suggest that the HML-E and HMR-I silencers , or elements located very close to them , are the sites of interaction . Despite intense efforts , we have not been able to generate a mutant in which HMR-I was deleted without also creating unexplained rearrangements in the locus . Therefore we cannot unequivocally conclude that the interactions between HML and HMR are directly mediated by the silencer elements . Given the interaction observed between regions containing E- and I-silencers from opposite loci , we then asked whether E- and I-silencers from the same loci also interact ( Figure 2E and 2F ) . 3C analysis using the AciI enzyme indicates that the AciI fragments containing HML-E and HMR-E elements interact frequently with nearby sites . Interestingly , HML-E and HMR-E interacted more strongly with sites within the silent loci than with sites located outside HML and HMR , despite being separated by comparable genomic distances . One explanation could be that the silent loci are more compact than active chromatin , which can result in increased 3C crosslinking frequencies [33] , [34] , [36] . Alternatively , HML-E and HMR-E interact preferentially with a site within HML and HMR respectively . Interestingly , we note that the peak of interaction is near the promoters of HMRa and HMLα Importantly , the interactions of HML-E and HMR-E with HML-I and HMR-I respectively were significantly less frequent than other interactions throughout these regions ( Figure 2E , F ) . If a loop existed between silencer elements within a given locus these preferred interactions would stand out as peaks on top of a less frequent background of interactions . Our results indicate that although cross-linking frequencies are generally increased within the silent loci , there is no preferential interaction between the E- and I- silencers of each HM locus as compared to interactions with other sites throughout the HM loci . To determine whether HML and HMR need to be in a heterochromatic state for them to interact , we analyzed mutants that are defective in silencing . We first chose to analyze sir4Δ , sir3Δ and sir2Δ cells , because in these mutants silencing at both HML and HMR is completely lost [41] . Using 3C , we find that HMR and HML no longer interact in sir4Δ , sir3Δ and sir2Δ mutant strains ( Figure 3A ) . Interactions between HMR and the adjacent right telomere are not affected to a similar extent . Interestingly , the interaction between HMR and the right telomere is reduced in the absence of Sir4p but not upon deletion of SIR2 and SIR3 . This observation could be related to the degree of peripheral anchoring of these loci ( see below ) . In agreement with the 3C data , colocalization of HML and HMR , as determined by live cell fluorescence microscopy , is largely reduced in sir4Δ and sir3Δ cells , in which only 5% and 7% of distances scored are <250 nm respectively ( Figure 3B ) . As compared to wild-type where in ∼60% of the cells HML and HMR are found colocalized or adjacent to each other , in sir4Δ cells the distance between these loci is less than 500 nm in only 21% of cells ( Figure 3B ) . Similarly , in sir3Δ cells <35% of cells scored show HML and HMR colocalized or immediately adjacent to each other ( n = 500; Figure 3B ) . The distribution of 3D distances measured in sir3Δ ( n = 500 ) and sir4Δ ( n = 307 ) cells is clearly shifted to greater distances as compared to wt ( n = 836 ) . These results indicate that the heterochromatic structure established by the Sir complex or the Sir4p , Sir3p , and Sir2p proteins themselves are critical for the HML-HMR interaction . To extend our study , we asked whether Sir1p , a protein that interacts with silencer elements flanking HML and HMR via the Rap1p/ORC complex during the establishment of the silent chromatin state [42] participates in HM loci interactions . Interestingly , we find that , similar to sir4Δ , sir3Δ , and sir2Δ mutants , in sir1Δ cells HMR and HML no longer interact as shown by 3C and by 3D microscopy ( Figure 3A , B ) , despite significant residual silencing ( see below ) . Interactions between each HM locus and the telomere on the opposite end of chromosome III are concomitantly reduced ( Figure S2G and H ) . Given the results obtained with sir1Δ cells we chose to determine the role of Esc2p that has been identified as a protein that can functionally substitute for Sir1p [43] . Although it is currently not known whether Esc2p directly binds the HM loci , there is strong evidence suggesting that Esc2p is directly affecting the HM loci . First , Esc2p was identified as a protein that when targeted to HML can induce silencing [44] . Second , Esc2p has been shown to directly bind Sir2p [44] . Third , overproduction of Esc2p can substitute for Sir1p and aids in the establishment of silencing at HM loci [43] . Deletion of ESC2 has only minimal effects on silencing ( [43] , and see below ) . Interestingly , as in sir1Δ cells , we find that deletion of ESC2 completely abolished the specific interaction between HML and HMR ( Figure 3A ) . We conclude that Esc2p plays a critical role in HML-HMR interactions , presumably by directly acting on the HM loci , although we cannot formally rule out a more indirect role . Furthermore , given the importance of the silencers and silencing proteins for the HML and HMR interaction , we chose to analyze a mutant in which silencing proteins are recruited ( albeit to a lesser extent than in wild-type ) and assembled at the silencers but in which the Sir complex fails to spread across the silenced loci [45] . The mutant sir2-345 contains a point mutation at residue 345 , which results in an Asn-to-Ala substitution . This mutant lacks deacetylase activity which results in a defect in silencing [23] . In a sir2-345 mutant , an interaction between HML and HMR can no longer be detected by 3C ( Figure 3A ) . This indicates that in order for this interaction to occur proper heterochromatin must be formed and that the mere presence of Sir proteins at the silencers is not sufficient to promote HM loci interaction . A defect in silencing leads to expression of both a- and α- information from HMR and HML respectively , as in diploid cells ( i . e . they display defects in mating ) . Therefore , we analyzed a diploid strain to determine whether the loss of HML-HMR interaction is due to the sir mutant cell's diploid characteristics . We found no significant difference in the crosslinking frequencies between HML and HMR in wild type diploid and haploid strains ( Figure S3A ) . We conclude that the loss of HML-HMR interactions in sir4Δ , sir3Δ , sir2Δ , and sir1Δ mutants is not due to the cell's diploid-like state . HML and HMR , as well as the telomeres , are clustered in silent compartments near the nuclear periphery [12] , [13] . We questioned whether anchoring of these loci to the nuclear envelope ( NE ) may facilitate long-range interactions between them . To address this issue we wished to determine whether HML and HMR can interact and colocalize when their peripheral localization was disrupted . Two partially redundant pathways are involved in tethering heterochromatic loci such as telomeres to the NE . The first pathway is dependent on the Sir4p and Esc1p proteins . It has previously been shown in G1 cells that anchoring of the HM loci to the NE is reduced in cells deleted for Sir complex components [46] , [47] and that Sir-dependent anchoring requires Esc1p . The second pathway requires the yKu70p/yKu80p heterodimer . If either one of these genes is deleted most telomeres are partially released from the periphery [16] , [47]–[49] , although HM loci remain peripherally located [47] . Figure 4 shows the radial position of the HM loci for WT and mutant strains in interphase ( and not only G1 ) cells to be directly comparable with 3C studies that involve analysis of non-synchronized cultures ( see below ) . Nuclear positions of the tetop and lacop tagged silent HML and HMR loci were visualized using TetR or LacI repressor-GFP fusion proteins in G1 and S-phase cells [47] , [50] . Data were acquired in three dimensions to assign the position of the resulting fluorescent spot relative to the GFP-tagged NE ( Nup49-GFP ) in the focal plane in which it was brightest and in one of three concentric nuclear zones of equal surface . Enrichment of the silent mating type loci near the nuclear envelope in wild-type cells is abolished in a sir4Δ strain [[47]; Figure 4] . Interestingly , we find that this effect is specific for sir4Δ cells: in sir3Δ mutants significant anchoring of both HML and HMR was retained , possibly due to binding of Sir4p to the silencer nucleation site ( Figure 4 ) . Since in sir3Δ mutant strains we no longer detected preferential interaction and colocalization of HML and HMR ( Figure 3 ) , we conclude that proximity to the NE is not sufficient for their interaction . In addition , we find that in esc1Δ cells , the HM loci maintain their peripheral localization . This suggests that Sir4p containing heterochromatin can associate with the nuclear periphery in an Esc1p-independent manner . HML and HMR are also both directly associated with the nuclear periphery in a manner that does not require yKu70p . In interphase the position of HMR is unaffected by the absence of yKu70p , while HML's anchoring to the NE is significantly increased ( [47] , Figure 4 ) . Further , the increase in peripheral localization of the GFP-tagged HML locus in yku70Δ cells is dependent on the presence of the HML locus [47] . Similarly , deletion of HMR reduces the peripheral localization of the right end of chromosome III ( KB , unpublished observations ) . These analyses suggest that peripheral localization of HM loci is not solely due to the close proximity of HM loci to telomeres that are often anchored to the nuclear periphery and further indicate that the HM loci strongly contribute to the peripheral localization of the ends of chromosome III . Next we analyzed strains deleted for both ESC1 and YKU70 in which both anchoring pathways are abolished . We find that peripheral anchoring of HML and HMR was only slightly but not significantly reduced in interphase cells ( Figure 4 ) . Anchoring was somewhat more reduced in G1 than in S phase cells ( data not shown ) . These observations on the radial position of HMR in its native chromosomal location extend those reported by Gartenberg and colleagues who found that deletion of both YKU70 and ESC1 resulted in loss of peripheral localization of an extrachromosomal HMR locus [46] . Our results suggest that chromosomal context plays a role in peripheral localization . We conclude that alternative Sir4p-dependent pathways exist that anchor HM loci to the nuclear periphery . Next we analyzed HM interactions by 3C . In yku70Δ and in esc1Δ cells , we observed a significant increase in the frequency with which HML and HMR interact as compared to wild type cells ( Figure 5A ) . Deletion of YKU80 did not significantly affect the crosslinking frequency . In yku70Δ esc1Δ double mutants the HML–HMR crosslinking frequency is slightly higher than in either single mutant . These results demonstrate that yKu70p and Esc1p are not required for HML and HMR to specifically interact . We also analyzed HML–HMR colocalization in these strains by live cell fluorescence microscopy ( Figure 5B ) . In esc1Δ cells 51% of cells measured exhibit HML and HMR colocalization or juxtaposition ( n = 391 ) , which is comparable to what we observed in wild type cells ( P = 0 . 063 wt vs esc1 ) . In yku70Δ cells HML and HMR are found colocalized in 18% of the cells and adjacent to each other in another 28% of cells ( n = 814 ) . The frequency of co-localization is comparable to wild type , but the distribution of distances between HML and HMR differs from wild type . It appears that in the absence of yKu70p more nuclei display widely separated loci than in wild type ( P = 6 . 1e−6 wt vs yku70Δ ) . This may be related to the fact that populations of yku70Δ cells display two semi-stable states of silencing: one in which telomeres are delocalized and one in which they remain clustered [51] . Finally , we found that colocalization of HML and HMR in yku70Δesc1Δ double mutants was also comparable to wild type: 52% of the cells measured still show HML and HMR colocalized or immediately adjacent to each other ( n = 165 ) ( Figure 5B ) . We note that the 3C analysis revealed a ∼4-fold increase in HML-HMR interactions in all three mutants , but that live cell fluorescence failed to detect an increase in colocalization of these loci . The increased crosslinking frequency as detected by 3C may be due to loss of interactions of HM loci with telomeres , which could result in an increased chance for HM loci to become ligated in the 3C assay or due to a more intimate association that is more easily crosslinked ( see discussion ) . These analyses show that HML-HMR interactions do not require the known membrane anchors yKu70p/yKu80p and Esc1p . However , their peripheral localization was also not abolished in the absence of both these membrane anchors . Our inability to genetically disrupt peripheral localization of the silent mating type loci prevented us from directly assessing the influence of membrane anchoring on facilitating HML-HMR interactions . Therefore , as an alternative approach , we set out to follow the positions of HML and HMR in wild type living cells over several minutes in order to determine whether HML-HMR interactions can be observed in the interior of the nucleus or only at the periphery ( Figure 6 ) . Figure 6A shows a representative movie comprising a series of 50 2D images taken at 10 s intervals of interphase cells on a wide-field Olympus XI inverted microscope . HML and HMR tags colocalized either near the NE as identified by the nuclear pore component Nup49p fused to CFP , or at the center of the nuclei imaged . In addition , colocalization was a transient event , because , after a few minutes , separation of previously colocalized loci was observed ( compare time points 9 and 12 or time points 4 and 5 ) . Thus , HML and HMR seem to collide and separate both at peripheral and internal nuclear locations . In order to determine whether HML and HMR were more likely to interact at the nuclear periphery , we followed their position relative to the nuclear center in single nuclei over time taking images in 2D every 1 . 5 seconds on a confocal LSM510 microscope . Figure 6B summarizes the distances between HML and HMR plotted against the distance of either HML or HMR to the nuclear center at every time point during nine 1–2 min time lapse movies ( n = 676 ) . We found that in 2D HML is separated <250 nm from HMR ( colocalization ) in >45% of the time points scored . Moreover , the probability of colocalization was similar in the interior fraction ( position of HML or HMR less than 720 nm from the nuclear center , about 2/3 of the positions ) and the peripheral fraction of the nucleus . These movies clearly demonstrate that over long periods , interaction between HML and HMR was independent of NE anchoring . Histone chaperones and other proteins involved in nucleosome assembly play roles in gene silencing , heterochromatin formation and heterochromatic clustering in a number of organisms including yeast [26] , [27] , [52]–[55] . We determined whether these activities are also required for interactions between HML and HMR . Yeast contains two histone assembly complexes . The chromatin assembly factor 1 ( CAF-1 ) complex is involved in nucleosome assembly in S phase [56] , whereas the HIR complex functions primarily outside of S phase [57] . The histone chaperone Asf1p stimulates the activity of both complexes [27] , [58] . In addition , the HIR and CAF-1 complexes are involved in two parallel , and partially redundant pathways that enhance silencing at HML and HMR [27] , [59] . First , we tested a strain in which the CAF-1 complex is disrupted by deletion of CAC1 . Cac1p is the largest subunit of the CAF-1 complex and in strains lacking Cac1p HML and HMR are weakly derepressed [26] . We find that deletion of CAC1 did not affect the frequency with which HMR and HML interact ( Figure 7A ) . Next we analyzed a strain lacking Hir1p , a subunit of the HIR protein complex . Deletion of HIR1 has also been reported to result in slight de-repression of HML and HMR [57] . As for cac1Δ strains we find that deletion of HIR1 has no effect on the frequency of the HML-HMR interaction ( Figure 7A ) . Given the known functional redundancy of HIR and CAF-1 complexes , we created a double mutant strain in which both CAC1 and HIR1 are deleted . We find that in this case the prominent interaction between HML and HMR is no longer observed ( Figure 7A ) . These results point to a role of nucleosome assembly in mediating HML-HMR interactions , and show that the HIR complex and CAF-1 complex are functionally redundant in this process . Interestingly , in the double mutant , interaction frequencies along the entire chromosome are two- to three-fold higher than the background interactions we observed for all other strains . This may point to a more flexible chromosome organization . To further investigate the role of nucleosome assembly , we studied a strain lacking the histone chaperone Asf1p which functions with both the CAF-1 and HIR complex . Recently a role for Asf1p has been proposed for telomere sub-nuclear positioning [60] . Interestingly , we find that in an asf1Δ mutant the interaction between HML and HMR is no longer observed ( Figure 7A ) . We have also analyzed asf1Δ cells by live cell fluorescence microscopy ( Figure 7B ) . As compared to wild-type where in ∼60% of the cells HML and HMR are found colocalized or adjacent to each other , asf1Δ cells only have 29% of cells with HML and HMR colocalized or adjacent to each other ( n = 352; P = 2 . 2e−16 wt versus asf1 ) . Asf1p is also required for Histone H3K56 acetylation and its deposition [61] , [62] . H3K56 acetylation and deacetylation has been found to play roles in silencing telomeric loci in yeast and tethering of telomere 14L [60] , [63] . For this reason we chose to analyze strains which lack Rtt109p , the enzyme that acetylates Histone H3K56 in an Asf1p-dependent manner [62] , [64] , [65] . We find that in this mutant the interaction between HML and HMR is still observed , albeit with a somewhat reduced crosslinking frequency as compared to wild-type . ( Figure S3B ) . Therefore , the loss of interaction observed in asf1Δ mutants is not solely due to a loss of Histone H3K56 acetylation . Thus , incorrect or unstable tetramer incorporation may lead to poorly organized chromatin that is unfavorable for heterochromatic loci to interact . In order to determine whether HML-HMR crosslinking frequencies and colocalization are related to silencing , we measured the level of silencing in the various mutant strains analyzed in this study . Previously , varying silencing defects were observed for the strains described here that display loss of the HML-HMR interactions ( sir1Δ , esc2Δ , asf1Δ and cac1Δhir1Δ ) [27] , [42] , [43] . In most cases silencing defects could be detected using strains that have a reporter gene inserted in one of the HM loci ( either URA3 or ADE2 ) . Use of a reporter provides highly sensitive assays to quantify de-repression of HM loci as expression of the reporter gene can be detected even when expressed at very low levels . However , these reporter assays do not quantify the level of mRNA production compared to a fully expressed or repressed state . In order to quantify mRNA levels of the endogenous genes directly in a population of cells we employed RT-PCR to quantify the level of a1 mRNA levels ( located at HMR ) in MATα strains . This allowed us to analyze silencing levels in the same strain in which interactions between HM loci were detected . We observe that deletion of SIR4 , SIR3 , SIR2 , SIR1 or combined deletion of CAC1 and HIR1 as well as a sir2-345 point mutation results in significant de-repression of HMR relative to the Adh1 gene that was used as a normalization control ( Figure 8 ) . However , the other two mutants that display loss of the HM-interactions ( esc2Δ and asf1Δ ) had no detectable levels of a1 expression , and thus had largely normal levels of silencing as determined by RT-PCR . Experiments employing reporter genes also revealed only very minor silencing defects in these strains [43] , [66] . We conclude that all mutants with a significant silencing defect have also lost the interaction between the HM loci . However , we find no clear quantitative correlation between silencing and HM interactions ( Figure 8 , inset ) because in two cases ( esc2Δ and asf1Δ ) HM interactions are lost , but silencing is mostly unaffected . We conclude that Sir-mediated silencing is not sufficient for clustering of HM loci , and that additional processes in heterochromatin formation are specifically required for associations between heterochromatic loci . These processes require at least Asf1p , Esc2p and possibly Sir1p .
Our live tracking of the sub-nuclear positions of HML and HMR in wild-type cells showed that these loci can colocalize as frequently when these loci are located near the center of the nucleus as when they are near its periphery . Therefore , association with the nuclear envelope is not required for HML-HMR interactions . Further , the results we obtained in a sir3Δ strain show that membrane anchoring is not sufficient for HML-HMR interactions to occur . We conclude that clustering of heterochromatic loci and NE anchoring are two distinct processes that each contribute to nuclear organization . Surprisingly , our analyses also reveal that peripheral localization of HM loci is not reduced upon inactivation of the two previously defined pathways for membrane anchoring of heterochromatin . As shown previously [47] , deletion of YKU70 increases the peripheral localization of HML in interphase cells , while not affecting the positioning of HMR . In addition , given that in yku70Δesc1Δ double mutant cells heterochromatin formation near telomeres is disrupted and Sir4p is found uniformly throughout the nucleus [46] , [48] but HM interactions are retained ( Figure 5 ) , these data also indicate that sequestration of Sir protein in clusters is not required for interactions between HML and HMR . Consistent with the loss of Sir protein clusters , we found that in yku70Δesc1Δ double mutant cells interactions between some telomeres is reduced , as detected by 3C , suggesting that in this mutant telomere clustering is affected , while HM interactions are retained ( Figure S3D ) . We observed that the interaction between HML and HMR , as detected by 3C , is more frequent in yku70Δ , esc1Δ , and yku70Δesc1Δ mutant cells than in wild-type cells . However , live fluorescence microscopy revealed no increase in their colocalization as compared to wild type cells . This apparent discrepancy may be explained in different ways . First , it is possible that the interaction between HML and HMR is more intimate , and thus more effectively crosslinked , in these mutants , in a manner that is not microscopically distinguishable from wild type . A more intimate association may be the result of an increase in Sir protein occupancy at the HM loci in these mutants . Sir protein occupancy at the HM loci is likely increased in these mutants because telomere silencing and clustering are affected [46] , [49] . Loss of Sir proteins from telomeres has been found to increase the available pool of Sir proteins that are accessible to the HM loci , which may enhance their ability to interact [14] , [51] . An alternative explanation is that 3C underestimates the HM crosslinking frequency in wild type cells , or overestimates their crosslinking frequency in these mutants . Given that the HM loci interact with each other as well as with telomeres , a loss of telomeric heterochromatin will reduce the number of interaction partners to which HM loci can be cross-linked and ligated during the 3C procedure , resulting in detection of relatively more frequent HML-HMR interactions in these mutants . Although our studies clearly found a strong correlation between 3C crosslinking frequency data and colocalization of HM loci , future experiments are needed to further quantify the relationship between 3C data and data obtained by fluorescence microscopy . The Sir complex and proteins that recruit this complex , as well as histones and nucleosome assembly factors all cooperate to assemble silenced chromatin domains . We find that mutants in each of these protein complexes display loss of HML-HMR interactions . Thus the pathways that mediate heterochromatin formation and the mechanism ( s ) that drive HM interactions are clearly related and are mediated by overlapping protein complexes . However , several observations indicate that these processes are mechanistically distinct as they differentially depend on specific chromatin factors . First , two mutants ( esc2Δ and asf1Δ ) that display a complete loss of interaction between HML and HMR display only very minor defects in silencing as detected by RT-PCR . Similar very minor silencing defects have been detected using reporter constructs . Huang et al . used a GFP reporter gene inserted in HMR to detect GFP expression in WT , sir3Δ and asf1Δ strains [66] . They found that in WT cells HMR is silent and only 0 . 3% of cells expressed GFP , whereas in sir3Δ cells the locus was mostly derepressed with 99% of cells expressing GFP . Deletion of ASF1 resulted in GFP expression in only 0 . 9% of cells , indicative of effective silencing . Although we cannot formally exclude the possibility that very small defects in silencing are sufficient to cause loss of HML-HMR interactions , we favor the interpretation that heterochromatin formation and silencing is not sufficient for HM interactions , and conversely that HM interactions are not essential for heterochromatin formation . Second , genetic evidence indicates that Hir1p and Asf1p act in the same silencing pathway [27] , but they display very different effects on HM interactions , suggesting that for the latter process they act in different pathways . In addition , single deletions of HIR1 , CAC1 or ASF1 all result in minor silencing defects [26] , [27] , [66] , [67] , but only deletion of ASF1 results in loss of HM interactions . Third , the cac1Δhir1Δ double mutant and the asf1Δ mutant display the same loss of HML-HMR interactions , but they have quantitatively very different effects on silencing [27] , again pointing to differential dependence of silencing and long-range interactions on these chromatin assembly factors . The differential effect of deletion of SIR1 on silencing and HM interactions is particularly interesting . In the absence of Sir1p HML and HMR are partially derepressed . This is due to the occurrence of two distinct populations of chromatin states: in one subset of cells the loci are completely repressed , whereas in the other subset they are fully expressed [42] . Our RT-PCR analysis of HMR expression suggests that ∼60% of loci remain repressed , whereas ∼40% are expressed . However , the 3C analysis showed a complete loss of HML-HMR interactions and the level of colocalization , as determined by live cell 3D imaging was indistinguishable from background levels observed in sir4Δ cells . These results indicate that Sir1p may have a specific role in long-range interactions between heterochromatic loci that is distinct from mediating gene silencing per se . Taken together , formation of silent heterochromatin at HML and HMR is essential but not sufficient for long-range interactions between HM loci . HML-HMR interactions require Asf1p , Esc2p and possibly Sir1p in a process that is distinct from silencing . Other proteins , such as other SIR complex components may also play a role in that process , but their role in HM interactions is more difficult to assess , as they are also essential for HM silencing . Interestingly , it has recently been shown that deletion of ASF1 shows a telomere-positioning defect , and also affects the sub-nuclear positioning of other chromosomal loci [60] . Deletion of ASF1 does not affect telomere silencing [27] , [67] , suggesting that silencing of telomeres is not sufficient for their positioning . Combined with our data , these results point to a specific Asf1p – dependent process that is required for heterochromatic positioning in the nucleus in general . Restriction fragments encompassing HML-E and HMR-I interact most frequently compared to other parts of the HM loci . These restriction fragments do not contain the boundary elements that have been identified up and downstream of HMR [68] , suggesting the HM interaction involves the HML-E and HMR-I silencer elements specifically . Interestingly , one protein that we identified as critical for long-range interactions , Sir1p , associates with replication related complexes bound to the silencer elements [69] , [70] , and another ( Asf1p ) displays genetic interactions with ORC2 [71] and physically associates with other replication factors such RF-C [72] . Unfortunately , we have not been able to precisely delete HMR-I so we have not been able to directly test the role of this element in mediating HM interactions . Deletion of HML-E would not address this issue as it would also result in derepression of HML . Our results are different from those recently described by Kamakaka and co-workers , who reported Sir3p-dependent looping interactions between the two silencers of HMR , HMR-E and HMR-I [28] . One explanation for this difference could be the fact that they used strains in which HMR was slightly modified to introduce extra Sau3A restriction sites , and HML and the active MAT locus were deleted , precluding HMR-HML interactions . However , we did not detect HML-E-HML-I interactions when we deleted HMR in our strain background ( not shown ) . An alternative explanation is that different strain backgrounds were used . The HML-HMR association is not essential for silencing , suggesting that the role of this interaction in silencing is either highly redundant with other pathways that contribute to heterochromatin formation or that it is involved in other processes , such as mating type switching or contributing to higher order nuclear organization in general . Various lines of evidence suggest that HM-interactions are not involved in mating type switching . First , we did not detect any differences in the interaction in either MATa or MATα cells , despite well-characterized mating-type-dependent differences between the left and right arm of chromosome III with regards to mobility and accessibility for recombination complexes [e . g . [73] , [74]] . Second , we also analyzed mutants in which the recombination enhancer ( RE ) , an element known to mediate donor preference in mating type switching , was deleted and observed only a minor increase in crosslinking frequencies between HML and HMR in a- or α- cells ( Figure S2C and D ) . In addition , previous studies also revealed no difference in nuclear positioning of HML and HMR in mutants when the RE was deleted [47] ( and data not shown ) . Lastly , we tested directly whether any mating type switching defect was observable in asf1Δ and esc2Δ mutants . We analyzed the mating proficiency of meiotic products of HO/” asf1Δ/” or HO/” esc2Δ/” strains and found that spore colonies did not mate with a tester strain , indicating that spores efficiently self-diploidized and thus were fully capable of switching ( data not shown ) . Thus , it appears that the HM-interaction does not play a critical role in mating type switching . We propose that the HML-HMR interaction plays primarily a structural role by contributing to clustering of heterochromatin and formation of heterochromatic sub-nuclear compartments ( see Figure 9 for model ) . In the absence of silencing proteins , HM-loci are not silenced and do not interact . Upon expression of silencing proteins , they are recruited to the HM-silencers resulting in heterochromatin formation and silencing . This step requires the presence of SIR proteins and the CAF-1/HIR1 complex for proper nucleosome assembly . Once silenced , these loci then engage in long-range interactions , which are dependent upon the presence of Asf1p , Esc2p , and Sir1p . Once heterochromatic clusters are formed , the nuclear distribution of silencer proteins becomes highly non-homogeneous with high local concentrations in the silent compartments and depletion in the rest of the nucleus . Nuclear compartmentalization could be advantageous because only loci located within the silent compartments will have access to abundant silencer proteins while the rest of the genome is precluded from inadvertently gaining access to heterochromatin proteins . Consistent with this model , a recent study showed that loss of heterochromatic clustering resulted in inappropriate Sir-mediated ectopic repression of genes throughout the genome [75] .
HMR , SIR1 , SIR2 , SIR3 , SIR4 , CAC1 , ASF1 , ESC2 , KU70 , KU80 , ESC1 , HIR1 , the recombination enhancer ( RE ) located on chromosome III ( SGD coordinates 29017–29799 ) and RTT109 were replaced with antibiotic resistance markers using a standard PCR based gene disruption strategy [76] . To generate the sir2-345 mutant , plasmid pRS 345 [23] , which is linked to LEU2 was cut with Hpa1 and integrated into chromosome III in a sir2Δ background . All strains used for 3C were maintained in a SK1 background ( Supplementary Table 2 ) . Cells were freshly streaked on YPD medium containing 2% glucose before 3C analysis . For microscopy analyses , yeast were grown at 30°C in rich glucose media ( YPD ) unless otherwise indicated . Strains are listed in Table S2 . Plasmids used to integrate the tet or lac operator arrays and repressors were as described [77] . The following PCR-amplified genomic fragments ( SGD coordinates ) were used for insertion near the respective loci: 15160–15773 for HML , 294892–295241 for HMR and 197194–196910 for MAT on Chr3 . LacI-GFP or lacI-CFP , and tetR-GFP or tetR-YFP , and where indicated GFP-Nup49 or CFP-Nup49 fusions , were introduced as described [77]–[79] . Note that the wild type strain with the tetop and lacop operator inserted near the HM loci has been described before [30] . For live and intact cell imaging , cultures carrying two color tagged integration sites were grown exponentially in YPD to OD600 nm< = 0 . 4 ( ∼1×107 cells/ml ) , and rinsed in complete synthetic medium before imaging . Microscopy was performed at 25°C . Cells were spread on synthetic complete 3% agarose patches for acquisition . 3D images were captured on a Metamorph driven Olympus IX81 wide-field microscope equipped with a Coolsnap HQ camera and a Polychrome V ( Till Photonics ) . Stacks of 21 images were acquired with a step size of 0 . 2 µm either at 490 nm for 200 ms for GFP or alternating the wavelength between 435 nm ( CFP ) and 512 nm ( YFP ) at every image plane , and exposures of 400 ms per wavelength . A 100×/1 . 4 Oil Plan-Apochromat objective ( Olympus ) was used . Position of GFP tagged loci relative to the nuclear rim identified by the Nup49-GFP signal were determined as a percentage of fluorescent spots in one of three concentric nuclear zones of equal surface in the plane bearing the brightest GFP-lacI or tetR-GFP focus using the Pointpicker plug-in for Image J [47] , [50] . Only the 10 core focal planes were scored . For 3D distance determination , CFP and YFP images were automatically analyzed using SpotDistance implemented as a plug-in for ImageJ , freely available at: http://bigwww . epfl . ch/spotdistance/ [80] . The measured distances were loaded into R software ( www . r-project . org ) and the measured distance distributions translated into a box plot . Outliers are defined as 1 . 5 times the Inter Quartile Range ( IQR ) and are represented as open circles . Different distance distributions ( determined as non-normal using a Kolmogorov-Smirnov test ) were scored for significant difference in R using the Wilcox test . 2D time-lapse imaging ( Figure 6B ) was performed on a Zeiss LSM510 confocal microscope using a 100× Plan-Apochromat objective ( NA = 1 . 4 ) partly at the RIO Imaging facility in Toulouse , France , and partly in Susan Gasser's laboratory at the University of Geneva , Switzerland . Live imaging was performed as described [30] . Nine independent 2D time-lapse series of 50 to 150 confocal images were acquired at 1 . 5 s intervals of G1-phase nuclei , following the tagged foci by adjusting the focal plane . 2D distances were measured manually using Metamorph . 3C was performed as described by Dekker et al . , with modifications described in Miele et al . [4] , [29] , [32] . Cells were freshly grown in YPD medium to an OD600 of 1 . 0 . Cells were then resuspended in buffer containing 0 . 4 M sorbitol , 0 . 4 M KCl , 40 mM Na ( H ) PO4 , 0 . 5 mM MgCl2 , and 0 . 1 mg/mL of zymolyase 100-T and incubated at 30°C for 40 minutes . Efficiency of the digestion of cell wall was tested by observation of hypotonic lysis within 1–2 minutes . Spheroplasts were washed three times in a buffer containing 0 . 1 M MES , 1 . 2 M sorbitol , 1 mM EDTA , and 0 . 5 mM MgCl2 and then resuspended in the same buffer . Formaldehyde was added to a final concentration of 1% and crosslinking was allowed to proceed for ten minutes at room temperature . The reaction was quenched by addition of glycine to a final concentration of 125 mM and incubation for 5 minutes at room temperature . Cells were washed three times and resuspended in the restriction enzyme buffer . Chromatin was solubilized by the addition of 0 . 1% final concentration of SDS and incubation for 10 minutes at 65°C . Trition X-100 was added to a final concentration of 1% . A restriction enzyme was added and samples were incubated overnight at the appropriate incubation temperature . The digestion efficiency was determined to be 80% and this percentage did not vary between restriction cut sites ( see Figure S3C ) . The restriction enzyme was inactivated by addition of SDS to a final concentration of 1 . 6% followed by incubation at 65°C for 20 minutes . Chromatin was diluted for ligation to promote intramolecular ligation over intermolecular ligation . Triton X-100 was added to 1% and DNA was ligated for 2 hours at 16°C with T4 DNA ligase . The cross-links are reversed overnight by incubation at 65°C in the presence of 5 microgram/ml of proteinase K . After overnight incubation an additional 5 microgram/ml of proteinase K was added and incubated for an additional 2 hours at 42°C . DNA was purified by a series of phenol-chloroform extractions followed by ethanol precipitation . The resulting template was then treated with RNAse A . In addition to the above 3C template a randomized control template was also generated which is used to determine PCR amplification efficiency of specific 3C ligation products . This template was created by digesting purified non-crosslinked yeast genomic DNA which is then followed by a random intermolecular ligation . The resulting template was purified by a series of phenol-chloroform extractions and ethanol precipitations . The resulting template was also treated with RNAse A . Once both the 3C templates and control templates are generated a PCR titration is performed to determine the amount of template to be used in the subsequent PCR reactions as shown in Figure S1A and B . PCR is performed in a 50 µl reaction in a buffer containing 10 mM Tris-Cl pH 8 . 4 , 50 mM KCl , 2 . 25 mM MgCl2 , 0 . 5 mM dNTPs and 0 . 4 µM of each primer . The following PCR program gives quantitative results: 32 times: 1 minute at 95°C , 45 seconds at 60°C , 2 minutes at 72°C . This is followed by 1 minute at 95°C , 45 seconds at 60°C , and 8 minutes at 72°C . PCR products are quantified semi-quantitatively on 1 . 5% agarose gels in the presence of ethidium bromide . Previous work displays that semi-quantitative PCR and quantitative real-time PCR yield similar results [39] , [81] , [82] . Multiple primer combinations are used that detect highly abundant 3C ligation products as well as infrequently formed products to be sure that the amount of template used in each reaction is within the linear range . The subsequent PCR reactions are done in triplicate for both the control and 3C template . The crosslinking frequency is then determined by calculating the ratio between the amount of PCR product obtained with the 3C template and the control template . The three resulting crosslinking frequencies are then averaged together and one value is obtained . This is the value that is plotted in interaction graphs . The standard deviation of the mean is determined and is used as the error bars ( see Table S3 for examples of crosslinking frequency determination ) . Restriction enzymes were chosen to create an equal distribution of restriction fragment cut sites and also to allow for important elements ( i . e . HMR-I , HMR-E , HML-E , HML-I , etc ) to be on different restriction fragments . Primers were then designed for restriction fragments of interest ( see Table S1 for sequences and Figure S1C for diagram of EcoRI primers ) . Primers were designed unidirectionally unless a unique primer could not be designed on that particular end of the fragment . They were designed to be approximately 28 base pairs long with 50% GC content . Once designed , the primers were tested on a control template and those primers that give aberrant products , multiple products , and abundant primer dimers were re-designed . 3C analyses for wild type and each mutant described above were performed in at least two , and in most cases three independent experiments , with each data point quantified in triplicate . Figure S4 displays some examples of biological repeats of 3C analyses that illustrate the highly reproducible nature of 3C interaction profiles in WT and several mutant strains . All 3C data are normalized to the wild type ( mating type a ) dataset so that all interactions can be quantitatively compared , as described in [33] , [34] . Datasets for wild-type ( mating type α ) , hmrΔ fine mapping analyses , ku70Δesc1Δ , and cac1Δhir1Δ mutants strains were normalized by calculating the average log ratio of crosslinking frequencies between the anchor fragment and neighboring fragments measured within each of the different strains as compared to wild type and setting this ratio at zero . For data normalization with all other mutants , 8 crosslinking frequencies were determined between pairs of loci located along yeast chromosome VI . Data normalization was performed by calculating the average log ratio of the set of 8 crosslinking frequencies measured in each mutant as compared to wild type and adjusting the mutant data sets so that this ratio becomes zero . EcoRI cutting efficiency was determined for a fragment upstream of HML , the fragment containing HML , and a fragment at the left telomere of chromosome III . Intact yeast cells were treated with 1% formaldehyde . Chromatin was solubilized and one part was digested with EcoRI while the other part was not . Cross-links were reversed and the DNA was purified . Semi-quantitative PCR was done across restriction fragments on both samples and the ratio of PCR products was calculated to determine the percentage of loci that were not digested upon formaldehyde cross-linking . The data was normalized for the amount of DNA used in each reaction using a pair of primers that amplify a region contained within an EcoRI fragment . Digestion efficiency was comparable to that reported previously [33] , [34] . The level of digestion was around 75–80% , and was not significantly different for HML as compared to other sites ( Figure S3C ) . Given that the digestion efficiency is linearly related to the level of cross-linking [34] , this result also implies that the level of cross-linking is similar at these locations . We conclude that the peak in crosslinking frequency observed at HML and HMR is not due to differences in digestion or cross-linking . Total RNA was isolated by using the RNeasy Mini Kit ( Qiagen , Valencia , CA ) . cDNA was synthesized using the SuperScript First-Strand Synthesis for RT-PCR protocol including DNase I treatment as described ( Invitrogen . com ) . The cDNA was synthesized using oligodT12-18 ( Invitrogen ) and then was amplified by PCR . Primer sequences for a1 expression are described by Smeal et al . [83] . Primer sequences for ADH1 , which was used as the internal control , are available upon request . | Chromosomes are non-randomly positioned inside cells , and this organization is relevant for genome regulation . Spatial clustering of heterochromatic loci provides a striking example of nuclear compartmentalization . In S . cerevisiae , the presence of heterochromatic sub-nuclear domains has been well established , but their mechanisms of formation are not fully understood . Here , we analyzed the DNA elements and protein complexes that are critical for formation of heterochromatic clusters . We focused on heterochromatic regions on chromosome III—the two telomeres , as well as the silent mating type loci HML and HMR , located on the left and right end of the chromosome , respectively . We employed live cell 3-D imaging and chromosome conformation capture ( 3C ) and found that these loci specifically interact most prominently near silencer elements that flank the loci . Analysis of a panel of mutants showed that complexes involved in silencing are also involved in long-range interactions . Interestingly , we find that heterochromatic interactions are mechanistically distinct from silencing and independent of tethering to the nuclear periphery . Our results indicate that formation of heterochromatic clusters depends on correctly assembled heterochromatin , and point to a step in heterochromatin formation that is not essential for gene silencing but is required for long-range interactions between heterochromatic loci . | [
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] | 2009 | Yeast Silent Mating Type Loci Form Heterochromatic Clusters through Silencer Protein-Dependent Long-Range Interactions |
Crosses between laboratory strains of mice provide a powerful way of detecting quantitative trait loci for complex traits related to human disease . Hundreds of these loci have been detected , but only a small number of the underlying causative genes have been identified . The main difficulty is the extensive linkage disequilibrium ( LD ) in intercross progeny and the slow process of fine-scale mapping by traditional methods . Recently , new approaches have been introduced , such as association studies with inbred lines and multigenerational crosses . These approaches are very useful for interval reduction , but generally do not provide single-gene resolution because of strong LD extending over one to several megabases . Here , we investigate the genetic structure of a natural population of mice in Arizona to determine its suitability for fine-scale LD mapping and association studies . There are three main findings: ( 1 ) Arizona mice have a high level of genetic variation , which includes a large fraction of the sequence variation present in classical strains of laboratory mice; ( 2 ) they show clear evidence of local inbreeding but appear to lack stable population structure across the study area; and ( 3 ) LD decays with distance at a rate similar to human populations , which is considerably more rapid than in laboratory populations of mice . Strong associations in Arizona mice are limited primarily to markers less than 100 kb apart , which provides the possibility of fine-scale association mapping at the level of one or a few genes . Although other considerations , such as sample size requirements and marker discovery , are serious issues in the implementation of association studies , the genetic variation and LD results indicate that wild mice could provide a useful tool for identifying genes that cause variation in complex traits .
The house mouse , Mus musculus , consists of three principal subspecies , with native populations of M . m . musculus in Eastern Europe and Asia , M . m . castaneus in Southeast Asia and India , and M . m . domesticus in Western Europe and the Middle East [1] . Populations in the Americas , Africa , and Australia are mainly of domesticus origin , due to recent transportation by Western European seafarers [1] , although an admixture of domesticus and castaneus has been found in one California population [2] , and other such cases may occur elsewhere . M . musculus developed a commensal relationship with humans at the dawn of agriculture , and natural populations ( “wild” mice ) of all three subspecies now live primarily in close association with human dwellings [3] . Laboratory strains were developed from domesticated pets and appear to be an admixture of all three subspecies [4 , 5] . Crosses between inbred strains of laboratory mice have been used very successfully to identify quantitative trait loci ( QTL ) that affect a variety of complex traits , including many related to human diseases such as atherosclerosis , diabetes , and obesity . Flint et al . [6] note that more than 2 , 000 mouse QTL have been detected , whereas only about 20 of the causal genes have been identified . The basic problem in gene identification is that most QTL have been discovered in F2 mapping populations , in which the confidence region for a QTL generally spans 20–40 cM ( containing hundreds of genes ) , and efficient methods for fine-mapping have not been available . The classical approach to fine-mapping is construction of congenic lines , which can take several years to achieve a resolution of 1 cM ( containing about 15 genes ) [6] . In recent years , new genetic and genomic approaches have been used to reduce the time and improve the resolution of QTL mapping in mice ( Table 1 ) . These approaches include haplotype analysis of parental lines to exclude regions of identity-by-descent [7 , 8] , association studies with a set of inbred lines [9–11] , and admixture mapping in laboratory stocks with multiple inbred parents and multiple generations of recombination [12] . The expected resolution of several methods is an interval containing roughly ten to 20 genes , although the actual resolution varies with other factors such as gene density . The use of transcriptional profiling and other functional annotation sometimes can reduce the number of likely candidates to just one or a few genes [12–15] . However , useful annotations are not always available , and could be misleading . Hence , there is a need for an efficient genetic method that achieves even finer mapping resolution than existing methods . In humans , association studies are being used extensively to identify genes that cause variation in complex traits [16–18] . This method relies on either genotyping the causative polymorphism directly , or on genotyping “tag” markers that are in strong linkage disequilibrium ( LD ) with the causative site . In human populations , strong LD occurs over a distance that varies depending on the genomic region , but is usually on the order of tens of kilobases [19–21] . Therefore , a significant marker–trait association in humans usually indicates that a causative polymorphism for the trait is located within about 100 kb of the marker , providing a resolution on the order of one or a few genes for LD mapping . This pattern of LD has been shaped by recombination , population structure , and demographic history . Although the house mouse has less recombination than humans [22] , the commensal relationship between the two species has resulted in parallels in demographic history that might have led to similarities in the LD pattern . Here , we investigate the genetic structure of a natural population of mice in Arizona to determine its suitability for fine-scale LD mapping and association studies . There are three main findings: ( 1 ) Arizona mice have a high level of genetic variation , which includes a large fraction of the sequence variation present in classical strains of laboratory mice; ( 2 ) they show clear evidence of local inbreeding but appear to lack stable population structure across the study area; and ( 3 ) LD decays with distance at a rate similar to human populations , which is considerably more rapid than in laboratory populations of mice . These results indicate that wild mice could provide a useful tool for identifying genes that cause variation in complex traits .
In this study , wild mice ( M . musculus domesticus ) were sampled from a natural population in the vicinity of Tucson , Arizona . A total of 94 mice were collected , each from a different site to avoid sampling close relatives , and we also collected small samples of the three M . musculus subspecies from their native ranges . To assess population structure and long-range LD , these mice were genotyped for a genome-wide set of 4 , 581 single nucleotide polymorphisms ( SNPs ) with a median distance between adjacent markers of ∼500 kb . These SNPs were ascertained in laboratory strains . In the Arizona mice , 89% of the SNPs are polymorphic , and 67% are “common” ( i . e . , minor allele frequency [MAF] > 0 . 05 ) . To assess short-range LD , we resequenced segments in four genomic regions , each on a different autosome , and each focused on a candidate gene from previous QTL studies of metabolic traits in laboratory mice ( Alox15 [23] , Apoa2 [13] , C3ar1 [24] , and Nr1h3 [25] ) . A total of 25 . 7 kb of sequence per mouse was obtained in segments of ∼1–2 kb , with one segment in each gene of interest and the others at distances of 25 , 100 , and 200 kb away from the gene in a single direction . The observed nucleotide diversity ( π , the average proportion of nucleotide differences between pairs of sequences ) is 0 . 10% in Alox15 , 0 . 37% in Apoa2 , 0 . 45% in C3ar1 , and 0 . 09% in Nr1h3 ( excluding coding sequence ) . Although the sample of loci sequenced in the Arizona mice is small , the mean π ( 0 . 25% ) is very similar to the mean of 0 . 21% ( SD = 0 . 20 ) for 21 autosomal loci in Western European populations of domesticus ( the source of North American populations ) [26 , 27] . This result indicates a high level of genetic variation in Arizona mice . For reference , human populations of Asian and European descent have an estimated π of 0 . 08% to 0 . 10% for autosomal loci [28 , 29] . The wild Arizona mice are polymorphic for a large fraction of SNPs found in classical inbred lines of laboratory mice . A total of 285 SNPs were discovered by resequencing the four regions in Arizona mice , and 163 of these are common ( MAF > 0 . 05 ) . In the same segments , public databases contain 63 SNPs that are polymorphic across classical inbred lines . The public databases do not contain a complete inventory of all SNPs that occur in laboratory strains , so these SNPs should be regarded as a sample . Within the sample of 63 classical line SNPs , 51% ( 32 ) occur with MAF > 0 . 05 in Arizona mice . Similarly , 67% of the 4 , 581 SNPs in the genome-wide panel ( ascertained in laboratory strains ) are common in the Arizona population . These results suggest that roughly 50% of the QTL found in classical line crosses will be segregating in the Arizona population , assuming that most QTL are due to SNPs ( rather than structural variation [30] ) and that causal SNPs are distributed in the same way as other SNPs . In a related study , T . Salcedo and M . Nachman ( unpublished data ) examined haplotypes of five X-linked loci in European domesticus and musculus subspecies , as well as eight classical inbred strains . They found that laboratory strain haplotypes often are common in the wild mouse populations , consistent with earlier studies comparing wild-derived and classical inbred lines [4] . These haplotype studies support the notion that many of the lab mouse QTL are common in wild mouse populations . In addition , because laboratory mice contain a limited sample of the genetic diversity that occurs in nature [5] , wild mice also provide an opportunity for new QTL discovery . The Arizona mice show significant deviations from the Hardy-Weinberg ( HW ) equilibrium , with an excess of homozygotes at 45% of autosomal loci ( α = 0 . 05 ) in the genome-wide panel . The inbreeding coefficient estimated from HW deviations is 0 . 20 averaged across loci . A similar study by Ihle et al . [31] of 204 microsatellite loci in domesticus populations in France , Germany , and Africa also revealed excess homozygosity . These results suggest the presence of population structure and/or inbreeding in wild mouse populations , as previously indicated by allozyme and other field studies of domesticus populations [32 , 33] . The relationships among wild mice were investigated by clustering genetic distances ( one minus the mean fraction of alleles shared per locus ) . Figure 1 shows a neighbor-joining tree for samples from Arizona and for the three subspecies from their native ranges . The star-shaped pattern for Arizona mice indicates a lack of geographic differentiation within the study area and suggests that most pairs are unrelated . Very similar trees were obtained by Ihle et al . [31] for samples from French , German , and African populations of domesticus . There is no overall correlation between genetic distance and collection site distance in Arizona ( Figure S1 ) , although several pairs of individuals with low genetic distances also have low collection site distances . This result indicates some local inbreeding , but argues against a gradient of differentiation across the study area . We also looked for cryptic structure in the Arizona population using the model-based clustering method of Pritchard et al . as implemented in the Structure 2 . 2 program [34] . When all the individuals in Figure 1 are used in the analysis , there is a large increase in the likelihood going from a model of one to a model of two subpopulations , but very small changes going from two to three or from three to four subpopulations ( Figure S2A ) . The two-subpopulation model separates the musculus , castaneus pair from the Arizona , western European domesticus pair , such that each individual is clearly assigned to one or the other group . The three- and four-subpopulation models also maintain this division . Analysis of the Arizona population alone gives only small changes in the likelihood with each increase in the number of subpopulations modeled ( Figure S2B ) . Therefore , the model-based structure analysis fails to support differentiation of the Arizona population into a small number of subpopulations . We also estimated the inbreeding coefficient of each individual and the kinship coefficient of each pair of individuals using a model that allows for inbreeding , but no population structure . The mean of the inbreeding coefficients is 0 . 21 ( consistent with the observed deviations from the HW equilibrium ) and 90 of the 94 estimates are less than 0 . 5 ( Figure S3 ) . Four mice have inbreeding coefficients greater than 0 . 50 , which is equivalent to three generations of full-sibling mating . The mean kinship coefficient is 0 . 0055 , and 91% of the 4 , 371 pairs have an estimate less than 0 . 0156 , which is the expected value for second cousins in a population with no inbreeding ( Figure S4 ) . Therefore , most pairs of mice are essentially unrelated , as indicated by the neighbor-joining tree in Figure 1 , but a small number are rather highly inbred , and several pairs are closely related ( see Figures S3 and S4 ) . Early studies of allozyme variation in North American domesticus showed genetic differentiation on a fine spatial scale , such as different buildings on the same farm , suggesting highly structured populations and low dispersal rates [32 , 35] . However , recent ecological studies have shown that wild mouse demes are very transient in nature , and there is considerable long-distance migration [36] . The results presented here are consistent with the ecological studies in suggesting some local inbreeding ( which may result in transient differentiation on a fine scale ) , but also considerable gene flow across distances on the order of tens of kilometers so that stable population structure within our study area appears to be absent . The decay of LD for autosomal SNPs from the genome-wide set is summarized in Figure 2 ( and Figure S5 ) , with comparisons to previous studies of human and laboratory mouse populations . The figures show that LD decays with physical distance in Arizona mice on a scale similar to samples from human populations of Asian and European descent [19] , although somewhat less rapidly . In the human samples , there is essentially no significant LD between markers >1 Mb apart , but in Arizona mice this distance is >2 Mb . However , in Arizona mice , when markers are more than 200 kb apart , r2 is nearly always less than 0 . 3 , which provides very low power for detecting associations unless the effect is very large [37] . The LD for X-linked SNPs may be slightly higher than for autosomal SNPs . In the range of 0–2 Mb , the mean of r2 for X-linked pairs is 0 . 072 , and that for autosomal pairs is 0 . 021 , but the sample size of X-linked pairs is small ( 82 X-linked versus 7 , 669 autosomal ) . Permutation testing shows essentially no significant LD between pairs of markers on different chromosomes in Arizona mice ( 1 . 3% are significant at the nominal 1% level ) . This result is consistent with the apparent lack of population structure ( despite the excess homozygosity ) . Figure 2 also shows LD in two types of laboratory mice that are being used to refine QTL location . One type is a set of 54 inbred lines used for association studies ( also known as “in silico” mapping [9] ) , and the other is an outbred “heterogeneous stock” ( HS ) founded from an eight-way cross of inbred lines and used for admixture mapping [12] . In contrast to natural populations of mice and humans , these laboratory mice have strong LD for distances up to several megabases , and r2 values of 1 are sometimes observed for very distant ( even unlinked ) markers , as noted previously [12 , 14 , 38] . The smaller sample size of inbred lines does not account for the much higher levels of LD , since comparisons with wild mice and humans of equal sample size show similar differences ( Figure S5 ) . These results indicate that wild mice have the potential to deliver much finer mapping resolution than laboratory populations . The genome-wide set of SNPs assayed in Arizona mice has relatively few pairs at short distances ( 96 pairs less than 100 kb apart ) . To assess short-range LD in more detail , we used resequencing data from four genomic regions . Figure 3 shows the pattern of LD decline over 200 kb in 77 Arizona mice for 163 common SNPs . The decrease in r2 is similar in all four regions , although somewhat less sharp for C3ar1 . The 95th percentile of r2 falls to less than 0 . 4 at 100 kb . Since the mouse genome has , on average , about one gene per 100 kb , these results indicate that the pattern of LD in the Arizona population can provide a mapping resolution on the order of one or a few genes . Figure 3 also compares LD in 60 Arizona mice with 60 unrelated European humans [19] . The human data include 3 , 891 SNPs selected from ten resequenced regions in order to match the allelic frequency distribution in the Arizona mice . These regions are from the Encyclopedia of DNA Elements ( ENCODE ) project . The mean r2 for SNPs within a 0–2 kb distance is somewhat lower in the Arizona mice ( 0 . 38 ) than in European humans ( 0 . 47 ) , but the ranges overlap ( 0 . 29 to 0 . 43 for the four mouse regions and 0 . 30 to 0 . 61 for the ten human regions ) . The pattern of LD decline in these samples is very similar for the two species . This result appears to be somewhat different than the slower decline of LD in mice over longer distances ( Figure 2 ) , which may be due to the small sample of genomic regions resequenced in the Arizona mice , since LD is known to vary considerably among regions in humans [19] . In any case , the differences are fairly small at both long- and short-range distances , suggesting that the resolution of association mapping in Arizona mice would be similar to that in human populations of European and Asian descent . The expected level of LD in a sample at equilibrium under the neutral model depends on the rate of recombination ( c ) , the effective population size ( Ne ) , and the diploid sample size ( n ) : E ( r2 ) = ( 1 / ( 1 + 4Nec ) ) + ( 1 / n ) [39] . The human genome has an average of about 1 . 20 cM/Mb ( based on a genetic map from families of European descent [40] , whereas the mouse has about 0 . 62 cM/Mb ( based on a genetic map from outbred laboratory mouse families [22] ) . This difference in recombination rate may account , at least in part , for the apparently slower rate of decline in LD over long physical distances in the Arizona mice compared with Asian humans ( Figure 2 ) . Figure 4 shows the relationship between LD and genetic distance , in which the latter was calculated from the genome-wide average estimates of cM/Mb . The decline of LD with genetic distance is very similar , except that when the genetic distance is less than 0 . 05 cM , the mean r2 of Arizona mice is less than in Asian humans . Although the sample size for mice in the genome-wide SNP set is small ( 69 pairs between 0 to 0 . 05 cM , compared with 230 pairs in Asian humans ) , the resequencing data in Figure 3 also suggest less LD at this distance . The pattern of LD decline over a short physical distance is very similar for the two species , but the local recombination rates are , on the average , less in the mouse than in humans ( 0 . 77 cM/Mb and 0 . 99 cM/Mb , respectively , in a ∼10 cM window around each region ) . Nevertheless , because LD varies considerably among regions , firm conclusions about a possible difference in short-range versus long-range LD will require data from additional genomic regions in wild mice . Although differences in recombination rate appear to account for much of the difference in LD decline in Arizona mice and non-African humans , expected LD is also dependent on population size . Figure 4 shows the expected decline in LD with genetic distance for Ne values of 1 , 000 , 3 , 000 , and 10 , 000 . The expectation for Ne = 3 , 000 fits the human data very well , but is not consistent with Ne estimates based on nucleotide diversity , which are 8 , 000–10 , 000 [29 , 41] . This observation is well known—i . e . , that LD levels in humans of European and Asian descent suggest a smaller effective population size than that indicated by polymorphism levels [41] . The discrepancy appears to be due to departures from demographic equilibrium , and both types of data are compatible with a range of simple bottleneck models for non-African humans [28] . The discrepancy for Arizona mice is even larger , since polymorphism levels are higher ( ∼0 . 2% versus ∼0 . 1% ) , implying a higher Ne . Wild populations of domesticus , like humans , have experienced large range expansion in the past few thousand generations ( humans out of Africa and domesticus out of the Middle East with agricultural humans [3 , 42] ) and possibly also bottlenecks associated with colonization . Therefore , further work on the comparative population genetics of wild mice and humans may contribute significantly to our understanding of sequence variation and evolution in both species . The results presented here show that the Arizona population of wild mice has a genetic structure that can complement and extend existing methods for identifying quantitative trait genes . It has a high level of genetic variation that captures a large fraction of the polymorphisms ( and presumably also the QTL ) in laboratory mice . It also has a favorable pattern of LD in that strong associations are limited primarily to markers less than 100 kb apart , which provides the possibility of fine-scale association mapping at the level of one or a few genes . Favorable patterns of genetic variation and LD are two basic requirements for useful association studies , but there are also important practical considerations such as obtaining an adequate sample size of interesting phenotypes and a sufficiently high density of SNPs to take advantage of the fine-scale LD . These are serious issues , but potentially tractable . Wild mice can be bred easily in the laboratory and phenotyped under controlled conditions , which should reduce the sample size requirements relative to human association studies . Family-based designs could be used to reduce the need to collect large numbers of mice in the wild . Furthermore , transgenic and knockout mouse technologies provide an immediate functional test within the same species for genes with putative associations , thus reducing the need for large replicate cohorts . In the short term , SNPs for association studies could be discovered in candidate genes by standard methods of resequencing . In the long term , new sequencing technologies may make this process much more efficient and less costly . In recent years , there has been a great deal of investment in whole-genome association studies in humans , and these efforts are coming to fruition [17 , 18 , 43 , 44] . There are two areas in which mouse association studies could complement those in humans . ( 1 ) Recent reports of whole-genome association in humans show a small number of hits that are highly reproducible and a much larger number that are promising , but require validation [18 , 43] . One possibility for validation is transgenic testing in mice , but this process is time consuming and may not be appropriate when homologous genes play different physiological roles in the two species . However , a SNP–trait association for a given gene in both humans and mice would suggest a true positive and also indicate that the trait is sensitive to variation of that gene in both species . Thus , candidate association studies in mice using human whole-genome association hits could provide an indication of whether transgenic testing in mice is likely to provide useful results . ( 2 ) Association studies in wild mice could be used for traits that cannot be measured easily in humans , such as response to carcinogen exposure , adverse effects of drugs at high dosage , susceptibility to disease agents , or gene expression in multiple tissues . Furthermore , the ability to control diet and other environmental exposures allows unbiased detection of genotype–environment interactions . Therefore , despite the growing success of human association studies , wild mouse studies have potential for contributing to our understanding of the genetic basis of complex traits of medical importance .
All aspects of the study were approved by the Institutional Animal Care and Use Committee of the University of Arizona and were performed in accordance with institutional policy and National Institutes of Health guidelines governing the humane treatment of vertebrate animals . Arizona mice were collected with Sherman traps at 94 different sites ( mostly barns and houses ) covering an area of 93 × 60 km in and around Tucson . These sites are spaced at least 100 m apart ( except for one pair at 60 m ) , with a median intersite distance of 13 . 1 km , and only one mouse per site was genotyped . A small sample ( seven to ten animals each ) of each of the three M . musculus subspecies were trapped from more widely dispersed sites in their native ranges: ten M . m . domesticus in Western Europe ( Italy , Greece , and Spain ) , seven M . m . musculus in Eastern Europe ( Slovakia , Poland , and Hungary ) , and nine M . m . castaneus in India ( Katrain , Dehardun , Mandi , and Siliguri ) . Animals were killed and DNA was extracted from liver using PureGene ( Gentra Systems , http://www . qiagen . com ) . Dataset S1 provides sample annotation . A genome-wide set of SNPs was genotyped for the 94 Arizona mice and seven to ten each of the subspecies from their native ranges . The genotyping was performed by Affymetrix using their GeneChip Mouse Mapping 5K SNP Kit ( http://www . affymetrix . com/support/technical/datasheets/mouse_5k_datasheet . pdf ) . This chip includes 5 , 071 assays for SNPs ascertained in laboratory strains of mice , of which 4 , 581 were successful with the wild mouse samples . The dataset for successful assays is 98% complete over all sites and individuals , and is provided in Datasets S2 and S3 . For LD estimates in Figure 2 ( 94 Arizona mice ) , we selected 2 , 974 autosomal SNPs with MAF > 0 . 05 , <10% missing values , and unique genomic location on mouse genome build 36 . These markers are well distributed across the genome , with median , mean , and standard deviation of distance between adjacent markers ( or marker and chromosome terminus ) of 536 , 857 , and 1 , 158 kb , respectively . For LD estimates in Figure S5 , we selected a subset of 54 Arizona mice at random and 2 , 859 SNPs with MAF > 0 . 05 and six or fewer missing values in those individuals . Sequence was obtained from 77 Arizona mice in each of four genomic regions ( a subset of animals genotyped using the Affymetrix chip ) . Each region consists of four segments of 1–2 kb in length , with one segment in a gene of interest and the others at distances of 25 , 100 , and 200 kb away from the gene in one direction . Partially overlapping polymerase chain reaction products ( two to four per segment ) were sequenced using standard Big Dye terminator chemistry and capillary electrophoresis on ABI3730 ( Applied Biosystems , http://www . appliedbiosystems . com ) . Sequence traces were base-called using Phred , assembled into contigs onto the mouse reference sequence , and then scanned for SNPs with Polyphred , version 5 . 01 [45] . Assembled traces and variant sites were visually inspected using Consed [46] to ensure the accuracy of the alignments and variant calls . This dataset is 90% complete over all sites and individuals and is provided in Datasets S4 and S5 . For LD comparison with ENCODE data from 60 humans of European descent , we selected a subset of 60 mice and 141 mouse SNPs with MAF > 0 . 05 and six or fewer missing genotypes for each SNP in those individuals . Two public databases , dbSNP mouse build 126 ( http://www . ncbi . nlm . nih . gov/projects/SNP ) and Perlegen mouse release 3 ( http://mouse . perlegen . com/mouse ) , were searched for mouse SNPs in the genomic regions that were resequenced in the Arizona mice . Overlap between the public and Arizona mouse SNPs was determined by flanking sequence alignment using Cross_Match ( http://www . phrap . org ) . Genotypes were downloaded , and SNPs that occur in classical inbred lines were identified as sites with at least two different genotypes among lines that are not wild derived ( i . e . , not in the list of wild derived lines provided on the Jackson Laboratory Web site; http://jaxmice . jax . org/list/cat481389 . html ) . Genotypic data were analyzed with R statistical software [47] . Exact HW tests were performed with the function “HWE . exact” in the “genetics” package [48] . The within-population inbreeding coefficient , which is the correlation between alleles at one locus within an individual [49] , was calculated using the “diseq” function . LD was estimated as the composite ( genotypic ) r2 , which is the squared correlation of genotypic indicators at two loci in a diploid individual , whereas the usual gametic r2 is the squared correlation of allelic indicators at two loci in a haploid gamete [49] . Since a large fraction of loci show significant deviation from the HW expectation in the Arizona mice , we prefer the genotypic rather than the usual gametic correlation , because its calculation does not require an assumption of random mating . However , to evaluate the potential difference , we used a maximum likelihood method ( implemented in the “LD” function of the R genetics package ) to estimate the gametic correlation . Although random mating is assumed for this estimation , deviations in the direction of excess homozygosity ( as observed in the mice ) are not likely to bias the estimate [50] . Figure S6 shows that there is very little difference between the squared genotypic and gametic correlation estimates in either Arizona mouse or human populations . Nevertheless , we present the assumption-free genotypic measure , which may be more relevant in the context of association studies [49] . Permutations ( n = 1 , 000 ) were used to obtain genome-wide significance thresholds for composite r2 . Genotypes from the genome-wide set of SNPs were used to construct a genetic distance matrix as the mean fraction over loci of the number of shared alleles between each pair of individuals . The loci consist of all SNPs ( 4 , 158 ) that have at least some nonmissing values within each of the four groups of wild-caught mice . This matrix was used to construct a neighbor-joining tree [51] with the “nj” function of the R statistics package “ape” [52] . Structure 2 . 2 ( http://pritch . bsd . uchicago . edu/structure . html ) was used to detect cryptic population structure using the model-based approach of Pritchard et al . [34] . This method assumes LD within subpopulations , so the full set of autosomal markers were thinned to a set of 752 in which no two markers were closer than 2 Mb apart ( the distance at which there is very little LD ) . Two sets of individuals were analyzed: ( 1 ) the full set of 120 mice shown in Figure 1 and ( 2 ) just the 94 Arizona mice . For each set of mice , the admixture model having one , two , three , or four subpopulations was analyzed . For each model and set of mice , three to seven independent runs of the program were made , with burn-in and subsequent steps each numbering 25 , 000 ( or , in some cases , 50 , 000 ) . Degrees of inbreeding and relatedness in the mice in our study were estimated by maximum likelihood using a model that allows for inbreeding but no population structure , as described in Milligan [53] , Hepler [54] , and Weir et al . [55] . This model is based on Jacquard's nine identity coefficients , Δ = Δ1 , … , Δ9 . Maximum likelihood estimates of the nine coefficients were obtained for each pair of individuals in our sample using an expectation–maximization algorithm . The estimated kinship coefficient , θXY for individuals X and Y , was obtained from the estimates of Δ and the relationship . The inbreeding coefficient for individual X ( FX ) was estimated as FX = 2θXX − 1 , where θXX is the kinship coefficient of an individual with itself . The data used for relatedness estimation consist of 3 , 928 autosomal SNPs from the genome-wide set . We performed a simulation study in which the performance of the estimators was evaluated with a set of markers similar to those used in this study . Data were simulated via gene-dropping , with 3 , 928 autosomal markers having allelic frequencies that matched those observed in the Arizona mice . We obtained genetic map positions for 2 , 087 of the 3 , 928 markers directly from a map of 8 , 513 markers [22] , and the remaining positions were estimated by interpolation . Recombination frequencies for pairs of adjacent loci were obtained using Haldane's map function . In the simulations of meioses from parent to offspring , crossovers occurred along each chromosome according to a no-interference model . We simulated individuals and pairs of individuals with a variety of different levels of relatedness and inbreeding . In general , estimated kinship coefficients were within 0 . 063 units of the true values in 95% of all simulated pairs of relatives . Estimated inbreeding coefficients were within 0 . 120 units of the true values in 95% of all simulated individuals . Estimation was more accurate for certain situations: the estimated inbreeding coefficient was below 0 . 031 for 95% of all simulated non-inbred individuals , and the estimated kinship coefficient was below 0 . 015 for 95% of all simulated pairs of non-inbred unrelated individuals . We started with the 60 classical and wild-derived inbred lines of Petkov et al . [38] , which were selected for their genetic diversity and to remove closely related “sibling” strains . Six of these lines were eliminated for lack of sufficient genotypic data ( LT/SvEiJ , CAST/EiJ , MOLD/RkJ , CZECH/EiJ , SKIVE/EiJ , and PWK/PhJ ) . Genotypes for the remaining 54 lines were obtained from the Wellcome-CTC Mouse Strain SNP Genotype Set Web site ( http://www . well . ox . ac . uk/mouse/INBREDS ) . From a total of 12 , 614 SNPs that are polymorphic across the 54 lines , we selected 2 , 855 autosomal SNPs with six or fewer missing values to match the allelic frequency distribution ( within 5% bins ) in a random subset of 54 Arizona mice , while maximizing overlap with the Arizona SNPs . These data are from the HS QTL project [12] , and genotypes were downloaded from their Web site ( http://gscan . well . ox . ac . uk ) . For the LD estimation , we selected either 94 ( Figure 2 ) or 54 ( Figure S5 ) animals at random from a pool of 1 , 940 animals with identifiers beginning with “A0” ( i . e . , not ancestors of other animals in the set ) . These 1 , 940 animals belong to 85 different families . The samples of 94 or 54 animals belong to 33 or 22 families , respectively . We also analyzed a sample of 85 animals , consisting of one randomly chosen individual per family , and the LD results are very similar . For example , at an intermarker distance of 2 Mb , the mean r2 = 0 . 31 and 0 . 26 and the 95th percentile of r2 is 1 . 00 and 0 . 96 for the samples of 85 and 94 , respectively . From a total of 12 , 112 SNPs genotyped in the HS animals , we selected a subset to match the corresponding Arizona set in terms of number and allelic frequency distribution ( within 5% bins ) while maximizing overlap with the Arizona SNPs . All selected SNPs had <10% missing values . To estimate long-distance LD for a set of SNPs comparable to the Arizona mouse data , we analyzed a selected set of genotypic data from the International HapMap Project [19] ( release 21; http://www . hapmap . org ) . Data for three population samples were used: 60 unrelated individuals with European ancestry ( Centre d'Etude du Polymorphisme Humain samples of Utah residents with ancestry from northern and western Europe [CEU] ) , 45 Japanese from Tokyo , Japan , and 45 Han Chinese from Beijing , China . The two Asian samples were combined for allelic frequency and LD estimation . A SNP set was selected separately for each human group ( Asian and European ) to match the Arizona mouse set in terms of number , allelic frequency distribution ( within 5% bins ) , and chromosomal distribution ( 20 linkage groups , excluding human Chromosomes 20–22 ) , but otherwise at random . The two Asian samples were combined for LD estimation by first calculating the genotypic correlations for the Japanese and Chinese samples separately , testing for homogeneity , and then averaging the two correlations using Fisher's z-transformation . The two sets of correlations are very homogenous , since 1 . 1% of the homogeneity tests are significant at the nominal level of 1% . For comparison to the sets of 54 mouse samples , 54 of the 60 CEU samples were chosen at random . For comparison to LD in SNPs discovered by resequencing Arizona mice , we selected SNPs discovered by resequencing a panel of 16 CEU individuals in 10 ENCODE regions and subsequently genotyped on 90 CEU individuals [19] . For the 60 unrelated CEU individuals , we selected a set of 3 , 891 SNPs with MAF > 0 . 05 , six or fewer missing values , and an allelic frequency distribution matching the 141 SNPs selected for a set of 60 Arizona mice . Genotypes were obtained from the HapMap Web site .
The GenBank ( http://www . ncbi . nlm . nih . gov/Genbank ) accession numbers for the regions resequenced in this study are EU007907 for Alox15 , EU007908 for Apoa2 , EU007909 for C3ar1 , and EU007910 for Nr1h3 . | Linkage disequilibrium ( LD ) refers to the nonrandom association of variants at different sites in the genome . In recent years , LD has been of great interest in biomedical research because of its utility in “association studies , ” where DNA sequence variants associated with disease traits are used to identify susceptibility genes . The resolution of this gene-finding tool depends on how the LD decays with distance between the associated sites . The pattern of LD decay is well known in human populations , where it provides high resolution on the order of one or a few genes . This paper shows that the pattern of LD in wild house mice ( in contrast to laboratory mice ) is very similar to that in human populations . This result means that wild mice ( reared in the laboratory ) could be used in association studies to identify genes that cause trait variation . Wild mouse association studies might complement those in humans by dealing with traits that are difficult to measure in humans ( such as response to carcinogen exposure ) and by filtering human associations for subsequent validation with genetically engineered mouse models . | [
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Spontaneous preterm birth ( SPTB ) is the leading cause of neonatal death and morbidity worldwide . Both maternal and fetal genetic factors likely contribute to SPTB . We performed a genome-wide association study ( GWAS ) on a population of Finnish origin that included 247 infants with SPTB ( gestational age [GA] < 36 weeks ) and 419 term controls ( GA 38–41 weeks ) . The strongest signal came within the gene encoding slit guidance ligand 2 ( SLIT2; rs116461311 , minor allele frequency 0 . 05 , p = 1 . 6×10−6 ) . Pathway analysis revealed the top-ranking pathway was axon guidance , which includes SLIT2 . In 172 very preterm-born infants ( GA <32 weeks ) , rs116461311 was clearly overrepresented ( odds ratio 4 . 06 , p = 1 . 55×10−7 ) . SLIT2 variants were associated with SPTB in another European population that comprised 260 very preterm infants and 9 , 630 controls . To gain functional insight , we used immunohistochemistry to visualize SLIT2 and its receptor ROBO1 in placentas from spontaneous preterm and term births . Both SLIT2 and ROBO1 were located in villous and decidual trophoblasts of embryonic origin . Based on qRT-PCR , the mRNA levels of SLIT2 and ROBO1 were higher in the basal plate of SPTB placentas compared to those from term or elective preterm deliveries . In addition , in spontaneous term and preterm births , placental SLIT2 expression was correlated with variations in fetal growth . Knockdown of ROBO1 in trophoblast-derived HTR8/SVneo cells by siRNA indicated that it regulate expression of several pregnancy-specific beta-1-glycoprotein ( PSG ) genes and genes involved in inflammation . Our results show that the fetal SLIT2 variant and both SLIT2 and ROBO1 expression in placenta and trophoblast cells may be correlated with susceptibility to SPTB . SLIT2-ROBO1 signaling was linked with regulation of genes involved in inflammation , PSG genes , decidualization and fetal growth . We propose that this receptor-ligand couple is a component of the signaling network that promotes SPTB .
Preterm live births that take place before 37 completed weeks of gestation and even as early as 22–24 weeks are a global problem . Up to 11 . 1% ( 15 million babies ) of all births worldwide occur prematurely , and approximately 45–50% of them are idiopathic or spontaneous [1–3] . Complications caused by preterm birth are the most common cause of neonatal deaths and the largest direct cause of deaths of children <5 years of age [1 , 3] . The research focusing on spontaneous preterm birth ( SPTB ) has been complicated by etiological , pathophysiological , and genetic heterogeneities . Multiple events are associated with SPTB , either independently or in concert [4] . These include intrauterine inflammation , called chorioamnionitis , preterm premature rupture of fetal membranes ( PPROM ) and abnormal fetal growth relative to uterine size [5 , 6] . It is important to find new biomarkers for early detection of SPTB . Currently , our understanding of the early molecular pathways leading to SPTB is incomplete and there are no effective means to prevent SPTB . Knowledge of how maternal and fetal genomes contribute to the risk of SPTB could provide more personalized tools to prevent it [7] . Epidemiological studies have shown that both fetal and maternal genes affect fetal growth , birth weight , birth length , head circumference , and gestational age ( GA ) [8–11] . A recent study indicated that variants of the fetal and maternal genome independently affect normal variations in birth weight [12] . In addition , maternal and fetal genomes are also considered to affect the susceptibility to preterm birth and duration of pregnancy in general [13–15] . The intrauterine environment influences fetal growth , and adverse intrauterine events affect pregnancy length not only in elective preterm pregnancies but also in SPTB [11] . Genetic analysis of 244 , 000 Swedish births resulting in twins , full siblings , and half-siblings revealed that 13% and 21% of the variation in birth timing is explained by fetal and maternal genetic factors , respectively [9] . Overall , preterm birth is a phenotype with contributions from both , maternal and fetal genomes that may have separate contributions and together with environmental factors , interactively determine the outcome [7 , 13 , 16] . A recent study that included a population of > 40 , 000 women and replication cohorts of > 8000 women identified several common variants in EBF1 , EEFSEC , and AGTR2 that showed associations with preterm birth at a genome-wide significance level [13] . In addition , other genome-wide association studies ( GWAS ) and SPTB genetic studies focused on mother [17–19] or infant [19–21] genomic signals have discovered genetic loci associated with preterm birth and gestational length . Studies that focused on fetal genomes have not revealed replicable associations between fetal genetic factors and SPTB . Many pathways and cellular processes are reported to be associated with SPTB , including response to infection , regulation of inflammation , stress , and other immunologically mediated processes [3] . According to our current understanding , inflammatory pathways also have roles in the initiation of spontaneous term birth , as normal labor starts when there is a shift in signaling between anti-inflammatory and proinflammatory pathways in the myometrium . This shift appears to involve many chemokines such as interleukin 8 ( IL8 ) , cytokines such as IL1 and IL6 , and contraction-associated proteins such as oxytocin receptor ( OXTR ) , connexin 43 ( CX43 ) , and prostaglandin receptors [22] . Therefore , it is likely that changes in inflammation-associated pathways also contribute to preterm birth . Evidence from candidate gene studies supports the role of inflammation-related factors in SPTB . For example , polymorphisms of the genes encoding TLR4 , TNF , IL1B , interferon gamma ( IFNγ ) , IL6 , and matrix metalloproteinases may be associated with increased risk of SPTB [5] . The aim of the present study was to use a GWAS to investigate fetal genetic variants that may predispose infants to SPTB in a homogeneous population of Finnish origin . A variant of slit guidance ligand 2 ( SLIT2 ) had the most suggestive association with SPTB in the GWAS and in a genetic pathway analysis . Therefore , we characterized SPTB-associated expression of SLIT2 and its receptor ROBO1 in the placenta and subsequently conducted experiments with relevant placenta-associated cells .
In order to find fetal genetic factors associated with predisposition to SPTB , we analyzed polymorphisms encompassing the entire genome for associations with SPTB . After quality control , 247 infants born spontaneously preterm and 419 infants born at term remained for inclusion in the GWAS . We performed the analysis for both GA ( quantitative trait ) and SPTB ( dichotomous setting ) . However , due to sample collection bias resulting in skewed GA distribution , we acknowledge that the results of the quantitative trait analysis should be interpreted with caution . Fig 1 summarizes the study workflow . We detected several suggestive associations ( p < 10−5 ) in the GWAS ( Fig 2 , Table 1 ) . The two most promising regions were within the genes encoding SLIT2 ( rs116461311 , p = 1 . 6 × 10−6 ) and succinyl-CoA:glutarate-CoA transferase ( SUGCT; rs57670997 , p = 1 . 8 × 10−6 ) . We also detected suggestive associations for GA as a quantitative trait ( S2 Table , S1 Fig ) . SNP rs116461311 within the SLIT2 gene showed the most significant signal for GA ( p = 3 . 1 × 10−7 , S1 Fig ) . In addition to SLIT2 , four regions showed suggestive signals both in the primary setting and in the GWAS of GA; these signals were within SUGCT , an intergenic region in chromosome 6 ( nearest loci LOC105377949 and LOC107986634 ) , and within the genes encoding anaplastic lymphoma receptor tyrosine kinase ( ALK ) and DLC1 Rho GTPase activating protein ( DLC1 ) . We further analyzed very preterm and moderate-to-late preterm SPTB infants separately against term-born controls ( S3 and S4 Tables ) . Three regions showed suggestive signals ( p < 10−5 ) both in the primary setting and in the analysis of very preterm birth ( S3 Table ) . These signals were within SLIT2 , in an intergenic region on chromosome 2 ( nearest genes THUMPD2 and SLC8A1 ) , and within the region encompassing the EXOSC1 , ZDHHC16 , MMS19 , and UBTD1 genes , which encode exosome component 1; zinc finger DHHC-type containing 16; MS19 homolog , cytosolic iron-sulfur assembly component; and ubiquitin domain containing 1 , respectively . The minor allele of SLIT2 , SNP rs116461311 , was overrepresented ( OR 4 . 06 , p = 1 . 55 × 10−7 ) in very preterm-born infants ( GA < 32 weeks ) compared to term-born infants . In moderate-to-late preterm infants ( GA 32–36 weeks ) , two regions showed suggestive signals ( S4 Table ) that were also evident in the primary analysis: an intergenic region on chromosome 3 ( nearest loci LOC105377173 and ROBO1 ) and within ADAMTS14 , which encodes ADAM metallopeptidase with thrombospondin type 1 motif 14 . We also studied associations with SPTB within the contexts of PPROM and no PPROM . There were separate suggestive associations with SPTB-PPROM and with SPTB without PPROM ( S5 and S6 Tables ) . For the SLIT2 region , the effects were similar for infants born after PPROM ( rs116461311 , OR = 3 . 5 , p = 3 . 0 × 10−5 ) and for those born after spontaneous onset of labor with intact fetal membranes ( rs116461311 , OR = 3 . 6 , p = 1 . 3 × 10−5 ) . To investigate potential maternal transmission of the minor allele of SPTB-associated rs116461311 ( in SLIT2 ) , we checked the MAF of the variant in maternal samples . The frequency of C-rs116461311 was 0 . 059 in SPTB mothers ( n = 230 ) and 0 . 035 in mothers with term delivery ( n = 378 ) . Transmission analysis was not feasible because of the low minor allele counts . SNPs with suggestive association signals in the region of the top GWAS gene ( SLIT2 ) were examined for association with SPTB in a European population ( n = 9890 ) [20] . In a European replication population of very preterm and term-born controls , rs12503652 and rs79034379 , which correlate with the best GWAS SNP of the SLIT2 region ( rs116461311 ) , were associated with SPTB ( Table 2 ) . The two SNPs were in high LD with one another ( r2 = 0 . 85 , D′ = 0 . 95 ) in the Finnish individuals in 1000 Genomes phase3 data . To investigate if the SNPs within regions with the most promising signals in the GWAS ( p < 10−5 ) have functional consequences , we screened the GTEx data to examine whether any of the suggestively associated SNPs colocalize with cis eQTLs; that is , whether they correlate with mRNA levels in the analyzed tissues . In the GTEx data , 26 of the SNPs with p < 10−5 for association with SPTB overlapped with significant eQTLs ( Table 3 ) . These SNPs were located within five different regions; the majority were in the region encompassing EXOSC1 , ZDHHC16 , MMS19 , and UBTD1 ( Tables 1 , S3 and S5 ) . These SNPs correlated with mRNA levels of the following genes in different tissues: ZDHHC16 , MMS19 , FRAT1 , ANKRD2 , UBTD1 , and RRP12 . Associated SNPs within the top GWAS region , SLIT2 , were not associated with mRNA levels . According to the GWAS catalog , none of the suggestively associated SNPs had been significantly associated with any phenotype . We further functionally annotated the SNPs ( p < 10−4 ) within the SLIT2 region with HaploReg , v 4 . 1 . Some of the most promising SNPs within SLIT2 ( including the best associating variant rs116461311 , as well as rs60126904 , rs115707845 , and rs16869667 ) were located within regions that contain histone marks and DNase-hypersensitive sites in several tissues . Furthermore , SLIT2 SNPs ( rs60126904 and rs115707845 ) mapped to predicted enhancers in several cell types and tissues , including neuronal cells , different cells in the brain , lung , spleen , adipose cells , colon and duodenum smooth muscle cells , fetal lung and kidney , and fetal membranes ( amnion ) . Thus , there is some evidence of the putative regulatory effects of SLIT2 SNPs in several tissues , including fetal tissues such as placenta . To identify biological pathways associated with SPTB , we performed pathway analysis of the GWAS data to search for gene set enrichment . SPTB was associated with 16 Kyoto Encyclopedia of Genes and Genomes ( KEGG ) pathways [corrected ( S7 Table ) and FDR adjusted p < 0 . 05 , Table 4] . The most significant pathways were axon guidance ( p = 8 . 6 × 10−10 ) , focal adhesion ( p = 6 . 6 × 10−7 ) , and vascular smooth muscle contraction ( p = 1 . 4 × 10−6 ) . Axon guidance , the most significant pathway , included SLIT2 and the gene encoding its receptor , ROBO1 . A Gene Ontology ( GO ) search revealed 35 GO terms associated with SPTB , with a false-discovery rate ( FDR ) of <0 . 05 ( S8 Table ) . GO sets that included SLIT2 and ROBO1 are listed in S9 Table . The three most significant GO sets that included SLIT2 were retinal ganglion cell axon guidance , telencephalon development , and negative chemotaxis . The three most significant GO sets that included ROBO1 were telencephalon development , neuron recognition , and negative chemotaxis . These results led us to a more-detailed investigation of the roles of SLIT2 and ROBO1 in SPTB . We detected suggestive association signals for SNPs in a region that encompasses SLIT2 and in a region downstream of ROBO1 . Protein Slit2 binds to Robo proteins specifically and with high affinity [23 , 24] . Therefore , we analyzed the localization of SLIT2 and its receptor ROBO1 in human placenta by immunohistochemical staining of placentas from SPTB and spontaneous term birth ( STB ) with anti‐human SLIT2 and ROBO1 antibodies ( Fig 3 ) . Both SLIT2 and ROBO1 localized to cytotrophoblasts , syncytiotrophoblasts , and decidual trophoblasts . In addition , we observed strong ROBO1 and faint SLIT2 staining in capillary endothelial cells . We also detected both proteins in the basal and chorionic plates of the placenta . We did not see apparent differences in staining intensities or cellular localization between placentas from SPTB and STB . This indicates that SLIT2 and ROBO1 are expressed in the placenta at the interface between mother and fetus during pregnancy . Immunohistochemistry demonstrated SLIT2 and ROBO1 in different types of trophoblasts in human placenta ( Fig 3 ) . To obtain more quantitative data about placental expression of these proteins , we analyzed SLIT2 and ROBO1 mRNA levels by qRT-PCR in samples collected from the basal and chorionic plates of placentas from SPTB ( n = 23 ) , STB ( n = 23 ) , and elective preterm birth ( EPTB ) ( n = 34 ) . We first compared SLIT2 and ROBO1 expression levels between SPTB ( n = 23 ) and STB ( n = 23 ) placentas ( Fig 4 ) . Both SLIT2 and ROBO1 mRNA levels were higher in the basal plate of SPTB placentas ( SLIT2 fold change [FC] = 1 . 679 , SD = 0 . 667; ROBO1 FC = 1 . 387 , SD = 0 . 670 ) compared to those of STB ( SLIT2 p = 0 . 004 , ROBO1 p = 0 . 013; Fig 4A ) . There were no differences in mRNA levels of SLIT2 ( p = 0 . 173 ) and ROBO1 ( p = 0 . 297 ) between the chorionic plates of SPTB and STB placentas ( Fig 4B ) . To explore the effects of mode of delivery and GA on SLIT2 and ROBO1 mRNA levels , we compared SPTB with EPTB placentas . SLIT2 and ROBO1 mRNA levels were significantly higher for SPTB ( SLIT2 FC = 1 . 595 , SD = 0 . 580; ROBO1 FC = 1 . 282 , SD = 0 . 577 ) compared to EPTB ( SLIT2 p = 0 . 005 , ROBO1 p = 0 . 031 ) in basal plate samples ( Fig 4A ) . There were no significant differences in these levels in EPTB and STB placentas ( SLIT2 p = 0 . 216 , ROBO1 p = 0 . 328; Fig 4A ) . These results suggest that higher SLIT2 and ROBO1 expression levels are associated with SPTB . SLIT/ROBO are involved in many processes that involve cell migration , including axon guidance; thus , they could affect trophoblast cell invasion and decidualization . To this end , we looked at whether SLIT2 or ROBO1 expression in the basal plate of the placenta is associated with fetal growth . We compared mRNA levels with birth weight-for-GA Z-scores ( weight Z-score ) , which included age and gender standardization of the infants . Deliveries with intrauterine growth restriction or other growth disorders were excluded . SLIT2 mRNA levels correlated with Z-scores ( p = 0 . 023 , rs = 0 . 351 ) in term and preterm fetuses delivered after spontaneous onset of labor ( SPTB and STB samples together , S3 Fig ) . This suggests that SLIT2 expression is associated with variations in fetal growth . To investigate potential functions of SLIT2 and ROBO1 in placental cells , we silenced SLIT2 and ROBO1 expression separately in the HTR‐8/SVneo human trophoblast cell line with small interfering RNAs ( siRNAs ) ( Fig 5 ) . qRT-PCR revealed that silencing percentages were 60% and 85% , for SLIT2 and ROBO1 , respectively . Corresponding percentages revealed by RNA sequencing were 75% and 74% for SLIT2 and ROBO1 , respectively . Next , we characterized the transcriptomes of trophoblasts in which SLIT2 or ROBO1 was silenced , as well as of cells treated with siRNA Universal Negative Control #1 . Transcriptomic data analysis identified 14 upregulated ( S10 Table ) and 12 downregulated ( S11 Table ) genes after SLIT2 knockdown compared to samples treated with siRNA Universal Negative Control . The threshold was an FDR-adjusted p value of ≤0 . 01 and an FC of ≥2 . 0 . By the same criteria , there were 216 upregulated ( S12 Table ) and 610 downregulated ( S13 Table ) genes after ROBO1 knockdown . KEGG pathway database analyses ( S14 Table , S15 Table ) identified the top pathways affected after SLIT2 and ROBO1 knockdown as inflammation-related pathways such as cytokine-cytokine receptor interaction ( KEGG . ID 4060 ) . Far fewer genes were affected by SLIT2 knockdown than by ROBO1 knockdown , probably because transfection reagent alone upregulated SLIT2 mRNA levels up to 4-fold ( p = 0 . 002 ) compared to untreated cells . Therefore , knockdown of SLIT2 expression brought SLIT2 mRNA levels close to the levels of intact cells . Transfection reagent by itself seemed to activate inflammation-related pathways . The ROBO1 expression level was not affected by transfection reagent . ROBO1 knockdown particularly affected genes encoding membrane receptors and other membrane proteins . KEGG pathway analysis revealed that hematopoietic cell lineage ( KEGG ID 4640 ) had the lowest p value ( 6 . 57 × 10−8 ) ( S15 Table ) . ROBO1 knockdown affected 14 of the 42 genes in this pathway: KIT , IL7R , IL1R1 , HLA-DRB1 , IL1A , ITGB3 , TFRC , ANPEP , IL1B , CD22 , CD24 , KITLG , CSF3 , and CD14 . SLIT2 ( FC = 2 . 0 , p = 0 . 005 ) was among the genes upregulated after ROBO1 knockdown ( S12 Table ) . One of the gene families highly affected by ROBO1 knockdown was pregnancy-specific glycoproteins ( PSG ) , a complex gene family that regulates maternal–fetal interactions [25] . Of the ten protein-coding human PSG genes , six were upregulated after ROBO1 knockdown . These data indicate that ROBO1 is an important regulator of the HTR8/SVneo cell transcriptome and suggest a role for ROBO1 in modulation of PSG gene expression . In addition , ROBO1 appears to have immunomodulatory functions in trophoblast-derived cells . To verify our suggestive findings from the RNA sequencing data , we used qRT-PCR to analyze the effect of ROBO1 knockdown on expression levels of selected genes from a larger number of specimens . Because many inflammation‐related pathways were involved , we investigated TGFA , CXCL6 , and total PSG expression levels ( Table 5 ) . TGFA was downregulated after ROBO1 knockdown , while CXCL6 was downregulated by both ROBO1 and SLIT2 knockdown . Select members of the PSG family were upregulated when ROBO1 was silenced ( Table 5 ) : PSG1 , PSG2 , PSG4 , PSG6 , PSG7 , and PSG9 . To verify , we measured total mRNA expression of different PSGs ( PSG1 , PSG2 , PSG3 , PSG4 , PSG5 , PSG6 , PSG7 , PSG8 , PSG9 , and PSG11 ) at the same time in one qRT-PCR reaction , as described previously [26] . We also tested the effect of knockdown on IL6 , TNFA , and SRGAP3 ( Table 5 ) . The results of qRT-PCR were generally in line with those of transcriptome sequencing ( Table 5 ) . Knockdown of ROBO1 downregulated mRNA expression of TGFA ( S4A Fig ) . Knockdown of either ROBO1 or SLIT2 downregulated CXCL6 , whereas PSGs were upregulated by ROBO1 knockdown , similar to the results of RNA sequencing . Inflammatory cytokines IL6 and TNFA were both downregulated after ROBO1 knockdown ( S4B Fig ) . IL6 was also downregulated after SLIT2 knockdown . There was a trend toward downregulation of SRGAP3 by ROBO1 knockdown . Thus , the RNA sequencing and qRT-PCR results are in accordance and confirm that ROBO1 knockdown affects the expression of immune response–modifying genes in a cell culture model .
Both maternal and fetal genetic factors contribute to SPTB . Nevertheless , variants in the fetal genome associated with SPTB predisposition are not well known . Our aim was to identify fetal genetic factors associated with SPTB . To this end , we performed a case–control GWAS study in a Finnish population that is known to be relatively genetically homogeneous . Based on these results , we identified a SLIT2 variant as a plausible factor for SPTB susceptibility . This led to further investigations to define high-risk populations and characterize SLIT2 and ROBO1 expression in the placenta and in trophoblast cells . The association of the SLIT2 variant with SPTB was strongest in the population of very premature births ( <32 weeks gestation ) , and this association was replicated in a European population with SPTB fetuses from 24 to 30 weeks gestation . We detected association signals for SNPs in a region that encompassed SLIT2 and for SNPs in a region downstream of ROBO1 , which encodes the receptor for SLIT2 . SLIT2 and ROBO1 encode proteins of the SLT2-ROBO1 signaling pathway; previous studies have indicated that this pathway is associated with different types of pregnancy complications , including preeclampsia [27 , 28] , impaired placentation of missed and threatened miscarriage in early pregnancy [29] , trophoblast invasion , and vascular remodeling during ectopic tubal pregnancy [29 , 30] . Our hypothesis-free GWAS study provides evidence that these genes have a role in another pregnancy complication , SPTB . We did not detect associations that would reach the stringent level of genome-wide significance ( p<10−8 ) . This may be due to a relatively small sample size in the GWAS , which was one of the limitations in the study . However , we did identify signals below the generally used threshold of suggestive association ( p <10−5 ) . Moreover , the SPTB-associated SNPs in the SLIT2 locus showed association in an independent data set . In the future , there is a need to validate our findings in larger data sets to detect signals that may have gone undetected in the current sample size . Previous study presented that fetal de novo mutations in genes that are involved in brain development are associated with preterm birth [31] . In line with this notion , SLIT2-ROBO1 signaling has a well-documented role in axon guidance during the development of the nervous system [32] . Therefore , it appears that at least in part the same fetal genetic factors are involved both in the onset of preterm birth and in brain development . It is known that preterm birth increases the risk of compromised brain development [33 , 34] . How much of the risk can be explained by shared genetic risk factors remains to be determined . KEGG pathway analysis of GWAS data showed that the top-ranking pathway was SLIT2/ROBO1 signaling–regulated axon guidance . Previous studies have indicated that brain and placental development may share common pathways [35–37] . Although SLIT and ROBO were originally identified as axon guidance cues , they interact in many other cellular processes , including regulation of cell migration , cell death , and angiogenesis . As such , they have an essential role in the development of tissues such as lung , liver , kidney , breast , and tissues of the reproductive system [38 , 39] . Trophoblasts cover a large portion of the placenta and have multiple roles in the maintenance of pregnancy . Invading trophoblasts have a critical function in biogenesis of the placenta [40 , 41] . Later during pregnancy , decidual trophoblasts may have a role in silencing immune cells in the decidua . The lining of placental villae consists of the syncytiotrophoblast layer and cytotrophoblasts , which have roles ranging from immune protection to uptake of nutrients from maternal blood [42] . In addition to their functions in biogenesis of the placenta and maintenance of pregnancy , trophoblasts may participate in labor induction [43] . Two‐thirds of early pregnancy failures may present with reduced trophoblast invasion [29] . SLIT-ROBO signaling may play autocrine and/or paracrine roles in trophoblast functions , such as differentiation and invasion , by influencing the migration of trophoblastic cells [29 , 44] . Thus , SLIT2-ROBO1 signaling may be involved in the pathogenesis of pregnancy failures via their effect on trophoblastic cell functions . Indeed , our immunohistochemical experiments demonstrated that villous and decidual trophoblasts from preterm and term placentas were strongly positive for SLIT2 and ROBO1 . These results are in line with those of a previous study , which demonstrated that villous syncytiotrophoblasts express high levels of SLIT2 and ROBO1 . The study also found that trophoblastic endothelial cells highly coexpress multiple SLIT ligands ( SLIT2 , SLIT3 ) and ROBO receptors ( ROBO1 , ROBO2 , and ROBO4 ) in full-term placenta . Thus , SLIT-ROBO signaling may also have an important role in the regulation of normal placental functions [27] . An earlier study found that levels of several SLIT/ROBO mRNAs and proteins are higher in preeclamptic placentas compared to normal controls [27] . Our data indicate that mean SLIT2 and ROBO1 mRNA levels were higher in SPTB placentas compared to placentas from spontaneous term deliveries and to placentas from elective preterm births . Consequently , increased levels of SLIT2 and ROBO1 mRNAs were associated with SPTB . In addition , SLIT2 may have a role in term spontaneous labor , as SLIT2 mRNA and protein expression are decreased in the myometrium after spontaneous term labor [45] . In addition to the associations of both the SLIT2 variant and mRNA expression of SLIT2 and ROBO1 in basal plate of placenta with SPTB , SLIT2 mRNA levels in placentas were associated with the birth weight of fetuses born after spontaneous labor . A GWAS of beef cattle identified SLIT2 as a candidate gene that affects the weight of internal organs [46] . As the fetal growth and intrauterine distention negatively associates the duration of pregnancy [47] influence of SLIT2 on fetal size is a potential mechanism that remains to be studied as a cause of SPTB . To understand more about the function of SLIT2 and ROBO1 in trophoblast cells , we silenced their expression separately in immortalized extravillous invading trophoblasts . Altogether , 26 and 826 genes were affected by SLIT2 or ROBO1 siRNA knockdown , respectively . The low number of genes affected by SLIT2 knockdown was probably because the transfection reagent alone upregulated SLIT2 mRNA levels compared to untreated cells . Consequently , knockdown of SLIT2 expression only brought SLIT2 mRNA levels back to the levels of control cells . However , the mRNA expression level of ROBO1 was not affected by the transfection reagent . Genes affected by ROBO1 knockdown were mostly related to infection , inflammation , and immune response . These results correspond with those of previous studies , suggested that members of the SLIT and ROBO families act as regulators of the inflammatory response [45 , 48] . Both pro‐inflammatory [45 , 49 , 50] and anti‐inflammatory [48 , 51] functions have been reported . Our results from invading trophoblast cells support a proinflammatory role for SLIT2-ROBO1 signaling , since the genes downregulated by ROBO1 knockdown included proinflammatory cytokines and chemokines such as IL1A , IL1B , CXCL8 , CCL2 , and CXCL6 . It is widely acknowledged that IL1 in particular , as well as other proinflammatory cytokines and chemokines , is associated with preterm labor [52–54] . IL1B is a primary secretory product of the inflammasome and as such is thought to have central roles in initiation of preterm labor , such as in the induction of prostaglandin synthesis . Both polymorphisms of IL1A and IL1B , as well as increased levels of IL1B , are associated with preterm birth [19 , 54–56] . CXCL6 is increased in amniotic fluid from patients with preterm labor complicated by intra-amniotic inflammation and from patients with SPTB without intra-amniotic infection/inflammation [57] . We propose that in trophoblast cells ROBO1 has a role in regulation of proinflammatory mediators . Genes involved in vascular formation ( vasculogenesis ) or development ( angiogenesis ) were not affected by SLIT2 or ROBO1 knockdown in trophoblasts . The PSG family was one of the immune response–associated gene families affected by ROBO1 knockdown . PSGs include ten placental trophoblast–synthetized glycoproteins that belong to the immunoglobulin superfamily [58] . Of the six PSGs upregulated by siRNA-induced knockdown , PSG1 was ranked among the top three upregulated genes ( S12 Table ) . PSGs are essential in the maintenance of normal pregnancy [58]; thus , altered PSG expression patterns could influence pregnancy complications . Over the years , complications such as abortion , preeclampsia , intrauterine growth retardation , fetal distress , and preterm delivery have all been linked to low PSG levels [58–63] . As ROBO1 was upregulated in SPTB placentas and knockdown of ROBO1 upregulated expression of PSG genes , we propose that ROBO1 signaling is important in downregulation of the expression of PSGs . In addition , PSG1 activates TGF-B 1 and TGFB2 [25 , 64 , 65]; TGFB1 suggestively associated with SPTB [13] and TGFB2 prevented preterm birth in experimental inflammatory stress [66] . The innate immune response and inflammation contribute to labor and delivery , particularly in preterm pregnancies [3 , 22 , 67 , 68] . Upregulation of proinflammatory cytokines stimulates and potentiates uterine contractions in the myometrium [69–71] . In preterm labor and delivery , it is mostly inflammatory signals that spread to the placenta , fetal membranes , and fetal compartment . It is plausible that SLIT2 and ROBO1 expressed by trophoblasts are associated with SPTB via regulation of inflammation-related factors . SLIT2-ROBO1–guided activation and propagation of inflammatory mediators throughout the fetal–maternal trophoblast interface of the uterine wall would likely influence the tissues actively involved in labor and delivery . As knockdown of ROBO1 downregulated many of the genes that encode cytokines and chemokines , it is probable that upregulation of ROBO1 in SPTB placentas compared to term placentas would also affect expression of these genes . There is both epidemiological and experimental evidence that untimely expression of cytokines and chemokines by either fetal or maternal tissues upregulates the activity of mediators , which leads to premature initiation of the parturition process [72] . In conclusion , the GWAS detected fetal association signals for SPTB and duration of pregnancy in the vicinity of SLIT2 and ROBO1 . SLIT2 and ROBO1 were upregulated in SPTB placentas , and further functional studies confirmed that this signaling pathway has a role in regulation of the pathways associated with infection , inflammation , and immune response in trophoblast-derived cells . These results suggest that SLIT2 and ROBO1 play specific roles in increasing susceptibility to SPTB . SLIT2-ROBO1 signaling is associated with complications in early pregnancy and it is possible that it influences invading trophoblasts during placentation . Based on the currently available evidence , we propose that activation of SLIT2-ROBO1 expression and signaling in trophoblast cells contributes to inflammatory and immune activation , which in turn leads to early labor and preterm birth .
The present studies received ethical approval from the participating centers ( Oulu University Hospital 79/2003 , 14/2010 , and 73/2013 ) . Informed consent was obtained from study participants or their parents . Characteristics of the Finnish study populations are summarized in S1 Table . The discovery GWAS study population consisted of singleton SPTB and term infants sampled in Oulu and Tampere University Hospitals . The study subjects were recruited prospectively during 2004–2014 and retrospectively from the 1973–2003 birth diaries of Oulu University Hospital . For replication , we downloaded the summary statistics of a European population described in a recent study by Rappoport et al . [20] through ImmPort ( http://www . immport . org/: SDY1205 , DOI: 10 . 21430/M37N6PJEQT ) . This population includes 260 SPTB cases ( 139 male and 121 female infants ) and 9 , 630 controls ( 4 , 055 males and 5 , 575 females ) . The cases were very preterm infants born between 25 and 30 weeks of gestation and were clinically defined as SPTB in 2005–2008 . The control population consisted of adults , originally from the Health and Retirement Study ( HRS ) [73] , who were matched for ethnicity with the European cases . In the Finnish cohorts , SPTB was defined as birth occurring after spontaneous onset of labor at <36 completed weeks + 1 day of gestation . All medically indicated preterm births and deliveries that included known major risk factors were excluded . These criteria led to exclusion of preterm deliveries that involved the following conditions or characteristics: multiple gestation , preeclampsia , intrauterine growth restriction , placental abruption , polyhydramnios , fetuses with anomalies , clinical chorioamnionitis or acute septic infection in the mother , diseases in the mother that could influence timing of delivery , alcohol/narcotic use , and accidents . Term birth was defined as birth occurring at 38–41 weeks ( 38 wk + 0 d to 41 wk + 6 d ) of gestation . The following conditions were used as exclusion criteria for the control population: multiple gestation , intrauterine growth restriction , placental abruption , polyhydramnios , fetuses with anomalies , and requirements for special care of the newborn . All control infants were from families with at least two term deliveries without any preterm deliveries in the family . Umbilical cord blood , umbilical cord tissue , or saliva was obtained from the study subjects . Commercial kits were used to extract genomic DNA from blood ( UltraClean Blood DNA Isolation Kit; MO BIO Laboratories , Inc . , Carlsbad , CA , USA or Puregene Blood Core Kit; Qiagen , Hilden , Germany ) and cord tissue ( Gentra Puregene Tissue Kit , Qiagen ) . OraGene DNA collection kits ( DNA Genotek , Ontario , Canada ) were used for collecting saliva , and DNA was extracted with the prepIT-L2P kit ( DNA Genotek ) . Genome-wide SNP genotyping was performed with the Infinium HumanCoreExome BeadChip ( Illumina , San Diego , CA , USA ) by the Technology Centre , Institute for Molecular Medicine Finland ( FIMM ) , University of Helsinki . Genome-wide SNP data were processed with PLINK , v . 1 . 9 [74] . SNPs with minor allele frequency ( MAF ) < 0 . 01 , genotyping rate < 0 . 9 , or deviation from Hardy–Weinberg equilibrium ( p < 0 . 0001 ) were excluded . Individuals with > 0 . 1 missing genotypes were excluded . Identical by descent ( IBD ) clustering and multidimensional scaling ( MDS ) analyses were performed with a linkage disequilibrium–pruned SNP set; population outliers and close relatives ( pihat > 0 . 2 ) were excluded . Prephasing of genotypes was performed with SHAPEIT2 [75] , followed by statistical imputation with IMPUTE2 [76] using the 1000 Genomes Phase 3 variant set ( October 2014 ) as the reference panel . Before association analysis , SNPs with impute info score < 0 . 8 or MAF < 0 . 05 in cases or controls were excluded . Altogether 6 , 778 , 521 SNPs or short insertions/deletions remained for analysis after these quality control steps . Associations between SPTB or GA and SNPs were assessed with the frequentist test under the additive model with SNPtest , v . 2 . 5 . 2 [77] . After the primary analysis , the following subgroups of SPTB infants were assessed: ( 1 ) very preterm infants ( GA 23–31 wk + 6 d ) , ( 2 ) moderate-to-late SPTB infants ( GA 32 wk + 0 d to 36 wk + 0 d ) , ( 3 ) PPROM before onset of labor , and ( 4 ) no PPROM before onset of labor . To account for population substructure in the GWAS , the first two MDS dimensions were included as covariates . In the GWAS , the effect of population stratification was minimal ( λ = 1 . 03 ) . Gene set analysis ( GSA ) -SNP was used to search for gene set enrichment in pathway analysis [78] . We included only genotyped SNPs located within genes in this analysis to avoid the complicating effects of SNPs in linkage disequilibrium . R , v . 3 . 2 . 2 ( https://www . r-project . org ) was used to create Manhattan plots . LocusZoom [79] was used to create regional association plots . We annotated SNPs with three approaches: ( 1 ) We used Genotype-Tissue Expression ( GTEx ) data to analyze whether the SNPs overlap with cis expression quantitative trait loci ( eQTLs ) [80]; 2 ) we screened whether the SNPs had been associated with any phenotypes in previous GWA studies using the GWAS catalog[81]; and ( 3 ) we assessed whether the SNPs were located within putative regulatory regions using HaploReg , v . 4 . 1 [82] . Samples from human placenta were collected at Oulu University Hospital during 2010–2016 as described [16] . The placental samples used in immunohistochemical staining and in qRT-PCR analysis of SLIT2 and ROBO1 expression were subject to similar inclusion criteria as the samples used in GWAS . The inclusion criteria of gestational age for preterm placental samples was from 25 weeks to 36 weeks+ 6 days and 39 weeks to 41 weeks + 6 days for term samples . The same conditions ( multiple gestation , intrauterine growth restriction , placental abruption , polyhydramnios , fetuses with anomalies or requirements for special care of the newborn ) as in GWAS were used as exclusion criteria for term controls . Spontaneous preterm samples had almost the same exclusion criteria except the population included few cases with chorioamnionitis or oligohydramnion . The control group of elective preterm samples included cases with various pregnancy complications like IUGR or pre-eclampsia resulting in elective preterm delivery without labor . Specifically , in total , 18 placental samples were analyzed by immunohistochemistry . Twelve samples were from SPTB deliveries ( GA from 25 wk + 2 d to 35 wk + 2 d ) , and six were from spontaneous term deliveries ( GA from 39 wk + 4 d to 41 wk +1 d ) . Samples from both basal and chorionic plates were included in the study . RT-qPCR was performed with 23 placental samples from SPTB ( GA from 25 wk + 2 d to 36 wk + 0 d ) , 34 from elective preterm birth ( EPTB ) ( GA from 25 wk + 1 d to 36 wk + 6 d ) , and 23 from spontaneous term birth ( STB ) ( GA from 39 wk + 1 d to 41 wk + 6 d ) . Localization of encoded proteins was visualized in placental tissues by immunohistochemical staining . Samples were embedded in paraffin and cut into 4-μm slices , deparaffinized , and rehydrated . Antigen retrieval was done in Tris-EDTA buffer . Endogenous peroxidase activity was blocked in blocking solution ( Agilent , Santa Clara , CA , USA ) . Samples from the chorionic plate were incubated with mouse anti-human SLIT2 antibody ( 1:4000 dilution , PA5-3113; ThermoFisher Scientific , Waltham , Massachusetts , USA ) or mouse anti-human ROBO1 antibody ( 1:2000 , PA5-34931; ThermoFisher Scientific ) . Samples from the basal plate of the placenta were incubated in a 1:5000 dilution of mouse anti-human SLIT2 antibody and 1:1000 dilution of mouse anti-human ROBO1 antibody . Bound antibodies were detected with the Envision kit ( Agilent ) . Tissue samples were homogenized , RNA was isolated with the RNeasy Mini Kit ( Qiagen ) , and cDNA was synthetized as described previously [16] . After the RT-PCR , cDNA samples were diluted 1:2 using Rnase-free H20 . SLIT2 and ROBO1 were relatively quantified by intron spanning assays with Light-Cycler96 ( Roche Diagnostics , Risch-Rotkreuz , Switzerland ) and cytochrome c-1 ( CYC1 ) as a reference gene . CYC1 was chosen as a reference gene because it is one of the most stably expressed genes in the placenta [16 , 83–85] . Primers and probes were: forward 5′-CTTCCAGAGACCATCACAGAAA-3′ and reverse 5′-CGTCTAAGCTTTTTATATGGTGAGAA-3′ for SLIT2 ( with UPL probe #79 ) , forward 5′-CGCAGAGAAACCTACACAGATG-3′ and reverse 5′-GGATTGGGCAGTAGGTGACT-3′ for ROBO1 ( with UPL probe #31 ) , and forward 5′-ATAAAGCGGCACAAGTGGTCA-3′ and reverse 5′-GATGGCTCTTGGGCTTGAGG-3′ for CYC1 ( with UPL probe #47 ) . Probes were from the Universal Probe library ( UPL ) Set ( Roche Diagnostics ) . Each qPCR measurement was done in triplicate . Levels of SLIT2 and ROBO1 were normalized against the CYC1 level , and relative quantifications were then assessed with the ΔΔ cycle threshold method . A few randomly chosen qPCR products were also verified by agarose gel electrophoresis and Sanger sequencing . Primers and probes genes for transforming growth factor alpha ( TGFA ) , C-X-C motif chemokine ligand 6 ( CXCL6 ) , and SLIT-ROBO Rho GTPase activating protein 3 ( SRGAP3 ) were: forward 5′-CCCTGGCTGTCCTTATCATC-3′ and reverse 5′-GGCACCACTCACAGTGTTTTC-3′ for TGFA ( with UPL probe #74 ) , forward 5′-CCAGAAAATTTTGGACAGTGG-3′ and reverse 5′-GGGATCTCCAGAAAACTGCTC-3′ for CXCL6 ( with UPL probe #61 ) , and forward 5′-GAAGGGCACTCGATGAGGT-3′ and reverse 5′-GCTCATGGTCTTCTCGATGTC-3′ for SRGAP3 ( with UPL probe #66 ) . Total mRNA expression of different PSGs was measured with PCR primers: forward 5′-CCTCTCAGCCCCTCCCTG-3′ and reverse 5′-GGCAAATTGTGGACAAGTAGAAGA-3′ ( with UPL probe #15 ) , which are complementary to sequences conserved in all but two PSG transcript variants that both lack the N domain [26] . IL6 and TNFA were analyzed with primers forward 5′-GCCCAGCTATGAACTCCTTCT-3′ and reverse 5′-GCGGCTACATCTTTGGAATC-3′ for IL-6 ( with UPL probe #43 ) and forward 5′-CAGCCTCTTCTCCTTCCGAT-3′ and reverse 5′-GCCAGAGGGCTGATTAGAGA-3′ for TNFA ( with UPL probe #40 ) . Human placental trophoblast cells HTR-8/SVneo ( CRL-3271™; ATCC , Manassas , Virginia , USA ) . were grown in RPMI-1640 culture media ( Thermo Fisher Scientific ) supplemented with 10% fetal bovine serum ( FBS; Sigma-Aldrich , St . Louis , MO , USA ) and 1× penicillin/streptomycin ( Sigma-Aldrich ) . Cells were cultured under standard culturing conditions ( 37°C , 5% CO2 , humidified atmosphere ) , and subculturing was performed with 0 . 05% trypsin/0 . 02% EDTA . siRNAs targeting SLIT2 ( s GUCAUAUCAAGAACUGUGAdTdT , a UCACAGUUCUUGAUAUGACdTdT ) and ROBO1 ( s CAUACCUAUGGCUACAUUUdTdT , a AAAUGUAGCCAUAGGUAUGdTdT ) ( Sigma-Aldrich ) were reverse transfected and then forward transfected in HTR-8/SVneo cells with Lipofectamine 3000 reagent ( Invitrogen , Carlsbad , CA , USA ) [86] . MISSION siRNA Universal Negative Control #1 ( Sigma-Aldrich ) was used as a negative control for siRNA transfection and was transfected in the same manner as siRNAs targeting SLIT2 and ROBO1 . In the reverse transfection , the cells ( 70 , 000 cells/well ) were incubated with siRNAs at a final concentration of 30 nM . The cells were transfected again after 24 h of incubation . The second transfection was done as a forward transfection in the presence of 40 nM siRNAs . Cells were incubated with siRNAs for 24 h after the second transfection , and then fresh medium was added and cells were incubated for an additional 24 h . Cells were harvested with 1× Trypsin-EDTA ( Sigma-Aldrich ) . Cells were disrupted with a 25 G needle and 1 ml syringe , and RNA was isolated in accordance with the manufacturer’s instructions ( RNeasy Micro Kit , Qiagen ) . The quality of isolated RNA was checked with an Agilent 2100 Bioanalyzer system at the Biocenter Oulu Sequencing Center , Finland . Samples containing total RNA were sent for transcriptomic analysis to the Finnish Functional Genomics Centre ( FFGC; Turku , Finland ) , where transcriptional profiles of SLIT2 ( n = 3 ) and ROBO1 ( n = 3 ) -silenced cells and negative-control cells ( n = 3 ) were detected with the Illumina HiSeq high‐throughput sequencing system . Whole cell RNA sequencing data was analyzed by the Bioinformatics Unit Core Service at the Turku Centre for Biotechnology , Finland . The transcriptomics data have been deposited in NCBI’s Gene Expression Omnibus [87] and are accessible through GEO Series accession number GSE119101 ( https://www . ncbi . nlm . nih . gov/geo/query/acc . cgi ? acc=GSE119101 ) Knockdown of SLIT2 and ROBO1 with siRNAs , total RNA isolation , cDNA synthesis , and qPCR were done as described above , except 30 nM siRNAs were used in the forward transfection instead of 40 nM . Differences in mRNA expression levels among the phenotypes were assessed by nonparametric Mann–Whitney U-test with SPSS Statistics 20 . 0 ( IBM Corporation ) . | Worldwide , more than 10% of babies are born prematurely without effective means of prevention . Premature birth is associated with mortality and lifelong comorbidities . Aggregation of spontaneous preterm birth in certain families suggests that there are underlying genetic factors that predispose to preterm birth . Both maternal and fetal genomes likely affect susceptibility . We set out to identify fetal genetic variants that predispose infants to premature birth in a population of Finnish origin . Our results from a genome-wide association study indicate that a variant of slit guidance ligand 2 ( SLIT2 ) is associated with the risk of spontaneous preterm birth . Furthermore , SLIT2 and its receptor roundabout guidance receptor 1 ( ROBO1 ) are expressed in placental cells , and their mRNA levels are higher in placentas from spontaneous preterm deliveries compared to term controls . Based on gene knockdown experiments in cultured placental tissue–derived cells , ROBO1 regulates expression of pregnancy-specific beta-1-glycoprotein ( PSG ) genes and genes involved in inflammation . Thus , our results indicate that the fetal SLIT2 variant and expression of both SLIT2 and ROBO1 in placental cells are correlated with susceptibility to spontaneous preterm birth . We propose that this receptor–ligand pair is a component of the signaling network that promotes spontaneous preterm birth . | [
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"immunology",
"preterm",... | 2019 | Risk of spontaneous preterm birth and fetal growth associates with fetal SLIT2 |
The use of host nutrients to support pathogen growth is central to disease . We addressed the relationship between metabolism and trophic behavior by comparing metabolic gene expression during potato tuber colonization by two oomycetes , the hemibiotroph Phytophthora infestans and the necrotroph Pythium ultimum . Genes for several pathways including amino acid , nucleotide , and cofactor biosynthesis were expressed more by Ph . infestans during its biotrophic stage compared to Py . ultimum . In contrast , Py . ultimum had higher expression of genes for metabolizing compounds that are normally sequestered within plant cells but released to the pathogen upon plant cell lysis , such as starch and triacylglycerides . The transcription pattern of metabolic genes in Ph . infestans during late infection became more like that of Py . ultimum , consistent with the former's transition to necrotrophy . Interspecific variation in metabolic gene content was limited but included the presence of γ-amylase only in Py . ultimum . The pathogens were also found to employ strikingly distinct strategies for using nitrate . Measurements of mRNA , 15N labeling studies , enzyme assays , and immunoblotting indicated that the assimilation pathway in Ph . infestans was nitrate-insensitive but induced during amino acid and ammonium starvation . In contrast , the pathway was nitrate-induced but not amino acid-repressed in Py . ultimum . The lack of amino acid repression in Py . ultimum appears due to the absence of a transcription factor common to fungi and Phytophthora that acts as a nitrogen metabolite repressor . Evidence for functional diversification in nitrate reductase protein was also observed . Its temperature optimum was adapted to each organism's growth range , and its Km was much lower in Py . ultimum . In summary , we observed divergence in patterns of gene expression , gene content , and enzyme function which contribute to the fitness of each species in its niche .
The most fundamental characteristic of microbial pathogenesis is the use of host nutrients to support pathogen growth [1 , 2] . Trophic lifestyles of plant pathogens have been categorized as biotrophic when the host stays alive during the nutrient exchange , or necrotrophic when the pathogen kills and feeds on the remains of plant cells [3] . An additional level of diversity in phytopathogens is that while some are exclusively plant colonizers , others cycle between saprophytism and parasitism . Much has been learned about the tactics that plant pathogens employ to suppress host defenses to maintain biotrophy or kill cells during necrotrophy [3 , 4] . However , little is known about how the life strategies of pathogens are reflected in their metabolism . Pathogens can be considered as occupants of specific environmental niches to which their metabolism has been tailored . Studies of natural and lab-induced variation have demonstrated that metabolism can evolve through multiple processes . Some involve major events such as the loss of a gene , or the acquisition of new functions by lateral transfer [5–7] . Smaller changes include mutations that modify regulatory proteins , alter promoter activity , or change the substrate affinity , reaction kinetics , or allosteric regulation of an enzyme [8–11] . Such mutations occur spontaneously within pathogen populations and when selected may help tune metabolism to a lifestyle , environment , or new host . Phytophthora infestans and Pythium ultimum present interesting contrasts in pathogen lifestyles . These species belong to sister genera in the peronosporalean lineage of oomycetes , which cause blights and rots of thousands of important plants [12] . Ph . infestans triggered the notorious Irish Famine and persists as arguably the most destructive pathogen of potato , infecting foliage and tubers [13] . Ph . infestans grows biotrophically for most of the disease cycle , producing haustoria and effectors that suppress host defenses and feeding on apoplastic nutrients [3] . Ph . infestans is classified as a hemibiotroph since host necrosis occurs near the end of the disease cycle [13 , 14] , although data that indicate that this stage is necrotrophic and not simply necrogenic are sparse . Py . ultimum also infects potato tubers but is a necrotroph . While tubers colonized by Ph . infestans remain firm unless secondary pathogens are present , Py . ultimum transforms tubers into watery rotted tissue while feeding off the liberated nutrients [15] . Like other members of its genus , Py . ultimum also grows in soil or plant debris [16] . In contrast , most members of the genus Phytophthora including Ph . infestans can only survive in nature by growing on living plants . The goal of this study was to understand how the metabolism of Ph . infestans and Py . ultimum is adapted to their respective lifestyles . Most prior comparisons of pathogens with distinct trophisms have examined infections of different plant species , which complicates analysis since each host may provide dissimilar nutrients [17 , 18] . This can be avoided with Ph . infestans and Py . ultimum since both infect potato tubers . In an earlier study , we focused on effectors and other pathogenicity factors expressed by these oomycetes during tuber infection [19] . In this paper , we concentrate on metabolism . We annotated metabolic genes of the two species , compared RNA-seq and metabolomic data from tubers and media at different stages of infection , and identified genus-specific differences in metabolic gene content and expression pattern . We also observed shifts in metabolic gene expression during tuber colonization by Ph . infestans that provide evidence of necrotrophy during the late stages of its disease cycle . We also focused on nitrate assimilation , which appeared to be more active in Py . ultimum . Measurements of RNA and protein levels , enzyme assays , and isotopic labeling revealed dramatic differences in how the two species use nitrate . Like many organisms , Ph . infestans prefers to obtain nitrogen from amino acids , using nitrate as a last resort . In contrast , Py . ultimum assimilates nitrate at all stages of growth regardless of the availability of more economical nitrogen sources . While the assimilation genes in Py . ultimum were nitrate-induced , this was not the case for Ph . infestans . How variation in expression pattern and enzyme function relates to each organism's lifestyle is discussed .
Genes from Ph . infestans and Py . ultimum were annotated as described in Materials and Methods . This involved primarily the use of the KEGG Automatic Annotation Server ( KAAS; [20] ) , the KEGG Orthology And Links Annotation tool ( KOALA; [21] ) , and protein domain databases . Orthologs between Ph . infestans and Py . ultimum were identified using OrthoMCL , and their annotations compared to identify and resolve ambiguities . The genes were then assigned Enzyme Commission ( EC ) and KEGG ortholog ( KO ) group numbers , and categorized into pathways using the KEGG schema . Enzymes that synthesize or modify proteins , nucleic acids , and the cell wall were excluded from analysis . We identified 1507 metabolic genes representing 586 EC numbers from Ph . infestans and 1468 genes representing 589 EC numbers from Py . ultimum ( Fig 1; S1 Table ) . These represent 8 . 5% and 9 . 2% of total genes , respectively . Much of the interspecific differences in gene numbers were due to gene family expansions . Since our goal was to use RNA-seq data to compare the expression of metabolic pathways in the two species , we performed several preliminary analyses to help predict whether that strategy would be valid . One concern was that differences in gene model quality could lead to false conclusions; for example , if gene models were consistently truncated in one species , this might lead to the inference that its genes were transcribed more weakly . However , such issues did not appear to be significant . The average coding sequence sizes in Ph . infestans and Py . ultimum were nearly identical at 1176 and 1149-nt , respectively ( Fig 1 ) . Moreover , the aggregate FPKM value ( fragments per kilobase per million mapped reads ) of metabolic genes during growth in rye media and tubers were very similar , averaging 114 , 214 and 118 , 152 in Ph . infestans and Py . ultimum , respectively . Several enzymes appeared to lack orthologs in one of the two oomycetes . Many enzymes initially appeared to be species-specific but were later detected as unannotated genes in the assembly . Excluding those , we detected in Ph . infestans but not Py . ultimum genes predicted to encode pyruvate phosphate dikinase ( e . g . PITG_03721; EC 2 . 7 . 9 . 1 ) , sorbitol/iditol dehydrogenase ( e . g . PITG_04121; EC 1 . 1 . 1 . 14 ) , salicylate dehydrogenase ( PITG_17117; EC 1 . 14 . 13 . 1 ) , and formate dehydrogenase ( PITG_13448; EC 1 . 2 . 1 . 2 ) . Based on searching the Fungidb . org and Eumicrobedb . org web sites [22 , 23] , orthologs of these genes were present in each of eight Phytophthora spp . in those databases but not any of the six sequenced members of Pythium . We also detected orthologs in Phytopythium vexans , which bridges the two genera [24] . The enzymes specific to Phytophthora were not distributed widely in other oomycetes . For example , absent from the downy mildews Hyaloperonospora arabidopsidis and Plasmopara halstedii , two Albugo white rusts , two Aphanomyces spp . , and two Saprolegnia spp . were sequences for pyruvate phosphate dikinase ( EC 2 . 7 . 9 . 1 ) , formate dehydrogenase ( EC 1 . 2 . 1 . 2 ) , and the sorbitol/iditol dehydrogenase ( EC 1 . 1 . 1 . 14 ) . The putative salicylate dehydrogenase ( EC 1 . 2 . 1 . 65 ) also appeared to be specific to Phytophthora . Several activities were also predicted to occur in Py . ultimum but not Ph . infestans . These included three enzymes involved in thiamine biosynthesis , which has been reported to be absent from haustoria-forming oomycetes [25] . Also lacking from all sequenced Phytophthora spp . were glucosamine-6-phosphate deaminase ( PYU1_G006886 , EC 3 . 5 . 99 . 6 ) and N-acetylglucosamine-6-phosphate deacetylase ( PYU1_G006885 , EC 3 . 5 . 1 . 25 ) , which contribute to chitin degradation . Interestingly , these genes are adjacent in the Py . ultimum genome . Orthologs were detected in Phytopythium , Saprolegnia , and Aphanomyces . These enzymes may be used to assimilate carbon from chitin in soil , but may also contribute to the synthesis of their cell walls [26] . Also present in Pythium but not Phytophthora spp . was a gene predicted to encode γ-amylase ( EC 3 . 2 . 1 . 3 ) . A gene for a putative nitrilase ( EC 3 . 5 . 5 . 1 ) , which hydrolyzes non‐peptide carbon-nitrogen bonds , was detected in three of the five sequenced Pythium spp . including Py . ultimum ( e . g . PYU1_G001840 ) , Phytopythium vexans , and five of the eleven sequenced Phytophthora spp . but not Ph . infestans . Such enzymes have been shown to break down the plant defense compound hydrogen cyanide and was identified in Ph . ramorum as a candidate for horizontal gene transfer [27 , 28] . Its patchy distribution in Pythium and Phytophthora suggests that the gene may have been present in an oomycete ancestor . To compare the metabolic transcriptomes of Ph . infestans and Py . ultimum , we used RNA-seq data from our prior study that focused on the early and late stages of potato tuber colonization [19] . As shown in Panel A of S2 Fig , Py . ultimum causes massive host necrosis throughout the disease cycle while necrosis only occurs at the late stages of colonization by Ph . infestans . The sampling scheme used for early and late timepoints in the RNA-seq experiment is illustrated in Panels B and C of S2 Fig . For Ph . infestans , samples collected at 1 . 5 and 4 days after inoculation represented the early and late stages of infection . We previously showed that mRNA levels of markers such as Avr3A and NPP1 were consistent with those timepoints representing biotrophic ( early ) and necrotrophic ( late ) stages of growth . For Py . ultimum , the early and late timepoints were represented by bands within lesions that had been colonized for 0 . 5 and 1 . 5 days; both exhibited massive necrosis . The RNA-seq experiment employed three biological replicates , and RT-qPCR of 12 genes showing differential expression in RNA-seq confirmed the robustness of the data [19] . Expression data were also generated from young and older ( sporulating ) cultures grown on rye and pea broth . An overview of metabolism was obtained by summing the FPKM of genes in each of 47 pathways ( Fig 2 ) . During early tuber infection , many pathways exhibited higher aggregate expression in one species than the other; "early" in this context corresponds to the biotrophic growth of Ph . infestans at 1 . 5 dpi and necrotrophic growth by the faster-growing Py . ultimum at 0 . 5 dpi . For example , genes in pathways for inositol phosphate , glycerolipid , and inorganic nitrogen metabolism were transcribed at 2 , 3 , and 4-fold higher levels in Py . ultimum ( bars in Fig 2 ) . In contrast , most pathways involved in amino acid , nucleotide , and cofactor biosynthesis were expressed 2 to 3-fold higher in Ph . infestans . The expression ratios measured between the species in planta were generally distinct from the ratios observed in hyphae of similar age from rye media ( circles in Fig 2 ) . While most ratios on artificial media were closer to unity than on tubers , this was not always true . For example , many pathways related to forming amino acids were higher in Ph . infestans in both tubers and media . Similarly , fatty acid biosynthesis was higher in Py . ultimum under both conditions . A few pathways exhibited opposite biases , such as sphingolipid biosynthesis which was higher in Py . ultimum on tubers but lower in rye media . It was interesting that the expression of genes related to oxidative phosphorylation varied between the species by less than 30% in both tubers and media . The biological relevance of the results from the rye media cultures is unclear since this is not a natural growth condition , especially for Ph . infestans , which only colonizes living plants . Nevertheless , comparisons between gene expression in tubers and media demonstrate that the two species adapt their metabolism to their environment . Similar conclusions can be drawn from RNA-seq data from pea media ( S1 Fig ) . As described below , several of our experiments suggested that the interspecific variation in mRNA levels associated with pathways was not accompanied by major differences in metabolite pools . For example , although differences were observed in the expression of amino acid and lipid metabolism genes , assays of hyphae from rye media revealed that each species had similar lipid and amino acid contents ( Fig 3A ) . Moreover , untargeted metabolomics identified only a few differences between young hyphae of Ph . infestans and Py . ultimum grown on rye media . This analysis yielded data on 188 identified and 349 unidentified compounds . Based on 12 biological replicates , several differences were detected at an uncorrected P-value threshold of 0 . 05 ( Fig 3B ) . These included four-fold higher pyruvate in Py . ultimum , and smaller increases in Ph . infestans of glycerol , threitol , oxobutanoate and aminoisobutyrate ( intermediates in amino acid metabolism ) , and galacturonic acid and galactarate ( from pectin degradation ) . It is tempting to link these differences with our previous data . For example , the higher pyruvate in Py . ultimum might be attributed to its lack of pyruvate phosphate dikinase ( EC 2 . 7 . 9 . 1 ) . Similarly , the higher levels of galacturonic acid and galactarate in Ph . infestans might reflect the fact that it produces more polygalacturonases ( EC 3 . 2 . 1 . 15 ) than Py . ultimum , as described in ref . [19] . Such speculations are interesting , but note that no metabolites were significantly different at an FDR threshold of 0 . 05 based on a Benjamini-Hochberg multiple testing correction . This is consistent with the concept that Ph . infestans and Py . ultimum form similar biosubstances through distinctly tuned metabolic pathways . Potato starch represents about 80% of the carbohydrate of potato tubers , and occurs as intracellular granules comprised of 20% amylose , which are α-glucose units joined by α-1 , 4 bonds , and 80% amylopectin , which also contains α-1 , 6 linkages [29 , 30] . Ph . infestans and Py . ultimum both encode α-amylases ( EC 3 . 2 . 1 . 1 ) , which degrade the 1 , 4 linkage [31] . However , only Py . ultimum produces an γ-amylase ( EC 3 . 2 . 1 . 3 ) , which is needed to break the 1 , 6 bond . Neither makes a β-amylase ( EC 3 . 2 . 1 . 2 ) , which plants and some microbes use to remove disaccharides from starch . Interestingly , our search of other oomycete genomes indicate that only Saprolegnia spp . express β-amylase . The expression patterns of the Ph . infestans and Py . ultimum amylases during tuber infection are shown in Fig 4A . In this and subsequent figures , mRNA levels are presented as per-gene normalized values averaged to 1 . 0 , based on the summed FPKM values of genes with the same EC number . At the early stage of infection , α-amylase mRNA was >50 times more abundant in Py . ultimum than Ph . infestans ( significantly different at P<0 . 05 ) . Expression rose in both species at the late timepoint , particularly in Ph . infestans where a >50-fold increase was recorded . These patterns are consistent with the predicted abilities of the pathogens to access starch: while Py . ultimum lyses cells and thus could access starch granules throughout infection , host cell lysis only occurs near the end of the Ph . infestans disease cycle . The high amylase activity of Py . ultimum during early infection is expected to provide that species with access to more glucose than Ph . infestans . Consistent with this is our observation that genes encoding glucose-6-phosphate dehydrogenase ( EC 1 . 1 . 1 . 49 ) and 6-phosphogluconate dehydrogenase ( EC 1 . 1 . 1 . 44 ) were expressed at about four-fold higher levels in Py . ultimum compared to Ph . infestans during early tuber infection ( Fig 4B ) . These differences were significant at P<0 . 05 . The two enzymes represent rate-limiting steps within the oxidative phase of the pentose phosphate pathway , which is an alternative route for obtaining energy from glucose in addition to enabling pentose synthesis . Expression levels of the genes in the two species became similar during late infection . Conversely , each of the three rate-limiting steps in gluconeogenesis were expressed two to four-fold higher in Ph . infestans than Py . ultimum during early tuber infection ( Fig 4D ) . These differences were significant at P<0 . 05 . Expression of the genes encoding these enzymes ( EC 3 . 1 . 3 . 11 , EC 4 . 1 . 1 . 49 , and EC 6 . 4 . 1 . 1 ) at higher levels in Ph . infestans compared to Py . ultimum is consistent with its need to generate intermediates for processes such as cell wall and amino acid biosynthesis . Ph . infestans is also probably better-suited to gluconeogenic flux since it , but not Py . ultimum , encodes pyruvate phosphate dikinase . This pyrophosphate-dependent transferase converts pyruvate to phosphoenolpyruvate more readily than pyruvate kinase , which uses ATP as the phosphate donor with a much higher ΔG [25] . An analysis of genes within this KEGG pathway revealed that the higher level of mRNA scored for Py . ultimum compared to Ph . infestans during early infection was attributable to genes that encode enzymes predicted to remove phosphate from inositol hexakisphosphate ( InsP6 , phytic acid ) and partially dephosphorylated derivatives such as inositol tetraphosphate ( InsP4 ) and pentaphosphate ( InsP5 ) . Enzymes for metabolizing myo-inositol were expressed at similar levels in the two species . About 20% of the total phosphate in tubers is stored as InsP6 [31] , primarily in protein storage vacuoles [32] . These organelles are expected to be accessed by Py . ultimum throughout disease but only during late infection by Ph . infestans . As shown in Fig 4C , this predicted pattern of InsP6 accessibility by the pathogens matches the expression of genes encoding InsP4 phosphotransferase ( EC 2 . 7 . 1 . 34 ) , InsP5 phosphotransferase ( EC 2 . 7 . 1 . 158 ) , multiple inositol-polyphosphate ( InsP4 to P6 ) phosphatase ( EC 3 . 1 . 3 . 32 ) , and acid phosphatase ( EC 3 . 1 . 3 . 2 ) . For example , in early tubers these genes exhibited 2 . 5 to 50-fold higher expression in Py . ultimum , with the differences being significant at P<0 . 05 . Increases were also observed between early and late infection by Ph . infestans , especially for InsP5 phosphotransferase which accumulated nine-fold higher levels of mRNA . Oomycetes lack orthologs of the InsP6 phytases that occur in plants and some microbes ( EC 3 . 1 . 3 . 8 and EC 3 . 1 . 3 . 26 ) , but some EC 3 . 1 . 3 . 2 phosphatases are known to act as phytases [33] . We showed above ( Fig 2 ) that the expression of genes in the KEGG glycerolipid metabolism pathway during early infection was three-fold higher in Py . ultimum than Ph . infestans . This was found to be attributable to the transcription patterns of lipases and enzymes for metabolizing the lipase reaction products , glycerol and fatty acids ( Fig 5A ) . For example , the level of lipase mRNA ( EC 3 . 1 . 1 . 3 ) during early tuber colonization was 3-fold higher in Py . ultimum than Ph . infestans . Although not shown in the figure , mRNA levels of genes encoding other classes of lipases were also higher in Py . ultimum during early infection including acylglycerol lipase ( EC 3 . 1 . 1 . 23 , 2-fold higher ) and lysosomal lipases ( EC 3 . 1 . 1 . 5 and EC 3 . 1 . 1 . 13 , 11 and 6-fold higher , respectively ) . Five of the six enzymes involved in the β-oxidation of fatty acids also exhibited higher expression in Py . ultimum in early tubers . This includes the gene encoding the enzyme for the carnitine shuttle that brings acyl-CoA into mitochondria ( EC 2 . 3 . 1 . 21 ) . Each of these differences between the species were significant at P<0 . 05 . One exception to this pattern was enoyl-CoA hydratase ( EC 4 . 2 . 1 . 17 ) , which showed similar mRNA levels in the two species . This bidirectional enzyme both degrades and synthesizes fatty acids . Each of the five enzymes that convert glycerol to the glycolytic intermediates dihydroxyacetone phosphate and 3-phosphoglycerate were also expressed at higher levels in Py . ultimum during early tuber infection , such as glycerate kinase ( EC 2 . 7 . 1 . 31 ) and glycerolphosphate dehydrogenase ( EC 1 . 1 . 1 . 8 ) . Each of these differences were significant at P<0 . 05 . During late infection , the aggregate expression of three of these five enzymes as well as lipases rose in Ph . infestans to levels similar to that observed for Py . ultimum , consistent with the transition of Ph . infestans to necrotrophy . It should be noted that a few of the enzymes in Fig 5A contribute to multiple pathways . For example , acetaldehyde dehydrogenase ( EC 1 . 2 . 1 . 3 ) converts not only glyceraldehyde to glycerate but also participates in the biosynthesis of carnitine . Similarly , some acid phosphatases ( EC 3 . 1 . 3 . 2 ) discussed in the prior section may also act on glycerol phosphates produced during lipid catabolism . Transcript levels of each enzyme involved in glycerolipid metabolism increased in Ph . infestans during late tuber infection to levels matching or exceeding that observed in early infection by Py . ultimum . This may reflect the transition of Ph . infestans to necrotrophy . An alternative explanation is that this aspect of metabolism increases during sporulation , which occurs during late infection . As shown in Fig 2 , the aggregate level of mRNA related to inorganic sulfate metabolism during early tuber colonization was 3-fold higher in Py . ultimum than Ph . infestans . Although we are unaware of data from potato tubers , plant leaves contain small amounts of sulfate in the apoplast , typically 0 . 01 to 1 mM , with much greater concentrations in cells within vacuoles , typically around 25 mM [34] . Further analysis indicated that the imbalance in mRNA levels was due to the pathway shown in Fig 5B , in which sulfate is reduced and converted to cysteine . Each of the five activities , starting at 3'-phosphoadenosine 5-phosphosulfate synthase ( EC 2 . 7 . 7 . 4 ) and ending with cysteine synthase ( EC 2 . 5 . 1 . 47 ) , came from genes that were expressed between 3 and 10-times higher in Py . ultimum than Ph . infestans during early tuber infection . Each of these differences were significant at P<0 . 05 . Similar to the situation in metazoans , our analysis indicates that the first two steps of this pathway in oomycetes are catalyzed by a bifunctional enzyme , phosphoadenosine-phosphosulfate synthase ( PAPS ) , unlike the situation in bacteria and plants which use two separate polypeptides [35] . Continuing the trend seen with the enzymes described earlier , expression of all of the sulfate assimilation genes rose in Ph . infestans during late infection to levels resembling those of Py . ultimum during early infection . This is consistent with the transition of Ph . infestans to necrotrophy . However , the mRNA levels of most genes encoding sulfate assimilation enzymes declined in Py . ultimum during late infection . It should be noted that we cannot claim with 100% confidence that the pathway in Fig 5B operates as shown , due to uncertainty about whether oomycetes make O-acetylserine . This substrate is made in most other organisms by serine O-acetyltransferase ( EC 2 . 3 . 1 . 30 ) , but no Ph . infestans or Py . ultimum gene was computationally predicted to encode that activity . However , two were annotated as homoserine acetyltransferase ( EC 2 . 3 . 1 . 31 ) , and one might be the EC 2 . 3 . 1 . 30 protein since enzymes that act on serine and homoserine are difficult to distinguish . Alternatively , a single enzyme might acetylate both serine and homoserine since some bacterial enzymes exhibit a similar Kcat for both substrates [36] . Most oomycetes can also transform sulfate to sulfite using sulfite oxidase ( EC 1 . 8 . 3 . 1 ) . This enzyme is not shown in the figure but was expressed at slightly higher levels in Ph . infestans . Multiple pathways related to forming amino acids displayed higher aggregate mRNA levels in Ph . infestans during early tuber colonization compared to Py . ultimum ( Fig 2 ) . In general , amino acids are generated from glycolytic and citric acid cycle intermediates and through interconversions from other amino acids . Tubers are a relatively rich source of free amino acids ( 50–100 mM ) , but most reside within the vacuole [37] . An examination of the expression data underlying the pathway summaries in Fig 2 indicated that enzymes that make most amino acids , except for methionine , were expressed significantly higher in Ph . infestans than Py . ultimum ( P<0 . 05 ) during early tuber colonization . This is illustrated in Fig 6A for arginine and Fig 6B for valine , leucine , and isoleucine . For example , genes encoding nine of the ten enzymes used to convert α-ketoglutarate to arginine were transcribed 5 to 10-fold higher by Ph . infestans . The only exception was glutamate N-acetyltransferase ( EC 2 . 3 . 1 . 1 ) , which had higher expression in Py . ultimum . In the pathway that generates valine , leucine , and isoleucine , genes for all 14 enzymes exhibited higher mRNA levels in early tuber infection by Ph . infestans than Py . ultimum . Interestingly , during late infection mRNA levels for each of these genes rose in Py . ultimum but fell in Ph . infestans . This decline in the latter may be related to the general reduction in metabolic mRNAs that we observed previously in Ph . infestans upon sporulation , since spores were forming at our late timepoint . The rise in Py . ultimum late during its disease cycle likely indicates that amino acids are becoming depleted . The transaminases ( EC 2 . 6 . 1 . - ) that are used to form all amino acids other than those mentioned earlier are shown in Fig 6C . Genes for these were uniformly expressed at higher levels in Ph . infestans during early infection ( P<0 . 05 ) . In most cases , their mRNAs rose in Py . ultimum during late infection . Nitrogen for amino acids , nucleotides , and other substances in eukaryotes are usually obtained from another organic compound such as an amino acid . Ammonium and nitrate are other sources , with the latter being assimilated through the action of nitrate reductase ( NR; EC 1 . 7 . 1 . 1 ) and nitrite reductase ( NiR; EC 1 . 7 . 1 . 4 ) . The NR and NiR genes , along with one encoding a nitrate transporter ( NRT ) , form a cluster in Phytophthora and Pythium genomes that appears to have been transferred horizontally from an oomycete ancestor to fungi [38] . Major differences in NR and NiR expression in Ph . infestans and Py . ultimum were observed during tuber colonization . As shown in Fig 6D , both enzymes were expressed >50-fold more by Py . ultimum during early infection . These differences were significant at P<0 . 05 . Their transcripts rose during late infection by Ph . infestans . These results were intriguing for several reasons . First , most isolates of Ph . infestans are reportedly unable to grow using nitrate as the sole nitrogen source [39] . This raises the question of whether the assimilation pathway is functional in Ph . infestans . This is not an unreasonable speculation considering that downy mildews have lost NR and NiR [40] . Second , our assays indicated that tubers contained only about 0 . 4 mM nitrate , compared to 50–100 mM of free amino acids and 2 mM ammonium . In most other organisms , nitrate assimilation is repressed by amino acids and ammonium since these alternative nitrogen sources do not require energy-intensive reduction steps [41] . It was therefore surprising that Py . ultimum strongly up-regulated the nitrate assimilation genes in the presence of a 100-fold excess of other nitrogen sources . To confirm prior reports that nitrate is a poor source of nitrogen for Ph . infestans [42] , we tested five isolates of Ph . infestans along with Py . ultimum and two isolates of Phytophthora mirabilis . The latter is a pathogen of the perennial herbaceous plant Mirabilis jalapa ( four-o'clock ) and is related to Ph . infestans [39] . Testing all three species on a common defined medium was challenging since most media did not support the growth of all species or strains . A version of Henninger's media [43] with nitrate or ammonium substituting for amino acids proved adequate , although growth was poor and the media did not support sporulation . All species grew in the defined media when the nitrogen source was 10 mM ammonium ( Fig 7 ) . Py . ultimum and Ph . mirabilis grew at similar rates on ammonium or nitrate . However , none of the Ph . infestans isolates grew when the ammonium was substituted by nitrate . The same result was obtained with Ph . infestans regardless of whether potassium or sodium nitrate was used , if the concentration was dropped to 1 mM , or if the pH of the media was reduced . To study nitrate metabolism in the three species , including whether Ph . infestans assimilated nitrate at all , a labeling study was performed in media spiked with 10 mM 15NO3– , 15NH4+ , or 15N-Gln . Measurements were made in "early" cultures where amino acids would still be abundant in media , and "late" cultures where amino acids would be depleted . In preliminary experiments , by assaying metabolites remaining in spent broth we established that the "early" and "late" conditions occurred when a hyphal mat initiated from an inoculum plug covered about 20 and 80% of the culture's surface area , respectively . This usually occurred in 2 and 6-day cultures of Ph . infestans , 3 and 8-day cultures of Ph . mirabilis , and 1 and 2-day cultures of Py . ultimum , respectively , although the exact time varied depending on the vigor of the inoculum . As shown in Fig 8A , the early and late cultures of each species retained about 50 and 1% of the starting concentration of amino acids , or about 1 . 5 and 0 . 03 mM , respectively . In all experiments described subsequently , spent media was assayed to validate the "early" and "late" condition of each sample . If a culture thought to represent an early timepoint appeared to be too aged based on the residual level of amino acids , it was discarded . After conditions for "early" and "late" growth were established , the labeling experiment was performed with the three 15N-labeled compounds ( added to separate cultures ) using six biological replicates each , plus unlabeled controls . Based on 15N/14N ratios in amino acids as measured by mass spectrometry , Ph . infestans and Ph . mirabilis both incorporated little 15NO3– or 15NH4+ in the amino acid-rich early timepoint but used large amounts of these two compounds at the late timepoint ( Fig 8C and 8D ) . For example , about 25 times more 15N from nitrate was incorporated into valine at the late versus early stages . 15N-Gln was used at similar rates at both timepoints ( Fig 8B ) , while intermediate results were obtained with 15NH4+ ( Fig 8D ) . For example , ammonium was assimilated into valine two times more in the late than early cultures by both Ph . infestans and Ph . mirabilis; similar trends were obtained for 13 of the other 14 amino acids that were assayable . The exception was glutamine which acquired nitrogen from 15NH4+ at similar rates at the early and late timepoints; this was not surprising since glutamine synthase was expressed more during early than late infection ( Fig 6D; EC 6 . 3 . 1 . 2 ) . The data demonstrate that Ph . infestans preferentially uses amino acids as a nitrogen source followed by ammonium , has a functional nitrate assimilation pathway , and that the pathway is repressed by amino acids and possibly ammonium similar to what occurs in most fungi [44] . The results with Py . ultimum were strikingly different . This species incorporated all three nitrogenous compounds at similar rates at each timepoint . Therefore , there was little evidence that amino acids repressed its nitrate assimilation pathway . Since rye media also contains about 0 . 3 mM ammonium , that compound does not appear to strongly repress nitrate assimilation . Another conspicuous difference between the species was that nitrate had a strong stimulatory effect on the expression of nitrate reductase , nitrite reductase , and the nitrate transporter in Py . ultimum ( NR , NiR , and NRT , respectively ) , little or no effect in Ph . infestans , and an intermediate effect in Ph . mirabilis . This is indicated by the RT-qPCR data in Fig 9A . For example , adding 10 mM nitrate to rye media caused NR mRNA in Py . ultimum to increase by 20 and 5-fold at the early and late timepoints , respectively . Parallel changes were observed for NiR and NRT mRNA . Our assays indicate that unamended rye media contains about 40 μM nitrate . In contrast , the Ph . infestans genes were not induced by 10 mM nitrate in media at the early or late timepoints . They were expressed highly at the late timepoint regardless of whether 10 mM nitrate was added . This mirrors their behavior during early and late tuber colonization ( Fig 6D ) . Culture age thus appears to be a strong determinant of expression of the genes in Ph . infestans . With Ph . mirabilis , adding 10 mM nitrate to early media cultures caused about two-fold increases in NR and NRT mRNA , although the absolute level of transcripts was very small ( too low to be visible in Fig 9A ) . At the late timepoint , mRNA levels increased strongly regardless of nitrate concentration , similar to Ph . infestans . However , adding nitrate caused an additional 2 to 5-fold increase in mRNA levels in the late cultures of Ph . mirabilis . Interestingly , higher induction was observed for NiR compared to NR , which is similar to the response observed in N . crassa [45] . Since NR in some organisms is subject to post-translational regulation [46] , we compared levels of NR mRNA with its enzymatic activity ( Fig 9B ) . Post-translational events did not appear to be a major factor in regulating the enzyme since NR specific activity and mRNA generally increased in parallel in each of the three species . Nitrate did seem to cause a disproportional increase in enzyme activity in late cultures of Ph . infestans , however . In the presence of nitrate , the specific activity of NR was about four times higher in Py . ultimum than Ph . infestans or Ph . mirabilis . The use of an antibody against NR also showed that mRNA and protein levels changed in concert . In our initial tests against protein extracts from Ph . infestans , we observed that the antibody was not very specific ( Fig 9C ) . NR from Ph . infestans and Py . ultimum are both predicted to be 93 kDa , after removing an intron from the Ph . infestans gene model which appeared to be incorrect based on RNA-seq data . While the antibody detected a 93 kDa band , it also detected a stronger band at 82 kDa . As shown in Fig 9B , we determined that the 93 kDa band was NR since it was absent in two strains in which NR transcription was blocked by homology-dependent gene silencing [47] . Also , the possibility that NR had aberrant electrophoretic mobility seemed unlikely since recombinant Ph . infestans NR expressed in E . coli with a 3 kDa hexahistidine tag yielded a band with an apparent mobility of 96 kDa ( Fig 9C , right lane ) . Next , we extended our analysis to all three species . The pattern of production of NR protein in Ph . infestans , Ph . mirabilis , and Py . ultimum is shown in Fig 9D . The intensity of the 93 kDa band shows a good match to the levels of NR mRNA and enzymatic activity shown in Fig 9A , and confirms that expression of the enzyme is regulated divergently in the three species . For example , NR protein was nitrate-induced in Py . ultimum and Ph . mirabilis , but in Ph . infestans was not induced by nitrate . Nitrate seemed to reduce NR protein ( and mRNA; Fig 9A ) levels slightly in Ph . infestans , which could be a sign of nitrate toxicity . In both Ph . infestans and Ph . mirabilis , the NR band was stronger in the late compared to early nitrate-supplemented samples . Since the right-most lane in the Ph . mirabilis panel was overloaded by 2–3 times compared to the other Ph . mirabilis lanes , we repeated the blot using fresh samples . This confirmed that its NR protein was more abundant in the late cultures , provided that nitrate was present ( S3 Fig ) . During our analysis of oomycete genomes we observed that all species of Phytophthora as well as downy mildews encode a protein annotated as a fungus-like nitrogen metabolite repression regulator . Intriguingly , this appears to be missing from other oomycetes including all sequenced species of Pythium . The fungal protein , which is called NMRA in Aspergillus nidulans and NMR1 in Neurospora crassa , is a transcription factor that causes more readily assimilated nitrogen sources such as ammonium and glutamine to be used instead of nitrate [44] . We observed that NR and the Ph . infestans ortholog of NMRA , PITG_14492 , are expressed in opposing patterns which is consistent with a role of the latter in repressing nitrate assimilation . As shown in Fig 10A , during early tuber colonization NR mRNA was low while NMRA mRNA was high , while the reverse patterns of expression were seen during late tuber infection . The same expression profiles were observed in early and late rye media cultures ( Fig 10B ) . As this paper was being written , a microarray study of Phytophthora capsici infecting tomato was published [48] . Our analysis of data from that paper deposited in ArrayExpress showed that the patterns of NR and NMRA expression in Ph . capsici matched that of Ph . infestans ( Fig 10C ) . Moreover , an NMRA-overexpressing transformant of Ph . capsici from that study showed reduced levels of NR mRNA ( Fig 10D ) . We considered the possibility that the NR proteins of each species had acquired distinct characteristics , since the environments that favor their growth are not equal . For example , only Py . ultimum is able to grow on organic debris in soil . In addition , Py . ultimum grows over a broader temperature range than Ph . infestans ( Fig 11A , dashed lines ) . It was therefore interesting to observe that the Py . ultimum NR remains active at much higher temperatures than NR of Ph . infestans ( Fig 11A , solid lines ) . Measurements of the Michaelis constant indicated differences in the affinity of each enzyme for nitrate ( Fig 11B ) . We measured the Km of NR from Aspergillus niger at 202 mM , which is close to the published value [49] . Compared to this benchmark , the Km of NR from Py . ultimum was slightly lower at 146 μM , while both Ph . infestans and Ph . mirabilis were much higher at 587 and 469 mM , respectively . To place these characteristics in context with the sequence similarity of the proteins , we assembled the Ph . mirabilis gene for NR from short reads deposited at NCBI ( Bioproject PRJNA52429 ) . The Ph . infestans and Ph . mirabilis proteins exhibited 96% similarity . Both were 76% similar to Py . ultimum NR , and 55–56% similar to the NR of A . niger . The Py . ultimum and A . niger enzymes exhibited 55% similarity .
We observed variation between the metabolism of Ph . infestans and Py . ultimum at multiple levels . Transcriptional differences often reflected each pathogen's access to nutrients . During early tuber colonization , most pathways that were expressed more in Py . ultimum involved metabolites liberated from lysing plant cells , while those transcribed at higher levels in Ph . infestans were associated with synthesizing compounds that probably occur at insufficient levels in the apoplast to support growth . A second level of divergence was in the machinery that regulates metabolism , such as that pertaining to nitrate assimilation which in Py . ultimum was more substrate-responsive and less repressed by other nitrogen sources . Regulatory differences may also affect amino acid biosynthesis , since most of these pathways were expressed at higher levels in Ph . infestans than Py . ultimum both during growth in media and tubers . A third facet of variation involved species-specific genes , such as γ-amylases which occur only in Py . ultimum and presumably help it exploit the most abundant carbon source in tubers . A fourth level of variation concerned protein function , as evidenced by the divergent Km and temperature optima of the NRs . Thus , some interspecific differences were due to short-term physiological responses and others to long-term evolutionary changes . We also observed that many pathways in Ph . infestans shifted to a higher Pythium-like pattern of expression during late infection . For example , transcripts of most glycerolipid , sulfate , and starch metabolism genes in Ph . infestans rose at the late timepoint . We believe that this is the first firm evidence that Ph . infestans perceives and utilizes nutrients from lysing cells . Although the textbook description of Ph . infestans is as a hemibiotroph , necrotrophy is not equivalent to necrogeny . Whether behavior that leads to plant death is necessarily necrotrophic has been debated in several pathosystems [50] . Alternative hypotheses have included the possibility that host necrosis is not a trophic strategy but instead reflects an inability of older hyphae to deliver defense-blocking effectors , or serves to humidify the apoplast [51] . Many of our conclusions are based on studies of mRNA levels , which might not always match enzymatic activity due to post-transcriptional or translational control [52] . Metabolic flux is also a function of substrate and not just enzyme concentration [53] , and many enzymes belong to complex networks . For example , while the higher expression of glycerolipid-degrading enzymes by Py . ultimum during early tuber infection is consistent with its need to digest host membranes to access intracellular nutrient , Py . ultimum may also be more inclined to cycle its own carbon through lipids . To test whether measurements of mRNA levels were a good surrogate for pathway activity , we focused on nitrate assimilation . We found parallel changes in NR mRNA , protein , enzymatic activity , and nitrate incorporation in both species . This concordance might not hold for all pathways , however . Indeed , differences in the levels of mRNAs for metabolite biosynthesis between the species were usually not reflected in the metabolite concentrations that were measured in media . While some of this disparity might be due to post-transcriptional control , it seems that Ph . infestans and Py . ultimum use distinct blends of metabolic pathways to form the same building blocks for growth . While some mRNA patterns were caused apparently by substrate-level induction of transcription , we observed higher expression of amino acid biosynthesis genes in Ph . infestans in both tubers and rye media . This may be an evolutionary adaptation that reflects the intimate interaction between Ph . infestans and its hosts . In plants , most amino acids enter the apoplast through UMAMITs ( Usually Multiple Amino acids Move In and out Transporters; [54] ) . However , some amino acids have very low apoplastic concentrations and would thus need to be synthesized by Ph . infestans [55 , 56] . While apoplastic amino acids are known to increase during some fungal and bacterial infections , whether this happens with Ph . infestans is unknown [55 , 56] . It would be interesting to investigate whether Ph . infestans effectors alter source-sink relationships or increase apoplastic nutrients by acting on UMAMITs , similar to how bacterial effectors influence SWEET transporters [57] . Such effects may extend to other compounds such as organic or inorganic phosphates . While intracellular host compounds such as phytate may provide Py . ultimum with ample phosphorus , studies of Fusarium graminearum colonizing maize showed that phosphate levels in the apoplast are growth-limiting [58] , a situation that may also affect Ph . infestans . Some features of Py . ultimum metabolism may help it inhabit multiple niches . This species differs from Ph . infestans in being able to grow not only on plants but also in organic debris in soil , where nitrate is usually present [59] . The low Km of Py . ultimum NR may help it acquire nitrate even at low concentrations . This resembles the situation in diatoms where Km differences between Skeletonema and Thalassiosira NRs were linked to their abilities to grow in low-nitrogen environments [60] . A low Km may not benefit Ph . infestans since that species only colonizes healthy plant tissues , which provide a reliable supply of nutrients . Indeed , we have attempted to infect tomato plants cultured under low-nitrogen regimes with Ph . infestans but observed little pathogen growth . This resembles the case in Arabidopsis where host mutations that reduced amino acid levels blocked downy mildew infection [61] . Another ecological difference between Py . ultimum and Ph . infestans is that the former is a pioneer colonizer [62] . Such species outcompete other microbes by growing quickly . Py . ultimum grows rapidly , but not necessarily efficiently . This may explain why it expressed NR and NiR at similar rates in early cultures ( containing substantial amino acids and ammonium ) and older nutrient-depleted cultures , and why it incorporated nitrate equally in standard rye media and media supplemented with ammonium or glutamine . In contrast , most fungi and Ph . infestans preferentially use amino acids or ammonium to avoid expending energy to reduce nitrate [41] . Comparisons of nitrate utilization in oomycetes and fungi are thought-provoking due to the evolutionary history of the pathway , and since NR has been a model for understanding fungal gene regulation . Fungi and oomycetes share little taxonomic affinity as they belong to different kingdoms , but fungi are thought to have acquired the nitrate assimilation gene cluster from an oomycete ancestor [38] . The transfer apparently also involved the nitrogen metabolite repression regulator transcription factor NMRA , which has apparently been deleted from the Pythium lineage . The loss of repressors may aid pioneer colonizers by helping them to rapidly use all nutrients in their environment . Also , NMRA may provide little benefit to Pythium since amino acids are typically present at low levels in soil . Apparently for similar reasons , soil-inhabiting streptomycetes have rarely developed amino acid feedback repression systems for many biosynthetic pathways [63] . Divergence in the Michaelis-Menten kinetics of NR was an additional interesting finding of the study , and is consistent with emerging evidence that changes in the Km of metabolic enzymes can influence the growth characteristics of an organism [64] . The Km of Py . ultimum NR resembles that of many fungi [49] , which is logical since both are common soil inhabitants . In contrast , the Km from Ph . infestans and Ph . mirabilis was several times higher . It follows that Py . ultimum is better-suited for utilizing low levels of nitrate in the environment . This is congruent with the greater reliance of Phytophthora spp . on organic nitrogen , but an alternative theory is that their NRs evolved to help detoxify high concentrations of nitrate , which can reach ~500 mM in leaf sap [65] . A role of NR in detoxification was suggested by our earlier study in Ph . infestans , in which knockdowns of the NR gene impeded growth and pathogenicity , but only when nitrate was at high levels [47] . Pythium mutants unable to grow on nitrate have not been reported . Why Ph . infestans lost the ability to grow on nitrate is enigmatic . Phytophthora fragariae and Phytophthora megasperma also require organic nitrogen , unlike most members of the genus as well as Pythium spp . [42] . Perhaps too much use of the assimilation pathway in some species would cause an imbalance in the cellular levels of its pyrimidine nucleotide cofactors . The ability of these species to use nitrate may also have evolved in response to how that compound is mobilized in their hosts . Alternatively , balancing metabolism away from nitrate may have been an energy-saving measure to help the hemibiotrophs compete against plant defenses . This may also explain why biotrophic oomycetes and fungi have lost the nitrate assimilation pathway [40] . One technical lesson from our experience is the importance in metabolic studies of evaluating the status of a culture by assaying nutrients in the media . Inferences about the biology of plant or animal pathogens as well as other microbes are often drawn from comparing gene expression in different media , such as complex or minimal formulations [66 , 67] . However , false conclusions may be drawn if nutrient concentrations at harvest time are not known . A related topic that could enhance our understanding of metabolic regulation concerns nutrient reserves in oomycete hyphae . We observed that biomass continued to increase in older cultures even after nutrients such as free amino acids were exhausted from the media . This suggests that growth is being sustained at least partly through the use of reserves . While the roles of lipid , protein , and carbohydrate stores in spore germination are well-described , their contributions to sustaining hyphal growth or sporulation is not understood [68 , 69] . Oomycete hyphae are coenocytic and contain large vacuoles , especially in older cultures . In plants and yeast , the vacuole is an important store of nutrients [70 , 71] , and whether the oomycete organelle plays a similar role is unknown .
Predicted proteins from Ph . infestans strain T30-4 were used as inputs for the KEGG-based KAAS and BlastKoala annotation servers [20 , 21] , which predicted functions and assigned proteins to KEGG orthology ( KO ) groups . Some metabolic genes were also identified using GO terms associated with each gene . The proteins were also used as queries in BLASTP ( 2 . 2 . 31+ ) searches against the NR database using a cut-off E-value of 1e-20 , and the Conserved Domain Database ( CDD ) using a cut-off E-value of 1e-10 . If the KEGG and BLAST-derived annotations were in conflict , we relied on the BLAST result only if supported by the CDD results . Pathway information was obtained using data from KEGG , supplemented with information from Metacyc [72] and eggNOG [73] . When grouping enzymes into pathways for expression analysis , the KEGG classification was used except that separate pathways were made for genes involved in the metabolism of inorganic nitrate and sulfate . Enzyme Commission ( EC ) numbers were obtained using the Expasy database . In some cases , enzymes could not be assigned to a specific EC number and were classified as a general oxidoreductase , dehydrogenase , etc . Genes from Py . ultimum were annotated essentially as described above . In addition , orthologs between the two species were identified using OrthoMCL , and discrepancies in annotation were evaluated manually . If a protein from one species lacked orthologs in the other , a search was made of the genome assembly to identify cases where a gene was present but had failed to be annotated . In addition to searching the T30-4 assembly of Ph . infestans released in 2009 [74] , we also examined a new assembly of strain 1306 based on long-read data and optical mapping [75] . After we completed our annotations of Ph . infestans , Rodenberg et al . [76] reported identifying 1 , 301 genes by matching Ph . infestans sequences to custom hidden Markov models of metabolic proteins from other organisms . All proteins from our analysis were present within the list generated by Rodenberg et al . A second group [77] reported identifying 1 , 375 genes using the KAAS tool , but these could not be compared directly to ours since their publication did not include the gene identifiers . Analyses of sequences from other oomycetes were performed using the Fungidb . org and EuMicrobeDb . org databases [22 , 23] . The sequence of NR from Ph . mirabilis were assembled from whole-genome sequencing data deposited in Genbank . Isolate MS-1 of Py . ultimum var . ultimum was provided by Dr . M . Stanghellini and isolated from potato in Riverside County , California . It was maintained at 21°C in the dark on half-strength V8 medium containing 1 . 5% agar . Strains of Ph . infestans and Ph . mirabilis were maintained in the dark at 18°C on rye-sucrose agar [78] . These were isolate 1306 collected from tomato in San Diego County , California ( A1 mating type , pathogenic on tomato and potato ) and others provided by Drs . W . Fry and N . Grünwald including genotypes US-11 ( A1 , pathogenic on both tomato and potato ) , US-22 ( A2 , more pathogenic on tomato than potato ) , US-23 ( A1 , more pathogenic on tomato than potato ) , and US-24 ( A1 , much more pathogenic on potato ) . Strains P19917 and P19930 of P . mirabilis ( A2 and A1 mating types , from Mexico ) were purchased from a culture collection . The identity of these species was confirmed by sequence analysis of their untranscribed spacer regions . Besides growth rate measurements which used all isolates , other studies used strains MS-1 , 1306 , and P19917 . Growth curves were performed using the media described by Henninger with 10 mM nitrate or ammonium substituted for amino acids [43] . Cultures for gene expression studies were grown using rye broth , pea broth , or infected tubers . The latter used cultivar Russet Burbank as described [19] . In brief , tubers were cut into 2 mm slices using a mandoline , and placed in a clear plastic box on a metal rack above moist paper towels . Infections were performed with three biological replicates ( triplicates ) , each executed in separate weeks . For inoculations with Ph . infestans , 105 zoospores were spread on the upper surface of each tuber slice using a rubber policeman . Slices were kept at 18°C in the dark and frozen in liquid nitrogen after 1 . 5 and 4 days . Sporulation began on day 3 . Minor darkening of the host tissue was observed under the sporangia-bearing aerial hyphae . Since Py . ultimum does not produce zoospores , infections were performed by placing a 2-mm plug from the growing edge of a 2-day agar culture in the center of each tuber slice . After 1 . 5 days , tuber tissue was dissected into concentric rings representing early and late stages of colonization . The outer ( early infection ) ring included a 3-mm region comprised of one-quarter of nondiscolored tuber tissue and three-quarters reddish brown tissue . The inner ( late infection ) ring included 3-mm of black tissue . Other defined media tested included those described by Hohl [42] , Xu [79] and Scheepens et al . [80] . Broth cultures used for mRNA , protein , or metabolite studies used 100 or 150-mm diameter plates with 3 . 1 μl of media per mm2 . RNA was obtained from the strains described above by grinding tissue to a powder under liquid nitrogen , followed by extraction using Sigma Plant RNA kits . RNA-seq was performed as described and the data are available at NCBI GEO under Bioproject PRJNA407960 [19] . In brief , after quality control indexed libraries were prepared using the Illumina Truseq kit v2 . Paired-end libraries were quantitated by Qubit analysis , multiplexed and sequenced using Illumina technology . Reads passing the quality filter were aligned to each pathogen’s genome using Bowtie 2 . 2 . 5 and Tophat 2 . 0 . 14 , allowing for one mismatch . This used the reference genomes of Ph . infestans isolate T30-4 and Py . ultimum isolate DAOM BR144 [74 , 81] . Expression and differential expression calls were made with edgeR using TMM normalization , a generalized linear model , and FDR calculations based on the Benjamini-Hochberg method [82] . However , most comparisons in this paper were performed using FPKM values to minimize artifacts resulting from errors in gene models . For studying the aggregate expression of pathways , genes were grouped by metabolic pathway according to the assignments in S1 Table , and then their FPKM values were added together . Many enzymes were represented in multiple pathways . Genes predicted to encode proteins with very broad activities , such as genes annotated unclassifiable oxidoreductases/dehydrogenases , were generally excluded from the analysis . RT-qPCR was performed as described [19] . In brief , primers ( S2 Table ) were designed to amplify bands from the 3′ end of genes . cDNA made using the Maximal First-Strand RT-PCR Kit were analyzed using a CFX Connect System ( Biorad ) using Dynamo HS SYBR Green qPCR kit ( Thermo Scientific ) . Assays were based on a minimum of two biological replicates using three technical replicates per tissue sample . Control amplifications were performed using no reverse transcriptase , and melt curves confirmed the fidelity of the amplification . Gene expression was normalized using the gene for ribosomal protein S3A . Expression data from Ph . capsici were obtained from ArrayExpress accession E-MTAB-5620 . Reported in Results are the median-normalized expression values from 8 and 24 hr dpi , based on three biological replicates [48] . Expression of the Hmp1 , Npp1 , and Cdc14 marker genes indicated that these timepoints represent biotrophic and necrotrophic stages similar to the early and late tuber timepoints described for Ph . infestans . For calculations of nitrate and ammonium from plant samples , materials were weighed , lyophilized , ground into a fine powder using an electric mill , and provided to the Analytical Lab of the University of California , Davis for analysis . Nitrate and ammonium were assayed using a diffusion-conductivity method followed by conductivity detection [83] . Free amino acids in tubers were analyzed in-house from similar materials using a ninhydrin assay method against extracts made using 10 mM HCl and with glycine as a standard , after eliminating proteins by sodium tungstate precipitation [84] . To determine ammonium and amino acid levels in spent media , broth was separated from hyphae by filtration , frozen , and provided to the Molecular Structure Facility at the University of California , Davis for analysis . Samples were acidified with sulfosalicyclic acid to remove protein prior to analysis using a Hitachi L-8900 . Samples were spiked with aminoethylated cysteine to allow quantification . Lipid determinations were carried out using a solvent extraction method [85] . This involved harvesting hyphae by vacuum filtration on Whatman type 54 paper , and then adding to 1 . 5 g of ground tissue 10 ml of chloroform plus 5 ml of methanol . After shaking at 125 rpm for 30 min , 4 ml of 0 . 73% NaCl was added to produce a 2:1:0 . 8 mixture of chloroform:methanol:water ( v/v/v ) . After further shaking , the mixture was passed through a Whatman GF/C filter and phases were separated by centrifugation at 350 ×g for 3 min . The bottom organic layer was then transferred to an aluminum planchet , dried , and weighed on a vintage Mettler B6 analytical balance . Untargeted metabolomics was performed using mycelia harvested from rye media broth cultures at the timepoints described in Results . Hyphae were rinsed in water to remove media and harvested by vacuum filtration . After weighing the samples , they were frozen in liquid nitrogen and provided to the West Coast Metabolomics Center at the University of California-Davis for analysis . This involved separation by gas chromatography followed by analysis by mass spectrometry . Compounds were identified using in-house spectra and standards from Massbank of North America . Isotopic enrichment analysis was performed by spiking the broth media with 10 mM of the 15N compounds described in the text , using six biological replicates , and harvesting the samples at the "early" and "late" timepoints as defined in the text . Data analyses determined relative levels of each metabolite and the 15N/14N percent atom enrichment . The results may be approximate due to kinetic isotope effects [86] . Hyphae were grown in clarified rye media with or without 10 mM nitrate . For assays of enzyme activity , cultures were harvested at the early and late timepoints by vacuum filtration and rinse with water to remove nitrate . Tissue was ground under liquid nitrogen and the resulting powder mixed with extraction buffer ( 20 mM Tris-HCl pH 8 . 0 , 150 mM NaCl , 10 mM EDTA , 0 . 2% NP-40 , 0 . 02 mg/ml Heparin , 1mM PMSF , 1 . 5 mM DTT ) . After mixing on ice for 30 min , the mixture was centrifuged at 5000 ×g for 15 min at 4°C , and the supernatant was used for enzyme assays . A direct nitrate assay based on a protocol from Sigma Aldrich was then used . Assays were performed in 1 ml of 53 mM potassium phosphate buffer pH 7 . 5 , 5 μM flavine adenine dinucleotide ( FAD ) , 0 . 2 mM β-nicotinamide adenine dinucleotide phosphate ( β-NADPH ) , and 10 mM potassium nitrate solution ( or water for blanks ) . Protein extract ( 20 , 20 , and 40 μl for Ph . infestans , Py . ultimum , and Ph . mirabilis , respectively ) , typically containing 100 to 200 μg of protein , was added to start the reaction and the oxidation of NADPH at room temperature was followed at 340 nm , with timepoints taken at approximately 15 minute intervals over 2 hr . Assays were performed at 21°C , except as indicated in Results . All were done with three independent biological replicates . Protein concentrations were determined using a BCA assay kit ( Pierce ) . Determinations of Km were performed with late timepoint samples grown with 10 mM nitrate using nine concentrations of nitrate ( 2-fold dilutions ) ranging from 0 to 8000 μM . A graph of the rate of reaction ( μmole min-1 ) versus nitrate concentration ( μM ) was plotted and Km estimated by non-linear regression analysis [87] . These determinations used extracts from the oomycetes and enzyme from A . niger from Sigma-Aldrich . Polyclonal antibodies against NR were obtained from Agrisera ( catalog number AS08 310 ) . Blotting was performed using HRP-labeled anti-rabbit IgG as described [88] . As a positive control , the Ph . infestans gene was expressed by cloning a PCR-amplified fragment into the BglII/HindIII sites of pBAD/HISB ( Invitrogen ) . Protein was prepared from arabinose-induced TOP10 E . coli cells , which were boiled in sample buffer prior to electrophoresis . As a negative control , protein was obtained from two transformants silenced for the Ph . infestans NR gene [47] . | A key feature of disease is the pathogen's consumption of host metabolites to support its growth and multiplication . Understanding how host nutrients are used by pathogens may lead to strategies for limiting disease , for example by developing inhibitors of metabolic pathways needed for pathogen growth . Feeding strategies of plant pathogens range between two extremes: necrotrophs kill host cells and consume the released nutrients , while biotrophs do not injure host cells but instead acquire nutrients from extracellular spaces in the plant . In this study , a comparison was made between the metabolism of Phytophthora infestans ( the infamous Irish Famine pathogen ) and Pythium ultimum during potato tuber colonization . These microbes have close evolutionary histories , but while Py . ultimum is a necrotroph , Ph . infestans is a biotroph for most of the disease cycle . It was discovered that distinct patterns of metabolic gene expression , gene content , and enzyme behavior underlie these lifestyles . For example , genes for utilizing compounds that are normally stored within plant cells were expressed more by Py . ultimum , while Ph . infestans appeared to synthesize more biosubstances from precursors . Several differences in carbon and nitrogen metabolism were linked to variation in enzyme content and gene expression regulators in the two species . | [
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"chem... | 2019 | Niche-specific metabolic adaptation in biotrophic and necrotrophic oomycetes is manifested in differential use of nutrients, variation in gene content, and enzyme evolution |
Hedgehog ( Hh ) signaling is essential for normal growth , patterning , and homeostasis of many tissues in diverse organisms , and is misregulated in a variety of diseases including cancer . Cytoplasmic Hedgehog signaling is activated by multisite phosphorylation of the seven-pass transmembrane protein Smoothened ( Smo ) in its cytoplasmic C-terminus . Aside from a short membrane-proximal stretch , the sequence of the C-terminus is highly divergent in different phyla , and the evidence suggests that the precise mechanism of Smo activation and transduction of the signal to downstream effectors also differs . To clarify the conserved role of G-protein-coupled receptor kinases ( GRKs ) in Smo regulation , we mapped four clusters of phosphorylation sites in the membrane-proximal C-terminus of Drosophila Smo that are phosphorylated by Gprk2 , one of the two fly GRKs . Phosphorylation at these sites enhances Smo dimerization and increases but is not essential for Smo activity . Three of these clusters overlap with regulatory phosphorylation sites in mouse Smo and are highly conserved throughout the bilaterian lineages , suggesting that they serve a common function . Consistent with this , we find that a C-terminally truncated form of Drosophila Smo consisting of just the highly conserved core , including Gprk2 regulatory sites , can recruit the downstream effector Costal-2 and activate target gene expression , in a Gprk2-dependent manner . These results indicate that GRK phosphorylation in the membrane proximal C-terminus is an evolutionarily ancient mechanism of Smo regulation , and point to a higher degree of similarity in the regulation and signaling mechanisms of bilaterian Smo proteins than has previously been recognized .
The Smoothened ( Smo ) family of seven-pass transmembrane proteins initiate cytoplasmic Hedgehog ( Hh ) signaling . Smo proteins are activated by multisite phosphorylation in the cytoplasmic C-terminal tail , which counteracts the electrostatic effects of adjacent clusters of positively charged residues thought to maintain the protein in an inactive conformation . Upon phosphorylation , Smo undergoes a conformational change , dimerizes , and accumulates at the plasma membrane ( Drosophila ) or primary cilium ( mammals ) , and activates downstream signaling , leading to stabilization of Ci/Gli family transcription factors and Hh target gene expression [1]–[3] . Smo is phosphorylated in a graded manner , with higher levels of Hh ligand inducing more extensive phosphorylation and thereby driving expression of higher-threshold target genes [2] , [4] . Although the extracellular N-terminus and seven-transmembrane regions of Smo are highly conserved , only the first 100 amino acids of the cytoplasmic C-terminus is broadly conserved . The more distal C-terminus , in many cases hundreds of amino acids long , is completely divergent in different phyla . Because they target different portions of the C-terminus , the phosphorylation mechanisms regulating Smo differ fundamentally between invertebrates and vertebrates . In Drosophila , phosphorylation at three clusters of Protein kinase A ( PKA ) and Casein kinase I ( CKI ) sites located in the Smo autoinhibitory domain ( SAID ) is necessary and sufficient for activation [5]–[7] . However , neither the SAID nor the critical PKA sites in Drosophila Smo are conserved in vertebrate Smo proteins; instead G-protein-coupled receptor kinase ( GRK ) 2 and CKI are the principal kinases that activate vertebrate Smo proteins by phosphorylating them at a different set of sites [2] . The means by which Smo engages the downstream signaling machinery through its C-terminus also appears to have diverged . In Drosophila and vertebrates , Smo binds to the downstream effector Cos2 and its orthologue Kif7 , respectively [8]–[10] . In addition to a negative role in Hh signaling , Cos2 and Kif7 are required for full activation of the pathway [11]–[13] , likely in the case of Cos2 because it helps to recruit the kinase Fused to Smo and to activate it [14] . Previous studies localized two separate binding sites for Cos2 in the Drosophila Smo C-terminus [8] , [9] , neither of which is conserved in vertebrates . Given that Drosophila and vertebrate Smo signal through similar effectors [3] , this divergence has been puzzling [15] . GRKs are also implicated in Smo activation in Drosophila . Gprk2 , one of the two Drosophila GRKs , is required for Smo to drive high-threshold Hh target gene expression [16]–[18] . Two pairs of Gprk2 phosphorylation sites ( called GPS1 and GPS2 ) have been mapped to the non-conserved portion of the Smo C-terminus , with phosphorylation at GPS1 suggested to contribute to the charge mechanism that overcomes inhibition by the SAID [18] . Dimerization of the kinase itself was also suggested to help promote Smo dimerization and activation in a catalytic-activity-independent manner [18] . On the other hand , loss of gprk2 causes a reduction in cyclic AMP ( cAMP ) levels , affecting PKA-dependent Smo activation . Target gene expression can be largely rescued in gprk2 mutants by increasing cAMP levels , suggesting that this indirect effect of Gprk2 on Smo plays an important role in Hh pathway function [19] . To further explore the effects of direct Gprk2 phosphorylation on Smo activity , we mapped four new clusters of Gprk2-dependent phosphorylation sites in the cytoplasmic C-terminus . We find that mutation of these sites to non-phosphorylatable residues reduces Smo dimerization and its ability to promote Hh target gene expression . Phosphomimetic mutations bypass the requirement for Gprk2 . Importantly , the phosphosites we mapped overlap with CKI/GRK sites mapped in the mouse Smo C-terminus , and are remarkably well-conserved in Smo orthologues throughout the bilaterian lineages . We demonstrate that the evolutionarily conserved core of Smo is a functional , GRK-regulated protein that is sufficient to activate downstream signaling , suggesting that all bilaterian Smo proteins share a common regulatory and signaling mechanism .
To assess their functional importance , we tested the effects of mutating the Gprk2 phosphosites using ptc-luciferase ( ptc-luc ) transcriptional reporter assays [22] in S2-R+ cells . In control experiments , gprk2 depletion using a mix of dsRNAs targeting the gprk2 5′- and 3′-untranslated regions ( UTRs ) significantly reduced both Smo phosphorylation and ptc-luc reporter activity in SmoSD-GFP transfected cells ( Figure S3A and B ) . Both effects could be rescued by expressing a wild-type gprk2 transgene lacking the UTRs , but not catalytically inactive mutants ( Figure S3A and B ) . gprk2 depletion had a similar effect on Hh-dependent signaling by endogenous Smo ( Figure S3C ) . Thus the effects of Gprk2 on Smo activity in S2 cells accurately reflect what is observed in vivo [18] . Mutation of all four Gprk2 phosphorylation clusters in the SmoSD background to Ala ( SmoSD . c1-4A-GFP ) reduced ptc-luc reporter activity by 80% compared to SmoSD-GFP , but did not eliminate it ( Figure 2A ) . Mutation of the four cluster 1 ( SmoSD . c1A ) or six cluster 2 ( SmoSD . c2A ) sites reduced SmoSD-GFP-driven ptc-luc reporter transcription , but both were significantly more active than SmoSD . c1-4A-GFP ( Figure 2A ) . Mutation of the five cluster 3 sites ( SmoSD . c3A ) had less effect , while mutation of the three sites in cluster 4 ( SmoSD . c4A ) had no significant effect on activity ( Figure 2A ) . Consistent with our observations in vivo , mutation of the GPS1 and 2 sites also had no significant effect on Smo activity ( Figure 2A ) . Steady-state levels of the various Gprk2 phosphorylation site Smo mutants were similar ( Figure S4A ) . We conclude that phosphorylation at clusters 1 and 2 , and to a lesser extent at cluster 3 , is required for full Smo activation . In tests of SmoSD-GFP transgenes bearing mutations in only a subset of sites within cluster 1 or 2 , we found that no subset impaired activity as much as mutating all sites within a cluster ( Figure S5A ) . We conclude that phosphorylation at many sites rather than a critical activating residue is important for Smo activity . The partial effect on activity when only some sites are mutated suggests that Gprk2 phosphorylation affects Smo activity in a graded manner . Next , we tested if mimicking the charge effect of Gprk2 phosphorylation at Smo clusters 1 and 2 could compensate for the lack of phosphorylation in Gprk2-depleted cells . In control cells , the Asp-substituted phosphomimetic SmoSD . c12D-GFP mutant was ∼25% less active than SmoSD-GFP ( Figure 2B ) . This may be because substituting Asp introduces less negative charge than does Ser/Thr phosphorylation under physiological conditions [23] . Importantly , the activity of SmoSD . c12D-GFP was unaffected by Gprk2 depletion ( Figure 2B ) . This insensitivity to Gprk2 required Asp substitution in both clusters , as each single cluster mutant ( SmoSD . c1D and SmoSD . c2D ) showed only a partial resistance to depletion of the kinase ( Figure 2B ) . Thus mimicking phosphorylation of SmoSD by Gprk2 at clusters 1 and 2 circumvents the requirement for the kinase itself . To confirm that the effects on SmoSD activity we observed reflect the normal situation , we mutated the Gprk2 phosphosites in a wild-type Smo background . To minimize any complication arising from endogenous Smo activity , we depleted it by treating the cells with smo 3′-UTR dsRNA . Smo depletion was efficient , reducing Hh-stimulated ptc-luc reporter activity by 86% ( Figure 2C ) . As expected , re-expressing a wild-type smo-gfp transgene made insensitive to the dsRNA by removing the 3′-UTR ( SmoWT-GFP ) restored Hh responsiveness ( Figure 2C ) . Mutation of all four Gprk2 phosphorylation clusters to Ala ( Smoc1-4A-GFP ) strongly impaired this rescue ( Figure 2C ) . Analysis of single cluster mutants confirmed that this was mainly attributable to mutation of clusters 1 and 2 ( Figure S5B ) . In cell surface biotinylation assays , we did not detect any effect of Gprk2 phosphosite mutations on the ability of Smo to traffic to the plasma membrane in response to Hh ( Figure S4B ) . We conclude that wild-type Smo shows a similar dependence on Gprk2 phosphorylation for full activity as SmoSD . Unlike PKA and CKI phosphorylation [5] , Gprk2 phosphorylation was not sufficient to constitutively activate Smo , as the activity of Smoc12D-GFP was as dependent on Hh as SmoWT-GFP ( Figure 2D ) . It was also not sufficient to enable Hh-dependent activation of Smo that has all three PKA sites in the SAID mutated to Ala ( in SmoSA . c12D ) ( Figure 2D ) . These results suggest that Gprk2 acts downstream of PKA to enhance Smo activity in Hh-responding cells , consistent with the idea that GRKs preferentially phosphorylate GPCRs in their activated state [24] . Phosphorylation by PKA and CKI triggers dimerization of Smo C-terminal tails , which promotes high-level signaling activity [1] . To see if direct phosphorylation by Gprk2 affects Smo dimerization , we adapted previously-described biosensors [1] for use in bioluminescence resonance energy transfer ( BRET ) experiments to measure SmoSD dimerization in intact cells . In control experiments , co-expression of SmoSD molecules C-terminally-tagged with GFP10 ( SmoSD-GFP10 ) and Renilla luciferase II ( SmoSD-Luc ) yielded a net BRET signal between the two which responded to Gprk2 . Gprk2 overexpression , which increased SmoSD-GFP phosphorylation ( Figure S3B , lanes 1 and 3 ) , also significantly increased net BRET ( Figure 2E ) . Conversely , gprk2 depletion significantly reduced net BRET ( Figure 2E ) , consistent with a previous report [18] . Re-expressing Gprk2 restored the BRET signal in gprk2-depleted cells ( Figure 2E ) , confirming the specificity of the effect of Gprk2 on SmoSD dimerization . Importantly , the cluster 1 and 2 phosphomimetic mutations eliminated the effect of gprk2 depletion on SmoSD dimerization ( Figure 2F ) . Thus , as in the ptc-luc reporter assay , mimicking phosphorylation of SmoSD at clusters 1 and 2 circumvented the requirement for Gprk2 . Taken together , the results of our functional studies suggest that Gprk2 directly enhances dimerization of active Smo by phosphorylating it at clusters 1 and 2 , driving it into or stabilizing its most active state . gprk2 mutant animals display several defects , including ectopic accumulation of Smo in Hh-responding cells and strong impairment or loss of intermediate/high but not low threshold target gene expression in the developing wing imaginal disc . To determine to what extent loss of direct phosphorylation of Smo by Gprk2 contributes to these defects , we expressed the wild-type and mutant forms of the protein during wing development . All transgenes were recombined into the same site in the genome using the ΦC31-based integration system [25] to ensure equal mRNA expression . For analysis of mutations in the SmoWT background , we co-expressed a smo 3′-UTR dsRNA transgene to deplete endogenous Smo . Expression of this dsRNA ( together with GFP as a negative control ) throughout the developing wing disc using the nub-GAL4 driver strongly suppressed Hh signaling , leading to loss of the central region of the adult wing patterned by Hh ( Figure 3A and B ) . Reintroduction of SmoWT-GFP fully rescued wing development and induced mild perturbations of anterior patterning indicative of Hh gain-of-function ( Figure 3C and E ) . Smoc1-4A-GFP had less activity , with no sign of gain-of-function phenotypes ( Figure 3D ) . However , it rescued development of the central region of the wing , restoring growth to about 84% of the normal size ( Figure 3D and E ) , suggesting that loss of direct Gprk2 phosphorylation has relatively mild effects on Smo activity in vivo . Analysis of Hh target gene expression in wing discs led us to a similar conclusion . Expression of smo 3′-UTR dsRNA in the dorsal compartment of the disc using ap-GAL4 eliminated expression of the intermediate threshold target gene ptc and high threshold target anterior en , and strongly reduced expression of the low threshold target dpp ( Figure 4A and B ) . Reintroducing SmoWT-GFP in this background restored Hh-dependent expression of all three genes , with signs of weak ectopic dpp and ptc expression apparent in far anterior cells ( Figure 4C and D ) . In contrast , Smoc1-4A-GFP rescued low ( dpp ) but not high ( en ) threshold target gene expression ( Figure 4E and F ) , matching observations in gprk2 mutants [16]–[18] . Hh-dependent expression of ptc was partially rescued ( Figure 4E ) . However , Ptc levels in Smoc1-4A-GFP-expressing dorsal cells were higher than is typically seen in gprk2 mutants , consistent with the observation that reduced levels of cAMP and PKA also contribute to the impairment of Hh signaling activity in the absence of Gprk2 [19] . The Gprk2 phosphosite mutations had a similar partial effect on the activity of SmoSD . Hh-independent ectopic expression of anterior en [5] was substantially lower in SmoSD . c1-4A-GFP-expressing discs than in those expressing SmoSD-GFP , but was still readily detectable ( Figure 4G and H ) . As in S2 cells , mimicking Gprk2 phosphorylation restored the ability of SmoSD to drive strong ectopic en expression in gprk2 mutant discs ( Figure 4I and J ) . Taken together , our in vivo analyses support the conclusion that direct phosphorylation by Gprk2 is not essential for Smo activity , but enhances it to its highest level . Interestingly , the cluster 1–4 Ala-substituted form of Smo faithfully phenocopied the effects of Gprk2 loss on Smo accumulation . In discs depleted of endogenous Smo , wild-type Smo-GFP accumulated in the normal pattern [26] , including low levels in most anterior Hh-responding cells ( identified by high levels of stabilized Ci ) ( Figure 4K , bracket ) . In contrast , Smoc1-4A-GFP accumulated ectopically in Hh-responding cells ( Figure 4L , bracket ) , as endogenous Smo does in gprk2 mutants [16] , [18] . We conclude that Gprk2 phosphorylation is required for the downregulation of Smo seen in cells where the Hh signaling pathway is active . Broad sequence conservation in the cytoplasmic C-terminus of Smo is limited to the membrane-proximal 100 amino acids ( up to amino acid 651 in Drosophila Smo - see Figure 5A ) . The remaining 385 amino acids of Drosophila Smo , including the SAID , PKA/CKI sites , and binding sites for the kinesin-like protein Cos2 [8] , [9] are only conserved among arthropods . The absence of PKA sites in vertebrate Smo orthologues was recently explained with the identification of GRK2 and CKI as the activating kinases for these proteins . GRK2 and CKI phosphorylate twelve sites in the cytoplasmic tail of mSmo , inducing a change to an active conformation , possibly by neutralizing a nearby stretch of basic amino acids as in flies [1] , [2] . Most of these sites are conserved in vertebrate Smo orthologues , suggesting that PKA and CKI together replace the function of PKA in activating vertebrate Smo through a mechanism that is similar to , but molecularly distinct from , that in flies [2] . In broader sequence alignments that include Smo orthologues from each of the three main bilaterian clades , we noted that the Gprk2 phosphorylation sites we mapped in Drosophila Smo overlap with the mSmo phosphorylation sites and show a remarkable degree of conservation in other species ( Figure 5A ) . In total , eight of the sites in Gprk2 clusters 1–3 correspond to phosphorylation sites in mSmo that are nearly universally conserved throughout the bilaterians , either as Ser/Thr residues or as Asp/Glu residues ( consistent with the evolution of phosphosites from functionally similar negatively charged residues [23] ) . The first two clusters ( PS0 and PS1 ) in mSmo , which contain most of the conserved sites , were functionally the most important [2] , as are the corresponding cluster 1 and 2 sites in Drosophila . Thus both at the level of sequence and function , the Gprk2/GRK2/CKI phosphorylation sites appear to represent an evolutionarily ancient and conserved mechanism of Smo regulation . If they share a common regulatory mechanism , we hypothesized that the bilaterian Smo orthologues may also have retained the activity of the ancestral form of Smo that was being regulated , i . e . they may share a conserved molecular signaling mechanism . To address this , we tested the effects of expressing just the highly conserved portion of Smo ( Smocore - amino acids 1–663 , truncated just after the broadly conserved third Gprk2 phosphorylation cluster; Figure 5A ) on Hh target gene expression . Consistent with our hypothesis , we found that Smocore was capable of activating ptc-luc reporter expression in endogenous Smo-depleted cells , to about 25% the level of SmoSD ( Figure 5B ) . This constitutive activity of Smocore was strongly reduced or abolished by gprk2 depletion or mutation of the Gprk2 phosphorylation sites ( Smocore . c1-3A ) , respectively ( Figure 5C ) , indicating that Smocore-GFP activity is regulated by Gprk2 phosphorylation . In endogenous Smo-depleted wing discs , Smocore-GFP rescued Hh-dependent expression of dpp , ptc , and even en ( though en levels remained lower than wild-type ) ( Figure 5D and E ) , as well as overall wing development ( Figure 3F ) . It also drove ectopic expression of dpp and ptc ( Figure 5D ) , producing anterior Hh gain-of-function phenotypes in adult wings that were even stronger than those observed with SmoWT-GFP ( Figure 3F ) . Consistent with the results of ptc-luc reporter assays , Smocore . c1-3A-GFP displayed no ability to rescue target gene expression in endogenous Smo-depleted discs ( Figure 5F and G ) . Similarly , when expressed in gprk2 mutant discs , the ability of Smocore-GFP to activate ptc expression was lost , and it appeared to inhibit the residual ptc expression resulting from endogenous Smo activity ( Figure 5H ) . Thus , as in the S2 cell assays , signaling in vivo was dependent on phosphorylation by Gprk2 . We conclude that the highly conserved core of Smo is a GRK-regulated protein that contains sequences sufficient for activating downstream signaling . Interestingly , deleting the C-terminus altered the pattern of Smo accumulation in discs in a manner that was inversely correlated with its activity . Normally , Smo levels are low in the far A compartment , where Smo is inhibited by the activity of Ptc , and high in the P compartment and first few rows of A Hh-responding cells , where Smo activity is high because Ptc is either not expressed ( P compartment ) or strongly inhibited by Hh ( e . g . Figure 4K ) . In contrast , Smocore-GFP levels were highest in far A cells where Smocore activity is lowest , and low throughout the Hh-responsive A zone and P compartment , where Smocore activity is expected to be highest ( Figure 5I ) . This pattern is reminiscent of the regulation of many GPCRs , which undergo GRK phosphorylation-dependent internalization and , in many cases degradation , after being activated [27] . Removing Gprk2 or mutating its phosphorylation sites eliminated the downregulation of Smocore in cells where the Hh pathway is strongly activated ( Figure 5J and K ) , indicating that the effect is indeed the result of direct phosphorylation . Thus Gprk2 controls both the accumulation and activity of Smocore , as GRK2 does ciliary accumulation and activity of mSmo [2] . In Drosophila and vertebrates , Smo binds to Cos2 and its orthologue Kif7 , respectively [8]–[10] , and these proteins are required for full activation of the pathway [11]–[13] . To see if Smocore recruits Cos2 , we adapted previously-described FRET biosensors [14] to measure Cos2-Smocore interaction by BRET . Co-expression of Smocore C-terminally-tagged with GFP10 ( Smocore-GFP10 ) and Cos2 C-terminally tagged with Renilla luciferase II ( Cos2-Luc ) yielded a net BRET signal that was responsive to Gprk2 . Gprk2 overexpression increased Smocore-Cos2 BRET more than 2 . 2-fold , whereas gprk2 depletion reduced it by 60% ( Figure 6A ) . The effects were specific , as re-expressing Gprk2 in gprk2-depleted cells fully rescued Smocore-Cos2 BRET ( Figure 6A ) . Smocore . c1-3A mimicked the effect of gprk2 depletion on Smocore-Cos2 interaction , even after depletion of endogenous Smo ( ruling out the possibility that the BRET signal is due to interaction of Cos2-Luc with endogenous Smo in Smo/Smocore oligomers ) ( Figure 6B ) . These results suggest that Smocore recruits Cos2 , in a Gprk2 phosphorylation-dependent manner . Previous studies localized separate binding sites for Cos2 in the Smo C-terminus between amino acids 651–686 and 818–1035 [8] , [9] , most of which is missing in Smocore . To see if the Cos2 recruitment activity we observed was due to binding between amino acid 651 and the end of Smocore at amino acid 663 , we made a further truncation to amino acid 651 ( see Figure 5A ) . SmoΔ651 interacted with Cos2 in the BRET assay even more efficiently than Smocore , in endogenous Smo-depleted cells ( Figure 6B ) , indicating that recruitment was not to the previously mapped sites . Further truncation to amino acid 625 ( SmoΔ625 ) , just N-proximal to Gprk2 phosphorylation cluster 2 ( Figure 5A ) , eliminated Cos2 recruitment ( Figure 6B ) . Importantly , the ability of these truncated Smo proteins to recruit Cos2 correlated with their activity in ptc-luc reporter assays ( Figure 6C ) . We confirmed that all proteins were expressed at similar levels ( Figure S6 ) . These results suggest that the region between 625 and 651 contains a novel Cos2 binding site that positively transduces signals downstream of Smo . Unlike previously mapped sites , this one is located in a region that is broadly conserved among bilaterian species .
GRKs tend to phosphorylate multiple Ser/Thr residues within short stretches of amino acids in their GPCR substrates [29]–[32] . We identified 18 Ser/Thr residues in four such clusters in the Smo C-terminus , mutation of which abolished Gprk2-dependent phosphorylation . Of these , we confirmed by LC-MS/MS analysis that 10 sites ( Ser604 , Thr606 , Thr610 , Thr612 , Ser658 , Ser659 , Ser660 , Ser675 , Ser679 , Ser682 ) are phosphorylated by Gprk2 , with Ser604 , Thr610 , and Thr612 being further validated using phosphospecific antisera . Two of the sites in cluster 3 ( Thr551 and Thr555 ) are likely not Gprk2 targets , as we did not detect phosphorylation at either site in control cells . We did not obtain peptide coverage in the region containing the remaining six sites ( Ser626 , Ser627 , Thr629 , Ser633 , Ser634 , and Ser635 ) , which make up cluster 2; however , phosphorylation at four of these sites has been observed by others [6] . Our results suggest that Gprk2 does phosphorylate at least some of these residues , since phosphomimetic mutations in cluster 2 are required to fully rescue Smo activity in gprk2-depleted cells . In mSmo , CK1 phosphorylates the sites corresponding to cluster 1 whereas GRK2 phosphorylates cluster 2 [2] . The role of CKI does not seem to be conserved , as CKI depletion had no appreciable effect on phosphorylation of the sites we mapped in Drosophila Smo ( Figure S7 ) . We observed Gprk2-dependent changes in phosphorylation at the GPS1 sites by LC-MS/MS but they were relatively small , suggesting that another kinase also phosphorylates these sites . In total , then , Gprk2 appears to be the principle kinase responsible for phosphorylating between 11 and 16 sites in the Drosophila Smo C-terminus . Gprk2 regulates Smo stability and activity , with both effects mediated at least partly through direct phosphorylation . Several observations indicate that Gprk2 directly enhances Smo activity in Hh-responding cells . The extent of the conformational shift that Smo undergoes upon activation is lower in gprk2-depleted cells , indicative of a lower activity state [18] . We confirmed previous observations that its ability to dimerize is also partly compromised [18] . The result is less robust activation of target gene expression . The reduced activity of Smo mutants with Ala substitutions at the Gprk2 phosphorylation sites in ptc-luc reporter assays confirms that Gprk2 enhances Smo activity by phosphorylating it . In particular , phosphorylation at clusters 1 and 2 seems to be critical , as Ala substitutions at these clusters caused the strongest impairment of target gene activation whereas phosphomimetic substitutions at both rendered Smo resistant to the effects of gprk2 depletion , as assessed by dimerization and target gene activation . The latter observations strongly argue against Gprk2 having a catalytic activity-independent function in regulating Smo , as has been suggested [18] . The effects of mutating the Gprk2 phosphorylation sites in Smo were more subtle in vivo than in ptc-luc reporter assays in S2 cells . We speculate that this is due to the artificial nature of the ptc-luc reporter assay itself . Although SmoSD expression or Hh treatment can yield 50-fold or more activation of the reporter , proteins that induce a ∼10-fold increase in these assays ( SmoSD . c1-4A , Smocore ) are capable of activating most target gene expression in vivo . Activity above this level may simply be non-physiological . Although Gprk2 phosphorylation contributes to activating Smo , it is neither necessary nor sufficient . Smo activation appears to be a two-step process , with phosphorylation by PKA and CKI in the SAID serving as the principal trigger ( Figure 7A and B ) . SAID phosphorylation has at least two effects . First , it inhibits Smo ubiquitination and its subsequent endocytosis and degradation , leading to Smo accumulation at the cell surface [33] , [34] . Second , it promotes Smo dimerization and a shift to a more active conformation [1] . In our analysis , mimicking PKA/CKI phosphorylation at all nine sites was sufficient for full expression of all target genes except en , which was only partially activated , independent of Gprk2 . Thus full PKA/CKI phosphorylation is sufficient to strongly , but not completely , activate Smo . Full activation requires phosphorylation by Gprk2 . Mimicking Gprk2 phosphorylation alone had no effect on Smo activity in the absence of Hh , nor could it activate in the absence of phosphorylation by PKA/CKI . This could be because access to the Gprk2 sites is blocked without prior PKA/CKI phosphorylation . However , it seems more likely that the effect of PKA/CKI in controlling accumulation of Smo at the cell surface , where GRKs are typically localized [35] , limits the influence of Gprk2 on Smo . Once Smo accumulates at the cell surface , Gprk2 appears to phosphorylate it constitutively . PKA and CKI phosphorylation disrupts electrostatic interactions between the SAID domain and the distal C-terminus , thereby promoting a more open and active Smo conformation [1] . Gprk2 phosphorylation appears to act by a different mechanism . The functionally important Gprk2 phosphorylation sites are not located in the SAID domain , and Gprk2 phosphorylation regulates the activity of the truncated Smocore protein that lacks both the SAID domain and distal C-terminus . These observations favour a model in which Gprk2 phosphorylation more directly affects the conformation of the proximal C-terminus or seven transmembrane domain portion of Smo to enhance its activity . Previous studies have shown that Gprk2 promotes Smo internalization and degradation in response to Hh [16]–[18] . The Smoc1-4A mutant accumulated ectopically in wild-type Hh-responding cells , as endogenous Smo does in gprk2 mutants , demonstrating that Gprk2 triggers Smo turnover by directly phosphorylating it . This is consistent with the typical role of GRKs in receptor desensitization , and supports the conclusion that Gprk2 phosphorylation limits the duration of Smo signaling [16] . The striking conservation of the first two Gprk2 phosphorylation clusters in all bilaterian Smo proteins clearly points to an ancient origin and common function . Indeed , there are some parallels between the functions of Gprk2 phosphorylation of Drosophila Smo and GRK2/CKI phosphorylation of mSmo [2] . In both cases , it is the same two membrane-proximal clusters that are most important for function . Ala substitution of these sites in either protein impairs dimerization of the C-terminal tail and target gene expression . In both cases , the magnitude of the effect correlates with the number of substitutions , implying that phosphorylation at these sites can activate Smo in a dose-dependent manner . Phosphorylation at these sites also controls trafficking of Smo in Hh-responding cells in both systems , being required for Shh-dependent ciliary translocation of mSmo and for Hh-dependent internalization and downregulation of Drosophila Smo . One important difference is that GRK phosphorylation is required and sufficient for Smo activation in mammals but not flies . In this regard , mSmo behaves more like the truncated Smocore protein ( Figure 7C and D ) . Our analysis indicates that Smocore contains all the sequences necessary for activating downstream signaling , although it may do so less effectively than full-length Smo . Like mSmo , Smocore signaling is strongly or completely inhibited by Ala substitution of Gprk2 clusters 1–3 , or by removal of the kinase , indicating that it is strictly dependent upon phosphorylation by Gprk2 . Smocore displays some constitutive activity . However , it is also regulated by Ptc . For example , in Smocore-GFP-expressing discs , cells that have higher Ptc activity ( such as those in the far A ) express target genes at lower levels than Hh-responding cells at the A/P boundary . Ptc overexpression in S2 cells reduces Smocore-driven ptc-luc reporter expression ( not shown ) . Because Ptc downregulates full-length Smo through a mechanism involving ubiquitination of the SAID [36] , the absence of this domain in Smocore could explain its accumulation in far A cells . How Ptc regulates Smocore activity is unclear , but could be related to its proposed function in regulating the levels of a Smo agonist or antagonist [37] . Signaling downstream of both Drosophila and mammalian Smo proteins involves Cos2/Kif7 . Despite lacking previously mapped Cos2 interaction domains , Smocore is capable of recruiting Cos2 , and the ability of successive C-terminally truncated forms of Smocore to do so correlates with their ability to stimulate target gene expression . This truncation approach allowed us to identify a region required for Smo-Cos2 interaction between amino acids 625–651 . Gprk2 phosphorylation cluster 2 falls within this region , and the ability of Smocore to recruit Cos2 is strongly influenced by Gprk2 phosphorylation . Phosphorylation may influence Smocore conformation in a way that favours Cos2 interaction . Alternatively , Cos2 may interact with this region preferentially in a phosphorylated state , as β-Arrestins do with GRK-phosphorylated GPCRs [38] . As this region falls in the portion of the Smo C-terminus that is broadly conserved , it could represent a mechanism of Smo regulation and signaling that is common to all bilaterian species , something that has previously been lacking . Our analysis of Smocore provides some insights into the potential evolutionary origin of Smo . Smocore is a highly conserved , minimal functional form of Smo , and we speculate that it may closely resemble the ancient form of Smo in the common bilaterian ancestor . It displays a mode of regulation that is typical of GPCR desensitization , suggesting that the ancient form of Smo may have behaved more like a classical GPCR . The evidence suggests that different mechanisms have evolved in different lineages for restricting the activity of Smocore , in the form of C-terminal negative regulatory domains . In vertebrates , a stretch of positively charged residues in the C-terminus serves to keep the core in an inactive conformation , and phosphorylation primarily at the first two GRK/CKI clusters overcomes this effect . This same phosphorylation mechanism has been retained in Drosophila and other arthropods . However , through evolutionary time , this group appears to have acquired a PKA/CKI-regulated autoinhibitory domain that has come to dominate Smo activity . In contrast to vertebrates , the ancestral GRK mechanism has been relegated to a modulatory role in flies , where it is required to achieve the highest level of Smo signaling . The principal role of driving Smo into an open conformation and activating downstream signaling has been assumed by PKA/CKI phosphorylation of the SAID domain . One consequence of SAID phosphorylation is recruitment of Cos2 and Fu to binding sites in the nonconserved distal C-terminus , leading to Cos2-dependent Fu dimerization and activation [14] , [39] , [40] . Fu dimerization is sufficient to strongly activate Hh signaling [14] . This Fu-dependent mechanism , mediated via the nonconserved Cos2 and Fu binding sites , is not thought to exist in vertebrate Hh signaling , and may account for the difference in signaling strength between full-length Smo and Smocore . Further analysis of Smocore will be necessary for a full understanding of how Drosophila Smo connects to the downstream signaling apparatus , and should provide insights into a signaling mechanism common to all Smo proteins .
For expression of Smo mutants , we first silently mutated codons 458 and 459 of wild-type and SmoSD [5] coding sequences to introduce an EcoRV site . A 1023 nt EcoRV-EcoRI fragment of wild-type or SmoSD coding sequence containing codon 458–798 and harboring all Gprk2 and PKA phosphorylation sites was subcloned into pBluescript ( pBS ) . The resulting constructs were used as templates for multiple rounds of PCR-based site-directed mutagenesis in order to mutate all Gprk2 sites . The modified EcoRV-EcoRI fragments were then cloned back into full-length Smo expression plasmids . To generate Smo truncations ( Smocore - amino acids 1–663 , SmoΔ651 - amino acids 1–651 , SmoΔ625 - amino acids 1–625 and SmoΔ603 - amino acids 1–603 ) Smo sequences between the EcoRV site at codon 458–459 and the indicated 3′ codon were PCR amplified , introducing a 3′ NotI site . The resulting EcoRV-NotI fragments were cloned into Smo expression vectors . All Smo constructs were C-terminally tagged with either GFP , GFP10 or RLucII . The tags were engineered as a cassette flanked by NotI and KpnI restriction sites . Coding fragments were cloned into expression constructs for use in cell culture ( pRmHa3 . puro [26] containing the metallothionein promoter ) and flies ( pUAST-AttB [25] ) . UAS-smo-3′UTR-dsRNA was generated by cloning a genomic PCR-generated fragment containing nucleotides 2L:281756 . . 281981 of the smo 3′-UTR . The 226 nt long fragment was cloned between the EcoRI-AvrII sites and in the opposite orientation between the NheI-XbaI sites of pWIZ ( Drosophila Genomics Resource Centre ) . To generate catalytically inactive forms of Gprk2 , point mutations changing Lys338/339→Met ( Gprk2kd1 [18] ) or Asp453→Asn ( Gprk2kd2 ) were generated by PCR mutagenesis and cloned downstream of a Myc-epitope tag in pRmHa3 . puro . A C-terminal luciferase-tagged Cos2 expression construct used in BRET assays was engineered by flanking the Cos2 coding sequence at the 5′ and 3′ end with an EcoRI and a NotI site , respectively . The resulting EcoRI-NotI fragment was cloned into pRmHa3 . puro . The RLucII cassette described above was cloned downstream of the Cos2 sequence at the NotI site . Fu coding sequence was cloned downstream of a Myc-epitope tag in pRmHa3 . puro . Sequences of all constructs were verified . For experiments involving Hh treatment , cells were co-transfected with pRmHa3 . puro/HhN [26] , which encodes an active N-terminal fragment of Drosophila Hh . For ptc-luc reporter assays a mixture of the following constructs was used: pRmHa3/Ci ( a gift from S . Cohen , University of Copenhagen , Denmark ) , pGL . basic/ptcΔ136-luc [22] , and pRL/CMV ( Promega ) . All UAS-Smo variant transgenic fly strains were generated by recombining the appropriate pUAST-attB transgenes into the 65B2 attP locus using the PhiC31 system [25] . Flies carrying a chromosome 2 insertion of the UAS-smo3′UTR-dsRNA transgene were generated by standard P-element-mediated transgenesis . Other fly strains and their sources: gprk2del1 and gprk2KO [16]; ap-GAL4 , nub-GAL4 , dpp10638 ( dpp-LacZ ) , UAS-Dicer , tubP::GAL80ts were from the Bloomington Drosophila Stock Center . Anti-pSer604 and anti-pThr610/pThr612 phosphospecific antisera were generated by GenScript . Rabbits were immunized with phosphorylated peptides ( KGRL{pS}ITLYNTHC or CSITLYN{pT}H{pT}DPVGL ) , and antibody was isolated from serum by modified peptide affinity column purification and unmodified peptide cross-adsorption . Anti-Smo antibody was raised in guinea pigs against the same His-tagged fragment of the Smo C-terminus ( amino acids 560–1036 ) as previously used [26] . Other antibodies were: rabbit α-GFP ( Torrey Pines Scientific ) ; rabbit α-β-galactosidase ( Santa Cruz Biotechnology ) ; mouse α-Ptc ( ApaI; developed by I . Guerrero ) and mouse α-En ( 4D9; developed by C . Goodman ) were obtained from the Developmental Studies Hybridoma Bank , created by the NICHD of the NIH and maintained at the Department of Biology , University of Iowa . For expression of SmoSD variants , flies were mated at 25°C and 0–48 h old offspring transferred to 29°C to inhibit GAL80ts and activate apGAL4-dependent transgene expression . For experiments involving rescue of dsRNA-mediated Smo depletion , crosses included a UAS-Dcr transgene and were carried out at 27°C to maximize the smo dsRNA phenotype while minimizing the ectopic effects of transgenic Smo overexpression . For experiments in a gprk2KO/gprk2del1 mutant background , flies were mated at 25°C and 0–48 h old offspring transferred to the restrictive temperature of 29°C [16] . For processing of adult wings , flies were collected in 50% ethanol/50% glycerol . After rinsing with water , wings were transferred into a drop of Faure's solution on glass slides and cover-slipped . For imaginal disc analyses , wandering third instar larval wing discs were dissected in phosphate-buffered saline ( PBS ) and kept on ice for a maximum of 20 min before fixation in PBS/0 . 2% Tween ( PBT ) containing 4% parafomaldehyde for 20 min . Discs were washed three times in PBT , followed by incubation for 30 min in PBT with 0 . 1% BSA ( BBT ) . Primary antibodies were diluted in BBT , added to the discs and incubated over night at 4°C . After four washes with PBT , the discs were incubated with fluorescently-labeled secondary antibodies ( Invitrogen and Jackson ImmunoResearch Laboratories ) diluted in BBT , for 2 hours at room temperature . After four to five more washes with PBT , discs were mounted on slides in mounting medium ( 10% PBS , 90% glycerol , 0 . 2% n-propyl gallate ) , cover-slipped , and imaged using a Zeiss LSM700 confocal microscope . Fig . 3A - UAS-Dcr/+;nub-GAL4/+ Fig . 3B - UAS-Dcr/UAS-GFP;nub-GAL4/UAS-smo3′UTR-dsRNA Fig . 3C - UAS-Dcr/+;nub-GAL4/UAS-smo3′UTR-dsRNA;UAS-SmoWT/+ Fig . 3D - UAS-Dcr/+;nub-GAL4/UAS-smo3′UTR-dsRNA;UAS-Smoc1-4A/+ Fig . 3F - UAS-Dcr/+;nub-GAL4/UAS-smo3′UTR-dsRNA;UAS-Smocore/+ Fig . 4A , B - UAS-Dcr/UAS-GFP;ap-GAL4 , dpp10638/UAS-smo3′UTR-dsRNA Fig . 4C , D , K - UAS-Dcr/+;ap-GAL4 , dpp10638/UAS-smo3′UTR-dsRNA;UAS-SmoWT-GFP/+ Fig . 4E , F , L - UAS-Dcr/+;ap-GAL4 , dpp10638/UAS-smo3′UTR-dsRNA;UAS-Smoc1-4A-GFP/+ Fig . 4G - ap-GAL4/+;UAS-SmoSD-GFP/tubP::GAL80ts Fig . 4H - ap-GAL4/+;UAS-SmoSD . c1-4A-GFP/tubP::GAL80ts Fig . 4I - ap-GAL4/+;UAS-SmoSD-GFP , gprk2del1/gprk2KO Fig . 4J - ap-GAL4/+;UAS-SmoSD . c12D-GFP , gprk2del1/gprk2KO Fig . 5D , E , I - UAS-Dcr/+;ap-GAL4 , dpp10638/UAS-smo3′UTR-dsRNA;UAS-Smocore-GFP/+ Fig . 5F , G , J - UAS-Dcr/+;ap-GAL4 , dpp10638/UAS-smo3′UTR-dsRNA;UAS-Smocore . c1-3A-GFP/+ Fig . 5H , K - ap-GAL4/+;UAS-Smocore-GFP , gprk2del1/gprk2KO Most experiments were performed using S2-R+ cells grown in Drosophila Schneider's medium ( Lonza ) supplemented with 10% fetal bovine serum ( Gibco ) and 50 U/ml penicillin and streptomycin ( Gibco ) . Exceptionally , experiments for Figures 1B and C were performed using Drosophila S2 cells adapted to growth in serum-free medium ( EX-CELL 420 , Sigma ) , which show more pronounced Smo phosphoshifts due to a higher basal level of phosphorylation [19] . Cells were cultured at 25°C unless otherwise indicated . dsRNA was prepared by in vitro transcription using templates PCR-amplified from genomic DNA ( nt 281756 . . 281981 of genomic scaffold 2L for smo 3′-UTR; nt 372–870 of the gprk2 coding sequence; nt 27259182 . . 27259345 of genomic scaffold 3R for gprk2 5′-UTR; and nt 27282732 . . 27283011 of genomic scaffold 3R for the 3′-UTR of gprk2 ) . β-Gal dsRNA was used as a control . Forward and reverse primers included T7 ( 5′-TAATACGACTCACTATAGGGAGA-3′ ) and T3 ( 5′-AATTAACCCTCACTAAAGGGAGA-3′ ) promoter sequences , respectively . Top and bottom strand RNAs were generated using MEGAscript T7 and T3 in vitro transcription kits , mixed in equal amounts , and heated to 95°C followed by slow cooling to room temperature to anneal . For biochemical analysis , <1×106 cells were typically plated on day 1 in 24 well plates in 0 . 5 ml of complete Schneider's medium and each well was transfected with 100–250 ng of the indicated pRmHa . puro expression constructs using X-tremeGENE HP transfection reagent ( Roche ) according to manufacturer's instructions . On day 2 , the cells of each well were split into 2 new wells of a 24 well plate and treated with 5 µg of the indicated dsRNA . On day 3 to 4 , a second dose of dsRNA was applied and transgene expression was induced by addition of CuSO4 to a final concentration of 0 . 5 mM . Cells were harvested and processed on day 7 . For ptc-luc reporter assays , S2-R+ cells were transfected in 24 well plates on day 1 of the experiment as described above . 100 ng pRmHa/Ci , 75 ng pGL . basic/ptcΔ136-luc [22] , 75 ng pRL/CMV , and 100 ng of each additional expression plasmid ( Smo/Gprk2 variant; HhN , as indicated ) were typically used . Total DNA amounts in the transfection mix were normalized using empty pRmHa . puro vector . On day 2 the cells were split into 4 wells of a 96 well plate and each well was treated with 0 . 5–1 µg dsRNA . On day 3 or 4 transgene expression was induced by addition of CuSO4 and a second dose of dsRNA was administered . Cells were processed on day 7 and luciferase activity measured using the Dual Luciferase Reporter system ( Promega ) according to manufacturer's instructions . Assays were performed at least two times in quadruplicate , and the data was pooled . Statistical significance was assessed using two-tailed Student's t-tests . For bioluminescence resonance energy transfer ( BRET ) experiments measuring Smo dimerization S2-R+ cells were transfected with 100 ng of the SmoSD-RLucII variant , 300 ng of the Smo-GFP10 variant and 100 ng of mycGprk2 ( if applicable ) per well of a 24-well plate . For BRET assays monitoring recruitment of Cos2 75 ng of Cos2-RLucII , 300 ng of the indicated Smo-GFP10 variant , and 75 ng mycFu plasmids were transfected . Cells were re-plated in 4 wells of a white-walled 96-well plate and subjected to dsRNA treatments and transgene induction as described above . BRET measurements were performed on day 7 as previously described [19] . Assays were performed at least two times in quadruplicate , and the data was pooled . S2 cells expressing Smo-GFP variants were lysed in lysis buffer [50 mM Tris pH 7 . 5 , 150 mM NaCl , 1% NP and containing 120 µg/ml AEBSF ( Sigma ) , 1× protease inhibitors ( Roche ) and 1× phosphatase inhibitors ( Roche ) ] for 15 min on ice . Insoluble material was removed by microcentrifugation for 15 min at 12 , 000× g and 4°C . Anti-GFP mAb agarose ( MBL International ) was added to soluble extracts and samples incubated on ice for 2 h . Beads were washed 2–3 times in 1 volume of lysis buffer and precipitated proteins extracted by addition of 1× SDS-PAGE sample buffer and heating at 75°C for 6 min . For most experiments , proteins were fractionated by SDS-PAGE on standard polyacrylamide gels . For Figure 1C , Phos-tag acrylamide ( Wako Pure Chemicals Industries , Ltd . ) was added to a final concentration of 7 . 5 mM to improve resolution of phosphoproteins [20] . Fractionated proteins were transferred to nitrocellulose membranes using a wet transfer apparatus and immunoblotted according to standard methods . Quantitation of signal intensity was performed using the Gels>Plot Lanes function of ImageJ 1 . 42q . Plots were normalized to equal total signal intensity ( area under the curve ) , to correct for differences in loading . S2-R+ cells were plated in 1 to 3 wells per condition of a 6-well plate and transfected with 2 . 5 µg/well of pRmHa3 . puro/SmoSD-GFP as above . A day later , medium was replaced and 20 µg/well control ( β-gal ) or gprk2 dsRNA was added to the cells . After three days of growth , the cells were harvested and replated in a 10-cm plate , along with 100 µg/plate of the appropriate dsRNA . SmoSD expression was induced by addition of 0 . 5 mM CuSO4 . 2–3 d later , cells were washed with ice-cold PBS and lysed in 3 ml RIPA buffer for 15 min on ice . Lysates were cleared by microcentrifugation for 15 min at 12 , 000× g and 4°C . SmoSD-GFP was immunoprecipitated using anti-GFP mAb agarose for 2 h at 4°C with rotation . Beads were washed 4 times with ice-cold RIPA buffer before addition of 1× SDS-PAGE sample buffer and heating at 75°C for 6 min . Samples were frozen at −80°C and typically 2 to 3 such preps were pooled for subsequent analysis . Pooled samples were fractionated by SDS-PAGE on 4–15% polyacrylamide gradient gels ( BioRad ) , stained using Colloidal Blue ( Life Technologies ) according to manufacturer's protocol , and the band corresponding to Smo was excised from the gel . Gel pieces were washed with water for 5 min and destained twice with the destaining buffer ( 50 mM ammonium bicarbonate , acetonitrile ) for 15 min . An extra wash of 5 min was performed after destaining with a buffer of ammonium bicarbonate ( 50 mM ) . Gel pieces were then dehydrated with acetonitrile . Proteins were reduced by adding the reduction buffer ( 10 mM DTT , 100 mM ammonium bicarbonate ) for 30 min at 40°C , and then alkylated by adding the alkylation buffer ( 55 mM iodoacetamide , 100 mM ammonium bicarbonate ) for 20 min at 40°C . Gel pieces were dehydrated and washed at 40°C by adding ACN for 5 min before discarding all the reagents . Gel pieces were dried for 5 min at 40°C and then re-hydrated at 4°C for 40 min with enzyme solution . Tryptic digestion was performed with a 6 ng/µl solution of sequencing grade trypsin from Promega in 25 mM ammonium bicarbonate buffer , incubated at 58°C for 1 h and stopped with 15 µl of 1% formic acid/2% acetonitrile . Chymotryptic digestion was performed with a 40 ng/µl solution ( Roche ) in 100 mM Tris HCl- 25 , mM CaCl2 , pH 8 buffer , incubated at 25°C for 4 h and stopped with 15 µl of 1% formic acid/2% acetonitrile . Supernatant was transferred into a 96-well plate and peptide extraction was performed with two 30-min extraction steps at room temperature using the extraction buffer ( 1% formic acid/50% ACN ) . All peptide extracts were pooled into the 96-well plate and then completely dried in vacuum centrifuge . The plate was sealed and stored at −20°C until LC-MS/MS analysis . Protein digestion with Asp-N was performed in solution on tryptic digests . Samples were re-solubilized in a 50 mM ammonium bicarbonate buffer and 1 ng of Asp-N was added to each sample . Samples were incubated at 37°C for 3 h . Prior to LC-MS/MS , peptide extracts were re-solubilized under agitation for 15 min in 11 µl of 0 . 2% formic acid and then centrifuged at 2000 rpm for 1 min . The LC column was a C18 reversed-phase column packed with a high-pressure packing cell . A 75 µm i . d . Self-Pack PicoFrit fused silica capillary ( New Objective , Woburn , MA ) of 15 cm length was packed with the C18 Jupiter 5 µm 300 Å reverse-phase material ( Phenomenex , Torrence , CA ) . This column was installed on the Easy-nLC II system ( Proxeon Biosystems , Odense , Denmark ) and coupled to the LTQ Orbitrap Velos ( ThermoFisher Scientific , Bremen , Germany ) equipped with a Proxeon nanoelectrospray ion source . The buffers used for chromatography were 0 . 2% formic acid ( buffer A ) and 100% acetonitrile/0 . 2% formic acid ( buffer B ) . During the first 12 min , 5 µl of sample were loaded on column with a flow of 600 nl/min and , subsequently , the gradient went from 2–80% buffer B in 60 min at a flow rate of 250 nL/min and then came back at 600 nL/min to 2% buffer B for 10min . LC-MS/MS data acquisition was accomplished using an eleven scan event cycle comprised of a full scan MS for scan event 1 acquired in the Orbitrap which enables high resolution/high mass accuracy analysis . The mass resolution for MS was set to 60 , 000 ( at m/z 400 ) and used to trigger the ten additional MS/MS events acquired in parallel in the linear ion trap for the ten most intense ions . Mass over charge ratio range was from 360 to 2000 for MS scanning with a target value of 1 , 000 , 000 charges and from ∼1/3 of parent m/z ratio to 2000 for MS/MS scanning with a target value of 10 , 000 charges . The data–dependent scan events used a maximum ion fill time of 100 ms and 1 microscan . Target ions already selected for MS/MS were dynamically excluded for 25 s . Nanospray and S-lens voltages were set to 0 . 9–1 . 8 kV and 50 V , respectively . Capillary temperature was set to 225°C . MS/MS conditions were: normalized collision energy , 35 V; activation q , 0 . 25; activation time , 10 ms . The peak list files were generated with extract_msn . exe ( version January 10 , 2011 ) using the following parameters: minimum mass set to 600 Da , maximum mass set to 6000 Da , no grouping of MS/MS spectra , precursor charge set to auto , and minimum number of fragment ions set to 10 . MS/MS spectra were queried against the SmoSD sequence using Mascot 2 . 3 ( Matrix Science ) . The mass tolerances for precursor and fragment ions were set to 10 ppm and 0 . 6 Da , respectively . Search parameters allowed for up to two missed enzyme cleavages . Oxidation of methionine and phosphorylation of serine , threonine and tyrosine were allowed as variable modifications while carbamidomethyl was set as a fixed modification . Matches for phosphopeptides were validated manually . In a few cases ( twice phosphorylated species of cluster 1 peptide W . AKRKDFEDKGRLSITLY . N in Chymotrypisin digest , once and twice phosphorylated species of the cluster 3 peptide R . MALTGAATGNSSSHGPR . K in trypsin+AspN digests ) , the phosphopeptides were not confirmed by MS2 , but were detected in full scan with mass accuracies of less than 2 ppm , and eluted with very similar retention times to other phosphospecies of the same peptide . Peptides were quantitated by manual integration of precursor ion LC spectra using Qual Browser ( Xcalibur from Thermo Scientific ) [21] , [41] . For each phosphopeptide identified , the relative level of phosphorylation in each sample was calculated as the ratio of the amount of phosphorylated: non-phosphorylated forms of the peptide . Multiple sequence alignment of full-length Smo proteins from nine bilaterian animal species was generated with Clustal-Omega . The species and accession numbers corresponding to the sequences used were: Homo sapiens ( NP_005622 . 1 ) , Mus musculus ( NP_795970 . 3 ) , Danio rerio ( NP_571102 . 1 ) , Paracentrotus lividus ( AEX61000 . 1 ) , Platynereis dumerilii ( ADK38671 . 1 ) , Drosophila melanogaster ( NP_523443 . 1 ) , Apis mellifera ( XP_395373 . 3 ) , Tribolium castaneum ( NP_001127850 . 1 ) , Daphnia pulex ( EFX80809 . 1 ) . | Hedgehog proteins are critical regulators of embryonic tissue growth and organization in species ranging from flies to humans . Binding of the secreted Hh protein to its receptor at the surface of cells triggers an intracellular signal that is initiated by Smoothened ( Smo ) . Upon exposure of cells to Hh , Smo becomes active and signals through a series of downstream proteins to regulate gene expression . Although Smo proteins in flies and mammals are similar , the critical regions involved in activation and signal initiation differ between the two , implying that different mechanisms have evolved in different organisms . Using the fruit fly as a model organism , we identified regions in Smo that are phosphorylated by a protein kinase called Gprk2 to enhance Smo activity . These phosphorylation sites overlap with previously identified sites in mouse Smo and are conserved in Smo proteins in many animals . Phosphorylation at these sites regulates the recruitment of Costal2 to Smo , a critical step in signal initiation , through a region of the protein that is also highly conserved . Our results indicate that Gprk2 phosphorylation represents an evolutionarily ancient and conserved mechanism for regulating Smo activity , and suggest that Smo regulation and signaling are more similar between different species than previously thought . | [
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] | 2014 | A Broadly Conserved G-Protein-Coupled Receptor Kinase Phosphorylation Mechanism Controls Drosophila Smoothened Activity |
Host defense against the intracellular pathogen Listeria monocytogenes ( Lm ) requires innate and adaptive immunity . Here , we directly imaged immune cell dynamics at Lm foci established by dendritic cells in the subcapsular red pulp ( scDC ) using intravital microscopy . Blood borne Lm rapidly associated with scDC . Myelomonocytic cells ( MMC ) swarmed around non-motile scDC forming foci from which blood flow was excluded . The depletion of scDC after foci were established resulted in a 10-fold reduction in viable Lm , while graded depletion of MMC resulted in 30–1000 fold increase in viable Lm in foci with enhanced blood flow . Effector CD8+ T cells at sites of infection displayed a two-tiered reduction in motility with antigen independent and antigen dependent components , including stable interactions with infected and non-infected scDC . Thus , swarming MMC contribute to control of Lm prior to development of T cell immunity by direct killing and sequestration from blood flow , while scDC appear to promote Lm survival while preferentially interacting with CD8+ T cells in effector sites .
Appropriate host immune response to pathogenic invasion is critical for survival . Secondary lymphoid tissues provide a structural context for multiple layers of the innate and adaptive immune response to infection . The spleen is a physiologically relevant tissue for immune responses to blood borne pathogens . The immune response to systemic Listeria monocytogenes ( Lm ) infection has been studied extensively in mice and is focused in the spleen and liver [1] . In this model , the innate immune system is responsible for detecting and containing infection while adaptive immunity is required for clearance of Lm and enhanced protection against future infections ( memory ) [2] . Lm is a gram positive intracellular bacterium and can cause severe infection in immune compromised individuals [3] . Lm expresses several virulence factors that enable invasion of the cytoplasm and movement from cell to cell through a contact dependent mechanism and thus grows in foci established by infection of one cell [4] . The spleen acts as a blood filter with a network of phagocytic cells in the marginal zone ( MZ ) and red pulp ( RP ) that are in direct contact with 5% of the the cardiac output . CD11c+ dendritic cells ( DC ) in the MZ and RP of the spleen sequester Lm from the blood and are required to initiate infection in the spleen [5] , [6] , [7] . At the site of infection DC orchestrate both recruitment and activation of innate effectors by secretion of inflammatory cytokines [8] . Aggregations of immune cells including myelomomonocytic cells ( MMC ) consisting of neutrophils and inflammatory monocyte subsets at foci of Lm growth are required to restrict bacterial growth and contain infected cells [9] , [10] , [11] . The process through which MMC converge on foci in the spleen is not understood . For example , expression of chemokine receptor CCR2 is required for monocyte egress from the bone marrow , but is dispensable for homing to infection sites once in the blood [12] . Although the innate immune system can restrict Lm infection , cells of the adaptive system , particularly CD8+ T cells , are required for sterilizing immunity [13] . DC bearing Lm antigens migrate from the MZ to the white pulp ( WP ) in a pertussis toxin sensitive process where they present antigen to T cells , which is required to prime adaptive immune responses [14] , [15] , [16] . DC that prime CD8+ T cells may be directly infected or acquire Lm antigens from infected apoptotic cells such as neutrophils [17] , [18] , [19] . After activation , CD8+ T cells proliferate extensively and exit the WP for bacterial clearance in the RP and to gain access to other sites of infection through the blood [20] . The mechanism of clearance is not completely understood , but requires perforin , IFNγ , TNFα and CCL3 [21] , [22] . Direct visualization of this process may provide insight as in vivo cytotoxicity has been associated with stable and prolonged interactions of antigen specific cytotoxic T lymphocytes ( CTL ) and target cells [23] , [24] . Tissue DC also play a role in the effector phase of T cell responses providing local signals for cytokine production [25] , [26] , [27] , [28] . However , the role of tissue DC in clearance of Lm and nature of T-DC interactions in RP foci is unknown . Live imaging of lymphoid structures by intravital microscopy has provided high-resolution information on the dynamic interactions that take place during immune responses in situ . Tracking of cells in real time reveals kinetic information that is lacking from static images . Intravital microscopy has been useful in understanding tissue specific responses to pathogens [29] . These studies have revealed active environmental sampling by resident DC networks that act as sentinals in peripheral organs such as skin and intestines during infection by Salmonella in the gut and protozoan parasites in the skin [30] , [31] , [32] , [33] . In addition , patrolling neutrophils and monocytes rapidly respond to invading Leishmania major or tissue injury [34] , [35] , [36] . The dynamics of these cells at inflammatory lesions in zebrafish models of tuberculosis have yielded unexpected role of macrophages in dissemination of infection [37] . In mouse models of Leishmania donovani and Bacillus Calmette-Guérin ( BCG ) infection , T cells are rapidly recruited to liver granulomas by inflammatory signals and antigen specific cells are retained [38] , [39] . Interactions of effector T cells with parasites and resident antigen presenting cells ( APC ) revealed zones of antigen specific contacts with pathogen associated APC , while some infected cells were not contacted by T cells in the brain and in the skin [40] , [41] , [42] . The mode of interaction of Lm specific effector T cells in infectious foci is unknown and cannot be predicted based on existing data . Multiphoton intravital imaging in the spleen is hindered by light absorption and scattering by red blood cells and auto-fluorescent metabolites concentrated in the RP . This interference is avoided by directly imaging WP of spleen fragments ex vivo [43] , [44] . However with these preparations physiological circulation and recruitment of cells from hematopoietic tissues such as the bone marrow are lost . We have found that intravital imaging in the RP with confocal microscopy yields high-resolution images suitable for analyzing cellular dynamics . We have previously reported the presence of an extensive DC network in the subcapsular RP ( scDC ) that can be directly visualized by intravital microscopy of the spleen [45] . Early after infection , macrophages and DC capture the bulk of Lm in the MZ and then migrate to the WP to present Lm antigens to activate T cells [5] , [6] , [16] , [46] . However , a minority of Lm does access the RP and establish foci of bacterial growth there . In addition , T cells exit the WP after activation to clear infected cells in the RP [20] . The role of the scDC network and immune cell dynamics in the response to Lm infection in the RP is unknown . Here we set out to observe the early events in the innate immune response and later clearance of Lm infection by adaptive T cells using in vivo imaging of the RP . We show that scDC interacted with Lm within 2 minutes after introduction into the blood stream , but at 48–72 hours post infection ( p . i . ) did not directly contribute to the innate control of bacterial growth once Lm foci are established . At 48 hours p . i . , MMC converged on foci by directed migration and restricted blood flow around infected cells . On day 5 p . i . , the peak of Lm growth , CD8+ T cells are recruited to these foci and displayed a two-tiered deceleration with antigen independent and antigen dependent components .
To test if scDC take up Lm , we used intravital microscopy in the spleen subcapsular RP to image the arrival of fluorescently labeled Lm in circulation of CD11c-EYFP mice [47] . Frozen spleen sections from CD11c-EYFP mice show that YFP+ cells are present in the RP and these cells are heterogeneous for surface staining of CD11c , MHC class II , F4/80 and CD11b ( Figure S1 in Text S1 ) . In the subcapsular RP , YFP+ cells stained strongly for F4/80 , a marker for RP macrophages but also expressed by a subset of DC isolated from spleen and DC subsets found in peripheral organs such as skin [25] , [48] . Most of these subcapsular YFP+ cells also displayed dendritic morphology and time-lapse images of these cells show they are largely non-motile but are actively extending and retracting their dendrites ( Figure 1A , Video S1 ) . This activity is similar to other reports of environmental sampling by DC networks in the lymph node [47] . Thus , it seems that a majority of these YFP+ cells in the subcapsular RP represent a subset of peripheral tissue DC . During image acquisition , 107 Bodipy-630 labeled Lm were injected into the retro-orbital plexus ( Video S1 ) . In some experiments , Lm were injected together with a 10 kDa rhodamine dextran , to mark the time of injection . Lm arrived in the RP within 30 seconds of the rhodamine dextran arrival which was about 60 seconds post injection ( data not shown ) . Of the Lm that came through the imaging field , 70+7 . 7% ( n = 6 mice , 135 bacteria , ) were associated with non-motile scDC 10 minutes after injection ( Figure 1B . ) . Lm-associated scDC remained non-motile for the duration of image acquisition ( up to 20 minutes ) and continued to actively probe the environment ( Video S1 ) . High-resolution z-stack images show that Lm are primarily located within or at the periphery of scDC ( Figure 1C ) . Lm were also co-localized with scDC in images of fixed spleen sections ( Figure S1 in Text S1 ) . The peripheral association may be due to the location of early phagocytic compartments , Lm attaching to or within dendrites below the limit of detection or via interactions with non-fluorescent cells containing Lm . By tracking Lm in the spleen in vivo , we found Lm speeds were initially high in the first few minutes post injection representing bacteria in flow however decelerated as they came in contact with DC ( Figure 1D–E ) . The number of bacteria arriving in the spleen decreased to less than 1 per field after 2 minutes suggesting they are rapidly taken out of circulation ( Figure 1F ) . The speeds of Lm that arrived at later time points were slower than those in flow suggesting they were within a slow moving non-fluorescent cell ( Figure 1G ) . To test if these slow moving Lm were within neutrophils , we repeated the above experiments with LysM-EGFP knock-in mice [49] . In uninfected mice , neutrophils and monocytes express high and intermediate levels of EGFP , respectively ( Figure S2 in Text S1 ) . In the subcapsular RP of uninfected spleens , EGFPhigh neutrophils were motile in patrolling fashion ( Figure 2A–B , Video S2 ) . Upon injection of 107 Lm , there was no acute change in crawling speed ( 15 minutes ) or at 2 hours post injection ( Figure 2C , Video S2 ) . At 2 hours , neutrophils were significantly more confined as indicated by a lower straightness ratio and displacement rate ( p<0 . 0001 , Figure 2D–E ) . A very small fraction of neutrophils ( for example 4 out of over 200 in the imaging field ) took up Lm ( Figure 2 , LM+ , Video S2 ) . The Lm containing neutrophils crawled with an average speed similar to Lm negative neutrophils in the same field ( Figure 2C ) . The number of neutrophils in the field increased acutely after Lm injection ( Figure 2F ) and increased in frequency of total splenocytes proportionately to the number of Lm injected suggesting recruitment from the bone marrow ( Figure S3 in Text S1 ) . During the course of Lm infection the expression level of EGFP in LysM-EGFP mice shifts such that neutrophils and monocytes express similar levels ( Figure S2 in Text S1 ) . Thus , we are not able to distinguish neutrophils and inflammatory monocytes in infected mice and will refer to all EGFP positive cells as myelomonocytes ( MMCs ) . For long-term visualization of bacteria , we generated Lm that express TagRFP from the actA promoter ( Lm-RFP ) , which is only expressed upon entry into the cytosol ( Materials and Methods ) . To visualize DC and MMC dynamics at the site of Lm growth ( Lm foci ) , we crossed CD11c-EYFP to LysM-EGFP transgenic mice . Prior to Lm injection LysM-EGFP+ cells crawled through the RP and displayed transient interactions with scDC ( Video S3 ) . Upon Lm-RFP infection , MMC accumulated at sites of Lm-RFP+ foci and accumulation increased from 24 to 48 hours ( Figure 3A–B ) . Interestingly , Lm-RFP were detected primarily in DC at 24 hours but spread to neighboring cells , including MMC , at 48 hours p . i . ( Figure 3C–D ) . Although we did not directly observe cell to cell spread , Lm-RFP were detectable at the tips of EYFP+ DC extensions or “listeriopods” , a mechanism by which Lm spread to neighboring cells [50] ( Figure S4 in Text S1 , Video S4 ) . We also noted fine EYFP+ tubules between well-separated scDC ( Figure S4 in Text S1 , Video S4 ) that may represent the in vivo counterparts of membrane nanotubes [51] . Infected scDC ( and non-DC ) contained multiple Lm ( Figure S4 in Text S1 , Video S4 ) . Most scDC in the field were enlarged and contained large vacuoles consistent with activation . Several scDC were clustered together with trapped or internalized MMCs ( Figure S4 in Text S1 ) . LysM-EGFP+ MMCs that accumulate on Lm-RFP foci were CD11b+ and Gr-1+ ( Figure S5 in Text S1 ) . To observe the mechanism by which MMC accumulate at the site of infection , intravital microscopy was initiated in LysM-EGFP mice infected with Lm-RFP 48 hours prior . MMCs crawled from the periphery ( up to 300 µm from the foci center ) toward established foci by directed migration , as illustrated by tracks of moving cells ( Figure 4A , Video S5 ) . The biased trajectories of MMCs are shown by plotting the change in distance to the foci center against the mean speed for each cell ( Figure 4B ) . Angles ( Ψ ) between MMC trajectories and the foci center [52] were more frequently less than 90° indicating directed migration towards the focus while no bias in migration within the RP is observed in the absence of infection ( p<0 . 0001 , Figure 4C ) . Overall turning angles were not different compared to cells crawling in uninfected mice however cells moved slightly faster ( Figure 4D–E ) . The signal to join an established focus seemed dominant over signals from some infected cells ( Video S5 ) . MMCs within the foci were quite dynamic , but confined within the region of the foci ( Video S5 ) . The Lm foci observed here are in the blood filled space of the RP . To test if MMC accumulation affects blood flow around infected cells , we selectively depleted Gr-1hi neutrophils alone or neutrophils and inflammatory monocytes with 125 or 250 µg of anti-Gr-1 antibody ( RB6-8C5 ) , respectively ( Figure 5A–B and Figure S6 in Text S1 ) . Mice were infected with Lm-RFP and intravital imaging was performed 48 hours later . In the absence of neutrophils ( 125 µg RB6-8C5 ) Lm-RFP growth increased , but they remained in foci ( Figure 5A–B ) . Injection of fluorescent dextran transiently highlights blood flow seconds after i . v . injection . The rate of blood flow in the field of view around Lm+ foci was greatly reduced in neutrophil depleted mice compared to untreated ( Figure 5C , Video S6 ) . In untreated mice blood flow at the foci is reduced to 40% of that outside the Lm foci ( Figure 5D ) . Strikingly , in neutrophil depleted mice , blood flow was specifically increased in these foci relative to the surrounding RP ( Figure 5C–D ) . Thus , MMC , particularly neutrophils , are essential for restriction of blood flow in Lm foci and maintenance of surrounding tissue health . The observation that Lm-RFP are detected in CD11c-EYFP DC in the first 24 hours p . i . is consistent with previous reports that CD11c+ cells are required to establish infection and were the only cells containing viable Lm in the spleen at this time point [7] . DC were also shown to secrete inflammatory cytokines thought to mediate recruitment and activation of innate effectors [8] . To test the requirement for scDC in maintaining established Lm foci , we depleted DC at 48 hours p . i . by treating CD11c-DtR transgenic mice with DT [14] . This treatment induces efficient deletion of CD11c+ cells ( Figure S7 in Text S1 ) and has also been shown to deplete MZ macrophage populations [53] . DC depletion resulted no significant change in the number of viable Lm recovered from the spleen 24 hours later ( 72 hours p . i . ) , although we note a modest reduction ( Figure S7 in Text S1 ) . The slight decrease in Lm burden after DC depletion suggests that , DC continue to serve as a protective niche for bacterial growth at 48–72 hours p . i , consistent with a role in establishing infection . However at these later time points , Lm may have spread to neighboring cells of various cell types masking the effect of DC depletion . The lack of increase in bacterial burden demonstrates that DC do not directly contribute innate protection in the 48–72 hours p . i . Although not addressed here , it is important to note that DCs that migrate to the white pulp are required for priming adaptive immunity necessary for later clearing the infection [54] . On days 3–5 p . i . Lm-RFP numbers in the spleen were constant and chronic infection would develop in the absence of an adaptive T cell response [Figure S8 in Text S1 , 55] . To track CD8+ T effectors at Lm foci by intravital microscopy , even after multiple cell divisions , we bred mice with one transgenic allele expressing the L9 . 6 T cell receptor ( TCR ) α and β chain and one transgenic allele with EGFP expression driven by the ubiquitin promoter ( L9 . 6-EGFP ) . L9 . 6 TCR recognizes the subdominant , but fully protective , p60217–225 peptide presented in a stable complex with H-2Kd [56] . Naïve CD8+ T cells were isolated from L9 . 6-EGFP mice and transferred to CB6/F1 recipients one day prior to infection with Lm-RFP . Excess antigen specific precursors leads to altered CD8+ T cell responses [57] , and thus we titrated down the number of L9 . 6-EGFP T cells required to detect T cells at Lm foci on day 5 p . i . ( Figure S9 in Text S1 ) . At 0 . 5 million L9 . 6-EGFP T cells transferred , we detected over 10 T cells at Lm foci . At 10 and 100 fold lower transfer numbers , T cells behaved in a similar manner but were too rare for satisfactory statistical analysis ( Figure S9 in Text S1 ) . Lm-RFP were detected in discrete foci on day 5 p . i . , but RFP signal was largely degraded on day 7 consistent with live Lm cultured from the spleen at those times ( Figure 6A and S8 in Text S1 ) . On day 5 p . i . , L9 . 6-EGFP T cells were detected in close proximity to Lm-RFP+ infected cells ( Figure 6A ) . Inside the foci , T cells were moving slowly ( mean speed = 3 . 64 µm/min ) and made extensive contacts with Lm-RFP+ cells ( Figure 6B , Video S7 ) . Many L9 . 6-EGFP cells engaged in contact with the same infected cell throughout the imaging period of up to 30 minutes . Outside the foci , L9 . 6-EGFP cells proximal ( within the field of view of approximately 200 µm from the foci center ) and distal ( over 200 µm ) to the foci moved at a similar speed of 5 . 23 and 5 . 37 µm/min , respectively , which was significantly faster compared to cells inside foci ( Figure 6B ) . L9 . 6-EGFP cells inside the foci displayed significantly higher arrest coefficients ( Figure 6C ) and were more confined compared to cells outside the foci ( Figure 6D ) . On day 7 p . i . , few RFP+ bacteria were detected at sites of infection ( marked by necrotic and auto-fluorescent tissue ) and correlated with fewer live bacteria cultured from the spleen ( Figure S8 in Text S1 ) . Coincident with the decrease in live bacteria , L9 . 6-EGFP CD8+ T cell motility was equivalent of those crawling outside the site of infection ( Figure 6B–D ) . Thus , L9 . 6-EGFP CD8+ T cell crawling was restricted when proximal to Lm-RFP+ infected cells but not distal to infected cells and not after live bacteria are killed . To test if MHC class I antigen recognition pathway was capable of arresting L9 . 6-EGFP cell migration outside foci , we injected the specific p60217–225 peptide i . v . , while monitoring crawling behavior of T cells in extra-foci RP of infected mice . As a control , OT-1-dsRed CD8+ T cells were monitored in separate mice . Fluorescent dextran was included with peptide injections to mark the time of arrival in the RP , which was ∼15 seconds after injection . The p60 peptide reduced the average speed of L9 . 6-EGFP cells from 5 . 6 to 3 . 5 µm/min in 1 . 5 minutes from arrival ( Figure 7A , B , Video S8 ) and had no effect on OT-1 T cell speed ( Figure 7C , D , Video S8 ) . OT-1 T cells decelerated in response to injection of OVA257–264 ( Figure 7C , D , Video S8 ) . These results indicate that antigen-presenting cells in the proximal and distal tissue around the foci can induce antigen specific T cell deceleration if sufficient antigen is available . In order to test if increased arrest in the foci is antigen dependent we activated polyclonal and L9 . 6 CD8+ T cells in vitro , differentially labeled them with Bodipy-630 or Snarf-1 and transferred them to CD11c-EYFP CB6/F1 mice infected with Lm-RFP 48 hours prior . This allowed us to simultaneously image antigen specific and polyclonal T cells together with DC and Lm-RFP . Including polyclonal cells acts as an internal control for antigen specific affects on motility . Both polyclonal and antigen specific T cells were detected at the site of infection ( Figure 8A , Video S9 ) . Crawling speeds of both polyclonal and antigen specific cells were reduced compared to cells distal to the site of infection , however antigen specific cell speeds were further reduced compared to polyclonal cells ( Figure 8B ) . L9 . 6 T cells displayed increased arrest duration ( consecutive time crawling speed is <2 µm/min ) and moved in a confined space as shown by the mean squared displacement ( µm2 ) over time ( Figure 8C–D ) . Antigen specific L9 . 6 T cells were also retained closer to the site of infection ( Figure 8E ) . The non-antigen specific effects at the site of infection were reduced as cells were located further away from the foci ( Figure 8F ) however the effects of antigen seemed to persist further out as antigen specific L9 . 6 T cells were arrested even 200 µm away from the foci center ( Figure 8G ) . Antigen specific arrest away from Lm-RFP+ infected cells may be due to infection of cells below the level of RFP fluorescence detection or acquisition of Lm antigens by phagocytic cells for cross-presentation . Next , T-DC interactions were characterized as stable ( speeds<5 µm/min and within 5 µm of DC ) , transient ( speeds 5–10 µm/min and come within 5 µm of DC ) or fleeting ( speeds>10 µm/min and come within 5 µm of DC ) , polyclonal T cell interactions were mostly fleeting , whereas L9 . 6 interactions were mostly stable ( Figure 8H ) . At Lm-RFP foci we observed multiple L9 . 6-EGFP cells clustered around individual DC present at the site of infection ( Figure 8I ) . Some DC were infected with multiple Lm-RFP while in others no Lm-RFP could be detected ( Video S10 ) . Interactions between L9 . 6-EGFP cells and scDC were extensive as DC wrapped their dendrites around T cells and the T cells frequently remained attached to one area on the DC for the entire imaging period ( up to 1 hour ) . As an additional control for antigen specific effects at Lm foci , we used a mutant strain Lm-218S , in which a mutation in the p60 amino acid sequence prevents loading of the p60217–225 peptide onto class I , but spares p60 function [58] . Because the response to p60217–225 is sub-dominant , it can be eliminated without altering the kinetics of bacterial clearance [58] . Because Lm-218S is not fluorescent , we identified infectious foci with propidium iodide ( PI ) , which stains nucleic acids accessible in dead cells and neutrophil nucleic acid nets [59] , [60] . In vitro-activated L9 . 6-EGFP cells were labeled with Bodipy-630 and transferred to CD11c-EYFP CB6/F1 mice 48 hours p . i . ( Figure S10A in Text S1 ) . L9 . 6 CD8+ T cells were detected at a higher frequency close to Lm-RFP foci compared to Lm-218S foci ( Figure S10B in Text S1 ) , suggesting antigen specific T cells were retained at foci . The average L9 . 6-EGFP cell speed and displacement rate was decreased significantly in both Lm-RFP and Lm-218S foci as compared to outside the foci ( Figure S10C–D in Text S1 ) . However , T cell motility was further reduced in Lm-RFP foci relative to Lm-218S foci ( 3 . 2 vs . 5 . 5 µm/min , p<0 . 0001 ) , demonstrating antigen dependent differences in the speed and confinement of crawling cells at the foci . This is further supported by decreased straightness index and higher arrest coefficients in Lm-RFP foci relative to Lm-218S foci ( Figure S10E–F in Text S1 ) .
We anticipated that our intravital analysis would require confirming some results that are known from earlier studies , but also allow us to break new ground in understanding the dynamics of immune responses in the spleen RP . Our results confirm earlier studies regarding the role of CD11c+ cells in initial capture of Lm [7] and the importance of MMC in the control of Lm growth [9] , [10] , [11] . We break new ground in demonstrating the speed of Lm capture , the dynamic process of directed migration of MMC to the focus , the role of MMC in reducing blood flow in foci , the relatively minor role of CD11c+ cells in ongoing innate control of Lm in the foci , and the demonstration of antigen independent and dependent components that affect CD8+ T cell movement in foci . Some would define DC based on their migration to T cell zones where they present antigen to naïve T cells , while others would include cells that reside in peripheral tissues and promote pathogen clearance by stimulating local cytokine secretion and T cell proliferation [25] , [26] , [27] , [28] . Our results suggest that scDC are bona fide DC by the later inclusion criteria and are phenotypically similar to cells recently described to be essential for activating cytokine production by effector cells in the dermis [25] . Similar DC networks exist in the intestines , kidney and brain where these cells may largely act in situ , rather than migrating to secondary lymphoid tissues [31] , [61] , [62] . DC are responsible for initiating both innate and adaptive immune responses to Lm in the spleen [8] , [14] , but the function of the scDC networks was previously unknown . Our result that Lm associate with scDC immediately after injection is consistent with DC depletion studies that show CD11c+ cells are required to capture Lm in the spleen [7] . Extension and retraction of DC dendrites was observed before and after interaction with Lm . The continued environmental probing even after associating with Lm may enhance interactions with immune cells such as neutrophils , inflammatory monocytes , natural killer ( NK ) cells , memory T cells or CTLs that can contribute to innate or adaptive recognition of infection . One day after infection , scDC contained live , intracellular bacteria ( as detected by actA driven RFP expression ) and Lm displayed mechanisms for cell-to-cell spread , such as listeriopods . Depletion of CD11c+ cells at 48–72 hours p . i . eliminated the Lm+ DC and moderately decreased the number of viable Lm in the spleen . This suggests that scDC may serve as a reservoir for bacteria and that Lm may exploit the scDC niche to maintain the infectious foci . Consistent with this , it was previously shown that elevated numbers of DC in the spleen resulted in increased bacterial load [63] . Infection of DC may be beneficial to the host as these cells orchestrate both innate and adaptive immune responses [8] , [14] . Although DC are required to prime adaptive cells required for clearing Lm , our data also suggest that once this role is fulfilled the persistently infected scDC in the red pulp are not necessary for innate control of infection . However , the scDC may have already fulfilled their roles at the time of deletion by early recruitment of MMC , which can then take over bacteriacidal and antigen presenting functions [64] . MMC were required for control of Lm as previously described [9] , [10] , but are not required to initiate or maintain foci through the first 48 hours of infection . This contrasts with Leishmania major infection in the skin , in which neutrophils are the reservoir required to establish infection [34] . These results also contrast with the role of macrophages in granulomas of zebrafish [37] in which motile macrophages promote spread of infection . The chemotactic attraction of MMC to Lm foci may serve to reduce egress of infected cells and dissemination to other organs . NK cell and inflammatory monocyte recruitment to Lm infected cells in the spleen is dependent on signals from chemokines [8] . However , recently it was shown that recruitment of monocytes to Lm foci in the liver was more dependent on adhesion molecules and not chemokines [12] . Thus , MMC recruitment mechanisms are likely to depend on the cell types infected and the specific structure of the tissue microenvironment . At Lm foci , swarming of MMCs around foci is reminiscent of responses to Toxoplasma gondii infection in the LN [52] . However , MMC swarming and mingling with infected scDC did not result in acute disruption of infected cells as was observed as for CD169+ macrophages in the LN . In contrast , DC internalized MMC at the site of infection . MMC at the site of infection may be a source of antigens important for priming adaptive responses [18] . Swarming and aggregation of MMCs at Lm foci was protective and maintained integrity of surrounding tissue . The MMC dependent restriction of blood flow in the foci may serve to wall off potentially harmful inflammation as well as spread of bacteria . Densely packed phagocytic cells surrounding the infected cells may act as a secondary containment to prevent bacterial escape from foci . Antigen specific effector CD8+ T cells infiltrated Lm foci and made prolonged interactions with infected cells . The speeds of L9 . 6-EGFP cells in the spleen RP were similar to effector T cells in the lymph nodes and peripheral sites such as skin [40] , [65] , [66] , [67] , [68] . The average speed of T cells within Lm-RFP+ foci ( day 5 p . i . ) was significantly reduced , but cells were quite dynamic with some forming asymmetric mobile junctions or “kinapses” and others forming more stable non-motile symmetric contacts that may represent immunological synapses [69] . Indeed , L9 . 6 T cells engaged infected cells with prolonged arrest durations over 10 minutes which is sufficient time to perform CTL activity [23] . However , we did not observe any obvious cytolysis of infected cells , which may indicate other mechanisms of clearance such as anti-microbial activity stimulated by IFNγ [21] , [22] . Interestingly , antigen specific cells resumed migration coincident with clearance of live bacteria . This suggests that antigen presentation does not persist at the site of infection in the absence of live bacteria . The introduction of systemic cognate antigen acutely arrested crawling T cells suggesting TCR-pMHC interactions do induce a robust “stop” signal to CD8+ T cells . Previous reports show that CD4+ T cells moved more rapidly ( ∼6 µm/min ) in liver granulomas of BCG infected mice with few T cells arrested [38] . Mycobacterium tuberculosis ( TB ) organisms grow slowly and induce delayed CD4+ T cell responses [70] . The relatively faster movement to CD4+ T cells in liver granulomas compared to CD8+ T cells in Lm foci in the spleen may reflect the relatively poor direct presentation of TB or BCG antigens . The comparison of polyclonal and antigen specific T cells , as well as use of “antigen null” Lm allowed us to finely dissect out antigen dependent and independent affects on motility at the site of infection . Antigen independent components that reduce T cell movement in Lm foci of the spleen may include reduced oxygenation/nutrient supply due to poor blood flow , increased cellular congestion , changes in extracellular matrix and increased expression of adhesion molecules like ICAM-1 on infected cells [12] , [71] . Recruitment of non-specific T cells may induce local crowding and prevent productive interactions between specific T cells and DC [72] . In a recent study , recall responses to Lm resulted in clusters of antigen specific and non-specific memory CD8+ T cells around infected cells in the RP within 6 hours and both specific and non-specific cells generated IFNγ , whereas only antigen specific memory cells made CCL3 [73] . It will be interesting to determine if non-specific effector cells are also stimulated to make IFNγ in Lm foci in the RP in primary responses . However , our data show that recruitment of non-specific T cells is transient as only antigen specific T cells were retained at foci in the effector phase of the primary response . Hierarchic antigen specific and antigen independent affects on motility are also observed in CD8+ and CD4+ T cells recruited to sites of Leishmania donovani infection in the liver and Leishmania major infection in the ear dermis , respectively [39] , [42] . In a recent study , ex vivo spleen fragments were imaged to study T cell and DC interactions during priming in Lm infection in the WP [16] . Imaging spleen sections allows access to the WP . In contrast , we imaged the intact spleen where blood flow was maintained [45] , but limited our observations to the RP and the effector arm of the immune response . Preservation of blood flow was integral to several findings in this study: a ) ability to visualize the fate of Lm immediately after injection; b ) observing the recruitment of MMC from the blood , which occurred continuously throughout the infection; c ) and that MMC accumulation in foci excludes blood flow potentially ‘walling-off’ the infection from the rest of the host . Our observations suggest a complex relationship between Lm and spleen DC where DC may provide a niche for pathogen growth but at the same time mediate protection by recruitment of innate effectors and presenting antigens to effector T cells .
This study was carried out in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the Public Health Service ( National Institutes of Health ) . The protocol was approved by the Institutional Animal Care and Use Committee of the New York University School of Medicine ( Assurance of Compliance Number: A3435-01 ) . All surgery was performed under Ketamine , Xyalazine and Acepromazine anesthesia , and all efforts were made to minimize suffering . LysM-EGFP , a gift of Dr . T . Graf , CD11c-EYFP mice , a gift of Dr . M . Nussenzweig , and CD11c-DtR , a gift of Dr . D . Littman , on the C57/B6 background were maintained in a colony at the barrier facility of the Skirball Institute of Biomolecular Medicine at New York University ( New York , NY ) . CB6/F1 recipients were purchased from Jackson Labs ( Bar Harbor , ME ) . L9 . 6 on a Balb/c background and Ub-GFP mice on a C57/B6 background were crossed to generate L9 . 6-EGFP CB6/F1 donors . CD11c-EYFP homozygous mice on the C57Bl6 background were bred to Balb/c mice to generate CD11c-EYP CB6/F1 recipients . OT-1 and Actin-dsRed mice were purchased from Jackson and crossed to generate OT-1-dsRED . Lm infected mice were housed under animal BSL2 conditions in a special room of the Skirball Institute specific pathogen free facility . Lm strains were constructed in the DP-L4056 strain background [74] . TagRFP from Entacmaea quadricolor [75] was codon optimized for expression in gram positive bacteria with Gene Designer software [76] and the cDNA was synthesized de novo ( DNA2 . 0 , Menlo Park , CA ) . The synthetic gene was cloned downstream of the actA promoter in the vector pPL2 and stably integrated at the tRNAArg locus of the bacterial chromosome in the as described previously [74] . All molecular constructs were confirmed by DNA sequencing . Virulent Lm strain aliquots were kept at −80°C and grown in Brain Heart Infused media ( BHI , Fisher ) for 3–4 hours until ∼0 . 1 optical density ( OD ) at 600 nm . Lm were diluted to the appropriate concentration in 200 µl PBS for inoculation into mice . For acute imaging experiments 1×107 Bodipy-630 labeled bacteria were injected into the retro-orbital plexus during image acquisition . For all other time points ( 24 hours and later ) 2 . 5×104 bacteria were injected . To facilitate location of infectious foci , in some experiments mice were infected with a 10-fold higher infectious dose ( 2 . 5×105 Lm-RFP ) . For MMC depletion , LysM-EGFP mice were treated with 125 or 250 µg RB6-8C5 antibody by i . p . injection 5 hours prior to infection with Lm-RFP . Assays were performed 48 hours p . i . For DC depletion , C57/B6 and CD11c-DtR transgenic mice were infected with Lm-RFP and 48 hours later treated with 1 µg DT by i . p . injection . Assays were performed 72 hours p . i . ( 24 hours after DT treatment ) . Images of the spleens were taken by intravital micrcoscopy and then splenocytes were collected for FACS or lysed with 0 . 05% Triton-X 100 and bacteria were plated in serial dilutions on Brain heart infused ( BHI ) agarose plates to obtain colony counts . Naïve CD8+ T cells were isolated from spleen by CD8+ T cell negative selection kit ( Miltenyi Biotec , Auburn , CA ) . 0 . 5×106 L9 . 6-EGFP or 500 OT-1-dsRed naïve cells were adoptively transferred to CB6/F1 and CD11c-EYFP CB6/F1 or C57/B6 recipients by i . v . retro-orbital injection in 100–200 µl PBS , one day before infection . 1×106 negatively selected naïve CD8+ T cells were incubated with 2 . 5×107 APC ( ACK treated and irradiated spleen cell suspension ) in 20 ml OK-DMEM , 10% fetal bovine serum with 10 nM p60217–225 and supplemented with 25 U/ml recombinant IL-2 in T25 flask ( Corning 430372 or BD 353081 ) . On day 4 post-activation , medium was replaced with fresh media plus 25 U/ml recombinant IL-2 and expanded up to 50 ml in T75 flask ( BD 353135 ) . T cells were used on day 6 post activation . In vitro activated T cells were labeled with 1 µM Bodipy 630/650 methyl bromide ( B22802 , Invitrogen , Carlsbad , CA ) or 1 µM Snarf-1 ( S22801 , Invitrogen , Carlsbad , CA ) by incubation at a concentration of 10–20×106 cells per ml in PBS at 37°C for 15 minutes . Lm were labeled at a concentration of 0 . 5–2×108 CFU per ml of 5 µM Bodipy 630/650 methyl bromide in BHI at 37°C for 15 minutes . After labeling , cells or bacteria were washed 2–3 times with PBS . Cell preparations for FACS were prepared by mashing the spleen through 40 µm filters in FACS buffer . Red blood cells were lysed by ACK . Frozen sections were prepared by fixing tissue fragments with 4% PFA PBS for 1 hour on ice and perfused with 30% sucrose PBS at least until tissue sank to the bottom of solution . Cells and tissue were stained with the following antibodies from eBioscience ( San Diego , CA ) : CD11c ( N418 ) -APC , CD11b ( M1/70 ) -APC , MHC class II ( M5/114 . 15 . 2 ) -APC , F4/80 ( BM8 ) -APC , Ly-6C ( AL-21 ) Pe-Cy7 , Ly-6G ( RB6-8C5 ) Alexa-700 . 10 µl of 10 µM p60217–225 peptide or 10 µg of OVA257–264 peptide plus 4 µg Alexa-647 10 kDa dextran ( D-22914 , Molecular Probes ) were diluted into 100 µl PBS and injected i . v . into the retro-orbital plexus of anesthetized mice during image acquisition . Alexa-647 10 kDa dextran was included to mark the time of injection . Mice were anesthetized with an intraperitoneal injection of Ketamine ( 50 mg/kg ) , Xyalazine ( 10 mg/kg ) and Acepromazine ( 1 . 7 mg/kg ) and boosted with a half dose every 30–60 minutes . The spleen was externalized by making a 1 cm incision just below the ribcage . The organ was gently tethered out of the body and a custom made plastic apparatus slid between the spleen and the mouse body . The apparatus was used to keep the organ out of the body and aids in stability . The apparatus does not disrupt the vasculature or connective tissue of the spleen . The mouse was then laid on a stage with the spleen positioned over a cover slip . The stage and mouse were heated to 37°C by flowing heated air over the system . The mouse was covered to prevent drying out the tissue and overheating . Oxygen was delivered to a mask that covers the snout to ensure the animal , and tissue , receive adequate oxygen . To verify that blood circulation through the spleen was not disrupted by the procedure , 4 µg Alexa-647 10 kDa dextran in 100 µl PBS were routinely injected i . v . into the retro-orbital plexus during image acquisition . For intravital imaging in spleen , we used a Zeiss LSM 510 or 710 laser scanning confocal microscope ( Carl Zeiss , Thornwood , NY ) using an inverted Plan-Apochromat 20×/0 . 75 , 25×/0 . 8 , 40×/1 . 3 Oil DIC , or FLUAR 40×/1 . 3 Oil objectives . EGFP , RFP and Alexa-647 10 kDa Dextran were imaged using appropriate combinations of 488-nm , 546-nm , and 633-nm laser lines and BP 505–530 , BP 560–615 , and LP 650 filter sets , respectively . ECFP , EGFP and EYFP were imaged using combinations of 458-nm , 488-nm and 514-nm laser lines and BP 475–525 , BP 505–530 and LP 530 filter sets , respectively . Time-lapse images were acquired by scanning 20×460 . 7×460 . 7 ( 20× ) or 20×230 . 3×230 . 3 ( 40× ) µm at 30 second intervals . In some cases z- stacks of images were taken at 3×10 µm steps or images were tiled during acquisition using a motorized stage . For high-resolution images of scDC and Lm , z- stack images were taken at 1 µm steps covering 14 to 20 µm . Movement of cells in tissue was tracked using Volocity software ( Improvision , Waltham , MA ) . Only cells that remained in the field of view for more than 5 frames ( 2 . 5 minutes ) out of a total at least 30 frames ( 15 minutes ) were counted as crawling cells . Distribution of cell velocities and motility parameters were non-Gaussian and thus Mann-Whitney rank sum test was used to compare data from each group . Statistical calculations and graphing were done in Prism ( GraphPad Software , LaJolla , CA ) . LysM ( Lyz2 ) MGI:96897 , LysM-eGFP ( Lyz2tm1 . 1Graf ) MGI:2654931 , CD11c ( Itgax ) MGI:96609 , CD11c-eYFP ( Tg ( Itgax-Venus ) 1Mnz ) MGI:3835666 , CD11c-DTR ( Tg ( Itgax-DTR/EGFP ) 57Lan ) MGI:3057163 , CD11b ( Itgam ) MGI:96607 , MHC class II ( H2-Ab1 ) MGI:103070 , F4/80 ( Emr1 ) MGI:106912 , Gr-1 ( Ly6g ) MGI:109440 , Ly-6C ( Ly6c1 ) MGI:96882 , CD8 ( Cd8a ) MGI:88346 , TCR α ( Tcra ) MGI:98553 , TCR β ( Tcrb ) MGI:98578 . Mouse Genome Informatics , The Jackson Laboratory , Bar Harbor , Maine . World Wide Web ( URL: http://www . informatics . jax . org ) . | The pathogenic bacteria Listeria monocytogenes ( Lm ) can access the intracellular space and establish infection in the host spleen and liver . Innate immune cells are required to detect and contain infection while specific adaptive T cells are activated and recruited to infection sites . Adaptive immunity enhances the function of innate cells and also directly kills infected cells to prevent further bacterial propagation . These cells respond to local environmental cues and often communicate via direct cell-to-cell contact . Here , we observed cellular dynamics in situ by imaging live tissue using intravital microscopy . We reconstituted the Lm infection model with bacteria and mouse strains engineered to express fluorescent proteins to label specfic cells . We find that dendritic cells ( DC ) in the spleen rapidly capture Lm from circulation , demonstrating a direct role of these cells in sequestering bacteria . Neutrophils converge on infected cells by directed migration to generate exanguinous foci within the otherwise blood rich red pulp . Finally , antigen specific CD8+ T cell interact extensively with infected cells and DC in the foci and are selectively retained compared to non-specific polyclonal T cells . These findings significantly advance our understanding of immune cell dynamics in the spleen in both the steady state and in response to Listeria infection . These studies could aid in development of disease therapies and vaccine strategies targeted towards enhancing DC , myelomonocytic and CD8+ T cell effector responses . | [
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"infectiou... | 2011 | Dynamic Imaging of the Effector Immune Response to Listeria Infection In Vivo |
We constructed a 400K WG tiling oligoarray for the horse and applied it for the discovery of copy number variations ( CNVs ) in 38 normal horses of 16 diverse breeds , and the Przewalski horse . Probes on the array represented 18 , 763 autosomal and X-linked genes , and intergenic , sub-telomeric and chrY sequences . We identified 258 CNV regions ( CNVRs ) across all autosomes , chrX and chrUn , but not in chrY . CNVs comprised 1 . 3% of the horse genome with chr12 being most enriched . American Miniature horses had the highest and American Quarter Horses the lowest number of CNVs in relation to Thoroughbred reference . The Przewalski horse was similar to native ponies and draft breeds . The majority of CNVRs involved genes , while 20% were located in intergenic regions . Similar to previous studies in horses and other mammals , molecular functions of CNV-associated genes were predominantly in sensory perception , immunity and reproduction . The findings were integrated with previous studies to generate a composite genome-wide dataset of 1476 CNVRs . Of these , 301 CNVRs were shared between studies , while 1174 were novel and require further validation . Integrated data revealed that to date , 41 out of over 400 breeds of the domestic horse have been analyzed for CNVs , of which 11 new breeds were added in this study . Finally , the composite CNV dataset was applied in a pilot study for the discovery of CNVs in 6 horses with XY disorders of sexual development . A homozygous deletion involving AKR1C gene cluster in chr29 in two affected horses was considered possibly causative because of the known role of AKR1C genes in testicular androgen synthesis and sexual development . While the findings improve and integrate the knowledge of CNVs in horses , they also show that for effective discovery of variants of biomedical importance , more breeds and individuals need to be analyzed using comparable methodological approaches .
The significance of gene duplication in long-term evolutionary changes was already recognized over 40 years ago by Susumu Ohno [1] . Yet , systematic genome-wide discovery and functional interpretation of inter- and intraspecific copy number variations ( CNVs ) in genes and non-genic DNA sequences , started in the past decade with foundational studies in humans [2] , [3] and mice [4] , followed by genome-wide ( GW ) CNV discovery in chicken [5] , cattle [6] , dogs [7] , [8] and other domestic species ( see [9] , [10] ) . It is now well established that CNVs are a common feature of vertebrate genomes . Typically , they are DNA sequence variants from at least 50 base-pairs ( bp ) to over several megabase-pairs ( Mb ) in size that are involved in deletions , insertions , duplications and translocations , causing structural differences between genomes [11] , [12] . In terms of the total number of DNA base-pairs , CNVs are responsible for more heritable sequence differences ( 0 . 5–1% ) between individuals than SNPs ( 0 . 1% ) [11] , [12] , [13] . One of the central goals of CNV research has been determining their association with genome instability , genetic diseases and congenital disorders . It is thought that CNVs , as a major source of inter-individual genetic variation , could explain variable penetrance of Mendelian and polygenic diseases , and variation in the phenotypic expression of complex traits [14] , [15] . Indeed , CNVs have been associated with common complex and polygenic disorders in humans affecting a broad range of biological processes , such as immune response , autoimmunity and inflammation [3] , [16] , [17]; musculoskeletal [18] , [19] and cardiovascular systems [20] , [21]; neurodevelopment , cognition and behavior [22] , [23] , and sexual development and reproduction [24] , [25] , [26] , [27] , [28] . The availability of whole genome ( WG ) sequence draft assemblies combined with the advances in array-based technologies and next generation sequencing ( NGS ) , have prompted CNV research in all main domestic animal species ( reviewed by [9] , [10] ) with the most advanced information currently available for cattle [6] , [29] , [30] , pigs [31] , and dogs [32] , [33] , [34] . In horses , five studies report about the discovery of CNVs in the whole genome [35] , [36] , [37] , [38] or in gene exons [39] . Attempts have also been made to associate CNVs with equine diseases [36] , adaptations [38] and phenotypic traits [37] , [39] . While these studies set a foundation for understanding the role of CNVs in equine biology , the current information is inadequate for efficient discovery of variants affecting equine health and disorders . This is because the studies have used different CNV discovery platforms , the number of breeds and individuals in some studies is very limited , and the majority of reported CNVs are study-specific and not validated by two or more independent studies . Also , the available information has not been integrated into a composite dataset to facilitate the analysis of known CNVs and the discovery of new ones . The aim of this study is to improve the current rather limited knowledge of CNVs in horses by their genome-wide discovery in multiple individuals of additional diverse horse breeds . Using a custom-made WG tiling array we generate a CNV map for the horse genome and integrate this with the previous CNV studies into a composite dataset . Finally , we carry out a pilot CNV analysis in horses with disorders of sexual development to test the utility of the array and the integrated dataset for the discovery of variants involved in equine complex disorders .
Texas A&M University ( USA ) and The University of Adelaide ( Australia ) collaborated to create a whole-genome ( WG ) 400K tiling array which was produced and printed by Agilent Technologies ( Design ID #030025 ) , and designated as the Texas-Adelaide array . The probes on the array represented 18 , 763 autosomal and X-linked genes , and intergenic , sub-telomeric and chrY sequences . Median genomic distance between the probes on the array was 7 . 5 kb; this distance was lower ( 4 kb ) in sub-telomeric regions , and higher ( ∼20 kb ) in the Y chromosome . Before using the array for CNV discovery in horses , the platform was tested for performance quality . Self-to-self control hybridizations ( Figure S1a ) showed 1 . 55% of False Discovery Rate ( FDR ) - an indication that the array design , fabrication , and array genomic hybridization ( aCGH ) procedures were optimal . As a proof-of principle , female-to-male hybridizations between two half-sib Thoroughbreds , Twilight ( female ) and Bravo ( male ) , showed massive loss in the X chromosome and a gain in the Y chromosome in the male , whereas only one CNV was detected in an autosome , chr3 ( Figure S1b ) . Hybridization quality was assessed by measuring Derivative Log Ratio Standard Deviation ( DLRSD ) which calculates probe-to probe log ratio noise and is typically <0 . 3 for good quality hybridizations . The DLRSD values for all hybridizations with blood DNA from Twilight and Bravo were <0 . 2 . Therefore , and because the oligonucleotides on the array were derived from the sequences of these two horses , DNA of Twilight and Bravo was used as a reference for all aCGH experiments: Twilight for females and Bravo for males . Further , because our DNA collection from horse breeds contained samples isolated from blood and hair , an additional self-to-self hybridization was conducted using DNA from blood and hair of one male Quarter Horse QH3-H528 ( Table S1 ) . Blood DNA gave good quality results with DLRSD = 0 . 14 , whereas consistent and high level hybridization noise was observed for hair DNA ( DLRSD = 0 . 41 ) ( Figure S1c ) . Due to this , CNVs in all samples were called with stringent criteria: log2 ratio alterations higher than 0 . 5 over 5 neighboring probes – a necessary compromise between calling CNVs with confidence and missing a few true calls . With median probe spacing of 7 . 5 kb on the array , this allowed detection CNVs of about 30 kb , and in probe-dense regions even smaller . We concluded that the performance of the equine 400K Texas-Adelaide whole-genome CGH array was optimal for the discovery of CNVs in the horse genome . The aCGH data are available at NCBI GEO accession GSE55266 . Collectively , 950 CNV calls were made across 36 horses , with an average of 26 . 4 calls per individual ( Table 1; Table S3 ) . The number of CNV calls was the highest in two American Miniature Horses ( 59 and 46 ) and the lowest in American Quarter Horses ( 12 and 14 ) , whereas the number of calls per individual was not significantly different between blood and hair DNA ( P = 0 . 07; Table 1 ) at the settings of log2±0 . 5 over 5 probes . The number and distribution of CNVRs in the two Przewalski horses were similar to those in domestic horses ( Table 1 , Table S4 ) . Because the Thoroughbred served as a reference , by default all the 950 CNV calls recorded in other breeds were also present in the Thoroughbred , though inversely with respect to gains and losses . However , because the Thoroughbred was compared with multiple individuals , the same CNV had different log2 values , and that is why the Thoroughbreds were not included in the comparisons of CNV metrics . The ADM-2 algorithm arranged adjacent and overlapping CNV calls ( CNVs ) within and between individual horses into 258 CNV regions ( CNVRs; Table S5 ) of which 114 were shared between at least 2 individuals of the same or different breeds , while 144 were private and found only in one individual . Two CNVRs were found in two or more individuals of the same breed but not in other breeds and were tentatively considered as breed-specific: a 14 kb loss in chr9 in Exmoor ponies , and a 39 kb loss in chr20 in Swiss Warmblood horses ( Table S4 ) . Based on the 258 CNVRs , a whole genome CNV map for the horse was constructed ( Figure 1 ) details of which are summarized in Table 2 . The mean size of CNVRs was 110 kb ranging from 1 kb to 2 . 5 Mb . The CNVRs occupied 1 . 15 % of the equine genome and were distributed over all horse chromosomes , except the Y , with the highest enrichment in chromosomes 12 ( 9 . 7% ) and 20 ( 3 . 0 % ) . Even though chr12 is the gene richest chromosome in the horse genome ( 15 genes/Mb ) , there was no overall correlation between CNV enrichment and gene density . For example , the enrichment values for the second and third gene densest chromosomes , chr11 and chr13 , were 0 . 02% and 0 . 28% , respectively ( Table 2 ) . Likewise , we did not observe CNV enrichment in sub-telomeres , as previously reported for humans [40]: the array contained 5 , 716 sub-telomeric probes , though only 10 CNVRs were detected in these regions in horses . In general , losses ( 173; 67% ) prevailed over gains ( 63; 24% ) , although 6 horses had more gains than losses ( Table 1 ) . Twenty-two CNVRs ( 8 . 5% ) were complex involving both losses and gains in different individuals ( Table 2 , Table S3 ) . Even though aCGH on diploid samples cannot discriminate between copies of alleles and thus , distinguish between heterozygous and homozygous CNVs , two gains and 14 losses were tentatively considered homozygous because of log2 alterations over 2 . 0 ( Table S6 ) . Homozygosity of 8 losses was confirmed by qualitative PCR ( Fig . S2 ) . The majority ( 82% ) of horse CNVRs contained one or more known Ensembl ( http://www . ensembl . org/index . html ) horse genes ( 158 CNVRs ) or non-horse mammalian reference genes ( 54 CNVRs ) ( Table S7 ) , while 46 CNVRs ( 18% ) were located in intergenic regions ( Table S8 ) . Gene containing CNVRs were also predominant in individual chromosomes with the exception of chr31 which was enriched with intergenic variants Fig . 2 . However , we consider calls for intergenic CNVRs tentative and subject to change as the annotation of the horse genome is still in progress . Altogether , the CNVRs involved 805 protein-coding genes ( 750 Ensembl genes , 33 non-Ensembl genes and 22 horse mRNAs; Table S7 ) but also non-coding small and long RNA genes , and pseudogenes . The largest CNVRs with the highest number of genes corresponded to clusters of olfactory and non-olfactory G-protein coupled receptors ( GPCRs ) or to immunity related genes , such as immunoglobulins , T-cell receptors , and MHC protein complex genes - a typical feature of CNVRs in all mammalian genomes studied so far [3] , [30] , [32] , [39] , [41] , [42] . Likewise , Gene Ontology ( GO ) analysis indicated that equine copy number variable genes are predominantly involved in biological processes and molecular functions related to transmembrane signal transduction , chemo-attractant sensory perception , immune response and steroid metabolism ( Fig . 3; Table S9 ) . Notably , 5 copy number variable genes from this study were associated with known OMIA ( http://omia . angis . org . au/home/ ) phenotypes for immune , reproductive or neuromuscular diseases ( Table 3 ) , though none of the OMIA records involved horses or CNVs . The CNVR overlapping with the BMPR1B gene has been earlier reported in horses and is of interest because of a possible role in the regulation of the rate of ovulation [39] . Comprehensive knowledge of CNVs in normal horse populations , within and across breeds , is a prerequisite for the discovery of variants that contribute to equine genetic diseases and disorders . Therefore , we aligned the 258 CNVRs identified in this study with previously published CNV data for the horse [35] , [36] , [37] , [38] , [39] . Altogether , we found records of about 2041 CNVs and CNVRs ( calling criteria vary between studies ) . These were further consolidated , based on adjacent locations or partial overlaps , into 1476 CNVRs of which 301 CNVRs ( 20% ) were shared between two or more studies ( Table S10 , Fig . 4 ) . The majority of shared CNVRs involved genes associated with olfactory reception ( 50 CNVRs ) and membrane transport ( 49 CNVRs ) but also genes involved in transcription ( 30 CNVRs ) , cell cycle regulation ( 12 CNVRs ) and RNA genes ( 34 CNVRs ) . Expectedly , CNVRs that were found in more than 100 horses and reported by all 6 studies exclusively involved olfactory receptors . Comparative analysis also revealed that novel ( study-specific ) CNVRs predominated over shared ones in all 6 studies ( Fig . 4 ) . Novel CNVRs of functional interest from this study involved genes related to sperm-egg interaction and fertilization in chr4:19 . 8–19 . 9 Mb; a developmental gene SOX2 in chr19:20 . 1 Mb; an X-linked region harboring genes of circadian pacemaker function chrX:83 . 8–84 . 0 Mb , and a complex CNVR in chrUn:225–226 kb with cancer related genes . Notably , the latter two CNVRs were found in more than 10 horses each . Details of all novel and shared CNVRs are presented in Table S10 . Nineteen CNVRs were validated by quantitative PCR ( qPCR ) using array probe-specific primers ( Table S2 ) . The regions were selected upon three criteria – size , gene content and novelty . The smallest tested CNVR was 4 kb and the largest 2 Mb; 13 involved clusters of horse genes , and 6 were novel . A summary of qPCR results are presented in Figure S3 and Table S11 . All selected CNVRs were first tested in the discovery horses and then analyzed in more individuals of the same breed to identify possible breed-specific tendencies . Overall , qPCR observations agreed well ( P-value <0 . 05 ) with the array CGH data for all discovery horses and for other animals of the same breed . For example , it confirmed a complex CNVR in chr27 involving CSMD1 gene ( CUB and Sushi multiple domains 1 ) which encodes a transmembrane and a candidate tumor suppressor protein [43] . Copy numbers in this region were tested on 11 breeds with at least 2 individuals each and showed a gain in native ponies , draft breeds and the Przewalski horse , and a loss in American Miniature horses in relation to the Thoroughbred ( Fig . 5A–B ) . Likewise , qPCR confirmed a CNVR in chr20 ( Fig . 5C ) which has been found only in this study and in indigenous plateau horses [38] . However , we found some differences too between the two data sets: e . g . , while qPCR confirmed a loss in chr20:32 . 0–32 . 4 Mb and chr17:18 . 8–19 . 0 Mb in the discovery Swiss Warmblood and Mongolian horses ( Table S3 ) , respectively , inclusion of additional horses from the same breeds resulted in a significant gain in these regions ( Fig . S3 ) . Also , initial qPCR confirmed a loss in chr7:74 . 8–74 . 9 Mb in the two discovery Swiss Warmblood horses ( Table S3 ) but no significant losses were found when more individuals were added . These minor discrepancies can be attributed to intra-breed variation: array CGH was based on 2 to 4 individuals , while qPCR involved 4 or more horses per breed ( Figure S3 , Table S11 ) . Two CNVRs , a complex 200 kb gain-loss region in chr1:114 . 0–114 . 2 Mb and a 2 . 2 kb gain in chrUn: 529–531 kb ) were validated by FISH using CNV-containing CHORI-241 BAC clones 132B13 ( Fig . S4 ) and 91B23 ( Fig . 6 ) , respectively . Clear differences in copy numbers between individual horses , as well as between homologous chromosomes of the same horse were observed . Additionally , the CNVR in chrUn was mapped to horse chr19q12–q13 ( Fig . 6 ) . Finally , we carried out a pilot study to test the utility of the tiling array and the integrated CNV data set ( Table S10 ) for the discovery of CNVs involved in equine XY disorders of sexual development ( XY DSD ) . Selection of the phenotype was based upon studies in humans suggesting contribution of CNVs to XY DSDs [25] , [27] , [28] . Array CGH experiments were carried out in 6 affected horses ( Table 4 ) : all had normal male 64 , XY karyotype with an intact SRY gene , abnormal male or female gonads , and female or female-like external phenotype [44] . We determined 179 CNVs ( average 30 calls per individual ) and 107 CNVRs , of which 83 were common and shared with normal equine populations , and 24 CNVRs were novel ( Table 5 ) . Only 3 novel CNVRs were shared between two or three XY DSD horses , while the remaining 21 were private and present in just one animal . Protein coding or miRNA genes with functions in cell cycle regulation , transcription and posttranscriptional processing were involved in 14 novel CNVRs . None of the CNV-genes had known functions in sexual differentiation or development . Analysis of common CNVRs for highly aberrant log2 values detected two likely homozygous deletions ( Table 5 ) : a 26 kb loss in chr7 ( log2 −2 . 2 ) and a ∼200 kb loss in chr29 ( log2 −3 . 5 ) . The latter was of particular interest because it was found in two closely related American Standardbreds with very similar male-pseudohermaphrodite phenotypes ( H348 and H369; Table 4 ) . The CNVR was also present in 10 out of the 38 normal horses ( Table S3 ) including one American Standardbred , though with a moderate aberration value ( log2average −0 . 7 ) compared to log2 = −3 . 5 in the two XY DSD horses . Most notably , the CNVR involved at least 4 members of the aldo-keto reductase AKR1C gene family , known to be critical in the backdoor pathway of dihydrotestosterone ( DHT ) synthesis and sexual development [45] , [46] . A schematic overview of the CNVR , including the involved genes and aberration profiles of all 47 array probes in the region , is presented in Fig . 7 . Homozygosity of the deletion was confirmed by fluorescence in situ hybridization ( FISH ) with a BAC clone ( CHORI-241-23N13 ) spanning the deletion . The BAC hybridized to chr29 in control animals but not in the two XY DSD horses , whereas a control BAC ( CHORI-241-76H613 ) with the CREM gene from a non-CNVR in chr29 [47] hybridized equally in the XY DSD horses and controls ( Fig . 7 ) . Homozygosity of the deletion was further confirmed by PCR showing that primers designed inside the CNVR amplified genomic DNA of control horses and the remaining 4 XY DSD horses , but not of the two male-pseudohermaphrodite American Standardbreds ( H348 and H369; Fig . 7 ) . Though primers designed outside the CNVR , amplified the DNA by PCR in all horses – an evidence that the DNA quality of the two Standardbreds was acceptable . We theorized that the homozygous deletion involving AKR1C genes in the two male-pseudohermaphrodite horses might be the risk factor for abnormal sexual development .
The present and all previous CNV studies in horses [35] , [36] , [37] , [38] , [39] differ by discovery platforms , genome coverage , resolution , the study cohorts and analytical methods ( Table 6 ) . Therefore , the overall numbers , size ranges and chromosomal distribution of CNVs vary between the studies . For example , it has been shown that due to analytical reasons , CGH-based studies tend to detect more losses than gains [59] . This holds true for the Agilent WG array in the present study and also the Nimblegen WG array [38] , though [38]slightly more gains were detected with the Agilent exon array [39] ( Table 6 ) . The latter was attributed to the large number of losses in the reference animal compared to the Thoroughbred ( Twilight ) genome sequence assembly EquCab2 [56] . In contrast , gains vastly predominate ( 97% ) among the CNVs found by NGS in a Quarter Horse mare [35] . Apparent differences in CNV calling algorithms and thresholds ( Table 6 ) , on the other hand , are responsible for the variation in the number of CNVs , their size and the criteria for merging individual CNVs into CNVRs . For example , in this study we mainly reported CNVRs because this is how the ADM-2 algorithm analyses and assembles the CNV calls ( CNVs ) within and across individuals . Further , specific features of the probe/array design , and not necessarily the number of probes , are responsible for the differences in the genomic distribution of discovered CNVs . So far , X-linked CNVs have been found only in this study and by Doan & colleagues [39] , and CNVs in chrUn only in this study . Surprisingly , the study with a three times denser 1 . 3 M Nimblegen array failed to detect CNVs in chrX , as well as in [38] chrs30 and 31 [38] . At the same time , the latter two small autosomes show the highest number of CNVs in the Quarter Horse mare [35] . Major differences are also in the size , diversity and origin of the study cohorts , ranging from just a few breeds and individuals [35] , [38] to over 15 breeds ( this study and [37] ) and hundreds of individuals [36] , [37] ( Table 6 ) . The many variables between the six studies ( Table 6 ) obviously confound assessments based solely on CNV metrics , and it would probably be more appropriate to compare the actual CNVs/CNVRs reported . Therefore , and in order to obtain a comprehensive overview about the status of CNV discovery in horses , we integrated the CNVs or CNVRs from all six studies ( [35] , [36] , [37] , [38] , [39] , this study ) according to their genomic locations into a composite dataset of 1476 CNVRs ( Table S10 ) . Of these , 301 are reported by at least two studies , while the remaining 1174 CNVRs are study-specific ( novel; Fig . 4 ) and require further validation . The integrated dataset is a needed resource for evaluating new CNV discoveries and gives an idea about the most intrinsic features of the CNV profile in horses . Copy number variants account for about 1 to 3 % of the horse genome and there are more CNVs that involve genes than those located in intergenic regions . Though , the number of intergenic CNVs is possibly deflated because all tiling arrays [38] , [39] , including ours , have been biased towards probes for gene exons . For example , 20% of the probes in the Texas-Adelaide WG array represent protein coding genes , whereas these genes make up only about 2–3% of the mammalian genome . Notably , all studies find chr12 as the most CNV-enriched ( Table 6 ) and not because of many CNVs , but because of a few very large clusters of olfactory receptors and immunity-related genes ( Tables S8 , S10 ) . Studies in human [3] , [60] , dogs [8] and cattle [30] have noted strong correlation between CNVs and segmental duplications ( SDs ) . This is because SDs share 90% sequence similarity with another genomic location and can promote CNV formation by non-allelic homologous recombination [61] . Similar tendency has been observed in horses [39] , although horse SDs are relatively small ( largest ∼60 kb ) and comprise only about 0 . 5–0 . 6 % of the genome [56] , thus less than the portion involved in CNVs ( Table 6 ) . Low level of SDs or low copy number repeats was also reported by a recent de novo analysis of the equine genome where no novel classes or types of interspersed repeats were identified [62] . An additional 0 . 4% of SDs are in unplaced contigs ( chrUn ) [56] , though in this study only 0 . 04 % of chrUn sequences had CNVs ( Table 2 ) . Likewise , chr25 which is the most SD-rich chromosome ( 1 . 7% ) according to EquCab2 genome assembly [56] , was only moderately enriched with CNVs ( 0 . 35% ) in this study . Yet , findings by us and others support the correlation between CNVs and SDs in some genomic regions . For example , a known large ( 750 kb ) segmental duplication at the boundary of ELA class I and class III [63] falls into a large common CNVR in chr20:30 , 127 , 886–31 , 231 , 182 ( Table S10 ) ; further , low copy number directional repeats have been associated with large deletions in the horse Y chromosome [44] or , GO categories , such as olfactory reception and immune response , prevail among the genes involved both in CNVs and SDs [52] . Therefore , for improved understanding of the genomic architecture of CNVs and their relation to genes and phenotypes in horses , it would be worthwhile to focus future CNV research on associations between CNVs and SDs , as recently successfully done in dogs [8] . It is noteworthy that regardless of the discovery methodology and study cohorts , functional groups of genes that are most affected by CNVs remain the same in all studies . These include genes for transmembrane signal transduction and chemo-attractant sensory perception ( olfactory and non-olfactory G-protein coupled receptors , GPCRs ) , immune response ( immunoglobulins , T-cell receptors , MHC protein complexes ) , and steroid metabolism ( Table S9 ) . Not coincidentally , CNVs are associated with the same groups of genes in humans [3] , [64] , cattle/ruminants [30] , [65] , [66] , pigs [31] , dogs [32] and even chicken [67] , suggesting the importance of inter-individual variation in these genes for adaptive plasticity [68] . Indeed , genetic diversity and fine functional tuning of sensory receptors , immunoglobulins , natural killer and Toll-like receptors is further enhanced by additional mechanisms , such as asynchronous replication which increases the rate of tandem duplications , and monoallelic expression , so that each sensory neuron or lymphoid cell expresses only one allele of a gene [69] , [70] . Conserved linkage between distinct olfactory receptor genes and the MHC in several mammalian species suggests their concerted function - in this case , MHC-influenced mate choice in reproduction [71] . Olfactory receptors are also thought to function as chemo-sensing receptors to regulate sperm density , motility , acrosome reaction and sperm-egg interaction in fertilization [71] , [72] . Thus functionally , the CNV-enriched genes in horses and other mammals fall into just three large categories: sensory perception , immunity and reproduction . Among the 258 CNVRs detected in this study , 20% were located in intergenic regions . These CNVRs were relatively small ( average 50 kb , median 35 kb ) and represented predominantly losses ( Fig . 2 , Table S8 ) . Prevalence of losses among intergenic CNVRs has also been found in dogs [32] . Although there is no information about possible implication of these regions on the function of genes in animal genomes , studies in humans show that intergenic deletions are significantly enriched among gene expression-associated CNVs [73] . Thus , with the improvement of genome sequence assembly and annotation in horses , intergenic CNVRs will be of interest for future studies . We also anticipate that as gene models are revised and converge more with the underlying reality of the genes , some intergenic CNVRs may become genic and vice versa . One of the goals of CNV research in horses is to find variants that distinguish between breeds or groups of breeds and could be associated with specific adaptations and phenotypic traits of interest . In order to visualize the breeds and the degree of diversity represented in this and previous studies , we performed a phylogenetic analysis using population data of 15 microsatellite loci [74] for the breeds involved ( E . G . Cothran , unpublished ) . The dendrogram in Figure 8 shows that while the major clades of domestic horses are represented , there is a clear preponderance of the breeds with Thoroughbred ancestry . It is therefore noteworthy that data for 11 new breeds , mainly representing native ponies and draft horses , were added in this study . Nevertheless , the current tally of horse breeds studied for CNVs is 41 ( Table S12 ) which is less than 10% of the over 400 horse breeds known worldwide [75] . Furthermore , given that just 7 breeds have been involved in 2 or more studies ( Fig . 8 , Table S12 ) and several breeds are represented by one individual [38] , [39] , any CNV reported to be breed-specific should be taken with caution . For example , our composite CNV dataset ( Table S10 ) shows that the 18 CNVs reported to be specific for Hanoverians [37] are present in other breeds . Likewise , only one ( chr13: 1 , 497 , 390 . 00–1 , 508 , 926 . 00; EIF2AK1 ) of the 7 plateau-breed-specific CNVs in heme binding genes [38] is not found in other breeds . The same happened with our data where initially we identified over 10 putative breed-specific CNVs which , after comparison , reduced to 2 - one in Exmoor pony , another in Swiss Warmblood horse ( Table S4 ) . Interestingly , no unique CNVs were found in the Przewalski horse which shared similarity mainly with ponies and draft breeds ( Table S3 ) . Besides , only 9 of the 25 CNVs in Przewalski horses were shared between the two individuals studied . Similar tendency for intra-breed individual variation was observed for domestic horses where private CNVs predominated over the shared ones . Nevertheless , as suggested by other studies in horses [39] , cattle [29] , pigs [31] and dogs [33] , we anticipate that a small percentage of CNVs might remain unique to their respective breeds , though this requires analysis of much larger and more diverse equine populations . On the other hand , most horse breeds are of recent origin with a good deal of cross-breeding until closed breeds were established which has led to a high degree of haplotype sharing [56] , [76] , and thereby decreased chances for finding breed-specific CNVRs compared to species like dogs [34] . Probably the most exciting goal of CNV research in any species is the discovery of pathogenic variants responsible for complex diseases and congenital disorders . Among these , disorders of sexual development ( DSDs ) are not uncommon in horses , though causative mutations have been identified for just a few: Y chromosome deletions in SRY-negative XY sex reversal mares [44] and a point mutation in the androgen receptor gene in 3 related SRY-positive XY mares [77] . Here , we conducted the first pilot CNV analysis in horses with XY DSD and identified a large autosomal ( chr29 ) deletion in 2 related American Standardbreds ( H348 and H369 , Table 4 ) . The animals were classified as male pseudo-hermaphrodites with XY male genotype , immature testes-like abdominal gonads , and female-like external phenotype ( Table 4 ) . The deletion in chr29:28 . 6–28 . 8 Mb was homozygous as confirmed by FISH and PCR , and involved at least 8 genes of which 4 belonged to the aldo-keto reductase family 1 , member C ( AKR1C; Fig . 7 ) . Annotation of these genes in the equine genome is , as yet , preliminary and based on the alignment with human AKR1C proteins in the UCSC Genome Browser ( http://genome . ucsc . edu/index . html ) and mammalian homology in Ensembl ( http://www . ensembl . org/index . html ) . Therefore in Fig . 7 , three genes are denoted as AKR1CL1 and one gene has three labels , corresponding to AKR1C2 in chimpanzee , AKR1C3 in human , and AKR1C4 in cattle . The AKR1C genes are members of the aldo-keto reductases ( AKR ) superfamily [78]and encode for 3α-hydroxysteroid dehydrogenases [78] which are critically involved in steroid hormone metabolism [79] . In the human genome , there are 4 family members - AKR1C1 , ALR1C2 , AKR1C3 and AKR1C4 , which share 86% sequence identity and are clustered in HSA10p15-p14 [78] , [79] . The human AKR1C genes are not widely expressed: AKR1C1 in brain , kidney , liver and testis , AKR1C2 in prostate and brain , AKR1C3 in prostate and mammary gland , and AKR1C4 in liver , whereas the rat has a single AKR1C gene expressed in liver[79] , [80] , [81] . Among other functions , the AKR1C genes are involved in the biochemical pathway that leads to dihydrotestosterone ( DHT ) synthesis without testosterone intermediate . As opposed to ‘classical’ DHT synthesis from cholesterol and testosterone , this pathway is known as ‘the backdoor pathway’ and was originally discovered in marsupials [82] and thereafter in eutherian mammals [45] , [46] , [83] , [84] . The importance of the ‘backdoor pathway’ and AKR1C genes in male sexual development was recently demonstrated by a study in humans showing that mutations in AKR1C2 and AKR1C4 genes cause abnormal virilization and disordered sexual development , including XY sex reversal [46] , [84] . Even though no mouse knockout models are available for any of the AKR1C genes ( MGI; http://www . informatics . jax . org/ ) , it is tempting to speculate that the homozygous deletion in horse chr29 is a causative or a risk factor for some forms of equine XY DSDs , such as male-pseudohermaphroditism , as observed in this study . It is also worth mentioning that a CNV analysis of human XY DSDs detected a clinically significant de novo 64 kb duplication in HSA10p14 [28] - a genomic segment next to the AKR1C gene cluster ( UCSC: http://genome . ucsc . edu/cgi-bin/hgGateway ) . Whether this is a coincidence or the region includes more copy number variable factors contributing to DSDs , needs further investigation . [45] , [46] , [84] [84] [28] . Our findings in horses might be of even broader interest because the two deletion carrying horses were elite American Standardbred pacers , Martha Maxine and Arizona Helen ( Table 4 ) , whose problematic sexual identity has become public , making headlines in The New York Times [85] and The Horse [86] . Thus , studies are underway to precisely determine the deletion breakpoints and develop molecular tests for detecting other horses with a similar deletion , as well as heterozygous carriers . Finally , the fact that only 2 XY DSD horses out of 6 had this mutation underscores the phenotypic and genetic heterogeneity of these disorders . This study represents an important contribution to CNV research in horses by identifying new CNVs and developing an integrated datset of 1476 CNVRs to facilitate the discovery of variants of biomedical importance . However , despite progress , the majority of the CNVRs reported for the horse require proper validation by methodologically comparable studies invloving more diverse breeds and individual animals . Last but not least , due to the very nature of CNVs , these regions are likely to have sequence assemblies not as accurate as non-variable regions . Thus , the findings also identified potential targets for genome re-sequencing and -assembly .
Procurement of peripheral blood and hair was performed according to the United States Government Principles for the Utilization and Care of Vertebrate Animals Used in Testing , Research and Training . These protocols were approved by Texas A&M Office of Research Compliance and Biosafety as AUP2009-115 , AUP2012-0250 . CRRC09-32 and CRRC09-47 . A horse WG tiling array was designed using the horse genome draft sequence ( EquCab2 , http://www . ncbi . nlm . nih . gov/assembly/286598; [56] , Oligowiz2 . 0 ( http://www . cbs . dtu . dk/services/OligoWiz/ ) , ArrayOligoSelector ( http://arrayoligosel . sourceforge . net/ ) , and ArrayDesign [87] software packages . The array comprised 417 , 377 60-mer oligonucleotide probes: 85 , 852 probes corresponded to one or more exons of the 18 , 763 annotated equine genes ( http://www . ncbi . nlm . nih . gov/genome/genomes/145 ? ) ; 305 , 416 probes originated from intergenic regions ( excluding sub-telomeres ) ; 5 , 716 probes were designed from sub-telomeres ( the terminal 1 Mb of each chromosome ) , and 519 probes represented the horse Y chromosome [58]; our unpublished data ) . [87]For intergenic probes , including chrUn , repeat-masked ( http://www . repeatmasker . org/ ) sequences were used . For reference genes , we first designed probes from exons . If these were not specific , attempts were made to design probes from introns and upstream/downstream flanking regions of those genes . Before inclusion in the array , the specificity of all sequences were analysed with BLAT ( http://www . kentinformatics . com/ ) and BLAST ( http://blast . ncbi . nlm . nih . gov/Blast . cgi ) against the EquCab2 reference genome sequence . Probes with more than one hit in the genome were discarded . Possible cross-hybridization of the probes was further evaluated using Kane's parameters [88] and all probes that had a total percent identity >75–80% with a non-target sequence , or probes with contiguous stretches of identity >15 nucleotides with a non-target sequence were discarded . Only probes with high specificity were kept in the final array . A Cytoband file was generated to align the horse draft sequence assembly with the cytogenetic map [89] . The array , designated as the Texas-Adelaide horse WG tiling array , was fabricated by Agilent Technologies using Agilent SurePrint G3 technology and 2×400K chip format ( two arrays on a single slide ) . The array is available at Agilent Technologies; Design ID #030025 , Cat . No G4124A . The CNV discovery cohort comprised 38 horses representing 16 diverse breeds and the Przewalski's horse ( Table S1 ) . Horse breeds were selected according to the recent population studies [51] , [56] , [76] , [90] with an aim to maximize the genetic diversity among samples and to encompass the common warm blood , cold blood ( draft ) and native pony breeds . An additional cohort of 52 normal horses representing the same 16 breeds was used for quantitative PCR validation of CNVs . Finally , a pilot study testing the utility of the tiling array for the discovery of CNVs contributing to equine congenital disorders used 6 horses previously diagnosed with XY disorders of sexual development ( XY DSDs; Table 4 ) [44] . Genomic DNA was isolated from peripheral blood or hair follicles using QIAGEN Gentra PureGene Blood kit ( Qiagen ) according to manufacturer's protocol . The DNA was cleaned with DNeasy Blood and Tissue kit ( Qiagen ) and quality checked by gel electrophoresis and by Nanodrop spectrophotometry ( Thermo Scientific ) . Probe labeling and array CGH experiments were performed according to Agilent Technologies Protocol Version 7 . 3 , March 2014 ( http://www . chem . agilent . com/Library/usermanuals/Public/G4410-90010_CGH_Enzymatic_7 . 3 . pdf ) . All hybridizations comprised of a pair of differently labeled probes , one of which was always the reference DNA – a Thoroughbred mare Twilight for females and a Thoroughbred stallion Bravo for males ( see explanations below ) . The genomic DNA ( gDNA ) was cleaved to 200–500 bp fragments with RsaI and AluI ( Promega ) and labeled with Cy3 ( the reference DNA ) or Cy5 ( sample DNA ) by random priming using Genomic DNA Enzymatic Labeling Kit ( Agilent Technologies ) . The products were cleaned with 30 kDa filters ( Amicon ) and the yield and specific activity of labeled DNA was determined with a Nanodrop spectrophotometer . Typical yield for 1 µg of starting DNA was 6–8 µg; specific activity for Cy3 was 25–40 pmol/µg and for Cy5 20–35 pmol/µg . The hybridization mixture was prepared using Agilent Oligo aCGH Hybridization Kit and contained equal quantity of Cy3 and Cy5 labeled probes , 1 µg/µL horse Cot1 DNA , 10× blocking agent , and 2× Hi-RPM buffer . Denatured and pre-annealed probe mixture was applied onto gasket slide , placed in Agilent SureHyb hybridization chamber , ‘sandwiched’ with an array slide and incubated in Agilent hybridization oven at 65°C for 40 hours . The array slides were washed with Agilent aCGH Wash Buffers 1 and 2 and dried with Acetonitrile and Stabilization and Drying Solutions ( Agilent Technologies ) . The slides were scanned with Agilent SureScan DNA Microarray Scanner and Scanner Control software v8 . 3 . The data were extracted and normalized with Agilent Feature Extraction software v10 . 10 . 1 . 1 and saved in . fep format . The Feature Extraction software also checks the quality of aCGH by measuring Derivative Log2 Ratio Standard Deviation ( DLRSD ) , Signal-To-Noise Ratio ( SNR ) and Background Noise ( BGNoise ) . The data were analyzed with Agilent Genomic Workbench 5 . 0 software . In each array spot log2 ratios of Cy3 versus Cy5 were computed with the default P-value threshold 0 . 05 and overlap threshold value 0 . 9 . The CNVs were represented by gains and losses of normalized fluorescence intensities relative to the reference and called by conservative criteria which required alterations of >0 . 5 log2 ratios over 5 neighboring probes . Homozygous losses were called when signal log2 ratio was <−2 . 0 . Copy number variable regions ( CNVRs ) were determined by ADM-2 algorithm [91] by combining overlapping and adjacent CNVs in all samples across the CGH experiments . Output files were generated with genomic coordinates and cytoband locations for all CNVs . The raw data were submitted to NCBI Gene Expression Omnibus ( GEO ) accession GSE55266 . To evaluate baseline variations and determine FDR [92] , [93] female and male self-to-self , and female-to-male control hybridizations were conducted using blood DNA from one female and one male Thoroughbred horses . The female Thoroughbred , Twilight , was the DNA donor for the horse reference sequence EquCab2 [56] and the origin of the probes on the tiling array . The male Thoroughbred , Bravo , a half-sibling to Twilight , was the DNA donor for the CHORI-241 BAC library ( http://bacpac . chori . org/equine241 . htm ) and the origin of all Y chromosome probes on the array . The FDR was calculated as a percentage of the ratio of CNVs in self-to-self hybridization to the total number of CNVs in all experiments . Additionally , array performance was evaluated by self-to-self hybridizations with blood and hair DNA from one Quarter Horse ( H528 , Table S1 ) . Hybridization quality was assessed by DLRSD which calculates probe-to probe log ratio noise of an array; ( http://www . chem . agilent . com/Library/applications/5989-6624EN . pdf ) : DLRSD <0 . 2 was considered excellent; 0 . 2≥DLRSD≤0 . 3 was good , and values >0 . 3 indicated poor quality hybridization . Horse chromosome enrichment percentage was determined by the total length of CNVRs present in each chromosome , divided by chromosome length ( Ensembl , http://www . ensembl . org/index . html ) . Ensembl gene list ( Ensembl Genebuild 73 . 2 ) along with their position in the horse genome was added to Agilent Genomic Workbench as a custom track to determine the genic and intergenic CNVs . Gene Ontology analysis ( GO ) and Kyoto Encyclopedia of Genes and Genomes ( KEGG ) pathway analysis of the genes present in CNVs were performed using DAVID bioinformatics tool with default settings [94] , [95] . Because only a limited number of genes in the horse genome have been annotated , horse gene IDs were converted to orthologous human Ensembl gene IDs by BioMart , followed by GO and pathway analyses , as described above . Biological functions of the genes in CNVRs were further analyzed manually by data mining in Ensembl ( http://www . ensembl . org/index . html ) , UCSC ( http://genome . ucsc . edu/ ) and NCBI ( http://www . ncbi . nlm . nih . gov/ ) Genome Browsers searching for data for equine orthologs in other mammalian species . CNVs present in intergenic regions were analyzed in UCSC genome browser and NCBI and GeneCards ( http://www . genecards . org/ ) for similarities to known mammalian genes . A composite CNV dataset for the horse ( Table S10 ) was generated by aligning genomic positions of CNVs/CNVRs from this and all previously published studies [35] , [36] , [37] , [38] , [39] . Partially or completely overlapping and adjacent CNVs ( the end position of a previous CNV and the start position of the next CNV are the same ) were consolidated into one CNVR . Genomic copy number changes as detected by aCGH were validated by quantitative PCR ( qPCR ) for 18 selected CNVRs using 22 probe-specific primers . Additionally , 8 putative homozygous deletions were validated by regular ( qualitative ) PCR . Primers ( Table S2 ) were designed inside CNVRs using array probe sequences and the horse whole genome sequence information ( EquCab2 at UCSC: http://genome . ucsc . edu/and Ensembl: http://www . ensembl . org/index . html ) and Primer3 software ( http://bioinfo . ut . ee/primer3-0 . 4 . 0/primer3/input . htm ) . The qPCR experiments were performed with LightCycler 480 ( Roche Diagnostics ) in triplicate assays . Each assay was done in triplicate 20 µL reactions containing 50 ng of template DNA , 10 µM primers and the SYBR Green PCR kit ( Roche ) . Relative copy numbers of the selected regions were determined in comparison to the reference sample ( Thoroughbred and Quarter Horse ) and normalized to an autosomal reference gene GAPDH . The cycling conditions were 1 cycle 5 min at 95°C; 45 cycles 10 sec at 95°C , 5 sec at 58°C , and 10 sec at 72°C; 1 cycle for melting curve 30 sec 95°C , 30 sec 65°C and final cooling 20 sec at 50°C . Quantification of the copy number was carried out using the comparative CT method ( 2ΔΔCt ) [96] , [97] with p<0 . 05 as a cut-off threshold for statistical significance . Qualitative PCR results were analyzed by agarose gel electrophoresis . CNV specific primers were used to screen CHORI-241 BAC library ( http://bacpac . chori . org/equine241 . htm ) by PCR ( Table S2 ) ; BAC DNA was isolated by Plasmid Midiprep kit ( Qiagen ) , labeled with biotin-16-dUTP or digoxigenin-11-dUTP using Biotin- or DIG-Nick Translation Mix ( Roche ) , and hybridized to metaphase chromosomes of CNV carriers and control horses following standard protocols [98] . A BAC clone representing a non-CNV region was used as a control in each FISH experiment . Images for a minimum of 20 metaphase and/or interphase cells were captured for each experiment and analyzed with a Zeiss Axioplan2 fluorescent microscope equipped with Isis v5 . 2 ( MetaSystems GmbH ) software . Genotypes for 15 microsatellite loci [74]; E . G . Cothran , unpublished ) were available for 32 out of 41 horse breeds involved in CNV studies ( see Table S12 ) . Majority-rule consensus of Restricted Maximum Likelihood ( RML ) trees were constructed and visualized as described elsewhere [74] . The Przewalski Horse population was used as an out-group . | Genomes of individuals in a species vary in many ways , one of which is DNA copy number variation ( CNV ) . This includes deletions , duplications , and complex rearrangements typically larger than 50 base-pairs . CNVs are part of normal genetic variation contributing to phenotypic diversity but can also be pathogenic and associated with diseases and disorders . In order to distinguish between the two , detailed knowledge about CNVs in the species of interest is needed . Here we studied the genomes of 38 normal horses of 16 diverse breeds , and identified 258 CNV regions . We integrated our findings with previously published horse CNVs and generated a composite dataset of ∼1400 CNVRs . Despite this large number , our analysis shows that CNV research in horses needs further improvement because the current data are based on 10% of horse breeds and that most CNVRs are study-specific and require validation . Finally , we analyzed CNVs in horses with disorders of sexual development and found in two male pseudo-hermaphrodites a large deletion disrupting a group of genes involved in sex hormone metabolism and sexual differentiation . The findings underline the possible role of CNVs in complex disorders such as development and reproduction . | [
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The saliva of blood-feeding arthropods contains a notable diversity of molecules that target the hemostatic and immune systems of the host . Dipetalodipin and triplatin are triatomine salivary proteins that exhibit high affinity binding to prostanoids , such as TXA2 , thus resulting in potent inhibitory effect on platelet aggregation in vitro . It was recently demonstrated that platelet-derived TXA2 mediates the formation of neutrophil extracellular traps ( NETs ) , a newly recognized link between inflammation and thrombosis that promote thrombus growth and stability . This study evaluated the ability of dipetalodipin and triplatin to block NETs formation in vitro . We also investigated the in vivo antithrombotic activity of TXA2 binding proteins by employing two murine models of experimental thrombosis . Remarkably , we observed that both inhibitors abolished the platelet-mediated formation of NETs in vitro . Dipetalodipin and triplatin significantly increased carotid artery occlusion time in a FeCl3-induced injury model . Treatment with TXA2-binding proteins also protected mice from lethal pulmonary thromboembolism evoked by the intravenous injection of collagen and epinephrine . Effective antithrombotic doses of dipetalodipin and triplatin did not increase blood loss , which was estimated using the tail transection method . Salivary TXA2-binding proteins , dipetalodipin and triplatin , are capable to prevent platelet-mediated NETs formation in vitro . This ability may contribute to the antithrombotic effects in vivo . Notably , both molecules inhibit arterial thrombosis without promoting excessive bleeding . Our results provide new insight into the antihemostatic effects of TXA2-binding proteins and may have important significance in elucidating the mechanisms of saliva to avoid host’s hemostatic responses and innate immune system .
To take a blood meal , triatomine bugs pierce the host skin searching for a blood vessel , which causes tissue damage and elicits the hemostatic response of the vertebrate host against blood loss . The first mechanism of vertebrate defense to counteract blood loss is constituted by platelet aggregation that forms the primary hemostatic plug . Following vascular injury , a number of extracellular matrix proteins , such as collagen and von Willebrand factor ( vWF ) , are exposed to flowing blood , thus initiating platelet adhesion [1] . The initial tethering induces platelet deceleration and “rolling” along the exposed extracellular matrix until stable adhesion can occur . This activation causes a cytoskeletal reorganization to change the platelet shape and cover a larger surface area at the site of damage . It also induces intracellular signaling , leading to cellular activation and the release of second wave mediators , such as adenosine diphosphate ( ADP ) and thromboxane A2 ( TXA2 ) , that amplify the activation signal and recruit additional platelets to the growing thrombus [2 , 3] . TXA2 is synthesized from membrane-released arachidonic acid during platelet activation and plays an important role in the positive feedback for activation and the recruitment of additional platelets to the primary hemostatic plug , thus contributing to thrombus formation [4] . Salivary glands from hematophagous animals constitute a major source of molecules capable of modulating hemostasis [5–7] . Blood-sucking-derived antihemostatic molecules are comprised of a notable diversity of platelet aggregation inhibitors , including enzyme inhibitors , nitric oxide ( NO ) -releasing molecules , integrin antagonists , apyrases , collagen-binding proteins and molecules that bind biogenic amines [6 , 8] . Dipetalodipin and triplatin , two salivary proteins belonging to the lipocalin family , have been recently characterized as high-affinity prostanoid-binding proteins that modulate platelet function , vasoconstriction , and angiogenesis [9 , 10] . Remarkably , both proteins are potent TXA2 scavengers , which explain their inhibitory effects on platelet aggregation induced by low concentrations of collagen , arachidonic acid and the TXA2 mimetic ( U46619 ) . In addition to hemostasis , the host’s response against tissue injury involves recruitment of inflammatory cells [5] . Neutrophils constitute the first line of defense against infection , since they are involved in phagocytosis and the intracellular degradation of invading microorganisms [11] or creating an extracellular environment to kill pathogens by a mechanism involving neutrophil extracellular traps ( NETs ) [12] . NETs have been described as web-like structures of DNA and proteins form through a process called NETosis [13] and they have been recently linked to blood coagulation [14] and platelet activation [15] . It is proposed that platelets play a relevant role in neutrophil functions [16 , 17] . In this context , it has been recently described that platelet-induced NET formation depends on the production of TXA2 [18] . In this study , we investigated the in vivo effects of dipetalodipin and triplatin on thrombus formation using two distinct mice models . Remarkably , both molecules inhibited arterial thrombosis and collagen-induced thromboembolism at doses that caused no bleeding effects . In addition , dipetalodipin and triplatin abolished the platelet-mediated formation of NETs . We conclude that TXA2 scavenger might represent an important mechanism of action of saliva to avoid host’s hemostatic responses and innate immune system .
Blood products used in this study were obtained from the Blood Bank at the University Hospital Clementino Fraga Filho from the Federal University of Rio de Janeiro ( Rio de Janeiro , Brazil ) . Blood donation was obtained from healthy adult subjects upon written informed consent . The use of blood products for research was further approved upon oral informed consent due to the elevated number of specific research projects and because the risks were low and the potential harm for participants was unlikely . Oral consent for the use of plasma and blood cells in this study was approved by The Committee for Ethics in Human Research ( CEP-HUCFF/FM 213/07 ) . The oral consent was documented in an appendix form of the blood donation written consent that states: “I also , authorize that the surplus of samples and cells of the bags , when not indicated to be applied in clinical can be used in research in basic sciences for health promotion . I am aware that research projects will be selected by the technical employee responsible for the transfusion service , with the criterion of being proven by the rules approved by the research ethics in Brazil , through the authorized organism—the National Council of Ethics ( CONEP ) . ” All animal care and experimental protocols were conducted following the guidelines of the institutional care and use committee ( Committee for Evaluation of Animal Use for Research from the Federal University of Rio de Janeiro , CAUAP-UFRJ ) and the NIH Guide for the Care and Use of Laboratory Animals ( ISBN 0-309-05377-3 ) . The protocols were approved by CAUAP-UFRJ under registry #IBQM/081-05/16 . Technicians dedicated to the animal facility at the Institute of Medical Biochemistry ( UFRJ ) carried out all aspects related to mouse husbandry under strict guidelines to insure careful and consistent handling of the animals . Recombinant dipetalodipin and triplatin were produced in Escherichia coli , purified , and quantified as described previously [9 , 10] . Standard collagen ( equine fibrillar type I Horm [type I/H] ) , was obtained from the Chrono-Log Corp . ( Haverstown , PA , USA ) . Anasedan ( xylazin ) and Dopalen ( ketamin ) were purchased from Agribrands ( Rio de Janeiro , RJ , Brazil ) . Epinephrine , HISTOPAQUE solution ( 10771 ) , phorbol myristate acetate ( PMA ) , L-α-phosphatidylcholine ( PC ) , and L-α-phosphatidylserine ( PS ) were purchased from the Sigma Chemical Co . ( St . Louis , MO , USA ) . A rabbit polyclonal antibody against histone H3 ( citrulline R2 + R8 + R17; ab5103 ) was from Abcam ( San Francisco , CA , USA ) and a goat anti-rabbit IgG labeled with Alexa 488 was from Molecular Probes ( São Paulo , SP , Brazil ) . Hoechst 33342 was purchased from Life Technologies ( São Paulo , SP , Brazil ) . Phospholipid vesicles ( PC/PS ) composed of 75% PC/25% PS ( w/w ) were prepared by sonication . Briefly , phospholipids in chloroform were dried with a N2 stream and lyophilized . The lipids were resuspended in 50 mM Tris-HCl and 150 mM NaCl ( pH 7 . 5 ) sonicated for 10 min and adjusted to a final concentration of 500 μM . The effect of dipetalodipin and triplatin on collagen-induced plasma clotting was evaluated on an Amelung KC4A coagulometer ( Labcon , Heppenheim , Germany ) as previously described [19] with slightly modifications . Coagulation time was monitored in human citrate-anticoagulated platelet-rich plasma ( PRP ) or in platelet-poor plasma ( PPP ) supplemented with 10 μM PC/PS . Human blood samples were collected from healthy donors in 3 . 2% trisodium citrate ( 9:1 , v/v ) ; PRP was obtained by centrifugation at 800 × g for 10 min and PPP was obtained by further centrifugation of the PRP at 2 , 000 × g for 10 min . Briefly , dipetalodipin ( 1 μM ) or triplatin ( 2 μM ) was incubated with collagen ( 50 μL ) for 10 min , at 37°C , before adding 50 μL of PRP or PPP containing PC/PS . After 10 min , clotting was triggered by the addition of CaCl2 ( 16 . 6 mM , final concentration ) . Whole blood from healthy donors was obtained by venipuncture in 3 . 2% sodium citrate ( 9:1 , v/v ) . Warmed ACD ( 85 mM sodium citrate , 110 mM glucose , 71 mM citric acid ) was added to the blood ( 1:9 v/v ACD to anticoagulated whole blood ) and centrifuged for 10 min , at 200 × g , at room temperature . The supernatant platelet-poor plasma ( PPP ) layer was discarded and the platelet pellet was gently resuspended in 1 mL of modified HEPES/Tyrode buffer ( 129 mM NaCl , 0 . 34 mM Na2HPO4 , 2 . 9 mM KCl , 12 mM NaHCO3 , 20 mM HEPES , 1 mM MgCl2 , 5 mM glucose pH 7 . 3 ) containing 150 μL of ACD . An additional 10 mL of modified HEPES/Tyrode buffer containing ACD was added , and the platelets were washed once and then separated by centrifugation at 1 , 000 × g for 15 min at room temperature . The platelet pellet was resuspended in modified HEPES/Tyrode buffer and adjusted to a concentration of 5 × 105 platelets/mL . Whole blood ( collected in 3 . 2% sodium citrate ) from healthy donors was diluted in an equal volume of PBS , and 10 mL were layered over 5 mL of HISTOPAQUE solution ( 10771 , Sigma Aldrich ) , and centrifuged at 400 × g for 40 min at room temperature . The lower interphase , which contained the granulocytes , was collected and transferred to a 15-mL Falcon tube and resuspended in 10 mL of ammonium chloride lysis buffer ( 1 . 7 M NH4Cl , 0 . 1 M KCO3 , 9 . 9 × 10−4 M EDTA ) to lyse red blood cells . Lysis was carried out twice followed by centrifugation for 10 min at 400 × g . Neutrophils were washed with PBS and resuspended at 1 x 106 cells/mL in high glucose DMEM ( GIBCO ) . Neutrophils were kept on ice . Neutrophils ( 5 × 104 ) were treated with 5 nM PMA , platelets ( 5 × 105 ) , or platelets activated with 1 . 3 μg/mL collagen . In selected experiments , the neutrophils were pretreated with dipetalodipin ( 1 μM ) or triplatin ( 1 μM ) prior to stimulation . Cells were seeded onto 13 mm cover-slips ( Glasscyto ) and incubated for 2 h , at 37°C ( except for PMA-treated cells which were incubated for 3 h ) in DMEM . Cells were fixed with 500 μL of 4% PFA for 10 min , washed 3 times with PBS and incubated for 10 min with blocking solution ( PBS , 10% FBS , 5 mg/ml BSA ) . After blocking , the samples were incubated with goat polyclonal anti-human histone H3 antibody at a 1:50 dilution in blocking solution . Samples were washed 3 times with blocking solution , incubated for 2 h with rabbit anti-goat IgG labeled with Alexa 488 at a 1:500 dilution and Hoechst 33342 at a 1:1000 dilution for NETs visualization , and analyzed under a confocal microscope ( Leica , Confocal Microscope LEICA DMI4000 TCS SPE , 20x ) . Images analyses were performed using the Image J software ( NIH ) . Balb/c mice ( both sexes ) were housed under controlled temperature ( 24 ± 1°C ) and light ( 12 h light starting at 7:00 a . m . ) conditions , and all experiments were conducted in accordance with the standards of animal care defined by the Institutional Committee ( Institute of Medical Biochemistry , Federal University of Rio de Janeiro ) . Balb/c mice were anesthetized with intramuscular xylazin ( 16 mg/kg ) followed by ketamine ( 100 mg/kg ) . The right common carotid artery was isolated via a midline cervical incision , and the blood flow was monitored continuously using a 0 . 5VB doppler flow probe coupled to a TS420 flowmeter ( Transonic Systems , Ithaca , NY , USA ) as described previously [20] . Thrombus formation was induced by applying a piece of filter paper ( 1 × 2 mm ) saturated with 7 . 5% FeCl3 solution on the adventitial surface of the artery for 3 min . Mean carotid artery blood flow was monitored for 60 min or until stable occlusion occurred ( defined as a blood flow of 0 ml/min for ≥ 5 min ) , at which time the experiment was terminated . Dipetalodipin or triplatin ( 0 . 2 or 0 . 5 mg/kg ) or phosphate-buffered saline ( PBS ) was injected in the vena cava 15 min before injury . Mice were anesthetized as described above . Dipetalodipin or triplatin ( 0 . 5 or 2 . 0 mg/kg ) or PBS was slowly injected into the inferior vena cava 15 min prior to the challenge . A mixture of 0 . 8 mg/kg collagen and 60 μg/kg epinephrine was then injected into the inferior vena cava . Animals that remained alive after 30 min were considered to be survivors . Mice were anesthetized as described above and injected intravenously with dipetalodipin , triplatin ( 0 . 5 or 2 . 0 mg/kg ) or PBS in 100 μL volumes . After 15 min , the distal 2 mm segment of the tail was removed and immediately immersed in 40 mL distilled water warmed to 37°C . The samples were properly homogenized and the absorbance was determined at 540 nm to estimate the hemoglobin content . No animal was allowed to bleed for more than 30 min . All of the statistical analyses were performed using GraphPad Prism 5 ( GraphPad Software ) . One-way analysis of variance ( ANOVA ) complemented by Tukey's post hoc test was used for comparisons between the test groups . The arterial thrombosis experiments were analyzed by one-way ANOVA with the post hoc Dunnett . The log-rank test was used for the comparison of survival curves . Differences were considered significant when P<0 . 05 . The results were expressed as the mean ± standard error .
Because dipetalodipin and triplatin inhibit platelet aggregation induced by low concentrations of collagen , we first evaluated their effect in counteracting the collagen-mediated acceleration of human plasma clotting . Coagulation experiments were performed using either platelet rich plasma ( PRP ) or platelet poor plasma ( PPP ) . Consistent with previous reports collagen accelerated plasma clotting [19 , 21] , regardless of whether platelets or phospholipids were present in the procoagulant lipid surface ( Fig 1A and 1B ) . However , dipatelodipin and triplatin only abolished this effect in the presence of platelets ( Fig 1A ) . Thus , as shown in Fig 1A , dipetalodipin ( 1 μM ) or triplatin ( 2 μM ) prolonged PRP clotting by 1 . 3-fold compared to collagen measurements ( 155 . 9 ± 12 . 2 s and 161 . 4 ± 12 . 8 s versus 118 . 5 ± 4 . 0 s ) . Addition of collagen to PPP also resulted in a significant shortening of the clotting time , but this effect was not abolished by either dipetalodipin or triplatin ( Fig 1B ) . It has been shown that TXA2 produced by activated platelets is a potential mediator in NET formation [18] . To examine the effects of dipetalodipin and triplatin on this response , neutrophils were exposed to platelets that were previously treated with collagen in the presence or in the absence of dipetalodipin or triplatin . NETs were further identified by the co-localization of extracellular DNA and citrullinated histones . Unstimulated neutrophils ( Fig 2A ) as well as neutrophils treated with resting platelets ( Fig 2B ) or collagen alone ( S1 Fig ) showed negligible release of NETs . In contrast , treatment of neutrophils with PMA , a positive control for NET formation , induced a strong response ( Fig 2C ) . Exposure of the neutrophils to platelets that were previously activated with collagen also evoked robust NET formation ( Fig 2D ) , an event that was dramatically inhibited by either dipetalodipin or triplatin ( 1 μM , Fig 2E and 2F , respectively ) . The in vivo antithrombotic activity of dipetalodipin and triplatin was evaluated by employing two murine models of experimental thrombosis . First , the effect of the TXA2-binding proteins on thrombus formation was assessed using a FeCl3-induced carotid artery injury [20] . Thrombus formation was estimated using a Doppler flow probe that allows for the monitoring of carotid blood flow until the vessel occludes , or for up to 60 min if occlusion does not occur . Fig 3 shows that 7 . 5% FeCl3 applied on top of the carotid artery resulted in a reproducible occlusive thrombosis ( all animals showed complete vessel occlusion within 20 minutes ) . Time to occlusion was not statistically significant between control mice and the mice treated either with 0 . 2 mg/kg dipetalodipin or triplatin , although 4 out of 10 dipetalodipin-treated mice and 2 out of 9 triplatin-treated mice were resistant to arterial occlusion ( Fig 3 ) . It is possible that thrombosis induction at this FeCl3 concentration is less sensitive for the subtle effect of low doses of dipetalodipin and triplatin . In contrast , treatment with 0 . 5 mg/kg of either dipetalodipin or triplatin produced significant resistance to thrombosis , as most animals showed no occlusion over the 60 min period ( Fig 3 ) . The efficacy of dipetalodipin and triplatin in inhibiting thrombus formation was further measured in a murine model of lethal pulmonary thromboembolism , induced by intravenous infusion of collagen and epinephrine . All of the mice treated with vehicle ( PBS , 10 out of 10 ) died within 5 min of collagen/epinephrine infusion ( Fig 4 ) . In contrast , the two groups of dipetalodipin—treated mice were significantly protected from death , with up to 50% of the mice surviving the challenge at the highest dose ( 2 . 0 mg/kg ) ( Fig 4A ) . When triplatin was administered prior to the collagen/epinephrine infusion , we observed a dose-dependent increase in the survival percentage ( 30% at 0 . 5 mg/kg and 60% at 2 . 0 mg/kg triplatin ) ( Fig 4B ) . Analysis of the histological sections of the lung tissues confirmed the presence of massive pulmonary thrombosis in PBS-treated mice , compared with the control mice or animals that were treated with either dipetalodipin or triplatin prior to the collagen/epinephrine challenge ( S2 Fig ) . The effects of dipetalodipin and triplatin in bleeding were estimated using the tail transection method . Fig 5 shows that bleeding was not significantly increased in the presence of antithrombotic concentrations of either of the inhibitors compared with mice receiving PBS . Dipetalodipin and triplatin did not produce bleeding , even at higher doses ( 2 . 0 mg/kg ) .
The systematic study and characterization of proteins from the saliva of blood-feeding arthropods constitutes a strategy for identifying new exogenous inhibitors of hemostasis [5 , 22] . Several hematophagous salivary inhibitors of platelet function have been identified , including enzyme inhibitors , NO-releasing molecules , integrin antagonists , apyrases , collagen-binding proteins and molecules that bind biogenic amines [6 , 8] . Among the platelet inhibitors , members of the lipocalin family have been shown to bind to and remove pro-aggregatory amines such as ADP [23] , epinephrine and serotonin [24] and eicosanoids [9 , 10] . Dipetalodipin and triplatin are proteins that exhibit a unique mechanism of antiplatelet action that consists of a direct interaction with prostanoids , such as TXA2 , preventing their biological effect [9 , 10] . In this report , we demonstrate that dipetalodipin and triplatin prevent platelet-mediated NETs formation in vitro and display antithrombotic activity in vivo . Both lipocalins are abundantly expressed in the salivary gland , and account for approximately 30% of total salivary lipocalins . Assuming a molecular mass of ∼20 kDa for dipetalodipin and triplatin , and the release of 50% of the salivary contents ( ∼1 μg/salivary gland pair ) upon feeding , a concentration of at least 1 μM of the inhibitor could exist in the feeding environment ( ∼15 μl ) ; this concentration is clearly in the range required for inhibition of NETs-formation observed in vitro . Upon activation , neutrophils release granule proteins , DNA and histones to form neutrophil extracellular traps ( NETs ) [25] . NETs formation has been recognized as an important event against pathogens [26] . In addition , in vitro and in vivo studies provide strong evidence that NETs promote thrombus formation by stimulating platelet aggregation , thrombin generation and contact pathway activation [15 , 27] . Of note , DNAse treatment inhibits venous thrombosis in mice [28] , reinforcing the hypothesis that NETs act as prothrombotic scaffolds for the recruitment of platelets and fibrin deposition during thrombus formation in vivo [15 , 27 , 28] . Furthermore , it was recently demonstrated that activated platelets induce the formation of NETs [18 , 28 , 29] . Our experiments demonstrate that dipetalodipin and triplatin reduce the formation of NETs in vitro , indicating that TXA2 produced by activated platelets is required for this process . In this context , inhibition of the TXA2 receptor or pharmacologic inhibition of platelet activation by aspirin impairs NETosis [18] . In addition , platelets contribute to neutrophil activation and NET formation in a murine model of transfusion-related acute lung injury , a process mediated by prostanoids because aspirin has a protective effect [18] . This finding suggests that the antithrombotic effect of dipetalodipin and triplatin may be due to , at least in part , the reduction in platelet-assisted NET formation . Other salivary inhibitors such as agaphelin , also inhibits NETs formation and prevent thrombosis without impairing hemostasis [30] . Interestingly , it has been recently reported that degrading of NETs by Leishmania infantum prevents their killing by neutrophils [31] . In this context , saliva components that modulate the inflammatory responses [32 , 33] as well as those capable to prevent NETs formation may contribute to evasion of parasites , such as trypanosomatids , from host’s innate immune responses . TXA2 , as well as ADP , is secreted by activated platelets and acts as an important second wave mediator for platelet activation and collagen-mediated aggregation . These mediators , which are released by activated platelets at the site of vascular injury are crucial for the establishment and maintenance of the thrombus [2 , 4] . Lack of TXA2 receptors results in thrombus instability and prolonged bleeding times [34 , 35] . Likewise , inhibition of TXA2 synthesis by aspirin results in reduced thrombus formation and high rates of embolization in vivo [36] . In addition , aspirin or TXA2 receptor antagonists reduce collagen-induced thrombus formation in in vitro flow experiments [36] . Accordingly , dipetalodipin and triplatin display antithrombotic activity in vivo , as demonstrated using a FeCl3-induced carotid artery injury model . These results are consistent with the observation that mice deficient in the TXA2 receptor exhibit prolonged occlusion time in the same thrombosis model used in our study [35] . Inhibition of TXA2 by dipetalodipin and triplatin may also explain their protective effects in the pulmonary thromboembolism assay , which is sensitive to compounds with antiplatelet activities [37] , including agents that inhibit the synthesis or action of TXA2 [38 , 39] . Notably , no significant bleeding was observed at antithrombotic doses of dipetalodipin and triplatin . Remarkably , other salivary gland-derived proteins display a similar effect: nitrophorin 2 and desmolaris , which inhibit the contact pathway of blood coagulation , are effective antithrombotic agents in vivo while promoting minor hemorrhagic effects in the tail transection bleeding assay [40 , 41] . This contrasts with other clotting inhibitors , such as the factor Xa inhibitor lufaxin [42] , which target downstream coagulation steps . A well-established mechanism for TXA2 production is through the binding of vWF to the platelet GPIb-IX-V complex . In vitro , this interaction initiates a cellular signaling cascade that elicits TXA2 production , GP-IIbIIIa exposure and platelet aggregation [35 , 43] . In vivo , deletion of components in the signaling cascade initiated by vWF increases the occlusion time of the carotid artery in the FeCl3-induced injury [35 , 44] . Additionally , the platelet-collagen interaction , mediated by GPVI , is involved in TXA2 production [45 , 46] . Our data demonstrated that dipetalodipin and triplatin counteract the collagen-mediated acceleration of human platelet-rich plasma clotting . Therefore , antithrombotic effect of dipetalodipin and triplatin impairs the downstream responses elicited by the platelet-collagen and platelet-vWF interactions , resulting in impaired availability of TXA2 which reportedly plays an important role in arterial thrombus consolidation . Altogether , we demonstrated that salivary TXA2-binding proteins , dipetalodipin and triplatin , are capable to prevent platelet-mediated NETs formation in vitro . Notably , both molecules inhibited arterial thrombosis without promoting excessive bleeding in mice models . Our results provide new insight into the antihemostatic effects of TXA2-binding proteins and may have important significance in elucidating the mechanisms of saliva to avoid the innate immune system . | Chagas disease is transmitted by the protozoan parasite Trypanosoma cruzi . The main form of transmission in endemic areas involves a life cycle in which blood-sucking triatomine vectors get infected by biting an infected animal or person . The saliva of blood-feeding arthropods contains a remarkable diversity of molecules that target the hemostatic and immune systems of the host . Thus , the systematic study and characterization of salivary proteins constitutes a strategy for identifying new exogenous compounds that may serve as prototypes for development of new drugs as well as strategies for vector control . Our group has studied the antihemostatic and antithrombotic properties of several exogenous inhibitors . In this report we demonstrated that the TXA2-binding proteins , dipetalodipin and triplatin , impair platelet-assisted formation of neutrophil extracellular traps ( NETs ) . NETs have been described as web-like structures of DNA and proteins that play an important role in killing of pathogens . In addition , NETs have been recently implicated in thrombus formation . According to this , we demonstrate here that dipetalodipin and triplatin exhibit antithrombotic activity in two distinct in vivo mice models that are highly dependent on platelets . Remarkably , both molecules inhibited thrombosis without promoting excessive bleeding . Altogether , our results provide new insight into the antihemostatic effects of TXA2-binding proteins and may help to elucidate the mechanisms of saliva to avoid host’s hemostatic responses and innate immune system . | [
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] | [] | 2015 | Salivary Thromboxane A2-Binding Proteins from Triatomine Vectors of Chagas Disease Inhibit Platelet-Mediated Neutrophil Extracellular Traps (NETs) Formation and Arterial Thrombosis |
To determine a cost-minimizing option for congenital toxoplasmosis in the United States . A decision-analytic and cost-minimization model was constructed to compare monthly maternal serological screening , prenatal treatment , and post-natal follow-up and treatment according to the current French ( Paris ) protocol , versus no systematic screening or perinatal treatment . Costs are based on published estimates of lifetime societal costs of developmental disabilities and current diagnostic and treatment costs . Probabilities are based on published results and clinical practice in the United States and France . One- and two-way sensitivity analyses are used to evaluate robustness of results . Universal monthly maternal screening for congenital toxoplasmosis with follow-up and treatment , following the French protocol , is found to be cost-saving , with savings of $620 per child screened . Results are robust to changes in test costs , value of statistical life , seroprevalence in women of childbearing age , fetal loss due to amniocentesis , and to bivariate analysis of test costs and incidence of primary T . gondii infection in pregnancy . Given the parameters in this model and a maternal screening test cost of $12 , screening is cost-saving for rates of congenital infection above 1 per 10 , 000 live births . If universal testing generates economies of scale in diagnostic tools—lowering test costs to about $2 per test—universal screening is cost-saving at rates of congenital infection well below the lowest reported rates in the United States of 1 per 10 , 000 live births . Universal screening according to the French protocol is cost saving for the US population within broad parameters for costs and probabilities .
Toxoplasmosis is a disease caused by the protozoan parasite Toxoplasma gondii , whose definitive host is the cat . Prevalence of toxoplasmosis varies greatly across geographic regions , specifically in relation to differences in climate , dietary practices , and hygiene . The most recent reliable estimate of T . gondii seroprevalence in the United States is derived from the National Health and Nutrition Examination Survey ( NHANES 1999–2004 ) . In that survey , sera were obtained from a cluster sample of US residents and tested by the Centers for Disease Control and Prevention ( CDC ) for T . gondii antibodies . Of nearly 16 , 000 persons tested , aged 6–49 years old , age-adjusted seroprevalence was 10 . 8% , and among women aged 15–44 years , it was 11% [45] . Thus , 89% of US women remain susceptible to acute Toxoplasma infection during childbearing years , and their children are at risk for congenital toxoplasmosis . Estimates of incidence of congenital toxoplasmosis are derived primarily from three studies conducted in the United States . In the 1970s , two prospective studies reported rates of congenital infection to be 10 in 10 , 000 live births [46] , [47] . Data from two surveys in Chicago in the 1980s suggest that incidence of CT was 9 in 10 , 000 live births [48] . More recently , data from the New England Regional Newborn Screening Program suggest that congenital infection was detected in 1 in 10 , 000 live births [49] , [50] , using a test similar to one that identifies 50% of infections [51] , [52] . Extrapolated to the approximately 4 million births in the United States each year , an estimated 400–4 , 000 infants are born each year with congenital toxoplasmosis [25] . In the United States , meat ( particularly pork and lamb ) has been identified as an important source of infection , yet the proportion of infection derived from meat versus gardening , eating raw or unwashed vegetables , exposure to cat feces , poor hand hygiene , and other routes that go unrecognized is not known [25] . Epidemiological studies of an outbreak of toxoplasmosis in western Canada in the 1990s implicated the municipal water supply as the source of infection [53] . Other water-borne outbreaks also have been reported [54] , [55] . Most often , congenital transmission occurs in mothers who acquire primary infection during gestation , although in rare cases congenital transmission has occurred due to the reactivation of a chronic infection in women who are immunocompromised ( due to AIDS or various medical treatments ) with subsequent congenital transmission [56] , [57] . Clinical evidence suggests that T . gondii may be present in the placenta for a number of weeks before being transmitted to the fetus , with an observed range from 4 to 16 weeks [57] . The majority of mothers who acquire acute infection during pregnancy fail to display any obvious symptoms , although a minority may present with malaise , low-grade fever , or lymphadenopathy [5] , [56] . Not all mothers who become infected with T . gondii transmit the infection to the fetus; frequency of vertical transmission increases with gestational age . Risk of transmission of maternal infection acquired before conception is virtually zero and transmission rates remain low for approximately the first 10 weeks . After that , the rate of transmission increases sharply , resulting in a steeply increasing incidence of congenital infection , with 2/3 of mothers transmitting after 30 weeks gestation [57] . While infected pregnant women typically present no symptoms , congenital infection may cause fetal death or injuries including vision and hearing deficits , cognitive impairment , or central nervous system lesions . Congenital T . gondii infections have varied manifestations , including symptomatic neonatal disease , with prematurity , rash , thrombocytopenia , illness mimicking out sepsis ( rule out sepsis ) , jaundice , hepatosplenomegaly , hepatitis , anemia , leukopenia or leukocytosis , seizures , meningitis , encephalitis , chorioretinitis or chorioretinal scars , vision loss , intracranial calcifications , hydrocephalus , and microcephalus . Disease , from mild to severe , may manifest within one month of birth or not until childhood or adolescent sequelae from previously undiagnosed infections become apparent , or may include subclinical infection [5] , [6] , [13] . The risk of severe disease is greater when maternal infection is acquired in the first or second trimester [13] . Despite higher rates of transmission of maternal infection to the fetus in the third trimester , transmission that occurs later in pregnancy generally results in subclinical infection or milder manifestations of congenital toxoplasmosis at birth . Congenital toxoplasmosis can be prevented only by preventing maternal infection or by stopping transmission from mother to fetus . Preconceptional and early pregnancy counseling can help women avoid personal exposure to T . gondii in undercooked food or material potentially contaminated by cat excrement . A 1994 study of toxoplasmosis in Belgium found that preconceptional education was associated with a 63% reduction in the rate of seroconversion [58] . Other studies , however , have found that mothers giving birth to congenitally infected infants in the United States commonly do not recognize risk factors for which education would have been effective [59] . Blocking transmission from mother to fetus by treating mothers with acute infection is a second way to prevent fetal infection . Maternal treatment is effective in blocking transmission in up to 60% of treated mothers [22] , [60] . If transplacental transmission occurs , manifestations of fetal infection can be managed and reduced substantially by diagnosing and treating fetal infection in utero . Early diagnosis and treatment of neonates and older children to treat manifest disease or to attempt to prevent disease progression is another option . With universal neonatal screening , intervention to treat neonates and children who present with symptoms has been found to be cost saving [61] . Some proponents of screening programs advocate universal screening of neonates , whereas others emphasize treating only infants who present with symptoms of acute infection , or even not treating at all in the absence of data from placebo-controlled randomized clinical trials that demonstrate efficacy [9] , [14] , [20] , [57] , [62] , [63] . In most cases , congenital infection is subclinical at birth , although sequelae develop over time and may cause damage later in life . Neonatal screening can be achieved at relatively low cost by expanding established newborn screening programs to include tests for toxoplasmosis [49] , [64] . The clear disadvantage of neonatal screening is that it cannot prevent injury sustained before birth , which may be permanent and profound .
A full listing of probabilities and references is given in Table 1 . The probabilities representing the efficacy of treatment at reducing adverse disease outcomes were derived primarily from Parisian data gathered at the reference center in Paris , France [15]–[22] . The percentages of children with disease manifestations reflect lifetime symptoms , not solely those that present at birth and are derived from clinical data and published studies [13] , [57] , [69] , [77]–[80] . Probabilities reflecting prevalence of toxoplasmosis , primary infection in pregnancy , and incidence of CT in the United States were extrapolated from national and regional studies within the United States [45]–[50] . Additional documentation of the probabilities is contained in the file , Text S1 , Supporting Information for Decision Tree and Table of Probabilities , available on line . The perspective of the study is that of societal costs . Cost estimates , the payoffs in the decision tree framework , were derived from Research Triangle Institute's ( RTI ) report , The Cost of Developmental Disabilities [81] . The study used the cost-of-illness ( COI ) approach to assess the lifetime costs of five developmental disabilities ( DD ) , three of which are relevant to congenital toxoplasmosis: severe cognitive impairment , hearing impairment , and visual impairment . By estimating social costs , the value of all resources used or lost as a result of the DD is included in the economic analysis , such as the costs of the medical and nonmedical services and equipment used as a result of the DD , as well as the earning and productivity losses for the infected persons and families who take time to care for the individual with a DD . The costs are incidence-based estimates , which measure the lifetime costs for an individual from the onset of the DD to death . Such estimates attempt to proxy potential cost savings that can be achieved through treatment to prevent or mitigate injury . Table 2 gives the cost estimates for various outcomes of congenital infection , with costs discounted at 3% , which is the recommended discount rate for health interventions used by the World Bank and the World Health Organization in the Global Burden of Disease reports [82]–[84] . We include cost estimates for severe disease requiring home care , while mild disease does not require home care . For outcomes characterized by multiple disabilities of a mild nature , specific DD costs were summed to produce the cost estimate . For outcomes characterized by multiple disabilities of a severe nature , the cost estimate for severe cognitive damage was summed with the cost estimate ( s ) for the other individual disabilities without home care costs , to avoid double counting . Costs were calculated based on normal life expectancy of 76 years and adjusted for impairment-specific survival probabilities [81] . The outcomes of congenital toxoplasmosis listed in Table 2 were selected based on observed clinical outcomes , as confirmed through the medical literature [13] , [57] , [69] , [77]–[80] and personal clinical experience ( RM ) . Indirect costs of psychological impacts borne by family members were not included in the estimates , nor were the costs associated with institutionalization in long-term care facilities . Mild cases are likely to have been underreported [81] . In sum , the assumptions made and limitations in the data are likely to bias the cost estimates downward , yielding a lower-bound estimate of the costs of each DD . Accordingly , the savings associated with prevention or mitigation of each disease outcome are likely to be higher than our estimates . We based the cost of fetal death on the range of estimates for the value of statistical life in the literature ( $5 , 000 , 000 ) adjusted to October 2010 dollars [85]–[89] . This value is assigned to all fetal death outcomes , regardless of direct cause ( disease or amniocentesis ) . Total cost estimates of each disease outcome also include test and treatment costs incurred throughout gestation and one year of postnatal treatment , as shown in Table 3 . At current volumes , serological tests for toxoplasmosis , including IgM , are priced at $12 per test . The Toxoplasmosis panel at a reference lab for confirmation of recent infection costs $385 ( PAMF-TSL , http://www . pamf . org/serology ) . Amniocentesis is assigned a cost of $1300 per procedure ( Personal communication to RM , M . Christmas M . D . , Little Company of Mary Hospital , Chicago , 2011 ) . The total dollar values for test costs included in each cost estimate reflect the cost per test multiplied by the number of tests required throughout pregnancy . Spiramycin is currently not commercially available in the United States . It can be obtained at no cost after consultation with the US Food and Drug Administration through a program with the pharmaceutical company , Sanofi-Aventis; the marginal cost to the firm is negligible because the drug is produced for other uses . Pyrimethamine , sulfadiazine , and folinic acid are used to treat fetal infection directly for the duration of pregnancy starting after the 18th week . At current output , pyrimethamine costs $1 . 56 per day and sulfadiazine costs $12 . 48 per day . Folinic acid costs $0 . 70 per week in parenteral formula administered orally . Treatment with PSF continues for approximately one year after birth , and costs for medicines total $210 for the entire year plus compounding cost of $20 to $50 per week ( the lower value of $20 was used ) . In addition , there are twice-weekly complete blood counts for the mother for the duration of pregnancy and for the baby for the first year of life , at $10 per sample ( ipharma . com , 2011 ) . Total costs for each possible outcome are observable on the decision tree , Figures 1 and 2 , which represent one tree divided to make it readable . Total cost estimates , reflecting test and treatment costs as well as estimated costs of disease , appear at each terminal node ( denoted by a triangle ) , shown as formulae for the sum of each type of cost times its respective repetitions . As an example , a child born with mild visual impairment whose mother was tested at 12 weeks of gestation with a positive result and who transmitted to the fetus , in spite of spiramycin treatment , and was treated with PSF will entail costs as follows: 2 maternal tests + confirmatory test ( Toxo panel at a reference lab ) + amniocentesis + spiramycin ( free ) + PSF for 22 weeks ( full term minus minimum age for PSF of 18 weeks ) + 22 weeks of twice-weekly blood tests for mother + pediatric treatment for 52 weeks ( including blood tests and compounding costs ) + societal costs of mild visual impairment . Figures 3 and 4 show the total costs for each scenario in dollars and the probability of each outcome , as well as the optimal ( cost-minimizing ) path . To determine the robustness of results to key parameters , sensitivity analysis was performed on incidence of primary T . gondii infection during pregnancy , population seroprevalence , risk of amniocentesis , the value of statistical life , and test costs because those variables would have the largest effect on model outcomes . Moreover , they are the variables most likely to vary between populations and thus warrant attention in applying the model to different populations . Net cost is particularly sensitive to seroprevalence because in populations with very low prevalence more mothers must be tested repeatedly throughout pregnancy . Similarly , the societal cost of CT is sensitive in low-incidence populations . The ranges for prevalence and incidence of primary infection during pregnancy were derived from estimates for the United States and regional surveys [13] , [57] , [69] , [77]–[80] . Risk of fetal death from amniocentesis could have a significant impact on societal cost because the full value of statistical life is applied to fetal death . The range for risk of amniocentesis is derived from high and low estimates from CDC and other published sources [90]–[92] . The range for value of statistical life was derived from a search of estimates in the literature [86] , [93] . Especially in low-prevalence populations , test costs could have a large impact on total cost . The upper bound derives from actual costs , and the lower bound is based on the cost of point-of-service tests for other conditions because most of the cost for testing is shipping and administrative expense . Severity of untreated infection seems to vary between populations , suggesting that the South American strain is more virulent than the European strain [27] . Efficacy of treatment , however , appears to be similar between populations [94] . For the US population , therefore , sensitivity analysis is not warranted for efficacy , the value of which is established in the literature [14] , [16]–[18] , [20] , [21] , [56] , [66] .
One-way sensitivity analysis graphs appear in Figures 5 , 6 , 7 , and 8 . The two lines on each graph correspond to the relevant decision ( screening versus no screening ) , and any deviation from horizontal reflects that strategy's sensitivity to the variable under consideration . In our model , only differences in the incidence of primary infection during pregnancy produce a change in the optimal strategy , which occurs below the lower bound of estimates for the United States . As seen in Figure 5 ( enlarged in Figure 6 ) , for rates of primary infection during pregnancy of less than 0 . 0002 , universal screening becomes the non-optimal strategy . Maternal incidence of 0 . 0002 corresponds to incidence of congenital infection on average of 0 . 0001 ( 1 in 10 , 000 ) , based on the 0 . 50 probability of maternal transmission ( over all trimesters ) without treatment [13] , [57] , [69] , [77]–[79] . As a result , in populations with extremely low rates of congenital infection , maternal screening is not found to be cost-saving . For other reasons , one might conclude that screening is the correct decision , but that determination is beyond the focus of this study . For all other variables tested , variation over the specified range of values reveals that the screening strategy is sensitive to those assumptions , but no threshold values are reached ( Figures 7 and 8 , and other analyses not shown ) . The expected value for cost of prenatal screening is less than the expected value for the cost of the no-screening option for all values of the variables tested . Cost savings increase with population seroprevalence ( Figure 7 ) since populations with higher rates of T . gondii infection , over a broad range , have higher rates of seroconversion over childbearing years and thus higher benefits ( lower societal cost of injury ) from screening . High-prevalence populations also have a smaller pool of susceptible women and thus will have lower cost of testing . Conversely , cost savings from universal screening decline with increasing fetal loss rates due to amniocentesis , with increasing serological test costs ( Figure 8 ) , and with cost of amniocentesis , but screening remains dominant . Lastly , variation of the value of statistical life from $600 , 000 to $10 , 000 , 000 had an equal effect on both the screening and no screening strategies . Two-way sensitivity analysis was performed on the variables for test costs and the rate of primary infection during pregnancy . Figures 9 and 10 reveal that reducing test costs effectively lowers the rate of primary infection in pregnancy for which screening is cost saving . Notably , if test costs are lowered significantly ( to roughly $2 per test , which is feasible given the cost of other in-office diagnostic tests ) , screening becomes the optimal strategy even at rates of primary infection in pregnancy well below the lowest reported rates of 2 in 10 , 000 in the United States . The decision-analytic model developed in this paper reveals that for populations with rates of congenital toxoplasmosis greater than 0 . 0001 ( 1 infected child per 10 , 000 live births , or 2 infected mothers per 10 , 000 ) , maternal serological screening is a cost-saving strategy . This finding is robust to changes in seroprevalence , incidence of maternal primary infection , amniocentesis risk , value of statistical life , and test costs . Given current estimates of the rate of congenital infection in the United States , implementation of a universal screening program for congenital toxoplasmosis prevention and treatment is predicted to generate cost savings of approximately $620 per birth . Sensitivity analysis shows that even for populations with extremely low rates of congenital infection , screening is cost saving at a test cost of $12 plus confirmatory test at $385 . Nevertheless , policy makers must be cautious when considering estimates of rates of congenital infection . Some studies have found rates of congenital infection in the United States below 0 . 0001 [49] , [50] , casting doubt on cost saving by universal screening as an intervention strategy at current test costs , although with our estimate of 0 . 0011 for the rate of primary infection in pregnancy , based on the midpoint of estimates from available sources , screening is a cost-saving strategy . Furthermore , if screening is initiated , we expect to observe economies of scale in test production . If test costs are reduced , screening becomes cost saving even in populations with rates of congenital infection below 0 . 0001 . Accordingly , as universal screening is enacted and test production expanded , economies of scale in test production may render screening a cost-saving strategy for all populations , even at extremely low rates of congenital infection . The capacity to test for several congenital conditions while drawing blood at one time opens the possibility of other cost savings ( economies of scope ) . Pooling the costs of testing for congenital cytomegalovirus and other conditions , for example , would reduce the threshold for cost savings for all conditions . The cost-minimization analysis described herein demonstrates that a careful and robust gestational screening program as carried out in France can be a cost-saving intervention in the United States . This paradigm can be readily applied to evaluating options for preventing toxoplasmosis in developing countries worldwide . In Brazil , for example , carefully performed and detailed regional programs are collecting data concerning gestational infection and congenital toxoplasmosis , which are amenable to analysis with the paradigm developed herein [27] . This paradigm is also readily applicable to analyses of other neglected tropical diseases . The recommendation of screening is complicated by the disparity between a best practice scenario , such as that analyzed in this study , and US health care reality . The above analysis implicitly assumes that all mothers receive care by the twelfth week of gestation for monthly checkups and adhere to the advice of their primary care providers in decisions regarding the management of pregnancy . In actuality , this scenario is unlikely . Lower-income mothers may lack the resources to travel to monthly checkups or may be discouraged from visits by a lack of health insurance or poor access to , or poor treatment in , public facilities . This study viewed all costs from a societal perspective and thus abstracted from the incidence of test and treatment costs . Even if the costs are covered by insurance , mothers without insurance will have a disincentive to report for pregnancy checkups . If this is the case , the benefits to be derived from screening for congenital toxoplasmosis will not be evenly distributed across income strata and demographics , and societal benefits are correspondingly reduced as well . This analysis assumes that initiating best practice is an essential step to promoting adherence and will contribute to the momentum for universal access to health care , in particular adequate prenatal care , which provides other benefits to society as well . Adherence can also be impaired due to maternal preference , regardless of income or accessibility . In France , in spite of compulsory universal screening , public medical care was associated with a late first test , fewer tests , and longer intervals between tests [95] . Public health coverage in the United States would need to address those shortcomings to achieve universal screening . Policy makers will also have to consider not only the extent to which screening may be cost saving , but also the important question of “who pays ? ” Taxpayers will likely bear the burden of test and treatment costs for low-income mothers . A further consideration is necessitated by the potentially low positive predictive value of maternal serum tests . If specificity ( identification of true negatives ) is less than 100% , the low prevalence of congenital infection dominates the calculation of positive predictive value , resulting in tests for which as few as 20% of positive test results correspond to actual infection . The present study is based on the assumption of 100% specificity after confirmatory test at a high quality reference lab . A study sponsored by the US Centers for Disease Control and Prevention ( CDC ) compared six test kits available for the detection of T . gondii antibodies in serum and found the sensitivity of the tests that might be used for screening ranged from 93 . 3% to 100% and the specificity ranged from 77 . 5% to 99 . 1% [96] . A more recent study compared the performance of four different Toxoplasma IgG and IgM assays . The Toxo assays considered were Vidia Toxo IgG and IgM ( bioMerieux , Marcy l'Etoile , France ) , Vidas Toxo IgG and IgM ( bioMerieux ) , AxSYM Toxo IgG and IgM ( Abbot Laboratories , Abbot Park , IL ) , and Liaison Toxo IgG and IgM ( Dia-Soring , Saluggia , Italy ) . For the Toxoplasma IgG assays , sensitivity was 100% and specificity between 98 . 49% and 100% . The Toxoplasma IgM assays performed with sensitivity between 82 . 35% and 100% and specificity between 99 . 73% and 100% [97] . For diseases with very low prevalence , even very high ( but less than 100% ) specificity translates into low positive predictive value ( PPV ) , which is the probability that disease is truly present given that the result of the screening test is positive . Written Pr ( D+|T+ ) , it is the posterior probability of a true-positive test result . Mittendorf and colleagues demonstrate clearly the effect of less than 100% specificity on PPV and argue that routine screening for toxoplasmosis in the United States is unwarranted because of the low incidence of congenital infection . Furthermore , due to the calculated low positive predictive value of serology tests for toxoplasmosis , they estimated that 12 . 1 fetuses without CT would be aborted for every fetus detected with congenital toxoplasmosis [98] . Given these calculations , they concluded that the adverse effects for healthy fetuses of universal screening outweigh the benefits derived from early detection and treatment of infected fetuses . The implications of the Mittendorf et al . analysis were considered very carefully . There are two reasons that their analysis does not apply . First , the protocol herein requires a confirmatory test at a reference lab , which at the present time has a specificity of 100%; second , our study calculates cost based on best practice . Mittendorf and colleagues and others using their analysis postulate elected abortions upon a positive confirmatory test [64] , [98] , [99] . CT is a treatable condition in almost all cases and thus , treatment , not abortion , is almost always considered best practice . Therefore , our model calculates the cost savings without assuming elected abortions . In recent years in France , there have been so few elected terminations ( three reported in 2008 ) [9] , [17] that including estimates would not alter our results . For infected mothers , the adverse consequences of universal screening can be reduced through the use of further confirmatory testing , such as amniocentesis with PCR . A recent study of the use of PCR of amniotic fluid in France reported a specificity of 100% , sensitivity of 92% , and positive predictive value of 100% [14] , [73] , meaning that a positive result definitively identifies infection of the fetus [73] . The use of amniocentesis to confirm fetal infection ( positive predictive value of 100% ) can reduce the risk of misinformed abortion , but this potentiality hinges on proper education of primary care physicians and mothers . The potential problems posed by positive predictive value are not devastating to the implementation of a screening program , although they do urge caution and diligence in the implementation of any such programs . While the use of PCR of amniotic fluid may prevent unnecessary elected abortions of healthy fetuses , sampling amniotic fluid is an invasive procedure and itself carries a risk of fetal loss . In the 1970s , the risk of miscarriage due to amniocentesis was estimated to be 0 . 50% ( 1 in 200 ) [91]; but in that era continuous ultrasound guidance for the procedure was not routine , and clarity and quality were far inferior to that of ultrasonography today . Amniocentesis is now considered routine , where medically indicated , and recent studies suggest a far lower rate of fetal loss due to amniocentesis; the Mayo Clinic reports loss rates of 1 in 300 ( 0 . 33% ) to 1 in 500 ( 0 . 20% ) , and a recent study suggests far lower loss rates of 1 in 1 , 600 ( 0 . 06% ) [90] , [92] . We use an average of the two Mayo Clinic estimates in the model ( 0 . 25% ) , which may greatly overstate risk . A concern with adding any testing to a prenatal protocol is the additional anxiety for mothers . Serology for T . gondii , however , can be carried out along with other routine tests and need not impose unusual stress . Moreover , mothers need not be informed of suspicious results until the sample has been confirmed with a second test and , if positive , sent for further testing to a reference lab . Thus only true positives would be informed of the need for medication and amniocentesis . Certainly , those both generate concern and risk . Except in extreme cases , however , mothers are not anxious about impossible outcomes , but about real outcomes , albeit having low probability in most cases . Awareness of personal agency is a powerful antidote to anxiety . Knowledge that they can help their unborn children with better information would be more likely to alleviate maternal anxiety than to make it less bearable . An additional limitation of the model is that only two possible strategies were analyzed: no screening and prenatal screening and treatment . Pre-pregnancy education was incorporated into the model via sensitivity analysis of reduction in seroprevalence and primary infection during pregnancy to assess the impact of the efficacy of education on the decision . Reducing the rate of maternal and congenital infection by as much as 60% ( the suggested effect of maternal education ) reduces the extent to which screening is cost saving , although , even with that effect , subsequent screening remained the optimal strategy . Recent analyses indicate that many times risk factors for T . gondii infection go unrecognized and thus could not be eliminated by education alone [29] , [59] , [100] . Additionally , universal neonatal screening was not considered in the model . Incorporation of this third strategy could render prenatal screening a sub-optimal strategy if cost is the only consideration , although screening would still be cost saving when compared to no systematic screening and no screening at all . Neonatal screening , however , misses the opportunity to treat prenatally and prevent profound injury with life-long consequences for the child , the family , and society . Finally , sensitivity analysis on the efficacy of treatment was not performed . Treatment efficacy estimates were generated based on published clinical results , and thus have not been subjected to sensitivity analysis , although variation of these estimates could have a potentially significant effect on the results generated by the model . More extensive screening and treatment in the United States would contribute to knowledge of efficacy in this population , with its possible mixture of European and Western Hemisphere strains of T . gondii , although preliminary results suggest that treatment is equally efficacious for different strains [94] . Moreover , if congenital toxoplasmosis becomes a more widely understood and reported disease in the United States , estimates of the rate of congenital infection will become more accurate and region-specific . A protocol of screening in suspected high-incidence populations would be another alternative . Universal screening according to the French protocol is cost saving for the US population within broad parameters for costs , seroprevalence , incidence of maternal and congenital toxoplasmosis , value of statistical life , and risk of fetal death from amniocentesis . It is also robust to changes in the discount rate within the normal range for health interventions . | We constructed a decision-analytic and cost-minimization model to compare monthly maternal serological screening for congenital toxoplasmosis , prenatal treatment , and post-natal follow-up and treatment according to the current French protocol , versus no systematic screening or perinatal treatment . Costs are based on published estimates of lifetime societal costs of developmental disabilities and current diagnostic and treatment costs . Probabilities are based on published results and clinical practice in the United States and France . We use sensitivity analysis to evaluate robustness of results . We find that universal monthly maternal screening for congenital toxoplasmosis with follow-up and treatment , following the French ( Paris ) protocol , leads to savings of $620 per child screened . Results are robust to changes in test costs , value of statistical life , seroprevalence in women of childbearing age , fetal loss due to amniocentesis , incidence of primary T . gondii infection during pregnancy , and to bivariate analysis of test costs and incidence of primary T . gondii infection . Given the parameters in this model and a maternal screening test cost of $12 , screening is cost-saving for rates of congenital infection above 1 per 10 , 000 live births . Universal screening according to the French protocol is cost saving for the US population within broad parameters for costs and probabilities . | [
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... | 2011 | Maternal Serologic Screening to Prevent Congenital Toxoplasmosis: A Decision-Analytic Economic Model |
Mitochondrial disorders have the highest incidence among congenital metabolic disorders characterized by biochemical respiratory chain complex deficiencies . It occurs at a rate of 1 in 5 , 000 births , and has phenotypic and genetic heterogeneity . Mutations in about 1 , 500 nuclear encoded mitochondrial proteins may cause mitochondrial dysfunction of energy production and mitochondrial disorders . More than 250 genes that cause mitochondrial disorders have been reported to date . However exact genetic diagnosis for patients still remained largely unknown . To reveal this heterogeneity , we performed comprehensive genomic analyses for 142 patients with childhood-onset mitochondrial respiratory chain complex deficiencies . The approach includes whole mtDNA and exome analyses using high-throughput sequencing , and chromosomal aberration analyses using high-density oligonucleotide arrays . We identified 37 novel mutations in known mitochondrial disease genes and 3 mitochondria-related genes ( MRPS23 , QRSL1 , and PNPLA4 ) as novel causative genes . We also identified 2 genes known to cause monogenic diseases ( MECP2 and TNNI3 ) and 3 chromosomal aberrations ( 6q24 . 3-q25 . 1 , 17p12 , and 22q11 . 21 ) as causes in this cohort . Our approaches enhance the ability to identify pathogenic gene mutations in patients with biochemically defined mitochondrial respiratory chain complex deficiencies in clinical settings . They also underscore clinical and genetic heterogeneity and will improve patient care of this complex disorder .
Human oxidative phosphorylation ( OXPHOS ) disease has the highest incidence among congenital metabolic disorders characterized by a biochemical respiratory chain complex deficiencies and is thought to occur at a rate of 1 in 5 , 000 births[1] . No more than 15–30% of pediatric diseases diagnosed as mitochondrial disorders show mitochondrial DNA ( mtDNA ) abnormalities[2 , 3]; the remaining cases occur because of defects in genes encoded in the nucleus . A certain amount of nuclear-encoded gene products are present in the mitochondria , and roughly 1 , 500 are thought to play important roles in mitochondrial function[4 , 5] . It is particularly difficult to diagnose patients with OXPHOS disease at the molecular level because of the massive numbers of potentially involved nuclear genes and genes not yet linked to human disease . Therefore , identification of the causative genes and an understanding of the pathogenic mechanisms of OXPHOS disease remain unsolved challenges . Recent studies[6 , 7] have shown that heterogeneous genetic backgrounds as well as genes previously not linked to mitochondrial functions or localization are associated with this disease . However , because of phenotypic and locus heterogeneity , only a fraction of patients has been identified to date . Limitations in target resequencing have motivated us to apply a comprehensive genomic analysis for more accurate molecular diagnosis and for the identification of novel causative genes . Here , we aimed to determine whether a comprehensive genomic analysis approach could be used to reveal the broad spectrum of genetic background of the disease[8] . One hundred and forty-two unrelated individuals with displayed childhood-onset mitochondrial respiratory chain complex deficiencies were selected . We applied long-range polymerase chain reaction ( PCR ) -based whole mtDNA sequencing , whole exome sequencing ( WES ) , and high-density oligonucleotide arrays to identify single-nucleotide variants ( SNVs ) , small insertions or deletions ( indels ) , and chromosomal aberrations for comprehensive genomic analyses .
In this study , 142 patients with childhood-onset mitochondrial respiratory chain complex deficiencies were enrolled and subjected to comprehensive genomic analyses ( detailed clinical characteristics are described in S1 Table ) . A schematic workflow of these analyses is shown in Fig 1 . Comprehensive genomic analyses included three approaches: ( i ) amplicon-based whole mtDNA sequencing for pathogenic mutations and large duplications/deletions , ( ii ) WES for pathogenic mutations in nuclear DNA , and ( iii ) high-density oligonucleotide arrays for chromosomal aberrations . The prioritized variants derived from each approach are described below . After comprehensive genomic analysis shown in Fig 1 , rare variants were filtered out and prioritized on the basis of the strategy described below . For mtDNA variants , we targeted variants confirmed and reported in MITOMAP[9] . Exome sequencing covered 89% ( ranged: from 70%–to 98% ) of the targeted bases , with more than 20-fold coverage . Detailed sequence statistics is shown in S2 Table . The precise strategy for WES variant prioritization is shown in S2 Fig . We evaluated our prioritization pipeline to validate whether it could feasibly enrich known OXPHOS disease-causing genes or mitochondria-related genes ( S3 Fig ) . Known OXPHOS disease-causing genes were clearly enriched in disease cases , whereas no prioritized genes were detected in healthy controls . Compared with healthy controls , mitochondria-related genes also exhibited a 1 . 64-fold enrichment . No enrichment was observed in randomly selected genes . These results suggest that mitochondria-related gene enrichment is caused by unidentified causative genes . To analyze chromosomal aberrations , we focused on rather large ( >100 Kb ) deletions or duplications . For prioritizing candidate aberrations , we filtered out deleted or duplicated regions found in the 524 in-house controls and manually curated the pathogenicity of the aberrations by referring to the OMIM , DGV , and DECIPHER databases . A breakdown of the 142 patients according to prioritized variants is shown in Fig 2 . Of the 142 patients with mitochondrial respiratory chain complex deficiencies , 102 ( 71 . 8% ) harbored at least 1 prioritized mtDNA mutation , nuclear gene mutation , or chromosomal abnormality . Ten ( 7 . 0% ) patients harbored mtDNA mutations , including one large deletion ( S4 Fig ) . In 29 patients ( 20 . 4% ) , firm molecular diagnoses were made in 20 genes previously linked to mitochondrial disorders . We newly confirmed 3 mitochondria-related genes ( MRPS23 , QRSL1 , and PNPLA4 ) as causative genes of mitochondrial respiratory chain complex deficiencies . Three patients ( 2 . 1% ) harbored mutations in genes known to cause monogenic diseases ( MECP2 and TNNI3 ) . Intriguingly , 4 patients ( 2 . 8% ) had pathogenic chromosomal deletions previously linked to other disorders ( 6q24 . 3-q25 . 1 , 22q11 . 21 , and 17p12 ) but not linked to mitochondrial respiratory chain complex deficiencies . In 53 ( 37 . 3% ) patients , we identified and designated candidate genes or loci as prioritized variants of unknown significance ( pVUS ) because these variants have possibilities to be pathogenic but have insufficient evidence to support a disease linage . The current lack of functional validation for linking these genes with mitochondrial disorders led us to classify these variants as inconclusive with respect to pathogenicity ( S3 , S4 and S5 Tables ) . The remaining 40 ( 28 . 2% ) patients lacked prioritized nuclear variants , mtDNA variants , and chromosomal abnormalities . Twenty-two genes were prioritized in 31 patients ( Table 1 ) . Of these , 29 patients harbored 41 disease-causing mutations in 20 genes known to cause OXPHOS disease: ACAD9 , BOLA3 , COQ4 , COX10 , EARS2 , ECHS1 , GFM1 , GTPBP3 , KARS , MPV17 , NDUFA10 , NDUFAF6 , NDUFB11 , NDUFS4 , RARS2 , RRM2B , SCO2 , SUCLA2 , TAZ , and TUFM . All such mutations were confirmed through Sanger sequencing and haplotype phasing . In particular , 8 patients had homozygous mutations , 19 had compound heterozygous mutations , and 2 had hemizygous mutations . Of the 41 mutations , 37 were novel and 4 were reported as pathogenic in the Human Gene Mutation Database[10] ( HGMD , professional version 2013 . 10 ) . BOLA3 , which plays an essential role in iron–sulfur cluster production , was mutated in 4 unrelated patients with severe lactic acidosis and combined respiratory chain complex deficiencies ( MIM 614299 ) . Three of these patients ( Pt045 , Pt268 , and Pt314 ) exhibited multiple organ failure; Pt268 and Pt314 had hypertrophic cardiomyopathy , and Pt045 developed seizures . All 4 patients exhibited decreased complex II activity and harbored the c . 287A>G ( p . H96R ) mutation . Pt314 and Pt286 patients showed clear long contiguous stretches of homozygosity ( LCSH ) ( 2 . 8 Mb , 3 . 2 Mb respectively ) around this p . H96R mutation . Pt268 also showed a short contiguous stretch of homozygosity ( 0 . 3 Mb ) . This homozygous region encompassing BOLA3 was shared between these unrelated individuals . Sanger sequencing identified the parents for these three patients as heterozygous carriers of this mutation . No p . H96R carriers were found in NHLBI GO Exome Sequencing Project ( ESP6500 ) , and 1 Japanese carrier in 1000 Genomes Project ( 1KG ) was found . We screened for mutations that violated the Hardy–Weinberg principle and only identified the p . H96R mutation . These results suggest that p . H96R is common in the Japanese population and has originated from a single founder ( S5 and S6 Figs ) . NDUFAF6 , which plays an important role in complex I assembly , was mutated in 4 unrelated patients: Pt101 , Pt512 , and Pt598 exhibited regression , whereas Pt330 exhibited muscle atrophy . All patients had complex I deficiency ( MIM 256000 ) . Pt101 shared 1 allele with Pt512 and another with Pt598 . Pt330 harbored homozygous mutation c . 820A>G ( p . R274G ) located in 1 . 3 Mb LCSH . Sanger sequencing identified the parents as heterozygous carriers of this mutation . Only 1 family was reported to harbor a mutation in this gene[18] ( S7 , S8 and S9 Figs ) . NDUFB11 , recently reported as causative gene for microphthalmia with linear skin defects syndrome ( MIM 300952 ) and encoding a complex I component , was mutated in Pt067 , a boy born to non-consanguineous parents under conditions of intrauterine growth restriction; this patient presented with heart failure , respiratory failure , complex I deficiency , and lethal infantile mitochondrial disorder ( LIMD ) . He harbored a hemizygous de novo mutation , c . 361G>A ( p . E121K ) , and there was no NDUFB11 protein expression in his fibroblasts ( S10 Fig ) . Because the p . E121 residue is highly conserved in this gene , we performed functional in vivo assays using a dndufb11-knockdown Drosophila model ( S11 Fig ) ; compared with controls , the mean lifespan was significantly reduced and the metabolic rate was lower in knockdown flies . Blue-native polyacrylamide gel electrophoresis ( BN-PAGE ) analysis showed a loss of complex I assembly , and lactate and pyruvate levels were increased in the knockdown flies . The in vivo dndufb11-knockdown Drosophila experiment further supported this conclusion . While preparing this manuscript , two girls harboring mutations in NDUFB11 with microphthalmia with linear skin defects were reported by van Rahden et al[19] . Our patient was a male and died 55 h after birth . He presented with redundant skin but had no linear skin defects . Pt459 , a boy with lactic acidosis , developmental delays , hypertrophic cardiomyopathy , seizure , and combined complex deficiencies ( I and IV ) , harbored the compound heterozygous mutations c . 1343T>A ( p . V448D ) and c . 953T>C ( p . I318T ) in KARS . KARS is a lysyl-transfer RNA synthetase that produces 2 proteins that localize to the cytosol and mitochondria . A cDNA complementation assay revealed that mitochondrial KARS successfully rescued the enzyme defect , but not cytosolic form ( S12 Fig ) . Detailed information and evidential support for other known genes are described in S1 Text . Five ( MRPS23 , C1QBP1 , ALAS2 , SLC25A26 , QRSL1 ) genes were identified as novel candidate genes ( Tables 2 and S3 ) . These genes were previously reported links to mitochondrial function but not mitochondrial respiratory chain complex deficiencies . Of these , we obtained pathogenic support for mutations in MRPS23 and QRSL1 . In addition , candidate genes that have no evidence of functional involvement in current mitochondrial biology are good targets for underlying novel mitochondrial biological functions . In one such case , we identified PNPLA4 as a novel causative gene for mitochondrial respiratory chain complex deficiencies and proved its mitochondrial localization for the direct evidence of mitochondrial functions . The supportive evidence included ( i ) the identification of independent mutations in candidate genes in unrelated individuals with exquisitely similar phenotypes , ( ii ) rescue of patients’ cellular phenotypes in a cDNA complementation assay , and ( iii ) identification of a de novo mutation in the candidate gene . Other pVUS for candidate genes are shown in S3 Table . A component of the highly conserved mitochondrial ribosome small subunit MRPS23[22] was mutated in Pt276 , a boy with hepatic disease and combined respiratory chain complex deficiencies . In this patient , enzyme activities in complexes I and IV were decreased by 28% and 14% of the normal fibroblastic values , respectively . The patient was born to a non-consanguineous family . However , high-density oligonucleotide array analysis identified an approximately 500 kb contiguous stretch of homozygosity encompassing MRPS23 . No other candidate gene was prioritized in our comprehensive genomic analysis . Pt276 harbored a homozygous c . 119C>G ( p . P40R ) mutation in MRPS23 ( NM_016070 ) ( Figs 3A and S13 ) . Sanger sequencing identified the parents as heterozygous carriers of this mutation . A complementation assay rescued the defect in complexes I and IV ( Figs 3B and S13 ) and restored mitochondrial 12S rRNA/16S rRNA expression ( Fig 3C ) . Pt250 , a girl with tachypnea , hypertrophic cardiomyopathy , adrenal insufficiency , hearing loss , and combined respiratory chain complex deficiencies ( I , II , III , and IV ) , harbored a homozygous mutation c . 398G>T ( p . G133V ) in QRSL1 ( NM_018292 ) ( Figs 3D and S14 ) . Her older brother , also ill , harbored the same homozygous mutation . Sanger sequencing identified the parents as heterozygous carriers of this mutation . The high-density oligonucleotide array analysis identified a shorter 100 kb contiguous stretch of homozygosity encompassing QRSL1 . QRSL1 ( hGatA ) is a glutaminase that produces ammonia , which is then transferred to misacylated Glu-charged tRNAGln to synthesize Gln-tRNAGln , which interacts with PET112L ( hGatB ) and GATC ( hGatC ) to form a trimeric enzyme hGatCAB[23] . Additional screening also identified an independent patient ( Pt860 ) harboring the compound heterozygous mutations c . 350G>A ( p . G117E ) and c . 398G>T ( p . G133V ) ( Fig 3E ) . In vitro reconstitution of Gln-tRNAGln formation using recombinant hGatCAB revealed strongly decreased transamidation activity in both mutant ( G117E or G133V ) hGatA ( Fig 3F ) . PNPLA4 has both triacylglycerol lipase and transacylase activities . Pt712 is a boy who inherited a hemizygous nonsense variant c . 559C>T ( p . R187X ) in PNPLA4 ( NM_001142389 ) from his mother ( Fig 4A and 4B ) . The colocalization of PNPLA4 and mitochondrial markers was identified by immunofluorescence microscopic observation ( Fig 4C ) . We confirmed PNPLA4 protein loss in the fibroblasts of this patient by qRT-PCR ( Fig 4D ) , sodium dodecyl sulfate ( SDS ) -PAGE/Western blotting ( Fig 4E ) , and immunohistochemistry ( Fig 4C ) . We found reduced complex I , III and IV assemblies of Pt712 fibroblasts under low glucose medium conditions ( Fig 4G ) . The expression of PNPLA4-V5 cDNA in the fibroblasts of Pt712 recovered an amount of complex III and IV assemblies under low glucose medium conditions ( Fig 4F and 4G ) . In our cohort , all patients showed mitochondrial respiratory chain complex deficiencies . Intriguingly , we identified 3 cases having mutations in two genes that were previously reported to cause other monogenic diseases but not linked to canonical mitochondrial disease . These are MECP2 and TNNI3 ( Table 2 ) . Pt053 , a boy with complex I deficiency and seizures , diarrhea , arrhythmia , regression , respiratory failure , liver dysfunction , and hearing loss , harbored the hemizygous de novo mutation c . 806delG ( p . G269fs , rs61750241 ) in MECP2 ( NM_004992 ) ( S15 Fig ) , a gene reported to cause Rett syndrome ( MIM 312750 ) . We also identified another boy , Pt369 , who harbored the hemizygous de novo mutation c . 17_18insG ( p . A6fs ) in MECP2 ( NM_001110792 ) ( S15 Fig ) . Pt827 was diagnosed with restrictive cardiomyopathy and complex I deficiency , and harbored the heterozygous de novo mutation c . 575G>A ( p . R192H , rs104894729 ) ( S16 Fig ) in TNNI3 ( NM_000363 ) ; this exact mutation was reported to cause autosomal dominant familial restrictive cardiomyopathy ( MIM 115210 ) . Electron microscopic examination also revealed abnormally shaped mitochondria with concentric cristae ( S16 Fig ) . It has long been thought that patients with mitochondrial respiratory chain complex deficiencies rarely suffer chromosomal rearrangements but instead harbor mtDNA mutation , deletion , and depletion or nuclear DNA mutation . We subjected our entire cohort to a high-density oligonucleotide array to precisely evaluate the presence of any copy number variations ( CNVs ) of >100 kb . Intriguingly , we identified 13 patients ( 9 . 2% ) harboring rare CNVs ( Tables 3 and S5 ) . Pt369 and Pt657 , 2 boys with complex IV deficiency from independent families , harbored similar deletions ( 1 , 429 and 1 , 387 kb ) in chromosome 17p12 . These 17p12 deletion disrupted the last 2 exons of COX10 in both patients ( Fig 5A ) . This region causes hereditary neuropathy with liability to pressure palsies ( HNPP ) ( MIM 162500 ) . Whole exome analysis of Pt657 revealed an additional mutation c . 683G>A ( p . R228H ) on the remaining allele of COX10 ( Fig 5B and 5C ) . Notably , p . R228 is highly conserved among species . The PolyPhen2 and SIFT algorithms predicted this mutation as “probably damaging . In both patients , fibroblastic COX10 mRNA expression was reduced ( Fig 5D ) . The complementation study using wild-type COX10 confirmed recovery of the complex IV deficiency in Pt657 ( Fig 5E , 5F and 5G ) . Taken together , we concluded that Pt657 is a primary mitochondrial disorders . In Pt369 , we concluded that de novo frameshift insertion mutation in MECP2 as a primary causative based on phenotype information , and classified 17p12 as pVUS . We identified de novo 6q24 . 3-q25 . 1 deletions ( S17 Fig ) in Pt452 and Pt695 , unrelated patients who harbored congenital heart defects . This region has been associated with the chromosome 6q24-q25 deletion syndrome ( MIM 612863 ) and congenital heart defects[24] . Pt587 , a boy diagnosed with LIMD and complex IV deficiency , harbored a deletion in 22q11 . 21 . This deletion , which has been linked to DiGeorge syndrome ( DGS , MIM 188400 ) and velo-cardio-facial syndrome ( VCFS , MIM 192430 ) , was confirmed as a de novo mutation in this patient ( S17 Fig ) .
We performed comprehensive genomic analyses , including whole mtDNA and exome sequence analyses using high-throughput sequencing and CNV screening using high-density oligonucleotide arrays , for 142 patients with childhood-onset mitochondrial respiratory chain complex deficiencies . We ultimately identified 41 mutations , of which 37 were novel , in 20 genes that were previously reported to cause OXPHOS disease and 3 novel mitochondria-related genes ( MRPS23 , QRSL1 , and PNPLA4 ) as causative genes of mitochondrial respiratory chain complex deficiencies . We also found 9 previously confirmed mtDNA mutations and 1 large mtDNA deletion . We further identified 2 genes known to cause monogenic diseases ( MECP2 , and TNNI3 ) and 3 chromosomal aberration regions ( 17p12 , 6q24 . 3-q25 . 1 , and 22q11 . 21 ) in our cohort . Collectively , this study defined firm genetic diagnoses in 49 of the 142 patients ( 34 . 5% ) . While the overall diagnostic rates for major and minor subgroups were similar ( 33 . 9% in the major subgroup and 36 . 4% in the minor subgroup ) , 35 out of 49 genetically diagnosed patients showed biochemical defects in their fibroblasts ( 71 . 4% ) , indicating a much higher genetic diagnostic yield in patients with such cellular defects . This is the first report to comprehensively assess patients diagnosed clinically and biochemically . MRPS23 is a component of the small mitochondrial ribosome subunit ( 28S ribosome ) . Mutations in MRPS16[25] and MRPS22[26] cause mitochondrial respiratory chain complex deficiencies because of reductions of 12S rRNA , a 28S ribosome component . One patient exhibited a reduced 12S rRNA/16S rRNA ratio that was restored in a complementation study . This was the first case of MRPS23-induced mitochondrial respiratory chain complex deficiencies . QRSL1 ( GatA ) is involved in Gln-tRNAGln formation . No mitochondrial glutaminyl-tRNA synthetase ( GlnRS ) has been identified in mammals; therefore , Gln-tRNAGln synthesis was proven to occur via an indirect pathway[23] . In particular , mt tRNAGln is first misaminoacylated by mt glutamyl-tRNA synthetase ( GluRS ) to form Glu-tRNAGln , followed by transamidation to form Gln-tRNAGln . This transamidation is processed by a human homolog of the Glu-tRNAGln amidotransferase hGatCAB heterotrimer . We clearly showed that mutations in QRSL1 ( GatA ) , a component of hGatCAB , observed in our patients were associated with severe transamidation activity defects . PNPLA4 encodes a calcium-independent phospholipase A2η ( iPLA2η ) that acts as an acylglycerol and retinol transacylase , triglyceride hydrolase . PNPLA4 has never been reported to associate with the mitochondria . Nine patatin-like phospholipase domain-containing proteins ( PNPLA1–9 ) are encoded in the human genome . iPLA2γ ( PNPLA8 ) is known to be involved in cardiolipin biosynthesis and mitochondrial respiration[27 , 28] . Recently , mutations in human PNPLA8 identified in a young girl with a suspected mitochondrial myopathy[29] . She presented with progressive muscle weakness , hypotonia , seizures , poor weight gain , and lactic acidosis . A deficiency in iPLA2β ( PNPLA9 ) was previously shown to cause abnormal phospholipid metabolism and mitochondrial defects in mice[30] . Here we demonstrated the mitochondrial localization of iPLA2η using immunohistochemistry and restored of the amount of complex IV in Pt712 fibroblast cells via the exogenous expression of wild-type PNPLA4 . We assume that PNPLA4 is also required for mitochondrial phospholipid metabolism and respiratory chain function . Although all patients were diagnosed with mitochondrial respiratory chain complex deficiencies , we identified 2 disease-causing genes and 2 pathogenic CNVs known to cause other genetic disorders in our cohort . These included MECP2 , TNNI3 , 6q24 . 3-q25 . 1 deletion , and 22q11 . 21 deletion . Because all of these patients had complex II activities within the normal range ( percentage of protein and citrate synthase ratio ) , we concluded that their defects were not artefactual[31 , 32] . Because these genes and loci are not directly linked to the respiratory chain complex , we consider the mitochondrial respiratory chain complex deficiencies are caused by secondary . Pt053 , Pt369 , and Pt827 were classified as having major ETC reductions in affected tissues , whereas Pt452 , Pt695 , and Pt587 , harbored deletions are all classified as minor . The fact these heterozygous deletions are all classified as minor suggests that the mitochondrial defects in these patients might be caused indirectly through haploinsufficiency . Because Pt053 and Pt369 harbored MECP2 mutations known to cause Rett syndrome , we re-evaluated the phenotypes of both patients and found phenotypes that overlapped with Rett syndrome characteristics ( seizures , microcephaly , cerebral atrophy , and hearing loss ) . Previous studies also reported mitochondrial dysfunction in Rett syndrome[33 , 34] . Although Pt827 was enrolled with a diagnosis of mitochondrial disease , after comprehensive genomic analyses , the clinical diagnosis was changed to cardiomyopathy , familial restrictive ( OMIM: 115210 ) caused by a mutation in TNNI3 . Jia et al reported a link between Tnni3 and mitochondrial dysfunction using knockout mice [35] . Two independent patients from our cohort showed 6q24 . 3-q25 . 1 deletions . Pt452 exhibited a phenotype similar to that of cases reported cases in OMIM ( MIM 612863 ) . Pt695 presented with respiratory distress and a congenital heart defect . We classified these patients as having chromosome 6q24-q25 deletion syndrome . The enrichment of this deletion supports the suggested link with mitochondrial dysfunction . Pt587 was difficult to diagnose based on clinical information , because he did not have the facial anomalies and cleft palate characteristic of DGS/VCFS . The 22q11 . 21 deletion includes some mitochondria-related genes ( PRODH , SLC25A1 , MRPL40 , TXNRD2 , COMT , TANGO2 , ZDHHC8 , and AIFM3 ) , suggesting a link between this deletion and mitochondrial dysfunction . The inclusion of a patient with features of DGS/VCFS and complex I deficiency in a study by Calvo et al[36] also indicates a link with mitochondrial dysfunction . With these in mind , we should be mindful that some patients with mitochondrial respiratory chain complex defects will have mutations in genes apparently unrelated to mitochondrial functions . Previous reports of mitochondrial disorders can be classified as either target resequence studies[37 , 38 , 7] or whole exome approaches[39 , 40 , 41] . When comparing target resequencing groups , our approaches are advantageous for the identification of mutations in other disease-causing genes , and the detection of chromosomal aberrations . WES groups[40 , 41] and our group detected pathogenic mutations in genes not linked to mitochondrial disorders . When comparing WES groups , our approaches are advantageous in terms of mtDNA sequencing and chromosomal aberration analysis . Our analysis could detect mtDNA heteroplasmy using long-range PCR-based sequencing and also revealed established pathogenic chromosomal deletions . Accordingly , we identified a composite combination of COX10 SNV and 17p12 deletion ( Pt657 ) . Previous WES and target exome reports achieved molecular diagnoses in 20%–60% of their cohorts . A precise comparison of overall diagnostic rates with previous studies is difficult , given the existence of several biases that affect the diagnostic rate , including prior mtDNA/nDNA genetic screening , population characteristics , phenotyping accuracy , and study design . In particular , the reports by Taylor et al[40] described a high rate of diagnosis ( approximately 60% ) in their cohort , although their patient group appeared to be enriched by consanguineous families ( 12 of 28 diagnosed cases ) . The report by Wortmann et al[41] described a rate of diagnosis ( 38% ) similar to ours . In our study , we emphasized functional analyses to conclude disease causality against pVUS and attempted to present molecular evidence of pathogenicity;in contrast , some previous studies lacked sufficient molecular evidence of pathogenicity . We designated the variants without any molecular evidence of pathogenicity as pVUS , even when the gene had been reported as a causal gene for mitochondrial disorders . We consider molecular evidence to be indispensable for a conclusive firm genetic diagnosis . We found that approximately 28 . 2% of patients lacked any prioritized variants . We likely missed pathogenic mutations in these unresolved cases for the following reasons , as discussed in a report by Calvo et al[6]: first , we may have missed pathogenic mutations because of a lack of sensitivity from low sequence coverage . Second , pathogenic mutations may be located in uncovered genomic regions ( e . g . , uncovered exons , introns , or regulatory regions not targeted by whole exome platforms ) . Third , our filtering strategy may have filtered true pathogenic mutations , although some were recovered by manual curation . Fourth , the hereditary assumption may be wrong . More dominant-acting cases may exist . Digenic/polygenic inheritance may also exist beyond our expectation . In conclusion , for suspected mitochondrial disorders , comprehensive analyses such as those in this study are worthwhile . We expanded the clinical disease spectrum and revealed the genetic landscape of this disorder .
In total , 142 patients with childhood-onset and enzymatically diagnosed mitochondrial respiratory chain complex deficiencies were enrolled in this study . Informed consent was obtained from the patients and their families before participation in the study . Patients with suspected mitochondrial respiratory chain complex deficiency were referred to the Saitama Medical University Hospital and Chiba Children’s Hospital in Japan from 2007 to 2013 . The inclusion criterion was a biochemical diagnosis of mitochondrial respiratory chain complex activity in a clinically affected tissue ( skeletal muscle , liver , or heart ) or fibroblasts in patients younger than at the age of 15 years . Patients with known nuclear or mtDNA mutations at the time of recruitment were excluded . The 142 included patients had not received a prior molecular diagnosis , despite varying degrees of exposure to genetic testing . This cohort included 3 non-Japanese cases: Pt346 ( father , American; mother , Japanese ) , Pt298 ( Brazilian ) , and Pt223 ( Vietnamese ) . Enzyme activity[42] was measured on the basis of spectrophotometric enzyme assays using fibroblasts from patient’s skin or biopsy specimens from diseased organs of patients with clinically suspected mitochondrial respiratory chain disorders[43] . All enrolled patients in this study had biochemical mitochondrial respiratory chain complex deficiencies; the enzymatic diagnoses are shown in S1A Fig . In brief , complex I deficiency was most common ( 61 patients , 43 . 0% ) , followed by ( in decreasing order of prevalence ) combined respiratory chain complex deficiencies ( 46 patients , 32 . 4% ) , complex IV deficiency ( 27 patients , 19 . 0% ) , MTDPS ( 5 patients , 3 . 5% ) , and complex III deficiency ( 3 patients , 2 . 1% ) ; no patients exhibited complex II deficiency . Diagnoses of mitochondrial respiratory chain complex deficiencies were assessed as “major” or “minor” on the basis of biochemical complex activity . Based on the Bernier criteria , severity was defined as major ( <20% in a tissue , <30% in a fibroblast cell line , or <30% in ≥2 tissues ) or minor ( <30% in a tissue , <40% in a fibroblast cell line , or <40% in ≥2 tissues ) in accordance with the residual mean citrate synthase or complex II activities relative to those of normal controls ( S1B Fig ) . The distribution of age of onset of these patients was as follows: 45 . 7% ( 65 patients ) before 1 month , 19 . 7% ( 28 patients ) within 1–6 months , 19 . 7% ( 28 patients ) within 6–24 months , 12 , 7% ( 18 patients ) within 2–10 years , and 2 . 1% ( 3 patients ) within 10–15 years ( S1C Fig ) . The clinical diagnoses of 142 patients are also shown in S1D Fig . The most common diagnosis was mitochondrial cytopathy ( 27 patients , 19 . 0% ) , followed by Leigh’s disease ( 25 patients , 17 . 6% ) , LIMD ( 23 patients , 16 . 2% ) , sudden unexpected death ( 17 patients , 12 . 0% ) , non-lethal infantile mitochondrial disorder ( NLIMD ) ( 16 patients , 11 . 3% ) , cardiomyopathy ( 11 patients , 7 . 7% ) , hepatic disease ( 11 patients , 7 . 7% ) , enteropathy ( 6 patients , 4 . 2% ) , neurodegenerative disorder ( 4 patients , 2 . 8% ) , and short stature ( 2 patients , 1 . 4% ) . The male:female ratio was 76:66 . There were no consanguineous relationships among our cohort . Detailed clinical characteristics are described in S1 Table . DNA was isolated from cultured fibroblast cells using the QIAamp DNA Blood mini Kit ( QIAGEN ) . Blood genomic DNA was isolated by phenol–chloroform extraction according to the standard protocol . Total RNAs were purified from HEK293FT cells , fibroblast cells using the SV Total RNA Isolation System ( Promega ) . cDNAs were synthesized from total RNAs using ReverTra Ace ( Toyobo ) . Total RNA was extracted from flies using TRIzol reagent ( Invitrogen ) , and RNA was reverse transcribed by SuperScript VILO transcriptase ( Invitrogen ) . To avoid the contamination of mitochondrial-origin nuclear genome sequences [44] ( NUMTs ) , a long-range mtDNA polymerase chain reaction ( PCR ) method was used in this study . DNA were extracted from patients skin fibroblast cells . These DNAs were checked for large-scale mtDNA rearrangements and subjected to large mtDNA deletion mapping using long-range PCR with amplicon 1 ( rCRS 619–8988 ) and amplicon 2 ( rCRS 8749–895 ) primers; 5′-GACGGGCTCACATCACCCCATAA-3′ and 5′-GCGTACGGCCAGGGCTATTGGT-3′ for amplicon 1 , and 5′-GCCACAACTAACCTCCTCGGGCTCCT-3′ and 5′-GGTGGCTGGCACGAAATTGACC-3′ for amplicon 2 . Indexed PCR fragment libraries were prepared from patient mtDNA using the Nextera XT DNA Sample Prep Kit ( Illumina ) according to the manufacturer’s protocol . Sequencing library concentrations were estimated using a library quantification kit ( Kapa Biosystems ) . Sequencing was performed with 150-bp paired-end reads on MiSeq ( Illumina ) . Read alignments to the 1000 Genomes Project phase II reference genome ( hs37d5 . fa ) , which contains rCRS sequences , were performed with the Burrows–Wheeler Aligner[45] ( BWA , version 0 . 7 . 0 ) . PCR duplicate reads were removed using Picard ( version 1 . 89 ) ; non-mappable reads were removed using SAMtools[46] ( version 0 . 1 . 19 ) . After filtering out those reads , we applied the Genome Analysis Toolkit[47] ( GATK version 2 . 4-9-nightly-2013-04-12-g3fc5478 ) base quality score recalibration and performed SNP and INDEL discovery ( UnifiedGenotyper ) . Confirmed pathogenic mutations and reported variants in MITOMAP and mtDNA deletions detected through reference-based alignment with BWA mapping were prioritized ( S4 Table ) . De novo mtDNA sequence assembly was performed using SPAdes ( version 3 . 0 . 0 ) [48] with iterations over values of 3 kmer sizes ( k = 75 , 95 , and 115 ) . Each assembly was aligned to the mitochondrial genome sequence of hs37d5 . fa using BLASTN ( version 2 . 2 . 29+ ) with default settings and was manually inspected to identify aberrations ( deletions , duplications , and rearrangements ) . A large mtDNA deletion in Pt334 was validated using long-range PCR with primers 5′-GCCACAACTAACCTCCTCGGGCTCCT-3′ and 5′-GGTGGCTGGCACGAAATTGACC-3′ . The mtDNA was also sequenced ( using primers 5′-ACTACCACTGACATGACTTTCCAA-3′ and 5′-TGTTGTTTGGATATATGGAGGATG-3′ for amplification and 5′-CTTATCCAGTGAACCACTATCACG-3′ for sequencing ) closer to the breakpoint as described above . Quantitative PCR[49] was used to determine whether mtDNA depletion was present in patients with decreased activity levels for multiple respiratory chain enzymes ( mtDNA gene MT-ND1 was compared against a nuclear gene [CFTR exon 24] ) . A diagnosis of MTDPS was made when the relative copy number ratio of mtDNA to nuclear DNA was less than 35% of that in healthy control tissues in 4 independent experiments . Quantitative reverse transcription PCR ( qRT-PCR ) was performed for the analysis of mRNA ( NDUFB11 , TTC37 , and PNPLA4 ) and mitochondrial rRNA expression[50] . Primers were designed with the Primer3 software[51] . Primer sequences used in the qRT-PCR analysis are listed in S6 Table . qRT-PCR of cDNA extracted from human cells was performed using SYBR Premix Ex Taq ( Takara ) , Power SYBR Green PCR Master Mix ( Life technologies ) , and Mx3000P ( Agilent Technologies ) . The relative mRNA concentration was normalized to the average of two housekeeping genes ( β-actin and GAPDH ) . qRT-PCR of cDNA extracted from flies was performed using SYBR Premix Ex Taq II ( Takara ) and Chromo 4 Four-Color Real-Time System ( Bio-Rad ) . Results were normalized to the rp49 mRNA level . Indexed genomic DNA ( gDNA ) libraries were prepared from patient gDNA , and exomes were captured using TruSeq ( Illumina ) , SeqCap EZ ( Roche AG , Basel , Switzerland ) , and SureSelect ( Agilent Technologies ) exome enrichment kits according to the manufacturers’ protocols . Sequencing library concentrations were estimated using a library quantification kit ( Kapa Biosystems ) . Sequencing was performed using 100-bp paired-end reads on a HiSeq2000 or GAIIx ( Illumina ) . The precise exome platforms used in this study are listed in S2 Table . The raw sequence read data passed the quality checks in FASTQC ( see URLs ) . Read trimming via base quality was performed using Trimmomatic[52] . Read alignment was performed with BWA , the hs37d5 reference genome , Picard , and SAMtools as described above . GATK was also used for insertion and deletion realignment , quality recalibration , and variant calling . Detected variants were annotated using both ANNOVAR ( version 2013Feb21 ) [53] and custom ruby scripts . Prediction scores were obtained from dbNSFP[54] . Variants that passed quality control were prioritized according to the following strategies ( S2 Fig ) . We only retained variants predicted to modify protein function; these included nonsense , splice site , coding indel , or missense variants . We removed variants with minor allele frequencies ( MAFs ) of >1 . 0% for dbSNP 137 without known medical impact ( allele frequencies were extracted from common_no_known_medical_impact_20130808 . vcf . gz ) , >0 . 1% for ESP6500 ( provided by ANNOVAR program ) database , >1 . 0% for 1KG ( these data are based on a phase 1 release v3 called from the 20101123 alignment and provided by ANNOVAR ) , >0 . 1% for the Exome Aggregation Consortium ( ExAC , accessed on December 2014 ) , and >0 . 4% in HGVD ( contains genetic variations determined by exome sequencing of 1 , 208 individuals in Japan; see URLs ) . Variants that were too common among cases ( ≥10 alleles ) were also excluded . Careful inspection of the reads using the Integrative Genomics Viewer[55 , 56] and NextCODE clinical sequence analyzer ( see URLs ) excluded doubtful genes from prioritized candidate genes when 2 sequence variants were present in the same read ( or read-pair ) . Variants that appeared to be mapping artifacts ( called by suspicious reads or end positions of NGS reads ) were also excluded through a manual inspection of NGS reads . Variants located within segmental duplication regions were excluded . In addition to these filters , Sorting Intolerant From Tolerant ( SIFT ) scores > 0 . 15 and Genomic Evolutionary Rate Profiling ( GERP ) scores < 2 . 5 were used for further prioritization . We also excluded variants inconsistent with a recessive mode of inheritance . Two ( or more ) variants on a single haplotype as identified by Sanger sequencing were also excluded . Finally , we filtered remaining genes based on MAF and genotype information in the 1 , 070 whole-genome reference panel database ( 1KJPN ) constructed in the Tohoku Medical Megabank Project in Japan ( http://ijgvd . megabank . tohoku . ac . jp/ ) . The details of the project and analysis are described in the 1KJPN literature[57] . To recover true mutations that were filtered out using current pipeline applying stringent conditions , we also applied this pipeline without a segmental duplication filter , SIFT filter , or GERP filter , followed by focusing on mitochondria-related genes . Enrichment analysis was conducted to evaluate our exome pipeline and included 128 cases and 175 ethnically matched healthy controls whose sequence reads exceeded 50 million; these were adjusted to 50 million reads per individual . We used a simplified exome analysis pipeline that did not include a manual inspection step , Sanger sequencing validation step , and 1KJPN filtering step . We also omitted the HGVD filtering step because these control data were included in the HGVD samples . The other steps were the same as those described above for the exome analysis pipeline . After processing the controls and cases , we calculated the percentage of individuals harboring prioritized genes . Comparisons of the percentages of controls and cases on the basis of known disease genes and mitochondria-related genes are shown in S3A Fig . To consider the background rate of this simplified pipeline , we also evaluated enrichment using randomly selected 908 genes with no strong mitochondrial relationships in their annotations . The gene set was generated 1000 times via random selection from all genes after excluding those known to cause OXPHOS disease and those listed in MitoCarta[18] . The results plus standard deviations are shown in S3B Fig . Prioritized variants were independently validated by Sanger sequencing . PCR products were either directly sequenced using GENEWIZ , ABI 3130XL , and BigDye v3 . 1 Terminators ( Applied Biosystems ) per the manufacturer’s protocols or sequenced after gel purification using the MinElute Gel Extraction Kit ( QIAGEN ) . Sequencing primers are listed in S7 Table . All compound heterozygous variants described in the main text were confirmed on different alleles ( phased ) using sequenced , cloned gDNA or cDNA derived from the patients’ fibroblasts . Patients’ familial DNA was also sequenced for haplotype phasing when available . All information about the experimentally confirmed localization of compound variants within a separate allele is presented in S3 Table . Amino acid sequences of orthologous genes were downloaded from the HomoloGene database ( see URLs ) . Amino acid sequence alignments were constructed with the ClustalW2 program[58] . Cells were cultured at 37°C and 5% CO2 in Dulbecco's modified Eagle’s medium ( DMEM 4 . 5 g/l glucose or 1 . 0 g/l glucose; Nacalai tasque ) supplemented with 10%–20% fetal bovine serum . Normal neonatal human dermal fibroblasts ( NHDFs; Takara ) and normal fetal human dermal fibroblasts ( fHDFs; Toyobo ) were used as control fibroblast cells . Open reading frames ( ORFs ) of candidate genes ( ACAD9 , BOLA3 , COX10 , KARS , MRPS23 , NDUFA10 , NDUFAF6 , PNPLA4 , and TUFM ) were PCR amplified from cDNA . Primer sequences used for cDNA cloning are listed in S8 Table . ORFs and pTurboRFP-mito ( TurboRFP fused to a mitochondrial targeting sequence derived from the subunit VIII of human cytochrome C oxidase; Evrogen ) were cloned into the CS-CA-MCS lentiviral vector with a C-terminal V5 tag , CAG promoter for mammalian cell expression , and blasticidin resistance using the In-Fusion HD Cloning Kit ( Clontech Laboratories , Inc . ) . Following this , 2 × 106 HEK293FT cells were seeded in 6-cm plates and co-transfected with ViraPower Packaging vectors ( pLP1 , pLP2 , pLP/VSVG; Invitrogen ) and a pCA-CS-ORF ( candidate gene ) -blast vector . Transfection was performed using Lipofectamine 2000 ( Invitrogen ) . Transfection medium was replaced with fresh medium 24 h after transfection . Supernatant containing the viral particles was collected 48 h after transfection and filtered through a 0 . 45 μm filter . Patients’ skin fibroblasts were infected with the viral supernatant and 5 μg/ml polybrene ( Sigma ) for 24–48 h . After 5–7 days , selection was initiated with 1–2 μg/ml blasticidin . After 1–3 months of selection , mitochondria were harvested from the cells for enzyme assays or BN-PAGE . To prepare enriched mitochondria , cell pellets were resuspended in ice-cold MegaFb Buffer ( 250 mM sucrose , 2 mM HEPES , 0 . 1 mM EGTA , pH 7 . 4 ) and homogenized with 20 strokes . The homogenates were centrifuged for 10 min at 600 g . Supernatants were centrifuged for an additional 10 min at 14 , 400 g . Pellets were resuspended in 400 μl MegaFb buffer , and 200 μl aliquots were frozen and thawed 3 times for complex II + III and complex III assays and protein estimation . The remaining samples were resuspended in hypotonic buffer ( 25 mM potassium phosphate , pH 7 . 2 , 5 mM MgCl2 ) for complex I , II , and IV , citrate synthase , and protein concentration assays and centrifuged for 10 min at 14 , 400 g . Pellets were resuspended in Hypotonic Buffer and subjected to 3 freeze–thaw cycles . These samples were stored at −80°C prior to enzyme assays . Respiratory chain enzyme activities were measured using cary300 ( Agilent Technologies ) as described previously[42] . Complex I , II , II + III , III , and IV activities were expressed as percentages of citrate synthase activity . To isolate mitochondria , cell pellets were suspended in mitochondria isolation buffer A ( 220 mM mannitol , 20 mM HEPES , 70 mM sucrose , 1 mM EDTA , pH 7 . 4 , 2 mg/ml bovine serum albumin , 1× protease inhibitor cocktail ) and homogenized with 20 strokes on ice . Homogenates were separated into cytosolic and nuclear fractions after centrifugation at 700 g for 5 min at 4°C . The supernatants were centrifuged at 10 , 000 g for 10 min at 4°C . Mitochondrial pellets were rinsed twice with mitochondria isolation buffer B ( 220 mM mannitol , 20 mM HEPES , 70 mM sucrose , 1 mM EDTA , pH 7 . 4 , 1× protease inhibitor cocktail ) . Mitochondria were isolated from adult flies as described previously[59] . Fifty flies were homogenized in 1 ml of chilled mitochondrial isolation medium ( MIM; 250 mM sucrose , 10 mM Tris pH 7 . 4 , 0 . 15 mM MgCl2 ) . The samples were centrifuged twice for 5 min at 1 , 000 g at 4°C to remove debris . The supernatant was centrifuged again for 5 min at 13 , 000 g at 4°C . Mitochondrial protein levels were determined using a bicinchoninic acid ( BCA ) assay . For SDS-PAGE analyses , enriched mitochondria and cell pellets were solubilized in M-PER Mammalian Protein Extraction Reagent ( Thermo Fisher Scientific ) and denatured for 30 min at 37°C . Prepared samples were separated by electrophoresis on 8% , 10% , and 15% SDS-PAGE gels , depending on the size of the detected protein . For BN-PAGE analyses , The NativePAGE Novex Bis-Tris Gel System ( Life Technologies ) was used according to the manufacturer’s protocol . Mitochondrial fractions were solubilized in NativePAGE sample buffer containing 0 . 5% Triton-X100 and separated on 4%–16% NativePAGE gels . The BN-PAGE analyses of Drosophila were performed as previously described[60] . Immunoblot analysis was performed as described previously[61] . Anti-NDUFA9 ( Complex I ) , anti-70 kDa Fp Subunit ( Complex II ) , anti-core 1 ( Complex III ) , anti-subunit 1 ( Complex IV ) , and anti-V5 antibodies were purchased from Life Technologies . Anti-Lamin A/C antibody was purchased from BD biosciences . Anti-HSP60 , anti-NDUFA10 , anti-ACAD9 , and anti-COX10 antibodies were purchased from Abcam , and anti-NDUFB11 antibody was purchased from Santa Cruz Biotechnology . Anti-TTC37 antibody was purchased from ProteinTech . Anti-PNPLA4 ( GS2 ) was purchased from GeneTex . Anti-tafazzin and anti-α/β-tubulin antibodies were purchased from Cell Signaling Technology . Anti-β-actin antibody was purchased from Sigma . Anti-MECP2 antibodies were purchased from Acris Antibodies and Merck Millipore . Normal human dermal fibroblast cells and patient cells were seeded in a 35-mm glass-bottom dish . Mitochondria were stained with 500 nM MitoTracker Orange CMXRos ( Molecular Probes ) for 30 min in DMEM containing 10% fetal bovine serum . Cells were fixed with 4% paraformaldehyde for 20 min and permeabilized by incubation in 0 . 2% Triton X-100 . After blocking with 3% bovine serum albumin , fluorescent staining was performed with rabbit anti-PNPLA4 antibody ( GeneTex ) or mouse anti-V5 antibody ( Life Technologies ) and secondary Alexa Fluor 488 antibody ( Molecular Probes ) or secondary FITC antibody ( Sigma ) . Cells were visualized with a Leica TCS SP8 confocal microscope . For siRNA transfection , Lipofectamine RNAiMAX ( Invitrogen ) and 120 pmol of siRNA were prepared according to the manufacturer’s instructions and directly added to a 10 cm culture dish of NHDF fibroblasts . Mitochondria were isolated after 6 days , and the assembly levels of respiratory chain complexes were analyzed using BN-PAGE and Western blotting . The Stealth RNAi siRNA ( Life Technologies ) sequences used for NDUFB11 knockdown are as follows: HSS147694 ( #94 ) , ACC CAG ACU CCC AUG GUU AUG ACA A; HSS147695 ( #95 ) , UCC AAG AGC GUG GGA UGG GAU GAA A; HSS147696 ( #96 ) , CCU CUU CUC AGA GCA CCU AAU UAA A . Stealth RNAi siRNA Negative Control , Med GC ( cat no . 12935–300 ) was used as the negative control . The Silencer Select RNAi siRNA ( Life Technologies ) used for MECP2 knockdown are as follows: s8644 ( #44 ) , s8645 ( #45 ) , s8646 ( #46 ) . Silencer Select RNAi siRNA Negative Control , No . 2 ( #2 ) ( cat no . 4390847 ) was used as the negative control . Flies were reared at 25°C in a standard glucose yeast agar medium containing propionic acid and n-butyl p-hydroxybenzoate as mold inhibitors . arm-Gal4 was obtained from the Bloomington Drosophila Stock Center . UAS-dndufb11 ( NP15 . 6 ) -IR ( 5717 ) was obtained from the Vienna Drosophila RNAi Center . UAS-GFP-IR ( GFP-IR-2 ) was obtained from the National Institute of Genetics Fly Stock Center . Newly eclosed flies were housed in a glass vial containing the standard glucose yeast medium and were transferred to fresh media every 2 days; the numbers of dead flies were counted at the time of transfer . At least 100 flies per genotype were used for experiments . Eight flies were placed in an 8-lane cell vial ( 1 cell; H 7 mm × W 8 mm × D 70 mm ) and bumped to the bottom . Pictures were taken at 5 s after bumping and used to measure the distance climbed by each individual . For each sample , the average climbing activity of 10 trials was determined . CO2 production was measured as described previously[62] . In brief , 10 adult flies were placed in a 1-ml plastic syringe that contained a small amount of CO2-absorbent material ( Soda lime ) , which was connected to a 200-μl glass disposable micropipette . A small amount of black ink was placed at the end of the micropipette as an indicator of CO2 production . The apparatus was kept on a flat surface at 25°C , and measurement was initiated after 10 min . The amount of CO2 produced by the flies was calculated according to changes in the air volume during 1 h of measurement . Assays were performed at least 3 times per genotype . Lactate and pyruvate measurements were performed as described previously[63] . The cDNAs for hGatA with C-terminal SBP-HA-tag and hGatC with C-terminal HA-tag were cloned into pENTR/D-TOPO ( Invitrogen ) . Each of the pathogenic point mutations ( G117E and G133V ) was introduced into the hGatA gene in the entry clone by site-directed mutagenesis using PrimeSTAR HS DNA polymerase ( Takara ) with primers 5′-GATCAGGGAGCTCTACTAATGGAAAAAACAAATTTAGA-3′ and 5′-TCATCTAAATTTGTTTTTTCCATTAGTAGAGCTCCCTGATC-3′ for G117E , and 5′-GATCTGGGAGCACAGATGTTGTATTTGGACCAGTTAAAAAC-3′ and 5′-GTTTTTAACTGGTCCAAATACAACATCTGTGCTCCCAGATC-3′ for G133V . The cDNAs for hGatA ( WT , G117E or G133V ) and hGatC were transferred from each entry clone to pHAGE to generate the expression vector[64] by LR reaction ( Invitrogen ) . HEK293T cells were co-transfected with lentiviral vectors ( TAT , VSVG , RRE , or REV ) , pHAGE-hGatA ( WT , G117E or G133V ) and pHAGE-hGatC . The transformants were cultured at 37°C for 3 days . Cells were harvested and suspended in lysis buffer [50 mM HEPES-KOH ( pH 7 . 5 ) , 200 mM KCl , 1 mM PMSF , 0 . 1% TritonX-100 , 1 mM DTT , 2 . 5 mM MgCl2] containing complete protease inhibitor cocktail ( Roche ) and were disrupted by sonication at 0°C . The hGatCA complex in the cell lysate was captured with streptavidin-Sepharose beads ( GE Healthcare ) and was eluted from the beads with 4 mM of biotin according to the manufacturer’s instructions . The eluted hGatCA complex was subjected to SDS-PAGE , stained by SyproRuby , and quantified with a FLA-7000 imaging analyzer ( Fujifilm ) with BSA as a standard . Recombinant hGatB was expressed in Escherichia coli and was purified as described previously[23] . As human mt GluRS strictly recognizes the post-transcriptional modification at the anticodon first position ( position 34 ) of human mt tRNAGln for glutamylation[23] , in vitro-transcribed human mt tRNAGln cannot be aminoacylated by human mt GluRS . However , Thermotoga matritima nondiscriminating GluRS can efficiently glutamylate tRNAGln bearing unmodified C at position 34[65] . We accordingly prepared in vitro-transcribed human mt tRNAGln with C34 for glutamylation by T . maritima GluRS . Human mt tRNAGln with C34 was transcribed in vitro by T7 RNA polymerase from the template DNA PCR-amplified with the synthetic DNAs 5′-GCTAATACGACTCACTATATAGGATGGGGTGTGATAGGTGGCACGGAG-3′ , 5′-ATAGGTGGCACGGAGAATTCTGGATTCTCAGGGATGGGTTCGAT-3′ , and 5′-TGGCTAGGACTATGAGAATCGAACCCATCCCTGA-3′ , as described previously[66 , 67] . The aminoacylation reaction was performed at 37°C for 30 min in a mixture containing 50 mM HEPES-KOH ( pH 7 . 5 ) , 20 mM KCl , 10mM MgCl2 , 2 mM ATP , 1 mM DTT , 1 mM spermidine , 20 μM [14C]L-glutamine ( 9 . 36 GBq/mmol ) , 0 . 02 A260 unit of tRNA transcript , and 1 . 88 μM T . maritima GluRS . The [14C]Glu-tRNAGln was extracted by phenol–chloroform treatment under acidic conditions followed by ethanol precipitation . Residual ATP in the reaction was removed using a Nap5 gel filtration column ( GE Healthcare ) . A small part of the mixture was spotted onto Whatman 3MM filter discs , followed by washing with 5% trichloroacetic acid , and the radioactivity was measured by liquid scintillation counting . In vitro reconstitution of Gln-tRNAGln formation by hGatCAB was performed as described previously[23] . The reaction was performed at 37°C in a mixture of 100 mM HEPES-KOH ( pH 7 . 5 ) , 30 mM KCl , 12 mM MgCl2 , and 2 . 5 mM DTT , 5 mM ATP , 6 . 3 nM recombinant hGatCA ( WT , G117E , or G133V ) , 1 . 03 μM recombinant hGatB , 65 nM [14C]Glu-tRNAGln and 2 mM glutamine . Over time , aliquots of the reaction mixture were taken at 0 , 1 , 5 , 10 , and 15 min , and were mixed with phenol–chloroform to extract aminoacyl-tRNAs under acidic conditions , followed by ethanol precipitation and removal of ATP using a Nap5 column . The amino acids attached to the tRNA were deacylated at 37°C for 30 min in 0 . 3% aqueous ammonia . The [14C] labeled amino acids were analyzed by thin-layer chromatography ( TLC ) on a cellulose plate ( Melck ) using a basic solvent system ( 28% ammonia solution:chloroform:methanol , 1:3:4 ) . The TLC plate was exposed to an imaging plate , and the radioactivity was visualized using FLA-7000 image analyzer ( Fujifilm ) . Samples were processed in accordance with the manufacturer’s instructions . In brief , two aliquots of 250 ng genomic DNA were digested with Nsp1 and Sty1 , and ligated to adaptors . Generic primers recognizing the enzyme-specific adaptor sequences were used to amplify adaptor-ligated DNA . After purification , 270 μg of the PCR product was fragmented and labeled with biotin . Hybridization was performed in an Affymetrix GeneChip Hybridization Oven 640 , and the arrays were washed and stained in an Affymetrix GeneChip Fluidics Station 450 . Arrays were scanned with an Affymetrix GeneChip Scanner 3000 7G . Hardware scripts were enabled and image processing performed using the Affymetrix GeneChip Command Console software ( AGCC ) . Genotypes were called using the Affymetrix Genotyping Console software v4 . 1 . 1 GTC with the Birdseed algorithm and a default-calling threshold of 0 . 1 . Samples were required to have an average minimum Quality Control SNP call rate of 99 . 7% . All samples were analyzed with GTC v4 . 1 . 1 . The predicted copy numbers as well as the start and end of each CNV segment were determined using the Hidden Markov Model . In all datasets , hg19 was used . All large CNVs were manually curated . The CNV calls were also generated using the PennCNV software[68] . Results are presented as mean ± SEM or SD for the number of experiments indicated in the figure legends . Statistical analysis of continuous data was performed with 2-tailed Student’s t test , as appropriate . p < 0 . 05 was considered statistically significant . The study was approved by the ethics committee of the Saitama Medical University . Written informed consent was obtained from all subjects prior to inclusion in this study . 1000 Genomes Project , http://www . 1000genomes . org/; hs37d5 . fa ftp://ftp . 1000genomes . ebi . ac . uk/vol1/ftp/technical/reference/phase2_reference_assembly_sequence/; DECIPHER , https://decipher . sanger . ac . uk; DGV , http://dgv . tcag . ca/dgv/app/home; ExAC [Dec . , 2014 accessed] , Cambridge , MA , http://exac . broadinstitute . org; ESP6500 [accessed via ANNOVAR 2013Feb21 version] , http://evs . gs . washington . edu/EVS/; FASTQC , http://www . bioinformatics . babraham . ac . uk/projects/fastqc/; GERP , http://mendel . stanford . edu/SidowLab/downloads/gerp/; The Human Genetic Variation Database ( HGVD ) , http://www . genome . med . kyoto-u . ac . jp/SnpDB/index . html; Hgvd2annovar , https://github . com/misshie/hgvd2annovar; Homologene , http://www . ncbi . nlm . nih . gov/homologene; MitoCarta http://www . broadinstitute . org/pubs/MitoCarta/index . html; mtDB , http://www . mtdb . igp . uu . se/; NextCODE , http://www . nextcode . com/; OMIM , http://www . omim . org; Picard , http://broadinstitute . github . io/picard/; PolyPhen-2 , http://genetics . bwh . harvard . edu/pph2/; R for statistical analysis , http://www . R-project . org/; Ruby , https://www . ruby-lang . org/en/; SIFT , http://sift . jcvi . org/ . | Mitochondria play a crucial role in ATP biosynthesis and comprise proteins encoded in both the nuclear and mitochondrial genomes . Although more than 250 mitochondrial disease-causing genes have been reported , the exact genetic causes in patients remain largely unknown . Here , we aimed to provide further insights into the pathogenic mechanisms of mitochondrial disorders . We investigated the genes encoded in the nuclear and mitochondrial genomes using comprehensive genomic analysis in 142 patients with mitochondrial respiratory chain complex deficiencies . We identified 3 novel disease-causing mitochondria-related genes ( MRPS23 , QRSL1 , and PNPLA4 ) as well as other disease-causing genes and novel pathogenic mutations in known mitochondrial disease-causing genes . All pathogenic mutations in this study are validated by genetic and/or functional evidence . Our findings , including the achievement of firm genetic diagnoses for 49 of 142 patients ( 34 . 5% ) , were higher than the general diagnosis rate of approximately 25% and demonstrated the value of comprehensive genomic analysis . Accordingly , we have shed light on the genetic heterogeneity underlying mitochondrial disorders . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] | [] | 2016 | A Comprehensive Genomic Analysis Reveals the Genetic Landscape of Mitochondrial Respiratory Chain Complex Deficiencies |
Plasmacytoid dendritic cells ( pDCs ) , considered critical for immunity against viruses , were recently associated with defense mechanisms against fungal infections . However , the immunomodulatory function of pDCs in pulmonary paracoccidiodomycosis ( PCM ) , an endemic fungal infection of Latin America , has been poorly defined . Here , we investigated the role of pDCs in the pathogenesis of PCM caused by the infection of 129Sv mice with 1 x 106 P . brasiliensis-yeasts . In vitro experiments showed that P . brasiliensis infection induces the maturation of pDCs and elevated synthesis of TNF-α and IFN-β . The in vivo infection caused a significant influx of pDCs to the lungs and increased levels of pulmonary type I IFN . Depletion of pDCs by a specific monoclonal antibody resulted in a less severe infection , reduced tissue pathology and increased survival time of infected mice . An increased influx of macrophages and neutrophils and elevated presence of CD4+ and CD8+ T lymphocytes expressing IFN-γ and IL-17 in the lungs of pDC-depleted mice were also observed . These findings were concomitant with decreased frequency of Treg cells and reduced levels of immunoregulatory cytokines such as IL-10 , TGF-β , IL-27 and IL-35 . Importantly , P . brasilienis infection increased the numbers of pulmonary pDCs expressing indoleamine 2 , 3-dioxygenase-1 ( IDO ) , an enzyme with immunoregulatory properties , that were reduced following pDC depletion . In agreement , an increased immunogenic activity of infected pDCs was observed when IDO-deficient or IDO-inhibited pDCs were employed in co-cultures with lymphocytes Altogether , our results suggest that in pulmonary PCM pDCs exert a tolerogenic function by an IDO-mediated mechanism that increases Treg activity .
Paracoccidioides brasiliensis , a thermally dimorphic fungus , is the causative agent of paracoccidioidomycosis ( PCM ) , the most prevalent deep mycosis in Latin America . In humans and murine models of PCM , resistance to disease is associated with the secretion of IFN-γ and other Th1 cytokines , whereas impaired Th1 immunity and the prevalent secretion of Th2 cytokines correlate with systemic and progressive disease [1–3] . The importance of Th17 immunity is not well defined . However , IL-17-expressing cells have been observed in cutaneous and mucosal lesions of PCM patients and have been associated with the organization of granulomas [4] . It was also recently reported that the diverse patterns of T cell responses of P . brasiliensis-infected individuals lead to different clinical manifestations . The resistance to infection observed in asymptomatic individuals was shown to be mediated by a predominant Th1 response , which is responsible for macrophage activation . The most severe form of the disease , the juvenile form , presents a prevalent Th2/Th9 response and an enhanced antibody response . In the chronic inflammatory response characteristic of the adult form of the disease , a prominent Th17 immunity with important participation of Th1 cells was described [5] . Additional studies with mouse Pattern Recognition Receptors-deficient ( PRR-deficient ) cells allowed us to demonstrate that dectin-1 , mannose receptor ( MR ) , TLR-2 , and TLR-4 control lymphocyte proliferation and IL-17 production induced by P . brasiliensis-stimulated dendritic cells ( DCs ) [6] . Our in vivo studies have also demonstrated that TLR2 deficiency enhanced Th17 immunity , which was associated with diminished expansion of regulatory T cells ( Tregs ) and increased lung pathology due to unrestrained inflammatory reactions [7] . Furthermore , studies with TLR4 , dectin-1 and MyD88 deficient mice led us to demonstrate the essential influence of these receptors and adaptor molecule expression in the control of lung pathology and dissemination of P . brasiliensis yeasts [8–10] . DCs are bone marrow derived cells that continuously survey their environment for invading microorganisms and are considered professional antigen-presenting cells ( APCs ) due to their unique ability to activate T cells [11] . Plasmacytoid dendritic cells ( pDCs ) are a subset of DCs that produce large amounts of type I interferon and are largely involved in the immunity against viral infections [12] . However , pDCs can also exert a tolerogenic function suppressing T cell immunity and expanding regulatory T cells ( Treg ) in infectious processes and neoplasms [13–16] . Upon viral exposure , pDCs initiate protective antiviral responses by secreting up to 1000-fold more type I IFNs than other cell types [16] . Following TLR stimulation [17 , 18] pDCs become potent APCs that secrete high levels of cytokines such as IFN-α and TNF-α and differentiate into mature pDCs upregulating MHC and costimulatory molecules and priming naive T cells to Th1 or Th17 differentiation [17–20] . Beyond the universe of viral infections , an important role of pDCs was demonstrated in the immune response against Legionella pneumophila , an intracellular bacterium . These studies showed that pDCs were quickly recruited to the lungs of infected mice , and their depletion led to increased bacterial load in a mechanism independent of type I IFNs production [21] . Furthermore , in some fungal infections an important involvement of pDCs was also described [2 , 22–24] . Ramirez-Ortiz showed that pDCs bind to and inhibit the growth of Aspergillus fumigatus hyphae and depletion of these cells renders mice hyper-susceptible to experimental aspergillosis [23] . Moreover , our group showed that dectin-2 , a C-type lectin receptor ( CLR ) expressed by human pDCs , acts in cooperation with the FcRγ chain to recognize A . fumigatus hyphae , activate signaling responses , synthesize TNF-α and IFN-α , and exert antifungal activity . Furthermore , hyphal stimulation of human pDCs triggers a distinct pattern of pDC gene expression and leads to formation of extracellular traps ( pETs ) [24] . In a previous study , we verified that in vitro P . brasiliensis infection induced in bone marrow-derived dendritic cells ( DCs ) of susceptible mice a prevalent inflammatory myeloid phenotype that secreted high levels of IL-12 , TNF-α , and IL-β , whereas in resistant mice , a mixed population of myeloid and pDCs secreting inflammatory cytokines and expressing elevated levels of secreted and membrane-bound TGF- β was observed [2] . In the present study , we investigated the contribution of pDCs to host defenses against murine PCM . Depletion of pDCs results in a less severe disease , a high frequency of activated CD4+ and CD8+ T lymphocytes , concomitant with elevated numbers of macrophages and neutrophils that migrate to the lungs of depleted mice . The analysis of lung homogenates showed diminished levels of type I IFN as well as reduced levels of immunoregulatory cytokines . Furthermore , a reduced number of Foxp3+ Treg cells and a decreased presence of pDCs expressing indoleamine 2 , 3-dioxygenase ( IDO ) , an enzyme with potent immunoregulatory properties , were found in the lungs of pDC-depleted mice . Finally , pDCs of IDO deficient mice and 1MT-treated pDCs stimulated by P . brasiliensis yeasts were more efficient in the induction and activation of T cells in parallel with reduced expansion of Treg cells . Taken together , our results demonstrate a tolerogenic activity of pDCs associated with increased expansion of Treg cells possibly by an IDO-mediated mechanism .
Initial experiments were focused on determining the pDCs response following P . brasilienis infection . pDCs were isolated from the lungs of uninfected and P . brasilienis infected mice at weeks 2 and 8 post-infection . The maturation of pDCs was assessed by flow cytometric evaluation of activation markers as well a the presence of type I IFNs and TNF-α in the supernatant of cell cultures . A gating strategy to the pDC analysys is represented in the Fig 1A . A mature phenotype of pDCs was induced by P . brasilienis infection . A higher frequency of cells expressing CD40 , CD80 , CD86 and MHC-II was observed in pulmonary pDCs isolated from infected mice ( Fig 1B and 1C ) when compared with cells from uninfected mice . The number of pDCs that migrate to the lungs was also determined . We observed an increased number of pDCs following P . brasilienis infection ( Fig 1D ) . Regarding cytokines production , pDCs from infected mice produced higher levels of IFN-β and TNF-α ( Fig 1E ) than pDCs isolated from non-infected mice . The severity of fungal infection in pDC-depleted and control groups of P . brasiliensis infected mice was then assessed at early and late periods of the disease by CFU counts , tissue pathology and mortality rates . The depletion of pDCs by mAb treatment efficiently reduced the afflux of pDCs to the lungs at 96 h , 2 and 8 weeks post-P . brasilienis infection ( Fig 2A ) . Reduced pulmonary fungal burdens were observed in pDC-depleted mice at weeks 2 and 8 after infection ( Fig 2B ) , although no differences were found at an early period of infection ( 96 h ) . Reduced hepatic fungal loads were observed in pDC-depleted mice only at week 8 after infection ( Fig 2C ) . Pulmonary lesions in pDC-sufficient mice ( Fig 2D and 2F ) replaced large part of normal tissue and were composed of organized granulomas of small sizes although in higher number and containing a higher number of yeasts cells than those found in the pDC-depleted mice ( Fig 2E and 2G ) . As a consequence , smaller lesion areas were observed in the lungs of this latter experimental group ( Fig 2H ) . Reduced liver lesions were also found in pDC-depleted mice ( S1 Fig ) . To assess the influence of pDCs on disease outcome , mortality of infected mice was registered daily . As shown in Fig 2I , at day 82 of infection all control mice were dead and four pDC-depleted mice were still alive . Because pDCs are major cells involved in the production of type I IFNs [25] the expression of IFN mRNA and proteins was evaluated in the lungs of 129Sv uninfected and P . brasilienis-infected mice as well as in pDC-depleted and control infected mice . An expressive increase of IFN-α and IFN-β mRNA was observed in the lungs of P . brasilienis infected mice ( Fig 3A ) but only IFN-β appeared in detectable levels in the supernatants of lung homogenates ( Fig 3B ) . The levels of IFN-β were consistent with the increased mRNA expression observed at almost all post-infection period studied . A significant reduction of IFN-α and IFN-β mRNA was observed in the lungs of pDC-depleted mice at weeks 2 and 8 of infection ( Fig 3C ) . Again , only IFN-β appeared in detectable levels in the supernatants of lung homogenates of control ( IgG ) and anti-pDC treated mice , and appeared in reduced levels in pDC-depleted mice ( Fig 3D ) at weeks 2 and 8 of infection . By two weeks after infection , lungs of pDC-depleted mice showed diminished levels of regulatory cytokines ( TGF-β and IL-10 ) , associated with increased levels of inflammatory cytokines such as IFN-γ , TNF-α , IL-12 and IL-6 ( Fig 3E ) . This behavior suggested that the pDCs were preferably priming regulatory or suppressive T cells and their reduction led to preferential inflammatory responses . By eight weeks after infection , this anti-inflammatory response became more evident: IL-35 , IL-27 , and TGF-β appeared in reduced levels in contrast to the elevated concentrations of Th1 and Th17 cytokines in the lungs of pDC-depleted mice ( Fig 3F ) . Since IL-27 was previously shown to play important immunoreregulatory functions in the liver , the hepatic synthesis of this cytokine was assessed at weeks 2 and 8 after P . brasiliensis infection , and reduced levels were found in pDC-depleted mice ( Fig 3G ) . In addition , the hepatic pDCs isolated from infected mice produced higher level of IL-27 than cells of uninfected mice ( S2 Fig ) . Moreover , consistent with the high levels of inflammatory cytokines observed , elevated concentrations of NO were detected in the supernatants of lung homogenates of pDC-depleted mice ( Fig 3H ) . Because pDCs are the major producers of type I IFNs and reduced levels of IFN-β were found in the lung supernatants of pDC-depleted mice , we next examined the susceptibility of IFNα/βR−/− mice , which do not respond to type I IFNs , to P . brasiliensis infection . To have o more complete view on the effects of IFNs signaling during PCM infection , we also evaluated the course of the disease in the IFNγR−/− and IRF1-/- mice . It is known that IFNs signaling is initiated by two distinct cell-surface receptors , type I IFN receptor ( IFNα/βR ) and type II IFN receptor ( IFNγR ) . Signaling through IFNαR/STAT1 leads to the formation IFNα-activated factor that mediates the activation of interferon regulatory factor 1 ( IRF-1 ) gene by binding to IFNγ-activated sequence ( GAS ) in IRF-1 promoter . Likewise , type II IFN signaling through IFNγR/STAT1 also results in STAT1 homodimers binding to GAS and IRF-1 [26–27] . Notably , IRF-1 was the first described member of the family of transcription factors known as Interferon Responsive Factors , which have essential roles in responses against intracellular pathogens , including generation of iNOS and subsequent NO production [28–29] . The severity of P . brasiliensis infection was assessed in IFNα/βR−/− , IFNγR−/− and IRF-1-/- mice at early and late periods of the disease . Pulmonary , liver and splenic fungal burdens were increased at weeks 2 ( Fig 4A ) and 8 ( Fig 4B ) after infection compared to those observed in WT mice . In addition , an increased number of nonorganized lesions containing high numbers of fungal cells and intense tissue destruction were observed in IFNα/βR−/− mice . Pulmonary lesions in IFNα/βR−/− mice replaced large part of normal tissue and were composed of confluent necrotic lesions containing many budding yeasts . The lesions in the lungs of WT mice occupied a small area and were composed of organized granulomas of small sizes ( Fig 4C and 4D ) . The lesions and severity of the disease in the IFNα/βR−/− mice was similar to those found in IFNγR−/− ( Fig 4E ) and IRF-1-/-mice ( Fig 4F ) as indicated by the area of pulmonary of lesions detected ( Fig 4G ) . Survival of P . brasiliensis-infected mice was registered daily over a 110-day period ( Fig 4H ) . All deficient strains showed increased mortality rates in comparison with WT mice . The mean survival time of IRF-1-/- mice was 35 days , of IFNα/βR−/− and IFNγR−/− mice was 40 days , while the WT mice presented a mean survival time of 80 days . Altogether these data indicate that type I and type II IFNs are protective to pulmonary PCM , and the less severe disease caused by depletion of pDCs cannot be attributed to the reduced levels of type I IFNs observed during depletion experiments . To better clarify the importance of pDCs in the polarization of T cell responses , the expression of genes associated with Treg and T cell subsets was measured by RT PCR in the lungs of pDC-depleted and control mice . As shown in Fig 5 , increased mRNA levels of the Th1- and Th17-related transcription factors Tbet and RORγC , and diminished expression of Foxp3 were detected . No significant changes in mRNA levels of GATA3 , a Th2-related transcription factor , were detected at all time points analyzed . The polarization of T-cell responses in the inflammatory infiltrates of lungs was also assessed by intracellular staining of IL-17– , IFN-γ– and IL-4-producing cells . Confirming mRNA studies , a higher frequency and number of CD4+ and CD8+ lymphocytes expressing intracellular IFN-γ and IL-17 were found in the lungs of pDC-depleted mice . No differences were found in lymphocytes expressing intracellular IL-4 between the studied groups ( Fig 6 ) . In order to verify whether depletion of pDC affected the influx of effector leucocytes to the lungs , the frequency and activation of macrophages , neutrophils and T cells was assessed by flow cytometry . A gating strategy was represented in the Fig 7A . At weeks 2 and 8 post-infection , an increased number of lung infiltrating leukocytes ( Fig 7B ) was detected in anti-pDC-treated mice . Compared with controls , a higher frequency and number of neutrophils ( Fig 7C ) , macrophages ( Fig 7D ) , and activated CD4+ ( Fig 7E ) and CD8+ T ( Fig 7F ) cells were observed in the lungs of pDCs depleted mice . In agreement , at week 2 ( Fig 7G ) post-infection a reduced frequency of infiltrating CD4+ T cells expressing deactivation or suppressive molecules ( CTLA4 , GITR , ICOS ) were seen in the lungs of pDC-depleted mice . However , only the number of infiltrating CD4+ T cells expressing GITR was reduced in the pDC depleted group . At week 8 post-infection only CTLA4 expressing lymphocytes were observed in decreased frequency ( Fig 7H ) . Since pDCs depletion affected the expansion and migration of T cells , we further characterized the influx of Treg cells to the lungs of treated and control mice . The frequency of CD4+ CD25+ T cells expressing Foxp3 in the lungs was determined by flow cytometry after 2 and 8 weeks of infection and gated cells in lung homogenates are shown in Fig 8A . pDC-depleted mice showed significantly lower frequency and number of pulmonary CD4+CD25+Foxp3+ Treg cells than IgG-treated control mice ( Fig 8B , left and central panels ) after 2 weeks of infection . Accordingly , the median fluorescence intensity ( MFI ) of Foxp3+ cells was lower in pDC-depleted mice at both analyzed periods ( Fig 8B , right panel ) . In order to verify whether the reduced expansion of CD4+Foxp3+ cells was associated with a change in their activation profile , the expression of some activation markers was measured . The Fig 8C and 8D show that at both post-infection periods analyzed , pDC depletion led to decreased frequency and number of CD4+Foxp3+ Treg cells expressing almost all activation markers studied ( CTLA-4 , GITR , ICOS ) . Our recent study showed that indolemine 2 , 3 dioxygenase control fungal burdens , and inflammatory reactions in pulmonary PCM [30] . In addition , the production of IDO by pDCs has been linked to the proliferation and activation of resting Foxp3+ Treg cells [30 , 31] . Our findings demonstrating a reduced frequency of Treg cells in pDC-depleted mice , led us to further investigate the participation of IDO in the tolerance mechanisms promoted by pDCs . First , we evaluated the production of IDO by pDCs isolated from uninfected and infected mice ( 2 and 8 weeks after P . brasiliensis infection ) . A gating strategy to the pDC analysis is represented in the Fig 9A . As can be seen , P . brasileinsis infection induced an increased frequency and number of pDCs expressing IDO in comparison with uninfected mice ( Fig 9B and 9C ) . Consistent with the IDO production , the levels of kynurenines were also found in increased levels in the supernatants of pDCs isolated from P . brasiliensis infected mice ( Fig 9D ) . Further studies demonstrated a reduced expression of IDO mRNA in the lungs of pDC-depleted mice at all post-infection periods assayed ( Fig 9E ) . In addition , the levels of kynurenines were also found in reduced levels in the lung homogenates of pDC-depleted mice ( Fig 9F ) . Furthermore , to better elucidate the role of IDO in the tolerogenic activity of pDCs , these cells were isolated from non-infected 129Sv mice , treated with 1MT , an IDO inhibitor , infected and matured in the presence of P . brasiliensis yeasts . These pDCS were then co-cultured with normal splenic lymphocytes from 129Sv mice . Accordingly , the IDO inhibition by 1MT led to a reduced frequency of Treg cells ( Fig 10A ) associated with enhanced proliferative response of CD3+ , CD4+ and CD8+ T cells ( Fig 10B ) , and increased activation of both T cells subsets ( Fig 10C ) . Equivalent results were obtained using the same experimental approach and cells from C57Bl/6 WT and C57BL/6 IDO-/- mice ( S3 Fig ) .
Several studies have demonstrated the important regulatory function of pDCs in immunity against viral infections , autoimmune diseases and in the maintenance of self-tolerance [15 , 32 , 33] . Although a prominent function of pDCs has been particularly associated with viral infections , recent investigations have expanded this concept to other types of pathogens . Under the universe of microbial infections new data have been added demonstrating an important role of these cells in bacterial [34–36] and fungal infections [2 , 23 , 24] . In the present study , we investigated the contribution of pDCs to host defenses against pulmonary PCM . Following pulmonary P . brasiensis infection of 129Sv WT mice , a considerable recruitment of pDCs to the lungs was observed . These recruited pDCs are able to present antigen to T cells and secrete cytokines as evidenced by the hight expression of coestimulatory molecules , MHC-II , TNF-α and IFN-β production . The influx of pDCs to the site of infection was also reported during A . fumigatus infection [23] , but here we were able to demonstrate the mature phenotype of these cells and their ability to secrete cytokines , including type I IFN . The depletion of pDCs led to a less severe infection , with decreased fungal burdens in the lungs , resulting in increased survival times . This better disease outcome was concomitant with a reduced number of organized lesions containing small numbers of fungal cells and diminished damaged tissue . These findings were opposed to those described previously where pDC-depleted mice were dramatically more susceptible to both pulmonary and systemic infection with A . fumigatus [23] . Therefore , pDCs can be viewed as protective or detrimental cells during fungal infections , depending on the fungal species that is causing the infection , and further studies with diverse fungal pathogens and morphotypes should be done to better understand the role of pDCs in fungal infections . pDCs secrete large amounts of type I IFN in response to several viruses and to a large variety of DNA and RNA sequences [37] , but their role during fungal infections remains unclear . The role for type I IFNs in invasive aspergillosis was investigated by comparing wild-type mice and IFNα/βR−/− mice . The deficient mice had accelerated mortality after intravenous challenge with A . fumigatus [23] . In accordance , IFNα/βR−/− mice were susceptible to Cryptococcus neoformans and failed to produce protective Th1 cytokines [38] , but studies with murine models of candidiasis have implicated type I IFN receptor-deficient mice with decreased survival rates after Candida albicans infection [39] . Here we showed that pDC respond to P . brasiliensis infection producing mRNA to IFN-α and IFN-β , secrete IFN-β at the site of infection but behave as tolerogenic cells that increase disease severity . In agreement , tolerogenic pDCs induced by TGF-β signaling and phosphorylated IDO produce high levels of IDO and TGF-β besides IFN-α/IFN-β in response to the noncanonical NF-;AB pathway of cell activation [32] . During pDC depletion reduced levels of type I IFNs were found in lung homogenates , leading us to hypothesize that the protective mechanism mediated by pDCs depletion could be due to the inhibition of type I IFNs production . To analyze this possibility we have further studied the course of the disease in IFNαβR -/- mice . A protective effect of type I IFN signaling was detected as demonstrated by the increased fungal loads , tissue pathology and mortality rates developed by deficient mice . It is important to highlight that in depletion experiments only reduced levels of type I IFN were seen whereas total abrogation of type I IFN signaling characterizes the response of type I IFNαβR -/- mice . Therefore , it is possible that total absence versus partial reduction of type I IFN could explain the apparent discrepancy observed in depletion studies versus experiments using genetically deficient mice . Furthermore , type I IFN signaling is important to nitric oxide ( NO ) production induced by type 2 nitric oxide synthase ( NOS2 ) [40 , 41] and NO has been described as one of the most important mediator involved in the fungicidal mechanisms and immunoprotection against P . brasiliensis infection [42 , 43] . Thus , the total absence of type I IFN signaling could have exacerbated more drastic effects in NO production than its partial reduction . It is also relevant to point out that pDC is described as the major source of type I IFNs , but these cytokines can be produced by almost any cell type in the body in response to stimulation of an array of transmembrane and cytosolic receptors [26] , but during pDC depletion only one source was withdrawal . Altogether , our data demonstrated that the immunoprotection induced by pDC depletion was not mediated by the inhibition of type I IFN production . Surprisingly , the severity of the disease caused by absence of type I IFN signaling was equivalent to that observed in IFNγR-/- mice . Indeed , IFNγ is a major cytokine associated with PCM resistance due to its macrophage activating activity , induction of NO and inflammatory cytokines such as TNFα resulting in inhibition of P . brasiliensis replication [1 , 3 , 44 , 45 , 46] . Because pDCs express MHC class II molecules as well as costimulatory molecules such as CD40 , CD80 and CD86 , they can present antigens to CD4+ T cells [47 , 48] . The pDCs have also been shown to be particularly involved in the differentiation of Th17 cells , an emergent T cell subtype that appears to have an important role in the immunity against fungal infections [49 , 50] . In addition , IFN-α produced by pDCs modulated the Th17 differentiation during the early infection of mice by Bordetella pertussis [36] . In contrast , in our study pDC depletion increased the differentiation of Th1 and Th17 cells indicating a tolerogenic function of these antigen-presenting cells . This activity , as demonstrated by enhanced expression of mRNA of transcription factors Tbet and RORc for Th1 and Th17 differentiation and production of elevated levels of type-1 and type-17 cytokines by pDC depleted mice , indicates the suppressive activity of this DC subset in the immunity against P . brasiliensis infection . The outcome of antigen presentation can be tolerogenic , leading to the differentiation of regulatory or suppressor T cells , T cell anergy and impaired T cell proliferation , depending on the signals developed at the time of antigen recognition [48 , 51] . Some reports showed that pDCs resident in human thymus drive natural Treg cell development [52 , 53] . Besides , the high expression of some cell markers like ICOS-L provides the maturation of human pDCs and the ability of inducing the differentiation of naive CD4+ T cells to Treg IL-10-producing cells [14] . Treg cells can also be induced by PD-L1 signaling [54] , and pDCs expressing high levels of this cell component were able to expand an elevated frequency of Treg cells in tolerized recipients . Moreover , splenic pDCs from PD-L1-deficient mice induce greater levels of CD4+ T cell proliferation than pDCs from WT mice [31 , 55 , 56] . In our model , the depletion of pDC affected the expression of Foxp3 , the major transcription factor of Treg cells . Accordingly , pDC-depleted mice showed lower frequency Treg cells in comparison with IgG-treated mice , besides a decreased expression of most of cell markers associated with the suppressive activity of Treg cells ( CTLA-4 , GITR , and ICOS ) . In a previous study , we showed that early depletion of Treg cells by anti-CD25 antibodies culminates with a less severe disease in susceptible and resistant mice infected with P . brasiliensis . Importantly , anti-CD25 treatment led to increased fungicidal mechanisms and increased secretion of Th1/Th2/Th17 cytokines without enhanced tissue pathology [57] . Another study using gain and loss approaches demonstrated the dual role of Tregs that are involved in the control of tissue pathology and in the differentiation of Th17 cells but also in the suppression of protective T cell immunity [58] . The findings here reported are in agreement with our previous studies because we could verify that the impaired Treg response resulted in effective Th1 and Th17 immune response that increased the influx of inflammatory cells to the site of infection without enhanced tissue pathology . This behavior suggests that in pulmonary PCM , pDCs prime and expand regulatory T cells and its deficiency contributes to more efficient Th1 and Th17 immune responses . The measurement of lung cytokines has also demonstrated the importance of pDCs in the production of regulatory cytokines . Indeed , TGF-β , IL-10 , IL-35 and IL-27 were found in reduced levels in the lungs of pDC-depleted mice . IL-35 is a recently described Treg cytokine required for maximal regulatory activity of murine and human Treg cells [59] . IL-27 has also broad inhibitory effects on Th1 , Th2 and Th17 cells as well as on the expansion of inducible Treg cells [60] . Furthermore , a recent study demonstrated that IL-27 produced by mouse hepatic pDCs has an important contribution to immunoregulation [61] . In agreement , our studies demonstrated a significant augment of IL-27 levels in lungs and liver homogenates after P . brasiliensis infection as well as a reduction of pulmonary and hepatic IL-27 in pDC-depleted mice . In addition , ex vivo experiments confirmed that hepatic pDCs are a source of IL-27 . Unfortunately , we did not detect IL-27 in the lung pDCs isolated from uninfected and infected mice . An explanation for this negative finding is the different yield of pDCs recovered from lungs and liver . The ex vivo culture of lung pDCs was performed with 1 x 105 cells while 3 x 105 cells were used in the liver pDC cultures . As a whole , the findings here reported confirmed the important tolerogenic role of pDCs in pulmonary PCM . These cells are involved in the expansion of Treg cells , inhibition of Th1 and Th17 immunity but their deficiency do not exert a deleterious effect because the increase inflammatory immunity was accompanied by significant reduction on fungal loads with consequent reduction in fungal-induced pathology . IDO is a rate-limiting enzyme that converts tryptophan to its metabolic products , collectively known as kynurenines . The expression of IDO by macrophages and DCs subsets allows them to inhibit T cell priming and proliferation associated with enhanced Treg cells differentiation , highlighting the importance of IDO expression in the prevention of hyper inflammatory responses [62] . Besides its enzymatic activity , IDO was also shown to be involved in intracellular signaling events responsible for the amplification and maintenance of a regulatory phenotype in pDCs that promotes tolerance [32 , 63 , 64] . Our data are in agreement with the axis IDO-Treg in promoting immune tolerance because an increased frequency and number of pDCs expressing IDO during P . brasilensis infection were found . In addition , a reduced expression of IDO mRNA in the lungs of pDC-depleted mice was detected at all post-infection periods . It was previously described that the IDO activity and sustained production of kynurenines promote the expansion of Treg cells [65] . In accordance , culture supernatants of pDCs isolated from infected mice showed higher levels of kynurenines than those obtained from uninfected mice . In addition , the in vivo depletion of pDCs reduces the levels of kynurenines produced indicating a close correlation between IDO expression , kynurenines production and increased expansion of Treg cells . Our data have also further elucidate the role of IDO in the tolerogenic activity of pDCs . The pDC treatement with 1MT and co-cultured with normal splenic lymphocytes from 129Sv mice led to reduced expansion of Treg cells associated with increased proliferation and activation of T cells . This finding was further confirmed using pDC from IDO-/- mice . In accordance , the frequency of Treg cells was significantly diminished when the pDCs were isolated from IDO-deficient mice than obtained from WT mice . Previous studies highlighted the involvement of a fungal infection in the IDO-dependent promotion of tolerogenic DCs . Candida-hyphae activate the tolerogenic program in some DC subsets and this behavior controls the balance between inflammation and tolerance . This balance is fundamental to the coevolution of host immunity and commensal fungal infections that occur without excessive detrimental effects to both organisms [64 , 66] . It is important to note that the main effect of IDO inhibition in the immunity of resistant and susceptible mice previously reported [30] is different from that here reported . In B10 . A mice , the IDO activity is mainly mediated by IFN-γ , whereas in the resistant A/J mice IDO is mainly induced by TGF-β signaling [2 , 30] . In addition , the early tolerogenic response developed by A/J mice is transitory and later counter balanced by a pro-inflammatory activity and prevalent NLRP3 activation resulting in a late Th1/Th17 immunity tightly regulated by Treg cells [57 , 67] . In the 129Sv background , we believe that the tolerogenic role of pDCs appears to be maintained in the course of infection , resulting in more severe infection that can be modulated by pDCs depletion . The disease severity developed by 129Sv mice is more close to that developed by the susceptible mouse strain . However , in contrast to B10 . A mice where suppression of T cell response is mediated by excessive pro-inflammatory innate immunity , the deficient T cell immunity here observed was mainly mediated by the sustained expansion of tolerogenic pDCs . Taken together , our results clearly demonstrated the tolerogenic function of pDCs during pulmonary PCM . These cells are involved in the differentiation of CD4+CD25+Foxp3+ Treg cells possibly by an IDO-mediated mechanism that impairs the development of protective Th1 and Th17 cells . Finally , we believe that these results contribute to a better understanding of immunoregulation during P . brasileinsis infection , and open perspectives of novel immunotherapeutic procedures based on the control of IDO production and Treg expansion .
Animal experiments were performed in strict accordance with the Brazilian Federal Law 11 , 794 establishing procedures for the scientific use of animals , and the State Law establishing the Animal Protection Code of the State of São Paulo . All efforts were made to minimize suffering , and all animal procedures were approved by the Ethics Committee on Animal Experiments of the Institute of Biomedical Sciences of University of São Paulo ( Proc . 180/11/CEEA ) . Eight- to 12-week-old male 129Sv WT , 129Sv IFNαβR-/- , 129Sv IFNγR-/- , 129Sv IRF1-/- , C57Bl/6 WT and C57Bl/6 IDO-/- mice were obtained from the specific pathogen free Isogenic Breeding Unit of the Department of Immunology , Institute of Biomedical Sciences , University of São Paulo . The highly virulent P . brasiliensis 18 isolate ( Pb18 ) was used throughout this study . Yeast cells were maintained by weekly cultivation in Fava Netto culture medium at 36°C and used on days 5–7 of culture . The viability of fungal suspensions , determined by Janus Green B vital dye ( Merck ) , was always higher than 95% . Mice were anesthetized and submitted to intra-tracheal ( i . t . ) infection as previously described [68] . Briefly , after intraperitoneal ( i . p . ) injection of ketamine and xylazine , animals were infected with 1×106 Pb18 yeast cells , contained in 50 μL of PBS , by surgical i . t . inoculation , which allowed dispensing of the fungal cells directly into the lungs . In vivo depletion of pDC with anti-CD317 ( PDCA-1 ) antibodies ( BioXcell , USA ) was performed as previously described [23] . Briefly , 129Sv WT mice were given i . p . injections of 250 μg of anti-CD317 ( clone BX44 , BioXcell ) or control rat IgG ( clone HRPN , BioXcell ) diluted in sterile PBS . Antibodies were administered on days -1 , O , 1 and every 3 days after infection with P . brasiliensis yeasts . The numbers of viable microorganisms in cell cultures and infected organs were determined by counting the number of colony-forming units ( CFU ) as previously described [69] . Mortality studies were done with groups of 10–12 mice . Deaths were registered daily . For histological examinations , the left lung and liver of infected mice was removed and fixed in 10% formalin . Five-micrometer sections were stained by hematoxylin-eosin for an analysis of the lesions and were silver stained ( Grocott stain ) for fungal evaluation . Morphometrical analysis was performed using a Nikon DXM 1200c camera and Nikon NIS AR 2 . 30 software . The areas of lesions were measured ( in square micrometers ) in 10 microscopic fields per slide in 5 mice per group . Results are expressed as the mean ± SEM of total area of lesions for each mouse . pDCs were isolated from lungs and liver of 129Sv infected mice after 2 and 8 weeks of P . brasiliensis infection by two rounds of positive selection , using anti-mPDCA coated magnetic beads ( Miltenyi Biotec ) . The pDCs were counted and used in flow cytometric analysis . Some groups of pDC were cultured overnight ( 1 x 105/well for lung pDCs; 3 x 105/well for liver pDCs ) . After 18 hr , the supernatants were removed and stored at -80°C to further measurements of cytokynes and kynurenines . Lungs and liver from P . brasilienis-infected 129Sv mice were collected after 2 and 8 weeks of infection . Both organs from uninfected 129Sv mice were also collected . To asses the leukocyte subpopulations after depletion of pDCs , the lungs from 129Sv pDC-depleted and control mice were removed after 96h , 2 and 8 weeks post infection and digested enzymatically for 40 minutes with collagenase ( 2 mg/mL ) in RPMI culture medium ( Sigma ) . Total lung leukocyte numbers were assessed with trypan blue , and viability was always >95% . For cell-surface staining , leukocytes and purified pDCs were washed and suspended at 1 × 106 cells/mL in staining buffer ( PBS , 2% fetal calf serum and 0 . 1% NaN3 ) . Fc receptors were blocked by the addition of unlabeled anti-CD16/32 ( eBioscience ) . Leukocytes were then stained in the dark for 20 min at 4°C with the optimal dilution of each monoclonal antibody . To pDC: anti-CD11c , B220 , PDCA , CD40 , CD80 , CD86 and MHC-II; lymphocytes: CD4 , CD8 , CD25 , CD69 , CTLA-4 , PD-1 , ICOS , GITR; macrophages and neutrophils: F4/80 , CD11b , Ly6G ( eBiosciences or BioLegend ) . Cells were washed twice with staining buffer , fixed with 2% paraformaldehyde ( PFA; Sigma ) . For intracellular detection of cytokines , leukocytes obtained from lungs were stimulated for 6 hours in complete RPMI medium containing 50 ng/mL phorbol 12-myristate 13-acetate , 500 ng/mL ionomycin ( Sigma ) , and 3 mM monensin ( eBioscience ) . Next , cells were labeled for surface molecules and then treated according to the manufacturer’s protocol for intracellular staining using the Cytofix/Cytoperm kit ( BD Biosciences ) and specifics antibodies anti-17 , IL-4 , IFN-γ , FoxP3 and IDO . Cells were washed twice with staining buffer , suspended in 100 μl , and an equal volume of PFA was added to fix the cells . A minimum of 50 , 000 events was acquired on FACScanto II flow cytometer ( BD Biosciences ) using the FACSDiva software ( BD Biosciences ) . Lymphocytes , macrophages and neutrophils were gated as judged from forward and side light scatter . For Treg cell characterization , FACS plots or histograms were gated on live CD45+CD4+CD25+ cells and the expression of FoxP3+ were determined . The cell surface expression of leukocyte markers as well as intracellular cytokine expression was analyzed using the FlowJo software ( Tree Star ) . Lungs were homogenized in TRIzol reagent using tissue grinders . Phase separation was achieved following addition of 0 . 2 ml chloroform per ml of TRIzol and centrifugation at 12 , 000×g for 15 min at 4°C . The upper aqueous RNA phase was transferred to a fresh tube and further purified using Ultraclean Tissue & Cells RNA Isolation Kit ( MO BIO Laboratories ) according to the manufacturer’s protocol . RNA purity and concentration were assessed on a NanoDrop ND-1000 spectrophotometer . An amount of 1 μg total RNA was reverse transcribed in a 20 μl reaction mixture using the High Capacity RNA-to-cDNA kit ( Applied Biosystems ) following the manufacturer’s instructions . The cDNA was amplified using TaqMan Universal PCR Master Mix ( Applied Biosystems ) and pre-developed TaqMan assay primers and probes ( IFN-α1 , Mm03030145_gH; IFN-β , Mm00439552_s1; Tbet , Mm00450960_m1; GATA3 , Mm00484683_m1; RORc , Mm01261022_m1; Foxp3 , Mm00475162_m1; IDO , Mm004922590_m1 all from Applied Biosystems ) . Data were normalized to GAPDH gene expression . PCR assays were performed on an MxP3000P QPCR System and data were developed using the MxPro qPCR software ( Stratagene ) . Supernatants from cell cultures were separated and stored at −80°C . Lungs and liver from mice uninfected and P . brasiliensis-infected mice were aseptically removed and individually disrupted in 5 mL of PBS . Supernatants were separated from cell debris by centrifugation at 3 , 000×g for 10 min and stored at -80°C . The levels of IFN-α , IFN-β , IL-4 , IL-6 , IL-10 , IL-12 , IL-17 , IL-27 , IL-35 , TNF-α , IFN-γ and TGF-β were measured by capture enzyme-linked immunosorbent assay ( ELISA ) with antibody pairs purchased from eBioscience or PBL . Nitric oxide production was quantified by the accumulation of nitrite in the supernatants from in vitro protocols by a standard Griess reaction [70] . All determinations were performed in duplicate , and results were expressed as micro molar concentration of NO . Plates were read using a spectrophotometric plate reader ( VersaMax , Molecular Devices ) . To monitor IDO enzymatic activity from the ex vivo pDC culture , kynurenines were measured using a modified spectrophotometric assay [71] . The amount of 50 mL of 30% trichloroacetic acid was added to 100 mL of DCs supernatants , vortexed , and centrifuged at 800 g for 5 min . A volume of 75 ml of the supernatant was then added to an equal volume of Ehrlich reagent ( 100 mg P-dimethylbenzaldehyde , 5 ml glacial acetic acid ) in a 96 well microtiter plate . Optical density was measured at 492 nm , using a Multiskan MS ( Labsystems ) microplate reader . A standard curve of defined L-kynurenine concentrations ( 0–100 mM ) was used to determine unknown kynurenine concentrations . Lung leukocytes were obtained from 129Sv , C57BL/6 WT and C57BL/6 IDO-/- uninfected mice as described above and the pDCs were isolated from cells suspensions by two rounds of positive selection , using anti-mPDCA coated magnetic beads ( Miltenyi Biotec ) . The lymphocytes were obtained from splenic cell suspensions of uninfected 129Sv and C57BL/6 WT mice and the cells isolated by positive selection using anti-CD3 coated magnetic beads ( Miltenyi Biotec ) . The pDCs from 129Sv mice were treated with 1MT ( 1mM ) ( Sigma ) and then challenged with P . brasiliensis yeasts at a DC: P . brasiliensis ratio of 10:1 . After 2 h , pDCs were co-cultured with the splenic lymphocytes at a DC:lymphocyte ratio of 1:10 [6] in RPMI media containing or not 1MT . Lymphocyte activation , cell division index ( CDI ) and the expression of FoxP3 were determined after 7 days of DC-lymphocyte co-culture . Lymphocytes were assayed for proliferation using an in vitro fluorescence-based assay . Briefly , 1 × 106 cells from spleens of uninfected C57BL/6 WT mice were stained with 1 μL ( 5 mM ) carboxyfluorescein diacetate succinimidyl ester ( CFSE; Molecular Probes ) in PBS and 5% fetal calf serum for 15 min at room temperature . CFSE-stained cells were cultured for 7 days with P . brasiliensis-infected pDCs as described above . Lymphocytes were then stained with anti-CD4 and anti-CD8 antibodies ( eBiosciences ) and analyzed by flow cytometry as described above . The CDI was calculated as previously described by [72] based on the number of CFSE+CD4+ or CFSE+CD8+ T cells found in the stimulated culture/number of CFSE+CD4+ or CFSE+CD8+ T cells in the unstimulated culture . For comparisons of two groups , means ± standard errors were analyzed by the two-tailed unpaired Student t-test with the Bonferroni correction applied when making multiple comparisons . For comparisons of greater than two groups , significance was determined using the one- or two-way analysis of variance ( ANOVA ) with Tukey’s multiple correction . Differences between survivals were compared by log-rank test Calculations were performed using statistical software ( GraphPad Prism 5 ) . Statistical significance was defined as P<0 . 05 following corrections . | The fungus Paracoccidioides brasiliensis causes paracoccidioidomycosis ( PCM ) , the most relevant deep mycosis in Latin America . The plasmacytoid dendritic cells ( pDCs ) are important immune cells involved in protection against viral infections , but their role in fungal infections remains unclear . Here , we investigated the role of pDCs in the pathogenesis of pulmonary PCM using a monoclonal antibody to deplete this DC subset . pDCs depletion leads to a less severe PCM associated with increased T cell response mainly mediated by Th1 and Th17 cells . The lung homogenates of depleted mice showed diminished levels of type I IFN and anti-inflammatory cytokines . In addition , a reduced number of regulatory T cells ( Treg ) paralleled a diminished number pDCs expressing IDO , a potent immunoregulatory enzyme . In agreement , pDCs of IDO-/- mice or IDO-inhibited pDCs stimulated by P . brasiliensis yeasts expanded elevated numbers of T cells concomitant with a reduced expansion of Treg cells . Taken together , our results demonstrate a tolerogenic activity of pDCs that enhances the severity of a pulmonary mycosis mediated by the concerted action of IDO and Treg cells . These results reveal a new function for pDCs in primary fungal infections and open new perspectives for immunotherapeutic procedures of PCM involving the control of IDO and Treg activity . | [
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"cytotoxic"... | 2016 | Tolerogenic Plasmacytoid Dendritic Cells Control Paracoccidioides brasiliensis Infection by Inducting Regulatory T Cells in an IDO-Dependent Manner |
The Salmonella enterica opvAB operon is a horizontally-acquired locus that undergoes phase variation under Dam methylation control . The OpvA and OpvB proteins form intertwining ribbons in the inner membrane . Synthesis of OpvA and OpvB alters lipopolysaccharide O-antigen chain length and confers resistance to bacteriophages 9NA ( Siphoviridae ) , Det7 ( Myoviridae ) , and P22 ( Podoviridae ) . These phages use the O-antigen as receptor . Because opvAB undergoes phase variation , S . enterica cultures contain subpopulations of opvABOFF and opvABON cells . In the presence of a bacteriophage that uses the O-antigen as receptor , the opvABOFF subpopulation is killed and the opvABON subpopulation is selected . Acquisition of phage resistance by phase variation of O-antigen chain length requires a payoff: opvAB expression reduces Salmonella virulence . However , phase variation permits resuscitation of the opvABOFF subpopulation as soon as phage challenge ceases . Phenotypic heterogeneity generated by opvAB phase variation thus preadapts Salmonella to survive phage challenge with a fitness cost that is transient only .
The study of differentiation in bacterial species that undergo developmental programs has played a historic role in biology [1 , 2 , 3] . In addition , phenotypic differences between colonies [4] and within colonies [5 , 6] were described many years ago in bacterial species that do not undergo development . Despite their technical limitations , these early studies contributed to bring about the idea that phenotypic heterogeneity might be a common phenomenon in the bacterial world [7] . This view has been confirmed by single cell analysis technologies [8 , 9 , 10 , 11 , 12] . Furthermore , theoretical analysis has provided evidence that phenotypic heterogeneity can have adaptive value , especially in hostile or changing environments [13 , 14 , 15] . In certain cases , the adaptive value of subpopulation formation is illustrated by experimental evidence [16 , 17 , 18] . Formation of bacterial lineages is governed by diverse mechanisms , including programmed genetic rearrangement [19] and contraction or expansion of DNA repeats at genome regions [20 , 21] . In other cases , however , lineage formation is controlled by epigenetic mechanisms: certain cell-to-cell differences serve as physiological signals , and signal propagation by a feedback loop generates an inheritable phenotype [12 , 22] . Cell-to-cell differences can be a consequence of environmental inputs or result from the noise intrinsical to many cellular processes [10 , 12 , 15] . In turn , the feedback loops that propagate the initial state beyond can be relatively simple or involve complex mechanisms like the formation of inheritable DNA adenine methylation patterns in the genome [12 , 23 , 24] . Some feedback loops are stable enough to cause bistability , the bifurcation of a bacterial population into two distinct phenotypic states [22] . If a feedback loop is metastable , reversion of the epigenetic state will occur after a certain number of cell divisions . Reversible bistability is usually known as phase variation , and typically involves reversible switching of gene expression from OFF to ON or from low to high expression [25 , 26 , 27] . Examples of phase variation have been described mostly in bacterial pathogens , and subpopulation formation is frequently viewed as a strategy that may facilitate evasion of the immune system during infection of animals [25 , 26] . This view is supported by the observation that phase-variable loci often encode envelope components or proteins involved in modification of the bacterial envelope [25 , 26] . Some phase-variable envelope modifications controlled by DNA adenine methylation play roles in bacteriophage resistance . For instance , phase variation in the gtrABC1 cluster protects S . enterica against the T5-like phage SPC35 , probably by an indirect mechanism [28] . In Haemophilus influenzae , DNA adenine methylation controls phase-variable resistance to bacteriophage HP1c1 but the underlying mechanism remains hypothetical [29] . Phase variation can also contribute to phage resistance without alteration of the bacterial surface . For instance , certain genes encoding restriction-modification systems show phase variation [30 , 31] . In this study , we describe a phase variation system that confers resistance to bacteriophages that use the lipopolysaccharide ( LPS ) O-antigen as receptor . The genome of Salmonella enterica contains a horizontally-acquired locus , known as opvAB or STM2209-STM2208 [32] . The opvA and opvB genes form a bicistronic operon [32] and encode inner membrane proteins [32] . OpvA is a small peptide of 34 amino acids , and OpvB is a larger protein of 221 amino acids with homology to the Wzz superfamily of regulators of LPS O-antigen chain length [32] . We show that expression of the S . enterica opvAB operon confers resistance to bacteriophages P22 ( Podoviridae ) , 9NA ( Siphoviridae ) , and Det7 ( Myoviridae ) by modification of the phage receptor , the LPS O-antigen . Because expression of opvAB is phase-variable , bacteriophage resistance occurs in the subpopulation of opvABON cells only . This subpopulation , which is extremely small , preadapts Salmonella to survive phage challenge albeit at the cost of reduced virulence . However , because the opvABON state is reversible , the virulence payoff is temporary , and a virulent bacterial population resuscitates as soon as phage challenge ceases .
OpvA and OpvB were previously shown to be inner membrane proteins involved in LPS synthesis [32] . Because the LPS is known to have a helical distribution in the cell envelope [33] , the OpvA and OpvB subcellular localization was investigated . For this purpose , a chromosomal opvB::mCherry fusion was constructed downstream of the opvB gene ( so that the strain remains OpvAB+ ) . In a wild type background , expression of opvB::mCherry was low in most cells ( Fig 1A ) . However , rare cells with high levels of expression of opvB::mCherry were detected ( Fig 1A ) , an observation consistent with the occurrence of phase variation skewed towards the OFF state [32] . Expression of opvB::mCherry was also monitored in an opvAB-constitutive ( opvABON ) strain engineered by elimination of GATC sites upstream of the opvAB promoter [32] . In an opvABON background , all cells displayed high levels of fluorescence , similar to those of the rare fluorescent cells visualized in a wild type background ( Fig 1B ) . In fluorescent cells , OpvB was seen forming helical intertwining ribbons in the inner membrane ( Fig 1A and 1B ) . The subcellular distribution of OpvA was examined using a plasmid-borne opvA::mCherry fusion . This experimental choice was based on the consideration that construction of an mCherry fusion in the upstream gene opvA would likely prevent opvB expression because of a polarity effect . In the strain carrying plasmid-borne opvA::mCherry , intense fluorescence was observed in all cells ( Fig 1C ) , presumably because opvA::mCherry overexpression from the multicopy plasmid abolished phase variation . This construction was useful , however , to permit clear-cut observation of helical intertwining ribbons formed by OpvA ( Fig 1D ) . The evidence that OpvA and OpvB may have a similar or identical distribution in the bacterial envelope is consistent with the physical interaction previously described between OpvA and OpvB [32] . Constitutive expression of opvAB leads to the production of a particular form of O-antigen in the S . enterica LPS , with a modal length of 3–8 repeat units [32] . A diagram of LPS structure is presented in S1 Fig , together with an electrophoretic separation of O-antigen chains and a diagram of the differences in LPS structure between opvABOFF and opvABON pubpopulations . To investigate the role of individual OpvA and OpvB proteins in control of O-antigen chain length , non-polar mutations in opvA and opvB were constructed in the wild type and in an opvABON background . In the wild type , lack of either OpvA or OpvB did not alter the electrophoretic profile of LPS ( Fig 2 ) , an observation consistent with two known facts: the subpopulation of cells that express opvAB in wild type Salmonella is very small [32] , and an OpvAB−mutant displays an LPS profile identical to that of the wild type [32] . In contrast , OpvA−opvBON and opvAON OpvB−mutants showed differences with the parental opvABON strain and also with the wild type: These observations suggested that the function of OpvA might be to prevent the formation of normal O-antigen so that OpvB could then impose its preferred modal length . To test this hypothesis , LPS structure was analyzed in an OpvA−opvBON background in the absence of either WzzST or WzzfepE . The results support the view that OpvB needs OpvA to prevent O-antigen formation by customary modal length regulators . In the absence of WzzST , OpvB alone was able to produce an O-antigen similar to that found in the opvABON strain ( Fig 2 ) . In contrast , lack of WzzfepE did not seem to facilitate OpvB function , suggesting that OpvB may mainly compete with WzzST . This preference may be related to the fact that both WzzST and OpvB convey relatively short preferred modal lengths: 3–8 for OpvB [32] and 16–35 for WzzST [36 , 37 , 38] compared with >100 for WzzfepE [34] . The LPS O-antigen is a typical receptor for bacteriophages [39] and modification of the O-antigen can confer bacteriophage resistance [40] . On these grounds , we tested whether opvAB expression increased Salmonella resistance to the virulent phages 9NA [41 , 42] and Det7 [43 , 44] . We also tested the historic phage P22 , using a virulent mutant to avoid lysogeny [45] . Three strains ( wild type , opvABON and ΔopvAB ) were challenged with 9NA , Det7 , and P22 , which belong to different bacteriophage families and use the O-antigen as receptor . The experiments shown in Fig 3 were carried out by inoculating an exponential culture of S . enterica with an aliquot of a phage suspension at a multiplicity of infection ( MOI ) >10 , and monitoring bacterial growth afterwards . The results can be summarized as follows: A tentative interpretation of these observations was that the wild type strain contained a subpopulation of opvABON cells that survived phage challenge . Because opvAB phase variation is skewed towards the OFF state [32] , the small size of the opvABON subpopulation and the regular formation of phage-sensitive opvABOFF cells caused growth retardation ( albeit to different degrees depending on the phage ) . In contrast , the opvABON strain grew normally , an observation consistent with the occurrence of phage resistance in the entire bacterial population . This interpretation was supported by analysis of the LPS profiles of wild type and opvABON strains grown in the presence of P22 , 9NA , and Det7 until stationary phase ( OD600 ~4 ) ( Fig 3 ) . After phage challenge , the wild type contained an LPS different from the LPS found in LB ( Fig 3D ) , and similar or identical to the LPS found in the opvABON strain ( Fig 2; see also [32] ) . In contrast , the LPS from the opvABON strain did not change upon phage challenge ( Fig 3D ) . Confirmation that challenge of the wild type with P22 , 9NA , and Det7 selected opvABON S . enterica cells was obtained by flow cytometry analysis ( Fig 4 ) . Expression of opvAB was monitored using a green fluorescent protein ( gfp ) fusion constructed downstream opvB ( so that the strain remains OpvAB+ ) . In the absence of phage , most S . enterica cells expressed opvAB at low levels; however , a small subpopulation that expressed opvAB at high levels was also detected . Phage challenge yielded mostly S . enterica cells with high levels of opvAB expression . These observations provide additional evidence that phages P22 , 9NA , and Det7 kill the opvABOFF subpopulation , and that opvABON cells overtake the culture . If the above model was correct , we reasoned , cessation of phage challenge should permit resuscitation of a phage-sensitive subpopulation as a consequence of opvAB phase variation . This prediction was tested by isolating single colonies from cultures in LB + phage . After removal of phage by streaking on green plates , individual isolates were cultured in LB and re-challenged with P22 , 9NA , and Det7 ( ≥ 20 isolates for each phage ) . All were phage-sensitive and their LPS profile was identical to that obtained before phage challenge . Representative examples are shown in Fig 5 . Unlike the wild type , individual isolates of the ΔopvAB strain remained phage-resistant after single colony isolation and were considered mutants ( see below ) . Challenge of a ΔopvAB strain with phages P22 , 9NA , and Det7 prevented growth for 5–6 h , and growth resumed afterwards ( Figs 3 and 5 ) . To investigate the cause ( s ) of phage resistance in the absence of OpvAB , individual colonies were isolated from stationary cultures of a ΔopvAB strain in LB + P22 , LB + 9NA , and LB + Det7 . Phage was removed by streaking on green plates . Independent isolates ( each from a different culture ) were then tested for phage resistance . Sixty seven out of 72 independent isolates turned out to be phage-resistant , thus confirming that they were mutants . Analysis of LPS in independent phage-resistant mutants revealed that a large fraction of such mutants displayed visible LPS anomalies ( Fig 6 ) . The few mutant isolates ( 5/67 ) that did not show LPS alterations may have LPS alterations that cannot be detected in gels or carry mutations that confer phage resistance by mechanisms unrelated to the LPS . Whatever the case , these experiments support the conclusion that resistance of S . enterica to phages P22 , 9NA , and Det7 in the absence of OpvAB is mutational . To determine whether isolates resistant to one phage were also resistant to other phages that target the O-antigen , cross-resistance was tested by growth in LB upon phage inoculation . Sixty seven mutants ( 24 P22-resistant , 24 9NA-resistant , and 19 Det7-resistant ) were tested ( S1 Table ) . The main conclusions from these experiments were as follows: Because the LPS plays roles in the interaction between S . enterica and the animal host [34 , 46 , 47] , we tested whether OpvAB-mediated alteration of O-antigen chain length affected Salmonella virulence . For this purpose , competitive indexes ( CI's ) [48] were calculated in the following experiments: ( i ) oral and intraperitoneal inoculation of BALB/c mice; ( ii ) infection of mouse macrophages in vitro; and ( iii ) exposure to guinea pig serum , an assay that provides reductionist assessment of the capacity of the pathogen to survive the bactericidal activity of complement [47] . As controls , CI's were also calculated in LB ( Table 1 ) . In all virulence assays , the CI of the opvABON strain was found to be lower than those of the wild type and the ΔopvAB strain . Because the wild type , the opvABON strain and the ΔopvAB strain show similar or identical growth rates in LB , the conclusion from these experiments was that expression of opvAB reduces Salmonella virulence ( Table 1 ) .
A tradeoff is established whenever the adaptive capacity of an organism is increased at the expense of lowering the fitness conferred by specific phenotypic traits [49] . Tradeoffs have been mainly studied in sexually reproducing organisms but they occur also in microbes [50 , 51 , 52 , 53] . In pathogens , for instance , acquisition of mutational resistance to antimicrobial compounds often affects fitness [54 , 55] , and may require loss of virulence as a payoff [56] . Bacteriophage resistance has been also shown to impair virulence in a variety of bacterial pathogens [57] . In this study , we describe a tradeoff that confers bacteriophage resistance at the expense of reducing virulence in the human pathogen Salmonella enterica . This tradeoff is however unusual because phage resistance is not mutational but epigenetic , and because the phage-resistant , avirulent phenotype is reversible . The opvAB operon is present in most Salmonella serovars ( S2 Table ) . Its products are inner membrane proteins that form intertwining ribbons ( Fig 1 ) reminiscent of those formed by the LPS in the outer membrane [33] . Synthesis of OpvA and OpvB causes a decrease of long O-antigen chains and an increase of short O-antigen chains in the LPS ( Fig 2; see also [32] ) . Genetic evidence presented in Fig 2 suggests that OpvA may prevent the formation of normal O-antigen , allowing OpvB to compete with the WzzST modal length regulator . A similar phenomenon occurs in Pseudomonas aeruginosa , where the Iap transmembrane peptide encoded by bacteriophage D3 disrupts endogenous O-antigen biosynthesis allowing a phage-encoded O-antigen polymerase to produce a different O-antigen [58] . OpvB confers a predominant modal length of 3–8 units , while the wild type LPS shows modal lenghts of 16–35 units and of >100 units ( Fig 2; see also [32] ) . As a consequence of the dramatic change in LPS structure caused by opvAB expression , S . enterica becomes resistant to bacteriophages 9NA , Det7 , and P22 ( Figs 3 and 4 ) , an observation consistent with the fact that the O-antigen is the bacterial surface receptor used by these bacteriophages [39 , 59] . Expression of opvAB undergoes phase variation under the control of DNA adenine methylation and the transcriptional regulator OxyR [32] . Because opvAB phase variation is skewed towards the OFF state [32] , S . enterica populations contain a major subpopulation of opvABOFF ( phage-sensitive ) cells and a minor subpopulation of opvABON ( phage-resistant ) cells . In the presence of a bacteriophage that targets the O-antigen , the opvABOFF subpopulation disappears and the opvABON subpopulation is selected ( Figs 3 and 4 ) . Hence , the existence of a small subpopulation of phage-resistant cells preadapts S . enterica to survive phage challenge . In OpvAB−S . enterica , acquisition of phage resistance is mutational only , and a frequent mechanism is alteration of LPS structure ( Fig 6 ) . Because the LPS plays major roles in bacterial physiology including resistance to environmental injuries and host-pathogen interaction [60] , opvAB phase variation may have selective value by providing S . enterica with a non-mutational , reversible mechanism of phage resistance . This mechanism offers the additional advantage of protecting Salmonella from multiple phages , perhaps from all phages that bind the O-antigen ( note that the phages used in this study belong to three different families: Podoviridae , Siphoviridae , and Myoviridae ) . Acquisition of phage resistance in opvABON cells requires a payoff: reduced virulence in both the mouse model and in vitro virulence assays ( Table 1 ) . In a phage-free environment , this payoff may be irrelevant because the avirulent subpopulation is minor as a consequence of skewed switching of opvAB toward the OFF state: 4 x 10−2 for ON→OFF switching vs 6 x 10−5 for OFF→ON switching [32] . In other words , only 1/1 , 000 S . enterica cells can be expected to be avirulent in a phage-free environment . The virulence payoff is therefore enforced in the presence of phage only , and its adaptive value may be obvious as it permits survival . On the other hand , the fitness cost of OpvAB-mediated phage resistance can be expected to be temporary because phase variation permits resuscitation of the virulent opvABOFF subpopulation as soon as phage challenge ceases ( Fig 5 ) . Resuscitation may actually be rapid as a consequence of skewed switching towards the opvABOFF state . Phase variation systems that contribute to bacteriophage resistance have been described previously . For instance , certain restriction-modification systems show phase-variable expression [31] . However , protection by restriction-modification systems can be expected to be incomplete as only a fraction of infecting phage genomes are modified [61] . Phase variation can also confer phage resistance by preventing infection , and an interesting example is the gtrABC1 cluster which protects S . enterica against the T5-like phage SPC35 [28] . Although the receptor of SPC35 is the BtuB vitamin transporter , GtrABC-mediated glycosylation of the LPS O-antigen may reduce SPC35 adsorption by an indirect mechanism [28] . In Haemophilus influenzae , phase-variable resistance to bacteriophage HP1c1 may involve changes in LPS [29] . Because these studies did not investigate the impact of phase variation on bacterial fitness , it remains unknown whether the tradeoff associated with opvAB phase variation is unusual or commonplace . However , if one considers that envelope structures play multiple roles in bacterial physiology aside from serving as phage receptors , it is tempting to predict that phase-variable bacteriophage resistance may frequently involve fitness costs . Whatever the payoff , however , phase-variable resistance may have a crucial advantage over mutation by creating phenotypic heterogeneity in a reversible manner .
Strains of Salmonella enterica used in this study ( Table 2 ) belong to serovar Typhimurium , and derive from the mouse-virulent strain ATCC 14028 . For simplicity , S . enterica serovar Typhimurium is routinely abbreviated as S . enterica . For the construction of strain SV7643 , a fragment containing the promoterless mCherry gene and the kanamycin resistance cassette was PCR-amplified from pDOC-R , an mCherry-containing derivative of plasmid pDOC [62] using primers HindIII-opvB-mCherry-5 and NdeI-opvB-mCherry-3 . The construct was integrated into the chromosome of S . enterica using the Lambda Red recombination system [63] . For the construction of strains SV5675 , SV6786 , SV6791 , and SV8020 , targeted gene disruption was achieved using plasmid pKD13 [63] and oligonucleotides listed in S3 Table: wzzB5-PS4 + wzzB3-PS1 for wzzST disruption , fepE5-PS4 + fepE3-PS1 for wzzfepE disruption , STM2209-PS4tris + STM2209-PS1 for opvA disruption , and STM2208-PS4 + STM2208-PS1 for opvB disruption . The kanamycin resistance cassettes were then excised by recombination with plasmid pCP20 [63] . For the construction of strain SV6727 , a fragment containing the promoterless green fluorescent protein ( gfp ) gene and the chloramphenicol resistance cassette was PCR-amplified from pZEP07 [64] using primers STM2208stop-GFP-5 and STM2208stop-GFP-3 . The fragment was integrated into the chromosome of S . enterica using the Lambda Red recombination system [63] . An opvB::gfp transcriptional fusion was formed downstream of the opvB stop codon , and the strain remained OpvAB+ . For the construction of strains SV7645 , SV8117 , and SV8118 , plasmid pKD46 was introduced in SV6401 , and the PCR products used for construction of strains SV7643 , SV8020 and SV5675 were integrated into the chromosome of SV6401 using the Lambda Red recombination system [63] . Bertani's lysogeny broth ( LB ) was used as standard liquid medium . Solid LB contained agar at 1 . 5% final concentration . Green plates [65] contained methyl blue ( Sigma-Aldrich , St . Louis , MO ) instead of aniline blue . Antibiotics were used at the concentrations described previously [66] . Bacteriophages 9NA [41 , 42] and Det7 [43] were kindly provided by Sherwood Casjens , University of Utah , Salt Lake City . Bacteriophage P22 H5 is a virulent derivative of bacteriophage P22 that carries a mutation in the c2 gene [45] , and was kindly provided by John R . Roth , University of California , Davis . For simplicity , P22 H5 is abbreviated as P22 throughout the text . A DNA fragment containing opvA and the native opvAB promoter was PCR-amplified using primers KpnI-opvA-plasmidoGFP-5 and KpnI-opvA-plasmidoGFP-3 ( S3 Table ) . The amplification product was cloned into pDOC-R [62] . The resulting plasmid produces an OpvA-mCherry fusion protein . Bacterial cells from 1 . 5 ml of an exponential culture in LB at 37°C ( OD600 ~0 . 15 ) were collected by centrifugation , washed in phosphate saline buffer ( PBS ) , and resuspended in 1 ml of the same buffer . Cells were fixed in 4% formaldehyde solution and incubated at room temperature for 30 minutes . Finally , cells were washed , resuspended in PBS buffer , and stored at 4°C . Images were obtained by using an Olympus IX-70 Delta Vision fluorescence microscope equipped with a 100X UPLS Apo objective . Pictures were taken using a CoolSNAP HQ/ICX285 camera and analyzed using ImageJ software ( Wayne Rasband , Research Services Branch , National Institute of Mental Health , MD , USA ) . Z-stacks ( optical sections separated by 0 . 2 μm ) of mCherry fluorescence were taken with the same microscope . Maximal intensity projections are shown . To investigate LPS profiles , bacterial cultures were grown in LB overnight . Bacterial cells were harvested and washed with 0 . 9% NaCl . The O . D . 600 of the washed bacterial suspension was measured to calculate cell concentration . A bacterial mass containing about 3 x 108 cells was pelleted by centrifugation . Treatments applied to the bacterial pellet , electrophoresis of crude bacterial extracts , and silver staining procedures were performed as described by Buendia-Claveria et al . [67] . Bacterial cultures were grown at 37°C in LB or LB + phage ( P22 , 9NA , or Det7 ) until exponential ( OD600 ~0 . 3 ) or stationary phase ( OD600 ~4 ) . Cells were then diluted in PBS . Data acquisition and analysis were performed using a Cytomics FC500-MPL cytometer ( Beckman Coulter , Brea , CA ) . Data were collected for 100 , 000 events per sample , and analyzed with CXP and FlowJo 8 . 7 software . Overnight cultures were diluted 1:100 in 3 ml LB and grown in aeration by shaking at 37°C until they reached an optical density OD600 ~0 . 3 . One hundred μl of a bacteriophage lysate ( P22 H5 , 9NA , or Det7 ) were added ( M . O . I . ≥10 ) , and OD600 was subsequently measured at 1 h intervals . Eight-week-old female BALB/c mice ( Charles River Laboratories , Santa Perpetua de Mogoda , Spain ) were inoculated with pairwise combinations of the wild type , an opvABON strain , and a ΔopvAB strain at a 1:1 ratio . Bacterial cultures were previously grown overnight at 37°C in LB without shaking . Oral inoculation was performed by feeding the mice with 25 μl of PBS containing 0 . 1% lactose and 108 bacterial colony-forming units ( CFU ) . Intraperitoneal inoculation was performed with 104 CFU in 200 μl of PBS . Bacteria were recovered from the spleen and the liver of infected mice at 2 days post-infection ( intraperitoneal challenge ) or 5 days post-infection ( oral challenge ) . A competitive index ( CI ) was calculated as described elsewhere [48] . To permit strain discrimination , ATCC 14208 was tagged with trg::MudJ ( Kmr ) , an allele that is neutral for virulence [68] . When necessary , cross-streaking on green plates with P22 H5 was used to discriminate phage-resistant isolates [65] . Infection of cultured J774 mouse macrophages , inoculation of guinea pig serum ( Sigma-Aldrich ) , and calculation of competitive indexes in vitro followed previously described protocols [68] . The Student's t test was used to determine whether the CI's were significant . Animal research adhered to the principles mandatory in the European Union , as established in the Legislative Act 86/609 CEE ( November 24 , 1986 ) and followed the specific protocols established by the Royal Decree 1201/2005 of the Government of Spain ( October 10 , 2005 ) . The protocols employed in the study were reviewed by the Comité Ético de Experimentación of the Consejo Superior de Investigaciones Científicas ( CSIC ) , and were approved by the Consejería de Medio Ambiente , Comunidad de Madrid , Spain , on December 12 , 2014 ( permit number PROEX 257/14 ) . | A tradeoff can increase the adaptive capacity of an organism at the expense of lowering the fitness conferred by specific traits . This study describes a tradeoff that confers bacteriophage resistance in Salmonella enterica at the expense of reducing its pathogenic capacity . Phase variation of the opvAB operon creates two subpopulations of bacterial cells , each with a distinct lipopolysaccharide structure . One subpopulation is large and virulent but sensitive to phages that use the lipopolysaccharide O-antigen as receptor , while the other is small and avirulent but phage resistant . In the presence of a phage that targets the O-antigen , only the avirulent subpopulation survives . However , phase variation permits resuscitation of the virulent opvABOFF subpopulation as soon as phage challenge ceases . This transient tradeoff may illustrate the adaptive value of epigenetic mechanisms that generate bacterial subpopulations in a reversible manner . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] | [] | 2015 | Epigenetic Control of Salmonella enterica O-Antigen Chain Length: A Tradeoff between Virulence and Bacteriophage Resistance |
Loss of CD4 T cell help correlates with virus persistence during acute hepatitis C virus ( HCV ) infection , but the underlying mechanism ( s ) remain unknown . We developed a combined proliferation/intracellular cytokine staining assay to monitor expansion of HCV-specific CD4 T cells and helper cytokines expression patterns during acute infections with different outcomes . We demonstrate that acute resolving HCV is characterized by strong Th1/Th17 responses with specific expansion of IL-21-producing CD4 T cells and increased IL-21 levels in plasma . In contrast , viral persistence was associated with lower frequencies of IL-21-producing CD4 T cells , reduced proliferation and increased expression of the inhibitory receptors T cell immunoglobulin and mucin-domain-containing-molecule-3 ( Tim-3 ) , programmed death 1 ( PD-1 ) and cytotoxic T-lymphocyte antigen 4 ( CTLA-4 ) on HCV-specific CD8 T cells . Progression to persistent infection was accompanied by increased plasma levels of the Tim-3 ligand Galectin-9 ( Gal-9 ) and expansion of Gal-9 expressing regulatory T cells ( Tregs ) . In vitro supplementation of Tim-3high HCV-specific CD8 T cells with IL-21 enhanced their proliferation and prevented Gal-9 induced apoptosis . siRNA-mediated knockdown of Gal-9 in Treg cells rescued IL-21 production by HCV-specific CD4 T cells . We propose that failure of CD4 T cell help during acute HCV is partially due to an imbalance between Th17 and Treg cells whereby exhaustion of both CD4 and CD8 T cells through the Tim-3/Gal-9 pathway may be limited by IL-21 producing Th17 cells or enhanced by Gal-9 producing Tregs .
The outcome of acute hepatitis C virus ( HCV ) infection towards spontaneous resolution or persistent viremia is dictated by the magnitude , breadth and quality of the virus-specific CD4 and CD8 T cell responses [1] , [2] . The essential role of CD4 helper T cells in mediating spontaneous viral clearance was demonstrated by several observations . First , the loss of CD4 helper T cell proliferative responses during acute HCV was associated with viral recurrence and the development of chronic infection [3] , [4] . Second , broad HCV-specific CD4 T cell responses are induced early in most acutely infected individuals but they undergo progressive loss of IL-2 production and diminished proliferation as infections progress towards viral persistence [5]–[8] . Third , CD4 T cell depletion in the chimpanzee model of HCV infection led to persistent low level viremia , the loss of CD8 function and the development of escape mutations in targeted CD8 cytotoxic T lymphocyte ( CTL ) epitopes [9] . These observations strongly suggest that CD4 helper T cells are critical in sustaining the functions of HCV-specific CD8 T cells . However , the underlying helper signals and the mechanisms of CD4 T cell failure remain elusive . T cell exhaustion has been proposed as a mechanism underlying the dysfunction of HCV-specific CD4 and CD8 T cells during acute infection . The over-expression of inhibitory receptors like T cell immunoglobulin and mucin-domain-containing-molecule-3 ( Tim-3 ) , programmed death 1 ( PD-1 ) and cytotoxic T-lymphocyte antigen 4 ( CTLA-4 ) and 2B4 was observed on HCV-specific CD8 T cells in the blood and liver of individuals developing chronic HCV infection ( reviewed in [10] ) . Blockade of these inhibitory pathways restored proliferation and cytokine production by HCV-specific CTLs [10] . The differential level of expression of these inhibitory receptors on virus-specific T cells and their respective ligands in certain tissues may contribute to various levels of exhaustion . For example , higher levels of exhaustion and apoptosis are observed in the liver where greater levels of the PD-1 ligand-1 ( PDL-1 ) and the Tim-3 ligand Galectin-9 ( Gal-9 ) are expressed [11]–[16] . Using MHC class II tetramers , Raziorrouh et al . have observed the increased expression of PD-1 and CTLA-4 on virus-specific CD4 T cells from patients with chronic HCV infection [17] . Blocking the PD-1 pathway restored the proliferation of HCV-specific CD4 helper T cells and the production of the Th1 cytokines interferon-gamma ( IFN-γ ) and tumor necrosis factor alpha ( TNF-α ) [17] . Whether this exhausted phenotype affects the production of other helper cytokines and mediators of CD4 T cell help was not investigated . Other possible mechanisms of T cell failure include inhibition of proliferation by Tregs or imbalance between the different CD4 helper T cell subsets ( e . g . Th1 , Th2 , Th17 ) during the progression of HCV infection . Increased Treg frequencies were observed in chronic HCV infection [18] , [19] . Tregs can have a direct inhibitory effect on virus-specific CD4 and CD8 T cells through production of the immuno-modulatory cytokines IL-10 and transforming growth factor beta ( TGF-β ) [17] or through expression of Gal-9 as observed during human immunodeficiency virus ( HIV ) infection [20] . Another subset that has become increasingly important is Th17 cells that produce a variety of cytokines including IL-17A , IL-21 and IL-22 . IL-17A-producing CD4 and CD8 T cells are highly enriched in the liver [21]–[23] and HCV-specific Th17 cells were detected in the peripheral blood during chronic HCV infection [24] . In addition , a temporal association was observed between increased virus-specific IL-17 responses and spontaneous recovery from recurrent hepatitis C in a liver transplant recipient [25] . Th17 cells were also associated with the control of several bacterial and viral infections [26] and are a potential source of IL-21 that has been recently identified as a major helper cytokine during chronic viral infection . Studies in the mouse model of lymphocytic choriomeningitis virus ( LCMV ) have demonstrated that IL-21 is required to sustain proliferation and effector functions of virus-specific CD8 T cells [27]–[29] . Similarly , data from HIV-infected individuals have demonstrated that IL-21 is associated with viral control and slower disease progression [30]–[32] . However , the role of Th17 cells and that of IL-21 as a helper cytokine during acute HCV infection were not studied . In this study , we performed a longitudinal analysis of CD4 helper T cell function and interaction between CD4 and CD8 T cells during acute HCV infection in individuals with spontaneous resolution vs persistent viremia . We specifically focused on IL-21 producing Th17 cells and the means by which Tregs control helper activity of CD4 T cells . We demonstrate a delicate balance between IL-21-producing Th17 cells and Gal-9 producing Tregs . This balance may favor either exhaustion or survival of HCV-specific CD4 and CD8 T cells during acute HCV infection .
The first goal of this study was to longitudinally examine and compare the magnitude and functional profile of HCV-specific CD4 T cells during acute HCV infections with different outcomes . However , the very low frequency of virus-specific CD4 T cells and the limited availability of HCV MHC class II tetramers prevented us from performing direct ex vivo analysis of these cells . Thus , we developed an assay combining carboxyfluorescein succinimidyl ester ( CFSE ) proliferation and intracellular cytokine staining ( ICS ) to determine the cytokine profile of HCV-specific CD4 T cells ( Supplementary Figure S1A ) . This is a qualitative rather than a quantitative assay that provides a general overview of the quality and function of HCV-specific CD4 T cells during different stages of infection . Peripheral blood mononuclear cells ( PBMCs ) were depleted of CD25+ cells before stimulation to limit inhibition of antigen-specific proliferation by Tregs and facilitate detection of HCV-specific T cells activated during the in vitro stimulation . Treg-depleted-PBMCs from HCV patients were labelled with CFSE and stimulated with HCV recombinant proteins in a standard 6 day CFSE proliferation assay as described in Materials and Methods and Supplementary Figure S1A . Virus-specific CD4 T cells were identified by the dilution of CFSE staining coupled with the up-regulation of CD25 , used as an early activation marker . FACS plots from a representative proliferation assay are presented in Supplementary Figure S1B . At the end of the proliferation on day 6 , cells were stimulated with phorbol 12-myristate 13- acetate ( PMA ) and ionomycin in a standard ICS assay to reveal their cytokine profile by gating on proliferating ( CFSElow ) cells . Due to the fact that proliferation and PMA/ionomycin induce down-modulation of CD4 , HCV-specific CD4 T cells were defined by gating on CD3+CD8neg T cells and examining the cytokines produced by CFSElow cells . We monitored the production of the Th1 cytokine: IFN-γ and TNF-α as well as the Th17 cytokines IL-17A and IL-21 . Representative FACS analysis plots for the ICS assay are presented in Supplementary Figure S2 . We used this CFSE/ICS assay to examine the functional profile of HCV-specific CD4 T cells in a cohort of injection drug users ( IDUs ) during acute HCV infection progressing towards either spontaneous resolution ( SR ) or chronic infection ( CI ) . Patients were recruited and followed as described in Materials and Methods . A summary of the patients' characteristics and demographics is presented in Table 1 . Two time- points were tested: i ) early acute phase ( 10 wks±1 wk post estimated date of infection ( PEI ) ) and ii ) late acute phase of infection ( 30 wks±6 wks PEI ) . As previously described [4] , [33]–[35] NS3- and NS4-specific proliferative responses were significantly higher in SR than CI patients during early acute HCV infection ( Supplementary Figure S1C ) . Examining the cytokine profile of HCV-specific CD4 T cells demonstrated specific expansion of Th17 ( IL-17A- and IL-21-producing ) and Th1 ( IFN-γ- and TNF-α- producing ) cells in SR patients as compared to CI patients in response to stimulation with NS3 and NS4 during both early and late acute infection ( Figure 1 ) . To validate the Th17 lineage of the IL-17A- and IL-21-producing CD4 T cells , we monitored the overall expansion of Th17 cells defined as CD161highCCR6+CD26+ [36] , [37] . We observed a specific increase in the frequency of Th17 cells in SR patients ( SR median value = 13 . 25% , pre-infection median value = 6 . 18% ( p<0 . 0001 ) ) , but not in CI patients or patients with long-term chronic HCV ( CI median value = 6 . 315% , chronic HCV median value = 4 . 89% ( p = 0 . 0006 ) ) ( Supplementary Figure S3A ) . We then sorted CD161highCCR6+CD26+ CD4 T cells from the peripheral blood of long-term HCV spontaneous resolvers or chronic patients ( Supplementary Figure S3B ) and the examined the expression of the Th17 lineage-specific transcription factors RORc and c-MAF ( Supplementary Figure S3C ) . RORc was highly expressed in CD161highCCR6+CD26+ CD4 T cells as compared to the CD161neg CD4 T cells thus validating their Th17 lineage . However , c-MAF mRNA was specifically up-regulated in Th17 cells from resolvers ( Supplementary Figure S3C ) . CD161highCCR6+CD26+ CD4 T cells expressed significantly higher levels of IL-17A and IL-21 as compared to CD161neg CD4 T cells upon stimulation with PMA/ionomycin ( data not shown ) . Altogether , these results confirm the specific expansion of IL-17A+IL-21+ Th17 CD4 T cells during acute resolving HCV . This is the first description of HCV-specific Th17 cells during acute HCV infection and suggests that these cells and the cytokines they produce may play an important role in spontaneous clearance of HCV . In order to assess the role of Th17 cytokines during acute HCV infection , we monitored levels of IL-17A and IL-21 in the plasma of acute HCV patients . SR patients ( n = 12 ) were characterized by an early Th17 response ( Figure 2A ) . Plasma levels of IL-17A were significantly higher at the early acute time point ( median value = 23 . 1 pg/ml ) in comparison to healthy donors ( HD ) ( n = 18 , p = 0 . 0001 ) , or to CI patients ( n = 14 , p = 0 . 0055 ) . Plasma IL-17A levels remained elevated in SR patients during the late acute phase of HCV infection ( median value = 23 . 9 pg/ml , n = 8 ) , as compared to healthy donors ( p = 0 . 002 ) and to CI patients ( p = 0 . 0274 , n = 9 ) . IL-21 displayed a different pattern of expression . Plasma levels were comparable in SR ( n = 12 ) and CI patients ( n = 22 ) during the early acute phase but increased significantly during the late acute phase in SR patients ( median value = 212 pg/ml , n = 21 ) as compared to CI patients ( median value = 79 . 1 pg/ml , p = 0 . 0007 , n = 19 ) and healthy donors ( median value = 95 pg/m , p = 0 . 0026 , n = 17 ) ( Figure 2A ) . This is consistent with results in the literature suggesting that IL-21 is more crucial during the memory than the primary phase of antiviral responses [27]–[29] . IL-21 can exert its helper effect through enhancing survival and proliferation of virus specific-CD8 T cells and preventing their exhaustion and/or apoptosis by persistent antigenic stimulation . Hence , we examined if the enhanced production of IL-21 during acute HCV influences the frequency of HCV-specific CD8 T cells . Indeed , we could establish a positive correlation between the plasma levels of IL-21 and the frequency of HCV-specific CD8 T cells detected by a panel of 7 MHC class I tetramers ( n = 28; r = 0 . 49 and p = 0 . 0053 ) ( Figure 2B ) . These results suggest that IL-21 provides some form of help in the maintenance of virus-specific CD8 T cell responses during acute HCV . Several studies have previously demonstrated that HCV-specific CD8 T cells up-regulate the expression of different exhaustion markers including PD-1 , Tim-3 and CTLA-4 during persistent viral replication and progression towards chronic infection . Expression of such markers and their different combinations were associated with different levels of functional impairment in the antiviral properties of HCV-specific CD8 T cells [16] , [38] , [39] . To evaluate the role of IL-21 in modulating T cell exhaustion , we first sought to determine the combined expression profile of the exhaustion markers PD-1 , Tim-3 , CTLA-4 and the memory marker CD127 on virus-specific CD8 T cells directly ex vivo during acute HCV ( n = 9 ) . Based on the levels of Tim-3 expression we were able to define three distinct patterns: Tim-3neg for no exhaustion Tim-3low for partial exhaustion and Tim-3high for a fully exhausted phenotype . Tim-3neg cells were mostly detected in SR patients ( n = 4 ) and were found to be negative for the exhaustion markers PD-1 and CTLA-4 but expressed high levels of the memory marker CD127 , associated with poly-functional T cells [40] . In contrast , Tim-3low and Tim-3high cells were detected in CI patients during acute HCV ( n = 7 ) . Tim-3low cells were PD-1highCTLA-4neg and expressed intermediate levels of CD127 . Tim-3high CD8 T cells were PD-1highCTLA-4high but CD127neg ( Figure 3A ) . These diverse expression patterns suggest different exhaustion statuses based on the increased expression of Tim-3 , PD-1 and CTLA-4 and the reduced expression of CD127 . Indeed , we observed a reduction in the proliferative capacity of HCV-specific cells in response to cognate HCV peptides with increased expression of Tim-3 ( Supplementary Figure S4 ) . Given that the frequency of HCV-specific T cells correlated with plasma levels of IL-21 , we hypothesized that IL-21 may preserve the functions and limit the exhaustion of HCV-specific T cells and enhance their survival . We examined the correlation between the frequency of exhausted T cells ( PD-1+Tim-3+HCV-tetramer+ CD8 T cells ) and the plasma levels of IL-21 . We established a negative correlation between these two parameters ( Figure 3B , p = 0 . 0005 , n = 11 ) . This suggests that the frequency and the functionality of HCV-specific CD8 T cells may be dependent on IL-21 , a T-helper cytokine . Tim-3 has recently emerged as a major determinant of the functional status of HCV-specific T cells [16] , [39] . The inhibitory effect of Tim-3 during the majority of chronic viral infections is dependent on interaction with its main ligand Gal-9 [15] , [20] , [41] , [42] . Consequently , we decided to quantify the levels of Gal-9 in plasma during acute HCV infections with different outcomes . Gal-9 was specifically higher in CI ( n = 13 ) as compared to SR ( n = 11 ) patients during the early and late acute phases of HCV ( p = 0 . 0009 and p = 0 . 0277 , respectively ) or as compared to healthy donors ( n = 10 , p<0 . 0001 ) . Gal-9 was also significantly elevated in the plasma of long-term HCV chronic patients ( n = 8 ) as compared to healthy donors ( p = 0 . 0003 ) ( Figure 3C ) . To further dissect the mechanisms contributing to the loss of the helper T cell response and , consequently , the inhibition of the CD8 T cell antiviral function , we examined the specific emergence of suppressive Tregs during acute HCV infections progressing to chronicity . First , we examined the frequency of peripheral CD4 Tregs using the classical markers CD25high CD127low and FoxP3+ . We observed a higher frequency of Tregs in CI patients during the late acute phase of HCV ( n = 9 ) as compared to pre-infection ( p = 0 . 0077 , n = 12 ) , SR ( p = 0 . 0206 , n = 8 ) and long-term chronic HCV patients ( p = 0 . 0301 , n = 28 ) ( Figure 4A ) . In depth phenotypic characterization demonstrated an increase in the frequency of Tregs co-expressing CTLA-4 and the ecto-enzyme CD39 in CI patients during the late acute phase of HCV infection ( p = 0 . 0491 vs pre-infection; p = 0 . 0104 vs SR and p = 0 . 0019 vs HD ) ( Figure 4B ) . As previously described , this subset of Tregs possesses a high suppressive potential , notably the inhibition of Th17 cells [43] . Thus , we sought to determine if the Treg/Th17 ratio is altered during acute HCV infection as observed during simian immunodeficiency virus ( SIV ) infection [44] . An imbalance in the ratio of CD39+ CTLA-4+ Tregs and of CD161highCCR6+CD26+ CD4 T cells was observed during late acute HCV infection ( Figure 4C , p = 0 . 0006 , n = 8 for SR and CI patients ) . Recent data in HIV patients has demonstrated that Tregs can be a source of Gal-9 production [20] . Given the expansion of CD39+ Tregs and the increase in plasma levels of Gal-9 in CI patients , we hypothesized that this subset may be a source of Gal-9 in CI patients . To test our hypothesis , CD39+ and CD39neg Tregs from chronic HCV patients were sorted by FACS . The quantification of gene expression by real-time PCR demonstrated that CD39+ Tregs ( grey symbols ) expressed higher levels of Gal-9 than CD39neg Tregs ( black symbols ) in chronic HCV patients ( p = 0 . 0007 , n = 10 ) ( Figure 4D ) . Furthermore , we established a positive correlation between the expression of Gal-9 and the mean fluorescence intensity ( MFI ) of FoxP3 ( p = 0 . 004 ) and CTLA-4 ( p<0 . 0001 ) ( Figure 4E ) . In summary , we observed a strong association between expression of CTLA-4 , CD39 and Gal-9 in FoxP3+ Tregs . This was coupled with the expansion of this T cell population during late acute HCV with a chronic evolution and the temporal decrease in HCV-specific Th17 cells in the same patients . These two observations suggest a fine balance between inflammatory and regulatory cells that may influence the outcome of the infection . We have demonstrated that progression to chronic HCV infection is associated with a shift from Th1/Th17 virus-specific CD4 T cells to Gal-9-expressing Tregs . This led to a failure in the maintenance of CD4 T cells which produce a key helper cytokine , IL-21 . This prompted us to investigate if the reduced frequency of IL-21 producing Th17 cells and therefore , the reduced levels of IL-21 in the plasma could be the mechanism restricting CD4 T cell help in acute infections with chronic evolution . IL-21 production could be limited directly through exhaustion of IL-21 producing Th17 cells or indirectly through modulation of Th17 cell function and cytokine producing capacity by inhibitory Tregs . Given that the exhaustion of HCV-specific Th17 cells could not be evaluated directly ex vivo because of a lack of appropriate HCV MHC class II tetramers , we investigated whether IL-17A and/or IL-21 could be restored upon the blockade of several inhibitory pathways in 6 patients during the late acute phase of HCV infection ( 30 wks±6 wks PEI ) . As described above , we used the combined CFSE/ICS assay to monitor the restoration in proliferation and to determine the functional profile of HCV-specific CD4 T cells following stimulation with the HCV NS4 antigen in the presence of isotype control antibodies or of neutralizing antibodies directed against PD-L1 , CTLA-4 and Tim-3 . We used this triad of blocking molecules to optimize the functional restoration of exhausted T cells . At the end of the 6 days CFSE proliferation assay , cells were stimulated with PMA/ionomycin to assess the intracellular production of cytokines . The restoration in cytokine production upon blockade of the inhibitory pathways is depicted in Figure 5A . Blocking the inhibitory pathways slightly enhanced the proliferation of HCV-specific CD4 T cells in response to NS3 and NS4 ( data not shown ) . Nevertheless , this blockade led to a significant increase in the percent of NS4-specific proliferating T cells which produce the Th17 cytokines , IL-17A and IL-21 ( p = 0 . 0078 and p = 0 . 0039 , respectively ) ( Figure 5B ) and the Th1 cytokines , IFN-γ and TNF-α ( p = 0 . 0078 and p = 0 . 0039 , respectively ) ( Figure 5C ) . Similar results were observed upon NS3 stimulation ( data not shown ) . Restoration was also tested in an additional group of 6 patients who had HCV-specific CD4 responses during the early acute phase that became undetectable during the late acute phase . Neutralizing the inhibitory pathways did not restore proliferation or cytokine production by CD4 T cells in this group suggesting that immune restoration is dependent on the maintenance of a minimal frequency of HCV-specific T cells ( data not shown ) . Altogether , these data suggest that HCV-specific Th17 cells are exhausted during acute HCV with chronic evolution and that there is a narrow window of opportunity where exhaustion can be reversed via interference with the implicated inhibitory pathway ( s ) . To confirm the key helper role of IL-21 during acute HCV , we investigated whether exogenous supplementation of IL-21 can rescue the proliferative capacity of exhausted HCV-specific T cells . The addition of IL-21 to a 6 day proliferation assay stimulated with the cognate HCV peptide led to a significant expansion of tetramer-positive cells in all patient samples collected at the early acute time point ( n = 7; p = 0 . 0379 ) . Although IL-21 enhanced proliferation of all HCV-specific CD8 T cells , its effect was more prominent on Tim-3low and Tim-3high cells ( Figure 6A ) . We have demonstrated that HCV-specific CD8 T cells can develop different levels of exhaustion according to the level of expression of Tim-3 . Furthermore , we demonstrated that progression to chronic HCV-infection is associated with lower plasma levels of IL-21 , increased Gal-9 and increased frequencies of Gal-9 expressing Tregs . Gal-9 can induce apoptosis of T cells upon interaction with its ligand Tim-3 [41] and may thus contribute to the inhibition of Tim-3+ HCV-specific CD8 T cells . So , we hypothesized that IL-21 may rescue HCV-specific cells from Gal-9-induced apoptosis . The anti-apoptotic effect of IL-21 was tested during a short-term exposure of HCV-specific T cells expressing different levels of Tim-3 to Gal-9 . PBMCs collected from SR or CI patients during acute HCV ( n = 12 ) were stimulated with Gal-9; the irrelevant ligand Galectin-3 ( Gal-3 ) ( used as a negative control ) or Staurosporin , an inhibitor of protein kinase C ( PKC ) ( used as a positive control ) . Apoptosis was assessed by examining the co-expression of Annexin-V and caspase 3 in total CD8 and HCV-tetramer+ T cells . Representative data of the responses from 5 patients with different patterns of Tim-3 expression ( Tim-3high ( n = 2 ) , Tim-3low ( n = 2 ) and Tim-3neg ( n = 1 ) ) are shown in Figure 6B . Spontaneous apoptosis was higher directly ex vivo in Tim-3high cells as compared to Tim-3low and Tim-3neg cells . Furthermore , the addition of Gal-9 but not Gal-3 triggered apoptosis in 1 . 13 to 77 . 2% ( median value 26 . 6% ) of HCV tetramer+ CD8 T cells from all HCV patients . Cell death was found to be more pronounced in patients with higher levels of T cell exhaustion ( Figure 6B ) . The addition of IL-21 reduced this Tim-3 mediated apoptosis to 3 . 66 to 68 . 4% ( median value 20 . 75% ) ( p = 0 . 0098 ) , which is similar to the non-specific apoptosis induced by Gal-3 ( Figure 6C ) . This data suggest that IL-21 may enhance the survival of HCV-specific CD8 T cells in vivo by down-modulation of the Gal-9/Tim-3-induced apoptosis . We have demonstrated the implication of the Gal-9/Tim-3 pathway in the functional inhibition of both HCV-specific CD4 and CD8 T cells and that IL-21 may reverse this inhibitory effect . In addition , we have demonstrated the expansion of Gal-9-expressing Tregs during acute HCV with chronic evolution . Thus , we hypothesized that Tregs may contribute to inhibiting HCV-specific IL-21 production not only through the production of the classical Treg immuno-modulatory cytokines like TGF-β or IL-10 , but also through the activation of the Gal-9/Tim-3 inhibitory pathway . In order to investigate this hypothesis , we performed a combined CFSE/ICS in the presence of regulatory T cells transfected with siRNA-specific for the Gal-9 gene ( LGALS9 ) or control siRNA ( scramble sequence ) ( Supplementary Figure S5A ) . The efficiency of gene knockdown was evaluated by quantitative RT-PCR ( qRT-PCR ) after transfection with specific or scrambled siRNA ( Supplementary Figure S5B ) . Tregs were added to the cultures at a ratio of 1∶4 ( Tregs∶CD25-depleted PBMCs ) as described by Elahi et al [20] . The addition of Tregs transfected with scrambled siRNA to cultures inhibited the proliferation of HCV-specific T cells in the samples from CI patients collected during the early acute phase . The production of IFN-γ and IL-21 by HCV-specific CD4 T cells ( CD3+CD8neg ) was also reduced by nearly 80% in comparison to cultures without Tregs ( Figure 7A , B ) . In contrast , Tregs transfected with siRNA specific to LGALS9 reduced the Treg-mediated inhibition of HCV-specific CD4 T cells secreting IFN-γ and IL-21 ( p = 0 . 0391 and p = 0 . 0078 respectively ) . The frequencies of HCV-specific IL-17A- and TNF-α- producing CD4 T cells , were not altered by the silencing of Gal-9 . However , the number of virus-specific Th17 cells was too low in these CI patients to establish definitive conclusions . Altogether , these data suggest that the proliferation of HCV-specific T cells secreting IL-21 may be partially controlled by Gal-9+CD39+ Tregs during acute HCV infection in CI patients . The delicate balance in frequencies between this cell subset and IL-21-producing Th17 cells may be one of the determinants of the outcome of acute HCV .
In this study , we demonstrated an important role for IL-21 as a major helper cytokine during acute HCV infection by limiting the T cell dysfunction induced by the Gal-9/Tim-3 interaction . We have demonstrated a direct correlation between higher levels of IL-21 production and cell proliferation , as well as cell survival and the inhibition of exhaustion of HCV-specific CD8 T cells . Moreover , our results have identified three different mechanisms of CD4 helper T cell failure during acute HCV infections with chronic evolution . First , the exhaustion of HCV-specific helper T cells may lead to decreased IL-21 production and failure to sustain efficient CTL responses . Second , an imbalance between inflammatory ( Th17 ) and regulatory ( Treg ) CD4 T cells may have a direct inhibitory effect on HCV-specific CTL responses . Third , we have identified CD39+ Tregs as a potential source of Gal-9 during chronic HCV infection and demonstrated that Gal-9-expressing Tregs can directly inhibit proliferation and IL-21 production by HCV-specific CD4 T cells . These mechanisms combined may limit CD4 T cell help , trigger exhaustion and apoptosis of HCV-specific T cells and favor virus persistence . The helper role of IL-21 during acute HCV can be mediated through direct and indirect effects . IL-21 acts directly to prevent exhaustion [27]–[29] , and to enhance the cytotoxic capacity of virus-specific CTLs through the up-regulation of perforin [45]–[47] and granulysin [48] . Also , it sustains the proliferation and survival of virus-specific memory CTLs [49] and decreases senescence and susceptibility to apoptosis through the modulation of caspase-3 expression [50] . Indirectly , IL-21 production by Th17 cells favors their development by increasing the expression of the IL-23 receptor ( IL-23R ) and thus enhancing the sensitivity to this Th17-polarizing cytokine [51] , [52] . IL-21 also inhibits the differentiation of Tregs by interfering with FoxP3 expression [53]–[55] . Moreover , it can counteract Treg-mediated suppression by inhibiting T cell IL-2 production , which leads to the impairment of Treg homeostasis through IL-2 deprivation [56] . We have observed a specific increase in the frequency of IL-21-producing Th17 cells , identified as CD161highCCR6+CD26+ CD4 T cells , during acute resolving HCV . The limited expansion of this subset seen in acute infections with chronic evolution can be due to its exhaustion status . Indeed , we have demonstrated that blocking the PD-1/Tim-3 and CTLA-4 inhibitory pathways can rescue IL-21 production . Another possibility is the modulation of the inhibitory effect of Tim-3 via human leukocyte antigen B ( HLA-B ) -associated transcript 3 ( Bat3 ) [57] . We have observed lower expressions of Bat3 in Th17 cells from chronically infected HCV patients when compared to SR patients ( data not shown ) . This is similar to features of T cell exhaustion during chronic HIV infection as well as in a mouse model of cancer [57] . IL-21-producing Th17 cells may preferentially home to the liver . Several studies have reported an increase in the frequency of Th17 cells in the livers of patients with chronic liver diseases , including infections with HBV and HCV [23] , [58] , [59] . Furthermore , the expression of CD161 on liver-resident HCV-specific IL-17-producing CD8 T cells ( Tc17 cells ) was found to be tightly linked to the expression of CXCR6 , a liver homing chemokine receptor [60] . Due to ethical constraints that restrict any liver biopsies during acute HCV infection , we examined the homing potential of Th17 cells from SR and CI patients by evaluating the expression of the homing receptors CCR5 , CXCR3 and CXCR6 . However , we did not observe any significant differences between the two groups ( data not shown ) . This result does not exclude the possibility that such liver homing cells were not detected because they are no longer in circulation . Similarly , we could not assess the contribution of other IL-21-producing cellular populations , such as follicular helper T cells which are mainly found in the lymph nodes and NKT cells which are mainly found in the liver . We have observed three levels of expression of the inhibitory receptor Tim-3 on HCV-specific CD8 T cells . The combination of Tim-3 with PD-1 , CTLA-4 and CD127 identified different degrees of functional impairment: un-exhausted ( Tim-3negPD-1negCTLA-4negCD127high ) , partially exhausted ( Tim-3lowPD-1highCTLA-4dimCD127dim ) and fully exhausted ( Tim-3highPD-1highCTLA-4highCD127neg ) HCV-specific CD8 T cells . Such a hierarchical model of exhaustion was proposed to explain the progressive loss of virus-specific CD8 T cell functions in LCMV [61] and HCV infections [10] , [38] , [39] . Although we did not observe any significant differences in the expression of CD160 ( data not shown ) , other inhibitory receptors such as 2B4 , LAG-3 and KLRG1 may also be critical in defining the exhaustion level of HCV-specific T cells [38] , [62] , [63] . Moreover , the level of expression may also be affected by the host's HLA genotype . Recent data have demonstrated that HIV patients carrying the protective HLA alleles ( HLA-B27 and HLA-B57 ) exhibited limited up-regulation of Tim-3 at the surface of HIV-specific CD8 T cells after cognate epitope stimulation [20] . In contrast , patients carrying the less protective alleles ( including HLA-A3 ) exhibited higher up-regulation of Tim-3 and were more susceptible to functional impairment . Interestingly , HLA-B27 has been associated with a higher rate of spontaneous resolution in acute HCV infection [64] , [65] and it is possible that it may play a similar role in limiting T cell exhaustion during acute HCV . Differential up-regulation of inhibitory receptors could be due to variable affinities of the peptide/MHC interactions with the T cell receptors that lead to multiple thresholds of activation . A blockade of the three inhibitory receptors , PD-1 , Tim-3 and CTLA-4 , rescued IL-17A and IL-21 production by HCV-specific CD4 T cells . This suggested that these pathways are implicated in helper T cell failure and exhaustion during acute HCV . In addition , it suggested that the hierarchical model of T cell exhaustion , previously observed in CD8 T cells , is also applicable to CD4 T cells . Indeed , gradual and progressive loss of CD4 helper function was observed in HCV infections progressing to chronicity where the earliest function lost was IL-2 production followed by proliferation then IFN-γ production [7] . In the present study , we could not restore CD4 T cell function in patients with chronic evolution where the response was undetectable during the late acute phase suggesting that there is a minimal threshold of T cell frequency and a window of opportunity for immune restoration to succeed . Interestingly , the blocking of all three pathways on exhausted HCV-specific CD8 T cells restored proliferation , but only Tim-3 blockage restored cytotoxic function [39] . Data from HIV and LCMV infections suggest that the level of expression of each inhibitory receptor could also dictate the efficiency of immune restoration upon its blockade [61] , [66] . Given the difficulty in phenotyping HCV-specific CD4 T cells directly ex vivo , further research is still needed to examine the individual contribution of each inhibitory receptor in defining the level of CD4 T cell exhaustion . It is also noteworthy that higher levels of expression of such inhibitory receptors were observed on HCV-specific CD8 T cells in the liver during chronic HCV infection [11]–[16] and this may limit immune restoration strategies and the immuno-modulatory role of IL-21 . Tregs were expanded during the acute phase of HCV infection in CI patients and may exert a direct inhibitory effect on the function of virus-specific T cells . In addition , we observed a specific expansion of Tregs co-expressing CTLA-4 and CD39 . CD39+ Tregs were also found to be expanded in HIV [67] and chronic HBV infections [68] and were shown to counteract or inhibit the expansion of Th17 cells during remission of patients with multiple sclerosis [69] . Moreover , a polymorphism in the CD39 gene was recently identified and associated with a slow progression to AIDS in HIV-infected patients [70] . Similar genetic susceptibility may explain the differential induction of CD39+ Tregs in HCV-infected patients . Other signals driving cross-regulation between regulatory T cells and IL-21-secreting Th17 CD4 T cells may involve TGF-β [71] , [72] and/or Notch signaling [73] , [74] . In summary , HCV infection may disrupt the balance between Th17 cells and Tregs and , therefore , tamper inflammation while diminishing the effector functions of HCV-specific T cells thus facilitating virus persistence [75] . We have observed the preferential expression of Gal-9 by CD39+ Tregs which contributes to their suppressive capacity [76] , [77] through interaction with Tim-3 on the surface of exhausted T cells as recently seen in HIV infection [20] . It is important to note that there are other sources of Gal-9 in vivo , specifically Kupffer cells in the liver that may contribute to the increase in apoptosis of liver-resident T cells [15] . We demonstrated a direct link between inhibition of HCV-specific T cell function and the expression of Gal-9 by Tregs during acute HCV infection . A delicate balance between IL-21 and Gal-9 can control survival , exhaustion and apoptosis of HCV-specific T cells and could be a major determinant of infectious outcome . We propose a model where HCV-specific CD4 and CD8 T cells are induced early during acute HCV infection but multiple mechanisms could contribute to failure of the immune response during the late acute phase . First , failure to expand IL-21-producing Th17 cells leads to diminished survival and function of HCV-specific CD8 T cells . Second , failure to control viral replication leads to the exhaustion of both virus-specific CD4 and CD8 T cells due to the up-regulation of different inhibitory receptors including PD-1 , Tim-3 and CTLA-4 . T cell exhaustion further aggravates the situation as IL-21 becomes limited , especially in the liver where HCV-specific CD8 T cells become dysfunctional and more susceptible to apoptosis . Finally , to counteract liver inflammation , Tregs are induced and act to further inhibit expansion of Th17 CD4 T cells while producing Gal-9 which can lead to the apoptosis of Tim-3 expressing CD4 and CD8 T cells . Polymorphism in the CD39 gene and the capacity of different HLA alleles to up-regulate inhibitory receptors may be the tipping point in determining the level of exhaustion and the outcome of infection in HCV patients ( Figure 8 ) .
HCV acutely infected subjects were recruited among high-risk HCV-seronegative IDUs participating in the Montreal Hepatitis C Cohort ( HEPCO ) at St . Luc hospital of the Centre Hospitalier de l'Université de Montréal as previously described [40] , [78] . This study was approved by the institutional ethics committee ( SL05 . 014 ) . All participants signed informed consent forms upon enrolment and experiments were performed in accordance with the Declaration of Helsinki . Participants were followed at scheduled 3-month intervals with a maximum duration of 22 weeks between visits . Acute infection was defined as either ( i ) detection of positive HCV RNA in the absence of HCV antibodies , followed by sero-conversion; ( ii ) a positive HCV antibody test following a previous negative test in the presence of positive HCV RNA; or ( iii ) a positive HCV antibody and RNA test within 3 months of a high-risk exposure . All patients tested negative for HIV and HBV . The estimated time of infection at recruitment was defined as the median time ( in weeks ) between the last negative test and first positive HCV RNA or antibody test . Spontaneous viral resolution ( SR , n = 13 ) or chronic infection ( CI , n = 24 ) was defined as the absence or the presence of HCV RNA at 24 weeks post-estimated time of infection ( PEI ) , respectively . Two time points were studied for acutely infected patients: early acute ( 10 wks±1 wk PEI ) and late acute ( 30 weeks±6 weeks PEI ) . Two additional categories of patients were studied: long-term HCV spontaneous resolvers ( R ) ( n = 8 ) , defined as HCV RNA negative and antibody positive at two consecutive tests >60 days apart , and long-term HCV chronically infected patients ( C ) ( n = 27 ) , defined as HCV RNA and antibody positive at recruitment with no prior negative test data . Healthy controls ( n = 18 ) were also studied . The characteristics and demographics of the study participants are summarized in Table 1 . HLA typing was performed as previously described [79] . Qualitative HCV RNA tests were performed using an automated COBAS Ampliprep/COBAS Amplicor HCV test , version 2 . 0 ( sensitivity , 50 IU/ml ) ( Roche Molecular Systems , Inc , Branchburg , NJ ) . HCV genotyping was done using standard sequencing for the NS5B region . Both tests were performed by the Laboratoire de Santé Publique du Québec ( St . -Anne-de-Bellevue , QC , Canada ) as part of the clinical follow- up of patients . The concentrations of IL-17A and IL-21 were determined in plasma samples collected in EDTA and culture supernatants using commercial ELISA kits ( eBioscience , San Diego , CA ) , according to the manufacturer's protocols . The lower detection limits of the kits are 4 and 31 pg/ml , respectively . The concentration of Gal-9 in plasma was determined using a commercial ELISA kit ( Uscn Life Science Inc . , Wuhan , China ) , according to the manufacturer's protocol . The lower detection limit of the kit is 7 . 8 pg/ml . Peptides were synthesized by Sheldon biotechnology Centre , McGill University , ( Montreal , QC , Canada ) . MHC class I tetramers were synthesized by either the National Immune Monitoring Laboratory ( NIML ) ( Montréal , QC , Canada ) or the NIH Tetramer Core Facility ( Emory University , Atlanta , GA ) and are as follows: HLA-A1-restricted HCV NS3 peptide aa 1436 to 1444 ( ATDALMTGY ) ( A1/NS3-1436 ) , HLA-A2-restricted HCV NS3 peptide aa 1073 to 1081 ( CINGVCWTV ) ( A2/NS3-1073 ) , HLA-A2-restricted HCV NS3 peptide aa 1406 to 1415 ( KLVALGINAV ) ( A2/NS3-1406 ) , HLA-A2-restricted HCV NS5b peptide aa 2594 to 1415 ( A2/NS5b-2594 ) , HLA-B7-restricted HCV core peptide aa 41 to 49 ( GPRLGVRAT ) ( B7/core-41 ) , HLA-B8-restricted HCV NS3 peptide aa 1395 to 1403 ( HSKKKCDEL ) ( B8/NS3-1395 ) and HLA-B27-restricted HCV NS5b peptide aa 2841 to 2849 ( ARMILMTHF ) ( B27/NS5b-2841 ) . Directly conjugated antibodies against the following surface molecules were used: CD4- PerCP ( clone SK3 ) , CD8- APC-H7 ( clone SK1 ) , CD25-PE or -PE-Cy7 ( clone M-A251 ) , CD26- FITC ( Clone L272 ) , CD161-PE-Cy5 ( clone DX12 ) , CCR5-FITC ( clone 2D7 ) , CCR6-PE ( clone 11A9 ) and PD-1-FITC ( clone MIH4 ) ( all from BD Biosciences , San Jose , CA ) ; CD39-PE or –PECy7 ( clone eBioA1 ) , CD127-eFluor 450 ( clone eBioRDR5 ) , CD160-Alexa 647 ( clone BY55 ) ( eBioscience ) ; CD3- ECD ( clone UCHT1 ) ( Beckman Coulter , Marseille , France ) ; Tim-3-PE or –PerCP ( clone 344823 ) and CXCR6-PE ( clone 56811 ) ( R&D Systems , Minneapolis , MN ) . The following intracellular antibodies were used: CTLA-4-APC ( clone BNI3 ) , caspase-3-Alexa 647 ( clone C92-065 ) , TNF-α-Alexa 700 ( clone Mab11 ) and IFN-γ-FITC ( clone 25723 ) all from BD Biosciences; IFN-γ-eFluor 450 ( clone 4SB3 ) , IL-17A-Alexa 647 ( clone eBio64DEC17 ) , IL-21-PE ( clone eBio3A3-N2 ) and FoxP3-Alexa 488 ( clone PCH101 ) ( eBioscience ) . Live cells were identified using Aqua Live/Dead Fixable Dead Cell Stain Kit according to the manufacturer's protocol ( Life Technologies , Burlington , ON ) . “Fluorescence minus one” control stains were used to determine background levels of staining . Multiparameter flow cytometry was performed using a standard BD LSR II instrument equipped with blue ( 488 nm ) , red ( 633 nm ) , and violet ( 405 nm ) lasers ( BD Biosciences , ) to systematically perform 11-9 color staining using the FACSDiva software ( Version 5 . 0 . 3 ) ( BD Biosciences ) . Compensation was performed with single fluorochromes and BD CompBeads ( BD Biosciences ) . Biexponential transformation was applied during the analysis of data files using FlowJo software , version 9 . 4 . 11 for Mac ( Tree Star , Inc . , Ashland , OR ) . Tregs were isolated using CD25 Microbeads II ( Miltenyi Biotech , Auburn , CA , USA ) and the purity was assessed by flow cytometry . CD4 T cells were purified by negative selection using a CD4 T Cell Isolation kit II ( Miltenyi Biotech ) , according to the manufacturer's instructions . All sorts were performed using the FACS Aria II Instrument ( BD Biosciences ) employing FACSDiva software ( Version 5 . 0 . 3 ) . For Th17 progenitor cells , purified CD4 T cells were labeled and sorted according to viability and the expression of CD3 , CD4 , CD127 , CD161 , CCR6 and CD26 . CD127low Tregs were excluded from the sort by gating on CD127high CD4 T cells . Two populations were collected: CD127highCD161neg or CD127highCD161highCCR6hiCD26hi CD4 T cells . Sorted cells were stimulated for 48 hours with anti-CD3/anti-CD28 before mRNA extraction and RT-PCR . For the purification of Tregs , CD4 T cells were isolated , labeled and sorted according to viability and the expression of CD3 , CD4 , CD127 , CD25 and CD39 . Three populations were collected: effector T cells ( CD25negCD127hi ) , CD39+ Tregs ( CD127lowCD25highCD39+ ) and CD39neg Tregs ( CD127lowCD25highCD39neg ) . Sorted cells were washed , and immediately lysed to extract mRNA as described below or fixed using a Foxp3 Staining Buffer Set ( eBiosciences ) to perform the intracellular staining of FoxP3 and CTLA-4 , according to the manufacturer's instructions . All flow cytometry assays were performed on cryo-preserved samples . For the phenotype analysis , 2×106 PBMCs were stained with freshly prepared tetramer-PE for 30 minutes at room temperature and washed in fluorescence-activated cell sorting ( FACS ) buffer ( 1× phosphate-buffered saline [PBS] , 1% fetal bovine serum [FBS] , 0 . 02% NaN3 ) . Samples were then stained with surface antibodies for 30 minutes at 4°C , washed twice in FACS buffer , and fixed in FACS Fix buffer ( 1× PBS , 1% formaldehyde ) . Cells were stimulated with PMA/ionomycin ( 50 ng/ml and 1 µg/ml , respectively ) . Following 2 hours of stimulation , 5 µg/ml of brefeldin A and 5 µg/ml of monensin sodium salt were added , and cells were incubated for a total of 16 hours . Cells were washed with FACS buffer , stained for viability and cell surface antigens , fixed and permeabilized using a FoxP3 buffer solution ( eBioscience ) . Then , the cells were stained with anti-IL-17A , anti-IL-21 and anti-IFN-γ antibodies for 30 minutes and washed twice in Perm buffer ( eBioscience ) . For the analysis , cells were gated on viable CD3+ CD8− T cells . CD25-depleted PBMCs were re-suspended in PBS at 20×106 cells/ml and stained with 0 . 5 µM CFSE ( Life Technologies , Burlington , ON , Canada ) for 8 minutes at room temperature . The reaction was stopped with human serum . Cells were washed three times in PBS and then re-suspended at 2×106 cells/ml in warm RPMI ( Life Technologies ) , 10% FCS ( R-10 ) medium . CFSE-labeled cells were stimulated for 6 days with or without 1 µg/ml of the HCV-recombinant proteins NS3 and NS4 ( Feldan , Quebec , QC , Canada ) in the presence of 200 ng/ml of anti-CD28/-CD49d ( Fastimmune , BD bioscience ) at 37°C and 5% CO2 . Recombinant human IL-2 ( 20 IU/ml ) ( NIH AIDS Research and Reference Reagent Program , Germantown , MD ) was added on day 3 . Some assays were performed in the presence of blocking antibodies against PD-L1 ( clone MIH1 , eBioscience ) , CTLA-4 ( Clone BNI3 , BD biosciences ) and Tim-3 ( Clone F38-2E2 , Biolegend ) at 10 µg/ml each or in the presence of IgG1 and IgG2a isotype control antibodies . On day 6 , cells were directly stained with surface antigens as described above or stimulated by PMA/ionomycin to assess cytokine secretion by HCV-specific T cells , identified by CFSElow expression . PBMCs were stimulated with 10 µg/ml of the cognate HCV peptide for 6 days in the presence or absence of IL-21 ( 20 ng/ml ) . HCV-specific cells were identified as HCV tetramer+CD8+ T cells . Fold expansion was calculated by dividing the frequency of HCV tetramer+CD8+ T cells after in vitro expansion by the frequency measured directly ex vivo . PBMCs were incubated for 4 hours with varying concentrations of Gal-9 or Gal-3 ( 1 µM each ) in R-10 . Cells were then stained for surface markers and the specific HCV-tetramers followed by Annexin V staining using Annexin V Apoptosis Detection Kit I ( BD biosciences ) . Cells were fixed and permeabilized with FoxP3 specific buffer ( eBioscience ) followed by intracellular staining with the anti-caspase-3 antibody . Total RNA was extracted using Real-Time Ready Cell Lysis kit ( Roche , Laval , QC , Canada ) according to the manufacturer's instructions . Reverse transcription was performed using Transcriptor Universal cDNA Master ( Roche ) . Real-time PCR amplification was performed using commercial primers ( Qiagen , Toronto , ON , Canada ) for RORc ( Assay ID QT00097888 , Gene bank accession number NM_005060 ) or c-MAF ( QT00023618 , NM_005360 ) ( Applied Biosystems , Foster City , CA , USA ) in combination with the LightCycler 480 SYBR Green I Master ( Roche ) . Transcription factor gene expression was quantified with the Advanced Relative Quantification method provided by the manufacturer and normalized with 28S mRNA expression . Quantitative PCR was performed using a LightCycler 480 detection system ( Roche ) . Total RNA was extracted and reverse transcribed as described above . Real-time PCR amplification was performed using the pre-developed assay-on-demand gene expression set for the Gal-9 gene ( LGALS9 ) ( Assay ID Hs00247135_m1 , Gene bank accession number NM_009587 . 2 , Applied Biosystems , Foster City , CA , USA ) and the Human 18S endogenous control ( HS_99999901 , Gene bank accession number X03205 . 1 , Applied Biosystems ) using the Taqman Universal PCR Master Mix . The quantification of Gal-9 mRNA expression was calculated with the absolute method provided by the manufacturer and expressed in Tregs relative to the expression in CD127hiCD25neg effector T cells . Quantitative PCR was performed using a LightCycler 480 detection system ( Roche ) . For the silencing of LGALS9 , we performed RNA interference experiments on isolated Treg cells according to the manufacturer's protocol by using Silencer siRNA Transfection II Kit ( Ambion , Applied Biosystems ) . Knockdown of LGALS9 in Treg cells was confirmed by qRT-PCR as shown in Supplementary Figure S5 . Control Treg cells received a scrambled siRNA . Cells were allowed to recover in R-10 complete media ( RPMI , 10% FCS ) at 37°C for 5 hours then used in the co-culture assay . The combined CFSE/ICS assays were performed as described above in the presence of Tregs added at a ratio of 1∶4 ( Tregs∶CD25-depleted CFSE labeled PBMCs ) . The percentage inhibition of cytokine production upon addition of Tregs to the stimulated PBMC cultures was calculated using the following formula: ( percentage CFSElow cytokine+CD8neg T cells in absence of Tregs – percentage CFSElow cytokine+CD8neg T cells in presence of Tregs ) /percentage CFSElow cytokine+CD8neg T cells in absence of Tregs×100 . All analyses were performed using GraphPad Prism version 5 . 0 ( GraphPad Software , San Diego , CA , USA ) . The Mann-Whitney U rank sum test was performed to compare the median values between two groups . The Wilcoxon signed rank test was performed to compare the median values between two paired groups . Correlations were determined by the Spearman rank test . P-values<0 . 05 were considered significant . | In this study , we investigated the mechanisms underlying failure of the CD4 helper T cell response during acute hepatitis C infection . We demonstrate that this failure is primarily due to loss of IL-21-producing CD4 T cells in individuals who progress towards chronic infection . This is accompanied by exhaustion of virus-specific cytotoxic CD8 T cells through upregulation of the exhaustion markers Tim-3 , PD-1 and CTLA-4 , higher plasma levels of the Tim-3 ligand Galectin-9 ( Gal-9 ) and increased frequency of Gal-9 producing regulatory T cells ( Tregs ) . In vitro supplementation with IL-21 rescued HCV-specific CD8 T cells from Gal-9 induced apoptosis . Blocking Gal-9 expression in Tregs restored IL-21 production by virus-specific CD4 helper T cells . Altogether , our results suggest that failure of CD4 T cell help during acute HCV may be partially meditated by an imbalance between IL-21-producing CD4 T cells and Treg cells whereby exhaustion of both CD4 and CD8 T cells through the Tim-3/Gal-9 pathway is counteracted by IL-21 . | [
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] | 2013 | Galectin-9 and IL-21 Mediate Cross-regulation between Th17 and Treg Cells during Acute Hepatitis C |
In biological systems that undergo processes such as differentiation , a clear concept of progression exists . We present a novel computational approach , called Sample Progression Discovery ( SPD ) , to discover patterns of biological progression underlying microarray gene expression data . SPD assumes that individual samples of a microarray dataset are related by an unknown biological process ( i . e . , differentiation , development , cell cycle , disease progression ) , and that each sample represents one unknown point along the progression of that process . SPD aims to organize the samples in a manner that reveals the underlying progression and to simultaneously identify subsets of genes that are responsible for that progression . We demonstrate the performance of SPD on a variety of microarray datasets that were generated by sampling a biological process at different points along its progression , without providing SPD any information of the underlying process . When applied to a cell cycle time series microarray dataset , SPD was not provided any prior knowledge of samples' time order or of which genes are cell-cycle regulated , yet SPD recovered the correct time order and identified many genes that have been associated with the cell cycle . When applied to B-cell differentiation data , SPD recovered the correct order of stages of normal B-cell differentiation and the linkage between preB-ALL tumor cells with their cell origin preB . When applied to mouse embryonic stem cell differentiation data , SPD uncovered a landscape of ESC differentiation into various lineages and genes that represent both generic and lineage specific processes . When applied to a prostate cancer microarray dataset , SPD identified gene modules that reflect a progression consistent with disease stages . SPD may be best viewed as a novel tool for synthesizing biological hypotheses because it provides a likely biological progression underlying a microarray dataset and , perhaps more importantly , the candidate genes that regulate that progression .
Biological processes of development , differentiation and aging are increasingly being described by the temporal ordering of highly orchestrated transcriptional programs [1] . When such processes are analyzed with gene expression microarrays at specified time points , a variety of computational methods are available to identify which genes vary and how they vary across part or all the time points [2] , [3] , [4] , [5] , [6] . However , when microarray samples of a biological process are available but their ordering is not known , fewer methods are available to recover the correct ordering , especially when the underlying process contains branchpoints , as occurs in the differentiation from hematopoietic stem cells to myeloid and lymphoid lineages . We present a novel method , referred to as Sample Progression Discovery ( SPD ) , to discover the progression among microarray samples , even if the progression contains branchpoints . In addition , SPD simultaneously identifies genes that define the progression . SPD can be used to generate biological hypotheses about a progressive relationship among samples , and the genes that serve as key candidate regulators of the underlying process . Recovery of an ordering among unordered objects has been studied in a variety of contexts . In computer vision , images taken from random viewpoints and angles were ordered for the purpose of multi-view matching [7] , where the ordering was based on predefined features that are invariant to different viewpoints . In genetics , spanning trees were applied to reconstruct genetic linkage maps [8] , which was an ordering of genetic markers . Using gene expression data of a small set of preselected genes , phylogenetic trees were constructed to study cancer progression among microarray cancer samples [9] , [10] . Microarray samples were also ordered by a traveling salesman path from combinatorial optimization theory , but feature selection was not discussed [11] , [12] . Although these methods proved useful in the recovery of an ordering from unordered objects , their direct applications cannot address the challenges of extracting progression and differentiation hierarchy from microarray gene expression data . Algorithms in [7] , [11] , [12] assume linear ordering of unordered objects , and therefore are not able to reveal potential branchpoints . Furthermore , most existing methods order samples based on carefully designed or preselected features . However , in microarray gene expression data , meaningful gene features are usually not known a priori . One important aspect of SPD is its feature selection ability . Assuming the underlying progression can be reflected by gradual expression changes of subsets of genes , SPD selects genes whose gradual changes support a common progression , and hypothesizes that the common progression is biologically meaningful . The SPD framework , as depicted in Figure 1 , discovers biological progression from gene expression microarray data using four steps: ( 1 ) cluster genes into modules of co-expressed genes , ( 2 ) construct minimum spanning tree ( MST ) for each module , ( 3 ) select modules that supports common MSTs , and ( 4 ) reconstruct an overall MST based on all the genes of all the selected modules . Gene clustering is needed to reduce the number of gene expression patterns to be tested . We introduce an iterative consensus k-means algorithm to derive coherent gene modules , where genes within each module are highly co-expressed . For each gene module , a minimum spanning tree ( MST ) is constructed [13] , where the nodes of the MST are the microarray samples and the edges are weighted by the distance between samples' gene expression profiles . Because a MST connects samples using the minimum number of edges and minimum total edge weights , it tends to connect samples that are more similar to each other . Therefore , we use the MST to describe the progression among the samples , defined by the gradual change of the corresponding gene module . The progression is not necessarily linear , and can contain branching points . SPD then performs feature selection by evaluating the statistical concordance between each gene module and each MST . We define a measure of “progression similarity” between two modules as the number of MSTs that are concordant with both of the two modules . If two modules are concordant with the same MST , these two modules share progression similarity , because their gradual changes support a common progression order among the microarray samples . A noteworthy point here is that modules that are concordant with the same MST are not necessarily correlated with each other; hence SPD is able to identify similarities that may be missed by correlation or regression-based analyses [14] , [15] , [16] . If there exist multiple modules that are concordant with a common set of MSTs , these modules support a common progression , which is likely to be biologically meaningful . SPD selects modules that share progression similarity , and constructs an overall MST based on all the genes within the selected modules . The overall MST and the selected modules serve as the basis for generating hypotheses of the underlying biological process and its regulators . To demonstrate the potential of SPD to reveal biological processes underlying microarray samples , we applied it to a variety of microarray datasets , each of which was associated with a known biological progression . In each case , the known progression was hidden from SPD , and was used to validate the progression discovered by SPD . First , SPD was applied to a time series microarray dataset of the cell cycle . SPD successfully recovered the correct time order of the samples and identified many genes that have been associated with the cell cycle . When applied to B-cell differentiation data , SPD recovered the correct order of different stages of normal B-cell differentiation , and identified the linkage between preB-ALL tumors and their preB cell of origin . SPD was applied to a mouse embryonic stem cell differentiation dataset , where SPD uncovered a landscape of ESC differentiation into various lineages and genes that represent both generic and lineage specific processes . When applied to a prostate cancer microarray dataset , SPD identified gene modules that reflect a progression consistent with disease stages . All of these applications of SPD are presented in the following sections and , collectively , show that SPD may be best viewed as a novel tool for synthesizing biological hypotheses , because it provides a likely biological progression across microarray samples and , perhaps more importantly , the candidate genes that regulate the progression . We implemented SPD using MATLAB graphical user interface . Our software is available at http://icbp . stanford . edu/software/SPD/ .
Microarray time series data of the cell cycle were used to evaluate the performance of SPD . Information on the temporal sample order and cell-cycle regulated genes were not provided to SPD . We hypothesized that SPD would recover the underlying biological progression ( in this case , the cell cycle ) and identify the genes associated with that progression . Five cell cycle time series gene expression datasets in [17] were independently analyzed by SPD . Here we present the SPD analysis on the series with the largest number of samples . SPD analysis of the other time series can be found in Supplement Text S1 . The input of SPD was a gene expression data matrix of 3196 high variance genes across 17 unordered samples from only one cell cycle . The SPD analysis was deliberately limited to samples in one cell cycle to avoid the possibility that SPD would order the samples using the cyclic behavior of cell-cycle regulated genes that can be easily observed across multiple cell cycles . SPD clustered the 3196 high variance genes into 154 modules of co-expressed genes , using an iterative consensus k-means approach ( see Methods ) . One MST was constructed for each module . Each MST represented a possible progression order of the samples based on the expression of its corresponding module . Then , a progression similarity matrix was constructed to quantify the similarity between pairs of modules . The ( ) element of the progression similarity matrix was defined as the number of MSTs concordant with both modules and . ( see Methods ) . The progression similarity matrix is shown in Figure 2 ( a ) , and a magnified portion is shown in Figure 2 ( b ) to highlight nine modules ( 3 , 10 , 17 , 24 , 4 , 30 , 6 , 5 and 20 ) that are regarded as similar in terms of progression . In the last step of SPD , the nine modules with the highest progression similarity were combined to construct an overall MST . The overall MST was visualized using high-dimensional embedding , shown in Figure 2 ( c ) , and revealed a near perfect restoration of the sample order . Interestingly , when we examined the MSTs constructed from each of the nine modules , we did not recover the correct order because we were essentially projecting the progression into a lower dimensional space . To demonstrate the value of the overall MST versus the individual-module MSTs for restoring the sample order , we applied a distance metric called topological overlap measure ( TOM ) [18] to evaluate the distance between the MSTs and the true sample order . Table 1 shows that the overall MST based on combining the nine modules ( the first row ) produced a more accurate sample order than the MSTs derived from the individual modules . Next , we compared SPD to the commonly used hierarchical clustering analysis of the dataset described above . After all , a MST can be regarded as a hierarchical clustering tree with single linkage [19] . The main difference between hierarchical clustering and the SPD framework is that SPD selects gene modules that share progression similarity , and reconstructs an overall MST based on the selected modules . To illustrate the significance of SPD's feature selection ability , we performed single linkage hierarchical clustering based on all the 3196 genes , which is equivalent to constructing a MST based on all these genes . The resulting dendrogram did not recover the correct sample order , as shown in Figure 2 ( d ) . Moreover , the TOM distance between the hierarchical clustering tree and the true sample order was much larger than that from SPD , as shown in Table 1 ( last row ) . This analysis demonstrates the importance of SPD's feature selection ability . To evaluate the robustness of SPD , we performed bootstrap analysis on the cell cycle microarray dataset . In each of the 100 bootstrap iterations , 90% of the 3196 genes were randomly selected . SPD was applied to each bootstrapped dataset separately . In each bootstrapped dataset , the clustering step might generate different gene modules that lead to different progression-related modules and a different overall MST . However , the overall MSTs were consistent across the bootstrapped datasets . The TOM distance was used to evaluate the distance between the 100 SPD results and the true sample order . The mean TOM distance was . The standard deviation of the TOM distance appeared to be comparable to the mean due to the statistical properties of TOM . To evaluate the statistical significance of this result , we performed random permutation analysis . We generated 1000 random MSTs , and computed the TOM distance between random MSTs and the true sample order . The mean of the random TOM distance was , which is substantially larger than the TOM distances obtained in the bootstrap analysis , indicating the robustness of SPD . In addition , we examined the diameters of the random MSTs , where the diameter is defined as the number of edges in the shortest path between the most distantly separated pair of nodes . The mean diameter of a random 17-node MST was . The diameter of the SPD result in Figure 2 ( c ) was 15 . The probability of obtaining such a large diameter by chance was low , which implied that the SPD result was statistically significant . The mean expression profiles of the nine modules are shown in Figure 2 ( e ) . Some of these modules are uncorrelated ( i . e . , modules 10 and 30 have a correlation coefficient of −0 . 06 ) , but SPD identified them as similar in terms of progression . Figure 2 ( f ) shows the mean expression profiles of the nine modules across all three cell cycles that were provided in the original dataset . Here , we can observe that some of the identified modules are cyclic . Gene sets in the Molecular Signatures Database ( MSigDB ) [20] were used to annotate the identified gene modules ( see Supplement Text S1 ) . As expected , these modules included many genes that have been associated previously with the cell cycle . For example , module 10 was highly enriched ( , hypergeometric test for gene set enrichment ) for genes that are targets of the E2F cell cycle transcription factor family . A likely explanation for the presence of the acyclic modules is that they represent the experimental perturbation that initially synchronized the cells . In the cell cycle microarray experiments , the measured population of cells were first synchronized , and then released . This initializing synchronization condition is a cellular perturbation that may take several cell cycles to decay away . We applied SPD to a B-cell differentiation dataset [21] , in which 9365 genes were measured for 44 samples across 5 normal differentiation stages and 1 malignant stage: 7 hematopoietic stem cells ( HSC ) , 7 common lymphoid progenitors ( CLP ) , 7 proB cells , 7 preB cells , 7 Immature B cells ( IM ) , 5 more terminally differentiated B cells ( 1 naive B cell , 1 centroblast CB , 1 centrocyte CC , 1 memory B cell , 1 CD19+ cell ) , and 4 preB-ALL cancer samples . Without providing SPD any information on the known differentiation stages of the sample , we tested whether SPD could recover the progression underlying this dataset , which is known to be: HSC , CLP , proB , preB , IM , naiveB/CB/CC/memoryB/CD19+ . Another objective was to determine whether the preB-ALL would be grouped near its preB cell origin . SPD selected ten gene modules ( composed of 2388 genes in total ) which supported a common progression . Based on these modules , an overall MST was constructed to describe the underlying progression . After obtaining the overall MST , samples were color-coded according to their known classifications , as shown in Figure 3 ( a ) . The identified progression was consistent with the known stages of normal B-cell differentiation , except for a missing link between immature B cells and the next more differentiated B cells ( naiveB/CB/CC/memoryB/CD19+ ) . The link between preB-ALL cancer samples and their cell origin ( normal preB cells ) was identified . The link between immature B cells and more differentiated B cells was missing , partly because MSTs do not allow for cycles . We hypothesized that if we removed the cancer samples and the outliers that are grouped next to the cancer samples , the missing link would be restored . To test this , we removed the cancer samples and the outliers , and performed SPD analysis again . The resulting MST was consistent with the stages of normal B-cell differentiation , as shown in Figure 3 ( b ) . Annotations of the selected modules can be found in Supplement Text S1 . Some modules contained genes that relate to B-cell differentiation but are generic in their function . Examples include proliferation genes ( , hypergeometric test ) , which are highly expressed in germinal center B-cells that are undergoing rapid expansion , but down-regulated at other stages . SPD also recovered modules of genes that are specific to B-cell differentiation . These were enriched in genes that are known markers of , or mechanistically related to , B-cell differentiation such as CD19 , CD20 , CD79 ( B-cell receptor ) , and the master transcription factors PAX5 and SP140 . We also observed enrichment ( ) for genes in the B-cell receptor ( BCR ) pathway , which is the key signaling pathway governing the maturation of B cells . The two examples in the previous subsections show that SPD is able to recover non-branching progression patterns . In this subsection , we demonstrate SPD's ability to recover branched progression patterns , using an embryonic stem cell differentiation dataset . Pluripotent embryonic stem cells ( ESCs ) are capable of differentiating into all cellular lineages in the development of a mature organism . We applied SPD to a dataset of 44 samples of mouse ESCs and their progeny which had been induced to differentiate into several lineages by specific interventions , as well as several differentiated cell types . The interventions included knockdown of Pou5f1/Oct4 ( leading to differentiation to trophoblasts ) , induction of GATA6 ( differentiation to endoderm lineage ) , treatment with N2B27 medium ( differentiation to neural lineages ) , and all-trans retinoic acid ( RA ) induction of embryonic carcinoma cells to cause differentiation [22] . The data included time series along each lineage of cells . When SPD was applied to this dataset , information on the interventions and the temporal order of the samples were hidden from the algorithm . SPD identified 35 modules that supported a common progression , which revealed a landscape of ESC differentiation into the various lineages . Remarkably , samples were perfectly ordered in time , with progressively later stages of differentiating cells radiating outwards from a core cluster of ESC samples , as shown in Figure 4 . A subset of induced pluripotent ( iPS ) cells clustered as a group , in close proximity to ESC samples . Trophoblast stem cells grouped with the trophoblast differentiation lineage , while stromal and fibroblast cell lines were correctly clustered with mature fibroblasts . The identified modules provided a fine-scale view of expression changes along each lineage . The identified modules included ones which changed in a similar fashion during differentiation of all cell types from ESCs , as well as ones that were uniquely associated with specific lineages . We annotated modules by comparison to known gene sets , and by examining the relationship between their constituent genes using Ingenuity Pathways Analysis ( IPA ) . Annotation results are available in Supplement Text S1 . Module 228 was progressively induced in all differentiating lineages , as shown in Figure 4 , and was enriched for genes that are targets of Suz12 and Ezh1 . The latter are members of the Polycomb complex that functions in maintaining self-renewal in ESCs . Thus induction of this module is consistent with a general loss of self-renewal potential in specialized cell types . Similarly , modules 54 and 55 ( enriched for Myc targets and genes involved in Oct4 maintenance of pluripotency ) were both down-regulated in each differentiating branch , but at differing rates with respect to each other , with the strongest muting of expression occurring along the trophoblast lineage . One module ( 329 ) was highly enriched for genes that share a common pattern of histone H3K27 methylation , and that are targets of the Ezh2/Polycomb complex . Notably these genes were progressively down-regulated in all branches except the neural lineage . This suggests particular subsets of Polycomb targets that are regulated in a tissue-specific manner . In the opposite direction , module 65 genes were strongly induced in trophoblast differentiation , and more modestly in the other branches . This module contained numerous genes that are induced by shRNA knockdown of the pluripotency factor Sox2 , as well as apoptosis-related genes . Intriguingly , this module included many genes involved in integrin signaling and endocytosis signaling . Thus its strong induction in differentiating trophoblasts ( which are involved in placental implantation of the embryo ) is consistent with their critical invasive properties , and the SPD result identifies genes that may be implicated in this phenotype . Two modules ( 3 and 123 ) were highly specifically regulated along the trophoblast differentiation branch . IPA analysis of module 3 indicated that this cluster of genes was highly enriched with targets of tumor necrosis factor ( TNF ) . This is concordant with the fact that over-expression of TNFa induces differentiation of ESC to trophoblasts . In the dataset analyzed with SPD , trophoblast differentiation was induced by down-regulation of Oct4 . The overlap with TNF targets suggests that these two mechanisms of induction share commonalities in the gene expression changes involved in generation of trophoblasts from ESC . Given the master-regulatory role of Oct4 in maintaining pluripotency , one hypothesis is that induction of TNF effects downstream changes in the Oct4 network , while at the same time producing changes in transcription that lead specifically to production of trophoblasts . Module 123 was annotated as associated with cell motility genes . Again , this is consistent with the invasive character of trophoblasts , and suggests genes that are involved in mediating this behavior . In summary , SPD perfectly recapitulates the lineages leading to differentiated cell types generated by targeted manipulations of ESCs . The differentiation landscape identified by SPD shows underlying progressive changes in gene expression that represent both generic processes as well as ones specific to particular lineages . The genes that constitute the modules supporting the differentiation tree represent targets for further investigation as to their role in organism development . We applied SPD to a prostate cancer microarray dataset [23] . This dataset contains a total of 163 patient samples , including tissue of normal prostate from organ donors , normal prostate tissue adjacent to the prostate tumor ( NAP ) , primary prostate tumor samples , and metastatic samples . When SPD was applied to this dataset , the clinical information on the samples were hidden from the algorithm . In this dataset , the average correlation between genes was small , consequently , SPD generated modules that contained a small number of genes . We excluded modules that contained less than 5 genes , leaving 46 coherent modules for subsequent analysis . SPD selected 12 modules ( 487 genes in total ) with high progression similarity and derived the tree structure shown in Figure 5 ( a ) . Normal and metastatic samples were enriched at the left and right ends of the tree . SPD produced a mixture of NAP and tumor samples in the middle of the tree . A larger fraction of NAP samples were closer to normal samples , and tumor samples were closer to the metastatic samples . The mix of NAP and tumor samples reflects possible field effect [23] , which suggested that normal tissue adjacent to primary tumor is more similar to the primary tumor than it is to normal tissues . The general trend in Figure 5 ( a ) reflected a progression consistent with disease stages . In addition , we observed details that we did not expect: a few normal samples were mixed with tumor samples; and the metastatic samples appeared to form two branches . To interpret the tree , we color-coded the nodes using the average gene expression of each of the 12 modules , and observed three expression patterns . Representative modules of the three patterns are shown in Figure 5 ( b ) , ( c ) and ( d ) . Color-codes of other modules are available in Supplement Text S1 . Module 2 and three other modules are gradually down-regulated from normal to tumor and metastatic samples , whereas module 32 and two other modules are gradually up-regulated . Interestingly , we observed that the expression of module 19 and four other modules first increase from normal to tumor and then gradually decrease in metastatic samples . Several modules show clear difference between the two branches in the upper right corner , i . e . Figures 5 ( c ) , ( d ) and several modules shown in Supplement Text S1 . The expressions of these modules indicate that the metastatic samples can be further divided into two subtypes . We used Gene Set Enrichment Analysis to annotate the modules that are up-regulated in primary tumor while down-regulated in both normal and metastatic samples . We noticed that these modules overlapped with genes involved in metastasis in several epithelial cancers ( not just prostate studies ) . They may reflect general processes underlying the epithelial-mesenchymal transition and cell migration . Of note , one of the genes in this module is CDH3 , a member of the cadherin family that interacts with CDH1 . Targeted down-regulation of cadherins by RNA interference has been demonstrated to induce cell migration . However , up-regulation from normal to primary tumors followed by down-regulation in metastases has not been commented upon previously . We also applied IPA to the genes that comprised these modules . The most significant interaction network centered around genes involved in androgen and estrogen signaling , and influenced by beta-estradiol . Although estradiol is the predominant sex hormone in females , it is also produced in males as a metabolic product of testosterone . Androgen signaling generally has a pro-survival effect in prostate cancers . Thus one possible interpretation of the SPD result is that it reflects the fact that in primary tumors , androgen signaling up-regulation confers a selective advantage in the natural history of the tumor; but that some metastases develop androgen-independence . A priori , from gene expression profiles , it is unknown which metastases are androgen-independent; hence SPD may be identifying both androgen-independent samples , together with the genes whose changes in expression drive the phenomenon .
SPD is a new approach to infer progression among microarray samples and identify genes that drive the progression . SPD represents a new class of machine learning algorithms that has not been extensively applied to microarray analysis . The more common machine learning algorithms that have been used to analyze microarray data include unsupervised clustering [19] , [24] , supervised classification [25] , [26] , [27] , [28] , and statistical tests for differential expression [20] , [29] . Although these algorithms are quite different from each other , they share a similar goal , which is to identify differences between different sample groups , i . e . normal vs . cancer . When applied to study a progressive biological process , these methods essentially bin the process into stages and identify differences between sample groups from consecutive stages of the progression . SPD differs significantly in this regard . Instead of assuming that samples in the same group are similar and focusing on the differences between groups , SPD treats individual samples as different points along an unknown biological progression , thus has the potential to discover how samples progress both within and across groups . As mentioned earlier , recovery of an ordering from unordered samples has been studied in several fields , computer vision , [7] , genetic linkage analysis [8] , [9] , [10] , microarray time series [11] , [12] . However , due to lack of ways to automatically select meaningful features , the direct application of these approaches cannot address the challenges of extracting unknown progression from microarray data . In contrast , SPD is unique in its ability to simultaneously identify both the progression relationship among samples and the genes that are associated with the progression , without prior knowledge or manual gene selection . SPD shares some similarities with bi-clustering , since both methods attempt to simultaneously organize genes and samples . However , the results of SPD and bi-clustering are quite different from each other . Bi-clustering organizes genes into clusters , and each gene cluster stratifies samples in a potentially different way . In contrast , SPD has a module selection step which selects the gene modules that are similar in terms of progression . The selected modules support a common progression pattern among the samples , defined by a single overall MST which is constructed based on all the genes in the selected modules . In SPD , we propose a new similarity measure , namely the progression similarity . This measure evaluates the similarity between gene modules based on whether they are concordant with common progression patterns represented by MSTs . In contrast to correlation and regression-based methods [14] , [15] , [16] where the expression profiles of gene modules are directly compared with each other , SPD evaluates progression similarities between gene modules via MSTs . We have shown that modules that are similar in SPD do not necessarily correlate with each other; this demonstrates that SPD is able to identify similarities that correlation and regression-based analyses may miss . As demonstrated in the analysis of the cell cycle time series and B-cell differentiation microarray data , SPD is able to discover the biological progression underlying a microarray dataset , while simultaneously selecting the genes that are known to be central to this progression . When applied to these datasets , SPD was not provided the information on the known ordering of the samples , and instead derived the ordering in an unsupervised fashion . Because the SPD-derived ordering is consistent with the time order of the samples , time represents the strongest progression signal , and the gradual shifts of the identified gene modules are associated with the time series experiment . Enrichment of transcription factors or pathways in the identified modules may be hypothesized as key drivers of the progression , and subject to further experimental validation . If the SPD-derived ordering were different from the time order , the strongest progression signal would be some factor other than time , which hints at other sources of variations present in the time series data . We view SPD as a hypothesis synthesis tool that may have greatest utility when applied to a microarray dataset where the underlying biological progression is unknown . For example , when applied to cancer samples , SPD assumes that there is an intrinsic progression underlying cancer development , and that the cancer samples collected from individual patients represent different stages in this progression . The inferred progression relationship among the cancer samples may therefore indicate a trajectory or hierarchy of cancer progression . Under this assumption , SPD extracts the progression among cancer samples and gene modules whose gradual shifts are associated with the progression , as demonstrated on human prostate cancer samples . The identified progression and gene modules form hypotheses to be validated . SPD is not limited to microarray data analysis and can be applied to a variety of high-dimensional datasets , including genomic , proteomic and image-based data .
Gene clustering reduces data dimension and noise . It is well known that gene clustering is a difficult optimization problem with many local minimums , and most clustering algorithms lack consistency and reproducibility across multiple runs [30] . We propose an iterative consensus k-means algorithm to derive consistent coherent gene modules . Our algorithm is an iterative divisive hierarchical clustering procedure . In every iteration , each gene module from the previous iteration is divided into two modules , until our stopping criterion is met . Details of the algorithm are as follows . Given an by gene expression data matrix , we perform the k-means algorithm times , with random initialization , to cluster the genes into k = 2 clusters . Clustering results are arranged into an by matrix , where the element is the cluster assignment of gene in the 'th run of k-means . In order to draw the consensus of the runs of k-means , we apply k-means again based on the by matrix , the collection of clustering results of the runs , to divide genes into two clusters . For each of the two clusters , the coherence is computed as the average Pearson correlation between each gene in the cluster and the cluster mean . If the coherence of a cluster is higher than a pre-specified threshold , this cluster is considered to be a coherent gene module . Otherwise , this cluster is further partitioned by iterating the algorithm . After the iterative process ends , we examine the resulting coherent modules pairwisely . If the Pearson correlation of two modules' centers is higher than a pre-specified threshold , these two modules are merged . This step iterates until no module-pair shares correlation higher than . The stopping criterion of cluster coherence guarantees that all resulting modules satisfy the pre-specified coherence threshold . Modules that share correlation higher than are merged , so that the resulting gene modules are not highly correlated with each other . We typically set the algorithm parameters to the following values: , , The purpose of our consensus k-means algorithm is to derive coherent modules that are not highly correlated with each other . Other clustering algorithms that achieve qualitatively similar performance can be adopted as the clustering component of SPD . When dealing with microarray gene expression data , without any prior knowledge of gene modules and the underlying progression , we find it helpful to cluster co-expressed genes into modules for the purpose of dimension reduction . On the other hand , if we have prior knowledge of predefined gene sets that describe pathways whose progression similarities are of interest , we can use these genes sets to supplement or replace the clustering results . SPD constructs minimum spanning trees ( MSTs ) based on expression data of subsets of genes , i . e . gene modules . A MST is an acyclic graph that connects all the samples using minimum total edge weights . The weight on the edge that connects samples and is defined as the Euclidean distance between the gene expression of samples and . We use Boruvka's algorithm [31] to construct one MST based on each gene module . Briefly , we begin with a disjoint graph with no edges , where each sample is one disjoint component , and then iteratively add edges . In each iteration , we randomly pick one of the smallest components , calculate its single linkage Euclidean distances to all other components , and add an edge that corresponds to the smallest single linkage distance . This process iterates until all samples are connected . Since the MST connects all the nodes using minimum total edge weights , it tends to connect samples that are more similar to each other . If we start from one sample and move along the edges of the MST , we will observe a gradual change of gene expression . Therefore , the MST reflects the progression among samples , defined by the gradual change of the set of genes based on which the MST is constructed . The key step of SPD is the comparison between the expression of gene modules and trees constructed from other modules . Given the expression data of a gene module in samples , we define an by distance matrix , where is the Euclidean distance between the gene expression profiles of samples and . Similarly , a tree structure can also be summarized in a matrix form , which is the adjacency matrix , where if samples and are directly connected in the tree; otherwise . In SPD , we define the concordance between a gene module and a tree as the concordance between the distance matrix and the adjacency matrix . Typically , the statistical concordance between and includes two aspects: ( 1 ) the distance between connected samples should be small , and ( 2 ) the distance between not-connected samples should be relatively larger [32] . In our analysis , we only focus on the former aspect . Our rationale is that we want to model progressions where the gene expression first drifts away from an initial state and then comes back . One such example is the cell cycle . We define the statistical concordance between a distance matrix and an adjacency matrix as ( 1 ) The meaning of is the total edge weights jointly defined by the gene module and the tree . If is small , the gene module and tree structure are concordant . Large implies that the gene module and tree are not concordant . In order to derive the -value of , we perform random permutations . We randomly permute the columns of the expression data , which is equivalent to reshuffling the rows and columns of the distance matrix . The -value is the probability of obtaining a smaller during random permutations . We typically perform 1000 permutations and use a -value threshold of 0 . 002 to determine whether a module and a tree are sufficiently concordant . Using Equation ( 1 ) , we evaluate the statistical concordance between all the gene modules and all the MSTs . Since each MST is constructed based on one gene module , a MST and its corresponding module are concordant by construction . If a module is concordant with the MST derived from another module , these two modules are similar in the sense that they support a common progression pattern . Based on the statistical concordance between all the modules and all the MSTs , a progression similarity matrix is derived . The element of the progression similarity matrix is the number of trees that are concordant with both modules and . For visualization , we re-order the modules by hierarchical clustering of the columns of the progression similarity matrix [14] , so that we can clearly identify similar modules along the diagonal , via visual inspection . We explored several algorithms to automatically identify similar modules from the progression similarity matrix , including hierarchical clustering with gap statistics , spectral partitioning , and forward and backward selection . However , there was not a single algorithm and parameter setting that performed well for all the datasets we analyzed . Since the number of modules in the progression similarity matrix is usually small , we decided to perform module selection manually . An automated algorithm for this step will introduce an additional parameter which is not as intuitive as manual selection . In the progression similarity matrix , if there is a diagonal block whose entries all have relatively high values , i . e . Figure 2 ( a ) and ( b ) , the corresponding modules are similar because they describe a common progression . SPD selects these similar modules , and constructs an overall MST that describes the common progression supported by the selected modules , which is likely to be biologically meaningful . | We present a novel computational approach , Sample Progression Discovery ( SPD ) , to discover biological progression underlying a microarray dataset . In contrast to the majority of microarray data analysis methods which identify differences between sample groups ( normal vs . cancer , treated vs . control ) , SPD aims to identify an underlying progression among individual samples , both within and across sample groups . We validated SPD's ability to discover biological progression using datasets of cell cycle , B-cell differentiation , and mouse embryonic stem cell differentiation . We view SPD as a hypothesis generation tool when applied to datasets where the progression is unclear . For example , when applied to a microarray dataset of cancer samples , SPD assumes that the cancer samples collected from individual patients represent different stages during an intrinsic progression underlying cancer development . The inferred relationship among the samples may therefore indicate a trajectory or hierarchy of cancer progression , which serves as a hypothesis to be tested . SPD is not limited to microarray data analysis , and can be applied to a variety of high-dimensional datasets . We implemented SPD using MATLAB graphical user interface , which is available at http://icbp . stanford . edu/software/SPD/ . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] | [
"computational",
"biology"
] | 2011 | Discovering Biological Progression Underlying Microarray Samples |
Group A human rotaviruses ( RVs ) are a major cause of severe gastroenteritis in infants and young children . Yet , aside from the genes encoding serotype antigens ( VP7; G-type and VP4; P-type ) , little is known about the genetic make-up of emerging and endemic human RV strains . To gain insight into the diversity and evolution of RVs circulating at a single location over a period of time , we sequenced the eleven-segmented , double-stranded RNA genomes of fifty-one G3P[8] strains collected from 1974 to 1991 at Children's Hospital National Medical Center , Washington , D . C . During this period , G1P[8] strains typically dominated , comprising on average 56% of RV infections each year in hospitalized children . A notable exception was in the 1976 and 1991 winter seasons when the incidence of G1P[8] infections decreased dramatically , a trend that correlated with a significant increase in G3P[8] infections . Our sequence analysis indicates that the 1976 season was characterized by the presence of several genetically distinct , co-circulating clades of G3P[8] viruses , which contained minor but significant differences in their encoded proteins . These 1976 lineages did not readily exchange gene segments with each other , but instead remained stable over the course of the season . In contrast , the 1991 season contained a single major clade , whose genome constellation was similar to one of the 1976 clades . The 1991 clade may have gained a fitness advantage after reassorting with as of yet unidentified RV strain ( s ) . This study reveals for the first time that genetically distinct RV clades of the same G/P-type can co-circulate and cause disease . The findings from this study also suggest that , although gene segment exchange occurs , most reassortant strains are replaced over time by lineages with preferred genome constellations . Elucidation of the selective pressures that favor maintenance of RVs with certain sets of genes may be necessary to anticipate future vaccine needs .
Group A rotaviruses ( RVs ) are the most important etiological agents of acute , dehydrating gastroenteritis in young children . It is estimated that RV infections result in more than 500 , 000 deaths each year worldwide , the vast majority of which occur in developing countries [1] , [2] . These pathogens are transmitted via the fecal-oral route with peak disease frequency occurring in cooler , winter months [3] . The infectious RV virion is a non-enveloped , triple-layered particle that encapsidates an eleven-segmented , double-stranded ( ds ) RNA genome [4] . Cumulatively , the viral genome encodes five or six nonstructural proteins ( NSP1-5 , and sometimes , NSP6 ) and six capsid proteins ( VP1-4 , VP6 , and VP7 ) [3] . The outermost capsid proteins , VP7 and VP4 , induce neutralizing antibodies during infection of a host; serotypes defined by these proteins are a traditional method of characterizing RV isolates [3] . Based on the sequences of genes encoding the serotype antigens , strains have been more recently classified into G-types ( VP7 ) and P-types ( VP4 ) [3] , [5] . To date , a total of 22 G-type and 31 P-type strains have been described in the literature [6] , [7] , [8] , [9] , [10] . Ongoing epidemiological surveillance indicates that strains with G-types of G1 , G2 , G3 , and G4 , and those with P-types of P[4] and P[8] , are the most prevalent cause of RV disease in humans . As such , these G/P-types are included in the currently licensed RV vaccines ( RotaTeq and Rotarix ) [11] . However , RV G/P-type distribution varies considerably from year-to-year for reasons that are not well understood [12] . For instance , an increased occurrence of one G/P-type will often accompany decreases in other G/P-types during a specific epidemic season [12] , [13] . This phenomenon suggests that an emergent G/P-type may gain an advantage due to transient , but as of yet unidentified , selective pressure ( s ) . In addition to the annual fluctuation in G/P-type distribution , the incidence of unusual types , such as G5 , G6 , G8 , G9 , G12 , and P[6] is rising in certain geographical locations [11] , [14] . Despite the observation that RV G/P-type diversity seems to be an ever-changing landscape , little is known about the genetic make-up of circulating strains . Compared to the wealth of sequence information for serotype antigens VP7 and VP4 , few sequences are available for genes encoding other viral proteins . Studies of segmented RNA viruses , such as influenza A , have demonstrated that internal protein genes can dramatically influence viral fitness [15] , [16] , [17] , [18] . Because they have segmented genomes , RVs are capable of undergoing gene reassortment during co-infection . These exchanges result in progeny virions with dsRNA segments belonging to more than one strain . However , due to the limited available sequence information , the extent to which reassortment occurs in nature is unknown . Consequently , there is an impetus to deduce the complete-genome sequences of individual RV isolates to better understand the evolutionary dynamics of this medically important pathogen . Recent studies by our laboratory and others have made some initial strides in the area of RV genomics . In particular , Matthijnssens et al . analyzed hundreds of human and animal RV gene sequences , including 35 complete genomes , to devise a novel classification and nomenclature system [5] , [6] . Their results show that most human RV isolates have genes similar in sequence to those of prototype genogroup strains Wa ( genotype 1 genes ) or DS-1 ( genotype 2 genes ) [5] . A RV is classified as a pure Wa or DS-1 genogroup member if its nine internal protein genes ( those encoding VP1-3 , VP6 , and NSP1-5 ) are genotype 1 or 2 , respectively . If an isolate contains both genotype 1 and 2 genes , it is considered an inter-genogroup reassortant . The G1P[8] , G3P[8] , G4P[8] , and G9P[8] primary isolates and laboratory strains ( cell-culture adapted ) , for which sequences are available , have only genotype 1 genes and , therefore , belong to the Wa genogroup [5] . In a similar manner , all known G2P[4] laboratory strains have only genotype 2 genes and are considered DS-1 genogroup strains [5] . The unusual human RV G/P-types ( G6 , G8 , G9 , G10 , G12 , P[6] , P[9] , and P[14] ) are more often inter-genogroup or inter-species reassortants [5] , [14] . It is not clear why some human RV G/P-types have ‘pure genogroup’ genome constellations , but it is possible that viral genes have co-evolved to create protein sets that operate best when kept together . In support of this idea , Heiman et al . found that genotype 1- or 2-specific amino acids cluster in definitive regions of viral proteins , many of which are sites of known protein-protein interactions [19] . It is important to note , however , that the genomes of very few primary G1P[8] , G2P[4] , G3P[8] , G4P[8] , or G9P[8] clinical isolates have been sequenced , making it difficult to ascertain whether preferred genome constellations are seen in human RVs that normally cause disease . Indeed , the lack of complete-genome sequence data has made it hard to answer some key questions related to RV diversity and evolution: Does reassortment readily occur between genogroups in nature ? Do genetically distinct clades of the same G/P-type exist and do they co-circulate during an epidemic season ? Is there a correlation between genome constellation and G/P-type dominance ? Towards answering these questions , we sequenced the complete genomes of G3P[8] RVs found in fifty-one archival stool samples , which were collected longitudinally ( 1974 to 1991 ) from sick children at Children's Hospital National Medical Center in Washington , DC [20] , [21] , [22] , [23] ( N . Santos et al . , unpublished data ) . The data presented in this report , derived from the first large-scale RV genomics project , provide exceptional insight into the evolution of group A RVs and their pattern of transmission through the human population .
During the years of 1974 to 1991 , stool specimens were collected from infants and young children who were hospitalized with gastroenteritis at Children's Hospital National Medical Center [20] , [21] , [22] , [23] ( N . Santos et al . , unpublished data ) . RNA was extracted from RV-positive samples and classified into G/P-types by polymerase chain reaction ( PCR ) -enzyme-linked immunosorbent assay ( ELISA ) [24] ( N . Santos et al . , unpublished data ) . Consistent with the distribution typically seen in the United States , G1P[8] , G2P[4] , G3P[8] , and G4P[8] strains were predominant , making up 83% of the total samples ( Table 1 ) . The incidence of G1P[8] was by far the highest , averaging 56% of the total samples , with G3P[8] strains being the second most prevalent at 20% . However , in 1976 and 1991 , the frequency of G1P[8] strains was much lower than normal ( 11% and 26% , respectively ) , which correlated with increased detection of G3P[8] strains ( 65% and 40% , respectively ) ( Table 1 ) . Due to the fluctuating pattern of occurrence , the G3P[8] strains were chosen for complete-genome sequence analysis and RNA was extracted from 150 stool samples . Of these 150 samples , 51 contained viral RNA of sufficient quantity and quality to obtain complete-genome sequences using a reverse transcription ( RT ) -PCR-sequencing pipeline at the J . Craig Venter Institute ( JCVI ) , Rockville , MD . Primers were designed based on the human strain P , the only G3P[8] RV genome completely sequenced to date , and were refined iteratively as data was generated during this project [19] . Nucleotide sequences of all eleven gene segments were derived for fifty-one of the samples . The open-reading frames ( ORFs ) of the gene segments were determined and , for some of the genes/samples , sequences for portions of the conserved 5′ and 3′ untranslated regions were also deduced ( Table 2 ) . A few of the ORF sequences have several nucleotides missing from either of their termini; nonetheless , the coding completeness for each gene is between 99 . 1 and 100% ( Table 2 ) . Multiple , overlapping reads ( 7 . 6 to 10 . 6 times coverage ) were determined , and the derived sequences showed no evidence of heterogeneity , suggesting that each stool specimen likely contained a single , dominant RV isolate ( Table 2 ) . G3 RV strains are quite ubiquitous in nature and have been isolated from various animal species ( monkeys , dogs , cats , pigs , cattle , lambs , goats , horses , rabbits , mice and humans ) [5] , [25] . The complete genomes of several animal ( SA11 , RRV , TUCH , 30/96 , CU-1 , K9 , A79-10 , Cat2 , Cat97 and A131 ) and human ( P , AU-1 , Ro1845 , HRC3A , and B4106 ) G3 strains have been sequenced and the individual genes classified into genotypes according to the system established by the Rotavirus Classification Working Group ( RCWG ) [5] , [6] , [26] . Using this system , it was shown that G3 strains have very divergent genome constellations and contain genes belonging to several genotypes ( Table S1 ) . Specially , the human G3P[8] strain P contains exclusively genotype 1 genes , making it a pure Wa genogroup virus , whereas the human G3P[9] strain AU-1 contains all genotype 3 genes ( Table S1 ) . Strains B4106 ( G3P[14] ) , Ro1845 ( G3P[3] ) , and HCR3A ( G3P[3] ) were isolated from humans following a interspecies transmission events , and contains human genotype 2 ( DS-1-like ) and genotype 3 genes , as well as animal RV-like genes ( Table S1 ) . Given the broad host range and observed genetic diversity for G3 serotype strains , we wondered whether the Washington , DC G3P[8] RVs contain genes belonging to a single or multiple genotypes . Using the RCWG classification system , we confirmed the G/P-types of the viruses and found that the other nine genes of the G3P[8] strains can be classified as genotype 1 ( G3-P[8]-I1-R1-C1-M1-A1-N1-T1-E1-H1 ) ( Table S1 ) . Thus , none of the fifty-one G3P[8] RVs are predicted to be inter-genogroup or inter-species reassortants , but instead can be considered pure Wa genogroup strains . Preliminary analysis of G2P[4] RVs from this same collection showed they contain only genotype 2 genes , allowing them to be classified into the DS-1 genogroup ( A . Rolle et al . , unpublished data ) . This observation suggests that , although opportunities for inter-genogroup reassortment theoretically existed , there appears to have been strong biases towards the maintenance of pure Wa-like genome constellations for the G3P[8] isolates . To investigate the genetic relatedness of the fifty-one G3P[8] RVs , we reconstructed phylogenetic trees using concatenated gene sequences ( i . e . , genome sequences ) ( Figure 1 ) . The results showed that the sequences did not necessarily cluster in a manner consistent with the year of sample collection . In particular , the genome sequences of RVs from the 1976 season appear related to those of from 1974 , 1975 , or 1979 strains and can be grouped into three distinct clades ( A , B , and C ) ( Figure 1 ) . The genome sequences of these earlier G3P[8] isolates seem more distantly related to those of the 1980 and 1991 isolates , which cluster closely together ( Figure 1 ) . An exception in 1991 is DC5751; this strain is an outlier and does not belong to the 1991 major clade ( Figure 1 ) . Due to the very limited number of samples from 1974 , 1975 , 1979 , and 1980 , it is difficult to determine the relationship among RVs within each of these years . Nonetheless , it is clear that multiple clades of Wa genogroup G3P[8] RVs co-circulated and caused disease in the 1976 season , but that the 1991 season was dominated by a single G3P[8] clade . The genetic variability among the G3P[8] strains found in the genome tree can either be attributed to the accumulation of point mutations over time ( genetic drift ) or to gene reassortment within the Wa genogroup ( genetic shift ) . To determine the contribution of these two evolutionary mechanisms , we performed phylogenetic analyses for each gene ( Figures 2–4 ) . The results using a maximum likelihood analyses are presented in Figures 2–4; however , the overall tree topologies were nearly identical when neighbor-joining analyses or bayesian inference were used ( data not shown ) . Clusters of sequences in the individual gene trees represent genetically-distinct alleles and have been color-coded based on the consensus of all phylogenetic algorithms tested . Reassortment events are indicated by ( i ) the movement of a particular isolate from one color-grouping to another or ( ii ) the emergence of new color-groupings . The summary of the individual gene phylogenies is consistent with the results using the genomes and reveals the true genetic make-up of the G3P[8] isolates ( Figure 5 ) . Each gene can be classified into four or five alleles ( orange , green , red , cyan , or navy blue ) that are defined by strong bootstrap ( neighbor-joining or maximum likelihood analyses ) or posterior probabilities ( bayesian inference ) ( Figures 2–4 and data not shown ) . Twenty of the fifty-one isolates ( 39% ) show genes that fall into the same topological position on each tree and maintain the same color , indicating the lack of intra-genogroup reassortment . For example , the 1976 clades B and C have pure-color genome constellations ( green and red , respectively ) , demonstrating that they each evolved distinctly and did not recently share genetic information ( Figure 5 ) . Likewise the 1974 and 1979 isolates ( DC1563 and DC1730; orange ) , as well as the 1975 and 1976 isolates ( DC5142 and DC2119; cyan ) are not predicted to be reassortants ( Figure 5 ) . This observation was surprising and suggests that , even within the Wa genogroup not all gene allele combinations are tolerated and there may be pressure ( s ) to maintain certain genome constellations . Nonetheless , thirty-one of the isolates ( 61% ) can be described as intra-genogroup reassortants , containing gene sequences with different phylogenetic patterns and , therefore , belonging to more than one color group ( Figure 5 ) . The majority of these reassortants belong to the 1976 clade A or the 1991 major clade and exhibit a cyan background with several navy blue alleles ( Figure 5 ) . None of the isolates from our collection show a predominant navy blue genome constellation , suggesting that these gene alleles may have been picked up from a G3P[8] strain not sequenced in this study or from co-circulating non-G3P[8] Wa genogroup viruses . The two other types of reassortants detected include: ( i ) the 1976 isolate ( DC168; clade A ) , which contains gene alleles belonging to the cyan and red color groups and ( ii ) the 1991 isolate ( DC5751 ) , which contains gene alleles belonging to all five color groups ( orange , green , red , cyan , or navy blue ) ( Figure 5 ) . The 1991 DC5751 isolate is particularly interesting , as several of its gene alleles ( orange , green , and red ) are not detected in the co-circulating G3P[8] RV population . We predict that , similar to the navy blue alleles seen in 1975 , 1976 , 1980 , and 1991 strains , the orange , green , and red alleles of DC5751 were donated by a Wa genogroup strain belonging to a different G/P-type . Future studies aimed at elucidating the genome constellations of the G1P[8] and G4P[8] strains from this archival stool collection will shed light on ( i ) whether these isolates also belong to the Wa genogroup and ( ii ) whether they exchanged genes segments with the G3P[8] population . Still , the results presented in this report suggest that , although genetic shift plays an important role in RV evolution , reassortment among viral genes that have become divergent due to genetic drift may create less fit genome constellations . Having observed that G3P[8] RVs encode genes that are genetically-divergent at the nucleotide level , we next sought to determine whether the color-coded alleles also encode different proteins . In particular , to identify the precise residues that distinguish proteins from the orange , green , red , cyan , or navy blue alleles , amino acid alignments were constructed . Residues in the alignments that differ depending on the color grouping of the gene ( i . e . , allele-specific differences ) were identified ( Table S2 ) . We found that , indeed , the grouping based on nucleotide analyses correlate significantly with changes in amino acid sequence . Proteins VP1 , VP6 , VP7 , NSP2 , NSP4 , and NSP5 are highly conserved among the G3P[8] RVs , showing only 6 to 15 allele-specific amino acid differences ( Table S2 ) . In contrast , proteins VP2 , VP3 , VP4 , and NSP3 are more variable and exhibit 27 to 41 differences ( Table S2 ) . By far the most variation was seen in NSP1 , which functions as an innate immune antagonist [27] , [28] . We found 101 allele-specific differences for this non-structural protein; the basis of such extreme variation is not known . The majority of the amino acid changes among the G3P[8] RVs of this study are also found in other published RV sequences . However , a few of the gene alleles show unique residues that have not been seen in any human or animal RV strain sequenced to date ( Table S2; yellow-shading ) . The high-resolution structures of G- and P-type antigens ( VP7 and VP4 , respectively ) of rhesus RV ( strain RRV ) have been solved , affording the opportunity to map the three-dimensional locations of the allele-specific differences [29] , [30] , [31] , [32] . For the VP7 glycoprotein , three putative neutralization domains ( 7-1A , 7-1B , and 7-2 ) are predicted based on amino acid alignments and the mapping of monoclonal antibody escape mutants ( Table S3 ) [29] . Of the six allele-specific differences in VP7 , four of them are located on the surface of the protein , in or near neutralization domains ( Figure 6 ) . In particular , domain 7-1A shows a single allele-specific difference ( RRV residue 123 ) , while two differences are located within domain 7-1B ( RRV residues 238 and 242 ) . A single amino acid change ( RRV residue 268 ) is also seen proximal to neutralization domain 7-2 . Although these differences are not sufficient to change the G-type of these viruses , they may subtly affect binding of neutralizing antibodies and confer a selective pressure that influences viral fitness . Additionally , the G3 component of the pentavalent RV vaccine RotaTeq ( strain Wi78 ) or those of vaccines currently being developed ( strains RV3 and P ) seem to match some VP7 proteins better than others ( Figure 6 and Table S2 ) [33] , [34] , [35] , [36] , [37] . Because the allele-specific differences identified in this study are also seen in VP7 sequences of present-day G3 RV strains , it will be important to learn whether they are determinants of vaccine efficacy . The VP4 spike protein is comprised of two structurally-distinct regions ( VP8* and VP5* ) generated following trypsin activation of the virion particle [3] . The VP8* region contains four putative neutralization domains ( 8-1 , 8-2 , 8-3 , and 8-4 ) defined by amino acid alignments and mapping of monoclonal antibody escape mutants [30] , [31] , [32] ( Table S4 ) . We found that of the 13 allele-specific differences in VP8* , four of them map to domain 8-1 ( RRV residues 78 , 146 , 173 , and 189 ) and four of them to domain 8-3 ( RRV residues 125 , 131 , 135 , and 162 ) ( Figure 7 ) . Changes at position 189 may be particularly important , as they are predicted to influence sialic acid receptor binding [31] . Compared with VP8* , the regions of VP5* involved in neutralizing antibody binding have not been well characterized , but the mapping of escape mutants have identified several important domains ( Table S5 ) . Additionally , amino acid alignments highlighted P[8]-specific residues of VP5* that might play a role in virus neutralization . We found ten allele-specific amino acid changes in VP5* , seven of which ( RRV residues 255 , 256 , 272 , 282 , 284 , 338 , and 436 ) are surface-exposed in either the native or trypsin-activation form of the protein . Based on its three-dimensional location , residue 436 is most likely to influence neutralizing antibody binding ( Figure 8 ) . Similar to the changes seen in VP7 , those in VP4 are not predicted to alter the P-type classification of these strains , and they represent the diversity seen modern day P[8] RVs . The sequences of the VP4 P[8] components of the RV vaccines RotaTeq ( strain Wi79 ) and Rotarix ( strain 89-12 ) are not available to the public [33] , [38] . Therefore , we cannot predict if or how these allele-specific changes might affect vaccine efficacy . RVs continue to be a primary cause of childhood diarrheal illness and are associated with significant morbidity and mortality , particularly in developing countries . Despite their medical importance , the lack of sequence information has hindered our understanding of how RVs evolve during and between epidemic seasons . Genome sequences of several laboratory strains have allowed for the development of classification systems based on the outer capsid protein genes ( G/P-types ) or the internal protein genes ( genogroups ) [5] , [6] . RVs with certain G/P-types ( such as G1P[8] , G3P[8] , and G4P[8] ) tend to contain all genotype 1 internal protein genes and belong to the Wa genogroup . In contrast , strains classified as G2P[4] seem to have only genotype 2 genes and to belong to the DS-1 genogroup . Although inter-genogroup reassortants exist , emerging evidence suggests that such mixed genome constellations ( those containing both genotype 1 and 2 genes ) may be less fit and selected against in nature . In support of this notion , we found that the genomes of fifty-one G3P[8] primary RV isolates are comprised only of genotype 1 genes , despite the fact that viruses containing genotype 2 genes ( i . e . , G2P[4] strains ) were present during the same epidemic season ( A . Rolle et al . , unpublished ) . It is possible that G2P[4] and G3P[8] strains did not physically co-infect children , thereby preventing the opportunity for reassortment . However , we think it is more likely that both co-infection and inter-genogroup reassortment occurred , but that the resultant viruses were unable to compete with parental strains . Thus , the natural selection of isolates containing genes that operate best when kept together may limit the amount of observed genetic shift that occurs during RV evolution . In essence , RVs must balance the advantages of gene reassortment with the disadvantages of unlinking preferred genes/protein combinations . This observation is in contrast to what has been generally reported for influenza A viruses , for which ongoing , robust reassortment is evident with limited evidence of genetic linkages among gene segments for those viruses infecting a common animal species [18] , [39] , [40] , [41] . In addition to reassortment biases between the DS-1 and Wa genogroups , our results also suggest that there may be preferences towards the maintenance of certain genome constellations even for RVs belonging to the same genogroup . Although the genes of the fifty-one G3P[8] RVs are technically genotype 1 , we found significant variation among them and were able to classify each into four or five distinct alleles . Many of the isolates show pure color genome constellations , indicating the lack of intra-genogroup reassortment . Of the isolates that do show evidence of genetic exchange , most did not reassort with co-circulating G3P[8] strains . Instead , we predict that the majority of reassortants pick up genes ( such as the navy blue alleles ) from other Wa genogroup viruses belonging to different G/P-types ( G1P[8] or G4P[8] ) . The lack of robust , ongoing reassortment may have resulted in the maintenance of the 1976 G3P[8] RVs as genetically distinct , stable , co-circulating clades ( A , B , and C ) . Importantly , the 1976 clades have amino acid differences in all eleven viral proteins . It is possible that allele-specific residues contributed to the evolution of genome constellations encoding more fit protein sets , much like what is seen at the genogroup level . In this manner , only intra-genogroup reassortants with gene alleles encoding compatible proteins ( such as cyan and navy blue ) emerged in the G3P[8] RV population . Moreover , by mapping the allele-specific amino acid differences onto the high-resolution structures of serotype antigens VP7 and VP4 , we found that several are located in or near putative neutralization domains . By having outer capsid proteins that are slightly different , and possibly more capable of mediating cell entry or evading the host immune response , the 1976 clade A viruses may have had a selective advantage . This advantage would explain why the 1991 epidemic season was characterized by a single clade of viruses whose outer capsid proteins are remarkably similar to those of the 1976 clade A strains . The observed diversity in VP7 and VP4 of the fifty-one archival G3P[8] RVs sequenced in this study mirrors what is seen in currently circulating strains . The results presented in the current report are expected to provide a foundation for future studies aimed at elucidating the role , if any , these amino acid changes have on viral fitness and vaccine efficacy .
The study population included infants and young children who were hospitalized with diarrhea at Children's Hospital National Medical Center , Washington , DC [20] , [21] , [23] . Fecal specimens ( rectal swabs or diaper scrapings ) were collected and tested for evidence of RV using electron microscopy and for viral antigen using ELISA . RNA was extracted from RV-positive samples using TRIzol ( Invitrogen ) and samples were classified into G/P-types based on the results of a microtiter plate hybridization-based PCR-ELISA [24] ( Santos et al , unpublished data ) . The isolated RNA was subsequently used for RT-PCR and nucleotide sequencing as described below . Oligonucleotide primers were initially designed based on the human RV strain P [19] and then improved iteratively as new sequence data was generated . Primers were designed every 600 bp along both sense and antisense strands to provide greater than 4 times ( 4× ) coverage by RT-PCR . An M13 tag was added to the 5′ end of each primer ( sense: TGTAAAACGACGGCCAGT; antisense CAGGAAACAGCTATGACC ) for use in sequencing ( see below ) . RT-PCRs were performed with 1 ng of RNA using OneStep RT-PCR kits ( Qiagen ) according to manufacturer's instructions with minor modifications . Reactions were scaled down to 1/5 the recommended volumes , the RNA templates were denatured in 50% DMSO at 95°C for 5 min , and 1 . 6 units RNase Out ( Invitrogen ) was added . Following RT-PCR cycling , the reactions were treated with 0 . 5 units of shrimp alkaline phosphatase and 1 unit of exonuclease I ( USB ) incubation at 37°C for 60 min to inactivate remaining deoxyribonucleotides and digest the single-stranded primers . Enzymes were heat inactivated by incubation at 72°C for 15 min . The RT-PCR products were sequenced with an ABI Prism BigDye v3 . 1 terminator cycle sequencing kit ( Applied Biosystems ) using M13 primers ( listed above ) . The dye terminator was removed using Performa DTR ( Edge Biosystems ) and sequences were obtained with a 3730 DNA Analyzer ( Applied Biosystems ) . Raw sequence data was trimmed to remove any primer-derived sequence as well as low quality sequence , and gene sequences were assembled using the Elvira and TIGR assemblers ( www . jcvi . org/cms/research/software ) . The gene sequences were then manually edited using CloE ( Closure Editor; JCVI ) and any polymorphisms were re-analyzed by sequencing . Finally , the Viral Genome ORF Reader ( VIGOR; JCVI ) program was used to: check segment length , perform alignments , ensure the fidelity of open-reading frames , correlate nucleotide polymorphisms with amino acid changes , and detect any potential sequence errors . Maximum likelihood phylogenetic trees were reconstructed using PhyML [42] employing the Hasegawa-Kishino-Yano substitution model ( HKY85 ) and gamma-distributed rate variation among sites . Bootstrap analysis was performed based on 1000 replicates and trees were visualized using FigTree ( http://tree . bio . ed . ac . uk/software ) . Amino acid alignments were constructed with MacVector 8 . 1 . 2 . ( Accelrys ) using ClustalW , BLOSUM Series , with the defaults set ( open gap penalty of 10 . 0 , extended gap penalty of 0 . 05 , and delay divergence of 40% ) . The sequence of strain Wi78 VP7 was found in Nishikawa et al . [37] . Structural analysis of VP7 ( PBD# 3FMG ) , VP8* ( PDB# 1KQR ) , and VP5* ( PDB# 2B4H ) , was performed using UCSF Chimera-Molecular Molecular Modeling System [43] . Accession numbers of published protein sequences used in this study include: strain RRV VP7 and VP4 ( AF295303 and AY033150 , respectively ) ; strain RV3 VP7 ( FJ998278 ) ; strain D VP4 ( EF672570 ) ; strain P ( EF583037–EF583037 and EF67598–EF67604 ) ; strain Wi61 ( EF583049–EF583052 and EF672619–EF672625 ) ; strain IAL28 ( EF583029–EF583032 and EF672584–EF672590 ) , strain DS-1 ( EF583025–EF583028 and EF672577–EF672583 ) . Accession numbers deposited into GenBank include: DC1563_1974 ( FJ947175–FJ947185 ) ; DC140_1975 ( FJ947738–FJ947748 ) ; DC1455_1975 ( FJ947186–FJ947196 ) ; DC5142_1975 ( FJ947197–FJ947207 ) ; DC2119_1976 ( FJ947395–FJ947405 ) ; DC2109_1976 ( FJ947373–FJ947383 ) ; DC1497_1976 ( FJ947340–FJ947350 ) ; DC131_1976 ( FJ947252–FJ947262 ) ; DC1494_1976 ( FJ947274–FJ947284 ) ; DC4772_1976 ( FJ947362–FJ947372 ) ; DC1898_1976 ( FJ947296–FJ947306 ) ; DC2069_1976 ( FJ947804–FJ947814 ) ; DC2106_1976 ( FJ947837–FJ947847 ) ; DC2081_1976 ( FJ947815–FJ947825 ) ; DC168_1976 ( FJ947749–FJ947759 ) ; DC2102_1976 ( FJ947826–FJ947836 ) ; DC2171_1976 ( FJ947406–FJ947416 ) ; DC139_1976 ( FJ947219–FJ947229 ) ; DC23_1976 ( FJ947208–FJ947218 ) ; DC2114_1976 ( FJ947384–FJ947394 ) ; DC1505_1976 ( FJ947351–FJ947361 ) ; DC2238_1976 ( FJ947417–FJ947427 ) ; DC133_1976 ( FJ947263–FJ947273 ) ; DC2266_1976 ( FJ947881–FJ947891 ) ; DC1496_1976 ( FJ947285–FJ947295 ) ; DC129_1976 ( FJ947230–FJ947240 ) ; DC2212_1976 ( FJ947848–FJ947858 ) ; DC2262_1976 ( FJ947870–FJ947880 ) ; DC2239_1976 ( FJ947859–FJ947869 ) ; DC130_1976 ( FJ947241–FJ947251 ) ; DC135_1979 ( FJ947307–FJ947317 ) ; DC1730_1979 ( FJ947318–FJ947328 ) ; DC1600_1980 ( FJ947771–FJ947781 ) ; DC792_1980 ( FJ947760–FJ947770 ) ; DC5553_1991 ( FJ947936–FJ947946 ) ; DC5544_1991 ( FJ947505–FJ947515 ) ; DC5549_1991 ( FJ947516–FJ947526 ) ; DC5710_1991 ( FJ947782–FJ947792 ) ; CH5459_1991 ( FJ947439–FJ947449 ) ; CH5446_1991 ( FJ947428–FJ947438 ) ; DC5728-1991 ( FJ947329–FJ947339 ) ; CH5475_1991 ( FJ947450–FJ947460 ) ; CH5484_1991 ( FJ947472–FJ947482 ) ; CH5483_1991 ( FJ947914–FJ947924 ) ; CH5455_1991 ( FJ947892–FJ947902 ) ; DC5491_1991 ( FJ947494–FJ947504 ) ; CH5477_1991 ( FJ947461–FJ947471 ) ; CH5488_1991 ( FJ947483–FJ947493 ) ; CH5498_1991 ( FJ947925–FJ947935 ) ; CH5470_1991 ( FJ947903–FJ947913 ) ; and DC5751_1991 ( FJ947793–FJ947803 ) . Fecal specimens were collected during 1974–1991 from infants and young children who were hospitalized with diarrhea at Children's Hospital National Medical Center , Washington , DC . Samples were de-identified and analyzed anonymously . Under these conditions , the Office of Human Subjects Research ( OHSR ) of the National Institutes of Health has determined that Federal regulations for the protection of human subjects do not apply to the research activities described in this study ( Exemption # 3937 ) . | Rotaviruses are the most important cause of severe diarrhea in infants and young children . Due to the segmented nature of their genomes , rotaviruses can exchange ( reassort ) genes during co-infections , a feature that is predicted to generate new , possibly more dangerous virus strains . However , the amount of gene reassortment occurring in nature is not known , as very few rotavirus genomes have been sequenced . To better understand the genetic make-up of rotaviruses circulating at a single location over a period of time , we sequenced the genomes of fifty-one isolates recovered from sick children from 1974 to 1991 at Children's Hospital National Medical Center , Washington , D . C . By analyzing these sequences , we found that several distinct groups ( clades ) of rotaviruses co-circulated and caused disease in a single epidemic season . In contrast to what was previously thought , very few rotaviruses exchanged gene segments with each other; instead , the genome constellations of the viruses remained relatively stable . We also discovered that these distinct rotavirus clades encode different viral proteins , which may be important in the development of effective vaccines . Together , the findings from this first large-scale rotavirus genomics project provide unparalleled insight into how these pathogens evolve during their spread through the human population . | [
"Abstract",
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"virology/virus",
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] | 2009 | Evolutionary Dynamics of Human Rotaviruses: Balancing Reassortment with Preferred Genome Constellations |
The identification of cancer drivers is a major goal of current cancer research . Finding driver genes within large chromosomal events is especially challenging because such alterations encompass many genes . Previously , we demonstrated that zebrafish malignant peripheral nerve sheath tumors ( MPNSTs ) are highly aneuploid , much like human tumors . In this study , we examined 147 zebrafish MPNSTs by massively parallel sequencing and identified both large and focal copy number alterations ( CNAs ) . Given the low degree of conserved synteny between fish and mammals , we reasoned that comparative analyses of CNAs from fish versus human MPNSTs would enable elimination of a large proportion of passenger mutations , especially on large CNAs . We established a list of orthologous genes between human and zebrafish , which includes approximately two-thirds of human protein-coding genes . For the subset of these genes found in human MPNST CNAs , only one quarter of their orthologues were co-gained or co-lost in zebrafish , dramatically narrowing the list of candidate cancer drivers for both focal and large CNAs . We conclude that zebrafish-human comparative analysis represents a powerful , and broadly applicable , tool to enrich for evolutionarily conserved cancer drivers .
The genomes of cancer cells usually contain a large number of aberrations ( point mutations , copy number alterations [CNAs] , chromosome translocations and epigenetic changes ) , which include causative genetic alterations ( drivers ) and a far greater number of genetic events ( passengers ) that do not influence cancer progression [1] . Identification of cancer drivers will advance our understanding of cancer biology and ultimately enable personalized cancer therapies . However , distinguishing drivers from passengers remains difficult because of the number and variability of genomic alterations in cancer cells . Copy number alterations are detected by methods including cytogenetics , array comparative genome hybridization ( aCGH ) and massively parallel sequencing [2] . The sizes of CNAs are variable and range from less than a single gene to entire chromosome changes [3] , [4] . Cancer drivers have been successfully identified within recurrent focal CNAs by using functional studies to evaluate all of the candidate genes [5] . In contrast , commonly observed large chromosome or chromosome arm-level CNAs , which are usually caused by aneuploidy , encompass too many genes to allow this approach . Neither improved resolution of genome scanning technology nor increased tumor sample size can fully resolve this problem because many cancer drivers likely occur within large CNAs [6] , [7] . Thus there is a critical need in the cancer field to find a way to reduce the number of candidate drivers in these very large CNAs to a number amenable to one-by-one functional testing [4] , [8]–[12] . Cross-species comparative oncogenomics is one approach to overcome this obstacle [13] , [14] . It is well established that the function of human cancer genes is well conserved in other mammals [15] . Recent large-scale mouse-to-human and dog-to-human comparisons confirmed that evolutionary conservation could be used as a filter to reduce the noise in genomic data sets [16]–[20] . Unfortunately , most mouse tumors exhibit little natural aneuploidy , and have fewer and less variable CNAs than human tumors . This reduces their effectiveness for comparative oncogenomics; although there are some exceptions , including malignant peripheral nerve sheath tumors ( MPNSTs ) as recently shown by CGH analysis of a small number of tumors [21] . Additionally , conserved syntenic blocks among mammals tend to be very large and thus the efficiency of filtering out passengers is relatively poor . As a result , these inter-mammal comparisons have mostly concentrated on focal CNAs . We sought to enhance the power of cross-species comparisons by using the more evolutionarily distant zebrafish . Teleost fish and the mammalian lineages separated about 450 million years ago and their respective genomics show a high degree of reshuffling , yielding a much lower degree of conserved synteny between human and zebrafish than between human and mouse [22] , [23] . Defining conserved synteny as pairs of genes that are within 100 genes of each other in each species , 90% of syntenic blocks conserved between zebrafish and humans contain 10 genes or fewer , and only 2% contain greater than 30 genes ( see [24]and Figure S1 ) . Consequently , the passenger genes that are co-enriched or co-depleted with genuine drivers in CNAs are more likely to differ between human and fish than between human and other mammals . Importantly , the zebrafish is now well validated as an excellent system in which to model human cancer . Zebrafish offer significant technical advantages due their large number of offspring , tractable genetics and amenability to in vivo imaging and chemical screening [25] . Numerous zebrafish models confirm that the function of core cancer genes , such as tp53 , pten , nf1 , nf2 , Myc , Mycn , mutant KRAS , and mutant BRAF , is conserved between humans and zebrafish [26]–[33] . Notably , several cancer mutations known to cause particular human tumor types have been shown to can lead to the same tumor types in zebrafish [26] , [27] , [30] , [32] , [33] . Moreover , a comparative oncogenomics study of human versus zebrafish T-cell acute lymphoblastic leukemia ( T-ALL ) successfully identified genes that were shared between focal CNAs in both species [34] . This provides strong justification for zebrafish-human tumor CNA comparisons , at least in the context of tumor types that have low-level aneuploidy . Given this success , we wished to apply this approach to tackle chromosome-arm level CNAs . We chose to address this question in MPNSTs , a tumor type that in humans displays particularly high levels of aneuploidy and has very poor prognosis . With the exception of a few hereditary susceptibility genes , such as NF1 and NF2 , drivers for this cancer type remain largely unknown . This in part reflects the extensive aneuploidy of these tumors and the consequent difficulty in identifying the key changes amongst so much genomic alteration . In zebrafish , MPNSTs are a very rare spontaneous tumor type , but various genetic mutations can predispose fish to develop them including heterozygosity for nf2a ( albeit at low penetrance ) , heterozygosity for any one of various ribosomal protein ( rp ) genes and homozygosity for an inactivating tp53 mutation , tp53M214K [27] , [28] , [35] . Rp heterozygotes and tp53 homozygotes develop MPNSTs at very high penetrance and tumors from the two genotypes have indistinguishable gene expression patterns . Consistent with this finding , our studies support a mechanistic link between these two MPNST models by showing that tumor cells in rp heterozygotes are unable to induce the tp53 protein [36] . Pathologists in multiple laboratories determined that these tumors were MPNSTs based upon both histological analysis and electron microscopy . Similar to human MPNSTs and also MPNSTs in murine genetically engineered models , these tumors consist of spindle cells aligned into stacks and fascicles to form a whirling , storiform pattern [27] , [28] , [37]–[39] . Moreover , electron microscopy studies indicate that the tumor cells have elongated interdigitating cytoplasmic processes and reduplicated external lamina , morphologic characteristics of nerve sheath differentiation [28] . Additionally , microarray analysis of both rp and p53 tumors indicated high expression of S100 in these tumors [36] , which is a common diagnostic marker for MPNSTs . Importantly , there is some overlap between the initiating genetic lesions seen in the zebrafish MPNSTs and human MPNSTs . As noted above , mutation of one paralog of the human NF2 gene , nf2a , can predispose zebrafish to develop MPNSTs , albeit at low penetrance that likely reflects compensation due to the duplication of this gene in zebrafish . Human MPNSTs , including those with mutation of the NF1 gene , frequently lose the CDKN2A gene , encoding both p16 and ARF , which disrupts activation of p53 [40]–[42] . Additionally , recent studies showed that mutation of both zebrafish paralogs of NF1 accelerates MPNST onset in p53 mutants [33] . Taken together , these studies suggest that zebrafish MPNSTs share drivers with human MPNSTs . We previously demonstrated that rp and tp53 mutant MPNSTs both display a high degree of aneuploidy [43] . Specifically , mitotic spreads showed that the chromosome number varied considerably between individual cells within each tumor , with the average trending around 3N [43] . To determine whether zebrafish MPNSTs contain recurrent genomic changes , we conducted a pilot CNA study of 36 tumors and were able to detect both recurrent focal CNAs and preferred whole-chromosome CNAs [43] . Notably , both types of genomic changes are a hallmark of human MPNSTs [6] , [44] . Given the limited conservation of synteny between human and zebrafish , we hypothesized that a gene-level comparison of CNAs in zebrafish and human MPNSTs could be employed to reduce the number of candidate cancer drivers on chromosome-arm level CNAs to be analyzed by functional studies . In this study , we stringently defined CNAs in zebrafish MPNSTs through analysis of 147 additional MPNSTs , and compared the preferred changes to ones that are characteristic of human MPNSTs . This comparative approach significantly reduced the number of candidate MPNST driver genes by approximately four-fold .
We chose to test the power of zebrafish and human comparative oncogenomics in the context of MPNSTs because the molecular determinants of this tumor type are poorly understood and the extensive aneuploidy makes it a particularly challenging problem . The general strategy of our approach is outlined in Figure S2 . Our first step was to construct a high-confidence map of recurrent copy number alterations in zebrafish MPNSTs . Initially , we identified CNAs for individual tumors by comparison of the massively parallel sequencing of DNA taken from fresh tumors versus normal ( tail ) tissue from the same fish . This latter control was particularly important because it has been shown that portions of the normal zebrafish genome can exhibit fish to fish germline copy number variation [45] . As noted above , the MPNSTs arising within diploid fish have near-triploid genomes [43] . Thus , the copy number calls for the tumor tissue were made relative to this 3N baseline copy number , such that underrepresented chromosomes ( “loss” ) exist at less than three copies , and overrepresented chromosomes ( “gains” ) exist at greater than three copies . These zebrafish MPNSTs were isolated from several different genetic backgrounds . 53 came from diploid fish heterozygous for any one of 14 rp mutations ( on 11 different chromosomes ) , and 49 were isolated from diploid fish homozygous for tp53M214K . In addition , given that MPNSTs have a near-triploid copy number [43] and triploid zebrafish are viable [46] , we also analyzed 45 tumors from triploid tp53M214K homozygotes to determine whether starting with a triploid genome would alter the genomic content of the resultant tumors . Interestingly , MPNSTs arising in triploid tp53M214K homozygotes had a pseudo-triploid chromosome number similar to MPNSTs from diploid fish , arguing strongly that this represents the preferred genomic state of this tumor type . Heat maps of all 147 tumors are shown in Figure S3A and per-sample numerical data is available in Dataset S1 and Dataset S2 . We next determined which CNAs were recurrent ( i . e . found in tumors significantly more frequently than would be expected by chance , given the amount of CNA per tumor ) . For this , segmented per-sample data for all 147 tumor:normal comparisons were subjected to statistical analysis using the GISTIC algorithm [47] in its JISTIC implementation [48] . Overall , recurrent large-scale CNAs accounted for almost 60% of the zebrafish genome . This analysis confirmed our prior conclusions about the contributions of whole-chromosome alterations [43] , and allowed stringent definition of the recurrent alterations . Specifically , all or most of nine different chromosomes ( chromosomes 9 , 10 , 11 , 13 , 19 , 20 , 22 , 23 and 25 ) were overrepresented and six chromosomes ( chromosomes 2 , 5 , 8 , 15 , 17 , 24 ) were underrepresented ( Figure 1 , Table S1 , Dataset S3 ) . With the exception of chromosome 25 , large-scale CNAs showed modest amplitudes , which is similar to findings in most human solid tumors [4] . Zebrafish centromeres have only been roughly mapped [49]–[53] . However , a careful examination of the CNAs in each of the individual tumors did not detect any common copy number breakpoints in the chromosomal region that contains each centromere ( Figure S3C ) . This suggests that zebrafish MPNSTs rarely exhibit “arm-level” CNAs , which are a common feature of human cancers [4] , [6] , [7] . Tumors arising in triploid versus diploid tp53 mutants did not show any statistically significant difference in the frequency with which any chromosome's copy number was altered ( Table S2 ) . This reinforces our conclusion that MPNSTs select for a similar karyotype regardless of the starting ploidy , and validates inclusion of the triploid fish tumors in our overall analysis . Alterations within tp53 and rp MPNSTs also appeared mostly similar , but a statistical analysis ( made possible by the large sample size for both genotypes ) revealed a slight preference for loss of chromosomes 6 , 17 , and 24 and gain of chromosomes 11 and 22 in rp tumors compared to tp53 tumors ( Table S2 ) . Notably , the tp53 gene is on chromosome 5; while this chromosome is recurrently underrepresented in zebrafish MPNSTs , this tendency is no more prevalent in tp53 mutant tumors than rp mutant tumors . This is consistent with our prior finding that both mutations exert their tumorigenic effect via a common pathway [36] . Almost every individual zebrafish tumor displayed a variety of focal CNAs ( i . e . affecting less than half a chromosome ) . Most of the identified focal CNAs spanned less than 10% of the chromosome . Additionally , most were not recurrent . Despite this heterogeneity , we did detect a number of recurrent focal CNAs . These were defined as either JISTIC-determined regions of less than 10 Mb and/or regions that scored in JISTIC's focal mode ( see Materials and Methods ) , which denotes significant recurrence relative to neighboring chromosomal sequences . Importantly , as anticipated , our enlarged sample size detected additional CNAs that were not evident in our previous study [43] , and it further refined the boundaries of formerly identified focal changes . In total , we found fourteen recurrent focal gains and three recurrent focal losses ( Figure 1 , Table S1 , Dataset S3 ) . Some of these focal changes overlie large events , and the focal and large alterations point in either the same or opposite directions . For example , focal amplifications are detected at multiple regions of chromosomes 20 and 25 , beyond the degree to which the whole chromosome is over-represented , and chromosome 17 contains several small over-represented regions even though it is generally under-represented . In addition , some of the focal CNAs that appear to be a rather large contiguous region ( as defined by the algorithm used ) have a fine structure that suggests several sub-peaks ( local Q-value maxima , Figure 2 ) . Because the Q-values across the entire region score as significant , any part could include driver genes . However , we speculate that the sub-peaks , which in a sense represent minimal overlap regions , may contain higher-probability candidates . Accordingly , we note that these regions often include the zebrafish orthologs of known oncogenes , such as jun , pdgfra , kita , mycn , ccnd2a , met , hrasa , and kras . Chromothripsis , a recently described phenomenon of cancer genomes [54] , is the catastrophic shattering of chromosomes followed by imperfect fragment rejoining and consequent acquisition of multiple genomic rearrangements . One result of these rearrangements is that a number of segments of a chromosome that were originally non-adjacent become linked and then co-amplified or co-depleted . In CNA analysis ( when viewing the sequence of the chromosome in its original order ) , this presents as an alternation between two or more copy number states along the length of all or part of the chromosome . Evaluation of the copy number data from our 147 tumors identified at least 47 chromosomes that had CNA patterns indicative of chromothripsis ( 1 . 3% of all chromosomes ) . These were observed in both tp53 and rp mutant zebrafish MPNSTs . Two examples are shown in Figure S3E , where the copy number clearly toggles back and forth between two or three different copy number states . While the degree of alteration seems less dramatic than cases reported in human tumors [7] , [54] , this indicates another similarity in the pathobiology of zebrafish and human cancer . More broadly , our data suggests that chromothripsis may be a hallmark of cancer-associated genomes in all vertebrates . We next focused our attention on analysis of human MPNSTs . Recently , 23 human MPNSTs in patients with inherited neurofibromatosis type 1 ( NF1; heterozygous germline NF1 mutation ) were examined using high resolution aCGH [41] ( Figure S3B ) . Almost half of human MPNSTs develop from neurofibromas in patients with NF1 mutations and these have been reported to share similar CNA and transcriptome profiles with sporadic MPNSTs [44] , [55] , [56] . Thus , we believe that this dataset will not be overly biased towards NF1-specific cooperating mutations . To enable comparison with our zebrafish data , we re-analyzed this human dataset using the same methods ( segmentation , GISTIC ) . To compensate for the small sample size of human tumors , we analyzed large-scale changes using an increased sensitivity threshold while ensuring that the resulting calls were largely consistent with the previously reported results [41] . In general agreement with prior studies of human MPNSTs [6] , [57]–[59] , we found that 5 chromosomes or chromosome arms were over-represented and 13 chromosomes or chromosome arms were under-represented ( Table 1 , Figure S4 , Table S3 , Dataset S4 ) . Similar to findings in other human solid tumors [4] , [6] , [7] , chromosome ( arm ) -level changes in human MPNSTs generally exhibited low amplitudes , but appeared at high frequency . In addition to recurrent large CNAs , we also identified 13 human recurrent focal gains and 7 recurrent focal losses ( Figure S4 , Table S3 , Dataset S4 ) . Similar to the zebrafish tumors , a subset of these human focal changes overlaid large-scale CNAs ( chromosomes 7 , 9 , 17 , see Table S3 , Dataset S4 ) . Samples displaying CNA patterns indicative of chromothripsis were also present in the human dataset in 44 instances ( 8 . 3% of chromosomes amongst all samples ) . Select examples in which the copy number toggles between two or three states along the length of the chromosome are shown in Figure S3F . To compare our zebrafish and human CNA datasets , we next established a correspondence table of proposed human-zebrafish orthologs represented by Ensembl gene models . These correspondences originated from reciprocal best hits from protein sequence similarity searches ( BLASTP ) , which were further refined using conserved synteny information [24] . This correspondence table covers 20 , 649 pairwise relationships . Once gene redundancy is eliminated , it comprises 20 , 216 distinct zebrafish genes and 13 , 338 distinct human genes . This disparity is due to a number of factors , but chiefly the increased number of paralogs in zebrafish arising from the teleost-specific , whole genome duplication event [60] . As the retention of both paralogs generally indicates some sub-functionalization , either in expression pattern or activity [61] , copy number alteration of either paralog could contribute to tumorigenesis in zebrafish . The zebrafish gene count is further inflated because some genes have been erroneously split into two or more adjacent gene models for lack of connecting transcript evidence . Genes unaccounted for in the correspondence table reflect technical difficulties in ortholog assignment , as well as orphan genes [62] in either lineage . These have been excluded from the following oncogenomic comparisons .
Our prior study of 36 zebrafish MPNSTs established the presence of aneuploidy and the preferential gain or loss of certain chromosomes [43] . Here , through the analysis of a much larger sample size , we can now assign statistical significance for these changes and conclude that 9 chromosomes are preferentially gained and 6 chromosomes are preferentially lost in these tumors ( Table S1 ) . In most cases , these preferences were found in MPNSTs that had been initiated by either rp or tp53 mutations . However , statistical analysis suggests that slight differences may exist for a subset of chromosomes , ( Table S2 ) . We note that most of the large-scale CNAs in our zebrafish tumors include entire chromosomes . However , we do find exceptions to this rule , and these CNAs typically affect the central portions of chromosomes , as opposed to the ends . This is somewhat surprising , given that zebrafish chromosomes are predominantly metacentric or submetacentric [43] , [69] , much like human chromosomes . We speculate that this reflects differences in chromosome breakability between zebrafish and human . The substantial number of zebrafish MPNST samples also allowed for an accurate assessment of focal CNAs . In addition , we established fine structure for some of the CNA regions , especially for the amplified regions , through changes in GISTIC scores ( G-scores ) and significance values ( Q-values ) occurring beyond the simple statistical significance cutoff . These focal significance peaks represent minimal overlapping regions within the context of already statistically significant CNAs , and likely encompass higher-probability candidates . Consistent with this notion , we note that most of these focal peaks contained known oncogenes such as hrasa , kdr , kita , kras , met , mycn , and pdgfra . Comparative oncogenomics is already well validated as a successful strategy to identify cancer drivers [13] , [14] . To date , these studies have been primarily limited to analysis of focal CNAs . However , it is clear that many of the large-scale copy number aberrations in solid tumors affect entire chromosomes , chromosome arms , or large portions thereof . Such changes are shared by many types of solid tumors [4] , [70] . More importantly , they have been associated with poor prognosis in multiple human tumor types [71]–[77] , including in the case of MPNST [44] , arguing that they must contain cancer drivers . These large chromosomal CNAs have been hypothesized to reflect the selective advantage of simultaneously targeting multiple cancer drivers [78] . Despite widespread appreciation that whole chromosome and chromosome-arm-sized CNAs must contain important cancer drivers [4] , [8]–[12] , identification of drivers in these large CNAs has remained a challenge as they simply contain too many genes for one-by-one functional characterization . A reduction of the number of candidate genes to be functionally analyzed would surely make such gene identification more practical , and this is the goal we pursued . We postulate that zebrafish-human comparative oncogenomics provides a unique opportunity to address chromosome arm-level CNAs because human and fish genomes are effectively “scrambled” relative to each other due to the long evolutionary separation between human and zebrafish [22] . To show this , we established a reliable human-fish gene comparison list that contains 13261 , or approximately two-thirds , of human protein-coding genes . This ortholog-based approach may exclude some human cancer genes ( as one example , we note that the locus encoding p14ARF is absent in zebrafish ) , but it places the focus on evolutionarily related genes that are likely to conserve biological function . Using this list , we nominated human genes as candidate drivers if their copy number changed in the same direction as one or more of the zebrafish paralogs . This allowed us to reduce the number of candidate driver genes in the human MPNST CNAs by roughly four-fold . This reduction is comparable to that expected by chance , based on the relative fractions of the human versus zebrafish genomes that are recurrently gained or lost in MPNSTs . As the number of passenger genes is generally thought to greatly exceed the number of genuine cancer drivers , this level of enrichment , and not greater , is the anticipated result . We believe that this underscores the challenge - essentially searching for a needle in a haystack – and highlights how the poor synteny between human and zebrafish has such a strong winnowing effect . While we believe that our list of co-gained and co-lost genes still contains far more passengers than drivers , we note that removing 75% percent of the passenger genes in large CNAs is a significant step towards homing in on the true drivers , making it feasible to functionally test the remaining candidates . As proof that the retained genes include genuine drivers , we note that the list of genes recurrently lost in both human and fish MPNSTs includes four tumor suppressors , NF1 , NF2 , SMARCB1 and PTEN , that are strongly associated with the development of human Schwann cell tumors [63]–[65] . Similarly , the list of co-gained genes includes many genes ( e . g . CCND2 , ETV6 , HGF , HSF1 , KIT , MDM2 , MET and PDGFR ) whose overexpression and/or gain-of-function mutation are associated with a various human solid tumors , including MPNST . In particular , MET has been recently identified as a driver and potential therapeutic target in human MPNSTs [79] , Hsf1 has been shown to be overexpressed and required for ras pathway activation and MPNST development following Nf1 loss in mice [80] , and inhibition of KIT and PDGFR impedes the proliferation of schwannoma and MPNST cell lines and the development of xenograft-derived plexiform neurofibromas [81]–[83] . The reductive power of our analysis is illustrated by consideration of human chromosome 17q , which is amplified frequently in human MPNST , and somewhat in other tumor types . The recurrently affected region includes over 500 genes , precluding systematic gene-by-gene testing . Previous studies had flagged some preferred candidates ( e . g . TOP2A , ETV4 , BIRC5 , JMJD6 , SEPT9 , and SOCS3 ) on the basis of mRNA levels in MPNST samples and known biological function [58] , [84] . Our comparative analysis identified only 54 of the human 17q genes as being recurrently gained in zebrafish MPNSTs . We believe that this is a tractable number for systematic evaluation for cancer driver function ( see below ) . Notably , of the previously highlighted candidates , only birc5b is also gained in zebrafish tumors . Subsequent to the completion of our analysis , it was reported that knockdown , or chemical inhibition , of BIRC5 suppresses growth of MPNST cell lines in vitro and xenografts in vivo [85] . We also looked carefully at the recurrent focal CNAs identified in the zebrafish MPNSTs , because focal-focal comparisons have been highly effective when comparing tumors from humans with those of other mammals , such as mouse and dog [16]–[20] . In stark contrast to these inter-mammalian comparisons , we found that there was very little concordance between human and zebrafish focals; essentially no overlaps were observed for losses and only a few overlapping genes were identified for gains . Notably , the co-gained regions included a small array of genes ( human chromosome 4 , zebrafish chromosome 20 ) that contains KDR , PDGFR and KIT; three genes identified as cancer drivers and potential drug targets in human MPNSTs [81]–[83] . We hypothesize that the dearth of shared focal alterations between human and zebrafish reflects differences in chromosome breakability in these two organisms . Breakability is a function of unstable regions , such as fragile sites and segmental duplications , and recent studies show that human focal CNAs are enriched around such unstable regions [86] . Accordingly , the KDR/PDGFR/KIT region on human chromosome 4 is known as a rare fragile site ( FRA4B ) . Thus , we predict that the presence or absence of cross-species focal-focal conservation will be largely determined by the evolutionary conservation fragile sites . Importantly , the lack of cross-species conservation does not rule out the possibility that the species-specific recurrent focal CNAs may carry cancer drivers . To capture these candidates , we looked for the overlap of focal CNAs in one species with large CNAs in the other . This analysis yielded few intersections for losses , but identified about 200 genes for gains that likely represent higher-probability driver candidates . We were also able to apply human-zebrafish comparisons to the identification of cancer relevant miRNAs . Using stringent search criteria ( see results ) we identified a handful of miRNAs as very strong candidate drivers ( some when lost , some when gained ) . Notably , nearly all of the identified miRNA seed families have been previously associated with cancer , in some cases causally , e . g . loss of miR-15 and miR-16 [87] . Moreover , one of the microRNA families that we found to be amplified in both species , miR-10 , has specifically shown to be overexpressed in NF1-associated MPNSTs , and its inhibition slowed cell proliferation in cell lines derived from such tumors [88] . CNA analysis alone cannot pinpoint individual driver genes , especially when entire chromosomes are recurrently gained or lost . Our comparative oncogenomics approach shrinks the candidate lists dramatically , identifying about 700 commonly gained and 1400 commonly lost genes . Additionally , a focus on higher-probability candidates - those that are in focal alterations in at least one of the two species – further reduced this list to about 250 commonly gained genes . We believe that this is a sufficient small number to allow systematic testing , for example by siRNA screening in human cell lines for transformation-associated phenotypes in vitro and tumorigenic ability in xenotransplants . Additionally , our in vivo studies show that zebrafish can be used to both validate genuine cancer drivers , as exemplified by our analysis of nf2b , and rule out passenger mutations . We believe that the zebrafish has unique features that would greatly enable the testing of large candidate numbers including relatively cheap cost , large clutch size and , most important , the well advanced zebrafish community effort to recover mutants for every gene [89] . In conclusion , our study makes the case that a comparative oncogenomics approach has the potential to overcome a longstanding barrier in cancer research , the aneuploid karyotype , that has by and large remained recalcitrant to systematic analysis owing to the large number of genes simultaneously affected . This provides a new way to mine human cancer CNA data from a comparative perspective , which could accelerate the rate of cancer driver discovery by reducing the number of genes to be tested in functional studies . In principle , the methodology employed here can be readily applied to other cancer types or be expanded to incorporate additional vertebrate species , thus establishing a phylo-oncogenomic basis for analysis .
The protocol for the collection and analysis of human tumor samples was approved by the local ethical committee of the University Hospitals Leuven . All animals were housed in AAALAC-approved facilities and maintained according to protocols approved by the Massachusetts Institute of Technology Committee on Animal Care . The tumor-prone zebrafish lines carrying either the tp53M214K point mutation or insertional mutations in multiple ribosomal protein genes ( rpL13hi1016 , rpL14hi823 , rpL35hi258 , rpL36hi1807 , rpL36ahi10 , rpL7hi1061 , rpS3ahi1290 , rpS5hi577b , rpS5hi1364a , rpS7hi1034b , rpS8hi1974 , rpS11hi2799 , rpS15ahi2649 , rpS18hi1026 , and rpS29hi2903 ) have been described previously [27] , [28] . Stocks were maintained as described previously and genotypes were determined by PCR at 8 to 18 weeks of age as described in [67] . Of the zebrafish homozygous for the tp53M214K point mutation , half were triploid and were made according to previously published methods [46] . Ploidy was determined by measuring DNA content of fish tail cells using propidium iodide ( 40 µg/ml ) staining-based FACS analysis . Fish heterozygous for insertional alleles of nf2ahi3332 , mcm3hi3068 and tln1hi3093 [67] were mated to fish heterozygous for rpl36ahi10 or heterozygous or homozygous for tp53M214K to obtain sibling single and double heterozygotes for tumor onset experiments . Wild type fish , single heterozygotes , and double heterozygotes arising from these crosses were identified by PCR genotyping [28] , [67] at 6–8 weeks of age , and siblings of different genotypes were housed in adjacent tanks at similar densities to minimize environmental differences . Fish were euthanized at first observation of protruding tumors or other signs of ill health , and the presence of MPNSTs in euthanized fish was confirmed by histology . For every tumor , DNA was isolated from macroscopically dissected tumors and separately from normal ( tail ) tissue from the same fish . Based upon this paired design , CNA calls for all tumors could be determined relative to the genome of the individual fish in which it arose ( Dataset S1 and Dataset S1b ) . Genomic DNA isolation was performed as described previously [43] . Generally , sequencing and data processing was similar as described in [43] , with some differences in detail ( see Text S1 ) . The zebrafish sequencing data reported in this paper have been deposited in the NIH GEO database ( accession no . GSE38397 ) . Normalized aCGH data ( Agilent Feature Extraction output ) for 23 human MPNST samples generated previously [41] , ArrayExpress database Experiment ( ID: E-MEXP-3052 ) was converted from log10 to log2 and submitted to the circular binary segmentation algorithm [90] as implemented in the BioConductor package DNAcopy ( v1 . 16 . 0 ) , and processed with the following key parameter settings: with smoothing , undo . SD = 1 . To determine recurrent CNAs , segmented data from both zebrafish ( sequencing ) and human ( aCGH ) MPNSTs was subjected to statistical analysis using the GISTIC algorithm [47] as implemented in the JISTIC software [48] . JISTIC runs were performed in both standard and “focal” mode . Evaluation of JISTIC results ( G-scores , Q-values ) comprised an additional layer of manual curation , resulting in a final set of binary calls ( yes or no ) for recurrent large and focal copy number gains and losses ( Dataset S3 and Dataset S4 , Table S1 and Table S3 ) . Specific details regarding the JISTIC runs and the manual calls are documented in Text S1 . High-confidence human-zebrafish gene correspondences were established based on the approach described in [24] , taking advantage of conserved synteny as a guiding principle for identifying evolutionary ortholog pairs , where possible . Only genes with Ensembl protein identifiers ( release 61 ) mapping to assembled zebrafish chromosomes 1–25 and to human chromosomes 1–22 and X were considered . The details of the approach are described in Text S1 . Only genes of Ensembl gene biotype “miRNA” ( release 61 ) from assembled zebrafish chromosomes 1–25 and from human chromosomes 1–22 and X were considered . Human and zebrafish miRNA genes also present in miRBase [91] ( 662 for human , 315 for zebrafish ) were then matched using their miRBase identifiers . Matching was performed based only on the central , numeric part of the identifiers ( which denotes a particular miRNA family ) , resulting in 89 correspondence groups containing one or more miRNAs from both human and zebrafish ( Table S5B ) . These groups were then searched for cases where at least one member miRNA from each species was in a recurrent CNA of a certain polarity , with no member miRNAs in either species being in a recurrent CNA of the opposite polarity . | Cancer is essentially a genetic disease , caused by serial genetic changes including point mutations and chromosome number abnormalities . The latter leads to copy number alterations of many genes . While there are usually thousands of these genetic changes in a given tumor , only a small fraction likely contribute to cancer development . One of the major challenges is to distinguish these cancer “driver” genes from “passenger” mutations that do not contribute to the cancer phenotype . In particular , identifying the driver genes on entire chromosomes that are frequently gained or lost in tumors remains a recalcitrant problem as these alterations contain so many genes . We demonstrate that , because the chromosomal location of genes is highly scrambled between zebrafish and human , the number of passenger genes can be dramatically reduced by comparing the genes in copy number alterations found in zebrafish and human tumors . Thus , our approach dramatically narrows down the list of candidate cancer drivers , and can accelerate discovery of novel cancer drivers and pathways that could inform future targeted therapy and personalized medicine . | [
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] | [] | 2013 | Comparative Oncogenomic Analysis of Copy Number Alterations in Human and Zebrafish Tumors Enables Cancer Driver Discovery |
Acinetobacter baumannii is an emerging cause of nosocomial infections . The isolation of strains resistant to multiple antibiotics is increasing at alarming rates . Although A . baumannii is considered as one of the more threatening “superbugs” for our healthcare system , little is known about the factors contributing to its pathogenesis . In this work we show that A . baumannii ATCC 17978 possesses an O-glycosylation system responsible for the glycosylation of multiple proteins . 2D-DIGE and mass spectrometry methods identified seven A . baumannii glycoproteins , of yet unknown function . The glycan structure was determined using a combination of MS and NMR techniques and consists of a branched pentasaccharide containing N-acetylgalactosamine , glucose , galactose , N-acetylglucosamine , and a derivative of glucuronic acid . A glycosylation deficient strain was generated by homologous recombination . This strain did not show any growth defects , but exhibited a severely diminished capacity to generate biofilms . Disruption of the glycosylation machinery also resulted in reduced virulence in two infection models , the amoebae Dictyostelium discoideum and the larvae of the insect Galleria mellonella , and reduced in vivo fitness in a mouse model of peritoneal sepsis . Despite A . baumannii genome plasticity , the O-glycosylation machinery appears to be present in all clinical isolates tested as well as in all of the genomes sequenced . This suggests the existence of a strong evolutionary pressure to retain this system . These results together indicate that O-glycosylation in A . baumannii is required for full virulence and therefore represents a novel target for the development of new antibiotics .
Acinetobacter baumannii is a strictly aerobic Gram negative , non-fermentative , opportunistic pathogen . Since the 1970's , this organism has frequently been isolated from healthcare facilities , but was easily controlled with antibiotics [1] , [2] . However , many clinical isolates of A . baumannii have recently emerged with extreme resistance to antibiotics , disinfectants , and desiccation , which has permitted A . baumannii to disseminate throughout healthcare facilities worldwide [3]–[7] . One recent study showed that from 2001 to 2008 the percentage of A . baumannii isolates resistant to at least three classes of antibiotics increased from 4% to 55% , and 17% of all isolates were resistant to at least four drug classes [8] . Panresistant strains of A . baumannii have also been isolated [9] . Because of its importance as an emerging pathogen , attention towards A . baumannii has increased considerably . Most of the efforts have focused on antibiotic resistance mechanisms , but little is known about its virulence factors . A significant amount of work has been done to characterize biofilm formation , which seems to play a role in pathogenesis [10] , [11] . Other suggested virulence factors for A . baumannii include the capsule , exopolysaccharide , pili and lipopolysaccharide ( LPS ) [11]–[14] . Undoubtedly , more research is needed in order to understand A . baumannii pathogenesis . Genomic analysis of all sequenced A . baumannii strains revealed the presence of homologous genes to those encoding enzymes involved in the Neisseria meningitidis protein O-glycosylation system . Many different mucosal pathogenic bacteria require protein glycosylation for virulence , and glycoproteins seem to play a role in adhesion , motility , DNA uptake , protein stability , immune evasion , and animal colonization [15] . Whereas N-glycosylation seems to be restricted to epsilon and a few delta proteobacteria , O-glycosylation appears to be more widespread among bacteria . Gram negative bacteria including Neisseria spp . and Bacteroides fragilis employ en bloc O-glycosylation as a general system to modify multiple proteins [16] , [17] . En bloc O-glycosylation is initiated by a specialized glycosyltransferase that attaches a nucleotide-activated monosaccharide-1P to an undecaprenolphosphate ( Und-P ) lipid carrier on the inner face of the inner membrane . A series of glycosyltransferases subsequently attach additional monosaccharides to the first sugar residue on Und-PP . When the carbohydrate structure is completed , the Und-PP linked glycan is flipped to the periplasmic face , where an O-oligosaccharyltransferase ( O-OTase ) transfers the carbohydrate to selected Ser or Thr residues in acceptor proteins [18] , [19] . Campylobacter jejuni employs a similar N-glycosylation pathway to modify about 65 proteins [20] . This work demonstrates the existence of a general O-glycosylation system in A . baumannii ATCC 17978 , which is required for efficient biofilm formation and pathogenesis in the Dictyostelium discoideum , Galleria mellonella , and murine septicemia virulence models . We identified seven glycoproteins carrying a branched pentasaccharide , the structure of which has been characterized by MS and NMR techniques . O-glycosylation appears to be ubiquitous in A . baumannii , which suggests that this system might be a possible target for novel antimicrobial treatments .
We initially searched the A . baumannii ATCC 17978 genome for homologues of known O-OTases . Via a BLAST analysis , we identified a homolog to the N . meningitidis O-OTase PglL ( A1S_3176; E-value 1e-9 ) that contained a Wzy_C motif . This motif is conserved in all O-OTases , but is also found in WaaL ligases , which catalyze the transfer of the O antigen to the Lipid A core [21] , [22] . To date , only experimental determination allows the assignment of an ORF containing the Wzy_C motif as either an O-OTase or a ligase [23] . No other ORFs contained a Wzy_C motif in the A . baumannii ATCC 17978 genome . A1S_3176 is not predicted to be part of an operon [24] . We carried out mutagenesis of the A1S_3176 gene by homologous recombination to evaluate if its encoded protein is an O-Otase or a WaaL ligase . PCR and DNA sequencing confirmed the creation of an A1S_3176 knockout strain , in which the targeted gene was replaced with a gentamicin resistance cassette . There was no significant difference between the growth curves of the wild-type and the A1S_3176 mutant strains at 37°C , indicating that growth in these conditions was not affected by the mutation ( Data not shown ) . Most of the Neisseria O-glycoproteins identified to date are associated to membranes [16] . Membrane extracts from wild type and ΔA1S_3176 A . baumannii strains were analyzed by SDS-PAGE followed by PAS staining , a technique that is specific for detecting glycans , but presents low sensitivity ( Fig . 1 ) . A broad band migrating from 25 to 35 kDa was visualized in the extract of A . baumannii WT . Although the membrane protein profile between the WT and the ΔA1S_3176 strains appeared similar , the band detected via PAS stain was not visible in the mutant strain , suggesting that A1S_3176 is required for glycosylation of at least one protein ( Fig . 1B ) . The PAS-reactive band disappeared upon treatment with proteinase K , associating the glycan signal with proteinaceous material . Complementation of A1S_3176 was achieved in trans , and analysis of A . baumannii ΔA1S_3176-pWH1266-pglL membrane extract showed the reappearance of the PAS stained band . Due to the aforementioned similarity between O-OTases and ligases , we carried out a conventional LPS extraction and analyzed the extract of the different strains via SDS-PAGE . Silver stain showed no obvious differences in the carbohydrate pattern were observed , suggesting that A1S_3176 is not involved in LPS synthesis ( Fig S1 ) . To further determine if A1S_3716 effected LPS biosynthesis , whole cells were digested with proteinase K and analyzed by Silver stain and no differences were observed ( data not shown ) . However , it has been reported that the O-antigen chains of certain A . baumannii strains are not detectable by Silver stain and therefore we cannot conclusively exclude a role of A1S_3176 in LPS synthesis [25] . Together these results suggest that A1S_3176 is an O-OTase responsible for O-glycosylation in A . baumannii and will be referred from here on as PglLAb , as per its N . meningitidis ortholog . To identify the glycoprotein ( s ) in A . baumannii , we performed two dimensional in-gel electrophoresis ( 2D-DIGE ) experiments [26] . Membrane samples of both WT and ΔpglL were isolated by ultracentrifugation and the lipidic components were removed as previously described [27] . Most of the signals corresponding to the wild type ( Fig . 2A , green ) and ΔpglL ( Fig . 2B , red ) proteins co-localized in the gel ( Fig . 2C , yellow ) , indicating that these proteins were likely not glycosylated . However , a few proteins exhibited differential electrophoretic behavior ( Fig . 2 ) . These proteins spots were excised , in-gel digested , and analyzed by MALDI-TOF/TOF MS and MS/MS . We identified two separate pairs of proteins , which according to their electrophoretic migration , appeared to be larger and more acidic in the WT strain ( WT1 and WT2 ) than in the ΔpglL strain ( MT1 and MT2 ) . Mass spectrometric analysis determined WT1 and MT1 samples to be A1S_3626 protein , whereas WT2 and MT2 were identified as A1S_3744 protein . Both , A1S_3626 and A1S_3744 are annotated as hypothetical proteins , and BLAST searches yielded homologues exclusively within the Acinetobacter genus . Analysis of the MALDI-TOF MS spectra of a tryptic digest of WT1 ( A1S_3626 ) revealed a peptide fragment of 2895 . 24 Da that was absent in MT1 ( Fig . 3A ) . MALDI-TOF-TOF MS/MS of this ion determined that in the wild-type strain the peptide SAGDQAASDIATATDNASAK was linked to the glycan HexNAc-Hex-Hex- ( HexNAc ) -300 , where 300 corresponded to an unknown residue of m/z 300 , whereas the same peptide was unmodified in ΔpglL sample ( Fig S3A ) . Similarly , MALDI-TOF MS analysis of a tryptic digest of WT2 ( A1S_3744 ) revealed a peptide fragment of 3852 . 69 Da that was absent in MT2 ( Fig . 3B ) . MALDI-TOF-TOF MS/MS of the 3852 . 69 Da peak revealed the same pentasaccharide identified on A1S_3626 on the peptide ETPKEEEQDKVETAVSEPQPQKPAK ( 2822 . 33 Da ) , whereas the same peptide was unmodified in ΔpglL sample ( Fig S3B ) . . We next purified membranes from A . baumannii , digested the sample with Pronase E , and enriched glycosylated peptides using activated charcoal microspin columns . We identified a peak in the MALDI-TOF MS of 1358 . 4 m/z that was subsequently analyzed by MALDI-TOF/TOF MS/MS ( Fig . 3C ) . Manual peak annotation identified the previously characterized pentasaccharide attached to a sodiated tripeptide containing the amino acids A , T and D . Overall , these results demonstrate that PglLAb glycosylates at least two different proteins with a pentasaccharide with a preliminary structure of HexNAc-Hex-Hex- ( HexNAc ) -300 . We observed other spots possibly corresponding to proteins migrating differently in A . baumannii WT and ΔpglL strains . The most prominent was marked as WT3 , and was observed only in the WT extract ( Fig . 2C ) . Mass spectroscopy analysis determined this spot corresponded to OmpA ( A1S_2840 ) . However , manual analysis using MS/MS of WT3 indicated that OmpA was not glycosylated . Western blot analysis of whole cell extracts of the WT and ΔpglL strains revealed no difference in OmpA expression levels , which implies that manipulation of membrane samples could account for apparent differences observed in expression levels of proteins detected by 2D-DIGE ( Fig S2 ) . To determine if additional glycoproteins were present in A . baumannii ATCC 17978 , we employed ZIC-HILIC glycopeptide enrichment . Utilizing membrane extracts previously shown to contain A1S_3626 and A1S_3744 putative glycopeptides were enriched and analyzed using an LTQ-Orbitrap Velos . HCD scans containing oxonium ion were manually inspected and searched using MASCOT resulting in the identification of at least 9 different glycosylation sites on 7 different glycoproteins in A . baumannii ATCC 17978 ( Table 1; Fig . 4 ) . This peptide-centric approach enabled multiple novel glycoproteins to be identified of which six of the seven proteins are annotated as uncharacterized hypothetical proteins , with the remaining being annotated as MotB ( A1S_1193 ) . ( Table 1 ) . This demonstrates that PglLAb is able to glycosylate multiple proteins in A . baumannii ATCC 17978 . Identification of the O-glycan of A . baumannii ATCC 17978 was achieved by 2D NMR analysis . The Pronase E digested membrane protein extracts characterized in Fig . 3C were analyzed by 1H:13C HSQC 2D NMR and revealed the structure of the pentasaccharide to be β-GlcNAc3NAcA4OAc-4- ( β-GlcNAc-6- ) -α-Gal-6-β-Glc-3-β-GalNAc- , with the amino acids S , E , and A attached in any combination ( Fig S4 , Table 2 ) . β-GlcNAc3NAcA4OAc ( corresponding to m/z 300; Fig . 3 ) is an O-acetylated derivative of glucuronic acid , and can account for the more acidic migration of the WT glycoproteins compared to the ΔpglL in the 2D-DIGE analysis . It has been suggested that biofilm formation is important for A . baumannii virulence [28] . We tested if O-glycosylation has an impact on biofilm formation in this organism . Biofilm formation was detected using crystal violet staining and quantitatively analyzed by comparing the ratio between cell growth ( OD600 ) and biofilm formation ( OD580 ) at 30°C after 48 hours incubation ( Fig . 5A ) . High absorbance values corresponding to a strong ability to create biofilms ( 1 . 23±0 . 48 and 1 . 12±0 . 40 ) were obtained for the WT strain and the ΔpglL strain complemented in trans respectively . On the contrary , the ΔpglL strain and the ΔpglL strain transformed with pWH1266 exhibited severely reduced levels of absorbance ( 0 . 18±0 . 07 and 0 . 20±0 . 04 ) . Similar results were also observed at 37°C ( data not shown ) . We further characterized the role of O-glycosylation in biofilm formation by employing a flow cell system . A . baumannii strains were stained with the green fluorescent stain SYTO 9 , visualized by confocal laser scanning microscopy , and quantitative analysis of the biofilms was performed with COMSTAT . Assessment of the initial attachment after 2 hours shows that ΔpglL strain and vector control had significantly less surface coverage ( 4 . 12% and 2 . 32% respectively ) than the WT and in trans complemented strain ( 6 . 41% and 6 . 45% respectively; Fig . 5B ) . Confocal microscopy and subsequent analysis of biofilms biomass , as well as average and maximal thickness after 24 hours showed significantly higher levels for the WT compared to the ΔpglL strain , and the phenotype was restored to WT levels when pglLAb was complemented in trans ( Fig . 5 C , D , E , F; *P<0 . 05 ) . These data indicate that the A . baumannii strain defective in O-glycosylation has a severely diminished capacity to form biofilms . Two well-established virulence models for A . baumannii are the D . discoideum predation and the G . mellonella infection models [5] , [29]–[33] . D . discoideum is an unicellular amoeba that feeds on bacteria and previous work has demonstrated similarity between phagocytosis of the amoebae and mammalian phagocytes [34] . We examined if protein glycosylation was required for virulence towards D . discoideum by co-incubation of A . baumannii strains with the amoebae on SM/5 nutrient agar . A . baumannii was previously shown to inhibit amoebae growth in the presence of 1% ethanol [5] . The WT strain was virulent and inhibited all D . discoideum growth in the presence of 1% ethanol , which resulted in no plaque being formed . However the ΔpglL strain was avirulent towards the amoeba , which resulted in plaque formation in the bacterial lawn within 48 hours and clearing of the plate within 4–5 days ( Fig S5 ) . G . mellonella have been used to study many host-pathogen interactions , and have several advantages over other virulence models including the presence of both humoral ( ie . antimicrobial peptides ) and cellular immune response systems ( phagocytic cells ) [32] . Most importantly , a correlation has been established between the virulence of several bacteria in G . mellonella and mammalian models [35] , [36] . For the G . mellonella , while a similar bacterial load ( 2 . 31±1 . 13×105 CFU ) was injected for each of the strains , only the WT and complemented strains were able to kill the wax moth larvae after 36 hours , ( 20% and 0% survival ) , whereas larvae injected with ΔpglL and the ΔpglL vector control strains had significantly higher survival rates ( 100% and 80%; Fig . 6 ) . The LD50 of the WT and complemented strains were determined to be approximately 2 . 6×104 and 1 . 4×104 respectively after 36 hours . No additional killing was observed in the ΔpglL or vector control strains up to 96 hours . A PBS injected control maintained 100% survival throughout the length of the virulence assay . These results demonstrate a critical role for O-glycosylation in the virulence of A . baumannii in these two model systems . We then tested A . baumannii ΔpglL virulence in vivo using a previously described murine septicemia competition model [37]–[39] . We first determined the LD50 of A . baumannii ATCC 17978 strain by injecting groups of 5 BALB/c mice with serially diluted bacteria cultures ( Fig . 7A ) . A very small dose range between full survival and full killing was observed , and the LD50 was determined to be 6 . 49×104 CFU/mouse . The competition index ( CI ) was defined as the number of ΔpglL CFUs recovered/number of WT CFUs recovered , divided by the number of ΔpglL CFUs inoculated/number of WT CFUs inoculated . Cultures of each strain were mixed at a ratio of 1∶1 , serial diluted , and plated to determine the initial CI . 1×105 CFU of the mixed strains were injected intraperitoneally into the BALB/c mice , which were subsequently sacrificed 18 hrs post injection . The spleens were aseptically harvested , serial diluted , and plated . All of the mice had a high spleen CFU load of 3 . 75±2 . 37×108 CFU/gram and were moribund at the time of sacrifice . While the initial prescreen showed a CI of 1 . 18±0 . 21 favoring the ΔpglL mutant , the spleen counts after 18 hrs showed a CI of 0 . 10±0 . 03 ( Fig . 7B ) . This data suggests that Ab ΔpglL has a competitive disadvantage as compared to the WT strain . Together , these results indicate that A . baumannii strains lacking O-glycosylation are attenuated in mice . To determine the degree of conservation of the O-glycosylation system in Acinetobacter sp . , we searched for the presence of PglLAb homologues in different species within the genus . This genomic search showed that PglLAb was present in all the genomes analyzed with high sequence homology ( Fig S6A ) . We obtained eight clinical isolates from the University of Alberta Hospital . The isolates were identified by 16S rDNA and recA sequencing to be different species within the Acinetobacter genus ( A . baumannii , A . nosocomialis , A . pittii , and A . calcoaceticus ) . Membranes of these strains were purified and analyzed by PAS staining for the presence of glycoproteins ( Fig S6B ) . While there appears to be variation in the size and intensity of the PAS stained band , all the isolates were positive for glycoproteins , demonstrating that PglLAb was active in all these strains . This indicates that despite the plasticity of Acinetobacter sp . genomes [40] , there is a strong evolutionary pressure to retain a functional O-glycosylation system .
Isolation of MDR strains of A . baumannii is increasing at impressive rates . Despite its growing incidence as nosocomial pathogen , only a few A . baumannii virulence factors have been characterized . In this article we describe a general O-glycosylation system in A . baumannii ATCC 17978 . Although once considered rare in prokaryotes , both N- and O-glycoproteins are present in all domains of life . In most bacterial species known to synthesize glycoproteins , glycosylation is restricted to a few proteins including adhesins , flagellins or pilins [15] . Only a few “general” glycosylation systems in which more than a single protein is glycosylated have been characterized . C . jejuni N-glycosylates more than 65 proteins with the same heptasaccharide . Inactivation of the glycosylation pathway does not have an effect on growth in vitro , but does reduce adhesion and invasion to cells in culture , and affects chicken and mice colonization [41] . Neisseria gonorrhoeae is able to O-glycosylate at least 12 proteins with a highly variable glycan structure [42] . The glycan has recently been shown to be important for infection of cervical epithelial cells [43] . Bacteroides fragilis also has a general O-glycosylation system , where hundreds of proteins are predicted to be glycosylated [44] . Inactivation of the glycosylation system results in severe growth defects in vitro [17] . It was then not surprising to see that the glycosylation mutant strain was outcompeted by the wild-type strain in gnotobiotic mice colonization experiments . Seven proteins are shown to be O-glycosylated by the PglL OTase encoded by the A1S_3176 gene . Cells unable to perform protein glycosylation do not show any differential growth phenotype in vitro , while exhibiting a diminished capacity to form biofilms and reduced virulence in D . discoideum , G . mellonella , and murine septicemia pathogenesis models systems . Two glycoproteins were identified using 2D-DIGE . To our knowledge , this is the first time this technique is applied to study bacterial glycoproteomics . The structure of the glycan used to decorate these proteins in A . baumannii was determined by a combination of MS and NMR techniques . The sugar was determined to be a pentasaccharide of the formula β-GlcNAc3NAcA4OAc-4- ( β-GlcNAc-6- ) -α-Gal-6-β-Glc-3-β-GalNAc-S/T ( Fig S4 ) . The glycan contains a terminal O-acetylated glucuronic acid derivative that is negatively charged and has not previously been described . A similar monosaccharide was found in Pseudomonas aeruginosa and Bordetella pertussis [45] . Of the glycoproteins identified , only one ( A1S_1193; MotB ) has any significant homology outside of the genus Acinetobacter , with the remaining being annotated as hypothetical proteins . MotB has homology with proteins such as Pal from Haemophilus influenzae that have been shown to bind to peptidoglycan and stabilize the outer membrane [46] . Functional characterization of A . baumannii glycoproteins will be crucial to explain the phenotypes associated with lack of glycosylation . Biofilms are proposed to be a virulence factor that is associated with increased antibiotic resistance , pathogenicity , and persistence of a bacterial population [47]–[49] . We have found that O-glycosylation enhances biofilm formation by A . baumannii ATCC 17978 . Biofilm formation is a multistep process that involves an initial weak association leading to an irreversible attachment , which leads eventually to a complex maturation into sophisticated superstructures [50] . We observed by flow cell and confocal imaging that glycosylation enhances the initial attachment as well as mature biofilm mass and density . It is tempting to speculate that glycans of the glycoproteins may have a function in cell-to-cell adhesion [51] . Further work will elucidate in which aspect protein glycosylation is required for efficient biofilm formation . The basic mechanisms of phagocytic cells are used in both amoebae and mammalian macrophages . As an infection model , the amoebae D . discoideum is considered a primitive macrophage . D . discoideum cells were unable to predate on A . baumannii WT lawns , but were able to efficiently predate on lawns of the glycosylation-deficient bacteria . It is uncertain how protein O-glycosylation protects A . baumannii from D . discoideum but we can hypothesize that glycosylation may help in the inhibition of phagocytosis by the amoebae , and/or prevent bacterial lysis by reactive oxygen species produced by the amoebae [52] . Another possibility is that glycosylation of certain proteins is required to interfere with bacterial degradation and intracellular vesicle transport and/or fusion , as shown for Legionella [53] . We also analyzed if protein O-glycosylation plays a role in pathogenesis in G . mellonella caterpillars . This model system has been recently shown to recreate the mammalian humoral immune system , with similar antimicrobial peptides , toll-like receptors , and the complement-like mechanism of melanization [54] . Similar to the D . discoideum model , A . baumannii ΔpglL strain was unable to kill G . mellonella . O-glycosylation could mediate killing of the larvae by stabilizing the bacterial outer membrane of A . baumannii , which could prevent killing by antimicrobial peptides . The negative charges of the glycan chains could play a role in this process . Alternatively , glycosylation could mask signals detected by the larvae or prevent phagocytosis by G . mellonella haemocytes , among other possibilities . The involvement of glycoproteins in virulence is further supported by the demonstration that the ΔpglL strain is outcompeted by wild type bacteria in a murine septicemia model . Thus , our experiments showed that glycosylation is critical for virulence in three different model systems . Further work using strains carrying mutations in individual glycoproteins will help to elucidate the exact role of protein glycosylation in pathogenesis . Glycoproteins are usually immunodominant in bacteria , and therefore , the glycoproteins identified in this study may be the base of future vaccine formulations and diagnostic methods . The prevalence of the O-glycosylation machinery in Acinetobacter sp . , together with its role in virulence in the three different pathogenesis models , suggest that protein O-glycosylation represents a novel target for the development of antibiotics that could be key to prevent further dissemination of this emerging human pathogen , which has become a major threat to our healthcare systems .
The bacterial strains and plasmids used in this study are listed in Table 3 . A . baumannii strains were grown in Luria Bertani broth/agar at 37°C . The antibiotics ampicillin ( Ap ) 100 µg/mL , gentamicin ( Gm ) 50 µg/mL , and tetracycline ( Tc ) 5 µg/mL were added for selection as needed . In order to create a ΔpglL via homologous recombination , we cloned a ∼3500 bp fragment consisting of ∼1000 bp upstream and downstream of A1S_3176 into pEXT20 using primers K/O pglLfwd and K/O pglLrev from A . baumannii ATCC 17978 genomic DNA ( Table 3 ) . The construct was subsequently subcloned from pEXT20 into pFLP2 . We then digested pFLP2-pglL with PsiI and replaced A1S_3176 with a SmaI excised Gentamicin resistance cassette ( aacC1 ) from pSPG1 [55] . The plasmid pFLP2 does not replicate in A . baumannii ATCC 17978 . This final construct was transformed into electro-competent A . baumannii WT cells and selection for a single recombination event was analyzed using media supplemented with gentamicin . Positive colonies were grown in 5 mL LB at 37°C for 72 hours , with 1/1000 re-inoculations into fresh LB media every 24 hour period . After 72 hours , the liquid culture was plated on LB agar supplemented with gentamicin and 10% sucrose to select for a double recombination event . Colony PCR using both internal and external primers showed the allelic exchange of A1S_3176 with aacC1 , generating a knockout mutant of A . baumannii pglL . Bacterial cultures were pelleted by centrifugation for 15 mins at 10 , 000×g , washed with PBS , resuspended in PBS , and subsequently lysed by French Press . Unbroken cells were pelleted by centrifugation for 15 mins @ 5 , 000×g . The supernatant was ultracentrifugated for 1 hr @ 100 , 000×g ( 4°C ) to pellet cell membrane . Samples were quantified by Bradford protein quantification ( Biorad ) and analyzed on a 12% SDS-PAGE . The PAS stain protocol used was previously described [56] . LPS was extracted according to Marolda et al [57] . Samples were resuspended in 50 µL of dH20 and analyzed by Silverstain on a 15% SDS-PAGE . Lipid-free membranes were obtained for 2D-DIGE analysis according to [27] . The material was resuspended in: 6 . 5 M Urea , 2 . 2 M thiourea , 1% w/v ASB-14 , 5 mM Tris-HCl pH 8 . 8 , 20 mM DDT , 0 . 5% IPG buffer . The samples were labeled using CyDye minimal labeling protocol ( Amersham Biosciences ) . A . baumannii WT membranes were labeled with Cy5 and ΔpglL were labeled with Cy3 . Samples were quantified by 2D-Quant kit ( GE Healthcare ) and 600 µg of each WT and ΔpglL membranes were mixed in Destreak solution ( GE Healthcare ) to a final volume of 450 µL . 24 cm pH 3–11 NL IPG strips were simultaneously rehydrated and sample loaded for 24 hrs at room temperature in the dark . Isoelectric focusing was done using the Ettan IPGphor system for a total of 56 , 000 Vhr in the dark . The strip was then incubated in 10 mL of equilibration solution ( 2% SDS , 50 mM Tris-HCl , 6 M Urea , 30% ( v/v ) glycerol , 0 . 002% bromophenol blue ) for 15 mins with 100 mg DTT and then 10 mL equilibration solution with 250 mg iodoacetamide . The strip was then sealed into a DALT 12 . 5 precast gel with 0 . 5% agarose . The system was run at 2 . 5 W/gel for 30 mins , the 17 W/gel until the dye front exited the bottom . The gel was visualized using FLA-5000 ( FujiFilm ) and the images analyzed by ImageQuant 5 . 0 . The gel was subsequently stained with Coomassie brilliant blue , and individual spots excised and prepared for mass spectrometry . Samples were in gel tryptically-digested and the peptides were desalted using C18 Zip-Tips and eluted with 60% CH3CN/40% H2O . Samples were spotted on a Bruker Daltonics MTP ground steel or Bruker Daltonics MTP AC600 Anchorchip target plate and air dried . 1 µL for ground steel and 0 . 4 µL for the AC600 target of 2 , 5-dihydroxybenzoic acid ( DHB , 10 mg/mL in 30% H2O , 70% CH3CN ) was spotted on top and allowed to dry . Mass spectra were obtained in the positive mode of ionization using a Bruker Daltonics ( Bremen , GmbH ) UltrafleXtreme MALDI TOF/TOF mass spectrometer . The FlexAnalysis software provided by the manufacturer was used for analysis of the mass spectra . The MS/MS spectra were obtained manually . The exact m/z used as the precursor m/z for MS/MS was determined first on a Bruker Daltonics ( Billerica , MA ) Apex Qe MALDI FTICR MS instrument and the MS/MS spectrum was automatically re-calibrated based upon this m/z . Lipid free membrane extracts were digested for 72 hrs at 37°C with 2 µL Pronase E ( 20 mg/mL ) being freshly added every 24 hrs . Glycosylated peptides were enriched using Active Charcoal Micro SpinColumn ( HARVARD Apparatus ) Briefly , the column was prewashed 3× with 400 µL of 0 . 1% TFA in of 80% ACN and 20% ddH2O and centrifuged at 500 RCF for 2 minutes . The column was equilibrated 3× using 400 µL of H2O . The sample was loaded 3× at 500 RCF for 2 minutes . The column was washed 2× with 200 µL of ddH2O at 500 RCF for 2 minutes . The glycan was eluted 3× with 100 µL 0 . 1% TFA in 50% ACN and 50% H2O at 1000 RCF for 2 minutes . The sample was dried by vacuum centrifugation and analyzed by MALDI-TOF/TOF MS and MS/MS . For NMR analysis glycoproteins were digested with a large excess of proteinase K at pH 8 ( adjusted by addition of ammonia ) at 37°C for 48 hours . Products of digestion or free oligosaccharides were separated on Sephadex G-15 column ( 1 . 5×60 cm ) and each fraction eluted before salt peak was dried and analyzed by 1H NMR . Fractions containing desired products were separated by anion exchange chromatography on Hitrap Q column ( 5 mL size , Amersham ) and glycan eluted with a linear gradient of NaCl ( 0–1 M , 1 h ) . Desalting was performed on Sephadex G15 prior to analysis by NMR . NMR experiments were carried out on a Varian INOVA 600 MHz ( 1H ) spectrometer with 3 mm gradient probe at 25°C with acetone internal reference ( 2 . 225 ppm for 1H and 31 . 45 ppm for 13C ) using standard pulse sequences DQCOSY , TOCSY ( mixing time 120 ms ) , ROESY ( mixing time 500 ms ) , HSQC and HMBC ( 100 ms long range transfer delay ) . AQ time was kept at 0 . 8–1 sec for H-H correlations and 0 . 25 sec for HSQC , 256 increments was acquired for t1 . Assignment of spectra was performed using Topspin 2 ( Bruker Biospin ) program for spectra visualization and overlap . Monosaccharides were identified by COSY , TOCSY and NOESY cross peak patterns and 13C NMR chemical shifts . Aminogroup location was concluded from high field signal position of aminated carbons ( CH at 45–60 ppm ) . Connections between monosaccharides were determined from transglycosidic NOE and HMBC correlations . Dried membrane protein-enriched fractions were resuspended in 6 M urea , 2 M thiourea , 40 mM NH4HCO3 . Samples were reduced , alkylated , digested with Lys-C ( 1/200 w/w ) and then trypsin ( 1/50 w/w ) as described previously [20] . Digested samples were then dialyzed against ultra-pure water overnight using a Mini Dialysis Kit with a molecular mass cut off of 1000 Da ( Amersham Biosciences , Buckinghamshire , UK ) and on completion were collected and lyophilized . ZIC-HILIC enrichment was performed according to [20] with minor modifications . Micro-columns composed of 10 µm ZIC-HILIC resin ( Sequant , Umeå , Sweden ) were packed into P10 tips on a stage of Empire C8 material ( Sigma ) to a bed length of 0 . 5 cm and washed with ultra-pure water prior to use . Dried digested samples were resuspended in 80% acetonitrile ( ACN ) , 5% formic acid ( FA ) and insoluble material removed by centrifugation at 20 , 000×g for 5 min at 4°C . Samples were adjusted to a concentration of 2 µg/µL and 100 µg of peptide material loaded onto a column and washed with 10 load volumes of 80% ACN , 5% FA . Peptides were eluted with 3 load volumes of ultra-pure water into low-bind tubes and concentrated using vacuum centrifugation . ZIC-HILIC fractions were resuspended in 0 . 1% FA and loaded onto a Acclaim PepMap 100 µm C18 Nano-Trap Column ( Dionex Corporation , Sunnyvale , CA ) for 10 min using a UltiMate 3000 intelligent LC system ( Dionex Corporation ) . Peptides were eluted and separated on 20 cm , 100 µm inner diameter , 360 µm outer diameter , ReproSil – Pur C18 AQ 3 µm ( Dr . Maisch , Ammerbuch-Entringen , Germany ) in house packed column . Enriched peptides derived from tryptic digests were analysed using an LTQ-Orbitrap Velos ( Thermo Scientific , San Jose CA ) . Samples were eluted using a gradient from 100% buffer A ( 0 . 5% acetic acid ) to 40% buffer B ( 0 . 5% acetic acid , 80% MeCN ) over 120 mins at a constant flow of 200 nL/min enabling the infusion of sample in the instrument using ESI . The LTQ-Orbitrap Velos was operated using Xcalibur v2 . 2 ( Thermo Scientific ) with a capillary temperature of 200°C in a data-dependent mode automatically switching between MS ion trap CID and HCD MS-MS . For each MS scan , the three most abundant precursor ions were selected for fragmentation with CID , activation time 30 ms and normalized collision energy 35 , followed by HCD , activation time 30 ms and normalized collision energy 45 . MS resolution was set to 60 , 000 with an ACG of 1e6 , maximum fill time of 500 ms and a mass window of m/z 600 to 2000 . MS-MS fragmentation was carried out with an ACG of 3e4/2e5 for CID/HCD and maximum fill time of 100 ms/500 ms CID/HCD . For HCD events an MS resolution of 7500 was set . A total of six HILIC enrichments were performed and analysis by the above protocol . Raw files were processed within Proteome Discover version 1 . 0 Build 43 ( Thermo Scientific ) to generate . mgf files . To identify possible glycopeptides within exported scans , the MS-MS module of GPMAW 8 . 2 called ‘mgf graph’ was utilized . This module allowed the identification of all scan events within the generated . mgf files containing the diagnostic oxonium m/z 301 . 10 ion . These scan events were manually inspected and identified as possible glycopeptides based on the presence of the deglycosylated peptide ion with a tolerance of 20 ppm . To facilitate glycopeptide assignments from HCD scan events , ions below the mass of the predicted deglycosylated peptides were extracted with Xcalibur v2 . 2 using the Spectrum list function . Ions with a deconvoluted mass above the deglycosylated peptide mass and ions corresponding to known carbohydrate oxonium ions such as 204 . 08 and 366 . 14 were removed in a similar approach to post-spectral processing of ETD data [58] , [59] . MASCOT v2 . 2 searches were conducted via the Australasian Proteomics Computational Facility ( www . apcf . edu . au ) with the Proteobacteria taxonomy selected . Searches were carried out with a parent ion mass accuracy of 20 ppm and a product ion accuracy of 0 . 02 Da with no protease specificity , instrument selected as MALDI-QIT-TOF ( use of this instrumentation setting was due to the observation of multiple internal cleavage products , extensive NH3 and H2O loss from a , b , y ions , which are all included within this scoring setting ) as well as the fixed modification carbamidomethyl ( C ) and variable modifications , oxidation ( M ) and deamidation ( N ) . An ion score cut-off of 20 was accepted and all data were searched with the decoy setting activated generating a zero false positive rate generated against the decoy database . Cultures were grown overnight and re-inoculated at an OD600 0 . 05 in 100 µL into replicates in a 96 well polystyrene plate ( Costar ) . The cultures were subsequently grown without shaking for 48 hours at 30°C . Bacterial growth was determined by measuring the absorbance at OD600 nm . The cultures were removed and the wells washed with ddH20 , followed by the addition of 100 µL of 1% crystal violet in ethanol to stain the cells . The plate was incubated for 30 mins with gentle agitation , then thoroughly washed with ddH20 , and the stained biofilms solubilized with 100 µL of 2% SDS for 30 minutes with gentle agitation . The amount of biofilm formed was quantified by measuring the absorbance at OD580 nm . The data was normalized using the ratio between OD580/OD600 . Flow cell experiments and fluorescent staining were performed as described previously by Seper et al . [60] . Briefly , the respective overnight cultures were adjusted to OD600 = 0 . 1 using 50-fold diluted LB ( 2% ) . Per channel , approximately 250 µl of the dilutions were inoculated . After static incubation for 2 h , flow of pre-warmed 2% LB ( 37°C ) was initiated ( 3 ml/h ) . Biofilms were allowed to form for a time period of 24 h and were stained with SYTO 9 ( Invitrogen ) for visualization . Images of attached bacteria or biofilms were acquired using a Leica SP5 confocal microscope ( Leica Microsystems , Mannheim , Germany ) with spectral detection and a Leica HCX PL APO CS 40× oil immersion objective ( NA 1 . 25 ) . For the SYTO 9 signal , the excitation wavelength was set at 488 nm and fluorescence emission was detected between 500–530 nm . Optical sections were recorded in 0 . 2 µm steps . For two-dimensional image visualization the Leica LAF and for three-dimensional image processing the AMIRA software ( direct volume rendering with VOLREN module ) was used . Quantification of image stacks was performed using COMSTAT ( http://www . comstat . dk ) [61] ( M . Vorregaard et al . , pers . comm . ) . For COMSTAT analysis at least six image stacks from three independent experiments were used . This assay was performed essentially as described by [62] . Briefly , midlogarithmic cultures of D . discoideum were mixed with overnight cultures of bacteria to a final concentration of 1×103 amoebae ml−1 . 0 . 2 ml of the suspension was then plated on SM/5 agar containing 1% ethanol . Plates were incubated at room temperature and monitored for D . discoideum plaques for 3–5 days . Wild type bacteria are toxic to the amoebae . Appearance of plaques indicates attenuation . This assay was performed as previously described [32] . Galleria mellonella larvae were bred in sterile conditions at 37°C by Dr . Andrew Kedde ( University of Alberta ) . After injection of bacteria , caterpillars were incubated at 37°C , and the number of dead caterpillars was scored every 5 hours . Caterpillars were considered dead when they were nonresponsive to touch . This experiment is a representative of 3 biological replicates . A murine model of disseminated sepsis using BALB/c mice ( 16–20 grams ) was used for bacterial challenge [63] , [64] . A . baumannii strains were grown for 18 h at 37°C in Luria broth with appropriate antibiotics and adjusted to the appropriate concentration in physiologic saline . Inoculums were prepared by mixing the bacterial suspensions 1∶1 ( v∶v ) with a 10% solution ( w/v ) of porcine mucin ( Sigma , St . Louis , MO ) which increases the infectivity of A . baumannii , allowing for a lower concentration of bacteria to be used [65]–[67] . Mice were injected intraperitoneally with 0 . 2 ml of the bacterial/mucin inoculums . Bacterial concentrations were determined by plating dilutions on Luria agar . The wild type strain lethal dose for 50% of animals was determined by the limit test where groups of 5 mice were infected with dilutions of bacteria , at a range of concentrations within 2 logs of a concentration of bacteria that had previously been shown to be lethal with this species of bacteria using a disseminated sepsis model . An in vivo competition assay was used to compare fitness between the wt and ΔpglL strains [37]–[39] . Liquid cultures containing individual strains were diluted and plated on LB agar . Mixed inoculums were established by mixing equal proportions of strains based on the OD600 . Once mixed the inoculums were serially diluted and plated on LB agar and LB agar with gentamycin to select for the ΔpglL . The expected ratio of CFU on LB compared to CFU on LB with gentamycin was 2∶1 . For bacterial competition experiments in vivo an animal model of sepsis was used . Groups of 3 BALB/c female 16–20-g mice were inoculated intraperitoneally with 1×105 CFUs of mixed inoculums ( 50% of each strain ) . Groups of 3 mice were sacrificed at 18 h after inoculation . Mice at 18 hours of infection were showing clinical signs of illness and were often moribund . Spleens were aseptically removed , weighed , and homogenized via passage through a cell strainer ( BD falcon 70 um cell strainer ) in physiological saline before plating serial log dilutions on Luria agar plates for bacterial quantification . If the two strains had equal fitness in vivo the ratio established prior to infection should be maintained . All procedures and experiments involving animals ( mice ) were approved by the Institutional Animal Care Committee of Defence Research and Development Canada Suffield ( protocol # CWS-08-1-1-1 ) , and were in accordance with guidelines from the Canadian Council of Animal Care . | Multidrug resistant ( MDR ) Acinetobacter baumannii strains are an increasing cause of nosocomial infections worldwide . Due to the remarkable ability of A . baumannii to gain resistance to antibiotics , this bacterium is now considered to be a “superbug” . A . baumannii strains resistant to all clinically relevant antibiotics known have also been isolated . Although MDR A . baumannii continues to disseminate globally , very little is known about its pathogenesis mechanisms . Our experiments revealed that A . baumannii ATCC 17978 has a functional O-linked protein glycosylation system , which seems to be present in all strains of A . baumannii sequenced to date and several clinical isolates . We identified seven glycoproteins and elucidated the structure of the glycan moiety . A glycosylation-deficient strain was generated . This strain produced severely reduced biofilms , and exhibited attenuated virulence in amoeba , insect , and murine models . These experiments suggest that glycosylation may play an important role in virulence and may lay the foundation for new drug discovery strategies that could stop the dissemination of this emerging human pathogen , which has become a major threat for healthcare systems . | [
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] | 2012 | Identification of a General O-linked Protein Glycosylation System in Acinetobacter baumannii and Its Role in Virulence and Biofilm Formation |
Antibody-dependent enhancement ( ADE ) of Ebola virus ( EBOV ) infection has been demonstrated in vitro , raising concerns about the detrimental potential of some anti-EBOV antibodies . ADE has been described for many viruses and mostly depends on the cross-linking of virus-antibody complexes to cell surface Fc receptors , leading to enhanced infection . However , little is known about the molecular mechanisms underlying this phenomenon . Here we show that Fcγ-receptor IIa ( FcγRIIa ) -mediated intracellular signaling through Src family protein tyrosine kinases ( PTKs ) is required for ADE of EBOV infection . We found that deletion of the FcγRIIa cytoplasmic tail abolished EBOV ADE due to decreased virus uptake into cellular endosomes . Furthermore , EBOV ADE , but not non-ADE infection , was significantly reduced by inhibition of the Src family protein PTK pathway , which was also found to be important to promote phagocytosis/macropinocytosis for viral uptake into endosomes . We further confirmed a significant increase of the Src phosphorylation mediated by ADE . These data suggest that antibody-EBOV complexes bound to the cell surface FcγRIIa activate the Src signaling pathway that leads to enhanced viral entry into cells , providing a novel perspective for the general understanding of ADE of virus infection .
Ebola virus ( EBOV ) , a member of the family Filoviridae , causes severe hemorrhagic fever in humans and nonhuman primates , with human case fatality rates of up to 90% [1] . EBOV expresses a glycoprotein ( GP ) that is the only viral surface protein and important for both receptor binding and membrane fusion [2 , 3] . EBOV entry is initiated by viral attachment to cell surface molecules such as T-cell immunoglobulin and mucin domain 1 ( TIM-1 ) and C-type lectins [4 , 5] , followed by internalization of the virus particle into cells via macropinocytosis [6–8] . In the late endosome , EBOV GP is cleaved by host proteases such as cathepsins L and B [9] , exposing the GP receptor binding site that then binds to the receptor , Niemann-Pick C1 ( NPC1 ) , followed by membrane fusion [10 , 11] . In addition to the direct interaction between GP and host cell receptors , it has been demonstrated that EBOV exploits some GP-specific antibodies for its entry into cells , leading to increased infectivity in vitro [12 , 13] . This phenomenon has been described for a number of viruses and is known as antibody-dependent enhancement ( ADE ) [14–17] . For some of these viruses , ADE has become a great concern to disease control by vaccination . Particularly , convalescent human sera have been shown to contain ADE antibodies [12 , 13] , raising concerns about potential detrimental effects of passive immunization with convalescent human sera , which is currently under consideration for treatment of Ebola virus disease . Importantly , it was recently demonstrated that therapeutic treatment with convalescent sera having in vitro neutralizing activities was not sufficient for protection against EBOV infection in nonhuman primates [18] . Although ADE was not evaluated in vitro and any enhanced pathogenicity in the treated animals was not observed , it might be possible that ADE antibodies counterbalanced the neutralizing activity as suggested previously [17] . Two distinct pathways of EBOV ADE , one mediated by Fc receptors and the other by complement component C1q and its ligands , are known [13 , 17] . In particular , the Fcγ receptor ( FcγR ) is commonly involved in ADE of virus infections [19 , 20] . However , the molecular mechanisms underlying ADE-mediated virus entry through FcγR are not fully understood . Three classes of FcγR , FcγRI ( CD64 ) , FcγRII ( CD32 ) , and FcγRIII ( CD16 ) , are expressed in various human immune cells such as dendritic cells , monocytes , and B lymphocytes [21] . Among these FcγRs , FcγRII is a key molecule for EBOV ADE of infection in human leukemia K562 cells [17] . Human FcγRII exists in two isoforms , FcγRIIa and FcγRIIb , which differ in their signal peptides and cytoplasmic tails . FcγRIIa is the active form of FcγRII and contains an immunoreceptor tyrosine-based activation motif ( ITAM ) in its cytoplasmic tail [21] . The cytoplasmic tail of FcγRIIa is known to contribute to the activitation of two structurally and functionally distinct protein-tyrosine kinase ( PTK ) classes , the sarcoma ( Src ) family PTKs [22 , 23] and spleen tyrosine kinase ( Syk ) [24] . In addition , Syk is reported to participate in activation of enzymes such as rat sarcoma ( Ras ) , phosphatidylinositol 3-kinase ( PI3K ) , and Bruton’s tyrosine kinase ( Btk ) [21 , 25] . These signaling pathways are known to be important for the induction of phagocytic and endocytic processes to internalize immune complexes [21 , 25 , 26] . In this study , we focused on the role of FcγRIIa and investigated the contribution of FcγRIIa-mediated signaling to the ADE of EBOV infection . We show that Src family PTKs are essential for EBOV ADE-mediated entry . Our data indicate that binding of antibody-virus complexes to the cell surface FcγRIIa triggers phosphorylation of Src family PTKs and activates subsequent signaling pathways , leading to enhanced viral uptake through phagocytosis and/or macropinocytosis .
To investigate the role of FcγRIIa and , in particular , the importance of its cytoplasmic tail in EBOV ADE , we compared the functions of wild-type FcγRIIa and a deletion mutant of FcγRIIa lacking its cytoplasmic tail ( FcγRIIaΔCT ) . Both molecules were expressed on Jurkat T cells , which are known to be poorly permissive for EBOV infection [27] and lack this Fc receptor [28] . Jurkat T cells were transduced with full-length FcγRIIa or FcγRIIaΔCT genes using a retrovirus vector ( Fig 1A and 1B ) and subsequently infected with vesicular stomatitis virus ( VSV ) pseudotyped with EBOV GP ( VSV-EBOV GP ) and infectious EBOV in the presence or absence of the GP-specific monoclonal antibody ( MAb ) ZGP12/1 . 1 , which is known to induce EBOV ADE [12] ( Fig 1C and 1D ) . We found that viral infectivity was almost undetectable in naive and control vector-transduced Jurkat T cells but the expression of wild-type FcγRIIa significantly enhanced the infectivity of VSV-EBOV GP and EBOV in the presence of ZGP12/1 . 1 , though not control IgG ( CTR IgG ) . Interestingly , the infection rate of FcγRIIaΔCT-expressing cells was significantly lower than that of cells expressing wild-type FcγRIIa . These results indicated that the FcγRIIa-MAb complex functioned as a receptor-like molecule on this poorly permissive cell line and efficiently promoted infection through the ADE of EBOV entry . More importantly , the results suggested that signaling pathways via the FcγRIIa cytoplasmic tail were likely involved in the ADE of EBOV entry into cells . FcγRIIa is known to modulate phagocytosis/macropinocytosis through signaling pathways via its cytoplasmic tail [29 , 30] . Therefore , to analyze viral binding and intracellular uptake in more detail , we produced lipophilic tracer ( DiI ) -labeled virus-like particles ( VLPs ) consisting of the major EBOV structural proteins , GP , matrix protein ( VP40 ) , and nucleoprotein ( NP ) , and monitored the localization of VLPs in each transduced Jurkat T cell line ( Fig 2 ) . The number of VLPs attached to the surface of naive and empty vector-transduced Jurkat T cells was not significantly different irrespective of the presence of CTR IgG and ZGP12/1 . 1 ( Fig 2A and 2C ) . In contrast , the attachment of VLPs was significantly enhanced to similar extents in Jurkat T cells expressing FcγRIIa and FcγRIIaΔCT in the presence of ZGP12/1 . 1 but not CTR IgG ( Fig 2A and 2C ) , suggesting that the FcγRIIa ectodomain expressed on Jurkat T cells had the ability to increase the VLP attachment mediated by ZGP12/1 . 1 . Next , we assessed the number of VLPs incorporated into intracellular vesicles along with Alexa Fluor 647 ( Alexa647 ) -labeled dextran Mw 10 , 000 ( Dx10 ) , a specific probe for visualizing phagocytotic and macropinocytotic vesicles [6 , 31] . After incubation for 2 h , ZGP12/1 . 1-treated VLPs efficiently colocalized with Dx10 in Jurkat T cells expressing wild-type FcγRIIa , but not in cells expressing FcγRIIaΔCT ( Fig 2B and 2D ) . Viral uptake was not observed drastically in the absence of FcγRIIa and ZGP12/1 . 1 . Furthermore , the number and size of Dx10-positive vesicles incorporated into Jurkat T cells expressing FcγRIIaΔCT were significantly smaller than those in cells expressing FcγRIIa , indicating the importance of the FcγRIIa cytoplasmic tail in activating the phagocytosis/macropinocytosis ( Fig 2B and 2E ) . These data suggested that the ADE infection of FcγRIIa-expressing Jurkat T cells was associated with enhanced viral uptake into cellular vesicles , most likely due to the activation of FcγRIIa-mediated signaling via its cytoplasmic tail . To identify the intracellular signaling pathway involved in the ADE of EBOV entry , we analyzed the effects of different inhibitors of signaling pathways in K562 cells , which naturally express FcγRIIa . Consistent with previous studies [17 , 32] , K562 cells were permissive to VSV-EBOV GP and EBOV infections , and viral infection rates were significantly enhanced in the presence of ZGP12/1 . 1 ( S1A and S1B Fig ) . We then tested inhibitors of Syk and Src family PTKs ( R788 and PP2 , respectively ) as these PTKs are known to be principally involved in signaling pathways downstream of FcγRIIa , and in particular to play important roles in inducing FcγR-mediated phagocytosis/macropinocytosis [26 , 33] . We found that the ADE of VSV-EBOV GP infection was significantly reduced in K562 cells treated with these inhibitors in a dose-dependent manner . In contrast , only a limited reduction was seen in non-ADE infection at the highest concentrations of the inhibitors ( Fig 3 ) . The ADE-specific inhibitory effect was more prominent in cells treated with PP2 than in those treated with R788 . Since Syk is reported to participate in the activation of signaling through PI3K , Btk , and Ras , we further examined which pathways downstream of Syk contributed to the ADE of VSV-EBOV GP infection using specific inhibitors of PI3K ( LY294002 ) , Btk ( LFM-A13 ) , and Ras ( Manumycin A ) ( Fig 3 ) . However , both ADE and non-ADE infections by VSV-EBOV GP were dose-dependently reduced by LY294002 and Manumycin A , respectively . LFM-A13 showed little effect on the infectivity of VSV-EBOV GP . Subsequently , we confirmed the effects of these inhibitors using infectious EBOV . Consistent with the data for VSV-EBOV GP , PP2 selectively reduced the ADE , but not the non-ADE infection . Interestingly , R788 showed no effects on the ADE of EBOV infection and rather enhanced the non-ADE infection . LFM-A13 slightly reduced both the ADE and the non-ADE infections , whereas LY294002 and Manumycin A did not inhibit the ADE infection , though Manumycin A slightly inhibited the non-ADE infection . To further investigate the role of Src- and Syk-mediated signaling in EBOV ADE , we generated Src and Syk knockdown K562 cells . K562 cells were transduced with retroviral vectors expressing small hairpin RNAs ( shRNAs ) for silencing Src or Syk genes ( Fig 4A and 4B ) and infected with VSV-EBOV GP in the presence or absence of ZGP12/1 . 1 ( Fig 4C ) . We found that transduced cells stably expressing Src shRNAs ( shSrc3 and shSrc4 ) showed approximately 50% reduction in protein levels ( Fig 4A ) and ZGP12/1 . 1-mediated ADE was significantly decreased in these cell lines ( Fig 4C ) . In contrast , no significant difference was seen between ADE ( ZGP12/1 . 1 ) and non-ADE ( CTR IgG ) infections in Syk knockdown cells although 2 of the Syk shRNAs ( shSyk3 and shSyk4 ) significantly reduced the expression of the Syk protein ( Fig 4B and 4C ) . These results demonstrated that FcγRIIa-mediated signaling through the activation of Src family PTKs contributed to the ADE of EBOV infection , but Syk-related signaling including PI3K , Btk , and Ras did not seem to be specifically involved . We further tested the effect of PP2 in K562 cell lines stably expressing dendritic cell-specific ICAM-3-grabbing non-integrin ( DC-SIGN ) or human macrophage galactose-type C-type lectin ( hMGL ) , both of which have been shown to act as attachment receptors for EBOV [32 , 34] , and found that PP2 had limited effects on the infectivity of VSV-EBOV GP in these cell lines ( S2 Fig ) . To directly detect the activation of Src family PTKs , we quantified the phosphorylation levels of Src in K562 cells ( Fig 5 ) . We found no significant difference in the cells inoculated with intact VLPs alone at each time point . Likewise , inoculation of CTR IgG-treated VLPs did not enhance Src phosphorylation levels . However , a significant increase of the Src phosphorylation was detected at 30 and 60 min after K562 cells were exposed to ZGP12/1 . 1-treated VLPs ( Fig 5 left ) . Furthermore , the enhanced phosphorylation was completely blocked by the Src family PTK inhibitor , PP2 ( Fig 5 right ) . These findings suggested that Src were activated by the interaction of the VLP-ZGP12/1 . 1 complex with FcγRIIa . To further characterize the role of the Src family PTK-dependent signaling in the ADE of EBOV infection , we analyzed the effect of PP2 on the attachment and uptake of DiI-labeled VLPs using K562 cells . We first compared the number of VLPs attached to the cell surface among untreated , CTR IgG- , and ZGP12/1 . 1-treated VLPs . Since the overexpression of FcγRIIa in Jurkat T cells increased the attachment of VLPs to the cell surface in the presence of ZGP12/1 . 1 ( Fig 2 ) , we hypothesized that ZGP12/1 . 1 would enhance the VLP attachment to K562 cells . However , the number of VLPs attached to the cell surface was not significantly different in the presence or absence of ZGP12/1 . 1 ( Fig 6A left and 6C ) , and was not affected by the PP2 treatment ( Fig 6A right and 6C ) , indicating that EBOV ADE in K562 cells did not result from increased viral attachment to the cell surface . For the visualization of the VLP uptake into endosomes , K562 cells expressing enhanced green fluorescent protein fused to Rab7 ( eGFP-Rab7 ) , a late endosome marker , were used to analyze colocalization of eGFP-Rab7 and internalized VLPs . We found that ZGP12/1 . 1-treated VLPs were efficiently colocalized with eGFP-Rab7 in K562 cells , whereas only 10–20% colocalization was seen in the cells inoculated with untreated or CTR IgG-treated VLPs ( Fig 6B left , 6D and S3A Fig ) . We further found that the enhanced colocalization of eGFP-Rab7 and ZGP12/1 . 1-treated VLPs was clearly blocked by the PP2 treatment ( Fig 6B right , 6D and S3B Fig ) . These results indicated that the ADE of EBOV entry into K562 cells was dependent on the Src family PTK activation leading to increased uptake of viral particles into cells . Finally , we investigated whether the ADE of EBOV entry into K562 cells depended on phagocytosis/macropinocytosis , which have been shown to be major pathways of the EBOV entry through non-ADE pathways [6–8] . We used Dx10 to visualize phagocytotic and macropinocytotic vesicles in K562 cells and analyzed its colocalization with VLPs . We found that approximately 70% of the ZGP12/1 . 1-treated VLP signals were overlapped with Dx10 in intracellular vesicles ( Fig 7A and 7C and S4A Fig ) . Furthermore , the colocalization of Dx10 and ZGP12/1 . 1-treated VLPs was significantly blocked by the PP2 treatment ( Fig 7B and 7C and S4B Fig ) . To confirm that these observations were EBOV-specific , we further analyzed DiI-labeled SUDV VLPs and found that ZGP12/1 . 1 affected neither attachment/uptake of SUDV VLPs nor Dx10 uptake . ( S5 Fig ) . These results suggested that the surface-bound VLP-ZGP12/1 . 1 complex was incorporated into cells through Src family PTK-dependent phagocytosis and/or macropinocytosis during the ADE of EBOV entry .
It is well established that after the attachment of virus particles to cell surface receptors a variety of signaling pathways are activated through tyrosine and phosphoinositol kinases , and the subsequent cellular events such as endocytosis , including macropinocytosis and phagocytosis , are important for the entry of viruses [35 , 36] . Likewise , it has been suggested that signaling pathways via FcγR are involved in ADE of virus infections [20] . However , there is limited information on the detailed molecular mechanisms of intracellular signaling pathways required for ADE of virus infection . It has been shown that the non-ADE entry of EBOV requires host factors such as PI3K , the Rho family , and protein kinase C [6 , 7 , 37] , although the virus-specific receptor molecules involved in these signaling pathways are not yet identified . In the present study , we focused on the ADE of EBOV entry and found that the FcγRIIa-mediated signaling pathway was essential for this process , which is distinct from those required for the non-ADE entry . The FcγRIIa cytoplasmic tail has been shown to be essential for ADE of dengue virus entry and the involvement of Syk cascade in ADE entry has been reported [38–40] . Our data indicate that the cytoplasmic tail of FcγRIIa is crucial for the ADE of EBOV infection and that Src family PTK-dependent signaling is important to enhance viral uptake into cellular vesicles during ADE-mediated entry of EBOV . Src family PTKs are non-receptor tyrosine kinases involved in the regulation of diverse cellular functions like proliferation , differentiation , adhesion , and phagocytosis [41 , 42] . Importantly , this signaling pathway is known to regulate endocytic machinery by triggering the reorganization of the actin cytoskeleton and membrane remodeling [21 , 26] . Indeed , previous studies have demonstrated that Src family PTK-dependent signaling is required for the non-ADE entry of some viruses into host cells [43 , 44] . Our data indicate that this signaling is also used to promote viral particle uptake during the FcγRIIa-mediated ADE of EBOV entry . It was noted that there was a significant increase ( approximately 400% ) in infectivity of VSV-EBOV GP when FcγRIIaΔCT is expressed on Jurkat T cells , although it was not as high as wildtype FcγRIIa . This observation suggest that the binding provided by the external portion of FcγRIIa may also have some importance and that the signaling function provided by the cytoplasmic portion of FcγRIIa further enhances the ADE effect . It might also be possible that the FcγRIIa associated with lipid rafts activates some FcγRIIa-mediated signals through its transmembrane domain as described previously [45] . Interestingly , we found that the Syk inhibitor R788 reduced the ADE efficiency of VSV-EBOV GP but not EBOV . While the VSV pseudotype system is widely used to study EBOV GP functions , it has been suggested that pseudotyped VSV and authentic EBOV can utilize different entry pathways since the particle size and structure of pseudotyped VSV do not accurately recapitulate those of EBOV [6 , 46] . Thus , it may be possible that the EBOV entry primarily relies on macropinocytosis as shown previously [6–8] , whereas VSV-EBOV GP can also be incorporated into smaller vesicles . We assume that this difference could influence the effect of the inhibitor since Syk-dependent signaling might be associated with caveolin-mediated endocytosis [47 , 48] . Another difference found between VSV-EBOV GP and authentic EBOV was that while the Syk inhibitor did not affect EBOV ADE , non-ADE infection was significantly enhanced in the presence of this inhibitor , an effect not observed for VSV-EBOV GP . This might be due to the effect on post-entry mechanisms such as antiviral cellular responses , as proposed by a recent study demonstrating that dengue virus-antibody complexes decreased type-I interferon-stimulated gene expression triggered by the FcγR-mediated signaling pathway through Syk , leading to enhanced replication of the virus [39 , 40] . Since such an antiviral response could be different between VSV- and EBOV-infected cells , it is possible that the Syk inhibitor specifically affected the replication of EBOV , but not VSV , RNA genomes . Previous studies have demonstrated that cellular C-type lectins such as DC-SIGN and hMGL serve as attachment receptors and promote the entry of EBOV into cells [5 , 32 , 34] . These C-type lectins , as well as Fc receptors , are thought to initiate phagocytic pathways for uptake of microorganisms , cell debris , and apoptotic cells [49 , 50] . Interestingly , both C-type lectins and ADE-antibodies , including ZGP12/1 . 1 , mainly bind to the mucin-like region of EBOV GP , which has a number of N- and O-linked glycosylation sites in the middle portion of the protein [17 , 32 , 34] , suggesting a similarity in the mechanism of the virus entry mediated by C-type lectins and ADE . However , the Src family PTK inhibitor PP2 showed limited effects on the infectivity of VSV-EBOV GP in the cell lines expressing DC-SIGN or hMGL . Taken together , our data suggest that the FcγRIIa-mediated EBOV ADE principally depends on signaling pathways distinct from those for C-type lectin-mediated entry , while both C-type lectins and ADE-antibody-FcγRIIa complexes are assumed to serve as attachment receptors and subsequent processes for membrane fusion ( i . e . , cathepsin cleavage and NPC1 binding ) appear also to be similar . In conclusion , our data indicate that EBOV ADE is not simply dependent on increased viral attachment through interaction between FcγRIIa and virus-antibody complexes , and that the induction of FcγRIIa-mediated signaling associated with the activation of Src family PTKs is essential for EBOV ADE . This signaling pathway most likely promotes macropinocytosis , the major entry pathway of EBOV , and leads to enhanced viral uptake into cells . The contribution of Src family PTKs to FcγRIIa-mediated ADE of virus entry has not been demonstrated previously . Discovery of this ADE mechanism provides a novel perspective for the general understanding of ADE of virus infection . Although the impact of ADE on disease progression remains unclear for many viruses , our findings may offer a potential new target to develop treatments for ADE-associated diseases such as dengue hemorrhagic fever and possibly Zika virus infection [16 , 51–53] since signaling pathways are known to be essential for virus entry into cells and some signaling inhibitors have been considered to be potential treatment options for virus infections [54–56] . However , since non-ADE entry mechanisms of these viruses are different from EBOV , it is required to investigate whether the Src family PTK-mediated ADE mechanism can be generally applied for other viruses known to utilize ADE entry into cells .
African green monkey kidney Vero E6 cells and human embryonic kidney ( HEK ) 293T cells were grown in Dulbecco’s modified Eagle’s medium ( DMEM ) ( Sigma ) , and human chronic myelogenous leukemia K562 , K562/DC-SIGN , and K562/hMGL cell lines [32 , 57] and human leukemic Jurkat T cells were grown in Roswell Park Memorial Institute ( RPMI ) 1640 medium ( Sigma ) . These media were supplemented with 10% fetal calf serum ( FCS ) ( Cell Culture Bioscience ) , 100 U/ml penicillin , and 0 . 1 mg/ml streptomycin ( Gibco ) . These cells were obtained from an already-existing collection in the Research Center for Zoonosis Control , Hokkaido University . EBOV expressing GFP [58] was propagated in Vero E6 cells and stored at -80°C . Replication-incompetent VSV pseudotyped with EBOV GP containing GFP instead of the VSV G gene ( VSV-EBOV GP ) was generated as described previously [3 , 59] . Virus titers in EBOV ADE cell line were determined as infectious units ( IUs ) by counting GFP-positive cells . All infectious work with EBOV was performed in the biosafety level 4 laboratory at the Integrated Research Facility of the Rocky Mountain Laboratories , Division of Intramural Research , National Institute of Allergy and Infectious Diseases , National Institutes of Health , Hamilton , Montana , USA . The FcγRIIa gene was PCR-amplified from a full-length cDNA library prepared from K562 cells using the primers , EcoRI-FcγRIIa ( 5’-GGGAATTCGGATGACTATGGAGACCCAA-3’ ) and FcγRIIa-XhoI ( 5’-ATTTCTCGAGTTTGTCATCCACTCAGCAAG-3’ ) . Mutant FcγRIIa lacking its cytoplasmic tail ( amino acid positions 241–317 ) was generated using a PrimeSTAR Mutagenesis Basal Kit ( Takara ) . After sequence confirmation , these PCR products were cloned into a murine leukemia virus-based retroviral vector , pMXs-Puro Retroviral Vector ( Cell Biolabs ) . To generate the retrovirus , 293T-derived Platinum-GP ( Plat-GP ) cells ( Cell Biolabs ) were cotransfected with pMXs-puro encoding FcγRIIa or FcγRIIaΔCT and the expression plasmid pCAGGS encoding the VSV G protein using Lipofectamine 2000 ( Invitrogen ) . Forty-eight h later , the culture supernatants containing retroviruses were collected , clarified through 0 . 45-μm filters , and then used to infect Jurkat T cells . Jurkat T cell lines stably expressing FcγRIIa or FcγRIIaΔCT were selected with RPMI medium containing 10% FCS , 100 U/ml penicillin , 0 . 1 mg/ml streptomycin , and 10 μg/ml puromycin ( Sigma-Aldrich ) . For some experiments , each Jurkat T cell line was cloned by limiting dilution to enrich the population of FcγRIIa-expressing cells . To check the expression levels of FcγRIIa and FcγRIIaΔCT , these cells were incubated with a mouse anti-CD32 monoclonal antibody ( GeneTex ) for 1 h at room temperature . After washing 3 times with phosphate-buffered saline ( PBS ) , binding of the primary antibody was detected with Alexa647-conjugated F ( ab' ) 2-goat anti-mouse IgG ( H+L ) ( Jackson ImmunoResearch ) . After further washing 3 times with PBS , the fluorescent intensity of the cells was analyzed using a FACS Canto flow cytometer ( BD Biosciences ) and FlowJo software ( Tree Star ) . EBOV was appropriately diluted to provide 50–100 IUs/50 μl in K562 cells and then incubated for 30 min-1 h at 37°C with or without 10 μg/ml MAbs . The anti-EBOV GP MAb ZGP12/1 . 1 ( IgG2a ) , which is known to enhance EBOV infection in vitro , was used as the ADE MAb [12] . S139/1 ( IgG2a ) , a MAb specific to influenza A virus hemagglutinin , was used as the CTR IgG [60] . K562 and Jurkat T cells were inoculated with EBOV alone or EBOV/MAb mixtures and incubated for 72 h . Virus infectivity was measured by counting the number of GFP-positive cells in FACS and analyzed using FlowJo software . VSV-EBOV GP appropriately diluted to yield 50–100 IUs/50 μl in K562 cells was incubated for 1 h at room temperature with or without 1 μg/ml MAbs , and then inoculated into K562 and Jurkat T cells . Twenty-four h later , GFP-positive cells were counted using an IN Cell Analyzer 2000 ( GE Healthcare ) . To reduce the background ( i . e . , residual ) infectivity of the parent VSV , VSV-EBOV GP was treated with a neutralizing MAb to VSV G protein ( VSV-G[N]1–9 ) before use . For purification of VLPs , HEK293T cells were transfected with equal amounts of the expression plasmids encoding EBOV or SUDV GP , VP40 , and NP using TransIT LT-1 ( Mirus ) according to the manufacturer's instructions . Forty-eight h after transfection , the culture supernatant was harvested and centrifuged at 3 , 500 rpm for 15 min at 4°C to remove cell debris . VLPs were precipitated through a 25% sucrose cushion by centrifugation at 11 , 000 rpm for 1 h at 4°C with an SW32Ti rotor ( Beckman ) . Pelleted VLPs were suspended in PBS , and fractionated through a 20–50% sucrose gradient in PBS at 28 , 000 rpm with an SW41 rotor ( Beckman ) for 2 h at 4°C . One ml of 1 μg/ml fractionated VLPs was incubated with 0 . 6 μl of 100 μM 1 , 1'-dioctadecyl-3 , 3 , 3' , 3'-tetramethylindocarbocyanine perchlorate ( DiI ) ( Molecular Probes ) in the dark for 1 h at room temperature with gentle agitation [6 , 61] . The eGFP-Rab7 fusion protein gene was cloned into a Moloney murine leukemia virus-based retrovirus plasmid [6 , 62] , and recombinant retroviruses for the expression of eGFP-Rab7 were produced and used to infect K562 cells as described above . K562 and Jurkat T cell lines were cultured in 35 mm glass-bottom dishes ( MatTek Corporation ) precoated with borate buffer containing 0 . 1 mg/ml poly-L-lysine ( Sigma ) . The cells were washed with 200 μl phenol red-free RPMI ( Gibco ) and inoculated with 100 μl of 1 μg/ml DiI-labeled VLPs treated with 20 μg/ml ZGP12/1 . 1 or CTR IgG for 1 h at room temperature , followed by incubation for 30 min on ice . They were then washed twice with the same medium to remove unbound DiI-labeled VLPs and incubated with 200 μl phenol red-free RPMI containing 2% FCS and 4% bovine serum albumin ( BSA ) for 0 and 2 h at 37°C to analyze DiI-labeled VLP attachment and internalization , respectively . To count the number of DiI-labeled VLPs , the cells were fixed with 4% paraformaldehyde for 15 min at room temperature . Then the nuclei were stained with 1 μg/ml 4' , 6-diamidino-2-phenylindole , dihydrochloride ( DAPI ) ( Molecular Probes ) for 10 min at room temperature . Microscopic images were acquired with a 63× oil objective lens on a Zeiss LSM780 inverted microscope and ZEN 2010 software ( Carl Zeiss ) . For measurement of the number of DiI-labeled VLPs , images of 4–20 optical sections were acquired in 1 micron steps . The number of DiI-labeled VLPs was determined in approximately 100 individual cells using MetaMorph software ( Molecular Devices ) and the average number per cell was calculated for each condition . For colocalization analysis , the percentage of DiI-labeled VLPs that colocalized with eGFP-Rab7 ( Both DiI- and eGFP-positive pixels/DiI-positive pixels × 100 ) was measured in approximately 100 individual cells using the Coloc module in ZEN 2010 software ( Carl Zeiss ) . One μg/ml DiI-labeled VLPs were treated with 20 μg/ml CTR IgG or ZGP12/1 . 1 for 1 h at room temperature . K562 and Jurkat T cell lines were cultured in poly-L-lysine-coated glass-bottom culture dishes and incubated with 100 μl untreated , CTR IgG- , or ZGP12/1 . 1-treated DiI-labeled VLPs for 30 min on ice . The cells were washed twice with 200 μl phenol red-free RPMI and then incubated with 200 μl phenol red-free RPMI containing 2% FCS , 4% BSA , and 0 . 5 mg/ml Dextran , Alexa Fluor 647 , 10 , 000 MW ( Alexa647-labeled Dx10 ) ( Molecular Probes ) for 1–2 h at 37°C . After washing twice with 200 μl phenol red-free RPMI to remove surface-unbound DiI-labeled VLPs and Alexa647-labeled Dx10 , and the cells were fixed with 4% paraformaldehyde for 15 min at room temperature . Then , the nuclei were stained with 1 μg/ml DAPI for 10 min at room temperature . Internalized DiI-labeled VLPs and Alexa647-labeled Dx10 were analyzed by confocal laser scanning microscopy as described above . The percentage of DiI-labeled VLPs that colocalized with Alexa647-labeled Dx10 ( Both DiI- and Alexa647-positive pixels/DiI-positive pixels × 100 ) was measured in approximately 100 individual cells using the Coloc module in ZEN 2010 software . The number and size of Dx10-positive vesicles were analyzed with MetaMorph software . For infection assays , the Syk inhibitor R788 ( Santa Cruz ) , Src family PTK inhibitor PP2 ( Tocris ) , BTK inhibitor LFM-A13 ( Focus Biomolecules ) , PI3K inhibitor LY294002 ( Wako ) , and Ras inhibitor Manumycin A ( Santa Cruz ) were used for treatments of K562 cells . R788 , LFM-A13 , and LY294002 were used at 0 . 15–40 μM . PP2 and Manumycin A were used at 0 . 15–10 μM . For imaging analysis , K562 cell lines were cultured in 35 mm glass-bottom dishes precoated with poly-L-lysine , and then treated with 20 μM PP2 for 1 h at 37°C . PP2-treated cells were washed with phenol red-free RPMI and inoculated with untreated , CTR IgG- , or ZGP12/1 . 1-treated DiI-labeled VLPs for 30 min on ice in the presence of 20 μM PP2 in the same medium . The cells were then washed twice with the same medium and incubated with phenol red-free RPMI containing 2% FCS , 4% BSA , and 20 μM PP2 for 0 and 2 h at 37°C . Then they were fixed and analyzed by confocal laser scanning microscopy as described above . Dimethyl sulfoxide ( DMSO , Sigma-Aldrich ) or ethanol ( Kanto Chemical ) was used as a solvent control . Plat-GP cells ( Cell Biolabs ) were cotransfected with pRS ( retroviral plasmids ) encoding human Src or Syk shRNA ( ORIGENE ) and the expression plasmid pCAGGS encoding the VSV G protein using Lipofectamine 2000 ( Invitrogen ) . ShSrc target sequences were: shSrc1:5’-GGAGGCTTCAACTCCTCGGACACCGTCAC-3’ , shSrc2: 5’-AAGAAAGGCGAGCGGCTCCAGATTGTCAA-3’ , shSrc3: 5’-GCAGTTGTATGCTGTGGTTTCAGAGGAGC-3’ , shSrc4: 5’-CTGGAGGCAATCAAGCAGACATAGAAGAG-3’ . ShSyk target sequences were: shSyk1:5’- GAATATGTGAAGCAGACATGGAACCTGCA-3’ , shSyk2: 5’- GGAGGAGGCAGAAGATTACCTGGTCCAGG-3’ , shSyk3: 5’- TGTCATTCAATCCGTATGAGCCAGAACTT-3’ , shSyk4: 5’- CTCTGGCAGCTAGTCGAGCATTATTCTTA-3’ . After incubation for 48 h , culture supernatants containing the retroviruses expressing human Src or Syk shRNAs were collected , clarified through 0 . 45-μm filters , and then used to infect K562 cells . Transduced K562 cell lines were selected with RPMI medium containing 10% FCS , 100 U/ml penicillin , 0 . 1 mg/ml streptomycin , and 5 μg/ml puromycin ( Sigma-Aldrich ) . To check the knockdown efficiency for Src and Syk , cells were collected and washed once with PBS and treated with lysis buffer ( 0 . 1% Nonidet P-40 , 150 mM NaCl , 1 mM EDTA , 10 mM Tris HCl , pH 7 . 8 ) in the presence of a protease inhibitor cocktail , Complete mini ( Roche ) . Then the lysates were mixed with SDS-PAGE sample buffer ( Bio-Rad ) with 5% 2-mercaptoethanol ( Wako ) and boiled for 5 min . The samples were electrophoresed by SDS-PAGE on 5 to 20% gradient polyacrylamide gel , SuperSep Ace ( Wako ) , and separated proteins were blotted on a polyvinylidene difluoride membrane ( Millipore ) . The membrane was blocked for at least 1 h at room temperature with Tris-buffered saline containing 0 . 1% Tween 20 ( TBST ) and 1% BSA . Then the membrane was incubated with a rabbit anti-Src antibody ( 36D10: Cell Signaling ) or mouse anti-Syk antibody ( 4D10 . 1: Abcam ) in TBST containing 1% BSA , followed by incubation with peroxidase-conjugated donkey anti-rabbit IgG ( H+L ) or peroxidase-conjugated goat anti-mouse IgG ( H+L ) ( Jackson ImmunoResearch ) , respectively , and visualization by Immobilon Western ( Millipore ) . Band intensities were analyzed with a VersaDoc Imaging System ( Bio-Rad ) and quantified with Image Lab version 3 . 0 software ( Bio-Rad ) . One μg/ml purified VLPs were treated with 20 μg/ml ZGP12/1 . 1 or CTR IgG for 1 h at room temperature . K562 cells were incubated with DMSO or 20 μM PP2 for 1 h at 37°C . Untreated or PP2-treated K562 cells were inoculated with untreated , CTR IgG- , or ZGP12/1 . 1-treated VLPs and incubated for 0 , 10 , 30 , or 60 min at 37°C . At each time point , cells were collected and washed once in PBS and treated with lysis buffer ( 0 . 1% Nonidet P-40 , 150 mM NaCl , 1 mM EDTA , 10 mM Tris HCl , pH 7 . 8 ) in the presence of a protease inhibitor cocktail , Complete mini ( Roche ) , and a phosphatase inhibitor cocktail , PhosSTOP ( Roche ) . Then the lysates were mixed with SDS-PAGE sample buffer ( Bio-Rad ) with 5% 2-mercaptoethanol ( Wako ) and boiled for 5 min . The samples were electrophoresed by SDS-PAGE on 5 to 20% gradient polyacrylamide gel , SuperSep Ace ( Wako ) , and separated proteins were blotted on a polyvinylidene difluoride membrane ( Millipore ) . The membrane was blocked for at least 1 h at room temperature with Tris-buffered saline containing 0 . 1% Tween 20 ( TBST ) and 1% BSA . Then the membrane was incubated with a phospho-Src family ( Tyr416 ) antibody ( Cell Signaling ) in TBST containing 1% BSA , followed by visualization using peroxidase-conjugated donkey anti-rabbit IgG ( H+L ) ( Jackson ImmunoResearch ) and Immobilon Western ( Millipore ) . Band intensities were analyzed with a VersaDoc Imaging System ( Bio-Rad ) and quantified with Image Lab version 3 . 0 software ( Bio-Rad ) . All data were analyzed using Excel software . In all experiments , Student’s t-test was used to evaluate statistical differences . P values of less than 0 . 05 were considered to be significant . | Antibody-dependent enhancement ( ADE ) , a phenomenon in which viral infectivity is increased by virus-specific antibodies , is observed in vitro for a large number of viruses . For some of these viruses , ADE often become an issue for disease control by vaccination . It has also been shown that some human sera convalescent from Ebola virus disease contain ADE antibodies . ADE has been shown mostly to depend on the cross-linking of virus-antibody complexes to cell surface Fc receptor , which activate various signaling pathways involved in the reorganization of the actin cytoskeleton and membrane remodeling . In this study , we demonstrate that Fc receptor-mediated intracellular signaling is a key factor for ADE of Ebola virus infection . We found that the antibody-virus complexes bound to the cell surface Fc receptors triggered the phosphorylation of particular protein-tyrosine kinases that activated signaling pathways leading to enhanced viral uptake into cells through phagocytosis and/or macropinocytosis . Our study provides new insights into mechanisms of ADE and also offer a potential new cellular target to develop treatments for ADE-associated diseases such as dengue hemorrhagic fever and possibly Zika virus infection . | [
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"signa... | 2016 | Fcγ-receptor IIa-mediated Src Signaling Pathway Is Essential for the Antibody-Dependent Enhancement of Ebola Virus Infection |
Trypanosoma cruzi , the etiological agent of Chagas disease , consumes glucose and amino acids depending on the environmental availability of each nutrient during its complex life cycle . For example , amino acids are the major energy and carbon sources in the intracellular stages of the T . cruzi parasite , but their consumption produces an accumulation of NH4+ in the environment , which is toxic . These parasites do not have a functional urea cycle to secrete excess nitrogen as low-toxicity waste . Glutamine synthetase ( GS ) plays a central role in regulating the carbon/nitrogen balance in the metabolism of most living organisms . We show here that the gene TcGS from T . cruzi encodes a functional glutamine synthetase; it can complement a defect in the GLN1 gene from Saccharomyces cerevisiae and utilizes ATP , glutamate and ammonium to yield glutamine in vitro . Overall , its kinetic characteristics are similar to other eukaryotic enzymes , and it is dependent on divalent cations . Its cytosolic/mitochondrial localization was confirmed by immunofluorescence . Inhibition by Methionine sulfoximine revealed that GS activity is indispensable under excess ammonium conditions . Coincidently , its expression levels are maximal in the amastigote stage of the life cycle , when amino acids are preferably consumed , and NH4+ production is predictable . During host-cell invasion , TcGS is required for the parasite to escape from the parasitophorous vacuole , a process sine qua non for the parasite to replicate and establish infection in host cells . These results are the first to establish a link between the activity of a metabolic enzyme and the ability of a parasite to reach its intracellular niche to replicate and establish host-cell infection .
Parasites display metabolic peculiarities that help them adapt to different environments during their life cycles and take advantage of the host’s resources . Trypanosoma cruzi , the causative agent of Chagas disease , is a digenetic protozoan that transitions among different environments in its vertebrate and invertebrate hosts during its life cycle , alternating between non-replicative and replicative stages [1] . Briefly , epimastigotes ( E ) , which are the replicative forms in the insect vector , colonize the digestive tube and differentiate into non-dividing infective metacyclic trypomastigotes ( MT ) in its terminal portion [2] . MT must invade the mammalian host cells through an energy-dependent mechanism to be able to differentiate into replicative stages and establish infection [3 , 4] . The trypomastigote invasion of host cells is an event that involves the recruitment of lysosomes to form a parasitophorous vacuole [5] . Once inside , it is assumed that low pH triggers the differentiation of MT into replicative intracellular amastigotes ( A ) [6] , which activates hydrolytic activities , enabling the release of A into the cytoplasm to initiate their replication [7–10] . After a variable number of cell divisions , A differentiate into a transient replicative form called intracellular epimastigotes ( IE ) , which ultimately differentiate into cell-derived trypomastigotes ( CDT ) [11] . CDT lyse the infected cells , and once they burst , the CDT have two fates: i . to infect neighbor cells; and ii . to reach the bloodstream , from which they can reach and infect remote tissues , or if a triatomine makes a bloodmeal while the CDT are circulating , they can infect a new insect , which will transmit the parasite into new mammalian hosts [6] . T . cruzi faces different physicochemical and nutritional conditions during its complex journey among different hosts . For example , it is well known that during midgut colonization , E preferably consume glucose during exponential growth and switches to the consumption of amino acids in the stationary phase [12 , 13] . An orchestrated metabolic switch happens: while the uptake of amino acids and several of their intermediate metabolites increases , the level of most glycolysis metabolites diminishes [14] . In addition , the A and IE stages obtain energy predominantly from amino acids during intracellular life [15] , whereas glucose seems to represent a significant energy source in only the form of CDT [16] . In summary , the T . cruzi life cycle involves plenty of situations in which glucose is scarce , and there is solid evidence showing amino acid consumption as an alternative energy source [17] . A main waste product of amino acid catabolism in ammoniotelic organisms is reduced metabolites containing -NH2 groups and NH3 , which is spontaneously converted into NH4+ in aqueous media . It is well known that T . cruzi does not have a functional urea cycle: alanine and NH3 are known nitrogen-containing excreta products [18–21] . The management of excesses of these compounds requires an enzymatic system that is able to recover NH4+ from H2O ( such as reversible , non-oxidative glutamate dehydrogenases ) and a robust transaminase network [18] . In other words , a specific metabolic configuration is required to address NH4+ accumulation in organisms that are avid amino acid consumers without a urea cycle . In this regard , a robust transamination network was described ( at least for E ) to transfer -NH2 from amino acids to oxoacids ( primarily but not exclusively α-ketoglutarate and oxaloacetate , rendering glutamate and aspartate , respectively , which are donors of -NH2 in a transamination reaction with pyruvate as the acceptor , forming Ala ) [22] . Eventually , if an increase in the ratio of glutamate/α-ketoglutarate occurs , two isoforms of glutamate dehydrogenase can also reversibly transfer the -NH2 group of glutamate to H2O , forming NH4+ [23–25] ( also reviewed in [17 , 18] ) . However , it should be noted that this step goes back to the initial problem of NH4+ accumulation , and in this situation , this reaction would stop or even go backward . Thus , an alternative step allowing the capture of NH4+ may be essential in these organisms . Glutamine synthetase ( GS ) [L-glutamate-ammonia ligase; EC 6 . 3 . 1 . 2] catalyzes the ATP-dependent formation of glutamine from glutamate and ammonia . GS has a major role in all organisms studied thus far . In particular , GS is the major NH4+-assimilation pathway in most organisms and is the enzyme that controls carbon/nitrogen balance in plants and animals alike [26–28] , simultaneously playing an important role in the maintenance of low concentrations of toxic ammonia in the mitochondria of plants [29 , 30] and uricotelic vertebrates [31] . In mammals , its role in NH4+ detoxification is also well established for several tissues , including brain and muscle [32] . It has received extensive attention for many years as a central metabolic point in both eukaryotes and prokaryotes . Thus , its structure , allosteric interactions and the effect of inhibitors on its activity are well characterized in species throughout nearly the entire range of living organisms , such as bacteria [33 , 34] , cyanobacteria [35] , fungi and yeast [30 , 36] , insects [37] and mammals [38 , 39] . It is known that GSs are present in trypanosomatids; an active recombinant GS was obtained after cloning and expressing of the corresponding gene from Leishmania donovani [40] , and GS activity was observed in T . cruzi E cell-free extracts [41 , 42] . However , the molecular and cellular aspects of the Glutamate—Glutamine pathway or its components have not been investigated in these pathogenic organisms . In this work , we present the first molecular and enzymological characterization of a GS from a trypanosoma . The data presented here show that GS in T . cruzi is fully functional in both of its localizations , similar to GS in plants and uricotelic vertebrates . We also show that this enzyme is involved in ammonia detoxification . Furthermore , we show for the first time that this enzyme affects the intracellular life stages of T . cruzi and is critical for its escape from parasitophorous vacuoles , which is required for the parasite to initiate intracellular replication .
As mentioned , the existence of GS activity in T . cruzi was previously shown [41 , 42] . We further characterized this T . cruzi enzyme by initially identifying two sequences in both haplotypes ( Esmeraldo-like and Non-Esmeraldo like ) of the T . cruzi CL Brener strain genome ( TcCLB . 503405 . 10 –Esmeraldo-like , seq . a- and TcCLB . 508175 . 370 –Non-Esmeraldo-like , seq . b- ) encoding putative type II glutamine synthetases ( GSII ) ( Fig 1 ) . Both sequences are located on chromosome 27 , spanning from coordinate 561646 to either 562911 ( seq . a ) or 562953 ( seq . b ) . They both display typical signatures of GSs . Allelic variants were also found in gene databases for the other strains . Sequences a and b also had an unusual 5’ terminus , consisting of A- and T-enriched stretches that encode a predicted transmembrane domain ( Fig 1A ) . This region is absent in the sequences of T . cruzi DM28 and Marinkellei strains and in any other GSs that has been studied or annotated so far . We clarified this issue by sequencing the genome fragments corresponding to seq . a and seq . b from the low-infectivity strain CL14 . These sequences were identical to those reported for the closely related strain CL Brener , and they revealed that the predicted translation start is out-of-frame for a functional GS , whereas an ATG codon lying 123 base pairs downstream conformed to a canonical GS open reading frame ( ORF ) . For these reasons , we established that the 5’ regions predicted in both seq . a and b from the CL Brener strain were not actually parts of the gene ( Fig 1B ) . We named this gene TcGS and selected sequence TcCLB . 503405 . 10 ( seq . a , Esmeraldo-like haplotype from CL Brenner ) starting at base pair 123 as our reference allele . A blast search for other GS genes in the T . cruzi genome yielded no other sequences . Phylogenetic analysis of the sequence revealed that it was closely related to sequences found in other trypanosomatids and the Leishmania genus . It was also shown to be related to other eukaryotic GS genes ( Fig 1C ) . We performed a functional complementation assay in Saccharomyces cerevisiae to evaluate the ability of the TcGS gene to express a functional enzyme and support cell growth by providing glutamine . We first amplified the TcGS ORF by high fidelity PCR and then sequenced and cloned expression vector p416GPD , a centromeric plasmid , into yeast as described in the Materials and Methods . As GS is essential for yeast in the absence of glutamine under most usual growth conditions , we chose to transfect the construction into strain SAH35 , a conditional mutant for ScGLN1 that does not express endogenous GS when grown on glucose as a carbon source . In other words , in the absence of glucose , both , the endogenous version of GS and TcGS are expressed , but in the presence of glucose , only TcGS is expressed . Therefore , for our system , in the absence of glutamine and the presence of glucose , growth rely exclusively on the ability of TcGS to encode a functional GS . The expression of gene TcGS was able to restore SAH35 growth in the presence of glucose in a similar way to the reintroduction of ScGLN1 ( Fig 2 ) , confirming that this gene encodes a functional GS . Once the functionality of the TcGS product was confirmed , we decided to better characterize it by expressing the active recombinant protein . We cloned TcGS into the bacterial expression vector pET-28a ( + ) , which also provided a His6 tag for purification . The purified protein showed an apparent molecular mass of 45 kDa , which is close to the predicted mass ( 42 kDa ) ( Fig 3A ) when evaluated by SDS-PAGE . However , when the soluble native protein from bacterial extracts was analyzed by analytical size-exclusion chromatography , the estimated molecular mass was 320 kDa ( Fig 3B ) , pointing to an octameric conformation of the native protein . TcGS expressed from E . coli was used for kinetic and enzymological characterizations . The reaction catalyzed by the recombinant enzyme was dependent on L-glutamate , NH4+ and ATP concentrations ( Fig 4A ) and showed an optimal pH at 8 . 0 ( Fig 4B ) . The KM of each of the substrates was in the submillimolar range ( Table 1 ) . Kinetic data were used to obtain the catalytic constants of the recombinant enzyme , including the activation energy of the reaction ( Fig 4C ) . The ATPase activity of TcGS was tested for all amino acids and was found to be specific for glutamate; aspartate , asparagine or histidine , however , the last three supported less than 10% of the activity observed with glutamate . All the other amino acids did not promote ATP hydrolysis . In contrast , glutamate analogs could successfully drive ATPase activity , although to various extents . Thus , while we observed nearly 75% activity with adipic acid , γ-aminobutyric acid ( GABA ) or pentanedioic acid was able to produce only 50% . Other analogs were less effective ( Fig 4D ) . The activity was dependent on the presence of divalent cations . Mg2+ was the most effective cation to support GS activity , but Mn2+ and Co2+ were able to support activity levels above 50% compared with magnesium in standard conditions of substrates , temperature and pH ( Fig 4E ) . Almost no activity was found in the presence of Zn2+ ions , such as in the presence of the divalent metal chelator EDTA . Ca2+ was a special case . No activity was found in the presence of Ca2+ alone . In addition , Ca2+ showed an inhibitory effect on Mg2+-driven activity . This inhibition exhibited a dose-dependent pattern ( Fig 4F ) with an estimated IC50 of 205 . 7 ± 2 . 8 μM ( Fig 4F—inset ) . We performed immunofluorescence assays in all the parasite stages using an Anti-GS antibody ( Sigma- Aldrich , St . Louis , Missouri ) ( S2 ) to determine the subcellular location of TcGS and to extend these analyses to other life cycle forms . The enzyme was spread throughout the cytoplasm and inside the mitochondrial lumen in all life cycle forms ( Fig 5A ) . We performed a differential permeabilization assay in E using digitonin in an attempt to confirm that the subcellular location indicated the presence of active enzyme . The permeabilization of different intracellular compartments was assessed by the release of marker enzyme activities into the medium: pyruvate kinase allowed us to trace the cytosolic fraction; hexokinase , the glycosome; and citrate synthase , the mitochondrial matrix . GS activity was found to be released in a two-step fashion . It was first observed at digitonin concentrations higher than those needed to release pyruvate kinase but smaller than those necessary to release mitochondrial citrate synthase . However , when the digitonin concentration was high enough to release citrate synthase , glutamine synthetase activity increased significantly ( Fig 5B ) . Taken together , both sets of data strongly support a dual ( cytoplasmic and mitochondrial ) localization of the active enzyme . Expression of the TcGS gene was analyzed by qRT-PCR in all five T . cruzi stages . mRNA levels were higher in A than in E , showing a dramatic ca . 70-fold increase ( Fig 6A ) . In contrast , the other forms displayed modest differences in mRNA levels compared with those of E . GS activity was also measured . In agreement with the gene expression data , GS activity was higher in the A form of the parasite , albeit it was ca . 5-fold greater than that measured in E . In addition , the E and MT forms showed significant GS activities ( Fig 6B ) . These all contrasted with the IE and CDT forms , where only near background activity levels were observed . Protein levels were evaluated by Western blot ( Fig 6C and 6D ) . The A form GS levels were again the highest among all life forms of T . cruzi . However , the profile was less sharp than it was in the other two analyses , and this life form showed only a ca . 1 . 4-fold greater amount of protein compared with the E form . Finally , CDT showed the smallest amount of TcGS protein , which is similar to that observed for mRNA expression and GS activity in this life form . Inhhibiting GS activity in the parasite was necessary to unveil the biological roles of GS . As TcGS are described as essential enzymes in most of organisms , and there are no available inducible knock down or knock out methods for essential genes in T . cruzi , we used a well-known chemical inhibitor considered specific for the enzyme , Methionine sulfoximine ( MS ) [45] . Recombinant TcGS activity ( expressed in E . coli ) and GS activity from E cell-free extracts were susceptible to MS in a dose-dependent manner . Their IC50 values were similar and estimated to be 20 . 72 ± 0 . 07 μM and 38 . 85 ± 0 . 08 μM , respectively , for recombinant TcGS and GS ( Fig 7A ) . Kinetic analysis results showed that MS changes the Michaelis-Menten pattern of GS ( Fig 7B ) , maintaining its Vmax value but increasing the KM values , by acting as a competitive inhibitor with respect to L-glutamate ( Fig 7C ) ; the Ki values were estimated to be 3 . 89 ± 0 . 04 μM and 4 . 65 ± 0 . 08 μM for the recombinant enzyme and GS activity in E cell extracts , respectively ( Fig 7D ) . Once we characterized the inhibition of TcGS by MS on the enzyme , we were interested in evaluating its effect on the parasite . Thus , we initially cultured E in the presence of different concentrations of MS . As previously shown , MS had a limited effect at concentrations up to 1 mM , showing an IC50 concentration of 17 . 0 ± 0 . 3 mM [42] . However , we evaluated the interaction between significant but non-lethal levels of ammonium and MS to account for our initial hypothesis that GS would be involved in NH4+ management . In these conditions , MS was able to inhibit parasite proliferation with a dose-dependent profile . The EC50 was 438 . 4 ± 47 . 4 μM , showing a nearly 40-fold increase in parasite sensitivity to MS ( Fig 8A–8C ) , which reciprocally means that the specific inhibition of TcGS also increases the sensitivity of T . cruzi E to the presence of NH4+ . During the mammalian host-cell infection ( particularly in the intracellular environment ) , the parasites undergo to a metabolic switch , consuming mainly proline instead of glucose [16] . Thus , as TcGS is relevant for E to address NH4+ toxicity , it could predictably be relevant to managing NH4+ toxicity during host-cell infection by T . cruzi . In this regard , CHO-K1 cells were infected with CDT , treated with different concentrations of MS ( or not treated , as a control ) throughout the entire intracellular cycle , and the number of burst CDT was recorded . MS decreased the number of released CDT in a dose-dependent manner compared to the control ( Fig 9A ) . If the production of CDT is taken as a measurement of the effect of MS , an EC50 of 20 . 02 ± 7 . 88 μM could be calculated ( Fig 9A inset ) . Whole host-cell infection is a complex process , involving several steps of replication and differentiation . Thus , the question of whether the treatment of infected CHO-K1 cells was affecting all the intracellular stages and their differentiation processes remained unanswered . We explored this point with synchronized infections as previously described [15] and treated the infected cells at defined time-points to measure the effect of MS on: i . the invasion process ( first 3 h before culture wash ) ; ii . the parasite survival in the parasitophorous vacuole and/or further exit of the parasitophorous vacuole; and iii . the effect of inhibiting TcGS on the intracellular stages A and IE . Our results show that A proliferation was inhibited to a higher extent than IE ( 51% and 34% , respectively ) ( Fig 9B ) . Interestingly , when the infected cells were treated with MS for the first 24 h post-infection , which initiated exposure to the drug immediately after invasion , a significant reduction in the number of released CDT was observed , raising the question of whether the inhibition of TcGS could cause the parasite to fail to escape from the vacuole . We showed that such inhibition of TcGS impaired the evasion of the parasitophorous vacuole ( Figs 9C and S3 ) . These results implicate TcGS as the first metabolic enzyme involved in T . cruzi evasion from the parasitophorous vacuole .
We initially confirmed the GS activity of the TcGS gene found in the T . cruzi databases through a functional yeast complementation assay . Once we confirmed that TcGS encodes a functional GS , we were interested in performing a biochemical characterization by obtaining an active recombinant enzyme expressed in E . coli . While this enzyme conforms to a canonical GS in many aspects , it shows some important differences . Eukaryotic GSII enzymes have been described to form oligomers composed of 8–10 monomers , with the latter organization being more frequent in the enzymes of plant origin [29] . In this respect , the size-exclusion data for TcGS agree with oligomeric organization as an octamer , which resembles the conformation found in mammals and fungi [38 , 47] . In terms of substrate specificity , TcGS activity was dependent on L-glutamate , NH4+ and Mg·ATP . Interestingly , L-glutamate analogs could support its activity to some extent , but no other tested amino acid was effective beyond 10% of the activity found with L-glutamate . These data depict an enzyme that is similar to its corresponding plant and animal enzymes [48] . In relation to co-factors , Mn2+ is the preferred cation for activity in bacterial GSs , but it is less effective than Mg2+ in eukaryotic GSs ( e . g . , [33 , 39] ) . Nevertheless , Mn2+ may be an important factor in regulating GS activity in eukaryotes; for example , the concentration of Mn2+ is close to the Kd concentration in the cytosol of brain cells , and it varies as a response to Ca2+ signaling , which likely affects GS activity [49] . TcGS shows a behavior similar to that found in eukaryotic GS: Mg2+ is the preferred cation , albeit Mn2+ ( and to a lesser extent , Co2+ ) can serve as a substitute . GSs are cytosolic enzymes in most studied organisms . However , additional mitochondrial locations have been well established for uricotelic vertebrates [31 , 50] , higher plants [51] and Drosophila melanogaster [37] . These dual localizations have been explained by the existence of weak mitochondrial-location determinants in the N-terminus domains of these proteins in the two former cases or by the existence of two different isoforms in the latter case [51 , 52] . In this context , it was important but not surprising that TcGS was observed to be a dual-location enzyme with a presence in both the cytosol and mitochondria . In fact , this result is consistent with the fact that the first step of amino acid metabolism , which consists of amino acid deamination or transamination , mostly occurs in one or both of these locations . Furthermore , the main enzymes involved in these processes and in NH4+ management ( i . e . , tyrosine and aspartate aminotransferases and glutamate dehydrogenase ) [22–25 , 53 , 54] also have mitochondrial and cytosolic localization . Furthermore , the present results suggest that localization to both the cytosol and mitochondria occur constitutively since this localization pattern does not seem to change during the different life stages of the parasite . Taken together , this information allowed us to propose that TcGS is a constitutive part of the NH4+ detoxification system in T . cruzi . Mitochondria are organelles displaying high-capacity Ca2+ transport systems , and consequently , they store substantial amounts of this cation , mostly in the form of Ca2+ phosphates [55] . Trypanosomatid mitochondrion are not an exception: they show vigorous Ca2+ transport systems akin to those found in mammalian mitochondria [56] . Even though this cation mostly accumulates in an inert form , mitochondria typically show concentrations of free Ca2+ that are nearly two orders of magnitude greater than those in the cytoplasm under non-stimulated conditions , i . e . , 1–5 μM [55] . In this regard , Ca2+ sensitivity by GS was observed in early research on eukaryotic enzymes [57 , 58] . In the case of mitochondrial GS , this inhibition may play a role in regulating its activity in vivo . However , TcGS shows negligible inhibition in the low micromolar range . Conversely , its half-maximal inhibition was found to occur at a Ca2+ concentration two orders of magnitude greater than its mitochondrial concentration . On the other hand , Ca2+ inhibition cannot be ascribed to ATP sequestration because at concentrations near the IC50 ( e . g . , 0 . 2 mM ) , [Mg·ATP] in the reaction mixture is predicted to be ca . 0 . 73 mM , whereas [Ca·ATP] is only ca . 0 . 11 mM [59]; these figures are comparable to a predicted [Mg·ATP] ≈ 0 . 73 mM in the absence of Ca2+ . With all this in mind , it can be concluded that the effect of Ca2+ on TcGS is that of a bona fide inhibitor , but the physiological implications of this inhibition are unclear . We were initially interested in evaluating the possible regulation of TcGS during the parasite’s life cycle to infer ( and then demonstrate ) the possible role ( s ) of TcGS in T . cruzi ( beyond the obvious role of supplying glutamine for protein synthesis ) . When TcGS was evaluated in terms of gene expression , protein amounts , or GS activity in the in vitro forms representing all the stages of the natural life cycle of the parasite , we found that the intracellular stage amastigote of T . cruzi showed higher amounts of GS-encoding mRNA , protein and enzyme activity . This expression pattern correlates with a metabolic switch from a life stage in which glycolysis prevails ( CDT ) to another in which amino acid metabolism is prevalent ( A ) [15][16] . These observations reinforced the hypothesis of a role of TcGS in the management of excess NH4+ produced by T . cruzi metabolism under these conditions . Corroboration of this idea requires a reliable and feasible method to diminish TcGS activity . As TcGS is described as a central enzyme in the metabolism of most studied organisms [45] , we chose to chemically inhibit it using the chemical inhibitor MS [60] . TcGS sensitivity to MS was found to fall in the micromolar range . This result is in sharp contrast to the millimolar values found for the human enzyme [60] , and at first sight , it is seen an opportunity for intervention against the parasite because GS activity is involved in glutamine synthesis [61 , 62] . Therefore , it was somewhat surprising to observe that MS had little effect on the proliferation of E even though TcGS showed remarkable sensitivity to this compound . However , it must be noted that during replication , the metabolism of the E form is mainly based on glucose consumption , thus producing little amounts ( if any ) of NH4+ . This consumption is the reason for minimal amounts of GS at this stage , both in terms of its activity and mRNA level . The sensitivity of E replication to MS was evaluated in the present of different concentrations of NH4OH supplemented to the culture medium to confirm that the effect of MS was related to the accumulation of extracellular NH4+ . MS affected E replication when NH4+ was present in millimolar amounts in the growth medium; under these conditions , proliferation was severely halted by concentrations of MS that had no previous effect , showing the involvement of TcGS in NH4+ detoxification . Summarizing , TcGS is involved in the management of NH4+ accumulation by incorporating it on glutamate , which in turn can be obtained by the amination of α-ketoglutarate by glutamate dehydrogenases [23–25] or transaminases [22] , by the oxidation of proline[63 , 64] or by its uptake from the extracellular medium[65] . Once we established the role of TcGS in the management of NH4+ production , it became evident that there was a relevant role for this enzyme in the intracellular life cycle stages , which are dependent on amino acid metabolism . First , we observed that the bursting of CDT forms from infected CHO-K1 diminished with MS treatment in a dose-dependent manner , showing that the inhibitor was affecting at least one process during the parasite’s intracellular cycle . After host-cell invasion , the CDT are initially found in vacuoles that undergo lysosome fusion to hold the parasite inside ( parasitophorous vacuoles ) [66–69] . Once inside these vacuoles , the invading trypomastigotes ( MT or CDT ) initiate a differentiation process to A , which is able to evade the vacuole into the cytoplasm in an acidic-pH-dependent way [7–10 , 70] to initiate intracellular proliferation in the cytosol [9 , 67 , 68 , 71–73] . Notably , Ley et al . previously showed that T . cruzi fails to escape from the parasitophorous vacuole when it is alkalinized by NH4Cl [9] . In this work , the inhibition of GS activity impaired parasitic vacuole evasion by A , the parasite stage displaying the highest GS activity . Interestingly , this process was also affected in a dose-dependent manner , and notably , MS showed its effect on CDT production at concentrations similar to the estimated IC50 of the recombinant enzyme . Remarkably , CHO-K1 is almost 103 times less sensitive to MS ( IC50 > 20 mM , selectivity index > 849 . 15 ) [42] , indicating that the observed phenomenon was not due to a toxic effect of MS on the host cells . In summary , considering the following: we propose that TcGS is involved in the maintenance of intracellular pH by contributing to the regulation of the intravacuolar content of NH4+ ( Fig 10 ) . We also show that interference with this system affects the efficiency of infection . To our knowledge , no reports on off-target effects of MS were published so far . However , this possibility cannot be ruled out . Upon the availability of methods allowing to perform knock-out or knock-down of essential genes in an inducible way in amastigotes , the involvement of GS in the evasion of parasites from the PV into the cytoplasm during infection of host-cells will reinforce the findings reported herein .
E from CL strain clone 14 were maintained in exponential growth phase by subculturing every 48 h in LIT medium supplemented with 10% FCS at 28°C as previously described [75] . The Chinese Hamster Ovary cell line CHO-K1 ( kindly provided by Maria Júlia Manso Alves , Department of Biochemistry , Institute of Chemistry , University of São Paulo , São Paulo—Brazil ) was cultivated in RPMI medium supplemented with 10% heat-inactivated fetal calf serum ( FCS ) , 0 . 15% ( w/v ) NaCO3 , 100 units/ml penicillin and 100 μg/ml streptomycin at 37°C in a humid atmosphere containing 5% CO2 . E of T . cruzi CL strain clone 14 [76] were maintained in the exponential growth phase by subculturing every 48 h in LIT medium supplemented with 10% FCS at 28°C . CDT were obtained by infection of CHO-K1 cells as described previously [46] . Cells were routinely grown on standard YP or YNB-based drop-out media supplemented with appropriate carbon sources . Introduction of plasmids into yeast cells was done by the lithium-acetate method [77] . The SAH35 strain is a derivative of W303-1a ( MATa leu2-3 , 112 trp1-1 can1-100 ura3-1 ade2-1 his3-11 , 15 GLN1UAS::GAL1UAS-6xHisGLN1-NATr ) in which the endogenous upstream 5’ untranslated and promoter sequences of the gene GLN1 were substituted with those from the GAL1 gene using a linear DNA construct and one-step gene replacement procedures . Briefly , plasmid pAH-GG1 was constructed by introducing PCR-amplified genomic sequences comprising nucleotides -569 to -246 with respect to GLN1 translation start and the ORF of GLN1 as HindIII-BglII and BamHI-ClaI fragments into plasmid pAH-N15 , respectively . The latter is a modified version of pYM-N15 [78] obtained from EUROSCARF ( http://www . euroscarf . de/index . html ) that had its GPD1 promoter substituted with a GAL1 promoter . In addition to the genomic sequence , the GS ORF fragment also included a His6 tag to be expressed as an N-terminus domain . The 2746 bp long HindIII-EcoRI fragment obtained from pAH-GG1 was introduced into W303-1a , and transformants were selected on YPGal plates supplemented with 0 . 1 mg/ml nourseothricin . Complementation assays were done by drop tests , as previously described [79] , on YNB-based drop-out media substituting ( NH3 ) 2SO4 with 10 mM glutamate as a non-repressible N-source and , where indicated , supplementing with 100 mg/l glutamine [80] . The putative TcGS gene ( TcCLB . 503405 . 10—template sequence ) was identified from the T . cruzi genome project database ( http://www . genedb . org ) . The TcGS coding region was amplified by PCR using T . cruzi CL14 strain genomic DNA as a template and gene-specific primers designed with restriction sites for the enzymes BamHI and XhoI: TcGS forward 5′-AAGGATCCATGACAGGC TTGAAGGAGAAAAG -3′ and TcGS reverse 5′-GGCTCGAGTGACAAATCGCCAAATTTCATCC -3′ . PCR amplification settings were set at 95°C ( 5 min ) and 32 cycles using the following conditions: initial denaturation cycle at 92°C ( 1 min ) , annealing at 60°C ( 1 min ) and elongation at 72°C ( 2 min ) . A single fragment ( 1 . 043 kb ) was amplified and the PCR product was purified and cloned into the pGEM-T Easy vector ( Promega , Madison , WI , United States ) . Selected clones were sequenced , and the expected identity of the cloned DNA fragments to GS was confirmed using the BLAST software program ( http://blast . ncbi . nlm . nih . gov/ ) . The gene encoding the putative GS enzyme was further subcloned into the pET28a ( + ) expression vector as previously described [34] , and the construct was used to transform E . coli BL21-CodonPlus ( DE3 ) cells . The bacteria were grown in Luria-Bertani ( LB ) medium containing 100 μg/ml Kanamycin and 5 μg/ml Tetracycline at 37°C until an OD600 of 0 . 6 was reached . Expression of TcGS was induced by the addition of the enzyme substrates ( 100 μM ) and isopropyl-1-thio-β-D-galactopyranoside ( IPTG ) to a final concentration of 0 . 25 mM , and cells were maintained at 16°C for 24 h . For protein purification , the cells were harvested , resuspended in lysis buffer ( 50 mM Tris-HCL pH 7 . 5 , 500 mM NaCl , and 1 mg/ml lysozyme ) containing protease inhibitors and subjected to 10 cycles of sonication ( ten 30 sec pulses followed by 30 sec of rest between cycles ) . The recombinant His6-tagged protein was purified using Ni2+ nitrilotriacetic ( NTA ) column affinity chromatography ( Qiagen , Hilden , North Rhine-Westphalia Germany ) according to the manufacturer’s instructions . Total RNA was extracted from different T . cruzi stages and CHO-K1 cells ( control ) using TRIzol reagent ( Invitrogen , Life Technologies , Carlsbad , California , United States ) . RNA preparations were treated with RNase-free DNase I ( Fermentas , Life Sciences , Waltham , Massachusetts , United States ) and checked by running aliquots in 1% agarose gels . Reverse transcription was performed with SuperScript IITM ( Invitrogen , Life Technologies , Carlsbad , California , United States ) using the anti-sense Oligo ( dT ) primer , 5 μg of RNA and by following the manufacturer’s instructions . The primers used for qRT-PCR analysis were designed using software PrimerBlast ( NCBI ) . Primers were designed based on the nucleotide sequences of T . cruzi glyceraldehyde-3-phosphate dehydrogenase ( GAPDH ) ( GenBank accession number: AI007393 ) , which was used as a housekeeping gene [27] , and TcGS ( GenBank accession number–template sequence: XP_803102 . 1 ) . The primer sequences were GAPDH forward ( 5′-GTGGCAGCACCGGTAACG-3′ ) , GAPDH reverse ( 5′-CAGGTCTTTCTTTTGCGAAT-3′ ) , TcGS forward ( 5′- AAGGATCCATGACAGGCTTGAAGGAGAAA AG -3′ ) and TcGS reverse ( 5′- GGCTCGAGTGACAAATCGCCAAATTTCATCC-3′ ) . qRT-PCR analyses were performed using Mastercycler ep REALPLEX 1 . 5 ( Eppendorf , Hamburg , Germany ) equipment and a SYBR Green QuantiMix EASY SYG KIT ( Biotools Quantimix EasySyg , Madrid , Spain ) for amplicon quantification . PCR conditions were as follows: initial denaturation at 95°C ( 10 min ) followed by 40 cycles of 94°C ( 1 min ) , 62°C ( 1 min ) and 72°C ( 2 min ) . In all cases , denaturation curves for the PCR products were obtained . Data obtained were analyzed using REALPLEX v1 . 5 software . A fold-change in the expression of transcripts was obtained using the 2-ΔCT method [81] . All time-fold variations were calculated using GAPDH as a housekeeping gene . cDNA from CHO-K1 cells was used as a control . The protein extracts were obtained from cells in exponential growth phase ( 5 x 107 cells/ml ) . Cells were harvested by centrifugation , washed 3 times with PBS and resuspended in TSB buffer . The parasites were lysed by sonication with 5 cycles of 30 sec with 30-sec rest intervals between cycles . After centrifugation at 12 , 000 x g for 30 min , the supernatants containing the protein extracts were used in enzyme activity assays and Western blotting . Quantitation of total protein was done by the classical method of Bradford [82] using a solution of BSA ( bovine serum albumin ) as a standard to construct calibration curves . Sodium dodecyl sulfate polyacrylamide gel electrophoresis ( SDS-PAGE ) was undertaken using 10% ( v/v ) polyacrylamide gels according to the method described in [83] . Briefly , the protein extracts ( Supernatants corresponding to 2x107 T . cruzi cells or 5x106 CHO-K1 ) or TcGS recombinant ( TcGSr ) was separated by ( SDS-PAGE ) and then transferred to nitrocellulose membranes ( Supported Nitrocellulose Membrane , Bio-Rad , Hercules , California , U . S . A ) using a Trans-Blot Semi-Dry Transfer Cell ( Bio-Rad ) [83] . After the transfer , the membranes were stained with Ponceau S ( 0 . 1% diluted in 10% acetic acid ) and detained in tap water , allowing the evaluation of transfer efficiency . Membranes were blocked for 2 h with PBS-0 . 3% Tween20 ( PBS-T ) supplemented with 5% skim milk . After blocking , the membranes were incubated with primary antibody anti-GS ( 1:1000 ) , stirring gently for 1 h at 4°C and were then washed three times for 5 min with PBS-T . Then , incubation was carried out for 45 min with secondary antibody conjugated with HRP enzyme ( 1:2500 ) ( GE Healthcare , horseradish peroxidase ) , followed by washes as described above . We then performed detection using chemiluminescence reagent SuperSignal West Pico Chemiluminescent Substrate ( Thermo Scientific , Waltham , Massachusetts , USA ) according to the manufacturer's manual . Exponentially growing E in different life cycle stages were resuspended in culture medium without serum containing 100 nM MitoTracker ( Molecular Probes , Eugene , Oregon , United States ) and treated according to manufacturer’s instructions for mitochondrial staining . Cells were washed with PBS and fixed with 4% ( v/v ) paraformaldehyde in PBS for 20 min at room temperature or with 100% methanol for 10 min . Paraformaldehyde-fixed cells were permeabilized with 0 . 1% Triton for 5 min . Fixed cells were washed three times with PBS and incubated with a 1:300 dilution of primary mouse antibody against GS for 1 h . The coverslips were rinsed three times with PBS and incubated with a 1:2000 dilution of goat anti-mouse IgG conjugated to Alexa Fluor 488TM in blocking solution for 1 h . After washing the coverslips three times in PBS , they were incubated with DAPI ( 1 mg/ml ) and washed again with PBS . Images were acquired through a z-series of 0 . 2 μm using a lens of 100X 1 . 35NA with Cell R software in Olympus IX81 microscopy . Images were deconvoluted using Autoquant X2 . 1 . Two methods were used to determine the enzymatic activity of TcGS . The first method was used in parasite extracts , and it measured NADH oxidation and the increase in absorbance at 340 nm . This molecule is substrate of lactate dehydrogenase ( LDH ) . Imidazole HCl buffer ( 34 mM ) , phosphoenolpyruvate ( 33 mM ) , magnesium chloride ( 2 mM ) , potassium chloride ( 18 . 9 mM ) β-NADH ( 0 . 25 mM ) , pyruvate kinase ( PK ) ( 28 units ) and LDH ( 40 units ) were added to their respective concentrations in two quartz cuvettes ( sample and white ) . In a first evaluation of the activity of GS , the substrates L-glutamate , NH4+ and ATP were adjusted to a final concentration of 1 mM . The measurements started with the recombinant enzyme or extract of T . cruzi , and a final oxidation of NADH at 340 nm was recorded . The reaction was started by adding 100 μg of the extract to the assay reaction mixture , which was incubated and measured for 10 min . The second method determined TcGS activity in the recombinant enzyme by measuring the production of inorganic phosphate ( Pi ) [84] . Before starting the reaction mix , the following solutions were prepared: 1 . Ammonium heptamolybdate solution: Approximately 32 ml of H2SO4 were carefully added into 100 ml of Milli-Q H2O in ice under laminar flow . Furthermore , we dissolved 3 . 7 grams of ammonium molybdate ( Sigma- Aldrich , St . Louis , Missouri , USA ) in 50 ml of Milli-Q H2O . The solutions were mixed , and 200 ml of Milli-Q H2O was added . The final solution was kept at room temperature and protected from light . 2 . Malachite green solution: 1 g of polyvinyl alcohol was dissolved in 50 ml of Milli-Q H2O . The solution was then filtered , and 18 . 5 mg of malachite green ( Sigma- Aldrich , St . Louis , Missouri , USA ) was added . The solution was mixed and stored at room temperature and protected from light . KM and Vmax values for recombinant TcGS were determined by regression analysis of the initial reaction velocity versus glutamate concentration using the Michaelis-Menten equation . The optimum pH for recombinant TcGS activity was determined using a three-buffer system , which ranged from a pH of 5 . 0 to 9 . 0 and was composed of 34 mM each of MES , imidazole HCl or Tris Buffer . The kinetic parameters of the enzymatic reactions were calculated from at least three independent experiments . Two methods were performed to verify the properties of MS as a TcGS inhibitor: ( i ) E extracts were carried as described previously and incubated with different concentrations of MS at 28°C for 30 min . After this time , GS activity was measured . ( ii ) TcGSr was purified as described previously , and the glutamine synthetase activity reaction was started with different concentrations of MS . Moreover , we investigated the inhibition constant ( Ki ) of glutamate . This constant is related to enzyme-inhibitor affinity . The Ki determination consists of the reestablishment of kinetic parameters under different concentrations of the inhibitor . Ultimately , Ki is the x-axis intersection of the linear function derived from the ratio of apparent Vmax / apparent KM [85] . E of T . cruzi in the exponential growth phase ( 5 . 0 to 6 . 0 x 107 cells/ml ) cultured in fresh-LIT medium were treated with different concentrations of MS ( range of 50 μM to 1 , 000 μM ) or not ( negative control ) . Rotenone ( 60 μM ) and antimycin ( 0 . 5 μM ) were used as positive controls . Cells ( 2 . 5 x 106 cells/ml ) were kept in 96-well culture plates at 28°C . Cell proliferation was estimated by reading the optical density ( OD ) at 620 nm for eight days as previously described [46] . On the fifth day of proliferation ( exponential growth phase ) , the IC50 was calculated by fitting the data to a typical dose-response sigmoidal curve using the programs OriginPro8 and GraphPad Prism 5 . 0 . CHO-K1 cells ( 5 . 0 x 104 per well ) were infected with CDT forms ( 2 . 5 x 106 per well—50 parasites per cell ) for three h in a 24 well-plate . CHO-K1 were cultivated in RPMI medium supplemented with SFB 10% , incubated at 37°C and treated with different concentrations of MS ( range of 5 μM to 500 μM ) . The plate was incubated at 33°C . CDT were collected in the extracellular medium on the fifth day and counted in a Neubauer chamber . CHO-K1 cells ( 1 . 0 x 104 per dish—Corning BioCoat Culture Dishes , New York , NY , United States ) , cultivated in RPMI medium supplemented with SFB 10% were incubated with CytoPainter LysoNIR Indicator Reagent ( Abcam , Cambridge , United Kingdom—1:1000 –v/v ) for 1 h , LysoNIR is a lysotropic dye that selectively accumulates in lysosomes via the lysosome pH gradient . After this time , the cultures were washed 2 times with PBS and infected with CDT forms ( 5 x 105 per well– 50 parasites per cell ) for three h . The cultures were washed another 2 times with PBS and incubated with MS ( concentrations for IC50 and IC80 in the intracellular cycle– 20 ) and Hoechst 33342 ( 1:1000 –Thermo Fisher Scientific ) . After different incubation times ( T0; 1 h , 6 h and 24 h ) , images were acquired with a digital DFC 365 FX camera coupled to a DMI6000B/AF6000 microscope ( Leica ) , and Software AF6000 was used to estimate the percentage of parasites within parasitophorous vacuoles . | Trypanosoma cruzi , the agent that causes Chagas disease , has a complex life cycle , alternating between insects and mammals and thus facing environments with different metabolite compositions . T . cruzi can consume glucose and/or amino acids , depending on their availability . However , amino acid consumption produces excess ammonium , which must be eliminated in a non-toxic manner . Here , we show that the enzyme glutamine synthetase contributes to the management of excess ammonium and uses it to form the amino acid glutamine . During its life cycle , the parasite invades mammalian host cells and transiently becomes enclosed in a tight vacuole , where it differentiates into the amastigote , an amino acid consumer stage . Amastigotes must escape from the vacuole into the host-cell cytoplasm to initiate intracellular replication . In this work , we show that the inhibition of T . cruzi glutamine synthetase aborts parasite evasion from the vacuole . We propose that this enzyme contributes to the control of ammonium produced by parasite metabolism , as ammonium increases the internal pH of the parasitophorous vacuole , making the enzymes for the T . cruzi evasion process non-functional . This knowledge could be useful for designing new anti-T . cruzi drugs . | [
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"pr... | 2018 | The glutamine synthetase of Trypanosoma cruzi is required for its resistance to ammonium accumulation and evasion of the parasitophorous vacuole during host-cell infection |
The four serotypes of dengue virus ( DENV ) cause dengue fever ( DF ) and dengue hemorrhagic fever/dengue shock syndrome ( DHF/DSS ) . Severe disease has been associated with heterotypic secondary DENV infection , mediated by cross-reactive antibodies ( Abs ) and/or cross-reactive T cells . The role of cross-reactive immunity in mediating enhanced disease versus cross-protection against secondary heterotypic DENV infection is not well defined . A better understanding of the cross-reactive immune response in natural infections is critical for development of safe and effective tetravalent vaccines . We studied the B cell phenotype of circulating B cells in the blood of pediatric patients suspected of dengue during the 2010–2011 dengue season in Managua , Nicaragua ( n = 216 ) , which was dominated by the DENV-3 serotype . We found a markedly larger percentage of plasmablast/plasma cells ( PB/PCs ) circulating in DENV-positive patients as compared to patients with Other Febrile Illnesses ( OFIs ) . The percentage of DENV-specific PB/PCs against DENV-3 represented 10% of the circulating antibody-producing cells ( ASCs ) in secondary DENV-3 infections . Importantly , the cross-reactive DENV-specific B cell response was higher against a heterotypic serotype , with 46% of circulating PB/PCs specific to DENV-2 and 10% specific to DENV-3 during acute infection . We also observed a higher cross-reactive DENV-specific IgG serum avidity directed against DENV-2 as compared to DENV-3 during acute infection . The neutralization capacity of the serum was broadly cross-reactive against the four DENV serotypes both during the acute phase and at 3 months post-onset of symptoms . Overall , the cross-reactive B cell immune response dominates during secondary DENV infections in humans . These results reflect our recent findings in a mouse model of DENV cross-protection . In addition , this study enabled the development of increased technical and research capacity of Nicaraguan scientists and the implementation of several new immunological assays in the field .
Dengue is the most prevalent mosquito-borne viral disease affecting humans worldwide , mainly encountered in tropical and sub-tropical regions in peri-urban and urban areas , with almost half of the world's population at risk for infection . Dengue is caused by four dengue virus serotypes ( DENV-1–4 ) , transmitted by Aedes aegypti and Ae . albopictus mosquitoes . DENV infection can be asymptomatic or can cause a spectrum of disease , which spans from classical dengue ( DF ) to more severe forms termed dengue hemorrhagic fever ( DHF ) and dengue shock syndrome ( DSS ) [1] . DF is an incapacitating severe flu-like illness that usually resolves spontaneously . The main symptoms include high fever , retro-orbital pain and headache , muscle and joint pain , and rash . DHF/DSS is a potentially fatal form of dengue . DHF is characterized by hemorrhagic manifestations , platelet count ≤100 , 000 cells/mL; and signs of plasma leakage that may include elevated hematocrit , pleural effusion , ascites , edema , hypoproteinemia and/or hypoalbuminemia . If plasma leakage continues without appropriate fluid resuscitation , DSS can ensue . DSS presents with signs of circulatory failure ( narrow pulse pressure or hypotension accompanied by clinical signs of shock ) in addition to the signs and symptoms found in DHF . An estimated 500 , 000 patients require hospitalization each year for DHF/DSS , a large proportion of whom are children [2] . Recently , the WHO developed a new classification of dengue disease that replaces the traditional classification and includes Dengue with or without Warning Signs and Severe Dengue [3] . This new classification has proven to be useful in clinical management of DENV-infected individuals; however , it may be less well-suited for pathogenesis studies [4] . The four DENV serotypes co-circulate in regions like South-East Asia where dengue is hyper-endemic . In contrast , in Nicaragua , one DENV serotype tends to dominate for several years , before being replaced by another serotype , with lower-level co-circulation of other DENV serotypes . DENV-3 has been the dominant serotype circulating in the period 2008 to 2011 in Nicaragua [5] . Prior to this , DENV-2 was the predominant serotype between 1999 and 2002 and again between 2005 and 2007 [5] , [6] , [7] , [8] , while DENV-1 predominated between 2002 and 2005 [9] . DENV-4 circulates at a low level in Nicaragua [9] . Although a large proportion of DENV infections remain asymptomatic , epidemiological studies have demonstrated an association between more severe disease and secondary ( 2° ) heterotypic DENV infections with a distinct serotype from the primary ( 1° ) DENV infection [10] , [11] , [12] , [13] , [14] . This increase in severity during 2° heterotypic DENV infections has been attributed to antibody ( Ab ) -dependent enhancement ( ADE ) , where Abs to the 1° infecting serotype bind but do not neutralize the second infecting serotype , instead facilitating an increase in viral uptake by Fcγ-receptor bearing cells [15] , [16] , [17] . In addition to ADE , cross-reactive T cells , formed during the 1° DENV infection , are over-activated , inducing a “cytokine-storm” syndrome implicated in the pathogenesis of shock syndrome and severe disease [18] , [19] , [20] , [21] . No specific treatment is currently available for dengue , and vaccines trials are in Phase 1 and 2 . A better understanding of the immune response developed during natural infections may be beneficial for future vaccine design as well as for defining correlates of protection for the current vaccine trials . Indeed , a balanced and long-lasting T cell , B cell and Ab response against the four serotypes is the goal of an effective tetravalent vaccine . While cross-reactive pre-formed Abs have been implicated in ADE , a cross-reactive B cell and Ab response may be beneficial and protective [22] , [23] , [24] , [25] . In addition , we and others have shown in a mouse model of DENV infection that cross-reactive T cells can be protective [25] , [26] , [27] . Clearly , in humans , cross-reactive immune responses can be protective , as the majority of 2° DENV infections are asymptomatic or result in mild disease [12] . Different B cell compartments can be identified according to their phenotype , and several B cell subsets circulate in the blood during the acute phase of an infection . Naïve B cells , memory B cells and plasma cells ( PCs ) are phenotyped by staining with surface markers followed by flow cytometry [28] . During a 1° infection , naïve B cells are stimulated and develop into antigen-specific B cells . These B cells either differentiate into memory B cells , which reside in the secondary lymphoid organs , or into PCs , which secrete antigen-specific Abs . Prior to differentiation into PCs , B cells undergo several cycles of proliferation and differentiate into an intermediate state called plasmablasts ( PBs ) [28] . Short-lived PCs are active during the acute infection , while long-lived PCs ( LLPCs ) migrate to the bone marrow and are responsible for long-term humoral immunity [29] , [30] . Memory B cells , which retain antigen-specific Abs at their surface , undergo affinity maturation , and only the clones bearing the Abs with the highest affinity survive long-term [31] . This process takes several weeks after the acute infection and continues despite the absence of circulating antigen . Memory B cells are the cells implicated in the antigen recall response and are rapidly activated during a 2° infection [28] . In this study , we analyzed the phenotype of circulating B cells by flow cytometry during the acute phase of infection in patients suspected of dengue presenting to the National Pediatric Reference Hospital , the Hospital Infantil Manuel de Jesús Rivera ( HIMJR ) , in Managua , Nicaragua . The striking increase we observed in the percentage of PB/PCs in DENV-positive patients prompted us to analyze the DENV-specific B cell response by ELISPOT ex vivo ( representing the circulating PCs at the time of infection ) in acute 2° infections , against the current infecting serotype ( DENV-3 ) and against a heterotypic serotype ( DENV-2 ) . In addition , we studied the DENV-specific avidity of serum IgG during acute infection and the neutralization capacity of the serum during the acute phase and at 3 months post-onset of symptoms . We found a higher number of cross-reactive DENV-specific PCs , which was associated with greater cross-reactive DENV-specific serum avidity during the acute phase of the infection , suggesting an important role for cross-reactive memory B cells in 2° DENV infections .
The protocol for this study was reviewed and approved by the Institutional Review Boards ( IRB ) of the University of California , Berkeley , and of the Nicaraguan Ministry of Health . Parents or legal guardians of all subjects provided written informed consent , and subjects 6 years of age and older provided assent . This study was performed from August 1 , 2010 , to January 31 , 2011 , during the peak of the dengue season in the Nicaraguan National Pediatric Reference Hospital , Hospital Infantil Manuel de Jesús Rivera ( HIMJR ) , located in the capital city of Managua . Inclusion criteria included age between 6 months and 15 years of age , fever or history of fever less than 7 days , and one or more of the following signs and symptoms: headache , arthralgia , myalgia , retro-orbital pain , positive tourniquet test , petechiae , or signs of bleeding . Exclusion criteria included: a ) a defined focus other than dengue , b ) children weighing less than 8 kg , c ) children less than 6 months of age , and d ) children 6 years of age and older displaying signs of altered consciousness at the time of recruitment . Patient data such as vital signs , clinical data , and radiographic or ultrasound results were collected on a daily basis by trained medical personnel using a standardized clinical report form until discharge . A blood sample was collected daily for a minimum of three days for Complete Blood Count ( CBC ) with platelets , blood chemistry , and diagnostic tests for dengue . Between days 14 and 21 after onset of symptoms , a blood sample was collected for convalescent follow-up . In addition , blood samples were collected at 3 , 6 , 12 , and 18 months post-illness onset . At each time-point , plasma and peripheral blood mononuclear cells ( PBMCs ) were prepared and stored in aliquots at −80°C and liquid nitrogen , respectively . Daily blood specimens were obtained from patients ( average 2 . 7 samples , range 1–3 ) , along with a convalescent/discharge sample ( for 96% of the enrolled patients ) . Analyzed samples were obtained between 1 and 8 days post-onset of symptoms ( mean of 5 . 6±0 . 08 days ) . Five mL of blood were collected in EDTA tubes ( Becton-Dickenson , Franklin Lakes , NJ ) for children with a body weight greater than 10 kg , and 4 mL were collected for children with a body weight equal or less than 10 kg . The transport temperature ( ∼28°C ) , time of sample collection , transport , reception , and processing ( total = ∼2 . 5 hours ( h ) ) were strictly controlled using personal data assistants ( PDAs ) with barcode scanners . Upon receipt in the National Virology Laboratory , an aliquot of 300 µL was removed for flow cytometry staining ( see below ) , and the remaining 4–5 mL of fresh blood was gently pipetted into a Leucosep tube ( Greiner Bio-One ) containing 3 mL of Ficoll Histopaque ( Sigma ) , and centrifuged at 500× g for 20 minutes ( min ) at room temperature . The plasma was removed and frozen in aliquots . The PBMC fraction was collected and transferred to a 15 mL conical tube containing 9 mL of PBS with 2% Fetal Bovine Serum ( FBS; Denville Scientific Inc . ) and 1% penicillin/streptomycin ( Sigma ) . Cells were washed 3 times in this solution by centrifugation at 500× g for 10 min and resuspended in 10 mL of complete media . Before the third wash , an aliquot of 500 µL was used to obtain a cell count using a hematology analyzer ( Sismex XS-1000i ) . After the third wash , cells were resuspended at a concentration of 107 cells/mL in freezing media consisting of 90% FBS and 10% dimethyl sulfoxide and aliquotted . Average yield was 9 . 6×106 total cells ( 3×106 to 17 . 6×106 ) . Cryovials containing the cell suspension were placed in isopropanol containers ( Mr . Frosty , Nalgene ) at −80°C overnight and then transferred to liquid nitrogen . Laboratory confirmation of DENV infection consisted of reverse transcription–polymerase chain reaction ( RT-PCR ) amplification of viral RNA [32]; isolation of DENV in C6/36 Aedes albopictus cells [7]; seroconversion of DENV-specific IgM antibodies as measured by IgM capture enzyme-linked immunosorbent assay ( ELISA ) [33] between acute-phase and convalescent-phase serum samples; and/or a four-fold or greater increase in total antibody titer , as measured by Inhibition ELISA [9] , [34] , between paired acute- and convalescent-phase serum samples . Identification of DENV serotype ( 1–4 ) was achieved by RT-PCR directed to the capsid gene [32] and/or nonstructural protein 3 gene [35] performed with RNA extracted from serum and/or supernatant of C6/36 cells obtained during virus isolation [36] . Primary DENV infections were defined by an antibody titer by Inhibition ELISA of <10 in acute-phase samples and/or <2 , 560 in convalescent-phase samples , and secondary DENV infections were defined by an antibody titer by Inhibition ELISA≥10 in acute-phase samples and/or ≥2 , 560 in convalescent-phase samples [6] . All serologic and virologic assays were performed in the National Virology Laboratory at the National Diagnosis and Reference Center ( CNDR ) of the Nicaraguan Ministry of Health . All clinical laboratory tests were performed in the Department of Clinical Chemistry at the CNDR or at the clinical laboratory at the Health Center Sócrates Flores Vivas [36] in Managua . DENV was propagated in Aedes albopictus C6/36 cells ( gift from P . Young , University of Queensland , Australia ) in M199 medium ( Invitrogen ) with 10% FBS at 28°C . Cell supernatants were collected on days 5 , 6 , 7 and 8 post-infection and either frozen at −80°C directly or after concentration . Concentrated virus was prepared by centrifugation through Amicon filters ( 50 kDa , 3 , 250× g for 20 min at 4°C ) . To prepare antigen for avidity and ELISPOT assays , DENV was cultivated in Vero cells in DMEM medium ( Invitrogen ) with 10% FBS at 37°C and 5% CO2 . Cell supernatants were collected on days 5 , 6 , 7 and 8 post-infection , clarified and concentrated by ultracentrifugation ( 26 , 000× g for 2 h at 4°C ) and resuspended in TNE ( Tris buffer , NaCl and EDTA ) or PBS . DENV-2 ( strain N172 , passage 2 ) and DENV-3 ( strain N7236 , passage 3 ) are clinical strains from two Nicaraguan patients isolated in the National Virology Laboratory in Managua , Nicaragua , and passaged minimally in our laboratory . Virus titers were obtained by plaque assay on baby hamster kidney cells ( BHK21 , clone 15 ) as previously described [37] . Raji-DC-SIGN-R cells ( gift from B . Doranz , Integral Molecular , Philadelphia , PA ) were grown in RPMI-1640 medium ( Invitrogen ) with 5% FBS at 37°C in 5% CO2 for use in neutralization assays [38] , [39] . On days 1 , 2 , and 3 of hospitalization , 300 ul of fresh whole blood was collected . Red blood cells were lysed using 1× RBC lysis buffer ( eBioscience ) . Cells were then blocked in 5% Normal Rat serum ( Jackson ImmunoResearch Inc . ) before staining . Cells were stained with anti-CD138 ( MI-15 ) or anti-HLA-DR FITC ( G46-6 ) , anti-CD20 PECy7 ( 2H7 ) , anti-CD27 PE ( O323 ) , and anti-CD38 PECy-5 ( HIT2 ) . For the analysis of marginal zone ( MZ ) B cells , cells were stained with anti-IgD FITC ( IA6-2 ) , anti-CD20 PECy7 , anti-CD27 PE , and anti-IgM PECy-5 ( G20-127 ) . Finally , cells were fixed in 2% paraformaldehyde . Samples were analyzed on a 4-color flow cytometer ( Epics XL , Beckman-Coulter ) . Results were analyzed using FlowJo software , version 7 . 2 . 5 ( TreeStar Software ) . All flow cytometric analysis was performed in the National Virology Laboratory at the CNDR in Managua . To quantify the number of DENV-specific PCs , frozen PBMCs from day 6 post-onset of symptoms were thawed and analyzed by ELISPOT ex vivo [40] . Ninety-six-well filter plates were first coated with 10 µg/well 4G2 monoclonal antibody ( MAb ) ( mouse , pan-DENV ) overnight at 4°C and then blocked for 2 h at 37°C with RPMI-1640 medium plus 10% FBS . Viruses DENV-2 N172 or DENV-3 N7236 prepared from infected Vero cells by ultracentrifugation were UV-inactivated for 10 min and then incubated with the plates at a dilution of 1∶25 in PBS to capture the virus . To detect the total number of IgG-secreting cells ( including both DENV-specific and non-specific ASCs ) , wells were coated with donkey anti-human IgG ( 10 µg/mL , Jackson ImmunoResearch Inc . ) . Virus-coated and anti-IgG-coated plates were incubated for 5–6 h with PBMCs to allow formation of Ab-antigen complexes ( anti-DENV Abs with DENV and total IgG with anti-IgG ) . Duplicate samples of 1×105 PBMCs per well ( for wells containing DENV antigen ) and 3×104 per well ( for wells containing anti-human IgG ) were plated in the first well , and four 2-fold dilutions were distributed in the subsequent wells . After the incubation period , cells were removed , and plates were washed and incubated with biotinylated anti-human IgG Ab overnight ( 1/1 , 000 , Jackson ImmunoResearch Inc . ) , followed by Streptavidin-Alkaline Phosphatase ( AP , Vector Inc . ) and BCIP/NBT substrate ( Vector Inc . ) . Resulting spots , representing DENV-specific Ab-producing B cells or total IgG Ab-producing cells , were counted by visual inspection using an inverted microscope . Control wells were coated with 4G2 MAb and PBS with no virus . For each sample , spots counted in the control wells were subtracted from the spots counted in the test wells coated with DENV-specific antigen . ELISPOT responses were considered to be positive if the number of spots was >200 spots/106 PBMCs for total IgG . Serum samples from the acute phase ( day 6 post-onset of symptoms ) and 3 months post-onset of symptoms were heat-inactivated at 56°C for 20 min and then diluted using eight 3-fold dilutions , beginning at 1∶10 and extending to 1∶21 , 870 . Neutralization was assessed by flow cytometry using a reporter ( GFP ) system with pseudo-infectious DENV reporter virus particles ( RVPs ) [39] . DENV RVP production ( DENV-1 , Western Pacific 74; DENV-2 , S16803; DENV-3 , CH53489; DENV-4 , TVP360; gift from B . Doranz , Integral Molecular ) was performed in 293TREx cell lines as described [38] , [39] . Supernatants containing RVPs were harvested , passed through 0 . 45-µm filters , aliquotted , and stored at −80°C . For all experiments , DENV RVPs were rapidly thawed from cryopreservation in a 37°C water bath and placed on ice for use in neutralization assays . DENV RVPs in RPMI-1640 complete medium were pre-incubated with an equal volume of serially diluted serum samples for 1 h at room temperature with slow agitation . Raji DC-SIGN-R cells were added to each well at a density of 40 , 000 cells per well , followed by incubation at 37°C in 5% CO2 for 48 h . Cells were subsequently fixed in 2% paraformaldehyde and analyzed for the percentage of cells expressing GFP by flow cytometry ( Becton-Dickinson LSRII ) . The percent infection for each serum dilution was calculated , and the raw data was expressed as percent infection versus log10 of the reciprocal serum dilution . The data were fitted to a sigmoidal dose-response curve , using Prism ( GraphPad Prism 5 . 0 Software ) to determine the titer of antibody that achieved a 50% reduction in infection ( 50% neutralization titer , NT50 ) . The NT50 titer is expressed as the reciprocal of the serum dilution . Maximum infection was determined in the absence of serum . Serum avidity was measured using a modified ELISA protocol with urea washes [25] , [41] , [42] . Supernatant from Vero cells infected with DENV-2 N172 and DENV-3 N7236 was ultracentrifuged ( 26 , 000× g for 2 h at 4°C ) to prepare concentrated virus . Viruses were UV-inactivated for 10 min , plated in carbonate buffer overnight in a flat-bottom 96-well plate , washed , and then blocked with PBS-T ( PBS with 0 . 1% Tween-20 ) containing 5% nonfat dry milk . Wells were incubated for 1 h with serum samples from 1° or 2° DENV infections diluted in blocking buffer . Convalescent samples ( day 14 to 21 post-onset of symptoms ) were used for the analysis of 1° DENV infections , while acute samples ( day 6 post-onset of symptoms ) were used for the analysis of 1° DENV infections . The plates were washed for 10 min with different concentrations of urea ( 6 M urea for primary DENV cases and 9 M urea for secondary DENV cases ) before adding the secondary biotin-conjugated Ab ( donkey anti-human IgG ) and streptavidin-AP conjugate . Finally , PnPP substrate was added to the wells , and optical density ( OD ) values were measured at 405 nm using KC Junior software . Background levels were measured in wells that were treated with normal human serum . For each plate , background was subtracted , and percentage of IgG bound was calculated by dividing the adjusted OD after urea washes by the adjusted OD after PBS . Non-parametric analyses using the two-sided Wilcoxon Rank Sum test were used for pairwise comparisons , and the Mann-Whitney test was used for non-paired analysis . The Spearman test was used to examine correlations . Calculations were performed in GraphPad Prism 5 . 0 software .
Between August 1 , 2010 , and January 31 , 2011 , 216 patients were enrolled for suspected dengue at the National Pediatric Reference Hospital , HIJMR . Twelve patients were excluded from analysis; one patient dropped out of the study after enrollment and 11 patients had an undetermined dengue diagnostic result . Overall , 204 patients were followed up and their characteristics are shown in Table 1 . One hundred and thirty patients ( 63 . 7% ) were laboratory-confirmed as dengue-positive . Among these , 75 ( 36 . 8% ) were 1° and 55 ( 63 . 2% ) were secondary 2° DENV infections ( Table 1 ) . Serotype identification was achieved in 86 . 2% of dengue-positive cases , with 108 of 112 ( 96 . 4% ) confirmed as DENV-3 infections . Of note , the severity of disease was relatively low in this season , with 32 ( 26 . 4% ) dengue-positive cases classified as DHF/DSS [1] . Prior to circulation of DENV-3 as the dominant serotype in 2008–2010 [5] , DENV-2 was the predominant circulating serotype in Nicaragua between 1999 and 2002 and again between 2005 and 2007 [6] , [7] , [8] , while DENV-1 predominated between 2002 and 2005 [9] . Thus , children with secondary DENV infections were most probably previously infected with DENV-1 , DENV-2 , or both . Fresh whole blood collected during the first three days of hospitalization in the HIMJR was stained with MAbs and analyzed by flow cytometry in order to phenotype the B cells circulating at the time of infection . Dengue diagnostic ( RT-PCR ) results were obtained within 24 h after hospital admission . B cells from all cases were phenotyped on day 1 , while B cells from all dengue-positive cases and one out of every five OFI cases were phenotyped on all three days . This staining allowed us to distinguish between naïve B cells ( CD20+CD27− ) , memory B cells ( CD20+CD27+ ) and PB/PCs ( CD20lowCD27high ) ( Figure 1A ) . In addition , among the memory B cells , the marginal zone ( MZ ) B cell subset was analyzed ( IgD+IgM+ ) ( Figure 1B ) . As expected , the PB/PCs expressed high levels of CD38 , which is a marker of cell activation , and variable levels of CD138 , which is a cell surface marker found only on PCs . In addition , this population expressed high levels of HLA-DR , indicating activation of these cells ( Figure 1A ) . The percentages of different B cell subsets were then analyzed over time . While no increase in percentage of PB/PCs over time was observed in OFI cases , this percentage increased and peaked on day 5 post-onset of symptoms in DENV-positive . On day 5 , a significant increase in percentage of PB/PCs was found in DENV-positive patients as compared to OFI cases ( mean DENV-positive = 4 . 72±0 . 97% vs . mean OFI = 0 . 96±0 . 69% , p = 0 . 022 ) ( Figure 2A ) . Of note , among DENV-positive patients , no statistical difference in percentage of PB/PCs was found at day 5 post-onset of symptoms between 1° and 2° infections ( mean 1° = 4 . 99±1 . 35% vs . mean 2° = 4 . 25±1 . 38% , p = 0 . 76 ) ( Figure 2B ) or between DF and DHF/DSS cases ( mean DF = 4 . 42±1 . 23% vs . mean DHF/DSS = 5 . 50±1 . 51% , p = 0 . 48 ) ( data not shown ) . A lower percentage of memory B cells was found on day 4 post-onset of symptoms in DENV-positive cases ( mean DENV-positive = 1 . 93±0 . 42% vs . mean OFI = 7 . 52±2 . 07% , p = 0 . 020 ) , but no clear increase over time was seen in either of the two populations ( Figure 2C ) . A slightly higher percentage of naïve B cells was noted on day 3 post-onset of symptoms in DENV-positive cases ( mean DENV-positive = 7 . 16±0 . 76% vs . mean OFI = 5 . 14±1 . 52% , p = 0 . 032 ) , but again no clear increase over time was seen in either population ( Figure 2D ) . A significantly higher percentage of MZ B cells was found on day 2 post-onset of symptoms in OFI cases ( mean DENV-positive = 6 . 57±2 . 55% vs . mean OFI = 20 . 82±3 . 09% , p = 0 . 020 ) , but no significant differences were found at later time-points ( Figure 2E ) . These data correlate with data on absolute numbers of B cells calculated based on the number of total lymphocytes ( Figure S1 ) . Of note , despite a higher number of total lymphocytes in OFI , the numbers of PB/PCs are greater in DENV-positive patients when compared to OFI between days 4 and 6 post-onset of symptoms . The characteristics of the patients with 2° DENV infections enrolled during the study are shown in Table 2 . Among the 55 cases , only confirmed DENV-3-positive cases were processed by ELISPOT to measure the number of DENV-specific PCs circulating in the peripheral blood during the acute phase ( day 6 post-onset of symptoms ) . Concentrated preparations of virions from clinical isolates of DENV-2 and DENV-3 from Nicaragua , minimally passaged in the laboratory , were used as antigen in order to match as closely as possible the virus to which the patients were exposed . Of 33 cases with detectable ASCs , DENV-3-specific PCs represented 11 . 5% of the total ASC/106 PBMCs ( mean DENV-3-specific ASC = 1 , 008±295 ASC/106 PBMCs and mean total ASC = 8 , 783±1 , 028 ASC/106 PBMCs ) ( Figure 3A ) . The median age of patients experiencing secondary DENV infection was 10 . 5 years , with a range of 5 . 5 to 15 . 8 years . According to epidemiological data regarding the DENV serotypes that have been circulating recently in Nicaragua [6] , [7] , [8] , [9] , [43] , these children could have been previously infected by DENV-1 and/or DENV-2 . As these are pediatric cases , the volume of blood drawn is restricted and thus the availability of PBMCs was limited . Therefore , only a subset of samples was processed using a second DENV serotype , in this case DENV-2 , in addition to DENV-3 as antigen ( Table 2 ) . DENV-2 was chosen to represent a cross-reactive , heterotypic serotype to which patients in the study were likely to have been exposed . A significantly higher number of DENV-2-specific ASC was found in these 2° DENV infections when compared to the number of DENV-3-specific ASC ( mean DENV-2 ASC = 4 , 402±823 ASC/106 PBMCs vs . mean DENV-3 ASC = 1 , 129±373 ASC/106 PBMCs; p<0 . 0001 ) ( Figure 3B ) . DENV-2-specific ASC represented on average 46±7% of the total ASC circulating at the time of infection , compared to 10±3% DENV-3-specific ASC ( p<0 . 0001 ) ( Figure 3C ) . Overall , these data show an increase in DENV-specific PCs during acute 2° DENV infections , with a greater increase in cross-reactive PCs that are specific to a previous infecting serotype rather than the current infecting serotype . A positive correlation was found between the titer of total DENV-specific Abs as measured by Inhibition ELISA and the number of DENV-2-specific PCs during acute infection , while no correlation was found with the number of DENV-3-specific PCs ( Figure 3D and E ) . This result suggests that the anti-DENV specific Abs are mostly produced by the cross-reactive PCs during an acute 2° DENV infection . In order to measure IgG serum avidity , we used a modified ELISA with urea washes [25] , [41] , [44] . The same clinical viral isolates from Nicaragua that were used in the ELISPOT assays were used in the avidity assay . To validate the assay using samples and virus from Nicaragua , we tested a subset of 42 1° DENV-3 cases from the 2010 hospital study . As the amount of IgG is low during the acute phase of 1° infections , we used serum samples from the convalescent phase ( day 14 to 21 post-onset of symptoms ) . The serum avidity of these samples was measured against both DENV-2 and DENV-3 . As expected , higher avidity was found against the infecting DENV serotype , DENV-3 , with a low level of cross-reactivity against DENV-2 ( mean % IgG bound to DENV-3 = 27 . 7±1 . 4% vs . mean % IgG bound to DENV-2 = 9 . 4±0 . 9%; p<0 . 0001 ) ( Figure 4A ) . We then measured the DENV-specific serum avidity during the acute phase of 2° DENV-3 infections ( day 6 post-onset of symptoms ) . The same subset of samples that was processed for DENV-2 and DENV-3 ELISPOT was processed by the avidity assay . As shown in Figure 4B , the cross-reactive serum avidity against DENV-2 was significantly higher than the homotypic serum avidity against DENV-3 ( mean % IgG bound to DENV-2 = 61 . 3±3 . 7% vs . mean % IgG bound to DENV-3 = 50 . 7±3 . 6%; p = 0 . 030 ) . Overall , these data show a greater cross-reactive DENV-specific IgG serum avidity as compared to homotypic DENV-specific IgG serum avidity during the acute phase of 2° DENV infections . Finally , we measured the DENV-specific neutralization capacity of patient serum against the 4 DENV serotypes using an RVP flow cytometry-based neutralization assay . The same subset of samples that was processed for DENV-2 and DENV-3 ELISPOTs was processed by the neutralization assay . The NT50 titer of 2° DENV-3 infections at 3 months post-onset of symptoms is shown in Figure 5A . The NT50 titer was high not only against DENV-3 ( mean 986±276 ) , the current infecting serotype , but also against DENV-2 ( mean 2039±371 ) . The NT50 against DENV-1 ( mean 404±91 ) and DENV-4 ( mean 390±192 ) were lower but detectable . Thus , after 2° DENV infections , a broad cross-reactive neutralization response develops against the 4 serotypes , consistent with previous reports . In addition , we measured the NT50 titer of these same samples during the acute phase of the infection at day 6 post-onset of symptoms . As expected , NT50 titers were higher during the acute phase when compared to the 3-month samples . The NT50 titer was high not only against DENV-3 ( mean 4783±1687 ) , the current infecting serotype , but also against DENV-2 ( mean 3979±1274 ) , DENV-1 ( mean 3244±1049 ) , and DENV-4 ( mean 4654±1342 ) . Thus , as at 3 months post-onset of symptoms , we found a broadly cross-reactive response to all 4 serotypes during the acute phase of the infection ( Figure 5B ) . Of note , no statistical significant difference was found between anti-DENV-2 and anti-DENV-3 NT50 titers , either during the acute phase or at the 3-month time-point .
In this study , we used flow cytometry to phenotype the B cell components circulating at the time of DENV infection , using fresh whole blood in Nicaragua . In addition , we measured the number of DENV-specific PCs during acute infection by ELISPOT using Nicaraguan virus preparations as antigen . Finally , we measured both the DENV-specific IgG serum avidity and neutralization capacity of the serum against different serotypes of DENV . Overall , we show that a large number of PB/PCs circulate during DENV infection when compared to OFIs , both during 1° and 2° DENV infections . We find a strikingly higher number of DENV-specific PCs and serum IgG avidity directed to a heterotypic DENV serotype ( DENV-2 ) as opposed to the current infecting serotype ( DENV-3 ) . Overall , we show that a cross-reactive B cell response dominates during the acute phase of 2° human DENV infections . A large percentage of PB/PCs circulate in the blood of DENV-infected children during the acute phase of infection , in both 1° and 2° DENV infections , as compared to children with OFIs . Of note , the amount of PB/PCs does not vary with age [45] . The percentage of PB/PCs circulating in the blood peaked at day 5 post-onset of symptoms . While we would have expected a high percentage of PB/PCs in both DENV-infected and OFI patients , the difference was marked and might point to either a stronger B cell response during DENV infections when compared to OFIs or to a difference between the time-points after infection at which the samples were collected in DENV-positive cases versus OFI cases . The definitive diagnosis of OFI cases is not known; however , possible differential diagnoses include influenza , rickettsiosis , and leptosporosis , among others . In an effort to define the possible viral etiology of OFIs , we analyzed DENV-negative cases using viral microarrays followed by deep sequencing and detected Human Herpesvirus 6 sequence and sequences related to other Herpesviridae and Circaviridae [46] . The course of disease of the OFIs , which may be different from dengue illness , and the fact that PB/PCs circulate in the blood for only a short period of time as compared to other B cell components [47] may explain the differences in percentage of PB/PCs between these two groups . In addition , certain viruses , like influenza and measles , are known to depress the immune system [48]; thus , some OFI patients may experience decreased proliferation of B cells either directly or secondarily due to decreased proliferation of T-helper cells , resulting in reduced numbers of PB/PCs . Of note , no difference in percentage of PB/PCs circulating in blood was noted when comparing 1° and 2° DENV infections . In contrast to PB/PCs , which circulate in the blood during a narrow time-window , the number of memory B cells circulating in the blood increases later during infection [47] . We observed an increase over time of memory B cells in DENV-infected patients , whereas this subset of cells decreased in OFI patients . Marginal zone ( MZ ) B cells are IgM+ “memory” B cells that have been implicated in the response against encapsulated bacteria , such as S . pneumoniae [49] . These cells are implicated in T-cell-independent immune responses and despite the presence of IgM at their surface , they present hypermutated immunoglobulin receptors [50] , [51] , [52] . Recently , highly neutralizing IgM+ MAbs have been generated from individuals infected by influenza [53] , and these MAbs have been shown to arise from the MZ B cell population [53] . We did not find a clear difference in the percentage of this population between the two groups . Thus , this subset of cells may not play a role during DENV infections . In order to further characterize the PB/PCs circulating during acute DENV infection , we measured the number of DENV-specific PCs at day 6 post-onset of symptoms by ex vivo ELISPOT , i . e . , without any stimulation of the PBMCs . First , we found that DENV-3-specific PCs constitute a substantial proportion ( ∼10% ) of total ASCs in the blood of patients with a 2° DENV-3 infection . Among the patients experiencing a 2° DENV-3 infection , a subset of samples were processed by ELISPOT against both DENV-2 and DENV-3 viruses . Interestingly , we found a higher number of PCs specific for the non-infecting serotype ( DENV-2 ) when compared to the currently infecting serotype ( DENV-3 ) . These DENV-2-specific PCs made up 46% of the total ASCs . These findings were associated with the IgG serum avidity data , where higher serum avidity was detected against DENV-2 as compared to DENV-3 . Thus , during an acute 2° DENV infection , cross-reactive PCs and cross-reactive Abs responsible for the higher avidity increase more than homotypic PCs and homotypic Abs directed to the current infecting serotype . In addition , a positive correlation between the total anti-DENV Ab titer was found only with DENV-2 specific PCs but not with DENV-3 specific PCs , consistent with other reports [44] . Thus , the increased number of anti-DENV Abs circulating during a 2° infection may be induced by cross-reactive PCs , and this rise in Ab titer is associated with an increased IgG serum avidity against a heterotypic serotype . These findings support the initial concept of “original antigenic sin” in dengue immunopathogenesis , whereby the humoral immune response in a secondary DENV infection is stronger to the prior infecting serotype [54] , [55] . These data are in accordance with our findings in our mouse model of sequential DENV infection , where we observed an increase in PCs , memory B cells , and highly avid Abs against the previous infecting serotype rather than against the current infecting serotype [25] . These data are also in accordance with recently published human data , which show an increase in cross-reactive memory B cells and cross-reactive serum avidity during the acute phase of 2° DENV infection in a population of DENV-infected children in Thailand [44] . These two sets of data are complementary , as we measured the number of DENV-specific PCs ex vivo ( plated directly for ELISPOT without prior in vitro stimulation ) during acute infection , while Mathew et al . [44] measured the number of memory B cells obtained from PBMCs polyclonally stimulated in vitro . Overall , these two studies suggest that the increase in cross-reactive PCs during an acute 2° DENV infection is mediated by the cross-reactive memory B cells formed during a previous infection with a different serotype . Neutralization assays during the acute phase and at 3 months post-onset of symptoms show a broadly cross-reactive response against the four serotypes of DENV , as previously described [56] . Thus , there appears to be no association during 2° DENV infection between neutralization capacity of the serum and the number of circulating DENV-specific PCs or increased DENV-specific serum avidity . Direct correlation between neutralization capacity of serum and serum avidity has not been shown thus far during DENV infection . In fact , it was found that no direct correlation exists between neutralization capacity and affinity of anti-DENV MAbs [57] ( K . Williams and E . Harris , unpublished data ) . In addition , in our mouse model of sequential DENV infection , we demonstrated an uncoupling of the neutralization and avidity responses during 2° DENV infections , with a higher DENV-specific avidity against the 1° infecting serotype and an increased neutralization capacity of the serum against the 2° infecting serotype [25] . Further analysis of 1° and 2° serum samples , including samples from patients enrolled in our Nicaraguan or other cohort studies for which the 1° infecting serotype is known , are needed to further investigate this question in humans . While other groups have used recombinant proteins for avidity and ELISPOT assays [44] , we used viral particles as antigen , prepared from Nicaraguan clinical viral isolates . Previous data have shown that human anti-DENV and anti-West Nile Virus ( WNV ) Abs bind to the viral prM/M protein and to sites on the envelope ( E ) protein or on several E monomers on the virion that are not preserved in the recombinant E formulation [58] , [59] , [60] . Thus , we preferred to use whole viral particles in our assays to better approximate the viral antigen seen by the immune response in vivo . In addition , the use of clinical viral isolates from Nicaragua represents the most relevant viral strains . The 2010–2011 dengue season in Nicaragua was characterized by low disease severity , with only 30 ( 23 . 1% ) cases of DHF and 2 cases ( 1 . 5% ) of DSS in our study . We did not find any difference in the number of DENV-specific PCs or in serum avidity during the acute infection between DF and DHF/DSS , but differences may exist in more severe cases . Further analyses of the B cell response during subsequent seasons with greater severity are warranted to study such associations . In addition , disease severity can be influenced by the serotype-specific sequence of infections and the time interval between sequential DENV infections [61] , [62] , [63] , issues that are better addressed using samples from prospective cohort studies . A separate study of a prior DENV-2 epidemic in Managua revealed a trend towards decreased serum avidity in more severe DSS cases when compared to DF and DHF cases ( M . O . Pohl , S . Zompi and E . Harris , unpublished data ) using both a urea-based ELISA and a virus competition ELISA [55] . More refined analysis of the serum avidity by surface plasmon resonance may be more sensitive , and such studies are currently underway . This study has several strengths . Given our established mouse model of DENV infection and disease , we can study the immune response in parallel in mice and humans . The mouse model allows a more complete mechanistic approach , e . g . , allowing the investigation of the role of the different immune components during DENV infections [25] , while the human studies extend the relevance of the findings to the clinical situation . For the first time , B cell- and Ab-based assays , including ELISPOTs and urea-based ELISAs , were carried out using viral particles purified from clinical isolates from the field as antigen . Using this type of antigen , prepared by propagating the virus in mammalian Vero cells , enables as close an approximation to the in vivo situation as possible . Finally , the flow cytometry was performed at the NVL/CNDR in Managua , Nicaragua . Although this limited the analysis to several four-color panels due to the cytometer available at the CNDR , it allowed analysis of fresh whole blood from children enrolled in the hospital-based dengue study . Importantly , establishing this assay in Nicaragua increased the research and technical skills of NVL personnel , which is complemented by our program of continuous training of Nicaraguan scientists at UC Berkeley in relevant scientific and technical areas . In-country use of the cytometer also resulted in continuous maintenance of the machine , which is now being used for additional projects , such as flow cytometry-based neutralization assays for serological investigation of DENV infection over time . One of the main limitations of this study was the low level of severity observed during the 2010–2011 season , which did not allow correlations between the number of DENV-specific PCs circulating during acute infection and disease severity to be performed . The use of samples from future more severe epidemics will be useful in investigating this question . In addition , the previous infecting serotype ( s ) of the 2° DENV infections hospitalized in this study is unknown . The use of samples from cohort studies , in which patients are followed prospectively over time , will allow an improved analysis of the serotype-cross-reactive response initially observed in this study . Overall , we have shown that during DENV infection , a high number of PB/PCs circulate in the blood and that during 2° DENV infection , the DENV-specific PCs are mostly cross-reactive and likely arise from memory B cells formed during previous heterotypic infections . This is associated with an increase in cross-reactive DENV-specific IgG serum avidity . The assays used in this study were either performed at the NVL in Managua , Nicaragua , or at UC Berkeley in collaboration with a researcher from Nicaragua who was trained in ELISPOT and avidity ELISA assays , thus increasing research capacity of Nicaraguan scientists . In addition , these assays were performed using clinical viral isolates from Nicaragua , better approximating the in vivo situation in humans . Lastly , these assays should be useful in the characterization of the humoral immune response induced by candidate dengue vaccines . | Dengue is the most common mosquito-borne viral infection of humans , with half the world's population at risk for infection . Four different dengue virus serotypes ( DENV-1 to -4 ) can cause the disease , which can be either inapparent or present with flu-like symptoms ( Dengue Fever ) , also known as “breakbone fever” . In a number of cases , the disease can be more severe and sometimes fatal , with signs of bleeding and vascular leakage leading to shock ( Dengue Hemorrhagic Fever/Dengue Shock Syndrome ) . Severe disease has been associated with secondary sequential DENV infections , i . e . , infection with a second DENV serotype different from the serotype causing the first infection . No specific treatment or vaccine is available . Understanding how the human immune response develops during a natural infection can be beneficial for future vaccine studies and trials . B cells are a subset of cells that produce antibodies and are thus essential in the response to natural infections and vaccines . We show here that during secondary DENV infections in humans , the B cell immune response to a previous infecting DENV serotype is stronger than the response against the current infecting serotype . In addition , this study allowed the development of research capacity and implementation of new immunological assays in Nicaragua . | [
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] | 2012 | Dominant Cross-Reactive B Cell Response during Secondary Acute Dengue Virus Infection in Humans |
Burkholderia pseudomallei is a gram-negative , facultative intracellular bacterium , which causes a disease known as melioidosis . Professional phagocytes represent a crucial first line of innate defense against invading pathogens . Uptake of pathogens by these cells involves the formation of a phagosome that matures by fusing with early and late endocytic vesicles , resulting in killing of ingested microbes . Host Rab GTPases are central regulators of vesicular trafficking following pathogen phagocytosis . However , it is unclear how Rab GTPases interact with B . pseudomallei to regulate the transport and maturation of bacterial-containing phagosomes . Here , we showed that the host Rab32 plays an important role in mediating antimicrobial activity by promoting phagosome maturation at an early phase of infection with B . pseudomallei . And we demonstrated that the expression level of Rab32 is increased through the downregulation of the synthesis of miR-30b/30c in B . pseudomallei infected macrophages . Subsequently , we showed that B . pseudomallei resides temporarily in Rab32-positive compartments with late endocytic features . And Rab32 enhances phagosome acidification and promotes the fusion of B . pseudomallei-containing phagosomes with lysosomes to activate cathepsin D , resulting in restricted intracellular growth of B . pseudomallei . Additionally , Rab32 mediates phagosome maturation depending on its guanosine triphosphate/guanosine diphosphate ( GTP/GDP ) binding state . Finally , we report the previously unrecognized role of miR-30b/30c in regulating B . pseudomallei-containing phagosome maturation by targeting Rab32 in macrophages . Altogether , we provide a novel insight into the host immune-regulated cellular pathway against B . pseudomallei infection is partially dependent on Rab32 trafficking pathway , which regulates phagosome maturation and enhances the killing of this bacterium in macrophages .
Host innate immune cells , particularly professional phagocytes , possess a wide range of antimicrobial defense mechanisms to eliminate the invading microbes [1] . Phagocytosis , an evolutionarily conserved process of the innate immune response , plays an indispensable role in the host-defense responses against a wide range of intracellular pathogens [2] . After the phagocytosis of pathogens by macrophages , the resulting intracellular vacuoles are termed as phagosomes [3] . The phagosomes are then processed in a series of interactions with different endosomes , resulting in the progressive acidification of the phagosome lumen and activation of the hydrolytic enzymes , which finally leads to their acquisition of degradative and antimicrobial properties [4] . Rab GTPases , well known as central regulators of vesicular trafficking , are closely linked to the endocytosis and trafficking of intracellular pathogens [5 , 6] . To date , many studies have shown that the Rab GTPases are involved in the formation and maturation of phagosomes . Phagosome purification combined with proteomic analysis have identified several Rab GTPases that associate with phagosomes . Of these , Rab5 and Rab7 are the most well-characterized Rab proteins with regard to their localization to phagosomes and their role in phagosome maturation [3] . Rab5 is associated with early phagosomes and facilitates the recruitment of its effector proteins , early endosome associated antigen ( EEA1 ) [7] . During the period of maturation , the phagosomes lose Rab5 and acquire Rab7 , which allows phagosomes to interact with the late endosomes and lysosomes [8] . Although there are over 70 Rab GTPases identified in mammalian cells and more than 20 on phagosomal membranes , but only a few of them have been investigated with regard to their function in phagosome maturation . Burkholderia pseudomallei is a facultative intracellular pathogen that causes the fatal infectious disease melioidosis , which has broad-spectrum clinical manifestations including pneumonia , localized abscesses , and septicemia [9] . Melioidosis is highly endemic across tropical and subtropical regions , especially in Southeast Asia and northern Australia . The common routes of infection with environmental B . pseudomallei are cutaneous inoculation , ingestion , and inhalation [10 , 11] . B . pseudomallei can invade and survive in both phagocytic and non-phagocytic cells [12 , 13] . Some mechanisms that allow phagocytes to limit the growth of B . pseudomallei have been elucidated [14–18] . Moreover , many studies have shown that B . pseudomallei can escape from the phagosome into the cytosol of phagocytic cells where it replicates and acquires actin-mediated motility , avoiding killing by the autophagy-dependent process [19–22] . However , the exact mechanistic details of B . pseudomallei adapt to the intraphagosomal environment and manipulate the phagocytic process remains unknown . Therefore , to identify host cell molecules and pathways utilized by B . pseudomallei for intracellular survival , we initially investigated the localization and expression of 19 Rab GTPases , which are critical regulators of membrane trafficking pathways . Using overexpression of EGFP-tagged Rab GTPases , we observed considerable localization of Rab32 with B . pseudomallei-containing phagosomes , and increased Rab32 expression . Rab32 is a multifunctional protein , depending upon its cellular localization and the cell type . It is well established that Rab32 is involved in the biogenesis of lysosome-related organelles ( LROs ) such as melanosomes , T cells , and platelet-dense granules [23 , 24] . In addition , Rab32 is also implicated in host response to bacterial infection . Hoffmann et al . previously showed , Rab32 associates with Legionella-containing vacuoles and appear to promote the intracellular growth of L . pneumophila [25] . Some recent studies have demonstrated that Rab32 is recruited to the vacuoles containing bacterial pathogens , such as S . Typhi and L . monocytogenes [26 , 27] , and it is essential to protect host cells from these pathogens . However , the exact mechanism of how Rab32 contributes to the restriction of intracellular pathogens is not completely understood . In addition to Rab GTPases can regulate phagosome maturation , increasing evidence indicates that microRNAs ( miRNAs ) are not only crucial regulators involved in modulating host innate immune responses to pathogens [28–30] , but also play critical roles in regulating the phagolysosomal pathway . However , the specific role of miRNAs in the regulation of membrane trafficking during B . pseudomallei infection is largely unknown . In this study , we aimed to explore the role of Rab32 in host-dependent immune mechanisms against B . pseudomallei infection . We found that B . pseudomallei upregulates the expression of Rab32 in infected macrophages by downregulating the expression of miR-30b/30c . Moreover , Rab32 is a functional GTPase that is required for limiting intracellular replication of B . pseudomallei by promoting the fusion of phagosomes with lysosomes .
Previous studies indicate that Rab GTPases have the ability to target microbial pathogen-containing vacuoles and coordinate a host-mediated defense response to control intracellular pathogen replication [26 , 27 , 31–33] . To investigate whether Rab32 is involved in preventing B . pseudomallei from replicating within the host cells , we used RAW 264 . 7 macrophages infected with B . pseudomallei and measured the expression of Rab32 by using quantitative real-time-PCR ( qRT-PCR ) and western blot analyses . As shown in Fig 1A and 1B , there was a gradual increase over time in the ratio of Rab32 to β-actin in B . pseudomallei infection ( multiplicity of infection , MOI = 10:1 ) as compared with an uninfected control in RAW264 . 7 cells . Consistent with the observed Rab32 which is upregulated in time course experiments; similar results were observed when MOI dependency was tested at 2 h post-infection ( Fig 1C and 1D ) . As host Rab GTPases regulate intracellular vesicular trafficking through specific interactions with vesicle membranes , we examined the localization of Rab32 in cultured macrophages infected with B . pseudomallei for different periods of time . We found that enhanced green fluorescent protein ( EGFP ) -Rab32 was strongly recruited to the B . pseudomallei-containing phagosomes 1 h to 6 h post-infection ( p . i . ) i . e . , after bacterial internalization ( Fig 1E ) . Maximum recruitment was at 2 h p . i . ( 60 . 4 ± 4 . 2% ) and recruitment gradually decreased after 4 h of infection ( Fig 1F ) . Interestingly , we found that Rab32 recruitment was specific for live B . pseudomallei as a heat-killed B . pseudomallei was unable to efficiently recruit Rab32 to phagosomes ( S1A Fig ) , compared to live B . pseudomallei only 5 . 3 ± 2 . 1% of heat-killed B . pseudomallei colocalized with Rab32 in time course experiments ( Fig 1F ) . In addition , we also found that heat-killed B . pseudomallei had no effect on the regulation of Rab32 mRNA and protein expression ( S1B and S1C Fig ) . Furthermore , heat-killed B . pseudomallei showed the same internalization rate as the live bacterium ( S1D and S1E Fig ) . Collectively , these results indicate that viable B . pseudomallei can be specifically sensed by the macrophages to trigger Rab32 expression and recruitment into the B . pseudomallei-containing phagosomes . To investigate the underlying mechanisms of B . pseudomallei infection which upregulates the expression of Rab32 , we used miRNA microarrays to analyze genome-wide miRNA expression profiles in RAW264 . 7 cells were infected with B . pseudomallei at an MOI of 10 . As shown in S1 Table , among the 124 differentially expressed miRNAs , 3 miRNAs were significantly upregulated ( P < 0 . 05 ) , while 121 miRNAs were significantly downregulated ( P < 0 . 05 ) . Fig 1A shows the heat map of top 40 miRNAs that were significant downregulated in response to B . pseudomallei infection at 4 h . MiRNAs negatively regulate the expression of target genes mainly by interaction in their 3' untranslated region ( UTR ) . Thus , we screened for miRNAs whose expression downregulated after B . pseudomallei infection by using target prediction tools: TargetScan and miRDB , as candidate miRNAs for the increased Rab32 expression specific . We found members of the miR-30 family were predicted to target the 3' UTR of Rab32 mRNA ( Fig 2B ) . The miR-30 family is an important member of miRNA family , which contains five members ( miR-30a , miR-30b , miR-30c , miR-30d , and miR-30e ) and located at different genomic positions [34] . To confirm the validity of our microarray data , the expression levels of key members of the mi-30 family of miRNAs ( miR-30b/30c/30d/30e ) were examined by qRT-PCR in macrophages after B . pseudomallei infection . As shown in Fig 2C , the expression of miR-30b/30c rapidly decreased in response to B . pseudomallei infection as early as 1 h p . i . , but miR-30d/30e did not decrease significantly . Additionally , similar results were obtained when B . pseudomallei infected RAW264 . 7 cells at 2 h p . i . , which showed a gradual decrease in the expression of miR-30b/30c in an MOI-dependent manner ( Fig 2D ) . We then also examined whether there were differential responses to the expression levels of miR-30 family members between live and heat-killed B . pseudomallei . Interestingly , the qRT-PCR analysis indicated that stimulation of RAW264 . 7 cells with heat-killed B . pseudomallei were unable to downregulate the expression of these miRNAs ( S2A and S2B Fig ) . The observed responses are consistent with results showing that heat-killed B . pseudomallei were unable to induce Rab32 expression and recruitment into the bacteria-containing phagosomes ( S1A and S1C Fig ) . Moreover , in order to examined whether the downregulation of miR-30b/30c was specific to B . pseudomallei , we used Burkholderia thailandensis ( an avirulent bacterium closely related to B . pseudomallei ) and other Gram-negative bacteria , like Salmonella typhimurium and Escherichia coli as controls . We found no significant changes in the expression levels of miR-30b/30c after infection with S . typhimurium , B . thailandensis , and E . coli ( Fig 2E ) . Taken together , these results show that the expression levels of miR-30b/30c decrease in response to B . pseudomallei infection . MiRNAs are small non-coding RNAs that negatively regulate post-transcriptional expression of target genes , which guide the binding of the miRNA-induced silencing complex ( miRISC ) to regions of partial complementarity located mainly within 3' untranslated region ( 3'UTR ) of target mRNAs , resulting in mRNA degradation and/or translational repression [35 , 36] . To identify whether Rab32 could be regulated by miR-30b and miR-30c . Firstly , we generated luciferase reporter vectors ( pmirGLO ) containing the wild-type or mutant 3′UTR of Rab32 mRNA predicted seed sequence ( Fig 3A ) . HEK293 cells were co-transfected with control or miR-30b/30c mimics and luciferase reporter vectors containing either wild-type or mutant sequence of Rab32 3′UTR . Luciferase activity was effectively suppressed in the cells co-transfected with miR-30b/30c mimics and the wild-type reporter vectors , while no obvious changes in luciferase activity were observed in the control or mutant reporter vector groups ( Fig 3B ) . The above data indicated that miR-30b/30c could bind to the 3′UTR predicted site of Rab32 , resulting in the suppression of Rab32 expression levels . Next , we explored whether overexpression of miR-30b/30c could decrease Rab32 expression in RAW264 . 7 cells . We found that mRNA and protein levels of Rab32 strongly decreased when treated with miR-30b/30c mimics as compared to the miRNA control ( Fig 3C and S3A Fig ) . By contrast , Rab32 mRNA levels and protein levels were enhanced when the cells were transfected with miR-30b/30c inhibitors ( Fig 3D and S3B Fig ) . These results clearly demonstrate that Rab32 is specific targets of miR-30b/30c in RAW264 . 7 cells . Since our results showed that B . pseudomallei infection upregulates Rab32 expression and recruits Rab32 to the bacterium-containing vacuole ( Fig 1B and 1E ) . Thus , we investigated whether miR-30b/30c affects the colocalization of Rab32 and B . pseudomallei phagosomes in RAW264 . 7 cells . As shown in Fig 3E and 3F by confocal microscopy , in RAW264 . 7 cells after transfection with the miR-30b/30c mimics , about 7% of B . pseudomallei was in Rab32-positive phagosomes at 2 h after infection , whereas transfection with the miR-30b/30c inhibitors significantly increased the proportion of Rab32-positive B . pseudomallei ( approximately 83%; Fig 3G and 3H ) . Collectively , these results demonstrated that miR-30b/30c suppressed the expression of Rab32 through mRNA degradation , thus affecting the recruitment of Rab32 to B . pseudomallei-containing phagosomes . Shortly after infection , Rab32 was recruited to the B . pseudomallei–containing phagosomes and remained associated with these phagosomes for several hours after infection ( Fig 1C and 1D ) . To monitor the trafficking stages of the bacteria–containing phagosomes in the endocytic pathway , we next investigated the features of the Rab32-positive compartments in B . pseudomallei infection . The association of markers for early ( EEA1 , Rab5 ) and late ( Rab7 ) endosomes with B . pseudomallei phagosomes were assessed from 0 . 5 to 4 h after infection ( S4A–S4C Fig ) . We found that EEA1 association with B . pseudomallei phagosomes was transient and confocal microscopy revealed detectible levels of EEA1 on phagosomal membranes at very early time-points ( Fig 4A and S4A Fig ) . Consistent with these observations , Rab5 association , was transient and occurred only during the first 30 min ( 23 . 6 ± 0 . 8% ) after infection with B . pseudomallei ( Fig 4B and S4B Fig ) . Conversely , late endosomal marker Rab7 associated with B . pseudomallei phagosomes from 30 min , peaked at around 2 h ( 51 . 6 ± 2 . 4% ) and declined afterward ( Fig 4B and S4C Fig ) . Therefore , the presence of Rab7 on B . pseudomallei phagosomes suggested that fusion of late endosomes with the B . pseudomallei phagosomes can occur at 2 h after infection . To further define the stage of the phagocytic sequence of Rab32-positive phagosomes , we next examined the time-course of Rab32 and other late endosomal markers ( LAMP1 , LAMP2 ) colocalizations with B . pseudomallei phagosomes ( S4D and S4E Fig ) . The percentage of Rab32-positive phagosomes colocalization with LAMP1 and LAMP2 was assessed via quantitative analysis . At 1 h p . i . , only small amounts of Rab32-positive phagosomes were found to associate with LAMP1 and LAMP2 ( 21 . 1 ± 1 . 8% , 23 . 4 ± 3 . 6% , respectively ) , indicating that fusion with late endosomes was minimal at this time . However , by 2 h p . i . the majority of Rab32-positive phagosomes had accumulated LAMP1 and LAMP2 ( 36 . 6 ± 1 . 2% , 41 . 2 ± 3 . 1% , respectively ) , indicating late endosome fusion had taken place ( Fig 4D and 4E ) . Moreover , we also evaluated the acidification of Rab32-positive phagosomes by using the acidotropic probe Lysotracker ( S4F Fig ) . We observed that 44 . 2 ± 4 . 3% of Rab32-positive phagosomes colocalized with lysotracker at 2 h p . i . , but thereafter this percentage decreases ( Fig 4F and 4G ) . Taken together , these results indicated that a substantial fraction of Rab32-positive phagosomes harboring B . pseudomallei appears to fuse with acidic late endosomes at early stages of infection . To further understand the functional consequences of Rab32 in B . pseudomallei infection , we investigated the effects of knockdown of Rab32 expression on B . pseudomallei phagosomes . We used a small interfering RNA ( siRNA ) -mediated knockdown of Rab32 expression in RAW264 . 7 macrophages . To test the silencing efficiency , the expression levels of Rab32 were analyzed by qRT-PCR and Western blot assays . We found that the mRNA ( 3-fold , p = 0 . 002 ) and protein ( 3 . 3-fold , p = 0 . 005 ) levels of endogenous Rab32 were significantly decreased in RAW264 . 7 cells transfected with Rab32 siRNA ( Fig 5A ) . Next , we examined whether Rab32 is required for B . pseudomallei phagosomes maturation . As shown in Fig 5B and 5C , Rab32 knockdown significantly reduced the percentage of association between B . pseudomallei phagosomes and LAMP1 compared to control siRNA at 2 h p . i . ( 2-fold , p = 0 . 003 ) . Similarly , the percentage of LysoTracker-positive B . pseudomallei phagosomes were also obviously lower in Rab32 siRNA transfected macrophages than that in control siRNA transfected macrophages ( 1 . 4-fold , p = 0 . 02; Fig 5D and 5E ) . These results suggested that Rab32 may interfere with the maturation of B . pseudomallei phagosomes . Additionally , using transmission electron microscopy ( TEM ) , we further observed the transport of B . pseudomallei phagosomes in Rab32-depleted RAW264 . 7 cells . At 2 h p . i . , TEM results showed that about 80% of the B . pseudomallei were intact and surrounded by the single-membrane phagosomes in control siRNA-transfected macrophages ( Fig 5F and 5G ) . Conversely , in the Rab32 siRNA transfected macrophages , most bacteria had escaped from the phagosomes into the cytoplasm at 2 h p . i . ( 4 . 6-fold , p = 0 . 008; Fig 5F and 5G ) . In agreement with the TEM observed results , colony forming unit ( CFU ) assays showed that Rab32 silencing resulted in significantly increased intracellular growth of B . pseudomallei compared to control siRNA treated macrophages ( 2 fold at 2 h , p = 0 . 007 and 2 . 2 fold at 6 h , p = 0 . 008; Fig 5H ) . And the growth of B . pseudomallei was not caused by differences in internalization , because the Rab32 knockdown did not affect the extent of internalization ( S5A Fig ) . Thus , our data indicated that Rab32 is not only involved in B . pseudomallei-containing phagosomes formation , but is also indispensable for controlling intracellular replication of B . pseudomallei in macrophages . Considering that the majority of the Rab32-positive phagosomes harboring B . pseudomallei had late endosomal features and Rab32 contributes to restricting the intracellular growth of B . pseudomallei in macrophages . Therefore , we hypothesized that Rab32 is involved in the fusion of B . pseudomallei-containing phagosomes with lysosomal compartment for more efficient degradation of invading B . pseudomallei . Rab GTPases cycle between the GDP- and GTP-bound states and are regulated by guanine nucleotide exchange factors ( GEFs ) and GTPase activating proteins ( GAPs ) that influence their subcellular localization and functions [5] . Therefore , we explore the impacts of overexpression of EGFP-Rab32 and mutants on phagosome maturation . Expression of the EGFP tagged Rab32-T37N ( inactive GDP-bound mutant ) , Rab32-Q83L ( active GTP-bound mutant ) and wild-type Rab32 caused no obvious effect on the internalization of B . pseudomallei in RAW264 . 7 cells ( S5B Fig ) . We then investigated whether the recruitment of Rab32 to the B . pseudomallei phagosome depends on its GTP/GDP binding state . Our results showed that overexpression of EGFP-Rab32-WT ( 4 fold , p = 0 . 0005 ) and EGFP-Rab32-Q83L ( 4 . 5 fold , p = 0 . 0002 ) significantly increase the recruitment of Rab32 to B . pseudomallei-containing phagosomes respectively , but not EGFP-Rab32-T37N ( S6A and S6B Fig ) . In the process of phagosome maturation , acidification of the phagosome is required for efficient phago-lysosomal fusion . Indeed , we observed that the overexpression of EGFP-Rab32-WT ( 5 . 7 fold , p = 0 . 001 ) or EGFP-Rab32-Q83L ( 8 . 2 fold , p = 0 . 006 ) showed significant enhancement in the association between B . pseudomallei phagosomes and the acidotropic probe Lysotracker as compared to the EGFP-Rab32-T37N groups , respectively ( Fig 6A and 6B ) . Moreover , the later stages of phagosome maturation are also characterized by the acquisition of lysosomal acid hydrolases , such as cathepsin D ( CTSD , the lysosomal marker ) [32] . Thus , we next examined the recruitment of CTSD to the B . pseudomallei phagosomes in RAW264 . 7 cells transfected with pEGFP-Rab32 and its mutant vectors . Expression of the dominant active mutant of EGFP-Rab32-Q83L significantly increased the association of endogenous CTSD with B . pseudomallei phagosomes ( 5 . 5 fold , p = 0 . 0006; Fig 6C and 6D ) . In contrast , the forced expression of the inactive mutant Rab32-T37N inhibited the recruitment of CTSD to phagosomes , compared to the EGFP-Rab32-WT groups ( 2 . 8 fold , p = 0 . 004; Fig 6C and 6D ) . The lysosomal enzyme CTSD is first synthesized as an inactive precursor ( pro-CTSD ) , which is then cleaved to produce the mature active form of CTSD in acidic lysosomes [37] . In addition , the activation of CTSD is crucial for the effective elimination of intracellular pathogens in phagolysosomes . Hence , the intracellular processing status of CTSD could be further used as an indicator of maturation of B . pseudomallei phagosomes . Consistent with Lysotracker and CTSD localization , we found that the overexpression of EGFP-Rab32 and EGFP-Rab32-Q83L significantly increased the levels of mature/activated form of CTSD ( Fig 6E ) , correlating with the increased killing of B . pseudomallei ( Fig 6F ) . Conversely , overexpression of the EGFP-Rab32-T37N significantly blocks CTSD maturation ( Fig 6E ) , leading to an increase in the number of intracellular B . pseudomallei ( Fig 6F ) . These data indicate that Rab32 GTPase activity is involved in the fusion of B . pseudomallei-containing phagosomes with the degradative lysosomal compartment . Several reports have pointed to a role of mi-30 family members in the immune response to pathogens [38–41] . It therefore appeared likely that the differential regulation of mi-30b/30c influences the immune response to B . pseudomallei infection . Rab32 is a functional target of miR-30b/30c and is required for phagosome maturation . Next , we extended our analysis to primary bone marrow–derived macrophages ( BMDMs ) and examined whether miR-30b/30c also regulate the phagosome maturation in B . pseudomallei infection . Firstly , we further established the specificity of miR-30b/30c via overexpression of miR-30b/30c mimics or inhibitors in BMDMs . Consistent with previous observations , qRT-PCR and western blot analysis demonstrated that transfection of BMDMs with miR-30b/30c mimics decreased Rab32 mRNA and protein expression ( S7A Fig ) , whereas transfection of BMDMs with miR-30b/30c inhibitors increased Rab32 mRNA and protein expression ( S7B Fig ) . Similarly , we next tested miR-30b/30c effects on the colocalization of Lysotracker and CTSD with B . pseudomallei-containing phagosomes in BMDMs by immunofluorescence analysis . As shown in Fig 7A–7C , at 2 h p . i . , transfection with miR-30b/30c mimics decreased the colocalization of B . pseudomallei phagosomes with Lysotracker ( 2 . 7-fold , p = 0 . 03; 2 . 9-fold , p = 0 . 02 , respectively ) and CTSD ( 2 . 3-fold , p = 0 . 02; 2 . 2-fold , p = 0 . 04 , respectively ) in BMDMs , when compared to the miR control . Conversely , the colocalization of Lysotracker ( 2 . 5 fold , p = 0 . 0002; 2 . 2 fold , p = 0 . 0007 , respectively ) and CTSD ( 1 . 9 fold , p = 0 . 0005; 1 . 8 fold , p = 0 . 0004 , respectively ) was markedly increased in B . pseudomallei-infected BMDMs transfected with miR-30b/30c inhibitors ( Fig 7D–7F ) . Additionally , since hydrolytic enzyme CTSD matures to the active form and obtains optimal antimicrobial activity in acidified lysosomes , we further investigated whether miR-30b/30c could affect the processing of CTSD in B . pseudomallei-infected BMDMs . Western blotting revealed that transfection with miR-30b/30c mimics significantly decreased the levels of mature/activated form of CTSD in BMDMs , whereas transfection with miR-30b/30c inhibitors had an inverse effect ( Fig 7G ) . Furthermore , as shown in Fig 7H and 7I , compared with the miR control group , transfection of BMDMs with miR-30b/30c mimics raised the intracellular growth of B . pseudomallei ( 1 . 9 fold at 4 h , p = 0 . 004; 2 . 2 fold at 4 h , p = 0 . 002 , respectively; Fig 7H ) , whereas transfection with miR-30b/30c inhibitors inhibited this growth ( 3 . 9-fold at 4 h , p = 0 . 005; 3 . 5-fold at 4 h , p = 0 . 008 , respectively; Fig 7I ) , as assessed by the CFU assay . These data collectively suggested that miR-30b/30c negatively regulate the maturation of B . pseudomallei-containing phagosomes and intracellular antimicrobial activity , which was consistent with our previous data , and further supports that Rab32 is a direct target of miR-30b/30c .
Accumulating evidence suggests that in phagocytic cells , the endosomal-lysosomal degradative pathway plays a critical role in innate host-defense mechanisms against a variety of bacterial invaders by facilitating phagosome-lysosome fusion [42–46] . Here , we demonstrate that Rab32 is involved in host defense against B . pseudomallei in the early stages of infection by regulating phagosome maturation in macrophages . Specifically , we reveal that the underlying mechanism for upregulated Rab32 expression after exposure to B . pseudomallei in macrophages is through decreased miR-30b/30c expression . Subsequently , Rab32 is recruited to the B . pseudomallei–containing phagosomes with late endocytic features and it promotes the fusion of the phagosome with lysosomes to activate lysosomal acid hydrolases , thus limiting the intracellular growth of B . pseudomallei in macrophages . In addition , increasing evidence suggests that B . pseudomallei type III protein secretion system ( TTSS ) is crucial for vesicle escape before the bacteria can be degraded [22 , 47 , 48] . Thus , we speculated that there may be several TTSS effectors that interfere with Rab32 function in order to facilitates B . pseudomallei escape from the Rab32-positive compartments as an alternate fate of this pathogen ( Fig 8 ) . Investigating the intracellular membrane trafficking involved in this host-pathogen interaction has recently led to the discovery of a novel host-defense pathway , where Rab GTPases play a central role . [49] . Previous studies indicate that Rab GTPases are involved in the infection process of many microbial pathogens . For instance , Rab5a is specifically recruited on Leishmania donovani phagosomes and inhibits the transport to lysosomes in human macrophages [50] , Rab34 is involved in the process of mycobacterial killing by macrophages [31] , and a number of Rab subfamily members , such as Rab5 , Rab7 , Rab14 , Rab20 , and Rab29 are involved in the intracellular replication of the bacterial pathogens Mycobacterium tuberculosis [51] , Candida albicans [32] , and Salmonella enterica serovar Typhimurium [52] . Recent studies also demonstrate the importance of a cell-autonomous , Rab32-dependent host-defense pathway against Salmonella enterica serovar Typhi and Listeria monocytogenes [26 , 27 , 53] . However , although Rab32 has been found to be crucial for suppressing the growth of the intracellular pathogens , its involvement in intracellular bacterial killing by macrophages has not yet demonstrated for B . pseudomallei and the exact mechanism underlying the Rab32-dependent elimination of bacterial pathogens is still relatively unknown . Phagosome maturation is a complex multi-step process . The nascent phagosome develops into an acidic , protease-rich phagolysosome through a series of fission and fusion processes with endocytic organelles , a key process enabling intracellular microbial killing and degradation [54] . Therefore , it is not surprising that the trafficking of intracellular pathogens is also the site where the immune system of the host cell initiates its response . In this study , we investigated in detail the early infection events of B . pseudomallei intracellular life with respect to the phagolysosomal pathway . Our study clearly shows that Rab32 is upregulated and recruited to the B . pseudomallei-containing phagosomes in macrophages upon live B . pseudomallei infection . This is consistent with the previous reports of Rab32 being efficiently recruited to the S . Typhi-containing phagosomes [27 , 53] . Interestingly , heat-killed B . pseudomallei fails to induce the expression and recruitment of Rab32 into the bacteria-containing phagosomes , suggesting that the Rab32 response to B . pseudomallei is may be activated by pathogen-induced damage . However , the signaling pathways underlying these differential responses still need to be identified and characterized in future studies . These observations suggest that Rab32 is a critical protective host cellular response to live B . pseudomallei infection . MiRNAs have been described as important modulators of the host immune response against pathogenic infection , but their role in the B . pseudomallei-macrophage interplay remain largely unclear . In our previous studies , we have shown that miR-4458 , miR-4667-5p , and miR-4668-5p regulate autophagy-mediated elimination of B . pseudomallei by targeting ATG10 [19] . Recently , several studies have found that miRNAs can also regulate the expression of Rab GTPases , such as Rab5a , Rab5c , and Rab11a [50 , 55 , 56] . Therefore , involvement of miRNAs in regulating Rab GTPase undoubtedly deserves further investigation . In this study , macrophages infected with B . pseudomallei showed a significant change in the expression pattern of a large number of miRNAs , suggesting their potential role in modulating the gene expression profile of the infected cells . Using target prediction and pathway enrichment analyses , we identified the key cellular pathways associated with the differentially expressed miRNAs and predicted mRNA targets during B . pseudoamllei infection , including the immune system , proinflammatory processes , apoptosis , cell cycle , and DNA replication and repair . Importantly , miRNA profiling revealed that four members of the miR-30 family are significantly downregulated in B . pseudomallei-infected macrophages . We further verified microarray data by qRT-PCR and found that only the expression of miR-30b and miR-30c were downregulated whereas miR-30d and miR-30e were not significantly altered . The miR-30 family members are expressed by genes localized in different genomic positions . In addition , they share a common seed sequence near the 5′ end but possess different compensatory sequences near the 3′ end [34] . These different compensatory sequences allow miR-30 family members to target different genes and pathways , thus are often differentially expressed and regulated during biological processes . Wang et al . reported that the expression levels of miR-30c , miR-30d and miR-30e were significantly decreased whereas the levels of miR-30a and miR-30b were not altered during osteoblast differentiation [57] . Therefore , the differentially regulated expression pattern with the miR-30 family members during B . pseudomallei infection could be due to differences in sequence outside the seed region . However , the exact reason for these differences still needs to be investigated further . Rab32 has been predicted to be a direct target of miR-30 family members in previous studies [58 , 59] . However , the function of miR-30b/30c on Rab32 during B . pseudomallei infection has not been reported . Indeed , we found that Rab32 is predicted as a target for miR-30 family members amongst the transcripts of all downregulated miRNAs . And there is an inverse correlation between the expression levels of miR-30b/30c and Rab32 . We found that the enforced expression of miR-30b/30c suppressed Rab32 protein expression , whereas transfection of the cells with inhibitors of miR-30b/30c resulted in an increase in Rab32 expression in RAW264 . 7 cells or BMDMs . Additionally , a role for miR-30b/30c in Rab32 suppression was also shown in the inhibition of Rab32 recruitment to the B . pseudomallei-containing phagosomes . We further investigated the functional significance of Rab32 upregulation and recruitment to the B . pseudomallei-containing phagosomes in infected macrophages . Previous studies have demonstrated that following active Rab5 dissociation from a phagosome , Rab7 is recruited into the late endosomal compartment , modulating its maturation [60] . Indeed , we found that B . pseudomallei recruits and retains Rab7 ( a late endosome marker ) but not Rab5 and EEA1 ( early endosome markers ) on its phagosomes . In addition , we found that B . pseudomallei not only specifically recruits Rab32 on bacterial phagosomes but also retains them in a compartment with late endocytic features , positive for LAMP1 , LAMP2 , and Lysotracker . Given the Rab GTPases has been demonstrated to regulate the fusion of phagosomes with lysosomes . Therefore , retention of Rab32 on B . pseudomallei-containing phagosomes might promote the constitutive fusion of bacterial phagosomes with lysosomes . We observed that the knockdown of Rab32 caused a significant decrease in the association of LAMP1 and Lysotracker with B . pseudomallei-containing phagosomes . For further evaluation of phagosome maturation , we determined the degree of phagosomal acidification and the recruitment of cathepsin D to the phagosome , because both events were critical importance for the antimicrobial activity of macrophages [61 , 62] . Our results have shown that the association of both Lysotracker and CTSD with Rab32-positive phagosomes is strongly dependent on the levels of active Rab32 present in macrophages . However , we also noticed that a portion of Rab32-positive phagosomes are free of late endosomal markers ( LAMP1 and LAMP2 ) and late endosomal/lysosomal probe ( Lysotracker ) from 1 to 6 h after infection ( Fig 4D , 4E and 4G ) , suggesting that not all Rab32-positive phagosomes are fused with late endosomes . Thus , Rab32 is involved in modulating phagosome maturation , but the process by which Rab32 drive the progression from B . pseudomallei-containing phagosomes to late endosomes to degradative lysosomes is limited . The acidic and reducing environment of lysosomes is optimal for CTSD activity . Similarly , we also demonstrated that the overexpression of EGFP-Rab32-WT or EGFP-Rab32-Q83L can enhance CTSD activation in macrophages . Altogether , these observations are consistent with the role of Rab32 in increasing the biogenesis of phagolysosomes . We also demonstrated that Rab32 activity is required for inhibiting B . pseudomallei replication in macrophages , as Rab32 knockdown or overexpression of EGFP-Rab32-T37N ( inactive GDP-bound mutant ) resulted in increased B . pseudomallei growth . We speculated that this was due to a defect in lysosome fusion , which ultimately disrupted the biogenesis of B . pseudomallei-containing phagolysosomes with complete degradative capacity . Previous studies have shown that intracellular survival of bacteria requires the halt of phagosome-lysosome fusion . Nonetheless , how phagosome-lysosome fusion is regulated in B . pseudomallei infection is still poorly understood . In the present study , our results demonstrate that Rab32 may regulate the delivery of B . pseudomallei-containing phagosomes to lysosomes , facilitating phagosome maturation and subsequent bacterial clearance . Numerous studies have explored the role of miRNA regulation in the immune response against bacteria . Several deregulated miRNAs in infected host cells such as miR-146a/b , miR-155 , miR-24 , miR-4270 , miR-27b , miR-17 , miR-4458 , miR-20a , and miR-144-3p have been shown to regulate cell inflammatory response , macrophage polarization , cell death/survival , and autophagy [63] . These findings indicate that the deregulation of miRNA expression may be associated with outcome of the host-pathogen interaction . Therefore , the observed effects on Rab32 expression prompted us to further explore the role of miR-30b/30c in the host immune response against B . pseudomallei infection . In this study , we found that the association of Lysotracker and CTSD with phagosomes was increased by the inhibition of miR-30b/30c expression , whereas these were inhibited by overexpression of miR-30b/30c . Additionally , inhibition of miR-30b/30c expression resulted in marked increase in the levels of mature lysosomal CTSD . Importantly , this was associated with an effective intracellular growth limitation of B . pseudomallei . Previous studies demonstrated that miR-30 family members play a crucial role in the regulation of autophagy [41 , 64] , and it has been reported that autophagy is capable , at least in part , to accelerate the phagosome maturation [65 , 66] . However , the role of miR-30b/30c in regulation of the phagolysosomal pathway and host-defense has not been reported . In this study , we demonstrated that miR-30b/30c is associated with the modulation of phagosome maturation and affects the intracellular survival of B . pseudomallei by targeting Rab32 in host innate immune cells . In conclusion , to the best of our knowledge , this is the novel report of miRNA-mediated Rab32 involved in modulating phagosome maturation , which at least partially exerts its antimicrobial activity by promoting phagosome maturation against B . pseudomallei infection . Our data indicate that B . pseudomallei upregulates the expression of Rab32 in infected macrophages by downregulating the expression of miR-30b/30c . Subsequently , B . pseudomallei resides , at least in the early phase of infection , in a Rab32-positive compartment , and more importantly , Rab32 promotes the fusion of B . pseudomallei-containing phagosomes with lysosomes that likely result in increased exposure of B . pseudomallei to lysosomal acid hydrolases , CTSD , and enhances the killing of B . pseudomallei by macrophages . We also demonstrate the previously unrecognized role of miR-30b/30c in modulating phagosome maturation in the host innate immune cells .
All animal experiments were performed in accordance with the Regulations for the Administration of Affairs Concerning Experimental Animals approved by the State Council of People’s Republic of China . All efforts were made to minimize animals' suffering . All studies were approved by the Laboratory Animal Welfare and Ethics Committee of the Third Military Medical University ( Permit Number: SYXK-20170002 ) . Murine macrophages RAW264 . 7 cell line ( Cat . TIB-71 ) and human embryonic kidney HEK293 ( Cat . CRL-1573 ) cell line were obtained from American Type Culture Collection , Manassas , Virginia . RAW264 . 7 cells were grown in high glucose DMEM medium ( Gibco , 11965–092 ) containing 10% fetal bovine serum ( FBS; Gibco , 10100–147 ) without addition of antibiotics . HEK293 cells were routinely cultured in RPMI 1640 medium ( Gibco , 11875–093 ) supplemented with 10% FBS and 100 U/ml penicillin/streptomycin ( Gibco , 15140–122 ) . Primary bone marrow–derived macrophages ( BMDMs ) were isolated from C57BL/6 mice and cultured in DMEM for 3–5 d in the presence of M-CSF ( R&D Systems , 416-ML ) . All the above cell lines were cultured at 37°C in 5% CO2 . For all experiments , the B . pseudomallei strain used in all experiments is BPC006 , a virulent clinical isolate from a melioidosis patient in China[67] . And E . coli K12 ( 29425 ) , S . typhimurium ( 14028 ) and Burkholderia thailandensis E264 ( 700388 ) were purchased from American Type Culture Collection ( ATCC , Maryland , USA ) . Bacteria were grown in Luria-Bertani ( LB ) broth for 18 h at 37°C . After washing twice with phosphate buffered saline ( PBS , pH 7 . 4; Gibco , 10010023 ) , the number of bacteria was estimated by measuring the absorbance of the bacterial suspension at 600 nm . In general , an absorbance of 0 . 33 to 0 . 35 was equivalent to approximately 108 CFU/ml of viable bacteria . The number of viable bacteria used in infection studies was determined by retrospective plating of serial 10-fold dilutions of the inoculum to LB agar . Live B . pseudomallei was handled under standard laboratory conditions ( biosafety containment level 3 ) . For experiments using heat-inactivated B . pseudomallei , bacteria were suspended in PBS , incubated at 70°C for 20 min and stored at -70°C until use . The EGFP-Rab32 plasmid construct was kindly provided by Dr . Ying Wan ( Biomedical Analysis Center , Army Medical University ) . The EGFP-Rab32-T37N and EGFP-Rab32-Q83L mutant were generated by PCR mutagenesis from the EGFP-Rab32 plasmid . The primary antibody used in this work as follows: Mouse anti-Rab32 ( sc-390178 ) and anti-cathepsin D ( sc-377299 ) were purchased from Santa Cruz Biotechnology . Rabbit anti-Rab5 ( 46449 ) , anti-Rab7 ( 9367 ) , anti-EEA1 ( 3288 ) and anti-β-actin ( 4970 ) antibody were obtained from Cell Signaling Technology . Rat anti-LAMP-1 ( 25245 ) and anti-LAMP-2 ( 13524 ) were obtained from Abcam . Mouse polyclonal anti-B . pseudomallei and rabbit polyclonal anti-B . pseudomallei antibody were obtained from immunized mice and rabbits . All secondary antibody used for immunofluorescence studies conjugated with Alexa Fluor 405 , 488 and 647 were purchased from Molecular Probes , All HRP-conjugated secondary antibody ( 115-035-003 , 111-035-003 ) were purchased from Jackson ImmunoResearch Laboratories . Samples were collected and the cell pellet was lysed in RIPA lysis buffer ( 50 mM Tris HCL , 150 mM NaCl , 0 . 1% Nonidet P-40 , 0 . 5% sodium desoxicholate , 1% SDS , 0 . 5% Benzonase endonuclease ( Merck Millipore ) and protease and phosphatase inhibitor cocktails ( Roche ) for 10 min at RT and then incubated at 95°C for 5 min . Protein concentration was determined by BCA Protein Assay according to the instructions of the supplier ( Thermo Fisher Scientific ) . Equal amounts of protein in 1x Laemmli buffer were denatured at 95°C for 5 min and subjected to standard SDS-PAGE and western blotting . A commercial protein marker was used for identification of protein size . Membranes were developed using ECL plus on ECL Hyper film ( GE Healthcare ) , scanned , and evaluated using ImageJ . β-actin was used as loading control . Total RNA was extracted using TRIzol ( Invitrogen Life Technologies ) according to the manufacturer’s instruction . RNA quality was assessed by using the Agilent 2100 bioanalyzer ( Agilent Technologies ) , and only samples with RNA integrity number >8 were used . MicroRNA microarray Assay was done using miRbase version 21 . 0 by LC Sciences ( LC Sciences , Houston , TX ) . Array experiments were conducted according to the manufacturer’s instructions . Briefly , the miRNAs were labeled with Agilent miRNA labeling reagent ( Agilent Technologies ) . Then , dephosphorylated RNA was linked with pCp-y3 and the labeled RNA was purified and hybridized to the miRNA microarray . Images were scanned with the Agilent array scanner ( Agilent Technologies ) using a grid file and analyzed with Agilent feature extraction software version 10 . 10 . GeneSpring software V12 ( Agilent Technologies ) was used for summarization , normalization , and quality control of miRNA microarray data . The miRNA array data were calculated by first subtracting the background value and then normalizing the signals by locally weighted regression . The express levels of miRNAs were designated as statistically significant when the 2-tailed P value was ≤0 . 05 . And signals <500 were interpreted as false-positive result . The statistically significant messenger RNAs were selected based on the fold change and adjusted P value ≤0 . 05 . Luciferase reporter construct was made by cloning mouse Rab32 sequence containing the potential miR-30b/c binding site into pMIR-Report construct ( Ambion , Austin , USA ) . The DNA oligonucleotides containing wild-type ( WT ) or mutant ( Mut ) 3’UTR of Rab32 were synthesized with flanking Spe I , Apa I and Hind III restriction enzyme digestion sites , respectively . All of the sequences are shown in Supplementary information , S2 Table . The HEK-293 cells were transfected with 0 . 8 μg of indicated wide-type or mutant firefly luciferase reporter vectors , 100 nM indicated miRNAs mimic , inhibitor or control ( RiboBio ) , and 0 . 04 μg of Renilla luciferase control vector ( pRL-TK-Promega ) using Lipofectamine 3000 ( Invitrogen Life Technologies ) . After transfection for 24 h , all of the cells were lysed via dual luciferase reporter assay system ( Promega ) , and then the fluorescence activity was detected via GloMax 20/20 Luminometer . Firefly luciferase activity was normalized to Renilla luciferase activity . qRT-PCR assays for miR-30b and miR-30c were performed by using TaqMan miRNA assays ( Ambion ) in a Bio-Rad IQ5 ( Bio-Rad Laboratories , Inc ) . The reactions were performed using the following parameters: 95°C for 2 min followed by 40 cycles of 95°C for 15 s and 60°C for 30 s . U6 small nuclear RNA was used as an endogenous control for data normalization . Relative expression was calculated using the comparative threshold cycle method . Quantitative RT-PCR analyses for the mRNA of Rab32 was performed by using PrimeScript RT-PCR kits ( Takara ) . The mRNA levels of β-actin were used as an internal control . The primers were shown in Supplementary information , S2 Table . For miRNA transfections , miR-30b and miR-30c mimic , miR-30b and miR-30c inhibitor are obtained from RiboBio ( Guangzhou , Guangdong , China ) . The sequences are as follows: miR-30b mimic , 5′-UGUAAACAUCCUACACUCAGCU-3′ and miR-30c mimic , 5′-UGUAAACAUCCUACACUCUCAGC-3′; miR-30b inhibitor , 5′-AGCUGAGUGUAGGAUGUUUACA-3′ and miR-30c inhibitor , 5′- GCUGAGAGUGUAGGAUGUUUACA-3′ . mimic Negative Control , 5′- UUUGUACUACACAAAAGUACUG-3′ and inhibitor Negative Control , 5′- CAGUACUUUUGUGUAGUACAAA-3′ . RAW264 . 7 cells or BMDMs were seeded in 24-well plates and co-transfected with miR-30b or mi-30c mimic ( 30 nM ) , inhibitor ( 30 nM ) and NC control oligo ( 30 nM ) using Lipofectamine 3000 ( Invitrogen , L3000008 ) according to the manufacturer’s instructions . After 24 h , cells were harvested and the expression levels of Rab32 mRNA or protein were detected by qRT-PCR and Western blotting as described above . For siRNA transfections , RAW264 . 7 macrophages were seeded at 1×106 per well in imaging dishes or standard 6-well culture plates for RNA or protein extraction in antibiotic-free DMEM and were incubated overnight . Cells were transfected with Lipofectamine 3000 , Opti-MEM ( Invitrogen , United Kingdom ) , and 50 nM Silencer Select Rab32 siRNA ( Santa Cruz Biotechnology , 152636 ) for 24 h . The effects of Rab32 siRNA were compared with those of a nontargeting control siRNA ( Santa Cruz Biotechnology , sc-44230 ) . For plasmid DNA transfections , RAW264 . 7 macrophages were seeded at 5 × 105 per well 1 d before the transfection according to the manufacturer’s protocol . Cells were transfected 16–20 h before further experiments . All experiments were performed in triplicate . For immunofluorescence studies , Samples were washed with PBS prior to fixation with 4% paraformaldehyde ( PFA , Electron Microscopy Sciences ) for 10 min . Cells were washed three times with PBS and permeablized with 0 . 05% Saponin ( Sigma ) , 1% bovine serum albumin ( BSA , Sigma-Aldrich ) in PBS for 10 min at room temperature . Subsequently , samples were incubated in 1% BSA/PBS for 5 min prior to incubation with primary and secondary antibody in 1% BSA/PBS for 1 h . Three washing steps with PBS for 5 min followed each antibody incubation . Finally , the nuclear stain DAPI ( Life technologies , 300 nM ) was applied for 10 min at room temperature . Glass coverslips were mounted on glass slides ( Thermo Scientific ) using Fluorescent mounting medium ( Dako Cytomation ) . For analysis of association of acidic compartments with B . pseudomallei phagosomes . RAW264 . 7 or BMDMs were incubated with 50 nM Lysotracker-DND99 ( Molecular Probes , L7528 ) for 1 h prior to infection . The cells viewed using a laser-scanning confocal microscope ( Zeiss , Germany ) . RAW264 . 7 cells were treated as indicated and were fixed in 2 . 5% glutaraldehyde at 4°C overnight and postfixed with 2% osmium tetroxide for 1 . 5 h at room temperature . After fixation , cells were embedded and stained with uranyl acetate/lead citrate . The sections were examined under a transmission electron microscope ( JEM-1400PLUS , Japan ) at 60 kV . Bacterial invasion of RAW264 . 7 cells or BMDMs was investigated by using the method described by Elsinghorst , except for the following modifications [68] . Cells were infected with B . pseudomallei at an MOI of 10:1 . One hour after infection , cells were washed twice with phosphate-buffered saline ( PBS ) , and 2 ml of fresh culture medium containing 250 μg of kanamycin per ml was added , and the preparation was incubated to kill the extracellular bacteria . After the indicated time points , cells were washed three times with PBS and lysed with 1 ml of 0 . 1% Triton X-100 ( Sigma ) after infection . Diluted cell lysates were plated on Luria broth plates . Colonies were counted after 36 h . Experiments were performed at least three times in triplicates . Macrophages silenced for Rab32 or expressing control siRNA , or transfected with pEGFP , pEGFP-Rab32 , pEGFP-Rab32-T37N and pEGFP-Rab32-Q83L were incubated with B . pseudomallei for 0 . 5 h , washed , and chased for 0 . 5 h as described and processed for imaging . Confocal images were made from consecutive fields , until 100 transfected cells were imaged . The transfected cell containing B . pseudomallei were counted and divided by the total number of the imaged cells . All images were analyzed by ImageJ software ( MD , USA ) . Images of the samples were acquired with blinding of the experimental conditions . The association of different markers with B . pseudomallei was measured by automated analysis of the mean relative fluorescent marker intensity in a 2-pixel wide ring around bacteria or by counting the percentage of B . pseudomallei associated with a marker . At least 250 or 100 bacteria per biological replicate were analysed B . pseudomallei the automated analysis or manual count respectively . The results are expressed as the mean ± SD of at least three separate experiments performed in triplicate . The differences between the groups were determined with the SPSS 13 . 0 software . Student’s t-test was used to analyze the data . The differences were considered significant at P<0 . 05 . Statistically significant differences are indicated by asterisks ( *P<0 . 05 , **P<0 . 01 ) . | Burkholderia pseudomallei is a gram-negative intracellular bacterium and the etiological agent of melioidosis . Little is known about the host innate immune system , which is engaged in a continuous battle against this pathogen and may contribute to the outcomes of melioidosis . Recently , Rab32 , a Rab GTPase was shown to be a critical regulator of a host defense pathway against intracellular bacterial pathogens . However , the exact mechanism of how Rab32 contributes to the restriction of intracellular pathogens is not completely understood . In this study , we determined that the infection of macrophages with B . pseudomallei resulted in the upregulation of Rab32 expression through the inhibition of miR-30b/30c expression . Subsequently , Rab32 is recruited to the B . pseudomallei-containing phagosomes and promotes the fusion of the phagosomes with lysosomes , which results in the increased exposure of B . pseudomallei to lysosomal acid hydrolases CTSD , thus limiting the intracellular growth of B . pseudomallei at an early phase of infection in macrophages . Our findings establish for the first time that Rab32 plays an important role in suppressing the intracellular replication of B . pseudomallei by modulating phagosome maturation in macrophages , providing a new insight into the host defense mechanisms against B . pseudomallei infection . | [
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"... | 2019 | Rab32 GTPase, as a direct target of miR-30b/c, controls the intracellular survival of Burkholderia pseudomallei by regulating phagosome maturation |
Natural killer ( NK ) cells are lymphocytes that play a major role in the elimination of virally-infected cells and tumor cells . NK cells recognize and target abnormal cells through activation of stimulatory receptors such as NKG2D . NKG2D ligands are self-proteins , which are absent or expressed at low levels on healthy cells but are induced upon cellular stress , transformation , or viral infection . The exact molecular mechanisms driving expression of these ligands remain poorly understood . Here we show that murine cytomegalovirus ( MCMV ) infection activates the phosphatidylinositol-3-kinase ( PI3K ) pathway and that this activation is required for the induction of the RAE-1 family of mouse NKG2D ligands . Among the multiple PI3K catalytic subunits , inhibition of the p110α catalytic subunit blocks this induction . Similarly , inhibition of p110α PI3K reduces cell surface expression of RAE-1 on transformed cells . Many viruses manipulate the PI3K pathway , and tumors frequently mutate the p110α oncogene . Thus , our findings suggest that dysregulation of the PI3K pathway is an important signal to induce expression of RAE-1 , and this may represent a commonality among various types of cellular stresses that result in the induction of NKG2D ligands .
Natural killer ( NK ) cells are specialized lymphocytes of the innate immune system that target both tumor cells and virally-infected cells . NK-cell cytotoxicity is regulated by a balance of signaling through inhibitory and stimulatory receptors [1] , [2] . Most of the inhibitory receptors generally recognize major histocompatibility complex I ( MHC-I ) molecules , a set of proteins often downregulated during viral infection or tumorigenesis . Stimulatory receptors recognize a wide variety of self-proteins that are induced upon viral infection or cellular transformation . Together , a net positive signal activates NK cells to secrete proinflammatory molecules TNF-α and IFN-γ , as well as effectors of lysis , granzymes and perforin [3] . NKG2D is a well-studied and potent NK-stimulatory receptor that is expressed on the surface of NK cells , activated CD8 T cells , and subsets of γδ T cells and NKT cells [4] . NKG2D can also function as a co-stimulatory receptor to enhance T-cell activation [5] , [6] . The human genome encodes at least seven NKG2D ligands ( MICA , MICB , ULBP1-4 , and RAET1G ) , and the mouse genome encodes at least nine NKG2D ligands ( MULT-1 , H60a-c , and RAE-1α-ε ) . Although the ligands bind NKG2D with varying affinities , they all trigger NK cell killing of target cells similarly . NKG2D ligand transcripts can be detected in certain cell types or during specific phases of development , but in general , ligand expression is low or absent in healthy cells [4] . However , ligands are induced during various stress conditions including transformation , DNA damage , and viral infection . Accordingly , NKG2D ligands are constitutively expressed on many tumor cell lines and on a large array of tumors including melanomas , leukemias , various carcinomas , and neuroblastomas [7] , [8] . NKG2D ligands are also upregulated in cells infected with viruses such as cytomegalovirus ( CMV ) , measles , Influenza A , and respiratory syncytial virus [9] , [10] . To counteract this NK recognition , tumors and viruses have evolved ways to shed or block surface expression of NKG2D ligands [11] , [12] . In particular , studies using mouse CMV ( MCMV ) with deletion mutations in genes encoding proteins that block ligand expression have shown that the ability of the virus to evade NKG2D recognition has a significant advantage on viral fitness in vivo [13]–[15] . Furthermore , aberrant expression of NKG2D ligands can lead to unwanted NKG2D signaling , which has been implicated in autoimmune diseases , such as rheumatoid arthritis and type 1 diabetes [16] . Therefore , regulation of ligand expression under different conditions is critical to prevent targeting of healthy cells . Several modes of regulation have been shown for NKG2D ligand expression . At the transcriptional level , expression of human NKG2D ligands MICA and MICB seems to be controlled by heat shock elements in their promoters [17] . Damage of genomic DNA also leads to increased expression of RAE-1 , MULT-1 , ULBP1-3 and MICA , and RAE-1 induction occurs through the action of ataxia telangiectasia mutated ( ATM ) and/or ataxia telangiectasia and Rad3-related ( ATR ) , as well as checkpoint effector kinase1 ( Chk1 ) [18] . Additionally , it was reported that c-Myc regulates RAE-1ε at the transcriptional level [19] . At the post-transcriptional level , the expression of MICA and MICB can be inhibited by cellular microRNAs , and MICB expression can also be inhibited by viral microRNAs [20] , [21] . Finally , the expression of MULT-1 is regulated post-translationally through ubiquitination [22] . The effect of NKG2D ligand expression on NK cell activity , both in vitro and in vivo , has been best characterized with the RAE-1 family of mouse NKG2D ligands . Cells that normally do not express NKG2D ligands become highly susceptible to NK cell-mediated lysis in vitro when transduced with RAE-1 [8] , [23] . Ectopic expression of RAE-1 in tumor cells also results in efficient clearance of tumor cells after subcutaneous transfer in vivo . Clearance in vivo is mediated by NK cells and in some cases CD8 T cells , despite expression of inhibitory MHC-I molecules in some tumor cells [6] , [24] . Together these data demonstrate that RAE-1 expression results in NK-cell susceptibility both in vitro and in vivo , and highlight the importance of understanding the molecular mechanism of RAE-1 expression . Despite some evidence showing the role of certain pathways and effector molecules in the expression of NKG2D ligands , much remains to be learned about the process , and uncovering the molecular mechanism that drive expression of each of the NKG2D ligands remains an active area of research in the field . In particular , very little is known concerning the mechanisms of RAE-1 induction in virus-infected cells . CMV infection results in the induction of transcripts encoding numerous NKG2D ligands , including RAE-1 , MULT-1 , and H60a in the mouse . However , both human and mouse CMV encode proteins that specifically inhibit expression of each of the NKG2D ligands at the protein level , suggesting that NK cell recognition of CMV-infected cells has put evolutionary pressure on the virus to evade this arm of the immune system . The inducibility of RAE-1 in MCMV-infected cells prompted us to use this well characterized virus to investigate the molecular mechanism of RAE-1 induction . Strikingly , our studies showed that virus-induced activation of phosphatidylinositol-3-kinase ( PI3K ) is essential for the induction of the RAE-1 family of mouse NKG2D ligands . Further studies demonstrated that PI3K is also important for the maintenance of RAE-1 and MULT-1 expression on transformed cells , showing the breadth of our findings . These results suggest that activation of the PI3K pathway , which occurs in cells infected with numerous viruses and in cancer cells , represents a common signal for regulating RAE-1 expression . Finally , the effect of PI3K inhibition on MULT-1 expression also reveals the possibility that PI3K activation may play a role in regulating expression of other NKG2D ligands in cells infected with other viruses and other pathologic states such as inflammatory diseases .
Most cell lines constitutively express varying levels of RAE-1 at the cell surface [8] . Because most cells in vivo generally express very low levels of NKG2D ligands , if any at all , we utilized established mouse-tail fibroblasts that do not express RAE-1 at the surface to investigate the mechanism of RAE-1 induction upon MCMV infection . These fibroblasts have previously been used to demonstrate RAE-1 induction upon activation of the DNA damage response [18] . Upon infection of fibroblasts with MCMV for 24 hours , there was a significant induction of RAE-1 expression at the RNA level ( Fig . 1A ) . In order to further observe RAE-1 induction at the cell surface , we utilized a MCMV mutant ( MCMVΔ152 ) lacking the m152 gene , which encodes an immune evasin that downregulates RAE-1 protein . Using this virus , we observed RAE-1 surface expression starting 18 hours post-infection with an even higher expression at 24 hours post-infection ( Fig . 1B ) . Importantly , RAE-1 surface expression was not observed upon infection with the revertant virus ( MCMVΔ152-rev ) at 24 hours post-infection , despite no significant difference in the levels of RAE-1 mRNA induction ( Fig . 1C ) . Although previous studies have demonstrated the ability of MCMV to induce RAE-1 expression , it was not determined whether induction occurs specifically in infected cells or also in neighboring uninfected cells by an indirect mechanism . To address this question , we distinguished infected versus uninfected cells by staining cells with an antibody specific for an MCMV protein , m157 , that is expressed at the cell surface of infected cells [25] . Co-staining experiments demonstrated that RAE-1 induction occurs only in infected cells , suggesting that RAE-1 induction is a direct consequence of infection ( Fig . 1D ) . The m157-positive cells that express RAE-1 at low levels are most likely cells that were recently infected in the cultures and have not had sufficient time to upregulate RAE-1 . In subsequent experiments , we determined which events associated with the viral life cycle are necessary for RAE-1 induction . Upon entry , MCMV initiates a sequence of well-characterized events including transcription of immediate early and early genes , which are essential for viral replication and for the activation of cellular pathways aimed at priming the cell for efficient viral replication [26] . Expression of these early genes is also required for the expression of late genes and subsequent packaging and budding of the virus [27] . To investigate whether expression of viral genes is necessary for RAE-1 induction , fibroblasts were infected with either MCMVΔ152 or UV-inactivated MCMVΔ152 for 24 hours . UV inactivation significantly impaired the ability of MCMVΔ152 to induce expression of RAE-1 both at the RNA and protein levels throughout the course of the infection ( Fig . 2A and B ) . Interferon-Stimulated Gene 15 ( ISG15 ) expression was significantly induced upon infection by both MCMVΔ152 ( Δ152 ) and UV-inactivated virus ( UV ) ( Fig . 2C ) , indicating that neither viral entry nor activation of the interferon response was affected by the UV treatment . As a control , MCMV early gene 1 ( e1 ) product was PCR amplified using viral genomic DNA extracted from either MCMVΔ152 or UV-inactivated MCMVΔ152 , and no amplification was observed from the UV-inactivated viral genomic DNA ( data not shown ) . UV-inactivation was also confirmed by the lack of plaque forming units in the supernatant of cells infected with UV-inactivated virus for 24 hours ( data not shown ) . We next determined whether viral DNA replication is required for the induction of RAE-1 using phosphonoacetic acid ( PAA ) , a chemical inhibitor that binds to the viral DNA polymerase and blocks CMV viral replication [28] . Infection of fibroblasts with MCMVΔ152 for 24 hours in the presence of PAA did not inhibit RAE-1 induction , indicating that viral DNA replication and late gene expression are dispensable for RAE-1 induction ( Fig . 2D ) . Altogether , our results suggest that expression of viral genes at an early stage upon infection prior to viral replication is necessary for the induction of RAE-1 . Stress-induced activation of the DNA damage response , through the action of ATM or ATR and Chk1 , has been implicated in the induction of RAE-1 and other NKG2D ligands [18] , [29] , [30] . Additionally , CMV has been shown to manipulate the DNA damage response [31] , [32] . Therefore , we tested the role of the DNA damage response in the induction of RAE-1 in MCMV-infected cells by infecting fibroblasts for 24 hours in the presence or absence of specific inhibitors of the DNA damage response pathway . Inhibition of Chk1 using SB218078 and UCN-01 , or inhibition of ATM/ATR using caffeine did not affect RAE-1 induction upon MCMV infection , indicating that activation of the DNA damage response is not required for MCMV-induced RAE-1 expression ( Fig . S1 ) . Many cellular pathways are activated early on upon viral infection to achieve a state of pro-survival and increased cellular proliferation for optimal replication and production of progeny virus [33] . Common cellular pathways activated upon viral infections include the mitogen-activated protein kinase ( MAPK ) and the phosphatidylinositol-3-kinase ( PI3K ) pathways [34] , [35] . The PI3K pathway , in particular , is crucial in controlling cell growth and survival and is a key pathway in promoting cellular transformation , another condition known to trigger NKG2D ligand expression [36] . Because our data suggested that early events upon viral infection are necessary to induce RAE-1 , we hypothesized that manipulation of some of these cellular pathways are involved in the induction . To test this hypothesis , fibroblasts were infected with MCMVΔ152 for 24 hours in the presence of known inhibitors of these pathways , and RAE-1 surface expression was analyzed . MCMV-induced RAE-1 induction was not affected by the presence of MAPK inhibitors ( Fig . S2 ) . Remarkably however , surface expression of RAE-1 was completely abrogated in the presence of LY294002 , a global inhibitor of PI3K that binds to the catalytic domain of the kinase [37] ( Fig . 3A ) . Viral titers in the supernatant collected from cells infected for 24 hours in the presence or absence of LY294002 were not significantly different , indicating that the absence of RAE-1 surface expression was not due to a lack of viral entry and replication ( Fig . 3B ) . Of note , input virus was removed two hours post-infection , and therefore , virus present in the supernatant at 24 hours post-infection is a measure of progeny virus produced as a result of infection and replication . Furthermore , inhibitors were added at two hours post-infection to fresh culture media to prevent possible blockage of viral attachment or entry . The requirement for active PI3K to induce RAE-1 suggests that MCMV infection activates the PI3K pathway . To determine whether the PI3K pathway is activated upon MCMV infection in our system , cellular lysates from MCMV-infected fibroblasts were analyzed by western blotting with an antibody specific for Akt phosphorylated at Serine 473 . As positive controls , whole cell lysates were obtained from cells treated with 20% fetal bovine serum ( FBS ) or cells stably expressing the catalytic subunit of PI3K ( p110α ) with an H1047R mutation that renders PI3K constitutively active [38] . Very little Akt phosphorylation was observed in uninfected cells . By contrast , Akt phosphorylation was readily detectable in MCMV-infected cells as well as in cells treated with FBS and cells stably expressing p110α H1047R ( Fig . 3C ) . When cells were infected in the presence of LY294002 , the phosphorylated form of Akt was no longer detectable . Altogether , our data indicate that MCMV infection activates the PI3K pathway , in accordance with data obtained with HCMV [39] , and that this activation is required for the induction of RAE-1 . There are three classes of enzymes in the PI3K superfamily , class I , II , and III . Akt activation occurs mainly through class I PI3K , and this is critical in regulating cell survival , metabolism , apoptosis , and cell cycle . Class I PI3Ks are heterodimeric molecules composed of a catalytic and a regulatory subunit and are classified into class IA or class IB PI3K . The catalytic subunits of class IA PI3K are p110α , β or δ , whereas class IB PI3K contains p110γ [40] . It is becoming increasingly appreciated that PI3K catalytic subunits play non-redundant roles in regulating the biology of the cell [41] . Thus , we hypothesized that RAE-1 induction upon MCMV infection occurs through a particular PI3K isoform such that a specific signal is required for its expression . In order to determine which of the PI3K isoforms are involved in RAE-1 induction , we first determined the expression patterns of each of the PI3K catalytic and regulatory subunits in our fibroblasts at the steady state level by RT-PCR analysis . Our analysis showed that all of the catalytic and regulatory subunits were detected to varying degrees in these cells ( Fig . 4A ) . We then employed isoform-specific inhibitors to test the role of each of the class I PI3Ks on MCMV-induced RAE-1 expression . RAE-1 surface expression was greatly diminished when cells were infected in the presence of inhibitors for p110α ( PI3Kαi2 and PI-103 ) , but not in the presence of inhibitors for p110β ( TGX-221 ) , p110δ ( IC87114 ) or p110γ ( AS252424 ) ( Fig . 4B ) . Similar to treatment with LY294002 , treatment with either PI3Kαi2 or PI-103 did not result in a significant change in the viral titer in the supernatant , indicating that the loss of RAE-1 expression in these cells was not due to the lack of viral entry or replication ( Fig . 4C ) . Compared to LY294002 , PI-103 is much more selective for p110α , but at higher concentrations it is still able to inhibit other targets in the pathway , namely DNA-PK and mTORC1 [42] . Therefore , to rule out possible contributions from these molecules on RAE-1 induction , selective inhibitors of DNA-PK and mTORC1 ( NU7026 and rapamycin , respectively ) were tested in the same assay . Neither NU7026 nor rapamycin treatment inhibited RAE-1 induction , suggesting that indeed RAE-1 induction upon MCMV infection involves signaling specifically through the p110α-containing PI3K ( Fig . 4D ) . These results were further confirmed using a wide range of inhibitor concentrations in MCMV-infected cells ( Fig . S3 ) . The gene encoding p110α is an oncogene that is commonly mutated in human cancers [43] , [44] . These mutations in p110α cause the PI3K pathway to be constitutively active , resulting in cellular transformation and oncogenesis [45]–[47] . Because RAE-1 molecules , along with other mouse and human NKG2D ligands , are frequently expressed on the surface of transformed cell lines as well as in some tumors in vivo [7] , [8] , we hypothesized that RAE-1 expression in transformed cells is also dictated by p110α PI3K signaling . To test this hypothesis , we first tested the effect of LY294002 treatment on three different types of transformed cell lines that all constitutively express RAE-1 at the cell surface: A20 ( a B lymphoma cell line ) , NIH 3T3 ( adherent fibroblast cell line ) and YAC-1 ( a T lymphoma cell line ) . Cell surface RAE-1 expression was susceptible to inhibition by LY294002 treatment in all three cell lines tested ( Fig . 5A ) , suggesting that RAE-1 expression in these cells also depends on active PI3K . To test the role of specific PI3K isoforms on RAE-1 expression in transformed cells , YAC-1 cells were treated with the same isoform-specific inhibitors used in Figure 4B and Figure S3 , at a wide range of concentrations . RAE-1 surface expression was measured at 24 hours post-treatment . Similar to the effect observed in MCMV-infected cells , PI-103 treatment led to a significant decrease in the expression of RAE-1 , whereas treatment with selective inhibitors of the other isoforms of PI3K ( p110β , γ , and δ ) or an inhibitor of DNA-PK had no significant effect on RAE-1 expression , even at high concentrations ( Fig . 5B ) . In NIH 3T3 cells ( Fig . 5C ) and A20 cells ( data not shown ) , we also observed inhibition of RAE-1 expression by PI-103 , but not by inhibitors of other PI3K isoforms . The lack of response to inhibitors that target the p110β , γ , and δ isoforms of PI3K strongly indicates that signaling through p110α is specifically involved in the expression of RAE-1 in transformed cells as well . We also tested whether RAE-1 expression was impacted by rapamycin , an inhibitor of mTORC1 , a downstream effector of PI3K . Whereas rapamycin did not inhibit RAE-1 expression in infected cells ( Fig . 4D ) , NIH 3T3 cells ( Fig . 5C ) or A20 cells ( data not shown ) , it did block RAE-1 expression in YAC-1 cells ( Fig . 5B ) . These data suggest that mTORC1 plays a role in supporting RAE-1 expression in some transformed cells but not in others or in MCMV-infected fibroblasts . In order to address whether the PI3K pathway regulates other mouse NKG2D ligands , we determined the effect of PI3K inhibition on expression of MULT-1 and H60a in NIH 3T3 cells , which constitutively express all three types of mouse NKG2D ligands . Similar to the results with RAE-1 , MULT-1 expression was suppressed in NIH 3T3 cells treated with LY294002 or PI-103 , but not with the other inhibitors ( Fig . 5C ) . In contrast , H60a expression was not significantly affected by the inhibition of PI3K . Altogether the data illustrate a specific role of p110α PI3K in regulating RAE-1 and MULT-1 mouse NKG2D ligands in transformed cells .
Using fibroblasts , we observed that RAE-1 induction occurs only in infected cells ( Fig . 1D ) and that this induction requires active viral gene expression ( Fig . 2 ) . Because viral infections are often accompanied by production of defective viral particles that do not contain the entire viral genome , such specificity will presumably spare cells infected with defective viral particles from NK-cell mediated killing . This discrimination may be beneficial for the host because cells exposed to defective viral particles contain nucleic acids that function as pathogen associated molecular patterns ( PAMPs ) and activate innate immune sensors that induce production of type-I IFN and other proinflammatory molecules . Indeed , UV-inactivated MCMV is a potent activator of ISG15 ( Fig . 2C ) . NK-mediated killing of these cells could potentially curtail inflammatory cytokine production . Additionally , cells infected with defective particles may also serve as good sources of antigens for cross-presentation by antigen presenting cells . Recently , Vance et al . described the principle that signals associated with active bacterial infection and manipulation of the host cell machinery , termed “patterns of pathogenesis , ” can serve to activate the innate immune response [49] . Here , we illustrated that UV-inactivated viral particles were sufficient to stimulate the IFN response , but expression of RAE-1 proteins was absolutely dependent on active infection and manipulation of the host cell machinery; activation of PI3K signaling being one example of such manipulation . Hence , PI3K activation appears to function as a “pattern of pathogenesis” for induction of RAE-1 expression . However , additional considerations described below , indicate that PI3K activation is not sufficient for Rae1 induction , suggesting that several signals may function cooperatively to induce RAE-1 expression . We observed that RAE-1 expression requires viral genes that are expressed prior to viral replication , as demonstrated by the use of UV-inactivated virus and PAA ( Fig . 2 ) . This may suggest that viral early proteins are mediating the induction of RAE-1 . Because immediate early proteins are the first to be expressed upon MCMV infection , we tested their role in the induction of RAE-1 . Overexpression of GFP-fused MCMV ie1 , ie2 , and ie3 proteins alone or in combination did not lead to the induction of RAE-1 ( Fig . S5 ) , suggesting that although these proteins may play a role , they are not sufficient for RAE-1 expression . In this manuscript , we focused on the involvement of cellular pathways that are activated during viral infection in the expression of RAE-1 . The PI3K pathway regulates cellular functions including metabolism , cell cycle progression , proliferation , and apoptosis , and it is often dysregulated in infected and transformed cells [34] , [50] . Class IA PI3K is generally activated through receptor tyrosine kinases ( RTKs ) , which are receptors for growth factors , cytokines , and hormones . If class IA PI3K activation alone is sufficient to induce RAE-1 induction , it should occur in response to many cellular stimuli independently of infection . To test this , we stimulated cells for 24 hours with PDGF , which activates the well-studied RTK , PDGF receptor . Despite robust activation of the PI3K pathway , as illustrated by phosphorylation of Akt , RAE-1 induction did not occur ( data not shown and Fig . S6A ) . Interestingly , PDGF-R has been shown to be a cellular receptor for HCMV [51] . Thus , the lack of RAE-1 induction with PDGF treatment is consistent with our finding that viral gene expression is absolutely necessary . Additionally , overexpression of a constitutively active form of p110α , p110α H1047R , by itself was insufficient to induce RAE-1 expression , again despite robust activation of the PI3K pathway ( Fig . S6B and 3C ) . Together these results strongly suggest that RAE-1 induction is tightly regulated such that expression of the main viral immediate early proteins ( ie1 , ie2 , and ie3 ) or activation of class IA PI3K in the absence of infection are not sufficient to induce ligand induction and that additional signals are likely required for the induction . Future investigations are necessary to identify these additional pathways that are necessary for RAE-1 induction . To determine whether PI3K activation is involved in regulating RAE-1 at the post-translational level , we stably expressed the coding region of RAE-1α or RAE-1γ isoform from an exogenous promoter . The choice of these isoforms came from our observation that they were induced upon MCMV infection at the RNA level ( Fig . S8A ) and at the protein level , confirmed by the use of two different mutant viruses lacking m152 ( Fig . S8B and C ) . RAE-1 expression in these cells was not affected by LY294002 treatment , arguing that trafficking of RAE-1 and sustained expression of mature RAE-1 proteins at the cell surface is not dependent on PI3K activation ( Fig . S7B ) . Notably , although LY294002 treatment of infected cells resulted in a complete loss of RAE-1 expression at the cell surface ( Fig . 3A ) , RAE-1 mRNA was still induced five fold compared to uninfected cells ( Fig . S7A ) . Therefore , it is possible that the PI3K pathway plays a role in regulating RAE-1 at least in part at the post-transcriptional level , prior to trafficking to the surface . Activation of PI3K can enhance cellular translation via formation of the translation initiation complex containing eIF4E [52] , raising the possibility that RAE-1 is regulated at the translational level upon PI3K activation . Nevertheless , LY294002 treatment reduced the amount of RAE-1 mRNA in infected cells by three fold , suggesting a possible role of PI3K in either transcription of the RAE-1 gene or stabilization of RAE-1 mRNA as well . It has recently been shown that transcripts of two human NKG2D ligands , MICA and MICB , are regulated by several cellular microRNAs [20] , raising an additional possibility that PI3K regulates microRNAs that target RAE-1 . The gene encoding the p110α catalytic subunit of PI3K is often mutated in mouse and human tumors so as to render PI3K constitutively active , and thus functions as an oncogene [53] . Despite the involvement of p110β , γ , and δ isoforms in cancer , p110α is the only catalytic subunit of PI3K found to be mutated in tumors , suggesting a unique role of p110α in cellular transformation [41] . We observed that p110α PI3K is important for the expression of RAE-1 in multiple transformed cell lines ( Fig . 5 ) . The mechanism by which the different PI3K heterodimers mediate their non-redundant functions is poorly understood [54] . It is possible that the specificity of p110α is achieved at the cell surface receptor level ( i . e . RTKs or GPCRs ) or by one of the downstream effectors of PI3K . Nonetheless , the role of p110α PI3K in regulating RAE-1 expression during both viral infection and transformation is an intriguing finding that deserves further investigation . In this study , we also observed an effect of PI3K inhibition on MULT-1 expression , but not H60a . The observed difference in the requirement for PI3K signaling for expression of different mouse NKG2D ligands is interesting and may have several explanations . One possibility is that the difference reflects a specialization in NKG2D ligands , in which RAE-1 and MULT-1 respond to activated PI3K , whereas H60a responds to distinct cellular cues or stress pathway mediators . The notion that NKG2D ligands respond to different stress pathways was already suggested by the finding that MULT-1 is unique among the mouse NKG2D ligands in being regulated by stress associated with heat shock or UV irradiation [22] . The possibility that H60a has unique regulatory properties is also suggested by the sequence of its 3′ untranslated region ( UTR ) , which is unusually long ( 3kb ) in comparison to those of RAE-1 and MULT-1 ( 400bp and 700bp , respectively ) , suggesting that it may contain a unique set of regulatory elements . PI3K and its downstream mediators such as Akt and mTORC1 have been key targets in the development of cancer therapies [50] . In particular , chemical analogues of the inhibitors used in this study are used in clinical studies as therapeutics for cancer . As cancer drug development progresses , it will be important to take into consideration the potential for these PI3K inhibitors to greatly diminish NK-cell recognition and cytolysis of targets; especially because NK cells are important for recognition and clearance of tumor cells [2] . Here , we identified a common pathway between infected and transformed cells that is required for expression of the RAE-1 family of mouse NKG2D ligands . The results of this study are the first to demonstrate the role of the PI3K pathway in the expression of NKG2D ligands or other events that sensitize cells for immune recognition . Our data suggest that PI3K dysregulation in the context of disease is a key signal sensed by cells for expression of RAE-1 . This study provides an important direction for future investigations designed to elucidate how NKG2D ligand expression is regulated and how it is restricted to diseased cells .
Established tail-derived fibroblasts were prepared as described previously [18] . Established fibroblasts , BALB/c 3T3 ( ATCC , CCL-163 ) , NIH 3T3 ( ATCC , CRL-1658 ) , and BOSC ( ATCC , CRL-11270 ) cells were maintained in DMEM with 5% FBS and 1% penicillin and streptomycin . YAC-1s ( ATCC , TIB-160 ) and A20s were maintained in RPMI . Peritoneal macrophages obtained from C57BL/6 mice were cultured overnight in RPMI with 10% MCSF provided by Dr . Portnoy ( UC Berkeley ) , 10% FBS , and 1% penicillin and streptomycin . MCMVΔ152 and Δ152-rev viruses were generously provided by Dr . Hill ( Oregon Health and Science University , Oregon ) . MCMVΔ152-GFP virus was kindly provided by Dr . Jonjic ( University of Rijeka , Croatia ) . MCMVWT ( Smith strain ) and MCMVΔm04+m06+m152 viruses were generously provided by Dr . Koszinowski ( Max von Pettenkofer-Institute , Munich , Germany ) . All viruses were propagated in NIH 3T3 cells and titered in BALB/c 3T3 cells . For all infection experiments , fibroblasts were infected at MOI of 5 , input virus removed at 2 hrs pi , and infection was allowed to take place for a total of 24 hrs . Supernatants were collected at the time of harvest at 24 hrs pi and used for titering in BALB/c 3T3s . For UV-inactivation of the virus , viral supernatant was placed directly under the UV light in a sterile tissue culture hood for 30 minutes . To confirm successful UV-inactivation , MCMV e1 gene was PCR amplified from viral genomic DNA isolated from equal volumes of untreated or UV-treated virus stock . Briefly , viral DNA was extracted from viral supernatants by adding an equal volume of phenol/chloroform followed by another round of chloroform extraction , and isopropanol was used to precipitate the DNA . UV-inactivation was further confirmed by performing a plaque assay on supernatants obtained from cells infected with either untreated or UV-treated virus . Fibroblasts and 3T3 cells were harvested in 2 mM EDTA PBS and stained with monoclonal anti-mouse pan-specific RAE-1 , RAE-1α/β/γ , RAE-1β/δ , RAE-1ε , MULT-1 , H60A or Rat IgG2A isotype control ( all purchased from R&D ) followed by PE-conjugated goat anti-rat IgG ( Jackson ImmunoResearch Laboratories ) . YAC-1s , A20s , and peritoneal macrophages were first incubated with an anti-mouse CD16/CD32 FcBlock ( BD ) , followed by pan RAE-1 antibody and FITC or PE-conjugated anti-rat IgG2A antibody ( BD ) . All samples were co-stained with 7-AAD ( BD ) . MCMV m157-specific monoclonal antibody ( 6H1 . 2 . 1 ) was generously provided by Dr . Yokoyama ( Washington University School of Medicine , MO ) . RNA from fibroblasts and macrophages were extracted in Trizol ( Invitrogen ) , treated with RQ1 DNase ( Promega ) , and total RNA was reverse transcribed using oligo ( dT ) 15 primer ( Integrated DNA Technologies ) and SuperScriptII ( Invitrogen ) at 42°C for 50 minutes . cDNAs were analyzed using ABI7300 Real Time PCR System . RAE-1 isoform specific primers were described previously [55] . Primers for RAE-1 and ISG15 are described in the Table S1 . cDNAs from uninfected tail fibroblasts were used to amplify regions within the catalytic and regulatory domains of class I PI3K using primers described in the Table S1 . Inhibitors for all infection experiments were added to the media 2 hrs pi to first allow viral attachment and entry , and they were left in the culture media for the remainder of the 24 hr infection . Phosphonoacetic acid ( PAA ) was purchased from Sigma Aldrich and used at a final concentration of 100 ug/ml , pH 7 . 4 . YAC-1s were cultured in the presence of PI3K inhibitors for 18 hrs . U0126 , SB203580 , SB600125 , SB218078 , UCN-01 , LY294002 , Rapamycin , and NU7026 were purchased from Calbiochem . PI3Kαi2 , PI-103 , TGX-221 , and AS252424 were purchased from Cayman Chemicals . Caffeine was purchased from Sigma , and IC87114 was kindly provided by Dr . Okkenhaug ( Babraham Institute , Cambridge , UK ) . The final concentrations of all of these inhibitors are stated in the figure legends of the corresponding figures . The coding region of RAE-1α or γ isoforms was cloned into a retroviral vector , pBMN-IN . p110α H1047R was cloned into a retroviral vector pMG-hygro . Retroviral supernatants were obtained as described previously [56] . MCMV ie1 , 2 , and 3 fused to GFP was cloned into pEGFP . N1 ( Clontech ) and transiently transfected using Lipofectamine 2000 ( Invitrogen ) . Mouse fibroblasts or peritoneal macrophages were serum-starved overnight and infected with MCMV in the presence of DMSO or LY294002 or treated with PDGF ( Sigma ) for 24 hrs . Fibroblasts transduced with empty vector or transduced with p110α H1047R were serum-starved overnight . Cell lysates were analyzed by western blotting for phospho-Akt S473 and Akt according to manufacturer's instructions ( Cell Signaling ) . The relative ratio of P-Akt to total Akt was determined using ImageJ . A two-tailed , paired student t-test was performed on all samples where statistical significance is indicated . All animals were handled in strict accordance with good animal practice as defined by the Panel on Euthanasia of the American Veterinary Society . We have received approval for these experiments from the UC Berkeley IACUC ( R292 ) . | Human and mouse cytomegaloviruses ( HCMV and MCMV ) are members of the Herpesvirus family . Both viruses cause disease in individuals with a compromised immune system , such as transplant patients and AIDS patients . Natural killer ( NK ) cells are essential players in the immune response against these viruses . NK cells recognize self-proteins , such as NKG2D ligands , that are poorly expressed on healthy cells but are upregulated on cells that are undergoing stress , such as infection and tumor development . The biological processes associated with NKG2D ligand expression in infected cells are unknown . The PI3K pathway , which controls many cellular processes , is activated by a variety of viruses to prime cells for efficient viral replication . We observed that MCMV activates the PI3K pathway and that this activation is required for NKG2D ligand expression . We also found that the expression of NKG2D ligands on cancer cell lines is dependent on this pathway . Our data suggest that NKG2D ligand expression , and thus recognition of infected and cancer cells by NK cells , is associated with a dysregulation in the PI3K pathway . | [
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... | 2011 | Expression of the RAE-1 Family of Stimulatory NK-Cell Ligands Requires Activation of the PI3K Pathway during Viral Infection and Transformation |
Proteins must move between different conformations of their native ensemble to perform their functions . Crystal structures obtained from high-resolution X-ray diffraction data reflect this heterogeneity as a spatial and temporal conformational average . Although movement between natively populated alternative conformations can be critical for characterizing molecular mechanisms , it is challenging to identify these conformations within electron density maps . Alternative side chain conformations are generally well separated into distinct rotameric conformations , but alternative backbone conformations can overlap at several atomic positions . Our model building program qFit uses mixed integer quadratic programming ( MIQP ) to evaluate an extremely large number of combinations of sidechain conformers and backbone fragments to locally explain the electron density . Here , we describe two major modeling enhancements to qFit: peptide flips and alternative glycine conformations . We find that peptide flips fall into four stereotypical clusters and are enriched in glycine residues at the n+1 position . The potential for insights uncovered by new peptide flips and glycine conformations is exemplified by HIV protease , where different inhibitors are associated with peptide flips in the “flap” regions adjacent to the inhibitor binding site . Our results paint a picture of peptide flips as conformational switches , often enabled by glycine flexibility , that result in dramatic local rearrangements . Our results furthermore demonstrate the power of large-scale computational analysis to provide new insights into conformational heterogeneity . Overall , improved modeling of backbone heterogeneity with high-resolution X-ray data will connect dynamics to the structure-function relationship and help drive new design strategies for inhibitors of biomedically important systems .
Even well-folded globular proteins exhibit significant flexibility in their native state [1] . However , despite advances in nuclear magnetic resonance dynamics experiments and computational simulations , accurately characterizing the nature and extent of biomolecular flexibility remains a formidable challenge [2] . While traditionally X-ray crystallography is associated with characterizing the ground state of a biomolecule , the ensemble nature of diffraction experiments means that precise details of alternative conformations can be accessed when the electron density maps are of sufficient quality and resolution [3] . These maps represent spatiotemporal averaged electron density from conformational heterogeneity across the millions of unit cells within a crystal [4 , 5] . Computational methods have made strides toward uncovering and modeling conformational heterogeneity in protein structures from crystallographic data [3] . However , there is currently no automated approach to recognize the features of extensive backbone flexibility in electron density maps , model the constituent alternative conformations , and validate that the incorporation of heterogeneity improves the model . B-factors theoretically model harmonic displacements from the mean position of each atom , but in practice are often convolved with occupancies of discrete alternative positions when multiple backbone conformations partially overlap [5] . Statistical analyses of electron density using Ringer has revealed evidence for a surprising number of “hidden” alternative conformations in electron density maps [6 , 7] . The phenix . ensemble_refinement method [8] uses electron density to bias molecular dynamics simulations , then assembles snapshots from this trajectory into a multi-copy ensemble model . However , energy barriers of the simulation may prevent sampling of well separated backbone conformations . Accurately modeling protein conformational heterogeneity , in particular when the mainchain adopts distinct conformations for one or a number of contiguous residues , remains a difficult task . The spatial overlap of electron density of multiple conformations and the relatively similar profiles of branching mainchain and sidechains blur structural features that can guide the human eye to reduce the large number of possible interpretations [9] . We have previously developed qFit [10] , a method for automatically disentangling and modeling alternative conformations and their associated occupancies , which are represented by the variable q ( for “occupancy” ) in standard structure factor equations . The qFit algorithm examines a vast number of alternative interpretations of the electron density map simultaneously . To propitiously explore a high-dimensional search space , conformational sampling is guided by the anisotropy of electron density at the Cβ atom position , the nexus of backbone and sidechain in polypeptides [11] . For each slightly shifted Cβ atom position , qFit samples sidechain conformations with a rotamer library [12] and uses inverse kinematics to maintain backbone closure [9] . Finally , it selects a set of one to four conformations for each residue that , collectively , optimally explain the local electron density in real space . However , the anisotropy of the Cβ atom limits the exploration radius of qFit to model backbone conformational heterogeneity . While protein backbone motions are often associated with large-amplitude conformational flexibility of surface loop regions , subtle motions can have important ripple effects in closely packed areas via sidechain-backbone coupling . For example , fast ( ps-ns ) backbone NH and sidechain methyl order parameters from spin relaxation experiments are highly correlated with each other in flexible regions [13] , suggesting that mainchain and sidechain motions collectively sample conformational substates . For example , a backbone backrub motion [14] repositions the Cα-Cβ bond vector in a plane perpendicular to the chain direction , enabling the sidechain to access alternative , often sparsely populated rotamers that otherwise would be energetically unfavorable . We previously linked coupled transitions between alternative sidechain conformations , like “falling dominos” , to enzymatic turnover and allostery [15 , 16] . Additionally , qFit cannot model discrete conformational substates such as peptide flips , which are >90° rotations of a peptide group while minimally perturbing the flanking residues . Some structure validation methods highlight incorrect peptide orientations [17] and even automate subsequent model rebuilding [18] . However , rebuilding fits a correct , unique conformation rather than multiple well-populated alternative peptide conformations . Peptide flips can have important functional roles in proteins . For example , flavodoxin undergoes peptide rotations between functional states as part of the catalytic cycle [19] , and peptide flips that convert β-sheet to α-sheet have been linked to amyloid formation [20] . Furthermore , high-resolution crystal structures have shown that alternative conformations related by a peptide flip may be populated in the same crystal , although not as commonly as backrubs [14] . Modeling alternative conformations of glycine residues , which lack a Cβ atom , is also a current limitation of qFit . The lack of a Cβ atom allows glycine residues to access otherwise forbidden regions of conformational space [11] and thereby fill special structural roles such as capping helix C-termini [21] . In addition , the flexibility of glycines may contribute directly to function at flexible inter-domain linkers or conformationally dynamic enzyme active sites [22] . Automatically modeling such cases as alternative conformations with qFit paves the way toward understanding their contributions to protein function . Increasingly , new experiments are being proposed which , combined with computational analysis , can extract the spatiotemporal ensemble from electron density maps [15 , 23 , 24] . Adding the capability to model peptide flips and alternative conformations for glycines will increase our power to uncover conformational heterogeneity . While the number of sampled conformations for glycines is modest owing to a missing side-chain , including peptide flips for all amino acids adds significant computational complexity to the qFit algorithm . A powerful quadratic programming algorithm lies at the core of qFit and is necessary to determine non-zero occupancies for up to four conformations from among hundreds or even thousands of candidate conformations for each residue . Even for modest sample sizes , around 500 , the number of combinations of candidate conformations is enormous , exceeding 109 . As more backbone motion is incorporated into qFit , the computational complexity increases , demanding a parallelized approach to refinement on a residue by residue basis . Although this moves rebuilding away from a single node towards a larger compute cluster , the combination of data-driven sampling and selection has enabled qFit to automatically build multiconformer models that have illuminated intramolecular networks of coupled conformational substates [16] and the effects of cryocooling crystals [25 , 26] . Similar hybrid approaches using robotics sampling and selection based on experimental NMR data are also being extended to nucleotide systems such as the excited state of HIV–1 TAR RNA [27] . Here we introduce qFit 2 . 0 , an updated version of the qFit algorithm with new capabilities for modeling near-native backbone conformational heterogeneity in crystal structures . We first describe the quadratic programming procedure that allows selection of a small set of conformations per residue that collectively account for the local electron density , and discuss its extension to fitting backbone atoms in addition to sidechain atoms . We then describe new conformational sampling features of qFit 2 . 0 , in particular glycine shifts and peptide flips . Finally , we validate the updated algorithm with both synthetic and experimental X-ray data . qFit 2 . 0 is freely available by webserver and source code is available for download at https://simtk . org/home/qfit .
To automatically identify alternative backbone conformations , including peptide flips , we augmented the sample-and-select protocol in qFit ( see Fig 1 and Methods ) . Previously , conformations were sampled based on anisotropy of the Cβ atom and were selected based on the fit between observed and calculated electron density for the sidechain ( Cβ atom and beyond ) only . Alternative conformations for mainchain atoms were ultimately included in the multiconformer model only because they accommodated the best sidechain fits . In qFit 2 . 0 , we now select conformations based on the fit between observed and calculated electron density for the sidechain atoms and also the backbone O atom . The O atom is an excellent yardstick for identifying backbone conformational heterogeneity for two reasons . First , it is furthest from the Cα-Cα axis so its density profile is somewhat isolated and is displaced most by rotations around that axis [14] . Second , it has more electrons than other backbone heavy atoms , so is most evident in electron density maps . This change allows us to select peptide flips outside of α-helices and β-sheets , where flips are prevented by steric and hydrogen-bonding constraints , then directly select flipped conformations . This procedure is effective because the large movement of the backbone O during a peptide flip leaves a major signature in the electron density . Incorporating the backbone O atom also enhances the detection of less discrete backbone conformational changes . In particular , we now sample alternative glycine conformations based on anisotropy of the electron density for the O atom , by analogy to the Cβ-driven sampling for all other amino acids . This results in alternative glycine conformations that are dictated by their own local electron density . After sampling , we select combinations of conformers from a pool of candidates based on both sidechain and backbone O atoms for all amino acids , including glycines . This addition results in greater potential to discover alternative conformations throughout the protein and include additional conformational heterogeneity in the final multiconformer model . The nullspace inverse kinematics procedure of qFit [9] naturally encodes backrub [14] , crankshaft [28 , 29] , and shear [30 , 31] motions ( S1 Fig ) where they are dictated by the anisotropy of the electron density for the Cβ atom . However , this anisotropy cannot identify more discrete substates of the backbone , such as peptide flips . Peptide flips are large , ~180° rotations of a peptide plane in protein backbone with minimal disturbance of adjacent peptide conformations . Enumerating many peptide flip candidate conformations with the nullspace inverse kinematics procedure would quickly lead to prohibitively large sample sizes . We therefore examined common geometries of discrete peptide flips to expedite sampling of discrete backbone substates in qFit 2 . 0 . Steric interactions prevent arbitrary rotations of the peptide plane , much like sidechains adopt preferred rotamer conformations . To identify plausible geometries for peptides relative to a single input peptide , we examined cases where the peptide rotates by 90–180° around the Cα-Cα axis . We identified 147 peptide flips modeled as alternative conformations in high-quality structures . After filtering this set of peptide flips with structure validation criteria and reserving some examples for a test set , we retained 79 examples that clustered around four geometries ( S1 Table , S1 Data ) . We observed that peptide flips often included rotation and translation within the peptide plane such that the first Cα moves “below” the Cα-Cα axis and the second Cα moves “above” it ( from the view in Fig 2A and 2C ) . These in-plane movements justify sampling geometries found in natural peptide flips in qFit 2 . 0 rather than , e . g . , simply rotating the peptide 180° around the Cα-Cα axis . The first two clusters , “simple down” ( Fig 2A and 2C , blue ) and “tweaked down” ( Fig 2A and 2C , red ) , feature a very nearly 180° rotation around the Cα-Cα axis , but with different in-plane adjustments . By contrast , the second two clusters , “left” ( Fig 2B and 2D , green ) and “right” ( Fig 2B and 2D , brown ) , feature rotations closer to 120° , but in opposite directions . Our dataset here is sufficient to propose plausible , well-validated peptide flip geometries for sampling in qFit 2 . 0 , and suggests that the four clusters could also be used to inspire moves in protein design . We found that the two “down” clusters were more common in tight turns between β-strands: 41–50% of flips in these clusters were found in turns , as compared to 0–14% for the other two flip clusters ( with a conservative definition of a turn; see Methods ) ( Table 1 ) . The flip is nearly always associated with a transition between Type I/I’ and II/II’ turns . The “left”/”right” clusters were dispersed among many irregular structural contexts , but not α-helices or β-sheets . Across the four clusters , the first residue of the peptide was a glycine 7 . 5% of the time , in line with the general abundance of glycines in proteins ( 7–8% ) . However , the second residue of the peptide was a glycine significantly more frequently ( 50% , p < 10−22 ) . This was true for the “left”/”right” clusters ( 21% , p < 0 . 05 ) and especially the two “down” clusters ( Fig 2C ) ( 64% , p < 10−24 ) . This may be in part because a glycine as the second residue of a peptide can lower the flip transition energy [32] . These results generally agree with reports of flip-like conformational differences between the same tight turn in separate homologous structures [33] . To test these advances , we first explored synthetic datasets spanning resolutions from 0 . 9 to 2 . 0 Å with increasing B-factors as a function of resolution and Gaussian noise added to structure factors ( see Methods ) . We used the Top8000 peptide flip geometry cluster centroids , with the alternative conformations at 70/30 occupancies for the “tweaked down” cluster and 50/50 occupancies for the other three clusters . Because qFit uses these geometries to sample peptide flips , we expected it would be able to successfully identify each flipped alternative conformation starting from the primary ( labeled “A” ) conformation at high-to-medium simulated resolution , but less well at lower simulated resolution . Indeed , qFit 2 . 0 successfully finds the flipped conformations for most peptide flip geometry clusters across resolutions with a 92% success rate overall; this rate drops only slightly with resolution from 0 . 9 to 2 . 0 Å ( Fig 3 ) . Since we rebuilt the entire protein chain , we also assessed the performance on other residues . By contrast to the true positive peptide flip results , the peptide flip and rotamer false positive rates remain quite low across clusters and resolutions ( Fig 3 ) . These results indicate that qFit 2 . 0 is effective at identifying peptide flip alternative conformations across a wide range of crystallographic resolutions without introducing spurious conformations . Although tests with synthetic datasets offer insight into resolution dependence , a more direct test of the usefulness of qFit 2 . 0 involves crystal structures with real data . We combined structures left out of the training set from the Top8000 peptide flip examples with a few more manually curated examples for a total of 15 test cases ( Table 2 ) . When comparing qFit 2 . 0 models to rerefined original structures , Rfree is better for 7/15 cases and Rwork is better for 8/15 cases ( S2 Fig ) . However , after rerefinement with automated removal and addition of water molecules to allow the ordered solvent to respond to the new protein alternative conformations modeled by qFit ( see Methods ) , Rfree is better for the qFit 2 . 0 model for 10/15 cases and Rwork is better for 13/15 cases ( Fig 4 ) . The differences generally are small: the average ΔRfree is ~0 . 1% . Overall , these results suggest that qFit 2 . 0 models explain experimental crystallographic data as well as or better than traditional refinement protocols at a global structural level . While global metrics are important , a major focus of the current work is correctly identifying local alternative backbone conformations . To explore this aspect , we compared results from qFit 2 . 0 to those from qFit 1 . 0 and original deposited structures for our test set ( Table 2 ) . qFit 2 . 0 successfully models both flipped conformations in 14/18 ( 78% ) cases . For example , Val539-Gly540 in the Kelch domain of human KLHL7 is modeled with two alternative conformations related by a peptide flip ( 1 . 63 Å , PDB ID 3ii7 ) ( Fig 5A ) . qFit 1 . 0 fails to discover the flip , resulting in significant difference electron density peaks ( Fig 5B ) . By contrast , qFit 2 . 0 beautifully recovers both alternative conformations ( Fig 5C ) . In another example , Asn42-Gly43 in carbohydrate binding domain 36 at high resolution ( 0 . 8 Å , PDB 1w0n ) adopts flipped peptide conformations—yet MolProbity flags geometry errors in the deposited structure that indicate it re-converges too quickly , with alternative conformations for only the Asn42 and not also Gly43 ( Fig 5D ) . qFit 1 . 0 fails to capture the flip ( Fig 5E ) . However , qFit 2 . 0 not only identifies both peptide flip conformations for Asn42 , but also includes split conformations for Gly43 , thereby repairing the covalent backbone geometry ( Fig 5F ) . In both cases , the peptide flip and glycine sampling enhancements in qFit 2 . 0 combine to model discrete backbone heterogeneity as accurately as or even better than the original structure . In addition to retrospective positive-control tests , we also looked prospectively for “hidden” peptide flip alternative conformations that are unmodeled in existing structures . One such example is Met519-Thr520 in RNA binding protein 39 . In chain A of the room-temperature structure ( PDB ID 4j5o ) , the mFo-DFc difference electron density map around this peptide has significant positive and negative peaks , indicating it is mismodeled as a single conformation ( Fig 6A ) . Other instances of this peptide—including in chain B of the room-temperature structure and both chains of the cryogenic structure—feature conformational diversity , much of which may be related to crystal contacts; however , these conformations fail to account for the room-temperature chain A mFo-DFc peaks ( Fig 6B ) . However , using the room-temperature data , qFit 2 . 0 identifies a peptide flip in this region , which repositions Met519 and flattens the local difference density ( Fig 6C ) . By contrast , it does not identify a peptide flip for this region in either chain using the cryogenic data , which is in accord with previous reports that cryocooling crystals can conceal or otherwise perturb conformational heterogeneity that is present at room temperature [25 , 26] . In addition to selection of conformers based on fit to density for the backbone O atom for all amino acids , qFit 2 . 0 also adds sampling based on this atom for glycine , enabling density-driven backbone sampling for the most flexible amino acid . This facilitates modeling peptide flips in which one of the constituent residues is a glycine , as seen in the examples above ( Fig 5 ) —but also opens the door to modeling less discrete glycine flexibility . For the 489 glycines across the 15 datasets in the test set ( Table 2 ) , qFit 1 . 0 cannot model more than a single conformation , but qFit 2 . 0 models alternative conformations for 365/489 ( 75% ) of glycines . The Cα displacements average 0 . 28 Å and range from <0 . 01 Å up to 1 . 70 Å . Only 4 ( 4% ) of these glycines were modeled with alternative conformations in the original PDB structures . These results show that the direct sampling and selection based on electron density for glycine backbone atoms in qFit 2 . 0 successfully identify conformational heterogeneity that was formerly unrecognized . For example , a small , glycine-rich loop in PDB ID 3ie5 is modeled with a single conformation in the deposited structure and qFit 1 . 0 model ( Fig 7A ) . By contrast , qFit 2 . 0 recognizes the anisotropy of the electron density for each of the three glycine O atoms in the loop , so models them with alternative conformations that collectively shift the entire mini-loop region ( Fig 7B ) . Selecting conformers based on fit to density for the backbone O atom helps find alternative conformations not only for glycines , but also more generally for other amino acids . In many cases , this additional data-driven aspect to conformer selection drives the identification of subtle , non-discrete backbone motions that are coupled to larger , discrete sidechain changes . Indeed , for the 15 proteins in Table 2 , qFit 2 . 0 shifts the Cα more than does qFit 1 . 0 for 52% of residues , but the reverse is true for only 20% of residues ( the remaining residues are not moved by either version ) ( Fig 8A ) . Furthermore , for 63% of the residues for which qFit 2 . 0 finds a new sidechain rotamer that qFit 1 . 0 does not , qFit 2 . 0 also moves the Cα more ( Fig 8B ) . These results imply that the backbone sampling by qFit 2 . 0 not only increases backbone heterogeneity in and of itself , but also drives discovery of sidechain conformational heterogeneity . As one specific example , Thr157 in cyclophilin A is modeled with alternative backbone and rotamer conformations in the deposited structure ( Fig 8A ) . qFit 1 . 0 fails to find the alternative rotamer because it maintains a single backbone conformation ( Fig 8B ) , but , driven by carbonyl O anisotropy , qFit 2 . 0 identifies the alternative backbone conformations , allowing it to discover the second rotamer ( Fig 8C ) . We also observed hidden peptide flips for the Ile50-Gly51 tight turn in the “flap” region of HIV–1 protease . HIV–1 protease is a homodimer , with residue numbers often denoted by 1–99 and 1’-99’ . The flap region consisting of residues 46–56 is an antiparallel β-sheet and tight turn at the interface of the dimer ( Fig 9A ) . In most of the hundreds of crystal structures of HIV–1 protease , the two tight turns ( Leu50-Gly51 and Leu50’-Gly51’ ) adopt an asymmetric conformation , with one flap in a single type I conformation and the other in a single type II conformation . However , NMR relaxation data suggest that these flips can undergo chemical exchange on a slow ( ~10 μs ) timescale in solution [35] . Mutational data also linked collective conformational exchanges of these flips to catalytic rates [36] . In line with these solution studies , we noticed that for many HIV–1 protease crystal structures , the electron density maps actually reveal strong evidence for alternative conformations related by dual peptide flips . For example , in one high-resolution inhibitor-bound structure ( PDB ID 3qih ) , the Leu50-Gly51 and Leu50’-Gly51’ flaps are modeled with single asymmetric conformations , but strong positive mFo-DFc electron density coincides with potentially flipped states ( Fig 9B ) . Strikingly , qFit 2 . 0 automatically identifies dual “flap flips” , suggesting the flaps actually populate two different asymmetric states ( green vs . purple in Fig 9C ) in this particular inhibitor complex . More generally , this result suggests that these inhibitor-gating flaps in HIV–1 protease sample multiple conformations more often than previously recognized across many inhibitor complexes , which may motivate further investigation of the effects that protein and inhibitor flexibility have on binding affinity , efficiency of catalytic inhibition , and arisal of drug resistance in this biomedically important target .
The ruggedness of protein energy landscapes leads to conformational heterogeneity even in folded globular proteins . Evidence for these alternative conformations is remarkably prevalent in high-resolution ( <2 Å ) crystallographic electron density maps [6] . However , because these alternative conformations are difficult and/or time-consuming to model manually using existing graphics and refinement tools , they are underrepresented in the PDB [6] . qFit is a computational approach to overcoming these problems , by automatically identifying “hidden” alternative conformations and using quadratic programming to select a parsimonious subset that collectively best explains the diffraction data . Here we have demonstrated a new version of this algorithm , called qFit 2 . 0 , with several enhancements to handling flexible backbone—most notably , automated detection of discrete peptide flips and explicit fitting of backbone atoms for glycines . qFit has previously captured different types of backbone motion that can occur in secondary structure . For example , it correctly identifies the backrub motion [14] that helps Ser99 transition between sidechain rotamers in the active-site β-sheet network of CypA [15 , 16] , and also identifies a previously hidden α-helix winding/unwinding or “shear” motion [14 , 30] ( S1 Fig ) . However , qFit 2 . 0 can now model larger backbone motions in which the backbone change itself is discrete , instead of inherently continuous but coupled to discrete sidechain rotamer changes . Specifically , it models peptide flips , which occur outside of helices and sheets and involve discrete jumps over a larger energetic barrier . Peptide flips have important implications for understanding protein function . For example , our results for HIV–1 protease ( Fig 9 ) strongly suggest that conformational heterogeneity , in particular peptide flips , may play underappreciated roles in protein-inhibitor complexes . Previously , molecular dynamics simulations identified a large-scale “curling” motion of these flaps that is maintained by drug-resistance mutations and therefore seems important for substrate access [37] . Although this motion is more dramatic than the peptide flaps at the tips of the flaps that we observe , it underlines that flap flexibility—potentially across multiple length scales—is central to protease function and viral propagation . The peptide flip acts as a key conformational switch between type I/II turns , rearranging its environment beyond its immediate sequence neighbors and enabling alternative sidechain conformations with implications for function . However , the large number of unmodeled turns in HIV protease structures illustrates the challenge of distinguishing alternative conformations in electron density maps , even at high resolution . As an additional example which unfortunately lacks deposited structure factors , the active-site Gly57-Asp58 peptide in C . beijerinckii flavodoxin adopts distinct peptide flip states in concert with the oxidation state of the FMN prosthetic group [19] . The N137A mutation removes artificial lattice contacts that otherwise influence the conformation of the Gly57-Asp58 peptide , which results in a mixture of these peptide conformations simultaneously populated in the crystal; this suggests these multiple flip states may also coexist in solution [19] . Beyond the specific improvements to peptide flips , qFit 2 . 0 now fits conformations for each residue based on both sidechain ( beyond Cβ ) and backbone ( carbonyl O ) atoms . Although we originally envisioned this change for modeling glycines , we observed that it results in dramatically more extensive backbone conformational heterogeneity across the protein ( Fig 8 ) . R-factors are similar or better ( Fig 4 ) , suggesting the new models with more heterogeneity are at least as good an explanation of the experimental data . Notably , these new backbone shifts drive discovery of many more alternative sidechain rotamers ( Fig 8 ) . Our results suggest that sidechain and backbone degrees of freedom in proteins are tightly coupled , in agreement with previous reports that even subtle backbone motions can facilitate rotamer changes [14] , open up breathing room for natural mutations [38] , and expand accessible sequence space in computational protein design [31 , 39] . Future work will investigate an armamentarium of methods for modeling larger backbone conformational change in qFit , including helix shear motions [30] , adjustments of entire α-helices [40 , 41] , correlated β-sheet flexing [28] , automated loop building algorithms such as Xpleo [9] , and pre-knowledge of conformational differences between homologous structures . While these future steps will move us closer to capturing the full hierarchy of protein conformational substates [42] , they will also dramatically increase the computational cost of automated multiconformer model building . Many aspects of qFit are parallelizable; however , the total computational cost for reproducing the data in this manuscript is approximately 105 CPU hours . As cloud-computing capabilities of 108 CPU hours can now be leveraged for pure simulation data [43] , we envision that marshalling similar computational capabilities will become increasingly important for analysis of experimental X-ray data . Such data-driven computational approaches to studying the dynamic relationship between protein structure and function will be especially powerful when applied to series of datasets in which the protein is subjected to perturbations that modulate conformational distributions , such as ligand binding or temperature change [23] .
To define possible relative geometries between flipped peptide conformations , we searched for trustworthy peptide flips modeled as alternative conformations in the Top8000 database . This database contains ~8000 ( 7957 ) quality-filtered protein chains from high-resolution crystal structures , each with resolution < 2 Å , MolProbity score [34] < 2 , nearly ideal covalent geometry , and <70% sequence identity to any other chain in the database [44] . We searched the Top8000 for peptides with carbonyl C-O bonds pointed away from each other ( O-O distance > C-C distance + 1 Å ) and rotated by at least 90° , and for which both flanking Cα atoms reconverged to < 1 . 5 Å . Although peptide rotations of < 90° also occur , they occur more often in irregular loop regions , have less well-converged backbone for flanking residues , and are generally more diverse and difficult to simply categorize . By contrast , in this study we investigate the class of localized peptide rotations with well-converged backbone for both flanking residues . These are either very small rotations , or large flips with a rotation nearer to 180° —the latter being the focus here . To identify test cases for qFit 2 . 0 , we curated the resulting dataset by removing examples with more than two alternative peptide conformations; a cis rather than trans conformation for either state; or obvious errors based on steric clashes , strained covalent geometry , or torsional outliers from MolProbity [34] . This resulted in 104 examples , from which we kept a randomly selected 79 for a geometry training set ( S1 Table ) . We combined a subset of the remaining 25 peptide flips with a few other known examples for a test set of 18 examples ( Table 1 ) . The resolution range is 0 . 92–1 . 95 Å for the training set and 0 . 80–1 . 85 Å for the test set . Next we characterized the geometry of peptide flips by clustering the coordinates of the flipped alternative conformation ( labeled “B” ) in the training set after superimposing onto a reference peptide . We used the k-means algorithm with RMSD between the five heavy atoms of the peptide backbone ( Cα1 , C1 , O1 , N2 , and Cα2 ) for different values of k . We selected k = 4 because we observed cluster centroids with approximately 180° , +120° , and -120° rotations and for k > 4 no other significantly different rotations were identified . Notably , all four cluster centroids featured translations of the flanking Cα atoms of >0 . 2 Å , and as much as >0 . 9 Å for one cluster ( “tweaked down” , red in Fig 2 ) . The transformation matrices relating the flipped peptide cluster centroids to the reference peptide were used in qFit 2 . 0 to sample plausible alternative conformations , with subsequent refinement adjusting the atomic positions away from the centroid geometry . We defined tight turns as having a mainchain-mainchain hydrogen bond between i–1 carbonyl C = O and i+2 amide N-H that was detectable by the program Probe [45] . This definition is somewhat conservative; several more examples also were visually similar to tight turns . Enrichment of glycines at the two positions involved in a peptide flip was assessed for different peptide flip clusters within the training set relative to a large set of 337 randomly selected structures containing 6 , 092 total glycines out of 78 , 094 total amino acid residues . The statistical significance of this enrichment was assessed using a one-tailed Fisher’s exact test based on the hypergeometric distribution [46] . Hydrogens were placed at nuclear positions for Label in qFit 1 . 0 and at electron-cloud positions for Label in qFit 2 . 0 . Correspondingly , for Label in qFit 2 . 0 , hydrogen van der Waals radii were taken from the new values in Reduce [48] , which are intended to match those used in PHENIX . Hydrogens were absent for all other steps in qFit , including the final refinement step; however , the user is encouraged to add hydrogens to the final qFit model for their protein of interest and proceed to other analyses . Future work will update programs for downstream analysis of qFit models such as CONTACT [16] to also use electron-cloud instead of nuclear hydrogen positions . To generate synthetic datasets for testing qFit , we used the protein chains containing the four peptide flip cluster centroids ( 3mcw B 101–102 , 2ior A 159–160 , 2g1u A 51–52 , 3g6k F 172–173 ) . We first used phenix . pdbtools to convert any anisotropic B-factors to isotropic , added 10 Å2 to each B-factor per Å of resolution worse than the original structure’s resolution to roughly simulate the general rise of B-factors with resolution , and placed the chain in a P1 box that comfortably encompassed it . Next we used phenix . fmodel to calculate structure factors ( with the “k_sol = 0 . 4” and “b_sol = 45” bulk solvent parameters , and also generating 5% R-free flags ) and added 10% noise in complex space with the sftools utility in CCP4 [47] . This process was repeated for every simulated resolution from 0 . 9 to 2 . 0 Å with a 0 . 1 Å step size . qFit uses an input parameter ( MC_AMPL ) to scale the magnitude of movements of the Cβ ( or O for glycines ) along the directions dictated by its thermal ellipsoid . As in previous work [10 , 16 , 26] , we explored multiple values for this parameter: 0 . 1 , 0 . 2 , and 0 . 3 . For evaluating results such as true vs . false positive peptide flips and rotamers here , we considered all three resulting qFit models for each dataset . This is sensible because an end user of qFit 2 . 0 will likely reproduce this same protocol ( with a few MC_AMPL values ) and thus have a choice of models to use for developing insights into conformational heterogeneity and its connection to function . For other analyses , we used the minimum-Rfree qFit model model unless otherwise noted . To compare R-factors between the deposited models and qFit 2 . 0 , we finalized both models with phenix . refine for 10 macro-cycles using the same parameters , including the “ordered_solvent = true” flag . The resulting R-factors for qFit 2 . 0 models are similar or slightly better ( Fig 4 ) . PHENIX version 1 . 9–1692 ( the most recent official release ) [49] was used for all steps of both qFit 1 . 0 and 2 . 0 . Coordinates and structures factors were obtained from the Protein Data Bank [50] . qFit uses the following libraries: IBM’s ILOG CPLEX solver for QP and MIQP , which is available free of charge for academic use , and LoopTK for inverse kinematics calculations [51] . qFit is implemented in parallel; it is capable of sampling and evaluating conformations for each residue as an independent job on a Linux cluster . We have implemented job management for qFit on both Oracle/Sun Grid Engine and LSF Platform . | Describing the multiple conformations of proteins is important for understanding the relationship between molecular flexibility and function . However , most methods for interpreting data from X-ray crystallography focus on building a single structure of the protein , which limits the potential for biological insights . Here we introduce an improved algorithm for using crystallographic data to model these multiple conformations that addresses two previously overlooked types of protein backbone flexibility: peptide flips and glycine movements . The method successfully models known examples of these types of multiple conformations , and also identifies new cases that were previously unrecognized but are well supported by the experimental data . For example , we discover glycine-driven peptide flips in the inhibitor-gating “flaps” of the drug target HIV protease that were not modeled in the original structures . Automatically modeling “hidden” multiple conformations of proteins using our algorithm may help drive biomedically relevant insights in structural biology pertaining to , e . g . , drug discovery for HIV–1 protease and other therapeutic targets . | [
"Abstract",
"Introduction",
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"and",
"Methods"
] | [] | 2015 | Exposing Hidden Alternative Backbone Conformations in X-ray Crystallography Using qFit |
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