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Experimental autoimmune orchitis ( EAO ) , the principal model of non-infectious testicular inflammatory disease , can be induced in susceptible mouse strains by immunization with autologous testicular homogenate and appropriate adjuvants . As previously established , the genome of DBA/2J mice encodes genes that are capable of conferring dominant resistance to EAO , while the genome of BALB/cByJ mice does not and they are therefore susceptible to EAO . In a genome scan , we previously identified Orch3 as the major quantitative trait locus controlling dominant resistance to EAO and mapped it to chromosome 11 . Here , by utilizing a forward genetic approach , we identified kinesin family member 1C ( Kif1c ) as a positional candidate for Orch3 and , using a transgenic approach , demonstrated that Kif1c is Orch3 . Mechanistically , we showed that the resistant Kif1cD2 allele leads to a reduced antigen-specific T cell proliferative response as a consequence of decreased MHC class II expression by antigen presenting cells , and that the L578→P578 and S1027→P1027 polymorphisms distinguishing the BALB/cByJ and DBA/2J alleles , respectively , can play a role in transcriptional regulation . These findings may provide mechanistic insight into how polymorphism in other kinesins such as KIF21B and KIF5A influence susceptibility and resistance to human autoimmune diseases .
Experimental autoimmune orchitis ( EAO ) is a model of idiopathic male infertility mediated by autoreactive T cells [1] , [2] . It can be induced in mice by active immunization with mouse testicular homogenate ( TH ) emulsified in complete Freund's adjuvant ( CFA ) and Bordetella pertussis toxin ( PTX ) [3] . In genetically susceptible mice , the inflammatory lesions comprised of monocytes , macrophages , lymphocytes , neutrophils , and eosinophils are mainly found in the seminiferous tubules of the testes in association with aspermatogenesis [3] . We previously have shown that MHC class II restricted CD4+ T cells are the primary effectors in autoimmune orchitis [4] , [5] . However , recent evidence suggests the involvement of CD8+ T cells during the onset and maintenance of chronic inflammation [6] , [7] . Various strains of inbred mice respond differently to EAO induction , indicating that susceptibility is genetically controlled . Previously , it was shown that BALB/cByJ ( CByJ ) mice are highly susceptible to EAO [8] whereas DBA/2J ( D2 ) and ( CByJ×D2 ) F1 hybrids ( CD2F1 ) are resistant [3] , [9] . This demonstrates that resistance to EAO is inherited as a dominant phenotype in this strain combination . Additionally , resistance can be adoptively transferred to CByJ mice with CD2F1 primed splenocytes [10] . Therefore , the factors that regulate EAO resistance appear to be governed by an immune-mediated dominant negative mechanism . Genome exclusion mapping was utilized to map the immunosuppressive genes regulating dominant resistance to EAO [10] with significant linkages to multiple loci residing on chromosomes ( Chr ) 1 and 11 [10] . Of these , Orch3 on Chr11 displayed the most significant linkage and accounted for the majority of disease resistance seen in D2 mice . In this study , congenic mapping was employed to restrict Orch3 to a ∼1 . 3 Mb interval that identified Kif1c ( kinesin family member 1c ) as a positional candidate . By generating CByJ . CD11B-Kif1cD2 transgenic ( Tg ) mice , we demonstrated that Kif1c underlies Orch3 . Mechanistically , we showed that the resistant Kif1cD2 allele leads to reduced antigen ( Ag ) -specific T cell responsiveness as a consequence of decreased MHC class II expression by myeloid cells , and that the L578→P578 and S1027→P1027 polymorphisms distinguishing the CByJ and D2 alleles , respectively , can play a role in regulating gene transcription .
In the genome scan in which Orch3 was identified , D11Mit219 , D11Mit8 , and D11Mit118 exhibited the most significant linkage [10] . As the first step in the positional-candidate gene cloning of Orch3 , we used marker-assisted selection to introgress the Orch3D2 allele onto the susceptible CByJ background . Next , we generated overlapping interval specific recombinant congenic ( ISRC ) lines ( Figure S1 and Figure S2 ) and studied them in a stepwise fashion for susceptibility and resistance to EAO ( Figure 1 ) . Importantly , since resistance to EAO is inherited as a dominant trait in CD2F1 hybrid mice [10] , and the pathology indices ( PI ) between heterozygous and homozygous congenic lines were not significantly different ( data not shown ) , the data were pooled for each line . Control parental CByJ mice were clearly susceptible to EAO , with an average PI of 4 . 0 , whereas D2 and CD2F1 hybrid mice were resistant , with an average PI of 0 . 1 and 0 . 8 , respectively ( Figure 2 ) . C . D2-Es3/Hba , C . D2-3 . 1 , C . D2-5 , C . D2-8 . 4 , C . D2-8 . 5 , and C . D2-9 mice were also susceptible with average scores of 3 . 6 , 4 . 9 , 2 . 6 , 3 . 7 , 3 . 8 , and 4 . 0 , respectively . In contrast , C . D2-Evi2 , C . D2-3 , C . D2-3 . 2 , C . D2-8 and C . D2-8 . 1 thru -8 . 3 were resistant with average scores of 0 . 2 , 0 . 6 , 1 . 3 , 1 . 7 , and ≤1 . 4 , respectively . These data placed Orch3 within the interval between D11Mit298 ( 69339966–69340164 ) and NLR ( nucleotide-binding domain and leucine rich repeat containing ) family , pyrin domain containing 1A , B , C ( Nlrp1a/b/c ) at 70 . 9–71 . 0 Mb ( 70904699–71098734 bp ) . Importantly , this excluded transient receptor potential cation channel , subfamily V , member 1 ( Trpv1 ) at 73 . 0 Mb ( 73047794–73074744 ) underlying Idd4 . 1 , a quantitative trait loci ( QTL ) controlling susceptibility to type 1 diabetes in the NOD mouse [11] , and inducible nitric oxide synthase ( Nos2/iNos ) , important in inflammatory diseases including autoimmunity [12] , [13] , as candidate genes for Orch3 . Nlrp1a/b/c is one of two highly polymorphic positional candidate loci of immunological relevance within the interval , the second gene being kinesin family member 1C ( Kif1c ) . However , Nlrp1c could be excluded as a candidate since it is a pseudogene ( www . informatics . jax . org ) and Nlrp1a and -b are less likely to be relevant to Orch3 than Kif1c due to discordance between EAO susceptibility and Nlrp1a and -b alleles among CByJ , BALB/cJ and D2 mice ( www . informatics . jax . org ) [14] . To confirm that Kif1c was the most likely candidate gene for Orch3 and to definitively exclude Nlrp1a/b as a positional candidate , we generated overlapping sub-ISRC congenic lines across the C . D2-3 . 2 interval and studied them for susceptibility to EAO ( Figure 3 ) . Statistically significant differences in EAO susceptibility between C . D2-3 . 2 , C . D2-3 . 2c and CByJ mice were observed ( Figure 3 , right panel ) . In contrast , the severity of EAO in C . D2-3 . 2a and C . D2-3 . 2b was not significantly different from that of CByJ mice . Moreover , dominant resistance co-segregated with Orch3 as evidenced by the fact that no significant difference in the PI between homozygous and heterozygous mice was detected across all congenic lines studied ( Figure 2 and Figure 3 ) . Taken together , these data restrict Orch3 to a ∼1 . 3 Mb interval distal of D11Mit298 ( 69339966–69340164 ) and proximal of D11Die30 ( 70552627–70552762 ) which includes Kif1c but not Nlrp1a and Nlrp1b ( Figure 3 , left panel ) , thereby excluding them as positional candidates for Orch3 . Given the role of Kif1c in macrophage function [15] , and that kinesins have been implicated in antigen processing and presentation [16] , we decided to directly test the hypothesis that Orch3 is Kif1c . We generated a transgenic mouse line that selectively expressed the resistant Kif1cD2 allele on the susceptible CByJ background using the human CD11B/ITGAM regulatory elements for macrophage/myeloid-specific expression of Kif1cD2 ( Figure 4A ) . The expression of the transgene did not affect macrophage/myeloid cell generation or homeostasis as similar percentages of splenic F4/80+ ( Figure 4B ) and CD11b+ cells ( Figure 4C ) were detected on Tg-Kif1cD2 mice compared to negative littermate control ( NLC ) mice . In addition , no differences in the expression of CD40 or CD86 were observed between strains at baseline ( data not shown ) . Compared to NLC , greater Kif1c protein expression was seen in thioglycolate-induced Tg-Kif1cD2 cells ( Figure 4D ) . Despite the existence of polymorphisms upstream of Kif1c in potential regulatory regions ( http://phenome . jax . org/ ) , we did not observe differences in Kif1c expression at the mRNA level between the Kif1cCByJ and Kif1cD2 alleles ( Figure 4E ) . NLC and Tg-Kif1cD2 mice were studied for susceptibility to EAO . The expression of Kif1cD2 in CD11b+ cells protected susceptible CByJ mice from developing EAO ( Figure 3 , right panel ) . This finding establishes Kif1c as being Orch3 . To better understand the mechanism of resistance to EAO conferred by Kif1cD2 , microarray analyses were performed on CD11b+ cells from NLC and Tg-Kif1cD2 mice . Using a false discovery rate ( FDR ) cutoff of 0 . 05 , we determined that 164 genes were differentially expressed between NLC and Tg-Kif1cD2 CD11b+ cells ( Table S1 ) . An analysis for functional inference using Ingenuity Pathway Analysis ( Ingenuity Systems , www . ingenuity . com ) revealed that T helper cell differentiation was the most significant pathway influenced by Kif1c ( p<2 . 80 E-10; Figure S3 and Table S2 ) . In addition , 18 of the top 20 pathways implicated a role for MHC class II , including antigen presentation . Indeed , compared to NLC CD11b+ cells , we observed a marked down regulation in MHC class II gene expression by Tg-Kif1cD2 CD11b+ cells ( Table S1 and Figure 5A , dark blue dots ) . This is consistent with the role of kinesin as the motor that drives MHC class II to the plus end of microtubules toward the cell surface [16] . To corroborate diminished class II expression , flow cytometric analysis was performed using naïve TCRβ−CD19−CD11b+ splenocytes . The results presented in Figure 5B show lower MHC class II expression on Tg-Kif1cD2 cells compared to NLC , D2 , and C . D2-3 . 2 mice . Despite the differences in MHC II expression , no significant difference in the proportion of total splenic CD11b+ cells was observed ( Figure 4C ) . Therefore , expression of the transgene in CD11b+ cells negatively regulates MHC II protein levels . To further establish a functional role for the differential expression of MHC class II , we assessed antigen presentation by examining Ag-specific T cell proliferation . NLC and Tg-Kif1cD2 mice were immunized with ovalbumin ( OVA ) +CFA or proteolipid protein ( PLP ) 180–199 peptide ( PLP180–190 ) +CFA on d0 and d7 . Spleen and lymph nodes ( LN ) were harvested at d10 and the proliferative responses evaluated . Compared to NLC antigen presenting cells ( APCs ) , T cell proliferation in response to OVA was significantly reduced when T cells were stimulated in the presence of Tg-Kif1cD2 APCs ( Figure 6A ) . Similar results were observed for PLP180–199-dependent T cell responses ( Figure 6B ) . These data show that expressing the Kif1cD2 allele in CD11b+ cells confers resistance to EAO by modulating APC function . Taken together our data suggest that Kif1c coding region polymorphism controls susceptibility to autoimmune orchitis . Kif1c alleles possess amino acid substitutions at residues 578 , 1027 , and 1066 [17] . Four haplotypes have been identified: LSS ( Kif1cCByJ ) , PSS , PPS , and PPY ( Kif1cD2 ) . In addition , it has been shown that the C-terminal region of KIF1c is involved in protein-protein interactions and cargo function [17]–[20] . Therefore , substitutions at 578 , 1027 , and/or 1066 may have a significant impact on KIF1c function . Given that KIF17b has been shown to control CREM-dependent transcription by regulating the intracellular location of the transcriptional coactivator ACT ( activator of CREM in testis ) [21] , [22] , and CREM binding to the Il2 promoter suppresses its activity [23] , we evaluated the effect of LSS Kif1cCByJ and PPY Kif1cD2 alleles on Il2 transcriptional activity as an in vitro assay of KIF1c allelic function . Jurkat cells were co-transfected with a plasmid containing the PPY Kif1cD2 allele , the LSS Kif1cByJ allele , or an empty plasmid , and an Il2-promoter luciferase reporter . Cells were then activated with phorbol myristate acetate ( PMA ) and calcimycin , a calcium ionophore , and the luciferase activity quantified . Jurkat cells that were transfected with the plasmid containing the PPY Kif1cD2 allele displayed significantly decreased luciferase activity ( mean decrease 31 . 46±8 . 59% , P = 0 . 03 ) as compared to the plasmid containing the LSS Kif1cCByJ allele or the control plasmid ( Figure 7A ) . These data demonstrate the functionality of the KIF1c structural polymorphism . To further characterize the amino acid ( s ) responsible for the observed differences on Il2-promoter activity associated with the alleles , we replaced the D2-P578→L578 ( LPY-KIF1c ) or D2-P1027→S1027 ( PSY-KIF1c ) . Jurkat cells were co-transfected with the plasmids containing the wild type D2 PPY-KIF1c allele , LPY-KIF1c ( P578→L578 ) or PSY-KIF1c ( P1027→S1027 ) mutant alleles , or a control plasmid , and Il2-promoter luciferase reporter . Cells were activated with PMA and calcimycin and luciferase activity was assessed . As shown in Figure 7B , LPY-KIF1c and PSY-KIF1c mutants resulted in increased Il2-promoter luciferase activity compared to the D2 PPY-KIF1c allele . Taken together , our data demonstrate that structural polymorphisms at position 578 and 1027 are critical for KIF1c allelic functions .
EAO is an organ-specific autoimmune disease that is a model of immunological male infertility [1] , [2] . We previously demonstrated that genetic control of EAO is complex and involves both H2-linked ( Orch1 ) and non-H2-linked ( Orch3 , Orch4 , and Orch5 ) genes [24] , [25] . The H2-linked immune response genes primarily control susceptibility to EAO , whereas the non-H2-linked genes suppress the phenotypic expression of disease associated with a susceptible Orch1/H2 allele [9] . Here we report the identification of Orch3 as Kif1c that suppresses EAO by decreasing MHC class II expression and impairing APC function . Importantly , Kif1c may be a shared-autoimmune gene controlling susceptibility to experimental allergic encephalomyelitis ( EAE ) [26] . Eae7 , Eae22 , and Eae23 are linked to Orch3 [27] , and CByJ and D2 mice are susceptible and resistant to EAE , respectively [28] . With the exception of tyrosine kinase-2 ( Tyk2 ) , in which a rare single nucleotide polymorphism in a well conserved APE motif within the pseudokinase domain is fully penetrant in controlling susceptibility to autoimmune diseases [29] , [30] , the vast majority of non-MHC autoimmune loci identified to date are QTL that exhibit only partial to minimal penetrance . This has proven to be problematic as researchers have attempted to positionally clone and characterize such genes [31] . The fact that Orch3/Kif1c controls a dominant negative immunoregulatory mechanism that suppresses autoimmune orchitis with a high degree of penetrance is unique . Because EAO resistance is conferred in a dominant fashion in this model , an animal must be Orch3CByJ/Kif1cCByJ homozygous to permit disease progression . By using a forward genetic approach , we have now established that Orch3 is Kif1c which , in isolation , controls resistance to EAO with a remarkable degree of penetrance . Using a transgenic approach we demonstrated that Kif1c is Orch3 , and that expression of the resistant Kif1cD2 allele by CD11b+ cells of CByJ mice confers complete protection from the development of EAO . Our data are consistent with the growing number of CD11b+ myeloid cell types with immunosuppressive activity [32] , [33] . Indeed , resistance to autoimmune type I diabetes in NOD mice and EAE correlated with the presence of immunomodulatory CD11b+ myeloid cells [34]–36 and the capacity of these cells to maintain a proper T regulatory cell function [37] . Kinesin family members are involved in the activation of immune cells and inflammatory responses [38] , [39] , and autoimmune disease GWAS identified KIF21B and KIF5A as candidates for autoimmune disease genes [40] , [41] , suggesting an immunoregulatory role for kinesin family members . In addition , kinesin proteins have been identified as the major molecular motor of microtubule-based intracellular transport [42] . Kif1c is expressed in a variety of tissues [43] and overexpression of a dominant negative form disrupts molecular motor-dependent Golgi-to-Endoplasmic Reticulum ( ER ) retrograde vesicular transport [18] . It is known that Kif1c alleles possess amino acid substitutions at residues 578 , 1027 , and 1066 [17] . Here , we demonstrated that residues 578 and 1027 are functionally significant . Although the amino acid polymorphism at residue 1027 is not in an evolutionarily conserved domain [17] , it is in the C-terminal region believed to participate in cargo binding . In fact , alterations of this domain have been shown to modify in vivo kinesin protein function [19] . Moreover , it has been shown that the C-terminal tail domain of KIF1c ( amino acids 811–1090 ) is involved in the interaction with bicaudal-D-related protein 1 ( BDRP1 ) and this interaction regulates secretory transport required for neurite development [20] . Therefore , the ability of KIF1c to bind and transport cargo may be altered by polymorphism in this region . However , motor-dependent Golgi-to-ER transport functions normally in Kif1c knockout mice [44] . Immunohistochemical staining partially co-localized KIF1c with the Golgi marker CTR433 , suggesting that KIF1c may also be involved in transport around the Golgi apparatus rather than only Golgi-to-ER transport . Accordingly , Wubbolts , et . al . [16] showed that kinesin plays a role in the vesicular transport of MHC II-containing lysosomes from the microtubule organizing center region towards the cell surface . Here , we provide evidence that the resistant Kif1cD2 allele negatively regulates the expression of MHC II proteins on APCs , since Tg-Kif1cD2 CD11b+ cells express lower mRNA and protein levels . The reduction in MHC II expression by CD11b+ Tg-Kif1cD2 cells was directly correlated with impaired antigen presentation as reflected by diminished Ag-specific T cell proliferative response . Whether amino acids at position 578 and 1027 on KIF1c are involved in MHC II expression is currently under investigation . Taken together , our results nevertheless provide mechanistic insight into how polymorphism in other kinesins including KIF21B and KIF5A influence human autoimmune disease susceptibility .
Mice were housed at 25°C with 12/12-h light-dark cycles and 40–60% humidity . The experimental procedures performed in this study were under the guidelines of the Animal Care and Use Committees of the University of Vermont ( Burlington , VT ) and University of Illinois at Urbana-Champaign ( Urbana , IL ) . BALB/cByJ ( CByJ ) , DBA/2J ( D2 ) , and ( BALB/cByJ×DBA/2J ) F1 hybrid ( CD2F1 ) mice were purchased from The Jackson Laboratory ( Bar Harbor , ME ) . The congenic lines in this study were generated using ( BALB/cAnPt×DBA/2NCr ) ×BALB/cAnPt backcross mice [45] . Third generation backcross mice heterozygous at Evi2 or at Hba and Es3 were selected and backcrossed for six generations to BALB/cAnPt mice and fixed by brother-sister mating to generate the C . D2-Evi2 and C . D2-Hba/Es3 lines . Overlapping interval specific recombinant congenic ( ISRC ) lines were generated by crossing C . D2-Evi2 mice to CByJ mice . F2 hybrids were genotyped using tail snip DNA and PCR with Chr11 microsatellite markers discriminating CByJ and D2 mice across the Orch3 candidate interval . Founders were analyzed for background contamination at a density of 2–5 cM and mice carrying CByJ alleles at all background marker loci were backcrossed an additional two generations to CByJ mice . The lines were fixed by brother-sister mating to generate the C . D2-3 , C . D2-5 , C . D2-8 , and C . D2-9 ISRC lines . Similarly , higher order resolution mapping panels of ISRC lines were generated by screening ( C . D2-3×CByJ ) ×CByJ , ( C . D2-8×CByJ ) ×CByJ and ( C . D2-3 . 2×CByJ ) ×CByJ backcross mice for recombinants . The genealogy and complete genotypes of the C . D2 congenic mice used in this study are given in Figure S1 and Figure S2 , respectively . The CByJ . CD11B-Kif1cD2 transgenic ( Tg-Kif1cD2 ) mice were generated by microinjection with a construct containing the human CD11B/ITGAM promoter [46] , Kif1cD2 cDNA , and the human growth hormone ( hGH ) polyA signal [47] into C fertilized eggs at the University of Vermont Transgenic/Knockout Facility . Mice were screened for hGH gene by PCR using hGH Fwd 5′ TAG GAA GAA GCC TAT ATC CCA AAG G 3′ , hGH Rev 5′ ACA GTC TCT CAA AGT CAG TGG GG 3′ primers . Proinsulin Fwd 5′ CTA GTT GCA GTA GTT CTC CAG 3′ and proinsulin Rev 5′ CCT GCC TAT CTT TCA GGT C 3′ primers were used as internal control . Genomic DNA was PCR-amplified using standard conditions and the following primers designed around a polymorphism in Nlrp1a: 5′-GGGCACATGGATTCAGAGAT-3′; 5′-AGAGACCCCACCCAACTTC-3′ . 10 µl of PCR reaction was digested using 5 units of ApaLI in 50 µl of 1× NEBuffer 4 ( New England BioLabs , Inc . , Ipswich , MA ) for 1 hour at 37°C . Resulting fragments were electrophoresed in 2% agarose gels and visualized by ethidium bromide . Six-12 week old mice were immunized as previously described [9] with 10 mg of TH plus CFA ( Sigma-Aldrich , St . Louis , MO ) supplemented with 200 µg of Mycobacterium tuberculosis H37Ra ( Difco Laboratories , Detroit , MI ) in conjunction with PTX ( List Biological Laboratories Inc . , Campbell , CA ) . EAO was evaluated at 25–30 days post-injection . The testes were processed for histological examination as previously described [9] . Histopathologic analysis was carried out in a double-blind manner with each testis being scored individually on a PI from 0–10 as described previously [9] . The overall score for each animal was calculated as the average of both testes with the strain means representing the average of the averages . Spleens were collected from CByJ and Tg-Kif1cD2 mice , and single cell suspensions were prepared by passing the cells through a 50 µm nylon mesh ( Small parts Inc , Miami Lakes , FL ) . Erythrocytes were lysed using complete Geyes solution , washed two times and plated to obtain adherent cells . Adherent cells were removed by treating with 0 . 025% Trypsin-EDTA ( Invitrogen , Carlsbad , California ) , washed three times and pelleted . Whole-cell lysates were prepared in Triton lysis buffer and equal amounts of protein were then separated via SDS-PAGE and transferred to nitrocellulose membranes as described previously [48] . Primary antibodies used for Western blot include anti-Kif1c and anti-Actin ( Santa Cruz Biotechnology Inc . , Santa Cruz , CA ) . Bound antibody was visualized by peroxidase-conjugated secondary antibody and detected by chemiluminescence ( Kirkegaard and Perry Laboratories , Gaithersburg , MD ) . NLC and Tg-Kif1cD2 myeloid cells from erythrocyte-free spleens were first enriched by negative selection ( using magnetic beads , Qiagen , Hilden , Germany ) to deplete cells expressing CD8 , CD4 , and IgM . For FACS isolation , negatively selected enriched-myeloid cells were stained with anti-CD11b–APCCy7 ( BD Pharmingen . Franklin Lakes , NJ ) , anti-CD11c-PECy5 . 5 ( Invitrogen , Camarillo , CA ) , anti-TCRβ–FITC , and anti-IA/IE-PE ( eBioscience , San Diego , CA ) , and sorted on a FACSAria ( BD Biosciences , San Jose , CA ) by gating in the TCRβ−IA/IE+CD11c−CD11b+ myeloid cell population . Antibodies against B220 and CD19 ( eBioscience ) were also used for flow cytometry . Total RNA was extracted and purified from TCRβ−IA/IE+CD11c−CD11b+ myeloid cells from naïve NLC and Tg-Kif1cD2 mice ( n = 6 to 10 mice/strain ) using RNeasy isolation reagent ( Qiagen Inc . ) . Purified RNA was quantified using a Nanodrop ND1000™ spectrophotometer ( Thermo Scientific , Wilmington , DE ) and quality was assessed using an Agilent 2100 bioanalyzer ( Agilent Technologies , Palo Alto , California ) . The RNA integrity number of all samples was greater than 8 . For microarray analysis , two RNA pools were created so that each pool contained RNA from 3 to 5 mice , and two arrays per strain were analyzed . RNA amplification and microarray analysis was performed at UVM Microarray Core Facility using previously described protocols [49] . Briefly , 2 µg of total RNA from each pooled sample were reverse transcribed to the single stranded cDNA using T7-oligo ( dT ) primer . T4 DNA polymerase was used to synthesize double-stranded cDNA , which served as a template for in vitro transcription using T7 RNA polymerase to produce biotinylated cRNA . The biotinylated cRNAs were fragmented into 50- to 200-base fragments and then hybridized to GeneChip Mouse Genome 430A 2 . 0 Arrays for 16 h at 45°C in a rotating Affymetrix GeneChip Hybridization Oven 320 . After hybridization , arrays were washed and stained with streptavidin-phycoerythrin on an automated Affymetrix GeneChip Fluidic Station F450 . The arrays were scanned with an Affymetrix GeneChip Scanner 2700 and the images quantified using Affymetrix GeneChip Operating Software . The signal intensity for each probe on each chip was calculated from scanned images using GeneChip Operating Software ( Affymetrix ) , and signal intensities were analyzed using BioConductor ( http://www . bioconductor . org ) . Probe intensities were background corrected , normalized , and summarized using the Robust Multichip Average method described by Speed and coworkers [50] , [51] . An alternative normalization method based on reference genes did not significantly change the results . The FDR for differential expression between NLC and Tg-Kif1cD2 for each individual gene was calculated using the method of Benjamini and Hochberg [52] . Gene expression data were analyzed using a threshold of FDR≤0 . 05 to identify differentially expressed genes . NLC and Tg-Kif1cD2 mice were immunized at d0 and d7 s . c . in the posterior right and left flank and the scruff of the neck with a sonicated PBS/oil emulsion containing 20 µg of OVA , faction V ( Sigma-Aldrich , St . Louis , MO ) , or 100 µg of PLP180–199 in CFA supplemented with 200 µg of Mycobacterium tuberculosis H37Ra . Spleens and LN were harvested on d10 . APCs from erythrocyte-free spleens were obtained by anti-CD4/anti-CD8 complement depletion and treated with mitomycin C ( 25 µg/ml; Sigma-Aldrich ) . Responder CD4 T cells from LN and spleens were isolated by negative selection as previously described [48] . Single cell suspensions of OVA- or PLP180–199-APCs ( 2×105 cells/well ) and Ag-specific responder CD4 T cell ( 1×105 cells/well ) suspensions were prepared in RPMI 1640 ( 5% FBS ) , and plated on standard 96-well U-bottom tissue culture plates . Cells were stimulated with 1 , 10 , and 25 µg/ml of OVA or 2 . 5 , 10 , and 50 µg/ml of PLP180–199 for 72 h at 37°C . During the last 18 h of culture , 1 µCi of [3H] thymidine ( PerkinElmer , Santa Clara , CA ) was added . Cells were harvested onto glass fiber filters and thymidine uptake was determined with a liquid scintillation counter . Jurkat cells were cultured in RPMI containing 10% FBS without stimulation for 24 hours at a concentration of 1×106 cells/ml . Plasmids encoding Kif1cD2 , Kif1cCByJ alleles , LPY-KIF1c and PSY-KIF1c mutants , corresponding empty vector ( pcDNA , Invitrogen , Carlsbad , CA ) , Il2 promoter ( −575 to +57 base pairs ) luciferase reporter , and control pGL2 luciferase reporter ( Promega , Madison , WI ) were used for transfection . Five micrograms of each plasmid were used for the transfection of approximately 5×106 Jurkat cells by electroporation at 250 mV and 900 µF in 250 µl of RPMI with a BioRad electroporator ( BioRad , Hercules , CA ) . Cells were subsequently cultured in RPMI and 10% FBS for 24 hours and then stimulated with PMA ( 10 ng/ml ) and calcium ionophore calcimycin ( 0 . 5 µg/ml ) for 3 hours . Cell lysates were prepared and supernatants collected to quantified luciferase activity ( Promega , Madison , WI ) . The luminescence was measured immediately using a luminometer ( Sunnyvale , CA ) . The transfection efficiency was compared between the samples by co-transfecting a plasmid encoding β-galactosidase . The luciferase activity was normalized using the β-galactosidase value . Point mutations were introduced in the plasmid encoding the Kif1c allele from the D2 mouse using the QuikChange Site-Directed mutagenesis kit ( Stratagene , USA ) . Briefly the plasmid was denatured and then annealed with the appropriate mutagenic primer that contained the desired mutation . Using Pfu DNA polymerase , new mutagenized strands were created . The parental DNA template was digested with DpnI and the new mutated plasmid was used to transform E . coli . The plasmid DNA was extracted using the Qiagen Maxi-Prep kit ( Qiagen , Valencia , CA ) . The primers used for mutagenesis of the nucleotide at position 1033 ( amino acid 578 ) of the D2 allele were: forward: 5′-GCTCGTGACGGAGCTGCTGGTGCTGAAGTC-3′; reverse: 5′-GACTTCAGCACCAGCAGCTCCGTCACGAGC- 3′; and for the nucleotide at position 3079 ( amino acid 1027 ) : Forward: 5′CGAAGACCCCACCGTTCTCGCAGGAATTCCC-3′ , and Reverse: 5′GGGAATTCCTGCGAGAACGGTGGGGTCTTCG-3′ . | Although the etiology of autoimmunity is not well known , a variety of studies have demonstrated that genetic predisposition is a major contributor to disease susceptibility and resistance . The major histocompatibility complex ( MHC ) is the primary genetic determinant of autoimmune disease susceptibility with multiple additional interacting loci required . However , the identification and characterization of non–MHC genes has been problematic , since most autoimmune diseases are polygenic with the individual genes exhibiting only partial or minimal penetrance . We previously identified Orch3 ( mouse chromosome 11 ) as the most important immune-suppressive locus controlling dominant resistance to autoimmune orchitis , the principal animal model of non-infectious testicular inflammatory/autoimmune disease . Here , using congenic mapping , we identified kinesin family member 1C ( Kif1c ) as a positional candidate for Orch3 . Furthermore , over-expression of the Kif1c resistant allele in susceptible mice rendered animals autoimmune orchitis resistant , demonstrating that Kif1c is Orch3 . We propose that Kif1c plays an immunoregulatory role by controlling the levels of MHC class II in antigen presenting cells and consequently impacting autoreactive orchitogenic T cell responses . These finding are particularly relevant since polymorphism in other kinesins such as KIF21B and KIF5A have been associated with susceptibility and resistance to human autoimmune disease . | [
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] | 2012 | Identification of Orch3, a Locus Controlling Dominant Resistance to Autoimmune Orchitis, as Kinesin Family Member 1C |
Malaria parasites must undergo sexual and sporogonic development in mosquitoes before they can infect their vertebrate hosts . We report the discovery and characterization of MISFIT , the first protein with paternal effect on the development of the rodent malaria parasite Plasmodium berghei in Anopheles mosquitoes . MISFIT is expressed in male gametocytes and localizes to the nuclei of male gametocytes , zygotes and ookinetes . Gene disruption results in mutant ookinetes with reduced genome content , microneme defects and altered transcriptional profiles of putative cell cycle regulators , which yet successfully invade the mosquito midgut . However , developmental arrest ensues during the ookinete transformation to oocysts leading to malaria transmission blockade . Genetic crosses between misfit mutant parasites and parasites that are either male or female gamete deficient reveal a strict requirement for a male misfit allele . MISFIT belongs to the family of formin-like proteins , which are known regulators of the dynamic remodeling of actin and microtubule networks . Our data identify the ookinete-to-oocyst transition as a critical cell cycle checkpoint in Plasmodium development and lead us to hypothesize that MISFIT may be a regulator of cell cycle progression . This study offers a new perspective for understanding the male contribution to malaria parasite development in the mosquito vector .
Malaria pathology is caused by asexual replication of apicomplexan parasites Plasmodium in the host bloodstream , but transmission between hosts requires sexual replication of parasites within mosquitoes . Subsets of sexually committed haploid merozoites escape each bloodstream replication cycle and differentiate into male and female gametocytes . Mature gametocytes are arrested in development until their uptake by a female mosquito during her blood meal . These cells reportedly have increased DNA content that may suggest selective gene amplification since genome replication does not occur during gametocytogenesis [1] , [2] , [3] . Gametogenesis begins within minutes of gametocyte ingestion into the mosquito gut . A male gametocyte undergoes three successive rounds of DNA replication producing eight haploid genome copies , initially confined within a persistent nucleus [2] , [3] . Karyokinesis and cytokinesis , and consequent release of eight gametes are facilitated by cytoplasmic axonemes , each of which pulls one genome copy into the developing flagellate microgamete [4] . This process is known as exflagellation and regulated by calcium-dependent signaling . Two key regulators have been identified in the rodent malaria parasite Plasmodium berghei: the cyclin-dependent kinase CDPK4 controls the initiation of genome replication [5] while a downstream mitogen-activated protein kinase , map-2 , regulates the onset of cytokinesis and release of microgametes [6] , [7] . In parallel , activated female gametes ( macrogametes ) enlarge and emerge from the red blood cells . Fertilization begins with gamete adhesion , followed by plasma membrane fusion and entry of the male nucleus and axoneme into the macrogamete [8] . The P48/45 protein on the surface of microgametes is essential for the initial fertilization stages [9] . In P . berghei , fusion is mediated by the male sterility factor HAP2 [10] , also known as generative cell specific 1 ( GCS1 ) [11] . Pronuclei fusion is followed by a meiotic replication cycle that , in the absence of nuclear division and cytokinesis , renders the zygote tetraploid [2] , [8] . Initiation of meiotic DNA replication is regulated by female-specific expression of the NIMA ( never-in-mitosis/Aspergillus ) -related kinase , Nek-4 [6] , [12] . Within the next 12–24 hours , the zygote elongates and develops into the mature ookinete . This process is associated with formation of the polar ring that acts as a microtubule-organizing centre ( MTOC ) at the ookinete apical pole , organizing a network of subpellicular microtubules [13] . This network regulates polarized trafficking of secretory organelles including micronemes and is linked to the ookinete actomyosin motor , together facilitating the motility and invasive ability of the ookinete that escapes the blood bolus and traverses the midgut epithelium . Further DNA replication and chromosome segregation occur only after the ookinete reaches the basal lamina , where it rounds up and transforms into the sessile oocyst . Morphological changes associated with this transition include loss of the apical complex and subpellicular microtubules , and parasite encasement in a proteinaceous capsule [4] . As development progresses , the nucleus becomes polyploid through multiple rounds of endomitosis while the plasmalemma invaginates forming sporoblasts . In the mature oocyst , synchronous nuclear divisions direct sporozoite budding-off from the sporoblasts , generating thousands of haploid sporozoites . These are released into the mosquito haemocoel , invade the salivary glands and infect new hosts during subsequent mosquito blood meals . Throughout Plasmodium development , DNA replication , chromosome segregation and cytokinesis are uncoupled . The molecular mechanisms underpinning and regulating this unorthodox cell cycle remain poorly understood . Here we report the discovery and characterization of MISFIT , a novel nuclear formin-like protein with critical functions in P . berghei sexual and sporogonic development in the mosquito . Formins are involved in the regulation of the actin and microtubule networks during mitosis , meiosis , cell polarization and vesicular trafficking [14] . The misfit gene is expressed in gametocytes , and the protein is detected in the nucleus of male gametocytes , zygotes and ookinetes . Disruption of the gene leads to ookinetes with incomplete genome content ( approximately 3C-values ) and defects in the transcription of putative cell cycle regulators . These ookinetes invade the mosquito midgut but are arrested in development during their subsequent transformation into oocysts , resulting in transmission failure . Our data suggest involvement of MISFIT in the regulation of microtubule remodeling during DNA replication and chromosome segregation in mitosis in male gametocytes and/or meiosis in zygotes . Furthermore , we establish the ookinete-to-oocyst transition as a cell cycle checkpoint of Plasmodium development . Mutant ookinetes also have severely reduced numbers of micronemes , but do invade the mosquito midgut . This points to an intriguing function of MISFIT in vesicular trafficking and challenges the long-held view that micronemes are indispensable for midgut invasion . Genetic crosses reveal an absolute requirement for a functional male allele of misfit in Plasmodium development in the mosquito . This is the first gene with paternal effect on Plasmodium post-fertilization development . Its discovery opens new research avenues for understanding the male contribution to parasite development in the mosquito and ultimately malaria transmission .
We searched published proteomic data for putative nuclear proteins expressed during P . berghei development in the mosquito to investigate the mechanisms that regulate the parasite sexual and early sporogonic development in the vector . Two separate studies detected the Pb000064 . 01 . 0 protein in mature oocysts [15] and in gametocytes [6] , respectively . We named this protein MISFIT for reasons explained below . It is an 180 kDa protein bearing a Formin Homology 2 ( FH2 ) domain , the defining feature of formins , and a nuclear localization signal ( NLS ) ( Figure S1A ) . Using a domain prediction algorithm for proteins associated with nuclear functions [16] , we detected a putative kinase domain at the N-terminus of MISFIT , downstream of the NLS . A basic amino acid region at the C-terminus of MISFIT shows similarities to the self-inhibitory Diaphanous Autoregulatory Domain ( DAD ) present at the C-termini of Diaphanous-related formins ( DRFs ) [17] . Two formins with orthologs in all plasmodia have been identified previously in Plasmodium falciparum [18] , [19] . Unlike MISFIT , these two and many other formins encompass a proline-rich FH1 domain that interacts with profilin-bound actin monomers , thus accelerating actin filament elongation [14] . Bioinformatic searches revealed the presence of orthologous MISFIT proteins in diverse Plasmodium species . Their identity with P . berghei MISFIT ranges from 92% in Plasmodium yoelli to 32% in P . falciparum and Plasmodium vivax . Similarities are highest in the FH2 domain and a central region of ∼180 amino acids ( Figure S2 ) . Putative N-terminal kinase-like domains are also predicted for P . yoelli and P . falciparum MISFITs . Phylogenetic analysis of the FH2 domains in all the apicomplexan formin-like proteins revealed highest similarity between Plasmodium MISFITs and Cryptosporidium parvum Formin 4 ( Figure S1B ) . We used quantitative real-time RT-PCR to investigate in vivo the stage-specific transcription of the misfit gene in midguts of A . gambiae mosquitoes fed on P . berghei-infected mice . Abundant transcripts were detected 1 h and 24 h post blood feeding ( pbf ) , corresponding to the beginning and end of parasite development in the midgut lumen , respectively ( Figure 1A ) . After invasion across the midgut epithelium and oocyst formation on the basal midgut wall , misfit expression drops significantly and is barely detectable after day-5 . RT-PCR analysis revealed misfit transcripts to be present in mixed asexual and sexual blood-stage parasites and purified gametocytes , but not in purified zygotes or ookinetes ( Figure 1B ) . Thus , transcripts observed in mosquito midguts 24 h pbf probably derive not from zygotes or ookinetes , but from earlier developmental stages that persist in the blood bolus . Data presented later in the manuscript revealed that expression of misfit takes place in gametocytes . Mutant P . berghei were generated by replacing part of misfit with a modified Toxoplasma gondii pyrimethamine resistance cassette in the Pbc507 GFP-expressing parasite reference line [20] . Integration of this disruption cassette was verified by pulse field gel electrophoresis , and generation of clonal Δpbmisfit parasites was confirmed by PCR and Southern blot analysis ( Figure S3 ) . Compared to wild-type ( wt ) controls , the Δpbmisfit knockout ( ko ) mutant parasites exhibited normal development of asexual blood stages , mature gametocytes and male gametes . The conversion rate of mutant macrogametes to ookinetes was also comparable to the controls ( Figure 1C ) , and both stages displayed normal morphology and surface distribution of the P28 protein [21] ( Figure 1D ) . However , sporogonic development of misfit ko parasites in both A . gambiae and A . stephensi mosquitoes was severely compromised: mature oocysts were extremely rare and small in size ( Figure 1E and Table S1 ) . Furthermore , unlike the highly organized nuclei of wt oocysts , the few Δpbmisfit oocysts that persisted to day-15 pbf showed much reduced and diffuse DNA staining ( Figure 1E ) , indicating possible defects in DNA replication and/or chromosome segregation . Oocyst numbers were severely reduced already at day 3 pbf ( Figure 1F and Table S2 ) , indicating that MISFIT is essential for the ookinete-to-oocyst developmental transition . This reduction became progressively more obvious , as mosquitoes gradually cleared defective oocysts . Direct membrane feeding of mosquitoes with a suspension of in vitro produced ookinetes in uninfected blood yielded similar results ( data not shown ) . These data were independently corroborated by disruption of misfit in the P . berghei 2 . 34 ANKA genetic background ( data not shown ) . We used A . gambiae C-type lectin 4 ( CTL4 ) knockdown ( kd ) mosquitoes to investigate whether mutant Δpbmisfit ookinetes can invade the midgut epithelium . CTL4 is an inhibitor of melanization , and its depletion by RNAi causes mosquitoes to melanize ookinetes soon after they reach the basal sub-epithelial space , where they encounter hemolymph components that are essential for melanization [22] . The numbers of melanized Δpbmisfit and wt control ookinetes were comparable , indicating that the mutant parasites are not invasion deficient ( Figure 1G ) . Furthermore , Δpbmisfit ookinetes injected directly into the mosquito hemocoel failed to rescue the ko phenotype ( Table S3 ) . Taken together our data clearly indicate that the Δpbmisfit phenotype is determined at the onset of oocyst development , and not by failure of midgut invasion . We used a single homologous recombination approach to generate a transgenic P . berghei line ( pbmisfit-myc ) expressing a C-terminal MYC-tagged MISFIT protein ( Figure S4 ) and investigate the pattern of MISFIT protein expression . Mosquitoes infected with tagged parasites exhibited intensities of sporulating oocysts comparable to those in control infections ( data not shown ) , indicating that the tagged protein is fully functional . Southern blot analysis of the parasite input ( blood-stage parasites from gametocyte-donor mice ) and output ( blood-stage parasites from sporozoite-recipient mice ) verified that developmental normality is not due to wt contaminants ( Figure 2A ) . Western blot analysis using an anti-MYC antibody revealed high MISFIT levels in gametocytes , both before ( non-activated ) and after ( activated ) induction of gametogenesis , and lower levels in purified ookinetes ( Figure 2B ) . In conjunction with the absence of misfit transcripts from zygotes and ookinetes ( Figure 1B ) , these data suggest protein carry over from earlier developmental stages . Indeed , the protein was also detected in purified male gametes ( Figure 2C ) . Immunofluorescence assays in pbmisfit-myc parasites provided clear insights into the sub-cellular localization and putative function of MISFIT . Consistent with its NLS prediction , MISFIT is localized in the nuclei of male gametocytes ( activated and not ) , zygotes and ookinetes ( Figure 3 ) . The presence of MISFIT in the male gametocyte nucleus was corroborated by co-localization experiments with SET ( Figure 3A ) , a protein putatively involved in chromatin dynamics , which also strongly accumulates in male gametocytes [23] . Importantly , MISFIT localization did not perfectly match the DNA staining; it exhibited broader , sometimes polarized distribution , indicating that the protein is not a ubiquitous component of chromosomes . A weak , slightly above background signal in female gametocytes ( Figure 3B ) , in conjunction with earlier proteomic data [6] , suggests the possibility of low protein expression in females . MISFIT was not detected in asexual blood stage trophozoites or schizonts ( data not shown ) . In male gametogenesis , each round of DNA replication is followed by segregation of the haploid genomes to different poles of the compartmentalized nucleus [8] . During this process , MISFIT-MYC staining appears to follow the distribution of DNA ( Figure 3C ) , possibly suggesting MISFIT involvement in chromosome segregation , which would be consistent with the putative function of formin-like proteins in regulating the microtubule cytoskeleton . Contrary to the clear detection of MISFIT-MYC in male gametes by western blot ( Figure 2C ) , immunofluorescence staining could not confirm the presence of this protein in emerging ( Figure 3D ) or released male gametes ( data not shown ) . In all confocal observations of exflagellating male gametocytes , MISFIT-MYC staining was confined within the parental gametocyte nucleus . The nuclear staining of MISFIT in zygotes and ookinetes resembled that in male gametocytes , with a broader pattern than that of the DNA staining and sometimes polarized or peripheral distribution ( Figure 3E , 3F ) . Since the effect of MISFIT on parasite development is manifested after fertilization , at the ookinete-to-oocyst transition , we investigated whether inheritance of female or male wt misfit alleles by the zygote would be sufficient to rescue the ko phenotype . We performed genetic crosses between Δpbmisfit parasites and P . berghei mutants deficient either in female ( Δpbs47 ) or in male ( Δpbs48/45 ) gametes [6] , [9] , [24] . The results revealed a strict requirement for a functional male copy of misfit ( Figure 4 and Table S4 ) . Crosses between Δpbmisfit and Δpbs47 mutants yielded oocysts of normal number , size , morphology , and capability to sporulate . In contrast , crosses between Δpbmisfit and Δpbs48/45 parasites invariably produced oocysts exhibiting the misfit ko phenotype . The requirement for a male misfit allele was corroborated by Δpbmisfit crosses with additional female or male gamete deficient mutants carrying functional misfit genes: Δpbnek4 [6] , Δpbmap2 [7] and Δpbcdpk4 [5] . Control crosses of Δpplp5 mutants [25] with the gamete deficient strain Δcdpk4 confirmed that the paternal effect is specific to Δpbmisfit parasites ( Table S4 ) . Pplp5 is required post-fertilization , during midgut invasion and its ko phenotype can thus be rescued by both maternal and paternal wt pplp5 alleles [25] , [26] . Based on these data , we named the gene misfit for male-inherited sporulation factor important for transmission . Microscopy observations suggested that Δpbmisfit ookinetes have reduced amounts of DNA ( Figure 5A ) . We treated parasites 1 h post fertilization with the DNA polymerase inhibitor aphidicolin to inhibit meiotic DNA replication in zygotes and produce ookinetes with diploid instead of tetraploid genomes [2] . We then used DAPI-staining measurements of microscopy images ( Figure 5B ) to compare the amounts of DNA between Δpbmisfit , aphidicolin-treated and untreated ookinetes . These measurements were normalized to the DNA content of asexual haploid parasites . Importantly , Δpbmisfit ookinetes exhibited an intermediate C-value of 3 indicating that in the absence of MISFIT , meiotic DNA replication was initiated but either was aborted prior to completion , or the starting DNA material was less than in the wt controls . Flow cytometry measurements of Δpbmisfit and wt ookinetes following treatment with a fluorescent DNA-intercalating dye DRAQ5 confirmed the mutant is DNA deficient ( Figure 5C ) . Infections of control and CTL4 kd A . gambiae with aphidicolin-treated ookinetes revealed that these ookinetes invade the mosquito midgut but fail to transform into oocysts , exhibiting a phenotype indistinguishable from that of misfit ko parasites ( Figure S5 ) . These results indicate that meiotic DNA replication in zygotes does not affect ookinete development and midgut invasion , but is critical for transforming ookinetes into oocysts , perhaps at initiation of mitosis in the oocyst . We investigated whether absence of MISFIT and the consequent effects on ookinete DNA content and meiotic replication also affect the ookinete transcriptome . Hybridizations of long oligonucleotide microarrays representing 5 , 361 genes encoded by the P . berghei genome identified 231 genes as at least 1 . 7-fold up- or downregulated in the in vitro cultured misfit-deficient ookinetes , as compared to wt controls ( Figure 5D and Table S5 ) . INTERPRO domain scans indicated that several such genes might function in cell cycle regulation and DNA replication . They include the transcription factor Myb1 that reportedly regulates the P . falciparum intra-erythrocytic cell cycle [27] , a member of the regulator of chromosome condensation superfamily [28] , DNA and RNA helicases , nucleoside biosynthesis enzymes , DNA repair enzymes , a cyclin , and eight kinases , some predicted to be cyclin-dependent . Genes involved in the regulation of transcription and translation were also included , e . g . hmgb2 , a known important regulator of sexual gene expression in P . yoelii [29] . However , the most affected gene by far ( 160-fold downregulated ) was the chitinase-encoding pbcht1 gene . Chitinase is a micronemal protein implicated in mosquito midgut invasion [30] . Orthologous P . falciparum and Plasmodium gallinaceum enzymes are thought to facilitate penetration of the chitinaceous peritrophic matrix that envelops the blood bolus in the midgut [31] . We used electron microscopy to investigate whether disruption of misfit causes morphological changes to ookinetes , undetectable by light microscopy . The results revealed that misfit ko ookinetes exhibit a severe defect in micronemes ( Figure 5E ) , the specialized organelles in the ookinete apical complex that secrete soluble or cell surface molecules , including CHT1 [31] . Of 38 analyzed sectioned profiles of mutant ookinetes , only one displayed normal micronemal content; 21 had greatly reduced microneme numbers , and 16 had none at all . We used RT-PCR to investigate whether the defect in microneme formation is accompanied by downregulation of additional micronemal protein encoding genes ( Figure 5F ) . Of four examined genes , warp [32] was also downregulated in the absence of MISFIT , but much less so than cht1 . The expression of ctrp [33] , [34] and soap [35] was unaffected .
Apicomplexan parasites require sexual reproduction to complete their complex life cycles . Sexual reproduction and subsequent sporogonic development of Plasmodium in mosquitoes ultimately result in malaria transmission . Understanding the genetic and molecular basis of transmission could lead to novel approaches for tackling one of the most devastating diseases of mankind . To date , three distinct classes of genes have been identified with critical functions in Plasmodium sexual and early sporogonic development . The first class includes genes such as P48/45 [9] that are expressed in gametocytes and playing essential roles in gamete development or fertilization . The second class encompasses genes expressed de novo in the zygote , e . g . ctrp and cht1; they are typically implicated in ookinete motility and invasion . The third class comprises two subclasses of genes showing maternal effects . One subclass includes genes such as P25 and P28 , which produce transcripts that are translationally repressed by the DOZI complex and only released for translation in the zygote [36] . The second subclass includes genes transcribed and translated in the female gametocyte but showing mutant phenotypes only post-fertilization , e . g . the LAP genes ( also known as PCCp ) with phenotypes manifested during oocyst development [24] , [37] . The molecular basis of these maternal effects is not well understood . The characterization of misfit hereby establishes a fourth class of genes that are critical for sexual and early sporogonic development . Misfit is the first gene with paternal effect on Plasmodium post-fertilization development . Disruption of the gene results in ookinetes that invade the mosquito midgut but are arrested in development during their transformation to oocysts , thus blocking transmission . Genetic crosses revealed that the functional male allele of misfit alone is necessary and sufficient for normal parasite development and subsequent transmission to the host . Misfit transcripts are restricted to gametocytes , but the protein is more broadly distributed: it is found not only in the male gametocyte but also in the zygote and the ookinete . Thus the paternal effect of misfit on the post-fertilization stages can be due to a knock-on effect caused by the protein function in the male gametocyte , paternal inheritance of the protein to the zygote , or both . Indeed MISFIT is detected in the male gamete , and therefore paternal inheritance is possible . However , strong MISFIT staining in the zygote and ookinete leaves open the possibility of additional de novo protein synthesis after fertilization . Such expression would be temporally limited , as transcripts are not detected in 8-hour zygotes . To explain the paternal effect , such de novo expression would either be insufficient for rescuing the mutant phenotype or would occur only in the male allele , due to genetic imprinting . Epigenetic mechanisms of transcriptional regulation have been described for the P . falciparum var genes [38] and are thought to be important throughout the Apicomplexa [39] . Overall , the discovery of misfit opens unprecedented opportunities to study the male gamete contribution to Plasmodium development . MISFIT contains an FH2 domain , the defining feature of formins , a family of proteins that regulate the dynamic remodeling of the cytoskeleton in eukaryotic cells [14] , [40] . The diverse functions of formins include regulation of actin nucleation and polymerization , orientation of the MTOC and spindle alignment at mitosis and meiosis , stabilization of microtubules , cell polarity and vesicular trafficking [41] , [42] , [43] , [44] . Two formins have been previously identified in the human malaria parasite , P . falciparum , and their orthologs exist in all plasmodia [18] , [19] . Both proteins , like many of the known formins , contain an FH1 domain that interacts with profilin to bring actin monomers to the polymerizing filament . Indeed , PfFormin1 regulates actin polymerization and localizes at the parasite-erythrocyte moving junction during invasion [18] . Apart from the FH2 domain , MISFIT does not share additional domains with the other two Plasmodium formins and thus is unlikely to share a similar function . Furthermore , MISFIT has an NLS , a DAD-like motif found in DRFs [17] and an unclassified kinase-like domain that is predicted to exist in nuclear proteins [16] . Recently , two formins with kinase C1-like domains were identified in the amoeba [45]; they localize with the spindle during mitosis and regulate DNA content and cell division . Loss of MISFIT function results in ookinetes with reduced DNA content . This finding , in conjunction with MISFIT expression in the male gametocyte , its nuclear localization and distribution , and its domain composition suggest a putative role of this novel formin-like protein in regulating the mitotic spindle during Plasmodium male gametogenesis . During mitotic DNA replication in the male gametocyte , the absence of MISFIT may affect the overall organization of the spindle or destabilize its microtubules , resulting in gametes carrying incomplete haploid genomes . As DNA synthesis and gametogenesis occur within minutes , mitotic checkpoints are unlikely to exist [46] . Indeed , it has been observed that a significant subset of wt male gametes lack nuclei [47] . Carrying less DNA may not compromise exflagellation and the fertilization capability of male gametes , but could affect meiotic chromosome segregation in the zygote , leading to checkpoint implementation and developmental arrest at the initiation of endomitosis in the oocyst . In support of this hypothesis , aphidicolin-treated zygotes that do not undergo meiotic DNA replication exhibit a phenotype similar to that of misfit mutant parasites: they form ookinetes that invade the mosquito midgut successfully but are developmentally arrested at the onset of oocyst transformation . As MISFIT is also found in the nucleus of zygotes and ookinetes , an additional role of this protein in meiotic DNA replication and spindle microtubule remodeling is also possible . In contrast to higher eukaryotes , the nuclear envelope of Plasmodium is maintained throughout the nuclear divisions ( endomitosis ) , and spindles do not originate from typical cytoplasmic centrioles . Instead , intranuclear spindles are organized by centriolar plaques located at the inner side of the nuclear membrane and originate from an amorphous cytoplasmic MTOC that transforms during mitosis into a structured kinetosome embedded in the nuclear envelope [47] . These atypical features of the Plasmodium cell cycle are in accordance with the nuclear localization of MISFIT , as opposed to the typical cytoplasmic localization of formins . One exception is an isoform ( mDia2 ) of a mammalian Diaphanous formin that was recently shown to also contain an NLS and shuttle between the cytoplasm and the nucleus [48]; the significance of this behavior of mDia2 remains unknown . The basic molecular mechanisms regulating the atypical Plasmodium cell cycle remain unclear , and developmental checkpoints similar to those described in higher eukaryotes have not been identified [46] . A lack of specificity in the cyclin/CDPK pairing is believed to relate to a less conserved and more flexible role of apicomplexan cyclins compared to higher eukaryotic cells [49] . Regardless of the exact function of MISFIT in mitosis and/or meiosis , our data suggest that the ookinete-to-oocyst transition serves as a checkpoint of Plasmodium cell cycle progression in the mosquito . Parasites that fail to successfully overcome this checkpoint are developmentally arrested and progressively cleared by the mosquito . Thus , the characterization of MISFIT provides a new perspective for studying the Plasmodium cell cycle regulation and its checkpoints . Our microarray data showed that genes encoding a cyclin , several CDPKs and additional putative cell cycle regulators are differentially regulated in misfit mutant ookinetes and are key candidates for being involved in these processes . The finding that misfit ko ookinetes have severely reduced micronemes is intriguing . Micronemes are the only known specialized secretory organelles of the ookinete and their secretions are thought to be important for host-cell recognition , binding and motility during parasite invasion [50] , [51] . Hence , the ability of misfit mutant ookinetes to invade the mosquito midgut challenges the long-held view that micronemes are essential for mosquito midgut invasion . Micronemes are synthesized de novo in the Golgi and translocate apically by using filamentous connections with sub-pellicular microtubules [3] , [51] . An obvious hypothesis would be that the microneme defect relates to the putative function of MISFIT in microtubule remodeling . However , sub-pellicular microtubules are organized in the cytoplasm by a circular MTOC known as the apical polar ring , whereas MISFIT is found only in the nucleus . The structure of the apical polar ring resembles the microgamete MTOC that organizes the formation of the mitotic spindle and axoneme [47] . It has not been established to date whether the apical polar ring is of maternal or paternal origin; it would be tempting to link the microneme phenotype of misfit with inheritance of a defective MTOC by the male gamete , but remains a subject for future research . The microneme deficit phenotype may also be due to changes in the expression of genes directly implicated in microneme formation . Indeed , our microarray experiments identified genes with putative functions in vesicle biogenesis and trafficking as being differentially regulated in misfit mutant ookinetes . Defective micronemes could in turn result in protein accumulation in the Golgi and generate negative signals that would downregulate the transcription of genes encoding micronemal proteins such as CHT1 and WARP . However , such feedback regulatory mechanisms are as yet unknown in Plasmodium . An alternative hypothesis is that the micronemal phenotype is caused by reduced production of cargo , e . g . CHT1 . This would be consistent with the finding that depletion of Pfg377 from P . falciparum female gametocytes leads to great reduction of secretory osmiophilic bodies [52] .
P . berghei strains ANKA 2 . 34 and 2 . 33 ( non-gametocyte producer ) , and the GFP-expressing reference lines 29c12 [53] and 507 [20] were propagated in mice using standard protocols . Parasite handling and purification of asexual and sexual blood stage parasites , male microgametes and ookinetes were performed as described [5] , [10] , [33] , [54] . For aphidicolin treatment , ookinete cultivation in vitro was allowed to proceed for 1 hour prior to addition of Nigrospora sphaerica aphidicolin at a final concentration of 50 µM ( Sigma ) [2] . A . gambiae Yaoundé and A . stephensi sda500 mosquitoes were cultivated and infected with P . berghei by either direct feeding on infected mice or ookinete membrane feeding using standard methods . For ookinete hemocoel injections , ookinetes were cultivated for 24 hours and injected into the thorax of A . stephensi mosquitoes ( 800 ookinetes per mosquito ) using glass capillary needles and Nanoject II microinjector ( Drummond Scientific ) . Protocols that involved the use of mice were approved by the UK Home Office ( Animals Scientific Procedures Act 1986 ) . Total RNA was isolated from parasite stages and mosquito midguts infected with Δpbmisfit using the Trizol® reagent ( Invitrogen ) . Gene-specific primers ( Table S6 ) were designed using Primer3 ( v . 0 . 4 . 0 ) . Quantitative real-time RT-PCR ( qRT-PCR ) was carried out using SYBR-Green and the ABI Prism 7700 Sequence Detector ( Applied Biosystems ) . Misfit transcript levels were normalized against transgenic gfp transcripts [53] that provided an internal reference for the fluctuation in parasite numbers during development . Three independent biological replicates were performed , which used different batches of mosquitoes fed on different blood sources ( different infected mice ) . The results of each biological replicate were the average of two technical replicates , in which RNA samples were processed in duplicate in the same qRT-PCR plate . Additional gene-specific primers were used for non-quantitative RT-PCR analysis of misfit , P28 , ama1 , cht1 , ctrp , soap , maebl and warp ( Table S6 and Protocol S1 ) . Targeted disruption of misfit by double homologous recombination in the P . berghei ANKA clone 2 . 34 or 507 genetic backgrounds was carried out as described [33] . In brief , 816 bp upstream and 870 bp downstream misfit target sequences were amplified from P . berghei ANKA clone 2 . 34 genomic DNA using the primer pairs pbmisfitA F ( ApaI ) /pbmisfitA R ( HindIII ) and pbmisfitB F ( EcoRI ) /pbmisfitB R ( BamHI ) , respectively ( Table S6 ) . PCR products were purified using the Promega Wizard® genomic DNA purification kit and cloned into the pBS-DHFR vector that encompasses the tgdhfr/ts pyrimethamine resistance cassette . For expression and localization studies , misfit was fused to a C-terminal myc tag by replacing 1 kb of the most 3′ terminal portion of the endogenous misfit locus with a tagged counterpart . Selection of transgenic parasite lines was carried out by pyrimethamine treatment and limiting dilution cloning to obtain clonal ko lines as described ( Protocol S1 ) [20] . Genomic DNA was prepared from transfected blood-stage parasite populations and subjected to diagnostic PCR and Southern blot analysis to assess successful integration ( Protocol S1 ) . For Southern blot analysis of the transgenic lines , genomic DNA was digested with EcoRV ( Δpbmisfit ) or HindIII ( pbmisfit-myc ) . The blot was hybridized against a PCR-generated probe recognizing an 816 bp ( Δpbmisfit; pbmisfit A F and R ) or 2 kb ( pbmisfit-myc; pbmisfit-myc F and R ) region of pbmisfit ( Table S6 ) . Pulse field gel electrophoresis was performed on chromosomes derived from purified blood stage parasites as previously described and the blot was hybridized against a probe recognizing the tgdhfr/ts cassette obtained by HindIII and EcoRV double restriction digest of the pBS-DHFR vector . Blood stage parasite enumeration and monitoring of the quality of preparations of purified gametocytes , male gametes and ookinetes were performed by light microscopy analysis of methanol-fixed Giemsa-stained ( Fluka ) blood films or parasite smears . Exflagellation assays and macrogamete to ookinete conversion were performed in ookinete medium as described [5] . For oocyst counts and imaging , infected midguts of female A . stephensi or A . gambiae were dissected in PBS , fixed in 4% formaldehyde in PBS ( FA-PBS ) for 30–45 min and washed 3 times in PBS for 15 min . Gene silencing was performed by injections of double stranded RNA in adult mosquitoes as described [22] . For Western blot analysis , samples of purified parasites were boiled under reducing conditions in SDS sample loading buffer , prior to 8% SDS-PAGE protein fractionation and immuno-detection according to standard procedures . For immunofluoresence assays ( IFA ) , purified parasite pellets were re-suspended in RPMI∶FCS ( 1∶1 ) , smeared on glass slides and allowed to air dry prior to fixation in 4% FA-PBS for 10 min . Activated gametocytes were allowed to settle onto poly-L-lysine ( 0 . 01% , Sigma ) coated glass slides in 4% FA-PBS o/n at 4°C . MISFIT-MYC was detected using a rabbit anti-myc monoclonal antibody ( Mab ) ( 71D10 , New England Biolabs ) according to manufacturer's instructions at a dilution of 1∶1000 ( WB ) or 1∶200 ( IFA ) . For co-staining with the rabbit anti-SET antibody ( dilution 1∶400 ) ( Pace et al . 2006 ) , MISFIT-myc was detected using a 1∶500 rat anti-myc antibody ( JAC6 , AbCam ) . P28 was detected with the 13 . 1-Cy3 Mab ( 1∶500 ) . Tubulin I ( TUB ) was detected with a mouse monoclonal antibody against Trypanosoma brucei alpha-tubulin ( tat1 ) at 1∶1000 for immunofluorescence and 1∶10000 for western blot [55] . Secondary antibodies used for IFA at 1∶1500 included: ALEXA FLUOR 488 goat anti-rabbit IgG , ALEXA FLUOR 488 goat anti-rat IgG , ALEXA FLUOR 647 goat anti-mouse or ALEXA FLUOR 647 goat anti-rabbit ( Molecular probes ) . For western blot analysis , horseradish peroxidase ( HRP ) conjugated goat anti-rabbit IgG ( 1∶15000 ) or goat anti-mouse IgG ( 1∶10000 ) ( Promega ) were used . DNA measurements were performed by either DAPI staining and quantification of fluorescent microscopy images , or by DRAQ5 staining and FACS ( Fluorescence-Activated Cell Sorting ) analysis ( Protocol S1 ) . Cells or tissues were mounted in VECTASHIELD Mounting Medium with or without DAPI ( Vector Labs ) . Parasites were imaged using a Leica DMT fluorescence microscope and images were captured using a Zeiss AxioCam HRc camera coupled to Zeiss Axiovision40 version 4 . 6 . 1 . 0 software . Post-processing of images was performed using ImageJ 1 . 40 . For IFA , visualization was achieved on a Leica SP5 confocal microscope . Images were background-corrected and noise-filtered with the Leica LAS AF software ( Leica Microsystems ) . 3D projections and additional image adjustments were performed with the Volocity ( PerkinElmer Inc ) and Adobe Photoshop CS2 ( Adobe ) software . Ookinetes were pelleted at 3 , 000 rpm and fixed in 2 . 5% glutataraldehyde and 2% paraformaldehyde in 0 . 1 M sodium cacodylate buffer pH 7 . 42 at RT for 15 min followed by 45 min at 4°C . After rinses , samples were fixed at RT in buffered 1% osmium tetroxide for 1 h followed by mordanting with 1% tannic acid and 1% sodium sulphate and then dehydrated in an ethanol and propylene oxide series , staining en bloc with 2% uranyl acetate at the 30% ethanol stage . Samples were embedded in TAAB Araldite 812 resin , ultrathin-sectioned at 60 nm on a Leica EMU6 ultramicrotome , contrasted with uranyl acetate and lead citrate and imaged on a 120 kV FEI Spirit Biotwin with a Tietz TemCam-F415 . Genetic crosses between different ko parasite strains was carried out as described [24] by infecting mice with different combinations of ko parasites . A . stephensi mosquitoes were infected by either direct feeding on mice or membrane feeding on ookinetes cultivated in vitro from parasites isolated from these mice and re-suspended in naïve mouse blood ( 800 ookinetes/µl blood ) . Δpbnek4 , Δpbcdpk4 , and Δpbmap2 parasites were provided by R . Tewari and O . Billker , and Δpsb47 and Δpbs48/45 were provided by C . J . Janse and A . P . Waters . The Plasmodium DNA microarray platform used in this study was manufactured by Agilent and encompassed 21 , 444 oligonucleotide probes for 5 , 361 P . berghei open reading frames [15] , [36] . 2 µg of total RNA of Pbc507 wt or Δpbmisfit ookinetes from three biological experiments were used as templates for the generation of Cy3 or Cy5 CTP ( Perkin and Elmer ) labeled cRNAs using the Agilent Low RNA Input Fluorescence Amplification Kit Protocol ( Protocol S1 ) . After hybridizations and washings , arrays were scanned using a Gene-Pix 4000B scanner and Gene-Pix Pro 4 . 0 software ( Axon instruments ) . Gene-Pix Pro 6 . 1 was utilized for grid-alignment , registering spot signal intensity , estimation of local backgrounds and manual inspection of spot quality . Data were subjected to normalization in GeneSpring 6 . 1 ( Agilent ) using the locally weighted linear regression method ( Lowess ) method and analyzed as described [56] using the Cluster software version 2 . 11 and Java Tree View software version 1 . 1 . 0 [57] , and Microsoft Excel . FH2-domain encoding sequences of orthologous MISFIT , Formin1 and Formin2 proteins were aligned separately . The three alignments were sequentially combined using the profile alignment feature implemented in ClustalW . The remaining sequences were individually added to the combined alignment . The phylogenetic tree was built using ClustalW's neighbor-joining algorithm , ignoring all gapped columns and performing 1000 bootstrap samples ( branch lengths indicate evolutionary distance ) . | The unicellular protozoan parasites that cause malaria must undergo sexual development and subsequent proliferation in mosquitoes before they can infect humans and cause malaria . We characterized the first protein with paternal effect on the development of malaria parasites in the mosquito . This protein , which we named MISFIT , is produced in the progenitor cells of male gametes and found in the nuclei of these cells as well as in the nuclei of zygotes and their invasive forms , termed ookinetes . Disruption of the gene that encodes MISFIT leads to ookinetes with reduced DNA content , a defective secretory machinery and altered expression of various regulators of DNA replication and cell division . These mutant parasites stop developing immediately after traversing the mosquito gut , leading to malaria transmission blockage . Our study offers a new perspective for understanding the sexual development of malaria parasites in the mosquito vector , which leads to transmission of one of the most devastating diseases of mankind . | [
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"biology/developm... | 2009 | Paternal Effect of the Nuclear Formin-like Protein MISFIT on Plasmodium Development in the Mosquito Vector |
Highly active antiretroviral therapy ( HAART ) can suppress HIV-1 replication and normalize the chronic immune activation associated with infection , but restoration of naïve CD4+ T cell populations is slow and usually incomplete for reasons that have yet to be determined . We tested the hypothesis that damage to the lymphoid tissue ( LT ) fibroblastic reticular cell ( FRC ) network contributes to naïve T cell loss in HIV-1 infection by restricting access to critical factors required for T cell survival . We show that collagen deposition and progressive loss of the FRC network in LTs prior to treatment restrict both access to and a major source of the survival factor interleukin-7 ( IL-7 ) . As a consequence , apoptosis within naïve T cell populations increases significantly , resulting in progressive depletion of both naïve CD4+ and CD8+ T cell populations . We further show that the extent of loss of the FRC network and collagen deposition predict the extent of restoration of the naïve T cell population after 6 month of HAART , and that restoration of FRC networks correlates with the stage of disease at which the therapy is initiated . Because restoration of the FRC network and reconstitution of naïve T cell populations are only optimal when therapy is initiated in the early/acute stage of infection , our findings strongly suggest that HAART should be initiated as soon as possible . Moreover , our findings also point to the potential use of adjunctive anti-fibrotic therapies to avert or moderate the pathological consequences of LT fibrosis , thereby improving immune reconstitution .
The hallmark of HIV-1 infection , depletion of CD4+ T cells , has been largely attributed to direct mechanisms of infection and cell death from viral replication or killing by virus-specific cytotoxic T-lymphocytes ( CTLs ) , and to indirect mechanisms such as increased apoptosis accompanying chronic immune activation associated with HIV-1 infections [1] . It is thus puzzling that if these were the sole mechanisms responsible for CD4+ T cell depletion , why 20% of HIV-1 infected patients have no significant increase in their peripheral blood CD4 count after initiation of HAART , since treatment can suppress viral replication to undetectable levels and normalize much of the chronic immune activation associated with infection [2]–[3] . Moreover , even among patients with significant increases in peripheral blood CD4+ T cells , few reconstitute to normal levels after years of HAART , and this incomplete immune reconstitution is associated with significantly higher rates of malignancy and other morbidities compared with HIV-uninfected individuals [4]–[11] . The preferential depletion of naïve T cells in blood and lymphoid tissues ( LT ) [3] , where they mainly reside , also poses particular difficulties for attributing depletion simply to direct mechanisms of viral infection or indirect mechanisms of activation-induced cell death ( AICD ) , since ( 1 ) naïve CD4+ T cells are resistant to HIV-1 infection and ( 2 ) AICD should primarily affect the activated effector and memory populations [12]–[14] . Furthermore , the similar extent of depletion of not only naïve CD4+ T cells but also naïve CD8+ T cells that are not usually infected by HIV [15]–[16] , suggests that there is a general mechanism impacting naïve T cell populations unrelated to direct infection . The incomplete restoration of naïve T cell populations with HAART also points to mechanisms in addition to AICD in depletion of CD4+ T cells , since suppression of this “drain” should enable repopulation of naïve CD4+ T cell populations by thymopoiesis and homeostatic proliferation of existing naïve T cells in secondary LT , but this does not happen many patients [17]–[20] . Cumulative observations therefore suggest that there may be additional mechanisms that impair the survival of naïve T cells , thereby restricting immune reconstitution [1] , [3] . To account for the preferential loss of naïve T cells , and failure of HAART to restore both naïve and memory populations by thymopoesis and homeostatic proliferation , we have proposed a damaged LT niche hypothesis in which collagen deposition disrupts the FRC network on which naïve T cells migrate and gain access to survival factors such as interleukin-7 ( IL-7 ) . This results in elevated levels of naïve T cell apoptosis [21]–[23] before treatment and impairs the reconstitution of naïve T cells after treatment . We recently showed in the SIV-rhesus macaque animal model that the critical disruption in LT architecture caused by collagen deposition and decreased access of T cells to survival factor IL-7 “posted” on the FRC network was in fact associated with increased apoptosis and depletion of both naïve CD4+ and CD8+ T cells . We also showed that this mechanism is a cooperative and cumulative vicious cycle in which the mutual interdependencies for survival of naïve T cells on IL-7 , and the FRC network on lymphotoxin-beta ( LT-β ) supplied by the T cells , perpetuate depletion of both T cells and the FRC network [24] . One implication of this model is that because the impact of LT fibrosis on CD4+ T cell depletion is progressive and cumulative , initiating HAART in the early stages of infection should improve immune reconstitution because there should be less collagen deposition and loss of the FRC network at this stage . We tested this hypothesis by examining LTs from HIV-1 infected individuals at baseline and 6 months after initiating HAART in the acute , pre-symptomatic and AIDS stages of infection . We first document the same damaged LT niche mechanism described in the SIV-rhesus macaque model of collagen deposition and loss of the FRC network with depletion of naïve T cells through increased apoptosis as a consequence of decreased access to IL-7 . We then show that the extent of loss of the FRC network and collagen deposition predict the extent of inhibition of naïve T cell apoptosis and restoration of the naïve T cell population in LT after 6 months of HAART , and total CD4 T cell counts in peripheral blood after 12 months of HAART . Furthermore , we find that the extent of restoration of FRC network after 6 months of HAART is highly dependent on the stage of disease at which the therapy is initiated , with greatest restoration only when HAART is initiated during the early stage of infection . This directly correlates with optimal inhibition of naïve T cell apoptosis and restoration of naïve T cells in the patients receiving HAART during the early stage of infection . This mechanism explains why initiation of HAART during the early stage of infection is associated with more rapid and complete CD4+ T cell restoration , and thus strongly argues for early initiation of HAART [25]–[26] . It also argues for a potential use of adjunctive therapies such as anti-fibrotic therapy to avert and/or revert the LT structure to improve immune reconstitution .
To evaluate this hypothesis , we first show that the FRC network is the major source of IL-7 for T cells in human LTs , as has been demonstrated in mice and monkeys [22] , [24] . In LT sections from uninfected individuals stained for IL-7 and desmin , a marker for FRCs , IL-7 largely co-localizes with the FRC network on which lymphocytes , antigen presenting cells and other cells within LTs migrate ( Figure 1A ) . This architecture allows T cells to efficiently access survival factors such as IL-7 and self-antigen-major histocompatibility complex as well as chemokines “posted” on their path . Thus , in the lymph node ( LN ) sections from HIV-1-uninfected individuals stained for type I collagen , desmin and T cells , the collagen within the FRC network co-localizes with desmin , and the T cells visibly contact the FRC network ( Figure 1B ) . In contrast , HIV-1 infection is associated with stage-specific progressive decreases in the FRC network ( Figure 1D-E ) and thus the available source of IL-7 ( Figure 1F ) . The depletion of FRCs correlates with a parallel increase in collagen deposited outside the FRC network , so that as infection progresses , fewer and fewer T cells are in contact with and have access to IL-7 on the FRC network ( Figure 1C ) compared with uninfected populations ( Figure 1B ) . Because survival of naïve T cells is dependent on access to IL-7 [21]–[23] , the collagen deposition-restricted access to and loss of the FRC network itself should result in an increase in apoptosis proportional to the extent of collagen deposition and decreased IL-7 source as infection progresses . We first demonstrate that contact with FRCs as a source of IL-7 is critical for T cell survival in an ex vivo culture system . We established monolayers of desmin+ IL-7+ FRC-like cells from stromal cells isolated from human tonsils ( Figure 2A–B ) , and show that IL-7 localizes to the surfaces of live cells stained without permeabilization ( Figure 2C ) . Only about 10% of naïve T cells underwent apoptosis if co-cultured with autologous IL-7+ FRC-like cells compared to about 30–40% of naïve T cells cultured for 2–3 days without stromal cells . We show that the enhanced survival is contact dependent and is mediated mainly via IL-7 , as antibody blocking of IL-7 or separation of T cells and the FRCs by transwells leads to increased apoptosis in naïve T cells ( Figure 2D–E ) . However , the blockade of IL-7 does not fully recapitulate the apoptosis level in the naïve T alone culture , suggesting that other survival factors such as CCL19 produced by FRCs may independently support the survival of naïve T cells [22] . These ex vivo co-culture results support the concept that naïve T cells need to contact FRCs in order to gain access to IL-7 to maintain their survival . Therefore , the loss of FRCs as well as the loss of the contact between naïve T cells and FRCs together in vivo would be expected to increase apoptosis and thereby deplete naïve T cells . We tested this hypothesis in LTs from HIV-1 infected patients and found that the stage-dependent increases in naïve T cell apoptosis ( Figure 3A ) were associated with depletion of both naïve CD4+ and CD8+ T cells ( Figure 3B–C ) , and that stage-dependent decreases in the FRC network ( Figure 1D ) were associated both with apoptosis and naïve T cell depletion ( Figure 3D–E ) . Because the LT damage-mediated naïve T cell depletion mechanism now documented in both HIV-1 infection and SIV infection [24] is cumulative and progressive , the later stage of infection , the greater the damage to LT structure . Thus , if treatment does not restore the LT structure that supports survival of naïve CD4+ T cells , the LT damage mediated naïve T cell depletion could adversely affect immune reconstitution , even with suppression of viral replication and immune activation by HAART . Conversely , the lesser extent of LT damage in early infection could improve immune reconstitution with HAART , if initiating treatment were to restore LT structure and improve naïve T cell survival . To test these predictions , we examined the effects of HAART initiated in the acute/early , pre-symptomatic and AIDS stages of infection on LT structure , naïve T cell apoptosis and restoration of naïve CD4+ T cell populations . Because loss of the FRC network and fibrosis are less in the acute/early stage than at later stages of HIV-1 infection ( Figure 1 ) , we would expect that the preservation of LT structure in acute/early HIV-1 infection would result in decreased apoptosis and greater increases in naïve T cells if HAART is initiated at this stage . We indeed found that the loss of the FRC network and collagen deposition prior to initiating HAART are associated with significantly increased naïve T cell apoptosis after 6 months of HAART ( p = 0 . 0016 and p = 0 . 0292 respectively ) ( Figure 4A–B ) . Furthermore , the level of naïve T cell apoptosis both before and after treatment is significantly associated with fewer naïve T cells in LTs ( p = 0 . 0012 ) . Taken together , these data suggest the extent of LT damage is associated with the extent of inhibition of naïve T cell apoptosis after HAART . We note that this now documents in LTs the previously reported predictive relationship between collagen in LTs and naïve CD4+ T cell increases in peripheral blood [27] . We also find that HAART initiated in the acute/early stage infection results in the greatest restoration of FRCs after 6 months of HAART , albeit not to the level in HIV-1 uninfected population ( Figure 5A–B ) . The restoration of LT structure is a slow process as even after 36 months of HAART the area occupied by the FRC network increases but still remains significantly less than in HIV-1 uninfected individuals . Minimal recovery of the FRC network is seen in HIV-1 infected patients starting HAART at chronic stages ( Figure 5A ) . At 6 months , there is no significant effect on removal of collagen deposition in LTs ( Figure 5A–B ) , but there is increased collagen co-localizing with the FRC network , as opposed to collagen deposits outside the network , albeit not to the same levels seen in HIV-1 uninfected individuals where 90 percent of collagen is within the FRC network ( Figure 5C-D ) . We further found that the new WHO guidelines for initiating HAART at CD4 counts of 350 cells/µl have a sound rationale in preservation of the FRC network , since only when therapy had been initiated at or above 350 cells/µl could we detect significant improvement of FRCs after 6-month HAART ( Figure S1 ) . HAART initiated in acute/early stage of infection is also associated with greatest decreases in apoptosis and optimal restoration of naïve T cell populations in LTs ( Figure 6 ) . In contrast , naïve T cell numbers in patients who initiated HAART in the AIDS stage of infection did not increase significantly , and apoptosis in naïve T cell populations remained high ( Figure 6 ) . These stage-related correlations apply as well to peripheral CD4+ T cell counts in patients receiving HAART for 12 months . The increase in peripheral CD4+ T cell counts to the level of counts in HIV-1 uninfected individuals depended on initiating HAART during the acute/early stage of infection ( Figure S2A ) . We also found that this stage-dependent restoration of peripheral CD4+ T cells can be predicted by the extent of fibrosis before initiation of HAART , again suggesting that fibrosis is one key factor that limits immune reconstitution after long-term HAART ( Figure S2B ) . We also assessed the relationships between viral load and the residual Ki67 level to the extent of restoration of naïve T cells when HAART was initiated at different stages . We found that increases in naïve T cells and decreases in apoptosis do not correlate with HAART-mediated suppression of viral replication and immune activation . HAART initiated at all stages of infection can potently and comparably inhibit viral replication and associated chronic immune activation ( Figure 7A and B ) . There is therefore no evidence that these processes are playing important roles in the stage-specific effects of time of initiation on apoptosis and recovery of naïve T cells within LTs . We in fact found no significant association between viral load and the number of naïve T cells or the number of apoptotic naïve T cells , nor any association between activation represented by the number of Ki67+ cells and the number of naïve T cells or the number of apoptotic naïve T cells after 6 month HAART ( Figure 7C–F ) .
It has generally been thought that viral and immune-cell mediated killing of CD4+ T cells and AICD accompanying chronic immune activation are respectively the major direct and indirect mechanisms of CD4+ depletion in HIV-1 infection , and that the slow and incomplete restoration of naïve CD4+ T cells is a consequence of the restricted capacity of the adult thymus to re-supply naive T cells [1] . Here we describe a novel mechanism that depletes CD4+ T cells , particularly naïve CD4+ T cells before HAART and determines the pace and extent of naïve CD4+ T cell restoration after HAART . Naïve T cells depend on IL-7 produced and presented by the FRC network for survival . Our IL-7 staining is consistent with a large literature on the FRC network as the site and source of most of the IL-7 [22] , [24] , [28]–[29] , although different from one report on human IL-7 staining in LTs [30] , probably due to different reagents and methodologies used . As HIV-1 infection advances , collagen deposition increases and the FRC network is destroyed , which decreases the amount of IL-7 available to support T cell survival . As a consequence , increased apoptosis depletes naïve T cells prior to HAART in proportion to the progressive destruction of LT structure from early to later stages of HIV-1 infection . Because of the progressive and cumulative nature of this pathological process , apoptosis of naïve T cells continues at elevated levels after HAART has been initiated , even though HAART can potently suppress viral replication and at least partially normalize immune activation . The elevated apoptosis level in naïve T cell populations is in proportion to pre-existing damage to LT structure , which is greater in the chronic stages of infection . Thus , predictably , early treatment results in better preservation and restoration of LT structure , which leads to improved survival of naïve T cells and greater increases in naïve T cell numbers . While the limited capacity of the thymus in the adult to supply naïve T cells will certainly limit the pace and extent of reconstitution , the LT structure to which thymic emigrants home thus also determines their subsequent survival . By analogy to earlier tap-and-drain models [31] , restoration of naïve T cells will be dependent not only on thymic output and from homeostatic proliferation of naïve T cell populations in LT , but also on the drain of overall apoptosis in this population . In such a model , the elevated level of apoptosis in naïve T cells in secondary LTs limits both the extent and pace of immune reconstitution . As the diversity of the naïve T cell repertoire is critical to defend against new infections and malignancies , the loss and slow restoration of the naïve T cell population creates “holes” in the T cell repertoire and therefore impairs host defenses even after HIV-1 replication has largely been suppressed [5] , [8]–[9] . Thus , therapeutic approaches to prevent or moderate damage to the LT niche and restore a functional FRC network could be particularly beneficial in increasing and preserving naïve T cell populations after HAART . The most straightforward way to do this is through earlier treatment . Our findings also suggest the potential clinical benefit of complementing IL-7 treatment during HIV-1 infection in the restoration of naïve T cell population . Indeed , studies have shown that complementing HAART with IL-7 during both SIV and HIV infection significantly increases the circulating naïve CD4+ T cell number [32]–[34] . Furthermore , it has been shown that IL-7 treatment could normalize the extent of apoptosis in CD4+ and CD8+ T cells from HIV-1-infected individuals via up-regulation of Bcl-2 levels [35]–[36] . These data consistently suggest that insufficient IL-7 is a key contributor in the impaired T cell homeostasis in SIV/HIV infection and limits the reconstitution of T cells . However , the immediate decline of the absolute numbers of both naïve CD4+ and CD8+ T cells after termination of IL-7 therapy [32]–[34] suggests that complementing IL-7 only provides transient survival benefit for naïve CD4 and CD8 T cells and strongly argues for the development of therapeutic interventions to provide long-term survival benefit for naïve T cells through preservation or restoration of the FRC network where naïve cells can access IL-7 . Our findings here clearly suggest that collagen deposition and the consequential loss of FRCs as the major source of IL-7 play critical roles in compromising homeostasis of naïve T cells . Therefore , the restoration of the lymphoid tissue niche could potentially provide long-term survival benefits for naïve T cells . Moreover , the development of adjunctive anti-fibrosis treatment such as pirfenidone and losartan [24] , [37]–[42] might additionally avert or revert the consequences of damage to the LT niche and improve immune reconstitution .
This human study was conducted according to the principles expressed in the Declaration of Helsinki . The study was approved by the Institutional Review Board of the University of Minnesota . All patients provided written informed consent for the collection of samples and subsequent analysis . Inguinal LN ( LN ) biopsies from HIV negative individuals and HIV-1-infected individuals at different clinical stages ( 7 at acute/early stage , 18 at presymptomatic stage and 8 at AIDS stage . Table 1 ) were obtained for this University of Minnesota Institutional Review Board-approved study . Viral load measurements were obtained the same day as biopsies . Each LN biopsy was immediately placed in fixative ( 4% neutral buffered paraformaldehyde or Streck's tissue fixative ) and paraffin embedded . All staining procedures were performed as previously described [24] , [43] using 5–30 µm tissue sections mounted on glass slides . Tissues were deparaffinized and rehydrated in deionized water . Heat-induced epitope retrieval was performed using a high-pressure cooker ( 125°C ) in either DIVA Decloaker or EDTA Decloaker ( Biocare Medical ) , followed by cooling to room temperature . Tissues for collagen type I staining required pre-treatment with 20 µg/ml proteinase K ( Roche Diagnostics ) in proteinase K buffer ( 0 . 2 M Tris , pH 7 . 4 , 20 mM CaCl2 ) for 15–20 min at room temperature . Tissue sections were then blocked with SNIPER Blocking Reagent ( Biocare Medical ) for 30 min at room temperature . Primary antibodies were diluted in TNB ( 0 . 1M Tris-HCl , pH 7 . 5; 0 . 15 M NaCl; 0 . 05% Tween 20 with Dupont blocking buffer ) and incubated overnight at 4°C . After the primary antibody incubation , sections were washed with phosphate buffered saline ( PBS ) and then incubated with fluorochrome-conjugated secondary antibodies in TNB for 2 hr at room temperature . Finally , sections were washed with PBS , nuclei were counterstained blue with DAPI , and mounted using Aqua Poly/Mount ( Polysciences Inc . ) . Immunofluorescent micrographs were taken using an Olympus BX61 Fluoview confocal microscope with the following objectives: x20 ( 0 . 75 NA ) , x40 ( 0 . 75 NA ) , and x60 ( 1 . 42 NA ) ; images were acquired and mean fluorescence intensities were analyzed using Olympus Fluoview software ( version 1 . 7a ) . Isotype-matched negative control antibodies in all instances yielded negative staining results ( see Table 2 , which lists the primary antibodies and antigen retrieval methodologies ) . Quantitative image analysis ( QIA ) was performed using 10–20 randomly acquired , high-powered images ( X200 or X400 magnification ) by either manually counting the cells in each image or by determining the percentage of LT area occupied by positive fluorescence signal using an automated action program in Adobe Photoshop CS with tools from Reindeer Graphics . The experimental protocols used here for human tissue samples had full IRB approval ( Institutional Review Board: Human Subjects Committee , Research Subjects' Protection Program , University of Minnesota ) and informed written consent was obtained from individual patients , or the legal guardians of minors , for the use of tissue in research applications prior to the initiation of surgery . Fresh human palatine tonsil tissues were obtained from routine tonsillectomies and processed within 1–2 h of completion of surgery . Viable tonsil lymphocyte suspensions were prepared by forcing cut tissue pieces through a metal sieve and collecting the released single cell suspension in complete RPMI medium ( 10% heat inactivated fetal calf serum , 1x l-glutamine , penicillin , and streptomycin solution; Invitrogen ) . The cells were washed and immediately cryopreserved . By culturing the stroma left on the metal sieve in complete RPMI medium , adherent proliferating fibroblasts were first visible after 2–5 days in culture , and confluent monolayers developed after 10–25 days . These primary stromal populations were readily released with trypsin , and the cells were further expanded and passaged using routine procedures for adherent cells . Some stromal cells were fixed in Streck's tissue fixative at one day prior to co-culture for analysis of intracellular desmin and IL-7 expression . For live stromal cells staining and imaging , stromal cells were directly incubated with antibody against IL-7 at 4°C without heat antigen retrieval and subject to secondary fluorochrome-conjugated-antibody staining . For co-culture of lymphocytes and stromal cells , 2×105 lymphocytes isolated from human tonsil were cultured in chamber slides without stromal cells , with autologous stromal cells ( 2×104cells/well ) , with stromal cells and IL-7 blocking antibody or with stromal cells but separated by transwells for 2 to 3 days . After co-culture , the slides were fixed in Streck's tissue fixative and stained for activated caspase3 , CD45RA and CD3 to quantify the number of apoptotic naïve T cells by QIA as described above . To test for differences in FRCs and collagen across all stages a 1-way ANOVA was used and post-hoc comparisons were made with Welch's modified 2 sample t-tests with a Bonferroni correction ( hence p-values are reported for differences between stages ) . A similar analysis was used to test for differences from the data that arose from the ex vivo culture system . To test for associations between FRCs and apoptotic naïve cell counts mixed models were used with FRCs as the explanatory variable in addition to clinical stage of infection ( since it is associated with both FRCs and apoptotic naïve cell counts ) . Random effects were included in these models since all of the data ( i . e . all time points ) were used to fit these models and random effects provide a simple way to incorporate correlation among measurements from the same subject into the model . Continuous variables were log transformed prior to fitting the model and restricted maximum likelihood was used to obtain parameter estimates . The same approach was used to test for an association between apoptotic naïve cell counts and naïve counts . A similar approach was used to test for an association between both Ki67 levels and viral load and apoptotic naïve cell counts and naïve counts except that FRCs and collagen were included in the model in addition to clinical stage of infection . To test if baseline FRCs or collagen are predictive of apoptotic naïve cell counts and naïve counts at 6 months post initiation of HAART , linear regression models were used that included the baseline value of the variable we were trying to predict at 6 months since such baseline values are potentially related to the value of the variable at 6 months and the baseline levels of FRCs or collagen . All continuous variables were first log transformed and standard model diagnostics were conducted . One sample t-tests were used to test for changes over the first 6 months of therapy for each stage . Spearman's rank correlation was used to test for associations that were potentially nonlinear ( but monotone ) . | The hallmark of HIV-1 infection is depletion of CD4 T cells , whose loss leads to the opportunistic infections and cancers characteristic of AIDS . Highly active antiretroviral therapy ( HAART ) can control HIV-1 replication , but reconstitution particularly of naïve T cells is often incomplete and slow . We show here that fibrosis damages lymphoid tissues ( LT ) , thereby contributing to depletion and incomplete reconstitution . Prior to treatment , chronic immune activation induces LT fibrosis to disrupt the fibroblastic reticular cell ( FRC ) network , the major source of the T cell survival factor interleukin 7 ( IL-7 ) . Fibrosis in this way interferes with the access of T cells to IL-7 “posted” on the FRC network . Without a source and access to IL-7 , naïve cells are depleted prior to initiating HAART because of increased apoptosis , and , even after initiating HAART , the losses continue by this mechanism because of pre-existing LT damage . Thus , LT fibrosis impairs immune reconstitution despite the beneficial effects of HAART in suppressing viral replication . Because less LT damage has accumulated in earlier stages of infection , early initiation of HAART also improves immune reconstitution . This LT damage mechanism also suggests that anti-fibrotic treatment in addition to HAART could further improve immune reconstitution . | [
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"microbiology"
] | 2012 | Lymphoid Tissue Damage in HIV-1 Infection Depletes Naïve T Cells and Limits T Cell Reconstitution after Antiretroviral Therapy |
Herpes simplex virus ( HSV ) enters cells by means of four essential glycoproteins - gD , gH/gL , gB , activated in a cascade fashion by gD binding to one of its receptors , nectin1 and HVEM . We report that the engineering in gH of a heterologous ligand – a single-chain antibody ( scFv ) to the cancer-specific HER2 receptor – expands the HSV tropism to cells which express HER2 as the sole receptor . The significance of this finding is twofold . It impacts on our understanding of HSV entry mechanism and the design of retargeted oncolytic-HSVs . Specifically , entry of the recombinant viruses carrying the scFv-HER2–gH chimera into HER2+ cells occurred in the absence of gD receptors , or upon deletion of key residues in gD that constitute the nectin1/HVEM binding sites . In essence , the scFv in gH substituted for gD-mediated activation and rendered a functional gD non-essential for entry via HER2 . The activation of the gH moiety in the chimera was carried out by the scFv in cis , not in trans as it occurs with wt-gD . With respect to the design of oncolytic-HSVs , previous retargeting strategies were based exclusively on insertion in gD of ligands to cancer-specific receptors . The current findings show that ( i ) gH accepts a heterologous ligand . The viruses retargeted via gH ( ii ) do not require the gD-dependent activation , and ( iii ) replicate and kill cells at high efficiency . Thus , gH represents an additional tool for the design of fully-virulent oncolytic-HSVs retargeted to cancer receptors and detargeted from gD receptors .
Entry of herpes simplex virus ( HSV ) into the cell is a multistep process that involves four virion glycoproteins ( gD , gH/gL , gB ) , all of which are required . gD is species-specific , and a major determinant of HSV tropism . gH/gL and gB constitute the conserved fusion apparatus across the Herpesviridae family; gB exhibits features typical of viral fusion glycoproteins [1–6] . Many steps in the HSV entry process remain to be elucidated and the overall model is partly speculative . Inasmuch as the process initiates with gD binding to one of its receptors , and culminates with gB-mediated virion-cell fusion , the commonly accepted model envisions that the four viral glycoproteins are activated in a cascade fashion by the receptor-bound gD through intermolecular signaling among the glycoproteins themselves [1] . Specifically , following virion attachment to cells , the interaction of gD with one of its alternative receptors—nectin1 , HVEM , and modified heparan sulphates [7–10]—results in conformational modifications to gD , in particular in the dislodgement of the ectodomain C-terminus , which carries the profusion domain [11–15] . Since this domain can interact with the heterodimer gH/gL [16 , 17] , most likely this step is a critical event in the activation cascade . Recently , we have shown that gH/gL interacts with two interchangeable receptors , αvβ6- and αvβ8-integrins , which promote HSV endocytosis , and most likely participate in the process of gH/gL activation [18] . Evidence for the activation cascade and for intermolecular signaling among the glycoproteins is indirect and rests on three sets of data: interactions among the four glycoproteins [17 , 19 , 20]; the ability of soluble gD to rescue the infection of gD-/- non-infectious virions and to promote fusion in a cell-cell fusion assay; the ability of soluble gD receptor to mediate virus entry into receptor-negative cells [15 , 21–23] . There is intense interest in HSV as an oncolytic agent ( o-HSV ) [24–27] . In the first and second generations o-HSVs , now in clinical trials , safety was obtained at the expense of virulence through single or multiple deletions . The most successful example is T-VEC , a HSV recombinant deleted in both copies of the γ134 . 5 gene and of ICP47 gene , and encoding the GM-CSF cytokine to boost the host immune response against the tumor [28] . In a phase III clinical trial , T-VEC improved the outcome of patients carrying metastatic melanoma [29] . A drawback of attenuation is that it strongly reduces the range of tumors against which the o-HSVs are effective . Thus , deletion of the γ134 . 5 genes restricts o-HSVs replication to cells defective in the PKR-dependent innate response . To overcome these limitations , non-attenuated o-HSVs retargeted to cancer-specific receptors and detargeted from the natural receptors were designed . They preserve the killing ability of wt-viruses [30 , 31] . So far , retargeting strategies entailed genetic modifications to gD , in particular the insertion of novel ligands , coupled with appropriate deletions for detargeting purposes [30 , 32–38] . The heterologous ligands included the IL13 cytokine , urokinase-type plasminogen activator or single chain antibodies ( scFvs ) . The retargeting through genetic modifications obtained in the above-mentioned studies has clear advantages over retargeting through coupling of appropriate moieties to virions , and even more so over non-replicating viruses ( see , for example [39] ) . In the former case virions maintain the retargeted phenotype generation after generation , even during replication in the tumor . In the latter case , targeting occurs only for a single generation , and viruses are usually non-detargeted , hence they also infect non cancer cells . Furthermore , non-replicating virions fail to propagate the therapeutic effect beyond the initially infected tumor cells . The cancer-specific receptor selected in our laboratory is HER2 ( human epidermal growth factor receptor 2 ) , a member of the EGFR ( epidermal growth factor receptor ) family , overexpressed in breast , ovary , gastric carcinomas , glioblastomas , etc [40] . Two fully retargeted o-HSVs were generated . They differ in the portions of gD that were deleted for detargeting purposes . R-LM113 carries the deletion of the AA 6–38 N-terminal region [32 , 33] . R-LM249 carries the deletion of the 61–218 core region [34] . In both viruses , the deleted sequences were replaced with the scFv to HER2 derived from trastuzumab , a humanized MAb now in clinical practice . The scFv binds HER2 at high affinity ( 29 . 3 nM ) [41] . In preclinical studies R-LM113 and R-LM249 exerted therapeutic effects against human breast and ovary cancers , and against a murine model of HER2+ glioblastoma [32–35 , 42] . Intraperitoneally-administered R-LM249 exerted therapeutic effect against metastases of ovary and breast cancers diffuse to the peritoneum , or to the brain [35] . Here , we engineered a heterologous ligand in gH . The aims were twofold , i . e . to better elucidate the respective roles of gD and gH/gL in HSV entry , and define whether gD is an absolute requirement for HSV entry , and to explore novel avenues in the design of retargeted o-HSVs . We report that the engineering in gH of a scFv to HER2 confers to the recombinant viruses the ability to use HER2 as the sole receptor , in the absence of gD receptors , or upon deletion of residues that form the nectin1/HVEM binding sites in gD .
R-VG803 carries the insertion of the scFv to HER2 ( herein named scFv-HER2 ) at the N-terminus of gH , the mCherry red fluorescent marker in the UL37–UL38 intergenic region , and the LoxP-bracketed BAC sequences between UL3 and UL4 ( schematic representation in Fig 1A ) . R-VG809 carries the deletion of the AA 6–38 portion in gD , and is otherwise identical to R-VG803 . The recombinant viruses were generated by transfection of the recombinant BAC-genomes into SK-OV-3 cells , a HER2+ cell line derived from human ovary carcinoma , and resistant to trastuzumab [35] . The presence of the scFv—gH chimera in R-VG803 and R-VG809 was verified by sequencing of the entire ORF , and by immunoblot of Vero cells infected with R-VG803 , R-VG809 , or R-LM5 [43] . The latter is essentially a wt-virus with genetic modifications similar to those of R-VG803 and R-GV809 , i . e . it carries wt-gD , the LoxP-bracketed BAC sequences , and EGFP ( Enhanced green fluorescence protein ) instead of mCherry . The annotated scFv-gH sequence is reported in S1 Fig . For immunoblotting , infected cell lysates were subjected to SDS-PAGE ( sodium dodecyl sulphate polyacrylamide gel electrophoresis ) , and the blots were immunoreacted to polyclonal antibody ( PAb ) to gH [44] . The chimeric scFv—gH migrated with a slower electrophoretic mobility than wt-gH from R-LM5 , and an apparent Mr of 130 K ( Fig 1B ) . Initially , we engineered R-VG803 . To test whether it can use HER2 as an entry receptor , we made use of J-HER2 cells . The parental J cells express no receptor for gD , hence cannot activate gD , and are not infected by wt-HSV [7] . J-HER2 cells transgenically express HER2 as the sole receptor [43] . As controls , we included J-nectin and J-HVEM cells , which transgenically express nectin1 or HVEM as receptors and are infected by wt-HSV [7] , and a panel of human and animal cells , which express the human or animal nectin1/HVEM . The panel included CHO , BHK , keratinocytic HaCaT , human fibroblastic HFF14 , epithelial HeLa , the neuronal SK-N-SH cells , and the HER2-positive SK-OV-3 cancer cells . As shown in Fig 2A , R-VG803 infected J-HER2 cells . The infection of J-nectin1 , J-HVEM , and of the animal and human cells ( Fig 2A ) was not surprising , given that R-VG803 encodes a wt-gD . Furthermore , R-VG803 could perform cell-to-cell spread in J-HER2 cells . Cells were infected at 0 . 01 PFU/cell , overlaid with medium containing MAb 52S ( ascites fluid 1:10 , 000 ) . At day 1 infection involved single cells . In the following day infection involved clusters of cells ( Fig 2B ) . We confirmed that R-VG803 infection occurs through the HER2 receptor , by blocking the infection with trastuzumab , in fluorescence microscopy ( Fig 2C ) , and flow cytometry ( Fig 2D ) assays . The results validate the inference that R-VG803 uses HER2 as the portal of entry in J-HER2 cells . This finding supports two fundamental conclusions . First , infection with a gH-retargeted HSV can take place in the absence of a gD receptor . Under these conditions , gD is physically present but functionally ablated as receptor-binding glycoprotein , as it can not be activated by its cognate receptor ( s ) and can not transmit the activation to gH . Second , the tropism of HSV can be modified by engineering a heterologous ligand in gH . We analysed the receptor usage in cells that express both sets of receptors , HER2 and nectin1/HVEM , exemplified by SK-OV-3 cells . The question was whether one receptor was preferentially used over the other , or each one was used alternatively . In the latter case , we expected that a block in the access to one of the two sets of receptors—e . g . HER2—should result in low extent of inhibition , whereas the simultaneous block to both sets of receptors should result in strong inhibition . The latter was indeed the case . As controls , we included the two retargeted viruses R-LM113 and R-LM249 , and wt R-LM5 . R-LM113 is detargeted from natural gD receptors [33 , 43] , even though the AA 6–38 deletion in gD removes only some residues implicated in the nectin1-binding site , in addition to the entire HVEM binding site . The nectin1 binding site is widespread in the molecule , and includes the Ig-folded core and portions located between AA 35–38 , 199–201 , 214–217 , 219–221 [12 , 13 , 34] . SK-OV-3 cells were infected with the indicated viruses , in the presence of trastuzumab , MAb HD1 to gD , or both . Fig 3A shows that trastuzumab or HD1 exerted almost no inhibition on R-VG803 when given singly , but practically abolished infection when given together . In contrast , R-LM113 and R-LM249 were inhibited by trastuzumab alone . Thus , R-VG803 can use alternatively HER2 or nectin1/HVEM to infect SK-OV-3 cells . Usage of one or the other portals of entry by R-VG803 depends on the spectrum of receptors displayed by the cells . To characterize further the scFv—gH chimera we asked whether infection can be blocked by the neutralizing MAb 52S to gH . This MAb recognizes a continuous epitope , independent of gL , with critical residues at S536 and A537 [45 , 46] . R-VG803 infection of both SK-OV-3 and J-HER2 cells was abolished by MAb 52S ( ascites fluid 1:25 ) ( Fig 3B and 3C ) , indicating that a key functional domain in wt-gH was preserved in the chimera . Inasmuch as R-VG803 infects J-HER2 cells independently of gD receptors and of neutralizing MAb to gD , we reasoned that it might be possible to engineer a recombinant carrying the scFv-HER2 in gH and the deletion of receptors’ binding sites from gD . We deleted the AA 6–38 region . R-VG809 failed to infect not only J-HVEM cells , but also J-nectin cells , and did not infect or infected very little the panel of animal and human cell lines employed above . It infected efficiently J-HER2 , CHO-HER2 and SK-OV-3 cells ( Fig 4A ) . In summary , R-VG809 exhibited a redirected tropism , strikingly different from that of R-VG803 ( compare Fig 4A with Fig 2A ) . R-VG809 was also capable of cell-to-cell spread in J-HER2 cells ( Fig 4B ) . Further validation that R-VG809 uses HER2 as portal of entry was provided by inhibition with trastuzumab ( Fig 4C and 4D ) . Analysis of the inhibitory effect of trastuzumab and MAb HD1 in SK-OV-3 cells shows that R-VG809 infection was inhibited by trastuzumab , even in the absence of MAb HD1 ( Fig 3A ) , confirming that HER2 is the only portal for R-VG809 . Infection of R-VG809 was blocked by MAb 52S , in agreement with the fact that R-VG809 and R-VG803 carry the same gH chimera ( Fig 3B and 3C ) . We conclude that R-VG809 infection via the HER2-retargeted gH does not require the receptors’ binding sites in gD , and the receptor-mediated gD activation . Inasmuch R-VG809 does not carry the deletion of the entire gD open reading frame , we cannot formally rule out that gD serves a hypothetical , additional , so-to-say structural function , i . e . it facilitates the formation and/or stabilization of complexes among the glycoproteins . We characterized the detargeting effect exerted by the AA 6–38 deletion in gD . The retargeted phenotype exhibited by R-LM113 may result from the deletion per se or from the combined deletion-insertion . For example , the scFv insert , which is ~ 270 AA long , is likely to induce distortions in gD N-terminus , such that it can not any longer interact with the core of the molecule . Moreover , the insert may mask part of the nectin1 binding site in gD . To discriminate among these possibilities we measured R-VG809 replication in J-nectin1 and Vero cells . We included R-VG803 and R-LM5 for comparison . Fig 5A and 5B shows that R-VG809 , but not R-VG803 and R-LM5 , failed to replicate in J-nectin and Vero cells . Also the cytolytic effect of R-VG809 was strikingly different from those of R-VG803 and R-LM5 , in that R-VG809 failed to kill J-nectin cells ( Fig 5C ) . Parenthetically , the increase in cells viability exhibited by R-VG809 and R-LM5 between day 1 and 4 may be consequent to fact that some cells were not infected at day 0 , and they replicated in the time interval of the assay . We conclude that the of AA 6–38 deletion in gD suffices to achieve full detargeting from both HVEM and nectin1 , even in the absence of any insert . Replication efficiency and cell killing are key properties for any candidate o-HSV . We verified the replication efficiency of R-VG803 and R-VG809 in J-HER2 cells , in comparison to that of R-LM113 , R-LM249 and R-LM5 . Fig 6A shows that the yields of R-VG803 and R-LM113 in cells infected at 0 . 1 PFU/cell were practically undistinguishable , implying that the extent of replication in J-HER2 cells is independent of whether the retargeting is achieved through gH or gD . Fig 6B compares the yields of R-VG803 , R-VG809 and R-LM5 in J-HER2 cells infected at 0 . 01 PFU/cell . R-VG809 was somewhat hampered relative to R-VG803 . R-VG809 was capable of cell-to-cell spread in J-HER2 cells; the decrease relative to R-VG803 likely reflected the lower extent of replication than the spread per se ( Fig 6C ) . Of interest was the growth in SK-OV-3 cells , as these are cancer cells , resistant to trastuzumab [35] . R-VG803 and R-VG809 replicated equally well , could not be differentiated from the wt R-LM5 , and replicated somewhat better than R-LM113 and R-LM249 ( Fig 6D ) . Lastly , we analyzed the ability of R-VG803 , R-VG809 to kill the SK-OV-3 tumor cells , in comparison to R-LM113 , R-LM249 and R-LM5 . Cytotoxicity caused by R-VG803 , R-VG809 , R-LM113 and R-LM249 were very similar one to the other , and much higher than that of R-LM5 ( Fig 7 ) .
The engineering of a novel ligand—a single chain antibody ( scFv ) directed to HER2—in gH conferred to HSV an expanded tropism for cells which express HER2 as the sole receptor . Virus entry mediated by the chimeric scFv-HER2–gH could occur in the absence of gD receptors , despite deletion of the receptor-binding sites in gD , or presence of gD-neutralizing MAbs . Basically , the key functions of gD are no longer essential , and can be replaced by a ligand in gH . This finding impacts on current view of how HSV enters cells , and on the strategies for retargeting the HSV tropism to receptors of choice . When wt-HSV enters target cells , gD serves two major functions . It serves as major receptor binding glycoprotein , and determinant of the viral tropism , i . e . it dictates which cells HSV will or will not infect . Secondly , the encounter of HSV with a cell carrying a gD receptor is signaled to gH/gL and gB , to trigger fusion . In essence , the receptor-bound gD initiates the cascade of activation of the entry glycoproteins [1–3 , 47 , 48] The control exerted by gD on virion-cell fusion ensures that the activation of the viral fusion machinery occurs only when HSV has reached a receptor-positive cell . In contrast to wt-virus , when the gH-retargeted viruses infect J-HER2 cells the activation of the chimeric scFv—gH does not require gD activation by its receptor , or receptor-binding sites in gD . gD is functionally ablated as receptor-binding glycoprotein and as activator of the downstream glycoproteins . gD is no longer a requirement to trigger fusion . Its functions have been taken over by the scFv in gH . In wt virus , the activation exerted by the receptor-bound gD on gH/gL necessarily occurs through intermolecular signaling . We refer to it as trans-signaling , as opposed to a signaling that occurs intramolecularly , herein referred to as cis-signaling . A novelty of our results is that the activation of gH can occur in cis , i . e . the scFv activates the gH moiety in the chimera . In the past , Klupp and Mettenleiter generated a non-viable PrV recombinant , carrying a deletion in gL [49] . Upon serial blind passages , a viable recombinant carrying a gD-gH fusion was isolated [50] . Subsequently , Cairns et al . constructed a similar HSV gD-gH chimera , in which the entire ectodomain of gD was fused to the N-terminus of gH ( named chimera 22 in their work ) [51] . In complementation assays , the HSV chimera rescued the infection of a gD-/- gH+ virus , or of a gH-/- gD+ virus . It was not tested for complementation of a double deletion gD-/- gH-/- virus . There are two key differences between the previous report [51] and our finding . First , in the complementation assays , the wt-gD in the gH-/- gD+ virus had the possibility to activate in trans the gH moiety in the gD-gH chimera . Conversely , the gD moiety in the chimera had the possibility to activate in trans the wt-gH present in the gD-/- gH+ virions . In either case , the activation may have taken place in-trans , as concluded by the Authors . Formal evidence for cis-activation of the gD-gH chimera was not provided [51] . Secondly , irrespective of the activation mechanism , in the complementing system the gH activation was mediated by gD , which has a binding site on gH [14–16 , 52] , and not by a heterologous ligand . The latter was indeed an unexpected possibility . Previous attempts to develop systems for HSV-mediated cell fusion , or HSV infection independent of gD led to partial indications as follows . In the cell-cell fusion assay , a partial deletion in the N-terminus of gH was reported to induce low , constitutive levels of fusion by gB , in the absence of gD or gD receptors [48] . Whether , once present in the virion , the same deletion will lead to a constitutive , low level gD-independent entry , or will lead to an exhausted fusion/entry machinery has not been ascertained . Uchida and collaborators reported on mutations in virion gB , or virion gH , that render these glycoproteins independent of gD activation by its major receptor nectin1 , but are still dependent on the activation by so-called unconventional gD receptors ( e . g . nectin3 present in J cells [14] ) , or receptors to a retargeted gD ( e . g . EGFR for a EGFR-retargeted gD ) . The ability of the mutant forms of gB or gH to carry out entry independently of any form of gD activation , or with a form of gD deleted in receptor-binding sites was not established [53] . Hence , previous studies are strikingly different from current study , where the receptor-binding activity of gD for nectin1/HVEM was ablated by deletion of key residues , and a heterologous receptor-binding activity was implanted in gH . As regards the field of oncolytic HSVs , our data show that gH accepted the insertion of a hetelogous ligand and became a tool for the retargeting of HSV tropism to a heterologous receptor . The ligand may be at least 270 AA in size , i . e . about 1/3 of gH ectodomain . The gH-mediated retargeting could be combined with detargeting , through a suitable deletion in gD . This ensued in the fully retargeted R-VG809 , whose replication and killing capacity for SK-OV-3 cells did not substantially differ , or were even better than those of the gD-retargeted R-LM113 and R-LM249 . In essence , changes in tropism through modifications in gH or in gD yield o-HSVs with substantially similar growth and lytic properties . Remarkably , both the gH- and the gD-retargeted o-HSVs grew almost as efficiently as the wt R-LM5 . They represent an improvement over the first generation retargeted o-HSVs , which were marred by a relatively low replication capacity [30 , 54] . We highlight that so far , gD was the only glycoprotein that successfully enabled the retargeting of HSV [30 , 33–38 , 54] . Earlier efforts to use glycoproteins other than gD , e . g . gC , did not meet with success [55] . Current findings expand the toolkit for generation of non attenuated retargeted o-HSVs . Two prospective applications are worth noting . The anti-HER2 huMAbs and small molecule inhibitors of HER2 signaling now in clinical trials have non-overlapping mechanisms of action , and patients clearly benefit from combinations [56 , 57] . However , a fraction of patients does not respond . The responders develop resistance , often within a year of treatment [58] . In the resistant cancer cells , the HER2 ectodomain is preserved , and the modifications affect the signaling portions of the receptor . This type of resistance is recapitulated in SK-OV-3 cells , which are HER2+ and trastuzumab-resistant [35] . The observation that R-VG809 , as well as R-LM249 [34 , 35] , can grow and kill SK-OV-3 cells raises the possibility that treatment with HER2-retargeted o-HSVs could be applied to patients who developed resistance to the anti-HER2 specific therapeutics . Secondly , the heterogeneity in cancers cells represents a limit to numerous therapeutic approaches . Heterogeneity is observed also in the extent of expression of cancer receptors . The possibility to retarget o-HSV tropism to cancer receptors via gH and via gD opens the way to the design of double-retargeted o-HSVs , which may be better suited to counteract cancer cell heterogeneity than singly-retargeted o-HSVs .
The receptor negative J cells , their counterparts expressing HER2 , nectin1 , HVEM and CHO-HER2 were described [7 , 43] . HFF14 cells were received by Dr . Frank Neipel ( University of Erlangen ) . Vero , RS , SK-OV-3 , HaCaT , BHK , HeLa and SK-N-SH cells were received by ATCC . The wt- HSV-1 ( F ) , R-LM113 , R-LM249 and R-LM5 were described [33 , 34 , 43 , 59] . First , we engineered R-VG801 , by insertion of the sequence encoding the trastuzumab scFv between AA 23 and 24 of gH . Subsequently we engineered R-VG803 by insertion of mCherry sequences into the UL37-UL38 intergenic region of R-VG801 . To generate R-VG801 , the starting viral genome was pYEBac102 , which carries LOX-P-bracketed p-BeloBAC sequences inserted between UL3 and UL4 of HSV-1 genome [60] . All engineering procedures were performed by means of galK recombineering [61] . Briefly , the GalK cassette , with homology arms to gH was amplified by means of primers gH6_galK_f ATGCGGTCCATGCCCAGGCCATCCAAAAACCATGGGTCTGTCTGCTCAGTCCTGTTGACAATTAATCATCGGCA and gH5_galK_r TCGTGGGGGTTATTATTTTGGGCGTTGCGTGGGGTCAGGTCCACGACTGGTCAGCACTGTCCTGCTCCTT . This cassette was electroporated in SW102 bacteria carrying pYEBac102 . The recombinant clones carrying the galK cassette were selected on M63 plates ( 15 mM ( NH4 ) 2SO4 , 100 mM KH2PO4 , 1 . 8 μg FeSO4·7H2O , adjusted to pH 7 ) supplemented with 1 mg/L D-biotin , 0 . 2% galactose , 45 mg/L L-leucine , 1 mM MgSO4·7H2O and 12 μg/ml chloramphenicol . To exclude galK false positive colonies , the recombinant clones were plated on McConkey agar base plates , supplemented with 1% galactose and 12 μg/ml chloramphenicol , and checked by colony PCR with primer galK_129_f ACAATCTCTGTTTGCCAACGCATTTGG and galK_417_r CATTGCCGCTGATCACCATGTCCACGC . Next , the trastuzumab scFv cassette , bracketed by Ser-Gly linkers and by upstream and downstream homology arms to gH , was amplified using pSG-ScFvHER2-SG ( a gift from Alfredo Nicosia ) as template . pSG-ScFvHER2-SG was obtained by inserting the synthetic antiHER2 scFv cassette , designed on the basis of published information [62]; Sequence 18 from Patent WO2004065416 ( Genbank CQ877234 ) ; Sequence 7 ( pS2072a ) from Patent WO2005100399 ( Genbank CS276173 ) into an appropriate vector . The scFv cassette was bracketed by the Ser-Gly linkers detailed below . Relative to sequence 18 from Patent WO2004065416 , nucleotides 769–771 were mutated in pSG-ScFvHER2-SG to generate a XhoI restriction site . Using pSG-ScFvHER2-SG as template , two separate fragments ( # 1 and # 2 ) were PCR-amplified by means of oligonucleotides which contained homology arms to gH . Specifically , fragment # 1 was amplified by means of primers gH23_8SG_scFv4D5_f TCGTGGGGGTTATTATTTTGGGCGTTGCGTGGGGTCAGG TCCACGACTGGCATAGTAGTGGCGGTGGCTCTGGATCCG and scFv4D5_358_r GGAAACGGTTCGGATCAGCCATCGG , using pSG-ScFvHER2-SG as template . Fragment # 2 was amplified by means of gH24_12SG_scFv4D5r ATGCGGTCCATGCCCAGGCCATCCAAAAACCATGGGTCTGTCTGCTCAGTACCG GATCCACCGGAACCAGAGCC and scFv4D5_315_f GGAGATCAAATCGGATATGCCGATGG using pSG-ScFvHER2-SG as template . Thereafter , fragments # 1 and # 2 were annealed and extended to generate the entire scFv-HER2 cassette , bracketed by the Ser-Gly linkers and the homology arms to gH . The sequence of the upstream and downstream Ser-Gly linkers were HSSGGGSG , and SSGGGSGSGGSG , respectively . The linker between VL and VH had the sequence SDMPMADPNRFRGKNLVFHS . The recombinant bacterial clones carried the scFv-HER2 cassette in place of the galK cassette . They were selected on M63 plates , supplemented with 1 mg/L D-biotin , 0 . 2% deoxy-2-galactose , 0 . 2% glycerol , 45 mg/L L-leucine , 1 mM MgSO4·7H2O and 12 μg/ml chloramphenicol . Bacterial colonies were checked for the presence of inserted sequence by colony PCR . The mCherry red fluorescent protein , under the CMV promoter , was inserted in the UL37-UL38 intergenic region of R-VG801 ( coordinates 84156–84157 ) , to generate R-VG803 , following the two step procedure outlined above . Briefly , we first inserted the galK cassette , amplified by means of oligonucleotides UL37/38_galK_f CCGCAGGCGTTGCGAGTACCCCGCGTCTTCGCGGGGTGTTATACGGCCACCCTGTTGACAATTAATCATCGGCA and UL37/38_galK_r TCCGGACAATCCCCCGGGCCTGGGTCCGCGAACGGGATGCCGGGACTTAATCAGCACTGTCCTGCTCCTT . Subsequently , the galK sequence was replaced with the promoter-mCherry cassette , amplified by means of oligonucleotides UL37/38_CMV_mcherry_f CCGCAGGCGTTGCGAGTACCCCGCGTCTTCGCGGGGTGTTATACGGCCACCGATGTACGGGCCAGATATACG and UL37/38_pA_mcherry_1958_r TCCGGACAATCCCCCGGGCCTGGGTCCGCGAACGGGATGCCGGGACTTAACCATAGAGCCCACCGCATCC . The starting material for R-VG809 was the R-VG803 BAC genome . To generate the AA 6–38 deletion in gD , a galK cassette flanked by homology arms to gD was amplified by means of primers gD5_galK_f TTGTCGTCATAGTGGGCCTCCATGGGGTCCGCGGCAAATATGCCTTGGCGCCTGTTGACAATTAATCATCGGCA and gD39_galK_r ATCGGGAGGCTGGGGGGCTGGAACGGGTCCGGTAGGCCCGCCTGGATGTGTCAGCACTGTCCTGCTCCTT . Next , we replaced the galK sequence with a synthetic double stranded oligonucleotide gD_aa5_39_f_r TTGTCGTCATAGTGGGCCTCCATGGGGTCCGCGGCAAATATGCCTTGGCGCACATCCAGGCGGGCCTACCGGACCCGTTCCAGCCCCCCAGCCTCCCGAT . In all cases , the recombinant viruses were generated by transfection of SK-OV-3 cells with the appropriate recombinant BAC DNA ( 500 ng ) by means of Lipofectamine 2000 ( Life Technologies ) . Virus growth was monitored by red fluorescence . The structure of the viral recombinants was verified by sequencing the gH and mCherry ORFs , and gD ORF for R-VG809 . Virus stocks were generated and titrated in SK-OV-3 cells , or in J-HER2 cells , as specified . Lysates of Vero cells infected with R-VG803 , R-VG809 or R-LM5 ( 3 PFU/cell ) were subjected to PAGE , transferred to PVDF membranes . Immunoblot reactivity to polyclonal antibody ( PAb ) to gH was assayed as detailed [44] . The indicated cells were infected with R-VG803 , or R-VG809 at 2 and 20 PFU/cell , respectively . Red fluorescence was monitored by fluorescence microscopy . Replicate monolayers of J-HER2 or SK-OV-3 cells in 12 well plates were preincubated with trastuzumab or non-immune mouse IgG ( 28 μg/ml , final concentration ) for 1 h , and then infected with R-VG803 , R-VG809 , R-LM113 , R-LM249 or R-LM5 ( 0 . 3 or 2 PFU/cell for J-HER2 or SK-OV-3 cells , respectively ) , in the same medium . Alternatively , virions were preincubated with MAbs HD1 ( 1 . 5 μg/ml , final concentration ) , or MAb 52 S ( ascites fluid 1:25 ) for 1 h at 37°C , and then allowed to absorb to cells for 90 min , in the absence or presence of trastuzumab , as indicated . Viral inocula were then removed , and cells were overlaid with medium containing the indicated antibodies . Virus replication was monitored at 24 h after infection by BD Accuri C6 flow cytometer . Results are expressed ad the mean of three independent experiments ± SD . To determine R-VG803 and R-VG809 growth in J-HER2 , SK-OV-3 , J-nectin , and Vero cells , the cells were infected with R-VG803 , R-LM113 , R-LM249 , R-LM5 at the indicated MOI . Unabsorbed virus was inactivated by rinsing cells with pH 3 solution ( 40 mM citric acid , 10 mM KCl , 135 mM NaCl ) . Cells were harvested at 3 ( 0 time ) , 24 and 48 h after infection and progeny virus ( intracellular plus extracellular ) was titrated in J-HER2 or SK-OV-3 cells , as indicated . SK-OV-3 and J-nectin cells were seeded in 96 well plates at 8x103 cell/well , and infected with R-VG803 , R-VG809 , R-LM113 , R-LM249 and R-LM5 ( 2 PFU/cell ) or mock-infected . AlamarBlue ( 10 μl/well , Life Technologies ) was added to the culture media at indicated times after infection and incubated for 4 h at 37°C . Plates were read at 560 and 600 nm with GloMax Discover System ( Promega ) . For each time point , cell viability was expressed as the percentage of AlamarBlue reduction in infected versus uninfected cells , excluding for each set of samples the contribution of medium alone . Each point represents the average of at least triplicate samples ± SD . HSV-1 strain F , Genbank GU73477 . gH coordinates 43783–46299 HSV-1 strain F , gD: Genbank L09242 scFv to HER2 Genbank CQ877234 , CS276173 mCherry Genbank HM771696 | To enter cells , all herpesviruses use the core fusion glycoproteins gH/gL and gB , in addition to species-specific glycoproteins responsible for specific tropism , etc . In HSV , the additional glycoprotein is the essential gD . We engineered in gH a heterologous ligand to the HER2 cancer receptor . The recombinant viruses entered cells through HER2 , independently of gD activation by its receptors , or despite deletion of key residues that are part of the receptors’ binding sites in gD . The ligand activated gH in cis . Cumulatively , the receptor-binding and activating functions of gD were no longer essential and were replaced by the heterologous ligand in gH . Relevance to translational medicine rests in the fact that gH can serve as a tool to retarget HSV tropism to cancer-specific receptors . This expands the toolkit for the design of fully-virulent oncolytic-HSVs . | [
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] | [] | 2015 | The Engineering of a Novel Ligand in gH Confers to HSV an Expanded Tropism Independent of gD Activation by Its Receptors |
Lafora disease is the most common teenage-onset neurodegenerative disease , the main teenage-onset form of progressive myoclonus epilepsy ( PME ) , and one of the severest epilepsies . Pathologically , a starch-like compound , polyglucosan , accumulates in neuronal cell bodies and overtakes neuronal small processes , mainly dendrites . Polyglucosan formation is catalyzed by glycogen synthase , which is activated through dephosphorylation by glycogen-associated protein phosphatase-1 ( PP1 ) . Here we remove PTG , one of the proteins that target PP1 to glycogen , from mice with Lafora disease . This results in near-complete disappearance of polyglucosans and in resolution of neurodegeneration and myoclonic epilepsy . This work discloses an entryway to treating this fatal epilepsy and potentially other glycogen storage diseases .
Lafora disease ( LD ) is caused by recessively inherited mutations in the EPM2A or EPM2B genes , encoding laforin ( a carbohydrate binding phosphatase ) and malin ( an E3 ubiquitin ligase ) [1] , [2] . The disease begins around age 15 with myoclonus ( jerk-like seizures ) and generalized convulsive seizures , which initially respond to medications . Over the next five years seizures become intractable and the myoclonus near-constant , and epileptic hallucinations with highly frightening content appear . Extremely frequent myoclonic seizures ( repetitive jerks ) and epileptic absence attacks permeate consciousness and prevent formulation of complete thoughts . Dementia and a vegetative state in constant myoclonus follow . Death occurs around age 25 in status epilepticus . Pathology consists of the progressive formation of polyglucosans , which are insoluble glucose polysaccharides that precipitate and aggregate into concretized masses called Lafora bodies ( LB ) , and in neurodegeneration . LB form in neuronal perikarya ( i . e . in the cell body near the nucleus ) and in neuronal short processes ( mostly dendrites ) . LB in the neuronal processes are much smaller but they massively outnumber LB in the perikarya . Extraneurally , LB also form in heart , liver , and skeletal muscle , but cause no symptoms in these organs [3]–[6] . A normal glycogen molecule contains up to 55 , 000 glucose units , yet remains soluble because its glucose chains are short ( 13 units ) , each chain is a branch of another , and the whole molecule is a sphere , the surface of which is composed of the hydrophilic ends of chains [7] . This unique organization allows mammalian cells to store large amounts of carbohydrate energy in a soluble rapidly accessible form . Without branching , glucose polymers 13 units or longer are poorly soluble and tend to precipitate and crystallize [8] . Polyglucosans are malformed glycogen molecules . They have very long chains , insufficient branches , and a resultant lack of spherical organization . They are more similar to plant amylopectin or starch than to glycogen , and like these plant carbohydrates they are insoluble , precipitate , and accumulate [3] , [5] , [9] . Glycogen is synthesized through coordinated actions of glycogen synthase ( GS ) and glycogen branching enzyme , the former responsible for chain elongation , the latter for chain branching . Glycogen is digested by glycogen phosphorylase ( GP ) and glycogen debranching enzyme . PTG ( protein targeting to glycogen ) is an indirect activator of GS and an indirect inhibitor of both GP and glycogen phosphorylase kinase ( GPK ) , the enzyme that activates GP . PTG performs this reciprocal activation of synthesis and inhibition of breakdown by binding the pleiotropic phosphatase PP1 through its C-terminus , binding glycogen , and through a common region in its N-terminus ( amino acid sequence WDNNE ) binding GS , GP , or GPK , thus targeting PP1 to each of the three enzymes . PP1 dephosphorylates each of the three enzymes , activating GS and inhibiting GP and GPK [10] , [11] . There are two main hypotheses of polyglucosan formation , the first based on evidence from cell models that laforin interacts with malin and with PTG , and that the laforin-malin complex downregulates GS through malin-mediated ubiquitination and degradation of PTG . In this hypothesis , absence of laforin or malin would increase PTG , which would over-activate GS , leading to excessive extension of glycogen chains and conversion of glycogen to polyglucosan [12]–[14] . Although results from animal models have yet to confirm this idea [15]–[17] , there is indeed a body of work implicating PTG . The second hypothesis is based on the observation that laforin dephosphorylates glycogen and that in LD there is progressive hyperphosphorylation of glycogen , causing it to unfold and precipitate . GS remains bound to the precipitating glycogen , but glycogen branching enzyme , the enzyme responsible for branching , even under normal condition does not associate tightly [16]–[19] . In this hypothesis , elongation by GS of the chains of the precipitated glycogen , with no branching , would convert glycogen to polyglucosan . Both hypotheses predict that inhibiting GS would prevent polyglucosan formation , and if LB are causative of the PME , this might ameliorate or cure the epilepsy . One way to inhibit GS would be to interfere with its activation by PTG . In the present work we genetically remove PTG from mice with LD . We obtain dramatic reduction in LB , and resolution of neurodegeneration and the PME . This work has direct implications for therapeutic intervention in this fatal disease .
We initially considered removing the muscle/brain isoform of GS ( GYS1 ) from LD mice by breeding GYS1-deficient mice with laforin-deficient mice . However , this is impractical because in 90% of cases GYS1-deficient mice cannot survive birth ( although the 10% that do are subsequently healthy with normal lifespan and exercise tolerance ) [20] , [21] . Recently , DePaoli-Roach generated a mouse line deficient of PTG . In contrast to an earlier report that disruption of the PTG gene was embryonic lethal [22] , the present mice are healthy and have normal lifespan [23] . Their glycogen is reduced by 30% in skeletal muscle and by 70% in brain . Laforin-deficient mice ( LKO ) have been extensively characterized and exhibit LB formation , neurodegeneration , and PME [24] . The PME is not as severe as in humans . The mice develop progressively worsening myoclonus , but convulsive seizures are not seen [24] . Unlike human patients and despite the neurodegenerative changes and progressive myoclonus LKO mice do not have a shortened lifespan ( unpublished observation ) . Metabolically , LKO mice have progressively increasing accumulation of glycogen in tissues , reaching approximately fivefold normal in brain and threefold in skeletal muscle by age nine to 12 months [16] . To remove PTG from the laforin-deficient mice , we bred LKO mice with PTG knockout mice and interbred their litters to produce PTG/laforin double knockout ( DKO ) animals . DKO mice are born at Mendelian frequency , have normal skin , body habitus and growth , exhibit no obvious behavioral abnormalities , and appear to have normal lifespan , our oldest presently healthy at 18 months of age . As mentioned , nine to 12 month-old LKO mice have vast amounts of LB in brain and other organs , and neurodegeneration [24] . We studied brain and skeletal muscle from LKO and DKO mice and their wild-type ( wt ) littermates at 12 months and found massive reduction in LB in DKO mice ( Figure 1 and Figure 2 ) . In hippocampus , frontal cortex and cerebellum , the numbers of LB in neuronal processes in DKO were respectively 3% , 0 . 1% , and 0 . 5% of those in LKO animals . The numbers of perikaryal LB were diminished to 10% in hippocampus and 5% in frontal cortex . In cerebellum , perikaryal LB were not significantly reduced in number , although they were much smaller in size . In skeletal muscle , LB had completely disappeared , compared to their very large quantities in LKO animals ( Figure 3 ) . Wt animals , as expected , had no LB in either tissue . To determine whether the reductions in LB correlated with reductions in glycogen content , we measured total glycogen in whole brain and skeletal muscle and found that the increased glycogen content of LKO mice had normalized to wt levels in DKO animals ( Figure 4 ) . Lost neurons are replaced by astrocytes . We assessed neuronal loss in DKO , LKO and wt animals at 12 months first by measuring gliosis , which we quantified by morphometric counts of glial fibrillary acidic protein ( GFAP ) -positive cells . In cerebellum , there were no differences between the genotypes . In hippocampus and frontal cortex , however , DKO mice had half the number of astrocytes as LKO animals , and the same number as wt , i . e . , they have no measurable gliosis ( Figure 5 ) . We next assessed neurodegeneration directly . In their original study of neuropathology in LKO mice , Ganesh and colleagues noted absence of apoptosis and necrosis . Using electron microscopy ( EM ) , they documented an unusual form of somatic degeneration characterized chiefly by shrinkage and retraction of plasma and nuclear membranes and darkening of the cytoplasm [24] . We performed EM studies in the present set of LKO , DKO and wt mice . Figure 6A–6C show representative wt cerebellar Purkinje neurons with characteristic full nuclei and cytoplasms and taut and circular plasma membranes . Numerous axon terminals are seen directly apposed to the membranes forming normal synapses lined one next to the other around the circumferences of the cells . Figure 6D–6F show typical LKO Purkinje cells . Nucleus and cytoplasm are shrunken . The plasma membrane is wrinkled and retracted with appearance of indistinct spaces between it and the axon boutons that would normally associate with it , effectively resulting in loss of synaptic contacts . Numerous LB in neuronal processes are present . Figure 6G–6I show representative DKO Purkinje cells . The cells are essentially back to normal with full nuclei and cytoplasms , circular plasma membranes , and generally a full complement of synapses around the cell body . However , the correction while near-perfect is not completely perfect . The plasma membrane is not quite as taut as in wt , and there are rare instances of synaptic contact loss . Myoclonus is a single jerk of the body or of a body part . Mice , like humans , exhibit a certain amount of physiologic myoclonus , such as hypnagogic myoclonus [25] , [26] . In LD patients , myoclonus is extremely frequent and in later stages near-constant and debilitating [4] , [5] , [25] . We counted myoclonus in 12 month-old wt , LKO , and DKO animals , blind to genotype . Myoclonus was defined as sudden rapid jerks of the head or of the dorsum of the animal . In the latter , the split-second myoclonus causes retropulsion of the animal , closely resembling the myoclonus we documented previously in canine LD [27] . LKO mice have fourfold increased myoclonus over wt . DKO were the same as wt ( Figure 7 ) . In their original description Ganesh and colleagues reported that in addition to myoclonus 80% of nine to 12 month-old LKO animals also exhibit myoclonic seizures ( polymyoclonus ) , consisting of rapid repetitive head and body jerks lasting few seconds and associated with epileptic discharges on electrocorticography [24] . We observed polymyoclonus in 80% of the present 12 month-old LKO mice , in no wt mice , and in no DKO mice .
In this study we show for the first time that removal of PTG in an animal model of LD reduces LB formation , and eliminates neuronal loss and the myoclonic epilepsy . PTG is not the only protein that targets PP1 to glycogen and glycogen metabolizing enzymes . Others include R6 , which like PTG is ubiquitously expressed , RGL/GM specific to striated muscle , and GL found in rodent liver [7] , [28] . It is therefore not surprising that skeletal muscle and brain of PTG-deficient mice still make glycogen , 70% and 30% of normal respectively [23] . What is surprising is the complete absence of LB in skeletal muscle in DKO . It would have been expected that if there is 70% glycogen synthesis in the absence of PTG , there would be 70% LB formation in the absence of laforin and PTG . Possibly , LB formation requires a threshold amount of glycogen . Alternatively , the laforin-malin complex in skeletal muscle acts specifically through PTG . On the other hand , if PTG is the preferred mediator of laforin-malin , it is surprising that its elimination from brain results in incomplete disappearance of LB , despite deeper glycogen reduction in brain in PTG deficient mice than in muscle . Much work ahead is needed to resolve these paradoxes . The cause of neurodegeneration in LD has received much attention in recent years . Presence of up to 28% protein in some LB [9] , [29] , and signs of neurodegeneration in LKO mice at two months of age when LB are still small [24] , led to considerations as to whether the neurodegeneration is related not to polyglucosans but to protein aggregation , similar to Alzheimer's and other neurodegenerative diseases [24] , [30]–[32] . In the present study , correction of the neurodegeneration through interference in glycogen metabolism suggests that the neurodegeneration is connected to the disturbance in glycogen metabolism . This is consistent with recent observations that neurons , unlike other cell types , are highly vulnerable to increases in glycogen and polyglucosan content , with upregulation of GS leading to cell death [13] . Presence of small LB in two month-old LKO mice indicates that polyglucosans were already formed and accumulating by that time , likely triggering cell death , even as they had not yet formed large LB . Proteins in LB could be glycogen-metabolizing and other proteins trapped amidst aggregating polyglucosans . Recently , it was reported that laforin enhances macroautophagy and that macroautophagy is dysfunctional in LD [33] , indicating that laforin might function not only to prevent polyglucosan formation but also in clearing polyglucosans when they do form . Our results show that preventing polyglucosan formation obviates other laforin functions and suffices to prevent LD in mouse . A major question in LD is why this particular neurodegenerative disease exhibits extremely severe epilepsy . Polyglucosans and LB occur in one other neurological disease , Adult Polyglucosan Body Disease ( APBD ) , caused by mutations in the glycogen branching enzyme gene [34] . APBD LB differ from LD LB in one respect . For reasons unknown , they form exclusively in axons , especially long axons traveling to and from peripheral structures ( skin , muscle , etc . ) and the central nervous system . Affected patients suffer from motor neuron disease , may have mild dementia , but have no epilepsy [34] , [35] . LD LB , on the other hand , are not seen in long tract axons , but instead almost completely replace the cytoplasm of vast numbers of small neuronal processes , mainly dendrites [3] , [5] , [6] . One possibility for the intractable epilepsy in LD is the progressive disturbance of dendritic function , the chief determinant of a neuron's excitability state . Near-complete disappearance of dendritic LB in the present study may account for the correction of the PME in our DKO mice . In this paper , we correct the pathology and eliminate the PME of LD through genetic depletion of one of the proteins that targets the PP1 phosphatase to glycogen and the glycogen metabolizing enzymes . The effect on glycogen is partial , i . e . glycogen is not altogether eliminated , only reduced , the reduction returning the elevated glycogen levels of LD to normal wt levels , correcting the cardinal features of the disease , and causing no apparent harm to the mice . The crystal structures of PP1 [36] , GS [37] , [38] , GP [39] , [40] , and GPK [41] are known , as is the PTG interaction domain with GS , GP and GPK [10] , [12] . Identification of inhibitors of this interaction through rational design or large-scale small molecule screens could result in a treatment for this fatal epilepsy . In addition to LD , accumulation of normal or abnormal glycogen is a cause of disease in several glycogen storage diseases including APBD and its severe fatal infantile form Andersen's disease [42] , and the common and debilitating glycogenosis Pompe disease ( acid maltase deficiency ) [43] . Our results in LD suggest that removal of PTG could also improve these diseases . In fact , GS itself was recently removed from a Pompe mouse model resulting in a cure of the disease in that model [44] . While complete elimination of GS in humans cannot be contemplated as this causes significant pathology including sudden cardiac death [45] , the Pompe study and our present work suggest that classes of medications that partially reduce GS or that partially reduce GS and activate GP , e . g . through interference in the PTG – GS/GP/GPK interaction , could have therapeutic benefit in multiple glycogenoses .
All animal procedures were approved by the Toronto Centre for Phenogenomics Animal Care Committee . Laforin-deficient mice were a gift of Dr . AV Delgado-Escueta and S Ganesh . Mice were sacrificed by cervical dislocation and tissues immediately fixed in 10% formalin . Periodic acid-Schiff-diastase ( PAS-D ) staining was as previously described [17] . PAS stains normal glycogen and polyglucosans . The short treatment with diastase ( amylase ) digests glycogen but not polyglucosans . Diastase resistant PAS stained structures are LB . For GFAP staining , deparaffinized 5 µm sections were incubated with a polyclonal GFAP antibody ( Dako ) for one hour . Sections were thoroughly rinsed , and antibody visualized using diaminobenzidine conjugated avidin biotin complex ( Vector ) . Images from PAS-D slides were acquired at a 400× magnification ( Olympus ) by a CCD camera ( Roper Scientific ) . Perikaryal and granular ( neuronal processes ) LB were distinguished by size and location . Numerical density [46] of both perikaryal and granular LB was then determined using the formula:where N is the number of either the perikaryal LB or the number of granular LB per unit volume of tissue ( number/mm3 ) , NpLBa is the number of perikaryal LB per area , NgLBa is the number of granular LB per area , d is the average diameter of either the perikaryal or granular LB , t is the thickness of the section ( 5 µm ) , and h is the smallest recognizable LB ( 1 µm ) . A minimum of 500 fields/animal were analyzed using an image analysis program ( Image Pro Plus , Media Cybernetics , Bethesda ) . Data were expressed as means ± SEM and significance calculated using an ANOVA analysis . Images from GFAP stained slides were acquired at a 250× magnification using the same microscope and equipment as above . The total number of GFAP positive cells was divided by the total area and expressed as cells/mm2 . Genotype was blinded to the reviewer . A minimum of 250 fields/animal were analyzed . Images were analyzed using an image analysis program ( Image J , NIH , Bethesda ) . Data were expressed as means ± SEM and significance calculated using ANOVA . Mice were sacrificed by cervical dislocation and tissues quickly frozen in liquid nitrogen . Tissues were ground with a mortar and pestle in liquid nitrogen . Aliquots of 30–50 mg of tissue were mixed with 30% potassium hydroxide ( KOH ) and boiled at 100°C with frequent mixing . Glycogen was then precipitated with a final concentration of 67% ethanol at −20°C , then pelleted . This process was repeated three times . The purified glycogen samples were then dried and suspended in sodium acetate buffer . Glycogen was digested with amyloglucosidase ( Sigma ) at 37°C . Released glucose was determined using a glucose assay kit ( Sigma ) . The amount of glycogen was calculated and expressed as µmoles of glucose per gram of tissue . Brains for electron microscopy were taken from mice first perfused through the left ventricle of the heart with 2 . 5% glutaraldehyde in 0 . 1 M phosphate buffer ( pH 7 . 4 ) . The tissue was minced into cubic 1 mm blocks and fixed for an additional two to four hours . Samples were then washed in buffer and post fixed in phosphate-buffered 2% OsO4 for one hour . They were then dehydrated in an ascending series of acetones prior to being infiltrated , embedded and polymerized at 60°C overnight in embed 812-Araldite . Ultrathin sections were then prepared and stained with uranyl acetate and lead citrate prior to examination and image acquisition in the EM ( JEOL JEM 1011 , Peabody , MA ) . Mice were placed in individual Plexiglas chambers and videotaped for four hours . Myoclonus was counted during periods when the animal was not exploring . Myoclonus counts were obtained in periods of a minimum of 10 minutes per mouse . The entire record was reviewed for detection of polymyoclonus . Observer was blinded to genotype . Myoclonus data in Figure 7 is shown as means ± SEM and significance calculated using an unpaired student's t-test . | Lafora disease ( LD ) is a fatal epilepsy that afflicts previously normal teenagers . It is caused by mutations in the EPM2A or EPM2B genes encoding the laforin carbohydrate-binding phosphatase and the malin E3 ubiquitin ligase . LD is the most common neurodegenerative epilepsy of adolescents . Affected children suffer an ordeal lasting 10 years , consisting of escalating seizures , constant body jerking , particularly frightening epileptic visual hallucinations , and later on dementia . They die of massive convulsion . Brain biopsies reveal accumulation of a starch-like compound , polyglucosan , overtaking dendrites and likely causing the disease , and neurodegeneration . Glycogen synthase ( GS ) , the enzyme that forms normal glycogen , is also responsible for synthesizing these polyglucosans . We reasoned that reducing GS activity might prevent polyglucosan formation . Mice deficient of Epm2a replicate LD and are a standard model . Members of our group generated mice deficient of PTG , a protein involved in activating GS . By breeding LD mice with PTG-lacking mice , we generated LD mice lacking the GS-activating effect of PTG . This resulted in a cure . The double knockout mice have almost no polyglucosan , no neurodegeneration , and no seizures . Our work opens an avenue of treatment for this fatal epilepsy , which may also be applicable to other glycogen storage diseases . | [
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"biol... | 2011 | PTG Depletion Removes Lafora Bodies and Rescues the Fatal Epilepsy of Lafora Disease |
Plant male gametogenesis involves complex and dynamic changes in gene expression . At present , little is known about the transcription factors involved in this process and how their activities are regulated . Here , we show that a pollen-specific transcription factor , WRKY34 , and its close homolog , WRKY2 , are required for male gametogenesis in Arabidopsis thaliana . When overexpressed using LAT52 , a strong pollen-specific promoter , epitope-tagged WRKY34 is temporally phosphorylated by MPK3 and MPK6 , two mitogen-activated protein kinases ( MAPKs , or MPKs ) , at early stages in pollen development . During pollen maturation , WRKY34 is dephosphorylated and degraded . Native promoter-driven WRKY34-YFP fusion also follows the same expression pattern at the protein level . WRKY34 functions redundantly with WRKY2 in pollen development , germination , and pollen tube growth . Loss of MPK3/MPK6 phosphorylation sites in WRKY34 compromises the function of WRKY34 in vivo . Epistasis interaction analysis confirmed that MPK6 belongs to the same genetic pathway of WRKY34 and WRKY2 . Our study demonstrates the importance of temporal post-translational regulation of WRKY transcription factors in the control of developmental phase transitions in plants .
Pollen , the male gametophyte of angiosperms , displays highly reduced structure of two or three cells at maturity . Because of the simple cell linage and dynamic developmental processes , plant male gametogenesis provides an interesting model for studying many fundamental cellular processes , including cell specification , cell polarity , cell cycle , and transcriptional regulation in these processes . During male gametogenesis , the uninucleate microspore ( uninucleate microspore stage , UNM ) undergoes an asymmetric mitosis to generate a large vegetative cell and a generative cell within it ( bicellular pollen stage , BCP ) . In Arabidopsis thaliana , before pollen maturation , the generative cell undergoes a second symmetric mitosis to create two sperm cells ( tricellular pollen stage , TCP ) . Prior to anther dehiscence and pollination , the TCP further develops into dehydrated mature pollen ( mature pollen stage , MP ) [1] . Pollen development is highly regulated , which is associated with successive global transcriptional regulation throughout the process [2] , [3] . The precise and dynamic regulation of male gametogenesis requires transcription factors . In Arabidopsis , over 600 transcription factors are expressed during male gametogenesis , which forms a dynamic regulatory network [2] , [4] . A subset of pollen-specific MIKC* MADS box proteins ( AGL30/65/66/94/104 ) are expressed preferentially during pollen maturation [2] , [5] . Double mutant combinations revealed the important roles these genes play in pollen germination and pollen fitness [5] . In Petunia , seven different zinc-finger transcription factors are expressed transiently and sequentially at different stages of pollen development [6] . Such transcription factors might each have specific target genes and constitute a regulatory cascade during pollen development [6] . Although progress has been made on the potential importance of transcription factors in male gametogenesis , little is yet known about the biological function of these transcription factors and how their activities are regulated to form temporal transcriptional regulatory networks . Besides expression regulation , post-translational modification is a common mechanism to regulate the activity of transcription factors . Phosphorylation/dephosphorylation through mitogen-activated protein kinase ( MAPK ) cascades is a conserved post-translational modification in eukaryotes . A MAPK cascade minimally consists of three kinases: a MAPK , a MAPK kinase ( MAPKK ) , and a MAPKK kinase ( MAPKKK ) . The activity of MAPKs is regulated by their upstream MAPKKs through phosphorylation , and MAPKKs are activated through phosphorylation by their upstream MAPKKK ( s ) . MAPKKKs are downstream of receptors/sensors and are activated in response to extracellular stimuli or to developmental signals [7] . Once activated , MAPKs can phosphorylate functionally divergent substrates on serine or threonine residues within a minimal S/T-P motif [8] . In Arabidopsis , there are 20 MAPKs , of which MPK3 ( At3g45640 ) and MPK6 ( At2g43790 ) are extensively studied . MPK3 and MPK6 have been revealed to phosphorylate multiple substrates , including transcription factors , in diverse biological processes [9]–[14] . For instance , WRKY33 ( At2g38470 ) is a WRKY transcription factor required for pathogen defense in Arabidopsis [15] . In response to Botrytis cinerea infection , WRKY33 is phosphorylated by MPK3/MPK6 , which is important for the activation of WRKY33 , as mutations of MAPK-phosphorylation sites compromise the function of WRKY33 in vivo [9] . In this report , we show that WRKY34 ( At4g26440 ) , a new substrate of Arabidopsis MPK3/MPK6 , is involved in male gametogenesis . WRKY34 , a close homolog of WRKY33 , is a pollen-specific WRKY transcription factor . When overexpressed using LAT52 , a strong pollen-specific promoter , WRKY34 protein is temporally phosphorylated by MPK3/MPK6 at early stages in pollen development and then becomes dephosphorylated and degraded right before pollen maturation . Loss-of-function genetic analysis shows that WRKY34 , together with a close homolog WRKY2 ( At5g56270 ) , plays important roles in pollen development and function . A complementation assay suggests that the phosphorylation of WRKY34 by MPK3/MPK6 is important for its function in vivo . Although single mutation of none of the WRKY2 , WRKY34 , MPK6 genes causes a pollen developmental defect , both the wrky2 mpk6 and wrky34 mpk6 double mutants exhibit pollen developmental defects similar to the wrky2 wrky34 double mutant , demonstrating that WRKY34 and WRKY2 indeed belong to the same pathway of MPK3/MPK6 in early pollen development .
After the identification of WRKY33 as a substrate of MPK3/MPK6 in regulating plant defense responses [9] , [16] , we examined other WRKYs that share high homology with WRKY33 for potential MAPK phosphorylation sites . WRKY transcription factors are divided into three groups based on the number of WRKY domains ( two copies in Group I , and one copy in Groups II and III ) and the structure of their zinc fingers ( C2HC in Group III but not in Group II proteins ) [17] . WRKY33 , with two WRKY domains , belongs to Group I in the WRKY family [17] . WRKY34 ( At4g26440 ) , another Group I member that shares high homoxlogy with WRKY33 , is a pollen-specific gene that is preferentially expressed during early stages of male gametogenesis [18] , [19] . WRKY34 also contains several consensus MAPK phosphorylation sites at similar positions as WRKY33 ( Figure 1A ) , indicating that WRKY34 might be a MPK3/MPK6 substrate as well . To determine if WRKY34 can be phosphorylated by MAPKs in vitro , we prepared a His-tagged recombinant WRKY34 protein for in vitro MAPK phosphorylation assays . WRKY34 can be strongly phosphorylated by activated MPK3 and MPK6 ( Figure 1B , upper panel ) . Without activation by the constitutively active MKK4DD/MKK5DD , MPK3 weakly phosphorylated WRKY34 , whereas MPK6 showed no activity , demonstrating that the activation of MPK3 and MPK6 was important for a high-level phosphorylation of WRKY34 . Control reactions with myelin basic protein ( MBP ) as an artificial substrate confirmed MPK3/MPK6 activation ( Figure 1B , lower panel ) . There are six putative MAPK phosphorylation sites ( Ser-87 , Ser-91 , Ser-98 , Ser-108 , Ser-274 , and Ser-544 ) within the WRKY34 protein ( Figure 1C ) . We performed site-directed mutagenesis to change these sites from Ser to Ala ( WRKY34SA ) . As shown in Figure 1D , the phosphorylation of WRKY34SA protein by MPK3 and MPK6 was greatly reduced , demonstrating that these SP-motifs are the major MPK3/MPK6-phosphorylation sites in WRKY34 . The residual phosphorylation of WRKY34SA also indicates the existence of other unidentified minor MAPK phosphorylation site ( s ) in WRKY34 . To determine whether WRKY34 is phosphorylated by MPK3/MPK6 in vivo , we developed an immunoblot protocol to detect WRKY34 protein during male gametogenesis . A four-copy myc tag ( 4myc ) was fused to the N terminus of WRKY34 protein , and a pollen-specific LAT52 promoter [20] was used to drive the transgene so that the 4myc-tagged WRKY34 protein could be expressed specifically and highly in pollen . Flowers or buds at various stages were collected for immunoblot detection of 4myc-WRKY34 protein in pollen . In this assay , the open flower right after anthesis was designated +1 ( Figure 2A ) . The flower at Stage 13 , in which anthesis was about to occur [21] , was designated as 0 . Buds/flowers at earlier stages were named with negative numbers −1 , −2 , and so on , according to their relative positions to the number 0 flower ( Figure 2A ) . Under our experimental conditions , as few as 10 flowers/buds were sufficient for protein extraction and the detection of 4myc-WRKY34 protein by immunoblot analysis . The stage of pollen development was determined by DAPI staining of pollen grains from dissected flowers/buds of multiple plants . The +1 and 0 flowers contained mature pollen ( MP ) grains . The −1 and −2 buds contained homogenous tricellular pollen ( TCP ) . The −3 to −5 buds contained a mixture of TCP and bicellular pollen ( BCP ) , indicating non-uniform development of pollen in these bud stages . The −6 and −7 buds contained solely BCP . We found that tagged 4myc-WRKY34 protein was first detectable in −6 buds , which contain BCP ( Figure 2B , top panel ) . The absence of 4myc-WRKY34 protein in earlier stages is likely a result of low LAT52 promoter activity [22] . The 4myc-WRKY34 signal was stronger in more developed buds and reached its peak in −2 and −1 buds with TCP ( Figure 2B , top panel ) . Interestingly , although driven by LAT52 , a promoter with the strongest activity in mature pollen [22] , the 4myc-WRKY34 protein signal was hardly detectable in 0 buds and open flowers ( Figure 2B , top panel ) . The transcripts from 4myc-WRKY34 transgene showed a similar expression pattern , as indicated by RT-PCR ( Figure S1 ) . We also tried an immunoblot assay using flowers from WRKY34 promoter-driven 4myc-WRKY34 transgenic plants ( PWRKY34:4myc-WRKY34 ) . However , 4myc-WRKY34 protein was not detectable in such samples , which is likely due to low WRKY34 promoter activity ( data not shown ) . Interestingly , as described later , the PWRKY34:WRKY34-YFP fusion showed a similar expression pattern as PLAT52:4myc-WRKY34 . Therefore , we conclude that the use of LAT52 promoter in this assay could represent , at least partially , the native WRKY34 expression and modification pattern . In the immunoblot assay , we noticed that 4myc-WRKY34 showed differential migrations in the SDS-polyacrylamide gel depending on the developmental stage of the flower buds . In −6 buds with BCP , 4myc-WRKY34 protein exhibited a slightly slower migration ( Figure 2B , top panel ) . In −5 to −3 buds with a mixture of BCP and TCP , 4myc-WRKY34 existed as doublets , and the faster moving band gradually accumulated ( Figure 2B , top panel ) . In −1 and −2 buds with TCP , 4myc-WRKY34 protein predominately existed as the faster migrating band ( Figure 2B , top panel ) . These results indicated that WRKY34 protein was modified in BCP , possibly by protein phosphorylation , and the modification is dependent on the pollen's developmental stage . To determine whether the slower migrating band of 4myc-WRKY34 is due to phosphorylation , we performed a Phos-tag mobility shift assay . In this assay , the Phos-tag reagent binds specifically to phosphorylated proteins and slows down their migration in the SDS-polyacrylamide gel [9] , [23] . As shown in Figure 2B ( middle panel ) , 4myc-WRKY34 protein was indeed phosphorylated in the BCP of −6 buds and was gradually dephosphorylated in late stages of the male gametogenesis . The phosphorylation of 4myc-WRKY34 was greatly reduced upon pollen maturation at −1 , which is followed by complete disappearance of WRKY34 protein in 0 flowers ( Figure 2B , top panel ) . We then performed immunoblot with 4myc-WRKY34SA transgenic plants to determine if the shifting of protein bands is dependent on the MAPK phosphorylation sites in WRKY34 . Although the protein expression pattern is similar to 4myc-WRKY34 , the 4myc-WRKY34SA protein showed no band shift in either the immunoblot or Phos-tag assay ( Figure 2C ) . This result further confirmed that WRKY34 was temporally phosphorylated during early pollen development , and the phosphorylation occurred on the MPK3/MPK6-phosphorylation sites delineated in the in vitro phosphorylation assay ( Figure 1C and 1D ) . To demonstrate that the in vivo phosphorylation of WRKY34 during pollen development is carried out by MPK3 and MPK6 , we introduced the 4myc-WRKY34 transgene into the mpk3 mpk6 double mutant background . Since the mpk3 mpk6 double mutant is embryo lethal [13] , we attempted pollen-specific RNAi suppression of MPK3 in the mpk6 mutant background . LAT52 promoter-driven MPK3RNAi construct was transformed into the mpk6 plants . Because of the pollen-specific expression of MPK3RNAi , the sporophytic tissues were not affected , which allowed us to obtain the double homozygous MPK3RNAi mpk6 plants . Real-time qPCR demonstrated that MPK3 expression in pollen from MPK3RNAi mpk6 plants was knocked down ( Figure 3A ) . We then performed immunoblot and Phos-tag assays of 4myc-WRKY34 in the MPK3RNAi mpk6 plants . The mobility shift of 4myc-WRKY34 was abolished in the absence of MPK3 and MPK6 ( Figure 3B , top and middle panels ) . This loss-of-function system demonstrated that the WRKY34 was phosphorylated specifically by MPK3 and/or MPK6 . The stability of WRKY34 protein apparently was not affected by the MAPK phosphorylation since mutation of the Ser residues that are phosphorylated by MPK3/MPK6 did not affect the protein expression pattern of WRKY34 during pollen development ( Figures 2C ) . Previous studies showed that WRKY34 is an early pollen gene enriched in UNM and BCP [19] and that mutation of the WRKY34 gene increases the pollen's tolerance to cold stress [18] . However , the biological function of WRKY34 in pollen development remains unclear . Under our growth conditions , single wrky34 mutant pollen showed no developmental defect . Since more than 50% of the WRKY family members are expressed in the male gametophytes [2] , we speculated that there might be functionally redundant WRKY member ( s ) in early pollen development . A phylogenetic analysis was used to identify such member ( s ) ( Figure S2 ) . WRKY34 is closely related to WRKY2 , a WRKY member expressed in various tissues including male gametophyte [24] . We examined by quantitative RT-PCR the expression patterns of WRKY34 and WRKY2 in several tissues . WRKY34 expression was very low in most examined tissues and was slightly higher in floral buds ( Figure 4A ) . In contrast , WRKY2 showed higher expression in all detected tissues ( Figure 4A ) . To examine the detailed expression patterns of WRKY2 and WRKY34 in pollen at different stages , we fused the WRKY2 and WRKY34 genomic sequences , which contain promoter and gene coding region , with YFP . The YFP signal of both fusion proteins was detectable in nuclei , which was consistent with their function as transcription factors . It is also noteworthy that WRKY2- and WRKY34-YFP signals were detectable in the vegetative cell but not in the generative or sperm cells . The PWRKY2:WRKY2-YFP signal was absent in UNMs ( Figure 4B and 4F ) , while it became significantly higher in BCP nuclei ( Figure 4C and 4G ) . The YFP signal in nuclei was also found in TCP ( Figure 4D and 4H ) and MP ( Figure 4E and 4I ) . For PWRKY34:WRKY34-YFP , the nucleus YFP signal was dim in UNM , although it was still distinguishable from the pollen auto-fluorescence ( Figure 4J and 4N ) . The signal was more detectable in BCP ( Figure 4K and 4O ) and TCP ( Figure 4L and 4P ) . However , in contrast to WRKY2 , the WRKY34-YFP signal was absent in MP ( Figure 4M and 4Q ) . These results showed that WRKY34 and WRKY2 expression overlaps at the BCP and TCP stages . In addition , the PWRKY34:WRKY34-YFP expression pattern was similar to the PLAT52:4myc-WRKY34 expression in the immunoblot assay ( Figure 2B , top panel ) . This further indicated that the WRKY34 protein expression pattern was not solely dependent on promoter activity . We next obtained a T-DNA insertion line for WRKY34 ( SALK_133019 hereafter wrky34-1 ) and two T-DNA lines for WRKY2 ( Salk_020399 and SAIL_739_F05 , hereafter wrky2-1 and wrky2-2 , respectively ) ( Figure 5A ) . wrky34-1 was reported to be a null mutant [18] . We performed quantitative RT-PCR to examine WRKY2 expression in wild-type , wrky2-1 , and wrky2-2 pollen . The result showed that the expression of WRKY2 was moderately knocked down in seedlings of both alleles ( Figure 5B ) . However , in pollen , WRKY2 expression was almost completely knocked out in wrky2-1 but not in wrky2-2 ( Figure 5B ) . Therefore , we crossed wrky34-1 with wrky2-1 to generate the wrky2-1 wrky34-1 double mutant and then examined the wrky2-1 wrky34-1 double mutant pollen function by reciprocal crosses using combinations of heterozygous mutants and wild type ( Table 1 ) . The male transmission of the mutant alleles was normal when pollen grains from either wrky2-1+/− or wrky34-1 +/− plants were used as pollen donors , suggesting that single mutations of either WRKY34 or WRKY2 had no effect on the function of pollen ( Table 1 ) . However , when using wrky2-1+/− wrky34-1−/− or wrky2-1−/− wrky34-1+/− plants as the male parents , we observed that the transmission of wrky2-1 wrky34-1 pollen was significantly reduced ( 0 . 04∶1 for pollen from wrky2-1+/− wrky34-1−/− plants and 0 . 01∶1 for pollen from wrky2-1−/− wrky34-1+/− plants , instead of the expected 1∶1 , p-value<0 . 0001 ) ( Table 1 ) . This result suggested that WRKY34 and WRKY2 are important for pollen function but also that a portion of the double mutant pollen grains remained functional . The transmission of wrky2-1 wrky34-1 female gametophytes was normal ( Table 1 ) , indicating that the female gametophyte function was not affected . Because of the leaky transmission of wrky2-1 wrky34-1 pollen , we were able to obtain wrky2-1 wrky34-1 homozygous double mutant plants at low frequency . Morphologically , the double mutant plant was indistinguishable from the wild type ( Figure 5C ) . To examine the development of wrky2-1 wrky34-1 pollen , we used Alexander's staining to distinguish normal and aborted pollen [25] . In this assay , the cytoplasm of normal pollen should show a purple color and the pollen wall a distinctive green color . Pollen grains from wild-type plants were viewed as full , round , purple-stained grains ( Figure 5D ) . In contrast , a portion of wrky2-1 wrky34-1 pollen exhibited aberrant morphology and green color ( 28% abortion , n = 200 ) , which indicated impaired pollen development of the double mutant ( Figure 5E ) . We then performed fluorescein diacetate ( FDA ) staining to check the viability of wrky2-1 wrky34-1 pollen ( Figure 5F and 5G ) . In comparison with wild-type pollen grains ( 96% viable ) , the majority of wrky2-1 wrky34-1 pollen failed to show FDA fluorescence and therefore was likely to be dead ( 67% ) . The non-viable rate in FDA staining was higher than that in the Alexander staining , indicating that FDA is a more sensitive viability assay . There were wrky2-1 wrky34-1 pollen grains with a small patch that failed to be stained using Alexander staining ( Figure 5E ) . They were classified as viable pollen , but might be non-viable . In contrast , FDA staining , which is dependent on both cellular esterase activity and plasma membrane integrity , gave much clearer results . For this reason , FDA staining was used for all the other experiments . We next stained the developing pollen at earlier stages with FDA . The lethality of wrky2-1 wrky34-1 pollen was first identifiable in -6 buds with BCP , and the percentage of lethal pollen increased following pollen development ( Figure S3 ) . The onset of pollen death in wrky2-1 wrky34-1 double mutant correlates with the appearance of WRKY34 protein in BCP and TCP stages ( Figure 2B , top panel ) , suggesting the requirement of these two WRKYs at these developmental stages . There are two possible reasons for the lower percentages of FDA positive pollen at early developmental stages and then the gradual increase in FDA positive pollen in the wild type ( Figure S3 ) . Firstly , the tapetal cell layer surrounding the developing pollen could reduce the efficiency of FDA staining at the early stage . Secondly , dissection and squeezing to release pollen from the anther and tapetum might damage the immature pollen . Side-by-side comparison revealed that the FDA positive pollen from wrky2-1 wrky34-1 plants continued to drop ( Figure S3 ) , indicating the loss of viability of wrky2-1 wrky34-1 mutant pollen . We also examined the ultrastructure of wrky2-1 wrky34-1 pollen using scanning electron microscopy ( SEM ) . Both wild-type and wrky2-1 wrky34-1 pollen appeared to have normal pollen wall structures ( Figure 5H and 5I ) . In contrast to the uniformly shaped wild-type pollen grains ( Figure 5H ) , the wrky2-1 wrky34-1 pollen grains were a mixture of shapes , including normal shaped pollen , collapsed pollen , and ruptured pollen remnant ( Figure 5I ) . This indicated that the development of wrky2-1 wrky34-1 pollen was defective . Further analysis with transmission electron microscopy ( TEM ) confirmed the abnormal ultrastructure of wrky2-1 wrky34-1 pollen . Consistent with the cytological staining results , a portion of the wrky2-1 wrky34-1 pollen was collapsed with leaky cytoplasm content ( Figure S4 ) . Furthermore , for the majority of wrky2-1 wrky34-1 pollen that exhibited similar exterior appearance as wild-type pollen , the intracellular ultrastructure was different from that of the wild-type pollen ( Figure 5J to 5M ) . The numbers of plastids and endoplasmic reticulum ( ER ) were reduced in wrky2-1 wrky34-1 pollen grain . In addition , the intine layer was discontinuous and undulated at the germination pore of the double mutant pollen grain ( Figure 5K and 5M ) . In addition to a pollen developmental defect , the in vitro germination assay revealed that the wrky2-1 wrky34-1 double mutant was defective in pollen function . In our assays , the average germination ratio of wild-type pollen was 78% ( Figures 6A and 7B ) , while only 28% of wrky2-1 wrky34-1 pollen was capable of germination under the same conditions ( Figures 6B and 7B ) . The reduction in pollen germination appears to be a result of reduced pollen viability . For the wrky2-1 wrky34-1 pollen that germinated , the pollen tube length was significantly shorter than the length of wild-type pollen tubes ( Figure 6A , 6B , and 7C ) . The average pollen tube length was 471 µm in the wild type and 288 µm in wrky2-1 wrky34-1 double mutant at 7 hours after germination in vitro , representing a 40% reduction in length in the double mutant pollen tubes . Pollination analysis followed by aniline blue staining further demonstrated that the wrky2-1 wrky34-1 double mutant was defective in pollen germination and pollen tube growth in vivo ( Figure 6C and 6D ) . Since WRKY34 protein was degraded before pollen maturation ( Figure 2B , top panel ) , we speculated that the reduced germination and tube growth of wrky2-1 wrky34-1 pollen were not an indication of a requirement of WRKY2/WRKY34 in these two processes but rather a result of weak pollen due to impaired development , which was also evident based on the TEM observation ( Figure 5J to 5M ) . To test whether phosphorylation of WRKY34 is important for its function in pollen development , we performed genetic complementation of wrky2-1 wrky34-1 pollen using WRKY34 promoter-driven 4myc-WRKY34WT or 4myc-WRKY34SA . Pollen from T2 homozygous progenies with a transgene expression level similar to wild type was selected and examined ( Figure S5 ) . PWRKY34:4myc-WRKY34WT wrky2-1 wrky34-1 pollen showed viability , germination , and pollen tube growth similar to wild-type pollen ( Figure 7 ) , indicating that the PWRKY34: 4myc-WRKY34WT transgene can complement the wrky2-1 wrky34-1 pollen phenotype . In contrast , the function of PWRKY34:4myc-WRKY34SA transgene was significantly compromised . The viability ratio of PWRKY34:4myc-WRKY34SA wrky2-1 wrky34-1 pollen was partially rescued to 67% from 33% of the wrky2-1 wrky34-1 pollen , which was significantly lower than wild-type ( 97% ) and PWRKY34:WRKY34WT complemented pollen ( 90% ) ( p-value <0 . 01 ) ( Figure 7A ) . The double mutant pollen germination rate ( 28% ) was only slightly rescued by PWRKY34:4myc-WRKY34SA ( 37% ) , while it was fully complemented by PWRKY34:4myc-WRKY34WT ( 73% ) , which was similar to wild-type pollen ( 78% ) ( p-value <0 . 01 ) ( Figure 7B ) . Furthermore , the average pollen tube length of PWRKY34:4myc-WRKY34SA wrky2-1 wrky34-1 pollen ( 263 µm ) was about the same as the double mutant ( 288 µm ) and much shorter than the wild-type ( 471 µm ) and PWRKY34:4myc-WRKY34WT wrky2-1 wrky34-1 pollen ( 451 µm ) ( p-value <0 . 01 ) ( Figure 7C ) . These results indicated that although the pollen lethality of the double mutant was partially rescued by WRKY34SA , the pollen function was still abnormal . As a result , we conclude that the phosphorylation of WRKY34 by MPK3/MPK6 is important for the function of WRKY34 protein in vivo . Although the native promoter-driven WRKY34 transgene ( PWRKY34:4myc-WRKY34WT ) could fully complement the wrky2-1 wrky34-1 mutant , immunoblot analysis failed to detect the tagged WRKY34WT protein in the inflorescences or floral buds in these rescued lines ( data not shown ) , which is most likely a result of the low expression level of the native promoter ( Figure 4 ) . To exclude the possibility that mutation of multiple Ser to Ala in WRKY34 altered its general functionality such that the WRKY34SA cannot bind or has reduced DNA-binding activity , we compared the W-box binding activity of the recombinant WRKY34 and WRKY34SA using electrophoretic mobility shift assay ( EMSA ) . As shown in Figure S6 , there was no difference in the W-box binding activity and specificity of WRKY34 after the Ser-to-Ala mutation , suggesting that the reduced functionality of WRKY34SA is not a result of a general loss of WRKY34 function . Based on these results , the phosphorylation by MPK3/MPK6 is important for the function of WRKY34 in pollen development and function . Due to the embryo lethality of mpk3 mpk6 double zygotes [13] , we cannot analyze the phenotype of pollen grains from the double homozygous plants . The mpk3 mpk6 double mutant pollen from mpk3+/− mpk6−/− or mpk3−/− mpk6+/− plants , although it exhibited altered transmission , did not show any developmental defects like wrky2-1 wrky34 pollen [26] . We speculate that in mpk3 mpk6 pollen the unphosphorylated WRKY34 and WRKY2 each retained basal level function , which kept the mpk3 mpk6 pollen above the threshold of visible developmental defects . This is consistent with the finding that WRKY34SA mutant protein can partially complement the wrky2-1 wrky34-1 mutant pollen . Alternatively , MPK3 or MPK6 protein carried over from the microspore mother cells of mpk3+/− mpk6−/− or mpk3−/− mpk6+/− plants , which have at least one good copy of MPK3 or MPK6 , could be sufficient to support the development of mpk3 mpk6 pollen . It is known that MAPKs are very stable proteins in cells . Although both MPK3 and MPK6 are involved in pollen function , MPK6 apparently is more important , as indicated by its much higher expression in pollen ( www . genevestigator . com ) . Therefore , we speculate that the double mutation of mpk6 and wrky34-1 ( or wrky2-1 ) , in which the pollen produced a single WRKY protein with reduced phosphorylation , might result in a weak phenotype in pollen development . As shown in Figure 8 , both mpk6 wrky34-1 and mpk6 wrky2-1 pollen showed developmental and functional defects that were similar to the wrky34-1 wrky2-1 double mutant pollen . The pollen viability was 84% in mpk6 wrky34-1 and 75% in mpk6 wrky2-1 , respectively , which indicated moderate pollen lethality in the double mutants ( p-value<0 . 05 ) ( Figure 8A ) . In accordance , the pollen germination rate was also decreased slightly from an average of 80% of wild-type pollen to 71% of mpk6 wrky34-1 and 63% of mpk6 wrky2-1 ( p-value<0 . 05 ) ( Figure 8B ) . Furthermore , the average pollen tube lengths of mpk6 wrky34-1 and mpk6 wrky2-1 was significantly reduced to 382 µm and 324 µm , respectively , in comparison with the 470 µm of wild-type pollen tubes ( p-value<0 . 01 ) ( Figure 8C ) . This result indicated that the mpk6 wrky34-1 and mpk6 wrky2-1 pollen function was affected and confirmed that MPK6 belongs to the same genetic pathway as WRKY34 and WRKY2 .
A long-standing question is how a MAPK cascade confers signaling specificity in diverse biological events . In yeast and mammals , the mechanisms to maintain signaling specificity of MAPKs include 1 ) cell-type specificity of other signaling components in the pathway , such as receptors , scaffolding proteins , and MAPK substrates [27]–[29]; 2 ) kinetics in signaling strength resulting in distinct outcomes [30]; and 3 ) cross-pathway suppression of downstream components [31]–[33] . However , in plants , such mechanisms have not been well studied . In Arabidopsis , MPK3 and MPK6 , two of the best-characterized MAPKs , function together in diverse biological processes , including plant growth , development , and response to environmental stimuli [12]–[14] , [16] , [26] , [34] , [35] . Differentially expressed substrates could help maintain the functional specificity of the activated MPK3/MPK6 signaling cascade in different cells/tissues . In response to pathogen attacks , MPK3 and MPK6 are activated and phosphorylate a subset of ACC synthase ( ACS ) isoforms to induce ethylene biosynthesis [12] . The pathogen responsive MPK3/MPK6 cascade also induces phytoalexin biosynthesis through the activation of downstream the WRKY33 substrate [9] , [36] . In stomatal development , MPK3/MPK6 phosphorylates SPEECHLESS , a basic helix-loop-helix transcription factor that is specifically expressed in stomatal lineage cells and negatively regulates stomatal formation [10] , [13] . In different biological processes , MPK3 and MPK6 are able to phosphorylate different WRKY homologs , e . g . WRKY33 and WRKY34 in plant defense and pollen development , respectively . Differential tissue/cell-specific expression of WRKY33 and WRKY34 allows the MPK3/MPK6 cascade to control different biological processes . WRKY transcription factors are one of the largest families of transcriptional regulators in plants [17] . Transcriptional regulation by WRKY members is an integral part of signaling networks that modulate many biological processes , most notably in response to diverse biotic and abiotic stresses [37] . WRKY transcription factors also have been implicated in plant growth and development processes , including senescence , seed development , and embryogenesis . For instance , WRKY53 binds to the promoters of a set of senescence-associated genes , and the overexpression or knockdown of WRKY53 gene lead to an altered senescence phenotype [38] . In seed , a WRKY transcription factor , MINISEED3 ( MINI3 ) , recruits a nuclear localized protein SHB1 to activate gene expression , which regulates endosperm proliferation and seed cavity enlargement [39] . The WRKY23 transcription factor is needed for proper root growth and development by stimulating the local biosynthesis of flavonols , which is dependent on auxin through the AUXIN RESPONSE FACTOR 7 ( ARF7 ) and ARF19 transcriptional response pathway [40] . Despite these recent discoveries , it is still unclear whether WRKY transcription factors share similar regulatory networks between environmental responses and developmental processes . Our results suggest that the MPK3/MPK6 signaling module could act as a molecular hub to integrate different signaling networks of WRKY transcription factors , although the upstream signaling cues are different . MPK3/MPK6 and WRKY34 also may integrate stress and developmental signaling in pollen . WRKY34 is involved in cold sensitivity in mature pollen , where it regulates expression of cold-specific transcription factors ( CBF ) [18] . MPK6 is rapidly activated by cold stress . Furthermore , MPK6 signaling is functionally involved in cold and salt stress responses [41] . It is therefore possible that MPK3 and MPK6 may be involved in the WRKY34-mediated cold tolerance in pollen . However , the MPK6 activity is positively related with cold tolerance , while WRKY34 seems to be a negative regulator in this process . More details are required to interpret the role of MPK3/MPK6-WRKY34 signaling module in pollen cold tolerance . WRKY2 plays a redundant role with WRKY34 in pollen development . Unlike WRKY34 , WKRY2 is expressed in various tissues ( Figure 4A ) and is likely to play pleiotropic roles in plant development . For example , the involvement of WRKY2 in embryogenesis and ABA-mediated seed germination has been reported [24] , [42] . In zygote , WRKY2 directly activates the transcription of WUSCHEL RELATED HOMEOBOX ( WOX ) genes to regulate polar organelle localization and asymmetric division [24] . Given that the mpk3 mpk6 double mutant is embryo lethal [13] , it is possible that the MAPK signaling cascade is involved also in the regulation of the WRKY2-WOX signaling pathway . Comparative analysis of WRKY2 activation by MPK3/MPK6 in pollen and embryogenesis would provide further insights into the regulation of WRKY transcription factors in diverse biological processes . Based on the transcriptomic profiles , two periods of temporal gene expression are defined in pollen development , an early phase and a late phase . Expression of “early genes” occurs after meiosis and declines toward pollen maturation , while “late genes” are preferentially expressed in TCP and MP stages [2] , [3] . The vegetative cell early-late transcriptome transition occurs mainly between the BCP and TCP stages , which exhibit not only a significantly reduced number of expressed genes but also a major shift in mRNA populations [2] . WRKY34 has been identified as an “early gene” , and its expression is suppressed by several MIKC* MADS box transcription factors during pollen maturation [5] , [19] . In this report , we found that WRKY34 from LAT52-driven transgene is phosphorylated at the BCP stage and becomes dephosphorylated at the TCP stage . The phosphorylation of WRKY34 is important for its biological function in male gametogenesis . Therefore , we propose that , besides the regulation at the transcriptional level , the post-translational modifications by MAPKs also plays a critical role in controlling the activity of this WRKY transcription factor , especially during early and late phase transition . The abundance of WRKY34 in early pollen development is regulated at both post-transcriptional and post-translational levels . In our assays , even though driven by LAT52 , a promoter specific at later pollen stages [20] , WRKY34 transcript was barely detectable in mature pollen ( Figure S1 ) , suggesting potential regulation of WRKY34 transcripts at the mRNA stability level . Moreover , despite the presence of WRKY34 transcripts at the TCP stage ( Figure S1 ) , WRKY34 protein was absent in MP ( Figure 2B , top panel ) , indicating rapid protein degradation in the process . In support of this conclusion , the abundance of the WRKY34-YFP protein from transgene driven by native WRKY34 promoter showed a similar pattern , as indicated by the YFP fluorescence ( Figure 4 ) . This further demonstrates that the abundance of WRKY34 protein is regulated at multiple levels and is not solely dependent on promoter activity . The protein stability of WRKY34 apparently is not associated with its phosphorylation state , since the abundance of WRKY34SA , an unphosphorylatable form of WRKY34 , followed the same pattern as WRKY34WT protein ( Figure 2C ) . Therefore , there should be a protein degradation pathway regulating WRKY34 protein abundance at late pollen stages that is independent of MPK3/MPK6 . WRKY2 protein appeared to be more stable in mature pollen ( Figure 4 ) . Pollen development involves dynamic transition of gene expression profiles , which requires rapid control of the transcriptional factors involved . The regulation of WRKY34 activity at multiple levels may reflect the complexity of the regulation of key transcription factors in this process .
Arabidopsis thaliana Columbia ecotype ( Col-0 ) was used as the wild type . T-DNA insertion alleles of WRKY34 ( SALK_133019 ) and WRKY2 ( Salk_020399 and SAIL_739_F05 ) were obtained from the Arabidopsis Biological Resource Center ( ABRC ) . Seeds were surface sterilized and imbibed at 4°C for 3 days , then plated on half-strength Murashige and Skoog medium with 0 . 45% Phytagar . Plates were incubated in a tissue culture chamber at 22°C under continuous light ( 70 µE m−2 s−1 ) for 7 days . Seedlings were then transplanted to soil and grown in the greenhouse with a 16-h-light/8-h-dark cycle . In PCR-based genotyping , the presence of the T-DNA and wild-type alleles was detected using LBa1 ( 5′-TGGTTCACGTAGTGGGCCATCG-3′ ) and two gene-specific primers: WRKY2-LP ( 5′-TTTTCTTTTTCACACGTTAAGCC-3′ ) and WRKY2-RP ( 5′-TGTTAGAACACGAATCACCCC-3′ ) for the wrky2-1 mutant , WRKY34-LP ( 5′-AGCTTGAGCCCAAGTTAAAGC-3′ ) and WRKY34-RP ( 5′-GCATGTCTTGGCCAGTACCGGATG-3′ ) for the wrky34-1 mutant . To generate the binary vector with the LAT52 promoter overexpression cassette , a modified version of pBI121 [9] was digested with HindIII and XhoI to replace the CaMV 35S promoter with the LAT52 promoter . To generate the PLAT52-driven 4myc-WRKY34 overexpression construct ( PLAT52:4myc-WRKY34 ) , we amplified the WRKY34 cDNA by using primers WRKY34-F ( 5′-CATATGGCTGGTATTGATAATAAAGCTGCTG-3′ ) and WRKY34-B ( 5′-ACTAGTCAATATCTGTCGTAATCTACTCAACATCTCTCTG-3′ ) . The PCR fragment was cloned into a modified pBlueScript II KS vector with a four-copy myc epitope tag coding sequence at the 5′-end [9] to generate pBS-4myc-WRKY34 construct . The 4myc-WRKY34 fragment was then cloned into the pBI-PLAT52 vector using SpeI and XhoI sites . To generate WRKY34SA cDNA , mutations were introduced into the pBS-4myc-WRKY34 construct by Quick Change site-directed mutagenesis [43] , [44] . Primers used were as following , with mutated residues in lower case: WRKY34-S91A ( 5′-TCTCTTCTCCTGGTCTTgccCCTGCAACTCTGTTAGAG-3′ ) , WRKY34-S87/91A ( 5′-ATCTCTgcTCCTGGTCTTgccCCTGCAACTCTGTTAGAG-3′ ) , WRKY34-S98A ( 5′-CTCTGTTAGAGgcTCCTGTTTTCCTCTC-3′ ) , WRKY34-S108A ( 5′-CTCAAACCCTTTGCTAgCTCAACAACCGGGAAG-3′ ) , WRKY34-S544A ( 5′-GAAGGTGGAACCAGTGgCACCACAACAGGGAC-3′ ) , and their reverse complementary primers . WRKY34SA , with all six Ser residues mutated to Ala residues , was generated by five successive mutagenesis steps and verified by sequencing . To generate the PLAT52:4myc-WRKY34SA construct , the WRKY34SA fragment was cloned into the pBI-PLAT52 vector using SpeI and XhoI sites . To generate the pollen-specific MPK3RNAi construct , the MPK3RNAi sequence , as described previously [13] , was cloned into the pBI-PLAT52 vector between the SpeI and XhoI sites . The construct was introduced into the mpk6-2 mutant [12] , and homozygous transgenic plants were identified as MPK3RNAi mpk6 . To generate the PLAT52: 4myc-WRKY34 overexpression construct with a BASTA selection marker for transformation of a MPK3RNAi mpk6 plant , the PLAT52:4myc-WRKY34 cassette was amplified and partially digested with ApaI and BamHI and then cloned into the pGreenII vector [45] . To generate PWRKY34:WRKY34-YFP and PWRKY2:WRKY2-YFP constructs , genomic fragments of WRKY34 and WRKY2 were amplified . PCR products and pGreenII-YFP plasmid were digested by XhoI and EcoRV , and ligation was performed . All the binary vectors described below were transformed into Agrobacterium strain GV3101 . Arabidopsis transformation was performed by the floral dip procedure [46] , and transformants were identified by screening for kanamycin or BASTA resistance . Fluorescence microscopy was performed with an Olympus IX70 inverted microscope with an ORCA digital camera . Pollen viability was examined using Alexander staining [25] . Pictures were taken on an Olympus Vanox AHBT3 upright microscope with a color digital camera . The FDA staining assay was performed as described [47] . DAPI was used to stain vegetative and generative/sperm nuclei to determine the pollen development . For FDA or DAPI staining of developing pollen , floral buds at each stage were carefully dissected under stereoscope . Anthers were isolated and transferred to a drop of FDA or DAPI solution . A fine needle was used to gently break the anthers , a cover slip was then used to carefully squeeze the anthers to release the pollen . For SEM , fresh pollen grains were coated directly with platinum and observed on an FEI Quanta 600 FEG Extended Vacuum Scanning Electron Microscope . Pollen germination assays were performed as described [48] . For pollen tube length measurements at 7 hour after germination , at least 100 pollen tubes in each sample were determined using ImageJ software [49] . The presented data are an average of 3 biological repeats . For purification of recombinant WRKY34 and its mutant proteins , the WRKY34WT and WRKY34SA cDNAs were cut from the pBS-4myc-WRKY34 constructs with NdeI/SpeI and ligated into the NdeI/NheI cut pET28a ( + ) vector in frame . The constructs were transformed into E . coli strain BL21 ( DE3 ) . The in vitro phosphorylation assay was performed as previously described [12] . Protein extraction was performed as previously described with modification [9] . Open flowers or closed buds at similar stages were collected from 20 inflorescences . The flowers/buds were ground in liquid nitrogen and extracted in 100 µl 1 . 5X SDS loading buffer . A 15 µl sample was loaded to each lane . The numbers of developing/mature pollen grains should be similar among each sample . However , due to the size difference of the flowers/buds at different developmental stages , different amounts of total proteins were present , which is reflected by the different amount of Rubisco large subunit protein in the Coomassie-blue stained control gels . In this experiment , a comparison of WRKY34 protein levels in an equal number of developing/mature pollen grains is better than in an equal amount of total proteins . A Phos-tag reagent ( NARD Institute ) was used for the phospho-protein mobility shift assay to detect in vivo phosphorylated WRKY34 protein as previously described [9] . The multiple sequence alignment of full-length protein sequences was performed using the ClustalW tool online ( http://www . ch . embnet . org/software/ClustalW . html ) . Phylogenetic trees were constructed and tested by MEGA5 based on the neighbor-joining method [50] . Total RNA was extracted from each tissue using RNAqueous ( Ambion Inc . ) according to the manufacturer's instructions . After DNase treatment , µg of total RNA was reverse transcribed , and quantitative PCR analysis was performed using an Optican 2 real-time PCR machine ( Bio-Rad ) . Relative levels of each transcript were calculated after being normalized to the UBC21 or EF1α control . EMSA was performed as previously described [9] . A synthetic DNA oligonucleotide ( 5′-CGTTGACCGTTGACCGAGTTGACTTTTTA-3′ with three W boxes underlined ) was used as a probe . Two complementary strands of the oligonucleotides were annealed and then labeled at the 5′ end using a T4 polynucleotide kinase . Freshly prepared recombinant WRKY34WT or WRKY34SA protein ( 1 µg ) was incubated with 20 , 000–50 , 000 cpm of DNA probe ( 2 pmole ) for 30 min at room temperature in a binding buffer ( 20 mM HEPES , pH 7 . 9 , 0 . 1 µg/µL herring sperm DNA , 0 . 5 mM DTT , 0 . 1 mM EDTA , 50 mM KCl ) in the presence or absence of an unlabeled competitor DNA . The resulting protein-DNA complexes were resolved in 5% non-denaturing polyacrylamide gel in half-strength TBE buffer . Following electrophoresis , the gel was dried onto 3 MM paper and exposed to X-ray film . | Pollen development , or male gametogenesis , is a process by which a haploid uninucleate microspore undergoes cell division and specification to form a mature pollen grain containing two sperm cells . The highly defined cell linage makes pollen development an ideal model to understand the regulation of plant cellular development . Pollen development has multiple phases and involves dynamic changes in gene expression , which highlights the importance of transcription factors and their regulatory pathway ( s ) . In this report , we demonstrate that WRKY34 and WRKY2 , two closely related WRKY transcription factors in Arabidopsis , play important roles in pollen development . WRKY34 is phosphorylated by MPK3/MPK6 , two functionally redundant mitogen-activated protein kinases ( MAPKs or MPKs ) , at early stages in pollen development . Utilizing a combination of genetic , biochemical , and cytological tools , we determined that this MAPK-WRKY signaling module functions at the early stage of pollen development . Loss of function of this pathway reduces pollen viability , and the surviving pollen has poor germination and reduced pollen tube growth , all of which reduce the transmission rate of the mutant pollen . This study discovers a novel stage-specific signaling pathway in pollen development . | [
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... | 2014 | Phosphorylation of a WRKY Transcription Factor by MAPKs Is Required for Pollen Development and Function in Arabidopsis |
Understanding how neurons cooperate to integrate sensory inputs and guide behavior is a fundamental problem in neuroscience . A large body of methods have been developed to study neuronal firing at the single cell and population levels , generally seeking interpretability as well as predictivity . However , these methods are usually confronted with the lack of ground-truth necessary to validate the approach . Here , using neuronal data from the head-direction ( HD ) system , we present evidence demonstrating how gradient boosted trees , a non-linear and supervised Machine Learning tool , can learn the relationship between behavioral parameters and neuronal responses with high accuracy by optimizing the information rate . Interestingly , and unlike other classes of Machine Learning methods , the intrinsic structure of the trees can be interpreted in relation to behavior ( e . g . to recover the tuning curves ) or to study how neurons cooperate with their peers in the network . We show how the method , unlike linear analysis , reveals that the coordination in thalamo-cortical circuits is qualitatively the same during wakefulness and sleep , indicating a brain-state independent feed-forward circuit . Machine Learning tools thus open new avenues for benchmarking model-based characterization of spike trains .
Investigating how the brain operates at the neuronal level is usually addressed by the specification of neuronal responses to an experimentally measurable variable or by the quantification of the temporal coordination of neuronal ensembles [1 , 2] . Using various methods , the responses of single neurons can be characterized by the tuning curves based on a single measurement ( i . e . average firing rate as a function of the observed value ) [3 , 4 , 5] , with generalized linear models accounting for the coding of multiple features [6 , 7] , biophysical models of spike train generation [8] or information measures and reverse reconstruction [1 , 9] . The coding of information in the brain relies on the coordinated firing of neuronal population [2 , 10 , 11 , 12] . The development of dense electrode arrays [13 , 14] and imaging techniques [15 , 16] in awake animals now allows monitoring of the activity of large ensembles of neurons and to address fundamental questions about neuronal network coordination . Neuronal interactions , in relation to behavior or internal parameters ( e . g . brain states ) , are evaluated by the statistical dependencies of spike trains , the most widely used method being linear cross-correlations [17] . These linear measures can be generalized to population correlation with tools such as Principal Component Analysis ( PCA ) [18 , 19] and Independent Component Analysis [20] . Generalized linear models were used to build predictions of single spike trains as a function of the peer network activity [6] and to provide a full statistical description of spatio-temporal neuronal responses and correlations [21] . Methods from graph theory offer ways to compare interactions at the network level across experimental conditions [22] . Finally , among the large body of available tools , evaluating neuronal coupling by fitting spiking activity to Ising models has provided key insights into the nature of neuronal coordination in a population [23 , 24] . The majority of the methods enumerated above rely on a set of assumptions regarding the statistics of the data or the biophysics of neuronal spiking , among others , while seeking explanatory power . To assert the validity of a particular approach , the usual procedure is to divide the data set into a training set , used to fit the model parameters , and a test set , on which the likelihood of the model is evaluated . However , this method , called cross-validation , does not rule out the possibility that a particular fit of the model parameters , even when leading to high likelihood , corresponds to the wrong model . For example , the omission of a key feature in the model may attribute erroneous contribution to the set of chosen variables . These limitations arise from the lack of ground-truth data that in the most complex ( and , therefore , interesting ) cases represent an unreachable goal . This lack of ground-truth data when performing data analysis is particularly unavoidable in neuroscience [25] . It has thus become necessary to establish standard , model-free methods that , even if they do not contribute to our understanding of the data , set levels of performance that may be used to benchmark model-based approaches [26 , 27] . Machine Learning provides a large array of techniques to classify datasets that have demonstrated high level of performance in fields ranging from image processing to astrophysics [28] . Using a supervised classifier , so-called gradient boosting [26 , 27] , we show how this method can determine an encoding model for predicting population spike trains knowing the stimulus input . We also show , in line with recently published work [27] , how gradient boosted trees ( XGB ) can also be used as a very efficient decoding model that is retrieving the stimulus likelihood knowing the spiking activity of a population of neurons . Finally , we demonstrate how it generates a very accurate encoding model for predicting a population spike train conditioned on another , anatomically projected , set of neuronal activity [6] . We tested the validity of the approach on data from the head-direction ( HD ) system [5 , 29 , 30] , a sensory pathway whose member neurons , the so-called HD cells , emit spike trains that can be explained with high accuracy simply by the direction of the head of the animal in the horizontal plane . Decision trees maximized their branching in input ranges where Fisher Information was maximal . We then determined the optimal parameters of the method for our data set . Finally , we applied this method to simultaneously recorded neurons in the thalamo-cortical network of the HD system , namely in the antero-dorsal nucleus of the thalamus ( ADn ) and the Post-subiculum ( PoSub ) . We demonstrate that non-linear encoders such as boosted gradients , but not linear analysis , reveal that thalamic neurons lead cortical neurons in a brain-state independent manner .
Machine Learning literature defines boosting as the combination of many weak classifiers with limited prediction performances in order to build a stronger classifier . The first boosting algorithm is AdaBoost ( Adaptive Boosting ) [31] which trains weak learners using a distribution of weight over the training set . This distribution of weight is updated after the convergence of a weak learner in order for the next weak learner to focus on the difficult examples i . e . the points that are hard to classify . Boosting algorithms come in different flavors for the type of learners or the updating of the weights [32 , 33] . Here we focused on the boosting using the decision tree model as the weak learner . The goal of the gradient boosted trees algorithm is to determine the optimal successive partition of features space in order to assign a weight or a label to a subset of the training examples . This algorithm is thus equivalent to decision trees in which input features are optimally segmented to determine a desired output . The problem is now to apply this reasoning to predict the spiking of neurons based on behavioral features and , conversely , to decode behavioral feature from a population of neurons coding for an internal representation of this feature . Lastly , this algorithms can be useful to predict the spike train of a given neuron from the spiking activity of an upstream neuronal population . Practically , we first defined the training set [ ( x1 , y1 ) , … , ( xm , ym ) ] where xi ∈ Rd is the i-th training example with d different features and yi is the target value . In this study , we focus on two different types of features: ( 1 ) behavioral features , in particular the HD and position of the animals and ( 2 ) spiking activity of neuronal ensembles . The goal of the learner reduces to how to make an accurate prediction y ^ i given xi and the correct value yi . A target value yi for a given training example xi is a spike count over a finite time bin for one neuron . Assuming neuronal spiking follows an inhomogeneous Poisson distribution , we thus defined the prediction of the model as: p ( y i = k | λ ) = λ k k ! exp - λ ( 1 ) for a given intensity parameter λ = λ ( xi ) , the single parameter of a Poisson distribution . We defined y ^ i for each training example as the prediction of the learning algorithm . This value corresponds to the mean of the predicted Poisson distribution . The measure of the performance of the model is made through an objective function O ( θ ) = L ( θ ) + Ω ( θ ) that sums the training loss L and the regularization term ( penalty for complexity ) Ω . The training loss to be minimized is then defined as the negative log-likelihood over the full set: - L ( θ ) = - ∑ i [ y i l o g ( y ^ i ) - y ^ i ] ( 2 ) also known as the Poisson loss . For the regularization term Ω , the complexity of the tree set was defined as Ω ( f ) = γ T + 1 2 λ ¯ ∑ j = 1 | L e a v e s | w j 2 ( 3 ) where T is the total number of leaves and wj the score of leaf j . γ and λ ¯ are two free parameters weighting the contribution of the two previous items in the objective function . For the sake of comparison with a related study [27] , we used the same values: γ = 0 . 4 and λ ^ = 0 . 0 . However , in the following section detailing the methods , we keep these two parameters as variables . To minimize the objective function , the learning algorithm must find the optimal set of split values and the optimal set of leaf values for each tree . An efficient strategy is thus to optimize trees sequentially i . e . the input of a tree is the output of the previous tree . After optimizing the t − 1 trees , the prediction at tree t is y ^ i t = y ^ i t - 1 + f t ( x i ) ft the function that maps the xi example onto the right leaf through the succession of tree partition . By taking advantage of the fact that the same score is assigned to all the input data that fall into the same leaf , the objective function can be transformed from a sum over the training set to a sum over the leaves set: O t ≈ ∑ j = 1 | L e a v e s | t [ ( ∑ i ∈ I j t g i ) w j + 1 2 ( ∑ i ∈ I j t h i + λ ) w j 2 ] ( 4 ) + γ | L e a v e s | t ( 5 ) The index function Ij = {i|f ( xi ) = wj} maps each training point xi to the corresponding leaf j while gi and hi are respectively the first order and second order derivatives of the loss function . In the case of Poisson regression , the gi and hi are defined as: g i = e y ^ i - y i ( 6 ) h i = e y ^ i ( 7 ) Finally , the sum of wj and w j 2 in Eq 5 is quadratic , which allows us to compute the optimal w j * and the corresponding best objective value O * ( w j * ) = - 1 2 ∑ j = 1 | L e a v e s | G j 2 H j + λ + γ | L e a v e s | ( 8 ) with G j = ∑ i ∈ I j g i and H j = ∑ i ∈ I j h i . The best tree structure is then found by sequentially splitting the features space , with each splitting position corresponding to the maximum gain: G a i n = 1 2 ( G L 2 H L + λ + G R 2 H R + λ - G R 2 + G L 2 H R + H L λ ) - γ ( 9 ) The gain for one split is a measure of fit improvement . It is the difference between the scores of the new leaves ( subscripts R , L: right and left leaves , respectively ) after the split and the score of the previous leaf . Details of the derivative steps and full explanations of the algorithm can be found in [34] . An example of the gradient boosted trees algorithm is shown in Fig 1 for a non-linear tuning curve ( blue curves Y ) . For each tree sequentially optimized ( 1 , 2 and 10 shown ) , the algorithm splits the tuning curve at different positions ( X0 , X1 , X2 , X3 , … ) and assigns a leaf score between each split . By iterating this procedure , the predicted firing rate ( black curves Y ^ ) progressively converges to the actual firing rate . To estimate the quality of a model , we used the pseudo-R2 score: p R 2 = 1 - ( y log y - y ) - ( y log y ^ - y ^ ) ( y log y - y ) - ( y log y ¯ - y ¯ ) ( 10 ) with y the target firing rate , y ^ the prediction , y ¯ the mean firing rate [35] . A value of 1 indicates a perfect model that reproduces entirely the dataset while a value of 0 indicates a model that is no better than the average value of the training set . To compute the pseudo-R2 score , the data set was divided into a training set and a test set , a procedure known as cross-validation , that prevents the model from over-fitting the training set . For all the predictions of firing rates , we used an 8-fold cross-validation , i . e the training set was divided into 8 discontinuous partitions with each one serving successively as the testing set . For each spiking activity predicted for one neuron , this procedure yields eight pR2 that were averaged . This mean pR2 served as a measure of performance of different techniques that were tested . In the present manuscript , we compare the prediction performance of XGB with three other methods . To this end , we computed the pseudo-R2 obtained with each method in an 8-fold cross-validation procedure . First , we tested a linear regression model between the animal’s HD and the binned spike trains . However , this method necessarily fails as the relation between the HD ( an angular value ) and the number of spikes emitted by HD cells is , in general , not linear . Therefore , we next linearized the HD by projecting the HD angular values on the first six harmonics of 2pi ( called the 6th order kernel in Fig 2B ) and performed a linear regression with binned spike trains . Thus , a training point xi corresponding to the direction θi is defined as a 12-dimensional input vector: xi = [… , cos ( kθi ) , sin ( kθi ) , …] for k in [1 , … , 6] . Finally , we tested a ‘model-based’ method: the tuning curve of a given HD neuron was computed from the training set and then used to predict the firing rate of the neuron in the test set . Fisher Information ( FI ) is directly related to the variance of the most optimal decoder and can be computed , under the assumption of a Poisson Process , directly from the tuning curve [36] . For recall , FI ( x ) = ( df/dx ) 2/f ( x ) with f ( x ) the firing rate at position x of the input feature . In practice , the Fisher Information was reduced to the squared slope of the line fitted between three successive bins of the tuning curve divided by the firing rate of the middle bin . Neuronal recordings that are analyzed in this report were described in a previously published paper [30] and are available for download ( https://crcns . org/data-sets/thalamus/th-1/ ) . Briefly , multi-site silicon probes ( Buzsaki32 and Buzsaki64 from Neuronexus ) were inserted over the antero-dorsal nucleus ( ADn ) of the thalamus in 7 mice . In three of these animals , a second probe was lowered to the post-subiculum ( PoSub ) . During the recording session , neurophysiological signals were acquired continuously at 20 kHz on a 256-channel Amplipex system ( Szeged; 16-bit resolution , analog multiplexing ) . The wide-band signal was downsampled to 1 . 25 kHz and used as the local-field potential signal . To track the position of the animals in the open maze and in their home cage during rest epochs , two small light-emitting diodes ( LEDs; 5-cm separation ) , mounted above the headstage , were recorded by a digital video camera at 30 frames per second . The LED locations were detected online and resampled at 39 Hz by the acquisition system . Spike sorting was performed semi-automatically , using KlustaKwik ( http://klustakwik . sourceforge . net/ ) . This was followed by manual adjustment of the waveform clusters using the software Klusters ( http://neurosuite . sourceforge . net/ ) . In animals implanted over the antero-dorsal nucleus , the thalamic probe was lowered until the first thalamic units could be detected on at least 2-3 shanks . The thalamic probe was then lowered by 70-140 μm at the end of each session . In the animals implanted in both the thalamus and in the post-subiculum , the subicular probe was moved everyday once large HD cell ensembles were recorded from the thalamus . Thereafter , the thalamic probes were left at the same position for as long as the quality of the recordings remained high . They were subsequently adjusted to optimize the yield of HD cells . To prevent statistical bias of neuron sampling , we discarded sessions from analysis that were separated by less than 3 days during which the thalamic probe was not moved . In all analyses , spike trains were binned in 25 ms bins and smoothed with a 125 ms kernel , unless stated otherwise . The only exception is for decoding which was performed with bins of 200 ms . The animal’s HD was calculated by the relative orientation of two LEDs ( blue and red ) located on top of the head ( see [30] for more details ) . The HD tuning curve of a neuron is the ratio between the histogram of spike counts as a function of HD ( 60 bins between 0 and 2π ) and total time spent in each bin of HD . For a given angular bin ϕi , the average firing rate is thus: f ( ϕ i ) = 1 T ∑ t n t δ ( ϕ i , ϕ t ) ∑ t δ ( ϕ i , ϕ t ) ( 11 ) where δ ( ϕi , ϕt ) = 1 if , at time t , the angular HD ϕt is equal to ϕi ( δ ( ϕi , ϕt ) = 0 otherwise ) , nt the number of spikes counted in the tth time bin and T = 25ms ( the time bin duration ) . The goal of Bayesian decoding in this study is to predict the HD of the animal given the spiking activity of recorded neurons . Let n = ( n1 , n2 , … , nN ) be the numbers of spikes fired by the HD neurons within a given time window ( 200 ms ) and Φ the set of possible angular direction between 0 and 2π . The algorithm computes the probability P ( Φ|n ) using the classical formula of conditional probability: P ( Φ | n ) = P ( n | Φ ) P ( Φ ) P ( n ) ( 12 ) Assuming the statistical independence of HD neurons and the Poisson distributions of their spikes , the probability P ( n|Φ ) can be evaluated as: P ( n | Φ ) = ∏ i = 1 N P ( n i | Φ ) = ∏ i = 1 N ( τ f i ( Φ ) ) n i n i ! e x p - τ f i ( Φ ) ( 13 ) with τ the length of the time window and fi ( Φ ) the average firing rate of cell i at position Φ . The full detail of the algorithm can be found in [37] . When using XGB for decoding the HD , we set the algorithm to do multiclass classification: the algorithm returns the predicted probabilities that population vector n ( a vector of spike count of each neuron ) belongs to each ‘class’ Φ = ( ϕ1 , ϕ2 , … , ϕk ) , i . e . 60 bins of HD . Briefly , learning of the decoder is achieved by minimizing the so-called ‘logarithmic loss’ computed as l o g l o s s = - 1 N ∑ i = 1 N ∑ j = 1 K y n i , ϕ j l o g ( p ( n i ∈ ϕ j ) ) where N is the number of data points , K the number of classes ( 60 bins of HD in our case ) , y n i , ϕ j = 1 if the data point ni is in class ϕj and 0 otherwise , and p ( ni ∈ ϕj ) is the predicted probability that observation ni is in class ϕj . Thus , a perfect classifier would have a null log loss ( for each data point , there is one and only one class that has a probability p = 1 and that is correctly labeled , i . e . y = 1 ) . To attest the robustness of our analyses , the methods presented in this study were tested on an emulation of spiking neuronal ensembles using the Brian simulator [38] . The network is composed of two layers of Poisson spiking neurons ( PADn and PPoSub ) and one layer of integrate-and-fire neurons ( IPoSub ) . Poisson spiking neurons were individually parameterized by angular tuning curves . We used the actual HD of an exploration session ( 20 min ) to generate a time-array of firing rate per neuron , at every time step of the simulation . Integrate-and-fire neurons follow a stochastic differential equation: d v d t = - v τ ( 14 ) with the membrane time constant τ = 50ms for all simulations . We set the spiking voltage threshold v = 1 and after-spike reset to v = 0 and no refractory period . The simulated integrate-and-fire neurons IPoSub , emulating spiking activity of observed PoSub neurons , received two sets of inputs . First , an input mimicking their actual tuning curve , each IPoSub neuron receiving a connection from one PPoSub neuron with a weight of 0 . 9 . In other words , each integrate-and-fire IPoSub neuron had a unique mirror Poisson spiking neuron in the PPoSub layer that provides major driving input depending on the angular HD . The second set of synapses to IPoSub were from a population mimicking ADn neurons , PADn , with full connectivity ( i . e . IPoSub receives inputs from all PADn neurons ) . The weights of the connections from PADn units and a given IPoSub neuron were parameterized by the angular distance between the preferred direction of the IADn and its pre-synaptic PADn neurons . More specifically , for two neurons i and j with respective preferred angular directions ϕi and ϕj , the synaptic weight is defined as: w i j = α e β ( c o s ( ϕ i - ϕ j ) - 1 ) ( 15 ) with α = 0 . 1 and β = 10 . The analyses presented in this report were run on Matlab ( Mathworks , 2017 ) and Python . Code is available online in a raw form and as a Jupyter notebook to present some of the analyses ( www . github . com/PeyracheLab/NeuroBoostedTrees ) . Gradient boosting was implemented with the XGBoost toolbox [34] .
We applied gradient boosted trees ( XGB ) to the prediction of spike counts from HD neurons recorded in ADn and PoSub ( see Methods and Fig 2A for a full display of the training process ) . Since the HD signal is a well-characterized signal relative to the angular direction of the animal’s head , we compared the prediction of XGB with the output of the model-based ( MB ) tuning curve ( that is , the firing rate expected from the HD of the animal knowing the tuning curve; see Fig 2B ) . The comparison shows that XGB reaches the same level of performance as MB for both ADn and PoSub . We then tested a generalized linear regression model with raw HD values or a 6th order kernel . In the first case , the model learns only from the angular features θ ranging from 0 to 2π . In the second case , the model learns with all the k harmonics ( cosθ , sinθ , … , coskθ , sinkθ ) . A 6th order projection was used as it can fit the typical width of a HD cell tuning curve ( approximatively 60 degrees at half peak ) . Not surprisingly , the simple linear model showed negative or null performances for both anatomical structures , because the relationship between a raw angular value and a binned spike train is unlikely linear ( Fig 2B ) . Preprocessing of the angular feature ( with the 6th order kernel ) increased the performance to the same levels as XGB and MB . In comparison with XGB , linear models and MB are straightforward models in terms of numbers of free parameters . We thus performed a grid-search to find the optimal number of trees and depth of each tree to find the best estimate of the performance , measured by the pseudo−R2 ( see Methods ) . A Bayesian Information Criterion ( BIC ) score ( Fig 2C ) was used to compare grid points . The BIC score was defined as BIC ( |Trees| , Depth ) = ( |Trees| + Depth ) log ( n ) − 2log ( L ) with n the number of time steps in the data training set and L the likelihood of the model . By penalizing more complex models using this approach , we found that 100 trees with a maximal depth of 5 were sufficient to predict spike trains for all neurons ( Fig 2C and 2D ) . Once the relationship between a behavioral feature and spiking activity has been learned , XGB can be used to decode the internal representation of this feature based on population spiking activity . We thus tested its performance on the decoding of the HD signal distributed over population of HD cells . To this end , spiking activity was binned in 200ms windows and XGB was trained and compared to a Bayesian decoding method , a technique widely used for such tasks [30 , 37] , that predicts the probability of having a particular HD at each time step based on the instantaneous spike count in the population . For both algorithms , 60 angular bins were used to predict the HD . We parametrized the gradient boosted trees to use the multi-class log-loss that outputs a probability of being in a certain class or not ( see Methods ) . We decoded the HD signal in sessions that contained more than 7 neurons in both ADn and PoSub ( n = 5 sessions , two animals ) . An example of 30 second decoding for XGB is shown in S1A Fig . Gradient boosted trees and Bayesian decoding show similar performances when using ADn activity as a feature while gradient boosted trees slightly outperforms Bayesian decoding for PoSub activity ( S1B Fig ) . In addition , we observed that the decoding of the HD from ADn firing rate outperforms the decoding of the head direction using PoSub activity . This observation was consistent for both methods . Gradient boosting , as most Machine Learning tools , can be considered a black box that achieves high levels of performance while the particular details of the learning procedure remain unknown . However , it is possible to retrieve the thresholds at which trees split the data to predict the target output ( as shown in Fig 1 ) . In the case of HD cells , whose firing was directly predicted from the HD of the animals , splits concentrated on HD values where the tuning curves were the steepest ( see examples of Fig 3A ) . In fact , the density of splits is strongly correlated with the Fisher Information ( Fig 3B ) , a measure that is related , but not equal , to tuning curve steepness and that estimates the variance of an optimal decoder [36] . Many neurons of the brain’s navigation system exhibit correlates to more than one behavioral parameters , for example HD and place [39 , 40 , 41] . We thus predicted spike trains based on the three observed behavioral features , assuming they were independent: x and y positions of the animal randomly foraging in the environment , as well as the HD . We thus increased the feature space and dissected the resulting splitting distribution of the gradient boosted trees . In average , the density of splits along the ( x , y ) coordinates was the highest in the corner of the environment ( Fig 3C and 3D ) where animals naturally spend a large amount of time . Analysis of the distribution of splits reveals that the HD feature was more segmented than the ( x , y ) coordinates for both ADn and PoSub ( Fig 3E , left ) , showing that HD neurons in both ADn and PoSub are primarily driven by HD . Nevertheless , we observed that the proportion of positive splits relative to angular splits was slightly higher for PoSub when compared to ADn . One potential issue with this approach is that training a large number of trees overfits the learning procedure: it is optimal for decoding performance but not necessarily for the interpretability of the tree structure . To best explain the contribution of various features to the spiking activity , it is sometimes more suited to concentrate on the structure of a smaller number of trees , and examine the ‘gain’ of each feature when training the first trees . In fact , the average gain ( see Eq 9 ) for each feature decreases exponentially as the number of trees increases ( S2 Fig ) . In addition , we found that random features were also more split as the number of trees increased ( S3 Fig ) . For all these reasons , we restricted our analyses to the characteristic decay constant of the gain as a function of number of trees ( S2 Fig ) , i . e . 30 trees with a depth of 2 . Shifting from split density to gain analysis , we thus demonstrate that the gain of spatial features ( x and y position ) was approximatively three times higher for PoSub neurons compared to ADn neurons ( Fig 3E right ) , in agreement with previous studies that employed model-based methods ( i . e . that assumed various properties of spike trains and sampling of the feature space ) [39 , 40] . To assess that the advantage of angular information over spatial information was not caused by a difference in the trajectories of the animals ( i . e sub-sampling of some portions of the 2 dimensional space ) , we generated , for each neuron , artificial spike trains sampled from either the angular or spatial tuning curves . In the case of angular tuning curve sampling , we found qualitatively the same gains for PoSub and ADn neurons ( Fig 3F , left ) . When sampling the spatial tuning curves to generate artificial spike trains , gains for spatial features were higher than for HD , as expected ( Fig 3F , right ) . However , the difference with HD gains was small , and the gains were not different for ADn and PoSub neurons , indicating that the place fields of these two classes of neurons do not convey much spatial information . Thus , we concluded that XGB , when used appropriately , is an efficient method for determining the relative contribution of various features to a series of spike trains . Brain functions arise from the communication of neurons with their peers in local and downstream networks . However , how these interactions take place remains largely unknown . With this question in mind , we thus applied XGB to neuronal peer-prediction , that is learning to estimate the spiking activity of one neuron as a function of the activity of a population of other , presumably anatomically-related neurons ( [6 , 21 , 30] ) . For each session that contained at least 7 neurons in both ADn and PoSub , the model learned all possible group combinations ( ADn to ADn , PoSub to ADn , PoSub to PoSub , ADn to PoSub ) . This learning was performed with no spike history , i . e . the bins used as features were synchronous to the bin predicted . For intra-group prediction , the target neuron was removed from the pool of feature neurons . Tested during wake , REM and non-REM sleep , we found that peer-prediction had the highest prediction score between ADn neurons and the lowest score between PoSub neurons ( Fig 4A ) . Inter-group predictions were similar . In all cases , scores during non-REM sleep were systematically lower than during wakefulness and REM , in agreement with previous analysis of peer-prediction in thalamo-cortical assemblies [30] . An uneven number of feature neurons is a potential confound in peer-prediction analysis . The prediction process was thus repeated by equalizing the number of neurons in both structures and it yielded scores similar to the original analysis ( Fig 4B ) . The activity within ADn is therefore more predictable than in the PoSub . To best capture the statistical dependencies between spikes trains , we focused on a gain analysis ( i . e . from the branching structure resulting from learning on only 30 trees with a depth of 2 ) and we found that the angular distance was a weak predictor of the split density for both ADn and PoSub ( Fig 4C ) . In others words , gradient boosted trees tend to split preferentially , yet mildly , the instantaneous firing rate of feature neurons that have a preferred direction closer to the target neuron . More surprisingly , we found no correlation between the mean firing rate of neurons and the density of splits ( Fig 4D ) . Feature data from neurons with high firing rates are characterized by a wider range of values to be split , yet , this does not lead to increased splitting . Thus , all neurons contributed to the prediction of the activity of another neuron despite each idiosyncratic spiking activity . While the HD signal is aligned with the actual heading of the awake animal in the PoSub , the spiking of HD cells in the ADn are best explained by the future heading of the animal , by about 10-50 ms [42 , 43] . This finding suggests that the neuronal activity in the ADn should lead PoSub spiking at least during wakefulness , perhaps in all brain states . We thus tested the ability of XGB to reveal the temporal constraints of neuronal communication across brain areas compared to the classical cross-correlation of spike train pairs . One issue with linear cross-correlation analysis is that it is dominated by the slow dynamics of the underlying signal and , while the HD signal has comparable dynamics during wake and REM sleep , it is accelerated during non-REM sleep [30] . During wakefulness and REM , cross-correlations do not reveal clear bias in the temporal organization of the ADn to PoSub communication . Furthermore , a Principal Component Analysis of the cross-correlograms reveals that , overall , cross-correlograms of thalamo-cortical pairs of neurons are rather good indicators of the ongoing brain state ( Fig 5A , left ) . Finally , the sign of the correlation between HD neurons depend , in all brain states , on the angular difference of their preferred direction [30] . Thus , cross-correlograms are in average flat ( Fig 5A , right ) , and the overall effect can only be captured by the study of the variance of the cross-correlograms . The variance of the corr-correlograms shows a slight biases for negative latencies from ADn to PoSub ( insets in Fig 5A , right ) , but , again , the variance profile ( and thus its resolution ) depends on the brain states . Can XGB reveal the temporal component of neuronal communication across brain areas ? To investigate this question , XBG was run for peer-prediction of individual PoSub neurons from multiple copies of ADn population activity at various time-lags . In other words , the model learned the relationship between the firing rates of feature neurons from time t − T to t + T ( in Fig 4A , the model had access only to time t ) . A graphical explanation of this procedure is shown in S4 Fig . Using only raw , unsmoothed spike counts , we found that the gain ( the number of splits multiplied by the mean gain ) was maximal at -25 ms when predicting PoSub firing rate with ADn activity ( Fig 5B ) , in agreement with the anticipation delay of ADn HD neurons [42 , 43] . The distribution of transmission delays was only weakly dependent on brain states , suggesting a hard-wired , internally organized circuit ( Fig 5B ) [30] . To assess that gradient boosting can determine temporal shifts between spike trains of neurons in vivo , independent of brain-state dynamics ( i . e . feature dynamics ) , we further tested the methods with smulations of spiking networks [38] . We first sought to replicate the temporal delay between ADn and PoSub shown in Fig 6A ( see Methods ) . To this end , we used HD tuning curves and the animal’s HD to generate series of spike trains in an artificial population of ADn and PoSub neurons . Those neurons are Poisson spiking neurons parameterized at each time step only by the instantaneous firing rate read from the angular tuning curves , thus referred to as T ( ADn ) and T ( PoSub ) . We then modeled a population of PoSub integrate-and-fire neurons that receive one-to-one inputs with a fixed weight from T ( PoSub ) and multiple inputs from T ( ADn ) with synaptic weights inversely proportional to the angular distance ( Fig 6A ) . As shown in Fig 6B for four neurons of each layer , the neurons of PoSub fired whenever the animal’s HD crossed their angular tuning curves . To demonstrate that PoSub neurons integrate information that is related to the tuning curves of T ( ADn ) , we showed the cross-correlation between each pair of neurons from the two layers , sorted by their preferred angular direction ( Fig 6C ) . As with cross-correlations of pairs of real HD neurons [30] , pairs of HD neurons with overlapping tuning curves show positive correlations ( i . e . peaks in the cross-correlgrams ) and pairs of opposite preferred directions show negative correlation ( i . e . dip in the cross-correlograms ) . As expected , the average cross-correlogram is flat ( inset in Fig 6D ) . To reproduce the observation that the temporal width of cross-correlations was smaller for non-REM sleep than for REM sleep and wake , we gradually changed the speed of the animal’s HD in input . As expected , the temporal width of cross-correlations was primarily driven by the feature dynamics as shown in Fig 6D for an angular speed accelerated four times . When doing peer-prediction with XGB as in Fig 5B , we observed that the prediction of time lag remained qualitatively the same when the angular speed was accelerated four times ( Fig 6E ) . We quantified the decrease of temporal width in the cross-correlogram for four different speeds with an exponential decay fit ( Fig 6F ) and the full width at half maximum ( FWHM , Fig 6G ) . In contrast , the FWHM resulting from XGB remained constant across conditions ( Fig 6G ) . Could the model confirm that XBG accurately tracks synaptic delays ? Even when synaptic transmission delay was set at 0 ms , the variance of the cross-correlograms was slightly shifted at negative time lags ( Fig 6D ) , unlike the XGB gain ( Fig 6E ) . This suggests that linear cross-correlations , but not XGB , is biased by the integration time constant of the post-synaptic neuron . In addition , we observed that changing the intrinsic transmission delay was fully captured by XGB ( Fig 6H ) . In conclusion , applying gradient boosted trees on neuronal ensembles reveals intrinsic temporal organization of the circuit , independent of the brain-state specific dynamics of the underlying features .
We first sought to validate the approach of learning a predictive model of spike trains from behavioral data with a decision tree learning algorithm that does not include a predefined model of the training set . To this end , we analyzed a dataset of HD cells [5 , 30] , whose firing in relation to behavior is among the best characterized signals in the mammalian nervous system . We demonstrated first that gradient boosted trees predicts the firing of the neurons with high accuracy by establishing a direct correspondence between the raw behavioral data ( in this case the HD angular value alone ) and the instantaneous spiking of the neurons ( Fig 2 ) . Using a Generalized Linear Model to regress the spiking activity of a neuron on raw behavioral data , such as the HD angular values , necessarily fails as this relationship is not generally linear . It is thus necessary to project the raw data on a set of orthogonal functions that linearize the inputs . Therefore , we used a basis of trigonometric functions up to the 6th order that can , in theory , capture the typical width of a HD cell tuning curve ( approximatively 60 degree width ) . In this case , the prediction performance was similar to XGB . The same type of transformation has been applied previously , for example Zernicke’s polynomials for position values in a circular environment [47] . However , it is clear from these two examples that one major strength of XGB is to generalize prediction to all possible behavioral data ( e . g . not depending on the particular shape of an environment for position data ) . Finally , the performance of XGB was similar to a model-based approach ( i . e . prediction of the firing rate on test data based on the tuning curve of the training set ) . This is not surprising for a class of neurons whose spiking activity is explained so well by an experimentally tractable signal . However , in general , tuning curves for even well defined neuronal responses explain actual spike trains only partially and XGB may well capture previously undetermined sources of variance . Although XGB can be viewed as a model-free technique that does not assume any particular statistics or generative model of the input data , the procedure still depends on a limited set of free parameters that need to be tuned for optimal performance . To facilitate the use of this classifier for future studies and assure reproducibility of analyses across laboratories , we systematically explored the parameter space for depth and number of trees for spike train prediction . When computing prediction performance ( measured by the pseudo-R2 ) , we found that minima were well localized , for all neurons , using the BIC score that penalizes over-complex models . More specifically , we show how the use of multiple trees ( approximatively 100 ) , each limited in depth ( typically five branching ) , was an optimal choice of parameters . Importantly , these optimal parameters did not seem to depend on a neuron’s intrinsic parameters ( e . g . firing rates ) and there was no obvious trade-off between tree depth and number of trees ( the two optimal values were independently distributed across neurons ) . While the structure of a multi-layered neural nets ( or other forms of deep architecture ) after learning the classification of a dataset is notoriously unanalyzable [48 , 49 , 50] , we show how the branching of the decision tree may be highly informative on how input data are matched to their output targets . The density of splits ( or branching ) across the series of trees was maximal in the range of inputs where firing rates vary the most . This could be interpreted as a maximum data splitting around the maxima of Fisher Information which is , for a Poisson process , directly related to the change in firing rate as a function of stimulus value , that is when spike trains are most informative about the encoded signal [36 , 51] . Although the relationship between tree branching and Fisher Information is , in our study , purely empirical , it is interesting to show , again , that unraveling the tree structure allows the understanding of how the data are learned by gradient boosting . In the case of neuronal peer-prediction , analyzing the structure of gradient boosted trees presents the advantage that all kinds of neuronal interactions ( positive , negative , linear or monotonically non-linear ) yield comparable estimates ( when quantifying split density or gain ) . This is in contrast with classical correlation analyses of individual spike trains relative to a population of peers that may be hard to interpret in certain cases where these interactions are both negative and positive ( [52 , 53] . As we show here , linear correlations are also directly affected by the ongoing brain dynamics . In addition , fitting spiking data to maximum entropy ( i . e . Ising ) models have revealed that linear correlations may not indicate the true coordination between spike trains [23 , 24] . The analysis of tree branching provides an estimate of the statistical dependencies between spike trains , independent of the underlying type of interaction and without assuming a particular transfer function for the target neuron [6] . The nature of neuronal coordination as observed from spike trains is still debated , for example in the hippocampus [54] , and unbiased , model-free methods may be highly informative on the nature of the actual statistical dependencies between neurons . We also report an optimal range of tree number that should be used for split analysis when regressing spike trains on behavioral features or the activity of other neurons ( Figs 3–5 ) . ‘Learning gain’ decreases exponentially with the number of trees ( Fig 7 ) . Using less trees ( typically 30 with a depth of 2 ) allows for estimation of how different features contribute to the output target , at the expense of prediction and decoding performance ( which are best estimated with approximatively 100 trees with a depth of 5 , see above ) . In contrast , fitting the data on too many trees leads to overfitting and should be avoided . Overall , readers interested in using this technique should bear in mind that meaningful information about the dataset can sometimes be overshadowed by high split density . In such cases , it is of best interest to reduce the number of trees and to ensure that the average gain for splits is large enough . A large class of neurons in the brain are modulated by several dimensions of incoming stimuli [41 , 55 , 56 , 57] , a property referred to as mixed-selectivity . Untangling the different contributions is sometimes challenging and gradient boosted trees offer a rapid and unequivocal approach to address this issue [26 , 27] . In fact , there is no intrinsic limit to the dimensionality of the inputs that can be learned . To further test this technique , we regressed spike trains of HD cells on spatial position , as well as on HD data . In line with previous reports [39 , 40] , the HD cells of the PoSub correlated also with spatial factors while in the ADn , neurons coded mostly for the HD ( Fig 3 ) . XGB thus enables to rapidly explore the correlates of spike trains to measurements of external or internal variables of the system . Investigation of neuronal dynamics does not always entail the regression of spiking data to variables of the experiments . Many studies have focused on the spatio-temporal coordination of neuronal networks in vivo , independent of any behaviorally-related processing ( [53 , 58 , 59] . In fact , the characterization of signal transmission between brain areas remains one of the most complex challenges of neuroscience as it first requires the recording of such data in vivo as well as the establishment of a proper model of interaction to determine the parameters of spike transmission ( e . g . conduction delay and post-synaptic integration time ) . Here we used data from the HD thalamo-cortical network [30] with simultaneous recording of PoSub and ADn . It allowed us to demonstrate a temporally-shifted relationship from ADn to PoSub . More precisely , we used gradient boosted trees to predict PoSub HD cell firing activity based on the ensemble spike trains of the HD cells of the ADn , at various time-lags between the two series of spike trains . PoSub spiking was mostly dependent on ADn activity in preceding time bins ( in average 25ms ) , thus indicating a likely feed-forward pathway . First , this replicates the findings that the HD signal of ADn neurons precedes the actual HD by about 25 ms [42 , 43 , 60] . Second , the temporal asymmetry in the prediction of cortical spiking relative to thalamic activity was preserved during sleep , both during REM and non-REM , and it therefore indicates that this differential temporal coding likely emerges from intrinsic wiring and dynamics . This confirms anatomical studies , as well as examination of putative synaptic interaction between neurons in this pathway [30] . The robustness of this approach was validated by the analysis of artificially generated spike trains , drawn from actual tuning curves and in which different input feature dynamics ( in our case , angular head velocity , or ‘virtual’ angular speed during sleep ) , transmission delays , and integration time constant were explored . This study confirmed the results of in vivo data: unlike linear cross-correlations , gradient boosting reveals temporal organization of spiking irrespective of the dynamics of the inputs and accurately extract , in all conditions , a delay introduced between spike trains ( Fig 6 ) . Furthermore , while PoSub integration time constant alone results in temporarily shifted cross-correlograms between ADn and PoSub simulated spike trains , gradient boosting captures only the synaptic transmission delay . Neurons convey information about external parameters , and it should thus be possible to decode these signals from population activity . The best examples are the demonstrations that position can be estimated from ensembles of hippocampal place cells during exploration and ‘imagination’ of future paths [61 , 62 , 63] as well as the HD signal during wakefulness [64] and sleep [30] . Decoding of neuronal signals has also been widely studied in the context of brain machine interface [65] . Bayesian decoding is the tool of reference to estimate a signal from ensembles of neurons . In fact , it computes the probability distribution of a particular signal given the tuning curves of the neurons and the instantaneous spike counts in the neuronal population . This technique generally assumes that spike counts are drawn from Poisson processes and that neurons are independent from each other ( [37] ) . Here we have compared the performance of Bayesian decoders and gradient boosted trees for decoding angular values based on the activity of either ADn or PoSub neuronal ensembles ( S1 Fig ) . We found that gradient boosted trees matched Bayesian decoding when using ADn neurons but were slightly better with PoSub activity . As emphasized in this report ( Fig 4E and 4F ) , PoSub activity does not encode only the HD but also spatial information about the location of the animal . In case of mixed-selectivity signals , a model-free technique such as gradient boosted trees is less impaired at predicting an external variable compared to the classical method of Bayesian decoding . The potential of these methods to unravel the dynamics of biological neuronal networks is tremendous and will be the scope of further studies . For instance , tracking synaptic transmission in pairwise spike trains [66] , uncoupling the phase-locking of neuronal spiking to concomitant and nested brain oscillations [67 , 68] , and determining the nature of the coordination in neuronal populations in relation to behavior [6 , 54] are examples of the current challenges of data analysis in systems neuroscience . In addition , future improvements of brain-machine interface will require the development of reliable and robust tools to decode neuronal activity [69 , 70] . In summary , gradient boosted trees methods are potentially helpful tools to explore a dataset and make a prediction on the underlying biological processes which , in turn , can be tested with more classical methods . They may also be used to decode signals for closed-loops experiments and brain-machine interface in animals or humans . Finally , these methods open avenues for the study of neuronal data , in general , as the branching of the tree structure can be analyzed as a ‘proxy’ of the biological system itself . | The thalamus is a brain structure that relays sensory information to the cortex and mediates cortico-cortical interaction . Unraveling the dialogue between the thalamus and the cortex is thus a central question in neuroscience , with direct implications on our understanding of how the brain operates at the macro scale and of the neuronal basis of brain disorders that possibly result from impaired thalamo-cortical networks , such as absent epilepsy and schizophrenia . Methods that are classically used to study the coordination between neuronal populations are usually sensitive to the ongoing global dynamics of the networks , in particular desynchronized ( wakefulness and REM sleep ) and synchronized ( non-REM sleep ) states . They thus fail to capture the underlying temporal coordination . By analyzing recordings of thalamic and cortical neuronal populations of the HD system in freely moving mice during exploration and sleep , we show how a general non-linear encoder captures a brain-state independent temporal coordination where the thalamic neurons leading their cortical targets by 20-50ms in all brain states . This study thus demonstrates how methods that do not assume any models of neuronal activity may be used to reveal important aspects of neuronal dynamics and coordination between brain regions . | [
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"tr... | 2018 | Brain-state invariant thalamo-cortical coordination revealed by non-linear encoders |
Antibody-dependent enhancement of viral infection is a well-described phenomenon that is based on the cellular uptake of infectious virus-antibody complexes following their interaction with Fcγ receptors expressed on myeloid cells . Here we describe a novel mechanism of antibody-mediated enhancement of infection by a flavivirus ( tick-borne encephalitis virus ) in transformed and primary human cells , which is independent of the presence of Fcγ receptors . Using chemical cross-linking and immunoassays , we demonstrate that the monoclonal antibody ( mab ) A5 , recognizing an epitope at the interface of the dimeric envelope protein E , causes dimer dissociation and leads to the exposure of the fusion loop ( FL ) . Under normal conditions of infection , this process is triggered only after virus uptake by the acidic pH in endosomes , resulting in the initiation of membrane fusion through the interaction of the FL with the endosomal membrane . Analysis of virus binding and cellular infection , together with inhibition by the FL-specific mab 4G2 , indicated that the FL , exposed after mab A5- induced dimer-dissociation , mediated attachment of the virus to the plasma membrane also at neutral pH , thereby increasing viral infectivity . Since antibody-induced enhancement of binding was not only observed with cells but also with liposomes , it is likely that increased infection was due to FL-lipid interactions and not to interactions with cellular plasma membrane proteins . The novel mechanism of antibody-induced infection enhancement adds a new facet to the complexity of antibody interactions with flaviviruses and may have implications for yet unresolved effects of polyclonal antibody responses on biological properties of these viruses .
Flaviviruses are small , enveloped viruses that cause significant human disease worldwide , including the mosquito-borne dengue , Zika , West Nile , Japanese encephalitis , and yellow fever viruses as well as tick-borne encephalitis virus ( TBEV ) [1] . Despite intensive research , the hunt for specific flavivirus receptors has yielded diverse results . A plethora of molecules at the plasma membranes of different cells have been shown to interact with flaviviruses and were proposed to function as attachment factors , but bona fide entry receptors are still ill-defined ( reviewed in [2 , 3] ) . The reported data are quite varied , suggesting that molecules involved in flavivirus cell attachment and entry differ among viruses and cells [4] . In most instances , the major envelope protein E ( which mediates viral membrane fusion upon receptor-mediated endocytosis ) has been implicated in such interactions . More recently , cellular lipid receptors , ( TIM ( T cell immunoglobulin mucin domain ) and TAM ( Tyro3 , Axl and Mer ) receptor families ) that recognize lipids in the viral membrane , have been shown to mediate flavivirus attachment and entry in certain instances [5 , 6] . Flaviviruses are assembled at the endoplasmic reticulum as immature virions [7] , in which the E proteins are associated with the prM protein ( precursor of M ) as heterodimers that form trimeric spikes [8] . During exocytosis , prM is processed by the cellular enzyme furin , giving rise to mature virions that contain the small M protein and E homodimers [9] covering the viral surface in a herringbone-like arrangement [10] . Each E monomer has three distinct domains ( domain I , II , III; Fig 1A ) , connected by short flexible linkers [11] . Domain II provides most of the intra-dimeric contacts and contains the conserved fusion loop ( FL ) at its distal end . In the dimer , the FL is buried in a pocket built by domains I and III of the neighboring subunit ( Fig 1A ) . Most flavivirus E proteins have a single N-linked glycan attached to domain I , while the dengue E proteins have an additional glycan in domain II [12] . In addition to direct virus-cell interactions , antibodies bound to virus particles can mediate attachment of such immune complexes to Fcγ receptor ( FcγR ) -bearing cells like monocytes , macrophages and dendritic cells , leading to endocytosis and—in the case of incomplete virus neutralization—to enhancement of infection [13–15] . This mechanism of antibody-dependent enhancement ( ADE ) is a well-documented phenomenon of flavivirus infections ( reviewed in [16 , 17] ) , but was also observed for many other viruses that are able to replicate in FcγR-positive cells [18] . ADE has been implicated in the pathogenesis of severe forms of dengue virus infections and is speculated to contribute to congenital Zika virus infections [17 , 19 , 20] , but the precise role of ADE in human infections is still debated ( reviewed in reference [21] ) . Recent evidence indicates that the proteins in the flavivirus envelope are in dynamic motion ( referred to as “virus breathing” ) , best described as an ensemble of conformations around equilibrium ( reviewed in [22] ) . These structural dynamics of the virus surface transiently expose sites in E that would be inaccessible in a static virus particle with a closed shell of 90 E dimers in a herringbone-like arrangement , as determined by cryo EM [10] . Structural analyses , however , have also revealed temperature-dependent changes of the viral envelope for certain dengue virus strains [23 , 24] , which can result in the exposure of cryptic epitopes and their recognition by certain mabs , leading to virus neutralization [25 , 26] . Through binding to such transiently accessible sites , antibodies , and possibly other ligands [27] , can lock E in different conformational states within the virion [25] . The structural dynamics of flaviviruses reflects the conformational flexibility of E , which is required during particle maturation as well as during viral membrane fusion . It is primarily made possible by flexible linker elements between each of the domains ( Fig 1A ) . For membrane fusion , the acidic pH of endosomes triggers the dissociation of E dimers and thus exposes the FL , allowing for its interaction with the endosomal membrane and the initiation of fusion . Membrane merging is then driven by an irreversible structural change of E that converts it into a stable post-fusion trimer ( reviewed in [28 , 29] ) . In this work , we describe a novel mechanism underlying antibody-mediated infection enhancement of TBEV in FcγR-negative cells that is dependent on FL-lipid interactions . We show that a mab recognizing an epitope at the E dimer interface , leads to the dissociation of the E dimer and thus to exposure of the FL . The FL then mediates direct attachment to the plasma membrane ( and liposomal membranes ) and thus increases the infectivity of TBE virus in FcγR-negative cells . Such a mechanism of antibody-mediated enhancement of infection has not yet been described for flaviviruses and adds a new facet to the potential effects of antibodies in flavivirus infections .
In the course of focus-reduction neutralization tests in HeLa-H1 ( HeLa ) cells , we observed a paradoxical infection-enhancing effect with one mab ( A5 ) out of a set of mabs specific for different antigenic sites in the E protein of TBEV ( Fig 1A ) . As seen in Fig 1B , mab A5 did not neutralize the virus even at the highest concentration of 1 , 250 μg/ml , but rather caused a significant increase ( up to 2 . 5-fold ) of infectivity . This property was not seen with mabs directed to other sites in E that either neutralized the virus ( IC3 , B4 ) or had no effect on infectivity ( 4G2 ) ( Fig 1B ) . Measuring the increase of virus production as a function of time post infection in HeLa cells revealed that mab A5-mediated infection enhancement was most prominent at early times of virus replication . After pre-incubation of the virus ( MOI 0 . 25 ) with mab A5 , the maximum increase of virus yield ( approximately 3-fold ) was reached at 16 hours post infection ( Fig 1C ) , which was also the time point of peak virus production in the absence of antibody . No significant enhancement effect was observed with the control mab 4G2 ( Fig 1C ) . Since HeLa cells do not express FcγRs [30] , these data suggest that the binding of mab A5 increased the infectivity of TBEV by an FcγR-independent mechanism . As suggested by blocking ELISAs with human sera ( Materials and methods ) , mab A5-like antibodies can also be induced in the course of natural TBEV infections , albeit in relatively rare instances . Only one ( serum #4 ) out of 30 sera was found to be positive in this assay ( 54% mab A5 blocking activity , S1 Table ) . Since several samples had higher overall TBEV-specific IgG titers than serum #4 , but were negative in mab A5 blocking ( S1 Table ) , this property does not appear to be linked to the total amount of specific antibodies present but to reflect the heterogeneity of antibody compositions in polyclonal sera from different individuals . A possible explanation for the observed enhancement of infectivity is the facilitation of viral cell attachment by mab A5 . Therefore , we first quantified virus attachment to cells in the absence of antibodies by using qPCR ( Materials and methods ) . Given that HeLa cells were efficiently infected by TBEV , binding of the virus to HeLa cells was surprisingly low ( less than 1% of input virus ) , irrespective of the temperature used ( 4 , 30 , and 37°C ) ( Fig 2A ) . To analyze whether this was a specific property of TBEV , we performed the same experiment with dengue virus ( serotype 2 , DENV2 , strain New Guinea C ) , which also replicates efficiently in HeLa cells . Although binding was slightly higher than for TBEV , the values were again remarkably low ( less than 1 . 5% of input virus ) ( Fig 2B ) . A similar picture was obtained in binding experiments with primary human foreskin fibroblasts ( HFFs ) , indicating that the low degree of virus attachment was not restricted to transformed cell lines such as HeLa cells ( Fig 2C ) . To validate these results and our experimental system , we used two approaches . First , we analyzed binding/internalization of human rhinovirus type 2 ( RV-A2 ) to HeLa cells , a system with well-defined and specific receptors ( i . e . members of the low-density lipoprotein receptor superfamily; [31] ) . As seen in Fig 2D , binding/internalization of RV-A2 was dramatically more efficient than that of the flaviviruses tested . It strongly increased with temperature , as described in the literature [32 , 33] . Secondly , we quantified binding of TBE and DEN2 viruses to immature monocyte-derived dendritic cells ( moDC ) , expressing DC-SIGN ( S1 Fig ) , which has been shown to be a specific attachment factor for dengue viruses [34] . Consistent with the potential of dengue viruses to interact with DC-SIGN , efficient binding of DENV2 to immature moDCs was observed , whereas binding of TBEV was as low as on HeLa cells ( Fig 2E ) . To assess possible implications of the low levels of cellular attachment ( Fig 1 ) on measurements of infectivity , we performed serial transfer experiments in a standard focus assay format ( Materials and methods ) . Consistent with the low degree of binding ( see Fig 2 ) , the number of foci declined only moderately from step to step ( Fig 3 ) , indicating that the usual determination of infectious units in virus-containing samples will yield a gross underestimate of the real number of infectious virus particles present . We next investigated the influence of mab A5 on TBEV attachment to HeLa cells . In contrast to other antibodies , mab A5 increased cell binding significantly ( approximately 4-to-5-fold , Fig 4A ) , supporting the hypothesis , that enhancement of infectivity was caused by facilitation of cell attachment . Mechanistically , one might imagine that interaction of the antibody with the virus surface leads to structural rearrangements [25] and the exposure of sites in E that allow interactions with yet unknown cellular protein receptors . If this were the case , no such effects should be seen in interactions with liposomes that consist of a mere lipid membrane . Results of binding experiments with liposomes are shown in Fig 4B . They clearly demonstrate that mab A5 strongly enhances binding to lipid membranes , suggesting that the phenomenon of A5-mediated enhancement of infectivity is due to direct interaction of E with the lipids of the plasma membrane . To verify that binding of TBEV to HeLa cells in the presence of mab A5 did not involve mab-FcγR-interactions , we performed blocking experiments with the FcγR-specific mab CD32 [35] , using the FcγR-positive K562 cell line as a control [36] . Consistent with the lack of FcγRs in HeLa cells [30] , the pre-incubation with mab CD32 had no effect on mab A5-mediated virus attachment to these cells ( Fig 5A ) . In contrast , and as expected , mab A5-mediated binding of TBEV to K562 cells was reduced upon pre-treatment of the cells with mab CD32 ( Fig 5B ) . The FL at the tip of DII has the capacity to insert into lipid membranes , but at neutral pH it is buried in a pocket lined by residues contributed by DI and DIII of the other subunit in the E dimer ( Fig 1A ) . Under conditions of natural infection , the FL becomes only exposed in the endosome through acidic-pH-induced dissociation of E after viral uptake by receptor-mediated endocytosis [28] . Due to the location of the epitope recognized by mab A5 at the E dimer interface ( Fig 1A ) , we speculated that antibody binding might lead to the dissociation of the dimer and exposure of the FL at neutral pH , allowing for its direct interaction with the plasma membrane . To assess this possibility , we performed chemical cross-linking experiments with a recombinant soluble E ( sE ) dimer of TBEV in the absence and presence of mab A5 . The FL-specific , non-neutralizing mab 4G2 [37 , 38] was used as a control . As shown in Fig 6A , cross-linking of sE yielded bands at ~50 kD and ~100 kD corresponding to the monomeric and dimeric form of the protein ( Fig 6A , lane 1 ) , in agreement with the dimeric structure of E [39 , 40] . In the presence of mab A5 , however , E dimers were absent and only bands of E monomers were visible , indicating that the E dimers had dissociated upon complex formation with mab A5 . In the case of the control mab 4G2 , however , no change of the cross-linking pattern of sE was observed ( Fig 6A ) . Note that the rabbit antiserum used for detection of TBEV E in the blot exhibited some reactivity with the mabs , leading to background bands at Mr around 150 kD . The absence of higher molecular weight bands indicates that cross-linking between E and mabs did not occur under the conditions used . We further assessed whether binding of mab A5 also led to exposure of the FL in the context of the virus particle . Since cross-linking of whole virions yields a complex pattern of oligomeric bands , meaningful interpretations with respect to mab A5-induced changes would not be possible in experiments similar to those conducted with the sE dimer [41] . Therefore , we studied putative exposure of the FL induced by mab A5 in an ELISA . TBEV was captured with a polyclonal anti-TBEV serum , and biotinylated mab 4G2 was used as a specific detector for the exposed FL [37 , 38] . The assay was performed in the absence of detergent to preserve the native particle structure [38 , 42] . The data in Fig 6B illustrate that incubation of TBEV with mab A5 resulted in a significantly higher reactivity of mab 4G2 compared to the control without A5 . This is in contrast to the non-dissociating DIII-specific mab B4 , which did not increase 4G2 binding [40] . To corroborate that mab A5-induced FL exposure is indeed responsible for enhanced membrane binding , we first analyzed the effect of the FL-specific mab 4G2 on mab A5-induced binding to liposomes . As shown in Fig 7 , this activity was inhibited in a concentration-dependent manner by the addition of mab 4G2 , but not by mabs directed to other sites ( DI—IC3 and DIII—B4 ) . We further verified this finding with another FL-specific mab ( A1 , [38 , 43] ) and obtained similar blocking activities ( S2 Fig ) . The same effect of mab A5-enhanced binding and its inhibition by mab 4G2 was observed in experiments with HeLa cells , Vero cells , HFFs , and immature moDCs ( Fig 8A–8D ) . These data are in accordance with FL-mediated binding of the virus to the plasma membranes of both primary cells and established cell lines . Although mab 4G2 is non-neutralizing under standard assay conditions , it acquired neutralizing activity when infection of HeLa as well as Vero cells was performed in the presence of mab A5 ( Fig 8E and 8F ) , consistent with the involvement of the FL in the mab A5-mediated infection process . Since the exposure of the FL can also be influenced by the maturation state of the virus [44] , we analyzed the protein composition of the TBEV preparation used in our analyses . As shown in S3 Fig , the TBEV preparation was largely mature , since it did not contain significant amounts of prM , in contrast to an immature control virus preparation obtained by growing the virus in the presence of ammonium chloride , which prevents prM cleavage . To rule out the possibility that mab A5 binds specifically to the plasma membrane , we tested its interaction with HeLa cells by FACS analyses . As controls , we used mabs IC3 , B4 and 4G2 ( Fig 1A ) and the FcγR-positive K562 cell line . None of the mabs showed any specific binding to HeLa cells ( S4 Fig ) , ruling out that the effects observed were due to direct binding of the mab to the cellular plasma membranes . Taken together , we conclude that the phenomenon of mab A5-induced enhancement of infection was indeed the result of increased virus attachment to the cells via the exposed FL . From the previous experiments it was unclear whether the antibody-mediated FL-exposure and membrane attachment might proceed to fusion already at neutral pH . We therefore conducted in vitro fusion assays using liposomes and TBEV labeled with the fluorescent probe pyrene ( Materials and methods ) . In the case of fusion , pyrene-containing phospholipids are diluted into the liposomes , resulting in the decrease of pyrene excimer fluorescence [45 , 46] . These experiments were performed in the presence and absence of mab A5 , both at neutral and acidic pH . As can be seen in Fig 9 , mab A5 was unable to induce fusion at pH 8 and did not inhibit fusion at low pH .
We have identified a new mechanism by which E protein-specific antibodies can enhance the binding of a flavivirus to the plasma membrane of target cells and thus increase its infectivity . This mechanism differs from the well-described phenomenon of antibody-dependent enhancement of infection , which is mediated by the binding of infectious virus-antibody complexes to FcγRs that are expressed on myeloid cells and trigger virus internalization [18] ( Fig 10 ) . In contrast , our experiments provide evidence for a different process of antibody-induced enhancement of infection independent of FcγRs that is mediated by the dissociation of the E dimer ( Fig 6A ) , the exposure of the otherwise buried FL ( Fig 6B ) , and the increased binding of the virus to the plasma membrane of target cells ( Figs 4A and 8A–8D ) . This mechanism appears to be based on the structural dynamics of the flavivirus envelope , antibody-promoted conformational changes , and membrane interactions of the FL that normally occur only in endosomes as a first step of low-pH-triggered viral membrane fusion ( Fig 10 ) [28 , 29] . Enhancement of infection of FcγR-negative cells ( Vero , BHK-21 ) was also described in experiments with the domain II-specific mouse mab E100 , directed against the E protein of West Nile virus ( WNV ) [47] , and the domain II-specific mouse mabs 1A5D-1 as well as 10A1D-2 , directed against the E protein of dengue virus serotype 2 [48] . In addition , in the context of screening for neutralizing activity using Vero cells , cell culture supernatants of some B cells from dengue infected patients also appeared to contain infectivity—enhancing antibodies [49] . The mechanism underlying these observations , however , was not resolved in these studies . Similarly , experiments with Sindbis virus , a member of another family of spherical enveloped viruses with icosahedral structure ( alphaviruses [50] ) , demonstrated that a mouse mab specific for an epitope in the receptor-binding protein E2 ( MCAB 49 ) increased the number of plaque forming units in BHK-21 cells [51] . In this case , increase of specific infectivity was correlated to increased cellular binding of Sindbis virus . The authors hypothesized that their observation might be due to antibody-mediated conformational changes promoting tighter binding of virions to the cell surface . Whether this augmented binding also involved the FL ( present in the alphavirus fusion protein E1 ) remains to be elucidated . Interestingly , enhanced infection was only seen with a specific strain of Sindbis virus but not with others , which may be related to differences in viral envelope dynamics , similar to those described for flaviviruses [52–54] . An apparently different mechanism of enhanced infection of FcγR-negative cells from humans ( A549 ) , hamsters ( BHK-21 ) , mice ( NIH3T3 ) , and mosquitoes ( C6-36 ) was demonstrated in experiments with dengue 2 virus ( strain PL046 ) and a mab specific for the prM protein [55] , which forms a complex with E in immature forms of flaviviruses [8] . These findings were discussed to be caused by molecular mimicry of prM of a cellular protein ( most likely HSP60 ) , allowing the simultaneous binding of the bivalent antibody to the virus as well as to the cell and thus to increase cellular attachment . This contrasts to the mechanism of enhancement described here . The combination of mab A5 with TBEV appears to be independent of interactions with cellular receptor-like proteins , because it can also be demonstrated with plain liposomes ( Fig 4B ) , suggesting that it is mediated by FL-interactions with the lipids in target membranes . Indirect evidence for antibody-promoted structural changes that increase the exposure of the FL had already become apparent in competitive binding studies with E-specific mabs [56 , 57] . Studies with TBE and dengue viruses provided evidence that the binding of antibodies to epitopes in domains II and III of E could lead to increased binding of FL-specific mabs . Detailed structural information about influences of antibody binding on the envelope protein arrangement of a flavivirus was first obtained by Lok et al . [25] using cryo EM of dengue 2 virus ( strain NGC ) in complex with a mab to the A strand of DIII . As discussed by Cockburn and colleagues [27] , such effects may also be caused by ligands other than antibodies and might contribute to the tuning of infection as well as cellular tropism . Beyond that , the exposure of otherwise cryptic protein surfaces by antibody binding can also modulate the fine specificity of antibody responses upon immunization with immune complexes [40] . The binding of the infection-enhancing mab A5 to the E dimer appears to interfere with the equilibrium between monomeric and dimeric states , favoring the monomer and exposing the FL . The epitope of A5 involves residues in DII lying at the interface of the monomers in the E dimer as revealed by the analysis of neutralization escape variants [58] and mutational mapping [59] . Interestingly , FcγR-independent enhancement of WNV infection was observed with a mab ( E100 ) that , like mab A5 , binds to an epitope at a similar site in domain II and the E dimer interface [47] . Based on this similarity , the mechanism of increased infectivity may be analogous and involve antibody-promoted E dimer dissociation in both virus systems . Since both mab A5 and mab E100 augment rather than inhibit infection , one has to assume that they are unable to block fusion in the endosome , even when they are co-internalized with the virus . Post-entry neutralization ( reviewed in [60] ) would require maintenance of the virus-antibody interaction at the acidic pH in endosomes . In this context , it is of note , that the epitopes of both mab A5 and mab E100 involve histidines , H208 in TBEV and H263 in WNV [47] . It is quite possible that protonation of these residues in the endosome might weaken or even abolish the antibody interactions with E . Domain and oligomeric rearrangements required for membrane fusion [28] would thus not be inhibited by antibodies specific for E , allowing for infection to proceed unimpaired . The FL-mediated binding to cellular plasma membranes—through E dimer dissociation induced by mab A5—mimics the first step of the viral fusion process that is normally triggered by the acidic pH in endosomes [29] . One could therefore speculate that fusion would occur already at this stage of antibody-mediated infection . However , we did not detect any mab-A5-induced fusion activity at neutral pH using liposomes ( Fig 9 ) similar to what was observed upon E dimer dissociation and FL exposure at alkaline pH [41] . These negative results are consistent with structural considerations that argue against the possibility of fusion without acidification , because the relocation of DIII—required for the fusogenic conformational change of E [28]—appears to be dependent on the protonation of one or more histidines at the interface of domain I and III [61] . Taken together , all the above data strongly suggest that mab A5-induced binding to the plasma membrane facilitated virus uptake by endocytosis . A striking observation of our binding experiments was the low degree of TBEV attachment to both transformed cell lines and primary cells under normal conditions of infection ( Fig 2 ) . Dengue virus bound with similar low efficiency to HeLa cells but—in contrast to TBEV—efficiently to immature dendritic cells , which express DC-SIGN , a previously identified attachment factor for dengue viruses ( reviewed in reference [62] ) . The difference appears to be due to interaction of E with DC-SIGN via a glycan at N67 [12] , which is present in dengue viruses but absent in TBEV and other flaviviruses [63] . A very low efficiency of cellular attachment is apparently sufficient for infection . Similar results ( less than 1% binding of input virus ) were obtained by Van der Schaar et al . [64] with the dengue 2 virus strain PR159S1 and monkey kidney cells ( BS-C-1 ) . The low efficiency of binding to certain cells may be responsible for the low specific infectivity of flaviviruses observed in many instances [14 , 64] . Serial transfer experiments of dengue virus [64] and TBEV ( Fig 3 ) indicate that conventional infectivity determinations lead to a gross underestimation of the real number of infectious particles present in virus suspensions , because of the low degree of virus binding to cells under the conditions of these assays . The identification of a novel mechanism of antibody-enhanced infection adds an additional facet to the complexity of virus interactions with the variable mixtures of antibodies in polyclonal sera . Influenced by various factors such as binding sites and avidities , the effects of antibody populations on the virus can be expected to be additive , cooperative or competitive and thus modulate neutralizing and infection-enhancing activities in different ways , depending on the antibody compositions of such sera . Importantly , the antibody composition can vary strongly among individuals [65–67] and is especially influenced by anamnestic responses as a result of the history of previous infections and vaccinations [20 , 40 , 68–70] . In addition to the heterogeneity of antibody responses , FL-mediated enhancement effects can also be influenced by properties of the virus ( breathing dynamics and extent of maturation , reviewed in references [22 , 71] ) . Future studies beyond the proof-of-principle presented here will be necessary to dissect this complexity and investigate whether and to which extent antibody-mediated enhancement in FcγR-negative cells can have implications for immunity and pathogenesis of human flavivirus infections .
Primary human foreskin fibroblasts ( HFFs ) were cultivated from anonymous dissociated foreskin samples ( Department of Pediatric Surgery , Medical University of Vienna , Vienna , Austria ) and used for virus interaction studies according to the ethical approval from the ethics committee of the Medical University of Vienna ( ECS 2061/2012 ) . Chicken embryo cells were prepared from 10-day-old embryonated eggs ( VALO Biomedia GmbH , Germany ) . Chicken embryos within the first two thirds of their development do not fall under the “Austrian Law on the Protection of Animals Used for Scientific Purposes” ( “Gesamte Rechtsvorschrift für Tierversuchsgesetz” ) , and therefore approval by an animal ethics committee was not required . Human serum samples from confirmed TBEV infections were originally sent to the Center for Virology for diagnostic purposes and used anonymously with the approval of the local ethics committee of the Medical University of Vienna ( EK 134/2008 ) . HeLa cells ( HeLa-H1 , strain Ohio , ATCC ) were cultured in Dulbecco’s Modified Eagle Medium ( DMEM , Gibco ) supplemented with 10% fetal calf serum ( FCS , Gibco ) . Primary human fibroblasts ( HFFs ) were grown in Minimum Essential Medium Eagle ( MEM , Sigma-Aldrich ) supplemented with 10% FCS and 1% non-essential amino acids solution ( Gibco ) . Vero cells ( ECACC ) were grown in DMEM ( Gibco ) supplemented with 5% FCS ( Gibco ) . K562 cells ( ATCC ) were grown in Iscove's Modified Dulbecco's Medium ( IMDM , Gibco ) supplemented with 10% FCS ( Gibco ) . Immature moDCs were prepared from whole blood of anonymous donors , purchased from the Austrian Red Cross Blood Bank ( Vienna , Austria ) . Peripheral blood was diluted 1:1 with phosphate-buffered saline pH 7 . 4 ( PBS , Sigma-Aldrich ) and mononuclear cells were separated using Ficoll-Paque ( GE Healthcare Life Science ) . CD14+ cells were obtained by MACS ( magnetic cell isolation and preparation ) using anti-CD14 magnetic beads according to the manufacturer’s protocol ( Miltenyi Biotech ) . The purity of the cells was ≥ 95% , as determined by flow cytometry analysis using a mouse anti-human CD14 antibody ( BD Bioscience ) ( S1 Fig ) . To generate immature dendritic cells , 1x106 purified CD14+ cells were cultured in RPMI-1640 medium ( Sigma-Aldrich ) , supplemented with 10% FCS , recombinant human GM-CSF ( 100 ng/ml , PeproTech ) and recombinant human IL-4 ( 25 ng/ml , PeproTech ) for 5 days [72] . On day 5 ( prior to binding assays ) , phenotypic characterization of the cells was carried out by flow cytometry analysis using conjugated mouse anti-human antibodies ( BD Bioscience ) directed to the surface molecules CD209 , CD1a , HLA-DR , CD80 , CD83 and CD86 . As shown in S1 Fig , ~90% of the cells were CD209 ( DC-SIGN ) and CD1a positive . The cell population had a typical immature moDC profile with high expression of CD209 , CD1a as well as HLA-DR and low ( or intermediate ) expression of CD80 , CD83 and CD86 ( S1 Fig ) [73 , 74] . Mabs A1 , A5 , B4 , IC3 , and 4G2 [77–80] were purified from serum-free hybridoma cell culture supernatants ( described in references [77–79] ) using protein A or G Sepharose High Performance columns according to the manufacturer’s instructions ( GE Healthcare Life Sciences ) . The hybridoma cell line HB 112: D1-4G2-4-15 ( producing mab 4G2 ) was obtained from ATCC . Specific characteristics of the mabs used in this study are summarized in Table 1 . Recombinant TBEV sE ( strain Neudoerfl , amino acid 1 to 400 ) containing a strep-tag was expressed in Drosophila S2 cells ( Invitrogen ) and purified by StrepTactin affinity chromatography as described previously [40 , 66] . The purity and size of the mabs as well as sE were controlled by Agilent 2100 Bioanalyzer electrophoresis and/or SDS-PAGE ( 15% polyacrylamide gels ) . The verification of the oligomeric structure and correct folding of the recombinant sE protein was described in a previous study [66] . Fifteen to 20 focus forming units ( FFU ) of TBEV were pre-incubated with serial dilutions of mabs for 1 hour at RT . TBEV-antibody complexes were then added to pre-chilled confluent HeLa cell monolayers in Medium199 ( Sigma-Aldrich ) containing 15 mM HEPES , 15 mM HEPPS , 0 . 1% BSA . After 1 hour at 4°C , the inoculum was removed and cells were washed twice to remove unbound virus . DMEM ( 1% FCS ) was added and the temperature was shifted to 37°C to allow infection of the cells . After 30 minutes incubation at 37°C , the cells were overlaid with 3% carboxymethyl cellulose in DMEM ( 1% FCS ) . Two days after infection , the cells were fixed with 4% paraformaldehyde for 20 minutes at RT and permeabilized for 30 minutes at 37°C with a Tris buffer ( 50 mM Tris , 150 mM NaCl , pH 7 . 6 ) containing 3% nonfat dry milk powder , 0 . 5% Triton X-100 , and 0 . 05% Tween 20 . Foci were visualized with a virus-specific polyclonal rabbit anti-TBEV serum ( obtained from the Core Unit of Biomedical Research , Division of Laboratory Animal Science and Genetics , Medical University of Vienna , Himberg , Austria ) , alkaline phosphatase-labeled goat anti-rabbit immunoglobulin G ( Sigma-Aldrich ) and SigmaFast Fast Red TR/naphthol AS-MX ( Sigma-Aldrich ) as a substrate . For the inhibition of mab A5-induced enhancement of infectivity , TBEV-mab complexes ( 15–20 FFU TBEV , final mab concentration 5 μg/ml ) were further incubated with mab 4G2 or control mabs ( final concentration for each mab 5 μg/ml ) for 1 hour at RT . For serial transfer experiments , TBEV was added to pre-chilled HeLa cell monolayers , incubated for 30 minutes at 4°C , harvested and then transferred onto fresh cells . To permit infection of bound virions , the cells were washed , pre-warmed medium was added , and the cells were shifted to 37°C . After 30 minutes at 37°C , the cells were covered with an overlay and incubated for 2 days at 37°C . The procedure was repeated nine times and foci were visualized as described above . TBEV ( 1x109 RNA copies ) with and without mabs ( 20 μg/ml ) was pre-incubated for 1 hour at RT . As described for the focus assays , the virus-antibody complexes were added to confluent HeLa or Vero cell monolayers and incubated for 1 hour at 4°C . The cells were washed , fresh medium was added , and the temperature was shifted to 37°C for infection . Eight , 16 and 24 hours post infection aliquots were taken from the HeLa cell culture supernatant and the infectivity titers were determined in focus assays . In the case of Vero cells , the cell culture supernatant was harvested 24 hours after infection and the number of RNA copies was determined by qPCR . L-α-phosphatidylcholine ( 25 mol% ) , L-α-phosphatidylethanolamine ( 22 . 5 mol% ) , 1 , 2-dipalmitoyl-sn-glycero-3-phosphoethanolamine-N- ( cap biotinyl ) ( 1 . 25 mol% ) , 1 , 2-dioleoyl-sn-glycero-3-phosphoethanolamine-N- ( cap biotinyl ) ( 1 . 25 mol% , all from Avanti Polar Lipids ) , and cholesterol ( 50 mol% , Sigma- Aldrich ) [82 , 83] in chloroform were dried to a thin film with a rotary evaporator in a high vacuum as described previously [82] . The lipid film was hydrated in liposome buffer ( 10 mM triethanolamine , 140 mM NaCl , pH 8 . 0 ) and subjected to 5 cycles of freezing and thawing . Liposomes were extruded through two 200 nm polycarbonate membranes by the use of a Liposofast syringe type extruder ( Avestin ) [82] . TBEV ( 0 . 5 μg/ml E protein ) was pre-incubated with and without mabs ( 20 μg/ml ) for 1 hour at room temperature ( RT ) . Then , biotinylated liposomes were added to a final concentration of 0 . 2 mM for 20 minutes at 37°C . The liposomes were aggregated by cross-linking with avidin ( Sigma-Aldrich ) and pelleted at 1 , 000 g for 15 minutes at RT . The pellet was resuspended in TAN buffer ( 50 mM triethanolamine , 100 mM NaCl , pH 8 . 0 ) containing 0 . 5% Triton X-100 . The amount of E protein in the pellet ( bound ) as well as in the supernatant ( unbound ) was quantified by 4-layer ELISA [76] . For the inhibition of mab A5-induced enhancement of binding , TBEV-mab complexes ( 0 . 5 μg/ml E protein , final mab concentration 10 μg/ml ) were further incubated with serial dilutions of mab 4G2 ( 2 . 5 , 5 , 10 μg/ml ) , mab A1 ( 2 . 5 , 5 , 10 μg/ml ) or control mabs ( final concentration for each mab 10 μg/ml ) for 1 hour at RT . Virus ( 1x109 RNA copies of TBEV , DENV or RV-A2 ) was pre-incubated with and without mabs ( 20 μg/ml ) for 1 hour at RT . HeLa cells , Vero cells and HFFs were detached with the non-enzymatic EDTA versene solution ( Gibco ) . 2x105 HeLa cells or 2x105 Vero cells or 2x105 HFFs or 1x106 immature moDCs were added at 4°C , 30°C or 37°C in binding buffer ( medium 199 ( Sigma-Aldrich ) , containing 15 mM HEPES , 15 mM HEPPS , 0 . 1% BSA , pH 7 . 6 ) . Twenty mM NH4Cl was included to prevent fusion in endosomes , release of the genome and its replication . After incubation for 1 hour at the respective temperature , cells were pelleted by low-speed centrifugation and washed twice with ice-cold PBS pH 7 . 4 ( Sigma-Aldrich ) to remove unbound virus . The viral RNA was extracted from the pellet and supernatant using RNeasy Mini kit ( Qiagen ) according to the manufacturer’s protocol . The number of bound and unbound genomic RNA copies was quantified by two-step quantitative reverse transcription PCR ( qPCR ) . To block the engagement of FcγRs by TBEV in the presence of virus-specific mabs , 1x106 HeLa cells or 1x106 FcγR-positive K562 were pre-treated with 2 . 5 μg of the mouse anti-human Fcγ RII/CD32a monoclonal antibody ( R&D Systems ) for 90 minutes at 37°C , as described in reference [35] . The pre-treated cells were then washed with medium and used for cell binding experiments . Fusion of virions with liposomes was determined by a change in the pyrene monomer and excimer fluorescence caused by the dilution of pyrene-labeled viral phospholipids into the unlabeled liposomal membrane [45 , 46] . TBEV with and without mab A5 ( same molar ratios as used for the liposome binding assays ) was pre-incubated for 1 hour at room temperature ( RT ) . Liposomes were added and the mixture was either treated with TAN buffer pH 8 . 0 or with 450 mM 2- ( N-morpholino ) ethanesulfonic acid ( MES ) , pre-titrated to yield a final pH of 5 . 5 in the assay . After an incubation for 1 hour at 37°C , the samples were back-neutralized with 300 mM triethanolamine . Fluorescence emission spectra were recorded at 21°C from 360 to 520 nm using an excitation wavelength of 343 nm and a Perkin Elmer LS 50B Fluorescence Spectrophotometer . The excimer and monomer peaks were measured at emission wavelengths of 480 and 397 nm , respectively . E protein was quantified by a 4-layer enzyme-linked immunosorbent assay ( ELISA ) as described previously [76] . The standard , purified TBEV , and the samples were denatured with 0 . 4% SDS for 30 minutes at 65°C [76] . cDNA was synthesized from isolated viral RNA with the iScript cDNA Synthesis Kit ( Bio-Rad ) . For the two-step quantitative reverse transcription PCR ( qPCR ) , cDNA was mixed with the respective probes ( 10 pmol , VBC biotech ) and primers ( 25 pmol , VBC Biotech ) , and TaqMan Universal PCR Mastermix ( LifeTechnologies ) . The following primers and probes were used: TBEV—forward primer: GAAGCGGAGGCTGAACAACT , reverse primer: TTGTCACGTTCCGTCTCCAG , probe: 5’-FAM-TGTGTACAGGCGCACCGGCA-TAMRA-3’ . DENV2—forward primer: CAGATGGAGGGAGAAGGAGTC , reverse primer: CGCCCTACTCTTGCTAACCA , probe: 5’-FAM-ACAGTCACAGAAGAAATCGCCGTGCA-TAMRA-3’ . RV-A2—forward primer: GGCCCCTGAATGTGGCTAA , reverse primer: AAGTAGTTGGTCCCATCCCG , probe: 5’-FAM-CCCTGCAGCTAGAGCACGTAACCC-TAMRA-3’ . The temperature profile of the reaction was 3 minutes at 50°C , 10 minutes at 95°C , followed by 45 cycles of 15 seconds at 95°C , 30 seconds at 55°C , and 30 seconds at 72°C [84 , 85] . Serial ten-fold dilutions of the plasmids pTNd/c TBEV ( containing the full-length genomic cDNA insert of TBEV strain Neudoerfl , [86] ) , plasmid bluescript HRV2 ( containing the full-length genomic cDNA insert of RV-A2 , [87] ) and plasmid MA-T DENV2 ( containing a part of the NS5 sequence of DENV2 NGC; synthesized by Invitrogen ) were used to generate a standard curve for quantification , as described previously for DENV2 [64] and TBEV [88] . TBEV sE ( 1 . 5 μg ) and mabs ( 4 μg ) were diluted in 800 μl TAN buffer pH 8 . 0 and incubated for 1 hour at RT . Chemical cross-linking with 10 mM dimethyl suberimidate ( DMS , Pierce ) was performed essentially as described previously [40 , 89] . The reaction was stopped by the addition of ethanolamine to a final concentration of 10 mM . The samples were precipitated with trichloroacetic acid ( TCA ) , subjected to SDS-PAGE under non-reducing conditions using 5% polyacrylamide gels and a phosphate-buffered system [90] . The proteins were blotted onto polyvinylidene difluoride membranes ( Bio-Rad ) with a Bio-Rad Trans-Blot semidry transfer cell [91] . Detection was carried out immunoenzymatically using a polyclonal rabbit anti-TBEV serum ( obtained from the Core Unit of Biomedical Research , Division of Laboratory Animal Science and Genetics , Medical University of Vienna , Himberg , Austria ) together with a horseradish peroxidase ( HRP ) -linked anti rabbit IgG ( from donkey , GE Healthcare Life Sciences ) as described previously [91] . Microtiter plates were coated with a polyclonal guinea pig anti-TBEV serum ( obtained from the Core Unit of Biomedical Research , Division of Laboratory Animal Science and Genetics , Medical University of Vienna , Himberg , Austria ) . After blocking with 1% BSA in PBS pH 7 . 4 , native TBE virions at an E protein concentration of 1 μg/ml in PBS pH 7 . 4 , containing 2% lamb serum ( PAA ) , were added and incubated for 1 hour at 37°C . No detergent was used at any stage to avoid destabilization of the virion [38 , 42] . Mabs ( 10 μg/ml ) were added to the bound virus and incubated for 1 hour at 37°C . Mab-induced FL exposure was analyzed with the biotin-labeled mab 4G2 at a concentration of 1 μg/ml and Streptavidin-HRP ( Sigma-Aldrich ) . Human serum samples were diluted 1:25 in PBS pH 7 . 4 ( containing 2% lamb serum ( PAA ) ) and added to strep-tagged recombinant TBEV sE ( 25 ng/well ) captured on Streptactin-coated plates ( IBA GmbH ) . After incubation for 1 hour at 37°C , the plates were washed with PBS and mab A5 was added ( 12 . 5 ng/well ) . Mab A5 bound to the antigen was detected using peroxidase-labeled rabbit anti mouse IgG ( Pierce ) . Results were expressed as percent mab reactivity ( absorbance ) in the absence of blocking antibodies . Quantitative ELISAs with human serum samples were performed as previously described using non-treated microtiter plates coated with 25 ng/well formalin-inactivated TBEV [92] . Dilution series of the human serum samples were added , and the plates were incubated for one hour at 37°C . Bound antibodies were detected with biotin-labeled goat anti-human IgG ( Pierce ) followed by Streptavidin—Peroxidase ( Sigma ) . TBEV-specific antibodies were quantified in IgG units by using a human post-infection anti-TBEV serum as a standard that was arbitrarily set to contain 1000 units . Standard curves ( two-fold dilutions , 7 data points ) were fitted with a four-parameter logistic regression ( GraphPad Prism 6 . 0 , GraphPad Software Inc . ) . The cut-off ( positive ≥ 220 units ) was based on testing 90 flavivirus-negative serum samples [92] . 5x105 HeLa or 5x105 K562 cells were incubated with mabs A5 , IC3 , 4G2 and B4 ( 2 μg/ml ) for 1 hour at 4°C . Alexa Fluor 488 goat-anti mouse IgG ( H+L ) , cross-adsorbed ( Invitrogen ) , was used for the detection of cell-bound mabs by FACS . ANOVA followed by Dunnett’s multiple comparison test and Student’s t-test were performed with log-transformed data . GraphPad Prism 6 . 0 was used for the analyses and p values < 0 . 05 were considered significant . | Antibodies are an important component of antiviral host responses and their binding to the surface of virus particles usually leads to neutralization of viral infectivity . In some instances , however , antibodies at sub-neutralizing concentrations can enhance infection of certain cells , because they facilitate the uptake of infectious virus-antibody complexes through interactions with antibody-specific cellular receptors ( Fcγ receptors ) . This mechanism is designated antibody-dependent enhancement of infection and implicated in the pathogenesis of dengue and possibly Zika virus infections , both mosquito-transmitted flaviviruses . Here we describe a novel mechanism of infection enhancement by antibodies that is independent of interactions with Fcγ receptors , using another important human-pathogenic flavivirus , tick-borne encephalitis virus . We demonstrate that binding of a specific antibody to the envelope protein E at the viral surface promotes the exposure of a structural element that interacts with the lipids of the cellular plasma membrane , thus increasing infection . Our study provides new insights into mechanisms that potentially modulate the antiviral effects of antibody populations present in post-infection sera . | [
"Abstract",
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"... | 2017 | A novel mechanism of antibody-mediated enhancement of flavivirus infection |
This study aims to analyze the clinical characteristics and treatment outcomes of 590 patients with brucellosis in Xinjiang , China . The clinical characteristics , laboratory findings , complications and prognosis of 590 patients infected with brucellosis were retrospectively analyzed . These patients had a mean age of 44 . 24 ± 15 . 83 years with 60 . 5% having a history of close contacting with cattle and sheep . Of them , 53 . 6% ( 316 /590 ) were in acute phase and 21 . 5% were in chronic phase . Agglutination test showed 98 . 5% positive with 34% blood culture positive of Brucella . The major symptoms were fatigue ( 91% ) , hyperhidrosis ( 88 . 1% ) , fever ( 86 . 9% ) , and joint pain ( 81% ) with 29 . 8% having enlarged liver , 26 . 1% having enlarged spleen and 23 . 2% having osteoarticular complications . Combination of doxycycline plus rifampicin for 12 weeks was an effective regimen for patients without complications . The 3-drug regimen ( doxycycline+rifampicin+levofloxacin ) for 12 weeks was recommended for these with complications . There were 6 patients died ( 1 . 02% ) with overall relapse rate of 5 . 98% . Brucellosis is mostly associated with contacting with domestic animal production in Xinjiang , China . Clinical symptoms include fever , fatigue , hyperhidrosis , and joint pain with common complication of osteoarticular involvement . Three-drug-regimen of doxycycline+rifampicin+levofloxacin for 12 weeks was effective for these patients with complications .
Brucellosis ( or undulant fever ) is a zoonotic disease with a worldwide distribution , mainly in the Mediterranean Basin , Middle East , Central and South America , and Asia [1] . Xinjiang Uygur Autonomous Region ( Xinjiang ) in western China is an agricultural area with animal production as its major primary industry . The incidence of brucellosis is high in this region [2] with prevalence being 9 . 80/100000 , 17 . 51/100000 , and 33 . 02/100000 in 2012 , 2013 , and 2014 , respectively [3] . The disease is transmitted to humans through closely contacting with sick animals or consumption of raw meat and dairy products [4] . Patients may present with fever , sweating , fatigue , and osteoarticular pain [5] . The major systemic complications of the disease involve osteoarticular involvement[6] , cardiological and neurological disorders . The incidence of endocarditis disease is about 2% , however , it accounts for 80% of brucellosis related death [5] . The combination of antibiotics is the main regimen for brucellosis [7] . Long-term of taking drugs is required for cure treatment and reducing relapsed cases [8] . In this study , the clinical features of 590 cases with brucellosis and their treatment were retrospectively analyzed .
A written informed consent was obtained from every patient and the study was approved by the Ethics Committee of The First Affiliated Hospital of Xinjiang Medical University . Patients diagnosed with brucellosis from 2005 to 2015 in The First Affiliated Hospital of Xinjiang Medical University were recruited . The diagnosis of brucellosis was based on medical history , clinical features , positive serum agglutination tests and/or blood cultures [9] . The patient’s presentation was categorized as acute phase ( with symptoms less than 3 months ) , subacute phase ( 3–6 months ) and chronic phase ( more than 6 months ) . The blood was cultured using automatic blood culture system ( France Biomerieux Co . Ltd . , Bact / ALERT 3D 60 ) with an average incubation time of 5–7 days according to the method described by Tabibnejad [10] . The pathogen of positive culture was identified using automatic microbial identification machine ( France Biomerieux Co . Ltd . , VITEK 2 COMPACT 30 ) . The clinical presentations , laboratory results and treatment outcome were recorded . The initial signs and symptoms of brucellosis cases include fever , sweats , malaise , anorexia , headache , pain in muscles , joint , and/or back and fatigue . The complications of brucellosis cases include osteoarticular , endocarditis , epididymalorchitis , nervous disorders , and liver involvement . The diagnosis of endocarditis was based on the revised diagnostic criteria of DUKE infective endocarditis [11] , presenting as valve vegetation on transthoracic echocardiography or transesophageal echocardiography . The epididymalorchitis was diagnosed by epididymal testicular pain and positive ultrasound findings . Liver involvement or liver damage refers to increased alanine aminotransferase and aspartate aminotransferase ( more than 2 times of the normal upper limit ) of laboratory tests , excluding other reasons . The diagnosis of nervous disorder included culture of Brucella using cerebrospinal fluid as gold standard and/or neurological symptoms and abnormal cerebrospinal fluid examination . Blood was collected from patients for testing ALT , AST , GGT , ALP , TBil and Alb measured by biochemical analyzer ( Roche cobas8000 ) . A complete blood count was determined on the Sysmex XN2000 analyzer . The erythrocyte sedimentation rate ( ESR ) was detected using Wechsler method . The C-reactive protein ( CRP ) was detected using the immune turbidimetric method ( Beckman immage800 ) . The standard tube agglutination antigen was purchased from the Institute of Infectious Diseases , China Center for Disease Control and Prevention . Blood culture was performed for these patients with symptom of chilling or their body temperature over 38 . 5°C before use of antimicrobial drugs . Chemotherapeutical regimens combined with two or three drugs were employed for treating these patients with different presentations and conditions . These combinations were doxycycline+rifampicin , doxycycline+levofloxacin , doxycycline+streptomycin and doxycycline+rifampicin+levofloxacin . The doses for orally taking these drugs were doxycycline , 100 mg p . o . , every 12 hours; rifampin , 600 mg p . o . , once per day; streptomycin , 1 g intramuscular injection , once per day , and levofloxacin , 500 mg p . o , once per day . For some reasons , we also prescribed the second-line drugs for some patients included levofloxacin ( 500 mg p . o , once per day ) , cotrimoxazole ( 960 mg p . o , twice per day ) , ciprofloxacin ( 750 mg p . o , twice per day ) and ceftriaxone ( 2g ivgtt , once per day ) . All patients were treated for 12 weeks and followed up for 6 months . Positive clinical symptoms and physical examinations indicated disease recurrence . The data were analyzed using SPSS software ( Version 17 . 0 , SPSS Inc . , Chicago , Ill . , USA ) . The measurement data were expressed as mean ± standard deviation . T test and chi-square test were used to analyze the differences . P < 0 . 05 was statistically significant .
A total of 590 patients were included in this study . Detailed demographics are shown in Table 1 . Of them , 455 ( 77 . 1% ) were male and 135 ( 22 . 9% ) were female with mean age of 44 . 24 ±15 . 83 ( 3–75 ) years . There were 316 cases in acute phase , 136 cases in subacute phase , 127 cases in chronic phase and 11 showed no symptom but showing serological positive in agglutination test . Most ( 357 , 60 . 5% ) of the patients were farmers for raising cattle and sheep; and 145 ( 24 . 6% ) cases had consumption history of dried raw meat or dairy products . There were 180 patients ( 30 . 5% ) having different complications . All the patients were given 12 weeks of treatment . And since 2010 , we gave those patients having complications three drugs combination regimen , doxycycline+rifampicin+levofloxacin , which significantly reduced relapsed cases compared to doxycycline+refampicin combination . Table 2 shows the clinical characteristics of these patients including symptoms and complications were analyzed . These symptoms for the most patients were fever ( 86 . 9% ) , sweating ( 88 . 1% ) , fatigue ( 91% ) , and joint pain ( 81% ) . Some patients had back pain ( 54 . 6% ) , and shivers ( 52 . 5% ) . The most common signs of physical examinations were enlarged liver ( 176 cases , 29 . 8% ) , and enlarged spleen ( 154 cases , 26 . 1% ) . There were 137 cases ( 23 . 2% ) with osteoarticular involvement , including 56 cases ( 40 . 9% ) of sacroiliac arthritis , 48 cases ( 35% ) of knee involvement , and 37 cases ( 27% ) of spondylitis . There were 21 cases that involved the joints of ankle , elbow and shoulder , and , most of them were single joint involvement . There were 15 cases of epididymalorchitis , which is the most frequently involved of urinary and reproductive system . There were 10 cases ( 1 . 69% ) complicated with endocarditis , including 8 cases ( 80% ) of aortic valvular neoplasm . Fatigue , sweating and fever are the most common symptoms and osteoarticular system is most commonly involved . Table 3 shows the results of laboratory tests . There were 267 patients ( 45 . 3% ) with anemia , 146 ( 24 . 7% ) with abnormal white blood cells , 117 ( 19 . 8% ) with thrombocytopenia , 382 ( 64 . 7% ) with elevated erythrocyte sedimentation rate ( ESR ) and 261 ( 44 . 2% ) with increased C-reactive protein ( CRP ) . The agglutination test antibody was positive ( ≥ 1:100 ) in 583 cases ( 99 . 8% ) with highest antibody titer of 1: 1600 . There were 179 patients ( 30 . 3% ) with elevated transaminase . Totally 468 cases were tested by blood culture and 159 cases were positive ( 34% ) of Brucella melitensis . The above suggest that elevated ESR and CRP are important laboratory indicators and that the blood culture needs to be improved . Table 4 shows the treatment and prognosis of these patients . Among the 590 patients , total of 468 patients were followed up . Fever is the symptom for the most patients , with 86 . 9% of the patients . When they received chemotherapeutical treatment , their body temperature returned to normal in 2–14 days after treatment with 85 . 2% ( 436/512 ) of the patients back to normal body temperature in one week . There were no significant differences in antipyretic effect among different treatment groups . For these patients without complications , relapse occurred in 10 patients ( 3 . 47% ) . There were 108 patients received without relapse in 6 months of follow-up . There was only one relapse ( 0 . 88% ) , less than the relapse rate of patients who received doxycycline+rifampin regimen for 6 weeks ( 3 . 30% ) . The patients took doxycycline+streptomycin and doxycycline+levofloxacin regimen , had higher relapse rate than doxycycline + rifampin regimen ( P<0 . 05 ) . For these patients with osteoarticular involvement , relapse was observed in 12 patients ( 8 . 76% ) , which is significantly higher than those without complications ( 3 . 47% ) ( p<0 . 05 , Table 4 ) . In addition , doxycycline+rifampicin regimen had the lowest relapse rate in patients without complications ( p< 0 . 05 ) . For those with osteoarticular complications , doxycycline+rifampicin+levofloxacin can have better treatment efficacy . All 10 cases with brucellosis endocarditis received had 3-drug regimen for 12 weeks . Among them , 6 cases had valve replacement surgery with good prognosis . The other 4 patients who did not received valve replacement surgery died from various reasons . These results indicate that doxycycline+rifampicin is a commonly used regimen with good efficacy for patients without complications . Combined use of doxycycline+rifampicin with levofloxacin is suitable for brucellosis patients with complications . We recommended 12 weeks continuous drug treatment .
Brucellosis has been increasingly becoming population health problem worldwide [12] in recent years . The number of brucellosis patients was increased yearly in our hospital in the last 10 years . During the hospital treatment , we found more patients had complications and at chronic stage . In the study , 23 . 5% of the 590 patients were at chronic phase , which is higher than other reports [4 , 13] , indicating that more patients in Xinjiang were diagnosed improperly , which causes delayed treatment . Epidemiologically , contacting with animals and/or consumption of uncooked , disinfected milk and dairy products are the main risk factors for individuals having the infection [14] . Studies showed that 62 . 6–94 . 6% of patients in Turkey [15 , 16] and 79 . 1% of patients in Iran [17] ate raw or uncooked animal products . We showed that 24 . 6% of our patients were infected through consumption of raw and uncooked animal products , which is lower than those patients from other countries . From our clinical data , it showed that 66 . 9% of the patients came to our hospital in the months from March to May , which is also matched the published studies in Xinjiang , China[18 , 19] . In the pasture areas of Xinjiang , it is so called Spring lambing season from March to early May . In the season , sheep farmers take time to look after the new lambs The close contacting with ewes and new born lambs may be the main cause for the peak season of patients . In this study , there are 60 . 5% of patients closely contacted with cattle and sheep and 66 . 9% of the patients came to our hospital during the lambing season , indicating that helping lambing is the major activity or risk for infection . In the study , 86 . 9% of brucellosis patients had fever . However , we found only 34% of those patients were blood culture positive , indicating blood bacteria may be not the main cause for fever . In addition , we found that the fever in all the patients was removed very quick once the patients took the drugs of doxycycline plus rifampicin . The fever was disappeared 2 or 14 days after taking antibiotics with the most ( 85 . 2% ) back to normal in one week . It may be important for the doctors to make prescription in remote endemic areas , where diagnostic facility is poor . Doctor may give doxycycline+rifampicin to these patients with fever before identification of pathogen . in the endemic areas for diagnostic treatment . If the fever is down , it may indicate that the infection is brucellosis Antimicrobial therapy is the most effective treatment of brucellosis if patients are given right diagnosis . The present study showed that the regimen of doxycycline+rifampin is suitable for these brucellosis cases without complications as recommended [17 , 20] . Patients given the doxycycline + levofloxacin regimen showed more relapse cases than doxycycline+rifampin regimen . However , we found that 3-drug regimen of doxycycline + rifampin + levofloxacin for osteoarticular complications showed very low relapse . There are no consensus for treating neurobrucellosis including the regimen and course . The first-line regimen is doxycycline and rifampicin with or without aminoglycosides has been suggested[21–23] . We had one patient with meningitis who was successfully treated by doxycycline + rifampicin combined with ceftriaxone regimen for 6 months . For these with brucellosis endocarditis , surgical treatment to replace valve should be performed for these patients with severe endocarditis if necessary . Maryam et al [24] showed that the mortality rate of brucellosis endocarditis with drug combined surgical treatment was 6 . 7% whereas that with drug treatment only was 32 . 7% . In our study , 10 patients with brucellosis endocarditis presented as fever , chest tightness , shortness of breath . Six patients were treated with antibiotics and valve replacement surgery with good prognosis . However , the other 4 patients without surgery died within 1-year of follow-up , indicating that the treatment of brucellosis endocarditis should include antibiotics and valve replacement surgery . For patients at acute phase without complications , first-line drugs including doxycycline + rifampicin was recommended for 12 weeks . For patients with chronic course or complications , in addition to the first-line drugs , quinolones /cephalosporins should be added for at least for 12 weeks , thus completely removing pathogens in vivo , improving the cure rate and reducing relapse rate . The serum agglutination test is a routing method for detecting antibodies in patients with brucellosis . Brucella bacteria culture is the "gold standard" for the diagnosis of brucellosis [25 , 26] . In conclusion , the epidemiological and medical history and clinical characteristics are crucial information in early and the differential diagnosis of brucellosis . WHO recommended first-line 2-drug regimen is still preferred; however , 3-drug regimen of doxycycline+rifampin+levofloxacin for 12 weeks is recommented for the patients with complications and at chronic stage . | Brucellosis is a highly contagious zoonosis caused by bacteria of the genus Brucella and affecting mammals . Human Brucellosis is caused by ingestion of unpasteurized or undercooked food product from infected animals , or close contact with them . The infection with same bacteria even with same type can lead to manifestations varying from patient to patient . And there is no consensus for treating all types of brucellosis . In this paper , we retrospectively reviewed symptoms of Brucellosis in 590 patients living in Xinjiang area of China . We found that the percentage of chronic Brucellosis in Xinjiang from our study was 23 . 5% , which was higher than previous report . The reason for this increasing can be further explored . We also suggest that , despite the WHO recommended first-line 2-drug regimen is effective and preferred in most cases , the 3-drug regimen of doxycycline+rifampin+levofloxacin for 12 weeks should be recommended for patients with complications or experienced prolonged treatment . These findings are of clinical significance to improve Brucellosis management . | [
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... | 2017 | The clinical features of 590 patients with brucellosis in Xinjiang, China with the emphasis on the treatment of complications |
Type 3 secretion systems ( T3SSs ) are essential components of two complex bacterial machineries: the flagellum , which drives cell motility , and the non-flagellar T3SS ( NF-T3SS ) , which delivers effectors into eukaryotic cells . Yet the origin , specialization , and diversification of these machineries remained unclear . We developed computational tools to identify homologous components of the two systems and to discriminate between them . Our analysis of >1 , 000 genomes identified 921 T3SSs , including 222 NF-T3SSs . Phylogenomic and comparative analyses of these systems argue that the NF-T3SS arose from an exaptation of the flagellum , i . e . the recruitment of part of the flagellum structure for the evolution of the new protein delivery function . This reconstructed chronology of the exaptation process proceeded in at least two steps . An intermediate ancestral form of NF-T3SS , whose descendants still exist in Myxococcales , lacked elements that are essential for motility and included a subset of NF-T3SS features . We argue that this ancestral version was involved in protein translocation . A second major step in the evolution of NF-T3SSs occurred via recruitment of secretins to the NF-T3SS , an event that occurred at least three times from different systems . In rhizobiales , a partial homologous gene replacement of the secretin resulted in two genes of complementary function . Acquisition of a secretin was followed by the rapid adaptation of the resulting NF-T3SSs to multiple , distinct eukaryotic cell envelopes where they became key in parasitic and mutualistic associations between prokaryotes and eukaryotes . Our work elucidates major steps of the evolutionary scenario leading to extant NF-T3SSs . It demonstrates how molecular evolution can convert one complex molecular machine into a second , equally complex machine by successive deletions , innovations , and recruitment from other molecular systems .
Microbial protein secretion facilitates environmental exploitation and manipulation [1] , [2] . The most frequent bacterial motility machinery , the flagellum , uses a type 3 secretion system ( T3SS ) to secrete its extracellular components . The non-flagellar type 3 protein secretion system ( NF-T3SS ) , often named injectisome , is homologous to the flagellum and also acts as a T3SS . This system is used to secrete its extracellular components and to deliver effectors into host cells . The NF-T3SS is an important virulence factor for animal pathogens within Salmonella , Escherichia , Chlamydia and Yersinia and plant pathogens within Xanthomonas , Ralstonia or Burkholderia ( for reviews see [3]–[8] ) . Some genomes encode several NF-T3SSs . In Burkholderia pseudomallei discrete NF-T3SSs are involved in animal and plant pathogenesis [9]–[11] , and in Salmonella enterica two NF-T3SSs are used in different phases of infection [12] . NF-T3SSs are exposed at the cell surface and are therefore targeted by the immune response . As a result , NF-T3SSs are being studied as targets for vaccines , e . g . for protection against Shigella [13] , and for new antibacterial drugs [14] . They have also been used to deliver vaccine antigens to the cytosol of eukaryotic cells [15] , [16] . NF-T3SSs have been most thoroughly studied for their role in antagonistic associations between pathogens and their hosts , but they also play an important role in mutualistic associations between bacteria and insects [17] , plants [18] , or fungi [19] . Phylogenetic evidence indicates that NF-T3SSs originated before most multicellular eukaryotes , possibly to favor interactions with early unicellular eukaryotes [20] . Each model NF-T3SS has its unique nomenclature in the literature . Hence , we use a unifying nomenclature throughout this publication [3] , naming the NF-T3SS core components with the prefix sct for secretion and cellular translocation , followed by the suffixes used in the Yersinia Ysc system ( see Table S1 for correspondence with other systems ) . When no unique name has been proposed we use the name of the Yersinia system by default , unless specifically specified . To avoid ambiguity , we follow Desvaux et al . [21] and use “translocation” for transport through a lipid bilayer and “secretion” for transport from the interior to the exterior of the cell . We use the term “delivery” to refer to the active transport from the interior of one cell to the cytosol of a second cell . The NF-T3SS is a complex protein structure that spans the cytoplasmic and outer membranes of bacteria and the cell envelope of the eukaryotic host to deliver effectors directly into its cytosol ( Figure 1A ) . The basal body of the NF-T3SS provides a structural basis for the secretion machinery involved in protein delivery . The outer membrane component of the basal body is formed by a homo-polymeric ring of secretins ( SctC ) [22] , [23] , whose inactivation leads to the accumulation of effectors in the periplasm [24] . This protein is part of a large family of pore-forming secretins , also found in Type IV pili ( T4P ) , Type II Secretion Systems ( T2SS ) , Flp pili encoded by the tight adherence ( Tad ) system and the extrusion machinery of filamentous phages [25] . At the inner-membrane the basal body inner ring is composed of SctJ and SctD [22] , [26] . The needle of the NF-T3SS is connected to the basal body at the inner membrane and extends outward from the cell [27] . In Salmonella , Shigella and Yersinia the needle is made of a major subunit ( SctF ) [26] , [28] , [29] . Phytopathogens do not have a needle but a flexible pilus-like structure encoded by HrpA [30] , [31] . HrpA shares several traits with SctF and its pilus presumably represents an adaptation of the NF-T3SS to the thick plant cell wall [32] . The needle is capped by a tip ( LcrV ) involved in regulating secretion and in positioning the translocation pore in the host cell membrane [33] , [34] . When the system is in contact with a target cell and delivery is activated , the translocon ( YopB and YopD ) acts as a pore-former in the eukaryotic membrane [35] . A few highly conserved proteins underneath the basal body are essential for the function of the NF-T3SS . One is a member of the F-/V- ATPase family ( SctN ) , with homologs in flagella and F0F1 proton-translocating ATPases [36]–[39] . This ATPase functions in the recognition and unfolding of secreted proteins and possibly participates in energizing the process of secretion [40]–[43] . In S . enterica Typhimurium , a protein similar to the flagellum C-ring “sorting” platform ( SctQ ) was suggested to orchestrate the order of protein secretion in interaction with SctK and SctL [44] . The remaining highly conserved proteins ( SctRSTUV ) form the secretion apparatus . Their functions are poorly understood but they are thought to include substrate selection and molecular switching between modes of secretion [45] , [46] . In Salmonella , Shigella , and Yersinia , another protein of importance , SctP , controls the needle-length during its assembly [26] , [47] , [48] . In Yersinia , SctP and SctU are involved in substrate-switching [45] , [49] , possibly by regulating the export of the inner rod protein ( SctI ) [49] . Two models were proposed for the initial stages of NF-T3SS assembly . In the outside-in model , inferred primarily from Yersinia data [50] , [51] , the initial assembly of the secretin rings ( SctC ) at the outer membrane favors assembly of the inner membrane rings by interacting with SctD . The secretion apparatus then assembles independently of the basal body . Together , these two structures recruit SctJ at the inner membrane . In the inside-out model , inferred primarily from Salmonella data [52] , assembly starts with the secretion apparatus , which provides a platform stabilizing the inner ring association between SctJ and SctD . The interaction of SctD and the secretin stabilizes the outer membrane rings . The SctQ C-ring and SctN ATPase are then recruited to the complex in both models . The general secretory pathway translocates the non-cytoplasmic components of this initial complex but once the ATPase is in place , the remaining components , including the inner rod ( SctI ) , the needle filament ( SctF ) and the tip ( LcrV ) , are secreted by the assembling NF-T3SS itself [53] . Upon contact with a host-cell membrane , the NF-T3SS initially secretes the translocators and then the effectors . The processes of NF-T3SS assembly and secretion of translocators and effectors involve a series of switches to control the timing , order and number of secreted proteins [54] . The flagellum assembly pathway shares many of these organizing principles , including switches of secretion substrates as the appendage forms [55] , [56] , and inside-out assembly [57] . Interestingly , it is not yet clear if NF-T3SS effectors are delivered through the central channel of the needle/pilus structures , as suggested by the designation “injectisome” . It is possible that the needle is only a sensor and regulator used to establish tight cell contacts and trigger the extracellular secretion of effectors [58] , [59] for subsequent translocation to the eukaryotic cell [60] . Experimentally studied NF-T3SSs include between 15 and 25 proteins , of which nine are ubiquitous core proteins ( SctCJNQRSTUV ) and four other ( SctDFLP ) are present in most systems ( Figure 1A , Table S1 ) [3] , [6] , [8] , [61] . Phylogenetic analyses of the ubiquitous proteins led to the identification of seven different NF-T3SS types [62] , each including one or a few different model systems: SPI1 includes an NF-T3SS from the S . enterica Pathogenicity Island 1 and from Shigella [27] , [63] , SPI2 is from a second locus in S . enterica [64] , [65] , Ysc from Yersinia [66] , Chlamy from Chlamydia trachomatis [67] , Rhizo from Rhizobium sp . strain NGR234 [18] , Hrp1 from Pseudomonas syringae [68] and Hrp2 from Ralstonia solanacearum [69] . Interestingly , this categorization distinguished systems involved in bacterial interactions with animals and protozoa ( SPI1 , SPI2 , Ysc , Chlamy systems ) from systems involved in interactions with plants and fungi ( Hrp1 , Hrp2 , Rhizo systems ) . A number of these NF-T3SS proteins are homologous to the flagellum [70] , clearly showing common ancestry of the two structures: of 13 ( nearly ) ubiquitous proteins in the NF-T3SS , nine have clear homologs in the flagellum ( SctJNQRSTUV/L ) , and two , SctP and SctF , have functional and structural counterparts [71] . SctP proteins play a central role , thought to be analogous to that of the flagellar protein FliK [26] , and they are interchangeable between Shigella and Salmonella SPI1 systems [47] . Unfortunately , they display very weak sequence similarity between closely related bacteria [47] , which precludes an evolutionary analysis by sequence similarity or phylogenetic methods . Similar problems arise when analyzing the chaperones of NF-T3SS , which are essential for needle complex formation and secretion , but are too diverse between NF-T3SSs of different families to allow comprehensive evolutionary studies . It is noteworthy that the flagellum outer membrane ring ( L-ring ) is formed with a lipoprotein unrelated to the secretin ( FlgH ) [72] . The trees of concatenated sequences of the flagellar components are approximately congruent with a tree of concatenated universal protein sequences [73] , suggesting relatively few cases of horizontal transfer [74] . On the other hand , the NF-T3SS has been extensively transferred among Proteobacteria [65] , [75]–[77] , albeit not among Chlamydiales [78] . When their genes were horizontally transferred , the imports seem to have included the entire set of genes in a single event for both flagellum and NF-T3SS [3] , [79] , [80] . A decade ago , several studies indicated one single phylogenetic split between the flagellum and the NF-T3SS [75] , [79] , [81] , [82] . This is compatible with three different evolutionary scenarios . The two elements might have independent origins from an ancestral system , or one system might have adapted pre-existing structures from the other system for a new function [61] , a process referred to as “exaptation” [83] . Understanding the details of the exaptation process requires an understanding of the direction of the evolutionary events . Current sequence databanks cover a much larger fraction of the prokaryotic world than ten years ago . Phylogenetic methods for dealing with multi-protein complexes have also been improved [84] , [85] , but these newer approaches have not yet been applied to infer the evolutionary history of T3SSs . The ongoing explosion of partially assembled genomes and metagenomes would also benefit from new tools for the detection and analysis of T3SSs from partial data . We have therefore produced such tools and applied them to genome data in order to determine the evolutionary origins and patterns of diversification of T3SSs .
We retrieved sequences corresponding to a diverse set of known flagella and NF-T3SSs from genome databanks . We focused initially on 12 gene families ( Table S1 ) , eight with homologs among flagella and NF-T3SSs ( the T3SS core genes: sctJNQRSTUV ) , one family specific to NF-T3SSs ( the secretin sctC ) and three specific to flagella ( genes encoding rod components: flgB , flgC and fliE ) . We searched for homologs of these genes , made multiple alignments , manually corrected them and built protein profiles ( Materials and Methods ) . We queried the proteins encoded in 1385 genomes containing 2575 replicons ( 1483 chromosomes and 1092 plasmids ) with these profiles using Hmmer 3 [86] . Replicons either had hits to the majority of the protein profiles ( Figure 1B ) , or to only few of them . In the latter case , the profiles retrieved homologs of the secretin and of the ATPase in other cell machineries . We filtered these hits , retaining hits that were statistically significant . We then selected hits from replicons containing a minimal number of the 12 gene families ( different criteria to infer NF-T3SSs or flagella , Materials and Methods ) , and those hits had to co-localize in units of two different core genes or more ( Materials and Methods ) . Subsequent expert analysis , informed by the available literature , resulted in a dataset of 921 putative T3SSs: 222 NF-T3SSs and 699 flagella distributed among 155 and 642 genomes , respectively . In the following sections , we summarize 216 NF-T3SSs , after excluding six on the basis of phylogenetic analyses ( Table S2 ) . We also analyzed a subset of 357 flagellar T3SSs that were representative of the diversity in the entire dataset and which had been manually curated ( Materials and Methods , Table S3 , Dataset S2 ) . The vast majority ( 92% ) of NF-T3SSs were encoded in chromosomes . NF-T3SSs were only identified in bacteria with outer and cytoplasmic membrane ( diderms ) : Chlamydiae , Proteobacteria , and Verrucomicrobia . Flagella were found in many more taxa , within diderms ( Acidobacteria , Aquificae , Bacteroidetes , Chloroflexi , Deferribacteres , Gemmatimonadetes , Nitrospirae , Planctomycetes , Proteobacteria , Spirochetes , Thermotogae and Verrucomicrobia ) , and also among bacteria lacking an outer membrane ( monoderms: Actinobacteria and Firmicutes ) . These results confirm previous studies showing that the possession of NF-T3SSs by bacterial taxa is much more restricted than flagella [79] . Some of the T3SS loci lacked core genes , but functional T3SS genes need not be in a single locus . We therefore investigated in detail the replicons with partial T3SS loci . 61 replicons had at least three of the nine NF-T3SS core genes homologs but lacked at least two of them . Only two of these systems corresponded to NF-T3SS and all others were of flagellar origin ( Figure 1B ) . This finding suggests that NF-T3SSs are rapidly deleted when they lose function . Incomplete loci might represent NF-T3SSs encoded in multiple loci , systems with different functions or systems undergoing genetic degradation . For example , a cryptic short NF-T3SS locus in E . coli ( ETT2 locus ) [87] often lacks sctT and genes encoding structural proteins such as sctL and sctD . ETT2 was suggested to play an important role in virulence by regulating the NF-T3SS of the locus for enterocyte effacement ( often termed LEE ) [88] , [89] . We then investigated the replicons lacking at most two of the nine core genes . Of 216 such NF-T3SSs , 21 included complete NF-T3SSs scattered in the genome and 10 corresponded to a Myxococcales system ( “Myxo” ) described below . As previously reported , the NF-T3SSs are spread over at least four loci in Chlamydia , three of which contain core genes [81] , [90] . Scattered NF-T3SS loci are present in all Chlamydiales genomes ( “Chlamy” systems ) , in Hamiltonella defensa [91] , an intracellular Proteobacterium , and in the plasmid pYPTS01 of Yersinia pseudotuberculosis PB1/+ . We note that the NF-T3SS is constitutively expressed in all development stages in Chlamydia [92] . Absence of specific regulatory elements might alleviate selection for the clustering of all NF-T3SSs genes and facilitate the fixation of rearrangements scattering the NF-T3SS into several loci . These disrupted loci are less likely to be transferred horizontally because acquisition of a complete system would require the co-transfer of different regions of a replicon . We tested the quality of the discrimination between NF-T3SSs and flagella by protein profiles with linear discriminant analysis ( Figure 2 , Figure S1 ) . Our results indicate that the accuracy of assignment was >97% in gene-by-gene analyses , and >99% for combined protein profiles ( see Materials and Methods ) , and that all mis-classified NF-T3SSs were in Myxo and Chlamy systems ( see below ) . The accuracy of discrimination between the two types of T3SS for single proteins shows that these profiles are potentially useful for unassembled genomic data , including metagenomic data . We have therefore implemented a web server that allows detection of NF-T3SS and flagellar genes with our profiles ( http://mobyle . pasteur . fr/cgi-bin/portal . py#forms::T3SSscan-FLAGscan ) . The NF-T3SSs described here can be queried and visualized from http://secreton . web . pasteur . fr . We now turn to the evolutionary origins of the T3SS , a topic that has been extensively debated [75] , [82] , [93] , [94] , in order to decide between three scenarios: the early split of the two systems , the flagellum-first or the NF-T3SS-first hypotheses ( Figure 3A ) . Our analysis showed that of the T3SS proteins with clear homologs between flagella and NF-T3SSs , only the ATPase also has homologs in other cell machineries with significant sequence similarity to allow rooting the T3SS tree . A set of homologs of the T3SS ATPase and F- and V- ATPase catalytic subunits [39] ( Protocol S1 ) were selected and aligned , resulting in sequences with an average length of 459 amino-acids . We selected 296 informative positions from the multiple alignment with BMGE [95] ( Dataset S1 ) , and chose the tree with the highest maximum likelihood from 200 phylogenies built with RAxML [96] . This tree supports the T3SS monophyly with high support ( 100% bootstrap ) , and places the root of the T3SS tree within flagellar sequences ( Figure 3B , Protocol S1 ) . NF-T3SS sequences emerge in one clade within the flagellar T3SSs . We also counted the proportion of the 1000 bootstrap trees fitting each of the three evolutionary hypotheses ( Figure 3A , Protocol S1 ) . 84% of the trees support the flagellum-first hypothesis , arguing strongly against an early split between flagella and NF-T3SSs or that flagella were derived from an NF-T3SS . We confirmed this result by an analysis on a larger dataset including all curated systems . It is often difficult to obtain clear bootstrap supports for inner branches in very large trees spanning sequences with limited similarity and/or few sites . However , even this very large dataset clearly supported the flagellum-first scenario ( >72% of the bootstrap trees , Text S1 , Figure S2 ) . In order to investigate early steps in the evolution of the NF-T3SS we reconstructed the phylogenies of the eight core proteins present in both NF-T3SSs and flagella for both single genes and their concatenated sequences . Initially we included the flagellar proteins to root the NF-T3SS tree . Then we restricted the analyses to the NF-T3SS proteins to obtain longer and more conserved multiple alignments allowing more accurate phylogenetic inference . The individual phylogenies of the eight core proteins support a common descent of all NF-T3SSs from a single ancestor and identify the same NF-T3SS groupings ( Figure S3 , Table S4 ) . These groupings extend and clarify a previous classification of NF-T3SSs [62] ( Figure 4 , Figure S4 , Text S2 ) . The use of the program Prunier [97] showed that any topological differences among the eight individual gene trees and the concatenate trees were supported by less than 90% of the bootstraps ( Text S3 ) . Thus , gene-wise and concatenated “rooted” and “unrooted” phylogenetic analyses all support a similar history for the eight core NF-T3SS genes showing that they evolved together , apart from their flagellar homologs . The NF-T3SS tree places the root between one group of systems found in Delta-proteobacteria of the Myxococcales order ( the “Myxo” group ) , and all remaining systems ( ≥98% bootstrap support , Figure 4 and Figures S4 , S5 ) . The early diverging Myxo group includes both a long and a short variant of the NF-T3SS locus . These variants lack core NF-T3SS genes , resulting in their prior annotations within the genome of Myxococcus xanthus as relics of NF-T3SS undergoing degradation [98] . If this interpretation were correct , then these genes should evolve quickly and our assignment of these variants to a basal phylogenetic position might be artifactual . However , we identified six additional genomes from the same clade ( Cystobacterineae ) having homologous systems ( Figure 5 ) ( see [99] for the taxonomy of Myxococcales ) . All fully sequenced genomes of Cystobacterineae have the “short” locus and a monophyletic group of three of these genomes also possesses the “long” locus . These loci have G+C contents within the 25–75% range of the G+C genomic content ( SeqinR [100] analysis with a 1 kb sliding window ) , and a conserved gene order ( Figure 5 ) . The core genes that are common to these variants correspond to the secretion apparatus , the ATPase , the smaller inner ring protein and the inner rod protein ( short locus ) . The long locus also contains the large inner ring protein . These core proteins interact with each other and also correspond to the most conserved NF-T3SS core proteins . The long and short loci each correspond to distinct monophyletic groupings ( Figure S4 ) that have probably been inherited vertically because the topology and branching structures of these phylogenies resemble those of the 16S rDNA tree ( Figure 5 ) . The conservation of these systems in sequence , gene composition and genetic organization is striking because the species harboring them diverged a long time ago . For example , the 16S rDNA subunits of Anaeromyxobacter and Myxococcus show lower sequence similarity than that between Escherichia coli and Vibrio cholerae . The strong conservation of these loci in sequence and organization over such long time scales suggests that they are functional . We argue that the Myxo NF-T3SSs probably derived from ancestors that were neither flagella nor protein delivery systems . Myxo systems lack proteins that are indispensable for flagellar function , such as FlgBCDEK , FliEG , FlgH and MotAB . They also lack NF-T3SS genes such as the secretin , the major needle subunit ( SctF ) , the tip protein ( LcrV ) and the translocon ( YopB/YopD ) . Homologs of the tip and translocon proteins may have been missed in our sequence similarity searches because of their rapid evolution . However , the flagellar proteins , the secretin and SctF are highly conserved and should have been found by our sequence similarity searches had they been present . Our profiles show significant sequence similarity between SctF , the major needle subunit of the NF-T3SS , and FliC/FlgL ( the flagellin and a hook-associated protein ) , whose homology was previously suggested based on structural data [71] , [101] . Hence , the earliest NF-T3SS probably contained an ancestral SctF that was lost in Myxo systems . The lack of an outer membrane channel and of SctF suggests that Myxo systems are not able to deliver effectors to eukaryotic cells and possibly not even to secrete proteins to the extracellular space . We next analyzed the diversification of NF-T3SS within the main branch of its phylogeny , i . e . among loci including a secretin . This branch includes all NF-T3SSs shown experimentally to deliver effectors into the eukaryotic cytosol . The first split along this branch separates the Chlamy from the other systems with 100% bootstrap support ( Figure 4 , Figure S3 , Table S4 ) . Subsequent diversification was very rapid within the other taxa as shown by a succession of short branches with weak bootstrap support ( Figure 4 and Figures S3 , S4 , S5 ) . To investigate the early NF-T3SS diversification we made a phylogenetic analysis of the NF-T3SS secretin together with secretins from T2SS , T4P , Tad system and filamentous phages [102] . Surprisingly , the phylogeny shows that secretins have been independently recruited to the NF-T3SS on at least three occasions ( Figure 6A ) . The Rhizo secretin RhcC2 branches together with secretins from the Tad loci ( e . g . RcpA and CpaC ) [103] . The secretin domain of Chlamy NF-T3SSs ( excluding a large unique N-ter region , see Figure 6B and [81] , [92] ) clusters with the gene IV secretin of filamentous phages within T2SS secretins . The secretins from the remaining NF-T3SSs cluster together in a third group ( Figure 6A ) hereafter referred as “NF-T3SS-like” secretins . The most parsimonious explanation for these results is that the last common ancestor of extant NF-T3SSs lacked a secretin . The secretin of Rhizo NF-T3SSs is encoded by two genes , rhcC1 and rhcC2 ( Figure 6B ) [104] , and we show that they have distinct origins . The gene rhcC2 encodes a protein whose architecture is similar to the secretin of the Tad locus of Caulobacter crescentus CpaC ( Figure 6B , Text S4 ) , in agreement with its phylogenetic position within Tad loci ( Figure 6A ) . It includes the “secretin” domain , absent from RhcC1 , and an N-terminal “BON” domain [105] . The gene rhcC1 is found at a conserved position in Rhizo loci , among other NF-T3SS core genes ( Figure 6C ) . The protein RhcC1 is homologous to the N-terminal part of the NF-T3SS-like secretins ( Blast search with e-value<10−3 , Figure 6B , Text S4 ) , which includes the first “N-domain” ( PFAM PF03958 ) of these secretins ( Figure 6B ) . This demonstrates that RhcC1 has a common origin with NF-T3SS-like secretins . Therefore , both protein domains analyses and phylogenetic analyses agree in suggesting the independent acquisition of the secretin in the ancestral Chlamy , and in the ancestor of all the other NF-T3SSs . According to this interpretation , the ancestral Rhizo system had originally an “NF-T3SS-like” secretin , RhcC1 , and secondarily acquired the secretin RhcC2 from a Tad locus . The recruitment of this second secretin was accompanied by the deletion of a large C-terminal fraction of the original secretin , and is thus an example of a partial homologous gene replacement . The association between the repertoire of NF-T3SS genes and the nature of the eukaryotic host maps well on the phylogenetic tree of the NF-T3SS ( Figure 4 , see Figure S4 and Text S2 for more details ) . Notably , there is a clear distinction between systems involved in interactions with animals or protozoa , on one hand , and plants and fungi on the other ( Figure 4 and Figure S4 ) . This is not necessarily expected because the phylogeny was based on ubiquitous , highly conserved , core genes that are not expected to drive the ecological diversification of the NF-T3SS . Indeed , Chlamydia effectors can be recognized and exported by the very distant NF-T3SS of Shigella [106] , and effectors of animal-associated NF-T3SS can be exported by plant-associated NF-T3SS [107] . Therefore , the specificity of the ecological interaction between the NF-T3SS and the eukaryotic cell is caused by the diversification of extracellular components such as the needle and the tip [26] ( see the gene content panel on Figure S4 ) . Hence , the clear separation of NF-T3SSs in terms of host cells in the phylogenetic tree of core genes likely reflects their genetic linkage to genes encoding the extracellular proteins of the NF-T3SS . The classification of the NF-T3SSs may help unravel unknown ecological interactions between free-living bacteria and eukaryotes ( Figure 4 , Figure S4 ) . Shewanella spp . are free-living marine bacteria . They are not pathogenic for fish , but are a major cause of marine seafood spoilage [108] . Their NF-T3SS system , SPI2 , is closely related to that found in Edwardsiella spp . which are true fish pathogens . We did not find any reports of specific interactions between M . mediterannea and eukaryotes , but this bacterium belongs to the microbiota of Posidonia oceania [109] , a marine angiosperm , and encodes a plant-related NF-T3SS ( Hrp1 ) . In some cases the associations between the NF-T3SS type and the host seem less clear-cut . X . albilineans , unlike other Xanthomonas phytopathogens , has one SPI1 system , which does not seem to be involved in pathogenesis , even though this bacterium proliferates in the xylem of plants [110] . Salmonella enterica encodes animal-related NF-T3SSs that are necessary for the infection of both animals and plants by this bacterium [111] . Hahella chejuensis , a marine Gamma-proteobacterium , is a potential biological agent to fight algae [112] but it is also part of the goat milk microbiota [113] , and encodes two Ysc NF-T3SSs of unknown function . Interestingly , such mismatches between NF-T3SS and eukaryotic host ( Figure S4 ) are only present in animal-protozoa systems that are able to interact with plants . Their study might provide clues on the historical adaptation of the ancestral NF-T3SS , which encoded a needle , to a cell-wall adapted pilus that can interact with plants . These observations also suggest a certain degree of flexibility in the interactions of NF-T3SSs with plant and animal hosts .
Our insights also allow us to propose a scenario for the evolution of the NF-T3SS ( Figure 7 ) . Initially , T3SS evolved to transport extracellular flagellar components [56] . The flagellar T3SS is not only an essential component of the flagellum but variants have also evolved to transport other proteins , e . g . virulence factors in Campylobacter jejuni and Y . enterocolitica [114] , [115] . In the endomutualist non-motile Buchnera spp . , the locus encoding flagellum components is reduced to the basal body , which has been proposed to serve as a protein secretion system [116] , [117] . Interestingly , flagella-like loci have been detected in the genomes of a dozen species that are not thought to have flagella [74] . These observations suggest that flagellar T3SSs have been exapted on multiple occasions for secretion of proteins unrelated to the flagellum . However , NF-T3SSs are monophyletic , indicating that their exaptation from the flagellum only occurred once . During experimental evolution , mutations that induce a loss of function are among the most frequent adaptive events detected [118] . We would then anticipate that exaptation to the NF-T3SS would have been accompanied by deletions of flagellum-specific genes . Yet the core function of the T3SS as a facilitator of protein translocation was probably never lost: ( i ) the secretion apparatus is highly conserved; ( ii ) the needle protein , which is translocated by the T3SS , is homologous to flagellar proteins; ( iii ) experimental evidence shows that extant NF-T3SS effectors can be secreted by the flagellum T3SS [119] . Our results contradict the proposal that NF-T3SS evolved in Chlamydiales before being transferred to Proteobacteria [62] , [93] . Transfer of the multiple loci within the Chlamy system would require multiple events , whereas the unique loci of other NF-T3SSs can be transferred in one single event . All Chlamy NF-T3SSs include a T2SS-like secretin whereas other NF-T3SSs share a secretin from a distinct origin ( Figure 6 ) . Finally , key elements between these systems have no homologs , e . g . the proposed tip protein for Chlamy ( CT584 ) cannot be aligned to tip proteins from other systems [120] . Hence , we propose that the last common ancestor of the NF-T3SSs derived from a flagellum , lacked a secretin and included a periplasmic or extracellular structure based on SctF . Interestingly , Spirochetes have periplasmic flagella , and in some cases lack the outer membrane protein FlgH [121] . Inactivation of the secretin in S . enterica SPI1 NF-T3SS prevents the formation of extracellular appendages but does not prevent the secretion of the main needle filament subunit ( SctF ) to the periplasm , where it remains associated with the inner ring proteins [53] . Hence , it is conceivable that a needle-like structure might have assembled at the periplasm in the ancestral NF-T3SS even in the absence of an outer membrane channel . We argue that this system was subsequently transferred across taxa prior to independent acquisitions of a secretin . The early evolution of the NF-T3SS was accompanied by the accretion of new genes that are present in even the most basal clades of the NF-T3SS ( Figure 7 ) . These include the structural genes sctD and sctI and probably also system-specific chaperones and regulators , whose evolutionary patterns are obscured by their fast evolutionary rates . The Myxo NF-T3SS was the first group to split from the others ( Figure 7 ) . Myxo systems are only present in Cystobacterineae and should have significant adaptive value because they are present in all available genomes of this taxon , show strict vertical inheritance and are highly conserved in sequence and genetic organization . The absence of the secretin and translocon as well as other proteins essential for protein delivery by other NF-T3SSs suggests that the Myxo NF-T3SS is unable to deliver effectors into the cytosol of eukaryotes . This is consistent with Cystobacterineae ecology , which are free-living bacteria that prey on other bacteria [122] . These systems could thus be involved in protein translocation and/or make some sort of periplasmic or extracellular structure . Functional analysis of these systems would be needed to understand their function . Acquisition of the secretin was the next major step in NF-T3SS evolution for which clear evidence is available . Our analysis shows that the secretin was recruited three times: in Chlamy ( from T2SS ) , in the other systems ( possibly from T4P ) and then again in Rhizo ( from Tad systems ) . This is consistent with the remarkable versatility of secretins as outer-membrane channels [123] . The interaction between the inner membrane rings and the secretin takes place between the C-terminal region of SctD and the N-terminus domains of the secretin [124]–[127] . Interestingly , the only part of the early secretin RhcC1 that remains in Rhizo after its partial replacement is the N-terminal domain that interacts with SctD ( Figure 6 , Text S4 ) . The Tad and the RhcC2 secretins lack this N-terminal domain and have a membrane-interaction , “BON” domain [105] , that is present in SctD but absent in other secretins . This domain architecture might interfere with a direct interaction between RhcC2 and SctD , which led to the conservation of RhcC1 as a linker between the two . In that case , interactions of the secretin during the assembly of the NF-T3SS might be critical for successful acquisitions of secretins from other systems . Flagellum assembly resembles the inside-out model of NF-T3SS assembly [128] , [129] . The ancestral NF-T3SS probably also assembled inside-out because it lacked a secretin . The inside-out assembly of the secretion apparatus and especially of the newly acquired SctD protein at the inner membrane might have led to interactions with secretins from other systems that stabilized an outer membrane channel in the NF-T3SS complex . Indeed , extant NF-T3SS secretins are inserted in membranes independently of the assembly of the inner ring . The inner ring assembles , and then stabilizes the secretin multimer [53] . These interactions presumably evolved towards a stable genetic linkage of the secretin with the NF-T3SS . Outside-in assembly modes , e . g . as proposed for Yersinia NF-T3SS , might have evolved after the acquisition of the secretin . Studies on the assembly of Myxo systems might therefore elucidate the mechanisms of assembly of the ancestral NF-T3SS and also of the evolution of the assembly process of the other NF-T3SSs . Acquisition of the secretin and of the translocon proteins allowed bacteria to deliver effectors to eukaryotic cells . This was followed by very rapid diversification of NF-T3SSs into groups with different characteristics and tropisms ( Figure 7 ) . Such rapid radiation hinders robust phylogenetic inference after the split of the Chlamy systems at the base of the remaining NF-T3SSs ( Figure 4 ) , even though we were able to infer older splits with strong confidence . Needle/pilus , tip and translocon proteins , all of which promote intimate interactions with the host , evolved quickly and were probably key determinants of NF-T3SSs radiation . The original NF-T3SS included a needle ( SctF ) resembling the flagellum homolog . The replacement of the needle by a pilus was a key late adaptation in NF-T3SSs that specifically interact with the cell walls of plants and fungi . Sequence evolution of the NF-T3SS pilus of some plant-associated bacteria is driven by strong positive/diversifying selection in response to host defenses [130] , [131] . It might be expected that vertebrate immune systems would have had similar effects on the evolution of animal-associated NF-T3SSs . Hence , diversifying selection on plant-associated NF-T3SSs is probably not the cause of the differences between pili and needles . Instead , the pilus probably reflects adaptation to the thick cell walls of plants and fungi . More genomic , functional and structural data on NF-T3SSs involved in plant interactions will be necessary to understand whether all these plant-associated NF-T3SSs arose independently or derived from the same ancestral NF-T3SS . This work shows how a key protein secretion system arose from the recruitment of a structure that evolved for another purpose . The T3SS was initially adapted to the transport of flagellar components through the membrane and was probably exapted on multiple occasions to transport other proteins . One of those exaptations resulted in the ancestral NF-T3SS . This system adapted to its new function by a series of gene losses and acquisitions . Strikingly , it acquired secretins multiple times . Thereafter , the system was able to deliver effectors directly to eukaryotic cells , which dramatically increased its rapid diversification due to the adaptive value of NF-T3SS for mutualistic and antagonistic interactions with eukaryotes . This evolutionary reconstruction represents a remarkable example of how successive losses and recruitments of components from a series of existing molecular machines can lead to the evolution of a new complex system .
Genomes were extracted from GenBank Refseq . To extend the taxon sampling , we added to the dataset some draft genomes of interest . We analyzed 1385 genomes with 2575 replicons ( 1483 chromosomes and 1092 plasmids ) . The NF-T3SS clusters identified in this study can be queried using different criteria ( including taxonomy and NF-T3SS family name ) , and visualized along with the results of our Hmmer profiles searches at http://secreton . web . pasteur . fr . The profiles of NF-T3SS and flagellum proteins can be queried at http://mobyle . pasteur . fr/cgi-bin/portal . py#forms::T3SSscan-FLAGscan . The list of NF-T3SSs and flagella included in phylogenetic analyses can be found in Dataset S2 . We selected one sequenced model organism from each described NF-T3SS family ( genomes marked in red on Figure S4 , list in Table S5 [6] ) . We extracted NF-T3SS protein sequences according to their genome sequence annotations and the literature . We performed similarity searches between these sequences with a Blast “all against all” search and applied a clustering algorithm with stringent parameters on the transformed e-value ( -log ( e-value ) , MCL [132] inflation parameter I = 1 . 5 ) to sequences showing hits with an e-value lower than 10−3 . We obtained nine families that were found in all model systems , which corresponded to the nine previously described NF-T3SS core proteins: SctC , SctJ , SctN , SctQ , SctR , SctS , SctT , SctU , SctV . We aligned these nine protein families with Muscle [133] , manually edited the alignments with Seaview [134] , and built sequence profiles with Hmmer [86] . A similar approach was conducted for flagella from phylogenetically distinct model organisms ( MCL clustering , I = 1 . 8 ) ( List in Table S3 ) . Out of 14 protein families widely conserved in flagella , eight were homologous to NF-T3SS core proteins ( Table S1 , protein clustering of protein families obtained from NF-T3SS and flagellar model systems , MCL parameter I = 2 . 5 ) , and were extracted to build Hmmer sequence profiles . We also selected three widely conserved flagellar families with no NF-T3SS homolog ( confirmed by the clustering above and Hmmer profile searches ) : FliE , FlgB , FlgC ( rod proteins ) , and built sequence profiles to identify other occurrences of these proteins . Additional profiles were also built for FlgDEKL , FliG , MotA and MotB ( MCL parameter I = 1 . 5 ) that are essential flagellar-specific genes [71] . To discriminate between homologous genes in flagella and NF-T3SSs , we performed a Hmmer search with the profiles of the eight proteins shared between them ( “core proteins” ) , the secretin ( the NF-T3SS-specific core proteins ) , and the three selected flagellum-specific proteins . Hmmer hits with Evalue and best-1-domain Evalue ( or i-evalue ) lower than 10−3 were selected . Two hits were said to be contiguous when separated by less than 35 genes ( average size of a flagellum cluster ) . We searched for clusters of contiguous hits to separate NF-T3SSs and flagellar systems . Clusters of genes showing positive hits for at least seven of the eight core genes , including a secretin , and lacking all three flagellum-specific genes were classed as NF-T3SSs . Sets of clusters of NF-T3SS core genes ( core genes+sctC ) not containing flagellum-specific genes were inferred as scattered NF-T3SSs . Flagellum clusters contained no secretin and had hits for at least 10 flagellar genes ( core genes+flagellum-specific genes ) . Scattered flagella had hits for at least 10 flagellar genes , and had at least one cluster containing flagellum-specific genes with one core gene . All detected NF-T3SSs , plus other clusters close to the definition above ( i . e . having fewer of the core genes clustered ) were manually curated and checked according to the available literature . Thus , the Myxo systems were retrieved even if they lacked a secretin and flagellum-specific genes . We did not include in our analysis the system of Lawsonia intracellularis because its flagellar genes and NF-T3SS genes were intermingled in different positions of its genome , rendering the reconstruction of the two systems more hazardous ( Table S2 ) . We attributed two types of Hmmer scores to genes with homologs in both systems: one score corresponding to the NF-T3SS profile and the other to the flagellar profile . We made a learning dataset including a third of the T3SS genes and their predicted role ( NF-T3SS or flagellum ) . This subset was randomly drawn from the set of all T3SS . Using linear discriminant analysis [135] , we predicted the type of system for the remaining two thirds of the dataset . We performed such an analysis with the combined dataset ( all eight genes common to the flagellum and NF-T3SS together ) as described above , and also in a gene-by-gene analysis . Accuracy is defined as the number of true predictions over the total number of predictions . We extracted from the genomes the genes encoding proteins homologous to T3SS core genes that were detected as part of a NF-T3SS or flagellum system . In a given system , when multiple Hmmer hits were available for a single gene , we kept the one displaying the lower Evalue and the maximal length . Many flagellar systems had multiple hits for the same genes scattered in the genome . We manually curated a subset of these flagella ( 357 out of 699 detected , the list of strains is in Dataset S2 ) . We aligned sequences with Muscle ( default parameters , [133] ) and selected informative sites with BMGE ( BLOSUM30 similarity matrix , gap rate cut-off = 0 . 20 , sliding window size = 3 , entropy score cut-off = 0 . 5 [95] ) . We built phylogenetic trees with RAxML ( [96] , Le and Gascuel [136] matrix + 4-categories-discretized Gamma distribution for rate variation among sites + empirical frequencies of amino-acids ) : we selected the best maximum likelihood tree among 200 different starting tree inferences , and computed 1000 bootstrap trees ( i . e . trees based on bootstrap alignments , consisting of randomized sites drawn with replacement from the original alignment , and of the same size of the original alignment ) . In the case of the ATPase SctN , we built an extra dataset that we extended with previously described outgroup sequences [39] ( see Text S1 ) and built a tree as described above . We also ran an extra phylogenetic analysis in a similar way on a subset of these sequences ( see Protocol S1 , Text S1 ) . We built a tree as indicated above with a secretin dataset that included i ) sequences identified in a previously described dataset [102] that were retrieved using their accession numbers; ii ) SctC of detected NF-T3SSs; iii ) all the secretins we found in Myxo and Chlamy genomes . Sequences displaying branch lengths longer than 1 substitution per site were excluded from phylogenetic analyses , and the phylogenetic reconstruction was run again with the cleansed dataset . This led to the exclusion of several flagellar systems and of five potential NF-T3SSs . Some of these systems are probably undergoing degradation ( Table S2 ) . The protein alignments of the genes were concatenated and phylogenetic trees were built with RAxML [96] ( Le and Gascuel matrix [136] + 4-categories-discretized Gamma distribution for rate variation among sites + empirical frequencies of amino-acids ) with 100 rapid bootstraps [96] for the rooted tree . We made a more thorough phylogenetic search for the unrooted dataset: we performed 100 bootstrap replicates , and mapped them on the best ( i . e . with the highest likelihood ) among 100 phylogenies obtained from distinct start trees . We attributed families to predicted NF-T3SSs according to previously defined families ( [62]; list of genomes in [6] ) . We searched a posteriori for putative significant inconsistencies between phylogenies of individual unrooted trees and the concatenate tree using the program Prunier [97] ( bootstrap threshold = 80% and 90% in both gene trees and in the reference tree , see Text S3 ) . We extended the cluster of NF-T3SS core genes by 10 genes upstream and downstream in the replicon sequence . All these protein sequences were extracted , and a similarity search ( Blast “all against all” ) was performed between them . Pairs of sequences having hits with e-value lower than 10−3 were clustered based on Blast alignments using the Silix program ( [137] , parameters used: minimal percentage identity = 20 , minimal percentage of sequence overlap = 50 , and minimal accepted length for sequences = 50 ) . The most abundant protein families , considering both replicons and NF-T3SS families , were extracted and Hmmer profiles were built from them to extend the search in NF-T3SS neighboring genes . We used the Scriptree program [138] to draw annotated trees ( Figure 4; Figures S3 , S4 , S5 ) and Figtree ( http://tree . bio . ed . ac . uk/software/figtree ) to draw trees ( Figure 3B , Figure 5 , Figure 6 ) . Graphics on Figure 1B , Figure 2 , and Figure S1 were drawn with R ( http://www . r-project . org ) . All figures were modified with Inkscape ( http://www . inkscape . org ) . | Most motile bacteria use a flagellum to move . The extracellular components of flagella are secreted by their own Type 3 Secretion System ( T3SS ) . The non-flagellar T3SS ( NF-T3SS ) , also named injectisome , includes many proteins that are homologous to flagellar components . NF-T3SSs are employed by many plant and animal pathogens to deliver effectors to host cells , including toxins . NF-T3SSs are complex protein machineries with >15 components that connect bacterial cell envelopes to eukaryotic cell membranes , including the intervening extracellular space . In this study , we designed computational tools to distinguish flagella and NF-T3SSs from other bacterial protein sequences . We show that NF-T3SSs evolved from the flagellum by a series of genetic deletions , innovations , and recruitments of components from other cellular structures . Our evolutionary analysis suggests that NF-T3SSs then quickly adapted to different eukaryotic cells while maintaining a core structure that remains highly similar to the flagellum . This is an example of evolutionary tinkering where a complex structure arises by exaptation , the recruitment of elements that evolved initially for other functions in other cellular structures . | [
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"g... | 2012 | The Non-Flagellar Type III Secretion System Evolved from the Bacterial Flagellum and Diversified into Host-Cell Adapted Systems |
We have examined the remains of a Pilgrim burial from St Mary Magdalen , Winchester . The individual was a young adult male , aged around 18–25 years at the time of death . Radiocarbon dating showed the remains dated to the late 11th–early 12th centuries , a time when pilgrimages were at their height in Europe . Several lines of evidence in connection with the burial suggested this was an individual of some means and prestige . Although buried within the leprosarium cemetery , the skeleton showed only minimal skeletal evidence for leprosy , which was confined to the bones of the feet and legs . Nonetheless , molecular testing of several skeletal elements , including uninvolved bones all showed robust evidence of DNA from Mycobacterium leprae , consistent with the lepromatous or multibacillary form of the disease . We infer that in life , this individual almost certainly suffered with multiple soft tissue lesions . Genotyping of the M . leprae strain showed this belonged to the 2F lineage , today associated with cases from South-Central and Western Asia . During osteological examination it was noted that the cranium and facial features displayed atypical morphology for northern European populations . Subsequently , geochemical isotopic analyses carried out on tooth enamel indicated that this individual was indeed not local to the Winchester region , although it was not possible to be more specific about their geographic origin .
We have recently examined cases of lepromatous leprosy ( LL ) recovered during excavations at the site of the St Mary Magdalen leprosarium , located to the east of Winchester , UK . Lepromatous or multibacillary leprosy is the more severe form of the disease , which lies at the opposite end of the spectrum from tuberculoid , or paucibacillary , leprosy . The two forms are manifestations of the same disease process , which is solely dependent on the immune response of the affected individual [1] . This leprosy hospital was an early foundation , probably dating back to the decades immediately following the Norman Conquest of 1066 [2] . The site is remarkable for the high number of burials displaying skeletal lesions characteristic of leprosy ( 86% ) [3] and the state of preservation of biomolecular markers of the disease , including mycolipids and DNA . This has previously allowed detailed genotyping by conventional PCR [4] and for next generation sequencing ( NGS ) to be successfully applied to four of the more robust cases . This revealed a remarkably high level of genomic conservation in the leprosy bacillus over the last one thousand years [5 , 6] . The inhumation that is the subject of the current study , designated Sk27 , had been buried in a chalk-cut anthropomorphic grave , similar to other individuals in the cemetery . This individual was interred together with a scallop shell , the traditional , and otherwise well-documented , symbol of a pilgrim who has made the journey to the shrine of St James in Santiago de Compostela , Spain ( Fig 1 ) . Pilgrimages to religious sites in medieval Europe were at their peak in the 12th century . This , together with stratigraphic data for the burial and radiocarbon dating , discussed later , suggested a time of death sometime in the first half of the 12th century . In the current study , we have looked in depth at the strain of leprosy causing disease in this pilgrim burial and have used radiocarbon dating and dietary isotopes to better relate these observations to the phylogeny of M . leprae and likely origins of this individual . As the skeletal lesions were minor , we have also sought evidence for other pathogens which may have contributed towards the early death of the individual . The findings are compared to other cases recently studied from this site . Together , these results add to our understanding of isolates behind the widespread nature of European leprosy in the high Middle Ages and in particular of a rare lineage which is less common amongst extant strains . The study concludes by considering these findings in their wider historical and comparative context
All necessary permits were obtained for the field studies , including a license ( -0070 ) to exhume and retain human remains , provided by the Ministry of Justice , 102 Petty France , London SW1H 9AJ . The site of St . Mary Magdalen , Winchester is designated by the site code AY352 . The skeletal remains , artefacts , environmental samples and paper archive are held in a permanent repository in the Department of Archaeology , University of Winchester . The skeleton that is the subject of this paper ( designated AY352/11/14 ( 489 ) Sk27 ) was excavated by hand from a sealed context and was from a single , west-east aligned , chalk-cut grave with a head-niche and inner ledge , within the northern cemetery area of the site . The grave had largely truncated an earlier grave ( Sk26 ) , of which only the head-niche , part of the northern side of the cut and a humerus remained in situ . ( The majority of Sk26 was recovered as disarticulated bone from the grave fill of Sk27 ) . The grave of Sk27 had subsequently been partially covered by the construction of the north wall of the medieval chapel ( ca . 1160s ) , leaving the west end of the grave under the doorway of the building . A number of other graves that predated the building of the chapel or other hospital buildings had been emptied out before walls or floors were constructed over them , so it is interesting to speculate as to whether Sk27 was deliberately left in situ . Recent excavations conducted at the eastern end of the medieval chapel , have revealed evidence for another structure , possibly an earlier phase of chapel dating to the original foundation in the late 11th century . It is possible that Sk27 was associated with this structure . The skeleton was in a supine and extended position , with the left upper limb at the side and the right upper limb flexed at the elbow with the hand on the pelvis . A scallop shell ( Pecten maximus , a species with a distribution along the European Atlantic coast from northern Norway to the Iberian peninsula [7] ) , pierced with two holes , was found on the left side of the pelvis ( see Fig 1 ) . The individual was very well preserved and nearly complete , with only the maxillary left lateral incisor , two hand phalanges and three pedal phalanges being absent . Two skeletons , Sk1 and Sk12 ( selected as controls for the biomolecular aspects of this study ) , were excavated by hand from sub-rectangular chalk-cut graves within the chapel . Sk1 had been buried within a “shouldered” coffin ( evidenced by the pattern of the coffin nails ) within a grave that cut through and disturbed a number of earlier graves . This would suggest that the burial dated to the 17th century , when the hospital/almshouse was in decline and was subject to reuse as a prisoner of war camp during the Anglo-Dutch wars of the latter half of that century [8] . The skeleton was supine and extended with the upper limbs straight at the sides and the hands on the pelvis . Sk12 was excavated from a plaster-lined grave covered with a Purbeck marble slab but was recovered as disarticulated bones , together with the disarticulated remains of a 2–3 year old child ( Sk13 ) suggesting that the grave had been robbed at some point before the chapel was demolished in the late 18th century . As the site was known to be a leprosarium and the possibility of finding individuals with skeletal evidence of leprosy was anticipated prior to excavation , the graves were subject to extensive sampling of the grave fills , which were then floated and hand-sorted . This allowed for near-complete retrieval of the small bones of the hands and feet , which are invaluable for the correct diagnosis of leprosy , particularly in its earlier stages . The skeletons underwent osteological examination in the Department of Archaeology , University of Winchester , Winchester , UK [3] . A detailed inventory of skeletal elements was completed using both written and diagrammatic proforma . Determination of sex in the adult individuals was undertaken using the methods of Phenice [9] for features of the pubic bone , Buikstra and Ubelaker [10] for the greater sciatic notch , and Acsádi and Nemeskéri [11] for features of the cranium and mandible . Individuals were then assigned one of five sex classifications: definite male ( M ) ; possible male ( ? M ) ; indeterminate ( ? ) ; possible female ( ? F ) ; definite female ( F ) . Estimation of age in the adult individuals was undertaken using the methods of Brooks and Suchey [12] for the pubic symphysis and Lovejoy et al . [13] for the auricular surface . Estimation of age in the non-adult individuals was undertaken using long bone lengths , dental development and epiphyseal fusion , as outlined in Scheuer and Black [14] . Individuals were then placed into one of the following age categories , using the Museum of London Archaeology guidelines , advocated by Falys and Lewis for adults [15]: foetal ( up to 36 weeks gestation ) ; perinate ( from 36 weeks gestation to 1 month ) ; infant ( 1 month to 1 year ) ; young child ( 1–5 years ) ; older child ( 6–11 years ) ; adolescent ( 12–17 years ) ; young adult ( 18–25 years ) ; young middle adult ( 26–35 years ) ; old middle adult ( 36–45 years ) ; mature adult ( 46+ years ) . Metric data from the crania , mandibles and post-cranial skeletons were recorded using the lists given in Buikstra and Ubelaker [10] , with additional measurements from the crania being recorded according to the criteria given in Wright [16] . The discriminant functions programs , FORDISC [17] and CRANID [16] were used to assist in the analysis of possible ancestral traits and geographic origins . In using this data , it is recognized that genetic admixture has resulted in considerable overlap between traits that are considered characteristic of major ancestral groups and therefore “pure” ancestral classifications are neither possible nor desired . There is no doubt that early craniometric studies were tainted by racism [18] but when modern methods and attitudes are used , it can still provide valuable additional information on the possible population affinity of archaeological individuals ( see the publications produced as part of the recent Roman Diaspora Project for examples of modern studies using craniometric data in combination with other techniques to assess patterns of migration and diversity in archaeological populations [19 , 20] . Stature was calculated using the methodology of Trotter [21] . All evidence for pathology and trauma was documented in detail through the use of descriptions and photographs and a variety of sources were used to diagnose the conditions represented . These sources are referenced at the appropriate places within the text . In particular , the individual was carefully examined for any skeletal manifestations of leprosy , including the rhino-maxillary syndrome and changes to the hands and feet ( described in detail elsewhere [3 , 4] ) .
Sk27 –The individual was found to be a young adult male ( 18–25 years ) with a stature of 168 . 9 ± 2 . 99cm ( calculated from the femur + tibia ) . This is within the expected range of average male stature for the period of 171cm , which was calculated by Roberts and Cox [34] from 8494 individuals from 34 British sites dating from c . 1050-c . 1550 . There were no lesions characteristic of leprosy in the rhino-maxillary area or hands . The lesions in the feet were restricted to the distal pedal phalanges , particularly those of the hallux , which were found to exhibit porotic changes and some resorption of the distal ends as a result of the initiation of achro-osteolysis . While such changes are not normally considered to be pathognomic for the disease , similar alterations are found in a number of other individuals from the hospital cemetery who do exhibit early-stage rhino-maxillary changes ( also recorded by Ortner [35] in individuals from Chichester ) and have been recorded as typical for early stage leprosy in the clinical literature ( Fig 2;[36] ) . The distal shafts of the tibiae of the individual also demonstrated evidence for remodelled periosteal lesions , with similar lesions also being found on the distal shaft of the left femur and the proximal shaft of the left fibula . These lesions form in response to inflammation or infection and can have numerous aetiologies , including trauma [37] , although it has also been suggested that , where the major focus of the reactive bone is on the distal ends of the bones , a diagnosis of leprosy should be considered [35] . If the lesions in this individual are to be ascribed to leprosy , it would suggest that the soft tissue manifestations of the disease , with associated inflammation and infection , were much more developed than the bony lesions . There was evidence for a large amount of dental calculus on the left maxillary and mandibular dentition ( Fig 3 ) . On the buccal surfaces of the teeth this had a nodular appearance and there was also evidence for calculus within the pits and furrows of the occlusal surfaces . This indicates that the calculus had not been smoothed down by the action of the cheek in normal masticatory function and that the entire occlusal surfaces of the dentition had at one point been covered by calculus . The left mandibular third molar had been lost ante-mortem and the alveolar bone was in the process of remodelling . It is possible that this tooth had been affected by dental caries that caused an amount of pain to the individual and prevented them from using the left side of their mouth during eating . The loss of this tooth allowed normal masticatory function to be restored by the time of the individual’s death ( as evidenced by the removal of calculus from the occlusal surfaces , leaving traces in the inaccessible pits and furrows ) . However , high levels of dental calculus have also been recorded in archaeological individuals with skeletal evidence for leprosy , where it is thought to relate to a soft , pulpy hospital diet , poor dental hygiene as a result of the leprous involvement of the oral cavity ( and also difficulty in using the hands to perform dental hygiene [38] ) , and mouth-breathing due to chronic inflammation of the nasal passages [3 , 39] . High levels of dental calculus are also found in modern individuals with the disease [38 , 40 , 41] . Dental calculus with a nodular appearance has been recorded in a number of other individuals from St Mary Magdalen with skeletal evidence for leprosy and was also seen in one individual with leprosy from St James and Mary Magdalene , Chichester , where it was argued to be related to paralysis of the facial muscles or loss of soft tissues of the cheek [39] . Therefore , it is possible that a similar aetiology may account for these changes in Sk27 , also supporting the assertion that the soft tissue manifestations of leprosy may have been more substantial than the bony lesions would suggest . The right maxillary central incisor showed resorption of the apical end of the root and the associated alveolar socket was shallow and porous in appearance . A number of individuals from St Mary Magdalen show evidence for constriction and abnormal development of the roots of the maxillary incisors and canines with associated shallow and porous alveolar sockets , which has been identified as leprogenic odontodysplasia [3 , 4] . In this case , however , the root does not show any evidence of constriction or abnormal development and the appearance is more consistent with resorption subsequent to trauma [42 , 43] . The individual had evidence for degenerative changes , in the form of porosity and osteophyte development , of the first and second cervical and the thoracic vertebrae , the coccyx , the acromial end of both claviculae and the anterior of the olecranon process of both ulnae . The mid-thoracic and lumbar vertebrae of the individual also had evidence for Schmorl’s nodes ( depressions of the surfaces of the vertebral bodies ) . There was evidence for entheseal changes , in the form of enthesophyte development , to the attachment sites for M . triceps ( the muscle principally responsible for extension of the arm ) on both ulnae , M . quadriceps femoris ( responsible for extending the knee ) on both patellae and for tendo calcaneus ( responsible for plantar flexion of the foot and flexion of the knee ) on both calcanei . The attachment sites for M . deltoideus ( involved in abduction , extension and rotation of the shoulder ) on the right scapula and the left clavicle , for the costoclavicular ligament ( responsible for stabilising the shoulder ) on both claviculae , for the common extensors ( responsible for extending the forearm ) on the right humerus , for M . vastus medialis ( involved in extending the knee ) on the left femur , for M . adductor magnus ( largely responsible for adduction and rotation of the thigh and involved in extension of the hip ) on both femorae and for M . abductor hallucis ( involved in abduction and flexion of the Hallux ) and M . flexor digitorum brevis ( responsible for flexion of the lateral four toes ) on the left calcaneus , also showed an increase in robusticity and development when compared to other attachment sites . The presence of degenerative changes in a young adult would seem to indicate an unusual degree of muscular and skeletal wear and tear related to increased levels of activity . That these changes do not simply reflect generalized wear and tear is supported by many studies demonstrating that an increase in the prevalence and severity of degenerative changes is strongly correlated with increasing age [44 , 45] . The assertion that these changes in Sk27 are related to activity patterns may also be supported by the finding that they are restricted to certain anatomical areas , namely the vertebral column , shoulders and elbows ( e . g . see refs [46–48] for studies where specific patterns of degenerative changes are linked to specific activity patterns , although a number of other studies have disputed this link , [49–51] ) . The presence of Schmorl’s nodes , which have a complicated aetiology but are presumed to be related to compressive forces to the back , including bending and twisting while supporting a weight [52 , 53] , may also support this interpretation , as would the presence of entheseal changes . These also have a complicated aetiology , with suggestions that they are more strongly correlated with age and sex than activity [54 , 55] , although recent studies have also found that activity may indeed play a part in their development [56 , 57] . During analysis , the cranial morphology of the individual was noted as being of an unusual type and unlike other individuals from the cemetery ( Fig 4 ) . Therefore , the cranial measurements ( S1 Table ) were inputted into FORDISC and CRANID , with additional measurements being taken where necessary . The individual was found not to have an affinity with any of the populations contained within the program databases , which do include some from northern Europe , although not Britain . Therefore , the individual could be said not to share a physical affinity with these northern European samples , although this should not be taken as implying anything about their specific identity or origin . Populations that are poorly represented in the database include those from southern Europe and northern Africa ( with the exception of Egypt ) , so there is a possibility that the individual could share physical cranial affinities with such populations , as his cranial morphology does bear similarities to other individuals from British archaeological populations who were also unclassifiable by FORDISC and have been suggested , on isotopic data , to originate from these areas [20]; ( Stephany Leach personal communication , 2012 ) .
Leprosy has afflicted humankind since antiquity and references to leprosy can be found in a diverse range of early sources including the Buddhist Pali Canon ( first few centuries AD ) , early medical texts , and the Bible , as well as evidence from the archaeological record . The earliest known human remains showing suspected skeletal evidence of the disease might date back almost 4000 years BP [69] . In Britain , cases are known from the 4th century AD onwards [70 , 71] but the disease reached endemic levels throughout the Middle Ages . This was followed by a decline from the 14th century onwards , the reasons for which have been the subject of speculation [72] . Reasons put forward to explain the decline have included susceptibility of sufferers to other infectious diseases like plague , due to Yersinia pestis , which ravaged the population of Europe in the middle of the century , and tuberculosis , another mycobacterium against which leprosy victims would have had little resistance . Indeed , leprosy is thought only to infect those with a predisposing genetic susceptibility . A number of human genetic factors probably influence the susceptibility to disease and its severity . These take the form of mutations in components of the innate and adaptive immune system ( see refs . [73 , 74] for reviews of candidate genes ) . The subsequent clinical course is determined by the ability of the host to mount an effective cellular immune response ( CMI ) . In tuberculoid , or paucibacillary , leprosy there are low numbers of bacilli , a good CMI response with an effective type 1-cytokine pattern and few lesions . At the other end of the spectrum , LL is characterized by numerous mycobacteria , often with disseminated sites of infection . This gives rise to the typical skeletal patterning often identified in human remains . In this form of leprosy , the T cells that mediate type 2-cytokine responses usually predominate . In recent years , some knowledge of the nature of medieval strains of leprosy has emerged from biomolecular studies of cases from the archaeological record [25 , 26 , 75] , including whole genome retrieval of a handful of European cases [5 , 6] . From these studies it has become apparent that the Mycobacterium leprae genome has not altered significantly in any way which might explain a decline in pathogenicity since the disease was at its peak in Europe . The Sk27 burial at the leprosarium of St Mary Magdalen , Winchester , represents the only example of a pilgrim burial with a scallop shell in a medieval leprosy hospital cemetery . Its presence in this context is of particular interest since a possible link between the increased popularity of pilgrimage and the rise of leprosy in western Europe , during the late 11th and early 12th century , has been previously noted [2] . The scallop shell has been associated with pilgrimage to the shrine of St . James the Great at the Cathedral of Santiago de Compostela , Galicia , Spain , since at least 1130 [86] . Pilgrimage to the shrine at Compostela grew particularly popular in the late 11th and early 12th century with the waning of Muslim attacks on the Iberian peninsula [87] . The Santiago pilgrimage , together with Jerusalem and Rome , represented one of the three great pilgrimages of the medieval period [88] and Santiago was the only place permitted to distribute scallop shells under pain of excommunication , although “fake” shells were also thought to have been sold during the medieval period [89] . The scallop shell buried with the Winchester individual has been identified as a specimen of Pecten maximus , which is found in Atlantic waters , including along the Galacian coast [7 , 90 , 91] . It is therefore the correct species of shell that would be expected to have been given to a pilgrim who had indeed completed the pilgrimage to Santiago . Burials with pierced scallop shells are generally rare , but there are examples both from Britain [92–96] , France [97 , 98] , Scandinavia [99] , Germany [100] , and a number from cemeteries along the pilgrimage route in Spain [101 , 102] . Throughout the medieval period the act of pilgrimage was viewed as a particularly efficacious spiritual and devotional practice and many of the medieval saints’ shrines were associated with miraculous cures and healing , including leprosy . For example , in the mid-12th century , Reginald of Durham related the story of a nobleman in southern England who conducted an experiment to determine which of England’s main cults would be most likely to cure him of the disease [103] . In England , although the principal shrines were Canterbury and Walsingham , Winchester was an important and popular pilgrim centre in its own right . Winchester in the early 12th century was a bustling and cosmopolitan city . Replete with shrines , religious institutions and hospitals , it also represented a central place in the pilgrimage landscape . Similarly , at Santiago de Compostela , during the 11th to 12th centuries , it is estimated that between 0 . 5 and 2 million people visited every year [104] . This could amount to over 5000 pilgrims a day . If , as the evidence presented above suggests , the pilgrim was not local to Winchester , his presence in southern England would not necessarily have been too unusual . Winchester housed several important relics and was also central to a network of pilgrim routes in the south of England stretching from Glastonbury in the west to Canterbury in the east . To the north of Winchester lay Reading Abbey , which was one of the most important pilgrimage sites in western Europe [86] and had acquired an important relic , the hand of St James , in the 1120s [87] . Such an acquisition would have been a major draw for pilgrims . Moreover , Winchester was only 15 km from the bustling port of Southampton where many pilgrims would have arrived from , or embarked upon , pilgrimages overseas . Thus Winchester , served by its own important shrines , was a key focal point in a wider pilgrim network . Our “Pilgrim” individual was buried in the Winchester leprosarium at some point in the early part of the 12th Century . His burial , in an anthroporphic grave cut was associated with a building , possibly an original chapel . The grave may have been left in situ when a later chapel was constructed above it , whereas others graves had been emptied out . These observations suggested he might have commanded a degree of status in death . The current study has shed a degree of light on the strain of leprosy from which he suffered and the skeletal signs of other problems which he endured , both related and unrelated to leprosy . The evidence found indicates that while he suffered from early-stage skeletal changes of leprosy , M . leprae DNA was recovered from diverse and macrosopically uninvolved bone samples , likely indicating that the disease was already more disseminated , possibly with soft tissue manifestations . Isotopic analysis showed he consumed a diet rich in animal protein but that he might not have been local to the chalk lands of Southern Britain . However , a number of aspects of his short life remain unknown . We cannot be sure of where he spent his early life . We do not know if he was already resident in the leprosarium before his pilgrimage , or whether he contracted the disease abroad and returned to Britain to end his life at St Mary Magdalen , Winchester . We have examined an 11th-12th century “Pilgrim” inhumation from the St Mary Magdalen Hill archaeological project , Winchester , UK . The anthropomorphic grave-cut contained the remains of a young adult male , between 18–25 years old at the time of his death . The grave also contained a pierced scallop shell , the symbol of the Camino de Santiago . Although interred in the North cemetery of the leprosarium , there were only minimal signs of leprosy on the skeleton and these were confined to the distal ends of the pedal phalanges and the lower legs . However , aDNA analysis revealed Mycobacterium leprae DNA in diverse skeletal elements , suggesting this individual suffered from lepromatous leprosy and would probably have displayed soft-tissue lesions in life . Genotyping showed he was infected with a type 2F isolate of M . leprae , nowadays associated with cases of leprosy from South-Central and Western Asia [4] . Several aspects of the burial and dietary isotope analysis indicated this may have been an individual of some prestige and means , who may have been a recent incomer to the hospital population . Strontium and oxygen isotopic analyses confirmed he was not local to the Winchester region but were not able to pinpoint his precise origins . However , despite limitations when using applied analysis to infer the origin , an unusual cranial morphology pointed to possible physical affinities with populations in North Africa or southern Europe . The occurrence of a type 2F strain in this individual would also be consistent with someone widely travelled or of possible foreign origin . Further ancient genome analysis linked to population genetics can potentially provide important additional information on the genetic origin , but overall these findings confirm the benefits of a multidisciplinary approach which allows investigation of the wider relationship between leprosy , medieval pilgrimage and M . leprae transmission . | This multidisciplinary research article , involving biomolecular analysis , osteology , strontium and oxygen isotopic analyses and archaeology , examines the remains of a Pilgrim burial excavated from the medieval leprosy hospital of St Mary Magdalen , Winchester , UK . Radiocarbon dating showed the remains dated to the late 11th–early 12th centuries , a time when pilgrimages were at their height in Europe . The leprosarium at Winchester is one of the earliest excavated examples from Western Europe and has been the subject of a series of recent academic papers . The site is remarkable for the high number of burials displaying skeletal lesions characteristic of leprosy ( 86% ) and the state of preservation of biomolecular markers of the disease , including mycolipids and DNA . Genotyping of the M . leprae strain showed this belonged to the 2F lineage , today associated with cases from South-Central and Western Asia . Several aspects of the burial and dietary isotope analysis indicated this was an individual of some prestige and means; an unusual cranial morphology pointed to possible origin outside of the British Isles . Strontium and oxygen isotopic analyses confirmed he was not local to the Winchester area but were not able to pinpoint his precise origins . Overall these findings confirm the benefits of a multidisciplinary approach which allows investigation of the wider relationship between leprosy , medieval pilgrimage and M . leprae transmission . | [
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"biology",... | 2017 | Investigation of a Medieval Pilgrim Burial Excavated from the Leprosarium of St Mary Magdalen Winchester, UK |
The ability of clonal bacterial populations to generate genomic and phenotypic heterogeneity is thought to be of great importance for many commensal and pathogenic bacteria . One common mechanism contributing to diversity formation relies on the inversion of small genomic DNA segments in a process commonly referred to as conservative site-specific recombination . This phenomenon is known to occur in several bacterial lineages , however it remains notoriously difficult to identify due to the lack of conserved features . Here , we report an easy-to-implement method based on high-throughput paired-end sequencing for genome-wide detection of conservative site-specific recombination on a single-nucleotide level . We demonstrate the effectiveness of the method by successfully detecting several novel inversion sites in an epidemic isolate of the enteric pathogen Clostridium difficile . Using an experimental approach , we validate the inversion potential of all detected sites in C . difficile and quantify their prevalence during exponential and stationary growth in vitro . In addition , we demonstrate that the master recombinase RecV is responsible for the inversion of some but not all invertible sites . Using a fluorescent gene-reporter system , we show that at least one gene from a two-component system located next to an invertible site is expressed in an on-off mode reminiscent of phase variation . We further demonstrate the applicability of our method by mining 209 publicly available sequencing datasets and show that conservative site-specific recombination is common in the bacterial realm but appears to be absent in some lineages . Finally , we show that the gene content associated with the inversion sites is diverse and goes beyond traditionally described surface components . Overall , our method provides a robust platform for detection of conservative site-specific recombination in bacteria and opens a new avenue for global exploration of this important phenomenon .
Seemingly clonal microbial populations often exhibit phenotypic and behavioral heterogeneity . This feature is widely observed in the microscopic world–from viruses to protozoa–and reflects the common need to adapt to the ever-changing environmental milieu . While point mutations and horizontal gene transfer influence long-term microbial evolution , sudden environmental fluctuations leave little room for the comparatively slow , conventional gene-induction response to facilitate adaptation . A common bet-hedging strategy adopted by bacteria is to alter the expression of specific cellular components ( e . g . flagella or pili ) in a dichotomous on-off mode . This process , termed phase variation , is heritable , reversible , and occurs at frequencies well-above typical mutation rates [1] . In addition , phase variation is a stochastic process for generating distinct subpopulations that might have better fitness or survival rate under rapidly changing , challenging conditions . The degree of diversity solely depends on the number of phase-variable loci . Accordingly , phase variation can quickly become the major source of heterogeneity with a profound impact on the survival or fitness capacity of the population as a whole . This is best exemplified in pathogens that need to constantly change the expression of surface antigens as a consequence of the pressure from the host immune system [2–4] . The underlying sources of bacterial heterogeneity are fundamentally diverse . One common mechanism of phase variation involves site-specific DNA inversions , catalyzed by the action of one or multiple tyrosine or serine-type recombinases [5 , 6] . The inverted genomic DNA fragment is frequently located in intergenic or 5’ untranslated regions and is delimited by short , inverted repeats . The inversion is typically cis-acting and has a direct impact on either the transcription or translation of the neighboring genes . This process creates a binary system that is either in a permissive ( on-configuration ) or non-permissive ( off-configuration ) state and as such is often dubbed a genetic or molecular switch . The net result is the creation of a heterogeneous bacterial community structure that is characterized by the co-existence of phenotypically distinct subpopulations . While switching is considered a stochastic process , environmental factors such as temperature , amino acids , carbon sources , osmolarity and iron limitation can influence inversion frequencies [7–10] . Additionally , an alternative model where cooperation rather than stochasticity is the driving force behind the switching has been proposed recently [11] . Recent evidence of lipoprotein phase variation in Mycoplasma gallisepticum and M . agalactiae also points towards a nonstochastic model during infection [12–14] . Phase variation as a result of DNA inversion was initially described in Salmonella enterica and Escherichia coli where it was associated with biphasic expression of flagella and pili respectively [15 , 16] . Using an analogy-based approach , other bacterial species were also found to use similar DNA inversion-mediated phase-variable mechanisms to control the expression of pili and related cell-surface appendages [15 , 17–21] . Expression of other surface components , such as outer membrane proteins and lipoproteins , have also been found to depend on DNA inversion [22–25] . However , DNA inversions do not affect merely surface components . For example , complex rearrangements among restriction-modification systems giving rise to differential methylation patterns have been extensively studied [26–31] . Additionally , DNA inversions are not confined to the bacterial realm , since they occur in bacteriophages , for example P1 and Mu , and plasmids such as R64 and p15B [32–34] . Finally , various non-surface components have been described to phase vary by mechanisms unrelated to DNA-inversion and ultimately influence multiple phenotypes related to immunoevasion , niche adaptation and virulence [35–42] . Despite the established importance and the substantial number of described examples in the literature , detection of novel DNA-inversion events remains a difficult task . This is primarily due to the lack of conserved and easily identifiable features specific to the inversion process . Site-specific recombinases cannot be used to determine the presence of genomic inversions in part because they are not intrinsically associated with the invertible site and might be encoded elsewhere in the genome . The only other hallmark of invertible sites are terminal inverted repeats . However , these are very short , typically in a range of 10–20 nucleotides and can often harbor mismatches that further hinders the ability of accurate detection . Recent technical advances have enabled researchers to probe bacterial population diversity to unprecedented levels . The advent of affordable next-generation sequencing has proved to be specifically useful in this regard as deep sequencing of genomic DNA harvested from a population of cells allows the capture of associated genomic heterogeneity in its entirety , including small DNA-inversions [43 , 44] . However , the majority of tools aimed at genomic structural variation discovery were developed for eukaryotic and specifically human genomes , especially in the context of cancer-associated chromosomal rearrangements [45 , 46] . Recently , a workflow incorporating several previously developed tools was tested for structural variation detection in bacteria . While single-nucleotide polymorphisms , small insertions , deletions , duplications and translocations were identified with high sensitivity , inversions remained notoriously difficult to detect [47] . In this manuscript , we present a simple and easily applicable method for detection of conservative site-specific recombination events by whole-genome sequencing or from previously generated sequencing datasets . We first used simulated sequencing data to conceptually validate our approach and to optimize detection parameters . We then applied this method to an epidemic isolate of Clostridium difficile , for which we confirmed four known and identified three novel inversion sites . Using an experimental approach , we validated the inversion potential of all identified sites , quantified their prevalence in exponentially and stationary growth phase and assessed the DNA inversion dependence on the major recombinase , RecV . Furthermore , using a fluorescent-reporter assay , we show that one gene found next to the inversion site is expressed in a phase-variable manner . Finally , we extend our analysis to 209 bacterial and archaeal sequencing datasets and show that this method can be used to detect known and novel inversion sites .
We reasoned that genomic inversions could be detected by looking for specific signatures following high-throughput deep sequencing of microbial genomes . Typically , paired-end sequencing on Illumina’s platforms produces millions of intrinsically associated pairs of short sequences called reads . Upon mapping to the reference sequence , these pairs of reads are characterized by similar inner-mate distance and converging orientation , i . e . one read from a pair maps to the forward strand and the other read from a pair maps to the reverse strand of the reference sequence ( region 1 in Fig 1A ) [48] . An atypical orientation of paired reads is produced when an inverted segment , illustrated by the black-and-white gradient in Fig 1A , is sequenced and mapped back to the unchanged , reference sequence . The resulting read pairs have the same orientation , i . e . both reads map to the same strand . Additionally , the read pair has an increase in the inner-mate distance matching approximately the size of the inversion . This scenario is possible if one read from a pair maps to the invariable region of the genome and the other read from a pair maps to the invertible segment ( region 2 in Fig 1A ) . Therefore , the presence of read pairs having the same orientation and higher mean inner-mate distance can be used as specific signature to detect genomic inversions . In addition to identifying invertible regions , recombination sites at single-nucleotide level can also be inferred from genomic high-throughput sequencing . As illustrated in Fig 1B , individual reads that span the junctions of invertible sites are trimmed on either the 5-prime or 3-prime end by the alignment software during the mapping process . The trimming , also called clipping , allows for reads to be aligned despite not matching contiguously to the reference sequence . This process results in the accumulation of trimmed reads at both extremities of the invertible segment with the specific build-up of 5-prime end clipped reads at the site of recombination . Mapping the start position of the 5-prime clipped reads therefore allows for precise identification of the site where the DNA strand is broken by the enzymatic activity of the recombinase to initiate the strand exchange required for inversion . We took an in silico approach to validate and optimize the proposed method . We first created an artificial and random DNA sequence that was subsequently used as the reference . We then manually reverse-complemented five distinct genomic regions ranging from 100 bp to 5 , 000 bp reproducing the natural process of conservative site-specific recombination . Next , both artificial genomes , i . e . reference and inverted , were individually used to simulate sequencing reads by emulating Illumina’s sequencing process with available bioinformatics tools [49] . In order to match variations in frequencies one could expect to find in invertible alleles in bacterial populations , we combined reads generated from both artificial genomes at proportions ranging from 0 . 01% to 50% ( S1 Methods ) . Following read mapping to the reference genome , same-orientation reads as well as 5-prime end clipped reads were extracted from the dataset and analyzed to identify genomic locations with high enrichment indicative of putative inversions . As expected , all five genomic locations presented high enrichment for same-orientation and 5-prime end clipped reads perfectly matching the genomic locations where inversions were introduced ( see S1 Fig for a representative example ) . These observations confirmed our initial hypothesis that small genomic inversions create specific and easily identifiable signatures in sequencing datasets . We then sought to determine the optimal parameters under which inversions up to 5 kbp are detected . We found that small read lengths ( e . g . 50 bp ) and larger insert-sizes ( e . g . ≥ 500 bp ) allowed for better detection of inversion ( S2 Fig ) . Additionally , read length was critical for detection of small inversions . For instance , no reads could be detected for a 100 bp inversion with read length of 150 bp regardless of other parameters . Finally , the limit of detection , arbitrarily defined as a cluster of ≥10 reads , was found to be significantly influenced by all three variables . Using optimal parameters ( i . e . smaller read length and larger insert-size ) , the limit of detection ( i . e . the frequency of the inversion in the population ) was estimated to be 0 . 1% for inversions larger than 500 bp and approximately 1% for inversions smaller than 500 bp . For suboptimal conditions ( i . e . longer read length and smaller insert-size ) , the limit of detection increased above 1% but was lower than 10% in all tested conditions ( S2 Fig ) . The limit of detection was also directly proportional to the sequencing depth ( S3 Fig ) . Taken together , these observations indicate that we can detect rare events of genomic inversions when a reference sequence and sufficient sequencing depth are available . Following the in silico validation of the method , we proceeded to determine the presence of genomic inversions in the opportunistic pathogen , C . difficile , where prior work has identified four short invertible regions designated “Cdi” ( for Clostridium difficile inversion ) [22 , 50 , 51] . Two of these invertible sites , Cdi1 and Cdi4 , have been shown to control the expression of adjacent genes ( cwpV and flagellar , respectively ) in a phase-variable manner . Cdi2 and Cdi3 are predicted invertible sites that have not been experimentally confirmed [50] . In order to determine if additional and similar genetic switches were present within C . difficile genomic context , we took advantage of existing datasets deposited in Sequence Read Archive repository ( SRA , https://www . ncbi . nlm . nih . gov/sra ) . Among the 8 , 468 results for C . difficile , we chose a single dataset derived from the sequencing of an epidemic ribotype-027 isolate at The Wellcome Trust Sanger Institute . We chose this dataset mainly because of its high sequencing depth ( 93 , 569 , 362 paired reads of 75 bp ) , which ensured that we could identify , in theory , inversions present at frequencies down to 0 . 1% . Reads were mapped to the C . difficile R20291 reference genome with high efficiency ( 90 , 185 , 223 mapped reads , 96 . 4% ) resulting in mean coverage of 1614X . Extraction of reads with the same relative orientation yielded a total of 256 , 856 pairs ( 513 , 712 individual reads , 0 . 57% ) , while extraction of 5-prime end clipped reads returned a total of 37 , 062 ( 0 . 04% ) reads . These low counts are consistent with the premise that unidirectional and 5-prime end clipped reads are rare . Cluster analysis revealed seven distinct groups with inversion sizes ≤ 5 kbp and variable read counts ( Fig 2A ) . Close examination of six individual clusters revealed strong enrichment of unidirectional read pairs in intergenic regions ( Fig 2B–2G ) , while one cluster spanned a small open reading frame ( Fig 2H ) . All identified regions also had a sharp accumulation of 5-prime end clipped reads on two distinct genomic positions , effectively identifying putative inversion boundaries ( Fig 2B–2H , separate plot in the top right corner , green bars ) . Since inverted repeats border the putative inversion segments , these regions may be recombining to generate an inversion event ( Fig 3 ) . Additionally , Cdi2 and Cdi5 sites are bordered by identical inverted repeats , suggesting recognition by a common recombinase . All other inverted repeats were unrelated . In the order of appearance , the first two clusters correspond to the previously described flagellar ( Cdi4 ) and cwpV ( Cdi1 ) switches respectively . Corresponding left and right inverted repeats as well as the size of the inversion perfectly match with previous reports [22 , 51] . The third cluster correspond to the previously cited Cdi2 [50] , located in vicinity of a signaling protein ( locus_tag CDR20291_0685 ) with conserved diguanylate cyclase ( GGDEF ) , diguanylate phosphodiesterase ( EAL ) , and sensor PAS domains . In an earlier study , the GGDEF-domain was shown to be defective but the EAL-domain was found intact [52] . An almost identical element bordered by the same inverted repeats is part of the fourth cluster named Cdi5 . CDR20291_0963 is the first gene in an apparent operon of three encoding a putative membrane bound O-acetyl transferase . The remaining coding sequences from the operon , CDR20291_0962 and 0961 encode respectively a SGNH hydrolase-like protein and a hypothetical protein with no conserved domains . The fifth cluster corresponds to the previously cited Cdi3 [50] , located upstream of another putative signaling protein ( locus_tag CDR20291_1514 ) containing both GGDEF and EAL domains . Once again , the GGDEF domain is mutated [52] , indicating that this protein is likely involved in degradation rather than formation of c-di-GMP . The sixth cluster , termed Cdi6 , is located upstream of an apparent operon of three genes encoding a classical two-component regulatory system . CDR20291_3127 encodes a putative signal transduction histidine kinase that carries a dimerization/phosphoacceptor domain , a histidine kinase domain on the C-terminal cytosolic portion , and a galactose binding-like domain on the N-terminal extra-cytoplasmic portion . This histidine kinase gene is flanked by genes encoding two cognate response regulators , CDR20291_3126 and 3128 , which have conserved C-terminal effector and N-terminal receiver domains . The seventh cluster , Cdi7 , spans a small open reading frame of 228 nucleotides encoding a hypothetical protein ( locus_tag CDR20291_3417 ) containing a domain of unknown function DUF1413 . Collectively , these results suggest that there are more invertible sites in the C . difficile R20291 genome than previously thought; these sites may influence a variety of cellular functions based on the functional diversity of genes encoded in vicinity . To determine if identified regions are subject to inversion during bacterial growth , we performed orientation-specific PCR on genomic DNA extracted from exponentially growing cells . Our PCR strategy and primer design are presented in Fig 4A . Using this approach , we detected two bands with the expected molecular weight corresponding to both orientations for all seven identified regions ( Fig 4B ) . We refer to a “published” orientation to indicate the sequence present in the published genome of C . difficile R20291 , and “inverse” orientation to refer to a sequence with an inversion in the corresponding site . Orientations were confirmed by DNA sequencing of the PCR products . This result effectively confirmed that all invertible segments , identified with our bioinformatics approach , exist in both orientations in actively growing cells under normal lab conditions . Since our end-point PCR approach did not allow for quantification of the frequency at which different orientations exist within bacterial population , we used new primers with high and very similar amplification efficiencies to allow for relative quantification using the ∆∆CT method ( S2 Methods ) . The percentage of the inverted state relative to the published orientation for C . difficile R20291 for all seven switches was determined during mid-exponential and early-stationary phase growth rate ( Fig 4C ) . As expected for a stochastic process , we found that different switches coexist in different proportions . In line with previous findings [51] , the flagellar switch , Cdi4 , occurs predominantly in the published ( ON ) orientation as the mean frequency of the inverted ( OFF ) state was found to be 16 . 0% , 12 . 6–20 . 2% ( 2 Standard Deviations or 95 . 45% confidence levels ) in actively growing cells . Similarly , the percentage of the inverted state ( ON ) was 14 . 3% , 13 . 4–15 . 4% for the cwpV switch , Cdi1 , which is marginally higher than previously reported values ( ~5–10% ) [22 , 53] . Switches detected upstream of both cyclic-di-GMP signaling proteins , namely Cdi2 and Cdi3 , were found to have higher inverted orientation proportions with respective frequencies of 67 . 0% , 57 . 8–75 . 1% and 51 . 4% , 37 . 7–65 . 0% . In contrast , the remaining three switches inverted at low frequency . Cdi7 had the lowest proportion quantified at 0 . 5% , 0 . 4–0 . 6% followed by Cdi5 at 2 . 6% , 1 . 7–3 . 8% and Cdi6 at 4 . 3% , 4 . 1–4 . 6% . Substantial differences in orientation frequencies suggest a low level of co-regulation , which in turn implies that C . difficile exhibit remarkable variations in inversion orientations on a single-cell level . Predictably , this should increase overall population diversity and collective functions . However , this presumed diversity is relatively stable , as nearly identical inversion proportions were found when genomic DNA was harvested from cells grown to early stationary growth phase . Collectively , these results demonstrated that our method allows for accurate and genome-wide detection of phase variable-like genomic inversions with wide range of input frequencies . Since the previously characterized C . difficile switches , Cdi1 and Cdi4 , have been shown to control the expression of downstream genes in the classical on-off mode reminiscent of phase variation , we sought to determine if genes found in the vicinity of newly identified switches might experience the same type of expression control . We thus developed a strategy to detect expression of CDR20291_3128 on a single-cell level using a fluorescent transcriptional reporter . Analysis of previously published transcriptomic data suggested that CDR20291_3128 is part of an operon with CDR20291_3127 and 3126 ( S4 Fig ) [53] . We thus decided to replace the entire coding sequence of the first gene from the predicted operon , CDR20291_3128 , with a C . difficile codon-optimized SNAP-tag gene reporter . The reporter strain , C . difficile R20291 ∆3128::SNAP-tag , was labeled with cell-permeable substrate and observed under a fluorescence microscope . As expected , no fluorescent signal was observed for the wild type R20291 strain as it lacks the SNAP-tag reporter . On the other hand , ∆3128::SNAP-tag cells displayed a robust but bimodal signal consistent with the hypothesis that the expression of CDR20291_3128 is likely phase-variable ( Fig 5 ) . Counts of bright cells were done on 15 images from different fields from two biological replicates and compared to the counts of total number of cells ( ~300 cells / image ) using ImageJ . The proportion of fluorescent-positive cells was estimated to be 4 . 28% ± 2 . 15% ( standard deviation ) which is virtually identical to the inverted orientation of the switch as quantified by qPCR ( 4 . 3% , 4 . 1–4 . 6% , Fig 4C ) . This suggests that the Cdi6 might be directly regulating the expression of the operon in an on-off manner as it was previously demonstrated with Cdi4 and Cdi1 switches . Accordingly , the inverted orientation likely represents the on-configuration and the published orientation represents the off-configuration of the switch . The tyrosine recombinase RecV catalyzes inversion of flagellar ( Cdi4 ) and cwpV ( Cdi1 ) switches [22 , 51] , so we sought to determine if RecV is also necessary for the inversion of newly identified switches . Inactivation of recV should prevent further inversions , locking individual switches in either the published ( pub ) or inverted ( inv ) orientations . We performed orientation-specific PCR in R20291 recV− ( recV::ermB ) strain constructed using ClosTron mutagenesis [53] . Consistent with previous reports , we observed a single orientation for both flagellar ( Cdi4 , inverted ) and cwpV ( Cdi1 , published ) switches in the recV−strain ( Fig 6 ) . Similarly , we observed only published orientation for Cdi5 and Cdi6 switches in the recV−background . On the other hand , we observed both orientations for Cdi2 and Cdi3 albeit with different band intensities as compared to the wildtype strain suggesting impaired but not complete loss of inversion . Finally , we did not detect any alterations for Cdi7 in the recV−background . However , due to the non-quantitative aspect of end-point PCR , we could not draw conclusions based merely on band intensities . We therefore used a more sensitive qPCR for the following experiments . As a second approach , we reasoned that overexpression of RecV would disrupt the relative stoichiometry and cause shifting of baseline proportions of the distinct switch orientations . We therefore placed recV with its native Shine-Dalgarno sequence under the control of a tetracycline-inducible promoter . The resulting plasmid was transferred in C . difficile R20291 wildtype strain by conjugation . Following induction , genomic DNA was extracted and the relative proportions of all switches quantified by qPCR ( Fig 7 ) . Change in the inversion proportions when recV was overexpressed relative to wildtype strain carrying the empty plasmid was observed for Cdi4 and Cdi1 as expected , but also for Cdi2 and Cdi6 . This is in agreement with our previous experiments in recV−background , as these switches were either locked ( Cdi4 , Cdi1 and Cdi6 ) or partially locked ( Cdi2 ) . No change in relative proportions was observed for Cdi5 , Cdi3 and Cdi7 switches . This observation partially contrasts with our previous experiment where loss of recV significantly impacted both Cdi5 and Cdi3 inversion . Lastly , overexpression of RecV did not affect the frequency of Cdi7 switching . Taken together , these combined observations suggest that RecV is essential for inverting Cdi4 ( flagellar switch ) , Cdi1 ( cwpV switch ) and Cdi6 , partially required for inverting Cdi2 , Cdi5 and Cdi3 , and dispensable for inverting Cdi7 . Thus , additional recombinases likely mediate inversion of some sites , either alone or in concert with RecV . Having successfully detected known and novel invertible sites in C . difficile , we aimed to determine whether other bacterial species harbor similar inversion signatures . Once again , we took advantage of sequencing datasets deposited in Sequence Read Archive ( SRA ) and European Nucleotide Archive ( ENA , https://www . ebi . ac . uk/ena ) ) . We limited our analysis to a subset of available datasets satisfying the following criteria: minimum of 2 million read pairs , maximum read length of 150 bp and inner-mate distance lower than 1 , 000 bp . Preference was given to those datasets for which the full-length reference sequence was also available . Out of 209 analyzed sequencing datasets , 203 were of bacterial and 6 of archaeal origin ( S2 Table ) . Bacterial samples were distributed among 13 phyla with marked bias toward Proteobacteria ( n = 80 ) and Firmicutes ( n = 66 ) , reflecting the limited diversity of available sequences in SRA and ENA repository databases . However , the overall diversity was relatively high with 127 different genera encompassing 177 different species . The remaining 26 samples represented distinct subspecies , strains or serovars . Archaeal samples were from 2 phyla and represented 6 different genera and species . The analysis procedure was automated with a custom script and putative inversions were further manually scored based on the size , intergenic location and the presence of inverted repeats or recombinases in vicinity . A complete summary of the analysis is reported in S2 Table . Overall , we found clear signatures of inversions in 43 samples covering 30 different genera and 34 distinct bacterial species . No signs of inversions were found in our small subset of archaeal genomes . Putative inversions were found in between 10–50% of species within the bacterial phyla; Firmicutes ( 15/66 , 23% of unique species ) , Bacteroidetes ( 7/20 , 35% ) , Proteobacteria ( 8/80 , 10% ) , Actinobacteria ( 3/19 , 16% ) , Spirochaetes ( 1/8 , 13% ) and Synergistetes ( 1/2 , 50% ) . Some interesting patterns were observed . Among 15 signature-positive unique samples from Firmicutes phylum , 14 belong to the class Clostridia and only 1 belong to the class Bacilli . Similarly , in the phylum Proteobacteria , the majority of signature-positive samples were detected in Gammaproteobacteria class ( 7/55 , 13% ) , one in Betaproteobacteria ( 1/13 , 8% ) and none in Alphaproteobacteria ( 0/4 ) , Deltaproteobacteria ( 0/2 ) and Epsilonproteobacteria ( 0/6 ) . On the other hand , signature-positive samples were more evenly distributed in Bacteroidetes phylum ( n = 20 ) , with most positives in Bacteroidia class ( 5/8 , 63% ) , one in Flavobacteriia ( 1/5 , 40% ) and Cytophagia ( 1/3 , 50% ) and none in Chitinophagia ( 0/2 ) and Sphingobacteria ( 0/2 ) . Overall , we found that many bacterial species harbor signatures of inversion yet they appear to segregate in specific lineages . This observation hints at possible evolutionary conservation and selective pressures , but the small and uneven sample size hinders robust statistical analysis . While DNA inversions have been readily described among bacteria , bacteriophages and plasmids , the diversity of the associated gene content was found to be relatively limited . Following identification of invertible sites among 34 distinct bacterial species , we proceeded to determine the surrounding genomic context . Unsurprisingly , we found high prevalence of recombination in between hsdS genes associated with type I restriction-modification ( R-M ) systems . This well-known phenomenon , described in a variety of bacterial species , is believed to influence global gene expression via alterations in methylation profiles ( recently reviewed in [54] ) . We found signs of DNA inversions among type I R-M systems in 13 distinct bacterial species confirming their broad occurrence . Genes encoding cell surface structures such as fimbriae , flagella and pili were also prevalent in vicinity of invertible sites . Some of the identified invertible segments were previously described , such as the fim switch in E . coli and the mad switch in Photorhabdus luminescens , but others were unknown . For example , we found a novel invertible site in vicinity of fimbriae locus in Providencia stuartii . In contrast to E . coli and P . luminescens fimbriae switches that are short ( 296 bp and 266 bp respectively excluding inverted repeats ) and contain only a promoter , this putative invertible segment is significantly larger ( 844 bp excluding 14 bp imperfect inverted repeats ) and encloses an open reading frame encoding a recombinase . In contrast to other clades , the most prevalent functions encoded in vicinity of invertible sites in Clostridia were related to intracellular signaling and chemotaxis ( S2 Table ) . To the best of our knowledge , none of these invertible sites have been previously described . For example , Anaerotignum propionicum DSM 1682 ( formerly Clostridium propionicum ) harbors an inversion signature located in vicinity of a methyl-accepting chemotaxis protein . Similarly , another inversion signature is found in Desulfitobacterium dehalogenans ATCC 51507 next to an open reading frame encoding a putative signaling protein with a phosphohydrolase conserved HD-type phosphodiesterase domain . Similarly , two distinct invertible sites , both found in proximity of genes encoding chemotaxis components are present in Clostridium thermocellum DSM 1313 . DNA inversion among prophage regions were readily detected in 4 species of Proteobacteria . The specific prophage regions seemed to revolve around structural genes , particularly tail fibers , which is also a well-known phenomenon occurring in bacteriophages such as P1 and Mu [33] . Finally , several species from Bacteroidetes phylum presented multiple DNA inversions spanning various cell surface components such as capsule and putative carbohydrate-binding receptors . This is consistent with previous reports where numerous invertible segments were found in several Bacteroides genomes [55 , 56] . In summary , the association of identified invertible sites with genes encoded in their vicinity hints at possible cis-regulation of a diverse set of bacterial functions .
While the use of next generation sequencing for detecting genomic structural variations has revealed genomic rearrangements such as deletions , insertions , inversions , duplications and translocations [44 , 57] , most of available tools have been designed for analyses of eukaryotic genomes . The drawback is that these tools often implement computationally demanding algorithms and do not always perform optimally on prokaryotic genomes . Recently , two attempts have been made to detect structural variation in prokaryotes . One method did not explicitly support inversion detection [58] and the other was applied only on a few selected E . coli species where fim switch and prophage shuffling was detected [59] . We reasoned that small inversions could be easily identified in bacterial genomes simply by clustering unusual paired reads that have the same relative orientation or 5-prime clipping ( Fig 1 ) . Using in silico simulations , we show that our approach is fairly flexible in terms of sequencing parameters allowing for previously generated datasets to be analyzed a posteriori . Furthermore , as reads smaller then 150 bp continue to be preferred in novel implementations of short-read sequencers ( e . g . Illumina’s HiSeq X , HiSeq 3000 , HiSeq 6000 , NovaSeq600 and NextSeq ) , our method of genome analysis should stay relevant in the near term . In theory , our method allows for global detection of genomic inversions regardless of the inversion size . However , large genomic inversions usually arise following homologous recombination in between substantial stretches of sequence homology scattered within the genome such as rRNA operons and transposable elements [60–62] . Because our method discards any reads that can equally map at multiple locations ( which reduces false-positive calls ) , these large inversions are not detected . This can be overcome by using mate-pair libraries that allow for distant genomic regions to be joined and sequenced on short fragments producing insert sizes of several kilo base pairs . One potential drawback of our approach is the need for deep sequencing coverage to successfully detect rare inversion events . On the other hand , the method is simple to implement , does not require powerful computing capacity and uses only free and widely available tools for mapping and analysis . Previous work had identified four small genomic segments that undergo inversion in C . difficile . The putative inversion sites , termed Cdi1 , Cdi2 and Cdi3 , were identified in a global comparative genomics survey of three complete C . difficile genomes [50] . Cdi1 undergoes inversion and regulates the expression of the downstream cwpV gene in a phase-variable manner [22] . The remaining two inversion sites , Cdi2 and Cdi3 , were never experimentally confirmed . An additional inversion site ( Cdi4 ) was recently identified and shown to control the expression of flagella and toxins in phase-variable manner [51] . Using our paired-end analysis approach , we detected all four known invertible sites and identified three novel sites . The invertible sites detected are of similar size ranging from 154 bp to 230 bp; all sites occur within intergenic regions with the exception of Cdi7 , which contains an open reading frame of 75 amino acids . This is consistent with previously characterized invertible segments . For example , E . coli ( fim switch , 314 bp; fot switch , 312 bp ) , Proteus mirabilis ( mrp switch , 251 bp ) , P . luminescens ( mad switch , 257 bp ) and Klebsiella pneumoniae ( Kpc fimbriae switch , 302 bp ) have small intergenic invertible segments with the exception of Salmonella whose flagellar switch is somewhat larger ( 966 bp ) [15–18 , 20] . While we experimentally confirmed that these putative sites undergo inversion ( Fig 4B ) , we observed that the proportion for each state , i . e . inverted versus published orientation , was variable . This variability might reflect the complex nature of regulation in terms of required recombinases or selective fitness in our growth conditions . Regardless , switching frequency was independent of bacterial growth phase ( Fig 4C ) . This is in sharp contrast to the fim switch regulation in both E . coli and K . pneumoniae . For example , transcription of fimA , the first gene downstream of the fim switch in E . coli , was found to be repressed as cells enter stationary phase in a manner dependent on the stationary phase-specific sigma factor , RpoS [63] . In K . pneumoniae , the fim switch is in the off-configuration during exponential growth in broth but undergoes inversion in the late stationary phase [21] . In contrast , the ratio of phase 1 versus phase 2 flagellar types in various Salmonella strains is mostly independent of growth phase [64] , similar to C . difficile strain R20291 flagellar on and off isolates were found to remain stable in either exponential or stationary growth phases [51] . Interestingly , flgB , cwpV , both c-di-GMP regulators and the two-component system are part of the agr quorum-sensing regulatory network in C . difficile [65] . Thus , it is possible that the control of phase-variable genes is under the influence of cell density . Alternatively , other factors independent of growth phase might impact inversion proportions in C . difficile as it was shown for E . coli [7] . Small DNA inversions in bacterial genomes are commonly associated with phase-variable expression of neighboring genes . Two previously characterized switches in C . difficile , Cdi1 and Cdi4 , also control the expression of their respective downstream genes in a phase-variable manner . The additional invertible sites identified in our study , namely Cdi2-3 and Cdi5-7 , may similarly regulate the expression of their adjacent genes . Indeed , we determined that the first gene from the two-component system found downstream of the Cdi6 is likely expressed in a phase-variable manner ( Fig 5 ) at levels similar to those detected in the qPCR orientation assay . However , assessing the direct impact of switch orientation on gene expression requires locking of the switch and measuring gene expression accordingly . Alternatively , restriction analysis of fluorescently labeled PCR products ( GeneScan analysis ) could be used [28] . Subsequent analyses are also needed to determine how switching alters gene expression , for example whether it modulates promoter orientation or affects transcriptional elongation . The detection of invertible DNA sequences raises questions regarding the enzymes responsible for these inversions . Two evolutionarily and mechanistically distinct families of enzymes , namely serine and tyrosine recombinases [5] , typically catalyze site-specific DNA inversions . In the majority of characterized systems , recombinases are located in the immediate vicinity of the switch and occasionally within the invertible segment ( e . g . Hin recombinase in S . Typhimurium ) [66] . One notable exception is Bacteroides fragilis where a single master recombinase of serine-type termed Mpi is responsible for inversion of at least thirteen regions scattered throughout the genome including seven distinct polysaccharide loci [55 , 56 , 67] . In C . difficile , the tyrosine-type recombinase RecV is responsible for inversion of cwpV ( Cdi1 ) and flagellar ( Cdi4 ) switches [22 , 51] . Our results indicate that RecV plays a role in the inversion of four out of five remaining invertible sites . The partial locking of these loci that results upon loss of the RecV recombinase suggests that other recombinases may partner with RecV to mediate inversions of Cdi2 , Cdi3 and Cdi5 invertible sites . This is reminiscent of hin / fin system where two DNA invertases contribute to flagellar phase variation in S . Typhimurium [68] . The sequence differences in the inverted repeats further suggest that other recombinases are required . One exception is Cdi2 and Cdi5 which share the same inverted repeats and thus might be inverted by one or more recombinases . Another exception was Cdi7 whose inversion was unaffected by either recV inactivation or overexpression ( Fig 6 ) . Cdi7 is the only invertible site in C . difficile strain R20291 genome that features a recombinase in its vicinity . It is therefore possible that inversion of Cdi7 is catalyzed by CDR20291_3416 , which is located next to the inversion site . Additional cellular factors or cis-acting elements might also participate in the DNA inversion process as was recently demonstrated for the fim switch in uropathogenic E . coli [69] . The method we have developed revealed that DNA inversions are frequently observed in a subset of bacterial species . Out of 44 samples carrying signs of inversions ( 35 unique species ) , the majority could be classified as Bacteroidetes , Firmicutes or Proteobacteria phyla . While this distribution probably reflects the uneven composition of our dataset with respect to other phyla rather than biological significance , some interesting patterns nevertheless emerged when positive samples were further reclassified . For example , the vast majority of inversion-positive samples from Firmicutes were members of Clostridia and could be further classified in eight distinct families . On the other hand , only one inversion signature was identified in the Bacilli class despite having substantial number of samples ( n = 22 , 18 unique species ) . This result suggests that small genomic inversions were positively selected in the Clostridia versus Bacilli early in the separation of these two lineages . Increasing the sample size and experimental validation of inversion events is necessary to support this hypothesis . Additionally , we cannot exclude that sequencing samples from Bacilli were suboptimal for detection of inversions ( inappropriate sequencing library construction , read length , sequencing depth etc . ) compared to samples belonging to Clostridia . Similar results were observed in the Proteobacteria phylum where inversion-positives samples were skewed toward the Gammaproteobacteria class . Since sampling size differences were even more pronounced for the Proteobacteria , additional testing in less represented classes such as Alpha- , Beta- , Delta- and Epsilonproteobacteria is needed to fully assess any differences in this lineage . Consistent with reported high prevalence of inversion events in Bacteroides species , several members of Bacteroidetes scored positive for inversion signatures in our analysis . Numerous inversion sites were detected in individual genomes of Bacteroides caccae , Odoribacter splanchnicus and Parabacteroides distasonis confirming previous reports in related species [55 , 56] . It is believed that Bacteroides use genomic inversions to generate subpopulations selectively expressing a wide range of cell surface structures which in turn provides selective advantage for microbes to establish dominance in the ever-challenging colonic environment [56] . Our results suggest that this phenomenon might be applicable to a wider range of species from the Bacteroidetes phylum . Known examples of genes whose expression is regulated by DNA inversion often revolve around surface components such as flagella , fimbriae , pili , capsule and related surface structures [15–20 , 51 , 55 , 56 , 70 , 71] . Our analysis suggests that bacteria might use this mechanism to regulate the expression of genes encoding a much larger set of functions than previously observed . For example , genes encoding signaling proteins , which were frequently found in the vicinity of invertible sites in Clostridia species , including the enteric pathogen C . difficile , solvent-producing C . butyricum and C . thermocellum , and environmental isolates H . halobius , Desulfosporosinus youngiae and Desulfotomaculum gibsoniae . In conclusion , our study shows that small genomic inversions , often associated with regulation of expression of neighboring genes , are prevalent in the bacterial world . Some species , including the human opportunistic pathogen C . difficile seems to have adopted this mode of regulation for a wide variety of functions including cell surface modification , intracellular signaling and environment sensing . As new bacterial strains are sequenced , our method will enable detection of novel inversions potentially providing valuable insights about bacterial evolution and lifestyle .
C . difficile R20291 , a ribotype-027 epidemic outbreak strain obtained from Trevor Lawley , was routinely propagated in Brain Hearth Infusion ( BHIS ) broth supplemented with 0 . 1% cysteine and 0 . 5% yeast extract [72] . Cultures were incubated at 37°C in an anaerobic chamber ( Coy Laboratories ) under anaerobic atmosphere composed of 85% nitrogen , 10% hydrogen and 5% carbon dioxide . E . coli DH5α and HB101/pK424 were routinely grown in LB broth or agar . Growth media was supplemented with antibiotics when required at following concentrations: ampicillin ( 100 μg/ml ) , chloramphenicol ( 25 μg/ml ) , thiamphenicol ( 100 μg/ml ) and cycloserine ( 50 μg/ml ) . For each invertible genomic segment , a set of three primers was designed to amplify published or inverted orientations ( see Fig 3A ) . All primers were designed based on the C . difficile R20291 published sequence ( NCBI Accession No . FN545816 . 1 ) and are listed in S1 Table . PCR was carried out on genomic DNA extracted from liquid cultures of three biological replicates grown in BHIS media to a mid-exponential phase ( OD600nm ~ 0 . 4 ) . Similarly , quantitative PCR ( qPCR ) was used to evaluate the proportion of the bacterial population that was in either published or inverted orientation at mid-exponential growth phase ( OD600nm ~ 0 . 4 ) and also early stationary phase ( ~ 2h after entering in stationary phase of growth ) . Amplifications were carried out in a Mx3005P qPCR system ( Stratagene ) in a total volume of 20 μl with the following components: 1X PCR buffer ( 12 mM Tris-HCl , pH 8 . 3 , 50 mM KCl , 8 mM MgCl2 , 150mM trehalose , 0 . 2% Tween 20 , 0 . 2 mg/ml bovine serum albumin , 0 . 2X SYBR green I ( Invitrogen ) ) , 0 . 5 units of Taq DNA polymerase ( New England BioLabs ) , 200 ng of genomic DNA and one of the primer sets specific for either the published or inverted orientation for Cdi1-6 . For the Cdi7 inversion site , iTaq Universal SYBR Green Supermix ( BioRad ) was used following the manufacturer’s recommendations . The following cycling conditions were used: 95°C for 2 min , followed by 40 cycles of 95°C for 15 s and 60°C for 1 min . Detailed primer concentrations , amplification efficiencies and amplicons lengths are summarized in S3 Table . The ΔΔCT method was used to calculate the ratio of published versus inverted configurations with rpoA as internal reference control as described in S2 Methods . Previously described codA-based allelic exchange method [73] was used to replace CDR20291_3128 coding sequence ( GenBank accession: CBE06969 . 1 ) with the C . difficile codon-optimized SNAP-tag coding sequence . Briefly , approximately 1300 bp genomic fragments were amplified upstream ( primers OS158 and OS159 ) and downstream ( primers OS162 and OS163 ) of the start and stop codons of CDR20291_3128 . A C . difficile codon-optimized SNAP-tag coding sequence was amplified from pFT46 vector using primers OS160 and OS161 [74] . Complementary overlapping sequences were added to the 5-prime end of primers to allow for accurate fusion of all PCR products into PmeI-linearized pMTL-SC7315 vector using Gibson Assembly Master Mix ( New England BioLabs ) . The resulting plasmid was then conjugated into C . difficile R20291 strain using the heat-stimulated conjugation method described elsewhere [75] . Mutants were selected as previously described [73] and screened by colony-PCR for the presence of the right SNAP-chromosomal junction and the absence of CDR20291_3128 coding sequence . All PCR products were sequenced to confirm the genetic construct and the absence of any secondary mutations . Additionally , Illumina sequencing of whole-genome DNA revealed no off-target mutations , and the genetic background was otherwise identical to the parental R20291 aside from the anticipated SNAP-tag allelic replacement . One representative clone was selected for fluorescent labeling . Fluorescent labeling of C . difficile cells was done as previously described with modifications [76] . Briefly , 5 ml of exponentially growing cultures ( OD600nm ~ 0 . 4 ) were washed once in PBS and resuspended in 0 . 1 ml PBS containing 250 nM SNAP-Cell TMR-Star ( New England BioLabs ) for 30 min at 37°C . The excess of fluorescent substrate was removed by washing the cells 5 times with PBS prior to mounting on glass slides with freshly prepared 1% agarose pads . Imaging was done on Eclipse 80i fluorescence microscope ( Nikon ) at 60X magnification using Photometrics CoolSNAP HQ camera ( Roper Scientific ) operated by NIS-Elements software ( Nikon ) . Acquired images were further minimally processed and pseudocolored in Photoshop CC 2018 ( Adobe Systems ) . Cells showing uniform fluorescence in the red channel were counted and compared to the total number of cells observed in the bright field . Counts were done on at least 5 images from different fields on two biological replicates . recV ( CDR20291_1004 ) was cloned in pRPF185 vector using SacI and BamHI restriction sites as previously described [51] . A control plasmid ( empty vector ) of the ATc-inducible expression vector was generated by removing the gusA gene from pRPF185 by digestion with SacI and BamHI and religating the vector backbone following treatment with Klenow . C . difficile strain R20291 containing pRPF185 empty vector and pRPF185:recV were grown overnight in Tryptone-Yeast Extract ( TY ) broth supplemented with thiamphenicol . The following day , cultures were back-diluted 1:50 into TY + thiamphenicol and grown to OD600nm = 0 . 3 . Once the cultures reached the right optical density , anhydrotetracycline ( 20 ng/ml ) was added and cultures were further incubated until early stationary phase was ( OD600nm ~ 1 . 5 ) at which point cells were pelleted and genomic DNA extracted by phenol-chloroform as previously described . Quantitative PCR was performed with SensiMix SYBR ( BioLine ) with 100 ng of genomic DNA and 100 nM primers in 20 μl . Reactions were run on Lightcycler 96 system ( Roche ) with the following three-step cycling conditions: 98°C for 2 min , followed by 40 cycles of 98°C for 30 s and 60°C for 1 min and 72°C for 30 sec . Quantification was done with ΔΔCT with rpoA as a reference as previously described . Random DNA sequence was generated using Bioinformatics Toolbox from Matlab R2017b ( MathWorks ) . Paired-end Illumina high-throughput sequencing reads were simulated using ART-MountRainier-2016-06-05 [49] using Illumina HiSeq 2500 and HiSeq 2000 built-in parameters with read length of 50 , 100 or 150 bp and mean fragment size of 250 , 500 or 800 bp ± 20% standard deviation . Read alignments were done using bwa version 0 . 7 . 13-r1126 [77] . Template size was inferred from bwa mappings using a custom script . SAM file manipulation was done using SAMtools version 1 . 5 [78] . Sequencing coverage was calculated using bedtools v2 . 26 . 0 [79] and HTSeq version 0 . 9 . 1 [80] . Extraction of same-orientation reads and 5-prime soft-clipped reads from SAM files was done using custom scripts as explained in S1 Methods . All scripts are available from https://github . com/camillilab/analyze_clusters . Some analyses were conducted in R version 3 . 4 . 1 [81] . Protein domain analysis was carried out using InterPro database ( https://www . ebi . ac . uk/interpro/ ) [82] . Terminal inverted repeats were identified by pairwise sequence alignment of invertible site boundaries using EMBOSS Water hosted on The European Bioinformatics Institute’s ( EMBL ) website ( https://www . ebi . ac . uk/Tools/psa/emboss_water/nucleotide . html ) . | Bacteria in many ecological niches experience a common challenge in the form of unpredictable environmental fluctuations . Rapid adaptation to challenging conditions is important for bacterial survival and successful proliferation . Altering gene expression through DNA inversion is a common mechanism adopted by many bacterial species that allows quick generation of distinct subpopulations with altered fitness . The characterization of these systems beyond a few classical cases is lagging due to the difficulties to accurately detect such inversion on a population level . In this study , we implement an easy-to-use method for detecting small genomic inversions in bacterial genomes . We successfully applied our approach to detect known and novel inversion sites in C . difficile . We further show that all detected sites undergo inversion and exist at different frequencies in vitro . The inversion of several sites seems dependent on the master recombinase RecV . We expand our analysis to a large collection of bacterial and archaeal strains and show that our method can be globally applied for detection of small genomic inversions . Taken together , this study advances the ability to characterize this important phenomenon . | [
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"geneti... | 2018 | Genome-wide detection of conservative site-specific recombination in bacteria |
Spermatogenesis is a dynamic process that is regulated by adhesive interactions between germ and Sertoli cells . Germ cells express the Junctional Adhesion Molecule-C ( JAM-C , encoded by Jam3 ) , which localizes to germ/Sertoli cell contacts . JAM-C is involved in germ cell polarity and acrosome formation . Using a proteomic approach , we demonstrated that JAM-C interacted with the Golgi reassembly stacking protein of 55 kDa ( GRASP55 , encoded by Gorasp2 ) in developing germ cells . Generation and study of Gorasp2-/- mice revealed that knock-out mice suffered from spermatogenesis defects . Acrosome formation and polarized localization of JAM-C in spermatids were altered in Gorasp2-/- mice . In addition , Golgi morphology of spermatocytes was disturbed in Gorasp2-/- mice . Crystal structures of GRASP55 in complex with JAM-C or JAM-B revealed that GRASP55 interacted via PDZ-mediated interactions with JAMs and induced a conformational change in GRASP55 with respect of its free conformation . An in silico pharmacophore approach identified a chemical compound called Graspin that inhibited PDZ-mediated interactions of GRASP55 with JAMs . Treatment of mice with Graspin hampered the polarized localization of JAM-C in spermatids , induced the premature release of spermatids and affected the Golgi morphology of meiotic spermatocytes .
Members of the Junctional Adhesion Molecular family exhibit a similar structure with two extracellular immunoglobulin domains , a single transmembrane region and a C-terminal PSD-95/Discs Large/ZO-1 ( PDZ ) -binding motif . Three of these proteins are highly similar: JAM-A , JAM-B and JAM-C [1] . The latter interacts with JAM-B and the leukocyte integrins αMβ2 and αXβ2 [2 , 3] . Since JAM-B and JAM-C are both expressed by endothelial cells , it has been proposed that their primary function consists in the regulation of inter-endothelial junctional tightness and leukocyte trans-endothelial migration [4] . However , studies of constitutive and conditional knock-out mice for Jam3 ( the gene encoding JAM-C ) revealed an essential function for JAM-C in spermatogenesis [5 , 6] . Spermatogenesis occurs in a stepwise manner , beginning with diploid spermatogonia at the basal surface of seminiferous tubules and ending with mature elongated spermatozoa in tubule lumens which are released at spermiation . Spermatogenesis involves adhesive interactions between developing germ and Sertoli cells [7] and is a continuous process that requires 34 . 5 days in mice . During that time , mitosis , meiosis and maturation occur in spermatogonia , spermatocytes and spermatids , respectively [8 , 9] . Spermatogenesis is a developmental system in which the Golgi apparatus undergoes dramatic rearrangements during the meiotic and post-meiotic phases [10] . Germ cells express JAM-C which participates to spermatogenesis via interaction with JAM-B during post-meiotic maturation of spermatids [6 , 11] . The strong decrease in sperm cells number in Jam3-deficient mice was attributed to the lack of JAM-C recruitment to the junctional plaques at germ/Sertoli cell contacts [6] . Junctional plaques are specialized adhesion structures that anchor germ cells to Sertoli cells and provide spermatids with polarization cues , including JAM-C-mediated polarity signals . The progressive confinement of JAM-C to junctional plaques begins in round spermatids and it is completed in heads of elongated spermatids that remain attached to Sertoli cells via an adhesive structure called apical ectoplasmic specialization [12] . However , little is known about the molecular mechanisms involved in JAM-C polarized localization to spermatids/Sertoli cell contacts . The present study used a combination of proteomic and genetic techniques with structural biochemistry and structure-based drug design approaches to investigate these mechanisms . We demonstrated that GRASP55 interacted with the PDZ-binding motif of JAM-C in testis . GRASP55 is a medial/trans Golgi molecule that is involved in Golgi stacking , Golgi fragmentation during mitosis and the unconventional protein transport triggered by cellular stress [13–18] . The cargo receptor function of GRASP55 was attributed to the interaction of GRASP55 PDZ domains with motifs in the C-terminal part of cargos such as CD8 , TGF-α , or CD83 [19–21] . We solved the 3D structure of GRASP55 in the ligand-free form and in complex with two cargos: JAM-C and JAM-B . The structure revealed a large conformational change between the “open/ligand-free” and “closed/cargo-bound” forms . We used a virtual screening strategy that combined high-throughput docking and pharmacophore filtering to identify protein-protein inhibitors of the GRASP55/JAM interaction [22 , 23] . The best inhibitor , referred to as Graspin for “GRASP55 INhibitor” , exhibited reasonable affinity and selectivity for inhibition of GRASP55/JAMs interaction . The biological relevance of GRASP55/JAM-C interaction in spermatogenesis was validated using genetic ablation of Gorasp2 ( encoding GRASP55 ) and chemical inhibition of GRASP55 PDZ-mediated interactions .
We used a proteomic approach to identify molecular mechanisms that regulate the PDZ-dependent functions of JAMs during spermatogenesis . Testes lysates and peptides corresponding to the terminal 19 amino acids ( aa ) of JAMs or mutant sequences that lacked the last three C-terminal aa were used in pulldown assays ( Fig 1A ) . Known PDZ-containing binders of JAMs , such as ZO-1 and ZO-2 and , several new binding partners were identified using mass spectrometry ( MS ) , including the Golgi Reassembly Stacking Protein of 55 kDa ( GRASP55 ) ( Table in S1 Table ) . The MS results indicated that the interaction of GRASP55 with JAMs was likely PDZ-dependent because GRASP55 was not pulled-down with the JAM peptides that lacked PDZ-binding motifs . Yeast two-hybrid interaction assays confirmed that the first PDZ domain of GRASP55 was necessary for interaction with JAM proteins ( Fig 1B ) . Conversely , the PDZ-binding motifs of the JAM sequences were required , as demonstrated in the yeast two-hybrid or peptide pull-down assays that were performed with mutant JAM sequences lacking the three C-terminal aa ( Fig 1B and 1C ) . Measurement of the relative binding of GRASP55 to JAM family members using homogenous time-resolved fluorescence ( HTRF ) or isothermal titration calorimetry ( ITC ) revealed five- to seven-fold higher affinity interactions of GRASP55 with JAM-B and JAM-C ( 4 . 9 μM and 3 . 7 μM , respectively ) as compared to JAM-A ( 27 μM ) ( Fig 1D and 1E; Table in S2 Table ) . Comparable affinities were measured using the full-length GRASP55 protein or isolated tandem PDZ domains ( PDZ12 ) ( Table in S2 Table ) , which supports that the critical residues that contribute to the affinity of GRASP55/JAMs interaction are present within the PDZ tandem domain of GRASP55 . We disrupted the gene encoding GRASP55 , Gorasp2 using homologous recombination to examine the function of GRASP55 in vivo , ( Fig A-C in S1 Fig ) . Gorasp2-deficient mice exhibited growth retardation , similarly to Jam3-deficient mice [24] ( Fig D in S1 Fig ) . Male Gorasp2-/- mice bred normally ( mating behaviors , plug production ) , but these mice were infertile . Therefore , we measured number and size of the litters . We never obtained offspring from Gorasp2-/- males , but Gorasp2-/- females were fertile ( Table 1 ) . Analysis of male reproductive organs isolated from Gorasp2-deficient males revealed no significant differences in the testis/body weight ratio or epididymis and seminal vesicles weights ( Fig E-G in S1 Fig ) . However , we observed a trend toward reduced sperm counts isolated from the epididymis ( Fig H in S1 Fig ) . Several defects such as bent midpiece and abnormal head or reduced motility were also found ( Fig I-K in S1 Fig ) . Microscopic examination confirmed that the epididymis of Gorasp2-/- mice contained rare abnormal cells with large nuclei ( Fig 2A ) , which indicates that spermiogenesis was affected . Spermatid maturation occurs in post-meiotic cells , and it is accompanied by the formation of an acrosome , which is stained with periodic acid-Schiff ( PAS ) reagent . Light microscopic examination of adult testes from Gorasp2-/- mice revealed that PAS staining was affected at all tubule stage differentiation , which suggests abnormal acrosome formation ( S2 Fig ) . This result was confirmed using an antibody against a component of the acrosomal matrix , SP56 , which becomes detectable at the beginning of acrosome assembly [25] . A complete loss of anti-SP56 staining was observed on testes sections from Gorasp2-deficient mice ( Fig 2B ) , and a disorganized and weak residual staining was observed using peanut agglutinin ( Fig 2C ) . These data demonstrated that Gorasp2 deficiency resulted in acrosomal defects that resembled the spermiogenesis defects previously described in Jam3-/- mice [6] . Therefore , we examined the relative localization of GRASP55 and JAM-C by immunofluorescence in tissue sections using Tyramide Signal Amplification ( TSA ) which allows combination of antibodies generated in the same species ( i . e . JAM-C and GRASP55 generated in rabbit ) . This technology is useful , but the enzymatic amplification step hampers comparison of signal intensities between different samples . JAM-C was widely distributed and heavily expressed in spermatogonia and primary spermatocytes . JAM-C expression was reduced in meiotic spermatocytes , with a complete loss in secondary meiotic cells and step 1 spermatids , and weak re-accumulation expression in step 2 spermatids ( Fig A , in S3 Fig and Fig 3A ) . Combination of GRASP55 and PNA staining revealed a co-polarized localization of JAM-C and GRASP55 in step 2 and step 3 round spermatids ( Fig 3A , arrowheads ) . This co-clustering of GRASP55 and JAM-C in the acrosomal region was maintained until stage VIII of seminiferous tubule differentiation , and it was lost in stage X tubules [26] . Co-immunoprecipitation experiments were performed to examine whether a transient interaction between GRASP55 and JAM-C was responsible for the co-polarized localization of these two proteins . Fig 3B shows that the two proteins co-immunoprecipitate . Testes lysates from Gorasp2-deficient mice were used as control . We thus questioned if Gorasp2-deficiency would affect JAM-C localization to acrosomal region of developing spermatids . Staining revealed that JAM-C expression was strongly reduced in round spermatids at all stages of seminiferous tubule differentiation ( Fig 3C ) , but JAM-C remained expressed in spermatogonia and spermatocytes of Gorasp2-/- mice . JAM-B interacts with JAM-C [2] and GRASP55 ( Fig 1D and 1E ) . Therefore , we examined whether JAM-B localization was affected in Gorasp2-deficient mice . We found a partial co-localization of JAM-B and JAM-C in spermatocytes and round spermatids in wild-type mice , and this co-localization was lost in Gorasp2-/- mice ( Fig B in S3 Fig ) . This result suggests that GRASP55 plays a role in the polarized re-localization of JAM-C with JAM-B at germ/Sertoli cell contacts during spermatid maturation . Spermatid maturation is associated to acrosome formation and apical ectoplasmic specialization assembly . Therefore , testes sections were stained with a well-known marker of apical ectoplasmic specializations , Nectin3 [27] . We observed a complete loss of Nectin3 staining which is consistent with defects in acrosome formation ( Fig A in S4 Fig ) . Other features of seminiferous tubule organization such as JAM-A/ZO-1 localization to basal ectoplasmic specialization or the number of Sertoli cells by seminiferous tubules were not affected in Gorasp2-/- mice ( Fig B-D in S4 Fig ) , which suggests that the spermatogenic defects in Gorasp2-/- mice were due to acrosome defects and reduced JAM-C expression in spermatids . “Golgi phase” initiates acrosome formation in step 1 round spermatids and GRASP55 is involved in Golgi apparatus assembly/disassembly [28 , 29] . Therefore , we investigated whether Gorasp2 deficiency also affected the Golgi remodeling that occurs during spermatogenesis . We used antibodies directed against the Golgi Matrix protein of 130kD ( GM130 ) to stain testes sections [30] . The results revealed that GM130 staining surrounded GRASP55 signals in spermatocytes of control mice . GM130 staining was more diffuse in spermatocytes from 35-days old Gorasp2-/- mice compared to littermate controls ( Fig 4A , arrowheads ) . We analyzed Golgi area using GM130 staining in seminiferous tubules at different differentiation stages . We found that few germ cells harbored a Golgi area greater than 5μm2 at early stages of seminiferous tubule differentiation ( II-III ) , but cells with an enlarged Golgi area were easily detected at later differentiation stages ( VIII ) in littermate control mice ( Fig 4B ) . In contrast , we found numerous enlarged Golgi in cells of the early stage tubules of Gorasp2-/- mice . Quantification indicated a specific increase in Golgi apparatus with areas greater than 5μm2 in stage II-IV seminiferous tubules of Gorasp2-/- mice compared to control animals ( Fig 4C ) . Golgi size increases during pachytene spermatocytes maturation prior to separation in four spermatid daughter cells [31] . Therefore , we investigated whether cells with enlarged Golgi corresponded to early spermatocytes using an antibody directed against SYCP3 [32] . Enlarged Golgi in Gorasp2-/- mice were present in pachytene spermatocytes of stage II-III seminiferous tubules ( Fig 4D ) . This result indicates that GRASP55 plays a role at an early stage of spermatogenic cell differentiation via regulation of Golgi reassembly at an early stage of meiotic pachytene spermatocyte maturation . We thus tested whether Golgi morphology of somatic cells was also affected by the loss of GRASP55 expression . Primary mouse embryonic fibroblasts ( MEFs ) isolated from Gorasp2-deficient embryos exhibited enlarged Golgi ribbons , which recovered a more compact appearance after GRASP55 re-expression ( Fig A in S5 Fig ) . We developed a dedicated image analysis protocol ( Fig B in S5 Fig and Supporting Information ) and quantified a two-fold reduction in Golgi density in cells lacking GRASP55 expression . Re-expression of the C-terminal mCherry-tagged form of GRASP55 rescued the Golgi density to the level of wild-type cells ( Fig C-D in S5 Fig ) . The mode of interaction of GRASP55 with JAMs may aid our understanding of the dual function of GRASP55 in Golgi stacking and JAM-B/JAM-C clustering . Therefore , we co-crystallized GRASP55 PDZ domains with peptides corresponding to the C-terminal 19-mer of mouse JAM-B ( JAM-B_P19 ) and JAM-C ( JAM-C_P19 ) . Following the nomenclature for residues binding to PDZ motifs [33] , the JAMB_P19 peptide C-terminal Isoleucine residue was designated Ile0 and subsequent residues toward the N-terminus were negatively decreased Ile-1 , Phe-2 , Ser-3 , Lys-4 , Thr-5 , His-6 , Lys-7 and Phe-8 . The bound structures of GRASP55 with an uncleaved 6xHis-Tag crystallized in the I4122 space group and contained 2 molecules in the asymmetric unit . The two structures of the complex with JAM-B ( PDB ID 5GMJ ) or JAM-C ( PDB ID 5GMI ) were solved at a resolution of 2 . 99 and 2 . 71 Å , respectively , using molecular replacement and refined to Rfree values of 27 . 4% and 29 . 1% , respectively ( S3 Table ) . Notably , GRASP55/JAM-C and GRASP55/JAM-B structures exhibited an unexpected ‘closed’ conformation that was characterized by a 33 degree rotation angle of PDZ2 towards the PDZ1 domain and a 12 . 1 Å root mean square deviation ( rmsd ) after superimposition of PDZ1 domains to the previously reported structure of the ‘ligand-free’ GRASP55 PDZ domains ( Fig 5A ) [34] . Normal mode analyses revealed that the transition between the ‘open/ligand-free’ and ‘closed/cargo bound’ conformations was confirmed using the three-lowest frequency normal modes [35 , 36] , which indicates that both conformations may exist in solution . The cargo bound conformation may be preferentially selected in the presence of C-terminal JAM peptides ( Fig A in S6 Fig ) . These structures indicate that JAM-B_P19 and JAM-C_P19 bind to a groove on the PDZ1 surface , and C-terminal residues penetrate the conventional hydrophobic cavity found in this PDZ domain ( Fig 5B; Fig B-C in S6 Fig ) . Most of the observed interactions occurred via the last four residues of JAM-B_P19 or JAM-C_P19 , where the carboxylate group of Ile0 is coordinated by a network of hydrogen bonds to the main chain amide groups in the “carboxylate binding loop” of GRASP55 PDZ1 ( Fig 5C; Fig D in S6 Fig ) . This well conserved loop generally exhibits the sequence motif: ϕ-G-ϕ ( Leu96-G97-Val98 in GRASP55 ) . Residues at positions 0 and -2 are inserted in an extended conformation and present supplementary hydrogen bonds with the 5th β-strand , which adds a 6th antiparallel β-strand to the conventional structure of the interface . Notably , one very unique feature and non-conventional interaction of GRASP55/JAM-B_P19 was the positioning of Arg101 at a close distance from the interface , which allows hydrogen-bonding interactions with PDZ2 domain amino acids ( such as Ala139 ) and Thr5 from JAM-B ( Fig 5D and 5E ) . In silico screening for inhibitors of GRASP55/JAM interaction was performed based on the allosteric structural differences between published ‘open/ligand-free’ [34] and ‘closed/cargo bound’ conformations of GRASP55 ( this study ) . The experimental approach was based on a dual strategy using molecular docking and pharmacophore filtering ( described in S1 Information ) . The first step consisted in high-throughput docking of a >200K compounds chemical library dedicated to protein-protein interactions into the binding site of the ‘closed/cargo-bound’ GRASP55 crystal structure ( PDB ID 5GMJ ) . This step was used to generate several conformations that would fit each compound of the chemical library into the binding pocket . The second step filtered million poses using a pharmacophore model . This model was based on the conventional binding interactions observed in the 3D structures of the GRASP55/JAM complex and consisted in 4 hydrogen bond donor/acceptor features and 2 hydrophobic constraints . Several compounds were selected as hits , which were confirmed using orthogonal screening assays . Compound PubChem CID #3113208 , referred to as Graspin for “GRASP55 INhibitor” hereafter , exhibited an IC50 of 8 . 4 μM towards GRASP55/JAM-B and 12 μM towards GRASP55/JAM-C as measured by HTRF ( Fig 6A and 6B ) . Graspin did not affect the irrelevant Erbin/P0071 PDZ-mediated interaction . Orthosteric validation using differential scanning fluorimetry ( DSF ) revealed that , Graspin , but not the JAM-C peptide , decreased the GRASP55 melting temperature ( Fig 6C ) , which suggests that Graspin affected GRASP55 protein stability and should mimic the loss of GRASP55 expression in a biological context . Notably , a reduction in Golgi density in wild-type MEFs was observed after 48 hours of Graspin treatment , but the Golgi density of Gorasp2-deficient MEFs was not changed ( Fig 6D ) . We next tested if GRASP55 expression or Graspin treatment affected JAM-C expression or localization in MEFs . No differences in JAM-C expression levels were observed between wild-type and Gorasp2-deficient cells in control conditions , but Graspin treatment induced a dose-dependent and specific decrease in GRASP55 and JAM-C expression in wild-type MEFs ( Fig 6E ) . This result indicated that Graspin treatment affected JAM-C expression in a GRASP55 dependent manner , likely due to decreased GRASP55 stability as suggested by the DSF results . In contrast , alternative pathways likely compensate for the constitutive loss of GRASP55 expression in somatic cells to maintain JAM-C expression . Gorasp2 deficiency results in spermatogenesis defects and loss of JAM-C localization in the acrosomal region . Therefore , we examined whether Graspin treatment affected spermatogenesis in vivo . Treatment was initiated in 27-days old mice to begin experiments in animals that did not experience a single wave of germ cell development , which ends on day 35 ( Fig A in S7 Fig ) . No obvious toxicity or changes in seminiferous tubule composition were observed under these conditions ( Fig B-C in S7 Fig ) . However , obvious tubule disorganization was visualized using DAPI/PNA staining of testes sections ( Fig D in S7 Fig ) , which suggests that tubule content was affected . This result was confirmed using flow cytometry and DAPI staining which allow quantification and discrimination of elongated spermatids ( ES ) , round spermatids ( RS , 1C ) , spermatogonia ( 2C ) and primary spermatocytes ( 4C ) [37] . A marked reduction of all spermatogenic cells was observed in Graspin-treated and Gorasp2-deficient mice ( Fig 7A and 7B ) . Quantification of flow-cytometry experiments revealed a specific decrease in the percentage of elongated cells in testes of Graspin-treated mice ( Fig 7C ) . This result is consistent with the twofold decrease in ES content observed on histological sections ( Fig E in S7 Fig ) . The expression of flow-cytometry results as absolute numbers revealed an overall two-fold reduction in testes cellularity ( Fig F in S7 Fig ) . This result suggests that Graspin induced ES depletion and affected spermatogenesis at earlier stage of differentiation , which decreased cellularity . Analysis of testes sections isolated from treated mice and stained for JAM-C and GRASP55 revealed that the down-regulation of JAM-C at the transition between spermatocyte and spermatids and the re-localization of JAM-C in the acrosomal region of RS were severely affected ( Fig 7D ) . Quantification of the frequency of co-polarized GRASP55/JAM-C staining in RS at stage V-VI and stage VIII revealed that the co-clustering of JAM-C staining with GRASP55 was severely decreased with Graspin treatment ( Fig 7E ) . This result prompted us to investigate whether Graspin treatment affected acrosomes . A strong decrease in SP56 staining and obvious reduction in ES content of some tubules was found after Graspin treatment ( Fig 7F ) . These effects were not due to increased apoptosis as revealed by TUNEL staining ( S8 Fig ) , which suggests that it may be due to disruption of apical ectoplasmic specialization and “premature spermiation” , as previously reported for other compounds that affect spermatogenesis [38] . Flow-cytometry comparison of epididymis content of Graspin- and vehicle- treated mice revealed a threefold increase in spermatozoa and cell debris in epididymis of Graspin treated mice ( Fig 8A and 8B ) . This increase was accompanied by a mislocalization of residual JAM-C staining to the acrosome of mature spermatozoa ( Fig 8C ) , which suggests that Graspin impaired the coordinated regulation of apical ectoplasmic specialization via inhibition of GRASP55 PDZ-mediated interactions . Graspin treatment also affected the Golgi density of pachytene spermatocytes which exhibited a significant increase in the frequencies of Golgi with areas greater than 5 μm2 in stage II-III tubules ( Fig 9 ) . Altogether , our data demonstrate that Graspin treatment mimics Gorasp2 deficiency and affects spermatogenesis via targeting Golgi reassembly in spermatocytes and inhibition of acrosomal related functions in spermatids .
JAM-C interacts with PAR3 via its PDZ-binding motif and it associates with CRUMBS ( CRUMBS3/PALS1/PATJ ) and PAR ( PAR3/PAR6/aPKC ) polarity complexes in spermatids [6 , 39] . In addition , JAM-C localizes to the acrosome of spermatozoa isolated from epididymis [40] . The constitutive or conditional deletion of Jam3 in germ cells results in a loss of cytoskeletal protein polarization with an arrest of differentiation at the stage of round spermatid [6] . The role of JAM-C in germ cell polarity and adhesion to Sertoli cell was further confirmed using a small compound that destabilizes apical ectoplasmic specializations , adjudin [41] . In this study , the authors reported that adjudin-induced germ cell loss was accompanied by a decrease in JAM-C association with PALS1/PAR6 , which may contribute to sperm cell release . However , the dynamic localization and trafficking of JAM-C to apical ectoplasmic specialization or acrosome is still poorly understood . The present study identified GRASP55 as an endogenous interacting partner of the JAM-C PDZ-binding motif in developing germ cells . Gorasp2-/- mice display male infertility but do not present other gross morphological defects , similarly to Jam3-deficient mice . The major defects of Gorasp2-/- developing germ cells were defects in acrosome formation , a reduced number of elongated spermatids , a lack of polarized localization of JAM-C in round spermatids and a dramatic enlargement of Golgi apparatus in early pachytene spermatocytes . These results raise the question of how a single Golgi protein can interfere with meiosis , acrosome formation and JAM-C trafficking ? Landmark studies have documented changes in Golgi morphology during meiotic division of spermatocytes or during early spermiogenesis [42 , 43] . However , the underlying molecular mechanisms are poorly understood . The Golgi size of rat pachytene spermatocytes increases from a diameter of 0 . 5–1 μm at stages I-III to 2–3 μm at stages IV-XII of seminiferous cycle [31] . This increase is consistent with our results showing that the threshold value of 5 μm2 for Golgi area discriminates between the spermatocytes in early ( II-III ) and late stage seminiferous tubules ( VI-XII ) . One remarkable finding was that chemical or genetic inhibition of GRASP55 resulted in Golgi enlargement of early pachytene spermatocytes , which suggests a delay of Golgi reassembly in these cells . The pachytene spermatocytes represent the longest phase of prophase during the first meiotic division [9] . Therefore , defects in Golgi reassembly may delay pachytene spermatocytes maturation and decrease cellularity as a consequence of meiotic phase lengthening . These changes are consistent with the known function of GRASP55 in Golgi stacking and breakdown in mitotic somatic cells [16 , 44] . Another finding was that chemical inhibition of GRASP55 resulted in defects of acrosome formation and premature spermiation . Acrosome development occurs during early spermiogenesis and results from the assembly of pro-acrosomic vesicles . These vesicles originate from the Golgi apparatus and GRASP55 has been reported to be specifically associated to the Golgi apparatus and acrosome of step 1–7 rat spermatids , which suggests that this protein plays a specific function in acrosome development [45] . Our results confirmed this hypothesis and demonstrated that this function relies , at least partially , on the transient interaction between GRASP55 and JAM-C during early spermiogenesis in mice ( step 1–7 spermatids ) . Therefore , we propose a model in which GRASP55 is involved in the coordinated regulation of JAM-C expression and localization in spermatids that contribute to apical ectoplasmic specialization polarity complex anchoring . Indeed , Gorasp2 deficiency resulted in acrosomal defects and the subsequent lack of polarized localization of JAM-C in the acrosomal region . Graspin inhibition of GRASP55 PDZ-mediated interactions induced more subtle changes in JAM-C expression and localization and resulted in “premature spermiation” . These effects are similar to what has been described for adjudin , which is a potential male contraceptive that specifically perturbs the function of apical ectoplasmic specializations [38 , 46] . Notably , adjudin treatment affects the association of JAM-C with polarity complex proteins [41] . These JAM-C-mediated interactions are PDZ-binding-motif-dependent and should be mutually exclusive from the interaction of JAM-C with GRASP55 [39] , which suggests that the JAM-C-interacting PDZ network plays a central role during spermiogenesis . Finally , our study revisits the structural properties of GRASP55 . A previously published , 3D structure of GRASP55 ( PDZ12 ) revealed an unusual metazoan circularly permutated PDZ domain-containing protein in which one PDZ domain contains a unique internal peptide ligand for the second PDZ domain . This intermolecular interaction between GRASP55 proteins was thought to form a strong and stable complex that bridged adjacent molecules and maintained Golgi stacks [34] . GRASP55 interaction with Golgin45 may also contribute to the Golgi stacking function of GRASP55 [47] . These intermolecular interactions between GRASP55 PDZ domains may be disrupted during the post-meiotic transition between spermatocytes and spermatids , and the PDZ1 ligand-binding domain of GRASP55 may be re-affected to JAM-C receptor function . This hypothesis is consistent with a proposed model in which the allosteric regulation of GRASP via phosphorylation disrupts it self-association and leads to Golgi breakdown during mitosis [14 , 48 , 49] . Our 3D structure pinpoints that the GRASP55/JAM-C ( or JAM-B ) complex involves a 3D interaction that induces significant conformational changes between the ‘ligand-free’ ( ‘Golgi bound’ conformation as described by Truschel et al [48] ) and the ‘cargo-bound’ conformation of the protein ( this study ) . The overlay of our structures with the published ‘ligand free’ form of GRASP55 reveals that the conformational changes occur in the main chain of the second PDZ domain ( PDZ2 ) and its relative orientation to PDZ1 , which compacts the PDZ2 into a ‘closed/cargo-bound’ conformation . Most of the interactions are present around the conventional hydrophobic cavity in the PDZ1 , but our structures reveal a very unique feature outside the conventional binding mode of the PDZ domain . Several supplementary intramolecular hydrogen bonds involving the Arg101 residue from the PDZ1 and Ala139 from the PDZ2 of GRASP55 were identified and contributed to the conformational exchange between free and bound conformations . In summary , our findings report the first non-redundant function for GRASP55 in mammals and establish a link between the function of GRASP55 in germ cells and the subcellular localization of JAM-C in spermatids . We also provide evidence that the inhibition of GRASP55 PDZ-mediated interactions using a small compound affects spermatogenesis via reduction of overall cellularity and induction of “premature spermiation” . These results demonstrate that the chemical targeting of PDZ scaffolds involved in complex biological pathway may be achieved in vivo which paves the way toward therapeutic targeting of PDZ-mediated interactions .
Rabbit anti-GRASP55 ( ref . 10598-1-AP , ProteinTech ) , rabbit anti-JAM-B 829 [50 , 51] , rabbit anti-JAM-C 501 [51] , goat anti-JAM-C ( ref . AF1213 , R&D system ) , mouse anti-GM130 ( ref . 610822 , BD Biosciences ) , mouse anti-SP56 ( ref . MA1-10866 , ThermoFisher Scientific ) , rabbit anti-Nectin3 ( ref . ab63931 , Abcam ) , rabbit anti-SYCP3 ( ref . ab15093 , Abcam ) and mouse anti-actin ( ref . A3853 , Sigma ) primary antibodies and biotinylated PeaNut Agglutinin ( PNA , ref . L6135 , Sigma ) were used for immunostaining and immunoblotting . Appropriate anti-rabbit , anti-goat or anti-mouse secondary antibodies were obtained from Jackson Immuno-research Laboratories . The full-length Gorasp2 cDNA encoding the GRASP55 protein was amplified by polymerase chain reaction ( PCR ) using the oligonucleotides 5'-CTCGAGATGGGCTCCTCGCAGAGC-3' and 5'-GGATCCCCAGAAGGCTCTGAAGCATCTGC-3' , containing XhoI and BamHI sites , respectively . The amplification product was cloned in the pGEM-T Easy vector ( Promega ) . The insert was recovered by XhoI/BamHI digestion and subcloned in the pmCherry-N1 vector ( Clontech ) . To generate fusion proteins , mouse Gorasp2 cDNA cloned into pGEM-T was used as template for PCR amplification of the open reading frame ( ORF ) for mGRASP55 PDZ1 ( aa 2–107 ) , PDZ12 ( aa 2–208 ) , mGRASP55 Full-length ( FL ) ( aa 2–451 ) or GRASP55Δ ( aa 106–451 ) using forward and reverse oligonucleotides flanked by attb1 and attb2 recombination sites . The following primers pairs were used: PDZ1 For: 5'- GGGGACAAGTTTGTACAAAAAAGCAGGCTTCCTGGTTCCGCGTGGATCCGGCTCCTCGCAGAGCGTCG-3’ or 5'-GGGGACAAGTTTGTACAAAAAAGCAGGCTTCGGCTCCTCGCAGAGCGTCGAGAT-3’ ( with and without sequence coding for a thrombin cleavage site , respectively ) ; PDZ2 For: 5'-GGGGACAAGTTTGTACAAAAAAGCAGGCTTCGGGGCCAACGAAAACGTTTGGCATGTGCTG-3’ PDZ1 Rev: 5'-GGGGACCACTTTGTACAAGAAAGCTGGGTCTTACCCGTCAAAGCTGCAGAAACGAATGCT-3' , PDZ2 Rev: 5'-GGGGACCACTTTGTACAAGAAAGCTGGGTCTTATTCAAAGGGGCGTGTAGGTATTCGGTGCA-3' and GRASP55 FL Rev: 5'-GGGGACCACTTTGTACAAGAAAGCTGGGTCTTAAGAAGGCTCTGAAGCATCTGCATCAGAC-3' . The amplicons were cloned by the BP reaction into pDONRZeo ( Gateway® Technology ) to produce the corresponding entry vectors . The coding sequences were transferred by LR cloning in pDESTTM15 and pDESTTM17 prokaryotic expression vectors intended to produce the corresponding N-terminal GST- or 6His-tagged fusion protein , respectively . This was accomplished by induction for 3 h at 37°C or 18 h at 25°C with 0 . 2 mM isopropyl-β-D-thiogalactopyranoside in E . coli BL21 ( DE3 ) bacteria cells transformed with the purified plasmids . Fusion proteins were recovered from the cell lysates by conventional affinity chromatography on Glutathione sepharose 4B ( GE17-0756-01 , Sigma-Aldrich ) or Ni-NTA Agarose ( R90115 , ThermoFisher ) . The 6His-tagged PDZ12 used for crystallography was further purified using Resource Q Sepharose anion exchange ( 17-1177-01 , GE Healthcare ) followed by Superdex 75 gel-filtration chromatography ( 17-5174-01 , GE Healthcare ) . Biotinylated 19-mer peptides corresponding to the carboxy-terminal sequences of JAM-A ( Biotin-SQPSTRSEGEFKQTSSFLV ) , JAM-B ( Biotin-SKVTTMSENDFKHTKSFII ) , JAM-C ( Biotin-NYIRTSEEGDFRHKSSFVI ) , and the same sequences lacking the three last amino acids ( Covalab , France ) were immobilized on streptavidin Sepharose high-performance beads ( GE Healthcare ) . Wild-type mouse testes were isolated , frozen in nitrogen , crushed with a pestle and solubilized in lysis buffer ( 50 mM HEPES pH 7 . 3 , 10% glycerol , 0 . 1 mM EDTA , 150 mM NaCl , 1% Triton X100 and protease inhibitors ) . One milliliter of testis lysate ( 5 mg of protein ) was added to the peptide-coupled beads ( 20 μL ) and incubated for 2 h . The beads were washed 5 times in lysis buffer , boiled in Laemmli buffer , and proteins were analyzed by mass spectrometry or immunoblotting . To visualize proteins by silver staining , 10% of the denatured protein extracts were loaded in a 4–12% Bis-Tris gradient pre-cast NuPAGE gel and run with MOPS buffer according to the manufacturer’s instructions ( Invitrogen ) . For mass spectrometry analysis , 90% of the denatured protein extracts were also loaded in a 4–12% Bis-Tris acrylamide gel , but running of the samples was stopped as soon as the proteins had stacked as a single band . Protein-containing bands were stained with Imperial Blue ( Thermo Scientific ) , cut from gel , and following reduction and iodoacetamide alkylation , digested with high sequencing grade trypsin ( Promega ) . The extracted peptides were further concentrated before analysis . Mass spectrometry analysis was conducted by liquid chromatography-tandem mass spectrometry ( LC-MSMS ) using a LTQ-Velos-Orbitrap ( Thermo Scientific ) online with a nanoLC RSLC Ultimate 3000 chromatography system ( Dionex ) . Five microliters corresponding to 1/5th of the whole sample was injected into the system in triplicate . After pre-concentrating and washing the sample on a Dionex Acclaim PepMap 100 C18 column ( 2 cm × 100 μm i . d . , 100 Å , 5 μm particle size ) , the peptides were separated on a Dionex Acclaim PepMap RSLC C18 column ( 15 cm × 75 μm i . d . , 100 Å , 2 μm particle size ) at a flow rate of 300 nL/min with a two-step linear gradient ( 4–20% acetonitrile/H2O; 0 . 1% formic acid for 90 min and 20-45-45% acetonitrile/H2O; 0 . 1% formic acid for 30 min ) . For peptide ionization using the nanospray source , the spray voltage was set at 1 . 4 kV , and the capillary temperature was 275°C . All of the samples were measured in data-dependent acquisition mode . Each run was preceded by a blank MS run to monitor system background . The peptide masses were measured using a full scan survey ( scan range of 300–1700 m/z , with 30 K FWHM resolution at m/z = 400 , target AGC value of 1 . 00 × 106 and maximum injection time of 500 ms ) . In parallel to the high-resolution full scan in Orbitrap , the data-dependent CID scans of the 10 most intense precursor ions were fragmented and measured in the linear ion trap ( normalized collision energy of 35% , activation time of 10 ms , target AGC value of 1 . 00 × 104 , maximum injection time of 100 ms , isolation window of 2 Da ) . Parent masses obtained in the Orbitrap analyzer were automatically calibrated using a locked mass of 445 . 1200 . The fragment ion masses were measured in the linear ion trap to obtain the maximum sensitivity and the maximum amount of MS/MS data . Dynamic exclusion was implemented with a repeat count of 1 and exclusion duration of 30 s . Raw files ( triplicates ) generated from mass spectrometry analysis were processed with Proteome Discoverer 1 . 4 ( ThermoFisher Scientific ) . This software was used to search the data using an in-house Mascot server ( version 2 . 4 . 1 , Matrix Science Inc . ) against the Mouse subset ( 16 , 696 sequences ) of the SwissProt database ( version 2014_11 ) . Database searches were performed using the following settings: a maximum of two trypsin miscleavages allowed , methionine oxidation and N-terminal protein acetylation as variable modifications , and cysteine carbamido-methylation as a fixed modification . A peptide mass tolerance of 6 ppm and fragment mass tolerance of 0 . 8 Da were used for the search analysis . Only peptides with high stringency Mascot score threshold ( identity , FDR < 1% ) were used for protein identification . Only proteins that interact with full-length peptides and not with peptides lacking the last three amino acids or bead control are listed in S1 Table . Number of peptide-spectrum matches was indicated to show the relative amount of pulled down proteins . Entry clones were used in a Gateway LR reaction to transfer the DNA coding for the full-length coding sequence or GRASP55Δ into the Y2H activation domain expression vector pACT2 [52] . DNA fragments encoding the cytoplasmic sequences of JAM-A , JAM-B ( 41 last residues ) and JAM-C ( 48 residues ) or lacking the sequence encoding the last three aa of the proteins ( JAMsΔ constructs ) were cloned into the Y2H binding domain expression vector pGBT9 . The vectors were then co-transformed in the AH109 yeast strain ( MATa , trp1-901 , leu2-3 , 112 , ura3-52 , his3-200 , gal4Δ , gal80Δ , LYS2∷GAL1UAS-GAL1TATAHIS3 , GAL2UAS-GAL2TATA-ADE2 , URA3∷MEL1 UASMEL1TATA-lacZ , MEL1 ) using the lithium acetate method [53] . Following transformation , the yeast were plated onto synthetic complete ( SC ) medium lacking leucine ( -L ) and tryptophan ( -W ) and were incubated at 30°C for 4 to 5 days . The yeast clones were then transferred in liquid SC-WL for 3 days at 30°C with agitation to normalize the yeast cell concentration used for the phenotypic assay . The cells were then diluted 1/20 in water and spotted onto selective medium ( -WHL ) for the phenotypic assay . The binding parameters for the JAM peptides to the fusion proteins were evaluated using the homogenous time-resolved fluorescence assay ( HTRF ) . Peptide binding to the fusion proteins was measured in 0 . 05 M HEPES , 0 . 15 M NaCl , and 0 . 25% BSA ( w/v ) pH 7 . 3 at equilibrium ( 18 h , 4°C ) in reaction mixtures consisting in: fusion proteins at the indicated concentrations ( Fig 1D ) or 2 . 5 x 10−9 M ( Fig 6B ) , anti-GST or anti-6His antibody coupled to terbium cryptate ( 1 x 10−9 M ) , streptavidin-d2 ( 1 . 25 x 10−9 M ) ( Cisbio ) , and biotinylated peptide ( 6 x 10−9 M ) with competing non-biotinylated peptide or organic compound at the indicated concentration . In the latter case , DMSO concentration was kept constant . Upon excitation of the reaction mixture at 337 nm , a 615 nm fluorescence emission is produced by the donor terbium that excites a 665 nm emission by the acceptor streptavidin-d2 bound to the biotinylated peptide , only if it resides in close vicinity to the donor , i . e . bound to the fusion protein . The intensity of light emission at 615 and 665 nm was measured using a Polarscan Omega ( BMG Labtech ) microplate reader equipped for HTRF . For each condition , the A665/A615 ratio ( R ) of fluorescence was calculated . The change in fluorescence , delta F ( ΔF ) , was then computed as follows: [ ( RSample-RNSB ) /RNSB]x100 , where RNSB is the A665/A615 fluorescence ratio produced by the reaction mixture without fusion protein or biotinylated peptide . The EC50 was determined by plotting the ratio of the ΔF with homologous non-biotinylated or pharmacological inhibitor over ΔF0 ( ΔF without competitor ) against the log of the inhibitory compound using dose-response and curve-fitting analyses in Prism software ( variable slope , four parameters ) . Values with an R square value greater than 0 . 99 were considered as significant . Isothermal titration calorimetry ( ITC ) was used to evaluate the thermodynamic parameters of the binding between GRASP55 and the selected JAM peptides . Purified GRASP55 was extensively dialyzed in 100 mM NaPO4 buffer at pH 7 . 5 . Peptide powders were dissolved directly in the last protein dialysate prior to the experiments . The protein concentration was calculated by measuring the absorbance at 280 nm using a NanoDrop ND1000 ( Thermo Scientific ) , and the titrations were conducted using a MicroCal ITC200 microcalorimeter ( GE Healthcare ) . Each experiment was designed using a titrant concentration ( peptide in the syringe ) set at 10 to 30 times the analyte concentration ( protein in the cell ) and generally using 17 injections of 2 . 3 μL at 25°C ( see S2 Table for details ) . A small initial injection ( generally 0 . 2 μL ) was included in the titration protocol to remove air bubbles trapped in the syringe prior to the titration . Integrated raw ITC data were fitted to a one-site nonlinear least-squares fit model using the MicroCal Origin plugin ( http://www . originlab . com/ ) after subtraction of the control experiments ( titration of the ligand from the syringe into the buffer ) when necessary . Finally , the ΔG ( G: Gibbs free energy ) and TΔS ( T: absolute temperature , S: entropy ) values were calculated from the fitted ΔH ( H: enthalpy ) and KA values using the following equations: ΔG = -R . T . lnKA and ΔG = ΔH–TΔS . Purified GRASP55 was concentrated to approximately 15 mg/mL in a solution of 20 mM Tris . HCl pH 8 . 0 , 150 mM NaCl for crystallization . Initial hits were obtained using commercially available sparse matrix screens ( Hampton Research ) using the sitting drop vapor diffusion method at 20°C . Optimization was conducted with the hanging drop vapor diffusion method , and diffraction-quality crystals were obtained in a solution of 2 . 0 M sodium formate , 0 . 1 M sodium acetate , pH 4 . 6 . Crystals were soaked with JAM-B or JAM-C peptide using a 1:1 molar ratio for one day . The crystals were cryoprotected in reservoir solution supplemented with 25% glycerol and then flash frozen in liquid nitrogen . For structural characterization and refinement , see Supplemental Experimental Procedures . Differential scanning fluorimetry ( DSF ) was performed as previously described [54] . A protein/SYPRO orange dye mix containing 4 μM GRASP55 and a 1:5 , 000 dilution of dye ( Life Technologies ) were prepared in phosphate-buffered saline ( PBS ) extemporally . Then , 19 . 5 μL of the protein/dye mix was aliquoted into a 96-well plate , and 0 . 5 μL of Graspin ( 2 mM stock solution in 100% DMSO , 50 μM final concentration ) or DMSO control ( 2 . 5% final DMSO concentration ) was dispensed . The GRASP55/JAM-C DSF experiment was performed by adding JAM-C peptide ( 1 mM stock in PBS ) to the protein/dye mix at a final concentration of 50 μM in the presence of 2 . 5% DMSO . After sealing with optical tape , thermal melting experiments were performed using a CFX96 ( Bio-Rad ) Real-time PCR detection system . The plates were first equilibrated at 25°C for 5 min and then heated at increments of 1°C every 60 s , from 20 to 90°C . The fluorescence intensity was recorded at every temperature step using the built-in FRET filter . Raw fluorescence data were evaluated using Microsoft Excel and GraphPad Prism template files adapted from Niesen et al [54] . After normalization , the melting temperatures ( Tm ) were measured using a Boltzmann fit equation in GraphPad Prism 5 . 03 . Mice were used in compliance with the laws and protocols approved by the animal ethics committees ( Agreement #02294 . 01 ) . Gorasp2-deficient animals were generated as described in Supporting Information . Mice used in this study were backcrossed for more than six generation onto C57BL/6J background . Knock-out mice or littermate controls were obtained from heterozygous crossing . Sperm analysis was outsourced to Charles River Company . Sperm concentration , percentage of cells with normal morphology , abnormal head , bent midpiece , normal motility but also weight of testis , epididymis and seminal vesicle were determined . The GRASP55 inhibitor Graspin ( PubChem CID #3113208 , Vitas-M Laboratory Ltd . , Ref . STK700118 ) was dissolved in 10% DMSO , 90% corn oil and was injected intraperitoneally into 27-day-old wild type male mice at 50 mg/kg on days 0 , 3 , 7 , 10 , and 14 ( see Fig A in S8 Fig ) . Mice receiving Graspin or vehicle treatments were sacrificed 16 days after treatment initiation . Gorasp2+/+ and Gorasp2-/- primary Mouse Embryonic Fibroblasts ( MEFs ) were isolated from 14-day embryos . The two uterine horns were collected in sterile conditions . Each embryo was released in PBS , head was collected for genotyping , liver and viscera were removed . Embryos were crushed on 70 μm cell strainer , washed in culture medium and seeded in 25 cm2 flask . MEFs were cultivated in DMEM supplemented with 10% fetal calf serum ( FCS ) , 2 mM L-Glutamine , 100 U/ml penicillin-streptomycin , 1% essential amino acids , 25 μM β-mercaptoethanol and 1 mM sodium pyruvate at 37°C in a 5% CO2 humidified atmosphere . Re-expression of GRASP55 in Gorasp2-/- MEFs was achieved upon transfection of GRASP FL fused to mCherry using MEF 2 Nucleofector Kit according to manufacturer instruction ( Lonza ) . For Graspin treatment , MEFs plated at 70% confluency were incubated overnight and treatment was started the following morning for 48hours with Graspin at indicated concentrations . Graspin stock solution was dissolved at 10mM concentration in anhydrous DMSO ( Cat# D12345 , Life Technology ) . Treatment with DMSO 0 . 5% corresponding to the highest Graspin concentration ( 50μM ) was used as control . For co-immunoprecipitation of GRASP55 with JAM-C , Gorasp2+/+ and Gorasp2-/- mouse testes were frozen in nitrogen , crushed with a pestle and solubilized in lysis buffer ( 50 mM HEPES pH 7 . 3 , 10% glycerol , 0 . 1 mM EDTA , 150 mM NaCl , 1% Triton X100 and protease inhibitors ) . Protein G Sepharose 4 Fast Flow ( GE Healthcare ) was coupled to an anti-GRASP55 or rabbit IgG control antibody and incubated with pre-cleared testis lysate ( 5 mg/mL of proteins , approximately 45 mg per condition ) overnight at 4°C . For GRASP55 immunoblotting , Gorasp2+/+ and Gorasp2-/- mouse lung , heart and testis tissues were frozen in nitrogen , crushed with a pestle and solubilized in RIPA buffer ( 50 mM Tris HCL pH 7 . 5 , 150 mM NaCl , 1% Triton X100 , 0 . 1% SDS , 1% Na deoxycholate and protease inhibitors ) . Denatured proteins were separated by electrophoresis in 8% or 10% acrylamide gels and transferred to nitrocellulose membrane . The membranes were blocked with 5% non-fat dry milk , 0 . 05% Tween , and 1X PBS for 1 h at room temperature and incubated with primary antibodies overnight at 4°C , followed by secondary antibodies for 1 h at room temperature ( RT ) . Testes were carefully collected , and surrounding tissues were removed . The organs were fixed in 4% paraformaldehyde in PBS overnight and conserved in ethanol 70% before paraffin-embedding . 3-μm-thick deparaffinized sections were stained with PAS or used for immunofluorescence . Primary antibodies were incubated overnight at 4°C , and secondary antibodies were incubated for 1 h RT . Same-species primary antibodies ( pAb 501 rabbit anti-mouse JAM-C and rabbit anti-mouse GRASP55 antibodies in Figs 3 and 7 ) were detected using tyramide signal amplification ( TSA ) according to manufacturer instructions ( PerkinElmer Inc . ) . The slides were mounted with Prolong Gold Antifade Reagent ( Invitrogen ) . For JAM-A , ZO-1 and SOX 9 staining , testes were fixed in 4% paraformaldehyde in PBS overnight , washed in PBS and transferred in 30% sucrose overnight before soaking , embedding and freezing in gelatin-sucrose solution ( 7 . 5% and 15% respectively , in PBS ) . Sections ( 14-μm-thick ) were generated with a CryoStar NX70 cryostat ( Thermo Scientific ) . IF were performed in same conditions as previously described . Detection of apoptotic cells on testis section after Graspin treatment was assessed by TUNEL staining according to manufacturer instructions ( DeadEnd Fluorometric TUNEL System , Promega ) . Images were acquired using LSM510 META and LSM880 AiryScan confocal microscopes ( Zeiss ) and analyzed using Zen , ImageJ and Adobe Photoshop software . Periodic Acid Schiff coloration of testis sections was performed on Bouin’s solution fixed tissues as previously described [55] using hematoxylin-eosin as counterstain . Intact epididymes ( caput , corpus and cauda ) were collected from Gorasp2+/+ , Gorasp2-/- , vehicle or Graspin treated mice . Epididymes were minced and placed into 500μl of PBS at 37°C from 30 min to allow sperm to swim-out . Diffused cell suspension were filtered through a 70μM cell stainer and resuspended in 500μl PBS solution . 50 μL of cell suspension were loaded into a cytospin chamber and centrifuged for 10 min at 250 rpm on poly L-Lysine coated slides . After centrifugation , supernatant were removed and cells on microscope glass slides were fixed 10 min in ice-cold methanol . Then , cells were washed in PBS and incubated with primary antibody solution ( JAM-C ) overnight at 4°C and secondary antibody , PNA-FITC and DAPI solution 1h , RT . The slides were mounted with Prolong Gold Antifade Reagent ( Invitrogen ) . Seminiferous tubules from decapsulated testes or epididymes were minced in PBS , warmed to 37°C and incubated for 15 min at room temperature with agitation ( 200 rpm on an orbitary shaker ) . Diffused germ cell suspension were collected in PBS , filtered through a 70μM cell strainer ( Ref 352350 , BD Falcon ) , fixed and permeabilized using the Cytofix/Cytoperm kit ( BD Biosciences ) . DNA was stained by incubation with DAPI for 30 min at room temperature . Flow cytometry analysis was performed using a BD-FORTESSA ( BD Biosciences ) cytometer , and the results were analyzed using BD-DIVA version 8 ( BD Bioscience ) , FlowJo version 10 ( TreeStar ) and Kaluza version 1 . 3 ( Beckman Coulter Inc . ) softwares . Data were analyzed for statistical significance using GraphPad Prism software with the methods that are mentioned in figure legends . | Spermatogenesis defects are a common cause of male sterility . Spermatogenesis occurs in the seminiferous tubules of the testes and involves adhesive interactions between developing germ cells and Sertoli cells . Knock-out mouse models identified several adhesion molecules that are critically involved in spermatogenesis . We previously demonstrated that the Junctional Adhesion Molecule-C ( JAM-C ) plays a crucial role in establishing spermatids polarity . The latter involves rearrangements of the Golgi apparatus in spermatids which contribute to acrosome formation . The present study demonstrated that the C-terminal cytosolic region of JAM-C interacted with the Golgi reassembly stacking protein of 55 kDa ( GRASP55 ) encoded by Gorasp2 and that spermatogenesis was impaired in Gorasp2-deficient mice . We developed an inhibitor of GRASP55 interaction with JAM-C and demonstrated that treatment of wild-type mice with the inhibitory compound induced germ cell loss . Therefore , the male infertility-associated pathway identified in this study is important not only from a genetic point of view , but also as a potential target for male contraception . | [
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"orga... | 2017 | Genetic, structural, and chemical insights into the dual function of GRASP55 in germ cell Golgi remodeling and JAM-C polarized localization during spermatogenesis |
Sexual reproduction is critical for successful evolution of eukaryotic organisms in adaptation to changing environments . In the opportunistic human fungal pathogens , the Cryptococcus pathogenic species complex , C . neoformans primarily undergoes bisexual reproduction , while C . deneoformans undergoes both unisexual and bisexual reproduction . During both unisexual and bisexual cycles , a common set of genetic circuits regulates a yeast-to-hyphal morphological transition , that produces either monokaryotic or dikaryotic hyphae . As such , both the unisexual and bisexual cycles can generate genotypic and phenotypic diversity de novo . Despite the similarities between these two cycles , genetic and morphological differences exist , such as the absence of an opposite mating-type partner and monokaryotic instead of dikaryotic hyphae during C . deneoformans unisexual cycle . To better understand the similarities and differences between these modes of sexual reproduction , we focused on two cellular processes involved in sexual reproduction: cell-cell fusion and karyogamy . We identified orthologs of the plasma membrane fusion protein Prm1 and the nuclear membrane fusion protein Kar5 in both Cryptococcus species , and demonstrated their conserved roles in cell fusion and karyogamy during C . deneoformans α-α unisexual reproduction and C . deneoformans and C . neoformans a-α bisexual reproduction . Notably , karyogamy occurs inside the basidum during bisexual reproduction in C . neoformans , but often occurs earlier following cell fusion during bisexual reproduction in C . deneoformans . Characterization of these two genes also showed that cell fusion is dispensable for solo unisexual reproduction in C . deneoformans . The blastospores produced along hyphae during C . deneoformans unisexual reproduction are diploid , suggesting that diploidization occurs early during hyphal development , possibly through either an endoreplication pathway or cell fusion-independent karyogamy events . Taken together , our findings suggest distinct mating mechanisms for unisexual and bisexual reproduction in Cryptococcus , exemplifying distinct evolutionary trajectories within this pathogenic species complex .
Sexual reproduction is ubiquitous in eukaryotic systems and promotes genetic diversity important for successful evolutionary adaptation to ever-changing environments [1] . In addition to bisexual reproduction between mating partners of opposite sexes , many eukaryotic systems , including fish , amphibians , and reptiles , can undergo unisexual reproduction , termed parthenogenesis , often in the absence of the opposite sex [2] . During bisexual reproduction , parental gametes undergo cell fusion and nuclear fusion to produce recombinant progeny , whereas during parthenogenesis , the maternal genome undergoes reduplication through either cell-cell fusion or endoreplication to produce clonal offspring of the mother [2] . Analogous to parthenogenesis , several human fungal pathogens have been reported to undergo both unisexual and bisexual reproduction [3 , 4] . In Candida albicans bisexual reproduction , a/a and α/α cells first undergo white-opaque switching to become mating competent and then form tetraploid cells via cell fusion and nuclear fusion . These cells then undergo a parasexual cycle to return to the diploid state . During C . albicans unisexual reproduction , loss of the Bar1 protease in a/a cells enables auto-response to MFα pheromone and promotes cell and nuclear fusion producing tetraploid cells [5] . During bisexual reproduction in the Cryptococcus species complex , cell fusion triggers a dramatic yeast-hyphal morphological transition , producing dikaryotic hyphae . The growing tips of these hyphae differentiate into basidia , in which two nuclei undergo nuclear fusion to produce basidiospores through meiosis [6] . During the unisexual cycle , α or a cells initiate hyphal growth and form monokaryotic hyphae , during which the haploid nucleus undergoes a ploidy increase through either cell-cell fusion followed by nuclear fusion , nuclear fusion between mother and daughter cells , or an endoreplication pathway , and the diploid nucleus inside the basidium then undergoes meiosis and produces haploid spore progeny [7 , 8] . Sexual reproduction has only been observed under laboratory conditions In the Cryptococcus species complex . However , spore-like cells have been harvested from the environment , suggesting the sexual cycle may occur in natural environments [9 , 10] . Unisexual reproduction has been documented for C . neoformans , C . deneoformans , and C . gattii [7 , 11 , 12] . Based on evidence from population genetics studies , natural isolates also recombine through unisexual reproduction , which may be of ecological significance because more than 99% of environmental and clinical isolates are the α mating type [13–16] . Of note , the unisexual cycle generates genotypic and phenotypic diversity de novo , similar to the bisexual cycle [17] . A common set of genetic circuits govern both unisexual and bisexual reproduction , [8 , 18–20] and both sexual cycles involve similar meiotic recombination mechanisms [21] . The recombining nature of the unisexual cycle can enable a clonal population to reverse Muller’s ratchet and avoid an evolutionary dead end [22] . Despite similar regulatory genetic circuits , fundamental differences are obvious between the two modes of sexual reproduction [23–25] . Genetically , the unisexual cycle is initiated in the absence of an opposite-mating type partner , whereas the bisexual cycle is initiated upon a-α cell-cell fusion . Morphologically , the unisexual cycle produces monokaryotic hyphae with unfused clamp cells , while the bisexual cycle produces dikaryotic hyphae with fused clamp cells , which allow a nucleus to migrate between adjacent hyphal compartments to maintain dikaryotic hyphae [24 , 25] . While diploidization is achieved through karyogamy in the bisexual cycle , it is not yet clear how diploidization is achieved during the unisexual cycle . Three hypotheses have been proposed , including 1 ) cell fusion followed by karyogamy; 2 ) karyogamy between mitotically dividing mother-daughter cells followed by either mis-segregation of the nucleus or cytokinesis arrest; and 3 ) endoreplication during hyphal growth [25 , 26] . In all bisexually reproducing organisms , gamete fusion is a fundamental process requiring a set of dedicated fusion proteins [27] . In the fungal kingdom , Prm1 ( Pheromone regulated multi-spanning membrane protein 1 ) is a conserved plasma membrane protein required for plasma membrane fusion during cell-cell fusion [28–30] . In Saccharomyces cerevisiae and Neurospora crassa , deletion of PRM1 reduces fusion frequency by approximately half and leads to cell lysis . The mutant phenotype is alleviated in the presence of a high calcium and exacerbated upon calcium depletion [31 , 32] . Prm1 is also required for asexual hyphal fusion in N . crassa [29] . In Schizosaccharomyces pombe , deletion of PRM1 causes a 95% reduction in cell fusion frequency independent of extracellular calcium concentration , but does not lead to a cell lysis phenotype [30] . Cell fusion has been well studied in Cryptococcus sexual cycles . During bisexual reproduction , a-α cell-cell fusion is required for hyphae induction and clamp cell-hyphal fusion is required for proper nuclear migration between adjacent hyphal compartments to maintain dikaryotic hyphal growth [6 , 33] . During unisexual reproduction , α-α cell-cell fusion occurs at a low frequency whereas the presence of a cells can enhance α-α cell fusion ~1000 fold in a ménage à trois fashion [7] . G proteins in the pheromone response pathway are required for cell-cell fusion [34] , and the master transcription factor Mat2 governs the yeast-hyphal morphological transition [18] . An evolutionarily conserved Ire1 kinase/endoribonuclease in the unfolded protein response pathway has been shown to negatively regulate the pheromone response pathway and is required for cell-cell fusion [35] . However , genes that are directly involved in plasma membrane fusion during cell-cell fusion have not been identified . A transcriptomic study showed that expression of the S . cerevisiae PRM1 homolog in C . deneoformans is highly upregulated during hyphal growth , suggesting it may function in the sexual cycle , but its involvement in cell-cell fusion had yet to be determined [18] . Karyogamy is an essential step for intermixing of parental genetic information during sexual reproduction . Two sets of genes regulate karyogamy in S . cerevisiae . The class I genes , including KAR1 , KAR3 , KAR4 , and KAR9 , regulate nuclear congression , while the class II genes , including KAR2 , KAR5 , KAR7 , KAR8 , and PRM3 , mediate inner and outer nuclear membrane fusion [36 , 37] . Lee and Heitman identified the Cryptococcus karyogamy genes KAR2 , KAR3 , KAR4 , KAR7 , and KAR8 based on homology to S . cerevisiae [38] . While homologs of KAR2 and KAR7 were identified in Cryptococcus with roles in filamentation and meiosis , respectively , homologs of KAR3 , KAR4 , and KAR8 did not show karyogamy defects during unisexual or bisexual reproduction . This suggests that these genes are either rewired in Cryptococcus compared with S . cerevisiae or are functionally redundant in regulating nuclear fusion . KAR2 , an ER-resident chaperone protein , is essential in Cryptococcus , and its overexpression partially rescues the filamentation defect of the ire1 mutant [35 , 39] . KAR7 maintains a conserved role in mediating nuclear membrane fusion during both Cryptococcus unisexual and bisexual reproduction . However , a diploid strain without KAR7 produced hyphae and basidia but failed to undergo sporulation , suggesting KAR7 may play additional roles in meiotic processes . In S . cerevisiae , Kar5 localizes to both inner and outer nuclear membranes at the spindle pole body , and coordinates the outer and inner nuclear membrane , facilitating the inner nuclear membrane fusion step during karyogamy [40–42] . However , a KAR5 homolog was not identified in Cryptococcus . A study on the Chlamydomonas nuclear fusion gene GEX1 by Ning and colleagues [43] showed that protist and plant GEX1 genes and fungal KAR5 genes belong to an ancient cysteine rich domain ( CRD ) containing protein family that is conserved throughout eukaryotes , suggesting that they may share a conserved role in nuclear membrane fusion . In that same study , a KAR5 ortholog was identified for a basidiomycetous fungus , Puccinia graminis [43] . In this study , we identified PRM1 and KAR5 orthologs in both C . neoformans and C . deneoformans and investigated their conserved functions in mediating plasma membrane and nuclear membrane fusion . Utilizing these two genes , we studied cell fusion and nuclear fusion in the C . neoformans bisexual cycle and the C . deneoformans unisexual and bisexual cycles . C . neoformans and C . deneoformans bisexual cycles were dependent on cell and nuclear fusion at different stages during sexual development , whereas , cell fusion was largely dispensable in the solo unisexual cycle of C . deneoformans and the ploidy duplication during unisexual reproduction is dependent on either endoreplication or cell fusion-independent karyogamy events . Our results provide mechanistic insights relevant to studies of mating mechanisms of unisexual reproduction and parthenogenesis in other eukaryotic systems .
To study cell-cell fusion during the Cryptococcus sexual cycles , we performed BLASTP searches to identify plasma membrane fusion protein , Prm1 , known to orchestrate cell-cell fusion during mating in other fungi . BLASTP searches using S . cerevisiae , C . albicans , Aspergillus fumigatus , S . pombe , and N . crassa Prm1 protein sequences [28–30] identified CNAG_05866 ( Cn Prm1 ) and CNF01070 ( CdPrm1 ) as candidate PRM1 genes in C . neoformans and C . deneoformans , respectively ( S1A and S1B Fig ) . The CnPrm1 and CdPrm1 proteins share 91% sequence identity and are the only candidate proteins that shared significant sequence similarity with Prm1 proteins from other fungal organisms . Reciprocal BLASTP searches confirmed the orthologous nature of these fungal PRM1 genes . Both CnPrm1 and CdPrm1 are predicted to share a similar protein topology with ScPrm1 and SpPrm1 , and contain four transmembrane domains based on Phobius prediction [44] . However , the Cryptococcus Prm1 proteins have a long C-terminal tail following the last transmembrane domain ( Fig 1A ) . Another crucial cellular process during sexual reproduction is karyogamy , the fusion of nuclei . One of the karyogamy proteins in S . cerevisiae , Kar5 , facilitates nuclear membrane fusion during mating [40 , 42] . We identified CNAG_04850 as the KAR5 gene in C . neoformans using the Kar5 protein sequence of Puccinia graminis [43] , which belongs to the same phylum ( Basidiomycota ) as Cryptococcus . The same BLASTP search failed to identify the CdKAR5 gene , but using the CnKAR5 genomic sequence we identified an unannotated region on chromosome 10 from bp 790071 to 792560 that encodes the KAR5 ortholog in C . deneoformans . BLASTP searches and phylogenetic analyses of Kar5 proteins from several fungal organisms suggested that Kar5 protein sequences are divergent across different fungal species ( S1C and S1D Fig ) . Multiple sequence alignment and topology predictions by Phobius prediction and COILS/PCOILS confirmed that CnKar5 and CdKar5 share a similar protein topology with ScKar5 and SpKar5 , with an N-terminal signal peptide and a CRD domain , followed by coiled-coiled domains and a C-terminal transmembrane domain , except that SpKar5 does not have the N-terminal signal peptide ( Fig 1B and S1E Fig ) [44 , 45] . Deletion of PRM1 caused a significant filamentation delay during C . neoformans bisexual reproduction ( Fig 2A ) . However , abundant hyphal production and sporulation were still observed after 10 days ( S2A Fig ) . To evaluate the overall impact of PRM1 deletion on overall mating progress , we quantified the relative spore production of prm1 mutants compared to the wild type at 7 days by Percoll gradient centrifugation . Deletion of PRM1 caused a mild reduction in spore production ( 87 . 3 ± 9% of wild type , p = 0 . 207 ) ( S3A Fig ) . We conducted a wild type mating between CF757 ( JEC20a URA5-NAT ) and CF762 ( JEC21α ADE2-NEO ) as a control . A total of 47 spore derived colonies were randomly chosen and analyzed ( S4A Fig ) . Among the 47 progeny , all eight genotypes of Mendelian inheritance were recovered at a distribution of frequency ranging from 2 . 1% to 23 . 4% ( 17% parental genotype MATa URA5-NAT , 2 . 1% for parental genotype MATα ADE2-NEO , 12 . 8% for MATα URA5-NAT , 23 . 4% for MATa ADE2-NEO , 6 . 4% for MATa URA5-NAT ADE2-NEO , 6 . 4% for MATα URA5-NAT ADE2-NEO , 17% for MATa , and 14 . 7% for MATα ) ( S4B and S4C Fig ) . This provides evidence that the cells isolated by Percoll gradient centrifugation are indeed spores . To address the involvement of Prm1 in cell-cell fusion , we performed cell fusion assays using two genetically marked mating partners . prm1 mutants showed a bilateral ( prm1Δ X prm1Δ ) cell fusion defect with a fusion frequency of 12% ± 4% relative to the wild type level ( Fig 2B ) , but no defect in unilateral ( prm1Δ X WT ) cell fusion . The basal level of cell fusion activity may allow prm1 mutants to produce abundant hyphae after a 10-day incubation on mating inducing medium ( S2A Fig ) . During C . neoformans bisexual reproduction , the dikaryotic hyphae generate clamp cells , which fuse with adjacent hyphal compartments to allow a nucleus to translocate between hyphal compartments and maintain the dikaryon status [6] . To test whether Prm1 plays a role in clamp cell-hyphal fusion , we examined hyphae by scanning electron microscopy ( SEM ) . The clamp cell and a peg from the adjacent hyphal compartment both exhibited elongated tubular morphology in prm1 mutants compared to clamp cell connections in the wild type ( Fig 2C ) , suggesting that these clamp cells and peg protrusions failed to undergo cell fusion . Transmission election microscopy ( TEM ) showed that the plasma membranes failed to undergo fusion in the clamp cells ( S5 Fig ) . DAPI staining of hyphal nuclei showed that a single nucleus was trapped in the prm1 mutant clamp cells , resulting in an abnormal number of nuclei in a single hyphal compartment ( Fig 2D ) . Clamp cell fusion is regulated by the pheromone signaling pathway , both PRM1 and MFα expression were maintained at a significantly high level after mating for seven days on mating inducing V8 medium compared to non-mating inducing YPD medium ( 3 . 4-fold increase for PRM1 , p <0 . 005; and 50 . 8-fold increase for MFα , p <0 . 005 ) ( Fig 2E and 2F ) . prm1 mutants exhibited a significant increase in MFα expression compared to wild type ( 1 . 9-fold increase , p <0 . 005 ) , suggesting that the cell fusion defect dampens MFα repression that occurs in response to SXI1α-SXIa repression following nuclear pairing ( Fig 2F ) . These results indicate that Prm1 plays a role in both cell-cell fusion and clamp cell-hyphal fusion during C . neoformans bisexual reproduction ( Fig 3G ) . Like prm1 mutants , kar5 mutants showed a significant delay in filamentation during C . neoformans bisexual reproduction ( Fig 3A ) ; the mutants produced abundant hyphae after 10 days ( S2B Fig ) . In contrast to other prm1 mutant phenotypes , kar5 mutants were not defective in cell fusion but exhibited sporulation defects ( Fig 3A and 3B ) . SEM studies showed that the abnormal basidia were either bald or had more than four budding sites compared to the four sites in the wild type ( Fig 3C ) . However , the wild type phenotype ( four spore chains ) was observed in kar5 mutants after longer mating incubation periods . Similar to prm1 mutants , deletion of KAR5 caused a mild reduction in spore production ( 77 . 2% ± 8 . 8% p <0 . 05 ) ( S3B Fig ) , suggesting that deletion of KAR5 did not completely block sporulation . We stained the nuclei within the abnormal basidia generated by kar5 mutants with DAPI and found two nuclei in close contact within the kar5 mutant bald basidia in contrast to either one nucleus or four meiotic nuclei present in wild type basidia ( Fig 3D and 3E ) . Quantification of 129 wild type basidia and 131 kar5 mutant basidia stained with DAPI showed that 5 . 7% wild type basidia versus 48 . 9% kar5 mutant basidia contained two nuclei , suggesting that deletion of KAR5 inhibited , but did not completely block karyogamy inside the basidia ( Fig 3E ) . The nuclear morphology of the C . neoformans kar5 mutant was similar to the kar5 mutant karyogamy phenotype in S . cerevisiae [42] , supporting the hypothesis that KAR5 plays a conserved role in mediating karyogamy during C . neoformans bisexual reproduction . KAR5 expression was upregulated upon mating induction and maintained at a significantly high level after mating for a week compared to non-mating inducing conditions ( 1 . 6-fold increase , p <0 . 05 ) . Deletion of PRM1 significantly reduced KAR5 expression ( 1 . 6-fold decrease , p <0 . 05 ) , suggesting control of gene expression following cell-cell fusion during C . neoformans bisexual reproduction ( Fig 3F and 3G ) . In contrast to C . neoformans , C . deneoformans prm1 mutants showed a mild delay in hyphal production ( Fig 4A ) , and exhibited a significant reduction in spore production compared to wild type C . deneoformans ( 27% ± 2 . 2% ) bisexual reproduction ( S3A Fig ) . PRM1 deletion caused both bilateral and unilateral cell fusion defects with fusion frequencies of 6 . 9% ± 2 . 6% and 8 . 2% ± 1 . 8% of the wild type levels , respectively ( Fig 4B ) . To understand the mechanistic requirement for Prm1 in cell-cell fusion during C . deneoformans bisexual reproduction , we monitored cell-cell fusion of prm1 mutants with confocal microscopy . In the same prm1 mutant cell fusion sample , both fused and unfused cells were detected by the presence and absence of inter-cellular mixing of fluorescent signals between the Nop1-GFP and mCherry labeled fusion pairs ( Fig 4C , S1 and S2 Movies ) . Based on quantification of fluorescent signal intermixing , the wild type cell fusion frequency was 90 . 6% , while the prm1 mutant unilateral cell fusion and bilateral cell fusion frequencies were 51 . 7% and 12 . 8% , respectively ( Fig 4D and S6 Fig ) . The unilateral cell fusion defect suggests that the Prm1 plays a more important role during bisexual reproduction in C . deneoformans compared to C . neoformans; in agreement with this observation , PRM1 expression level was maintained at a similar high level after mating for seven days compared with 36 hours ( Fig 4E ) . To visualize the structures of the plasma membrane at the conjugation sites between the fusion pairs , we stained both wild type and prm1 mutant fusion pairs with the lipophilic dye FM4-64 . The prm1 mutant fusion pairs exhibited robust staining of the plasma membrane boundaries at the conjugation site ( Fig 4F ) . Compared to the fused wild type cells , the plasma membrane of the prm1 mutant fusion pairs failed to undergo membrane fusion at the conjugation sites , and a layer of cell wall material was present between the plasma membranes ( Fig 4G and S7A Fig ) . In 2 out of 20 observed fusion pairs by TEM , the plasma membranes formed extensive invaginations into the opposite cytosolic compartments without membrane fusion ( Fig 4G ) . Similar to C . neoformans bisexual reproduction , prm1 mutants also exhibited a clamp cell-hyphal fusion defect during C . deneoformans bisexual reproduction ( S7B Fig ) . However , both wild type and prm1 mutant crosses produced hyphae with unfused clamp cells , which are characteristics of monokaryotic hyphae ( S7B and S8A Figs ) . Overall , these results suggest that PRM1 plays a more significant role in C . deneoformans bisexual reproduction in comparison to C . neoformans . Like prm1 mutants , kar5 mutants showed a mild delay in hyphal production , and produced significantly fewer spores compared to wild type ( 9 . 5% ± 2 . 7% ) ( Fig 5A and S3B Fig ) . SEM studies demonstrated that C . deneoformans kar5 mutants produced basidia with abnormal sporulation patterns during bisexual reproduction , similar to C . neoformans kar5 mutants ( Fig 5B ) . Deletion of KAR5 caused both bilateral and unilateral cell fusion defects with fusion frequencies of 32 . 3% ± 6% and 24 . 5% ± 2 . 7% compared to the wild type level , respectively ( Fig 5C ) . To test whether KAR5 is directly involved in cell-cell fusion , we quantified cell-cell fusion events for kar5 mutants based on fluorescent signal intermixing , and found that kar5 mutant cell-cell fusion frequency was 86 . 4% , similar to wild type ( Fig 4D and S6D Fig ) , suggesting that Kar5 plays a role in post-fusion survival mechanisms for cell fusion products , and that the function of CdKar5 in bisexual reproduction is diverged from CnKar5 ( Fig 3B , and 5C ) . Furthermore , CdKAR5 and CdMFα expression were upregulated upon mating induction , but returned to basal level after mating for seven days , which is distinct from CnKAR5 and CnMFα expression patterns ( Figs 2F , 3F , 5D and 5E ) . However , CdKAR5 expression was significantly reduced for Cdprm1 mutants compared to wild type ( 2 . 7-fold decrease , p <0 . 05 ) ( Fig 5D ) , similar to C . neoformans ( Fig 3F ) . To elucidate the phenotypic differences of prm1 and kar5 mutants during bisexual reproduction between C . neoformans and C . deneoformans , we stained wild type and mutant hyphal nuclei with DAPI . In contrast to the dikaryotic hyphae produced by C . neoformans ( Fig 2D ) , C . deneoformans bisexual reproduction produced monokaryotic hyphae ( S8A Fig ) , similar to those produced during C . deneoformans unisexual reproduction ( S8B Fig ) . To dissect the involvement of Prm1 and Kar5 in monokaryotic hyphae formation during C . deneoformans bisexual mating , we tracked nuclear dynamics using the nucleolar marker Nop1-GFP [38] . During early bisexual mating at 48 hours , wild type produced both monokaryotic and dikaryotic hyphae ( Fig 5F and S9A Fig ) , whereas prm1 mutants mainly produced monokaryotic hyphae ( S9A Fig ) . In both wild type and kar5 mutant hyphae , pairs of congressed nuclei were observed , resembled the C . neoformans kar5 mutant karyogamy phenotype inside basidia during bisexual reproduction ( Figs 3D and 5F and S9A Fig ) . After 10 days , monokaryotic and dikaryotic hyphae were present in the wild type cross , while prm1 mutants mainly produced monokaryotic hyphae and kar5 mutants mainly produced dikaryotic hyphae ( S9B Fig ) . After six weeks , wild type and prm1 mutants mainly produced monokaryotic hyphae , whereas , kar5 mutants produced both monokaryotic and dikaryotic hyphae ( S9C Fig ) . Live cell imaging of hyphal nuclear morphology suggests the following: 1 ) karyogamy may take place early in bisexual reproduction in C . deneoformans; 2 ) deletion of PRM1 leads to monokaryotic hyphae formation; and 3 ) deletion of KAR5 blocks early karyogamy in fused cells and could explain the observed post-fusion survival defect for the fused cells , which in turn promoted dikaryon hyphae formation . To confirm that karyogamy occurs early during C . deneoformans bisexual reproduction , we followed the hyphal nuclear dynamics between mating partners labeled with fluorescent markers ( nucleolar marker Nop1-GFP and nuclear marker H3-mCherry ) . We observed nuclear congression in fused a-α cells ( Fig 6A ) ; and a single nucleus labeled with both fluorescent protein markers was observed , confirming that karyogamy can occur immediately after cell fusion ( Fig 6B ) . We also observed both dikaryotic hyphae with fused clamp cells and monokaryotic hyphae with unfused clamp cells during the early mating process ( Fig 6C and 6D ) . These hyphae expressed both parental fluorescent markers , indicating that karyogamy can occur at different stages during C . deneoformans bisexual reproduction . To test whether Kar5 functions in karyogamy immediately after cell fusion and deletion of KAR5 leads to dikaryon formation , we quantified monokaryon and dikaryon fusion products and mature hyphae labeled with both nuclear fluorescent markers in wild type and kar5 mutant crosses ( Fig 6E and 6F ) . Among 125 wild type and 126 kar5 mutant cell fusion products , 60 . 8% wild type versus 22 . 2% kar5 mutant fused cells were monokaryotic ( Fig 6E ) . Among 133 wild type and 132 kar5 mutant mature hyphae , 68 . 4% wild type versus 36 . 4% kar5 mutant mature hyphae were monokaryotic ( Fig 6F ) . These results confirmed that deletion of KAR5 inhibited , but did not completely block karyogamy in early cell fusion products , and promoted dikaryon formation . In contrast to bisexual reproduction , deletion of PRM1 and KAR5 in C . deneoformans did not impact filamentation during solo unisexual reproduction ( Fig 7A ) , and caused less reduction in spore production relative to the wild type level ( 57 . 3% ± 7 . 2% and 52 . 8% ± 4 . 6% , respectively ) ( Fig 7A and S3 Fig ) . PRM1 and MFα expression were upregulated upon mating induction , but , KAR5 expression was maintained at a low level and was not affected by pheromone induction ( Fig 7B ) , suggesting KAR5 may play a less important role in solo unisexual reproduction . Similar to what is seen during bisexual reproduction in C . deneoformans , PRM1 expression was maintained at a significantly high level after mating for seven days compared to non-mating inducing conditions ( 6 . 2-fold increase , p <0 . 005 ) , whereas pheromone signaling subsided to basal level , indicating that PRM1 expression is not tightly coordinated with the pheromone signaling pathway in C . deneoformans ( Fig 7B ) . Although PRM1 expression was significantly upregulated , cell fusion occurred at a 1000-fold lower frequency during unisexual reproduction in C . deneoformans compared to both C . neoformans and C . deneoformans bisexual reproduction ( Fig 7C ) . Among cells that underwent cell-cell fusion during unisexual reproduction , deletion of PRM1 and KAR5 caused both bilateral and unilateral cell fusion defects ( Fig 7D ) , and deletion of KAR5 produced basidia with abnormal sporulation patterns ( Fig 7E ) , which were also observed during bisexual reproduction . These results suggest that during unisexual reproduction , a minority of cells undergo α-α cell fusion followed by karyogamy , similar to C . deneoformans bisexual reproduction . Although cell fusion is largely dispensable for solo unisexual reproduction , karyogamy may function independently of cell fusion between mother and daughter cells or inside basidium . Deletion of KAR7 has been indicated to block nuclear congression inside the basidium during unisexual reproduction [38] . To test whether KAR5 has similar functions , we stained wild type , kar5 mutant , and kar7 mutant basidia with DAPI . Interestingly , all strains produced basidia with one , two , or more than two nuclei , which may represent three different stages of meiosis inside basidia ( one nucleus as pre-meiosis , two nuclei as post meiosis I , and more than two nuclei as post meiosis II ) ( S10A Fig ) . Among 114 wild type , 116 kar5 mutant , and 115 kar7 mutant basidia , only 1 . 8% wild type , 4 . 3% kar5 mutant , and 1 . 7% kar7 mutant basidia contained two nuclei ( S10B Fig ) , which is different from the cnkar5 mutant with 48 . 9% basidia containing two pre-karyogamy nuclei during bisexual reproduction ( Fig 3E ) , suggesting that nuclear fusion occurs differently during unisexual reproduction of strain XL280α . If KAR5 and KAR7 were required for karyogamy in the basidia , we would have expected to see a higher population of basidia with 2 nuclei trapped at a pre-karyogamy stage compared to wild type . However , wild type and kar5 mutants exhibited similar basidia nuclear morphology with few two nuclei basidia ( S10B Fig ) , indicating that KAR5 is not required for a later stage of unisexual reproduction , and nuclear fusion is not occurring inside the basidium . The kar7 mutant produced 24 . 3% basidia versus 60 . 5% basidia in wild type with more than two nuclei ( S10B Fig ) , suggesting that KAR7 plays a role in meiosis during unisexual reproduction , supporting the previous observation that a diploid kar7/kar7 mutant has a defect in sporulation [38] . To validate these results , we examined basidia nuclear morphology based on nuclear fluorescent signals of wild type ( CF836 ) , kar5 mutant ( CF718 ) , and kar7 mutant ( CF1442 ) cells labeled with Nop1-GFP , and observed similar results ( S11 Fig ) , supporting the hypothesis that karyogamy occurs at a low frequency and karyogamy defects do not impact basidia nuclear morphology during solo unisexual reproduction . Given that cell fusion is dispensable in solo unisexual reproduction , and kar5 is not required for meiotic basidia formation , we aimed to confirm that meiosis was involved during spore production . We generated prm1 spo11 and kar5 spo11 double mutants and observed two short spore chains compared to the four long spore chains produced by prm1 and kar5 single mutants ( S12 Fig ) . The lack of normal spore chains confirms that spore production in unisexual reproduction is indeed dependent on the key meiotic gene SPO11 as shown previously [8] . It is unclear how diploidization occurs during solo unisexual reproduction . By following mating partners of the same mating type labeled with different fluorescent markers ( nucleolar marker Nop1-GFP and nuclear marker H3-mCherry ) , we showed that hyphae frequently originated from single cells rather than as of α-α cell fusion products ( S3 Movie ) , which further confirmed that cell fusion is dispensable for the solo yeast-hyphal morphological transition . To understand when and where diploidization takes place during solo unisexual reproduction , we dissected nascent blastospores from the growing hyphae ( Fig 8 ) and analyzed their ploidy by FACS ( Table 1 and S3 Table ) . In the wild type , 66 out of 71 blastospores dissected from eight budding sites germinated with a survival rate of 93% . FACS analysis of 16 blastospore derived colonies , including two from each budding site , showed that all were diploid ( Fig 8 ) . prm1 and kar5 mutants exhibited blastospore germination defects with survival rates of 19 . 2% and 62 . 1% respectively . prm1 spo11 and kar5 spo11 double mutants exhibited blastospore survival rates of 63 . 3% and 92 . 5% respectively . FACS analysis revealed all blastospores of the prm1 mutant , 12 blastospores from 6 budding sites ( four blastospores from two budding sites failed to germinate ) of the prm1 spo11 double mutant , and 14 blastospores from seven budding sites ( two blastospores from one budding site failed to germinate ) of the kar5 mutant were diploid . In analysis of 19 blastospores from 10 budding sites in the kar5 spo11 double mutant , 6 blastospores were haploid , and 13 were diploid ( Fig 8 ) . The six haploid blastospores were dissected from three budding sites , suggesting that blastospores originating from the same budding site may have the same ploidy composition . To infer whether the observed single nucleus in the kar7 mutant basidia might be a product of karyogamy ( S10 and S11 Figs ) , we dissected 248 blastospores from 46 budding sites for the kar7 mutant , and only 16 blastospores from 10 budding sites germinated with a survival rate of 6 . 45% , suggesting Kar7 is required for wild type blastospore survival ( Table 1 and S3 Table ) . Among 15 blastospores analyzed , 9 were diploid , 3 were haploid , and 3 were aneuploid ( Table 1 and S13 Fig ) , suggesting that the nuclei inside kar7 mutant basidia are likely largely diploid and that diploidization occurs earlier and outside of the basidium . The limited sample size of dissected blastospores presented here may explain why a few haploid blastospores were only recovered from the kar5 spo11 double mutant and kar7 mutant but not from wild type or the other mutant strains . That 74 out of a total of 86 ( 86% ) tested blastospores were diploid suggests that diploidization occurs early in the hyphae during unisexual reproduction , and this process may be dependent on an endoreplication pathway or early karyogamy events between mother and daughter cells or inside the growing hyphae . Prm1 and Kar5 were dispensable for diploidization , but may contribute to blastospore survival , implying that Prm1 and Kar5 could have additional cellular functions .
Without an obligate requirement for a mating partner , unisexual reproduction mitigates the two-fold cost of bisexual reproduction in finding an opposite mate . However , lacking genome diversity , clonal unisexual reproduction could be considered an evolutionary dead-end . In Cryptococcus , this assumption is challenged , as unisexual reproduction can generate genotypic and phenotypic diversity de novo by forming aneuploid progeny through meiosis [17] . Given that more than 99% of the natural isolates are α mating type , the presence of a unisexual cycle allows a clonal population to adapt to changing environments , which provides ecological significance to the Cryptococcus pathogenic species complex [46] . In this study , we demonstrated that a small population of cells undergo cell-cell fusion and nuclear fusion during unisexual reproduction , which enables recombination between cells of the same mating type . In response to selection pressures in the environment , the cell fusion dependent unisexual reproduction could facilitate selection of beneficial alleles in a large same sex population and reverse Muller’s ratchet [22] . Same sex cell-cell fusion can be further stimulated by the presence of small population of the opposite mating type [7] . Besides the similar ecological benefits conferred by unisexual and bisexual reproduction , many studies have shown that both modes of sexual cycles share a common signaling network that regulates the yeast-to-hyphal morphological transition and meiotic recombination [25 , 26 , 47] . Despite the similarities , there are key mechanistic differences between the two . In this study , we focused on two key cellular processes involved in sexual reproduction , cell-cell fusion and nuclear fusion , and studied their involvement in unisexual and bisexual reproduction in two sister Cryptococcus species harboring different sexual cycles . Cryptococcus orthologs of the S . cerevisiae cell fusion gene PRM1 perform conserved roles during Cryptococcus sexual reproduction . Prm1 facilitates cell fusion between a and α mating partner cells , cell fusion between α-α cells , and clamp cell-hyphal fusion during dikaryotic hyphal growth . During C . neoformans bisexual reproduction , deletion of PRM1 caused a bilateral ( prm1Δ X prm1Δ ) cell fusion defect , which is similar to what has been observed in S . cerevisiae and N . crassa [29 , 31] . However , during C . deneoformans bisexual reproduction , deletion of PRM1 caused both unilateral ( prm1Δ X WT ) and bilateral ( prm1Δ X prm1Δ ) cell fusion defects , suggesting that Prm1 plays a more significant role in C . deneoformans . Cell-cell fusion and clamp cell-hyphal fusion in Cryptococcus is analogous to cell fusion between conidial anastomosis tubes and hyphal fusion in filamentous fungi [48 , 49] . Like in S . cerevisiae , N . crassa , and S . pombe , deletion of PRM1 resulted in plasma membrane curvature at the membrane merger site ( Fig 4D ) , but these membranes were separated by a layer of cell wall ( Fig 4G and S6 Fig ) , similar to the prm1 mutant phenotype in S . pombe . Although deletion of PRM1 caused a cell fusion defect , it did not completely block cell fusion in Cryptococcus , suggesting that Prm1 is not the sole membrane fusion protein . Additional candidate cell fusion genes have been identified in S . cerevisiae and N . crassa , including FIG1 , LFD1 , and LFD2; but BLASTP searches failed to identify homologs of these genes in Cryptococcus [31 , 32] . Prm1 may be the evolutionary conserved core component for cell fusion in the fungal kingdom , and species-specific plasma membrane fusion machinery may have evolved independently . Similarly , the Cryptococcus karyogamy machinery has been previously shown to function differently than that of S . cerevisiae [38] . Deletion of KAR5 did not completely block either unisexual or bisexual reproduction , suggesting that additional karyogamy genes may have redundant functions with KAR5 . The nuclear morphology inside cnkar5 mutant basidia and cdkar5 mutant early fusion products is similar to the kar5 mutant karyogamy defect phenotype in S . cerevisiae , indicating KAR5 plays a conserved role in nuclear fusion between Saccharomyces and Cryptococcus [41] . During C . neoformans bisexual reproduction , deletion of KAR5 blocked nuclear fusion inside basidia , whereas , during C . deneoformans bisexual reproduction , deletion of KAR5 blocked nuclear fusion at an early developmental step and caused growth arrest for the cell fusion products leading to an apparent cell fusion defect . Early karyogamy in C . deneoformans wild type relieved the requirement for pheromone signaling for directing clamp cell-hyphal fusion during dikaryotic hyphal growth , and the pheromone expression level was rapidly reduced to a basal level in the wild type . However , deletion of KAR5 promoted dikaryotic hyphal growth , and as a consequence the pheromone signaling pathway in kar5 mutants was significantly upregulated compared to the wild type . The pheromone expression patterns validated KAR5’s function in karyogamy . During C . neoformans and C . deneoformans bisexual reproduction , the involvement of KAR5 in nuclear fusion revealed that karyogamy machinery takes place at different sexual development stages between these two closely related sister species . As reported by Ning and colleagues , the Kar5 protein belongs to a divergent nuclear fusion protein family [43] . Neither CnKar5 nor CdKar5 share sequence similarities outside of the conserved CRD domain with Kar5 proteins from other ascomycetous fungi . Interestingly , the CnKar5 and CdKar5 protein sequences share 85% identity , compared to the average of 93% identity for the 5569 orthologs shared by these two sister species [50] . This suggests that the KAR5 gene has undergone more rapid divergent evolution . The divergence of these proteins may contribute to the mechanistic differences in the karyogamy machinery and may represent a barrier for inter-species nuclear fusion ( Fig 9 ) . Several diploid or aneuploid environmental and clinical hybrid isolates of the two Cryptococcus species have been reported , but the few that produce spores have a <10% germination rate [51] . Incompatibility in components of the karyogamy machinery may help to generate a physical barrier for mating and drive speciation events within the Cryptococcus species complex . Although we validated the conserved roles for PRM1 and KAR5 , neither is the sole fusion protein for plasma membrane fusion or nuclear membrane fusion; and deletion of these two factors caused different impacts on bisexual cycles in Cryptococcus ( Fig 9 ) . In C . neoformans , Prm1 participates in cell-cell fusion during the initial mating process and mediates clamp cell-hyphal fusion , which is required for maintaining dikaryotic hyphal growth , and Kar5 functions in karyogamy inside the basidia during bisexual reproduction . whereas , in C . deneoformans , Prm1 plays a more significant role in cell-cell fusion , and Kar5 can function in karyogamy immediately following cell fusion , which produces monokaryotic diploid hyphae ( Fig 9 ) . However , the observed monokaryotic hyphae could be derived from unisexual reproduction , as pheromone produced by cells of the opposite mating type can promote unisexual reproduction [7] . To address this , we used GFP- and mCherry-labeled nuclear markers to show that the nuclei inside of the monokaryotic hyphae are indeed karyogamy products labeled with both fluorescent markers and thus the products of bisexual reproduction ( Fig 6 ) . Collectively , these results demonstrated that there are major differences in both the cell fusion machinery and the karyogamy program during bisexual reproduction between these two closely related sister species ( Fig 9 ) . In contrast to bisexual reproduction , deletion of PRM1 did not cause a significant phenotypic defect during solo unisexual reproduction in C . deneoformans . Although PRM1 was highly upregulated during the unisexual cycle , α-α cell fusion occurred at a 1000-fold lower frequency compared to a-α cell fusion . Furthermore , live cell imaging of yeast cell germination during unisexual reproduction provided compelling evidence that the yeast-hyphal morphological transition is largely independent of cell-cell fusion . It is likely PRM1 may be a fortuitous transcriptional target during unisexual reproduction . However , it is worth noting that those cells that undergo cell-cell fusion do complete the unisexual cycle follow a pathway similar to the bisexual mating mechanism in C . deneoformans , and both PRM1 and KAR5 mediate cell-cell and nuclear fusion during modes of unisexual reproduction that results from α-α cell fusion as detected with genetically marked strains . In bisexual reproduction , pheromone expression is dampened by the formation of the transcription factor complex Sxi1α-Sxi2a after a-α cell fusion [52] . Interestingly , pheromone expression was also dampened quickly during unisexual reproduction , but the transcriptional downregulation trigger must differ from bisexual reproduction because the opposite mating type was absent . During bisexual reproduction in both C . neoformans and C . deneoformans , KAR5 expression was upregulated and dampened by PRM1 deletion . KAR5 expression was maintained at a basal level and was not affected by the deletion of PRM1 during unisexual reproduction . Furthermore , deletion of KAR5 did not change basidia nuclear morphology compared to wild type , demonstrating that KAR5 is not required for unisexual reproduction . The fact that wild type , the kar5 mutant , and the kar7 mutant produced very few basidia with the two nuclei , indicating either that karyogamy does not occur inside the basidia during unisexual reproduction or that karyogamy occurs transiently and it is hard to capture by DAPI staining or nucleolar fluorescent marker Nop1-GFP . Interestingly , FACS analyses showed that the majority of blastospores produced along the hyphae from unisexual reproduction were diploid , supporting the hypothesis that nuclear fusion does not occur inside the basidium . Despite the fact that deletion of KAR5 does not impact unisexual reproduction and nuclear fusion does not occur inside basidium , we can not entirely rule out that karyogamy could occur during unisexual reproduction , as deletion of KAR5 did not completely block karyogamy during bisexual reproduction , and karyogamy genes in Cryptococcus share redundant functions [38] . Karyogamy occurs early during C . deneoformans bisexual reproduction , and it could also occur early in mother and daughter cells or growing hyphae , which leads to ploidy duplication . However , we favor the interpretation that karyogamy is dispensable for solo unisexual reproduction and an endoreplication pathway , which has been implicated in the formation of polyploid titan cells during Cryptococcus animal infection , contributes to ploidy duplication [53 , 54] ( Fig 9 ) , which must be differentially controlled compared to titan cell formation , as titan cells reach a much higher ploidy [53] . With the ability to undergo both unisexual and bisexual reproduction , Cryptococcus serves as a model system to study the mating mechanisms for different sexual cycles . Our findings reveal the evolutionary differences in bisexual reproduction within the Cryptococcus species complex and suggest that the unisexual mating mechanism is plastic and complex , providing mechanistic insights to studies of mating mechanisms of unisexual reproduction and parthenogenesis in other eukaryotic systems .
Strains and plasmids used in this study are listed in S1 Table . All strains used to study bisexual reproduction in C . neoformans were generated in the congenic MATα H99 and MATa KN99 strain backgrounds [33] . All strains used to study bisexual reproduction in C . deneoformans were generated in the congenic MATα JEC21 and MATa JEC20 strain backgrounds [55] . All strains used to study unisexual reproduction in C . deneoformans were generated in the MATα XL280 strain background [7] . Yeast cells were grown at 30°C on Yeast extract Peptone Dextrose ( YPD ) medium . Strains harboring dominant selectable markers were grown on YPD medium supplemented with nourseothricin ( NAT ) or G418 ( NEO ) . Mating assays were performed on either 5% V8 juice agar medium ( pH = 5 . 0 for C . neoformans and pH = 7 . 0 for C . deneoformans ) or Murashige and Skoog ( MS ) medium minus sucrose ( Sigma-Aldrich ) in the dark at room temperature for the designated time period . To identify the PRM1 orthologs in C . neoformans and C . deneoformans , BLASTP searches using the S . cerevisiae , S . pombe , C . albicans , N . crassa , and A . fumigatus Prm1 protein sequences were conducted against C . neoformans H99 and C . deneoformans JEC21 genomes on FungiDB ( www . fungidb . org ) [56] . This approach identified CNAG_05866 in C . neoformans and CNF01070 for C . deneoformans as candidate PRM1 genes . Reciprocal BLAST searches confirmed that these two genes are PRM1 orthologs in Cryptococcus spp . Phobius prediction suggested that both CdPrm1 and CnPrm1 have four transmembrane domains at the same amino acid positions ( 67–87 , 352–371 , 433–455 , and 647–688 ) [44] . To identify the KAR5 othologs in C . neoformans and C . deneoformans , a BLASTP search using the P . graminis Kar5 protein sequence against the C . neoformans H99 genome identified CNAG_04850 as a candidate KAR5 gene for C . neoformans . However , the same BLASTP search failed to identify a candidate KAR5 gene for C . deneoformans . A subsequent BLASTP search using the C . neoformans KAR5 gene sequence against the C . deneoformans JEC21 genome identified a region from bp 790071 to 792560 on chromosome 10 encoding a protein that shares 85% identity with the C . neoformans candidate Kar5 protein sequence . Multiple sequence alignment of candidate Cryptococcus Kar5 protein sequences with predicted Kar5 protein sequences from other fungal species using the MUSCLE program confirmed they contain Cysteine Rich Domain ( CRD ) [43 , 57] . Phylogenetic analyses for Prm1 and Kar5 were tested with 1000 bootstrap replicas by using the maximum likelihood method in MEGA7 [58 , 59] . Phobius prediction predicted that both CdKar5 and CnKar5 have an N-terminal signal peptide and a C-terminal transmembrane domain at amino acid positions 1–16 and 476–501 for CdKar5 , and 1–21 and 477–502 for CnKar5 [44] . The COILS/PCOILS program predicted that CdKar5 has four coiled-coil domains at amino acid positions 179–199 , 216–236 , 318–339 , and 368–389 , and that CnKar5 has two coiled-coil domains at amino acid positions 180–200 and 370–390 [45] . S1 Table and S2 Table lists the plasmids and primers , respectively , used in this study . To generate deletion mutants for genes of interest , deletion constructs consisting of the 5’ and 3’ regions of the targeted genes flanking an appropriate selection marker ( NAT or NEO cassette ) were generated by overlap PCR as previously described [60] . The deletion constructs were introduced into the respective strains via biolistic transformation as previously described [61] . Stable transformants were selected on YPD medium supplemented with NAT ( 100 mg/L ) or G418 ( 200 mg/L ) . Gene replacements by homologous recombination were confirmed by PCR and Southern hybridization . To generate C . deneoformans wild type strains with dominant selectable markers for cell fusion assays , an analogous method was used to insert a dominant selectable marker ( NAT cassette ) into the intergenic region immediately downstream of the URA5 gene ( CNG03730 ) and a dominant selectable marker ( NEO cassette ) into the intergenic region between CNE02520 and CNE02530 , which is downstream of the ADE2 gene ( CNE02500 ) . To visualize the cytosol in Cryptococcus , a plasmid encoding the cytosolic mCherry gene and containing a dominant selectable marker ( NEO cassette ) was generated . The mCherry coding sequence was amplified from pLKB25 [62] and inserted into pXL1 after the GPD1 promoter using the Gibson assembly method , which assembles multiple DNA fragments with 20 to 40 bp overlap sequences in a single reaction containing exonuclease , DNA polymerase , and ligase [63] , resulting in pCF1 . To monitor nuclear morphology and dynamics during Cryptococcus sexual reproduction , plasmid pSL04 encoding a GFP-tagged nucleolar protein Nop1 from a previous study [38] and a plasmid encoding an mCherry-tagged histone H3 were used . To express the H3-mCherry chimera , the 1075-bp 5’UTR and the 683-bp 3’UTR of the H3 gene were used as promoter ( P ) and terminator ( T ) , respectively . The H3 promoter and coding sequences before the stop codon and the H3 terminator sequence were amplified from JEC21α genomic DNA , and the mCherry coding sequence was inserted between the H3 coding sequence and H3 terminator by overlap PCR . The chimera expression cassette H3P-H3-mCherry-H3T was then inserted into pAI3 using the Gibson assembly method [63] , resulting in pCF9 . C . deneoformans strains were biolistically transformed with the pCF1 , pSL04 , and pCF9 plasmids , and the fluorescent protein expression cassettes were randomly inserted into the genomes . Stable transformants were screened based on fluorescent signals and the selectable markers . In C . neoformans bisexual reproduction , YSB119 ( H99α aca1Δ::NAT ura5 ACA1-URA5 ) and YSB121 ( KN99a aca1Δ::NEO ura5 ACA1-URA5 ) were used as genetically marked wild type strains to study the fusion competency of prm1 ( CF56 and CF562 ) and kar5 ( CF57 and CF549 ) mutants . In C . deneoformans bisexual reproduction , CF757 ( JEC20a URA5-NAT ) and CF762 ( JEC21α ADE2-NEO ) were used as wild type strains to study the fusion competency of prm1 ( CF1 and CF313 ) and kar5 ( CF487 and CF364 ) mutants . InC . deneoformans unisexual reproduction , CF750 ( XL280α URA5-NAT ) and CF752 ( XL280α ADE2-NEO ) were used as wild type strains to study the fusion competency of prm1 ( CF317 and CF659 ) and kar5 ( CF150 and CF260 ) mutants . Strains for each fusion pair were grown overnight in YPD liquid medium at 30°C . Cells were washed twice with ddH2O and diluted to a final density of OD600 = 2 . Then , 50 μl of equal-volume mixed cells were spotted on V8 medium and incubated for 48 hours ( for bisexual reproduction ) or 72 hours ( for unisexual reproduction ) in the dark at room temperature . The cells were then removed , washed with ddH2O , and plated in serial dilution on both YPD medium and YPD medium supplemented with both NAT and G418 . The cells were incubated for five days at room temperature . Cell-cell fusion frequency was measured by counting the average number of double drug resistant cfu/total cfu . To quantify the cell-cell fusion frequency during C . deneoformans bisexual reproduction based on fluorescent signal mixing , CF830 ( JEC21α NOP1-GFP-NAT ) was mated with JEC20a for wild type fusion frequency , CF768 ( JEC20a prm1Δ::NEO NOP1-GFP-NAT ) was mated with either JEC21α for prm1 mutant unilateral cell fusion frequency or with CF1 ( JEC21α prm1Δ::NEO ) for prm1 mutant bilateral cell fusion frequency , and CF723 ( JEC20a kar5Δ::NEO NOP1-GFP-NAT ) was mated with CF487 ( JEC21α kar5Δ::NEO ) for kar5 mutant bilateral cell fusion frequency . Cells were prepared as described above and collected for direct fluorescence microscopic observation after 24 hours of incubation . Approximately 100 fusion events were recorded for each mating and were identified by the presence of conjugation tubes connecting the fusion pairs . Fusion frequency was determined by the number of fusion pairs with Nop1-GFP labeled nuclei in both cellular compartments/total fusion events . To determine whether prm1 and kar5 mutants were defective in spore production , spores were isolated by Percoll gradient centrifugation as previously described [64] . For C . neoformans bisexual reproduction , CF56 ( H99α prm1Δ::NAT ) crossed with CF562 ( KN99a prm1Δ::NEO ) and CF57 ( H99α kar5Δ::NAT ) crossed with CF549 ( KN99a kar5Δ::NEO ) were compared to the wild type cross between H99α and KN99a . For C . deneoformans bisexual reproduction , CF1 ( JEC21α prm1Δ::NEO ) crossed with CF313 ( JEC20a prm1Δ::NAT ) and CF487 ( JEC21α kar5Δ::NEO ) crossed with CF364 ( JEC20a kar5Δ::NAT ) were compared to wild type cross between JEC21α and JEC20a . For C . deneoformans unisexual mating , CF317 ( XL280α prm1Δ::NEO ) and CF260 ( XL280α kar5Δ::NEO ) were compared to the wild type XL280α . For each mating , triplicates were performed for statistical analysis . Strains were grown overnight in YPD liquid medium . Cells were washed twice with ddH2O and diluted to a final cell density of OD600 = 0 . 5 . Then , 10 μl of equal-volume mixed cells were spotted on V8 medium and incubated for seven days in the dark at room temperature . The entire mating patch was suspended in 60% Percoll ( GE Health ) in PBS with 0 . 1% Triton X100 . After centrifugation at 10 , 000 X g for 30 mins in an SW41Ti ultracentrifuge rotor ( Beckman-Coulter ) , a band of spores near the bottom of the Percoll gradient was recovered with a 1-ml tuberculin syringe and transferred into an Eppendorf tube . The total spore production was determined by multiplying the spore density , measured by hemocytometer , with the final volume . Wild type matings between CF757 ( JEC20a URA5-NAT ) and CF762 ( JEC21α ADE2-NEO ) were conducted as controls . The isolated cells were serially diluted and plated on YPD medium and allowed to recover for five days at 30°C . A total of 47 colonies were randomly chosen and grown on YPD medium supplemented with either NAT or G418 to assess growth phenotypes ( S2 Fig ) . Mating type specific primer pairs were used to determine the MAT locus for the progeny . For all three modes of sexual reproduction studied , prm1 and kar5 mutant strains and wild type strains were grown overnight in YPD liquid medium . Cells were washed twice with ddH2O and diluted to OD600 = 2 . Then 250 Δl of an equal-volume mixture of cells were spotted on V8 medium or YPD medium and incubated for 36 hours ( YPD and V8 ) or one week ( V8 ) , as the pheromone pathway has been shown to be upregulated upon mating induction on V8 medium and the expression levels are maintained at relatively high levels between 24 and 48 hours [8] . Mating patches were harvested and flash frozen in liquid nitrogen . RNA was extracted using TRIzol reagent ( Thermo ) following the manufacturer’s instructions . RNA was treated with Turbo DNAse ( Ambion ) , and single-stranded cDNA was synthesized by AffinityScript RT-RNAse ( Stratagene ) . For each sample , cDNA synthesized without the RT/RNAse block enzyme mixture was used as a “no RT control” to control for genomic DNA contamination . The relative expression level of target genes was measured by quantitative real-time PCR using Brilliant III ultra-fast SYBR green QPCR mix ( Stratagene ) in an Applied Biosystems 7500 Real-Time PCR System . For each target , a “no template control” was performed to analyze melting curves to exclude primer artifacts . Technical triplicates and biological triplicates were performed for each sample . Gene expression levels were normalized using the endogenous reference gene GPD1 and determined by using the comparative ΔΔCt method . The primers used for RT-PCR are listed in S2 Table . The Student’s t-test was used to determine if the relative gene expression levels between different strains exhibited statistically significant differences ( P <0 . 05 ) . To visualize the nuclei during sexual reproduction , cells were stained with DAPI as previously described [62] . In brief , a 1-mm3 MS agar block containing hyphae on the edge of mating patches was excised and transferred to a small petri dish . The agar block was fixed in 3 . 7% formaldehyde and permeabilized in 1% Triton X100 . The agar block was stained with 2 Δg/ml DAPI ( Sigma ) and transferred to a glass slide and covered with a cover slip for fluorescent microscopic observation . To visualize the plasma membrane of the conjugation tubes during C . deneoformans prm1 mutant bisexual reproduction , strain CF1 ( JEC21α prm1Δ::NEO ) was crossed with CF768 ( JEC20a prm1Δ::NEO NOP1-GFP-NAT ) . After incubation on V8 medium for 24 hours , cells were harvested and resuspended in cold YPD liquid medium on ice . FM4-64 ( Thermo ) was added at a final concentration of 10 μM and the cells were stained on ice for 15 mins . The cells were then washed with cold YPD medium and fixed in 3 . 7% formaldehyde in PBS for 10 mins . After a final wash with PBS , the stained cells were examined immediately by confocal microscopy . Hyphal growth on the edge of mating patches , basidia , and spore chains were captured using a Nikon Eclipse E400 microscope equipped with a Nikon DXM1200F camera . For fluorescence imaging of hyphae , an agar block supporting hyphal growth was excised and transferred onto a glass slide and covered with a coverslip . For fluorescence imaging of short early hyphae and fusion pairs , early mating patches were harvested and suspended in ddH2O and cells were placed on a glass slide containing a 2% agar patch and covered with a coverslip . Fluorescent images were obtained using a Deltavision system ( Olympus IX-71 base ) equipped with a Coolsnap HQ2 high resolution SSD camera . Images were processed using the software FIJI . Confocal fluorescent images were captured by confocal laser scanning microscopy using a Zeiss LSM 710 Confocal Microscope at the Duke Light Microscopy Core Facility . Plan-Apochromat 63X/1 . 40 Oil DIC M27 objective lenses were used for imaging , and a smart setup was used for image acquisition configuration . Confocal fluorescent images and movies were processed using the ZEN software . SEM and TEM were performed at the North Carolina State University Center for Electron Microscopy , Raleigh , NC , USA . Samples were prepared for SEM as previously described [8] . In brief , 1-mm3 MS agar blocks containing hyphae on the edge of mating patches were excised and fixed in 0 . 1 M sodium cacodylate buffer , pH = 6 . 8 , containing 3% glutaraldehyde at 4°C for several weeks . Before viewing , the agar block was rinsed with cold 0 . 1 M sodium cacodylate buffer , pH = 6 . 8 three times and post-fixed in 2% osmium tetroxide in cold 0 . 1 M cacodylate buffer , pH = 6 . 8 for 2 . 5 hours at 4°C . Then the block was critical-point dried with liquid CO2 and sputter coated with 50 Å of gold/palladium using a Hummer 6 . 2 sputter coater ( Anatech ) . The samples were viewed at 15KV with a JSM 5900LV scanning electron microscope ( JEOL ) and captured with a Digital Scan Generator ( JEOL ) image acquisition system . For TEM , conjugation tubes were prepared by crossing strain CF712 ( JEC21α prm1Δ::NAT mCherry-NEO ) with CF768 ( JEC20a prm1Δ::NEO NOP1-GFP-NAT ) . After incubation on V8 medium for 24 hours , cells were harvested and analyzed with a B-C Astrios Sorter to enrich fusion pairs that were positive for both GFP and mCherry fluorescence at the Duke Cancer Institute Flow Cytometry Shared Resource . Hyphae were prepared by crossing strain CF56 ( H99α prm1Δ::NAT ) with CF562 ( KN99a prm1Δ::NEO ) . After incubation on V8 medium for four weeks , hyphae on the edge of the mating patches were harvested for observation of clamp cell morphology . Upon harvest , cells or hyphae were immediately fixed in 3% glutaraldehyde in 0 . 1 M sodium cacodylate buffer , pH = 6 . 8 , at 4°C for several weeks . The sample preparation was performed as previously described [62] . In brief , cells were post-fixed with 4% KMnO4 and pre-embedded in 2% agarose . After dehydration with an increasing gradient of ethanol solutions and filtration with Spurr’s resin , the agarose block was embedded in 100% Spurr’s in BEEF capsules . Thin sections were cut and collected on 200-mesh grids , followed by staining with 4% aqueous uranyl acetate and Reynold’s lead citrate . Grids were viewed using a Philips 400T transmission electron microscope . TEM images were processed with Photoshop ( Adobe ) . Ploidy of blastospores was determined by Fluorescence Activated Cell Sorting ( FACS ) analysis as previously described [65] . XL280α and MN142 . 6 ( XL280α/α ura5Δ::NAT/ura5Δ::NEO ) were used as haploid and diploid controls respectively . Dissected blastospores were grown on YPD medium between three and five days at 30°C to yield colonies . Cells were harvested and washed with PBS buffer . After fixation in 70% ethanol at 4°C overnight , cells were washed once with 1 ml of NS buffer ( 10 mM Tris-HCl , pH = 7 . 2 , 250 mM sucrose , 1 mM EDTA , pH = 8 . 0 , 1 mM MgCl2 , 0 . 1 mM CaCl2 , 0 . 1 mM ZnCl2 , 0 . 4 mM phenylmethylsulfonyl fluoride , and 7 mM β-mercaptoethanol ) , and stained in 180 μl NS buffer with 20 μl 10 mg/ml RNase and 5 μl 0 . 5 mg/ml propidium iodide at 4°C overnight . Then , 50 μl stained cells were diluted in 2 ml of 50 mM Tris-HCl , pH = 8 . 0 and sonicated for 1 min . For each sample , 10 , 000 cells were analyzed on the FL1 channel on the Becton-Dickinson FACScan at Duke Cancer Institute Flow Cytometry Shared Resource . Data analysis was performed using the software FlowJo . | Sexuality is ubiquitous in eukaryotic systems , but it is present in diverse forms , ranging from distinct sexual individuals to parthenogenic organisms in both animals and plants . Consequently , different organisms have evolved different reproduction strategies in which cell-cell fusion and nuclear fusion ( karyogamy ) play fundamental roles . The opportunistic human fungal pathogen Cryptococcus neoformans can undergo both bisexual reproduction between a and α cells and selfing unisexual reproduction , which offsets the cost of finding a mating partner , coinciding with the observation that 99% of clinical and environmental isolates are mating type α . It has been a central interest to elucidate the similarities and differences between these two sexual cycles . Here , we identified and characterized two genes in the Cryptococcus species complex , PRM1 and KAR5 , which play conserved roles in plasma membrane fusion and karyogamy in fungi . We showed that unisexual reproduction is largely independent from cell-cell fusion and is mechanistically different from bisexual reproduction . We also demonstrated that karyogamy takes place at different stages during bisexual reproduction between two sister species , exemplifying distinct evolutionary trajectories within the pathogenic species complex . | [
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"experiment... | 2017 | PRM1 and KAR5 function in cell-cell fusion and karyogamy to drive distinct bisexual and unisexual cycles in the Cryptococcus pathogenic species complex |
Central corneal thickness ( CCT ) , one of the most highly heritable human traits ( h2 typically>0 . 9 ) , is important for the diagnosis of glaucoma and a potential risk factor for glaucoma susceptibility . We conducted genome-wide association studies in five cohorts from Australia and the United Kingdom ( total N = 5058 ) . Three cohorts were based on individually genotyped twin collections , with the remaining two cohorts genotyped on pooled samples from singletons with extreme trait values . The pooled sample findings were validated by individual genotyping the pooled samples together with additional samples also within extreme quantiles . We describe methods for efficient combined analysis of the results from these different study designs . We have identified and replicated quantitative trait loci on chromosomes 13 and 16 for association with CCT . The locus on chromosome 13 ( nearest gene FOXO1 ) had an overall meta-analysis p-value for all the individually genotyped samples of 4 . 6×10−10 . The locus on chromosome 16 was associated with CCT with p = 8 . 95×10−11 . The nearest gene to the associated chromosome 16 SNPs was ZNF469 , a locus recently implicated in Brittle Cornea Syndrome ( BCS ) , a very rare disorder characterized by abnormal thin corneas . Our findings suggest that in addition to rare variants in ZNF469 underlying CCT variation in BCS patients , more common variants near this gene may contribute to CCT variation in the general population .
Glaucoma is one of the leading causes of irreversible blindness worldwide . It is estimated that by 2010 , approximately 60 . 5 million people globally will be affected by this condition [1] . It is characterized by a progressive loss of retinal ganglion cells which will lead to visual field damage . The most common form is open-angle glaucoma ( OAG ) , an adult-onset condition that generally affects people over the age of 40 . Whilst several well-established risk factors including high intra-ocular pressure , ethnicity , increasing age and positive family history have been identified for OAG , recent evidence indicates that a decreased CCT is also a major risk factor . Numerous studies have shown that people with a thin cornea have a substantially increased risk of developing OAG and its associated visual loss [2]–[4] . It is conceivable from these data that there may be common genes in the pathways of both CCT and OAG [5] . Therefore , CCT is considered a useful quantitative trait for further dissecting the genetic aetiology of OAG . CCT is also an important measure in determining a person's suitability for laser refractive surgery to correct myopia and it may be abnormal in a range of corneal diseases such as corneal dystrophies , keratoconus and herpes simplex keratitis . CCT is one of the most heritable human traits; the estimated heritability from existing studies is up to 0 . 95 [5] . Despite the strong evidence for a genetic background , the genetic architecture of corneal thickness remains unknown . Some candidate gene analyses have been conducted to assess the contribution of particular genes to this trait . For example , the candidates COL1A1 and COL1A2 encoding type I alpha collagens were determined based on the extreme CCT values observed in the connective tissue disorder osteogenesis imperfecta ( OI ) [6] , [7] as explored by Dimasi et al [8] . Other possible candidates are the type V collagen genes COL5A1and COL5A2 involved in Ehlers-Danlos syndrome ( EDS ) [9] , fibrillin-1 gene ( FBN1 ) responsible for Marfan syndrome [10] , PAX6 associated with aniridia [11] and FOXC1 associated with abnormal ocular development [12] . Candidate gene analyses for normal CCT variation have been focused on the already known associations of disease genes with abnormal CCT; Genome–wide association ( GWA ) studies , on the other hand , can identify new genetic relationships without bias to known biology or disease associations of annotated well studied genes . We carried out a multi-stage study on a panel of over 5 , 000 individuals in order to detect the genetic variation for CCT . In the first stage , we conducted GWA studies on the two twin cohorts from Australia and the UK separately . The first stage meta-analysis on the twin cohorts uncovered several promising chromosomal regions associated with CCT . We conducted another set of GWA studies on two population-based cohorts utilizing sample pooling techniques prior to genotyping ( pool genotyping design ) and developed a new analytical technique that allows comparison of the results from the different study designs . The findings were further validated by individually genotyping an extended cohort ( pooled samples plus additional samples with extreme CCT values ) . Sample size of each study population and schematic of the study design can be found in Table S1 and Figure S1 respectively .
CCT values in both twin cohorts are normally distributed with a mean of 544 . 3µm ( ±35 . 0µm ) in the combined Australian ( AU ) twin cohort , and a mean of 545 . 8µm ( ±34 . 0 µm ) in the UK twin cohort ( Table 1 ) . We report the results for standardized trait values – for effect sizes on the original scale , simply multiply by the trait standard deviation . We found weak association signals with the smallest p-values on the scales of 10−6 from the combined AU twin cohort alone , as was expected from the Q-Q plot ( Figure S2 ) . Except for one SNP suggesting a strong association signal ( p-value of 2 . 9×10−08 ) , the UK cohort was found mainly with weak associations ( Figure S3 ) . This may be due to the relatively small sample size of a single dataset , so we performed a first-stage meta-analysis on both twin cohorts as the Discovery sample . A common set of 524 , 813 SNPs was left after merging the datasets , among which 0 . 4% SNPs were further excluded because of ambiguous ( A/T , C/G ) polymorphism types at these loci . Furthermore , the effects and allele frequencies estimated from the UK samples were altered to have the same reference alleles as in the combined AU twin samples . The association signals were clearly enhanced in the meta-analysis . The meta-analysis results can be visualized by a Manhattan plot in Figure S4 , and the top 5 SNPs with p-values from the association tests lower or around 1×10−7 are listed in Table 2 . The results from meta-analysis of the twin cohorts revealed the most significant association around 86 . 86 Mb ( build 36 . 3 ) on chromosome 16 . The genotyped SNP rs12447690 had a strong genome-wide significant p-value of 1 . 67×10−09 , with the stronger signal from the UK samples ( Table 2 ) . The fourth SNP in Table 2 , rs9938149 is the top SNP in the imputation set ( Figure 1 ) . rs9938149 is 33 . 5 kb away from rs12447690 , and they are in high linkage disequilibrium ( LD ) with r2 of 0 . 748 . A few other imputed SNPs within 20 kb of the top SNP show strong association signals because of high LD in this region . The nearest gene is ZNF469 on chromosome 16q24 , 108 kb away from the top imputed SNPs . It is a small gene with a span of 42 kb ( 86 , 997K . 87 , 039K , build 36 . 3 ) . As shown in Figure 1 , there is evidence for recombination between the associated SNPs and the putative gene ZNF469 . This gene encodes a zinc-finger protein . Rare mutations in this gene cause Brittle Cornea Syndrome ( BCS ) , a recessive disorder characterized by a thin cornea leading to progressive visual loss and blindness [13] . Another associated SNP in Table 2 , rs2755237 ( p = 1 . 57×10−07 ) is 20 kb from the 3′ end of the gene FOXO1 on chromosome 13q14 . 1 . It remained as the strongest signal in the imputation set ( Figure 2 ) . Two other SNPs approximately 1 kb away , rs2721051 and rs2755238 , were masked by the top SNP in the plot . They are in high LD with rs2755237 ( r2 of 0 . 736 ) . The gene FOXO1 belongs to the forkhead family of transcription factors , the same family as the candidate gene FOXC1 ( 6q25 ) that was previously associated with early onset glaucoma ( see Introduction ) . The two remaining SNPs in Table 2 were found in the same region around 126 , 300K to126 , 400 K on chromosome 10 . The SNPs rs1006368 and rs11245330 within the gene FAM53B ( 10q26 . 13 ) , are 35kb apart and in complete LD ( r2 of 1 ) . They had the same meta-analysis p-value from the twin cohorts of 4 . 94×10−08 . An imputed SNP rs4962399 also in this gene improved the p-value to 2 . 8×10−09 ( Figure S5 ) . Several other SNPs with a similar level of significance spread over this region also because of high LD . FAM53B was reported as related to the hypothetical protein LOC9679 in Reference Sequence database ( RefSeq , NCBI ) . As demonstrated above , evidence for association with CCT at loci on chromosomes 16 , 13 and 10 , was found in the Discovery sample of the meta-analyzed twin cohorts . As the replication , we conducted another GWA study on the population-based cohorts using pool genotyping design and validated the findings by individually genotyping the extended cohort ( pooled samples plus extra samples with extreme phenotypes ) . Descriptive statistics of the two population-based cohorts are provided in Table 3 . With the advantage of time and cost efficiency , pool genotyping design provided an expedient examination of the top variants from the results in the twin cohorts . We compared the allelic effect estimated from each cohort as shown in Figure 3 . In order to reveal the association signals more clearly , we also performed a meta-analysis based on the two sets of GWA results from the twin samples and the population-based samples ( results shown in Table S2 , Manhattan plot in Figure S6 ) . The most significant SNP rs12447690 from the twin cohorts had smaller effect sizes estimated from the pooled samples ( Figure 3 ) . Similar results were found in the other SNP rs9938149 in the ZNF469 region ( 33 . 5kb away from the most associated SNP rs12447690 ) . Although there was an overall genome-wide significant p-value for rs12447690 in the meta-analysis with twin cohorts ( Table S2 ) , the results from pooled samples alone did not show a clear replication for the SNPs near ZNF469 . However , when we added the additional samples to the pooled samples , the individual genotyping results did show evidence for replication ( p = 0 . 014 ) in the extended cohort ( pooled+extra samples ) . The meta-analysis based on all the individually genotyped samples yielded an overall p-value of 8 . 95×10−11 for the SNP rs12447690 . The final results summarizing the findings from all the individually genotyped samples are presented in Table 4 . In both DNA and blood pooled samples , SNP rs2755237 near FOXO1 showed estimated allelic effects similar to the results from the twin cohorts ( Figure 3 ) . The other SNP rs2721051 in high LD with rs2755237 had a similar result ( Table S2 ) . This demonstrated a clear replication of these two variants from the pooled samples . The individual genotyped results on the extended cohort displayed the same pattern and obtained significances for both SNPs ( Table 4 ) . Due to the smaller pool sizes , the estimated allelic effects from the pooled samples have relatively larger standard errors and hence neither pool considered separately showed a significant ( P<0 . 05 ) association ( Table S2 ) . In the overall meta-analysis , rs2721051 and rs2755237 obtained p-values of 4 . 6×10−10 and 7 . 02×10−09 respectively ( Table 4 ) . The SNPs from the chromosome 10 region associated with CCT in the discovery sample had similar estimated effects in the first ( DNA ) pool . However effects in the opposite direction ( e . g . negative effect for the same reference allele compared to positive effects in other samples ) were observed in the second ( blood ) pool sample , indicating a possible false positive association with CCT ( Figure 3 ) . Another interesting result arising from the meta-analysis of twin cohorts and the pooled samples is the SNP rs7044529 , which is within the gene COL5A1 ( 9q34 . 2–q34 . 3 ) . As outlined in the introduction , the type V collagen gene COL5A1 is a strong candidate for CCT , given the phenotypic association between the connective tissue disorder EDS and abnormal CCT values . Extremely thin corneas are common findings in EDS [9] . The estimated allelic effects for rs7044529 were similar in all the samples , with a weighted effect of −0 . 15 . This SNP has a moderate overall p-value of 9 . 3×10−06 ( Table S2 ) .
CCT is an important clinical measurement of human eyes . Recent studies have highlighted CCT as a prognosticator for the development of glaucoma , one of the leading causes of irreversible blindness worldwide , with a thin CCT potentially increasing the risk of developing a subtype known as open-angle glaucoma ( OAG ) [2]–[4] . The genetic aetiology of OAG is not well understood , with only one major gene myocilin identified [14] . Given that OAG has a complex molecular aetiology , the breakdown of the dichotomous trait ( i . e . , “affected” or “unaffected” status ) into its quantitative measurement will aid in the search for disease-susceptibility genes . It is therefore of highly clinical significance to explore the genetic factors that contribute to CCT variation . Thus , we conducted a multi-stage study on over 5 , 000 samples with the purpose of detecting the genetic variants for the human CCT . We conducted GWA studies on the discovery sample of the two twin cohorts from Australia and the UK . Another set of GWA studies were performed on the two population-based cohorts in pool genotyping design and the results were further validated by individual genotyping the extended cohort ( pooled samples plus additional samples with extreme phenotypes ) . We have identified a novel locus near FOXO1 ( overall p-value of 4 . 6×10−10 for SNP rs2721051 ) , which accounts for ∼1 . 2% variation in normal human CCT . FOXO1 , located at 13q14 . 1 is a 111kb gene belonging to the forkhead family of transcription factors and characterized by a distinct forkhead domain . Whilst the specific functions of this gene are unknown , it may play a role in myogenic growth and differentiation ( RefSeq , NCBI ) . Translocation of this gene with PAX3 has been associated with alveolar rhabdomyosarcoma ( RefSeq , NCBI ) . A recent study by Berry et al . reported that the transcription factor gene FOXC1 ( 6p25 ) regulates the expression of FOXO1 and binds to a conserved element in the FOXO1 promoter [15] . FOXC1 is a major transcription factor involved in the development of the anterior segment of the eye , which is involved in both anterior segment dysgenesis and congenital glaucoma phenotypes [16] . In the twin cohorts we obtained genome-wide significant association for the genotyped SNPs rs12447690 ( p = 1 . 67×10−09 ) and rs9938149 ( p = 1 . 08×10−07 ) , ∼140kb and ∼108kb respectively from the gene ZNF469 ( 16q24 ) . By individually genotyping the population-based samples with extreme CCT values , we showed that rs12447690 was well replicated with an overall p-value of 8 . 95×10−11 , accounting for 1 . 29% of the variation in CCT . ZNF469 was recently implicated in a study of the rare disorder BCS [13] . Abu et al . showed that rare sequence variants in ZNF469 segregated with BCS . The SNPs we report near ZNF469 have high MAFs – for example rs12447690 has MAF 0 . 44 in HapMap CEU samples , with a similar value in the cohorts presented here . Given the recombination hotspot ( Figure 1 ) and the large difference in allele frequency between such variants and the rare variants identified by Abu et al . , our findings are unlikely to be explained by linkage disequilibrium ( LD ) between the rare and common variants ( the r2 parameter cannot be high between such polymorphisms ) . At the 16q24 locus there are four putative genes nearer to rs12447690 than ZNF469 . However , in each case the putative genes are poorly characterized with only a hypothetical protein role . Interestingly , one of the clinical features of BCS patients is hyperlaxity of the joints [13] . A small part of the AU twin cohort overlaps with samples from a pelvic floor study by Hansell et al [17] , which included measurements of joint mobility [18] ( Figure S7 ) . Based on a small sample size of 102 individuals , CCT was inversely correlated ( Pearson correlation −0 . 221 , P = 0 . 02583 ) with thumb bending degree , but was uncorrelated with the other two measurements of joint mobility ( Figure S7 ) . To minimize multiple testing , we only tested for association of the thumb bending measure of joint mobility , and focused on 31 SNPs in the ZNF469 region of interest . Despite the limited power in this study , 2 SNPs rs7198446 and rs7500421 in the underlying region were nominally associated with thumb bending degree , with p-values of 0 . 0298 and 0 . 0471 respectively ( Figure S8 ) . These SNPs are halfway ( ∼60kb to both sides ) between the top SNPs on chromosome16 found in the CCT study and the gene ZNF469 . We also checked the associations of these variants with CCT in this sample , but none of them was significant . We have demonstrated a flexible approach to GWA studies using different designs . By taking into account of the thresholds used to determine high and low pools for the quantitative trait ( together with population allele frequencies ) , we mapped the estimates of the differences in pooling allele frequency between high and low pools to the effect sizes on additive scale of the quantitative trait . In summary , we identified a novel QTL for CCT near gene FOXO1 ( 13q14 . 1 ) with p = 4 . 60×10−10 . Common variants near ZNF469 ( 16q24 ) were found in this study as associated with CCT with p = 8 . 95×10−11 . Our findings suggest that in addition to rare variants in ZNF469 underlying CCT variation in BCS patients , more common variants near this gene may contribute to CCT variation in the general population .
This study was conducted according to the principles expressed in the Declaration of Helsinki . The study was approved by the human ethics committee of the University of Tasmania , Royal Victorian Eye and Ear Hospital , Queensland Institute of Medical Research and the Flinders Medical Centre . Informed consent was obtained from parents with the child's assent or from adult participants before testing . Three twin cohorts were recruited from Australia and the UK . The AU twin cohort consisted of two sub-samples , 953 individuals from the Brisbane Adolescent Twin Study ( BATS ) and 761 individuals from the Twin Eye Study in Tasmania ( TEST ) , making up a whole cohort of 1714 participants from 786 families . A full description of the AU twin cohorts is given in Mackey et al [19] . Twins from the UK were a sub-sample from the cohorts collected at St Thomas' Hospital in London . 1759 people from 1119 families were included in this study . Nearly 90% of the UK samples are adult women . Details of the UK twin cohort are given in Healey et al [20] . CCT was measured in the twin cohorts using ultrasound pachymetry and recorded for both eyes . Measurements were performed using a Tomey SP 2000 ( Tomey Corp . , Nagoya , Japan ) or a DGH Technology ( model 500; Scarsdale , NY ) pachymeter in the Australian and UK twin cohorts respectively . Twin pairs were measured at the same time of day to avoid bias related to diurnal variation . With little evidence for a significant difference between the left and right eyes ( ANOVA p-value = 0 . 575 ) , the mean CCT value of both eyes was used throughout as our measurement . In the AU twin cohorts , DNA samples extracted from each person were hybridized to the Illumina HumanHap 610W Quad arrays , with the samples from BATS genotyped by deCODE Genetics and the ones from TEST genotyped by the Center for Inherited Disease Research ( CIDR ) . We scrutinized the genotypic data ( SNPs ) and screened them according to a series of quality control criteria , including minor allele frequency ( MAF ) ≥1% , p-value for Hardy-Weinberg equilibrium test≥10−6 , SNP call rate>95% or Illumina Beadstudio GenCall score≥0 . 7 . After cleaning , 530 , 656 SNPs were left for association testing in AU twin cohorts . The UK samples were partly genotyped on the Illumina Hap610W arrays at CIDR , and partly genotyped on Illumina HumHap 300K Duo arrays at Wellcome Trust Sanger Institute . Slightly different quality control criteria compared with the AU twin study were applied: MAF≥1% , p-value for Hardy-Weinberg equilibrium test≥10−4 and SNP call rate>95% , resulting in a complete set of 548 , 001 SNPs for the association tests . We screened the genotypic data for ancestral outliers using principal component analysis [21] . By comparing AU twin data with 16 global populations sourced from HapMap Phase 3 and Northern European sub-populations from a previous study by McEvoy [22] , 2% of the samples were excluded for being identified as ancestral outliers; thus giving us greater confidence in the homogeneity of the study sample ( Figure S2 ) . UK twin samples were also screened for genetic outliers by comparison with the reference of three main populations from HapMap Phase 2 . The Q-Q plot ( Figure S3 ) clearly shows the homogeneity of the UK panel except for one data point . The discrepancy between the observed and expected statistics for this variant suggests a potential association signal . Higher density markers on autosomes were also available from imputation . We imputed data using MACH for the AU samples based on a set of 469 , 117 SNPs which were common to the six Illumina 610K subsamples at QIMR . The imputation for the UK samples were undertaken with reference to HapMap release 22 CEU using IMPUTE version 2 [23] . Each of the imputed datasets contains up to 2 . 4 million SNPs . Both AU and UK twin cohorts in our study consist of either twin pairs or their close relatives ( parents , siblings ) in the family . Samples within the family are genetically related , sharing the chromosomal regions of identity-by-descent ( IBD ) . In those regions , the related samples will provide the similar genetic information . Failing to estimate the IBD states will result in an increased false-positive rate in the association tests . To avoid this problem , we conducted the association test ( –fastassoc ) in MERLIN [24] . It incorporated genetic relatedness between the samples by estimating the IBD prior to the association tests . The AU samples were controlled for both age and gender effects , whilst the predominantly female UK samples were only controlled for age effects . We standardized the trait distribution of CCT to increase the inter-sample compatibility as well as robustness to extreme observations . Two population-based cohorts were studied in the case-control pool design . We measured and recorded CCT for both cohorts in the same way as in the Australian twin cohorts . The first cohort utilized was the Blue Mountains Eye Study ( BMES ) . This population-based study , designed to investigate the genetics and epidemiology of ocular disease , recruited 3654 individuals living in a defined geographical region in the Blue Mountains ( west of Sydney , Australia ) . Both DNA and CCT measurements were available for 953 individuals . Jawaid et al showed that the optimal fraction for quantitative trait locus ( QTL ) mapping using pooled DNA samples was 20% [25] . Thus in this study , DNA samples extracted from the individuals among the thick CCT group ( upper 20% of the CCT distribution ) were constructed as a control pool , whereas DNA samples from the thin group ( lower 20% of the distribution ) as a case pool . This resulted in 190 individuals in each tail although in practice sufficient DNA was only available for 143 individuals in the thin pool and 146 individuals in the thick pool . The drop-out due to insufficient DNA was random with respect to phenotype , suggesting we were effectively sampling the extremes from a total sample size of ∼145/190 * 953 = 727 . Concentration of DNA samples were carefully adjusted by serial dilutions and quantified using PicoGreen ( InVitrogen ) , to ensure the equal quantity of DNA contributed by individual samples . Pooled DNA was genotyped on Illumina Human 1M-Duo V3 arrays at Queensland Institute of Medical Research ( QIMR , Brisbane , Australia ) in triplicate . The second cohort , based on a blood pooling design [26] was collected from Adelaide , Australia . This study consisted of 530 unrelated individuals in total , with 106 individuals in the thin CCT group ( covers 20% lower tail of the underlying CCT distribution ) and 105 individuals in the thick CCT group ( covers 20% upper tail ) . The CCT values for the middle group were not recorded . Equal quantity ( 100 µL ) of whole blood was aliquoted shortly after venesection from each individual . This aliquot was stored at 4°C then lysed immediately prior to pooling . A single DNA extraction was then performed on each blood pool using QIAmp maxi kit ( Qiagen ) . Each blood pool was genotyped on Illumina Human 1M-Duo V3 arrays at QIMR , with four replications . The output of the raw red and green bead scores from the genotyping stage was available for the pooled data analysis . We applied the same data processing protocol to both cohorts , similar to the method described in the supplementary methods in Brown et al [27] . Before calibrating the raw scores , a number of SNPs with more than 10% negative scores on each array were excluded , as well as the SNPs with the sum of mean red and green scores across each array smaller than 1200 . This step was included to ensure that the calibration was done on a pre-cleaned dataset . A normalization/correction factor ( corr ) was calculated by forcing the mean value of the pooling allele frequency to be 0 . 5 over all SNPs on each stripe ( Illumina Human 1M-Duo V3 array has 6 stripes on a single array ) . The pooling allele frequency ( PAF ) was then estimated based on the raw red intensities and the corrected green intensities for all the SNPs ( PAF = red/ ( red+green/corr ) ) . A final set of autosomal SNPs met the following criteria: more than 5 probes in each pool; with a MAF greater than 1%; without a significant variance difference between case and control pools ( i . e . , the log10 transformed p-values from an F test on the ratio of case control pool variances were smaller than 6 ) , was taken forward to a linear regression model [28] . The underlying idea was to regress the pooling allele frequency on the case/control status for each SNP and estimate the pooling error across all the SNPs ( for more details see MacGregor et al [28] , [29] ) . The p-value from comparing the test statistic in the MacGregor paper ( T2-x ) to χ2 ( 1 ) distribution was computed to assess the significance of allele frequency difference between the two pools ( d ) . Individual SNPs of interest were genotyped in most individuals included in the DNA and blood pools as well as additional 102 samples ( 72 samples from BMES population and 30 samples from Adelaide population ) belonging to the extreme quantiles of the CCT distribution but not available for pooling . SNPs were genotyped using iPLEX GOLD chemistry ( Sequenom ) on an Autoflex Mass Spectrometer ( Sequenom ) at the Australia Genome Research Facility ( Brisbane , Australia ) . Since the pooling design dichotomizes the quantitative trait of CCT as a binary trait ( case/control status ) , results from the pooling cohorts are not comparable with those from the twin cohorts . An alternative way of enabling such comparison is to transform the case/control frequency difference ( d ) to be the allelic effect ( β ) , given information on the allele frequency ( p ) and the upper/lower threshold cutting up both tails ( TU/TL ) . Following the notions in Jawaid et al [25] , the expected allele frequencies in the two pools arewhere N is the sample size; Φ is the density function of standard normal distribution; TU and TL are the upper and lower thresholds; P ( G ) is the genotypic frequency; μG stands for the mean trait value for the corresponding genotype; , assume no dominance effects for the QTL , then is the trait variance for each genotype . Thus the case control frequency difference between the two pools is . It demonstrates the relation between the case control frequency difference ( d ) in a pooling design and the allelic effect ( β ) in a conventional design , given the allele frequency ( p ) and the upper/lower threshold ( TU/TL ) . Based on the inverse function of d , the allelic effect can be obtained from the estimated frequency difference of the case control pools . As described earlier , the lower threshold in this study is the 20% quantile of the standard normal distribution and the 80% quantile for the upper threshold . The allele frequencies estimated from the combined AU twin cohort were fitted as the allele frequency parameter , p in this context . We also applied the association mapping method for selective genotyping design in Huang and Lin [30] to the combined cohort with extreme CCT phenotypes ( pooled samples plus extra samples which were individually genotyped for a small number of SNPs ) . Our settings fit in the second design in their paper , namely , a random sample of n individuals whose trait values fall into certain regions is selected for genotyping and the trait values are retained for only those individuals . Therefore , we utilized the conditional likelihood described in the paper to obtain the unbiased estimator of the effect size and its standard deviation . As mentioned above , the mean CCT values were measured and standardized in the same way for all the five cohorts . Since each of the sample size with all the Caucasian samples was sufficiently large , the distributions of CCT values in all the cohorts were good approximations of CCT distribution for Caucasian population found in clinical studies , normal distribution with mean ∼540µm [31] ( Figure S9 ) . These compatibilities ensured the comparison of the results from two or more cohorts in a single meta-analysis . It will considerably enlarge the overall sample size and increase the power to identify associations . A test statistic for the meta-analysis , with β as the allelic effect from sample Si and the weight as its inverse variance , is expected to be distributed as a chi-square with 1 degree of freedom . This test assessing the significance of the weighted effect size with respect to its combined variance , has the advantage of taking into account the direction of the allelic effect . Therefore , the reference alleles from all the samples were required to be coordinated before the meta-analysis . In our study , a small proportion ( <1% ) of SNPs with the ambiguous polymorphism types ( A/T , C/G ) were excluded prior to our main analyses . | Central corneal thickness ( CCT ) is an important eye measurement . It has been considered as a prognosticator for the development of glaucoma , with a thin cornea potentially increasing the risk of developing a subtype known as open-angle glaucoma . CCT is highly heritable , yet its genetic determinants are poorly characterized . We have revealed two loci near gene FOXO1 and ZNF469 associated with CCT in this multi-stage genome-wide association study examining over 5 , 000 samples . It is of particular interest that , while rare mutations in ZNF469 cause Brittle Cornea Syndrome , more common variants near this gene also contribute to CCT variation in the general population . Furthermore , given the relation between CCT and glaucoma , results from our CCT studies will implement the search for the disease-susceptibility genes of glaucoma . | [
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] | [
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] | 2010 | Common Genetic Variants near the Brittle Cornea Syndrome Locus ZNF469 Influence the Blinding Disease Risk Factor Central Corneal Thickness |
This study employed various monitoring methods to assess the impact of repeated rounds of mass drug administration ( MDA ) on bancroftian filariasis in Papua New Guinea , which has the largest filariasis problem in the Pacific region . Residents of rural villages near Madang were studied prior to and one year after each of three rounds of MDA with diethylcarbamazine plus albendazole administered per World Health Organization ( WHO ) guidelines . The mean MDA compliance rate was 72 . 9% . Three rounds of MDA decreased microfilaremia rates ( Mf , 1 ml night blood by filter ) from 18 . 6% pre-MDA to 1 . 3% after the third MDA ( a 94% decrease ) . Mf clearance rates in infected persons were 71% , 90 . 7% , and 98 . 1% after 1 , 2 , and 3 rounds of MDA . Rates of filarial antigenemia assessed by card test ( a marker for adult worm infection ) decreased from 47 . 5% to 17 . 1% ( a 64% decrease ) after 3 rounds of MDA . The filarial antibody rate ( IgG4 antibodies to Bm14 , an indicator of filarial infection status and/or exposure to mosquito-borne infective larvae ) decreased from 59 . 3% to 25 . 1% ( a 54 . 6% decrease ) . Mf , antigen , and antibody rates decreased more rapidly in children <11 years of age ( by 100% , 84 . 2% , and 76 . 8% , respectively ) relative to older individuals , perhaps reflecting their lighter infections and shorter durations of exposure/infection prior to MDA . Incidence rates for microfilaremia , filarial antigenemia , and antifilarial antibodies also decreased significantly after MDA . Filarial DNA rates in Anopheles punctulatus mosquitoes that had recently taken a blood meal decreased from 15 . 1% to 1 . 0% ( a 92 . 3% decrease ) . MDA had dramatic effects on all filariasis parameters in the study area and also reduced incidence rates . Follow-up studies will be needed to determine whether residual infection rates in residents of these villages are sufficient to support sustained transmission by the An . punctulatus vector . Lymphatic filariasis elimination should be feasible in Papua New Guinea if MDA can be effectively delivered to endemic populations .
Lymphatic filariasis ( LF ) is a deforming and disabling infectious disease that causes elephantiasis and hydroceles . The infection affects some 120 million people in an estimated 83 countries in tropical and subtropical regions , with an estimated 1 . 2 billion individuals at risk [1] . Most LF is caused by Wuchereria bancrofti , a nematode parasite that is transmitted to humans by mosquitoes . The World Health Assembly passed a resolution in 1997 that called for global elimination of LF as a public health problem ( WHA Resolution 50 . 29 , see www . filariasis . org ) . The World Health Organization ( WHO ) developed a plan for elimination that is based on selective diagnosis to identify endemic areas followed by repeated , annual cycles of mass drug administration ( MDA ) of antifilarial medications [1] , [2] . The most recent summary from WHO reported that approximately 1 . 9 billion doses of MDA were distributed to more than 500 million individuals between 2000 and 2007 [3] . Thus , the Global Programme to Eliminate Lymphatic Filariasis ( GPELF ) is the largest infectious disease intervention program attempted to date based on MDA . Applied field research is needed to validate the GPELF strategy and to test methods for measuring the impact of MDA . Recent papers have reported encouraging data on the impact of MDA with diethylcarbamazine ( DEC ) plus albendazole on various filariasis parameters in Egypt and emphasized the importance of compliance in MDA programs [4] , [5] . However , more information is needed from areas with different epidemiological and ecological parameters , e . g . mosquito vectorial capacity , transmission intensity , baseline infection rates , and climate . Bancroftian filariasis is a major public health problem in Papua New Guinea [6] . With approximately 39% of its population infected , the country has some of the highest LF infection rates in the world [7] , despite the fact the principal vectors there ( Anopheles punctulatus group , which also transmit malaria ) are less efficient for filariasis transmission than Culex or Aedes mosquitoes that serve as vectors in other endemic regions [6] , [8] . At this time , Papua New Guinea has more filariasis cases than any other country in the Pacific region [9] . Although it is the only country in the region that has not yet fully implemented a national LF elimination program , the Papua New Guinea Department of Health has recently initiated a MDA program for elimination in several provinces . In some areas , MDA will overlap with the distribution of insecticide-treated bednets for malaria control . This overlap in public health interventions may benefit LF elimination efforts , as suggested by reports from the Solomon Islands where DDT spraying ( used for malaria control ) reduced LF transmission [10] . Several studies conducted over the past 10 years have assessed the impact of MDA on LF infection parameters in Papua New Guinea . For example , a study performed in 14 villages in East Sepik Province found that four rounds of MDA with DEC plus ivermectin or with DEC alone ( drug regimens that have been superseded by the current WHO recommendation of single dose DEC plus albendazole ) dramatically decreased microfilaremia ( Mf ) prevalence rates and transmission parameters in areas with high and moderate baseline infection and transmission rates [11] . Other studies in offshore island communities in Papua New Guinea found dramatic decreases in Mf and/or filarial antigenemia rates following MDA or community distribution of DEC alone or DEC with albendazole [12] , [13] . We now report results from a community study that was designed to evaluate the efficacy of repeated rounds of MDA with DEC plus albendazole ( distributed according to WHO guidelines [14] ) on a number of filariasis infection parameters . Results of this study should be useful for those responsible for planning and implementing national LF elimination programs in Papua New Guinea and in other areas where filariasis is transmitted by Anopheles mosquitoes .
The study was performed in 4 villages in the Usino-Bundi district , Madang Province , Papua New Guinea . The villages are located approximately 40 km southwest of the provincial capital , Madang town . The study villages were located at least 2 km from untreated filariasis-endemic villages . This is the estimated flight range of the local mosquito vector [15] . Villages were mapped and censuses were conducted prior to the first round of MDA and annually thereafter . Two Infection prevalence surveys were performed before the first round of MDA , and this was repeated approximately 12 months after each of three annual rounds of MDA . Field teams comprised of trained nurses and field technicians met with community leaders and held outdoor community education sessions to inform people about the health significance and biology of LF , the planned MDA program , and the importance of blood tests for monitoring the impact of MDA . Annual follow-up meetings were held to communicate preliminary results and to provide community members with opportunities to ask questions about the project . Community liaison personnel mobilized village residents to participate in the study . Children <2 years of age , children who weighed <10 kg , pregnant women , and people with severe chronic illness or acute illness with fever were excluded from the study . We reassessed eligibility for treatment each year . For example , women who were pregnant in year 1 were eligible for the study in later years if they were not pregnant . Survey teams enrolled subjects in the late afternoon by obtaining oral informed consent from adults and recording demographic information . Enrollment of children required their assent and consent from at least one parent . The population was surveyed twice prior to the first round of MDA . The first pre-MDA survey ( pre-MDA-A , which collected day blood samples for antigen and antibody testing only without microfilaria testing ) was performed approximately 2 years prior to the first round of MDA . The second pre-MDA survey ( pre-MDA-B , with blood for Mf , antigen , and antibody testing ) was performed together with the first round of MDA ( with blood collection just prior to treatment ) . MDA comprised the WHO-recommended regimen of a single oral dose of diethylcarbamazine citrate ( 6 mg/kg body weight ) with albendazole ( 400 mg regardless of weight ) . This was repeated once per year for a total of three years . Project staff directly observed ingestion of antifilarial medications . Some people agreed to receive MDA but refused to provide blood samples . MDA compliance rates were estimated by dividing the number of people who ingested DEC with albendazole by the number of village residents in the census who were at least 2 years of age . This is similar to “observed coverage” in GPELF guidelines [14] . However , persons ineligible for treatment ( e . g . , pregnant women ) are included in the denominator for our compliance calculations but not in the GPELF “observed coverage” . All tests were performed in the Papua New Guinea Institute of Medical Research Laboratories near Madang . Microfilaremia was assessed by membrane filtration of 1 ml of venous blood collected between 9 p . m . and 12 midnight [16] . The Mf prevalence rate was calculated by dividing the number of people who were Mf positive by the number of people tested for Mf . Few blood samples were collected from children younger than 6 years of age , and results from these samples are not included in this report . We also calculated community microfilaria load ( CMFL ) as a measure of the total amount of Mf present in study communities as previously described [17] . CMFL is defined as the antilog of the [sum of log ( X+1 ) /N]–1 , where X is the MF count in positive subjects and N is the number of people tested for microfilaremia . Circulating filarial antigenemia ( CFA ) was assessed with a rapid-format antigen card test ( Filariasis Now , Binax Inc . , Portland , Maine , USA ) [18] , [19] . Test instructions call for testing 100 µl of whole blood . We tested 70 µl of plasma , which is the approximate volume of plasma in 100 µl of whole blood . Card tests were read visually at 10 minutes . IgG4 antibodies to recombinant filarial antigen Bm14 in human plasma were detected by ELISA as previously described [20] . Sera were tested in duplicate , and borderline samples were retested . Prior studies have shown that this test is sensitive and specific for infection or heavy exposure to filarial parasites [20]–[22] . Mosquitoes were collected with CDC light traps ( without dry ice ) placed in houses ( 1 night per house ) in study villages over 4 months period before MDA commenced and for 4 months starting 6 to 9 months following each round of MDA . Two pre-MDA mosquito collections were conducted . The first ( pre-MDA-A ) was conducted approximately 12 to 18 months prior to the first round of MDA; the second ( pre-MDA-B ) was 1 to 5 months prior to the first round of MDA . Blood-engorged , gravid , or semi-gravid An . punctulatus group mosquitoes ( all of which had recently ingested blood ) were identified by morphology and sorted into pools by household . W . bancrofti DNA was detected in mosquito pools by PCR as previously described in detail [23]–[25] , except mosquitoes were macerated by vortexing with ball bearings [26] instead of by mortar and pestle . Mosquito infection rates ( maximum likelihood estimates with 95% confidence intervals ) were calculated with PoolScreen 2 . 02 software [27] . Data entry was performed with Visual FoxPro software with field limits and double data entry . We used the SPSS v . 14 software package ( SPSS , Chicago , IL ) for statistical analysis . The chi-square test was used to assess the significance of differences in proportions . This study ( including the oral consent process ) was reviewed and approved by institutional review boards at Washington University School of Medicine and Case Western Reserve University and the Medical Research Advisory Committee of the Papua New Guinea Department of Health . The sponsor of the study ( Division of Microbiology and Infectious Diseases , NIAID , NIH , Bethesda , MD ) also reviewed the study protocol to ensure compliance with GCP standards . Study personnel informed prospective study participants about the study by reading them a consent document in the local language . Oral consent was documented on case report forms . Participation by children required consent from at least one parent and the child's assent . As noted above , some subjects agreed to take anti-filarial medications but refused blood tests .
Table 1 shows baseline infection indicators by age group just prior to the first round of MDA ( pre-MDA-B survey data ) . Mf prevalence increased dramatically up to age 20 years , with slightly higher rates in older age groups . The mean±SD of the number of Mf per ml in 106 microfilaremic subjects was 610±1073 ( median 161; range 1–5 , 960 ) . CFA and Bm14-specific IgG4 antibody rates increased dramatically from age 6–10 years to 21–30 years , with slight increases ( CFA ) or little change ( Bm14 ) in older age groups . Antibody and CFA rates were much higher than Mf rates in all age groups . Persons with Mf or filarial antigenemia had a significantly higher antibody rate ( 81 . 9% , n = 279 ) than persons with negative Mf and CFA tests ( 37 . 6% , N = 287 ) ( P<0 . 001 ) . Antibody rates were higher than CFA rates in younger age groups ( ≤30 years of age , P<0 . 001 ) , but CFA rates were similar to antibody rates in older people ( difference not significant ) . Filarial infection rates ( Mf and CFA ) were significantly higher in males than in females ( Table 2 ) . Males also had higher antifilarial antibody rates , but the difference was not statistically significant . Gender differences in infection and antibody rates were much more striking in adults than in children 6 to 15 years of age , although the same trends were present in children . The mean MDA compliance rate over the 3 rounds of MDA was 72 . 9% ( Table 3 ) . However , compliance rates were much lower in children 2–5 years of age compared to those in older individuals . MDA had dramatic effects on all filariasis parameters examined ( Table 4 ) . Over the three annual rounds of MDA , microfilaremia ( Mf prevalence rates and CMFL ) decreased more rapidly and to lower levels than CFA or antibody rates . Antigenemia and antibody prevalence rates in young children decreased more after MDA than rates for the total study population . Seven of 529 subjects tested had Mf one year after the third round of MDA . Mf counts in these subjects ranged from 1–52 Mf/ml ( mean 18 . 0±20 . 5; median 9 ) . These subjects tended to have high Mf counts prior to MDA . Only one of the subjects with Mf detected after MDA round 3 had not received MDA; two had been treated once , one had been treated twice , and two had been treated three times . Table 5 shows CFA and antibody rates in Mf-positive subjects detected in study villages before MDA and after each round of MDA . These rates did not change significantly after MDA . P values for differences in CFA and Bm14 antibody rates ( for samples from Mf-positive subjects ) in different years of the study were 0 . 60 and 0 . 78 , respectively ( chi-square ) . Longitudinal Mf data were available for 104 subjects who were initially Mf positive and who had repeat Mf testing approximately one year after one or more rounds of MDA until Mf clearance was achieved . Mf clearance rates were 76% ( 79/107 ) , 95 . 2% ( 99/104 ) , and 98 . 1% ( 102/104 ) after 1 , 2 , or 3 rounds of treatment , respectively; 2 subjects had persistent microfilaremia after 3 rounds of treatment . Subjects with higher baseline Mf counts tended to require more rounds of MDA to completely clear Mf . The geometric mean and median Mf counts for 79 people who cleared Mf after one round of MDA were 64 . 8 and 89 ( range , 1–3813 ) ; geometric mean and median Mf counts for 25 subjects who failed to clear Mf after one round of MDA were 604 and 833 ( range 11–5279 ) . The difference in baseline Mf counts between the two groups was statistically significant ( P<0 . 001 by the Mann Whitney U test ) . Microfilaria incidence rates in persons who were Mf-negative just prior to MDA were 1 . 7% ( 7/408 ) , 0 . 4% ( 2/555 ) , and 0 . 2% ( 1/472 ) after MDA rounds 1 , 2 , and 3 , respectively . Note that Mf incidence data were not available for the period between the two pre-MDA surveys . Despite this , the decrease in Mf incidence rates after MDA was statistically significant ( P = 0 . 013 by chi square ) . The mean Mf count in persons with Mf incidence was 86 . 2±112 Mf/ml ( median 26 , range 7–353 ) . Of course , some of these cases may represent “pseudo-incidence” due to technical problems with Mf detection or clerical errors . Most people with Mf incidence had positive antigen ( 7/10 ) and antibody ( 8/10 ) tests one year prior to the appearance of Mf . Four subjects with microfilaremia at baseline were Mf-negative after MDA but positive again with counts ranging from 47 to 68 Mf/ml one year later . Such cases of temporary Mf clearance following treatment were not counted in clearance or incidence results shown above . Table 6 shows Bm14 antibody and CFA incidence events and rates for the total study population and for children 6–15 years of age . Incidence rates for the 2 year period between the 2 pre-MDA surveys were high . Pre-MDA incidence rates in children <16 years of age were not significantly different from those in older people . Incidence rates decreased dramatically after MDA . Incidence rates for the 2 year period after the first round of MDA were significantly lower than those for the two year period between the pre-MDA-A and pre-MDA-B surveys ( Table 6 ) . Incidence rates for antifilarial antibodies and CFA decreased by 75% and 63% in the total study population ( and by 68% and 70% in children ) , respectively , after 3 rounds of MDA . 573 pools of recently fed ( blood fed , gravid , or semigravid ) mosquitoes ( 3 , 729 mosquitoes ) were tested for filarial DNA by PCR ( Table 7 ) . The mosquitoes were collected from 114 . 6±16 . 9 houses per year ( approximately 70% of the houses in study villages ) . The mean number of recently fed mosquitoes per pool was 6 . 5±6 . 6 ( median 4 . 0; range 1–28 ) . The high baseline rate of filarial DNA in mosquitoes just prior to MDA ( 15 . 1% in the pre-MDA-B survey ) decreased rapidly after MDA ( Table 7 ) . The 92 . 3 % decrease in the filarial DNA rate after 3 rounds of MDA was similar to the 93% decrease in the Mf prevalence rate observed in the human population .
This is the first detailed report on the effects of repeated rounds of MDA with DEC and albendazole on filariasis infection parameters in an area with Anopheles transmission . The study site had baseline filarial infection rates that were high in the global context but moderate for Papua New Guinea . Baseline infection rates were higher in older age groups and higher in males than in females . These trends probably reflect increased cumulative exposure in older people and differences in exposure between males and females . Since the gender differences were much more striking in adults , these could also be related to biological factors such as hormone levels . The performance of the ICT antigen test and the Bm14 antibody test require some comment before we address the impact of MDA on filariasis parameters in this study . The ICT test detected filarial antigenemia in a high percentage of untreated Mf-positive subjects ( detected by membrane filtration of 1 ml of venous blood ) , and this sensitivity was maintained after MDA . This is in contrast to a recent study from Kenya that reported decreased sensitivity of the ICT test in Mf carriers ( detected by the counting chamber method with 0 . 1 ml of finger prick blood ) after 2 rounds of MDA [28] . The Bm14 antibody test was less sensitive than the CFA test in Mf-positive subjects in the present study , and it was also somewhat less sensitive than previously reported [20] , [22] . However , both the CFA test and the Bm14 antibody test were much more sensitive than Mf detection for detecting filariasis activity in the study communities , and this is consistent with prior reports [5] , [29] . Antibody rates in children <11 years of age were much higher than Mf or CFA rates , both before and after MDA . This supports the strategy of testing sentinel populations of young children for antifilarial antibodies as a means of assessing recent filariasis activity in communities [30] . Population MDA compliance rates were very good throughout the 3-year study period . However , this required a lot of effort , with multiple visits to the study villages and labor-intensive recruitment of village residents . It might be easier to achieve high compliance rates in a national MDA program that was not linked to collection of venous blood . MDA compliance rates were low in children <6 years of age . This may have reflected parents' concerns about blood tests in their young children . We believe that the national LF elimination program in Papua New Guinea will need to develop new strategies to achieve high MDA compliance in young children . Information campaigns should emphasize the dual benefits of MDA on LF and soil-transmitted helminth infections . MDA dramatically reduced all filariasis infection parameters in the study villages . As in earlier studies , Mf rates in people and parasite DNA rates in mosquitoes fell more rapidly than CFA or antibody rates [5] , [31] , 32 . While low residual filarial DNA rates in mosquitoes indicate the presence of Mf carriers in communities following MDA , this does not necessarily mean that significant LF transmission will continue in these areas . PCR can detect DNA from dead filarial parasites in mosquitoes [33] , and most Mf taken up by anopheline vectors do not survive to become infective larvae ( L3 ) [34] , [35] . CFA and anti-filarial antibody rates fell more rapidly after MDA in children <11 years of age than in the total study population; this may be because infection intensities and years of infection/exposure tend to be lower in young children than in older individuals . Although infection rates decreased in children after MDA , many young children had positive CFA and/or anti-filarial antibody tests after 3 rounds of MDA . Of course , these children had been exposed to the parasite for years prior to MDA . Children born after LF transmission has been interrupted should not have positive CFA or antibody tests [30] . Surveillance activities to verify interruption of transmission should focus on testing young children . Mosquito monitoring provides a non-invasive means of detecting residual infections in communities if the number of young children available for testing is small . This study provided interesting longitudinal data on effects of MDA on Mf clearance in individuals and on incidence rates for different filariasis parameters . Mf clearance rates in this study after one or more annual doses of DEC with albendazole were higher than those reported from clinical trials performed in Sri Lanka and Egypt [36]–[38] . However , while all subjects in the clinical trials had high baseline Mf counts , all Mf carriers were considered in current community-based study . The current study also found that Mf clearance rates after MDA were lower in persons with high baseline Mf counts . The incidence data are very exciting , because they demonstrated that MDA significantly decreased the incidence of Mf , CFA , and antifilarial antibodies in the study population . This is the first study that has documented decreased filariasis incidence rates following MDA . However , incidence events observed after MDA-3 suggest that 3 rounds of MDA was not sufficient to completely eliminate LF transmission in this setting . The impact of three rounds of MDA in the current study was at least as impressive as that recently reported from Egypt ( Giza governorate ) with the same MDA regimen , although this “high prevalence” study area in Egypt had lower LF infection rates before MDA ( 11 . 5% Mf , 19 . 0% CFA , and 3 . 07% mosquito DNA ) and higher MDA compliance rates than our study site in Papua New Guinea [5] . This suggests that the encouraging results reported from Egypt can be replicated in areas with very different epidemiological parameters . Changes in infection parameters following MDA must be considered in the context of the local mosquito vector . An . punctulatus is a less efficient LF vector than Cx . pipiens ( the principal LF vector species in Egypt ) . We do not know the minimum requirements for sustained transmission of W . bancrofti by An . punctulatus . However , Tisch et al recently reported that LF parameters continued to decrease in villages in a different area of Papua New Guinea ( in East Sepik Province , approximately 300 km from the Usino study site ) for at least 5 years after Mf rates had been reduced to low levels by 5 rounds of MDA with DEC and ivermectin [32] . It is possible that three rounds of DEC with albendazole ( which reduced the Mf rate to 1 . 3% with a 97 . 9% decline in CMFL ) would have been sufficient to reduce LF transmission rates to unsustainable levels in the Usino study area . The study villages received a fourth round of MDA in 2006; long term follow-up studies will be needed to determine whether four rounds of MDA have interrupted LF transmission in this area . For the time being , the results from Usino are quite encouraging . Taken together with earlier studies , they suggest that LF elimination should be feasible in Papua New Guinea and other endemic areas with Anopheles transmission if MDA can be effectively delivered to endemic populations . Prospects for LF elimination should be even brighter if MDA can be integrated with distribution of insecticide-treated bednets [11] . | Lymphatic filariasis ( LF ) is a deforming and disabling disease that is caused by parasitic worms that are transmitted by mosquitoes . While a number of countries have initiated LF elimination programs based on mass drug administration ( MDA ) , relatively little good information is available on the impact of MDA on filariasis prevalence and incidence rates in populations . This study assessed the impact of three rounds of MDA ( with single doses of diethylcarbamazine and albendazole ) on filariasis infection rates in villages in Papua New Guinea , which has the largest filariasis problem in the Pacific region . MDA dramatically reduced rates for all filariasis infection markers tested . These included microfilaremia ( parasites in blood that are necessary for transmission of the infection ) , filarial antigenemia ( a marker for adult worm infection ) , anti-filarial antibodies ( which indicate infection or heavy exposure to the parasite ) , and parasites in mosquitoes that transmit the infection . In addition to curing existing infections , MDA also reduced new infection rates in the study population to very low levels . These results suggest that it should be possible to eliminate LF in Papua New Guinea if MDA can be effectively delivered to endemic populations . | [
"Abstract",
"Introduction",
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] | [
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"diseases/epidemiology",
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] | 2008 | The Impact of Repeated Rounds of Mass Drug Administration with Diethylcarbamazine Plus Albendazole on Bancroftian Filariasis in Papua New Guinea |
There is continuing interest in understanding factors that facilitate the evolution and stability of cooperation within and between species . Such interactions will often involve plasticity in investment behavior , in response to the interacting partner's investments . Our aim here is to investigate the evolution and stability of reciprocal investment behavior in interspecific interactions , a key phenomenon strongly supported by experimental observations . In particular , we present a comprehensive analysis of a continuous reciprocal investment game between mutualists , both in well-mixed and spatially structured populations , and we demonstrate a series of novel mechanisms for maintaining interspecific mutualism . We demonstrate that mutualistic partners invariably follow investment cycles , during which mutualism first increases , before both partners eventually reduce their investments to zero , so that these cycles always conclude with full defection . We show that the key mechanism for stabilizing mutualism is phase polymorphism along the investment cycle . Although mutualistic partners perpetually change their strategies , the community-level distribution of investment levels becomes stationary . In spatially structured populations , the maintenance of polymorphism is further facilitated by dynamic mosaic structures , in which mutualistic partners form expanding and collapsing spatial bubbles or clusters . Additionally , we reveal strategy-diversity thresholds , both for well-mixed and spatially structured mutualistic communities , and discuss factors for meeting these thresholds , and thus maintaining mutualism . Our results demonstrate that interspecific mutualism , when considered as plastic investment behavior , can be unstable , and , in agreement with empirical observations , may involve a polymorphism of investment levels , varying both in space and in time . Identifying the mechanisms maintaining such polymorphism , and hence mutualism in natural communities , provides a significant step towards understanding the coevolution and population dynamics of mutualistic interactions .
Investigating factors that promote cooperation is one of the main topics in evolutionary biology [1] , [2] . Cooperation , a costly act that provides benefit for a partner [3] , [4] , is widespread in nature [5]–[7] and has been essential in shaping our biosphere [8] , [9] . The basic dilemma of intraspecific cooperation [10] also applies to interspecific mutualism [2] , [5]: while both partners of such interactions would be better off helping each other , a cheater that accepts help without reciprocating will have higher fitness and thus spread in the population [11]–[14] . Cheating consistently committed by one partner can shift a mutualistic interaction into parasitism [15] , as corroborated by observations in ant–plant mutualisms [16]–[18] or mycorrhizal mutualisms [19] , [20] . Despite the underlying dilemma being similar , interspecific cooperation differs from intraspecific cooperation in several key features . In interspecific cooperation , the interaction is under the control of two separate genomes , the evolutionary success of strategies in one species directly depends on the strategies in its partner species [21] , [22] rather than on those on its own species , and the spread of a successful strategy in one species does not automatically result in the spread of a matching strategy in the other . Another consequence of partners belonging to different species is that one important mechanism promoting cooperation , kin selection [1] , [2] , cannot play a role . Furthermore , in many mutualisms , the partners occupy different niches [5] , and are thus not in direct competition with each other . For all these reasons , models of intraspecific cooperation do not cover the specificities of mutualisms , so that mechanisms promoting mutualism have to be explored and identified separately [14] , [22] . Knowing the costs and benefits of a mutualistic interaction is fundamental for understanding its ecology and evolution [13] , [23] . Commonly studied examples are nutritional mutualisms , such as mycorrhiza [24]–[26] or rhizobia [27] , and other forms of symbiosis , including endosymbiosis [9] . However , these interactions are often not described by a single discrete event , but involve the long-term , often continuous , exchange of goods ( such as in rhizobia–plant interactions ) [28] , [29] . Quantifying the effective costs and benefits of these recurrent , and often reactive or conditional , exchanges is more complicated . For example , experiments found that the volume of nitrogen-containing substances provided by the nitrogen-fixing bacteria ( such as ammonium , aspartate , or alanine ) is increased by the concentration of oxygen and carbohydrates ( such as succinate or glutamate ) provided and controlled by the host plant [30] , [31] . In turn , from the perspective of the plant , higher nitrogen supply via fixation can enhance plant metabolism [27] , [32] , which can translate into higher carbohydrate supply to the symbiont [28] . Many studies have revealed similar mechanisms for the conditional exchange of nutrients ( such as phosphates and carbohydrates ) in mycorrhizal symbiosis [19] , [33]–[35] . Such long-term ( even lifelong ) associations allow partners continuously to adjust their investments into the mutualistic interaction [36] . Individuals may increase or decrease rewards in response to increased or decreased services received from a partner [18] , [28] , [34] , [37]–[39] . This iterative reciprocation throughout an interaction obviously involves phenotypic plasticity of the traits involved in the interaction [40] , [41] and offers a control mechanism between the partners [42] . Akin to reaction norms , which describe how the environment can affect a genotype's expression [41] , the rule of reciprocation can be described by an interaction norm [40] , which thus characterizes the expression of a trait as a function of the interacting partner's strategy . In spite of the biological importance of , and the wealth of information available for , interspecific cooperation , the evolutionary dynamics of mutualism are far less understood [13] , [14] . Moreover , among models of mutualism , few concentrate on the evolutionary dynamics of interactions on the individual level when there is continuous feedback between the partners [42] , as captured by the concept of partner fidelity feedback [1] , [11] . One of the few existing models addressing this challenge is the one proposed by Doebeli and Knowlton [43] , which is among the three most cited evolutionary models in the mutualism literature ( along with biological market models [44]; and models of geographic mosaic theory of coevolution [45] ) . In their individual-based model , each individual's strategy is characterized by two values: the so-called initial offer and the reward rate . The initial offer amounts to an unconditional or fixed investment in the mutualistic interaction , whereas the reward rate quantifies a conditional or variable component , which determines how an individual's investment depends on the payoff it gained from its current partner in the previous round . This distinction is well founded in the biology of mutualistic interactions . For example , in mutualistic interactions involving ants defending their mutualistic partners from predation , as in the case of ants and lycaenid butterfly larvae [46] or aphids [14] , both partners can adjust their investments by providing less nectar or less tending . There is also an unconditional initial investment in many interactions , which is required for establishing an interaction with a partner before evaluating its quality as a mutualist [14] . Examples include honeydew droplets or volatile substances from tentacle organs to attract partners [17] or chemical compounds released by plants in mycorrhizal or rhizobial mutualisms [27] . Moreover , creating an interface for physical contact sometimes requires high investments from both parties before an exchange of nutrients can commence [47] . Doebeli and Knowlton [43] concluded that population structure or spatial confinement is essential for stabilizing mutualisms . They elegantly demonstrated that without the facilitating effect of space , mutualistic investments vanish from the populations . Nevertheless , the specific role of spatial structure and the differences in the dynamics of mutualism in spatially structured and well-mixed populations need to be still more deeply understood . Moreover , Doebeli and Knowlton's conclusion regarding the necessity of spatial population structure was based on a single example . Reviews of the mutualism literature [13] , [14] , [38] have therefore debated the importance of space in stabilizing mutualism , and independent theoretical studies [37] could not corroborate the necessity of space for stabilizing mutualism . What are the causes for this apparent discrepancy ? Are mutualisms really unstable in the absence of spatial structure ? Our aim here is to unravel the role of space in the evolutionary dynamics of mutualism and to provide a platform for connecting model results with experimental findings .
Each individual's strategy for interacting with individuals from the other guild is specified by two ( non-negative ) quantitative adaptive traits: an unconditional investment , determining the initial offer to be made to a partner , and a conditional investment , determining the reward rate according to which investment received from a partner are reciprocated . Thus , the strategy of Mutualist A is given by the pair ( ) , and the strategy of Mutualist B is given by the pair ( ) . The initial offer is an unconditional and fixed investment into the mutualistic interaction , whereas the reward rate determines how the investment changes depending on the last payoff gained from the interaction with the current partner . Payoffs are calculated through an iterative procedure , based on a fixed number of iterations , or interaction rounds . Following Doebeli and Knowlton [43] , we use rounds . Before the first iteration , the payoffs of all individuals are set to zero . Below we consider the investments made , costs incurred , benefits received , and payoffs accrued by a mutualist with strategy interacting with a mutualist with strategy . In the first iteration , the investment is simply given by the trait , . In every subsequent iteration , the investment is determined by a linear reactive strategy , where is the net benefit , or payoff , obtained in the previous iteration by strategy interacting with strategy ( see below for further details on how partners are chosen ) . Investments are always non-negative: if they would be negative , they are set to zero . The payoffs are calculated from the investments made by the individuals of Mutualist A and Mutualist B . Each investment implies a cost for the donor and a benefit for the receiver , Accordingly , the payoff from one iteration of the interaction iswhere and , respectively , are the investments of the focal individual and of its partner in round [43] . Total payoffs are obtained by summing payoffs over all rounds of the mutualistic interaction , . Compared to traditional game theoretical models , for which the benefit-to-cost ratio is given by ( benefit divided by the cost of cooperation ) , for the current model , it is much harder to define the benefit-to-cost relationship , because of the nonlinear benefit function and the complex iterated nature of the game . It is therefore helpful to examine an approximation for infinitesimally small investments: in this case , the benefit function simplifies to . We can then consider the benefit-to-cost ratio in this limit , which gives . This simple expression serves as an upper bound: for higher investments , the nonlinearity of benefits causes the benefit-to-cost ratio always to fall below . Hence , for our model , a higher benefit-to-cost ratio means a higher product of the two parameter values for the benefit function compared to the parameter value for the cost function . In the spatial model , the focal individual and its closest neighbors ( we use the Moore neighborhood with ) compete for the focal site . In the well-mixed model , we randomly draw as competitors individuals from the focal individual's whole population . We employ either of two update rules . With “best takes over” updating , which was also used by Doebeli and Knowlton [43] , the individual with the highest payoff replaces the focal individual [43] , [48] , [49] . This implies that , if no competitor has a higher payoff than the focal individual , the later stays unchanged . If two individuals have the same payoffs , the winner is randomly chosen between them . With “pairwise comparison” updating , a random competitor ( interacting with individual ) replaces the focal individual ( interacting with individual ) with probability , depending on their payoff difference [50] , [51]; for scaling the strength of selection , we use . Both rules belong to the class of so-called death–birth updating processes [51] . The two traits can mutate independently with probability per update . The mutant trait value is drawn from a normal distribution , with a mean equaling the current trait value and a given variance . Doebeli and Knowlton [43] assumed that the standard deviation of this normal distribution is a given percentage ( ) of the current trait value . This assumption implies that the coefficient of variation ( ) is constant; thus , for smaller trait values the resultant variance is smaller than for larger trait values . Accordingly , when a trait value approaches , its mutational variance also approaches . This means that trait values can essentially get “stuck” close to . To evaluate the consequences of this effect , we also consider models in which the mutational standard deviation is kept fixed ( ) . In our model , updates occur per generation , where is the population of Mutualist A and Mutualist B . In the spatial model , is the width and height of the square lattice ( we consider values , , , and ) . For each update , we choose an interacting pair of Mutualist A and B . In the spatial model , the chosen individuals that occupy matching sites on the two lattices , whereas in the well-mixed model , they are randomly drawn from the two lattices . With synchronous updating , all individuals are updated at once , while with asynchronous updating , randomly chosen individuals are updated . Unless mentioned otherwise , we use asynchronous updating . Each update starts with an update of the payoffs of the involved individuals , followed by competition among them . We initialize the model dynamics with two homogeneous populations with both trait values close to ( , unless indicated otherwise ) , implying that individuals are not mutualistic . We also consider different initial conditions , with one or both of the traits set to higher values ( chosen from the interval ) . We then run the dynamics for generations ( unless otherwise indicated ) , which is a time horizon chosen to be long enough to detect the main dynamical trends for all considered model settings .
As a first step , we determine best-response equilibria of the mutualistic investments . The interspecific best response is defined here as the strategy of mutualist that has the highest payoff playing against strategy in the other mutualist guild , for , . Thus , investment strategies are in a best-response equilibrium , if and , if , that is , these strategies are the best responses to each other . Incidentally , this implies , which highlights a similarity with the concept of Nash equilibrium in intraspecific games; in that case , a strategy simply is the best response to itself [52] . As an analytical derivation of the best-response function is not possible for our model , we calculate it numerically by fixing a strategy for Mutualist A , and then scan the two-dimensional strategy space of Mutualist B for the strategy that yields the highest payoff to Mutualist B . We find that the best response to no investment is no investment , , which therefore is a best-response equilibrium . The intuitive explanation is simple: when a partner does not reciprocate , the best strategy is not to invest in that partner . Furthermore , as our numerical investigations reveal , , i . e . , no investment by both mutualists ( , , , and ) , is the only best-response equilibrium of our model . Analyzing the local stability around this equilibrium , we find two types of local best-response dynamics . The equilibrium is locally stable [53] , but strategies converge there only if they start out below a threshold level of reciprocation ( gray lines in Figure 1A and B ) . Using the same approximation as Killingback and Doebeli [54] for small investments , we find that this threshold is determined by the slopes of the benefit and cost functions at zero investment , [53] , [54] , with and for our model . Thus , when starting out below , best-response strategies converge to the no-investment equilibrium , whereas when strategies start out above , best responses lead to an increase in investment levels . To understand the latter behavior , we consider the global best-response dynamics , which gives us full information about the coevolutionary changes we must expect in mutualistic investment strategies . For this , we start from the initial strategy of one mutualist , determine the optimal strategy of its partner , then again determine the optimal strategy of the first mutualist , and so on ( Figure 1A ) . Interestingly , this shows that the no-investment strategy is not always the best response: above the thick gray line in Figure 1A , the best response differs from and causes reciprocation to increase in the first step ( Figure 1A ) . After a few best-response steps , however , the dynamics always converge to the no-investment equilibrium , which is thus a global attractor of the best-response dynamics . In conclusion , when the best-response dynamics start out below the threshold line , these dynamics will directly lead to the no-investment equilibrium , whereas when the initial strategies lie above the threshold line , the best-response dynamics will cause investments to increase temporarily , before bringing them down to eventually ( Figure 1A ) . Throughout this study , we refer to the latter behavior as the investment cycle . We now show how our insights from the best-response analysis above extend to individual-based evolutionary dynamics under low degrees of polymorphism ( Figure 1B , C ) . We find that when started below a threshold line ( thick gray line in Figure 1B ) , the evolutionary dynamics monotonically converge to no investment . Above that line , the evolutionary dynamics temporarily drive investments up ( Figure 1B and C ) . After these investments have passed a maximum , they monotonically converge to zero . In other words , we again find a “boom and bust” kind of investment cycle . We can obtain the threshold of increasing investments ( thick gray line in Figure 1B ) in the limit of vanishing polymorphism . In that case , the selection pressures on the investment traits are given by , where is the focal mutualist ( A or B ) , is the other mutualist ( B or A , respectively ) , is the focal trait ( or ) , is the strategy of a mutant in , ( ) is the resident strategy in , and is the resident strategy in . Positive selection pressures mean that mutants with increased trait values have higher payoffs than the current resident , and therefore can spread in the population . This kind of evolutionary dynamics is still simplified compared with an individual-based model; it yields good approximations only when population dynamics are sufficiently faster than trait dynamics ( ) , so mutants mostly encounter monomorphic populations , and when mutational steps are sufficiently small ( ) , so the derivatives defining the selection pressures carry sufficient information for predicting the fate of all arising mutants . The obtained threshold line ( thick gray line in Figure 1B ) is the unstable part of the evolutionary isocline for trait , along which the selection pressure on passes and thus changes sign . For small investments , and thus for , this isocline is located at . We find that our aforementioned results regarding the investment cycle are robust . First , we can approximate the underlying individual-based evolutionary dynamics by adaptive dynamics theory [55] , using the selection pressures defined above . For low mutation probabilities and standard deviations , this approximation is accurate . Second , we can consider “best takes over” updating in an individual-based model with low degrees of polymorphism , and third , we can use a modification of this updating , so that the most successful mutant is drawn from a circle around the resident traits ( for this , we sample random combinations of mutants from a circle of radius , where and denote the trait differences between mutants and residents , and choose the one mutant with the highest payoff ) . All three of these variants yield results in agreement with those summarized above . The emergence of the investment cycle can best be understood by examining the gradual coevolution of the two investment traits . Evolution starts from a slightly reactive state ( exceeds the threshold ) , and both the unconditional and conditional investments first increase , as selection pressures are positive on both traits . Higher reactivity ( resulting from higher conditional investment ) selects for a higher initial investment , because making a high initial investment then yields high returns already from the first round of the interaction; consequently , individuals obtain higher payoffs by making high investments already from the beginning of the interaction . While the initial investment increases , the selection pressure for the conditional response decreases and finally reverses , as a strategy investing a large amount in the beginning and increasing investments even further in the following rounds may end up overinvesting . Eventually , after the reactivity evolves close to ( falling below ) , the initial investments also evolve to . In this final phase , with very little reactivity , the dynamics simply resemble those of the continuous prisoner's dilemma , in which no cooperative investments can be maintained without additional mechanisms . Next , we introduce a measure that helps us monitor the evolution of strategies along the investment cycle , and that suitably reduces the two-dimensional trait space , spanned by the two investment traits , to one dimension . For this purpose , we define cycle phases , and for Mutualist A and B , respectively , so that these monotonically increase along the investment cycle . As shown by the small arrows in Figure 1B , these phases are determined by the direction of the selection gradients ( , ) acting on the traits ( , ) of Mutualist with . Depending on the signs of and , we can distinguish four quadrants of , measured clockwise relative to the positive vertical axis . In the first quadrant , ; in the second quadrant , ; in the third quadrant , ; and in the fourth quadrant , . The boundaries between these phases thus correspond to evolutionary isoclines , i . e . , to curves in the trait space along which the selection pressure vanishes for either one of the two traits . Phase I is characterized by positive selection pressures on and , so that both trait values and investment levels increase ( phase I in Figure 1B and 1C , ) . In phase II , while trait still increases , trait declines , as the selection pressure on is negative ( phase II in Figure 1B and 1C , ) . In phase III , more exploitative strategies , which invest less and thus gain more , are favored by selection , so that investment levels evolve to , as traits and both decline ( phase III in Figure 1B and C , ) . For low degrees of polymorphism , selection gradients in the fourth quadrant rarely occur; here , trait would grow while trait would shrink ( ) . Figure 1 shows that the cycle phase derived from the selection gradients acting on Mutualists A and B adequately indicates the direction of evolutionary dynamics along the investment cycle , in monomorphic populations or in populations with a low degree of polymorphism . In the next step of our analysis , we allow higher degrees of polymorphism . As shown in the previous section , when mutation probability and/or mutation variance are low , the polymorphic spread among strategies remains narrow , as the two mutualist communities evolve along the investment cycle ( Figure 2A , left-hand side ) . However , there is a sharp transition in the outcome as the variety of mutants increases . Above a critical supply of strategy diversity , the two polymorphic populations can perpetually maintain strategies that on average are mutualistic and that lead to a high and stable level of average payoff ( Figure 2A , right-hand side ) . This stable community-level mutualism still implies cyclic behavior , as the averages of both investment traits gradually evolve along the investment cycle also in populations with higher degrees of polymorphism ( Figure 2B–D ) . Importantly , however , with the increase of mutational variability , this cyclic behavior becomes perpetual , as the evolutionary dynamics no longer collapse to zero investments at the end of phase III . The increase of mutational variance not only affects the polymorphic spread of strategies along the investment cycle , but also its shape and amplitude ( observe the decrease of cycle amplitude with the increase of in Figure 2B–D ) . To understand these effects of mutational variability , we need to appreciate , first , how and why polymorphism arises , and second , what it implies for the community-level stability of mutualistic interactions . For this , it is helpful again to consider phases and selection gradients along the investment cycle . Individuals in polymorphic populations encounter a diverse set of strategies , so the selection gradients they experience need to be determined accordingly: , where is the focal individual , the sum extends over all individuals of the other mutualist , and the parenthesis encloses the expected payoff of a mutant offspring of individual with strategy . These selection gradients , shown as arrows in Figure 3A , help us understand the emergence of cyclic dynamics and phase polymorphism . At the beginning of the investment cycle ( phase I ) , mutations will typically cause some symmetry breaking between the investment strategies of the two mutualists , while the polymorphic spread among strategies still remains narrow ( Figure 3A , Panel 1 ) . Once a trajectory reaches phase II , the selection pressures on the two traits approach , making them especially susceptible to neutral drift , and thus enhancing the symmetry breaking and polymorphic spread ( observe the diversity of gradient angles in Figure 3A , Panel 2 ) . Similar mechanisms operate at the boundary between phases II and III , where selection pressures become weak on the traits ( Figure 3A , Panels 3 and 4 ) . Finally , when a trajectory reaches phase III ( Figure 3A , Panel 5 ) , the strongest effect occurs: when traits evolve close to the boundary that separates trait combinations corresponding to phases III and I ( see the partially overlapping black and thick gray lines in Figure 1B ) , mutations can take the two traits across the boundary , from phase III to I and back . Such a jump across the boundary changes the sign of the selection gradient for both of the traits for at least one of the mutualists ( Figure 3A , Panels 6 and 1 ) . This causes recurrent transitions across the boundary , so trajectories linger at this boundary , which naturally increases their polymorphic spread . Once a sufficient proportion of the population has thus traversed the boundary , the investment cycle is retriggered ( Figure 3A , Panel 1 ) . Notice that the degree of phase polymorphism varies along the investment cycle . It typically decreases in the middle of phases I and III ( observe how all gradients are pointing in essentially just one direction in Figure 3A , Panels 1 and 5 ) , and increases at the boundaries between the phases ( observe the diversity of gradient angles in Figure 3A , Panels 2 , 3 , 4 , 6 ) . With further increases of mutational variability , even higher levels of polymorphism develop , so strategies diffuse across all phases of the investment cycle . In highly polymorphic populations , as a consequence of this phase spread , selection pressures become widely different for different parts of the populations; hence , a wide variety of strategies becomes established , ranging all the way from phase I to phase IV ( Figure 3B ) . Competition between strategies and strategy pairs shapes the phase distribution of the community ( Figure 3B and C ) , as individuals or pairs with a competitive disadvantage fade out from the community . These losing strategies are typically those at the beginning of phase I or at the end of phase III ( or ) , as well as strategy pairs with an extreme asymmetry or exploitation ( at the tails of the distribution in Figure 3C ) . The two most successful , and hence most frequent strategies , are conditional cooperators ( akin to Tit-for-Tat strategies , with high and low ; Figure 3B , peak close to ) and unconditional cooperators ( akin to All-C strategies , with high and low ; Figure 3B , peak close to ) . The result of competition within the polymorphic populations is thus a diverse cast of interactions , ranging from strongly mutualistic ( central peak in Figure 3C , corresponding to both mutualists being in the same phase ) to exploitative ( two lateral peaks in Figure 3C , corresponding to one mutualist being in phase I and the other in phase III , or vice versa ) . We highlight that the results depicted in Figure 2A are essentially invariant for lower mutation rates ( not shown ) . The intuitive explanation is that such lower mutation rates have two effects . First , there are fewer mutations occurring in any given time window , which by itself would hinder the retriggering of the investment cycle . Second , the pace of directional evolution slows down for such lower rates , so the trait distribution lingers for longer periods at the phase boundaries , which by itself would facilitate the retriggering of the investment cycle . These two effects essentially cancel , leaving the critical levels of mutational variability needed for retriggering the investment cycle largely independent of the considered mutation rates . By contrast , this retriggering is strongly affected by the benefit-to-cost ratio . When the benefit-to-cost ratio is large , a smaller amount of mutational variability suffices to maintain strategy polymorphism and thus community-level mutualism ( Figure 2A , compare upper and lower pairs of curves ) . Moreover , localized interactions and limited dispersal promote strategy polymorphism , by creating a spatial mosaic structure , as we will describe in more detail in the next section . Accordingly , in spatially structured populations the transition to stable community-level mutualism appears at lower mutational variability ( Figure 2A , compare gray to black pairs of curves ) . In spatially structured mutualistic communities with local interactions and limited dispersal , strategy polymorphism occurs together with a dynamic spatial mosaic structure ( Figure 4A ) of spatially abutting “bubbles . ” Here we use the term “bubble” to describe spatial clusters that are compact and contiguous , contain similar strategies on the inside and different ones on the outside ( Figure 4B ) , and grow gradually in size from a small core before disappearing through a sudden collapse ( Figure 4D ) . For the most part , there is a strong correspondence between Mutualist A and Mutualist B with regard to the position and extent of spatial bubbles , and typically the corresponding strategies are asymmetric , giving one species a higher payoff than the other ( compare the shading of corresponding sites in Figure 4A ) . To fully understand the role of spatial population structure in stabilizing mutualism , we thus have to understand the composition of , and the ongoing dynamics among and within , these bubbles . As we saw in the previous section , symmetry breaking and phase polymorphism along the investment cycle can lead to asymmetry between the mutualistic partners . This emerging asymmetry is strongly exaggerated by the spatial bubble structure , as competitively inferior strategies vanish quickly , while exploiting strategies are likely to attempt an invasion of adjacent bubbles , supported by their high payoffs . Hence , spatial bubbles are often composed of exploiting strategies and their exploited partners . The degree of asymmetry and its trend among bubbles can vary , and this diversity of asymmetries provides the stage for bubbles expanding , splitting , or collapsing in various ways ( Figure 5 ) . If a strategy can outcompete that of a neighboring strategy , its successful invasion further depends on its maintaining its competitive superiority in the invaded patch . Hence , invasion success can be determined by considering the relative payoff of the invader before and after invasion . To demonstrate this , we consider the interface between two bubbles as the site where strategy pairs can meet . We can then analyze all possible dynamics at this interface . We label the two bubbles so that Mutualist A has a higher payoff ( > ) in bubble 1 than in bubble 2 . We can neglect cases with equal payoffs in the two bubbles , as these do not change the configuration of strategies , and thus do not contribute to the bubble dynamics . Relations between the payoffs in bubble 1 , at the interface , and in bubble 2 ( Figure 5 ) can thus be represented as , , , or for Mutualist A , and by , , , or for Mutualist B , yielding seven distinct situations: , , , , , , . Corresponding to Figure 5 , the upper row in these stacked symbols refers to Mutualist A and the lower row to Mutualist B , while the first column refers to the payoff comparison between bubble 1 and the interface , and the second column to the interface and bubble 2 . The first four cases , in which Mutualist A in bubble 1 always has a higher fitness than Mutualist A at the interface ( ) , correspond to replacement dynamics ( Figure 5A–D ) involving unidirectional invasion ( Figure 5A ) , partner swapping ( Figure 5B ) , catalyzed invasion ( Figure 5C ) , and coexistence of the two bubbles ( Figure 5D ) . In the last three cases , Mutualist A has a higher payoff at the interface than in either bubble ( ) . We can interpret these situations as having a bubble with a strategy pair formed at the interface that can spread in both directions . The resultant new pairs of adjacent bubbles will then behave in one of the ways covered by the first four cases above . Thus , the four cases shown in Figure 5A–D and discussed in more detail in that figure's caption cover all possible dynamics between the two bubbles . The most relevant case for preserving phase polymorphism occurs when the two exploiting strategies of two adjacent bubbles , having high payoffs within their bubble , can both enter the intervening interface , but their exploited partners cannot ( Figure 5D ) . Then , these exploiting strategies meet at the interface , but are mismatched: by interacting with each other , they experience lower payoffs compared to when they interact with their original partners . Consequently , neither bubble can invade the other ( under deterministic updating ) , and an insulating boundary layer forms between them ( Figure 5D ) . These effects yield a relatively static mosaic structure , in which most bubbles are separated by insulating boundary layers , which in turn fosters the long-term coexistence of a diverse set of strategies in both mutualist guilds . Nevertheless , the resulting mosaics are eventually not immune to the degradation of mutualism within bubbles , as strategy pairs evolve along the investment cycle , making the mosaic structure ( if only slowly ) dynamic . The dynamics of the spatial mosaic are governed by evolutionary processes that maintain a balance between the expansion or emergence and the contraction or collapse of bubbles . First of all , inside a bubble , evolution drives strategies through the investment cycle . Sooner or later , this stochastic evolution changes the strategy pairs of two neighboring bubbles in such a way that their boundary layer ( Figure 5E , gray area ) loses its insulating property , thus enabling invasion from one bubble to the other ( Figure 5E , white or black areas ) . Although this invasion itself is a rapid process , the evolutionary time that is required for the insulating boundary layer to break down is usually long . Counteracting mechanisms can restore the loss of diversity resulting from bubble collapse: this happens through the emergence of new bubbles as a result of successfully established mutations ( if such a mutant conquers only part of a bubble ) or through the fragmentation of existing bubbles . In the latter case , mutants occurring within the insulating boundary layer are able to invade either one of the adjacent bubbles . Through this invasion , the mutant opens up the boundary and can catalyze the invasion of strategies from the neighboring bubble ( similar to how Mutualist A1 catalyzes the invasion of B1 , as in Figure 5C ) . Thus , while the two neighboring bubbles could originally not invade each other , this becomes possible through the mutant serving as a “third party . ” The resultant expansion of the invading bubble can then split the invaded bubble ( Figure 4D , from fifth the column onwards ) , upon which the two resultant parts can take separate evolutionary paths . In summary , strategy diversity , and thus , community-level mutualism , is efficiently stabilized through the formation of an insulating boundary layer between bubbles of strategies . This would result in a static mosaic structure , which , however , becomes dynamic as strategies evolve along the investment cycle . The invasions resulting from these stochastic evolutionary processes establish a balance between the emergence and collapse of bubbles that maintains a level of polymorphism in a more efficient way than the corresponding well-mixed mutualistic community . The diversity threshold for community-level mutualism is thus more easily passed in spatially structured communities ( Figure 2A ) . In the light of our understanding of the evolution and stability of interspecific cooperative investments established in the previous sections , we can now revisit , complement , and extend the pioneering investigation of Doebeli and Knowlton ( DK ) [43] . Specifically , we can present a more comprehensive and systematic overview of the evolution of interspecific cooperative investments under various relevant conditions ( Figure 6 ) . First , we present the necessary condition that no mutualistic investments can evolve below , that is , when the benefit-to-cost ratio falls below and mutualism is thus not advantageous ( see thin black lines with white background in Figure 6 ) , which in general holds under all conditions . Also , the transition to high stable levels of mutualistic investments is sharper for higher benefit-to-cost ratio ( rows with in Figure 6 ) . Second , besides the synchronous updating that was originally applied by DK in the spatial model , we also consider asynchronous updating , and find that mutualism is unstable for a wider range of benefit-to-cost ratios ( compare third and fourth columns in Figure 6 ) . Third , we test different competition rules under asynchronous updating , such as the pairwise comparison rule instead of the best-takes-over rule used by DK , and we can conclude that outcomes are essentially unaffected by these different rules ( not shown ) . Fourth , we consider two methods for generating mutant traits . In one version , as in the original DK model , we draw the trait values of mutants with a constant coefficient of variation , so that the mutational standard deviation linearly increases with the current trait value ( row labeled “ constant” in Figure 6 ) . With this approach , mutational variance for small trait values becomes very low , equaling when trait values equal . Here we examine a different assumption , according to which mutational variance is constant for all trait values ( rows labeled “ constant” in Figure 6 ) . Comparing the results , we arrive at an important conclusion , namely , that the qualitative contrast reported by DK between “gradual evolutionary decay of cooperation” in the well-mixed model and “long term persistence of mutualism” in the spatially structured model is restricted to the assumption that mutations have a constant coefficient of variation ( “ constant” in Figure 6 ) . Notably , our investigation reveals that relaxing this assumption , by assuming constant and medium levels of mutational variance , mutualism robustly evolves for all kinds of populations structures and update rules ( compare “ constant” vs . “ constant” in Figure 6 ) . We note here that our results are qualitatively robust to changes of the number of iterations during the mutualistic interaction , which we have confirmed by examining shorter ( ) and longer ( ) interactions instead of ( not shown ) . Fifth , we demonstrate that below a threshold level of mutational variability no stable levels of mutualistic investments evolve in the community , and this threshold is considerably lower for higher benefit-to-cost ratios and for spatially structured populations ( Figure 2A ) . In summary , we conclude that spatial population structure has a beneficial effect on the evolution of stable high interspecific investment levels , but this effect is only apparent for constant , for small mutational variability , and for small benefit-to-cost ratios . By changing these conditions , mutualism can be stable both in well-mixed and in spatially structured communities . Finally , our results enable us to understand the mechanisms underlying the evolution and stability of mutualism in greater depth . In particular , we can highlight several new mechanisms for stabilizing mutualism , both in well-mixed and spatially structured populations . First and foremost , we have presented the investment cycle ( Figure 1 ) , which drives the main coevolutionary dynamics of traits , and underlies the evolution of cooperative investments levels in mutualist communities . While the cyclic dynamics can already be seen in DK's results ( e . g . , in their Figure 2 ) , here we have put it into the spotlight of our analysis . Second , we have demonstrated the spreading of the investment cycle phases , and have revealed the diverse ways strategies interact when they are in different phases , both within and between mutualist guilds ( see Figure 2 and Figure 5 ) . Thus , in contrast to the interpretation of DK , that mutualism is maintained by a balance between the “continual reoccurrence of mutualistic types” and then a “gradual evolutionary decay of cooperation” ( DK ) , we show that mutualism is mainly stabilized by phase polymorphism along the investment cycle ( Figures 2 , 3 , and 4 ) . The emerging phase polymorphism and underlying strategy diversity recurrently retrigger evolutionarily increasing levels of cooperative investments in some portion of the community ( phase I in Figure 3A , B ) , a process that is essential for maintaining high investment levels . Third , while DK already noticed “considerable genetic heterogeneity , ” here we have demonstrated the existence of sharp diversity thresholds . In addition , we can provide an explanation for the differences in the stability of mutualism under constant vs . constant , as well as under low vs . high . These differences derive from the fact that if phase polymorphism is largely lost , it is much harder to retrigger the investment cycle ( by attaining trait combinations above ) once the community has reached the last phase of the investment cycle ( or in other words , once phase I has vanished from the community ) . For similar reasons , any mechanism that prevents or counteracts the generation of phase polymorphism will increase the chances of losing mutualism . Whereas DK suggested that “for mutualism to evolve , … spatial structure… is required , ” here we have reversed that logic , by clarifying that strategy diversity and phase polymorphism along the investment cycle are responsible for maintaining high investment levels and that the only effect of spatial structure is to enhance this polymorphism . Fourth , we have studied spatial mosaic dynamics by analyzing replacement dynamics in the mutualist populations to understand why spatial structure increases polymorphism ( Figure 5 ) . Combining our insights with DK's intuitive concept of the “boiling sea of mutualistic bubbles , ” our investigation reveals the complex dynamics among bubbles and the key role of the insulating boundary layer in preserving polymorphism in spatially structured populations . Fifth , this enables us to understand why asynchronous updating makes mutualism less stable , as it more easily shatters insulating boundaries , promotes asymmetric and uncoupled invasion of the two mutualists among bubbles , and hence makes the homogenization of bubbles more likely . Sixth , while our results explain why spatial structure is helpful in maintaining mutualism , they also demonstrate that space itself does not always suffice , and neither always is necessary , to maintain community-level mutualism .
Our analysis has shown that when our model community exhibits a stable mean level of mutualism , it is invariably characterized by a high degree of polymorphism , and that mutualism persists only if this polymorphism is maintained . Without strategy polymorphism , the evolutionarily stable state of the system is a community consisting only of full defectors ( no investment ) . This is because full defection is the best response to itself , and no mutant investing more can spread in either species [53] . No other strategy pairs are best responses to each other , so there are no other evolutionarily stable states . However , there are many pairs of strategies that can spread in initially non-mutualistic populations ( Figure 1 ) ; above a threshold of reciprocating investments , evolution guides these strategies through an investment cycle , which eventually always results in no investment . Hence , mutualistic investments in our model are fundamentally unstable [56] , never reaching finite stable levels even though they may initially be increasing . This means that in our model evolution without strategy polymorphism can only temporarily lead to high mutualistic investments before these eventually collapse again . Similar dynamics have been observed in studies investigating the evolution of intraspecific cooperative investments in different game-theoretical models . For example , in the prisoner's dilemma game with discrete reactive strategies [4] , [57] , the Tit-for-Tat strategy ( TFT ) can oust the always-defect strategy ( All-D ) , but the always-cooperate strategy ( All-C ) can spread in a population adopting TFT , which in turn enables invasion by All-D . As mentioned in the Results section , TFT is similar to strategies with high conditional investments in our model , whereas All-C is similar to strategies with dominating unconditional investments . Without the continuous reestablishment of strategies by mutations , models with discrete strategies may also end up in a fully defective state [4] , [57] . In contrast to these results for communities with low degrees of polymorphism , when sufficient polymorphism is generated , community-level mutualism becomes stable . For this to happen , the degree of polymorphism needs to exceed a threshold ( Figure 2A ) . Even in well-mixed populations , stochastic symmetry breaking in the interactions , combined with phase polymorphism along the investment cycle , leads to the emergence of a high variety of strategy pairings and payoffs ( Figure 3B , C ) . While evolution drives individual strategy pairs toward exploitation ( and , ultimately , to zero investment ) , the exploited partner has a fitness disadvantage: consequently , the highly exploitative pairs are replaced by more mutualistic pairs , which show less asymmetry in their payoffs ( Figure 3C ) . These pairs are typically composed of strategies from phase I of the investment cycle ( Figure 3 ) . Our findings thus indicate that the interspecific interactions exist in a state of permanent flux , fluctuating between different investment levels at the individual level . In contrast , the mean level of mutualistic investment remains positive ( and for high degrees of polymorphism becomes stable ) , shaped by a balance between two components of selection: strategy evolution along the investment cycle and replacement of overly exploited strategies and of mismatched strategy pairs . Spatial population structure further facilitates the stability of mutualism by playing a key role in supporting polymorphism ( Figure 4 and 5 ) . However , limited dispersal and localized interaction alone do not maintain mutualism , but only when they work together with mutational variance that is high enough to sustain a critical level of polymorphism ( Figure 2A ) . In spatially structured populations , the interaction among emerging , invading , and collapsing spatial bubbles of strategy pairs creates a dynamic spatial mosaic , by means of which different phases of the investment cycle are distributed among bubbles . As a result of this phase spread , the evolutionary dynamics of mutualistic investments become decoherent among the different bubbles . This is called phase diffusion , which in general occurs when stochastic drift reduces correlations among the cycle phases of subsystems ( here the spatial bubbles ) comprising a system ( here the full community ) . Consequently , among bubbles , the community shows a wide but stable range of interaction types along the mutualism–exploitation continuum ( Figure 7D ) . We have shown how mechanisms operating at the interface of these bubbles effectively prevent the spatial homogenization of strategies across the community by creating insulating boundary layers ( Figure 4B and 5D ) that in turn sustain the spatial mosaic structure of bubbles together with the implied strategy polymorphism . We emphasize here that the mechanism of spatial population dynamics and interaction between neighboring bubbles described here fundamentally differs from previously described roles of spatial structure in models of intraspecific cooperation ( in which , in a nutshell , cooperation is maintained by the clustering of cooperators and by their spatial segregation from defectors [49] ) . One implication of our study is that the diversity of mutualistic strategies in natural communities may be high not only because of mutation and recombination , or inherent species diversity , but also as a product of selection pressures resulting from the complex dynamics of mutualistic interactions occurring within polymorphic mutualist guilds . We note here that , based on our model assumptions , the two mutualist populations may correspond not only to single species interacting pairwise , but also to two interacting mutualist guilds [58] , that is , a collection of species with the same function in mutually beneficial ecological interactions . Thus , strategy polymorphism in our model can relate not only to variation within , but also across , species . Indeed , growing empirical evidence suggests that polymorphisms of mutualistic investment strategies are common in nature [19] , [21] , [22] , [27] , [34] , [58]–[66] , even on small spatial scales [67] , [68] . Many studies suggest that microbial populations and communities are often structurally and genetically more diverse [67] , [69] , considering both type or strain richness and/or genetic diversity [68] , than what can be explained by local host diversity [70] . Also the effectiveness of rhizobia , such as their ability to form nodules and their capacity to fix nitrogen , varies greatly within species , and naturally , between species [27] , [58] , [71] , [72]; similar conclusions hold for the performance of mycorrhizal interactions [26] , [65] , [73] . This diversity amounts to a high variety of investment strategies; in other words , less mutualistic types coexist with more beneficial mutualists in natural communities [6] , [19] , [21] , [22] , [27] , [34] , [36] , [71] . Mutualistic interactions are known to shift along the mutualism–exploitation continuum in response to changes in environmental factors [7] , [19] , [58] , [59] , [74] , [75] . For example , many nutritional mutualisms , including mycorrhizal or rhizobial mutualisms [13] , are highly beneficial for host plants as long as the resource provided ( e . g . , phosphorus , nitrogen , or copper ) is absent from the environment , but can become harmful ( implying that costs exceed benefits ) when that resource no longer is a limiting factor [2] , [38] , [19] , [76] . This not only underscores the importance of reactive strategies for modeling mutualism , but also offers one explanation for the spatial mosaic structures observed that involve different genotypes , as well as the different local coevolutionary states shaped by different local selective forces [45] , [65] , [77]–[79] . Our findings highlight that spatial environmental heterogeneity is not required for the creation of such mosaics , as the mechanisms unraveled here provide a testable alternative explanation of these empirical observations , even in the complete absence of spatial environmental heterogeneity . Mutualisms can also be unstable on a much longer time scale , and there can be a diversity of mutualistic , parasitic , and free-living variants within higher taxa . The phylogenetic analysis of mycorrhizal and free-living homobasidiomycetes suggests that there have been several transformations between symbiotic and free-living forms [80] . The gain and loss of mutualistic traits thus seems to be relatively common on an evolutionary time scale , a finding that is in good agreement with our model-based results . The model by Doebeli and Knowlton [43] has been criticized for being applicable only to organisms with high cognitive abilities [13] . Yet it has been demonstrated that even the simplest unicellular organisms are capable of complex reactive behavior . For example , it has been shown that , in response to the concentration of received nutrients and synthesized products , hosts and symbionts can control their exchange of material simply by controlling fluxes through their various metabolic pathways [31] , regulating and operating proteins [29] , [81] , or inducing structural changes at the host–symbiont interface [28] , [82] . Such adjustments closely resemble the reactive , conditional nature of interspecific cooperative investments , as captured by the model we have analyzed here . However , there are assumptions in our model that can and should be relaxed and modified in subsequent studies . For example , in the model studied here , one individual always interacts with only one partner . Yet , in the majority of examples in nature , one host can interact with several symbionts at the same time , and vice versa [12] , [13] , [27] . The square grid we have considered here might be suitable if both mutualists have limited dispersal and are thus spatially confined . Of course , one or both partners can be more motile , without well-mixed populations being the immediate result . Moreover , different interaction topologies could be considered , such as small-world or scale-free networks . Finally , partners in the current model have similar life cycles , which might apply only to a very limited number of biological examples; thus , assuming life-cycle asymmetries could be an important extension of the current model [43] . Our study has shown that the community-level picture of mutualism can be quite different from that at the individual level . As the mean outcome can provide misleading or poor information , a full understanding of the involved ecological and evolutionary dynamics requires an appreciation of the distribution of outcomes [40] . In line with various recent studies , we have demonstrated that mutually beneficial interspecific interactions should not be conceived only as ( ) interactions , but as a continuous range of symmetrically beneficial ( ) , asymmetrically beneficial ( ) , and explicitly exploitative or parasitic ( ) interactions [36] ( Figures 3 and 7 ) . Our results thus suggest that it is not enough to monitor average fitness advantages , as localized individual interactions may be situated at different points along the mutualism–parasitism continuum ( Figure 7 ) , and may also shift in time . The long-standing notion of mutualistic interactions being static is thus becoming extended as new findings , both experimental and theoretical , broaden our understanding . Consequently , exploitation and mutualism are not always strictly separate types of interactions , but in many instances may serve as boundaries of a continuous distribution of interactions between two mutualist guilds . This distribution reflects not only population or guild-level variation , but also dynamical changes of interactions occurring on ecological and evolutionary time scales . | Mutualistic interactions between species are often best understood as gradually adjustable reciprocal investments made continuously or iteratively between participants . Prime examples are the mycorrhizal and rhizobial mutualisms so strongly affecting the productivity of plants . When such interactions are described by continuous reciprocal investment games , participants adjust their investments plastically in response to their mutualistic partner's most recent investment . Although common sense suggests that such conditional or reactive behavior provides a potent defense against exploitation , our comprehensive model analysis reveals that the coevolution of investment strategies will often instead induce instability and decay of mutualistic interactions . We also identify several factors that can prevent this decay . First , mutualisms can be stably maintained if the investment strategies of participants are sufficiently diverse . Second , if participants are limited in their movements , the formation of dynamic spatial mosaic structures promotes strategy diversity and thereby facilitates the maintenance of mutualism . These ecological and evolutionary dynamics result in communities with a diversity of interaction types , ranging from mutually beneficial to exploitative , and varying both in space and in time . | [
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
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] | 2012 | Strategy Diversity Stabilizes Mutualism through Investment Cycles, Phase Polymorphism, and Spatial Bubbles |
The differential modulation of agonist and antagonist binding to opioid receptors ( ORs ) by sodium ( Na+ ) has been known for decades . To shed light on the molecular determinants , thermodynamics , and kinetics of Na+ translocation through the μ-OR ( MOR ) , we used a multi-ensemble Markov model framework combining equilibrium and non-equilibrium atomistic molecular dynamics simulations of Na+ binding to MOR active or inactive crystal structures embedded in an explicit lipid bilayer . We identify an energetically favorable , continuous ion pathway through the MOR active conformation only , and provide , for the first time: i ) estimates of the energy differences and required timescales of Na+ translocation in inactive and active MORs , ii ) estimates of Na+-induced changes to agonist binding validated by radioligand measurements , and iii ) testable hypotheses of molecular determinants and correlated motions involved in this translocation , which are likely to play a key role in MOR signaling .
Evidence of allosteric modulation of receptor signaling by cations was first presented in the literature for opioid receptors ( ORs ) . Specifically , sodium ( Na+ ) and lithium , but not other monovalent or divalent cations , were shown to enhance receptor binding of opiate antagonists and to reduce the binding of opiate agonists , thus altering ligand properties in vivo [1] . Over the course of years , the original hypothesis that Na+ stabilizes an inactive conformation of the receptor was extended to several other G protein-coupled receptors ( GPCRs ) [2] , but it was only recently supported by various ultra-high resolution crystal structures of inactive GPCRs , including that of δ-OR [3] . In this structure , Na+ was found to be bound at an allosteric site through coordination with two water molecules as well as receptor residues N1313 . 35 , S1353 . 39 , and D952 . 50 ( superscripts refer to the Ballesteros-Weinstein generic numbering scheme [4] ) . Notably , we observed a similar ion coordination in molecular dynamics ( MD ) simulation studies [5] of Na+ binding from the bulk solvent to the inactive μ- and κ-OR ( MOR and KOR , respectively ) crystal structures embedded in a hydrated 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine ( POPC ) /10% cholesterol lipid bilayer and at physiological concentrations of Na+ . Unlike their inactive crystal structures , experimental structures of active GPCRs ( e . g . , those of MOR [6 , 7] ) , show a collapsed ion binding site which likely results in weaker Na+ binding affinity and consequent ion departure from the receptor . How Na+ migrates into the cytosol has recently been described in the literature for the active state of the M2 muscarinic receptor [8] . One conclusion of that study is that Na+ egress into the cytosol occurs without significant energy barriers when the D2 . 50 is protonated and another fairly conserved residue , Y7 . 53 , is in an upward configuration . Notably , the intracellular egress of Na+ is further facilitated by the formation of a hydrated pathway connecting the orthosteric ligand binding pocket to the G protein binding site , a feature that has also been seen in experimental structures ( e . g . , those of active MOR [6 , 7] ) as well as in recent simulation studies of GPCRs such as the adenosine A2A receptor [9] and the serotonin 5-HT1A receptor [10] . Herein , using a combination of molecular dynamics ( MD ) , Markov State Models ( MSMs ) , and machine learning tools , we provide , for the first time , estimates of the timescales associated with Na+ translocation through the TM helix bundle of either active or inactive MOR conformations embedded in an explicit POPC/10% cholesterol lipid bilayer at a physiological concentration of Na+ . Moreover , we present complete free-energy profiles of Na+ movement through these receptor states , estimates of Na+-induced changes to agonist binding validated by radioligand measurements , and testable hypotheses of the most important underlying motions and molecular determinants involved in Na+ translocation .
The three-dimensional spatial density distributions of Na+ across inactive or active MOR , the latter with either a charged or a protonated D1142 . 50 , were obtained from the corresponding combined trajectories of unbiased MD and US simulations ( see the Methods section for details ) . As shown in Fig 1 , clear differences exist in the spatial distribution of Na+ across the active and inactive MOR , with the inactive receptor structure ( Fig 1a ) exhibiting several more localized high-density regions for the ion ( red hotspots ) compared to active MOR ( Fig 1b and 1c ) . Perhaps the most striking difference between the active and inactive MOR is the continuous Na+ density distribution observed through the entire TM bundle in the active , but not the inactive , MOR . To generate testable hypotheses of the most important molecular determinants involved in Na+ translocation among residues close to high ion densities , we extracted lists of residue pairs ( S3 Table ) whose minimum heavy atom distance fluctuations had a correlation larger than 0 . 6 to the most dominant tIC0 and tIC1 components . Graphs illustrating these selected residue pairs on the inactive or active MOR crystal structures are shown in S2 Fig . These highly correlated inter-residue distance fluctuations to tIC0 and tIC1 ( e . g . , those involving the conserved , functionally important , NPxxY ( x ) 5 , 6F motif in rhodopsin-like GPCRs ) can be interpreted as the main contributors to the slowest ( and most important ) motion modes in the simulated inactive and active MOR systems . For instance , out of a total of 176 residue pairs that are highly correlated to tIC0 in the simulated inactive MOR ( S3 Table ) , Y3367 . 53 , F343H8 and N3327 . 49 are involved in 89 , 58 , and 30 pairs , respectively , while other residues are only involved in 3 or fewer pairs . Notably , disruption of the interaction between rhodopsin residues corresponding to positions Y3367 . 53 and F343H8 in MOR has been shown to lead to rhodopsin activation [14] . Overall , the simulated active MOR systems exhibited a reduced number of highly correlated inter-residue distance fluctuations to the most dominant tIC0 and tIC1 components compared to the inactive simulated MOR ( S3 Table ) , although most of them still involved residues of the NPxxY ( x ) 5 , 6F motif . While N3327 . 49 also stood out as a main contributor to the most important motions of the two simulated active MOR systems , Y3367 . 53 and F343H8 were found not to be involved in the most important motions in the active MOR system with a protonated D1142 . 50 . Notably , recently published MD simulations of three different rhodopsin-like GPCRs [9] revealed that three distinct rotamer conformations of the conserved Y7 . 53 residue were correlated with the occlusion or opening of a continuous intrinsic water channel characteristic of an inactive or active conformational state of the receptor , respectively . The observed larger number of relevant tIC0 and tIC1 components involving Y3367 . 53 in the inactive MOR compared to the active receptor ( S3 Table ) suggests that Na+ translocation to the cytosol in inactive MOR is hindered by several residues that have to move in a concerted manner to enable Y3367 . 53 to change its rotameric state and allow opening of the continuous intrinsic water channel . The highly correlated inter-residue distance fluctuations to tIC1 are very different in the simulated inactive and active MOR systems ( S3 Table ) . While in the inactive MOR all highly-correlated pairs to tIC1 involve the conserved F2896 . 44 residue in concerted motion with TM1 , TM2 , and TM3 residues , in the active MOR simulated with a charged D1142 . 50 , roughly half of the pairs are between residues located in the orthosteric ligand binding pocket ( e . g . , Y1483 . 33 , Y1493 . 34 , and N1503 . 35 ) and residues at the allosteric Na+ binding site ( e . g . , A1132 . 49 and D1142 . 50 ) . In contrast , in the active MOR simulated with a protonated D1142 . 50 , all but one highly-correlated pairs to tIC1 involve the so-called “rotamer toggle switch” W2936 . 48 in concerted motion with TM3 , TM4 , TM5 , and TM7 residues . Notably , many of these residues have a known functional role [15] , which , based on the above , might be due to their contribution to Na+ translocation . Using the MEMM framework ( see Methods ) , we calculated the thermodynamics of Na+ translocation through both the inactive and active MOR . The derived free-energy profiles of inactive and active MOR are reported in Fig 2 . As seen in this figure , Na+ binding at its allosteric site ( Na+ z-coordinate = 0 ) is ~6 kcal/mol more energetically favorable in the inactive MOR compared to the receptor active state at pH = 7 ( up to ~11 kcal/mol compared to active MOR with a neutral D2 . 50 ) . This means that in the inactive MOR , the Na+ ion needs to overcome a significantly higher free-energy barrier to egress to the cytosol compared to the active MOR ( especially the state with a neutral D2 . 50 , where the free energy barrier for the translocation is the lowest ) , making ion egress less likely to occur in an inactive MOR structure . We also built MSMs to elucidate the kinetics of Na+ translocation in the inactive or active MOR . For this , we not only present the results of MOR simulated with either a charged or protonated D1142 . 50 , but also those of a mixed model system at pH 7 that would capture , in principle , protonation changes of the residue ( see Methods for details ) . Details of the MEMM construction and its validation are provided in the Methods section and S3 Fig , respectively . The microstates of the Markov model for each system were divided into a small set of metastable states , which were labeled according to the Na+ position relative to the receptor as “extracellular” , “bound” , or “cytoplasmic” states . The transition networks between these states are shown in Fig 3a for the inactive MOR , and in Fig 3b and 3c for active MOR with charged and protonated D1142 . 50 , respectively . S4 , S5 and S6 Tables report the transition times between these metastable states for inactive MOR , active MOR with charged D1142 . 50 , and active MOR with protonated D1142 . 50 , respectively . The observed larger number of Na+ bound states in the inactive MOR ( Fig 3a ) indicates a more rugged energy landscape than in the active receptor with multiple local minima that can trap the Na+ ion . In order to obtain kinetic estimates of Na+ translocation that can be compared to experiments , we coupled the Markov model obtained from TRAM to a bulk state with a fixed ion concentration , and calculated Na+ transition times from extracellular bulk to bound states ( Na+ binding; Fig 4a ) , from bound to extracellular states ( Na+ dissociation; Fig 4b ) , and from bound to intracellular states ( Na+ egress; Fig 4c ) at different concentrations ( see the Methods section ) . As expected , the Na+ binding kinetics is highly concentration-dependent while the Na+ dissociation and egress kinetics are virtually independent on concentration . While the timescale of Na+ binding to the receptor is similar for the different receptor conformations , the timescales of Na+ dissociation and egress differ between inactive and active MOR . Specifically , based on the “mixed model” at pH 7 , Na+ dissociation from the active MOR is estimated to take ~0 . 3 ( 0 . 2 , 2 . 0 ) μs , which is significantly faster than in the inactive MOR ( ~5 . 5 ( 3 . 0 , 8 . 0 ) μs ) . This is consistent with the prediction that a Na+ bound state in the active MOR has significantly higher free energy compared to the inactive MOR . The Na+ egress timescales are estimated to be of the order of hundreds of milliseconds to ~60 s depending on whether the active MOR has a protonated or charged D1142 . 50 , whereas Na+ leaves the inactive MOR state in ~100 seconds , suggesting that Na+ can more easily migrate to the cytosol in an active MOR with a protonated D1142 . 50 than in the inactive MOR . Notably , these predicted timescales are similar to the experimentally derived lifetimes of GPCR/G protein complexes [16 , 17] . From the concentration-dependent MSM model , we estimated the Na+ binding affinity to be 23 mM ( from 14 mM to 50 mM with errors ) at a ligand-free , inactive MOR or significantly lower ( 850 mM; from 650 mM to 1 . 3 M with errors ) at active MOR models with charged D2 . 50 ( S4 Fig ) . The corresponding values for the active models with a neutral D2 . 50 and the model at a constant pH = 7 . 0 are in excess of 1 M . To explain Na+ modulation of ligand binding to MOR , we applied the two-state receptor theory ( see Methods ) , and used the free-energies obtained from the aforementioned models to calculate sodium-induced stabilization of the receptor inactive state relative to the active one . Given that antagonists bind with equal affinity to both active and inactive conformations of the receptor , this model is consistent with the observation that antagonist bound fractions are not affected by ion concentrations . In the case of a full agonist , we can quantitatively estimate the extent to which its bound fraction is modulated by the ion concentration . Specifically , assuming a binding affinity of ~4 nM [18] for MOR agonist DAMGO at the active conformation of the receptor , we estimated the relative bound fraction of DAMGO to active MOR at constant pH = 7 as a function of the ion concentration as described in the Methods section , and report these results in Fig 5 , together with experimental values obtained by radioligand binding experiments . The calculated percent reduction in agonist binding at increasing ion concentrations ( solid line in Fig 5 ) by this simple model is in good agreement with the experimental data , and indicates that ligand binding modulation is triggered by the stabilization of the inactive conformation of the receptor in the presence of sodium , which affects orthosteric ligand binding affinity . The model estimates that 60 mM of Na+ ( with a confidence interval between 50 and 150 mM ) are required to achieve a 50% reduction of DAMGO binding , in excellent agreement with the experimental value of 60 mM . For sodium concentrations above 200 mM , the simple model employed here slightly underestimates the effect of sodium , suggesting that direct interactions with the ligand or double occupation of the receptor by multiple ions might play a role at high ionic strength . Saturation experiments ( see S5 Fig ) are also in reasonable agreement with this simple allosteric model . In the presence of sodium ( 25 mM ) , the affinity of 3H-DAMGO does not appreciably change ( KD 1 . 8 and 0 . 89 nM for control and sodium conditions ) while the Bmax is lowered by 50% ( 333 fmol/mg protein to 156 fmol/mg protein ) . This is consistent with a shift of the receptor to an inactive state from an active one . In summary , the combination of MD , MSMs , and machine learning tools is powerful in that it provides , for the first time , both kinetic and thermodynamic estimates of Na+ translocation through active or inactive MOR states in a membrane mimetic environment and at a physiological concentration of Na+ . The results provide quantitative support to the notion that Na+ can more easily egress from the cytosol in an active MOR with a protonated D1142 . 50 than in an inactive receptor , as well as testable hypotheses of the most important underlying motions and molecular determinants involved in Na+ translocation .
The active and inactive MOR systems were modeled based on the respective crystal structures ( PDB entries 5C1M and 4DKL , respectively ) . The missing loop between TM5 and TM6 in 4DKL was added as described previously [14 , 19] . For the active MOR , the N-terminal region preceding residue M65 was removed and the missing residues on the helix 8 at the C-terminus was rebuilt using the Prime package included in the Schrödinger’s suite [20] to ensure both simulated systems had identical primary sequences . Both inactive and active MOR models were embedded in a POPC and cholesterol bilayer with a mixing POPC:cholesterol≈9:1 ratio and an area of 79×79 Å2 . The membrane and protein were then neutralized and solvated with explicit TIP3P water and a NaCl concentration of 150 mM . The entire simulation systems contained approximately 60 , 000 atoms with a volume of 79×79×106 Å3 and were assembled using the CHARMM-GUI webserver [21] . The CHARMM36 force field [22 , 23] was used to model protein , lipids and ions and all molecular dynamics ( MD ) simulations were carried out using the NAMD software package [24] . Both inactive and active MOR systems were simulated in the NPT ensemble using the Nosé-Hoover Langevin piston method [25 , 26] to maintain the pressure at 1 atm , and a Langevin thermostat to maintain the temperature around 310 K . Long-range electrostatic interactions were calculated using the Particle-Mesh Ewald ( PME ) algorithm [27] . The van der Waals interactions were switched off gradually between 10 and 12 Å . Periodic boundary conditions were applied to the simulation boxes , and an integration time step of 2 fs was used for all simulations . After a multi-step equilibration with gradually decreasing harmonic constraints on lipid and protein heavy atoms , following the CHARMM-GUI membrane builder equilibration protocol , an additional 60 ns unconstrained equilibration run was carried out . The last snapshot of this equilibration run was used as a starting point for umbrella sampling simulations . US simulations were carried out to enhance sampling of the Na+ ion translocation across the membrane through the interior of the TM helix bundle of MOR . A bias was applied to the Z-coordinate of a reference sodium ion , parallel to the normal vector of the membrane surface and measured from a reference position ( Z = 0 ) corresponding to the location of the Na+ allosteric binding site defined as the center of mass of the Cα atoms of residues D1142 . 50 , N1503 . 35 , W2936 . 48 , and Y3267 . 43 ( the superscripts refer to the Ballesteros-Weinstein numbering scheme [4] ) . For each active and inactive MOR system , 157 starting configurations for US windows , uniformly spaced by 0 . 5 Å , were selected to cover the entire TM region of the protein and part of the bulk solvent ( from Z = +40 Å in the extracellular region to Z = -35 Å in the intracellular region ) . The reference sodium ion was slowly pulled from one window to another . A harmonic biasing potential with a force constant of 10 kcal/ ( mol·Å2 ) was applied along the Z variable to constrain the Na+ ion in the center of each window . A flat-bottom cylindrical constraint with radius of 15 Å was applied to avoid insufficient sampling of the reference ion in the bulk solvent and to prevent the disturbance by other ions . To prevent the drift of MOR in the membrane , a harmonic potential was applied to the head groups of POPC lipids with a force constant of 10 kcal/ ( mol·Å2 ) . Each US window was run for at least 7 ns ( in addition to 1 ns of equilibration run ) or until the relative entropy [28] reached values below 0 . 2 for an average simulation length of 11 . 8 ns and a maximum simulation length of 100 ns . To assess the kinetic behavior of the ion across the protein , we also carried out a set of unbiased simulations , starting from the last frame of each umbrella sampling window and running additional 12 ns of simulation . The same simulation settings as the biased simulations were used , while all restraint potentials on the sodium and the lipids were removed . 3D density distribution maps were built using a grid-based approach . First , global translational and rotational motions of the protein in all simulation trajectories were removed by fitting to a reference structure using the protein Cα atoms root mean square deviation ( RMSD ) . Then , a 3D rectangular grid covering the entire TM domain of the protein and a small part of the bulk solvent was built using a uniform grid spacing of 1 . 25 Å in all directions and amounting to a volume of 30×30×70 Å3 , and a total of 32 , 256 grid points . The 3D bins defined by the grid were used to obtain the reweighted probability for the reference ion’s 3D position using the data from both umbrella sampling and unbiased simulations and the weighted histogram analysis method ( WHAM ) estimator implemented in the python library PyEmma [29] . The reweighted density values were normalized to the averaged density values of the grid points in the bulk solvent ( 0 . 01 particles/nm3 ) . The results were saved as a dx grid file , which was subsequently rendered as layered 3D color maps using the visualization software Pymol [30] . Sodium-interacting protein residues across the TM bundle were selected using the active MOR with charged D1142 . 50 as a reference structure , which has sodium density registered over a larger area compared to the three simulated MOR systems . A total of 105 residues within 4 . 4 Å from density grid points with values at least 7 times larger than the bulk region density were identified using an in-house python code . The pair-wise distances between residue heavy atoms as a function of time were extracted using PyEmma and used as input features for tICA [31] . tICA uses a linear transformation to map the original input data r ( t ) onto a new set of time-lagged independent components ( see reference [31] for details ) . These components are correlated and their autocorrelation is maximal at a fixed lag-time [31] . Notably , the most dominant components span a linear subspace that contains the slowest , and therefore most relevant , degrees of freedom . These components can therefore provide the dimensional reduction that is necessary for the construction of a MSM [31 , 32] using PyEmma . A lag time of 0 . 1 ns was used for our tICA calculations and the first two most dominant independent components , tIC0 and tIC1 , were used to describe the protein dynamics portion of our final MSM , which includes the Na+ motions as well . The residue pairs whose minimum heavy atom distance fluctuations exhibited a larger than 0 . 6 correlation ( the absolute value of the Pearson correlation coefficient ) relative to tIC0 and tIC1 were considered the slowest ( and most important ) motion modes . We projected trajectories of the inter-residue minimum distance fluctuations between heavy atoms of the 105 selected residues near Na+ high-density regions onto the two most dominant independent components tICA0 and tICA1 with PyEmma and calculated the free energy landscapes of all three simulated MOR systems i . e . , active MOR with either charged or protonated D1142 . 50 , and the inactive MOR . We included tICs extracted from both unbiased MD simulations and umbrella sampling to construct the combined free energy landscapes sampled in both sets of simulations . The combined landscapes were then subjected to k-means clustering using PyEmma . Different k values were selected depending on the complexity of the individual free-energy landscape . Specifically , we chose k = 5 , 7 and 4 for the inactive MOR , active MOR with charged D1142 . 50 , and active MOR with protonated D1142 . 50 MOR , respectively . The resulting cluster centers were then used to assign the frames in trajectories from the unbiased and umbrella samplings simulations individually . In order to optimally utilize both sets of unbiased MD and umbrella sampling simulations to derive equilibrium and kinetic properties of the system , we used the recently published transition-based reweighing method ( TRAM ) [11] to estimate a MEMM . This approach aims at overcoming the limitations of standard MD simulations ( e . g . , insufficient sampling of transition states ) by integrating the results of enhanced sampling techniques such as umbrella samplings [11 , 33] . Since the Na+ binding , dissociation and egress from the TM bundle does not only depend on the Na+ movement alone , but also on the protein conformational dynamics , we designed a MEMM that takes both aspects into account . The trajectories from both the biased and unbiased simulations were discretized into microstates encoding the Na+ position , as well as the slowest protein degrees of freedom captured by tICA , which are represented by the transitions between the conformational states on the free energy landscape in the space of tIC0 and tIC1 approximated by the k-mean clusters of the landscape . Specifically , microstates were defined based on ( i ) the z coordinate of the Na+ ion , which was divided into 100 bins covering the entire range of the umbrella sampling , and ( ii ) N k-means clustering of the two slowest tICA0 and tICA1 components , leading to a total of N×100 microstates , with N = 6 , 5 , and 4 for the inactive MOR , active MOR with charged D1142 . 50 , and active MOR with protonated D1142 . 50 , respectively . We label the microstates as ( z , i ) , with 1 ≤ z ≤ 100 and 1 ≤ i ≤ N . The discretized trajectories were used together to obtain a maximum-likelihood TRAM estimation of the transition matrix in the unbiased thermodynamic state via the python package PyEmma [29] . A lag time of 200 frames ( or 0 . 4 ns ) , selected based on the convergence of the implied time scales , was used for TRAM . The free-energy of the microstates G - ( z , i ) was obtained from the steady-state probabilities from the Markov model estimated from TRAM . In order to obtain the one-dimensional free energy profiles of the active and inactive MOR systems as a function of z , we integrated out the tICA dimensions via the relation: G ( z ) = - k B T l n [ ∑ i = 1 N e x p ( - G - ( z , i ) k B T ) ] ( 1 ) Next , we calculated the timescales employed by the reference sodium ion to bind to and dissociate from the extracellular side of the receptor , as well as to egress from the cytoplasmic side . Considering the much higher Na+ concentrations in the extracellular region compared to the cytoplasmic side of the cell membrane under physiological conditions and the resulting unfavorable membrane potential , no ion binding from the intracellular side was taken into account . For the kinetics estimates , sodium trajectories that crossed the periodic boundary between two unit cells along the z-direction were split in order to remove artificial transitions between microstates close to the intracellular side and the extracellular side ( i . e . z~0 and z~100 , respectively ) without actually going through the receptor . A kinetic model was constructed by first assigning all microstates from the MSM estimated from TRAM into a small number of metastable states ( Npcca = 9 , 5 and 7 for inactive , active with charged D2 . 50 and active with neutral D2 . 50 MORs , respectively ) by using the Perron-cluster cluster analysis [34] ( PCCA+ ) . A Npcca × Npcca transition matrix between the Npcca metastable states was then estimated using the Hummer-Szabo method [35] , and a Markov model estimated from this transition matrix using the PyEMMA package . Furthermore , metastable states were clustered into three groups depending on whether Na+ , occupied the intracellular , bound , or cytoplasmic regions , respectively . Specifically , microstate ( i , z ) was assigned to the cytoplasmic state if 1 ≤ z ≤ 10 . A microstate belonging to one of the bins with 30 ≤ z ≤ 60 was considered to belong to the ion bound state , whereas microstates with 90 ≤ z ≤ 100 were considered to belong to the extracellular state . Each of the Npcca metastable states was then assigned to one of the three groups ( intracellular , bound , or cytoplasmic ) if 90% of its microstates belonged to such a group . In order to assess the effect of D2 . 50 protonation on sodium binding , we constructed a kinetic model that combines the properties of the sodium binding to the receptor with charged and neutral D2 . 50 , which we label with indices α and β , respectively . Specifically , to establish a common reference state for the active model of MOR , we assumed that the pKa of D2 . 50 in the absence of Na+ nearby is pKa ≈ 9 [13] , which corresponds to a free-energy difference of ΔG0 ≈ 2 . 6 kcal/mol at physiological pH ≈ 7 . 0 . Using this shift , we expressed the free energy of the microstates z of the MOR system with charged D2 . 50 as ε α ( Act . ) ( z ) = e α ( Act . ) ( z ) + Δ G 0 ( 2 ) where e α ( Act . ) ( z ) are the free-energies obtained from the simulation trajectories of the MOR system with charged D2 . 50 . We then obtained the thermodynamic properties for the combined system as a function of the ion position as exp ( - ε ( Act . ) ( z ) k B T ) = exp ( - e α ( Act . ) ( z ) + Δ G 0 k B T ) + exp ( - e β ( Act . ) ( z ) k B T ) ( 3 ) where e β ( Act . ) ( z ) are the free-energies obtained from simulation trajectories of the MOR system with neutral D2 . 50 , while the probability of observing a charged sidechain as a function of the ion position is: p α ( z ) = 1 1 + exp ( − e β ( Act . ) ( z ) − e α ( Act . ) ( z ) − Δ G 0 k B T ) = 1 1 + π β ( Act . ) ( z ) π α ( Act . ) ( z ) exp ( Δ G 0 k B T ) ≡ exp ( − Δ G ( z ) k B T ) ( 4 ) We then modeled the rates for a fixed protonation state of D2 . 50 using the kinetic models obtained from analysis of the simulation run on MOR with either a charged or neutral D2 . 50: K ( z , i , x ; z ′ , i ′ , x ) = K x ( z , i ; z ′ , i ′ ) ( 5 ) where x = α , β ( i . e . , charged and neutral D2 . 50 states , respectively ) , while z and i indicate , as before , the position of the sodium ion and the conformational microstate of the protein . Following the evidence from NMR [36] we modeled the protonation process for given z and i with a constant deprotonation rate ( off-rate ) koff K ( z , i , β ; z ′ , i ′ , α ) = δ ( z , z ′ ) δ ( i , i ′ ) k off ( 6 ) Based on published work [36] , we used koff = 106 s−1 . The protonation state that ensures that the free energy difference between the two protonation states is preserved is therefore K ( z , i , α ; z ′ , i ′ , β ) = δ ( z , z ′ ) δ ( i , i ′ ) k off e x p ( Δ G ( z ) k B T ) ( 7 ) while δ ( z , z′ ) δ ( i , i′ ) guarantees that only protonation events for a fixed ion position and side-chain conformations are possible . Finally , the rates between the PCCA macrostates a and b defined above were approximated as: K ( a , x ; b , x ′ ) = ∑ j , z ′ ∈ b ∑ i , z ∈ a π x ( i , z ) K ( z , i , x ; z ′ , i ′ , x ′ ) ( 8 ) The matrix K was used to calculate kinetic rates for the constant pH = 7 . 0 model of the active MOR system . In order to address the effects of sodium at physiological concentrations , we supplemented the Markov model by coupling it to reference states corresponding to the intracellular and extracellular bulk with constant sodium concentrations [Na+]IC and [Na+]EC , respectively . We modeled the kinetics of ions across the receptor stepwise [37] , as follows: Na EC + R k EC + ⇌ k EC - ( Na ∙ R ) EC k i j ⇌ k j i Na R k j l ⇌ k l j ( Na ∙ R ) IC k IC - ⇌ k IC + Na IC + R ( 9 ) where NaEC and NaIC indicate a cation in the extracellular or intracellular space , respectively and parenthesis indicate the formation of an encounter complex , defined as the presence of an ion within a cylinder of radius r0 = 1 . 5 nm in the extracellular or intracellular region of the bulk . Rates kab were obtained from the estimated Markov model , while the rates for the formation of the encounter complexes , k EC + and k IC + , were obtained from the 3D Smoluchowski expressions for a given ion diffusion constant DNa ≅ 20 nm2/μs and bulk concentration , k EC + = 4 π D Na r EC [ Na + ] EC ( 10 ) where rEC is encounter complex radius . The rates of ion dissociation from the encounter complex , k EC - and k IC - determine the capture probabilities , γEC and γIC defined as the probability of an ion to take part in the binding reaction , conditional on having formed the encounter complex: γ EC = k EC - k EC - + ∑ j k i j ( 11 ) A similar equation for γIC was defined for the intracellular encounter complex . The values of γ were estimated [38] from the unbiased simulations described in the text . The Na+ binding , dissociation , and egress rates were calculated by coarse-graining the transition matrix corresponding to the stepwise kinetic model and defined , respectively , as the rate of transition between the extracellular unbound and the bound state , between the bound and the extracellular unbound state , and between the bound and the intracellular unbound state . We employed a minimal two-state model for receptor activation , which resulted in the same functional form as the operational Black-Leff model . Let τu and τb be the equilibrium constants between the active and inactive states of the ligand-free and ligand-bound receptors , respectively , and let K and K⋆ be the binding affinities of the ligand to the inactive and active receptor states , respectively . Then the fraction of receptors bound to a ligand is: f b = [ L ] L 50 + [ L ] ( 12 ) where L 50 = K ⋆ 1 + τ u 1 + τ b ( 13 ) Notably , for antagonists , τu ∼ τb , and L50 does not depend on the equilibrium . For full agonists , on the other hand , τb ≪ τu and therefore L50 ≅ K⋆ ( 1 + τu ) . Thus , the percent change of the fraction of bound ligands at ligand concentration x = [ L ] / L 50 ( 0 ) when the sodium concentration changes from 0 to [Na+] is: Δ f b f b = f b ( [ Na + ] ) - f b ( 0 ) f b ( 0 ) = 1 - ρ ( [ Na + ] ) x + ρ ( [ Na + ] ) ( 14 ) where ρ ( [ Na + ] ) = L 50 ( [ Na + ] ) / L 50 ( 0 ) . While varying concentrations of sodium can also affect the affinity of ligands ( K⋆ ) , we posit , in agreement with the well-established assumption in the literature ( see , e . g . [2] and references therein ) , that the dominant mechanism of modulation was through changes in the stability of the active and inactive states of the receptor ( τu ) : ρ ( [ Na + ] ) ≃ τ u ( [ Na + ] ) τ u 0 ( 15 ) and we used the results from our simulations to estimate this ratio . Specifically , the kinetic models obtained from the TRAM estimation characterized the dynamics of two states of the receptor . If we denote with p i ( Ina . ) and with p i ( Act . ) the probabilities obtained for the steady-state of the two models , we can express the relative free-energies of all the states of the receptor as { ε i ( Ina . ) = - log p i ( Ina . ) ε i ( Act . ) = - log p i ( Act . ) - μ ( 16 ) where we measure energies in units of the thermal energy kT and μ is the activation free-energy of the receptor in the absence of sodium . Specifically , the fraction of receptors in the activated MOR state is f ⋆ = ∑ i e - ε i ( Act . ) ∑ i e - ε i ( Act . ) + ∑ i e - ε i ( Ina . ) = e - μ e - μ + Z ( Ina . ) / Z ( Act . ) ( 17 ) where we indicated with Z ( Ina . ) and Z ( Act . ) the partition functions obtained summing over all the states of the respective systems . Thus τ u = 1 - f ⋆ f ⋆ = Z ( Ina . ) e - μ Z ( Act . ) ( 18 ) which gives in the end: ρ ( [ Na + ] ) = ( Z ( Ina . ) Z ( Act . ) ) [ Na + ] ( Z ( Ina . ) Z ( Act . ) ) 0 - 1 ( 19 ) A bootstrapping procedure similar to the one described previously [11] was used to estimate the errors of free energy and transition times . For each simulation system , 12 bootstrap samples were obtained randomly selecting ( with repetitions ) unbiased trajectories for a total number of frames equal to 90% of the full sample . The resampled unbiased trajectories and the full set of umbrella sampling trajectories were then combined and used to construct individual MEMMs via TRAM . The transition times were estimated as the median of the mean first passage times calculated from individual bootstrap samples and the full sample . Confidence intervals were estimated as the differences from the 1st and 3rd quartiles . Binding studies were carried out using membranes from CHO cells stably transfected with the MOR-1 clone , as previously described [39] . Membranes ( 200 μg protein ) were prepared and binding assays carried out with 3H-DAMGO incubated at 25°C for 1 . 5 h in potassium phosphate buffer ( 50 mM , pH 7 . 4 ) with MgSO4 ( 5 mM ) in a volume of 500 μl . At the end of the incubation , the samples were filtered over glass fiber filters and binding determined by scintillation counting . In each experiment , samples were assayed in triplicate and specific binding defined as the difference between total binding and binding in the presence of levallorphan ( 10 μM ) . Studies looking at the effects of varying concentrations of NaCl utilized the indicated concentration of NaCl with 3H-DAMGO ( 1 nM ) . Values are the average of three independent replications of each experiment . | Notwithstanding years of research supporting the notion that μ-opioid receptor ( MOR ) function can be modulated by sodium ions ( Na+ ) , a complete understanding of Na+ translocation through the receptor and its effect on ligand binding at MOR requires additional information . Here , we use computer simulations to elucidate the energetics involved in sodium binding at inactive and active MOR , the timescales of sodium translocation through these receptor conformations , and the molecular determinants involved in this process . | [
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"... | 2019 | Kinetic and thermodynamic insights into sodium ion translocation through the μ-opioid receptor from molecular dynamics and machine learning analysis |
Correlations in local neocortical spiking activity can provide insight into the underlying organization of cortical microcircuitry . However , identifying structure in patterned multi-neuronal spiking remains a daunting task due to the high dimensionality of the activity . Using two-photon imaging , we monitored spontaneous circuit dynamics in large , densely sampled neuronal populations within slices of mouse primary auditory , somatosensory , and visual cortex . Using the lagged correlation of spiking activity between neurons , we generated functional wiring diagrams to gain insight into the underlying neocortical circuitry . By establishing the presence of graph invariants , which are label-independent characteristics common to all circuit topologies , our study revealed organizational features that generalized across functionally distinct cortical regions . Regardless of sensory area , random and -nearest neighbors null graphs failed to capture the structure of experimentally derived functional circuitry . These null models indicated that despite a bias in the data towards spatially proximal functional connections , functional circuit structure is best described by non-random and occasionally distal connections . Eigenvector centrality , which quantifies the importance of a neuron in the temporal flow of circuit activity , was highly related to feedforwardness in all functional circuits . The number of nodes participating in a functional circuit did not scale with the number of neurons imaged regardless of sensory area , indicating that circuit size is not tied to the sampling of neocortex . Local circuit flow comprehensively covered angular space regardless of the spatial scale that we tested , demonstrating that circuitry itself does not bias activity flow toward pia . Finally , analysis revealed that a minimal numerical sample size of neurons was necessary to capture at least 90 percent of functional circuit topology . These data and analyses indicated that functional circuitry exhibited rules of organization which generalized across three areas of sensory neocortex .
Transmission and processing of information in the brain is in large part determined by the connectivity between neurons [1] . The neocortical microcircuit hypothesis states that the neocortex is composed of repeated elements of a generalized circuit that are tweaked for specialization in each area [2] . Supporting this hypothesis , local synaptic connectivity in the neocortex is non-random and is at least partly determined by neuron location and class [2]–[12] . These rules imply that there is a probabilistic or partially stereotyped wiring diagram . The extent to which these rules generalize across the neocortex , however , is unclear . Analysis of neocortical microcircuit spiking activity in different brain regions has revealed common dynamical features [12]–[15] , suggesting that circuits may share similarities between regions . In this study , we use the spatiotemporal correlations of firing activity between neurons to generate functional wiring diagrams [15]–[19] . Modeling studies have shown a clear relationship between connectivity and neural firing [15] , [20]–[24] . This suggests that we can gain insight into the underlying structure and organization of cortical circuitry by analyzing the emergent dynamics of large populations of neocortical neurons . Here we employed high speed two-photon calcium imaging [25] to densely sample the spiking activity of up to 1126 neurons within a 1 . 1 mm diameter field of view , spanning multiple columns and layers in three different areas of the sensory neocortex . We then applied post-processing algorithms to detect spatiotemporal relationships between spiking neurons and modeled this activity as wiring diagrams , or graphs [15] . Graph theory is a useful technique to quantify network dynamics , and has been increasingly applied in the neural context to understand brain connectivity patterns [21] , [26] , [27] . One potential approach to identify invariant features of functional wiring diagrams within and between areas of cortex is to isolate graph isomorphisms . For example , the unlabeled graphs and are isomorphic when any two nodes and of are connected in if and only if that connection exists in . However , such an analysis currently remains intractable in graphs of sizes analyzed here , as the best known algorithm runs in polynomial time [28] . Perhaps more importantly , the organizational features of connectivity that have been described to date reflect probabilistic , rather than deterministic microcircuit architectures [5] , [8] , [9] , making it unlikely that connectivity patterns in the brain are formally isomorphic . In order to test the postulate that the organization of functional circuitry generalizes across the neocortex , we instead applied functions that are invariant to labeling of the nodes of the graph . In other words , if A is the adjacency matrix describing graph , we wanted to describe the function such that , where is the × permutation matrix [29] . In the context of our study , we aimed to identify features of a neuronal circuit wiring diagram that are invariant to the particular identities of the neurons . Thus , we characterized each neuron only by the connections it had with other neurons . While neurons and activation patterns between animals and regions may vary in their individual details , these abstract , global characteristics of circuit structure stay constant , even following the relabeling of the neurons . By investigating label-independent features , called graph invariants , we hoped to disregard features of the functional circuit that may be susceptible to over-fitting , and focus on features that are stable across slices and areas of the neocortex . Many graph invariants have been previously described , such as maximum degree and MAXCUT value [29] . Some particularly useful invariants include the graph eigenvalues and eigenvectors [29] , [30] . We apply these analyses to functional wiring diagrams generated from imaging data from three sensory neocortical areas to test the validity of a functional analogue to a generalized circuit architecture of the neocortex .
All procedures were performed in accordance and approved by the Institutional Animal Care and Use Committee at the University of Chicago . To foster reproducibility and fast development of future work based upon these results , we have published functional graph analysis tools under an open source , GPLv3 license , available here: https://github . com/ssgrn/GraphInvariantsNeocortex . All statistical analyses were performed with MATLAB ( MathWorks ) . Unless otherwise noted , data are presented as mean ± SD . All values in the text are in reference to the Pearson correlation computed with the command corrcoef . For nonparametric distribution comparison between the three sensory areas , the Kruskal-Wallis test ( KW-test ) was implemented via the kruskalwallis function . The nonparametric Komolgorov-Smirnov test ( KS-test ) , noted at use , was used to compare fitted distributions to data . The Komolgorov-Smirnov test were implemented using the command kstest2 . For tests of significance , was used as the cutoff . Algebraic connectivity and eigenvector centrality were computed using the MIT Toolbox for Network Analysis ( http://strategic . mit . edu/downloads . php ? page=matlab_networks ) . Graph figures were generated using the open source Python graph visualization tool NetworkX ( http://networkx . github . io/ ) . Circular variance was computed with the MATLAB Toolbox for Circular Statistics [32] . We compared our data to two null models: random topologies and -nearest neighbors topologies . Each random topology was formed by preserving the locations of neurons in a corresponding functional topology and then assigning a 0 . 5 probability of forming a directed edge between every neuron in the field of view . Each -nearest neighbors topology was formed by preserving the locations of neurons in a corresponding functional topology and then forming a directed edge from neuron A to neuron B if neuron B was one of -nearest neighbors of neuron A . In all analyses , we used .
To determine whether A1 , S1 , and V1 functional circuit wiring diagrams exhibited invariant features , we monitored neuronal activity in 43 slices from each region of the mouse neocortex ( 11 of A1 , 21 of S1 , and 11 of V1 ) using high speed multi-photon calcium imaging [15] , [25] , [31] . Spontaneous circuit activity requires intact excitatory amino acid transmission [15] , [33] , sufficient oxygenation [34] and corresponds to UP states within single neurons which comprise the functional circuit [15] , [35] . Previous reports have found that spontaneous activity delineates all of the possible multi-neuronal patterns within a sampled population and that a sensory input activates only a subset of these patterns [14] , [36] . By monitoring spontaneous activity in the imaged field of view , we hoped to maximize the number of pairwise correlations within the imaged populations . We imaged the flow of activity through large populations of neurons ( A1: 595±101 cells , S1: 704±157 cells , V1: 734±129 cells ) at the mesoscale in a two-dimensional circular imaging plane with a diameter of 1 . 1 mm that comprised multiple layers and columns with single-cell resolution ( Figure 1A ) . We confirmed activity was not biased to any one lamina and that our sampling was uniform across our field of view , since the amount of activity observed across all circuit events did not differ between layers ( , KW-test; see Methods for explanation of laminar identification ) . Because temporal resolution of multi-photon microscopy is compromised at these spatial scales , we used the heuristically optimized path scan technique [25] ( Figure 1B ) , which allowed us to achieve fast frame rates ( frame duration 86±17 . 7 ms ) that did not differ between regions ( , KW-test ) . We deconvolved calcium fluorescence changes of each detected neuron into spike trains ( Figure 1C ) [31] and generated rasters of spiking activity for the entire imaged population of neurons ( Figure 1D ) . All regions of the sensory neocortex showed a common capacity for emergent , multi-neuronal patterned activity , characterized by discrete periods ( >500 ms ) of correlated action potential generation within subsets of neurons . Circuit events were separated by periods of quiescence and we refer to these distinct , clustered epochs of spontaneous action potentials as individual circuit events . The start and finish of a circuit event was easily resolvable because the field of view was either quiescent , corresponding to a DOWN state in a single neuron , or was active , corresponding to a UP state in a single neuron [35] . One circuit event lasted 1203±456 ms in A1 , 1568±885 ms in S1 , and 1342±698 ms in V1 . We imaged 82 total circuit events in A1 , 268 total events in S1 , and 104 total events in V1 . Using this data , we generated graphical abstractions , or circuit topologies , corresponding to functional activity over all circuit events observed in a single field of view . Neurons were represented as nodes in each graph . Edges between nodes were directional and formed according to the following rule: neuron A was considered functionally connected to neuron B if neuron B fired in the subsequent frame ( Figure 1E ) . These edges were then weighted according to how many times this single frame lagged correlation occurred , normalized to the number of events in that field of view . Thus , stronger edge weights indicated reliable , correlated spiking , whereas weaker edge weights indicated unreliable , weakly correlated spiking ( Figure 1E ) . The resultant graphs contained a large number of edges ( median: 3 . 4×104 functional connections , range: 4 . 2×105 functional connections ) . Note that although a functional relationship between neurons increases the probability of them having a synaptic connection [18] , [33] , a linear relationship between each functional edge and a synaptic connection does not exist [16] . Rather , given our method of inference , the functional connectivity measure captured the flow of activity through the network during a circuit event . There is an ongoing debate on whether the cortical column , which is oriented perpendicular to pia , regulates and shapes the flow of information in sensory cortices [47] . Coronal slices allowed us to image activity patterns with near simultaneity across all lamina . Using this data , we assessed directional flow in functional graphs by computing the angle and distance between the source and destination of directed functional connections relative to the orientation of pia . Flow maps are plots that capture direction of circuit flow with points scattered at a radius and angle about the origin . represents the distance of the functional connection from the source to the sink , and represents the angle between the source and the sink . We measured the amount of angular clustering of activity flow in sensory areas by computing the circular variance of functional connections . The clustering of points at a particular angle indicates stereotypy of functional flow across events in a neighborhood of the functional topology . We calculated the amount of angular clustering by computing the circular variance of the set of points . Circular variance is defined as:The value of the circular variance varies from 0 to 1; the lower the value , the tighter the clustering of points about a single mean angle . In functional circuit topologies from all three areas of the sensory neocortex , flow covered the entire angular space , regardless of the pairwise distance , or radius , spanned by the functional connection ( Figure 5A ) . We found that the spread of circular variance increased for functional connections which spanned the largest distances , most likely due boundaries imposed by pia , internal capsule , or field of view ( Figure 5B ) . Thus we did not find a canonical circuit flow in spontaneous cortical activity regardless of sensory area . The highly distributed nature of functional topologies suggested that large fields of view are necessary to fully capture invariant features of functional topology . We sought to confirm this hypothesis by examining the spatial dependency of connectedness in functional topologies . Connectedness in the context of an imaged field of view can be described as an aperture problem: large interlinked networks look like disjoint groups of interacting cells if viewed only in small parts , while viewing the entire network at once reveals one giant component . For efficient computation in our graph invariant framework , we examined this problem in the following way: disjoint modules of network activity could be characterized as a weakly connected functional topology with a small algebraic connectivity . We explored how algebraic connectivity of the functional topology was modulated by two variables: minimum weight and field of view size . Because edge weight corresponds to the reliability of an observation of a spike correlation , thresholding minimum weight in a functional topology pruned its weaker edges . We defined field of view size as the maximum pairwise distance between any two neurons investigated . Together , these variables represented spatial and sampling bias during experiments . We found that the algebraic connectivity of functional topologies followed similar trajectories in all three sensory areas: smaller fields of view and the exclusion of the weakest functional connections resulted in weakly connected graphs ( Figure 6A ) . Taken together , these data suggest that one must employ large fields of view and low edge weight thresholds to capture an independent functional circuit . Interestingly , we found a field of view size in each sensory area at which the algebraic connectivity seemed to reach capacity or asymptote; above this distance , larger fields of view did not result in significantly increased connectivity . This finding suggested that a subsample size less than 1 . 1 square mm would capture a complete functional circuit topology . To further understand the interplay between experimental field of view and the topology of the functional circuits , we specified a general model of Field of View ( FOV ) Error , or how well a functional topology is captured as a function of field of view size ( Figure 6B ) . FOV error varies with the distribution of functional connections inherent to each neocortical region ( Figure 2 , right column ) . Formally , let denote the existence of a functional connection between neurons and , and denote the pairwise distance between and . Let be a pairwise distance . Then , We computed the average FOV error over all pairwise combinations of neurons in all sensory areas as a function of . To achieve less than 10 percent FOV error , we found that must be at least 676 microns in A1 , 660 microns in S1 , and 583 microns in V1 ( Figure 6C ) . This corresponds to a minimum of 430 neurons in A1 , 510 neurons in S1 , and 478 neurons in V1 by computing a cumulative distribution of neuronal density based on the probability distributions of pairwise distances in our fields of view ( Figure 6D ) . In contrast , we found less than 10 percent FOV error was achieved with just 93 microns in -nearest neighbors topologies , and 884 microns ( almost the entire imaging field of view ) in topologies with a uniform random spatial distribution of functional connectivity ( Figure 6C ) . In the random graphs , error dropped linearly as field of view size was increased ( = 0 . 9995 ) . Thus , it appears that large FOVs result in fewer errors about underlying functional topology , and that the field of view error is lessened by skew in the likelihood of a connection toward shorter distances .
All regions of the sensory neocortex showed a common capacity for spontaneous circuit activations that emerged from the underlying local synaptic connectivity [15] . Using the statistical dependencies of spiking between pairs of neurons , we generated directed and weighted functional graphs . This approach revealed a scaling relationship between A1 and S1 [15] , but was unable to delineate exactly what graph features were common to both regions . In this study , we conducted an analysis of graph invariance in functional circuit topologies generated from three regions of sensory neocortex in order to extend the graph theoretic approach toward delineating generalized rules of connectivity . The graph invariant framework allowed us to examine how circuits are similar , by considering how graph properties independent of neuronal labeling are consistent between areas . This represents a top-down approach which extracted global features of functional connectivity from large , dense sampling of neuronal activity in the neocortex . This analysis revealed multiple graph invariants that are consistent across sensory areas . The structure of neocortical functional topologies were well-characterized by non-random connectivity that was not merely dependent on spatial proximity , despite the fact that the probability of functional connection peaked proximally . In all areas , distal connections were required to achieve connected graphs , reminiscent of the daisy arrangement of dense local and patchy distal neocortical connections suggested by neuronal anatomy [2] , [48] . We found that functional topologies of all areas were connected , and the degree of connectivity was statistically indistinguishable between areas . Moreover , functional connections were structured even within a local circuit of the functional topology . We found that eigenvector centrality , a measure of influence in local flow , is log-normally distributed in all sensory areas , and is highly correlated with out-degree , and weakly correlated with in-degree . The size of functional topology does not scale with the number of neurons in the field of view , revealing that circuit activity is comprised of structured activations of subsets of neurons . Local circuit flow comprehensively covers angular space regardless of spatial scale , which is inconsistent with a canonical flow of spontaneous activity . Finally , our analysis revealed that given a large imaged field of view , a minimal numerical sample size was necessary to minimize the error of falsely characterizing two neurons as being independent . In summary , the invariant features revealed by this study suggest the existence of a generalized functional circuit throughout the sensory neocortex , strengthening the argument that the neocortical microcircuit hypothesis should be framed as probabilistic rules of connectivity and organization . This is not to say that label-dependent features do not play a role in mediating the structure of functional topology . For example , although connectivity is strongly biased towards spatial proximity between neurons , the -nearest neighbors rule and random topologies poorly recapitulated functional topologies in the data . This indicates that other connectivity rules that are not simply dependent on spatial proximity , such as those based on cell types [11] , [49] , likely play an important role . As another example , we found that the distribution of eigenvector centrality , which strongly correlates with out-degree in all areas , is highest in V1 , and that the ratio of the number of open sequences to closed sequences , which stays constant as a function of path length in all areas , is highest in V1 . These analyses suggest that V1 may be more feedforward than A1 and S1 , a result consistent with previous studies [37] , [42] . The translation of the eigenvector centrality distribution seen in Figure 4A may represent a tweaking of a generalized rule ( fitting to a log-normal distribution ) to optimize the circuit for a particular function ( feedforwardness ) . In general , it is possible that the specialization of the circuit to the overall function of the cortical area is label-dependent , or dependent on emergent properties of cell phenotypes . However , despite the fact that label dependent rules of connectivity are likely present , by investigating global features of functional circuit topology that are invariant to the details of individual neurons , we are able to reveal abstract structural rules present in functional wiring in a computationally efficient manner . We emphasize that our functional approach does not necessarily identify causal connectivity , but rather pairwise correlative dynamics [50] . However , we also note that there is a relationship between structure and function [18] . This relationship is likely enhanced in this study as the high sampling density employed here should dramatically increase the likelihood that a correlation could reflect a causal connection , since the likelihood of a synaptic connection increases with spatial proximity [8] . We consider the slice preparation to be an isolated system that allows us to study the local connectivity that defines cortical microcircuitry and remove the potentially conflating influence of long modulatory and long afferent inputs . This approach allowed us to maximize the imaged field of view and the corresponding numerical sample of neurons . In addition , coronal slices allowed us to examine the potential influence of laminar boundaries on functional circuitry . We found that a field of view of approximately 640 µm is necessary to correctly establish functional dependence between two neurons in the sensory neocortex . This field of view results from having a minimal numerical sampling while having sufficient distal functional connections that are necessary to generate a connected graph . The necessity of distal functional connections that extend beyond layers and columns may indicate that functional circuits represent information from multiple octaves in A1 [51] whiskers in S1 [52] , or a natural visual scene in V1 [53] . Our data are consistent with anatomical studies that have revealed a patchy , distributed axonal structure which has been postulated to limit signal redundancy while enabling the potential for integration of information within local populations of neurons [48] , [54] . For these hypotheses to be properly evaluated , future work toward understanding the role of connectivity in cortical dynamics and behavior will require a combination of research at the in-vitro and in-vivo level . Interestingly , we found that the connectedness of the topology depended not only on the size of the field of view , but also on whether the most unreliable connections were considered . In a previous study employing a network model , we similarly found that weak connections were necessary to recapitulate experimentally observed circuit dynamics [15] . In this study , functional topologies became sparse and modular as minimum thresholds on weight were increased , likely because fewer functional connections were reliable . When only the most reliable functional connections were considered , the topologies were sparsely connected regardless of sensory area . By investigating invariant metrics without setting thresholds on how reliably active the neurons were , we did not bias ourselves to only investigating the most reliable connections . Such a bias may lead to subsampling errors , exactly parallel to the problems that arise from using small fields of view . Since circuit topologies become highly connected with the inclusion of weak functional connections , weak connections may be necessary to provide a large dynamic range similar to a previous study of mouse V1 [37] , [42] . These data and analyses suggest that the generalized features of functional circuitry identified in this study maximize the capacity of this system to represent the sensory environment . | Information in the brain is represented and processed by populations of interconnected neurons . However , there is a lack of a clear understanding of the structure and organization of circuit wiring , particularly at the mesoscale which spans multiple columns and layers . In this study , we sought to evaluate whether functional circuit architecture generalizes across the neocortex , testing the existence of a functional analogue to the neocortical microcircuit hypothesis . We analyzed the correlational structure of spontaneous circuit activations in primary auditory , somatosensory , and visual neocortex to generate functional topologies . In these graphs , neurons were represented as nodes , and time-lagged firing between neurons were directed edges . Edge weights reflected how many times the lagged firing occurred and was synonymous to the strength of the functional connection between two neurons . The presence of label-independent features , identified by investigating functional circuit topologies under a graph invariant framework , suggest that functionally distinct areas of the neocortex carry features of a generalized functional cortical circuit . Furthermore , our analyses show that the simultaneous recording of large sections of cortical circuitry is necessary to recognize these features and avoid undersampling errors . | [
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] | 2014 | Analysis of Graph Invariants in Functional Neocortical Circuitry Reveals Generalized Features Common to Three Areas of Sensory Cortex |
Although livestock vaccination is effective in preventing Rift Valley fever ( RVF ) epidemics , there are concerns about safety and effectiveness of the only commercially available RVF Smithburn vaccine . We conducted a randomized controlled field trial to evaluate the immunogenicity and safety of the new RVF Clone 13 vaccine , recently registered in South Africa . In a blinded randomized controlled field trial , 404 animals ( 85 cattle , 168 sheep , and 151 goats ) in three farms in Kenya were divided into three groups . Group A included males and non-pregnant females that were randomized and assigned to two groups; one vaccinated with RVF Clone 13 and the other given placebo . Groups B included animals in 1st half of pregnancy , and group C animals in 2nd half of pregnancy , which were also randomized and either vaccinated and given placebo . Animals were monitored for one year and virus antibodies titers assessed on days 14 , 28 , 56 , 183 and 365 . In vaccinated goats ( N = 72 ) , 72% developed anti-RVF virus IgM antibodies and 97% neutralizing IgG antibodies . In vaccinated sheep ( N = 77 ) , 84% developed IgM and 91% neutralizing IgG antibodies . Vaccinated cattle ( N = 42 ) did not develop IgM antibodies but 67% developed neutralizing IgG antibodies . At day 14 post-vaccination , the odds of being seropositive for IgG in the vaccine group was 3 . 6 ( 95% CI , 1 . 5 – 9 . 2 ) in cattle , 90 . 0 ( 95% CI , 25 . 1 – 579 . 2 ) in goats , and 40 . 0 ( 95% CI , 16 . 5 – 110 . 5 ) in sheep . Abortion was observed in one vaccinated goat but histopathologic analysis did not indicate RVF virus infection . There was no evidence of teratogenicity in vaccinated or placebo animals . The results suggest RVF Clone 13 vaccine is safe to use and has high ( >90% ) immunogenicity in sheep and goats but moderate ( > 65% ) immunogenicity in cattle .
Rift Valley fever ( RVF ) is an acute disease that is caused by a phlebovirus of the Bunyaviridae family of viruses that affects livestock ( cattle , sheep , goats , camels ) and humans in Africa and the Arabian Peninsula [1–3] . In Africa , periodic and severe epidemics have been reported in Kenya , Somalia , Tanzania , Sudan , South Africa , Zimbabwe , Senegal , Mauritania , Egypt , and Madagascar [2 , 4–8] . Even though determining the actual morbidity and mortality in humans has been difficult , an RVF epidemic in Egypt in 1977 resulted in an estimated 200 , 000 human cases and 600 deaths whereas the one in East Africa ( Kenya , Somalia , Tanzania ) in 1997–98 resulted in over 100 , 000 cases and over 450 deaths in Kenya alone [4 , 9–11] . The RVF epidemic in Saudi Arabia and Yemen in 2002 resulted in an estimated 4000 human cases and over 200 deaths [2 , 3] . Over 80% of the RVF-infected humans are either asymptomatic or have a mild to moderate influenza-like disease . However most fatal cases develop severe disease characterized by central nervous system complications , retinitis , severe jaundice , haemorrhagic syndrome and death [12 , 13] . The RVF epidemics also result in massive livestock abortions , death of primarily young animals , and devastating economic losses associated with animal quarantines and trade restrictions [14] . For example , the economic losses resulting from the 2006–07 RVF epidemic in Kenya alone were estimated at US$32 million [15] . The losses were associated with effects on the livestock value chains such as livestock producers , traders , slaughterhouses , and butchers; and effects on the national income such as decline in the livestock market and other sectors such as transportation , chemicals , petroleum and tourism [15] . The RVF epidemics occur during years of El Niño weather characterized by heavier than usual rainfall , resulting in hatching of a high population of floodwater Aedes species mosquitoes that transmit the virus to susceptible livestock and human populations [1] . Apart from mosquito transmission , humans can be infected by consuming animal products from infected animals , a transmission pathway that is associated with most of the severe human cases [16] . For the endemic countries , there is a prediction model that has been improving steadily , which can provide an early warning of a few months prior to an epidemic [17 , 18] . Since the RVF outbreak in the Arabian Peninsula in 2000 , there has been increasing concern that RVF virus can be spread to other non-endemic regions through movement of infected travellers , mosquitoes , or animals , which would raise major biosafety and biosecurity concerns globally [19] . Experts agree that the most effective intervention against epidemics and for enhancing preparedness in the face of possible global spread of RVF virus is mass vaccination of livestock in high risk areas , and perhaps humans that may be at immediate risk [20] . If carried out effectively before an epidemic , livestock vaccination can either prevent the epidemic or significantly reduce its extent and severity in livestock and subsequent human infections [21] . In sub-Saharan Africa , vaccination of susceptible livestock is widely used , but with varying degrees of success . Two vaccines are commercially available for vaccination of animals against RVF; both of them produced from a pantropic Entebbe strain of RVF virus referred to as Smithburn strain , that was isolated from mosquitoes in Uganda in 1944 and attenuated through extensive passaging in mice [22–24] . A formalin inactivated Smithburn vaccine is safe for use during epizootics and in pregnant animals; but it is poorly immunogenic and confers only short term immunity , thus requiring booster doses and regular revaccination to achieve and maintain immunity [22] . The inactivated Smithburn vaccine also confers poor colostral immunity and it requires long production lead time due to the tedious process of inactivation that requires rigorous biosafety and biosecurity measures . The live Smithburn vaccine is more immunogenic and requires only a single dose; however it causes abortion and foetal teratogenicity when administered to pregnant animals [23] . In addition , there have been reports that the live vaccine can revert to virulence and be transmitted from vaccinated to susceptible animal and humans resulting in RVF disease [14] . Because of these shortcomings of the Smithburn vaccines , there has been need to develop safer and more efficacious RVF vaccines . Presently , there is no commercially available human vaccine against RVF disease . There are a number of candidate livestock vaccines that have undergone experimental and field trials . The MP-12 is an RVF virus strain was generated from the wild type parental strain ZH548 ( isolated from an infected patient in Egypt ) following serial passages with a chemical mutagen . MP-12 is a temperature-sensitive mutant that carries mutations in the M- and L-segments that contribute to the attenuation of virulence [25 , 26] . There are two candidate MP-12 vaccines , one with a deletion at the NSs region of the virus genome , and the other with a deletion at the NSm region of the virus [27] . In experimental infections in livestock and non-human primates , the MP-12 NSm mutant has shown good immunogenicity and protection from challenge [27 , 28] . Recently , a recombinant RVF virus derived from RVF strain ZH501 , an isolate from a human patient in Egypt , but lacking the NSm gene in the M-segment and carrying a green fluorescent protein in place of the NSs gene in the S-segment ( ΔNSs-ΔNSmRVFV ) was generated by reverse genetics [29] . The availability of such a vaccine virus lacking virulence-associated genes and insertion of the non-viral GFP gives it the capability for distinguishing vaccinated animals from natural infections , which is an important feature . Experimental studies using ΔNSs-ΔNSmRVFV in sheep showed no virulence even in high doses , accompanied by strong immunogenicity and no teratogeny [29] . The RVF Clone 13 virus is a plaque isolate of the 74HB59 strain of RVF virus recovered from an RVF-infected patient in Central Africa that lacks approximately 70% of a NSs open reading frame , and is therefore significantly attenuated [30] . A live RVF Clone 13 vaccine was registered for use in cattle , sheep and goats in South Africa in 2009 and in Namibia in 2011 , and over 50 million doses have been sold since [23] . Studies on safety and immunogenicity of the vaccine carried out in South Africa indicates that the vaccine is highly immunogenic , and it does not cause abortion or foetal teratogenicity in ewes vaccinated during pregnancy [31] . The vaccine was also found to induce production of neutralizing antibodies that were protective against virus challenge in ewes and calves [31 , 32] . In experimental challenge studies , RVF Clone 13 vaccine protected cattle and sheep to titers similar to those observed for the Smithburn strain [31 , 32] with a good dose-response effect . More importantly , no abortion or teratogeny were reported in animals vaccinated with RVF Clone 13 , in contrast to animals vaccinated with the Smithburn strain vaccine [32] . Here , we carried out field trials for RVF Clone 13 RVF vaccine in commercial livestock farms in Kenya in order to provide more data that would enable this vaccine to gain broader registration in Africa as an important tool in the prevention and control of RVF . Cattle , sheep and goats in three livestock farms , including those in early and late pregnancy , were vaccinated with RVF Clone 13 to determine the immunogenicity and safety of the vaccine at the recommended dose in adult and young animals and in pregnant females at different stages of pregnancy .
Clone 13 RVF ( strain 74HB59 ) vaccine was provided by Onderstepoort Biological Products ( OBP , Onderstepoort , South Africa ) as freeze dried pellet ( Batch # 13 ) . For injection , the pellet was suspension in 1 milliliter of diluent consisting of glucosamine serum ( Batch # 8306 ) . Each reconstituted milliliter contained at least 1 x 105 plaque forming units per ml of the RVF Clone virus , the recommended minimum dose [31] . The placebo was the glucosamine serum diluent in 1 milliliter volume provided by OBP . Each study animals was subcutaneously injected with 1 ml of either reconstituted RVF Clone 13 vaccine or placebo . Cold chain was maintained throughout the transportation of the vaccine from the manufacturer to injection of animals . Ethical approval for this study was obtained from the Kenya Medical Research Institute , Nairobi , Kenya ( SSC # 2098 ) and it adhered to the Kenya national guidelines for animal care and use as stipulated by the National Commission for Science , Technology , and Innovation . Approval was also obtained from the United States’ Centers for Disease Control and Prevention and the Department of Veterinary Services , Government of Kenya . The study was conducted at three livestock farms in Kenya; the Kiboko Farm , Kabete Veterinary Farm , and Ngong Veterinary Farm . The Kiboko farm , owned by the Kenya Agriculture Research Institute is located in Makindu division of Makueni County . The farm size is 15 , 400 hectares mainly covered by pastures , research crops , fodder and pastures , shrubs and woodland . Wild animals found in the farm include elephants , antelopes , and leopards . The domestic animals kept in the farm are cattle ( Sahiwal , Borana and Zebu breeds ) and gala goats . The farming system is outdoor grazing for the cattle and goats , which are kept separate . Routine vaccination is carried out against Foot-and-mouth disease for cattle and contagious caprine pleuropneumonia for goats . Weekly anti-tick dipping is carried out for cattle . The Kabete farm , owned by the government of Kenya , is located in Westlands District of Nairobi County . The farm size is about five acres and the animal species kept are cattle ( Friesian , Ayrshire and Friesian-Ayrshire crosses ) , sheep ( Dopper crosses ) and horses . The farm practices outdoor grazing with hay supplementation . The Ngong farm , owned by the government of Kenya is located in Kajiado North District of Kajiado County . The farm is 1 , 138 acres and has cattle ( Friesian , Ayrshire , Charolaise and their crosses ) and sheep ( Doper , Red Maasai and their crosses ) . The farm practices extensive outdoor grazing and routine vaccination is carried out against Foot-and-mouth disease for cattle and Enterotoxaemia and Pestes de Petit Ruminant for sheep . The farms were found suitable due to their good record keeping of breeding , health and feeding records for individual animals . The study was conducted in cattle , sheep and goats aged at least 6 months at the start of the study . Cattle and goats were enrolled in Kiboko farm whereas cattle and sheep were enrolled in both Ngong and Kabete farms . Prior to enrolment into the study , RVF virus sero-status of the animals was determined; only seronegative animals were enrolled . All animals were given individual identification using ear tags . This was a blinded randomized controlled study . The study was conducted in accordance with the European Medicines Agency recommendations for clinical trials , with the independent monitoring of the study carried out by Tests and Trials Company , Monzon , Spain . Training on good clinical practices was given to all study participants before commencement of the trial . Female animals were tested for pregnancy by manual palpation and ultrasonography in cattle , and by ultrasonography only in sheep and goats . The animals were then divided into three groups; A , B and C shown in Fig . 1 . Group A enrolled males and non-pregnant females allocated to two treatments using a randomised complete block design run at each farm and randomised to treatment ( one randomization per farm and species ) . Group B enrolled cattle , sheep and goats in the 1st half of pregnancy allocated to the two treatments using randomised complete block design in all three farms . Group C enrolled cattle , sheep and goats in the 2nd half of pregnancy allocated to the two treatments using randomised complete block design and run in all three farms on the species available . For each of groups A , B , and C , the placebo and vaccinated animals were housed separately to avoid contact after drug administration . Animals were monitored for 1 year with sampling on days 0 , 14 , 28 , 56 , 183 and 365 . All study personnel were blinded to the treatment status of the study animals . Rectal body temperature was taken for each animal on day 0 , 1 , 2 and 3 post-injection . In addition , any animal that developed a clinical condition at any time during the study was subjected to full clinical examination by a veterinarian , specimens collected for analysis , and diagnosis provided . For any animals that died , complete post-mortem investigations were carried out . Sera were collected on day 0 , and 14 , 28 , 56 , 183 and 365 days post-injection from each animal and tested for anti-RVF virus IgM and IgG antibodies by enzyme-linked immunoassay ( ELISA ) using a kits from Biological Diagnostic Supplies Limited ( United Kingdom ) , according the manufacturer’s instructions [33] . For IgG antibody detection , a recombinant antigen-based indirect ELISA was used to detect anti-RVF virus IgG antibodies . Positive sera were detected using recombinant Protein G horseradish peroxidase conjugate and 2 , 2'-Azinobis [3-ethylbenzothiazoline-6-sulfonic acid]-diammonium salt ( ABTS ) substrate . Net optical density ( OD ) values were recorded for each specimen and then used to calculate percent positivity ( PP ) using a positive control provided by the manufacturer as the denominator . Appropriate negative controls were run with each set of specimens . The PP cutoff was ≥25 for all three species . For IgM antibodies , an IgM capture ELISA was carried out using rabbit anti-sheep IgM capture antibody and positive specimens detected using mouse anti-RVF virus antibodies and horseradish peroxidase-conjugated anti-mouse IgG . The net OD values of test specimens were expressed as PP of the positive control provided by the manufacturer , with a PP cut-off of ≥7 . 9 for sheep specimens , ≥ 9 . 5 for goat specimens , and ≥14 . 3 for cattle specimens .
Among the 3 study farms , a total of 404 animals were enrolled in the study; 151 goats , 85 cattle and 168 sheep . Of these , 170 , 87 , and 147 animals were enrolled in group A , B and C , respectively ( Fig . 1 ) . Vaccinated cattle ( N = 42 ) did not develop any anti-RVF virus IgM antibodies but 67% developed anti-RVF virus IgG antibodies that were maintained in 43 . 6% of the animals through day 365 post-vaccination ( Fig . 2 ) . In vaccinated goats ( N = 72 ) , 72% developed IgM antibodies and 97% developed IgG antibodies that were maintained in all animals through day 365 ( Fig . 3 ) . In vaccinated sheep ( N = 78 ) , 84% developed IgM and 91% IgG antibodies that were maintained in 52 . 6% of the animals by day 365 ( Fig . 4 ) . At day 14 , the odds of being seropositive for IgG in the vaccine group were significantly higher ( P < 0 . 05 ) in vaccinated animals when compared to the placebo group , with an odds ratio of 4 in cattle , 90 in goats , and 40 in sheep ( Table 1 ) . The IgM antibody response between placebo and vaccinated groups in cattle and goats was statistically insignificant . However in sheep , IgM response was significantly higher in vaccinated as compared to placebo group of animals ( Table 1 ) . To determine whether the IgG antibodies were neutralizing , we conducted VNT for vaccinated bovine ( N = 40 ) , goats ( N = 46 ) , and sheep ( N = 46 ) sera that were ELISA positive . Overall , 89 . 6% ( 116/130 ) of the ELISA positive samples were also positive by VNT whereas 91% ( 10/11 ) of the ELISA negative samples were negative by VNT ( Kappa = 0 . 52 ) . Table 2 compares the ELISA titers ( expressed as percent positive ) against VNT titers ( log dilution ) . As shown previously , cattle had lower ELISA and VNT titers whereas goats had the highest titers ( Table 2 ) . No fever was reported in any of the study animals . One goat at Kiboko farm was killed by predators and two animals in Ngong farm ( a sheep and a cow ) died as a result of bloating . There were no RVF-associated mortalities among the study animals . One case of abortion was reported in a vaccinated goat at late pregnancy . However , histopathologic examination and laboratory testing by polymerase chain reaction did not reveal evidence of RVF virus infection . There were no congenital malformations in either the placebo or vaccinated animals .
Although the need for a better RVF livestock vaccine has been recognized for many years , the efforts to generate and manufacture one have been slow and difficult . This is perhaps because of the limited market , which is primarily in Africa , and the fact that RVF cases and epidemics can sometimes be absent for over 10 years even in endemic countries . As a prevention and control measure , livestock vaccination should be used in the context of a national strategy guided by a risk-based analysis [20] . Whether the strategy includes structured regular vaccinations to prevent the disease or immediate action to prevent an imminent outbreak , livestock vaccination needs to be systematic and thorough , targeting all high risk regions in a country and accompanied by other important measures such as monitoring and evaluation to determine coverage and sentinel surveillance ( Munyua et al . , IN PRESS ) . The explosive and sequential nature of RVF outbreaks in sub-Saharan Africa has often meant that when an early warning for the disease is issued , even in the presence of adequate resources , there are inadequate vaccine reserves globally to cover livestock at risk in one country , leave alone in multiple countries . To mitigate this risk , the idea of creating a shared vaccine bank consisting of epidemic—prone countries has been discussed but never implemented . The RVF Clone 13 vaccine had undergone testing under experimental conditions but no studies under field conditions had been conducted ( 31 , 32 ) . Therefore , we undertook this field trial in various commercial livestock farms in Kenya in order to obtain data on safety and immunogenicity under various livestock management conditions that can enable the vaccine to be registered broadly in Africa . Our data shows that RVF Clone 13 vaccine is safe to use in pregnant livestock , with the one abortion in a goat in this study not linked to the vaccine based upon histopathological analysis . The RVF Clone 13 safety finding is in agreement with other studies using this natural mutant that lacks 70% of the NSs gene of the virus , and that has been shown to be avirulent to mice , sheep , goats and cattle in various studies [30–32] . More importantly , the virus has undergone many serial passages in a number of laboratories for over 20 years with no evidence of reversion to virulence in vitro or in vivo , making it an ideal and safe RVF vaccine that will be acceptable for mass livestock vaccine to farmers during periods of imminent outbreaks . Our data also showed high ( >90% ) immunogenicity of the vaccine in sheep and goats and moderate ( > 65% ) immunogenicity in cattle . Even though there was no natural RVF outbreak during the period of the field trials , the Clone 13 vaccinated animals developed high neutralizing antibodies . These results are in agreement with experimental challenge studies with the vaccine in calves and sheep where neutralizing antibodies and prevention from challenge with virulent virus were reported in all vaccinated animal [31 , 32] . The moderate immunogenicity to Clone 13 vaccine observed in cattle in this study is consistent with a previous study that showed cattle tend to mount a weaker immune response to RVF virus vaccine when compared to sheep and goats [37] . It been suggested that the NSs deletion in RVF Clone 13 vaccine virus gives it capacity for differentiating infected from vaccinated animals . However , we do not have a validated molecular or serological test that can be applied for this purpose . The next steps for RVF Clone 13 are to apply for licensing of the vaccine in Kenya and other African countries . In Kenya , the Department of Veterinary Services is using the data from this study to file for the licensing of the vaccine through Kenya Pharmacy and Poisons Board . This study had some limitations . First , the use of 1 x 105 pfu dose in cattle , which was informed by controlled experimental studies , was misguided . Therefore , we recommend that for the purpose of registration , the RVF Clone 13 vaccine be administered at 1 x 105 in goats and sheep and a higher does ( to be determined ) in cattle . Another field study to confirm the safety and immunogenicity of this higher dosage of vaccine is planned . Second , there was no evidence of natural RVF infection in any of the three farms that would have enabled us to assess the ability of RVF Clone 13 vaccine to protect from infection . Third , a few placebo animals were seropositive for anti-RVF IgG antibodies suggesting either mild natural infection during the trial or possible RVF Clone 13 transmission within the herds . | Although livestock vaccination is effective in preventing Rift Valley fever ( RVF ) outbreaks , there are concerns about safety and effectiveness of the only commercially available vaccine for the disease . Here , we conducted a field trial in Kenya to evaluate the safety and ability to induce protection for a new RVF vaccine , referred to as Clone 13 , that was recently registered in South Africa . A total of 404 animals , consisting of cattle , sheep , and goats , were divided two groups and one group was vaccinated with Clone 13 vaccine while the other group was not vaccinated . The animals were followed for one year and analyzed for RVF antibody levels at days 14 , 28 , 56 , 183 , and 365 after vaccination . Between 91% and 97% of vaccinated sheep and goats develop antibodies to the vaccine , whereas only 67% of the vaccinated cattle developed antibodies . These finding indicate that the Clone 13 vaccine induces high levels of protective antibodies in sheep and goats and moderate levels in cattle . The vaccine was safe since none of vaccinated animals developed evidence of RVF disease including deformities in newborns , and only 1 out of 120 pregnant animals had an abortion that was not associated with the RVF disease . | [
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] | [] | 2015 | Randomized Controlled Field Trial to Assess the Immunogenicity and Safety of Rift Valley Fever Clone 13 Vaccine in Livestock |
Osteoarthritis ( OA ) is a degenerative condition caused by dysregulation of multiple molecular signalling pathways . Such dysregulation results in damage to cartilage , a smooth and protective tissue that enables low friction articulation of synovial joints . Matrix metalloproteinases ( MMPs ) , especially MMP-13 , are key enzymes in the cleavage of type II collagen which is a vital component for cartilage integrity . Transforming growth factor beta ( TGFβ ) can protect against pro-inflammatory cytokine-mediated MMP expression . With age there is a change in the ratio of two TGFβ type I receptors ( Alk1/Alk5 ) , a shift that results in TGFβ losing its protective role in cartilage homeostasis . Instead , TGFβ promotes cartilage degradation which correlates with the spontaneous development of OA in murine models . However , the mechanism by which TGFβ protects against pro-inflammatory responses and how this changes with age has not been extensively studied . As TGFβ signalling is complex , we used systems biology to combine experimental and computational outputs to examine how the system changes with age . Experiments showed that the repressive effect of TGFβ on chondrocytes treated with a pro-inflammatory stimulus required Alk5 . Computational modelling revealed two independent mechanisms were needed to explain the crosstalk between TGFβ and pro-inflammatory signalling pathways . A novel meta-analysis of microarray data from OA patient tissue was used to create a Cytoscape network representative of human OA and revealed the importance of inflammation . Combining the modelled genes with the microarray network provided a global overview into the crosstalk between the different signalling pathways involved in OA development . Our results provide further insights into the mechanisms that cause TGFβ signalling to change from a protective to a detrimental pathway in cartilage with ageing . Moreover , such a systems biology approach may enable restoration of the protective role of TGFβ as a potential therapy to prevent age-related loss of cartilage and the development of OA .
Osteoarthritis ( OA ) is a spectrum of degenerative disorders that become much more prevalent with age to the extent that 50% of those aged ≥65 years suffer from the disease globally [1] . Treatments are limited with no therapies that directly target the disease; instead , the focus is on relieving symptoms and improving function . This is achieved through the use of painkilling medications in combination with physiotherapy , as well as educating patients to manage their weight , with the last resort being total joint replacement [2] . Understanding where and when to target OA progression is complex due to the multifactorial nature of OA development . For example , many pathways such as Wnt/β-catenin , mTor , phosphatidylinositol 3-kinases ( PI3K ) /Akt , Indian Hedgehog , protein kinase K and Notch have been linked to the destruction of cartilage and the development of OA based on animal model data [3–8] . Transforming growth factor β ( TGFβ ) is a growth factor with significant therapeutic potential due to its pleiotropic role in disease progression . It has varying effects depending on not only the type of tissue but the age and environment surrounding the tissue . TGFβ activates signalling pathways that typically have anabolic effects on cartilage such that targeting components of this pathway has potential for new treatment therapies . For example , it has been shown that TGFβ is required for normal cartilage development and is crucial for maintaining chondrocyte homeostasis in synovial joints [9] . In addition , we and others have reported that TGFβ has a protective effect against a multitude of inflammatory stimuli [10–12] , including interleukin-1 alpha ( IL-1α , henceforth referred to as IL-1 ) in combination with oncostatin M ( OSM ) ( cytokines known to be elevated in OA synovial fluid which markedly induce cartilage destruction [13] ) . This potent inflammatory stimulus promotes the expression of the collagenases , matrix metalloproteinase ( MMP ) 1 and MMP13 , whilst supressing the expression of their endogenous inhibitor , tissue inhibitor of metalloproteinases ( TIMP ) 1 [14] . Inclusion of TGFβ has been shown to reverse this expression profile [10] . IL-1+OSM has been shown to activate multiple signalling pathways in chondrocytes [15–17] , but the mechanism by which TGFβ blocks such cytokine-induced MMP expression in human chondrocytes has not been described . TGFβ is known to have a role in matrix production by inducing collagen types I and II , and proteoglycans [18] . It also counteracts major catabolic genes such as Runt-related transcription factor 2 ( RUNX2 ) , a disintegrin and metalloproteinase with thrombospondin motifs 5 ( ADAMTS5 ) and collagen 10 [19] , as well as inducing TIMPs to inhibit metalloproteinase-mediated damage [20] . The canonical TGFβ pathway can have either catabolic or anabolic effects depending on which of its receptors is activated [21] . In healthy cartilage , TGFβ signals through two type 1 TGF receptors , activin-like kinase 1 and 5 ( Alk1 ( ACVRL1 ) and Alk5 ( TGFBR1 ) , respectively ) . TGFβ predominantly signals through Alk5 due to its abundance [21] . Alk1 and Alk5 both form dimers to mediate their effect . Alk5 forms homodimers that in turn bind TGFβ , whilst Alk1 forms a heterodimer with Alk5 such that Alk1 signalling is dependent on Alk5 [22] . Alk5 binding to TGFβ leads to Smad 2/3 phosphorylation , which blocks terminal differentiation , chondrocyte hypertrophy and also stimulates matrix production [21] . When the balance shifts toward Alk1 signalling , this causes increased Smad 1/5/8 phosphorylation [21] which enhances chondrocyte hypertrophy , terminal differentiation and matrix breakdown by MMPs such as MMP-13 [21] . Age is believed to be the major driving factor for conversion of Alk5 to Alk1 signalling in cartilage , with Alk5 levels decreasing more rapidly than Alk1 leading to an increase in the Alk1/Alk5 ratio [21] . It has been suggested that Alk5 levels may decrease due to a change in the ratio of Alk5 synthesis/degradation with age [23] , but the mechanisms involved are unknown . Of particular interest is how a change in the Alk1/Alk5 ratio affects the ability of TGFβ to protect against the damaging effects of inflammatory insults such as IL1+OSM . The construction , and development , of computational models has previously aided in our understanding of TGFβ signalling [24] . In order to better understand TGFβ interactions with pro-inflammatory stimuli , we modified and combined two previously published models [23 , 25] to provide new insight into the complex interactions that allow TGFβ to mediate its protective effects against inflammation , as well as how these interactions change with ageing . To contextualise this model in a global environment , we examined publically available microarray data to reveal how dysregulation of one system can affect a variety of others , ultimately leading to OA progression .
We used an experimental approach to examine how TGFβ represses the induction of MMP13 by a pro-inflammatory stimulus . We first confirmed the previously shown synergistic effect of IL-1+OSM on MMP13 induction [13 , 26] in SW1353 chondrocytes could be repressed by TGFβ ( at varying doses ) as we have previously reported in both human and bovine cartilage [10 , 27 , 28] ( see S1 Fig ) . This repression took longer than 12 hours , becoming evident at 24 hours and increasingly potent with time: combined data from multiple cell populations indicated the repression was approximately 42% of the IL-1+OSM induction at 24 hours , rising to 68% at 48 hours ( Fig 1A ) . Note that the dose of IL-1 used was quite low ( 0 . 5 ng/ml ) as previous studies have shown that low concentrations of IL-1 have a biological effect in SW1353 cells [29] . In addition , it should be pointed out that Fig 1 has unusually high n values . This is because we needed an accurate determination of the percentage of repression for constructing the model . We also showed the kinetics of MMP13 induction by IL1+OSM with and without TGFβ by normalising the data at each time point to the control values ( Fig 1B ) . This shows that in the absence of TGFβ MMP13 increases up to 24 hours and then starts to decline at 48 hours . The addition of TGFβ does not alter the kinetics for the first 12 hours but prevents any further increase at 24 hours and by 48 hours MMP13 levels are greatly reduced . It is important to note that MMP13 is nearly absent in untreated controls , this results in a high CT value . Therefore , any change in the basal expression can result in vastly different fold change values for the treated samples ( Fig 1B ) . The repressive effect seen by TGFβ was more constant across samples ( Fig 1A ) . Treatment of SW1353 chondrocytes with TGFβ ( 2 h ) led to a significant upregulation of the Alk5-inducible gene plasminogen activator inhibitor-1 ( PAI1 ) [30] , whilst the Alk1-dependent gene inhibitor of DNA binding 1 ( ID1 ) [31] was unaffected ( S2 Fig ) . In line with this observation , assessment of receptor expression revealed TGFBR1 ( Alk5 ) expression was higher than ACVRL1 ( Alk1 ) ( S3 Fig ) . We next confirmed that siRNA-mediated TGFBR1 silencing ( S4 Fig ) prevented the observed repression of MMP13 repression by TGFβ ( S2 Fig ) . Computational modelling was used to explore how TGFβ-mediated repression of IL-1+OSM-induced MMP13 expression changed with age . Using the experimental data generated previously we combined , and then expanded upon , models of IL-1+OSM [25] and TGFβ [23] signalling in chondrocytes ( see S2 File ) . In the combined model , we first assumed that TGFβ signalling through Alk5 could only impact MMP13 expression via JunB interactions with activator protein-1 ( AP-1 ) complexes that consist of either c-Jun/c-Fos heterodimers or c-Jun homodimers ( Fig 2; reactions highlighted in red ) . With this assumption the model simulations matched the repression seen experimentally at 24 h , although it could not replicate the increased repression observed at 48 h ( Fig 3A and 3B ) . We hypothesised that the enhanced repression at 48 h could be due to increased MMP13 mRNA degradation ( Fig 2; reaction highlighted in blue ) . As the protein ( s ) and/or microRNA ( s ) responsible for this are currently unknown , we included a dummy species to mediate this effect . With the model adapted to include increased MMP13 mRNA degradation ( instead of transcriptional repression via AP-1 interactions ) , the simulations were able to match the repression seen at both 24 and 48 h ( Fig 3C ) . However , this model failed to fully replicate the minor effects that changes in TGFβ concentration had on repression we had observed experimentally ( Fig 3D and S1 Fig ) . We next used a model that included both transcriptional repression via AP-1 interactions and increased degradation of MMP13 mRNA ( simplified and complete model schematics are presented in Fig 2 and S5 Fig , respectively ) and could simulate comparable levels of repression to those observed experimentally ( Fig 3E ) , with changes in TGFβ concentration having minimal effects on the simulated MMP13 repression ( Fig 3F ) . The model also closely matched the kinetics of MMP13 induction after stimulation by IL1+OSM shown experimentally ( Fig 1B ) . We next evaluated the reliability of the predictions from our model by assessing the effect of a 6 h pre-treatment with TGFβ on the IL-1+OSM response . The model predicted that MMP13 repression would be observed after 12 hours of IL-1+OSM treatment , and this would subsequently increase; the predictions matched experimental data ( see S6 Fig ) . Confident we could make accurate predictions with the model , we then simulated the model stochastically over 48 h . This predicted that the levels of MMP13 mRNA generated by IL-1+OSM stimulation are highly variable whilst inclusion of TGFβ reduced this variability from around 12 h onwards ( Fig 4 ) . A 24 month time simulation , representative of an ageing model , resulted in decreased Alk5 abundance including the availability of Alk5 homodimers ( Fig 5A ) . Alk1/Alk5 heterodimers only declined slightly such that the Alk1/Alk5 ratio increased across the simulation , replicating what occurs with age [21] . We used the model to examine how ageing affects a pro-inflammatory stimulus ( IL-1+OSM ) . At early time points ( 4 months ) when Alk5 homodimers dominate , the pro-inflammatory stimulus was markedly abrogated by TGFβ with MMP13 mRNA expression returning to basal levels rapidly ( Fig 5B ) . The Alk1/Alk5 heterodimers and Alk5 homodimer ratios reached equality at about 7 months . Shortly after this ( 9 months ) , the MMP13 repression was still evident albeit slightly reduced ( Fig 5C ) . However , once Alk1 becomes the dominant receptor ( e . g . 23 months ) , basal MMP13 mRNA levels are higher in the presence of TGFβ resulting in a marginally higher level of MMP13 mRNA following IL-1+OSM addition ( Fig 5D ) ; thus , the overall increase in MMP13 from basal levels induced by IL-1+OSM addition was less compared to IL-1+OSM+TGFβ suggesting there was still some minor repression ( Fig 5D ) . Furthermore , the induced MMP13 persisted for longer compared to earlier time points , and returned to a basal expression level that was higher compared to time points when Alk5 was dominant ( compare Fig 5B–5D ) . An advantage of computational modelling is that it can be used to make predictions and test possible therapeutic interventions . In order to test the effect of ameliorating the damaging effects of TGFβ it was necessary to modify the model to allow for RUNX2 inactivation via a mechanism that was independent of TGFβ/Alk5 signalling . The previous assumption had been a simplification but it is known that other mechanisms are involved [32] . Therefore an additional reaction for RUNX2 inactivation was added to the model , although it had little effect on the model output in the presence of TGFβ ( S7 Fig ) . 1D11 is an antibody that targets TGFβ , leading to its degradation . It has been demonstrated that injection of this antibody into the subchondral bone can attenuate surgically induced OA progression in mice and rats [33] , and so has promising clinical applications for human OA . We modelled the addition of the antibody by adding a species ( Anti-TGF ) which could bind to TGFβ and degrade it in both its inactive and active forms . We also assumed that Anti-TGF degrades over time and leave the system . It took Anti-TGF about 34 hours to completely leave the system , the same length of time as was reported in a murine model of OA [34] ( S8 Fig ) . Simulated injections of Anti-TGF were modelled at different time-points and the effect on MMP13 mRNA was examined over a 30 month time period ( Fig 6 ) . A single “injection” at 6 months , led to an increase in MMP13 mRNA . A second injection , 24 days later helped to reduce the levels of MMP13 mRNA at later time-points . However , a third injection after another 24 days dramatically reduced the levels of MMP13 mRNA . ( Fig 6A ) . Having discovered that three “injections” reduced levels of MMP13 mRNA , we used the model to explore different time lags between each injection ( Fig 6B ) . The results showed that the optimal strategy was to space the simulated “injections” every 24 days . We also examined the effect of late interventions with a single “injection” at 19 months at which time Alk1 is the dominant receptor , and TGFβ signalling has mainly detrimental effects ( Fig 6C ) . As for the 6-month intervention , this led to an increase in MMP13 mRNA but prevented the continual increase in MMP13 mRNA after 25 months . A second injection 24 days later greatly reduced levels of MM13 and a third injection after another 24 days , completely reduced MMP13 levels and even after a pro-inflammatory stimulus at 24 months , the increase in MMP13 was only very transitory . As for the early intervention , spacing “injections” every 24 days was more effective than short time intervals ( Fig 6D ) but in all cases interventions at 19 months were much more effective than the 6 month interventions ( compare Fig 6B and 6D ) . Therefore the model predicts that later interventions when TGFβ signalling is predominantly via the Alk1 pathway , are more effective . We used publically available microarray data to examine the overall network of genes involved in human OA and to identify interactions between the IL-1 , OSM and TGFβ pathways . DAVID analysis of the clustered Cytoscape network we created to represent human OA ( Fig 8A ) highlighted their function . Only the top 14 clusters had significant enrichment , and of these clusters 1 and 5 ( Fig 8A ) had multiple significantly upregulated functional terms relating to inflammation ( see S3 File ) . Tight clustering was observed for both clusters suggesting there was considerable cross-talk/interaction between the genes in each cluster . Overlaying the genes present in the model identified three specific clusters ( Fig 8B ) . Both TGFBR1 and SMAD1 were located in the largest cluster , whilst both c-Fos ( FOS ) and JunB ( JUNB ) also had links to genes within the network ( Fig 8B ) . The implications of these findings are discussed below .
Matrix-degrading enzymes play important roles in the development of OA , with MMP-13 considered the key collagenase [35 , 36] . We initially confirmed previous studies demonstrating significant repression of IL-1+OSM-induced MMP13 mRNA in chondrocytes by TGFβ [10–12] , and our findings highlighted that TGFβ needed to be present for at least 12 h for repression to occur . This repression became more pronounced with prolonged stimulation and we also found pre-treatment with TGFβ ( for 6 h ) could still result in significant MMP13 repression even when removed prior to cytokine stimulation ( S6 Fig ) . Together , these findings indicated that de novo synthesis of a tertiary mediator was required to effect the observed repression . The mechanism by which TGFβ protects against MMP13 upregulation had previously not been explored . By using siRNA silencing of TGFBR1 , we showed that Alk5-dependent Smad2/3 signalling was required to mediate this effect . Two potential mechanisms are that this pathway leads to upregulation of components that either inhibit transcription of MMP13 or increase the degradation of MMP13 mRNA . Computational modelling indicated that both AP-1 complex inhibition and increased instability of MMP13 mRNA were required to accurately match experimental data although the necessary downstream proteins have not yet been clearly identified . Despite the alterations made to the model it still matched the simulation output of the key proteins from the original models ( S9–S11 Figs ) . In addition , AP-1 component expression was in line with data published previously by our group [17 , 37] . The computational model gave further insights into how TGFβ protects against inflammatory effects via the Alk5/Smad2/3 signalling pathway and demonstrated why the age-related increase in the Alk1/Alk5 ratio may be so damaging . The model also predicts that TGFβ will decrease the variability in the cellular response to an inflammatory insult , a finding that will be interesting to test in future studies . There are a number of potential candidates for the TGFβ-mediated repression of MMP13 . The primary candidate for AP-1 competitive inhibition is JunB as there is a substantial body of evidence showing that it is a direct downstream target of Smad3 [38 , 39] and works to antagonise rapid gene transcription [40–42] . Studies have shown it can displace cFos in the AP-1 complex and bind cJun [39 , 41] . It has also been demonstrated to limit the effects of IL-1 , in particular MMP synthesis [38] . Finally , it has been shown to repress gene expression in epithelial-mesenchymal transition in cancer due to upregulation by TGFβ , demonstrating TGFβ can produce significantly high JunB expression to limit gene transcription [38] . There is also evidence that Smad2/3 can interact directly to antagonise AP-1 complex binding , in particular to cFos and cJun [43] . JunD is also a promising candidate along with the tissue inhibitors of metalloproteinases which are all strongly induced by TGFβ [44] . How TGFβ leads to MMP13 mRNA degradation is not currently known but there are a number of potential mechanisms . Both vinculin and far upstream element ( FUSE ) have been shown to bind to the 3’ UTR of MMP13 which in turn promotes the decay of MMP13 mRNA [45] . Sirtuin 2 ( Sirt2 ) has also been shown to supress MMP13 , possibly as a result of TGFβ [46] . Reports have also suggested that histone deacetylase ( Hdac ) 4 can repress MMP13 [47] by binding to the MMP13 promotor [48] preventing further transcription . This protective effect has been questioned by other reports claiming the opposite is true with Hdac4 responsible for an increase in MMP13 [49 , 50] . Lastly , TGFβ leads to upregulation of a number of microRNAs [51] which are known to mediate their effect by increasing mRNA degradation . For example , miR-27a is upregulated by TGFβ [52] and has been shown to target MMP13 mRNA [53] . Determining how TGFβ mediates both AP-1 complex inhibition and mRNA degradation may identify specific therapeutic targets to help reduce cartilage damage with age and OA progression . The addition of active TGFβ to cultured medium has been widely used for engineered cartilage growth but it has been shown that there is a gradient of TGFβ in tissue constructs due to its high rate of depletion via cellular internalisation [54] . Although the turnover of TGFβ was not included in the current model , it would be straightforward to extend the model to include additional reactions . This would be an important modification if the model was to be used to examine TGFβ signalling in the context of tissue engineering . TGFβ signalling shifts towards Alk1 responses with age [21 , 23] . Our model predicted that despite Alk1 signalling leading to an increase in MMP13 [21] and cFos phosphorylation [55] , there is still some degree of repression to the IL-1+OSM-mediated MMP13 upregulation , although greatly reduced . This may be because Alk1 stimulates MMP13 upregulation through a different mechanism to IL-1+OSM . Alk1 is believed to upregulate MMP13 via Smad1 which can activate Runt related transcription factor 2 ( Runx2 ) and lead to increased MMP13 [56] . Conversely , IL-1+OSM induces MMP13 via AP-1 components [17] . As a result , the remaining Alk5 dimers can still provide some repression as Alk1 has little direct effect . Despite this , when Alk1 was the dominant receptor the increase in IL-1+OSM-induced MMP13 mRNA took longer to return to basal expression levels ( compared to when Alk5 was dominant ) . As the basal expression was already high , this would lead to a longer and more pronounced response that could result in damage to already compromised tissue . TGFβ is stored in a latent form in the synovial fluid [57] and is constantly being activated in the joint [58] . This release and activation is increased when under load or during exposure to inflammation [59 , 60] . There are no reports of this changing with age , but if TGFβ is dysregulated in older organisms , the release of TGFβ in response to inflammation could result in increased damage compared to younger counterparts , as a previously protective pathway changes to a catabolic pathway . Identifying how the TGFβ response has changed with age may provide therapeutic targets to help limit such damage in aged individuals , averting cartilage damage and OA development or progression . We used the model to test the effect of potential therapeutic treatments by simulating interventions that would ameliorate the damaging effects of TGFβ . The model predicted that simulated treatments with anti-TGF , anti-Alk1 , or Alk5 addition were all more effective if given at later time points when Alk1 is the predominant receptor , i . e . the timing of interventions may depend on the Alk1/Alk5 ratio . These predictions could be tested in a cellular model of OA in future work . However , we are currently unaware of any antibodies for Alk1 but hopefully they will be available in the future so that these model predictions could be tested . Although overexpression of Alk5 has not yet been tested as a potential treatment for patients , the model suggests that this may be a particularly effective treatment as it prevents Alk1 from becoming the dominant receptor . Testing the predictions in a future study will give further insights into the validity of the assumptions and may suggest further model refinements . Modelling and experimental work is an iterative process . Although we reach points where new insights have been gained , and the model can be published and made publicly available , the cycle may continue with models being re-used , adapted and tested by new experimental data [61] . Although we primarily used deterministic simulations for the computational modelling , stochastic effects can be important in biological systems such as variability in cellular responses . Stochastic modelling predicted that TGFβ reduced the variability of a pro-inflammatory response and when the system was pre-treated with TGFβ this reduced variability was even more pronounced ( S6B Fig ) . Although it can have negative effects in disease , inflammation is an important biological response that helps to eliminate the consequences of cell injury , degrade necrotic cells and the damaged parts of tissues , as well as initiating repair [62] . Therefore , inflammatory responses are normally beneficial and it is only when they become chronically activated that damage and disease progression occur [63]; it is therefore important that they are tightly regulated . The variability of the IL-1+OSM response could lead to damage , with high levels of MMP-13 leading to cartilage degradation [64] . Conversely , insufficient upregulation of MMP13 could result in defective tissue turnover [65] . Thus , TGFβ may help regulate inflammatory responses by reducing variability which may be lost due to ageing and promote the development and/or progression of OA . Since multiple pro-inflammatory pathways have been implicated in the initiation and progression of OA , we focused our attention on the potent cytokine stimulus of IL-1+OSM which we recently demonstrated has considerable overlap with many other pro-inflammatory mediators [17] . Using publically available microarray data allowed us to create a Cytoscape network representative of human OA , with which we could contextualise our model and identify other pathways IL-1 , OSM and TGFβ may interact with . Overlaying our model genes provided biological insight into how gene changes in the model can interact with a range of different pathways ( Fig 9 ) . Specific gene interactions highlight how changes in genes from one pathway can then lead to crosstalk with other pathways , altering them and helping to drive disease progression . This analysis identified four genes present in the model: TGFBR1 , SMAD1 , FOS and JUNB . TGFBR1 was only directly linked to CD84 , a membrane receptor of the signalling lymphocyte activation molecule family . Although the analysis showed that TGFBR1 and CD84 are significantly co-expressed , there is currently no evidence in the literature to support a functional relationship between them . Therefore this could be a novel connection warranting further investigation . CD84 indirectly links TGFBR1 to multiple genes , most of which are already linked to SMAD1 . This indicates that SMAD1 may affect multiple genes that are dysregulated in OA , and highlights the importance of catabolic TGFβ signalling . The gene with the strongest connection to SMAD1 was EGF-like domain multiple 7 ( EGFL7 ) —a gene linked to calcium iron binding , Notch signalling and OA [66] . Although not directly linked to SMAD1 , there were multiple genes in cluster 1 related to Notch , Complement and the Toll-like receptor signalling pathways , providing further evidence of crosstalk between pathways in OA ( Fig 9 ) . JUNB was linked to the immediate early response 3 ( IER3 ) gene , which suggests not only a link to ERK signalling but also plays a key role in cellular stresses such as apoptosis [67 , 68] . Regulator of G-Protein Signalling 1 ( RGS1 ) was also linked to JUNB . RGS1 has been linked to the mechanical loading response [69] , as well as pain in OA patients [70] . cFos and early growth response 1 ( EGR1 ) have been shown to be co-regulated [71] and this may be important in the inflammatory response and OA development [72–74] . Also closely linked to cFos was ZFP36 ring finger protein , a protein that binds to AU-rich element-containing mRNAs to promote their degradation [65] . There is a cFos , cJun and AP-1 binding site in the ZFP36 promoter suggesting its expression may be increased in OA [75 , 76] . Further exploration into these interactions and incorporating them into the model could help to identify interesting targets for future study and possible drug interventions . This study does have some limitations . Firstly , it was necessary to use a chondrosarcoma cell line ( SW1353 ) which is not ideal as it has been shown that they have a different gene expression profile to primary human articular chondrocytes ( HACs ) [77] . However , HACs were not readily available and would not have provided sufficient data for the construction and testing of the computational model . SW1353 cells are a well-established model of inflammation producing a similar catabolic response similar to HACs [77 , 78] and so was a reasonable choice for this study . Secondly , we only examined the effect on gene expression after stimulation with TGFβ , IL1+OSM+TGFβ , or knockdown of ALK5 in this study . It would be particularly interesting to examine the effects of knocking down ALK5 on levels of phospho-Smads in a future study to examine whether or not the increase in MMP13 is due to a switch from Alk5 to Alk1 signalling . Computational models have limitations as it is necessary to make simplifying assumptions . The assumptions of the model presented here were based on current knowledge , enabling the model to capture the behaviour of the experimental system under different conditions . The model was based on two previous published models [25 , 79] and it was necessary to reduce the complexity of integrated model . Therefore we made further simplifying assumptions but showed that this had little effect on the model output ( S9–S11 Figs ) . In order to combine the previous models , we needed to make further assumptions regarding the effect of TGFβ signalling on MMP13 expression and although this allowed us to match our model to experimental data , there may alternative mechanisms that have yet to be explored . In summary , we have shown that TGFβ can repress MMP13 expression and reduce the variability of an inflammatory response which , together , limit joint damage . We confirm that in chondrocytes this is a result of Alk5 receptor signalling whilst computational modelling predicts that receptor changes towards an Alk1-dominant phenotype with age could result in prolonged damage from inflammation . The model output suggests that this is due to both an increase in basal levels of MMP13 and a significant reduction in the protective effect of TGFβ after an acute pro-inflammatory event . Herein , we have highlighted the advantages of combining computational modelling , bioinformatics and experimental techniques to more comprehensively explore a system and potentially identify new therapeutic targets for further study .
IL-1α was a generous gift from Dr . K . Ray ( GSK , Stevenage , UK ) , whilst OSM was generated in-house . TGFβ was purchased from Peprotech ( Rocky Hill , USA ) . All chemicals used for reverse transcription were purchased from Thermo Fisher ( Loughborough , UK ) . The primers and master mix components for real-time PCR ( qPCR ) experiments were designed and purchased from Sigma-Aldrich ( St . Louis , USA ) unless stated otherwise . The human chondrosarcoma cell line , SW1353 , was purchased from American Type Culture Collection ( catalogue no . HTB-94; Rockville , MD ) . Cells were cultured at 37°C in a medium containing Dulbecco's Modified Eagle’s Medium/Nutrient Mixture F-12 ( DMEM/F-12 ) ( Sigma-Aldrich ) supplemented with 1% glutamine , non-essential amino acids , penicillin ( 100 IU/ml ) and streptomycin ( 100 μg/ml ) plus 10% foetal calf serum ( FCS ) . Cells were cultured in serum-free medium overnight prior to stimulation . RNA extraction and cDNA synthesis were performed using the Cells-to-SignalTM kit ( Life Technologies , Carlsbad , USA ) as directed . mRNA levels of genes were obtained from standard curves and corrected using GAPDH or 18S ribosomal RNA levels following TaqMan PCR according to the manufacturer’s instructions ( Applied Biosystems , Warrington , UK ) . Oligonucleotide primers were designed using Primer Express software version 1 . 0 ( Applied Biosystems ) , to be in different exons close to , or spanning , an exon boundary so as to prevent amplification of residual cDNA . The sequences of primers and probes used were as previously described [80] , or: GAPDH: For , 5’-GTGAACCATGAGAAGTATGACAAC-3’; Rev , 5’-CATGAGTCCTTCCACGATACC-3’; Probe , 5’-CCTCAAGATCATCAGCAATGCCTCCTG-3’; TGFBR1: For , 5’-GCAGACTTAGGACTGGCAGTAAG-3’; Rev , 5’-AGAACTTCAGGGGCCATGT-3’; Universal Probe Library ( Roche , Burgess Hill , UK ) Probe #5; ACVRL1: For , 5’-AGACCCCCACCATCCCTA-3’; Rev , 5’-CGCATCATCTGAGCTAGGC-3’; Probe #71; ID1: For , 5’-CCAGAACCGCAAGGTGAG-3’; Rev 5’-GGTCCCTGATGTAGTCGATGA-3’; Probe #39; PAI1: For , 5’-AAGGCACCTCTGAGAACTTCA-3’; Rev , 5’-CCCAGGACTAGGCAGGTG-3’; Probe #19 . The relative gene expression in samples was then determined using either a Lightcycler ( Roche Diagnostics , Indianapolis , USA ) or a 7900HT PCR system ( Applied Biosystems ) . Protein extraction was performed using a previously described protocol [80] . Lysates were resolved by sodium dodecyl sulfate polyacrylamide gel electrophoresis , using a 12% acrylamide gel . Proteins were then transferred to nitrocellulose membranes , and subsequently probed overnight with the following antibodies: anti-Alk5 ( Abcam , Cambridge , UK ) at 1:1000 and anti-GAPDH ( Millipore , Watford , UK ) at 1:30000 . SW1353 chondrocytes were serum-starved overnight prior to treatment for 24 h with 50 nM ON-TARGET Plus siRNAs ( Dharmacon , Colorado , USA ) in serum-free antibiotic containing medium and Dharmafect1 transfection reagent ( Dharmacon ) , following the manufacturer’s protocol . Cells were washed to remove siRNA and transfection reagent before cytokine stimulation . An integrated model was created based upon two previously published models , one representing the pro-inflammatory stimulus IL-1+OSM [25] and another of simulated age-related changes in murine joints which contained a TGFβ component [23] . The model assumptions are given in S2 File together with full details of all components and reactions . The model was constructed in complex pathway simulator ( COPASI ) [81] . Deterministic simulations were run using the simulation algorithm LSODA [82] . Simulations were configured with the following parameters: Duration ( 1440 ) , Interval Size ( 1 ) , Relative Tolerance ( 1e-06 ) , Absolute Tolerance ( 1e-12 ) , Maximum Internal Steps ( 10000 ) . Stochastic simulations were run using the direct method , which uses the Gillespie algorithm [83] . Simulations were configured with the maximum internal step set at 1000000 whilst random seed was not used . COPASI was also used for parameter estimations , primarily using the genetic algorithm ( with the parameters: number of generations ( 1000 ) , population size ( 20 ) , random number generator ( 1 ) and seed ( 0 ) ) , with further refinements using the Hooke and Jeeves algorithm ( with the parameters: tolerance limit ( 1e-08 ) , iteration limit ( 50 ) and Rho ( 0 . 2 ) ) . The model was exported in Systems Biology Mark-up Language ( SBML ) [84] , whilst simulation data were exported from COPASI and visualised using MATLAB r2013a ( MathWorks Inc . , Natick , USA ) , via the built-in graph feature . The model network diagrams were visualised using CellDesigner 4 . 4 [85] and Systems Biology Graphical Notation ( SBGN ) [86] . Simulations were run using COPASI version 4 . 20 . The model was deposited in Biomodels [61] and assigned the identifier MODEL1805080001 . To create a network overview of human OA we accessed publically available OA microarray data ( all Affymetrix ) from the Gene Expression Omnibus [87] . Of these , we only used diseased samples , obtaining 50 synovial samples from 3 different studies [88–90] . These were normalised and then combined using R [91] . Differences caused by experimental variation between samples were normalised using ComBat [92] , followed by determination of gene interactions and the strength of these interactions using Algorithm for the Reconstruction of Accurate Cellular Networks ( ARACNE ) [93] . The resulting data were then imported into Cytoscape [94] and clustered to generate an overview of OA as a network . Functional analysis of the clusters was performed using the Database for Annotation , Visualization and Integrated Discovery ( DAVID ) [95] . | Osteoarthritis ( OA ) is a debilitating disease that is a consequence of cartilage degeneration , often for a variety of reasons . Age is typically the driving force behind OA , and one reason is that biological pathways change as we get older and can become damaging . Transforming growth factor beta ( TGFβ ) is one such pathway , which in young tissues has an important role in keeping the joint healthy as well as protecting against damage caused by inflammation . As we age this pathway starts to promote damage . However , how its effect on inflammation changes has not yet been studied in detail . We used a range of experimental and computational techniques to explore how TGFβ helps to protect against inflammation , but also how these interactions change as we age . We found that with ageing TGFβ may lead to a prolonged inflammatory response in older individuals , resulting in more damage than it normally would in a younger individual suggesting a once protective pathway can now lead to prolonged damage . A better understanding of this change may allow us to develop drugs to repair this pathway , and re-establish its once protective effect . | [
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"analysis",... | 2019 | Systems biology reveals how altered TGFβ signalling with age reduces protection against pro-inflammatory stimuli |
Investigating ligand-regulated allosteric coupling between protein domains is fundamental to understand cell-life regulation . The Hsp70 family of chaperones represents an example of proteins in which ATP binding and hydrolysis at the Nucleotide Binding Domain ( NBD ) modulate substrate recognition at the Substrate Binding Domain ( SBD ) . Herein , a comparative analysis of an allosteric ( Hsp70-DnaK ) and a non-allosteric structural homolog ( Hsp110-Sse1 ) of the Hsp70 family is carried out through molecular dynamics simulations , starting from different conformations and ligand-states . Analysis of ligand-dependent modulation of internal fluctuations and local deformation patterns highlights the structural and dynamical changes occurring at residue level upon ATP-ADP exchange , which are connected to the conformational transition between closed and open structures . By identifying the dynamically responsive protein regions and specific cross-domain hydrogen-bonding patterns that differentiate Hsp70 from Hsp110 as a function of the nucleotide , we propose a molecular mechanism for the allosteric signal propagation of the ATP-encoded conformational signal .
Heat shock proteins ( HSPs ) are essential macromolecules involved in housekeeping cellular activities , whose expression levels can be modulated in response to environmental conditions . The Hsp70 family of proteins plays essential roles in maintaining cellular protein homeostasis . Under normal conditions , Hsp70 can fold nascent polypeptides as they emerge from ribosomes or refold misfolded proteins , regulate the stability and activity of specific proteins and solubilize aggregates [1] , [2] . Hsp70 is also involved in protein degradation , ubiquitination , assembly and disassembly of oligomeric complexes and translocation of proteins across membranes [2] , [3] , [4] . Under stress conditions , increased expression of Hsp70 helps to preserve and recover the correct functional structure of client proteins by binding to denatured conformations [1] . Given its involvement in many cellular control and regulation processes , recent studies have shown a key role of Hsp70 in several diseases: some of these , for instance several cancer types ( breast , endometrial , oral , colorectal , prostate cancers , and certain leukemias ) are associated with overactivity/overexpression of the chaperone [5] . Defects in Hsp70's activity and consequent abnormal protein misfolding and accumulation are involved in neurodegenerative diseases , such as Alzheimer , Parkinson , and Huntington [5] , and in aging processes [6] , [7] . This evidence points to Hsp70 as an interesting drug target [5] , [7] , [8] . From the structural viewpoint , members of the Hsp70 family are composed of two domains connected by a highly conserved 14 residue-linker: a ∼44 kDa N-terminal nucleotide binding domain ( NBD ) , with ATPase activity , and a ∼25 kDa substrate binding domain ( SBD ) , which binds peptides [2] , [4] ( Figure 1 ) . The NBD consists of lobe I and lobe II , which in turn can be divided into subdomains: IA ( residues 1–37 and 120–171 ) and IB ( residues 38–119 ) , IIA ( residues 172–227 and 311–368 ) and IIB ( residues 228–310 ) . Domains IB and IIB are connected by flexible hinges to IA and IIA respectively and regulate the access to the nucleotide binding site . The NBD terminal helix ( residues 369–383 ) is localized between the two lobes and connects the NBD to the inter-domain linker . The SBD also contains two subdomains , a β-sandwich base ( βSBD ) and a domain made of 5 α-helixes ( A to E ) ( αSBD ) forming a lid over the polypeptide binding site [1] , [9] . The βSBD loops protrude upwards forming a deep hydrophobic cavity closed up by helix B , where peptides can bind in a linear conformation [2] . In Hsp70 the relative three-dimensional arrangement of the two domains is regulated by the presence of a specific nucleotide and their activities are coupled through allosteric mechanisms: the specific nucleotide bound to the NBD regulates the SBD conformation required for peptide binding [10] , [11] . The crystal structure of bacterial Hsp70 , DnaK , in the ADP-bound closed conformation [9] displays the two domains completely separated by the linker in a flexible and extended solvent exposed conformation . In contrast , the X-ray structure of yeast Hsp110 , a structural homolog of Hsp70 , shows an ATP-bound open conformation [12] . In this conformation , the αSBD is widely open with respect to the βSBD [2] , and the linker folds in a β-strand localized in a hydrophobic binding pocket between the IA and IIA subdomains of the NBD , thus docking the SBD to the NBD [1] , [7] . In the ATP-bound state , association and dissociation rates for substrates are high , while substrates affinity is low . After ATP hydrolysis to ADP the affinity for substrates is high , while substrate exchange rate is low [2] . Experimental evidence has established the allosteric coupling between NBD and SBD and the essential role of the linker in this mechanism [10] , [13] . The linker transduces allosteric signals in both directions: polypeptide binding in the SBD can also transmit changes to the NBD , increasing the ATP hydrolysis rate [1] . Allosteric coupling between the two domains is absent in Hsp110 [2] , in spite of the high structural similarity of the two proteins . The molecular determinants for the presence or absence of allosteric coupling in these families of proteins are still poorly understood and they represent a significant challenge and an opportunity to structure-based drug design [14] . In this study , we aim at elucidating the atomic origins of the allosteric communication in Hsp70 protein family in comparison with non-allosteric Hsp110 by means of molecular dynamics ( MD ) . By simulating several protein-nucleotide complexes in a fully solvated environment and applying a set of structural and dynamical analyses specifically developed for the study of allosteric systems [15] , [16] , [17] , [18] , we aim to gain insights into the mechanisms of nucleotide-induced signal propagation in Hsp70 and identify functional hotspots involved in the response to ATP and ADP in different conformational states of the protein . To this end , we simulated multiple MD trajectories of Hsp70 and Hsp110 proteins in complex with ATP , ADP and in the apo form ( total simulation time: 1 . 9 microseconds ) . The all-atom detail is maintained throughout the analysis , with the aim of relating the observed large-scale motions and conformational changes to their atomistic physico-chemical origin . The comparison between the allosteric and the non-allosteric species allows determining the interactions and specific clusters of residues that are responsible for the different long-range , nucleotide-driven structural effects at the SBD domain . Finally , coarse-grained elastic network models ( ENM ) are used to investigate the conformational transition mechanisms , and the results are critically discussed with respect to the ones from all-atom simulations .
In the previous sections we identified significant differences in the global structure and dynamics of DnaK and Sse1 in response to ATP or ADP binding . In particular , we observed that the non-allosteric protein is not modulated by the ligand exchange at the lobe I-lobe II interface . In this section we aim to gain residue-based insight into the structural and dynamical rearrangement leading to the allosteric signal between the nucleotide binding site , the linker region and the SBD in the different ligand states of DnaK and compare them to Sse1 . The residue-based modulation is analyzed by considering the time-dependent dynamical evolution of geometric strain and the average conformational mobility to identify mechanical hinges . Geometric strain is a measure of the time-dependent local deformation of the structure with respect to the average conformation ( see Materials and Methods for details ) . Although not measuring the energy involved in the deformation , this quantity monitors protein areas undergoing significant microscopic rearrangements . Namely , regions involved in conformational changes show strain peaks , which can be related to local structural changes during the structural transition in response to a nucleotide . To complement the dynamical analysis , the network of ligand-modulated hydrogen bonds connecting nucleotide binding site and SBD and supporting the allosteric communication is analyzed . The all-atom picture of the conformational transition between open and closed state of DnaK in the presence of ADP , and in the opposite direction in the presence of ATP , presented in the previous sections , consists of two subsequent conformational events occurring in a well-defined order: namely , in the closing transition one has detachment/local unfolding of αSBD , followed by the displacement of βSBD , while in the opening transition the two steps are reversed ( first step is onset of docking of βSBD mediated by the loop 210-linker interaction , followed by unfolding at αSBD ) . The conformational changes from open to closed structure or vice-versa are compared to those obtained with a coarse grained approach based on Elastic Network Models . By imposing the known DnaK start and end conformation and using the PATH-ENM tool from the AD-ENM Web Server [26] , we simulate a transition pathway connecting the two states , based on the most representative normal modes of each conformation . Interestingly , the order of events observed in both directions corresponds to what suggested by our all-atom approach . See Supplemental Information for details ( Figure S7 ) . On the other hand , the correspondence between all-atom and coarse-grained approach is lost when comparing the internal dynamics of Sse1 and of the homology modeled open DnaK . The three most relevant normal modes of the two proteins , calculated by means of the AD-ENM server [26] show a significant similarity ( Figure S8 ) as expected because of the structural homology between the two proteins . Also , the prediction of hinges by means of Anisotropic Network Model ( ANM ) web server HingeProt [27] , [28] locates hinge residues at essentially the same positions ( 393 , 520 , 510 , 537 , DnaK numbering ) in all cases . Therefore , no indication of differentiated ligand-based modulation of the dynamics of Sse1 and DnaK can be obtained by applying ENM-based methods to these systems , despite the fact that the coarse-grained methods catch the global displacements highlighted by the all atom analyses .
The aim of this study was to investigate by MD simulations the molecular basis of allosteric communication mechanisms in DnaK in contrast with the non-allosteric behavior of Sse1 . The conformational transition induced by ATP on the closed state of DnaK , that is the linker docking to the hydrophobic binding pocket at the NBD and the αSBD opening , consists of significant subdomain rearrangements . Computational investigations of large-scale structural changes usually rely on coarse-grained models , which , by making use of simplified protein representations and , in some cases , of the knowledge of the initial and final states of the transition , can efficiently model sizeable rearrangements and provide useful information on the underlying mechanisms . Elastic Network Models can be used to retrieve collective , functionally relevant motions [27] , [28] , [29] around the specific structures on which the Hamiltonian of the system is built and allow to predict possible transition pathways between two given conformations , based on native fluctuations . Recently , a coarse-grained approach based on UNRES MD simulations [22] was used to model the full conformational transition in Hsp70 , by posing distance constraints on the NBD subdomains that simulate the presence or absence of bound ATP . The motion of SBD and NBD domains was shown to be modulated and , interestingly , the occupancy of open and closed SBD states was found to correlate with the “ligand” presence , in agreement with experimental data . Overall , coarse-grained methods can shed light on ligand-activated modulation of protein motions , since the latter are largely determined by the structural organization of the native state . However , such models lack by definition the atomic detail that is required to understand the finely tuned physico chemical origin underlying ligand-based modulation . Similarly , differences arising from sequence divergence in homologues , such as the ones observed between Hsp70/DnaK and Hsp110/Sse1 , cannot easily accounted for by coarse-grained methods . The question addressed in the present work , namely to elucidate the molecular mechanism underlying Hsp70 allostery in comparison to its non allosteric homologue Hsp110 , can therefore take advantage of full atomic detail , as shown in the previous section in comparison to ENM results . On the other hand , a well-known limitation of all-atom MD simulations is sampling . Large conformational rearrangements may be out of reach for a single 100 ns MD simulation run . Enhanced sampling methods like accelerated MD [30] , as well as non-dynamical energy optimization pathways strategies [31] , [32] can provide a high resolution model for a complex structural transition with higher efficiency than unbiased MD . As an alternative , information on the global conformational changes may be inferred from standard MD trajectories by extrapolating collective motions inducing the transition by means of PCA methods . Such an approach was recently attempted for Hsp70 by Nicolai et al . [21] with the aim of defining the dynamic modes involved in the transition . With a complementary point of view , in this paper we have applied a set of recently developed methods [15] , [16] , [17] , [18] that allow us to identify the relevant residues which are involved in the early onset of a conformational change in DnaK . We comparatively analyze the structural and dynamical changes that occur at the single residue level on the ns scale and relate these to the complete conformational transition . The underlying reasoning is that transitions can be triggered or favored by networks of interconnected residues that respond to specific signals ( ligand binding , exchange or even covalent modifications ) by changing their dynamic states . The link between residue-level changes in protein dynamics and long-range propagation of allosteric signals has been probed by NMR analysis [33] , [34] , [35] . Therefore , even if we are still unable to observe full conformational changes , the theoretical identification , coupled to validation against experimental data , of functionally relevant residues throughout the structure of the protein , in explicitly distinct ligand states , helps to shed light on the molecular determinants of allostery in different proteins of the same family . In our study , while the progress of the opening transition in ATP-bound closed DnaK is observed only at an initial stage , the onset of the opposite closing transition occurring in the modeled open DnaK , with the αSBD detaching from the NBD domain , is detected in our MD trajectories to a significant extent . In both directions the transition is the result of consistent microscopic modifications , such as spatial rearrangements or dynamical modulation of specific residues , which work as rigid units and flexible hinges and respond to the specific ligand . The comparison between DnaK and Sse1 , where such conformational changes are not observed , helps validate our observations and provides a model for the allosteric mechanism in Hsp70 , identifying relevant structural residue hotspots at the atomic level . Our combined analysis identifies two pathways transmitting the ligand encoded signal: loop 195 , interacting with ATP , appears as the most relevant sensor and induces a dynamical modulation at loop 210 . In parallel , the coordination with K67 and E168 stabilizes the hydrogen bond network that connects the binding site , through domain IA , to the C-terminal residues and the linker . The combined effect of such interactions results in the stiffening of the interface between lobe I and lobe II and induces the conformational rearrangement of loop 210 . The stabilization of the interface between lobes I and II and with the linker is in turn reflected by the increased coordination of the βSBD with the NBD . In the presence of ADP , the increased linker mobility , due to the loose coordination between the nucleotide and C-terminal end of NBD , as well as the relative mobility of lobes IA and IIA , stimulates motion through a hinge located at residue D390 that is propagated to the βSBD and sets up its rigid movement . Interestingly , the latter is coupled to an increased mobility of NBD subdomain IIB . This picture is supported by the dynamical and sequence-based comparison with the non-allosteric Sse1 . In particular , loop 195 and loop 210 shows a different sequence composition in Sse1 . This is likely to induce a different dynamical behavior , as pointed out in the Results section . In Sse1 the persistence of interactions between loop 195 and nucleotide after ATP-ADP exchange , as well as the increased solvent protection of loop 210 through the adjacent rigid loop 180 traps the structure of the interface between domains IA and IIA of the ATP state in a stable conformation . Available mutational data confirm the relevance of the interactions between loop 195 and nucleotide . Mutants of G195 disrupt the ATP-induced structural dynamics [36] , while T196 mutants have a reduced ATPase activity [36] . Also , the network originating from K67 is known to be essential for ATPase activity and for inter-domain communication , and mutants of this position display a reduced ATPase activity [37] . The same holds for E168 mutants [36] , [37] which induce impairment of interdomain communication [13] , [36] , uncoupling ATP activity and substrate release . Recent NMR work [10] has identified the protein hotspots , constituting the allosteric network in NBD , that respond to the nucleotide exchange with a conformational transition by means of chemical shift perturbation . The identified network consists of the linker and the IIA β-sheet connecting loop 210 and loop 195 , which is in agreement with our simulations results . Interestingly , our flexibility analysis investigates motions on the ns-scale , when conformational changes have not completely occurred yet . It is worth noting that the relative flexibility increase at loop 210 and at the linker in presence of ATP compared to ADP point towards an activation of the same region . Our dynamical results can also be qualitatively compared to hydrogen exchange data , reporting on general flexibility properties [38] . Regions that undergo a modulation of protection to hydrogen exchange , in particular NBD linker and SBD residues 400–500 , are affected in our simulation by a significant change in the dynamical pattern that may anticipate the structural rearrangements . Flexibility changes upon nucleotide exchange , in the non-allosteric Sse1 , are differently distributed on the protein structure , do not involve the interface between NBD and SBD and are in general less intense . These observations support the relevance of the dynamical modulation to the Hsp70 allostery . The binding site of the ATPase-stimulating cochaperone DnaJ has recently been reported to be highly dynamical and located along the β-strand 220 [39] . DnaJ is hypothesized to bind to the open Hsp70 structure and enhance ATP hydrolysis , thereby favoring the substrate- and ADP-bound conformation . Considering the open DnaK state simulation in the presence of ATP , we observed increased rigidity along strand 220 , which propagates to domain IIB . The bound cochaperone can enhance this rigidity and improve the coordination between lobes I and II , hence promoting ATP-hydrolysis . Moreover , the Gestwicki group identified small molecules that bind to the cleft between IA and IIA and work as stimulating effectors of ATP hydrolysis in synergism with DnaJ [40] . One of these compounds is found to bind to the same β-strand involved in DnaJ interaction , which further confirms the main functional role played by this protein region . According to our simulations , the coordination of domain IIA and IIB is modulated by the presence of ATP in both DnaK simulations . The motion of subdomain IIB with ADP is due to the enhanced mobility of strand 220 and of residues 308 , as a consequence of the reduced interaction between loop 195 and nucleotide upon ATP-ADP exchange , inducing the opening of the binding clamp . The effect of the nucleotide exchange on the modulation of the subdomain arrangement in the NDB has been object of experimental and computational investigation . In particular , MD simulations [41] confirmed by NMR data on a homologue system [42] , showed that nucleotide exchange AMPPNP-ADP induces a rotation of domain IIB coupled to the opening of the nucleotide-binding pocket . In agreement with these results , we observe that ADP significantly affects the mobility of IIB by increasing the flexibility of two hinges , residues 225 and 308 , and hence opening the binding clamp . Moreover , a reduced connection of domain IIB is displayed also by the absence of interaction between ADP and residue R342 at the interface between domain IIA and IIB , in both conformations , open and closed . Mutational studies [36] show that residue substitutions around hinge 225 affect the ATPase rate , although they do not perturb the in vivo refolding function . Binding of small molecules in the vicinity of this region in the ADP state and not in the ATP state strongly suggest a ligand-induced modulation of the binding area [43] . The consistency between our dynamical data and experimental results suggests that the dynamical effect induced by ligands on MD-compatible time scales can shed light on the molecular basis of allosteric mechanism coupled to large structural rearrangements . A systematic comparison between Hsp70 and its non-allosteric homologue Hsp110 to single out sequence determinants of Hsp70 allostery , by means of Statistical Coupling Analysis ( SCA ) , was recently performed [19] . A sparse network of coevolving residues that differentiate Hsp70 and Hsp110 families has been identified and hence these residues have been suggested to be necessary for determining the allosteric mechanism in Hsp70 . We have focused instead on the mechanistic differences between DnaK and Sse1 with an all-atom approach and have identified those protein segments that display a different dynamical behavior in the two proteins , either increasing the coordination between nucleotide binding site and SBD or acting as flexible hinges . The hotspots we identified , comprising the β-strands 220 , loop 195 , loop 210 and 180 in lobe II and the hydrogen bond network connecting nucleotide to the linker , provide the minimal mechanistic unit that can be considered allosterically responsive . The comparison with the set of residues provided by Smock et al . returns a common group of residues , including E168 , loop 195 , T151 , K152 , N412 and T413 . As expected due to the differences in the nature of the analysis , the two sets do not fully overlap , since some amino acids involved in the allosteric mechanism may be conserved between Hsp110 and Hsp70 . Also , not every residue of the SCA sector is expected to be directly essential for the allosteric function per se , but might be relevant to ensure stability and compensate for other functionally relevant mutations . In contrast to the SCA analysis , no strongly responsive regions were identified on the β-sheet body of βSBD , but only on its loop regions . This discrepancy might also be influenced by the absence of a peptide substrate in our simulations . Overall , by crossing the dynamical and the sequence information , a subset of critical positions affecting allosteric communication can be promptly identified and rationalized in a mechanistic perspective . By complementing sequence and structural-dynamical analysis one could hence define and explain the minimal required set of mutations that abolish allostery in Hsp70 . More generally , by applying our dynamical analysis approach in a comparative study of an allosteric and a non-allosteric system , we demonstrated that including functional dynamics , internal residue-residue coordination , and protein flexibility information , could help unveil ligand-responsive regions and possible binding sites of a protein with allosteric properties , which may not be immediately evident in a single-structure representation . This offers the opportunity of modulating protein function by specifically addressing regions crucial for the functional dynamics of the protein through specific mutations or small molecules targeting allosteric sites different from the classical binding site targets .
As initial structure of DnaK , an Hsp70 homolog , the X-ray structure of E . coli DnaK ( PDB ID: 2KHO [9] ) in complex with ADP-Mg2+ was employed . ATP complex was built by substituting ADP with ATP-Mg2+ coordinates obtained from 2EA8 structure [44] . Hsp110 X-ray structure of S . cerevisiae ( PDB ID: 3C7N_A [12] ) in complex with ATP-Mg2+ was utilized as starting point . For the ADP complex , ligand coordinates were substituted with ADP-Mg2+ obtained from 1S3X [45] . The apo forms were obtained removing ligand coordinates . The DnaK open conformation homology model , bound to ATP , was obtained from a previous study [19] . ADP complexes and apo structure were built as previously described . All complexes were solvated in a triclinic box of SPC water keeping a minimum distance of 1 nm between the solute and each face of the box . This results in about 100 . 000 water molecules included in the DnaK and Sse1 . Total charge was neutralized with Na+ ions added to the simulation box at random positions . Molecular dynamics simulations were performed with Gromacs 4 . 0 package [46] , employing the GROMOS96 ( ff43a1 ) force field [47] . All complexes were energy relaxed with 1000 step of steepest-descent energy minimization . MD simulations were performed using the LINCS algorithm [48] to constrain bond lengths and periodic boundary conditions were applied in all directions . Long-range electrostatic forces were treated using the Fast Particle-Mesh Ewald method ( PME ) [49] . Van der Waals forces and Coulomb potential were treated using a cut-off of 0 . 9 nm and the simulation time step was set to 2 fs . An initial velocity obtained according to a Maxwell distribution at 300 K was given to all the atoms . All simulations were run in NVT environment employing V-rescale as temperature coupling algorithm , with reference temperature set at 300 K . Three independent simulations were run for both DnaK and Sse1 . The total simulation time was 200 ns for ADP and apo states . Production runs for ATP complexes were extended to 225 ns and 210 ns for DnaK and Sse1 , respectively . To evaluate the effects of ligand bound on single residues and on protein domains and the intrinsic differences between DnaK and Sse1 , different analyses were carried out on the equilibrated trajectories . | Allostery , or the capability of proteins to respond to ligand binding events with a variation in structure or dynamics at a distant site , is a common feature for biomolecular function and regulation in a large number of proteins . Intra-protein connections and inter-residue coordinations underlie allosteric mechanisms and react to binding primarily through a finely tuned modulation of motions and structures at the microscopic scale . Hence , all-atom molecular dynamics simulations are suitable to investigate the molecular basis of allostery . Moreover , understanding intra-protein communication pathways at atomistic resolutions offers unique opportunities in rational drug design . Proteins of the Hsp70 family are allosteric molecular chaperones involved in maintaining cellular protein homeostasis . These proteins are involved in several types of cancer , neurodegenerative diseases , aging and infections and are therefore pharmaceutically relevant targets . In this work we have analyzed , by multiple molecular dynamics simulations , the long-range dynamical and conformational effects of ligands bound to Hsp70 , and found relevant differences in comparison to the known non-allosteric structural homolog Hsp110 . The resulting model of the mechanism of allosteric propagation offers the opportunity of identifying on-pathway allosteric druggable sites , which we propose could guide rational drug-design efforts targeting Hsp70 . | [
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] | 2012 | Molecular Mechanism of Allosteric Communication in Hsp70 Revealed by Molecular Dynamics Simulations |
Persistent hepatitis B virus ( HBV ) infection relies on the establishment and maintenance of covalently closed circular ( ccc ) DNA , a 3 . 2 kb episome that serves as a viral transcription template , in the nucleus of an infected hepatocyte . Although evidence suggests that cccDNA is the repair product of nucleocapsid associated relaxed circular ( rc ) DNA , the cellular DNA polymerases involving in repairing the discontinuity in both strands of rcDNA as well as the underlying mechanism remain to be fully understood . Taking a chemical genetics approach , we found that DNA polymerase alpha ( Pol α ) is essential for cccDNA intracellular amplification , a genome recycling pathway that maintains a stable cccDNA pool in infected hepatocytes . Specifically , inhibition of Pol α by small molecule inhibitors aphidicolin or CD437 as well as silencing of Pol α expression by siRNA led to suppression of cccDNA amplification in human hepatoma cells . CRISPR-Cas9 knock-in of a CD437-resistant mutation into Pol α genes completely abolished the effect of CD437 on cccDNA formation , indicating that CD437 directly targets Pol α to disrupt cccDNA biosynthesis . Mechanistically , Pol α is recruited to HBV rcDNA and required for the generation of minus strand covalently closed circular rcDNA , suggesting that Pol α is involved in the repair of the minus strand DNA nick in cccDNA synthesis . Our study thus reveals that the distinct host DNA polymerases are hijacked by HBV to support the biosynthesis of cccDNA from intracellular amplification pathway compared to that from de novo viral infection , which requires Pol κ and Pol λ .
Hepatitis B virus ( HBV ) chronically infects 257 million people worldwide [1] . Chronic HBV carriers have a higher risk of developing cirrhosis and hepatocellular carcinoma ( HCC ) , which accounts for approximately 686 , 000 annual deaths [1] . Current therapies with viral polymerase inhibitors and pegylated alpha-interferon ( IFN-α ) can drastically reduce virus load and prevent disease progression but fail to cure the viral infection in the vast majority of treated patients [2 , 3] . The reason for the failure of cure is primarily due to the inability to eradicate HBV covalently closed circular ( ccc ) DNA [2 , 4] . The cccDNA exists in the nucleus of infected hepatocytes as a minichromosome and functions to transcribe viral RNAs and support viral replication [5 , 6] . As a result , the persistence of functional cccDNA is responsible for viral rebound after the cessation of antiviral treatment [7 , 8] . Therefore , understanding the mechanisms underlying cccDNA biosynthesis , maintenance and transcription regulation is essential for the development of novel antiviral therapeutics to cure chronic hepatitis B [9–11] . Unlike chromosomal DNA , cccDNA lacks a replication origin , and thereby cannot replicate through semi-conservative replication . Instead , all cccDNA molecules are converted from relaxed circular ( rc ) DNA in the nucleocapsids of infecting virions or mature cytoplasmic progeny nucleocapsids [12–14] . The biosynthesis of cccDNA from these two routes is designated as de novo synthesis and intracellular amplification , respectively . The rcDNA is a nicked double-stranded DNA with cohesive ends at both strands . The minus strand of rcDNA , synthesized from reverse transcription of pregenomic ( pg ) RNA , has a viral DNA polymerase covalently attached to the 5’ end and a short redundant sequence at both termini , whereas the plus strand has an 18 nt RNA primer linked to its 5’ end and is variable in length at the 3’ end . Given the unique structure of rcDNA , the conversion of rcDNA to cccDNA requires at least four steps: ( i ) the completion of plus strand DNA synthesis by DNA polymerases; ( ii ) removal of the viral polymerase covalently attached at the 5’ end of minus strand DNA and the capped RNA primer at the 5’ end of plus strand DNA via unknown mechanisms; ( iii ) processing of the ends of both strands of rcDNA by cellular nucleases; and ( iv ) filling in the gaps by host DNA polymerases and ligation of DNA ends by ligases [15] . These biochemical reactions have been speculated to be carried out by host cellular DNA repair machinery . Indeed , tyrosyl-DNA phosphodiesterase 2 ( TDP2 ) [16] , flap endonuclease 1 ( FEN1 ) [17] and DNA ligases 1 , 3 and 4 [18] had been shown to play essential roles in cccDNA synthesis . As for the gap-filling of rcDNA plus strand , viral polymerase activity is dispensable and an unidentified cellular DNA polymerase must have been hijacked for this process [19] . Recently , a genetic study in HepG2 cells expressing sodium-taurocholate cotransporting polypeptide ( NTCP ) , but deficient in expression of individual cellular DNA polymerases revealed that DNA Pol κ and Pol λ were required for cccDNA formation in de novo HBV infection [20] . However , this work did not address the role of these cellular DNA polymerases in cccDNA biosynthesis from the intracellular amplification pathway which is crucial for maintaining a proper size of cccDNA pool in infected hepatocytes [21 , 22] . Of note , our recent work showed that treatment with HBV core protein allosteric modulators ( CpAMs ) to induce premature uncoating of viral nucleocapsids led to reduced cccDNA formation in de novo infection , but increased cccDNA synthesis through intracellular amplification pathway [23] . This finding suggests that cccDNA de novo synthesis and intracellular amplification are differentially regulated by viral and/or host cellular factors and may recruit different DNA repair complexes to convert rcDNA into cccDNA . Accordingly , we investigated whether cccDNA intracellular amplification pathway utilizes the same DNA polymerases as cccDNA de novo synthesis does through a chemical genetics approach . To our surprise , we found that a non-canonical DNA repair polymerase Pol α , as well as Pol δ and ɛ , but not Pol κ and Pol λ , substantially contributed to the conversion of rcDNA to cccDNA during intracellular amplification of cccDNA in human hepatoma cells . Particularly , both inhibition of Pol α by specific inhibitors and silencing of Pol α expression by siRNA resulted in reduction of cccDNA synthesis . Conversely , inhibition of cccDNA formation by a Pol α inhibitor could be rescued by a single amino acid substitution in Pol α that abrogates the binding of the inhibitor . We also obtained evidence suggesting that Pol α is recruited to HBV rcDNA and participates in the repair of the nick in minus strand DNA . Taken together , we have identified Pol α as well as Pol δ and ɛ as novel host factors essential for cccDNA intracellular amplification and provided further evidence supporting the notion that de novo cccDNA synthesis and intracellular amplification of cccDNA are differentially regulated .
It was reported recently that APH , an inhibitor of B family DNA polymerases that include Pol α , Pol δ and Pol ε , did not inhibit HBV cccDNA biosynthesis during de novo infection [20 , 24] . Consistent with this report , we demonstrated that , while cccDNA synthesis in HBV infection of C3AhNTCP cells can be inhibited by HBV entry inhibitor Myrcludex-B as compared to dimethyl sulfoxide ( DMSO ) -treated controls [25] , APH treatment during the infection had no apparent influence on the levels of cccDNA ( Fig 1A , upper panel ) . Meanwhile , we also validated the authenticity of the DNA species present in the Hirt DNA preparations , as 88°C heat denaturalization followed by EcoRI digestion converted DP-rcDNA and cccDNA into 1 . 6 kb single-stranded DNA and unit-length ( 3 . 2 kb ) double-stranded linear ( dsl ) DNA , respectively ( Fig 1A , lower panel ) [26 , 27] . Because EcoRI linearization of cccDNA after heat denaturalization of Hirt DNA increased Southern blot hybridization signals and resulted in a more accurate quantification of cccDNA , we used this cccDNA validation method as our routine cccDNA assay in this study . As stated above , cccDNA synthesis occurs not only during de novo infection , but also through a process called intracellular amplification in which rcDNA in cytoplasmic progeny nucleocapsids are shuttled back into the nuclei to convert into cccDNA [12–14] . To study cccDNA intracellular amplification pathway , we utilized HepAD38 cells which support tetracycline ( tet ) -off inducible HBV replication and cccDNA intracellular amplification but not de novo infection [28] . Meanwhile , a reversible HBV polymerase inhibitor named foscarnet , or phosphonoformic acid ( PFA ) , was applied to cell culture to arrest and synchronize HBV DNA replication primarily at full-length minus-strand DNA stage ( S1 Fig ) . Upon release of PFA arresting , HBV DNA synthesis resumed , resulting in the sequential generation of rcDNA and cccDNA in a time-dependent manner [29] . As shown in S1 Fig , cccDNA became easily detectable after 16 h of PFA removal by Southern blot hybridization . Interestingly , distinct from its effect on cccDNA synthesis in de novo HBV infection , APH treatment reduced the level of cccDNA in HepAD38 cells in a dose-dependent manner , while other replication intermediates , including ssDNA , rcDNA and DP-rcDNA , were not affected ( Fig 1B ) . Similar effect of APH on cccDNA synthesis was also observed in another HepG2-derived stable cell line ( HepDES19 ) supporting HBV replication ( S2 . Fig ) . To investigate whether the observed reduction of cccDNA in APH-treated HepAD38 cells was due to reduced synthesis or accelerated decay , we determined the effect of APH on the established cccDNA pool . Specifically , HepAD38 cells were cultured for 48 h after release of PFA arresting to allow the establishment of cccDNA pool and then followed by treatment with indicated concentrations of APH for 24 h . As shown in Fig 1C , APH treatment did not apparently alter the level of established cccDNA . This result thus implies that APH specifically reduced cccDNA synthesis rather than accelerated its decay . Moreover , the effect of APH on cccDNA synthesis is independent of PFA arresting of HBV DNA synthesis , because in the absence of PFA arresting , treatment of HepAD38 cells with APH from day 6 to day 8 after tet removal similarly reduced the level of cccDNA ( S3 Fig ) . Collectively , these results indicate that one or multiple APH sensitive DNA polymerases might be required for HBV cccDNA synthesis via intracellular amplification pathway , but not de novo infection of hepatocytes . The distinct effects of APH on HBV cccDNA biosynthesis imply that different host DNA polymerases are hijacked by the two pathways to repair rcDNA into cccDNA . Knowing Pol κ and Pol λ contribute to de novo cccDNA synthesis [20] , we performed a focused siRNA screen to identify which cellular DNA polymerases are required for intracellular cccDNA amplification in HepAD38 cells . Using a set of siRNAs that were previously used in de novo cccDNA synthesis screening [20 , 30] , we achieved efficient knockdown for the majority of the cellular DNA polymerases in HepAD38 cells ( Fig 2A ) and demonstrated that knocking down the expression of only Pol α , Pol δ or Pol ε resulted in significant reduction of cccDNA amplification ( Fig 2B ) . These results are consistent with the results that APH , an inhibitor of the B family DNA polymerases , specifically inhibits cccDNA amplification , but not de novo cccDNA synthesis ( Fig 1B ) . Intriguingly , knocking down the expression of polymerases Pol κ or Pol λ , which had been shown to be essential for de novo cccDNA synthesis [20] , did not apparently affect cccDNA intracellular amplification ( Fig 2B ) . Of note , due to the insufficient knockdown of POL H , Q , Z and REV1 expression ( Fig 2A ) , their roles in cccDNA amplification cannot be determined . Nevertheless , these results further strengthen the notion that different host cellular DNA polymerases preferentially involve in cccDNA synthesis from de novo infection and intracellular amplification pathways . Amplification of cccDNA was inhibited by both APH treatment ( Fig 1B ) and silencing of three B family DNA polymerases ( Fig 2B ) . These results suggest all the three DNA polymerases play a role in the conversion of rcDNA to cccDNA , presumably by completing plus strand DNA synthesis and/or catalyzing DNA strand elongation during DNA end processing . In fact , both Pol δ and ɛ are best known as a replicative DNA polymerase that catalyzes both lagging and leading strand DNA synthesis during semi-conservative DNA replication [31] , they also play an important role in long-patch base excision repair and nucleotide excision repair [31] . We thus postulated that these two DNA polymerases may primarily mediate the inhibitory effect of APH on cccDNA synthesis . To investigate this hypothesis , Pol δ1 expression in HepAD38 cells was knocked out by CRISPR-Cas9 to generate a cell line HepAD38-POLD1-/- . The loss of Pol δ1 expression was confirmed by a Western blot assay ( S4 Fig , panel A ) . Sanger sequencing of the gRNA targeting genomic DNA region further confirmed the disruption and indel mutation of two POLD1 gene alleles ( S4 Fig , panel B ) . In agreement with our siRNA screening results ( Fig 2B ) , the deficiency of Pol δ1 hampered cccDNA amplification ( S4 Fig , panel C ) . Ironically , APH treatment of HepAD38-POLD1-/- cells still significantly reduced cccDNA amplification ( S4 Fig , panel C ) , suggesting that another APH sensitive DNA polymerase is also required for cccDNA amplification and mediates APH suppression of cccDNA synthesis . Moreover , overexpression of Pol δ1 in HepAD38 cells as well as partial reconstitution of Pol δ1 expression in HepAD38-POLD1-/- cells by plasmid transfection not only increased the level of cccDNA , but also proportionally increased the level of DP-rcDNA ( S4 Fig , panel D ) . Because APH specifically reduced cccDNA but not DP-rcDNA ( S4 Fig , panel C ) , these results further argue a critical role of other APH-sensitive polymerases in cccDNA amplification . Pol α1 , another APH-sensitive DNA polymerase , was also identified by siRNA screening to be required for cccDNA amplification in HepAD38 cells ( Fig 2 ) . Pol α1 is a component of the primosome complex . Once primase has created an RNA primer , Pol α starts DNA synthesis to elongate the primer at replication origins and on Okazaki fragments by approximately 20 nucleotides , from which the other replicative DNA polymerases , Pol δ or Pol ε , catalyze further elongation of the DNA chain [31 , 32] . To investigate the role of Pol α in cccDNA amplification , we first confirmed our siRNA screening result by using additional Pol α1 siRNAs to deplete its expression and demonstrated that silencing of Pol α1 specifically resulted in cccDNA reduction compared with that in cells transfected by scramble siRNA ( Fig 3A and 3B ) . Although APH treatment could further reduce the level of cccDNA in cells that Pol α1 expression was knocked down by siRNA ( S5 Fig ) , the results clearly indicate that Pol α plays an important role in cccDNA amplification and other members of group B family DNA polymerases also contribute to cccDNA amplification . Pol α1 is the catalytic subunit of primosome which also contains a regulatory subunit Pol α2 and two primase subunits PRIM1 and PRIM2 . In addition to Pol α1 , knockdown of the regulatory subunit Pol α2 also reduced cccDNA amplification ( S6 Fig ) , suggesting Pol α1 most likely couples with Pol α2 in regulating cccDNA amplification . Unfortunately , our repeated attempts to knock down each of the two primase subunits were not successful . CD437 , a recently identified Pol α1 specific inhibitor [33] , dose dependently reduced cccDNA levels in HepAD38 and HepDES19 cells , while the amount of rcDNA was not significantly affected ( Fig 3C and S2 Fig ) . As expected , cccDNA reduction was due to impaired cccDNA formation , rather than accelerated cccDNA decay because the stability of existing cccDNA was not affected by CD437 treatment ( S7 Fig ) . It had been reported that L764 is a key residue for Pol α1 to interact with CD437 and L764S mutation renders Pol α1 resistance to CD437 [33] . Importantly , this residue is outside of the Pol α1 catalytic domain , thereby inferring that the mutation does not affect Pol α1 function [33] . To validate that CD437 suppresses cccDNA amplification via specific targeting of Pol α1 , we utilized a CRISPR knock-in strategy to edit Pol α1 into Pol α1L764S in HepAD38 cells . The principle of CRISPR knock-in design is depicted in Fig 4A . The successful gene editing of TTA to TCA was confirmed by Sanger sequencing of genomic DNA regions spanning the POLΑ1 L764 position for acquired individual clones ( Fig 4A ) . In all tested HepAD38-Pol α1L764S clones , cccDNA amplification was resistant to CD437 treatment as comparing to parental cells expressing wild-type Pol α1 ( POLΑ1WT ) ( S8 Fig ) . This phenomenon was further validated with two representative clones harboring the POLΑ1 L764S mutation ( POLΑ1L764S C6 and C7 ) . As shown in Fig 4B and 4C , although 0 . 2 μM and 1 μM of CD437 treatment significantly reduced cccDNA amplification in POLΑ1WT cells , it did not affect cccDNA amplification in POLΑ1L764S C6 and C7 cells . As a control , cccDNA amplification in all these cells was still sensitive to APH treatment ( Fig 4B and 4C ) . These results thus indicate that CD437 inhibits cccDNA amplification by specifically targeting Pol α1 and suggest that DNA Pol α is indeed involved in cccDNA amplification in HepAD38 cells . In addition to its role in DNA replication , Pol α also localizes in the cytoplasm and is responsible for the generation of cytosolic DNA:RNA hybrids to antagonize pattern recognition receptor cyclic GMP-AMP synthase ( cGAS ) , which prevents spontaneous activation of type-I interferon response [34] . To determine whether suppression of Pol α expression or its enzymatic activity in HepAD38 cells induces interferon and proinflammatory response which subsequently activates antiviral protein expression and hampers cccDNA amplification , we examined the expression of selected key cytokines ( IL-29 , CXCL10 , TNF-α and IL-1β ) upon silencing of Pol α1 by two different siRNAs or inhibition of Pol α activity by APH . No induction of these cytokines had been observed under these treatment conditions ( Fig 5A–5C ) . In agreement with these results , the inhibitory effect of APH on cccDNA amplification did not rely on new protein synthesis , as cccDNA amplification could be efficiently inhibited by APH under the condition that protein synthesis was blocked by cycloheximide ( Fig 5D ) . Moreover , inhibition of Pol α by APH for as short as 8 h was sufficient to inhibit cccDNA amplification ( Fig 5E ) . Because inhibition of group B DNA polymerases can inhibit cellular DNA synthesis and APH is commonly used for arresting cell cycle at S phase [35] . Therefore , it is possible that the observed reduction of cccDNA synthesis by inhibition of Pol α and other group B DNA polymerases was due to disruption of cell cycle progression of HepAD38 cells . Although our cccDNA synthesis assays were performed in confluent cultures , we would like to experimentally determine whether APH and CD437 treatment altered cell cycle progression under this condition . As shown in S9 Fig , flow cytometry analyses demonstrated that treatment of HepAD38 cells cultured in the sub-confluent condition with APH or CD437 arrested the cells in S phase , whereas culturing HepAD38 cells under the confluent condition which our cccDNA synthesis assays were performed arrested the cells in G1/S or G2/S phases and APH or CD437 treatment for 24 h did not change the cell cycle distribution . Furthermore , Western blot analysis of histone H3 Ser10 phosphorylation , a marker of mitosis [36] , confirmed that the cells in confluent cultures are arrested at G1 or G2 phase , but not in M phase ( S9 Fig , panel B ) . Hence , the observed effects of APH and CD437 on cccDNA synthesis under this experimental condition are unlikely due to their regulation of cell division . Taken together , several lines of evidence presented above strongly suggest that Pol α plays a rapid and direct role in cccDNA amplification in HepAD38 cells . As above functional studies have indicated that Pol α plays a direct role in cccDNA amplification , we further investigated whether Pol α and other B family DNA polymerases are physically recruited to HBV DNA during the conversion of rcDNA to cccDNA . To this end , we performed chromatin immunoprecipitation ( ChIP ) assay to characterize the potential interaction between HBV DNA and Polymerases , with histone H3 as a positive control . Because HepAD38 cell harbors a single copy of the tet-CMV IE promoter driven HBV transgene [28] , we designed specific primers to selectively amplify episomal viral DNA ( F1-R1 ) and the viral transgene integrated in chromosome ( F2-R2 ) ( Fig 6A ) . As anticipated , no episomal HBV DNA was pulled-down by the antibody against Pol α1 or histone H3 in the absence of HBV replication ( Fig 6B , tet+ ) . However , a significant association between episomal HBV DNA and Pol α1 or Pol δ , but not Pol ɛ and Pol κ , was detected at 24 h after removal of PFA to allow rcDNA and cccDNA synthesis to take place ( Fig 6B , tet-/DMSO ) . Interestingly , inhibiting the conversion of rcDNA to cccDNA by APH did not alter the association of Pol α1 to episomal HBV DNA ( Fig 6B , tet-/APH ) . This later result suggests that inhibition of Pol α1 enzymatic activity does not disrupt its recruitment to episomal HBV DNA . However , the sole scaffold function of Pol α1 devoid of enzymatic activity is not sufficient to support cccDNA synthesis . In marked contrast , only H3 antibody , but not antibody against any of the tested polymerases , could pull down HBV transgene in a manner independent of HBV DNA replication and cccDNA synthesis ( Fig 6C ) . These results thus suggest that Pol α1 and Pol δ can be specifically recruited to HBV rcDNA , but not the HBV transgene integrated in the cellular chromosome , most likely through interacting with rcDNA associated proteins , such as other components of DNA repair machinery or recognition of specific histone post-translational modifications . Notably , because cccDNA constitutes only a small portion of total HBV DNA ( Fig 1A ) [26 , 37] , the fact that approximately 10% of episomal HBV DNA were associated with histone H3 indicates that in addition to cccDNA , other HBV nuclear DNA species , i . e . deproteinized ( or protein-free ) rcDNA , may also be associated with nucleosomes and exist as minichromosomes ( Fig 6B ) . In support of this notion , blocking the conversion of DP-rcDNA to cccDNA by APH did not affect the association between histone H3 and HBV DNA ( Fig 6B , tet-/APH ) . Moreover , histones H3 and H2A were significantly enriched onto episomal HBV DNA after enabling rcDNA synthesis by removal of PFA from culture medium ( Fig 6D ) . In order to determine which step of rcDNA to cccDNA conversion requires Pol α and other B group DNA polymerases , we first examined their role in the gap filling event ( or the elongation ) of viral plus strand DNA . To this end , HepAD38 cells were cultured in the absence of tet and presence of PFA for 4 days to arrest viral DNA synthesis at the full-length minus-strand DNA stage , and then were mock-treated ( DMSO ) or treated with 1 μM of APH or CD437 in the absence of PFA for 24 h to resume plus-strand DNA synthesis . HBV core DNA was detected by Southern blot assay with a probe specifically hybridizing to plus-stranded viral DNA . The results clearly indicated that both APH and CDC437 did not inhibit plus strand synthesis ( Fig 7A ) . Similarly , siRNA knockdown of Pol α1 expression also did not affect plus strand synthesis ( Fig 7B ) . In agreement with these results , in vitro synthesis of plus-strand DNA in purified PFA-arrested nucleocapsids in an endogenous DNA polymerase reaction ( EPR ) could not be inhibited by APH or CD437 ( Fig 7C ) . These results clearly suggest that Pol α and other group B DNA polymerases do not play a role in elongation of the incomplete plus strand DNA in cccDNA synthesis . However , due to the limited resolution of this assay , the role of those cellular DNA polymerases in the closure of the gap or nick in both strands of rcDNA cannot be determined . Recently , a covalently closed minus strand rcDNA , or cc ( - ) rcDNA , had been identified and considered as a potential intermediate of cccDNA synthesis [38 , 39] . This finding suggests that the discontinuity in two strands of rcDNA is sequentially repaired . While the precursor—product relationship of DP-rcDNA , cc ( - ) rcDNA and cccDNA has not been firmly established in the field , it will be interesting to dissect their relationship by inhibition of cccDNA synthesis with DNA polymerase inhibitors . As shown in Fig 7D , treatment of Hirt DNA preparations with exonuclease I ( Exo I ) and III ( Exo III ) to remove DNA species containing open ends revealed a ladder of several DNA species migrating between supercoiled cccDNA and rcDNA , which can be converted into unit-length double-stranded linear DNA by EcoRI digestion and are thus different topological isoforms of supercoiled cccDNA [40 , 41] . Moreover , an additional DNA species migrating faster than cccDNA and resistant to EcoRI digestion is the covalently closed minus strand DNA , or cc ( - ) DNA , which is derived from exonuclease digestion of the gapped positive strand of cc ( - ) rcDNA [38] ( as depicted in Fig 7D ) . To investigate whether Pol α is required for the repair of the minus strand DNA gap in cccDNA amplification , HepAD38 cells were mock-treated or treated with 1 μM of APH or CD437 upon removal of PFA for 24 h . As anticipated , treatment with APH and CD437 reduced the levels of cccDNA . Interestingly , the level of cc ( - ) rcDNA was also reduced in APH and CD437 treated cells ( Fig 7E ) . These results thus suggest that Pol α may play an important role in repairing the discontinuity of minus strand in the conversion of rcDNA to cccDNA .
Different from adenoviruses which antagonize cellular DNA repair machinery to prevent unwanted repair of its double-stranded linear DNA genome [42] , or herpes simplex virus-1 ( HSV-1 ) for which DNA repair proteins are recruited to their incoming genomes to restrict viral transcription [43] , HBV , on the other hand , takes advantage of cellular DNA repair machinery to repair the discontinuity in its rcDNA genome and convert into a transcription permissive cccDNA . Indeed , due to its limited coding capacity , the replication of HBV genomic DNA heavily relies on the exploitation of host cellular proteins [44] . Several host cellular DNA repair proteins , including TDP2 [16] , DNA ligases [18] , FEN1 [17] and DNA topoisomerases [29] have been identified to be involved in cccDNA synthesis . Through a loss-of-function genetic screening in HBV infection of HepG2NTCP cells , Pol κ and Pol λ were found to significantly contribute to cccDNA biosynthesis in de novo HBV infection [20] . Taking a chemical genetics approach , we demonstrated herein that both siRNA knockdown of Pol α expression and inhibition of its enzymatic activity by APH or CD437 reduced cccDNA intracellular amplification ( Figs 1B , 2 and 3 ) . The fact that cccDNA amplification in cells harboring mutant Pol α resistant to CD437 was no longer inhibited by the compound verified Pol α1 as its functional target in suppression of cccDNA synthesis ( Fig 4 ) . It is worth noting that our siRNA screening also identified Pol δ1 and Pol ε that appeared to contribute to cccDNA amplification ( Fig 2 ) . Moreover , reduced cccDNA synthesis in Pol δ knockout HepAD38 cells ( S4 Fig ) and recruitment of Pol δ to episomal HBV DNA ( Fig 6B ) strongly suggest an important role of this DNA polymerase in cccDNA amplification . Although Pol ε and Pol δ are primary DNA replication polymerases catalyzing leading chain and lagging chain elongation , they also play critical roles in nucleotide excision repair and base excision repair [31] . Hence , like Pol α , those DNA polymerases may also participate in cccDNA amplification Interestingly , distinct from de novo cccDNA synthesis where Pol κ and Pol λ play an essential role [20] , we found that these cellular DNA polymerases were dispensable for cccDNA intracellular amplification ( Fig 2 ) . This finding is consistent with the report showing that siRNA knockdown of Pol κ expression in HepDES19 cells did not inhibit cccDNA intracellular amplification [18] . Consistent with these functional assay results , ChIP assay also indicated that Pol κ was not recruited to episomal HBV DNA in HepAD38 cells ( Fig 6B ) . Instead , we demonstrated herein that Pol α as well as Pol δ and ɛ play an important role in intracellular amplification of cccDNA but are not required for de novo cccDNA synthesis ( Fig 1 ) [20] . The requirement of distinct cellular DNA polymerases in cccDNA synthesis through the two different pathways strongly suggests that different DNA repair complexes may be recruited to convert rcDNA from incoming virions and progeny nucleocapsids into cccDNA . One plausible explanation for this intriguing phenomenon is that whereas the plus-strand of rcDNA in virion particles is largely incomplete , the length of plus strand DNA from progeny mature nucleocapsid is much longer and close to completion [23 , 37] . Such a structural difference in the plus strand 3’ terminus of precursor rcDNAs may result in the recruitment of different DNA repair complexes to catalyze their conversion into cccDNA . Alternatively , it is also possible that the infecting virions enter the cytoplasm of hepatocytes via endocytosis where the low pH environment in endosomes may trigger structural shifts of nucleocapsids . On the contrary , the intracellular progeny nucleocapsids are most likely not exposed to such an acid environment . The difference in nucleocapsid structures may result in nuclear import of rcDNA via distinct pathways and deposition of rcDNA in different regions of the nucleus . Indeed , a recent study revealed that interaction between capsid and a capsid disassembly related protein CPSF6 determines the nuclear domain where human immunodeficiency virus ( HIV ) DNA travels to and subsequently integrates at [45] . Moreover , human papilloma virus ( HPV ) DNA replication occurs in specific nuclear regions where fragile host DNA chromosomes and DNA repair proteins localize [46 , 47] . Therefore , a likely scenario is that the distinct structure features presented on the nucleocapsids from incoming virions and intracellular progeny mature nucleocapsids direct their rcDNA to be transported to distinct nuclear domains where different DNA repair complexes are enriched and recruited for cccDNA synthesis . In addition , despite the fact that HBx protein is not required for de novo cccDNA synthesis [48] , due to its expression in HBV replicating stable cell lines , such as HepAD38 and HepDES19 cells , but lack during the initial period of de novo infection , the contribution of HBx in the observed differential regulation of cccDNA amplification in these cell lines cannot be ruled out . Mechanistically , our results suggest a direct role of Pol α in cccDNA amplification . First , inhibition of cccDNA amplification by Pol α inhibitors was rapid and independent of the induction of antiviral genes ( 5A , Fig 5C and 5E ) ; Second , stopping new protein synthesis by cycloheximide did not attenuate the effect of Pol α inhibitors on cccDNA amplification ( Fig 5D ) ; Third , our experiments were conducted in confluent and quiescent cells , thereby the observed reduction in cccDNA synthesis by suppression of Pol α expression or inhibition of its polymerase activity is not due to the indirect effect of suppressing the cell cycle progression ( S9 Fig ) . Finally , we demonstrated that Pol α1 and Pol δ are physically recruited to HBV rcDNA , but not to integrated HBV transgene , by ChIP assays ( Fig 6 ) . It was reported recently that unintegrated retroviral DNA are loaded with histones quickly after their nuclear import to assemble into an extrachromosome structure that is under epigenetic regulation [49 , 50] . Interestingly , we demonstrated herein that a substantial percentage ( 10% ) of episomal HBV DNA is associated with histone H3 ( Fig 6 ) , suggesting that in addition to cccDNA , other HBV DNA species , most likely the nuclear DP-rcDNA , may also acquire nucleosome structures and exist as episomal minichromosomes [51] . This notion is further supported by the results that inhibition of rcDNA conversion into cccDNA by APH does not alter the amount of HBV DNA associated with histones . Moreover , accumulating evidence suggests that certain histone modifications that orchestrate nucleosome remodeling at DNA damage sites are involved in regulating the recruitment of DNA repair factors [52–55] . Therefore , histone association or chromatinization of rcDNA may be necessary for efficient recruitment of DNA repair complex and cccDNA formation . Compared to histones , only a small , but significant fraction of episomal HBV DNA ( approximately 0 . 05% ) were associated with Pol α1 or δ , which is consistent with the fact that only a small fraction of DP-rcDNA is converted into cccDNA in hepatoma cells . Although Pol α can bind to histone H2A and histone H2B in vitro [56] , its differential recruitment to a small fraction of HBV episomal rcDNA , but not to the integrated HBV transgene , indicated that other viral and/or host cellular factors play a role in recruitment of Pol α to HBV DNA . In addition to rcDNA , a small percentage of cccDNA is converted from dslDNA , a replication intermediate generated through in-situ priming of plus strand DNA synthesis [57] , via non-homologous end joining ( NHEJ ) DNA repair pathway [27 , 58] . The dslDNA-derived cccDNA usually does not support productive viral replication due to the error-prone repair of viral DNA by the NHEJ pathway [59 , 60] . As stated above , despite the fact that several DNA repair enzymes have been identified to play essential roles in cccDNA synthesis from rcDNA precursor , the DNA repair pathways that catalyze rcDNA from either incoming virions or mature progeny nucleocapsids into cccDNA remain elusive . However , the recent identification of a cc ( - ) rcDNA species suggests that conversion of rcDNA into cccDNA might be through a sequential repair of the nick and gap of minus and plus strands of rcDNA by one or two distinct single-strand DNA repair complexes [17 , 38] . The fact that inhibition of Pol α by CD437 reduced the formation of cc ( - ) rcDNA ( Fig 7E ) indicates that Pol α is required for the repair of rcDNA minus strand . Recently , FEN1 , a single strand DNA repair component , had been shown to be required for cccDNA synthesis via both de novo infection and intracellular amplification pathways , most likely by processing the 5’ flapped structure presented in rcDNA . It will be interesting to further investigate the functional relationship between Pol α and FEN1 in cccDNA synthesis . Unlike its role in DNA replication , the role of Pol α in DNA repair was only intensively studied recently . Particularly , in addition to promoting NHEJ DNA repair in Hela cells [61] , Pol α has been shown to catalyze the fill-in synthesis to counteract DNA hyper-resection in double strand break repair of telomerase DNA and hence , regulate the choices of DNA repair pathways [62 , 63] . Since our results suggest a role of Pol α in the repair of the HBV minus strand DNA discontinuity ( Fig 7E ) , it is possible that Pol α catalyzes the partial extension of the 3’ end in the minus strand that creates a homology overlap with the 5’ end , which could be repaired through the homology-directed DNA repair pathway . This hypothesis will be investigated by comparing the terminal sequence of minus strand DNA bound to Pol α in the absence and presence of APH by ChIP-seq technology . In conclusion , taking advantage of a chemical genetics screening approach in combination with our synchronized and rapid cccDNA formation assay in HepAD38 cells , we obtained evidence supporting a hypothesis that cellular Pol α as well as other members of B group DNA polymerases are required for cccDNA intracellular amplification , most likely through direct recruitment to nuclear rcDNA and catalyzing cccDNA synthesis . The cccDNA intracellular amplification in human and mouse hepatocyte-derived cell lines supporting transient or stable HBV replication or in the liver of HBV transgenic mice have been documented in the last three decades [26 , 28 , 64–67] and widely used as the model of HBV cccDNA synthesis [17 , 18 , 38] . However , due to the small extent or undetectable level of cccDNA amplification in HBV infected primary human hepatocytes or NTCP-expressing HepG2 cells [20 , 22 , 48 , 68 , 69] , it remains to be determined whether the cccDNA amplification in the stable cell lines and HBV infected hepatocytes is via the same or distinct mechanisms . Nevertheless , identification of distinct cellular DNA polymerases required for de novo cccDNA synthesis and intracellular cccDNA amplification sheds light on uncovering the DNA repair pathways governing the establishment and maintenance of cccDNA pools in HBV infected hepatocytes , which will establish molecular basis for development of novel therapeutics to resolve chronic HBV infections [44] .
Human hepatoblastoma cell HepG2 and its subclone C3A ( ATCC HB-8065 ) were purchased from ATCC . C3AhNTCP cell line stably expressing human NTCP was established as previously described [70] . HepG2 and C3ANTCP were cultured in DMEM/F12 media ( Corning ) supplemented with 10% fetal bovine serum ( FBS ) , 100 U/ml penicillin and 100 μg/ml streptomycin . HepAD38 is an HepG2 derived cell line that supports tetracycline ( tet ) -off inducible HBV replication and was provided by Dr . Christoph Seeger at Fox Chase Cancer Center [28] . HepDES19 is an HepG2 derived cell line supporting tet-off inducible replication of HBV with deficiency of envelope protein expression and was established in our laboratory [26] . HepAD38 and HepDES19 cells were maintained in DMEM/F12 media supplemented with 10% FBS , 100 U/ml penicillin , 100 μg/ml streptomycin , 1 μg/ml tet and 400 μg/ml G-418 . Tet was removed from HepAD38 or HepDES19 culture media when initiation of HBV replication is needed . All cells were maintained in a 5% CO2 incubator at 37°C . All cell culture experiments were performed in 50 μg/ml rat tail collagen ( Corning ) coated plates . Anti-Pol α1 antibody ( sc-373884 ) , anti-Pol δ1 antibody ( sc-17776 ) and anti-Pol α2 antibody ( sc- 398255 ) used in Western blot assays were purchased from Santa Cruz Biotechnology and used with 1:200 dilution . Anti-β-actin antibody ( 3700 ) was purchased from Cell Signaling Technology and used with 1:2000 dilution . Anti-Pol α1 antibody ( ab177994 ) , anti-Pol δ1 antibody ( ab225907 ) and anti-Pol ε antibody ( ab241943 ) used in chromatin immunoprecipitation assays were purchased from Abcam . Anti-Pol κ antibody was purchased from Bethyl Laboratories ( A301-977A ) . Anti-histone H3 ( 4620 ) and anti-histone H2A ( 12349 ) antibodies were purchased from Cell Signaling Technology . Anti-rabbit IgG was purchased from Sigma ( 31887 ) . All the antibodies used in chromatin immunoprecipitation are IP compatible . Foscarnet ( P6801 ) , aphidicolin ( A0781 ) and CD437 ( C5865 ) were purchased from Millipore-Sigma . Cycloheximide ( 2112 ) was purchased from Cell Signaling Technology . Myrcludex B is a gift of Dr . Stephan Urban [71] . Entecavir ( ETV ) was provided by Dr . Willan S . Mason at Fox Chase Cancer Center . pLX-sgRNA was a gift from Eric Lander & David Sabatini ( Addgene 50662 ) . pcDNA3 . 1/POLD1-FLAG plasmid was purchased from Genscript ( OHu14862 ) . HepAD38 cells were seeded into 6-well plates at a density of 6 × 105 cells per well and cultured in the absence of tet to initiate HBV replication . Two days later , 2 mM PFA was added into the culture media to arrest and synchronize HBV replication . Culture media were refreshed every other day . On day 6 post seeding , 1 μg/ml tet was added into culture medium to stop pgRNA transcription from HBV transgene and PFA was removed from culture medium to resume HBV DNA synthesis and cccDNA formation . Effects of compounds on cccDNA synthesis can be evaluated by treating the cells starting at PFA removal for 24 h . To test the effect of compounds on cccDNA stability , the cells were left untreated after PFA removal for 48 h to allow the establishment of cccDNA pool , followed by compound treatment at desired concentrations for 24 h in the presence of 1 μM Entecavir . Hirt DNA was extracted and amounts of cccDNA were determined by Southern blot hybridization as described below . HepAD38 cells were seeded into 6-well plates at a density of 6 × 105 cells per well and cultured in the absence of tet . Two days later , 2 mM PFA was added into the culture media . On day 4 post seeding , the cells were re-seeded and transfected with 10 pmol siRNA oligos and 1 μl RNAiMAX ( life technologies ) following the manufacturer’s protocol . Two days later , 1 μg/ml tet was added into culture medium to stop pgRNA transcription from HBV transgene and PFA was removed from culture medium to resume HBV DNA synthesis and cccDNA formation . Cells were harvested 24 h later . Total RNA was extracted using TRIzol reagent ( Invitrogen ) . Gene silencing efficiencies were validated by qRT-PCR ( comparative Ct method ( ΔΔCt ) using β-actin as an internal control ) or Western blot assays . The siRNA oligo sequences for screening are listed in S1 Table . The qRT-PCR primers are listed in S2 Table . The Pol α1 siRNA ( SR303612 ) and Pol α2 siRNA ( SR308429 ) used in validation experiments ( Fig 4A and S6 Fig ) were purchased from Origene . HBV virions were harvested from culture media of HepAD38 cells and concentrated by 8% PEG-8000 as described previously [70] . For infection , C3AhNTCP cells were cultured in DMEM supplemented with 3% FBS , and 2% DMSO for 24 h . The cells were then infected with HBV at a MOI of 500 genome equivalents in DMEM containing 3% FBS , 2% DMSO and 4% PEG-8000 ( Sigma P1458 ) . The inoculums were removed at 12 h post infection ( hpi ) and the cell monolayers were washed with PBS for 5 times before refreshing with DMEM containing 3% FBS , 2% DMSO and 4% PEG-8000 . The infected cultures were harvested at 12 or 48 hpi . The POLD1 sgRNA CRISPR-Cas9 All-in-One Lentivector was purchased from Abm Biology ( target sequence: CGAGGATCTATGGCTGATGG ) . Lenti-X Packaging Single Shots ( VSV-G ) ( Clontech ) were used to package POLD1 sgRNA CRISPR-Cas9 virus following manufacturer’s protocol . One milliliter of POLD1 sgRNA CRISPR-Cas9 virus preparation mixed with 1 ml DMEM/F12 complete media containing 1 μg/ml tet were applied to HepAD38 cells . After selection with 2 μg/ml puromycin for 2 weeks , the survival cell clones were expanded . POLD1 knockout was verified by Western blot assay and Sanger sequencing of genomic DNA in a single clone and designated as HepAD38-POLD1-/- . This gene editing protocol was modified from its original designer [33] . At first , Cas9-expressing lentivector ( Dharmacon ) was packaged into lentivirus by using Lenti-X Packaging Single Shots ( VSV-G ) ( Clontech ) following the manufacturer’s protocol . HepAD38 cells were transduced with the Cas9-expressing lentivirus and selected by 10 μM Blasticidin for 2 weeks to acquire HepAD38-Cas9 cells . Secondly , POLA1 sgRNA sequence 5’-GTTAGTGATCTGCAATGCTAA-3’ was cloned into pLX-sgRNA vector ( Addgene 50662 ) , resulting in pLX-sgPOLΑ1 that expresses guide RNA targeting POLA1 L764 coding region . To knock-in POLΑ1L764S , 1 μg of pLX-sgPOLΑ1 plasmid were transfected into 1 × 106 HepAD38-Cas9 cells seeded in a 6-well plate , in combination with 50 pmol synthesized single-stranded DNA oligo 5’-ACCCCAAGCAAACACTGAATCCAACAGGAAATGCTTTTTCCCCCTTTCTAAGTTAAATTTACCATAATGTTCCCAGCGATGTTAGTGATCTGCAATGCTGATGGAAGAACATTTAGCTCACACATGATCTGCAAAATGAACTTGGCATCTTTCCAGGTGTGTTCCAACAGGTATAACAGTTGAGAAGATTCACTGTACAG-3’ serving as a repair template , by using lipofectamine 2000 according to the manufacturer’s protocol . Two days after transfection , cells were exposed to 10 μM CD437 for 14 days and the surviving single colonies were expanded into cell lines . To validate POLΑ1L764S knock-in , genomic DNA from the isolated cell lines was extracted and DNA flanking L764 coding region was amplified by PCR with 5’- AGCATTGGGATCAGTGGTATG-3’ and 5’-AACACGCTGCACCTGGCATTC-3’ primer pair , and L764S mutation were confirmed by Sanger sequence method . HBV cccDNA was extracted by a modified Hirt DNA extraction protocol [37] . Briefly , cells from one well of a 6-well plate were lysed by 800 μl Hirt DNA lysis buffer ( 10 mM Tris-HCl , pH 8 . 0; 0 . 625% SDS; 10 mM EDTA ) for 30 min at room temperature , followed by adding 200 μl of 5 M NaCl to thoroughly mix and incubate overnight at 4°C . On the next day , supernatants were collected after centrifugation at 12000 × g for 30 min at 4°C , phase extracted by phenol for twice and phenol-chloroform ( 1:1 ) for once . DNA in the aqueous phase was precipitated by mixing with 0 . 7 volume of isopropanol at -20°C overnight . DNA was pelleted by centrifugation at 12 , 000 × g , washed by 70% ethanol and dissolved in 20 μl nuclease-free water . If indicated , Hirt DNA samples were denatured at 88ºC for 5 minutes and chilled on ice . Such a procedure allows the complete denaturation of DP-rcDNA into single-stranded DNA , whereas cccDNA remains as a double-stranded circular DNA . The heat denatured Hirt DNA samples were further digested with EcoRI to linearize cccDNA into unit-length double-stranded linear DNA . If needed , Hirt DNA was digested by Exo I & III to reveal minus strand covalently closed rcDNA . Intracellular HBV core DNA was extracted by using 400 μl of core DNA lysis buffer ( 10 mM Tris-HCl , pH 8 . 0; 1 mM EDTA; 1% Nonidet P-40 ) to lyse cells from one well of a 12-well plate for 10 min at room temperature . Cytoplasmic fraction was acquired after spinning at 12 , 000 × g to remove cell debris , and further subjected to 200 μg/ml proteinase K ( Ambion ) digestion in proteinase K digestion buffer ( 10 mM Tris-HCl , pH 8 . 0; 100 mM NaCl; 1 mM EDTA; 0 . 5% SDS ) for 1 h at 45°C . Equal volume of phenol-chloroform was used to perform phase extraction . DNA in the aqueous phase was then extracted following the same procedure described above for Hirt DNA . For Southern blot analysis , the extracted DNA samples were resolved in 1 . 2% agarose gel electrophoresis and transferred onto an Amersham Hybond-N+ membrane ( GE Healthcare ) . After UV crosslink , the membrane was probed with α-32P-UTP labeled plus-strand specific full-length riboprobe . α-32P-UTP labeled minus-strand specific full-length riboprobe was used if indicated ( Fig 7A and 7B ) . Radioactive signals were imaged by a Typhoon scanner . Approximately 2 × 107 cells in a 10 cm Petri dish were crosslinked by 1% formaldehyde for 10 min at room temperature , followed by quenching with 0 . 125 M glycine for 5 min . Cells were then lysed on ice for 10 min in 1 mL ChIP lysis buffer ( 50 mM Tris-HCl , pH 8 . 0; 1% SDS; 10 mM EDTA ) containing 1 × protease inhibitor cocktail ( Roche ) , scraped and collected into a 1 . 5 mL tube followed by ultrasound sonication to produce average fragment size 500–1000 bp of DNA . For each immunoprecipitation reaction , 100 μl of the supernatant ( 25 μg chromatin DNA ) were used to incubate with 1 μg indicated antibody in ChIP dilution buffer ( 10 mM Tris-HCl , pH 8 . 0; 1% Triton X-100; 0 . 1% SDS; 150 mM NaCl; 2 mM EDTA ) containing 1 × protease inhibitor cocktail ( Roche ) overnight at 4°C . Next day , 25 μl of protein G Dynabeads ( Invitrogen ) were added to each reaction and incubated for another 6 h at 4°C . Beads were then washed twice by ChIP low salt buffer ( 20 mM Tris-HCl , pH 8 . 0; 1% Triton X-100; 0 . 1% SDS; 150 mM NaCl; 2 mM EDTA ) , ChIP high salt buffer ( 20 mM Tris-HCl , pH 8 . 0; 1% Triton X-100; 0 . 1% SDS; 500 mM NaCl; 2 mM EDTA ) , ChIP LiCl buffer ( 10 mM Tris-HCl , pH 8 . 0; 1% Nonidet P-40; 250 mM LiCl; 1 mM EDTA ) and TE buffer ( 10 mM Tris-HCl , pH8 . 0; 1 mM EDTA ) ; and eluted by 200 μl ChIP elution buffer ( TE buffer containing 1% SDS; 100 mM NaCl; 5 mM dithiothreitol ) . ChIP elutes were incubated at 65°C overnight to reverse crosslink Protein-DNA complex . After digestion with 1 μl of 1 μg/ml RNase A ( Roche ) at 37°C for 1 h followed by 2 μl of 20 mg/ml proteinase K at 37°C for another 2 h , DNA was purified by Qiagen DNA purification kit and stored at -20°C . DNA quantity was measured by real time PCR using specific primers listed in S2 Table . HepAD38 cells were cultured in tet-free media for 6 days with 2 mM PFA added from day 2 to day 6 to arrest HBV DNA replication . After harvesting , one 10 cm dish of cells were lysed with 3 ml core DNA lysis buffer ( 10 mM Tris-HCl , pH 8 . 0; 1 mM EDTA; 1% Nonidet P-40 ) for 10 min at room temperature , followed with 4 h 45 , 000 × rpm ultracentrifugation in 30% sucrose at 4°C to pellet intracellular capsids . After resuspending in 300 μl of TNE buffer ( 0 . 15 M NaCl; 0 . 01 M Tris-HCl , pH 7 . 4; 0 . 1 mM EDTA ) , each 50 μl of the aliquots were subjected to incubation with 50 μl 2 × EPR buffer ( 0 . 15 M NaCl; 0 . 1 M Tris-HCl , pH 8 . 0; 20 mM MgCl2; 2 mM dithiothreitol; 0 . 2% ( vol/vol ) Nonidet P-40 ) with indicated compound treatment for 16 h at 37°C . The next day , the reaction mix was subjected to core DNA extraction and the extracted DNA samples were resolved by agarose gel electrophoresis and HBV DNA was detected by Southern blot hybridization . HepAD38 cells were cultured in 6-well plates at sub-confluent ( 50% ) or confluent ( 100% ) conditions and then treated with the indicated compounds ( DMSO , 1 μM APH , 1 μM CD437 ) . After compound treatment for 24 h , cells were fully trypsinized into individual single cells and fixed with 66% ethanol overnight at 4°C . Next day , cells were stained with 1 × Propidium iodide staining buffer ( Abcam 139418 ) containing 10 μg/ml Propidium Iodide solution and 500 U/ml RNaseA at 37ºC in the dark for 30 minutes . Approximately 1 , 000 cells/sample were analyzed using flow a BD FACS Canto with excitation laser at 488nm and emission detected using detector D with 575/25 bandpass filter . The flow histograms were generated using FlowJo software . | CCC DNA is the most refractory HBV replication intermediate under long-term antiviral therapies and is responsible for the viral rebound after treatment cessation . Therefore , understanding the biosynthesis and maintenance of cccDNA minichromosome is crucial for the development of novel antiviral therapeutics to cure chronic HBV infection . Although it has been clearly demonstrated that cccDNA biosynthesis relies on host cellular DNA repair machinery , the molecular pathways that convert rcDNA into cccDNA remain to be identified . Here we report that DNA polymerase alpha ( Pol α ) as well as Pol δ and ɛ are required for converting rcDNA into cccDNA through intracellular cccDNA amplification . This finding adds novel molecular insights on cccDNA biosynthesis . Further understanding the mechanism of cccDNA synthesis should reveal molecular targets for developing therapeutic agents to eradicate cccDNA and cure chronic hepatitis B . | [
"Abstract",
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"analysis"... | 2019 | DNA Polymerase alpha is essential for intracellular amplification of hepatitis B virus covalently closed circular DNA |
Eimeria spp . are a highly successful group of intracellular protozoan parasites that develop within intestinal epithelial cells of poultry , causing coccidiosis . As a result of resistance against anticoccidial drugs and the expense of manufacturing live vaccines , it is necessary to understand the relationship between Eimeria and its host more deeply , with a view to developing recombinant vaccines . Eimeria possesses a family of microneme lectins ( MICs ) that contain microneme adhesive repeat regions ( MARR ) . We show that the major MARR protein from Eimeria tenella , EtMIC3 , is deployed at the parasite-host interface during the early stages of invasion . EtMIC3 consists of seven tandem MAR1-type domains , which possess a high specificity for sialylated glycans as shown by cell-based assays and carbohydrate microarray analyses . The restricted tissue staining pattern observed for EtMIC3 in the chicken caecal epithelium indicates that EtMIC3 contributes to guiding the parasite to the site of invasion in the chicken gut . The microarray analyses also reveal a lack of recognition of glycan sequences terminating in the N-glycolyl form of sialic acid by EtMIC3 . Thus the parasite is well adapted to the avian host which lacks N-glycolyl neuraminic acid . We provide new structural insight into the MAR1 family of domains and reveal the atomic resolution basis for the sialic acid-based carbohydrate recognition . Finally , a preliminary chicken immunization trial provides evidence that recombinant EtMIC3 protein and EtMIC3 DNA are effective vaccine candidates .
The phylum Apicomplexa contains some of the most widespread protozoan parasites of humans and animals . Key members include Plasmodium spp . , Eimeria spp . , Neospora caninum and Toxoplasma gondii . Eimeria spp . are a highly successful group of host-specific , intracellular protozoan parasites that develop within intestinal epithelial cells , causing Coccidiosis , which is economically one of the most important diseases in modern poultry farming , and causes billion dollar economic losses worldwide [1] . The importance of the poultry industry is highlighted by the effort to develop anticoccidial drugs , however many of these have been thwarted by drug resistance . The incorporation of vaccination with avirulence strains of Eimeria has vastly improved the control of infections . The development of recombinant vaccines is hampered by a relatively poor molecular understanding of the Eimeria-host interface . Infection by apicomplexans is established in the host by rapid and forced invasion of host cells using a multistep process [2] . It begins with an initial phase of non-oriented cell attachment then a search across cellular surfaces for a particular niche and finally deployment of the cell entry machinery . Microneme proteins secreted in the early stages of this process participate in attachment to the host cell and subsequent formation of the connection with the parasite actinomyosin system , thereby providing the platform from which to drive invasion [3] . A family of microneme lectins ( MICs ) has been described that recognize sialylated glycans via microneme adhesive repeat regions ( MARR ) [4] . The first MARR protein to be characterized was MIC1 from Toxoplasma gondii ( TgMIC1 ) , which possesses a pair of N-terminal MARR that form two distinct subfamilies based on sequence , MAR1 and MAR2 . TgMIC1 recognizes sialic acid ( Sia ) -terminating glycan chains: a wide variety of sialyl linkages including α2–3 , α2–6 and α2–8 that are abundantly present on host cell surfaces . This broad specificity likely contributes to T . gondii's ability to establish an infection in all warm-blooded animals [4] , [5] . T . gondii also possesses additional MARR proteins that further extend the repertoire of sialylated cell-surface glycoconjugates recognized by this parasite [6] . High resolution structures have highlighted a critical TxH motif in the MAR2 domain that coordinates the sialyl moiety [4] , [5] . Intriguingly , MARR are also present in proteins of enteric coccidian parasites with very specific host and tissue tropisms , such as Eimeria spp . that exhibit strong site-specificity of development in the chicken intestine . Eimeria tenella develops within cells of the caecum and caecal tonsils located at the ileocecal junction , whereas Eimeria acervulina infects cells of the duodenum and Eimeria maxima infects cells of the jejunum [7] . E . tenella possesses a MARR-containing microneme protein , EtMIC3 , which is composed of seven tandem MARR that belong exclusively to the MAR1 family [3] , [8] , [9] ( Figure S1 ) . In this paper we provide a detailed structural , biochemical and cellular characterization of EtMIC3 . We demonstrate that EtMIC3 is composed of tandem MAR1 domains that possess a high specificity for sialylated glycans that terminate in N-acetylneuraminic acid ( NeuAc ) , but not in N-glycolylneuraminic acid ( NeuGc ) . The ability of EtMIC3 to bind to α2–3 sialyl sequences and their abundance in the chicken caecal epithelium , are likely to contribute to directing the parasite to this specific location in the chicken gut . Furthermore , we demonstrate that recombinant EtMIC3 protein or DNA act as an effective vaccine .
To confirm the intraparasite localization for EtMIC3 prior to secretion , immunogold labeling of E . tenella sporozoites with anti-EtMIC3 antibodies was performed and visualized using transmission electron microscopy ( TEM ) . As shown in Figure 1a , gold particles decorate exclusively the microneme compartments . The polar location of EtMIC3 was confirmed by immunofluorescence microscopy ( IFA; Figure 1b ) showing localization in merozoites developing within schizonts in the chicken caecum . To follow the localization of EtMIC3 during invasion E . tenella sporozoites were incubated with monolayers of Madin-Darby bovine kidney ( MDBK ) cells , which were then fixed , permeabilized and examined by immunofluorescence assay ( IFA ) and differential interference contrast ( DIC ) microscopy ( Figure 1c ) . After attachment to the host cell , the sporozoite caused invagination of the host cell membrane and became committed to invasion with an extruded conoid . EtMIC3 was present at the apical surface of the sporozoite throughout these early invasion stages ( Figure 1c ) and during invasion was detected at the interface between the host and parasite cell membranes where it was present on a bead like structure that forms a tight ring around the apical perimeter of the sporozoite ( Figure 2 ) . To examine more precisely the point at which EtMIC3 functions in invasion , the localization of EtMIC3 was compared to that of two other important microneme proteins EtAMA1 , an integral component of the moving junction together with rhoptry neck ( RON ) proteins [10] and EtMIC5 [11] , [12] , [13] , a lactose-binding , secreted microneme protein . In fixed and permeabilized parasites , EtMIC3 labeled a necklace structure comprising 14 separate foci present at the junction between the invading parasite and the host cell . This was proximal to a similar staining pattern for EtAMA1 , but not aligned exactly ( Figure 2a ) . In contrast , visualization of fixed , non-permeabilized sporozoites revealed that during invasion EtMIC3 is detected around the circumference of the parasite at the host cell-parasite junction and deposited on the host cell surface , whereas EtAMA1 is not labeled ( Figure 2b ) . This suggests that whilst EtAMA1 is buried within the moving junction and , in the absence of permeabilization , not accessible to antibody , EtMIC3 is more peripherally associated with the junction and remains surface exposed and in contact with the host cell . Dual immunofluorescence staining of EtMIC3 and EtMIC5 was also performed on fixed and permeabilized sporozoites and in parasites that were apically attached to host cells EtMIC3 serum gave a strong signal at the apical tip of the sporozoite , whilst the majority of EtMIC5 labeling was detected just posterior to this region ( Figure 2c ) , indicating that it was not yet secreted . Sporozoite lysates were incubated with monolayers of MDBK cells and proteins that bound to the cells identified by Western blotting . Whilst EtMIC1 , EtMIC2 , EtMIC3 and EtMIC4 proteins were readily detected in the unbound fraction of the sporozoite lysate , only EtMIC3 was observed to any extent in the cell bound fraction ( Figure 3a ) . Subsequent ELISA type cell-based binding assays performed with sporozoite lysate showed a dose dependent increase in the bound fraction of EtMIC3 ( Figure 3b ) . EtMIC3 possesses a tandem MARR , and the MARRs in the MIC proteins of T . gondii , and N . caninum have been shown to recognize a variety of sialylated glycans [4] , [5] , [6] . To establish whether host cell sialyl glycans are a target for EtMIC3 , cell binding assays were performed in the presence of exo-α-sialidase ( neuraminidase ) , which strips cell surface sialic acid residues , or the presence of fetuin , a sialylated glycoprotein derived from bovine fetal serum , which would compete with sialyl oligosaccharides on the cell surface for MIC3 binding . Treatment with neuraminidase at 0 . 25 units per ml or fetuin at 100 µg per ml effectively inhibited binding of EtMIC3 to host cells ( Figure 3c & 3d ) . In contrast , treatment with asialofetuin , a glycoprotein that lacks sialic acid and instead has terminal galactose residues , did not compete for EtMIC3 binding . Interestingly , treatment with free sialic acid ( NeuAc ) did not inhibit EtMIC3 binding , which is in sharp contrast with our observation with TgMIC1 whose binding is inhibited by free sialic acid [4] , [6] . Fetuin and multi-sialylated gangliosides containing at least one terminal α2–3 sialyl linkage were extremely potent inhibitors of EtMIC3 binding . The GD1a disialo-ganglioside which possesses both terminal and side chain α2–3 sialic acid moieties is a potent inhibitor of cell binding , whereas the related GD1b disialo-ganglioside , in which only the α2–8 di-sialyl side chain is present , was not ( Figure S2 ) . This is in accord with the results of microarray analyses ( see below ) . Sialyllactose with α2–3-linked sialic acid ( Siaα2–3Galβ1–4Glc ) was more effective in inhibiting the binding of EtMIC3 from a sporozoite lysate to MDBK cells than α2–6-linked sialyllactose ( Figure 4a ) . Binding assays were also performed when MDBK cells were preincubated with plant lectins that have preferences for binding either α2–6 or α2–3 sialyl linkages , namely Sambucus Nigra agglutinin ( SNA ) [14] and Maackia amurensis agglutinin ( MAA ) [15] , respectively . MAA ( consisting of both Maackia amurensis hemagglutinin and leukoagglutinin ) inhibited the binding of EtMIC3 to MDBK cells at lower concentrations compared with SNA ( Figure 4b ) . This indicates that α2–3-linked sialyl glycans present on the MDBK cell surface are the dominate ligands in the EtMIC3 binding . To test the cell specificity of EtMIC3 binding in host tissues , we performed binding assays using histological sections taken from throughout the chicken intestine ( Figure 4c ) . Incubation of these sections with biotinylated SNA and Maackia amurensis hemagglutinin ( MAAII ) lectins showed an abundance of MAAII staining ( and by inference , mucin-type sialyl glycan sequences [15] ) in sections taken from caecum . The tissue staining pattern observed for EtMIC3 was similar to that of MAAII: the binding was predominantly to the caecal epithelium . To assess the carbohydrate binding specificity of EtMIC3 , we performed cell-independent binding analyses using carbohydrate microarrays composed of 115 lipid-linked oligosaccharide probes . Among these are 97 sialylated probes with differing sialic acid linkages , backbone chain lengths and sequences; 18 nonsialylated ( neutral and sulfated ) probes were included as negative controls ( Figure 5 , and Table S1 ) . Microarray analyses were performed with recombinant proteins consisting of single MAR domain ( EtMIC3-MAR1b ) , or tandem MAR domains ( 1a-1b-1d-1e , Figure S1 ) collectively referred to as EtMIC3-MAR5 . For comparison we analyzed in parallel the recombinant MARR of T . gondii MIC1 ( TgMIC1-MARR ) . Similar to TgMIC1-MARR , the binding of EtMIC3-MAR1b and EtMIC3-MAR5 was to sialylated probes in the arrays , and no binding signal was observed with probes that lack sialic acids ( Figure 5 ) . Compared with the five-domain construct , EtMIC3-MAR5 , the single domain EtMIC3-MAR1b had a more selective binding profile ( Figure 5a ) . Notably , it gave little or no binding to sialyl di- or trisaccharide sequences , such as probes 19 , 20 , 27–34 , 57–61 , 70 and 76 ( Table S1 ) , but bound well to sialyl tetrasaccharides and longer sequences . Among the best ligands for EtMIC3-MAR1b are sialylated N-glycan probes ( probes 56 , 87 and 93 ) , a sialyl Lewisx ( SiaLex ) probe which has a sulfate group at the 6-position of the N-acetylglucosamine ( GlcNAc ) residue ( probe 49 ) , and ganglioside-related probes that have terminal α2–3 sialic acid and side chain sialic acid , e . g . GD1a and GT1b ( probes 66 and 109 , Table 1 ) . The five-domain construct , EtMIC3-MAR5 bound to a broader spectrum of sialyl probes with enhanced binding intensities overall compared to MAR1b ( Figure 5a and b ) . Little or no binding was observed to α2–8-linked sialyl probes with the two EtMIC3 proteins . The intensities of binding signals elicited with α2–3 and α2–6-linked sialyl sequences sharing similar backbones and lipid moieties were comparable ( Table 1 ) . This pattern of binding is different from that observed in the inhibition studies where free oligosaccharides were used as inhibitors of the binding of EtMIC3 sporozoite lysate to MDBK cells , in which the α2–3-linked sialyllactose was a more potent inhibitor ( Figure 4a ) . A striking finding is that neither EtMIC3-MAR1b nor EtMIC3-MAR5 bound to sialyl sequences that terminate in the N-glycolyl form of sialic acids ( NeuGc ) , e . g . probes 39 , 60 and 88 in Table 1; this is in sharp contrast to TgMIC1-MARR which gave comparable or even stronger binding to the NeuGc probes than to their NeuAc analogs ( Table 1 ) . To select a MAR domain for structural studies , each of the five unique MAR1 domains were analyzed for cell binding using a cell-based ELISA assay . All of the five MARRs , but not a thioredoxin control protein , bound to MDBK cells . The second , third and fourth MARR ( MAR1b , 1c , 1d ) exhibited the most intense binding signals ( Figure S3 ) . For high resolution structural analysis , we selected the second MAR domain , EtMIC3-MAR1b , which as shown above gave robust binding signals to sialyl glycan sequences in microarray analyses ( Figure 5a ) . The solution structure of EtMIC3-MAR1b determined by NMR spectroscopy comprises the distorted β-barrel arrangement and flanking helices of the classic MAR domain ( Table 2 ) . Three conserved disulfide bonds , C1–C4 , C5–C7 and C6–C8 ( namely C163–C201 , C216–C226 and C220–C256 , Figures 6a and S1 ) stabilize the core structure . A comparison of the structure with that of MAR1 and MAR2 of TgMIC1 reveals that EtMIC3-MAR1b contains a prominent extension to the first helix and subsequent loop ( MAR1 insertion ) , which is stabilized and pinned together by an extra disulfide bond exclusive to the MAR1 subfamily ( C2–C3 namely C171–C179; Figures 6a and S1 ) . EtMIC3-MAR1b superimposes with an RMSD of 2 . 2 Å over 104 equivalent backbone Cα atoms with the MAR1 domain from TgMIC1 ( PDB code 2JH1; Figure S4 ) . The carbohydrate binding properties of the MAR2 subfamily have been well characterized structurally [4] , [5] , [6]; however no equivalent information is available for the MAR1 subfamily as occupancy in the MAR1 site of TgMIC1 was not established in soaking and co-crystallization experiments . Our NMR structure of EtMIC3-MAR1b provides an opportunity to study recognition of the MAR1 family in detail . To localize the carbohydrate binding region further , we performed NMR titration experiments using 15N , 13C-labeled EtMIC3-MAR1b in the presence of α2–3- and α2–6-linked sialyllactoses . Significant amide chemical shift changes were observed for resonances of several residues proximal to the expected carbohydrate binding site based on TgMIC1 ( Figure S5 ) . To provide an atomic resolution basis for recognition we embarked on the structural characterization for the carbohydrate-bound forms . Isotope 13C-filtered/edited NOESY spectra were recorded on complexes between 13C/15N-EtMIC3-MAR1b and sialyl N-acetyllactosamines ( Siaα2–6Galβ1–4GlcNAc or Siaα2–3Galβ1–4GlcNAc ) to identify intermolecular NOEs ( Figure S4 ) . A total of nine NOEs were assigned either to the ring protons or to unambiguously well dispersed side chains ( Table S2 ) . The α2–3 linked and α2–6 linked carbohydrate complexes exhibit similar patterns of intermolecular NOEs . Structures of the carbohydrate complexes were subsequently calculated invoking both intermolecular NOEs and chemical shift-derived distance restraints using the HADDOCK approach [16] . The lowest energy ensembles of water-refined structures superpose well over the intermolecular interface . As expected from NOEs the mode of sialic acid recognition is identical for the Siaα2–3Galβ1–4GlcNAc and Siaα2–6Galβ1–4GlcNAc , the major difference being the relative position of the galactose unit ( Figure S4 ) . Although the mode of recognition for the sialyl moiety is highly similar to that observed for MAR2 domain from TgMIC1 , the ‘MAR1 insertion’ makes several new contacts via L175 and Y178 ( Figure 6b ) . MDBK is a cell line that supports invasion and intracellular development of E . tenella sporozoites and we used this to investigate whether sialylated structures on the cell surface contribute to parasite invasion . Using uracil uptake assays , in which parasite growth is measured over a period of 48 hours in culture , we found no significant reductions in radiolabel uptake following any of the treatments that had shown effects on EtMIC3 binding to MDBK cells ( neuraminidase , fetuin , sialic acid , α2–3 or α2–6 sialyllactose , MAA or SNA lectins , gangliosides GD1a or GT1b ) . This indicates that binding to sialyl groups is not essential for overall parasite invasion of cultured cells . In these assays parasites were left in contact with the cells over the whole 48 hour period and as in vitro conditions differ so markedly from the in vivo situation , within the gut of the chicken , it is conceivable that specificity is swamped by other factors , especially over extended incubation periods . Given the immediate secretion of EtMIC3 and its likely deployment at very early during invasion , we next investigated the effect of these treatments on short-term cultures in which sporozoites were allowed to invade the MDBK monolayers for only 15 minutes before fixation and enumeration of intracellular parasites . Under these conditions we found dose-dependent inhibition of sporozoite invasion following treatments with GD1a and GT1b gangliosides and with α2–3 sialyllactose ( Figure 7 ) . In contrast treatment with fetuin , sialic acid or α2–6 sialyllactose did not cause significant inhibition of sporozoite invasion . We carried out exploratory immunization and challenge experiments in chicken to determine whether immunization with EtMIC3 could induce protection against parasite infection . Five independent experiments were carried out using purified EtMIC3-MAR recombinant protein ( EtMIC3-MAR1c ) or EtMIC3-MAR DNAs ( of MAR1c and MAR5 ) as immunogens . In each case , following challenge with E . tenella oocysts , there was statistically significant reduction in oocyst shedding in vaccinated groups of birds compared to control groups ( data from two independent experiments are shown in Figure 8 ) .
Host cell invasion by apicomplexan parasites is a conserved and complex , multi-step process . While details are emerging of the key phases of invasion , the early stages remain the least well understood . It appears that parasites first attach transiently to the host cell surface via GPI-anchored surface proteins known in T . gondii as SRSs ( Surface Antigen Glycoprotein Related Sequences ) [17] , [18] and which have been shown to bind sulfated glycosaminoglycans such as heparin [19] , [20] . The loose attachment mediated by the SRSs is thought to enable efficient sampling of cell surfaces , which is followed by an irreversible interaction with the apical end of the parasite , allowing for proper engagement of the invasion machinery [2] . There are several adhesive microneme proteins that are neither assembled into the moving junction during invasion nor belong to the SRS family of surface proteins . The MARR-containing MIC proteins from coccidians are prominent examples of these and likely play a role in initiating the transition from transient , non-oriented binding to irreversible apical attachment . We have demonstrated that EtMIC3 , a MARR-containing protein from Eimeria tenella , is secreted at the early stages of invasion prior to the formation of the moving junction . It is localized at the interface of the host cell membrane and apical attachment of the parasite interface and remains proximal to the moving junction complex during invasion . EtMIC3 and EtAMA1 antibodies each label 14 focal points that decorate the circumference of the junction; the reason for this is unknown but it is unlikely to relate to sub-pellicular microtubules which number 24 in E . tenella ( D . Ferguson , P . Monaghan and F . Tomley , unpublished observations ) . During the attachment stage of parasite invasion of MDBK cells , EtMIC3 was rapidly deployed to the sporozoite apical surface whereas another secreted microneme protein , EtMIC5 , was not deployed . These observations raise the intriguing question as to whether the two molecules localize to the same or different populations of micronemes . Although heterogeneous populations of micronemes provides an attractive hypothesis for a staged deployment of microneme proteins during invasion , further work is required to provide further experimental evidence and elucidate the exact mechanism . Interestingly , invasion by Eimeria tenella is only sensitive to inhibition by soluble sialylated carbohydrates in the very early stages of contact between parasite and host cell ( Figure 7 ) . This observation is consistent with the view that EtMIC3 is secreted ahead of the moving junction to promote efficient cell-adhesion and assist in early stage invasion . This echoes the notion that parasites use multiple ligand–receptor interactions to ensure invasion during the various stages of the infection [21] . Compared to TgMIC1 , a more restricted set of sialyl oligosaccharides are bound by EtMIC3; notably EtMIC3 does not recognize the N-glycolyl form of sialic acids and also shows little binding to α2–8-linked sialyl oligosaccharides . All of the MARR for EtMIC3 belong to the MAR1 family and three of these , MAR1b , MAR1c and MAR1d , are highly active for cell binding ( Figure S3 ) . In addition to active site TxH motif found in MAR2 domains , the MAR1 family also possess an extended first helix and loop which can be seen from the structure of EtMIC3-MAR1b to also coordinate the carbohydrate ligand via the side chains of L175 and Y178 ( Figure 6b and S4 ) . The methyl group of the N-acetyl moiety NeuAc makes several intimate contacts with this insertion , explaining why EtMIC3 cannot recognize the NeuGc form as the additional hydroxyl group would not be accommodated without significant rearrangement . Furthermore , the central residue in TxH is normally a small side chain in MAR2 domains , but in EtMIC3-MAR1b this is replaced by the larger leucine ( i . e . L238 ) that contacts directly the glycerol side chain of sialic acid ( Figure 6b and S4 ) . The first and last MAR1 domains of EtMIC3 ( MAR1a and MAR1e; Figure S1 ) show significant differences in these positions and this is consistent with the weaker binding of these two domains to cells ( Figure S3 ) . Complex sialylated glycans are yet to be identified in coccidians [22] , [23] . Given their wide distribution in warm-blooded animals , it is appropriate that sialylated glycans of the host are the targets for the MARR proteins . We have shown that binding specificity goes beyond simple recognition of sialic acid and includes the sialyl linkage , the chain length and further modification of the backbone sequence . Although stronger inhibitory activity was observed with α2–3-linked sialyllactose compared with the α2–6 analog in the inhibition of cell binding experiments , the preference for α2–3 sialyl oligosaccharides was not apparent in the carbohydrate microarray analyses . This is of interest , as in contrast to MAR1b and MAR5 of EtMIC3 , the TgMIC1-MARR did show stronger binding to α2–3 than to α2–6 sialyl sequences in the microarrays ( Figure 5c , and Table 1 ) , in accord with our previous finding [4] , [5] . With EtMIC3 there are maybe several explanations for the discrepancy in the relative potencies of sialyl α2–3 vs to α2–6 in the inhibition and the microarray binding assays . First , it is possible that the multivalent binding in the microarray system ( both the oligosaccharide ligands and the EtMIC3 MAR domains are in oligomeric form ) may result in substantial amplification of the binding response thus rendering it difficult to observe differential binding affinities/avidities towards the sialyl ligands . An example is the rather selective binding profile observed with the single-domain construct EtMIC3-MAR1b that becomes blurred with the five-domain construct EtMIC3-MAR5 . It is also important to note that compared with the MAR2 domain present in TgMIC1 , the EtMIC3 MAR domains ( MAR1 family ) have an inherent increased affinity for sialyl oligosaccharides due to additional interactions with sialic acid mediated by the MAR1 insertion between α1 and β1 and the HLT motif ( Figures 6 and S1 ) ; this would make it more difficult to detect the difference in binding intensities for EtMIC3-MAR1b even when it was tested under the same conditions as TgMIC1-MARR . Second , the structure of the MAR2 domain of TgMIC1 revealed a water-mediated hydrogen bond network between protein ( E205 , E206 and E207 ) and Gal O6 position of the carbohydrate ligand , which contributed to the α2–3-linked sialyl oligosaccharide binding preference [4] , [5] . Interestingly , several of these positions are replaced with other amino acid residues in the MAR1 domains from EtMIC3 ( e . g . 241PSE in MAR1b , 382NPQ in MAR1c and 533NPQ in MAR1d ) ; this may lead to the absence of structured water network thus providing an explanation for the lack of significant binding preference for α2–3-linked sialyl oligosaccharides in our microarray analyses . Finally , the increased flexibility of the α2–6 over the α2–3 sialyl linkage would also contribute to an additional entropic penalty upon ordering in the complex , and this may at least in part account for the stronger inhibitory activity of α2–3 sialyllactose in the inhibition assays where free oligosaccharides were used in solution as inhibitors . E . tenella sporozoites invade primarily the caecal epithelium of chickens , in contrast to T . gondii zoites which have the ability to infect almost any nucleated cell . All the EtMIC3 MAR domains belong to the MAR1 family and they are likely to have similar binding specificities; whereas T . gondii possesses several proteins ( e . g . TgMIC1 and TgMIC13 ) with diverse MAR domains ( MAR1 and MAR2 family ) that are capable of more promiscuous glycan binding . It is interesting that our microarray analyses revealed a lack of recognition of NeuGc-terminating glycans by EtMIC3 , which are rare in the chicken host [24] . The opposite , namely a preference of the NeuGc form of the sialyl ligand GM1 , was revealed by microarray analysis of the oncogenic virus SV40 for which the primary host is the monkey that , unlike humans , can synthesize NeuGc [25] . The T . gondii MIC1 recognizes glycans with both NeuAc and NeuGc forms of sialic acids consistent with its very broad cell tropisms . These differing specificities are clearly major factors in the host tropisms of these microbes . The restricted tissue staining pattern observed for EtMIC3 , namely in the chicken caecal epithelium , but not in other parts of the chicken intestine , indicates that EtMIC3 play a key role in efficiently directing the parasite to the caecum . Apart from the specificities of EtMIC3-MAR1b toward different sialic acid forms and linkages , the carbohydrate microarray analyses have revealed modulation of binding strength in the presence of certain sulfate modifications of the sialyl oligosaccharide sequences . EtMIC3-MAR1b gave stronger binding to the 3'SiaLex sequence that has a sulfate at position 6 of the GlcNAc residue ( 6-SU SiaLex; probe 49 in Table 1 ) than to analogs lacking sulfate on GlcNAc ( probe 45 and 47 ) or having an additional sulfate group on the galactose ( Gal ) residue ( 6 , 6′-SU SiaLex; probe 51 ) . We have previously reported that sulfation pattern plays an important role in carbohydrate recognition by Neospora caninum MIC1 [6] . In that study , we observed strong binding of NcMIC1-MARR to two sulfated SiaLex probes both of which have a sulfate group on the Gal residue ( as in probes 47 and 51 ) . These properties of MIC proteins might have implications for tissue tropism . It is worth noting that the greater binding to 6-SU SiaLex sequence is a feature shared with highly pathogenic poultry influenza viruses including H5N1 viruses [26] , [27] . These viruses also target the chicken intestinal tract . Rotational treatment with anticoccidial drugs and commercial live vaccine is current best way to control infecting within chicken flocks . Due to the high expense of scaling-up the production of live parasite vaccine , there have been a number of recent efforts to develop subunit and recombinant coccidiosis vaccines using both DNA and protein based antigens [28] , [29] , [30] , [31] . However , few have been successful and much work needs to be done to identify appropriate antigens and the optimal mode of delivery . The role of EtMIC3 in targeting host sialyl glycans in the early stages of invasion and its prominent location at the host-parasite interface suggests that it may serve as an effective vaccine antigen . We have carried out five independent challenge experiments in groups of birds vaccinated with recombinant EtMIC3-MAR protein or EtMIC3-MAR DNA and found that EtMIC3 vaccination results in highly significant reductions in oocyst output after challenge infection ( Figure 8 ) . Whilst these are small-scale experiments , the consistency of the trials and level of efficacy ( around 50% reduction in oocyst shedding following vaccination ) are higher than seen in many studies with other antigens , indicating that EtMIC3 should be considered as a good candidate antigen for future recombinant vaccine development .
This study was carried out in strict accordance with the Animals ( Scientific Procedures ) Act 1986 , an Act of Parliament of the United Kingdom . All animal studies and protocols were approved by the Institute for Animal Health Ethical Review Committee and the United Kingdom Government Home Office under project license number PPL 80/2545 . The authors are committed to the principals of the 3Rs: reduction ( in numbers ) , refinement ( of procedures ) and replacement ( with laboratory procedures ) of experimental animals , commensurate with being able to do statistically and biologically significant experiments for animal health . Enriched environments have been introduced for our animals in line with guidelines from the National Centre for the 3Rs . Recombinant EtMIC3 fragments were expressed and purified using previously described strategies [32] , [33] . Constructs corresponding to EtMIC3-MAR1a ( residues 42 to 153 ) , EtMIC3-MAR1b ( residues 154 to 289 ) , EtMIC3-MAR1c ( residues 290 to 440 ) EtMIC3-MAR1d ( residues 743 to 874 ) , EtMIC3-MAR1e ( residues 875 to 988 ) and EtMIC3-MAR5 ( comprising sequences encompassing MAR1a , MAR1b , MAR1d and MAR1e residues 1-298 , 750-921 ) were each cloned into pET32b Xa/LIC plasmid ( Novagen ) and expressed as thioredoxin fusion proteins in Origami ( DE3 ) ( Novagen ) [34] . For binding assays and vaccination experiments recombinant proteins were used as thioredoxin-hexa-His fusions and unfused thioredoxin protein was prepared in parallel from ‘empty’ vector as a control . For structure calculation an optimized construct of EtMIC3-MAR1b was generated encompassing residues 153–274 . Protein expression was induced with 500 µM isopropyl β-D-thiogalactopyranoside overnight at 30°C . The fusion protein was purified by affinity chromatography using a nickel-nitrilotriacetic acid ( Ni-NTA ) resin ( Qiagen ) and separated from thioredoxin in a factor Xa cleavage reaction ( Novagen ) . Factor Xa was removed from the sample by binding it to an immobilised Xarrest agarose resin ( Novagen ) and residual protease was inhibited with 1 mM AEBSF ( Novagen ) . Thioredoxin was removed from the sample by passing the sample back across a Ni-NTA resin . The protein was concentrated to ∼1 mM and exchanged into phosphate buffer for NMR ( 20 mM sodium phosphate pH 6 . 5 , 50 mM NaCl for the structure calculation and 20 mM sodium phosphate pH 5 . 5 mM NaCl for binding studies ) . 15N , 13C-labelled samples were produced in minimal media , containing 0 . 07% 15NH4Cl and 0 . 2% 13C6-glucose . Recombinant TgMIC1-MARR was prepared as described [4] , [6] . Confluent monolayers of MDBK cells were blocked with 1% BSA in PBS for 2 h at 4°C , washed three times in PBS then incubated with sporozoite lysate or recombinant-expressed proteins ( 0 . 001 mg/ml to 2 mg/ml ) for 1 h at 4°C . Monolayers were washed four times with PBS to remove unbound proteins , then cells and bound proteins were solubilised in SDS sample buffer , separated by SDS PAGE , transferred to nitrocellulose and probed with rabbit sera raised to EtMIC1 , EtMIC2 , EtMIC3 and EtMIC4 . Dose dependent binding of EtMIC3 was determined by ELISA using gluteraldehyde fixed MDBK cells . For binding inhibition experiments , MDBK cells were treated as follows: neuraminidase ( from C . perfringens ) obtained from Sigma , used at 0 . 5 to 0 . 125 units/ml , 37°C , 1 h; lectins SNA ( from Sambucus nigra ) or MAA ( from Maackia amurensis ) obtained from Sigma , used at 10 , 50 or 100 µg/ml , 4°C for 30 min . Alternatively , sporozoite lysates or recombinant proteins were treated as follows: fetuin and asialofetuin ( from fetal calf serum ) obtained from Sigma , used at 1 to 1000 µg/ml , 4°C for 10 min; sialic acid ( NeuAc ) , α2–3 sialyllactose and α2–6 sialyllactose ( from bovine colostrum ) obtained from Sigma , used at 10–200 µg/ml , 4°C for 10 min; gangliosides GD1a , GD1b and GT1b ( from bovine brain ) , obtained from Sigma , ganglioside GD1a ( from bovine brain ) obtained from Alexis biochemicals ) , used at 100 µg/ml 4°C for 10 min . Microarrays were composed of lipid-linked oligosaccharide probes , namely neoglycolipids ( NGL ) and glycolipids , robotically printed on nitrocellulose-coated glass slides at 2 and 5 fmol per spot using a non-contact instrument [4] , [35] . The NGLs were prepared by either reductive amination [36] or oxime ligation [37] . Among these are 97 sialylated probes with differing sialic acid linkage , glycan backbone , chain length and sequence , and 18 nonsialylated ( neutral and sulfated ) probes were included as negative controls ( Figure 5 , and Table S1 ) . The microarray binding assays were performed at ambient temperature . His-tagged EtMIC3-MAR1b and TgMIC1-MARR were assayed essentially as described [4] , [6] ) . In brief , the arrayed slides were blocked for 1 h with 1% w/v bovine serum albumin ( Sigma ) in Pierce Casein Blocker solution ( casein/BSA ) . EtMIC3-MAR1b and TgMIC1-MARR were precomplexed with mouse monoclonal anti-polyhistidine and biotinylated goat anti-mouse IgG antibodies ( Sigma ) in a ratio of 1∶2 . 5∶2 . 5 ( by weight ) and overlaid onto the arrays at 40 µg/ml . For the analyses of EtMIC3-MAR5 , precomplexation was not required . The protein was tested at 40 µg/ml , and followed by overlay with anti-polyhistidine and biotinylated anti-mouse IgG antibodies ( 10 µg/ml , precomplexed in a ratio of 1∶1 ) . Binding was detected using Alexa Fluor 647-conjugated streptavidin ( Molecular Probes ) . Microarray data analysis and presentation were carried out using dedicated software [38] . The binding to oligosaccharide probes was dose-related , and results at 5 fmol per spot are shown . E . tenella sporozoites were allowed to settle at ambient temperature onto monolayers of MDBK cells grown on coverslips , then these were incubated at 41°C for 5 min . Cells were fixed in 4% paraformaldehyde , permeabilized with Triton X-100 and blocked with 1% BSA in PBS . Caecae were removed from infected chickens at 96 h post infection and fixed in paraformaldehyde . Sections were submitted to histology for automated dehydration , paraffin embedding , sectioning and staining . They were cut using a microtome , dewaxed , pressure cooked and treated with 1% BSA in PBS to block non-specific staining [39] Cell monolayers and gut sections were incubated with various sera generated against E . tenella proteins as previously described [40]; chicken anti-EtMIC3 serum ( 1∶300 ) , rabbit anti-EtMIC3 serum , ( 1∶300 ) , mouse anti-tubulin ( 1∶1000 ) , chicken anti-EtAMA1 , ( 1∶400 ) or rabbit anti-EtMIC5 serum ( 1; 200 ) . After washing , cells were incubated with appropriate secondary antibodies; goat anti-chicken-Alexa Fluor 488 ( green ) and goat anti–mouse Alexa Fluor 568 ( red ) and then briefly incubated with DAPI . Coverslips and sections were examined with a Zeiss Axioskop microscope or a Leica confocal microscope using Ar , Kr and 633 HeNe lasers . Samples ( pellets of sporozoites or pieces of infected tissue ) were fixed in 2% paraformaldehyde in 0 . 1 M phosphate buffer , dehydrated and embedded in LR White resin . Thin sections were blocked with 1% BSA in PBS , floated on drops of rabbit anti-MIC3 antibody , washed and exposed to goat anti-rabbit Ig conjugated to 10 nm gold . Finally grids were washed and stained with uranyl acetate prior to examination in the electron microscope . All NMR spectra on the structure determinations of EtMIC3-MAR1b ( residues 153–274 ) were recorded on 15N , 13C-labelled samples . Backbone and side-chain assignment were completed using standard double and triple-resonance assignment methodology [41] , [42] , [43] . The side-chain assignments were completed using HCCH-total correlation ( TOCSY ) spectroscopy and ( H ) CC ( CO ) NH TOCSY [43] . 3D 1H-15N/13C NOESY-HSQC ( mixing time 100 ms at 500 MHz and 800 MHz ) experiments provided the distance restraints used in the final structure calculation . The ARIA protocol [44] was used for completion of the NOE assignment and the interface to the CNS structure calculation program [45] . Dihedral angle restraints derived from TALOS+ were also implemented [46] . The frequency window tolerance for assigning NOEs was ±0 . 05 ppm and ±0 . 07 ppm for direct and indirect proton dimensions and ±0 . 5 ppm and ±0 . 5 ppm for nitrogen and carbon dimensions , respectively . The ARIA parameters , p , Tv , and Nv , were set to default values . A slow cooling step was used with 72000 steps of 0 . 003 ps dynamics [47] . The 10 lowest energy structures had no NOE violations greater than 0 . 5 Å and dihedral angle violations greater than 5° . The structural statistics are presented in Table 1 . For the HADDOCK-derived structures of the carbohydrate-bound complexes the following protocol was used . The final family of 10 structures for EtMIC3-MAR1b were used as starting structures . The family of starting structures for the carbohydrate ligand were generated by selecting random torsion angles about the glycosidic bond . Two thousand starting structures for the complex were generated by selecting random structures from the above families and carrying out rigid-body minimisation , from which 1000 were used for subsequent simulated annealing ( SA ) . During the SA and subsequent water-refinement stage , amino acid side chains within the putative carbohydrate binding site and whole carbohydrate ligand were allowed complete flexibility . The entire Raver1 peptide was also allowed complete flexibility during the calculation . 200 lowest-energy SA models were selected for a final water-refinement stage . NOE restraints were derived in standard fashion from heteronuclear-filtered NOE spectra ( 9 NOEs were identified in each complex and hydrogen bond restraints were included between the sialic acid carboxylate and threonine residue in the HLT motif ) . NOEs to sugar rings were implemented in an ambiguous manner . For NMR mapping experiments , 15N-labelled EtMIC3-MAR1b was prepared in 20 mM sodium phosphate buffer at pH 5 . 5 at approximately 1 mM in 0 . 5 ml . Either sialic acid ( NeuAc ) , Siaα2–3Galβ1–4Glc , Siaα2–6Galβ1–4Glc , Siaα2–3Galβ1–4GlcNAc or Siaα2–6Galβ1–4GlcNAc in the same buffer were introduced at several steps up to a 50 fold molar excess and 2D 1H-15N HSQC spectra were recorded at each stage under identical experimental conditions . The final saturated position is shown in Figure S5 . Samples of intestinal tissue including upper , mid , lower intestine and caeca , were removed immediately post-mortem from a 3 week old SPF Light Sussex chicken into 10% buffered formalin and subsequently embedded in paraffin . Sections ( 10 µm ) were cut onto glass slides , dewaxed and treated with 10 mM Na citrate ( pH 6 . 5 ) for 15 min in a microwave oven . Sections were blocked overnight in 5% BSA then binding of EtMIC3 or biotinylated plant lectins SNA or MAA-II ( Vector Lab ) was carried out using a Vectastain ABC-AP system . For EtMIC3 , sections were incubated first with normal mouse serum , then rinsed and incubated with EtMIC3-MAR5 recombinant protein ( 100 µg/ml ) for 30 min followed by washing , incubation with mouse anti-His serum for 30 min , washing and incubation with diluted biotinylated secondary antibody for 20 min . For SNA or MAAII , sections were incubated directly with biotinylated lectins ( ∼20 µg/ml; Vector Labs ) . All sections were processed for development with the VECTASTAIN ABC-AP reagent and substrate according to the manufacturer's instructions . In vitro infection of Madin Darby Bovine Kidney ( MDCK ) cells was carried out essentially as described previously [40] . Briefly for invasion assays , semi-confluent monolayers grown on coverslips in 24-well tissue culture plates were infected with 106 freshly purified sporozoites and the plates re-incubated at 41°C for 15 minutes , at which time they were fixed in methanol , stained with haematoxylin and eosin , mounted under polyvinyl resin and examined at 400×magnification . The total number of intracellular parasites ( within vacuoles ) for 10 random fields was counted on each coverslip and at least three coverslips were examined for each treatment . For uracil uptake assays that measure parasite replication as an indirect read-out of parasite invasion [48] , semi-confluent monolayers in 96-well plates were infected with 105 freshly purified sporozoites together with 1 µCi [5 , 6]-[3H]-uracil ( Perkin-Elmer NEN ) and incubated for 48 hr , after which cells were lysed , harvested onto glass fibre filter mats with a cell harvester ( Packard Filtermate ) and uracil uptake quantified as counts per minutes using a direct beta-counter ( MicroBeta , Perkin-Elmer-Wallac ) . Each treatment was replicated four times and control wells without parasites were set up for each experiment . Treatments used in this study were pre-incubation of sporozoites with fetuin , asialofetuin , sialic acid ( NeuAc ) , α2–3 sialyllactose , α2–6 sialyllactose , gangliosides GD1a or GT1b ( ranging from 10 µg/ml to 1 mg/ml ) for 10 minutes at room temperature , or pre-incubation of MDBK cells with SNA or MAA lectins ( ranging from 5 to 100 µg/ml ) or neuraminidase ( 0 . 05 to 0 . 5 units/ml ) for 1 hr at 41°C . Chickens were immunized with purified recombinant proteins ( prepared as described above ) or by DNA vaccination using pcDNA3 . 1 as the vector . Briefly , DNA corresponding to EtMIC3-MAR1c ( residues 290–440 ) was PCR amplified with 5′ Eco RI and 3′ Xba I linkers and DNA corresponding to EtMIC3-MAR5 was PCR amplified with 5′ Nco I and 3′ Hind III linkers and each fragment cloned into pcDNA3 . 1 . One week-old pathogen free Light Sussex ( SPF ) chickens were divided into groups ( n = 5–8 ) . For protein immunizations , birds were injected subcutaneously with 100 µg recombinant protein split between two sites in the skin of the neck area . Three injections were administered at two weekly intervals , the first two in Titermax gold adjuvant ( Sigma ) and the third in Freund's incomplete adjuvant . Control groups were immunized with PBS or with thioredoxin fusion protein expressed and purified from empty pET32b vector . For DNA immunizations , birds were injected into the leg muscle with 100 µg plasmid split between two sites . Two injections were administered at two weekly intervals and control groups were immunized with PBS or with pcDNA3 . 1 plasmid DNA lacking a cloned insert . One week after the final immunization all birds were challenged with 250 E . tenella oocysts and total faecal droppings were collected from each individual bird on a daily basis from between 5 and 11 days post challenge . Faecal samples were processed to determine total oocyst counts from each individual bird using a MacMaster flotation chamber . Group averages and standard errors of the means were calculated and statistical significances between the means of different treatment groups determined using post-hoc Tukey analysis of variance . | Eimeria spp . are highly successful protozoan parasites of the intestine of birds and one of the most important diseases in modern poultry farming . The economic impact is significant causing billion dollar losses to the industry and as a result there is pressing need for new therapeutic approaches . Anticoccidial drugs are thwarted by resistance , live vaccines are expensive to manufacture and few recombinant vaccine antigens have been characterized in detail . We show that the microneme protein , MIC3 from Eimeria tenella , is deployed at the parasite-host interface during the early stages of invasion . We provide new atomic resolution insight into its predilection for sialic acid-bearing glycans and demonstrate its role in invasion . We also provide evidence that EtMIC3-based vaccines induce protection in preliminary immunization studies . | [
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"parasi... | 2011 | The Role of Sialyl Glycan Recognition in Host Tissue Tropism of the Avian Parasite Eimeria tenella |
During cell division , the mitotic spindle segregates replicated chromosomes to opposite poles of the cell , while the position of the spindle determines the plane of cleavage . Spindle positioning and chromosome segregation depend on pulling forces on microtubules extending from the centrosomes to the cell cortex . Critical in pulling force generation is the cortical anchoring of cytoplasmic dynein by a conserved ternary complex of Gα , GPR-1/2 , and LIN-5 proteins in C . elegans ( Gα–LGN–NuMA in mammals ) . Previously , we showed that the polarity kinase PKC-3 phosphorylates LIN-5 to control spindle positioning in early C . elegans embryos . Here , we investigate whether additional LIN-5 phosphorylations regulate cortical pulling forces , making use of targeted alteration of in vivo phosphorylated residues by CRISPR/Cas9-mediated genetic engineering . Four distinct in vivo phosphorylated LIN-5 residues were found to have critical functions in spindle positioning . Two of these residues form part of a 30 amino acid binding site for GPR-1 , which we identified by reverse two-hybrid screening . We provide evidence for a dual-kinase mechanism , involving GSK3 phosphorylation of S659 followed by phosphorylation of S662 by casein kinase 1 . These LIN-5 phosphorylations promote LIN-5–GPR-1/2 interaction and contribute to cortical pulling forces . The other two critical residues , T168 and T181 , form part of a cyclin-dependent kinase consensus site and are phosphorylated by CDK1-cyclin B in vitro . We applied a novel strategy to characterize early embryonic defects in lethal T168 , T181 knockin substitution mutants , and provide evidence for sequential LIN-5 N-terminal phosphorylation and dephosphorylation in dynein recruitment . Our data support that phosphorylation of multiple LIN-5 domains by different kinases contributes to a mechanism for spatiotemporal control of spindle positioning and chromosome segregation .
Animal development and tissue homeostasis depend critically on cell divisions that create cells with specific shapes and functions , in the right numbers and at the proper positions . The spindle apparatus plays a central role in the cell division process , as it segregates the chromosomes in mitosis and determines the plane of cell cleavage during cytokinesis [1–3] . Placement of the spindle in the cell center during division results in the formation of daughter cells of equal size , whereas off-center migration and spindle rotation allows the creation of differently sized daughter cells at specific locations . Moreover , the plane of cell cleavage determines whether polarized cells undergo symmetric or asymmetric cell division . Asymmetric cell divisions create cell diversity and allow maintenance of tissue-specific stem cells , by combining self-renewal with the generation of differentiating daughter cells ( Reviews: [4 , 5] ) . Thus , tight control of the spindle function and position is needed to coordinate chromosome segregation with cleavage plane determination , which is essential for genetic stability , tissue integrity and stem cell maintenance in a wide variety of evolutionary contexts . Pioneering studies in Caenorhabditis elegans and Drosophila melanogaster revealed that the position of the spindle responds to polarity cues during asymmetric cell division [1 , 2 , 4 , 5] . In C . elegans , anterior-posterior ( A-P ) polarity is established after fertilization of the oocyte . This involves re-distribution of specific partitioning-defective ( PAR ) proteins into two opposing domains of the cell cortex . The PDZ-domain proteins PAR-3 and PAR-6 form a complex with the PKC-3 aPKC polarity kinase and become restricted to the anterior half of the zygote , while the PAR-2 ring-finger protein and PAR-1 kinase occupy the posterior domain [6] . This A-P polarity guides the asymmetric localization of cytoplasmic determinants as well as the position of the mitotic spindle . During the first mitotic division , the spindle is positioned off-center , to instruct an asymmetric cell division that creates a larger anterior blastomere ( AB ) and smaller germline precursor cell ( P1 ) . Next , the spindle rotates by 90 degrees in P1 , to instruct another asymmetric division with a cleavage plane perpendicular to the one of AB . These early divisions of the C . elegans embryo have served as an important model for studies of the coordinated regulation of cell polarity , fate determinant localization , and spindle positioning during asymmetric cell division . In addition , studies in C . elegans and Drosophila uncovered an evolutionarily conserved protein complex that mediates spindle positioning . This complex consists of the alpha subunit of a heterotrimeric G protein in association with the TPR/GoLoco protein GPR-1/2 and coiled-coil protein LIN-5 in C . elegans ( Gα–Pins–Mud in Drosophila , Gα–LGN–NuMA in mammals ) ( Reviews: [1–6] ) . The GPR-1/2 GoLoco motifs interact with Gα-GDP [7] , while the tetratricopeptide repeats ( TPR ) associate with the C-terminus of LIN-5 ( Fig 1A ) . The ternary protein complex acts at the cell cortex in conjunction with cytoplasmic dynein and microtubule plus ends to generate microtubule pulling forces that promote chromosome segregation and position the spindle [8–12] . Based on results obtained for NuMA , an extended N-terminal domain of LIN-5 likely mediates interaction with the dynein motor complex [9] . It remains unclear how Gα–GPR-1/2–LIN-5 engages dynein and microtubule depolymerization in the generation of cortical pulling forces , and how pulling forces are temporally and spatially restricted . Asymmetric positioning and rotation of the spindle result from imbalance in the pulling forces . It has long been known that the cortical polarity of the C . elegans zygote is fundamental for the spatial organization of pulling forces , creating a higher net force in the posterior than the anterior , which causes the spindle to move off center [13 , 14] . This is in part achieved through PKC-3 mediated phosphorylation of LIN-5 , which inhibits anteriorly directed pulling forces [15] . Phosphorylation also appears to regulate cortical pulling forces in other systems . For example , phosphorylation by aPKC inhibits Pins/LGN localization to the apical cell membrane and promotes planar cell division of MDCK canine kidney cells during cyst formation [16] . Moreover , phosphorylation of NuMA by PLK1 and CDK1 has been implicated in the timing of chromosome segregation and positioning of the mitotic spindle in human cells [17 , 18] . In addition to spindle positioning , the Gα–GPR-1/2–LIN-5 complex is essential for chromosome segregation , in all cell divisions except for the first few embryonic divisions in C . elegans [19–21] . Phosphorylation is likely to play a key role in coordinating chromosome segregation and spindle positioning through spatiotemporal regulation of Gα–GPR-1/2–LIN-5 function . Our previous studies identified extensive in vivo phosphorylation of LIN-5 in C . elegans embryos [15] . The function of the majority of these phosphorylations remained unknown . Here we apply a combination of techniques to determine which phosphorylations are critical for LIN-5 function . CRISPR/Cas9-mediated genetic engineering allowed us to introduce single codon alterations in the C . elegans genome , and to compare non-phosphorylatable and potentially phosphomimetic LIN-5 mutants . In addition to PKC-3 , we found that the PAR-1 polarity kinase likely phosphorylates LIN-5 in vivo , but physiological consequences of this phosphorylation were not detected . Alanine substitution mutagenesis of lin-5 transgenes pointed to four phosphorylated residues with critical functional contributions . Two of these residues form part of a 30 amino-acid domain of LIN-5 required for binding GPR-1/2 . Phosphorylation of these residues promotes cortical pulling forces and GPR-1/2 localization in vivo , and appears to occur sequentially by GSK3 and casein kinase 1 ( CK1 ) . Moreover , we identified essential residues in the LIN-5 N-terminus that are phosphorylated by CDK1 . Our data from extensive knockin replacement mutants are consistent with a mechanism involving sequential phosphorylation and dephosphorylation of the LIN-5 N-terminus in dynein recruitment to the meiotic spindle and cell cortex . Thus , a combination of phosphorylations by cell-cycle and polarity associated kinases likely underlies the spatiotemporal control of pulling forces in chromosome segregation and asymmetric cell division .
Previously , we described that at least 25 residues of LIN-5 are phosphorylated in vivo ( Fig 1A ) [15] . To acquire insight in which phosphorylations are functionally relevant , we replaced each phosphorylated serine or threonine with an alanine residue that cannot be phosphorylated . The relevant codon alterations were introduced in a cloned genomic lin-5 DNA fragment and subsequently tested for functionally complementing the lin-5 ( e1348 ) null mutation in vivo [19] . In the presence of maternal product , lin-5 ( e1348 ) mutants fail to undergo chromosome segregation during postembryonic divisions and continue abortive mitoses [19–21] . Transgenes containing wild type lin-5 or gfp::lin-5 coding sequences restored post-embryonic cell divisions in lin-5 ( e1348 ) null mutants ( Fig 1B ) . However , these lin-5 transgenes appeared susceptible to germline and somatic silencing , as reliable rescue and GFP-LIN-5 expression was observed only in the F1 generation . Hence , we examined transgenic F1 animals , focusing on vulval development and nuclear divisions in the intestine as a quantitative measure for LIN-5 function ( Fig 1B ) . Alanine substitutions of threonine 168 , serine 659 , and serine 662 were the only single amino acid changes that significantly compromised LIN-5 function in vivo . The T168A mutation had the strongest effect and almost completely eliminated the ability to restore intestinal divisions in lin-5 ( e1348 ) null mutants ( Fig 1B ) . Interestingly , this strong effect was specific for the intestine: LIN-5T168A expression allowed lin-5 mutants to develop a normal vulva ( S1 Fig ) . T168 forms part of an ideal consensus phosphorylation site ( S/T*-P-x-K/R ) for the mitotic cyclin-dependent kinase 1 ( CDK-1 ) [22] . CDK-1 is likely to regulate LIN-5 , as multiple CDK-1 consensus sites are present in the LIN-5 N- and C-terminus , and CDK1 phosphoregulation of the NuMA C-terminus has been reported [18 , 23] . We generated double alanine substitutions of T168 in combination with T181 or S199 , two nearby candidate residues for CDK-1 phosphorylation . Strikingly , the transgene encoding LIN-5[T168A , T181A] , but not LIN-5[T168A , S199A] , completely failed to rescue intestinal mitoses and vulva formation in lin-5 ( e1348 ) mutants ( Fig 1B and S1 Fig ) . Because phosphorylation of T181 by itself was not essential for post-embryonic divisions , T168 and T181 phosphorylations likely cooperate to control LIN-5 function . The individual and combined S659A and S662A substitutions ( LIN-5[S659A , S662A] ) also reduced lin-5 ( e1348 ) complementation . By contrast , simultaneous alanine substitutions of serines 729 , 734 , 737 , and 739 did not prevent LIN-5 function ( Fig 1B and S1 Fig ) . In agreement with the latter result , PKC-3 ( aPKC ) phosphorylation of these residues inhibits LIN-5 function and is not required for cell division [15] . Our alanine-substitution experiments indicate that in addition to spatiotemporal regulation of LIN-5 by PKC-3 , phosphorylation of LIN-5 residues in the dynein-interacting N-terminus and GPR-1/2 binding C-terminus may contribute to LIN-5 regulation in vivo . To determine whether CDK1 is indeed able to phosphorylate T168 and T181 of LIN-5 , we performed in vitro kinase assays with recombinant GST-LIN-5 expressed in E . coli as a substrate . Indeed , immunopurified human CDK1/cyclin B phosphorylated GST-LIN-5 , but not GST alone ( S2A and S2B Fig ) . Analysis of in vitro phosphorylated GST-LIN-5 by mass spectrometry revealed extensive phosphorylation of T168 , T181 , and S744 of LIN-5 ( S2B Fig ) . Additionally , peptides containing phosphorylated T704 and S756 were also found , and some other phosphopeptides less frequently . Taken together , CDK1/cyclin B phosphorylates LIN-5 in vitro at multiple sites including T168 and T181 , and phosphorylation of T168 and T181 in vivo appears to be required for LIN-5 function . In contrast to T168 and T181 , residues S659 and S662 are not part of apparent consensus phosphorylation sites . In our previous in vivo mass-spectrometry data , the S659 , S662 double phosphorylated peptides were abundant , while the corresponding unphosphorylated peptides were not detected [15] . This may indicate that S659 and S662 are constitutively phosphorylated in early embryos . To gain insight in which kinases may be involved , we examined LIN-5 phosphorylation in vitro with a series of polarity and cell cycle kinases , followed by mass spectrometry analyses . This revealed several residues that were phosphorylated by multiple kinases in vitro ( Fig 2A ) . In striking contrast , S659 was only phosphorylated by GSK3 , and none of the tested kinases phosphorylated S662 ( Fig 2A ) . We considered several potential explanations for this lack of phosphorylation: the responsible kinase ( s ) may not have been included in the assays , residue S662 may not be accessible in the recombinant protein , or S662 phosphorylation may require a priming event . To test the latter possibility , we performed in vitro kinase assays with synthetic peptides that contain the S659 and S662 residues , either unphosphorylated or phosphorylated at one of the positions . Testing several kinases , we found that casein kinase 1 ( CK1 ) efficiently phosphorylates S662 , but only when the peptide contained a phosphorylated S659 residue ( Fig 2B ) . As for the full length protein , only GSK3 phosphorylated S659 in the unphosphorylated peptide . Based on the combined in vitro data , we propose that GSK3 phosphorylation of residue S659 is a priming reaction for CK1 phosphorylation of S662 . Highly similar phosphorylation has been reported for the Wnt/Frizzled co-receptor LRP6 , with GSK3 priming for CK1 phosphorylation at similar sites [24 , 25] . In addition to CDK1 , GSK3 and CK1 phosphorylation , our analyses revealed phosphorylation of LIN-5 by the polarity kinase PAR-1 . While several phosphopeptides were detected , some were rare and the quantitative software program MaxQuant only recognized the S397 and S739 LIN-5 residues as in vitro phosphorylated by PAR-1 ( Fig 2A ) . S397 is located in the LIN-5 coiled coil region and its phosphorylation was previously observed in embryos ( Fig 2A ) [15] . However , our previous in vivo analysis failed to identify LIN-5 phosphorylations that were diminished after par-1 RNAi [15] . Re-evaluation of the quantitative mass spectrometry data revealed that , although masked by an abundant unrelated peptide , the ratio between the phosphorylated and unphosphorylated S397 peptide was severely reduced in par-1 ( RNAi ) embryos compared to control RNAi embryos ( S3 Fig ) . In contrast , S739 phosphorylation was not significantly affected by par-1 knockdown in vivo [15] . Taken together , we identified multiple phosphorylated LIN-5 residues as well as candidate kinases that could be important in the regulation of LIN-5 function . In addition to four adjoining residues phosphorylated by PKC-3 in the C-terminus , T168 and T181 may be phosphorylated by CDK-1 , S397 by PAR-1 , and S659 by GSK-3 , to prime phosphorylation of S662 by CK1 . Both S659 , S662 and the four residues phosphorylated by PKC-3 are located in the LIN-5 C-terminus which mediates GPR-1/2 binding [15 , 26] . As phosphorylation could affect GPR-1/2 association , we wanted to define which LIN-5 residues are critical for GPR-1/2 binding . Testing deletion constructs in yeast two-hybrid assays confirmed that the LIN-5 C-terminal region is sufficient for GPR-1 association . GPR-1 interaction was observed for all truncated LIN-5 proteins except for those with deletions in the 609–671 amino acid region ( Fig 3A ) . At the same time , including only the 609–671 LIN-5 fragment did not allow growth in this assay , possibly due to an inability of this short fragment to fold properly in yeast ( Fig 3A ) . The essential 609–671 region does not contain serine 729 , 734 , 737 , and 739 phosphorylated by PKC-3 in vivo , in agreement with our previous conclusion that PKC-3 phosphorylation of LIN-5 does not prevent interaction with GPR-1/2 [15] . To identify specific LIN-5 amino acids required for GPR-1/2 interaction , we performed “reverse yeast two-hybrid screening” . This method selects mutations that disrupt bait-prey protein interactions , making use of URA3-mediated conversion of 5-fluoroorotic acid ( 5-FOA ) to a toxic product [27] . The normal interaction between LIN-5 and GPR-1 leads to GAL4-controlled URA3 expression in yeast two-hybrid assays , and causes cell death in the presence of 5-FOA . Thus , following mutagenesis of one of the binding partners , interaction-deficient alleles can be recovered from 5-FOA-resistant colonies [28] . We used PCR-based random mutagenesis of LIN-5 prey fragments ( amino acids 609–821 ) , and isolated 163 5-FOA resistant yeast colonies in a reverse yeast two-hybrid screen ( for details see Materials and Methods , S4A Fig ) . 89 colonies contained a single missense mutation in the LIN-5 coding sequences , together changing 15 different amino acids . Substitutions of 12 of these 15 individual amino acids caused loss of GPR-1 interaction again in the re-test ( Fig 3B and 3C ) . The 12 affected residues were all located between amino acids 638–667 of LIN-5 . Importantly , the interaction-defective alleles included missense mutations of the phosphorylated residues S659 and S662 . In fact , S662 was found altered to glycine , cysteine and asparagine ( S4B Fig ) . These data indicate that a 30 amino acid stretch in the LIN-5 C-terminal region , which includes the in vivo phosphorylated S659 and S662 residues , mediates the interaction with GPR-1 . Following up on the interaction defective alleles , we noticed that the effect of missense mutations was substantially reduced when tested in the context of full length LIN-5 , compared to the C-terminus only . Western blot analysis did not reveal substantial differences in protein levels compared to wild type ( S5A Fig ) . The LIN-5 coiled-coil region promotes dimerization and is thereby expected to increase GPR-1 binding avidity . Only one of the four most frequently identified mutations , L663S , also interfered with full length LIN-5 binding to GPR-1 ( Fig 3D , left panel ) . However , at a reduced temperature ( 20°C ) , this leucine 663 to serine ( LIN-5[L663S] ) mutation still allowed growth on selective media , indicating that GPR-1 interaction is not completely abolished . We also tested S659 and S662 phosphorylation-site mutants in the context of full length LIN-5 . While the single mutations had little effect on GPR-1 binding , replacement of both serine 659 and 662 by alanine reduced GPR-1 interaction in yeast , as detected by lack of growth on -His plates at 30°C ( Fig 3D , right panel ) . Phosphomimetic substitutions ( S to D or E ) of S659 , S662 , or both , did not reduce interaction ( Fig 3D , right panel ) . These results are consistent with phosphorylation of S659 and S662 contributing to GPR-1/2 binding , and taking place in yeast as well as C . elegans . Taken together , our forward and reverse yeast two-hybrid assays identified LIN-5 residues that appear to mediate interaction with GPR-1/2 , which are located within a 30 amino acid C-terminal domain . This includes S659 and S662 , of which the phosphorylation in vivo likely contributes to GPR-1/2 binding . We used CRISPR/Cas9-mediated gene targeting to engineer lin-5 alleles and examine the effects of amino acid substitutions in vivo [29–32] . First , we created the lin-5[L663S] mutation by introducing a single nucleotide alteration in the endogenous lin-5 locus . This resulted in a typical lin-5 loss-of-function phenotype , with homozygous sterile , thin and uncoordinated larvae that fail to undergo chromosome segregation but continue abortive mitoses [19 , 20] . We determined the number of nuclei in the intestine and ventral cord , following fixation and staining of DNA . In lin-5[L663S] mutants , both tissues contained severely reduced numbers of nuclei compared to the wild type , consistent with a failure to undergo chromosome segregation in most post-embryonic divisions ( Fig 4A and 4B , S6A Fig ) . Thus , a single change of amino acid L663 in the GPR-1-binding motif of LIN-5 results in strong loss-of-lin-5 function . This result confirms the power of reverse yeast two-hybrid screening in identifying amino acids that affect protein-protein interactions in vivo [27] . Next , we used genome engineering to alter the in vivo phosphorylated residues T168 , T181 , S397 , S659 and S662 . For each residue , we created a non-phosphorylatable alanine substitution allele , as well as one or more potentially phosphomimetic alleles that contain aspartic acid or glutamic acid at the relevant positions . Alteration of the PAR-1 phosphorylated S397 residue had no apparent effect . Homozygous S397A and S397E animals were viable and showed normal development . Even close examination of LIN-5-mediated processes did not reveal abnormalities ( See below; Fig 4C and 4D , S6A and S6B Fig and S1 Video ) . Thus , although this phosphorylation occurs in vivo , it is by itself not a major determinant of LIN-5 function . Compared to our transgene rescue experiments ( Fig 1B and S1 Fig ) , the effect of S659 and S662 alanine substitution mutations in endogenous lin-5 was quite mild . The lin-5[S659A , S662A] double mutant animals were viable , with only a slight reduction in intestinal nuclei number ( S6A Fig ) , but displayed a significant increase in embryonic lethality ( 3 . 6±1 . 0% at 25°C , wild type 0 . 9±0 . 4% ) . The phosphomimetic lin-5[S659E , S662D] mutation did not cause embryonic lethality or larval defects , consistent with constitutive phosphorylation of these residues in early embryos ( S6A Fig ) . In stark contrast , alteration of the candidate CDK-1 phosphorylated residues in the N-terminus , threonine 168 and 181 to alanine ( lin-5[T168A , T181A] ) , aspartic acid ( lin-5[T168D , T181D] ) or glutamic acid ( lin-5[T168E , T181E] ) , all resulted in typical lin-5 mutant offspring . Regardless of the mutant combination , homozygous animals derived from heterozygous parents developed into sterile , thin and uncoordinated larvae , and showed severely impaired cell division during larval development ( Fig 4A and 4B ) . Importantly , substitution of threonine 168 and 181 with serine residues ( lin-5[T168S , T181S] ) did not lead to any detectable phenotype or defects in cell division ( Fig 4A and 4B ) . These observations and the in vivo phosphorylation of T168 and T181 indicates that phosphoregulation of T168 and T181 is critical for LIN-5 function , in agreement with the results of the transgene rescue experiments ( Fig 1B and S1 Fig ) . Together , our targeted genome alterations identified several individual amino acids that are required for the in vivo function of LIN-5 , including phosphorylated residues in the N-terminus and residues in the GPR-1 binding domain . Additional characterizations of the non-phosphorylatable and phosphomimetic mutants revealed insight in the functional contribution of LIN-5 phosphorylation . As the contribution of S659 and S662 phosphorylation appeared quite subtle , we examined the spindle in early embryos with substitutions of these residues in detail . In the wild type , meiosis completes after fertilization and results in the formation of a haploid maternal pronucleus , which migrates to meet the paternal pronucleus in the posterior , after which the adjoined pronuclei and centrosomes migrate to the center , rotate and form a spindle along the long axis of the zygote [1 , 6] ( S1 Video ) . Observations with differential interference contrast ( DIC ) microscopy showed that these events all occur normally in lin-5[S659A , S662A] and lin-5[S659E , S662D] mutants . Subsequently , in wild type embryos , the chromosomes become aligned at the metaphase plate and are segregated to opposite poles during anaphase . During spindle elongation , the posterior spindle pole oscillates extensively , while the anterior pole remains relatively steady . This coincides with spindle movement towards the posterior , and is followed by flattening of the posterior pole ( S1 Video ) . Starting in anaphase , mutant embryos with non-phosphorylatable lin-5[S659A , S662A] deviated from the wild type , while lin-5[S659E , S662D] mutants showed no phenotype . Specifically , lin-5[S659A , S662A] mutants showed significantly dampened oscillation of both the anterior and posterior pole , reduced spindle elongation , and nearly absent flattening of the posterior spindle pole ( Fig 4C and S6B Fig ) . Nevertheless , both non-phosphorylatable and phosphomimetic S659 , S662 mutants underwent asymmetric division of the zygote as normal , which resulted in the formation of a larger anterior blastomere ( AB ) and smaller germline precursor cell ( P1 ) . The spindle normally rotates by 90 degrees prior to division of the P1 blastomere ( S1 Video ) . This failed to occur or was incomplete in 47 . 1% of the lin-5[S659A , S662A] two-cell embryos , compared to 6 . 3% and 7 . 3% incomplete rotation scored in wild type and lin-5[S659E , S662D] mutant embryos , respectively ( Fig 4C and S6B Fig ) . As protein levels were comparable to wild type ( S5B Fig ) , these results suggest that cortical pulling forces are reduced in lin-5[S659A , S662A] mutants . Interestingly , this does not disrupt the asymmetry of the first division and has only a small effect on viability . To determine cortical pulling forces more directly , we performed spindle severing assays with a UV laser beam [13] . Confirming our DIC analyses , the peak velocities of spindle pole movements were significantly reduced in lin-5[S659A , S662A] embryos ( anterior pole 20 . 5% , posterior pole 18 . 4% reduced compared to wild type ) ( Fig 4D , S2 and S5 Videos ) . Similar experiments performed with lin-5[S659E , S662D] mutant embryos and PAR-1 phosphorylation site mutants ( S397A and S397E ) did not reveal significant divergence from the wild type ( Fig 4D , S3 , S4 and S6 Videos ) . These data support the conclusion that phosphorylation of S659 and S662 contributes to cortical pulling forces , both in the anterior and posterior , and thereby to spindle pole oscillation , spindle elongation , posterior pole flattening and spindle rotation in P1 . Moreover , the finding that pulling forces , albeit reduced , remained asymmetric in lin-5[S659A , S662A] mutants explains why these mutants show normal asymmetry of the first division , and normal sizes of the AB and P1 blastomeres . We wondered whether Wnt-signaling could locally control GSK-3 kinase activity to affect LIN-5 S659 , S662 phosphorylation and asymmetric cell division . In the EMS blastomere of the 4-cell embryo , the spindle rotates from a left/right to anterior/posterior position to correctly specify and position the E and MS daughter cells [33] . This rotation is redundantly controlled by MES-1/SRC-1 and MOM-2/MOM-5 Wnt/Frizzled signaling pathways [34] . We examined whether the Wnt pathway contributes to EMS spindle rotation through phosphorylation of LIN-5[S659 , S662] . Making use of a mes-1 ( bn74ts ) mutant strain expressing GFP-β-tubulin , we observed normal spindle rotation in lin-5[S659A , S662A] mutant embryos , with only one of 13 embryos showing a tilted spindle angle in the EMS blastomere ( S6C Fig ) . mes-1 ( bn74ts ) ; lin-5[S659E , S662D] mutant embryos showed an occasional failed rotation or tilted spindle angle . In control mes-1 ( bn74ts ) ; gsk-3 ( RNAi ) mutants , the EMS spindle failed to rotate in 9/11 embryos ( S6C Fig ) . This clear difference in phenotype shows that LIN-5 S659 phosphorylation is not the major contribution of GSK-3 in EMS spindle rotation . Asymmetric divisions of epithelial seam cells in the C . elegans epidermis also depend on a Wnt-β- catenin asymmetry pathway [35 , 36] , and remained normal in lin-5[S659A , S662A] and lin-5[S659E , S662D] mutants . Thus , evidence for developmental regulation of LIN-5–GPR-1/2 interaction through Wnt-signaling was not obtained . Instead , absence of unphosphorylated S659 , S662 peptides in our mass spectrometry analyses , and the wild type appearance of phosphomimetic mutants point to constitutive phosphorylation of the S659 , S662 residues . Our yeast two-hybrid data showed reduced interaction between LIN-5[S659A , S662A] and GPR-1 compared to wild type , which likely explains the reduced pulling forces observed in vivo . We examined whether the colocalization between LIN-5 and GPR-1 in vivo depends on LIN-5 phosphorylation . Hereto , we generated strains with lin-5[S659 , S662] double phosphorylation-site alterations in combination with egfp::gpr-1 , a CRISPR/Cas9-mediated knockin allele of the endogenous gpr-1 locus . Immunohistochemical detection of eGFP and LIN-5 showed normal colocalization of LIN-5 and GPR-1 in phosphomimetic lin-5[S659E , S662D] mutants at the centrosomes and cell cortex ( Fig 5 and S7 Fig; note that LIN-5 becomes clearly visible at the cortex only after the one-cell stage ) . In contrast , in lin-5[S659A , S662A] mutant embryos , GPR-1 localized to the cortex but no longer accumulated at the centrosomes ( Fig 5 ) . Notably , GPR-1/2 localization at the cortex primarily depends on association with the GOA-1 and GPA-16 Gα proteins and is required for pulling forces , whereas ASPM-1–LIN-5 anchors GPR-1/2 at the centrosome without early embryonic requirement [21 , 37] . Thus , while the loss of centrosomal GPR-1 appears to confirm a reduced binding affinity for LIN-5[S659A , S662A] compared to wild type LIN-5 , the reduced pulling forces likely result from a similarly reduced affinity between these proteins at the cortex . Nevertheless , LIN-5 still localized to the cortex in lin-5[S659A , S662A] mutants ( S7 Fig ) . This likely reflects different dynamics of the two complexes; with rapid exchange of LIN-5 at the cortex while centrosomal GPR-1/2 accumulation likely depends on prolonged LIN-5 association . The combined observations in yeast two-hybrid assays , phenotypic analyses , and protein localization studies strongly indicate that phosphorylation of LIN-5 residues S659 and S662 contributes to the affinity of the LIN-5/GPR-1/2 interaction in vivo . Characterization of the CDK-1 phosphorylation site mutants required a different strategy , as homozygous lin-5[T168A , T181A] and lin-5[T168D , T181D] mutants are fully sterile . To be able to examine the effects of these mutations in early embryos , we created trans-heterozygotes carrying these mutations and egfp::lin-5 , a functional CRISPR/Cas9-generated knockin allele of endogenous lin-5 . The egfp::lin-5 allele served both as a visible balancer for the lin-5 phosphorylation site mutations , and allowed selective knockdown of functional lin-5 by RNAi against egfp . This strategy allowed us to obtain and characterize early embryos with CDK1-phosphorylation site alterations in LIN-5 . Control immunohistochemical staining experiments confirmed that egfp RNAi treatment of homozygous egfp::lin-5 adults completely removed LIN-5 and eGFP from the offspring ( S8 Fig ) . Following egfp RNAi treatment of heterozygous animals with wild type lin-5 ( lin-5 ( + ) / egfp::lin-5 ) , LIN-5 localized normally , but the eGFP staining was lost ( Fig 6 ) . These results demonstrate that the RNAi effect remains specific for egfp::lin-5 and does not carry over to the untagged lin-5 allele . Testing balanced lin-5[T168A , T181A] and lin-5[T168D , T181D] animals the same way , we observed that the mutant LIN-5 proteins are expressed and localize as normal to the cortex and centrosomes , while the early embryonic divisions were clearly defective ( Fig 6 and S5C Fig ) . Interestingly , lin-5[T168A , T181A] and lin-5[T168D , T181D] showed similar abnormalities , emphasizing the critical role for the in vivo phosphorylated threonine residues at these positions . Using the above-described method , we also performed live imaging by time-lapse DIC microscopy and spindle severing experiments with lin-5[T168A , T181A] and lin-5[T168D , T181D] mutant embryos . Again , the defects observed in both mutants resembled lin-5 strong loss-of-function [19 , 26] , and cortical pulling forces were greatly reduced in both mutants ( Fig 4E and S7 and S8 Videos ) . In contrast , homozygous lin-5[T168S , T181S] mutants showed normal spindle pulling forces ( Fig 4E and S9 Video ) . This indicates that the two threonine residues are not essential per se , but phosphorylation and de-phosphorylation at these sites is likely critical . The lin-5[T168S , T181S] mutants did show dampened spindle oscillation , which might result from somewhat different kinetics of threonine versus serine phosphorylation and dephosphorylation in CDK1 substrates [38] . Because the N-terminus of LIN-5 is implicated in the recruitment of dynein [9] , we crossed both mutants with an mCherry::dhc-1 strain , in which the mCherry tag was introduced into the endogenous dynein heavy chain gene by CRISPR/Cas9-mediated knockin . This homozygous mCherry::dhc-1 strain is viable and develops as normal . mCherry::DHC-1 was diffusely detected in the cytoplasm , and distinctly localized at the nuclear envelope , kinetochores , astral microtubules , spindle poles and cell cortex . Localization of dynein was dynamic during all stages of mitosis , but cortical dynein was barely detectable at the one-cell stage . However , following treatment of permeabilized embryos with nocodazole to depolymerize microtubules , mCherry::DHC-1 accumulated on the cell cortex of one-cell embryos in metaphase and anaphase ( Fig 7A and S9 Fig ) . Strikingly , this cortical dynein localization was abolished by lin-5 RNAi , and did not occur in lin-5[T168A , T181A] and lin-5[T168D , T181D] mutant embryos ( Fig 7A ) . Since these mutant LIN-5 forms localize to the cell cortex , T168 and T181 are critical for the function of LIN-5 as a cortical dynein anchor . In addition to cortical localization of dynein in mitosis , LIN-5 is also required for dynein recruitment to the poles of the meiotic spindle [37] . Accumulation of dynein at the spindle poles , as well as the cell cortex , occurs coincident with anaphase onset of meiosis I and II , and is needed for spindle rotation and expulsion of chromosomes into a polar body [37 , 39 , 40] . While homozygous lin-5[T168S , T181S] mutants showed normal meiosis , we observed polar body absence and abnormally large polar bodies in eGFP::LIN-5-depleted lin-5[T168A , T181A] and lin-5[T168D , T181A] embryos , consistent with lin-5 loss of function . To examine meiotic spindle rotation and dynein localization in such embryos , we combined the lin-5 mutations , balanced by egfp::lin-5 , with homozygous gfp::tbb-2 β—tubulin and mCherry::DHC-1 dynein reporters ( Fig 7B and S10–S21 Videos ) . In a control strain with wild type LIN-5 , spindle rotation and dynein accumulation occurred in 10 of 11 embryos ( the one exception showed rotation but only weak mCherry::DHC-1 accumulation ) ( Fig 7B left and S10–S12 Videos ) . Examination of egfp RNAi treated egfp::lin-5 embryos with combined DIC and fluorescence microscopy revealed normal diffuse association of DHC-1 with the meiotic spindle in meiotic prophase , followed by gradual loss of mCherry::DHC-1 from the anaphase spindle , rather than accumulation of dynein at the poles . The failure in dynein localization coincided with failure to rotate the meiotic spindle ( Fig 7B ) . These results agree with our previously reported meiotic lin-5 RNAi phenotype [21 , 37] , although this time we also observed abnormally elongated meiotic spindles in meiosis II in a subset of the embryos , as has been reported for dynein complex subunits [40] . eGFP::LIN-5-depleted lin-5[T168A , T181A] and lin-5[T168D , T181D] embryos were indistinguishable from lin-5 knockdown mutants ( Fig 7B and S13–S21 Videos ) . In conclusion , substitution of LIN-5 T168 and T181 with non-phosphorylatable alanine or phosphomimetic aspartic acid residues creates a severe defect in LIN-5-mediated dynein recruitment . In contrast , replacement of the same residues with phosphorylatable serine residues did not compromise LIN-5 function ( Fig 4A , 4B and 4E ) . Combined with the available literature [37 , 39 , 41] , these data point to CDK-1-mediated phosphorylation and subsequent dephosphorylation of the LIN-5 N-terminus as a critical step in dynein recruitment to the meiotic spindle and cell cortex ( see below ) .
In this study , we investigated whether the extensive in vivo phosphorylation of the LIN-5NuMA protein is important for chromosome segregation and cell cleavage plane determination . We combined in vivo and in vitro phosphorylation analysis , identified critical phosphorylated LIN-5 residues by complementation , and defined the LIN-5–GPR-1 interaction domain by reverse yeast two-hybrid screening . Using this information , we created phosphosite mutants and tagged alleles by genetic engineering , and determined the in vivo contribution of individual phosphorylated residues by protein localization studies , time-lapse microscopy and spindle severing experiments . The combined data indicate that a variety of cell cycle and polarity kinases phosphorylate LIN-5 , with specific phosphorylations promoting pulling force generation while others inhibit LIN-5 function . The combined phosphorylations of the LIN-5 N-terminus and C-terminus are critical in the spatiotemporal control of cortical pulling forces , and thereby for correct chromosome segregation and spindle positioning ( Fig 8 ) . CRISPR/Cas9-mediated genomic engineering has added an important tool to a powerful genetic system , and more efficient procedures are continuously developed [31 , 42–46] . The use of CRISPR/Cas9 allowed us to precisely alter one or two codons of specific serine/threonine residues within the normal genetic background . Using knockin alleles eliminates unwanted effects of transgene overexpression or silencing . In particular transgene silencing has long hampered lin-5 studies and was also observed in our complementation studies . Transgene expression levels that are close to a threshold level may explain why the lin-5[S659A , S662A] mutation showed a strong loss-of-function phenotype , while the effect of the same mutations introduced in the endogenous locus was less severe . In addition to phosphosite mutations , we also created tagged endogenous alleles of lin-5 , gpr-1 and dhc-1 for fluorescent fusion protein expression . This allowed the development of a novel method for analysis of early lethal mutations . This method makes use of a functional eGFP-tagged allele , which acts as a visible balancer and allows the specific removal of wild type function by egfp RNAi . In a previous study , we revealed in vivo kinase activity through differential labeling of C . elegans cultures with stable nitrogen isotopes , followed by kinase knockdown and quantitative analysis of phosphopeptides by mass spectrometry [15] . This strategy worked well for PKC-3 , but various limitations can prevent detection of kinase-substrate relations in vivo . The phosphorylation of LIN-5 by PAR-1 was missed in our previous analysis , because of overlap between the relevant LIN-5 phosphopeptides and unrelated peptides . Identification of mitotic substrates of CDK-1 is difficult in vivo , because CDK-1 knockdown results in complete sterility and arrest of fertilized oocytes before completion of meiosis [47] . Casein kinase I , in turn , is represented by 87 family members in C . elegans [48] , making it less likely that knockdown experiments will reveal a quantitative difference in substrate phosphorylation . The in vitro kinase assays in the current study revealed candidate kinases that were otherwise difficult to detect . The PAR-1 in vitro kinase assays pointed to a specific LIN-5 phosphorylation that was subsequently confirmed by our in vivo data . The in vitro phosphorylation of peptides with single phosphorylated residues was instrumental in detecting a probable two-step mechanism for S662 phosphorylation by CKI , following a priming phosphorylation by GSK3 . Thus , while detecting direct phosphorylation in vivo remains the ultimate goal , in vitro assays continue to provide meaningful insight . The combined in vitro and in vivo kinase analyses strongly suggest that PAR-1 phosphorylates LIN-5 at serine 397 . Replacing this serine with non-phosphorylatable alanine or phosphomimetic glutamic acid apparently did not affect viability , development , cell division , chromosome segregation or spindle pulling forces . In fact , many phosphorylations that occur in vivo may be bystander rather than regulatory events , and determining which phosphorylations are critical in vivo has received great attention in the current study . The first selection came from alanine substitution mutagenesis combined with complementation of a lin-5 null mutation . This revealed that 4 of the 25 phosphorylated residues are critical for LIN-5 function . As we could only score larval divisions in this assay , we cannot exclude that additional phosphorylations may be critical during embryogenesis . Remarkably , 2 of the 4 critical residues form part of a probable GPR-1/2 binding domain , while the other 2 appear to mediate contact with dynein at the cortex . We defined the GPR-1/2 binding domain through screening for LIN-5 residues that are essential for GPR-1 interaction in yeast two-hybrid assays . The strong clustering of missense mutations in this screen combined with results from deletion analyses suggests a short linear GPR-interaction epitope . This is in full agreement with results from crystal structure studies of the related NuMA-LGN complex . The TPR repeats in the N-terminal half of LGN form helix-turn-helix repeats that together organize into a superhelical bundle [49 , 50] . The inner surface of this bundle forms a binding channel for an extended NuMA peptide of 28 amino acids [49] . Many electrostatic and hydrogen interactions between side chains of the NuMA peptide and TPR motifs together provide a high affinity binding site . The TPR-repeat interaction site in LIN-5 resembles that of NuMA in size , position , and overall amino-acid composition . The exact residues are not well-conserved , however , probably because the many amino acids that contribute weak interactions provide a limited biological constraint for the conservation of individual amino acids . Notably , the core of the binding site contains EPEQLDDW in human NuMA and SPDSLPDF in LIN-5 , sharing three identical and two similar residues as well as negative charge . The NuMA peptide contains four acidic residues ( D , E ) , while two D residues and two phosphorylated serines are negatively charged in the LIN-5 peptide . Phosphorylation offers the opportunity to regulate LIN-5–GPR-1/2 binding . In fact , dual GSK3 and CK1 phosphorylation of the LRP6 Wnt-co-receptor regulates the interaction of LRP6 with axin [24 , 51] . We did not obtain evidence to support developmentally regulated LIN-5–GPR-1 binding . Alanine substitution of S659 and S662 significantly reduced spindle pulling forces , but division of the zygote , EMS blastomere and seam cells continued to be asymmetric . The latter types of divisions depend on the Wnt-β —catenin asymmetry pathway , which in EMS positions the spindle redundantly with mes-1/src-1 signaling [34] . Even the combined lin-5[S659A , S662A] mutation and mes-1 knockdown did not interfere with A-P positioning of the spindle in EMS . Moreover , we could functionally replace serine 659 and 662 with glutamic and aspartic acid , suggesting that charge , rather than phosphoregulation , is critical for GPR-1/2 interaction . A contribution of CDK-1 phosphorylation in LIN-5 regulation was expected . CDK1/cyclin B kinases are the master regulators of mitosis that phosphorylate hundreds of substrate proteins [22 , 52 , 53] . The LIN-5 N- and C-terminus and corresponding domains in NuMA contain multiple CDK1 consensus sites . CDK1/cyclin B has been shown to regulate Xenopus and human NuMA through phosphorylation of the C-terminus [18 , 54] . Specifically , phosphorylation at T2055 interferes with the cortical localization of NuMA , thereby inhibiting dynein recruitment until CDK1/cyclin B is inactivated at the metaphase/anaphase transition [18] . Our results indicate that this temporal regulation may also involve critical phosphorylation of the dynein-interacting N-terminus of NuMA by CDK1/cyclin B . In C . elegans , dynein recruitment to the meiotic spindle and cell cortex , as well as mitotic pulling forces , depend on activation of the anaphase promoting complex/cyclosome ( APC/C ) , and inactivation of CDK-1/cyclin B [37 , 39 , 41] . Thus , phosphorylation of specific mitotic substrates by CDK-1/cyclin B is likely to inhibit dynein recruitment and pulling force generation . A recent study identified the p150 dynactin subunit as a likely candidate for inhibition by CDK-1/cyclin B phosphorylation [40] . Our results point to the LIN-5 N-terminus as another critical target for CDK-1 regulation . Supporting this conclusion , T168 , T181 are part of CDK consensus sites , are phosphorylated in vivo , and are efficiently phosphorylated by CDK1/cyclin B in vitro . Substitution of LIN-5 T168 and T181 with phosphomimetic glutamic acid or aspartic acid residues resulted in strong loss of LIN-5 function , supporting that CDK-1 phosphorylation normally inhibits LIN-5 . More surprising , an indistinguishable phenotype was observed following T168 and T181 replacement with non-phosphorylatable alanine . This could indicate that the threonine residues are critical for LIN-5 folding , or that phosphorylation of these threonines in the N-terminus also contributes to dynein recruitment . In stark contrast to alanine substitution , replacement of the same residues with phosphorylatable serine had no detectable effect on pulling forces , meiotic and mitotic cell divisions , viability and fertility . While other explanations are possible , these data are consistent with a required sequential CDK-1 phosphorylation and dephosphorylation of LIN-5 T168 and T181 . Therefore , we propose a two-step model , in which CDK-1/cyclin B induces the assembly of a LIN-5 pre-force generating complex in prometaphase . Subsequent removal of the phosphates , which follows CDK inactivation by the APC/C at anaphase onset , promotes interaction of this complex with dynein . Many of the lessons learned from studies in worms and flies have subsequently been found to apply broadly to the animal kingdom . The initial discovery of LIN-5 requirement in spindle positioning in C . elegans [19] has contributed to identifying similar functions for NuMA in mammalian systems [55] . It will be intriguing to find out to what extent the phosphoregulation of pulling forces translates from C . elegans to mammalian systems , and specifically whether reversible CDK1 phosphorylation of the NuMA N-terminus controls dynein interaction and spindle positioning .
Strains were cultured on nematode growth medium plates , seeded with Escherichia coli OP50 as previously described [56] . Animals were maintained at 20°C , unless stated otherwise . All strains used in this study are found in S1 Table . Genome modifications in strains SV1568 , SV1569 , SV1586 , SV1588 , SV1589 , SV1590 , SV1600 , SV1619 , SV1621 , SV1622 , SV1695 and SV1901 were introduced by making use of CRISPR/Cas9 genome editing as described below . For functional analysis of wild type and phosphomutant LIN-5 , 5 ng/μl Plin-5::gfp::lin-5 DNA , together with 5 ng/μl Psur-5::dsRed and 25 ng/μl Lambda DNA ( Fermentas ) , was injected into the gonad of SV918 young adults . Psur-5::dsRed positive F1 progeny were selected making use of a fluorescence stereo microscope ( Leica , MZ16F ) . After this , lin-5 ( e1348 ) homozygous animals were selected based on absence of pharyngeal Pmyo-2::gfp , expressed from the mIn1 balancer chromosome . Rescue analysis of lin-5 null animals was performed by Differential Interference Contrast and fluorescence microscopy , using a Zeiss Axioplan microscope . Intestinal nuclei were counted only in animals expressing Psur-5::dsRed in all intestinal nuclei . Vulval development was assayed for all animals L4 and older . For quantification of cell numbers in CRISPR/Cas9 knockin mutants , asynchronous populations of animals were fixed , DNA stained with propidium iodide and intestinal and ventral cord nuclei were counted using a Zeiss Axioplan fluorescence microscope . Cells were counted at late larval stages . For the ventral cord , all nuclei of the P2-to-P10 daughter cells and juvenile motor neurons in the region between these cells were counted . For in vitro CDK1 kinase assays , immunoprecipitations were performed from mitotic lysates of HeLa cells using mouse monoclonal anti cyclin B1 ( GNS1 ) or beads alone as negative control . Immunoprecipitations were incubated for 30 min at 30°C with either Histone H1 , bacterially produced GST or GST–LIN-5 in kinase buffer containing 50 mM HEPES at pH 7 . 5 , 5 mM MgCl2 , 2 . 5 mM MnCl2 , 1 mM dithiothreitol , 50 μM ATP and 2 . 5 μCi [γ-32P] ATP . Reactions were terminated by the addition of SDS ( 5x sample buffer ) . For mass spectrometry analysis , no [γ-32P] ATP was added to the kinase assays and incubation time was prolonged to 2 hours at 30°C . For in vitro GSK3 and CK1 kinase assays , peptides ( RRRIRCGSPDSLPDFLADN ) containing either unphosphorylated , phosphorylated S659 or phosphorylated S662 were used . Kinases were incubated for 30 min at 25°C with synthetic peptide in kinase buffer containing 200 μM ATP , 50 mM HEPES at pH 7 . 5 , 10 mM MgCl2 , 1 mM EGTA , 2 mM dithiothreitol , supplemented with 20 μCi [γ-32P] ATP for radioactive kinase assays . Reactions were terminated by the addition of SDS ( 4x sample buffer ) . All other in vitro kinase assays were performed as previously described [15] . In short , kinases were incubated for 30 min at 25°C with bacterially produced GST or GST–LIN-5 in kinase buffer containing 200 μM ATP , 50 mM HEPES at pH 7 . 5 , 10 mM MgCl2 , 1 mM EGTA , 2 mM dithiothreitol , supplemented with 20 μCi [γ-32P] ATP for radioactive kinase assays . Reactions were terminated by the addition of SDS ( 4x sample buffer ) . For mass spectrometry analysis , no [γ-32P] ATP was added to the kinase assays and incubation time was prolonged to 2 hours at 25°C . Kinases used in this study were: recombinant C . elegans PAR-1 ( a kind gift from Erik Griffin and Geraldine Seydoux ) , and mammalian Aurora B ( a kind gift from Susanne Lens ) , CK1 ( New England Biolabs ) , CK2 ( New England Biolabs ) , and GSK3 ( New England Biolabs ) . Gel bands were cut and processed for protein in-gel digestion as described elsewhere [15] . Briefly , proteins were reduced with dithiothreitol and then alkylated with iodoacetamide . Trypsin was added at a concentration of 10 ng/μl and the mixture was digested overnight at 37°C . Subsequently , peptides were collected from the supernatants and a second extraction using 10% formic acid was performed . Phosphopeptides from LIN-5 were enriched using TiO2 chromatography [57] . Basically , home-made GELoader tips ( Eppendorf , Hamburg , Germany ) were packed with TiO2 beads ( 5 μm , INERTSIL ) . Peptides were loaded in 10% formic acid and subsequently washed with 20 μl of 80% acetonitrile , 0 . 1% trifluoroacetic acid ( Fluka , Sigma-Aldrich ) . Phosphopeptides were then eluted twice with 20 μl of 1 . 25% ammonia solution ( Merck , Germany ) , pH 10 . 5 , and 3 μl of 100% formic acid was finally added to acidify the samples . Nanoflow LC-MS/MS was carried out by coupling an Agilent 1100 HPLC system ( Agilent Technologies , Waldbronn , Germany ) to an LTQ-Orbitrap XL mass spectrometer ( Thermo Electron , Bremen , Germany ) . Peptide samples were delivered to a trap column ( AquaTM C18 , 5 μm ( Phenomenex , Torrance , CA ) ; 20 mm x 100-μm inner diameter , packed in house ) at 5 μl/min in 100% solvent A ( 0 . 1 M acetic acid in water ) . Next , peptides eluted from the trap column onto an analytical column ( ReproSil-Pur C18-AQ , 3μm ( Dr . Maisch GmbH , Ammerbuch , Germany ) ; 40 cm x 50-μm inner diameter , packed in house ) at ~100 nl/min in a 90 min or 3 h gradient from 0 to 40% solvent B ( 0 . 1 M acetic acid in 8:2 ( v/v ) acetonitrile/water ) . The eluent was sprayed via distal coated emitter tips butt-connected to the analytical column . The mass-spectrometer was operated in data-dependent mode , automatically switching between MS and MS/MS . Full-scan MS spectra ( from m/z 300 to 1500 ) were acquired in the Orbitrap with a resolution of 60 , 000 at m/z 400 after accumulation to target value of 500 , 000 in the linear ion trap . The five most intense ions at a threshold above 5000 were selected for collision-induced fragmentation in the linear ion trap at a normalized collision energy of 35% after accumulation to a target value of 10 , 000 . Peak lists were created from raw files with MaxQuant43 . Peptide identification was carried out with Mascot ( Matrix Science ) against a Caenorhabditis elegans protein database ( http://www . wormbase . org ) supplemented with all the frequently observed contaminants in MS ( 23 , 502 protein sequences in total ) . The following parameters were used: 10 ppm precursor mass tolerance , 0 . 6 Da fragment ion tolerance , up to 3 missed cleavages , carbamidomethyl cysteine as fixed modification , oxidized methionine , phosphorylated serine , threonine and tyrosine as variable modifications . Alternatively , MaxQuant and its search engine Andromeda was also employed for peptide identification and quantification . Data are available via ProteomeXchange with identifier PXD004906 Full length gpr-1 was PCR amplified from the ORFeome library ( kind gift from Marc Vidal ) using KOD polymerase ( Novagen ) and cloned into bait vector pPC97 . Fragments of lin-5 were PCR amplified from the ORFeome library with KOD polymerase ( Novagen ) and cloned into prey vector pPC86-AN [58] . DB::GPR-1- and AD::LIN-5-encoding plasmids were transformed sequentially into yeast strain Y8930 [58] . Positive interactions were identified on the basis of the activation of the HIS3 and ADE2 reporter genes , indicated by growth on synthetic complete –leucine −tryptophan −histidine + 2 mM 3-Amino-1 , 2 , 4-triazole ( Sc −leu−trp−his + 3-AT ) and synthetic complete –leucine −tryptophan −adenine ( Sc −leu−trp−ade ) plates . To generate mutant clones , PCR was performed on pVP054 ( pPC86-AN containing nucleotides 1821–2466 encoding amino acid 609–821 of lin-5 ) with increased MgCl2 concentration of 7 mM . PCR products were cloned into pPC86-AN and transformed to DH5α competent cells . Bacterial colonies were collected and the DNA was isolated using a Nucleobond Xtra DNA purification kit ( Macherey-Nagel ) . Bacterial clones were transformed into MB004 ( Y8930 in which ADE2 is replaced by URA3 by homologous recombination ) containing DB::GPR-1 and plated on synthetic complete –leucine −tryptophan + 2 g/l 5-fluoroacetic acid ( Sc −leu−trp + FOA ) . Colonies were picked and spotted to synthetic complete –leucine −tryptophan ( Sc −leu−trp ) plates for validation , PCR and sequencing . Clones with single amino acid changes were re-tested by PCR amplification of the fragment and re-cloning into pPC86-AN . Interaction deficient alleles were identified on the basis of no activation of the HIS3 or URA3 reporter gene , indicated by absence of growth on Sc −leu−trp−his + 3-AT plates and synthetic complete –leucine −tryptophan –uracil ( Sc −leu−trp−ura ) plates . For generation of full length mutant clones , plasmids containing fragment clones with selected point mutations were digested and cloned into pVP055 ( pPC86-AN containing nucleotides 1–2466 encoding amino acid 1–821 of lin-5 ) . Phosphomutants were generated by either site-directed mutagenesis of pVP055 or Gibson assembly into pVP055 of short regions of lin-5 with point mutations carried in the overlapping region . DB::GPR-1 and AD::LIN-5-encoding plasmids were transformed sequentially into yeast strain MB004 . Interaction deficient alleles were identified on the basis of no activation of the HIS3 or URA3 reporter gene , indicated by absence of growth on Sc −leu−trp−his + 3-AT plates and Sc −leu−trp−ura plates . CRISPR repair constructs were inserted into the pBSK vector using Gibson Assembly ( New England Biolabs ) . Homologous arms of at least 1500 bp upstream and downstream of the CRISPR/Cas9 cleavage site were amplified from either cosmid C03G3 ( for lin-5 constructs ) or C . elegans genomic DNA using KOD Polymerase ( Novagen ) . Linkers containing the altered cleavage sites and point mutations were synthesized ( Integrated DNA technologies ) . For fkbp::egfp::gpr-1 , codon-optimized fkbp was synthesized ( Integrated DNA technologies ) and codon-optimized egfp was amplified from pMA-egfp ( a kind gift from Anthony Hyman ) . For egfp::lin-5 , codon-optimized egfp was amplified from pMA-egfp . For mcherry::dhc-1 , codon-optimized mcherry was amplified from TH0563-PAZ-mCherry ( a kind gift from Anthony Hyman ) . Mismatches were introduced in the sgRNA target site to prevent cleavage of knockin alleles . All plasmids and primers used for cloning are available upon request . Young adults were injected with a solution containing the following injection mix: 30–50 ng/μl Peft-3::Cas9 ( Addgene 46168; [59] , 30–100 ng/μl u6::sgRNA with appropriate target for dhc-1 , gpr-1 and lin-5 , 30–50 ng/μl repair template and 2 . 5 ng/μl pmyo-2::tdTomato . Progeny of animals that express tdTomato were picked to new plates 3–4 days post injection . PCRs with primers diagnostic for homologous recombination at the endogenous locus were performed on F2-F3 populations , where one primer targeted the altered basepairs in the sgRNA site , point mutation or fluorescent tag and the other targeted a region just outside the homology arm . All primers used for genome editing are available upon request . For yeast protein lysates , cultures were grown overnight at 30°C . Yeast cells corresponding to 4 OD of culture were harvested , treated with Sodium hydroxide and resuspended in 100 2X sample buffer containing β-mercaptoethanol [60] . For C . elegans protein lysates , strains SV1569 , SV1663 and SV1664 were grown at 20°C one generation on NGM plates seeded with HB101 , followed by a second generation in S-Medium with HB101 bacteria . Gravid adults were harvested and embryos were isolated by hypochlorite treatment . Embryo pellets were snap frozen in liquid nitrogen , grinded using mortar and pestle and resuspended in 5 ml fresh lysis buffer ( containing 20 mM Tris-HCl pH 7 . 8 , 250 mM NaCl , 15% glycerol , 0 . 5% IGEPAL , 0 . 5 mM EDTA , 50 mM Sodium fluoride , 1 mM β-mercaptoethanol and protease inhibitors ( Roche complete , Mini , EDTA-free ) ) . The suspension was passed through a French press 3 times , and the lysate was cleared at 13 , 000 rpm for 15 min at 4°C . Protein samples were separated on gradient acrylamide gels and subjected to western blotting on polyvinylidene difluoride membrane ( Immobilon-P , Millipore ) . Membranes were blocked with 5% skim milk in PBST for 1 hour at room temperature , or overnight at 4°C for stripped blots . For protein detection , primary antibodies used in this study were: mouse anti–LIN-5 ( 1:1000 ) [19] and rabbit anti-Tubulin ( 1:1000 , Abcam ) for stripped blots . Secondary antibodies used were: donkey anti-mouse HRP ( 1:5000 , Abcam ) and goat anti-rabbit HRP ( 1:5000 , Jackson Immunoresearch ) . Proteins were dectected with Signalfire Plus chemiluminescent detection ( Cell Signaling Technologies ) and a Chemidoc MP Imager ( Bio-Rad ) . DIC time-lapse imaging was performed on strains N2 , SV1568 , SV1588 , SV1590 and SV1600 . Animals were grown overnight at 25°C . RNAi feeding of N2 against gsk-3 was performed with the bacterial clone from the Orfeome-based RNAi Library [61 , 62] . L4 animals were grown for approximately 32 hours at 15°C before shifting overnight to 25°C for imaging , except SV1901 which was kept at 20°C . Embryos were dissected from adults in a solution of 0 . 8x egg salt ( containing 94 mM NaCl , 32 mM KCl , 2 . 7 mM CaCl2 , 2 . 7 mM MgCl2 , 4 mM HEPES , pH 7 . 5; [63] ) on coverslips and mounted on slides with 3% agarose prepared with egg salt . Embryos were imaged with 5s time intervals with a 100x/1 . 4 NA lens on a Zeiss microscope at 20°C . Relative positions of the spindle and furrow were analyzed manually using ImageJ . Live-cell imaging of EMS rotation was performed on strains SV1783 , SV1784 and SV1785 . L4 animals were grown overnight at 20°C . Embryos were dissected from young adults as above and imaged with a 100x/1 . 4 NA lens on a Zeiss microscope at 20°C . Spindle rotation in EMS was followed over time with images taken at several time points . Live-cell imaging of microtubule depolymerization upon nocodazole treatment was performed on strain AZ244 . Young adult animals were injected with dsRNA [64] against perm-1 and grown for 20 hours at 15°C . Embryos were dissected from young adults in a solution of 0 . 8x egg salt containing 1 μM nocodazole on coverslips and mounted on concave slides . Embryos were imaged with a 60x/1 . 4 NA lens on a Nikon Eclipse Ti microscope with Perfect Focus System and Yokogawa CSU-X1-A1 spinning disk confocal head at room temperature . Live-cell imaging of mitotic DHC-1 localization was performed on strains SV1619 , SV1635 , SV1638 and SV1639 . Young adult animals were injected with dsRNA [64] against perm-1 and egfp and grown for 20 hours at 15°C . Embryos were dissected from young adults in a solution of 0 . 8x egg salt containing 1 μM nocodazole on coverslips and mounted on concave slides . Still images of mitotic embryos in metaphase were taken within minutes after nocodazole addition . Eliminating nonspecific toxic effects , embryos on the same slide at the same time continued nuclear envelope degradation , and perm-1 ( RNAi ) embryos continued embryonic development in the absence of nocodazole . Embryos were imaged with a 60x/1 . 4 NA lens on a Nikon Eclipse Ti microscope with Perfect Focus System and Yokogawa CSU-X1-A1 spinning disk confocal head at room temperature . mCherry::DHC-1 localization was analyzed in mitotic one-cell embryos after nuclear envelope breakdown . Mitotic embryos were also identified based on presence of a polar body , enlarged centrosomes and remnant of the mitotic spindle . Live-cell imaging of meiotic DHC-1 localization was performed on strains SV1702 , SV1898 , SV1899 and SV1902 . For RNAi treated animals , young adult animals were injected with dsRNA [64] against egfp and grown for 24 hours at 15°C . Embryos were dissected from young adults as above and imaged with 10s time intervals with a 100x/1 . 4 NA lens on a Zeiss microscope at 20°C . For images presented in Fig 7B and S12 , S15 , S18 and S21 Videos , images were processed by subtracting a Gaussian-blur filtered image ( Sigma ( Radius ) : 20 ) using ImageJ . S10 , S11 , S13 , S14 , S16 , S17 , S19 and S20 Videos represent the unprocessed files . Spindle severing with a UV laser microbeam was performed on strains SV1585 , SV1594 , SV1596 , SV1618 , SV1700 and SV1701 essentially as previously described [13] . RNAi feeding of SV1700 and SV1701 against egfp was performed with a bacterial clone containing full length egfp in the L4440 double T7 plasmid [61] . L4 animals were grown on RNAi for approximately 48 hours . For analysis of spindle pulling forces , animals were kept at 25°C for 24 h before ablations . Spindle ablations were carried out at 25°C ( Fig 4D ) or 20°C ( Fig 4E ) on a spinning disk confocal microscope . The spindle midzones were severed at anaphase onset and images of GFP-β-tubulin were taken at 0 . 5 s intervals . For analysis , the position of the spindle poles was automatically tracked using the MTrack2 plugin in ImageJ . Peak velocities of the anterior and posterior spindle poles were determined within a 12 . 5 s time frame after ablation . Representative videos for every strains are shown in S2–S9 Videos . Microscope setup: Nikon Eclipse Ti microscope with Perfect Focus System , Yokogawa CSU-X1-A1 spinning disk confocal head , S Fluor 100x N . A . 0 . 5–1 . 3 objective ( at 1 . 3 ) , Photometrics Evolve 512 EMCCD camera , Cobolt Calypso 491 nm ( 100 mW ) and Teem Photonics 355 nm Q-switched pulsed lasers , ILas system ( Roper Scientific France/ PICT-IBiSA , Institut Curie ) to control the UV laser , ET-GFP ( 49002 ) filter , ASI motorized stage MS-2000-XYZ with Piezo Top Plate with Tokai Hit INUBG2E-ZILCS Stage Top Incubator ( controlled at 25°C ) , controlled by MetaMorph 7 . 7 software . For immunostaining , embryos were dissected from adults in 8 μl of water on poly-L-lysine–coated slides . Embryos were freeze-cracked and fixed for 5 min in methanol at −20°C and then for 20 min in acetone at −20°C . After fixation , embryos were rehydrated in phosphate-buffered saline ( PBS ) containing 0 . 05% Tween-20 ( PBST ) and blocked with blocking solution ( PBST containing 1% bovine serum albumin and 1% goat serum [Sigma-Aldrich] ) for 1 h . Embryos were stained with primary and secondary antibodies for 1 h and washed after each incubation with PBST four times , 15 min each time . Finally , the embryos were embedded in ProLong Gold Antifade containing 4′ , 6-diamidino-2-phenylindole ( DAPI ) . Primary antibodies used in this study were: mouse anti–LIN-5 ( 1:10; [19] and rabbit anti-GFP ( 1:500 , Life Technologies ) . Secondary antibodies were used at a concentration of 1:500 . Secondary antibodies used were: goat anti-rabbit Alexa Fluor 488 , and goat anti-mouse Alexa Fluor 568 ( Invitrogen ) . Images were taken with a 63x/1 . 4 NA lens on a Zeiss confocal microscope . Embryos were dissected and stained with antibodies as described above . Images were taken with a 63x/1 . 4 NA lens on a Zeiss confocal microscope using identical microscope setting for all images taken for every secondary antibody . Mean intensity of LIN-5 was measured using ImageJ by selecting fixed size regions that depended on the developmental stage . For every embryo 2 centrosomes and cytoplasmic regions were quantified . | Protein kinases control biological processes by phosphorylating specific amino acids of substrate proteins . It remains a major challenge to identify which phosphorylation events are critical in vivo and how phosphorylation affects protein function . Recent developments in CRISPR/Cas9-based genetic engineering make it possible to substitute individual amino acids , which allows investigating the role of single and multi-site phosphorylation of substrates in vivo . Here , we focus on an intensively phosphorylated cell division protein , LIN-5NuMA . C . elegans LIN-5 participates in chromosome segregation and is essential for positioning the spindle and cell cleavage plane during asymmetric cell division . Previously , we demonstrated that the polarity kinase PKC-3 phosphorylates LIN-5 to inhibit its function . Our current analysis reveals four additional phosphorylated residues that are critical for LIN-5 function . Two of these residues contribute to the interaction of LIN-5 with its binding partner GPR-1/2 , whereas the other two residues are critical in dynein motor recruitment by LIN-5 . Together , our results reveal that multisite phosphorylation of LIN-5 is essential to ensure proper chromosome segregation and spindle positioning . | [
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"biolo... | 2016 | Multisite Phosphorylation of NuMA-Related LIN-5 Controls Mitotic Spindle Positioning in C. elegans |
Telomeres are nucleoprotein structures located at the linear ends of eukaryotic chromosomes . Telomere integrity is required for cell proliferation and survival . Although the vast majority of eukaryotic species use telomerase as a primary means for telomere maintenance , a few species can use recombination or retrotransposon-mediated maintenance pathways . Since Saccharomyces cerevisiae can use both telomerase and recombination to replicate telomeres , budding yeast provides a useful system with which to examine the evolutionary advantages of telomerase and recombination in preserving an organism or cell under natural selection . In this study , we examined the life span in telomerase-null , post-senescent type II survivors that have employed homologous recombination to replicate their telomeres . Type II recombination survivors stably maintained chromosomal integrity but exhibited a significantly reduced replicative life span . Normal patterns of cell morphology at the end of a replicative life span and aging-dependent sterility were observed in telomerase-null type II survivors , suggesting the type II survivors aged prematurely in a manner that is phenotypically consistent with that of wild-type senescent cells . The shortened life span of type II survivors was extended by calorie restriction or TOR1 deletion , but not by Fob1p inactivation or Sir2p over-expression . Intriguingly , rDNA recombination was decreased in type II survivors , indicating that the premature aging of type II survivors was not caused by an increase in extra-chromosomal rDNA circle accumulation . Reintroduction of telomerase activity immediately restored the replicative life span of type II survivors despite their heterogeneous telomeres . These results suggest that telomere recombination accelerates cellular aging in telomerase-null type II survivors and that telomerase is likely a superior telomere maintenance pathway in sustaining yeast replicative life span .
Telomeres are the physical ends of linear eukaryotic chromosomes and are composed of specific repetitive DNA sequences and binding proteins [1] , [2] . The functional integrity of telomeres is required for cell proliferation and survival because they protect chromosome ends from nucleolytic degradation and help to distinguish normal chromosome ends from DNA double-strand breaks [3]–[5] . Additionally , telomeres can compensate for the incomplete replication of chromosomal DNA by conventional DNA polymerases [6] , [7] . In eukaryotes , telomeres can be maintained by three different mechanisms , namely a telomerase-dependent pathway , a recombination pathway and a retrotransposon-mediated transposition pathway [8] , [9] . Telomerase-dependent telomere replication has been documented in the vast majority of eukaryotic species including in budding yeast and humans . In these species , repetitive telomeric DNA is added to the chromosome ends by telomerase , a specialized reverse transcriptase that catalyzes the addition of telomeric DNA using its intrinsic RNA template [10] , [11] . Recombination-dependent telomere maintenance has been reported in a few organisms that naturally lack telomerase , including the lower dipterans Chironomus and Anopheles and the plant Allium spp [12]–[14] . Retrotransposon-mediated telomere maintenance has been well adapted by the fruit fly Drosophila melanogaster [15]–[18] . The wider use of telomerase in eukaryotes suggests that it has been evolutionarily selected for as an advantageous mechanism for maintaining telomere integrity and stability , however , the reasons why telomerase has been adopted by so many eukaryotic species are not clear . Interestingly , some organisms are likely capable of using both telomerase and recombination to replicate their telomeres . For example , previous studies have reported that 85% of the human cancer cells are telomerase positive , however the other 15% cancer cells are telomerase negative [19] and maintain their telomeres by recombination pathway , also termed alternative lengthening of telomeres ( ALT ) [20] . In the budding yeast Saccharomyces cerevisiae , a RAD52-dependent homologous recombination pathway can be employed by a minority of telomerase-negative cells as an alternative method for telomere maintenance . These cells are called post-senescent survivors . Two types of post-senescent survivors exist and are distinguishable by their characteristic telomere patterns . Type I survivors exhibit amplification of Y' elements and have very short TG1–3 repetitive tracts on the chromosome ends [21] . Type II survivors show a variable pattern of long tracts of TG1–3 repeats and only modest Y' amplification [22] . Because type II survivors have long and heterogeneous telomeric repeats , and their telomere maintenance requires both RAD50 and RAD52 , they resemble human ALT cells [20] , [23]–[25] . In budding yeast , telomerase seems to be the preferential telomere-elongation pathway . Introduction of the telomerase component EST1 back into an est1Δ type I survivor that exhibits extensive Y' amplification results in the elongation of the terminal telomeric tract back to wild-type length , as well as a substantial reduction in Y' copy number [21] , [22] . Similarly , following reintroduction of telomerase into a type II survivor , telomeres gradually return to a wild-type telomeric structure that can be confirmed by examining telomeric restriction patterns via Southern blotting [22] . To investigate whether recombination is inferior to telomerase in preserving an organism or cell under natural selection , we compared cellular traits in telomerase-null post-senescent type II survivor cells to cellular traits in telomerase positive cells . Type I recombination survivors were not included in this report because they have a severe growth defect and highly abnormal karyotypes [21] , [26] . In this report we demonstrate that recombination was as efficient as telomerase in maintaining cell survival and overall genome stability , but telomerase-null cells using recombination-only maintenance of telomeres had a shortened replicative life span ( RLS ) when compared to telomerase-positive cells . In yeast , RLS is defined as the total number of daughter cells generated by a mother cell before cell death [27] . RLS was significantly reduced in type II survivors . The decline in RLS was not due to a defect in the canonical aging regulation pathways and the reintroduction of telomerase activity immediately restored the RLS of type II survivors to that of a wild type cell . Our results provide experimental evidence supporting the notion that telomerase is superior to telomere recombination in the regulation of yeast replicative life span .
To determine whether the recombination pathway is as efficient as the telomerase pathway in maintaining cell survival , we mated either type II survivors ( ALT II pathway in humans ) or telomerase-proficient cells ( TERT pathway in humans ) with yeast cells whose telomerase was recently inactivated ( pre-survivors , SEN ) ( Figure 1A ) . The viability of the resulting diploids was examined . Diploids generated by crossing two SEN populations senesced and underwent crisis ( Figure 1A , sectors 3 and 4 ) . In contrast , diploids generated by crossing a type II survivor with a SEN ( Figure 1A , sectors 5 and 6 ) grew as vigorously as the diploids created by mating a TERT with a SEN ( Figure 1A , sectors 1 and 2 ) . These data are consistent with previous reports [28] and suggest that telomere maintenance by recombination is as efficient as telomere maintenance by telomerase in maintaining cell survival . Genome integrity is maintained in telomerase-proficient cells because telomeres are not recognized as DNA double-strand breaks [3] . To ascertain if genome stability was altered in telomerase-negative type II survivors , we carried out several phenotypic analyses and compared our results to those obtained from telomerase-positive ( wild-type ) cells . First , we determined that type II survivor cells grew as robustly as the wild-type cells ( Figure 1B ) [22] . Second , we found that type II survivors exhibited similar levels of sensitivity to four separate DNA damage-inducing agents when compared to wild-type cells ( Figure 1B ) . Third , telomere position effect ( TPE ) , a silencing mechanism combining telomere architecture and classical heterochromatin features , was slightly enhanced in type II survivor cells , indicating that the heterochromatic state of telomeres has not been damaged ( Figure 1C ) . This observation was consistent with previous reports where increasing the length of telomeres was found to enhance TPE [29]–[31] . Fourth , normal telomere positioning at the nuclear periphery was maintained in type II survivors , as shown by immunostaining of the telomeric repeat binding protein Rap1p ( Figure 1D ) . Fifth , pulsed-field gel electrophoresis revealed that haploid type II survivors contained linear chromosomes that were indistinguishable from wild-type cells ( Figure 1E ) . Finally , the gross-chromosomal rearrangement ( GCR ) analyses showed that the type II survivors had a very low GCR rate , in contrast with the rad50Δ mutants that displayed a significant increase of GCR events ( Figure 1F ) . This behavior of the type II survivors was similar to that seen in wild-type cells as previously reported ( Figure 1F ) [32] . These results suggested that the elevated recombination at type II survivor telomeres has not caused any noticeable defects in DNA replication or repair , and the chromosomes of the type II survivors are stably maintained . A link between an increase of repetitive rDNA recombination and cellular aging has been well established in S . cerevisiae [33] . With the activation of homologous recombination at telomeric repeats , the type II survivor cells showed more heterogeneous lengths of telomeric TG1–3 tracts and modest Y' telomere amplification ( Figure 2A ) [22] . Conversely , DNA instability was not observed in another part of the genome when gross chromosomal rearrangements were examined in type II survivors ( Figure 1F ) . This discontinuity of results led us to wonder if the replicative capacity of the type II survivors was comparable to that of telomerase-positive cells . A population of budding yeast cells , can be grown indefinitely in culture under optimal conditions using either telomerase or recombination for telomere maintenance ( Figure 1A ) [21] , [22] . However , the replicative capacity of a single yeast cell is finite . This is because of the activity of other functional aging pathways , and this finite life span holds true whether the telomeres are maintained by telomerase or by recombination throughout the life span [33] , [34] . Since yeast cells reproduce by asymmetric cell division with a larger mother cell giving rise to a smaller daughter cell , the two cells can be separated right after each cell division by micromanipulation . The number of daughter cells that a mother cell can produce before senescence defines the replicative life span of that cell . The average number of cell divisions undergone by a group of mother cells defines the mean replicative life span of a yeast strain [27] , [35] . A young cell will become mother cell after production of its first daughter . Replicative life span ( RLS ) analysis showed that the mean life span of the type II survivors was 15 . 3 generations , which was much shorter than 27 . 8 generations of wild-type cells ( Figure 2A ) . Apparently , the reduction in the replicative capacity of type II survivors was neither mating-type nor strain-specific ( Figure S1A , S1B ) . Consistently , the type II survivor cells derived from deletion of the telomerase subunit EST3 also showed significantly decreased life span ( Figure S1C ) . Previous studies showed that , type II survivors are stable over time , but their telomeres experience a cycle of continuous shortening and abrupt elongation during the outgrowth ( Figure 2B ) [22] . To determine whether the accelerated cellular senescence persists during the outgrowth , we analyzed the life span of the 1st- , 10th- , and 25th-restreaked type II survivors . All these survivors exhibited significantly reduced life span , despite the changes in telomere length ( Figure 2B ) . Thus , for the first time , a severely reduced life span was observed in the telomerase-null type II survivors . As previously reported , critically short telomere ( s ) cause telomerase-deficient cells to abruptly cease cell division , and senesce at the G2/M checkpoint ( Figure S2 ) [36] . To determine whether the accelerated senescence of type II survivors was caused by critically short telomere ( s ) , the morphology of cells at the end of their life span was indexed according to a previously established method where the fraction of unbudded , small-budded , and large-budded cells is determined [37] . In our experiments , the large-budded proportion of old type II cells was comparable to that of old wild-type cells ( Figure 2C ) , suggesting that type II survivors may age by a process that is independent of critically-short-telomeres . Long telomeres have also been proposed to affect replicative life span . For example , rif1Δ cells have much longer telomeres than wild-type cells and their replicative life span is reduced [38] . These data with rif1Δ cells led to the generation of a hypothesis that long telomeres may reduce life span by competing for Sir silencing factors with the non-telomeric loci [38] , [39] . Because the telomerase-null type II survivors possess long and heterogeneous telomeres , it is possible that long telomeres per se in these cells result in the life span decline . To test this possibility , yeast cells that harbored long telomeres by temporarily over-expressing telomerase were subject to a life span assay . Results show that these cells had regular life span ( Figure 2E ) , indicating that long telomeres per se may not be the direct cause of the shorter life span we saw in the type II survivors . To confirm that the telomerase-null type II survivors died of replicative aging but not general sickness , we examined age-dependent sterility in type II survivors . Sterility due to loss of silencing at HMLα and HMRa loci has been reported as an aging-specific phenotype in budding yeast [40] , [41] . We determined the percentage of sterile cells as cells aged by documenting the inability of cells to respond to a mating pheromone , α factor . Similar to the wild-type cells , type II survivors became sterile at a higher frequency the older they got ( Figure 2D ) . Together , the data from all the phenotypic assays in the section led us to conclude that telomerase-null type II survivors aged prematurely in a manner that was phenotypically indistinguishable from that of telomerase-positive wild-type cells . Calorie restriction ( CR ) is an intervention which slows the aging process and increases life span in many organisms [42] . In yeast , CR can be executed by reducing the glucose concentration of growth media from 2% to 0 . 5% ( or 0 . 05% ) , resulting in a significant increase of life span ( Figure 3A ) [43] , [44] . Life span extension by CR in yeast involves at least three nutrient-responsive kinases: TOR ( target of rapamycin ) , Sch9 , and protein kinase A ( PKA ) [43] , [45]–[47] . To better understand life span regulation in type II survivor cells , we examined whether these canonical aging pathways function in type II survivors . Although type II survivors exhibited accelerated replicative aging , CR ( in 0 . 05% glucose ) significantly extended the survivors' life span from 12 . 6 to 16 . 7 generations ( Figure 3A ) . The deletion of TOR1 also significantly extended the mean and maximum life span of type II survivors ( Figure 3B ) . Subsequently , we found that the inactivation of Tor1 affected neither the senescence nor survivor-arising rate of est2Δ cells ( Figure S3 ) . In addition , tor1Δ type II survivors exhibited shorter life span than that of tor1Δ telomerase-positive cells ( Figure 3B ) . Based on these data , we propose that TOR1 regulates the replicative life span of type II survivors independently of telomere recombination . The extension of life span by either calorie restriction or Tor1 deletion further indicated that type II survivors are not simply sick cells . In every way we examined them phenotypically , type II survivors seemed to resemble wild-type cells with the exception that their telomeres were elongated through telomere-telomere recombination and not telomerase ( Figure 2A ) . Because telomerase has been suggested to play a role in capping of telomeres and facilitating cell proliferation [48] , there is a possibility that the lack of telomerase capping provides an essential senescence signal . Alternatively , the increased telomere recombination per se in telomerase-null survivors induced chromosomal instability at telomere and this may be the cause of the decreased life span . To distinguish between these two possibilities , we examined the RLS of telomerase-deficient pre-survivors . Heterozygous yeast diploid cells with a single EST2 deletion were dissected and subjected to serial restreaking on YPD plates every 48 hours . Both the spores taken immediately from the tetrad dissection and the cells that were grown on YPD plates for 48 hours had wild-type life span ( Figure 4A and 4B ) . Decreased RLS was only observed in telomerase-null pre-survivors during the later serial restreaks when there was severe loss of telomeric DNA ( Figure 4C ) . Reintroduction of telomerase restored the low RLS of pre-survivors by elongation of short telomeres , suggesting that the short RLS of late passages was caused by critically short telomere ( s ) ( Figure 4C ) . Together , these data supported a model where the absence of Est2p did not directly cause a reduction in replicative capacity and the shorter life span of type II survivors was not caused by the lack of telomerase capping . The observation of loss-of-productivity in late passages of telomerase-null pre-survivors mirrors what is known to happen to est2Δ cells on serial streak-outs ( Figure 1A ) , or in liquid-growing culture ( Figure S2A ) [36] , [49] . Mother cells exhibited the same rate of cell viability reduction as the logarithmically growing cells , the vast majority of which are young cells , suggesting that the older mother cells and younger cells do not have appreciable difference in their ability to maintain telomeres in the absence of telomerase . In budding yeast , telomerase appears to be the preferred pathway for telomere maintenance [21] , [22] . To examine whether reintroducing telomerase activity in survivors may inhibit telomere recombination and rescue the short RLS , we performed a mating assay in which est2Δ type II survivor cells ( MATα ) were mated with wild-type cells ( MATa ) . The telomerase-positive diploids ( named “survivor diploids” ) had a heterogeneous telomere-length ( Figure 5A ) . However , they possessed similar replicative capacity to the wild-type diploids ( Figure 5A ) , indicating that telomerase is dominant over recombination in regulating cellular life span , and further suggesting that heterogeneous long-telomeres are not the cause of premature aging . The diploid cells in this background ( BY4743 ) lived significantly longer than haploid cells , and this phenomenon was also observed by Kaeberlein et al . [50] . Next , both the telomerase-negative and positive haploid cells were obtained by tetrad dissection from the “survivor diploids” . Interestingly , all the spores had long heterogeneous telomeres but possessed the same replicative capacity as the wild-type haploids ( Figure 5B ) . These results are supportive of the following conclusions: ( i ) reintroduction of telomerase activity is able to extend the short RLS of type II survivors; ( ii ) the reduced replicative capacity of telomerase-null type II survivors resulted from telomere alteration; ( iii ) lack of telomerase capping does not cause a decline of replicative capacity , consistent with the results shown in Figure 4; ( iv ) long telomeres per se do not affect cellular life span , consistent with our previous results shown in Figure 2E; ( v ) telomerase may restore RLS by inhibiting telomere recombination rather than regulating telomere length . To further verify the idea that reintroducing telomerase activity into survivors may inhibit telomere recombination and rescue the cellular life span , we reintroduced EST2 into the type II survivors which were originally derived from cells with an EST2 deletion . Reintroduction of telomerase activity caused a gradual shortening of very long telomeres in type II survivors , and eventually recovered the wild-type telomere pattern ( after ∼25 restreaks , see middle panels of Figure 6A and 6B ) . These data suggested that when compared to recombination , telomerase was the preferred mechanism for telomere maintenance and the presence of telomerase suppressed telomere-telomere recombination [22] . Consistent with the results of our mating assay ( Figure 5 ) , the RLS of type II survivors was restored immediately after the reintroduction of EST2 in spite of the long telomeres ( Figure 6C ) . Accordingly , a plasmid-borne EST3 restored the life span of est3Δ type II survivors immediately after being transformed ( Figure 6D ) . Reintroduction of a catalytically inactive est2 ( DD670-1AA ) into est2Δ type II survivors , on the other hand , failed to restore either the telomere length or the typical life span ( Figure 6 ) . These observations suggested that functional telomerase is required for the life span restoration in type II survivors . In budding yeast , a change of rDNA recombination rate causes reciprocal changes in the cellular life span . For example , elimination of the replication block protein FOB1 or over-expression of SIR2 significantly extended cellular life spans by reducing rDNA recombination , whereas the deletion of SIR2 had the opposite effect [51]–[53] . In the telomerase-null type II survivors , recombination was presumably activated at the telomere loci . We wondered whether increased telomere recombination affected the stability of rDNA loci . A marker loss assay was performed as described previously [54] to analyze the rDNA recombination rate in type II survivors . Interestingly , the rDNA recombination rate in type II survivors was 3-fold lower than that observed in wild-type cells ( Figure 7A ) , thereby suggesting that extra-chromosomal rDNA circles ( ERCs ) do not contribute to the acceleration of aging process in type II survivors . Like in wild-type cells , deletion of SIR2 in type II survivors led to a decline of life span from 14 . 6 to 8 . 6 generations ( Figure 7B ) . Unexpectedly , neither the deletion of FOB1 nor introduction of an extra-copy of SIR2 into type II survivors could extend their life span ( Figure 7C and 7D ) . Double deletion of FOB1 and SIR2 did not affect the life span of wild-type cells [53] , whereas combined deletion of FOB1 and SIR2 reduced the life span of type II survivors ( Figure 7E ) . We were unable to determine why FOB1 deletion or Sir2 over-expression did not positively influence the RLS of type II survivors . It is possible that the increased telomere recombination sequestered recombination factors and caused a reduction in rDNA recombination ( Figure 7A ) . Thus , either FOB1 deletion or Sir2 over-expression could no longer reduce rDNA recombination levels that were already lower .
In this study , we reported that telomerase-null type II survivors , which employ homologous recombination to efficiently maintain telomeres , exhibited normal chromosomal stability in an assay that measures gross chromosomal rearrangement rates , but accelerated cellular senescence . The reduced replicative life span of type II cells could be extended by either calorie restriction or inactivation of the TOR pathway , but not by FOB1 deletion or SIR2 over-expression . Reintroduction of telomerase restored the life span of type II survivors to wild-type level , indicating the superiority of telomerase over homologous recombination in guaranteeing full replicative potential . In most eukaryotic species studied so far , telomere replication involves either telomerase or a recombination pathway [9] . Stable maintenance of telomeres is required for cell proliferation , survival and preservation of a species [55] . Reactivation of telomerase or telomere-recombination is associated with immortalization of mammalian cells grown in tissue culture , including human cells [19] , [56] . Similarly , the budding yeast S . cerevisiae , can be grown indefinitely in culture under optimal conditions with either telomerase or telomere-recombination activated for telomere maintenance ( Figure 1A ) [21] , [22] . However , for a single yeast cell , its replicative capacity is finite due to the activity of other aging pathways regardless of how telomeres are maintained throughout the life span [33] , [34] . Surprisingly , we found that the budding yeast type II survivor cells , which have adopted homologous recombination to replicate their telomeres , possessed shorter replicative life span ( Figure 2 and Figure S1 ) . Type II survivor cells differ from wild-type cells by the nature of their repetitive telomeric DNA sequences , the physiological challenges they may face , the length of their heterogeneous telomeres , the absence of telomerase capping , the heterochromatin structure at these telomeres , and the telomere recombination status . Since each of these differences alone or a combination of these differences may be responsible for the shortened RLS in type II survivors , we examined further the contributions of these differences in the premature senescence phenotype . Compared to wild-type cells , the type II survivors did not exhibit altered sensitivity to various DNA damage-inducing reagents ( Figure 1B ) . Additionally , they did not show an increase in the rate of gross chromosomal rearrangement events ( Figure 1F ) . Consistent with the genetic assay , type II survivor cells and wild-type cells displayed identical chromosomal banding patterns when compared using pulsed-filed gel electrophoresis ( Figure 1E ) . Moreover , telomere silencing was slightly enhanced in type II survivors ( Figure 1C ) , and the telomere clustering at the nuclear periphery remained similar to the wild-type cells ( Figure 1D ) . These results indicate that the type II survivors are phenotypically healthy , instead of generally “sick” cells . When examining cell morphology at the end of the life span , type II survivor cells showed similar fractions of cells that were large-budded and small-budded when compared to wild-type cells at the same stage of life span ( Figure 2C ) . In addition , the type II survivors exhibited the aging-associated sterility in a manner that was nearly identical to that of wild type cells ( Figure 2D ) . These observations on one hand raise the argument that the type II cells are premature aging instead of premature death , and on the other hand challenge the idea that the life span reduction of type II survivors is due to their critically short telomere ( s ) which could cause more cells to senesce at G2/M phase ( Figure S2 ) . Additionally , the life span of type II survivors was extended by calorie restriction or inactivation of the TOR1 pathway ( Figure 3 ) , and reduced by SIR2 deletion ( Figure 7B ) , further supporting the argument that the type II survivors age prematurely . Since telomerase has been shown to play a capping function in maintaining telomere integrity [48] , it remains unclear how telomere capping is maintained in the type II survivors . In the telomerase deficient pre-survivors with a moderate loss of telomeric DNA , the defect of telomerase capping due to lack of Est2p did not detectably affect the replicative capacity ( Figure 4A and 4B ) . Consistent with those data , the telomerase-null cells newly derived from EST2/est2 hybrids ( crosses between type II survivors and wild-type haploids ) have a comparable life span to the telomerase proficient cells regardless of the length of their heterogeneous telomeres ( Figure 5B ) . Thus , the life span reduction in telomerase-null type II survivors did not appear to be a consequence of a loss of telomerase capping by Est2p . Recent studies on the role of telomere length in aging have expanded from the cellular level to the anatomical/organismal level . Telomerase-deficient mice with critically short telomeres exhibit decreased viability associated with diminished proliferative capacity of B and T cells [57]–[59] . However , when telomere length is kept above the critically short length , the relationship between telomere length and life span seems to be controversial . In nematode Caenorhabditis elegans , Joeng et al . showed that worms with longer telomeres live longer [60]; whereas Raices et al . demonstrated that telomere length contributed little to the normal aging process [61] . In Drosophila melanogaster , longer telomeres were found to have no effect on the life span of the adult flies [62] . In the yeast rif1Δ cells , long telomeres were proposed to contribute to accelerated cellular senescence by titrating away limiting pools of Sir silencing factors from non-telomeric silenced loci [38] , [39] . Several lines of evidence presented in our current study do not support the hypothesis that longer telomeres alone contribute to a shortened life span in yeast . For example , the yeast cells that harbored long telomeres by temporarily over-expressing telomerase exhibited wild-type life span ( Figure 2E ) . Additionally , the hybrid diploid cells obtained from mating wild-type and type II haploids had full replicative capacity in spite of heterogeneous long telomeres ( Figure 5A ) . Moreover , reintroduction of telomerase slowly restored the telomere-length homogeneity , but immediately restored the life span ( Figure 6 ) . Finally , over-expression of the essential silencing factor Sir2p had no effect on the replicative life span of type II survivors ( Figure 7D ) . These results indicate that long-telomere length per se in the type II survivors is not associated with the accelerated cellular aging we observed . Most likely , type II survivors aged prematurely in a telomere-length independent manner . The results presented in our current work are different from the ones reported previously [38] , where rif1Δ or tlc1 mutants were exploited to characterize the relationship between telomere length and life span . In our experiments ( Figure 2E , Figure 5 , and Figure 6 ) , no parameters other than telomere length have been changed , and this might help to explain the discrepancy of our results and those reported previously [38] . In contrast to the controversial role of telomere length in longevity determination , loss of genome integrity is generally believed to contribute to the finite life span of organisms from yeast to humans [63] . A causal link between repetitive DNA instability and aging has been previously established in S . cerevisiae . The rate of aging in mother cells is dictated by the stability of the rDNA , which is present in 100–150 tandem arrays of 9 . 1-kb repeats [33] , [64] , [65] . During the aging of mother cells , extra-chromosomal rDNA circles ( ERCs ) are formed by homologous recombination between rDNA repeats . Importantly , ERCs are self-replicating via an origin in the rDNA repeat-unit during subsequent cell cycles and they display biased segregation to mother cells due to a lack of CEN element [66] . Thus , ERCs accumulate with the aging of mother cell in a Septin- and Bud6-dependent manner , and likely contribute to cellular senescence once a threshold level is reached [67] , [68] . In type II survivors , rDNA recombination was decreased compared to the wild-type cells ( Figure 7A ) . So it is unlikely that the ERCs contributed to the acceleration of the aging process in type II survivors , and it is likely that other aging pathway ( s ) dominated the aging process . Accordingly , SIR2-overexpression or FOB1-deletion did not extend RLS in type II survivors because the ERC pathway was recessive in the aging process of these cells . However , SIR2-deletion should still further shorten RLS because it makes the ERC pathway dominant again . As telomeres are arranged in TG-rich repeats , we could not rule out the possibility that telomere circles might affect cellular life span in the same way as rDNA circles . However , qualitative and quantitative determination of telomeric DNA-containing rings shows that telomere circles exclusively exist during the time when survivors are being generated , but not after survivors are established [69] . In addition , telomere repeats do not contain self-replicating origin elements . It's unlikely that telomere circles would accumulate during the aging process of survivors . Given that the recombination has been increased at telomeric loci in type II cells in a manner similar to that of rDNA recombination in aging cells [70] , telomere recombination may titrate away vital transcription and/or replication factors that play a role in preventing cellular senescence . Accordingly , we did observe significantly reduced rDNA recombination in telomerase-null type II survivors ( Figure 7A ) . However , we could not detect any DNA replication or repair defect on the general chromosome loci as shown by several lines of evidence . The telomerase-null type II survivors did not exhibit altered sensitivity to various DNA damage-inducing reagents when compared to wild-type cells ( Figure 1B ) , thereby indicating there was no obvious DNA replication or repair defect on the general chromosome loci . In addition , the gross-chromosomal rearrangement ( GCR ) rate was not increased in type II survivors as previously reported ( Figure 1F ) [32] . Moreover , the chromosomal banding pattern of type II survivors was comparable to the wild-type cells as displayed by pulsed-field gel electrophoresis ( Figure 1E ) . At this point , we could not explain why telomeres preferentially competed with the rDNA loci for recombination . One possibility is that our assays ( Figure 1 ) are not sensitive enough to detect any replication or repair defect on the general chromosome loci . Alternatively , both telomeric and ribosomal DNAs are favorable substrates for certain factor ( s ) , such as Sir2p binding , and an increase of recombination in either one would affect the rate of recombination at the other . However , SIR2 over-expression , which might compensate for the decrease of Sir2p at rDNA loci , did not extend the replicative life span of type II survivors ( Figure 7D ) , thereby leading us to propose that at least Sir2p is not the factor that might be involved in regulating the relative recombination rates at both telomeres and the rDNA . The shorter life span of the pre-survivors , which was potentially caused by severe telomere loss , could be rescued by reintroduction of telomerase , presumably due to recovery of telomere length by telomerase ( Figure 4C ) . Interestingly , reintroduction of telomerase immediately restored the short life span of telomerase-null type II survivors despite insignificant changes in telomere length ( Figure 5 and Figure 6 ) , implying that a distinct mechanism is engaged in the life span regulation upon reactivation of telomerase . Reintroduction of telomerase activity caused a gradual shortening of very long telomeres in type II survivors and eventually re-established the wild-type telomere Southern blotting banding pattern ( Figure 6A and 6B , middle panels ) as previously reported [22] . This observation suggested that the presence of telomerase somehow suppressed telomere-telomere recombination . Catalytically inactive telomerase failed to inhibit telomere recombination as reflected by the continuous presence of heterogeneous telomere pattern ( Figure 6A and 6B , right panels ) , thus , it could not recovery the replicative life span of type II survivors ( Figure 6C ) . We therefore propose a model where telomere recombination leads to accelerated cellular aging in telomerase-null survivors and functional telomerase rescues the replicative life span of type II survivors by inhibiting telomere recombination . In conclusion , telomerase has evolved to be as a superior mechanism to telomere recombination in regulating cellular life span . Telomerase likely plays a duel role in regulating life span . It helps maintain the telomeres above the critically short length necessary to reach full replicative potential , while also inhibiting the telomeric recombination that otherwise leads to a decline of cellular replicative capacity .
Unless otherwise noted , all yeast strains used in this study were BY4742 ( MATα his3Δ1 leu2Δ0 lys2Δ0 ura3Δ0 ) , BY4741 ( MATa his3Δ1 leu2Δ0 met15Δ0 ura3Δ0 ) , BY4743 ( MATα/MATa his3Δ1/his3Δ1 leu2Δ0/leu2Δ0 lys2Δ0/+ met15Δ0/+ ura3Δ0/ura3Δ0 ) , and their derivatives . All strains were grown at 30°C and on YPD ( 10 g/L yeast extract , 20 g/L peptone , 2% dextrose ) unless otherwise stated . tor1Δ , sir2Δ and fob1Δ strains were from EUROSCARF consortium . est2Δ was a deletion of the EST2 open reading frame using a pRS303 plasmid which contained 800 bp homologous sequences to up- and down-stream of EST2 ORF . The same method was used for the deletion of the open reading frame of EST3 . sir2Δ fob1Δ mutants were obtained by deletion of the SIR2 ORF in the fob1Δ strain . All gene disruptions were verified by PCR . Strains over-expressing Sir2p were constructed by genomic integration of an extra-copy of SIR2 . Integration of SIR2 at LEU2 locus was accomplished by transforming cells with Hpa I digested plasmid pRS305-SIR2 . In addition to the entire coding region of SIR2 , 800 nucleotides of up-stream and down-stream sequence were included . Plasmid pRS305-SIR2 was constructed by ligation of the PCR-amplified products into the BamH I and Sal I sites of pRS305 . The pRS316-EST3 centromere plasmid was constructed as described [71] . The pRS316-EST2 centromere plasmid was a gift from Dr . Yasumasa Tsukamoto . The pRS316-est2 ( DD670-1AA ) was constructed using site-directed mutagenesis method . Replicative life span assay of yeast cells was performed as described previously [72] , [73] . Prior to analysis , strains were patched onto fresh solid medium and grown for 2 days at 30°C . Single colonies were then arrayed onto standard YPD plates using a micro-manipulator and allowed to grow for about 3 hours . Virgin daughter cells were isolated as buds from mother cells and subject to life span analysis . During life span experiments , plates were incubated at 30°C during the daytime and stored overnight ( ∼8 hr ) at 4°C . Each experiment consisted of more than 50 mother cells and was independently repeated at least twice . Data shown in the results represent one single experiment . Statistical significance was determined by a Wilcoxon rank sum test using Stata 8 software . Differences are stated to be significant when the confidence is higher than 95% . Genomic DNA prepared from each strain was digested by XhoI or 4 bp cutter ( MspI , HaeIII , HinfI , AluI ) , separated on a 1 . 0% gel , transferred to Hybond-N+ membrane ( GE Healthcare ) , cross-linked by UV and then probed with C1–3A/TG1–3 telomere-specific probe as described previously [22] . Ten-fold dilutions of each strain were patched on YPD containing the indicated doses of phleomycin ( Sigma ) , methyl methanesulfonate ( MMS; Sigma ) , hydroxyurea ( HU; Sigma ) , or exposed to UV with indicated doses , or grown at 23°C , 30°C , and 37°C . Photos were taken after two days . Each strain that contains URA3-marked telomere VII-L was grown to log phase at 30°C . Ten-fold serial dilutions were plated on YC complete medium and YC containing 5-FOA ( 5-Fluoroorotic Acid ) at 1 g/L . Plates were incubated at 30°C for two days and then photos were taken . Immunostaining of Rap1 was performed as described previously [74] . Agarose plugs for pulsed-field gel electrophoresis ( PFGE ) were prepared as described previously [75] . PFGE was performed on a Bio-Rad CHEF-DR-III system in 0 . 5×TBE at 14°C using the following program: step 1 , voltage 3 . 6 V/cm , switch 120 s , time 20 hr; step 2 , voltage 3 . 6 V/cm , switch 300 s , time 24 hr . After electrophoresis , DNA was visualized by ethidium bromide staining . GCR rate in indicated strains was determined as previously described [76] . The nonessential gene , HXT13 , located distal to the CAN1 , was replaced with a second selectable marker , the URA3 gene . Each strain was inoculated into YPD medium and grown at 30°C until the culture reached saturation . Cells of suitable dilutions were spread on YC plates in the presence or absence of 60 mg/L L-canavanine and 1 g/L 5-FOA . A fluctuation test and the method of the median were used to assess GCR rate [77] . Sensitivity to α factor was performed as previously described [41] . Cells of various ages were scored for their ability to undergo cell cycle arrest and schmooing in response to the yeast mating pheromone , α factor . After 4 hours of α factor challenge , cells were transferred to fresh medium to complete their life span . All cells documented underwent at least one cell division after being removed from the presence of α factor . The rate of marker loss in rDNA was measured as described [54] . Strains carrying a URA3 marker integrated into the rDNA array were grown in YC medium lacking uracil until the culture reached saturation . Cells of suitable dilutions were spread on YC plates with and without 5-FOA . Plates were incubated at 30°C for two days and colonies were counted . The number of colonies on 5-FOA plates divided by the number of colonies on YC plates was reported as the rate of marker loss . A Student's t test was used to determine the statistical significance of the data . | Telomeres are the specialized structures at the ends of eukaryotic linear chromosomes . The simple guanine-rich DNA repeats at telomeres and their associated proteins are important for chromosome stability . Most eukaryotic species have evolved an enzyme named telomerase to replicate their telomeric DNA . Telomerase usually contains a protein catalytic subunit and a RNA template subunit . A few eukaryotic species can use either telomere recombination or retrotransposon-mediated transposition to accomplish telomere elongation . Interestingly , the baker's yeast Saccharomyces cerevisiae can use both telomerase and recombination to replicate telomeres . In this study , we utilize this unique eukaryotic model system to compare the efficiency of these two mechanisms in the maintenance of cellular function and life span . Telomerase-null cells that used recombination to elongate telomeres were able to maintain relatively stable chromosomes; however , they exhibited a shortened replicative life span which may represent a novel aging pathway . Reintroduction of telomerase inhibited telomere recombination and restored the replicative life span of these cells , implying that telomerase is superior to telomere recombination in the regulation of yeast replicative life span . | [
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] | 2009 | Telomere Recombination Accelerates Cellular Aging in Saccharomyces cerevisiae |
Ebola virus disease afflicts both human and animal populations and is caused by four ebolaviruses . These different ebolaviruses may have distinct reservoir hosts and ecological contexts that determine how , where , and when different ebolavirus spillover events occur . Understanding these virus-specific relationships is important for preventing transmission of ebolaviruses from wildlife to humans . We examine the ecological contexts surrounding 34 human index case infections of ebolaviruses from 1976–2014 . Determining possible sources of spillover from wildlife , characterizing the environment of each event , and creating ecological niche models to estimate habitats suitable for spillover , we find that index case infections of two ebolaviruses , Ebola virus and Sudan virus , have occurred under different ecological contexts . The index cases of Ebola virus infection are more associated with tropical evergreen broadleaf forests and consuming bushmeat than the cases of Sudan virus . Given these differences , we emphasize caution when generalizing across different ebolaviruses and that location and virus-specific ecological knowledge will be essential to unravelling how human and animal behavior lead to the emergence of Ebola virus disease .
From the first recognized outbreak of Ebola virus disease ( EVD ) in 1976 to the recent outbreak beginning in 2013 , our knowledge about the molecular biology and epidemiology of viruses belonging to the genus Ebolavirus has increased dramatically . Yet after nearly 40 years of research , we still have a limited understanding of the ecology and evolution of these viruses outside the context of outbreaks in humans [1] . One limitation in understanding ebolavirus ecology has been identifying the reservoir hosts in which ebolaviruses persist in nature , while another obstacle has been determining what causes the sporadic transmission of ebolaviruses from their natural reservoir into other animals and humans , leading to subsequent human-to-human transmission and outbreaks of EVD . These initial episodes of animal-to-human transmission are called spillover events , and knowing when , where , and under what environmental conditions ebolavirus spillovers occur could reveal underlying relationships in ebolavirus ecology . Additionally , identifying host-pathogen interactions of ebolaviruses with their natural reservoir and spillover hosts , as well as the interactions of these hosts with humans , could help researchers improve preemptive measures for transmission from wildlife as well as answer fundamental questions about virus ecology . The genus Ebolavirus belongs to the family Filoviridae along with the genera Cuevavirus and Marburgvirus . Five species of viruses have been established in the genus Ebolavirus: Zaire ebolavirus , Bundibugyo ebolavirus , Sudan ebolavirus , Taï Forest ebolavirus , and Reston ebolavirus . The viruses belonging to these species are known as Ebola virus ( EBOV ) , Bundibugyo virus ( BDBV ) , Sudan virus ( SUDV ) , Taï Forest virus ( TAFV ) , and Reston virus ( RESTV ) , respectively [2] . These different ebolaviruses are genetically distinct , with SUDV and RESTV being the most divergent from the other ebolaviruses [3] . Factors influencing the speciation of ebolaviruses and how ebolavirus speciation relates to reservoir host evolution and ecology remain enigmatic . No ebolavirus has ever been isolated from a putative reservoir species . In addition , of all the ebolaviruses , only EBOV has had its RNA detected in potential reservoir hosts , 3 species of African fruit bats [4] . Duikers ( Cephalophus species ) , gorillas ( Gorilla gorilla ) , chimpanzees ( Pan troglodytes ) , and various rodents have also tested positive for EBOV RNA [5 , 6] . It is widely suspected that these are probably incidental hosts that are indirectly infected by bats [7] . While serological evidence exists for RESTV in Asian bats and TAFV was found in a deceased chimpanzee , both SUDV and BDBV have yet to be identified via serology or PCR in any wildlife [7] . Therefore , we do not know the definitive reservoir host species for any ebolavirus or what factors influence ebolavirus transmission from wildlife into human populations . While the difficulty of detecting ebolaviruses in wildlife reservoirs hinders the identification of reservoir hosts and the determination of their enzootic cycles , examining the ecology of ebolaviruses at the human-animal interface could yield insights about potential animal hosts as well as the ecological conditions that drive the emergence of these pathogens . EBOV , SUDV , BDBV , and TAFV are known to cause EVD in humans . Antibodies to RESTV have been detected in humans in the Philippines [8]; however no RESTV spillover events in humans have been documented , and it is assumed that RESTV is nonpathogenic in humans [9] . Therefore , outbreaks of EVD in human populations have enabled researchers to characterize the other four ebolaviruses according to their locality , case fatality , and epidemiology [10] , as well as understand human-to-human transmission [11] . However , the individual spillover events that lead to outbreaks in humans have not been as well characterized . While few ebolavirus spillover events have been confirmed , there are reported index cases , the first human cases to be clinically described or laboratory confirmed in a chain of transmission . The central estimate for the incubation period until onset of EVD is 5 . 3–12 . 7 days for EBOV , 3 . 35–12 days for SUDV , and 6 . 3–7 days for BDBV [12] . Therefore , these index cases provide an approximation of roughly where and when spillover events have occurred . Since only EBOV has been sparsely detected in wildlife , examining these spillover events via index case reports is currently the only way that we can consistently compare the ecologies of multiple ebolaviruses . In order to specify the ecological contexts of ebolavirus spillover events , one must first define the habitats where spillover events occur . Ecological niche models ( ENMs ) can be used to qualitatively compare the habitats where different species occur and identify regions of habitat suitability [13] . This toolset is increasingly being used to predict the ecological niches of viruses . For example , cases of human monkeypox disease have been used to model the ecological niches of monkeypox virus [14 , 15] . Instead of using species occurrences and predicting fundamental ecological niches , we can use the locations of ebolavirus index cases and their associated spillover events from wildlife into humans to determine suitable habitats for ebolavirus spillover . Comparing the suitable spillover habitats of different ebolaviruses allows us to further compare the ecological contexts of multiple ebolaviruses and determine virus-specific factors of spillover . Here we characterize the habitat and context of all known ebolavirus index case infections and associated spillover events into humans from 1976–2014 to investigate species and location specific ecological relationships . We use an ENM modeling approach that is optimized for small sample sizes to compare the habitats of spillover events of different ebolaviruses . In doing so , we find that distinct ebolaviruses spill over into humans under specific ecological contexts and are associated with different habitats .
We identified a total of 34 index cases and the associated spillover events of four ebolaviruses ( 24 EBOV , 7 SUDV , 2 BDBV , and 1 TAFV ) ( Table 1 ) . We hereafter refer to both these index cases and their associated spillover events as “spillover events . ” Spillover events of viruses from each species occurred in distinct geographic locations ( Fig 1 ) , while 1 SUDV and 4 EBOV spillover events occurred in the same location as a previous event . EBOV spillover events have occurred at latitudes ranging from -5 . 3°-8 . 6° throughout the year during both wet and dry seasons . SUDV spillover events were more spatially clustered at . 64°-4 . 6° and 6/7 ( 86% ) occurred during the wet season . Two SUDV spillovers occurred in the same location during the same season within 3 years from each other . The two BDBV events occurred at . 77°-2 . 7° during the wet season , and the TAFV event also occurred during the wet season . We used the locations of ebolavirus spillover events and environmental covariates to create ecological niche models , which identified habitats similar to those where different ebolaviruses have spilled over into humans . Suitable habitats for EBOV and SUDV spillover events within Africa are shown in Fig 2 . These models were made under the assumption that EBOV and SUDV spillovers from wildlife do not occur outside of mainland Africa . Additional models were made to compare the habitats of EBOV and SUDV spillover events within a global context ( Fig A in S1 Text ) . Due to the limited sample size of TAFV and BDBV spillover events , we could not create models for these species that were statistically significant . The minimum training presence threshold was chosen to create the binary maps because it was more liberal than the 10 percentile training presence threshold . The minimum training presence threshold is established by the lowest habitat suitability in the training data set; therefore , all indicated regions have ecological conditions that at minimum match those in the least suitable confirmed location of spillover . The models for EBOV and SUDV at the minimum training presence threshold successfully predicted spillover event locations at high rates , 85% ( 17/20 ) and 66% ( 4/6 ) respectively . A P value of 3e-05 was calculated for the SUDV models and 3e-19 for the EBOV models , indicating that both models were statistically significant at predicting distribution of spillover events compared to random . The models of EBOV and SUDV spillovers at the minimum training presence threshold overlapped in approximately 12% of their total area . No SUDV spillover events were within the model of EBOV , and only three EBOV events occurred within the model of SUDV . Of the original 20 environmental covariates , 9 were determined to be important in contributing to the models of both ebolaviruses ( Table 2 ) . SUDV spillover events occurred at a significantly higher mean elevation than those of EBOV ( p = 0 . 004 ) . The 95% CI for the difference in means of SUDV and EBOV events was 196–671 m . EBOV events are also more associated with evergreen broadleaf forest compared to other land cover types than SUDV events ( p = 0 . 0007 ) , whereas SUDV events are more associated with woodland ( p = 0 . 0078 ) . The long-term monthly mean rainfall and temperature varied between SUDV and EBOV locations ( Fig 3 ) . Comparing SUDV and EBOV spillover locations , there was no significant difference in the mean temperature ( p = 0 . 18 ) or rainfall ( p = 0 . 95 ) of the actual month when an event occurred . The suspected animal sources of all known spillover events of viruses from different Ebolavirus species are shown in Table 1 . The geographic distributions of these animals from the IUCN Red List [16] in relation to EBOV and SUDV ENMs are in Figs B-D in S1 Text . EBOV spillover events were more associated with bushmeat contact than SUDV spillover events ( p = 0 . 012 ) . Chimpanzees , gorillas , duikers , monkeys , and fruit bats were all suspected sources of spillover for EBOV . Only one SUDV spillover event could be potentially linked to the bushmeat of a baboon , a species not found to be associated with EBOV spillover . In the majority of SUDV spillover events , no possible animal source could be identified . Two SUDV spillover events were linked to the same factory containing insectivorous bats and rodents .
The recent outbreak of EVD has inspired research across many fields , so it is critical to communicate that multiple ebolaviruses can cause EVD outbreaks and could have distinct ecological relationships . Our findings demonstrate that the spillover events of different ebolaviruses do occur within specific ecological contexts and habitats . EBOV spillovers have occurred within or on the edges of tropical evergreen broadleaf forests , and index patients are often hunters , villagers , or outdoor workers who have come into contact with animals such as bats , primates , and duikers . In contrast , SUDV spillover events occur at higher elevations , are more associated with woodlands , and have cryptic animal sources of spillover . In order to study the ecological contexts of TAFV and BDBV , more information on their possible animal reservoirs and spillover events are necessary . Our study provides an approximation of the different ecological contexts of the index cases and spillover events of four ebolaviruses known to cause EVD in humans . We compared the contexts of EBOV and SUDV spillover events as well as qualitatively estimated areas of habitat suitability for spillover of these viruses . We did not attempt to determine the fundamental ecological niches of different ebolaviruses and Ebolavirus species . Instead , we compared the ecology of ebolaviruses based on the contexts of index cases and associated spillover events . Our models indicate habitats that are similar to those where index cases have occurred . A biogeographical study with additional assumptions about ebolaviruses and their hosts could quantitatively compare whether the differences in EBOV and SUDV spillover event locations are due to differences in niche conservatism or differences in the distributions of spillover events . One limitation to our approach is that spillover event locations are unlikely to be independent and index case reports may be subject to geographical and temporal variation in reporting bias . Therefore , our models could exclude actual habitats of these viruses . For instance , more EBOV spillover events have been detected in the western Congo Basin than in the central Congo Basin . Thus , parts of the central Congo Basin are excluded from our models despite that this region includes putative EBOV host ranges ( Figs B-D in S1 Text ) . Our models may also include habitats that are ecologically suitable based on spillover events but are unlikely to contain the viruses . For example , we identified habitats in Southern Africa that have suitable ecological conditions but are geographically isolated from where ebolaviruses have so far been detected . A further limitation to our study is that we used index case reports to approximate when spillover events occurred and analyzed the mean environmental data from the month of symptom onset or date of death , if symptom onset date was unavailable . Therefore , the variable duration of illness and incubation periods for ebolaviruses may influence our estimations of spillover event locations and results about seasonality . Additionally , historical monthly precipitation data was limited in spillover locations , so we used coarse resolution data to classify seasons and compare the precipitation within the month of a spillover event . Long-term monthly mean and bioclimatic data were available at much higher resolutions and were used for our other analyses . Until more ebolavirus spillover events are confirmed , our study provides an approximation of the ecological conditions of spillover events of ebolaviruses . Despite these limitations , our study further supports that researchers cannot generalize about the ecological contexts of different ebolaviruses . Previous authors have used climatic data and ENMs to make inferences about spatial and temporal relationships of ebolaviruses . One group used NVDI models and Landsat data and found that the 1994–1996 EVD outbreaks occurred in tropical forest and were associated with climate changes from drier to wetter conditions [17] . In contrast , another group found that 1994–2002 EVD outbreaks were associated with drier conditions at the end of the rainy season [18] , while another study found EVD outbreaks to be associated with lower temperatures and higher humidity [19] . These studies did not differentiate between different ebolaviruses , which may explain their discrepancies . Considering the different contexts of SUDV and EBOV spillover events , we found no associations between the temperature or precipitation during the month of a spillover event , and spillovers of both ebolaviruses occurred in both wet and dry seasons . We also find that generalizing across ebolaviruses when making ENMs can miss virus-specific relationships . For instance , one group used the occurrence data of the 3 species of Old World fruit bats that were positive for EBOV RNA , EBOV infections in wildlife , and the locations of outbreaks associated with multiple ebolaviruses to create predictive risk maps for EVD [20] . This approach assumes that the reservoir species for different ebolaviruses are the same and that the spillover events of these viruses occur under the same ecological conditions . However , another group used the occurrence data from 12 EVD outbreaks in the period of 1976–2002 to create ENMs and found that eliminating SUDV occurrence data from the other ebolaviruses created a prediction that did not include the distribution of SUDV [21] . Using a modeling approach that was optimized for small sample sizes and spillover locations from 1976–2014 , we corroborate this observation that EBOV and SUDV are associated with different habitats and may need to be considered separately in further ecological modeling . The habitats suitable for SUDV and EBOV spillovers correspond with the serological evidence of these viruses in humans and wildlife . Our models showed that habitats in West Africa and Central Africa were suitable for EBOV spillover , while East Africa and parts of Central Africa were more suitable for SUDV spillover . Serological surveys in humans or animals have found antibodies to EBOV or SUDV in the majority of the countries identified by our models ( Table 3 ) . However , the cross-reactivity of different ebolavirus antibodies in these assays makes it difficult to distinguish the type of ebolavirus infection . As more seroepidemiological surveys are done and diagnostics improve , we can use this information to make more informed conclusions about where different ebolaviruses are found in humans and animals . Understanding the ecological contexts of ebolavirus spillover events also allows us to infer about the potential geographic distributions of these viruses and their respective hosts . Our models support that there is ample suitable habitat for EBOV and SUDV spillover . The recent discovery of Lloviu virus , a related filovirus , in insectivorous Miniopterus schreibersii bats in Europe [22] , the detection of filovirus RNA and antibodies in Rousettus leschenaultii in China and Bangladesh [23 , 24] , the circulation of RESTV in Southeast Asia [25 , 26] and the recent emergence of EBOV in humans in West Africa suggest the possible circulation for filoviruses far beyond the areas with recorded EVD outbreaks . The lack of recorded spillover events in areas with suitable ecological conditions could therefore be due to the absence of pathogenic filoviruses and their respective hosts , lack of recognition of spillover events , absence of ecological and anthropogenic factors driving specific spillover events , or a combination of these factors . Considering the different environments in which SUDV and EBOV spillovers have occurred , we can form two hypotheses about their distributions and reservoir hosts: SUDV and EBOV occupy different host species ( potentially multiple species ) with different habitats or SUDV and EBOV persist in the same species that is able to occupy multiple habitats . We can investigate these potential host relationships through comparing our models with the distributions of animal species that have been previously associated with ebolaviruses . The suitable habitats that we determined for EBOV and SUDV spillovers are shared among some potential bat hosts and are specific to others . The 3 species of fruit bats that were positive for EBOV RNA , Hypsignathus monstrosus , Myonycteris torquata , and Epopmops franqueti , have geographic ranges that overlap more closely with the tropical forests where EBOV spillovers have occurred , but the eastern boundaries of these species occur near SUDV spillover events as well [27] ( Fig B in S1 Text ) . Additional African bat species have been identified as potential reservoirs for EBOV based on serology [7] , but again the cross-reactivity of these assays makes it difficult to make associations with particular ebolaviruses . Of the distributions of serologically positive bat species ( Fig C in S1 Text ) , those of Micropteropus pusillus and Mops condylurus best match the woodland habitat associated with SUDV [28 , 29] . M . condylurus belongs to the family Molossidae , whereas the other potential ebolavirus hosts belong to Pteropodidae . Moreover , bats belonging to the same genus ( M . trevori ) were found in the textile factory in Nzara where at least two independent spillover events of SUDV occurred [30] and have a geographic distribution within the SUDV habitat ( Fig D in S1 Text ) . Perhaps the evolutionary and ecological differences between molossid and pteropid bats could explain the divergence between SUDV and EBOV . The hypothesis that different ebolaviruses may have different host species , and therefore different habitats suitable for spillover , is supported by in vitro and in vivo experiments . In vitro studies have shown that the receptor NPC1 influences filovirus susceptibility in different bat species [31] . These studies may be useful in determining whether particular bat species are capable reservoirs for different ebolaviruses . In addition , experimental infection studies showed efficient replication of Marburg virus , but limited replication of the five ebolaviruses in Rousettus aegypticus [32 , 33] , the reservoir host for Marburg virus . These findings highlight the potential for a single filovirus-single reservoir host species relationship , which may be why EBOV and SUDV spillovers occur in different habitats . Different relationships of ebolaviruses with secondary hosts and regional human-animal interfaces could also explain the differing contexts of EBOV and SUDV events . The majority of the EBOV spillover cases came from infected primates , whereas the sources of SUDV were unidentified . Additionally , there have been no documented outbreaks of EVD in chimpanzees in East Africa near the habitat of SUDV , indicating that reservoir hosts of SUDV may not come into contact with wild apes . For example , western lowland gorillas and chimpanzees share Ficus spp . as a food source with the potential EBOV reservoir bat species H . monstrosus [34 , 35] , and such an epizootic link may not exist for SUDV and its reservoir host . Furthermore , other forest-dwelling animals , such as the bay duiker ( Cephalophus dorsalis ) , are only associated with EBOV spillovers and have been positive for EBOV RNA , while the woodland savannah-inhabiting baboon ( Papio sp . ) has only been associated with an SUDV spillover . The different animal species that are associated with these two viruses and their spillovers further supports that these ebolaviruses may have different ecologies . Lastly , our study also provides more evidence about the evolution of ebolaviruses . It has been previously noted that there is remarkably little genetic diversity between both spatially and temporally separated strains of the same ebolavirus [36] . We found relatively large and contiguous areas of suitable habitat for both EBOV and SUDV spillover , which might explain why genetically similar viruses can circulate across large distances . Meanwhile , isolates of EBOV and SUDV differ by more than 40% in their genomes on the nucleotide level [37] , which could be explained by the small overlap in their spillover habitats and possible geographical isolation of their host species . Current phylogenetic trees place SUDV in a different clade than EBOV , and it is possible that geographic isolation led to this speciation , potentially due to the Albertine Rift [36] , which is near the eastern border of the EBOV habitats in our models . More extensive sampling of ebolaviruses in wildlife and rapid identification of index cases will increase our understanding of ebolavirus ecology and evolution , as well as potentially guide preemptive control strategies . Overall , we show that ecological contexts of ebolavirus spillover events are virus-specific , relating to particular habitats , animal distributions , and human activities . Therefore , researchers must be careful about generalizing about ebolaviruses and their ecologies . Uncovering nuances in virus ecology will require further explorations of the human-animal interfaces that lead to viral spillover and collaborations across disciplines .
The geographic coordinates and identities of index cases were determined from the original literature describing EVD outbreaks and case reports ( Table 1 ) , using the Centers for Disease Control and Prevention’s EVD chronology as a guide [38] , as well as a database of 22 EVD outbreaks [39] . Index cases were defined as patients who were the first to exhibit symptoms of EVD in an epidemic chain and had no previous contact with EVD patients . Additionally , index cases often had direct contact with wildlife prior to becoming symptomatic for EVD . The index case dates were determined by the date of symptom onset for the index patient . If this date was unavailable , the date of death of the index patient was used . In four cases only the month of an index case could be determined . Additional index cases were identified by considering separate epidemic chains of transmission . Within the EVD outbreaks in the Republic of the Congo and Gabon are multiple spillover events , characterized by separate virus strains and epidemic chains of transmission [40 , 41] . Index case patient demographics were determined from the literature . Research studies and case reports were examined to link index patients to potential sources of spillover , all of which were circumstantial . The majority of the coordinates that we determined for spillover event locations corresponded to the index point locations in a recently created EVD database , which contains details about some spillover events [39]; however we identified additional spillover events that were not described in the database . We included the locations of index cases in Meliandou ( Guinea ) and Boende ( DRC ) that were not included in the database . We also used adjusted locations for the villages of Mwembe and Nakisamata ( S1 Text ) . Climate and terrain data were used to construct the ENMs . Layers of rasterized climate data of 19 bioclimatic variables as well as elevation came from the WorldClim database [42] , which averages values from 1950–2000 at a spatial resolution of 30 arc seconds . We point sampled the elevation as well as long-term monthly mean rainfall and temperature at spillover locations from the WorldClim dataset in QGIS [43] . To look for seasonal relationships , we gathered the monthly mean precipitation during the month and year at the location where a spillover event occurred . We used the GPCP Version 2 . 2 Combined Precipitation Data Set provided by the NOAA/OAR/ESRL PSD , Boulder , Colorado , USA ( available at http://www . esrl . noaa . gov/psd/ ) . The GPCP data set has a spatial coverage of 2 . 5° latitude X 2 . 5° longitude , and uses a combination of satellite and gauge data to calculate mm precipitation per day [44] . Monthly values in the dataset are from 1979-October 2014 . Therefore , we could not obtain precise monthly precipitation data for the 3 spillover events prior to 1979 , so we did not include these events in analyses of within season rainfall , and we used the long-term monthly mean precipitation for classifying them into wet or dry seasons . Temperature data for the specific month of a spillover event was gathered from the GHCN CAMS Gridded 2m Temperature ( Land ) dataset also provided by the NOAA/OAR/ESRL PSD , which has a resolution of . 5° latitude X . 5° longitude and contains monthly mean land surface temperatures from 1948 to October 2012 [45] . Vegetation and land cover were determined by mapping spillover event locations on raster maps from the Global Landcover facility ( available at http://glcfapp . glcf . umd . edu ) . We used a global map with a spatial resolution of 225 seconds and fourteen land cover classes developed from NOAA-AVHRR satellite images from 1981–1994 . We point sampled each location in QGIS to determine the land cover classification at that geographic location . The ENMs were built using Maximum Entropy Species Distribution Modeling ( MaxEnt ) , version 3 . 3 . 3k [46] . The MaxEnt program applies a machine learning method to estimate the distribution of a species under maximum entropy in geographic space using environmental factors as covariates and presence-only data as inputs [47] . We chose MaxEnt over other ENMs because it is robust with small numbers of occurrences and presence-only data [48] . Models were built to determine suitable habitat for ebolaviruses using spillover events as presence-only inputs . We used the 20 environmental covariates clipped to mainland Africa for our models and analyses because TAFV , BDBV , SUDV and EBOV spillovers have only occurred within mainland Africa . We also created models with a global environmental extent for comparison . Because our aim was to characterize the environments where different ebolavirus spillover events have occurred , we did not make assumptions about sampling or the density of the population . Instead of designing the models to provide probabilistic output , we used our models as indices of habitat suitability [13] . MaxEnt can use a subset of presence points to train the model , while reserving a subset to test the predictive strength of the model . Iteratively leaving out a single occurrence point , training the model , and then testing whether that point is included in the model , works well for determining the predictive ability of a model with a small sample size [49] . Therefore , we used a leave-one-out cross-validation method for each species , in which for a sample size n of spillover locations for each species , we divided the data into n equal size folds and kept one fold out to test the model . We repeated this process n times and then averaged the models for each species . In addition to these sampling changes , the MaxEnt models were run on the default parameters with the cumulative output and the jackknife approach for comparing environmental covariates . The cumulative output reflects habitat suitability , where the probability of occurrence in each cell is the sum of the probability in that cell as well as all other cells with lesser or equal probability [49] . The minimum training presence and the 10 percentile training presence were compared as thresholds to determine which regions were suitable or unsuitable for the respective species . To test whether the models were statistically significant at predicting presence locations compared to random , we created a program for the statistical test described by Pearson et al . 2006 [49] ( available at: https://github . com/AndrewJudson/jackknife ) . We calculated the percent overlap of the models by dividing the area of overlap by the total area of both models . Traditional niche overlap statistics such as Schoener’s D and I were not calculated because these assume a probability distribution for the species [50] , whereas our models predicted habitat suitability . Reducing the number of environmental covariates in ENMs enables researchers to determine which covariates are driving the model . We chose to use the same covariates across the different models so that we could compare the models with each other . We used a hierarchical approach and correlation matrix to remove covariates from the initial 20 that did not contribute to the models of either ebolavirus and were highly correlated with each other . We removed covariates as long as there were no changes from the original models . For analyses and mapping , we used the models with all 20 covariates . All statistical tests to determine whether the spillover events of a particular ebolavirus were more associated with certain ecological conditions were done using Fisher’s exact tests . In order to compare the differences in mean elevation , temperature , or precipitation at spillover locations , two-tailed Welch’s t-tests were used . All statistical analyses were performed in R [51] , and a significance level of p < 0 . 05 was used . | Multiple Ebola virus disease outbreaks have occurred over the past 40 years , yet we still do not know the geographical distributions , definitive host species , and suitable habitats for animal-to-human transmission of different ebolaviruses . Each Ebola virus disease outbreak has started with at least one transmission event from a wildlife host to a human , also known as a spillover event . While researchers have studied these events in regards to Ebola virus disease outbreaks , many studies neglect that there are multiple ebolaviruses and that these viruses may differ in their spillover events . We characterize the specific ecological contexts of different ebolavirus spillover events based on recorded index case infections . Comparing the environmental contexts of these cases and using ecological niche modelling , we find that two ebolaviruses have different suitable habitats for spillover . The different habitats and contexts of the two ebolaviruses involved in the majority of outbreaks , Ebola virus and Sudan virus , indicate that we must further investigate virus-specific differences in ebolaviruses and their hosts . | [
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"g... | 2016 | Ecological Contexts of Index Cases and Spillover Events of Different Ebolaviruses |
In internal membrane-containing viruses , a lipid vesicle enclosed by the icosahedral capsid protects the genome . It has been postulated that this internal membrane is the genome delivery device of the virus . Viruses built with this architectural principle infect hosts in all three domains of cellular life . Here , using a combination of electron microscopy techniques , we investigate bacteriophage PRD1 , the best understood model for such viruses , to unveil the mechanism behind the genome translocation across the cell envelope . To deliver its double-stranded DNA , the icosahedral protein-rich virus membrane transforms into a tubular structure protruding from one of the 12 vertices of the capsid . We suggest that this viral nanotube exits from the same vertex used for DNA packaging , which is biochemically distinct from the other 11 . The tube crosses the capsid through an aperture corresponding to the loss of the peripentonal P3 major capsid protein trimers , penton protein P31 and membrane protein P16 . The remodeling of the internal viral membrane is nucleated by changes in osmolarity and loss of capsid-membrane interactions as consequence of the de-capping of the vertices . This engages the polymerization of the tail tube , which is structured by membrane-associated proteins . We have observed that the proteo-lipidic tube in vivo can pierce the gram-negative bacterial cell envelope allowing the viral genome to be shuttled to the host cell . The internal diameter of the tube allows one double-stranded DNA chain to be translocated . We conclude that the assembly principles of the viral tunneling nanotube take advantage of proteo-lipid interactions that confer to the tail tube elastic , mechanical and functional properties employed also in other protein-membrane systems .
A fundamental step in the lifecycle of all known viruses is the genome translocation into the target cell . Although this process has been elucidated for several enveloped viruses [1] , [2] , and for double-stranded ( ds ) DNA head-tailed bacteriophages [3]–[7] , equivalent information on internal membrane-containing viruses is scarce . PRD1 is an internal membrane-containing dsDNA bacteriophage ( family Tectiviridae ) whose crystallographic studies ( Figure 1A , left ) have provided unprecedented insights into the assembly mechanism of large complex viruses [8]–[10] . With several other such examples [11]–[16] , this has led to a novel principle of classifying viruses based on their major capsid protein ( MCP ) fold [17] , [18] . Such viruses pose fundamental questions about the morphogenesis of the membrane and the genome packaging and ejection processes that utilize the lipid bilayer enclosing the genome . PRD1 packages its genome capped with terminal protein P8 [19] into a preformed membrane-containing procapsid using the packaging complex at the unique vertex specifically composed of ( i ) the packaging ATPase P9 , ( ii ) the packaging accessory protein P6 , and ( iii ) two small membrane proteins P20 and P22 ( Figure 1A , right ) [19]–[22] . The other 11 vertices are different , being constructed from ( i ) the vertex-stabilizing membrane protein P16 , ( ii ) penton protein P31 , ( iii ) spike protein P5 , and ( iv ) receptor binding protein P2 ( Figure 1A , right ) [8] , [23]–[25] . So far , the 3D structure of this unique vertex is not known . Interestingly , PBCV-1 , an algae infecting virus , and the largest virus described , Mimivirus infecting Acanthamoeba polyphaga , both with an internal membrane and thought to belong to the same structure-based virus lineage with PRD1 , have also recently been shown to possess a unique vertex [26]–[29] . Activation of the PRD1 infection process in a broad range of gram-negative hosts such as Escherichia coli , Salmonella enterica , and Pseudomonas aeruginosa is triggered by specific binding of the viral protein P2 to the cellular receptor . A model for DNA delivery has been postulated from biochemical and genetic studies which point to the involvement of viral membrane proteins P7/P14 , P18 , and P32 in the formation of the putative membranous tail tube protruding from one vertex [30] , [31] . Here , we combine immuno-labelling , cryo-electron microscopy , and cryo-electron tomography ( cryo-ET; single-particle , subtomogram averaging , and cellular tomography ) analyses using wild-type ( wt ) PRD1 , DNA-packaging-deficient mutant Sus1 particles ( i . e . , procapsids ) and in vivo analysis of virus-infected cells to report a new principle of virus–cell interaction essential for viral genome translocation . We suggest that the PRD1 tube protrudes from the same unique vertex used for DNA packaging and that it is structured , implying the direct involvement of self-assembling and lattice forming membrane-associated proteins . Furthermore , we demonstrate that the internal vesicle in DNA-less procapsids can undergo acrobatics . This ability underscores the general elasto-mechanical properties of giant unilamellar ( proteo- ) vesicles and the triggering factors of the viral vesicle shape transition leading to the assembly of the tail tube . This assembly process and the tunnelling of the viral tail tube through the cell envelope is reminiscent of cellular membrane nanotubes used in cell-to-cell communication [32] , [33] .
The samples used throughout this study contained a mixture of intact viruses and empty particles as well as particles with a tube and individual tubes devoid of capsid ( Figure 1B ) . In 2D cryo-images of PRD1 tail tube at 50 , 000× magnification , the tube's wall appeared as a bilayer structure with dimensions similar to those of the vesicle within the capsid ( Figure 1C ) . We adopted ageing of the PRD1 sample as a way to obtain particles with a tube because a trigger for synchronous genome ejection in vitro is as yet unknown . Whether the genome ejection machinery uses the same vertex through which the genome is packaged remains unclear . Circumstantial evidence based on immuno-labelling of packaging-vertex-associating proteins P20 and P6 suggested that the DNA packaging and ejection vertices might coincide , implying that upon tube formation P20 and P6 may be dislocated ( Protocol S1 and Figure S1 ) . We also performed subtomogram averaging of intact wt PRD1 particles with no imposition of icosahedral symmetry and with a loose shell mask that included the vesicle in the alignment process in the attempt to detect coarse asymmetrical structural features . Although we confirmed previous results on the conformational flexibility of the spike complex [23] , at this level of analysis we could not firmly detect structural differences between the 12 vertices [5 . 8 nm resolution at the 0 . 5 threshold of the Fourier shell correlation ( FSC ) ; Figure S2A] . Further classification and higher resolution studies are required to fully resolve the structure of the packaging vertex . We focused our analysis on 3D tomographic reconstructions of individual PRD1 particles with a tube on which icosahedral symmetry was not imposed ( Figure 1D ) . These tomographic reconstructions showed that the icosahedral capsid was largely preserved , with a unique tube with a diameter of ∼14 nm and with variable lengths ( mean 51 . 4±9 . 4 nm , n = 70 ) protruding from a single vertex ( Figure 1D–E ) . In rare cases the distal part of the tube appeared closed ( black arrow in Figure 1D , top left ) . As far as can be judged in the presence of the missing-wedge effect , the capsid is not structurally compromised except at some vertices , including the one with the protruding tube , where an opening of ∼15 nm diameter allows the tube to exit through the vertex ( Figures 1D and 2A , left ) . Overall capsid and membrane thicknesses agree with those reported from previous PRD1 studies ( Figure 2 ) [8] , [9] , [34] . Interestingly , subtomogram averaging of the capsids with a tube carried out using Dynamo software ( at 6 . 4 nm resolution , no icosahedral symmetry imposed; Figures 2A , right and S2B , top left ) [35] suggests that there is preferential de-capping of contiguous vertices , one of which is adjacent to the vertex from which the tube protrudes ( Figure 2B ) . These apertures imply the loss of the peripentonal MCPs ( P3 ) , membrane proteins P16 , penton proteins P31 , and vertex-associating proteins P2 and P5 ( Figure 2C ) . In turn , this de-capping of the vertices leads to the loss of the P16 protein interactions and P3 N-terminal contacts with the underlying membrane ( Figure 2D ) . Whereas in the virions the membrane follows icosahedral symmetry [8] , [9] , [34] , distinct vesicle morphologies were detected in the individual tomograms of the particles with a tail tube . These ranged from a membrane not fully deformed , most probably illustrating the initial stages of DNA ejection ( Figure 1D , top ) , to particles where the membrane appears to clearly deflate in proximity of the de-capped vertex complexes ( Figures 1D , bottom , and 2A , left ) . In some tomograms , clear density attributable to DNA was also visible within the vesicles with a protruding tube ( Figure 1B and 1D , top left ) . In addition , particles where the vesicle shape was drastically compromised resembling a “map pin” were seen ( Figure 1D , bottom ) . The change in the vesicle size from an icosahedral one to a membrane with a protruding tail tube ( as shown in Figure 1D , below ) causes a drastic reduction in membrane area ( ∼30% ) and volume ( ∼60% ) , reflecting one of the last stages in DNA translocation . Additionally , the exit direction of the tail tube was not always aligned with the icosahedral 5-fold axis but angled ( Figure 1D , bottom ) , in some cases , with a deflection of ∼20° ( Protocol S2 ) . In previous studies , the membrane isolated from empty PRD1 procapsids ( sus1 mutant ) by guanidine hydrochloride treatment has been shown to form tubular structures , whereas the DNA-containing vesicles isolated from the virions mainly adopt a spherical shape [31] . Mutant sus1 has a defect in the packaging ATPase gene IX ( encoding protein P9 ) , and thus it does not package DNA . Using a similar ageing regime and buffer conditions to that used for wt PRD1 , we inspected the ability of the procapsid to form the tail tube and the procapsid membrane morphology by 2D and cryo-ET imaging . Indeed , tubes were assembled and projected from one of the vertices as for wt PRD1 ( Figure S3 ) . Remarkably , the membrane in the procapsid exhibited far more varied morphologies than the membrane in the virion . These diverse membrane shapes within the capsid included stomatocyte-like , discocyte-like shapes , and internal tubes budding and pinching off as extra vesicle from the larger one ( Figure 3A–B ) . Intriguingly , these tails tubulate and pinch off tangentially to the vesicle ( Figure 3B–D ) . This direction of tubulation is completely different from that observed in other PRD1-tube particles in which the tube polymerizes orthogonally to the vesicle ( Figures 1D , 4 , and S3 ) . In addition , two tubes were occasionally visible budding from the vesicle ( Figure 3E ) . To grasp whether a conserved structure was present at the exit-portal between the vesicle and the capsid aperture ( hereafter called “gate” ) , several subregions corresponding to the gate ( n = 138 ) were averaged ( Figure 4A ) . Manual fitting of a hexameric model of the only viral packaging ATPase structure available ( STIV2 protein B204 , [36] ) from a nontailed dsDNA virus into the PRD1 gate structure indicates a size mismatch between the tube and the multimeric ring ( Figure 4B ) . Also , within the current resolution limits ( ∼5 . 7 nm; Figure S2B , top right ) , there were no indications of an ordered multimeric ring-like structure of radius >8 nm at the gate ( red arrowheads in Figure 4A , left ) that could correspond to a portal or to a larger multimer of the packaging ATPase P9 or the packaging efficiency factor P6 or their heteromultimer . Notably , the density corresponding to the vesicle forms a continuum with the tube , resembling a funnel with the narrow end traversing the PRD1 open vertex ( Figure 4A , left ) . Cutting the averaged volume nearby this aperture exposes the density of the tube appearing to stem rather like a hoof-shaped object ( Figure 4A , right ) . Analysis of 2D images and subsequent 3D tomographic reconstruction of individual PRD1 particles with a tube showed a limited number of particles with the long axis of the tube aligned ( or quasi ) with the direction of the electron beam ( hereafter called “orthogonal” tubes ) ( Figure 1B ) . This orientation in 2D images of PRD1 suggested that the tube might possess rotational symmetry ( Figure 5A ) . Conversely , previous Fourier analysis of individual tubes with the long axis lying quasi-parallel to the imaging plane ( hereafter called “longitudinal” tubes ) showed too weak periodicity to unequivocally support a helical symmetry for the tube . Thus , we performed rotational symmetry and classification analyses on a set of orthogonal tubes ( n = 1 , 758 ) extracted from 2D cryo-images of PRD1 procapsids ( see Material and Methods ) . These analyses suggested a subset of tubes with a 3-fold rotational symmetry ( 18% ) besides those displaying 2-fold symmetry ( 28% ) , spurious symmetries ( 35% ) , or higher symmetries ( together summing up to 19% ) ( Figures 5B and S4 ) . Such a distribution of rotational symmetries prompted the possibility that ( i ) we were framing tubes at different stages of assembly ( or disassembly ) with structural heterogeneity , ( ii ) we were not viewing the tubes exactly along their symmetry axis , and/or ( iii ) the structure of the tube possessed also a helical component . Therefore , we extended this study to reconstructed cryo-electron tomograms of wt PRD1 particles with a tube ( also showing the preferential longitudinal orientation; Figure 1C ) . Due to the well-known missing wedge effect on cylindrical objects in this orientation , we performed subtomogram averaging of the tubes to increase signal-to-noise , to compensate for the missing-wedge loss , and to reliably assess the presence of a density pattern . However , no symmetry was assumed or imposed during this process . Prior to averaging , 167 subboxed tubes ( with the axes oriented along the z-direction ) were classified using a multireference alignment approach with four references ( see Material and Methods , Protocol S2 , and Figure S5A ) . Of the four resulting classes ( class 1 , n = 35; class 2 , n = 33; class 3 , n = 64; class 4 , n = 35 ) , based on relatively higher mean cross-correlation ( cc ) with the corresponding references , reasonable angular distribution of the set of tubes covering the geometric sphere and visual inspection of the densities , only class 2 and class 3 tube averages were further considered [class 1 recapitulated basic structural features of class 2 and 3 ( respectively cc1–2 = 0 . 61 and c1–3 = 0 . 69 ) , whereas class 4 was the most structurally incongruous ( cc4–2 = 0 . 49 and cc4–3 = 0 . 53; Figure S5B ) ] . The corresponding z-slices showed a pattern of alternating strong ( red dots ) and weak ( cyan arrows ) densities ( Figure 5C , top and insets ) that we interpreted as the cross-sectional views of upright strands ( stronger densities ) skeletonizing the tail tube and interacting laterally to each other . This pattern was not fixed across the z-slices ( see , e . g . , xy-slice 20 versus xy-slice 25 in Figure 5C , left top ) . To assess whether this lobular distribution of density was artifactual , simulation of tomographic data using a featureless cylindrical shell supported the bona fide averaged reconstructed tube models ( see Protocol S3 and Figure S5D ) . Furthermore , both averaged volumes contained an additional unique ring-like structure ( Ø∼18 nm ) crowning the tube , although it was much more distinctive in class 2 ( gold arrows in Figure 5C , bottom; this ring was not present in the averaged volume of class 1; Figure S5B ) . Thus , both 2D image and 3D volume analyses indicated that the tube possesses a degree of order and structure . However , the morphological variability noted in individually visualized PRD1 particles with a tube ( Figures 1B–D , 2A , left , and 3 ) , in the distribution of rotational symmetries ( Figure 5B ) , as well as in the resulting averaged tube volumes ( Figures 5C and S5B ) imply that the structure of the tube is variable . The parameters of the two averaged tube models calculated from the mean density profile along z of the central xz section indicate that both tubes possess an equivalent inner diameter ( 2r1∼4 . 5 nm ) but possibly slightly different outer diameters ( the smallest being 2r2∼14 nm ) ( Figure 5D ) . PRD1 genome entry occurs in a few minutes , inducing superinfection immunity [37] . This does not prevent other viruses binding to the cell but blocks the entry at a later stage , allowing entry intermediates to be detected . To visualize the PRD1 DNA delivery through the membranous tail tube in vivo , we used cellular cryo-tomography and tomography analysis on S . enterica and E . coli infected with a high multiplicity of infection ( MOI = 30 ) . For cellular cryo-tomography , whole infected E . coli cells were vitrified ∼30 min postinfection ( p . i . ) . From six tomograms 11 viruses were analysed , revealing nine tail tubes with a diameter 15 . 9±1 . 7 nm . Viruses were visualized at distinct stages of the infection process—for example , ( i ) a DNA-containing particle with the tail tube piercing the outer membrane ( Figure 6A , left ) , ( ii ) a half-empty particle ( Figure 6A , centre ) , and ( iii ) an empty particle with a deformed vesicle morphology within the capsid ( Figure 6A , right ) . For cellular tomography , the infection process in S . enterica was analysed at 5 and 30 min p . i . ( Movie S1 ) . At 5 min p . i . , based on 43 tomograms , most of the viruses ( n = 119 in total ) attached to the cell were still full of DNA . In 92 cases , tubes could be clearly visualized with a diameter 14 . 3±5 nm . Some capsids were seen to adhere to the cell outer membrane , whereas in others the capsids were found separated from the cell surface , having a part of their tubes standing outside the outer membrane ( Figure 6B ) . In the latter case , the distance between surfaces of the bacterial outer membrane and the virus capsid varied from 5 to 44 nm , with an average of 19 . 3 nm ( n = 21 ) . When the entire tail tube was visible upon cell envelope penetration ( for 13 viruses ) , its length was 47 . 6±4 . 5 nm . In some cases , DNA injected from the virus capsid could be seen as a central linear density within the tail tubes ( Figure 6B ) . At 30 min p . i . , viruses ( 53 viruses extracted from 29 tomograms ) appeared empty with no visible dense material inside the capsid ( Figure 6B , right ) , thus indicating that they had most likely injected their genetic material . The tubes had a diameter of 13±7 nm ( n = 36 ) and a length of 36±15 nm ( n = 32 ) . The distance from the bacterial outer membrane and the virus capsid varied from 10 to 24 nm , with an average of 15 nm ( n = 20 ) . Occasionally , a clear invagination of the inner and outer host membranes was visualized where the incipient tube pinched the cell envelope ( Figure 6C and Movie S2 ) .
Using PRD1 procapsids we have clarified that the internal pressure due to the packaged DNA does not induce the membrane transformation and consequently both lipids and membrane-associated proteins orchestrate the membrane transition as originally observed in the quantitative biochemical virus dissociation studies [31] . Our data reveal a range of viral membrane shapes ( Figures 1B–D , 2A , left , and 3 ) . Particularly striking , membrane morphotypes were the discoid- and stomatoid-like vesicles observed in the procapsids ( Figure 3A ) , mimicking almost the homeostatic functions typical of the plasma membrane of blood cells [38] . This membrane remodelling occurs in response to changes in environmental conditions—namely , osmolarity . By inference in PRD1 , the exchange of osmolytes with the external solution through the capsid ( in vitro vertex de-capping by ageing ) ( Figure 3A , right ) or the direct structural alteration initially caused by the attachment to the cell by the viral receptor binding protein P2 ( in vivo vertex de-capping ) destabilises the icosahedral vesicle , which ultimately leads to the tail tube formation ( Figure 7A ) . These are universal membrane morphologies that can be modelled by considering the reduction in vesicle volume versus the reduction of monolayer area difference between the two leaflets ( area-difference-elasticity theory ) [38] , [39] . Under specific environmental conditions , vesicles composed only of lipids can also form tubes favoured , for example , by specific lipid compositions [40] , [41] . In particular , phosphatidylethanolamine ( PE ) species lead to negative curvature [42] , whereas lipids with negatively charged headgroups respond to changes in pH and/or concentration of ionic strength . Notably , the PRD1 vesicle is composed mainly of PE ( 53% ) and phosphatidylglycerol ( PG; 43% ) , with an asymmetrical distribution of lipids between the two membrane layers with the PE and PG species mainly segregated in the inner and outer leaflet , respectively [9] . However , in PRD1 , the transformation of the membrane implies the redistribution of the membrane-associated proteins ( occupying ∼50% of the membrane volume ) of which only the vertex-stabilizing protein P16 is icosahedrally ordered [8] , [24] . This redistribution of the proteins facilitating the tube formation and scission ( Figure 3B ) is in line with several other model protein-membrane systems [41]–[43] . Thus , considered as a giant unilamellar ( proteo- ) vesicle , the PRD1 membrane is primed to readily react to environmental changes ( Figure 3A , right ) , rationalising previous observations where , for example , changes in buffer and/or temperature increased tube formation [44] . The viral vesicle does not form a hollow cylinder but rather a structured tube ( ∼4 . 8 nm thick ) , implying that the viral membrane-associated proteins act as a scaffold for the tube . Indeed , cross-sectional views for the most ordered tubes ( Figure 5C ) show alternate regions of high and low density ( Figure 5B–C ) , possibly indicating a multistrand architecture . Also , visual inspection of the two averaged tubes superimposed using the ring-like structure as pivot corroborates that the differences might be variations on a common core assembly ( Figure S6 ) . The observed high-contrast density regions ( Figure 5C , insets ) may be segregated membrane domains enriched in proteins polymerizing outward from the gate , possibly in an ordered fashion and with a coiling component ( Figure 7B–C ) . The weaker intercalating density could indicate that lateral contacts between the polymerizing building blocks are more labile ( Figure 7C , bottom ) , reflecting the dramatic curvature needed in the proteo-lipidic tube ( 2r∼8 . 8 nm; Figure 5D ) . Candidate scaffolding proteins include the single-pass transmembrane proteins P7/P14 and P32 and the multipass transmembrane protein P18 , whose knock-out impairs tube formation [30] . The primary sequences of these do not have any significant similarity with known viral and cellular proteins . In mature virions , the assembly of the tail tube and its correct direction through the opening of the vertex could be linked to the DNA counterpressure . The limited space in the virion restricts the conformational changes of the vesicle . The putative interaction of ATPase P9 with the viral genome via its terminal protein P8 [20] might serve the nucleation point and guide tail tube polymerization . This is consistent with the fact that in the wt PRD1 the majority of the tubes were rarely seen as short as those detected in the procapsids and confined within the capsid ( Figure 3B ) . Biochemical evidence supports structural crosstalk between the membrane and the unique vertex via the interactions of P22 , P20 , and P6 in complex with P9 and the packaged viral genome via the terminal protein P8 [19] , [20] , [22] . Intriguingly , the observed ring-like structure in the two averaged tube volumes matches into the capsid density at the aperture of the de-capped vertex ( Figure 7A , inset ) , suggesting that the ring might be composed of capsid proteins such as peripentonal P3 monomers remaining attached during the tube ejection or proteins specific to the unique vertex . Finally , the overall geometric parameters of the tail tube—outer diameter ∼14 nm , internal diameter ∼4 . 5 nm ( as from Figure 5D ) , and average length ∼50 nm—make this the smallest membrane nanotubes known to be capable of transporting biological material . Cellular tunnelling membrane nanotubes ( TNTs ) , such as filipodia , implicated in cell-to-cell bridging and in shuttling different cellular and viral cargos , possess a diameter ranging from 50 to 200 nm [32] , [33] . Our 3D studies of PRD1–cell interactions map in vivo the sequence of events leading to infection . The overall in vitro tube characteristics are preserved , and in the cellular context , the viral genome delivery device enters almost orthogonally to the cell surface ( variance ∼30° ) . Occasionally , the virus capsid was seen juxtaposed to the cell , producing a detectable infolding of the outer and inner membranes ( Figure 6C and Movie S2 ) , with the polymerizing tail tube practically drilling through the entire bacterial cell envelope ( Figure 6 ) . Such membrane perforation has also been indirectly followed by measurements of ion gradients across the cell membranes during infection [30] , pinpointing proteins P11 and P7 ( Figure 1A , right ) as the effectors of host cell penetration . In other cases , the virus capsid was seen at a few nanometers from the cell surface , with the assembled tail tube tunnelling through the outer membrane and the cell wall reaching the cytoplasmic membrane ( Figure 6A , right , and 6B ) . The viral tail tube wall does not fuse with the cellular membrane , probably as a result of protein scaffolding protection . The length of the tube , which is on average at least three times longer than the thickness of a typical cell envelope of S . enterica ( ∼15 nm thick ) , guarantees genome protection during delivery into the cytoplasm ( Figure 6A , right , and 6B ) . Once in the cytoplasmic compartment , release of the viral genomic DNA might be triggered by the intracellular pH conditions that would favour the opening of the distal part ( tip ) of the tube ( black arrow in Figure 1D , top left ) , allowing the DNA to exit through it , fuelled initially by the energy stored in the pressurized capsid ( Figure 7 ) . Additionally , the reactivity of the PRD1 vesicle to environmental changes ( Figure 3A ) implicates osmotic pressure as a driving force of the genome translocation . The internal diameter of 4 . 5 nm of the viral nanotube suggests that one double-stranded DNA chain ( Ø∼2 . 6 nm [9] ) can be translocated . The internal diameter of this tail tube is in line with that of the proteinaceous tails of the head-tailed bacteriophages . A schematic model summarising the PRD1 infection process is shown in Figure 7A . Viruses have devised different strategies to protect and to shuttle their genomes into cells . The protruding tail of membrane-containing PRD1 has superficial similarity with the proteinaceous tail of the head-tailed bacteriophages such as T4 . However , the origin and nature of the PRD1 nanotube is actually strikingly different . The PRD1 cell envelope tunnelling mechanism as a novel method of genome translocation is evocative in terms of its proteo-lipidic nature and cargo-shuttling functionality of cellular tunnelling nanotubes used in cell-to-cell communication . Internal-membrane-containing viruses infect organisms from all cellular domains of life and include bacterial viruses such as PM2 [12] , P23-77 [45] , and SSIP-1 [46]; archaeal viruses such as SH1 [47] , HHIV-2 [48] , and STIV [49]; and eukaryotic viruses such as poxviruses , iridoviruses , mimiviruses , and asfarviruses [27] , [29] , [50] , [51] , all of which must deliver genetic material into the host cell . We suggest that the remodeling of the proteo-vesicle into a dynamic membranous tail structure as seen in PRD1 might , suitably adapted to different hosts , underpin a shuttling mechanism common to all such viruses possessing a linear genome .
The wt PRD1 and P9-defective mutant sus1 ( for production of procapsids ) were propagated in nonsuppressor host Salmonella enterica Typhimurium LT2 DS88 and on suppressor strain Salmonella enterica Typhimurium LT2 PSA ( pLM2 ) , respectively [52] . For wt and procapsid particle production , DS88 cells were infected at an MOI of approximately 8 . For procapsid production 15 min after infection , the cells were collected ( Sorvall SLA3000 rotor , 5000 rpm , 10 min , 22°C ) and resuspended in fresh prewarmed ( 37°C ) growth medium . The particles were purified by polyethylene glycol-NaCl precipitation , rate zonal , and equilibrium centrifugation in sucrose , and concentrated by differential centrifugation ( Sorvall T647 . 5 rotor , 113 , 580×g , 2 h , 5°C ) using 20 mM potassium phosphate , pH 7 . 2 , 1 mM MgCl2 . The protein concentrations were measured by Coomassie blue method using bovine serum albumin as a standard . The specific infectivity of wt specimen was 1–2×1013 pfu/mg of protein . Purified procapsids had a low wt/revertant background ( titer reduction of 104 on suppressor host PSA and reduction of >107 on nonsuppressor host DS88 ) . For cryo-ET of individual wt PRD1 and Sus1 particles , a 5 µl volume of 10 nm gold fiducial markers ( Aurion BSA gold tracer 10 nm ) was mixed with a 10 µl volume of purified PRD1 sample before vitrification process . We applied 4 µl of sample ( at ∼0 . 6 mg/ml ) to a 200 mesh R2/1 ( or R3 . 5/1 ) holey carbon copper grid ( Quantifoil Micro Tools GmbH , Jena , Germany ) placed in the controlled environment ( 95% relative humidity ) of the Vitrobot ( FEI Inc . ) . After 1 min incubation , the excess of liquid was removed by blotting with filter paper and the grid rapidly plunged into liquid ethane for subsequent data collection . A similar protocol was used for cryo-EM of Sus1 mutants . For PRD1–cell interaction studies by electron and cryo-electron tomography , DS88 and/or E . coli K-12 JE2572 ( RP4 ) were used as a host and grown at 37°C . Cells ( exponential growth phase , OD600 = 0 . 5 ) were infected with wt PRD1 at an MOI of 30 . At 5 and 30 min p . i . , samples were taken and put on ice . The cells were collected by centrifugation ( 2 , 000×g , 3 min ) and were inserted into sample carrier holders for high-pressure freezing using an EMPACT 2 ( Leica ) . The vitrified samples were freeze-substituted at low temperature using a LFS2 ( Leica ) as described in [53] . Finally , the resin blocks were sectioned into 200- and 150-nm-thick sections using a 3 mm diamond knife ( ultra 45° , Diatome ) with an ultramicrotome ( UC6 , Leica ) . For cellular cryo-ET , at ∼30 min p . i . cells were collected by centrifugation ( 2 , 000×g , 3 min ) and vitrified on quantifoil grids using an automatic plunge freezing apparatus [either a vitrobot ( FEI ) or a EM GP ( Leica ) ] . For PRD1 single particle cryo-electron tomography , vitrified grids were cryo-transferred at liquid nitrogen temperature into a 914 high-tilt tomography cryo-holder ( Gatan Inc . ) and viewed on a JEOL JEM-2200FS field emission gun ( FEG ) microscope operated at 200 kV . Tomographic single-axis tilt series of wt and Sus1 particles were collected under low-dose conditions on an UltraScan 4000 , 4K×4K Gatan CCD camera ( Gatan Inc . ) , over a tilt range of ±64 with 1 . 5° increments and at underfocus values ranging from 5 to 8 µm , using the semiautomatic data acquisition software SerialEM [54] . Twenty tilt series at a nominal magnification of 30 , 000 and a binning factor of 2 , thus producing a pixel size of 0 . 76 nm and 28 tilt series at a nominal magnification of 25 , 000 and a binning factor of 2 , thus producing a pixel size of 0 . 88 nm , were collected with SerialEM in low-dose mode . The in-column Omega energy filter helped to record images with improved signal-to-noise ratio by zero-loss filtering with an energy window of 30 eV centred at the zero-loss peak . The total dose used for a tilt series was 90–100 electrons/Å2 . For epon-embedded PRD1-infected cell studies , tilted series were collected from −60 to +60° at two angles ( 90° from one another ) using a dual-axis tomography holder ( 2040 , Fischione ) on a 200 kV FEG microscope ( JEOL 2010F ) equipped with an Ultrascan 4000 4K×4K camera . For vitrified PRD1-infected cells , a data collection strategy similar to that used for cryo-ET of individual PRD1 particles was adopted . Two-dimensional ( 2D ) images were collected on JEOL JEM-2200FS FEG microscope operated at 200 kV at cryogenic temperature and with in-column Omega energy filter , with a 10 eV slit centered at the zero-loss peak . Digital micrographs were recorded under low-dose conditions ( ∼10 e−/Å2 per exposure ) with an underfocus range from 2 . 0 to 6 . 0 µm at a nominal magnification of 40 , 000 with an UltraScan 4000 , 4K×4K CCD camera ( Gatan Inc . ) , resulting in a final pixel size of 2 . 8 Å . For alignment and 3D reconstruction of the tilted series , we used IMOD and/or Tomo3D software [55] , [56] . We used 10 nm gold particles as fiducial markers during alignment , and 3D reconstruction was carried out by weight back-projection and SIRT . No contrast transfer function ( CTF ) correction was applied , thus limiting our reconstructions to the first zero of the CTF ( around ∼1/5 nm in our data-collection setup ) . Of the several reconstructed tomograms we initially selected 1 , 207 PRD1 intact particles with a box of 120×120×120 voxels and 251 volumes corresponding to PRD1 particles with a tube and individual tubes , using a box of 140×140×140 voxels . Subtomogram averaging was carried out using Dynamo software [35] . The resolution of the different subtomogram averaged maps was assessed by Fourier shell correlation ( FSC ) between independent half datasets at the 0 . 5 threshold criterion in Dynamo ( Figure S2 ) . In single-particle averaging of intact PRD1 particles , a full range of rotational searches was performed against a PRD1 template model filtered at 8 . 0 nm with a loose spherical-shell mask including the vesicle and virus spikes ( inner and outer radii of 16 and 49 nm ) . Subsequent refinements of the initial alignment parameters were scaled down to finer search angles and angular intervals but never imposing 60-fold symmetry . A total of 824 subtomograms aligned with a cross-correlation higher than 0 . 5 of the mean cross-correlation with the reference contributed to the nonicosahedral averaged wt PRD1 structure ( Figure S2A ) . For nonintact PRD1 particles , the rough orientations of the single subtomograms relative to the tube were clearly recognizable , enabling the construction of a first set of alignment parameters by manual operation on the particles ( Protocol S2 and Figure S7A ) . As a result of this coarse alignment , a crude averaged model filtered to 8 nm was generated and used as a starting template for the global computerized alignment and averaging protocol . Shifts along the tube long axis were limited , whereas a 360° rotation around this particle orientation was searched; a mask inclusive of capsid and tube was used during this process ( Figure S7A ) . The angular search allowed the particle to pivot inside a cone with an aperture of 60° and rotate inside a full range of 360° . An initial angular sampling of 15° was employed in both cases , with three subsequent coarse-to-fine refinement steps that halved the angular interval and operated a new search around the previous cross-correlation maximum . The set of best orientations provided the alignment parameters that generated the reference used in the next iteration . This procedure was iterated four times onto binned particles and the alignment parameters used to compute a constrained covariance matrix of the initial 251 PRD1-tube and tube sub-volumes . The posterior classification by principal component analysis ( PCA ) using Dynamo software [35] allowed reducing the structural heterogeneity of the selected structures to a set of 174 sub-volumes . Then , further steps with finer sampling were carried out onto fully sized particle ( pivoting range of 20° and azymuthal rotation range of 20° , in both cases with an initial angular interval of 5° ) until no further improvement in the alignment parameters was observed . Then , different subboxing schemes and masks were used for the single-particle subtomogram averaging of the capsid alone , exit-portal , and tube ( Protocol S2 ) . One hundred and seventy-four particles contributed to the subtomogram averaging of the capsid and 138 to the subtomogram averaging of the exit-gate , whereas 33 and 64 , respectively , contributed to the averaged model tube of class 2 and averaged model tube of class 3 ( Figure 5C ) . For the subtomogram averaging of the tubes , an iterative multireference protocol combining alignment and classification was carried out using as initial references four featureless cylindrical shells ( Protocol S2 ) . To validate the results of this alignment , a simulated dataset was created and aligned using the same numerical procedure applied onto the real dataset ( Protocol S3 ) . Digitally recorded 2D images of vitrified PRD1 procapsids were normalized and inspected for the presence of tubes lying with the long axis quasi-orthogonally to the projected plane , a nonpreferential orientation as also observed in tomograms . This subset of views of the tube ( n = 1 , 758 ) was extracted using a box with 80×80 pixel dimensions ( 2 . 8 Å/pixel ) . Then , the selected tubes were low-pass filtered to 15 Å and the rotational power spectra calculated with harmonics from 1 to 9 and classified using a 5×5 KerDenSOM classificatory matrix using XMIPP [57] . Extracted cryo-subtomograms used for the analysis of individual PRD1 particles with tube were denoised by anisotropic nonlinear diffusion using TOMOAND software [58] . To minimize possible docking inaccuracy , we used the icosahedral cryo-EM density ( EMDB ID 1012 ) fitted with the PRD1 atomic model ( PDB ID 1W8X ) as our icosahedral PRD1 reference model . The PRD1 cryo-EM map was then filtered at 6 . 0 nm resolution to match the resolution achieved with our reconstructions ( see the corresponding Fourier shell correlation plots in Figure S2 ) . Using Chimera software [59] “fit-into-map” command , we therefore superimposed our icosahedral PRD1-tube subtomogram averaged capsid density onto the icosahedral cryo-EM capsid map ( ∼95% correlation; we also checked for coarse magnification errors that are <1 . 7% ) . Once the icosahedral version of our cryo-electron tomography reconstruction was oriented onto the PRD1 reference model , we then used it as the target onto which we superimposed our single-particle PRD1-tube averaged map . This allowed the spatial description and localisation of the PRD1 atomic model ( PDB ID 1W8X ) in the context of our subtomogram averaged densities . Dynamo , Chimera , and Amira 5 . 3 . 3 ( Visage Imaging GmbH , Berlin ) software were also used to analyse the averaged maps , to estimate tubes' length and exit angle , and to prepare correspondent figures . | Viral survival and propagation depend on the ability of the viruses to transfer their genetic material to a host cell . Viral genome delivery has been described for viruses that directly enclose their genome in a capsid or nucleocapsid , but not for internal membrane-containing viruses in which the genome is protected by a lipid vesicle enclosed by the icosahedral capsid . The latter infect organisms across the three domains of life . We use a range of electron microscopy techniques to reveal how one such virus , the bacteriophage PRD1 , which uses gram negative bacteria as its host , delivers its double-stranded DNA to the bacteria across the cell envelope . The PRD1 bacteriophage is special in that it doesn't carry a rigid tail; rather it creates a tube tail when needed at the time of infection to pass its DNA through to the host . We now show that this tube formation is accomplished via concerted restructuring of the icosahedral capsid and remodeling of the internal icosahedral protein-rich virus membrane . We also find that this tail tube is studded with membrane-associated proteins and its internal diameter allows one double-stranded DNA chain to be injected . Finally , we capture PRD1 in 3-D with the proteo-lipidic tail piercing the gram-negative bacterial cell and shuttling its viral genome in vivo . These results provide insights into a new mechanism of viral genome delivery . | [
"Abstract",
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"Methods"
] | [] | 2013 | Mechanism of Membranous Tunnelling Nanotube Formation in Viral Genome Delivery |
Vaccination with Mycobacterium bovis bacille Calmette-Guérin ( BCG ) is widely used to reduce the risk of childhood tuberculosis and has been reported to have efficacy against two other mycobacterial diseases , leprosy and Buruli ulcer caused by M . ulcerans ( Mu ) . Studies in experimental models have also shown some efficacy against infection caused by Mu . In mice , most studies use the C57BL/6 strain that is known to develop good cell-mediated protective immunity . We hypothesized that there may be differences in vaccination efficacy between C57BL/6 and the less resistant BALB/c strain . We evaluated BCG vaccine efficacy against challenge with ∼3×105 M . ulcerans in the right hind footpad using three strains: initially , the Australian type strain , designated Mu1617 , then , a Malaysian strain , Mu1615 , and a recent Ghanaian isolate , Mu1059 . The latter two strains both produce mycolactone while the Australian strain has lost that capacity . CFU of both BCG and Mu and splenocyte cytokine production were determined at intervals after infection . Time to footpad swelling was assessed weekly . BCG injection induced visible scars in 95 . 5% of BALB/c mice but only 43 . 4% of C57BL/6 mice . BCG persisted at higher levels in spleens of BALB/c than C57BL/6 mice . Vaccination delayed swelling and reduced Mu CFU in BALB/c mice , regardless of challenge strain . However , vaccination was only protective against Mu1615 and Mu1617 in C57BL/6 mice . Possible correlates of the better protection of BALB/c mice included 1 ) the near universal development of BCG scars in these mice compared to less frequent and smaller scars observed in C57BL/6 mice and 2 ) the induction of sustained cytokine , e . g . , IL17 , production as detected in the spleens of BALB/c mice whereas cytokine production was significantly reduced , e . g . , IL17 , or transient , e . g . , Ifnγ , in the spleens of C57BL/6 mice . The efficacy of BCG against M . ulcerans , in particular , and possibly mycobacteria in general , may vary due to differences in both host and pathogen .
BCG vaccination is widely practiced around the world , primarily to protect against tuberculosis . BCG is a safe vaccine but its efficacy against tuberculosis varies by geographical region and possibly by BCG strain due to mutations related to culturing practices in multiple laboratories for many decades . The current consensus is that it protects against disseminated tuberculosis in young children but that it has limited value in protecting against adult pulmonary tuberculosis , perhaps affording 50% protection at best [1] . On the other hand , large trials [2] have shown that even where BCG has no discernible benefit against tuberculosis , it does protect against leprosy , a disease caused by another mycobacterium , M . leprae . Against yet another mycobacterial disease , known as Mycobacterium ulcerans disease or Buruli Ulcer ( BU ) , retrospective and prospective studies have found that BCG vaccination appears to have protective efficacy for only up to 6 months but there may be longer term protection against severe forms of BU , such as osteomyelitis [3] , [4] , [5] , [6] , [7] . A case report indicated that the Th1 type immunity following BCG vaccination changed to a Th2 type after the onset of BU [8] , [9] . Our preliminary investigation of a toxin-negative Mu strain and studies by others suggested differences in host response between C57BL/6 and BALB/c mice [10] , [11] , [12] , and therefore , studies in mice might help identify the timing and nature of the switch and allow testing of alternative ways to maintain protective immunity . Mycobacterium ulcerans disease was first described in the medical literature in 1948 in Australian patients [13] . The disease still occurs there , primarily in coastal areas visited by vacationers . In contrast , many more cases have been documented to occur in Africa , initially in the Congo [14] and Uganda [15] , and then , increasingly in West Africa where it primarily affects impoverished people in rural riverine and swampy areas [16] , [17] , [18] . The exact mode of transmission is controversial . Bug bites are frequently but not universally recalled . M . ulcerans grows slowly at ∼30–32 °C . It was the first mycobacterium shown to produce a toxin , an immunosuppressive macrolide , named mycolactone [19] , [20] , [21] . Toxin-producing colonies have a yellowish color . The toxin is encoded by the pksA gene , located on a giant plasmid [22] , [23] , [24] . The toxin destroys subcutaneous fat cells , apparently by both apoptotic and necrotic mechanisms [25] , [26] , [27] . Both guinea pigs and mice have been used to model the disease and study the organism [21] , [28] , [29] , [30] . In mice injected in the hind footpad , there is gradual , infection-dose-dependent swelling that becomes severe before the onset of ulceration and , if allowed , may progress to foot and limb loss and death [31] , [32] . Here , we vaccinated BALB/c and C57BL/6 mice with BCG ( Pasteur ) and , after 8 weeks , challenged vaccinated and unvaccinated mice with either M . ulcerans 1059 ( Mu1059 ) , a recent clinical isolate from Ghana , or with Mu1615 , a strain originally isolated from Malaysia in the 1960s . Both strains produce mycolactone and both cause a gradually severe swelling in mouse footpads in unvaccinated mice .
M . ulcerans 1059 ( Mu1059 , a recent clinical isolate from Ghana ) and M . ulcerans 1615 ( Mu1615 , an isolate originally obtained from a patient in Malaysia in the 1960s , [33] were kindly provided by Dr . Pamela Small , University of Tennessee . M . ulcerans 1617 ( Mu1617 , the type strain isolated from a patient in Australia in the 1940s , [13] ) was obtained from the American Type Culture Collection ( ATCC , Manassas , VA ) . Thin layer chromatographic analysis and cytotoxicity assays of ethanolic extracts showed that Mu1059 and Mu1615 , but not Mu1617 , produce mycolactone and kill macrophages and fibroblasts ( [34] , and see Fig . S3 ) . All three strains were passaged in mouse footpads before use in these studies . The bacilli were harvested from swollen footpads at the grade 3 level , i . e . , swelling with inflammation of the footpad and leg [35] . Female BALB/c and C57BL/6 mice , aged 4–6 weeks , obtained from Charles River ( Wilmington , MA ) , were vaccinated subcutaneously with 5 . 8×104 CFU of M . bovis BCG , Pasteur strain , in 0 . 2 ml or with the diluent ( Middlebrook 7H9 , also 0 . 2 ml ) as a sham manipulation , 8 weeks before challenge with M . ulcerans . Mice were inoculated in the right hind footpad with approximately 3×105 in 0 . 03 ml of Mu1059 , Mu1615 , or Mu1617 . At different time points after challenge , mice were sacrificed and footpad tissue was harvested , minced with fine scissors [36] , suspended in 2 . 0 ml PBS , serially diluted , and plated for CFU analysis on Middlebrook selective 7H11 plates ( Becton-Dickinson , Sparks , MD ) . Mice were evaluated for footpad swelling weekly using an established scoring system [35] with grade 1 showing footpad swelling , grade 2 swelling with inflammation , and grade 3 swelling and inflammation of the entire foot [32] . Time to grade 1 swelling was assessed by Kaplan-Meier analysis . All animal procedures were conducted according to relevant national and international guidelines . The study was conducted adhering to the Johns Hopkins University guidelines for animal husbandry and was approved by the Johns Hopkins Animal Care and Use Committee , protocols MO08M240 and MO05M226 . After BCG or sham vaccination , spleens were harvested from mice , placed in 2 . 5 ml RPMI 1640 ( Mediatech , Herndon , VA ) and passed through a 70 µm cell strainer ( BD Falcon 352350 ) into a centrifuge tube . From the suspension , 120 µl was added to 1 . 88 ml of RPMI containing 5% fetal bovine serum and 1% penicillin ( 100 U/ml ) and streptomycin ( 100 µg/ml ) . From this suspension 100 µl was added to triplicate wells of a 96 well plate ( Costar 3595 , Corning , NY ) containing 10 µl of culture filtrate protein of Mtb H37Rv ( CFP , [10 µg/ml] ) or Mtb antigen 85 ( Ag85 ) , also at 10 µg/ml , both supplied by Colorado State University TB Vaccine Testing and Research Materials Contract ( NIH-NIAID N01-AI-40091 ) , or with Concanavalin A ( ConA , Sigma , [2 µg/ml] ) . The cells were incubated at 37 °C for 48 hours before harvesting , pooling , and freezing at −70 °C of triplicate 50 µl supernatants . The remainder of the suspension was used to enumerate BCG CFU . A 23-plex Luminex assay ( Biorad , Hercules , CA ) was used to detect 4 Th1 ( IL2 , IL12b/p40 , IL12p70 , and Ifnγ ) , 4 Th2 ( IL4 , IL5 , IL10 , and IL13 ) , and 4 proinflammatory cytokines ( IL1α , IL1β , IL6 , and Tnfα ) as well as IL17 , IL9 , 6 chemokines ( Cxcl1 , Ccl2 , Ccl3 , Ccl4 , Ccl5 , and Ccl11 ) , and 3 colony stimulating factors ( IL3 , Csf2 , and Csf3 ) . Using aliquots from the same supernatants , Tgfβ was detected using Milliplex beads ( Millipore , Billerica , MA ) . Comparisons were made by the log-rank test for time-to-grade 1 swelling and by 2-way ANOVA for log10 transformed CFU counts and cytokine levels .
Nearly all BALB/c mice developed visible scars at the site of vaccination in the flank ( Fig . 1 ) but such scars occurred less frequently and were smaller in C57BL/6 mice . This observation was assessed and noted for each mouse 13 weeks after vaccination and 5 weeks after M . ulcerans challenge . In all , 95 . 5% of BALB/c mice but only 43 . 4% of C57BL/6 mice had scars after BCG vaccination . No sham-vaccinated mice had scars . C57BL/6 mice are considered to be more resistant than BALB/c mice to intracellular infections with mycobacteria or leishmania species [37] , [38] . Consistent with these observations we found that after subcutaneous M . bovis BCG vaccination , BALB/c mice have higher levels of BCG detectable in the spleen than do C57BL/6 mice ( Fig . 2 A , B , C ) . In addition , the levels persisted longer in BALB/c mice . The number of BCG CFU in the spleen tended to be higher in M . ulcerans-challenged C57BL/6 compared to unchallenged mice ( Fig . 2 B and C ) whereas there was no difference between challenged and unchallenged BALB/c mice . Mice were inoculated with freshly isolated suspensions containing ∼10 AFB/high-power microscopic field or 2 . 4–3×105 M . ulcerans in a volume of ∼0 . 03 ml in the right hind footpad , resulting in an implantation of ∼3 . 1–3 . 2 log10 of the Australian type strain , Mu1617 on day 1 ( Fig . 3A ) . As reported by others ( e . g . , [39] ) there is a lag phase with little or no increase in CFU during the first 2 weeks after challenge , followed by a logarithmic increase accompanied by footpad swelling by week 5 to 6 when the CFU counts reach 105 or higher . For example at week 2 after infection , we detected from ∼3–3 . 5 log10 M . ulcerans CFU in the mouse footpads infected with Mu1059 or Mu1615 , independent of BCG vaccination status ( data not shown ) . At week 6 , after the onset of swelling in the sham-vaccinated mice , marked differences in M . ulcerans CFU counts were observed between BCG-vaccinated and unvaccinated ( i . e . , sham ) BALB/c mice regardless of the infecting M . ulcerans strain ( Mu1617 , p<0 . 01 , Mu 1059 , p<0 . 001 , or Mu1615 , p<0 . 001 , Figure 3 ) . In C57BL/6 mice BCG vaccination did not result in a reduction in Mu1617 ( Fig . 3A ) or Mu1059 CFU ( Fig . 3B ) but did lead to a significant ( p<0 . 01 ) reduction in M . ulcerans 1615 CFU ( Fig . 3C ) in the footpads of mice . In unvaccinated BALB/c and C57BL/6 mice , the median time to grade 1 or higher footpad swelling was ∼5–6 weeks following infection with either of the toxin-producing strains ( Fig . 4A and 4B ) whereas it was 6 . 5 weeks in C57BL/6 mice and 16 weeks in BALB/c mice infected with the non-toxin-producing Mu1617 strain ( Fig . 4C ) . All unvaccinated BALB/c and C57BL/6 mice developed footpad swelling except for 37% of BALB/c mice challenged with the Mu1617 strain . In BCG vaccinated BALB/c mice , the median time to swelling was >26 weeks in mice challenged with the Mu1059 Ghanaian strain ( Fig . 4A ) and 14 weeks with the Mu1615 Malaysian strain ( Fig . 4B ) . Only 23% of vaccinated BALB/c mice developed swelling by week 36 after infection with the toxin free , Mu1617 Australian strain ( Fig . 4C ) . Remarkably , approximately 25% , 50 , or 75% of , vaccinated BALB/c mice infected with Mu1615 , Mu1059 , and Mu1617 , respectively , never developed swelling . In addition , some appeared to self-heal with a regression of the swelling . In contrast , the effect of BCG vaccination on median time to swelling in C57BL/6 mice varied from a delay of only 1 week in mice challenged with the Mu1059 strain ( Fig . 4A ) to a delay of 7 weeks in mice challenged with the Mu1615 and Mu1617 strains ( Fig . 4B and 4C ) . All vaccinated C57BL/6 mice eventually developed swelling regardless of the challenge strain . Taken together , these results suggest that vaccine efficacy varies according to both the mouse strain and the M . ulcerans strain that were tested . At different times after vaccination , splenocytes were assessed for the ability to produce cytokines after restimulation with CFP or Ag85 of Mtb as well as Concanavalin A . The responses to Ag85 correlated very well with those to CFP . Because we tested more time points with CFP , we report , for the sake of simplicity , only those results . Similar results for cytokine production were observed after challenge with either Mu1615 or Mu1059 and , therefore , those data are combined .
BCG vaccination protects BALB/c mice better than C57BL/6 mice from the consequences of M . ulcerans infection . In the case of infection with the Mu1059 isolate from Ghana , C57BL/6 mice were essentially not protected at all whereas most BALB/c remained swelling free . In general , BALB/c mice make a stronger and more sustained cytokine response than do C57BL/6 mice . The most salient difference in cytokine production between the two mouse strains was the IL17 response . IL17 is known to be associated with protection against extracellular fungi and bacteria [40] . Others have also observed differential production of IL17 between C57BL/6 and BALB/c mouse strains [38] . In contrast to our findings of an association between high levels of IL17 and BCG-induced protection from M . ulcerans disease , Lopez Kostka found that BALB/c mice produced “excessive” levels of IL17 , as well as Th2 cytokines , and are more susceptible to cutaneous leishmaniasis after infection with L . major [38] . In the leishmania model , C57BL/6 mice have a strong Th1 response but produce little IL17 . In this model , killing of the organism occurs following Ifnγ production and macrophage activation with elaboration of nitric oxide . BCG , on the other hand , induces granuloma formation that may help contain mycobacteria . Very recently , Okamoto Yoshida et al . reported that mice lacking IL17 , in a C57BL/6 background , fail to produce granulomas after pulmonary BCG infection [41] . Whether subcutaneous BCG vaccination promotes granuloma formation in footpads and protection against M . ulcerans infection requires further investigation . Our findings in BALB/c mice are consistent with those of Coutanceau et al . [10] who also observed a >3 log10 reduction in Mu1615 CFU at the site of infection in mice vaccinated subcutaneously with BCG Pasteur ( Fig . 3C ) . The results here extend the data to C57BL/6 mice in which there was also a 3 . 26 log10 reduction in Mu1615 CFU at 6 weeks after challenge . An earlier study [12] found that in intravenously BCG-vaccinated C57BL/6 mice challenged with M . ulcerans strain 5150 from the Congo , there was only a 1 . 35–1 . 85 log10 reduction in the footpad CFU counts 7 weeks after challenge . We likewise saw a reduction of only 0 . 88 log10 CFU in vaccinated C57BL/6 mice challenged with the Ghanaian Mu1059 strain . However , vaccinated BALB/c mice challenged with Mu1059 showed a 4 . 32 log10 reduction in CFU . These data strongly support the idea that there are host differences in the ability to be protected by BCG from M . ulcerans infection as well as marked differences in the protection conferred against different strains of M . ulcerans . In addition to counting M . ulcerans CFU , we assessed the ability of BCG vaccination to prevent footpad swelling , a clinically observable consequence of M . ulcerans infection in mice . BCG vaccination delayed the onset of footpad swelling in both BALB/c and C57BL/6 mice . However , the delay was greater in BALB/c mice , regardless of the challenge strain and C57BL/6 mice showed only a 1-week delay in swelling when challenged with the Ghanaian Mu1059 strain . These findings support the differences found in CFU and also tend to confirm the difference in host susceptibility to M . ulcerans noted parenthetically by others [10] . Differential susceptibility to mycobacterial infection in mice has been the subject of numerous studies . BALB/c and C57BL/6 mice have very similar survival rates after aerosol infection with M . tuberculosis . Both strains are markedly resistant compared to CBA , DBA/2 , C3H , and 129/SvJ when challenged by the intravenous or aerosol routes . Interestingly , the distinction was overcome by increasing the i . v . challenge dose [42] . This study was followed up by evaluating the ability of BCG vaccination to protect BALB/c and DBA/2 ( both having the same MHC type ) against an intravenous challenge with M . tuberculosis . For both strains there was a ∼10-fold reduction in the number of CFU in the lung 80 days after challenge . However , at this time , there was also a 100-fold difference in the number of CFU in the lungs of the immunized BALB/c and DBA/2 mice . In addition , the DBA/2 mice also had extensive necrotic lesions whereas the BALB/c lesions were more compact and epithelioid like [43] . Similar findings were obtained when comparing vaccinated C57BL/6 mice and the susceptible strains , DBA/2 and CBA/J [44] . Other studies have linked differential susceptibility to matrix metalloproteinases such as Mmp9 [45] . Hence , the finding of a difference in the susceptibility of different mouse strains to mycobacteria is not novel but the difference in susceptibility of BALB/c and C57BL/6 mice , both resistant to M . tuberculosis , to M . ulcerans has not been shown before nor , to our knowledge , has the difference in the ability of BCG vaccination to protect these different mouse strains been examined before . The importance of IL17 may be due to the fact that the intracellular phase is relatively brief after M . ulcerans infection due to toxin-mediated killing of phagocytic cells whereas , in mice , M . tuberculosis infection remains intracellular throughout the course of infection ( unpublished observations and [46] ) . Studies in progress indicate that at week 2 after infection with a mycolactone-producing strain , Mu1615 , the organisms are still largely intracellular . By week 3 , the infection is predominantly extracellular in BALB/c mice , presumably due to the destruction of phagocytes by mycolactone . BCG vaccination may promote IL17 production , particularly in this mouse strain , and enable resistance against extracellular organisms . In contrast , C57BL/6 mice , infected with Mu1617 , which does not produce mycolactone , have abundant organisms that appear to be intracellular , even at 4 weeks after infection . The results of this study suggest that vaccination with BCG may protect some hosts more effectively than others against M . ulcerans infection or disease . In addition , the protection may depend on the strain of M . ulcerans prevalent in a given community . While the benefit of BCG vaccination may be variable , we also found no evidence of vaccination leading to exacerbated disease in this model . | Vaccination with Mycobacterium bovis bacille Calmette-Guérin ( BCG ) is used to reduce the risk of childhood tuberculosis and is reported to have efficacy against two other diseases also caused by mycobacteria , leprosy and Buruli ulcer caused by M . ulcerans . We hypothesized that there may be differences in the effectiveness of BCG vaccination in different mouse strains . We vaccinated two mouse strains with BCG eight weeks before infection with three different strains of M . ulcerans . Two of the bacterial strains make a toxin that is critical for Buruli ulcer disease and the third does not . We observed the progression of disease in vaccinated and mock-vaccinated mice and also evaluated the immune response of the mice . We found that the BALB/c mice respond to BCG vaccination with prominent scars , a vigorous immune response , and delayed or no manifestations of M . ulcerans infection . C57BL/6 mice , on the other hand , usually do not have vaccination scars , make a relatively short-lived and/or weaker immune response , and all show disease at the site of M . ulcerans infection . We conclude that the efficacy of BCG against M . ulcerans , and possibly other diseases , depends on the nature of the host and of the infecting strain of the bacteria . | [
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"epidemi... | 2011 | BCG-Mediated Protection against Mycobacterium ulcerans Infection in the Mouse |
Aspergillus fumigatus is a mold that causes severe pulmonary infections . Our knowledge of how A . fumigatus growth is controlled in the respiratory tract is developing , but still limited . Alveolar macrophages , lung resident macrophages , and airway epithelial cells constitute the first lines of defense against inhaled A . fumigatus conidia . Subsequently , neutrophils and inflammatory CCR2+ monocytes are recruited to the respiratory tract to prevent fungal growth . However , the mechanism of neutrophil and macrophage recruitment to the respiratory tract after A . fumigatus exposure remains an area of ongoing investigation . Here we show that A . fumigatus pulmonary challenge induces expression of the inflammasome-dependent cytokines IL-1β and IL-18 within the first 12 hours , while IL-1α expression continually increases over at least the first 48 hours . Strikingly , Il1r1-deficient mice are highly susceptible to pulmonary A . fumigatus challenge exemplified by robust fungal proliferation in the lung parenchyma . Enhanced susceptibility of Il1r1-deficient mice correlated with defects in leukocyte recruitment and anti-fungal activity . Importantly , IL-1α rather than IL-1β was crucial for optimal leukocyte recruitment . IL-1α signaling enhanced the production of CXCL1 . Moreover , CCR2+ monocytes are required for optimal early IL-1α and CXCL1 expression in the lungs , as selective depletion of these cells resulted in their diminished expression , which in turn regulated the early accumulation of neutrophils in the lung after A . fumigatus challenge . Enhancement of pulmonary neutrophil recruitment and anti-fungal activity by CXCL1 treatment could limit fungal growth in the absence of IL-1α signaling . In contrast to the role of IL-1α in neutrophil recruitment , the inflammasome and IL-1β were only essential for optimal activation of anti-fungal activity of macrophages . As such , Pycard-deficient mice are mildly susceptible to A . fumigatus infection . Taken together , our data reveal central , non-redundant roles for IL-1α and IL-1β in controlling A . fumigatus infection in the murine lung .
The mold Aspergillus fumigatus is one of the leading causes of invasive fungal infections . It is the causative agent of severe pulmonary infections such as invasive pulmonary aspergillosis ( IPA ) , a disease of high morbidity and mortality which affects immunocompromised individuals [1] . IPA has been a disease of growing concern over recent decades due to an increase in the immunocompromised population , specifically caused by advances in immunosuppressive drugs and organ transplantation methods as well as chemotherapy treatments in cancer patients [2] . In addition , there is increasing evidence that IPA can sporadically develop in certain immunocompetent populations [3] . Currently there are no available vaccines for A . fumigatus and anti-fungal drugs have a modest rate of success in limiting high mortality rates typically due to late diagnosis of IPA [1 , 2 , 4] . Moreover , the recent emergence of drug resistance has further limited treatment options in certain clinical cases and geographic areas [5 , 6 , 7] . The concentration of Aspergillus conidia in air samples ranges from 0 . 2–15 conidia/m3 and on a daily basis an individual can inhale hundreds of conidia [8] . In most immunocompetent individuals the conidia are typically removed from the body by physical barriers encountered within the respiratory tract . However , if the conidia escape this primary immune barrier and enter the lung , they will be removed by alveolar macrophages and other resident leukocytes , such as CCR2+ monocytes . Conversely , in an individual lacking a sufficient immune response , Aspergillus conidia are able to swell , germinate , and form hyphae , invading pulmonary tissue with the potential to disseminate systemically [9 , 10] . Our understanding of the inflammatory pathways necessary for an immunocompetent individual to maintain control of A . fumigatus while constantly being exposed to conidia is an ongoing area of investigation . Control of A . fumigatus growth in the lung during invasive infection is highly dependent on rapid recruitment and activation of innate immune cells , including neutrophils [11] , inflammatory monocytes [10 , 12] , NKT cells [13] , and plasmacytoid dendritic cells [14] . The importance of appropriate activation of leukocytes in the control of A . fumigatus is highlighted by patients and mice with chronic granulomatous disease or lacking NADPH oxidase subunits , being highly susceptible to developing IPA after A . fumigatus challenge [15 , 16 , 17] . Furthermore , patients who become neutropenic after chemotherapy for a bone marrow transplant are at a higher risk for developing IPA [18 , 19 , 20 , 21] . In the murine model of A . fumigatus infection , CXCR2 and its ligands are important signaling components for neutrophil recruitment [22 , 23 , 24] . In the absence of CXCR2 signaling during pulmonary A . fumigatus infection , there is a decrease in neutrophil recruitment along with a higher fungal burden and increased mortality rate , similar to a neutropenic model [23] . Additionally , a role for CCR2 signaling has been shown to be necessary to promote recruitment and differentiation of inflammatory monocytes from the bone marrow into CD11b+ dendritic cells upon A . fumigatus infection [10 , 12] . However , the exact sequence of events necessary for the expression of chemotactic molecules for optimal leukocyte recruitment has not been well elucidated . In addition , it has been shown that polymorphisms in the Interleukin ( IL ) -1 gene cluster may be important in determining the susceptibility or resistance to IPA in humans [25 , 26] . The IL-1 gene cluster codes for two pro-inflammatory cytokines , IL-1α and IL-1β , as well as the IL-1 receptor antagonist ( IL-1Ra ) [27] . All three of these IL-1 family members bind to the IL-1 receptor , type I ( IL-1RI ) . IL-1α and IL-1β enhance the immune response while IL-1Ra competitively binds to IL-1RI , thereby preventing the binding of IL-1α and IL-1β [27] . Although IL-1α and IL-1β are both pro-inflammatory cytokines within the same IL-1 cytokine family , they differ in their maturation processes . IL-1α can be released as pro-IL-1α or mature IL-1α after calpain cleavage . In either form it can actively bind to IL-1RI and mediate downstream signaling [27 , 28] . Conversely , IL-1β is first produced as inactive pro-IL-1β which must be cleaved by a caspase-1 containing inflammasome to yield the mature biologically active cytokine [29] . After fungal exposure , IL-1β production has been linked to activation of the NLRP3 inflammasome [30 , 31 , 32 , 33 , 34 , 35 , 36 , 37] . Mice lacking the NLRP3 inflammasome are highly susceptible to disseminated candidiasis [30 , 36 , 37] . However , the role of inflammasome activation by A . fumigatus in vivo is unknown . The role of IL-1α in regulating the pulmonary inflammatory response after infectious challenge is much less understood and is an active area of research . Importantly , several studies have shown that IL-1α and IL-1β can have non-redundant roles in infection and inflammation . Specifically , it has been demonstrated that an increase of IL-1α correlated with early neutrophil recruitment , while IL-1β correlated with macrophage recruitment during later time points in a model of sterile inflammation [38 , 39] . During pulmonary Legionella pneumophila infection IL-1α is essential for early neutrophil responses [40] . In a systemic candidiasis model , IL-1α and IL-1β played non-redundant roles in anti-fungal immunity by enhancing anti-fungal activity of leukocytes and recruitment of neutrophils , respectively [41] . However , the role ( s ) of IL-1 cytokines after challenge with the mold A . fumigatus remains to be fully defined . Here , we delineate the differential roles of IL-1α and IL-1β after in vivo challenge with A . fumigatus and further define the sequence of events required for leukocyte recruitment after A . fumigatus challenge . Specifically , we observed , unlike the diseases caused by the yeast Candida albicans [30 , 36 , 37] , that the inflammasome is not essential for preventing severe invasive pulmonary aspergillosis , but does participate in initiating the full anti-fungal activity of leukocytes . In stark contrast , IL-1α signaling through IL-1RI is crucial for the control of pulmonary A . fumigatus infection through optimal leukocyte recruitment , which correlated with CXCL1 expression . CCR2+ monocytes regulated the early expression of IL-1α and CXCL1 , and promoted early neutrophil accumulation in the airways . Treatment of Il1r1-deficient mice with a chemokine known to enhance neutrophil recruitment enhanced immunity against pulmonary A . fumigatus infection . Thus , our studies define the specific sequence of events regulated by both IL-1α and IL-1β necessary for control of A . fumigatus growth and lung damage within the respiratory tract .
To examine the early pulmonary inflammatory milieu induced after A . fumigatus challenge , bronchoalveolar lavage fluid ( BALF ) was collected 6 , 12 , 24 , and 48 h after intratracheal ( i . t . ) instillation of ∼5×107 conidia of the CEA10 strain of A . fumigatus . Of note , both the inflammasome-dependent cytokines IL-1β ( Fig . 1A ) and IL-18 ( Fig . 1B ) were expressed within approximately 6 h after A . fumigatus challenge . In contrast , IL-1α ( Fig . 1C ) and IL-1Ra ( Fig . 1D ) were expressed in a linearly increasing manner during the first 48 h . Thus , A . fumigatus challenge results in temporally distinct expression of IL-1 cytokine family members . In one cohort of human patients it has been shown that a complex polymorphism in the Il1a , Il1b , and Il1rn genes , which was associated with decreased IL-1 dependent inflammatory events , resulted in increased risk for the development of IPA [25] . Because of this prior clinical observation plus our finding that both IL-1α and IL-1β are produced in the lungs after A . fumigatus challenge ( Fig . 1 ) , we questioned whether IL-1RI signaling was critical in the clearance of A . fumigatus from the lung . To globally test the role of IL-1 signaling in limiting A . fumigatus growth in the respiratory tract of mice , we challenged C57BL/6 and Il1r1-deficient mice with ∼5×107 conidia of A . fumigatus CEA10 delivered via the i . t . route . Subsequently , control of A . fumigatus in the respiratory tract was assessed by histological analysis at 24 , 48 , and 72 h after instillation . Strikingly , Grocott-Gomori methenamine silver ( GMS ) staining of lung tissue from Il1r1-deficient mice revealed the presence of a significant fraction of germinating A . fumigatus conidia at 48 h that was not observed in C57BL/6 mice ( Fig . 2A ) . When the presence of germinating A . fumigatus conidia was quantified over the first 72 h , C57BL/6 mice displayed minimal germination that was ∼4% at 48 h before resolving ( Fig . 2B ) ; in contrast , Il1r1-deficient mice displayed a significant impairment in controlling A . fumigatus germination within 24 h ( Fig . 2B ) . By 48 h , the majority of fungal conidia in Il1r1-deficient mice were germinated ( Fig . 2B ) . High levels of germination were observed in the majority of Il1r1-deficient mice and this was associated with significant mortality in those mice ( Fig . 2C ) . To strengthen our conclusion that IL-1RI signaling was crucial for controlling A . fumigatus germination in the lungs rather than a development issue in the Il1r1-deficient mice , we treated C57BL/6 mice intraperitoneally ( i . p . ) with 200 μg of hIL1ra , which antagonizes IL-1α and IL-1β , or placebo every 24 h starting one day prior to challenging mice with ∼5×107 conidia of A . fumigatus . Lung tissue from hIL1ra-treated C57BL/6 mice revealed the presence of a significant fraction of germinating A . fumigatus conidia at 48 h , which was not observed in placebo treated C57BL/6 mice ( S1 Fig . ) . Taken together , these results strongly support the conclusion that IL-1RI signaling is critical for prevention of A . fumigatus strain CEA10 pulmonary proliferation and host damage . Neutrophils and macrophages are widely acknowledged to be critical effector cells for clearing A . fumigatus from the lungs [42] . Assessing cellular recruitment via differential microscopic counting of cytospins stained with Diff-Quik from the bronchoalveolar lavage fluid at 12 , 24 , and 48 h post-challenge demonstrated a significant impairment in neutrophil recruitment at each time point analyzed , while macrophage recruitment was similar between C57BL/6 and Il1r1-deficient mice at early time points after A . fumigatus challenge , but were decreased by 48 h ( Fig . 2D ) . When inflammatory infiltrates within the BALF and lung parenchyma were assessed at 12 , 24 , and 36 h by flow cytometry a similar decrease in neutrophils in both compartments was observed in the Il1r1-deficient mice ( S2A-S2B Fig . ) , while CD11b+ macrophages ( S2C Fig . ) , CD11c+ alveolar macrophages ( S2D Fig . ) , and CD103+ dendritic cells ( S2E Fig . ) were found at similar levels as observed in C57BL/6 mice . We next questioned whether leukocyte recruitment was diminished in Myd88-deficient mice because it is the key signaling adapter for IL-1RI , as well as TLRs [27 , 43] , and Myd88-deficient mice have an impaired ability to control pulmonary A . fumigatus growth [44] . Indeed , Myd88-deficient mice exhibited defective neutrophil recruitment 12 and 24 h after A . fumigatus instillation , but normal macrophage recruitment at these early time points ( S3 Fig . ) . Thus , mice deficient in Il1r1 and Myd88 are highly impaired in their ability to clear A . fumigatus from the lungs , which correlates with defects in early neutrophil recruitment to the lungs . It is well documented that IL-1β secretion requires the function of the inflammasome [29] and that both the inflammasome and IL-1β are important in limiting systemic fungal infections [30 , 33 , 35 , 36 , 37 , 41 , 45] . Recent in vitro studies have shown that the NLRP3-ASC-Capase1 inflammasome can be triggered by A . fumigatus [31] , but the in vivo relevance of this triggering during A . fumigatus infection remains unknown . Multiple inflammasome complexes exist , but ASC ( Pycard ) is a central adapter protein needed for maturation of IL-1β and IL-18 [29] . Thus , to determine the role of the inflammasome after A . fumigatus challenge , we challenged C57BL/6 and Pycard-deficient mice with ∼5×107 conidia of A . fumigatus CEA10 i . t . ; subsequently , control of A . fumigatus in the respiratory tract was assessed by histological analysis at 24 , 48 , and 72 h after instillation . GMS staining of lung tissue from Pycard-deficient mice revealed the presence of germinating A . fumigatus conidia at elevated frequencies compared to C57BL/6 mice at 48 h ( Fig . 3A-B ) , but this phenotype was less severe than what was observed in Il1r1-deficient mice and did not result in murine mortality ( Fig . 2 ) . When the presence of germinating A . fumigatus conidia was quantified over the first 72 h , C57BL/6 mice display minimal germination that was ∼3% at 48 h ( Fig . 3B ) . Pycard-deficient mice displayed normal control of A . fumigatus germination at 24 h . However , by 48 h impaired control of A . fumigatus germination ( ∼22% ) was observed , but these mice were ultimately able to resolve the A . fumigatus challenge ( Fig . 3B ) . Because , neutrophils and macrophages are widely acknowledged to be critical effector cells for clearing A . fumigatus from the lungs [42] and were diminished in the absence of IL-1RI signaling ( Fig . 2C ) , we next assessed inflammatory cell recruitment in BALF via differential microscopic counting of cytospins stained with Diff-Quik from the bronchoalveolar lavage fluid at 12 , 24 , and 48 h after instillation . Interestingly , C57BL/6 and Pycard-deficient mice demonstrated equivalent neutrophil and macrophage recruitment at each time point analyzed ( Fig . 3C ) . Moreover , when the inflammatory infiltrates within the BALF and lung parenchyma were assessed at 12 , 24 , and 36 h by flow cytometry the number of neutrophils in the BALF and lung parenchyma , CD11b+ macrophages , CD11c+ alveolar macrophages , and CD103+ dendritic cells in the lung parenchyma were found at similar levels in C57BL/6 and Pycard-deficient mice ( S2 Fig . ) . When we examined the expression of IL-1β in the BALF of Pycard-deficient mice , no expression of IL-1β at 12 h was observed while significant levels were detected in C57BL/6 mice ( Fig . 3D ) ; however , when IL-1α was examined in the lung parenchyma we observed equivalent levels of cytokine expression ( Fig . 3E ) , suggesting that IL-1α signaling could still be activated in the Pycard-deficient mice . Since Pycard-deficient mice did not demonstrate impaired leukocyte recruitment after A . fumigatus challenge , we next sought to quantitate the anti-fungal activity of macrophages from C57BL/6 and Pycard-deficient mice . Hyphal damage induced by macrophages was assessed using the XTT hyphal damage assay , which measures fungal cell metabolic activity as an indirect measure of fungal viability [46] . C57BL/6 and Pycard-deficient bone marrow-derived macrophages induced similar hyphal damage when co-cultured with A . fumigatus under normoxic conditions ( Fig . 3F , yellow bars ) . Interestingly , a previous report demonstrated enhanced anti-fungal activity of leukocytes against fungal hyphae under hypoxic conditions [46] , which occurs within the lungs after A . fumigatus challenge and at sites of microbial infection [47 , 48] . Intriguingly , time-points when hypoxia is observed also coincides with the recruitment of inflammatory monocytes to the site of infection [12] . Thus , we sought to test the contribution of the inflammasome to the anti-fungal response of macrophages under hypoxic conditions . Similar to the previous findings [46] , C57BL/6 bone marrow-derived macrophages displayed significantly enhanced anti-fungal activity when cultured in hypoxia ( Fig . 3F ) . In contrast , Pycard-deficient macrophages induced less hyphal damage when co-cultured with A . fumigatus under hypoxic conditions ( Fig . 3F , blue bars ) . Since activation of the inflammasome triggers the release of both IL-1β and IL-18 we next sought to assess which inflammasome-dependent cytokine was responsible for increasing the anti-fungal activity of macrophages in hypoxia . C57BL/6 macrophages were treated with an isotype control antibody , anti-IL1β antibody , or anti-IL18 antibody during the co-culture with A . fumigatus germlings . Subsequently , fungal damage was again assessed by an XTT assay . Macrophages treated with an isotype control antibody display increased anti-fungal activity in hypoxia . This increased anti-fungal activity was lost in the presence of a blocking anti-IL1β antibody , but not a blocking anti-IL18 antibody ( Fig . 3G ) . Collectively , these data demonstrate that mice deficient in Pycard are mildly impaired in their ability to clear A . fumigatus from the lungs , which correlated with in vitro defects in the anti-hyphal activity induced by IL-1β in hypoxia , rather than inflammatory cell recruitment to the lungs . As Il1r1-deficient mice were much less able to control A . fumigatus germination than Pycard-deficient mice ( Fig . 2 & 3 ) and Pycard-deficient mice still produced IL-1α in the lungs ( Fig . 3D ) , we next sought to understand the role IL-1α played in the clearance of A . fumigatus from the lung . To determine the role of IL-1α after A . fumigatus challenge , we treated C57BL/6 mice i . p . with 40 μg of goat IgG or anti-IL1α 24 h prior to and 24 h after challenging mice with ∼5×107 conidia of A . fumigatus . Control of A . fumigatus in the respiratory tract was assessed by histological analysis at 48 h after instillation . GMS staining of lung tissue from anti-IL1α treated C57BL/6 mice revealed the presence of germinating A . fumigatus conidia at significantly higher frequencies than seen in goat IgG treated C57BL/6 mice ( Fig . 4A & B ) . As leukocyte recruitment to the lungs was significantly impaired in Il1r1-deficient , but not Pycard-deficient , mice following A . fumigatus challenge , we next assessed inflammatory cell recruitment to the BALF via differential microscopic counting of cytospins stained with Diff-Quik from the bronchoalveolar lavage fluid at 24 and 48 h post-challenge . Interestingly , anti-IL1α treated C57BL/6 mice demonstrated reduced neutrophil recruitment at 24 h post-A . fumigatus challenge ( Fig . 4C ) . Additionally , treatment of Pycard-deficient mice with anti-IL1α significantly enhanced the susceptibility of those mice to A . fumigatus challenge , mirroring what was found in Il1r1-deficient mice ( S4 Fig . ) . Thus , blocking IL-1α in mice significantly impairs early neutrophil recruitment to the lungs early after A . fumigatus challenge resulting in impaired control of A . fumigatus germination in the lungs . As both Il1r1-deficient mice and anti-IL1α treated C57BL/6 mice displayed significantly decreased cellular infiltration into the BALF ( Fig . 2D and 4C ) , we next sought to understand the roles that IL-1α , IL-1RI , and the inflammasome play in setting up the inflammatory milieu within the lungs . Thus , we challenged four cohorts of mice , C57BL/6 treated with 40 μg of goat IgG , C57BL/6 treated with 40 μg of anti-IL1α , Il1r1-deficient , and Pycard-deficient , with ∼5×107 conidia of A . fumigatus . Twenty-four hours after challenge , the inflammatory milieu in the lung parenchyma was assessed by a 12-plex multiplex cytokine assay . Anti-IL1α treatment , rather than Pycard-deficiency , largely mirrored the inflammatory cytokine defects found in the Il1r1-deficient mice ( Fig . 5 ) fitting with the biological outcomes of A . fumigatus challenge in those mice . Specifically , TNFα , CCL3 , and CCL4 expression was not diminished in the absence of IL-1α , IL-1RI , or ASC ( Fig . 5 ) . Interestingly , CXCL1 and G-CSF expression were significantly reduced in Il1r1-deficient mice . CXCL1 expression was almost entirely dependent on IL-1α signaling ( Fig . 5 ) , while G-CSF expression trend to being dependent on both IL-1α and ASC in an additive manner ( Fig . 5 ) . A similar trend , as observed with CXCL1 , was seen with IL-6 and CCL2 , but it did not reach significance ( Fig . 5 ) . Thus , blocking IL-1α in mice significantly decreased the abundance of CXCL1 in the lungs , which correlates with the decreased neutrophil recruitment in Il1r1-deficient mice . As IL1α was necessary for optimal CXCL1 expression and neutrophil infiltration into the BALF ( Fig . 4C & 5 ) , we next sought to identify potential cellular sources of IL-1α in response to pulmonary challenge with A . fumigatus . Within the lung of a naïve mouse several potential sources of IL-1α exist including: non-hematopoietic cells ( epithelial and endothelial cells ) , alveolar macrophages in the airway spaces , and CCR2+ monocytes within the lung parenchyma . During pulmonary Mycobacterium tuberculosis infection two distinct populations of myeloid cells co-express IL-1α and IL-1β: inflammatory monocytes which are CD11b+ CD11c− Ly6c+ and monocytic dendritic cells which are CD11b+ CD11c+ [49] . In response to pulmonary A . fumigatus challenge , CCR2+ inflammatory monocytes are rapidly recruited to the lung and give rise to monocyte-derived dendritic cells that play essential roles in innate defense against invasive aspergillosis [12] . Interestingly , both CCR2+ inflammatory monocytes and monocyte-derived dendritic cells show increased transcription of the Il1a gene at 48 h post-A . fumigatus challenge [12] , but whether lung-resident CCR2+ monocytes could contribute to IL-1α production at early times after infection was not explored . Thus , we challenged either C57BL/6 or CCR2-depleter mice [10 , 50] , which had been treated one day prior with 250 ng of diphtheria toxin , with ∼5×107 conidia of A . fumigatus . To confirm depletion of the CCR2+ monocytes we quantified CCR2+ inflammatory monocytes ( identified as CD45+CD11b+Ly6C+Ly6G− ) in the BALF and lung parenchyma 8 h after A . fumigatus challenge by flow cytometry . We found that diphtheria toxin had no effect on CCR2+ monocytes in control animals , while CCR2-depleter mice treated with DT had no detectable Ly6C+ inflammatory monocytes , in the BALF or lung parenchyma as expected ( Fig . 6A ) [12] . We found that IL-1α protein levels were significantly decreased when CCR2+ monocytes were absent ( Fig . 6B ) consistent with the idea that lung-resident CCR2+ inflammatory monocytes are important for producing and/or inducing expression of this cytokine in the lung at early times after infection . Since blocking IL-1α in mice significantly decreased the expression of CXCL1 in the lungs ( Fig . 5 ) , we next asked whether CXCL1 protein levels were diminished in the lung parenchyma of the CCR2-depleter mice . We found that CXCL1 protein levels were also significantly decreased in the absence of CCR2+ monocytes ( Fig . 6C ) . Thus , CCR2+ monocytes are important regulators of the early expression of IL-1α and CXCL1 . Consistent with the importance of these factors in promoting early neutrophil recruitment ( Fig . 2 and 4 ) , diminished IL-1α and CXCL1 levels in CCR2-depleter mice correlated with diminished recruitment of neutrophils to the airways 8 h after A . fumigatus challenge ( Fig . 6D ) . Thus , CCR2+ monocytes are important regulators of the early expression of IL-1α and CXCL1 , which are required for optimal recruitment of neutrophils at early times after A . fumigatus challenge . As both Il1r1-deficient mice and anti-IL1α treated mice displayed significantly decreased cellular infiltration into the BALF ( Fig . 2D and 4C ) that correlated with decreased abundance of CXCL1 ( Fig . 5 ) , we next sought to test whether immunotherapy which enhances neutrophil accumulation in the lungs , such as CXCL1 supplementation , could enhance control of A . fumigatus growth in the Il1r1-deficient mice . We challenged either C57BL/6 or Il1r1-deficient mice with ∼5×107 conidia of A . fumigatus . Three hours after challenge mice were treated i . t . with either PBS or 0 . 5 μg CXCL1 . As expected , Il1r1-deficient mice displayed a significant impairment in controlling A . fumigatus germination at 48 h when compared with C57BL/6 mice ( Fig . 7A-B ) . Provision of CXCL1 to Il1r1-deficient mice could partially rescue control of A . fumigatus germination in the lungs , while no enhancement in control of fungal growth was observed in the CXCL1 treated C57BL/6 mice ( Fig . 7A-B ) . Furthermore , provision of CXCL1 i . t . rescued the impairment of anti-IL1α treated C57BL/6 mice in controlling A . fumigatus infection ( S5A Fig . ) . As expected , twenty-four hours after challenge the recruitment of neutrophils , but not macrophages , to the BALF in Il1r1-deficient mice was enhanced by the provision of CXCL1 ( Fig . 7C ) . Additionally , neutrophil recruitment to the BALF in anti-IL1α treated C57BL/6 mice was significantly enhanced ( S5B Fig . ) . While CXCL1 provision enhanced neutrophil accumulation in the airways of Il1r1-deficient mice , we also sought to test whether the anti-hyphal activity of neutrophils was altered in the absence of IL-1RI signaling but exogenous addition of CXCL1 . Hyphal damage induced by neutrophils isolated from the bone marrow of respective mouse genotypes was assessed using the XTT hyphal damage assay [46] . C57BL/6 bone marrow neutrophils induced robust hyphal damage when co-cultured with A . fumigatus , which was not further enhanced by treated with 50 nM of CXCL1 ( Fig . 7D ) . Interestingly , Il1r1-deficient bone marrow neutrophils induced significantly less damage to A . fumigatus hyphae than was observed with C57BL/6 bone marrow neutrophils ( Fig . 7D ) . In contrast to the treatment of C57BL/6 bone marrow neutrophils , treatment of Il1r1-deficient bone marrow neutrophils with 50 nM of CXCL1 significantly enhanced the anti-hyphal activity of those cells ( Fig . 7D ) . When cell death and endothelial/epithelial cell leakage were assessed in vivo by lactate dehydrogenase ( LDH ) and albumin measurement , respectively , in the BALF both markers were increased in the absence of IL-1RI ( Fig . 7E-F ) . CXCL1 supplementation reduced both markers , but albumin levels were more dramatically reduced than LDH levels ( 71% versus 32% , respectively ) ( Fig . 7E-F ) . Thus , provision of CXCL1 could significantly enhance neutrophil recruitment to the lungs in the absence of IL-1α signaling and enhanced the in vitro anti-hyphal activity of Il1r1-deficient bone marrow neutrophils , which together ultimately resulted in a partial repair of the A . fumigatus control mechanisms in the Il1r1-deficent lungs .
In this study , we uncover an essential function for IL-1RI in preventing fungal proliferation and host damage in murine lungs . We have demonstrated a novel dichotomy for the IL-1 cytokines in regulating the innate immune response induced by A . fumigatus . Specifically , IL-1α is required for initiating the correct inflammatory signals necessary for optimal leukocyte recruitment , while the inflammasome and IL-1β was necessary for optimal anti-fungal activity against fungal hyphae . We have elucidated that IL-1α plays the dominant role in activating IL-1RI signaling which results in amplified CXCL1 expression , which correlated with optimal leukocyte recruitment to the respiratory tract . CCR2+ monocytes were important cells in regulating the early production of IL-1α , CXCL1 , and neutrophil recruitment . Taken together , our data demonstrate that signaling through IL-1RI by both IL-1α and IL-1β was necessary for optimal control of A . fumigatus pulmonary challenge to prevent IPA development . IL-1RI signaling was essential in resisting pulmonary A . fumigatus challenge in our studies , as demonstrated by Il1r1-deficient mice being unable to resist fungal growth resulting in significant mortality in those animals . This finding is consistent with results reported by Pearlman and colleagues who also found that Il1r1 was needed to prevent the development of A . fumigatus induced keratitis [51] . Moreover , van de Veerdonk and colleagues have recently shown that a polysaccharide fungal virulence factor , galactosaminogalactan ( GAG ) , from A . fumigatus induces the expression of IL-1Ra , which antagonizes IL-1 signaling resulting in enhanced susceptibility to IPA [52] . Gresnigt et al demonstrated that GAG pretreatment of BALB/c mice resulted in more fungal growth associated with impaired neutrophil recruitment , which was completely dependent on IL-1Ra expression [52] . However , the importance of GAG induction of IL-1Ra during a live pulmonary A . fumigatus infection remains unknown . GAG expression might actually be reduced at specific infection sites during in vivo A . fumigatus challenge because hypoxia , which occurs after A . fumigatus challenge [47] has been observed to reduce GAG production [46] . In general , the temporal and spatial dynamics of fungal cell wall PAMPs in vivo during an active infection is not fully understood and likely complicated by the heterogeneous nature of the lung and infection site microenvironments . Downstream of IL-1RI the proximal signaling adapter to propagate IL-1 signaling is MyD88 . Similar to our observation with Il1r1-deficient mice , Marr and colleagues [44] and Hohl and colleagues ( Jhingran A . et al , in press ) have found the Myd88-deficient mice are more susceptible to A . fumigatus challenge . Additionally , impaired control of pulmonary histoplasmosis and disseminated candidiasis was observed in Il1r1-deficient and Il1a/Il1b-doubly deficient mice , respectively [41 , 45] . While our studies and the studies just discussed strongly support a role for IL-1RI signaling in limiting IPA , and other invasive fungal infections , Romani and colleagues have observed that Il1r1-deficient mice were more resistant to pulmonary A . fumigatus challenge [53] . The difference with our study is potentially due to the A . fumigatus strain studied , as Romani and colleagues have shown that different A . fumigatus strains have diverse abilities to induce pathology and immune responses [54] . Importantly , the infection models studied are significantly different , with Romani and colleagues utilizing a cyclophosphamide-induced immunosuppression model with Aspergillus conidia delivered on 3 consecutive days intranasally [53] , while our studies used immunocompetent mice and a single dose of Aspergillus conidia given intratracheally . Additionally Bellocchio et al . [53] , reported that histological analyses in the Il1r1-deficient mice revealed “numerous fungal elements in the relative absence of signs of inflammatory pathology” which is consistent with the results we report here in our experimental model . Murine mortality in infectious disease models can result from direct pathogen mediated damage or immunopathogenesis , and it is unclear , in this regard , how our models differ . What appears to be clear , however , is that in the absence of IL-1RI signaling , Aspergillus proliferation increases in vivo . Taken together , all these findings demonstrate that the IL-1 signaling pathway is likely central for resistance to fungal diseases , but their role during immunosuppression and frequency of fungal exposure/quantity may differ , warranting further exploration of the IL-1 cytokine family in each clinically relevant model of IPA . In further support of our observation , the protective role of IL-1 cytokines in anti-fungal immunity uncovered in our study using the murine model of A . fumigatus infection is likely to be operational in humans as indicated by genetic linkage studies . First , individuals with SNPs in the IL-1 gene cluster , which are associated with decreased IL-1 dependent inflammatory events , were at increased risk for the development of IPA [25 , 26] . Second , polymorphisms in the CIAS1 gene play a central role regulating inflammasome activity and IL-1β production , which can alter the risk of a subset of patients to developing recurrent vulvovaginal candidiasis [55] . Third , macrophages from patients with chronic cavitary pulmonary aspergillosis ( CCPA ) had prolonged expression of Il1a and Il1b after A . fumigatus treatment when compared to healthy controls and SNPs in the Il1b and Il1rn loci are associated with susceptibility to developing CCPA [56] . Thus , targeting the IL-1 cytokine pathways in humans could be important in managing fungal infections . In previous papers exploring the role of MyD88 during A . fumigatus [44 , 51] it was shown that fungal growth was not controlled , but the mechanism impaired in the absence of IL-1RI and MyD88 signaling remains an open question . In this study and a parallel study by Jhingran et al ( in press ) it was demonstrated that MyD88 and IL1RI mediated signals are necessary for optimal leukocyte recruitment after pulmonary A . fumigatus challenge , which is needed for preventing the development of IPA . Analogously , in the A . fumigatus keratitis model both Myd88- and Il1r1-deficient mice demonstrated reduced cellular infiltrate early after inoculation [51] . However , why the lack of IL-1RI or MyD88 signaling results in decreased cellular infiltrates was an open question . Interestingly , we found a decrease in the expression of the chemokine CXCL1 in Il1r1-deficient mice , which others have also observed in challenged Myd88-deficient mice [44] ( Jhingran A . et al , in press ) . CXCL1 , together with CXCL2 and CXCL5 , are ligands for CXCR2 and are key chemoattractants for recruitment of neutrophils . Administration of a blocking anti-CXCR2 antibody or genetic ablation of Cxcr2 has been shown to exacerbate mortality and delay neutrophil recruitment following pulmonary A . fumigatus challenge [23 , 24] . Moreover , transient over-expression of CXCL1 in CC10-expressing lung epithelial cells resulted in significantly enhanced leukocyte accumulation and reduced fungal burden [22] . Correspondingly , when we treated Il1r1-deficient mice with recombinant murine CXCL1 we observed significantly enhanced neutrophil accumulation . In addition , Il1r1-deficient bone marrow neutrophils displayed decreased anti-hyphal activity in vitro , which was restored by treatment with CXCL1 . These data demonstrate that both IL-1RI and CXCL1 signaling is critical in not only enhancing neutrophil recruitment to the airways in the Il1r1-deficient mice , but also in inducing the optimal anti-hyphal state of the recruited neutrophils . While the mechanism behind CXCL1 mediated anti-hyphal activity in our model is unknown , neutrophils from Cxcl1-deficient mice have an impaired reactive oxygen response in a polymicrobial sepsis model [57] . Moreover , Cxcl1-deficient neutrophils stimulated with Klebsiella pneumoniae had reduced expression of p67phox and p47phox and reduced production of myeloperoxidase , nitric oxide , and hydrogen peroxide , which results in decreased killing of Klebsiella pneumoniae by the neutrophils [58] . Finally , IL-8 has been shown to be important for priming the human neutrophils reactive oxygen burst [59] . Thus , our data supports a model where IL-1RI signaling is critical for optimal neutrophil recruitment and activation of their anti-hyphal activity in part through the regulation of CXCL1 abundance . Further support for this conclusion comes from a recent analysis of mice with a myeloid deficiency of the transcriptional regulator HIF1α . Loss of myeloid HIF1α results in severe susceptibility to the same strain of A . fumigatus utilized here in part through reduction in neutrophil recruitment . Importantly , loss of HIF1α resulted in decreased IL1-α and CXCL1 levels after A . fumigatus challenge similar to what we observed in our studies [60] . Interestingly , other inflammatory pathways are also temporally regulating neutrophil recruitment after A . fumigatus challenge , because Card9-deficient mice had a late defect in neutrophil recruitment that was associated with a more global diminution of the inflammatory milieu [61] . In addition to the early defect in neutrophil recruitment Il1r1-deficient mice also had decreased macrophage recruitment to the airways by 48 h post-inoculation . The reason for this is unknown at this time , but it is known that G-CSF deficient mice have monocyte defects and our cytokine analysis demonstrated that Il1r1-deficient mice had significantly lower level of G-CSF in the airways [62] . Thus , further studies exploring the regulation of multiple neutrophil chemotactic pathways , such as CXCR2- , CCR1- , IL17- , leukotriene- , and complement-dependent pathways , and monocyte chemotactic pathways , such as G-CSFR—and CCR2-dependent pathways , are needed after pulmonary fungal challenge . IL1RI , together with IL1RAcP , is the high-affinity receptor for both IL-1α and IL-1β [27] . The maturation and secretion of IL-1α and IL-1β is known to be regulated by distinct proteolytic pathways dependent on calpain and caspase-1 , respectively [27 , 63] . Numerous fungal pathogens have been shown to activate the inflammasome resulting in the production of IL-1β [30 , 31 , 32 , 33 , 34 , 35 , 36 , 37] . Importantly for our studies , others have demonstrated that the NLRP3-ASC-Caspase1 inflammasome could be activated by A . fumigatus [31] , but the in vivo relevance of that finding was unknown . Control of C . albicans infection , which also activated the NLRP3-ASC inflammasome , was highly dependent on NLRP3 and IL-1β [30 , 36 , 37 , 41] . In sharp contrast , our current results indicate that the inflammasome only plays a modest role in the control of pulmonary A . fumigatus growth . In our experiments , neutrophil recruitment in mice lacking the inflammasome was completely normal , which is in contrast to C . albicans infection where mice deficient in IL-1β displayed a significant reduction in neutrophil recruitment [41] . Furthermore , antibody blockade of IL-1β during pulmonary Histoplasma capsulatum infection resulted in decreased survival associated with decreased recruitment of Gr-1+ cells early and CD4+ cells late to the lungs of challenged animals [45] . Thus , we were surprised to observe such a dominant role for IL-1α in regulating early leukocyte recruitment following pulmonary A . fumigatus challenge , which correlates with its regulation of the chemokine CXCL1 . In support of this finding , during sterile inflammation the importance of IL-1α in regulating neutrophil recruitment is unquestionable [38 , 39] . It has also been demonstrated that IL-1α plays a critical role during murine L . pneumophila infection , initiating neutrophil recruitment and the inflammatory response early after infection [40] . Others have previously shown that IL-1RI and MyD88 expression within a radioresistant population of cells was essential for optimal expression of CXCL1 and CXCL2 during L . pneumophila infection [64] . Interestingly , in their parallel study Hohl and colleagues found that IL-1RI/MyD88 signaling in a radioresistant cell population was necessary for optimal CXCL1 expression and neutrophil recruitment early after pulmonary A . fumigatus challenge ( Jhingran A . et al , in press ) . Because of the early importance of IL-1 cytokines in regulating the pulmonary anti-fungal immune response , non-hematopoietic cells ( epithelial or endothelial cells ) or lung-resident myeloid cells could represent potential sources of IL-1α and IL-1β after A . fumigatus challenge . During pulmonary Mycobacterium tuberculosis infection two distinct populations of myeloid cells co-express IL-1α and IL-1β: inflammatory monocytes which are CD11b+ CD11c− Ly6c+ and monocytic dendritic cells which are CD11b+ CD11c+ [49] . After pulmonary A . fumigatus challenge both inflammatory monocytes and monocytic dendritic cells are found in the lung parenchyma and both show increased transcription of the Il1a gene [12] . Here our data demonstrates that CCR2+ monocytes are at least one of the important cell types regulating the early expression of IL-1α and CXCL1 , as well as neutrophil recruitment at 8 hpi . However , in the absence of CCR2+ monocytes there is still a significant amount of IL-1α and CXCL1 produced in the lungs after A . fumigatus challenge , thus there are likely multiple sources of IL-1α that can regulate early pulmonary neutrophil accumulation . Moreover , by 48 h after infection CXCL1 levels and neutrophil recruitment to the lung is unaffected in CCR2-depleter mice [12] , thus suggesting that distinct mechanisms of neutrophil recruitment are operational at various times after infection . This is supported by observation that Myd88-deficient and Card9-deficient mice have early or late defects in neutrophil recruitment , respectively ( Jhingran A . et al , in press and [61] ) . In our experiments the inflammasome and IL-1β appear to regulate the anti-fungal activity of macrophages against hyphae , especially under hypoxic conditions . This enhancement of anti-fungal activity in hypoxic microenvironments is physiologically and clinically important because hypoxia can be generated within the lungs of mice with IPA [47] , which is coincident with inflammatory monocyte arrival to the lungs [12] . Understanding how hypoxia can enhance the anti-fungal activity of macrophage in an inflammasome and IL-1β dependent manner will be important in understanding how macrophages limit fungal growth . Interestingly , a recent paper from Torres et al demonstrated that acidosis , which can be driven by hypoxia , resulted in increased IL-1β production in response to P . aeruginosa challenge [65] . Perhaps somewhat surprisingly , in the absence of MyD88 anti-fungal activity against A . fumigatus conidia remains intact ( Jhingran A . et al , in press ) . It has been shown in other fungal pathogens that IL-1β treatment of human peripheral blood leukocytes enhances their anti-fungal activity against Paracoccidiodies brasiliensis [66 , 67] . Additionally , Il1r1- and Nlrp3-deficient macrophages have impaired antifungal activity against P . brasiliensis [34] . In contrast , during disseminated candidiasis Il1a-deficiency was associated with decreased anti-fungal activity of leukocytes [41] . Thus , studies designed to understand the differential dependencies of the IL-1 cytokines in regulating leukocyte recruitment and anti-fungal activity during a range of fungal diseases and morphological forms are needed . In addition to understanding the cellular source of IL-1α and IL-1β , understanding the inflammatory pathways leading to expression of IL-1α and IL-1β are essential to our understanding of resistance to IPA . In the absence of dectin-1 signaling there is decreased expression of both IL-1α and IL-1β [68 , 69] . The loss of HIF1α in the LysM-expressing cells also resulted in decreased IL-1α levels after A . fumigatus challenge [60] , which can be regulated by dectin-1 agonists such as β-glucan [70] . Pulmonary A . fumigatus infection results in significant tissue damage and cell death , but the exact type of cell death is not known . Moreover , the phenotype of cell death will be shaped by the hypoxic microenvironment found during IPA . The type of cellular death occurring in vivo during A . fumigatus will have important immunological impacts shaping the early IL-1α and IL-1β response because necrotic cell death favors IL-1α release while pyroptosis favors IL-1β release [71] . Interestingly , C . albicans mutants with defects in inducing pyroptosis also demonstrated defects in inducing IL-1β secretion , but IL-1α release was not examined [72] . Additionally , understanding how deficiencies in PRR signaling alters the overall inflammatory response will be crucial as patients with SNPs in PRRs are known to have elevated risks for developing IPA [73] . Our data demonstrate that in the Pycard-deficient mice there are elevated levels of TNFα , CCL3 , and CCL4 . One explanation for observing elevated levels of TNFα , CCL3 , and CCL4 could be the range or degree that PRRs are being engaged in the Pycard-deficient mice and/or temporal and spatial dynamics of fungal cell wall PAMP engagement with PRRs in vivo that are not fully understood and further complicated by a PRR known to be engaged during infection now being absent . It is well defined that prolonged corticosteroid treatment increases susceptibility of hosts to IPA [74] . Interestingly , dexamethasone induces the expression and release of IL-1RII [75] . IL-1RII is known to limit the activity of IL-1 cytokines and/or sequester IL-1α protein in the cytosol , preventing the cleavage of IL-1α by calpain [63] . Dexamethasone has also been shown to impair IL-1α and IL-1β secretion from human mast cells in response to Pseudomonas aeruginosa stimulation [76] . Moreover , dexamethasone treatment of bronchoalveolar macrophages prior to treatment with A . fumigatus conidia significantly impaired their release of IL-1α [77 , 78] . Because we have uncovered such a prominent role for IL-1α in controlling pulmonary A . fumigatus challenge , future studies exploring the cleavage status of IL-1α and expression of IL-1RII in clinically relevant models are critical . Finally , the importance of appropriate activation of leukocytes in the control of A . fumigatus is highlighted by patients with chronic granulomatous disease being highly susceptible to A . fumigatus [15 , 16 , 17] . Interestingly , CGD patients or mice are typically in a hyperinflammatory state , which is linked to inflammasome activity and IL-1β expression [79 , 80] . Further , blockade of IL-1 cytokines in p47phox-deficient mice through treatment with hIL1ra results in improved control of A . fumigatus [79] . Together , these studies demonstrate that further exploration of the positive and negative regulators of IL-1 signaling during invasive fungal infections is needed . Moreover , it is critical that we continue to explore the regulation of the inflammatory response induced in each of the different subpopulations of hosts susceptible to developing invasive fungal infections in order to develop patient specific novel immunotherapeutic approaches that could complement treatment with anti-fungal agents .
C57BL/6J mice were bred in-house . Pycard ( ASC ) -deficient and Myd88-deficient mice were originally provided by Dr . Vishiva Dixit ( Genentech ) and Dr . Mark Jutila ( Montana State University ) , respectively . Il1r1-deficient ( Stock #003245 ) and C57BL/6 ( Stock #000664 ) mice were originally purchased from Jackson Laboratories . Mouse strains were then bred in-house . The CCR2-depleter ( CCR2-DTR ) strain was generated on the C57BL/6 background as previously described [10 , 50] . Control animals for CCR2+ monocyte depletion experiments were sex—and age-matched , non-transgenic littermates . All mice were 8–10 weeks of age at the time of infection . All animal experiments were approved by the Montana State University or Rutgers University Institutional Animal Care and Use Committee . A . fumigatus strain CEA10 or Af293 was grown on glucose minimal media ( GMM ) agar plates for 3 days or Sabouraud dextrose agar ( SDA ) for 7–10 days at 37°C , respectively . Conidia were harvested by adding 0 . 01% Tween 80 to plates and gently scraping conidia from the plates using a cell scraper . Conidia were then filtered through sterile Miracloth , were washed and resuspended in phosphate buffered saline ( PBS ) , and counted on a hemacytometer . Mice were challenged with A . fumigatus conidia by the i . t . route . Mice were anesthetized with 2 . 5% 2 , 2 , 2-tribromoethanol or a Ketamine/Xylazine solution given i . p . ; subsequently , mice were challenged i . t . with ∼5 × 107 A . fumigatus conidia in a volume of 100 μl . At the indicated time after A . fumigatus challenge , mice were euthanized using a lethal overdose of pentobarbital . Bronchoalveolar lavage fluid ( BALF ) was collected by washing the lungs with 2 ml of PBS containing 0 . 05M EDTA . BALF was clarified by centrifugation and stored at −20°C until analysis . BAL cells were resuspended in 200 μl of PBS and total BAL cells were determined by hemacytometer count . BAL cells were subsequently spun onto glass slides using a Cytospin4 cytocentrifuge ( Thermo Scientific ) and stained with Diff-Quik stain set ( Siemens ) for differential counting . For histological analysis lungs were filled with and stored in 10% buffered formalin phosphate for at least 24 hours . Lungs were then embedded in paraffin and sectioned into 5-micron sections . Sections were stained with H&E and GMS using standard histological techniques to assess lung inflammatory infiltrates and fungal germination , respectively . For cytokine analysis lungs were homogenized in 2 ml of PBS . After clarification , lung homogenates were stored at −20°C until analysis . For IL-1α neutralization studies , normal goat IgG control and anti-mIL-1α neutralizing antibody were purchased from R&D systems . IgG control or anti-mIL-1α neutralizing antibody were administered i . p . at 40 μg per mouse . Administration of neutralizing antibody was given every other day , beginning the day prior to A . fumigatus challenge . For CXCL1 reconstitution studies , recombinant murine CXCL1 was purchased from PeproTech . CXCL1 was administered i . t . at 0 . 1–0 . 5 μg per mouse and was given 3 hours after A . fumigatus challenge . For the hIL1ra studies , recombinant hIL1ra and the appropriate placebo ( Amgen ) were kindly provided by Dr . Charles A . Dinarello . The hIL1ra and placebo were administered i . p . at 200 mg per mouse given at −24 , 0 , and +24 h relative to A . fumigatus challenge . For depletions of CCR2+ cells , CCR2-DTR mice and control littermates received 250 ng of diphtheria toxin i . p . one day prior to infection . Diphtheria toxin was purchased from List Biological Laboratories ( Campbell , CA ) and reconstituted at 1 mg/ml in PBS . Aliquots were stored at −80°C . The specificity and efficiency of depletion in the lung was confirmed by flow cytometry . To assess lung damage , bronchoalveolar lavage fluid was analyzed by measuring lactate dehydrogenase levels using a CytoTox 96 Cytotoxicity Assay ( Promega ) following the manufacturer’s instructions . To assess vascular/pulmonary leakage , bronchoalveolar lavage fluid was analyzed using an Albumin BCG Reagent Set ( Eagle Diagnostics ) . A standard curve was made by diluting the calibrator in PBS . Then 100 μl of sample or standard was transferred to a 96 well flat-bottomed plate , mixed with 100 μl of BCG reagent , let sit at RT for 5 min and then read on a plate reader at 630 nm . After collection of the BAL fluid , lung samples were minced in RPMI containing 100 units/ml of collagenase ( Gibco ) at 37°C for 60 minutes , followed by disruption through a 40-μm filter . After which , red blood cells were lysed using a Tris ammonium chloride solution . Staining of ∼107 cells was performed in 200 μl of PBS containing 2% bovine serum and 2 mM EDTA . For analysis of leukocytes , antibody staining was both conducted at 4°C for 30 minutes . Phenotypic analysis of leukocytes was conducted using a panel of cell surface markers: CD11b , CD11c , Ly6g , Ly6c , 7/4 , CD19 , and I-A/I-E , as previously described [10] . All antibodies used for analysis were purchased from Biolegend , BD Biosciences , eBioscience or Novus Biologicals . After staining , cells were washed and fixed with 1% paraformaldehyde in PBS . Fluorescent intensities were measured using an LSR ( BD Biosciences ) and data were analyzed using FlowJo software ( Tree Star ) . Bronchoalveolar lavage fluid and lung homogenates from C57BL/6 mice challenged with A . fumigatus for 6 , 12 , 24 , and 48 h were initially analyzed for cytokines and chemokines using ProcartaPlex Mouse Cytokine & Chemokine 36-plex ( Affymetrix-eBioscience ) . IL-1Ra levels were determined by ELISA ( R&D Systems ) . Plates were read using a BioPlex 200 ( Bio-Rad ) or a SpectraMax Paradigm plate reader ( Molecular Devices ) . Femurs and tibias from 8–10 week old mice were obtained and centrifuged to collect bone marrow . Cells were resuspended in media containing RPMI 1640 , 2 mM L-glutamic acid , 50 mg/l gentamycin , 100 U/ml penicillin/streptomycin , 30% L929 cell supernatant , 20% FBS and 0 . 0004% 2-ME . On day 3 fresh medium was added to the cultures . Cells were incubated for a total of 6 days at 37°C and 5% CO2 . Bone marrow neutrophils were isolated from femurs and tibias from 8–12 week old C57BL/6 and Il1r1-deficient mice as previously described [60] . Briefly , single cell suspensions of bone marrow in HBSS containing 0 . 1% FBS and 1% glucose were resuspended in 3 ml of 45% Percoll ( GE Healthcare ) . A discontinuous Percoll gradient was set-up consisting of ( top to bottom ) 3 ml 45% , 2 ml 50% , 2 ml 55% , 2 ml 62% , and 3 ml 81% . Gradients were then centrifuged for 30 min at 1600 × g in a Sorvall Legend Mach 1 . 6R benchtop centrifuge . Bone marrow neutrophils were collected from the 62%/81% border and washed with HBSS before counting and viability assessment . An XTT assay was used to measure fungal metabolic activity as previously described [46] . Bone marrow derived macrophages and CEA10 germlings were incubated together in normoxic or hypoxic conditions at a 10:1 ( effector:target ) ratio for 5 hours . Bone marrow neutrophils and CEA10 germlings were incubated together in normoxic conditions at a 10:1 ( effector:target ) ratio for 2 hours with or without 50 nM CXCL1 [81] . Following incubation , macrophages or neutrophils were lysed and the remaining fungi were incubated with 0 . 4 mg/ml XTT and 0 . 05 mg/ml coenzyme Q for 1 h and the optical density ( OD ) subsequently measured on a spectrophotometer at a wavelength of 450 nm . The percent fungal damage was defined by the equation: ( 1-[A450 of fungi with cells—A450 of cells alone] / [A450 of fungi alone] ) * 100 . Statistical significance was determined by a Student’s t-test , one-way ANOVA using a Bonferroni post-test , or Kruskal-Wallis one-way ANOVA with Dunn’s post-test through the GraphPad Prism 5 software as outlines in the figure legends . | Aspergillus spp . are ubiquitous in the environment , and even though individuals are regularly exposed to fungal spores clinical invasive disease is a rare manifestation . In contrast , individuals with weakened immune systems develop severe disease , such as invasive pulmonary aspergillosis ( IPA ) . IPA is associated with extremely poor prognoses and unacceptably high mortality rates . Knowledge gained from understanding how immunocompetent mammals control Aspergillus challenge will help develop new immunomodulatory strategies aimed at improving patient outcomes . It is well known that neutrophils and monocytes are crucial immune cells that act to limit fungal growth . Our work demonstrates a central role for the cytokine IL-1α in orchestrating the optimal recruitment of neutrophils and monocytes , whereas IL-1β and the inflammasome are more important in activation of anti-fungal activity of the monocytes . Moreover , our studies indicate that CCR2+ monocytes are required for optimal production of IL-1α in the lungs of A . fumigatus challenged mice . Thus , our data highlight a crucial role of the IL-1 cytokine in mediating anti-fungal immunity which might be harnessed to treat clinical cases of IPA . | [
"Abstract",
"Introduction",
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] | [] | 2015 | IL-1α Signaling Is Critical for Leukocyte Recruitment after Pulmonary Aspergillus fumigatus Challenge |
Large-scale proteomic analyses in Escherichia coli have documented the composition and physical relationships of multiprotein complexes , but not their functional organization into biological pathways and processes . Conversely , genetic interaction ( GI ) screens can provide insights into the biological role ( s ) of individual gene and higher order associations . Combining the information from both approaches should elucidate how complexes and pathways intersect functionally at a systems level . However , such integrative analysis has been hindered due to the lack of relevant GI data . Here we present a systematic , unbiased , and quantitative synthetic genetic array screen in E . coli describing the genetic dependencies and functional cross-talk among over 600 , 000 digenic mutant combinations . Combining this epistasis information with putative functional modules derived from previous proteomic data and genomic context-based methods revealed unexpected associations , including new components required for the biogenesis of iron-sulphur and ribosome integrity , and the interplay between molecular chaperones and proteases . We find that functionally-linked genes co-conserved among γ-proteobacteria are far more likely to have correlated GI profiles than genes with divergent patterns of evolution . Overall , examining bacterial GIs in the context of protein complexes provides avenues for a deeper mechanistic understanding of core microbial systems .
A key feature of the molecular organization of microbes is the tendency of functionally-linked proteins to associate as components of macromolecular complexes , operons , or other biological groupings . As a consequence , the gene products present in a bacterial cell are organized into functional modules , which in turn mediate the major cellular pathways and processes that support bacterial cell growth , proliferation , and adaptation [1]–[3] . Identifying the pairwise functional relationships between genes can reveal these modules , and elucidate the molecular systems that underlie the functional organization of a microbial cell . While chromosomal associations informative about gene functional relationships can be inferred computationally using genomic context ( GC ) -based methods [4] , [5] , knowledge of the composition and connectivity of multiprotein complexes and their organization into pathways requires experimentation , and such information remains incomplete even in one of the most tractable and well-studied , prokaryotic model-organisms , Escherichia coli [1] , [6] . Physical interactions can be mapped with high-confidence based on the affinity-purification of chromosomally-tagged proteins in combination with mass spectrometry ( APMS ) , which aims to isolate and identify endogenous protein complexes . Analogous to the tandem affinity purification ( i . e . , TAP tag ) method developed for yeast [7]–[9] , we developed an efficient sequential peptide affinity purification procedure for E . coli [2] , [10] and used it to decipher the global physical organization of a bacterial cell [2] , [10]–[12] . Our protein-protein interaction ( PPI ) map allows for the prediction of protein functions for previously uncharacterized components of soluble macromolecular complexes that co-purify with functionally annotated subunits , via ‘guilt-by-association’ [2] , [10] . We further integrated our proteomic data with comparative genomic inferences to define a more comprehensive network of functional interactions covering most of E . coli's cytosolic proteome [2] , [3] . Nevertheless , these maps do not fully capture the global systems organization of complexes within biological pathways or processes . To this end , we and others have developed high-throughput genetic screening methods to systematically map epistasis relationships ( i . e . , genetic interactions , abbreviated as GIs hereafter ) between bacterial gene pairs [13]–[16] . Biochemical pathways and networks are often robust [17] , such that most bacterial genes produce no discernible phenotype when singly deleted or mutated [18] . Indeed , only ∼300 of E . coli's 4 , 145 protein-coding genes are essential under standard laboratory conditions [19] . However , examining the fitness of double mutants can reveal functional dependencies . Hence , our quantitative E . coli synthetic genetic array ( eSGA ) technology , which simplifies the systematic generation and phenotypic scoring of large numbers of double mutants created by mating collections of engineered E . coli strains en masse [13] , [16] , can reveal the functional relationships of previously uncharacterized gene products [1] , [6] . For example , loss of two non-essential genes , which functionally compensate or buffer each other , may show an aggravating ( synthetic sick or lethal , or SSL ) GI if the combination of mutations critically impairs a process essential for cell growth or viability . Conversely , ‘alleviating’ ( i . e . , buffering or suppression ) GIs can occur between two genes encoding subunits of the same protein complex , where inactivation of either one alone annihilates complex activity , such that loss of the second component confers no additional defect . Indeed , the global patterns of aggravating and alleviating interactions measured by large-scale GI screens have been used to decipher the functional organization of biological pathways and protein complexes in yeast [20]–[23] . Here , to study the global organization of the E . coli interactome , we employ our eSGA approach in an unbiased manner by performing 163 functionally diverse query genes . The resulting filtered GI network was then combined with existing PPI data and GC-derived interactions to reveal pathway-level crosstalk between disparate protein complexes , and specific biological roles of uncharacterized bacterial gene products .
Since fully comprehensive screens are not yet practicable , we selected a diverse , minimally-redundant set of broadly representative ‘query’ genes for our screens ( see Protocol S1 ) . After generating selectable mutants in a hyper-recombinant Hfr-Cavalli ( Hfr C ) ‘donor’ strain background marked with a chloramphenicol-resistance cassette ( CmR ) , the corresponding deletion alleles were transferred by conjugation into a near genome-wide mutant collection of F- ‘recipient’ mutant strains , arrayed in duplicate at 384-colony density . This collection , contains 3 , 968 non-essential single gene deletions in which the open reading frame was replaced and marked by a kanamycin resistance ( KanR ) cassette ( i . e . , the Keio collection ) [19] , and 149 hypomorphic mutant strains [13] , [16] , in which a KanR marker was integrated into the 3′-UTR to alter transcript abundance or stability [13] ( Figure 1A , Protocol S2 ) . In total , a set of 163 query ‘donor’ genes with evidence of expression and whose products had high physical interaction degree were selected for screening ( Protocol S1 ) . These included 93 genes linked to core bacterial processes ( Figure 1B ) , such as metabolism , cell envelope biogenesis , transcription , protein synthesis and chromosomal replication and repair , and 25 genes of unknown function ( Table S1 ) . Since accurate quantitation of epistasis depends on reliable estimations of mutant fitness [24] , we performed two independent replicate screens such that each donor-recipient mutant gene pair was tested eight times to account for experimental variation ( see Protocol S2 ) . Following genetic transfer , the double mutants were selected on rich medium ( Luria Broth ) containing both marker drugs ( Kan+Cm ) . After outgrowth for 36 hrs at 32°C , the plates were imaged digitally . Colony growth was quantified using a data processing strategy originally devised for yeast SGA analysis [24] , [25] , to correct for possible batch and plate position effects , and the different intrinsic growth rates of the single mutants [26] . We also eliminated from consideration pairs of closely-linked loci that potentially suffer from reduced recombination efficiency due to linkage suppression [24] , [25] . Overall replicate screen reproducibility was high ( r = 0 . 7; Figure 2A ) , similar to that reported for other high-quality GI studies [16] , [24] , [27] . We used a multiplicative model to calculate epistasis ( S ) scores [21] , [22] , [28] , determining both the strength and confidence of putative GIs based on differences between the observed growth of the digenic mutants and the expected growth rates . The null hypothesis assumes independent fitness defects for non-interacting gene pairs - that is , if two alleles are functionally unrelated ( i . e . , independent ) , their joint fitness defects should combine in a multiplicative ( i . e . , non-synergistic ) manner , as was done previously for yeast [25] , [29] . Conversely , S-scores deviating significantly from expectation represent candidates for functional associations ( i . e . , genes working together in a pathway to perform a specialized cellular activity ) [29] . The S-scores calculated for ∼600 , 000 digenic mutant combinations tested showed a normal distribution centered on zero ( i . e . , neutral ) ( Figure 2B ) , consistent with the expectation that GIs are relatively rare , with the fitness of most double mutants ( i . e . , functionally unrelated ) typically equal to the product of individual single mutant growth defects [1] , [30] . To rigorously define GIs , as with our previous studies [13] , [16] , we applied stringent statistical thresholds corresponding to two standard deviations ( |Z-score|≥2; P≤0 . 05 ) of the score distribution to define significant outliers ( Protocol S2 ) . After filtering , the network encompassed GI with S-scores of −3 or lower ( 25 , 239 in total ) that indicate aggravating ( i . e . , SSL ) relationships , and GIs with S-scores of +3 or higher ( 17 , 466 ) representing alleviating relationships ( Figure 2B , Table S2 ) , which occasionally ( but rarely ) reflect suppression of an impaired growth phenotype conferred by a single allele . Like other biological networks [24] , [31] , the filtered GI network had a modular connectivity structure ( average clustering coefficient = 0 . 23 , Figure S1A ) , wherein the majority of the genes have few GIs compared to a small number ( n = 25 ) of highly connected ( edge ≥640 ) ‘hubs’ ( Figure S1B ) . As was reported for yeast [27] , [32] , [33] , essential E . coli genes tend to be more highly connected in the network compared to non-essential genes , both in terms of GI degree ( Figure S1C , Protocol S3 ) and overall network betweenness ( i . e . , a graph centrality measure reflecting the proportion of shortest paths between pairs of nodes that go through a particular gene ) ( Figure S1D , Protocol S3 ) . Essential subunits of annotated protein complexes are also significantly enriched ( p = 2 . 2×10−16 ) in aggravating interactions with each other , compared to pairs of components within non-essential complexes ( Figure 2C , Protocol S3 ) , suggesting that as in yeast [34] , essential bacterial protein complexes occupy a central position within the E . coli GI network , just as they do in the E . coli PPI network [10] . Comparison of the filtered GI network against a reference set of manually curated GIs extracted from the literature showed high ( ∼75% ) agreement , which is significant ( p-value ≤10−4 ) by random sampling null models ( Figure 2D , Table S3 , Protocol S3 ) . For instance , our network captured the synthetic lethality reported between mutants of the chaperones , cbpA and dnaJ [35] , and between the exonucleases recB and recJ , and recB and components of the RecFOR DNA repair complex , which jointly function in RecA-mediated recombination [36] . As the number of interactions in the literature curated reference set was quite limited , we examined if the interacting gene pairs were enriched for functional relatedness using a battery of different metrics ( see Protocol S4 ) . For example , inspection of the GI network revealed a slight but significant ( p = 1 . 2×10−43 ) tendency for E . coli genes encoding subunits of the same protein complexes to display correlated patterns of GIs as compared to randomly selected protein pairs ( Figure 2E ) . Likewise , the components of the membrane-associated ferric enterobactin permease complex , FepD and FepG [37] , [38] , showed highly correlated ( rfepD , fepG = 0 . 5; Figure 2E ) GI patterns , consistent with their co-operative role in transporting iron-bound siderophores into the cytoplasm [39] . Indeed , by every other measure examined , including functional associations predicted by GC methods ( p = 2 . 2×10−118 ) [2] , mRNA co-expression ( p = 3 . 3×10−93 ) [40] , and phenomic ( i . e . , chemical genetic , p = 4 . 8×10−14 ) profiles [41]; we found that pairs of genes showing similar connectivity patterns in the GI network tended to be more highly correlated ( i . e . , as measured by Pearson Correlation Co-efficient ( PCC ) scores ) ( Figure S2A–C , Protocol S4 ) . Similarly , genes present within the same operon in E . coli [42] had significantly ( p = 6 . 1×10−252 ) more positively correlated genetic profiles than random pairs of genes ( Figure 2F ) , and this correlation was likely not due to polarity effects as the last and the first genes within each operon were , on average , just as likely to be positively correlated as the first and the middle genes ( Figure S2D ) ; intuitively , however the last gene cannot possibly underlie the GI phenotypes for every operon ( Protocol S5 ) . An illustrative example is the highly similar ( rtusC , tusD = 0 . 8 ) GI patterns of the two gene products , tusCD , encoded by the sulfur mediator operon , tusBCDE ( Figure 2F ) , consistent with their joint role in coordinating sulfur transfer [43] . Taken together , the benchmarking underscored the reliability and coverage of our screen data , indicating that the filtered GI network is informative about biological relationships at the level of individual gene pairs , multiprotein complexes , and pathways . To identify broader functional groupings ( i . e . , modules or interconnected gene sets ) , we sorted the genes according to their biological process annotations , and examined the extent to which their corresponding high-confidence GI ( |S-score≥3|; P≤0 . 05 ) tended towards alleviating or aggravating GI ( Figure 3A ) , using a “monochromatic” score that has been previously used to unveil the modularity of yeast GI networks [44] , [45] . While discrete clusters were clearly identified ( Figure 3B and 3C ) from the GI spanning the constituent genes within bioprocesses with high alleviating or aggravating monochromatic scores , several of these bioprocesses displayed extensive inter-connectivity , suggestive of biological cross-talk ( Table S4 , Protocol S6 ) . For example , alleviating interactions bridge the cell envelope machinery ( e . g . , alr , dadX , aer ) to phospholipid biosynthesis ( clsB , pgpA , ugpA , ugpB , cdh ) ( Figure 3B ) , consistent with their close coupling during membrane formation and integrity [16] , [46] . Conversely , other process combinations were preferentially enriched for aggravating relationships ( Figure 3C ) . For example , strong SSL associations were observed between the homologous recombination machinery ( recABC ) and DNA polymerases [polIII ( dnaNQ , holAC ) ; polIV ( dinB ) ] , whose coordination is critical for genomic integrity [47] . Likewise , sulfur-relay systems [yccK ( tusE ) , yheLMN complex ( tusBCD ) ] , which channel sulfur from various trafficking pathways to 2-thiouridine [43] , showed aggravating interactions with downstream iron-sulfur ( Fe-S ) cluster scaffold assembly factors ( e . g . , ydhD , gntY ) ( Figure 3C ) . Similarly , the ferric ( Fe3+ ) enterobactin transporter system ( e . g . , fepBCDG complex , fepA , fepE ) showed strong SSL links with the CSD ( cysteine sulfinate desulfinase ) sulfur transfer apparatus ( e . g . , csdAEL ) ( Figure 3C ) , implying overlap in iron homeostasis . Since the global patterns of GI measured by eSGA reflect biological relationships , we examined our GI network specifically to delineate novel functional roles for bacterial genes of unclear biological significance . Clustering the GIs resulting from the monochromatic analysis ( Protocol S6 ) implicated orphan genes lacking annotations to specific pathways . For instance , seven unannotated genes ( ynjABCDEFI ) were grouped together with particular components ( e . g . , sufCDS , ydhD ) of the “Suf” Fe-S cluster assembly machinery ( Figure 3C ) , consistent with a recent report that YnjE is a sulfur transferase required for molybdopterin biosynthesis [48] . Another illustrative example is a modular sub-network consisting of RavA ( Regulatory ATPase variant A ) , a AAA+ ATPase of the MoxR protein family whose physiological function is uncertain , and its binding partner , ViaA ( von Willebrand factor A domain interacting AAA+ ATPase ) [49] , which also exhibited strong aggravating connections with the Fe-S cluster assembly apparatus ( Figure 4A ) . Consistent with predicted epistasis , ravA viaA Fe-S triple deletion strains showed virtually identical GIs ( i . e . , SSL ) as ravA Fe-S or viaA Fe-S double mutants ( Figure 4A ) , which were confirmed independently by liquid culture growth assays ( Figure 4B , Protocol S7; representative ravA viaA hscA triple mutant shown ) . To further examine the link with Fe-S assembly , we exploited the observations that , at sub-lethal dosages , bactericidal drugs such as aminoglycosides ( e . g . , streptomycin , gentamycin ) cause cell death via mechanisms that are dependent on Fe-S clusters [50]–[53] , and that the uptake of aminoglycosides are directly influenced by the Isc pathway of Fe-S cluster biogenesis [54] . As a result , strains deficient in Fe-S assembly show decreased drug sensitivity [52] , [54] . We therefore tested the influence of ravA and viaA on Fe-S biogenesis in strains over-expressing the isc assembly machinery ( iscRSUA-hscBA-fdx-iscX ) on a multicopy plasmid ( pRKISC ) [55] upon challenge with the aminoglycoside , kanamycin . Notably , the presence of kanamycin impaired wild-type , but not ravA viaA double mutants ( Figure 4C , Protocol S8 ) . Consistent with this , ravA and viaA also showed GIs with cofactors required for Fe-S cluster formation , including genes involved in the biosynthesis of L-cysteine ( e . g . , the serine acetyltransferase complex , cysEK; hemoprotein subunit of sulfite reductase , cysIJ ) from which precursor sulfur is extracted ( Figure 4A ) . The fact that cysteine biosynthetic genes become essential despite the presence of rich media suggests a defect in cysteine transport in the cysB mutant strain ( Figure 4D , Protocol S7 ) . Thus , defects in the de novo biosynthesis of cysteine , coupled with impaired import , likely decrease the pool of cysteine available for Fe-S biogenesis and related sulfur transfer reactions by this pathway , which is mirrored as an aggravating phenotype . Since the uptake and assimilation of inorganic sulfurs by cysteine biosynthesis genes in bacteria requires the CysAUWP ABC transporter complex [56]–[58] , while organic sulfurs are imported by other ABC transporters [59] , we challenged strains over-expressing ravA with inorganic ( e . g . , SO42− and S2O32− ) and organic [taurine , 2- ( 4-pyridyl ) -ethanesulfonate ( PESF ) , and cysteine ( i . e . , Cys-S-S-Cys ) ] sulfur compounds ( Figure 4E , Protocol S9 ) . Unlike wild-type E . coli , ravA over-expressing strains showed increased sensitivity to inorganic , but not organic sulfurs ( Figure 4E , Protocol S9 ) , seemingly due to perturbation of the normal RavA-ViaA stoichiometry necessary for normal cell function . Taken together , a direct or indirect impact of RavA/ViaA on bacterial sulfur transport is consistent with our GI data , reflecting the tight integration of these systems . Since the growth assays confirmed participation of ravA and viaA in Fe-S assembly ( Figure 4B and 4C ) , we performed co-immunoprecipitation ( co-IP ) experiments to determine whether these two proteins interact physically with the Fe-S cluster ( Isc ) assembly proteins , with which they showed strong aggravating interactions ( Figure 4A ) . Indeed , endogenous affinity-tagged Isc proteins specifically and efficiently co-precipitated native RavA and ViaA ( Figure 4F , Protocol S10 ) , implying joint participation in cellular iron homeostasis through physical associations . Most notably , the fact that ravA-viaA mutants displayed a strong aggravating phenotype between the subunits of Isc complex supports the idea that these two overlooked processes function redundantly to tightly regulate cellular iron levels required for the maintenance of cell viability . That is while deletion of subunits of either protein complex shows a similar effect as loss of the entire complex , mutations in both complexes ( i . e . , RavA-ViaA and Isc simultaneously perturbed ) result in SSL phenotypes due to system failure . Another example of functional insights resulting from this GI analysis involves a sub-network ( Figure 5A ) of aggravating GIs connecting the late ribosome biogenesis factor , rsgA , with both the ribosome and an unannotated gene , yaiF , which , while not essential in E . coli , is predicted to belong to a protein family of acetyl-transferases that are widely conserved among microbes ( Table S5 ) . Although the co-IP experiments showed no physical association between YaiF and RsgA in E . coli solubilized cell extracts ( data not shown ) , as with the GI dataset , analysis of previously published large-scale phenomics ( i . e . , chemical genetic profiling ) data [41] showed that a mutant strain lacking yaiF is hyper-sensitive to antibiotics ( macrolide , tetracycline , amino-glycoside ) targeting protein synthesis ( Figure 5B ) . Similarly , we found that the mutant strain lacking yaiF or rsgA was sensitive to tetracycline , whereas the yaiF rsgA double mutant exhibited increased drug sensitivity ( Figure 5C , Protocol S7 ) , suggesting participation of YaiF in translation . To evaluate this link further , we examined ribosome profiles in yaiF deletion mutants . Unlike rsgA , the ribosome profile of yaiF mutant from the log-phase culture was nearly wild-type ( Figure 5D , Protocol S11 ) , consistent with the previous finding where loss of known protein synthesis gene products , including the ribosome modulation factor , rmf [60] , resulted in near wild-type profiles . However , in contrast to wild-type cells , yaiF or rsgA mutants exhibited translational defects , including mistranslation as indicated by higher read-through of out-of-frame amber ( UAG ) and opal ( UGA ) nonsense codon alleles and miscoding of +1 and −1 frame-shift mutations in a β-galactosidase reporter [61] ( Figure 5E , Protocol S11 ) . Strikingly , these defects were exacerbated when both yaiF and rsgA were deleted ( Figure 5E , Protocol S11 ) , consistent with our genetic data . Moreover , strains lacking yaiF delayed the production of mature 16S rRNA , resulting in the accumulation of late unprocessed 17S rRNA molecules ( Figure 5F , Protocol S11 ) in a similar manner to the mutant strain lacking rsgA [62] , [63] . This effect was specific as overexpression of yaiF or rsgA in trans fully rescued the 17S rRNA defects in the respective deletion strains ( data not shown ) , indicating the involvement of YaiF in bacterial protein synthesis . However , further experiments are warranted to delineate how YaiF affects RNA processing and ribosome biogenesis , potentially in a pathway relating to RsgA . Molecular chaperones often have numerous binding partners , as they typically participate in the folding , assembly , transport , and stability of multiple client proteins involved in distinct processes [64] , [65] . Previous systems-wide analyses of physical and genetic interactions involving chaperones in yeast has revealed an extensive interplay of inter-chaperone interactions that mediate protein homeostasis in eukaryotes [66] . Since earlier studies in E . coli have largely focused on reductionist biochemical analyses of single or closely related chaperones in isolation , the extent of functional connectivity between bacterial chaperones and their cofactors and substrates has not been explored systematically [67] . We address this gap by examining the global epistatic relationships of 22 general , widely conserved bacterial chaperones and ATP-dependent proteases , including ribosome-associated trigger factor ( tig ) , and members of the Hsp40 ( cbpA , djlA , dnaJ , hscB ) , Hsp70 ( dnaK , hscA , hscC , yegD ) , Hsp90 ( htpG ) , Hsp100 ( clpA , clpB , clpX , hslU ) , small HSPs ( hsp33 , ibpA , ibpB ) , and ATP-dependent proteases ( clpP , ftsH , hslV , lon ) ( Figure 6A , Table S1 ) . By applying the same strict filtering criteria ( |S-score≥3|; P≤0 . 05 ) as previously , a network of 3 , 816 high-confidence GIs involving one or more of these factors ( Table S2 ) , revealed functional redundancy and cross talk between these determinants of protein stability . For example , a sub-network of alleviating GIs ( Figure 3B ) connected the ATP-dependent molecular chaperone , clpX , and its serine protease , clpP , with other known and putative chaperones/co-factors , such as the ATP-dependent protease ( hslV ) , small heat shock proteins ( HSPs ) ( ibpA ) , and hsp100 ( clpA ) , presumably reflecting functional cooperation in substrate recognition and degradation [68]–[70] . While the number of GIs identified per chaperone varied significantly , ranging from 6 ( e . g . , hsp33 ) to well over 600 ( e . g . , cbpA ) , with chaperones localized in the cytosol showing the highest connectivity ( Figure 6A , Table S6 ) , many non-chaperone genes in this sub-network interacted preferentially with a single chaperone , consistent with a specific role in protein folding ( Table S7 ) . For example , while the dnaJ chaperone paralog cbpA showed strong aggravating interactions with over 200 non-chaperones , the NAD-dependent malate dehydrogenase , sfcA only interacted with Hsp70 chaperone , dnaK . In contrast to most soluble proteins , the outer membrane porin , ompA , interacted with 10 different chaperones ( Table S8 ) , reflecting the multiphasic nature of membrane protein , secretion , transport , and assembly . As each gene in the GI network possesses a GI profile , or signature , describing its functional interactions with other tested genes , the biological roles of incompletely characterized components can be inferred based on their GI profile correlation with annotated genes [6] , [16] , [21] ( Table S9 ) . To filter high-confidence correlations , we chose a PCC cut-off score ( ≥0 . 3 ) that captured roughly 18% ( 438 of 2 , 385 ) of the correlated gene pairs mapping to well-annotated EcoCyc complexes or pathways ( Figure S3A , Protocol S12 ) . As implied by the GI network , the correlated GI profiles showed strong functional coordination among distinct chaperone systems ( Figure 6B , Table S9 ) . An illustrative example is the highly correlated ( ribpA , ibpB>0 . 5 ) interaction profiles of two small HSPs , ibpA and ibpB , which prevent irreversible protein aggregation due to high temperature [71] , [72] ( Figure 6B ) . Likewise , a strong correlation was observed between the ATP-dependent protein unfoldases , clpX and clpA ( Figure 6B ) , consistent with their documented cooperation in maintaining client protein stability [73] . To gain insight into the prevalence of functional dependencies between protein complexes and chaperones , we next assessed the degree to which protein complexes were enriched with aggravating or alleviating interactions involving chaperones . We observed that roughly half of all putative soluble protein complexes showed significant ( p-value ≤0 . 05 ) enrichment for alleviating interactions involving one or more of the 18 chaperone containing protein complexes compiled from our own large-scale proteomics survey [2] and the EcoCyc database ( Figure 6C , Protocol S13 ) . Large complexes related to general metabolism and envelope biogenesis interacted with multiple chaperones ( Table S10 ) . Chaperone-related complexes shared many non-chaperone interactors , as evidenced by high Jaccard similarity indices , suggesting functional cooperation in complex formation or maintenance ( Figure 6D , Table S10 , Protocol S13 ) . Strikingly , ATP-dependent proteases , such as clpP interacted strongly with members of the small HSPs and Hsp100 families ( Figure 6E , Table S10 ) , consistent with previously reported interplay in protein folding and quality control [74] , [75] . Likewise , GIs connected members of the Hsp100 and Hsp70 families ( Figure 6E ) , likely reflecting Hsp100's role in rescuing protein aggregates caused by defects in Hsp70-mediated protein folding [76] . As well , members of the Hsp40 and Hsp90 systems showed strong genetic crosstalk ( Figure 6E ) , consistent with current models of system dependencies between these chaperones [77] . Despite the scope of the screens , the experimentally mapped GI network of E . coli is sparse . To glean additional insights into the functional organization of bacterial processes , we combined our GI data with alternate evidence of functional associations , such as physical interaction information and GC-based inferences , analogous to integrative studies reported in yeast [20] , [23] , [78] . In particular , we examined a previously published set of 316 putative E . coli functional modules [2] , [3] , encompassing protein complexes and 43% ( 1 , 784 ) of all 4 , 145 known protein-coding genes in E . coli ( Table S11 ) , probing for significant enrichment of GIs between modules . Although only ∼5% ( 104 ) of these components were screened as query mutants by eSGA , we observed significant enrichment of GIs between certain functional groupings , or modules , either as protein complexes or overlapping pathways ( Figure S3B ) . After applying stringent permutation testing ( Protocol S14 ) , we identified 302 significant enrichments ( p-value ≤0 . 05 ) , of which the vast majority ( 99% ) occurred between different modules ( Figure S3C , Table S12 ) . As reported for yeast [20] , [22] , aggravating GIs were far more prevalent than alleviating interactions between modules ( Figure S3D ) . The preponderance of GIs between modules provided an opportunity to explore the nature of functional crosstalk between biological systems ( Figure S4A , Table S13 ) . For example , the Suf Fe-S cluster biosynthetic module , members of the DNA polymerase module involved in proofreading and correcting replication errors via exonuclease activity , and components of the Psp ( phage shock protein ) system , mediating cellular responses to envelope instability and maintaining respiratory chains in E . coli , showed a remarkably high degree of interconnectivity ( Figure S4B ) . In addition to previously noted strong aggravating GIs with the functionally equivalent Isc Fe-S system ( encoded by iscRSUA-hscBA ) [13] , particularly evident ( Figure S4B ) from the Suf module ( sufABCDSE ) were aggravating crosstalk with the vitamin B12 transport system , which participates in the E . coli response to reactive oxygen species [79] . Fe-S clusters play important roles in sensing redox/oxidative stress and iron homeostasis [80] , and their breakdown can lead to accumulation of reactive oxygen species that triggers an adaptive response [81] . Structural similarity between certain components ( e . g . , btuD vs . sufC ) [82] is also suggestive of functional dependency . Functional coupling was also evident between the Psp ( phage shock protein ) and cell-envelope associated modules , such as Sap ( sensitive to antimicrobial peptides ) , Mgl ( β-methylgalactoside transporter ) , Mdt ( multidrug resistance exporter ) and Nar ( Nitrate reductase ) transporters , as well as with members of purine salvage pathway ( Figure S4B ) , consistent with joint participation in respiration , maintenance of proton-motive force , and envelope integrity [83]–[86] . Conversely , alleviating interactions were preferentially detected among different module pairs , such as between the small heat shock chaperones ( e . g . , ibpAB ) and multidrug efflux transporters ( acrAB-tolC ) ( Figure S4B ) , possibly reflecting the active secretion of toxic protein degradation products [87] . Genes encoding members of the AAA+ family of proteases such as clpA-clpP and hslV-clpP , exhibited strong alleviating interactions with the hslV-ftsH protein quality control factors [69] , suggesting they work in union ( Table S12 ) . On an individual component level , alleviating interactions often occurred between structurally similar proteins , such as the energy-dependent proteases hslV and clpP underlying a common mechanism in protein degradation [88] . Given that a large proportion of E . coli genes are conserved among a majority of bacteria , particularly among closely related γ-proteobacterial species [2] , [10] , we investigated the evolutionary significance of the putative functional associations detected by eSGA in E . coli by examining co-conservation of orthologs among other sequenced prokaryotes . Phylogenetic profiles were created by retrieving orthologous groups across a total of 233 fully sequenced γ-proteobacterial genomes ( 29 closely-related E . coli serotypes , 64 enterobacterial and 140 γ-proteobacterial species ) from the eggNOG database [89] ( Table S14 ) . These profiles were used to derive mutual information ( MI ) scores based on the degree of similarity in the pattern of co-conservation of a given pair of genes ( Protocol S15 ) . We focused on gene pairs having correlated GI profiles in E . coli with a PCC score of ≥0 . 3 , which favored interactions among components of the same complex and pathway ( Figure S3 ) . Consistent with biological expectation , co-conserved subunits of E . coli modules tended to possess highly correlated GI profiles on average compared to those belonging to different ( i . e . , between ) complexes or pathways ( Figure 7A and 7B ) . Applying an MI score cut-off ≥0 . 2 , representing a probability of co-conservation more significant than expected by random chance ( Figure S5A and S5B ) , revealed several functionally highly correlated ( r≥0 . 5 ) co-conserved clusters in γ-proteobacterial species ( Table S15 , Figure S5B ) . These included essential E . coli factors functioning in core bacterial bioprocesses such as envelope biogenesis , gluconeogenesis , and RNA/DNA/protein synthesis , which were all highly inter-connected by GIs ( Figure 7C ) . Furthermore , this analysis revealed varying degrees of functional correlation ( i . e . , at greater or less than 50% conservation ) between several large , co-conserved , but non-essential bacterial protein complexes . For example , orthologues of the substrate ( e . g . , Sap and Fep ABC transporters ) and proton ( e . g . , periplasmic nitrate reductase ) transporter complexes , as well as the sulfur relay heterohexameric TusBCD machinery ( Figure 7D ) , were all evolutionarily co-conserved , consistent with their broad functional importance across γ-proteobacterial species . Surprisingly , however , some subunits of highly co-conserved complexes and pathways had notable differences in their GI profiles . For example , two partly redundant , non-essential , highly conserved lysyl-tRNA synthetases of E . coli , lysU and lysS , each capable of sustaining protein synthesis [90] , [91] , were functionally anti-correlated with other tRNA synthetases ( e . g . , thrS , tyrS ) ( Figure 7E ) . This suggests opposing functions in support of translation , consistent with previous reports of distinct functions for these genes [90] , [91] . Likewise , anti-correlated GI profiles were observed among subunits of the flagellum complex , which were largely found in closely-related E . coli serotypes and enterobacterial species , but which lacked orthologs among other γ-proteobacteria ( Figure 7F ) , suggesting specialized roles in flagellum assembly [92] . Since co-conservation and correlated GI profiles reflect shared functionality [93] , [94] , we were able to delineate specific biological relationships . For example , the co-conserved components of the ferric enterobactin ABC transporter ( e . g . , fepBCD ) and enterobactin synthetases ( e . g . , entBE ) ( Figure S5C ) showed highly correlated GI profiles , consistent with their joint participation in iron homeostasis [95] , [96] . Likewise , significant correlation was observed among the subunits of the sulfur transfer mediator ( e . g . , tusBCD ) and the thiamin ( e . g . , thiCDEFM ) biosynthesis machinery ( Figure S5C ) , both of which participate in thiamin production [97] , [98] .
The vast majority ( >90% ) of E . coli's genes are dispensable for viability under standard laboratory culture conditions [19] . Unbiased interaction screens are increasingly being used to characterize the biological organization of E . coli [1] , [2] , [13] , [14] , [16] . Yet despite being one of the most heavily studied bacteria , nearly one-third of E . coli's genes currently lack experiment-based functional annotations [1] . While proteomics and GC approaches are valuable for understanding how bacterial gene products associate into discrete biological entities ( i . e . , protein complexes ) [2] , [3] , [99] , they often fail to reveal higher order ( i . e . , pathway-level ) functional relationships and process cross-talk that underlie genetic redundancy , impeding systems-level modeling [100] , [101] . Genetic screens have long been appreciated as a powerful means for probing biological relationships in bacteria , but historically these studies have been focused on individual genes , complexes , or pathways in isolation [1] , [6] , [16] . Recent technical advances , including the development of high-throughput methods such as eSGA , GIANT-coli , and Tn-Seq [13]–[16] , now permit the systematic mapping of epistatic dependencies . In the present study , we have markedly expanded on previous initial surveys of the bacterial GI space [13] , [16] , achieving a scope for a prokaryote that begins to approach that reported for yeast [24] , [102] . Our current GI map , although still sparse , encompasses virtually the entire E . coli proteome . Given the functional information contained within the recorded GI patterns , this map , despite being incomplete , represents a substantial resource for mechanistic prediction . In this study , based solely on our GI data , we were able to discover novel components and unexpected connections in well-studied pathways essential for bacterial fitness such as the association of RavA and ViaA with Fe-S and cysteine assembly , and the implication of the previously uncharacterized component YaiF in maintaining ribosomal integrity , especially in preserving translational fidelity and protein synthesis . The GI map also provides insights into the global architecture of convergent and compensatory pathway crosstalk that contributes to the overall robustness of bacterial processes . To facilitate mechanistic exploration at both levels , we report all high-confidence interactions in a dedicated open web-portal ( http://ecoli . med . utoronto . ca/esga ) , allowing examination of both individual pair-wise gene interactions and broader connectivity among bacterial complexes and biological processes . Integrative analyses have been documented extensively in yeast [20] , [21] , [45] , [103] , however the lack of unbiased GI data has hindered such analysis in bacteria . By combining the eSGA data from this study with previously reported E . coli functional modules derived by physical interaction mapping and GC [2] , [3] , we found unexpected relationships between certain complexes and pathways . For example , by illuminating how chaperones cooperate within a bacterial cell , we revealed unforeseen functional dependencies , suggesting an overarching surveillance network maintains protein homeostasis in bacteria . Despite deriving meaningful biological information by expanding the scope of GI data , the current network still remains sparse , as only ∼10% ( ∼600 K out of ∼8 million ) of all possible digenic mutant E . coli gene pairs were evaluated by eSGA to date . Hence , we have likely missed important patterns of connectivity that potentially biases our global inferences , leading to an underestimation of the extent of process crosstalk . However , our integrated approach revealed several novel functional associations between functional modules with significant enrichment in inter-module GIs , revealing various pathways and complexes that participate in related biological processes . This present shortfall will be overcome as the coverage of available GI data improves over the coming years and will provide a greater understanding of the functional organization of the bacterial cell . The ability to extrapolate the epistatic connectivity diagram of E . coli to other microbial species lacking experimental information provides a conceptual framework for exploring bacterial evolution across different lifestyles and phylogenetically diverse microbiomes [104] . Our preliminary exploration of the co-conservation of genes and functional modules with correlated GI profiles among γ-proteobacteria illustrates the potential to outline possible adaptations , such as connectivity between iron-import and sulfonation in the biogenesis of thiamin utilization , which are linked to bacterial pathogenesis of enteric bacteria [97] , [105] , [106] . Thus , epistatic interactions can describe how sequence evolution in bacterial species drives functional specialization , environmental adaptations , and , potentially , speciation .
Bacterial strains used in this study are listed in Table S16 and Protocol S16 . Procedures used for the compilation of donor query targets for eSGA , strain construction , eSGA screens , computational processing epistatic interaction data to derive high confidence GI scores , the analysis of GI network properties , monochromatic analysis , computing correlation scores using GI profiles , enrichment of GI associations within and between functional modules , evolutionary conservation , phenotypic assays , as well as other relevant methods are described in detail in Supplementary Information . Network graphs were generated using Cytoscape ( ver . 2 . 8 . 2 ) , and the heat-maps were generated using in-house JAVA scripts or MATLAB . | Genome-wide genetic interaction ( GI ) screens have been performed in yeast , but no analogous large-scale studies have yet been reported for bacteria . Here , we have used E . coli synthetic genetic array ( eSGA ) technology developed by our group to quantitatively map GIs to reveal epistatic dependencies and functional cross-talk among ∼600 , 000 digenic mutant combinations . By combining this epistasis information with functional modules derived by our group's earlier efforts from proteomic and genomic context ( GC ) -based methods , we identify several unexpected pathway-level dependencies , functional links between protein complexes , and biological roles of uncharacterized bacterial gene products . As part of the study , two of our pathway predictions from GI screens were validated experimentally , where we confirmed the role of these new components in iron-sulphur biogenesis and ribosome integrity . We also extrapolated the epistatic connectivity diagram of E . coli to 233 distantly related γ-proteobacterial species lacking GI information , and identified co-conserved genes and functional modules important for bacterial pathogenesis . Overall , this study describes the first genome-scale map of GIs in gram-negative bacterium , and through integrative analysis with previously derived protein-protein and GC-based interaction networks presents a number of novel insights into the architecture of bacterial pathways that could not have been discerned through either network alone . | [
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"p... | 2014 | Quantitative Genome-Wide Genetic Interaction Screens Reveal Global Epistatic Relationships of Protein Complexes in Escherichia coli |
The mammalian immune system has the ability to discriminate between pathogens and innocuous microbes by detecting conserved molecular patterns . In addition to conserved microbial patterns , the mammalian immune system may recognize distinct pathogen-induced processes through a mechanism which is poorly understood . Previous studies have shown that a type III secretion system ( T3SS ) in Yersinia pseudotuberculosis leads to decreased survival of this bacterium in primary murine macrophages by unknown mechanisms . Here , we use colony forming unit assays and fluorescence microscopy to investigate how the T3SS triggers killing of Yersinia in macrophages . We present evidence that Yersinia outer protein E ( YopE ) delivered by the T3SS triggers intracellular killing response against Yersinia . YopE mimics eukaryotic GTPase activating proteins ( GAPs ) and inactivates Rho GTPases in host cells . Unlike wild-type YopE , catalytically dead YopER144A is impaired in restricting Yersinia intracellular survival , highlighting that the GAP activity of YopE is detected as a danger signal . Additionally , a second translocated effector , YopT , counteracts the YopE triggered killing effect by decreasing the translocation level of YopE and possibly by competing for the same pool of Rho GTPase targets . Moreover , inactivation of Rho GTPases by Clostridium difficile Toxin B mimics the effect of YopE and promotes increased killing of Yersinia in macrophages . Using a Rac inhibitor NSC23766 and a Rho inhibitor TAT-C3 , we show that macrophages restrict Yersinia intracellular survival in response to Rac1 inhibition , but not Rho inhibition . In summary , our findings reveal that primary macrophages sense manipulation of Rho GTPases by Yersinia YopE and actively counteract pathogenic infection by restricting intracellular bacterial survival . Our results uncover a new mode of innate immune recognition in response to pathogenic infection .
Innate immunity provides an early and critical protection against pathogenic infection . In the dominant paradigm of innate immunity , host cells detect pathogens by recognition of “microorganism-associated molecular patterns” ( MAMPs ) via pattern recognition receptors ( PRRs ) [1] . However , MAMPs , such as flagellin or lipopolysaccharide ( LPS ) , are conserved microbial structures found in both pathogenic and nonpathogenic bacteria . How then do host cells distinguish pathogens from innocuous microbes ? Alternate theories propose that , in addition to MAMPs , host cells also respond to distinct pathogen-induced signals , termed “patterns of pathogenesis” [2]–[4] . Several recent studies have demonstrated that host cells sense the activities of bacterial effectors , such as inhibition of host protein synthesis , activation of host Rho GTPases or pore forming activity , resulting in an active response against the pathogenic attack [5]–[10] . The protective immune response that is triggered by the detection of microbial effectors is defined as an “effector-triggered immune response” ( ETIR ) . In the genus of Yersinia , three species are pathogenic for humans: Yersinia pestis , Yersinia pseudotuberculosis and Yersinia enterocolitica . Y . pestis is the causative agent of plague and is typically transmitted by fleabites or aerosols [11] , [12] . Y . pseudotuberculosis and Y . enterocolitica are associated with self-limiting gastroenteritis acquired from contaminated food or water [11] . The virulence of pathogenic Yersinia requires a plasmid ( pYV in Y . pseudotuberculosis ) , which encodes a T3SS and a suite of effectors named Yersinia outer proteins ( Yops ) [13] . Upon Yersinia infection , Yop effectors are translocated into host cells by the T3SS to modulate host signaling pathways [13] . Four Yop effectors act to target Rho GTPases by distinct mechanisms: YopE mimics the eukaryotic GTPase activating protein ( GAP ) and promotes GTP hydrolysis to inhibit Rho GTPase activation; YopH , a protein tyrosine phosphatase , impacts Rho GTPase activation by interrupting activating signals for guanine exchange factors ( GEFs ) ; YopT , a cysteine protease , proteolytically removes the C-terminal isoprenoid moiety of Rho GTPases , therefore releasing their membrane anchors; YpkA can bind to Rho GTPases with a guanine dissociation inhibitor ( GDI ) domain [13] . By disturbing Rho GTPase activity , YopE , YopH , YopT and YpkA exert a negative effect on cytoskeleton dynamics , thus contributing to the anti-phagocytic activity of the Yersinia T3SS . In addition , YopJ inhibits NF-κB and MAPK signaling pathways , while YopK regulates effector delivery as well as host responses [10] . Translocators YopB and YopD are required for the formation of the T3SS channel and delivery of effector Yops . The prototypical bacterial effector YopE is a 219 amino acid protein containing a Rho GAP domain ( residues 96 to 219 ) [14] . YopEGAP shares homology with SptPGAP from Salmonella Typhimurium and ExoSGAP from Pseudomonas aeruginosa . YopE introduces an “arginine finger” into the GTPases catalytic site , which results in efficient GTP hydrolysis and deactivation of GTPases . Exchanging Arg144 in the “arginine finger” with an alanine residue abolishes YopE GAP activity [14] . In mammalian cells , YopE localizes to plasma membrane and unidentified perinuclear compartments , which requires a hydrophobic leucine-rich motif within its membrane localization domain ( MLD , residues 53 to 79 ) [15]–[18] . Stability of YopE in host cells is influenced by allelic variations of residues 62 and 75 , as found in different Yersinia strains . The presence of lysine residues at position 62 or 75 can mediate YopE ubiquitination and degradation by the host cell proteasome pathway [19] . Both subcellular membrane localization and stability of YopE are important for its GAP activity [16] , [19] . YopE is equally effective on Rac1 , RhoA and Cdc42 in vitro [14] , whereas it is preferably active on Rac1 and RhoA , but not Cdc42 , in vivo [20] . Unlike YopE , YopT seems to be primarily effective on RhoA , but not Rac1 or Cdc42 in vivo [21] . However , overexpressed YopT also acts on Rac1 in Yersinia-infected epithelial cells [22] . Interestingly , under the latter condition , YopT competes with YopE for the same pool of membrane-associated Rac1 , promotes translocation of cleaved Rac1 into the nucleus , and therefore interferes with the ability of YopE to inactivate Rac1 [22] . Yersinia is generally considered as an extracellular pathogen , as the bacteria grow primarily in an extracellular form in vivo; however , these bacteria can survive and grow inside phagocytic cells , which may be important for the early stages of colonization [23] . It is suggested that macrophages might serve as permissive sites for bacterial replication or even as transport vehicles from the initial site of infection to deeper lymph tissues [24] . Interestingly , T3SS function decreases survival of Y . pseudotuberculosis in murine macrophages . Under experimental conditions in which T3SS expression is pre-induced , macrophages restrict intracellular survival of wild-type Y . pseudotuberculosis , but not a yopB− mutant ( deficient in Yops translocation ) or a pYV− mutant ( missing the entire T3SS ) [25] . Thus , some T3SS-dependent factor encoded in the wild-type strain triggers a bactericidal response in macrophages , the mechanism of which remains unclear . It has been shown that upon internalization of Y . pseudotuberculosis , the T3SS stimulates Ca2+-dependent phagolysosome fusion in macrophages , mediated by the Ca2+ sensor SytVII , leading to increased killing of intracellular bacteria [26] . Also , it has been reported that the Y . pseudotuberculosis T3SS stimulates Ca2+- and caspase-1-dependent lysosome exocytosis , releasing antimicrobial factors [27] . Yet , further studies are needed to determine the molecular basis of innate immune recognition of the Yersinia T3SS , and the role of this process in determining the fate of the bacteria in macrophages . Here we hypothesize that the activities of the Yersinia T3SS effectors are sensed by host cells as patterns of pathogenesis , which stimulate an intracellular killing response against Yersinia as a type of ETIR . We show that macrophages recognize pathogenic Y . pseudotuberculosis through T3SS functions and elicit an intracellular killing response to counteract infection . We provide evidence that YopE GAP activity is a critical factor sensed by macrophages , with YopH playing a minor role . Overexpression of YopT counteracts the YopE-triggered killing effect possibly by competing for the Rho GTPase target and by reducing YopE translocation . Also , this YopE-triggered intracellular killing response can be mimicked by other bacterial derived toxins like Clostridium difficile Toxin B , indicating that host cells sense manipulation of Rho GTPases as a conserved surveillance pathway to detect pathogens . Thus , our data provide another example of a protective host response induced by pathogenic bacteria through recognition of bacterial effector activities on Rho GTPases , revealing a novel mode of innate immune recognition towards pathogenic infection .
Previous studies have shown that T3SS decreases survival of Y . pseudotuberculosis in murine macrophages [25] , [26] . To determine if specific Yop effectors might contribute to decreased survival of Y . pseudotuberculosis in macrophages , the wild-type strain IP2666 and several yop deletion mutants were studied . Initially , the survival of IP2666 ( wild-type ) , IP17 ( yopEH− ) , IP27 ( yopEHJ− ) and IP37 ( yopEHJMKYpkA− ) ( Table 1 ) in murine bone marrow-derived macrophages ( BMDMs ) was compared . Naïve BMDMs were infected with the indicated strains , followed by gentamicin treatment to eliminate extracellular bacteria . At 1 h and 23 h post infection , infected BMDMs were lysed and spread on LB plates to enumerate viable bacteria . CFU at 1 h post infection was considered as the initial intracellular bacterial count . The ratio of CFU between 23 h and 1 h post infection was calculated for each strain . At 1 h post infection , IP2666 showed lower CFU as compared to IP17 , IP27 and IP37 ( Figure S1A ) . This is expected because IP2666 expresses Yops with anti-phagocytic functions ( YopE and YopH ) ; however the other strains are yopEH− mutants . At 23 h post infection , IP17 displayed significantly higher level of CFU as compared to IP2666 , but similar level as compared to IP27 and IP37 ( Figure S1B ) . Consistently , for the ratio of CFU at 23 h/1 h , the level of IP17 was significantly higher than IP2666 , but similar to IP27 and IP37 ( Figure 1A ) . To rule out a threshold effect due to the differences in the initial bacterial uptake , BMDMs were infected with IP2666 or IP17 at different MOIs ( Figure S2 ) . Even with higher CFU at 1 h post infection , IP2666 ( MOI = 10 ) still showed decreased survival in comparison to IP17 ( MOI = 5 or 2 . 5 ) at 23 h post infection ( Figure S2AB ) . Therefore , IP2666 shows reduced intracellular survival , in contrast to IPI7 , which shows an intracellular growth phenotype , indicating that deletion of yopE and yopH promotes Yersinia survival inside macrophages . To further elucidate the effects of YopE and YopH on intracellular survival of Yersinia , IP2666 ( wild-type ) , IP6 ( yopE− ) , IP15 ( yopH− ) and IP17 ( yopEH− ) ( Table 1 ) were compared by CFU assay ( Figure 1B ) . IP6 showed an intracellular growth phenotype similar to IP17 , while IP15 had an intermediate phenotype ( Figure 1B ) . The results were further confirmed by fluorescence microscopy . IP2666 , IP6 and IP17 encoding GFP were used to infect BMDMs for different lengths of time . One hour before fixation and examination of the samples by fluorescence microscopy , IPTG was added to induce de novo expression of GFP from viable intracellular bacteria ( Figure 2 ) . At 23 h post infection , IP6 and IP17 showed greater survival compared to IP2666 ( Figure 2 ) . These results demonstrate that YopE is required for reduced survival of Yersinia in macrophages , and YopH cooperates with YopE in this process . To determine whether SytVII-mediated phagolysosome fusion contributes to YopE-dependent intracellular killing , SytVII−/− BMDMs were compared to wild-type BMDMs for their ability to restrict intracellular survival of IP2666 , IP17 or IP40 ( yopB mutant , Table 1 ) . The SytVII−/− genotype was verified by PCR using mouse-tail genomic DNA , in comparison to wild-type mice ( Figure S3A ) . No significant difference was observed by CFU assay for IP2666 survival inside wild-type or SytVII−/− BMDMs ( Figure S3B ) , suggesting that SytVII-mediated phagolysosome fusion does not contribute to the YopE-dependent killing of Yersinia in macrophages . Under our experimental conditions , Yersinia infection does not cause significant cell death of macrophages ( below 2% LDH release after 23 h from IP2666 or IP6 infected macrophages , data not shown ) . Accordingly , reduced intracellular survival of IP2666 is not due to enhanced Yersinia-induced macrophage cell death . We also investigated the possibility that IP2666 infection induces gentamicin uptake and leads to enhanced bacterial killing by gentamicin . If this is true , with increasing amount of gentamicin , intracellular IP2666 would be more sensitive than IP17 , due to more gentamicin uptake . To analyze this possibility , the survival of IP2666 and IP17 in macrophages was compared with increasing amount of gentamicin . IP2666 and IP17 responded similarly to increasing amounts of gentamicin ( Figure S4 ) , indicating that reduced intracellular survival of IP2666 is not due to increased gentamicin internalization . To investigate if the GAP activity of YopE is crucial for macrophages to restrict survival of intracellular Yersinia , experiments were carried out to compare survival of bacteria producing YopE or YopER144A . In YopER144A , a single substitution of arginine to alanine was introduced at amino acid 144 to yield a catalytically dead protein [14] . A plasmid vector encoding yopE or yopER144A was introduced into IP6 ( Table 1 ) . The production level of YopE or YopER144A from the vector in trans was similar to the native level in the wild-type strain as shown by SDS-PAGE and immunoblotting ( Figure 3A , compare lanes 1 , 3 and 4 ) . The survival of IP6+pYopE and IP6+pYopER144A in macrophages was then compared . IP2666 or IP6 containing the empty vector ( Table 1 ) were analyzed in parallel as controls . IP6+pYopE displayed a reduced intracellular survival phenotype , similar to IP2666+empty vector ( Figure 3B ) . In contrast , IP6+pYopER144A showed increased intracellular survival , comparable to IP6+empty vector ( Figure 3B ) . Unexpectedly , the empty vector ( pMMB67HE ) had a negative effect on Yersinia survival inside macrophages ( Figure S5 ) , possibly due to the metabolic burden introduced by the plasmid [28] , [29] . Nevertheless , these results demonstrate that YopE GAP activity is indispensable for causing reduced survival of Yersinia in macrophages , and we hypothesize that YopE GAP activity is somehow recognized by macrophages , triggering increased killing of intracellular Yersinia . Given the activity of YopT towards Rho GTPases and its crosstalk with YopE , the potential influence of YopT on survival of Yersinia inside macrophages was studied . IP2666 is a yopT mutant due to a naturally-occurring deletion in pYV in this strain [30] . Plasmids that overexpress YopT or catalytically-inactive YopTC139S were introduced into IP2666; control strains containing the empty vector or a plasmid producing native levels of YopT under its native promoter were also constructed ( Table 1 ) . Analysis of proteins secreted by the bacteria under low calcium conditions using SDS-PAGE and immunoblotting showed that YopT and YopTC139S were overproduced at equal levels , while the native level of YopT was undetectable ( Figure 4A , compare lanes 2 , 3 and 4 ) . Interestingly , when these strains were used to infect macrophages , overexpression of YopT in IP2666 significantly increased Yersinia intracellular survival , giving the opposite effect of YopE ( Figure 4B and Figure S6A ) . Yersinia survival in macrophages was moderately increased when YopTC139S was overexpressed in IP2666 ( Figure 4B and Figure S6A ) , indicating that YopT catalytic activity is important for counteracting the YopE-triggered killing effect . Expression of YopT at native level in IP2666 also slightly improved Yersinia intracellular survival ( Figure 4B and Figure S6A ) . Using detergent extraction assay and immunoblotting , lysates of infected macrophage were analyzed to detect the amounts of YopE that were translocated by the different strains . Overexpression of YopT or YopTC139S in IP2666 diminished YopE translocation to 8% or 25% of wild-type level respectively ( Figure S7AB ) . Native level of YopT in IP2666 slightly reduced YopE translocation ( 75% of wild-type level ) ( Figure S7AB ) . Active and inactive YopT proteins were overexpressed in IP6 or IP37 to further examine the mechanism by which this effector counteracts killing of Yersinia in macrophages . Overexpression of YopT or YopTC139S in IP6 equally enhanced bacterial survival ( Figure S6B ) , while overexpression of active or inactive YopT proteins in IP37 had no effect on Yersinia survival inside macrophages ( Figure S6C ) . Taken together , these results suggest that YopT has the ability to counteract YopE-triggered intracellular killing effect , which is partially dependent on YopT protease activity . YopT catalytic activity may counteract the YopE effect by competing with YopE for a Rho GTPase target or by reducing YopE translocation . Thus , inactivation of a Rho GTPase by a specific mechanism , i . e . GAP mechanism , appears to be sensed by macrophages , resulting in increased killing of intracellular Yersinia . Localization to membranes and stability of YopE are critical for functional GAP activity against Rho GTPases in host cells [15] , [16] , [19] . Since our results suggest that YopE GAP activity is sensed by macrophages , we hypothesize that membrane localization and stability of YopE will impact its ability to stimulate an intracellular killing response . To examine this possibility , plasmids encoding YopE variants that were defective for membrane localization ( YopE3N ) [17] or less stable ( YopER62K ) [19] were introduced into IP6 . The resulting strains ( Table 1 ) were used to infect macrophages and detergent extraction assays were used to compare the amounts of YopE , YopE3N and YopER62K that were translocated . The yopB mutant IP40 , which is defective for Yop translocation , was used to infect macrophages as a negative control . The amount of YopE3N in the soluble fraction was comparable to wild-type YopE , indicating equal translocation of these proteins ( Figure 5A , compare lanes 3 and 1 ) . Some YopE proteins with reduced Rho GAP activity are translocated at higher levels as compared to the wild-type protein into epithelial cells infected with Y . pseudotuberculosis [31] . We did not observe hypertranslocation of YopE proteins with reduced Rho GAP activity in our experiments , possibly because YopE has a reduced ability to negatively regulate its own translocation into macrophages as compared to epithelial cells . The amount of YopER62K in the soluble fraction was lower compared to wild-type YopE , probably due to decreased stability as a result of increased ubiquitination ( Figure 5A , compare lanes 5 and 1 ) . The appearance of a slower migrating band for YopER62K was consistent with ubiquitination ( Figure 5A , lane 5 ) . IP6+YopE3N and IP6+YopER62K displayed improved survival in macrophages in comparison to IP6+YopE at 24 h post infection , as determined using immunofluorescence microscopy to detect intracellular Yersinia ( Figure 5B ) . The results , quantified by the percentage of macrophages containing fluorescent intracellular Yersinia ( Figure 5C ) , or CFU assay ( Figure S8A ) , showed that IP6+YopE3N and IP6+YopER62K had increased bacterial survival compared to IP6+YopE at 24 h post infection . Since membrane localization and stability are important for YopE to efficiently inactivate Rho GTPases , these results provide additional evidence that macrophages sense the inactivation of one or more Rho GTPases , which results in killing of intracellular Yesinia . YopE variants with altered Rho GTPase specificities [31] were compared to wild-type YopE for their capability to trigger intracellular killing response . YopEL109A has lower GAP activity towards RhoA ( 70% of wild-type level ) and Rac2 ( 70% of wild-type level ) ; YopE-SptP fusion protein , which contains the secretion and translocation domains of YopE and the GAP domain of SptP , has no GAP activity towards RhoA and decreased activity towards Rac1 ( 83% of wild-type level ) and Rac2 ( 34% of wild-type level ) [31] . The amounts of translocated YopEL109A and YopE-SptP were comparable to wild-type YopE in Yersinia-infected macrophages , and YopE-SptP displayed reduced mobility as expected due to its higher molecular weight ( Figure 5A , compare lanes 1 , 2 and 4 ) . At 24 h post infection , IP6+YopEL109A and IP6+YopE-SptP showed improved survival inside macrophages compared to IP6+YopE , as demonstrated by immunofluorescence microscopy ( Figure 6AB ) and CFU assays ( Figure S8B ) . These results indicate that the specificity of YopE GAP activity may impact its ability to trigger the intracellular killing . However , the results obtained with the YopEL109A and YopE-SptP variants did not reveal if inactivation of a specific Rho GTPase by YopE is important for intracellular killing . Since the activity of YopEL109A and YopE-SptP towards Rho GTPases other than RhoA , Rac1 and Rac2 is not clearly known , it is difficult to declare YopE interruption of which specific Rho GTPase is essential for macrophage recognition and intracellular killing . To explore if this intracellular killing response applies to bacterial toxins targeting Rho GTPases , Clostridium difficile Toxin B was added to Yersinia infected macrophages . Toxin B has been well characterized to inactivate a wide range of Rho GTPases through glycosylation , including Rac1 , RhoA/B/C , RhoG , TC10 , and Cdc42 [32]–[34] . With Toxin B treatment , the survival of IP6 , IP17 and IP40 was dramatically decreased as revealed by CFU assays ( Figure 7A and B ) and fluorescence microscopy in conjunction with mCherry induction ( Figure 7C ) . Toxin B did not affect Yersinia growth in tissue culture media in the absence of macrophages; Toxin B did not cause significant cytotoxicity in macrophages in these experiments ( data not shown ) . These results suggest that down-regulation of Rho GTPases by Toxin B is perceived by macrophages , inducing an intracellular killing response , mimicking the effect of YopE . Thus , the bactericidal effect triggered by Rho GTPase-inactivating toxins may be a general and conserved response to these bacterial toxins . In addition , the fact that Toxin B decreases IP40 survival inside macrophages implies that T3SS translocon is not essential for macrophage recognition of Rho GTPases-inactivating toxins to cause a bactericidal response . To identify the Rho GTPase target of YopE critical for causing intracellular killing , specific Rho GTPase inhibitors were studied for their capability to mimic the YopE effect . Treatment with Rac1 inhibitor NSC23766 negatively impacted IP6 and IP40 survival inside macrophages , as demonstrated by CFU assays ( Figure 8AB ) and fluorescence microscopy with mCherry induction ( Figure 8C ) . The Rac1 inhibitor triggered a reduced bactericidal effect in comparison to Toxin B in the CFU assay ( compare Figure 7AB and 8AB ) . In contrast to the Rac1 inhibitor , the RhoA inhibitor TAT-C3 did not significantly affect Yersinia survival inside macrophages ( Figure S9BC ) . Dramatic morphological changes were observed in TAT-C3 treated macrophages as early as 4 h upon treatment , confirming the efficiency of TAT-C3 towards RhoA ( Figure S9A ) . These results signify that macrophages restrict Yersinia intracellular survival in response to Rac1 inhibition , but not to Rho inhibition . Several recent studies have shown that the activities of certain bacterial effectors can stimulate transcriptional changes in host cells , resulting in ETIRs [5]–[9] . For example , activation of Rac1 and Cdc42 by SopE from Salmonella enterica serovar Typhimurium is sensed through NOD1 receptor , eliciting NF-κB activation in the host cells as a protective response [9] . To study if YopE stimulates an altered host response that can occur at the transcriptional level , the production of nitric oxide ( NO ) from macrophages infected with IP2666 , IP6 , IP17 or IP40 was compared . Specifically , the concentration of nitrite ( NO2− ) , an indicator of NO , was measured by Griess assay . At 23 h post infection , comparing to IP6- , IP17- or IP40-infected macrophages , IP2666-infected macrophages produced significantly higher levels of NO ( Figure 9 ) . LPS- and IFN γ-treated macrophages were used as a positive control , while uninfected macrophages were used as a negative control ( Figure 9 ) . To investigate whether YopE dependent-intracellular killing signals through NOD1 receptor , Nod1−/− BMDMs were compared to wild-type BMDMs for their ability to restrict intracellular survival of IP2666 or IP6 by CFU assay . No significant difference was observed for IP2666 survival inside wild-type or Nod1−/− BMDMs ( Figure S10 ) . These results suggest that macrophages respond to wild-type Yersinia differently from yopE− mutant strains and produce higher levels of NO; however , YopE-triggered intracellular killing is not mediated by NOD1 receptor .
The aims of this study were to determine T3SS-dependent factors that restrict Yersinia survival inside macrophages and characterize the mechanism of this “patterns of pathogenesis” triggered host response . Our findings reveal that primary naïve macrophages sense manipulation of Rho GTPases by Yersinia Yop effectors . Three known effector Yops directly inhibit host Rho GTPases: YopE , YpkA and YopT; a fourth effector , YopH , inhibits signals that activate these small GTPases . YopE is an important virulence factor for resistance of Yersinia to the innate immunity , as a Y . pseudotuberculosis yopE null mutant was defective for systemic spread following oral infection in the animal model [35] . However , on the other hand , here we show that YopE GAP activity towards Rho GTPases is recognized by macrophages , stimulating increased killing of intracellular Y . pseudotuberculosis ( Figure 10 ) . YopH cooperates with YopE to cause this killing effect , most likely by inhibiting a phosphotyrosine dependent signaling pathway that activates Rho GTPases in response to Yersinia infection ( Figure 10 ) . YpkA has very mild effect on Yersinia intracellular survival ( data not shown ) , perhaps due to its low expression level in comparison to other Yops . Interestingly , we have observed that overexpression of YopT counteracts the YopE-triggered intracellular killing effect , which involves the protease activity of YopT . We speculate that an important biological function of YopT is to counteract sensing of YopE by the innate immune system , possibly by preventing YopE access to activated Rho GTPase targets or removing YopE-inactivated Rho GTPases from phagosome membranes ( Figure 10 ) . Zhang et al . studied a Y . pseudotuberculosis strain ( 32777 ) , different from that used here ( IP2666 ) , and showed that a mutant of 32777 encoding catalytically inactive YopJ , YopT , YopE and YopH still triggered intracellular bacterial killing , to the same level as wild-type 32777 [25] . We speculate that 32777 has additional Rho GTPase-inactivating effector ( s ) causing bacterial killing , which remain to be identified . We have obtained evidence that Toxin B decreases Yersinia survival in macrophages by inactivating several Rho GTPases ( Figure 10 ) . To date , at least 20 Rho GTPase proteins belonging to 8 subfamilies have been described in mammals [36] , [37] . Interestingly , we have shown that the target preference of YopE impacts its ability to trigger bacterial killing . Thus , one intriguing question to ask is does the innate immune system monitor effector manipulation of a specific Rho GTPase ? Our results showed that Rac inhibition , but not Rho inhibition , stimulates the macrophage killing response against intracellular Yersinia ( Figure 10 ) . However , the Rac inhibitor only partially promotes killing of Yersinia in macrophages in comparison to Toxin B or YopE , suggesting that disturbance of additional Rho GTPases contributes to the intracellular killing response . Other Rho GTPase candidates may include , but are not limited to , Rac2 and RhoG , which have been shown to be YopE targets and expressed in macrophages [31] , [37]–[39] . Further investigation is required to reveal if additional Rho GTPases serve as surveillance points in response to pathogenic effector manipulation [37] . Rho GTPases act as molecular switches that regulate numerous cellular functions , like cytoskeletal dynamics , gene transcription , vesicular trafficking , cell growth and apoptosis [37] , [40] . In order to ensure proper signaling responses , the activities of Rho GTPases are tightly regulated by multiple mechanisms , including the canonical regulators ( GAPs , GEFs and GDIs ) and direct post-translational modifications ( like phosphorylation and ubiquitination ) [40] , [41] . The abnormal inactivation of Rho GTPases by YopE might interfere with multiple Rho GTPase-mediated signaling pathways and lead to many different consequences to trigger intracellular bacteria killing in macrophages . One possibility is that YopE may cause accumulation of inactivated GDP-bound Rho GTPases on phagosome ( Figure 10 ) , which could be modified by ubiquitination to stimulate signaling pathways . Activation of Rac1 by cytotoxic necrotizing factor 1 ( CNF1 ) from Escherichia coli induces Rac1 poly- and mono-ubiquitination , the biological function of the latter remains unclear [42] . In line with this , GDP-bound RhoA is targeted by the ubiquitin E3 ligase Cullin-3 for poly-ubiquitination and degradation [43] . Thus , it is tempting to speculate that YopE-inactivated GDP-bound Rho GTPases could be mono-ubiquitinated and serve as signaling components; or they could be poly-ubiquitinated to mediate xenophagic degradation of bacteria-containing vesicles [44] . Alternatively , by modulating vesicular trafficking , YopE activity may interrupt formation of Y . pseudotuberculosis-containing autophagosomes , which have been shown to be impaired in acidification and support survival of the bacteria in macrophages [45] . On the other hand , given that the role of autophagy in Yersinia survival in macrophages is controversial [45] , [46] , it is possible that YopE activity promotes autophagy to eliminate intracellular bacteria . Deuretzbaher et al . showed that β1-integrin-mediated Y . enterocolitica internalization by macrophages was coupled to autophagy activation , which seemed to be deleterious for bacterial intracellular survival . Another possibility is that the disruption of the actin cytoskeleton by YopE is sensed by the innate immune system . It has been suggested that NOD receptors or inflammasome components associated with the actin cytoskeleton may act as surveillance mechanisms , becoming activated upon perturbations by pathogens [2] . Interesting , a recent study by Shao and colleagues showed that Rho-inactivating toxins such as Clostridium difficile Toxin B and Clostridium botulinum C3 trigger Pyrin inflammasome activation in BMDMs [47] . They further demonstrated that Burkholderia cenocepacia induced inactivation of Rho GTPase stimulates Pyrin inflammasome activation as an immune defense , which limits bacterial intra-macrophage growth and regulates lung inflammation in infected mice [47] . Whether YopE triggers Yersinia intracellular killing through the inflammasome pathway remains to be investigated . The overall host cell innate immune response to a T3SS-containing bacterial pathogen is unique and multifactorial . MAMPs , the T3SS translocon channel , and the activities of bacterial effectors are likely recognized as combined pathogenic signals by the host cell . A two-signal model , requiring a MAMP and a pattern of pathogenesis , was proposed as an innate immune strategy to evaluate the virulence potential of a pathogen and adjust immune response appropriately to avoid self-damaging inflammation [48] . For example , a type IV secretion system allows Legionella pneumophila to deliver bacterial effectors into the host cell cytosol to inhibit host protein synthesis [6] . In this case , the effector-mediated interference of host protein synthesis , in concert with TLR signaling , results in prolonged activation of NF-κB as an ETIR [6] . Our data suggest that the YopBD translocon is not essential for Toxin B- or Rac inhibitor-triggered bacterial killing in macrophages . Further studies are needed to determine if TLRs or β1-integrins are possible receptors in MAMP-PRR pathways that facilitate the YopE-triggered killing effect . Alternatively , some studies in the literature support the idea that patterns of pathogenesis are sufficient to induce defense responses independently of classical MAMPs [5] , [49] , [50] . Boyer et al . demonstrated that Escherichia coli CNF1 elicited a vigorous ETIR in flies via activation of Rac2 and the IMD kinase pathway , which was observed even in the absence of PRR ligation [5] . Thus , it is possible that unbalanced disruption of Rho GTPases by YopE is adequate to stimulate a protective immune response , resulting in restriction of Yersinia survival in macrophages . Roy and colleagues observed that during internalization of Salmonella enterica serovar Typhimurium or Y . pseudotuberculosis , the T3SSs of these pathogens stimulated SytVII-dependent phagolysosome fusion and bacterial killing in macrophages [26] . We have shown that YopE-triggered intracellular bacterial killing does not require SytVII , suggesting that there are at least two independent pathways by which killing of Yersinia internalized by macrophages can be stimulated . The YopE-dependent pathway senses inactivation of Rho GTPases , while the SytVII dependent pathway appears to recognize translocon insertion in the plasma membrane . Various bacterial T3SS and T4SS effectors modulate Rho GTPase functions and interfere with corresponding host signaling pathways to benefit pathogenic infection [51] . Given that Rho GTPases play multiple roles in many signaling pathways critical for cellular functions , it is not surprising to envision surveillance mechanisms monitoring the status of Rho GTPases . Our work highlights that inactivation of Rac1 , and possibly other GTPases , by YopE from Y . pseudotuberculosis is detected by macrophages as a danger signal , stimulating an ETIR that restricts intracellular bacterial survival . Detection of pathogens via Rho GTPase surveillance adds another layer of complexity to the mechanisms of innate immune recognition , improving our understanding of how the innate immune system responds to pathogenic infection .
Use of mice for the preparation of BMDMs was carried out in accordance with a protocol that adhered to the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health ( NIH ) and was reviewed and approved ( approval #206152 ) by the Institutional Animal Care and Use Committee at Stony Brook University , which operates under Assurance #A3011-01 , approved by the NIH Office of Laboratory Animal Welfare . The Y . pseudotuberculosis strains used in this study are shown in Table 1 . These bacteria were grown on LB agar plates or in LB broth at 28°C supplemented with 100 µg/ml ampicillin , 25 µg/ml kanamycin or 30 µg/ml chloramphenicol as needed . The plasmids pMMB67HE [52] , pYopE [14] , pYopER144A [14] , pPEYopE [30] , pYopT [53] , pPTYopT [30] , pYopTC139S [18] , p67GFP3 . 1 [23] and p207mCherry [54] have been previously described . A new series of plasmids expressing yopE mutants were created as described below . Plasmids encoding yopEL109A , yopER62K and yopE3N were generated as follows . DNA fragments encoding yopEL109A , yopER62K or yopE3N were obtained by PCR using primers yopE-3 ( 5′-CGGATCCCATATGAAAATATCATCATTTATTTC-3′ ) and yopE-EcoRI ( 5′-CGCGGAATTCCCATATCACATCAATGACAGTAATTT-3′ ) . Recombinant plasmid DNA ( pBAD33/YopEL109A , a gift from Joan Mecsas , Tufts University ) , or Y . pseudotuberculosis virulence plasmid DNA ( from 32777 yopER62K or 32777 yopE3N , Zhang et al . submitted ) was used as template for the PCR to obtain yopEL109A , yopER62K and yopE3N , respectively . The resulting DNA fragments were inserted into pETBlue2 vector using blunt end ligation . To create a plasmid encoding the yopE-sptP fusion , a DNA fragment containing the first 100 codons of yopE ( yopE1–100 ) was amplified from IP2666 virulence plasmid DNA with primers yopE-infusion-5 ( 5′-TAATAAATAGTCATATGAAAATATCATCATTTATTTCTACATCACTG-3′ ) and yopE-infusion-3 ( 5′-AGGTTGCTTACTTTCCGTAGGACTTGGCATTTGTGC-3′ ) . A DNA fragment containing codons 166–293 of sptP ( sptP166–293 ) was amplified with primers sptP-infusion-5 ( 5′-ATGCCAAGTCCTACGGAAAGTAAGCAACCTTTACTCAGTATCG-3′ ) and sptP-infusion-3 ( 5′-CAGCCAAGCTGAATTTTAGCCGGCTTCTATTTTCTCAAGTTC-3′ ) using chromosomal DNA from Salmonella enterica Typhimurium strain 14028 as template . A DNA fragment encoding the yopE1–100sptP166–263 fusion was made by overlapping PCR using the yopE1–100 and sptP166–293 fragments as templates and primers yopE-infusion-5 and sptP-infusion-3 . The product was inserted into pETBlue2 by blunt end ligation . The sequences of the inserts in the plasmids described above were confirmed by DNA sequencing . DNA fragments encoding yopEL109A , yopER62K , yopE3N or yopE1–100sptP166–263 were obtained from the pETBlue2 vectors by digestion with NdeI and EcoRI , and ligated between the NdeI and EcoRI sites in pPEYopE , thereby replacing the wild-type yopE gene , and placing the mutant alleles under control of the native yopE promoter . The resulting plasmids pYopEL109A , pYopER62K , pYopE3N and pYopE-SptP were introduced into E . coli S17-1 λpir by electroporation and subsequently transferred into IP6 ( Table 1 ) by conjugation as described previously [55] . Bone marrow-derived macrophages ( BMDMs ) were isolated and cultured from femurs of C57BL/6 wild-type mice ( Jackson Laboratory ) or SytVII−/− C57BL/6 mice ( a generous gift from Dr . Norma Andrews , University of Maryland ) , or Nod1−/− C57BL/6 mice ( a generous gift from Dr . Andreas Baumler , University of California-Davis ) as previously described [56] . 24 h before infection , macrophages were seeded into 24-well tissue culture plate at a density of 1 . 5×105 cells/well in Dulbecco's modified Eagle medium supplemented with 10% fetal bovine serum ( Hyclone ) , 15% L-cell conditioned medium , 1 mM sodium pyruvate and 2 mM glutamate . Y . pseudotuberculosis strains were grown at 28°C in LB broth with aeration overnight . The next day , overnight cultures were diluted 1∶40 into fresh LB broth containing 2 . 5 mM CaCl2 and sub-cultured at 37°C for 2 h to induce yop gene expression . Bacteria were washed once and resuspended in HBSS to obtain optical density at OD 600 nm . Next , bacteria were diluted into cell culture medium to infect macrophages at an MOI of 10 , unless specified . After centrifugation for 5 min at 700 rpm to facilitate bacterial contact with macrophages , another 15 min incubation was performed at 37°C , giving the total infection time of 20 min . The end of 20 min incubation is considered as 0 h post infection . To eliminate extracellular bacteria , unless specified , the cells were then incubated in medium containing 8 µg/ml gentamicin for 1 h , and then maintained in fresh medium containing 4 . 5 µg/ml gentamicin until the end of incubation . When indicated , 40 ng/ml Toxin B ( Calbiochem ) , 100 µM NSC23766 ( Calbiochem ) , or 10 µg/ml TAT-C3 was added at 0 h post infection and maintained throughout the experiment . TAT-C3 was purified and kindly provided by Dr . Gloria Viboud , Stony Brook University [57] . At the time points indicated in the figures , the infected BMDMs were washed twice with HBSS , lysed and scraped with 500 µl 0 . 1% Triton X-100 in HBSS to release intracellular bacteria . After collecting the lysates , 500 µl HBSS was used to rinse the wells and collect any residual bacteria . The lysates and the wash were combined , serially diluted and spread on LB plates , and then incubated at 28°C for 2 days to enumerate output CFU . The primary antibodies used were a cocktail of two monoclonal mouse anti-YopE antibodies designated 202 and 149 ( unpublished data ) , the monoclonal mouse anti-YopH antibody designated 3D10 ( a gift from Dr . Richard Siegel , NIH ) diluted 1∶1000 , a polyclonal rabbit anti-YopT antibody diluted 1∶500 [30] , and a polyclonal rabbit anti-β-actin antibody ( Cell signaling ) diluted in 1∶1000 . The secondary antibodies used were a goat anti-mouse antibody conjugated to IRD800 ( Rockland ) diluted 1∶5000 and a donkey anti-rabbit antibody conjugated to IRD800 ( Rockland ) diluted 1∶5000 . The protein samples were separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis , transferred to nitrocellulose membranes , and subjected to immunoblotting with specific primary and secondary antibodies . The membranes were then scanned and analyzed with the Odyssey system ( Li-Cor Biosciences ) . BMDMs were prepared and infected as described above , except that they were seeded into wells with glass coverslips , which had been washed with acetone and heated at 180°C for 4 h to remove LPS . At indicated time points , infected BMDMs were washed three times with PBS and fixed with 2 . 5% PFA for 10 min . When needed , 0 . 5 mM Isopropyl-β-D-thiogalactopyranoside ( IPTG ) was added at 1 h before fixation to induce de novo GFP expression , or at 2 h before fixation to induce de novo mCherry expression . When indicated , immunofluorescence staining was performed as described previously [23] . Briefly , the fixed cells were permeabilized with 0 . 1% Triton X-100 in PBS for 1 min , followed by blocking with 3% bovine serum albumin in PBS for 10 min . The cells were then incubated with a polyclonal rabbit anti-Yersinia antibody SB349 diluted 1∶1000 for 30 min . After washing with PBS , the cells were incubated with FITC conjugated anti-rabbit antibody ( Jackson Laboratories ) diluted 1∶250 for 40 min . After washing , the coverslips were inverted onto 6 µl Prolong Gold anti-fade reagent ( Invitrogen ) on a microscope slide . The slides were examined by fluorescence microscopy using a Zeiss Axioplan2 microscope with a 32× objective . Three randomly selected fields of each slide were examined . In each field , about 50 BMDMs were examined from merged images of phase contrast and fluorescence , which were captured with a Spot camera ( Diagnotic Instruments , Inc ) and processed with Adobe Photoshop . Percentage of cells containing bacteria was quantified using three independent experiments . Detergent extraction assays were performed as previously described in [58] . BMDMs were infected as described above , except that they were seeded in 6 well plates at a density of 8×105 cells/well and infected at an MOI of 30 for 2 h . The infected cells were washed twice with ice-cold HBSS and lysed with 50 µl 1% Triton X-100 in HBSS containing EDTA-free protease inhibitor cocktail ( ROCHE ) . After 10 min on ice , the cells were scraped from the plate to collect the lysates . The soluble and insoluble fractions of the lysates were separated by centrifugation ( 14000 rpm , 10 min , 4°C ) and subsequently analyzed using immunoblotting as described above . Chromosome DNA was isolated from C57BL/6 wild-type or SytVII−/− mouse tails and used as templates for PCR amplification . Briefly , tail tips were digested in 500 µl lysis buffer ( 0 . 1M NaCl , 0 . 05M Tris-HCL pH 7 . 7 , 1% SDS and 2 . 5 mM EDTA ) with 40 µg/ml freshly added proteinase K ( Sigma ) , and incubated at 55°C overnight . The resulting supernatant were collected and mixed with 500 µl isopropanol to precipitate chromosomal DNA . After centrifugation ( 14000 rpm , 10 min , RT ) , the pellets were washed twice with 70% ethanol , air-dried for 5 min , and dissolved in 100 µl TE buffer . Genotyping PCR were performed with the following primers: P1 ( 5′-CATCCTCCACTGGCCATGAATG-3′ ) , P2 ( 5′-GCTTCACCTTGGTCTCCAG-3′ ) , P3 ( 5′-CTTGGGTGGAGAGGCTATTC-3′ ) and P4 ( 5′-AGGTGAGATGACAGGAGATC-3′ ) . PCR products were analyzed by agarose gel electrophoresis . NO levels generated by infected macrophages were determined by measuring the accumulation of nitrite ( NO2− ) using the Griess assay as described previously [59] . Control macrophages were treated with E . coli LPS ( 100 µg/µl , Sigma ) and IFN γ ( 0 . 1 units/µl , ROCHE ) throughout the experiment . At 23 h post infection , conditioned medium were collected and centrifuged ( 14000 rpm , 10 min , RT ) . 100 µl of the supernatant was mixed with 100 µl Griess reagent ( 0 . 5% sulfanilamide and 0 . 05% N- ( 1-naphthyl ) ethylenediamide in 2 . 5% acetic acid ) and incubated for 10 min at room temperature . The samples were then measured at OD550 nm . The concentration of NO2− was calculated by using a standard curve prepared with sodium nitrite . The GenBank accession number for the YopE protein studied in this work is CAA68609 . 1 . | The type III secretion system ( T3SS ) is a macromolecular protein export pathway found in gram-negative bacteria . It delivers bacterial toxins into eukaryotic cells to promote pathogenic infection . T3SSs and the bacterial toxins delivered are critical arsenals for many bacterial pathogens of clinical significance , such as Yersinia , Salmonella and Shigella . On the other hand , the mammalian immune system may recognize the T3SS as a danger signal to signify pathogenic infection , and to stimulate appropriate defense against pathogens . Here , we show that the innate immune system recognizes the activity of YopE delivered by the Yersinia T3SS . Modulation of host Rho GTPases by YopE elicits a defensive response , which results in killing of bacteria in host cells . Inhibition of host Rho GTPases by Clostridium difficile Toxin B , another bacterial toxin , mimics the YopE-triggered killing effect . Our study demonstrates that host cells sense manipulation of Rho GTPases by bacterial toxins as a surveillance mechanism , revealing new insights into innate immune recognition of pathogenic infections . | [
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"sciences"... | 2014 | The GAP Activity of Type III Effector YopE Triggers Killing of Yersinia in Macrophages |
Standard human landing catches ( sHLCs ) have historically been a key component of Onchocerca volvulus transmission monitoring , but expose health-workers to potentially hazardous vector bites . Novel human-bait-free trapping methods have been developed , but do not always work where they are needed and may not generate O . volvulus surveillance data that is directly comparable with historic data . Simuliid sHLCs and mineral-oil protected HLCs ( mopHLCs ) were performed in a rural village of Amazonas state , Brazil . A four-hour direct comparisons of sHLCs and mopHLCs was carried-out using six vector collectors , each of whom used one leg for a sHLC and one for a mopHLC . Two-person collection teams then exclusively performed either mopHLCs or sHLCs for a further set of 12 four-hour collections . Following the completion of all collections , simuliid-bite mark estimates were made from legs used exclusively in sHLCs and legs used exclusively in mopHLCs . All of the 1669 captured simuliids were identified as the O . volvulus vector Simulium oyapockense . Overall , mopHLC simuliids captured per hour ( S/H ) rates were lower than those obtained with sHLC trapping ( 15 . 5 S/H versus 20 S/H ) . Direct comparisons of simuliid capture rates found that vector-collectors captured simuliids significantly more efficiently ( x¯: 20 . 5 S/H ) with mopHLC trapping than with sHLC trapping ( x¯: 16 . 4 S/H ) : P-value = 0 . 002 . MopHLCs performed in isolation were , however , observed to capture vectors less efficiently ( x¯: 13 . 4 S/H ) than sHLCs performed under similar conditions ( x¯: 19 . 98 S/H ) . All six vector collectors had significantly higher simuliid capture per counted bite mark ( SC/CBM ) rates using mopHLCs than they were observe to have using sHLCs ( x¯: 21 SC/CBM versus x¯: 1 SC/CBM; p-value = 0 . 03125 ) . Vector collectors captured significantly more simuliids per counted bite mark with mopHLCs than with sHLCs . Further investigations into the utility of mopHLCs for onchocerciasis xenomonitoring and beyond are merited .
A key component of the WHO´s nascent onchocerciasis elimination programme is the entomological monitoring of O . volvulus transmission by its blackfly vectors [1 , 2] . Historically , the African Programme for Onchocerciasis Control ( APOC ) and Onchocerciasis Elimination Program for the Americas ( OEPA ) have used human-baited vector collection ( HBVC ) to calculate infectious bite rates [1–3] . These rates have , in turn , been used to classify regional onchocerciasis endemicity levels and to plan for the cessation of mass drug administration [3–7] . While the epidemiological data generated from such HBVC continues to be valued for such purposes , there is increasing concern about the health risk that the use of this technique poses to vector collectors [8–10] . In order to avoid such health risks , alternative vector capture methods have been developed . Bellec [11] and Bellec-style traps [12 , 13] , which capture ovipositing rather than host-seeking female blackflies , can be used to capture O . volvulus infected female blackflies [12 , 13] . However , these traps are not as efficient or convenient as HBVC and questions have been raised as to whether epidemiological data generated from such trapping can be compared directly with historical data obtained from traditional HBVC [9] . Recently , Esperanza Window Traps ( EWTs ) , which use visual and gaseous ( CO2 ) cues to allure host-seeking onchocerciasis vectors , have been developed [8 , 9] . While epidemiological data collected from these EWTs is more likely to be comparable with that collected with HBVCs , which also target host-seeking female blackflies , these traps have not worked everywhere they have been trialled and therefore probably cannot be used everywhere O . volvulus entomological monitoring is needed [8 , 9] . The WHO´s nascent lymphatic and onchocerciasis elimination programme thus urgently needs novel methods of blackfly capture , which do not expose vector collectors to unnecessary risks from vector bites [1 , 2] . Both the Bellec and EWT trapping methods capture blackflies by immobilizing and suffocating them with a viscous liquid substance that gums-up their delicate wings , legs and respiratory spiracles [8–13] . Here , we have applied mineral oil directly to the legs of vector collectors in order to combine HBVC with mineral oil vector capture . Our work has specifically tested , whether this type of HBVC reduces the number of onchocerciasis vector bites suffered by vector collectors during their collections and therefore whether WHO policy makers should consider recommending this type of vector collection as a substitute for standard human landing catches ( sHLCs ) .
This study was performed in São Gabriel da Cachoeira , which is a rural village of Amazonas state , Brazil . The village is situated deep in the amazon rainforest and close to , but outside , the WHO-recognized Amazonia onchocerciasis focus [14–17] . All of the vector collection sites used for this study are ~600 km South West of the onchocerciasis endemic Yanomami mission post known as Toototobi [17] . São Gabriel da Cachoeira shares many ecological , geophysical and climatic conditions with Toototobi , but , critically , is not thought to have ever had any O . volvulus transmission [14–17] . Critically too , Simulium oyapockense , which is thought to be the principal O . volvulus vector in Toototobi , is also known to occur abundantly and to bite humans in high numbers in São Gabriel da Cachoeira [15 , 16] . This village was , thus , considered an ideal location to assess the utility and safety of mopHLC trapping as it was assumed that vector collectors would not be exposed to any unnecessary risk of O . volvulus infection . In a pilot study performed in São Gabriel da Cachoeira between the 25th and the 30th of September ( inclusive ) , in which 4 , 781 simuliids were collected from five sites , all but one of the simuliids collected were identified as S . oyapockense . Although the one non-S . oyapockense collected in the pilot study ( which was identified as Simulium ochraceum ) is also a known vector of O . volvulus , we decided to exclude the collection site where it was captured in an attempt to collect data that was directly attributable to the behaviour of just one species of blackfly vector ( S . oyapockense ) . We chose to exclude another site used in the pilot study because it was the least productive of the remaining four . Blackfly vector collections for this study were , thus , performed at three sites within São Gabriel da Cachoeira , each more than 0 . 5 km apart: Collection site ( 1 ) : named Comunidade Areal: 0°8'60''S/66°57'7 . 2''W; collection site ( 2 ) : named “Porto de Camanaus”: 0°8'56''S/66°56'8 . 79''W , and collection site ( 3 ) : named “Casa de Camanaus”: 0°8'51''S/66°56'23 . 23''W . In order to recruit vector collectors without pre-existing simuliid bites on their legs , six Manaus residents were selected to participate in this study . While Manaus , like São Gabriel da Cachoeira , is also situated in Amazons state ( Brazil ) and is also surrounded by the Amazon rainforest , it is a city of more than two million inhabitants and suffers from high levels of watercourse pollution , which prevents simuliid larval breeding and thus simuliid adult biting in the area occurs only rarely ( if at all ) [18–20] . MopHLCs were performed by vector collectors applying approximately 50 ml of pharmaceutical-grade mineral oil to the skin surface of one of their legs . Vector collectors were asked to apply the mineral oil ( which was sourced from a local chemist ) evenly and as a thick continuous layer . They were also asked to avoid trying to rub the oil into their skin ( as one might with a sun cream ) so that the mineral oil formed a continuous barrier between the vector collectors´ skin and the open-air . The Rioquímica ( São Paulo , Brazil ) mineral oil used for this study is a typical pharmaceutical-grade mineral oil , which can be cheaply and easily purchased from chemists throughout Brazil . It is a colourless , odourless mixture of liquid hydrocarbons , produced from petroleum distillation . During mopHLC collections , blackflies landing on mineral oil protected legs were quickly immobilised by it and then transferred manually with watchmakers´ forceps from the oil to a glass collection tube filled with 100% ethanol . Blackflies landing on the unprotected legs were collected directly in ethanol using a sHLC collection procedure that is widely practiced in the area and elsewhere in the world [10 , 21] . For this procedure , the vector collector touched the ~1 . 5 cm diameter mouth of a 6 ml ( bijou-style ) glass collection tube ( brimming with 80–100% ethanol ) to a patch of their skin that a female blackfly that had just landed on [21] . Typically , during this study blackflies did not move before they came into contact with the tube´s ethanol and would subsequently sink to the bottom of the tube shortly after they had . Occasionally , blackflies would attempt to take-off before being collected; however , many of these blackflies were also collected as they often flew directly into the collection tube . The efficiency and safety of the mopHLCs and sHLCs vector capturing techniques was compared using a set of 24 four-hour vector collections performed daily between 8 am and 12 noon from the 26th to the 28th of October 2017 . The 24 collections used one vector collector leg each and were performed in two-person teams at the three collections sites , which are described in detail in the ‘study site selection” section above . The three vector collection teams used for this study were composed of the following vector collectors: JWPS and CAC , team 1; JLC and TTRS , team 2 , and FACP and YVSS , team 3 . Collection team 1 collected at collection site 1 on the 26th of October 2017; at collection site 2 on the 27th and at collection site 3 on the 28th . Collection team 2 collected at site 2 on the 26th; at site 3 on the 27th and at site 1 on the 28th . Collection team 3 collected at site 3 on the 26th; at site 1 on the 27th and at site 2 on the 28th . Prior to the initiation of the study , all six vector collectors were asked to randomly select one leg to use exclusively for all of their mopHLC trapping and told to use their other leg for all of their sHLC trapping . Vector collectors were also instructed not to tell any of the other vector collectors which leg they had chosen to use for either type of trapping . This was done so as to reduce the risk of observer bias during the bite-counting stage of this study ( see below ) . To protect the vector collectors from the risk of sunburn , vector collectors were also asked to apply factor 50 sunscreen to their legs approximately one hour before beginning their collections for every day of the study . On the 26th of October 2017 experiments designed to directly compare between mopHLCs and sHLCs were carried out . For this , a set of 12 four-hour vector collections were performed by our three two-person vector collector teams . During these collections , each of our six vector collector used one of their legs for mopHLC vector capture and one of their legs for sHLC vector capture . In order to assess the efficiency of mopHLCs performed in isolation of exposed human legs , on the 27th and 28th of October our vector collector teams were asked to perform exclusively one type of vector collection: either mopHLCs or sHLCs . During the course of these two days a total of 12 vector collections ( in which a single vector collector used one leg to collect vectors ) were performed by our three vector collector teams: eight mopHLCs and four sHLCs . Four of these mopHLCs collections were performed on the 27th of October by vector collector teams 1 and 3 and four were performed on the 28th by vector collect teams 2 and 3 . Vector collector teams 1 and 2 , performed sHLCs ( in isolation of mopHLCs ) on the 28th and 27th of October 2017 , respectively . Blackflies collected during the course of this study , by both mopHLCs and sHLCs , were all identified as S . oyapockense using morphological keys and information provided in Shelley et al . 2010 [15] and Hamada et al . 2015 [16] . While the vector collection data above was sufficient to compare the capture efficiencies of mopHLCs and sHLCs , it was necessary to estimate the number of vector bites that vector collectors suffered during their collections in order to compare their safety . For this reason , estimates of the number of bites each of our vector collectors suffered during their collections were made and used ( together with our collection data ) to calculate estimates of the number of simuliids that each vector collector captured for each bite they suffered . In recognition that the form of simuliid bite marks varies over time and thus that the reliability with which they can be discriminate from other types of skin blemish also varies , we made two estimates of the number of bite marks each vector collector suffered . One set of estimates was made using bite counts taken immediately after all of the vector collections were completed ( on the 28th of October 2017 ) and one was based on bite counts that were made two days later ( on the 30th of October ) . Prior to the initiation of bite counting and on both bite-counting days , bite counters were trained how to identify a simuliid bite-mark using photographs ( similar to those shown in Figs 1–3 ) . Bite counters were then asked to circle all of the simuliid bite marks they could see on each of our vector collector´s legs and then count-off the bite marks . After each bite counter had completed their counting , they wiped-clean the pen-marks on the vector collectors legs with 100% ethanol . A subsequent bite-count of a vector collectors legs was only completed once all traces of the marker pen had been cleaned away . To minimise the impact of our vector collectors suffering blackfly bites out-side the study period , our vector collectors were asked to use long trousers while not collecting blackflies and to declare any simuliid bite marks they had acquired prior to the initiation of the study ( so they could be discounted from the study ) . Two of our vector collectors declared the existence of simuliid bites on their legs ( FACP and JWPS ) prior to the initiation of the study and had these bite-marks excluded from their analysis; the other four had no visual sign of simuliid bite-marks on the legs prior to the initiation of the study . The first set of bite counts were taken in São Gabriel da Cachoeira immediately after the completion of the third day of vector collection on the 28th of October . These bite counts were made when simuliid bite-marks were still fresh and at their most visible ( see Fig 1 ) and were performed by our six study vector collectors . To minimise the impact of observer bias , vector collectors did not count bite marks on their own legs or on the legs of their vector collecting partner . This meant that on the 28th of October four bite counts were taken for each leg of each of our vector collectors . Although the bite-counters used in this part of our study did not know whether the legs they were counting bites from had been used for mopHLCs or sHLCs they did know the objectives of our study and for this reason we have classified these bite counts as “semi-blind” . The raw data from these bite counts is shown in Table 1 . The second set of bite counts was taken in Manaus using only “fully blind” simuliid bite counters . These bite counters were not only unaware of which legs the vector collectors had used for mopHLC and sHLCs , but were , in fact , entirely ignorant of all aspects of our study´s design and objectives . A set of ten such bite counters were used on the 30th October to obtain a total of six bite mark estimates for each of the legs of each of our six vector collectors . The raw data from these bite counts is shown in Table 2 . Differences between the number of simuliids captured per counted bite mark ( SC/CBM ) obtained using sHLC and mopHLC trapping were tested for statistical significance using Wilcoxon rank sum tests . Observed differences in the efficiency of collections ( i . e the number of simuliids captured per hour ) in direct comparison between sHLCs and mopHLCs were tested for significance using a paired Wilcoxon signed rank test . Observed differences in the efficiency of simuliid collection with mopHLCs performed in isolation of sHLCs and various kinds of sHLCs were tested for significance using Wilcoxon sum rank tests [22] . All statistical analysis was implemented in the statistical analysis program R ( version 3 . 4 . 2 ) [23] . Vector capture was performed following a protocol approved by the research ethics committee of the Fundação Osvaldo Cruz-FIOCRUZ/IOC ( approval number CAAE: 41678515 . 1 . 0000 . 5248 ) and followed a similar approach to that described by Shelley et al . [20] . All six vector collector participants recruited to the study were adults ( over the age of 23 ) and had the experiment explained and its objective explained to them . All six participates provided written consent for their participation in the study . All six vector collectors also provided their consent to be identified in the figures used in this manuscript .
Both mopHLCs and sHLCs proved highly successful methods of simuliid capture at all three collection sites in São Gabriel da Cachoeira . In total 1 , 669 blackflies were captured for this study: 869 with mopHLC and 800 with sHLC , all of which were identified as S . oyapockense ( Tables 1 and 2 ) . Simuliid vectors were captured more efficiently with mopHLCs than they were with sHLCs when the two techniques were performed simultaneously on the 26th of October 2017 ( Fig 4 and Tables 1 and 2 ) . Vector collectors were calculated to capture between 5 . 25 and 28 . 75 simuliids per hour ( S/H ) using mopHLCs and between 11 . 25 and 25 . 75 S/H using sHLCs . On average simuliids were captured at a rate of 20 . 5 S/H ( x¯ ) using mopHLC and at a rate of 16 . 4 S/H ( x¯ ) by sHLC trapping . The difference between the two collection techniques´ capture rates was found to be significant using a paired Wilcoxon signed rank test: P-value = 0 . 002 . Simuliid vectors were captured less efficiently with mopHLCs than they were with sHLCs when mopHLCs were performed in the absence of vector collectors performing sHLCs and thus when they were performed in the absence of exposed leg skin ( Fig 5 and Table 1 ) . Fig 5 shows a comparison of the eight mopHLCs and the four sHLCs capture rates calculated from collections performed on the 27th and 28th of October . In contrast to what was observed in direct comparisons ( performed on the 26th of October ) , the eight mopHLCs performed in isolation of sHLCs were observed to capture simuliids significantly less efficiently ( x¯: 11 . 72 S/H ) than the four sHLCs ( x¯: 25 . 06 S/H ) performed over the same period ( P = 0 . 002165 , Wilcoxon sum rank test ) . A significant difference ( P = 0 . 002165 , Wilcoxon sum rank test ) was also found when these eight mopHLCs ( performed in isolation of exposed leg skin ) were compared with the collection data obtained from all 12 sHLCs used in this study i . e when sHLC data from the 26th was included in the analysis ( Fig 6 ) . Fig 2 shows the state of the legs of our vector collectors immediately after the completion of collections and thus at the time when our “semi-blind” bite counters conducted their fresh bite counts . Fig 3 shows the state of our vector collectors´ legs on the day that our “fully blind” bite-mark counters made their bite mark counts . Using mopHLC vector capture , vector collectors were estimated to have suffered between zero and 6 . 25 ( x¯ ) simuliid bites by our semi-blind counters ( see Table 1 ) and between two ( x¯ ) to 13 . 5 ( x¯ ) bites by our fully blind counters ( see Table 2 ) . Whereas using sHLC vector capture , our vector collectors were estimated to have suffered between 90 ( x¯ ) and 173 ( x¯ ) bite marks by our semi-blind bite counters ( Table 1 ) and between 93 ( x¯ ) and 203 ( x¯ ) by our bite marks by our fully blinded bite counters ( Table 2 ) . For each of our six vector collectors , the number of simuliids captured per counted bite mark counted ( SC/CBM ) was calculated separately for both their mopHLC and sHLC collections ( Tables 1 and 2 ) . The set of six SC/CBMs calculated from the fully blind bite count data are shown graphically in Fig 7 . Using this data , mopHLCs were calculated to have SC/CBMs of between 6 . 8 and 32 . 6 [x¯: 21]; whereas sHLCs were calculated to have SC/CBMs of between 0 . 4 and 1 . 8 [x¯: 1] ( Table 2 ) . Using the semi-blind count data , mopHLCs were calculated to have SC/CBMs of between 25 . 33 and 95 . 6 [x¯: 37 . 23]; whereas sHLCs were calculated to have SC/CBMs of between 0 . 26 and 2 . 21 [x¯: 1 . 03] ( Table 1 ) . As can be seen in Tables 1 and 2 , Wilcoxon rank sum tests showed that all six vector collectors had SC/CBMs that were all significantly higher for their mopHLC collections than for their sHLCs collections ( p-values: ≤ 0 . 03125 ) , regardless of which set of bite estimates were used to calculate the SC/CBMs . Our results therefore show that our vector collectors that applied mineral oil to their skin during human landing catches captured significantly more S . oyapockense for each bite they suffer than they did using sHLCs . In our experiments , thus , mopHLCs were seen to be significantly safer than sHLCs for onchocerciasis vector trapping .
The primary objective of this study was to test the hypothesis that mopHLCs are safer than sHLCs for the capture of O . volvulus vectors . In order to do this we estimated the vector-capture-per-bite rates of the two vector capture techniques . Our experiments were conducted in a region just outside Amazonia onchocerciasis focus . In a previous study , performed as part of the WHO´s Onchocerciasis elimination programme , a total of 51 , 341 O . volvulus vectors were captured by sHLCs in the Amazonia onchocerciasis focus between 2006 and 2013 [7] . If mopHLCs had been used by these vector collectors , and they benefited from the same level of protection observed in our experiments , they could have avoided approximately 48 , 896 O . volvulus vector bites . Extrapolating globally , if the technique was used everywhere HLCs are presently being used for O . volvulus vector trapping , and provided similar protection to what we have observed , the technique could potentially help vector collectors avoid suffering millions of simuliid bites [1 , 2] . There is , thus , a strong argument for the utility of mopHLC to be tested in areas where HLCs are presently being used to monitor O . volvulus transmission and to launch studies to investigate if mopHLCs are equally effective for the capture of other O . volvulus vector species ( most importantly S . damnosum ) as they are for S . oyapockense capture . Whether the same potential health benefits are shared by highly experienced WHO vector collectors , who maybe better than our vector collectors at capturing vectors before they have the chance to bite [10] , needs also to be investigated . While both sets of our bite-counting estimates clearly show that mopHLCs are safer than sHLCs , whether they completely eliminate ( or can be adapted to completely eliminate ) the risk of simuliid vector biting during simuliid trapping is not completely clear . In our study , the mopHLC bite-counter estimates made by our vector collectors ( on the 28th of October 2017 ) were much lower than those made by our blind counters ( 2 . 125 x¯ versus 7 . 9 x¯ ) . Although these results could be explained by the bite-counts performed by our vector collectors´ suffering from an observer bias , which our blind bite-counters did not suffer from , there are other alternative explanations too . Differences in the difficulty in distinguishing simuliid bite-marks from other types of skin blemishes on the days our two different bite counts were conducted , for example , could also explain this observation . The human immune response to blackfly bites can vary greatly across time and between individuals and this can affect the visual appearance of bite-marks as well as the ease with which they are identified [24–26] . As is illustrated in Figs 1–3 , the simuliid bite marks counted in this study tended to be more pronounced immediately after our collections were completed , which may have made them easier to discriminate from other types of skin blemish in the first round of counting . Consistent with the notion that the first round of counts were more accurate and than the late counts , the standard deviation of almost all of the bite-count estimates made on the 28th of October can be seen to be much lower than those taken on the 30th ( see Tables 1 and 2 ) . It is , thus , likely that the lower mopHLC bite estimates taken on 28th of October more accurately reflect the true number of bites suffered by our vector collectors during the study than the counts made on 30th do . As can been see in Tables 1 and 2 , half of our vector collectors ( JLC , CMA , JWPS ) were scored by at least half of their 10 bite-counter assessors as having no bites at all on the legs they used in mopHLC trapping . And furthermore , two of these vector collectors ( JLC , JWPS ) were reported on the 28th of October 2017 ( the date our standard deviation analysis suggest is more accurate ) as having no bites at all on their legs by all four bite-counters that assessed them . It seems , thus , likely that one , if not several , of our vector collectors suffered no simuliid bites at all during their mopHLC trapping sessions . This observation is important because it suggests that at least some of the mopHLC trapping done in this study was completely simuliid-bite risk-free and thus that mopHLCs , if optimised , have the potential to become a risk-free strategy of simuliid vector trapping . At present , it is not clear to us if the vector collectors who were recorded ( by between 8 and 9 of our bite-counters ) as having simuliid bite marks on the legs , performed mopHLCs slightly differently from those that appeared to have suffered none . Although we attempted to train our vector collectors to apply an even amount of mineral oil across the surface of their legs , it may be , for example , that , in practise , they did not all prepare an equally thick and/or equally distributed layer of mineral oil across their legs . It could be , thus , that the low-levels of simuliid-biting suffered during mopHLC collections could be eliminated completely by adopting an optimised and standardised mineral oil skin-application protocol . It could , however , also be that the bite-marks on the legs of these vector collectors were acquired out-side of our designated collection periods . As noted in the methods section of this paper , although vector collectors were requested to use long-trousers whenever they were not collecting blackflies , wearing trousers in Equatorial São Gabriel da Cachoeira can be uncomfortable and , thus , this proved difficult to enforce . Several human-bait-free trapping methods have been developed and used to monitor O . volvulus transmission in simuliids [8–13] . Whether these human-bait-free traps capture the exact same blackflies that are captured with HLCs and , thus , whether the O . volvulus transmission data generated from these traps can be treated as the same as data generated with HLCs has been questioned [9] . Given how important vector transmission data collected from HLCs has been for the design of past onchocerciasis disease control and elimination strategies , even small differences in the data generated from non-standard HLCs trapping could have non-trivial impacts on the effectiveness of future onchocerciasis control programmes [1–3] . Even though the methodology of our mopHLCs differs only slightly from sHLCs , we observed a significant difference in simuliid capture efficiency between it and sHLCs , which could translate into a difference in the epidemiological data collected by the two methods . Although , thus , methodological similarities between sHLCs and mopHLCs might intuitively lead one to expect the two techniques to obtain similar epidemiologically data this may not be the case and still needs to be shown; just as it has still needs to be shown if other simuliid host-seeking trapping methods like EWTs collect data that is epidemiological similar to that collected with sHLCs [8–10] . In addition to counting the number of simuliid vectors carrying L3 ( infectious stage ) O . volvulus larvae , epidemiological monitoring of onchocerciasis has traditionally also counted the number of parous biting female blackflies whenever possible . This counting of parous biting females , however , usually requires the collection of fresh specimens and thus it is not always practical to do . Although we did not specifically investigate the utility of mopHLCs for assessing whether females were parous or not , we believe that , because mopHLC trapping ( like sHLC trapping ) captures fresh blackfly specimens in a good physiological state , mopHLCs may be more reliable and/or convenient than EWTs for this purpose . We think that establishing whether this is the case should be viewed as a priority for anyone wishing to further develop mopHLC trapping as data from parous biting blackflies could be used to help characterise the differences between the epidemiological data generated from mopHLCs and sHLCs . And even if such differences prove to be significant , if they are well- characterised disease control planners should be able to factor them into their disease models to design reliable disease control strategies . In our direct comparison experiments , mopHLC trapping captured simuliids significantly more efficiently than sHLC trapping; conversely , however , when mopHLC trapping was performed in isolation of sHLCs ( and thus exposed skin trapping ) mopHLC trapping was observed to capture simuliids significantly less efficiently than sHLCs . Our experiments have , thus , shown that while mopHLC performed in isolation of sHLCs can effectively trap S . oyapockense more safely than sHLCs , more mopHLC or longer mopHLCs will need to performed in order to acquire the same number of simuliids obtained with sHLCs . This loss of efficiency makes mopHLCs less practical for disease monitoring than sHLCs , it may , however , be possible to improve the efficiency of mopHLCs . While there is relatively little data on how anthropophilic simuliids are lured to human hosts , it is clear that skin odour volatiles play a crucial role in luring host-seeking anthropophilic mosquito species [27–29] . It could be , thus , that the loss of efficiency of mopHLC-only trapping , which we observed in our experiments , is explained by skin-applied mineral oil preventing or reducing the release of simuliid-attracting skin odour volatiles that are released in sHLCs . Consistent with this notion , recent human-bait-free simuliid trapping experiments performed in Africa , found that in addition to CO2 and various visual cues , sweaty socks and unwashed trousers , presumably soaked in skin odour volatiles , are a powerful attractant to lure for the African onchocerciasis vector S . damnosum [8 , 9] . It may , therefore , be possible to improve the efficiency of mopHLC by dressing vector collectors in clothes that prevent simuliid biting but allow the natural release of skin odour volatiles . It may also be possible to improve mopHLC using artificial lures like CO2 or lures ( like sweaty socks ) and/or combining these with specially clothed mopHLC vector collectors . Although such lures could potentially increase the yield of blackflies captured with mopHLC trapping , they could also potentially distort the epidemiological data collected from it . It is , therefore , important that if lures are used they are used with extreme care and the impact that they have on the epidemiological data they generate is carefully characterised . While the greatest appeal of mopHLC trapping over the human-bait-free alternatives is that it is likely to generate epidemiological data that is similar to that generated by sHLCs , there are also potential logistical and financial factors that make it appealing too . For example , it can be difficult to transport and mount trapping apparatus used for non-human baited trapping to some field areas where blackfly trapping is needed , such as some heavily forested areas of the Amazonia onchocerciasis focus [15 , 17] . As the equipment used for mopHLC is extremely minimal is size , weight and cost , mopHLC trapping is logistically more practical than , for example , EWTs in such settings . Similarly , while it maybe possible to leave some non-human baited traps for very long periods ( in order to the large numbers of vectors required for onchocerciasis monitoring ) , such long trapping periods could necessitate expensive and more frequent trips to hard-to-reach sites ( i . e one trip for setting-up and one trip for dismounting of traps ) . Our results here have shown that mopHLCs can be used as an alternative to sHLCs and can significantly reduce ( and may have to potential to eliminate ) the number of bites suffered during human-baited Simulium trapping . Our results have also shown that while mopHLC trapping done in isolation of sHLCs are less efficient than sHLCs , there may be scope to improve their efficiency . Further research to investigate whether mopHLCs can eliminate health-risks to vector collectors is needed . Further research to determine if mopHLCs can provide health benefits to vector collectors capturing other Simulium vectors is also needed as are investigations into the health benefits of mopHLCs for more expert vector collectors who may be better than our vector collectors at capturing blackflies before they bite . We also believe , moreover , that further research in to the utility of the general approach of vector capture by surface ( skin/hair/feather ) application of viscous or sticky substances to living vertebrates for the capture of arthropod disease vectors also merits further research . And that the general approach described here could be extremely useful to other medical and veterinary arthropod borne disease research and control programmes . | Standard human landing catches ( sHLCs ) have historically been used to obtain key Onchocerca volvulus transmission data that has helped with the design and monitoring of the WHO´s onchocerciasis control programmes . To avoid the health risks associated with sHLCs , alternative human-bait-free blackfly trapping methods , most of which immobilize and suffocate blackflies with a viscous liquid substance , have been developed . Questions , however , have be raised as to whether these human-bait-free trapping methods generate O . volvulus transmission data that is directly comparable with historic sHLC data . In this study , we have combined sHLCs with mineral oil vector capture and shown that the skin application of mineral oil can significantly reduce ( and possibly eliminate ) simuliid biting during HLCs . In direct comparisons , we have shown that mineral oil protected human landing catches ( mopHLCs ) were more efficient at capturing the O . volvulus vector Simulium oyapockense than sHLCs . We have also shown that mopHLCs , performed in isolation of vector collectors using exposed skin for their trapping , are less efficient than HLCs , but still function well . We believe that mopHLCs represent a promising alternative to sHLCs that merit further testing for their utility in the epidemiological monitoring of onchocerciasis and , indeed , other vector borne diseases as well . | [
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"... | 2019 | Blackflies in the ointment: O. volvulus vector biting can be significantly reduced by the skin-application of mineral oil during human landing catches |
Elucidating the mechanism of action of trypanocidal compounds is an important step in the development of more efficient drugs against Trypanosoma brucei . In a screening approach using an RNAi library in T . brucei bloodstream forms , we identified a member of the mitochondrial carrier family , TbMCP14 , as a prime candidate mediating the action of a group of anti-parasitic choline analogs . Depletion of TbMCP14 by inducible RNAi in both bloodstream and procyclic forms increased resistance of parasites towards the compounds by 7-fold and 3-fold , respectively , compared to uninduced cells . In addition , down-regulation of TbMCP14 protected bloodstream form mitochondria from a drug-induced decrease in mitochondrial membrane potential . Conversely , over-expression of the carrier in procyclic forms increased parasite susceptibility more than 13-fold . Metabolomic analyses of parasites over-expressing TbMCP14 showed increased levels of the proline metabolite , pyrroline-5-carboxylate , suggesting a possible involvement of TbMCP14 in energy production . The generation of TbMCP14 knock-out parasites showed that the carrier is not essential for survival of T . brucei bloodstream forms , but reduced parasite proliferation under standard culture conditions . In contrast , depletion of TbMCP14 in procyclic forms resulted in growth arrest , followed by parasite death . The time point at which parasite proliferation stopped was dependent on the major energy source , i . e . glucose versus proline , in the culture medium . Together with our findings that proline-dependent ATP production in crude mitochondria from TbMCP14-depleted trypanosomes was reduced compared to control mitochondria , the study demonstrates that TbMCP14 is involved in energy production in T . brucei . Since TbMCP14 belongs to a trypanosomatid-specific clade of mitochondrial carrier family proteins showing very poor similarity to mitochondrial carriers of mammals , it may represent an interesting target for drug action or targeting .
African trypanosomes are vector-borne protozoans that cause serious public health problems and severe economic losses in sub-Saharan African countries . The current chemotherapy against Trypanosoma brucei , the causative agent of human African trypanosomiasis , or sleeping sickness , and the related cattle disease Nagana , is based on multiple injections of drugs some of which are associated with serious side effects . Treatment of Nagana is commonly based on mutagenic drugs including ethidium bromide and isometamidium chloride , and also on suramin and diminazene aceturate , both with considerable toxicity to cattle [1] . In the case of human African trypanosomiasis , pentamidine and suramin are widely used during the first stage of the disease , when the parasites are confined to the hemolymphatic system . The second stage of sleeping sickness , which is characterized by parasite invasion of the central nervous system , is treated with melarsoprol or a combination of nifurtimox/eflornithine [2] . Melarsoprol , the only drug against both forms of sleeping sickness , which are caused by T . b . gambiense or T . b . rhodesiense , is highly toxic causing encephalopathies in 5% of cases . In addition , there are well-known examples of drug resistance in the field [3 , 4] . In the laboratory , trypanosome drug resistance has frequently been found to involve loss of nutrient transporters: the aminopurine transporter TbAT1 for melaminophenyl arsenicals and diamidines [5] , the aquaglyceroporin TbAQP2 for melarsoprol and pentamidine [6] , and the amino acid permease TbAAT6 for eflornithine [7–9] . These transporters ( i ) import drugs in addition to their natural substrates [7 , 10–12] and ( ii ) are not essential [6 , 7 , 13] . Loss-of-function mutations in the corresponding genes can therefore render the trypanosomes resistant by reducing drug uptake . However , a number of trypanocides accumulate in the trypanosomes' single mitochondrion , possibly targeting mitochondrial structures including the kinetoplast [14–16] , the intercatenated network of circular DNA molecules that comprises the parasite’s mitochondrial genome . This implies that transporters of the ( inner ) mitochondrial membrane are also involved in drug accumulation and activity . The nature of these transporters , and whether they play a role in drug resistance , is unknown . T . brucei and other protozoan parasites acquire nutrients and building blocks of macromolecules for rapid cell proliferation from their mammalian or insect hosts . However , recent reports have shown that trypanosomatids not only acquire lipids for membrane formation from the environment , but are also capable of de novo synthesis of all major membrane lipid classes ( reviewed in [17] ) . The most abundant phospholipid class in T . brucei is phosphatidylcholine ( PC ) [18] , which can be generated by acylation of lyso-PC taken up from the host [19] . Alternatively , PC can be produced from host-derived choline [20] by sequential action of three enzymes via the CDP-choline pathway [17] . This pathway is essential for survival of T . brucei parasites in culture [17] . PC is also the most abundant phospholipid class in malaria parasites ( Plasmodium spp . ) ( reviewed in [21] ) . Its synthesis can occur via multiple routes , including the CDP-choline pathway ( reviewed in [22 , 23] ) . The inability to knock out individual genes involved in this pathway suggests that PC formation via CDP-choline is essential in Plasmodium [24] . In addition , uptake of the substrate for this pathway , choline , can be inhibited by a set of choline analogs , which have been found to be toxic for malaria parasites , at nanomolar concentrations [25–27] . Although the primary target of the drugs is likely the inhibition of choline uptake , resulting in inhibition of PC synthesis [28–30] , other mechanisms of action have been proposed [31 , 32] . Structural refinements of the drugs has led to the development of third- and fourth-generation compounds , one of which , named T3 ( or albitiazolium ) , is currently in clinical trials to treat severe malaria [30] . More recently , a subset of these compounds has also been shown to be toxic for T . brucei and Leishmania parasites at ( sub- ) micromolar concentrations [33] . Their mode of action is , however , unclear: although they effectively inhibit choline uptake and , thus , de novo PC formation in T . brucei [20] , they may kill trypanosomes by affecting mitochondrial structure and function [20 , 33] . In the present study , we used three of the leading choline analogs , a bis-quartenary ammonium salt , G25 [34] , and two bis-tiazolium salts , T3 and T4 [35] , to elucidate their site ( s ) and mode ( s ) of action against T . brucei . For this , we screened an RNAi library previously established in T . brucei bloodstream forms [9] to identify genes conferring parasite resistance towards the choline analogs . Interestingly , we found that treatment of T . brucei bloodstream forms with these drugs selected parasite populations in which the expression of a gene encoding a member of the mitochondrial carrier protein family , MCP14 , was down-regulated . Expression of MCP14 was found to be essential for normal growth of both bloodstream and procyclic form trypanosomes in culture .
Recently , an inducible RNAi library has been established in T . brucei bloodstream forms , which allows an unbiased approach to identify genes involved in drug uptake or action [9] . We have used this library to elucidate the mode and site of action of a set of choline analogs known to be toxic for parasitic protozoa , including T . brucei [27 , 33] . In a first step , we determined the concentrations of G25 , T3 and T4 required to kill 98% of T . brucei bloodstream forms ( EC98 ) after 3 days of culture using Alamar blue assays [9] ( Fig 1A ) . These concentrations were subsequently used to treat separate trypanosome cultures with G25 , T3 and T4 , following induction of RNAi for 60 h with tetracycline ( Fig 1B ) . After 8 days , parasites cultured in the absence of tetracycline were dead , while resistant trypanosomes started to proliferate in cultures incubated with tetracycline . After another 3 days of culture , during which time parasites were kept in fresh medium to allow optimal growth , DNA was extracted and inserts potentially conferring resistance towards the drugs were amplified using specific primers [9] . Interestingly , the individual screens using G25 , T3 and T4 all resulted in selection of trypanosomes bearing RNAi inserts partially covering the gene encoding putative mitochondrial carrier protein 14 ( TbMCP14; Tb927 . 10 . 13120 ) , a member of a large family of mitochondrial carriers [36] . Screening with G25 and T3 selected parasites bearing the same RNAi insert , while T4 selected parasites harboring a different TbMCP14 RNAi sequence ( Fig 1C , green line ) . Tb927 . 10 . 13120 was annotated to comprise an ORF of 1035 bp ( TriTrypDB , GeneDB ) , encoding a protein of 344 amino acids . A C-terminally tagged product of this ORF was shown to localize to the mitochondrion [36] . However , recent results from transcriptome analyses suggested that a second potential start codon 171 bp upstream of the annotated ATG might exist [37 , 38] . RT-PCR with a spliced leader primer ( primer 12 , S1 Table ) and TbMCP14 reverse primers ( primers 2 and 4 , S1 Table ) generated products consistent with Tb927 . 10 . 13120 encoding an mRNA of 1206 bp ( Fig 1C , right panel ) , resulting in a predicted full-length protein of 401 amino acids . To verify the involvement of TbMCP14 in drug resistance towards choline analogs , expression of Tb927 . 10 . 13120 was down-regulated by inducible RNAi in T . brucei bloodstream forms . Addition of tetracycline to parasites in culture showed no growth phenotype , despite efficient reduction in Tb927 . 10 . 13120 transcript level ( Fig 2A ) . The non-essentiality of Tb927 . 10 . 13120 as assessed by RNAi was not surprising since trypanosomes selected from the RNAi library were viable after 11 days of RNAi induction ( see above ) . However , treatment of parasites after down-regulation of Tb927 . 10 . 13120 expression showed increased resistance towards G25 , T3 , and T4 ( Fig 2B–2D ) . In Alamar blue assays , the EC50 values of TbMCP14-depleted bloodstream form parasites for the compounds increased an average of 7-fold compared to uninduced cells . Subsequently , Tb927 . 10 . 13120 expression was also down-regulated using RNAi in T . brucei procyclic forms . Incubation of parasites in the presence of tetracycline showed disappearance of Tb927 . 10 . 13120 mRNA levels and a small growth defect ( Fig 3A ) . In line with the results obtained for bloodstream forms ( Fig 2B–2D ) , RNAi against Tb927 . 10 . 13120 conferred increased resistance ( approximately 3-fold ) of procyclic form parasites towards T3 ( Fig 3B ) . To further confirm the involvement of TbMCP14 in drug action , we over-expressed a tetracycline-inducible ectopic copy of cMyc-tagged Tb927 . 10 . 13120 in procyclic and bloodstream form trypanosomes . Analysis by SDS-PAGE and immunoblotting showed that cMyc-TbMCP14 was expressed in the presence , but not in the absence , of tetracycline as an approximately 48 kDa protein , and that expression of full-length cMyc-TbMCP14 conferred increased susceptibility ( >13-fold ) to parasites against T3 ( Fig 3C ) . These results clearly demonstrate that the tagged version of the full-length protein is functional . In contrast , no effect on sensitivity towards T3 was observed in parasites over-expressing a tagged version of the short ( truncated ) form of TbMCP14 , which migrated with an apparent molecular mass of 42 kDa ( Fig 3D ) . In control experiments , drug sensitivity was assessed in T . brucei procyclic forms over-expressing another member of the MCP family , TbMCP5 . This protein has previously been shown to act as ADP/ATP carrier [39] . In contrast to procyclic form trypanosomes over-expressing TbMCP14 ( Fig 3C ) , expression of N-terminally cMyc-tagged TbMCP5 ( which is known to be functional [39] ) had no major effect on the EC50 value for T3 ( S1A and S1B Fig ) . Additionally , viability of T . brucei bloodstream forms over-expressing cMyc-TbMCP14 ( full-length ) cultured in the presence of various concentrations of G25 was investigated by propidium iodide ( PI ) staining . While dead parasites are permeable to PI , resulting in its intercalation into DNA with subsequent fluorescence emission ( PI positive ) , living parasites are impermeable to PI and show no emission of fluorescence . The results show that over-expression of TbMCP14 slightly increased toxicity of G25 ( S2 Fig , top panels ) , whereas its down-regulation had a protective effect on parasite survival in the presence of the drug ( S2 Fig , bottom panels ) . In addition , the data show that G25 is only toxic for T . brucei bloodstream forms after prolonged incubation , i . e . after 72 h ( S2 Fig , top left , green line ) . Taken together , the results demonstrate that TbMCP14 expression is closely linked to the action of the choline analogs , G25 , T3 and T4 . In a previous report , the truncated version of TbMCP14 was expressed as cMyc-tagged version that was found to localize in the mitochondrion [36] . We now show by immunofluorescence microscopy that also full-length TbMCP14 localizes to the mitochondrion , co-localizing with the mitochondrial marker protein voltage-dependent anion channel ( VDAC ) ( Fig 4 ) . The results further demonstrate that the N-terminal 57 amino acids of full-length TbMCP14 are not essential for correct targeting of the protein to the mitochondrion , although they are required for drug susceptibility . It has been suggested that the trypanocidal activity of choline analogs may occur via modulation of mitochondrial membrane potential ( ΔΨm ) [33] . We revisited this proposal by measuring drug-induced changes in ΔΨm in T . brucei bloodstream forms , in which TbMCP14 was over-expressed or down-regulated . Using the mitochondrial dye tetramethylrhodamine ethyl ester ( TMRE ) and flow cytometry , we detected a decrease in ΔΨm following treatment of parasites for 24 h with increasing concentrations of G25 ( Fig 5A ) . This drug-induced decrease in ΔΨm was largely prevented in parasites after RNAi-mediated down-regulation of TbMCP14 . Conversely , sensitivity of ΔΨm to high concentrations of G25 was slightly increased in parasites after over-expression of TbMCP14 ( Fig 5B ) . In control experiments , parasite viability during drug treatment was measured by incorporation of PI and flow cytometry analysis . We found no difference in PI staining between parasites before and after incubation for 24 h in the presence of G25 , ruling out the possibility that the observed decrease in ΔΨm was the result of parasite death , rather than drug action ( S3 Fig ) . Together , these results demonstrate that TbMCP14 is involved in drug-induced alterations of ΔΨm , which clearly is an early event during G25 action . Although the mode of action of diamidines is likely multi-factorial , there is evidence that pentamidine and other cationic trypanocides may accumulate inside mitochondria and cause a decrease of ΔΨm in kinetoplastids [15 , 40–42] . For this reason we studied if TbMCP14 might be involved in the mode of action of diamidines and the quaternary ammonium phenanthridine isometamidium by assessing the sensitivity of trypanosomes after over-expression or down-regulation of TbMCP14 to three diamidines , pentamidine , DB75 and diminazene aceturate , as well as isometamidium chloride ( Fig 6 ) . Interestingly , we found that over-expression of TbMCP14 in procyclic forms resulted in an approximately 14-fold increase in parasite susceptibility towards pentamidine ( Fig 6 ) . However , only small changes in pentamidine sensitivity were seen after depletion of TbMCP14 . It is possible that the remaining levels of TbMCP14 ( see above ) masked possible effects of these compounds on RNAi parasites , or that the primary targets of pentamidine are cytosolic , or in other sub-cellular compartments . In contrast to pentamidine , no significant changes in toxicity were found for DB75 , diminazene aceturate , or isometamidium chloride upon over-expression of TbMCP14 ( Fig 6C ) . In addition , sensitivity of procyclic form trypanosomes towards pentamidine was unaffected in parasites over-expressing TbMCP5 ( S1C Fig ) . To further study the importance of TbMCP14 in T . brucei viability , we generated bloodstream and procyclic form Tb927 . 10 . 13120 ( conditional ) null mutants . Since RNAi against TbMCP14 in bloodstream forms showed no growth defect , we attempted to generate straight knock-out parasites by sequentially deleting the two endogenous Tb927 . 10 . 13120 alleles . Successful replacement of the first and second alleles by blasticidin resistance and phleomycin resistance genes , respectively , was verified by PCR ( Fig 7A ) . The resulting TbMCP14 null bloodstream forms were viable , but they showed reduced growth in culture compared to the parental cell line ( Fig 7B ) . The cell doubling time of the null mutant was calculated to be 10 . 0 ± 0 . 8 h , compared to 6 . 3 ± 0 . 1 h ( mean values ± standard deviations from three independent experiments ) of the parental strain . Together , the results show that TbMCP14 is essential for normal growth of T . brucei bloodstream forms in culture , but non-essential for viability under these conditions . Because T . brucei procyclic forms showed slightly reduced growth in culture after RNAi against TbMCP14 ( Fig 3A ) , we followed a different strategy to obtain procyclic form TbMCP14 conditional null mutants by introducing a tetracycline-inducible ectopic copy of Tb927 . 10 . 13120 before knocking out the second allele . To be able to monitor expression of ectopic TbMCP14 , the gene was extended with a sequence encoding cMyc at its 3’ end . Again , successful deletion of the two endogenous alleles was verified by PCR ( Fig 7A ) . Resulting parasites cultured in the presence of tetracycline , i . e . expressing cMyc-tagged ectopic TbMCP14 , grew normally in standard growth medium ( Fig 7C ) . In contrast , after removal of tetracycline from the culture medium , parasites showed reduced growth after 6 days of culture ( Fig 7C ) . SDS-PAGE and immunoblotting revealed that cMyc-tagged TbMCP14 was expressed in parasites cultured in the presence of tetracycline , but disappeared during ablation of TbMCP14 expression after removal of tetracycline ( Fig 7D ) . Together , the results show that TbMCP14 is essential for growth of T . brucei procyclic forms in culture and confirms that cMyc-tagged TbMCP14 is functional ( see also Fig 3C ) . To elucidate the physiological function of TbMCP14 , we performed untargeted metabolomic analyses of small metabolites [43] in T . brucei procyclic forms after over-expression of TbMCP14 . This approach revealed that a metabolite with a mass compatible with pyrroline-5-carboxylate , was the only metabolite showing a greater than 3-fold change in abundance with statistical significance ( P<0 . 05 ) in parasites over-expressing TbMCP14 ( Fig 8 ) . Pyrroline-5-carboxylate is the degradation product of proline produced in the mitochondrion by the action of proline dehydrogenase [44] , suggesting that TbMCP14 might play a role in proline metabolism . Since proline is abundant in the culture medium , changes in this amino acid are not apparent , nor are changes to glutamate , the amino acid formed from pyrroline-5-carboxylate whose mitochondrial abundance is negligible compared to its abundance in the culture medium . Glutamate is then converted to 2-ketoglutarate , which is also produced from glucose , as are other carboxylic acids such as succinate , fumarate and malate , which explains why pyrroline-5-carboxylate is the only discriminatory metabolite identified in these experiments . Based on this finding , we investigated if down-regulation of TbMCP14 may show a more pronounced growth defect if procyclic form trypanosomes were cultured in glucose-depleted medium ( SDM80 ) , in which they are known to increase consumption of amino acids , in particular proline , for energy production by >6 times compared to parasites grown in standard medium containing glucose ( SDM79 ) [44] . Our results showed that after RNAi against TbMCP14 , trypanosomes showed a much stronger growth defect in SDM80 compared to SDM79 , resulting in growth arrest after 5 days of induction ( Fig 9A , compare with Fig 3A ) . When SDM80 was supplemented with 5 . 5 mM glucose , the growth defect was delayed ( Fig 9B ) , demonstrating that the availability of glucose improved parasite growth in TbMCP14-depleted cells . Together , these results indicate that TbMCP14 is likely involved in metabolism of proline for energy production . In line with this interpretation , we found that depletion of TbMCP14 in conditional knock-out parasites cultured in glucose-depleted medium ( SDM80 ) again reduced parasite growth ( Fig 9C ) compared to parasites grown in the presence of glucose ( Fig 9D ) . In contrast , depletion of TbMCP14 had no effect on growth of trypanosomes cultured in glucose-supplemented SDM80 for up to 6 days ( Fig 9C ) . Culturing conditional knock-out parasites in glucose-depleted medium had no effect on ablation of TbMCP14 expression ( S4 Fig ) . It has been demonstrated that ATP production in crude mitochondria can be measured using digitonin-permeabilized trypanosome suspensions [45] . In the presence of ADP , addition of succinate to crude mitochondria results in ATP production via oxidative phosphorylation , whereas addition of 2-ketoglutarate induces ATP formation via substrate level phosphorylation [46] . We now used these conditions to measure ATP production in crude mitochondria of TbMCP14 conditional knock-out trypanosomes . Crude mitochondria were prepared from parasites cultured in SDM80 containing glucose in the presence or absence of tetracycline for 6 days to maintain or deplete , respectively , expression of TbMCP14 . Under these conditions , depletion of TbMCP14 had no effect on parasite growth ( Fig 10A ) . Crude mitochondria isolated from control and TbMCP14-depleted parasites ( Fig 10A , inset ) were incubated for 30 min in the absence or presence of succinate , 2-ketoglutarate or proline as substrates for ATP production . We found that depletion of TbMCP14 has no effect on ATP formation using succinate or 2-ketoglutarate as substrates ( Fig 10B and 10C ) . In contrast , ATP production using different concentrations of proline as substrate was decreased in mitochondria from TbMCP14-depleted parasites compared to control cells ( Fig 10D and 10E ) . The observation that proline-dependent ATP production was inhibited by antimycin ( Fig 10D ) , an inhibitor of complex III of the electron transport chain , indicates that ATP is formed via oxidative phosphorylation . Together , these results strongly indicate that TbMCP14 is involved in metabolism of proline for energy production in mitochondria , possibly by promoting proline transport through the mitochondrial inner membrane . While the N-terminal half of TbMCP14 ( amino acids 1 to 161 ) is devoid of known motifs , the C-terminal half ( amino acids 162 to 402 ) carries mitochondrial carrier protein ( MCP ) motifs of about 100 amino acids each , which are typical for transporters of the inner mitochondrial membrane ( Pfam entry PF00153 ) . Mitochondrial carriers usually possess three such motifs , whereas TbMCP14 only has two . A profile search with PF00153 against SwissProt , the manually curated section of UniProt [47] , returned 1347 hits of E-value <10–10 , of which only 24 ( 1 . 8% ) possessed two MC motifs while 1302 ( 97% ) had three . Blastp similarity searches [48] with TbMCP14 as the query returned highly significant hits ( expectancy E<10–12 ) from trypanosomatids only , followed by many hits from the viridiplantae . The most similar human protein to TbMCP14 was SLC25A44 , a mitochondrial carrier of unknown function [36] . A phylogenetic tree of a Muscle multiple alignment [49] of representative hits supplemented with selected human MCPs ( S5 Fig ) confirmed that the trypanosomatid TbMCP14 orthologues form a clearly separate clade within the mitochondrial carrier superfamily .
Previous studies have shown that choline analogs are potent inhibitors of choline uptake and affect PC metabolism in protozoa [25 , 26] . However , more recent results [33] , including our own involving pulse-chase experiments using labeled choline in presence of G25 in T . brucei procyclic forms [20] , indicated that inhibition of phospholipid synthesis may not be the main target of G25 in trypanosomes . Instead , these reports indicated that parasite death by choline analogs is mediated via affecting mitochondrial function . A mechanism for the uptake and site of action of the drugs was , however , not proposed . We now demonstrate that toxicity of the choline analogs G25 , T4 and T3 , is mediated by a member of the mitochondrial carrier family , TbMCP14 . Evidence for the involvement of TbMCP14 in drug action is several fold: First , TbMCP14 was identified by an unbiased screening approach using a RNAi library in T . brucei bloodstream forms . Its down-regulation resulted in selection of parasite populations showing substantially lower susceptibilities towards the three drugs in separate screens . Second , depletion of TbMCP14 by RNAi in both bloodstream and procyclic forms increased resistance of parasites towards the drugs on average by 7-fold and 3-fold , respectively , compared to uninduced cells . Third , over-expression of a tagged form of TbMCP14 in procyclic forms resulted in hypersensitivity towards T3 . Fourth , down-regulation of TbMCP14 protected bloodstream form mitochondria from drug-induced decrease in mitochondrial membrane potential . The mitochondrial carrier family consists of a group of related proteins with conserved sequence features , i . e . three tandem repeats of about 100 amino acids , each of them with two predicted transmembrane alpha helices connected by a hydrophilic loop , and a conserved signature signal sequence motif [50 , 51] . Members of the mitochondrial carrier family are involved in transport of mono- , di- and tricarboxylates , co-factors like NAD+ , FAD and coenzyme A , amino acids , and other substrates necessary for mitochondrial function [52] . In a previous report , in silico analysis of the T . brucei genome using conserved amino acid sequences and protein domains suggested the presence of 24 mitochondrial carrier family proteins [36] . In addition , using previously described and characterized mitochondrial carriers from yeast and humans as references , putative functions were proposed for 20 of the predicted carriers in T . brucei [36] . At present , however , biochemical data about their substrate specificities or physiological functions is only available for a few members , one of them being TbMCP5 , an ATP/ADP translocator [39] . We now show that TbMCP14 belongs to a trypanosomatid-specific clade of mitochondrial carrier family proteins that shows relatively weak similarity to mitochondrial carriers of mammals , making it an interesting target for drug action and/or targeting . Attempts to express TbMCP14 in Xenopus laevis oocytes or Saccharomyces cerevisiae to study substrate specificity were unsuccessful , possibly because the carrier mislocalized in these model expression systems . However , by generating TbMCP14 knock-out mutants in T . brucei bloodstream and procyclic forms , we were able to demonstrate that TbMCP14 is closely linked to mitochondrial energy production . Deletion of both alleles of TbMCP14 in bloodstream forms showed that the carrier is not essential for survival in this life-cycle form , but reduced parasite proliferation under standard culture conditions , i . e . in the presence of glucose . A much stronger growth defect was observed for procyclic form TbMCP14 conditional knock-out parasites . Ablation of TbMCP14 expression resulted in growth arrest . Interestingly , the time point at which parasite proliferation stopped was dependent on the availability of glucose as energy source in the culture medium . In medium containing low glucose ( SDM80 ) , procyclic form trypanosomes have been shown to switch from glucose metabolism to catabolism of amino acids , mostly proline [44 , 53] . Under these conditions , growth of TbMCP14-depleted parasites was clearly reduced compared to control trypanosomes cultured in the presence of standard glucose concentrations ( SDM79 ) . In line with these observations , we found that proline-dependent ATP production in crude mitochondria from TbMCP14-depleted procyclic form trypanosomes was clearly reduced compared to control mitochondria . In contrast , no changes in ATP production were observed in mitochondria after knocking out TbMCP14 when succinate or 2-ketoglutarate were used as substrates for oxidative phosphorylation or substrate level phosphorylation , respectively , demonstrating that the processes themselves were not affected by the absence of TbMCP14 . Together with our observation that the levels of the proline metabolite , pyrroline-5-carboxylate , were affected in procyclic forms over-expressing TbMCP14 , these results demonstrate that TbMCP14 is involved in proline-dependent energy production , possibly by acting as a mitochondrial proline carrier . Since proline-dependent ATP production in mitochondria isolated from TbMCP14-depleted cells can still be observed , TbMCP14's role in proline uptake may be indirect . Alternatively , other transporters may allow proline import into mitochondria in the absence of TbMCP14 . Our observation that depletion of TbMCP14 also affects growth of bloodstream form parasites , which don’t rely on proline as source of energy , may be explained by its ability to transport other essential metabolites . In fact , relatively broad substrate specificities have been reported for several members of the MCP family . In addition , available data indicate that mitochondrial proline dehydrogenase , and thus proline metabolism , is also important for normal growth of bloodstream forms ( http://www . genedb . org/gene/Tb927 . 7 . 210 ) . Furthermore , inhibition of proline transport by depletion of TbMCP14 may affect mitochondrial protein synthesis . At present , it is unclear how choline analogs cross the plasma membrane of T . brucei . Previous studies in Plasmodium using radiolabeled members of the group of choline analogs suggested that the compounds are taken up into parasites involving an erythrocyte plasma membrane choline carrier [25 , 30] . Although choline is efficiently taken up by T . brucei bloodstream and procyclic forms [20] , a choline carrier has not yet been identified .
T . brucei bloodstream forms co-expressing T7 RNA polymerase and a tetracycline repressor ( known as New York single-marker cells , NY-SM; [54] ) were cultured at 37°C in HMI-9 containing 10% ( v/v ) heat-inactivated FBS . Derived clones to down-regulate or over-express TbMCP14 were cultured in the presence of 2 . 5 μg/ml phleomycin or 0 . 1 μg/ml puromycin , respectively . TbMCP14 knock-out parasites were cultured in the presence of 5 μg/ml hygromycin and 2 . 5 μg/ml blasticidin . T . brucei 29–13 procyclic forms [54] were cultured at 27°C in SDM79 containing 10% ( v/v ) heat-inactivated FBS , in the presence of 25 μg/ml hygromycin , and 15 μg/ml G418 . The derived clones containing different double-stranded RNA constructs against TbMCP14 ( Tb927 . 10 . 13120 ) were cultured in the presence of an additional 2 μg/ml puromycin . TbMCP14 conditional knock-out procyclic forms were cultivated in the presence of 5 μg/ml blasticidin , 0 . 2 μg/ml phleomycin and 2 μg/ml puromycin , and 1 μg/ml tetracycline to maintain expression of the ectopic copy of TbMCP14 . Growth of T . brucei procyclic forms in glucose-depleted medium was studied in SDM80 [44] , supplemented with 9% dialyzed ( 10’000 molecular weight cut-off ) and heat-inactivated FCS and 1% non-dialyzed and heat-inactivated FBS . Susceptibility of T . brucei bloodstream forms to G25 , T3 and T4 was assessed by Alamar blue assays [55] . Briefly , serial dilutions of G25 , T3 or T4 starting at 10 , 250 or 10 μM ( from 10 mM aqueous stock solutions ) , respectively , were prepared in HMI-9 containing 10% ( v/v ) FBS in 96-well plates ( 100 μl final volume ) . Pentamidine , DB75 and diminazene aceturate were added to parasite cultures from stock solutions in DMSO ( 100 μM , 2 . 2 mM and 20 mM , respectively ) , isometamidium chloride was added from a 20 mM aqueous stock solution . Parasites were added to a final density of 1 × 104 cells/ml . After incubation for 70 h at 37°C , 10 μl of Alamar blue solution ( 12 . 5 mg of resazurin in 100 ml PBS , composed of 137 mM NaCl , 2 . 7 mM KCl , 10 mM Na2HPO4 , 1 . 76 mM KH2PO4 , pH 7 . 2 ) was added to all wells and incubation was continued for another 2 h at 37°C . Fluorescence was measured using a spectromax GEMINI plate reader at 544 nm excitation , 590 nm emission and 570 nm cut-off . Drug screening using an RNAi library constructed in T . brucei bloodstream forms was performed as described before [9] . Briefly , a frozen stabilate of 3 × 106 parasites was thawed in 30 ml HMI-9 supplemented with 10% FBS and daily diluted to the same density ( 3 × 106 cells/30 ml ) . After three passages , RNAi was induced by addition of tetracycline to the culture . After three days , the parasite culture was split in flasks containing 106 cells/10 ml medium . Drug concentrations determined to kill 98% of parasites ( EC98 ) by Alamar blue assays were used for selection of resistant parasites . EC98 concentrations of G25 , T3 or T4 were added to the culture flasks , which were incubated until resistant populations started growing . Finally , genomic DNA was extracted from resistant parasites . DNA fragments conferring resistance were amplified by PCR , cloned into PCRII-TOPO ( Invitrogen ) and identified by DNA sequencing . Two RNAi vectors , pALC14 and pMS14 ( derivatives of pLew100 [54] ) , both harboring a tetracycline-inducible stem loop , were used to down-regulate TbMCP14 . The pALC14 plasmid ( described in [46] ) has the stem loop under control of the GPEET promoter and was used to transfect procyclic forms , whereas the pMS14 plasmid [56] , which is regulated by an rRNA promoter , was used to transfect bloodstream forms . TbMCP14 gene fragments were cloned into the vectors using PCR products obtained with primers 1 and 2 ( S1 Table ) , resulting in plasmids pJPM14pc and pJPM14bs . For over-expression in procyclic and bloodstream form trypanosomes , the TbMCP14 open reading frame ( amplified using primers 3 and 4 , S1 Table ) was inserted into an expression vector based on pLew100 [54 , 57] , containing a C-terminal extension encoding 3x-cMyc to allow tetracycline-inducible expression of cMyc-tagged TbMCP14 , resulting in plasmid pJPM14O . The same strategy was used to induce over-expression of the truncated version of TbMCP14 except that a shorter open reading frame ( amplified using primers 5 and 4 , S1 Table ) was inserted in the vector . Procyclic form TbMCP14 conditional knock-out parasites were generated stepwise by i ) replacing one of the endogenous alleles with a blasticidin resistance gene by homologous recombination , ii ) inserting an ectopic copy of TbMCP14 , C-terminally tagged with cMyc , and iii ) replacing the remaining endogenous allele of TbMCP14 by a phleomycin resistance gene . The corresponding vectors were generated as follows; first , a fragment of 400 nt from the 5’-flanking region of TbMCP14 was amplified using primer 6 , having an XhoI restriction site , and primer 7 , having a HindIII restriction site ( Suppl . S1 Table ) . Second , a fragment of 458 nt from the 3’-flanking region of TbMCP14 was amplified using primers 8 and 9 ( Suppl . S1 Table ) . Subsequently , the two fragments were inserted into vector pKOblast [58] , which contains the procyclin EP1-EP2 intergenic region , a blasticidin resistance gene , and the tubulin intergenic region , resulting in vector pJPM14KOblast . The blasticidin resistance gene was then replaced by a phleomycin resistance gene using the flanking restriction sites AscI and PacI , resulting in vector pJPM14KOphleo . Plasmid extraction was performed using Qiagen Plasmid Midi Kit ( Qiagen , Hilden , Germany ) according to the manufacturer’s instructions . Before transfection of T . brucei parasites , pLew-based plasmids were linearized with NotI while pKO plasmids were digested with XhoI/NotI to release linear fragments containing the respective resistance genes flanked by sequences for homologous recombination with TbMCP14 . T . brucei procyclic and bloodstream forms were harvested at mid-log phase , washed once in buffer ( 132 mM NaCl , 8 mM KCl , 8 mM Na2HPO4 , 1 . 5 mM KH2PO4 , 0 . 5 mM magnesium acetate , 0 . 09 mM calcium acetate , pH 7 . 0 ) and resuspended in fresh buffer at a density of 8 × 107 cells/ml . Subsequently , 440 μl of parasite suspension were mixed with 10–15 μg of digested plasmids and transferred to a 0 . 2-cm pulse cuvette ( Bio-Rad ) . Electroporation was conducted with a BTX Electroporation 600 system ( Axon Lab , Baden , Switzerland ) with one pulse ( 1 . 5 kV charging voltage , 2 . 5 kV resistance , 25 microfarads capacitance timing , and 186 resistance timing ) . Cells were immediately inoculated in 10 ml of procyclic or bloodstream form medium . Dilutions were plated into 24-well plates and after 24 h selected for antibiotic resistance . Clones were obtained by limiting dilution . Total RNA was isolated using the SV Total RNA Isolation System ( Promega ) , following the manufacturer’s instructions . cDNA was synthesized from total RNA ( 0 . 1–0 . 5 μg ) using SuperScript II reverse transcriptase ( Invitrogen ) . For Northern blotting , total RNA ( 10–15 μg ) was separated on formaldehyde-agarose gels ( 1% agarose , 2% formaldehyde in 20 mM Mops , pH 7 . 0 , containing 8 mM sodium acetate and 1 mM EDTA ) and transferred to Amersham Hybond-N+ nylon membranes ( GE Healthcare , Buckinghamshire , UK ) . The PCR products used to construct the RNAi stem loop vectors served as templates to make the [32P]-labeled probes by random priming , using Prime-a-Gene Labeling System ( Promega ) . Hybridization was performed overnight at 60°C in hybridization buffer containing 7% ( w/v ) SDS , 1 mM EDTA , 0 . 5 M Na2HPO4 , 24 mM H3PO4 , pH 7 . 2 , and the membrane was analyzed by autoradiography using BioMax MS film and a TransScreen-HE intensifying screen . Ribosomal RNA was visualized on the same formaldehyde-agarose gel by ethidium bromide staining to control for equal loading . Parasites ( 106 in 100 μl ) were allowed to adhere to a microscope slide for 10 min , fixed with 4% paraformaldehyde in PBS , washed with PBS , and permeabilized with 0 . 2% ( w/v ) Triton X-100 in PBS . After incubation in PBS containing 2% bovine serum albumin ( blocking buffer ) for 30 min , primary antibody in blocking solution was added for 45 min . Antibodies used were mouse monoclonal anti-cMyc 9E10 ( Santa Cruz Biotechnology , Heidelberg , Germany ) and rabbit anti-VDAC antiserum at dilutions of 1:250 and 1:1000 , respectively . After washing with PBS , the corresponding secondary fluorophore-conjugated antibodies , goat anti-mouse Alexa Fluor 594 and goat anti-rabbit Alexa Fluor 488 ( Invitrogen ) , respectively , at dilutions of 1:100 in blocking solution , were added for 45 min . Free antibody was removed by washing with PBS and cells were mounted with Vectashield containing 4 , 6-diamidino-2-phenylindole ( DAPI; Vector Laboratories ) . The slides were analyzed using a Leica SP2 microscope equipped with a 100 × oil objective . Photographs were acquired with Leica LAS AF Version 2 . 1 . 0 software ( Leica Microsystems ) . T . brucei bloodstream forms were incubated in the presence of 80–350 nM G25 for 24 h . Aliquots of 0 . 5 ml were taken to measure mitochondrial membrane potential ( ΔΨm ) and cell permeability by propidium iodide ( PI ) staining . The ΔΨm was measured by adding 25 nM tetramethylrhodamine ethyl ester ( TMRE ) to bloodstream form cultures . After 30 min of incubation at 37°C , parasites were washed with and resuspended in PBS , and immediately analyzed by flow cytometry ( FACScan BD , equipped with Cytek solid state laser ) using the FL2-channel detector . The geometrical mean values of 10’000 gated events were normalized to control samples . In control cultures , 50 μM carbonyl cyanide m-chlorophenyl hydrazone was added to disrupt ΔΨm . For evaluation of cell permeability , 10 μg/ml of PI was added to parasite cultures and incubated for 10 min at 37°C , protected from light . Subsequently , 0 . 5 ml of culture was transferred to FACS tubes and fluorescence was measured using FL3-channel detector . Ten thousand gated events were separated into two areas—according to fluorescence intensity—as follows: the fluorescence intensity of a sample containing digitonin-permeabilized parasites was measured and referred to as PI-positive ( PI+ ) . Fluorescence intensities lower than this value were considered PI-negative ( PI- ) . A crude mitochondrial fraction from TbMCP14 conditional knock-out parasites cultured in glucose-depleted medium ( SDM80 ) supplemented with 10% heat-inactivated FBS were prepared as described before [45] . Briefly , 108 parasites were collected by centrifugation and washed once in cold sodium phosphate buffer ( 150 mM Tris-HCl pH 7 . 9 , 20 mM NaH2PO4 and 20 mM glucose ) . The cell pellet was resuspended in 0 . 5 ml SoTE ( 0 . 6 M sorbitol , 20 mM Tris-HCl , pH 7 . 5 , and 2 mM EDTA ) and combined with 0 . 5 ml of 0 . 02% ( w/v ) digitonin in SoTE . After 5 min of incubation on ice , the suspension was centrifuged at 5’500 × g and the remaining pellet ( mitochondrial suspension ) was resuspended in 750 μl of assay buffer ( 20 mM Tris-HCl , pH 7 . 4 , 15 mM KH2PO4 , 0 . 6 M sorbitol , 10 mM MgSO4 , 10 mg/ml fatty-acid-free bovine serum albumin ) . ATP production assays were done as described [59] . Briefly , 5 mM succinate , 5 mM 2-ketoglutarate or different concentrations of proline , together with 67 μM ADP , were added to 71 . 5 μl of mitochondrial suspension . After incubation at room temperature for 30 min , the reaction was stopped and the ATP concentration was determined using ATP Bioluminescence Assay Kit CLS II ( Roche , Basel , Switzerland ) . Inhibitors were pre-incubated with mitochondrial suspension for 10 min on ice and used at the following final concentrations: atractyloside ( 43 μM ) and antimycin ( 2 . 7 μM ) . Parasites ( 5 × 107 cells ) collected from cultures grown to mid log phase were harvested and quenched and metabolites extracted in 100 μl of chloroform/methanol/water ( 1:3:1 , by vol ) as previously described in [60] . HPLC using a ZIC-pHILIC column ( 150 mm × 4 . 6 mm , 5 μm column , Merck Sequant and a Dionex UltiMate 3000 RSLC system ( Thermo , Hemel Hempstead , UK ) with metabolite masses identified using a Thermo Orbitrap Exactive ( Thermo Fisher Scientific , Hemel Hempstead , UK ) operated in polarity switching mode with lock-mass correction applied to enhance calibration stability . XCMS software [61] was used for untargeted peak detection and mzMatch . R [62] for peak matching and annotation of related peaks . The IDEOM software package [63] was used to identify metabolites either through matching accurate masses and retention times of authentic standards ( Metabolomics Standards Initiative confidence level 1 ) or using predicted retention times using a previously validated model [64] ( Metabolomics Standards Initiative confidence level 2 ) if authentic standards were not available . Profile searches were performed with the command line version of HMMer 3 . 01 [65] and the results were parsed with ad hoc Perl scripts . SwissProt release 2014_05 was downloaded from ftp . uniprot . org . Blast searches were carried out on blast . ncbi . nlm . nih . gov . Muscle multiple alignments and Neighbor-Joining trees were done with amino acid sequences on Mega5 [66] , using default parameters and the JTT substitution model . GenBank accession numbers of the ( full-length ) sequences of S5 Fig are the following: T . vivax , 340057877; T . grayi , 686632047; T . cruzi , 407846745; T . rangeli , 554941519; L . donovani , 398013843; L . major , 157867905; L . braziliensis , 154335581; Phytomonas sp . , 588319594; Strigomonas culicis , 528241051; Angomonas deanei , 528250442; Ricinus communis , 255580342; Glycine max , 356568805; Oryza sativa , 115455415; Medicago truncatula , 657381127; Vitis vinifera , 359488385; SLC25AA1 , 13436407; SLC25AA4 , 178659; SLC25AA29 , 119602101; SLC25AA32 , 18256909; SLC25AA36 , 119599418; SLC25AA44 , 14250748 . | Human and animal trypanosomiases caused by Trypanosoma brucei parasites represent major burdens to human welfare and agricultural development in rural sub-Saharan Africa . Although the numbers of infected humans have decreased continuously during the last decades , emerging resistance and adverse side effects against commonly used drugs require an urgent need for the identification of novel drug targets and the development of new drugs . Using an unbiased genome-wide screen to search for genes involved in the mode of action of trypanocidal compounds , we identified a member of the mitochondrial carrier family , TbMCP14 , as prime candidate to mediate the action of a group of anti-parasitic choline analogs against T . brucei . Ablation of TbMCP14 expression by RNA interference or gene deletion decreases the susceptibility of parasites towards the compounds while over-expression of the carrier shows the opposite effect . In addition , down-regulation of TbMCP14 protects mitochondria from drug-induced decrease in mitochondrial membrane potential and reduces proline-dependent ATP production . Together , the results demonstrate that TbMCP14 is involved in energy production in T . brucei , possibly by acting as a mitochondrial proline carrier , and reveal TbMCP14 as candidate protein for drug action or targeting . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [] | 2015 | An Atypical Mitochondrial Carrier That Mediates Drug Action in Trypanosoma brucei |
It is a long-held belief in evolutionary biology that the rate of molecular evolution for a given DNA sequence is inversely related to the level of functional constraint . This belief holds true for the protein-coding homeotic ( Hox ) genes originally discovered in Drosophila melanogaster . Expression of the Hox genes in Drosophila embryos is essential for body patterning and is controlled by an extensive array of cis-regulatory modules ( CRMs ) . How the regulatory modules functionally evolve in different species is not clear . A comparison of the CRMs for the Abdominal-B gene from different Drosophila species reveals relatively low levels of overall sequence conservation . However , embryonic enhancer CRMs from other Drosophila species direct transgenic reporter gene expression in the same spatial and temporal patterns during development as their D . melanogaster orthologs . Bioinformatic analysis reveals the presence of short conserved sequences within defined CRMs , representing gap and pair-rule transcription factor binding sites . One predicted binding site for the gap transcription factor KRUPPEL in the IAB5 CRM was found to be altered in Superabdominal ( Sab ) mutations . In Sab mutant flies , the third abdominal segment is transformed into a copy of the fifth abdominal segment . A model for KRUPPEL-mediated repression at this binding site is presented . These findings challenge our current understanding of the relationship between sequence evolution at the molecular level and functional activity of a CRM . While the overall sequence conservation at Drosophila CRMs is not distinctive from neighboring genomic regions , functionally critical transcription factor binding sites within embryonic enhancer CRMs are highly conserved . These results have implications for understanding mechanisms of gene expression during embryonic development , enhancer function , and the molecular evolution of eukaryotic regulatory modules .
The Drosophila bithorax complex ( BX-C ) is over 300 kb in size [1] , but contains only three homeotic ( Hox ) genes , Ultrabithorax ( Ubx ) , abdominal-A ( abd-A ) , and Abdominal-B ( Abd-B ) [2] . These genes control the identity of ten parasegments ( PS5-14 ) in the posterior thorax and abdomen of the developing fly and are important in the evolution of animal morphology [3] . Extensive genomic regions between the Hox genes in the BX-C , called infraabdominal ( iab ) regions , harbor distinct non-genic DNA sequences , called cis-regulatory modules ( CRMs ) , which regulate the neighboring Hox genes ( Figure 1A ) ( for recent comprehensive reviews see [4] , [5] ) . One type of CRM , the embryonic enhancer , acts in response to gap and pair-rule factors to initiate specific patterns of transcription for the Hox genes during early embryonic development . Other classes of CRMs include insulators , which act as boundary elements to prevent cross-talk between adjacent iab regions [6] , [7] , and Trithorax and Polycomb response elements , which function to maintain patterns of Hox gene expression or silencing in later developmental stages via chromatin-mediated effects [8] , [9] . The BX-C Hox gene Abd-B specifies the developmental identity of the 10th to 14th parasegments ( abdominal segments 5–9 ) during Drosophila melanogaster development [10] . The iab-5 to iab-8 genomic regions each harbor at least one embryonic enhancer CRM which is responsible for driving Abd-B expression in specific segments ( Figure 1A ) [4] , [11] . The IAB5 enhancer CRM in the iab-5 genomic region is capable of driving Abd-B expression in the presumptive fifth , seventh , and ninth abdominal segments of Drosophila melanogaster [12] . Similarly , the IAB8 enhancer CRM in the iab-8 region is responsible for driving Abd-B expression in the presumptive eighth abdominal segment [13] , [14] . Enhancer CRMs usually contain a high number of transcription factor binding sites ( TFBSs ) , strongly indicating that regulation of gene expression by these CRMs is controlled by the binding of specific transcription factors ( TFs ) [15] , [16] . Previous work on the IAB5 enhancer CRM identified several TFs that directly regulate IAB5 activity . IAB5 is thought to mediate transcriptional activation of Abd-B by the binding of the pair-rule factor FUSHI-TARAZU ( FTZ ) [17] , which is expressed in seven stripes in the developing embryo . There are currently three reported gap transcriptional repressors known to bind at the IAB5 CRM; KRUPPEL ( KR ) , KNIRPS ( KNI ) and HUNCHBACK ( HB ) [17] . KR has been shown to set the anterior boundary for IAB5 activation in the embryo . KNI is thought to be a weak repressor , while the role for HB remains unclear , although previous studies suggest it may act as a direct repressor [17] . The high level of conservation of the homeodomain-coding sequences for the Hox proteins was essential to their discovery in species as diverse as fish , frogs and humans [18] . However , equivalent sequence knowledge does not exist for the evolution of the extensive array of CRMs that are critical for the control of Hox gene expression patterns . Early pioneering research on the evolution of sequence and functional activity at CRMs in Drosophila has focused on the eve stripe 2 enhancer ( S2E ) . In particular , Ludwig and colleagues discovered that the S2Es in D . yakuba , D . erecta and D . pseudoobscura , identified by sequence alignment to the D . melanogaster S2E , are able to drive reporter gene expression in transgenic D . melanogaster embryos in a comparable spatio-temporal pattern to the endogenous D . melanogaster S2E [19] . This evolutionary analysis was recently extended by the Eisen lab to the more evolutionarily divergent scavenger fly ( Sepsid ) species . The eve stripe 2 , stripe 3+7 , stripe 4+6 and muscle-heart enhancers from Sepsid species ( S . cynipsea , T . putris , and T . superba ) are all able to drive reporter gene expression in transgenic D . melanogaster in a spatio-temporal pattern comparable to their D . melanogaster CRM orthologs [20] . The conservation of the functional activity of these enhancers paradoxically contrasts with the relative lack of overall sequence conservation of the S2E enhancer within Drosophila and the more pronounced rearrangement of sequences at the eve genomic regulatory region in Sepsid species relative to Drosophila . Despite these and other recent advances deciphering other regulatory sequences [21]–[24] , there remain many challenges in identifying Drosophila cis-regulatory sequences through the application of bioinformatic comparative sequence analysis . In large genomes such as that of vertebrates , high level sequence conservation of a non-protein coding genomic region compared to surrounding genomic regions is often indicative of potential cis-regulatory activity [25]–[32] . However , these types of comparative studies have been less successful in small-genome invertebrates such as Drosophila melanogaster and Caenorhabditis elegans [33] , [34] . To address these issues , we compared the sequence conservation at many of the previously identified CRMs for the Abd-B gene in the Drosophila melanogaster BX-C ( Figure 1A ) . These analyses were made possible by the recent sequencing of twelve Drosophila genomes [35] . In this study we analyzed BX-C sequences from seven species spanning approximately 60 million years of evolutionary time: D . melanogaster , D . simulans , D . erecta , D . yakuba , D . ananassae , D . pseudoobscura and D . virilis ( Figure 1B ) [36] . Our experiments demonstrate that despite a distinctive lack of sequence conservation when compared to neighboring genomic regions , the experimentally well-defined IAB5 and IAB8 enhancer CRMs are functionally conserved across the Drosophila genus . While overall levels of sequence conservation may not necessarily correlate with functional conservation , sequence homology to known functional CRMs in D . melanogaster may assist with the identification of functional CRM orthologs in the other Drosophila species . In our quest to further understand the evolution of CRM function at the molecular level , we also developed a more stringent bioinformatic approach to identify highly conserved TFBSs critical for the functional activity of enhancers . It will be of great interest to apply these bioinformatic analyses to the molecular dissection of enhancer function and to identify additional CRMs in the Drosophila genome .
Bioinformatic analysis of DNA sequence reveals that for the BX-C as a whole and the 3′ control regions of the Abd-B gene ( iab5–iab8 ) , there is a strong correlation between the species divergence time and the level of sequence conservation ( Figure 1B and Table S1 ) . In agreement with the biological paradigm that functional regions in the genomes of closely related species are subject to evolutionary constraint , the Abd-B exons exhibit a significantly higher level of sequence conservation than the neighboring sequences of the BX-C across all seven Drosophila species ( Figure 1B , Abd-B exons ) . In contrast , the specific functional CRMs identified in the BX-C do not follow this pattern , but are comparably conserved to the neighboring genomic sequences in all the species analyzed ( Figure 1B , CRMs and iab5–iab8 ) . Detailed analysis of the sequence conservation and genomic coordinates of DNA regions at the D . melanogaster BX-C are shown in Table S1 . The trend of a relative lack of sequence conservation is found within each class of CRMs , including enhancers , insulators , anti-insulators and Polycomb-response elements , suggesting that sequences are evolving rapidly at all types of CRMs in the BX-C . The non-protein coding regions of the BX-C are only slightly more conserved across the Drosophila genus than the neighboring upstream genomic region of equal size from outside of the BX-C on chromosome 3R and are comparable in level of conservation to the considerably more compact ( ∼18kb ) eve gene and associated genomic regulatory regions ( Table S1 ) . The lack of sequence conservation of the iab regulatory regions and associated CRMs compared to neighboring protein-coding sequences led us to investigate whether the spatio-temporal expression pattern of Abd-B in other Drosophila species is different from that in D . melanogaster . In situ hybridization ( ISH ) with probes against Abd-B in embryos collected from the different Drosophila species revealed that the expression pattern is conserved in all species at early stages of development ( Figure S1 ) and is localized to abdominal segments 5–9 in late stage embryos ( data not shown ) . This result indicates that the regulation of Abd-B gene expression in the embryo may be evolutionarily conserved . Similar to the other BX-C CRMs , the sequences at the IAB5 and IAB8 enhancer CRMs are no more conserved than neighboring regions of DNA . The 1kb IAB5 [12] and 1 . 6kb IAB8 [14] enhancers are well-defined regions discovered in transgenic studies . Comparison of IAB5 to the neighboring downstream genomic region of equal length ( dIAB5 ) reveals that the two regions do not demonstrate significant differences in levels of sequence conservation ( Figure 2A ) and both regions have progressively diminishing levels of sequence conservation in more distantly related Drosophila species ( Figure 2B ) . Therefore , the IAB5 CRM appears no more highly conserved than an equal-sized neighboring region of DNA . To compare the functional activity of IAB5 and dIAB5 regions from D . melanogaster , they were each tested in transgenic reporter gene assays . In contrast to the IAB5 region , dIAB5 is unable to activate reporter gene expression during any stage of embryonic development ( Figure 2C ) , although this does not preclude the dIAB5 region from other potential functional activities . The sequence conservation of the IAB8 enhancer CRM also rapidly decreases in species more distantly related to D . melanogaster . IAB8 exhibits significantly lower levels of sequence conservation across the Drosophila genus when compared to the conservation of the IAB5 enhancer ( Figure 2B ) . Indeed , the IAB8 enhancer exhibits the lowest levels of sequence conservation of the known enhancers of the BX-C across the Drosophila genus ( Table S1 ) . The striking lack of underlying sequence conservation demonstrated by the BX-C CRMs suggests that they are evolving rapidly in Drosophila species . This prompts the intriguing question of whether the functional activity of a CRM can be conserved in the absence of overall sequence conservation . In order to test this question , we generated transgenic D . melanogaster harboring a reporter construct with the orthologous IAB5 or IAB8 sequences from different Drosophila species ( Figure 3A ) . Despite the lack of sequence conservation across the Drosophila genus , orthologous IAB5 regions , identified by simple sequence alignment using default VISTA values [37] ( see Materials and Methods ) , from each of the six species tested ( D . melanogaster , D . simulans , D . erecta , D . yakuba , D . ananassae , and D . pseudoobscura ) were able to drive lacZ ( Figure 3B ) and white ( not shown ) reporter gene expression in the fifth , seventh , and ninth abdominal segments . These patterns are evident in both stage 5 and stage 9 embryos and are consistent with the known pattern of IAB5 activity [12] , [38] . Despite a more pronounced lack of underlying sequence conservation orthologous IAB8 regions , identified by simple sequence alignment in each of the three species tested ( D . melanogaster , D . simulans , and D . pseudoobscura ) were also able to drive lacZ ( Figure 3B ) and white ( not shown ) reporter gene expression in a conserved pattern in the eighth abdominal segment of D . melanogaster embryos at stage 5 and stage 9 in transgenic assays ( Figure 3C ) [14] . Note that the additional staining that appears in the anterior region in Drosophila embryos when using the lacZ ISH probe and is not specific to transgenes carrying the IAB5 or IAB8 enhancers . This ectopic staining anterior staining , which corresponds to thoracic segment T1 in stage 9 embryos ( see embryos in Figure 3B ) , has been documented in the literature as background staining [12] , [14] that occurs when using the lacZ ISH probe . Detailed analysis of sequence conservation within the IAB5 enhancer CRM reveals three sub-regions that are highly conserved even in distantly related Drosophila species ( Figure 2A ) . This discovery prompted us to analyze the spatial distribution of predicted TFBSs in the D . melanogaster IAB5 sequence to examine whether they were clustered in the regions of high conservation . In order to perform this analysis , experimentally verified TFBSs in the D . melanogaster genome were compiled using databases from the Eisen [39] , Siggia [40] and Desplan [41] laboratories in combination with the Transfac public database [42] and additional experimentally confirmed TFBSs found in literature searches as described in the Materials and Methods section ( Dataset S1 ) . ANN-Spec [43] was used to align the TFBS sequences and develop an alignment matrix and a position weight matrix ( PWM ) for each of six TFs: BICOID ( BCD ) , EVEN-SKIPPED ( EVE ) , FUSHI-TARAZU ( FTZ ) , HUNCHBACK ( HB ) , KNIRPS ( KNI ) and KRUPPEL ( KR ) ( Figure 4A ) ( see Materials and Methods for details ) . Using Motility [44] , putative TFBSs were scored in the IAB5 enhancer CRM and the neighboring downstream IAB5 region ( dIAB5 ) ( Figure 2 ) . The IAB5 and dIAB5 sequences were also each randomized 1000 times ( rIAB5 and rdIAB5 ) and the 99 . 5 percentile score for a putative TFBS in the randomized sequence was calculated for each of the six TFs ( Figure 4B ) . All putative TFBSs located in IAB5 and dIAB5 with scores above the 99 . 5 percentile score from the corresponding randomized sequence were identified ( Figure 4B ) . Chi-square tests were used to determine if there is significant enrichment of TFBSs at IAB5 ( see Materials and Methods for detailed description ) . In addition , a subset of TFBSs with a score above the 99 . 5 percentile were identified as high scoring sites by comparing the number of TFBSs predicted in the IAB5 and dIAB5 regions to the number of sites identified in the corresponding randomized sequences within the same range of scores . These computational bioinformatic approaches are described in detail in the Materials and Methods section and summarized in a concise flow chart ( see Figure S9 ) . The IAB5 CRM sequence features significant enrichment of putative HB TFBSs when compared to both dIAB5 ( p<0 . 001 ) and rIAB5 ( p<0 . 001 ) ( Figure 4B and 4C ) . There is also an enrichment of KR binding sites in IAB5 when compared to dIAB5 and rIAB5 , though not statistically significant ( Figure 4B and 4C ) . In comparison , the dIAB5 sequence is not significantly enriched in putative binding sites for any of the six TFs analyzed . Additionally , one high-scoring FTZ site , six high-scoring HB sites and one high-scoring KR site ( see Materials and Methods for definition of high-scoring ) were identified in IAB5 ( Figure 4B and 4C and Figure S2A , S2B ) . These high-scoring TFBSs are not clustered in the sub-regions of the IAB5 CRM that exhibit high levels of conservation across Drosophila species ( Figure S2A ) . Similar TFBS enrichment in IAB5 compared to dIAB5 was not observed for BCD or EVE . These results are in agreement with the known functional activities of HB , KR and FTZ with respect to the IAB5 CRM . HB and KR are known transcriptional repressors that act through binding IAB5 , while FTZ is a known activator of IAB5 [17] . BCD and EVE were found not to be direct regulators of IAB5 in previous TF mutant studies [17] , reflected in the lack of significant TFBS enrichment for these two factors in the IAB5 CRM sequence when compared to the dIAB5 sequence ( Figure 4B and 4C ) . Similar bioinformatic analysis was performed on the previously identified IAB2 [45] , IAB7a [11] , IAB7b and IAB8 [46] embryonic enhancer CRMs from the BX-C ( Table S2 ) . In general , these other IAB enhancers also exhibit greater enrichment of high-scoring putative TFBSs than neighboring regions of equal size , comparable sequence conservation and unknown function ( Figure S3 , S4 , S5 , S6 ) . High-scoring HB and KR TFBS are found in many of the IAB enhancer CRMs , though overall enrichment , when compared to the neighboring and randomized genomic regions , is not always statistically significant ( Figure S7 , S8 ) . In particular , IAB7b exhibits a similar profile of putative TFBSs to the IAB5 enhancer , featuring an enrichment of high-scoring KR , HB and FTZ binding sites ( Figure S4 , S7B , S8B ) . Superabdominal ( Sab ) is a gain of function homeotic mutation [10] . In wild-type ( WT ) adult male flies , the abdominal segments A5 , A6 , A7 and A8 exhibit a characteristic dark pigmentation . In the Sab1 mutant , abdominal segment A3 , but not A4 , exhibits ectopic dark pigmentation , suggesting a phenotypic transformation of A3 towards an A5-like identity ( Figure 5A ) [10] . Furthermore , the Abd-B gene is expressed in A3 of Sab1 mutants , whereas it is normally repressed in this segment in WT embryos [10] . Although the molecular nature of the Sab1 mutation was not known , this suggested that the IAB5 enhancer CRM may be ectopically active in the A3 segment in flies carrying the Sab1 mutation ( Figure 5 ) . We hypothesized that if there is ectopic activation of IAB5 , it may occur by two possible means . First , a mutation in the IAB5 sequence could create an additional activator TFBS so that IAB5 might overcome the normal repression of Abd-B in A3 . The second possibility is that a strong repressor TFBS is mutated such that the repressor TF can no longer effectively bind and repress transcriptional activation of Abd-B by IAB5 in A3 . Sequencing of the Abd-B regulatory region of the Sab1 mutant reveals a single point mutation in the center of the IAB5 CRM sequence ( Figure 5B ) . This is the only mutation in the IAB5 CRM in Sab1 mutants and this point mutation is located in the highest scoring putative KR repressor TFBS predicted in our bioinformatic analysis . The Sab1 mutation presumably significantly weakens the affinity of KR for this TFBS as it substitutes the best possible base ( G ) at the fourth nucleotide position ( base position 104543 in U31961 ) in the binding site to the worst possible base ( A ) at that position ( Figure 5B ) . Effectively , the Sab1 mutation transforms this KR TFBS from a high to very low affinity site . Furthermore , this binding site is the only statistically significant high-scoring KR site identified by our computational analysis in IAB5 and is completely conserved in Drosophila species from D . melanogaster to D . mojavensis ( Figure 5C ) . The mutation of the high-scoring KR TFBS in the IAB5 enhancer CRM in Sab1 flies appears to allow IAB5 to ectopically activate Abd-B in the A3 segment ( Figure 5D ) . Correspondingly , Kr mutant embryos exhibit an anterior expansion of the Abd-B expression domain , which confirms our suggestion that KR is no longer acting as a repressor of the IAB5 enhancer in Sab1 mutants [17] . IAB5 does not ectopically activate Abd-B in A4 due to the absence of the necessary FTZ activator ( see Discussion for details ) ( Figure 5D ) . Intriguingly , sequencing of the IAB5 region in an independently generated line with the Sab phenotype ( Sab2 ) reveals a second point mutation in the exact same KR binding site as in Sab1 . This mutation is the only one in the IAB5 CRM of Sab2 flies ( A>G substitution at base 104541 in U31961 ) and would also be predicted to severely disrupt the strength of the KR binding site , based on our bioinformatic analysis ( Figure 5B ) . To address the functional importance of the Sab KR site for in vivo repression of the IAB5 CRM , we generated transgenic D . melanogaster carrying a reporter construct with the IAB5 CRM harboring the Sab1 or Sab2 mutation ( Figure 6A ) . In contrast to the wild-type ( WT ) IAB5 CRM , which drives reporter gene expression in the fifth , seventh , and ninth abdominal segments , the Sab mutant IAB5 CRMs drive ectopic expression in three distinct additional anterior stripes of lacZ ( Figure 6B ) and white ( data not shown ) . The ectopic anterior stripes of expression driven by the Sab mutant IAB5 CRMs observed in Stage 5 and Stage 9 correspond to the second thoracic ( T2 ) , first ( A1 ) and third ( A3 ) abdominal segments and overlap with the endogenous expression pattern of the FTZ activator ( Figure 6C ) . Additional background staining , which has been previously documented [14] , [47] , also appears in the anterior region in Drosophila embryos when using the lacZ ISH probe . This background expression is observed in embryos carrying a WT copy of the IAB5 enhancer and is slightly more anterior , corresponding to segment T1 , than the ectopic expression seen in T2 from the Sab mutant IAB5 embryos ( Figure 6B ) . The anterior expansion of IAB5 CRM activity seen in the mutant transgenic embryos confirms that the Sab binding site is critical for KR-mediated repression of the IAB5 enhancer CRM ( see Discussion for detailed analysis ) .
The relative lack of overall sequence conservation at the functional CRMs of the Abd-B gene compared to surrounding genomic regions is consistent with emerging studies of other CRMs in Drosophila [16] . Indeed , only 2% of the identified conserved sequences outside of exons in mammals correspond to known CRMs [48] , suggesting that sequence conservation alone may not be an indicator of regulatory function . The relative lack of information for many CRMs has in general made computational predictions of regulatory modules based on sequence conservation very challenging . Indeed , a number of other studies have suggested that the function of a CRM can be conserved in Drosophila [22] , [49] and related insect species [20] even when the sequence varies ( for a review see [50] ) . The results from this study indicate that the CRM sequences at the Hox genes in Drosophila are rapidly evolving compared to neighboring protein-coding sequences ( Table S1 ) and therefore may be difficult to identify in other Drosophila species by conservation of primary sequence alone . Comparative genomic techniques based on sequence conservation to identify CRMs have been shown to be more effective in species with larger intergenic sequences , as is the case between the larger Sepsid genomes and the smaller Drosophila genomes [34] . Despite this fact , once a CRM from the BX-C has been identified ( in this case in D . melanogaster ) , simple sequence alignment is able to identify orthologous CRMs in other Drosophila species with conserved functional activity . The conserved function of diverged CRMs suggests that the molecular mechanisms which regulate CRM function may also be evolutionarily conserved . The functional conservation of orthologous CRMs in Drosophila , despite a lack of overall sequence conservation , has several plausible explanations . A particularly compelling argument may be that while there is an overall lack of sequence conservation in a CRM , highly conserved functional sub-regions ( such as TFBSs ) might be embedded within a larger region of non-functional DNA . However , previous studies have indicated that other properties of the DNA sequences in a CRM may also be conserved , such as the combinatorial architecture of TFBSs which may include features such as clustering of the binding sites [15] , [16] , [51] . In the context of the BX-C CRMs further bioinformatic studies , molecular analysis and transgenic assays to test the individual conserved sub-regions of the IAB5 CRM for enhancer function will clarify this issue . It will also be interesting to investigate functional compatibility in orthologous CRM sub-regions from different species . Could a functional enhancer be constructed from reciprocal halves of the IAB5 enhancer CRMs from D . melanogaster and D . pseudoobscura ? Previous studies with the eve stripe 2 enhancer have shown that a chimeric enhancer constructed from two halves of the functional enhancers identified in D . melanogaster and D . pseudoobscura is able to recapitulate the function of the individual component enhancers [52] . Another key area for future investigation is whether the functional conservation observed for embryonic enhancers from different Drosophila species extends to other classes of CRMs in the BX-C and , even more broadly , to CRMs elsewhere in the genome . For example , recent evidence has indicated that some functional overlap exists between the activity of the D . melanogaster Fab-7 and Fab-8 insulators [53] and PREs from the BX-C [54] ( Figure 1A ) , even in the absence of significant sequence homology . These findings suggest that orthologous insulators and PREs from different Drosophila species , which share a lack of underlying sequence conservation ( Table S1 ) , may also be evolutionarily conserved in function . Hyperabdominal ( Hab ) is another gain of function homeotic mutation at the BX-C [2] . The abd-A expression domain in Hab embryos is extended further anterior compared to WT embryos and the third thoracic segment ( T3 ) is transformed toward an A2-like identity [2] , [55] . The most common Hab phenotype is loss of the haltere and/or the third leg normally found in segment T3 and the gain of bristles which are normally found in segment A2 [2] , [55] . The Hab mutation is a single point mutation that maps within the IAB2 embryonic enhancer sequence [55] . This single point mutation is located within the highest scoring bioinformatically predicted KR site in IAB2 in our analysis . Specifically , the mutation is a G to A substitution in the fourth base position of the KR binding site – the exact same mutation as in the highest scoring KR binding site in the IAB5 enhancer of Sab1 mutants . In Hab embryos , mutation of the highest scoring KR binding site in IAB2 severely weakens KR binding affinity . An IAB2-directed lacZ reporter construct confirms that the identified single point mutation in the KR binding site of IAB2 results in ectopic gene expression in segment A3 , in which KR is present [56] . The O'Connor lab also performed a DNA footprinting assay on the IAB2 enhancer CRM with KR and HB proteins [56] . These biochemical binding data offer an opportunity for us to directly test the accuracy of our computational TFBSs predictions . All the KR and HB sites identified by the DNA footprinting assay overlap with sites that we predict using bioinformatic analysis in IAB2 , including the high-scoring KR binding site mutated in Hab flies [56] . A critical question remains concerning the nature of the sequences which are responsible for the molecular activity of the CRM . Based on the Sab phenotype and the corresponding point mutation that we have characterized in the IAB5 CRM sequence in Sab1 and Sab2 mutants , we hypothesize that a single TFBS mutation can dramatically alter the functional activity of a CRM . In the case of the IAB5 transcriptional enhancer , a single G to A substitution in the fourth base position of the highest scoring computationally predicted KR binding site in the CRM , with no additional changes in the 1027bp IAB5 CRM sequence , is able to mediate ectopic activation of the enhancer and drive Abd-B expression in abdominal segment 3 ( A3 ) in Sab1 mutants ( Figure 5 ) . This point mutation would significantly lower the affinity of KR binding to this site , as predicted by the KR consensus binding sequence . Prior to this study , the molecular nature of the Sab1 and Sab2 homeotic mutations was unknown . Our transgenic reporter gene assay reveals that the IAB5 enhancer carrying just the Sab1 or Sab2 single point mutation ( Figure 6A ) is able to ectopically activate reporter gene expression in three additional anterior segments; T2 , A1 and A3 ( Figure 6B ) . This anterior expansion of IAB5 activity corresponds precisely with the embryonic domains of KR and FTZ expression ( Figure 6C ) . The three ectopic anterior stripes of gene expression observed therefore strongly indicate that the Sab point mutations leave the IAB5 CRM unable to respond to repression through KR binding . The ablation of KR binding consequently allows the IAB5 CRM to respond to a wider domain of activation by FTZ in the embryo ( Figure 6C ) . Given that the Sab IAB5 CRMs can drive ectopic gene expression in anterior segments T2 , A1 and A3 , an intriguing question is why in adult Sab mutants only A3 is transformed to an A5-like identity , while the phenotypes of the A1 and T2 segments appear unaffected . The observed differences can be resolved by considering the gradient of KR protein across the anterio-posterior axis in the early Drosophila embryo ( Figure 6D ) . In A3 , KR is present at a low concentration ( Figure 6D ) [57] . Since the mutated Sab KR binding site presumably has very low affinity for KR , the TF can no longer effectively bind to it in A3 and repress IAB5 activity . As a result , in A3 , the Sab IAB5 CRM is able to direct both reporter gene expression on transgenes and Abd-B expression at the endogenous BX-C ( Figure 6B–6D ) . In contrast , cells in segments T1 , T3 , A2 and A4 lack the presence of the known activator TF , FTZ [17] , so IAB5 is inactive and Abd-B is not expressed ( Figure 6D ) . In the more anterior A1 segment , KR protein concentration is at its peak ( Figure 6D ) [57] . Thus , at this very high concentration KR may still be able to bind ( albeit in a restricted manner ) to the mutated Sab binding site in IAB5 in the A1 segment of Sab1 and Sab2 embryos . As a result , IAB5 remains repressed and Abd-B is not expressed from the endogenous BX-C in A1 in these flies . In our sensitive transgenic assay we can detect ectopic reporter gene expression driven by the Sab IAB5 CRMs in A1 ( Figure 6B ) . However , the expression in A1 is consistently weaker than in A3 or T2 , suggesting that the Sab IAB5 CRM may continue to be partially repressed by KR binding in A1 . It is possible that the high KR concentration in A1 ensures that despite reduced binding of KR to the IAB5 CRM at the endogenous BX-C in Sab mutants , it is still above a threshold level and is therefore capable of preventing activation of the Abd-B target gene by IAB5 ( Figure 6D ) . Similarly , in nuclei located in segment T2 there is a high level of KR present , which may prevent activation of the Abd-B gene by the IAB5 CRM at the endogenous BX-C in Sab mutants ( Figure 6D ) . An additional genetic component contributing to the repression of Abd-B in A1 and T2 in Sab mutants may be the high level of ULTRABITHORAX ( in A1 ) and ANTENNAPEDIA ( in T2 ) Hox proteins . It is feasible that the phenotypic identity of these segments is maintained in Sab mutants by high level expression of the endogenous Hox proteins , even if Abd-B is weakly expressed under the direction of the mutant IAB5 CRM . The absence of Sab IAB5 activity in segment C3 ( labial segment ) from both transgenes and at the endogenous locus , even in the presence of the FTZ activator , suggests that repression of the IAB5 enhancer CRM requires additional anterior repressor TFs . In an effort to directly compare the predictive specificity of our TF PWM with existing PWMs , we obtained KR PWMs from the Berkeley Drosophila Transcription Network Project ( BDTNP ) [39] , from the Transfac repository [42] and from eCisAnalyst [58] . To determine the relative specificity with which the different matrices can indicate the location of functional binding sites , each PWM was individually used to scan through the D . melanogaster BX-C . The total number of predicted binding sites in the BX-C and the fraction of predicted KR binding sites that scored below the known Sab and Hab sites in the BX-C was counted ( Table S3 ) . This analysis was performed with a relatively stringent score threshold corresponding to ln ( p ) <−6 . 8 to accurately reflect existing bioinformatic approaches [58] . The new KR PWM developed in this study returns fewer predicted sites than the BDTNP and eCis-Analyst matrices , by approximately 10% ( or 75 binding sites ) . This potentially reduces the false discovery rate for binding sites . The Transfac matrix returns slightly fewer hits across the BX-C , but performs worse than the newly developed PWM in predicting the rank of the Sab and , especially , Hab KRUPPEL binding sites . The new KR PWM therefore offers an improvement over the existing PWMs as it increases the stringency of prediction for functional binding sites ( compared to the Transfac matrix ) , without increasing the false discovery rate ( when compared to the BDTNP and eCis-Analyst matrices ) ( Table S3 ) . The agreement of our bioinformatic predictions with experimental data from the Sab and Hab homeotic mutants leads us to conclude that: ( 1 ) the position weight matrices ( PWMs ) for KRUPPEL and HUNCHBACK accurately predict TFBSs in CRMs; ( 2 ) the bioinformatic approach and simple statistical analysis used to obtain these results is effective; ( 3 ) the high-scoring KRUPPEL binding sites found in IAB5 and IAB2 are functional and necessary for repression of the respective CRMs; ( 4 ) KRUPPEL is a critical repressor factor , essential for establishing the correct pattern of expression of the Abd-B and abd-A Hox genes at the endogenous BX-C . Previous studies have highlighted the functional importance of clustered binding of TFs to regulate enhancer activity [15] , [16] , [51] . Clustering of TFBSs has also recently been found to be a typical characteristic in blastoderm-stage Drosophila CRMs [39] . However , our bioinformatic analysis combined with the results in the Hab and Sab mutants suggest that clustering of KR binding sites may not be necessary for effective repression of enhancer CRM activity . This does not preclude the existence of additional KR sites within a given enhancer CRM . In some cases these additional sites may be capable of contributing to repression of CRM activity and therefore play a role in the degree of functional robustness of CRM repression . The Hab and Sab mutants also raise another intriguing question – do they represent the only two gain-of-function point mutations in the entire BX-C ? The only point mutations recovered from large scale genetic screens [2] were those in the Hab ( IAB2 ) and Sab ( IAB5 ) KR binding sites . Intriguingly , mutations in both binding sites were recovered independently on two separate occasions , supporting the notion that the screens successfully identified all possible point mutations causing homeotic transformations of segment identity . In the case of the Hab and Sab mutations the ablation of a single KR binding site is sufficient to cause a gain-of-functional activity for the IAB2 or IAB5 embryonic enhancer CRM , respectively . Therefore , clustering analysis of TFBSs may not be sufficient to predict all functional CRMs in the genome . It will be of interest to investigate how important clustering of putative functionally redundant TFBSs is for CRM activity . The absence of additional gain-of-function point mutations in the BX-C may indicate that at some CRMs there is extensive functional redundancy amongst clustered binding sites for critical TFs . Our bioinformatic studies to identify the sequences responsible for IAB enhancer function are therefore a critical starting point from which to perform the molecular dissection of additional CRMs active during Drosophila embryonic development . In particular , computational prediction of TFBSs promises to be a very useful tool to identify other sequences in the iab regions of the BX-C with transcriptional enhancer function . Experimental verification of the functional activity of TFBSs in conserved vs . non-conserved sub-regions of the CRMs from the BX-C and other genomic loci will greatly enhance our understanding of how evolution acts on the functional constraints of regulatory modules at the sequence level .
Genomic regions from the Abd-B gene in the Drosophila melanogaster bithorax complex from the annotated U31961 Genbank sequence were identified in the Berkeley Drosophila Genome Project D . melanogaster genome ( annotated April 2004 release ) and shown as ‘MEL Chr3R’ in Table S1 . The class A Abd-B transcript and cis-regulatory modules from D . melanogaster used in the sequence conservation analysis were as described in Table S1 and the following publications: IAB8 and IAB7b [46] , IAB7a and IAB6 [11] , IAB5 [12] , IAB2 [45] , Fab-8 [14] , Fab-7 [59] , [60] and Mcp [45] , [60] , PTS7 [61] , PTS6 [47] , PTE [62] , [63] , iab8PRE [14] . Conservation analysis across the seven different Drosophila species was carried out using the following genome sequencing data: D . simulans ( April 2005 , Washington University School of Medicine in St . Louis , http://medschool . wustl . edu/ ) , D . erecta ( October 2004 , Agencourt Bioscience Corporation ) , D . yakuba ( April 2004 , Washington University School of Medicine in St . Louis ) , D . ananassae ( July 2004 , The Institute for Genomic Research ) , D . erecta ( October 2004 , Agencourt Bioscience Corporation ) , D . pseudoobscura ( July 2003 , Human Genome Sequencing Center at Baylor College of Medicine , http://www . hgsc . bcm . tmc . edu/ ) and D . virilis ( July 2004 , Agencourt Bioscience Corporation ) [35] . Sequences were globally aligned with VISTA sequence alignment tools [37] and conserved regions were identified using default VISTA values . Level of conservation is indicated by color code: >90% red , 60–90% orange , 30–60% yellow , <30% green . In situ hybridization probes to detect transcription of Abd-B in five different species of Drosophila were PCR-amplified using D . melanogaster yw67 or D . pseudoobscura adult genomic DNA as a template . An orthologous region to the previously described Bexon region ( exon 8 of the D . melanogaster Abd-B gene ) [64] was identified in D . pseudoobscura using VISTA alignment [37] . The DNA regions were PCR amplified and cloned into pGEMT-Easy ( Promega ) . PCR primer sequences were as follows: Bexon mel s , 5′-GAACAAGAAGAACTCACAGC-3′ ( 53954 ) ; Bexon mel as , 5′-TAGGCATAGGTGTAGGTGTAGG-3′ ( 55566 ) ; Bexon pse s , 5′-GTCAAGAACGACACAACCATTC-3′ ( Chr 2 , 17752184 ) ; Bexon pse as , 5′-GATCAAGCGGAGTCGATACAC-3′ ( Chr 2 , 17751140 ) ; Sense and antisense RNA probes ( relative to the direction of Abd-B transcription ) were prepared using a digoxigenin ( DIG ) RNA-labeling kit ( Roche , Gipf-Oberfrick , Switzerland ) . The expression pattern of Abd-B in D . melanogaster , D . simulans , D . yakuba and D . erecta was detected using the D . melanogaster Bexon probe . In D . pseudoobscura , Abd-B expression was detected using the species-specific D . pseudoobscura Bexon probe . Embryos from each of the five species were collected , fixed and hybridized with the appropriate probes as previously described [64] . Experimentally determined TFBSs from the Drosophila genome were compiled from existing databases in the Eisen [39] , Siggia [40] and Desplan [41] laboratories in combination with the Transfac public database [42] , with duplicated TFBSs removed . Literature searches identified additional experimentally determined TFBSs that were excluded from these four sources ( see Dataset S1 ) . TFBSs sourced from the experimental literature were characterized through DNase I footprinting and chromatin immunoprecipitation ( ChIP ) assays . These additional TFBSs were therefore added to generate a large composite database of experimentally determined TFBSs for six TF: BICOID ( 59 sites ) , EVEN-SKIPPED ( 25 sites ) , FUSHI-TARAZU ( 99 sites ) , HUNCHBACK ( 101 sites ) , KNIRPS ( 79 sites ) and KRUPPEL ( 82 sites ) . The compiled TFBS sequences of varying lengths were input for the program ANN-Spec [43] , which created a sequence alignment of a specified length , an alignment matrix and a position weight matrix ( PWM ) ( Figure 4 and Dataset S1 ) . The optimal length of each matrix was determined by the alignment and PWM score , the number of TFBSs from the compiled database used and by comparing our PWM to other PWMs . The PWMs created by the ANN-Spec algorithm take into account the frequency of each nucleotide at each position in the TFBS and the frequency of a given nucleotide and word in the genome [43] . Graphical representations of the TFBSs were created using Berkeley WebLogo [65] . The program Motility was used to identify putative TFBSs within a given sequence [44] . Motility inputs the PWM and sequence from D . melanogaster and outputs a list of putative binding sites and their associated scores and locations . The IAB5 enhancer CRM ( IAB5 ) and the neighboring downstream genomic region of equal size ( dIAB5 ) were run through the Motility program with each individual TF PWM . As an additional control , to determine the enrichment of binding sites that we would expect by chance in a sequence with the same length and GC content , the IAB5 and dIAB5 sequence were randomized 1000 times and also run through the Motility program for each individual TF PWM . Two different methods were used to analyze the output scores from Motility . One method is used to reduce false negatives—99 . 5 percentile analyses—and the other to reduce false positives—high-scoring sites . Using the program R , the 99 . 5 percentile score of binding sites for each TF found in the randomized sequences was recorded . It was then determined how many TFBSs in the IAB5 enhancer or dIAB5 region scored above the 99 . 5 percentile of each the corresponding randomized sequences: randomized IAB5 ( rIAB5 ) and randomized downstream IAB5 ( rdIAB5 ) . Chi-square tests were used to determine if there was a significant enrichment of TFBSs in the IAB5 and dIAB5 regions as compared to each other and to the rIAB5 and rdIAB5 sequences , respectively . The computational bioinformatic approaches are summarized in a concise flow chart ( Figure S9 ) . High-scoring TFBSs were identified by a more stringent mathematical analysis . For the rIAB5 enhancer or rdIAB5 sequences , the bin distribution of scores for putative binding sites for each of the six TFs was plotted on a histogram . The number of TFBSs in the IAB5 or dIAB5 sequence was then compared to the number of sites identified in the corresponding randomized sequences within the same range of scores . A chi square test was performed on the number of TFBSs in comparable score ranges for the randomized sequences ( the expected value ) and the IAB5 or dIAB5 sequence ( the observed value ) until the expected number of TFBSs in the randomized sequence is greater than one . Effectively , this approach identifies whether there are a significantly greater number of high-scoring TFBSs in the IAB5 enhancer CRM or dIAB5 region than what would be found on average in the randomized sequences . Stocks used in the sequencing of D . melanogaster , D . simulans , D . erecta , D . yakuba , D . ananassae , D . pseudoobscura , and D . virilis were provided by the Tucson Stock Center ( D . melanogaster: 14021-0231 . 36 , D . simulans: 14021-0251 . 195 , D . erecta: 14021-0224 . 01 , D . yakuba: 14021-0261 . 01 , D . ananassae: 14024-0371 . 13 , D . pseudoobscura: 14011-0121 . 94 , D . virilis: 15010-1051 . 87 ) . The location of IAB5 and IAB8 orthologous regions from each species were identified by aligning the D . melanogaster genomic sequence to each of the other Drosophila genomes using VISTA [37] . These regions were PCR amplified from genomic DNA of each species . The PCR primers were designed to border the predicted IAB5 or IAB8 of each species and included a linker ( bases A , T and a NotI restriction site ) appended to the 5′ end of each upstream primer and a linker ( bases A , T and an AscI restriction site ) appended to the 5′ end of each downstream primer . IAB5 Primers used: D . melanogaster and D . simulans: 5′- ATGCGGCCGCTCCACTTCCGAACTTGGTCGAC-3′ , 5′-ATGGCGCGCCCGATTCTGCTGGCCATGACCAT-3′; D . erecta: 5′-ATGCGGCCGCTCCACTTCCGAACTTGGTCGAC-3′ , 5′-ATGGCGCGCCCGATTCCGTTGGCCATGGCCAT-3′; D . yakuba: 5′-ATGCGGCCGCTCCACTTCCGAACTTGGTCGGC-3′ , 5′-ATGGCGCGCCCGATTCCGCTAGCCATGACCAT-3′; D . ananassae: 5′-ATGCGGCCGCTGGAGGAAAAGCGGAAAATGCA-3′ , 5′-ATGGCGCGCCCGATTACGATGGCCATGACCAT-3′; D . pseudoobscura: 5′-ATGCGGCCGCTTCCATAATGAACCCCGCGGAA-3′ , 5′-ATGGCGCGCCTTGTGGCCCTGACAGTGAAGAG-3′; The neighboring 1027 bp genomic region downstream of IAB5 ( relative to the Abd-B gene ) in D . melanogaster ( dIAB5 ) was also amplified using the following primers: 5′-ATGCGGCCGCGGCGTAGTAGTCGACTGACCCA-3′ , 5′-ATGGCGCGCCCGATTGAATGTCGCCATTCGCT-3′ . IAB8 primers used: IAB8 D . melanogaster 5′-ATGCGGCCGCATGGGTTTTATGTATTCATTGG-3′ 5′- ATGGCGCGCCACAAAAGCCAAAAACGCTGCAG-3′ IAB8 D . simulans: 5′- ATGCGGCCGCATGGGATTTTTGTATTCATTGG-3′ 5′- ATGGCGCGCCACAAAAGCCAAAAACGCTGCAG-3′ IAB8 D . pseudoobscura: 5′- ATGCGGCCGCATGCCTTTTATGTATTCATCGG-3′ 5′- ATGGCGCGCCAATTGAAATCGGGAAAGAACTC-3′ The IAB5 and IAB8 genomic regions were inserted in the unique NotI and AscI sites of a previously constructed pEZ vector between the white and eve-lacZ reporter genes [62] ( Figure 3A ) . The same IAB5 D . melanogaster primers were used to amplify the Sab1 and Sab2 mutant IAB5 CRMs from Sab1 and Sab2 mutant lines , respectively . Reporter transgenes were introduced into the Drosophila germ-line using standard methods for P element mediated transformation [66] . Multiple transgenic lines were generated for each construct and at least two independent lines were analyzed by in situ hybridization . Embryos were collected , fixed and hybridized with digoxigenin-labeled lacZ or white probes as previously described [64] . The stock used to sequence the D . melanogaster Sab1 mutation in the IAB5 genomic region was previously described [10] and provided by Bloomington Drosophila Stock Center ( D . melanogaster stock number: 3497 ) . The Sab2 mutation was induced on an Mcp mutant background by Ed Lewis and has not been separated . The Sab2 fly stock was provided by Ian Duncan . The Sab1 mutation is a G to A transition at position 104543 and Sab2 is an A to G transition at position 104541 on D . melanogaster chromosome 3R in the BX-C sequence ( U31961 ) . | The fertilized animal embryo is a mass of uniform cells that becomes a complex , segmented , and highly organized structure of differentiated cells through the process of development . This vital process is controlled by networks of developmental genes interacting with each other on the molecular level . Because these genes are crucial for animal development , they are conserved both in function and at the DNA sequence level in related species . We have examined critical DNA sequence modules which regulate genes that pattern the early embryo in different species of the fruit fly . We found that despite rapid evolution of the DNA sequences , the regulatory sequences from one fruit fly species are able to operate when tested in another fruit fly species . Further analysis reveals that there are sequences within these regulatory DNA modules which are conserved across different species and which are critical for regulatory function . These conserved sequences represent critical binding sites for protein transcription factors . These findings have important implications for our understanding of gene regulation during development and evolution across diverse animal species ranging from the fruit fly to humans . | [
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"... | 2009 | Functional Evolution of cis-Regulatory Modules at a Homeotic Gene in Drosophila |
Acinetobacter baumannii is a common pathogen whose recent resistance to drugs has emerged as a major health problem . Ethanol has been found to increase the virulence of A . baumannii in Dictyostelium discoideum and Caenorhabditis elegans models of infection . To better understand the causes of this effect , we examined the transcriptional profile of A . baumannii grown in the presence or absence of ethanol using RNA-Seq . Using the Illumina/Solexa platform , a total of 43 , 453 , 960 reads ( 35 nt ) were obtained , of which 3 , 596 , 474 mapped uniquely to the genome . Our analysis revealed that ethanol induces the expression of 49 genes that belong to different functional categories . A strong induction was observed for genes encoding metabolic enzymes , indicating that ethanol is efficiently assimilated . In addition , we detected the induction of genes encoding stress proteins , including upsA , hsp90 , groEL and lon as well as permeases , efflux pumps and a secreted phospholipase C . In stationary phase , ethanol strongly induced several genes involved with iron assimilation and a high-affinity phosphate transport system , indicating that A . baumannii makes a better use of the iron and phosphate resources in the medium when ethanol is used as a carbon source . To evaluate the role of phospholipase C ( Plc1 ) in virulence , we generated and analyzed a deletion mutant for plc1 . This strain exhibits a modest , but reproducible , reduction in the cytotoxic effect caused by A . baumannii on epithelial cells , suggesting that phospholipase C is important for virulence . Overall , our results indicate the power of applying RNA-Seq to identify key modulators of bacterial pathogenesis . We suggest that the effect of ethanol on the virulence of A . baumannii is multifactorial and includes a general stress response and other specific components such as phospholipase C .
Acinetobacters are Gram-negative bacteria that belong to the Moraxellaceae family [1] . The members of the Acinetobacter group are metabolically versatile since they can metabolize an important number of compounds such as aliphatic alcohols , some amino acids , decarboxylic and fatty acids , unbranched hydrocarbons , aromatic compounds , mandelate , and n-hexadecane . [2] . Moreover , accumulation of wax esters has been described for various Acinetobacter species [3] . These features have attracted attention toward several species of the genus given their potential use in the chemical industry . Recently , A . baumannii has emerged as an opportunistic pathogen . Nosocomial and community acquired infections are associated with a wide spectrum of clinical manifestations , including pneumonia ( the most frequent pathology associated with this microorganism ) , urinary tract infections , bacteremia and meningitis [4]-[7] . Furthermore , there has been a recent emergence of multidrug-resistant ( MRD ) isolates of A . baumannii strains resistant to a wide range of antimicrobial drugs such as aminopenicillins , ureidopenicillins , cephalosporins , chloramphenicol , and tetracycline [8] , [9] . Indeed , 89% of Acinetobacter strains isolated from patients injured in Iraq and Afghanistan were resistant to at least two major classes of antibiotics [10] , [11] . So far , lipopolysaccharide ( LPS ) [12] , [13] , an outer membrane protein named OmpA [14] , [15] , the pili [16] , and two siderophore mediated iron-acquisition systems [17]–[19] have been proposed as determinants of A . baumannii pathogenicity . It is conceivable that additional elements could be involved in the pathogenesis of this bacterium . The complete genome sequences of several isolates of this species revealed the presence of homologues of virulence genes from other pathogens [20]–[23] . Examples include homologues of luxI and luxR that allow cell-cell communication , genes that encode two-component systems , genes that code for several hydrolytic enzymes , efflux pumps , and genes involved with resistance to antibiotics . However , in most cases , evidence regarding the contribution of each of these elements to Acinetobacter pathogenicity is lacking . It was previously observed , that co incubation of yeast with A . baumannii promotes bacterial growth; the molecule responsible for this effect was shown to be ethanol . It was demonstrated that low concentrations of ethanol not only stimulated A . baumanni growth but also helped the ability of this bacteria to endure salt stress . Furthermore , in the presence of ethanol A . baumannii showed increased pathogenicity towards C . elegans [24] . It was subsequently reported that the increased pathogenicity of ethanol-fed A . baumannii was also observed when D . discoideum was used as a model host [25] . Furthermore , genes associated with A . baumannii virulence were identified by insertional mutagenesis; one of the genes identified by this strategy is homologous to pstC , which encodes a component of the high affinity phosphate transport system [25] . Interestingly , in some pathogenic bacteria the phosphate regulon appears to be part of a network that controls virulence and a particular stress response ( recently reviewed by [26] ) . Another gene identified in the insertional screen was rpoH , which in many species , encodes the sigma factor that is responsible of the transcriptional induction of the genes that mediate the heat-stress response ( HSR ) [27] . The HSR has been shown to be required for full virulence in other pathogenic bacteria [28]–[31] . Thus , the potential contribution of the HSR to the virulence of A . baumannii remains as an attractive possibility . To explore the underlying basis for the increased virulence of A . baumannii in the presence of ethanol , we characterized the transcriptional profile of A . baumannii grown in rich medium in the presence or absence of ethanol . Seventy genes whose expression is altered by the presence of ethanol in the growth medium were identified . Based on our results we suggest that the increased virulence of A . baumannii in the presence of ethanol is due to increased metabolic capacity , coupled with the expression of several key factors mostly related with stress responses that likely contribute to the virulence of this bacterium . In addition , ethanol promotes the expression of plc1 , which encodes an A . baumannii-specific phospholipase C . We found that a plc mutant showed a reduction in A . baumannii-induced cytotoxicity of epithelial cells , suggesting that phospholipase C acts as a virulence factor in this bacterium .
To identify genes important for an inducible virulence response in Acinetobacter , we first search for genes that were differentially expressed in the presence of ethanol . Total RNA was isolated from A . baumannii cells grown to mid-log phase in the absence or presence of ethanol ( see Methods section ) . For the first set of samples , the mRNA was selectively enriched through a single step of rRNA depletion . These samples were fragmented and used to obtain cDNA libraries that were sequenced as described in Methods section . A total of 6 , 441 , 146 and 6 , 603 , 654 28 nt reads were obtained for each library ( “no ethanol” and “ethanol” , respectively ) . Of these , 4 , 364 , 106 , ( no ethanol ) and 4 , 824 , 047 ( ethanol ) reads mapped to multiple targets in the genome and only 312 , 266 ( no ethanol ) and 546 , 498 ( ethanol ) mapped uniquely . Analysis of 1% of the reads that mapped to the genome multiple locations revealed that most were derived from 23S , 16S , and 5S rRNA . In order to obtain a more representative sampling of the coding regions , the libraries were sequenced an additional two times . Additional RNA samples were prepared in duplicate experiments and subjected to three-cycles of rRNA depletion followed by size exclusion to remove small RNAs , but no substantial improvement in the number of unique reads was achieved with this procedure . Combining all of the sequencing from both experiments produced a total of 3 , 596 , 474 unique reads that represent a total of 100 , 701 , 272 nucleotides ( 28 nt per read ) , a 25 . 3 fold average coverage of the A . baumannii genome . The sequences obtained from these experiments were mapped to the A . baumannii genome using the current annotation in Genbank ( accession: CP000521 version CP000521 . 1 ) . As expected , between 72 and 84% of the unique sequences correspond to previously annotated coding regions , whereas the remainder correspond to intercistronic regions , RNA molecules such as the tmRNA , ribonuclease P , 7S RNA , and possible regulatory RNAs , such as the TPP riboswitch . Two previously unannotated genes were also identified . These genes are a putative ferredoxine located downstream of A1S_0845 , and a gene located upstream of A1S_2262 that has sequence similarity to SirA . Two different approaches were used to demonstrate that the number of reads that map to a particular open reading frame correlate with the expression level of that gene . In the first approach , mRNA from two different tissues was analyzed using microarrays and RNA-Seq [32] . In the second one , microarray and RNA-seq data were compared with protein expression data obtained by shotgun mass spectroscopy [33] . In both cases , good levels of correlation were observed . Therefore , we computed the total number of reads for each gene , and this number was divided into windows of 250 bp to calculate the number of relative reads ( NRR ) per window . We observed that the highest NRR mapped to the loci corresponding to the tmRNA and RNase P , followed by the genes A1S_2840 ( NRR 50 , 000 ) , and A1S_2218 ( NRR 41 , 000 ) that encode OmpA ( Outer Membrane Protein A ) , and the pili subunit CsuA/B , respectively . The NRR was also high for genes encoding proteins related to transcription , translation and energy generation . We detected 163 genes with a NRR less than 1 ( Table S1 ) , suggesting that some genes are expressed at a low level or that these are not readily detected because of experimental bias . As shown in Figure 1 , 50% of Acinetobacter genes have NRR values of approximately 150 . Both technical and biological duplicates showed high reproducibility ( Fig . 1 ) . To identify the genes that are induced or repressed by ethanol , we normalized the number of reads for each pair of libraries , and the number of reads for each gene was compared . The genes that reproducibly showed a ratio larger than 1 . 9 or below 0 . 5 in both biological replicates and a P value of 0 . 05 or less were considered as regulated by ethanol . From 101 genes that passed the first criterion , only 70 showed a P-value below 0 . 05 . From these , 21 genes were repressed and 49 were induced by ethanol ( Table 1 ) . We also extracted total RNA from cultures grown to stationary phase in the presence of ethanol and performed a more limited RNA-Seq experiment that produced 146 , 170 unique reads . The NRR for each gene was calculated and arranged by rank order ( Table S2 ) . RNA from stationary phase cells with ethanol exhibited a large number of reads for genes related with the synthesis of siderophores and iron uptake . In fact , in this sample , 33 genes related with iron acquisition are among the 10% of the genes that showed the highest NRR values ( Table S2 ) . Interestingly , a putative operon encoding four proteins similar to the high-affinity phosphate transport system were also found among the 10% of the genes with highest NRR . Given the relevance of Fe and phosphate acquisition to bacterial pathogenesis we further explored the expression of these genes by qRT-PCR or using lacZ as reporter gene ( see below ) . We examined in detail the genes that were induced by growth in the presence of ethanol during exponential phase . The most strongly induced genes encode proteins related to central metabolism or with ethanol/acetate assimilation . These included ethanol dehydrogenase ( A1S_2098 ) and aldehyde dehydrogenase ( A1S_2102 ) , which showed an average induction of 12 . 6 and 13 . 2-fold , respectively . A . baumannii has two other genes that potentially encode a Fe-dependent ethanol dehydrogenase , i . e . , A1S_2053 , and A1S_2702; these genes are transcriptionally active since they showed a NRR of 28 and 194 . However , their expression is not induced by ethanol . Other genes that may encode additional ethanol dehydrogenases are A1S_1788 and A1S_3436 . We observed a slight induction of A1S_1788 by ethanol , but it showed a p-value higher than the selected cutoff ( Table 2 ) . Therefore , under our experimental conditions , A . baumannii seems to be oxidizing ethanol to acetate by the activity of the enzymes encoded by A1S_2098 , A1S_2102 and perhaps A1S_1788 ( Fig . 2 ) . In many bacteria , after conversion to acetate , ethanol is further metabolized into acetyl-CoA and then assimilated through the glyoxylate cycle [34] , [35] . Acetyl-CoA synthesis occurs by the action of ackA and pta ( acetate kinase and phosphate acetyltransferase , respectively ) as has been demonstrated for Corynebacterium glutamicum [36] , [37] or through acs ( acetyl-CoA synthetase ) as has been demonstrated for Escherichia coli [38] , [39] . In these bacteria , ackA and pta are arranged in a bicistronic operon [40] , [41] . In A . baumannii , these genes are contiguous in the chromosome and therefore may be part of a single operon . From our data , we found that the genes coding for pta ( A1S_0481 ) and ackA ( A1S_0482 ) showed a 4 . 4 ( Table 1 ) and 5 . 3 ( Table 2 ) fold induction in the presence of ethanol . The same situation was found for the gene A1S_2148 , which encodes acs which was induced 3 . 4 fold . Both acs and ackA showed a p-value higher than the threshold ( Table 2 ) , but nonetheless , evidence obtained by quantitative RT-PCR corroborated the induction of these two genes by ethanol ( see below ) . Interestingly , A1S_3300 , which encodes an acetate permease , was induced 4 . 6 fold ( Table 1 ) . In E . coli , acetate is excreted into the culture medium during exponential phase when the cells are grown in the presence of a high concentration of acetogenic sugars . However , when the culture begins the transition into stationary phase , acetate assimilation begins . In exponential phase , pyruvate is converted to acetate through the action of ackA and pta , whereas in stationary phase , acetate is assimilated by acs [38] . This does not seem to be the case in A . baumannii , since our results indicate that during exponential phase all these genes are simultaneously expressed . Therefore , a balance between assimilation and excretion may be occurring . In many organisms , acetate is metabolized through the glyoxylate cycle , which in conjunction with other reactions of the citric acid cycle ( TCA ) allows the net synthesis of succinate from two molecules of acetyl-CoA . At the first step of this cycle , acetyl-CoA and oxaloacetate are used to form citrate . Isocitrate is then converted to glyoxylate and succinate , and finally malate is formed from glyoxylate and acetyl-CoA ( Fig . 2 ) . The enzymes that carry out these reactions are citrate synthase , aconitase , isocitrate lyase , and malate synthase [34] , [35] , [42] , [43] . We observed that the genes encoding citrate synthase ( A1S_2710 ) , and malate synthase G ( A1S_1601 ) were induced 2 . 5 and 2 . 7 fold respectively but with a p-value above the threshold ( Table 2 ) . qRT-PCR experiments verified that both genes are indeed induced by ethanol ( see below ) . Therefore , acetate assimilation appears to take place through the glyoxylate cycle in A . baumannii . In E . coli there are two different malate synthases ( i . e . , malate synthase A and G encoded by aceB and glcB , respectively ) [44]–[46] . This latter gene , glcB , codes for a secondary malate synthase that can replace the malate synthase A when aceB is mutated [44] . In contrast , only the malate synthase G is present in A . baumannii , similar to the situation found in C . glutamicum [37] . Unexpectedly , we did not observe an induction of the gene encoding isocitrate lyase ( A1S_1008 ) . This may be due to the presence of glucose in the media we used in these experiments , which may have repressed the expression of the isocitrate lyase gene . This result suggests that under these conditions , control of the isocitrate dehydrogenase by phosphorylation is sufficient for activation of the glyoxylate cycle . In A . baumannii the genes encoding isocitrate lyase , malate synthase and isocitrate kinase are not encoded by the same operon . Therefore , it is conceivable that these genes are differentially regulated . We also detected the induction ( 2 . 5 fold ) of A1S_3449 , a gene encoding a putative phosphoenolpyruvate carboxylase ( PEPCx ) ( Table 1 ) . In other bacteria , this enzyme converts phosphoenolpyruvate to oxaloacetate accomplishing an anaplerotic function ( Fig . 2 ) [47] . Another ethanol-induced enzyme related to the metabolism of acetate is a putative acetyl-CoA hydrolase/transferase , encoded by A1S_3231 . The product of this gene is highly similar to proteins found in other bacteria , and it is 62% similar to Ach1 ( acetyl-CoA hydrolase ) from Saccharomyces cerevisiae . In S . cerevisiae , it has been shown that ach1 is not involved in the hydrolysis of acetyl-CoA , as originally thought . Instead , Ach1 transfers CoASH from succinyl-CoA to acetate , and this activity is required to support growth in acetate [48] . Due to the high similarity between CoA tranferases and hydrolases the actual activity of A1S_3231 in A . baumannii remains to be determined . We detected a two-fold repression of A1S_3025 which encodes a putative malate∶quinone reductase ( MQO ) . A . baumannii , like many other bacteria , possesses two genes that encode for a malate dehydrogenase , a membrane-associated malate∶quinone oxidoreductase ( MQO ) ( A1S_0923 ) , and a cytoplasmic malate dehydrogenase ( MDH ) ( A1S_3025 ) . Our results indicate that the expression level of A1S_3025 did not change in response to ethanol whereas the putative MQO A1S_0923 was down regulated by 50% . Given that MQO is repressed , MDH should be the main enzyme responsible for malate oxidation in this condition ( Fig . 2 ) . Similarly , MQO does not seem to play a significant role in malate oxidation in E . coli [49] , but for C . glutamicum it has been shown that the malate∶quinone reductase ( MQO ) is the main enzyme catalyzing the oxidation of malate to oxalacetate [50] . A 2-fold reduction was also observed for A1S_1334 encoding L-serine deaminase . The reaction catalyzed by this enzyme yields pyruvate and ammonia . It is possible that this reduction helps prevent a further increase in the availability of acetyl-CoA above the level that ethanol catabolism produces . Overall these results indicate that a variety of metabolic genes are affected by the presence of ethanol and show for the first time the metabolic pathways involved in ethanol assimilation in this bacterium . In exponential phase , ethanol elicits the induction of 11 genes that encode hypothetical proteins that do not belong to any pfam or COG already described ( Table 1 ) . Five of these genes are unique to A . baumannii ATCC17978 , and three of them are located in pathogenicity island 4 [20] . Of the remaining six , A1S_2195 is only present in organisms that belong to the Acinetobacter genus , and the other five have homologues in many other bacteria ( Table 1 ) . Of particular interest , A1S_2509 is present only in A . baumannii ATCC17978 and the non-pathogenic A . baylyi ADP1 . The proteins encoded by these organisms are 40% identical; the first 50 residues of this protein showed high similarity with DjlC ( DnaJ- containing domain protein ) from E . coli and its homologues in other bacteria [28] . Interestingly , A1S_2509 is adjacent to a gene encoding an HSP70-like protein , and this arrangement is conserved among several bacteria [51] . It has been shown that DjlC produces a 10-fold activation of the ATPase activity of the HSP70-like protein [52] , and it was proposed that DjlC and HSP70-like were required to respond to certain stress conditions . Therefore , it is possible that A1S_2509 may help to resist the ethanol stress together with A1S_2510 ( HSP70-like ) . Consistent with this hypothesis , we observed that A1S_2510 ( HSP70-like ) is mildly induced by ethanol ( 1 . 4 fold , p-value 0 . 006 ) ( data not shown ) . The A1S_1641 gene , which encodes a fatty acid desaturase , was induced 2 . 2 fold ( Table 1 ) . In other microorganisms , it has been shown that an increase in the amount of unsaturated fatty acids facilitates adaptation to stressful conditions such as acid pH , ionic stress and ethanol [53]–[56] . Other genes induced by ethanol are A1S_1750 and A1S_1752 , that likely are part of an operon and encode for an RND-type efflux pump that confers resistance to various antibiotics in A . baumannii BM4454 [57] . Interestingly , it has been shown that an RND efflux pump contributes to drug resistance and virulence of Francisella tularensis in mice [58] . We also observed the induction of A1S_1950 , which encodes a protein that belongs to the universal stress protein family . It is known that members of this family are induced when the cell is exposed to agents that induce stress [59]–[61] . Interestingly , A . baumannii has five proteins that belong to this family A1S_1950 , A1S_2692 , A1S_2072 , A1S_0214 and A1S_1246 , but only A1S_1950 was induced by ethanol . Recently , it was shown that overexpression of rpoH in E . coli , induces a set of genes that were not originally considered as a part of the heat-shock response ( HSR ) ; acpD is one of these genes [62] . The physiological role of AcpD is still uncertain since its original assignment was as an ACP-phosphohydrolase . AcpD was subsequently shown to be an azoreductase [63] . The induction of acpD ( A1S_1354 ) by ethanol supports the idea that this gene is part of a stress response . A reduction of two-fold was detected for a cluster of five genes that could form an operon from A1S_1266 to A1S_1270; unfortunately , the function of these genes is unknown . One of the aims of this work was to identify potential virulence factors whose expression is induced in presence of ethanol . In this regard , two general traits were observed . First , there was the mild induction of Hsp90 , GroEL , and Lon . In many bacterial species , these genes are part of the heat-shock stress response ( HSR ) [64]–[69] . Second , several genes known to be important for survival under diverse stress conditions exhibited increased expression ( Table 1 ) . Members of the HSR are chaperones that refold or prevent aggregation of misfolded proteins [27] , [70] , and Lon is a protease that hydrolyzes proteins with unstructured regions [71] . In many bacteria , the control of the HSR is mediated by the sigma factor σ32 , encoded by the rpoH gene [27] . It has been shown that the HSR is required for full virulence in some pathogenic bacteria . For instance , DnaJ-like ( HSP40 ) from Vibrio tapetis is required for cytotoxicity of hemocytes [28] , σ32 is required for the invasion of epithelial cells by Neisseria gonorrhoeae [29] and the chaperons HSP90 and GroEL of many pathogenic bacteria induce the production of interleukin-8 , modulating the immune response [30] , [31] , [72] . Consistent with these reports , a strain of A . baumannii carrying a transposon insertion in the gene encoding for σ32 ( rpoH ) was shown previously to be avirulent in the presence of ethanol towards C . elegans and D . discoideum [20] . Therefore , it is conceivable that ethanol could exacerbate the virulence of A . baumannii through the induction of heat-shock proteins , such as Hsp90 , GroEL and Lon . The products of other genes listed in Table 1 may also help A . baumannii to tolerate stress conditions . Since it has been shown that one stress response might help bacteria to contend with other stress conditions [73]–[76] , it is attractive to hypothesize that ethanol could improve the ability of A . baumannii to survive in the host since that several pathways of stress responses are activated . Among the genes that we detected as induced by ethanol ( Table 1 ) , A1S_0043 encoding a phospholipase C deserves particular attention . This protein has been recognized as a virulence factor in other pathogenic bacteria [77]–[79] . For this reason , we further analyzed this gene as described below . To validate the induction of some of the genes identified by RNA-Seq ( Table 1 ) , we carried out qRT-PCR experiments . The expression of A1S_2664 , A1S_0294 , and A1S_0043 that encode for GroEL , HSP90 and phospholipase C , respectively , was measured , along with several genes whose expression was induced by ethanol but showed a p-value above the threshold ( Table 2 ) . These latter genes were A1S_0482 , A1S_2148 , A1S_2710 , and A1S_1601 which encode acetate kinase , acetyl_CoA synthetase , citrate synthase , and malate dehydrogenase G , respectively . Ethanol dehydrogenase ( A1S_2098 ) was used as a positive control . The down-regulated gene A1S_1266 was also included in this analysis . A1S_2846 and A1S_0880 were used as internal controls to calculate the fold-change after treatment with ethanol ( see methods section ) . To test the expression of the genes above mentioned , we used total RNA isolated from exponential cultures of A . baumannii grown in the absence or presence of ethanol . As shown in Fig . 3A , qRT-PCR experiments confirmed that the expression of all these genes was regulated by ethanol . Moreover , the fold change detected for each gene was similar to the ratio of induction and repression observed by RNA-Seq ( Fig . 3B ) . These results support the conclusions outlined in the previous section regarding ethanol metabolism . To validate the high expression level of the genes detected in the samples obtained from stationary phase cultures grown in the presence of ethanol , we also measured the expression levels of A1S_2381 , A1S_2566 , and A1S_2578 by qRT-PCR . These genes were randomly chosen among the genes that are related to Fe uptake and showed a high number of reads ( NRR ) ( Table S2 ) . A1S_2381 is required for acinetobactin synthesis and is located within a locus of 13 genes that are involved in the synthesis and transport of acinetobactin in A . baumannii ATCC19606 and A . baumannii ATCC17978 . In contrast , A1S_2566 and A1S_2578 ( encoding a protein required for siderophore synthesis and a siderophore receptor , respectively ) are part of a second locus for Fe acquisition that is present in A . baumannii ATCC17978 but not in A . baumannii ATCC19606 [17]–[19] . To test the expression of these genes , we used total RNA from stationary phase cells that were grown in the presence or absence of ethanol ( see methods ) . As shown in Fig . 3B , the expression of these genes was induced by the presence of ethanol in the culture medium , although this effect could be indirect given that a higher O . D . 600 is reached when ethanol is included in the culture medium [24] ( see panel C in Figure 3 ) . We also tested the induction of expression for the genes that belong to the putative pts operon ( A1S_2448 to A1S_2445 ) which encode a high-affinity phosphate transport system . For this study , we used lacZ as reporter gene . The promoter region upstream of A1S_2448 ( homologous to pstS ) was cloned into pMP220 . The amount of β-galactosidase produced by A . baumannii transformed with this construction was low when 10 mM PO4 was included in the culture medium ( Fig . 3C , measures indicated by asterisks ) . The expression of lacZ was evaluated in A . baumannii cells grown in the absence or presence of ethanol at different time points of incubation . As shown in Fig . 3C , a low level of β-galactosidase activity was detected for both cultures at OD600 <3 , but higher activities were observed as the cultures approached stationary phase . At 24 h of incubation , in the presence of ethanol higher amounts of β-galactosidase were detected nevertheless both cultures showed a similar OD indicating that increased β-galactosidase was not due to higher cell numbers ( Fig . 3C ) . To ensure that plasmid integrity was intact through these experiments , we rescued the plasmids from both ethanol treated and untreated cultures at the end of the experiment and found that in each case the plasmid were functional and without detectable rearrangements . Thus , these results indicate that the high-affinity phosphate transport system of A . baumannii is highly expressed at high cell densities and that A1S_2448 is induced after incubation with ethanol . The induction of the transport genes A1S_2448-45 is of particular significance since it has been demonstrated previously that a strain of A . baumannii carrying an insertion in A1S_2447 ( homologue of ptsC ) was avirulent towards C . elegans and D . discoideum [20] . Therefore , it is conceivable that ethanol could exacerbate the virulence of A . baumannii taking advantage of the induction of these uptake systems ( Fe and phosphate ) that in other bacteria have also been related with virulence [26] . It has been reported that community-acquired Acinetobacter infections are associated with underlying conditions such as alcoholism , smoking , chronic obstructive pulmonary disease and diabetes [80]–[82] . Our results provide mechanistic insight into how ethanol may modulate A . baumannii infections . Furthermore , the molecular mechanism underlying this effect could be multifactorial , given that ethanol up regulates TLR2 causing inflammation of the airway epithelium [83] . Ethanol also induces a delay of viability loss in stationary-phase cultures of bacteria [84] , and we demonstrate that ethanol induces a stress response that may give the pathogen a better fitness to survive in the host . One of the genes that was induced by ethanol encoded a phospholipase C ( plc; A1S_0043 ) . A . baumannii has another gene encoding a phospholipase C ( A1S_2055 ) . Both genes are absent in the non-pathogenic A . baylyi ADP1 but present in other strains of A . baumannii that have been sequenced [23] . The proteins encoded by A1S_0043 and A1S_2055 , show a similarity of 72% , and both are highly similar ( 75% similarity ) to the phospholipases reported for Burkholderia pseudomallei . As is the case for phospholipase C proteins in other bacteria [85] , [86] , the N-terminal region contains the conserved residues that are recognized by the twin-arginine secretion system; therefore both phospholipases may be secreted . In addition , from the gene arrangement it can be proposed that A1S_0043 is expressed as a monocistronic mRNA since no other coding region is predicted to be located in the adjacent 404 bp downstream A1S_0043 , and the upstream ORF , A1S_3479 , is transcribed in opposite direction . To evaluate the contribution of the phospholipase C ( encoded by A1S_0043 , from here on referred to as plc1 ) to A . baumannii virulence , we isolated a mutant strain carrying the insertion of a kanamycin cassette in the coding region of plc1 ( see methods ) . This mutant strain did not show any apparent growth defects upon growth in liquid medium ( data not shown ) . The ability of this strain to produce cellular damage on a monolayer of epithelial cells was tested as described below . Incubating a monolayer of epithelial cells in the presence of A . baumannii has been reported to elicit several morphological and physiological changes , such as loss of viability as revealed by trypan blue staining , detachment from the culture plate , and a general shrinking of the cells [14] , [87] . Consistent with these reports we found that after infection , FaDu epithelial cells became permeable to trypan blue indicating that A . baumannii compromises the membrane permeability . Furthermore , after 18 h of infection we observed extensive detachment of the cell monolayer and cellular death in many of the remaining cells ( Fig . 4B and C; stained non-infected controls are shown in Fig . S1 ) . It has been shown that the intracellular enzyme lactate dehydrogenase ( LDH ) is released into the culture medium after any insult that compromises the integrity of the plasma membrane . Therefore , we assessed cell damage by measuring LDH release upon infection with A . baumannii . For this assay , a monolayer of FaDu cells was infected with A . baumannii and the amount of LDH released was measured after 22 h of incubation . The amount of damage produced by the different strains was estimated as percent of the amount LDH released when the cells were infected with wild-type A . baumannii . As shown in Fig . 4D , only live bacteria triggered LDH release indicating that cell damage is a consequence of the bacterial infection . Using this assay , the cytotoxic effect produced by the strain carrying the plc1Δ::kan allele was determined . A reduction in the amount of LDH released into the culture medium upon infection with this strain was observed ( Fig . 4D ) . To further validate this result an infection was carried out with either the wild-type or the plc1 mutant transformed with pWH1266-Gm ( empty vector ) and pWH1266-Gm containing the plc1 gene , respectively . Cells infected with wild-type and plc mutant strain containing the plc1+ gene released a similar amount of LDH ( Fig . 4D ) , indicating that phospholipase C contributes to cause cellular damage . Bacteria recovered from the infection plate were used to confirm that the complementing plasmid was stably maintained without detectable rearrangements ( data not shown ) . Phospholipase C has been reported as a virulence factor in many bacteria , such as Pseudomonas aeruginosa , Legionella monocytogenes and in the Gram-positive bacteria Clostridium perfringens [77] , [88] . P . aeruginosa has an acidic phospholipase that shows strong hemolytic activity , and contributes to its ability to cause cellular damage [89] . Recently it has been shown that L . monocytogenes uses a phosphatidylinositol-specific phospholipase C to escape efficiently from the phagosome in macrophages [79] , [90] , and it also has a phosphatidylcholine-prefering phospholipase C that is involved in the escape from the phagosome in epithelial cells [91] , [92] . B . pseudomallei has two phospholipases C that hydrolyze phosphatidylcholine and sphingomyelin and neither is hemolytic for human erythrocytes . However , it was reported that Plc-2 has a significant role in the virulence of this pathogen towards HeLa cells , whereas Plc-1 seems to have a minor one [78] . Thus , our results demonstrating that A . baumannii phospholipase C is important for virulence is consistent with finding with several other organisms . Overall our results demonstrate a number of important conclusions: First , RNA-Seq provides a comprehensive , detailed overview of the bacterial transcriptome . Even though contaminating rDNA reads can be present in large numbers , large numbers of unique reads can still be obtained by deep sequencing . Second , in A . baumannii , ethanol is efficiently assimilated as a carbon source through the glyoxylate cycle that is a pathway required for full virulence in many pathogens . Third , ethanol induces the expression of many proteins related to stress , including UspA , Hsp90 , GroEL , Lon . Specific stress responses may help bacteria to contend with adverse condition pathogens face during infection . Fourth , ethanol induces the expression of a phospholipase C that contributes to A . baumannii cytotoxicity . Fifth , ethanol promotes the growth of A . baumannii , and presumably during stationary phase the resources of the medium are more efficiently utilized by the induction of the two Fe uptake systems and the high-affinity phosphate transporter system . Thus , overall these studies contribute a wealth of new information into the pathogenic response of Acinetobacter baumannii .
A . baumannii ATCC17978 was grown in YPDA culture medium ( 1% yeast extract , 2% peptone , 2% dextrose , and 0 . 012% adenine sulfate ) at room temperature , or at the temperature indicated . When indicated , 1 . 1% ethanol was added to the culture medium . In this study 1 . 1% ethanol was used instead of 1% ethanol as previously published [20] because 1 . 1% ethanol caused more reproducible effects previous reported on A . baumannii growth . Bacterial strains were also grown in LB . When required , antibiotics were added at the following concentrations: ampicillin ( 100 µg/ml ) , kanamycin ( 50 µg/ml ) , gentamicin ( 20 µg/ml ) , tetracycline ( 10 µg/ml ) . Cloning were performed using the plasmids pCR2 . 1-TOPO ( Invitrogen ) and pUC19R ( Invitrogen ) . pUC4K was used as source of the kanamycin cassette ( GE Healtcare Life Sciences ) . pJQ200 was used as suicide plasmid [93] . pJQ200 confers GmR and carries the sacB gene from Bacillus subtilis to counterselect the presence of the plasmid in the presence of sucrose . This plasmid was also used as a source of the GmR cassette . pWH1266 was used as a shuttle vector for E . coli and A . baumannii [94] . pMP220 was used to construct transcriptional fusions to the promoter-less lacZ [95] . The sequences of the oligonucleotides used in this work are in Table S3 . Chromosomal DNA was obtained using the GenElute Bacterial Genomic DNA kit from Sigma-Aldrich . Plasmids were purified using the plasmid purification kit from Qiagen . DNA was amplified using PrimeStar HS Taq polymerase or LA Taq polymerase ( Takara ) according to the recommendations of the manufacturer . Transformation of E . coli was carried out using CaCl2 competent cells [96] . Electroporation was used to transform A . baumannii cells , following the protocols previously reported [97] . A baumannii cultures were grown to mid-log phase ( OD600 nm = 1 . 8 ) in YPDA or YPDA with 1 . 1% ethanol , at room temperature and shaking of 150 rpm . The cells were collected at 4°C and the RNA was isolated using the RiboPure-Bacteria kit ( Ambion ) according to the manufacturer's instructions . Residual DNA in the samples was removed using DNaseI . The integrity of the RNA was analyzed using an Agilent bioanalyzer ( Agilent technologies ) . The MICROBExpress kit ( Ambion ) was used to remove the 23S and 16S rRNA from the total RNA samples . When indicated , the samples of enriched mRNA were subject to a final step of purification using the Megaclear kit from Ambion . To evaluate the degree of rRNA depletion the samples were analyzed on an Agilent bioanalyzer . The same protocol was used to isolate RNA from A . baumannii cultures from stationary phase . In this case , the cells were collected three hours after the OD600 of the cultures did not show any further increase . The first two libraries ( corresponding to the cultures with or without ethanol ) were obtained using 2 µg of enriched mRNA that was depleted only once with the ribo-minus beads included in the MICROBExpress kit . For the samples corresponding to the biological duplicates , we performed two steps of depletion with ribo-minus beads and an additional purification step using the Megaclear kit . Double-stranded cDNA was obtained using hexameric random primers and the Super-script double-stranded cDNA synthesis kit from Invitrogen . The cDNA was purified using the Qiaquick PCR Purification kit from Qiagen , and subject to a partial digestion with DNaseI in order to obtain a substantial enrichment of fragments between 100 and 300 bp . After digestion , the sample was loaded on a 1 . 2% agarose gel , and the fragments between 100 and 300 bp were purified using the Qiaquick Gel Extraction kit from Qiagen . The ends of the fragments were end-repaired and A-tailed . For this , the End-It kit ( Epicenter ) was used according to the manufacturer's instructions . The repaired cDNA was purified using the Qiaquick PCR purification kit and A-tailed using the Klenow fragment of the DNase polymerase ( NewEngland-BioLabs ) and dATP . The sample was purified and ligated to the genomic adapters provided by Illumina . After ligation , the sample was loaded on a 2% agarose E-gel ( Invitrogen ) , and the fragments between 150 and 350 bp were excised from the gel and purified using the Qiaquick gel extraction kit . A PCR reaction of the gel-purified cDNA was performed in 50 µl using the 1X master mix Phusion-High Fidelity DNA polymerase , and the primers 1 . 1 and 2 . 1 provided by Ilumina . The reaction was amplified with 17 cycles , and the sample loaded on a 1 . 2% agarose gel and the fragments between 150 and 350 bp were excised from the gel and purified . The sample was quantified spectrophotometrically using a nanodrop ( Thermo ) and sequenced in a Genome analyzer II ( Illumina ) . The raw reads of 35 bp were truncated as 28-mers and remapped with the Efficient Local Alignment of Nucleotide Data ( ELAND ) allowing for 1 and 2 nt mismatches . The output file containing only the sequences that mapped once in the genome was further analyzed to ascertain genome coverage and to assign the number of reads per locus ( orf or intercistronic region ) . To identify the genes regulated by ethanol , the libraries were initially compared by pairs; for this , the number of reads for each coding region was determined , the number of total reads was normalized between these libraries and the ratio of reads between ethanol and no ethanol was calculated . The genes that showed a ratio larger than 1 . 9 and lower that 0 . 5 were considered potential candidates . Finally , the number of reads for the four libraries was normalized and the Student's t-test was applied for each gene . Those genes that showed a P-value lower or equal to 0 . 05 were considered as genes regulated by ethanol . To obtain information regarding the level of expression among the genes , we calculate the number of relative reads ( NRR ) per coding region using a window of 250 bp . The RNA was isolated as described in the previous section . As templates for this assay we used the same RNA samples that were used for the synthesis of first Illumina libraries and two additional pair of samples that were independently obtained . The reverse transcription step was carried out using the iScript Select cDNA Synthesis Kit from Bio-Rad , according to the manufacturer's instructions . The primer3 software [98] was used to select primers that would amplify a product of approximately 200 bp . The quantitative real-time PCR assay was performed with SYBR-Green I master mix ( Applied Biosystems ) in a LightCycler 480 system . Reactions were set up according to the manufacturer's instructions , and three technical replicates for each sample were included . The amplification conditions were: 95°C , 5 min ( ramp/rate of 4 . 8°C/s ) , followed by 45 cycles of 95°C 10 sec ( ramp/rate 4 . 8°C/s ) , 55°C 20 sec ( ramp/rate 2 . 5°C/s ) , and 72°C 30 sec ( ramp/rate 4 . 8°C/s ) . The specificity of the reaction was confirmed by obtaining a melting curve from 95 to 55°C and visualizing the amplified product in a 5% polyacrylamide/TAE gel . The absence of product using only RNA in the PCR reaction ( without reverse transcriptase ) was also verified . The Cp value was defined as the cycle in which the fluorescence value was above the background . The efficiency of the amplifications for each pair of primers was determined obtaining a standard curve using serial dilutions of DNA . The efficiency was calculated using the formula E = 10 ( 1/-s ) X100 where s is the slope of the curve . The fold change was calculated using the 2−ΔΔCt ( 2−ΔΔCp ) method [99] . A1S_2846 encoding a putative sulfite reductase was used as internal control . Similar results were obtained if A1S_0880 encoding MinC was used as internal control instead of A1S_2846 . To obtain the A . baumannii mutant strain in the plc1 gene , a fragment of 2579 bp carrying the plc1 gene was amplified by PCR using the oligonucleotides A1S_0043 . 1 and A1S_0043 . 2 and cloned into pCR2 . 1-TOPO plasmid . An internal fragment of 519 bp from the coding region of plc1 was removed by inverse PCR using the oligonucleotides A1S_0043 . A and A1S_0043 . B and substituted with a kanamycin resistance cassette . The DNA fragment carrying the plc1Δ::kan allele was subcloned into pJQ200 . The resultant plasmid was used to electroporate A . baumannii cells . Single recombinants appeared after overnight incubation on LB plates in the presence of gentamicin . Double recombinants were selected plating serial dilutions of different GmR colonies on LB plates with kanamycin and 3% sucrose . The proper replacement was confirmed by PCR . Plasmid pWH1266 ( ApR TcR ) that is stable in A . baumannii was used to carry the plc1 gene . To generate this construct a PCR fragment carrying plc1 ( oligonucleotides A1S_0043 . 1 and A1S_0043 . 2 ) was cloned into pWH1266 using the BamH1 and SalI sites . It has been shown that a gene cloned in these sites is expressed under control of the Tet promoter . The resulting plasmid does not confer any Tc resistance and given that A . baumannii ATCC17978 is ApR , we proceeded to construct the plasmids pWH1266-Kan and pWH1266-Gm , in which a kanamycin or gentamicin resistance cassette was cloned into the EcoRI site of pWH1266 . The gene conferring GmR resistance was obtained by PCR using the oligonucleotides acc3 and acc4 . The gene conferring KanR was obtained by PCR using the oligonucleotides Kanfw1 and Kanrev1 . The plc1 gene was cloned in pWH1266-KanR and pMH266-GmR . As a control the gfp gene was cloned in pWH1266-Kan and introduced to A . baumannii; as expected , green-fluorescent cells were observed . The pMP220/2248p plasmid carrying the transcriptional fusion of lacZ to the control region of A1S_2448 was constructed by cloning a PCR fragment of 913 bp obtained by PCR using the oligonucleotides AB2448up2 and AB2448dw5 . This fragment carries the promoter region located upstream of A1S_2448 . A . baumannii cells carrying pMP220/2248p were grown in YPDA-Tc , or YPDA-Tc supplemented with 1% ethanol , or 10 mM PO4 buffer pH 7 . The cultures were grown aerobically at 30°C and aliquots were assay at different time points . β-galactosidase activity was determined in Chloroform/SDS-permeabilised cells . Hydrolysis of o-nitrophenyl-β-D-galactopyranoside was carried out at 37°C . Activities are expressed in terms of cell density using the formula of Miller [100] . The FaDu cell line originating from a hypopharyngeal carcinoma was obtained from ATCC ( ATCC HTB-43 ) . The cell line was grown under 5% CO2 at 37°C in Eagle's minimum essential medium with Earle's balanced salt solution ( ATCC 30–203 ) supplemented with 10% heat-inactivated fetal bovine serum ( Gibco 16140 ) and 1% of a solution containing penicillin/streptomycin at 10 , 000 U/ml and 10 mg/ml , respectively ( Gibco 15140 ) . The cells were seeded in 12 well-plates and infected when they reached 5×105–7×105 cells per well . Before infection , the monolayer of epithelial cells was carefully washed with PBS , and fresh medium without antibiotics was added . Bacterial strains were grown on plates of LB or LB with the appropriate antibiotic and incubated overnight at 37°C . The next day a suspension of bacterial cells was prepared in PBS , and the OD600 was registered and adjusted ( 2 OD600 nm = 1×109 cells/ml ) . Formaldehyde-fixed bacteria were prepared by incubation of the suspension in 1% formaldehyde for 4 h at 4°C as described [101] . The epithelial cells were infected at an MOI of 100 with no more than 10 µl of bacterial suspension . Mock-infections and infections were done in duplicate . The plates were centrifuged at 1 , 500 rpm for 5 min and then incubated for 22 hrs at 37°C and 5% CO2 . The amount of LDH released into the culture medium was determined according to the manufacturer's instructions ( BioVision Research Products . Mountain View , CA ) . Each set of experiments was performed in triplicate . Bacteria recovered from the infection plate were used to determine the number of colony forming units on plates with and without gentamicin . The restriction pattern of the plasmid obtained from these cells was analyzed by double digestions with EcoRI and SalI or EcoRI and BamHI . | Acinetobacter baumannii has recently emerged as a frequent opportunistic pathogen . In the presence of ethanol A . baumannii increases its pathogenicity towards Dictyostelium discoideum and Caenorhabditis elegans , and community-acquired infections of A . baumannii are associated with alcoholism . Ethanol negatively affects both epithelial cells and alters the bacterial physiology . To explore the underlying basis for the increased virulence of A . baumannii in the presence of ethanol we examined the transcriptional profile of this bacterium using the novel methodology known as RNA-Seq . We show that ethanol induces the expression of a phospholipase C , which contributes to A . baumannii cytotoxicity . We also show that many proteins related to stress were induced and that ethanol is efficiently assimilated as a carbon source leading to induction in stationary phase of two different Fe uptake systems and a phosphate transport system . Interestingly , a previous study showed that a mutant in the high-affinity phosphate uptake system was avirulent . Our work contributes to the understanding of A . baumannii pathogenesis and provides a powerful approach that can be extended to other pathogenic bacteria . | [
"Abstract",
"Introduction",
"Results/Discussion",
"Methods"
] | [
"microbiology/cellular",
"microbiology",
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"pathogenesis",
"genetics",
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"genomics"
] | 2010 | Molecular Mechanisms of Ethanol-Induced Pathogenesis Revealed by RNA-Sequencing |
Bacteria prudently regulate their metabolic phenotypes by sensing the availability of specific nutrients , expressing the required genes for their metabolism , and repressing them after specific metabolites are depleted . It is unclear , however , how genetic networks maintain and transmit phenotypic states between generations under rapidly fluctuating environments . By subjecting bacteria to fluctuating carbon sources ( glucose and lactose ) using microfluidics , we discover two types of non-genetic memory in Escherichia coli and analyze their benefits . First , phenotypic memory conferred by transmission of stable intracellular lac proteins dramatically reduces lag phases under cyclical fluctuations with intermediate timescales ( 1–10 generations ) . Second , response memory , a hysteretic behavior in which gene expression persists after removal of its external inducer , enhances adaptation when environments fluctuate over short timescales ( <1 generation ) . Using a mathematical model we analyze the benefits of memory across environmental fluctuation timescales . We show that memory mechanisms provide an important class of survival strategies in biology that improve long-term fitness under fluctuating environments . These results can be used to understand how organisms adapt to fluctuating levels of nutrients , antibiotics , and other environmental stresses .
Escherichia coli cells grown in the presence of both glucose and lactose first consume glucose , which is more easily metabolized , before expressing the genes necessary for lactose catabolism [1]–[3] . The prioritization of bacterial metabolism toward a specific substrate is achieved by catabolite repression and is often observed in microorganisms grown in the presence of multiple carbon sources [4] . Metabolite selection usually favors more accessible energy sources when multiple substrates are available [5] . Since transitions between metabolic phenotypes incur a significant growth rate cost , microorganisms are faced with a fitness optimization problem in temporally fluctuating environments [6] . For instance , a premature commitment to new metabolic substrates initially present in low quantities may limit long-term fitness if levels remain insufficient to support growth . Similarly , a delayed phenotypic switch may reduce overall nutrient intake and , as a result , cells may be outcompeted by populations with a more timely response . Recently , simple laws that relate bacterial growth , translational efficiency , and metabolic rates have been revealed through a combination of theory and experiments [7] . These laws , which hold for bacteria growing in constant environments ( e . g . in chemostats ) , can be used to predict key features of bacterial adaptation , including fitness landscapes of drug resistance [8] . In fluctuating environments , however , little quantitative data exists on the physiological strategies that bacteria use to optimize growth . When environments fluctuate , steady-state growth may not be achieved in any given environment , and long-term growth rates must be measured across multiple fluctuations over longer timescales . Experimentally , this presents challenges that are currently being addressed using microfluidics and microscopy , e . g . yeast have been grown in alternating sugars [9] , while bacteria have been exposed to single step changes of carbon source [10] . Here , we present experiments in bacteria over longer timescales , during which many back-and-forth nutrient fluctuations are made while continuously measuring cellular growth . In particular , we probe gene regulatory networks using an innovative microfluidics device over timescales that have not previously been examined and discover that memory-based bacterial growth strategies constitute a primary mode of adaptation . Memory in bacteria has been studied in the context of epigenetic switches [11] , which can maintain stable phenotypic states over hundreds of generations . It was recently demonstrated that cell fate decisions in Bacillus subtilis employ memory in the transition between sessile chaining and motility [12] . More broadly , historical growth conditions are known to alter several bacterial responses [13] , implying that memory may be present in multiple cellular processes . Indeed , the presence of feedback loops , coupled with a tuning of gene expression levels , can introduce hysteresis and memory in genetic networks [14] . Despite these observations , very little is known regarding how memory influences growth rates and , more importantly , the recovery from sudden environmental changes . Moreover , along with prudent gene regulation , bacteria employ an additional fail-safe known as the stringent response , which is useful in case carbon starvation persists and cell viability becomes compromised . Coordinated by the signaling molecule ( p ) ppGpp , which accumulates under either amino-acid depletion or carbon starvation [15]–[17] , the resulting protective state exhibits growth arrest , lowered translational and metabolic activity [18] , and expression of biosynthetic genes [19] . Cellular memory of historical phenotypes could impart a key advantage in a changing environment by alleviating the cost of frequent regulatory switches , as well as mitigating the stringent response , while allowing cells to adapt to multiple environments . This possibility , while beneficial in theory [20] , has not been tested or quantified experimentally . We investigate memory-based adaptive mechanisms by asking whether bacterial cells grown in fluctuating environments would either adopt a mixed phenotype and remember adaption to both environments , avoid metabolic switching altogether and lock into a single phenotype , or fail to fully adapt to either environment and remain in a partially adapted state . We developed a microfluidic device that maintains growing bacterial populations inside microscopic growth chambers ( GCs ) to study phenotypic changes that occur in E . coli in response to sudden environmental changes ( see Fig . 1a for schematic representations of the device ) . Our microfluidic device shares certain properties with a chemostat – namely the maintenance of a constant population size and a steady influx of fresh nutrients . However , while a chemostat maintains a static chemical environment , the small volume of our device allows the chemical environment to be changed very rapidly ( Fig . S1 and Text S1 ) . Since the chemical environment is not stable but rather in constant flux , we call our device a chemoflux . Its design builds on previous ones used to study bacterial aging [21] , yeast fitness under a changing environment [9] , or to characterize growth of mycobacterial cells [22] .
The growth rate of E . coli cells is quantified using the lateral displacement of cells 10 to 15 microns away from the end of the growth chambers ( Fig 1b , see Materials and Methods section for further details ) . As we changed the media flowing in the main channel from MOPS minimal media ( MMM ) supplemented with 0 . 4% glucose to MMM+0 . 4% lactose , a lag phase , manifested as vanishing lateral movement , occurred immediately following the environmental change ( Fig . 2a and Supp . Video S2 ) and lasted approximately 35 minutes . Following the lag phase , cells entered a recovery phase and progressively resumed growth as the lateral speed reached a stable rate 55 minutes after the glucose-to-lactose transition . The measured durations of the lag+recovery phases in our device are in agreement with bulk measurements of diauxic shifts , where transitions between glucose- and lactose-consuming phenotypes occur within an hour on average [23] . On the other hand , lactose-to-glucose transitions do not impose a significant metabolic burden on the cells and cellular growth recovered within 5 minutes ( Fig . 2a , inset ) . The determinants of lag and recovery phases are analyzed in the next section of Results . To investigate whether lac induction is remembered after the removal of lactose , we monitored the growth dynamics of cells in an environment where MMM+0 . 4% glucose and MMM+0 . 4% lactose conditions alternate every 4 hours ( here , we define as the environmental duration ) . In Fig . 2b , cells were subjected to three consecutive glucose/lactose cycles: the first glucose-to-lactose transition resulted in significant lag+recovery phases , but cells were able to grow on lactose without having to go through a lag phase when we reintroduced lactose at and . The response to glucose/lactose transitions eventually became seamless , indicating that cells conserved the ability to metabolize lactose through the 4-hour exposures to glucose . Cells grown under cyclical glucose/lactose conditions thus displayed phenotypic memory of their previous metabolic adaptation . We determined the timescale over which phenotypic memory persists by analyzing the dependence of the lag phase on the time since the last exposure to lactose . Fully induced lac cells , grown in lactose conditions for 4 h , were exposed to MMM+0 . 4% glucose for a time , and then switched to a MMM+0 . 4% lactose environment . The growth rate of the population following the glucose/lactose transition was used to determine the duration of the lag and recovery phases ( Fig . S3 ) . The duration of the lag+recovery phases was measured when is 4h , 5 . 5h , 7h , 9h or 12h , or when cells are grown without ever being exposed to lactose ( ) . Fig . 2c shows that lac-induced cells retained their ability to grow on lactose for , and went through a progressively longer lag phase as increased . To identify the proteins that confer phenotypic memory in the lac operon ( LacZ , LacY or LacA ) , we measured the duration of the lag+recovery phases for cells that constitutively express one of the three lac operon genes . Each gene is driven by the Ptet promoter ( Fig . 3a ) and details about the over-expression constructs ( pZA31-lacZ , pZA31-lacY and pZA31-lacA in Fig . 3b–d ) are included in the Materials and Methods section . The duration of the lag+recovery phases for pZA31-lacZ cells , which over-expressed the β-galactosidase enzyme , was less than 10 minutes ( Fig . 3b ) , while the lag+recovery phases of pZA31-lacY cells , which over-expressed the lactose permease , lasted approximately 40 minutes ( Fig . 3c ) . Over-expression of lacA , the thiogalactoside transacetylase , introduced additional variability in the cellular response between populations and the lag+recovery phases typically lasted longer than 60 minutes ( Fig . 3d ) , ruling out LacA's role in phenotypic memory . These results indicate that high levels of LacZ , and to a lesser extent LacY , are sufficient to maintain cells in an induced state . Since LacZ and LacY have very low degradation rates ( respectively and [24] , [25] ) the main factor that decreases internal levels of lac proteins is dilution due to cell growth . For comparison , we note that the generation time – the time for the population to double in size – in minimal medium is approximately 60 minutes ( see [26] , Text S1 , and Fig . S2 ) . The maintenance of phenotypic memory should therefore be limited by the number of residual proteins transmitted between the mother and daughter cell during cell division , and phenotypic memory may have an intrinsic lifetime which is tied to the minimal lac protein concentration necessary to maintain cells in an induced state . To confirm this hypothesis , we next measured the in vivo lac protein dynamics during lactose/glucose fluctuations using a strain expressing functional LacY-Venus fusion molecules [27] . In Fig . 3e , when lactose and glucose alternated with an environmental duration , the LacY-Venus permease density decayed to its baseline level with a half-life of 60 minutes , confirming that Lac levels decreased mainly through dilution by growth . Following the reintroduction of lactose , LacY production resumed after a 25 minute lag and reached its half-maximal value in 21 minutes . When was decreased to 90 minutes , expression of the lac operon was modulated by the environmental fluctuations but did not decay to zero ( Fig . 3f ) and cells maintained a residual intracellular lac protein level in the absence of lactose . In Fig . 2c , the duration of the lag+recovery phases converged toward the value when 12 hours or more separated lactose exposures . This suggests that the level of lac proteins transmitted upon cell divisions was insufficient to maintain cells in a fully or partially induced lac state after 10–12 generations . Furthermore , the observation that the same population subjected to many glucose/lactose fluctuations still underwent a lag phase when lactose was removed for more than 4 hours indicates that memory of lactose adaptation does not result from the evolution and fixation of constitutive mutants within the population . We analyzed the determinants of lag and recovery phases by exposing uninduced cells to faster fluctuations with an environmental duration T = 10 or 30 minutes , which is significantly shorter than the 55 minutes required for full adaptation in constant lactose . For ( Fig . 4a ) , only the first exposure to lactose resulted in cessation of growth; when lactose was reintroduced after 60 minutes , no lag phase was present and cells were fully able to grow under lactose conditions . We observed the same behavior in Fig . 4b for , where the lag phase still lasted as long as but growth started to recover under glucose conditions and continued to increase through the second exposure to lactose . Cells growing in a rapidly fluctuating environment , T = 10 and 30 minutes , were able to grow optimally after only 20 and 30 minutes of lactose exposure respectively , compared to 55 minutes for constant lactose ( Fig . 4c ) . These experiments yield two key observations . First , the total time to adapt to lactose is shorter when glucose alternates with lactose during the adaptation process . Second , during the glucose exposures ( Figs . 4a , 30–60 min; 4b , 10–20 min ) , cells are able to resume growth but at a reduced rate . We therefore hypothesized that the lag phase is due to two major barriers that must be crossed before cells can resume normal growth: ( A ) initiation of lac protein production , and ( B ) recovery from the stringent response caused by carbon starvation [15] , [28] . Barrier A consists of de-repression of the lac operon , lac transcript production , and translation of the first functional LacZ and LacY molecules , which enable subsequent positive feedback . Since these initial events occur in series once the lac operon is stochastically de-repressed [27] , there exists a certain minimum time to cross the first barrier . In contrast , recovery from the stringent response is only complete once the accumulated ( p ) ppGpp has decreased to its basal level – barrier B therefore gets longer the more time cells spend without glucose [28] . To test this hypothesis , we attempted to reduce barrier A by starting with a small amount of lac protein initially , but not enough to completely eliminate the lag . From Fig . 2c , we know that cells avoid going through a lag phase when grown for up to 4 hours in glucose , i . e . about 4 cell divisions , hence their lac proteins are more than induced; we infer that lac levels are sufficiently high to prevent stringent response during lactose exposures once cells have crossed this threshold . We grew lac-induced cells under glucose conditions for 8 hours ( ) , which diluted their lac proteins to of their maximal level , before beginning rapid lactose-glucose fluctuations . The measured duration of the lag+recovery phase for pre-induced cells was approximately 25 minutes ( Fig . 4d , top panel ) , in agreement with the lag times shown in Fig . 2c , confirming that the lag phase was reduced but not eliminated . When the pre-induced cells were exposed to 5 , 10 or 15 minute fluctuating conditions , they experienced a lag phase only during the first lactose exposure ( Fig . 4d ) , and immediately recovered their ability to fully grow on both glucose and lactose . We plot the lag+recovery times across different fluctuation regimes spanning environmental durations T = 3–60 minutes in Fig . 4e . We observed that for rapid fluctuations ( ) the total adaptation time was approximately equal to the duration of the lactose exposure ( red line in Fig . 4e ) . This indicates that we have minimized barrier A ( which normally takes a fixed amount of time ) , and we are mainly seeing barrier B ( which is proportional to the duration of carbon stress ) . For , cells are able to resume normal growth in lactose hence barrier B is crossed before the glucose exposure . Our biological model makes several predictions , which are confirmed in the following section through direct measurements of cytoplasmic lac levels . First , Fig . 4d shows that for cells do not cross the barrier B threshold ( induction ) during the initial lactose exposure , but are able to cross it during the glucose exposure; while the cells must be able to maintain their metabolic state using phenotypic memory , the very rapid adaptation suggests that cells may also continue adapting to lactose during the glucose exposures . Second , the initiation of lac protein production – barrier A – is a process with a fixed timescale that does not depend on the duration of carbon stress . Third , once barrier A is crossed , barrier B can be crossed in as little as 3 minutes ( Fig . 4e , ) . We test these predictions in the next section by using a LacY fluorescent protein fusion to measure the dynamics of lac induction and we further elaborate on this simple biological model of the lag phases in the Discussion . To reproduce the conditions of Fig . 4 , we measured the changes in LacY-Venus protein levels in response to short ( 10–60 min ) lactose exposures . Subjecting cells to a single pulse of lactose – instead of cyclical fluctuations – ensured that induction dynamics were measured independently of other effects , such as starvation and the stringent response , which may be compounded by multiple glucose-to-lactose transitions . In Fig . 5a , we observed continued production of lac proteins after each lactose pulse: LacY-Venus levels continued to rise in the absence of lactose and started to decrease approximately 40 minutes after lactose was removed from the environment . These results confirm our conclusion , based on growth measurements in Fig . 4 , that lac induction continues during the glucose environments following lactose . We term this behavior response memory: the ability of a regulatory network to continue to respond after the stimulus has been removed . Hysteresis and expression delays are to be expected in multi-level gene regulatory circuits , and in the particular case of lac regulation these delays can involve the kinetics of mRNA degradation [29] , repressor re-binding [30] , [31] , catabolite repression mediated by cAMP [32] , and dynamics of allolactose , the intracellular inducer of the lac operon [33] . We therefore characterized the relative contributions of these effects to the observed response memory . First , the ability to detect in vivo changes in lac protein levels is set by the maturation time of LacY-Venus ( both folding and chromophore formation , measured to last less than 7 minutes in vivo [34] ) , which introduces a delay between observed and actual protein levels . To accurately measure the delay associated with the LacY-Venus protein maturation , we analyzed the LacY-Venus fluorescence levels when glucose and lactose environments alternate with an environmental duration of 90 minutes and measured the phase difference between the environment and the LacY-Venus levels . Since no lag phase is observed for cells under 90 minutes glucose/lactose fluctuations ( Fig . 2c ) , reporter delays do not result from temporary carbon starvation or decreased protein production during a lag phase , and are due solely to the reporter maturation time . The average delay measured under these experimental conditions is 13 . 8 minutes ( Fig . 5b ) , which is an upper bound on the LacY-Venus maturation time since it includes both maturation time and protein production time . The observed peak at 40 minutes in Fig . 5a is therefore only partially accounted for by reporter delay . We carried out experiments in which cells grown in MMM+ glucose were subjected to a 60 minutes pulse of MMM+ glucose+1 mM of the unmetabolizable inducer IPTG , which yielded identical results to the induction by lactose ( Fig . 5c ) . In contrast to induction using lactose , which requires LacZ activity to produce the inducer allolactose , IPTG induces the lac operon directly . Moreover , while cells under glucose/lactose fluctuations experience fluctuating levels of glucose-mediated catabolite repression , constant glucose levels in the IPTG experiments eliminate this effect . Hence , we see that neither lactose/allolactose metabolism nor changes in catabolite repression are required for the observed overshoot . Furthermore , this experiment shows that the stringent response caused by carbon starvation does not significantly affect the induction dynamics . We next tested whether residual intracellular inducer could account for the observed response memory , by using 2-nitrophenyl β-D-fucopyranoside ( ONPF ) , an anti-inducer molecule that competitively binds LacI , excludes IPTG , and increases LacI's affinity for its operator site . In Fig . 5c , cells grown in the presence or absence of 1 mM ONPF exhibited nearly identical induction profiles under IPTG ( minutes ) . However , they exhibited significantly different response memory profiles when the inducer was removed at minutes: lac expression in the presence of ONPF started to decrease 20 minutes after IPTG removal , compared to the 40 minutes measured in the absence of ONPF . Residual intracellular LacI-bound inducer could therefore account for at least 20 minutes of sustained response in the IPTG/glucose and lactose/glucose experiments . The remaining 6 minutes of response memory , not accounted for by reporter delay , can be explained by the measured time for LacI to fully rebind lac operator sites in the presence of ONPF ( min , [30] , [31] ) as well as the lifetime of lac mRNA ( min , [29] ) . These in vivo measurements support our predictions above based on the growth rate dynamics . First , we found that response memory enables cells to continue responding to lactose through the glucose exposures . Second , we showed in Fig . 5c that the initiation of lac protein production is a process with a fixed time that does not depend on the duration of carbon stress . We note that because our experiment is not designed for single-molecule sensitivity , we cannot measure the initiation events themselves . However , we clearly see that cells cross our detection threshold at approximately the same time when induced with IPTG in glucose ( i . e . without any carbon stress ) or with lactose under carbon stress . Third , we measured the post-initiation rate constant for lac protein production to be . This implies that post-initiation the time to increase lac induction levels to would be approximately minutes , which is consistent with our prediction that barrier B can be crossed in as little as 3 minutes . While the major determinants of the lag phase were found to be the initial induction steps and the recovery from stringent response , the potential fitness gains that cells might reap from response memory remained unclear . To better quantify the fitness advantage of response memory in the lac operon , we adapted the established metabolic model described in [35] to fluctuating environments ( see Materials and Methods ) . We focused exclusively on the observed memory effects and their impact on metabolic activity , and did not model the stringent response since it did not significantly affect the induction dynamics ( Fig . 5c ) . The model explicitly accounts for intracellular concentrations of lactose , allolactose , lac operon mRNA , and lac proteins , and captures several features we observed in experiments . For example , in response to a single pulse of extracellular inducer , protein levels can continue to increase after the stimulus is removed , causing an overshoot , if sufficient mRNA and intracellular inducer levels are maintained ( Fig . 6a ) . Likewise , the model exhibits phenotypic memory consistent with our observations . Fig . 6b shows the minimum and maximum lac protein levels at equilibrium as a function of the environmental duration in units of generation time ( measured in the bulk in [26] to be 60 minutes in MMM+glucose ) . Since response memory can be explained by the LacI-mediated repression kinetics ( Fig . 5c ) , and given that the timescales for LacI rebinding to the operator have been measured to be only a few minutes [30] , [31] , our data suggest that there is sufficient residual allolactose inside the cell for sustained expression . We used the model to test this conclusion by artificially reducing the allolactose degradation rate to zero during glucose environments . We obtained similar results across a range of slower but non-zero degradation rates . We show in Fig . 6c the lac protein levels predicted by solving the model with ( solid line ) and without ( dotted line ) residual inducer , the latter yielding the response memory behavior in which cells continue adapting through the glucose exposures . The predicted dynamics closely follow the measured lac levels obtained from minutes IPTG induction ( cyan line ) . The highlighted regions in Fig . 6c correspond to excess metabolic activity , which we compute by integrating the total amount of lactose consumed over a full glucose/lactose cycle at equilibrium ( ) . We find that cells with response memory exhibit an increased capability to metabolize lactose following short exposures to lactose and , if the fluctuating conditions were to persist , are able to hydrolyze up to 100% more lactose when the environment fluctuates faster than the typical generation time ( generations , Fig . 6d ) . The modeling results support a picture in which response memory provides a large adaptive advantage when external fluctuations occur faster than the cell division time , while phenotypic memory is beneficial for slower fluctuations , spanning several generations .
We have presented two distinct memory mechanisms in the lac operon of E . coli , phenotypic and response memory , each of which is beneficial over different timescales . Phenotypic memory allows cells to maintain an adapted state for multiple generations after a specific carbon source is removed from the environment . Since phenotypic memory operates through the transmission of stable cytoplasmic proteins , it may be employed as a general strategy in other organisms to transmit metabolic information between generations , as observed e . g . in the yeast galactose system [9] , [36] . More generally , the intrinsic mechanism behind phenotypic memory being passive – based on intracellular proteins whose lifetime is longer than a typical generation – similar memory effects are expected to be present for other fluctuations and in other organisms . Adaptation mechanisms that rely on the expression of long-lived permease molecules – e . g . small molecule transport [37] or antibiotic/toxin efflux systems [38] – or the production of enzymatic components whose activity confers a distinct fitness advantage such as sigma factors involved in stress response systems [39] constitute examples of phenotypic memory mechanisms . We used fast fluctuating environments to dissect the determinants of lag phases following a transition from glucose to lactose . Our results suggest a simple biological model of the lag phase in which lac protein activity and the stringent response are mutually inhibitory processes: Lac protein activity in lactose has an inhibitory effect on the stringent response due to glucose production and amino acid synthesis , while the stringent response initially inhibits lac protein production through its global inhibitory effects on translation . To see this , we consider two examples . First , we compare for uninduced and pre-induced cells ( Fig . 4b+d ) . In the pre-induced case , after the first lactose exposure cells rapidly recover full growth in glucose , whereas if no lac proteins are initially available , cells experience a slow recovery in glucose . The stringent response due to the lactose exposure is therefore much less severe when a small amount of LacZ ( induced ) is available to hydrolyze lactose and initiate positive autoregulation . Second , we note that for ( Fig . 4e ) , full adaptation to lactose is achieved by the second lactose exposure , which means that lac protein levels can cross the threshold within 6 minutes total . However , for ( Fig . 4d ) , the cells do not begin growing during the first lactose exposure even though more than minutes have elapsed . We conclude that protein production during the stringent response is too slow to allow cells to cross the threshold during the short lactose exposures for . While cells under fast glucose/lactose fluctuations could in principle become constitutively active and never repress the lac operon , the metabolic cost associated with unnecessary lac expression would incur a significant fitness disadvantage [40] . In particular , if lactose encounters unexpectedly cease , this cost will no longer be temporary , but sustained by the population indefinitely . Cells employing response memory avoid such long-term cost by transiently expressing the required genes for a short amount of time following an initial exposure to the stimulus , with a maximal metabolic cost that is limited by the duration of this transient expression . Should environmental fluctuations cease , cells will suffer only a small , short-term fitness cost . On the other hand , should fast fluctuations persist , as we have shown the cells reap a significant fitness benefit . In particular , we showed that cells reach higher induction levels more rapidly by maintaining their response profile following the removal of an external inducer . Memory in different genetic network architectures could affect not only the cost of gene expression , but also the evolution of gene expression levels . The timescale over which phenotypic memory persists is determined to a large extent by the gene's expression level ( provided the protein is sufficiently stable ) . Expression levels may be evolutionarily tuned not only to support growth in a single environment , but also to provide cells' progeny with memory of past environments . The interplay of memory and metabolic constraints could thus dramatically change the nature of evolutionary trajectories and optima . We expect theoretical analyses may be fruitfully applied to explore these possibilities . The power of the memory mechanisms we have described lies in their universality . Protein lifetimes and regulatory networks can be tuned in simple ways to give rise to physiological memory under rapidly changing conditions . Microorganisms have to handle both internal and external sources of noise , and while many genetic networks have evolved to exploit stochastic fluctuations of intracellular molecular components to regulate key cellular processes [41] , we have shown that molecular rates of signal transduction reactions can be modulated to optimize response profiles for growth in fluctuating environments . Together , phenotypic and response memory allow bacteria to adapt to a wide range of fluctuation timescales in sophisticated , history-dependent ways . These memory mechanisms constitute general strategies that bacteria can employ to adapt to diverse environmental fluctuations – including nutrients , antibiotics , and other physiological stresses .
The microfluidic device used in this study was made using standard soft lithography and microfabrication techniques and consists of growth chambers and a main flow channel patterned from two SU-8 layers 1 . 1 microns ( SU-8 2 , spun at 3000 rpm ) and 20 microns ( SU-8 2025 , spun at 4000 rpm ) in height , respectively . The devices were fabricated by making polydimethylsiloxane ( PDMS ) replicates of the SU-8 master . The PDMS devices were peeled from the silicon master and 1 . 5 mm holes were punched ( Harris Uni-core , Ted Pella ) to create the input and output ports and each individual device was bonded to a glass bottom petri dish ( PELCO Glass Bottom Dishes , Ted Pella ) using an oxygen plasma treatment . 16ga needles attached to tygon tubing ( TYGON tubing , Cole Parmer ) were inserted into each port and inline solenoid valves ( two-way normally closed 1/16 12VDC , Cole Parmer ) were used to control liquid flow inside the device from pressurized reservoirs . A flow rate of 5 mL/h , which corresponds to a flow speed of 30 cm/s inside the main channel , was used by applying a 6psi pressure to the reservoirs . When transitioning between two media , both valves were closed for 15 seconds before the new one was opened to let the pressure equilibrate inside the device and to avoid backflow problems . A T-junction upstream of the growth chambers ensured that transitions between the different media occurred very rapidly . By flowing a fluorescent dye inside the device , the transition between each type of media was measured to occur in less than 250 milliseconds ( Supp . Video S1 ) in the main flow channel and no residual flow from the “off” inlet port was observed . Cells inside the growth chambers push their immediate neighbors toward the main flow channel as they increase in size , and the lateral speed at which the cells move is proportional to the population's mean elongation rate . An optical flow algorithm implemented using openCV [42] was used to measure the displacement between successive frames . This displacement was used to find the average cell speed over the region between 10 and 15 away from the closed end of the growth chamber . The cell speed was then averaged over a 5 minute time-window , averaged over the 5 chambers present in the image , and scaled relative to the speed measured under MMM+0 . 4% glucose conditions . The lateral speed reports on the cumulative growth rate of cells in the first 10 microns of the growth chamber providing a measure of the relative growth rate of the population . Error bars on relative growth plots report the standard error of the mean as averaged over the 5 chambers present in a single field of view . These error bars measure intrinsic cell-to-cell variability in growth , due to stochasticity in cell division rates , elongation rates , and gene expression processes . The lac induction dynamics of a population subjected to sudden environmental changes are modeled as described in [35] , with an additional equation to account for mRNA transcription . The model assumes that LacY protein levels are proportional to LacZ levels . Unless otherwise noted in Table 1 , refer to [35] for a complete rationalization behind each parameter's value . The set of equations are given by ( 1 ) ( 2 ) ( 3 ) ( 4 ) where , , , and are the intracellular concentrations of lactose , allolactose , mRNA and LacZ proteins , respectively ( parameters are specified in Table 1 ) . Model equations were solved numerically for cyclical glucose/lactose conditions with an environmental duration minutes . After a time , the lac expression levels immediately before a glucose/lactose ( lactose/glucose ) change are recorded to obtain the minimum ( maximum ) lac protein level . The expression for the lactose hydrolysis rate is given by ( 5 ) where , , and are obtained by solving Eqns . 1-4 , and . To qualitatively compare behaviors with and without response memory , we artificially reduced the rate of allolactose turnover in glucose environments ( taking ) to attain response memory in our simple model . Similar results were obtained by reducing instead the mRNA degradation rate in the transition from lactose to glucose . Full methods as well as further details of microfluidic fabrication , strain description , image acquisition and analysis , and any associated references are provided in Text S1 . | Bacterial adaptation to new environments typically involves reorganization of gene expression that temporarily decreases growth rates . By exposing cells to fluctuating conditions using an innovative microfluidic device , we discover that E . coli cells can remember past environments , which accelerates their physiological adaptation . Using a modeling approach combined with experiments , we demonstrate the adaptive advantage of memory for organisms that 1 ) transmit long-lived intracellular proteins between generations or 2 ) respond to fluctuations in a history-dependent manner . Our work describes one of the simplest examples of adaptive memory in a living organism and provides significant insights into the behavior of genetic networks under diverse fluctuations , including nutrients , antibiotics , and other environmental stresses . | [
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] | 2014 | Memory and Fitness Optimization of Bacteria under Fluctuating Environments |
The complex life cycle of the genus Schistosoma drives the parasites to employ subtle developmentally dependent gene regulatory machineries . Small non-coding RNAs ( sncRNAs ) are essential gene regulatory factors that , through their impact on mRNA and genome stability , control stage-specific gene expression . Abundant sncRNAs have been identified in this genus . However , their functionally associated partners , Argonaute family proteins , which are the key components of the RNA-induced silencing complex ( RISC ) , have not yet been fully explored . Two monoclonal antibodies ( mAbs ) specific to Schistosoma japonicum Argonaute protein Ago2 ( SjAgo2 ) , but not SjAgo1 and SjAgo3 , were generated . Soluble adult worm antigen preparation ( SWAP ) was subjected to immunoprecipitation with the mAbs and the captured SjAgo2 protein was subsequently confirmed by Western blot and mass spectrometry ( MS ) analysis . The small RNA population associated with native SjAgo2 in adult parasites was extracted from the immunoprecipitated complex and subjected to library construction . High-through-put sequencing of these libraries yielded a total of ≈50 million high-quality reads . Classification of these small RNAs showed that endogenous siRNAs ( endo-siRNAs ) generated from transposable elements ( TEs ) , especially from the subclasses of LINE and LTR , were prominent . Further bioinformatics analysis revealed that siRNAs derived from ten types of well-defined retrotransposons were dramatically enriched in the SjAgo2-specific libraries compared to small RNA libraries constructed with total small RNAs from separated adult worms . These results suggest that a key function of SjAgo2 is to maintain genome stability through suppressing the activities of retrotransposons . In this study , we identified and characterized one of the three S . japonicum Argonautes , SjAgo2 , and its associated small RNAs were found to be predominantly derived from particular classes of retrotransposons . Thus , a major function of SjAgo2 appears to associate with the maintenance of genome stability via suppression of retroelements . The data advance our understanding of the gene regulatory mechanisms in the blood fluke .
Schistosomiasis is a chronic debilitating disease caused by the parasitic blood flukes of the genus Schistosoma , which afflicts more than 230 million individuals in 77 endemic countries ( http://www . who . int/mediacentre/factsheets/fs115/en/index . html ) . The schistosomes have a complex developmental life cycle characterized by an asexual multiplication phase ( mother sporocysts and daughter sporocysts ) in the molluscan hosts and a sexual development and reproduction phase ( lung-stage schistosomula , juvenile , adult male and female worms , and eggs ) in mammalian hosts , as well as the aquatic free-swimming phase including miracidia and cercariae [1] . It is well known that the schistosome parasites undergo dramatic morphological transformation and rapid physiological adaptation to its life niche during development [2] , which is essentially controlled by subtle gene regulatory mechanisms [1] , [3]–[6] . The decoding of the genomes of the three major pathogenic blood flukes , Schistosoma japonicum , Schistosoma mansoni , and Schistosoma haematobium , has provided a valuable entity for a systematic dissection of the parasite biology [4] , [7] , [8] . In the past decade , small non-coding RNAs ( sncRNAs ) have emerged as critical regulators of gene expression both at transcriptional and post-transcriptional levels in metazoans , plants , fungi , and viruses [9]–[12] . In schistosomes , sncRNA repertoires at different developmental stages of the parasites have been revealed [13]–[19] . Both microRNAs ( miRNAs ) and small endogenous interfering RNAs ( endo-siRNAs ) are expressed in a stage- and gender-biased manner . MiRNA transcripts are generated primarily from the intergenic regions of the genome , whereas endo-siRNAs are principally originated from the transposable elements , including transposons and retrotransposons . The preferential expression of these sncRNAs in different developmental stages and sexes suggests that they play distinct roles in modulating development , maturation , and reproduction of the parasite [14]–[16] , [18] , [19] . To exert their activities , sncRNAs must be selectively loaded onto their relevant machinery , the RNA-induced silencing complex ( RISC ) , and guide the RISC to their complementary templates . Argonaute family proteins are at the heart of RISCs , which can be divided into Ago and PIWI subfamilies [20] , and a third clade , termed ‘group III Argonautes’ is worm-specific for binding secondary siRNAs [21] . Although small RNA pathways are evolutionally conserved , the number of Argonaute genes varies dramatically in different organisms , ranging from one in the fission yeast Schizosaccharomyces pombe to twenty-seven in the nematode Caenorhabditis elegans [21] . Different small RNA regulatory pathways ( SRRPs ) may be mediated by one Argonaute protein , such as metazoan-like Argonaute in the single-cell parasite Toxoplasma gondii [22] , or entangled with multiple Argonaute proteins , which compete and collaborate with each other to form regulatory networks [23]–[25] . In S . mansoni , four Argonaute proteins were identified by two groups mainly based on bioinformatic analysis , but SmAgo3 and SmAgo4 seemed to be generated from an alternatively spliced mRNA [26] . Argonaute orthologs in S . japonicum ( SjAgos ) have been also reported by two groups [27] , [28] . Both of them tried to determine the full-length sequences of the three Argonaute proteins and described the molecular characteristics of SjAgos . Chen et al . also reported the differential expression of SjAgos during the parasite development and suggested that SjAgos coordinated in different SRRPs may be involved in regulating schistosome development [27] . In addition , no PIWI homologue was identified in S . japonicum , though it was found in its closely related genus Schmidtea mediterranea [29] , [30] . Although abundant small non-coding RNAs have been identified in schistosomes , the authentic function of Argonaute proteins in different SRRPs is still largely unknown . SjAgo1 has been previously speculated to participate in the miRNA pathway due to its high homology with miRNA-associated Argonautes in flies , humans , and worms , although experimental support for this idea is still lacking [31] . In this study , by using SjAgo2-specific mAb ( 27A9 ) , native SjAgo2 complex and the associated small RNAs in the parasite were identified and deeply analyzed . Classification of the small RNAs led us to propose that suppression of parasitic retrotransposons within the genome may be the primordial biological function of SjAgo2 .
The parasite-infected Oncomelania hupensis were provided by Jiangxi Institute of Parasitic Diseases , Nanchang , China . The freshly released cercariae of S . japonicum were harvested for Total RNA isolation . To obtain hepatic schistosomula and adult worms , New Zealand White rabbits were percutaneously infected with S . japonicum cercariae ( 1000 to 1500 per rabbit ) . Hepatic schistosomula were isolated from the rabbits at 2 weeks post-infection , while mixed adult worms were obtained after 6-weeks post infection by hepatic-portal perfusion . Male and female adult worms were manually separated with the aid of a light microscope . Eggs were isolated from liver tissues of infected rabbits by enzyme digestion method [32] . All procedures performed on animals within this study were conducted following animal husbandry guidelines of the Chinese Academy of Medical Sciences and with permission from the Experimental Animal Committee of Chinese Academy of Medical Sciences with the Ethical Clearance Number IPB-2011-6 . Total RNAs of S . japonicum at different developmental stages ( cercariae , hepatic schistosomula , separated adult male and female worms , and eggs ) were extracted using RNeasy Mini kit ( QIAGEN ) and the contaminating genomic DNA was removed from RNA samples with TURBO DNA-free™ kit ( Ambion , CA , USA ) . RNA quantification and quality control was conducted by denaturing agarose gel electrophoresis and Nanodrop ND-1000 spectrophotometer ( Nanodrop Technologies , Wilmington , DE ) . One µg total RNA from S . japonicum adult worms was used to synthesize the first strand cDNA using SuperScript™ III Reverse Transcriptase Kit ( Invitrogen , CA , USA ) , with oligo ( dT ) 15 primer . The 5′ UTR of SjAgo2 gene was amplified with a SMART RACE cDNA Amplification Kit according to the manufacturer's instructions ( Clontech , CA , USA ) . The amplicons were cloned into T-Vector and sequenced . The primers used for 5′ RACE were listed in Table S1 . xQRT-PCR was performed to quantitate the expression level of SjAgo1 , SjAgo2 , and SjAog3 transcripts at different developmental stages of the parasite and between separated adult worms . For each sample , 1 µg total RNA was reverse transcribed into first-strand cDNA using SuperScript™ III Reverse Transcriptase Kit ( Invitrogen ) with Oligo dT ( 15 ) primer by incubation for 5 min at 25°C , 60 min at 50°C , and 15 min at 70°C . The resulting cDNA products were diluted 20-fold with nuclease-free water before qPCR . Each 25 µl PCR reaction contained 12 . 5 µl of 2×Brilliant II SYBR Green QPCR Master Mix ( Agilent , USA ) , 1 µl cDNA , 1 µl of the forward and reverse primer pair ( Table S1 ) , and 10 . 5 µl of sterile water . The PCR conditions included 40 cycles with denaturation at 95°C for 30 s , followed by annealing and extension at 60°C for 1 min . A dissociation step ( 95°C for 15 s , 60°C for 1 min , 95°C for 15 s , and 60°C for 15 s ) was added to confirm the amplification specificity for each gene . The PCR products were separated on a 2 . 5% agarose gel to confirm the presence of a single band with the expected size . Quantification of the expression for each SjAgo gene during the parasite development was performed by normalizing against a novel house-keeping gene , PSMD4 ( 26S proteasome non-ATPase regulatory subunit 4 , GenBank accession number: FN320595 ) [33] and applying the comparative 2−ΔΔCt method using the software SDS 1 . 4 . The SWAP ( soluble adult worm antigen preparation ) was prepared mainly as previously described with minor modification . Briefly , the S . japonicum adult worms were washed in PBS for five times to reduce contamination of host components , homogenized on ice in lysis buffer containing 20 mM Tris-HCl ( pH 7 . 4 ) , 200 mM NaCl , 2 . 5 mM MgCl2 , 0 . 05% NP-40 , EDTA-free protease inhibitor cocktail ( Roche ) and RNasin ( Promega ) at a final concentration of 0 . 1 U/µl . The homogenate was then centrifuged at 14 , 000 g for 10 min at 4°C and the supernatant was collected carefully to avoid the top lipid layer . This procedure was repeated until the supernatant was clear . The supernatant was stored at −80°C for further use . The DNA fragments encoding tSjAgo1 ( aa198-1009 ) , SjAgo2 ( aa1-935 ) , and SjAgo3 ( aa1-923 ) were amplified from S . japonicum adult worm cDNA using high fidelity Phusion DNA polymerase ( Finnzymes Oy , Finland ) with KpnI and NotI endonucleases site added at their 5′ and 3′ terminus , respectively ( Primer sets were listed in Table S1 ) . The PCR was performed with an initial denaturation for 1 min at 98°C . Ten PCR cycles were performed as follows: 98°C for 8 s , 50°C for 30 s and 72°C for 1 min , followed by another twenty PCR cycles: 98°C for 8 s , 55°C for 30 s and 72°C for 1 min , with a final extension at 72°C for 5 min . The amplicons were digested with KpnI and NotI restriction endonucleases , and cloned into pcDNA3-FLAG3C vector . The recombinant plasmids were transformed into DH5α ( DE3 ) Escherichia coli and positive clones were selected for sequencing . The correct recombinant plasmids were designated as FLAG-tSjAgo1 , FLAG-SjAgo2 , and FLAG-SjAgo3 , respectively . To generate Flag-tagged recombinant SjAgos , human 293T cells were grown in Dulbecco's modified Eagle's medium supplemented with 2 mM L-glutamine and 10% fetal bovine serum . 293T cells were transfected at 90% confluency in 60-mm dishes with 8 µg of FLAG-tSjAgo1 , FLAG-SjAgo2 , FLAG-SjAgo3 , or the empty vector , respectively , using Lipofectamine™ 2000 ( Invitrogen ) . The cells were further cultured for 36 h at 37°C in a 5% CO2 incubator . Cell extracts were prepared in 200 µl lysis buffer containing 20 mM Tris-HCl ( pH 7 . 5 ) , 150 mM NaCl , 1% Triton X-100 , and protease inhibitors . Monoclonal antibodies 27A9 and 11E8 to SjAgo2 protein were produced by Abmart Inc ( Shanghai , China ) . Briefly , the optimal peptide immunogens were selected from SjAgo2 by an in-house peptide selection database called Antibody Designer . Two cDNA fragments encoding aa1-232 and aa34–305 of SjAgo2 were subcloned into pET30a vector ( Novagen ) between BamHI and HindIII endonuclease sites . The recombinant plasmids were transformed into BL21 ( DE3 ) E . coli . Two His-tag recombinant proteins were then expressed in E . coli and purified with Ni-NTA agarose beads . Six BALB/c mice were immunized subcutaneously with the peptides . Spleen cells obtained from immunized mice were fused with SP2/0 myeloma cells according to the standard procedure . Positive hybridomas were cloned , and immunoglobulin G ( IgG ) was purified by protein G affinity chromatography from ascite liquid . Immunoprecipitations were carried out essentially as described by Kiriakidou et al . [34] . For immunoprecipitation of endogenous SjAgo2 protein , a procedure of sequential depletion by absorption was adapted . One ml SWAP was first mixed with 100 µl of Protein-A/G agarose slurry ( 50% ) ( Abmart , Shanghai , China ) and incubated at 4°C for 2 h with gentle rotation ( Mock ) . After centrifugation at 2 , 500 rpm for 5 min , the supernatant was recovered and subsequently mixed with 4 µg normal mouse IgG ( Santa Cruz Biotechnology ) and incubated with gentle rotation at 4°C for 2 h . Then , 40 µl of Protein-A/G agarose was added and continually incubated at 4°C for another 2 h . The agarose beads were collected by centrifugation for 5 min at 2 , 500 rpm ( moIgG IP ) . The supernatant was divided into equal parts and respectively mixed with 4 µg of 11E8 or 27A9 mAb , and gently incubated at 4°C for 4 h . The immunocomplex were captured by addition of 20 µl of Protein-A/G agarose beads and gently rotating for 2 h at 4°C . The beads were collected by centrifugation for 5 min at 2 , 500 rpm ( mAb IP ) . The beads in the three sequential IP assays ( without antibodies , with moIgG , and with specific mAbs ) were further washed with 1 ml ice-cold lysis buffer for 5 times and resuspended with 1×SDS loading buffer . The protein samples were boiled for 10 min . After centrifugation , the supernatant was collected and used for further analysis . Western blot analysis was performed as previously described [35] . Cell extracts with over-expressed tSjAgo1 , SjAgo2 , SjAgo3 , SWAP , as well as immunoprecipitates were separately mixed with SDS-PAGE loading buffer and separated on SDS-PAGE gels , and transferred to the PVDF membrane . The membrane was blocked with 5% SMP in TBS for 90 min at room temperature . Anti-Flag mAb M2 ( 1∶2 , 000 dilution , Sigma ) or anti-SjAgo2 mAbs ( at a final concentration of 10 µg/ml ) was used for detection of the target proteins . The HRP ( horseradish peroxidase ) -conjugated goat anti-mouse IgG ( Zhongshan , China ) at a dilution of 1∶10 , 000 was used as a secondary antibody and signal was detected with a luminol-based chemiluminescent substrate ( CSN ) . To confirm that SjAgo2 was truly precipitated by the mAbs , two IP and MS assays were performed . In the first assay , the immunocomplex directly precipitated by mAb 27A9 from SWAP was resolved on a 10% SDS-PAGE gel and visualized by Coomassie Brilliant Blue staining . Protein bands with different molecular weights ( >170 kDa , 130–170 kDa , 90–130 kDa , 70–80 kDa , 60–70 kDa , and 42–52 kDa ) were excised and subjected to Orbitrap MS analysis . In the second assay , SWAP was sequentially incubated with Protein-A/G agarose beads ( Mock ) , normal mouse IgG , and eventually with mAb 27A9 . The immunoprecipitates were resolved on a 10% SDS-PAGE gel . Protein bands with sizes of ≈70–90 kDa and ≈90–120 kDa were excised from the gel ( Figure S1 ) and digested with trypsin . The resulting peptides were analyzed by Orbitrap MS and identified by blasting against the protein datasets of S . japonicum downloaded from SDSPB ( http://lifecenter . sgst . cn/schistosoma/en/schdownload . do ) and Uniprot ( http://www . uniprot . org/uniprot/ ? query=taxonomy%3a6182&format= ) . The SjAgo2 associated small RNAs were extracted as previously described [34] . RNA quantification and quality were evaluated by an Agilent 2100 Bioanalyzer ( Figure S2 ) . Small RNA libraries were constructed mainly as previously described [18] . Briefly , RNAs between 15–40 nucleotides ( nt ) were excised from a 15% TBE urea polyacrylamide gel electrophoresis ( PAGE ) . The RNA sample was purified and their 5′ and 3′ termini were ligated with Illumina's proprietary adapters , which was further used as templates to synthesize first-strand cDNA . The cDNA was amplified by PCR with a high fidelity Phusion DNA polymerase and the Illumina's small RNA primer set . The libraries were sequenced on the Illumina Genome Analyzer II platform at the BGI ( Beijing Genomics Institute , Shenzhen , China ) . IP assays were performed from two independent biological repeats with mAb 27A9 , and the RNAs were separately applied for library construction and sequencing . The two libraries were designated as SP1 and SP2 , respectively . Raw datasets produced by Solexa sequencing from the two libraries were tagged and pooled . Clean reads were obtained after removing of the low quality reads , adaptor null reads , insert null reads , 5′ adaptor contaminants , and reads with ployA tail . Adapter sequences were trimmed from 5′ and 3′ ends of clean reads . All identical sequences were counted and merged as unique sequences . These unique reads affiliated with read counts were mapped to the S . japonicum genome draft ( sjr2_contig . fasta ) ( http://lifecenter . sgst . cn/schistosoma/en/schdownload . do ) using the program SOAP version 2 . 20 [36] . First , we investigated the length distribution of small RNA reads in the two libraries that perfectly matched the genome draft of S . japonicum , and the small RNAs were categorized by the bioinformatic pipeline as described [18] . Afterwards , an alternative bioinformatic pipeline was designed to classify the small RNA reads that perfectly matched the reference genome . Briefly , the reads were matched to the transposable elements in the S . japonicum genome predicted by using REPET software ( http://urgi . versailles . inra . fr/index . php/urgi/Tools/REPET ) , in an order of LINE ( Long Interspersed Elements ) , SINE ( Short Interspersed Elements ) , LTR ( Transposable elements with Long Terminal Repeats ) , TIR ( Terminal inverted repeat ) , MITE ( Miniature inverted-repeat transposable elements ) , and unknown TE . The remaining small RNAs were aligned to S . japonicum predicted mRNA sequences ( sjr_mRNA . fasta ) downloaded from SDSPB using SOAP 2 . 20 aligner , and perfectly matched reads were retained as mRNA related siRNA . Next , the endo-siRNAs depleted reads were then BLAST-searched against the 78 known mature miRNAs of S . japonicum deposited in Sanger miRBase [37] , [38] ( Release 17 ) using the program Patscan [39] , and further BLAST-searched against the conserved and novel S . japonicum miRNAs reported in our previous study [18] . Finally , homologs to rRNA , tRNA , snoRNA , and other small RNAs [40] were filtered and the remaining reads were labeled as unknown small RNAs . To further characterize the small RNAs identified , full length sequences of 29 classes of retrotransposons [4] , [41]–[43] were retrieved from the NCBI GenBank database [44] . The small RNA reads from the SP1 , SP2 , SjM , and SjF libraries were mapped to these retrotransposons . The abundance of these retrotransposon-derived siRNAs was reflected based on their expression values ( TPM , transcripts per million ) . A set of graphs depicting the distribution and abundance of retrotransposon-derived siRNAs were further constructed as previously described [18] . Briefly , the expression of each base on these TEs was the sum of the TPM value of siRNAs that mapped to the position . A proper bin ( 10 or 50 bases ) was then selected based on the length of TE sequences , and the average expression value was calculated for each bin .
To investigate the possibility of functional or stage specificity of the three Argonaute paralogues in S . japonicum , we determined the transcription levels of the three Argonaute genes in the parasite before and after host invasion using qRT-PCR with that of 26S proteasome non-ATPase regulatory subunit 4 ( PSMD4 ) as an endogenous control [33] . The overall expression level of the three genes was much lower in cercariae than in other stages within the host ( Figure 1 ) . This observation suggests that the SjAgos were mainly functional in the late developmental stages of the parasite . The expression of SjAgo1 in eggs , miracidium , cercariae , schistosomula , and adult worms has been reported earlier by Lou et al . [28] . Even though the trend of the expression of SjAgo1 was found similar between the two studies , our results were more profound than those reported previously . The difference was most likely caused by the different endogenous controls used in the two studies . The SjGAPDH gene was recently found to be unstably transcribed during the parasite development , which means that it is not suitable as an endogenous transcriptional control [33] . SjAgo2 and SjAgo3 presented a reversed expression pattern between male and female adult worms ( Figure 1B and C ) . The expression of SjAgo2 was up-regulated in schistosomula and female parasites , whereas SjAgo3 was highly expressed in schistosomula and male worms . Previously , Chen et al . reported that the expression of SjAgo1 was significantly higher in eggs than that in adult worms and the expression of SjAgo2 and SjAgo3 was not significantly different between male and female parasites [27] . This inconsistency is likely due to different experimental conditions , especially the endogenous controls applied in the two studies . However , it cannot be ruled out that the parasite strains in the two studies might be different . The two groups mentioned above also reported their analysis on the Argonaute family members in S . japonicum but with different results [27] , [28] . In light of the uncertainty of the size of SjAgo2 protein , we performed 5′ RACE to determine the N-terminal region of the protein , for the C-terminus of the protein has been definitively defined . We confirmed that the full-length SjAgo2 protein contains 935 amino acids as reported by Chen et al . [27] , but not 945 amino acids as reported by Luo et al . [28] . In order to obtain specific mAbs against SjAgo2 , two optimal peptide immunogens , aa1-232 and aa34-305 of SjAgo2 , that avoided the major homologous regions with SjAgo3 , were selected for immunizing BALB/c mice and two mAbs , 11E8 and 27A9 , were generated . To determine the specificity of the mAbs against SjAgo2 , we cloned the ORFs of the three Argonaute genes in the eukaryotic vector pcDNA3-FLAG3C , and the SjAgos were expressed in human 293T cells . Western blot analysis confirmed that SjAgo2 and SjAgo3 , but not SjAgo1 , were expressed in the 293T cells . Next , we tried to express a truncated form of SjAgo1 ( tSjAgo1 , aa198-1009 ) , since the N-terminus of SjAgo1 displayed very low similarity with SjAgo2 and SjAgo3 [27] , it is unlikely that the mAb to the N-terminus of SjAgo1 would cross react with SjAgo2 and SjAgo3 . The tSjAgo1 was successfully expressed in 293T cells , though the expression level was relatively lower than that of SjAgo2 and SjAgo3 ( Figure 2A ) . The recognition of the recombinant SjAgo2 by mAb 11E8 or 27A9 was confirmed by Western blot analysis ( Figure 2B ) . To determine whether both mAbs would cross-react with SjAgo1 and SjAgo3 , equal amounts of the recombinant tSjAgo1 , SjAgo2 , and SjAgo3 were loaded in each lane ( Figure S3 ) . The blot was further detected by mAb 11E8 or 27A9 , and both mAbs only specifically recognized SjAgo2 , but not tSjAgo1 and SjAgo3 ( Figure 2C ) . Immunoprecipitates from all experimental groups were separated by 10% SDS-PAGE ( Figure S4 ) and followed by Western blot analysis ( Figure 3A ) . Two prominent bands at a molecular weight of approximately 100 kDa were observed . However , the lower band ( asterisked ) also appeared in the immunoprecipitates captured by normal mouse IgG , indicating that it may have been caused by non-specific binding to mouse IgG . As indicated by the molecular weight , we speculated that the lower band might be the IgG-binding protein paramyosin ( PMY ) [45]–[47] . In contrast , the upper band ( arrowed ) is more close to the theoretical molecular weight of SjAgo2 ( 105 . 9 kDa ) . Western blot analysis was performed to determine the reactivity and specificity of the mAb 27A9 directly against SWAP , and two bands ( arrowed ) with the size of ∼100 kDa were detected ( Figure 3B ) . By using Orbitrap MS analysis , 38 peptides derived from SjAgo2 were identified from bands between ∼90–130 kDa in 27A9 immunoprecipitates , whereas no peptides derived from SjAgo1 and SjAgo3 were detected in the immunoprecipitates ( Table 1 ) , which further confirmed the specificity of the mAb 27A9 to SjAgo2 . The RISC forming proteins like TRBP and DDX6 were not identified in the immunoprecipitates . This could be due to the experimental condition which may not be suitable for the coprecipitation of these proteins; or due to the missing sequence information of the two proteins in the S . japonicum database which prevented the identification of these two proteins in the MS analysis . The appearance of the 13 peptides derived from PMY in the Orbitrap MS analysis supported our speculation that this was due to its IgG-binding property of the molecule ( Table 1 ) . In addition to PMY , several other cytoskeleton and motor proteins , including actin , myosin , dynein , spectrin , and kinesin , were also detected in the immunoprecipitates ( Table S2 ) , which were presumably co-purified through interaction with PMY [48] . Strikingly , several members of the heat shock protein ( HSP ) family ( 90 , 97 , and 110 kDa respectively ) , and three isoforms of the HSP70 protein were identified ( Table S2 ) . However , these proteins also appeared in the mock group in the second MS analysis ( Table S3 ) , indicating that they were non-specifically captured by the protein-G/A agarose beads . This finding was consistent with the previous observation that the HSP70 homologue in S . mansoni ( SCHMA-HSP70 ) can readily bind to protein-G Sepharose [46] . Recent studies in human and flies revealed that HSP90 protein can chaperone Argonautes and facilitate the loading of small RNA duplexes [49]–[51] . More recently , HSP90 was reported to participate in the Piwi-interacting RNA ( piRNA ) pathway and function in canalization [52] . Our results here suggest that HSP members in S . japonicum do not directly interact with SjAgos; thus , whether they can participate in the assembly of RISC complex remains unclear . Nevertheless , as no SjAgo1 and SjAgo3 were detected in 27A9 immunoprecipitates , these co-precipitated contaminating proteins have no influence on analyses of the small RNA population associated with SjAgo2 . 32 , 876 , 012 and 21 , 822 , 050 high quality reads were obtained respectively from the two small RNA libraries , SP1 and SP2 ( both were established from the SjAgo2 complex with mAb 27A9 ) ( Table S4 ) . The redundancy level of both libraries was ∼85% ( Redundancy = 100− ( Total Unique Clean Reads/Total High-quality Clean Reads ×100 ) ) ( Table S5 ) , which presented a similar sequencing depth as our previous study [18] . We investigated the length distribution of small RNA reads in the SP1 and SP2 libraries that perfectly matched the draft genomic sequence of S . japonicum ( Figure 4 ) . The length distribution of the reads in both libraries presented a quite similar pattern , both at total and unique level . The 20 nt reads were predominant in both libraries , which accounted for 46 . 1% ( SP1 ) and 55 . 7% ( SP2 ) of the reads , respectively , followed by the 21 nt reads . Thus , the reads length of sncRNAs associated with SjAgo2 was closer to that of endogenous siRNAs bound to Drosophila Ago2 , which peaks at 21 nt [25] , [53] , rather than miRNAs , whose sizes are typically ≈22 nt [54] , [55] . We systematically defined the sncRNAs in both libraries SP1 and SP2 ( Figure 5A and B ) , using the bioinformatic pipeline as reported previously [18] . We also compared the data to that obtained from the adult worm libraries SjM and SjF , which were constructed with total small RNA ( Figure 5C and D ) [18] . The proportions of LTR- and LINE-derived siRNAs were significantly higher than that of miRNA , rRNA , TIR- and MITE-derived siRNAs in the two libraries compared to that constructed with total small RNAs . For the LINE-derived siRNAs , the proportion increased from ≈3% in the adult small RNA libraries to an average of 17% in the SjAgo2-specific libraries . For the LTR-derived siRNAs , the proportion in the SjAgo2-specific libraries was at least 5-fold higher than that in the libraries SjF and SjM ( from ≈4% to an average of 22% ) . This difference strongly suggests that SjAgo2 preferentially associated with siRNAs derived from LINE and LTR retrotransposons . Regarding the mRNA related small RNAs , the proportion of this group in SjAgo2-specific libraries was twice as high as that in the small RNA libraries of separated adult worms ( Figure 5A , B , C , and D ) . This is due to the reason that numerous TE-derived transcripts were deposited in the predicted S . japonicum database as mRNA sequences ( sjr_mRNA . fasta ) . Thus , a mass of TE-derived siRNAs may have been categorized as mRNA-related small RNAs . Therefore , an optimized bioinformatic pipeline was designed to sort the small RNAs from SjAgo2-specific libraries . As a result , the proportion of mRNA-related small RNAs substantially decreased in contrast to that of retrotransposon-derived siRNAs , in particular LTR-derived siRNAs , which increased nearly one-third ( Figure 5E and F ) . This observation further implies that SjAgo2 predominantly interacts with retrotransposon-derived siRNAs . TE components have been recognized as one of the principal forces driving genome diversity and evolution [56] . However , too many insertions of TEs into the genome may be deleterious , imposing that they must be under appropriate control to keep the integrity of the genome [57] . In S . japonicum , the repetitive elements account for more than 40% of the genome sequences [4] . And the mobile genetic elements ( MGEs ) in S . japonicum have been categorized into several classes , including short interspersed nucleotide elements ( SINEs ) -like retrotransposons [58] , LTR [4] , [41] , non-LTR [4] , [42] , and Penelope-like retrotransposons [4] . We therefore further investigated whether the small RNAs interacted with SjAgo2 were restricted to any particular class of retrotransposons . The expression levels of siRNAs derived from 29 well-defined retrotransposons in the SP1 , SP2 , SjM , and SjF libraries were presented based on their TPM value ( Table 2 ) . We found that siRNAs in the SjAgo2-specific libraries were mainly derived from 11 classes of retrotransposons ( Table 2 , Top 11 ) . For example , siRNAs generated from retrotransposon SjCHGCS11 , SjCHGCS13 , SjCHGCS14 , and Sj-penelope1 were 4–6 fold more in the SjAgo2-specific libraries than that in the libraries SjM and SjF ( Figure 6A and B ) . Sense siRNAs generated from LINE SjCHGCS21 were also enriched in the SP1 and SP2 libraries ( Figure 6C ) . In contrast , the abundance of siRNAs derived from SjCHGCS10 , Sjpido , SjCHGCS1 , SjCHGCS2 , SjCHGCS19 , SjCHGCS20 , SjR2 , and SjCHGCS3 was decreased in the SjAgo2-specific libraries compared to that in the SjM and SjF libraries ( Table 2 , and Figure 6C ) , suggesting that the function of siRNAs from these classes of retrotransposons were correlated to SjAgo2 . We further evaluated the correlation between the transcription levels of the well-defined retrotransposons of S . japonicum and the enrichment of the siRNAs in the SjAgo2 complex by analysis of the whole-transcriptome data generated from separated adult worms ( Piao et al . , unpublished data ) . Interestingly , for several classes of retrotransposons , an obvious inverse relationship was observed between the abundance of mRNA transcripts and amount of relevant siRNAs in the SjAgo2-specific libraries . For instance , siRNAs derived from retrotransposon SjCHGCS6 , Sj-penelope1 , Sj-penelope2 , SjCHGCS21 , SjCHGCS9 , and SjCHGCS4 were highly enriched in the SjAgo2 libraries , whereas the levels of the corresponding transcripts of these mobile elements were much lower ( Table 2 ) . On the contrary , siRNAs derived from retrotransposon SjCHGCS20 , SjR2 , and SjCHGCS3 were much less in the SjAgo2 libraries , the transcripts of these retroelements were relatively more ( Table 2 ) . These findings suggest that siRNAs enriched in the SjAgo2 libraries were not affected by the transcription levels of the retrotransposons , and SjAgo2 may be functionally specialized to suppress a group of transposable elements in the parasite . However , this regulatory model cannot be applied to all types of retrotransposons . It can be explained by the facts that the transcriptome data reflect the transcriptional levels of retroelements within the whole worms , while the expression of SjAgo2 in the parasite may be tissue-specific as its ortholog in S . mansoni [59] . Based on the property of its associated small RNA population , we postulated that SjAgo2 is mainly involved in such a mechanism by regulating retrotransposon at the transcriptional level . A similar function of Argonaute protein has previously been suggested in studies of Trypanosoma brucei , D . melanogaster , and mice [25] , [53] , [60]–[63] . In addition , the Ago2 transcripts in S . mansoni exhibited a germline-specific expression in both adult female and male worms [59] . This observation indicates that , in schistosome adult worms , Ago2 functions in the maintenance of genome stability in germline cells by retrotransposons silencing . Previous studies in Drosophila and vertebrates have shown that the endo-siRNA pathway is involved in transposons silencing in somatic tissues [25] , [53] , [57] , [60] , [63]; whereas transposons are mainly controlled by the piRNA pathway in germline cells , which functions through Piwi subclade proteins [64] , [65] . However , the piRNA pathway does not appear to be specialized in schistosome as no Piwi homolog has been discovered in its genome [15] , [31] . The siRNA pathway mediated by SjAgo2 in schistosome germline could , to some extent , compensate for the absence of the piRNA pathway as suggested previously [31] . Given the fact that SjAgo2 is ubiquitously expressed during various developmental stages of the parasite , though at different levels , SjAgo2 may be bi-functional in both somatic and germline cells . However , further studies are needed to dissect it out . Though the PAZ and Piwi domains were highly homologous between SjAgo2 and SjAgo3 , substantial differences exist in the region corresponding to the typical Mid domain , which has been definitively established to play role in 5′ end recognition of the guide strand [27] , [66] . The reverse expression pattern of SjAgo2 and SjAgo3 genes in male and female adult worms was also observed ( Figure 1 ) . Both of these observations indicate that SjAgo3 may play an analogous , but non-redundant role to SjAgo2 in S . japonicum , such as suppressing the activities of TEs in somatic cells . One line of evidence supporting this is that a substantial portion of small RNAs derived from DNA transposons TIR and MITE was detected in adult worms , with an amount even more than that of LTR- and LINE-derived siRNAs in both male and female worms ( Figure 5C and D ) . Another possibility is that SjAgo3 may also restrict the activities of retrotransposons , such as SjR1 , SjR2 , and Sjpido , via binding with siRNAs that not enriched in the SjAgo2-specific libraries ( Figure 6C ) . Only a small proportion of miRNAs was found to be associated with SjAgo2 ( Figure 5A and B ) , which is in line with the suggestion that the miRNA pathway in schistosomes is mainly mediated by Drosha , Dicer , and Ago1 , as Ago1 is more closely related to Argonaute orthologs involved in the miRNA pathway in flies , humans , and worms [31] . Our findings here as well as those found in Drosophila suggest that some miRNAs were still bound to their unconventional partner , Ago2 , in addition to being strongly associated with Ago1 [67] , [68] . Thus , the phenomenon that some miRNAs sorted onto the SjAgo2 complex exhibits the complexity of a small RNA regulatory network in schistosome parasite and suggests that different silencing pathways may cross-link with each other and share or compete the apparatus required in the biogenesis of different small RNAs . In Drosophila , miRNA are generated in a Dicer1-dependent manner , whereas siRNAs are produced in a Dicer2-dependently manner [60] . However , the dsRNA-binding protein Loquacious ( Loqs ) , a typical miRNA factor associated with Dicer1 , may actually be required for the biogenesis of endo-siRNAs [25] , [69] . Since only one Dicer gene was found in S . japonicum [28] , the miRNA pathway and endo-siRNA system in schistosomes may share one Dicer in the production of miRNA and siRNA duplex , cross-linking both pathways at upstream . In summary , using a mAb specific to SjAgo2 , we have systematically investigated the small RNAs bound to the protein . SjAgo2 was determined to associate mainly with endo-siRNAs derived from LINE and LTR types of transposable elements in adult S . japonicum . The enrichment of siRNAs in the SjAgo2-specific libraries was found to be restricted to particular types of retrotransposons . These results emphasize the potential role of SjAgo2 in maintaining genomic stability in germ-line and/or somatic cells by repressing retrotransposons . | Schistosomiasis , a chronic disease caused by agents of the genus Schistosoma , still afflicts more than 230 million people worldwide . The genomes of the three major pathogenic blood flukes , Schistosoma japonicum , Schistosoma mansoni , and Schistosoma haematobium , have been decoded as valuable entities for a systematic dissection of the biological characteristics of the parasites . Transposable elements constitute a major component in the genome of schistosomes and have been recognized as remnants of evolutionary events , but some of them are still active today . Thereby , the activity of these active mobile genetic elements should be restricted by elaborate mechanisms to protect genome stability . Our study showed that one of the three S . japonicum Argonaute proteins , SjAgo2 , is involved in such mechanisms . By using specific mAb , native SjAgo2 protein was immunoisolated from a soluble adult worm antigen preparation , and its associated small RNAs were extracted for deep sequencing . We found that SjAgo2 is mainly associated with particular types of retrotransposon-derived siRNAs . For instance , siRNAs generated from 10 classes of well-defined retrotransposons were significantly enriched in the SjAgo2-specific libraries . Thus , a major function of Ago2 in S . japonicum is proposed to be the maintenance of genome stability via retrotransposon suppression . Our findings advance understanding of the putative gene regulatory mechanisms in a flatworm parasite . | [
"Abstract",
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] | [
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] | 2012 | Identification and Characterization of Argonaute Protein, Ago2 and Its Associated Small RNAs in Schistosoma japonicum |
In response to iron deficiency , the budding yeast Saccharomyces cerevisiae undergoes a metabolic remodeling in order to optimize iron utilization . The tandem zinc finger ( TZF ) -containing protein Cth2 plays a critical role in this adaptation by binding and promoting the degradation of multiple mRNAs that contain AU-rich elements ( AREs ) . Here , we demonstrate that Cth2 also functions as a translational repressor of its target mRNAs . By complementary approaches , we demonstrate that Cth2 protein inhibits the translation of SDH4 , which encodes a subunit of succinate dehydrogenase , and CTH2 mRNAs in response to iron depletion . Both the AREs within SDH4 and CTH2 transcripts , and the Cth2 TZF are essential for translational repression . We show that the role played by Cth2 as a negative translational regulator extends to other mRNA targets such as WTM1 , CCP1 and HEM15 . A structure-function analysis of Cth2 protein suggests that the Cth2 amino-terminal domain ( NTD ) is important for both mRNA turnover and translation inhibition , while its carboxy-terminal domain ( CTD ) only participates in the regulation of translation , but is dispensable for mRNA degradation . Finally , we demonstrate that the Cth2 CTD is physiologically relevant for adaptation to iron deficiency .
Iron is indispensable for all eukaryotic organisms because it serves as a redox cofactor in a wide range of critical biological processes , including the synthesis of the principal cellular components ( DNA , proteins , lipids and other metabolites ) , mitochondrial respiration , photosynthesis , and oxygen sensing and transport . Despite being very abundant , iron bioavailability is extremely low . Consequently , cells have developed refined transcriptional and post-transcriptional strategies to properly respond to iron depletion . In response to iron deficiency , the budding yeast Saccharomyces cerevisiae activates the expression of Cth2 , an RNA-binding protein that , in coordination with its partially redundant homolog Cth1 , promotes the metabolic remodeling of cellular processes in order to optimize iron utilization [1 , 2] . Cth1 and Cth2 belong to a family of proteins whose most studied exponent is mammalian tristetraprolin ( TTP/Tis11 ) [3–8] . The most remarkable trait of the TTP family of proteins is the presence of two highly conserved Cx8Cx5Cx3H tandem zinc fingers ( TZFs ) through which they specifically bind to AU-rich elements ( AREs ) within the 3' untranslated region ( 3'-UTR ) of many target mRNAs . The main function assigned to TTP-family proteins consists in promoting ARE-mediated mRNA decay ( AMD ) . Yeast Cth2 protein shuttles between the nucleus and the cytoplasm , and performs different ARE-dependent functions according to its subcellular localization . The binding of Cth2 to ARE-containing mRNAs takes place in the nucleus , where it can promote the degradation of extended transcripts by influencing the 3ʼ-end processing of its target mRNAs [9 , 10] . Mature Cth2-bound mRNAs are then translocated to the cytosol through mRNA export pathways and directed to specific sites to undergo degradation via the RNA helicase Dhh1 and the 5ʼ to 3ʼ exonuclease Xrn1 [11] . Upon iron scarcity , Cth2 promotes the degradation of multiple ARE-containing mRNAs including those that encode a subunit of succinate dehydrogenase ( SDH4 ) , ferrochelatase ( HEM15 ) , mitochondrial cytochrome-c peroxidase ( CCP1 ) and a ribonucleotide reductase inhibitor ( WTM1 ) [1 , 12] . The Cth2 protein contains three regions ( CR1 , CR2 and CR3 ) conserved in the Saccharomyces species [9] . Previous studies have demonstrated that CR1 is important for the mechanism of SDH4 mRNA decay , but not for nucleocytoplasmic shuttling [9 , 13] . Besides , the Cth2 protein contains an ARE within the 3’-UTR of its mRNA that facilitates its auto-degradation [13] . Cth2 negative feedback regulation is important to rapidly recover mitochondrial respiration and growth when yeast cells shift from iron-deficient to iron-sufficient conditions [13] . Mammalian TTP proteins have been implicated in the regulation of diverse physiological processes including inflammatory and immune responses . Interestingly , recent studies have also implicated mammalian TTP protein in the regulation of iron metabolism by promoting the turnover of mRNAs that encode for iron-containing proteins , such as Transferrin receptor 1 [14–16] . TTP protein interacts with multiple components of the mRNA decay and translation repression machineries , including the CCR4/CAF1/NOT1 complex , cap-binding factor eIF4E2 , the Dhh1 homolog RCK/p54 , the poly ( A ) -binding protein and the exosome [17–23] . Thus TTP-dependent AMD can proceed through the Xrn1-dependent 5’ to 3’ degradation pathway and via the exosome in a 3’ to 5’ mRNA decay mechanism [18 , 20 , 24] . Furthermore , in addition to promote AMD , mammalian TTP represses translation through interactions with RCK/p54 , which acts as both a promoter of decapping and a translational repressor [17 , 25] . Like yeast Cth2 , mammalian TTP-family proteins also shuttle between the nucleus and the cytoplasm , and regulate mRNA biogenesis and fate at many levels [5 , 26–28] . Moreover , the TTP-family member Tis11b modulates the expression of DII4 mRNA in endothelial cells by interfering with its habitual 3’-end processing [29] . Similarly to its yeast counterparts , feedback regulatory loops have been described for TTP , in this case at both the mRNA decay and translational levels [25 , 30–32] . We previously reported that yeast cells which express an ARE mutant allele of the CTH2 transcript display a poor correlation between CTH2 mRNA and Cth2 protein levels [13] . These observations prompted us to investigate a potential role for Cth2 in targeted translational regulation . Here we demonstrate a new mRNA regulatory function for Cth2 as an inhibitor of the translation of specific transcripts under iron-deficient conditions . The Cth2 function in mRNA translation regulation relies on the presence of an ARE within the target mRNA and an intact TZF domain in the Cth2 protein . Finally , we performed a Cth2 structure-function analysis to decipher the contribution of each conserved domain to either mRNA decay or translation regulation .
We have previously reported that the mRNA levels of SDH4 , which encodes a subunit of succinate dehydrogenase , lower in response to iron starvation in a Cth2- and ARE-dependent manner [1] . Given that TTP limits the expression of its target mRNAs , not only by promoting their degradation but also by inhibiting their translation , we decided to investigate whether the down-regulation of SDH4 expression by iron depletion could also be controlled at the translational level . Therefore , we analyzed the translation stage of SDH4 mRNAs in yeast cells grown under iron-sufficient ( SC medium supplemented with 10 μM FAS , +Fe ) and iron-deficient ( SC supplemented with 100 μM BPS , -Fe ) conditions . Translation was measured by two different approaches . First , we defined SDH4 translation efficiency as the Sdh4 protein/SDH4 mRNA ratio , normalized to the translation efficiency of 3-phosphoglycerate kinase PGK1 . For protein level determinations , we did Western blot analyses of a Flag epitope-tagged version of Sdh4 protein and specific Pgk1 antibodies . To assess the mRNA levels , we used RT-qPCR with specific Flag2-SDH4 and PGK1 oligonucleotides ( see S1 Table ) . As expected , iron depletion led to a drop in SDH4 mRNA to 31% of the iron-sufficiency levels ( Fig 1A ) . However , the Flag2-Sdh4 protein levels lowered to a greater extent ( 11% of iron-sufficiency levels ) . Neither PGK1 mRNA not Pgk1 protein levels were altered by changes in iron availability . These results indicated that Sdh4 translation efficiency defined as ( Sdh4/SDH4 ) / ( Pgk1/PGK1 ) decreased 3-fold under iron-deficient conditions ( Fig 1A ) . However , the enhanced reduction of the Sdh4 protein levels observed in iron deficiency could also be explained by a diminished Sdh4 protein stability . This alternative possibility impelled us to analyze the half-life of the Flag2-Sdh4 protein under iron-sufficient and iron-deficient conditions by using cycloheximide ( CHX ) as an inhibitor of translation . As shown in Fig 1B , under low iron conditions ( -Fe ) the Flag2-Sdh4 protein half-life ( ~41 min ) was approximately twice as long as the half-life obtained in high iron conditions ( +Fe: ~18 min ) . Therefore , the drop in the Sdh4 protein levels observed under low iron conditions was not due to Sdh4 destabilization . Instead by considering Sdh4 protein stability , we could conclude that Sdh4 translation efficiency decreases by 6-fold upon iron deficiency . To further test the SDH4 translational levels , we followed a second experimental approach . We obtained polysome profiles under high and low iron conditions , and then we determined the distribution of SDH4 mRNA among the different polysomal fractions . Our results showed that , under iron-sufficient conditions , SDH4 mRNAs were greatly associated with the heavy polysomal fractions , whereas SDH4 mRNA abundance shifted to the monosomal 80S peak under iron depletion ( Fig 1C and 1E ) . On the contrary , the polysome profile of the actin ACT1 mRNA , which was used as a non iron regulated control , was seen to be highly associated with polyribosomes under both +Fe and -Fe conditions ( Fig 1D and 1F ) . These results indicated that the association of multiple ribosomes to SDH4 mRNA , but not ACT1 mRNA , greatly diminished under iron-limited conditions . Altogether , these two experimental approaches strongly suggest that SDH4 mRNA is translationally inhibited under iron deficiency . SDH4 mRNA contains two AREs within its 3’-UTR . Since the degradation of SDH4 mRNA under iron deficiency depends on these AREs [1] , we wondered whether the negative regulation of SDH4 translation observed under low iron conditions was also ARE-dependent . For this purpose yeast sdh4Δ cells expressing a plasmid–borne copy of Flag2-SDH4 ( SDH4 ) or Flag2-SDH4 with four adenine to cytosine mutations introduced in its two AREs ( SDH4-AREmt ) were grown under low iron conditions for 7 h and translation efficiency was measured via the protein/mRNA ratio levels . In agreement with previous results [1] , when the AREs within SDH4 3’-UTR were mutated , the SDH4 mRNA levels displayed a 5-fold increase ( Fig 2A ) . However , the Sdh4 protein levels rose ~16-fold compared to the wild-type SDH4 , which resulted in a 3-fold increment in Sdh4 translation efficiency ( Fig 2A ) . These results suggest that the AREs within the 3’-UTR of SDH4 mRNA are involved in the negative regulation of the translation of SDH4 under iron deficiency . This result was corroborated by the polysomal profile obtained for the SDH4 and SDH4-AREmt mRNAs under iron-limited conditions . While wild-type SDH4 mRNA was closely associated with the 80S peak , which is commonly interpreted as a translational inhibition occurring at the initiation step , the mutation of the AREs provoked a shift of SDH4 mRNA toward the polysomal fractions , which is indicative of an amelioration of its translation ( Fig 2B ) . Once again , the ACT1 mRNA profile did not show any changes in its association with polysomes ( Fig 2C ) . We have previously established that SDH4 mRNA is highly associated with polysomes under iron sufficiency . So we wondered whether AREs could affect the translation of SDH4 mRNA under iron-repleted conditions . As shown in Fig 2D , the ARE mutations did not alter the SDH4 mRNA profile , in a similar way to the control ACT1 ( Fig 2E ) . Therefore , we conclude that an ARE-mediated inhibition of SDH4 translation takes place that is specific to iron-deficient conditions . In response to iron deficiency , the Cth2 protein binds the AREs in SDH4 mRNA and promotes its degradation [1] . Since these AREs constitute the cis regulatory element involved in the translational regulation of SDH4 mRNA by low iron , we decided to assess whether Cth2 was responsible for the iron-regulated repression of SDH4 translation . To test this hypothesis , we analyzed SDH4 translation efficiency via protein/mRNA levels in cells grown under iron-deficient conditions that coexpressed Flag2-SDH4 either with CTH2 , the empty vector , or with the TZF mutant CTH2-C190R that cannot bind mRNA . In order to exclude interferences from Cth1 , which plays a secondary role in AMD under iron deficiency , all Cth2-related experiments described in this work were performed in a cth1Δcth2Δ background expressing different versions of Cth2 protein , as described [1 , 2 , 10 , 11] . As previously reported [1] , in the absence of Cth2 ( cth2Δ ) or when Cth2 is not functional ( CTH2-C190R ) , the SDH4 mRNA levels increased ~1 . 5 to 1 . 8-fold ( Fig 3A ) , whereas the Sdh4 protein levels showed a more marked increment ( ~8 to 10-fold ) . Consequently under iron-deficient conditions , SDH4 translation efficiency augmented by 5 to 7-fold in the absence of a functional Cth2 protein . Then we determined the effect of Cth2 on the association of SDH4 mRNA with the different polysomal fractions . As shown in Fig 3 ( panels B and D ) , the association of SDH4 mRNA with the heavier polysomal fractions was enhanced in both the absence of CTH2 ( cth2Δ ) and the cells that expressed CTH2-C190R , grown under low iron conditions . Cth2 did not significantly alter the distribution profile of ACT1 mRNA among the different polysomal fractions ( Fig 3C and 3E ) . Taken together , these results demonstrate that SDH4 translational repression under iron deficiency is mediated by the Cth2 protein through the binding of its TZFs to the AREs in the 3’-UTR of SDH4 mRNA . The Cth2 protein binds to the ARE within its own transcript to promote decay in an auto-regulated mechanism that limits its own expression [13] . This negative feedback loop allows a rapid response when iron supplementation occurs , due to the more rapid decline in Cth2 protein levels and the recovery of crucial iron-dependent processes such as respiration [13] . To address whether the AREs within CTH2 mRNA were also involved in translational regulation , yeast cells that expressed either the Flag2-CTH2 allele or its ARE mutant version Flag2-CTH2-AREmt were grown under iron-deficient conditions , and the translation efficiency of CTH2 mRNA was analyzed . The CTH2 mRNA levels increased 1 . 3-fold in the cells that expressed CTH2-AREmt compared to wild-type CTH2 , while the protein levels increased 4 . 8-fold ( Fig 4A ) . Thus CTH2 mRNA translation efficiency was 3 . 6-fold better in the CTH2-AREmt cells than in the wild-type cells ( Fig 4A ) . Once again , these results were confirmed by a slightly stronger presence of CTH2 mRNA in heavy polysomal fractions and by a reduction in the monosomal fractions in those cells that expressed CTH2-AREmt versus CTH2 ( Fig 4B ) , while the ACT1 mRNA profile was similar in both strains ( Fig 4C ) . These results indicate that AREs act as a cis-regulatory element that is responsible for the translational repression of CTH2 mRNA under iron deficiency . To assess whether the Cth2 protein was the trans factor that regulated CTH2 mRNA expression at the translational level , we analyzed the translation efficiency of CTH2 mRNA in yeast cells that expressed either the Flag2-CTH2 or the Flag2-CTH2-C190R TZF mutant allele . In CTH2-C190R cells , the CTH2 mRNA levels augmented 2 . 8-fold compared to the wild-type CTH2 cells , whereas the protein levels increased 4 . 5-fold . If we consider that Cth2 protein stability was not altered by the C190R mutation ( S1 Fig ) , we could conclude that CTH2 translation efficiency was 1 . 6-fold higher when the Cth2 protein was unable to bind CTH2 mRNA ( Fig 5A ) . Consistently with these results , the CTH2 mRNA profile after polyribosome fractioning showed a stronger association with the heavier polysome fractions in CTH2-C190R than in CTH2 cells , while the ACT1 mRNA profile was similar in both strains ( Fig 5B and 5C ) . Taken together , these data strongly suggest that CTH2 mRNA undergoes an auto-translational repression in iron deficiency , which is mediated by the specific binding of the Cth2 protein , via its TZF domain , to the AREs of CTH2 transcript . After demonstrating that SDH4 and CTH2 transcripts , both well-established targets of the Cth2 protein at the mRNA decay level , were also repressed at the translational level by Cth2-binding to their AREs , we aimed to study if this Cth2-dependent translational repression was a phenomenon that could extend to other Cth2 target mRNAs . For this purpose , we analyzed the polyribosomal profiles of additional Cth2 target-mRNAs in yeast cells that lacked ( cth2Δ ) or expressed CTH2 . In order to more quantitatively address the association of these transcripts to ribosomes , the fractions that corresponded to monosomes and polysomes were pooled together prior to RNA extraction , and the mRNA association to each pool was determined . This analysis showed that the presence of CCP1 , HEM15 and WTM1 mRNAs in the pooled polysomal versus monosomal fractions was significantly stronger in the absence of Cth2 ( cth2Δ ) compared to the wild-type CTH2-expressing cells ( Fig 6A , 6B and 6C , respectively ) , while differences were minimal for the negative control ACT1 ( Fig 6D ) . In addition to this conjunct analysis , each fraction was separately extracted and independently analyzed , and the profiles obtained for these mRNAs qualitatively confirmed the increased association of CCP1 , HEM15 and WTM1 mRNAs with the polysomal fractions in the cells that lacked CTH2 compared to the CTH2-expressing cells ( S2A , S2B and S2C Fig , respectively ) . These profiles were similar to those obtained for SDH4 in this or previous experiments ( S2E and S2F Fig and Fig 3B ) , while the non-iron related ACT1 mRNA showed no Cth2-related differences in its association with polysomal fractions ( S2D Fig ) . This analysis confirmed the results obtained with the pooled fractions , and supported that , in addition to SDH4 , other previously described targets of Cth2 at the mRNA decay level , such as CCP1 , HEM15 and WTM1 , were also regulated at the translational level , and showed a Cth2-dependent inhibition of translation under iron-deficient conditions . Previous studies have shown that the deletion of the 89 amino-terminal aminoacids of the Cth2 protein , which contains the conserved CR1 region , greatly impaired its ability to promote targeted mRNA degradation without affecting its shuttling between the nucleus and the cytoplasm [9 , 10] . This finding led us to hypothesize that the CR1 region was important for the Cth2 recruitment of components of the mRNA degradation machinery [9] . To decipher which Cth2 domains were important for its role in targeted translational repression , we tested the translation efficiency of SDH4 mRNA under iron deprivation in the presence of different truncated versions of the Cth2 protein fused to GFP ( Fig 7A: GFP-Cth2ΔN89 , which lacks CR1; GFP-Cth2ΔN170 , which lacks CR1 and CR2; and GFP-Cth2ΔC52 , which lacks CR3 ) . Similarly to previous experiments , we used the cells that expressed full-length CTH2 ( GFP-CTH2 ) or lacked CTH2 as controls . We have previously shown that the amino-terminal fusion of GFP to Cth2 does not affect its function in mRNA decay and growth under iron-deficient conditions [10] . Furthermore , all the Cth2 truncated proteins used herein were able to shuttle between the nucleus and the cytoplasm ( [10]; S3 Fig ) . In the absence of CTH2 ( cth2Δ ) , we observed a 1 . 7-fold increase in the SDH4 mRNA levels compared to the cells that expressed GFP-CTH2 ( CTH2 ) , while the Sdh4 protein levels rose 2 . 9-fold ( Fig 7B ) . These data indicated that SDH4 translation efficiency was enhanced by 1 . 7-fold in the cth2Δ cells ( Fig 7B ) . When the cells that expressed CTH2ΔN89 or CTH2ΔN170 were analyzed , we observed an increase in SDH4 mRNA and Sdh4 protein abundance , which did not reach the levels achieved by the cells that lacked CTH2 ( Fig 7B ) . It was noteworthy that SDH4 translation efficiency slightly increased in CTH2ΔN89 cells , and reached levels close to cth2Δ cells in CTH2ΔN170 cells ( Fig 7B ) . To address the contribution of Cth2 NTD to SDH4 translational efficiency in more detail , we performed ribosomal profiles under low iron conditions in yeast cells that expressed CTH2ΔN170 compared to the wild-type CTH2 or cth2Δ cells ( Fig 7C ) . We observed that the SDH4 mRNA association with polysomes displayed by CTH2-ΔN170 cells exhibited an intermediate profile between the profile of the CTH2 and cth2Δ cells ( Fig 7C ) . These results firmly suggest that both the conserved CR1 and CR2 NTDs of Cth2 contribute to Sdh4 translation inhibition . We extended our study to Cth2 CTD , where an additional conserved CR3 region lies ( [9]; Fig 7A ) . As previously reported , the steady-state SDH4 mRNA levels were not altered when Cth2 CTD was deleted , which suggests that the CR3 region does not participate in mRNA decay ( [9]; Fig 7B: CTH2ΔC52 ) . To unequivocally determine whether Cth2 CTD contributed to SDH4 mRNA stability , we analyzed the half-life of SDH4 mRNA under iron-deficient conditions in cells that expressed wild-type CTH2 , CTH2ΔC52 or no CTH2 ( cth2Δ ) . The half-life of SDH4 mRNA in the CTH2ΔC52 mutant cells grown under iron deficiency conditions was similar to that observed in the wild-type CTH2 cells , and lower than that of the cth2Δ cells ( Fig 7D ) . Thus we can conclude that Cth2 CTD does not influence SDH4 mRNA stability . However , protein quantification suggests that SDH4 translation efficiency significantly augments in CTH2ΔC52 cells ( Fig 7B ) . To further address whether Cth2 CTD deletion led to improved SDH4 translation , we performed ribosome profiles . We observed that the association of SDH4 mRNA with the 80S monosomal peak weakened and shifted to heavier fractions in the yeast cells that expressed CTH2ΔC52 ( Fig 7E ) . Similarly to the CTH2ΔN170 cells , the CTH2ΔC52-expressing strain displayed an intermediate distribution between the CTH2 and cth2Δ cells ( Fig 7E ) . Taken together , these results suggest that Cth2 NTD is important for both SDH4 translational repression and decay , whereas CTD is involved in translation but not in mRNA decay . Translational inhibition and mRNA decay are intimately coupled processes . However , we showed here that the Cth2 CTD is only implicated in the translational repression , but not the mRNA turnover , of the SDH4 mRNA ( Fig 7 ) . To explore the contribution of the Cth2 CTD to the adaptation of yeast cells to iron depletion , we analyzed the growth of CTH2ΔC52 cells as compared to cells lacking or expressing wild-type CTH2 . As previously reported , CTH2 expression did not influence yeast growth under iron-sufficient conditions ( [1]; Fig 8A ) . Interestingly , the Cth2 CTD mutant showed a slight growth defect in a solid medium containing the Fe2+-specific chelator Ferrozine ( Fig 8A ) . In order to further test this observation , we analyzed the growth of these strains in liquid medium , both in iron-sufficient and iron-deficient conditions ( Fig 8B–8E ) . Again , no growth differences were observed under iron sufficiency ( Fig 8B and 8C ) . However , when cultivated in iron-deprived conditions , the CTH2ΔC52-expressing cells displayed an important growth defect , which was reflected by both the maximum optical density at 600 nm ( OD600nm ) and the μmax values achieved ( Fig 8D and 8E ) . Taken together , these results support a physiologically relevant role for Cth2 CTD under iron deficiency , probably due to its defect in translational repression .
In response to iron deficiency , yeast cells activate the expression of CTH2 , which encodes an RNA-binding protein that down-regulates multiple iron-dependent metabolic processes to optimize iron utilization [1] . When in the nucleus , Cth2 binds through its Cx8Cx5Cx3H-type TZFs to the AREs within the 3’-UTR of specific target mRNAs and promotes their decay by two described mechanisms [2] . In most cases , mRNA-bound Cth2 is exported to the cytoplasm where 5’ to 3’ degradation occurs [1 , 11] . Occasionally , Cth2 interferes with the polyadenylation site choice in its target transcripts and promotes the synthesis of extended mRNAs , which are rapidly degraded in the nucleus [9 , 10] . Several observations prompted us to propose that Cth2 could also regulate the translation efficiency of specific mRNAs . First , under iron-deficient conditions the mRNA levels of some Cth2 targets did not correlate with their corresponding protein amount [13] . Second , Cth2 genetically and physically interacted with Dhh1 RNA helicase , which is the yeast homolog of mammalian RCK/P54 translational repressor [11] . Third , in xrn1Δ , dcp1Δ and dcp2Δ mutant cells , Cth2 localized to processing-bodies , where transcripts temporarily incompetent for translation accumulate [33] . Here we have shown that Cth2 alters the fate of its target mRNAs by inhibiting their translation . This finding reinforces the importance of Cth2 in the repression of non-essential iron-consuming processes to facilitate the adaptation to iron scarcity . By using protein/mRNA ratio measurements and by determining the mRNA association to different fractions of a polyribosome profile , we have concluded that SDH4 mRNA translation greatly diminishes under iron-deficient conditions . We have observed that , under iron starvation , SDH4 mRNA strongly associates to the monosome 80S peak and is scarce in the polysomal fractions ( Fig 1 ) . This profile is commonly interpreted as a translational repression that occurs in the initiation step , the most commonly regulated step in translation [34–38] . In principle , the shift of SDH4 mRNA from polysomes to the 80S peak could be a consequence of the mild , but highly reproducible , global arrest of translation initiation that we have observed upon iron deficiency ( Fig 1 , 83% of polysomes in iron sufficiency versus 72% of polysomes in iron deficiency ) . However , this was not the case because the percentage of SDH4 mRNA association to the heavy fractions of polysomes lowered from 79% in iron-sufficient conditions to 48% in iron deficiency , which represents a 3-fold greater decrease than the global profiles . On the other hand , ACT1 mRNA changes its polysomal association from 93% to 82% , which represents a slight decrease that is quite correlative to the mild global change in polysome levels . These results strongly suggest that a specific translational regulation of SDH4 , but not ACT1 , mRNA occurs in response to iron deficiency . In mammals , AREs participate in translation repression through the action of ARE-binding proteins such as TIA-1 and TIAR , and in translation activation via RNA-binding proteins of the ELAV family such as HuR [39–42] . More recently , Cth2 mammalian homolog TTP has been shown to repress the translation of ARE-containing transcripts with the help of the DEAD-box RNA helicase RCK/P54 , or by entering in competition for ARE-binding with HuR [17 , 25] . Therefore , we decided to investigate whether the mechanisms that regulate SDH4 mRNA translation , in an iron bioavailability-dependent manner , actually involved the AREs within its 3’-UTR . Our dual assay indicated that , under iron-deficient conditions , the mutations in the AREs of SDH4 mRNA enhanced its translation efficiency ( Fig 2 ) . Interestingly , the ARE regulation of SDH4 translation was not observed under iron-sufficient conditions , where CTH2 expression is not detectable [1]; Fig 2 ) . These observations strongly suggested that Cth2 could be the regulatory factor implicated in the SDH4 translational regulation under iron scarcity . Once again the measurement of the protein/mRNA levels and polysome profiles indicated that SDH4 translation improved in the absence of Cth2 or in the presence of a TZF-mutant Cth2 protein ( Fig 3 ) . Further analyses showed that the association with polysomes of other Cth2 mRNA targets , which participate in iron-dependent processes ( CCP1 , HEM15 , WTM1 and CTH2 itself ) , increased when CTH2 was not expressed ( Figs 5 and 6 ) . Altogether , these results suggest that Cth2 exerts both a general mRNA decay and translational repression of ARE-containing mRNAs that facilitate the adaptation to iron scarcity . Strikingly , the SDH4 mRNA still shows a high association to the 80S monosome peak under iron-deficient conditions despite the lack of ARE ( Fig 2B ) or Cth1 and Cth2 proteins ( Fig 3B and 3D ) . These results suggest that other currently unknown regulatory factors independent of Cth1 and Cth2 , and functioning through cis elements different from the AREs , could be influencing the translation of the SDH4 mRNA . CTH2 negative feedback regulation deserves special attention . We have previously reported that the Cth2 protein binds to an ARE within its own transcript and promotes its decay [13] . Now we know that CTH2 auto-regulation also occurs at the translational repression level . This fine-tuned adjustment of Cth2 levels is especially relevant when yeast cells return to iron-sufficient conditions and a rapid shut-off of Cth2 protein becomes peremptory to reactivate Cth2-repressed processes , such as mitochondrial respiration , which are necessary for an optimal resumption of growth [13] . Yeast CTH1 mRNA also contains functional AREs within its 3’-UTR that allow degradation via the Cth1 and Cth2 proteins [13] . In mammals , TTP also limits its own expression through an ARE-dependent feedback-regulatory loop at both the mRNA degradation and translational repression levels , which facilitates a rapid return to a resting state upon the removal of the activation signal [25 , 30 , 31] . Other TTP-family members , such as TIS11b and TIS11d , also possess AREs within the 3’-UTR of their respective mRNAs , and auto- and cross-regulate their expression in mouse embryonic stem cells [43] . It has been proposed that the interconnections between regulators that act on their own and on each other’s mRNAs would allow for an increased control and coordination of the expression of a broader set of mRNAs , which would thus permit faster metabolic adaptations in response to diverse environmental signals [44] . The Cth2-mediated regulation that we describe herein constitutes a novel example of translational regulation of iron metabolism in eukaryotes , which recalls the IRE/IRP system described in mammals . Although both regulatory networks act at the post-transcriptional level , the result of the IRE/IRP system depends on the mRNA region to which the corresponding IRP protein binds , with the 5’-UTR involved in translational inhibition and the 3’-UTR in mRNA stabilization ( reviewed in [45–47] ) . In the case of the ARE/Cth2 system there is only one type of cis element situated in the 3’-UTR region of its target mRNAs [1] . As we show herein , Cth2 binding to AREs can mediate both translational repression and mRNA decay . Very little is currently known about the mechanisms by which Cth2 regulates both processes . Transcript half-life measurements have shown that the conserved CR1 within Cth2 NTD is important for targeted mRNA turnover , probably due to its implication in recruiting the components of the mRNA decay machinery [9] . Moreover , lack of Cth2 NTD leads to the formation of extended transcripts that are quickly degraded [9] . We decided to investigate which Cth2 domains were necessary for either mRNA turnover or translational inhibition . Our analysis showed that Cth2 NTD was important for both mRNA degradation and translation inhibition , while CTD was involved in translation regulation , but was dispensable for mRNA decay ( Fig 7 ) . Importantly , the results obtained with the Cth2 CTD mutant suggest that the role of Cth2 in translational repression is physiologically relevant , which greatly supports the intrinsic importance of Cth2 function as a translational regulator . Transcript translation and degradation are intimately related processes , with mRNA decay generally occurring as a consequence of translational repression [48 , 49] . For instance , the decapping activators Dhh1 slows down the movement of ribosomes on mRNAs during the elongation phase of translation , prior to the activation of decapping and independently of it [50 , 51] . However , there are also examples where both processes have been separated . For example , a distinct role of some ARE-binding proteins in translation inhibition , but not in mRNA decay , has been established [52] . In the case of Cth2 , we currently do not know which process takes place first , activation of decay or translational repression . Our results indicate that distinctive partner/s may interact with Cth2 CTD to regulate translation , while other common factors would possibly be implicated in both decay and translation through interactions with Cth2 NTD . Further work is necessary to identity Cth2 trans-acting factors , to distinguish their general regulatory function from its Cth2-dependent role , and to characterize the initial events that lead to Cth2 repression of gene expression .
BY4741 wild-type ( MATa his3Δ1 leu2Δ0 met15Δ0 ura3Δ0 ) and sdh4Δ mutant ( BY4741 sdh4::KanMX4 ) strains were obtained from Research Genetics . cth1Δcth2Δ ( BY4741 cth1::KanMX4 cth2::HisMX6 ) and cth1Δcth2Δsdh4Δ ( BY4741 cth1::KanMX4 cth2::HisMX6 sdh4::hphB ) mutant strains have been previously described [1] . For the RNA , protein and polyribosome profile analyses , yeast cell precultures transformed with specific plasmids ( listed in S2 Table ) were incubated overnight at 30°C in synthetic complete medium lacking specific requirements ( SC minus ) . They were then reinoculated at OD600nm = 0 . 2–0 . 4 and incubated 7 h in SC minus supplemented with 10 μM ferrous ammonium sulfate or FAS ( iron-sufficient conditions: +Fe ) or SC minus supplemented with 100 μM of the Fe2+-specific chelator bathophenanthroline disulfonate or BPS ( iron-deficient conditions: -Fe ) to exponential phase . For fluorescence microscopy , yeast cells were cultivated in SC-Ura supplemented with 100 μM BPS to early exponential phase . For growth assays in liquid media , yeast cells were inoculated in 96-well plates at an OD600nm of 0 . 1 in 260 μL of liquid SC-Ura medium without ( +Fe ) or with 700 μM Ferrozine ( -Fe ) , and the OD600nm was determined in a Spectrostar Nano absorbance microplate reader ( BMGLabtech ) every 30 min for 2–3 days at 28°C . μmax is the maximum specific growth rate ( h−1 ) and was calculated from each condition by directly fitting OD600nm measurements versus time to the reparameterized Gompertz equation [53] , ln ( ODt/OD0 ) = D * exp {-exp[ ( ( μmax*e ) /D ) * ( λ - t ) + 1]} , where OD0 is the initial OD and ODt is the OD at time t; D = ln ( OD∞/OD0 ) is the OD value reached with OD∞ as the asymptotic maximum , μmax is the maximum specific growth rate ( h−1 ) , and λ is the lag phase period ( h ) . Growth assays in solid media ( 1 . 5% agar ) were performed as previously described [54] . Cells were cultivated to exponential phase , diluted to an OD600nm of 0 . 1 and then spotted directly and after 1:10 and 1:100 dilutions in SC-Ura ( +Fe ) or SC-Ura with 700 μM Ferrozine ( -Fe ) . Solid media were incubated at 30°C and then photographed . Total yeast RNA isolation , reverse transcription and quantitative real-time PCR ( RT-qPCR ) were performed as previously described [55] . An oligo-dT primer was used for the reverse transcription , and specific primer pairs were used for the RT-qPCR ( listed in S1 Table ) . The data and error bars represent the relative average and standard deviations of at least two independent biological samples . For mRNA half-life determination , yeast cells were grown overnight in SC-Ura-Leu-raffinose ( 2% [w/v] raffinose , no glucose ) and were reinoculated in SC-Ura-Leu-galactose ( 2% [w/v] galactose , no glucose ) supplemented with 100 μM BPS at 30°C until exponential growth phase ( OD600nm of 0 . 4–0 . 6 , approximately 4 h ) . Then , glucose was added to a final concentration of 4% [w/v] to inhibit the transcription of the PGAL1-SDH4 fusions . After glucose addition , aliquots were isolated at successive times ( 0 , 5 , 10 and 15 min ) , total RNA was extracted and cDNA was obtained as described above with one modification , the use of random primers instead of oligo-dT . The cDNA was then analyzed by RT-qPCR using specific primer pairs ( listed in S1 Table ) . SDH4 mRNA levels were normalized to PGK1 mRNA levels . The mRNA half-life was determined from three independent experiments . Tailed t-student tests were applied to evaluate statistical significance . Total protein extracts were obtained by using the alkali method [56] . Equal amounts of protein were resolved in 10% SDS-PAGE gels and transferred to nitrocellulose membranes . Ponceau staining was used to assess protein transfer . Flag2-Sdh4 and Flag2-Cth2 were detected using a horseradish peroxidase ( HRP ) -conjugated anti-Flag antibody ( A8592; Sigma ) . Anti-Pgk1 primary antibody ( 22C5D8; Invitrogen ) and HRP-labeled secondary anti-mouse antibody ( GE Healthcare Life Sciences ) were used to determine the Pgk1 protein levels as loading control . ECL Select Western blotting detection kit was used ( GE Healthcare Life Sciences ) . Immunoblot images were obtained in an ImageQuant LAS 4000 mini Biomolecular Imager ( GE Healthcare Life Sciences ) and specific signals were quantified with ImageQuant TL analysis software ( GE Healthcare Life Sciences ) . Flag2-SDH4 translation efficiency was calculated as: ( Flag2-Sdh4 protein / Flag2-SDH4 mRNA ) / ( Pgk1 protein / PGK1 mRNA ) and Flag2-CTH2 translation efficiency was calculated as: ( Flag2-Cth2 protein / Flag2-CTH2 mRNA ) / ( Pgk1 protein / PGK1 mRNA ) . For protein half-life determination purposes , cells were grown exponentially in SC-Ura supplemented with 10 μM FAS and in SC-Ura supplemented with 100 μM of BPS for 7 h as described above . Protein translation was stopped by adding cycloheximide ( CHX ) to a final 50 μg/mL concentration . The Flag2-Sdh4 , Flag2-Cth2 and Flag2-Cth2-C190R protein levels were determined at successive times ( 0 , 5 , 15 , 30 and 60 min ) after adding CHX . A nonspecific anti-FLAG band was used as loading control in Flag2-Sdh4 half-life determination . Cells were grown to the exponential phase in SC minus the specific requirements and were supplemented with 100 μM of BPS for 7 h . Preparation of cells and polysome gradients were performed as described by Garre et al . [57] , with some modifications . A culture volume that corresponded to an OD600nm of 60 was chilled for 5 min on ice in the presence of 0 . 1 mg/mL CHX . Cells were harvested by centrifugation at 6000 × g for 4 min at 4°C and washed twice with 1 mL of lysis buffer ( 20 mM Tris-HCl , pH 8 , 140 mM KCl , 5 mM MgCl2 , 0 . 5 mM dithiothreitol , 1% Triton X-100 , 0 . 1 mg/mL CHX , and 0 . 5 mg/mL heparin ) . Cells were resuspended in 700 μL of lysis buffer , a 0 . 5-mL volume of glass beads was added , and cells were disrupted by vortexing 8 times for 30 s with 30 s of incubation on ice in between . Lysates were cleared by centrifugation at 5000 rpm for 5 min at 4°C , after which the supernatant was recovered and centrifuged at 8000 rpm for 5 min at 4°C . Finally , glycerol was added to the supernatant at a final concentration of 5% and extracts were frozen in liquid nitrogen and stored at -70°C . Samples of 8 . 5 absorbance at 260 nm ( A260nm ) units were loaded onto 5–50% sucrose gradients and were separated by ultracentrifugation for 2 h 40 min at 35000 rpm in a Beckman SW41 rotor at 4°C . Gradients were then fractionated by isotonic pumping of 60% sucrose from the bottom and either eleven 1 mL-samples or twenty-two 0 . 5 mL-samples were recovered . The polysomal profiles were monitored by online UV detection at 260 nm ( Density Gradient Fractionation System; Teledyne Isco , Lincoln , NE ) . For the RNA analyses of the polysomal fractions , 8 μL of mixed lys and spo mRNAs at 3 ng/ μL from Bacillus subtilis were added to 200 μL of each fraction before extraction . RNA was extracted using SpeedTools Total RNA Extraction kit ( Biotools B&M Labs ) with the rDNAse treatment after the RNA elution step . For the unified monosomal and polysomal fractions , equal volumes of each fraction were combined in a final 200 μL volume and RNA was extracted with the same kit . Specific mRNAs were analyzed by RT-qPCR using specific primer pairs ( listed in S1 Table ) and represented as a percentage of total . All the values were normalized with spiked-in mRNA levels of B . subtilis lys and spo . Yeast cells transformed with GFP-containing plasmids were visualized in an Axioskop 2 fluorescence microscope ( Zeiss ) . Images were captured with a SPOT camera ( Diagnostic Instruments ) . | Iron is essential for eukaryotes because it is required for many fundamental processes such as DNA replication , protein translation or respiration , but it is very insoluble and can , therefore , easily go scarce . For this reason , eukaryotic cells have developed adaptive responses to iron deficiency . Under iron limitation conditions , the yeast Saccharomyces cerevisiae induces the expression of Cth2 , a protein with tandem zinc fingers that binds to adenine and uracil-rich sequences in the 3’-UTR of specific mRNAs related to iron metabolism , promoting their degradation . Here we show that Cth2 inhibits the translation of ARE-containing mRNAs , including SDH4 , WTM1 , HEM15 and CCP1 , which encode proteins that contain iron or participate in iron-dependent pathways , and CTH2 itself , which is subjected to an autoregulatory loop that controls its expression . We also dissected different domains of Cth2 that are differentially involved in mRNA decay and translational inhibition . The involvement of Cth2 in translational control reinforces the importance of this ARE-binding protein as a post-transcriptional regulator of the iron response in yeast . By acting at different steps in the life of specific mRNA targets , Cth2 action ensures yeast cells a proper distribution of iron by optimizing its utilization in essential processes . | [
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... | 2018 | Yeast Cth2 protein represses the translation of ARE-containing mRNAs in response to iron deficiency |
Annotating and interpreting the results of genome-wide association studies ( GWAS ) remains challenging . Assigning function to genetic variants as expression quantitative trait loci is an expanding and useful approach , but focuses exclusively on mRNA rather than protein levels . Many variants remain without annotation . To address this problem , we measured the steady state abundance of 441 human signaling and transcription factor proteins from 68 Yoruba HapMap lymphoblastoid cell lines to identify novel relationships between inter-individual protein levels , genetic variants , and sensitivity to chemotherapeutic agents . Proteins were measured using micro-western and reverse phase protein arrays from three independent cell line thaws to permit mixed effect modeling of protein biological replicates . We observed enrichment of protein quantitative trait loci ( pQTLs ) for cellular sensitivity to two commonly used chemotherapeutics: cisplatin and paclitaxel . We functionally validated the target protein of a genome-wide significant trans-pQTL for its relevance in paclitaxel-induced apoptosis . GWAS overlap results of drug-induced apoptosis and cytotoxicity for paclitaxel and cisplatin revealed unique SNPs associated with the pharmacologic traits ( at p<0 . 001 ) . Interestingly , GWAS SNPs from various regions of the genome implicated the same target protein ( p<0 . 0001 ) that correlated with drug induced cytotoxicity or apoptosis ( p≤0 . 05 ) . Two genes were functionally validated for association with drug response using siRNA: SMC1A with cisplatin response and ZNF569 with paclitaxel response . This work allows pharmacogenomic discovery to progress from the transcriptome to the proteome and offers potential for identification of new therapeutic targets . This approach , linking targeted proteomic data to variation in pharmacologic response , can be generalized to other studies evaluating genotype-phenotype relationships and provide insight into chemotherapeutic mechanisms .
Pharmacogenomics aims to identify clinically actionable markers associated with response or toxicity; for oncology , evaluating genotype-phenotype relationships is particularly important because non-response and adverse events associated with chemotherapy can be life-threatening . Drug response and toxicity are thought to be multi-genic traits requiring whole genome studies to capture the most relevant variants . To complement clinical data and enhance discovery of genetic variants associated with sensitivity to drugs using a whole genome approach , we and others ( reviewed by Wheeler and Dolan [1] ) have developed cell-based models using International HapMap lymphoblastoid cell lines ( LCLs ) . The genetic and expression environment for these cells has been well characterized thus allowing for genome-wide association studies ( GWAS ) and functional follow-up studies . Genetic variants associated with a given chemotherapeutic discovered in the LCL pharmacogenomic model have been replicated in clinical trials , arguably the most relevant system for biomedical science [2] , [3] , [4] , [5] , [6] . In addition to their value in pharmacogenomics discovery [7] , [8] , [9] , [10] , [11] , LCLs have had broad utility as a discovery tool for genetic markers associated with many functional phenotypes , including: gene expression [12] , [13] , [14] , [15] , [16]; modified cytosines [17]; variation in mRNA decay rates across individuals [18]; DNase hypersensitivity [19]; and baseline micro RNA levels [20] . In addition , the LCL model has been used to identify genetic markers of inflammatory cell death [21] , bipolar disorder [22] , and response to serotonin reuptake inhibitors [23] , [24] . Therefore , incorporating protein expression information into an existing dataset of genetic , epigenetic , mRNA expression , and drug sensitivity has the potential to identify novel candidates and mechanisms relevant to pharmacologic traits . Previously , we reported that SNPs associated with inter-individual variation in cytotoxicity of chemotherapeutic agents in LCLs are enriched in expression quantitative trait loci ( eQTLs ) and separately , enrichment was observed for eQTLs associated with ten or more target genes [25] . SNPs that overlapped between preclinical LCL studies and outcomes of patients treated with the same drug were also enriched in eQTLs [2] . An implicit assumption in these analyses and studies of other complex traits is that mRNA transcript abundances are a suitable proxy measurement for their corresponding protein levels . However , recent data has demonstrated poor overall correlations between mRNA and protein expression [26] , [27] , [28] , [29] , [30] . To investigate the role of genomics in protein expression and the role protein expression plays in altering pharmacologic responses , we employed the micro-western array ( MWA ) [31] , a method that is approximately 1000-fold more sensitive and has an ∼100-fold greater dynamic range than standard mass spectrometry methods and requires ∼200-fold less sample and antibody than standard immunoblotting methods [32] , [33] . After screening 4 , 366 previously unvalidated antibodies targeting 1 , 848 transcription factors ( TFs ) and 200 well-validated antibodies targeting cell signaling proteins , we used MWAs and reverse phase protein arrays ( RPPAs ) to collect protein data regarding 441 protein isoforms from 68 HapMap Yoruba ( YRI ) LCLs . Baseline protein levels were evaluated for their correlations with cellular sensitivity to cisplatin and paclitaxel , two of the most widely-used and successful chemotherapeutics worldwide that are mechanistically distinct [34] , [35] , [36] . The measurement of proteins in HapMap LCLs is of great value to complement the extensive publicly available genetic information already available on these cell lines . Although LCLs are not tumor cells , upon transformation they are likely to have changes in pathways that control cell cycle and cell proliferation , which are relevant pathways for anti-cancer drugs . Furthermore , we identified genetic variants associated with chemotherapeutic sensitivity that acted through their effect on protein levels . We observed an enrichment of pQTLs in genome variants associated with pharmacologic phenotypes . We combined this information to identify proteins relevant for pharmacologic phenotypes through multiple independent SNPs throughout the genome .
Prior to our global analysis , a pilot study consisting of three independent biological replicates of six cell lines demonstrated significant variation not only among protein levels from different individuals , but also among cells thawed and propagated independently from the same individual . Based on a significant thaw effect explaining 3 . 75% of global protein expression variation ( p = 0 . 01 , F test ) , we measured baseline , steady-state protein levels from three independent thaws ( thawed simultaneously ) from each of 68 unrelated YRI LCLs to have a more accurate estimate of inter-individual variation in protein expression . These measurements were evaluated with both fixed effect ( by averaging the three thaws ) and mixed effect ( by incorporating a random thaw effect per individual ) models . Mixed effect modeling ( MEM ) allowed us to gain additional power from multiple measurements compared with simply averaging across the biological replicates in a linear model ( Figure 1a ) . Relationships identified by fixed effect that had conflicting trends ( i . e . positive and negative associations ) across biological replicates were more likely to be false positives ( Figure 1b ) than the observations that were reproducible by MEM ( across biological replicates ) ( Figure 1c ) ; we therefore considered the MEM to be the more robust approach and used this method for all subsequent estimates of protein-drug associations . Cell growth inhibition and caspase 3/7 activation were measured following treatment of 68 unrelated YRI LCLs with cisplatin ( 5 µM ) or paclitaxel ( 12 . 5 nM ) . Notably , the correlation between cytotoxicity and apoptosis was greater for paclitaxel ( r2 = 0 . 35 ) than cisplatin ( r2 = 0 . 04 ) , indicating that apoptotic cell death was a larger contributor to paclitaxel-mediated cell growth inhibition compared with cisplatin ( Figure S1 ) . We also assessed the effect of date of cell thaw on cellular phenotypes and found a significant correlation across two independent thaws ( Figure S2; p<0 . 0001 and r2>0 . 28 for cytotoxicity , p<0 . 003 and r2>0 . 38 for apoptosis ) . From a starting pool of 4 , 366 antibodies , 198 antibodies producing a single predominant signal at the predicted molecular weight were carried forward for population-level quantification with the RPPA approach and 243 antibodies that displayed at least one band the size of the targeted protein isoform of interest with a signal-to-noise ratio ≥3 ( but additional bands ) were selected for subsequent population-level quantification by MWAs . We quantified the expression of 441 proteins across the same set of 68 individual LCLs for which we measured responses to chemotherapeutic agents . At an FDR of 20% , 64 proteins were associated with one or more of the four drug phenotypes . At p<0 . 05 , 52 and 60 protein levels were associated with paclitaxel-induced apoptosis and cytotoxicity , respectively , and 47 and 39 proteins were associated with cisplatin-induced apoptosis and cytotoxicity , respectively . Table S2 details these nominal associations for each phenotype and Table 1 highlights the top three associations for each phenotype . We compared the overlap between the two drugs and identified four proteins that were unique to the apoptotic pathway including CDKN2B , PDK1 , TFB1M and ZNF132 . EP300 was the only protein exclusively associated with cytotoxicity for both drugs . This observation implies that loss of cell viability in response to these two drugs occurs through distinct mechanisms . Using hierarchical clustering of the drug-protein effect sizes , seven significant clusters were defined by permutation analysis ( p<0 . 001 ) ( Figure 2a ) . We were unable to identify any significantly enriched pathways due to the limited and biased background set of proteins evaluated; however , we did observe proteins of similar function within the clusters . Protein levels in cluster one ( Figure 2b ) were associated with increased resistance to both drugs when measured for either phenotype . Proteins in this cluster included many known metabolism-regulating proteins , DNA damage response factors , proteins associated with innate immune response , and transcription factors associated with various stages of developmental biology . Metabolism-regulating proteins included mTor , p70S6K ( T421/S424 ) , Gab1 ( Y627 ) , GSK3beta , and ONECUT2 . DNA damage-related proteins in cluster one included apoptosis antagonizing transcription factor ( AATF ) and structural maintenance of chromosomes protein 1A ( SMC1A ) . Proteins with known associations to immune response included several ubiquitin ligases such as TRIM13 and TRIM26 . Protein levels in cluster 3 ( Figure 2c ) were associated with increased cellular sensitivity to both cisplatin and paclitaxel phenotypes and included many proteins related to calcium signaling: phospholipase C gamma 2 ( PLCG2 ) , c-Src ( SRC ) and focal adhesion kinase ( FAK ) . Other proteins in cluster three included the tumor suppressor p15ink4b ( CDKN2B ) , estrogen receptor beta ( ESR2 ) , beta actin ( BACT ) , alpha tubulin ( TUBA ) , and several transcription factors including c-MYC ( MYC ) , Hairless homolog ( HR ) , H6 family homeobox 1 ( HMX1 ) , and ETS-related transcription factor Elf-4 ( ELF4 ) . Protein levels in cluster 7 ( Figure 2d ) were associated more strongly with cellular sensitivity/resistance to drug cytotoxicity as compared with drug-induced apoptosis . Drug-induced cytotoxicity is a broad phenotype that includes cellular processes such as necrosis , cell death through apoptotic and non-apoptotic pathways , cell cycle arrest , and damaged cells undergoing DNA repair [37] , whereas caspase 3/7 activation represents a specific process of cell death . Upon evaluation of all proteins with a genome-wide significant pQTL , we identified one protein that was also associated with paclitaxel-induced apoptosis . The trans pQTL on chromosome 16 , rs6834 , was significantly correlated ( p = 2 . 66×10−15 ) with death inducer-obliterator 1 ( DIDO1 ) protein levels ( Figure 3a ) . DIDO1 was in cluster 3 ( Figure 2c ) , indicating that increased baseline levels conferred greater cellular sensitivity to both chemotherapeutic agents . DIDO1 protein levels were significantly correlated with paclitaxel-induced apoptosis ( p = 0 . 01 r2 = 0 . 02; Figure 3b ) . However , the DIDO1 pQTL was not significantly associated with paclitaxel-induced apoptosis ( p = 0 . 25 , Figure 3c ) . Despite the lack of statistical significance ( likely because of small sample size ) , the directionality was consistent with the observed protein relationship: cells containing two C alleles had lower levels of DIDO1 and lower paclitaxel-induced caspase 3/7 activation . DIDO1 mRNA levels were not associated with paclitaxel apoptosis ( p>0 . 05 ) , suggesting that this relationship was protein-specific . Using RNA interference , we performed gene knockdowns in YRI LCLs and examined the effect of knockdown on paclitaxel-induced cytotoxicity and apoptosis . Three different LCLs were nucleofected with siRNA against DIDO1 . Although knockdown levels varied considerably , the maximal degrees of protein knockdown observed for 24 or 48 hours in 18522 , 18853 , and 19192 , were 20% , 48% , and 59% , respectively . When we pooled data from all cell lines and experiments using a MEM , knockdown of DIDO1 resulted in a significant ( p = 0 . 005 ) decrease in paclitaxel-induced caspase activity . On average , paclitaxel-induced apoptosis was decreased by 11 . 9% in cells following knockdown of DIDO1 ( Figure 3d ) . Using the pQTLs and eQTLs ( unadjusted p<10−4 ) from the genes included in our protein dataset , we evaluated enrichment with paclitaxel and cisplatin-induced cytotoxicity and apoptosis associated SNPs at unadjusted p<10−3 ( Figure 4 ) . For cisplatin , only the apoptosis phenotype demonstrated pQTL enrichment ( p<0 . 001 ) ( Figure 4a , 4b , left panels ) . Conversely , both paclitaxel phenotypes demonstrated pQTL enrichment ( Figure 4c , 4d ) . When evaluating eQTLs , only cisplatin cytotoxicity showed enrichment for eQTLs ( Figure 4b ) . However , when evaluating all expressed genes , eQTLs showed enrichment for all drugs and phenotypes except for cisplatin-induced apoptosis ( data not shown ) . Using both cell growth inhibition and apoptosis as cellular phenotypes , we identified pQTLs ( defined at p<10−4 ) associated with these phenotypes at p<0 . 001 . From that overlap of pQTLs , we then analyzed the relationship between target protein levels and the respective drug phenotype ( p≤0 . 05 ) ( Figure 5 ) . Overlapping GWAS signals identified five proteins for cisplatin phenotypes and 21 proteins for paclitaxel phenotypes ( Table S3 ) . For each phenotype , we also identified individual lists of proteins-pQTL pairs that both associate with cisplatin or paclitaxel phenotypes ( Table S4 ) . For cisplatin GWAS , there were 79 pQTLs targeting 27 proteins for cytotoxicity and 169 pQTLs targeting 27 proteins for apoptosis . For paclitaxel GWAS , there were 107 pQTLs targeting 38 proteins for cytotoxicity and 119 pQTLs targeting 42 proteins for apoptosis . Interestingly , the protein SRC was implicated through all four phenotypes . We prioritized proteins for functional studies using the apoptosis relationship for paclitaxel and the cytotoxicity relationship for cisplatin . Among the five proteins whose baseline expression levels associated with cisplatin cytotoxicity and apoptosis , we found structural maintenance of chromosomes 1A ( SMC1A ) to have the most significant relationship with cytotoxicity ( p = 0 . 005 , r2 = 0 . 039 ) ( Figure 6a and 6b ) . We therefore selected it for further functional validation . SMC1A did not associate with either cisplatin phenotype at the mRNA level suggesting that this was a protein-specific relationship . Because more proteins were associated with paclitaxel-mediated apoptosis and cytotoxicity phenotypes , we prioritized functional follow-up based on a combination of p-values and q-values ( to correct for multiple hypothesis testing ) . At p<0 . 005 , five proteins were significantly associated with paclitaxel-induced apoptosis . Zinc finger protein 569 ( ZNF569 ) ( Figure 6c , 6d ) had the lowest association q value . At the mRNA level , ZNF569 had a weak correlation with paclitaxel-induced apoptosis ( p = 0 . 04 , r2 = 0 . 06 ) , but no relationship with paclitaxel-induced cytotoxicity . Table 2 lists the pQTLs that implicated SMC1A with the two cisplatin phenotypes and ZNF569 with the two paclitaxel phenotypes . We observed a different set of SNPs associated with each protein-drug pair that also associated with either apoptosis or cytotoxicity ( Table 2 ) . Because independent pQTLs associated with the drug-induced phenotypes , we functionally validated the relationship of these proteins with their respective drug-induced phenotypes . We selected three LCLs ( 18502 , 19138 , 19201 ) with mid to high protein expression and performed siRNA nucleofection . We assessed knockdown at 24 and 48 hours post nucleofection . Knockdown of SMC1A protein levels varied across the cell lines; we did not observe more than 57% , 71% , and 62% protein knockdown for 18502 , 19138 , and 19201 , respectively , for either time point . Using a MEM to examine the effect across cell lines , we determined that knockdown of SMC1A resulted in a 19% increase in apoptosis ( p = 0 . 0002 ) and a 10 . 4% decrease in cell survival ( p = 0 . 009 ) in response to cisplatin ( Figure 7a ) . Knockdown of ZNF569 protein levels varied across the cell lines , but we observed no more than 45% , 58% , and 54% protein knockdown across 18502 , 19138 , and 19201 , respectively , for either time point . Using a MEM to combine the effect across cell lines , knockdown of ZNF569 resulted in a 9 . 9% average reduction in apoptosis ( p = 0 . 002 ) and a 26 . 8% increase in cell growth inhibition ( p = 0 . 0001 ) ( Figure 7b ) in response to paclitaxel . Because growth rate has been previously identified as a heritable trait that is relevant in pharmacologic studies , we evaluated the relationship between steady state protein levels and intrinsic growth rate [38] for the proteins measured . Approximately 10% ( 45/441 ) of the proteins were correlated with growth at p<0 . 05 ( Table 3 ) . Notably , SMC1A protein levels were significantly correlated with growth rate ( p = 0 . 0007 ) , whereas ZNF569 protein levels were not ( p>0 . 05 ) ( Figure S3 ) . When we adjusted for growth rate , the association of SMC1A protein levels with cisplatin phenotypes was no longer significant ( p>0 . 05 ) .
In this study , we evaluated 4 , 366 antibodies targeting 2 , 048 unique proteins . From this set , we identified antibodies targeting 441 protein isoforms expressed at baseline in LCLs and quantified them across three biological samples from 68 YRI LCLs . The use of multiple biological samples allowed us to implement mixed effects modeling to increase the robustness of our observations . Many protein expression levels were correlated with sensitivity to two cellular phenotypes ( cytotoxicity and apoptosis ) of two chemotherapeutic agents: paclitaxel and cisplatin . We validated one such finding through knockdown of DIDO1 in three LCLs , which resulted in a decrease in paclitaxel-induced apoptosis . Quantitative trait loci for pharmacologic phenotypes were compared to quantitative trait loci for protein expression to better understand the functional significance of genetic variants contributing to inter-individual variability in drug response . For each drug , we identified overlapping and unique sets of genetic variants associated with protein expression that were also correlated with drug-induced apoptosis and cytotoxicity . We further validated two such proteins through gene knockdown and concomitant modulation of cellular sensitivity to drug treatment: SMC1A levels were associated with resistance to cisplatin treatment , and ZNF569 levels were associated with sensitivity to paclitaxel treatment . This study illustrates the utility of applying a highly-sensitive , novel , antibody-based technology to simultaneously measure many proteins across a large set of individuals . Using this method , we identified hundreds of novel genome loci that uniquely influence the expression of proteins that ultimately influence the sensitivity of cells to chemotherapeutic agents through both caspase 3/7 activation and other pathways leading to loss of cell viability . We evaluated protein expression in the International HapMap LCLs because these samples have previously been used for many studies relating genetics to gene expression [14] , [16] , [39] and cellular phenotypes [1] , thus allowing us to perform comprehensive studies of genetics , protein expression , and pharmacology . LCLs are immortalized B-lymphocytes and , as a result , represent “non-cancerous” cells that may provide us with important protein targets for ameliorating bone marrow suppression . However they also have some of the pathways relevant to anti-cancer drugs . We specifically chose the YRI population because of their greater genetic diversity relative to other populations . We expect that this data will have wide applicability to other genetic and pharmacological studies because of the important addition of protein levels to other studies . Whereas polymorphisms in coding regions that affect amino acid composition would seem to have the greatest effect on drug response , genetic variation that affects transcript abundance level has also been shown to affect drug response [25] . A disproportionate number of drug response associated SNPs in a broad array of chemotherapeutic agents are eQTLs and are associated with the transcriptional expression level of multiple genes [25] . However , our work has demonstrated poor global correlations between inter-individual mRNA and protein levels ( unpublished data ) . Therefore , functional annotation of pharmacologic SNPs and their relationships with proteins may result in important new discoveries as it has in this study . We note that 46 , 863 of the 121 , 484 trans pQTLs identified at P<10−4 are also cis-acting eQTLs ( within 1 Mb upstream of the transcription start state to 1 Mb downstream of the transcription end site ) for at least one of the 18 , 227 gene models quantified by RNA-Seq at P<0 . 05 . This proportion ( 38 . 6% ) is statistically enriched compared with the proportion of all single nucleotide variants genome-wide that are cis-eQTLs ( 36 . 6% , Fisher's exact test P<2 . 2×10−16 , odds ratio = 1 . 09 ) , suggesting that cis-acting may contribute to some extent to underlying trans-genetic regulation of protein levels . Because we performed multiple analyses to examine overlap and enrichment of protein and drug QTL , the p-value thresholds used in this study were more permissive relative to that typically used for genome-wide analyses . By contrast to various chemotherapeutics that exhibit GWAS enrichment in eQTLs [25] , paclitaxel GWAS results were not enriched in eQTLs; however , we identified enrichment in pQTLs for both paclitaxel-induced apoptosis and cytotoxicity phenotypes . Therefore , genetic variants associated with the level of a protein appear to be more important for sensitivity to this drug than mRNA regulatory variants . We functionally validated one of these observations , DIDO1 , by siRNA knockdown . DIDO1 is a tyrosine phosphorylated transcription factor that is localized to the nucleus [40] . DIDO1 was also found within cluster 3 , which contained proteins with increased baseline levels correlating with greater cytotoxicity and apoptosis to each chemotherapeutic agent tested . DIDO1 is generally believed to function through apoptosis-related processes; however , it has also been suggested to function in mitotic division based on gene overexpression in mice [41] . This proposed function provides a clear mechanistic connection to paclitaxel , a drug that kills cells through microtubule inhibition . Both paclitaxel and cisplatin have been in use for decades , and significant effort has been expended to identify strategies that result in increased tumor sensitivity to these agents , including targeting the activity of drug resistance pathways . However , this approach is only successful if the cancerous and non-cancerous cells differ in their response to modulation . Improving the therapeutic index for patients occurs if the “modulating agent” increases the sensitivity of chemotherapy in the tumor while decreasing toxicity in non-tumor tissues . This study offers an opportunity to identify the relationship between transcription factors and signaling molecules and drug sensitivities in a non-tumor environment . For example , high levels of proteins identified in cluster 3 were associated with greater sensitivity to both cisplatin and paclitaxel; yet several of these proteins including c-Src [42] , [43] and c-Myc [44] , [45] have been shown to be overexpressed in tumor cells and their expression correlates with paclitaxel or cisplatin resistance . c-Src tyrosine kinase is overexpressed in a high proportion of ovarian cancers and ovarian cancer cell lines . Its inhibition , either pharmacologically or through gene knockdown , results in an increase in sensitivity of ovarian cancer cells to paclitaxel and cisplatin [43] . The increased cytotoxicity in response to c-Src inhibition was associated with a large increase in processing and activation of caspase-3 . Our data support these proteins as potential drug targets , because reducing their levels in LCLs would result in lower sensitivity to the toxic effects of cisplatin and paclitaxel in contrast to cancerous cells . We anticipate that this dataset will therefore have great utility for the development of novel modulators of chemotherapy . Although LCLs are a more likely model for toxicity , we identified several relationships that have been recapitulated in tumor response . Signal transducer and activator of transcription 3 ( STAT3 ) had the strongest negative associations with cisplatin- and paclitaxel-induced apoptosis , suggesting high levels of STAT3 protein conveyed drug resistance . STAT3 mRNA expression has previously been reported to be associated with cisplatin resistance in many cancer types , including head and neck [46] , small cell lung carcinoma [47] , and human epidermoid cancer cells [48] , in which the CRE/ATF binding elements in the STAT3 promoter were shown to be important for mediating cisplatin resistance . STAT3 mRNA expression has also been implicated in paclitaxel resistance . Knockdown of STAT3 conveyed sensitivity to paclitaxel in lung cancer cell lines [49] . STAT3 has been hypothesized as a potential target to modulate paclitaxel sensitivity in cancer patients [50] . PTEN is also an example of same direction of effect in LCLs and cancer cells , however unlike STAT3 , increased levels of PTEN convey sensitivity . Recent studies have demonstrated that PTEN has the ability to enhance cancer cell sensitivity to particular anticancer agents . PTEN might reverse the chemoresistance of human ovarian cancer cells to cisplatin through inactivation of the PI3K/AKT cell survival pathway and may serve as a potential molecular target for the treatment of chemoresistant ovarian cancer [51] . SMC1A is part of the multi-protein cohesion complex required for sister chromatid cohesion . This cohesion complex has been shown to interact with the BRCA1 DNA repair protein and has been shown to be phosphorylated by ATM , a serine/threonine kinase activated by DNA double-strand breaks [52] . The cohesion complex has also been shown to be important for expression regulation and genomic stability [53] . Mutations in SMC1A have been shown to cause Cornelia de Lange syndrome , a multisystem developmental disorder with defects ranging from limb formations to cardiac , gastrointestinal , growth and cognitive systems [53] . Coding variants have also been identified in colon cancer [54] and have been implicated in impairing cellular response to toxic treatment [55] . Accumulated SMC1A protein has been linked to bortezomib-induced cell death , demonstrating its relevance for another chemotherapeutic agent [56] , but this is the first study implicating SMC1A for cisplatin-induced cellular response . Recently , Wip1 , an important signaling protein in cellular growth following DNA damage , has been identified as an upstream regulator of SMC1A [57] , further suggesting an important role for this protein in cancer and chemotherapeutic response . SMC1A has also been linked to cellular growth rate and was identified within cluster one which included proteins whose levels were associated with reduced cytotoxicity and apoptosis phenotypes across both drugs . Another protein we functionally validated associated with paclitaxel , ZNF569 , was a notable candidate because it has been functionally implicated as a transcriptional repressor that suppresses MAPK signaling [58] . Because of the importance of MAPK signaling in breast cancer [59] and the common use of paclitaxel as a breast cancer therapy [60] , this association presents an interesting biological mechanism and potential therapeutic marker . ZNF569 is supported in our data as a transcriptional suppressor of MAPK signaling , because lower ZNF569 protein levels were correlated with increased cellular survival . In addition , ZNF569 was also found in the cluster of proteins that negatively correlated more strongly with cytotoxicity than apoptosis for both drugs , perhaps indicating a role for ZNF569 in cell growth inhibition unrelated to caspase 3/7 activation . Notably , this study focused on two widely used but mechanistically distinct agents . By examining two distinct cell phenotypes , cell growth inhibition and caspase 3/7 activation , our study identified proteins associated with different cell signaling pathways responsible for cell growth inhibition . Although our study did not reveal candidates with strikingly high effect sizes that were predictive of drug sensitivity , it revealed many unique proteins whose expression levels were correlated with phenotypic measurements for a single drug . This observation is consistent with multiple proteins contributing small influences to drug sensitivity . The protein data collected in this study allowed us to gain a new understanding of the potential mechanisms and pathways relevant for cell viability and the genetic variants regulating those proteins . Interpreting GWAS results continues to present challenges; increasingly , eQTL studies are being used to inform [25] , [61] , [62] interpretation of these results and are the focus of expanded studies to understand biological mechanisms [63] , [64] . These association tests have been extended to other functional units in the genome from microRNAs [20] to DNA hypersensitivity sites [19] and modified cytosines [17] . The main factor limiting the inclusion of proteins in GWAS studies has been the lack of a reliable , high-throughput methodology to quantify them across populations of individuals . The approach described in this study , including the newly developed microwestern array [32] , has started to bridge that technological gap [33] , and this study demonstrates the utility of targeted protein-omic datasets to understand cellular phenotypes and genomic studies .
YRI LCLs derived from unrelated individuals from the population residing in Ibadan , Nigeria ( n = 68 ) were chosen for consistency with publicly available mRNA expression data on a single population [16] . LCLs were cultured in RPMI 1640 media containing 20 mM L-glutamine and either 15% fetal bovine serum ( Hyclone , Logan , UT ) for baseline protein quantification , cisplatin and paclitaxel apoptosis and cisplatin cytotoxicity experiments or bovine growth serum ( Hyclone , Logan , UT ) for paclitaxel cytotoxicity experiments . Cell lines were diluted three times per week at a concentration of 300 , 000–350 , 000 cells/mL and maintained in a 37°C , 5% CO2 humidified incubator . Medium and components were purchased from Cellgro ( Herndon , VA ) . Drug-induced apoptosis and cytotoxicity phenotypes were determined at 5 µM cisplatin and 12 . 5 nM paclitaxel . Both drugs were prepared as described previously: cisplatin [65] and paclitaxel [66] . The cytotoxic effect of cisplatin [65] and paclitaxel [66] was determined using a short-term cellular growth inhibition assay , and the apoptotic effect was measured using a caspase 3/7 activity detection reagent Caspase-Glo 3/7 ( Promega Corporation , Madison , WI ) . Three independent thaws constituting biological replicates of 68 unrelated YRI cell lines were propagated and pelleted ( 5 . 1 million cells per pellet ) . Cells were spun at 400 RPM , aspirated , and washed in ice-cold PBS . This process was repeated twice and then the pellets snap frozen in liquid nitrogen and placed at −80 degrees . Total protein was extracted by re-suspension in 1 . 0 mL of 1 . 5% SDS lysis buffer ( 240 mM Tris-acetate , 1 . 5% w/v SDS , 0 . 5% w/v glycerol , 5 mM EDTA ) containing 50 mM DTT , protease inhibitors ( 1 µg/mL aprotinin , 1 µg/mL leupeptin , 1 µg/mL pepstatin ) , and phosphatase inhibitors ( 1 mM sodium orthovanadate , 10 mM β-glycerophosphate ) . To ensure complete protein denaturation , samples were boiled for 10 min , sonicated for 10 min ( alternating 30 s on , 30 s off ) with a Bioruptor ( Diagenode ) , and concentrated to 5–10 µg/µL using a 96-well micro-concentration device with a 10 kDa molecular weight cutoff ( Millipore ) . To identify sources of steady-state protein expression variation , we performed a pilot study to quantify 21 proteins across three independent cultures from two independent thaws from two YRI LCLs ( NA18861 and NA19193 ) . We performed a multifactorial ANOVA to assess the proportion of protein expression variation explained for each of these variables across all proteins . We observed a significant thaw effect explaining 3 . 75% of global protein expression variation ( p = 0 . 01 , F test ) , whereas culture only explained 0 . 13% of protein expression variation ( p = 0 . 85 , F test ) . Using a mixed-effects model with a random nested effect , ( 1|individual/thaw/culture ) , only 2 . 71×10−14% of protein expression variation was between cultures within thaws , whereas 5 . 29% of variation was between thaws within individuals . Initially , three biological replicates for each of 11–12 individuals were pooled together into six pools for screening 4 , 366 rabbit polyclonal antibodies at a 1∶1000 dilution . Printing , gel fabrication , horizontal semidry electrophoresis , transfer , blotting , and scanning were performed as in Ciaccio et al . [32] , permitting 96 antibodies to be screened over six pooled lysates per MWA . The 4 , 366 antibodies were directed against 1 , 848 unique TFs and 200 unique cell signaling proteins . Of this set , 198 antibodies producing a single predominant band the size of the targeted protein isoform of interest with a signal-to-noise ratio ≥3 were selected for subsequent population-level quantification by RPPAs; antibodies that displayed at least one band the size of the targeted protein isoform of interest with a signal to noise ratio ≥3 but additional bands were selected for subsequent population-level quantification by MWAs . This approach ultimately allowed us to quantify protein levels from 441 antibodies ( 341 TF and 100 signaling ) directed at 391 unique protein isoforms across three biological replicates of 68 LCLs . Additional antibody details are listed in Table S5 . For RPPA quantification , four technical replicates of each of three biological replicates of all 68 individuals were spotted using a noncontact piezoelectric microarrayer ( GeSiM Nanoplotter 2 . 1E ) onto nitrocellulose membranes ( Biorad ) . Serial dilutions of each of the six pooled lysates used for the original antibody screen and an A431 skin carcinoma cell line control were also printed for each array to ensure the linearity and quality of the antibody signal . Features with background-subtracted integrated intensities <0 or signal to noise ratio <3 ( Z test p>0 . 05 ) were identified in each array and excluded from further analysis . The distributions of background-corrected integrated intensities for all features on each array were first log2-quantile normalized using the limma package in R to correct for overall antibody hybridization efficiency differences in the signal . The relative expression of a given protein for a sample was then quantified using the linear model ( 1 ) , where μjp is the log-quantile normalized , background-corrected integrated intensity of sample j on array p , λj is the effect due to sample j across all arrays in a print ( due to differing amounts of total protein spotted on the array for each sample ) , estimated by medianj ( cjp ) . Odyssey output text files were parsed in Python and quantified and normalized in R . For micro-western quantification , three technical replicates of each of the three biological replicates of all 68 individuals were spotted as above onto polyacrylamide gels . Gel fabrication , horizontal semidry electrophoresis , transfer , and scanning were performed as in Ciaccio et al . [32] with the exception of separating each blot into four quadrants rather than using a 96-well gasket to permit 68×3 = 204 samples to be quantified with a single antibody on a single quadrant . Feature extraction and data normalization were performed as with RPPAs . For antibodies that produced multiple bands ( signal to noise ratio >3 ) , all isoforms were quantified and their relative molecular weights recorded . The expression of a given protein for an individual was quantified using the above linear model ( equation 1 ) with the addition of a batch term ( β ) to correct for global intensity distribution differences across multiple microwesterns for the same antibody . For replicates within platforms for the same antibody across the entire population , we took the average of the expression measurements . For replicates across platforms , we selected the platform that yielded the highest median background-corrected integrated intensity . To reduce the inflated effect of technical noise because of low antibody signals and provide more accurate inter-individual protein expression measurements , antibodies in the bottom deciles of median background-corrected integrated intensities or in the top deciles of technical CVs for either platform were flagged and eliminated from further comparative analyses . For each protein measurement from either method , we constructed linear mixed effects models , in which p is the array- and sample-load normalized integrated signal intensity for all biological replicates of all individuals comprising the population , C is the fixed effect of the drug , T|I is the random thaw effect per individual , and e is the residual error . The model was fitted to each protein by residual maximum likelihood using the lmer function in the R package lme4 ( v 0 . 999999-0 ) . This mixed effect model incorporates the direction of effect for each biological replicate and insures that those with conflicting directions would result in a less significant p-value . Fixed effect p-values for covariates were estimated using the pamer . fnc function in the LMERConvenienceFunctions package ( v 1 . 6 . 8 . 3 ) . The significance of covariate effects was assessed by estimating false discovery rates using Storey's q-value method . Hierarchical Clustering . Hierarchical clustering was performed in R using Euclidean distance and the Ward method in hclust ( ) for the standardized coefficients between the regression of 370 protein isoforms ( rows ) by the four drug phenotypes ( columns ) , with the apoptosis coefficients inverted to match directionality with the cytotoxicity coefficients . The number of significant clusters was determined by performing 1000 permutations of the column coefficients , clustering them , and selecting the number of observed clusters at a tree height that significantly exceeded all tree heights from the permutations ( k = 7 , p<0 . 001 ) . HapMap genotypes were obtained from the 1000 genomes , June 2011 , phase I , low-pass whole genome SNP genotype release ( www . 1000genomes . org ) . Missing values were imputed by BIMBAM ( v 1 . 0 ) using the default parameters to derive mean imputed genotypes . SNPs with MAF<0 . 05 and SNPs with significant deviation from Hardy-Weinberg equilibrium ( Fischer's exact test , p<0 . 001 ) were excluded , reducing the set to 9 , 345 , 571 SNPs and indels for association analyses . To ensure that low MAF SNPs were not generating spurious associations due to outliers , we compared the MAF distribution of SNPs associated with protein and drug phenotypes with all SNPs ( Figure S4 ) . The average MAFs for protein ( . 17 ) and drug ( . 15 ) associations do not show a bias as compared with the genome ( . 16 ) . Each protein expression measurement was inverse normal transformed prior to association analysis . Drug-induced cytotoxicity phenotypes were log-transformed to better approximate normal distributions . We tested for normality using the Shapiro-Wilk test and none of the drug phenotypes deviated significantly from normality ( p>0 . 001 ) . We selected this threshold because of the smaller sample size and also examined the frequency distribution to ensure that outliers were not substantially driving false positive associations . Protein expression and drug phenotypes were then tested for association with all markers genome-wide by linear regression implemented in Python and R using custom scripts . For each phenotype , we selected the most significantly associated SNV within each recombination window , defined by splitting the genome into 25 , 307 blocks flanked by >10 cM/Mb recombination rates estimated from HapMap . For each drug , we generated 1 , 000 randomly selected sets of SNPs of the same size and matching the same MAF distribution as all SNPs significantly associated with that drug ( dQTLs ) at p<10−3 and examined the overlap of these dQTLs with pQTLs and eQTLs at p<10−4 , as previously described [25] . We empirically determined the enrichment p-value by comparing the observed dQTL-pQTL or dQTL-eQTL SNP overlap to the null distribution . We also evaluated enrichment of dQTLs at p<10−4 for the SNP-transcript association to test the robustness of an enrichment result to the choice of p-value threshold . To investigate whether the observed enrichment of dQTLs to be pQTLs or eQTLs was driven by linkage disequilibrium , we performed an additional simulation analysis after selecting only the most significant dQTLs for each recombination block . LCLs were seeded at a density of 550 , 000 cells/mL 24 hours before nucleofection . Amaxa's Cell Line 96-well Nucleofector Kit SF ( Lonza Inc , Basel , Switzerland ) was used to perform the transfection . Cells were centrifuged at 90 g for 10 minutes at room temperature and resuspended at a concentration of 1 , 000 , 000 cells in 20 µL of SF/supplement solution ( included in SF Kit Lonza Catalog #V4SC2096 ) and 2 µM final concentration of AllStars negative Control siRNA labeled with AlexaFluor488 ( Qiagen Inc . , Valencia , CA ) or a pool of siRNA ( Qiagen ) ( See Table S1 ) . The cells were nucleofected using Amaxa's DN-100 program . Cells were allowed to rest for 10 minutes before the addition of pre-warmed ( in 37° water bath for a minimum of 20 minutes ) RPMI media and then another 5 minutes after the addition of warm RPMI media . Cells were then plated for protein measurements and drug treatments . Cells were harvested at 24 and 48 hours post-nucleofection for protein measurement . Drug treatment was done 18 hours following transfection for cell survival measurement and 24 hours after transfection for apoptosis measurement . Apoptosis was measured as described above , whereas cell survival was measured as described above for cisplatin and using Cell-Titer Glo ( Promega ) for paclitaxel . Each experiment was done twice , with two independent transfections . To assess the size and significance of the effect of siRNA knockdown on drug response ( survival for cytotoxicity assay and caspase activity for apoptosis assay ) we fit the following linear mixed effect model: , in which knockdown is 1 if the gene was knocked down and 0 if scrambled . Cell line id ( denoted by id ) and experiment were used as random effects to properly account for correlation between replicates . To increase precision , we pooled the data from all cell lines . The mixed effects model was fit using lme4 package in the R Statistical package ( http://cran . r-project . org/ ) . The goodness-of-fit of the model was assessed by examining the residuals . Normality of the residuals was assessed using the Shapiro-Wilk test in the R Statistical package . Log-transformation of the response variable was used to achieve approximate normality . | The central dogma of biology explains that DNA is transcribed to mRNA that is further translated into protein . Many genome-wide studies have implicated genetic variation that influences gene expression and that ultimately affect downstream complex traits including response to drugs . However , because of technical limitations , few studies have evaluated the contribution of genetic variation on protein expression and ensuing effects on downstream phenotypes . To overcome this challenge , we used a novel technology to simultaneously measure the baseline expression of 441 proteins in lymphoblastoid cell lines and compared them with publicly available genetic data . To further illustrate the utility of this approach , we compared protein-level measurements with chemotherapeutic induced apoptosis and cell-growth inhibition data . This study demonstrates the importance of using protein information to understand the functional consequences of genetic variants identified in genome-wide association studies . This protein data set will also have broad utility for understanding the relationship between other genome-wide studies of complex traits . | [
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"... | 2014 | Protein Quantitative Trait Loci Identify Novel Candidates Modulating Cellular Response to Chemotherapy |
Gene expression as an intermediate molecular phenotype has been a focus of research interest . In particular , studies of expression quantitative trait loci ( eQTL ) have offered promise for understanding gene regulation through the discovery of genetic variants that explain variation in gene expression levels . Existing eQTL methods are designed for assessing the effects of common variants , but not rare variants . Here , we address the problem by establishing a novel analytical framework for evaluating the effects of rare or private variants on gene expression . Our method starts from the identification of outlier individuals that show markedly different gene expression from the majority of a population , and then reveals the contributions of private SNPs to the aberrant gene expression in these outliers . Using population-scale mRNA sequencing data , we identify outlier individuals using a multivariate approach . We find that outlier individuals are more readily detected with respect to gene sets that include genes involved in cellular regulation and signal transduction , and less likely to be detected with respect to the gene sets with genes involved in metabolic pathways and other fundamental molecular functions . Analysis of polymorphic data suggests that private SNPs of outlier individuals are enriched in the enhancer and promoter regions of corresponding aberrantly-expressed genes , suggesting a specific regulatory role of private SNPs , while the commonly-occurring regulatory genetic variants ( i . e . , eQTL SNPs ) show little evidence of involvement . Additional data suggest that non-genetic factors may also underlie aberrant gene expression . Taken together , our findings advance a novel viewpoint relevant to situations wherein common eQTLs fail to predict gene expression when heritable , rare inter-individual variation exists . The analytical framework we describe , taking into consideration the reality of differential phenotypic robustness , may be valuable for investigating complex traits and conditions .
The advent of high-throughput genotyping and sequencing technologies enables a comprehensive characterization of the genomic and transcriptomic landscapes of each individual . Deciphering the massive data points associated with individuals presents a major challenge [1 , 2] . Over the last couple of years , eQTL analyses have provided in-depth insights into the effect of genetic variation on regulating gene expression [3–6] . More recently , research has also focused on the contribution of genetic variation on the variance of gene expression [7–9] . The analytical frameworks adopted by most eQTL studies have historically been based on population-level test statistics , which are powerful for establishing associations between commonly-occurring genetic variations and gene expression . However , few frameworks or statistics are available for assessing the impacts of rare genetic variants to gene expression ( except , for example , [10] ) . The problem is further exacerbated by the fact that individual gene expression is a function of both genetic and non-genetic ( such as epigenetic and environmental ) factors , as well as their combined action . Our failure to detect the effects of rare variants with large effects in biological samples , along with the inherent difficulty in dissecting the complex factors influencing gene expression will hinder efforts to define and prioritize relevant variants and impede the development of improved personalized diagnostic and therapeutic options . Here , we envision an alternative approach based on the theory of multivariate outliers to address these technical challenges . More specifically , we measure how any two individuals differ in their expression profiles and quantify these differences with respect to a set of genes between individuals . Based on the expression differences , we detect outlier individuals whose expression profiles are so divergent from those of others in the population that the divergence cannot be explained by random sampling variation alone . Many methods of outlier detection have been developed . The most commonly used of these methods , such as those based on the estimation of the location and scatter of the data points or the quantiles of the data , are more applicable to univariate than multivariate settings . In practice , however , phenotypic traits are associated with changes of multiple genes in biological pathways and molecular networks , more often than single gene alterations . Reliably identifying outliers in such a multivariate setting is a challenging problem—unlike the simpler case of univariate outlier detection , simple graphical diagnostic tools like the boxplot often lack statistical power when the analysis of more than one dimension is attempted [11] . To this end , we adapted the multivariate outlier method that allows simultaneous evaluation of expression data with respect to many dimensions derived from multiple genes . With this method , even though there is no natural ordering of multivariate data on which “extremeness” of an observation can be ascertained , outliers showing markedly different data profile can be detected . Using a framework based on this approach , we specifically address the following research questions: Are there any differences between the functional properties of genes tending to ( or tending not to ) be aberrantly expressed ? Is aberrant expression population-specific ? What are the roles of genetic and non-genetic factors in aberrant expression ? Do common or rare genetic variants contribute to aberrant expression ? Our overall results clearly demonstrate that outliers , while often considered as error or noise , do carry important biologically-relevant information . Thus , the careful characterization of the genetic bases underlying the markedly different expression profiles of outlier samples is both worthwhile and necessary . Accurate description of inter-individual expression differences requires the incorporation of the effects of both common and rare regulatory genetic variants .
The main results of our study comprise three parts . The first part concerns the identification of sets of functionally related genes whose expression discrepancies among individuals are significantly greater ( or smaller ) than those of random gene sets . The second part concerns the identification of outlier individuals whose expression profiles with respect to gene sets are significantly divergent from those of others in the population . The third part concerns the uncovered evidence that private SNPs contribute to aberrant expression in outlier individuals . Data analysis in the first two parts relied on a metric of statistical distance that can quantify the dissimilarities between individuals in the expression levels of gene sets , rather than single gene . To this purpose , we adapted Mahalanobis distance ( MD ) , a multivariate metric that can be used to measure the dissimilarity between two vectors [12] . Key features of MD are illustrated in Fig . 1 , which shows a hypothetical example of MD , compared to the simple Euclidean distance . Here , the expression levels of two genes are correlated and the Euclidean distance is not an appropriate measure of distance between data points ( or individuals ) . MD , on the other hand , accounts for the correlation through estimating the covariance matrix from the observations , making MD a more appropriate distance statistic . With a given gene set ( e . g . , the two genes of the hypothetical example ) , we can calculate MDi for N individuals under consideration ( i = 1 to N ) . Each MDi is the multivariate distance from the individual i to the population mean , with the correlation between expression profiles of individuals captured by the inter-individual expression covariance . In Fig . 1A , the top three data points with largest MDi are labeled with 1 , 2 , and 3 , while the Euclidean distances from these data points to the population mean are not the largest . With MDi of each individual , we can calculate the sum of squared MDi ( SSMD ) . SSMD summarizes the overall distribution of MDi across individuals for the gene set . The squaring operation puts more weight on larger MDi values of outlier individuals . Gene sets with larger SSMD are more likely to contain genes that are aberrantly expressed by outlier individuals . Thus , comparing SSMD values of gene sets , we can identify sets of genes that tend to ( or tend not to be ) aberrantly expressed ( i . e . , Part 1 of the main results ) . The outlier individuals can be identified with ordered MDi . To do so , we used the tool for multivariate outlier recognition , chi-square plot [13] . As seen in Fig . 1B , the three data points with the largest MDi are recognized as outliers . These data points , as shown in Fig . 1A , are the most remote observations with the largest MDi to the population mean . None of the three data points would otherwise be identified as outliers by using Euclidean distance . More important , none of them would otherwise be identified as outliers if we used any univariate approach . This is because that , when the two genes are considered separately , the expression levels of either gene in the three individuals are in the “normal” range . Finally the purpose of identifying outlier individuals is to study the genetic basis of aberrant expression of genes in outliers . That is to say , once the outlier individuals are identified , the genetic variation associated with outlier individuals can be further analyzed to see what kinds of genetic variation contribute to aberrant expression ( i . e . , Part 2 of the main results ) . We started by identifying gene sets that are more likely to be aberrantly expressed . We obtained the expression data matrix of 10 , 231 protein-coding genes in 326 lymphoblastoid cell lines ( LCLs ) of European descent ( EUR ) from the Geuvadis project RNA-seq study [3] . We used SSMD to measure the total deviation of expression profiles from all individuals to the population mean for gene sets . We computed SSMD for all gene sets with fewer than 150 expressed genes in the Molecular Signatures Database ( MSigDB ) [14] and the GWAS catalog [15] . We identified 31 MSigDB gene sets whose SSMD values were significantly larger than those of random control gene sets that contain the same number of genes randomly selected from all expressed genes ( Bonferroni corrected P < 0 . 01 , permutation test ) ( Table 1 ) . These 31 gene sets , containing 1 , 855 distinct genes that are more likely to be aberrantly expressed in defined outlier individuals . We named these gene sets and genes L-SSMD gene sets and genes . Fig . 2 shows one of L-SSMD gene sets , G-protein coupled receptor activity , which contains 94 genes . In addition , eight GWAS catalog gene sets showed relatively large SSMD ( P < 0 . 001 , permutation test ) , though not significant following Bonferroni correction . These sets included genes implicated in adverse responses to chemotherapy , conduct disorder , fasting insulin-related traits , metabolite levels , obesity , retinal vascular caliber , temperament , or thyroid hormone levels ( S1Table ) . To identify outlier individuals , we applied chi-square plot to examine MD values of all individuals with respect to each of the 31 L-SSMD gene sets . We identified 17 distinct outliers in total , 11 of which were found in more than one gene set , and almost all gene sets had more than one outlier . The distributions of outliers in the gene sets are given in S1 Fig Fig . 2 shows that three outliers were detected in the L-SSMD gene set , G-protein coupled receptor activity , using chi-square plot . Fourteen gene sets with significantly smaller SSMD ( S-SSMD ) were identified ( Bonferroni corrected P < 0 . 01 , Table 2 ) . The S-SSMD genes ( n = 534 ) in the 14 S-SSMD gene sets are involved in homologous recombination repair of replication-independent double-strand breaks , catalysis of the transfer of a phosphate group to a carbohydrate substrate molecule , or cell cycle control . GWAS gene sets implicated in alcohol dependence and metabolic syndrome showed significantly smaller SSMD than random gene set ( S1 Table ) . We evaluated the power of SSMD as a statistic describing the propensity of a gene set for aberrant expression . We considered the influences of the sample size ( n ) and the size of gene set ( m ) . In cases where the SSMD are insensitive to n or m , the power would be maintained when n or m changes . However , we found that the power dropped substantially when n dropped from 326 to 300 or when m dropped from 37 to 31 , suggesting that SSMD is sensitive to both n and m ( Fig . 3A , B ) . This might be due to that only a small number of genes in the gene set tested that were expressed aberrantly in few individuals , and the power analyses for m and n were based on the sub-sampling of genes and individual samples , respectively ( Materials and Methods ) . Nevertheless , owning to the sensitivities , it was necessary to validate our results of identified L- and S-SSMD gene sets , which were obtained using the Geuvadis LCL expression data [3] . We validated our results by taking into consideration three factors: ( 1 ) the robustness against the influence of data normalization methods , ( 2 ) the replicability against technical variability , and ( 3 ) the reproducibility against independent expression data of different tissues . The “original” Geuvadis expression data we used to identify L- and S-SSMD gene sets had been normalized by using the algorithm of probabilistic estimation of expression residuals ( PEER ) [16 , 17] . We first showed that the PEER normalization algorithm did not change our results . To do so , we downloaded the “raw” Geuvadis expression data quantified in reads per kilobase per million ( RPKM ) without PEER normalization . Two replicate sets of raw RPKM data were available for most of the Geuvadis samples . We therefore used each set independently to test the significance of SSMD for L- and S-SSMD gene sets against random control sets . The procedure was similar to what we used for establishing the original L- and S-SSMD gene sets . Briefly , for each L- or S-SSMD gene set , we tested whether the SSMD computed with raw RPKM data tended to be larger or smaller than that of random gene sets . The observed SSMD was compared against SSMD values computed from 1 , 000 replicates of randomly selected genes and the significance was evaluated by examining how many times the observed SSMD was larger or smaller than random SSMD . As expected , with the original ( PEER normalized ) expression data , all 31 L-SSMD gene sets had a larger SSMD than sets of randomly selected genes , while all 14 S-SSMD gene sets had a smaller SSMD . The same patterns were recovered with the raw RPKM expression data ( Fig . 3C ) . These results indicated that our results for L- or S-SSMD gene sets were robust against the normalization methods and the technical variability . In addition , we used independent gene expression data from tissues different from LCL to validate our results . We obtained the expression data of whole blood and muscle ( in 156 and 138 samples , respectively ) from the pilot study of the Genotype-Tissue Expression project ( GTEx ) [18] . We re-computed SSMD using the GTEx data and conducted the same validation tests . With GTEx data , the frequency of observed SSMD greater than random SSMD was significantly higher for L-SSMD gene sets than S-SSMD gene sets ( Kolmogorov-Smirnov [K-S] test , P = 1 . 02e-5 and 9 . 9e-4 , for whole blood and muscle , respectively , Fig . 3C ) . These results suggested that gene sets tending to have larger observed SSMD in LCL were more likely to have larger SSMD in the other two tested tissues , or vice versa . The consistency in the direction of SSMD patterns validates the biological significance of L- and S-SSMD gene sets . Next we examined which gene sets show strong population-specific SSMD . For a given gene set , we first computed MDi with the gene expression data for all 402 samples of both European ( EUR , n = 326 ) and African ( AFR , n = 76 ) ancestries . We then use these MDi to compute SSMDEUR and SSMDAFR for EUR and AFR samples , respectively , and calculated the difference in SSMD between them: diffSSMDEUR-YRI = SSMDEUR-SSMDAFR . To assess the significance , we computed diffSSMDrand by randomly assigning samples without regard to their identities of original populations . For each gene set , we computed 1 , 000 permutations of diffSSMDrand to obtain the null distribution of expected diffSSMDEUR-YRI . We compared the value of diffSSMDEUR-YRI with the null distribution to obtain its significance . We used two random sets of genes ( n = 20 and 40 ) to show that the values of diffSSMD were proportional to gene set size and changed linearly with the ratio by which the total samples were partitioned into two sub-groups ( Fig . 4A ) . In the test , we ignored the EUR and AFR ancestries of samples . We randomly shuffled the 402 samples , partitioned them to two sub-groups with different ratios ( such as , 201/201 or 326/76 ) , and computed the diffSSMD between the two sub-groups . We repeated this 1 , 000 times per ratio to obtain null distributions of diffSSMD . We found that , regardless of gene set size , when samples were partitioned into groups of equal size ( i . e . , 201/201 ) , the average diffSSMD was close to zero . When samples were partitioned unequally , the average value of diffSSMD increased with the degree of inequality in a linear manner . When the ratio of partition was fixed ( e . g . , 326/76 , the actual sample ratio of EUR and AFR ) , the average diffSSMD reflected the size of the gene set ( e . g . , twice as large for the 40-gene set as the 20-gene set ) . When both the ratio of partition and the gene set was fixed , as we did in the real test for each gene set , the values of null diffSSMD fluctuated only due to the random assignment of samples into the two sub-groups . Similarly , in our significance test for diffSSMDEUR-YRI , both the gene set size and the ratio of partition ( =326/76 ) were fixed , and the null distribution of diffSSMD , diffSSMDrand , was constructed from 1 , 000 random repeats of the partition of shuffled samples . An observed diffSSMDEUR-YRI was considered to be significant when it was greater or smaller than all values of diffSSMDrand . In total , 231 gene sets showed significantly smaller diffSSMDEUR-YRI than diffSSMDrand in our analysis ( S2 Table ) . For these gene sets , the differences between SSMDEUR and SSMDAFR were relatively smaller than those differences calculated when EUR and AFR individuals were randomly assigned . This was likely caused by the relatively large SSMDAFR in real data . In other words , AFR samples were more likely to produce disproportionally larger SSMD than EUR samples . In contrast , only four gene sets showed the opposite pattern—that is , for these genes , diffSSMDEUR-YRI was significantly larger than diffSSMDrand . Genes in these four sets included: ( 1 ) genes involved in the process preventing the degeneration of the photoreceptor ( a specialized cell type that is sensitive to light ) , ( 2 ) genes down-regulated in prostate tumor ( a tumor with distinct signatures differentiate between African-American and European-American patients [19] ) , ( 3 ) genes associated with malignant fibrous histiocytoma tumors , and ( 4 ) genes up-regulated in colon tissue upon the knockout of MBD2 , a methyl-CpG binding protein that mediates the methylation signal . Finally , the power analysis for diffSSMDEUR-YRI was conducted using the first gene set among the four with significantly larger diffSSMDEUR-YRI . The result suggested that the difference in sample size between EUR and AFR had little impact on the sensitivity of asserting that the tested gene set was significant . As shown in Fig . 4B , when the EUR were subsampled from 326 to 76 ( the sample size of AFR ) , the power of diffSSMD only slightly decreased . To evaluate the contributions of genetic or non-genetic factors in causing aberrant expression , we utilized three statistical metrics to characterize L- and S-SSMD genes and compared the properties of the two groups of genes ( Materials and Methods ) . The three metrics are: ( 1 ) the discordant gene expression , measured as the relative mean difference in gene expression , between twin pairs , considering both monozygotic ( MZ ) and dizygotic ( DZ ) twins [9]; ( 2 ) the narrow-sense heritability ( h2 ) of gene expression [20]; and ( 3 ) the coefficient of variation ( CV ) of single-cell gene expression [21] . The discordant expression between twin pairs in L-SSMD genes is greater than that in S-SSMD genes ( P = 2 . 8e-15 between MZ pairs and 3 . 0e-34 between DZ pairs; K-S test , Fig . 5A ) . The more pronounced discordant expression between MZ pairs for L-SSMD genes , compared to S-SSMD genes , is likely due to the effect of environmental factors . L-SSMD genes may have increased sensitivity to environmental factors . On the other hand , regardless of L- or S-SSMD genes , the discordant expression is always greater between DZ pairs than between MZ pairs . This suggests that genetic diversity increases the level of discordance in gene expression . The difference is more pronounced for L-SSMD genes ( P = 5 . 6e-23 and 5 . 4e-6 for L- and S-SSMD genes , respectively; S3 Table ) . L-SSMD genes tend to have a smaller h2 than S-SSMD genes ( P = 3 . 6e-5 , K-S test , Fig . 5B ) . Similar results were obtained with different h2 estimates ( e . g . , those using data from another twin cohort [22] and those using data from unrelated individuals [23] ) . Furthermore , L-SSMD genes showed greater expression variability at the single-cell level than S-SSMD ( P = 7 . 7e-21 , K-S test , Fig . 5C ) . Forty genes were found to be shared between L-SSMD and S-SSMD groups . Excluding these overlapping genes did not qualitatively change any results described above . To evaluate the contribution of eQTLs to aberrant expression , we obtained 419 , 983 cis-acting eQTL SNPs ( eSNPs ) associated with 13 , 703 genes from a previous study [3] . We found that 20 . 3% of L-SSMD genes and 19 . 3% of S-SSMD genes have cis-eSNP ( s ) . That is to say , there is no difference in cis-eSNP existence between L- and S-SSMD genes ( P = 0 . 67 , Fisher’s exact test ) . Due to the prevalence of eSNPs , this result was not unexpected . Next we set out to examine whether outlier individuals are more likely to have an eQTL genotype that might explain their outlier status . In particular , we calculated the genotype-scaled effect size ( β = |β|*genotype , where genotype = {0 , 1 , 2} , to take into account of the direction of the effect ) for all cis-eSNPs of associated genes in L-SSMD gene sets for outlier individuals . Multiple eSNPs in the same genes were treated independently and the values of genotype-scaled effect sizes calculated were pooled together as βoutlier . We did the same calculation for the same sets of genes for all non-outlier individuals and obtained βnon-outlier . We hypothesized that if cis-eSNPs cause the outlier’s gene expression level to deviate away from the population mean , then the genotype-scaled effect size of these eSNPs in outlier individuals should be less likely to be zero and more likely to be larger than that of non-outlier individuals . However , we found that 45 . 3% of βoutlier ( n = 24 , 649 , pooling from 63 outlier-gene pairs , i . e . , pairs of outlier individual and gene in corresponding gene sets ) and 46 . 2% of βnon-outlier ( n = 3 , 329 , 296 , pooling from 309 outlier-gene pairs ) were zeros . There was no difference between the two fractions ( P = 0 . 086 , χ2 test ) . Considering that this result might be affected by the uncontrolled linkage disequilibrium between eSNPs , we re-performed the analysis using only the most significant eSNP per gene . With such a single-eSNP setting , we found that 9 . 49% of βoutlier ( n = 875 , pooling from 63 outlier-gene pairs ) and 10 . 58% of βnon-outlier ( n = 118 , 965 , pooling from 309 outlier-gene pairs ) were zeros . Again , there was no difference between the two fractions ( P = 0 . 3448 , χ2 test ) . Furthermore , with only the most significant cis-eSNP per gene , we found that the distribution of nonzero βoutlier was similar to that of nonzero βnon-outlier ( K-S test , P = 0 . 67 , Fig . 6 ) . These results suggest that eSNPs , as commonly-occurring regulatory genetic variants , may not be responsible for aberrant expression of genes under their regulation . We resorted to examining whether private SNPs are responsible for aberrant expression . We tested whether private SNPs are enriched in regulatory regions of L-SSMD genes in outlier individuals . The SNP density was calculated by pooling SNPs , which are private to each outlier individual , in 1Mb cis-regulatory regions of L-SSMD genes . Based on the ENCODE annotations [24] , the regulatory regions were divided into seven subclasses , namely , E ( predicted enhancer ) , TSS ( predicted promoter region including TSS ) , T ( predicted transcribed region ) , PF ( predicted promoter flanking region ) , CTCF ( CTCF-enriched element ) , R ( predicted repressed or low-activity region ) , and WE ( predicted weak enhancer or open chromatin cis-regulatory element ) . We found that the density of private SNPs in E regions of L-SSMD genes in outlier individuals was significantly higher than that in the same E regions in non-outlier individuals ( P < 0 . 001 , one-tailed t test ) . The density was also significantly higher than that derived from three additional control settings , including the reconstructed E regions from the locations 10 Mb away from genes , and randomly selected L-SSMD or S-SSMD genes ( Materials and Methods ) . In summary , we randomly selected individuals or genes in a total of four different manners to construct the control scenario , from which the private SNP density was calculated and compared with the observed density . The most salient finding was that for the E regions , the observed density of private SNPs in L-SSMD genes was significantly higher than any of the controls ( Table 3 ) . In addition , we also found that , for TSS , the density is significantly higher than three controls ( P < 0 . 001 , one-tailed t test ) . These results are consistent with the findings of a previous study , which also focused on the effects of rare variant on causing outlier expression [25] . The rest of the region classes showed less significant enrichment or similar levels of the density ( Table 3 ) . For illustrative purpose , two private SNPs , rs189458147 and rs117086221 , located in E region of PMAIP1 and TSS region of NEIL1 are depicted ( S2 Fig ) .
We have used MD as a measure of distance between two points in the space defined by two or more correlated variables to quantify the deviation of individuals’ gene-set expression to the population mean . This quantity allowed us to identify outliers . The sum of the quantity across individuals ( i . e . , SSMD ) allowed us to assess how likely a gene set is to be aberrantly expressed in outlier individuals . As expected , genes involved in fundamental molecular functions and metabolic pathways are unlikely to be aberrantly expressed , showing a small SSMD . In contrast , genes in the gene sets with large SSMD tend to be involved in regulation of cellular processes and modulation of signal transduction ( see Table 1 ) . Notably , three gene sets with large SSMD have GO definitions: ( 1 ) extracellular ligand gated ion channel activity , ( 2 ) G-protein coupled receptor activity , and ( 3 ) transmission of nerve impulse . G-protein coupled receptors constitute a large protein family of receptors that sense molecules outside the cell and activate inside signal transduction pathways , implicated in various human diseases and development processes [26–28] . Widespread genetic regulatory variants have been uncovered by eQTL analyses . Most eQTLs are detected based on linear regression between genotype and gene expression level . The inherent limitation of this method is that only commonly-occurring regulatory genetic variants will be discovered . Our analysis of cis-acting eQTLs in gene sets suggests that the observed patterns of expression are unlikely to be related to commonly-occurring regulatory genetic variation . The fact that eQTLs are less likely to be responsible for aberrant expression of genes under their regulation underscores the technical limitation of the eQTL method in dealing with gene expression regulation in outliers . Instead we discovered that private SNPs are likely to be responsible for aberrant expression . Our results suggest that private SNPs are significantly enriched in enhancer and promoter regions of aberrantly-expressed genes . This is in agreement with the findings of [25] , in which Montgomery and colleagues reported the identification of the signal of rare SNPs underlying large changes in gene expression by calculating whether individuals with outlier array expression values are enriched for rare genetic variants . They used Z-score as a measurement of how far the observed value is from the mean of the sample . They found that individuals with gene expression Z-score ≥ 2 have an excess of rare variants within 100 kb of the transcription start site . The signal was found to be statistically significant for rare variants landing in highly conserved sites [25] . Taken together , results from both studies suggest that rare or private SNPs contribute to the large changes in gene expression . Awareness of this effect is important as it means that a rare genetic variant , even only seen in an individual genome , could potentially be regulating the expression of the phenotype to an extreme extent relative to the population mean . This makes sense because the recent explosion of human population size has created abundances of rare variants [29] . These variants , segregating in single individuals or only in small groups of people , have not been subject to the test of natural selection , and thus can potentially have stronger functional consequences . They may underlie aberrant gene expression and may also underlie susceptibility to complex diseases . Therefore , the individual bearing private SNPs causing aberrant gene expression might be an interesting model of phenotypes relevant to the function of the aberrantly-expressed gene . Otherwise , on the population level , the variants may bear little relevance to the phenotypes . Intrinsic properties of gene sets are defined not only by descriptive functions of genes they include but also several measurable genetic metrics . Combined use of these metrics has demonstrated the contribution of both genetic and environmental factors to aberrant expression . First , twin data facilitated the dissection of the contributions of genetic and non-genetic factors . The discordance in gene expression is expected to be larger between pairs of dizygotic ( DZ ) twins than between pairs of monozygotic ( MZ ) twins , as the phenotypic difference between DZ pairs may result from both genetic and environmental effects . We indeed observed the difference between MZ and DZ in discordant expression as expected , and to the same extent for both genes tending to and tending not to be aberrantly expressed . This result suggests that genetic diversity increases overall expression variability . More importantly , we found that the discordant expression in MZ pairs for genes tending to be aberrantly expressed is greater than that for genes that tend not to be aberrantly expressed . This result suggests that under the same genetic background , aberrantly expressed genes are more likely to be sensitive to the change of environmental factors than non-aberrantly expressed genes . Second , heritability is a dimensionless measure of the weight of genetic factors in explaining the phenotypic variation among individuals [30–32] . We showed that genes with small SSMD have a higher narrow-sense heritability of gene expression than genes with large SSMD . Third , we detected that genes tending to be aberrantly expressed have a higher expression variability at the single-cell level than genes tending not to be aberrantly expressed . This result suggests that intrinsic single-cell expression contributes to aberrant expression . In summary , we leveraged the 1 , 000 genomes RNA-seq data to identify aberrant gene expression in humans , and described a multivariate framework for detecting aberrantly-expressed gene sets and outlier individuals , offering a new way of measuring inter-individual variation in gene expression . This novel perspective on how to measure differences in gene expression between individual human subjects may provide important clues into the mechanisms of human adaptation , and may also be helpful for the arising field of personalized medicine .
We downloaded gene expression data produced by the Geuvadis project RNA-seq study [3] from the website of EBI ArrayExpress via accessions E-GEUV-1 and E-GEUV-3 . The samples included 462 unrelated human LCLs from the EUR ( CEU , FIN , GBR , TSI ) and YRI populations , most of which had been sequenced in the 1000 Genome Project Phase 1 . The expression data were normalized by using the algorithm of probabilistic estimation of expression residuals ( PEER ) [3 , 17 , 33] . To minimize the impact of unspecific sources on measurement of individual’s expression , principal component analysis ( PCA ) was applied to the full expression matrix . Based on the PCA results , 19 EUR individuals with unusual global expression profiles relative to the rest of individuals in the population were excluded due to potential technical artifacts ( S3 Fig ) . We also excluded individuals whose genotype information was unavailable in the 1000 Genome Project Phase 1 , resulting in a total of 402 remaining samples ( 326 EUR and 76 AFR ) . Gene sets were downloaded from MSigDB v4 . 0 [14] . The MSigDB gene sets had been divided into seven groups: C1—positional gene sets ( n = 326 ) , C2—Curated gene set ( n = 4 , 722 ) , C3—motif gene ( n = 836 ) , C4—Computational gene sets ( n = 858 ) , C5— GO gene sets ( n = 1 , 454 ) , C6—oncogenic signatures ( n = 189 ) , and C7—immunologic signatures ( n = 1 , 910 ) . The annotated gene sets of the NHGRI GWAS Catalog [15] were obtained from http://www . genome . gov/gwastudies ( accessed April 2014 ) . To calculate MD , the correlation between the expression profiles of individuals was captured by the inter-individual expression covariance , Covab . For expression E between any two individuals a and b , Covab is computed as: Covab=∑k=1m ( Eak−μa ) ( Ebk−μb ) m−1 , where m is the number of genes in the gene set under study , and µa and µb are the mean gene expression values for individuals a and b , respectively . Given all pair-wise comparisons of individuals we obtained the inter-individual covariance matrix Cov . We employed the minimum covariance determinant ( MCD ) estimator [34] to compute a robust version of Cov , as implemented in the Matlab toolbox LIBRA [35] . We then computed the MD for each individual as MDi= ( Ei⋅− μ→ ) TCov−1 ( Ei⋅−μ→ ) , where μ →is m length vector of the per-gene mean values across all individuals . The statistic S S M D = ∑ M D i 2was calculated for each set . To approximate the empirical null distributions for SSMD , we applied resampling for gene sets with different numbers of genes , ranging from 2 to 150 . For a given number of genes m , we randomly sampled m genes from the full expression matrix without replacement , and then computed SSMD for the resampled gene set . The procedure was repeated 1 , 000 times for all gene sets . More permutations were performed for significant gene sets until the desired Bonferroni correction level P = 0 . 01 was either achieved or rejected . The resampling process breaks correlation structure between genes , hence providing a background distribution of expected random distribution of SSMD . We compared the SSMD in the observed gene set to equally-sized sets drawn at random from all assayed genes . The chi-square plot was plotted as the I ranked MD value against the values of χ2 ( p , m ) , where p = ( i-0 . 5 ) /I and m is the number of genes in the gene set . The right panel of Fig . 1 is the chi-square plot that supports the multivariate outliers identified [13] . A chi-square plot draws the empirical distribution function of the square of the MD against the χ2 distribution with degree of freedom equal to m . A break in the tail of the χ2 distribution is an indicator for outliers [36] , given that the square of the MD is approximately distributed as a χ2 distribution [13 , 37] . To evaluate the sensitivity of SSMD as a statistic for detecting L-SSMD gene set , power analyses were conducted . One selected L-SSMD gene set , POTTI_ETOPOSIDE_SENSITIVITY , was used as the test set . The impacts of sample size ( n ) and the size of gene set ( m ) were considered . The selected L-SSMD gene set contained 37 genes , that is , m = 37 , while the sample size n = 326 . The original expression data matrix was subsampled by lowering either n or m . For each subsampled n or m value , 100 random replicates of expression data matrix were constructed . The SSMD was computed for each subsampled replicate and the significance of the observed SSMD was assessed by permutation tests , as described above for detecting L-SSMD gene sets . The more sensitive is SSMD to n or m , the less would subsampled replicates remain significant as an L-SSMD . To compute the discordant expression of genes between twin pairs , twinsUK gene expression data from the study of [22] were acquired . The discordant expression , i . e . , the expression differences between each pair of twins , was measured as done previously [9] . Briefly , for each gene , the relative mean difference ( RMD ) in expression between MZ twin pairs and between DZ twin pairs was computed . For a pair of MZ twins , i , for example , the RMD was computed using R M D i = | y i M Z 1 − y i M Z 2 | 2 y ¯ i , where y ¯ i is the arithmetic mean of the levels of gene expression for that MZ twin pair ( designated as y i M Z 1 and y i M Z 2 ) . For each gene , the data from all MZ or DZ twin pairs were pooled to compute the mean RMD per gene , 1 n ∑ R M D i , where n is the number of twin pairs . The computed mean RMD per gene was normalized by the value computed in the same way but with the expression data reconstructed by randomly assigning the identities of twin pairs . The values of narrow-sense heritability ( h2 ) of gene expression were obtained from the study of [20] . The different estimates of h2 were also obtained from the studies of [22] and [23] . The single-cell gene expression levels measured in 42 LCLs were acquired from the study of [21] . The absolute value of slope coefficient ( |β| ) of the linear regression model was used as the measure of the effect size of each eSNP . The gene expression levels across individuals were normalized using Z-score to make the values of β uncorrelated with the total gene expression levels . The sign of β was ignored because it is only relative against the genotypes of each eSNP , which were denoted by 0 for homozygous major alleles , 1 for heterozygous alleles , and 2 for homozygous minor alleles . Instead , an eSNP’s effect direction was determined by whether the eSNP causes gene expression to shift away from or towards the mean gene expression for the majority of individuals in the populations . In this sense , the notation of genotypes ( 0 , 1 , 2 ) provided the information of effect direction for eSNP . If an individual’s eSNP genotype is 0 , then the effect of the eSNP is to maintain the same expression level for the eSNP-regulated gene between outlier individuals and the majority of individuals in the population; on the other hand , if the eSNP’s genotype is 1 or 2 , then the effect of the eSNP is to either increase or decrease ( depending on the sign of the slope ) the expression of the gene by one or two times of |β| than that of genotype 0 . Therefore , the effect size was weighted by the genotype: β = |β|*genotype . The genotype-scaled effect size was used in the comparison of the combined eSNP effects between outlier and non-outlier individuals . Both heterozygous and homozygous private SNPs , with allele frequency of 1/ ( 2N ) and 1/N , respectively , for each individual ( where N is the number of individuals ) , were counted . The cis-regions of tested genes were split into seven subclasses of regulatory regions , according to the combined chromatin state segmentation of the ENCODE GM12878 sample [24] . The density of private SNPs in each subclass of the regions was assessed for enrichment significance by comparing the observed density with that of randomly generated control regions . To provide comprehensive controls , four different means were used to construct control regions: ( 1 ) randomly selected non-outlier individuals to replace outlier individuals , ( 2 ) randomly selected genomic regions located 10 Mb away from L-SSMD genes , ( 3 ) randomly selected shuffled L-SSMD genes in the same amount of original gene set , and ( 4 ) shuffled S-SSMD genes in the same amount of original gene sets . | The uniqueness of individuals is due to differences in the combination of genetic , epigenetic and environmental determinants . Understanding the genetic basis of phenotypic variation is a key objective in genetics . Gene expression has been considered as an intermediate phenotype , and the association between gene expression and commonly-occurring genetic variants in the general population has been convincingly established . However , there are few methods to assess the impact of rare genetic variants , such as private SNPs , on gene expression . Here we describe a systematic approach , based on the theory of multivariate outlier detection , to identify individuals that show unusual or aberrant gene expression , relative the rest of the study cohort . Through characterizing detected outliers and corresponding gene sets , we are able to identify which gene sets tend to be aberrantly expressed and which individuals show deviant gene expression within a population . One of our major findings is that private SNPs may contribute to aberrant expression in outlier individuals . These private SNPs are more frequently located in the enhancer and promoter regions of genes that are aberrantly expressed , suggesting a possible regulatory function of these SNPs . Overall , our results provide new insight into the determinants of inter-individual variation , which have not been evaluated by large population-level cohort studies . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [] | 2015 | Aberrant Gene Expression in Humans |
Hypertension ( HTN ) is a devastating disease with a higher incidence in African Americans than European Americans , inspiring searches for genetic variants that contribute to this difference . We report the results of a large-scale admixture scan for genes contributing HTN risk , in which we screened 1 , 670 African Americans with HTN and 387 control individuals for regions of the genome with elevated proportion of African or European ancestry . No loci were identified that were significantly associated with HTN . We also searched for evidence of an admixture signal at 40 candidate genes and eight previously reported linkage peaks , but none appears to contribute substantially to the differential HTN risk between African and European Americans . Finally , we observed nominal association at one of the loci detected in the admixture scan of Zhu et al . 2005 ( p = 0 . 016 at 6q24 . 3 correcting for four hypotheses tested ) , although we caution that the significance is marginal and the estimated odds ratio of 1 . 19 per African allele is less than what would be expected from the original report; thus , further work is needed to follow up this locus .
Essential hypertension ( HTN ) is a widely prevalent condition with devastating clinical consequences including stroke , myocardial infarction , heart failure , and chronic kidney disease . Familial aggregation studies have established HTN as a complex trait , with both environmental and genetic determinants , and heritability for blood pressure has been estimated at about 30% [1] . Although HTN is prevalent worldwide ( with particular abundance in developed countries ) , disease prevalence varies with ethnicity . In the United States , African Americans are disproportionately susceptible to HTN compared with other ethnic groups; they had an adjusted 1 . 6-fold higher prevalence of HTN than European Americans ( and 2 . 5-fold higher than Mexican Americans ) in the National Health and Nutritional Examination Survey ( NHANES ) in 2003–2004 [2] . The higher risk of HTN in African Americans has been hypothesized to be due ( at least in part ) to genetic risk variants that exist at a higher frequency in the ancestral African population than the ancestral European population [3] . Moreover , mean biochemical characteristics , such as plasma renin activity , urinary kallikrein and dopamine levels , differ between African Americans and European Americans with HTN , suggesting potentially different mechanisms of blood pressure elevation [4] . Admixture mapping is a technique that searches for genetic variants that differ strikingly in frequency between continental populations , and also contribute to disease . The idea of admixture mapping is to screen through the genome in a population of recently mixed ancestry , such as African Americans , identifying genome segments where in people with disease , there is a substantial deviation in the proportion of one of the parental ancestries from the genome-wide average . We specifically searched for regions with elevated African ancestry , based on the known higher rate of HTN in people of African ancestry . Although the idea of admixture mapping is not new , it has only recently been implemented in practice with the introduction of panels of ancestry-informative markers [5 , 6] and statistical data analysis methods for detection of disease genes [7–10] . To date , four genome-wide admixture mapping scans have been published: one for HTN [11] , one for multiple sclerosis [12] , one for prostate cancer [13] and one for inflammatory biomarkers [14] . In addition to offering a novel method for identifying genetic determinants of HTN , admixture scans of HTN in African American may offer insights into the differences in salt-handling and blood pressure regulation between Africans/African Americans and European Americans; these differences are epidemiologically well-established and could be due to either genetic or non-genetic causes ( see for example [15] ) .
The ANCESTRYMAP software [7] allows us to make precise estimates of individual African ancestry , which can be tested for correlation to HTN status . We find a trend towards increased African ancestry in hypertensive individuals ( 0 . 760 ) relative to control individuals ( 0 . 749 ) in the MEC; however , the result does not achieve statistical significance . The addition of the African/European ancestry term to a logistic regression model predicting HTN status that includes age , body mass index ( BMI ) , and type II diabetes mellitus status ( T2DM ) also fails to significantly improve the fit of the model ( unpublished data ) . Previous studies have also found a nonsignificant trend of HTN with increasing African ancestry [11 , 18] , We carried out the genome-wide admixture scan by genotyping our 1 , 554 markers in the 1 , 670 individuals with HTN and 387 control participants . The resulting data were analyzed using two methods ( Table 2 ) : ( a ) an affected-only statistic , which calculates likelihood of association based on an estimate of the ancestry at a particular location relative to the overall average of the individual's genome ( obviating the need for a separate control group ) , and ( b ) a case-control statistic , which measures the average ancestry deviation at a particular location in individuals with HTN and compares this with control participants [7] . While the affected-only statistic theoretically has more power to detect risk loci , the case-control statistic ensures that any deviation in African ancestry from the genome-wide average is present only in people with disease ( for example , a locus unrelated to the disease could have been under selection some time in the recent history of the African American population , causing a rise in African ancestry relative to the average in the genome , irrespective of disease status ) . We found no evidence for association to HTN . The genome-wide score , obtained by averaging the evidence of association at equally spaced points across the genome is −0 . 1 in the MEC and 0 . 6 for GCI , which does not meet our published thresholds of 1 for suggestiveness or 2 for significance [19] . The maximum local LOD score is 1 . 9 in the MEC and 3 . 3 in the GCI study ( Table 2 , Figure 1 ) , again falling short of our published threshold of suggestiveness ( LOD = 4 ) or significance ( LOD = 5 ) [19] . Admixture mapping allows the merging of individuals with disease and control participants from multiple cohorts . This can increase the power to detect risk alleles with small effects , although merging data from cohorts collected in different ways can also weaken signals by combining heterogeneous phenotypes . We merged data from the MEC and GCI , yielding a total of 1 , 670 individuals with HTN and 387 control participants . The global genome-wide LOD score for the combined data was −0 . 03 , indicating that the null hypothesis of no disease locus is slightly more favored than the hypothesis of a disease locus somewhere in the genome . The highest local LOD score applying the affected-only statistic was 2 . 09 on the X chromosome ( Figure 1 ) . The site on chromosome 4 with the highest LOD scores in the GCI scan showed a weakened LOD = 1 . 39 in the combined scan . One concern with whole genome scanning for disease variants is the risk of false negatives , with true disease variants buried underneath the noise of many loci , which necessitated a large correction for multiple hypothesis testing . One technique that has been proposed to deal with this problem is to pay special attention to candidate loci based on prior knowledge from linkage studies , association studies , and biological studies [20] . There have already been a handful of studies that mapped genes for extreme forms of HTN or hypotension [21] , dozens of whole genome linkage scans for HTN , and thousands of candidate gene association studies [22 , 23] . In principle , taking these previous studies into account should help to prioritize signals in whole genome scans . To take advantage of this insight , we identified a small set of particularly plausible loci , to which we paid special attention even if the loci did not meet stringent thresholds of statistical significance correcting for scanning the whole genome . We first carried out a focused analysis of 40 candidate genes previously identified in association studies ( Table 3 ) , and which we selected in three ways . First we searched PubMed ( http://www . ncbi . nlm . nih . gov/sites/entrez ? db=PubMed ) , the Genetic Association Database [24] , and the HUGE Database ( http://www . cdc . gov/genomics/hugenet ) for genetic association studies involving HTN or blood pressure . We focused on genes with variants that demonstrated convincing association with HTN or blood pressure in two independent populations ( see Materials and Methods for details of selection process ) . The genes we selected were primarily implicated in the renin-angiotensin-aldosterone axis , the adrenergic system , salt homeostasis , and T2DM . Second , we selected eight candidate loci based on their containing genes known to be causal in familial forms of HTN or hypotension; some of these overlap with those from the first category [21] . Third , we selected five candidate loci highlighted in a recent study by Young et al . [3] , which focused on genetic variants implicated in salt handling and heat dissipation that show substantial worldwide frequency differences and marked differences between Sub-Saharan Africa and Northern Europe . For each of the 40 genes , we calculated odds ratios ( and credible intervals ) for their admixture association to HTN risk in the combined GCI–MEC scan ( Materials and Methods ) . Only three of these loci have a 90% credible interval that excludes no risk due to ancestry: AGTR1 , CYP4A11 , and WNK1 . The WNK1 and AGTR1 genes both show increased HTN risk with inheritance of the African allele , which is the direction that might be expected given that African Americans have a higher rate of HTN ( we estimate an increased risk for HTN of 1 . 11 and 1 . 14 for inheritance of one copy of the African allele at these loci , respectively ) . These signals of association are nonsignificant given the number of genes we tested . Moreover , because of the substantial extent of admixture linkage disequilibrium , even if these signals are real they may simply represent the effect of alleles of nearby genes rather than the proposed candidate genes . Admixture scanning of additional samples and other follow-up will be necessary to confirm these are genuine associations . We also tested whether the admixture signals we found correlated with previously reported linkage peaks . Table 4 includes credible intervals for the top loci found in a recent meta-analyses of whole genome linkage scans for blood pressure traits [25–27] . In our admixture scan , none of these loci showed a significant association of ancestry with HTN risk . Our scan can also be compared with the previous admixture mapping study for HTN , which identified two main candidate loci for association and two secondary loci [11] . We calculated odds ratios and credible intervals for all four of these peaks . Figure 2 demonstrates LOD scores for the 6q24 . 3 , 2p25 . 1 , 21q21 , and 3q13 . 31 loci across a range of risk models . Overall , we find weak evidence for association with HTN for the 6q24 . 3 locus , with estimated odds ratios for HTN of 1 . 19 ( 95% credible interval 1 . 06–1 . 34 , p = 0 . 004 by likelihood ratio test; p = 0 . 016 with Bonferroni correction for four hypotheses ) . For the 6q24 . 1 locus , there is an increased risk of HTN with inheritance of the African ancestral allele . This is the same direction that was also seen in the original report , although the quantitative effect is less than would have been necessary to generate the signal in reference [11] . We constructed an exclusion map to rule out most loci in the genome as contributing substantially increased risk due to African or European ancestry . To obtain the exclusion map we estimated a confidence interval , for each position in the genome , for the factor by which the risk due to African ( or European ) ancestry differs from the risk due to European ( or African ) ancestry at that locus ( Materials and Methods ) . For the 1 , 670 hypertensive individuals , 95 . 9% of the genome could be excluded as having risks > 1 . 3-fold due to African ancestry , and 98 . 7% could be excluded as having risks > 1 . 3-fold due to European ancestry at a significance of p < 0 . 05 ( Table 5 ) . The percentages of the genome excluded at various levels of risk are shown in Table 5 . As our participants derive from two separate populations with different HTN definitions , we expect some loss of power from combining samples . We therefore also constructed an exclusion map with participants from the larger MEC cohort only . The percentage of the genome excluded using the MEC participants is shown in parentheses in Table 5 , and reveals that , at a significance level of p < 0 . 05 , 95 . 4% and 98 . 4% of the genome could be excluded as having risks > 1 . 3-fold due to African ancestry and European ancestry , respectively . Numerous covariates are known to affect blood pressure , including age , smoking , BMI , T2DM , and alcohol use . We considered the possible contribution of these covariates to the admixture association to HTN in two ways . Since T2DM is known to have an effect on blood pressure , we performed an admixture scan using only the 1 , 378 individuals with HTN but without T2DM from MEC and GCI . This revealed no significant or suggestive loci , with a genome-wide score of −0 . 1 and a peak LOD score of 1 . 8 . We also attempted to address the presence of multiple covariates by constructing a logistic regression model for MEC HTN status including age , BMI , and T2DM , all of which are known HTN covariates , and all of which showed a significant association with HTN status in the MEC cohort . Using this model , we sought to identify surprising occurrences of HTN , which could not be accounted for by these three covariates . To do so , we determined the Pearson residual [28] for each individual , ranked participants in order of decreasing residual , and selected the top 25 percent of participants ( highest residuals ) for analysis . These should represent relatively lean , young , non-diabetic hypertensive individuals . Using the same regression model , we determined the Pearson residual for the GCI samples and for further analysis , and selected individuals who passed the cutoff defined in the MEC cohort . We then performed an admixture scan on the 482 individuals from MEC+GCI in the top 25 percent of HTN severity and compared them with 387 MEC control individuals . The genome-wide score is 0 . 0 ( highest local LOD = 1 . 8 ) , which does not reach statistical significance .
We have completed the largest and highest density HTN admixture scan to date and failed to identify any loci that are significantly , or even suggestively , associated with HTN after correcting for multiple hypothesis testing . Our large sample size also allows us to exclude > 95% of the genome as harboring risk loci of > 1 . 3 due to African or European ancestry . Although we cannot rule out weak ancestry effects , the negative results suggest that there may be no common variants with a strong effect accounting for differences in HTN prevalence between African and European Americans . These results thus increase the weight of evidence that non-genetic causes ( diet and environment ) contribute to the different epidemiology across populations . An intriguing aspect of this study is the analysis of four loci from a previously reported admixture scan of HTN [11] . We observed nominal replication of the admixture association at one of these loci ( p = 0 . 016 correcting for four hypotheses tested ) , and the direction of the association ( increased HTN with increased African ancestry ) is the same as previously reported . We caution that these results could represent statistical fluctuations , as numerous other loci in our scan scored more strongly . Another concern is that the estimate for the increased risk for HTN ( 1 . 19 ) arising from the inheritance of one African allele at this locus is sufficiently small that it would have been very surprising to observe genome-wide significant peaks in a scan with the sample size and map density studied by Zhu et al . [11] . Further follow-up studies will be necessary to properly test these loci for association . A possible way to reconcile the results from the two studies is that the samples in the Zhu et al . [11] study had a somewhat different phenotype than the ones we studied . Their definition of HTN , with multiple affected family members , may have been more genetically heritable , and thus their phenotype may have been more likely to yield association signals . We also specifically evaluated risk at 40 biologically plausible HTN candidate gene loci as well as eight previously identified linkage peaks . For a complex disease , such as HTN , in which effects are expected to be weak , combining the wealth of prior genetic and biochemical data with whole genome scans may be essential for uncovering genes . Although our data highlight a small number of candidate loci , including the angiotensin Type I receptor and CYP4A11 , independent studies will be needed for corroboration . We also examined five candidate genes that were highlighted by Young et al . [3] , who proposed that HTN may arise from the interaction of salt-availability in humans populations with heat-adapted alleles that vary widely in frequency across populations . None of the five genes produced an admixture signal , suggesting that the underlying alleles do not explain a substantial amount of differential HTN risk across these populations . A potential pitfall for our analysis is that we combined samples from two different studies , each with a different definition of HTN . The GCI study is based on physician-diagnosis , while the MEC , with its questionnaire-based data collection , obtains most information from patient self-report . To increase comparability across the two studies , we restricted our analysis of the MEC samples to individuals who reported using HTN-specific medications , guaranteeing that both the GCI and MEC samples were physician-treated individuals with HTN . We also performed additional analyses with non-diabetics only ( since the percentage of participants with diabetes differed significantly in the two studies ) . We recognize that the difference in the phenotypes may reduce power for some analyses , as genetic determinants of HTN may not have the same effect in the two populations . In general , in our admixture mapping studies—not only for HTN , but also for prostate cancer [13] and multiple sclerosis [12]—we have taken an inclusive approach , analyzing as many individuals as possible that fit a loose definition of the phenotype , and following up marginal peaks by exploratory analysis across different subgroups . This was successful in identifying a locus for prostate cancer [13]; however , since it can also reduce power in some contexts , here we also present analyses of more homogeneous subgroups . We conclude by noting that other factors may have contributed to our inability to identify HTN genetic variants by admixture mapping . It is possible that the phenotype definition we focused on was not sufficiently strong . Past successes at finding genetic risk factors for HTN have focused on families with extreme , familial forms of HTN , and here we aimed to find common variants affecting more commonly observed HTN in the community and the clinic [21] . For HTN , which is a classic complex trait , there are also a number of covariates that we did not consider , and that may have contributed to reduced power for detection of genetic determinants . In future admixture mapping and whole genome scans for HTN genes in African Americans , it will be particularly important to study samples that have been assessed not only for presence or absence of HTN , but also for differences in covariates that are known to differ across populations such as plasma renin activity , urinary kallikrein , and dopamine levels [4] . This may also offer insights into the differences in blood pressure and salt handling known to exist between African and European Americans [15] .
The samples in this study ( n = 2 , 057 ) were all self-declared African Americans , and came from the California component of the MEC ( n = 1 , 552 ) and from the GCI CARDIO study ( n = 505 ) . MEC is a National Cancer Institute funded prospective cohort of African Americans , Japanese Americans , Latinos , Native Hawaiians , and European Americans in California ( mainly Los Angeles ) and Hawaii . African Americans in this cohort were chosen by selecting census tracts in Los Angeles with a minimum percentage of individuals self-identified as African Americans in the 1990 census . Potential cohort members were identified through Department of Motor Vehicles drivers' license files and , for African-Americans , Health Care Financing Administration data files . Between 1993 and 1996 , participants entered the cohort by completing a 26-page , self-administered ( baseline ) questionnaire that asked about diet , demographic factors , and history of prior medical conditions ( e . g . , HTN ) . In 2001 , a short follow-up questionnaire was sent to update information on specific dietary habits as well as to obtain information about new diagnoses of medical conditions since recruitment . In the MEC , hypertensive individuals were defined as those who indicated on the baseline questionnaire that they had a history of HTN , and had taken or were taking antihypertensive medications , and who reported themselves as hypertensive on the follow-up questionnaire . Normotensive control participants were defined as those who answered no to all of the above questions [16] . The GCI collection consisted of individuals referred by primary care physicians or specialists . For patients to be regarded as hypertensive , they required at least two documented blood pressures > 140/90 prior to the initiation of anti-hypertensive medication . If blood pressures prior to initiation of medication were not available , then the patients required two documented blood pressures > 140/90 while under treatment . The phase one panel ( 911 samples in our study ) consisted of 1 , 824 SNPs , mostly overlapping the set described in reference [12] . The core of this panel consisted of 1 , 536 SNPs chosen from the map published in [5] and genotyped using the Illumina GoldenGate platform [29]; we then supplemented this panel with an additional 288 SNPs genotyped on the Sequenom MassArray and iPLEX platforms [30] to fill in gaps in the map and increase density at regions of high interest . The phase two panel ( 1 , 146 samples in our study ) consisted of 1 , 566 SNPs , largely overlapping the panel described in reference [14] . This panel was constructed by supplementing the database of ancestry informative markers reported on in Smith et al . [5] , with > 1 , 500 new markers selected from Hinds et al . [31] as likely to be highly informative about ancestry and to fill in gaps in the phase one panel . The final phase two panel of SNPs was chosen as the most informative 1 , 536 SNPs from the extended database ( genotyped on the Illumina GoldenGate platform ) , supplemented by 30 SNPs genotyped using the Sequenom MassArray and iPLEX platforms [30] to increase density in regions of high interest . To obtain frequency estimates for each of the SNPs in Africans and Europeans , we used previously published data [5 , 13] . West African ancestral frequencies were estimated using samples from Ghana ( n = 33 ) , Cameroon ( n = 20 ) , and Nigeria ( n = 122 ) . European frequencies were obtained using samples from Baltimore ( n = 38 ) , Chicago ( n = 39 ) , Italy ( n = 42 ) , Poland ( n = 47 ) and Utah ( n = 93 ) . These samples provided a Bayesian prior distribution for the allele frequencies in the parental populations as described in reference [7] . All the MEC samples were subjected to whole-genome amplification ( Molecular Staging ) to produce sufficient DNA sufficient for genotyping [32] . DNA samples were excluded if they showed ( a ) less than 85% genotyping success rate , or ( b ) a striking excess or deficiency of heterozygote genotypes compared with that expected from the individual's estimated proportion of European ancestry . The high heterozygosity filter is aimed at removing individuals who have one European parent , and who are not correctly modeled by the ANCESTRYMAP software so that analysis of these samples might weaken statistical power [7] . The low heterozygosity filter is aimed at removing individuals with low quality DNA and high genotyping error rate . We used a series of criteria for eliminating SNPs from the analyses . We started with two panels of SNPs , designated phase one consisting of 1 , 824 SNPs and phase two consisting of 1 , 566 SNPs . A total of 760 SNPs were common to both panels , leaving 2 , 630 unique SNPs . Individuals were genotyped in either the phase one or phase two panel , but not both . We eliminated SNPs from the analysis by including only those with > 85% genotyping success rate in African American HTN participants , and that had reliable genotype clustering patterns as judged by an experienced research technician ( GJM ) . This left 2 , 007 SNPs . We next imposed a requirement for Hardy-Weinberg equilibrium ( p > 0 . 01 ) in both the ancestral West African or European American populations . Finally , we required that the frequency in African American control participants was appropriately intermediate between ancestral West Africans and European Americans [7] . This left 1 , 966 SNPs . We also eliminated SNPs that demonstrated linkage disequilibrium in the parental populations , as these are liable to produce false positive signals of association [19] . After these filters , we were left with 1 , 554 markers useable for analysis . The ANCESTRYMAP software described in [7] was used for all analyses . The program combines information from multiple , densely spaced markers that are each partially informative about African versus European ancestry , to produce robust , multipoint estimates . The LOD score for association is defined as the log ratio of the likelihood of the data under a disease model , divided by the likelihood of the data under no disease model . We evaluated LOD scores at equally spaced points across the genome . At each point , we used a multiplicative model of risk , with risk of disease integrated over the inheritance of 0 , 1 , and 2 copies of an African ancestral allele . By the convention used in the manuscript , a risk > 1 . 0 for inheritance of one African ancestry allele at a given locus describes a model where African ancestry increases disease risk relative to European ancestry . The ANCESTRYMAP software uses Bayesian statistics and thus requires specification of a prior distribution on risk models before carrying out the analysis . We ran a range of risk models for the MEC , GCI , and MEC+GCI samples , and averaged the LOD score at equally spaced points in the genome ( one point every centimorgan ) . The prior distribution we used was a range of ten risk models from 1 . 6-fold increased risk due to inheritance of one African ancestral allele to 1 . 6-fold increased risk due to inheritance of one European allele . We used three overlapping sources to identify candidate genes: PubMed ( http://www . ncbi . nlm . nih . gov/sites/entrez ? db=PubMed ) , the Genetic Association Database [24] , and the Human Genetic Epidemiology ( HUGE ) Database ( http://www . cdc . gov/genomics/hugenet ) . We searched PubMed for all references mentioning association of genetic variants with HTN or blood pressure ( details of search terms are available upon request ) . We performed similar searches using the Genetic Association Database and the HUGE database . We identified over two hundred genes for which variants had been tested for association with HTN . From these , we selected genes that had positive associations for at least one variant with blood pressure or HTN in two or more populations . We restricted ourselves to association studies with at least 100 participants with HTN and 100 control participants or 200 total individuals for quantitative trait evaluation . For each candidate gene , we identified the genetic position using Build 35 of the public genome reference sequence ( http://genome . ucsc . edu ) and selected the closest marker to estimate the ancestry-associated HTN risk at that locus . To obtain credible intervals for increased risk due to African ancestry at candidate loci in the genome , we carried out repeated runs of ANCESTRYMAP , each testing for a different disease model . The analysis was repeated for 65 disease models , consecutively running the analysis software for disease risk models of 0 . 40 , 0 . 42 , 0 . 44 , 0 . 46 … , 1 . 66 , 1 . 68 and 1 . 70-fold increased risk due to one African allele , and searching for the maximum likelihood risk model . The 90% and 95% credible intervals for increased risk due to African ancestry were obtained by a likelihood ratio test: as the range of models for which the log base ten of the likelihood of the disease model was within 0 . 588 and 0 . 883 of the maximum ( we used interpolation to extract the disease risk model , accurate to two decimal places , that met this criterion ) . A logistic regression model was developed to predict HTN status using the 1 , 165 MEC HTN participants and 387 MEC HTN control participants , with age , BMI , and T2DM status as independent variables . Full covariate information was available for 1 , 132 MEC participants with HTN and all 387 MEC control participants . Using coefficients determined from the model , the Pearson residual [28] was calculated for each individual . Individuals were ranked by residual , and the top 25% of individuals were selected for the analysis . Using the same coefficients , a regression residual was also calculated for the 505 GCI participants , and the 199 individuals with residuals above the same cutoff were selected for a combined admixture scan with the 283 MEC participants and 387 MEC control participants . All analyses were performed using Stata 8 . 0 ( StataCorp ) . See http://genepath . med . harvard . edu/~reich for our ANCESTRYMAP software .
Accession numbers for genes mentioned in this paper from the Entrez GeneID database ( http://www . ncbi . nlm . nih . gov/sites/entrez ? db=gene ) are ACE ( 1636 ) ; ADD1 ( 118 ) ; ADIPOQ ( 9370 ) ; ADRB1 ( 153 ) ; ADRB2 ( 154 ) ; ADRB3 ( 155 ) ; AGT ( 183 ) ; AGTR1 ( 185 ) ; CORIN ( 10699 ) ; CYBA ( 1535 ) ; CYP11B2 ( 1585 ) ; CYP3A5 ( 1577 ) ; CYP4A11 ( 1579 ) ; DRD1 ( 1812 ) ; ECE1 ( 1889 ) ; EDN1 ( 1906 ) ; EDNRA ( 1909 ) ; GNAS ( 2778 ) ; GNB3 ( 2784 ) ; GRK4 ( 2868 ) ; HSD11B2 ( 3291 ) ; IL6 ( 3569 ) ; MMP3 ( 4314 ) ; MTHFR ( 4524 ) ; NOS3 ( 4846 ) ; NR3C2 ( 4306 ) ; PPARG ( 5468 ) ; PPARGC1A ( 10891 ) ; REN ( 5972 ) ; RETN ( 56729 ) ; RGS2 ( 5997 ) ; SCNN1A ( 6337 ) ; SCNN1B ( 6338 ) ; SCNN1G ( 6340 ) ; SGK1 ( 6446 ) ; SLC12A3 ( 6559 ) ; SLC4A5 ( 57835 ) ;TNF ( 7124 ) ; WNK1 ( 65125 ) ; and WNK4 ( 65266 ) . | High blood pressure is more frequent and severe among African Americans than European Americans . To explore whether there are genetic underpinnings to this pattern , we screened the genomes of 1 , 670 African Americans , searching for loci at which people with hypertension ( HTN ) have more than the average proportion of African ancestry ( eighty percent ) . We do not detect any region of clearly significant association . In a previous , smaller admixture scan for HTN genes , Zhu and colleagues ( 2005 ) reported two regions of association , which we would have expected to replicate if they were as strong as they initially appeared . While we detect marginal evidence of association at one , the signal is very weak , and much weaker than would have been expected from the previous report , so further work is necessary to understand this region . Our results are consistent with there being no common variants with a strong effect accounting for differences in HTN prevalence between African and European Americans . This increases the weight of evidence that non-genetic causes explain most of the difference in rates across populations . | [
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clinicaltrials . gov NTC02092116
Antiretroviral therapy ( ART ) effectively suppresses viral replication and partially restores immune functions in human immunodeficiency virus type-1 ( HIV-1 ) infected individuals [1] . However , HIV-1 integrates into the host DNA , thus establishing the basis for latent infection . As ART cannot eliminate transcriptionally inactive or latent virus , adjunctive interventions that efficiently activate latent virus are needed to achieve the ultimate goal of a cure for HIV-1 infection . HIV-1 preferentially integrates into the host genome of activated CD4+ cells [2 , 3] . Upon integration , activation of the host cell transcription machinery leads to the production of new virions . Cells that are actively producing virus typically die rapidly ( half-life ~24 hrs ) due to virus-induced cytopathic effects and/or immune-mediated killing [4] . However , a minority of memory CD4+ T cells carrying replication-competent provirus persists in a resting state during viral suppression by ART [5 , 6] . Such transcriptionally silent infected cells are invisible to the host immune system but retain the capacity to reinitiate production of infectious viral particles upon activation . This latent reservoir , likely established within days of infection [7] , persists throughout life due to long half-life as well as proliferation of the latently infected memory CD4+ T cells [8 , 9] , and thus represents the primary barrier to an HIV-1 cure [10] . One proposed way of curing HIV is to activate virus transcription and kill latently infected cells in the presence of ART to prevent spreading the infection [11] . Induction of global T cell activation by mitogenic or other potent activators ( e . g . PHA , PMA , prostratin ) effectively reverses HIV-1 from latency ex vivo [12 , 13] , but such compounds are generally too toxic for clinical use [14] . Therefore , investigating the capacity of small molecule latency reversing agents ( LRA ) to induce production of virus without causing global T cell activation has been a top research priority for researchers in recent years [15–17] . The ability to induce HIV-1 viremia or at least cell surface expression of viral proteins and presentation of viral antigens is a fundamental requirement for enabling immune mediated killing of latently infected cells and , thus , defines the key goal of LRAs in eradication strategies . A central mechanism for maintaining HIV-1 latency is the activity of histone deacetylases ( HDAC ) that represses proviral transcription by promoting histone deacetylation [3 , 18] . Several studies have shown that HDAC inhibitors ( HDACi ) can disrupt HIV-1 latency in vitro [19–21] . There is , however , great variability in the potency among HDACi and very limited data exist on clinical efficacy of various HDACi in reversing HIV-1 latency [15] . Vorinostat , the first potent HDACi to be investigated in a HIV-1 clinical trial [22] , increased HIV-1 transcription in CD4+ T cells but did not induce plasma HIV-1 RNA in two multiple-dose studies [23 , 24] . In contrast , we recently demonstrated that treatment with panobinostat , a hydroxamic acid pan-HDACi like vorinostat , increased both HIV-1 transcription as well as the proportion of plasma samples positive for HIV-1 RNA in 15 ART suppressed participants [25] . Although no significant reductions in the size of the latent HIV-1 reservoir were observed in any of these studies , they demonstrated that HDACi exhibit desired key qualities of LRA including the ability to induce virus transcription in vivo . To investigate further the potential of HDACi as the LRA component in the ‘kick and kill approach’ to purge the HIV-1 reservoir , we initiated a study of romidepsin , the most potent HDACi according to ex vivo measures [26] , to investigate its clinical safety and potential for reversing HIV-1 latency in individuals on long-term ART . In addition , we investigated the impact of romidepsin on T cell activation and function in light of the findings of a recent in vitro study suggesting that HDACi negatively affect cytotoxic T-lymphocytes thus impairing the elimination of HIV-infected cells by [27] . The trial data reported here are the results of the first part of a two-step clinical trial . The objective of the first part was to verify the safety and effect of romidepsin prior to incorporation into the second part comprising combination therapy with romidepsin and the therapeutic HIV-1 vaccine , vacc-4x ( Bionor Pharma ) [28] .
Six HIV-1 infected persons ( 5 male , 1 female ) were enrolled in the study ( Fig 1 ) . The study participants were all Caucasian and had been on ART for a median of 9 . 5 years ( range 4 . 2–14 . 5 ) with a median CD4+ count of 645 cells per μL ( range 510–1 , 000 ) at inclusion ( baseline characteristics shown in Table 1 ) . All six participants received one 4 hour romidepsin infusion ( 5 mg/m2 ) per week for three consecutive weeks and were followed for up to 70 days after the last infusion . The per-protocol defined dose of romidepsin ( 5 mg/m2 ) had not been investigated previously in HIV patients and corresponded to ~36% of the recommended dosing in cancer treatment ( 14 mg/m2 ) . We observed no severe adverse events ( SAEs ) or suspected unexpected serious adverse reactions ( SUSAR ) . Forty-one adverse events ( AE ) were registered during follow-up of which 35 AEs were considered related to romidepsin ( Table 2 ) . All drug-related AEs were mild ( grade 1 , n = 35 ) and resolved spontaneously within a few days . The number of AEs reported by each study participant during follow-up ranged from 1 to 13 . The most common romidepsin-related AEs were abdominal symptoms ( e . g . nausea [n = 11] , borborygmia [n = 4] , abdominal pain [n = 2] ) and fatigue ( n = 5 ) . Modest changes in white blood cell counts ( WBC ) and T cell counts were observed during the study ( S2 Fig ) with the lowest levels generally observed after the second romidepsin infusion , but no further decline following the third infusion . Reassuringly , neutrophil counts below 1000 cells/μL , CD4+ cell counts below 350 cells/μL , or platelet counts below 100 , 000 cells/μL were not observed . The level of histone acetylation is a biomarker of the pharmacodynamic effect of an HDACi on cells [25] . Using flow cytometry , we observed cyclic increases in lymphocyte histone H3 acetylation following each romidepsin infusion confirming the anticipated biological effect of the drug ( Fig 2A ) . The peak level of lymphocyte histone H3 acetylation tended to be higher from the first to third infusion ( p = 0 . 06 ) . Next , as an intracellular measure of HIV-1 transcription in latently infected cells we quantified changes in cell-associated un-spliced HIV-1 RNA ( CA US HIV-1 RNA ) [29] . In all 6 patients , CA US HIV-1 RNA levels increased significantly from baseline to multiple on-treatment time points ( p = 0 . 03 , Fig 2B and S1 Fig ) . CA US HIV-1 RNA peaked immediately ( ~½ hr ) after the completion of each romidepsin infusion but the increases in HIV-1 transcription were most pronounced after the second and third infusion ( maximum fold-increase from baseline ranged from 2 . 8 to 5 . 0 ) . We found no association between baseline CA US HIV-1 RNA and the relative increase in HIV-1 transcription ( S1 Fig ) . To determine if the observed increases in HIV-1 transcription also led to the viral particle release into the plasma , we quantified plasma HIV-1 RNA using a standard clinical assay ( Roche COBAS TaqMan HIV-1 Test , v2 . 0 , lower limit of quantification of 20 copies/mL ) . In 5 of 6 patients , plasma HIV-1 RNA increased from undetectable levels at baseline to quantifiable levels ( range 21–119 copies/mL ) at least once post-infusion ( Fig 2C , p = 0 . 03 for baseline compared to day 10 after first infusion ) . While two participants had had plasma HIV-1 RNA “blips” of 81 copies/mL and 64 copies/mL 2 . 3 and 9 . 3 years prior to inclusion , respectively , the median duration of viral suppression below 50 copies/mL prior to study inclusion was 9 . 1 years ( Table 1 ) . Despite comparable levels of HIV-1 transcription , quantifiable plasma HIV-1 RNA was detected in only 2 of 6 subjects after the third infusion compared to 5 of 6 after the second infusion ( p = 0 . 24 ) . These increases in plasma HIV-1 RNA were subsequently confirmed ( Fig 2D ) with a transcription mediated amplification ( TMA ) -based methodology ( Procleix Ultrio Plus , Genprobe ) that is commonly used for screening donor blood for HIV-1 infection [30] . The detection of quantifiable plasma HIV-1 RNA coincided with romidepsin infusions and generally appeared following increases in lymphocyte H3 acetylation as well as HIV-1 transcription ( Fig 2E and 2F ) . In one participant ( ID3 , Fig 2C ) who initially displayed detectable plasma HIV-1 RNA and then became undetectable by 7 days after the third infusion , we observed quantifiable plasma HIV-1 RNA of 42 and 68 copies/mL at day 56 and 84 post first romidepsin dose , respectively . This individual reported being adherent to ART throughout the study and no external cause for the appearance of quantifiable HIV-1 RNA at the late follow-up visits could be identified . Extended follow-up revealed that by day 112 following the third infusion , plasma HIV-1 RNA had returned to undetectable levels in this individual . Altogether , these data demonstrate that romidepsin had a pronounced and consistent effect on HIV-1 transcription leading to quantifiable levels of plasma HIV-1 RNA using a standard clinical assay . To determine if reversal of HIV-1 latency by romidepsin impacted the viral reservoir , we first used qPCR-based assays to measure total HIV-1 DNA and 2-LTR episomes in CD4+ T cells isolated from the 6 participants . Although one participant had a 67% decline in total HIV-1 DNA from baseline to last follow-up , we observed no overall change in total HIV-1 DNA levels indicating that the frequency of CD4+ T cells harboring total HIV DNA remained stable following romidepsin administration ( Fig 3A and 3B ) . On a cohort level , the amount of 2-LTR HIV-1 DNA also did not change during the study ( Fig 3C ) . Of note , a large increase in 2-LTR HIV-1 DNA was observed in the individual receiving integrase-inhibitor based combination ART . Next , we used the novel Tat/rev Induced Limiting Dilution Assay ( TILDA ) to measure the frequency of cells with multiply spliced HIV RNA upon maximal cellular activation with PMA/ionomycin before and after romidepsin treatment ( Fig 3D ) . Four of 4 ( 100% ) participants with available samples , were TILDA positive before romidepsin treatment , and 5 of 6 ( 83 . 3% ) patients were TILDA positive 6 weeks after the third romidepsin infusion . In the four participants with available samples before romidepsin , 2 of 4 participants had stable numbers of positive events in the TILDA assay from pre/on romidepsin levels to 6 weeks after the last infusion ( 1–2% decrease ) whereas 2 of 4 participants had moderate 49–83% decreases . Finally , we used a quantitative viral outgrowth assay ( qVOA ) to assess changes in the frequency of resting CD4+ cells carrying inducible replication competent proviruses . We found no significant changes the replication competent reservoir from baseline to 6 weeks after the third romidepsin infusion as measured by qVOA ( Fig 3E and S1 Table ) . Overall , we found no substantial reduction in the frequency of cells harboring total HIV-1 DNA or in the size of the inducible replication-competent HIV-1 reservoir following romidepsin treatment . To assess the effects of romidepsin on differentiation and activation status of T cells , we performed flow cytometry analyses at day one , day 10 , and day 56 after the first romidepsin infusion . First , we observed changes in the relative proportions of both CD4+ and CD8+ T cell memory subsets . The mean frequency of naïve CD4+ T cells increased from 47 . 3% at baseline to 56 . 9% day one after the first dose ( p = 0 . 03 ) ( Fig 3A ) . These frequencies had returned to pre-dosing levels at the subsequent time points . Similarly , the frequency of naïve CD8+ T cells significantly increased 24 hours after the first dose ( baseline 19 . 3% to 31% on day 1 , Fig 3B ) . T cell activation was evaluated by measuring the frequency of cells expressing CD69 or co-expressing HLA-DR and CD38 ( gating strategy depicted in S3 Fig ) . The percentage of both CD4+ and CD8+ T cells expressing CD69 increased substantially at 24 hours after the first dose ( Fig 4C and 4D ) . The largest increase in percentage of cells expressing CD69 was observed in the effector memory ( EM ) CD4+ T cells ( mean increase from 11 . 9% to 23 . 7% CD69+ , Fig 4C ) and terminally differentiated ( TD ) CD8+ T cells ( Fig 4D ) . Similarly , the proportion of CD4+ and CD8+ cells co-expressing HLA-DR/CD38 increased significantly over baseline at three days following the second infusion ( Fig 4E and 4F ) . As observed for CD69 , the greatest increase in HLA-DR/CD38 co-expressing CD4+ and CD8+ T cells was observed in the effector memory compartment . Further , we evaluated the effect of romidepsin on frequency of CD4+ and CD8+ T cells expressing the exhaustion marker PD-1 . Day one after the first infusion there was a significant decrease in the frequency of both CD4+ and CD8+ T cells expressing PD-1 and for the CD4+ T cells there was also a reduction at day 10 after the first infusion ( Fig 4G and 4H ) . These early changes in the frequency of cells expressing PD-1 which were found across all memory subsets had returned to pre-dosing baseline levels at day 56 after the first infusion . In vitro data suggests that HDACi , and romidepsin in particular , may induce or intensify T cell dysfunction compromising the clearance of virus-producing cells [27] . To investigate whether this finding could be recapitulated during clinical administration , we first evaluated the impact of romidepsin on the function of HIV-1-specific CD4+ and CD8+ T cells . Following ex vivo stimulation of PBMCs with a library of 150 overlapping HIV-gag peptides , we performed intracellular cytokine staining ( ICS ) for IFN-γ , TNF-α and IL-2 ( S4 Fig ) . The HIV-1-specific CD8+ T cells primarily exhibited an EM or TD phenotype and produced solely IFN-γ or both IFN-γ and TNF-α . The majority of HIV-1-specific CD4+ T was EM cells and co-produced all three cytokines analyzed . The ICS analyses showed no negative impact on the CD4+ or CD8+ T cell capacity to produce IFNγ , TNFα , or IL-2 following romidepsin administration , both with regard to the frequency ( % ) of HIV-gag specific EM CD4+ and EM and TD CD8+ T cells present and with regard to the levels ( MFI ) of cytokines produced by the individual cells ( Fig 5A–5H ) . We also found no change in non-HIV-1 specific CD4+ and CD8+ T cell responses to staphylococcal enterotoxin b ( SEB ) during romidepsin treatment ( S5 Fig ) . Similar to the flow cytometry-based measures , ELIspot analyses with overlapping HIV p24 gag peptides showed no change in functional responses following romidepsin treatment ( S6 Fig ) . Collectively , these data indicate that romidepsin treatment had no detrimental effect on HIV-1-specific and general T cell immunity in this study .
Herein , we demonstrated that significant viral reactivation can be safely induced using the HDACi romidepsin in long-term suppressed HIV-1 individuals on ART . The cyclic increases in lymphocyte H3 acetylation , HIV-1 transcription , and plasma HIV-1 RNA following infusion of romidepsin link the events leading from romidepsin infusion , via epigenetic modification and induction of HIV-1 transcription , to increases in plasma HIV-1 RNA . Importantly , this reversal of HIV-1 latency was measured using standard clinical assays for detection of HIV-1 RNA in plasma . Furthermore and very important from a safety perspective , romidepsin did not alter the proportion of HIV-1-specific T cells or inhibit T cell cytokine production . However , despite the increases in viral production and preserved T cell functions , no substantial changes in the size of the HIV-1 reservoir were observed . Previous clinical trials provide support for the use of HDACi to safely disrupt HIV-1 latency in vivo; however , the magnitude of viral induction in the present study was greater than anything previously reported for any LRA tested in humans . In the pioneering study by Archin et al . [22] , a single 400 mg oral dose of the HDACi vorinostat produced a median 4 . 6 fold increase in HIV-1 transcription in resting memory CD4+ T cells . Despite the clear increase in HIV-1 transcription , no increase in plasma HIV-1 RNA could be detected using the ultrasensitive single copy assay [22 , 31] . Subsequent multi-dose studies have confirmed an effect of vorinostat on HIV-1 transcription but no consistent changes in plasma HIV-1 RNA were detected in these studies [23 , 24] suggesting that post-transcriptional blocks may mitigate the effect of vorinostat as an LRA[32] . Further , a recent publication questioned whether any of the clinically available LRAs would be potent enough to reverse latency when administered individually [13] . The present study demonstrated potent in vivo latency reversal with a single drug resulting in increased plasma HIV-1 RNA that was readily quantified with standard commercial assays . However , the exact proportion of infected cells reversed from latency out of the total pool of inducible latently infected cells remains unknown . Another key observation in the present study was the unambiguous increase in HIV-1 transcription and release of viral particles following the second romidepsin infusion as compared to following the first romidepsin infusion . Clearly , the hyper-acetylated state induced by the first romidepsin infusion ( Fig 2B ) did not reach baseline level before the second romidepsin infusion . Therefore , the effect of the second romidepsin infusion may add to the sustained effects of the first infusion , which might explain the more pronounced effect on HIV-1 transcription and viral particle release . It is likely that on a single cell basis HIV-1 transcription needs to cross a certain threshold to overcome transcriptional blocks before it gives rise to viral protein translation and virion production [3] . Such an outcome would be consistent with the increase in both CA US and plasma HIV-1 RNA following the second infusion . Interestingly , lymphocyte H3 histone acetylation and CA US HIV-1 RNA levels further increased following the third infusion , compared to after the second infusion , whereas plasma HIV-1 RNA did not . Up-regulation of intracellular factors that block viral translation , unknown effects of romidepsin or the induction of intracellular antiviral immune responses towards HIV-1 could also account for this observation but larger studies are needed to shed light on whether this potential difference in response between the second and third infusion is biologically relevant . In addition , indirect effects of romidepsin on CD4+ T cells such as more generalized activation ( as measured by CD69 expression ) may also play a role in the observed increases in HIV transcription . HDACs are epigenetic regulators with the capacity to alter the expression of genes involved in a broad range of immune cell functions , thus affecting their interaction with and responsiveness to pathogens [33] . In vitro studies have suggested that HDACi in general and romidepsin in particular inhibit HIV-1 specific T cell immunity leading to impaired clearance of virus-producing cells [27] . In this study , we examined the participants’ cellular immunity and found no evidence for suppression of HIV-1-specific or non-HIV-1-specific CD4+ or CD8+ T cell immunity during or after romidepsin treatment . Our clinical observations are in line with other findings from anti-tumor experiments showing that T and NK cells are resistant to the immunosuppressive functions of HDACi [34] . Further , in our study expression of the negative regulator of immune responses , PD-1 on CD4+ and CD8+ T cells , decreased significantly while T cell activation increased suggesting that romidepsin did not impair T cell reactivity . Collectively , our findings strongly suggest that romidepsin does not negatively affect T cell functions in vivo which is critically important for future trials combining HDACi with interventions ( e . g . therapeutic HIV-1 vaccination ) designed to enhance CTL-mediated killing of latently infected cells . One such trial combining romidepsin and therapeutic HIV-1 vaccination using vacc-4x is currently under way as part B of the present study in our clinic ( see http://clinicaltrials . gov NTC02092116 ) . In the current study , we found no significant effect of romidepsin treatment on the size of the HIV-1 reservoir when measuring total HIV-1 DNA , the frequency of cells with multiply spliced HIV RNA upon maximal cellular activation with PMA/ionomycin according or by qVOA . Whether this persistence of a functional reservoir is due to incomplete latency reversal and/or insufficient clearance of reactivated cells ( e . g . due to CTL-resistant viruses as recently suggested [35] ) remains to be investigated . In general , the safety and tolerability of HDACi in latency reversal trials has been good . Nevertheless , due to the broad epigenetic effects of HDACi including the potential to modulate signaling pathways and the expression of numerous proteins , careful monitoring of adverse events is essential [23–25] . In accordance with experiences in oncology patients [36] , the most frequently reported adverse effects of romidepsin in HIV-infected persons were abdominal symptoms and fatigue . While these symptoms were common in this study , they were generally mild and did not lead to dose de-escalations or study withdrawals according to the pre-specified protocol criteria . In addition to potential AE that lead to patient discomfort , animal and in vitro studies indicate that HDACi could potentially interfere with the function of other immune cells such as plasmacytoid dendritic cells , macrophages , and neutrophils , leading to increased risk of infection [27 , 37] . Reassuringly , in our trial and in previous trials using HDACi treatment to reverse HIV-1 latency , an increased risk of infections among study participants has not been observed [23–25] . Further , we did not observe clinically significant or persistent decreases in neutrophil , monocyte , CD4+ , or CD8+ counts . Collectively , our data suggest that the utilized romidepsin dosing schedule has an acceptable safety profile in HIV-1-infected persons and does not result in persistent changes in blood biochemistry levels . While our findings can be used as a basis for investigating romidepsin in future HIV eradication trials , the limitations of this study should also be acknowledged . First , the small sample size limited the strength of our statistical analyses . Despite this limitation , the cyclic appearance and near-identical inter-individual patterns of HIV-1 transcription and plasma HIV-1 RNA levels , clearly show that pronounced viral reactivation does occur during romidepsin treatment in ART treated HIV-1 subjects . Second , our study only included Caucasians and care should be taken when generalizing the results to other populations as responses to romidepsin may differ among populations [38] . In summary , in this study we demonstrated significant reversal of HIV-1 latency following romidepsin infusions . Romidepsin-induced increases in HIV-1 transcription were followed by increases in readily measurable plasma HIV-1 RNA . Plasma HIV-1 RNA peaked at levels readily quantifiable with certified clinical assays thus establishing a new benchmark for future trials investigating the in vivo potency of LRAs to be used in HIV-1 eradication efforts .
We conducted this single-arm , single-site , phase Ib/IIa clinical trial at Aarhus University Hospital , Denmark as a first step of a two-step clinical study between March 2014 and July 2014 . This study enrolled HIV-1 infected adults on ART with virological suppression for at least one year ( <50 copies/mL , minimum 2 measurements per year ) and CD4+ T cell counts above 500/μL at inclusion . Major exclusion criteria included: hepatitis B or C co-infection; clinically significant cardiac disease including QTc-prolongation; any significant acute medical illness in the 8 weeks prior to inclusion; unacceptable values of the hematologic and clinical chemistry; history of malignancy; or diabetes . Full details regarding inclusion/exclusion criteria can be found at http://clinicaltrials . gov . Approximately one hour prior to romidepsin treatment , a blood draw was performed . Hematologic and clinical chemistry was checked pre-infusion and additional material stored for endpoint analyses . Thirty minutes prior to infusion patients received 8 mg ondensatron as prophylactic antiemetic treatment . Patients received romidepsin ( 5 mg/m2 ) administered intravenously over a 4 hour period once weekly for three consecutive weeks while maintaining ART . This dose regimen corresponds to the 28-day cyclic regimen used to treat T cell lymphomas but at ~36% of the recommended oncology dose ( 14 mg/m2 ) . The dose of 5 mg/m2 was chosen based upon extensive pre-clinical ex vivo testing of the ability of romidepsin to induce HIV-1 production in latently infected resting CD4+ T cells isolated from ART suppressed HIV patients [26] . Of note , romidepsin is metabolized through CYP3A4 and inhibitors or inducers of this enzyme could affect romidepsin exposure . In a pharmacokinetic drug interaction trial the strong CYP3A4 inhibitor ketoconazole increased the overall romidepsin exposure by approximately 25% and 10% for area under the curve ( AUC ) 0-∞ and peak exposure ( Cmax ) , respectively , compared to romidepsin alone [39] . Thus , co-administration of ketoconazole slightly decreased the romidepsin clearance and volume of distribution , but did not have a statistically significant effect on Cmax . While ketoconazole is classified by FDA as a strong in vivo inhibitor of CYP3A4 , protease inhibitors such as darunavir/ritonavir and atazanavir are classified as moderate inhibitors of CYP3A4 whereas efavirenz is classified as a moderate inducer of CYP3A4 [40] . Based on a thorough evaluation of the romidepsin investigator’s brochure , we estimated that the risk of clinically significant drug-drug interaction was extremely low and that a potential interaction between antiretroviral drugs and romidepsin was very unlikely to cause >25% increase/decrease in romidepsin exposure . Including the baseline , on therapy and follow up visits , there were a total of 13 study visits . Blood was drawn at each visit including 1 hour prior to and 1/2 hour after receipt of each dose , 24 and 72 hours after the first dose , 72 hours after the second and third dose , as well as 1 , 6 , and 10 weeks after completion of romidepsin . At each follow-up visit , self-reported adherence to ART was recorded . Safety assessments were actively performed during on all study visits . This included recording all patient-reported adverse events ( AEs ) and serious adverse events ( SAEs ) . For each AE/SAE the relationship to romidepsin was evaluated and the severity graded according to the Common Terminology Criteria for Adverse Events ( CTCAE ) version 4 . 0 . The pre-specified primary endpoint was safety and tolerability of romidepsin at a reduced dosing of 5 mg/m2 in HIV-1 infected patients . Secondary endpoints included change from baseline in HIV-1 transcription according to CA US HIV-1 RNA measures in unfractionated CD4+ T cells , change from baseline in plasma HIV-1 RNA , and change from baseline in total HIV-1 DNA per 106 CD4+ T cells . Changes from baseline in T cell activation markers , T cell subset distribution , and PD-1 expression as well as changes from baseline in HIV-1-specific and non-HIV-1-specific T cell immunity were exploratory immunological endpoints . Change from baseline in the frequency of cells with multiply spliced HIV RNA upon maximal cellular activation with PMA/ionomycin using a novel assay Tat/rev Induced Limiting Dilution Assay ( TILDA ) and 2-long terminal repeat ( LTR ) circles per 106 CD4+ T cells were exploratory virological endpoints . For quantification of CA US HIV-1 RNA , CD4+ T-cells were isolated from peripheral blood mononuclear cells ( PBMC ) using a CD4+ T-cell isolation kit and magnetic-activated cell sorting ( MACS ) columns ( Miltenyi Biotec , Teterow , Germany; purity >95% ) . Isolated CD4+ cells were lysed and lysates were stored at -80°C until RNA and DNA was extracted ( Allprep isolation kit , Qiagen ) . Template preparation and denaturation was performed in 13 . 5μL reaction volume containing a mixture of 11 . 5μL patient extracted RNA , 1μL of 10mM deoxynucleoside triphosphates mix , 1 . 5 μg of random primers and 0 . 25 μg Oligo ( dT ) 12-18 primer ( LifeTechnologies , Denmark ) at 65°C for 5 min followed by immediate incubation on ice for 5 min . First-strand cDNA production was performed by adding a mixture of 4 μL 5X first-strand buffer ( 250 mM Tris-HCl ( pH 8 . 3 ) , 375 mM KCl , 15 mM MgCl2 ) , 1μL of 0 . 1M DTT , 20 U RNaseOUT Recombinant RNase Inhibitor and 200 units of SuperScriptTM III reverse transcriptase ( LifeTechnologies , Denmark ) . Reverse transcription was performed in the resulting 20μL total reaction volume at 42°C for 45 minutes followed by heat inactivation of the reverse transcriptase at 80°C for 15 minutes . The ddPCR mixture for the CA US HIV-1 RNA assay consisted of: 11 μL 2x digital PCR supermix ( BioRad , DK ) , 3 μL of primer/probe ( primers SL19/20 final concentration1000nM and MGB probe SL30MIDDLE 5’-TACTCACCAGTCGCCGC-3 final concentration 250nM , 5μL nuclease-free water and 3μL patient derived cDNA resulting in 22μL reaction volume . To adjust for the total cellular input in each sample , relative copy numbers were normalized to two human endogenous control genes: TBP PL ( VIC ) assay ID—Hs00183533_m1 and IPO8 ( FAM ) assay ID—Hs00427620_m1 ( TaqMan gene expression assay , LifeTechnologies , Denmark ) . All HIV RT samples were assayed in six replicates while the reference genes were assayed in duplicate . The PCR reaction mixture was loaded into the BioRad QX- 100 emulsification device fractionating each sample into ~20 , 000 nanoliter-sized droplets following the manufacturer’s instructions . PCR cycling conditions were as follows: 95°C for 10 min , followed by 40 cycles of a 30 second denaturation at 95°C followed by a 59°C extension for 60 seconds and a final 10 minutes at 98°C . After cycling droplets were subsequently read automatically by the QX100 droplet reader ( BioRad ) and the data was analyzed with the QuantaSoftTM analysis software ( BioRad ) . The six HIV replicates generated 80 , 000–98 , 000 droplets to be analyzed per time point . The presence of HIV-1 RNA in EDTA plasma was quantified with the Cobas TaqMan HIV-1 Test , v2 . 0 ( Roche ) according the manufacturer’s instruction . This assay has a lower limit of quantification of 20 copies HIV-1 RNA/mL but can provide a qualitative assessment of the presence of HIV-1 RNA below the 20 copy range . The presence of HIV-1 RNA in plasma was also qualitatively assessed using nucleic acid testing using a transcription-mediated amplification ( TMA ) based detection method as described by the manufacturer ( Procleix Ultrio Plus , Novartis ) with 50% sensitivity at 3 . 8 copies/mL and 95% sensitivity at 12 copies/mL [30] . TMA results were considered binary and defined as positive or negative according to assay outcomes . For HIV-1 DNA quantifications , CD4+ T cells were isolated using a CD4+ T Cell Isolation Kit Miltenyi biotec , cat no 130-096-533 ) on LS columns ( Miltenyi biotec , cat no 130-042-401 ) . After CD4+ T isolation , cells were resuspended in lysis buffer and digested as previously described [41] . Cell lysates were used directly for HIV-1 DNA quantifications using the QX100 Droplet Digital PCR system ( Bio-Rad ) to determine the absolute levels of total HIV-1 DNA per 106 CD4+ T cells . HIV-1 2-LTR circles where quantified as previously described [42] . CD4+ T cells were isolated from PBMCs from study participants by negative magnetic selection ( StemCell ) , and stimulated with phorbol myristate acetate ( PMA; 100ng/mL ) and ionomycin ( 1μg/mL ) for 12hrs . Dilutions of the stimulated cells ( ranging from 18 , 000 to 1 , 000 cells , 24 replicates per dilution ) were distributed in a 96 well plate and directly subjected to RT-PCR . Multiply spliced HIV RNA was quantified by semi-nested real time PCR with primers in tat and rev as previously described [43] with some minor modifications . The frequency of positive cells was calculated using the maximum likelihood method [44] and this number was then expressed as a frequency of cells with inducible multiply spliced HIV RNA per million CD4+ T-cells . Viral outgrowth assays were performed as previously described with the following modifications [25 , 45–47] . Resting CD4+ T cells were enriched from 150 million cryopreserved PBMCs by negative depletion via a 2-step protocol [45] . Briefly , the first step was to enrich CD4+ T cells from PBMCs using Miltenyi CD4+ T Cell Isolation Kit ( Cat #: 130-096-533 ) according to the manufacturer’s protocol . The second step was to further enrich for resting CD4+ T cells via depletion of cells expressing CD69 , CD25 or HLA-DR ( Miltenyi Cat #: CD69 Microbeads Kit II– 130-092-355; CD25 Microbeads II– 130-092-983; HLA-DR Microbeads– 130-046-101 ) . Resting CD4+ T cell purity , as determined by flow cytometry , was 98% [mean value with a 95% CI of 97 . 03 to 98 . 97%] . All cell incubations at 37°C unless otherwise noted . The culture medium for this assay was RPMI with L-glutamine; 1% streptomycin and penicillin; 10% fetal calf serum; recombinant human IL-2 ( 100 U/mL ) ( Gibco #PHC0027 ) ; conditioned media from a mix lymphocyte reaction culture as described in [46] . On day 0 resting CD4+ T cells were seeded at 20 , 000 cells/well in round-bottom 96-well plates and stimulated with irradiated allogeneic PBMCs from HIV-negative healthy donors and phytohemagglutinin ( 1μg/mL ) ( PHA; Remel #R30852801 ) . After 48 hours , the cells were extensively washed to remove PHA and 10 , 000 MOLT-4/CCR5+ cells were added to each well . On days 5 , 7 , and 9 , 75% of the culture media per well was replenished with fresh media with an additional 10 , 000 MOLT-4/CCR5+ cells added to each well with the fresh media on day 9 . On day 12 , the cell supernatant from each well was harvested and the number of wells containing replication competent HIV was assessed by incubation of the supernatant with TZM-bl cells via firefly luciferase reporter gene activity [48] . On day 15 , wells positive for luciferase activity was determined using the Britelite plus Reporter Gene Assay System , 100 mL ( Perkin Elmer #: 6066761 ) . Estimated frequencies of cells with replication-competent HIV before and after romidepsin treatment were calculated using limiting dilution analysis as described in [44] . Flow cytometry for histone acetylation levels was based on the method developed by Rigby et al . [49] . Immediately after isolation 1x106 PBMCs were re-suspended in 3 mL ice-cold PBS containing 1% FBS , centrifuged and re-suspended for fixation in 200μL 1% paraformaldehyde . The cells were fixed on ice for 15 min , washed in 4 mL ice-cold PBS , re-suspended in 200μL of PBS , and stored at 4°C . Within one week cells were washed with PBS containing 2% FBS and permeabilized with 200μL of 0 . 1% Triton X-100 in PBS for 10 min . at room temperature . After washing with PBS/2% FBS , the samples were blocked in 600μL of PBS/10% FBS for 20 min . Samples were stained with polyclonal rabbit anti-acetyl histone H3 ( 10μg/mL ) ( Merck Millipore #06–599 ) or normal rabbit serum ( control stain ) ( LifeTechnologies #10510 ) for 1 hour and then washed and incubated with donkey anti-rabbit IgG ( H+L ) Alexa Flour 488 ( 6μg/mL ) ( LifeTechnologies #A21206 ) for 1 hour at room temperature in the dark . Cells were washed , re-suspended in 150μL PBS and analyzed . ~50 , 000 events were acquired per sample . The median fluorescence intensity ( MFI ) for each patient at each time point was derived via subtraction of the background MFI ( isotype control stain ) for each sample from the anti-acetyl histone H3 stain . Frozen PBMC’s were thawed and 5x105 cells were immediately stained with Near-IR live-dead dye ( LifeTechnologies , Denmark ) , blocked and then stained with antibodies to CD4-PE-Cy7 ( SK3 ) , CD8+-PerCP-Cy5 . 5 ( SK1 ) , CD45RA ( HI100 ) , CCR7 ( G043H7 ) CD69-APC ( FN50 ) , HLA-DR-PE ( G46-6 ) and CD38-BV605 ( HB7 ) or PD-1 ( EH12 . 1 ) ( all Biolegend except PD-1 , CD38 , HLA-DR and CD8+; BD Bioscience ) . Only singlet , live cells were included in the data analyses . T cells were gated based upon size and granularity ( lymphocyte gate ) . Within the lymphocyte gate T cells were sub-gated based upon their expression of either CD4 or CD8+ . Memory subsets within CD4+ and CD8+ T cells were defined based on CCR7 and CD45RA expression . Activation status was determined based upon CD69 expression or HLA-DR/CD38 co-expression . Gates for activation markers and PD-1 were determined using isotope control antibodies . Cryo-preserved PBMCs were analyzed using intracellular cytokine staining ( ICS ) . PBMCs were thawed and rested for 18 hours at 37°C , 5%CO2 . Next , PBMCs were washed , counted and resuspended at a concentration of 3 . 3x106 cells/mL in total volume of 0 . 6 mL for each condition . PBMCs were stimulated for 6 hours at 37°C , 5%CO2 with HIV-1 Gag peptide pool ( 150 peptides mix , final conc . 2μg/mL per peptide , IPT , PepMix HIV ( GAG ) Ultra ) in the presence of secretion inhibitors ( Golgistop at 0 . 7μL/mL , and Golgiplug at 1μL/mL , BD ) and co-stimulatory molecules ( αCD28 , and αCD49d , at 1μg/mL each , BD ) . Un-stimulated and positive control samples ( staphylococcal enterotoxin b , SEB at 1μg/mL , Sigma-Aldrich ) were included for each time point . After the stimulation , cells were stained with Near-IR amino reactive dye for viability ( Invitrogen ) followed by surface staining ( including CD4+ ( OKT4 ) and CCR7 ( G043H7 ) from Biolegend and CD8+ ( RPA-T8 ) and CD45RA ( HI100 ) from BD ) and intracellular cytokine staining ( IFNγ ( B27 ) , IL-2 ( MQ1-17H12 ) , TNFα ( Mab11 ) from Biolegend ) using BD Cytofix/Cytoperm protocol . ~800 , 000 events were collected per sample . Gating strategy for analyzing CD8+ and CD4+ T cell responses in memory subsets are illustrated in S3 Fig . After defining gates for positive IFNγ , TNFα , and IL-2 expression , we utilized Boolean combination gate analyses to create the full array of possible combinations ( 7 response patterns for 3 functions ) . Fluorescence minus one ( FMO ) controls were performed for surface marker CCR7 and intracellular markers IFNγ , IL-2 , TNFα . Based on background cytokine response in un-stimulated control samples a positive HIV-1-specific response for CD8+ and CD4+ T cells was defined as values greater than 0 . 05% and 0 . 015% respectively ( after background response in the un-stimulated control was subtracted . For the analyses of MFI values ( S4 Fig ) only samples with a positive HIV response were included . All samples were analyzed on a BD FACSVerse cytometer and data was analyzed using FlowJo Version 10 . 0 . 7 . T-cell proliferation assays and ELISPOT ( to detect γ-interferon were carried using overlapping 15-mer peptides to HIV p24 synthesized at Schafer-N ( Copenhagen , Denmark ) and staphylococcal enterotoxin B as positive control ( Sigma-Aldrich AG , St . Louis MO , USA ) as antigens according to the methods described by Pollard et al . [28] . ELISPOT results were considered valid if the mean of triplicate wells did not exceed 50 spot forming units ( sfu ) /106 cells and the positive control was >500 sfu/106 cells . The study was designed to determine the safety profile of a reduced romidepsin dose regimen in HIV-1 patients on ART . Baseline characteristics were tabulated and adverse events graded according to CTCAE criteria . Changes from baseline to specific time points were tested using paired t-test or Wilcoxon signed-rank test . Delta values were assessed using the binomial test ( two-sided ) . The study was approved by the Danish Health and Medical Authorities as well as the Danish Data Protection Agency . Ethics committee approval was obtained in accordance with the principles of the Helsinki Declaration . Each patient provided written informed consent prior to any study procedures . The trial is registered at http://clinicaltrials . gov ( NTC02092116 ) | One proposed way of curing HIV is to activate virus transcription and kill latently infected cells while the presence of antiretroviral therapy prevents spreading the infection . Induction of global T cell activation by mitogenic or other potent activators effectively reverses HIV-1 from latency ex vivo , but such compounds are generally too toxic for clinical use . Therefore , investigating the capacity of small molecule latency reversing agents to induce production of virus without causing global T cell activation has been a top research priority for scientists in recent years . In the present clinical trial , we demonstrate that significant viral reactivation can be safely induced using the depsipeptide romidepsin ( HDAC inhibitor ) in long-term suppressed HIV-1 individuals on antiretroviral therapy . Following each romidepsin infusion , we observed clear increases in lymphocyte H3 acetylation , HIV-1 transcription , and plasma HIV-1 RNA . Importantly , this reversal of HIV-1 latency could be measured using standard clinical assays for detection of plasma HIV-1 RNA . Furthermore , romidepsin did not alter the proportion of HIV-specific T cells or inhibit T cell cytokine production which is critically important for future trials combining HDAC inhibitors with interventions ( e . g . therapeutic HIV-1 vaccination ) designed to enhance killing of latently infected cells . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] | [] | 2015 | The Depsipeptide Romidepsin Reverses HIV-1 Latency In Vivo |
It is acknowledged that some obesity trajectories are set early in life , and that rapid weight gain in infancy is a risk factor for later development of obesity . Identifying modifiable factors associated with early rapid weight gain is a prerequisite for curtailing the growing worldwide obesity epidemic . Recently , much attention has been given to findings indicating that gut microbiota may play a role in obesity development . We aim at identifying how the development of early gut microbiota is associated with expected infant growth . We developed a novel procedure that allows for the identification of longitudinal gut microbiota patterns ( corresponding to the gut ecosystem developing ) , which are associated with an outcome of interest , while appropriately controlling for the false discovery rate . Our method identified developmental pathways of Staphylococcus species and Escherichia coli that were associated with expected growth , and traditional methods indicated that the detection of Bacteroides species at day 30 was associated with growth . Our method should have wide future applicability for studying gut microbiota , and is particularly important for translational considerations , as it is critical to understand the timing of microbiome transitions prior to attempting to manipulate gut microbiota in early life .
Gut microbiota has a critical role in human health [1]–[6]; early infancy is of special interest because the early life period is a determinant for the subsequent adult-like microbiota . Once the first microbes arrive in the sterile gut of the newborn , a dynamic process starts , where activation of genes and expression of receptors in the host plays an important role for the building of niches and the further selection of microbes . More importantly , studies on germ free animals have revealed the presence of time-dependent exposure windows that rely on microbial stimuli from the gut [7] ( i . e . development of tolerance [8] , [9] , sensitivity to biogenic amines [10] , influences on cecum size [10] , and optimal functioning of diverse systems , such as angiogenesis [11] and stress responses [12] ) . Obesity has been linked to gut microbiota in humans , by being associated with reduced bacterial diversity and altered representation of bacterial genes and metabolic pathways [4] . Since rapid weight gain in early life is a risk factor for the later development of obesity [13] , we aimed to study whether early infant gut microbiota was associated with the World Health Organization's definition of expected growth in the first six months of life . As gut microbiota can be altered , or even transplanted [4] , there is large potential for future medical interventions . We describe a novel method that identifies patterns of gut microbiota exposures associated with potential time-dependent exposure windows in longitudinal data . We implement this method in the Norwegian Microflora Study ( NOMIC ) to reveal which patterns of gut microbiota ( representing the gut ecosystem developing ) are associated with expected infant growth , and compare the results to a standard linear regression model . We aim at identifying how the development of early gut microbiota affects infant growth . Proper knowledge of the time dependencies of gut microbiota as an exposure is a crucial underpinning before experimental attempts to manipulate early gut microbiota can be made . In light of this , our method will have considerable future applications , especially in the translational area of gut microbiota research .
The study was approved by the Regional Ethics Committee for Medical Research in Norway ( approval ref 2002 , S-02216 ) and the Norwegian Data Inspectorate ( ref 2002/1934-2 ) . The approvals , as well as informed consent from the mothers , were obtained prior to collection of data and samples . NOMIC is a birth cohort designed to study the establishment of gut microbiota during infancy and its consequences for child health . Participating mothers were recruited to the NOMIC study by a paediatrician at the maternity ward in a county hospital in South Norway . The recruitment protocol purposefully oversampled preterm children; whenever a preterm-birth mother was enrolled , two mothers of consecutively born term infants were recruited . The recruitment started in November 2002 and was completed in May 2005 . Eligibility criteria required that mothers were fluent in Norwegian and a resident in the pertinent geographic area . After the informed consent forms were signed by the mothers , containers for fecal samples and a questionnaire were provided to the participants at the maternity ward . The mothers were asked to collect and freeze one fecal sample from themselves at postpartum day 4 , as well as samples from their infants when they were 4 , 10 , 30 , and 120 days old . Study personnel retrieved the fecal samples and kept them frozen during transport to the Biobank of the Norwegian Institute of Public Health , Oslo , where they were stored at −20 C upon arrival . Further questionnaires were sent to the families when their infants were aged 6 , 12 , 18 , and 24 months . Six hundred and one mothers agreed to participate in the NOMIC study , however , 86 ( 14% ) of these mothers never returned any fecal samples , which left 524 infants with available fecal samples from one or more occasions . Children that were preterm ( 152 ) ( defined as gestational age less than 253 days ) , term children born via caesarean section ( 90 ) , or term vaginally born children who had been exposed to antibiotics before day 4 of life ( 36 ) , were then excluded from the current analysis , leaving 246 children . Mothers extracted information on weight from their “baby health visit” cards and reported this information in questionnaires . Information on gestational age and preterm delivery was obtained from the Medical Birth Registry of Norway . To be included in the analysis , we required birthweight and another weight measurement within 122 to 244 days of birth ( approximately 4 to 8 months ) . These two measurements are henceforth referred to as measurements at birth and approximately 6 months of life . If multiple measurements were available during the latter period , the closest to 6 months was used . Data from 218 children ( 110 females and 108 males ) met the inclusion criteria . A child is expected to follow the percentile given by its birth weight , which can be expressed as an age and sex standardised Z-score . Following recommendations from the Norwegian Health Directorate [14] , we used the World Health Organisation's weight-for-age growth curves [15] to describe expected growth . These sex-specific growth curves start with birthweight and provide the percentile distribution of infant weights for infants across ages . We generated sex standardised Z-scores for birth ( ) and for six months of age ( ) , and these Z-scores were compared . The Z-scores were calculated at the time of measurement . We chose approximately 6 months ( instead of 12 or 24 months ) as the outcome because we had the most complete dataset at this time , and reviews on rapid growth in early childhood failed to differentiate any particular time point from 6 to 24 months as clearly superior in predicting later obesity [13] , [16] . We defined the outcome of interest to be the difference in Z-scores: . This definition was chosen to be in concordance with the current literature , where the most frequent definition of rapid growth was a Z-score change in weight-for-age [13] . If a child's Z-score deviated between time periods , it was indicative of deviant growth and labelled as either increased growth ( reaching higher weights than expected from its birthweight ) or decreased growth ( undershooting the target weight and reaching lower weights than expected ) . If a child's growth followed the expected growth trajectory described by the WHO growth curves , they would have an outcome of 0 . As is often done in studies focusing on growth of infants , we used the change in Z-score threshold of 0 . 67 to define expected growth [13] . Thus infants with a Z-score of between and are regarded to be growing as expected . The distribution of the difference in the estimated Z-scores was found to be approximately Normally distributed , with a mean of , median of , and IQR of to for females , and a mean of , median of , and IQR of to for males . To aid in the interpretation of Z-scores , the relationship ( at different birth weights ) between change in Z-score and weight at six months is displayed in Figure 1 . Table 1 contains further descriptive characteristics of the study participants . The data in this study originated from a microarray dataset previously published [17] . The probes were constructed based on a limited 389 clone dataset [18] ( constructed from DNA extracted from the fecal samples obtained on days 4 , 10 , 30 , and 120 ) and subsequently evaluated on a 3845 clone dataset using Basic Local Alignment Search Tool ( BLAST ) [19] on a local database containing the dataset . Detailed information about this process can be found in a previous paper from the NOMIC study [17] . The exposures of interest are intensity readings for 22 probes , encoding different gut microbiota species ( spp . ) groups at 4 , 10 , 30 , and 120 days since birth . The probes , labelling sequence , and target bacteria spp . groups are displayed in Table 2 . The frequency of each probes detection , stratified by day and sex , are shown in the SI as Table S1 . Each intensity reading at every time point is dichotomised into either detected or non-detected . We selected this categorisation since we had no information on the distributions of the different probes' intensities in the average population , i . e . it was not possible to choose appropriate demarcations for low , moderate , or high levels . Each microbiota spp . group were examined individually . Information on potential confounders was obtained by questionnaires filled in by the mothers and from the Medical Birth Registry of Norway . Variables considered a priori to be potential confounders were antibiotics use ( after day 4 of life ) , sex , having received milk substitutes , maternal smoking , and parity , however , stepwise regression procedures led to the removal of all considered confounders due to a lack of effect . After microbial exposures corresponding to altered growth were identified , the distributions of birthweight , usage of the newborn intensive care unit , preeclampsia , physician-diagnosed poor fetal growth as reported by the mother , gestational age , and maternal BMI were investigated with respect to microbial exposures , to identify if the findings could have been influenced by these variables . Usage of the newborn intensive care unit , preeclampsia , and poor fetal growth were not initially investigated as potential confounders due to their low prevalence in this subset , which prevented us from obtaining reliable effect estimates when including them in any model . When considering the relationship between microbes and growth , our initial investigations found evidence for effect modification by sex . This led us to perform separate stratified analyses . We were interested in identifying time points at which the detection of specific gut microbiota spp . groups were significantly associated with growth trajectory . That is , we investigated whether we could identify any time points , where the detection of gut microbiota spp . groups , shifted the growth outcome , the mean change in Z-score . We modelled this relationship by including the detection of gut microbiota at each time point ( days 4 , 10 , 30 , and 120 ) separately , using a standard linear regression model ( separately for every gut microbiota spp . group ) . Thus the linear model constructed in our analysis is as follows:where is the change in Z-score for the infant ( ) , and denotes the detection of the gut microbiota spp . group ( ) at the time point ( ) . We tested for the significance of using the mixed directional false discovery rate ( mdFDR ) controlling method described in Guo et al . ( 2010 ) [20] . We first tested at significance level of 5% . We then repeated the analysis at 20% level of significance in order to identify biologically interesting results that were not statistically significant at the 5% level of significance . Briefly summarising the method , we defined as the p-value for the test: ( 1 ) for . We then treated as the intersection of all over , and as the union of all over . The following procedure was then undertaken: It is conceivable that , in an infant , it is not the effect of the gut microbiota at a singular time point , but rather the gut ecosystem developing over time , which influences growth . To capture this evolution , it is possible to describe an infant's exposure to gut microbiota as a pattern over time . For example , one infant's pattern could be a gut microbiota spp . that is detected at days 4 , 10 , and 30 , then non-detected at day 120 . Each combination of possible values of the gut microbiota ( detected or not detected ) at different time points ( 4 , 10 , 30 , 120 days ) was considered to be a pattern . All 16 possible patterns are displayed in Figure 2 . If a pattern was observed to occur less than 15% of the time , it was not included as a testable pattern . Below 15% frequency we did not have adequate power to warrant testing . Let denote the population mean for the growth outcome variable ( change in Z-scores , representing difference from expected growth ) of infants with pattern , ( where pattern has 4 time points: days 4 , 10 , 30 and 120 ) for the gut microbiota spp . , . Let denote the estimate of using the sample mean and let denote the standard error associated with the sample mean . Using and for each pattern and gut microbiota spp . group , we applied Tuke's method [21] to test for equivalence to zero: ( 2 ) where was chosen to be , as mentioned previously . Our analysis focused on attempting to identify a pattern which corresponded to expected growth ( ) instead of a comparison analysis ( e . g . pattern compared to pattern has an odds ratio of 2 for expected growth versus unexpected growth ) for two reasons . Firstly , we believed that the former concept was more clinically useful and interesting than the latter . Secondly , we were unable to easily select an appropriate reference pattern ( from those displayed in Figure 2 ) as multiple testing issues and concerns of model overfitting arose when considering multiple rounds of model fitting to identify the most appropriate reference patterns ( e . g . the pattern with the most extreme growth ) . In this analysis , we were concerned with identifying which gut microbiota spp . group patterns corresponded to a mean change in Z-score that was significantly close to zero ( i . e . did not deviate from expected growth ) . This is in contrast to the previous time-specific analysis , which was focused on the relative shift in change in Z-score , when the exposure was either present of absent . Similar to the previous analysis , we applied the mdFDR controlling method of Guo et al . ( 2010 ) at a rate of 0 . 05 [20] . Once we identified a significant pattern ( i . e . one where ) , we tested to see if some time points might be superfluous and not adding information; for example , it may be that only the first 30 days of exposure that affect growth , so the last time point ( day 120 ) would not be relevant and could be removed from the pattern . From the mixed directional false discovery rate controlling method [20] , each four time point pattern was tested at an adjusted significance level of ; if the p-value of pattern ( ) was less than then ( by using a Bonferroni adjustment ) we had the opportunity to perform an additional test to pattern without risk of losing the significant result for the four time point pattern . That is , consider the p-values of the patterns , without day 120 ( ) , without days 30 and 120 ( ) , and without days 10 , 30 , and 120 ( ) , to be denoted as , , , and , respectively . The following procedures were performed after finding a four time point pattern whose mean is significantly close to zero: The process ended when a pattern's mean was either not significantly close to zero , or when ( ) was not large enough to allow continued testing . This process controlled the false discovery rate , while simultaneously ensuring that no significant finding was subsequently lost by the additional testing to remove superfluous time points . A short proof , that this adaptation still retains control of the false discovery rate , is provided in the SI . By implementing this adaptation , the resultant hypotheses of interest were:The data reduction process was only considered from the right side of the pattern to avoid confounding . By definition , a confounder must affect both the exposure and outcome , and it is not possible for an exposure at day 120 to affect the exposure between days 4 and 30 . In contrast , an exposure at day 4 may influence the exposure at day 10 , and is therefore a possible confounder . We stress that , by only undertaking this process on the right side of the pattern , we do not imply that the right side of the pattern is less important . Instead , we view the process as adding information where possible ( by culling superfluous points on the right side of the pattern ) and leaving the pattern otherwise alone . If a pattern was found to have its mean significantly close to zero ( i . e . the null hypothesis in ( 2 ) is rejected ) , the mean of the pattern's crude contrast ( i . e . if detection at days 4 and 10 was significant , the crude contrast would be non-detection at days 4 and 10 ) was tested for difference to zero , using a t-test at . If the crude contrast was not found to be significantly different from zero , the pattern was discarded from the significant findings . In the event of a significant crude contrast , a Welch two sample t-test was performed to test if the means of the pattern and crude contrast differed from each other . This test was performed at a significance level of due to the decrease in sample size ( and hence power ) when only considering the set of infants with either the pattern of interest or the crude contrast . Tests found to be significant at were noted as such .
We applied the methods ( listed above ) to each gut microbiota spp . group in Table 2 and displayed significant time-specific results ( from standard linear regressions ) in Figure 3 and pattern results ( from our novel method ) in Figure 4 . In the time-specific analyses , with a false discovery rate of 5% applied , we found the detection of Bacteroides spp . ( Probe 22 ) at day 30 to be significantly associated with reducing growth in males , when compared to non-detection ( Figure 3 ) . The current literature shows that Bacteroides spp . is protective against obesity [22] . In the pattern analyses , we note that the detection of Staphylococcus spp . ( Probe 4 ) at day 4 was associated with expected growth in females and males ( Figure 4 ) . 98 males ( 96% ) and 94 females ( 91% ) had detectable levels of Staphylococcus spp . ( Probe 4 ) at day 4 . The literature highlights that colonisation of Staphylococcus spp . is a normal feature of healthy gut flora [23] . We also found that Escherichia coli ( Probe 13 ) detection from day 4 through to 30 was associated with expected growth in males ( Figure 4 ) , which occurred in 75 ( 77% ) of the males . The current literature indicates that colonisation of Escherichia coli is a normal feature of healthy gut flora development [24] . We are careful to refer to our exposures as “detected” and “not-detected” , and never as “present” and “absent” . This is because our detection limits for the different bacteria are likely very different , and therefore such references would be inappropriate , even though we are using detected/not-detected as a proxy for present/absent . Higher ( and varying ) detection limits results in misclassification of the exposure , and biases our results towards the null . This does not invalidate our findings , but did reduce our ability to identify additional significant findings . We were concerned that our pattern analysis findings were caused by confounding that occurred before four days of life . When comparing infants with detected Staphylococcus spp . ( Probe 4 ) at day 4 to those without , we found evidence that males with non-detected Staphylococcus spp . ( Probe 4 ) at day 4 had lower birthweight ( mean 3 . 19 Kg vs 3 . 58 Kg ) and higher proportion of usage of the newborn intensive care unit , ( 25% vs 6% ) , however , these findings were inverted in the female stratum ( 3 . 68 Kg vs 3 . 55 Kg and 0% vs 5% ) , and we therefore found no conclusive evidence of confounding . We also found no noticeable differences in the rates of preeclampsia , poor fetal growth , gestational age , or maternal BMI . No noticeable differences were found in any of the above variables when checking for confounding in Escherichia coli ( Probe 13 ) . While our outcome was focused on investigating growth in the first six months of life , the growth rate of a child is set in different phases during life , including in utero [16] . As we found no evidence of confounding by physician-diagnosed poor fetal growth , we were not concerned with issues pertaining to in utero growth . While we had data on growth at 6 , 12 , and 24 months , we ultimately chose approximately 6 months as the outcome as we had the most complete dataset at this time , and reviews on rapid growth in early childhood failed to differentiate any time point between 6 to 24 months as clearly superior [13] , [16] . Confounding by race and ethnicity was not considered due to the low proportion of non-ethnically Norwegian mothers in the study ( 11% in the subset used for the analysis ) . Duration of exclusive breastfeeding was evaluated with our surrogate variable , “use of milk substitutes . ” This was not found to be an important confounder , probably due to the long length of average breastfeeding in Norway ( greater than one year; only 33% of the subset used for the analysis had used one or more milk substitutes before day 30 ) . By investigating one overarching theme ( “how does the gut microbiota affect infant growth ? ” ) through two different questions , we obtained two different set of results . We note that these two set of results are not mutually exclusive , nor contrasting in nature . Instead they offer different perspectives: the time-specific analysis aids in highlighting where gut microbiota has an association with the mean of the outcome , which is useful in situations where the outcome is shifted away from 0 and it is hard to find a true “healthy reference group” . The pattern analysis is useful in identifying how the gut microbiota develops over time in babies with expected growth ( i . e . we found that Escherichia coli ( Probe 13 ) detection from day 4 through to 30 was associated with expected growth in males ) . This allowed us to combine a number of exposures over time , which , when viewed together , formed a cohesive message about the outcome . The message was that certain patterns corresponded to expected growth , and deviation from those patterns was associated with not achieving expected growth – instead of only identifying singular gut microbiota exposures that shifted growth . It is important to note that as no contrasts ( beyond the crude contrasts ) were compared to the “expected growth” pattern , we cannot make inferences about the association between expected growth and patterns that are partially different from the “expected growth” pattern . We can only assert that the presence of particular exposure patterns are associated with expected growth , and that they significantly differed from their crude contrasts ( which were also significantly different from expected growth ) . When considering the application of the pattern analysis method to other analyses , it is important to note that it cannot account for confounding . We propose that in situations where confounding variables are at work , the above method be used to extract a plausible reference pattern , and then a traditional logistic regression strategy should be implemented to address confounding . This process of reference pattern selection adds value to the current methodology literature , as it enables the transparent selection of a sensible reference pattern in scenarios ( such as the one above ) where it is not a simple matter to select a baseline a priori . In addition , other analyses may contain a multitude of time points , which would make the current strategy of creating longitudinal patterns unfeasible . In such situations , it would be advisable to “bin” similar time points to reduce the complexity of the dataset , and then apply our procedure in an attempt to identify binned time points that are interesting . Once such binned time points are identified , the method can be reapplied in the original data , restricted to the time points of interest . There are no issues with including more taxa , as the method is applied to each taxon independently . In addition , reference patterns are only considered when they have high frequencies and abnormal conditions are by definition less common . It is therefore necessary to “search” for a healthy common reference pattern and then test to see if deviating from the healthy reference ( i . e . the crude contrast ) results in illness . In certain situations , the outcome may be dependent on the interaction between two gut microbiota spp . groups , which would result in the above method not being appropriate without an extension . By creating patterns consisting of two – or more – gut microbiota spp . groups , and then applying the methods described here , the intra-gut microbiota spp . group dependencies can be accounted for . As with all methods , we are limited by the granularity of our longitudinal observations and the observational nature of our data . Our method identifies time-dependent points that may contain information about potential time-dependent exposure windows that are reflected in the observed data . That is , if one assumes there is a time-dependent exposure window requiring a microbe to be detected between 100–110 days , but the microbe does not simply dissipate from the body at day 111 , so a strong relationship exists between day 110 and 120 , then the method will identify a time-dependent point at day 120 ( reflecting the time-dependent exposure window at days 100–110 ) . This is simply a feature of the data , and the length of time surrounding each time-dependent exposure window when it is reflected in the data ( i . e . when the microbes remain similar ) may vary from microbe to microbe and be dependent on the situation at hand . The only way to prove that a time-dependent exposure window has occurred is through experiments . Using observational data , our method provides a novel way to describe potential time-dependent exposure windows that may have been reflected into the observable data . These descriptions can be further used to create time-dependent hypotheses for experiments concerned with the existence of time-dependent exposure windows . Furthermore , we highlight that our statistical methods were designed to control the false discovery rate , over a large number of tests . In doing so , it is likely that we discarded a number of clinically significant findings that were not found to be statistically significant . We therefore make no claims about the gut microbiota spp . groups that were not found to have any significant results , as the absence of evidence is not evidence of absence . Our outcome ( the difference in Z-scores of weight-for-age for approximately 6 months versus birth ) was not centred around 0 ( mean/median of and for females and males respectively ) , which raised concerns that our weight-for-age variable was perhaps inappropriate , and that a measure that also included length might be more appropriate . We investigated the larger Norwegian Human Milk Study cohort ( n = 3529 ) , of which NOMIC is a subsample [25] . We found that the median weight-for-age Z-score at birth was 0 . 76 , decreasing to 0 . 31 at approximately 6 months of life , while the median weight-for-length Z-score at birth was 0 . 63 , decreasing to 0 . 06 at approximately 6 months . This suggests that the Norwegian infants were born with more mass than one would expect for their appropriate length , and both weight-for-age and weight-for-length measures show similar trends . These findings from the larger Norwegian Human Milk Study cohort were similar to what we found in NOMIC . Similar results have been shown in the Norwegian Medical Birth Registry , where it has been found that from the early 1970s to the late 1990s the birthweight of Norwegian infants has been increasing [26] . These findings strengthen the recommendations from the Norwegian Health Directorate to use the World Health Organization's growth curves [14] . It is also worth noting that because the female distribution is centred so far from zero ( mean/median of ) , we lack power when detecting gut microbiota patterns that results in a positive change in Z-score . Furthermore , our “approximately 6 months” Z-score was calculated as the closest observed Z-score to 6 months , within 4–8 months . This implies an inherent assumption that the growth velocity of the child at the observed time point ( between 4–8 months ) is not different to that of the child at 6 months . This assumption may over or under-estimate the growth velocity , however , it will do so entirely at random ( with regards to the exposure ) and therefore will only bias the results towards the null , and does not invalidate our findings . Our results expand on the current literature relating gut microbiota to growth , in both methodology and biological findings . With regards to methodology , we developed a novel method to analyse longitudinal data that contains information about the development of an ecosystem over time . Crucially , this method controls the false discovery rate associated with multiple levels of multidimensional testing . We expanded the biological literature by reporting time-dependent patterns associated with expected growth , which , in some cases , confirmed the importance of gut microbiota spp . groups previously reported on . | Some obesity trajectories are set early in life , with rapid weight gain being a risk factor for later development of obesity . Recently , much attention has been given to findings indicating that gut microbiota may play a role in obesity development . The existence of time-dependent exposure windows , which rely on stimuli from the gut to initiate healthy development , gives the evolution of early life gut microbiota a critical role in human health . We identified children that followed their expected growth trajectories at six months of life , and those that had deviated . We then developed a novel statistical approach that allowed the identification of longitudinal gut microbiota patterns ( e . g . a particular species was detected at days 4 , 10 , and 30 and not detected at day 120 ) that were associated with expected growth , while appropriately restricting the false discovery rate . We further identified when a deviation from the proposed longitudinal gut microbiota patterns would result in an abnormal growth outcome ( either rapid or decreased growth at six months of life ) . We found developmental pathways of Staphylococcus species and Escherichia coli that were associated with expected growth , as well as indications that Bacteroides species at day 30 was associated with growth . | [
"Abstract",
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] | 2013 | Novel Developmental Analyses Identify Longitudinal Patterns of Early Gut Microbiota that Affect Infant Growth |
In the phytopathogenic basidiomycete Ustilago maydis , sexual and pathogenic development are tightly connected and controlled by the heterodimeric bE/bW transcription factor complex encoded by the b-mating type locus . The formation of the active bE/bW heterodimer leads to the formation of filaments , induces a G2 cell cycle arrest , and triggers pathogenicity . Here , we identify a set of 345 bE/bW responsive genes which show altered expression during these developmental changes; several of these genes are associated with cell cycle coordination , morphogenesis and pathogenicity . 90% of the genes that show altered expression upon bE/bW-activation require the zinc finger transcription factor Rbf1 , one of the few factors directly regulated by the bE/bW heterodimer . Rbf1 is a novel master regulator in a multilayered network of transcription factors that facilitates the complex regulatory traits of sexual and pathogenic development .
In a wide range of fungi , complex developmental traits such as cell identity , morphogenesis and sexual development are controlled by mating type loci [1] , [2] , [3] . In the smut fungi , a group of plant pathogens , these traits also include the ability to infect their host plants . In Ustilago maydis , a smut fungus that infects maize , it is the b-mating type locus that is critical for both sexual as well as for pathogenic development . Similar to other smuts , U . maydis exhibits a dimorphic life cycle . The haploid , cigar-shaped cells , called sporidia , multiply by yeast-like budding , and the dikaryon , which is formed upon the fusion of two compatible sporidia , grows as a filament . This switch in cell morphology is accompanied by an alteration of the life-style . While the sporidia are apathogenic and grow strictly saprophytic , the filament is biotrophic , i . e . it depends on the living tissue of its host plant maize for further development . Initially , the dikaryotic hypha consists of a long tip cell with the accumulated cytoplasm; the succeeding , older parts consist of “empty” cells that are separated by regularly spaced septae . Cell division is stalled until the hypha has penetrated the cuticula of a corn plant , and only then a “true” filament with multiple septated compartments is formed . Upon plant invasion , hyphae traverse the plant without harming the cells and without an apparent host defense response . After several days , the fungus induces plant tumors , coinciding with a massive proliferation of fungal hyphae [for review , see 4] . In order to fuse and to form the pathogenic filament , the two sporidia must carry different alleles both of the biallelic a- and of the multiallelic b-mating type locus . The a-locus encodes a pheromone/receptor system required for cell sensing , initiation of filamentous conjugation tubes , and cell fusion . After fusion , the crucial step for the initiation of the pathogenic phase is the formation of a heterodimeric complex of two homeodomain proteins , bE and bW , which are encoded by the b-mating type . This bE/bW complex is formed only when the two proteins are derived from different b-alleles , and is sufficient to initiate the switch from budding to filamentous growth . Concomitantly , activation of b leads to a cell cycle arrest that is only released after host plant infection . It has been shown conclusively that the bE/bW complex is sufficient to initiate the pathogenic development , as exemplified by haploid “solopathogenic” strains that harbor different alleles of bE and bW and that are capable to infect plants without a mating partner [5] . Thus , it is conceivable that genes regulated by the bE/bW heterodimer are involved in ( 1 ) the establishment of the biotrophic phase , ( 2 ) cell cycle regulation and ( 3 ) the dimorphic transition from budding to the polarized growth of the filament . However , until now , only four b-regulated genes have been identified with impact on these processes , three of which are required during the very early infection stages . biz1 encodes a zinc finger transcription factor that is involved in the G2 cell cycle arrest preceding plant penetration as well as in the induction of appressoria , specific infection structures at the tip of penetrating hyphae [6] . The mitogen-activated protein ( MAP ) kinase Kpp6 is required for the subsequent step: U . maydis strains harboring a non-activatable kpp6 allele still form appressoria , but are defective in the penetration of the plant cuticula [7] . After plant penetration , the clp1 gene is required for further proliferation of dikaryotic filaments in planta . clp1 mutant strains still penetrate the plant cuticula , but development is stalled prior the first mitotic division; in addition , mutant strains do not form clamps , a structure that ensures the proper distribution of nuclei in the dikaryotic hyphae [8] . Interestingly , the induced expression of clp1 strongly interferes with the b-dependent induction of several of the genes regulated by the bE/bW-heterodimer , indicating that Clp1 may modulate the activity of the bE/bW complex . And finally , the b-dependently expressed cyclin Pcl12 is involved in the polarized growth of the b-dependent filament , but is dispensable for pathogenic development [9] . The bE/bW heterodimer binds to a conserved sequence motif , the b-binding sequence ( bbs ) that has been identified in the b-dependently induced lga2-gene [10] . Out of the 20 b-dependent genes identified so far , only two additional genes were found to harbor the bbs-motif: the above mentioned clp1 gene , and frb52 , a gene with unknown function [11] . As the majority of b-controlled genes is obviously not directly regulated by bE/bW , it appears likely that the bE/bW heterodimer triggers a regulatory cascade with a limited number of direct targets genes . Thus , these “class I” genes should encompass regulators that trigger the regulation of the larger number of indirect , “class II” b targets . It was proposed that these regulators play pivotal roles either in all ( as master regulator ) or distinct ( as relay ) b-dependent processes . Here , we employed U . maydis strains that harbor inducible combinations of the bE and bW genes [11] and DNA array technology to investigate the b-dependent processes in a time-resolved manner . Our analysis provides insight in the complex interconnection of cell cycle regulation during the dimorphic switch and highlights the specific characteristics of the “pathogenic” hyphae . Most important , we identify the zinc-finger transcription factor Rbf1 as a novel master regulator that is required for all b-dependent processes .
In order to identify genes regulated by the bE/bW heterodimer , we performed microarray experiments with custom Affymetrix arrays ( MPIUstilagoA ) covering 5823 of the predicted 6786 U . maydis genes . Changes in gene expression were monitored during a 12-h time course ( with samples taken at 1h , 2h , 3h , 5h , 12h ) using the haploid U . maydis strains AB31 and AB33 that harbor the bE1 and bW2 genes under the control of the arabinose-inducible crg1 promoter and the nitrate-inducible nar1 promoter , respectively [11] . Induction of bE1/bW2 in these strains results in a filament that resembles the infectious hypha formed after fusion of compatible sporidia [11] . Strains AB32 and AB34 , which harbor the incompatible bE2 and bW2 combination , were used as controls . Expression of bE and bW genes was induced by a shift from glucose- to arabinose ( AB31 and AB32 ) or from glutamine- to nitrate containing media ( AB33 and AB34 ) . The expression profiles after b-induction in AB31 and AB33 were similar , but not identical . Firstly , the use of different media had an effect on gene expression , and , secondly , the use of the crg1 promoter resulted in gene expression values that were two- to fivefold higher when compared with nar1-driven gene expression ( Suppl . Fig . S1 ) . To account for expression changes caused by the medium shift , we considered changes only as relevant when the expression for a particular gene was altered significantly in both AB31 and AB33 in at least one time point ( change in expression ≥2 , adjusted p-value ≤0 . 01 ) . Using these criteria , 206 genes were induced and 139 were repressed in response to b-induction ( Fig . 1; Suppl . Table S1 ) . Within this list , all genes with a significant b-dependent regulation identified in previous studies were present , emphasizing the validity of the global approach and the quality of our data set ( Suppl . Table S2 ) . From the 345 b-regulated genes , a total of 239 were functionally classified using the Blast2Go tool [12] . Using enrichment analysis , we did not observe a significant over-representation of b-induced genes in any of the Gene Ontology ( GO ) categories ( http://www . geneontology . org ) . However , for the b-down-regulated genes , we observed a significant enrichment of the GO categories “Cell Cycle” ( GO:0007049; 29 genes ) , “Chromosome” ( GO:0005694; 25 genes ) and “DNA metabolic process” ( GO:0006259; 19 genes ) , “Cytoskeleton” ( GO0005856; 16 genes ) and “Microtuble cytoskeleton” ( GO:0015630; 9 genes ) ( Suppl . Table S3 ) . The induction of the active bE1/bW2-heterodimer leads to a G2 cell cycle arrest , and in accordance with this observation we found cln1 , clb1 and clb2 , which encode a G1-type cyclin and two B-type cyclins [13] , [14] among the down-regulated genes ( −29 . 9-fold , −7 . 7-fold and −2 . 6-fold , respectively; Suppl . Table S1 ) . cln1 and clb1 are involved in G1 to S transition , clb1 and clb2 in the G2 to M transition; thus , it is expected that these genes are poorly expressed in cells that are arrested in G2 . For clb1 it has been shown previously that the repression leads to a G2 cell cycle arrest [14]; thus , the observed low expression of this cyclin may trigger the b-induced G2 arrest . Additionally , we find um03928 , encoding a homologue of the S . pombe Cdr2 protein , as 40 . 7 fold down-regulated . In S . pombe , Cdr2 functions as a mitotic inducer via the Wee1 kinase and is required for G2/M transition [15] . In U . maydis , Wee1 has been shown to be a central regulator for G2/M transition [16]; however , a function for the Cdr2 homologue um03928 has not been assigned yet . Another level of complexity may be achieved via the up-regulation of the Cdk5 associated Pho80 Cyclin Like protein Pcl12 ( 49 . 1-fold , Suppl . Table S1 ) . Induced expression of pcl12 leads to a G2 cell cycle arrest , and promotes filamentous growth [C . Pothiratana and J . Kämper , unpublished; 9] . Thus , the b-induced cell cycle arrest may be realized via the synchronized regulation of independent pathways . In line with the cell cycle arrest , we observe the repression of genes involved in DNA-replication and nucleotide metabolism , as , for example , um01008 , encoding the catalytic subunit of DNA polymerase epsilon ( 3 . 6-fold down-regulated at 12h ) , or um06402 , encoding a DNA replication licensing factor ( 3 , 2-fold down-regulated at 12 h; Suppl . Table S1 , FunCat DNA ) . Several of the b-regulated genes can be attributed to the morphological switch from budding- to filamentous growth . A total of 20 genes with a potential function in cell wall synthesis or modification was found to be induced , starting 3 h after b-induction , which coincides with the onset of filamentation; five additional genes were repressed ( Suppl . Table S1 , FunCat: CW ) . These genes encode for chitin synthases as well as for exochitinases , chitin deacetylases , and exo- and endoglucanases , indicating that the cell wall composition is altered during the switch from sporidia to hyphae . The largest “functional” group ( 74 genes ) encodes for potentially secreted proteins . 34 of them have no ascribed function , and of these 15 are specific for U . maydis . Such secreted proteins are candidates for effectors that may play a role in the establishment of the biotrophic interaction ( Suppl . Table S1 , secreted ) . To identify b-dependent genes important for pathogenic development , we focused initially on genes whose expression was “strictly” dependent on the presence of the bE/bW heterodimer , i . e . genes that showed only basal expression levels in strains AB32 and AB34 and showed a more than 10-fold induction upon expression of an active bE1/bW2-heterodimer . None of the 53 genes that fulfilled these criteria showed a significant similarity to known pathogenicity factors . Potential exceptions were dik6 and dkh6 , which encode two related seven trans-membrane ( 7TM ) domain proteins . 7TM proteins represent an extended protein family in M . grisea that is discussed to function in plant/pathogen interactions [17] . However , neither the single , nor the double deletion of the two genes had an impact on pathogenic development ( Suppl . Table S1 , G . Weinzierl and J . Kämper , unpublished ) . In total , we deleted 30 of the 53 strictly b-dependent genes in the haploid , solopathogenic strain SG200; in addition , nine genes have been analyzed in the course of previous studies . 35 of the 39 deletion strains did not show altered virulence when assayed in plant infection assays . However , the individual deletion of each of the five genes encoding proteins with potential regulatory functions affected pathogenic development or filamentous growth ( Suppl . Table S1 ) . Among these genes was clp1 ( um02438 ) , which has been identified in the course of this study and has been shown to be required for pathogenic development and in planta proliferation [8] . The biz1 gene ( um02549 ) encodes a C2H2 zinc finger transcription factor that is required for pathogenic development and efficient appressoria formation [6] . In addition , we could show that the deletion of two genes encoding potential homeodomain transcription factors ( um12024 and um04928 , termed hdp1 and hdp2 ) impaired filamentous growth or led to loss of pathogenicity , respectively; the detailed characterization of these two genes will be published elsewhere . Here we will focus on the analysis of um03172 , encoding a potential C2H2 zinc finger transcription factor . Due to the initially observed phenotype ( see below ) , the U . maydis gene um03172 was termed rbf1 ( regulator of b-filament ) . According to our microarray analysis , rbf1 expression was strongly induced early after b-induction ( Fig . 2A ) . Significant expression was detected already 1h after b-induction in AB33 ( 13 . 6-fold induction ) , and expression peaked at 2h to 3 h ( 176 . 3-fold in AB33 at 2h and 297 . 4-fold in AB31 at 3 h , respectively; Fig . 2A ) . In the control strains AB32 and AB34 rbf1 expression was not detectable . The b-dependent expression of rbf1 was confirmed by qRT-PCR using strains AB31 and AB32 ( Fig . 2B ) . Within the rbf1 promoter , we identified three motifs with similarities to the previously identified b-binding sequences ( bbs ) ( Fig . 2C ) . We used an AB31 derivative expressing the bE1 protein fused to a triple HA-tag ( AB31bE1:3xHA ) for quantitative chromatin immunoprecipitation analysis ( qChIP ) . Induction of bE1:3xHA/bW2 genes in this strain led to filamentous growth ( see below ) , demonstrating that the bE1:3HA protein is functional ( data not shown ) . In a qChIP analysis with bE1:3xHA , a significant enrichment ( P = 5 . 7 10−5 , Students t-test ) was observed for the PCR amplicon covering the bbs-motif located at position −1377 , when compared to a amplicon covering a region further upstream in the rbf1 promoter ( Fig . 2D ) . The bbs−1377-motif shares also the highest sequence similarity with the previously described bbs-motifs ( Fig . 2C ) . When the rbf1 gene with a promoter fragment deleted for bbs−1377 was used for transformation of a strain deleted for rbf1 , the rbf1 deletion phenotype could not be complemented ( Fig . 3D , Table 1 , see below ) , demonstrating that bbs−1377 is required for expression of rbf1 . The early induction of rbf1 upon b-activation , the presence of a conserved bbs-motif which is bound by the bE/bW heterodimer in vivo , and the requirement of this bbs-motif for rbf1-function strongly suggest that rbf1 is a direct target of the bE/bW heterodimer . The cDNA-copy of rbf1 was obtained by RACE and revealed four introns when compared to the genomic locus . The predicted open reading frame encodes a protein of 404 amino acids ( aa ) with an N-terminal C2H2 zinc finger domain ( aa 18 to 131 ) , a putative nuclear localization sequence ( RHRR , aa 95 to 98 ) within the zinc finger domain and a C-terminal glutamine-rich sequence ( aa 365 to 373 ) ( Fig . 2E ) . To determine the localization of Rbf1 , the open reading frame was fused to a triple eGFP gene and integrated into strain AB31 via homologous recombination , thereby replacing the native rbf1 gene . Fluorescence microscopy of the resulting strain AB31rbf1:3eGFP ( UMS63 ) revealed a nuclear localization of the functional Rbf1-3xGFP fusion protein upon induction of the bE/bW heterodimer ( Fig . 2F ) , fostering the assumption that rbf1 encodes a C2H2 zinc finger transcription factor . To investigate the biological function of rbf1 , the gene was deleted in the haploid solopathogenic strain SG200 ( a1mfa2bE1bW2 ) and in the haploid U . maydis wild-type strains FB1 ( a1b1 ) and FB2 ( a2b2 ) , producing strains SG200Δrbf1 ( UMS20 ) , FB1Δrbf1 ( UMS49 ) and FB2Δrbf1 ( UMS51 ) , respectively . In all strains , the deletion of rbf1 did not cause any obvious phenotype in haploid sporidia growing in axenic culture , and the growth rate was not altered in different minimal or complete media ( data not shown ) . However , when the compatible strains FB1Δrbf1 and FB2Δrbf1 were crossed on charcoal containing plates , only very short filaments were observed at the edge of the forming colonies , while the cross of FB1 or FB2 resulted in fuzzy white colonies indicative for the formation of the filamentous dikaryon ( Fig . 3A ) . Similarly , only scarce filament formation was observed in SG200Δrbf1 ( Fig . 3B ) . Since SG200 cells undergo the dimorphic switch without the need of a mating partner on charcoal containing media , we can exclude that the drastically reduced filamentation is caused by a defect in cell-cell fusion . Treatment of FB1Δrbf1 cells with synthetic a2 pheromone resulted in the formation of conjugation tubes which were indistinguishable from those produced by wild-type FB1 cells , indicating that deletion of rbf1 does not affect polarized growth per se ( Fig . 3C ) . Transformation of SG200Δrbf1 with plasmid pRbf1 harboring the rbf1 gene and 3kb of 5′sequence restored the fuzzy colony appearance; three independent transformants ( SG200Δrbf1 ip::rbf1 ) were indistinguishable from the SG200 wild type strain ( Fig . 3 D ) . However , the rbf1 deletion phenotype was not complemented when plasmid pRbf1Δbbs−1377 , in which the bbs-motif at position −1377 in the rbf1 promoter was deleted , was used for transformation ( SG200Δrbf1 ip::rbf1Δbbs−1377 ) ( Fig . 3 D ) . To assess the role of rbf1 during pathogenic development , seven days old maize plants were inoculated with SG200Δrbf1 , or with a mixture of FB1Δrbf1 and FB2Δrbf1 , and scored for tumor formation . Seven days post inoculation ( dpi ) 95% and 94% of the plants inoculated with SG200 and a mixture of FB1 and FB2 , respectively , had developed tumors . In contrast , inoculation with the respective Δrbf1 mutants resulted in the complete absence of infection symptoms ( Table 1 ) . As expected , transformation of SG200Δrbf1 with pRbf1 ( SG200Δrbf1 ip::rbf1 ) restored pathogenicity , while transformation with pRbf1Δbbs−1377 ( SG200Δrbf1 ip::rbf1Δbbs−1377 ) did not ( Table 1 ) . To determine at which stage of pathogenic development the rbf1 mutant strains were blocked , fungal hyphae were stained with calcofluor at 2 dpi . Microscopic observation revealed that the Δrbf1-strains formed filaments on the leaf surface ( Fig . 3E ) , however , we did not observe any hyphae within plant cells . To assess whether SG200Δrbf1 was able to form appressoria , we co-inoculated plants with a mixture of SG200 and SG200Δrbf1 strains , each expressing either cytoplasmatically localized CFP or YFP to distinguish the strains . In the combinations SG200-CFP/SG200Δrbf1-YFP and SG200-YFP/SG200Δrbf1-CFP , we counted 57 and 60 appressoria for the SG200 strains on the leaf surface , respectively . By contrast , we were unable to detect any appressoria formation for the SG200Δrbf1 strains in the same surface areas . Thus , the observed pathogenicity defect of Δrbf1 strains results from the inability to form appressoria and to penetrate the plant cuticle . To get a more detailed view on the role of rbf1 during b-dependent filament formation , we deleted the gene in strain AB31 . More than 90% of the cells had switched to filamentous growth 12h after b-gene induction in AB31 , while in AB31Δrbf1 ( UMS25 ) no filament formation was observed ( Fig . 4A ) . Upon induction of bE1/bW2 in AB31 the cells stop to divide; in contrast , in AB31Δrbf1 cells continued to grow by budding ( Fig . 4A and 4C ) , indicating that rbf1 is required for both filamentous growth as well as for the b-dependent cell cycle arrest . FACS analysis of AB31 cells revealed an accumulation of cells containing a 2C DNA content upon b-induction , indicative for the b-induced G2-cell cycle arrest . In AB31Δrbf1 , however , the distribution of cells with 1C and 2C DNA content was comparable to the wild-type strain FB2 , corroborating the requirement of rbf1 for the b-induced cell cycle arrest ( Fig . 4B ) . To dissect b-dependent and rbf1-dependent processes , we constructed strain CP27 ( a2Δb::Pcrg1:rbf1 ) , an FB2 derivative in which the b-locus was replaced by a copy of rbf1 under control of the arabinose-inducible crg1 promoter . Induction of rbf1 in CP27 resulted in the formation of filamentous cells that were indistinguishable from b-induced filaments: the cells contained single nuclei ( Fig . 4A ) and stopped to divide ( Fig . 4C ) . FACS analysis revealed that rbf1 induction in CP27 leads to a G2 cell cycle arrest ( Fig . 4B ) analogous to that observed after b-induction . In summary , our results demonstrate that rbf1 is required for b-dependent filament formation and G2 cell cycle arrest and , in addition , sufficient to induce these developmental steps in the absence of an active bE/bW-heterodimer . To analyze the connection between b- and rbf1-mediated gene-regulation in more detail , we performed DNA-array analysis . b-dependent genes for which rbf1 is required for expression were identified by comparing the transcriptional profile of strains AB31Δrbf1 and AB31 at 3h , 5h and 12h after b-induction . Induced expression ( 5h ) of rbf1 in strain CP27 ( a2Δb::Pcrg1:rbf1 ) was used to identify genes for which rbf1 is sufficient for regulation . 189 ( 91 . 7% ) out of the 206 previously identified b-induced genes showed no significant changes in expression after b-induction in strain AB31Δrbf1 ( Fig . 5; Suppl . Table S4 ) . From the remaining 17 genes , 11 showed comparable expression levels after b-induction in AB31 and AB31Δrbf1 , and 6 genes showed significant , but reduced expression levels in AB31Δrbf1 . The 11 genes that showed no altered b-dependent expression upon rbf1 deletion did not respond to rbf1 induction in strain CP27; we consider these genes to be regulated only by b , and not by Rbf1 ( “only b” , Fig . 5 , Suppl . Table S4 ) . With the exception of um00027 , all these genes harbor sequence motifs with similarities to the b-binding site within their promoter sequences . In addition , they are all up-regulated early upon b-induction , indicating that these genes are most likely direct targets of the bE/bW heterodimer . The six genes that show a significant , but reduced b-responsive expression in AB31Δrbf1 all respond to rbf1 induction in CP27 . Four of the genes harbor b-binding sites in their promoter regions; apparently , these genes may be regulated directly via b and , in addition , independently via rbf1 ( “rbf1 OR b sufficient” , Fig . 5 , Suppl . Table S4 ) . For a large fraction ( 46% ) of the b-dependent genes rbf1 is both sufficient as well as required for expression; for these genes , deletion of rbf1 abolishes the b-dependent induction , and they respond to rbf1-induction in CP27 . It is likely that the regulation of these genes occurs by a b-mediated regulatory cascade via Rbf1 as a central regulator ( “rbf1 required AND sufficient” , Fig . 5 , Suppl . Table S4 ) . Expression of the remaining 102 genes was dependent on rbf1 , however , no significant induction was detected 5h after rbf1 induction in CP27 . Notably , 63 of these genes were late b-induced ( 12h after b-induction in AB31 ) , and additional 22 genes were only weakly induced ( less than 3-fold ) , or only transiently induced 5h after b-induction in AB31 . It is well possible that these genes respond to rbf1 only after prolonged rbf1 induction ( >5h ) . For 16 genes , we observed a significant b-dependent induction , no induction in AB31Δrbf1 , and no rbf1-dependent induction in CP27 . Thus , we have to assume that for the regulation of these genes the action of both b and rbf1 is required ( “rbf1 AND b required” , Fig . 5 , Suppl . Table S4 ) . An analogous scenario was found for the b-dependently repressed genes: of the 139 b-dependently repressed genes , the repression was abrogated for 129 ( 92 . 8% ) genes in AB31Δrbf1 . For a total of 69 genes rbf1 was both required and sufficient for repression . Formally , the b-repressed genes can be grouped equivalent to the b-induced genes ( b only; rbf1 AND b; rbf1 OR b; only rbf1; Fig . 5 , Suppl . Table S4 ) . To assess whether the rbf1-dependent gene expression involves the binding of Rbf1 , we dissected the promoter of dik6 , one of the rbf1 responsive genes , by means of qChIP analysis . We used an AB31 derivative where the rbf1 gene was replaced by a rbf1-3xHA fusion ( AB31rbf1:3xHA ) . Induction of bE1/bW2 in this strain triggers the expression of the Rbf1-3xHA fusion protein , which results in filamentous growth , demonstrating that the Rbf1-3xHA fusion protein is functional ( Data not shown ) . qChIP analysis was performed via a set of 9 overlapping amplicons spanning 930 bp of the dik6 promoter ( Fig . 6A ) ; as controls , we used an amplicon upstream of the potential promoter ( −1703 to −1829 with respect to the ATG ) and an amplicon within the dik6 ORF ( Fig . 6A ) . With the exception of an amplicon spanning the region from −9 to −157 , all amplicons within the promoter showed significant ( P<0 . 001 ) differences in enrichment when compared to the control amplicon located within the ORF . The amplicons with the highest enrichment were found to span the region from −825 to −422 ( Fig . 6B ) The functional analysis of the dik6 promoter by means of promoter-GFP fusions revealed that Rbf1-induced GFP expression levels declined when the dik6 promoter was truncated from 816 to 638 bp , while a 298 bp fragment was not sufficient to mediate expression ( Fig . 6A , C ) . Internal promoter deletions corresponding to the amplicons used for the qChip analysis revealed that deletion of the dik6 promoter region from −825 to −680 ( corresponding to amplicon 3 ) led to reduced Rbf1-dependent induction , while the deletion of the promoter region from −601 to −500 ( corresponding to amplicon 5 ) abolished expression completely ( Fig . 6A , C ) . In summary , our data indicate that the dik6 promoter has at least one binding site for Rbf1 that is required for Rbf1-mediated dik6-expression . Previously , it was shown that rbf1 is induced when haploid cells are treated with compatible pheromone [18] . Since both bE as well as bW are also induced upon pheromone treatment [19] , we asked whether Rbf1 might be required for pheromone-dependent expression of the b genes . However , real time qRT-PCR analysis revealed no difference in the abundance of bE and bW transcripts in the strains FB1 and FB1Δrbf1 ( UMS49; a1b1Δrbf1 ) upon treatment ( 75 min ) with synthetic a2 pheromone ( see Suppl . Fig . S2 ) . Thus , we can exclude the possibility that Rbf1 is required for the pheromone-dependent b-induction . In summary , our data identify Rbf1 as the central regulatory switch within the b-dependent regulatory cascade , which is not only required for the regulation of the majority of the b-dependent genes , but also indispensable for all b-mediated developmental processes .
The switch from saprophytic to biotrophic growth of U . maydis requires a meticulous coordination of different processes , such as cell cycle control , the change to polarized growth , and , most interestingly , the onset of a program facilitating plant invasion and colonization . The top-most control instance for these processes is the b-mating type locus; it has been conclusively shown that compatible b-alleles are both required and sufficient for pathogenic development [5] . The bE/bW-heterodimer also controls polarized cell growth and induces a G2 cell cycle arrest , but not exclusively , since both can be triggered as well via the pheromone/receptor system encoded by the a-mating type locus [20] . Necessarily , the a and b loci are cross-controlled: activation of the a-pathway leads to induction of the bE and bW genes via Prf1 , and the formation of an active bE/bW-heterodimer after cell fusion leads to a down-regulation of the a-pathway [19] , [21] . Since a direct binding of the bE/bW heterodimer to promoters of the plethora of genes associated with b-dependent processes appeared unlikely , we have favored a model that places b on top of regulatory proteins ( relays ) mediating the regulation of further downstream targets . We have now identified the C2H2 zinc finger transcription factor Rbf1 as a central key player within this regulatory network . The fast induction of rbf1 upon b-activation , the binding of the bE/bW-heterodimer to a defined b-binding site in the rbf1-promoter region as well as the requirement of this binding site for rbf1 function define rbf1 as a direct target of the bE/bW-heterodimer . Deletion of rbf1 abolishes all b-mediated processes , and induction of rbf1 leads to filamentation and a G2 cell cycle arrest analogous to that observed upon b-induction . In addition , we could show that rbf1 is required for regulation of the far majority of b-regulated genes , and , for a large fraction , also sufficient . Thus , we consider Rbf1 as a key master regulator whose action is sufficient to induce an entire complex developmental pathway . Despite of the essential function of Rbf1 within the b-regulatory cascade , we consider it unlikely that rbf1 alone is sufficient to trigger pathogenic development of U . maydis , because clp1 , which was shown to be required for pathogenicity [8] , is induced directly by b and independently from rbf1 . We were not able to address this question experimentally , since transformants with a constitutively expressed rbf1 gene were not viable , most probably as a result of the rbf1 induced cell cycle arrest . In fungi , only few master regulators of pathogenic development have been identified yet . In Candida albicans , WOR1 is the master regulator of white to opaque switching [22] , and the C . neoformans Gat201 [23] is a key regulator of melanin production and capsule formation . The C . neoformans Cir1 transcriptional regulator integrates the sensing of iron with the expression of virulence factors , with signalling pathways influencing virulence , and with growth at elevated temperature [24] , [25] . WOR1 and Gat201 are required ( and sufficient ) for the initiation of specific programs that are tightly linked to fungal pathogenesis . In contrast , nearly all of the genes regulated by b require rbf1 for their expression , and it is not possible to assign specific , common functions to the rbf1-regulated genes , or to the few genes that are not regulated by Rbf1 . Thus , different from WOR1 and Gat201 , Rbf1 regulates not the genes of a specific , defined pathway , but is required for the regulation of all b-dependent processes . Similarly , the C . neoformans Cir1 regulator is involved in the regulation of all major virulence traits [24] , [25] . The cell cycle block of the b-induced filaments is only released upon plant penetration . Our data reveal a complex contribution of different key players to control the cell cycle . At least four different transcription factors , namely bE/bW , Rbf1 , and the two Rbf1-dependent factors Biz1 and Hdp1 are involved in cell cycle regulation . The ectopic expression of any of these factors leads to the formation of G2 arrested hyphae [6] , [8 , C . Pothiratana and J . Kämper , unpublished] , which argues for a complex transcriptional network with different levels of relays that allow the integration of various stimuli , as for example , the unknown signal that leads to the release of the cell cycle after penetration of the host plant . The regulatory control achieved via b , Rbf1 , Biz1 and Hdp1 may funnel into the transcriptional regulation of different key factors for cell cycle control , as we observe the transcriptional regulation of different cyclins ( cln1 , clb1 , clb2 and pcl12 ) and of the potential Wee1 kinase Um03928 . The Um03928 homologue in S . pombe , Cdr2 , is required for the proper formation of septae , and functions as mitotic inducer via the negative regulation of the central cell cycle regulator Wee1 [15] , [26]; the U . maydis Wee1 was shown to trigger filamentous growth and a G2 arrest [9] , [16] . Obviously , the b-induced G2 cell cycle arrest is controlled by several independent regulatory pathways . The induction of b leads to the formation of polar growing hyphae , and several of the b-dependently regulated genes reflect this morphological change and the altered requirements of the cell for e . g . long distance transport or cell wall remodeling . However , the most interesting trait by which the b-induced filament differs from other filaments like the pheromone-induced conjugation tube is its ability to infect the host . The exploitation of the b-dependently regulated genes provides for the first time comprehensive insights into the complex developmental processes during morphogenic switching and pathogenic development of U . maydis . The pathogenic potential of the hyphae may for once be marked by an altered cell wall composition , as we observe the differential regulation of several genes involved in cell wall synthesis , including chitin synthases and chitin deacetylases . Rebuilding or masking of the cell wall is a strategy of pathogens to evade perception or to protect themselves from defense responses of the host [27] . However , deletion of either of the two b-regulated chitin deacetyases does not affect virulence in U . maydis ( B . Günther , J . Kämper , B . Moerschbacher , unpublished ) , and neither are the two chitin synthases chs1 and chs4 required for pathogenicity [28] , most likely due to overlapping and/or redundant functions . The other intriguing characteristic of the b-filament is the secretion of various potential effector proteins . Such effectors are thought to be involved in suppression of host defense responses and redirection of nutrient flow during biotrophic growth . The expression of putative effectors prior to the contact with the plant indicates a priming mechanism of the fungal hypha to facilitate rapid suppression of plant defense responses and the fast establishment of the biotrophic interface subsequent to plant penetration . The observation that the temperature-induced inactivation of the bE1/bW2-heterodimer in planta abolishes expression of various additional candidate effector genes [29] that are not identified as b-regulated in this study , implies that the temporal expression of these genes is subject to combinatorial gene regulation involving the bE/bW-heterodimer and other plant-induced factors . The competence of the b-filaments to penetrate the plant cuticula is reflected by the induction of Biz1 and the MAP kinase Kpp6 . Both factors have been shown to be required for efficient formation of appressoria and subsequent penetration . Rbf1 is required for the b-dependent induction of both genes , which explains the absence of appressoria in rbf1 mutant strains . Rbf1 is required for the induction of most , but not all b-regulated genes . All genes that are exclusively regulated by bE/bW harbor b-binding sites within their promoters , and it is conceivable that these genes are regulated via direct binding of the bE/bW-heterodimer . The majority of the b-regulated genes , however , lack putative b-binding sites , indicating that the b-dependent regulatory circuit involves additional transcription factors . Similarly , those genes for which rbf1 is required and sufficient for regulation may be directly regulated by Rbf1 . Our data indicate that Rbf1 binding to the promoter of the dik6 gene is required for Rbf1-mediated dik6 expression , which emphasizes the function of Rbf1 as a transcription factor . However , the actual Rbf1 binding site has not been determined yet . The in silico analysis of rbf1-regulated genes may be constrained by the fact that Rbf1 triggers the induction of at least three transcription factors , leading to a superimposition of direct and indirect effects . For a small fraction of genes , both b and rbf1 are required for regulation , which can be explained by a combinatorial action of two transcription factors [30] . A substantial number of genes is down-regulated upon b-induction . Intriguingly , two of the very few known transcription factors that can act both as transcriptional activators and repressors , the S . cerevisiae Rme1 protein and the human YY1 protein , are both C2H2 zinc-finger proteins [31] , [32] . Thus , it is well possible that the repression of genes is also directly mediated via Rbf1 . The dimorphic switch and the onset of pathogenic development trigger a multilayered regulatory cascade that involves several transcription factors ( Fig . 7 ) . Is there a specific reason that the bE/bW-heterodimer regulates only a small number of genes directly and more than 90% in dependence on a second master regulator ? For once , additional regulators allow more signals to be integrated into the regulatory circuits , which may help to quickly adapt to changing environmental conditions during biotrophic development , thereby avoiding nutrient stress or plant defense responses . In particular , Rbf1 interconnects the a- and b-dependent regulatory pathways , as both pheromone-response [18] as well as b-induction leads to rbf1 expression . Since we could not determine a specific function for Rbf1 in the pheromone-dependent signalling pathway and deletion of rbf1 is not required for conjugation tube formation and for pheromone-induced G2 cell cycle arrest , we consider it unlikely that rbf1 plays a central role in a-dependent signalling or gene regulation . One possibility is that the pheromone-induced expression of b and rbf1 primes the cells for post-fusion events . The a- and b-dependently induced cell cycle arrest is independently coordinated; thus , the pheromone-induced rbf1 expression facilitates rapid switching of developmental programs thereby minimizing the time preceding plant infection ( Fig . 7 ) . In essence , our study provides fundamental new insights into the complex regulatory traits of sexual , as well as pathogenic development of U . maydis . The identification of key factors points towards an emerging picture that explains how multilayered regulatory pathways can dynamically interact to control complex developmental decisions . We believe that this work is not only relevant for U . maydis but can also serve as a model for other fungi and higher organisms .
Escherichia coli strain TOP10 ( Invitrogen ) was used for cloning purposes . Growth conditions and media for E . coli [33] and U . maydis [8] , [34] , [35] and the quantification of appressoria formation [6] have been described previously . U . maydis strains with relevance for this study are listed in Suppl . Table S5 . U . maydis strains carrying crg1 expression constructs were induced in array medium [8] or CM medium [34] supplemented with 1% arabinose instead of 1% glucose as described in [8]; equivalently , for nar1-induction , array medium supplemented with 3 . 8g/l KNO3 instead of glutamine ( 4 . 38 g/l ) as nitrogen source was used . Mating assays and plant infections are described in reference [35] . For pheromone stimulation of U . maydis cells we followed the protocol of [36] . Molecular methods followed described protocols [33] . DNA isolation and transformation procedures for U . maydis were carried out as described [37] . For all gene deletions , we used the PCR based approach described in [38] . For the Rbf1-3xeGFP fusion , 1 kb of the 3′end of the rbf1 ORF and 1 kb of the 3′ UTR were PCR-amplified , introducing two SfiI sites and removing the stop-codon of rbf1; both fragments were ligated to an SfiI 3xeGFP-HygR fragment of pUMA647 ( K . Zarnack and M . Feldbrügge , unpublished ) in pCR2 . 1 TOPO ( Invitrogen ) as backbone , yielding pMS85 . To replace the b-mating type locus with the arabinose inducible rbf1 allele , the rbf1-ORF was PCR amplified , creating an NdeI site at the start and a NotI site following the stop codon , and cloned into pCR2 . 1 TOPO . The NdeI-NotI rbf1-ORF-fragment , a 1 . 3 kb BstXI ( blunt ) -NdeI crg1-promotor fragment and a 0 . 3 kb NotI-EcoRI ( blunt ) nos-terminator fragment from pRU12 [11] were integrated into the StuI site of pCRΔb [38] to generate pCRΔb-crg:rbf1 . For the generation of HA-tagged bE1- and Rbf1-fusion proteins 1 kb of the 3′end of the ORF and 1 kb of the 3′ UTR were PCR-amplified , introducing two SfiI sites and removing the stop-codon; respective fragments were ligated to an SfiI 3xHA-HygR fragment of pUMA792 ( M . Feldbrügge , unpublished ) and cloned into pCRII TOPO , yielding plasmids pDS1 and pDS3 . After linearization plasmids were integrated into the bE1 and rbf1 loci , respectively , of strain AB31 by homologous recombination . All PCR amplified fragments were verified by sequencing . For transformation , either linearized plasmid DNA or PCR generated linear DNA was used; homologous integration was verified by Southern blot . For complementation of the rbf1 deletion , a 3kb region upstream of the rbf1 ORF was PCR amplified introducing a 5′-FseI and a 3′-NdeI restriction site and inserted with the NdeI-NotI rbf1-ORF fragment of pCRΔb-crg:rbf1 into pRU11-NotI6474 ( a pRU11 [11] derivative in which the NotI site at position 6474 has been removed by a fill up reaction ) by three-fragment ligation to generate pRbf1 . Generation of pRbf1Δbbs−1377 was performed as described for pRbf1 , with the exception that the bbs-motif at position −1377 within the 3kb rbf1- upstream region was removed by standard PCR techniques [39] . For generation of dik6 promoter-GFP fusion constructs the 2448 bp dik6 promoter fragment was PCR-amplified and integrated into pRU4 [11] digested with HpaI and NdeI . From the resulting plasmid dik6 promoter fragments of 816 bp , 638 bp and 298 bp were recovered as BclI ( blunt ) /NdeI , MscI ( blunt ) /NdeI and HindIII ( blunt ) /NdeI fragments and integrated into pRU4 [11] digested with HpaI and NdeI . Internal deletions in the dik6 promoter were introduced by standard PCR techniques [39] . PCR amplified fragments were integrated into pRU11 via FseI/NdeI restriction sites [11] . RNA extraction and qRT-PCR analysis for rbf1 , bW , bE and ppi was performed as described [8] . Full-length rbf1 cDNA was isolated using the GeneRacer Kit ( Invitrogen ) , cloned in pCR2 . 1 TOPO ( Invitrogen ) and sequenced . For overview of primers used see Suppl . Table S6 . 50 ml cultures of U . maydis were grown until OD600 = 0 , 6–1 , 0 and cross-linked by addition of formaldehyde ( 1% final concentration ) for 15 min at RT; glycine was added to a final concentration of 0 . 125 M , cells were harvested by centrifugation and washed three times in TBS ( 50 mM Tris-HCl , 150 mM NaCl , pH 7 . 6 ) . The pellet was resupended in 1 . 5 ml FA lysis buffer ( 50 mM HEPES-KOH [pH 7 . 5] , 150 mM NaCl , 1 mM EDTA , 1% [v/v] Triton-X-100 , 0 . 1% [w/v] sodium deoxycholate , 0 . 1% [w/v] sodium dodecyl sulfate [SDS] ) supplemented with 2 mM PMSF , 5 mM benzamidine and 1× Complete EDTA-free ( Roche ) . Cells were lysed with a cell mill ( Retsch MM200 , 25Hz , 5min ) in liquid nitrogen pre-cooled grinding jars and the powdery cell extract thawed on ice . 1 ml aliquots of the resulting suspension were sonicated on ice; sonication was set to yield a DNA average size of 400–500 bp . After centrifugation ( 17000g , 15 min , 4°C ) the supernatant was used as the input sample in immunoprecipitation experiments . For each experiment , 400 µl aliquots of the input sample were incubated with 25 µl monoclonal anti-HA-agarose beads ( Sigma-Aldrich ) over night at 4°C on a rotating wheel . Washing of beads and recovery of the immunoprecipitated DNA was done according to the ChIP protocol from the Haber Lab ( http://www . bio . brandeis . edu/haberlab/jehsite/protocol . html ) with the following modifications . All washing steps were carried out at 4°C and repeated one more time , with exception of the TE wash . Proteinase K treatment was done with 50 µl TE containing 3 . 5 mg/ml Proteinase K without glycogen , and phenol/chlorophorm extraction was done without LiCl . Samples were analysed by qPCR on a Bio-Rad iCycler using the Mesa Green qPCR MasterMix Plus ( Eurogentec ) with 400 nM Primer ( each ) and 1 µl immunoprecipitated DNA or 1/100 diluted input DNA , respectively . Amplicons were normalized to input DNA using the Bio-Rad IQ5 software . Custom-designed Affymetrix chips were used for DNA-array analysis . Probe sets for the individual genes are visualized at http://mips . helmholtz-muenchen . de/genre/proj/ustilago/Target preparation , hybridization and data analysis was performed essentially as described before [40] , with the following alterations: 5 µg RNA were used for first strand cDNA synthesis at 50°C with Superscript II ( Invitrogen ) ; for all experiments , an adjusted P-value for the false discovery rate [41] of ≤0 . 01 and a change in expression of ≥2 was used for filtering . For analysis of b-dependent gene expression strain AB31 ( a2 Pcrg1:bE1/bW2 ) was compared to strain AB32 ( a2 Pcrg1:bE2/bW2 ) and strain AB33 ( a2 Pnar1:bE1/bW2 ) was compared to strain AB34 ( a2 Pnar1:bE2/bW2 ) at the given time points . For analysis of rbf1-dependent gene expression strain AB31 ( a2 Pcrg1:bE1/bW2 ) was compared to AB31Δrbf1 ( a2 Pcrg1:bE1/bW2 Δrbf1 ) and strain CP27 ( a2 Δb::Pcrg1:rbf1 ) was compared to strain JB2 ( a2 Δb ) at the given time points . Expression values were calculated as mean of two biological replicates . All array data have been submitted to GEO/NCBI ( GSE18750 , GSE18754 and GSE18756 ) . De novo promoter motif search was performed using the TAMO framework [42] extended to include AlignAce , Bioprospector , Cismodul , Improbizer , Meme , MDScan and Weeder . Output of each algorithm was collected , converted into a position weight matrix and scored with a hypergeometric test reflecting a random selection null hypothesis [43] . Flow cytometry measurements were performed as described before [20] . Cell counting was performed with a Neubauer counting chamber . Microscopic analysis was performed using an Axioimager equipped with an Axiocam MRm camera or a Lumar V12 equipped with an Axiocam HRc ( Zeiss , Jena , Germany ) . Nuclei were stained with DAPI Vectashield H-1200 ( Vector Laboratories ) , fungal cell walls with 2 µg/ml Calcofluor white ( Sigma , St . Louis , MO ) in PBS . All images were processed with Axiovision ( Zeiss , Jena , Germany ) . clp1 ( um02438 ) XP_758585 , rbf1 ( um03172 ) XP_759319 , hdp1 ( um12024 ) XP_761909 . 1 , hdp2 ( um04928 ) XP_761075 , biz1 ( um02549 ) XP_758696 , cln1 ( um04791 ) XP_760938 , clb1 ( um03758 ) XP_759905 , clb2 ( um10279 ) XP_758735 , cdr2-like protein ( um03928 ) XP_760075 , pcl12 ( um10529 . 2 ) XP_760585 , DNA polymerase epsilon ( um01008 ) XP_757155 , DNA replication licensing factor ( um06402 ) XP_762549 . | The basidiomycetous fungus Ustilago maydis is the causal agent of the smut disease on corn . The fungus exhibits two different life-styles , a saprophytic and a pathogenic stage , where it grows yeast-like by budding , or as filamentous , dikaryotic hyphae , respectively . The switch between these two stages is controlled by a heterodimeric transcription factor , bE/bW , which is encoded by the b-mating type locus . We have now identified the genes that are regulated in response to the activation of bE/bW , following the b-mediated developmental change , and address their contribution to the altered morphology and pathogenic development . Interestingly , most of the b-responsive genes are not regulated directly by the bE/bW proteins , but require the action of a second transcription factor , Rbf1 , which is induced by bE/bW . Rbf1 defines a novel master regulator as a central component in a multilayered network of different , hierarchically ordered transcription factors that facilitate the complex regulatory traits to coordinate morphology as well as sexual and pathogenic development . | [
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"microb... | 2010 | The Transcription Factor Rbf1 Is the Master Regulator for b-Mating Type Controlled Pathogenic Development in Ustilago maydis |
Understanding the factors that affect the host-feeding preferences of triatomine bugs is crucial for estimating transmission risks and predicting the effects of control tactics targeting domestic animals . We tested whether Triatoma infestans bugs prefer to feed on dogs vs . chickens and on dogs vs . cats and whether vector density modified host choices and other vital rates under natural conditions . Two host choice experiments were conducted in small caged huts with two rooms between which bugs could move freely . Matched pairs of dog–chicken ( six ) and dog–cat ( three ) were assigned randomly to two levels of vector abundance and exposed to starved bugs during three nights . Bloodmeals from 1 , 160 bugs were tested by a direct enzyme-linked immunosorbent assay . Conditional logistic regression showed that dogs were highly preferred over chickens or cats and that vector density modified host-feeding choices . The relative risk of a bug being blood-engorged increased significantly when it fed only on dog rather than chicken or cat . Bugs achieved higher post-exposure weight at higher vector densities and successive occasions , more so if they fed on a dog rather than on a cat . Our findings strongly refute the hypothesis that T . infestans prefers to blood-feed on chickens rather than dogs . An increase in dog or cat availability or accessibility will increase the rate of bug feeding on them and exert strong non-linear effects on R0 . When combined with between-dog heterogeneities in exposure , infection , and infectiousness , the strong bug preference for dogs can be exploited to target dogs in general , and even the specific individuals that account for most of the risk , with topical lotions or insecticide-impregnated collars to turn them into baited lethal traps or use them as transmission or infestation sentinels based on their immune response to Trypanosoma cruzi or bug salivary antigens .
Host choice of hematophagous insects mainly depends on relative host abundance and proximity , host defensive behavior , the density of blood-sucking insects , and the spatial and temporal concurrence of hosts and insects [1] , [2] . Examples of innate ( genetically determined ) host-feeding preferences are few , and convincing evidence with both experimental and field support is scarce [1] , [3] . Fleas ( Xenopsylla conformis ) do not have an innate preference but can discriminate between juvenile and adult hosts , and derive a higher reproductive reward when feeding on juvenile hosts [4] . In Lutzomyia longipalpis sandflies , host size was the main determinant of host-feeding choices among a human , a dog and a chicken exposed simultaneously to laboratory-reared sandflies [5] , and its feeding success on chickens was density-dependent [6] . For Triatoma infestans bugs [7] and Simulium damnosum blackflies [8] , the proportion of insects biting humans was strongly density-dependent . For Glossina palpalis gambiensis tsetse flies , male flies preferred to feed on cattle rather on reptiles in a stable; the host species selected for the second bloodmeal depended on the host encountered for the first bloodmeal , the between-meal interval and the interaction between these two factors [9] . In mosquitoes , acquired feeding preferences are reflected in their tendency to return to the same villages , houses , host species and oviposition sites [10] . A non-homogeneous distribution of vector feeding contacts on the same host species leads to a basic reproduction number of the pathogen ( R0 ) greater than or equal to that obtained under uniform host selection , a result that still holds when groups of mosquitoes and hosts are highly structured in patches [11] , [12] . Triatomine bugs ( Hemiptera: Reduviidae ) are the vectors of Trypanosoma cruzi , the causal agent of Chagas disease . Triatoma infestans ( Klug ) , the main vector of T . cruzi , is a highly domiciliated species that also occurs in peridomestic structures housing domestic animals [13] . Like most species of triatomine bugs , T . infestans shows eclectic host-feeding patterns [14] , [15] . Host proximity has usually been considered more important than host preference for hungry bugs seeking to feed [14] . In laboratory-based host choice experiments of Triatoma sordida ( a species typically associated with birds ) , first-instar nymphs significantly preferred birds to humans [16] whereas fifth-instar nymphs feeding success and bloodmeal size were significantly larger on guinea pigs than on pigeons [17] . Triatoma infestans preferred caged chickens to guinea pigs though not in all replicates [18] . In a simultaneous exposure of four caged vertebrate species to separate groups of fifth-instar nymphs of T . infestans , Triatoma dimidiata and Rhodnius prolixus , none displayed dominant host-feeding preferences among dogs , chickens and opossums but toads were only rarely fed upon [19] . These authors [19] concluded that T . infestans showed a slight preference for dogs in short daytime experiments and a slight one for chickens in overnight trials . No measure of variability in host-feeding choices between the 7–22 replicates for each triatomine species was reported and neither were statistical procedures described . Within the restricted experimental conditions used , the tested triatomine species do not appear to have a fixed or dominant preference for any of the study hosts , and the question whether there are host-feeding preferences between dogs and chickens is still unresolved . In rural areas of the Argentine Chaco , domestic T . infestans blood-fed more frequently on dogs or chickens than on the human hosts or cats with which they shared sleeping quarters [7] . Seasonal host shifts were recorded . In spring-summer bug collections , the proportion of domestic bugs that fed on dogs increased significantly with increasing numbers of dogs and T . infestans in bedroom areas , and decreased as bug feeding frequency on chickens rose . Feedings on cats increased significantly with the number of cats and decreased with the number of dogs in bedroom areas . Dog-fed T . infestans had higher infection prevalence with T . cruzi than bugs feeding on other hosts , but many bugs within a given house fed on up to four different bloodmeal sources in summer [20] . Both domestic dogs and cats acted as a source of T . cruzi infection to other species , including humans , whereas chickens ( not susceptible to T . cruzi ) contributed strongly to bug population growth [21] , [22] . Using molecular typing techniques of T . cruzi , we recently showed that dogs , cats and a large fraction of the T . infestans within a household shared the same parasite sublineage and therefore were connected epidemiologically [23] . Understanding the factors that affect the host-feeding selection patterns of triatomine bugs is crucial to estimating transmission risks and predicting the putative effects of introducing or removing domestic animal hosts or targeting them for control . The recent emergence of pyrethroid resistance in T . infestans in northern Argentina and Bolivia [24] , combined with the low effectiveness of standard residual spraying of pyrethroid insecticides in peridomestic structures [25] , gave strong impetus to the search for cost-effective , alternative treatments based on the application of powder , topical lotions or insecticide-impregnated collars to the domestic animals themselves [26]–[28] . Whether chickens or dogs would be the preferred targets is one of the questions that motivated the current study , in which we report the first binary discrete host choice experiments of triatomine bugs conducted in small mud-and-thatch huts under natural climatic conditions . We tested whether T . infestans displayed host-feeding preferences between dogs and chickens and between dogs and cats , all unrestrained , and whether the density of vectors per hut modified host-feeding success , blood-engorgement and other vital rates in replicated trials . Analysis of field blood-feeding patterns and laboratory experiments supported the hypothesis that T . infestans would prefer chickens to dogs and dogs to cats , though the evidence regarding chickens and dogs was inconclusive [15] , [19] , [29] . We also hypothesized that blood-feeding success , engorgement and post-exposure bug weight would be reduced in a density-dependent way [13] , [30] . To infer the putative processes accounting for the observed discrepancies , we re-examined the reported host-feeding patterns of domestic T . infestans in the field in light of experimental host choices and the demographic and behavior patterns of domestic animal hosts .
The trials were carried out in the field station run by the Argentinean National Vector Control Program in Punilla , Province of Córdoba ( 31°14′S , 64°28′W ) in summer ( late January ) and in early winter ( June ) 2006 . Study location and experimental set-up were previously described [27] , [31] . For the present study , six small experimental huts simulating typical mud-and-thatch houses ( 1 . 60×0 . 80×0 . 80 m with a 40 cm-wide entrance ) were built and subdivided into two equally-sized rooms that shared an adobe-bricked wall with loose bricks; this arrangement allowed the bugs to hide and move freely between rooms . The lower third of the middle wall and all of the other walls were plastered on the inside with a 7∶1 mixture of soil and cement , and a cement carpet was added over the floors of beaten earth . A cage of plastic mosquito netting mounted on a metal frame was placed above each hut to prevent bugs from escaping . The six huts were arranged in two rows over a 50 m2 rectangle . Seven mongrel male dogs ( approximate age range , 4–7 years; mean weight , 10 . 8 kg; SD , 3 . 4; range , 7–15 ) were used in the trial . All dogs had been exposed to T . infestans and had worn deltamethrin-impregnated collars for a four-month period ending six months before the current experiment [27] but not thereafter . According to the collars' manufacturer , the residual effect of the insecticide should cease within six months or one month after removing the collars; since collar use started >10 months before the first trial , no residual effect was expected to occur at this time . Dogs were vaccinated and dewormed with mebendazole prior to the start of the trial; they were kept in kennels made of chicken wire and a roof and fed twice daily . Chickens ( all females; approximate age range , 2–2 . 5 years; mean weight , 2 . 4 kg; SD , 0 . 3; range , 1 . 9–2 . 8 ) of Lohmann breed were identified with a color ribbon and kept separately from other animals in a similar pen . Cats were a female and two male adults ( approximate age range , 2 . 5–4 years; mean weight , 2 . 7 kg; SD , 0 . 2; range , 2 . 5–2 . 9 ) . Dogs , but not chickens or cats , had previously been exposed to T . infestans bites six months before the first trial [27] . Chickens and cats had not been treated with insecticides . During the trials each animal was stationed individually inside a specific experimental hut at sunset and then released every morning into its specific area within the compound . This study complied with guidelines on research and biological testing activities involving live vertebrate animals from the Institutional Animal Care and Use Committee ( IACUC ) at FCEN-UBA , which is based on the International Guiding Principles for Biomedical Research Involving Animals developed by the Council for International Organizations of Medical Sciences . The T . infestans bugs used in these experiments were first or third generation from bugs collected in Córdoba , Santiago del Estero and San Luis ( Argentina ) ; they had been reared on chickens at the insectary ( at 27°C , relative humidity 70% ) , fed to repletion on the fourth instar , and starved for 2 . 5 ( first trial ) to 3 . 5 months ( second trial ) prior exposure to the hosts . This long starvation period ( >2 months after they molted to fifth instars ) normally does not increase bug mortality , and was used to secure that the previous bloodmeals on chickens were completely digested at the time of the trials ( i . e . , no ‘false positive” bloodmeal ) . Before release , a 20% sample of triatomine bugs for each trial was weighed individually with an electronic balance ( precision , 0 . 1 mg ) , and the volume and shape of the bugs' midgut was observed by transparency against a torch light to check their nutritional status semi-qualitatively based on the size of the bug abdomen and occurrence of blood remnants [27] , [32] . This classification ( by which bugs are scored as unfed , little fed , medium fed , and fully fed ) was consistent between observers . All bugs were classified as unfed immediately before the trials . The first trial was started on late January 2006 ( summer ) and included six matched dog-chicken pairs , each housed in a different hut . Each pair was randomly assigned to one of two levels of bug abundance ( 30–31 or 90–91 fifth-instar nymphs of T . infestans ) ; the upper bug density level was chosen because it had revealed negative density-dependent effects on domestic bug host-feeding patterns whereas the lower one did not [7] . The trial was replicated on three successive nights in the absence of any artificial source of light . Each host species was housed in a different room . Hosts were rotated among huts and between rooms every night , so that each individual host was matched with a different individual of the other host species during each of the three nights , and each individual room housed alternate host species in successive nights . Before the hosts were stationed within the huts at 8 p . m . , the bugs were placed in a box with holes on the central wall at mid-day , and recovered after dismantling the movable parts of each hut on the next morning at 8 a . m . On recovery , all insects were immediately brought to the insectary , counted , scored for degree of engorgement , kept for 2 days post-recovery and then weighed ( to allow them to approach the body weight plateau after eliminating the surplus of water in the bloodmeal ) , put in a vial labeled with a unique identifier for each bug , and then frozen at −20°C until dissection and bloodmeal identification . A subsample of 20 bugs not exposed to the hosts ( control bugs ) was frozen at −20°C at the same time as the recovered bugs to check whether there was any residual chicken bloodmeal in them . Given the experimental setup , we exclude the possibility that the small proportions of lost bugs escaped from the caged huts , and assume that lost bugs were most likely eaten by hosts . The proportion of blood-fed bugs is defined as the number of fed bugs ( including little-fed , medium-fed and fully-fed bugs ) plus bugs in the unfed nutritional class that later were ELISA-reactive to the test host species , relative to the total number of bugs examined for nutritional status; “fed” is therefore a composite category adjusted for bloodmeal reactivity among unfed bugs . The proportion of engorged bugs is defined as the sum of bugs medium fed and fully fed relative to the total number of fed bugs . The second trial , conducted in June 2006 ( late fall ) , included three pairs of dog-cat and used the same protocol as the first trial except that hosts were stationed in the huts at 6 p . m . One replicate could not be finished properly because the cat fled away at the outset; this replicate was excluded from all calculations and analysis . Temperature and relative humidity inside the huts were measured using data loggers ( Hobo H08 , Onset ) inserted into the thatched roofs of both rooms and on the outside wall of a hut in the first trial , and on each of the three huts in the second trial . In the dog-chicken trial , mean internal temperatures from 8 p . m . ( sunset ) to 8 a . m . over the three trial nights were 22 , 24 and 21°C , respectively; the mean temperature difference between rooms within a hut ( dog-to-chicken ) in the stated period ranged from −0 . 2 to +0 . 7°C . In the dog-cat trial , mean ( minimum , maximum ) internal temperatures from 6 p . m . to 8 a . m . over the three huts in each trial night were 8 . 8 ( 5 . 4 , 13 . 3 ) , 7 . 6 ( 3 . 7 , 12 . 2 ) , and 10 . 0°C ( 7 . 8 , 14 . 9 ) , respectively . The mean temperature difference between rooms within a hut ( dog-to-cat ) averaged over the three huts for each trial night was −0 . 52 ( SD , 0 . 46 ) , +0 . 09 ( SD , 0 . 27 ) , and −0 . 41°C ( SD , 0 . 53 ) . Standardization of the direct ELISA assay was based on previous procedures [33] , [34] and the ELISA reagents' manufacturer manual ( Kirkegaard & Perry Laboratories ( KPL ) Inc . , Gaithersburg , MD ) . The data collected were entered in an Access database . Feeding indices ( FI ) were calculated as the ratio of the number of bugs that fed on a given host species X to the number of bugs that fed on the matched host species Y ( whether or not the bugs that fed on X fed on Y and vice versa ) . As only one host of each host species was present we did not need to correct for the number of hosts [35] . Four related measures of blood gain by the bugs were used: i ) feeding success , a binary variable measuring the likelihood of blood-feeding on any one or on both host species inside the hut ( i . e . , overall feeding success: fed bugs relative to the number of bugs recovered alive or dead ) , or on a specific host species as determined by ELISA ( i . e . , host choice ) ; ii ) engorgement ( a binary variable including medium-fed and fully-fed bugs: engorged bugs relative to the number of fed bugs ) ; iii ) nutritional status ( a categorical variable with four levels ) , and iv ) post-exposure bug weight ( a continuous variable , measured two days after host exposure ) . Engorgement and post-exposure bug weight measure the amount of blood imbibed overall or on a given host species . Exact 95% confidence intervals ( 95% CI ) for mean vital rates ( i . e . , binary variables ) were based on the binomial distribution . The effect size on several binary response variables was estimated by fitting random-effects logistic regression models clustered by hut to the data using the command xtlogit in Stata 9 . 1 [36] . The use of random-effects models addresses the fact that insects within a hut roughly share the same environment and other undetermined characteristics that may create dependencies between responses within the same cluster of observations . We tested for significant ( P<0 . 05 ) effects of trial ( dog-chicken trial = 1; dog-cat trial = 2 ) , vector density ( two levels ) and occasion ( three levels ) on several vital rates: bug recovery ( including both dead and alive bugs relative to the number of released bugs ) ; bug loss and mortality ( missing and dead bugs relative to the number of released bugs , respectively ) ; overall feeding success and engorgement , as defined above . An interaction term between vector density and occasion was added to each main-effects model . Host-feeding choices were analyzed by conditional ( fixed-effects ) logistic regression using McFadden's choice model with the command clogit and robust standard errors . These analyses only included unmixed host choices ( i . e . , dog , other ) in each trial because bugs with mixed or no bloodmeal could not be considered for this analysis . To examine whether host choices were modified by vector density levels , occasion and individual dog , interaction terms were added to each of the models . Alternatively , exact binomial tests were used to test for differences between host choices in each replicate relative to the null hypothesis of no selective host choice . Random-effects multiple linear regression with the command xtreg was used to test for significant effects on post-exposure bug weight of vector density , host blood source ( unmixed ) , nutritional status and occasion . Interaction terms were added one by one to the model with main effects and retained in the final model if P<0 . 1 . When the response variable was nutritional status , multinomial logit models were used .
Of 1 , 622 triatomine bugs released in both trials , 1 , 536 ( 94 . 7% ) were recovered and examined for nutritional status ( Table 1 ) . Random-effects logistic regression showed that the overall loss rate of bugs was significantly higher in the dog-chicken trial ( 6 . 8% ) conducted in summer than in the dog-cat trial ( 2 . 4% ) run in late fall ( OR = 0 . 32 , 95% CI , 0 . 11–0 . 96 , P = 0 . 042 ) , but the reverse happened with the observed mortality rate ( 0 . 3% vs 3 . 3% , respectively; OR = 12 . 23 , 95% CI , 3 . 56–41 . 98 , P<0 . 001 ) , with no significant occasion effects in both cases . Most of the dead bugs recovered were unfed ( 17 of 21 ) and had very low weight . Significantly more bugs blood-fed ( 98 . 7% ) in the dog-chicken trial than in the dog-cat trial ( 71 . 4%; OR = 0 . 031 , 95% CI , 0 . 016–0 . 058 , P<0 . 001 ) , but among the fed bugs , engorgement status did not differ between trials ( 46 . 8% vs 44 . 4% , respectively , OR = 0 . 96; 95% CI , 0 . 68–1 . 36 , P>0 . 8 ) . Vector density adjusted for occasion effects did not modify significantly any of the vital rates in both trials ( Table 1 ) . In the dog-chicken trial , we observed that most of the bugs were recovered from the thatched roof of the dog's room , followed by the adobe bricks in the mid-wall; the fewer bugs recovered from the chicken's room were in the thatched roof . Of all the bugs with identified bloodmeals , 81 . 8% had feedings on dogs and 24 . 0% on chickens . The dog-to-chicken mean feeding index was 7 . 0 ( 95% CI , 3 . 7–10 . 3 ) . The total mean percentage of insects that fed on dogs only ( 75 . 0% , 95% CI , 71 . 5–78 . 3% ) was significantly higher than that on chickens only ( 18 . 0% , 95% CI , 15 . 1–21 . 1% ) ( Fig . 1A ) . Both feeding choices were highly significantly correlated ( r = 0 . 88 , P<0 . 001 ) at each hut ( Fig . 2A ) . Only 5 . 8% ( 95% CI , 4 . 1–7 . 9% ) of bugs fed on both hosts , and 1 . 2% ( 95% CI , 0 . 5–2 . 4% ) on none . Conditional logistic regression showed that dogs were highly preferred to chickens ( OR = 11 . 2; 95% CI , 6 . 2–20 . 1 , P<0 . 001 ) and high vector density significantly reduced feedings on dogs ( OR = 0 . 51; 95% CI , 0 . 32–0 . 82 , P = 0 . 005 ) , with significantly reduced dog choice at occasion 2 ( OR = 0 . 37 , 95% CI , 0 . 22–0 . 62 , P<0 . 001 ) . Feedings on dogs were homogeneous among individual dogs ( P>0 . 1 ) . When each replicate was taken separately , dogs were significantly preferred over chickens in 16 of 18 replicates ( binomial test , P≤0 . 001 in 13 replicates and P<0 . 05 in 3 replicates; one trial was marginally significant , P = 0 . 06 , and one not significant ) . Eighteen ( 47% ) of the 38 mixed bloodmeals recorded were from a single dog . None of the 20 control bugs not exposed to the hosts were positive for chicken bloodmeal . In the dog-cat trial , the apparent dispersion pattern of bugs on recovery was more mixed among days; only in one day were most of the bugs located in the dog's thatched roof . Of the bugs with identified bloodmeals , 69 . 0% had feedings on dogs and 31 . 6% on cats . The dog-to-cat mean feeding index was 4 . 8 ( 95% CI , 2 . 7–6 . 9 ) . Significantly more bugs blood-fed on dogs only ( 48 . 5% , 95% CI , 44 . 1–52 . 8% ) than on cats only ( 22 . 0% , 95% CI , 18 . 5–25 . 7% ) ; both indices were highly correlated ( r = 0 . 71 , P<0 . 001 ) though the relation was even stronger in the dog-chicken trial ( Figs . 1B and 2B ) . Only 0 . 4% ( 95% CI , 0 . 05–1 . 4% ) of bugs fed on both hosts , and no feeding was detected in 29 . 2% ( 95% CI , 25 . 3–33 . 2% ) . Conditional logistic regression showed that dogs were significantly preferred to cats ( OR = 7 . 8; 95% CI , 1 . 7–35 . 8 , P<0 . 001 ) and vector density reduced significantly the likelihood of feeding on dogs ( OR = 0 . 09; 95% CI , 0 . 01–0 . 66 , P = 0 . 018 ) , with significantly increased dog choice at occasion 2 ( OR = 8 . 9 , 95% CI , 1 . 6–48 . 7 , P = 0 . 012 ) . Heterogeneous feeding rates on individual dogs 3 ( OR = 6 . 5 , 95% CI , 2 . 6–11 . 1 , P<0 . 001 ) and 4 ( OR = 0 . 24 , 95% CI , 0 . 07–0 . 84 , P = 0 . 025 ) relative to dog 2 were recorded . Bugs significantly preferred the dog in five replicates ( P≤0 . 001 in four replicates , P<0 . 02 in one ) and the cat only in one replicate ( P<0 . 001 ) , whereas no significant differences were found in two replicates ( P>0 . 2 ) . Two of the cats frequently allowed the bugs to blood-feed on them though with large variations between nights . In the excluded replicate that had no cat , 93% of the released bugs were recovered and 79% of them were fed on dog only , with no feeding on cat detected . The relationship between proportional host body weight and host-feeding preferences in both trials is shown in Fig . 3 . Two different patterns were obtained . The proportion of bugs that fed on dogs and proportional dog body weight were unrelated in the dog-chicken trial , whereas a significant relationship was found in the dog-cat trial ( OR = 1 . 21; 95% CI , 1 . 03–1 . 44 , P = 0 . 022 ) where exclusion of an outlier value gave a stronger relationship ( OR = 1 . 32; 95% CI , 1 . 20–1 . 45 , P<0 . 001 ) . Table 2 shows the relation between bug nutritional status on recovery of live and dead bugs , post-exposure mean bug weight , and bloodmeal source in both trials . Before exposure to hosts , the distributions of bug weight in the dog-chicken trial ( mean , 61 . 9 mg; 95% CI , 60 . 3–63 . 5 ) and in the dog-cat trial ( mean , 59 . 3 mg; 95% CI , 56 . 6–62 . 0 ) were not significantly different ( Anova , F = 2 . 80 , df = 340 , P = 0 . 095 ) . Post-exposure mean bug weight in the dog-chicken trial ( 238 . 1 mg ) was significantly higher than in the dog-cat trial ( 136 . 8 mg ) ( Anova , F = 432 . 3 , df = 1 , 503 and 1 , P<0 . 001 ) , and steadily and significantly increased with nutritional status class in both trials ( Anova , dog-chicken: R2 = 0 . 61 , F = 515 . 6 , df = 973 and 3 , P<0 . 001; dog-cat: R2 = 0 . 59 , F = 253 . 0 , df = 524 and 3 , P<0 . 001 ) . In total , 1 , 160 bugs were tested by ELISA and bloodmeals from 1 , 023 bugs were identified . The percentage of bugs with dog bloodmeal only varied marginally from 74 . 8% to 81 . 8% among nutritional classes in the dog-chicken trial ( χ2 = 6 . 60 , df = 3 , P = 0 . 086 ) , but increased significantly from 35 . 0% to 62 . 5–76 . 0% in the dog-cat trial ( χ2 = 16 . 1 , df = 3 , P<0 . 001 ) . The fraction of bugs with mixed meals on dogs and chickens steadily increased with nutritional status up to 12 . 1% in the fully-fed bugs . More bugs in the unfed nutritional class were ELISA-reactive in the dog-chicken trial ( 68 . 7% of 16 ) than in the dog-cat trial ( 15 . 9% of 126 ) ( Fisher's exact test , P<0 . 001 ) . Most bugs classified as little-fed in the dog-cat trial and not reactive to dog or cat by ELISA had residual chicken bloodmeals taken in the insectary three months before . The post-exposure engorged status and mean bug weight of T . infestans according to vector density and individual host blood source are shown in Table 3 and Fig . 4 , respectively . In the dog-chicken trial , the percentage of blood-engorged bugs was higher if the bug fed on dog only ( 43 . 4–48 . 5% ) rather than only on chicken ( 34 . 1–36 . 7% ) , whereas bugs with mixed bloodmeals were more frequently engorged ( 70 . 4–72 . 7% ) than those with unmixed meals ( Table 3 ) . Relative to little-fed bugs ( unfed bugs were rare ) , the relative risk ratio ( RRR ) of a bug being medium-fed ( RRR = 1 . 62 , 95% CI , 1 . 02–2 . 57 , P = 0 . 039 ) or fully-fed ( RRR = 2 . 1 , 95% CI , 0 . 8–5 . 3 , P = 0 . 14 ) was significantly higher if the bug had fed on a dog only , after adjusting for significant occasion effects ( P<0 . 001 ) and non-significant ( P>0 . 4 ) vector density effects ( n = 600 , χ2 = 44 . 3 , P<0 . 001 , AIC = 1059 . 2 , df = 10 ) . All two-way interaction terms were not significant . Post-exposure mean bug weight varied significantly ( P<0 . 001 ) with nutritional status and its interaction with occasion but not with vector density or host blood source ( P>0 . 6 ) ( R2 = 0 . 606 , n = 583 , P<0 . 001 ) ( Fig . 4A ) . In the dog-cat trial , the dog-fed bugs engorged significantly more than the cat-fed bugs at lower vector densities ( 64 . 6% vs 18 . 8% , respectively ) , but there were smaller differences at higher levels of infestation ( 44 . 7% vs 37 . 0% , respectively ) ( Table 3 ) . When compared to unfed bugs , the relative risk ratio of a bug being little-fed ( RRR = 4 . 7 , 95% CI , 1 . 8–12 . 4 , P = 0 . 002 ) , medium-fed ( RRR = 7 . 2 , 95% CI , 2 . 6–19 . 5 , P<0 . 001 ) or fully-fed ( RRR = 3 . 8 , 95% CI , 0 . 98–15 . 1 , P = 0 . 053 ) increased significantly if the bug had a feeding on dog only , after adjusting for significant occasion effects ( P<0 . 02 ) and marginal effects ( P = 0 . 056 ) of vector density ( n = 372 , χ2 = 31 . 9 , P<0 . 001 , AIC = 745 . 3 , df = 15 ) . Post-exposure mean bug weight ( log-transformed to normalize the distribution ) was significantly modified by host blood source ( P = 0 . 022 ) , vector density ( positively , P = 0 . 008 ) , nutritional status ( positively , P<0 . 001 ) and occasion ( P<0 . 001 ) ( Fig . 4B ) . Addition of interaction terms revealed significant effects ( P<0 . 03 ) between occasion and vector density or nutritional status ( n = 372 , R2 = 0 . 75 , P<0 . 001 ) .
Increased host tolerance implies increased residence and feeding times on the host , which in turn will increase fitness by increasing the overall rate at which blood is obtained , eggs are produced , and survival per feeding attempt [55] . The nutritional quality of blood may differ substantively between host species of R . prolixus [56] , with chicken blood having half the hematocrit than mammals and much lower hemoglobin or plasma protein than dogs [57] . Therefore , the aggregate fitness implications of host choices remain to be established . Of note , the host bloodmeal choice variable includes a survival component because it was measured on recovered , fed bugs . Because bloodmeal size increases the probabilities of T . infestans emitting dejecta sooner [58] , ingesting trypanosomes and becoming infected [21] , it follows that preferred , tolerant hosts such as dogs will seriously increase transmission rates relative to other domestic hosts . By virtue of allowing larger bloodmeals , the likelihood of dogs being repeatedly contaminated with bug feces and eventually superinfected with various parasite strains would be increased . The large frequency of unmixed dog bloodmeals shown by T . infestans in some field locations further suggests that a strong , stable link between individual dogs or groups of dogs and groups of bugs occurs in some households , thereby increasing transmission of T . cruzi back and forth from dogs to bugs and creating a transient partial refuge for other host species ( a zooprophylactic effect ) . In most households , however , the frequency of mixed bloodmeals on dogs is high during spring-summer , and because domestic host species and bugs are more connected the flux of parasites between them is enhanced . Selective host choice amplified by a greater feeding success on diseased or infected hosts will increase the basic reproduction number of T . cruzi ( though with possibly depressed prevalence and incidence as the outbreak follows through ) compared with the base case represented by homogeneous contact rates [11] , [12] , [59] . An increase in dog or cat availability or accessibility in domestic areas will increase the rate of bug feeding on them which in turn will exert non-linear effects on R0 through the squared biting rate term . When the proportion of insects feeding on a given host species ( i . e . , humans ) varies with the relative abundance of non-human ( i . e . , dogs , cats , chickens ) and human hosts and with the ratio of vectors to hosts , as our studies have shown , the relationship between R0 and host blood indices is predicted to be strongly non-linear [2] . This implies that different tactics that seek to reduce vector abundance will exert very different impacts on parasite transmission depending on the exact relationship between R0 and the vector-to-host ratio . The empirical evidence further supports the prediction that removal of dogs from bedroom areas will strongly decrease domestic bug population size , transmission rates and human incidence of infection [22] . Heterogeneities in vector feeding rates and in host exposure and infection will tend to create ‘hot’ and ‘cold’ spots of transmission , which can be used to target more accurately and efficiently host species and individuals accounting for most of the risk . Application of pyrethroid-impregnated dog collars , causing reduced repellency but increased bug mortality for extended periods [27] , are predicted to strongly reduce domestic bug population size and transmission rates . The various layers of heterogeneity involving dogs in rural endemic areas , including household aggregation of infection , infectiousness to bugs and exposure patterns [21] , [51] , can be used when designing control measures . For increased impact , collars or other similar tools should be preferentially applied to those dogs that are infected with T . cruzi and/or highly infectious to bugs and that are also closely associated with domestic sites ( e . g . , pups , females in reproductive state or restrained dogs ) . Such dogs can be turned into baited lethal traps , though a thorough cost-effectiveness assessment of such tactics is needed before large-scale field application . Other possible applications are to use dogs as baited sentinels of bug presence through the use of its immune response to salivary antigens for serologic surveillance during a bug elimination campaign [60] and as sentinels of parasite transmission [51] . | Chagas disease is a complex zoonosis with more than 150 mammalian host species , nearly a dozen blood-sucking triatomine species as main vectors , and 9–11 million people infected with Trypanosoma cruzi ( its causal agent ) in the Americas . Triatoma infestans , a highly domesticated species and one of the main vectors , feeds more often on domestic animals than on humans in northern Argentina . The question of whether there are host-feeding preferences among dogs , cats , and chickens is crucial to estimating transmission risks and predicting the effects of control tactics targeting them . This article reports the first host choice experiments of triatomine bugs conducted in small huts under natural conditions . The results demonstrate that T . infestans consistently preferred dogs to chickens or cats , with host shifts occurring more frequently at higher vector densities . Combined with earlier findings showing that dogs have high infection rates , are highly infectious , and have high contact rates with humans and domestic bugs , our results reinforce the role of dogs as the key reservoirs of T . cruzi . The strong bug preference for dogs can be exploited to target dogs with topical lotions or insecticide-impregnated collars to turn them into baited lethal traps or use them as transmission or infestation sentinels . | [
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"of",
"infec... | 2009 | Strong Host-Feeding Preferences of the Vector Triatoma infestans Modified by Vector Density: Implications for the Epidemiology of Chagas Disease |
Mycobacterium ulcerans infection , commonly known as Buruli ulcer ( BU ) , is a debilitating neglected tropical disease . Its management remains complex and has three main components: antibiotic treatment combining rifampicin and streptomycin for 56 days , wound dressings and skin grafts for large ulcerations , and physical therapy to prevent functional limitations after care . In Benin , BU patient care is being integrated into the government health system . In this paper , we report on an innovative pilot program designed to introduce BU decentralization in Ouinhi district , one of Benin’s most endemic districts previously served by centralized hospital-based care . We conducted intervention-oriented research implemented in four steps: baseline study , training of health district clinical staff , outreach education , outcome and impact assessments . Study results demonstrated that early BU lesions ( 71% of all detected cases ) could be treated in the community following outreach education , and that most of the afflicted were willing to accept decentralized treatment . Ninety-three percent were successfully treated with antibiotics alone . The impact evaluation found that community confidence in decentralized BU care was greatly enhanced by clinic staff who came to be seen as having expertise in the care of most chronic wounds . This study documents a successful BU outreach and decentralized care program reaching early BU cases not previously treated by a proactive centralized BU program . The pilot program further demonstrates the added value of integrated wound management for NTD control .
The endemic Ouinhi district is located along the Ouémé River in southern Benin ( Fig 1 ) . It is one of the five most endemic districts ( Fig 2A ) ; of these , it has the highest number of Category III cases ( Fig 2B ) . The local population depends on multiple household livelihood strategies , predominantly fishing , small-scale agriculture , and travel to urban areas in Benin and Nigeria for seasonal labor and remittance . Underdeveloped road and communication infrastructure limit community access to health resources . The research area is served by three local health centers in Sagon , Dasso , and Tohoue , which operate under the direction of the district hospital in Ouinhi ( Fig 3 ) . Treatment modalities available in the region are diverse , and include: local clinics; drug peddlers in local markets and small pharmacies; traditional wound specialists who specialize in plant-based topical treatments or physiotherapy; and healers , diviners , and religious leaders that apply metaphysical techniques . There are multiple religions in the region including Islam , Catholicism , Pentecostal Christianity , and vodun , the indigenous religion of the predominant ethnic group in the region , the Mahi-Fon . The diversity of medical and religious practices leaves the population open to multiple possible interpretations of chronic wounds that do not heal . Previous research [9–11] found that households often seek multiple forms of health care simultaneously , and may add any of the above modalities to biomedical care . Before the pilot intervention , suspected cases of BU either went to clinics in the national health system or were brought directly to the nearest center specialized in Buruli ulcer treatment , the Centre Sanitaire et Nutritionnel Gbemoten ( CSNG ) ( Fig 4A ) . Located in Zangnanado , CSNG is one of the four reference centers for BU treatment ( CDTUBs ) that form the national BU system ( Fig 3 ) . Operated as a private Catholic facility , Zangnanado is relatively close ( 10–15 miles ) to most patients in the study area , although accessibility becomes an issue during the rainy season , when much of the endemic region is flooded . CSNG covers much of the cost of BU treatment and transportation to the hospital , and has established a vigilant system of case detection , since the hospital often faces resistance from suspected cases . CSNG has been treating Buruli ulcer in Benin since 1989 , and has developed considerable surgical expertise in its treatment and an exceptionally low rate of relapse [12 , 13] . The center has developed an extensive network of village volunteers who work in collaboration with trained health workers to identify cases and raise awareness about the disease . Before decentralization of Buruli ulcer care , clinics in the endemic region collaborated with CSNG staff to refer all suspected BU cases ( Fig 4A ) , following a general protocol of excision even for Category I ulcers . A key factor in getting CSNG to accept the pilot was the inclusion of other wounds in the decentralization protocols . Because tropical ulcers and other chronic wounds are often unresponsive to treatment and can require extensive stays , hospitals are obliged to expend considerable financial and human resources in their treatment . The new protocols promised to reduce the burden of treating chronic ulcers in the hospital by catching them early enough to be treated at local clinics . This would allow CSNG staff to focus their resources on their area of expertise: surgical care of advanced Buruli cases . The pilot intervention also required the collaboration of officials of the national health system . Permission was granted by both the coordinator of the zone hospital in Covè and the head doctor of the district hospital in Ouinhi who oversees the clinics under his jurisdiction . The current head district doctor was particularly receptive to the idea of introducing decentralized care in the clinics .
As part of a community intervention , this study was approved by the Benin’s National Ethical Committee for Health research ( IRB00006860 N°148/MS/DC/SGM/DFRS/CNPERS/SA ) . The national and regional health authorities also gave their authorization for the implementation of the study and fully participated in the interventions . All participants ( patients , village volunteers and local staffs ) were widely informed about the study and the process . They were assured about the anonymity of all data collected and any information gathered during the evaluation process . All patients as well as interviewees signed a written informed consent form , after the content had been fully explained to them by a local translator independent of the team of researchers ( for those who were illiterate ) . For participants under 18 years old , they were informed together with their parent ( usually the mother ) or guardian before the parent / guardian signed the consent form . A specific informed consent form was given by the Tohoue nurse for the inclusion of his photograph in the article . A baseline study of BU-related perceptions and healthcare-seeking behavior was conducted in 2011 . The primary aim of the study was to identify determinants of treatment delay in the most endemic district covered by CSNG . One hundred and two households with patients treated for BU in areas covered by CSNG from 2000 to 2010 were interviewed . This first stage of formative research investigated: local perceptions of all chronic ulcers; recognition of the signs of BU at different stages; home-based wound care; healthcare-seeking behavior for chronic wounds; reasons for consulting ( and not consulting ) available biomedical facilities; and reasons for delaying treatment . Our research was informed by previous social science investigations of BU conducted in Benin [10] as well as elsewhere in West Africa [14 , 7 , 15 , 16] . The perceptions and experiences of former and current patients have proven to be valuable when designing both community outreach and clinic based BU interventions [17 , 18] . An innovative outreach education program being developed by the Stop Buruli Consortium in Benin , Cameroon , and Ghana [19] was adapted for use in Ouinhi based on the findings of stage one formative research . The education program took the form of an image-rich PowerPoint presentation about BU delivered by clinic staff and health volunteers equipped with generators , computers , LCD projectors and sound systems ( Fig 5 ) . A question–answer format was adopted with new questions added as they arose during community meetings ( Table 1 ) as part of an iterative process . Mass outreach education events were designed to be interactive , not passive , and questions were invited from the community . PowerPoint presentations were employed because they are easy to modify in response to questions posed and issued raised . Social scientists conducted ongoing translational research to identify how best to respond to questions in a way that was at once scientifically accurate and comprehensible to local audiences . Messages and visuals were tested and changed as needed . Community outreach education meetings were held in the evenings , organized by local volunteers , and facilitated by volunteers and clinic staff trained in how to communicate information and field questions from the community . The social science team responsible for developing the educational program selected and mentored a CDTUB staff member with strong communication skills to serve as a health staff trainer . Prior to functioning as a trainer , he had several months of experience delivering education programs during the pretesting of the outreach program . Training was practical and focused on how to present the material on slides in an easy-to-understand manner , respond to common questions raised by the audience , and facilitate interaction . Social scientists monitored all outreach programs as a means of collecting community feedback to modify the educational program . Village chiefs , local healers , and former patients were invited to all outreach meetings . At the conclusion of outreach meetings , health staff offered the opportunity for screening to those community members who wished to learn whether their wounds might be BU , either at that time or at a participating clinic the next day . BU community support groups were established in villages associated with each participating clinic to help identify possible BU cases , encourage all villagers with chronic ulcers or wounds to seek treatment at participating clinics , provide psychosocial support during the process of decentralized BU treatment , and to follow up on cases of treatment dropout . These groups were composed of village volunteers who had already been working with CSNG previously , health volunteers from other programs , village leaders , and healers and religious leaders interested in participating . Groups met at clinics once a month and coordinated activities with clinic staff . In order to facilitate the introduction of decentralized treatment in Ouinhi , a support group was established in each district . Support groups included representatives from each village and were selected by village chiefs and their advisors . The proposed list was then confirmed with health staff from the district healthcare center , and three members were selected as officers ( a chair , a secretary , and a treasurer ) . Support group members helped arrange and attended outreach activities , assisted in early detection , and identified vulnerable patients ( for all wound types ) in particular need of assistance . The assistance provided to those in dire need consisted of daily transport for treatment for those living more than 2 kilometers from a clinic , a modest food allowance , and school support for children who might otherwise drop out of school as a result of treatment . Support in the form of food and transportation have increased BU treatment acceptability and adherence in established decentralized treatment programs in countries such as Ghana [20] . Over the course of two months , the medical staff of CDTUB Allada trained Ouinhi district health personnel in the Center on the principles of wound care . The medical doctor responsible for Ouinhi district hospital , the nurses responsible for three clinics in Ouinhi , and two attendants per clinic all received training . The training was conducted in six stages . First , the doctor from the district hospital was brought up to date on major research findings related to the epidemiology and treatment of Buruli ulcer . Emphasis was placed on advances in BU control and care since the setting of the Global Buruli ulcer initiative in 1997 . Second , the two nurses and their clinic attendants were given a less intensive orientation into advances in BU research and treatment as well as the basic principles of wound care with an emphasis placed on wound hygiene . Instruction was also given on: how to diagnose BU; differential diagnosis of BU per type of lesion ( nodule , plaque , ulcer ) ; categorization of BU; the characteristics and differential diagnosis of common types of chronic ulcers and skin diseases; general principles of treatment and different components of BU treatment; reference criteria; identification and management of treatment side effects and contraindications such as during pregnancy; therapeutic management of cases ( BU and leprosy , BU and pregnancy , BU and tuberculosis ) ; different types of wound dressings and steps for each type; basic principles of wound dressing; when to request laboratory analysis; how to take swabs; and how to send samples for laboratory analysis . Third , existing health staff wound care practices were elicited , reviewed and compared against best practices advocated by WHO [21] . Fourth , practical clinical training was provided by staff at the Allada CDTUB . The practical training included: general wound hygiene techniques; bandaging skills; recognition and prevention of common wound infections; and basic physical therapy as a means of disability prevention . Trainees were provided hands-on experience with BU patients at Allada hospital . Fifth , trainees visited decentralized centers of Zè district and participated in active case detection . They also participated in BU outreach programs using the innovative approach to BU education being introduced in Ouinhi and first pretested in Zè . Sixth , trainees were instructed on how to complete wound reporting and treatment monitoring data sheets . Upon oral examination at the end of the training period , trainees were able to successfully demonstrate knowledge of the materials covered throughout the training , with particular focus on BU diagnosis criteria , the use of streptomycin and rifampicin , and protocols for wound care . Following training , health staff returned to their clinics . Staff from Allada visited them every time they suspected a BU case . During their visit in Ouinhi , staff from Allada supervised and monitored practices of the trainees , and they were in routine contact with staff . When required , advanced BU patients were referred to CSNG . Other chronic ulcers ( e . g . , vascular ulcers , cancers , or large non-BU ulcers ) requiring advanced care were referred to CSNG or another appropriate treatment center ( Fig 4B ) . Lab tests were requested for every suspected case of BU , and staff from Allada , assisted by the district health workers , collected the samples ( FNA for non-ulcerated lesions and swabs for ulcers ) required for laboratory analysis . Samples were sent to Allada CDTUB for direct smear examination and to the reference laboratory for mycobacteria in Cotonou , for PCR . Allada also provided medical supplies ( antibiotics , wound dressing material , sample collection material ) to clinics as needed . Outcome and impact assessments of the project were conducted two years after the pilot intervention was initiated . The outcome assessment reviewed quantitative data on cases seen and successfully treated or referred . This entailed a review of clinic records on patient self-referral for wounds suggestive of different categories of BU as well as other chronic ulcers of at least six months’ duration . Data was also collected on patient adherence to decentralized BU treatment and the referral of cases from Tohoue to other clinical facilities . The impact evaluation entailed interviews and focus groups with clinic staff , patients , community volunteers and local leaders , and health officials . It generated in-depth qualitative data that considered intended and unintended effects of the intervention within the community . Interviews focused on: lines of communication and collaboration between clinic and community stakeholders; patient satisfaction with decentralized care; and the impact of expanded care on the reputation of the clinic and the status of health care workers and volunteers . The impact evaluation was conducted by a team of four social scientists and clinicians who conducted interviews with the informants listed in Table 2 . All interviews were conducted using pretested interview guides . The maps presented in this article ( Figs 1 and 2 ) were drawn using QGIS 1 . 8 . 0 and ArcView 3 . 2 software , based on open access shapes files obtained from www . diva-gis . org .
The baseline study revealed poor community-level recognition of Category I BU , but some level of familiarity with the signs of more advanced BU due to the outreach efforts of CSNG . Research revealed that enabling and health service-related factors delayed health care seeking for chronic wounds far more than predisposing factors related to such cultural concerns as witchcraft [cf . 22 , 23 , 24] . In households where suspected cases of BU had been identified , family members were often reluctant to accept the diagnosis , and had delayed hospital treatment due to practical concerns and rumors about what transpired within the hospital . These concerns included: competing work and child care obligations fundamental to household survival; concern about meeting indirect costs of hospital care; fear of abandonment; and fear of amputation ( often described within the community as a standard practice at CSNG ) . Former patients also frequently complained of not being informed about how long their hospitalization would last and not being informed about how their treatment was progressing . Outreach education programs were carried out in 22 villages in the Ouinhi health district . Approximately 4000 community members attended outreach meetings over the course of two years , with an audience size of 140–300 people per outreach program . Village leaders and local healers who supported BU outreach activities attended all meetings and contributed to their legitimacy . Half of the 20 outreach sessions were led by the staff nurse of Tohoue clinic , and the other half by village volunteers who had proven to be effective communicators in past health programs . Among these volunteers , one in particular was looked to for guidance , and he assisted other volunteers from several other villages in organizing and conducting outreach programs . Post-outreach interviews with 60 key informants from 15 villages conducted the day after outreach found that community members greatly appreciated the question and answer framework that provided the structure for the educational PowerPoint . Community members also appreciated the use of images to depict key messages , before and after pictures of wounds that had been treated , and the testimonials of past patients . The testimonials offered at outreach meetings were initially presented by former patients treated in centralized care who had recovered . As the project progressed , patients successfully treated in decentralized care began providing testimonials as well . The community was very happy to hear that free outpatient treatment was available for not just BU , but for all chronic wounds at Tohoue , and they felt reassured when patients spoke of their positive experience with health staff . The staff of the three healthcare centers selected in the Ouinhi district already had basic knowledge of Buruli ulcer prior to the training , but were not aware of decentralized treatment protocols or their effectiveness , and did not feel competent to treat BU or other chronic ulcers . Chronic ulcers were referred and not treated in their clinics prior to training . Training addressed knowledge gaps in wound assessment and wound care procedures , especially antibiotic treatment protocols . After the training period in Allada , they were able to make a more accurate clinical diagnosis of BU , provide and follow appropriate antibiotic treatment , and deliver correct wound care to patients . Training also taught staff to provide adequate wound care to chronic non-complicated ulcers , thereby avoiding the systematic referral of simple cases to CSNG . Table 3 summarizes patterns of referral , treatment and adherence to treatment in the Ouinhi district following the pilot intervention . A few findings are worth highlighting . Ouinhi is a district in which proactive BU case finding has been going on for over two decades by CSNG hospital . CSNG is highly motivated to identify BU cases inasmuch as its funding is tied to treating BU surgically . While the hospital has an impressive track record of treating more serious Category II and III BU cases , its record for detecting Category I cases is well below the national average . The pilot study demonstrated that Category I cases could be identified in the community following outreach education , and that these community members were willing to accept decentralized treatment . During the impact evaluation , the families of several successfully treated patients under the decentralized scheme reported that they had refused to be treated at CSNG or had delayed doing so because of grave concerns as to how this would affect the well-being of their household . Outreach education increased BU identification by community members . In the two years prior to the pilot project , the nurse at Tohoue clinic saw 14 chronic ulcer patients ( Buruli ulcer and other ulcers ) . All of these cases were referred to CSNG , and he received no feedback about them . After the outreach program , the number of community members with chronic ulcers coming to the Tohoue and Dasso clinics soared to 96 ( over a two-year period of time ) , with most patients coming directly to the Tohoue clinic because of the reputation of the nurse for treating cases effectively . A smaller number of chronic ulcer cases visited Dasso clinic located 5 kilometers away , but treatment was not offered . Fifty-three of the 96 cases of chronic ulcer ( 55% ) who were seen at Tohoue and Dasso were self-referred , with the remaining 43 ( 45% ) referred by support group members . During the impact evaluation , the families of several successfully treated patients under the new decentralized scheme described how outreach programs had convinced them of the need for early treatment . Following outreach programs , they had sought care at the local clinic without delay . Notably , of the 96 chronic ulcer cases seen in Tohoue and Dasso , 53 ( 55% ) were suspected to be BU cases , and of these 41 ( 77% ) were confirmed to be BU . Of these confirmed cases 29 ( 71% ) were Category I or II BU cases treatable by a decentralized care protocol ( Picture 3A and 3B ) . Impressively , all BU cases treated completed a full 56 days of treatment . Twenty-seven of the 29 cases of BU in decentralized care ( 93% ) were successfully treated at Tohoue . The two remaining cases eventually required surgery and were referred to CSNG for surgery . Another 48 cases of chronic ulcer were seen at the clinic , of which 14 were treated . The remaining 34 cases were beyond the capability of the nurse to treat and were referred to CSNG for surgery . Out of the 96 chronic ulcer patients treated by the two healthcare centers , 43 were referred by support group members and of these 27 were suspected BU cases . Notably , traditional healers referred 7 of these patients . Nineteen out of the 27 suspected BU cases proved positive for the PCR and 11 patients were followed up for treatment compliance by the support group . As part of the social assistance provided to vulnerable patients , daily transport to the clinic and feeding were provided respectively to 10 patients and 35 patients . Transport to CSNG was provided for 35 patients , including both advanced ( Category III ) BU cases and non-BU chronic ulcers . Medication assistance was offered to 22 non-BU patients , and 8 children were offered support to keep them in school . CSNG , the regional reference center for Buruli ulcer , has experienced three major shifts in responsibilities as a result of the intervention . First , patients in the Ouinhi district now have the choice to seek decentralized , non-surgical care at peripheral health clinics for early-stage Buruli ulcers rather than additional surgical care at CSNG for all BU cases . Second , the care of chronic , non-Buruli ulcers is now offered by the clinics participating in the pilot project . Finally , CDTUB Allada , the country’s main reference center for Buruli ulcer , oversees the follow-up care for wounds treated in the peripheral clinics . The impact evaluation found that while serious cases of BU are being referred to CSNG hospital , CSNG is not referring non-BU cases to Tohoue clinic for treatment or to manage postsurgical follow-up care on an outpatient basis . There was one exception . The parents of a girl whose Buruli ulcer had not responded well to repeated surgeries at CSNG and required further treatment was told by staff that they might try decentralized treatment with antibiotics at Tohoue clinic during the month that CSNG was closed . The patient did so with a positive result . CSNG’s participation in the project has thus far been a peaceful coexistence with the decentralized BU pilot . Allada and CSNG have maintained a strong professional relationship , and in the future CSNG will presumably benefit from a reduced number of non-BU chronic ulcers to better focus its considerable expertise on the treatment of advanced Buruli cases . If the decentralized pilot goes to scale , and each clinic in the district is able to treat the same number of cases as Tohoue , the burden on CSNG will be reduced significantly . CSNG’s proactive outreach system remains in place in Ouinhi , and the two systems work in parallel providing greater and more effective coverage for BU case detection . The clinic at Tohoue has assumed the care of early BU cases , and with the expertise and material support of the Allada reference center , has also accepted care of chronic ulcers within their capacity to treat . The impact evaluation found that this shift in the focus of wound care has resulted in an increase in social capital for the clinic , but also an increase in duties and responsibilities of staff without commensurate increases in salary . The nurse who directs the Tohoue clinic ( Fig 6 ) was already very popular , and participation in the pilot project has increased his reputation in the community in two ways . As the presenter in approximately half of all outreach programs , his visibility and reputation for wound care expertise has grown and been reinforced . His collaboration with the Allada CDTUB and increased ability to triage chronic ulcer cases when necessary has also signaled to the community that he has access to a broader health care network and resources . For example , the nurse agreed to treat a nine-year-old boy who was bitten by a snake and who had been told by doctors at two hospitals that his leg would have to be amputated . The family refused to accept amputation and upon hearing about free care at Tohoue consulted the nurse . The nurse treated the wound , the boy kept his leg , and the nurse was able to arrange for the boy to receive physical therapy at Allada . At a time when many local clinics are chronically under-resourced , having access to adequate supplies for ulcer management and being able to personally refer cases of wounds requiring advanced care is a powerful form of capital when serving a population that deals with uncertainty at nearly all levels of health-seeking . The success of the pilot project in treating all cases of Category I and II BU , without incurring the costs of centralized care to households , provides a powerful demonstration effect for the larger community of the viability of decentralized care , the treatment protocol’s effectiveness , and Tohoue staff’s clinical competence . The evaluation found evidence that greater respect for Tohoue clinic ( as a source of reliable , professional , and empathetic care ) has had an impact beyond wound management . The reputation of the clinic is now being leveraged for other community-based health care activities . Given these advantages , the nurse and his clinic attendants remain supportive of the intervention , although they acknowledge that it has increased their workload in an already understaffed clinic . Moreover , decentralized care , its supervision , and the treatment of other chronic wounds incurred additional costs as did patient support in the form of feeding . In order to sustain clinic success these costs would need to be covered in the future . More pressing was another point of concern . Raising community consciousness about the importance of wound care has the potential of indirectly encouraging people to visit the clinic with wounds that might be managed at home . To reduce the burden on clinics like Tohoue , and the health care system in general , practical community-based wound care education will be necessary . Wound care education will need to focus on common wounds and skin diseases as well as follow-up care and scar management for chronic ulcers . Village volunteer networks serve as an invaluable if under-acknowledged resource for the health system , providing a level of surveillance and contact that neither the national health system nor the detection team from a reference hospital can match . As a result of the intervention , village volunteers saw several significant modifications to their roles: they shared in the work of detection with other members of the newly-formed community support groups; they accompanied suspected early BU cases to a local clinic; and once a patient was treated at a clinic , they provided ongoing psychosocial support . The impact evaluation found that psychosocial support provided by support group members contributed to the 100% adherence rate of decentralized BU patients . The impact evaluation also found that volunteers now interacted in positive ways with healers and religious leaders participating in support groups and their collaboration was seen by the community in a positive light . The intervention provided an opportunity for traditional healers and religious leaders to participate in support groups and be advocates for decentralized BU treatment . Several local healers and religious leaders became members of support groups and 16 healers actively participated in outreach programs . At the beginning of the project some concern was raised about allowing healers to participate in support groups based on negative experiences in the past . A few years before the pilot intervention , two healers who attended an NTD training used course attendance as a means of recruiting and keeping patients instead of referring them . The impact evaluation found no case where a healer used membership in a support group to claim expertise in curing chronic ulcers or as a means of attracting new clients . On the contrary , their attendance at outreach programs demonstrated to the public that they advocated promptly taking suspected cases of BU to local clinics . Other support group members spoke of the cultural sensitivity involved in negotiating the transfer of patients from traditional to biomedical care . A 29-year-old community support group member noted: The social science team observed that as decentralized BU care removed many of the previous obstacles to seeking biomedical treatment for chronic wounds , community members were far more willing to consider this care option . Healers in Ouinhi who joined support groups recognized this as well . They found that participation in support groups and outreach programs added to their own prestige instead of diminishing it . Participation in a successful campaign reinforced their standing and trustworthiness in the public eye . During interviews , patients identified a number of factors that made them more receptive to seeking decentralized care for BU than undergoing surgery , even when surgical care is free and offered by a hospital with an excellent reputation . The fear of surgery , grafting , and amputation , and the strong general association of CSNG with these practices , has long been a major factor in patient delay in the region [12 , 25 , 26] . The vivid image of amputation , kept fresh in the popular imagination by living examples , inspired particular terror especially among children . Grafting is also seen as a horrific practice because it involves the cutting of healthy flesh , a logic that does not translate well into local understandings of treatment and is generally regarded as perverse [12 , 27 , 28] . Community members often joke that when one goes to CSNG they go in with one wound and end up with two ( due to grafting ) ; the center is referred to in the communities by the name “e kan bo tren” , “they cut and attach” . Another common way of referring to the hospital is also telling: it is referred to as a prison , an image associated with the indeterminacy of one’s duration of stay . Patients treated at Tohoue spoke of being very satisfied with decentralized care for three major reasons . First , surgery was avoided and this reduced their fear of being treated . Second , they had a clearer idea of how long treatment would last and they were better apprised of how their treatment was progressing . Indeterminacy was identified as a significant concern for households of those being treated for BU and linked to social displacement . Hospitalization imposes a significant economic challenge on households living on the margin through indirect and opportunity costs , even when most direct costs of hospital care are covered [29–31] . Patient and guardian displacement has serious repercussions for the household production of health [32] and requires securing replacement labor for agricultural and domestic tasks . Displacement is also psychologically wrenching , and a source of tremendous anxiety for patients and their care providers [7] . When the duration of displacement is uncertain , long-term planning for patients , guardians , and households is all but impossible . Interviews with patients revealed that a major reason for the popularity of decentralized care was that it offers a more clearly delineated source of treatment duration , enabling household activity and resource planning . The following case vignette aptly illustrates why decentralized care appealed to a household that recognized that a family member had a chronic wound that required treatment , but were reluctant to seek care at CSNG hospital . The story involves a 38-year-old mother of three who chose to try decentralized care after seeking general wound care for her daughter at a clinic and hospital . The informant , like several others interviewed , also commented on her interactions with the nurse in Tohoue , stating that he addressed her concerns and treated her with respect ( “At the health center in Tohoue , the patient is treated with respect and love; the head nurse laughs with everyone” ) ( Fig 3B ) . The impact evaluation revealed that the nurse’s close connection to the community and empathy for patients were major factors contributing to the popularity of decentralized care .
We have provided quantitative and qualitative evidence of Category I and early stage Category II BU cases being treated as a result of the combination of outreach education and the provision of decentralized care . Few cases of Category I BU are treated at CSNG hospital ( 2% compared to 12% at national level ) and no cases of BU were treated at Tohoue clinic prior to the pilot project . Following outreach programs , 53 suspected BU cases were screened at the clinic and 77% of all confirmed cases were Category I or early stage Category II BU . This finding demonstrates the importance of community-based interventions and decentralized care in the control of BU [8 , 14] , and is all the more compelling because of the strength and diligence of CSNG’s surveillance program for case detection for many years prior to the intervention . We found strong community support for the outreach program , both for its innovative educational approach and for the content of its messages . In particular , community members found the images that accompanied the text and oral presentation served as a useful mnemonic for accurate recall . Experienced volunteers and health staff who had been trained in earlier forms of BU outreach education expressed a preference for the new pedagogy as more dynamic and accessible . Self-referral rates after outreach were high . The provision of free decentralized care eliminated or considerably reduced the primary constraints to seeking centralized treatment noted by patients who had delayed seeking care for BU . These constraints included practical and economic difficulties in sustaining prolonged displacement , the disruption of daily activities and fear of surgery and possible amputation . Community members were highly receptive to the idea of decentralized care , as evidenced by the number of cases arriving at the clinics after outreach programs . Patients who were confirmed as having Category I and II BU all elected to receive decentralized care , and all of them successfully completed the full course of antibiotic treatment . One of the most significant impacts of the intervention was that women no longer needed to consult husbands ( or other men in positions of authority ) about attending clinics for BU treatment for themselves or their children . In Ouinhi , it is normative for women to consult men before traveling to a clinic . If men are not available , this can result in significant treatment delay and , in the case of a disease like BU requiring weeks of outpatient treatment , treatment non-adherence . Notably if a woman is required to travel to a clinic daily , this may place her in a position of social risk to rumor about her moral identity . As a result of the outreach education , BU became the exception to this general rule . Community members came to understand the necessity for continuous treatment at the clinic . Women attending clinics did not report feeling vulnerable to social critique if they went to the clinic in the absence of their husbands , nor subject to social stigma for their movements outside their households or villages . We observed this change occur in real time in Ouinhi . Nearly half ( 45% ) of the chronic ulcers treated at Tohoue were referred to the clinic by members of community support groups . Support groups also proved effective in approaching family members to negotiate the transfer of patients from traditional medicine to biomedical care , and served a valuable role in following up with cases that dropped out of therapy or were non-adherent . All such cases completed treatment once contacted by support groups . Support group members received praise for their role in outreach activities by government health staff during monthly meetings held at local clinics . Health staff interviewed during the impact evaluation appreciated the support group model and hoped to leverage BU groups to assist them in implementing health programs beyond Buruli ulcer . When designing the pilot intervention , the team was attentive to the many tasks and responsibilities of community volunteers . In another district ( Zé ) of Benin , social science team members found that when linear programs like BU establish separate cadres of volunteers , jealousy over resources and confusion over roles occurs between volunteers associated with different groups . During the pilot project , existing volunteers were placed within BU support groups comprised of many different kinds of stakeholders . Support group members saw their role as assisting health volunteers perform their many tasks , and tensions among members was not reported . Volunteers very much appreciated this assistance . The treatment of all chronic ulcers free of charge reduced the chance of clinic staff being accused of favoritism by a population that little understands the reasoning behind vertical programs , especially programs that do not involve contagious diseases . Assurance that wound treatment costs would be covered regardless of diagnosis was a major factor in convincing people who were hesitant to consult the clinic before to do so now . The reputation of the Tohoue clinic in the community was positive to begin with , but wound care was not seen as a service routinely provided given that chronic wounds were generally referred . Introducing chronic wound care increased the clinic’s reputation and the staff were soon recognized as having expertise . Patients interviewed about their treatment at the clinic were very satisfied with the care they received and have become the best advocates of decentralization care being piloted . Some have volunteered to present testimonials of their care at outreach meetings . Practical training in wound care was well received by clinic staff . Monitoring by staff from Allada found that training resulted in greater self-confidence to treat , sound clinical practice , and appropriate referrals to hospital in keeping with established treatment guidelines . Ongoing feedback about referrals was much appreciated by clinic staff and constitutes a form of continuing education that should increase efficiency and reduce costs for the health system [33] . For more than a decade it was not possible to set up decentralized BU care in the Zou department . The pilot intervention demonstrated that this is possible when introduced as a win-win situation for the CSNG hospital and local clinics . The hospital offering centralized care is happy to have Category I BU cases and non- BU chronic ulcers treated at local clinics , freeing them to attend to and use their resources for more serious cases . The relationship between the CSNG hospital and local clinics participating in decentralized care is still fragile , however , and cannot yet be described as collaborative . There are four challenges that will need to be faced if decentralized treatment for BU is to go to scale in the Zou department and be sustainable . First , it will be important to mainstream the programs such that wound care becomes part of the routine scope of work for the clinic nurse . Next , wound care outreach and clinical care will need to be coordinated , and the program locally supervised . The experience gained by the national Buruli ulcer program through the implementation of this pilot program must be capitalized upon , so that this program can serve as the technical and administrative foundation for an integrated wound management program at the regional and health district level . A second challenge is the attrition of trained staff due to re-assignment . New health staff will continually need to be trained in wound care . It is worth looking into whether this can be done through short workshops followed by field apprenticeships with experienced health staff who have demonstrated good wound care skills . A third challenge will be keeping BU support groups , health volunteers and clinic staff motivated . Resources are necessary for members of support groups to accompany suspected cases of BU to the clinic , as some community members feel reluctant to visit clinics without a person familiar with the clinic to help support them during an initial visit . Volunteers who accompany suspected patients for screening require travel funds . Motivation for support group members will also need to be provided if they are charged with participating in an integrated NTD and wound care program . The importance of face-to-face meetings for sustaining collaboration has been noted elsewhere in Africa [34] . The motivation of clinic staff also must be taken into account . If asked to increase their workload to include wound care , they need to be provided with the resources to do so , and receive some form of incentive or recognition [34] . Research is currently under way to determine what kinds of motivations are effective and feasible for volunteers and clinic staff . A fourth challenge is the need for wound care outreach education as a complement to the BU outreach programs currently being conducted . As pointed out by clinic staff , education about wound care and skin disease management is needed so clinics are not swamped with cases that may be managed at home , or cases managed in the clinic that require follow-up care at home associated with wound hygiene and scar management . The intervention of the project had a very positive impact on Tohoue clinic attendance , which has notably increased since the outreach program and introduction of decentralized wound management . According to the health workers , the demand for medical care had significantly increased . Three fundamental factors have affected the attendance of the health center: the effect of the awareness-raising sessions , proximity of care , and free medical care for all chronic wounds . The awareness-raising sessions allowed people to have information about the disease ( its causes , manifestations and treatment ) , but also to become aware of the sequelae and social consequences that it could generate . As a result , the population was notably more prompt to resort to the center for any BU-like sign or symptom . The proximity of care was also described as one of the motivating factors in the search for medical treatment in the population , since patients no longer need to travel more than thirty kilometers for medical care , and households no longer need to worry about providing caregivers for patients in hospital . The free medical treatment was also one of the main reasons why they systematically go to the health center in case of problem . As the clinic’s prestige has risen , a concomitant decrease in the use of traditional healers has been observed in the community . Staff from three clinics were trained in BU and chronic wound care in this pilot study . However , only one clinic was fully functional during the entire intervention period . Staff from the other clinics were assigned elsewhere during the study . When new staff were then sent to short trainings in Lalo and Allada they were not as motivated as staff initially trained in longer , more hands-on and comprehensive courses . These staff preferred to refer cases to Tohoue clinic . Staff transfer limited our ability to learn from a larger sample of clinics . Another limitation was the inability of CSNG to offer technical supervision of wound care during the intervention . Lack of staff prevented the local hospital from offering supervision , and this had to be offered by the staff of CDTUB Allada . To ensure sustainability , if the intervention goes to scale , health district authorities will need to support monitoring activities locally . Four lessons learned from this successful community outreach and pilot decentralization care program for BU may be highlighted as having relevance for other health interventions . First , the dramatic increase in BU case detection in a region already having proactive case detection activities associated with free centralized care illustrates the importance of more accessible care that does not engender indirect , social and opportunity costs associated with displacement . Secondly , positive reception of the program reveals the importance of formative , action-oriented research in guiding program design . Thirdly , the program’s success suggests significant contributions of culturally sensitive outreach education that is responsive to questions , and the role of community volunteer groups in detection , negotiating participation , and providing support to patients and households . The pilot project also demonstrates the added value of integrated wound management for the control of neglected tropical skin diseases [35] . The importance of integrated prevention and care models has long been recognized as integral to strengthening health systems and improving quality and sustainability in health care [35–38] . This program not only produced improved outcomes for Benin’s NTD program , but also addressed the local need for community wound care as basic to primary care . It also demonstrated that community-based programs which bring care closer to the people increase the motivation of community volunteers and health staff serving in peripheral health centers [39] . The reputation and status of both is enhanced . Based on the success of this project a larger community-based wound care pilot project is now under way in the region . This new project will explore in greater detail the costs of bringing integrated neglected skin diseases/ chronic wound care provision to scale along with community outreach programs on home-based wound care . As decentralized BU treatment adopts oral therapy ( with rifampicin and clarithromycin ) for the treatment of Category I cases , appropriate home based wound care management will become all the more important . | The management of Buruli ulcer ( BU ) is complex , resulting in high costs to families and health systems . Early detection and treatment heals lesions without functional limitations . Decentralization of the management of this disease into the peripheral health system remains a challenge for national control programs . We report here on an innovative pilot intervention of decentralization of the management of BU in one of the most BU-endemic districts in Benin . The intervention was preceded by a culturally sensitive outreach campaign , which explained the disease’s symptoms and treatment options , and increased self-referral . It also included the treatment of all chronic ulcers free of charge . While serious cases of BU were still referred to the reference hospital for treatment , study results showed that 71% of BU cases could be treated in decentralized care; of these , 93% were successfully treated without functional limitations with antibiotics alone . The decentralized treatment option brought in new cases not previously treated by a proactive centralized BU program , and maintained total patient adherence to treatment protocols , in part through the support of community volunteer groups . The model developed in this pilot study may serve as the foundation and proof of concept for a larger community-based decentralized wound care agenda . | [
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"a... | 2018 | Implementation of a decentralized community-based treatment program to improve the management of Buruli ulcer in the Ouinhi district of Benin, West Africa |
Visceral Leishmaniasis ( VL; also known as Kala-azar ) is an ultimately fatal disease endemic in Bihar . A 2007 observational cohort study in Bihar of 251 patients with VL treated with 20 mg/Kg intravenous liposomal amphotericin B ( Ambisome ) demonstrated a 98% cure rate at 6-months . Between July 2007 and August 2012 , Médecins Sans Frontières ( MSF ) and the Rajendra Memorial Research Institute ( RMRI ) implemented a VL treatment project in Bihar , India—an area highly endemic for Leishmania donovani—using this regimen as first-line treatment . Intravenous Ambisome 20 mg/kg was administered in four doses of 5 mg/kg over 4–10 days , depending on the severity of disease . Initial clinical cure at discharge was defined as improved symptoms , cessation of fever , and recession of spleen enlargement . This observational retrospective cohort study describes 8749 patients with laboratory-confirmed primary VL treated over a 5-year period: 1396 at primary healthcare centers , 7189 at hospital , and 164 at treatment camps . Initial clinical cure was achieved in 99 . 3% of patients ( 8692/8749 ) ; 0 . 3% of patients ( 26/8749 ) defaulted from treatment and 0 . 4% ( 31/8749 ) died . Overall , 1 . 8% of patients ( 161/8749 ) were co-infected with HIV and 0 . 6% ( 51/8749 ) with tuberculosis . Treatment was discontinued because of severe allergic reactions in 0 . 1% of patients ( 7/8749 ) . Overall , 27 patients ( 0 . 3% ) were readmitted with post Kala-azar dermal leishmaniasis ( PKDL ) . Risk factors for late presentation included female sex , age >15 years and being from a scheduled caste . In 2012 , a long-term efficacy survey in the same area of Bihar determined relapse rates of VL after 5 years' intervention with Ambisome . Of 984 immunocompetent patients discharged between September 2010 and December 2011 , 827 ( 84 . 0% ) were traced in order to determine their long-term outcomes . Of these , 20 patients ( 2 . 4% ) had relapsed or received further treatment for VL . Of those completing 6 , 12 , and 15 month follow-up , 0 . 3% ( 2/767 ) , 3 . 7% ( 14/383 ) , and 2 . 4% ( 4/164 ) , respectively , had relapsed . The mean ±SD time-to-relapse was 9 . 6±3 . 0 months . This is the largest cohort of VL patients treated with 20 mg/kg Ambisome worldwide . The drug has high initial and long-term efficacy , and a low rate of adverse reactions when administered under field conditions in Bihar , India . Although challenging , its use as first line treatment in rural settings in Bihar is safe and feasible .
Visceral leishmaniasis ( VL ) , also known as Kala-azar , is a protozoan parasitic disease transmitted by phlebotomine sandflies . It is estimated that in 2004 a total of 1 , 071 , 743 disability-adjusted life years were lost to VL in South East Asia alone [1]; if left untreated the disease is fatal . India contributes the highest number of VL cases worldwide and in 2011 reported 33 , 187 cases , of which 76% originated in Bihar state [2] . , Despite a fall in reported cases in 2012 in India , there is evidence of substantial under-reporting of VL [3] , [4] and the estimated annual incidence lies between 146 , 700–282 , 800 cases [5] . In 2005 , India , Nepal , and Bangladesh signed a tripartite memorandum of understanding committing to the elimination of VL by 2015 . In 2007 , Médecins Sans Frontières ( MSF ) , in collaboration with the Rajendra Memorial Research Institute of Medical Science ( RMRI; Patna , Bihar , India ) , and the National Vector Borne Disease Control Programme of India , carried out an observational cohort study in Vaishali district , Bihar of 251 VL patients treated using 20 mg/kg liposomal amphotericin B ( Ambisome; Gilead Pharmaceuticals , Foster City , CA , USA ) as first-line treatment . All patients were admitted to the district hospital for the duration of treatment , and given four doses of Ambisome 5 mg/kg over a 10-day period . The intent-to-treat analysis yielded a treatment effectiveness rate of 98 . 8% at 6 months , with no relapses and an excellent safety profile [6] . In coordination with the RMRI , MSF shortly thereafter signed an agreement with the State Health Society , Bihar to reinforce the existing programme by identifying VL patients in Vaishali district and treating with Ambisome 20 mg/kg . Ambisome is a brand name for Liposomal Amphotericin B . There are a number of preparations of Liposomal Amphotericin B available on the market; however due to the lack of standard and widely applicable regulations or guidance for liposomal technology , it is important that this specific preparation be named . At time of publication , none of the rival preparations have undergone peer reviewed non-inferiority studies against Ambisome nor received stringent regulatory approval for use in VL . It is for this reason that MSF and the WHO currently only use Ambisome rather than other preparations . However it is urgent that clear regulatory guidelines for endemic countries be established by a normative setting organisation like the WHO and other existing formulations be formally evaluated [7] . This observational retrospective cohort study describes the field outcomes and experiences of the programme over the subsequent 5 years , discussing the challenges of implementing Ambisome treatment at the field level , and describes the long-term outcomes of treatment after 5 years of routine operational use .
All patients with a history consistent with VL ( fever of >2 weeks duration and splenomegaly ) were confirmed using rK39 rapid diagnostic tests ( DiaMed-IT LEISH; DiaMed AG , Cressier , Switzerland ) . Patients presenting with relapse , or in whom there was continued suspicion of VL despite negative diagnostic tests , were referred to a tertiary center ( RMRI ) for parasitological confirmation through splenic or bone marrow aspiration . The RMRI is a tertiary research institution that specializes in all aspects of VL research and treatment . General demographic data were recorded for all patients diagnosed with VL , in addition to clinical history , Hb level , height , weight and malaria rapid diagnostic test result . Also recorded was ‘caste’ , a form of social stratification used in India , and the categories used in the study were: scheduled caste , other backward class , scheduled tribe , and general category . Other backward class is a collective term used by the government of India for castes that are educationally and socially disadvantaged . Scheduled caste and scheduled tribe are terms used for two groups of historically disadvantaged people recognized in the Constitution of India . These three groups combined account for approximately 60% of India's population . General category comprises those who do not fit within the other categories and are not considered to be disadvantaged . Initially only inpatients deemed to be at high risk of HIV ( e . g . those experiencing a relapse of VL or with a history suggestive of higher risk , such as migrant workers ) were offered an HIV test , however this policy was changed in March 2011 so all patients treated at the district hospital level aged >14 years were offered testing . All women ≥14 were offered a pregnancy test . Patients received four doses of 5 mg/kg Ambisome over 4–10 days depending on the clinical severity of their illness . Initially all patients were treated on days 0 , 1 , 4 , and 9 . However , once the safety of the treatment was established , and because of increasing patient numbers and the hospital's limited capacity , the duration of treatment for all clinically stable inpatients was reduced to 4 consecutive days . The 10-day regimen was maintained for severely ill inpatients and for ambulatory patients treated at the PHCs . Initial cure was defined as improvement of symptoms , cessation of fever , and reduction of spleen size at time of discharge . Considering the risks of splenic puncture and in light of a previous study showing >98% cure rate at 6 months using the same regimen [6] , test-of-cure was planned only on those patients with suspicion of treatment failure , of whom there were none . Patients received health education regarding VL , and advice given to return or be actively contacted at 3 , 6 , and 12 months for follow-up . Additionally , all patients received health education regarding post Kala-azar dermal leishmaniasis ( PKDL ) and the possibility of relapse of VL , and were advised to return to the district hospital if either situation occurred . Towards the end of the 5-year period of analysis , an active follow-up survey was conducted to determine the long-term relapse rates for a sub-cohort of VL patients . All patients not known to be HIV-positive residing within 8 of the 16 administrative blocks constituting Vaishali district , and who had completed VL treatment between two reference dates ( September 2010 to December 2011 ) spanning 18 months prior to the survey date ( March 2012 ) were traced . Any history of mortality , relapse , or retreatment was recorded . The eight administrative blocks , with an average of 215 , 000 residents per block , were selected for ease of access and highest density of patients treated within the programme . All data were entered into a standard Microsoft Excel database; double data-entry was not done . Regular database cleaning comprised checks for inconsistencies with reference to source documents where necessary . An epidemiologist ensured the database was well maintained and regularly audited the quality of data transfer . Nutritional status ( Body Mass Index ) was assessed using weight and height data , whilst World Health Organization Anthro and Anthro Plus software ( Geneva , Switzerland ) was used to calculate a weight-for-height Z-score for children aged <5 years and a BMI-for-age Z-score for those aged ≥5–19 years . A retrospective analysis of all routinely collected program data was conducted using SPSS version 19 statistical software ( IBM , Chicago , IL , USA ) . A multivariate logistic regression model was also developed to determine risk factors significantly ( p<0 . 05 ) associated with being a ‘late presenter’ on univariate analysis ( i . e . >4 weeks of illness prior to treatment ) . This analysis met the Médecins Sans Frontières Institutional Ethics Review Committee criteria for a study involving the analysis of routinely collected program data . Although a new treatment in the Indian setting , the programme utilised a recognised treatment for VL and was run in coordination with the State Health Society through a memorandum of understanding , which is the usual procedure for NGOs operating in this context . All electronic data were analysed anonymously .
Of the 8749 patients , 42 . 9% of patients were female , a proportion substantially lower than the 47 . 12% of females in the background population sex distribution [10] . The mean ±SD age was 22 . 7±17 . 1 years ( range 0 . 5–90 ) ; 44 . 5% of patients were aged <15 years , of whom 6 . 9% were aged <5 years . As the age of patients increased , the proportion of males increased ( Figure 2 ) . The odds ratio ( OR ) of being male and enrolled into the program at age groups ≥15–34 , ≥35–54 , and ≥55 years versus baseline ( <15 years ) was 1 . 6 ( 95% CI 1 . 4–1 . 7 ) , 2 . 0 ( 95% CI 1 . 8–2 . 2 ) , and 2 . 5 ( 95% CI 2 . 1–3 . 1 ) , respectively ( p<0 . 01 ) . Overall , age group accounted for 86% of the variability in sex ratio . A total of 7338/8749 patients ( 83 . 8% ) were from scheduled caste/tribe or other backward classes ( Table 1 ) . Of the cohort , 95 . 6% had primary VL and 4 . 4% gave a history of one or more previous episodes of VL . Of the latter , 4% presented with a history of a single episode for which they had received a course of treatment that had resulted in apparent recovery , whilst the remainder reported multiple episodes . Patients describing previous episodes of VL reported being treated with: amphotericin B deoxycholate ( 1 . 2% , n = 104 ) , sodium stibogluconate ( SSG; 1 . 5% , n = 135 ) or miltefosine ( 1 . 5% , n = 128 ) for their most recent episode of VL . A total of 1813 patients with VL were registered at the PHC , of whom 416 ( 22 . 9% ) appeared to meet the referral criteria and were referred to the district hospital for treatment . Therefore , 16 . 0% ( 1397/8749 ) of patients were treated at rural primary health centers , 78 . 6% ( 6874/8749 ) were treated at the district hospital , and 3 . 6% ( 314/8749 ) were treated in the tertiary referral center ( RMRI ) . The remaining 1 . 9% ( 164/8749 ) of patients were treated in the community by MSF during occasional mobile treatment campaigns during the 5-year period . Overall , 73 . 7% of patients originated from within Vaishali district; however , this proportion decreased from 81 . 3% in 2008 to 65 . 7% in 2011 , reflecting an increasing number seeking care in the programme from outside the district . The proportion of patients residing in one of the blocks containing a MSF supported PHC whose first presentation to the programme was at the level of the PHC ( as opposed to the district hospital ) remained similar at 34 . 9% , 40 . 7% , 33 . 5% and 32 . 2% for the whole years 2008–2011 respectively . The Ambisome 20 mg/kg total dose was received by 79 . 2% ( 6928/8749 ) of patients over 7–10 days and 20 . 2% ( 1767/8749 ) of patients over 4 consecutive days . The clinical characteristics of all the patients are shown in Table 2 . Of note , the mean Hb level at admission was 8 . 4 g/dL , with 46 . 1% of patients ( 4034/8749 ) presenting with a Hb level of <8 g/dL . The mean spleen size ( palpable below the costal margin ) at admission was 6 . 1 cm; 34 . 5% of the cohort presented with a spleen size >6 cm . Both these indicators directly correlated with duration of illness prior to treatment ( Pearsons Correlation r = 0 . 215 and r = −0 . 108 for Hb and Spleen size respectively , p<0 . 001 ) . Compared with early presenters , late presenters had slightly lower mean Hb levels ( 8 . 1 vs 8 . 6 g/dL ) and greater splenomegaly ( 6 . 9 vs 5 . 5 cm ) . Although no association between different age groups and spleen size at the time of admission was seen , there was a direct correlation between increasing age and increasing Hb ( Pearsons Correlation r = 0 . 232 , p≤0 . 001 ) . Of the 3749 female patients within the cohort , 1810 were aged <14 year and were not offered pregnancy tests . Women with a documented history of hysterectomy or sterilization ( a common and encouraged form of long-term contraception in India ) were also not offered tests . Thus of the 1939 females aged ≥14 years , 1783 ( 92% ) had tests performed of which 49 ( 2 . 75% ) were positive at the time of treatment . This represented 1 . 3% of all women within the cohort ( n = 3749 ) . Of the pregnant patients , the mean ±SD age was 25 . 4±5 . 6 years , and the mean ±SD Hb level at admission was 7 . 6±1 . 8 g/dL . The mean ±SD duration of illness of pregnant patients was 6 . 6±5 . 6 weeks prior to treatment in the program . Of the VL patients treated , 161 ( 1 . 8% ) were HIV-positive ( Table 3 ) . Of these , 26 had been previously diagnosed with HIV and already on antiretroviral therapy . The odds of being HIV-positive and having previously experienced a single or multiple episodes of VL at time of admission was 13 . 6-times higher than in the overall cohort ( 95% CI 9 . 7–19 . 0; p<0 . 001 ) . Of the 7254 patients ( including HIV positive ) , whose anthropometric data was recorded at baseline 40 . 8% ( n = 2962 ) were malnourished , with 18 . 0% ( n = 1306 ) having severe acute malnutrition and 22 . 8% ( n = 1656 ) having moderate acute malnutrition . There was a higher prevalence of malnutrition in the younger age groups , with the odds ( CI ) of being malnourished amongst the <5 and 5 - ≤19 years age groups 1 . 7 ( 1 . 4–2 . 2 ) and 2 . 2 ( 2 . 0–2 . 4 ) times higher respectively compared to the >19 years age group ( p<0 . 001 ) . There was no significant difference between the global nutritional status of patients known to be HIV positive and the remainder of the cohort ( 43 . 4% vs 40 . 8% globally malnourished respectively , RR ( 95%CI ) = 1 . 1 ( 0 . 9–1 . 3 ) , p = 0 . 506 ) , nor was there a significant difference in the prevalence of severe acute malnutrition ( SAM ) between patients known to be HIV positive and the remainder of the cohort – 22 . 6% vs 17 . 9% respectively , RR ( 95%CI ) = 1 . 3 ( 0 . 95–1 . 7 ) , p = 0 . 124 . The rate of initial cure of VL treatment , defined as cessation of fever , improvement of symptoms and recession of spleen enlargement at the time of discharge , was achieved in 99 . 3% ( 8692/8749 ) of patients . A total of 26 ( 0 . 3% ) patients defaulted after receiving ≥1 dose of Ambisome , and 31 ( 0 . 4% ) died during treatment . The case fatality rate of HIV patients during treatment was 4/161 ( 2 . 5% ) , compared to 27/8588 ( 0 . 3% ) for patients not known to be HIV positive . The relative risk of mortality during treatment in patients with HIV was 7 . 9 ( 95% CI 2 . 8–22 . 3 ) times higher than that of patients not known to be HIV positive ( p<0 . 001 ) . Over half of all patients ( 58 . 1% , n = 5085 ) reported feeling unwell for <4 weeks prior to receiving treatment in the program , whereas 24 . 6% and 17 . 2% of patients were unwell for 4–8 and >8 weeks , respectively . The median duration of illness prior to admission was 4 weeks ( IQR 3–8 ) , whilst the mean duration was 6 . 4 weeks ( SD 6 . 1 ) . The odds of late presentation ( defined as presenting >4 weeks after developing symptoms ) were significantly higher in females ( OR 1 . 2; 95% CI 1 . 1–1 . 3; p = 0 . 001 ) , those from a scheduled caste ( OR 1 . 2; 95% CI 1 . 0–1 . 3; p = 0 . 03 ) , and age ≥15 years ( OR 1 . 4; 95% CI 1 . 3–1 . 6; p<0 . 001 ) ( Table 4 ) . Receiving treatment in the PHC setting ( OR 0 . 6; 95% CI 0 . 6–0 . 7; p<0 . 001 ) and having had a previous episode of VL ( OR 0 . 8; 95% CI 0 . 6–0 . 9; p = 0 . 013 ) appeared to have a negative association against late presentation . Patients being diagnosed at the PHC level reported a shorter duration of symptoms prior to receiving treatment ( 1 . 0 week less , CI 0 . 8–1 . 3 , p<0 . 001 ) than those who presented directly to the hospital for diagnosis and treatment . Neither residing within one of the blocks that MSF supports nor receiving care in a mobile treatment camp affected time of presentation . Of the total patients treated , 7 . 2% ( 628/8749 ) suffered adverse reactions during treatment with Ambisome; 0 . 1% ( 7/8749 ) patients stopped treatment because of severe allergic reactions . The most common recorded complaints were nausea/vomiting ( 3 . 1% ) , back pain ( 1 . 9% ) , urticaria ( 1 . 2% ) , and rigors ( 0 . 5% ) . Neither location nor duration of treatment were associated with significant differences in initial cure rate , default , or adverse events . Twenty-seven ( 0 . 3% ) VL patients returned passively to the program following treatment complaining of symptoms subsequently confirmed as PKDL . The mean ±SD lengths of time from completion of treatment to development of skin lesions ( as reported by the patients ) and completion of treatment to formal diagnosis of PKDL were 20 . 4±12 . 1 months ( range , 5 . 4–44 . 8 ) and 27 . 4±11 . 7 months ( range , 10 . 1–53 . 2 ) , respectively . Passive follow-up rates within the program were low , with 53 . 2% ( 4653/8749 ) , 38 . 1% ( 3334/8749 ) , and 1 . 5% ( 129/8749 ) of patients presenting at 3 , 6 , and 12-month follow-up , respectively . As previously described , an active follow-up survey was conducted in March 2012 of all patients who completed VL treatment between September 2010 and December 2011 , who were not known to be HIV-positive , and who resided in eight administrative blocks within Vaishali district . A total of 984 patients met the criteria and 84 . 0% ( n = 827 ) were successfully traced . The 984 patients represent 45 . 7% of all admissions into the program during this time period . Apart from patient origin , there were no significant differences in demographic and clinical characteristics between this group and the overall study cohort at the time of admission into the program . Table 5 details the outcomes of the active follow-up survey . Overall , 827 , 767 , 383 , and 164 patients completed 3 , 6 , 12 , and 15 months post-treatment , respectively ( NOTE: these numbers are progressive and inclusive , e . g . those patients completing 12-month follow-up who had not relapsed were included in the denominator of the 6-month follow-up group but not vice versa ) . The proportion ‘lost to follow-up’ remained consistent at 13 . 5–16 . 3% for all the time periods . Most ( 14/20 , 70% ) relapses occurred at 6–12 months following treatment , with a mean ±SD time to relapse of 9 . 6±3 . 0 months . Relapse rates were 0% , 0 . 3% , 3 . 2% , and 1 . 9% for patients completing 3 , 6 , 12 , and 15 months following treatment respectively . The cumulative probability of relapse following treatment is shown on the Kaplan–Meier survival curve in Figure 3 and was 0% , 1 . 1% , 2 . 3% , 3 . 3% and 4% for patients completing 3 , 6 , 12 , 15 and 18 months respectively .
This study cohort represents the largest number of VL patients treated with liposomal amphotericin B ( Ambisome ) to date worldwide . Although based in one district only , this program has treated an estimated 5 . 8% of all reported VL cases in India between 2008 and 2011 [2] . Age distributions of patients with VL in the subcontinent context have been described in other epidemiological descriptions in India [11] , [12] and Bangladesh [13] which also identified the lower proportion of reported female cases in comparison to the background populations; however , in this study the clear under-representation of older females being treated is of interest and raises the question of whether adult females are less likely to access treatment and have poorer outcomes in this setting . Indeed , this situation has been observed in the Bangladeshi setting where one population based survey among 2 , 348 people demonstrated a case-fatality rate of 19% among adult women , compared with 6–8% among other demographic groups [14] . However , although health-care facilities in many regions report more male than female cases , the sex ratio can be accurately ascertained only in community-based studies , as data from facilities reflect any disparities in access to health care [15] . Further qualitative research into this phenomenon in the Indian context would be invaluable . Only 15 . 5% of the cohort in this program described themselves as being from a forward caste . The remainder was from backward classes or scheduled tribes and castes , supporting the evidence that VL is a disease of the poor and most vulnerable [16] . In India caste can be seen as a proxy for socioeconomic status [17] and is an important determinant of social position; therefore , it affects numerous aspects of daily life [8] . Additionally , members of the same caste tend to live within specific areas , known as ‘tolas’ , within villages . Together with the poor quality of housing and level of poverty , the well known spatial clustering of VL transmission could contribute to this relationship between low caste and VL . Associations between low caste , reduced access to treatment and more clinically severe VL in Bihar have already been described elsewhere [18] , as have the associations between the damp floors , mud plastered walls [19] , poor quality thatched housing [20] and high household population density [21] typically seen in lower caste households . As such , in Bihar it is imperative that government schemes such as the Indira Awaas Yojana social welfare programme , designed to provide quality housing for the rural poor in India , be encouraged , implemented and availed . Children appeared to reach the point-of-treatment earlier than adults in this cohort , and although female sex was a marginal risk factor for late presentation , there was no evidence that in-program mortality was worse for females . A relatively large number of pregnant patients with VL ( n = 49 ) were treated with Ambisome and their outcomes were all good; it is unfortunate that the stage of pregnancy and long-term outcomes of mother and child were not routinely recorded . A large proportion of patients appeared to be malnourished on presentation to the program . Considering the high background prevalence of malnutrition in Bihar [22] , it is difficult to determine the relationship between malnutrition and symptomatic VL in this cohort , and to what degree patients were malnourished prior to being infected by L . donovani , as opposed to becoming malnourished as a consequence of VL . There is , however , evidence that malnutrition is associated with early visceralization in L . donovani infection and with disease severity [23]–[25] . Providing effective and sustained treatment for the nutritional component of VL proved challenging in this setting because of the short inpatient stays and lack of local nutrition therapies—it is likely to remain so as new shorter-course VL therapies are developed . Particularly alarming is the 18 . 3% prevalence of severe acute malnutrition among children aged <5 years with VL . These patients are at an increased risk of overall mortality with this degree of wasting [26] . It is well established that HIV-positive patients with VL have poorer outcomes [27] . A previous study conducted within the same center using the same treatment regimen showed increased relapse rates and , in particular , early mortality associated with HIV–VL co-infection [28] . As a result of these outcomes and the numbers of patients being newly-diagnosed with HIV as a result of their VL presentation , MSF started offering all patients voluntary counseling for HIV testing in 2011 . Prior to 2005 , the pentavalent antimonial SSG was the widely available first-line treatment for VL recommended by the National Programme in India for more than half a century . However , in addition to the established toxicity of SSG , there is increasing evidence of rising resistance [29] , and reports of treatment failure as high as 65% [30] . This has resulted in the gradual introduction of the synthetic phospholipid derivative hexadecylphospocholine , miltefosine ( MF ) as first-line treatment in VL . MF is a 28-day oral treatment that initially showed promising efficacy and tolerability [31]–[33] . However , its use is restricted in pregnant and lactating women due to its teratogenicity , requiring a minimum of 3 months contraceptive cover during and following the completion of treatment [34]; a recent population pharmacokinetic modeling study of MF has suggested that contraceptive cover should be extended to 5 months [35] . More recent evidence from India has suggested relapse rates of 6 . 8% at 6- months following treatment with MF [36] , which is double that reported in the original study [37] . A separate Indian study demonstrated relapse rates of 7 . 6% at 12-months following treatment with MF [38] . In the Nepalese context , the relapse rates following MF treatment appear substantially worse with reports of 10 . 8% and 20 . 0% at 6 and 12 months , respectively [39] . Measurement of in-vitro susceptibility to MF in patients with relapsed VL has shown lower susceptibility than that found in pre-treatment isolates [40] . Intravenous amphotericin B deoxycholate remains the second-line treatment recommended for VL by the National Programme in India . Although effective , the treatment regimen requires prolonged hospital stays of up to 30 days and has a substantial toxicity profile [15] . Liposomal preparations of amphotericin B allow higher doses to be safely given in a shorter time frame . Over the past decade , numerous studies have been conducted in India examining the effectiveness of liposomal formulations of amphotericin B as monotherapy [7] and in combination [41] . These have shown efficacy ranges >90% for liposomal amphotericin B doses ranging from 5–20 mg/kg . A key phase III study by Sundar et al . demonstrated the safety and >95% efficacy of a single-dose regimen of liposomal amphotericin B 10 mg/kg at 6 months [42] . The study was pivotal in the adoption of this regimen as first-line treatment for VL in South East Asia by the World Health Organization Expert Committee [15] . However , common limitations of these studies include the small cohort sizes and the lack of validation of the results under field conditions . There are several concerns regarding the introduction of liposomal amphotericin B into national programs , particularly in India . Firstly , the cost of the ‘gold standard’ preparation ( Ambisome ) is significantly higher than that of other treatment options , despite the agreed company ‘access price’ of USD 18 per 50 mg vial for use in developing countries [29] . However , a cost-effectiveness analysis comparing 10 different treatment modalities showed that if this price was reduced to below USD 9 . 80 per vial , single dose 10 mg/kg Ambisome would become the most cost-effective treatment [43] . A second concern is the capacity of the healthcare systems of VL endemic countries to maintain the necessary cold chain if Ambisome is to be used in rural areas . Thirdly , because Ambisome is given as an intravenous infusion , it could be considered technically challenging to correctly prepare and administer in those areas where there are limited numbers of qualified nurses and doctors . The outcomes of this MSF-supported programme provides strong evidence that many of these challenges can be overcome . The successful use of Ambisome to treat 1397 patients in rural PHCs with existing government staff suggests that , with appropriate support and training , it is possible to provide high-quality care for VL patients in such rural settings . A functional cold chain ILR requiring a range of 2–8°C to store vaccines for the Expanded Programme of Immunization in India already exists in the majority of rural PHCs , and vaccination in even the most rural areas is already well established in India . The present program has shown that providing an additional ILR for the storage of Ambisome is a pragmatic solution to the cold chain issue , especially considering the limited number of districts in India where VL is endemic . However , careful monitoring and maintenance of the ILRs remains essential . Increased availability of electronic thermometers to improve the identification of deviations outside set temperature ranges is recommended , as is the inclusion by the manufacturer of a visual vial indicator that will make it easier to identify and discard vials that have been exposed to high temperatures . At the district hospital level ILRs remain an option , but as the required storage temperature of Ambisome ranges between freezing and 25°C , storage in air-conditioned rooms is also a possibility , provided 24-hour generator back-up is available . This program has also demonstrated that a lack of highly-skilled clinic staff is not a barrier to using ‘complex’ treatments such as Ambisome at the rural PHC level . After appropriate training , lesser-skilled health workers ( e . g . dressing nurses ) were able to independently prepare , administer , and monitor Ambisome treatment . As suggested by the exceptionally low default rate from ambulatory care , the delegation of responsibility and empowerment ( or task shifting ) for the management of VL patients to such individuals , following diagnosis by the PHC doctor , also meant that more thorough patient counseling and health education was possible at the point-of-care since the care provider had more opportunity to spend time with patients . This is important when considering the time constraints and heavy patient loads that are a daily reality for the more skilled health workers in the PHCs of India , which is reflected in the generally poor community perception of the quality of PHC care in India [8] . The low mortality rate at the PHC level also suggests that the health workers were able to identify and refer 22 . 9% of VL patients defined as higher-risk by the MSF protocol , who may have been better served by further assessment and treatment at higher centers of care . However , this conclusion would be better supported by an audit of the appropriateness of the referrals . The present study has also shown that patients accessing care at the PHC level present earlier than those seeking care at the hospital level . Ambulatory treatment at the community level has clear benefits from both societal and healthcare provider perspectives , and is a policy that should be encouraged . However , it is clear that without a change in the community perception of the PHC system in this context , which itself must be based on a good quality of care provision , the full potential of community/rural based management of VL will never be realised . In conclusion , although expensive , the 20 mg/kg Ambisome regimen is a safe , effective , and feasible treatment for VL patients in Bihar , India . With few severe adverse events , it was well accepted by both patients and medical staff within this MSF-supported program . The active follow-up survey performed after 4-years of routine use indicated that the VL relapse rate remains exceptionally low within 6 months of treatment; however , there is a substantial number of relapses at 6–12 months post-treatment . With a move towards a 10 mg/kg single-dose liposomal amphotericin B regimen and shorter-course combination therapies , and the target of disease elimination in mind , we suggest that 1-year follow-up monitoring be recommended for VL patients in these newer treatment modalities whose longer-term efficacy has yet to be established . | Visceral leishmaniasis ( VL ) , also known as Kala-azar , is a protozoan parasitic disease transmitted by phlebotomine sandflies . After malaria , VL accounts for the second-highest burden of parasitic diseases worldwide . India has half of all the VL patients worldwide , of which up to 90% are in Bihar state . Between 2007–2012 , Médecins Sans Frontières ( MSF ) together with the Rajendra Memorial Research Institute ( RMRI ) supported existing health structures in Vaishali district , Bihar , by treating 8749 VL patients with intravenous liposomal amphotericin B ( Ambisome ) 20 mg/kg . Initial cure rate was high , with low default and mortality rates . We describe the demographic and clinical characteristics of this large patient group , including risk factors for late presentation . Ambisome can be given in short courses and is safer , better tolerated , and more effective than existing VL treatments . The MSF-supported program treated nearly 1400 ambulatory patients in rural primary healthcare centers , using existing government facilities and non-incentivized staff , demonstrating that a resource-limited healthcare system in a rural setting can meet the cold chain and human resource standards required to administer Ambisome safely . We also describe a long-term follow-up survey showing a continuing low VL relapse rate after 5 years of routine use of Ambisome . More relapses occurred after 6-month follow-up; suggesting a 12-month follow-up in future VL studies may be more appropriate . | [
"Abstract",
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] | 2014 | Five-Year Field Results and Long-Term Effectiveness of 20 mg/kg Liposomal Amphotericin B (Ambisome) for Visceral Leishmaniasis in Bihar, India |
Simian Foamy Virus ( SFV ) can be transmitted from non-human primates ( NHP ) to humans . However , there are no documented cases of human to human transmission , and significant differences exist between infection in NHP and human hosts . The mechanism for these between-host differences is not completely understood . In this paper we develop a new Bayesian approach to the detection of APOBEC3-mediated hypermutation , and use it to compare SFV sequences from human and NHP hosts living in close proximity in Bangladesh . We find that human APOBEC3G can induce genetic changes that may prevent SFV replication in infected humans in vivo .
Simian foamy viruses ( SFV ) comprise a subfamily of retroviruses that naturally infect all primates examined with the notable exception of humans . In non-human primates ( NHP ) , they show strong evidence of co-evolution with their hosts [1] . Persistent infection with SFV is ubiquitous in populations of free-ranging NHP [2] , [3] and is not thought to be pathogenic in the natural host . However , recent work shows increased morbidity and mortality for macaques infected with SFV and SIV ( simian immunodeficiency virus ) compared to those infected with SIV alone [4] . SFV has been zoonotically transmitted to humans on more independent occasions than any other simian-borne retrovirus [5] , [6] . There are no documented cases of human to human SFV transmission , including between discordant couples [7] , [8] . The factors underlying the apparent lack of human-to-human transmission are not well understood . However , the apparent lack of viral replication in humans is probably an important factor [7] , [9] . In NHP , SFV is believed to be transmitted through saliva , primarily through biting . This conclusion is supported by studies that have shown high levels of viral RNA in the oral mucosa of NHP , indicative of replication at that site [10] , [11] . The large number of NHP infected with SFV and relatively frequent zoonotic transmission allow study of the roles that viral strain variation and host immune response may play in preventing SFV from becoming an endemic human virus . There have been no direct experimental infections of a susceptible host with SFV or any other foamy virus . However , blood transfusions from an SFV positive NHP to an SFV negative NHP have been reported [12] , [13] . From these studies , a model for the events that occur after SFV infection has been proposed . Briefly , initial infection is of PBMCs . Viral DNA integrations are found in these cells , but replication is not detectable . When a latently infected PBMC migrates to the oral mucosa , an unknown process occurs that leads to infection of superficial epithelial cells , in which the virus can replicate [10] , [11] . Infections are persistent , but the only cells that have been found to replicate virus are in the oral mucosa . However , almost all organs in an infected NHP contain latent proviruses at levels suggesting there are many other cell types other than PBMCs that can be latently infected . Host-viral interactions are better understood for SIV , an NHP-borne lentivirus , than for SFV . In particular the innate immune system is known to play an important role in limiting lentiviral inter-species transmission . Host factors such as SAMHD1 , tetherin , and APOBEC3 [14] are known to restrict lentiviruses , which in turn have evolved viral protein antagonists to counter these specific host factors . Cross-species transmission of lentiviruses can be limited by the specificity of these viral antagonists for the host species to which the virus has adapted [15] . The APOBEC3 family of proteins are cytidine deaminases that act on negative strand single-stranded DNA , which is created during reverse transcription . Deamination changes C to U , which then appears as G to A mutations on the positive strand [14] . The importance of APOBEC3G as a barrier to cross-species transmission of SIV has recently been highlighted by Etienne et al [16] , who provide evidence that the ability of SIVcpz Vif to adapt to restrict chimpanzee APOBEC3G was more important than its ability to counter SAMHD1 with another viral gene , vpx . Human APOBEC3 has also been shown to be a potent SFV restriction factor in tissue culture [17] . Some G to A mutations have also been observed in SFV sequences derived from human hosts [17] . These authors suggested that the observed mutations may have been due to APOBEC3 hypermutation , but they noted that strain-level polymorphisms , random retroviral mutations , or other processes could not be excluded as alternative explanations . Also , current methods for detecting and quantifying APOBEC3-mediated hypermutation have limited sensitivities at low rates of hypermutation . Thus , new methods are needed to resolve how APOBEC3 proteins might protect humans from zoonotic transmission of retroviruses . APOBEC3 activity against retroviruses can be inferred via the local sequence specificity of these editing enzymes . In general , APOBEC3 activity is detectable as an overall excess of plus-strand G to A mutations , however , the various members of the APOBEC3 gene family each have their own local nucleotide context specificity [18] . Much of the work on this specificity has focused on the dinucleotide pair formed by a G and the nucleotide immediately following on the positive strand . For example , human APOBEC3G is known to induce mutation in a GG context . Thus the level of activity of a given APOBEC3 enzyme can be characterized using the counts of G to A mutations in and out of context for that enzyme . Continuing the APOBEC3G example , by comparing the number of GG dinucleotide context G to A mutations to the number of such mutations outside this context , one can detect APOBEC3G hypermutation . Similarly , hypermutation by other APOBEC3 proteins can be inferred by G to A mutations in other dinucleotide contexts . Currently , the most popular approach , as implemented in the widely used HYPERMUT program [19] , is to use a Fisher test to determine if the in context mutations statistically exceed the out of context mutations . This application of the Fisher test has three shortcomings: first , when testing the equality of two binomial distributions , the nominal p-value of the Fisher test does not correspond to the actual rejection rate under the null [20]–[23] . Indeed , by simulating under the null in parameter regimes relevant to hypermutation analysis we show that it does indeed deviate from the nominal p-value , and importantly that the level of deviation depends on the parameters and thus cannot be ameliorated by a simple global change of cut off . However , we also find that the “mid-P” variant [24] does show significantly better performance than the classical Fisher test in this respect . Second , the Fisher test does not provide an estimate of the relative probability of mutation ( i . e . the effect size ) . Third , because the Fisher test requires a strict segregation of sites into “in context” and “out of context , ” it does not provide a foundation for further generalization to incorporate subtleties such as varying “strengths” of hypermutation contexts . In this paper , we employ a Bayesian method to detect and quantify hypermutation by estimating the relative probability , along with uncertainty estimates , of G to A mutation in a given APOBEC3-associated context versus a control context . In addition to providing a more sensitive test , the Bayesian methodology provides an integrated means to estimate effect size ( i . e . , hypermutation strength ) and significance ( to decide whether hypermutation is occurring ) . The risk ratio ( described below ) is a natural choice to report alongside the Fisher p-value for effect size estimation , as HYPERMUT does . Our approach does a better job of effect size estimation than the risk ratio for a range of parameter values spanning the data sets we have analyzed . Finally , the Bayesian approach can be directly generalized to situations such as different strengths of various hypermutation contexts . Using this Bayesian approach , we examined the hypermutation patterns of 1097 blood proviral DNA sequences from 169 rhesus macaques , as well as 152 buccal swab RNA sequences from 30 of these animals , and compared them to the hypermutation patterns of 77 SFV proviral DNA sequences detected in blood obtained from 8 zoonotically infected humans sampled from the same geographic areas as the macaques [3] , [25] , [9] . The buccal swabs are important for our analysis as they represent SFV as it is actively replicating rather than latently present in blood . For our studies of SFV variation , we have examined 1125 nucleotides of the gag gene [3] . This region of the genome was chosen for our studies because in FV , the gag sequence is the most variable of those encoding virion associated proteins [26] . This is unlike the case of orthoretroviruses , where the env gene is the most variable . The 1125 nucleotides were also chosen because this region contains only one short motif ( PSAP ) that is known to be required for FV replication . We reasoned that the relatively high variability in this region of gag would allow us to define viral strains . Since we had a large data set from this region of gag [3] , [25] , [9] , we used these sequences to determine potential APOBEC3 mediated hypermutation of SFV . Although we found evidence of hypermutation in SFV sequences from both humans and macaques , the relative frequency and intensity of SFV gag hypermutation differed significantly between macaques and humans , as did the dinucleotide contexts , suggestive of different host APOBEC3 activities . Moreover , by comparing macaque buccal swab RNA sequences to those obtained from human whole blood , we conclude that the signature of hypermutation in human host SFV sequences is not present in the viruses shed from monkey oral mucosal tissues , but likely arose after at least one round of replication in the human host . Taken together , our results indicate that human APOBEC3G is at least one mechanism that protects humans from extensive replication of some SFV strains .
To ameliorate the issues with applying the Fisher test described in the introduction , we developed a Bayesian approach to use the in-context versus out-of-context mutation counts to statistically identify hypermutation and quantify its strength ( Figure 1 ) . Our method uses the same data as the Fisher test to describe the ratio , with uncertainty estimates , of the probability of G to A mutation in a dinucleotide context of interest compared to the corresponding probability in a control context . We call this ratio the relative probability ratio . The uncertainty estimates associated with the relative probability ratio are crucial . For instance , if we see mutation in one out of four context X positions , and two mutations out of four context Y positions , then we can guess that the relative probability ratio is 1/2 . However , one can make this statement with much higher certainty if we have 1000 out of 4000 X context mutations and 2000 out of 4000 Y context mutations . This notion of an estimate with uncertainty can be formalized using Bayesian statistics as the posterior distribution of a model parameter given the data . In our setting , the model parameter of interest is the relative probability of G to A mutation in a dinucleotide context associated with a particular APOBEC activity , the focus context , to the probability of the same mutation elsewhere , the control context . This relative probability will be simply quantified as the ratio of the probabilities that we will call the relative probability ratio . We use two summaries of the posterior distribution of the relative probability ratio . The first is the location of the 0 . 05 quantile , which we abbreviate Q05 . Q05 signifies the level for which , with posterior probability 0 . 95 , the analysis predicts that the true relative probability ratio is greater than or equal to Q05 . In casual terms , if Q05 is equal to 2 , then we are 95% sure mutations in the focus context occur at least twice as frequently as those in the control context . We call the sequence as hypermutated in a given context when the corresponding Q05 value of the posterior distribution for the probability ratio exceeds 1 . The other summary used is the Maximum A Posteriori ( MAP ) value for the relative probability . The MAP is the most likely value , or mode , of the posterior distribution . As such it represents our best estimate of the relative probability ratio . It is important to note that the MAP of this ratio , the object of interest to us , is not the same as the ratio of the MAP numerator and MAP denominator . The difference between the two is especially apparent when the distributions on the numerator and denominator have substantial skew , as is often the case in our setting where the bulk of the probability can be on one side of the MAP value for each distribution . Indeed , the difference between the MAP of the ratio of two Beta-distributed random variables and the corresponding ratio of the MAP values can get arbitrarily large ( Figure S1 ) . Note that we will be testing “overlapping” contexts such as GG and GR ( G followed by a G or an A ) . When GR is preferred over GG , for example , this means that the combination of mutation in the GG and GA contexts was more significant than considering GG sites alone . For each sequence identified as hypermutated in more than one context , the context with the highest Q05 value was identified as the call pattern . The call pattern thus represents the context in which evidence of hypermutation is strongest . Validations were carried out on mutation counts simulated from a range of relative probability ratios and background mutation probabilities ( see Materials and Methods ) . Ideally , according to the definition of the p-value , one would get a uniform distribution of p-values under the null . Although it is not possible to get an exactly uniform distribution under the null in a discrete setting such as the Fisher test , it is desirable to have this distribution as close to uniform as possible ( e . g . , [24] ) . Under a variety of simulation conditions , we find that the classical Fisher test is far from having a uniform distribution under the null in that the observed p-value is consistently smaller than the nominal p-value . Thus , we confirm in this parameter regime the observations of others that the Fisher test is consistently “conservative . ” These simulations showed that our method is more sensitive than the Fisher exact test ( Table 1 ) , and that the sensitivity of the classical Fisher test cannot be improved by a simple predetermined change of cutoff ( Supplementary Figures S2 & S3 ) . We note that our method is slightly “liberal” for some parameter regimes ( in particular for testing the range between 0 . 05 and 0 . 1 ) and conservative for others . Additionally , the simulations allowed us to directly compare our MAP estimates to the true relative probability ratios used to generate the simulated data . Typically researchers have calculated effect size ( hypermutation strength ) by the risk ratio ( RR , also known as relative risk ) , as is done on the HYPERMUT web site ( see Materials and Methods ) . For most of the parameter domain , MAP estimates were consistently closer to the relative probability ratios used for simulation than were the RR estimates in terms of mean squared error ( Figure 2 ) . The simulation parameter regime for this figure was chosen to span the range observed in the SFV and HIV sequences used in this study . The “mid-P” variant of the Fisher exact test ( reviewed in [24] ) splits the probability of the observed contingency table in half , and assigns one half of the probability to the “more extreme table” category and half to the “less extreme table” category . This variant performed significantly better than the classical Fisher test in generating an appropriate p-value distribution ( Supplementary Figures S2 & S3 ) . For the simulations performed in this paper , this effectively corrected the issues of p-value cutoff observed with the classical Fisher test . However , the current methodology for hypermutation detection uses the classical Fisher test , rather than the mid-P version . Furthermore , in terms of the Receiver Operating Characteristic ( ROC ) curve to judge the true positive rate as parameterized by the false positive rate , the Bayesian approach performs slightly better than the mid-P approach ( Figure S4 ) . We also validated our method using sequence data from an in vitro study by Refsland et al . [27] , which involved knocking out members of the APOBEC3 family from human cell lines and measuring the consequent levels of hypermutation . On the Refsland data set , our methodology detected significantly more positives when the corresponding APOBEC was present , and the two tests had equal false positive rates when it was not . ( Table S1 ) . Using simulations based on the Refsland sequences , with no context-specificity to their mutations ( see Materials and Methods ) , we see that the median positive probability for our method is below the expected 5% ( Table S2 ) . In addition , we validated our method by applying it to sequence data from a study by Land et al . [28] that found a significant correlation between CD4 count and presence of strongly hypermutated HIV virus . We performed a similar analysis as in the original paper but with a slightly different bioinformatics pipeline , ( see Materials and Methods ) and did not see a significant effect when applying the Mann-Whitney test to compare CD4 counts between hypermutation positive and negative calls made by either the Fisher test or our approach . However , when we added the requirement that sequences considered positive for hypermutation by Q05 also have a large effect size as measured by MAP ( in the top 25% ) we did find a significant elevation in CD4 count compared to the rest of the sequences ( p = 0 . 026 ) . However , we did not see a significant effect when taking sequences that were positive according to mid-P and in the top 25% of effect size according to risk ratio ( p = 0 . 31 ) . Additionally , when restricting to the sequences found to be hypermutated , we find a much more significant nonparametric positive correlation between effect size and CD4 count using our method ( Kendall tau p = 0 . 0026 ) than using mid-P together with the risk ratio ( p = 0 . 060 ) . These findings emphasize the importance of accurate effect size estimation , which forms an important part of our analyses of SFV sequences below . Thus , a Bayesian framework to directly estimate the relative probability of mutation in or out of a given APOBEC3 context avoids problems associated with applying the Fisher test and provides a more accurate means for quantifying the level of hypermutation than previously described . The corresponding code is already publicly available ( http://github . com/fhcrc/hyperfreq; see Materials and Methods for details ) and will be made available as a web tool in the near future . In order to investigate whether APOBEC3 activities alter SFV in macaques and/or humans infected with the virus , and to compare the levels of APOBEC3 activities in humans and macaques , we analyzed SFV gag sequences from a diverse collection of human blood samples as well as macaque blood and buccal samples collected across multiple urban and forested locations in Bangladesh [3] , [25] , [9] . Overall , 50 out of 77 ( ∼65% ) human host SFV sequences obtained were found to be affected by hypermutation ( Table 2 ) . SFV from all but one of the 8 humans showed evidence of APOBEC3G hypermutation in at least one sequence . The exception was one individual ( BGH150 ) , whose 6 SFV clones showed no evidence of G to A hypermutation in any context . We note that the BGH150 sequences were similar to those detected in the macaques from the same region , indicating that the sequences were not amplified from contaminating plasmid . In two of our human subjects , both of whom were infected by more than one SFV strain , we observed hypermutation in clones corresponding to only one of the viral strains . Although buccal swabs were taken from the humans sampled as part of this study , none of these tested positive for SFV . In contrast , only 82 out of 1097 ( ∼8 . 1% ) of SFV sequences from monkey blood were found to be hypermutated , and only 42 of the 169 monkeys sampled had at least one hypermutation-positive sequence . Hypermutation was more prevalent in human blood sequences than monkey blood sequences ( Fisher p = 1 . 3×10−32 ) . Defining a sample to be hypermutated if at least one sequence obtained from the sample was hypermutated , hypermutation was more prevalent in human blood samples compared to monkey blood samples ( Fisher p = 1 . 7×10−4 ) . Additionally , the distribution of relative probability ratio across all sequences , irrespective of inferred hypermutation status , was higher for human host SFV sequences than for monkey host sequences ( Figure 3 ) . Furthermore , sequences marked as hypermutated showed a higher relative probability ratio of hypermutation in human blood than in monkey blood ( Bonferroni-corrected Wilcoxon p = 1 . 9×10−6 ) . Different context patterns were observed between human and monkey sequences ( Figure 4 ) . Of the 152 sequences obtained from the 30 macaque buccal swab samples , only 8 – from 5 samples – were found to be hypermutated . Thus , hypermutation was also more prevalent in human blood sequences than monkey buccal sequences ( Fisher p = 2 . 3×10−22 ) . Similarly , more human blood samples had evidence of some hypermutation than monkey buccal samples ( Fisher p = 4 . 3×10−4 ) . Furthermore , the MAP relative probability ratios of monkey buccal sequences were significantly lower than those of the GG positive human blood sequences ( Figure 5; Bonferroni-corrected Wilcoxon p = 0 . 023 ) . While the frequency of hypermutation observed in monkey blood samples is higher than that of monkey buccal samples , no statistical significance was found for this relationship . Thus , overall , with a high degree of statistical significance , more human host SFV sequences were found to be hypermutated than monkey host SFV sequences , and human host SFV sequences had a higher level of hypermutation than the SFV sequences from the macaque host . Hypermutation of human host sequences in these data was most frequently associated with the GG and GR ( i . e . GG or GA ) dinucleotide contexts ( 45 out of 50 sequences; 90% ) , consistent with APOBEC3G activity as well as combined APOBEC3G and APOBEC3F activity [27] . In contrast , monkeys exhibited a significant amount of GA and GM ( i . e . GA or GC ) context hypermutation ( 37 out of 82 sequences; 45% ) . GM context hypermutation was also observed in a study that examined hypermutation of the XMRV retrovirus in macaques [29] . Overall , hypermutation in human host sequences was more likely to be called in GG and GR contexts than for monkey host sequences ( Fisher p = 1 . 3×10−5 ) . Furthermore , human blood SFV sequences identified as hypermutated in GG and GR contexts exhibited higher MAP relative probabilities than macaque blood SFV sequences ( Bonferroni-corrected Wilcoxon p = 4 . 8×10−8 and p = 3 . 7×10−4 , respectively for the two contexts ) , corresponding to stronger action of APOBEC3G . The GM context , characteristic of macaque APOBEC3DE hypermutation [29] , showed elevated levels in SFV from macaque samples ( Figure 4 ) . While the 8 monkey buccal sequences ( out of 152 ) marked as hypermutated all exhibited the strongest hypermutation signal in a GG context , as mentioned above , the strength and abundance of this hypermutation signal was significantly lower in monkey buccal samples than human blood samples . Of the 77 human blood sequences , 36 ( 46 . 8% ) contained stop codons within the coding region when the sequences were translated . These stop codons were “in-frame” in that they were the result of a point mutation rather than insertion or deletion and a consequent frame shift . In contrast , only 63 of the 1097 ( 5 . 7% ) monkey blood sequences had such stop codons . Thus , such stop codons are more likely in blood samples from humans than those from monkeys irrespective of whether the entire sequences were called hypermutated by any test ( Fisher p = 2 . 2×10−16 ) . When considering only sequences called hypermutation positive , this statistical relationship held ( Fisher p = 6 . 5×10−13 ) . The same was true when looking at only GG context positive sequences ( Fisher p = 1 . 0×10−12 ) . Stop codons were correlated with presence of hypermutation activity in humans: all human sequences with stop codons were classified as hypermutated , and only 15 human host sequences called hypermutation positive lacked stop codons . Thus we find that the number of stop codons in sequences from human host blood samples is statistically significantly higher than in monkey host blood sequences . 6 of the 152 ( 3 . 9% ) monkey buccal swab sequences had in-frame stop codons . Thus , stop codons are also significantly more prevalent in human blood sequences than they are in monkey buccal sequences ( Fisher p = 1 . 1×10−14 ) . While the empirical frequency of stop codons is higher in monkey blood samples than in buccal samples , this relationship was not found to be statistically significant . Overall , by applying Bayesian analysis we show that hypermutation is statistically more prevalent , stronger and in distinct dinucleotide contexts in the human host sequences , and correlates with the presence of stop codons in a coding region for gag that would preclude virus replication ( Figure 6 ) .
We have developed Bayesian methodology to test for and quantify the strength of hypermutation . Our motivation for doing so was to quantify the relative probability of mutation in various nucleotide contexts . This Bayesian method tidily formalizes this idea as estimation , with uncertainty , of the ratio of probability of mutation in two contexts as a ratio of beta-distributed random variables . This enables a unified approach to significance testing ( hypermutation detection ) and effect size ( hypermutation strength ) estimation . We show that the Bayesian effect size estimate performs better than the classically-used risk ratio ( henceforth RR ) over a range of parameter values ( Figure 2 ) . Additionally , it is recognized in the statistics community that the Fisher test is only appropriate when the “marginals” , i . e . the row ( in this study the number of mutants versus not ) and column ( in this study the number of sites in dinucleotide context versus not ) sums , are fixed in advance [21] . This is not the case for hypermutation detection . A number of statistical papers have highlighted problems with applying the Fisher test when this assumption is violated [20]–[23] . For example , by direct enumeration of tables , D'Agostino et al . [20] have shown that the Fisher test does not produce appropriate p-values when testing the equality of two binomial distributions . In our simulated data we also find that the classical Fisher test is less sensitive than our method ( Tables 1 and S1 ) , and that this lack of sensitivity cannot be easily remedied by considering alternate globally-applied cut-offs ( Figures S2 & S3 ) . However , the “mid-P” variant of the Fisher test does generate a null distribution that is significantly closer to the uniform than the classical Fisher test and consequently is more sensitive . This variant should be preferred to the classical Fisher test when sensitive detection of hypermutation is desired using a Fisher-type test . Others have proposed alternate means of investigating hypermutation . One approach is to test ratios derived from k-mer motif frequencies in sequences with a Hotelling T2 test [30] . This method has the advantage of not needing to have every sequence paired with a putatively non-hypermutated sequence , however , it requires long sequences to get sufficient power ( in that paper they used whole HIV genomes ) . Another group [31] has made a software package to investigate potential hypermutation using plots , but did not formalize a statistical methodology . Using validation and an application to real data , we have shown that the Bayesian framework is an appropriate way to analyze hypermutation-by-context data and that it avoids issues associated with applying the Fisher exact test in this setting for significance testing . We also show that the effect size estimates , which follow naturally from our framework , are more accurate than the standard risk ratio estimator . A further advantage of the Bayesian framework proposed here is that it can incorporate diverse sources of information as well as uncertainty of “hidden” variables in a principled way . We will take advantage of this feature in future work . Specifically , our next step will be to account for a variety of “strengths” of k-mer context specificities . We are motivated by observations that some contexts are more strongly associated with hypermutation than others [32] , [18] , [33] . Thus it is not possible to strictly segregate motifs into “hypermutation associated” versus not , making it impossible to apply tests such as the Fisher exact test . This flexibility comes at the cost of some non-trivial computation . Indeed , although we are able to employ a closed form expression for the probability density function in a ratio of Beta distributions , this expression involves hypergeometric functions that take work to evaluate beyond standard implementations of these functions . This is in contrast with the FET and the RR estimators , which are easily implemented and computationally efficient . The code used to evaluate sequences for hypermutation using our posterior estimation framework is available at http://github . com/fhcrc/hyperfreq . This program , as well as the routines to perform clustering to find representative non-hypermutated sequences , will be made into a more user-friendly form released within the next year and linked to from the same hyperfreq website . Using this methodology we found that hypermutation in SFV latent proviral sequences from zoonotically infected humans is common , strong , and primarily in the GG dinucleotide context with some in GA and GR ( i . e . GG and GA combined ) . This corresponds primarily to APOBEC3G activity , perhaps combined with activity of another APOBEC3 . In contrast , the hypermutation signal observed in macaques is rare , generally much weaker , and in a distinct set of dinucleotide contexts . A relatively small number of these sequences exhibit very strong GM ( i . e . G followed by A or C ) and GA context hypermutation , suggestive of rhesus macaque APOBEC3DE activity [29] . By quantifying the strength , frequency , and context specificity of APOBEC3 acting on SFV , we show that it is likely an important restriction factor that acts in vivo to limit replication of some SFV strains in the human host ( Figure 6 ) . This is true not only when comparing hypermutation levels between proviruses present in human blood and monkey blood , but also when comparing SFV sequences present in human blood and monkey buccal swabs . This is important , as oral mucosal tissues are the apparent source of infectious virus . APOBEC3G-mediated inhibition of replication in humans could explain the lack of human to human transmission of these strains . The differences in hypermutation context and strength suggest that the observed hypermutation in human host sequences could not have originated in macaques prior to transmission , and must instead be occurring within human hosts . Other researchers have shown human APOBEC3 to be a potent SFV restriction factor in vitro [17] . These researchers also observed G to A mutations in SFV sequences derived from four bushmeat hunters from Southern Cameroon [17] . These individuals were persistently infected with gorilla SFV from 10 to 30 year old bites , and viral loads in PBMCs were described as being low . Several G to A mutations were observed , some of which were in GG and GA contexts , which may be explained by APOBEC3G or APOBEC3F activity that targeted the viruses . However , the authors of that study did not take a statistical approach and stated that they could not rule out alternate causes for the observed mutations . Thus the present study is the first to clearly show human APOBEC3 activity against SFV in vivo . There are conflicting data on whether or not there is an SFV viral antagonist to APOBEC3 analogous to lentiviral Vif . While some researchers [34]–[36] report that the nonstructural protein Bet can counteract APOBEC3 activity , others [17] have not been able to detect a difference between restriction of wild-type viruses and viruses lacking Bet . However , it is possible that viruses can evade APOBEC3 using other mechanisms . For example , murine leukemia virus does this via modification of the Gag protein rather than through a specific viral antagonist [37] , [38] . In either case , our data support a model where some strains of SFV are sensitive to inactivation by human APOBEC3G . APOBEC3 enzymes work on ssDNA during reverse transcription . Unlike HIV , SFV primarily undergoes reverse transcription prior to infection of new cells , and only the DNA already present in the virion gets incorporated into new cells [39] , [40] . Thus , evidence of human APOBEC activity acting on SFV implies at least one round of replication within the human host . This study provides the first evidence , although indirect , supporting SFV replication in humans . However , this conclusion is in contrast to other work failing to detect SFV replication in human oral or blood cells using other methods [7] . Indeed , in a companion study [9] we were unable to detect SFV RNA in buccal swab samples from the same seropositive humans . This suggests that the level of replication in humans may be below the limit of detection , which is consistent with the overall low proviral titers observed in human blood . Almost half of the human host SFV gag sequences in this study contained in-frame stop codons within the coding region , which would prevent further replication . Although there are likely to be replication competent proviruses in humans , our studies have failed to detect any SFV transcripts . We cannot say there are no transcripts , only that our RT-PCR methods have failed to detect these . We also could not exclude the possibility that there is a strain- or host-level effect on hypermutation frequency . In Feeroz et al . [3] we demonstrated that SFV gag sequences from free-ranging rhesus macaques in Bangladesh primarily cluster into six strains , and that these strains have a strong correspondence with sampling location and/or origin of the animal . Here we observe that some of these SFV strains show more evidence of hypermutation than others ( Table 2 ) . Two humans and 10 monkeys were infected with the karamjal strain , a strain characteristically found in animals that originate from the Karamjal region of Bangladesh . Only one out of the 73 sequences of the karamjal strain was found to be hypermutated , and that one hypermutated sequence was from a macaque . Additionally , no hypermutated sequences were found in a human infected with the charmaguria strain , a strain detected in the macaques in the town of Charmaguria . On the other hand , 22 of the 31 sequences in bormi2 sequenced from human hosts ( see [25] for terminology ) were positive for hypermutation , and every human of the four infected with bormi2 had at least one hypermutated sequence . This contrasts with only one sequence of the 102 bormi2 sequences obtained from monkey hosts being positive for hypermutation . Additional data are required to understand how viral strain and host response influence hypermutation .
The data set is completely described in [3] , [25] . The human study population consisted of eight human subjects who were found to be positive for SFV by PCR as part of a larger study , as well as 169 free-ranging macaques ( M . mulatta ) . The macaques and humans were sampled in regions of Bangladesh where they come into close contact in the context of daily life . RT-PCR was performed to clone partial gag sequences ( 1125 bp ) from buccal swab RNA of 30 macaques [9] , while gag proviral sequences were PCR amplified and sequenced from blood of macaques and humans . An average of six clones per sample were sequenced . | Simian Foamy Virus ( SFV ) is a very common retrovirus in monkeys . When an infected monkey bites a human it can transmit the virus to the human; however , there are no documented cases of human to human transmission . There also appear to be significant differences between infection in monkey and human hosts . The reason for these differences in the two hosts is not completely understood . In this paper we show that a family of host defense enzymes called APOBEC3 may prevent replication of SFV in humans . They do this by changing the genome of the virus so that it cannot replicate . Although this same process also happens in monkeys , it appears to happen less than in humans , and the changes that the monkey APOBEC3 enzymes make are less likely to prevent the virus from replicating . We are able to make these inferences by seeing characteristic types of mutations in a collection of virus DNA sequences sampled in Bangladesh . We develop new statistical methodology to do this analysis . | [
"Abstract",
"Introduction",
"Results",
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] | [
"mathematics",
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] | 2014 | A Novel Bayesian Method for Detection of APOBEC3-Mediated Hypermutation and Its Application to Zoonotic Transmission of Simian Foamy Viruses |
Rabies remains a major public health threat in many parts of the world and is responsible for an estimated 55 , 000 human deaths annually . The burden of rabies is estimated to be around US$20 million in Africa , with the highest financial expenditure being the cost of post-exposure prophylaxis ( PEP ) . However , these calculations may be substantial underestimates because the costs to households of coping with endemic rabies have not been investigated . We therefore aimed to estimate the household costs , health-seeking behaviour , coping strategies , and outcomes of exposure to rabies in rural and urban communities in Tanzania . Extensive investigative interviews were used to estimate the incidence of human deaths and bite exposures . Questionnaires with bite victims and their families were used to investigate health-seeking behaviour and costs ( medical and non-medical costs ) associated with exposure to rabies . We calculated that an average patient in rural Tanzania , where most people live on less than US$1 per day , would need to spend over US$100 to complete WHO recommended PEP schedules . High costs and frequent shortages of PEP led to poor compliance with PEP regimens , delays in presentation to health facilities , and increased risk of death . The true costs of obtaining PEP were twice as high as those previously reported from Africa and should be considered in re-evaluations of the burden of rabies .
Rabies is a fatal zoonotic infection of the central nervous system caused by a lyssavirus [1] . This disease , which can affect all mammals , is transmitted in the saliva of infectious animals [2] . Rabies is endemic in low income countries , causing an estimated 55 , 000 human deaths each year with over 98% of these deaths following bites from rabid dogs [3] . Annual expenditure for rabies control and prevention in Asia and Africa has been estimated to exceed US$500 million , with most of these costs spent on provision of post-exposure prophylaxis ( PEP ) [3] . However , reliable data on disease burden are scarce in most low income countries , particularly across Africa [4] , [5] . Rabies can be controlled through mass dog vaccination [6]–[10] and human deaths prevented through timely and appropriate PEP , which consists of rapid and thorough washing of the wound , completion of post-exposure vaccination schedules plus inoculation with rabies immunoglobulin ( RIG ) for severely exposed bite-victims [11] . Various PEP schedules are recommended by WHO and by the US Advisory Committee on Immunization Practices ( ACIP ) , requiring different numbers of doses [12] , [13] . Despite the effectiveness of PEP , many thousands of people still die from rabies especially in rural areas of Asia and Africa where canine rabies is endemic . These deaths are affected by the accessibility and affordability of PEP , which are key factors in determining human disease risk [14] . Access to health services has been defined as a multidimensional process that , in addition to the quality of care , involves geographical accessibility , availability of the right type of care for those who need it , financial accessibility , and acceptability of services [15] . Geographical factors are known to be important but are often overlooked when quantifying the economic burden of disease [16]–[21] . More generally , problems of access to adequate and appropriate health care are common in developing countries [22]–[26] . In most countries in Sub-Saharan Africa , there are many reasons why prompt access to appropriate PEP remains a serious challenge for bite-victims . Cold chain requirements for storage of vaccines between 2–8°C limit access to areas where electricity is available [27] . Frequent shortages of biologicals ( vaccines and immunoglobulin ) , particularly in rural clinics also limits access [5] , and WHO-recommended schedules that include administration of RIG are very rarely followed in Africa [3] . Tanzania is a low income country where canine rabies is endemic , with around 1 , 500 human rabies deaths estimated to occur annually [4] . Although some data are available on the treatment-seeking behaviour of bite victims and the associated costs of accessing rabies PEP in rural areas of northern Tanzania [5] , this study presents a more complete evaluation of PEP costs and determinants of human disease risk , capturing a broad range of socioeconomic settings and including both urban and rural communities . This study provides detailed insight into the consequences of rabies exposures , by investigating the health-seeking behaviour and coping strategies of bite victims .
The study was conducted in 4 districts in Tanzania , Serengeti and Musoma Urban in northern Tanzania and Ulanga and Kilombero in southern Tanzania , covering both urban and rural populations and the main livelihoods of agro-pastoralism and subsistence agriculture ( Figure 1 ) . Serengeti district is inhabited mainly by agro-pastoralists . The district hospital is located in Mugumu town , the headquarters of the district . There are no tarmac roads in Serengeti district and thus most roads are in poor condition especially during the rainy seasons . Musoma Urban district is located on the shores of Lake Victoria . In this district most people are employed in small business , small-scale agriculture , the Tanzanian civil service and fishing [28] . Musoma Urban is an urban district with better physical and social infrastructure and where all major town roads are tarmac . Musoma Urban serves as the headquarters of the Mara region and is where Mara regional hospital is located . In southern Tanzania , Ulanga and Kilombero districts are situated in the floodplain of the Kilombero valley . The majority of people living in these two districts are subsistence farmers , fishermen or pastoralists . District hospitals in Ulanga and Kilombero are located in Mahenge town and Ifakara town , which are the respective district headquarters . Both districts have very poor roads although there are a few short stretches of tarmac in the district capitals and on the steepest roads . Flooding in the Kilombero valley makes roads inaccessible during the rainy season , reducing access to health facilities . We used the criteria of the Tanzanian National Bureau of Statistics ( NBS ) in differentiating rural and urban areas [28] . The definition of urban areas according to NBS , applied in this study , is that urban areas are regional and district headquarters with boundaries as identified by the Tanzanian Village Act of 1975 and Urban Ward Act of 1976 . In this study , Musoma Urban district was identified as a typical urban area , all district headquarters were assigned as urban areas , and all other areas outside of district headquarters were classified as rural areas . Two methodologies were used in this study: 1 ) Extensive investigative interviews to determine rabies exposure incidence in the study areas , conducted in the three districts of Serengeti , Ulanga and Kilombero; and 2 ) questionnaires administered in all 4 study districts to determine health seeking behaviour , associated costs and coping strategies . We compiled animal bite records and case reports from veterinary and livestock offices and details of patients reporting with animal-bite injuries from hospitals , clinics and dispensaries within the focal districts of Kilombero , Ulanga and Serengeti . These records were used to initiate extensive investigative interviews to determine networks of transmission; we actively searched and traced all identified sources of infection ( i . e . biting animals ) and subsequent cases of onward transmission/bite exposure , as previously described [6] . During the visits to households of bite victims , we collected information about the age , gender , and livelihood of bite victims , the severity of the bite , and the circumstances of the bite . Information was recorded on the attacking animal such as aggressive or abnormal behavior , drooling/salivation , vocalization , roaming , listlessness , or paralysis , and its subsequent fate . For known biting animals , information was collected from their owner ( if identified ) on how the animal may have become infected and whether it had any previous history of vaccination . The aforementioned clinical signs were used to evaluate whether the attacking animal could be clinically categorized as rabid , based on the criteria of the ‘six-step’ method [29] . The ‘six step’ method is a diagnostic method based on epidemiological ( history of exposure ) and clinical criteria . Such criteria were previously reported to be accurate for 75% of specimens submitted for laboratory confirmation [30] . Whenever possible , brain stem samples from carcasses of animals that caused bite injuries were collected using the ‘straw’ technique as recommended by the World Health Organisation for laboratory confirmation [31] , [32] . Universal Transverse Mercator coordinates were collected using a handheld Global Positioning System for each health facility and household visited and used to estimate an overall straight-line distance travelled by bite patients whilst seeking PEP . A structured open-ended questionnaire was also administered to a subset of rabid animal bite victims and the families of rabies victims ( n = 415 , including 18 rabies death cases ) bitten between January 2006 to December 2008 . We collected information on demographic characteristics of the victims , costs related to the bite and seeking medical attention and coping strategies of bitten individuals and their families . We recorded the number of health facilities visited by the victim whilst seeking PEP , the number of days spent at each health facility , the amount of money paid for medical services , travel and other costs and how these funds were raised . When patients were escorted by an adult family member/guardian during the PEP seeking process , related costs were also captured . In order to validate costs incurred , heads of households were asked to produce receipts and in the absence of receipts , market prices or local fares were used to estimate the costs . Respondents were also asked to mention how much time both the patient and carer spent in seeking PEP . However , the questionnaire did not capture losses due to the premature death of a household member due to rabies or of being absent from school for school children . Human demographic data for the study were drawn from the Tanzanian national population and housing census of 2002 [28] . The estimated population growth rates for each district according to the 2002 census were used to project the population size of the study areas for 2006–8 . The total numbers of traced suspect bite and rabies death cases in the study areas for the period of January 2006–December 2008 , together with the projected demographic data were used to estimate the annual incidence of rabies exposures and of human rabies deaths per 100 , 000 persons . For this analysis , the direct medical costs included the costs of biologicals ( only rabies vaccines , since RIG was not administered in the study areas ) and the costs associated with wound care , such as antibiotics , tetanus immunizations and disinfection . The price year was 2010 . The indirect costs included out-of-pocket expenses for patients , such as transport costs to and from health centres and hospitals , accommodation and other costs for communication and subsistence while seeking PEP . Non-medical costs included productivity losses due to time spent seeking PEP . Time lost for both patients and escorts was valued in monetary terms according to projections of per capita daily income from the Tanzanian Household Budget Survey ( HBS ) of 2007 [33] . All medical and non-medical costs were expressed in terms of Tanzanian shillings ( TZS ) , and converted to US dollars ( US$ ) using the average annual exchange rate in 2010 , which was 1 TZS to US$ 0 . 000687 [34] . The total number of PEP doses administered and patient visits made to health centres to receive PEP were derived from the questionnaires and validated from hospital records . We used the number of doses received to estimate patient compliance during PEP courses . We calculated ( i ) average costs per suspect bite victim and ( ii ) average costs per dose . The average cost per suspect bite was defined as the average amount of cash spent by victims and caretakers following a bite , including costs of receiving PEP . Therefore suspect rabies bite victims including those who did not seek medical attention were included in this calculation . Average cost per dose was defined as the average amount of cash spent by patients and their carer ( s ) in receiving a single PEP dose . Therefore only patients who sought and successfully obtained at least one dose of PEP are included in this calculation . This was estimated by summing all cash costs spent on obtaining PEP and dividing by the total number of doses delivered . We also calculated the predicted average costs of PEP according to different regimens including intramuscular ( IM ) and intradermal ( ID ) administration and methods of subsidization that could be used in the future . These were calculated as the mean cost per dose plus annual income lost per dose , all multiplied by the number of clinic visits in the PEP regimen . These losses were converted into the percentage of annual income lost and equivalent days wages lost . Chi-square tests were used to examine differences in sources of funds used to pay for PEP between victims from rural and urban areas and the proportion of victims that were escorted while seeking PEP . The Welch Two Sample t-test was used to determine the differences in average costs per suspect bite , numbers of hospitals visited before receiving PEP and delays in receiving PEP , between patients from rural and urban areas . Regressions were applied to assess factors affecting the costs of acquiring PEP , delays to obtaining PEP , probability of completing PEP ( logistic regression ) and probability of death following exposure to rabies ( logistic regression ) . Explanatory variables investigated included direct medical costs , travel costs , accommodation costs , other costs , and loss of productivity costs , gender , residence ( rural or urban ) , district and distance to PEP delivering hospitals . Every explanatory variable was tested to assess significance ( at P<0 . 05 ) then a final multivariate regression model was developed using backward stepwise variable selection . All statistical analyses were implemented within the R statistical programming environment [35] . The study protocol was approved by the Medical Research Coordinating Committee of the National Institute for Medical Research of Tanzania , with approval number NIMR/HQ/R . 8a/vol . IX/994 and the Institutional Review Board of the Ifakara Health Institute , including the use of oral consent for the collection of interview data . Written consent was not obtained as the study followed established procedures for collecting interview data in Tanzania without the collection of biological samples from humans . The study was cleared by the District Executive Director in every study district and Village Executive Officers were asked for permission prior to starting work in each village . Before administering questionnaires , participants were orally informed about the purpose of the study , the data to be collected and the freedom of their participation and their right to withdraw from the study at any time during the interview . Participants were then asked if they would wish to be interviewed . All respondents agreed verbally and the interviews were conducted .
Animal bite injuries were traced and investigated across three districts ( Ulanga , Kilombero and Serengeti ) , from January 2006 to December 2009 . Active searching revealed 599 animal bite injuries that met the case definition of being caused by suspect rabid animals as per criteria of the ‘six-step’ method: 136 in Kilombero district , 248 in Ulanga district and 215 in Serengeti district . Estimates of the annual incidence of bites from suspected rabid dogs per 100 , 000 persons , and annual incidence of human rabies deaths are summarised in Table 1 . We were unable to trace all bite cases reported in hospital records; however , we suspect that using this methodology we captured the vast majority of rabies exposures including many instances where the bite victim did not report to hospital . The ages of suspect bite victims ranged from 1 to 90 years . The majority of suspect bite victims ( 51% ) were children less than 15 years of age . The reported sources of bite exposure to humans were: domestic dogs ( 535 or 89% ) , others including humans ( 4 or 0 . 7% ) , livestock ( 1 or 0 . 2% ) , domestic cats ( 19 or 3% ) and wild animals ( 32 or 5% ) . Reports of bites from wild animals included: jackals , honey badgers , genets , hyena , mongoose , wild pig and monkeys . The species were not determined due to potential ambiguities in identification . The peak of bites in Ulanga district was observed between July and September 2007 ( Figure 2 ) , when there was an outbreak of rabies in which 64 people were bitten by suspect rabid animals . Structured open-ended questionnaires were administered to 415 bite victims bitten by suspect rabid animals between January 2006 and December 2008; 97 in Kilombero , 141 in Ulanga , 152 in Serengeti and 25 in Musoma Urban that were identified from hospital records . Questionnaires were not administered to all cases traced through active searching because of time constraints during fieldwork . Only 12% of these bite victims received PEP free of charge on a first-come first-served basis , the reminder had to pay for PEP , with rural bite victims paying around $12 per PEP dose and urban bite victims paying $8 per dose ( Table 2 ) . Direct medical costs per suspect bite victim ranged from zero for those who either received free medical services or did not seek medical attention , to more than US$250 for complicated bites , which involved surgical operations . There was no significant difference in productive days lost by bite victims from rural or urban areas , due to seeking health care following exposure ( 10 . 52 days in rural areas and 10 . 98 days in urban , p = 0 . 18 ) . The average time lost per dose was very similar for rural and urban victims ( 5 . 3 days for rural victims and 5 . 2 days for urban victims ) because the frequent shortages of PEP in district hospitals meant that patients living in district town centres ( urban areas ) also sometimes had to travel to major cities . The monetary value for time lost per suspect bite was equivalent to US$7 . 22 in rural areas whereas in urban areas it was estimated to be equivalent to US$17 . 03 . The costs associated with receiving PEP including travel , accommodation and other costs are summarised in Table 2 . Ninety-four percent ( 391/415 ) of these suspect bite victims reported to health facilities for PEP . About half of these bite victims reported , immediately after being bitten by animals but there was considerable variance in delays before receiving the first PEP dose between rural and urban bite victims . Bite victims in rural areas took longer , on average , to receive PEP than those in urban areas ( Figure 3 , mean 5 . 57 days , 95% CI 4 . 25–6 . 9 days in rural areas versus mean 3 . 64 days , 95% CI 2 . 09–5 . 19 days , in urban areas , χ2 = 10 . 91 , df = 3 , p = 0 . 01 ) . Of 272 bite victims who lived far from district hospitals ( more than 10 kilometres ) , only 39% received PEP within 7 days after exposure whereas , 64% of those who lived close to district hospitals received PEP within 7 days after exposure ( χ2 = 14 . 59 , df = 3 , p = 0 . 002 ) . Bite victims from urban areas where the district hospital was located in their home town did not incur many indirect costs compared with patients from rural areas who had to travel further to these hospitals . If PEP was not in stock at district hospitals , victims had to either wait for hospitals to procure PEP or travel elsewhere to receive PEP . We found that 40% ( 156/391 ) of patients attended multiple heath facilities ( maximum of five heath facilities ) for PEP . Of these 85% ( 132/156 ) were patients from rural areas ( χ2 = 32 . 11 , df = 2 , p<0 . 0001 ) . A total of 841 doses were delivered to suspect rabid bite victims for the period between January 2006 and December 2008 . Generally , patients were advised to get 3 doses of PEP intramuscularly on day 0 , 7 and 28 according to Tanzanian health authorities , a regimen that is not recommended by WHO . On average suspect bite victims received 2 . 82 doses of PEP ( 95% CI 2 . 75 to 2 . 90 doses , Table 3 ) . Almost 30% of suspect bite victims , who required PEP , did not receive any doses . The majority ( 73% ) of suspect rabies bite victims were escorted by an adult family member to hospital . There was no significant difference in whether bite victims from rural versus urban areas were escorted to hospital ( χ2 = 0 . 71 , df = 1 , p = 0 . 40 ) . Families adopted various coping strategies to meet the costs of obtaining PEP . Families that had no savings had to transform their assets into cash . Poor rural families with little or no assets often were unable to afford PEP and experienced financial hardship while raising funds for PEP . We found that residence ( rural or urban ) had a significant impact on the source from which households obtained funds to pay for PEP ( χ2 = 38 . 80 , p<0 . 0001 ) . Patients from urban areas were more likely to use money from their salaries or sell their assets whereas patients from rural areas either obtained funds from selling crops or selling livestock ( Figure 4 ) . Poor rural farmers were worst affected because they depend solely on one source of income ( agricultural produce ) . Despite the importance of PEP for saving the lives of bite victims , we found that shortages of PEP were common at the district hospitals . These shortages together with the expense of PEP created financial difficulties for many poor individuals , particularly those living in rural areas who had to raise money to pay for PEP , transport costs to reach urban areas and subsistence while receiving PEP . The implications of these costs associated with receiving PEP included delays in receiving PEP as summarised in figure 4 , poor compliance with PEP regimens and human rabies deaths for those who did not obtain PEP . Just over 72% ( 298/415 ) of suspect bite victims received at least one dose of PEP . Of those that received their first dose , only 67% returned for a second dose , i . e . 5% of patients dropped out after a single dose . There was a further drop out of 16% after the second dose and very few patients received the last two doses ( Figure 5 ) . Patients from rural areas reported that they did not complete PEP because they were: i ) unable to afford the vaccine , 54%; ii ) vaccine was not available at the hospital , 32%; iii ) the wound had already healed , 10%; iv ) they were advised by the medical officer to discontinue PEP , 3% or v ) they ignored advice to complete PEP , 1% . Reasons cited by urban patients were: i ) lack of vaccine at the hospital , 64%; ii ) unaffordable costs of vaccine , 24%; iii ) advice from medical officers to discontinue PEP , 8%; and iv ) because the wound had healed , 4% . Costs were a significant obstacle for bite victims to both obtain and complete PEP ( p<0 . 05 ) . We therefore calculated the predicted costs of completing PEP under different regimens that are recommended by WHO , assuming PEP is provided free-of-charge , as well as being made available at local health centres and not just at district hospitals therefore minimizing travel costs . The costs of completing PEP under these scenarios are presented in Table 4 . We found that 28% ( 117/415 ) of bite victims did not receive PEP of any kind , of them 18/117 ( 15% ) developed rabies , whereas none of those who received a single dose of PEP developed rabies . Most of the deaths occurred in households dependent on subsistence farming ( 89% ) , involved children less than 16 years of age ( 78% ) and occurred in areas far from hospital ( 78% of deaths occurred in areas more than 10 kilometers away from nearest district hospital and 89% further than 60 kilometers from the regional hospital ) . In a multivariate analysis , distance to the district hospital and direct medical costs were the only significant predictors of human rabies deaths ( p<0 . 05 ) .
The present study confirms that rabies remains a serious public health and economic problem in developing countries where canine rabies is endemic . Bites from suspect rabid animals impose a substantial financial burden on affected households , especially for poor rural bite victims who suffer excessively high costs in obtaining PEP compared to those from urban areas , and are less likely to receive vaccine . PEP is vital for human rabies prevention and requires repeat visits to hospital to complete a full course . Rural bite victims often live far from major health facilities in urban areas , where PEP can be obtained; however , even in these areas the availability of PEP is not guaranteed . In remote areas , travel to a regional hospital where PEP shortages are less frequent , can take more than 18 hours and is expensive . Moreover , costs were almost double for patients that needed to be escorted by a family member/adult , with rural bite victims incurring disproportionately higher indirect costs and a higher risk of developing rabies and dying from the disease . Delays to receiving PEP , due to hospital shortages and time spent raising money or waiting for district hospitals to procure PEP increased the risk of developing this fatal disease . The need to repeatedly visit hospital to complete PEP may deter poor people living in remote rural areas from obtaining and completing PEP , which may explain why the risk of rabies was higher for those living further from major hospitals . More generally , the distance to major hospitals seems to be an obstacle for people living in rural areas in Africa . A study in Ivory Coast reported that over 75% of patients who discontinued of PEP were from outside the capital city , Abidjan [36] . In summary , we have shown that major inequalities in health care , and access to and affordability of PEP for bite victims exist in Tanzania and have demonstrated the importance of evaluating health-seeking behavior in local settings . Adoption of a reduced 4-dose regimen such as the Essen 4-dose or the Zagreb regimen could reduce the number of hospital visits that patients need to make to complete their PEP course , in comparison to the 5-dose Essen regimen currently recommended by WHO . In several Asian countries ID regimens are being used that can reduce the total volume of vaccine required by up to 80% , and also only require 4 hospital visits [37] . However , even with the adoption of reduced 4-dose regimens ( IM or ID ) indirect costs alone would still be between US$ 40–50 . This is equivalent to almost 20% of the average annual income in rural Tanzania , and is therefore unaffordable for many rural Tanzanians . For patients bitten by healthy animals , follow up of the biting animal ( vaccination status and 10-day observation period ) could be used to discontinue PEP and reduce costs . However , our study shows that clinicians would require training to provide this advice as on some occasions discontinuation of PEP was given when the biting animal was suspect for rabies . It is not clear why the Tanzanian government generally administers a 3-dose regimen , but we did not find any deaths as a result of this unconventional regimen , which suggests that further research into reduced dose regimens is warranted . In Tanzania , although the government aims to provide PEP free-of-charge , budgets allocated for this are often insufficient , resulting in shortages . We found that PEP was provided free-of-charge to less than 20% of bite victims , whilst the reminder had to pay , incurring costs that were equivalent to around two months income . If patients fully adhered to recommended regimens these costs would be considerably higher . We show that if PEP was fully subsidized and reduced dose regimens were instead adopted , costs to patients would be substantially reduced . Therefore , it is important for governments to consider strategies that increase accessibility and affordability of PEP to the rural poor who are at the most risk from the disease . This would assist poor families with few assets or little means to pay , especially poor farmers who depend on selling farm outputs to obtain money for PEP . In comparison to the literature , our study suggests that costs of seeking PEP are substantially underestimated . A previous study estimated that a full course of PEP ( direct and indirect costs , excluding those of any patient escorts ) to be US$ 39 . 57 in Africa including 1% of patients receiving RIG [7] . Our results showed that for a full course of PEP excluding RIG , a rural Tanzanian patient would have to pay more than US$100 following a 5-dose regimen , hence we recommend re-evaluation of the burden of rabies in Africa . Furthermore , our study highlighted inequalities such as travel costs for rural patients being more than double than those from urban areas . Our study did not include annual expenditure for rabies control in dogs ( previously estimated at $9 . 7 million ) or the long-term impacts of the death of a household member due to rabies , absence from school by schoolchildren and psychological impacts of exposure and death from the disease . These additional factors are likely to considerably increase the longer-term economic impacts from rabies exposure beyond what has been estimated here . One of the most effective methods to reduce expenditure on PEP is for veterinary services to invest in mass dog vaccination . Studies in northwest Tanzania have demonstrated the impact of mass dog vaccination on reducing animal-bite injuries and demand for PEP [38] , [39] . Strategies to prevent human rabies should therefore also include mass vaccination of domestic dog populations , which maintain the disease . High levels of mass dog vaccination coverage in Africa can be achieved at a relatively low cost , estimated at less than US$2 per dog [39] , [40] which make this a highly effective way to control rabies in the medium- to long-term [41] . If major investments would be made to control rabies in dogs , the majority of African countries could likely afford to subsidize PEP . However , this requires the adoption of a one health approach , involving collaboration and sharing of information between public health and veterinary services for effective rabies control and prevention [42] . Recently we have seen an increased effort by the international community to improve the health of the world's poor . Attention has been focused on the relationship between health and poverty , particularly in relation to the Millennium Development Goals ( MDGs ) [43] . One of the major goals of the MDGs is a 50% reduction in the number of people living in absolute poverty by 2015 . Diseases such as malaria , HIV/AIDS and TB have featured prominently in terms of attracting funding for achieving these goals because they have been prioritized by the international health community and donor agencies due to the high number of fatalities they cause in Africa each year . Rabies is severely neglected and its control is overlooked by authorities . However , this study demonstrated that the burden of rabies for poor households is substantial and calls for national and global attention . Integrating rabies control into Tanzania's National Strategy for Growth and Reduction of Poverty ( NSGRP ) would contribute to meeting the MDGs , particularly of eradicating extreme poverty ( MDG 1 ) and combating HIV/AIDS , malaria , and other diseases ( MDG 6 ) . Specifically our data shows that rabies imposes a disproportionate financial hardship and high risk of dying of rabies to rural poor families because of the need to access costly PEP promptly and highlights the need to re-evaluate the burden of rabies in Africa . | Rabies remains a major public health problem , although the means to control and prevent this disease are available through mass dog vaccination and provision of post-exposure prophylaxis ( PEP ) to people exposed to bites by rabid or suspect rabid animals . Despite its necessity as a life-saving measure to prevent the fatal onset of rabies , access to PEP is a major problem in developing countries . We used extensive investigative interviews to estimate rabies incidence ( deaths and exposures ) and questionnaires to bite victims and their families to investigate health-seeking behaviour and costs associated with receiving PEP , in four districts covering both rural and urban Tanzania . Frequent shortages at health centres limited prompt access to PEP . Suspect bite victims often had to travel long distances to major hospitals to receive costly PEP , causing delays and increasing the risk of developing rabies . We calculated that an average patient in rural Tanzania would need to spend over $100 to complete the WHO recommended PEP schedules , unaffordable for many Tanzanians , who survive under the poverty line . Our data shows that rabies imposes a disproportionate financial hardship and high risk of dying of rabies to rural poor families and highlights the need to re-evaluate the burden of rabies in Africa . | [
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] | [] | 2013 | The Burden of Rabies in Tanzania and Its Impact on Local Communities |
Viral infections of central nervous system ( CNS ) often trigger inflammatory responses that give rise to a wide range of pathological outcomes . The CNS is equipped with an elaborate network of innate immune sentinels ( e . g . microglia , macrophages , dendritic cells ) that routinely serve as first responders to these infections . The mechanisms that underlie the dynamic programming of these cells following CNS viral infection remain undefined . To gain insights into this programming , we utilized a combination of genomic and two-photon imaging approaches to study a pure innate immune response to a noncytopathic virus ( lymphocytic choriomeningitis virus ) as it established persistence in the brain . This enabled us to evaluate how global gene expression patterns were translated into myeloid cell dynamics following infection . Two-photon imaging studies revealed that innate myeloid cells mounted a vigorous early response to viral infection characterized by enhanced vascular patrolling and a complete morphological transformation . Interestingly , innate immune activity subsided over time and returned to a quasi-normal state as the virus established widespread persistence in the brain . At the genomic level , early myeloid cell dynamics were associated with massive changes in CNS gene expression , most of which declined over time and were linked to type I interferon signaling ( IFN-I ) . Surprisingly , in the absence of IFN-I signaling , almost no differential gene expression was observed in the nervous system despite increased viral loads . In addition , two-photon imaging studies revealed that IFN-I receptor deficient myeloid cells were unresponsive to viral infection and remained in a naïve state . These data demonstrate that IFN-I engages non-redundant programming responsible for nearly all innate immune activity in the brain following a noncytopathic viral infection . This Achilles' heel could explain why so many neurotropic viruses have acquired strategies to suppress IFN-I .
The central nervous system ( CNS ) is an immunologically specialized compartment consisting of the brain and spinal cord [1] . These structures are lined by what is referred to as the meninges . Most blood vessels within the CNS are non-fenestrated , meaning the endothelial cells that comprise these vessels are connected by tight junctions which limit the influx of vascular materials into the CNS [2] . Tight junctions are a key feature of the blood brain and blood cerebral spinal fluid barriers that help protect the CNS from peripheral challenges . Despite this elaborate barrier structure , many infectious agents have evolved clever strategies to access the CNS [3] . This tissue must therefore be equipped to mount an immune response to preserve its cellular inhabitants , some of which are non-replicative ( e . g . neurons ) . Because most immune responses begin with pattern recognition or the sensing of “danger” [4] , [5] , tissues often possess elaborate networks of innate immune sentinels that typically serve as the first responders to infectious agents . Despite its immunoprivileged status [6] , the CNS is no different from the periphery in this regard . The most abundant innate immune sentinels in the CNS are referred to as microglia [7] . These cells are ramified and distributed evenly throughout the CNS parenchyma . In addition , recent intravital imaging studies have demonstrated that microglia processes are highly dynamic and continually scan the CNS [8] , [9] . The meninges , choroid plexus , and perivascular spaces in the CNS are also inhabited by specialized macrophages as well as dendritic cells ( DCs ) [10] , [11] , [12] , [13] . Unlike microglia [14] , these cells are hematopoietically-derived and turnover at regular intervals [12] . In fact , a recent study demonstrated that DCs residing in the meninges and choroid plexus are Flt3-ligand responsive and have a 5–7 day half-life [12] . Thus , the innate immune composition of the CNS lining in some ways resembles that observed in peripheral tissues . Because many infectious agents can invade and replicate within the CNS , it is critical that the innate immune sentinels who inhabit this environment be able to respond quickly and provide the inflammatory cues required to recruit a successful adaptive response . It is also imperative that this be accomplished in a minimally injurious manner so as to preserve the integrity of the nervous system . A key element in most innate anti-viral responses is the production of type I interferons ( IFN-I ) [15] , [16] . There are many different IFN-I subtypes ( alpha , beta , delta , epsilon , kappa , omega , tau , zeta ) , but they all bind to the IFN-α receptor ( IFNAR ) , which consists of two chains ( IFNAR1 and IFNAR2 ) . Upon receptor binding , IFN-I can induce an anti-viral state within responding cells [15] , [17] , [18] and facilitate the development of an adaptive immune response by promoting antigen presentation , immune recruitment , etc . The timing and coordination of this response is critical and often dictates that outcome of an infection . In the absence IFN-I , nearly all neurotropic viruses tested acquire a replicative advantage within the CNS and increase their virulence [19] . This explains why so many mammalian viruses have evolved strategies to subvert the IFN-I system [20] , [21] . While the importance of innate immunity in protecting the CNS from neurotropic infections is well recognized [19] , little is known about how the innate immune program translates into cellular dynamics upon viral challenge . It is also unclear to what degree interferons influence the global responsiveness of the virally infected CNS . We sought mechanistic insights into the dynamics of this process by using the lymphocytic choriomeningitis virus ( LCMV ) model system . LCMV is a non-cytopathic arenavirus ideally suited to study pure innate immunity . The virus is detected by retinoic acid-inducible gene I ( RIG-I ) and melanoma-differentiation-associated gene 5 ( MDA5 ) – two cytosolic pathogen recognition receptors [22] . In addition , LCMV does not directly kill the cells it infects in vivo , which eliminates a potential confounding variable associated with release of damage associated molecular pattern molecules ( DAMPs ) from injured cells [23] . Intracerebral inoculation of immunocompetent mice with LCMV results in the development of fatal meningitis at day 6 post-infection , which is due to infiltrating cytotoxic lymphocytes ( CTL ) and myelomonocytic cells [24] . We previously observed that LCMV establishes lifelong persistence in the CNS of mice with a CD8+ T cell repertoire directed against ovalbumin ( OT-I mice ) [25] , [26] . OT-I mice become asymptomatic viral carriers due to their inability to mount either a virus-specific CD8+ or CD4+ T cell response against LCMV [25] . Following intracerebral inoculation , LCMV first replicates in the meninges of OT-I mice and then moves into parenchymal astrocytes over a two month period [26] . At later stages of viral persistence ( 4–5 months ) , LCMV transitions into oligodendrocytes . The reproducibility of this model afforded us the opportunity to study how the brain responds innately to the establishment of a persistent viral infection . Using a combination of genomic and dynamic imaging approaches , we revealed that the brain mounts a vigorous innate response to LCMV that subsides as the virus transitions from the meninges into the parenchyma . Interestingly , we identified an Achilles' heel in the brain's innate defense against this non-cytopathic arenavirus . In the absence of IFN-I signaling , all innate immune gene expression and cellular dynamics were abrogated , which rendered LCMV invisible to its murine host .
Unlike wild type B6 mice , we previously observed that OT-I mice [27] , [28] infected intracerebrally with LCMV do not develop neurological symptoms or fatal meningitis due to an inability to mount an LCMV-specific CD8 or CD4 T cell response [25] , [26] . Instead , LCMV establishes lifelong persistence in the brain and peripheral tissues of OT-I mice , and they remain asymptomatic . Over time the virus transitions from the meninges ( day 15; Fig . 1A ) to the brain parenchyma ( days 60 and 140; Fig . 1A ) . Once within the parenchyma , the virus first replicates in astrocytes ( day 60 ) and later gains access to oligodendrocyes ( day 140 ) [26] . These three time points were therefore selected to represent the different stages of LCMV persistence in a murine host rendered deficient in eliciting an adaptive immune response . To gain insights into the factors associated with LCMV persistence in the nervous system , we first quantified viral loads by plaque assay ( Fig . 1B ) and quantitative-PCR ( Q-PCR ) [29] ( Fig . 1C ) at the denoted time points post-infection . Plaque assay is a measure of infectious virus , and , interestingly , no significant difference in infectious virus was detected at any of the time points ( Fig . 1B ) , despite a major change in viral antigen distribution as demonstrated by immunohistochemistry ( Fig . 1A ) . As virus inundated the brain parenchyma at day 60 , a one log increase ( p<0 . 05 ) in viral genome copies was observed by Q-PCR relative to the day 15 time point ( Fig . 1C ) . No significant differences were detected between days 60 and 140 . The discrepancy between the viral plaque and Q-PCR results suggest that LCMV produces more defective interfering ( non-infectious ) particles upon entering the brain parenchyma . To determine if the shift in LCMV tropism was associated with mutation ( s ) , we next performed sequence analyses on viral clones extracted from the brains of OT-I mice at days 15 , 60 , and 140 post-infection ( Fig . 1D ) . We sequenced the LCMV glycoprotein ( GPC ) , nucleoprotein ( NP ) , and Z protein genes because of their documented participation in viral attachment , fusion , replication , and spreading of infectious virions [30] , [31] , [32] , [33] . Sequencing results of plaque purified clones ( 3 per animal ) revealed no mutations in the Z protein . One viral isolate extracted from the brain of a day 140 mouse had a single amino acid substitution of phenylalanine to leucine ( F260L ) in the GP1 region of GPC . The F260L mutation has been reported in the immunosuppressive strain of LCMV referred as clone 13 and is thought to give this virus a replicative advantage in peripheral tissues ( not the brain ) [32] , [34] . However , this mutation was not observed in any of the other isolates extracted from the day 140 time point . In addition , no GPC mutations were observed at any other time point . Analysis of the nucleoprotein revealed very similar results . A single amino acid substitution from isoleucine to valine at position 323 ( I323V ) was detected in one viral isolate at day 15 and two viral isolates at day 140; however , this mutation was sporadic and not likely to influence viral tropism . Thus , our results demonstrate that LCMV was remarkably stable as it established persistence in the brains of OT-I mice and no consistent mutation could explain the observed tropism shift . Given our inability to explain LCMV tropism through viral mutation , we next sought insights into the innate immune pressures placed on the virus over time . Infection of OT-I mice provided an ideal opportunity to study pure innate immunity without the confounding influences of an adaptive immune response . Gene array analyses were performed on total brain RNA extracted from LCMV-infected OT-I mice at the denoted time points and compared to a mock-infected control group ( Fig . 2 , Table S1 ) . Of the 35 , 556 candidates represented on the microarrays , 585 genes showed a statistically significant ( p<0 . 05 ) difference in expression of at least 1 . 5-fold ( Table S1 ) , and among these 504 had a known gene annotation . As depicted in the heat map ( Fig . 2A ) , most alterations in gene expression ( up or down ) were observed at day 15 post-infection and then returned to baseline levels as LCMV established widespread persistence in the brain parenchyma at later time points ( days 60 and 140 ) . When genes were clustered together based on their pattern of expression ( up-regulation , down-regulation , or no change ) at the different time points post-infection , it was revealed that most genes were up-regulated at day 15 and returned baseline levels by day 140 post-infection ( n = 397 genes ) ( Fig . 2B , Table S1 ) . A small subset of genes were phasic ( n = 33 ) , meaning that they were up at day 15 , back to baseline at day 60 , and up again at day 140 . Most remaining genes were classified into the category of being down-regulated , with the majority being down-regulated at the day 15 time-point ( n = 87 ) . Interestingly , several genes remained down-regulated as LCMV shifted tropism during the last stages of viral persistence ( n = 59 ) . A complete summary of all differentially regulated genes is provided in Table S1 . To establish the identity and interactions between innate immune genes that responded in the LCMV-infected brain , we used Ingenuity Pathway Analysis ( IPA ) software to construct a protein interaction network ( Fig . 2C ) and define the pathways that were most active at the early time point ( day 15 ) post-infection ( Fig . 2D ) . The protein interaction network in Fig . 2C provides a graphical representation of genes identified by IPA as interacting with one another and can be used to infer a coordinated response ( see Table S1 for a complete list of genes used to construct this network ) . Interestingly , at day 15 post-infection , the network was highly dynamic , with most genes being up-regulated ( blue ) . This response was mostly quenched by day 60 and was in fact shifted toward down-regulation ( red ) by the late phase of infection ( day 140 ) . These data suggested that the establishment of LCMV persistence in the brain was associated with a decline in innate immune responsiveness . To gain support for this concept , we next used IPA to identify the top 10 pathways that were active at day 15 post-infection ( Fig . 2D , Table S1 ) . As expected , most active pathways at this time were associated with immunological activity ( e . g . pattern recognition , interferon signaling , antigen presentation , etc ) ; however , a negative impact on nervous system function ( e . g . synaptic long term depression ) was also observed . In fact , several genes responsible for nervous system function remained depressed at day 140 post-infection ( see Table S1 for examples ) . Immunologically , the brain was highly dynamic at day 15 post-infection and showed a very marked signature linked to type I interferon ( IFN-I ) signaling ( Fig . 3A ) . In addition , genes associated with pattern recognition ( Fig . 3B ) , chemoattraction ( Fig . 3C ) , and antigen presentation ( Fig . 3D ) were also highly active , fitting with the development of a robust innate immune response . To validate the microarray data , we performed quantitative PCR analysis for 20 randomly selected immunological genes ( Fig . S1 , S2; Table S2 ) . There were no discrepancies between the microarray and Q-PCR data , which confirmed the fidelity of our microarray approach . Overall , the immunological response to LCMV at day 15 was quite robust and included most of the genes that typically set the stage for an efficient anti-viral response . Interestingly , many genes had returned to baseline expression levels by day 60 , and the entire innate immune response to LCMV was largely silenced by day 140 ( Fig . 3 , S1 , S2 ) . These data demonstrate that an initially robust response to LCMV subsides as the virus establishes long term persistence in the brain . The CNS is equipped with an elaborate network of innate immune sentinels that inhabit the meninges and parenchyma [13] , [35] . Microglia , the most abundant CNS-resident myeloid cells , possess highly dynamic processes that continually scan the extracellular space in the uninflamed brain [8] . In general , myeloid sentinels are among the first responders to CNS perturbations and thus serve as a barometer for the state of immunological activity in this tissue . Our microarray data established a time line during which innate immune gene expression subsided as LCMV established persistence . To determine how innate myeloid cells responded to LCMV over this time line , we imaged the meninges and underlying brain parenchyma of infected vs . mock-infected OT-I CX3CR1-GFP+/− mice through a surgically thinned skull window [36] using intravital two-photon laser scanning microscopy ( TPLSM ) [24] , [35] . CX3CR1-GFP+/− reporter mice [37] were used because brain-resident ( e . g . microglia , meningeal macrophages , etc . ) as well as circulating ( e . g . monocytes ) myeloid cells can be visualized [37] . At day 15 post-infection , we observed a marked transformation in the morphology and dynamics of CX3CR1-GFP+/− cells ( primarily microglia ) in the brain parenchyma ( Fig . 4A–B; Movie S1 ) . Relative to mock-infected controls , microglia from day 15 mice had enlarged somas , were amoeboid in shape , and had retracted cell processes . This was quantified by measuring microglia branch length and complexity in TPLSM z-stacks ( Fig . 4C , E , F; Movie S2 ) . These data revealed a statistically significant reduction ( p<0 . 05 ) in microglia branch length ( Fig . 4E ) and complexity ( Fig . 4F ) at day 15 post-infection , which is indicative of activation . In addition , the luminal surface of blood vessels was heavily patrolled by GFP+ cells ( presumably monocytes ) at day 15 ( Fig . 4D , Movie S3 ) . Quantification revealed a nearly 2 log increase in the number of GFP+ cells scanning the vasculature at this time ( Fig . 4G ) . By day 60 post-infection , the CX3CR1-GFP+/− microglia retained their enlarged , amoeboid morphology ( Fig . 4A–C , E–F; Movie S1 ) ; however , vascular patrolling had declined to the levels observed in mock-infected control mice ( Fig . 4G; Movie S3 ) . Interestingly , at day 140 post-infection , despite extensive viral persistence , myeloid cell activity in the brain had returned to a quasi-normal state ( Fig . 4; Movies S1 , S3 ) . Although microglia branch length and complexity was slightly reduced , the values were comparable to that observed in mock-infected control mice ( Fig . 4E , F ) . Vascular patrolling had also returned to baseline levels ( Fig . 4G ) . These data indicate that myeloid cell dynamics over time mirrored the pattern of innate immune gene expression following LCMV infection , with both subsiding as the virus established persistence in the parenchyma . Because our microarray data revealed a gene expression signature that was linked in part to IFN-I signaling , we next quantified the expression of IFN-α ( 13 subsets using universal primers ) [38] and IFN-β1 in the brain by Q-PCR ( Fig . 5A , B ) . At day 15 post-infection , a significant ( p<0 . 05 ) 26-fold increase in IFN-β1 expression was detected in the brain and IFN-α expression trended upward , although it did not reach statistical significance . IFN-β1 levels dramatically declined by day 60 post-infection and returned to baseline by day 145 post-infection . To evaluate whether IFN-I exerted anti-viral pressure on LCMV during the early or late stages of viral persistence , we quantified viral loads in OT-I mice lacking the IFN-I receptor ( OT-I IFNR−/− ) . Increased viral loads were observed in the serum of OT-I IFNR−/− at all time points post-infection , demonstrating that peripheral viral loads are influenced by IFN-I ( Fig . 5C ) . Interestingly , viral titers were significantly increased ( p<0 . 05 ) in the brains of OT-I IFNR−/− only at day 15 post-infection ( Fig . 5D ) . No difference was noted at day 145 , which was consistent with the reduction of IFN-I to baseline levels by this time point ( Fig . 5A , B ) . These data suggested that IFN-I exerted anti-viral pressure only during the early stages of LCMV persistence in the brain . To directly test this assertion , we measured the degree to which LCMV penetrated the brain parenchyma in OT-I vs . OT-I IFNR−/− at day 15 post-infection . This was accomplished by flow cytometrically quantifying the percentage of microglia ( a representative parenchyma cell ) that contained LCMV antigen . In the absence of IFNR , a marked increase in the percentage of LCMV+ microglia was detected ( Fig . 5E , F ) , suggesting that the virus was able to invade the parenchyma more efficiently . This ultimately resulted in a greater abundance of viral antigen in the brain parenchyma during the late stage ( day 140 ) of persistence ( Fig . 5G ) . The IFN-I expression pattern and its anti-viral activity in the brain supported a role for this innate cytokine in the defense against LCMV . However , the impact of IFN-I on the global anti-viral program remained unclear . To address this question , we used a microarray approach to quantify the genes that were differentially regulated in the brains of LCMV-infected OT-I vs . OT-I IFNR−/− at early and late stages of persistence ( Fig . 6 , Table S1 ) . Surprisingly , deletion of IFN-I signaling resulted in near complete inactivation of the entire anti-viral program at days 5 , 15 , and 140 post-infection . At day 5 post-infection , 137 annotated genes were differentially expressed in OT-I mice relative to the mock-infected control group . Among these only three genes were upregulated in IFNR−/− mice: LCN2 ( 2 . 46-fold ) , H2-K1 ( 1 . 73-fold ) , and GBP4 ( 1 . 66-fold ) . The number of annotated , differentially expressed genes increased to >500 by day 15 post-infection in OT-I mice; however , only 1 gene ( HSPA1b ) was upregulated in IFNR−/− mice , which is not associated with immune function . In fact , focused heat maps revealed that no innate immune genes were up- or down-regulated in IFNR−/− mice at day 15 or 140 post-infection besides VCAM1 and CCL21b ( Fig . 6C ) . Further analyses at day 140 post-infection uncovered only 3 additional upregulated genes ( SCRG1 , LY86 , SFT2D2 ) in IFNR−/− mice . In essence , LCMV became invisible in the brain of its murine host . These data indicate that almost all differential gene expression observed in LCMV-infected brains is either directly or indirectly linked to IFN-I signaling . Given that IFN-I induced all gene expression in the LCMV-infected brain , we set out to determine whether this pathway was responsible for innate myeloid cell dynamics . This is a particularly important question because innate immune cells like microglia can respond within minutes to soluble cues ( e . g . ATP mediated purinergic receptor signaling ) [9] that do not necessarily require changes in gene expression . To address how CNS myeloid cells respond to LCMV in the absence of IFN-I signaling , we imaged the brains of OT-I IFNR−/− CX3CRI-GFP+/− mice by TPLSM at day 15 post-infection – a time point when a robust innate myeloid response is typically observed ( Fig . 4 ) . Interestingly , our TPLSM studies revealed that IFNR−/− mice were completely unable to sense and respond dynamically to LCMV ( Fig . 7; Movie S4 ) . In the absence of IFN-I signaling , microglia remained ramified and their branch length and complexity was comparable to that observed in mock-infected control mice ( Fig . 7A–D ) . This was particularly interesting given that the percentage of LCMV-infected microglia increased 2-fold in IFNR−/− mice ( Fig . 5E , F ) ; thus , there was a greater potential for these cells to be directly stimulated by LCMV . As another measure of innate myeloid activity , we quantified the amount of vascular patrolling by CX3CRI-GFP+/− cells in the presence or absence of IFNR−/− ( Fig . 7E ) . Similar to the microglia data , vascular patrolling in IFNR−/− was comparable to that observed in mock-infected controls . In concert , these results indicate that IFN-I signaling not only induces gene expression but is also responsible for innate myeloid cell dynamics following LCMV infection of the brain .
Innate protection of the CNS is mediated by an elaborate network of innate immune sentinels that consist of microglia , specialized macrophages , and DCs [13] . These often serve as the first responders against invading infectious agents and must hold these microbes in check prior to the arrival of adaptive immune cells . In this study , we unexpectedly uncovered that the brain has an Achilles' heel in its defense against a non-cytopathic arenavirus . Specifically , all gene expression and innate myeloid cell dynamics were completely abrogated in the absence of IFN-I signaling . That LCMV induced an IFN-I signature of gene expression in the brain was not surprising given that the virus is detected by RIG-I/MDA5 and is known to trigger IFN-I production [22] . It was not predicted , however , that all differentially regulated genes ( both up and down ) would be linked exclusively to this pathway . During the early stage of infection , when LCMV localized primarily to the meninges and superficial parenchyma , a robust innate response was observed at the genomic and cellular levels . At this time point , 5 logs of infectious virus were detected in the brain , 585 genes were differentially regulated , microglia had transformed morphologically , and vascular patrolling by innate myeloid cells was markedly elevated . These were all indicators of a successful innate response . During the later stages of persistence , no consistent pattern of viral mutation was observed , nor was there any gain in the efficiency of infectious virion generation . However , both IFN-β synthesis and the network of innate immune gene expression were largely silenced as the virus moved into the brain parenchyma . This coincided with the restoration of myeloid cell dynamics to a quasi-normal state by 140 days post-infection , suggesting equilibration between LCMV and its murine host . Importantly , when IFNR−/− mice were infected with LCMV , no anti-viral response was observed at the genomic or dynamic levels despite increased viral loads and infection of microglia . These data indicate that the brain has only one way to respond innately to LCMV . This Achilles' heel has in turn been exploited by LCMV and most other arenaviruses , which were demonstrated in vitro to suppress IFN-I synthesis and signaling [22] , [39] , [40] , [41] . This could also explain why many other neurotropic viruses have acquired strategies to dampen the IFN-I pathway [20] . Because LCMV showed no discernable mutation pattern as it invaded the brain , we focused instead on the evolution of the innate inflammatory response , which is known to influence the tropism and virulence of many neurotropic viruses [19] . During the early stages of persistence , LCMV elicited a classic innate response that appeared capable of supporting a successful adaptive response ( which never followed due to the restricted T cell repertoire in OT-I mice ) . The innate program was coordinated and highly interactive . In fact , 170 gene products were assembled into a protein interaction network identified using IPA software ( see Table S1 for individual genes ) . Genes associated with pattern recognition ( e . g . TLR2 , TLR3 , TLR7 , MyD88 , RIG-I , PKR , MDA-5 ) , antigen presentation ( e . g . MHC I , MHC II , B2M , TAP1 , TAP2 ) , chemoattraction ( e . g . CCL2 , 3 , 5 , 7 , 9 , 10 ) , and IFN-I signaling ( e . g . IRF7 , IRF8 , IRF9 , STAT1 , STAT2 ) were all highly expressed at this time point ( refer to Table S1 for a complete list ) . Innate anti-viral genes were also highly expressed at day 15 . Some of the best described anti-viral factors included dsRNA activated protein kinase ( PKR ) , 2′-5′ oligoadenylate synthatases ( OAS1g , OAS1b , OAS2 and OASL ) , and 3′ to 5′ exonuclease specific to ssRNA ( ISG-20 ) . We also observed increased expression of several other anti-virals , which include but are not limited to bone marrow stromal cell antigen 2 ( BST-2 ) , viperin , interferon-induced transmembrane protein 3 ( IFITM3 ) , interferon-induced protein with tetratricopeptide repeats 1 ( IFIT1 ) , guanylate binding protein 2 ( GBP-2 ) , and the anti-viral helicase , DDX-60 . Studies have shown that these gene products directly interfere with the replication of several mammalian viruses , including human immunodeficiency virus ( BST-2 ) [42] , influenza A ( viperin ) [43] , Influenza A/West Nile/Dengue virus ( IFITM3 ) [44] , [45] , vesicular stomatitis virus/encephalomyocarditis virus ( GBP2 ) [46] , and hepatitis C virus ( DDX-60 ) [17] . However , the importance of these factors in restricting the replication of LCMV in the brain remains unknown . Recent studies have demonstrated that IFN-I induces expression of many different anti-viral factors , some broadly acting and others with targeted specificity [17] . Given the breadth of factors uncovered at day 15 , it is likely that IFN-I expression induces a generic anti-viral state in the brain capable of handling a variety of different infections . As LCMV moved into the deeper brain parenchyma , a dramatic reduction in IFN-β production and overall innate immune gene expression was observed . During this transition , the number of viral genome copies increased , but the amount of infectious virus remained constant , suggesting that defective interfering particles were generated [47] , [48] . A previous study demonstrated that LCMV downregulates GP expression during persistence in the CNS [49] , which could explain the stable set point of infectious virus observed in the brains of OT-I mice over time . Even more interesting , however , was the steady decline in innate immune gene expression that proceeded to a near complete silencing by the late stage of persistence ( day 140 ) . There are two conceivable explanations for this result . First , there are many negative regulators of IFN-I production [50] , and we found that two were increased in expression at days 5 and 15 post-infection ( NLRC5 and TRIM21 ) . NLRC5 is a NOD-like family protein recently shown to block phosphorylation of IκB kinase ( IKK ) complex , which in turn reduces nuclear factor κB ( NF-κB ) activation [51] . NLRC5 also interacts with RIG-I/MDA5 and impedes their function . Importantly , siRNA mediated silencing of NLRC5 resulted in increased IFN-I production by VSV-infected cells [51] . The other negative regulator detected in the brains of OT-I mice was the E3 ligase Ro52 ( TRIM21 ) . This protein was shown to interact with IRF3 and promote its degradation , thus decreasing IFN-β promoter activity [52] . The upregulation of both NLRC5 and TRIM21 at days 5 and 15 could explain the decline in IFN-I expression by day 60 . Because chronic IFN-I production has the potential to disrupt neurological function , negative regulation could be a strategy used by the brain to quench the innate response . Another explanation for the decline in CNS immune activity is that LCMV and most other arenaviruses tested can dampen IFN-I production [22] , [39] , [40] , [41] . This activity maps to the C-terminal region of the LCMV NP [39] , [40] , which binds to the kinase domain of IKKε preventing it from phosphorylating IRF3 [41] . This consequently reduces the production of IFN-β . Given that most arenaviruses have acquired a similar strategy to quench IFN-I production , it is likely that this property provides a replicative advantage in vivo and perhaps an improved ability to equilibrate with their host during persistence . Of particular interest in the brain is the fact that the entire gene expression profile following LCMV infection is linked to IFN-I signaling . We detected no differentially regulated genes in IFNR−/− mice , and the virus was able to more efficiently invade the brain parenchyma . Thus , it seems reasonable to conclude that LCMV has evolved a strategy to mirror an IFN-I receptor knockout mouse , because this is the only innate pathway available to the brain following infection . This theory is further supported by studies showing that the IFN-I signature is also minimal in mice persistently infected from birth with LCMV ( referred to as carrier mice ) [53] , [54] . Therefore , suppression of IFN-I appears to be a cardinal feature of LCMV persistence . At the dynamic level , the innate myeloid response to LCMV was also quite fascinating . Recent TPLSM studies have demonstrated that brain resident myeloid cells like microglia are remarkably dynamic ( even in the naïve brain ) and can rapidly respond to inflammatory challenges [8] , [9] . To date , investigators have focused primarily on microglial responses to parenchymal injuries . Following laser injury , for example , microglia were shown to extend processes within minutes toward the site of damage , and this response was dependent on purinergic receptor signaling [8] , [9] . At the outset of our studies , it was unclear whether brain myeloid cells would respond similarly to a viral infection . Interestingly , we observed that microglia responded innately to a LCMV infection by transforming into an amoeboid morphology and reducing branch length/complexity . This program is likely set into motion to sequester virus and facilitate antigen presentation , which is supported by our microarray data showing that many anti-viral and antigen presentation genes are up-regulated at day 15 . We also observed a marked increase in vascular patrolling by myeloid cells at this time point , fitting with increased expression of the adhesion molecule , VCAM1 , as well as production of myelomonocytic recruiting chemoattractants like CCL2 , 3 , and 5 . CX3CR1-GFP+/− monocytes were shown previously to patrol the luminal surface of blood vessels [55] , and these cells are known to enter the brains of LCMV-infected mice [24] . Based on our imaging , genomic , and knockout data , IFN-I initiates the program that facilitates the arrival of innate myeloid cells . Over time , however , myeloid cell dynamics subside in the LCMV-infected brain , eventually returning to a quasi-normal state despite widespread viral persistence . This coincided with a decline in IFN-I production , which suggested that IFN-I ( rather than purinergic ) signaling was responsible for all innate myeloid cells dynamics . We proved this definitively by studying immune cell dynamics in IFNR−/− mice . In the absence of IFN-I signaling , innate myeloid cells in the LCMV-infected brain behaved similarly to mock-infected controls . This result demonstrated that IFN-I alone orchestrated all innate immune gene expression and myeloid cell dynamics following LCMV infection , which is surprisingly rare example of a tissue having no redundant mechanisms in place to mount a response . We believe that the implications of findings are broad and may facilitate the design of therapeutics to increase or decrease anti-viral immunity in the CNS . The importance of IFN-I signaling in the LCMV model was clearly demonstrated by Muller and colleagues who showed that IFNR−/− mice do not develop LCMV induced meningitis , but instead become asymptomatic viral carriers [56] . Based on our findings , this result is likely explained by a near complete shutdown of all innate immune activity in the brains of IFNR−/− mice . Recent studies have also shown using a murine model of cerebral malaria induced by the parasite , plasmodium berghei , that IFNR−/− mice do not develop fatal disease [57] . AT-rich motifs in the plasmodium genome trigger IFN-I production , which appears to facilitate the development of cerebral malaria . Thus , it will be important to identify the innate immune signature induced in the brains of plasmodium infected mice in the presence or absence of IFN-I signaling . It will also be important to determine how much the brain relies on IFN-I for its response to other neurotropic viruses . A recent study demonstrated that IFN-I production by innate myeloid cells in the lymphatics can protect peripheral nerves from a fatal VSV infection [58] , but it remains to be determined whether IFN-I is the exclusive pathway used to innately protect the nervous system . Our prediction is that cytopathic neurotropic viruses will trigger other innate pathways in the brain due to the release of DAMPs associated with direct cellular injury . Detection of non-cytopathic viruses , on the other hand , may be more dependent on IFN-I release . Arenaviruses like LCMV appear to exploit this fact to become invisible in their hosts . We too may be able to exploit the brains exclusive reliance on IFN-I to develop therapies that modulate immunity to CNS infections .
C57BL/6 ( B6 ) , B6-Tg ( TcraTcrb ) 1100Mjb/J ( OT-I ) [27] , [28] , and B6 CX3CR1-GFP+/+ [37] mice were purchased from The Jackson Laboratory . OT-I and CX3CR1-GFP+/+ mice were then maintained in a closed breeding facility at The National Institutes of Health ( NIH ) . B6 IFN-I receptor−/− ( IFN-IR−/− ) [56] mice were generously provided by Dr . Jonathan Sprent ( formerly at The Scripps Research Institute ) . OT-I IFN-IR−/− , OT-I CX3CR1-GFP+/− and OT-I IFN-IR−/− CX3CR1-GFP+/− mice were generated by interbreeding the aforementioned strains . This study was carried out in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health . The protocol was approved by the NINDS Animal Care and Use Committee ( Assurance Number: 1295-12 ) . All experimental procedures were performed under anesthesia and conducted in a manner minimize suffering . Animals 6–8 weeks old were intracerebrally ( i . c . ) infected with 103 PFU LCMV Armstrong ( Arm ) . Stocks were prepared by single passage in BHK-21 cells at a low multiplicity of infection ( MOI of 0 . 01 ) , and the titer was determined by plaque assay in Vero cells . Brain tissue extracted from mice that received an intracardiac perfusion with 25 ml of saline were homogenized in 1 ml of RPMI and centrifuged at 16 , 000 g for 5 min . The supernatant fraction was used to determine the viral titer by plaque assay on Vero cells . Subsequently , plaque purified viral isolates were selected for RNA extraction using a PureLink Viral RNA/DNA mini kit ( Invitrogen ) . The RNA was then reverse transcribed and PCR amplified by using gene specific primers . The following primers were used for PCR amplification and sequencing: GPC-Fwd ( ATGGGTCAGATTGTGACAATG ) , GPC-660Fwd ( CATGATTTACATTGCATTTC ) , GPC-Rev ( TCAGCGTCTTTTCCAGACGG ) , Z-Fwd ( GCACCGGGGATCCTAGGC ) , Z-Rev ( GTGTGTGTGTGTGGGTGTGCGTG ) , NP-Fwd ( ATGTCCTTGTCTAAGGAAG ) , NP526-Fwd ( CAATCAATTTGGCACAATGC ) , NP1215-Fwd ( CGTTGATCAAAAACAATTCAAG ) , NP-Rev ( TTAGAGTGTCACAACATTTGGG ) . The pellet fraction from the homogenized brain was treated with Trizol ( Invitrogen ) and total RNA was extracted by using a PureLink RNA mini kit ( Invitrogen ) . One µg of RNA was then treated with amplification grade DNAse I ( Invitrogen ) and reverse transcribed with iScript ( Bio-Rad ) reverse-transcription reagent kit , which contains a mixture of oligo ( dT ) primers and random hexamers without any gene specific primers . All the Q-PCR reactions were performed in 20 µl volumes using SoFast EvaGreen super mix ( Bio-Rad ) in a 96-well optic tray on a CFX96 Real-Time PCR machine ( Bio-Rad ) . The reactions were conducted in triplicate , and samples without reverse transcriptase were used as a non template control . The Q-PCR cycling conditions were as follows: initial denaturation at 95°C for 3 min followed by 40 cycles with denaturation at 95°C for 10 seconds , annealing for 10 seconds and extension at 72°C for 20 seconds . The optimal annealing temperature for gene specific primers ( see Table S2 ) was determined prior to the experimental runs . The housekeeping gene beta-actin was used as a reference . For determination of viral genome copy number , Q-PCR for the LCMV glycoprotein was conducted using 10 ng of cDNA and referenced to known quantities of linearized LCMV S-segment plasmid DNA as described previously [29] . To visualize LCMV antigen , 6-µm frozen sagittal brain sections were cut with a cryomicrotome and fixed for 10 min with 4% paraformaldehyde in PBS . Sections were then treated with an avidin-biotin blocking kit ( Vector Laboratories ) per the manufacturer's instructions and incubated overnight at 4°C with a rat anti-LCMV nucleoprotein monoclonal antibody ( 1∶1000 dilution; VL-4 clone , BioXcell ) . Following the incubation with primary antibody , sections were washed , incubated with a biotinylated anti-rat secondary ( 1∶400; 1 hr room temperature; Jackson ImmunoResearch ) , washed , and incubated with streptavidin-Rhodamine Red X ( 1∶400; 1 hr room temperature; Jackson ImmunoResearch ) . Lastly , all sections were stained with 1 µg/ml 4′ , 6′-diamidino-2-phenylindole ( DAPI; Sigma-Aldrich ) to visualize cell nuclei . All working stocks of primary and secondary reagents were diluted in PBS containing 2% FBS . Two-color reconstructions of sagittal brain sections ( Fig . 1A and 5G ) were generated using a Zeiss Z1 inverted epifluorescence microscope fitted with an automated xyz stage , an Axiocam digital camera , and a 5× objective ( Carl Zeiss Microscopy ) . Individual images were assembled into a composite image using a mosaic feature in the Axiovision acquisition software ( Version 4 . 8 , Carl Zeiss Microscopy ) . For intravital imaging experiments , mice were anesthetized and maintained at a core temperature of 37°C . To generate a viewing window into the brain , skull bones were thinned as described previously [36] , [59] . Prior to imaging , mice were injected intravenously with 100 µl normal saline containing Qtracker non targeted quantum dots ( 655 nm; 0 . 2 µm; Invitrogen ) . All 4D imaging data were collected using a Leica SP5 two-photon microscope ( Leica ) equipped with an 8 , 000-Hz resonant scanner , a 20×/1 . 0 NA water-dipping objective , and a Mai Tai HP DeepSee Laser ( Spectra-Physics ) tuned to 920 nm . Fluorescence emission was separated by high-efficiency custom dichroic mirrors ( Semrock ) and collected with an NDD4 external detector ( Leica ) . Static 3D images were captured using a z step size of 1 µm to a depth of 100 µm beneath the skull bone . 3D time lapses were captured at the same depth using a 2 . 5 µm z step size and a 1 min time interval . All quantitative analyses of two-photon data were performed using Imaris 7 . 3 software ( Bitplane ) . Microglia were identified as branched GFP+ cells residing in the brain parenchyma of CX3CR1-GFP+/− reporter mice and selected randomly by first using the “spots” function in Imaris to identify all cell bodies in a given volume . The identification numbers of each cell were then entered into a randomizer after which individual microglia were sequentially selected from the randomized list for quantification . Only microglia whose processes were all within the field of view were quantified . Microglial branch length and the number of termini were quantified using the “FilamentTracer” feature in Imaris . Branch endpoints , bifurcations , and initiation points were identified on each cell manually and connected using the “FilamentTracer” tool ( see Fig . 4C for examples ) . The resultant tracings were then used to calculate the total process length ( µm ) and number of terminal branch points per process . A process was defined as an extension originating from the cell body of a microglia . To calculate the number of CX3CR1-GFP+/− cells per unit volume of cerebral vasculature , the “surfaces” tool in Imaris was used to generate volume renderings of blood vessels visualized by intravenously injected 655 nm quantum dots . After calculating vascular volumes ( mm3 ) , the CX3CR1-GFP+/− cells were counted manually in individual vessels at three time points ( 0 min , 30 min , and 60 min ) . This number was then averaged and divided by the vascular volume to obtain cells per mm3 of blood vessel . Single cell suspensions of brain and spleen were performed after intracardiac perfusion of anesthetized mice with 25 ml of normal saline to remove the contaminating blood lymphocytes . To isolate brain infiltrating leukocytes , minced brains were incubated with 1 ml of collagenase D ( 1 mg/ml; Roche ) at 37°C for 30 min followed by mechanical disruption through a 100 µm filter . Homogenates were then resuspended in 4 ml of 90% Percoll ( GE Healthcare ) in HBSS , and a Percoll gradient was prepared by overlaying 3 ml of 60% Percoll , 4 ml of 40% Percoll , and 3 ml of 1× HBSS , respectively . The gradients were then centrifuged at 1700 rpm for 20 min at 4°C , after which the band ( interface between 60% and 40% Percoll ) corresponding to mononuclear cells was isolated , and a single cell suspension was prepared by washing these cells with 1× HBSS followed by RPMI . Splenocytes were prepared by mechanical disruption through a 100 µm filter , which were then treated with red blood cell lysis buffer ( ammonium chloride; 0 . 02 M Tris-HCl and 0 . 14 M NH4Cl; pH 7 . 2 ) and washed twice before staining . For all tissues , the absolute number of mononuclear cells was determined prior to flow cytometric analysis . Mononuclear cells isolated from different organs were blocked with 3 . 3 µg/ml anti-mouse CD16/CD32 ( Fc block; BD Biosciences , clone 2 . 4G2 ) in PBS containing 1% FBS for 20 min prior to antibody staining . Single cell suspensions were stained with the following antibodies: anti-CD45 . 2-FITC ( BD Bioscience , clone 104 ) , CD8-Pacific Blue ( Invitrogen , clone 5H10 ) , CD4-Qdot 605 ( Invitrogen , clone RM4-5 ) , CD11b-PE-Cy7 ( eBioscience , clone M1/70 ) , Gr1-APC ( BD Bioscience , clone RB6-8C5 ) , CD11c-APC-Cy7 ( Biolegend , clone N418 ) , Thy1 . 2-Alexa Fluor 700 ( Biolegend , clone 30-H12 ) , NK1 . 1-PerCP Cy5 . 5 ( BD Bioscience , clone PK136 ) , and CD45 . 2-APC-Cy7 ( BD Bioscience , clone 104 ) . For detection of intracellular LCMV , cells were fixed with 4% PFA , permeabilized with 0 . 1% saponin , and stained with a rat anti-LCMV nucleoprotein monoclonal antibody ( VL-4 clone , BioXcell ) directly conjugated to Alexa Fluor 647 using an antibody labeling kit ( Invitrogen ) . Cells were acquired using a digital flow cytometer ( Digital LSR II; BD ) and flow cytometric data were analyzed with FlowJo software ( Version 9 . 0 , Tree Star , Inc ) . Samples were prepared according to Affymetrix protocols ( Affymetrix , Inc ) . RNA quality and quantity was ensured using the Bioanalyzer ( Agilent , Inc . ) and NanoDrop ( Thermo Scientific , Inc . ) respectively . For RNA labeling , 200 nanograms of total RNA was used in conjunction with the Affymetrix recommended protocol for the GeneChip 1 . 0 ST chips . The hybridization cocktail containing the fragmented and labeled cDNAs was hybridized to the Affymetrix Mouse Genome ST 1 . 0 GeneChips . The chips were washed and stained by the Affymetrix Fluidics Station using the standard format and protocols as described by Affymetrix . The probe arrays were stained with streptavidin phycoerythrin solution ( Molecular Probes , Carlsbad , CA ) and enhanced by using an antibody solution containing 0 . 5 mg/mL of biotinylated anti-streptavidin ( Vector Laboratories , Burlingame , CA ) . An Affymetrix Gene Chip Scanner 3000 was used to scan the probe arrays . Gene expression intensities were calculated using Affymetrix AGCC software . Gene fragment data summarization and normalization was accomplished using the Expression Console with the “RMA Sketch” option selected ( Affymetrix , Inc ) . Quality was assured via Tukey box plot , PCA scatter plot and correlation-based heat map using functions in “R” ( www . cran . r-project . org ) . Locally Weighted Scatterplot Smoothing ( Lowess ) modeling of the data ( coefficient of variation modeled by mean expression ) was used to characterize noise for the system and discard noise-biased data . Differential expression was tested for via ANOVA under BH correction conditions followed by a TukeyHSD post-hoc test . Gene fragments found to have a corrected p-value<0 . 05 by ANOVA and a post-hoc p-value<0 . 05 were deemed to have significant differential expression between the corresponding cell types if the absolute difference of means was ≥1 . 5-fold . Gene annotations were assigned where possible using MGI ( www . informatics . jax . org ) and IPA ( www . ingenuity . com ) . IPA was also used to generate a protein interaction network comparing differential expression in LCMV- versus mock-infected mice at days 15 , 60 , and 140 post-infection ( Fig . 2C ) . Biological function associations were assigned using AmiGO ( amigo . geneontology . org ) and the differential expression for select functions depicted using the enhanced heat map function in “R” ( heatmap . 2 ) . Genes downstream of IFN-I signaling were assigned using a combination of gene lists obtained from AmiGO and IPA . Statistical significance ( p<0 . 05 ) was determined in SigmaPlot 11 . 0 using a one-way ANOVA for normally distributed data or an ANOVA on ranks for populations with non-Gaussian distributions . Graphs were generated using SigmaPlot 11 . 0 and GraphPad Prism 5 . 04 . | The central nervous system is equipped with innate immune cells that serve as first responders to sterile injuries and infections . The mechanisms that program the movement and morphological transformations of these cells following infection remain undefined . Here , we utilized a combination of genomic and in vivo imaging approaches to define pathways that program the motion of innate immune cells responding to a noncytopathic virus as it established persistence in the brain . In vivo imaging studies performed in the living brain revealed that innate myeloid cells mounted a vigorous early response that returned to a “naïve” state during persistence . This was associated at the genomic level with robust changes in gene expression that were mostly quenched over time . Analysis of the gene expression pattern revealed a prominent type I interferon ( IFN-I ) signature only at the early stage of infection . Surprisingly , in the absence of type I interferon ( IFN-I ) signaling , almost no genes were differentially expressed in the virally infected nervous system and all innate myeloid cells were unresponsive . These data indicate IFN-I programs all innate myeloid activity in the nervous system following a noncytopathic viral infection . This non-redundant anti-viral program represents an Achilles' heel that can be exploited by neurotropic viruses . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] | [
"neuroscience",
"immunology",
"biology"
] | 2013 | Type I Interferon Programs Innate Myeloid Dynamics and Gene Expression in the Virally Infected Nervous System |
Pentavalent antimonials have been the first line treatment for dermal leishmaniasis in Colombia for over 30 years . Miltefosine is administered as second line treatment since 2005 . The susceptibility of circulating populations of Leishmania to these drugs is unknown despite clinical evidence supporting the emergence of resistance . In vitro susceptibility was determined for intracellular amastigotes of 245 clinical strains of the most prevalent Leishmania Viannia species in Colombia to miltefosine ( HePC ) and/or meglumine antimoniate ( SbV ) ; 163 , ( 80% ) were evaluated for both drugs . Additionally , susceptibility to SbV was examined in two cohorts of 85 L . V . panamensis strains isolated between 1980–1989 and 2000–2009 in the municipality of Tumaco . Susceptibility to each drug differed among strains of the same species and between species . Whereas 68% of L . V . braziliensis strains presented in vitro resistance to HePC , 69% were sensitive to SbV . Resistance to HePC and SbV occurred respectively , in 20% y 21% of L . panamensis strains . Only 3% of L . V . guyanensis were resistant to HePC , and none to SbV . Drug susceptibility differed between geographic regions and time periods . Subpopulations having disparate susceptibility to SbV were discerned among L . V . panamensis strains isolated during 1980–1990 in Tumaco where resistant strains belonged to zymodeme 2 . 3 , and sensitive strains to zymodeme 2 . 2 . Large scale evaluation of clinical strains of Leishmania Viannia species demonstrated species , population , geographic , and epidemiologic differences in susceptibility to meglumine antimoniate and miltefosine , and provided baseline information for monitoring susceptibility to these drugs . Sensitive and resistant clinical strains within each species , and zymodeme as a proxy marker of antimony susceptibility for L . V . panamensis , will be useful in deciphering factors involved in susceptibility and the distribution of sensitive and resistant populations .
Pentavalent antimonial drugs , ( sodium stibogluconate and meglumine antimoniate ) have been the first-line monotherapeutic treatment for dermal leishmaniasis in Central and South America for decades . Parenteral administration , volumes of drug requiring divided doses in adults , frequent and potentially severe adverse effects , and the logistical challenges of accessing medical supervision of therapy contribute to interruption and abandonment of treatment , clinical failure , and loss of susceptibility [1] , [2] , [3] . Miltefosine ( hexadecylphosphocholine ) , an oral drug originally developed for treatment of cancer , was approved in 2005 for the treatment of cutaneous leishmaniasis in adults and children in Colombia , and is administered as second line treatment in patients having contraindications or who fail to respond to antimonial drugs . Miltefosine has demonstrated efficacy comparable to pentavalent antimonials against infection caused by Leishmania Viannia panamensis in Colombia [4] , [5] , L . V . guyanensis [6] and L . V . braziliensis in Brazil [7] and L . V . braziliensis in Bolivia [8] . Nevertheless , treatment failures and relapses have been observed for both treatments in these and other randomized controlled clinical trials [5] , [9] . Multiple factors contribute to the outcome of treatment , including those of the host ( immune status , pharmacokinetics , pharmacogenetics , drug metabolism , adherence to treatment ) , pharmacological properties of the drug ( formulation and pharmacodynamics ) and parasite characteristics ( biochemical and molecular differences among species and strains ) [4] , [10] . Evidence for the emergence drug resistance to antimonial drugs [11] , [12] and miltefosine [13] , [14] has been reported for visceral and cutaneous leishmaniasis . Although the role of drug susceptibility in treatment failure has been difficult to establish because therapeutic response is multifactorial , prospective analyses of strains isolated prior to treatment and at failure have demonstrated that loss of susceptibility to antimony and to miltefosine can contribute to treatment failure in dermal leishmaniasis [12] , [13] . Reports based on clinical response to different drugs in diverse geographical settings indicate wide variation in effectiveness [4] , [6] , [7] , [8] , [15] . In Colombia , where L . V . panamensis is the predominant species isolated from civilian patient populations [16] , [17] , [18] , 91% of patients responded to miltefosine treatment , whereas only 53% of patients responded in Guatemala , where L . mexicana and L . V . braziliensis are common [4] . Cutaneous leishmaniasis caused by L . V . braziliensis in Guatemala was highly responsive to sodium stibogluconate [19] whereas disease caused by L . V . guyanensis was poorly responsive to treatment with meglumine antimoniate in Brazil [15] but highly responsive in Peru [20] . Although some of these reports are not based on randomized , controlled clinical trials , they portray the therapeutic response in endemic settings . In vitro evidence of inter species differences in the susceptibility of Leishmania to antileishmanial drugs has also been reported based on small numbers of strains of diverse species isolated from patients with visceral as well as cutaneous disease [21] , [22] . Technical constraints in evaluating EC50 based on intracellular survival of clinical strains of Leishmania have limited routine or large scale assessment of drug susceptibility , and prevented the understanding of drug susceptibility in the context of prevention and control . This large scale study of susceptibility to drugs in use in Colombia documented significant differences in susceptibility to miltefosine and meglumine antimoniate among strains of the same species and between species of the Viannia subgenus , as well as geographic variation in drug susceptibility of populations of these species . Additionally , this analysis demonstrated for the first time , intrinsic differences in the susceptibility to meglumine antimoniate between phenotypically distinct populations of L . V . panamensis .
This study sought to determine the susceptibility of the most prevalent species of Leishmania in Colombia to antileishmanial drugs currently in use , and to explore possible geographic variations in drug susceptibility of the corresponding parasite populations . The in vitro susceptibility of clinical strains of L . V . panamensis , L . V . braziliensis and L . V . guyanensis isolated at diagnosis from patients who acquired infection in foci of transmission in the Pacific , Andean , Orinoquía and Amazon regions of Colombia was evaluated . Since treatment with pentavalent antimonials has been the standard of care in Colombia since 1980 , we also examined whether the susceptibility to SbV of L . V . panamensis , the most prevalent species among civilian patients , changed over the 10 year periods from 1980–1989 and 2000–2009 in two foci of transmission in the municipality of Tumaco on the Pacific coast of Colombia . Clinical and community based studies conducted in Tumaco since 1980 have contributed to the collection and characterization of clinical strains based on isoenzyme polymorphism profiles ( zymodeme ) [16] . These resources and demographic and epidemiologic variables ( residence within focus of transmission , age , sex and occupation ) of the corresponding patients in these endemic foci were exploited to examine epidemiologic associations . All Leishmania Viannia strains were isolated at diagnosis from patients with cutaneous lesions by medical personnel in two national reference centers for leishmaniasis , and cryopreserved in liquid nitrogen in the biobanks of these centers: Centro Internacional de Entrenamiento e Investigaciones Médicas , CIDEIM , Cali , and the Centro Dermatológico Federico Lleras Acosta , CDFLLA , Bogotá , Colombia . In vitro susceptibility was evaluated within four passages from isolation . Species identification was achieved by isoenzyme electrophoresis or indirect immunofluorescence using species-specific monoclonal antibodies as described elsewhere [16] , [17] . Prior to conducting drug susceptibility assays , the species identity was re-confirmed for approximately 70% of the strains included in this study . The proportion of strains of each species that was evaluated was based on the relative prevalence of the species in each of the regions of high transmission; 245 strains were evaluated: 163 for both drugs , plus 41 for SbV only and 41 for HePC only . The number of strains of each species that were evaluated for susceptibility to SbV and/or HePC , is summarized in Table 1 . Additionally , in order to characterize the profile of susceptibility to SbV in an area of high transmission and long-term use of this drug , we evaluated 170 clinical strains of L . V . panamensis isolated from patients residing in transmission foci along the Rosario and Mira rivers; 85 of the 170 strains were isolated between 1980 and 1989 following the initiation of the national leishmaniasis control program , and 85 between 2000 and 2009; 13 of the latter strains were included in the sample of L panamensis evaluated for susceptibility to SbV and HePC from the Pacific Coast region . This study was approved and monitored by the Ethics Committees of CIDEIM and CDFLLA for the use of Leishmania strains and clinical information of the corresponding patients in accordance with national and international guidelines for Good Clinical Practice . Prior written informed consent for the use of information from clinical histories had been obtained at the time of diagnosis from patients included in this study . Internal standards consisting of the sensitive strain ( MHOM/COL/86/1166 ) and the experimentally derived SbV resistant line ( MHOM/COL/86/1166-1000 . 1 ) [23] and HePC resistant line ( MHOM/COL/86/1166-LUC056 ) [24] were included in each experiment to confirm the discriminatory capacity of the assays . The SbV and HePC resistant lines were propagated and maintained in the presence of 1000 µmoles SbIII/L and 60 µmoles HePC/L , respectively . Additive-free meglumine antimoniate ( SbV; Walter Reed 214975AK; lot no . BLO918690-278-1A1W601; antimony analysis , 25%–26 . 5% by weight ) and 1-hexadecylphosphocholine ( HePC; miltefosine; Cayman Chemical Co . , Ann Arbor , MI ) were utilized for in vitro susceptibility evaluation . Trivalent antimony ( SbIII ) as potassium antimonyl tartrate thrihydrate was obtained from Sigma–Aldrich Chemical Company , St . Louis , MO . Susceptibility was determined based on reduction of intracellular parasite burden in U-937 macrophages ( ATCC CRL-159 . 3 ) as described by Fernández et al 2012 [24] . Briefly , 1 . 2×105 U-937 cells were differentiated to macrophages by treatment with phorbol 12-myristate 13-acetate ( PMA; 100 ng/ml; Sigma ) , then infected with promastigotes opsonized with 10% AB positive human serum at a ratio of 5 parasites per macrophage . Infected cells were incubated for 24 hours to allow differentiation of intracellular parasites to amastigotes . Afterwards supernatants were replaced with complete RPMI containing 16 µM HePC or 32 µg SbV/ml . In the case of SbV , medium containing 32 µg SbV/ml was replenished 48 h later and incubation continued for an additional 24 h . HePC exposure was conducted over 48 h without replenishment [24] . Infection was assessed blindly by one of two experienced microscopists who evaluated all slides for this study . Four replicates of infected cells exposed to each drug and unexposed infected control macrophages were evaluated . The number of intracellular amastigotes per cell was determined for 100 macrophages per replica . Susceptibility was expressed as percent reduction of infection , determined by comparing parasite burden of infected cells exposed to the drug versus that of infected cells without drug . The cutoff defining sensitive and resistant strains for each drug in vitro was based upon previously published analyses [24] . However , for the current study , an indeterminate range of parasite reduction was defined based on the absence of data within this range in the dataset used to derive the cutoff . Strains presenting a reduction of parasite burden between 35% and 48% for SbV and between 44% and 56% for HePC , were considered to have indeterminate susceptibility , Supplemental Figure S1 . Therefore in vitro sensitivity or resistance was defined respectively by reduction of parasite burden above or below the indeterminate range for the corresponding drug . In order to examine the relationship between genotypic diversity and drug-susceptibility profiles , the relative genetic diversity and proximity of L . V . panamensis strains pertaining to zymodemes 2 . 2 ( n = 10 ) and 2 . 3 ( n = 10 ) , plus 12 other strains of this species without zymodeme classification from the Pacific coast region , and L . V . guyanensis strains from the Amazon ( n = 9 ) and Andean region ( n = 8 ) were analyzed by multilocus microsatellite typing ( MLMT ) . The geographic distribution of L . V . guyanensis and its principal vector Lutzomyia umbratilis in Colombia , had previously been limited to the Amazon River basin . Therefore , in addition to drug susceptibility , the genetic diversity and relationship of the L . V . guyanensis populations involved in the 2003–2005 epidemic of domestic transmission by Lutzomyia longiflucosa in Chaparral , Tolima in the Andean foothills [25] , [26] and strains of L . V . guyanensis from patients occupationally exposed to sylvatic transmission in the Amazon region were also analyzed . DNA was extracted from log-phase promastigotes using the Quigen Blood & Tissue Kit ( Qiagen , USA ) . Fourteen microsatellites distributed in 13 Leishmania chromosomes were amplified by PCR , as previously described [27] . The size of the microsatellites was determined by mobility of the PCR products in 4 . 5% agarose gels . Genetic distances were estimated using MSA software and populations and neighbor joining trees were constructed using MEGA 5 . Strains of L . Viannia from each region were selected using a simple random sampling technique . To explore differences in susceptibility to SbV and HePC of Leishmania Viannia strains according to species and geographic regions , Kruskal-Wallis ( K-W ) tests and Dunn's post-test for multiple comparisons were performed . Differences in the susceptibility to SbV among L . V . panamensis strains from two endemic foci during two 10-year time periods , and between zymodeme 2 . 2 and 2 . 3 were analyzed using the Mann-Whitney non-parametric test . Association between in vitro susceptibility of L . V . panamensis to SbV and zymodeme , age or occupation was examined using contingency tables ( Chi square ) . Comparison of proportions was calculated using the Z test . Correlation of susceptibility to HePC and SbV was evaluated based on the Spearman test . P values <0 . 05 were considered significant . Data were compiled in Microsoft Excel and analyzed using Prism 5 ( GraphPad , Inc ) .
Susceptibility to SbV and HePC differed among strains of the same species and between species of the ( Viannia ) subgenus ( Figure 1 ) . Quantitative analysis showed that L . V . braziliensis strains were significantly less susceptible to both drugs compared with other ( Viannia ) species . Qualitative analysis with respect to the cutoff thresholds and indeterminate zones of susceptibility in vitro revealed that L . V . guyanensis presented the highest proportion of sensitive strains for both drugs ( 82% , 28/34 for HePC and 86% , 25/29 for SbV ) with only one strain being classified as resistant to miltefosine and none for SbV , whereas L . V . braziliensis exhibited the highest proportion of resistant strains ( 68% 43/63 ) for HePC ( P<0 . 05 ) , yet a high proportion ( 69% , 40/58 ) were sensitive to SbV . The in vitro susceptibility of a comparatively small proportion overall of strains of these species of the Viannia subgenus fell within the indeterminate range: 8% for SbV and 16% for HePC . Analysis of the distribution of susceptibility of strains of each species based on the median and inter-quartile range corroborated the high susceptibility of L . V . panamensis and L . V . guyanensis strains to SbV and HePC; over half of strains of these two species were highly sensitive , with ≥79% and ≥70% reduction of infection respectively , when exposed to 32 µg SbV/ml , and ≥66% and ≥72% reduction respectively , when exposed to 16 µM HePC ( 6 . 5 µg/mL ) . In contrast , 50% of L . V . braziliensis strains presented in vitro resistance to the discriminatory concentration of HePC with ≤32% reduction of parasite burden . However , the inter-quartile distribution of the susceptibility of L . V . braziliensis strains to SbV revealed that 50% of L . V . braziliensis strains were moderately sensitive , with ≥58% reduction of parasite burden , and 25% were highly sensitive with ≥76% reduction of infection . Only 10% ( 16/163 ) of strains evaluated in vitro for both drugs were resistant to both: 9% ( 7/80 ) L . V . panamensis and 17% ( 9/54 ) L . V . braziliensis . While correlation analysis of all strains using the Spearman test indicated a statistically significant relationship between the susceptibility to each drug ( P = 0 . 0002 ) , the attributable effect was very low , r = 0 . 283 . Exploratory analyses revealed geographic variation in drug susceptibility of the L . Viannia species most prevalent in different natural geographic regions . Strains from patients who acquired infection in regions east of the Andes mountain ranges ( Orinoquía and Amazon regions ) were significantly less susceptible to HePC than strains from the Pacific Coast region on the western side of the Andes , Figure 2 . The lower susceptibility to HePC of strains from Amazon was influenced principally by L . V . braziliensis ( K-W: P = 0 . 0003 , Dunn's test: P<0 . 05 ) . Strains originating from the Orinoquía region presented the lowest susceptibility to both drugs . Although most of the strains originating from this region were L . V . braziliensis , L . V . panamensis strains from this region also contributed to the lower susceptibility to HePC . A significantly higher proportion of L . V . panamensis strains from the Orinoquía and Amazon regions presented in vitro resistance to HePC ( 46% , 11/24 ) compared with strains from Andean and Pacific regions ( 14% , 5/35 and 10% , 5/48 respectively ) ; however , susceptibility of the same strains to SbV was similar across regions , Figure 3A and B . Notably , strains presenting resistance to miltefosine were isolated during and after 2005 , and year of isolation was inversely correlated with intracellular parasite survival after exposure to 16 µM HePC ( P = 0 . 043 , r = −0 . 358 ) Supplemental Figure S2 . Though not statistically significant , L . V . braziliensis strains from the Pacific region displayed greater susceptibility to SbV compared with other regions , but were less susceptible to HePC compared to strains of this species from other regions , Figure 3 C and D . Strains presenting resistance to both HePC and SbV originated from the Andes , Orinoquia and Amazon regions . The frequency distribution by species of these L . V . panamensis and L . V . braziliensis strains displayed an inverse relationship from west to east of the Andes , Supplemental Figure S3 . Evaluation of the susceptibility to SbV among L . V . panamensis strains ( n = 170 ) from two endemic foci ( Rosario and Mira Rivers ) in the municipality of Tumaco , during two 10 year periods over 3 decades , revealed that strains from patients from the Rosario River focus presented a significantly lower median % reduction of parasite burden ( P<0 . 05 ) and higher frequency of in vitro resistance to SbV during the decade 1980–89 ( 45% , 20/44 ) compared with the decade from 2000–09 ( 25% , 6/24 ) . In contrast , the median % reduction of parasite burden was unchanged in the Mira River focus during the same periods but the frequency of resistance was significantly higher ( P<0 . 05 ) during the period 2000–09 ( 38% , 23/61 ) compared with the earlier period 1980–89 ( 17% , 7/41 ) , Figure 4A . Surprisingly , discrete populations of L . V . panamensis were discernible at the upper and lower limits of susceptibility in the Rosario River focus during the period 1980–1989 . Based on the median and inter-quartile range , a high reduction of parasite burden ( >87% ) was detected in 25% of strains and a very low ( <11% ) reduction of parasite burden was evident in 25% of strains from the Rosario River focus during the period 1980–1989 . These populations continued to circulate during 2000–2009 in both foci but in different proportions , Figure 4A . Most L . V . panamensis strains isolated in the municipality of Tumaco during the decade 1980–89 had been previously classified by isoenzyme analysis as zymodeme 2 . 2 and 2 . 3 , which corresponded to the most common isoenzyme profiles of L . V . panamensis in the southwestern region of Colombia [16] . Correlation of zymodeme with susceptibility to SbV revealed a significant association of the susceptibility phenotype with zymodeme ( P<0 . 05 ) among strains isolated during the period 1980-1989 , when zymodeme characterization was routine , Figure 4B and C . This association was confirmed in 20 strains isolated during the decade 2000–2009 ( data not shown ) . Most resistant strains from both endemic foci pertained to zymodeme 2 . 3 , whereas sensitive strains pertained to zymodeme 2 . 2 . Furthermore , strains of zymodeme 2 . 3 were significantly less susceptible to SbV than strains belonging to zymodeme 2 . 2 ( P<0 . 0001 ) . Evaluation of these characteristics in strains pertaining to zymodemes 2 . 2 and 2 . 3 from other Departments within and outside of the Pacific coast region ( n = 9 ) , corroborated the SbV sensitive and resistant phenotype of these zymodemes that was observed in the Mira and Rosario River foci , ( Data not shown ) . Multilocus microsatellite typing ( MLMT ) revealed genetic diversity among the L . V . panamensis strains evaluated as well as two independent clusters that coincided with zymodeme 2 . 2 and zymodeme 2 . 3 and the susceptibility phenotype for antimonials , Figure 5 . L . V . guyanensis strains were also genetically diverse within the two geographical regions represented; however , 6 of the 9 strains isolated in Chaparral , Tolima ( Andean region ) had identical MLMT profiles , suggesting the predominance of a clonal parasite population in this focus of transmission . No relationship between MLMT genotype and susceptibility to SbV was evident among the L . V . guyanensis strains , which displayed limited variability in drug susceptibility . Associations were also detected between zymodeme , patient age and occupation . A significantly higher number of strains isolated from children under seven years of age in the Municipality of Tumaco pertained to zymodeme 2 . 3 , Figure 6A . In contrast , a significantly higher number of strains isolated from individuals involved in agricultural activity pertained to zymodeme 2 . 2 . Frequency distributions of strains by zymodeme and according to the age of the corresponding patient yielded epidemiologic profiles characteristic of sylvatic transmission for zymodeme 2 . 2 and domestic transmission for zymodeme 2 . 3 , Figure 6B and 6C .
This comprehensive evaluation of drug susceptibility of clinical strains of Leishmania Viannia species is novel in several aspects: the magnitude of the sample of clinical strains; the defined timeframes and geographical distribution represented by the strains included; the analyses of strains pertaining to three species of the Viannia subgenus; and the correlation of susceptibility to SbV with isoenzyme phenotype and demographic characteristics of the corresponding patients . The results of this study provide a detailed profile of susceptibility to meglumine antimoniate and miltefosine , the first and second line drugs currently used to treat dermal leishmaniasis in Colombia and most of Latin America , for the most prevalent species in regions of high transmission in Colombia . The clinical response to antimonial drugs and miltefosine in different geographical contexts has long suggested differences in drug efficacy for disease caused by different species . In this in vitro analysis , strains of L . V . guyanensis , a species that has only recently been encountered in the context of domestic transmission in Colombia [25] , were found to be consistently sensitive to both SbV and HePC . In contrast , 20% of strains of L . V . panamensis , the most prevalent species in Colombia [16] , [17] , [18] and frequently transmitted in the domestic setting , were resistant to SbV or HePC in vitro . Although a similar proportion of strains of L . V . braziliensis were resistant to SbV , the reduction of parasite burden at the SbV concentration approximating Cmax in plasma during treatment was significantly lower for this species than for L . V . panamensis . Furthermore , overall in vitro susceptibility of L . V . braziliensis strains to miltefosine was remarkably low , with the majority ( 68% ) being resistant to 16 µM ( 6 . 5 µg/mL ) miltefosine , a concentration that distinguishes WT from experimentally selected lines [24] . This finding concurs with the lower clinical response to HePC reported in patients infected with L . V . braziliensis [4] , [20] in some geographical areas [4] or occupational contexts [5] . In populations occupationally exposed to the sylvatic cycle of transmission of L . V . braziliensis , such as military personnel , and in regions where L . V . braziliensis is the predominant cause of dermal leishmaniasis , the risk of poor therapeutic outcome with HePC may be higher . Nevertheless , as for other antimicrobial agents , in vitro susceptibility does not necessarily predict individual clinical outcomes [28] , [29] , [30] . Rather , the risk or frequency of treatment failure increases in relation with the minimum inhibitory drug concentration ( MIC ) or IC50 . However , clinical response , which is multi-factorial , can be achieved despite in vitro resistance to a given drug [31] as illustrated by the high proportion of dermal leishmaniasis patients infected with L . V . braziliensis in Colombia , Brazil and Bolivia that have responded to treatment with HePC [5] , [7] , [8] . Nevertheless , the high frequency of in vitro resistance to HePC among L . V . braziliensis strains circulating in Colombia underscores the importance of systematic follow-up of treatment and the rationale for combined therapies that could reduce the risk of failure and selection of resistant populations . Clinical response data and pharmacokinetic considerations of drug exposure in designing and interpreting in vitro susceptibility are sorely needed to reliably characterize the relationship between clinical outcome and drug susceptibility . Recognizing that clinical response and Leishmania species are not routinely determined outside of clinical trials , this relationship would be most informatively addressed within the scope of randomized , controlled clinical trials in which many of the factors influencing clinical response are controlled . In vitro evaluation of anti-leishmanial drug susceptibility of clinical strains relies on quantitative assessment of intracellular survival of amastigotes following exposure of infected host cells to the corresponding drugs [32] , [33] . The recent implementation of an assay based on the burden of surviving intracellular parasites after exposure to a single drug concentration that discriminates WT and experimentally selected resistant populations [24] was critical to the feasibility of this large scale study . The results substantiated a wide spectrum of susceptibility within each species , illustrating the importance of evaluating a representative sample of strains that is inclusive of the diversity of the species . The analysis of clinical strains from different geographic regions revealed lower susceptibility to both HePC and SbV among populations of Leishmania originating east of the Andes mountain range , an important natural geographic barrier . Although the proportions of the three species from patients originating from the eastern and western sides of the Andes differed , overall , Leishmania strains from the Pacific and Andean regions were more sensitive to both drugs than strains from Orinoquía and Amazon regions , Figure 2 . The finding that L . V . panamensis strains isolated from patients originating in Orinoquía and the Amazon region were significantly less susceptible to HePC than strains of this species originating from the Andean and Pacific Coast regions , Figure 3 , raises the question of whether populations of this species acquired by occupationally exposed individuals may have derived from a cycle of transmission involving intrinsically less susceptible parasite populations , or alternatively , might reflect exposure to HePC treatment . Supporting the plausibility of drug pressure contributing to this pattern , the majority ( 79% ) of L . V . panamensis strains from Orinoquia and Amazonia derived from cases diagnosed after 2005 , and HePC-resistant strains were isolated from 2005 onward ( Supplemental Figure S2 ) , several from uniformed service personnel . However , multiple factors are likely to have contributed to the relationship between year of isolation and resistance to HePC . Zymodeme or microsatelite analyses of these strains may reveal whether distinct populations of L . V . panamensis transmitted within the ecological and epidemiological circumstances in these regions contributed to the differences in susceptibility . Examination of SbV susceptibility of L . V . panamensis strains isolated during the decade 1980–1989 from patients of two riverine foci in the municipality of Tumaco in relation with zymodeme analysis [16] , showed that resistant strains corresponded with zymodeme 2 . 3 and susceptibilible to zymodeme 2 . 2 . These phenotypic differences were also discernible at the genetic level; L . V . panamensis strains from both zymodemes independently clustered in the display of MLMT analyses . This finding and the confirmation of the susceptibility phenotypes of L . V . panamensis strains of zymodeme 2 . 2 and 2 . 3 from other areas of transmission within and outside of the Pacific coast region , provide compelling evidence of intrinsic differences in susceptibility within this species . Although unlikely to be directly involved in susceptibility to antimonials , isoenzyme polymorphisms and/or microsatellites associated with the susceptibility phenotype provide potentially exploitable markers for epidemiological applications and clinical decisions . These populations can also provide insight into the mechanisms involved in their divergent susceptibilities to antimony that may be relevant and useful across species . Low drug susceptibility may be an intrinsic and/or acquired phenotype; a strain having low intrinsic susceptibility or tolerance could become further unresponsive as evidenced by some strains isolated pre-treatment with either SbV or HePC , and at treatment failure [12] , [13] . Nevertheless , considering the long history of monotherapeutic use of pentavalent antimonials in Colombia and elsewhere in the region , evidence supporting the likelihood of anthroponotic as well as zoonotic transmission , and the documentation of acquired resistance in prospectively isolated clinical strains , the discrimination of intrinsic and/or acquired bases of drug susceptibility phenotype remains challenging . Intrinsic resistance to specific drugs resulting from absence of the corresponding molecular target as seen in particular phylogenic groups of bacteria has not been observed for any antileishmanial drug . Monotherapy could amplify intrinsic resistance , as well as promote acquired mechanisms . The biological cost or advantage of loss of susceptibility and the role of anthroponotic transmission will influence the impact of treatment policy and practice on the drug susceptibility of prevalent Leishmania populations . The observed association of Leishmania zymodeme with patient occupation and age as well as parasite drug susceptibility in endemic riverine foci of the municipality of Tumaco supports the overlap of domestic and sylvatic transmission cycles among the inhabitants of these communities . The SbV resistance phenotype of zymodeme 2 . 3 and the association of this zymodeme with children in the communities of Tumaco suggest that domestic transmission may have been a factor in the emergence and dissemination of the zymodeme 2 . 3 population of L . V . panamensis in these foci during two decades spanning 30 years . The feasibility of assessing drug susceptibility using a single drug concentration and the precedent of being able to distinguish sensitive and resistant strains based on an intrinsic biochemical profile such as zymodeme provide opportunity to address this relationship . Meanwhile , the spectrum of susceptibility and frequency of in vitro resistance to first and second line treatments heighten the importance of alternative and combination treatment strategies . | Treatment of dermal leishmaniasis is unsuccessful in an important proportion of cases and evidence of loss of susceptibility to antimonial drugs and miltefosine has been demonstrated in some cases of treatment failure with these medications . Despite the variability in the clinical outcome of treatment , little is known about the susceptibility of the different species and diverse populations of these species circulating in areas of high transmission . Based on 402 strains isolated from patients , the susceptibility of the Leishmania species most frequently causing dermal leishmaniasis in Colombia was determined to first and second line medications commonly used in Latin America . The results showed that susceptibility to each drug varied among the species and populations of each species , geographically between regions east and west of the Andes mountain range , during different time periods over 30 years , and within different epidemiological circumstances . The findings provide a comprehensive picture of drug susceptibility of dermal leishmaniasis in Colombia and baseline information for monitoring the emergence of drug resistance . | [
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] | [
"infectious",
"diseases",
"medicine",
"and",
"health",
"sciences"
] | 2014 | Miltefosine and Antimonial Drug Susceptibility of Leishmania Viannia Species and Populations in Regions of High Transmission in Colombia |
Cell shape changes and proliferation are two fundamental strategies for morphogenesis in animal development . During embryogenesis of the simple chordate Ciona intestinalis , elongation of individual notochord cells constitutes a crucial stage of notochord growth , which contributes to the establishment of the larval body plan . The mechanism of cell elongation is elusive . Here we show that although notochord cells do not divide , they use a cytokinesis-like actomyosin mechanism to drive cell elongation . The actomyosin network forming at the equator of each notochord cell includes phosphorylated myosin regulatory light chain , α-actinin , cofilin , tropomyosin , and talin . We demonstrate that cofilin and α-actinin are two crucial components for cell elongation . Cortical flow contributes to the assembly of the actomyosin ring . Similar to cytokinetic cells , membrane blebs that cause local contractions form at the basal cortex next to the equator and participate in force generation . We present a model in which the cooperation of equatorial actomyosin ring-based constriction and bleb-associated contractions at the basal cortex promotes cell elongation . Our results demonstrate that a cytokinesis-like contractile mechanism is co-opted in a completely different developmental scenario to achieve cell shape change instead of cell division . We discuss the occurrences of actomyosin rings aside from cell division , suggesting that circumferential contraction is an evolutionally conserved mechanism to drive cell or tissue elongation .
Individual cell shape changes contribute significantly to morphogenesis during embryonic development [1] . The actomyosin network is a central player in the formation and transformation of functional cell shapes . Actin and myosin filaments are highly and dynamically organized in different developmental contexts , and often exist in a higher structure as a ring . The equatorial circumferential ring in cytokinesis is essential for the cell division to occur [2] . An actomyosin ring is also present in the yolk syncytial layer of zebrafish embryo , and is implicated in the epiboly movement of the enveloping cell layer [3] . In addition , the actomyosin ring is readily assembled after a wound in the cell membrane , and is responsible for the wound healing [4] . Body elongation is an essential morphogenetic process in the development of a bilateral body plan [5] . In many chordates , the elongation of an anatomically central structure , the notochord , contributes to this process [6] . In the simple chordate Ciona intestinalis , elongation of notochord occurs in three consecutive phases: convergent extension , individual cell elongation , and cell migration [7]–[12] . During the individual cell elongation phase , notochord cells lengthen dramatically [12] , [13] and reduce their diameter substantially . A circumferential constriction forms midway in the cylindrical cell , and an actomyosin ring appears at the constriction , suggesting that the furrow results from the action of the contractile actomyosin ring , similar to the formation of the cleavage furrow in cytokinesis . In cytokinesis , the establishment of the contractile ring is a highly coordinated process . Its initial positioning is regulated through the signaling of the anaphase spindles and the cortex [14] , [15] . The actual assembly of the ring at the equator involves either localized de novo assembly of actomyosin filaments at the equator [16] , [17] or a directional cortical flow of preexisting filaments . The cortical flow mechanism subscribes to the movement of actin and myosin filaments at the cortex , from other regions of the cell , toward the equator as a consequence of a gradient in actomyosin activity [18]–[22] . These two recruitment mechanisms are not necessarily mutually exclusive . In Dictyostelium cells , myosin II is recruited to the equator by both cortical flow and de novo association [22] . The organization of the actomyosin ring during furrow ingression is highly dynamic and constantly remodeled . Therefore , in addition to actin and myosin , the contractile ring contains other proteins that regulate actin nucleation , capping , polymerization , disassembly , cross-linking , and myosin activity [23] . The actin-depolymerizing factor ( ADF ) /cofilin mediates actin filament turnover [24] , [25] . In Xenopus , cofilin is required for furrow formation [26] , and in fission yeast , it is necessary for the formation and maintenance of the contractile ring [27] . Tropomyosin stabilizes actin filaments and regulates the access of other actin-binding proteins including myosins [28] , [29] . α-actinin , in addition to cross-linking actin filaments , tethers actin to the membrane in the equatorial region [30] , [31] . Talin , an actin-binding protein that bridges actin filaments and the adhesion apparatus [32] , has also been localized to the cleavage furrow [33] . Although actomyosin is significantly enriched at the equator in dividing cells , a substantial actomyosin contractility remains outside of the furrow [34] . Formation of membrane blebs is commonly observed at the cell poles from the onset of anaphase until late cytokinesis [35]–[38] . Blebs are transient detachments of the cell membrane from the actin cortex and the streaming of cytosol that inflates the membrane [39] . The creation of a bleb requires critical levels of cytosolic pressure , membrane tension , and membrane–cortex adhesion energy [40] , whereas bleb retraction requires a local contraction of the newly assembled actomyosin elements [41] . During cytokinesis , an underappreciated morphogenetic event is the cell elongation that proceeds the final cell division . This is evident , for example , in the division of the fertilized egg , where the total cell length between two poles progressively increases as the ingression deepens . In this study we examined the components and dynamics of the equatorial actomyosin network in notochord cells , and its contribution to cell elongation in the absence of cell division .
The notochord is located in a central position in the tail of Ciona intestinalis embryo ( Figure 1A and 1B ) . The specification of the notochord lineage , marked by the expression of the conserved transcription factor brachyury , is completed at the 110 cell stage [42] , [43] . During gastrulation , 10 notochord precursors undergo two rounds of cell division and the resulting 40 cells form a monolayer epithelium anterior to the blastopore [8] , [11] , [44] , [45] . Subsequently , in approximately 3 h up to the early tailbud stage , convergent extension takes place that rearranges the cells into a stack-of-coins configuration at 14 hpf ( Figure 1A ) . During the next 5 h notochord cells elongate approximately 2 . 5-fold , whereas the cell number , the cell arrangement , and cell volume remain unchanged ( Figure 1B and 1C , Figure S1A ) [12] . As a result , individual notochord cells , which are overall cylindrical , change from a coin shape to a drum shape ( Figure 1D and 1E ) . The elongation takes place along the anterior–posterior ( A-P ) axis of the embryo at a steady rate ( Figure S1B and S1C ) . The nucleus of each cell , whose volume appears constant , becomes positioned against the posterior cell membrane . A circumferential constriction appears midway between the anterior and posterior ends of each cell from the onset of elongation phase , and persists throughout the elongation process . This equatorial constriction is colocalized with a circumferential band of actin and myosin filaments ( Figure S2 ) [46] , which is similar to the actomyosin ring present at the cleavage furrow of dividing cells and responsible for cytokinesis ( Figure S3 ) . In contrast to cytokinesis , however , no cell division occurs in Ciona notochord . Because the formation of a cleavage furrow is invariably preceded by an S phase and mitosis , we asked if cryptic cell cycle events could have taken place in notochord cells . Specifically we examined if DNA synthesis corresponding to the S phase had occurred , by monitoring bromodeoxyuridine ( BrdU ) incorporation . While many cells in the head and the dorsal neural tube are positive for BrdU , corresponding to continuous cell proliferation in these tissues , no BrdU is incorporated in notochord cells ( Figure 1F–G′ ) . Phosphorylation of core histone H3 ( pH3 ) at an invariant serine residue ( Ser 10 ) is a highly conserved histone modification and correlates specifically with chromosome condensation during the prophase of mitosis [47] . Immunohistochemistry using anti-pH3 shows nuclear staining in the mitotic cells in the head , but not in the notochord ( Figure 1H and 1H′ ) . These facts show that nondividing Ciona notochord cells form an equatorial constriction during elongation . The actomyosin ring is positioned in the basal cortex at a position that is equal distance from the two ends of the cell , the lateral domains ( the center of which differentiates into apical domain during lumen formation ) ( Figure 2A ) . Myosin II is essential for the contractility of the actomyosin ring in cytokinesis [48] . Its motor function is activated by the reversible phosphorylation of myosin regulatory light chain ( MRLC ) at Serine 19 [49] . Specific antibodies against pS19 MRLC stain the cortical equatorial region of notochord cells , where they colocalize with phallacidin-labeled actin filaments ( arrows in Figure 2B and 2B′ ) . Both components are also present and partially overlap at the lateral domains ( arrowhead in Figure 2B ) . We previously employed microarray analysis to profile notochord cell gene expression at the mid-tailbud stage and identified multiple actin binding proteins that are either specifically expressed or highly enriched in the notochord ( unpublished data ) [50] . Among them are Ciona homologs of cofilin , α-actinin , tropomyosin , and talin . A combination of immunohistochemistry and fluorescent fusion proteins reveal that these proteins are present at the equatorial cortex of Ciona notochord cells ( Figure 2C and 2D ) . Noticeably , whereas α-actinin , tropomyosin , and talin fluorescent fusion proteins occupy a wide equatorial region in live embryo , cofilin-mCherry is more restricted to the equator . In addition , fluorescent protein-tagged Ciona IQGAP , anillin , and septin 2 are also localized in the equatorial cortex of elongating cells ( Figure S4 ) . Thus , the localization of actomyosin contractile elements and regulatory proteins in the notochord equatorial region resembles remarkably the contractile ring at cleavage furrow of a dividing cell . During cell elongation , we observed frequent membrane deformations at the basal surface . Time-lapse movies of notochord cells expressing lifeact-mEGFP revealed two phases of membrane deformation , a fast inflation phase , which lasts 26 . 71±9 . 80 s ( n = 14 ) , followed by a slow retraction phase , which is completed in 181 . 50±34 . 29 s ( Movie S1 , Figure 3A and 3B ) . The cortex of the membrane is devoid of actin during its inflation , similar to blebs observed in other systems , suggesting a detachment of the membrane from the actin cortex due to a transient increase of intracellular pressure [41] . Actin is recruited to the bleb cortex after the membrane deformation has reached its maximum and begins its slow recovery ( Figure 3A and 3B ) . It is known that the retraction of a bleb involves the reconstitution of the actin cortex and the recruitment of myosin to power an active contraction event [39] , [41] . We asked if bleb retraction can constitute a contraction in notochord cells at the basal surface by examining the molecular components of a bleb during its recovery . Indeed , tropomyosin , cofilin , and MRLC are recruited to the bleb very early during the recovery of the membrane deformation ( Figure 3C ) , before actin appears in the bleb . These results suggest that the retraction of bleb-like membrane deformation in notochord cells represents individual contractions at the basal surface . Basal bleb-like contractions occur throughout the elongation phase , at very similar frequencies ( 0 . 42±0 . 05/cell/min , mean ± s . e . m . , n = 42 ) regardless the developmental times and regions of the notochord ( Figure S5 ) . Most blebs form beside the equatorial constriction . The average size of a deformation is 37 . 39±3 . 3 µm2 ( n = 17 ) , covering only a small area ( 5% ) of the basal membrane ( 734 . 81±45 . 88 µm2 , n = 6 ) , indicating that the contractile activity associated with bleb retraction is local , and applies a discrete compression inward . To test if these basal contractions ( transverse loading ) can be converted into forces pushing along the longitudinal axis and thus potentiating cell elongation ( axial strain ) , we examined the behavior of the ends of notochord cells when a basal bleb occurs . At the early stage of lumen formation , both equatorial constriction and actomyosin ring persist , and notochord cells continue to elongate ( Figure S1 and Figure S5 ) [46] . Extracellular luminal pockets emerge between adjacent notochord cells and are enclosed by newly differentiated apical/luminal domains . Time-lapse movies show a displacement of the apical membrane following the retraction of a basal bleb ( Movie S2 , Figure 3D ) . As the basal bleb forms , the apical membrane moves toward the center of the bleb-bearing cell along the longitudinal axis , then slowly returns to its previous position after the bleb recovers ( Figure 3E ) . To relate these two events we conducted temporal cross-correlation analysis of the membrane movements . Correlation between temporal profiles of basal blebbing and apical membrane displacement is high ( mean <R> = 0 . 76±0 . 05 , n = 4 ) , indicative of similar overall dynamics . Moreover , the bleb retraction precedes the outbound movement of apical membrane by 49 . 87±23 . 92 s . This result suggests that a discrete local contraction during bleb retraction at the basal surface can be converted to a longitudinal pushing force that produces strain along the direction of cell elongation ( Figure 3F ) . To address which mechanism underlies the formation of equatorial contractile rings in notochord cells , we analyzed the dynamics of actin and myosin filaments in live embryos . Actin behavior was followed with several probes: human actin N-terminally tagged to mCherry ( mCherry-hActin ) , lifeact-mEGFP , and mCherry-utrophin . The latter two consist of small peptides derived from the actin binding protein Abp140 of S . cerevisiae and human utrophin , respectively , and bind to endogenous actin without interfering with its dynamics [51] , [52] . To visualize myosin , we expressed mCherry-MRLC . These tagged proteins have the same localization patterns as endogenous proteins and serve as reliable probes for endogenous structures ( compare Figure 2B and Figure 4 , Figure S6 ) . To determine if cortical flow is involved in the recruitment of actin to the equatorial plane , we collected time-lapse movies of elongating notochord cell expressing lifeact-mEGFP ( Figure 4A ) . In order to avoid cytoplasmic signal and to record only the mobile elements at the basal cortex , five Z-sections ( 0 . 5 µm/section ) from the basal surface were taken and projected . Lifeact-mEGFP reveals a highly dynamic flow of circumferential actin filaments , which emerge at the boundaries of the equatorial region , toward the equator ( Figure 4A , white and yellow arrowheads follow specific filaments , and Movie S3 ) . In addition , these films demonstrate the presence of short actin filaments that emerge from the lateral domains . These filaments are initially oriented along the longitudinal axis of the cell , and travel toward the equator . As they approach the equatorial region , they reorient , align , and merge with the circumferential filaments ( green arrow follows one short filament in Figure 4A ) . A similar flow of circumferential actin filaments was observed using mCherry-utrophin ( Figure S6 and Movie S4 ) . The 3D time-lapse recordings of notochord cells expressing mCherry-MRLC show that the cortical flow is not only restricted to actin . Myosin form circumferential filaments and move in a similar fashion toward the equator ( Figure 4B and Movie S5 ) . Although actin and myosin colocalize in filament bundles in the equatorial region ( Figure 4C ) , intensity correlation analysis indicates that they are also separately present ( Figure 4D , ROI shown in Figure 4C ) . Several methods were used to further determine the dynamics of actin filaments . We manually tracked single actin filaments in the time-lapse projection movie of a cell expressing lifeact-mEGFP ( Figure 4E ) . The average velocity is 33 . 9±4 . 9 nm/s ( n = 9 , Table S1 ) . A kymograph generated from the movie confirmed the highly dynamic and polarized cortical flow of circumferentially oriented actin filaments within the equatorial region ( Figure 4F ) , with a calculated velocity of 29 . 5±10 . 5 nm/s ( n = 2 , Table S1 ) . Next , we measured the dynamic turnover of actin by fluorescence recovery after photobleaching ( FRAP ) in notochord cells expressing mCherry-hActin . As shown in Figure 4G , we photobleached a region that contained the whole equatorial circumferential actin filaments ( blue bracket ) . The total fluorescence prior to bleach fully recovers , with a halftime of recovery of 54 . 24±7 . 59 s ( n = 4 , Figure 4H ) . To ascertain whether movement of actin toward the equator contributes to fluorescence recovery , we determined recovery halftimes separately for peripheral and central regions . Recovery is faster in the anterior and posterior regions than in the middle region . The average velocity of the filaments based on FRAP is 40 . 8±3 . 8 nm/s ( n = 4 , Table S1 ) . These results together indicate that cortical flow contributes considerably to the formation of the actomyosin contractile ring of notochord cells . The movement of actin and myosin filaments is continuous without oscillation , and the constriction shows no relaxation . The flow persists for at least 5 h as cells elongate; however , we did not observe any accumulation of actomyosin filaments at the equator . Phallacidin staining of actin filaments at different time points confirms that the width and the intensity of the actin ring remains relatively constant ( Figure S2 ) . Previous work has shown that notochord in embryos treated with latrunculin B or blebbistatin fail to elongate [46] . The ubiquitous presence of actomyosin in the embryo does not allow us to exclude that the notochord phenotype is secondary to a defect elsewhere . We therefore took a genetic approach and disrupted components of actomyosin network specifically in the notochord using a notochord-specific promoter . The lack of an accumulation of actin filaments at the equator during 5 h of elongation , despite the continuous flow , suggests that an actin turnover mechanism operates in the notochord cells , similarly to cytokinesis . This is consistent with the restricted localization of cofilin , a known actin severing factor , at the equator ( Figure 2C and 2D ) . The activity of cofilin is regulated by its phosphorylation state . Phosphorylation of an amino-terminal serine ( Ser 3 in human nonmuscle cofilin ) prevents cofilin from binding to actin and thus impairs its function [53] , [54] . P-cofilin can be mimicked by mutating Ser 3 into glutamate . The phosphomimetic mutant S3E has been shown to act as a dominant negative [55] that inhibits the dephosphorylation of endogenous cofilin and ADF , presumably through sequestering cofilin-specific phosphatase [56] , [57] . Most multicellular organisms have multiple cofilin/ADF genes; Ciona , however , has only one , which has a homologous serine at position 5 ( Figure 5A ) . We therefore generated a S5E mutant , and expressed it under the control of multidom or brachyury promoter [58] via electroporation into one-cell stage embryos , which results in mosaic expression in the notochord cells . Mutant protein was not observed until 14 hpf ( Figure S7D ) ; therefore , the expression of the dominant negative does not affect the division of notochord precursors cells ( Figure S7E ) . At 18 hpf , 37% of notochord cells ( n = 97 ) expressing cofilinS5E have abnormal morphology ( Figure 5B and Figure S7B , S7C ) , whereas cells expressing wild-type cofilin are normal ( n = 39 ) ( Figure S7A ) . Abnormal cells appear either shortened with a larger diameter , dumbbell shaped , or excluded from the notochord . We also co-electroporated lifeact-mEGFP under the brachyury promoter , which allows us to monitor the actin localization in both wild-type and mutant cells in the same embryo ( Figure 5B ) . Two wild-type cells flanking the cofilinS5E-expressing cell are able to elongate , and exert pushing forces along the longitudinal axis , squeezing the cofilinS5E cell to assume a dumbbell shape . Actin accumulate abnormally off the equator in the cofilinS5E cell ( yellow arrowheads in Figure 5B ) , in contrast to the usual localization at the equatorial region , as seen in a wild-type cell ( yellow arrows in Figure 5B ) . We interpret these phenotypes as results of the disruption of actin filament disassembly and of the actin flux within notochord cells . As a consequence of this disruption , there is less equatorial constriction and less overall pressure in the cell . When the neighboring wild-type cells continuously exert longitudinal pressure along the A-P axis , the mutant cell ultimately becomes squeezed ( Figure 5C ) . To address the role of the contractile ring at the equator in cell elongation , we examined the cells at the ends of the notochord . The first cell ( cell 1 ) and last cell ( cell 40 ) of the notochord are unique because they have only one notochord cell as neighbor . This asymmetry determines that the end cells in the subsequent lumen formation phase form one apical/luminal domain at the side of notochord cell/cell contact , in contrast to the other 38 cells , which create two apical/luminal domains at the opposite ends of the cells ( Figure 2A ) [12] , [59] . We examined morphology and actin filament dynamics by collecting time-lapse movies of the ends of notochord expressing lifeact-mEGFP ( Figure S8A , Movie S6 ) . Cells anterior to cell 40 possess an equatorial actin ring , form circumferential constriction , and elongate , whereas cell 40 accumulates actin filaments at its posterior tip . No circumferential constriction is present in cell 40 , and it does not elongate . Intriguingly , the time-lapse movie shows dynamic unidirectional movement of actin filaments toward the posterior tip of this cell , in contrast to the bidirectional movement of actin toward the equator in anterior cells . The lack of elongation was observed at both ends of the notochord ( Figure S8B , S8C , S8E ) . The different behavior exhibited in the end cells is unlikely the result of differential cell sizes because the notochord cell division is equal and the placement of cells is locally random [11] , [13] , [44] , but is caused by the absence of an equatorial contractile mechanism . To confirm this , we artificially generated end cells by cutting the embryo at random positions before the elongation phase . The newly created end cells invariably failed to form a circumferential constriction and to elongate ( Figure S8D ) . These results together support an essential role for the equatorial actomyosin ring in notochord cell elongation . α-actinin has been implicated in cytokinesis in different organisms . It localizes to the cleavage furrow in both fungi and animal cells [31] , [60]–[64] , and regulates actin dynamics and controls the rate of furrow progression [31] , [64]–[68] . α-actinin , through the interaction of spectrin domains , forms antiparallel rod-shaped dimers , with two actin-binding heads at the opposite ends of the complex [30] . The spectrin repeats in the rod domain also serve as binding platform for a variety of transmembrane proteins [69] . The Ciona α-actinin has the typical domain organization of vertebrate α-actinin ( Figure 6A ) . We generated a truncated α-actininROD mutant by removing the N-terminal head ( Figure 6A ) . α-actininROD lacks the ability to bind actin , but has been shown to form heterodimers with endogenous α-actinin . The mutant is dominant-negative and causes the displacement of endogenous α-actinin and cytokinesis defects [65] . Expressed under the brachyury promoter , the mutant does not affect the cell division of notochord precursors and notochord convergent extension ( Figure S9D ) . However , of cells expressing α-actininROD ( n = 145 ) , 33% are impaired ( Figures 6B and S9B–D ) at the elongation stage . At early phases , actin filament movement is highly dynamic but disorganized ( Movie S7 ) , with an increase of bleb movement . At later phases , mutant cells do not elongate normally , but become asymmetric , with the constriction shifted toward one end of the cells ( Figure 6B ) . The circumferential actin filament bundles move along the A-P axis over the entire basal surface ( Movie S8 ) . None of these phenotypes occur in cells expressing wild-type α-actinin ( n = 33 , Figure S9A ) . To explore if equatorial constriction by circumferential actomyosin network activity is a general mechanism from an evolutionary perspective , we examined the organization of actin filaments in notochord cells in Oikopleura dioica , an appendicularian separated from the ascidian lineage possibly during the Cambrian evolution [70] . The genomic architecture of Oikopleura has drastically diverged and highly modified since the last common ancestor [71] . The Oikopleura notochord has only 20 cells after embryonic development , and despite of having a similar morphology to ascidians , utilizes remarkably different genetic tool kits for its development [72] . Nevertheless , a circumferential basal constriction is present in the equatorial region of elongating notochord cells ( red arrows in Figure 7A ) , where an actin ring also localizes ( white arrows in Figure 7A ) .
In animal cells , contractile elements are supplied in part by cortical flow from other regions of the cell to the equator [18] , [19] , [21] , [22] , [76] , [77] . We show that cortical flow of actin filaments also contributes considerably to the formation of the actomyosin contractile ring in elongating notochord cells ( Figure 4 ) . The concentration of activated myosin in the equatorial region ( Figure 2B ) and the reorientation of short actin filaments ( Figure 4A ) lend support to the model that cortical flow is driven by a contractility gradient , and heightened contractility can orient the filaments to form a ring [78] , [79] . The velocity of filament movement lies in the same range ( tens nm per second , Table S1 ) as the speed observed during cytokinesis [20] , [35] . Myosin filaments feature a similar directed movement . Several studies suggest that the recruitment of actin and myosin to the equator in dividing cells is at least partly independent [48] . Similarly , circumferential actin and myosin filaments only partially colocalize in notochord cells , indicating that myosin filaments do not simply slide along actin filaments toward the equator . It has been shown that cofilin plays an important role in actin turnover during cytokinesis [25] , [80] , [81] . The failed furrow formation and cell elongation in notochord cells expressing cofilin mutant indicate that cofilin performs a similar function in regulating the dynamics of the contractile ring . In contrast to other actin binding proteins that are distributed over a wide equatorial region , cofilin is enriched in a narrow band precisely at the equator . Cortical actin filaments flowing in from both sides may encounter cofilin last , and be disassembled in this narrow region . α-actinin is crucial for the regulation of furrow progression during cytokinesis [31] . Due to its ability to cross-link actin filaments and to bind membrane proteins [30] , [69] , it is also involved in the positioning of the ring during cytokinesis in fission yeast [63] , and expression of α-actininROD in mammalian cells causes a displacement of the actin ring and accelerated cytokinesis [65] . Similarly , in notochord cells expressing the α-actininROD mutant , equatorial localization of the contractile ring is disturbed , and the circumferential actin filaments roam over the entire basal surface ( Movie S8 ) . Overexpression of ROD mutant may saturate the membrane actin filament tethering sites , and disrupt the anchoring of contractile actin filaments to membrane at the equator , resulting in a shift of constriction away from the equator ( Figure 6C ) . The presence of tropomyosin and talin in the equatorial region of notochord cells adds further to the resemblances between the notochord contractile ring and the cytokinetic contractile ring . Tropomyosin may regulate the stability of the actin filaments [28] , [82] , thereby confining the actin disassembly by cofilin in a narrow zone at the equator [83] , [84] . Talin may connect the actomyosin filaments with the plasma membrane in notochord cells , as it does during cytokinesis [85] . Cytokinesis is invariably preceded by an interphase and mitosis , in which the duplication and separation of chromosomes occur , respectively . In contrast , notochord cells establish a functional equatorial contractile ring without an S phase and mitosis , suggesting that significant aspects of cytokinesis can be controlled independently from events of the cell cycle . For example , the microtubule organization in elongating notochord cells bears little resemblance to that of a dividing cell . There is no central spindle , nor astral microtubules . Instead , microtubule filaments are found mainly in the membrane cortex , and a significant amount of microtubules are arranged circumferentially in the basal domain ( Figure S11A ) [46] , similar to what is found in plants [86] . Detailed analyses reveal that circumferential microtubules are located in the lower cortex , beneath the cortical circumferential actin filaments ( Figure S11C ) . Whereas actin filaments are highly mobile , microtubule filaments exhibit little mobility in the same time scale ( unpublished data ) . Furthermore , disruption of microtubules with 40 µM nocodazol [46] affects neither the positioning of the equatorial actomyosin filaments ( Figure S11D ) nor notochord cell elongation ( Figure S11E ) , in contrast to the treatment with myosin inhibitor blebbistatin [46] , which significantly reduces cell elongation . Thus , both the establishment of the equatorial actomyosin ring and cell elongation are independent from the microtubule network . In addition , the nucleus is invariably positioned at the posterior end of each cell ( except cell 40 ) . Hence , the establishment of an equatorial actomyosin ring can only be regulated through a spindle-independent mechanism . Such a mechanism has been alluded by the observation of polar lobe formation in molluscan early embryogenesis . For example , Ilyanassa obsoleta embryos at first cleavage form two contractile rings . In addition to the cleavage furrow in the animal hemisphere between the spindle poles , a second constriction forms in the vegetal hemisphere below the spindles and orthogonal to the first furrow , creating a transient polar lobe that represents an elongation of the cell [87]–[89] . In cytokinesis , the mitotic apparatus has been shown to be dispensable because the disruption or removal of the mitotic apparatus at anaphase or later does not affect cell cleavage [2] , [90] . A spindle-independent pathway has recently been identified , which utilizes cortical polarity signals to position the ring and furrow , and partly redundantly regulates asymmetric cell division of the Drosophila neuroblasts with the central spindles [91] . In addition , polar cortical contractility and blebs can modulate the position of the ring in dividing cells in culture [92] . These and our observation indicate that the capacity and potential of the basic cellular and molecular toolkit used to position the ring is still underappreciated . Several observations indicate that the equatorial actin ring in notochord cells is contractile . The actin filaments are associated with phosphorylated myosin filaments . Inhibition of myosin activity abrogates the furrow formation . Disruption of the ring dynamics by the cofilin mutant results in a failure to form the furrow . Mislocalization of the ring by α-actinin mutant causes the furrow to shift to one side . Furthermore , the flow of actin filaments toward the equator is consistent with the idea that the contractility of actomyosin ring at the equator powers the flow [78] . The circumferential actomyosin ring in cytokinesis is essential for furrow formation and ingression , which in most cases is associated with an elongation of the cell before the final division ( Figure 7B ) . Four pieces of evidence support that the contractile ring at the equator contributes to the notochord cell elongation . First , the notochord in embryos treated with latrunculin B or blebbistatin fails to elongate [46] . Second , cells expressing the cofilin dominant negative , which interferes with the actin dynamics , fail to elongate , and are pressed by neighboring cells with normal contractile ring activity . Third , the end cells , which normally do not assemble a ring at the equator , do not elongate . Lastly , in cells expressing α-actinin mutant , the actin filaments remain contractile but are mislocalized , and the elongation is partial and abnormal . We therefore suggest that the equatorial constriction force is transduced hydraulically to a longitudinal pushing force that drives cells to elongate within the confine of the notochordal sheath ( Figure 7C ) . In addition , the hydraulic pressure created by the equatorial ring is likely the cause for tearing of the basal membrane off the actin cortex to form blebs , which may act as valves releasing the cortical contractility , as it occurs in cytokinesis [92] . The traditional view envisions that the actomyosin ring generates force through myosin-dependent actin filament sliding , as it occurs in muscle sarcomeres [93] . This mechanism has been complemented recently by the finding that myosin II plays an important role in cross-linking actin filaments and exerting tension [94] . Significantly , we have observed numerous local contractions on the circumferential basal surface mostly between the equatorial region and the lateral domains . This suggests that the equatorial region is under higher tension , which makes it less conducive for membrane deformation . Furthermore and intriguingly , we observed a correlation between the basal blebbing and membrane movement along the A-P axis . This temporal coupling supports that a discrete local contraction at the basal circumference can also be converted to a longitudinal pushing force that exerts at the two poles of the cell ( Figure 3F ) . Our time-lapse movies show a return of the apical domain to its original position ( Figure 3E ) . Cell elongation may partly result from repeated stresses originated at the basal surface over a long period , after the notochord cells , considered here as fully elastic , reach their yield point [95] . Alternatively , based on a more realistic model of the living cell as being viscoelastic [96] or poroelastic [97] , frequent stresses ( min ) can produce sustained deformation over a large time scale ( hours ) [98] , [99] . The contractile ring , in addition to providing a direct role in driving cell elongation , may act as a tension-based barrier to channel force ( or displacement of cytoplasm ) to the cell's poles , and provide a ratchet mechanism to maintain a fraction of elongation gained through each bleb retraction event ( Figure 3G ) . The biophysical mechanism for the cell elongation is likely to be more complex . For example , it has been demonstrated that actomyosin flow generates reverse directional forces that drive the spreading of the enveloping cell layer over the yolk cell in zebrafish gastrulation [3] . This suggests that the equator-bound actomyosin flow seen in notochord cells may also generate an A-P pulling force by flow-friction mechanism , which in turns participates in notochord cell elongation . Appendicularians , together with ascidians , belong to the Tunicata subphylum , which diverged from the vertebrates very early during chordate evolution . The third Chordate subphylum , Cephalochordata , diverged before the split of tunicates and vertebrates [100] . Intriguingly , notochord cells in the amphioxus Branchiostoma lanceolatum also contain transverse actin and myosin filaments that are contractile [101] , [102] , although amphioxus notochord cells do not elongate , and the actin filament contractility facilitates animal locomotion . It thus appears that the notochord of early chordates is a contractile device . The notochord in ascidians and appendicularians , which has a small number of cells , achieves tissue elongation by circumferential contraction , whereas in amphioxus it elongates by cell proliferation and applies the contractility of the actomyosin elements for a different purpose . A noncytokinetic circumferential actin ring has also been found in other tissue types—for example , during polar lobe formation , and in the myoid segment of retina rods in certain fish species , where it is essential for the dramatic elongation of the rod after light stimulation [103] , [104] . In addition , early workers have noted that a number of isolated individual amphibian cells , particularly the neural plate cells , can elongate , and intriguingly , they show local constriction rings traveling the length of the cell as successive waves [105] . Similar travelling constriction rings that contain actomyosin filaments have also been observed in leucocytes during cell shape changes and migration [106]–[109] . Furthermore , circumferential actin filaments are found in multiple cell types in plant roots , and are important for the anisotropic growth of individual cells and the extension of the root [110]–[112] . At a tissue level , numerous circumferential actin filaments are present at the outer surface of the hypodermal cells in the C . elegans embryo during development ( Figure 7D ) . The elongation of the body is accomplished by the contractility of these actin filaments squeezing the embryo circumferentially [113] . Finally , the collective effect of basal contraction of individual follicle cells , through the action of a transverse array of actomyosin filaments along the circumference , drives the elongation of the Drosophila ovary [114] . Taken together , we propose that the circumferential contraction as a biophysical solution for anisotropic shape change , specifically bipolar extension of a symmetric biological unit , is a widespread phenomenon that appeared many times in evolution and is mechanistically scalable , as it can operate in single cells as well as in a whole embryo .
Ciona intestinalis were collected from several fjords around Bergen , Norway , or purchased from Roscoff Marine Station , France . Animals were maintained in running filtered seawater . Gametes from several individuals were surgically removed and mixed . After fertilization , the embryos were dechorionated with 1% sodium thioglycolate and 0 . 05% protease E as previously described [115] , then washed four times in UV-treated seawater . The embryos were cultured at 16°C . Oikopleura dioica were obtained from cultures of the Sars Centre Appendicularia Facility . For in vitro fertilization , females were collected in glass dishes and left to spawn . Sperm from several males was used for fertilization . Embryos were left to develop at 19°C . Cofilin , cofilinS5E , α-actinin , α-actininROD , EB1 , tropomyosin , IQGAP , anillin , and septin 2 were amplified from Ciona cDNA using primers listed in Table S2 . PCR products were used to create entry clones by recombination using the pCR8/GW/TOPO system ( Invitrogen ) . The entry clones were used to generate notochord expression constructs using destination vectors Minos-B3-eBra-bpFOG-B5::R1-ccdB/CmR-R2-mCherry [12] ( for cofilin-mCherry , cofilinS5E-mCherry , α-actinin-mCherry , α-actininROD-mCherry , EB1-mCherry , IQGAP-mCherry , anillin-mCherry , and septin 2-mCherry ) and Minos-B3-eBra-bpFOG-B5::Kozak-mCherry-R1-ccdB/CmR-R2 [46] ( for mCherry-tropomyosin ) with the Gateway cloning method ( Invitrogen ) . The mCherry-talinA I/LWEQ , mCherry-hActin , mCherry-UtrCH , lifeact-mEGFP , and mCherry-MRLC , ensconsin-3XGFP expression clones were described previously [46] . We also created a cofilinS5E-mCherry expression construct by recombining the entry clone into Minos-B3-multidom-B5::R1-ccdB/CmR-R2-mCherry that was modified from Minos-B3-eBra-bpFOG-B5::R1-ccdB/CmR-R2-mCherry , in which the promoter eBra-bpFOG was replaced with the notochord-specific promoter from Ciona multidom gene [58] . Electroporation was performed as described previously [42] with some modifications . Plasmid DNA ( 80 µg in 80 µl ) was mixed with 400 µl 0 . 95 M mannitol , then added to 300 µl dechorionated fertilized eggs and electroporated in a 4 mm cuvette using a Gene Pulser Xcell System ( BIO-RAD ) , with a square pulse protocol ( 50 V and 15 ms per pulse ) . After electroporation , embryos were cultured at 16°C . Full-length cofilin and tropomyosin cDNAs from the entry clones were subcloned into pT7MAT provided by Proteogenix . Recombinant proteins were produced in E . coli and used to immunize mice . Antisera were affinity-purified according to the manufacturer's protocol ( Proteogenix ) . Polyclonal rabbit anti-talinA I/LWEQ antibody was a gift from R . O . McCann . Polyclonal rabbit anti-MRLC phosphorylated at S19 ( pS19 MRLC ) antibody was purchased from Cell Signaling Technology ( 3671 ) . Monoclonal rat anti–α-actinin antibody was obtained from Abcam ( MAC276 ) . Alexa 568-conjugated anti-rat , anti-rabbit , and anti-mouse secondary antibodies were from Invitrogen ( A11077 , A11011 , and A11004 , respectively ) . For α-actinin , talin , cofilin , and tropomyosin antibody staining , Ciona embryos were fixed with 4% formaldehyde in filtered seawater for 3 h at 4°C , washed with PBS containing 0 . 1% Triton X-100 ( PBST ) , and incubated in blocking buffer ( PBST+10% goat serum ) for 3 h at room temperature ( RT ) . Embryos were incubated overnight with the primary antibodies diluted 1/200 in blocking buffer at 4°C , followed by three washes within 8 h with PBST at 4°C . Secondary antibodies , diluted 1/300 , were incubated overnight at RT , followed by three washes with PBST at 4°C within 8 h . pS19 MRLC antibody staining was performed according to a published protocol [116] . After the procedure , the embryos were counterstained with 3 unit/ml BODIPY FL phallacidin ( Invitrogen , B607 ) for 1 h at RT and washed three times . To detect mitotic nuclei in Ciona embryos , we used an anti-phospho-histone H3 antibody ( Ser 10 , Upstate/Millipore , 06-570 ) at a 1/200 dilution , followed by an anti-rabbit Alexa-568-coupled secondary antibody ( Invitrogen A11011 , dilution 1/1 , 000 ) . The embryos were counterstained with DAPI ( 1 µg/ml ) . To stain actin filaments in Oikopleura dioica embryos , embryos were fixed in 4% formaldehyde containing 0 . 5 M NaCl and 0 . 1 M MOPS ( pH 7 . 5 ) overnight at 4°C . After several washes in PBS , samples were incubated in 2 unit/ml BODIPY FL phallacidin ( Invitrogen , B607 ) for 7 d at 4°C . To detect nuclei in S phase , we used the thymidine analog 5-bromo-2′-deoxyuridine-5′-monophosphate ( BrdU ) . Live embryos at late tailbud 3–4 stages [45] were incubated for 45 min at room temperature in 5 mM BrdU in filtered sea water ( FSW ) ; then quickly rinsed and thoroughly washed in FSW twice for 10 min . Embryos were then fixed overnight at 4°C in 4% paraformaldehyde in PBS , pH 7 . 5 containing 0 . 5 M NaCl and 0 . 1% Tween 20 ( Tw ) . After several washes , embryos were permeabilized with washes in PBS 0 . 5% Triton X100 and a 10′ incubation in acetone at −20°C . Before immunohistochemistry , samples were incubated in 4 N HCl for 10 min to denature the DNA , then washed in PBS 0 . 1% Tw . Embryos were blocked for 2 h at room temperature in PBS containing 0 . 2% Triton X100 , 0 . 3% BSA , and 10% goat serum . BrdU incorporation was then detected using a primary mouse anti-BrdU antibody ( Roche , 11 170 376 001 , 1/50 ) and secondary anti-mouse Alexa 568–coupled antibody ( Invitrogen , A-11004 , 1/1 , 000 ) . Nomarski images were taken using a Nikon Eclipse ( E800 ) microscope equipped with a 40× objective ( NA 1 . 00 ) and a SPOT RtKE CCD camera ( Diagnostic Instruments ) , and a Zeiss Imager . M2 microscope equipped with a 100× objective ( NA 1 . 30 ) and a pco . sensicam camera ( Pco Imaging ) . Confocal images were taken using a Leica TCS SP5 confocal laser-scanning microscope equipped with 40× oil-immersion and 63× water-immersion objectives ( NA 1 . 25 and 1 . 40 , respectively ) . If necessary , embryos were sedated using 0 . 2% MS222 ( Sigma , A5040 ) . To visualize the dynamics of F-actin ( mCherry-UtrCH and lifeact-mEGFP ) and myosin filaments ( mCherry-MRLC ) , we collected z-stacks of notochord cells at regular intervals , as specified in the movie legends . ImageJ and Leica TCS SP5 LAS AF software package were used to perform maximum projections and to construct movies . Fluorescence intensity was measured with ImageJ . The kymograph was compiled using the kymograph plugin in ImageJ . The velocity of single actin filaments was determined by calculation from the kymograph and by manual tracking in time-lapse movies using the Manual Tracking plugin in ImageJ . Colocalization of actin and myosin was analyzed using the Intensity Correlation Analysis plugin in ImageJ . The Leica TCS SP5 was utilized to bleach the whole equatorial domain of notochord cells . Maximum laser power at 561 nm was used for an empirically determined number of iterations to achieve bleaching throughout the full thickness of the cortical equatorial actin signals . After bleaching , images were taken at regular intervals ( between 4 . 5 and 9 s ) with the same laser at 30% laser intensity . To calculate the halftime of recovery , the signal intensity in the region of interest ( ROI ) was measured over time . The background obtained from areas outside the embryo was subtracted . Bleaching during image acquisition was corrected by calculating the loss of signals in unbleached notochord cells and from the signal intensities in the image series before bleaching . The intensity was plotted as a function of time , and the half-time of recovery , t1/2 , was extracted . The velocity was calculated from t1/2 of the whole bleached region and the width of ¼ of the bleached region under the assumption of a directed flow of the filaments from the lateral domains toward the equator . Time delays between basal blebbing and luminal membrane movement were determined by cross-correlation . We measured the relative locations of the membrane at the basal bleb and the apical/luminal domain over time using ImageJ . Resulting curves were smoothed using a bisquare algorithm implemented in SigmaPlot software ( Systat Software ) . Cross-correlation analysis was performed applying Igor Pro ( Wavemetrics ) cross-correlation function . In situ hybridization was carried out as described by Wada et al . [117] . Cdc45 was amplified with 5′-ATGTTAATTACCGACCCAGTAAAGG-3′ and 5′-TTATGACATTATAGTGATGAGAGCG-3′ and cloned into pCRII TOPO ( Invitrogen ) . The plasmid was linearized using Xho I and transcribed using DIG RNA Labeling Kit Sp6 ( Roche ) . | The actomyosin cytoskeleton is the primary force that drives cell shape changes . These fibers are organized in elaborate structures that form sarcomeres in the muscle and the contractile ring during cytokinesis . In cytokinesis , the establishment of an equatorial actomyosin ring is preceded and regulated by many cell cycle events , and the ring itself is a complex and dynamic structure . Here we report the presence of an equatorial circumferential actomyosin structure with remarkable similarities to the cytokinetic ring formed in postmitotic notochord cells of sea squirt Ciona intestinalis . The notochord is a transient rod-like structure found in all embryos that belong to the phylum Chordata , and in Ciona , a simple chordate , it consists of only 40 cylindrical cells arranged in a single file , which elongate individually during development . Our study shows that the activity of the equatorial actomyosin ring is required for the elongation of the notochord cells . We also find that cortical flow contributes significantly to the formation of the ring at the equator . Similar to cytokinetic cells , we observe the formation of membrane blebs outside the equatorial region . Our analyses suggest that cooperation of actomyosin ring-based circumferential constriction and bleb-associated contractions drive cell elongation in Ciona . We conclude that cells can utilize a cytokinesis-like force generation mechanism to promote cell shape change instead of cell division . | [
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"biology"
] | 2014 | An Equatorial Contractile Mechanism Drives Cell Elongation but not Cell Division |
MicroRNAs ( miRNAs ) are a class of short non-coding RNA that play important roles in disease processes in animals and are present in a highly stable cell-free form in body fluids . Here , we examine the capacity of host and parasite miRNAs to serve as tissue or serum biomarkers of Schistosoma mansoni infection . We used Exiqon miRNA microarrays to profile miRNA expression in the livers of mice infected with S . mansoni at 7 weeks post-infection . Thirty-three mouse miRNAs were differentially expressed in infected compared to naïve mice ( >2 fold change , p<0 . 05 ) including miR-199a-3p , miR-199a-5p , miR-214 and miR-21 , which have previously been associated with liver fibrosis in other settings . Five of the mouse miRNAs were also significantly elevated in serum by twelve weeks post-infection . Sequencing of small RNAs from serum confirmed the presence of these miRNAs and further revealed eleven parasite-derived miRNAs that were detectable by eight weeks post infection . Analysis of host and parasite miRNA abundance by qRT-PCR was extended to serum of patients from low and high infection sites in Zimbabwe and Uganda . The host-derived miRNAs failed to distinguish uninfected from infected individuals . However , analysis of three of the parasite-derived miRNAs ( miR-277 , miR-3479-3p and bantam ) could detect infected individuals from low and high infection intensity sites with specificity/sensitivity values of 89%/80% and 80%/90% , respectively . This work identifies parasite-derived miRNAs as novel markers of S . mansoni infection in both mice and humans , with the potential to be used with existing techniques to improve S . mansoni diagnosis . In contrast , although host miRNAs are differentially expressed in the liver during infection their abundance levels in serum are variable in human patients and may be useful in cases of extreme pathology but likely hold limited value for detecting prevalence of infection .
Helminths are parasitic worms that infect a third of the world's population and cause a diverse range of health consequences leading to significant social and economical burdens [1] , [2] . Schistosomiasis is a chronic disease caused by blood flukes of the genus Schistosoma that affects more than 200 million people worldwide and is second only to malaria as the most important lethal human parasitic disease in tropical and subtropical regions . Schistosomiasis is predominantly caused by hepatic S . mansoni and urogenital S . haematobium [3] . It is estimated that the mortality rates due to haematemesis ( S . mansoni ) and renal failure ( S . haematobium ) are around 130 , 000 and 150 , 000 per year respectively [4] . In addition , schistosomiasis is associated with anaemia , diarrhoea , under nutrition , chronic pain and exercise intolerance , which are estimated to contribute to 0 . 02–0 . 15 disability-adjusted life-years ( DALY ) [5] . Diagnosis of schistosome infection is crucial for patient management , evaluation of treatment efficiency , monitoring of disease transmission and success of control strategies , as recommended by the World Health Organization [6] . In the field , S . mansoni and other intestinal schistosomes are currently diagnosed through the detection of the parasite eggs in stool specimens using microscopic techniques such as Kato-Katz or ether-concentration [7] . While these techniques are relatively simple , inexpensive and specific , their major drawbacks include poor sensitivity in detecting low-intensity infections ( for example , in children ) , their inability to detect pre-patent or single sex infection and their failure to detect infection in individuals where eggs are trapped in tissues and not excreted [8] . Available antibody-based assays are useful for diagnosis in some cases ( e . g . foreign travellers ) but they cannot differentiate past and active infection and can also cross-react with antigens from other helminths [9] . These assays therefore do not offer a definitive diagnosis in schistosome-endemic areas . Recent studies have shown success with point-of-care tests for Schistosoma circulating cathodic and anodic antigens ( CCA and CAA , respectively ) in serum and urine , which decrease rapidly after chemotherapy [8] , [10] , [11] , [12] , [13] , [14] and these are now being further developed for use in the field [15] . Detection of schistosome DNA in urine and stool samples or plasma by the polymerase chain reaction ( PCR ) method is another strategy for routine diagnosis of infection that has shown promising results [16] , [17] , [18] , [19] , [20] . Here we examine whether microRNAs ( miRNAs ) , which are extremely stable in serum and detectable by quantitative reverse transcription PCR ( qRT-PCR ) could provide an additional diagnostic tool for S . mansoni infection . miRNAs are a class of naturally occurring small non-coding RNA produced from animal , plant and viral genomes [21] . They are incorporated into the RNA-induced silencing complex ( RISC ) and function by binding to messenger RNAs ( mRNAs ) and inhibiting translation and/or causing mRNA destabilization [22] . Depending on the genes they target , miRNAs have diverse functions inside cells , from regulation of developmental programming to viral-host interactions [23] , [24] , [25] . In the last 5 years , reports have shown that miRNAs circulate in serum in a cell-free form and many cell types secrete miRNAs through encapsulation within exosomes or in association with specific proteins [26] , [27] . These extracellular RNAs have been implicated in cell-to-cell communication in a range of systems [28] , [29] , and have been shown to be extremely stable in body fluids [27] , [30] . They have received extensive attention for their promise as biomarkers of disease , including cancer [31] , [32] , [33] . Extracellular miRNAs have also been shown to be altered in human serum and/or plasma in infection settings , including hepatitis C and hepatitis B infections [34] , [35] as well as during pulmonary tuberculosis [36] . A recent report has also identified miRNAs derived from rice in human serum [37] , sparking interest in foreign RNA in body fluids and its diagnostic potential . Here we investigate the potential of miRNAs to act as tissue and serum biomarkers of experimental mouse and natural human S . mansoni infection . We demonstrate that several host miRNAs are dysregulated in the liver of mice during S . mansoni infection , but do not serve as reliable serum biomarkers of infection in humans . In contrast , we identify at least three parasite-derived miRNAs in the serum of mice infected with S . mansoni that are also detected in human patients and can distinguish ‘egg-negative’ from ‘egg-positive’ individuals with high specificity and sensitivity . We anticipate that parasite-derived miRNAs may provide a general platform for specific and non-invasive detection of active helminth infection .
For miRNA array analysis of liver and Illumina sequencing of serum in experiment 1 , 8–10 week old C57BL/6 mice were left uninfected or infected percutaneously with ∼180 S . mansoni cercariae , weighed regularly , and euthanized 7 weeks post infection . For the 12-week time course , 8–10 week old C57BL/6 mice were left uninfected or infected percutaneously with ∼80 cercariae , weighed regularly , and euthanized at 4 , 6 , 8 and 12 weeks post infection . Whole blood was drawn from mice by cardiac puncture . The needle was removed before emptying the syringe to avoid haemolysis and blood was allowed to sit for 1 h at RT to clot . Serum was separated by centrifugation at 2500 g for 15 min at 4°C , and the supernatant was collected into a new tube and spun at 10 , 000 g for 1 min to remove remaining cells . The resultant supernatant was transferred into a new tube and stored at −20°C prior to RNA extraction . Human serum was screened retrospectively from samples obtained from schistosome endemic areas in Zimbabwe and Uganda . The study group included in this investigation ( Zimbabwe ) was part of a larger study on the molecular immunoepidemiology of human schistosomiasis ( carried out between November 1999 and March 2000 ) and had not been included in the National Schistosome Control Programme and therefore had not received treatment for schistosomiasis or other helminth infections . After collection of all samples , all participants were offered anti-helminthic treatment with the recommended dose of praziquantel ( 40 mg/kg of body weight ) . The selection of samples for screening here was based on availability of sufficient serum for miRNA analysis , and comprised five ‘egg positive’ individuals with an average egg per gram in stool ( epg ) = 108 , range: 39-277 and nine ‘egg-negative’ individuals ( Table 1 ) . According to the WHO's classification , Zimbabwe has high to moderate levels of S . haemobium infection ( prevalence ranging from 10% to greater than 70% ) but low S . mansoni prevalence ( less than 10% ) . The selection of serum for screening from Piida ( Uganda ) participants was based on availability of sufficient material and comprised twenty individuals infected with S . mansoni with an average epg = 1117 ( range: 105-4030 ) and ten egg-negative individuals . The study group included in this investigation were part of a larger study carried out in Butiaba village , adjacent to Lake Albert , Masindi district , Uganda in 1996 , described further in [38] . The cohort had moderate to high S . mansoni infection intensities and prevalence of 91% . After collection of stool and serum samples all the study participants , irrespective of the infection status , received 2 doses of praziquantel , 40 mg/kg of body weight , 6 weeks apart . Efficacy of chemotherapy was assessed 6 weeks after each treatment . Animal experiments were conducted under a Project License granted by the Home Office ( United Kingdom ) , reference 60/4104 , in accordance with local guidelines and approved by the Ethical Review Committee of the University of Edinburgh . For the human serum samples collected in Chiredzi , permission to conduct the work in this province was obtained from the Provincial Medical Director . Ethical approval was received from the Medical Research Council of Zimbabwe ( MRCZ ) . Only compliant participants were recruited into the study and they were free to drop out at any point during the study . At the beginning of the study , participants and their parents/guardians ( in case of children ) had the aims and procedures of the project explained fully in the local language , Shona , and oral consent ( as was customary ) was obtained from participants and parents/guardian before parasitology and blood samples were obtained . For the samples collected in Piida , ethical clearance was obtained from the Uganda National Council of Science and Technology ( ethics committee for Vector Control Division , Ugandan Ministry of Health ) . The aims and procedures were explained to the local community at the start of the study and oral consent was obtained from all adults and from the parents/legal guardians of all children under 15 who were willing to participate . Due to cultural reasons and low levels of literacy , oral consent is deemed acceptable by the Ugandan Ministry of Health and was approved by the Uganda National Council of Science and Technology . Upon oral consent participants were enrolled in the study with a written record of their name , age , sex and case number , this served as both the record of oral consent and enrolment record . Participants in the Zimbabwe study were checked for both urogenital and intestinal schistosomiasis and for inclusion in this analysis had to be free of any soil-transmitted helminths and also free of S . haematobium infection to avoid cross reactivity between different helminth parasites . For the analysis of urogenital schistosome infection ( S . haematobium ) participants submitted three urine and three stool samples ( over four consecutive days ) . 10 ml of each sample received was processed on the day of collection by a urine filtration method [39] . Stool samples were prepared and examined on the day of collection using the Kato-Katz faecal smear for detection of S . mansoni eggs and soil transmitted helminths; this was carried out by trained and experienced technical staff from the National Institute of Health Research [40] . A single slide for microscopic examination was prepared from each urine and stool sample . Serum was prepared from 10 ml venous blood collected from study participants , frozen at −20°C and afterwards stored at −80°C . Samples were transported frozen to Edinburgh and stored at −80°C prior to serological assays . Participants in the Ugandan study had duplicate 50 mg Kato-Katz slides prepared from 3 consecutive stool samples for detection of S . mansoni eggs , expressed as mean epg; this was carried out by trained and experienced technical staff from the Vector Control division at the Ministry of Health in Uganda . Serum was prepared from 10 ml venous blood samples , frozen at −20°C and transported to Cambridge for storage at −80°C prior to serological assays . For the 12-week time course experiment , total RNA was extracted from serum using the miRVana PARIS extraction kit ( Ambion ) , according to the manufacturer's protocol . In brief , 100 µl of serum was thawed on ice , mixed with an equal volume of 2× Denaturing Solution and kept on ice for 10 min . Samples were extracted with an equal volume of acid-phenol chloroform , vortexed for 30 s and centrifuged for 10 min at 10 , 000 g at RT . The aqueous phase was mixed with 1 . 25 volumes of 100% ethanol and added to the mirVana PARIS column . The column was washed and RNA eluted in 100 µl of 0 . 1 mM EDTA . RNA samples were stored at −20°C prior to further analysis . Extracted RNA was quantified by Qubit ( Invitrogen ) . Due to small volumes and low amounts of RNA in available human serum samples the extraction protocol was adjusted to result in more concentrated RNA . To do this , 50 µl of serum was thawed on ice , mixed with 50 µl of ddH2O and 100 µl of 2× Denaturing Solution ( as supplied in the miRVana Paris kit ) and kept on ice for 10 min . Samples were spiked with 10 fmoles of a synthetic RNA , Spike1: 5′-UGCUGAAUGCGUAGCUAUAAGC-3′ ( IDT ) and extracted with an equal volume of acid-phenol chloroform , vortexed for 30 s and centrifuged for 10 min at 10 , 000 g at RT . The aqueous phase was mixed with 1/10 volume of 3M sodium acetate , 10 µg of GlycoBlue ( Ambion ) and an equal volume of isopropanol . Samples were allowed to precipitate overnight at −20°C and were then centrifuged at >10 , 000 g at 4°C . Pellets were washed twice with 75% ethanol , air-dried and then resuspended in 25 µl of 0 . 1 mM EDTA . The total RNA concentration was below the limit of detection based on Qubit ( Invitrogen ) . Liver tissue was immersed in RNA Later Solution ( Ambion ) overnight at 4°C prior to extraction using TRIzol Reagent ( Invitrogen ) according to the manufacturer's protocol . RNA was quantified by NanoDrop and integrity assessed by 10% PAGE or Bioanalyzer 2100 . All RNA samples used in the microarray analysis had RIN >8 . For reverse transcription of mouse serum samples , a fixed amount of extracted RNA ( 1 . 5 ng ) was used as an input and 0 . 1 fmoles of a synthetic RNA , Spike2: 5′-CGUAUCGAGUGAUGUCACGUA-3′ , was added at the RT step for normalization . For human serum samples , where the total RNA concentration was below the detection limit , a fixed volume of RNA ( 5 µl ) , corresponding to 10 µl of extracted serum , was used as the input and Spike1 ( added at the time of purification ) was used for normalization . For reverse transcription of RNA extracted from liver , 200 ng of total RNA was used in each reaction . Reverse transcription reactions were performed using the miScript System ( Qiagen ) according to the manufacturer's protocol . PCR was carried out with SYBR green real-time PCR assays ( Qiagen ) and miScript primers to detect mouse and human miRNAs , according to the manufacturer's protocol ( Qiagen ) . Primers for S . mansoni-specific miRNAs and the synthetic spikes were used at 200 nM final concentration and were purchased from Invitrogen: miR-277 , 5′-TAAATGCATTTTCTGGCCCG-3′ , miR-2162-3p , 5′-TATTATGCAACGTTTCACTCT-3′ , miR-3479-3p , 5′-TATTGCACTAACCTTCGCCTTG-3′ , bantam , 5′- TGAGATCGCGATTAAAGCTGGT-3′ , miR-2a-3p , 5′-TCACAGCCAGTATTGATGAAC-3′ , miR-71a-3p , 5′- TGAAAGACGATGGTAGTGAGAT-3′ , sma-miR-n1 , 5′-AACTCAGTGGCCTATCGGT-3′ , sma-miR-n2 , 5′-TCAGCTGTGTTCATGTCTTCGA-3′ , sma-miR-n3 , 5′- TGGCGCTTAGTAGAATGTCACCG-3′ , Spike1 , 5′-TGCTGAATGCGTAGCTATAAGC-3′ , Spike2 , 5′-CGTATCGAGTGATGTCACGTA-3′ . Data were collected on a Light Cycler 480 System ( Roche ) with the following temperature profile: pre-denaturation 15 min at 95°C followed by 50 cycles of denaturation for 15 s at 95°C , annealing for 30 s at 55°C , elongation for 30 s at 70°C . The efficiencies of pre-optimized miScript host miRNA probes ( Qiagen ) were measured from standard curves and ranged between 93–100% and the efficiency of custom probes ranged from 87–97%; both displayed homogenous melting curves and amplification products of the expected size , as described in [41] , which were examined here by 6% TBE PAGE ( data not shown ) . Two technical replicates were carried out for each biological replicate . Nuclease free water was used as a non-template control . For the array analysis , 1 µg of total RNA was labelled using the Hy3 power labeling kit ( Exiqon ) and hybridized to codelink slides printed with the miRCury 8 . 1 probe set as described elsewhere [42] . Hybridization and washing were carried out following the manufacturer's protocols ( Exiqon ) . Background signal was subtracted from foreground signal and data were transformed to log-2 scale . Between-array normalization was carried out using global array percentiles ( matching median of each array ) ; triplicate probes were represented by the median for each array . Empirical Bayes moderated t statistic ( eBayes ) was used to test the null hypothesis of “no differential expression” between uninfected ( n = 3 ) and infected ( n = 3 ) liver samples . Since this array was only used as a filter for further validation , the p values were not adjusted for multiple testing . The Exiqon 8 . 1 arrays contained 384 probes specific for mouse miRNAs . For analysis of miRNAs in liver samples , the relative fold change between naïve and infected samples was calculated using the 2−ΔΔCt method [43] , normalized to miR-16; values for infected mice were compared to values for age-matched naïve controls and the median value for naïve mice was set to 1 for the purpose of calculating fold change . For serum miRNA data analysis , Ct values were “median-normalized” to synthetic RNA spike oligos as described previously [27]: relative change was calculated as 2−Ctn , where Ctn stands for normalized Ct values . The spike-in sequences did not match any known miRNA in miRBase and the primers for detecting these did not yield signals in serum by qRT-PCR , indicating that they do not cross-hybridize with mouse or human small RNAs ( data not shown ) . Fold change was calculated as the ratio of the relative change value of the sample compared to an average of the relative change values of uninfected samples . For the cumulative analysis of miRNAs , the arithmetic mean of fold changes for miR-277 , miR-3479-3p and bantam were used . Statistical analysis of qRT-PCR data and receiver operator characteristic ( ROC ) curve analysis ( 95% confidence intervals ) was performed with GraphPad Prism ( Version 6 ) software . Two-way ANOVA followed by a Sidak multiple comparison test was used to calculate statistical differences for the mouse miRNA time course data from serum and liver . For the parasite miRNA serum time course , one-way ANOVA followed by Holm-Sidak multiple comparison was used . For analysis of the human serum samples , the Man-Whitney test was used and p-values of <0 . 05 were considered statistically significant . The measurement of miRNA levels by qRT-PCR was carried out by a trained doctoral student who was not blinded to the results of the infection status of each sample . Of the samples available for screening , none were excluded from the analysis . For small RNA sequencing in experiment 1 , total RNA was extracted from serum of 8 pooled S . mansoni-infected mice ( Wk 7 , 180 cercariae ) and 8 uninfected age matched controls ( 400 µl total volume ) according to the miRVana PARIS protocol ( as described above ) . The small RNAs were size selected by 15% PAGE and prepared according to the Illumina small RNA Sample Preparation Kit version 1 . 5 and sequenced on the GAIIX . For small RNA sequencing in experiment 2 , total RNA was extracted from serum of 3 pooled S . mansoni infected mice ( Wk 8 , 80 cercariae ) and 3 uninfected age matched controls ( 300 µl total volume ) according to the miRVana PARIS protocol . The library was prepared according to the TruSeq Small RNA protocol ( without size-selecting small RNA ) and sequenced on the HiSeq2 . Raw reads were obtained in fastq format and 3′ adapters trimmed using cutadapt , requiring at least a 6 bp match to the adapter sequence and a quality threshold of 20 . Only reads that contained the adapter were retained; reads were subsequently collapsed on primary fasta sequence and only reads present at ≥2 copies were analyzed . Trimmed , collapsed reads ≥17 bp were then aligned to mouse ( MM9 ) or S . mansoni genomes ( V5 . 0 ) using BOWTIE version 0 . 12 . 5 , requiring a perfect match to the full length of the sequence . Reads that mapped to either genome were then BLASTN aligned against the RFAM database [BLASTN parameters: -max_target_seqs 1 -outfmt ‘6 std qseq sseq’ -task blastn -word_size 6 -dust no] and categorized according to matches to Rfam class ( e . g . rRNA , tRNA , etc . ) . Mouse reads without rfam similarities ( other than miRNAs ) were aligned to mature miRNAs in miRBase version 19 . Some trimmed miRNA reads aligned to more than one family member: the assignment of these ambiguous reads is designated with “X” in Table S3 . RNAs that aligned to the S . mansoni genome and did not show RFAM similarities were passed to mirDeep2 . 0 . 0 . 5 using platyhelminth miRNAs from miRBase 19 as guides ( Table S4 ) ; reads mapping to known miRNAs from miRBase were identified regardless of miRdeep score , for prediction of novel miRNAs a cut-off value of 0 was used for reporting in Table 1 .
miRNAs are dysregulated in most disease contexts and play important roles in mediating how cells respond to insult and infection ( reviewed in [44] ) . Approximately 4–6 weeks after S . mansoni infection , mature female parasites produce eggs , some of which are carried by the blood-flow to the liver where they become trapped [45] . The host immune response induced by the presence of the egg antigens leads to the formation of granulomatous lesions , which are composed of immune cells and collagen fibres [46] and result in fibrosis and associated pathology . In order to identify miRNAs associated with S . mansoni-induced liver pathology , and to prioritise candidates for further screening as biomarkers , we first compared expression profiles of miRNAs in livers of naïve mice or mice that were infected with S . mansoni at a high dose ( ∼180 cercariae ) . Tissues were collected at 7 weeks post infection , at which time substantial granulomas were observed ( data not shown ) . A total of 33 mouse miRNAs were differentially expressed: 26 miRNAs were up-regulated and 7 miRNAs were down-regulated in infected mice , based on a fold change cut-off of ≥2 and p value cut off <0 . 05 ( Table S1 , Fig . S1 ) . The miRNAs that displayed the largest differential expression included miR-199a and miR-214 , which are known to be altered in liver fibrosis caused by hepatitis C infection or induced by carbon tetrachloride [47] , [48] . Among the down regulated miRNAs was the liver-enriched miR-122 , which is dysregulated during hepatitis C infection , acetaminophen overdose and hepatocellular carcinoma and is involved in lipid metabolism [49] , [50] . For validation of the microarray results , the miRNAs that displayed the largest fold change were quantified by qRT-PCR and normalized to miR-16 ( a total of 6 up-regulated miRNAs and 6 down-regulated miRNAs were examined ) . Consistent with the array results , there was an increase in miR-199-5p , miR-199-3p , miR-214 , miR-21 , miR-210 , and a reduction of miR-192 , miR-194 , miR-365 , miR-122 and miR-151 in the liver tissue of S . mansoni infected mice as compared to naïve mice; miR-9 and miR-744 did not display differential expression and were not analysed further ( Table 1 ) . All of these miRNAs are perfectly conserved in mouse and human . Between weeks 6 and 12 , female parasites continue to produce ∼300 eggs per day [51] , resulting in an increase in the number of granulomas in the liver and the development of fibrosis [45] . For the 10 miRNAs validated to be differentially expressed at 7 weeks post infection , we next examined their temporal expression between 4–12 weeks post infection using a lower parasite dose ( 80 cercariae ) . All data from infected mice were compared to age-matched naive mice . To account for differences in RNA extraction or qRT-PCR efficiency , the data were normalised to miR-16 , which displayed stable expression in the liver during infection ( Fig . S2 ) . Of the 10 miRNAs examined , all except miR-365 and miR-151 were differentially expressed between naïve and infected mice by 6–8 weeks post infection ( Fig . 1 , Table S2 ) . This timing correlated with the deposition of eggs in the liver , which were detected by 6 weeks post infection and increased by 8 and 12 weeks post infection ( Fig . S3 ) . Our results suggest that these cellular miRNAs represent tissue biomarkers of infection that may play a role in the development and progression of liver fibrosis induced by S . mansoni egg deposition . Several studies in non-helminth systems have shown that liver-derived miRNAs are detectable in serum and can be used as biomarkers in disease states [52] , [53] , [54] , [55] , [56] . We therefore examined whether the murine miRNAs that are altered in liver tissue are similarly altered in serum during S . mansoni infection . qRT-PCR was used to measure miRNA levels in the serum of mice infected with S . mansoni over the 12 week time course . The methodology of miRNA analysis in body fluids is not well standardized , and it is still not clear which small RNAs are appropriate for normalization [57] , [58] , [59] , [60] . Here we used a constant amount of total RNA in the reverse transcription reaction . To account for any variation in qRT-PCR efficiency due to contaminants , miRNA levels were normalized to a synthetic RNA oligo ( “spike-in” ) that was included at the reverse-transcription step . The ratio of miRNA levels in infected versus age-matched naïve mice was quantified at each time point and plotted as fold change ( Fig . 2 ) . Compared to the analysis of liver samples , there is more variation in the serum miRNA levels between biological replicates . As shown in Fig . 2 , the levels of miR-192 , miR-194 and miR-122 in serum do not change between 4–12 weeks post infection , whereas five of the miRNAs that are up-regulated in the liver are also significantly elevated in serum at 12 weeks post infection ( p<0 . 05 ) , ranging from 2 . 6 fold ( miR-21 ) to 4 . 7 fold ( miR-214 ) ( Table S2 ) . These five host miRNAs represent potential serum biomarkers of S . mansoni infection . However , since their levels do not change until 12 weeks post infection in mice , they may only be useful in cases of more advanced pathology . Multiple cell types release or secrete miRNAs into the circulation [59] , [61] and it is possible that other miRNAs , beyond those differentially expressed in the liver , might represent biomarkers of infection . To examine this in an unbiased fashion , small RNAs from serum of naïve mice or mice infected with S . mansoni were sequenced using the Illumina platform . Small RNA libraries were prepared in two independent experiments , using two different preparation methods ( Methods ) . In both experiments , the majority of small RNA reads aligned to the mouse genome ( ranging from 63–71% , Table 2 ) . A small percentage of reads unambiguously aligned to the S . mansoni genome in infected mice ( 0 . 04–0 . 14% ) ; <0 . 01% of reads mapped to the S . mansoni genome in naïve samples . Interestingly , the majority of reads in all samples were derived from tRNAs: 92–98% of the reads that mapped to the mouse genome and 42–100% of reads that mapped to the S . mansoni draft genome ( Table 2 ) . It is important to note , however , that due to the sequence similarity of the tRNAs between species and the scope for post-transcriptional editing , we cannot at this point definitively determine the organism from which these derive . Only 1–6% of the reads that mapped to the mouse genome were miRNAs ( Table 2 , listed in Table S3 ) . There was no correlation between differences in host miRNA levels in naive and infected mice from the two experiments ( data not shown ) , this could relate to the different doses , although it is not possible to derive statistical conclusions from these data due to low read numbers . A total of 78 and 29 mature miRNAs are known to be encoded by the trematodes S . japonicum and S . mansoni , respectively [62] , [63] , [64] , [65] , and further miRNAs have been predicted [62] . Analysis of the reads that mapped to the S . mansoni draft genome using the miRdeep2 program [66] identified at least 11 miRNAs from infected samples: 8 of these were positively identified based on identity to known miRNAs in S . mansoni and/or S . japonicum ( Table 3 ) [64] , [65] and 3 are predicted by miRdeep ( here named sma-miR-n1 , sma-miR-n2 and sma-miR-n3 ) . The predicted stem-loop structures for the putative pre-miRNAs are shown in Fig . 3; since the depth of coverage of S . mansoni reads in this study was very low and reads did not map to both arms of the hairpin , these cannot yet be considered prototypical miRNAs . However , sma-miR-n3 shares a seed site with Schmidtea mediterranea miR-2160 and was annotated as sma-miR-8437 in a study of S . mansoni miRNAs published after submission of this manuscript [67] . Additional analysis of the datasets allowing 1 mismatch to the S . mansoni draft genome identified one further miRNA from infected but not naïve serum: miR-277 , which is identical to miR-277 in S . japonicum and Echinococcus granulosus but has a C→T mutation at position 17 in relation to the S . mansoni draft genome ( Table 3 ) . Other reads from infected samples that aligned to S . mansoni but did not make the miRdeep2 cut-offs are provided in Table S4 . It is possible that some of these less abundant sequences derive from real miRNAs but the coverage in these studies is not sufficient to determine this . To determine the kinetic profile of parasite miRNAs in serum during S . mansoni infection , qRT-PCR analysis was carried out as described above , using primers specific for 9 of the 11 parasite miRNAs . The other 2 miRNAs , sma-miR-10-5p and sma-let-7-3p , were excluded from analysis because they are highly similar to homologous mouse miRNAs that are present at >100 fold higher read frequencies ( Table S3 ) . Importantly , most miRNAs in helminth parasites have evolved after the last common ancestor with their vertebrate hosts and are therefore distinguishable in sequence , however several miRNAs are perfectly conserved across animals or highly similar in sequence [63] . Several of the parasite-specific probes showed a signal in the serum of naïve mice , which is presumably due to cross-hybridization with endogenous small RNAs . In cases where no signal was observed in naïve mice , the maximum cycle value of 50 was set as background for the purpose of calculating signal over noise ( which we interchange here with “fold change” ) . Six of the nine parasite miRNA probes tested ( miR-277 , bantam , miR-3479-3p , miR-2a-3p , miR-n1 , miR-n2 ) showed a statistically significant signal over noise at 8 or 12 weeks post infection ( Fig . 4 , p<0 . 05 ) ; the three miRNAs that were not reliably detected ( miR-n3 , miR-71a-3p , miR-2162-3p ) were not analysed further . The average signal over noise ratios for each probe during the time course of infection are provided in Table S5 and range from 4 . 2 to >3 , 000 . Based on the results described above , we extended our analyses to human patients , using the 6 parasite miRNAs and 5 mouse miRNAs that displayed differential abundance in serum of infected compared to naïve mice . Serum samples from two field sites were examined: an area of high infection in the Piida community of Uganda and an area of low infection in the Chiredzi community of Zimbabwe . The high infection samples were collected from mixed-age participants from Piida diagnosed as S . mansoni infected , termed ‘egg positive’ and compared to volunteers from the same community with undetectable parasite eggs in the stool , termed ‘egg-negative’ . The low infection samples were collected from children in Chiredzi diagnosed with S . mansoni and compared to age matched participants with undetectable eggs by standard stool examination methods . Demographic data of individuals are provided in Tables 4 and 5 . The signal over noise was calculated as described above , using synthetic spike-ins for normalization . miR-n1 , miR-n2 and miR-2a-3p were below the detection limit ( Ct = 50 ) in both ‘egg-positive’ and ‘egg-negative’ samples . The 5 host miRNAs were detectable in serum ( miR-21 , miR-199-3p , miR-199-5p , miR-210 , miR-214 ) but showed variable abundance and failed to differentiate ‘egg-positive’ and ‘egg-negative’ participants ( Fig . S4 ) . In contrast , three out of the six parasite miRNAs ( bantam , miR-277 and miR-3479-3p ) displayed a significant signal over noise level in the serum of S . mansoni infected individuals ‘egg-positive’ from both high ( Fig . 5A ) and low ( Fig . 5B ) infection endemic areas , compared to the ‘egg-negative’ participants from the same communities ( p<0 . 05 , Mann – Whitney test ) . Data presented using ROC curves show that the single parasite miRNAs discriminated between S . mansoni ‘egg-negative’ and ‘egg-positive’ with an area under the curve ( AUC ) of 0 . 785 , 0 . 790 , 0 . 768 for bantam , miR-277 and miR-3479-3p , respectively , in the individuals from Uganda ( Fig . 5A ) and 0 . 889 , 0 . 933 , 0 . 911 in the individuals from Zimbabwe ( Fig . 5B ) . Using optimal cut-off points , this translates to detection of S . mansoni infected individuals with specificity/sensitivity of 80%/60% , 80%/70% and 80%/60% , in the patients from Uganda ( Fig . 5A ) and specificity/sensitivity of 100%/60% , 89%/80% and 89%/80% respectively in the patients from Zimbabwe ( Fig . 5B ) . A repeated measurement of the parasite miRNA levels in the same samples displayed Pearson correlation values between 0 . 86 to 0 . 95 and comparable specificity/sensitivity values ( Table S6 ) . When combining the data for all three of the miRNAs into a cumulative value , the AUC increased to 0 . 845 and 0 . 933 for each cohort of participants . This resulted in improved specificity/sensitivity in detection for samples from Uganda ( 80%/90% ) using a fold change cut-off of 1 . 189 ( Fig . 6 ) . This approach is very similar to a recent report that uses a “miRNA score” based on cumulative normalized signals of miRNAs [68]; analysis of our data based on cumulative fold change or cumulative normalized signals yields very similar results ( Fig . S5 ) . These results show that combining data for bantam , miR-277 and miR-3479-3p may improve sensitivity of S . mansoni diagnosis compared to analysis of individual miRNAs .
The recent evidence that miRNAs can be released into circulation from mammalian cells and tissues has stimulated extensive interest in the potential use of these molecules as non-invasive biomarkers [31] , [32] , [57] . MiRNA-based diagnostics are being developed for a number of diseases and although qRT-PCR is the most common detection method at present , there is extensive interest in improving and diversifying detection technologies , which may provide more field-friendly tools . Since miRNAs have been shown to be extremely stable in body fluids [27] , [30] , [69] , we anticipate that these nucleic acids could be particularly useful as diagnostics in field settings where collection and storage conditions can be difficult to control . Here we find that miRNAs derived from the helminth parasite S . mansoni are present in infected mouse and human serum and offer advantages over endogenous miRNAs as biomarkers of infection . Specifically , we find 9 known miRNAs and at least 2 novel putative miRNAs derived from S . mansoni that are present in the serum of infected mice . The read counts of some of these are very low ( between 2–66 reads per 930 , 209 mouse miRNAs reads ) and will require further validation with better coverage . However , we show that three of these miRNAs ( bantam , miR-277 , mirR-3479-3p ) can be detected in human serum from schistosome endemic areas . These represent a direct marker for infection and may also provide an indirect marker for the pathology induced by infection . Notably , a study published after submission of this manuscript identified 5 miRNAs derived from S . japonicum in the plasma of infected rabbits and 3 of these are identical or homologous to those identified here: bantam , miR-3479-3p and miR-10-5p [70] , providing independent validation for the presence of trematode miRNAs in the serum of infected animals . Here we demonstrate small RNAs derived from a helminth parasite are also present in patient serum , and provides a starting point for developing more field-friendly methods for their detection . This work also extends a burgeoning area of research detailing “foreign” small RNAs in body fluids . Zhang et al . , ( 2012 ) recently reported that the plant miRNA , miR-168a , is present in human and animal serum and demonstrated that this derives from a rice diet [37] . Wang et al . , ( 2012 ) recently reported that a wide range of exogenous RNAs can be found in human plasma , including small RNAs derived from bacteria and fungi [71] . From our results is not yet clear whether the miRNAs identified in serum are actively secreted from the parasite and how they are stabilized , since serum contains high amounts of RNases [72] , [73] . From the time course analysis presented here , schistosome-derived small RNAs were reliably detected in serum by 8 weeks post infection , after deposition of the eggs in the liver ( Fig . 4 and Fig . S4 ) . At present , we cannot determine whether these RNAs derive from the adult worms or the eggs; further in vitro and in vivo studies will shed light on this issue , which is relevant to diagnostic applications , for example the capacity to detect pre-patent infection . It is intriguing to think that existence of these miRNAs outside the parasite has a function , but this is beyond the scope of the current analysis . Given the short size of miRNAs and the fact that they do not require perfect complementarity with their targets , one could predict hundreds of possible targets in the host . Interestingly , Xue et al . ( 2008 ) showed that three of the miRNAs that we find in serum ( sja-bantam , sja-miR-71 and sja-let-7 ) are expressed during all the stages of parasite development but are enriched in the cercariae , suggesting that they may be important during the initial stages of schistosome infection [65] . The bantam miRNA has been implicated in regulating organ growth in response to environmental conditions in Drosophila as well as C . elegans [74] , [75] but functional homologues of bantam do not exist in mammals . An initial objective in this study was to identify host miRNAs that may be involved in liver pathology associated with S . mansoni infection and to then determine whether these hold any diagnostic value . A number of reports have demonstrated an increase in miR-122 and miR-192 in plasma or serum upon viral infection as well as chemically induced liver disease [54] , [56] . However , according to our analysis , although miR-192 , miR-122 and miR-194 were down-regulated in the liver during infection , their levels in serum did not change significantly ( Fig . 1–2 ) . In contrast , the miRNAs up-regulated in the liver ( miR-199-3p , miR-199-5p , miR-21 , miR-214 and miR-210 ) showed significantly higher levels in mouse serum at 12 weeks post infection ( Fig . 2 ) , however these failed to differentiate S . mansoni infected from uninfected humans ( Fig . S4 ) . It should be noted that in addition to significant liver disease , pulmonary and intestinal complications can also occur during S . mansoni infection that could also contribute to serum miRNA levels [45] , [76] . Related to this , a possible limitation in the use of endogenous miRNAs as biomarkers is the fact that their differential abundance in serum can derive from multiple cell types and can also be attributed to unrelated conditions [59] . Although the diagnostic value of these host miRNAs in serum is therefore not obvious , our work provides a foundation for further research into the functional role of these miRNAs in S . mansoni pathogenesis . Interestingly , our results do not overlap with those reported by Han et al . , ( 2013 ) who examined changes in host miRNA levels in the liver of BALB/c mice during S . japonicum infection . We assume this may be due to the very early time point ( 10 days post infection ) used in their study . Indeed , it is likely that the host miRNA changes we observe are primarily related to the liver pathology and/or the immune response initiated by the parasite eggs trapped in the liver , rather than the initial host immune response to the schistosomula . Several of the miRNAs we identify as differentially expressed are already known to be associated with liver fibrosis or disease in other , non-helminth , settings [49] , [50] , [77] , [78] . The functional role of the miRNAs in the pathology induced by S . mansoni infection remains to be determined . Future work in this area will shed light on the molecular basis of pathology and may offer innovative new therapeutic strategies . Importantly , we report here that parasite-derived miRNAs can be detected in human serum and can distinguish ‘egg-negative’ from ‘egg-positive’ individuals in areas of both low and high infection intensity . By combining data for miR-277 , miR-3479-3p and bantam we detected infection with a sensitivity of 80–90% and specificity of 80–89% . We anticipate that this may be improved further by optimizing isolation protocols , probe design and more robust methods for normalizing the data , for example to identify appropriate endogenous small RNAs that could be used as controls , rather than synthetic spike-ins [79] . The main limitation of miRNA detection in serum appears to be cross-hybridization of the probes with endogenous small RNAs , which influences the signal to noise ratios . In particular , we report the finding that the majority of small RNAs in mouse serum are derived from tRNAs ( Table 2 ) , consistent with a recent study [80] . It is possible that depletion of these tRNAs prior to qRT-PCR may improve the specificity or sensitivity of miRNA detection; this requires further investigation . In addition , one of the parasite-derived miRNAs identified by sequencing , miR-2162-3p could not be validated by qRT-PCR , likely owing to its low GC content ( 33% ) . Optimization of probe design for the parasite-derived miRNAs may also greatly increase their diagnostic utility in larger scale studies in human patients . On this note , the work presented here was performed on a relatively small number of individuals . Following further optimization of the extraction methods and probe design to minimize cross hybridization and sensitivity , larger studies will be important to assess the full potential of the proposed miRNA biomarkers , including positive and negative predictive values in comparison to existing techniques . It will also be of interest to determine the origin of these parasite-derived miRNAs and examine their abundance levels in response to treatment . We anticipate that the parasite miRNAs in serum could complement or transform existing diagnostic strategies and may serve as a platform for detecting a range of helminth infections . | Schistosomiasis is a chronic disease caused by blood flukes that affects over 200 million people worldwide , of which 90% live in Sub-Saharan Africa . In the field setting schistosomiasis caused by S . mansoni is diagnosed by detection of parasite eggs in stool samples using microscopic techniques . Here we investigate the potential of microRNAs ( miRNAs ) , a class of short noncoding RNAs , to act as biomarkers of S . mansoni infection . We have identified a specific subset of murine miRNAs whose expression is significantly altered in the liver between 6–12 weeks post infection . However their abundance in serum is not significantly different between naïve and S . mansoni-infected mice until twelve weeks post infection and they do not display consistent differential abundance in the serum of infected versus uninfected humans . In contrast , three parasite-derived miRNAs ( miR-277 , bantam and miR-3479-3p ) were detected in the serum of infected mice and human patients and the combined detection of these miRNAs could distinguish S . mansoni infected from uninfected individuals from low and high infection intensity areas with 89%/80% or 80%/90% specificity/sensitivity , respectively . These results demonstrate that miRNAs of parasite origin are a new class of serum biomarker for detecting S . mansoni and likely other helminth infections . | [
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] | [
"medicine",
"infectious",
"diseases",
"diagnostic",
"medicine",
"pathology",
"general",
"pathology",
"biomarkers",
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] | 2014 | Parasite-Derived MicroRNAs in Host Serum As Novel Biomarkers of Helminth Infection |
The fission yeast Schizosaccharomyces pombe Rec12 protein , the homolog of Spo11 in other organisms , initiates meiotic recombination by creating DNA double-strand breaks ( DSBs ) and becoming covalently linked to the DNA ends of the break . This protein–DNA linkage has previously been detected only in mutants such as rad50S in which break repair is impeded and DSBs accumulate . In the budding yeast Saccharomyces cerevisiae , the DSB distribution in a rad50S mutant is markedly different from that in wild-type ( RAD50 ) meiosis , and it was suggested that this might also be true for other organisms . Here , we show that we can detect Rec12-DNA linkages in Sc . pombe rad50+ cells , which are proficient for DSB repair . In contrast to the results from Sa . cerevisiae , genome-wide microarray analysis of Rec12-DNA reveals indistinguishable meiotic DSB distributions in rad50+ and rad50S strains of Sc . pombe . These results confirm our earlier findings describing the occurrence of widely spaced DSBs primarily in large intergenic regions of DNA and demonstrate the relevance and usefulness of fission yeast studies employing rad50S . We propose that the differential behavior of rad50S strains reflects a major difference in DSB regulation between the two species—specifically , the requirement for the Rad50-containing complex for DSB formation in budding yeast but not in fission yeast . Use of rad50S and related mutations may be a useful method for DSB analysis in other species .
Sexual reproduction involves the fusion of two gametes to create diploid offspring with equal genetic contributions from each parent . To maintain the proper chromosome number ( ploidy ) , it is therefore necessary for the gametes to be haploid . This is achieved via meiosis , where a single round of DNA replication is followed by two nuclear divisions: in the first division , homologous chromosomes ( homologs ) separate from each other ( Meiosis I ) , followed in the second division by the separation of sister chromatids ( Meiosis II ) . Meiotic recombination , a highly conserved feature of meiosis , creates between the homologs a physical connection that is necessary in most species for proper homolog segregation during Meiosis I . Before the first meiotic division , homologs become aligned and then intimately synapsed [1] . During this time meiotic recombination is initiated by DNA double-strand breaks ( DSBs ) , introduced by Spo11 in the budding yeast Saccharomyces cerevisiae or its ortholog Rec12 in the fission yeast Schizosaccharomyces pombe [2] . The DNA ends undergo 5′ to 3′ resection , producing 3′ single-stranded ( ss ) ends capable of invading intact homologous DNA , with the invaded duplex serving as the template for new DNA synthesis [3] . Resolution of the joint DNA molecules can result in a reciprocal exchange of genetic information , called a crossover , which aids proper homolog segregation at Meiosis I . This exchange of genetic material is also beneficial in that it enhances the genetic diversity of the progeny . As a type II topoisomerase-like protein , Spo11 ( or Rec12 ) breaks phosphodiester bonds in the two DNA strands and becomes covalently bound to each 5′ DNA end of the DSB [4] , [5] . This DNA-protein linkage enables determination of where DSBs are made , by chromatin immunoprecipitation ( ChIP ) of Spo11 or Rec12 and assay of the attached DNA , e . g . by tiling microarray hybridization . In wild-type cells the Spo11 protein is removed from the DNA end by endonuclease action before strand resection occurs [6] . In rad50S mutants , the bound Spo11 or Rec12 protein is not removed from the DNA ends , repair of the DSB by recombination is blocked , and the protein-bound DSBs accumulate [2] . This has facilitated genome-wide analysis of the DSB distribution in both fission and budding yeast strains with the rad50S mutation . These comprehensive DSB maps revealed in both organisms regions of DNA within which DSBs are made at high frequency , called DSB hotspots [5] , 7 . Two recent studies [8] , [9] described a new technique for genome-wide mapping of DSBs that cast doubt on earlier results where a rad50S mutant was used . It had previously been observed that DSBs in S . cerevisiae strains with a rad50S mutation ( or mutations in other genes with similar phenotypes , such as sae2Δ and mre11S ) did not show in many regions of the genome the same DSB pattern as that in dmc1 Δ mutants [10] . In addition , the overall genetic map of recombination ( crossovers ) did not agree in certain intervals with the frequency of DSBs determined in rad50S strains [11] . This led Buhler et al . [8] and Blitzblau et al . [9] to develop a method that enriched for regions of ss DNA formed in a dmc1 mutant; dmc1 mutants lack a protein important for strand exchange , and DSBs with resected ends accumulate in these mutants . The enriched ss DNA was hybridized to a genome-wide tiling microarray of oligonucleotides to identify sites of DSBs . The results showed , in many but not all regions of the genome , a clear under-representation of DSB hotspots in rad50S-like mutants compared to the distributions in the wild type or dmc1Δ mutant , which appear similar by Southern blot analysis . Specifically , the intensity of breakage at some , but not all , DSB hotspots was greatly reduced in the rad50S-like mutants compared to that in the wild type or dmc1Δ mutant . The validity of DSB maps created with rad50S mutants , not only in S . cerevisiae but in other organisms as well , is therefore under new scrutiny . Our lab has reported that DSB hotspots in S . pombe are preferentially located in large intergenic regions and are widely-spaced – on average there are about 65 kb between hotspots – but these experiments were done with rad50S mutants [5] , [12] . We wanted to know if a wild-type ( rad50+ ) strain has a DSB map similar to that seen in rad50S mutants . ChIP experiments to detect the Spo11-DNA covalently linked intermediates in RAD50 strains of budding yeast have not been successful [13] , [14; M . Lichten , personal communication] , apparently due to the short life-span of the hypothesized Spo11-DNA complexes . By contrast , in fission yeast we were able to detect and analyze the wild-type ( rad50+ ) Rec12-DNA complexes . To our knowledge , this is the first time that this protein-DNA intermediate has been detected in recombination-proficient cells . We report here that the locations of DSBs , measured as Rec12-DNA linkages , across the genome in S . pombe rad50+ meiosis are indistinguishable from those in rad50S strains , although the intensities are lower , as expected due to ongoing DSB repair in rad50+ strains . Therefore , conclusions from our earlier studies using the rad50S mutation are still valid: in particular , DSBs are separated by large distances and are preferentially located in large intergenic regions [5] , [12] . However , the genetic recombination maps ( crossover distributions ) and physical maps ( DSB distributions in rad50+ and rad50S strains ) display non-congruence in S . pombe . We discuss the significance of these observations for studies of meiotic recombination in S . pombe and in other species , including humans .
We began our comparison of the DSB distributions in rad50+ and rad50S strains by assaying DSBs using standard Southern blots . rad50+ and rad50S strains were meiotically induced ( Figure S1 ) , and the DNA was extracted and digested with NotI restriction enzyme to generate large DNA fragments , which were separated by pulsed-field gel electrophoresis . Previous Southern blot analyses of DNA from rad50+ and rad50S strains revealed the same meiotic DSB pattern on the 0 . 5 Mb NotI restriction fragment J , which includes the well-characterized DSB hotspot mbs1 [5] , [12] , [15] . Two additional NotI fragments were probed to strengthen this observation; these analyses were of the 0 . 5 Mb NotI fragment K ( Figure 1A and S2A ) and the 1 . 2 Mb NotI fragment D ( Figure 1B and S2B ) . These results revealed that rad50+ strains have on each fragment multiple DSB sites at the same locations as those from a rad50S strain . As expected , in almost all cases the maximal level of the transient DSBs in the rad50+ strain was less than that in the rad50S strain , in which DSBs accumulate . At each hotspot site on these NotI fragments in a rad50+ strain there is a hotspot in the rad50S strain , and vice versa . We next compared DSB sites in a repair-deficient mutant other than rad50S in which DSBs accumulate . During meiotic recombination in S . pombe there are two mediator complexes that assist the strand exchange protein Rhp51 in strand invasion: Swi5-Sfr1 and Rhp55-Rhp57 [16] , [17] . Mutants lacking either complex show reduced recombination and delayed DSB repair , and strains with a mutation in both complexes display recombination defects and spore viability as severe as an rhp51 null mutant [16] , [18] but slightly better growth and meiotic induction than an rhp51 null mutant ( RWH , unpublished data ) . Thus , the double swi5Δ rhp57Δ mutant is an ideal candidate for assaying defective DSB repair at a stage later than the rad50S repair defect , allowing for DSB accumulation in a non-rad50S strain . Southern blot analysis of NotI fragments K ( Figure 1A ) , D ( Figure 1B ) , and J ( data not shown ) from the swi5Δ rhp57Δ mutant revealed a DSB pattern similar to those seen in rad50+ and rad50S strains , except that the broken DNA persisted in rad50S and swi5Δ rhp57Δ mutants but was repaired in wild type . Thus , by Southern blot analysis in the rad50S mutant there is no lack of DSB sites that are present in other mutants , unlike the situation in S . cerevisiae , as noted above [8] , [9] . Since Rec12 becomes covalently bound to the DNA ends at a meiotic DSB [5] , ChIP of epitope-tagged Rec12 protein without exogenous cross-linking can identify the genomic loci where DSBs occur . Previous ChIP analysis of FLAG-tagged Rec12 in rad50S meiosis showed that DSB hotspots assayed by locus-specific PCR gave a meiosis-specific signal dependent on Rec12 ( i . e . , DSB formation ) , while DSB coldspots gave no detectable signal [5] . We wanted to know if it was possible to repeat this analysis in a rad50+ meiosis , or if Rec12 was removed from the DNA too quickly to be detected , as appears to be the case in budding yeast [13] , [14] . PCR analysis of two prominent DSB hotspots , ade6-3049 on chromosome III [19] and mbs1 on chromosome I , revealed that DNA isolated 3 . 5 h after induction of meiosis was considerably enriched by ChIP when compared to 0 h ( uninduced ) DNA , based on the relative abundance of PCR products . This was true for DNA from a rad50+ strain as well as from a rad50S strain , though as expected enrichment was lower in the rad50+ strain due to ongoing repair of the DSBs ( Figure 2 ) . There was no detectable enrichment at the DSB coldspot ura1 ( Figure 2C and [5] ) . In addition , the enrichment at the hotspots in rad50+ was transient: very little signal was detected at 0 h ( before DSB formation ) or at 6 h after meiotic induction ( after DSB repair ) . The maximal signal was at 3 . 5 h , which is about the time of maximal DSBs detectable by Southern blots in rad50+ strains ( Figure 1 and [5] ) . This contrasts with a rad50S meiosis , where the PCR assay detects high DNA enrichment at least to 6 h after meiotic induction [5] , a reflection of Rec12 remaining bound and the DSBs not being repaired in rad50S meiosis . As an additional test for Rec12-DNA linkages in rad50+ strains , we treated meiotic extracts with a protease ( or not , as a control ) and extracted the material with phenol . Protein-linked DNA is removed from the aqueous phase by phenol extraction [20] . A significant fraction of the DNA at the mbs1 and ade6-3049 DSB hotspots was removed by phenol extraction , as expected for DNA covalently linked to Rec12 protein , unless the extracted material was treated with a protease before extraction . This was true for material from both rad50+ and rad50S strains ( Figure S3 ) , and contrasts sharply with results from S . cerevisiae , in which no detectable DNA is removed by phenol extraction in RAD50 strains [20] . Our results show that a significant fraction of the DNA at DSB hotspots in S . pombe rad50+ strains remains linked to a protein , likely Rec12 . To extend these observations to the entire genome , we used a genome-wide microarray analysis similar to our previous analysis with rad50S strains [5] . We prepared Rec12-DNA samples from immunoprecipitated ( IP ) chromatin and from whole-cell extracts ( WCE ) prepared at 0 and 3 . 5 h in rad50+ meiosis and at 0 and 5 h in rad50S meiosis . These samples were amplified , differentially labeled , and hybridized to a tiling oligonucleotide microarray ( ∼44 , 000 60-mers , “probes , ” spaced approximately every 290 bp across ∼12 . 5 Mb of the non-repetitive S . pombe genome ) . The relative frequency of Rec12-DNA linkage at each probe position was measured as the median-normalized ratio of IP signal to WCE signal . The 0 h data [log ( IP/WCE ) values] were normally distributed , as expected for random background data ( Figure S4 ) . In contrast , a distinct subset of probes in both the 3 . 5 h rad50+ and 5 h rad50S data showed elevated non-normal ratios , reflecting genuine enrichment over background . The analysis below is focused on these enriched values . The data show that the sites of Rec12-DNA linkage , and hence the sites of meiotic DSBs , in a rad50+ meiosis almost completely coincide with those in a rad50S meiosis . The genomic intervals of NotI fragment K and NotI fragment D , analyzed for DSBs by Southern blot analysis ( Figure 1A and B ) , are compared by microarray analysis in Figure 3 . There are no significant peaks of Rec12-DNA linkage in rad50+ that are not also in rad50S; this correspondence is true genome-wide , as well ( Figure S5 ) . This result is dramatically different from that observed in S . cerevisiae , where multiple genomic regions show many more DSB hotspots in RAD50 ( dmc1Δ ) meiosis than in rad50S meiosis , as measured by the enrichment for accumulated ss DNA ends [8] , [9] . Within these regions , at many DSB hotspots seen in RAD50 ( dmc1Δ ) the level of breakage in rad50S falls below the authors' definition of a hotspot . We note in particular that the DSB patterns surrounding the centromeres in rad50S and rad50+ strains are indistinguishable in S . pombe ( Figures 3 and S5 ) but markedly different in S . cerevisiae [8] , [9] . Closer examination of one hotspot from each of NotI fragments K and D revealed that the shape of the enrichment peaks , considering non-background probes , was essentially identical for the rad50+ and rad50S datasets , but with ∼3-fold less enrichment in the rad50+ experiment ( Figure 4 ) . This 3-fold difference is consistent with comparisons of maximal meiotic DSB frequencies in rad50+ and rad50S strains by Southern blot analysis [5; unpublished data] and appears to hold true genome-wide ( Figures 5A , S6A and S7A ) . The matching peak shapes indicate that the Rec12-DNA shear sizes , DSB positions , and relative DSB intensities are nearly identical in the rad50+ and rad50S experiments . This result rules out the possibility that the Rec12-DNA species detected by microarray hybridization in the rad50+ experiment involves a significantly different length of DNA than that in the rad50S experiment . More specifically , we can discount the Rec12-DNA species in the rad50+ experiment being a short Rec12-oligonucleotide released after DSB end-processing [6] , rather than the Rec12-DNA intermediate first formed by Rec12 and accumulating in the rad50S background . In fact , such a short Rec12-oligonucleotide would not be amplified and hybridized in the procedure used here . As expected , the lengths of the two strands of DNA extending from one side of the DSBs at one hotspot to a common restriction site were similar ( Figure S8 ) , suggesting that at least some of the 5′ ends remain full length ( i . e . , attached to Rec12 ) . We analyzed our genome-wide data on a probe-by-probe basis to determine if hotspots of DSBs were at the same positions in both rad50+ and rad50S; i . e . , are the probes with high IP/WCE ratios in rad50+ also high in rad50S ? For each of the ∼44 , 000 probes on the microarray , the IP/WCE ratio from the 3 . 5 h rad50+ DNA was plotted against the IP/WCE ratio of the 5 h rad50S DNA; these are the times of maximal DSB levels in the two strains ( Figure 1 [5] , [12] ) . Essentially every probe that showed enrichment ( high normalized IP/WCE ratio ) in one strain was enriched in the other ( Figures 5A and S6A ) . There is a clear quantitative , positive correlation between the IP/WCE ratios ( Figure S9A ) of these enriched ( DSB hotspot ) probes across the two experimental conditions , consistent with the data in Figure 4 . Background probes showed no such quantitative correlation . Probes showing enrichment in the rad50S 5 h ( induced ) DNA ( i . e . , DSB hotspot probes ) showed , however , no significant enrichment in the rad50+ 0 h ( non-induced ) DNA ( Figures 5B , S6B , and S9A ) , as expected since DSB hotspots are not apparent in the 0 h data ( Figures 3 and S5 ) . The subset of enriched probes in the 5 h rad50S and 3 . 5 h rad50+ conditions was consistent across the two independent inductions of rad50S and rad50+ ( Figure S10 ) . These data indicate that there are no obvious regions of the S . pombe genome where DSB hotspots occur in rad50+ but not in rad50S strains . Compared to the correlation between the S . pombe rad50+ and rad50S meiotic datasets , the correlation between the RAD50 ( dmc1Δ ) and rad50S enrichment ratios of S . cerevisiae is much weaker ( Figures S6C , S6D , and S9B ) . Among probes showing enrichment , there are many probes that have a higher , and often much higher , enrichment ratio in RAD50 ( dmc1Δ ) meiosis than in rad50S meiosis , as well as other probes that show similar high enrichment ratios in both . This is expected , given loci where DSBs are frequent in both RAD50 ( dmc1Δ ) and rad50S meiosis and other loci where DSBs are frequent only in RAD50 ( dmc1Δ ) [8] , [9] . As another way of comparing the meiotically induced rad50S and rad50+ data from S . pombe , we identified regions of significant ChIP enrichment using ChIPOTle [21] , with a p value cutoff of 0 . 001 . Due to the accumulation of Rec12-DNA intermediates , Rec12 ChIP enrichment over background should be greater in the rad50S experiments . As the p value that ChIPOTle attaches to peaks is dependent on their degree of enrichment over background , peaks can be detected with greater sensitivity in the rad50S experiments . Therefore , for any given significance threshold , if the same pattern of DSBs occurs in both the rad50S and rad50+ experiments , we expect some peaks ( the stronger ones ) to be detected in both sets of experiments but other peaks ( the weaker ones ) to be detected only in the rad50S experiments . This is what we observed . Combining the two independent inductions ( Datasets S1 and S2 ) , an average of 10 . 2% and 5 . 0% of the genome was enriched ( i . e . , within ChIPOTle-determined peaks ) in the 5 h rad50S and the 3 . 5 h rad50+ data , respectively , but 4 . 9% of the genome was enriched in both . Therefore , there is no significant class of peaks identified in the rad50+ data that do not have equivalents in the rad50S data . In contrast , in S . cerevisiae [8] 63% of the genome was enriched in the RAD50 ( dmc1Δ ) strain , and 32% in the rad50S strain , but 31% of the genome was enriched in both . Therefore , in S . cerevisiae there is a significant class of probes that are enriched only in the RAD50 ( dmc1Δ ) background , as well as probes that are enriched in both backgrounds . A simpler consideration of the ChIPOTle analysis leads to the same conclusion . In our S . pombe data , an average of 255 significant peaks was detected in the two 3 . 5 h rad50+ datasets , and 427 in the two 5 h rad50S datasets . Essentially all ( 94% ) of the rad50+ peaks were present in the corresponding rad50S datasets ( i . e . , the peaks overlap ) , but only 48% of rad50S peaks were present in the rad50+ dataset . That is , there are almost no peaks detectable in the rad50+ background that are not detected in the rad50S background . The larger number of peaks identified in the rad50S background is expected from the greater peak detection sensitivity of ChIPOTle using the rad50S dataset , as discussed above . For probes showing enrichment in either the 3 . 5 h rad50+ or 5 h rad50S datasets , the rad50S enrichment ratio is consistently ∼3 fold higher than the rad50+ enrichment ratio ( Figure S7A ) . In comparison , the data from S . cerevisiae [8] look very different . Here , 95% of 2010 rad50S peaks overlap with RAD50 ( dmc1Δ ) peaks but only 60% of 1816 RAD50 ( dmc1Δ ) peaks overlap with rad50S peaks . That is , there is a substantial number of loci ( hotspots ) where significant DNA breakage is seen in the RAD50 ( dmc1Δ ) strain but not in the rad50S strain , as well as other loci where significant breakage is seen in both strains ( Figure S7B ) .
An analysis of DSBs by ChIP of the Spo11 protein in a rad50+ meiosis in budding yeast has not been successful [13] , [14; M . Lichten , personal communication] , presumably because Spo11 is rapidly removed from the DSB 5′ ends . The success of our Rec12-ChIP analysis in fission yeast rad50+ strains ( Figures 2 , 3 , and S5 ) suggests that the Rec12 protein remains linked to DNA for a longer period of time in fission yeast than does Spo11 in budding yeast . However , even in fission yeast , Rec12 appears to be removed in a rather short period – a DNA sample taken 30 min after the 3 . 5 h DNA sample studied here ( Figures 2 , 3 , and S5 ) and similarly analyzed on a microarray showed no discernible difference genome-wide from the 0 h pre-meiotic DNA sample ( unpublished data ) . In addition , multiple assays for Rec12-DNA by PCR at selected loci show that the Rec12-DNA species diminishes substantially between 3 . 5 and 4 h ( Figure 2 and unpublished data ) . Thus , the first step of DSB repair ( Rec12 removal ) begins about 30 min after DSB formation ( which occurs at about 3 h after meiotic induction ) and about 30 min before joint DNA molecules ( single Holliday junctions ) are first detected [22] . The time between DSB formation and joint molecule detection in S . cerevisiae is also about 1 h [e . g . , 23] . We infer that in S . pombe the Rec12-DNA complex persists until the nuclease for its removal , perhaps the MRN ( Mre11-Rad50-Nbs1 ) complex , binds and acts on this intermediate . In S . cerevisiae this step may be very fast . Why does the rad50S mutation behave differently in these two yeasts ? The answer may lie in the differential dependence on the MRN ( MRX in S . cerevisiae ) complex for DSB formation in these two distantly related yeasts . S . cerevisiae rad50Δ and mre11Δ mutants do not form DSBs [24] , [25] , whereas S . pombe rad32Δ ( mre11 homolog ) and rad50Δ mutants form DSBs with the same kinetics as rad50S mutants , although none of these mutants repair the DSBs [26] . The dependence on MRX for DSB formation in budding yeast likely reflects its Spo11-dependent binding at sites of DSBs [13] , where it is then also in position to quickly remove the Spo11 protein from the DNA . Since fission yeast lacks this MRN requirement for DSB formation , MRN may be recruited only after DSBs are formed , allowing for a greater life-span of Rec12-DNA complexes . The initial steps of DSB repair – the removal of Rec12 ( Spo11 ) and resection to form invasive ss DNA ends [6] – by MRN and other proteins are thought to be similar in both organisms . The rad50S mutation commonly used in both organisms changes the same amino acid of the protein ( Lys81→Ile81 ) [12] , [18] , [24] , [27] , but this rad50S mutant does not form the full number of DSBs in budding yeast [8] , [9] . These observations lead us to suggest that in budding yeast , which requires MRX for DSB formation , the rad50S ( K81I ) mutant is incompetent ( or less competent ) compared to RAD50 to activate DSB formation at some sites or regions but not at others . Thus , not all hotspots are revealed in S . cerevisiae rad50S ( K81I ) strains [8] , [9] . In dmc1 mutants , a more complete spectrum of hotspots would , in this view , be activated by the wild-type MRX complex , as observed [8] , [9] . In contrast , the lack of MRN requirement for DSB formation in S . pombe may be the basis for the rad50S mutation having no discernible effect on the distribution of DSBs in fission yeast . The decision to make DSBs is made before MRN's meiotic activity on DNA , making MRN unnecessary for the formation – but not the processing – of meiotic DSBs . Thus , in S . pombe the entire spectrum of DSBs , with readily detectable Rec12-DNA complexes , is observed . In S . cerevisiae and other species in which Rad50 is required for DSB formation , rad50 mutants with an amino acid substitution other than Rad50 ( K81I ) [27] and that accumulate DSBs may also allow a full spectrum of DSBs to be observed . Crossovers arising from meiotic recombination are much more uniformly distributed across the genomes of both fission yeast and budding yeast than are the sites of DSBs observed in rad50S strains [8] , [11] , [12] , [15] . A recent study by Buhler et al . [8] determined that the non-congruence in S . cerevisiae is due at least in part to a lower DSB frequency and more restricted DSB distribution in a rad50S strain than in a dmc1Δ strain , which appears to be more representative of wild-type meiosis . Our results in wild-type ( rad50+ ) S . pombe meiosis reveal the same DSB pattern as that seen in earlier studies of rad50S mutants [5] , [12]: meiotic DSBs are preferentially located in large intergenic DNA regions and are separated by long distances ( ∼65 kb on average ) where no DSBs are apparent . Studies of wild-type ( rad50+ ) meiosis have in the past been problematic , primarily because the repair of DSBs in wild-type strains prevents all of the meiotic DSBs from being analyzed and low-level breaks can be missed . While there may be low-level DSBs dispersed across the S . pombe genome and not detected in our analysis , it is clear that there are essentially no DSB hotspots in rad50+ that are not present in rad50S ( Figures 3 , 5 , and S5 ) . In S . pombe , some intervals with no detectable DSBs nevertheless contain abundant crossovers [5] , [12] , [15] . The 0 . 5 Mb region of NotI fragment J on chromosome I has been extensively studied both genetically for crossovers and physically for DSBs [12] . The number of DSBs detected in this interval – about one DSB per four DNA molecules in a meiotic cell – is not enough to account for the crossovers that occur on this fragment – about one per meiotic cell – since there are about three times more intersister ( genetically silent ) exchanges than interhomolog exchanges , at least at the major DSB hotspot mbs1 on that fragment [15] . In the 57 kb res2 – ura1 subregion of NotI fragment J there are ∼0 . 08 crossovers , over 10 times more than predicted by the <0 . 005 DSBs per meiotic tetrad [12; unpublished data] . It had been suggested that crossovers in such regions might arise from ss nicks [15] , but since all meiotic crossovers are dependent on Rec12 [28] , we would expect even sites of nicks to have Rec12 covalently linked to the DNA and therefore enriched by ChIP . Ludin et al . [29] analyzed by microarrays the genome-wide distribution of Rec12 after it was formaldehyde-crosslinked to DNA and found a more uniform distribution than we find for Rec12 self-linked to DNA . Although much of the Rec12 detected with formaldehyde-crosslinking does not make detectable DSBs , this population of Rec12 may nevertheless be required for crossovers in DSB-poor regions . Although the basis of the DSB–crossover discrepancy remains undetermined , our results rule out one explanation – that DSBs are underrepresented in rad50S strains . Results from the DSB analysis of a dmc1Δ mutant in S . cerevisiae [8] , [9] have brought into question the reliability of DSB maps generated using the rad50S mutation . Our results in S . pombe question whether these findings from budding yeast apply to other organisms . rad50S-like mutations may reveal the wild-type distribution in other species , particularly those in which Rad50 is not required for DSB formation , such as Arabidopsis thaliana , Drosophila melanogaster , Coprinus cinereus , and perhaps Caenorhabditis elegans [30] , [31] , [32; M . Zolan , personal communication] . In species that appear not to have a Dmc1 ortholog a microarray analysis of DSBs performed with a rad50S-like mutant may be the most feasible method to reveal the DSB distribution . Our results indicate that in these cases the results may reflect those in wild type . Regardless of the genetic background used and methodology chosen , understanding where meiotic DSBs occur and what DNA characteristics influence DSB location remains an important question in understanding the regulation of meiotic recombination .
Strains used were GP1979 ( h−/h− ade6-52/ade6-M26 lys3-37/+ +/ura1-171 pro1-1/+ pat1-114/pat1-114 end1-458/end1-458 ) , GP3718 ( h+ ade6-3049 pat1-114 rad50S end1-458 ) , GP6203 ( h−/h− ade6-3049/ade6-3049 pat1-114/pat1-114 rad50S/rad50S rec12-201::6His-2FLAG/rec12-201::6His-2FLAG +/his4-239 lys4-95/+ ) , and GP6232 ( h−/h− ade6-3049/ade6-3049 pat1-114/pat1-114 rec12-201::6His-2FLAG/rec12-201::6His-2FLAG +/his4-239 lys4-95/+ ) . Alleles were described previously [5] , [18] , [19] , [26] . To assess events in S . pombe meiosis , we used strains carrying the temperature-sensitive pat1-114 mutation , which affords high synchrony but has no detectable effect on DSB formation or location [5] , [33] . Cultures were grown to mid log-phase and starved for nitrogen to arrest cells in the G1 phase of the cell cycle; nitrogen was restored and the temperature raised to initiate meiosis . Cells were harvested , embedded in agarose plugs , and treated with enzymes to lyse the cells and to partially purify the DNA . After digestion with NotI restriction enzyme , the DNA was subjected to pulsed-field gel electrophoresis and Southern blot hybridization . These methods are detailed elsewhere [12] , [34] . The probe used on NotI fragment K ( Figure 1A and S2A ) extends from bp 3600336 to bp 3601359 on chromosome I; the probe used on NotI fragment D ( Figure 1B and S2B ) extends from bp 1025344 to bp 1026300 on chromosome I ( accession # NC_003424 . 3 ) . Strains with both rad50+ and rad50S genetic backgrounds were induced twice . Chromatin was prepared , immunoprecipitated , assayed by locus-specific PCR , and analyzed on microarrays as described [5] , except that Agilent Whole Genome 4×44 K S . pombe oligonucleotide microarrays were used . The 0 h and 3 . 5 h rad50+ DNA and the 5 h rad50S DNA were analyzed on microarrays twice; the 4 h rad50+ DNA was analyzed only once , as was the 0 h rad50S DNA , which confirmed earlier results [5] . Regions of significant enrichment were identified using the Gaussian setting of ChIPOTle ( v 1 . 0 ) [21] with a p value cutoff of 0 . 001 . | During meiosis , which creates haploid gametes from diploid cells , recombination between two homologous chromosomes increases genetic diversity and , in most organisms , is crucial for proper segregation of chromosomes into haploid nuclei . To better understand where recombination occurs and why it occurs there , we investigated in fission yeast the initiating step in recombination—formation of DNA double-strand breaks ( DSBs ) . A genome-wide DSB map is crucial to understand how DNA sequence and chromatin structure affect DSB formation and may help answer these questions in other organisms , including humans . Mutants in which DSBs accumulate are particularly useful for determining the DSB distribution . As recently reported , however , in budding yeast the DSB distribution in one such widely used mutant , rad50S , differs markedly from that in a dmc1 mutant , in which DSBs also accumulate and appear to have a more nearly wild-type distribution . We have detected in fission yeast a DNA–protein intermediate of recombination assumed to exist , but never before detected , in a recombination-proficient strain ( rad50+ ) . The distributions of this intermediate , and therefore those of DSBs , in rad50+ and rad50S strains are indistinguishable . rad50S-like mutations may also accurately reflect the wild-type DSB distribution in other species and may be particularly useful in species lacking Dmc1 orthologs . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
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"Methods"
] | [
"genetics",
"and",
"genomics/chromosome",
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] | 2008 | Indistinguishable Landscapes of Meiotic DNA Breaks in rad50+ and rad50S Strains of Fission Yeast Revealed by a Novel rad50+ Recombination Intermediate |
Death adders ( Acanthophis spp ) are found in Australia , Papua New Guinea and parts of eastern Indonesia . This study aimed to investigate the clinical syndrome of death adder envenoming and response to antivenom treatment . Definite death adder bites were recruited from the Australian Snakebite Project ( ASP ) as defined by expert identification or detection of death adder venom in blood . Clinical effects and laboratory results were collected prospectively , including the time course of neurotoxicity and response to treatment . Enzyme immunoassay was used to measure venom concentrations . Twenty nine patients had definite death adder bites; median age 45 yr ( 5–74 yr ) ; 25 were male . Envenoming occurred in 14 patients . Two further patients had allergic reactions without envenoming , both snake handlers with previous death adder bites . Of 14 envenomed patients , 12 developed neurotoxicity characterised by ptosis ( 12 ) , diplopia ( 9 ) , bulbar weakness ( 7 ) , intercostal muscle weakness ( 2 ) and limb weakness ( 2 ) . Intubation and mechanical ventilation were required for two patients for 17 and 83 hours . The median time to onset of neurotoxicity was 4 hours ( 0 . 5–15 . 5 hr ) . One patient bitten by a northern death adder developed myotoxicity and one patient only developed systemic symptoms without neurotoxicity . No patient developed venom induced consumption coagulopathy . Antivenom was administered to 13 patients , all receiving one vial initially . The median time for resolution of neurotoxicity post-antivenom was 21 hours ( 5–168 ) . The median peak venom concentration in 13 envenomed patients with blood samples was 22 ng/mL ( 4 . 4–245 ng/mL ) . In eight patients where post-antivenom bloods were available , no venom was detected after one vial of antivenom . Death adder envenoming is characterised by neurotoxicity , which is mild in most cases . One vial of death adder antivenom was sufficient to bind all circulating venom . The persistent neurological effects despite antivenom , suggests that neurotoxicity is not reversed by antivenom .
Death adders ( genus Acanthophis ) are a member of the snake family Elapidae . They inhabit most of Australia ( excluding Victoria and Tasmania ) , Papua New Guinea , Irian Jaya and the Indonesian islands of Seram , Halmahera , Obi and Tanimbar . Considerable debate about the taxonomy of individual species continues , with up to 12 species of death adder being proposed [1] , [2] . Death adders are readily distinguishable from other Australian snakes by their “viper-like” appearance . They also differ to other Australian elapids because they are ambush predators , being primarily active at night . Death adder venom has been the subject of considerable in vitro investigation and several venom components have been isolated and identified . Until recently , post-synaptic neurotoxins were thought to be the most important components of death adder venom and numerous post-synaptic toxins have been isolated [2]–[6] . However , recent work has identified a number of pre-synaptic neurotoxins present in at least three species of death adder [7]–[9] . Several other components have been identified in death adder venom , including myotoxins , pro-coagulants , anticoagulants and toxins which interfere with platelet aggregation [10]–[17] . The clinical significance of several of these components remains unclear . There is limited published information about the clinical effects of death adder envenoming and its treatment . Neurotoxicity appears to be the most important clinical effect of death adder envenoming [2] , [18] , [19] . Most of the available clinical information comes from two case series from Port Moresby General Hospital in Papua New Guinea . Campbell's 1966 paper provided the first case series of death adder bites with 15 cases [18] . It included five patients with evidence of neurotoxicity , two of whom had extensive paralysis . The study describes the successful reversal of envenoming with antivenom therapy but does not provide objective evidence of the duration of effects after treatment . Definite identification of the involved snake was only available for some of the cases . Lalloo et al reported a further 32 cases of death adder bites from Papua New Guinea with confirmation by enzyme immunoassay [19] . Neurotoxicity was a feature in 17 ( 53% ) of these patients , with five patients requiring intubation and ventilation . The study found a variable response to antivenom , with some cases responding rapidly with a reversal of effects , and other cases not responding at all . The limited information on Australian death adder bites does not provide a complete description of the envenoming syndrome . In a prospective series of 21 cases from tropical northern Australia , eight ( 38% ) developed neurotoxicity [20] . There is controversy regarding the dose and effectiveness of antivenom and whether adjunctive therapy with anticholinesterases such as neostigmine play a role in treatment [2] , [20]–[27] . The aim of this study is to describe the clinical syndrome of death adder envenoming in Australia and evaluate the response of death adder envenoming to antivenom therapy .
Acanthophis antarcticus ( Common Death Adder ) venom was purchased from Venom Supplies , South Australia . Death adder antivenom was manufactured by CSL Ltd . Polyclonal monovalent rabbit IgG to A . antarcticus venom was purchased from the Western Australian Institute for Medical Research . Tetramethylbenzidine ( TMB ) was purchased from Sigma . Rabbit IgG was biotinylated using EZ-link sulfo-NHS-LC-Biotin ( Pierce #21335 ) . Streptavidin-conjugated horseradish peroxidise was purchased from Millipore Chemicon . Skim milk ‘Diploma’ brand instant powder was prepared as a 1% solution in phosphate buffered saline ( PBS ) for blocking solution . Bovine Serum Albumin ( BSA ) was obtained from Bovostar . Greiner microlon high binding 96 well plates were used for the enzyme immunoassays . The plates were read on a BioTek ELx808 at 450 nm . Patients with death adder bites were recruited as part of the Australian Snakebite Project ( ASP ) . ASP is an ongoing prospective multicentre study which recruits patients from over 100 hospitals in Australia . The inclusion criterion for ASP is any patient who has been bitten by a snake , either suspected or confirmed . The only exclusion criterion is any patient less than two years of age . Patients are recruited to the ASP by local investigators present in treating or referral hospitals , or by clinical toxicologists when contact is made through the Poisons Information Centre Network in Australia . Patient information , patient consent , study procedures and datasheets are faxed to local investigators and are included as Protocol S1 . Ethics approval has been obtained from the human research ethics committee of the Menzies School of Health Research and 20 human research ethics committees relevant to all institutions involved in the study . Informed written consent was obtained from all patients in the study . Information on patient demographics , bite circumstances , clinical evaluation of the patient , laboratory results , treatments given and response to therapy are recorded for all patients recruited on datasheets made available to treating doctors . All decisions about treatment of the patient are made by the treating doctor or from advice given by the National Poison Information Centre Network . This information is entered in the study database and coded to a clinical envenoming syndrome according to previously defined criteria [28] . Multiple serum samples are taken from each patient both pre- and post-antivenom administration which are then spun , aliquotted and stored at −80°C for later analysis of venom and antivenom . The pre-antivenom samples are used to confirm the presence and concentration of specific venoms . Post-antivenom samples are used to confirm the absence of detectable free venom after antivenom administration . The ASP database was searched from January 2002 to January 2012 for all potential cases of death adder bites . Potential death adder bite cases were defined by either a positive CSL snake venom detection kit ( sVDK ) result , expert identification of the snake or by clinical findings that were suggestive of envenoming by death adder ( eg . neurotoxicity in the absence of coagulopathy ) . Blood samples from these possible cases were analysed to confirm the type of venom with enzyme immunoassay if pre-antivenom blood was available . Definite cases were defined as those with positive expert identification or detection of death adder venom with specific venom enzyme immunoassay . Specific venom enzyme immunoassay was performed on all patient samples using a previously described technique developed for Australian snakebites [29] . All washings were done with 0 . 02% Tween 20 in PBS . Plates were coated with 100 µL of rabbit anti-A . antarcticus IgG 1 µg/mL in carbonate buffer ( 50 mM pH 9 . 6 ) . After one hour at room temperature they were refrigerated at 4°C overnight . Each plate was washed and then blocked with 300 µL of blocking solution ( dilute skim milk ) to occupy free binding sites on the plates . Each plate was then washed again after one hour before adding 100 µL of patient sample , control or spiked sample to each well , as a dilution of 10% or 1% or both , in PBS . Following three washes , 100 µL of biotinylated rabbit anti-A . antarcticus IgG ( 0 . 2 ug/mL in 0 . 5% BSA/PBS ) was added to each sample . After a further hour the plates were washed another three times , and 100 µL of Strepavidin-conjugated horseradish peroxidase ( 0 . 15 µg/mL in 0 . 5% BSA/PBS ) was added . Then , after 1 hour the plates were again washed three times . Tetramethylbenzidine ( 100 µL ) was added and the colour left to develop for two minutes . Then to each sample 50 µL of 1M sulfuric acid was added to halt the reaction . Samples are all performed in triplicate and the mean value calculated . The coefficient of variation was less than 5% for all experiments . The EP17-A protocol was used to determine the limit of blank and limit of detection of the assay [30] . Previous studies of taipan ( Oxyuranus sp . ) venom have shown that using this approach the level of detection can be set as low as 0 . 15 ng/mL [29] . Twenty four non-envenomed serum samples were measured unspiked ( blank ) and spiked at a concentration such that the overlap of absorbance with the unspiked samples was ≤5% . This level was determined as 0 . 2 ng/ml . Standard curves were fitted by linear and non-linear regression and the data was plotted to fit a sigmoidal dose–response curve with an r2 value of 0 . 99 . Normality of the data was assessed by the Kolmogorov-Smirnov test and the Shapiro-Wilk normality test . Descriptive data is presented as medians with interquartile ranges ( IQR ) and ranges . All analyses and graphics were done in GraphPad Prism version 5 . 03 for Windows , GraphPad Software , San Diego California USA , www . graphpad . com .
The median age of the patients was 45 years ( IQR: 33–52 y; Range 5–74 y , ) ; 25 patients were male ( 86% ) . The bite site was the upper limb in 20 cases ( 69% ) , lower limb in eight cases ( 28% ) and not known in one case . The activity that led to the bite was intentionally interfering with the snake in 17 cases ( 59% ) , stepping on or near the snake in seven cases ( 24% ) , removing debris or interfering with something on the ground near the snake in four cases ( 14% ) and not known in one case . Bites to snake handlers made up 15 of the cases ( 52% ) . Adequate pressure bandage with immobilisation was used as first aid in 22 cases ( 76% ) . Of the 14 death adder bites that occurred in the wild , nine of them occurred in the evening/night between 6pm and 6am . The snake was identified as a death adder by an expert in 19 cases . In nine of these the species of death adder was determined: four A . praelongus ( Northern Death Adder ) , two A . antarcticus ( Common Death Adder ) , two A . hawkei ( Barkly Tableland Death Adder ) and one A . rugosus ( Rough-scaled Death Adder ) . There were too few envenomed cases by each species to allow any comparison between species . Bites occurred all around Australia , but bites in the wild occurred mainly in the north ( Figure 1 ) . Local and regional bite site effects occurred in 20 of the 29 patients which was most commonly pain at the bite site , but in 13 patients there were more severe effects with swelling ( 11 ) and bruising ( 4 ) ( Figure 2 ) . Over a period of days four patients went on to develop cellulitis at the bite site requiring antibiotic therapy . One of these patients required surgery for flexor sheath synovitis and one required a 48 hour intensive care unit admission for septic shock following cellulitis at the bite site . Fourteen of the definite death adder bites resulted in systemic envenoming ( Table 2 ) . Neurotoxicity was the most common clinical syndrome , with myotoxicity in one patient and no patients with VICC . In addition to envenoming , two patients had allergic reactions to venom . There were no deaths . All patients with systemic envenoming developed local effects except two where there was no documentation of local effects . Neurotoxicity developed in 12 patients . In ten patients neurotoxicity was mild with paralysis limited to muscles innervated by the cranial nerves and not requiring intubation - ptosis , external ophthalmoplegia and/or diplopia , and bulbar weakness . The most common earliest indicator of neurotoxicity was ptosis in 10 patients and then ophthalmoplegia/diplopia in six . The only patient where the onset of neurotoxicity was observed more than 12 hours post bite at 15 . 5 hours was a five year old boy who was not woken overnight to test for ptosis . Severe neurotoxicity occurred in two patients who required intubation and mechanical ventilation for 17 and 83 hours . Table 3 provides the time of onset and resolution of neurotoxicity . Non-specific systemic symptoms occurred in three patients , one in which neurotoxicity did not develop . The commonest systemic symptoms were nausea and vomiting . Myotoxicity occurred in one patient bitten by a northern death adder ( A . praelongus ) who developed severe local myalgia with a maximum CK of 4770 U/L [31] Two patients who had previously been bitten by death adders developed allergic reactions to venom without evidence of envenoming . The first patient had shortness of breath , erythema and itch to the affected arm . The second developed widespread rash , diaphoresis , urinary and faecal incontinence , and tongue/peri-orbital oedema . Laboratory investigation results were available for 12 of the 14 systemically envenomed patients . All 12 patients an elevated white cell count , with a median peak value of 17 . 5×109 ( Range 11 . 4–41 . 9×109 ) and an elevated neutrophil count , with a median value of 15 . 5×109 ( range 10 . 4–39 . 3×109 ) . Lymphocyte count was decreased in all 12 patients with a median nadir value of 0 . 9×109 ( Range 0 . 3–1 . 3×109 ) . The activated partial thromboplastin time ( aPTT ) was elevated in two envenomed patients ( 45 and 49 sec ) who had normal fibrinogen levels . A bite site sVDK was performed in eight of the 14 envenomed cases , which were all positive for death adder . In a further three of the 14 a urine sVDK was done and all three were positive for death adder venom . Antivenom was administered to all 12 patients with evidence of neurotoxicity and to the patient with myotoxicity . All patients received CSL monovalent death adder antivenom and an initial dose of one vial of antivenom . Subsequent doses of antivenom were administered to eight of the patients . The median dose of antivenom administered was 2 vials ( Range 1–5 ) and the median time from bite to antivenom was 10 hours ( IQR: 5–15 hr ) . The median time of resolution of all features of neurotoxicity after antivenom therapy was 21 hours ( IQR 5 . 0–28 . 5 hr; Range 5–168 hr ) . The early use of antivenom did not appear to be associated with less severe neurotoxicity . In the two patients with increased aPTT results , the aPTT returned to the normal range rapidly after these patients received antivenom . Systemic hypersensitivity reactions occurred in five patients receiving antivenom . These were mild ( limited to the skin ) in four cases however one anaphylactic reaction occurred with urticaria , wheeze , dyspnoea and chest tightness . Antivenom was not stopped in any patients because of these reactions . Neostigmine was administered to four patients including the two patients with severe neurotoxicity requiring intubation . In the first intubated patient , a dose of 2 . 5 mg of neostigmine was given with 600 mcg of atropine after intubation . Although the ptosis appeared to resolve the patient had ongoing respiratory weakness requiring intubation for a further five hours . The second intubated patient received three boluses of 0 . 5 mg , 2 . 5 mg and 2 . 5 mg of neostigmine followed by an infusion of 20 mcg per hour for 24 hours . After an initial improvement with eye opening , no further improvement in neurotoxicity was observed and the infusion was ceased due to bradycardia . Two other patients received neostigmine and atropine therapy with no demonstrated clinical benefit . Pre-antivenom blood samples were available for 10 of the 12 patients with neurotoxicity and the one patient who had non-specific systemic effects in isolation . The median peak venom concentration was 22 ng/mL ( IQR: 8 . 5–29 ng/mL , range 4 . 4–245 ng/mL ) . The patient who developed myotoxicity had no detectable venom in his pre-antivenom blood sample but that sample had measurable human IgG against death adder venom , consistent with his previous death adder bite . Death adder venom was detected in blood samples from four patients who did not have evidence of systemic envenoming , with concentrations of 0 . 7 , 0 . 9 , 3 . 7 and 40 ng/mL . In the eight cases where post-antivenom blood samples were available , including the patient with the highest venom level of 245 ng/mL , there was no detectable venom . All of these patients had only received their first vial of death adder antivenom before this blood sample was taken .
This study confirms that neurotoxicity is the main feature of envenoming by Australian death adders and that in the majority of cases severe life-threatening paralysis does not develop . Measurement of venom concentrations demonstrated that all free venom was bound after one vial of death adder antivenom so larger doses are not required . This included patients envenomed by four different death adder species . Neurotoxicity did not appear to resolve or reverse with the use of antivenom . Previously reported possible effectiveness of anticholinesterates [27] , [32]–[34] was not supported by this study , with the use of neostigmine providing little benefit in four cases . Given that neurotoxicity did not appear to resolve or reverse with the use of antivenom or anticholinesterases it is most likely to be due to irreversible injury from presynaptic neurotoxins , similar to the neurotoxicity from other Australian elapids such as the taipan [2] , [35] . Although it is possible that antivenom prevented those with mild neurotoxicity from getting progressively worse , this only occurred in one patient ( Table 3 , Row 4 ) and the two patients with severe neurotoxicity received antivenom within 6 hours ( Table 3 ) . The current recommended guidelines for snake bite patients in Australia of observation for at least 12 hours and not discharging at night , are well supported by the data in the study . Only one patient had delayed onset of neurotoxicity ( 15 . 5 hours ) , and it is likely that earlier onset was not picked up due to limited observations overnight , particularly waking this child to assess ptosis . A previous analysis of ASP data showed that all cases of neurotoxicity developed within 12 hours [36] . Just over half of death adder bites were in snake handlers which is the reason that a number of bites occurred in regions where death adders do not occur in the wild , such as Victoria . It also explains , in part , the reason for the predominance of upper limb bites , when compared to other studies of Australian snakes [37] . The study supports the fact that death adder bites from snakes in the wild are rare . In addition , they are more likely to occur at night and when the snake is disturbed . Unlike other Australasian elapids death adders are ambush predators and they are most active nocturnally . In this study it has been shown that patients bitten by death adders have a characteristic pattern of white blood cell count changes , namely leucocytosis , neutrophilia and lymphopenia . This has been previously reported for snake envenoming [38] , but because it is less reliable in some snake species such as brown snakes [36] , it is only helpful if the snake is known to be a death adder . An anticoagulant type coagulopathy was seen in two patients , an effect that has not been described in Australian death adder bites before . This is similar to the coagulopathy seen in Australian black snake bites with an elevation of the aPTT [37] and although a useful marker of envenoming is unlikely to be clinically significant . Normal fibrinogen levels confirm that it is not a consumption coagulopathy . Low concentrations of death adder venom were detected in blood samples from three patients who had no signs of systemic envenoming . These three concentrations were below those of any of the patients that developed neurotoxicity , indicating that a threshold blood concentration may need to be reached before neurotoxicity occurs . There was one patient with a high death adder venom concentration in their blood sample without any evidence of envenoming , indicating possible inter-person variability in susceptibility to venom effects and/or inter-snake variability in venom toxin composition [10] , [39] Some possible limitations of the study include the method of selection of cases for examination which in some patients was based upon prior knowledge of the syndrome of death adder envenoming . This may mean that some cases of death adder bite may have been missed and may be the reason for the much higher incidence of neurotoxicity in our study compared to previous studies . Because of the rarity of death adder bites and the small number of some species of death adder included in this study , other undescribed clinical effects of venom may occur . This study raises important questions about neurotoxicity , including the failure of antivenom to reverse neurotoxicity in death adder bites . This is consistent with the recent isolation of pre-synaptic neurotoxins in death adder venoms . It supports presynaptic neurotoxicity being the predominant cause of neurotoxicity in death adder bites as with other neurotoxic Australasian elapids . This is also consistent with a recent study that has shown that the rarity of neurotoxicity in brown snake envenoming is due to presynaptic neurotoxins in brown snake venom being less potent and only being a small proportion of the venom [40] . Our study suggests that severe neurotoxicity developed early and rapidly and that early antivenom ( within six hours ) in these two patients did not prevent neurotoxicity ( Table 3 ) . This differs to a previous study from Papua New Guinea which found that early antivenom treatment within 4 hours of a taipan bite was associated with a lower incidence of intubation/ventilation ( 33% compared to 66% ) [41] . Conversely , less severe neurotoxicity had a later onset , and the use of antivenom in these patients also did not appear to change the natural course of neurotoxicity , except possibly in one patient ( Table 3 , Row 4 ) . The median time to antivenom in the study was 10 hours , which is much longer than for treating venom induced consumption coagulopathy [42] . Table 3 shows that antivenom was given in response to the development of neurotoxicity accounting for this longer time to administration , which also means it is probably being given too late . It could be argued that antivenom may have limited benefit in the treatment of death adder neurotoxicity and that antivenom should only be given early in patients prior to the rapid onset of neurotoxicity . However , larger and controlled studies are required to determine this . Death adder envenoming is rare in Australia but can potentially cause severe neurotoxicity as seen in two of 14 envenoming cases in this study . Given the potential for severe neurotoxicity , the snake's wide distribution and the presence of the snake in private collections , it remains an important snake to consider . Whilst most cases are not life threatening , the failure of antivenom and anticholinesterases to reverse neurotoxicity once it is established is a concern . In the absence of a randomised controlled trial demonstrating the effectiveness of antivenom to prevent the development of neurotoxicity , and given the demonstrable risk of giving antivenom ( systemic hypersensitivity and anaphylaxis ) , the potential benefit of early antivenom remains uncertain . | Death adders are a genus of venomous snakes found in Australia , Papua New Guinea and Indonesia . Death adder envenoming is a rare but important health problem in Australasia . Definite death adder bites were recruited as part of the Australian Snakebite Project ( ASP ) . Clinical effects , laboratory results and response to antivenom treatment were recorded for each case . Death adder envenoming was confirmed by enzyme immunoassay in blood collected from patients . The most important clinical effect was neurotoxicity , which was mild in most cases . One vial of antivenom was shown to be effective at binding circulating death adder venom . However , antivenom had little effect on the neurotoxicity that developed in envenomed patients and neurotoxicity took on average one day to resolve . This study supports the idea of presynaptic neurotoxicity in death adder envenoming which was previously thought to be due to post-synaptic neurotoxicity . The study calls into question the benefit of antivenom , with poor response shown in patients with both mild and severe envenoming . | [
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] | [
"medicine",
"immunotoxicology",
"immunology",
"toxicology"
] | 2012 | Death Adder Envenoming Causes Neurotoxicity Not Reversed by Antivenom - Australian Snakebite Project (ASP-16) |
Human leishmaniases are parasitic diseases causing severe morbidity and mortality . No vaccine is available and numerous factors limit the use of current therapies . There is thus an urgent need for innovative initiatives to identify new chemotypes displaying selective activity against intracellular Leishmania amastigotes that develop and proliferate inside macrophages , thereby causing the pathology of leishmaniasis . We have developed a biologically sound High Content Analysis assay , based on the use of homogeneous populations of primary mouse macrophages hosting Leishmania amazonensis amastigotes . In contrast to classical promastigote-based screens , our assay more closely mimics the environment where intracellular amastigotes are growing within acidic parasitophorous vacuoles of their host cells . This multi-parametric assay provides quantitative data that accurately monitors the parasitic load of amastigotes-hosting macrophage cultures for the discovery of leishmanicidal compounds , but also their potential toxic effect on host macrophages . We validated our approach by using a small set of compounds of leishmanicidal drugs and recently published chemical entities . Based on their intramacrophagic leishmanicidal activity and their toxicity against host cells , compounds were classified as irrelevant or relevant for entering the next step in the drug discovery pipeline . Our assay represents a new screening platform that overcomes several limitations in anti-leishmanial drug discovery . First , the ability to detect toxicity on primary macrophages allows for discovery of compounds able to cross the membranes of macrophage , vacuole and amastigote , thereby accelerating the hit to lead development process for compounds selectively targeting intracellular parasites . Second , our assay allows discovery of anti-leishmanials that interfere with biological functions of the macrophage required for parasite development and growth , such as organelle trafficking/acidification or production of microbicidal effectors . These data thus validate a novel phenotypic screening assay using virulent Leishmania amastigotes growing inside primary macrophage to identify new chemical entities with bona fide drug potential .
Human leishmaniases are diseases that are endemic throughout tropical and subtropical areas causing severe morbidity and mortality with an estimated worldwide incidence of 1 , 500 , 000 newly reported clinical cases per year . More than 12 million people are currently infected and 350 million people are at risk [1] . Causal agents of human leishmaniases are Euglenozoan digenetic parasites belonging to the Trypanosomatidae family and the genus Leishmania . They are cycling between i ) blood-feeding phlebotomine insects where they develop as extracellular flagellated promastigotes , and ii ) a range of mammals , including rodents , canids and human where they develop as obligatory intracellular amastigotes . Depending on both the Leishmania species and the mammal host genetic and immune status , four main clinical forms of leishmaniasis can be distinguished , including i ) the visceral form , which causes long-term fever , weight loss , hepatosplenomegaly and pancytopenia , and is usually fatal if left untreated , ii ) the cutaneous form characterized by single or multiple lesions , which generally self-cures over months , iii ) the muco-cutaneous form affecting mainly nasopharyngeal mucosa characterized by extensive tissue destruction causing severe facial disfiguration and respiratory disturbances , and iv ) a diffuse form in which non-ulcerating lesions are spread over large skin areas . Leishmaniases result in a strong social stigma and marginalization for infected individuals and has an important negative impact on welfare and productivity of people from developing countries [2]–[4] . The current treatment of leishmaniasis essentially relies on chemotherapy as , to date , neither preventive nor therapeutic vaccines are available . Pentavalent antimonials have been used for more than 70 years and are still the recommended first line of treatment . However , these drugs not only require a long course of parenteral treatment with repeated injections and careful monitoring in health centers , but also display variable efficacy and toxic side effects [1] , [5]–[7] . Alternative therapeutic approaches based on the use of Amphotericin B ( AmphoB ) , an antifungal polyene antibiotic , and its lipid-carrier formulations have been successfully applied when first line drugs were no longer effective [8] , [9] . Nevertheless , the very high costs of these drugs limit their widespread use . In recent years , new molecules such as the anti-neoplastic agent Miltefosine , new treatments such as drug combinations , or new administration routes like topical formulations and oral administration , have been introduced in anti-leishmanial chemotherapy . However , in view of the recent spreading of Leishmania showing resistance to the limited number of existing drugs in various parts of the world , there is an urgent need to develop new , safe , fast acting , and affordable treatments . While several new chemical scaffolds have been identified recently , they were issued from screening campaigns that were primarily based on the use of extracellular promastigotes [10] , [11] , i . e . the developmental stage that differentiates within the mid gut of sand fly hosts . It is noteworthy that promastigotes differ significantly from amastigotes with respect to morphology , the composition of their surface glycocalyx , and metabolism . These biological differences reflect distinct developmental programs that adapt Leishmania for extra- and intracellular survival in the phlebotomine mid gut and the macrophage parasitophorous vacuole ( PV ) , respectively [12]–[16] . Conceivably , this stage specific biology has important consequences on how the parasite responds to chemicals [17]–[19] . When comparing the leishmanicidal activity of antimony in infected animals versus cultured parasites , the antimony susceptibility determined in vivo correlated better with the in vitro assays performed with intracellular amastigotes than with extracellular promastigotes [20] . Moreover , host features such as the permeability of plasma- and PV- membranes or the presence of molecules able to directly interfere with or metabolize chemicals are key parameters to consider for discovering compounds with selective activity against the intracellular amastigote stage . Leishmania survival within macrophages depends on the capacity of amastigotes to evade or to resist the innate host cytotoxic activities . It is possible that rescue of these activities will lead to efficient intracellular amastigote destruction . Thus , an assay based on the phenotype classification of primary macrophages hosting Leishmania amastigotes may allow to discover compounds that confer to infected macrophage full leishmanicidal activities [18] , [21]–[24] . With the aim to establish a biologically relevant screening system that accounts for all of these considerations , we designed and validated a miniaturized High Content Analysis assay , relying on primary mouse macrophages hosting virulent L . amazonensis amastigotes . This approach overcomes limitations associated with promastigote-based screens [19] , [25] . It allows the rapid selection of compounds that are able to interfere with Leishmania amastigote growth and survival within primary macrophages either directly , or indirectly by modifying macrophage organelle trafficking or acidification required for intracellular parasite growth . Based on robust statistical methods , quality control metrics , hit identification classification and validation , we developed a powerful data analysis pipeline that provides for each tested compound metrics on amastigote load and their toxic effect on host macrophages at the single cell level and for the entire sample population analyzed .
Female Swiss nu/nu and BALB/c mice , between 8- and 12-week of age , were obtained from Charles River . Bone marrow cell suspensions recovered from tibias and femurs of BALB/c mice were suspended in DMEM medium ( Gibco , life technologies ) containing 4 g/L glucose , 1 mM pyruvate and 3 . 97 mM L-Alanyl-L-Glutamine , 10% heat-inactivated fetal calf serum ( FCS , Dominique Dutscher SAS ) , streptomycin ( 50 µg/mL ) and penicillin ( 50 IU/mL ) ( Biochrom AG , IBS International ) ( culture medium ) and with 50 ng/mL recombinant mouse CSF-1 ( rmCSF-1 ) ( ImmunoTools ) . Cells were distributed in bacteriologic plastic flasks ( Corning Life Science , 7×105 cells/ml ) and were incubated at 37°C in a 7 . 5% CO2 air atmosphere for 6 days . Six days old bone marrow-derived , loosely adherent macrophages were washed with Dulbecco's phosphate buffered solution ( PBS ) and detached by gentle flushing ( 25 min at 37°C ) with pre-warmed 1% EDTA in PBS without Ca2+ and Mg2+ ( Biochrom AG ) . Recovered macrophages were suspended in either culture medium for HCS assay or cold PBS with 2% FCS and 0 . 05% sodium azide ( PBS-FCS-Az ) for FACS quality controls . Macrophages for FACS analysis were transferred to round-bottomed 96-well plates ( Corning Costar ) at a concentration of 3×105 cells/well . All subsequent steps were performed on ice and with ice-cold reagents . Cells were centrifuged ( 300 g ) for 5 minutes and then incubated in PBS-FCS-Az supplemented with 10% donkey serum for 20 minutes . After centrifugation , cells were incubated for 30 minutes in PBS-FCS-Az containing a combination of fluorescent reporter-conjugated antibodies . Flow cytometry results were acquired on a Gallios flow cytometer ( Beckman Coulter ) and data analyzed with the Kaluza software package ( Beckman Coulter ) . The anti-mouse mAbs were purchased from Pharmingen for FITC-labeled 2G9 anti I-Ad/I-Ed clone , or eBioscience for the followings clones: e450-conjugated N418 anti-CD11c ( p150/90 ) , APC-conjugated M1/70 anti-CD11b/CR3 α-chain , PE-conjugated 16-10A1 anti-CD80/B7-1 , APC-conjugated BM8 anti-F4/80 , and PE-conjugated AFS98 anti-CD115 . L . amazonensis strain LV79 ( MPRO/BR/1972/M1841 ) was genetically modified by chromosomal integration of the fluorescent DsRed2 molecule [26] and propagated in Swiss nu/nu mice by subcutaneous injection of 106 amastigotes into hind footpad . Six to eight weeks after amastigote inoculation lesions were excised and amastigotes purified by a modified version of the method originally described by M . Rabinovitch and colleagues [27] . Briefly , lesions were minced in PBS supplemented with streptomycin ( 100 µg/mL ) and penicillin ( 100 IU/mL ) , and disrupted by hand in a glass homogenizer . Tissue debris were removed by 2 rounds of centrifugation at 30 g for 10 mn at 4°C . Amastigotes present in the supernatant were washed 2 times by centrifugation at 1500 g for 10 mn at 4°C before distribution in macrophage cultures . A high number of live amastigotes expressing homogenous levels of DsRed2 were recovered as determined by FACS analysis ( data not shown ) . Reference compounds , Leucine Methyl Ester ( Leu-OMe ) [27] , AmphoB and cycloheximide , were solubilized in DMSO ( Sigma-Aldrich ) . Based on literature data , we selected 60 compounds with established or potential leishmanicidal , anti-fungal or anti-microbial and cytotoxic activities to validate our experimental and data analysis pipelines . Details about their origins , working concentrations and known activity are provided in Table S1 . We defined the following control conditions: C− 1% DMSO- , C+ , 0 . 5 µM AmphoB- and C† 180 µM cycloheximide . All compounds were assayed at 10 µM or as stated in Table S1 . The detailed plate maps used in this study with the position of controls are depicted in Tables S2 and S3 ( see table legend for details ) . Six days-old bone marrow-derived adherent macrophages were recovered as described above and deposited in culture-treated flat-optically clear bottom black 384-well plates ( CellCarrier plate , PerkinElmer ) at a density of 1 . 5×104 cells in 70 µl of medium supplemented with 12 ng/ml of rmCSF-1 per well , resulting in a 80% confluence monolayer without formation of cellular aggregates . Five hours later , purified DsRed2-expressing amastigotes were added to the macrophages at a multiplicity of 3 parasites per host cell ( MOI = 3 ) ( 30 µl/well ) . Macrophage cultures were further incubated at 34°C , which is the permissive temperature for the surviving and multiplication of LV79 amastigotes [28] , [29] . After an overnight incubation period , more than 85% of macrophages harbored intracellular parasites that were already multiplying in growing PVs [30] . At this time , compounds ( Tables S2 , S3 ) were added to macrophages ( 1 µl/well ) resulting in a final concentration of 1% DMSO in each well . The cultures were then maintained 3 days at 34°C until processing for image acquisition . One hour before image acquisition , the cells were incubated with vital cell-permeant dyes Hoechst 33342 ( 12 µM ) and LysoTracker DND-26 ( 1 µM ) ( life technologies ) . Optimization of operating parameters included an automated dispensing of biological material ( macrophages and amastigotes ) and chemicals ( vehicle , compounds ) using the Te-MO 96-channel pipetting head of a TECAN Freedom EVOware platform located under laminar flow in a BSL2 facility . The homogeneity and the reproducibility of all pipetting procedures were assessed by quantitative image analysis during assay development ( data not shown ) . After 60 minutes of contact with fluorescent reporters , three channel images were acquired in a fully automated and unbiased manner using a spinning disk confocal microscope ( OPERA QEHS , PerkinElmer Technologies ) and a 10× air objective ( NA = 0 . 4 ) using the following sequential acquisition settings: ( i ) 561 nm laser line excitation , filter 600/40 for DsRed2 detection , ( ii ) 488 nm laser line excitation , filter 540/75 for Lysotracker DND-26 detection and ( iii ) 405 nm laser line excitation , filter 450/50 for Hoechst 33342 detection . Fifteen images per channel , covering the entire surface of each well , were collected for reliable statistical analysis taking into account potential cell-distribution and spatial compound effect biases . The images were transferred to the Columbus Conductor™ Database ( Perkin Elmer Technologies ) for storage and further analysis . The image analysis was performed by batches in Columbus using custom designed image analysis scripts developed beforehand with the Acapella Image analysis software ( version 2 . 5 - Perkin Elmer Technologies ) . The script was subdivided in three object segmentation subroutines detecting successively and independently the nuclei , the PV and the Am with their respective associated features ( number , size , and intensity ) ; the living macrophage population characterisation is based on a combination of host cell nucleus size and intensity features which are key characteristics of the relative fitness of the macrophage population . Finally , all the quantitative data generated were exported in readable file format to be subsequently analyzed in the data analysis workflow described below . To validate our pipeline , selections of image analysis outputs , including macrophage nuclei , PV and Am counts that best represented typical compound-induced phenotypes , were used . We applied a standardized data analysis workflow to automate and validate the interpretation of the large amount of data generated by image acquisition and analysis; it consists of the following three main classical hands-off steps [31]:
Current screening protocols for the discovery of anti-leishmanial compounds are compromised by both the types of parasites and host cells employed . First , the use of culture-derived promastigotes and axenic amastigotes are not reflecting the biology and environment of parasites inside the macrophage . In addition Pescher and colleagues recently demonstrated that axenic amastigotes were not able to induce acute visceral disease in hamsters compared to tissue-derived amastigotes thus minimizing the potential interest of using host-free parasites [35] . Second , the use of macrophage cell lines as host cells for Leishmania is problematic due to the mandatory use of chemicals to induce terminal macrophage differentiation , chemicals that are known to result in modulation of macrophage sensitivity to compounds , thus compromising the interpretation of screening results [18] , [36] , [37] . Finally , the combination of both i . e . using host cell lines infected with culture-derived parasites results in i ) the presence of large quantity of extracellular proliferating promastigotes and ii ) a lower rate of host cells hosting metacyclic promastigotes able to differentiate into cell-cycling amastigotes . To overcome these limitations , we set up a reliable assay based on the use of mouse primary macrophages and highly virulent lesions-derived amastigotes of L . amazonensis , which were genetically modified to stably express a DsRed2 fluorescent reporter [26] . Homogeneous populations of macrophages differentiated from bone marrow progenitors by incubation with Colony Stimulating Factor 1 ( CSF-1 ) [29] ( Figure S2 ) were distributed in 384-well plates , and amastigotes freshly prepared from Swiss nude mouse lesions [38] were then added to the macrophage monolayer . In contrast to promastigote-based protocols , L . amazonensis amastigotes were readily phagocytized by macrophages leading to a high and sustained infection rate . After a few hours , amastigotes were already multiplying , resulting in the development of large PVs , a phenotypic hallmark of a successful intracellular L . amazonensis infection ( Figure 1A ) [30] , [39] . No extracellular amastigotes can be evidenced either by phase contrast or confocal fluorescence microscopy ( Figures 1A , 1B ) . The PV property to accumulate the cell-permeant LysoTracker DND-26 , a fluorescent weak base probe , is a signature of the sustained fusion of macrophage late endocytic organelles with amastigotes-containing phagosomes ( Figure 1B ) [39] , [40] . When amastigote growth is blocked or amastigotes are killed in presence of a leishmanicidal agent like AmphoB , PVs are either strongly reduced in size or no longer detected ( Figure 1C ) . The disappearance of PVs was correlated in a previous study to elimination of intracellular amastigotes as shown by fluorescence and differential interference contrast microscopy , and real-time quantitative PCR [29] . The presence/absence of PVs represents thus a powerful digital readout to monitor a leishmanicidal effect , a criterion we already used successfully in a non-automated visual assay for selecting 2-quinoline derivatives with activity against intracellular L . amazonensis amastigotes [29] , [41] . Concomitantly , our assay allows monitoring the health status of host macrophages by visualizing their nuclear morphology with the permeant DNA probe Hoechst 33342 . In presence of a toxic compound like cycloheximide , dead macrophages were easily differentiated from healthy cells and identified by the loss of nuclear integrity ( Figure 1B , 1C , 1D ) . Based on this biologically relevant and quantifiable infection system we established an automated phenotypic screening pipeline described below . To minimize any experimentally induced biases , we developed a linear procedure that consists of the sequential addition of mouse bone marrow-derived macrophages , purified tissue-derived amastigotes and chemicals in 384-well optical imaging clear bottom plates , without any washing steps ( Figure 2A ) . This protocol minimizes the potential heterogeneity between wells , thereby avoiding sample perturbation and artifacts over the subsequent incubation period . The procedure is finalized after 3 days of co-culture by the addition of the fluorescent reporters LysoTracker DND-26 and Hoechst 33342 one hour before image acquisition . To validate our procedure , images were acquired in numerous control wells for the 3 different fluorescent reporters corresponding to the counts of DsRed2-tagged amastigotes , LysoTracker-positive PVs and macrophage Hoechst-stained nuclei ( see next paragraph for a detailed description of the procedure ) . In order to avoid biases due to potential heterogeneity of the macrophage monolayer that could arise over time , and to increase the size of the population analyzed , image acquisitions were performed at low magnification using a dry 10× objective for the entire surface of the wells , resulting in acquisition and analysis of all cells for each sample . The images were thereafter segmented using Acapella scripts and the outputs normalized and expressed as percentages of media control ( Figure 2B ) . The presence of 1% DMSO ( C- ) did not induce toxic effect on macrophages as demonstrated by the similar values obtained for the VI ( Figure 2B bottom panel and Figure S3 ) . On the contrary , the presence of a toxic compound for the macrophage , like cycloheximide , was easily evidenced by the dramatic decrease of the VI compared to untreated or DMSO-treated samples ( Figure 2B , bottom panel ) . As expected , in presence of 2 leishmanicidal agents L-Leu-oMe and AmphoB , amastigote and PV counts were significantly reduced compared to negative controls ( Figure 2B , top and middle panels ) without inducing toxicity on host macrophages ( Figure 2B , bottom panel ) . When performing a comparative analysis between amastigote and PV counts , we observed a good correlation in dose-response experiments using known leishmanicidal agents ( Figure 2C and data not shown ) . Specifically , the IC50 of AmphoB was estimated at 0 . 11 µM and 0 . 17 µM for the PV and amastigote output , respectively , which , furthermore , are consistent with published values [10] . Because the PV readout can be efficiently quantified at lower magnification ( 10× objective ) , allowing for the analyses of the entire well per sample , we performed the subsequent screen using the presence/absence of PVs as the principal readout for parasite burden generating statistically highly relevant screening data . The box-and-whisker diagrams depicted in Figure 2B for the different variables strengthen and validate the homogeneity and the reproducibility of pipetting procedures , including the chemical distribution routine , used in this assay . The counts of macrophage nuclei , PVs , and amastigotes were subsequently used to establish a data analysis pipeline described in the following . We applied our experimental approach to a small compound library combining known leishmanicidal drugs , newly published structures and antifungal or cytotoxic agents ( Table S1 ) . These compounds were initially tested in quadruplicates per plate in 2 different experiments ( plates P1–P2 for Exp1 and P3–P4 for Exp2 ) . In experiments 3 to 7 , we used single data points for each compound on each plate ( plates P5 to P9 corresponding to Exp3 to Exp7 ) at a concentration of 10 µM unless stated otherwise ( Table S1 ) . The precise design of the assay plates is described in Tables S2 and S3 . In P5 to P9 , we removed the “media” negative control , which was redundant to the “vehicle” control ( 1% DMSO ) since no toxicity towards the macrophage and amastigote populations could be evidenced ( Figure 2B and Figure S3 ) . We also included in these plates cycloheximide-treated cells as positive control for macrophage toxicity ( C† ) , which allowed us to more adequately classify compounds with strong toxic effect on macrophages and only very weak effect on amastigotes ( Figures 1D and 2B ) as shown in our assay validation plate . We developed thereafter a stringent data analysis pipeline based on strong proven statistical methods for quality control , normalization and ranking of the results to validate and analyse the screening outcomes as described in the methods section . The three original readouts chosen from the image analysis ( count of macrophages , PVs and amastigotes ) are de facto independent and were used to define five variables: Total Macrophages ( TM ) , Healthy Macrophages ( HM ) , Viability Index ( VI = HM/TM ) , total number of Amastigotes ( Am ) , and the ratio between PVs and healthy macrophages ( PV/HM ) . These variables allow for precise phenotype discrimination and efficient hit identification . Critical main hands-off steps of the data analysis pipeline are described below [31] . Among the dominant class of 18 compounds that presented a strong anti-leishmanial activity associated with high toxicity to host macrophages a majority of compounds were Paullone derivatives ( Figure 3 , image C3 for an illustration ) . Paullones have been described previously as inhibitors of cyclin-dependent kinases and glycogen synthase kinase-3 , and also as inhibitors of L . donovani axenic amastigotes [42] . High toxicity described against host cells for these molecules indicated that screening on host-free parasite populations can lead to false positive hits , a conclusion also reached by De Muylder and colleagues [18] . Some Paullone derivatives were reported as either inefficient within THP1 macrophages and/or too toxic for the host cell [42] . A second class of compounds ( chalcone derivatives; compounds c10 , c13-16 ) was identified that did not induce any noticeable phenotype in our assay ( Figure 3 ) , although they have been previously identified as active against L . donovani axenic amastigotes in the micromolar range [43] . Finally , Acivicin ( c49 ) , Aphidicolin ( c51 ) and Phenyltoxamine ( c52 ) did not exhibit any activity on intramacrophagic amastigotes ( Figure 3 ) , even though these molecules were described previously as potent growth inhibitors for L . major promastigotes by Sharlow and coworkers [10] . Lack of leishmanicidal activity of these compounds against intramacrophagic amastigotes was certainly due to their inability to cross the host macrophage membranes surrounding the parasites . Control experiments performed on L . amazonensis promastigotes indeed confirmed the activity of these compounds towards host-free parasites , with IC50 values of 0 . 01 µM , 0 . 48 µM , and > = 5 µM for Acivicin , Aphidicolin , and Phenyltoxamine , respectively ( Figure 4 ) . Anti-leishmanial compounds were distributed into two phenotypic categories . The first comprised 4 compounds with low leishmanicidal activity at 10 µM on intracellular amastigotes ( c29 , c38 , c40 and c44 ) ( Figure 3 ) . This category includes notably the known drugs Pentamidine Isethionate ( c38 ) , a molecule active on viscerotropic and dermotropic Leishmania species [44] different from L . amazonensis , Miconazole ( c40 ) and Clotrimazole ( c44 ) , two antifungals with known anti-leishmanial activity [45] , which showed variable efficacy depending on therapy conditions and Leishmania species [46]–[48] . Moreover , while Pentamidine Isethionate in particular has been recently validated as a strong growth inhibitor of L . major [10] for both promastigote and axenic amastigote–like stages with an EC50 value similar to the value we obtained with L . amazonensis promastigotes ( 0 . 65 µM , Figure 4 ) , it only exhibited low level of intra-macrophage activity ( above 10 µM EC50 ) [47] . Such discrepancies between hit compounds showing leishmanicidal activities against either promastigotes or intramacrophagic amastigotes have already been observed [18] , [49] , reinforcing the value of our approach . The second category includes compounds that displayed a strong intra-macrophagic anti-leishmanial phenotype such as our reference compounds , Leu-oMe ( c43 and c60 ) and AmphoB ( c55 ) and four compounds ( c28 , c32 , c34 and c53 ) ( Figure 3 ) identified by Guiguemde and co-workers for their activity against L . major promastigotes [50] . Our results further reinforce the need and the adequacy of cellular assays such as the one presented here for rapid and successful identification of active molecules on Leishmania cell-cycling amastigotes hosted by primary macrophages [49] . In the present study , we developed a scalable , throughput capable high content approach to select chemicals able to eliminate L . amazonensis amastigotes that are actively multiplying within the acidic giant parasitophorous vacuoles of primary macrophages . This novel assay is simple and relies on only few experimental steps during which highly pure populations of amastigotes , compounds and fluorescent reporters are sequentially added to adherent macrophages without any washing or addition of fixative reagent . It generated robust and reproducible data based on the manipulation of large homogeneous populations of infected macrophages and allowed a dual measure of leishmanicidal activity against intramacrophagic parasites and the host macrophage health status . By allowing real-time monitoring and kinetic studies on living adherent primary macrophages , this approach offers many advantages over assays that have been described recently in the literature with respect to assay reproducibility and infection homogeneity [11] , [18] , [49] , [51] . Additionally , it enables the discovery of leishmanicidal compounds acting through the activation of microbicidal mechanisms of the host macrophage . Finally , the compound incubation period of our HCA assay was successfully prolonged up to six days ( Figure S6 ) thus allowing for the discovery of slow-acting leishmanicidal compounds with kinetics similar to antimonials . Analyses of screening campaigns performed with compounds from kinase inhibitor libraries as part of the LeishDrug project sponsored by the EU's Seventh Framework Programme for Research are ongoing [52] . | Leishmaniases are neglected diseases caused by protozoan parasites that belong to the genus Leishmania . No vaccine exists against any form of leishmaniasis and most of the existing anti-leishmanial drugs have serious side effects . Current strategies for discovering new leishmanicidal molecules are largely using inappropriate types of host cells or employing the irrelevant insect-specific parasite stage . We presented here an innovative and biologically relevant drug screening assay based on the use of the mammalian macrophage host cells and Leishmania pathogenic amastigotes . Our visual fluorescence assay has been established with the objective to screen diverse small-molecules including chemicals and natural compounds that selectively target intra-macrophagic amastigotes without displaying toxicity for the macrophage host cells . The validation of a miniaturized assay , relying on automated handling of biological materials and fluorescent imaging probes , image acquisition , data storage and analysis is presented . Based on robust statistical methods and quality control metrics , the data analysis pipeline allows for the classification of compounds based on their effect on parasite and macrophage survival observed after three days of treatment . | [
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results/Discussion"
] | [
"biotechnology",
"parastic",
"protozoans",
"leishmania",
"small",
"molecules",
"protozoology",
"host-pathogen",
"interaction",
"microbiology",
"biology",
"drug",
"discovery"
] | 2013 | High Content Analysis of Primary Macrophages Hosting Proliferating Leishmania Amastigotes: Application to Anti-leishmanial Drug Discovery |
Type 2 diabetes ( T2D ) is a complex metabolic disease associated with obesity , insulin resistance and hypoinsulinemia due to pancreatic β-cell dysfunction . Reduced mitochondrial function is thought to be central to β-cell dysfunction . Mitochondrial dysfunction and reduced insulin secretion are also observed in β-cells of humans with the most common human genetic disorder , Down syndrome ( DS , Trisomy 21 ) . To identify regions of chromosome 21 that may be associated with perturbed glucose homeostasis we profiled the glycaemic status of different DS mouse models . The Ts65Dn and Dp16 DS mouse lines were hyperglycemic , while Tc1 and Ts1Rhr mice were not , providing us with a region of chromosome 21 containing genes that cause hyperglycemia . We then examined whether any of these genes were upregulated in a set of ~5 , 000 gene expression changes we had identified in a large gene expression analysis of human T2D β-cells . This approach produced a single gene , RCAN1 , as a candidate gene linking hyperglycemia and functional changes in T2D β-cells . Further investigations demonstrated that RCAN1 methylation is reduced in human T2D islets at multiple sites , correlating with increased expression . RCAN1 protein expression was also increased in db/db mouse islets and in human and mouse islets exposed to high glucose . Mice overexpressing RCAN1 had reduced in vivo glucose-stimulated insulin secretion and their β-cells displayed mitochondrial dysfunction including hyperpolarised membrane potential , reduced oxidative phosphorylation and low ATP production . This lack of β-cell ATP had functional consequences by negatively affecting both glucose-stimulated membrane depolarisation and ATP-dependent insulin granule exocytosis . Thus , from amongst the myriad of gene expression changes occurring in T2D β-cells where we had little knowledge of which changes cause β-cell dysfunction , we applied a trisomy 21 screening approach which linked RCAN1 to β-cell mitochondrial dysfunction in T2D .
Type 2 diabetes ( T2D ) is a complex metabolic disorder characterised by elevated blood glucose levels . Pancreatic β-cell dysfunction and reduced insulin output in the presence of insulin resistance is the primary cause of T2D . The mechanisms leading to a switch from β-cell compensation during the early stages of insulin resistance to β-cell failure in the latter stages remain unknown . Studies from human T2D islets provide the most direct evidence regarding the nature of such β-cell changes . Reduced β-cell mass and insulin content is observed in T2D [1] , but these are not insurmountable given the capacity of sulphonylureas , GLP-1 agonists or bariatric surgery to restore insulin secretion and plasma glucose in T2D patients . Clearly alternative pathways exist to drive β-cell dysfunction and reduced glucose-stimulated insulin secretion ( GSIS ) . For example , oxidative stress is increased in human T2D β-cells and negatively correlates with GSIS impairment [2] . T2D β-cells also display marked mitochondrial dysfunction; characterised by a reduced respiratory response to glucose [3] in association with lower ATP levels [4] . Given that mitochondrial function is central to oxidative stress , ATP production and GSIS in β-cells , and that these are major defects in T2D β-cells , identifying the genes responsible for β-cell mitochondrial dysfunction is essential to further our understanding of the mechanisms controlling β-cell function . As one approach to identifying causative genes , several genome-wide association studies ( GWAS ) have compared gene expression changes in healthy and T2D human patients ( see [5] for full details ) and gene array and proteomic studies have been conducted on T2D islets [6 , 7] . The largest such study involved 89 donors and identified 4 , 920 gene expression changes using RNA Sequencing in T2D islets [8] . However , identifying which of these changes are functionally relevant to β-cell dysfunction in T2D is a significant challenge . Interestingly , islets derived from fetal Down syndrome ( DS ) tissue exhibit β-cell mitochondrial dysfunction , low ATP levels and reduced insulin secretion [9] . We have therefore exploited the phenotypes shared by β-cells derived from DS and T2D islets in an attempt to detect functionally relevant genes in human islets that underlie β-cell dysfunction in T2D . Using this approach we identified a single lead candidate , a gene called Regulator of calcineurin 1 ( RCAN1 ) , which is overexpressed in T2D islets and when overexpressed in mouse islets , causes β-cell mitochondrial dysfunction and reduced ATP production to inhibit insulin secretion .
To screen for chromosome 21 genes that may contribute to diabetes , measured fasting blood glucose levels ( in mM ) were measured in 4 mouse models of DS; Ts65Dn , Dp16 , Ts1Rhr and Tc1 ( Fig 1A ) . These transgenic mouse lines either have a partial or whole trisomy of mouse chromosome 16 ( largely homologous to human chromosome 21 ) or contain an incomplete freely segregating human chromosome 21 ( Tc1 ) ( Fig 1F ) . We found that Ts65Dn ( control 8 . 0 ± 0 . 3 , n = 17 vs Ts65Dn 10 . 9 ± 0 . 9 , n = 14 , p < 0 . 01 ) and Dp16 ( control 9 . 7 ± 0 . 5 , n = 10 vs Dp16 12 . 1 ± 0 . 9 , n = 11 , p < 0 . 05 ) mice were hyperglycaemic , Ts1Rhr mice were normoglycaemic ( control 11 . 1 ± 0 . 6 , n = 18 vs Ts1Rhr 11 . 5 ± 0 . 4 , n = 12 ) , and Tc1 mice were hypoglycaemic ( control 13 . 6 ± 0 . 6 , n = 23 vs Tc1 9 . 4 ± 0 . 5 , n = 23 , p < 0 . 001 ) . Ts65Dn mice ( Fig 1B and 1C ) demonstrated poorer glucose tolerance ( measured by intraperitoneal glucose tolerance tests ( IPGTT ) ) but no change was observed in the Tc1 mouse line ( Fig 1D and 1E ) . These data indicated that a subset of chromosome 21 genes contributed to the development of glucose intolerance and hyperglycaemia . Mapping the trisomic regions of chromosome 21 unique to Ts65Dn and Dp16 mice amongst these lines identified a region of 38 candidate genes that contains genes that must contribute to the hyperglycaemic phenotype ( Fig 1F ) . We next used RNA Seq data from human islets from a Swedish study obtained from 89 donors ( 77 non-diabetic ( ND , HbA1c <6 . 5% ) and 12 T2D ( HbA1c >6 . 5% ) [8] to identify whether any of these 38 genes have increased expression in T2D islets . Five genes were significantly up regulated; EVA1C ( p = 0 . 038 ) , OLIG2 ( p = 0 . 009 ) , IFNAR1 ( p = 0 . 021 ) , RCAN1 ( p = 0 . 009 ) and RUNX1 ( p = 0 . 0003 ) ( Fig 1F ) . EVA1C is a Slit receptor involved in Robo-mediated axonal guidance [10] , OLIG2 regulates spinal cord oligodendrocyte and motor neuron development [11] , IFNAR1 is an interferon receptor with no role in the initiation or progression of diabetes [12] and RUNX1 is involved in haematopoiesis [13] . Only RCAN1 has any known role in affecting mitochondrial function [14] or insulin secretion when either chronically overexpressed in mouse islets [15] or transiently transfected into a mouse β-cell line [16] . RCAN1 is highly abundant in human islets , being in the top 13% most highly expressed genes across the genome [8] . In human T2D islets , gene expression of RCAN1 was 153% of that in ND islets ( Fig 2A ) . RCAN1 expression correlated significantly with the clinical measure of long-term glycaemic status , glycosylated haemoglobin ( HbA1c , Fig 2B ) and BMI ( S1A Fig ) across all samples . When RCAN1 expression was separated across HbA1c categories , we found that expression in islets from HbA1c >6 . 5% ( T2D ) was higher than that in healthy islets ( HbA1c <6% ) but not different to those with impaired glucose tolerance ( HbA1c 6–6 . 5% ) ( S1B Fig ) , indicating that islet RCAN1 expression increases after insulin resistance has occurred . Furthermore , this human islet data was consolidated by global islet genome expression data from an earlier study [17] that profiled gene expression in islets from an obesity-induced diabetes-resistant mouse strain and from a diabetes-susceptible mouse strain before ( 4 weeks of age ) and after ( 10 weeks of age ) the onset of diabetes . This mouse islet data demonstrated that mouse islet RCAN1 expression is correlated with increased plasma triglycerides ( S1C Fig ) and increased body weight ( S1D Fig ) , both of which are associated with T2D in humans . To understand more about RCAN1 in human T2D islets , we analysed previously published data using the Infinium 450k array to examine global changes in DNA methylation in human T2D islets [18] . Compared to the non-diabetic group , RCAN1 had the fifth largest difference in methylation across the entire analysed genome in T2D islets , and the largest difference in methylation of all analysed chromosome 21 genes [18] . Additionally , of all 16 analysed RCAN1 methylation sites on the 450k array , 3 show a significant negative correlation across all samples between methylation status and RCAN1 expression ( Fig 2C–2E ) . Importantly , these 3 sites also displayed significant reductions in methylation in T2D islets from 51 . 1 ± 1 . 8% in non-diabetic islets ( n = 34 ) to 40 . 2 ± 3 . 1% in T2D islets ( n = 15 , p<0 . 01 , data is mean ± SEM ) at site cg05156137 , 57 . 9 ± 1 . 9% vs 48 ± 3 . 2% ( p<0 . 01 ) at cg21301258 and 42 . 3 ± 1 . 5% vs 29 . 5 ± 1 . 9% ( p<0 . 001 ) at cg05056497 [18] . Thus , our data demonstrated that RCAN1 expression is linked to hyperglycaemia in DS mice , it correlated in islets with a worsening metabolic profile in obese mice , and it is increased in human T2D islets . Furthermore , RCAN1 methylation at three different sites correlated with RCAN1 expression in human islets and methylation status at these sites is reduced in T2D islets . This combination of multiple data sets strongly supports the concept that RCAN1 expression is increased in T2D β-cells . We next confirmed whether human islets express the RCAN1 protein . RCAN1 has two isoforms called RCAN1 . 1 and RCAN1 . 4 ( S2D Fig ) . Each differs in their start exon but both contain common exons 5 , 6 and 7 . Exon 7 contains the calcineurin binding motif [19] and both isoforms are thought to have shared functions as inhibitors of calcineurin . Western blot analysis revealed that RCAN1 . 1 and RCAN1 . 4 isoforms were both present ( Fig 2F ) , with the RCAN1 . 1 isoform expression ~4 fold higher , similar to mouse islets and the mouse MIN6 β-cell line , an insulinoma cell line derived from a transgenic mouse expressing the large T-antigen of SV40 in pancreatic β-cells ( Fig 2G ) . We observed a significant increase in RCAN1 . 1 and RCAN1 . 4 protein ( Fig 2H ) in islets from the leptin receptor deficient T2D mouse model , db/db ( 12 week old males , db/+ weight = 22 . 5 ± 1 . 1 g , plasma glucose = 8 . 5 ± 0 . 3 mM , db/db weight = 46 . 6 ± 1 . 1 g , plasma glucose = 24 . 1 ± 1 . 4 mM ) . RCAN1 . 1 expression was ~10 times that of RCAN1 . 4 in db/db islets ( Fig 2I ) . Prolonged exposure to high glucose also induced RCAN1 expression in human islets ( Fig 3A ) , mouse islets ( Fig 3B ) and MIN6 cells ( Fig 3C ) . This induction was reversed when Ca2+ entry was reduced with the L-type Ca2+ channel blocker nifedipine ( Fig 3D and 3E ) or by inhibiting oxidative stress with the antioxidant N-acetylcysteine ( NAC ) ( Fig 3F and 3G ) . Thus , increased Ca2+ and oxidative stress both induced β-cell RCAN1 expression under hyperglycaemic conditions and RCAN1 . 1 is the major RCAN1 isoform in human and mouse β-cells . We measured in vivo GSIS in mice overexpressing RCAN1 . 1 ( henceforth referred to as RCAN1ox ) as reduced GSIS is a hallmark in T2D individuals [14 , 15 , 20] , and as RCAN1 . 1 is the major β-cell RCAN1 isoform with the greatest increase in db/db islets . Basal plasma insulin levels were not different ( Fig 4A ) but in vivo GSIS is reduced in RCAN1ox mice ( Fig 4B and 4C ) . This is similar to findings demonstrating that transient overexpression of RCAN1 in a β-cell line reduced in vitro GSIS [16] . This reduced in vivo GSIS in RCAN1ox mice is not due to increased insulin sensitivity , as these mice demonstrated no change in insulin tolerance ( Fig 4D and 4E ) or in plasma glucagon levels ( Fig 4F ) . We then tested whether increasing RCAN1 affects β-cell mitochondrial function , as the focus of this study is to identify potential regulators of mitochondrial dysfunction in T2D β-cells . Islets from RCAN1ox mice have double the RCAN1 . 1 gene expression and a 2 . 5 fold increase in protein level [14] , similar to the increase in RCAN1 . 1 protein expression that we report here in db/db islets . Islet respiration ( oxygen consumption rate ) was assessed in RCAN1ox and wild-type ( WT ) islets ( Fig 5A ) . At both 3mM and 20mM glucose RCAN1ox islets had a significantly lower basal oxygen consumption rate ( 3mM WT 2 . 82 ± 0 . 54 vs RCAN1ox 0 . 64 ± 0 . 30 pmoles/min/μg protein and 20mM WT 4 . 11 ± 0 . 76 vs RCAN1ox 1 . 89 ± 0 . 49 pmoles /min/μg protein , Fig 5B ) . Uncoupled respiration due to proton ( H+ ) leak ( measured in the presence of oligomycin ) was also significantly lower in RCAN1ox islets ( WT 1 . 28 ± 0 . 34 vs RCAN1ox 0 . 48 ± 0 . 26 pmoles/min/μg protein , S3A Fig ) . Basal mitochondrial respiration was significantly decreased and respiration due to ATP turnover showed a trend towards reduction in RCAN1ox islets ( S3B and S3C Fig ) demonstrating a consistent respiratory defect with RCAN1 overexpression across multiple aspects of mitochondrial function . Unsurprisingly , ATP levels were reduced in RCAN1ox islets ( Fig 5C ) . To understand whether these changes are due to alterations upstream of the mitochondrial electron transport chain or could be directly attributed to mitochondrial dysfunction , we stimulated complex II of the electron transport chain directly with methyl succinate . This resulted in significant insulin secretion from WT islets but far less in RCAN1ox islets ( Fig 5D ) , indicating a respiratory defect within the mitochondria downstream of complex I . Since RCAN1 interacts with the mitochondrial ATP translocator , ANT , in Drosophila neurons [21] , we used the ANT inhibitor carboxyatractyloside ( CAT ) to test whether the effect of RCAN1 on mitochondrial function in β-cells is mediated through changes in ANT function . CAT significantly reduced GSIS in WT islets , but had no effect in RCAN1ox islets ( Fig 5E ) . RCAN1 does not have a classical N-terminal mitochondrial localisation signal [22] and immunocytochemical co-localisation studies further demonstrate that RCAN1 does not localise to mitochondria in MIN6 cells ( Fig 5F–5H ) . While some overlap was observed due to the nature of co-localisation studies , we believe the data does not support a mitochondrial localisation of RCAN1 . No fluorescence was detected when the primary antibody was replaced by either saline or non-immune rabbit serum , and used with the secondary antibody as negative controls . To further understand how mitochondrial output is diminished in RCAN1ox β-cells , we first measured the protein expression of various mitochondrial markers . No changes in the expression of TOM20 ( marker of total mitochondrial protein ) , NDUFA9 ( complex I ) , SDHA ( complex II ) , or CORE1 ( complex III ) were observed , and a lack of OPA1 cleavage infers mitochondrial fission was unaltered ( Fig 6A ) . Electron microscopy analysis of mitochondrial area in β-cells further demonstrated no change in the absolute ( Fig 6B ) or relative ( Fig 6C ) area of mitochondria in RCAN1ox β-cells . We observed the same outcome when measuring mitochondrial volume using the mitochondrial marker tetramethylrhodamine methyl ester ( TMRM ) in live cells ( Fig 6D ) . We observe increased TMRM fluorescence in RCAN1ox β-cells at rest , indicative of mitochondrial hyperpolarisation ( Fig 6E ) . Furthermore , while a normal mitochondrial hyperpolarisation in response to glucose [23] was observed in WT cells , no such response occurred in RCAN1ox cells ( Fig 6E ) . Thus , the mitochondrial electrochemical gradient is altered in RCAN1ox β-cells and does not change in response to high glucose . Having established that mitochondrial function and ATP output are compromised in RCAN1ox β-cells , we next tested whether this is functionally relevant for specific ATP-dependent components of the GSIS pathway . Mitochondria are central to ATP production in response to high glucose in β-cells . This triggers closure of plasma membrane KATP channels , membrane depolarisation , Ca2+ entry and insulin secretion . Perforated patch whole cell voltage clamp recordings from single β-cells were used to measure K+ currents in WT ( Fig 7A ) and RCAN1ox ( Fig 7B ) β-cells . This established that the average current-voltage relationships were identical in these cells ( Fig 7C ) . In the presence of 20mM glucose , the K+ current amplitude produced by this same voltage pulse protocol was reduced in WT β-cells and caused a rightward shift in the current-voltage relationship near the reversal potential , indicative of membrane depolarisation ( S4A Fig ) . However such a change was diminished in RCAN1ox β-cells ( S4B Fig ) . To measure membrane potential directly , current clamp recordings , still obtained in the perforated patch clamp configuration to maintain the endogenous intracellular ATP concentration , were undertaken . These demonstrated that WT ( Fig 7D ) and RCAN1ox ( Fig 7E ) β-cells were both depolarised and fire action potentials in response to high glucose and had similar resting membrane potentials ( WT -67 . 4 ± 1 . 4 mV , n = 7 , RCAN1ox -65 . 3 ± 3 . 4 mV , n = 10 ) . However , the amount of glucose-induced membrane depolarisation was less in RCAN1ox β-cells ( p < 0 . 01 , Fig 7F ) . Addition of the KATP channel antagonist , tolbutamide , caused membrane depolarisation in WT ( Fig 7G ) and RCAN1ox β-cells ( Fig 7H ) to the same extent ( Fig 7I ) . Similarly in voltage clamp mode , tolbutamide caused equal changes in K+ current amplitude and the estimated reversal potential in both WT ( S4C Fig ) and RCAN1ox ( S4D Fig ) β-cells . Thus , the decreased ATP production in RCAN1ox β-cells reduced glucose-induced closure of plasma membrane KATP channels to limit glucose-induced membrane depolarization . As ATP is also required for vesicle transport in β-cells [24] , we utilized membrane capacitance measurements to test if RCAN1 overexpression negatively affects insulin exocytosis . We initially used the perforated patch clamp mode to maintain endogenous intracellular ATP concentrations . A series of ten depolarizing pulses resulted in an increase in membrane capacitance in WT ( Fig 8A ) and RCAN1ox β-cells due to insulin exocytosis but this secretion was not sustained in RCAN1ox β-cells ( Fig 8B ) . This was not due to altered Ca2+ current size ( Fig 8C ) . Given ATP production is low in RCAN1ox β-cells; we then punctured the cell membrane using the whole cell patch clamp approach in order to introduce an equal amount of ATP ( 3mM ) into the β-cell cytosol in both groups via the pipette solution . Under these conditions we observed robust secretion in WT and RCAN1ox β-cells ( Fig 8D ) that is similar in both groups ( Fig 8E ) . Ca2+ current size is the same in these groups ( Fig 8F ) . Thus , a lack of ATP in RCAN1ox β-cells has negative effects directly on vesicle fusion .
In this study we attempted to identify genes that regulate mitochondrial function in β-cells and underlie mitochondrial dysfunction and reduced GSIS in T2D β-cells . This approach produced a single candidate , RCAN1 , which is overexpressed in human T2D islets . We validated our screening approach by establishing that higher RCAN1 levels caused mitochondrial dysfunction resulting in low ATP levels in β-cells . This reduced ATP availability has direct functional consequences on glucose-stimulated membrane depolarisation as well as depolarisation-induced insulin exocytosis . Further investigation revealed that increased RCAN1 hyperpolarises the mitochondrial membrane and blunts the respiratory output of β-cell mitochondria . Thus , this approach enabled the identification of a single candidate gene , from 4 , 920 genes with altered expression in T2D islets [8] , that is capable of causing mitochondrial dysfunction and reduced insulin secretion . T2D is a complex multi-systemic metabolic disorder with β-cell dysfunction at its core . Islets isolated from T2D patients have lower ATP levels [4] and elevated ROS accumulation that correlates with the impairment of GSIS [25] which is reversed in human T2D islets pre-treated with anti-oxidants [26] . Such data highlights the central role of oxidative stress and impaired mitochondrial function in T2D β-cell dysfunction . Islets from DS individuals display fragmented mitochondria and reduced insulin secretion [9] and similar changes are seen in human T2D β-cells . While the mechanisms underlying these mitochondrial changes in DS β-cells remain poorly defined , DS individuals also have mitochondrial dysfunction and increased oxidative stress in a number of other cell types [9 , 27 , 28] . The early onset of mitochondrial dysfunction in fetal DS β-cells is indicative of genetic mechanisms driving this phenotype . Our observation that the trisomy 21 mouse models , Ts65Dn and Ts16 , are hyperglycaemic , and that Ts65Dn mice have impaired glucose tolerance , indicates that some mouse chromosome 16 genes regulate blood glucose levels and potentially β-cell function . This hyperglycemia may well be due to reduced β-cell output , similar to that observed in human DS islets [9] . As Tc1 and Ts1Rhr mice are not hyperglycaemic , and Tc1 mice have normal glucose tolerance , we were able to refine the list of candidate genes to 38 . Of these , five were overexpressed in T2D islets; EVA1C , OLIG2 , IFNAR1 , RCAN1 and RUNX1 . RCAN1 was of particular interest when focusing on mitochondrial function and insulin secretion . We note that we have not confirmed that RCAN1 expression is increased in human DS islets or in islets from mouse models of trisomy 21 . However given that neuronal expression of RCAN1 is almost double that of normal [29] , we assume that this is similar in mouse models triplicating RCAN1 such as Ts65Dn and Tc1 . Given that the altered mitochondrial morphology observed in human DS β-cells [9] , is not seen in our β-cells overexpressing RCAN1 , chromosome 21 genes other than RCAN1 may also cause some of the pathological changes in DS β-cells . We must emphasize here that the DS screening approach was not used to provide a guide on DS genes that cause hyperglycemia or β-cell dysfunction , but rather as a tool to help identify genes important in β-cell dysfunction in T2D from a study that had yielded almost 5000 gene expression changes . The relationship between DS and diabetes is both poorly studied and highly complex . While the incidence of T1D is increased in the DS population [30 , 31] , few publications exist regarding the incidence of T2D . One such study indicates an increased incidence of T2D in DS individuals [32] and high fasting blood glucose and insulin resistance are more prevalent in the DS population [33 , 34] . However the increased prevalence of obesity in this population needs to be considered . The diagnosis of young DS individuals with T1D is not always based on an increased incidence of β-cell autoantibodies [31] , and clarification in a larger study will be needed to clearly identify whether these cases are truly autoimmune T1D or a genetically-caused early onset form of diabetes associated with chromosome 21 genes being overexpressed . It is also worth noting that fine mapping of a region on chromosome 21 that shows linkage to T1D contains RCAN1 [35] . Given that increased hypoinsulinemia has been long reported in the DS population [36] and that β-cell dysfunction and low insulin release is seen even in fetal DS islets [9] , DS individuals may have the capacity to cope with this through other genetically induced changes that increase , for example , peripheral insulin sensitivity . The hypoglycaemia observed in the Tc1 mouse model indicates there may be some chromosome 21 genes that would provide beneficial effects on glycemic control in diabetes . This idea is reinforced in the human insulin-dependent DS population who require a lower dose of insulin compared with age-matched insulin-dependent diabetics [37] . Further study into whether some chromosome 21 genes could be responsible for improved insulin sensitivity or reduced insulin secretion are worthy of future investigation . RCAN1 is a stress-induced protein known to regulate mitochondrial function in neurons [14 , 21 , 38] . RCAN1 overexpression increases mitochondrial ROS in neurons and pancreatic islets , and reduces GSIS [14 , 15] . As such , it was our lead candidate from the results of our screening approach . The DNA methylation data in human T2D islets adds key mechanistic insight to explain how RCAN1 expression is increased in T2D β-cells . Reduced RCAN1 methylation was found to correlate with increased RCAN1 expression at three different sites , and it was only at these sites that the methylation status was reduced in T2D islets . What drives these methylation changes in β-cell RCAN1 during T2D is an important question worth addressing in the future . Our Western blot data from db/db mouse islets illustrates that RCAN1 protein expression increases in T2D islets , and that RCAN1 . 1 is 10 times more highly expressed than RCAN1 . 4 in db/db islets . Such data is a good illustration that gene changes may not reflect protein expression given the 50% increase in RCAN1 gene expression in T2D islets vs . 3 fold increased RCAN1 . 1 protein expression in db/db islets . It also highlights the fact that genome-wide expression screens may miss important targets that have small gene , but large protein , expression changes . As such , approaches such as GWAS , as well as our DS-based approach , will be limited in their scope in this respect . RCAN1 . 1 and RCAN1 . 4 expression were also elevated in response to glucose in MIN6 cells . This was driven by Ca2+ and oxidative stress , consistent with the mechanism of RCAN1 induction in neurons [39] . Thus , we demonstrate that RCAN1 expression is linked to hyperglycaemia in DS mice , that it correlates in islets with a worsening metabolic profile in obese mice , that it is increased in human T2D islets , that RCAN1 methylation at three methylation sites correlates with RCAN1 expression in human islets and that methylation status at these sites is reduced in T2D islets . This is further consolidated by protein expression data demonstrating not only that RCAN1 . 1 and RCAN1 . 4 increases in db/db islets but that chronic high glucose increases expression of both RCAN1 isoforms in islets through a mechanism that involves increased Ca2+ and oxidative stress . Ca2+ entry is thought to be increased in T2D β-cells due to chronic high glucose levels and oxidative stress is linked to the degree of GSIS impairment in human T2D islets . This data strongly supports the concept that RCAN1 expression increases in T2D β-cells and that this is driven my cell stresses that are relevant to the pathogenesis of β-cell failure in T2D . The effects on β-cell function that we attribute to RCAN1 overexpression in our transgenic mice are consolidated by the findings of others using independent models . This includes the finding that transient overexpression of RCAN1 reduces GSIS in a β-cell line [16] and significantly , that β-cell number and islet size are reduced , as reported in our RCAN1ox line [15] , in mice overexpressing RCAN1 created independently of our study [40] . Thus is appears unlikely that off-target effects related to transgene insertion in our RCAN1ox mice drive the phenotypes we observe here . We demonstrate that increased RCAN1 inhibits ATP production and mitochondrial function . The lack of succinate-induced insulin secretion clearly identifies defective mitochondrial respiration in RCAN1ox β-cells , but exactly what drives this is unclear . ANT exports ATP out of the mitochondrial matrix while importing ADP . Disruption of ANT reduces cellular ATP levels and inhibits the electron transport chain , resulting in reduced oxygen consumption rates , such as we observe in RCAN1ox islets . In one respect , our data is consistent with findings in Drosophila neurons that RCAN1 interacts with and blocks ANT activity when overexpressed and reduces cytosolic ATP levels [21] . Our finding that mitochondria are hyperpolarized in RCAN1ox β-cells could be explained by reduced ANT output because a decrease in cellular ATP levels , resulting in increased substrate entry into the electron transport chain . However , if ATP is trapped in the mitochondria due to defective nucleotide transport , ATP synthase , and therefore respiration , will be inhibited . As electrons continue to enter the electron transport chain , protons will continue to be pumped into the inner membrane space and membrane potential will increase as we observed in RCAN1ox β-cells in 3 mM glucose . This situation also occurs in our WT β-cells in the presence of increased glucose , except that as ATP is exported from the mitochondria in these cells , respiration increases . However , as we do not observe a clear mitochondrial localisation of RCAN1 in β-cells a direct interaction between RCAN1 and ANT seems unlikely . We suggest alternatively that inhibiting ANT activity in RCAN1ox β-cells did not reduce insulin secretion because the mitochondria is already hyperpolarised and added glucose cannot drive further respiration in RCAN1ox β-cells . We observe RCAN1 MIN6 cell localisation in both the cytoplasm and nucleus . This is somewhat in contrast to similar experiments showing little β-cell nuclear localisation [15] . RCAN1 is normally expressed in both the nucleus and cytoplasm , with the degree of nuclear localisation being cell-type dependent [41] . RCAN1 nuclear localisation is significantly reduced in the presence of activated calcineurin [42] . As calcineurin activity is regulated acutely by calcium , differences in RCAN1 localisation could readily be caused by small differences in experimental conditions such as culture media , temperature , buffer capacity of solutions and any stress placed upon the cells . This should be kept in mind when comparing cytosolic and nuclear RCAN1 localisation . No evidence suggests that these factors affect mitochondrial localisation of RCAN1 , but it is worth considering given that this has been reported in Drosophila neurons [21] . The mitochondrial respiratory defects we observe in RCAN1ox β-cells are not associated with altered mitochondrial morphology . The expression of TOM20 , a marker of total mitochondrial protein , is unchanged and electron microscopy analysis and mitochondrial staining indicate that mitochondrial mass is unchanged in β-cells overexpressing RCAN1 . The reduced oxygen consumption rate we observe at baseline in RCAN1ox islets is therefore not due to reduced mitochondrial mass . Some reduction in mitochondrial size is reported in RCAN1ox β-cells but this is far less than that reported in neurons [14 , 21 , 38] . Whether such differences are strain or cell type dependent is unknown but our data shows that overt morphological changes are not required for RCAN1 to cause mitochondrial dysfunction . Mitochondrial and cytoplasmic calcineurin activity increases in response to changes in cytosolic Ca2+ in β-cells [43] . While the functional roles of altered calcineurin activity in different intracellular locations is not clear , increased RCAN1 would be expected to suppress at least some of them , potentially including mitochondrial oxidative phosphorylation . As RCAN1 is not present in β-cell mitochondria , other possibilities such as changes in calcineurin-dependent gene expression will need to be investigated . Indeed , in skeletal muscle , calcineurin can regulate the expression of some mitochondrial genes [44] . Whether such a mechanism exists in β-cells remains , to our knowledge , unknown . We hypothesise that the expression of unidentified mitochondrial proteins are altered in RCAN1ox β-cells , resulting in reduced nucleotide transport and hyperpolarisation of the mitochondrial membrane , to reduce glucose-stimulated insulin secretion . Our patch clamp studies provide a functional link between RCAN1-induced mitochondrial dysfunction and reduced insulin secretion . The fact that tolbutamide had the same effect in WT and RCAN1ox β-cells , but that high glucose had a reduced effect on membrane depolarisation in RCAN1ox cells is clear evidence that glucose-induced KATP channel closure is hindered in RCAN1ox β-cells . Biphasic glucose stimulated insulin secretion is reduced in T2D islets [25 , 45] and we demonstrate here the same phenotype in RCAN1ox islets . Unaltered insulin sensitivity and glucagon release in RCAN1ox mice provides further support that the reduced in vivo GSIS we observe in RCAN1ox mice is due to β-cell failure . Glucose metabolism raises the cellular ATP/ADP ratio in β-cells to close KATP channels , depolarise the plasma membrane and open voltage-gated Ca2+ channels to trigger insulin granule exocytosis . Whether membrane depolarisation is reduced in T2D β-cells as we observe in RCAN1ox β-cells is unknown , but might be assumed given the reduced glucose oxidation [25] and ATP production [4] reported in human T2D islets . The use of whole cell capacitance to provide 3mM ATP to these β-cells demonstrates that a lack of ATP drives the low exocytosis phenotype in RCAN1ox β-cells . The fact that we were able to rescue this exocytosis phenotype with a single molecule ( i . e . ; ATP ) is a very strong indicator that low ATP levels are responsible for the secretory defect observed in RCAN1ox β-cells . The earliest phase of exocytosis represents release of docked insulin granules , while the slower second phase requires granule recruitment from the reserve pool in an ATP-dependent manner [24] . Our capacitance data shows the readily releasable vesicle pool is not affected in RCAN1ox β-cells , which is unsurprising given insulin granule localisation is unchanged in RCAN1ox β-cells [15] . It appears that RCAN1ox β-cells produce enough ATP under basal conditions for vesicle docking and priming to occur , and defects in exocytosis are only observed under stimulated conditions where rapid ATP generation is required . Our data also demonstrates that perforated patch clamp should be used in such experiments so as to avoid artefacts produced by washout of cytoplasmic second messengers . This genetic screening approach we have developed combining different trisomy 21 mouse models with whole genome data from human T2D islets has identified a potential regulator of β-cell mitochondrial dysfunction in T2D . This work goes well beyond previous findings related to the function of RCAN1 by identifying it , through an unbiased multi-centre screening approach , as a lead candidate in the control of whole body glucose metabolism and in the β-cell dysfunction which is central in humans to the transition from insulin resistance to T2D . Furthermore , our data demonstrating that RCAN1 methylation is reduced at multiple sites in human T2D β-cells and that methylation status at these sites correlates with RCAN1 expression is further validation of our screening approach and provides a mechanistic pathway that clearly explains how RCAN1 expression changes in T2D β-cells . Similarly , such an approach could be applied to other human health disorders with phenotypes shared with DS individuals . Given the large number of gene changes observed in complex human diseases like T2D , such an approach could aid in deciphering the complex data sets now being obtained with ever improving genetic search tools . An example of this provided by this present study is insulin resistance , as the hypoglycaemic status of Tc1 mice indicates that chromosome 21 genes unique to this DS mouse model may improve some aspects of insulin sensitivity . This may have clinical applications for T2D research also , given the importance of insulin resistance in the pathogenesis of this disease .
3–5 month old male mice were used in this study with approval from the individual institutional animal welfare committees at each site . Dp ( 16Cbr1-ORF9 ) 1Rhr ( called Ts1Rhr ) [46] , Dp ( 16 ) 1Yey ( called Dp16 ) [47] and Ts65Dn [48] mice were maintained on a B6EiC3Sn/J background . Tc1 mice ( called Tc1TybEmcf ) [49] were bred by crossing female Tc1 mice to male ( C57BL/6JNimr x 129S8/Nimr ) F1 mice . Mice homozygous for the diabetes spontaneous mutation ( Leprdb ) , named here as db/db mice , were maintained on a C57BL/KsJ background . RCAN1ox mice are transgenic C57BL/6xCBA mice stably overexpressing human RCAN1 . 1 [20] . While multiple RCAN1ox founder lines were originally generated , only a single line was used for this study . We observed no overt differences between the three RCAN1ox lines initially created , but these investigations were unrelated to glucose metabolism . Use of human islets was approved by the ethics committee at Lund University and University of Adelaide . In Adelaide , human islets were obtained from heart beating organ donors through the Australian Islet Consortium ( RAH 100205b and St Vincent’s Hospital Melbourne ( SVH HREC-D 103/05 ) . Consent for donated human pancreata for research in all cases was obtained through Donate Life Australia . In Sweden , informed consent for organ donation for medical research was obtained from pancreatic donors or their relatives in accordance with the approval by the regional ethics committees ( 173/2007 ) in Lund and Uppsala , Sweden . Use of mice was approved by the Flinders University , University of California Irvine , Garvan Institute , MRC Harwell and University of California San Diego Animal Ethics Committees . Mice were euthanized via overdose inhalation of isoflurane . All animal research at Flinders University was approved by the Flinders University Animal Welfare Committee ( 797–11 , 620/07 ) following guidelines issued by the National Health and Medical Research Council of Australia . Approval at USCD was provided by the UCSD Institutional Animal Care and Use Committee ( S09315 ) and followed guidelines provided by that body . All animal work at MRC was carried out with the approval of the Ethical Review Board and under Licence from , and following guidelines provided by , the UK Home Office . At the Garvan Institute , procedures were approved by the Garvan Institute/St . Vincent’s Hospital Animal Experimentation Ethics Committee ( 14_21 ) , following guidelines issued by the National Health and Medical Research Council of Australia . At UCI , animal experiments involving mice were approved by the University of California Irvine ( UCI ) institutional animal care and use committee ( IACUC ) ( approval number: 2008–2779 ) following guideline provided by that body . Blood was collected from mice fasted for 6 hours . For Ts65Dn , Dp16 and Ts1Rhr mice , blood was obtained from tail tips and glucose measured using a One-Touch Ultra Blood Glucose Monitoring System ( LifeScan , Milpitas , CA , USA ) or Contour Blood Glucose Monitoring System ( Bayer HealthCare , Mishawaka , IN , USA ) . For Tc1 mice , blood was collected from the retro-orbital sinus and measured using an AU680 clinical chemistry analyser ( Beckman Coulter , Brea CA , USA ) . After 12–16 hour overnight fasting , glucose tolerance was measured by administering intra-peritoneal glucose ( 2 . 0 g/kg ) . Islets from 89 cadaver donors ( 77 control and 12 T2D ) of European ancestry were provided by the Nordic Islet Transplantation Programme and processed as described [8] . Pancreases were removed from heart beating deceased donors and disaggregated by infusing the ducts with cold collagenase ( NB1 GMP grade from SERVA , Heidelberg , Germany ) . Dissociated islet and acinar tissue were separated on a continuous Biocoll ( Biochrom AG , Berlin ) density gradient ( polysucrose 400 and amidotrizoic acid ) on a refrigerated apheresis system ( Model 2991 , COBE Laboratories , Lakewood , CO . ) Pancreatic islets isolated from age matched , male C57BL/6 × CBA wild type ( WT ) and transgenic mice stably overexpressing human RCAN1 . 1 ( RCAN1ox ) [20] were used in all experiments . Experiments were approved by the Flinders University Animal Welfare and Institutional Biosafety Committees . Mice were killed by an anaesthetic overdose of isoflurane and islets isolated as previously described [15] . MIN6 cells , an insulinoma cell line derived from a transgenic mouse expressing the large T-antigen of SV40 in pancreatic β-cells ( passage number 37–39 ) , were grown in Dulbecco’s Modified Eagles Medium ( DMEM ) media ( 11 . 1 mM glucose , 15% fetal calf serum ) at 37°C in 5% CO2 . Islet RNA was extracted using QIAshredder columns and an RNAeasy minikit ( Qiagen ) . All RNA samples were subjected to a DNAse treatment to remove any genomic DNA ( TURBO DNA-free kit , Life Technologies ) prior to reverse transcription ( Omniscript , Qiagen ) . Quantitative real-time PCR analysis was carried out in triplicate utilising SyBR-Green ( Qiagen ) . All results were normalised to β-actin expression which was used as a house-keeping gene . Mean normalised expression values and fold gene expression were calculated using Qgene Module software . The respiratory responses of islets isolated from wild type and RCAN1ox mice were assessed using the Seahorse XF24 Flux Analyser ( Seahorse Bioscience ) . Islets were washed in DMEM ( 3mM glucose , 1mM pyruvate , 1mM glutamate , 1% fetal bovine serum ) and approximately 50 islets were added to each well of a 24-well XF24 islet capture microplate . Islets were incubated at 37°C in a non-CO2 incubator for 1hr prior to bioenergetics assessment . Six basal oxygen consumption rate ( OCR ) measurements were performed using the Seahorse analyser and measurements were repeated following injection of 20mM glucose , 5μM oligomycin , and 1μM Antimycin A . Respiratory parameters of mitochondrial function were calculated as described previously [50] . Non-mitochondrial respiration was subtracted from all mitochondrial respiration parameters . Following the assay , protein content of each well was assessed by standard BCA assay ( Thermo Fisher ) . Mitochondrial respiration was normalised to total islet protein content . 25 μg of islet or mitochondrial protein lysates were separated on a Criterion-TGX stain-free gel ( Bio-Rad ) . Immunoreactive proteins were visualised on a Fuji-Film LAS4000 and Gel-Doc Ez-Imager ( Bio-Rad ) . Primary antibodies; anti-RCAN1 ( 1:200 , Sigma Aldrich ) , anti-TOM20 ( 1:1000 , Jackson Laboratories ) , anti-β-actin ( 1:200 , Sigma Aldrich ) , anti-NDUFA9 ( 1:1000 , Sigma Aldrich ) , anti-SDHA ( 1:2000 , Sigma Aldrich ) , anti-CORE1 ( 1:1200 , Sigma Aldrich ) and anti-Opa1 ( 1:1500 , Sigma Aldrich ) . Secondary antibodies; donkey anti-rabbit horse-radish peroxidase ( HRP ) ( 1:100 , Life Technologies ) and donkey anti-mouse HRP ( 1:100 , Life Technologies ) . Whole-cell patch clamp recording was performed using an EPC‐10 patch clamp amplifier and PatchMaster software ( HEKA Electronik GmbH ) . Patch pipettes were pulled from borosilicate glass and fire polished , with resistance of 3–5 MΩ . Patch clamping was performed in the perforated patch configuration for capacitance measurements , with internal solution containing ( mM ) : 140 CsCl , 2 MgCl2 , 5 EGTA , 0 . 5 CaCl2 and 10 Hepes , adjusted to pH 7 . 2 , and with 240 μg ml−1 amphotericin B . For whole cell capacitance measurements , amphotericin was removed and 3mM ATP added . External solution contained ( mM ) : 140 NaCl , 5 Hepes , 2 MgCl2 and 10 CaCl2 and , adjusted to pH 7 . 4 with NaOH . Capacitance measurements utilized the Lock-in module of the PatchMaster software , with capacitance change measured in response to 10 voltage steps to 10mV of 500 ms duration at 1Hz from a resting membrane potential of −80 mV . Internal solution for measurement of K+ currents and membrane potential was ( mM ) : 10 NaCl , 145 KCl , 10 Hepes , 1 MgCl2 , 1 EGTA , adjusted to pH 7 . 2 . External solution was ( mM ) : 140 NaCl , 2 . 8 KCl , 10 Hepes , 1 MgCl2 , 2 CaCl2 adjusted to pH 7 . 4 . Cells were identified on their response to high glucose and/or having a whole cell capacitance over 5pF . Experiments were carried out at 22–24°C . ATP content of groups of 80 islets in the presence of 20 mM glucose was measured using a commercially available bioluminescent ATP quantitation kit ( Sigma Aldrich ) as per the manufactures instructions . ATP content was normalised to total protein content . Insulin secretion assays from isolated islets were carried as previously described [15] . For some experiments , potassium carboxyatractyloside ( 200 μM ) or methyl-succinate ( 10 mM ) were added . Plasma glucagon was measured from mice fasted for 2 hours using an ELISA ( Crystal Chem , USA ) . The in vivo GSIS measurements were undertaken on mice fasted for 2 hours and 2mg/g body weight of glucose ( PharmaLab , Australia ) was injected ( i . p . ) into mice and blood glucose measured at various interval from 0 to 60 minutes via a tail bleed . Insulin was quantified using an Ultra Sensitive Mouse Insulin ELISA Kit ( Crystal Chem , USA ) as per the manufacturer’s instructions for a low range assay . Absorbance was measured at 450 nm and 620 nm using a BIOMECK-3000 micro-plate reader ( Beckman-Coulter , USA ) and MultiMode detection software . Insulin tolerance tests were carried on mice fasted for 1 hour and 0 . 75 units/kg body weight insulin ( Novo Nordisk , Australia ) was injected ( i . p . ) into 40 day old mice . Blood glucose was measured via a tail bleed using an ACCU-CHEK Performa glucometer ( Roche Diagnostics , Australia ) . Mitochondrial volume was calculated from electron micrographs obtained as previously described [15] . Total mitochondrial volume per cell was calculated from these images using ImageJ image analysis software ( National Institute of Health , Bethesda , MD , USA ) after subtraction of the nuclear volume . This was calculated as both absolute volume and the volume fraction of the entire β-cell . Relative volume was also calculated from isolated cells loaded for 30 min with tetramethylrhodamine methyl ester ( TMRM , 1μM ) . Images were analysed using the masking function in the Image J digital image analysis software ( National Institute of Health , Bethesda , MD , USA ) . Mitochondrial membrane potential was measured as the mean cell fluorescence of cells loaded with TMRM . Images were captured under identical conditions for all groups and data presented as mean TMRM fluorescence in each group . DNA methylation profiling of human pancreatic islets was performed at the SCIBLU genomics center at Lund University with the Infinium HumanMethylation450 BeadChip ( Illumina , Inc . , San Diego , CA ) . The experimental and bioinformatics analyses have previously been described [18] . In short , DNA from human pancreatic islets was bisulfite converted using the EZ DNA Methylation Kit D5001 ( Zymo Research , Orange , CA ) according to the manufacturer’s instructions . Bisulfite converted DNA was amplified , fragmented and hybridized to the BeadChips following the standard Infinium protocol . T2D islet samples were randomized across the chips and all samples were analyzed on the same machine by the same technician to reduce batch effects . The DNA methylation data were exported from GenomeStudio and Bioconductor and the lumi package were used for further analyses . Individual probes were filtered based on their mean detection P-value and those with a P-value > 0 . 01 were excluded from further analysis . M-values were calculated from β-values using the following equation: M = log2 β-value / ( 1-β-value ) and were then used for further statistical analysis . To identify differences in DNA methylation between T2D and non-diabetic islets a linear regression model was used including batch , gender , BMI , age , islet purity and days of culture as covariates and DNA methylation as the quantitative variable . As the β-value is easier to interpret biologically , M-values were converted to β-values when describing the results and creating the figures . Cells were incubated with MitoTracker Red ( 1μM ) at 37°C for 15 min and then fixed with 4% formaldehyde for 15 min at 22°C . The cells were stained with anti-RCAN1 antibody ( 1:100 ) and FITC conjugated antibody ( 1:100 ) as previously described [51] . The cells were viewed under laser scanning confocal microscope ( Olympus , FV1000-IX81 Japan ) using a 40X oil immersion lens . Multitrack scanning mode was used to record single- and double-labelled cells . Parametrically distributed data were analysed using a Student’s unpaired t test and a Mann-Whitney U test was used to analyse nonparametric data sets . Statistical significance was p < 0 . 05 . All data are shown as mean ± SEM . | Mitochondrial dysfunction and reduced insulin secretion are key features of β-cell dysfunction in Type 2 diabetes ( T2D ) . Down syndrome ( DS ) is a genetic disorder caused by trisomy of chromosome 21 that also displays β-cell mitochondrial dysfunction and reduced insulin secretion in humans . Given these similarities in β-cell dysfunction in T2D and DS , we developed a trisomy 21 screening method to identify genes that may be important in T2D . This approach used different DS mouse models combined with human gene expression data from T2D β-cells . From this we identified a single candidate , Regulator of calcineurin 1 ( RCAN1 ) . High RCAN1 expression occurs in human and mouse T2D islets . Increased RCAN1 expression in mice reduced β-cell mitochondrial function and ATP availability , and this has negative implications for multiple ATP-dependent steps in glucose-stimulated insulin secretion . | [
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"bioenergetics"... | 2016 | A Syntenic Cross Species Aneuploidy Genetic Screen Links RCAN1 Expression to β-Cell Mitochondrial Dysfunction in Type 2 Diabetes |
Kaposi sarcoma-associated herpesvirus ( KSHV ) establishes a lifelong latent infection and causes several malignancies in humans . Murine herpesvirus 68 ( MHV-68 ) is a related γ2-herpesvirus frequently used as a model to study the biology of γ-herpesviruses in vivo . The KSHV latency-associated nuclear antigen ( kLANA ) and the MHV68 mLANA ( orf73 ) protein are required for latent viral replication and persistence . Latent episomal KSHV genomes and kLANA form nuclear microdomains , termed ‘LANA speckles’ , which also contain cellular chromatin proteins , including BRD2 and BRD4 , members of the BRD/BET family of chromatin modulators . We solved the X-ray crystal structure of the C-terminal DNA binding domains ( CTD ) of kLANA and MHV-68 mLANA . While these structures share the overall fold with the EBNA1 protein of Epstein-Barr virus , they differ substantially in their surface characteristics . Opposite to the DNA binding site , both kLANA and mLANA CTD contain a characteristic lysine-rich positively charged surface patch , which appears to be a unique feature of γ2-herpesviral LANA proteins . Importantly , kLANA and mLANA CTD dimers undergo higher order oligomerization . Using NMR spectroscopy we identified a specific binding site for the ET domains of BRD2/4 on kLANA . Functional studies employing multiple kLANA mutants indicate that the oligomerization of native kLANA CTD dimers , the characteristic basic patch and the ET binding site on the kLANA surface are required for the formation of kLANA ‘nuclear speckles’ and latent replication . Similarly , the basic patch on mLANA contributes to the establishment of MHV-68 latency in spleen cells in vivo . In summary , our data provide a structural basis for the formation of higher order LANA oligomers , which is required for nuclear speckle formation , latent replication and viral persistence .
Kaposi sarcoma-associated herpesvirus ( KSHV , also HHV8 ) , the cause of Kaposi Sarcoma and two lymphoid neoplasms , can persist in a latent form in infected endothelial and B-cells [1] . The key player in the regulation of KSHV latency is the latency-associated nuclear antigen ( LANA ) , which is detected in all KSHV infected cells [2] , [3] and is required for the latent episomal replication of this virus [4] , [5] . The terminal repeat ( TR ) region of KSHV contains 20–40 TR elements , which constitute the latent origin of replication [5] , [6] . The C-terminal domain ( CTD ) of LANA forms dimers , which bind two adjacent DNA sequences , the LANA binding sites ( LBS1 & LBS2 ) in a single TR [4] , [7] . Thus , with respect to DNA binding , LANA resembles other viral origin binding proteins including EBNA-1 of Epstein-Barr virus ( EBV ) [8] and E2 of human papillomavirus ( HPV ) [9] , [10] . LANA also recruits components of the cellular replication machinery to the KSHV latent origin of replication , thereby allowing the virus to replicate its latent episome in the S phase of the cell cycle along with the cellular chromatin [11] . It also regulates transcription of both viral [12] , [13] and cellular genes [14] , [15] , [16] , [17] , [18] . In latently infected cells LANA and the viral episomes are concentrated in characteristic nuclear speckles [3] , [19] , [20] , [21] . To ensure the partitioning of newly synthesized genomes to daughter cells during mitosis LANA tethers KSHV genomes to host mitotic chromosomes by attaching its N-terminal domain to histones H2A/B [22] . In addition , the LANA CTD also binds to mitotic chromosomes and interacts with chromatin-associated proteins [22] , [23] , [24] , [25] including members of the BET ( Bromodomain and ET domain ) family [26] , [27] , [28] . Increasing evidence points to an important role of BET family members in the life cycle of several DNA tumor virus families . BRD4 has been shown to be involved in the tethering of bovine papillomavirus E2 protein and associated episomal viral DNA to host mitotic chromosomes [29] . Moreover the human papillomavirus ( HPV ) E2 proteins act as transcriptional regulators , and this function also involves BRD4 [30] , [31] , [32] . In addition , BRD4 has also been implicated in the latent replication of Merkel cell polyoma virus [33] . For LANA , there is evidence that BRD4 contributes to the recruitment of this protein to chromatin and to its transcriptional properties [26] , [28] while BRD2 may also affect the role of LANA as a transcriptional activator and is able to phosphorylate the LANA CTD [27] . Thus , BET proteins play a pivotal role in the life cycles of multiple dsDNA viruses that cause latent infections in the host . Murine herpesvirus 68 ( MHV-68 ) is a γ2-herpesvirus , which provides an in vivo model for the study of KSHV [34] , [35] . The open reading frame 73 ( orf73 ) of MHV-68 encodes mLANA , which is distantly related to KSHV LANA ( in the following referred to as kLANA ) . Similarly to kLANA , mLANA binds to specific sites within the TR region of the MHV-68 genome , is required for the latent replication and for establishment of latency in splenic B-cells in vivo [36] , [37] , [38] , [39] . The ability of mLANA to act as a transcriptional activator may be linked to its recruitment of BRD2 or BRD4 [40] . Here we report the crystal structures of both kLANA and mLANA CTDs . Both structures display unexpected features . We show that LANA dimers form oligomers and that chromatin associated BET proteins bind two sites on kLANA . Both LANA oligomerization and BET binding contribute to latent replication , nuclear speckle formation and persistence of γ2-herpesvirses , in vivo and in vitro .
The structure of the kLANA fragment comprising residues 1013–1149 was solved by X-ray crystallography at a resolution of 2 . 60 Å ( Figure 1A , B ) , where electron density was observed for residues 1014–1147 . kLANA ( 1013–1149 ) forms dimers that are stabilized by an eight-stranded antiparallel intermolecular β-barrel to which each monomer contributes four β-strands ( β1–β4 ) . In addition to the stabilization by the hydrogen bonding network of the β-barrel , hydrophobic amino acid side chains project into the core and form a tightly packed hydrophobic cluster . The total dimer interface area is 2080 Å2 indicating that LANA is an obligate dimer [41] . Strand β2 contains a β-bulge , which lies directly above a cluster of six water molecules that are observed in the electron density map ( Figure S1A ) . These form a hydrogen bonding network with the amino acid side chains Y1103 and Y1105 that are also part of the dimer interface . The β-barrel is flanked by two α helices , α2 and α3 . The N-terminal helix , α1 , is packed against the two other helices and is not in direct contact with the central β-barrel . We also solved the crystal structure of a C-terminal fragment of MHV-68 LANA , mLANA ( 124–260 ) , at a resolution of 2 . 14 Å , where a detailed structure was obtained for residues 130–260 ( Figures S1B , C ) . It also is a native dimer , and the fold is very well conserved with kLANA ( Figure 1D ) . Moreover , the two LANA structures share the same fold with the 3D structures of the dimeric DNA binding domains of Epstein-Barr virus' EBNA-1 [42] and papillomavirus E2 [43] , [44] ( Figures 1D , E ) , even though the corresponding sequence identities are only 16% and 10% , respectively ( Figures S1D , E ) . However , the structured CTDs of kLANA and mLANA share 28% sequence identity and the root-mean square deviation ( r . m . s . d . ) of the peptide backbone is only 2 . 2 Å . The r . m . s . d . between the CTDs of kLANA and EBNA-1 of 3 . 1 Å is significantly larger ( Figure 1D ) . Between the two LANAs , the regions of highest structural conservation contain the entire β-barrel and the helices α2 and α3 . Several amino acid residues of kLANA have previously been identified to be crucial for specific viral DNA binding [24] , [45] . These are all located on the bottom part of the LANA CTDs as shown in Figures 1C and S1C ( see also Figure S4C ) . For example , the peptide segment PYG at position 1065–1067 of kLANA forms a solvent accessible epitope at the beginning of helix α2 ( Figure 1C ) . As shown previously , substitution of these three residues to alanines abolishes binding of LANA to the LBS sites in the KSHV TR [24] , [45] . We confirmed this finding by electrophoretic mobility shift assay ( EMSA ) using a dsDNA oligonucleotide probe containing LBS1 and LBS2 ( Figure S1F ) . We additionally tested the single point mutants S1086A and S1086E which remove a single OH group , or add a single negative charge in the center of the expected DNA binding site , respectively . As expected , S1086E strongly reduced specific DNA binding and therefore also impaired latent replication , whereas S1086A had no effect on either of these functions ( Figure S1F , G ) . Thus , consistent with the previously reported EBNA-1:DNA complex structure [42] , our findings demonstrate that the ‘bottom’ face of the kLANA CTD mediates the specific binding to LBS1/2 in the TR region of the KSHV genome . During our crystallization trials , we obtained three different crystal forms of the kLANA CTD , all of which contained higher order oligomers ( Figure 2A , Table S1 ) . The monoclinic and orthorhombic crystals of the kLANA CTD contained pentameric rings of dimers , whereas the cubic crystals contained tetrameric rings of dimers . Also mLANA CTD was observed to self-associate laterally where the dimers were arranged as linear chains . In all structures the oligomerization interfaces are formed by helices α1 and α3 ( Figure 2B ) , and the interface comprises an area of approx . 500 Å2 . In kLANA , the interface is mostly hydrophobic , whereas it has a more hydrophilic character in mLANA . While it was previously suggested that LANA might form native higher order oligomers [7] , no equivalent intermolecular contacts were observed in any of the previously described crystal structures of EBNA-1 [42] . We thus explored if the observed LANA oligomerization interfaces are functionally important and also mediate LANA self-association in vivo . We first determined the oligomerization state of recombinant kLANA ( 1013–1149 ) and mLANA ( 124–260 ) in solution . Separation of LANA CTD species by asymmetric field flow fractionation and multi-angle static light scattering showed that the purified CTDs exist mostly as dimers of 31–32 kDa in solution ( Figure 2C ) . No monomers were observed . In order to investigate the potential existence of oligomers of LANA dimers under more physiological conditions , recombinant , immobilized GST-fused kLANA ( 934–1162 ) was incubated with extracts of eukaryotic cells containing transfected full-length ( FL ) kLANA ( 1–1162 ) . The interaction of the two LANA proteins , indicative of self-association , could readily be detected for wt kLANA . The substitution M1117D reduced and the substitution A1121E abolished kLANA oligomerization ( Figure 2D ) . While LBS binding was comparable to wt kLANA ( Figure 2E ) , all lateral association mutants proved to be defective in their ability to replicate a plasmid containing four TR elements ( Figure 2F ) . Notably , the lateral self-association of kLANA dimers appears to be independent of specific DNA binding , since kLANA CTD mutants defective in DNA binding are capable of self-association ( Figure S1H ) . Thus , self-association of kLANA dimers via intermolecular side chain contacts between helices α1 and α3 is a prerequisite for the latent replication . We and others have previously shown that the ET domains of BRD2 and of BRD4 interact with kLANA and mLANA [26] , [27] , [28] , [40] . In order to determine the specific interaction sites in the kLANA CTD and the ET domains of BRD2 and BRD4 , we performed chemical shift perturbation experiments by nuclear magnetic resonance ( NMR ) spectroscopy . [2H , 13C , 15N]-labeled kLANA ( 1013–1149 ) yielded a well dispersed [1H , 15N]-TROSY spectrum that is characteristic of a folded globular protein ( Figure 3A ) . When we added unlabeled BRD4 ET ( 600–680 ) to [2H , 13C , 15N]-labeled kLANA ( 1013–1149 ) , only some of the kLANA resonances shifted significantly in an ET domain concentration-dependent manner ( Figure 3A ) . The detailed quantification of the chemical shift perturbations ( Figure 3B ) revealed the kLANA peptide segment 1125–1129 at the C-terminal end of helix α3 to be most affected , and there were no significant alternative epitopes identified ( Figure 3C , right ) . Thus , BRD4 ET ( 600–680 ) binds to a single site on the kLANA CTD surface . In order to identify the binding site for the kLANA CTD on the ET domains of BRD2/4 , we performed the complementary experiment . [1H , 15N]-TROSY spectra of either [1H , 15N]-labeled BRD2 ET ( 632–713 ) or BRD4 ET ( 600–680 ) were recorded in the absence and in the presence of unlabeled kLANA ( 996–1153 ) ( Figures 3D , E ) . The ET:kLANA interaction strongly depends on charge , which is evident from the ionic strength dependent chemical shift perturbations ( Figure 3E ) . The NMR line-broadening follows the same trend for all observed peaks ( Figure 3D ) , which suggests an overall increasing particle size upon strong ET:kLANA association . The most affected backbone amide groups in the BRD4 ET domain comprise R616 , S619 and E653–E657 ( Figure 3E , top ) . The interaction with BRD2 ET ( 632–713 ) was observed to be virtually identical and to affect the corresponding amino acids R648 , S651 and E685–E689 ( Figure 3E , bottom ) . When mapped onto the surface of the globular ET domain [46] , all of these affected amino acids are contiguous and form a single epitope ( Figure 3C , left ) . Thus , the kLANA CTD binds at a single site on surfaces of BRD2/4 ET domains . In order to confirm the binding site for kLANA on the ET domain we generated mutations in the ET domain of FL GFP-BRD2 and tested them in co-immunoprecipitation experiments with FL wt kLANA ( Figure 4A ) . The alanine substitution of any one of the negatively charged amino acids contained in the peptide segment BRD2-ET ( 682–687 ) resulted in the complete loss of kLANA binding ( Figure 4A ) . Consistent with our NMR data showing ionic strength-dependence of kLANA:ET binding , this result confirms the importance of electrostatic forces in this interaction . The F688Y substitution also abolished binding to kLANA . The substitution of S651 to any larger amino acid severely reduced the interaction with kLANA presumably by steric effects that appear to dominate there . Only the R648A and E689A substitutions appeared not to affect kLANA binding . Thus , most amino acid substitutions in the vicinity of the kLANA binding epitope of BRD2 ET reduced or abolished binding , confirming the interaction site as identified by NMR . We also generated a panel of mutants of FL kLANA and tested them in a co-immunoprecipitation assay with GFP-tagged BRD2 and BRD4 ( Figure 4B ) . The kLANA R1119M substitution impaired binding of the ET domains of both BET proteins . R1119 forms a positive charge at the bottom of a cleft , which is occupied by anions in the kLANA crystals ( Figure S2B ) . The substitution at this position might thus abolish anion binding , rearrange the adjacent peptide segment 1125–1129 and reduce ET binding . The substitutions P1127R had no significant effect on ET binding , while the mutations H1126E and to a lesser degree L1128D , enhanced BET protein binding . The results were similar for BRD2 and BRD4 suggesting that the mode of interaction is virtually identical for both proteins . We next compared the binding of these kLANA mutants to FL BRD2 , the BRD2 ET domain alone ( ET: aa640-719 ) or the entire C-terminal domain of BRD2 ( CT: aa640-801 ) . We found that the binding of the BRD2-ET to LANA was much more susceptible to the LANA substitutions H1126E , L1128D , R1119M then binding of the FL BRD2 or the BRD2-CT ( Figure S2B ) . This result indicates that , while the ET domain binds to the kLANA region defined by aa 1125–1129 , an additional contact point may exist in the BRD2 C-terminal domain or FL BRD2 ( see also below ) . To further delineate regions in kLANA that contribute to its interaction with BET proteins , four double-point charge inversion substitutions were selected in a reasonable radius around the peptide segment 1125–1129 of the kLANA CTD . The mutants were tested for their ability to induce specific chemical shift perturbations in 15N-labeled BRD4-ET ( 600–680 ) ( Figure S2C ) . The substitutions KK ( 1113–1114 ) EE and KK ( 1140–1141 ) EE did not disrupt binding , but the substitutions KAR ( 1030–1032 ) EAE and KK ( 1069–1070 ) EE , located at the ‘bottom’ of the LANA structure that mediates the specific binding to viral DNA ( see above ) led to significant impairment . Based on these data we performed in silico docking of the globular ET domain to kLANA using ‘Rosetta Dock’ [47] . Two global orientations of BRD2 ET ( 632-713 ) relative to kLANA ( 1013–1149 ) displayed comparably low energy scores ( Figure S2D ) . In both models , F688 of BRD2 ET was placed near the N-terminus of helix α2 of kLANA . In model I , the acidic peptide segment of residues 682–689 in BRD2 ET is placed in the basic cleft of kLANA right underneath the peptide segment 1125–1129 . In model II ( Figure 4C , S2D ) , BRD2 ET is rotated by 180° relative to model I . Notably , in our NMR study we initially observed particularly strong chemical shift perturbations only at low salt concentrations in the segment 643–647 of BRD4 ET ( 600–680 ) , ( Figure 3E ) . This structural element of ET forms a surface exposed loop between helix α2 and the major LANA binding epitope of ET . Since LANA is a dimer , two ET domains can bind to it . However this only occurs to a significant degree at low salt concentrations , when electrostatic interaction is strong . In model II this would lead to cooperative self-interactions at the above-mentioned segment of ET ( Figure 4D , S2D ) . Thus , only the second model is supported by the observed salt-dependent NMR chemical shift perturbations and is also in better overall agreement with the corresponding mutagenesis data . We next investigated how the ET binding site in the kLANA CTD contributes to kLANA's functions ( Figure 4E , F ) . All mutants in the ET binding site , except for P1127R , were incapable of replicating a plasmid carrying 4 TR elements in transiently transfected cells ( Figure 4E ) . With the exception of K1070E all mutants were still able to bind LBS ( Figure 4F ) . The ability of kLANA ET binding site mutants to oligomerize was comparable to wt kLANA ( Figure S2E ) . Thus , several of the kLANA residues whose NMR resonances shift in response to ET domain binding are required for successful latent episomal replication without affecting the binding to the viral latent origin of replication or kLANA oligomerization . Although the fold of the two γ2-herpesviral LANA CTDs is closely similar to that of the γ1-herpesviral EBNA-1 , their surface charge at the face opposing the specific DNA binding site is inverted ( Figure 1B ) . The conservation of the basic , lysine-rich patch in the top surfaces of both kLANA and mLANA may indicate an important , conserved function ( Figure S4C , S1D ) . Indeed , the alanine substitution of two single lysine side chains K1109 and K1138 severely reduced both BRD2 and BRD4 binding , while the double substitution K1109A/K1138A completely abolished it ( Figure 5A ) . While the substitutions K1055A and K1113A did not significantly affect BRD4 binding , they abolished BRD2 binding by kLANA ( Figure S3A ) . As we already mapped a specific ET domain interaction to the 1125–1129 epitope in kLANA , this result suggested that a second significant interaction site between LANA CTD and BET proteins exists . An amino acid sequence alignment of the BRD2/4 ET domains including their C-terminally adjacent sequence elements pointed to an acidic , serine-rich stretch as a candidate for this interaction ( Figure S3B ) . In order to test this hypothesis , a range of N- and C-terminally truncated fragments of BRD2 ( 640–801 ) was generated and assayed for their capability to interact with FL kLANA ( Figure S3C ) . Binding of BRD2 ( 640–801 ) was very strong , while the fragment BRD2 ( 720–801 ) , which lacks the globular ET domain , did not bind kLANA . Likewise , the fragment BRD2 ( 640–773 ) , which only lacks the serine-rich sequence element , was severely impaired in kLANA binding . Using NMR spectroscopy , we observed that the 15N-labeled BRD4 ( 600–722 ) , which contains the ET domain and the C-terminal serine-rich peptide , behaves closely similar to 15N-BRD4-ET ( 600–680 ) in solution ( Figure S3D ) . However , when kLANA ( 996–1153 ) was added , resonances broadened substantially and the spectrum of BRD4 ( 600–722 ) nearly disappeared , indicating a substantially increased particle size and strong binding . This effect was considerably milder when kLANA ( 996–1153 ) was added to 15N-labeled ET fragments lacking the serine stretch . Thus , two independent experimental approaches show that the serine-rich acidic sequence of BRD2/4 strongly enhances kLANA interactions with BRD2/4 . In order to further understand the role of the kLANA ‘basic top’ , we tested mutants of this area with respect to other LANA functions . The pull down of full-length LANA with a GST-fused LANA CTD was impaired by lysine to alanine substitutions in this region . In particular , K1109A/K1138A severely reduced kLANA oligomerization ( Figure 5B ) . None of these lysine to alanine replacements affected binding to LBS DNA ( Figure 5C ) . However , in the transient replication assay ( Figure 5D ) the double mutant ( K1109A/K1138A ) showed a consistently reduced ability to replicate latent viral DNA , while the corresponding single substitutions had no significant effect . We have previously shown that residues 228–231 ( KKLK ) , which are located on the basic surface of mLANA ( Figure 5E ) , influence the interactions with BRD2 and BRD4 , and affect mLANA-mediated transcriptional activation [40] ( see also Figure 5F ) . In order to assess the functional role of this basic surface element in vivo , we inserted this mLANA mutant into a recombinant MHV-68 genome cloned into a bacterial artificial chromosome . Mutant and revertant viruses were then used to infect mice intranasally and compared to a previously described [36] mLANA deletion mutant ( ‘73-STOP’ ) and its revertant . The 228–231 4A mutant replicated normally in tissue culture ( not shown ) . On day 6 after intranasal infection , this mutant replicated to wt levels in the lungs of infected mice ( not shown ) . However , on day 17 after infection , when MHV-68 latency had been established , the 4A mutant showed a pronounced reduction of viral genome copy numbers in spleen cells approaching the phenotype seen with the mLANA deletion mutant ( Figure 5G ) . In a reactivation assay with latently infected splenocytes plated on a susceptible cell line , even high numbers of splenocytes failed to yield reactivatable virus ( Figure 5H ) . Based on these data , we conclude that the ‘basic top’ , common to kLANA and mLANA proteins , plays an important role in the interaction with the BET proteins and contributes to latent replication/persistence . One of the characteristic features of kLANA is the formation of nuclear micro-domains ( ‘speckles’ ) in latently infected cells [3] , [48] , [49] . The viral genomes colocalize with LANA in these speckles , and the presence of the KSHV TR region , which contains the LBS sites , is required for their assembly [19] . We tested a selection of the kLANA mutants described above for their ability to form nuclear speckles in the presence of a TR containing plasmid ( Figure 6A ) . The FL wt kLANA protein formed many distinct speckles in most of the transfected cells , while the LBS binding deficient PYG ( 1065–1067 ) AAA mutant ( Figure S1F ) , showed a diffuse nuclear localization , indicating that specific viral DNA binding is a prerequisite for kLANA speckle assembly . Also the kLANA mutant A1121E , defective in self-association ( Figure 2 ) , did not form nuclear speckles suggesting a crucial role of inter-dimer interactions between helices α1 and α3 in this process . Individual substitutions of lysine residues on the ‘basic top’ of kLANA did not result in a loss of speckles , while the double mutant K1109A/K1138A showed an impairment of speckle formation ( Figure 6A , B ) . This indicates that also the ‘basic top’ contributes to higher order oligomerization of LANA in vivo . Furthermore , mutants K1070E , R1119M and H1126E localized near the ET binding site were compromised in speckle formation , while the surface exposed residues P1127 and L1128 did not significantly affect this process ( Figure 6A , B ) . Overall , the sites for viral DNA binding , self-association of kLANA dimers , and residues near a binding site for chromatin-associated BRD2/4 proteins are required for formation of the characteristic kLANA nuclear speckles .
In this study we solved the 3D structures of kLANA CTD and mLANA CTD . They share the overall fold with the origin binding proteins of Epstein-Barr virus , EBNA-1 [42] and of human papillomavirus , E2 [43] . However , their surface characteristics are substantially distinct from EBNA-1 and E2 , which provided the basis for a specific functional annotation of three faces in the CTDs of kLANA and mLANA ( see also Table S2 ) . The self-association of LANA CTDs observed in both kLANA and mLANA crystals represents a key characteristic feature of these proteins . In all crystals , the inter-dimer interactions were mediated by helices α1 and α3 . The angles between two neighboring LANA dimers range from 0° for mLANA , 72° for the kLANA pentameric rings to 90° for the kLANA tetrameric ring ( Figure 2A , B ) . Moreover , both pentameric ring structures of kLANA dimers display ring puckering , where the interface between two dimers is oriented out of the ring plane ( Figure S4B ) . This provides direct crystallographic evidence that the interface between LANA dimers is generally compatible with a range of relative LANA dimer orientations . Due to the hinge-like character of the inter-dimer interface , in vivo native LANA oligomers might differ in shape from the closed ring structures or the linear chain observed in the respective crystals . EBNA-1 dimers physically link target viral DNA sites via their linking domains that are distinct from the DNA binding domains [50] . The ability of EBNA-1 to self-associate through disparate domains was shown to be important for its function in viral replication and transcriptional control [51] . In contrast to EBNA-1 , self-association of LANA appears to be mediated by its C-terminal DNA binding domain . kLANA binds cooperatively to LBS1 and LBS2 within the KSHV TR [4] . DNA bending has been proposed to be a prerequisite for the initiation of DNA replication [52] , [53] and a LBS1/2 containing probe was previously shown to be bent by ∼110° when both sites were occupied [54] . Two adjacent kLANA dimers in our monoclinic crystals are perfectly oriented to bind and bend LBS1/2 to this extent ( Figures 2A , S4A ) . While our oligomerization mutants of kLANA ( M1117D and A1121E ) could still bind DNA ( Figure 2E ) they were not able to promote KSHV episome replication ( Figure 2F ) . Consequently , kLANA inter-dimer interactions may contribute to KSHV latent replication through their impact on DNA bending . On the other hand , self-association of kLANA dimers appears to be functionally important beyond the bending of viral DNA , because mutations that disrupt the inter-dimer interface also abolish the formation of the characteristic nuclear kLANA speckles ( Figure 6 ) . Unexpectedly , we found that also the positively charged ‘top’ of the kLANA CTD contributes to speckle formation . In particular the double mutant K1109A/K1138A , which removes four positive charges per kLANA dimer , shows reduced oligomerization ( Figure 5B ) and speckle formation ( Figure 6 ) . Although this mutant was not impaired in LBS binding , it showed a reduced capacity to replicate a TR containing plasmid ( Figure 5C , D ) . Likewise , the mLANA 4A mutant was incapable of establishing latency in the spleens of infected mice ( Figures 5G , H ) . Thus , interaction partners other than LBS1/2 appear to significantly enhance LANA speckle formation via the ‘basic top’ , which appears to be generally required for latent replication/persistence . We found that the binding of BET proteins to kLANA occurs via two distinct sequence elements of BRD2/4 . In addition to the interaction of the serine-rich stretch of BET proteins with the ‘basic top’ of LANA CTD , their globular ET domain binds near residues 1125–1129 of kLANA ( Figures 3 , 4 , S4C ) . Both interactions are required for strong LANA:BET binding ( Figure S3C ) . The serine-rich tails of BET proteins might interact with neighboring LANA dimers , which would stabilize LANA oligomers . This interaction may therefore promote the oligomerization of LANA CTDs and consequently the formation of nuclear speckles . In solution , the kLANA and mLANA CTDs exist as isolated dimers ( Figure 2C ) suggesting that other interaction partners of LANA might be required to shift the equilibrium towards higher order LANA oligomers in order to promote speckle formation in vivo . However , for sterical reasons pairs of LBS1/2-bound kLANA dimers could not oligomerize directly , but would require at least one more bridging dimer between them . Interaction of such LBS-free LANA dimers with LBS-bound dimers could be enhanced by other binding partners like the BET proteins ( Figure 7 ) . While the present data do not allow final conclusions , we are tempted to speculate that LANA speckles contain LANA oligomers that are stabilized by interactions with ( i ) LBS DNA , ( ii ) BET proteins , and potentially ( iii ) other interaction partners of FL LANA . Such a scenario is consistent with our observations , and it would allow tethering many TR-repeats into a single nuclear speckle . Our NMR data place the ET domain binding site and the viral episome binding site in very close proximity on the kLANA surface , which makes the simultaneous binding of LBS and ET on the same kLANA dimer unlikely due to sterical hindrance . However , it is well established that viral episomes and BET proteins colocalize with the LANA speckles [28] , [55] . This can be reconciled in a model that envisages viral DNA and BET proteins interacting with distinct kLANA molecules that are present in the same oligomeric aggregate ( Figure 7 ) . It appears possible that in addition to the acidic serine-rich sequence element of the BET proteins , also other acidic factors might stabilize kLANA oligomers by interactions with its ‘basic top’ . Candidates would also include kLANA's own acidic internal repeat region or the phosphate backbone of DNA molecules . kLANA has been shown to interact also with other host chromatin proteins [11] and thus it is conceivable that further contributors to kLANA oligomerization exist . Overall , kLANA CTD oligomerization could allow the alternative occupation of overlapping binding sites on different LANA molecules in the nuclear speckles . The N-terminal residues 5–13 of kLANA are required for chromatin association [22] , [25] , [56] and latent replication [57] . A chromatin binding domain has also been identified in the kLANA CTD [23] , [24] , [58] . Previous studies found that multiple alanine substitutions near residues 1125–1129 of the kLANA CTD abolish its association with the mitotic chromosomes [23] ( Figure S4C ) . We found that BET proteins , known to associate with mitotic chromosomes [59] , [60] , interact with this part of kLANA CTD ( Figure 3A–C , 4B ) and could therefore contribute to interactions between the kLANA CTD and host chromosomes . Most of our kLANA mutants targeting the ET domain binding site were impaired in latent replication/persistence ( Figure 4E ) and kLANA speckle formation ( Figure 6 ) . Thus , in addition to LBS DNA binding and kLANA oligomerization , kLANA chromatin association through BET proteins could be a third essential factor for KSHV persistence . In conclusion , our structural and functional data revealed kLANA oligomerization via its CTD as an Achilles' heel of this γ2-herpesvirus . A single point mutation at the critical kLANA interface has the potential to abolish KSHV persistence and thus provides a possible antiviral target . In addition , the promotion of kLANA oligomerization by host protein contributors may provide further points of interference to compromise latent viral replication , and thereby prevent human diseases that are caused by persistent KSHV infections .
All animal experiments were in compliance with the German Animal Welfare Act , and the protocol was approved by the local Animal Care and Use Committee ( District Government of Upper Bavaria; permit number 124/08 ) . All protein constructs were expressed from synthetic genes ( Invitrogen ) in pET-based vectors providing resistance to ampicillin . All of them carried an N-terminal his6 tag joined by a thrombin protease cleavage site . Expression was carried out in E . coli BL21 ( DE3 ) ( Stratagene ) . Unlabeled proteins were produced in 1 L shaking flask cultures of ZYP-5052 auto-inducing rich medium [61] , which were inoculated with a starting OD600 of 0 . 1 and were incubated over night at 37°C . For expression of seleno-methionine ( SeMet ) labeled KSHV LANA ( 1013-1149 ) , a preculture of 2×1 L minimal medium was first grown from an OD600 of 0 . 1 to 1 . 0 at 37°C ( 80 mM K/Na-phosphate pH 7 . 0 , 40 mM NH4Cl , 4 mM Na2SO4 , 2 mM MgSO4 , 0 . 5% ( w/v ) glucose , 33 µM thiamine chloride , 0 . 2× trace metals [61] . The complete cell mass was then transferred to 500 mL expression culture ( same as above without trace metal mixture but containing 100 mg/L lysine , phenylalanine , and threonine , 50 mg/L isoleucine , leucine , and valine , and 60 mg/L seleno-methionine ) . Subsequently , expression was induced with 1 mM IPTG and the culture was incubated for 9 h at 37°C . For expression of isotope labeled proteins for NMR analysis , precultures of 2×1 L CN-040 minimal medium were first grown from an OD600 of 0 . 1 to 1 . 0 at 37°C ( 100 mM K/Na-phosphate pH 7 . 0 , 1 g/L NH4Cl , 5 mM Na2SO4 , 2 mM MgSO4 , 4 g/L glucose , 1× MEM vitamin solution ( Sigma-Aldrich ) , 0 . 2× trace metals [61] . At this stage , no labeling substrates were included . The complete cell mass was then transferred to 500 mL expression cultures in CN-040 , which depending on the requirements contained 15N-NH4Cl , 13C-glucose , and was based on deuterium oxide ( all by Cambridge Isoptope Laboratories ) for KSHV LANA ( 1013-1149 ) . Expression was induced with 1 mM IPTG and the cultures were incubated for 9 h at 37°C . His6-tagged kLANA and mLANA CTD fragments were expressed in E . coli . Bacterial cells were suspended in guanidine buffer ( 100 mM sodium phosphate , 10 mM tris-Cl , 6 M guanidine-Cl , 2 mM DTT , pH 8 . 0 ) and disrupted on an ultrasonic homogenizer until a clear solution was obtained . The homogenate was cleared from insoluble constituents by centrifugation at 37 , 000× g for 30 min . Protein originating from 10 g of wet cell mass was coupled to 5 mL of Ni-NTA Superflow beads ( Qiagen ) . For KSHV LANA and MHV-68 LANA constructs , an interrupted linear guanidine gradient was applied to the beads ( 6 . 0 M–1 . 8 M guanidine in 42 min at 1 mL/min , 1 . 8 M for 20 min at 1 mL/min , 1 . 8 M for 40 min at 0 . 1 mL/min , 1 . 8 M–0 M in 18 min at 1 mL/min ) . Proteins were eluted in imidazole buffer ( 100 mM sodium phosphate , 10 mM tris-Cl , 500 mM imidazole , 2 mM DTT , pH 5 . 8 ) . For KSHV LANA and MHV-68 LANA constructs , the procedure of running the gradient and subsequent elution was repeated four times on the same beads and elution fractions were pooled and concentrated using 10 kD MWCO Vivaspin 20 spin filters ( Sartorius ) . For BRD2 and BRD4 ET domain constructs a smooth linear guanidine gradient was applied ( 6 . 0 M–0 M in 60 min at 1 mL/min ) . Here , a single elution step was considered sufficient . For all constructs , the buffer was exchanged to thrombin cleavage buffer ( 20 mM tris-Cl , 100 mM NaCl , 2 mM DTT , pH 8 . 0 ) by dialysis and the his6 tag was cleaved with thrombin ( Sigma-Aldrich ) at a concentration of 2 u/µmol at 22°C . After complete digest , the protease was inactivated with Complete EDTA-free Protease Inhibitor Cocktail ( Roche ) and removed on Benzamidine Sepharose 4 Fast Flow ( GE Healthcare ) . For BRD2 and BRD4 ET domain constructs , the cleaved his6 tag was removed on nickel beads and the proteins were concentrated and transferred to their final buffers in 5 kD MWCO Vivaspin 20 spin filters ( Sartorius ) . For KSHV LANA and MHV-68 LANA constructs the cleaved his6 tag was separated using 10 kD MWCO Vivaspin 20 spin filters ( Sartorius ) in the presence of 100 mM imidazole , pH 6 . 5 . The proteins were subsequently concentrated and transferred to their final buffers on the same spin filters . All protein constructs harbored the non-native amino acid sequence glycine-serine at their N-terminus , which was left from the thrombin cleavage site . Identity , integrity , and purity of the proteins were confirmed by SDS-PAGE and mass spectrometry . Flow fractionation experiments were carried out on a Wyatt Eclipse 3 separation system with a Wyatt Dawn Heleos-II static light scattering detector and a Wyatt Optilab rEX refractometer in conjunction with components of a Shimadzu HPLC system . A short flow channel ( 145 mm length , Wyatt ) equipped with a 490 µm spacer on a 10 kD PLGC regenerated cellulose membrane ( Millipore ) was connected to the system . The detector flow was 1 . 00 mL/min and the cross flow was 2 . 00 mL/min . Each run , 40 µg of protein were loaded . Running buffer was 10 mM bis-tris-Cl , pH 6 . 5 , 50 mM NaCl , 0 . 01% NaN3 . For molecular weight determination , the refractive index was used as a measure of protein concentration . KSHV LANA ( 1013-1149 ) , monoclinic crystal form: 1 . 5 µL of 2 . 0 mM protein ( 1 . 0 mM for the SeMet derivative ) in 5 mM bis-tris-Cl , pH 6 . 5 , 10 mM DTT were added to 1 . 5 µL of 0 . 1 M sodium bicine , pH 9 . 0 , 1 . 0 M lithium chloride , 7% ( w/v ) PEG 6000 . The mixture was incubated at 12°C in a hanging drop setup . Crystals grew in a few days and were cryo-protected by short soaking in 0 . 1 M sodium bicine , pH 9 . 0 , 1 . 0 M lithium chloride , 7% ( w/v ) PEG 6000 , 25% ( v/v ) glycerol . KSHV LANA ( 1013-1149 ) , orthorhombic crystal form: 1 . 5 µL of 0 . 8 mM protein in 5 mM bis-tris-Cl , pH 6 . 5 , 200 mM LiCl , 4 mM DTT were added to 1 . 5 µL of 0 . 2 M lithium citrate , pH 7 . 6 , 20% ( w/v ) PEG 3350 . The mixture was incubated at 20°C in a hanging drop setup . Crystals grew in a few days and were cryo-protected by short soaking in 0 . 2 M lithium citrate , pH 7 . 6 , 20% ( w/v ) PEG 3350 , 30% ( v/v ) glycerol . KSHV LANA ( 996-1153 ) , cubic crystal form: 1 µL of 1 mM protein in 5 mM bis-tris-Cl , pH 6 . 5 , 2 mM DTT was added to 1 µL of 0 . 1 M sodium citrate , pH 2 . 5 , 1 . 5 M ammonium sulfate . The mixture was incubated at 4°C in a hanging drop setup . Crystals grew in a few days and were cryo-protected by short soaking in 0 . 1 M sodium citrate , pH 2 . 5 , 1 . 5 M ammonium sulfate , 25% ( v/v ) glycerol . MHV-68 LANA ( 124-260 ) , triclinic crystal form: 1 . 5 µL of 2 . 0 mM protein in 5 mM bis-tris-Cl , pH 6 . 5 , 10 mM DTT were added to 1 . 5 µL of 0 . 1 M sodium bicine , pH 9 . 0 , 1 . 0 M lithium chloride , 7% ( w/v ) PEG 6000 . The mixture was incubated at 12°C in a hanging drop setup . Crystals grew in a few days and were cryo-protected by short soaking in 0 . 1 M sodium bicine , pH 9 . 0 , 1 . 0 M lithium chloride , 7% ( w/v ) PEG 6000 , 25% ( v/v ) glycerol . All datasets were collected under cryogenic temperatures either on beamline 14 . 2 of BESSY II of the Helmholtz–Zentrum Berlin ( HZB ) , Germany or on our Rigaku MicroMax-007 HF rotating anode home source ( Table S1 ) . The crystallographic phase problem was solved through a single-wavelength anomalous diffraction experiment carried out with a seleno-methionine derivative of monoclinic KSHV LANA ( 1013-1149 ) at the absorption peak wavelength of selenium . Phase information was derived from the anomalous signal of the peak dataset using Phenix . autosol and an initial model was built using Phenix . autobuild , both of the Phenix software suite [62] . The initial model was then completed through iterative steps of manual building in Coot [63] and refinement against a high-resolution native dataset of monoclinic KSHV LANA ( 1013-1149 ) that had been corrected for anisotropic diffraction using the anisotropy correction server [64] . The datasets of orthorhombic and cubic KSHV LANA fragments as well as MHV-68 LANA ( 124-260 ) were phased by molecular replacement ( MR ) with Phenix . auto_mr [62] using a monomer of monoclinic KSHV LANA ( 1013-1149 ) as search model . The search model for MHV-68 LANA ( 124-260 ) was modified prior to MR by pruning non-conserved residues to account for structural differences arising from its low sequence identity with KSHV LANA . For orthorhombic and cubic KSHV LANA fragments , placed models instantly resulted good electron density maps and could be pursued with refinement . For MHV-68 LANA ( 124-260 ) , however , the placed model had first to be improved by alternate rebuilding and relaxation with phenix . mr_rosetta [65] . Refinement was carried out for all structures in Phenix . refine [62] with restraints on bond lengths , bond angles , planarities , and chirality . Atomic B-factors were treated as being isotropic while the presence of anisotropic domain motion was acknowledged by performing TLS refinement . Refinement was stopped when Rwork and Rfree converged . For mapping of the LANA-binding epitope on the ET domains , [1H , 15N]-TROSY-type HSQC spectra [66] of 0 . 48 mM 15N-labeled BRD2 ( 632-713 ) or 15N-BRD4 ( 600-680 ) in 20 mM bis-tris-Cl , pH 6 . 5 , 2 mM DTT , 5% ( v/v ) D2O , and NaCl in rising concentrations of 50 , 100 , 200 , 350 , and 500 mM were recorded at 20°C in the absence and presence of 0 . 96 mM unlabeled KSHV LANA ( 996-1153 ) . While the backbone amide assignment for BRD4 ( 600-680 ) was adapted from published data [46] , the backbone assignment for BRD2 ( 632-713 ) was obtained from a set of HNCO , HN ( CA ) CO , HNCACB , and CBCA ( CO ) NH experiments on a sample of 0 . 2 mM [13C , 15N]-BRD2 ( 632-713 ) in 20 mM bis-tris-Cl , pH 6 . 5 , 5% ( v/v ) D2O , 200 mM NaCl , and 2 mM DTT at 20°C . Experiments were carried out on a Bruker Avance III 600 NMR spectrometer equipped with a cryogenic probehead . The ET domain constructs used in the determination of the LANA-binding epitope carried the four non-native amino acids glycine-serine-glycine-serine at their N-terminus , where the first two originated from the thrombin cleavage site and the further two were introduced as a spacer to the highly acidic N-terminus of the ET domains , which appears to inhibit thrombin digest in cis . For mapping of the ET-binding epitope on the KSHV LANA C-terminal domain , [1H , 15N]-TROSY-type HSQC spectra of 0 . 48 mM [2H , 13C , 15N]-KSHV LANA ( 1013-1149 ) in 10 mM bis-tris-Cl , pH 6 . 5 , 5% ( v/v ) D2O , 30 mM NaCl , and 2 mM DTT were recorded at 37°C in the absence and presence of unlabeled BRD4 ( 600-680 ) in concentrations of 0 . 14 , 0 . 34 , 0 . 48 , 0 . 72 , and 0 . 96 mM . A sequence specific backbone assignment for essentially all observable resonances of the KSHV LANA ( 1013-1149 ) was obtained from a set of TROSY-type 3D experiments ( tr-HNCO , tr-HN ( CA ) CO , tr-HNCA , and tr-HNCACB ) [67] , [68] on a sample of 0 . 5 mM [2H , 13C , 15N]-KSHV LANA ( 1013-1149 ) in 10 mM bis-tris-Cl , pH 6 . 5 , 5% ( v/v ) D2O , and 2 mM DTT at 37°C . These experiments were carried out on a Bruker AV 900 NMR spectrometer equipped with a cryogenic probehead . The BRD4 ET domain construct used here carried the non-native amino acid sequence GSGGGPGS at its N-terminus , where the first two residues originated from the thrombin cleavage site and the others were introduced as a spacer to the highly acidic N-terminus of the ET domain . For analysis of the chemical shift perturbations of 1H and 15N backbone resonances , a weighted average chemical shift change , Δav , was calculated according to Dehner et al . [69] . Docking simulations of KSHV LANA with the ET domain were done with the RosettaDock web server ( http://rosettadock . graylab . jhu . edu/ , access in January 2013 [47] . The server performs a local rigid body docking search and adjusts side chain conformations at the surface . Input PDB files contained both protein fragments at a distance of ∼10 Å to each other ( Figure S2C ) . The model of the BRD2 ET domain was generated based on the NMR structure of the BRD4 ET domain [46] . Both domains share a high sequence identity of 85% , where the point mutations affect only solvent-exposed residues and are mostly conservative in nature . Therefore , the 12 respective side chains of the BRD4 ET domain were altered by replacement for likely conformers of their equivalents of BRD2 using Coot [63] . Coordinates of the protein backbone and all other side chains were kept unchanged . Bent DNA fragments for modeling of KSHV LANA DBD:LBS complexes ( Figure S4 ) were generated with the 3D DART web server ( http://haddock . chem . uu . nl/dna/dna . php , access in November 2012 [70] . The HEK 293 , HEK293T and HeLa cells were cultured in Dulbecco's modified Eagle's medium ( Gibco ) supplemented with 10% heat-inactivated fetal calf serum , 50 IU/ml penicillin , 50 µg/ml streptomycin , and 200 µg/ml L-glutamine at 37°C with 5% CO2 . Full length ( FL ) wt KSHV LANA in pcDNA3 ( pcDNA3-LANA ) , GFP-BRD2 , GFP-BRD4 ( HUNK ) , pGTR4 , and wt MHV-68 LANA ( pVR1255 orf73 ) vectors were described previously [26] , [71] , [40] , [58] . The GST-LANA CTD ( aa934-1162 ) was cloned by PCR of the respective LANA fragment , using pcDNA3 LANA as a template , and inserted into the BamHI and EcoRI sites of the pGEX-6P1 vector , creating a construct with LANA CTD fused to the C-terminus of the GST protein . All of the point mutants of FL wt KSHV LANA , GST-LANA CTD ( aa934-1162 ) , GFP-BRD2 , and FL wt mLANA were created by either single or multiple round site directed mutagenesis . All constructs were sequence verified . The TR1 vector was cloned by inserting a 590 bp fragment containing KSHV genomic sequence derived by partial digest of cosmid 83 [72] into the pBluescript vector ( Stratagene ) . An 801 bp Not I digested TR fragment was introduced in a second step and checked for correct orientation by sequencing . The MHV-68 genome cloned into a Bacterial Artificial Chromosome ( BAC ) [73] was used to produce recombinant virus . BAC mutagenesis was performed as described in [74] . The Orf73 sequence of approximately 1 kb and 1 kb of flanking sequence on each side were cloned into the shuttle plasmid pST-SNR ( Kan resistance ) using restriction enzymes SacI and XmaI . Mutations were introduced by two PCR reactions each using one of the flanking primers and a mutagenesis primer spanning the position to be mutated . Subsequently both PCR products were annealed and the resulting fragment amplified to obtain the entire 3 kb fragment for cloning into pST-SNR . Revertants for both mutant viruses were made by using the wt encoding shuttle plasmid . The BAC cassette was excised from viral genomes in REF-Cre cells and MHV-68 was produced in BHK21 cells as described in [73] . Extracts for co-immunoprecipitation assays were prepared from ∼1×106 293/293T cells transfected using Fugene6 ( Promega ) and harvested 2 days after transfection . Cells were suspended in 300 µl of lysis buffer ( for KSHV LANA co-IPs: 50 mM Tris ( pH 7 . 6 ) , 60 mM NaCl , 0 . 5 mM EDTA , 1% glycerol , 0 . 2% NP-40; for MHV-68 LANA co-IPs: 20 mM Tris ( pH 7 . 6 ) , 150 mM NaCl , 1 mM EDTA , 1% TritonX100 ) with protease inhibitors: 1 . 5 µM aprotinin ( Applichem ) , 10 µM leupeptin ( Applichem ) , 100 µM phenylmethylsulfonyl fluoride ( PMSF , Applichem ) , 1 µM benzamidine ( Applichem ) , 1 . 46 µM pepstatin A ( Applichem ) . The extracts were sonicated 3×10 s , cell debris was pelleted and the lysates were pre-cleared with Protein A/G beads ( Amersham Biosciences ) for 30 min at 4°C on a rolling platform . Protein A ( for anti-GFP IP ) or Protein G ( for anti-HA IP ) beads were incubated with rabbit anti-GFP antibody ( Clontech ) or rat anti-HA antibody ( Roche ) respectively , the incubation was performed overnight at 4°C on a rolling platform . Subsequently , the antibody conjugated beads were washed 3 times with 500 µl of respective lysis buffer . 20 µg ( for anti-GFP ) and 200 µg ( for anti-HA ) antibody was bound to 80 µl of Protein A beads ( anti-GFP ) or 100 µl of Protein G beads ( anti-HA ) . Antibody conjugated beads were aliquoted , 15 µl per IP and 250 µl of cell extract was added per sample and incubated overnight at 4°C on a rolling platform . The beads were then pelleted and washed 6 times with respective lysis buffer . Samples were suspended in 5 µl of loading buffer ( 5 mM Tris pH 6 . 8 ) , 45% glycerol , 5% SDS , 0 . 1% Pyronin Y , 3 . 5% β-mercaptoethanol ) , boiled and the proteins separated on an SDS-polyacrylamide gel ( 8% ) and transferred to a nitrocellulose membrane . Proteins were detected using following antibodies: rat anti-LANA ( ABI; 1∶500 ) , mouse anti-GFP ( Clontech; 1∶1000 ) , mouse anti-HA ( Roche; 1∶1000 ) , and mouse anti-actin ( SIGMA; 1∶1000 ) and visualized with the ECL reagent ( Amersham Biosciences ) . The LAS3000 imager ( FujiFilm ) was used to capture the images of the signal . Cell lysates for GST pull downs were prepared as for co-immunoprecipitation , but without pre-clearing step and the lysis buffer contained 150 mM NaCl . 250 µl of cell lysate were added per pull down sample . GST-LANA CTD ( wt and mutant ) beads were prepared ahead of time . 2 ml overnight bacterial culture were diluted 1∶10 and grown until the OD600 = 1 . 5 was reached , at which point GST-LANA CTD fusion protein expression was induced by adding IPTG ( 1 mM final concentration ) and incubating the cultures for 4 h at 30°C . Subsequently , the cultures were spun down , resuspended in PBS with 0 . 5% NP40 and protease inhibitors and sonicated 3×30 sec on ice . The spin was repeated and 100 µl of 50% glutathione sepharose bead slurry , previously washed three times with wash buffer ( PBS , 0 . 5% NP40 , protease inhibitors and 5% glycerol ) , were added per sample and incubated overnight , while rolling at 4°C . Next , the GST fusion protein coupled beads were washed three times with wash buffer . The amount of each protein bound to 10 µl beads was estimated based on a Coomassie stain of an SDS PAGE gel and was then adjusted accordingly . After cell lysates were added to GST fusion protein coupled beads the binding reactions were incubated 3 h at 4°C on a rolling platform and subsequently washed six times with wash buffer . After adding 5 µl of loading buffer , beads were boiled and the supernatants were loaded on to a SDS-polyacrylamide gel ( 8% ) separated and transferred to a nitrocellulose membrane . GST-LANA CTD proteins were detected with Ponceau S , directly after transfer and the full length LANA proteins with rat anti-LANA antibody , as described above for the co-immunoprecipitation . 5′ Dy682 labeled oligonucleotides ( IBA ) containing both LANA binding sites EMSA-LANA BS-top: GAG GCG GCG CGC GGC CCC ATG CCC GGG CGG GAG GCG CCG CAG GCC CCG GCG GCG TCC CCG GC and EMSA-LANA BS-bottom: GCC GGG GAC GCC GCC GGG GCC TGC GGC GCC TCC CGC CCG GGC ATG GGG CCG CGC GCC GCC TC were annealed in annealing buffer ( 20 mM Tris-HCl , pH 7 . 6 , 50 mM NaCl , 10 mM MgCl2 ) . GST-LANA CTD proteins ( wt and mutants ) were prepared as for the oligomerization assay , but following the binding to the beads and washing , they were eluted in 50 µl of elution buffer ( PBS , 0 . 5% NP40 , 1% glycerol , 60 mM glutathione , protease inhibitors , pH adjusted to 7 . 3 ) for 3 h at 4°C . The level of expression of each protein was estimated based on a Coomassie stain of an SDS polyacrylamide gel and was then adjusted accordingly . LANA proteins were incubated 30 min at room temperature in the dark , with 1 µl of 5 µM probe in a final volume of 15 µl in a buffer containing 30 mM TrisHCl , pH 7 . 5 , 50 mM KCl , 10 mM MgCl2 , 1 mM EDTA , 10% glycerol , 0 . 25% Tween 20 , 1 mM dithiothreitol , 0 . 5 µg/µl BSA , and 0 . 75 µg poly ( dI-dC ) . The samples were separated by electrophoresis on a native 4% polyacrylamide gel in 1xTris-borate-EDTA for 2 h and imaged with Odyssey Imager ( LI-COR ) . This assay was performed as previously described [4] . Briefly , 1×105 HeLa cells were plated per well of a 6-well plate . On the next day cells were transfected with pGTR4 plasmid [71] , containing four KSHV terminal repeats ( TR ) , and a GFP coding sequence and the pEGFP-C1 ( Clontech ) plasmid , used as an internal non-replicating control . Alternatively , pTR1 and pBluescript were transfected as the replicon and the non-replicating control respectively . 72 h later cells were harvested in lysis buffer ( 10 mM Tris-HCl pH 8 . 0 , 10 mM EDTA , 0 . 6% SDS ) . The chromosomal DNA was precipitated overnight with 0 . 85M NaCl and pelleted . The episomal DNA was purified using phenol-chlorophorm extraction and the Gel lock columns ( 5PRIME ) , precipitated with ethanol and the pellet was dissolved in 20 µl of water . 90% of DNA was digested for 72 h with 60 U of MfeI HF ( or KpnI ) ( NEB ) and 60 U DpnI ( NEB ) and the remaining 10% with 40 U MfeI HF ( or KpnI ) only . The MfeI ( KpnI ) enzyme linearizes the pGTR4 ( pTR1 ) as well as pEGFP-C1 ( pBluescript ) vectors . The MfeI ( KpnI ) /DpnI digestion reveals the efficiency of replication , while the single MfeI ( KpnI ) digestion is used to estimate the amount of input DNA . Digested DNA was loaded and separated on a 0 . 8% agarose gel , and transferred to a nitrocellulose membrane by Southern blotting . A sequence coding for GFP ( for the pGTR4 and pEGFP ) or fragment of pBluescript vector sequence ( for the TR1 and pBluescript ) , labeled with alkaline phosphatase was used as a probe to detect the bands of interest . The AlkPhos Direct Labeling Reagents ( GE Healthcare/Amersham Biosciences ) were used to label the probe and the CDP-Star was used as a chemiluminescent substrate for alkaline phosphatase . 1×105 HeLa cells were plated per well of a 6 well plate on coverslips and subsequently transfected using Fugene6 transfection reagent ( Promega ) . 48 hours post transfection cells were washed with PBS and fixed with 4% paraformaldehyde ( PFA ) in phosphate buffered saline ( PBS ) ( pH 7 . 4 ) for 20 min at room temperature . PFA was then quenched with 125 mM glycine and the coverslips were washed 3×5 min with PBS . Subsequently , cells were permeabilized with 0 . 2% Triton X-100 in PBS for 10 min at room temperature and blocked with 10% FCS in PBS for 1 h at room temperature . Next , coverslips were incubated with primary antibody ( anti-LANA mouse monoclonal; 1∶100 , Novocastra ) in 10% FCS in PBS for 1 h at 37°C and subsequently washed 3 times with 10% FCS in PBS . The incubation with secondary antibody ( donkey anti-mouse CY3 conjugated IgG , Jackson Laboratories; 1∶400 ) and DAPI ( 4′ , 6-diamino-2phenylindol; 1∶100 ) followed for 1 h at 37°C , again in 10% FCS in PBS . Cells were again washed 3 times for 5 min in PBS at room temperature and mounted with Moviol containing DABCO . To quantify the number of speckles per nucleus ( Figure 6B ) we used the CellProfiler software [75] . We analyzed minimum 80 cells per sample . All pixel intensities were rescaled to 0 to 1 . Using the Otsu Global thresholding method [76] in the DAPI channel , the nuclear area was defined . Clumped nuclei were distinguished based on the shape . Next the GFP positive cells ( transfected with pGTR4 , which expresses GFP ) were identified using the Otsu Global thresholding method distinguishing clumped cells based on intensity . Nuclei were masked with the identified GFP positive cells . Subsequently , LANA signal was masked with the nuclei of the GFP positive cells , allowing further analysis only on LANA signal from the GFP positive ( and therefore also TR positive ) nuclei . LANA speckles were then identified using Robust Background per object thresholding method . Clumped objects were distinguished based on intensity . Using the “Relate Objects” function we established a parent-child relationship between the LANA speckles ( “children” ) and the nuclei ( “parents” ) in order to determine the speckle number per nucleus . Total 80–110 cells from two independent experiments were analyzed per sample . Standard errors of the means and statistically significant differences were determined using Kruskal-Wallis test and Dunn's post test ( GraphPad Prism , version 5 . 02; GraphPad Software , Inc . ) C57BL/6 mice were purchased from Charles River Laboratories ( Sulzfeld , Germany ) . To characterize the recombinant MHV-68 in vivo , mice were infected intranasally ( i . n . ) with the 5×104 PFU of virus . For determination of frequency of virus reactivation and genomic load , spleens were harvested at day 17 after infection . To determine the frequency of cells carrying virus reactivating from latency , serial threefold dilutions of splenocytes ( starting with 1 . 5×105 cells/well ) were plated onto NIH 3T3 cells ( 104 cells/well ) , as described previously [77] . The presence of preformed infectious virus was determined by plating parallel samples of mechanically disrupted cells ( latent virus cannot reactivate from killed cells ) . A non-linear regression plot was used to infer frequencies of reactivating cells , based on the Poisson distribution , by determining the cell number at which 63 . 2% of the wells scored positive for a CPE ( MOI = 1 ) – dashed line in Figure 5H . Viral load in the spleens of infected mice was determined , as described previously [78] by quantitative real-time PCR using the ABI 7300 real-time PCR system ( Applied Biosystems , Foster City , CA ) and TaqMan universal PCR master mix ( Life Technologies ) . Using primers and probes as described previously [79] , a 70 bp region of the MHV-68 glycoprotein B ( gB ) gene was amplified from spleen cells DNA and viral DNA copy numbers were quantified . The murine ribosomal protein L8 ( rpl8 ) was amplified in parallel and used to normalize between the samples . The data are presented as viral genome copy numbers relative to the copy number of L8 . The quantification limit was set at 50 copies per sample , according to published recommendations [80] . The statistical analysis was performed with Graph Pad Prism 5 . 02 ( GraphPad Software , Inc . ) The P values were calculated with One Way Anova analysis with Tukey's multiple comparison test . ( *** ) P<0 . 001 . The atomic coordinates and structure factors have been deposited in the RCSB Protein Data Bank with the following accession numbers: 2YPY: kLANA ( 1013–1149 ) , decameric ring , monoclinic crystal form; 2YPZ: kLANA ( 1013–1149 ) , decameric ring , orthorhombic crystal form; 2YQ0: kLANA ( 996–1153 ) , octameric ring , cubic crystal form; 2YQ1: mLANA ( 124–260 ) , triclinic crystal form . | Kaposi sarcoma-associated herpesvirus ( KSHV ) causes Kaposi Sarcoma , Primary Effusion lymphoma and the plasma cell variant of Multicentric Castleman's Disease . Its oncogenic effect is linked to its ability to persist in a latent form for the life time of infected individuals . During latency viral genomes are replicated and passed to daughter cells in synchrony with the infected cell without the formation of new virions . A key viral protein in this process is the latency-associated nuclear antigen , LANA . In latently infected cells , viral genomes and LANA form characteristic nuclear microdomains , termed ‘LANA speckles’ , which also contain cellular chromatin components . We have solved the crystal structure of the c-terminal , DNA-binding , domain ( CTD ) of KSHV LANA ( kLANA ) and its homologue mLANA of a related murine γ2-herpesvirus , which is frequently used as a model to study latent persistence in vivo . We also identified the binding site for two chromatin proteins , BRD2/4 , by NMR spectroscopy . We demonstrate the functional importance of these structural features , and their contribution to latent replication and ‘LANA speckle’ formation , in cell culture and in vivo experiments . Our results provide a structural basis for the assembly of LANA-containing nuclear structures that are required for latent viral replication and persistence . | [
"Abstract",
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"Methods"
] | [] | 2013 | A Structural Basis for BRD2/4-Mediated Host Chromatin Interaction and Oligomer Assembly of Kaposi Sarcoma-Associated Herpesvirus and Murine Gammaherpesvirus LANA Proteins |
The tad operons encode the machinery required for adhesive Flp ( fimbrial low-molecular-weight protein ) pili biogenesis . Vibrio vulnificus , an opportunistic pathogen , harbors three distinct tad loci . Among them , only tad1 locus was highly upregulated in in vivo growing bacteria compared to in vitro culture condition . To understand the pathogenic roles of the three tad loci during infection , we constructed single , double and triple tad loci deletion mutants . Interestingly , only the Δtad123 triple mutant cells exhibited significantly decreased lethality in mice . Ultrastructural observations revealed short , thin filamentous projections disappeared on the Δtad123 mutant cells . Since the pilin was paradoxically non-immunogenic , a V5 tag was fused to Flp to visualize the pilin protein by using immunogold EM and immunofluorescence microscopy . The Δtad123 mutant cells showed attenuated host cell adhesion , decreased biofilm formation , delayed RtxA1 exotoxin secretion and subsequently impaired translocation across the intestinal epithelium compared to wild type , which could be partially complemented with each wild type operon . The Δtad123 mutant was susceptible to complement-mediated bacteriolysis , predominantly via the alternative pathway , suggesting stealth hiding role of the Tad pili . Complement depletion by treating with anti-C5 antibody rescued the viable count of Δtad123 in infected mouse bloodstream to the level comparable to wild type strain . Taken together , all three tad loci cooperate to confer successful invasion of V . vulnificus into deeper tissue and evasion from host defense mechanisms , ultimately resulting in septicemia .
Vibrio vulnificus is an opportunistic Gram-negative marine pathogen that causes fatal septicemia and necrotizing wound infections in susceptible individuals with underlying hepatic diseases and other immunocompromised conditions . V . vulnificus is halophilic and found worldwide in warm coastal and brackish waters in association with shellfish such as oysters and other sea animals . In humans , this pathogen frequently causes rapidly progressing fatal sepsis with a mortality rate of greater than 50% within a few days post-infection after eating raw seafood and contamination of preexisting wounds [1–4] . During the infectious process , V . vulnificus must cope with dramatic environmental changes by sensing changes in the host milieu [5] . To establish successful infections in vivo , V . vulnificus must manage spatiotemporally coordinated changes in the expression levels of various virulence genes . To understand the genome-wide gene expression changes in V . vulnificus after infection , we recently performed a transcriptomic analysis of cells grown in vivo using a rat peritoneal infection model . Notably , among the newly identified in vivo-expressed genes , a Flp/Tad pilus-encoding gene cluster ( the tad1 locus ) was found to be highly upregulated . Flp pili are polymers of the mature Flp pilin protein , and they are assembled and secreted by a complex of proteins encoded by the tad operon . Flp pili were reported to be abundantly expressed , extremely adhesive , and bundled in Aggregatibacter ( previously Actinobacillus ) [6–9] . The Tad proteins have been reported to be essential for adherence , biofilm formation , colonization , and pathogenesis in a number of genera and are considered to be instrumental in the colonization of diverse environmental niches [6 , 7 , 10–12] . The genus Vibrio includes three main human pathogens ( V . cholerae , V . parahaemolyticus and V . vulnificus ) , all of which were reported to carry genes of pili biogenesis . The type IV pili were most well characterized in pathogenic vibrios and studied for pathogenic roles . The mannose-sensitive hemagglutinin ( MSHA ) and chitin-regulated pilus ( ChiRP ) , members of the type IV pilus , were reported to contribute to biofilm formation . V . cholerae toxin co-regulated pilus ( TCP ) is critical for host colonization and serves the cognate receptor for cholera toxin ( CTX ) phage [13–15] . The Flp subtype pilus related to the TCP is associated with the tight adherence ( Tad ) , from which the gene locus name originated [16] . Homologs of the tad locus are widely distributed in the Vibrionaceae and many Vibrio genomes encode multiple tad loci [17] . V . vulnificus CMCP6 harbors three distinct tad loci [18] ( S1 Fig ) , among which the tad1 locus has been identified as a possible virulence factor because of its ubiquity in sequenced virulent V . vulnificus strains [19–21] . The tad1 expression was preferentially induced under iron-rich conditions [18] , whilst the tad3 locus was expressed in artificial seawater [22] . Recently , through transposon ( Tn ) insertion mutation analysis , the tad2 locus ( VV2_0084 to VV2_0095 ) was reported to be important in initial surface attachment , auto-aggregation and resistance to mechanical clearance of bacterial biofilms [12] . However , the pathogenic roles of Tad pili have not yet been addressed for Vibrionaceae . This study attempted to investigate the contribution of the high in vivo expression of the tad1 operon to the V . vulnificus pathogenicity and to understand why three similar tad operons were maintained throughout the long history of evolution . We evaluated how each tad operon contributes to V . vulnificus virulence . Since the three tad operons share genes with similar function , single-gene-mutation analyses could not rule out overlapping functions of the remaining genes in the same operon or in the other tad operons . Thus , we constructed mutant strains with single and multiple complete tad loci deletions and then complemented them with individual cosmid clones harboring each tad operon . Using a variety of mouse infection models coupled with molecular genetic analyses , we demonstrate here that all three tad operons are required for V . vulnificus pathogenicity as the cryptic pili contribute to host cell and tissue invasion , survival in the blood , and resistance to complement activation .
To understand how host signals modulate tad operon expression in V . vulnificus , we analyzed the in vivo transcriptional levels of three structural flp genes using a rat peritoneal infection model . Real time RT-PCR results indicated a significantly higher flp-1 mRNA level when the bacteria were grown in vivo , corresponding to an approximately 878-fold increase ( Fig 1A ) ( P < 0 . 001 ) . Conversely , both the flp-2 and flp-3 transcript levels were slightly decreased when V . vulnificus was grown in vivo ( Fig 1A ) ( P < 0 . 05 for flp-2 and P < 0 . 001 for flp-3 ) . The expression levels of the flp genes were also measured using conventional RT-PCR . Using different numbers of amplification cycles , we confirmed that the flp-2 and flp-3 genes were transcribed at low levels under both tested conditions; in particular , flp-2 expression was detected only after 35 cycles ( Fig 1B ) . In a wide variety of bacteria , type IV pili expression is solid-surface dependent [23 , 24] , and the tad1 locus was recently found to be expressed under iron-limited conditions [18] . Thus , we measured the expression of the flp-1 gene under these growth conditions . As shown in Fig 1C and 1D , both the iron-limited and surface-associated growth conditions clearly stimulated flp-1 transcription , increasing its expression levels by approximately 131- and 210-fold , respectively ( P < 0 . 001 compared to that of the expression level in HI broth ) . Combining these two conditions significantly increased the flp-1 transcript level by 367-fold ( P < 0 . 01 ) , but the transcription level was still much lower than that observed in vivo . This finding indicates that changing one or two growth parameters in culture does not mirror the in vivo environment , where multiple host factors and growth conditions would simultaneously influence tad1 operon expression . To explore the contribution of each tad operon to V . vulnificus pathogenicity , we performed mouse lethality assays employing intraperitoneal ( i . p . ) and intragastric ( i . g . ) infection routes . Interestingly , in the i . p . infection model , the Δtad123 mutant showed a 41-fold increase in the LD50 , while the single and double mutants showed no differences ( Table 1 ) . Significantly prolonged survival was observed in the Δtad123 mutant-administered mice , which received infectious doses of 1 . 0 × 107 and 1 . 0 × 106 CFU/mouse . At a dose of 107 CFU/mouse , all of the mice infected with wild-type cells died within 5 hours post-infection , whereas approximately 60% of the mice infected with the Δtad123 mutant survived up to 48 h after the challenge ( S2 Fig ) ( P < 0 . 01 ) . However , after i . g . infection , which leads to slower translocation of the bacteria into blood circulation , we observed only a 10-fold LD50 increase ( Table 1 ) . The lethality varied depending on the route of infection , which influences the rate of bacterial invasion , growth and/or clearance at both the primary infection site and in the blood stream . Taken together , all three tad operons must be deleted to significantly ameliorate V . vulnificus virulence . Since common pili are generally involved in the attachment of bacteria to surfaces in nature , we hypothesized that deletion of the three tad operons might influence the adhesive ability of V . vulnificus . To test this hypothesis , we performed an adhesion assay in which HeLa cells were infected with V . vulnificus at an MOI of 250 followed by quantification of the number of bacteria adhered to the host cells . After incubation for 45 min , the number of Δtad123 mutant cells adhered to the HeLa cells was 15-fold less than that of the parental wild-type strain ( Fig 2A ) ( P < 0 . 001 ) . The wild-type strain formed small clusters of aggregated bacteria on the surfaces of the HeLa cells , eventually leading to cell lysis . In contrast , only a few Δtad123 mutant cells attached to the surfaces of the HeLa cells , and the infected host cells maintained cell contours similar to those of the uninfected cells . However , the adhesion of Δtad123 mutant cells to the host cells gradually increased in a time-dependent manner ( Fig 2B , P < 0 . 01 ) . The Δtad1 mutation played a dominant role in the inhibition of V . vulnificus adhesion to host cells ( S3A Fig ) . Complementation with the tad1 , tad2 or tad3 operon ( S4 Fig ) significantly rescued the adhesive ability of the Δtad123 mutant cells ( Fig 2A ) ( P < 0 . 001 for tad1 , tad2 and tad3 ) . To observe the morphology of the Tad pili , we prepared in vivo grown wild-type , Δtad123 , and Δtad123 cells carrying pLAFR3::tad1 locus then performed scanning electron microscopy ( SEM ) observation ( Fig 3 ) . In the wild-type strain , the cell surface appeared to be covered with slime-like material . Corrugated elevations and grooves ran along the longitudinal axis . In the Δtad123 mutant strain , which was devoid of the slime-like materials , the grooves and elevations were more conspicuous compared with those of the isogenic wild-type strain . Moreover , the directionality of the convexity of the surface structure was absent on the mutant surface . Interestingly , the cell surfaces of the in trans tad1 complemented strains showed similar structural characteristics to the wild type strain , suggesting that the Tad pili contribute to the formation of the slime-like surface structure . However , the typical surface groove and convexity was less obvious in the complemented strains . These results suggest that the Tad pili of V . vulnificus might also contribute to the cell envelops biogenesis by including the slime-like outer structure . We tried to further characterize the thin fimbrial projections of the putative Flp pili via immunogold electron microscopy . Firstly , we produced recombinant Flp pilin proteins and attempted to raise specific antibodies against them in animals . However , we could not obtain any appreciably immunogenic antisera even after many repeated trials . Peptide-based immunizations were also unsuccessful in raising specific antibody responses . We came to conclude that the Flp pilin have very low immunogenicity . To solve this problem , we constructed V . vulnificus strains carrying a pBAD24::FlpV5 plasmid expressing a hybrid protein of Flp pilin fused to the highly immunogenic V5 tag ( S5 Fig ) with the expectation that the plasmid-encoded FlpV5 subunits would assemble into growing pilus fibers under the control of an arabinose-inducible promoter . By using dot blot analysis with an anti-V5 antibody , we confirmed V5-positive signals in the wild type V . vulnificus transconjugants ( WT-FlpV5 ) under the inducing conditions ( Fig 4A ) . The immunogold-labeling analysis revealed that wild-type cells displayed gold particles on their surface ( white arrow ) , indicating expressed FlpV5 pilins assembled into the authentic pili ( Fig 4B ) . However , the transconjugated mutant cells ( Δtad123-FlpV5 ) rarely displayed gold particles and this phenotype was complemented in trans by the cosmid harboring the wild-type tad1 locus ( Fig 4B ) . Interestingly , aggregated gold particles were detected on the grid near bacterial cells ( orange arrow ) , suggesting FlpV5 proteins overexpressed under the arabinose induction did not assemble into pilus structure and exported from the bacterial cells . For quantitative analysis , we enumerated the gold particles associated with 5 bacterial cells per group ( total 15 bacteria/group ) from representative photos under x10 , 000 magnifications . The number of gold particles associated with the Δtad123 mutant cells was significantly scantier than that of the WT ( P < 0 . 01 ) ( Fig 4C ) . The decreased number of gold particles was significantly rescued by the tad1 operon complementation ( P < 0 . 001 ) ( Fig 4C ) . Supporting the results of the immunogold staining , immunofluorescence detection via confocal microscopy also revealed positive fluorescent signals for V5p in the FlpV5-expressing wild-type strain ( Fig 4D ) . In contrast , the Δtad123 mutant cells did not show any fluorescent signals , and this deficiency was complemented in trans by cosmids encoding the wild-type tad1 locus ( Fig 4D ) . Many broken filaments were found in the backgrounds of the EM photos , suggesting detachment of the brittle pilus structures during the sample preparation procedures . Taken together , the EM analyses demonstrated the obvious existence of extracellular Flp structures in wild-type V . vulnificus CMCP6 . RtxA1 is a crucial cytotoxin involved in cellular damage and necrosis of infected tissues [25–29] . We previously reported that host cell contact is required for RtxA1 production and cytotoxicity [25] . Thus , we speculated that attenuated adherence to host cells should hamper RtxA1 production and consequently attenuate host cell killing and tissue invasion . We performed a Western blot analysis to assess RtxA1 production after HeLa cell infection . The toxin was detected using an anti-GD domain antibody targeting the C-terminal fragment ( RtxA1-C; approximately 130 kDa ) , which is internalized in the host cell cytoplasm [30] . As a result of its impaired ability to maintain contact with its host cells , the Δtad123 mutant exhibited significantly lower toxin production compared with that of its parental strain ( Fig 5A ) . RtxA1 was secreted in a time-delayed manner in the mutant cells , and its secretion gradually increased over time . This delay was significantly rescued by the tad operon complementation ( Fig 5A ) . We next assessed the cytotoxicity of V . vulnificus toward HeLa cells over a time course . As shown in Fig 5B , the Δtad123 mutant cells showed significantly delayed cytotoxicity toward HeLa cells ( P < 0 . 001 ) , whereas the single and double mutants showed no changes ( P > 0 . 05 ) ( S3B Fig ) . The cytotoxicity of the Δtad123 mutant cells approached the wild-type level after 2 . 5 h of incubation ( Fig 5B ) . To investigate the possibility that this result might have been due to bacterial growth retardation in the HeLa cell culture medium , we examined the growth profiles of test strains in high-glucose Dulbecco’s Modified Eagle’s Medium ( DMEM ) ( S6 Fig ) . No growth difference was observed between the wild type and Δtad123 mutant strains . This delay in the cytotoxicity was significantly recovered by the in trans complementation with either the tad1 or the tad3 operons ( Fig 5C ) in the presence of tetracycline ( P < 0 . 01 for tad1 and P < 0 . 001 for tad3 ) . The Δtad1 mutation appeared to play the most dominant role in the inhibition of V . vulnificus adhesion to host cells ( S3A Fig ) . These findings , together with the LD50 results , highlight the significance of the three tad operons for the adhesion-related virulence of V . vulnificus . The contribution of each tad operon was investigated for the biofilm formation . The Δtad123 mutant showed significantly decreased biofilm formation compared with wild type strain ( P < 0 . 001 ) ( Fig 6A & 6B ) . The Δtad1 mutation appeared to play the most dominant role in the inhibition of V . vulnificus adhesion to host cells ( S3C Fig ) . The biofilm formation defect of the Δtad123 mutant was complemented in trans by the cosmid harboring each of wild type tad loci ( Fig 6A & 6B ) . Bacterial pili are used to attach to host cells and tissues , and confer invasive competence [16 , 31–34] . Furthermore , secretion of the RtxA1 cytotoxin , which is induced by adhesion of the bacterial cells to the host cells , is highly correlated with host tissue invasion [25] . To investigate the effects of mutation of the tad123 loci on V . vulnificus invasion , we carried out an in vivo invasion assay using a mouse ligated ileal loop infection model . The viable bacterial cells in the blood of the infected mice were quantified to evaluate tissue invasiveness of bacteria . The number of bacterial cells in the blood samples from the Δtad123 mutant-infected mice was significantly lower than that in the mice infected with the wild-type strain , even 6 hours post-infection ( Fig 7A ) ( P < 0 . 001 ) . In addition to the in vivo invasion assay , bacterial invasiveness was further confirmed using an in vitro intestinal epithelial barrier system . Polarized HCA-7 cells grown on Transwells were apically infected with bacteria , leading to physical apical-to-basolateral trans-epithelial migration of the bacteria . After 3 to 5 hours of incubation , we detected significantly fewer Δtad123 mutant cells than wild-type cells in the basolateral chamber ( Fig 7B ) ( P < 0 . 05 ) . The single and double mutants showed no changes ( S3D Fig ) . The cell count of the Δtad123 mutant reached that of the wild-type strain after 6 hours of incubation . The defect of trans-epithelial translocation of the Δtad123 mutant was complemented in trans by the cosmid harboring each of wild type tad loci ( Fig 7C ) . Taken together , the in vitro data and the in vivo invasion results demonstrate a function for Tad pili in conferring invasive competence to V . vulnificus . It is likely that the impaired invasion alone could not fully account for the higher LD50 observed for the Δtad123 mutant in the intraperitoneal infection model ( Table 1 ) ; therefore we hypothesized that mutation of the tad123 loci could compromise V . vulnificus survival in the bloodstream . To investigate this possibility , we monitored the number of viable bacteria in the blood over a time course following intraperitoneal ( i . p . ) or intravenous ( i . v . ) infection . Interestingly , the triple mutant cells were defective at surviving in mouse blood . Significantly fewer mutant cells were recovered from the blood of mice infected via both routes ( Fig 8A and 8B ) . In particular , very few mutant cells were detected after direct introduction of the bacteria into the blood stream via i . v . injection , resulting in an approximately 3-log reduction in the number of CFUs compared with the number of CFUs detected for the wild-type strain ( Fig 8A ) . The viable bacteria in the blood following i . p . infection should represent V . vulnificus cells that succeeded at both invasive translocation and resisting the serum bactericidal activities . On the other hand , the i . v . infection model shows how well the wild-type and mutant bacteria survived the serum bactericidal activities . These findings clearly indicate that Tad pili also play important roles in the survival of V . vulnificus in the blood stream . Serum bactericidal activity is an important innate immune defense against intravascular invasion by bacterial pathogens [35 , 36] . Thus , we hypothesized that Tad pili might play a protective role against serum components . To address this hypothesis , we tested the susceptibility of triple mutant cells to normal human serum ( NHS ) . Bacterial viability was assessed after 2 hours of incubation with different NHS concentrations . Notably , the bacteria lacking all three tad loci were extremely sensitive to human serum ( Fig 9A ) . For the Δtad123 mutant , 20% NHS led to dramatically decreased viability , and exposure to 40% NHS resulted in 4-log scale decrease of the viable cells . In contrast , the wild-type cells showed resistance against human serum ( Fig 9A ) . A time course assay with 60% NHS was carried out to further compare the serum resistance levels of the isogenic mutant and the wild-type strains . During the first hour of incubation , more than 3-log scale of the Δtad123 mutant lost viability ( Fig 9B ) . The single and double mutants showed no changes ( S3E Fig ) . The serum susceptibility of the Δtad123 mutant was complemented in trans by the cosmid harboring each of wild type tad loci ( Fig 9A & 9B ) . This result explains the significant difference in the survival rates observed between the wild type and Δtad123 mutant strains , and further confirms that Tad pili are required for V . vulnificus serum resistance . Given that the complement system , which is activated by pathogenic bacteria is primarily responsible for the direct killing of bacteria in NHS [37] , we further dissected the bactericidal activity of three complement pathways activated by V . vulnificus . Indeed , the use of heat-inactivated serum ( HIS ) lacking the lytic complement activity successfully rescued the viability of the mutant strain ( Fig 9C ) . This finding indicates that heat-labile complement proteins are responsible for the killing of the Δtad123 mutant cells in NHS . Complement activation occurs via one or more of three pathways: the classical pathway , the MBL/lectin pathway and the alternative pathway [35] . To identify which complement pathway was responsible for the death of the Δtad123 mutant cells in serum , we selectively blocked the specific complement activation pathways . Remarkably , inhibition of the alternative pathway completely ablated the complement-mediated killing activity . The survival of the Δtad123 mutant cells fully recovered to the wild-type level in bentonite-absorbed NHS ( Fig 9C ) . Furthermore , inhibition of either the classical pathway or the lectin pathway partially recovered the survival of the mutant cells ( Fig 9C ) . The serum susceptibility of the Δtad123 mutant was complemented in trans by the cosmid harboring each of wild type tad loci ( Fig 9C ) . Taken together , these results indicate that Tad pili likely play an important role in protecting V . vulnificus from direct complement-mediated bacteriolysis resulting predominantly from activation of the alternative pathway . To test whether serum susceptibility of the Δtad123 mutant is reverted in vivo by inhibition of complement system , we pretreated mice with a specific complement-inhibiting drug ( anti-C5 antibody ) approved by FDA [38] and then infected the mice with wild type or Δtad123 mutant cells . We monitored the number of viable bacteria in the blood in a time course following intraperitoneal infection . As shown in Fig 9D , the viable bacterial count of Δtad123 mutant could be rescued by the anti-C5 antibody treatment almost to the level of wild type strain . These data clearly indicate that reduced viability of the Δtad123 mutant is due to increased susceptibility to complement system in the mouse infection model . Given the innately lower complement level in mice compared with human [39] , the Tad pili system should play more dominant roles in the pathogenesis of human infections .
Host-pathogen interactions during microbial infections can be described as a dynamic battlefield where the microbe’s clever strategies for survival and multiplication confront the formidable host immune defenses . To investigate the virulence regulation of V . vulnificus during infection , we recently performed comparative genome-wide transcriptional analyses of cells grown in vitro and in vivo . A rat peritoneal infection model was used to simulate the physiological host milieu . Interestingly , among the newly identified in vivo-expressed candidate genes , tad1 was found to be highly upregulated in vivo ( unpublished data ) . The pathogenic potential of the tad1 cluster is also supported by previous reports of the ubiquity of the tad1 locus in sequenced virulent V . vulnificus strains [19–21] . Furthermore , it is notable that the genome of V . vulnificus CMCP6 contains three distinct tad loci , in which similar functional genes are organized in the same order and transcriptional orientation . In this study , our goals were to investigate why V . vulnificus CMCP6 has maintained three tad loci throughout evolution and how each tad operon contributes to V . vulnificus virulence and to determine whether all three tad operons are required for its virulence . By deleting each tad locus and complementing the deletion in trans , we attempted to address these questions ( at least in part ) and found that all three tad operons are required for the full virulence of V . vulnificus . Only complete abrogation of all three tad loci led to significantly decreased lethality in mice ( Table 1 ) . Based on animal and cell culture infection models coupled with molecular genetic analyses , we came to understand the coordinated contributions of the three V . vulnificus tad operons to host cell invasion as well as to survival of complement-mediated bacteriolysis . Deletion of all three tad loci impaired the adherence of the bacterial cells to the host cells ( Fig 2 ) , thus hampering RtxA1 cytotoxin production and delivery ( Fig 5 ) and , consequently , tissue invasion ( Fig 7 ) . These results corroborate our previous findings that host cell contact is required for V . vulnificus toxin secretion and pathogenicity [25] . The bactericidal action of serum is an important component of the host defense against bloodstream infections [35 , 36] . As most fatal cases of V . vulnificus infection result from septicemia , serum resistance is considered an essential feature for survival in the host environment . It is well documented that clinical V . vulnificus isolates have a significantly greater survival ability in human serum compared with that of environmental isolates [40 , 41] . Several mechanisms have been proposed to explain this phenomenon , the most significant of which may be differences in siderophore expression and/or capsule formation [40] . In the present study , we discovered a novel function of V . vulnificus Tad pili in conferring resistance to the complement-mediated bactericidal activity of its host . The ubiquity of the tad1 cluster in virulent V . vulnificus strains suggests that the surface expression of Tad pili may be another key determinant for the survival of V . vulnificus in host milieus , which could conceivably differentiate the clinical and environmental strains . Bacteria lacking Tad pili rapidly lost viability in serum via direct complement-mediated bacteriolysis , predominantly activated via the alternative pathway . The mechanism through which Tad pili protect bacteria from complement attack should be further studied . The poor immunogenicity of Flp pili could have something to do with the serum resistance . Given that the tad triple mutant lost its slime-like surface morphology ( which could be complemented in trans by cosmids harboring an individual tad operon ) , it is plausible that Flp pili could anchor secreted polysaccharides during formation of durable capsular lattice . Inhibition of the alternative complement pathway by the Flp pili might be related to the low immunogenicity of the structural pilin protein . To understand the poor recognition of Tad pili by the immune system , we analyzed the antigenicity and structural characteristics of Tad pilin using bioinformatics tools . After in silico prediction of the 3D structure of Tad pilin , we compared it with the orthologs from Aggregatibacter actinomycetemcomitans , which seem to have high functional similarity with that of V . vulnificus . Bordetella pertussis Fim2 and Escherichia coli CfaB ( S7 Fig ) . V . vulnificus Tad pilin was predicted to form an alpha helix that partially overlaps structurally with the A . actinomycetemcomitans Flp1 and Flp2 , which share the Flp common motif [8] , and B . pertussis Fim2 pilins , which are thought to contribute to the assembly of pilin monomers into the fimbrial ultrastructure . When compared with the immunogenic Fim2 and CfaB pilins , which function as vaccine candidates , Tad pilin appeared to be relatively hydrophobic , and only a small fraction contained the hydrophilicity required for antigenicity ( S8 Fig ) . The presence of pilus-like structures has been reported to be more closely associated with clinical isolates of V . vulnificus than with environmental strains [42] . Under SEM , we observed filamentous surface structures that extended from the wild-type cell bodies that were absent from the Δtad123 triple operon mutant cells ( Fig 3 ) . Interestingly , the presumable Tad pili structure became more elongated when the cells were grown in vivo , suggesting a pathogenic function during establishment of successful infections . This morphological change under in vivo culture conditions corroborates the previously suggested hypothesis that the Tad pili significantly contribute to V . vulnificus pathogenicity [12] . The thickness and size of the putative pili structures were quite elusive , unlike other Tad/Flp pili such as those of Aggregatibacter ( previously Actinobacillus ) [6–9] . To confirm the cell surface expression of Tad pili , we performed immunogold-labeling and fluorescence staining . To the best of our knowledge , no specific ultrastructural analysis of V . vulnificus Tad pili and their molecular pathogenic roles have been previously reported . While performing these experiments , we failed to raise functional antibodies against the V . vulnificus Flp pilin , presumably because of its very low hydrophilicity and immunogenicity as addressed above . To overcome this obstacle , we first fused a V5 tag sequence to the N- or C-terminus of the flp-1 gene on the chromosome . However , we could not detect any signal from chromosomally V5-tagged Flp in a dot blot analysis using an anti-V5 antibody . The V5-tagged Flp might have been structurally defective , leading to ineffective assembly into pili structures . Alternatively , the engineered strains may have incurred polar effects on downstream gene expression during double crossover homologous recombination . We subsequently constructed a V5-tagged Flp overexpression system encoded on the multicopy pBAD24 plasmid ( S5 Fig ) . Our hypothesis was that , when expressed under the control of an arabinose-inducible promoter , some proportion of the overexpressed V5-tagged Flp proteins might be randomly incorporated during assembly of the chromosomally expressed native pilin subunits . As expected , we could detect positive signals from V . vulnificus cells overexpressing the Flp-V5 fusion protein in both experiments ( Fig 4 ) . However , only a fraction of the transconjugants carrying the overexpression plasmid could be stained with immunogold or fluorescence approaches , suggesting minimal incorporation of V5-tagged Flp expressed from the single-copy chromosomal locus possibly due to structural deformations by addition of the V5 tag . Taken together , our results provide new insights into the pathogenic significance of Tad pili in V . vulnificus CMCP6 . The Tad provide pathogenic V . vulnificus with the ability to adhere to and invade host cells and shield the cells against complement-mediated bacteriolysis inside the host . During these two distinct stages of infection , the Tad pili-mediated host cell adhesion and evasion of the anti-complement activity inside host provide , respectively , the signal required to induce expression of the potent RtxA1 cytotoxin and the ability of V . vulnificus to robustly grow in vivo .
Bacterial strains and plasmids used in this study are listed in Table 2 . V . vulnificus CMCP6 is a highly virulent clinical isolate from the Chonnam National University Hospital , South Korea [5 , 25] . V . vulnificus and E . coli were grown in 2 . 5% NaCl heart infusion ( HI ) and in Luria-Bertani ( LB ) medium , respectively . Antibiotics were used as previously described [43] . We constructed in-frame single , double , and triple deletion mutants of entire genes in the tad1 , tad2 and tad3 loci by the allelic-exchange method . We designed two sets of primers to amplify ~1-kb DNA fragments in the upstream or downstream region of each tad operon ( S1 Table ) . The primers were synthesized with overhangs recognized by specific restriction enzymes ( REs ) . The upstream and downstream amplicons of each tad operon were ligated by cross-over PCR to produce a 2-kb fragment [44] . The fusion fragments were digested with appropriate REs and subcloned into pDM4 suicide vector . The resulting recombinant vector was transformed into E . coli SM10 λ pir and subsequently transferred into V . vulnificus CMCP6 by conjugation . Stable CmR transconjugants were selected on Vibrio-selective thiosulfate citrate bile salt sucrose ( TCBS ) agar plate containing Cm . Plating of the transconjugants on 2 . 5% NaCl HI agar plate containing 10% sucrose was performed to select clones that experienced second homologous recombination events forcing excision of the vector sequence and leaving only mutated or wild-type allele of the genes . Each in-frame deletion mutation was confirmed by PCR with the chromosomal DNA from the respective mutant as template . For the use in genetic complementation experiments , we screened cosmid clones that contain intact tad1 , tad2 or tad3 operon from a pLAFR3 cosmid library of V . vulnificus CMCP6 [25 , 45] . The selected cosmid library clone containing an individual tad operon was transferred to the triple tad operon deletion mutant by triparental mating with a conjugative helper plasmid pRK2013 . The transconjugants were screened on TCBS agar plates containing tetracycline and confirmed by PCR . To fulfill molecular Koch’s postulates , we performed a complementation analysis . The Δtad123 mutant was separately complemented with an individual cosmid clone harboring each tad operon . The restoration of tad operon expression was confirmed by the conventional RT-PCR ( S4 Fig ) . The transcriptional levels of the three structural flp genes , which encoded the major structural components of Flp pili , were measured by conventional and real-time RT-PCR . gyrA was chosen as the reference gene forn the qRT-PCR as previously reported [45] . Forward and reverse primer pairs were designed and are provided in S2 Table . Total RNA was isolated from log-phase bacterial cells grown in the rat peritoneal cavity or in 2 . 5% NaCl HI broth using the RNeasy minikit ( Qiagen ) . One microgram of purified RNA was converted into cDNA using QuantiTect Reverse Transcription Kit ( Qiagen ) in accordance with the manufacturer’s protocol . qRT-PCR was performed to quantify each target transcript using QuantiTect SYBR green PCR kit ( Qiagen ) . The relative gene expression was normalized to the expression of gyrA using the threshold cycle ( ΔΔCT ) method [46] . For conventional RT-PCR , 16S rRNA was used as the internal standard . After 25 to 35 cycles , the amplicons were separated on 2% ( wt/vol ) agarose gels and stained with ethidium bromide . The transcription levels of flp-1 under iron-limited and solid surface growth conditions were also analyzed by qRT-PCR . For the iron limitation experiment , dipyridyl ( Sigma-Aldrich ) was added to the 2 . 5% NaCl HI broth at a final concentration of 80 μM for iron limitation . All animal experimental procedures were performed with approval from the Chonnam National University Institutional Animal Care and Use Committee under protocol CNU IACUC-H-2015-44 . Animal research facility maintenance and experimental procedures were carried out strictly keeping the guideline in the Animal Welfare Act legislated by Korean Ministry of Agriculture , Food and Rural Affairs . The intraperitoneal 50% lethal dose ( i . p . LD50 ) of V . vulnificus was determined using 7-week-old , randomly bred specific-pathogen-free ( SPF ) female ICR mice ( Daehan Animal Co . , Daejeon , South Korea ) . Five mice per group were intraperitoneally inoculated with 10-fold serial dilutions of fresh bacterial suspensions ( 109 to 105 CFU/mouse ) . The intragastric ( i . g . ) LD50 was determined using six-day-old randomly bred SPF CD-1 suckling mice ( Daehan Animal Co . , Daejeon , South Korea ) . Seven mice per group were intragastrically administered with 10-fold serial dilutions of fresh bacterial suspensions containing 0 . 1% Evans blue ( Sigma-Aldrich ) to ensure correct i . g . administration . The control animals received 100 μl of PBS containing 0 . 1% Evans Blue . The challenged mice were monitored for 48 h . LD50 values were calculated based on probit analysis , using IBM SPSS 21 . 0 software ( IBM ) . DNA fragments of the structural flp-1 pilus gene without its stop codon were amplified and subcloned into the pBAD24 vector . Subsequently , double-stranded oligonucleotides encoding the V5 peptide , “GGTAAGCCTATCCCTAACCCTCTCCTCGGTCTCGATTCTACGTAA” , were fused to the C-terminus of the flp-1 gene in the pBAD24-Flp plasmid . At the end of the V5 sequence , a TAA codon was added to terminate translation . The pBAD24 plasmids containing the Flp-V5 fusion protein were transformed into E . coli DH5α competent cell . The sequence of the cloned fragment was confirmed by DNA sequencing . The resulting vectors were transferred into V . vulnificus via triparental mating with a conjugative helper plasmid pRK2013 . The transconjugants were screened on 2 . 5% NaCl HI agar plates containing ampicillin . V . vulnificus strains carrying pCMM2103 ( pBAD24::Flp-V5 ) were grown for 4 h on 2 . 5% NaCl HI agar plates containing ampicillin . Flp-V5 expression was induced for 4 h via addition of 0 . 1% L-arabinose . The cell suspensions were applied to nitrocellulose membrane and fixed with 4% paraformaldehyde for 20 min . The membrane was blocked for 1 h using 5% skim milk in PBS and then incubated with anti-V5 polyclonal antibodies ( diluted 1:5000 , Abcam ) for 2 h . After washing , the membrane was developed with HRP-conjugated goat anti-rabbit IgG secondary antibody ( Dako ) . Stained dots on a white background indicated positive results . To compare surface structure of the wild-type , Δtad123 and Δtad123 ( pLAFR3::tad1 ) , we performed SEM observation . Bacteria were grown in vivo using a rat peritoneal infection model as previously described [45] . To minimize shearing force during bacterial preparations , all procedures were carefully performed . And we also applied osmotic adaptation with fixative by 3 staged applying a step-down approach from 2 . 5% NaCl containing fixative to 0 . 9% and 0% NaCl containing solution with a gentle agitation . Bacterial cells were fixed at room temperature for 4 h in a fixation solution containing 0 . 5% glutaraldehyde and 4% paraformaldehyde in 0 . 05 M sodium cacodylate buffer ( pH 7 . 2 ) . After three washes with 0 . 05 M cacodylate buffer , all of the samples were mounted on nickel grids coated with carbon film ( 150 mesh ) ( EMS , USA ) . After blocking nonspecific binding sites with 1% BSA in EM-immunogold ( EMG ) buffer ( 0 . 05% Tween , 0 . 5 M NaCl , 0 . 01 M phosphate buffer , pH 7 . 2 ) , the samples were incubated at 4°C for 24 h with anti-V5 tag monoclonal antibody ( ab27671 , Abcam , UK ) at a 1:20 dilution at 4°C , followed with incubation for 1 h in goat anti-rat antibody ( 1:50 ) conjugated to 6 nm gold particles . The grids were washed in EMG buffer , PBS , and distilled water and stained for 12 min with 4% uranyl acetate in deionized distilled water . The surfaces of all of the samples were observed using a field emission scanning electron microscope ( Helios G3 CX , FEI Co . , Hillsboro , Oregon , USA ) at 1 kV acceleration with TED mode . A drop of V . vulnificus cell suspension was applied to a nickel grid coated with carbon film for 1 min . Because of its structural fragility of V . vulnificus , we prepared the bacterial sample with very gentle manner such as limited frequencies of pipetting and washing processes . Moreover , to minimize the insults from the critical points drying , we firstly fixed the in vivo grown cells with osmolarity-modified fixative ( which contains 2 . 5% NaCl ) and changed the solution to conventional fixative for SEM study ( 0 . 5% glutaraldehyde and 4% paraformaldehyde in 0 . 05 M sodium cacodylate buffer ( pH 7 . 2 ) ) under room temperature . Moreover , to reduce damages from electron and enhance the resolution beam during SEM analysis , we used the focused ion scanning electron microscope ( FIB ) . Subsequently , the samples were incubated with the anti-V5 polyclonal antibody ( diluted 1:20 , Abcam ) and labeled with 5-nm colloidal gold-conjugated goat anti-rabbit IgG secondary antibody ( diluted 1:20 , BritishBioCell , UK ) . V . vulnificus cells were fixed in a fixation solution containing 0 . 5% glutaraldehyde and 4% paraformaldehyde in 0 . 05 M sodium cacodylate buffer ( pH 7 . 2 ) at room temperature for 4 h . After three washes with 0 . 05 M cacodylate buffer , all of the samples were mounted on nickel grids coated with carbon film ( 150 mesh ) ( EMS , USA ) . After staining with 2% uranyl acetate , the samples were examined with a transmission electron microscope ( TEM ) ( JEM-1400; JEOL Ltd . , Japan ) at 80 kV acceleration . For quantification and statistical analysis of immunogold-conjugated observation by EM , we counted gold particles in obtained EM photos . To get objective results , three different researchers independently counted gold dots associated with 5 bacterial images under x10 , 000 magnification field . To induce V5-tagged pilin expression , mid-log phase V . vulnificus cells were grown for 4 h on 2 . 5% NaCl HI-ampicillin agar plates supplemented with 0 . 1% L-arabinose . Bacterial pellet was then gently suspended in PBS buffer . The induced bacterial cells were directly immobilized on poly-L-lysine-coated coverslips . Samples were fixed with 4% formaldehyde for 30 min and then incubated with primary anti-V5 antibodies ( 1:300 ) for 2 h . After three washes with PBS buffer , the cells were incubated for 1 h with a Texas Red-conjugated anti-rabbit secondary antibody ( Molecular Probes ) and DAPI ( Invitrogen ) . The samples were observed under a laser scanning confocal microscope ( LSM 510 , Zeiss , Oberkochen , Germany ) , and the obtained images were analyzed by using the ZEN Lite software ( Zeiss , Oberkochen , Germany ) . We quantitatively analyzed bacterial adhesion to host cell by using viable cell counting and microscopic observation . HeLa cell monolayers ( 5x105/well ) were grown on 24 well plates ( SPL , cat#30024 ) and then infected for 45 minutes with log-phase V . vulnificus cells at MOI 250 . The monolayer was washed twice with PBS to remove non-adherent bacteria . The wells were then suspended with 200 μl of PBS containing 0 . 1% Triton and incubated for 10 minutes at room temperature . The number of colony forming units ( CFU ) that adhered to Hela cells was enumerated by ten fold serially diluting in PBS and spotted on HI agar plates . For microscopic observation , the cells were fixed in methanol after the PBS washing and stained with 0 . 1% Giemsa solution ( Sigma-Aldrich ) . The number of V . vulnificus cells that adhered to single HeLa cells was counted under a light microscope at 400× and 1 , 000× magnification ( Nikon Eclipse 50i , Japan ) . To induce the biofilm formation , freshly cultured V . vulnificus cells ( 5x105 CFU/ml ) were applied into each well of 24 well plates ( SPL , cat#30024 ) . The plates were further incubated at 37°C for 24 hours and then gently washed once with PBS . The wells were stained with 200 μl of 0 . 3% crystal violet for 15 minutes and gently washed with PBS . The stained biofilm was extracted with 200 μl of 100% ethanol and two fold diluted with PBS to measure the absorbance at 595 nm by a microplate reader ( Molecular Devices Corp . , Menlo Park , CA ) . To acquire the confocal microscopic images of biofilm , the biofilm was induced in 4 Well Cell Culture Slide ( SPL , cat#30124 ) for 24 hours and then gently washed once with PBS . The biofilm was then stained with acridine orange and observed by a confocal microscope as previously reported [47] . The samples were observed under a LSM510 confocal microscope ( Zeiss , Oberkochen , Germany ) , and the obtained images were analyzed by using the ZEN 2012 x32 blue software . To detect RtxA1 , HeLa cells grown in 6-well plates were infected for 35 and 45 min with log-phase V . vulnificus strains at an MOI of 100 . The bacteria attached to the HeLa cells were lysed using a lysis buffer ( Cell Signaling ) , followed by concentration using an Amicon Ultra-0 . 5 centrifugal filter apparatus ( Merck KgaA ) . The samples were then subjected to 10% SDS-PAGE . RtxA1 proteins were detected using an anti-GD domain antibody ( RtxA1-C , a band of approximately 130 kDa ) [30] . To determine the effect of tad operon mutations on cytotoxicity against HeLa cells , we performed the lactate dehydrogenase ( LDH ) release assay as previously described [43] . Bacterial cells that translocated from the intestine to the bloodstream were measured as previously described [48] . Seven-week-old randomly bred SPF female ICR mice were starved for 16 h . The ileum was tied off in a 5-cm segment and log-phase V . vulnificus cells ( 4 . 0 × 106 CFU/400 μl ) were inoculated into the ligated segment . Blood samples were acquired from the infected mice via cardiac puncture . The number of viable bacterial cells was counted by plating on 2 . 5% NaCl HI agar plates . In parallel , viable V . vulnificus cells in the ligated ileal loops were also enumerated by plating on TCBS agar plates . Polarized HCA-7 cells grown in Transwell filter chambers ( 8 μm pore size; CoStar , Cambridge , MA , USA ) were apically exposed to log-phase V . vulnificus cells at an MOI of 5 . Invasiveness was determined by measuring the number of bacterial cells that translocated from the apical to basolateral compartment of the Transwells . Viable bacterial cells were counted by plating on 2 . 5% NaCl HI agar plates . In vivo growth of V . vulnificus was measured using the dialysis tube implantation model as previously described [48] . CelluSep H1 dialysis tubing ( MWCO 12 , 000~14 , 000; Membrane Filtration Products , Inc . Texas ) was incubated with PBS overnight . The dialysis tube was disinfected with 70% alcohol for 1 h and washed three times with sterile PBS before use . Seven-week-old female Sprague Dawley ( SD ) rats ( DBL . Co . Ltd , Daejeon , Korea ) were anesthetized with a mixture of 10% Zoletil and 5% Rumpun dissolved in PBS . Three 10-cm dialysis tubes containing 2 ml of 5 × 105 CFU/ml V . vulnificus cells were surgically implanted into the rat peritoneal cavity . The bacterial growth at each time point was analyzed using three rats . Culture samples were harvested for viable cell counting on 2 . 5% NaCl HI agar plates 2 , 4 and 6 h after implantation . To assess bacterial growth in blood , seven mice per group were intravenously ( i . v . ) or i . p . injected with 100 μl of 5 × 105 CFU cells that had been incubated in the rat peritoneal cavity for 6 h for induction of tad1 locus expression and in vivo adaptation . Blood samples were acquired from the infected mice via cardiac puncture at the indicated times . Viable bacterial cells were counted by plating on 2 . 5% NaCl HI agar plates . Log-phase V . vulnificus cells ( 1 . 0 × 107 CFU/10 μl ) were added to 200 μl of PBS containing various NHS concentrations . The samples were incubated at 37°C for appropriate times . Viable bacterial cells were counted by plating on 2 . 5% NaCl HI agar plates . To block activation of the classical pathway , NHS was pretreated with 10 mM ethylene glycol-bis ( 2-aminoethylether ) -N , N , N′ , N′-tetraacetic acid and 5 mM MgCl2 for 30 min at 37°C ( EGTA/Mg2+ ) [49] . To prepare the MBL-depleted serum , mannose-agarose beads ( Sigma-Aldrich ) were washed three times with sterile PBS and then incubated with NHS at 4°C for 1 h with gentle rotation [50] . The alternative pathway is inhibited via properdin absorption with bentonite [51] . 10 mg of bentonite was washed three times with PBS and incubated with NHS at 37°C for 10 min to absorb the properdin . Seven-week-old randomly bred SPF female ICR mice were intraperitoneally administered with 40 mg/kg/day of anti-C5 monoclonal antibody ( Hycult BiotechInc , Pa , USA ) or isotype control two times in two-days interval following manufacturer’s instruction . Twenty-four hours after the second administration of the anti-C5 , mice were intraperitoneally infected with 5 x 105 CFU cells that had been incubated in the rat peritoneal cavity for 6 h for in vivo adaptation . Blood samples were acquired from the infected mice by eye puncture in a time course . Viable bacterial cells were counted by plating on 2 . 5% NaCl HI agar plates . The results are expressed as the mean ± standard error of the mean ( SEM ) unless otherwise stated . Each experiment was repeated a minimum of three times , and the results from representative experiments are shown . Statistical analyses were performed using the Prism 6 . 00 software for Windows ( GraphPad software , San Diego , CA ) . Multiple comparisons were performed using Student’s t test and analysis of variance ( ANOVA ) followed by Bonferroni post hoc tests . P-values < 0 . 05 was considered statistically significant . | Vibrio vulnificus is so called “flesh eating bacterium” causing fatal sepsis accompanying destruction ( necrosis ) of soft tissue . The fatal infection occurs after eating contaminated seafood such as oysters or exposure of pre-existing wounds to seawater . Here we show an important bacterial factor that should be used to adhere to human cells and avoid from host immune system . It is very thin thread-like projections from bacterial surface called Tad ( tight adhesion ) pili . V . vulnificus interestingly harbors three Tad gene genetic loci called operons . To understand the roles of the three Tad operons in the pathogenesis , we deleted each of those three gene loci . Employing mouse infection models coupled with molecular genetic analyses , we demonstrate here that all those three Tad operons are cooperatively required for V . vulnificus pathogenicity . More specifically , the thin pili threads , hardly observed even under electron microscope , contribute to host cell and tissue invasion , survival in the blood , and resistance to killing activities of serum . These findings explain why V . vulnificus has propensity for invading into blood stream from intestine and growing well in the blood resisting against protective immune responses . | [
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"c... | 2019 | A stealth adhesion factor contributes to Vibrio vulnificus pathogenicity: Flp pili play roles in host invasion, survival in the blood stream and resistance to complement activation |
Non-coding RNAs are much more common than previously thought . However , for the vast majority of non-coding RNAs , the cellular function remains enigmatic . The two long non-coding RNA ( lncRNA ) genes DLEU1 and DLEU2 map to a critical region at chromosomal band 13q14 . 3 that is recurrently deleted in solid tumors and hematopoietic malignancies like chronic lymphocytic leukemia ( CLL ) . While no point mutations have been found in the protein coding candidate genes at 13q14 . 3 , they are deregulated in malignant cells , suggesting an epigenetic tumor suppressor mechanism . We therefore characterized the epigenetic makeup of 13q14 . 3 in CLL cells and found histone modifications by chromatin-immunoprecipitation ( ChIP ) that are associated with activated transcription and significant DNA-demethylation at the transcriptional start sites of DLEU1 and DLEU2 using 5 different semi-quantitative and quantitative methods ( aPRIMES , BioCOBRA , MCIp , MassARRAY , and bisulfite sequencing ) . These epigenetic aberrations were correlated with transcriptional deregulation of the neighboring candidate tumor suppressor genes , suggesting a coregulation in cis of this gene cluster . We found that the 13q14 . 3 genes in addition to their previously known functions regulate NF-kB activity , which we could show after overexpression , siRNA–mediated knockdown , and dominant-negative mutant genes by using Western blots with previously undescribed antibodies , by a customized ELISA as well as by reporter assays . In addition , we performed an unbiased screen of 810 human miRNAs and identified the miR-15/16 family of genes at 13q14 . 3 as the strongest inducers of NF-kB activity . In summary , the tumor suppressor mechanism at 13q14 . 3 is a cluster of genes controlled by two lncRNA genes that are regulated by DNA-methylation and histone modifications and whose members all regulate NF-kB . Therefore , the tumor suppressor mechanism in 13q14 . 3 underlines the role both of epigenetic aberrations and of lncRNA genes in human tumorigenesis and is an example of colocalization of a functionally related gene cluster .
Non-coding RNAs ( ncRNA ) are emerging as an important factor for the aberrant gene expression associated with cancer [1] . NcRNA genes are mostly involved in the regulation of target gene function [2] . Their mode of action varies from posttranscriptional regulation ( i . e . miRNA genes ) [3] to modulation of transcription in cis or in trans , either via competition or blockage mechanisms [4] , by acting as chromatin organizers that target chromatin modifying factors ( e . g . HOTAIR , KCNLQT1 and XIST ) [5] . NcRNA genes can even act as enhancers themselves [6] . However , for the vast majority of ncRNAs , the specific cellular function remains enigmatic . Two long ncRNA ( lncRNA ) genes DLEU1 ( Gene ID: 10301 ) and DLEU2 ( Gene ID: 8847 ) map to a critical region at chromosomal band 13q14 . 3 that is recurrently deleted in hematopoietic and solid tumors ( Figure 1 ) [7]–[10] . DLEU2 splicing variants have been suggested to represent the primary transcripts ( pri-miR ) of miR-15a ( Gene ID: 406948 ) and miR-16-1 ( Gene ID: 406950 ) because of their localization and coregulation [11] . MiR-15/16 are among the most strongly and ubiquitously expressed miRNA genes in human cells [12] and appear to exert a crucial role in tumorigenesis [13] . In chronic lymphocytic leukemia ( CLL ) , more than 50% of cases harbor a deletion of the critical region at 13q14 . 3 [7] , [14] . Loss of 13q14 . 3 is also the most common aberration in the CLL precursor monoclonal B-cell lymphocytosis ( MBL ) [15] . The tumor suppressor mechanism at 13q14 . 3 is multifactorial and is likely to involve other genetic elements than miR-15a/16-1 , since ( i ) knocking out miR-15a and miR-16-1 in mice leads to a lymphoproliferative disease [16] , but rare cases of CLL have been described where the deletion at 13q14 . 3 does not encompass the miRNA genes [10] , [17] , [18] . ( ii ) Deletion of a larger region at 13q14 . 3 including adjacent regions in addition to miR-15a/16-1 leads to more aggressive disease in mice and humans that more frequently resembles a CLL phenotype [16] , [18]–[20] . ( iii ) Familial CLL can be associated with deletion of DLEU7 ( Gene ID: 220107 ) localized more proximal in 13q14 . 3 than with miR-15a/miR-16 [21] . It remains unclear how the miRNAs and the other candidate tumor suppressor genes are functionally inactivated in CLL . Sequence mutations in the miRNA genes that lead to aberrant processing from primary transcripts occur only very rarely in CLL [18] , [22]–[24] . In addition , the miRNA genes may be more commonly affected by a processing defect ( Allegra et al . , manuscript submitted ) . No point mutations have been found in the other candidate genes at 13q14 . 3 [25] . However , in support of their role as tumor suppressors , the two miRNA genes and the other candidate tumor suppressor genes in the region are downregulated in CLL cells compared to non-malignant B-cells [10] , [13] , [26] , [27] . Thus , epigenetic aberrations play a major role in the pathomechanism of CLL [28]–[30] and not only the genes but also regulatory sequences ( e . g . CpG islands ) are conserved in the mouse [31] . Accordingly , we have investigated the epigenetic features of the critical region at 13q14 . 3 in detail to dissect the underlying regulatory network . Interestingly , two genes in the vicinity of the critical 13q14 . 3 region are imprinted ( RB1 , Gene ID: 5925 and HTR2A , Gene ID: 3356 ) [32] , [33] . Parental imprinting is a mechanism where epigenetically regulated lncRNA genes control the expression of genes in cis . Similar to an imprinting mechanism , we recently found a complex epigenetic regulatory mechanism that involves asynchronous replication timing and monoallelic expression in non-malignant B-cells isolated from healthy donors [34] , [35] . In addition , the copy of an epigenetic aberration to the homologous chromosome could account in CLL for the observed high incidence of loss of heterozygosity at 13q14 . 3 without loss of genetic material or the occurrence of mutations [10] , [36] . Incomplete inactivation by epigenetic markers could also explain the frequent occurrence of genetic loss of the second copy of 13q14 . 3 in clonal evolution [34] , [37] . In summary , these findings together with the transcriptional deregulation in CLL cells made it very likely that the function of the tumor suppressor mechanism at 13q14 . 3 is lost through epigenetic aberrations . We therefore characterized the epigenetic makeup of 13q14 . 3 in a thoroughly selected cohort of CLL patients ( n = 143 , see Table S1 for patient characteristics ) , and found significant DNA-demethylation of two specific sequences within conserved CpG islands at the transcriptional start sites ( TSS ) of DLEU1 and DLEU2/Alt1 ( ENST00000425586 ) . This epigenetic aberration was correlated with transcriptional deregulation of the neighboring candidate tumor suppressor genes . Such a coregulation in cis of several tumor suppressor genes points to a functionally related gene cluster that is involved in the same cellular pathway . In support of this view we found that the 13q14 . 3 candidate tumor suppressor genes KPNA3 ( Gene ID: 3839 ) , RFP2 ( Gene ID: 10206 ) and C13ORF1 ( Gene ID: 57213 ) are positive regulators of NF-kB activity . In addition , we performed an unbiased screen of 810 human miRNAs and showed the miR-15/16 family of genes to be the strongest inducers of NF-kB activity . As one major function of NF-kB in CLL has been shown to be prevention of apoptosis [38]–[40] , our findings contrast with the supposed role of the 13q14 genes as tumor suppressor genes . Based on these results it will be tempting to dissect the exact molecular link between 13q14 . 3 and NF-kB in CLL . In summary , the tumor suppressor mechanism at 13q14 . 3 is orchestrated by two epigenetically controlled lncRNA genes regulating a cluster of genes that impact on NF-kB .
For a comprehensive characterization of the epigenetic make-up of the critical region at 13q14 . 3 in CLL cells , DNA-methylation of the whole region ( from ITM2B Gene ID: 9445 to DLEU7 ) was quantified in primary patient and healthy proband samples ( Table S1 for patient and Table S2 for healthy proband characteristics ) . In addition , the CpG islands of the candidate genes were analyzed for changes in histone modifications . Applying five different techniques for detection and quantification of DNA-methylation [41]–[45] , we found that two regions displayed significantly different DNA-methylation patterns in CLL cells compared to non-malignant B-cells ( Figure 1 , lanes 1–3; Figures S1 , S2 ) . The differentially methylated regions are localized within the CpG islands D and E at the transcriptional start sites of the lncRNA genes DLEU1 ( region “D6” ) and the DLEU2 variant Alt1 , respectively ( region “E6”; Figure 1 , Figure S1 for validation and S2A , S2B for detail ) . In a region of chromosomal band 3q25 . 33 that shows a genetic makeup similar to 13q14 . 3 , no aberrant DNA-methylation could be detected ( Figure S2C , S2D ) . Also no differential DNA-methylation was found in CLL at the retinoblastoma tumor suppressor gene RB1 at 13q14 . 3 that has been implicated in the pathomechanism of the disease [16] , [18] , or the DLEU7 gene ( Figure S2D , S2E ) [46] . To corroborate the finding of a relaxed chromatin conformation in CLL , the CpG islands C , D and E were analyzed for the presence of histone modifications that correlate with open chromatin and active transcription ( dimethylation of H3K4 , “H3K4me2” ) [47] or with epigenetic mechanisms leading to transcriptional inactivation ( macroH2A ) [48] . In line with a more relaxed chromatin in CLL cells as compared to non-malignant cells , H3K4me2 showed significantly more enrichment , while less chromatin was precipitated that carried the macroH2A modification ( Figure 1 , lanes 4 and 5 ) . Therefore unexpectedly , active chromatin marks were detected in CLL cells at 13q14 . 3 instead of repressive epigenetic marks that are characteristic for tumor suppressor inactivation . In order to test whether aberrant DNA-methylation is independent of prognostic and cytogenetic characteristics and thus a unifying feature of CLL , we analyzed a larger cohort of CLL patients ( Figure 2 , Table S1 ) . DNA-hypomethylation was independent of 13q14 . 3 gene dosage and was also not a result of the advanced age of the patients ( Figure 2B and 2C , compare age-matched controls; characteristics are listed in Table S2; for Mann-Whitney Rank Sum Test see Table S6 ) . Interestingly , DNA-methylation was significantly retained in CLL cells with a deletion of 11q22-q23 covering the ATM ( Gene ID: 472 ) gene , and the most pronounced loss of DNA-methylation was found in patients with a deletion of TP53 ( Gene ID: 7157; Figure 2B and 2C ) . It can be speculated that the DNA-damage repair function of the ATM kinase could be involved in aberrant DNA-demethylation [49] or that a defect in 11q could be epistatic to loss of function of 13q14 . 3 [50] , but this needs to be shown in further analyses . Finally , levels of DNA-methylation were not significantly correlated with mutation status of the immunglobulin heavy chain variable segment genes ( IGHV ) , an important prognostic marker in CLL ( Figure S3A ) [51] , or with overall survival ( Figure S3B and S3C ) , implying that DNA-hypomethylation is present in CLL patients from all prognostic subgroups . In order to complement the single time point analyses of DNA-methylation with assessment of the dynamic changes over time , we analyzed peripheral blood mononuclear cell ( PBMC ) samples collected from patients at different time points during the course of the disease ( Figure S3D ) . Intriguingly , 4/10 CLL PBMC samples ( P7-P10 ) displayed more DNA-hypomethylation at 13q14 . 3 than would be expected from the content of CLL cells within the PBMC sample . These findings suggest that DNA-demethylation at 13q14 . 3 could be an ongoing process in CLL and should also be studied as a marker for imminent disease progression . In summary , DNA-methylation at 13q14 . 3 was aberrantly lower in 58 of 61 patients ( 95% ) compared to non-malignant B-cells ( Figure 2D ) , proposing that DNA-hypomethylation at 13q14 . 3 seems to be a universal feature of CLL . Next we investigated the functional impact of the epigenetic aberrations in 13q14 . 3 . As reported previously , the protein-coding and the miRNA candidate tumor suppressor genes ( including their host gene DLEU2; [11] ) in the critical region are downregulated in CLL cells ( Figure 3A and 3B ) [26] . In contrast , the lncRNA genes DLEU1 and variant DLEU2/Alt1 that display DNA-hypomethylation at their 5′ ends are significantly upregulated in CLL cells ( Figure 3C ) . To exclude bias caused by the influence of more complex interrelations e . g . by deletion of the critical region , we focused on samples with retention of both copies of 13q14 . 3 . We found a significant inverse correlation of gene expression of the lncRNA genes DLEU1 and the DLEU2 variant Alt1 [52] with DNA-methylation levels in regions D6 and E6 that are localized at their transcriptional start sites . The Pearson correlation coefficient for DLEU2/Alt1b with D6 was R = −0 . 33 ( p = 0 . 022 ) and for DLEU1 with E6 the coefficient R = −0 . 28 ( p = 0 . 044; see Figure 3E , for correlation coefficients see panels F , G ) . This suggests the direct regulation of DLEU1 and DLEU2/Alt1 by DNA-methylation . In contrast , expression of the protein-coding genes in the region and the miR-15a/-16-1 host gene DLEU2 were positively correlated with DNA-methylation levels ( Figure 3D; correlation coefficients F , G ) , suggesting an indirect regulation by DNA-demethylation e . g . via the lncRNA genes . Levels of mature miR-15a and miR-16 showed no significant correlation with DNA-methylation levels , probably because they are subject to additional posttranscriptional deregulation ( Allegra et al . , manuscript submitted ) . Differences in DNA-methylation supposedly reflects differential binding of transcription factors , and we comparatively analysed the sequences at D6 and E6 for binding motifs of transcription factors by comparing it to the TRANSFAC database using PATCH ( PatchTM public 1 . 0 , http://www . gene-regulation . com/cgi-bin/pub/programs/patch/bin/patch . cgi ) . Intriguingly , a number of transcription factor binding motifs are present both in the D6 and E6 sequence , further suggesting that these sequences might be regulated by similar pathways ( Table S3 ) . In order to understand how DNA-demethylation of D6 and E6 would impact on transcriptional deregulation of 13q14 . 3 , we first tested 16 cell lines for presence of DNA-methylation at 13q14 . 3 ( Figure S4A , S4B ) and whether DNA-demethylation results in transcriptional deregulation of 13q14 . 3 candidate genes . Only Jurkat cells showed DNA-methylation in both loci and could be DNA-demethylated both at D6 or E6 ( Figure S4A–S4F ) . Downregulation of the protein-coding candidate genes detected in CLL cells could not be reproduced in Jurkat cells in-vitro , probably because either the cellular system ( T-cells ) or the treatment does not faithfully reproduce the complex in-vivo situation ( Figure S4F ) . Interestingly , the levels of mature miR-15a and miR-16 also remained unchanged , which is in line with a recent report where incubation of CLL cells with a inhibitor of histone deacetylases ( HDACi ) led to upregulation of miR-15a and miR-16-1 in only 35% of patient samples [53] . These findings suggest that the miRNA genes are regulated at the post-transcriptional level in the majority of CLL patients ( Allegra , manuscript submitted ) . However , as expected we could show that both lncRNA genes DLEU1 and DLEU2/Alt1 were upregulated in Jurkat cells upon DNA-demethylation in-vitro ( Figure S4F ) , underlining that their transcriptional activity depends on levels of DNA-methylation . In order to test the functional relevance of the hypomethylated DNA-sequences , their impact on the expression of luciferase reporter constructs was quantified . The two sequence elements D6 and E6 completely lost their capacity to activate transcription when they were in-vitro DNA-methylated ( Figure 3H and 3I , Figure S4G–S4J ) , which is in line with an upregulation of the lncRNA genes in CLL cells upon DNA-demethylation . In addition , inclusion of the non-methylated D6 sequence led to a transcriptional inhibition of the reporter construct in all three cell lines analyzed , suggesting that transcriptional inhibitors might bind to the sequence element ( Figure 3H and 3I ) . In contrast , no changes in transcription were found when the E6 element was included ( Figure S4G–S4J ) , suggesting that either no transcription factors would bind to that sequence or that the reporter system did not faithfully reproduce the in-vivo situation . Both could be the case if E6 would represent an element of higher order chromatin e . g . a boundary element . Such an element could be bound by CTCF protein ( Gene ID: 10664 ) , which insulates active chromatin from heterochromatic gene deserts [30] reminiscent of the region distal to DLEU1 that is gene-poor . In addition , CTCF has a central role in transcriptional control exerted by ncRNA genes in cis , probably by segregating regulatory elements like enhancers and promoters [54] , and its binding to DNA is sensitive to DNA-methylation [55] . In addition , CTCF binding sites were predicted to be localized close to or within D6 and E6 ( Figure S4K ) . We therefore tested CTCF binding at 13q14 . 3 using ChIP-qPCR , and in fact CTCF binds to E6 and D6 in a subset of CLL cells but not in sorted B-cells from healthy donors ( Figure 3J ) . Therefore , CTCF is a candidate for modulating transcription at 13q14 . 3 in cis in a subset of CLL cells . In order to further delineate the regulatory mechanism of the lncRNA genes DLEU1 and DLEU2/Alt1 , we tested whether they exert their function by binding to chromatin . As expression levels of DLEU1 and DLEU2/Alt1 were too low for direct visualization of the lncRNA transcripts using RNA-FISH , we used RNA-seq of RNA bound to chromatin [56] that was isolated from murine embryonic stem cells , HeLa and U2OS cells . However , compared to the other genes localized in the critical region , no significant enrichment of DLEU1 or DLEU2 transcripts was found to be bound to chromatin ( Figure S5 ) . It is therefore unlikely that DLEU1 or DLEU2 exert their function by binding to chromatin , but rather regulate the neighboring cluster of candidate tumor suppressor genes by divergent transcription ( see Discussion ) . This coregulation of the 13q14 . 3 genes implies that they are also functionally related , e . g . that the respective gene products are involved in similar cellular processes . To understand which common pathway is targeted by the 13q14 . 3 candidate genes , we analyzed their gene function . For most of the 13q14 . 3 candidate genes , the associated molecular function remains unclear . Examples are miR-15a and miR-16-1 , for which a role in regulation of the cell cycle has been shown [16] , [57]–[59] . Interestingly , for these miRNA genes and for several additional gene products at 13q14 . 3 , an involvement in the NF-kB pathway has been postulated: miR-15a and miR-16-1 ( inducing NF-kB ) [60] and DLEU7 ( repressing NF-kB ) [61] modulate this central signalling pathway . For KPNA3 , whose loss leads to an expansion of hemocytes in Drosophila [62] , binding of the NF-kB DNA-binding subunit p65/RELA ( Gene ID: 5970 ) has been reported , suggesting a NF-kB inductive role [63] . Because of this suggestive functional link of the 13q14 . 3 gene cluster , our further experiments focused on their involvement on NF-kB signalling . First we tested whether miR-15a and miR-16 modulate NF-kB with an unbiased whole genome miRNA ( miRNome ) screen and measured NF-kB activity with a luciferase reporter assay [64] . Of 810 miR-mimics transduced into HEK293 cells , the miR-15a/miR-16 family ( miR-15a , miR-15b , miR-16 , miR195 , miR424 , miR497 ) showed the strongest induction of NF-kB of all tested miRNA families ( Figure 4A ) . Compared to a non-specific control miRNA , transfection of miR-15a and miR-16 miRmics into HEK293 cells significantly enhanced the induction of NF-kB by TNFalpha ( Figure 4B ) . In line with this finding , NF-kB target genes like IL6 , IL8 , CXCL1 and TNFalpha were induced in three different cell lines derived from embryonic kidney and breast cancer , albeit with different induction patterns ( Figure 4C–4E ) , suggesting that the modulation of NF-kB by the miR-15/16 miRNA family can occur in different tissues . Thus , in addition to their previously reported role in regulation of cell-cycle associated genes [16] , [58] , [65] , the miR-15/-16 family of genes is capable of inducing NF-kB . As activation of NF-kB has been shown in CLL cells to prevent apoptosis [38]–[40] , an inducive effect of miR-15/-16 of this pathway is difficult to reconcile with their tumorsuppressive role at least in the tissue analysed here . Therefore to validate an involvement of miR-15/-16 in NF-kB signalling we sought to identify target genes that modulate NF-kB in addition to the previously reported target genes that are associated with cell cycle progression . The miR-15/miR-16 family of miRNAs has been reported to target several genes involved in NF-kB signalling: IKKa/CHUK , the NF-kB activating kinase itself ( Gene ID: 1142 ) [66] , TAB3 ( Gene ID:257397 ) , an adaptor protein connecting TRAF6 with the NF-kB activating kinase TAK1 [60] , and the transcriptional coregulator NCOR2/SMRT ( Gene ID: 9612 ) [67] . As a control we included SMAD7 ( Gene ID: 4092 ) that is a predicted target of miR-15a ( TargetScan6 . 2 algorithm ) , and a negative modulator of NF-kB activity [68] but has not been validated as a target so far . In order to delineate the molecular mode of induction of NF-kB activity by miR-15a , miR-15b and miR-16 , the respective miR-mimics were cotransfected with luciferase reporter constructs containing 3′UTRs or parts of the 3′UTRs of the candidate target genes into HEK293T cells . While constructs containing 3′UTRs of genes previously reported to be targets of miR-15a and/or miR-16 ( CHUK/IKKa , SMRT and TAB3 ) showed lower luciferase activity after miRmimics-15a/-16 transfection , luciferase activity from the control reporter SMAD7 selected using in-silico prediction remained constant ( Figure 4F ) . Thus we reproduced previously reported findings on gene targets of the miR-15/miR-16 family that modulate NF-kB transcription factor activity either directly ( NCOR2/SMRT ) or via upstream kinases ( IKKa/CHUK ) or upstream adaptor proteins ( TAB3 ) . The strong induction of NF-kB by the miR-15/miR-16 family in our screen however suggests that additional genes are targeted by these miRNAs that are part of the NF-kB circuitry . We confirmed that knockdown of KPNA3 located in 13q14 . 3 and the family member KPNA4 ( Gene ID: 3840 ) located in 3q25 . 33 ( Figure S2D ) leads to a loss of inducibility of NF-kB activity by TNFalpha ( Figure 5A ) . However , double knockdown of both genes did not lead to a full loss of NF-kB induction . In addition we analysed whether C13ORF1 , RFP2 and its bicistronic ORF KCNRG ( Gene ID: 283518 ) , the protein-coding genes closest to or included in the minimally deleted region , are also involved in NF-kB signalling . To this end we knocked down candidate genes from the minimally deleted region and induced NF-kB with TNFalpha ( Figure 5B ) . Even though TNFalpha activates NF-kB via several pathways , knocking down RFP2 and , depending on the NF-kB recognition sequence used , also KCNRG and C13ORF1 led to a decrease in the activation of NF-kB ( Figure 5B , Figure S6A ) . To further validate the role of RFP2 in NF-kB signalling , we exogenously overexpressed RFP2 in HEK293-T , HEK293 , controlled overexpression of RFP2 with a specific antibody we raised in guinea pig against recombinant full length RFP2 and quantified NF-kB activity with a luciferase reporter assay ( Figure 5C; Figure S6B ) . An induction of NF-kB was also observed when RFP2 was overexpressed in primary CLL cells ( Figure 5D ) . As overexpression of recombinant proteins may lead to artificial activation of NF-kB signalling , we separately overexpressed recombinant GFP as a negative control using 50 fold more plasmid than RFP2 expression plasmid and did not observe activation of NF-kB ( Figure S6C ) , underlining that the effect of RFP2 is specific . These findings raise the question how RFP2 activates NF-kB . NF-kB activation is only induced 7hrs after transfection of the RFP2 expression plasmid , which is the same time point when the exogenous RFP2 protein can first be detected ( Figure 5C , Figure S6B ) . This suggests a direct effect by overexpression of RFP2 and excludes transcriptional induction of other factors , which would require at least an additional 1–2 hrs . The activation of NF-kB by RFP2 could be blocked by dominant negative ( dn ) IKK and dnIkB [69] , suggesting that the effect of RFP2 takes place upstream of these factors ( Figure 5E ) . In addition , loss of the ubiquitin-ligase activity of RFP2 by mutating C13A [70] completely abrogated the activation of NF-kB by RFP2 ( Figure 5E ) . In order to identify the NF-kB component that is targeted by RFP2 activation , all DNA-binding components of the NF-kB signalling pathway were knocked down individually . Downregulation of RELA and to lesser extent of p105 ( Gene ID: 4790 ) reduced the activation of NF-kB by RFP2 ( Figure 5F ) . Corroborating this finding in a custom oligonucleotide-coupled ELISA ( co-ELISA ) [71] , RFP2 specifically induced the activity of RELA ( Figure 5G ) . It has recently been shown that the RFP2 protein interacts with VCP , ATP2A2/SERCA2 [70] and SQSTM1 [72] . We therefore asked whether these proteins would be involved in the modulation of NF-kB activity by RFP2 . However , knockdown of ATP2A2 and SQSTM1 did not result in enhanced activity of NF-kB ( Figure 5H; Figure S6D ) . In contrast , knockdown of VCP substantially increased the activation of NF-kB by RFP2 ( Figure 5H and Figure S6D ) . This finding is intriguing as VCP and SQSTM1 link RFP2 not only to endoplasmatic reticulum associated protein degradation ( ERAD ) and autophagy [70] , [72] , but also to regulation of TRAF6 [73] , [74] that is involved in signalling pathways such as CD40/CD40L and TLR that are central to the pathogenesis of CLL . RFP2 is a member of the family of tripartite motif proteins ( TRIM ) but lacks the SPRY domain ( pfam00622 ) common to other TRIM proteins [75] . Intriguingly , the neighboring C13ORF1 gene has a SPRY domain , suggesting a functional interaction of RFP2 and C13ORF1 . While knockdown of C13ORF1 led to a reduction in NF-kB inducibility ( Figure 5B ) , co-expression of RFP2 and C13ORF1 did not lead to a synergistic induction of NF-kB activity ( Figure S6D ) . As RFP2 is an integral membrane protein [70] and requires disruptive RIPA buffer extraction for analysis , physical interaction with C13ORF1 could not be shown by pulldown experiments . However , support for the interaction of RFP2 and C13ORF1 proteins came from the observation that coexpression of RFP2 stabilized expression of C13ORF1 ( Figure 5I ) , even though RFP2 has a destabilizing ( auto- ) ubiquitin ligase activity [70] .
Several lines of evidence suggest that the tumor suppressor function of 13q14 . 3 distal to RB1 is multigenic [16] , [20] and is not inactivated by mutation [25] , but rather by transcriptional deregulation [10] , [13] , [26] , [27] . In line with this notion we found DNA-demethylation at the 5′ends of the lncRNA genes DLEU1 and DLEU2 in more than 95% of CLL patients ( Figure 2D , Figure 6A ) . Hypomethylation in cancer cells usually coincides with chromosomal instability , which we cannot exclude for 13q14 . 3 , or with reexpression of silenced oncogenes . In fact , a genome-wide DNA-demethylation has been observed for CLL cells [76] , but the functional consequence is unclear . At 13q14 . 3 , DNA-methylation levels comparable to non-malignant B-cells were observed at all tested loci except for the elements D6 and E6 . DNA-demethylation of the regions D6 and E6 in CLL cells is directly correlated with an increase in the expression of DLEU1 and DLEU2 and inversely correlated with the expression of the neighboring candidate tumor suppressing protein-coding genes ( Figure 6B ) . The expression of antisense transcripts is usually lower and is not necessarily coupled to expression of the respective sense transcripts [77] , which is what we observed at 13q14 . 3 for the lncRNA genes DLEU1 and DLEU2 and the protein-coding genes . As for the cis-regulatory mode of action of lncRNA genes , a direct RNA-DNA interaction has been shown to recruit repressors , which leads to changes in chromatin conformation [4] , [78] . However , this option seems unlikely as for none of the transcriptional units at 13q14 . 3 we found substantial enrichment in the chromatin-bound RNA fraction . A second mode of action could be competition by ( i ) “divergent transcription” of the ncRNA genes that recruits essential factors away from the candidate tumor suppressor genes [78] , ( ii ) collision of transcription complexes initiated from different promotors ( e . g . E6 and the DLEU2 promotor ) but transcribing through the same sequences , or ( iii ) elongation through transcriptional regulators like enhancers/repressors that leads to the deposit of specialized epigenetic marks inhibiting transcription from the opposite strand [79] . Interestingly , D6 seems to inherently harbor transcriptional repressive properties . The described mechanisms are only dependent on the initiation of transcription and can be independent of the resulting ( antisense ) RNA molecule itself . The dispensable role of the DLEU1 transcript itself is also suggested by the lack of conservation of the DLEU1 gene sequence and its multitude of splicing variants [8] . In fact , lncRNAs involved in regulation in cis are in general poorly conserved , probably because these mechanisms are mostly topological [80] and thus sequence independent . A topological regulation is also suggested by the presence of a homologous region on 3q25 . 33 ( Figure S2D ) and the conservation of the orientation of the genes and CpG islands in Mus musculus [31] . However , it should be noted that in the mouse there is no overlap of DLEU2 with RFP2 , but the sequence similarity of the first exon of RFP2 and exon 11 of DLEU2 is conserved [9] . This suggests at least for this pair of genes the possibility of a RNAi-like regulatory mechanism . Finally , transcription in the region could be regulated by a central locus control region , organizing the intranuclear localization of 13q14 . 3 e . g . by binding of chromatin organizing proteins like CTCF . While DNA-methylation dependent aberrant binding of CTCF could be observed at D6 and E6 in a patient subset , more advanced experiments ( e . g . 3–6C analyses ) are required to assess the functional impact of changed binding properties of chromatin organizing factors such as CTCF . Interestingly , epigenetic deregulation of lncRNA genes leading to aberrant transcription of neighboring genes occurs also in acute leukemia . The lncRNA HOTAIRM1 for example is expressed exclusively in the myeloid lineage and controls expression of the proximal HOXA gene cluster [81] . Similarly , the ncRNA vault RNA2-1 ( vtRNA2-1 ) in the commonly deleted region of chromosome 5q is monoallelically methylated and expressed in healthy individuals , while it is epigenetically inactivated in AML , leading to activation of NF-kB via RNA-binding protein kinase R ( PKR , [82] ) . Another example resembling the molecular mechanism of the 13q14 . 3 locus is silencing of the tumor suppressor WT1 by the overlapping WT1-antisense lncRNA WT1-AS , which is monoallelically expressed in non-malignant cells and becomes activated in AML by hypomethylation [83] . Thus , epigenetic deregulation of ncRNA genes seems to be a recurrent disease related phenomenon both in chronic and acute leukemias , leading to aberrant function of tumor suppressor- or oncogenes . The transcriptional activities of the 13q14 . 3 candidate genes all correlate with the DNA-methylation levels in the region . This co-regulation suggests that 13q14 . 3 genes are also functionally related , i . e . are involved in the same cellular pathways . Such clusters of genes seem more common in drosophila than in mammalian cells [84] . In human cells , only a subset of ubiquitously expressed genes and a small set of atypical genes is grouped together into coregulated clusters [85] . A reason for evolutionary conservation of a genetic neighbourhood of functionally connected genes is the coregulation of these genes [85] . Examples in the mammalian system are the globin gene family , groups of olfactory receptors , histone-coding genes , HOX genes , genes of the major histocompatibility complex and imprinted genes . In addition , most long non-coding RNA genes are involved in regulating functionally related gene clusters [2] . One major unifying scheme of these gene clusters seems to be the transcriptional activity from the same chromosomal strand [85] , which has been shown for 13q14 . 3 [35] . Similarly , the topological organization of these gene clusters is highly conserved between mammals , which is also true for 13q14 . 3 [31] , [50] and its homologous cluster at 3q25 . 33 . It is therefore very likely that the 13q14 . 3 candidate genes are also functionally related , and we and others could show that they activate or repress the NF-kB signalling pathway ( Figure 6C ) . NF-kB signalling is centrally involved in the homeostasis of the hematopoietic system where it is induced in inflammation and inhibits apoptosis [86] . NF-kB signalling has already been shown to be activated in CLL cells [38]–[40] , [87] , where it is postulated to help in cellular survival [87] . In CLL , NF-kB is activated by the interaction with the microenvironment [39] , which is crucial for the survival of CLL cells [51] . NF-kB is also activated via the B-cell receptor ( BCR ) that plays an important role in the pathogenesis of CLL [51] . Similarly , NF-kB is activated by interaction of TCL1 ( Gene ID: 8115 ) and ATM in CLL [88] , two genes that are coregulated in CLL cells [89] and centrally involved in the pathogenesis of CLL . In contrast , in early developmental stages of a CLL-like disease in transgenic mice , repressive p50/p50 NF-kB dimers ( Gene ID: 4790 ) cause epigenetic lesions that even precede genetic lesions [29] , suggesting that at different stages of the disease , NF-kB could play different roles . Genome- and exome-wide analyses of CLL cells have recently shown that mutations are present in genes involved in NF-kB signalling [90] , and intriguingly mutations in a NF-kB-pathway associated gene ( MYD88 , Gene ID: 4615 ) seem to be even enriched in del ( 13q ) patients [91] . This is most interesting as MYD88 is required for TLR signalling via TRAF6 , a protein that is bound by SQSTM1 and VCP [73] , which interact with RFP2 [70] , [72] . Further studies will be required to understand the molecular interplay of these proteins in full detail and especially to accommodate the unexpected induction of NF-kB activity by several genes localized at 13q14 with their tumorsuppressive function . After recent reports have shown 13q14 . 3 genes to be inhibitors of NF-kB signalling [60] , [61] , here we demonstrate that the miR-15a/16 cluster , KPNA3 ( and KPNA4 from 3q25 . 33 ) and RFP2 are positively correlated with NF-kB function ( Figure 6C ) : the miRNA15/16 family of genes were among the strongest inducers of NF-kB in an unbiased screen , KPNA3 is the transporter of p65 and RFP2 induces canonical NF-kB signalling . NF-kB activity is normally associated with an inhibition of apoptosis , and in fact has been shown to be induced in CLL cells by pro-survival microenvironmental stimulants like e . g . CD40L , BAFF; stromal cells or B-cell receptor stimulation [38] , [87] , [92]–[94] . However , there are a few instances where NF-kB activity can also induce apoptosis . The most relevant example is probably the negative selection of T-cells [95] , where strong signalling from the T-cell receptor upon recognition of self-antigens induces apoptosis via activation of NF-kB above a certain threshold . While in B-cells negative selection is somewhat dissimilar , loss of negative selection in CLL cells would make sense considering i ) the autoreactivity of CLL cells and ii ) the importance of consistent BCR signalling induced by self-antigens in the pathogenesis of the disease [96] . Thus , even though within the same cell , NF-kB activity cannot be at the same time silenced and activated , the activity of NF-kB can change during the leukemogenesis of CLL and the role of the tumor suppressor mechanism in 13q14 could be required only at specific timepoints . The speculative involvement of 13q14 genes in negative B-cell selection could explain how deletion of NF-kB-inducing genes at 13q14 would lead to CLL leukemogenesis at an early timepoint , while malignant B-cells from of terminal stage CLL then exhibit increased levels of NF-kB that prevent apoptosis as has been shown previously ( see above ) . In this respect it should be borne in mind that the functional assays quantifying the impact of 13q14 genes on NF-kB signalling performed both by us and by others depend on in-vitro experiments mostly in cell lines and not in primary cells except for RFP2 ( Figure 5D ) . In addition , overexpression and knockdown of 13q14 genes was performed using recombinant constructs . These experimental settings and their results might therefore not properly reflect the physiological situation , especially when looking at such finely tuned systems like NF-kB signalling . However , NF-kB has been shown to be a promising target for therapeutic intervention in CLL cells [97] , [98] , and further functional experiments and especially in-vivo analyses should be performed to fully understand the mechanistic link between 13q14 and NF-kB in CLL . In summary , we uncovered a cluster of functionally related genes that are coregulated by long non-coding RNA genes in cis and are epigenetically deregulated in malignant cells . We previously speculated that the epigenetic deregulation could explain a stepwise inactivation of the tumor suppressor mechanism [34] . This would complement the findings of clonal evolution and/or extent of 13q14 deletion being associated with a more aggressive form of CLL [18] , [37] , and the presence of pre-malignant stages of the disease ( e . g . MBL ) [15] . Further work is required to identify transcription factors binding to the demethylated regions and characterization of their intranuclear localization . It will also be of interest to test whether the observed epigenetic aberrations are present already in premalignant cells of mouse models [23] , [99] or whether they constitute the aberrations that have been postulated to be present in hematopoietic stem cells of CLL patients [100] .
Mononuclear cells were isolated from peripheral blood by density centrifugation using Ficoll ( Biochrom AG ) according to the manufacturer's instructions . For positive selection of CD19+ B-cells and CLL cells from peripheral blood , mononuclear cells ( PBMCs ) were labeled with CD19 MACS magnetic MicroBeads and isolated using MACS LS Column placed in the magnetic field of MACS Separator . The purity of the CD19+ fraction was 95%±3% ( ± SEM ) after purification from PBMCs from healthy probands and 97%±2% for purification from PBMCs of CLL patients as measured by flow cytometry ( FACSCalibur , BD Biosciences ) using anti-CD19 FITC-labeled antibodies ( anti-CD19 MicroBeads , Dako ) that specifically binds the CD19 epitope . Peripheral blood samples were obtained from patients after informed consent by a procedure approved by the Ethics Committee of Ulm University ( approval 96/08 ) , and peripheral blood was drawn from fully anonymised age-matched healthy probands at the german red cross ( DRK ) in accordance with the Declaration of Helsinki . Standard 20 µl qPCR reactions contained 10 µl SYBR Green mixture ( Absolute QPCR SYBR Green ROX Mix , Thermo Scientific ) and primers at 70 nM final concentration . Thermal cycling conditions were 15 minutes at 95°C , 40 cycles of 15 s at 95°C and 30 s at 60°C , dissociation curve 15 s at 95°C , 15 s at 60°C and heated to 95°C ( within 20 minutes ) , held for 15 s and cooled down to 4°Ç using the 7300 Real-Time PCR system ( Applied Biosystems ) . A standard curve , using template dilutions of HeLa and HEK293 cDNA was measured to determine PCR efficiency and allow exact quantification of template . All primers used for qPCR are listed in the Table S4 . Reverse transcription of total RNA was carried out using the AffinityScript QPCR cDNA Synthesis Kit ( Agilent ) , a reaction lacking reverse transcriptase ( -RT ) was included for each template where primers did not span an intron and amplification of product would have been possible from contaminating genomic DNA . For mRNA detection , Ct-values were normalized using dilution standard curves and three housekeeping genes ( PGK2 , LMNB1 , PPIA ) or for the miRNA genes using the ddCT method with RNU6B and SNORA73A as internal normalization controls . 10 ng of total RNA was reverse transcribed using the miScript Reverse Transcription Kit ( QIAGEN ) where reactions were scaled down to 10 µl . The completed RT reactions were diluted to 50 µl with DEPC-treated water and PCR amplification for real-time quantitative analysis was performed using the miScript SYBR Green PCR kit ( QIAGEN ) . Total reaction volume of qPCR was 20 µl , and 2 µl of the diluted RT reactions were used as template . For miRNAs custom forward primers were used to final 0 . 5 µM ( sequences see Table S4 ) and primers for normalization controls RNU6B and SNORA73A were purchased from QIAGEN . The annealing temperature was 55°C . To study the effect of DNA-methylation in vitro , the regions D6 and E6 were cloned with their physiological promoter into the pCpGL vector ( kind gift from Michael Rehli ) [101] to investigate their impact on transcription and whether this is dependent on DNA-methylation . The promoters of the large ncRNAs DLEU1/DLEU2 and DLEU2/Alt1 were cloned in both directions with and without the putative regulatory elements D6 and E6 . The construct containing D6 was 2 kb in size and the construct lacking D6 was 1 . 3 kb in size . These products could be amplified from placenta DNA ( SIGMA-Aldrich ) using the HotStarTaq Plus PCR system ( Qiagen; cycling: 95°C: 5 min; 40 cycles of 95°C: 30 sec , 58°C: 30 sec , 72°C: 1/1 . 5 min; hold 10°C ) . Constructs containing or not containing E6 were 4000 and 3500 bp in size and amplified with the Expand High Fidelity PCR System ( Roche ) using PAC 372-3 from 13q14 . 3 as template [7] . Cycling was performed 95°C 2 min , 10× [95°C 20 s , 60°C 30 s , 68°C 4 min] , 20× [95°C 20 s , 60°C 20 s , 68°C 4 min +20 s in each cycle] , 68°C 7 min , hold 4°C . The desired constructs were amplified with primers containing BamH1 and SpeI recognition sites ( see Table S4 ) and cloned into the TOPO TA cloning vector ( Invitrogen ) . Plasmids from positive clones were digested with BamH1 and SpeI ( NEB ) using 3 µg TOPO-plasmid-insert-DNA or 1 µg pCpGL vector for 1 h at 37°C . The insert was isolated on a 1% agerose gel ( 50 min , 150 V ) and extracted using QIAEX II Kit ( Qiagen ) . For sticky end ligation a 3 times molar excess of insert over pCpGL vector backbone was used in a ligation reaction with 0 . 1u T4 ligase ( Invitrogen ) incubating 1 h at 37°C or at 16°C over night . The ligation reaction was purified by ethanol precipitation , resuspended in 5 µl water and 1 µl was used to transform competent PIR1 E . coli cells ( Invitrogen ) bacterial cells via electroporation ( Gene Pulser II , BIO-RAD ) . After electroporation in a 2 mm cuvette at 25 µF and 2 . 5 kV setting the pulser at 200× , transforming 50 ng DNA within a total volume of 400 µl , cells were plated on zeocin containing plates and incubated at 37°C overnight . For transient transfections , plasmids were isolated and purified using the EndoFree Plasmid Kit ( Qiagen ) . In vitro methylation was performed using SssI methylase ( NEB ) according to manufacturer's instructions but incubating for 4 h at 37°C and adding 1 µl fresh SAM after 2 h . To measure the impact of miR-15a , miR-15b and miR-16 on potential target genes , parts of or the whole 3′UTRs of TAB3 , CHUK , SMAD7 and SMRT were cloned into the vector pMIR-Report ( Applied Biosystems ) . Sequences containing the miR target sites in the 3′UTRs of TAB3 , CHUK , SMRT “KF” and SMAD7 were amplified from HEK293T genomic DNA using the corresponding primers ( containing restriction sites for HindIII , SpeI or SacI; see Table S4 ) and the PRECISOR high-fidelity DNA polymerase ( BioCat ) according to the manufacturers instructions . Amplified products were purified using the PCR Purification Kit from Qiagen , digested with HindIII , SpeI or SacI ( FastDigest Enzymes , Fermentas ) and ligated with pMIR-Report ( T4 DNA Ligase , Fermentas ) . Plasmid backbone had been digested with the respective enzymes and purified via agarose gel extraction ( Qiagen ) . Reporters containing just the miR target site and the respective mutated sequence ( “SMRT” and “SMRTmut” ) were cloned as described previously [67] . 1 µg of genomic DNA was converted using EpiTect 96 Bisulfite Kit or EpiTect Bisulfite Kit ( Qiagen ) in a GeneAmp PCR System 2700 ( Applied Biosystems ) with a reaction volume of 100 µl . After desulphonation , converted DNA was eluted 2 times in 20 µl prewarmed ( 65°C ) water . Bisulfite conversion was performed on dilution series ( different degree of methylation ) of placenta DNA ( SIGMA-Aldrich ) , DNA from CLL patients and from B cells of healthy individuals for quantitative methylation analysis by BioCOBRA or massARRAY as well as bisulfite sequencing . For BioCOBRA analysis ( combined bisulfite restriction analysis with the Agilent 2100 Bioanalyzer platform , [102] , bisulfite converted DNA was amplified using primers specific for converted template ( see Table S4 ) . After purification of the PCR products using Rapid PCR Purification System ( Marligen Biosciences ) , products were digested with BstUI ( NEB ) over night at 60°C . Fragments were subsequently analysed with DNA 1000 LabChip ( Agilent ) on the Agilent 2100 Bioanalyzer . For all amplicons a calibration curve was measured with defined mixtures of methylated and unmethylated DNA ( Figure S1A ) . Fully unmethylated DNA was generated by whole genome amplification ( REPLI-g Kit , Qiagen ) , and after purification ( QIAamp DNA Mini Kit , Qiagen ) , half of the amplified and purified DNA was in vitro methylated using SssI methylase ( NEB ) . Mass-spectrometric methylation analysis was performed using MassARRAY ( Sequenom ) analysis according to [42] for the potential regulatory element E6 within 13q14 . 3 , because lack of a BstUI recognition site precluded BioCOBRA . The target gene regions were amplified by PCR ( see Table S4 ) after sodium-bisulfite conversion of template DNA using primers specific for converted template . In this amplification , reverse PCR primers were tagged with the T7 recognition sequence for reverse transcription . Deoxynucleotides in the PCR reaction were dephosphorylated using shrimp alkaline phosphatase ( SAP ) at 37°C for 20 min followed by 5 min heat inactivation of SAP at 85°C . Making use of the T7 recognition sequence , a single-stranded RNA copy of the template was generated by in vitro transcription . The produced RNA was cleaved specifically at Uracil by RNase A . The cleavage products were analyzed using matrix-assisted laser desorption ionization – time of flight ( MALDI-TOF ) mass spectrometry in a final elution volume of 27 µl . Cleavage product signals with a 16 Da shift ( or a multiple thereof ) represent methylation events; signal intensity was correlated with the degree of DNA-methylation . Bisulfite converted DNA ( EpiTect Bisulfite Kit , Qiagen ) was amplified using primers specific for converted DNA . After PCR purification ( Rapid PCR Purification System , Marligen Biosciences ) the product was cloned into pCR2 . 1-TOPO vector and subsequently transformed into One Shot Mach1-T1 competent E . coli cells ( Invitrogen ) . Positive clones were selected by colony PCR using M13 primers; cycling: 95°C: 12 min; 40 cycles of 95°C: 30 sec , 55°C: 30 sec , 72°C: 1 min; 72°C: 7 min; hold 10°C . PCR products of the expected size were purified ( Marligen Biosciences ) and sequenced ( BigDye Terminator v3 . 1 Cycle Sequencing Kit , Applied Biosystems ) using M13 forward primer with the ABI Prism 3100 Genetic Analyzer 3130xl ( Applied Biosystems ) . Cycling: 96°C: 1 min; 25 cycles of 96°C: 10 sec , 52°C: 5 sec , 60°C: 2 min; hold 10°C . The sequencing reactions were purified with the DyeEx 96 Kit or DyeEx 2 . 0 Spin Kit ( Qiagen ) to remove non-incorporated nucleotides . Analysis of sequences was performed using MethTools ( http://genome . imb-jena . de/methtools/ ) . aPRIMES was performed according to [45] using 500 ng genomic DNA that was digested using 10 U MseI ( NEB ) for 3 h . The MseI-fragments were then subjected to linker mediated PCR using primer ddMse11 and primer Lib1 at an initial annealing temperature of 65°C that was shifted down to 15°C with a ramp of 18°C/min ( MWG , Ebersberg , Germany ) and ligation using T4-DNA-Ligase ( 10 U , Roche ) was performed at 15°C overnight . Half of the resulting ligated MseI fragments were digested with the restriction enzyme McrBC ( NEB ) for 8 h and the other half of was digested with two methylation-sensitive endonucleases , HpaII and BstUI 3 h each . Proteinase K ( Invitrogen ) was used for digestion before amplification using Expand Long Template system ( Boehringer ) and Lib1 primer in a MWG thermo cycler; cycling: 72°C: 3 min 20 cycles ( 94°C: 30 s , 62°C: 30 s , 72°C: 90 s ) , 72°C: 10 min . The PCR products were recovered by ethanol precipitation and DNA was eluted in 30 µL 0 . 1× TE , pH 8 . In vitro methylated CpG islands from rice were used as positive controls for methylation and 10 pg were spiked in DNA samples used for aPRIMES to control methylation and methylation-sensitive digestion . Mitochondrial CpG island clones that were present in the original library were used as controls for unmethylated and allelically/partially methylated CGIs . Genomic DNA ( 2 µg ) isolated from CD19 sorted B cells of either CLL patients or healthy individuals was immuno-precipitated using recombinant MBD2–Fc fusion protein [103] . DNA was homogenized through a 22G needle and fragmented to a mean size of 400–500 bp using ultrasonication ( 2×30pulses , 24 s , 10% amplitude , Bioruptor , Diagenode ) . 30 µg of MBD-Fc protein was coupled to SIMAG protein-A magnetic beads ( Chemicell ) 3 h at 4°C in TBS . After completing MBD-Fc protein binding to the magnetic beads , precipitation of the sonicated sample DNA was performed in low salt buffer for 3 h at 4°C . Fractionated elution from the beads was performed using buffers A–F with increasing salt concentrations . In order to ensure complete elution of methylated DNA , elution with buffer F was repeated once . The collected fractions were desalted using the MinElute Kit ( Qiagen ) and eluates were diluted 1∶10 and analyzed for control genes ( SNRPN , ZAP70; primer sequences see Table S4 ) with qPCR . Samples were subsequently processed for array hybridization . For ChIP 1–5×107 viably frozen CD19-sorted B cells from either CLL patients or healthy individuals were washed once with DMEM medium , taken up in 1 ml PBS and formaldehyde cross link was performed at a final concentration of 1% for 10 min at RT while rotating . Cross-linked samples were sonicated in 300 µl SDS lysis buffer ( 1% SDS , 10 mM EDTA , 50 mM Tris/HCl pH 8 . 1 , 167 mM NaCl , protease inhibitors ) 8 times 30 seconds on/off at high amplitude using a Bioruptor ( Diagenode ) . The sonicated material was diluted 1∶10 with dilution buffer ( 0 . 01% SDS , 1 . 2 mM EDTA , 16 . 7 mM Tris/HCl pH 8 . 1 , 1 . 1% TritonX100 , protease inhibitors ) , subjected to 1 h preclearing with 30 µl of salmon sperm saturated protein A/G agarose beads ( Millipore ) . Precleared chromatin samples were incubated over night with either 5 µg specific antibody ( CTCF , H3K4me2 , macroH2a1 . 2 , Millipore ) , or 5 µg normal IgGs ( Santa Cruz ) at 4°C . Antibody bound chromatin was precipitated by adding 50 µl of salmon sperm saturated protein A/G agarose beads 4 h at 4°C and unspecifically bound material was removed by washing with low salt buffer , high salt buffer , LiCl buffer and two times with TE buffer . Cross link was reversed over night at 65°C and RNaseA ( 30 min , 37°C ) as well as ProteinaseK digest ( 2 h , 45°C ) was performed before purification of precipitated DNA using GFXTM PCR DNA and Gel Band Purification Kit ( GE Healthcare ) . Precipitation efficiency was analyzed by qPCR for positive and negative control regions ( for primers see Table S4 ) on antibody and control IgG precipitated fractions and expressed as percentage of input DNA using a calibration curve for quantification . Predicted CTCF binding sites were identified at http://www . essex . ac . uk/bs/molonc/binfo/ctcfbind . htm . Microarrays were either produced by spotting PCR-amplified 1 kbp fragments from the promotors of RFP2 , DLEU1 and DLEU2/Alt1 ( CpG islands C , D and E ) for aPRIMES . For MCIp arrays were custom designed ( eArray , Agilent ) to tile promotors −3 . 8 to +1 . 8 kbp from the transcriptional start sites of the region chr13:47702475–49164179 ( ITM2B – EBPL ) and complete tiling of the region chr13:49265143–50317955 ( C13ORF1 – DLEU7; GRCh37 hg18 ) . 60 bp oligonucleotides were designed with 30 bp nonoverlapping spacing . The resulting 9863 oligonucleotides were combined with 10 bp linker sequence and had an average melting temperature of 70 . 43°C . For custom arrays , the 13q14 . 3 oligonucleotides were complemented with the Agilent normalization group ( 1262 ) and replicate group ( 4626 ) oligonucleotides . Labeling of ChIP and MCIp samples was performed using the BioPrime Total Genomic Labeling System ( Invitrogen ) . For CTCF ChIP samples the precipitate was labeled using Cy5 and the input was labeled with Cy3 . For the MCIp samples only the elutions from the high salt fraction were labeled , the common reference ( T cell pool ) was labeled with Cy3 and the CLL/healthy donor sample with Cy5 . In order to predict labeling efficiency , the samples were measured at the wavelengths A260 , A320 , A555 , A650 , A750 , and the following equations were used to determine the yield: Cy3: DNA amount [ µg] ( A260–A320 ) *50*0 . 04 , Dye incorporation ( A555–A650 ) /0 . 15*40 Cy5: DNA amount [ µg] ( A260–A320 ) *50*0 . 04 , Dye incorporation ( A650–A750 ) /0 . 24*40 The hybridization of the MCIp samples was performed according to protocol number G4170-90012 for Agilent Microarray Analysis of Methlylated DNA Immunoprecipitation version . 1 . 0 . The hybridization of the ChIP samples was performed as described in the protocol number G4481-90010 for Agilent Mammalian ChIP-on-chip version 10 . 1 applying the instructions given for the 4× format . Cell lines were seeded at a density of 5×106 in 4 ml of the appropriate medium in 6-well plates . After 24 hrs , they were treated with a final concentration of 1 . 5 µM 5-Aza-2′-deoxycytidine ( Sigma-Aldrich ) or the respective amount of DMSO solvent in the control reaction for 6 days with daily medium and drug replacement . The chromatin fraction of RNA was prepared from isolated nuclei after shearing in a Covaris sonicator ( Covaris , Inc . ) . The sample was then centrifuged and the soluble chromatin was loaded on a sucrose gradient as described [104] . Fractions containing DNA fragments > 5000 bp ( equivalent to 25 nucleosomes with a 200 bp nucleosome repeat length ) were pooled . RNA was phenol/chloroform-extracted after proteinase K and DNase I treatments and RNA-sequencing was performed . After rRNA depletion , RNAs were subjected to metal ion catalyzed cleavage to sizes between 60–200 nucleotides with the Ambion RNA fragmentation reagents . Libraries for Solexa sequencing were generated according to the standard protocol for mRNA ( Illumina ) that comprised first strand cDNA synthesis , second strand cDNA synthesis , end repair , addition of a single A base and adapter ligation . PCR products were size excised from low melting agarose gels ( 200–400 bp range ) and phenol extracted . Sequencing was performed on the Illumina GAIIx platform at the sequencing core facilities of the EMBL , DKFZ and BioQuant in Heidelberg , Germany . Initial RNA sequence analysis was performed with the Bioconductor ( http://www . bioconductor . org ) package for the R statistical programming language to assess the read quality and to produce a reads coverage file . The integrative genomics viewer ( http://www . broadinstitute . org/igv ) was used to visualize the coverage file and the RefSeq genes ( NCBI ) . Reads were aligned on the GRCh37/hg19 ( 2009 ) assembly version of the human genome reporting unique hits without mismatches and with and without trimming of the 3′ and 5′ ends . Data is available at ArrayExpress ( www . ebi . ac . uk/arrayexpress ) , Experiment name: lncRNAs at 13q14 . 3; ArrayExpress accession: E-MTAB-1335 ( U2OS ) and E-MTAB-582 ( HeLa ) . All cell lines were cultured according to DSMZ ( www . dsmz . de ) recommendations . Adherent cell lines were transiently transfected with indicated constructs using the Nanofectin Kit ( PAA ) . A half confluent flask of cells was transfected according to manufactures instructions using 5 µg of DNA for a 25 cm2 flask and 8 µg for a 75 cm2 culture vessel . Suspension cell lines were transfected according to the Nucleofection protocol of Amaxa ( Lonza ) . For each cell line 2×106 cells were transfected using 5 µg plasmid DNA ( 2 µg pmax GFP as transfection control ) and 100 µl Nucleofector solution . The whole procedure was performed following manufacturer's instructions and preparing the 12-well plates with 1 . 5 ml prewarmed medium . For Nucleofection the protocol A-023 was used . Gene transcripts were knocked down using either the Universal probe library system ( Roche Diagnostics ) and validated by q-RT-PCR to be below 30% of siCONP-treated cells . siRNAs were also synthesized using the Silencer siRNA construction kit ( Ambion ) and modified according to [105] , or validated siRNAs were ordered from Applied biosystems . For simultaneous transfection of plasmids and miR-mimics ( “miRVANAs” ) or miR-inhibitors ( both Life Technologies , Darmstadt , Germany ) into HEK293T cells , Lipofectamine2000 ( Invitrogen , Karslruhe , Germany ) , Hyperfect ( Quiagen ) or miRus transit-LT1 ( Geneflow ) was used . 4×105 cells/well were seeded in 24 well plates and transfected according to the manufacturers instructions after 24 h using 0 . 5 µg Plasmid and 10 pmol miR-mimics or miR inhibitors , respectively . For single transfection of 10 pmol miR-mimics or miR-inhibitors , the same protocol was used and the cells harvested after 24 h for Western blot or expression analysis . Transfection efficiency was tested by transfection of pmaxGFP ( Lonza , Cologne , Germany ) or siGlo ( Dharmacon , Darmstadt ) and subsequent detection by flow cytometry . Specific antibodies were raised by immunizing guinea pigs with recombinant RFP2 S154-E264 10×His-tagged purified proteins . Guinea pigs were immunized for the first time at 8 weeks of age with 100 µg of protein per animal diluted 1∶1 with Complete Freud's adjuvant ( Sigma ) . Subsequently animals were immunized monthly with 100 µg of protein per animal diluted 1∶1 with Incomplete Freud's adjuvant ( Sigma ) . During this process , serum was taken periodically by heart-punction . After 24 months animals were bled . Blood was collected in Vacutainer Blood collection tubes ( BD ) left at RT for 1 hr and blood cells sedimented by spinning at 2000 rpm 1 hr at RT . After sedimentation , serum was collected and aliquoted for storage at −80°C or complemented with 0 . 02% sodium azide as preservative and kept at 4°C . The polyclonal antibodies were tested against purified recombinant protein in Western blot analysis and against protein over-expressed in mammalian cells by Western blot analysis and immunofluorescence . Overall survival curves were estimated by the Kaplan-Meier method . Logrank tests were used for comparing survival distributions between groups . Wilcoxon rank sum tests were used to test for differences in expression or methylation distributions between two groups . For significance of Pearson correlation coefficients , t-distribution was calculated with t = r/sqrt[ ( 1−r∧2 ) / ( N−2 ) ] . For assessment of statistical significance , test results with p-values p<0 . 05 were considered to be statistically significant . | Recent results suggest that genome regions not coding for proteins are read and transcribed into RNA . While the function for the majority of the resulting non-coding RNA molecules remains unclear , some of them are termed according to their length ( typically 200–2 , 000 nucleotides ) as long non-coding RNA ( lncRNA ) genes that play a role in regulating the activity of target genes . In most instances , this deregulation involves changes of so-called “epigenetic” marks associated with the DNA that are inherited to the cellular progeny without changes in the DNA sequence . Here we describe an example where two lncRNA genes ( DLEU1 and DLEU2 ) are epigenetically deregulated together with a cluster of neighboring protein-coding tumor suppressor genes in almost all patients suffering from chronic lymphocytic leukemia . Such a common regulation suggests that the affected genes are involved in the same cellular pathway . In line with this notion , the 13q14 . 3 genes modulate the NF-kB signalling pathway , either inducing or repressing its activity . An activation of NF-kB has previously been shown to promote survival of the leukemic cells , underlining the importance of the 13q14 . 3 tumor suppressor locus for the pathomechanism of the disease . | [
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"oncology",... | 2013 | Epigenetic Upregulation of lncRNAs at 13q14.3 in Leukemia Is Linked to the In Cis Downregulation of a Gene Cluster That Targets NF-kB |
Computational efforts to identify functional elements within genomes leverage comparative sequence information by looking for regions that exhibit evidence of selective constraint . One way of detecting constrained elements is to follow a bottom-up approach by computing constraint scores for individual positions of a multiple alignment and then defining constrained elements as segments of contiguous , highly scoring nucleotide positions . Here we present GERP++ , a new tool that uses maximum likelihood evolutionary rate estimation for position-specific scoring and , in contrast to previous bottom-up methods , a novel dynamic programming approach to subsequently define constrained elements . GERP++ evaluates a richer set of candidate element breakpoints and ranks them based on statistical significance , eliminating the need for biased heuristic extension techniques . Using GERP++ we identify over 1 . 3 million constrained elements spanning over 7% of the human genome . We predict a higher fraction than earlier estimates largely due to the annotation of longer constrained elements , which improves one to one correspondence between predicted elements with known functional sequences . GERP++ is an efficient and effective tool to provide both nucleotide- and element-level constraint scores within deep multiple sequence alignments .
The identification and annotation of all functional elements in the human genome is one of the main goals of contemporary genetics in general , and the ENCODE project in particular [1] , [2] , [3] . Comparative sequence analysis , enabled by multiple sequence alignments of the human genome to dozens of mammalian species , has become a powerful tool in the pursuit of this goal , as sequence conservation due to negative selection is often a strong signal of biological function . After constructing a multiple sequence alignment , one can quantify evolutionary rates at the level of individual positions and identify segments of the alignment that show significantly elevated levels of conservation . Several computational methods for constrained element ( CE ) detection have been developed , with most falling into one of two broad categories: generative model-based approaches , which attempt to explicitly model the quantity and distribution of constraint within an alignment , and bottom-up approaches , which first estimate constraint at individual positions and then look for clusters of highly constrained positions . A widely used generative approach , phastCons [4] , uses a phylo-Hidden Markov Model ( HMM ) to find the most likely parse of the alignment into constrained and neutral hidden states . While HMMs are widely used in modeling biological sequences , they have known drawbacks: transition probabilities imply a specific geometric state duration distribution , which in the context of phastCons means predicted constrained and neutral segment length . This may bias the resulting estimates of element length and total genomic fraction under constraint . One of the leading bottom-up approaches is GERP [5] , which quantifies position-specific constraint in terms of rejected substitutions ( RS ) , the difference between the neutral rate of substitution and the observed rate as estimated by maximum likelihood , and heuristically extends contiguous segments of constrained positions ( RS>0 ) in a BLAST-like [6] manner . However , GERP is computationally slow because its maximum likelihood computation uses the Expectation Maximization algorithm [7] to estimate a new set of branch lengths for each position of the alignment; this step is also undesirable methodologically because it involves estimating k real-valued parameters from k nucleotides of data . Furthermore , the extension heuristic used by GERP ( and other bottom-up methods [8] ) may induce biases in the length of predicted CEs . In this work we present GERP++ , a novel bottom-up method for constrained element detection that like GERP uses rejected substitutions as a metric of constraint . GERP++ uses a significantly faster and more statistically robust maximum likelihood estimation procedure to compute expected rates of evolution that results in a more than 100-fold reduction in computation time . In addition , we introduce a novel criterion of grouping constrained positions into constrained elements using statistical significance as a guide and assigning p-values to our predictions . We apply a dynamic programming approach to globally predict a set of constrained elements ranked by their p-values and a concomitant false positive rate estimate . Using GERP++ we analyzed an alignment of the human genome and 33 other mammalian species , identifying over 1 . 3 million constrained elements spanning over 7% of the human genome with high confidence . Compared to previous methods , we predict a larger fraction of the human genome to be contained in constrained elements due to the annotation of many fewer but longer elements , with a very low false positive rate .
Like other bottom-up approaches , the GERP++ algorithm consists of two components: calculation of position-specific constraint scores for each column of a multiple alignment , and subsequent aggregation of neighboring columns into segments that score significantly higher than expected by chance ( Fig 1; see Methods for more detailed description ) . These are largely independent procedures: the GERP++ score for a specific position depends entirely on the nucleotides at that position and not on any global element predictions , while identification of statistically significant high-scoring segments depends only on the additivity of individual position scores and can potentially be used in conjunction with other position-specific scoring metrics . Constraint intensity at individual alignment positions is quantified in terms of “rejected substitutions” ( RS ) , defined as the number of substitutions expected under neutrality minus the number of substitutions “observed” at the position [5] . Thus , positive scores represent a substitution deficit ( which would be expected for sites under selective constraint ) , while negative scores represent a substitution surplus . To estimate this quantity at each aligned position , GERP++ begins with a pre-defined neutral tree relating the genomes present within the alignment that supplies both the total neutral rate across the entire tree and the relative length of each individual branch . For each alignment column , we estimate a scaling factor , applied uniformly to all branches of the tree , that maximizes the probability of the observed nucleotides in the alignment column . The product of the scaling factor and the neutral rate defines the ‘observed’ rate of evolution at each position . Then , in the element-finding step , GERP++ uses the position-specific RS scores to generate a set of candidate elements . For each putative element it computes a p-value based on the element's length and score ( defined as the sum of RS scores for each position within the element ) that represents the probability of observing such an element in the null model . These p-values are used to rank CEs in order of significance and report a set of non-overlapping predictions , starting with the lowest ( best ) p-value . Rather than applying a fixed cutoff , GERP++ estimates the false positive rate by randomly permuting the input RS-scores and treating any prediction within the shuffled sequence as a false positive , similar to the first version of GERP [1] , [5] . We used GERP++ to analyze the TBA alignment of the human genome to 33 other mammalian species ( the most distant mammalian species is Platypus ) spanning over 3 billion positions with a phylogenetic scope of 5 . 83 substitutions per neutral site . We identified 1 , 354 , 034 constrained elements covering 214 , 749 , 502 nucleotides , or approximately 7% of the human genome , with an estimated false positive rate of 0 . 86% at the nucleotide level ( see Methods for details ) . Compared to a slightly negative background average of −0 . 125 RS , GERP++ predictions and certain known functional elements display an elevated level of constraint , in excess of 1 . 7 RS . GERP++ elements range in size from 4 to nearly 2000 bases , with mean length of 158 . 6 nucleotides . The minimum ( 4 bases ) and maximum lengths ( 2000 bases ) are parameters of the algorithm , and the tail of the length distribution ( Fig S2A ) suggests that with a more permissive upper bound even longer elements could be identified . We observe significant variation among entire chromosomes of both average RS score and fraction of positions predicted to belong to constrained elements ( Fig 2 ) . The mean constraint level varied from −0 . 3 to −0 . 05 RS with the exception of chromosome X , which was the only chromosome with a positive average RS score , just under 0 . 1 RS . This result is consistent with earlier work [9] , which suggested that the X chromosome in rodents has a reduced mutation rate . We also observe substantial fluctuation in the fraction of each chromosome predicted to be inside constrained elements , which varied from 1% of the Y chromosome to 4–9% for other chromosomes . We expect this metric to be low for the Y chromosome because a large portion of the alignments for the Y chromosome are too shallow to perform a rate estimation , but even when adjusting for “effective” chromosome size much of the fluctuation remains ( Fig 2B ) . Surprisingly , despite a low fraction of the Y chromosome being within constrained elements , it does not have a particularly low average RS score , while the X chromosome does not exhibit a high CE fraction despite the positive average RS . In fact , there appears to be at best weak correlation between these two metrics of constraint: since the null model is derived from the actual distribution of RS scores for a given region , any ( additive ) difference in RS score applied uniformly to every position in the region would not change the p-value of any candidate element ( although in practice this would alter the exact boundaries , resulting in a slightly different candidate set ) . The chromosomal fraction within predicted constrained elements ultimately depends more on the distribution and variance of the scores rather than the mean . Unfortunately , this is impossible to quantify exactly due to confounding factors such as differences in alignment quality and depth . The only major parameter for GERP++ is a false positive rate cutoff that determines at what point the algorithm should stop generating predictions in order to avoid too many false discoveries . Throughout its execution GERP++ keeps track of the constrained elements predicted so far , as well as estimates of the number and total size of false positive predictions for the specified cutoff level . Examining how these quantities grow as the cutoff parameter increases permits us to estimate the amount of total constraint that can be detected using this methodology and give an approximate upper bound on the amount of constraint within the human genome . Let B ( c ) be the number of bases within constrained elements predicted at false positive cutoff c , and let B* ( c ) = B ( c ) −F ( c ) be the same quantity adjusted for false positive predictions by subtracting the estimated number of false positive bases ( as found in shuffled alignments ) at cutoff c . Fig 3 shows B and B* as a function of c from 0 to 50%: while B continues to increase , B* starts to level off right as B begins to grow linearly . This suggests that maxc B* ( c ) can be used to estimate the total number of bases in constrained elements that can be annotated using this method in any given region or the entire genome . Approximately 225 megabases , or nearly 7 . 3% of the human genome can be detected as contained in CEs using GERP++ at the mammalian phylogenetic scope . If we adjust for the portions of the genome where rate estimation was not performed ( but with a deeper alignment might be in the future ) , we estimate that up to 8% of the human genome consists of CEs detectable using this kind of methodology . Combined with the observation that about 190 megabases , or 6 . 2% can be detected at a false positive cutoff of 0 ( Fig 3 ) , we obtain a fairly narrow estimate of 6–8% of the human genome under detectable evolutionary constraint , in the mammalian scope . We note that this estimate depends on alignment quality , since we may fail to pinpoint constrained elements not only due to method-intrinsic limitations but also because an appropriate signal may be absent in a given multiple alignment . We next examine the relationship between evolutionary constraint and several classes of biologically important regions . Overall , coding exons exhibit by far the strongest levels of constraint , as quantified both by the average RS score within functional elements ( Fig 4A ) , and by fraction of bases that overlap the predicted CEs ( see Table 1 ) . Both 5′ and 3′ UTR regions show weaker but noticeable constraint levels and , somewhat surprisingly , introns on average have slightly lower RS scores than the overall genomic baseline . However , a nontrivial fraction of introns does exhibit evidence of constraint , as nearly 7% of intron positions overlap predicted elements ( Table 1 ) , and these positions make up a large fraction of constrained element bases ( see Fig 4B ) . Over 94% of the coding exons in the human genome overlap at least one predicted CE; conversely , only about 16% of constrained elements overlap a coding exon . CEs that overlap exons are on average ∼60 nucleotides or 40% longer , and consequently have more than two-fold higher scores , than elements that do not overlap exons ( both t-tests significant at p-value<2 . 2·10−16 ) . While overall these results are consistent with what was observed using the previous version of GERP [5] on much more limited alignments , the length difference between exon-associated and non-overlapping CEs is somewhat smaller than what was previously found . This is partially explained by the differences in the pattern of constraint between coding exons and other regions . Because the previous GERP by default only merges blocks of contiguous constrained positions if they are separated by at most one unconstrained position [5] , it is far more likely to generate longer elements in exonic regions where most unconstrained bases correspond to 3rd positions of a codon and are usually flanked by constrained positions . In noncoding regions where unconstrained positions are distributed more irregularly and often occur consecutively , the previous GERP algorithm [5] ends up fragmenting longer constrained regions and generating shorter elements . Because GERP++ does not base merging decisions on any such fixed threshold it is able to better annotate longer noncoding CEs . To further test this hypothesis , and to investigate a potentially useful signal for detecting coding exons , we introduce a metric that rigorously quantifies this pattern of constraint for any region . For any given segment , we define the 3-periodicity bias as the maximum over the 3 possible reading frames of the mean RS score at positions 1 and 2 minus the mean RS score at position 3 . This metric quantifies a periodic bias in constraint and effectively deals with unknown reading frame location and lack of a reading frame altogether , since the maximum is taken over all 3 possibilities . As Fig 5 shows , the 3-periodicity bias is a strong signal characteristic of coding exons ( mean 2 . 96 ) compared to other regions such as UTRs , introns , and ncRNAs ( mean 0 . 13–0 . 38 , difference significant at p-value<2 . 2·10−16 ) . We partitioned the constrained elements predicted by GERP++ according to exon overlap , and found that CEs overlapping coding exons have a much greater mean 3-periodicity bias ( Table 2 ) . However , the difference between CEs that did not overlap any annotated exons , and known nonexonic regions such as introns was still significant , suggesting some of these CEs intersect unannotated exonic regions . To test this hypothesis , we checked the constrained elements that did not overlap any known coding exons against exon predictions made by the computational gene prediction tool CONTRAST [10] . We found 16 , 881 CEs ( making up 1 . 5% of all CEs that did not overlap known genes ) that overlapped CONTRAST predictions , and these CEs had a significantly higher 3-periodicity bias ( 1 . 33 ) than those that did not overlap CONTRAST predictions ( 0 . 54 ) . As this latter figure is still higher than the average 3-periodicity of clearly non-exonic elements , it is possible that a fraction of these elements overlap unannotated exons or pseudogenes with recently lost function . It is interesting to note that the difference between 3-periodicity bias of GERP++ CEs that overlap known exons ( 2 . 46 ) and CEs that overlap CONTRAST predictions ( 1 . 33 ) is also significant . This is likely a combination of two factors: false positives ( or errors in identifying the exact boundary ) in CONTRAST predictions , and selection bias that manifests as exons with higher 3-periodicity being more conserved and/or easier to identify , and thus annotated in the UCSC Known Genes set . We compared the GERP++ constrained element predictions in placental mammals ( see Methods ) to phastCons [4] , the leading generative model-based tool . Not surprisingly , we found significant overlap between GERP++ and phastCons predictions: 80% of GERP++ predictions overlapped at least one phastCons prediction , and vice versa . However , aside from both algorithms detecting clearly constrained areas , there are substantial differences: GERP++ predicts significantly fewer elements , which are much longer on average ( see Fig S2B for distribution of phastCons element lengths ) and cover a substantially larger portion of the human genome - almost twice as much as the 4% predicted by phastCons ( Fig 6A ) . As a result , on a nucleotide level GERP++ overlaps 90% of phastCons predictions while only half of GERP++ CE positions are covered by phastCons . Part of the reason for these differences is that often phastCons predicts multiple elements where GERP++ makes one longer prediction . PhastCons thus skips intermediate positions which may be under weaker constraint yet still part of one large functional element , as the example in Fig 6E shows . In order to demonstrate that this is not an isolated occurrence and to quantify fragmentation of known functional elements , we computed the number of distinct predicted constrained elements overlapping each annotated coding exon . While the total number of exons that overlap at least one constrained element prediction is approximately the same between the two methods , GERP++ is significantly more effective at identifying entire exons as a single predicted CE , rather than fragmented between two or more CEs like phastCons ( Fig 6C & 6D ) . This phenomenon is not limited to coding exons , as we observed similar behavior for experimentally identified RNA Polymerase II ( PolII ) binding sites ( see Methods ) , which correspond to poised or active promoters . GERP++ overlaps a larger fraction of nucleotides within 50 base pairs of a PolII binding site ( 26% vs 19% for phastCons ) , and exhibits similarly reduced fragmentation as with coding exons ( Fig 7 ) . Due in part to its ability to annotate larger elements in one piece , GERP++ is more effective at predicting constraint within several types of known functional regions . At the nucleotide level GERP++ elements cover a substantially larger fraction of several major types of functional elements , especially coding exons and UTRs ( Fig 6B ) . The improved resolution in detection of known functional elements suggests GERP++ may also be more effective at predicting unannotated regions that are not only constrained but also functional .
One of the main challenges in constrained element detection is the lack of a clear gold standard for evaluating the quality of predictions . Human functional elements are sometimes unconstrained at the mammalian scope or missed at the assembly or alignment stages , and CE predictions that do not correspond to any known annotations may have unknown function , and cannot be definitively considered false positives . Given these limitations , we have shown that GERP++ offers several advantages over its predecessor GERP and makes fewer assumptions about the shape of conservation than previous approaches such as PhastCons . Previous bottom-up approaches have been limited largely by the simple heuristics used to merge constrained positions into longer elements; these heuristics may introduce biases in element length due to patterned constraint such as the 3-periodicity in coding exons . With GERP++ we evaluate a much richer set of candidate elements , selecting and ranking final predictions according to statistically meaningful p-values . Despite the added computational cost at this stage , GERP++ overall is more than 100 times faster than GERP due to the speedup in rate estimation . Because GERP++ estimates a single parameter that directly translates into evolutionary rate , rather than an independent parameter for each branch of the tree , the computation is not only faster but also results in more statistically robust estimates as alignment depth increases . GERP++ takes a few days on a typical machine or a few hours on a small cluster to complete an analysis of the human genome aligned to 33 mammalian species , and can scale to virtually any reasonable genome size and alignment depth . Our understanding of the evolutionary forces constraining sequence variation is still limited , especially in noncoding regions . This presents a challenge for generative model-based approaches , which model implicitly or explicitly the distribution of length and intensity of constrained elements and the total genomic fraction under constraint . In contrast , rate estimation and element prediction in GERP++ are largely independent procedures , and while GERP's rejected substitution metric [5] accurately quantifies constraint intensity at individual positions , any additive position-specific scoring scheme could potentially be used instead . For example , in future implementations of the GERP++ package more elaborate or context-dependent models of nucleotide evolution could be easily incorporated in order to improve position-specific evolutionary rate estimation without drastically changing the overall algorithm . One drawback of GERP++ and other similar approaches is sensitivity to variation in and erroneous estimates of the neutral rate of substitution . Neutral rate estimates are often subject to some uncertainty and can vary depending on the methodology , alignment quality , and genomic region . To test the ability of GERP++ to tolerate a reasonable amount of error in neutral rate estimates , we repeated our analysis with the neutral tree scaled up or down by 5 or 10% . Not surprisingly , overestimating the neutral rate leads to overprediction of constraint , and vice versa . For a fixed false positive cutoff , we observed a linear relationship between the input neutral rate and the amount of constrained element bases predicted; a 5/10% change in neutral rate leads to approximately 8/15% change in the number of predicted constrained bases . It is important to note that our false positive rates and p-values are computed based on the implicit assumption that the score distribution is homogeneous within a region and all sites are independent . While this assumption has been present in previous approaches that also relied in permuted alignments for false positive rate estimation , it is central to the GERP++ p-value computation . Finally , the greedy manner of resolving candidate element overlap conflicts by smallest p-value presents another potential limitation , as for elements with equal average constraint this will break ties in favor of the longer element . This may or may not be biologically meaningful , especially if complicated conservation patterns are involved or two strongly conserved functional elements are very close together ( and the segment between them is at least somewhat constrained ) . These hypothetical effects are likely mitigated by GERP++'s position-specific scores , which enable higher resolution analysis within individual CEs , and which ultimately may be the criterion upon which to decide whether any particular long element may better be regarded as two shorter ones . GERP++ recapitulates known biology , at both the nucleotide level and on the scale of entire functional elements and even chromosomes . GERP++ scores are accurate enough to obtain a strong signal of synonymous substitution in coding exons , and the elevated average RS score for chromosome X ( Fig 2A ) agrees with earlier findings [2] , [3] . Compared to phastCons , GERP++ predictions overlap a larger fraction of known functional elements ( Fig 4B ) and have greater 1∶1 correspondence to constrained coding exons ( Fig 6C & 6D ) and promoters ( Fig 7 ) . Our analysis has also yielded interesting biological insights , including the likely presence of unannotated coding exons among our predicted constrained elements . We detect around 7% of the human genome to be contained in CEs in the mammalian scope , a slightly larger amount than previous predictions , yet with a lower estimated false positive rate . While this estimate is inexact , our analysis suggests 6% and 8% as reasonable lower and upper bounds , a somewhat tighter range than earlier estimates [1] , [2] . Computationally , GERP++ is efficient enough to perform whole-genome analysis of deep mammalian alignments within a few cpu-days , making it suitable for high-throughput analysis of the ever increasing amounts of genomic data . We hope GERP++ will prove to be a useful tool in analyzing , quantifying , and annotating constraint and discovering novel functional elements in the human and other genomes for which sufficient comparative data exist .
GERP++ is available at http://mendel . stanford . edu/SidowLab/downloads/gerp/index . html Given a multiple sequence alignment and a phylogenetic tree with branch lengths representing the neutral rate between the species within that alignment , GERP++ quantifies constraint intensity at each individual position in terms of rejected substitutions [5] , the difference between the neutral rate and the estimated evolutionary rate at the position . For our analysis the alignment was compressed to remove gaps in the reference sequence ( human ) , although the RS score computation algorithm does not assume any specific reference sequence . In order to estimate the evolutionary rate we model nucleotide evolution as a continuous-time Markov process , which specifies for each pair of nucleotides a and b and duration t the probability of a transforming into b over time t , designated by pab ( t ) . Many such evolutionary models have been developed [11] , [12] , each with its own set of simplifying assumptions . GERP++ implements the HKY85 model [13] , but any time-reversible model ( where papab ( t ) = pbpba ( t ) for all pairs of nucleotides a and b ) that permits efficient computation of pab ( t ) can be used instead . For each individual alignment column GERP++ labels the leaves of the phylogenetic tree with the corresponding nucleotides c1 , … , ck; gapped species are projected out . Although this is not necessarily ideal and sometimes leads to information loss , it avoids some of the common difficulties and potentially serious biases that accompany modeling gaps in alignments: aligner errors and artifacts that result from simplified gap penalties and incorrect handling of duplications and rearrangements , assembly mistakes , and missing sequence data . Furthermore , this treatment of gaps avoids explicitly penalizing constrained elements that have undergone lineage-specific deletion [5] . Once the gapped species are removed , the site-specific neutral rate is computed as the sum of the branch lengths in the trimmed tree . When there are fewer than 3 species remaining no rate estimation is performed for that position , as there are not enough species to even form a valid tree . We estimate by maximum likelihood a homogeneous scaling factor of the neutral tree at each position; similar but independently developed methods were used for rate estimation in [14] , [15] . Specifically , we introduce a scaling parameter r that represents the site's rate of evolution relative to neutrality . When r<1 the quantity ( 1−r ) can be naturally interpreted as the fraction of neutral substitutions “rejected” by evolutionary selection . GERP++ estimates r by maximum likelihood , where the likelihood is given by L ( r ) = Pr ( c1 , … , ck | Tr ) , where Tr is the neutral tree T scaled by r . For any given r , and therefore fixed tree Tr , this function can be computed efficiently using a dynamic programming algorithm due to Felsenstein [16] . If n is an internal node with children n1 and n2 , and {c1 , … , ck}n represents the subset of the leaves corresponding to the subtree rooted at n , thenwhere Tr ( x , y ) is the branch lengths in Tr between two neighboring nodes x and y . Since the leaf nucleotides are observed , this equation can be used to compute the subtree probability for all internal nodes , starting at the bottom and reaching the root , where we can compute L ( r ) = Pr ( c1 , … , ck | Tr ) = Σa Pr ( {c1 , … , ck}n | root = a ) pa . Assuming a fixed alphabet and an evolutionary model where the probabilities pab ( t ) are computable in constant time , this algorithm runs in time O ( k ) where k is the number of species in the phylogenetic tree . Using this algorithm as a subroutine to calculate L ( r ) , GERP++ computes the maximum likelihood value of r using Brent's method [17] , [18] , a numerical optimization technique that tends to require relatively few computations of the function being optimized . The evolutionary rate for a site with neutral rate n is estimated to be rn , and the final RS score is computed as n−rn = n ( 1−r ) . As maximum likelihood may estimate very large or even infinite values of r , we impose a cap of r = 3 on GERP++ rate estimates , yielding RS scores that range between −2n and +n . These scores are then used as the basis for prediction of constrained elements within the region . Given position-specific constraint scores , GERP++ generates a list of elements that exhibit evidence of evolutionary constraint beyond what is likely to occur by chance . For each element , we compute a p-value that represents the probability of a random neutral segment of equal length having an equal or higher RS score . In addition to being used to select final predictions from the set of candidate elements , these p-values in conjunction with position-specific scores provide useful information for biological analysis . Every segment of contiguous multiple alignment columns is a candidate element . Because considering all possible segments within the alignment is computationally infeasible , GERP++ generates a list of candidate elements using several simple biological heuristics to prune the possibilities . First , we impose a user-specified minimum and maximum on candidate element length; while real functional elements vary in length , very few extend beyond several thousand bases , and even these will not be missed entirely as GERP++ will identify their most constrained parts . Second , since positive RS scores indicate constraint , GERP++ allows only candidate elements that start and end at positions with RS≥0 and cannot be extended further in either direction; this rule has the additional benefit of imposing sensible boundary conditions on predicted elements . Finally , we only consider candidate elements with score above a certain value , which is a function of the element length and the median neutral rate of the region . This allows pruning of candidate elements that have low scores relative to their lengths , and since they will end up with poor p-values anyway ignoring them early reduces the memory requirements considerably . Using neutrality as the null hypothesis , we can now define p-values for candidate and predicted elements on the basis of score and length . If the probability of a single neutral position having RS score x is given by P ( x ) , then for an element of length L and score S the p-value is the probability of having score at least S in exactly L positions , and is given by:The RS score distribution is irregular ( Fig S3 ) and therefore cannot be easily modeled by common statistical distributions; however , the p-values can be computed using dynamic programming , for L = 1 , … , Lmax , provided the distribution P ( x ) can be computed and the space of possible scores x is not too large . The latter is assured by discretizing to within a specified tolerance t; since individual scores range from −2n to +n , there are 3n/t possible discretized scores . We now build a histogram of these discrete scores from the alignment , with two exceptions . First , we exclude long consecutive runs of “shallow” positions ( default at least 10 ) , i . e . positions with neutral rate below specified cutoff ( default 0 . 5 substitutions per site ) , as there are many such primate-specific regions and they tend to skew the score distribution . Additionally , remaining shallow positions are given a small penalty to discourage GERP++ from predicting CEs consisting mostly of shallow positions . Second , we exclude positions that belong to clearly constrained regions , which are identified using a preliminary pass of the algorithm ( with false positive cutoff set to 0 ) . All other scores are used to build a score histogram for each region . In order to eliminate artifacts caused by zero probabilities , we add a small uniform prior to the histogram to ensure every discretized score appears at least once . Once all candidate elements have been assigned p-values , GERP++ selects elements in a greedy manner , from smallest to highest p-value , discarding any elements that overlap previously reported elements . As the p-value increases so does the expected false positive rate of our predictions; when this reaches a user-specified threshold the algorithm terminates . While it would be ideal to compute this directly from the p-values , the multiple hypothesis correction in this case is non-trivial because GERP++ reports a non-overlapping set of predictions . Therefore , we adopt the approach of Cooper et al [2] , [5] and estimate the false positive rate by generating several independent permuted alignments . These alignments are obtained by randomly shuffling columns of the original multiple alignments , excluding long stretches of shallow positions . TBA [19] alignments of the human genome ( hg18 ) to 43 other vertebrate species were obtained from the UCSC genome browser [20] , [21] together with a phylogenetic tree with the generally accepted topology ( Fig S1 ) and neutral branch lengths estimated from 4-fold degenerate sites . Both the tree and alignments were projected to the 34 mammalian species . The alignment was compressed to remove gaps in the human sequence , and GERP++ scores were computed for every position with at least 3 ungapped species present , or approximately 88 . 9% of the 3 . 08 billion positions on the 22 autosomes and X/Y chromosomes . We used the HKY85 [13] model of evolution with the transition/transversion ratio set to 2 . 0 and nucleotide frequencies estimated from the multiple alignment . To limit memory requirements and allow parallelization of the constrained element computation , each chromosome was broken up into regions of approximately 2 megabases , with long segments where no RS score was computed chosen as boundaries . These boundary segments contain no information usable by GERP++ and because the algorithm never annotates constrained elements spanning them , excluding such segments did not sacrifice any predictive ability . These boundary regions made up approximately 6 . 8% of the human genome , including a 30 . 2 megabase region that made up more than half of chromosome Y . Constrained element predictions were generated using default parameters and a 5% false positive cutoff measured in terms of number of predictions; the estimated nucleotide-level false positive rate was under 1% . As additional validation , we computed overlap between our predictions and a set of ancestral repeats ( L2 ) annotated by RepeatMasker . We found the overlap to be in line with what we expected given our estimated false positive rates: about 5% of the repeats overlap a predicted CE , with around 1 . 6% nucleotide-level overlap . Gene , noncoding RNA , and PhastCons conserved element annotations were obtained from the UCSC genome browser's [20] , [21] Known Genes [22] , RNA Genes , and Conservation [4] tracks respectively . To avoid skewed statistics due to alternative splicing , gene annotations were resolved to a consistent nonoverlapping set where any segment belonging to multiple conflicting annotations was assigned a single annotation in the following order of priority: coding exon , 5′ UTR , 3′ UTR , intron . For meaningful comparison against phastCons , separate GERP++ scores and constrained elements were generated according to the same procedure as above but using only placental mammal data ( ignoring platypus and opossum in the alignment and projecting them out of the phylogenetic tree ) . PolII binding regions were defined as 50 bp upstream and downstream of PolII binding ‘peaks’ as identified from ChIP-seq experiments performed by the ENCODE Consortium [3] . A 100 bp window allows capture of the likely PolII binding site and its flanking sequence . We obtained data from nine ChIP-seq experiments conducted in two labs ( the Snyder lab at Yale and the Myers lab at Hudson Alpha ) on six cell types . Data was downloaded through the DCC at UCSC ( ftp://encodeftp . cse . ucsc . edu ) . All data have passed publication embargo periods . Overlap statistics were calculated as described above for other annotation sets and averaged across all nine experiments . | There are millions of sequences in the human genome that perform essential functions , such as protein-coding exons , noncoding RNAs , and regulatory sequences that control the transcription of genes . However , these functional sequences are embedded in a background of DNA that serves no discernible function . Thus , a major challenge in the field of genomics is the accurate identification of functional sequences in the human genome . One approach to identify functional sequences is to align the genome sequences of many divergent species and search for sequences whose similarity has been maintained during evolution . We have developed GERP++ , a software tool that utilizes this “comparative genomics” approach to identify putatively functional sequences . Given a multiple sequence alignment , GERP++ identifies sites under evolutionary constraint , i . e . , sites that show fewer substitutions than would be expected to occur during neutral evolution . GERP++ then aggregates these sites into longer , potentially functional sequences called constrained elements . Using GERP++ results in improved resolution of functional sequence elements in the human genome and reveals that a higher proportion of the human genome is under evolutionary constraint ( ∼7% ) than was previously estimated . | [
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"c... | 2010 | Identifying a High Fraction of the Human Genome to be under Selective Constraint Using GERP++ |
Mycobacterium ulcerans is the causative agent of Buruli ulcer ( BU ) . In West Africa there is an association between BU and residence in low-lying rural villages where aquatic sources are plentiful . Infection occurs through unknown environmental exposure; human-to-human infection is rare . Molecular evidence for M . ulcerans in environmental samples is well documented , but the association of M . ulcerans in the environment with Buruli ulcer has not been studied in West Africa in an area with accurate case data . Environmental samples were collected from twenty-five villages in three communes of Benin . Sites sampled included 12 BU endemic villages within the Ouheme and Couffo River drainages and 13 villages near the Mono River and along the coast or ridge where BU has never been identified . Triplicate water filtrand samples from major water sources and samples from three dominant aquatic plant species were collected . Detection of M . ulcerans was based on quantitative polymerase chain reaction . Results show a significant association between M . ulcerans in environmental samples and Buruli ulcer cases in a village ( p = 0 . 0001 ) . A “dose response” was observed in that increasing numbers of M . ulceran- positive environmental samples were associated with increasing prevalence of BU cases ( R2 = 0 . 586 ) . This study provides the first spatial data on the overlap of M . ulcerans in the environment and BU cases in Benin where case data are based on active surveillance . The study also provides the first evidence on M . ulcerans in well-defined non-endemic sites . Most environmental pathogens are more broadly distributed in the environment than in human populations . The congruence of M . ulcerans in the environment and human infection raises the possibility that humans play a role in the ecology of M . ulcerans . Methods developed could be useful for identifying new areas where humans may be at high risk for BU .
Mycobacterium ulcerans is the causative agent of Buruli ulcer , a necrotizing skin disease prevalent in at least 30 subtropical countries [1] . In Africa , close to 30 , 000 cases were reported between 2005 and 2010 [2] . Cote d'Ivoire , with the highest incidence , reported 2533 cases in 2010 . The major virulence determinant in M . ulcerans is a macrolide , mycolactone that is responsible for the necrosis and immunosuppression characteristic of Buruli ulcer [3] . Genes for mycolactone biosynthesis form a 110 kb cluster on a large 174KB plasmid [4] . Identification of M . ulcerans in the environment is based upon PCR amplification of mycolactone gene sequence , and two insertion sequences ( IS2404 and IS2606 ) present in high copy number in M . ulcerans [5]–[8] . Although mycolactone-encoding plasmids have been found in other mycobacterial species in the M . marinum complex as well as in unique clades of M . marinum none of these species have been identified in Africa . M . ulcerans transmission is still not understood; however it is likely to occur from contact with the environment [1] . There is little evidence of person-to-person transmission though rare cases of possible human-to-human transmission have been described [9] . Residence near an aquatic environment has been identified as a consistent risk factor for infection in Africa [10]–[12] . However , the association of M . ulcerans with water is a large-scale ( e . g . , regional ) association; contact with water per se has not been directly implicated as a risk factor for Buruli ulcer . In fact , some groups most closely associated with prolonged and frequent water contact such as fisherman , are not at high risk for infection [13] , [14] . The completion of the M . ulcerans genome sequence in 2004 by Stinear et al . provided a portrait of a species undergoing reductive evolution [15] . The identification of the unique high copy number insertion sequences IS2404 and IS2606 in M . ulcerans along with genes encoding mycolactone biosynthesis led to the development of molecular tools for identification of M . ulcerans in environmental samples [4] . More recently , variable number tandem repeat ( VNTR ) typing and SNP analysis has been used to discriminate between Ghanaian M . ulcerans isolates [6] , [16] , [17] . In the past 10 years , there have been numerous reports of M . ulcerans DNA in aquatic samples collected in Buruli ulcer endemic regions of West Africa [18]–[22] . Using IS2404-PCR , M . ulcerans DNA has been detected in many species of invertebrates , as well as in fish , snails and frogs [18] , [19] . In a collection of 57 hemipterans in a BU endemic area in Benin , Kotlowski et al . detected M . ulcerans DNA in 4/5 taxa of predaceous hemipterans [18] . M . ulcerans DNA has also been detected in association with water plants , and in a number of aquatic invertebrate species by groups working in Cote d'Ivoire and Cameroon [19]–[21] . More recent standards for identification of M . ulcerans DNA in environmental samples require detection of both IS2404 and sequence associated with enoyl reductase ( ER ) or ketoreductase ( KR ) domains from the polyketide synthase genes which encode mycolatone ( mlsA , mlsB ) . Using these criteria , qPCR was used to detect M . ulcerans DNA in one endemic and two non-endemic villages in Ghana [22] . In this study , 148 environmental samples including water ( N = 13 ) , detritus ( N = 45 ) , tree trunk biofilm ( N = 45 ) and plant biofilm ( N = 45 ) were tested for M . ulcerans . M . ulcerans was detected in only 1 water sample from an endemic village; all other samples were negative [22] . In the only large-scale study where environmental samples were collected by standard sampling methods , M . ulcerans DNA was detected in both BU endemic and non-endemic villages within adjacent districts in Ghana . Although M . ulcerans DNA was detected in 12 . 8% ( 15/117 ) of predaceous hemipterans samples , M . ulcerans DNA was not detected in 59 of the 89 primarily invertebrate taxa collected [6] . Using conventional PCR , M . ulcerans DNA was detected in 8/82 ( 9 . 8% ) water samples , results comparable to data from the qPCR study reported from Ghana ( 7 . 7% ) [6] , [22] . The most unexpected result from this study was that M . ulcerans was detected equally in samples from BU endemic and non-endemic villages . In this study , BU epidemiology was based on passive surveillance . When teams were later sent to the same villages to conduct active case finding , BU cases were detected in nearly all of the villages previously labeled non-endemic . Although several studies have been published in the past 10 years on detection of M . ulcerans DNA in the environment , it is difficult to glean robust , comparative data because of the lack of details on sampling methodology , methods for ecological sampling , lack of data from “control” sites , and lack of accurate epidemiological data . In the present study we have used standardized , consistent sampling methods , and multiple target , serial qPCR , to identify M . ulcerans DNA in environmental samples from 25 villages in Benin . Highly accurate prevalence data , based on the active surveillance program established by the National Buruli Ulcer Program , made it possible to compare the presence of M . ulcerans in the environment with Buruli ulcer cases in 22 of these villages . Environmental samples included water filtrand from major village water sources , and dominant plant samples , along with random invertebrate , excrement , and soil samples . Samples were assayed for M . ulcerans DNA and DNA from other mycolactone producing mycobacteria ( MPM ) using serial , quantitative PCR analysis first targeting IS2404 followed by the enoyl reductase ( ER ) domain found on the plasmid responsible for mycolactone . Results of this study show a positive relationship between bacterial distribution among environmental samples and community disease burden . Not only did PCR positive results have high predictive value for BU endemicity , the number of positive samples showed a positive correlation with BU prevalence .
Environmental samples analyzed in this study were collected from a total of 25 villages . Of the 25 total villages sampled , 22 of these had prevalence ( number of Buruli ulcer cases/1000 people ) data based on village-based active case surveillance program that had been in place for over five years ( Figure 1 ) . In this program , data has been collected monthly in each village on cutaneous lesions with patients being sent to Lalo Health Center for confirmation . Quarterly site visits have been made by health center personnel to validate data collected by community volunteers . Villages were located in the Couffo , Ouhémé , or Mono River basins , near the coast or along a ridge at 100 M adjacent to endemic sites along the Ouhémé River . Quantitative analysis of M . ulcerans DNA was performed on samples collected from all villages ( N = 25 villages ) ; however , comparisons between M . ulcerans presence and abundance and Buruli ulcer prevalence could only be made with 22 of the 25 villages with known prevalence data . Elevation values were derived from 90 m resolution NASA Shuttle Radar Topographic Mission ( SRTM ) ( 2000 ) digital elevation model ( DEM ) data , acquired from the University of Maryland Global Land cover Facility ( http://glcf . umiacs . umd . edu/data/srtm ) . Elevation sinks were filled before extracting values corresponding to specific village locations using ArcGIS 9 . 3 software program ( ESRI Inc . , Redlands , CA ) . Standard operating procedures for quality assurance of molecular analyses were strictly followed according to the Quality Assurance/Quality Control Guidance for Laboratories Performing PCR analyses on Environmental Samples and microbial source tracking by the Environmental Protection Agency , USA [23] . Ten-percent of samples were sent to two independent laboratories for evaluation as part of a quality control program ( Table S1 ) . Statistical analyses were performed using SPSS Statistics 19 . 0 . Chi-square and Bonferroni post-hoc tests were used to determine whether there were significant differences in IS2404 and ER positivity between sample matrices and matrix positivity and endemicity . The Fisher's exact test was used to determine whether IS2404 and/or ER positivity was positively associated with Buruli ulcer endemicity . Pearson's correlation was used to determine whether there was a correlation between IS2404 and ER positivity and Buruli ulcer prevalence , and linear regression was used to model the relationships between IS2404 and ER with Buruli ulcer prevalence . Significance was defined as p≤0 . 05 .
Although Buruli ulcer has been consistently associated with residence in low-lying areas where water accumulates , none of the sites previously studied included low-lying swamp areas close to the coast . Altitude was incorporated into our study of 25 villages to determine how broadly the association between low altitude and Buruli ulcer held true . Our results showed a unimodal distribution with respect to altitude . Villages with 5 year BU prevalence less than 15 cases/1000 population were most common either at elevations less than 25 m ( Figure 1 ) , or at high elevations ( 90–100 m ) . Three villages with BU prevalence greater than 20 cases/1000 population were situated between 20–50 meters . Three of the non-endemic villages , Athieme , Zounhomne and Se , lie within the Mono River drainage , an area in which Buruli ulcer has never been reported , and another 3 ( Wedjame , Tangnigbadji and Koundokpoe Center ) are located on a high ridge adjacent to the Oehme River ( 110 m , 109 m , and 90 m respectively ) . The remaining 4 non-endemic villages are less than 18 km from the coast and include Guezin in the Couffo delta , Djegbadji on the coast , and Vekky degbadji and So-Ava near the mouth of the Oehme River . Although high BU prevalence is characteristic of communities upstream on the Couffo and Oehme rivers , BU is absent or at very low prevalence in communities near the mouth of these rivers . Water bodies in these communities consist of brackish water most of the year . However , during the rainy season a large influx of fresh water decreases the salinity of these aquatic habitats [24] . Accurate longitudinal case data were available for 22 of the 25 sampled villages ( Table 1 ) . From these , 21 villages had analytes that were IS2404 positive suggesting the possible presence of M . ulcerans . IS2404 positive samples were detected in 9/10 non-endemic villages and 12/12 endemic villages . However , when IS2404 positive samples were analyzed for the presence of a second target , the enoyl reductase ( ER ) domain required for mycolactone synthesis , only 2/10 non-endemic villages had samples that were ER positive , whereas 9/12 endemic villages had ER positive samples ( Table 1 ) . IS2404-PCR showed a positive predictive value of 12/12 ( 100% ) for endemic villages , but IS2404 alone only accurately predicted 1/10 non-endemic villages ( 10% ) . The overall predictive value of IS2404-PCR alone for the BU status of all sites was 13/22 ( 59% ) . The overall predictive value of ER-PCR on IS2404 positive samples for BU status was 17/22 ( 77%; p = 0 . 0011 ) . The additional use of the ER probe accurately predicted 9/12 endemic sites ( 75% ) , and 8/10 ( 80% ) non-endemic villages ( p = 0 . 0574 ) . The average ct values of IS2404 positive samples was 37 . 25 suggesting the possibility that lower bacterial abundance may explain the failure to detect ER from some IS2404 positive samples , rather than a lack of specificity to M . ulcerans or other MPMs . There was no significant difference , however , between the average ct values in samples collected from endemic or non-endemic habitats ( p = 0 . 08 ) . It was possible to estimate the numbers of M . ulcerans DNA in environmental samples using ER-PCR in 92% ( 12/13 ) of IS2404 positive samples whose ct values ranged from 27 . 68 to 34 . 85 ( Table S2 ) . The ability to estimate bacterial burden fell as the ct value increased . Bacterial numbers could be estimated by ER-PCR in 44% ( 11/25 ) of samples whose IS2404 ct values ranged from 35 . 43 and 36 . 97 and only in 19% ( 15/78 ) of samples whose IS2404 ct values ranged from 37 . 03 and 39 . 88 ( Table S2 ) . Forty IS2404 negative samples were tested with ER-PCR and none were found positive . If M . ulcerans were contracted through environmental exposure , it would be expected that the extent of M . ulcerans in the environment would correlate with the extent of Buruli ulcer disease in humans if surveillance and reporting were accurate . To test this hypothesis we compared PCR positivity with BU prevalence in that site ( Table 1 ) . The numbers of samples taken per site differed , because sites differed in the number of water sources . However , as seen in Figure 3 , there was a reasonable and statistically significant linear relationship between numbers of M . ulcerans positive samples and the prevalence of Buruli ulcer cases . M . ulcerans DNA was found in 40–75% of the samples tested in four highly endemic communities ( Akpome , Yamanto , Tchi-Ahomadegbe , and Tandji ) with BU prevalence above 10/1000 . With few exceptions , less than 25% of environmental samples were positive from sites with BU prevalence below 10/1000 ( Table 1 ) . Using Pearson's test of correlation , IS2404 positivity was strongly correlated with Buruli ulcer prevalence ( ρ = 0 . 674; p = 0 . 0001 ) as was ER positivity ( ρ = 0 . 765; p = 0 . 0001 ) . There was a significant linear relationship of Buruli ulcer prevalence and IS2404 and ER positivity , with 45% and 59% of the variation in BU prevalence explained by IS2404 ( R2 = 0 . 454 ) and ER positivity ( R2 = 0 . 586 ) , respectively . Thus , although the numbers of IS2404 positive samples/site were correlated with BU prevalence , serial PCR using IS2404-PCR followed by ER-PCR on IS2404 positive samples substantially improved the ability ( by 14% ) to predict Buruli ulcer prevalence at a site based on PCR results from environmental samples ( Figure 3 ) . In order to determine the presence and abundance of M . ulcerans within and around water sources , 275 samples were collected from 25 villages ( Table 2 ) . Samples were collected from eight different matrices . Water filtrand samples had a consistently higher positivity than any other matrix assayed . Twenty of the forty-seven well water filtrand samples collected were positive for IS2404 . From these 20 , 14 were positive for ER DNA , and the mean bacterial load was 1 . 68×103 GU/mL . Thirty-five pond or river filtrand samples were positive for IS2404 , and 15 of these were also positive for ER . Mean genome units were 1 . 68×103 GU/mL . Nine water filtrand samples were collected from cisterns . Of these , four contained IS2404 , and one contained both IS2404 and ER DNA ( Table 2 ) . Three of the six IS2404 positive biofilm samples ( N = 19 total collected ) contained ER DNA with a mean quantity of 4 . 04×104 GU/sample . Twelve of the 46 soil samples were IS2404 positive . Out of these , three were also positive for ER . Soil samples contained the highest quantity of M . ulcerans DNA with a mean quantity of 3 . 18×106 GU/sample . Thirty-six of 69 macrophytes contained IS2404 DNA . Of these , two were also positive for ER . One macrophyte sample had 1 . 07×104 GU/sample and one had 1 . 08×104 GU/mL , with a mean quantity of 1 . 07×104 GU/sample . One of two excrement samples and one of nine invertebrate/vertebrate samples were positive for IS2404 , however neither matrix was positive for ER . Collectively , water filtrand had the highest positivity from all other matrices sampled , and well filtrand had the highest overall positivity . There was no significant difference in IS2404 positivity between matrices ( p = 0 . 071 ) , but there were significantly more ER positive samples from well filtrand than from soil and macrophytes ( p = 0 . 004 and . 0001 respectively ) , and pond/river filtrand had significantly more ER positive samples than macrophytes ( p = 0 . 001 ) . Matrices were also analyzed with respect to positivity and endemicity . There was a significantly higher number of positive samples from well filtrand collected in endemic villages compared to well filtrand samples analyzed from non-endemic villages ( p = 0 . 001 ) . Neither IS2404 nor ER positivity differed significantly between endemic and non-endemic sites for any other matrix .
This is the first large-scale spatial study in West Africa in which the distribution of M . ulcerans in the environment and cases of Buruli ulcer were mapped using longitudinal Buruli ulcer case data based on active surveillance . A major finding from this study was the identification of a positive relationship between the presence and abundance of M . ulcerans DNA in a village , and the numbers of Buruli ulcer cases in humans . These results contrast significantly with those of our earlier large-scale study conducted in Ghana [6] , [25] where M . ulcerans DNA was detected in the environment equally in endemic and non-endemic villages . How can these discrepancies be explained ? We think the primary reason for these different findings lies in the methods used to detect and report BU cases in Benin and Ghana . In Benin , a program of monthly active case detection using community volunteers has been well established since 2004 . Active surveillance has generated highly accurate case data though it is labor intensive . In Ghana , BU cases are spread over a much larger geographic region , and case detection has relied on passive surveillance , a much less accurate epidemiological method [6] , [26]–[28] . There were also differences between the environmental sampling conducted in Benin and Ghana . Although water filtrand , plants and soil were sampled using similar methodology in both countries , invertebrates made up a large portion of the samples collected in Ghana whereas standardized sampling of invertebrates was not conducted in Benin [6] . The results from the study in Ghana were based on conventional PCR whereas qPCR was used for sample analysis in Benin . Of these factors we consider the difference in accuracy of case detection to be the most likely explanation for the fact that a significant correlation between BU cases and the presence of M . ulcerans in the environment was found in Benin but not in Ghana . More recently , our team , as well as other Ghanaian field teams , has discovered Buruli ulcer in many Ghanaian communities previously designated non-endemic . Results from this study provide strong advocacy for the use of prevalence data from active case surveillance as a basis for any study attempting to link Buruli ulcer with M . ulcerans in environmental samples . Geography may play a role in the distribution of M . ulcerans as well as in the distribution of Buruli ulcer prevalence . Villages with less than 15/1000 BU cases were located at elevations less than 25 m or at elevations greater than 80 meters , and a similar distribution was found for M . ulcerans . Villages located at the lowest elevations were , in general , close to the coast where the presence of high salinity could be inhibitory to the growth of M . ulcerans , or to the presence of M . ulcerans associated habitats . BU has been extremely rare in people living on the coast in West Africa . Our results differed from a study by Sopoh et al . where the prevalence of Buruli ulcer was correlated with lowland areas at an altitude less than 50 m [29] . However , the apparent discrepancies between these studies may lie in the difference in scope . In the Sopoh paper , study sites were located within a more narrow geographic area compared to the sites presented in this paper , and none of those sites described by Sopoh et al . were located within 30 km of the coast . Ten of the sites in this study were below 8 m and four were at sea level . None of the sites in the Sopoh et al . study were located at such low elevations . Additionally , elevation values derived from SRTM data were less precise than values obtained from the Trimble GPS unit employed by Sopoh et al . Therefore , SRTM error may have also contributed to differences in the study outcomes . Despite this limitation , our results were sufficient to confirm data showing the low prevalence of Buruli ulcer in coastal communities in West Africa . Our study confirms the necessity of serial testing with multiple PCR probes when evaluating environmental samples for presence of an organism [5]–[7] , [22] . Although IS2404 positive samples were detected in nine of ten aquatic habitats located in non-endemic villages , further evidence for M . ulcerans in these samples could only be obtained in two samples using ER-PCR . The copy number of IS2404 is at least 18 fold higher than that of the ER sequence . Threshold values ( ct ) for some IS2404 positive samples were high , suggesting the presence of too few organisms for ER detection . IS2404 has been found in several mycobacterial groups closely related to M . ulcerans in the M . marinum complex associated with aquatic environments . However a second explanation for the presence of IS2404 positive/ER negative samples in non-endemic areas is that they may reflect the presence of mycobacterial species in the M . marinum complex which are closely related to M . ulcerans but do not cause Buruli ulcer [6] . This is the first report of M . ulcerans DNA in water filtrand from wells and cisterns . However , M . ulcerans DNA has been associated with surface waters in several studies [6] , [7] , [22] . Ground and surface water exchange has been well documented [30]–[33] and this exchange is defined by floodplain geomorphology [34] . It is likely that the presence of M . ulcerans in these water sources is related to fluctuations in hydroperiod that lead to exchange of M . ulcerans or M . ulcerans DNA within the surface-groundwater continuum . Digging of wells , pits , mineral mining , or groundwater detraction converts groundwater to surface water , thus bringing the communities within groundwater to the surface , and affecting the biodiversity within the aquatic habitat [34] . Although results in this paper are consistent with results from many other studies reporting M . ulcerans DNA in natural water sources and water filtrand [6]–[8] , our data do not support a role for transmission of M . ulcerans through direct contact with water or suggest that M . ulcerans grows freely in water . Genome units of M . ulcerans in water were between 100–1000/ml . In contrast aquatic pathogens such as Vibrio cholera are often present in numbers greater than 106/ml [35] . Our results are more consistent with the hypothesis that organisms detected in water are swept into aquatic sites through run-off from precipitation or sloughing from biofilms within the aquatic habitat . Nonetheless , the fact that water run-off collects organisms from a considerable area provides a simple method for initial screening of a site to determine the likelihood of M . ulcerans in a community . One of the most intriguing aspects of our study is the clue it provides to understanding the relationship between M . ulcerans in the environment and M . ulcerans in humans . A primary feature of many environmental pathogens such as Clostridium tetani , Francisella tularensis , or Borrelia burgdorferi , is that human infection represents a dead end host for the pathogen [36]–[38] . Consistent with this relationship , the pathogen is often detected in the environment in the absence of human infection . However , not only did we find a strong relationship between the presence of M . ulcerans in the environment and the presence of Buruli ulcer in humans , we also found that the detection of M . ulcerans DNA in multiple sample types within a single village was a strong predictor of high Buruli ulcer case burden . This finding raises the interesting possibility that humans play an active role in the distribution of M . ulcerans in the environment . In recent studies , we have identified very high levels of M . ulcerans in environmental sites characterized as “high human activity” areas ( unpublished data ) . This observation is consistent with the widely reported association between Buruli ulcer and anthropomorphic changes in the environment such as sand winnowing , gold mining [39] , [40] , rice agriculture [41] or other landscape disturbance [42] , [43] and suggests that the relationship between M . ulcerans and the environment and M . ulcerans in humans may be more complex than previously appreciated . | Buruli ulcer , a severe , cutaneous disease in West and Central Africa is caused by Mycobacterium ulcerans . Person-to-person spread of M . ulcerans is rare . There is a strong epidemiological association with residence near slow moving water , but lack of accurate case data in Africa has greatly complicated transmission studies of M . ulcerans from the environment to humans . We have combined molecular tools for identification of M . ulcerans in the environment with accurate Buruli ulcer case data based on a long standing active surveillance program to map the association between Buruli ulcer and M . ulcerans in the environment in Benin . We found a positive association between M . ulcerans in the environment and Buruli ulcer cases and show that as the numbers of M . ulcerans positive samples/village increase so does the prevalence of Buruli ulcer . Many environmental pathogens are widespread in the environment in the absence of human disease . The failure to obtain definitive proof for M . ulcerans in environmental samples where Buruli ulcer is absent raises the intriguing possibility that humans play a role in the distribution of M . ulcerans . Sampling methods we have developed could be especially useful for identifying new areas where people may be at risk for Buruli ulcer . | [
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] | [
"biology"
] | 2012 | Detection of Mycobacterium ulcerans in the Environment Predicts Prevalence of Buruli Ulcer in Benin |
Schistosomiasis is a neglected tropical disease caused by Schistosoma parasites . Intervention relies on identifying high-risk regions , yet rapid Schistosoma diagnostics ( Kato-Katz stool assays ( KK ) and circulating cathodic antigen urine assays ( CCA ) ) yield different prevalence estimates . We mapped S . mansoni prevalence and delineated at-risk regions using a survey of schoolchildren in Rwanda , where Schistosoma mansoni is an endemic parasite . We asked if different diagnostics resulted in disparities in projected infection risk . Infection data was obtained from a 2014 Rwandan school-based survey that used KK and CCA diagnostics . Across 386 schools screened by CCA ( N = 19 , 217 ) . To allow for uncertainty when interpreting ambiguous CCA trace readings , which accounted for 28 . 8% of total test results , we generated two presence-absence datasets: CCA trace as positive and CCA trace as negative . Samples ( N = 9 , 175 ) from 185 schools were also screened by KK . We included land surface temperature ( LST ) and the Normalized Difference Vegetation and Normalized Difference Water Indices ( NDVI , NDWI ) as predictors in geostatistical regressions . Across 8 , 647 children tested by both methods , prevalence was 35 . 93% for CCA trace as positive , 7 . 21% for CCA trace as negative and 1 . 95% for KK . LST was identified as a risk factor using KK , whereas NDVI was a risk factor for CCA models . Models predicted high endemicity in Northern and Western regions of Rwanda , though the CCA trace as positive model identified additional high-risk areas that were overlooked by the other methods . Estimates of current burden for children at highest risk ( boys aged 5–9 years ) varied by an order of magnitude , with 671 , 856 boys projected to be infected by CCA trace as positive and only 60 , 453 projected by CCA trace as negative results . Our findings show that people in Rwanda’s Northern , Western and capital regions are at high risk of S . mansoni infection . However , variation in identification of environmental risk factors and delineation of at-risk regions using different diagnostics likely provides confusing messages to disease intervention managers . Further research and statistical analyses , such as latent class analysis , can be used to improve CCA result classification and assess its use in guiding treatment regimes .
Schistosomiasis , caused by parasitic trematode species of the genus Schistosoma , is an infectious disease affecting people throughout the world’s tropical and sub-tropical regions [1 , 2] . Chronic infections can lead to impaired growth and development in children , making schistosomiasis one of the world’s most important neglected tropical diseases [3] . Schistosomiasis is often linked to absence of access to latrines and / or clean water , which can lead to the use of freshwater bodies that can become contaminated with parasite eggs when infected people urinate or defecate while bathing , washing and swimming . Freshwater snails , often present in these water bodies , act as intermediate hosts for the parasites . Following infection of appropriate snail hosts , asexual replication occurs followed by the development of the infectious stages of the parasite which can be released into the water and infect people . Consequently , infection-related morbidity is especially common in poor agricultural areas that rely on unsanitized freshwater [4 , 5] . Globally , it is estimated that more than 779 million people live in areas with high risk of human Schistosoma transmission [6] . Infection risk is particularly high in sub-Saharan Africa , where up to 90% of the world’s infections occur [6 , 7] . Burdens in this region are enormous , matching or exceeding those related to malaria and HIV/AIDS [3] . An estimated 300 , 000 people die from schistosomiasis in Africa each year [8] . Mass delivery of anthelminthic treatment can reduce Schistosoma prevalence and facilitate major improvements to public health outcomes [9] . Mass administration of praziquantel can be cost effective , especially in areas with relatively high prevalence of infection and high transmission intensity [7 , 10] . Yet burdens are so great that mass drug administration remains unaffordable for most low-income endemic countries [9 , 11] . Steps have been taken by Merck KGaA , the United States Agency for International Development , the Bill and Melinda Gates Foundation , the British Department of International Development and the Global Network for Neglected Tropical Diseases to increase delivery of doses to sub-Saharan African countries [12] . Designing effective drug delivery programmes to reduce Schistosoma transmission is complicated by inadequate understanding of regional burdens and risk factors [13 , 14] . The geographical distributions and transmission rates of Schistosoma parasites are poorly studied in many endemic regions but are broadly known to be driven by environmental heterogeneity [15–17] . Climate or environmental variables that influence soil moisture and composition can reflect variability in molluscan host distributions and parasite larval survival rates [18–20] . Data-driven approaches to identify environmental correlates of infection risk in understudied endemic regions are imperative to design mitigation procedures . In addition to climatic and environmental heterogeneity in infection risk , uncertainty surrounding regional infection prevalence is a barrier to treatment design . The World Health Organization ( WHO ) recommends that treatment for schistosomiasis should be provided to areas of high endemism in efforts to reduce morbidity . Such treatment is important not only for morbidity control but also for current pushes to eliminate schistosomiasis where feasible [21] . Developing treatment regimens to achieve these goals relies on gathering accurate estimates of infection prevalence . Moreover , with targets for 2020–2030 now under public consultation [21] , critical assessments of inferences resulting from different diagnostic tests are needed . This is particularly true considering that different diagnostics may be chosen depending on whether a country’s specified goal is elimination as a public health problem ( morbidity control ) or interruption of transmission . However , gathering estimates of prevalence is challenging , particularly since symptoms of intestinal schistosomiasis are incredibly variable and can include headache , fever , rash , anaemia , bloody diarrhoea and abdominal pain , hepatosplenomegaly , blood in urine , burning sensation during urination , fibrosis of the bladder , and specifically in females , genital lesions which may lead to irreversible consequences , including infertility [2 , 22] . Use of rapid diagnostic tests is therefore recommended for generating estimates of prevalence . For intestinal schistosomiasis , detection of eggs in the faeces ( primarily using the Kato-Katz ( KK ) method , which involves microscopic examination of faecal smears [23] ) or of circulating cathodic antigen ( CCA ) in urine are the primary methods of choice for diagnosis of infections [24 , 25] . However , the two methods can return different prevalence estimates , with CCA generally yielding higher sensitivity [26 , 27] . The KK method may show particularly low sensitivity in low to moderate endemic areas , especially when there are many low-intensity infections [28] . Without an accurate understanding of current burdens and environmental correlates , identifying areas in need of treatment remains difficult . Geostatistical models that use up-to-date infection data and account for environmental risk factors are useful tools for producing evidence-based projections of populations at risk of Schistosoma infection [29 , 30] . Modelling assessments should ideally be formulated following adequate scrutiny of assessment of the performances and inferences that are provided by different available diagnostic methods . Rwanda is a landlocked central African country bordered by Tanzania to the East , Uganda to the North , the Democratic Republic of the Congo ( DRC ) to the West , and Burundi to the South . With a land area of 26 , 338 square kilometres and a population of over 10 . 7 million , Rwanda is one of the most densely populated countries in Africa [31] . The economy is mostly agriculture-based and the average life expectancy is 63 years [32] . Rwanda sustained widespread public health disruption as a result of political and social unrest throughout the 1990’s [33] . Health workforce training and public health outcomes have since improved , however , infectious disease monitoring and control still present major challenges [34–36] . Previous surveys suggest that Schistosoma mansoni is highly endemic and hence a parasite of high public health importance in Rwanda [34 , 37] . While some evidence suggests intestinal schistosomiasis reaches 60% prevalence or higher in certain areas , research on infection rates is limited to small-scale regional studies [1 , 38–40] . Consequently , we have a poor understanding of risk factors for schistosomiasis in Rwanda . This study aims to understand geographical variation in S . mansoni infection risk in Rwanda and to provide new insights into uncertainties in treatment pathways that can arise from variation in chosen on-the-ground diagnostic procedures . To accomplish these aims , we outline two key objectives . First , we apply geostatistical models to data from a national school-based survey in Rwanda to identify S . mansoni risk factors , map infection prevalence and delineate endemic clusters of high risk . Second , we compare geographical patterns in projected infection risk arising from the use of the CCA and KK methods . We hypothesize that infection risk will be spatially clustered within the country but that geographical disparities in the size and intensity of these clusters will arise when relying on different diagnostics , providing confusing messages to policymakers designing treatment guidelines .
Ethical clearance for this analytical study was provided by The National Ethics Committee in Rwanda ( Sep 2014 , Ref No: 261/RNEC/2014 ) . Schistosoma mansoni presence-absence data was obtained from a nationwide school-based survey undertaken in Rwanda between June and mid-July 2014 . Methods for school selection were as follows: a national sampling effort was carried out following the first nationwide surveys for prevalence of intestinal schistosomiasis and soil-transmitted helminthiasis ( STH ) in Rwandan schoolchildren , conducted between 2007 and 2008 [1] . This sampling scheme was designed to ( 1 ) provide insights into endemicity of S . mansoni across the country and ( 2 ) guide the decision of new treatment and surveillance strategies for Rwanda , in alignment with WHO guidelines [41] . The scheme took into consideration groups of sectors as administrative mapping units . Schools were chosen by selecting units likely to have similar S . mansoni transmission characteristics ( based on epidemiological characteristics such as nearby perennial water bodies ) and to ensure sample sizes in each mapping unit were statistically representative . To assess possible geographical disparities in risk mapping arising from choice of diagnostic method , infection data was obtained using both the circulating cathodic antigen ( CCA; detected in urine ) and Kato-Katz ( KK; detected in faeces ) diagnostic methods . Specifically , CCA was used to survey S . mansoni infection in schoolchildren ( aged 5 to 18 years ) across 386 schools . A single urine sample was collected from each randomly-selected participant and tested with a point of care CCA rapid test ( Rapid Medical Diagnostics , South Africa ) . A single-use pipette was used to add the drop of urine to the test cassette well , followed by a drop of the provided buffer . It should be noted that CCA tests returns negative , trace , 1+ , 2++ or 3+++ readings , which are designed to give an indication of the strength of the reading . Results were read after 20 minutes and graded into one of four intensities: 0 = negative; trace; 1+; 2++; 3+++ using a reference image showing representative incremental readings ( Supporting Information , S1 Fig ) . All CCA kits were from Rapid Medical Diagnostics Batch number 33955 , ensuring we did not need to account for possible batch-to-batch variation in trace readings . We did not use a band density reader to avoid observational bias , as it would have been extremely expensive to provide such a tool to every team in the field . Moreover , we note that even though there is an mReader that Mobile Assay and SCORE , developed in 2016 for providing quantitative CCA test results , this mReader cannot distinguish between a trace ‘true positive’ and a trace ‘false positive’ . Therefore , during this study and indeed to this day , the visual read of the intensity of the test band on the strip compared to the supplied control image is still considered standard practice in Rwanda . The KK method was also used in 174 of these schools ( concurrent urine and faecal samples were collected from the same participants ) , while a further 11 schools were surveyed using only KK ( bringing the total number of schools surveyed using KK to 185 ) . For this test , a single stool specimen was collected from each participant and duplicate thick smears were prepared for microscopic examination . Smears were assessed for presence of S . mansoni eggs by trained technicians , with each smear assessed by at least two different technicians . Quality control was performed by independent external consultants to ensure accurate diagnosis from KK microscopy . This involved random allocation of 10% of the smears for re-examination by two independent experts . For each of the visited schools , up to 50 students per school were sampled for parasite infection . However , while the original CCA datasets included 19 , 371 children , only children with complete information were included in the analysis ( children without age , sex , or geocoordinates recorded were excluded ) . As a result , the total number of children included in CCA analyses was 19 , 217 . Following removal of children with missing data , the total number of pupils ranged from 25–50 per school for CCA sampling ( mean = 49 . 78 , sd = 1 . 89 ) and from 25–50 for KK sampling ( mean = 49 . 59 , sd = 2 . 05 ) . Across the 174 schools sampled by all three methods , the number of pupils ranged from 44–50 ( mean = 49 . 70 , sd = 1 . 01 ) . Environmental measurements were extracted at the school level to be included as covariates in analyses . We extracted information for three variables likely to influence Schistosoma spp . survival and transmission . These included: average land surface temperature ( LST ) , extracted from the WorldClim database ( www . worldclim . org ) , and the Normalized Difference Vegetation and Normalized Difference Water Indices ( NDVI and NDWI ) , both extracted from the National Oceanographic and Atmospheric Administrations’ Satellite and Information Services database ( NOAASIS ) ( http://noaasis . noaa . gov/ ) . LST was included because this can influence both the density of intermediate molluscan hosts and the rate of schistosomal development within the molluscan host [42] . NDVI and NDWI variables capture local variation in vegetation , moisture and the presence of water bodies , which can impact the distributions of intermediate molluscan hosts [16 , 42 , 43] . Environmental variables were obtained using the Google Earth Engine in ArcGIS version 10 . 4 . 0 . 5524 [44] at 1km x 1km grid cell resolution and were standardized to unit variance prior to analysis . Our analysis assessed the presence of S . mansoni infection in 19 , 217 students from 386 schools who provided a urine sample for CCA assay analysis . While trace readings are recommended by the manufacturer and by the WHO [45] to be considered as positive infections , some programs have reported weaker trace readings as negative because they may not reliably confirm the presence or absence of infection [46] . For our analysis , we created two datasets for statistical analyses to account for this uncertainty when categorizing trace readings [47] . To do this , CCA tests were stratified into two separate presence-absence datasets , namely CCA with trace as positive ( i . e . only those readings of 0 were considered negative , while readings of trace , 1+ , 2+ or 3++ were considered positive ) and CCA with trace as negative ( i . e . readings of either 0 or trace were considered negative , while all other readings were considered positive ) . In addition , 9 , 175 students had stool specimens collected for Kato-Katz analyses , collected from 185 of the 386 schools . Data regarding school geolocation and participant demography ( i . e . age and sex ) was included for all observations . We stratified ages of participants into a three-level categorical variable ( 5 to 9 years old; 10 to 14; and 15 to 18 years old ) . The average age of participants included in analyses was 13 . 36 years . School polygon centroids were estimated from a shapefile representing Rwanda’s current administrative units ( obtained from the geographic data warehouse DIVA GIS ( www . diva-gis . org/Data ) ) . Parasite infection and environmental covariate data were linked to their corresponding school centroids . To assess evidence for spatial autocorrelation in infection probability , we fit logistic regression models ( binomial errors with logit link function ) using participant sex and age ( categorical variables ) and the scaled environmental predictors LST , NDVI and NDWI . Correlations between environmental covariates were investigated using Pearson’s correlations . Residuals were extracted and examined with semivariograms ( calculated using functions in the ‘geoR’ package [48] ) in R version 3 . 1 . 1 ( The R foundation for statistical computing , Vienna , Austria , http://www . R-project . org ) . A semivariogram is a graphical representation of the spatial variation in an outcome variable; residual semivariograms represent spatial variation that is left unexplained after accounting for predictors . A semivariogram is characterised by three parameters: the partial sill , representing the spatially structured semivariance component and indicating the tendency for geographical clustering; the nugget , representing the spatially unstructured semivariance component ( representing either small-scale spatial variability , measurement error or random variation ) ; and the range , representing the pairwise distance above which two locations can be considered independent ( indicative of the average size of geographical clusters ) . We estimated the tendency for geographical clustering within a region ( i . e . proportion of variation due to spatial proximity ) by dividing the partial sill by the sum of the nugget plus the partial sill [49] . Separate models were developed using KK , CCA with trace as positive and CCA with trace as negative presence-absence datasets . Examination of spatial autocorrelation revealed some level of residual spatial clustering for each model ( see Results below ) . We implemented geostatistical models to account for our covariates and to simultaneously explore this autocorrelation . Bayesian logistic models with geostatistical random effects were built for CCA tests using the open software OpenBUGS [50] . We assumed the observed presence-absence vectors for each diagnostic group were random draws from an underlying infection probability according to a Bernoulli distribution . Using a logit link function , we modelled this probability as a linear regression that included an intercept , our fixed predictors and a multivariate normal geostatistical random effect capturing distances ( km ) between pairs of locations ( using the spatial . exp function BUGS language , which is essentially a Bayesian kriging model ) . Note that due to a low overall prevalence in the KK dataset , we had inadequate infection data to generate precise estimates of spatial effects . We instead investigated possible spatial clustering using aggregated data by classifying locations as a binomial variable based on whether that location’s mean observed prevalence was higher or lower than the mean prevalence ( 1 . 95% ) observed in the entire dataset ( i . e . each survey location was categorised using 1 or 0 based on whether its prevalence was ≥ 1 . 95% or < 1 . 95% ) . Geostatistical models were estimated in a Bayesian framework using Markov Chain Monte Carlo ( MCMC ) sampling based on the Gibbs sampler in OpenBUGS [50] . Normal priors with mean = 0 and variance = 100 ( i . e . precision = 0 . 01 ) were specified for intercepts and regression coefficients . Geostatistical random effects were assumed to follow a normal distribution with mean = 0 and variance = 1/tau , where tau was drawn from a gamma distribution ( shape = 0 . 001 , scale = 0 . 001 ) . For CCA models , a burn-in of 5 , 000 MCMC iterations was used followed by 5 , 000 iterations . For the KK model , a burn-in of 2 , 000 iterations was used followed by another 3 , 300 iterations . Convergence for all models was assessed visually based on inspection of posterior density and trace plots . Significance of predictor effects was inferred based on whether 95% confidence intervals of posterior estimates did not include zero . Model predictions were used to generate representative maps of the prevalence of S . mansoni infections across Rwanda for boys aged between 5–9 years , the subgroup with the highest overall prevalence of S . mansoni infection in our dataset ( though it should be noted that age was not a significant predictor of infection probability , see Results below ) . Predictions were made at the nodes of a 0 . 03 × 0 . 03 decimal degree grid ( approximately 3km2 ) . The mean and standard deviation were extracted from the posterior distributions of predicted risk . Marginal predictions of risk were calculated using the spatial . unipred command in OpenBUGS , which carries out single site predictions to yield marginal prediction intervals for each sample site . To assess geographical discrepancies in S . mansoni endemicity and the estimated numbers of at-risk individuals across the three diagnostic datasets , we selected the highest risk group in our dataset , represented as boys aged between 5 to 9 years old . A raster map of the estimated total population size of this select group ( estimated for the year 2018 ) was multiplied by the predicted prevalence of S . mansoni in the at-risk group to produce a map of the total number of infected children in each grid cell . To create the 2018 population raster , we retrieved a 2015 population density raster from the Center for International Earth Science Information Network ( CIESIN ) [51] , which was originally estimated using National Institute of Statistics Rwanda’s Fourth Population and Housing Census 2012 data . This raster was multiplied by the reported United Nations Development Programme ( UNDP ) average annual rate of population change ( i . e . 2 . 53% ) , which was then multiplied by the proportion of 5 to 9 year-olds ( i . e . 13 . 5% ) to produce a raster map of the estimated densities of children in this focal group in 2018 . All spatial calculations and plots were conducted in ArcGIS version 10 . 4 . 0 . 5524 [44] . Data required to replicate analyses is included in Supporting Information , S1 Data .
A total of 174 schools were tested for the prevalence of S . mansoni infection using all three methods , with 8 , 647 pupils providing both stool and urine samples . Across these samples , observed prevalence using CCA with trace as positive was 37 . 5% , 8 . 6% when using CCA with trace as negative and only 2% when using KK ( Supporting Information , S1 Table ) . Results were broadly similar when taken across the entire dataset: only 1 . 95% of the 9 , 175 children tested with the KK method were diagnosed as infected ( Table 1 ) , while observed prevalence was 35 . 93% for CCA with trace as positive and 7 . 21% for CCA with trace as negative ( N = 19 , 218; Table 1 ) . Despite these large discrepancies in diagnosed outcomes , some spatial agreement was evident across tests . Prevalence was generally highest in Northern and Western regions of the country for all three diagnostic groups ( Fig 1: Panel A to C ) . However , this pattern of spatial variation was more evident for the CCA with trace as positive group , with many high-burden locations ( i . e . with prevalence >50% ) occurring within close proximity of one another in the Northern and Western regions of Rwanda ( Fig 1: Panel B ) . The KK and CCA with trace as negative groups tended to show very low prevalence in most regions , with only a few high-prevalence locations occurring in the Northern and Western Regions ( Fig 1: Panel A and C , respectively ) . Semivariograms based on residuals from non-spatial models revealed a tendency for spatial clustering for all diagnostic groups , warranting the need for geostatistical methods ( Supporting Information , S2 Fig ) . Sex of participants was an important risk factor for S . mansoni infection across all models , with males exhibiting higher risk compared to females ( odds ratios of increased risk for males = 1 . 71 , 1 . 08 and 1 . 35 for KK , CCA with trace as positive and CCA with trace as negative , respectively; Table 2 ) . However , environmental predictors differed among methods . We found a positive association between LST and infection risk when using the KK test , whereas NDVI was positively associated with risk for both CCA groups ( Table 2 ) . For the KK method , regions with highest probability of harbouring above-average prevalence generally occurred in the Northern region , Nyagatare and Burera districts , the Western region such as Rusizi districts and also in inland-areas of Rwanda such as Kamonyi and Rwamagana ( Fig 2: Panel A; see S3 Fig in Supporting Information for locations of districts ) . Predicted prevalence of S . mansoni using CCA with trace as positive was mostly between 30 to 40% across Rwanda , with highest prevalence ( i . e . with >50% predicted prevalence ) occurring in Northern districts ( including Nyagatare , Gicumbi and Gakenke ) as well as Southern districts such as Gisagara and Nyanza ( Fig 2: Panel B; S3 Fig ) . In contrast , predicted prevalence using CCA with trace as negative was mostly <10% across Rwanda , with the highest predicted prevalence observed only in a small localized area in the Northern Nyagatare district ( Fig 2: Panel C; S3 Fig ) . Importantly , vast areas of the country identified as high-risk when considering trace results as positive were estimated to have prevalence <10% when considering trace results as negative . Our spatially-adjusted projection maps identified areas where high densities of individuals in the focal group ( boys aged 5 to 9 years ) live in risk-prone environments . Projections were broadly in agreement across diagnostic tests , though it should be noted that our KK prediction map is restricted to estimating total at-risk individuals in spatial clusters with above-average predicted prevalence . Areas within and around the capital Kigali in the central area of Rwanda ( i . e . the capital city Kigali , and the southwest part of Kigali including Rwezamenyo , Gitega , Kimisagara , Nyakabanda sectors ) had high estimated densities of at-risk individuals across all three tests ( Fig 3: Panel A to C; S3 Fig ) . In addition , target areas were also identified in localised areas around Mururu sector in Rusizi district in South-Western province , and Nkombo sector which is located around the southern end of Lake Kivu in Rusizi district . Despite some general agreement , we identified considerable discrepancies in spatial patterns and estimated densities of at-risk children across diagnostic tests . For the CCA with trace as positive test , we estimated that approximately 671 , 856 boys aged 5 to 9 years are currently infected with S . mansoni in Rwanda ( 95% CI: 655 , 349–678 , 692 ) , while only 60 , 453 individuals in this target group are predicted to be infected based on the CCA with trace as negative test ( 95% CI: 52 , 452–61 , 116; Table 3 ) . While both CCA datasets identified the Gisenyi sector of the Rubavu district in the Western province as a potential target , estimated densities were much higher when using the CCA with trace as positive data ( with up to 887 at-risk individuals per square km; compared to 117 people per square km for CCA with trace as negative; Fig 3: Panel B and C ) . Moreover , the KK map identified a target area around Rukomo sector in Gicumbi district ( North-Eastern region ) that was not identified by the CCA tests ( Fig 3: Panel A ) .
Helminth infection is among the most common causes of anaemia and subsequent hospitalization in Rwanda [31 , 54] . As one of Africa’s most densely populated countries and with an economy that relies on agriculture [32] , it is unsurprising that up to 36% of schoolchildren are estimated to be infected with S . mansoni . However , infection rates are not homogenous throughout the country . Determining accurate estimates of Schistosoma prevalence is an important step to design mitigation programs , particularly considering that even low infection intensities can cause morbidity [3] . We provide multiple lines of evidence that different diagnostic procedures yield different inferences about S . mansoni infection rates and spatial patterns in Rwandan schoolchildren . Our prevalence estimates varied largely across procedures , with the KK method yielding far lower estimates compared to the CCA datasets . Explaining this discrepancy requires an understanding of what these tests are designed to detect . Positive detection by the KK method is limited to individuals that are infected with egg-producing female worms in sufficient numbers to consistently yield eggs in their faeces . This immediately rules out detection of some infections that are composed of male worms , of worms that have not reached sexual maturity or low numbers of worms that produce low numbers of eggs . Moreover , parasite egg counts in our study ( as in most KK studies ) were based on a single stool sample , which can limit the ability of technicians to identify infections [28] . Finally , other work suggests that KK detections are strongly associated with infection intensity or egg-laying rates [55] . In contrast , CCA tests are thought to provide a more unbiased estimate across heterogeneous environments [26 , 56 , 57] . Children who harbour pre-patent adult worms or low densities of egg-producing females are highly likely to be diagnosed as uninfected using the KK method [58] , while detection of schistosome-released antigenic proteins using CCA may still be accurate [26] . Running separate analyses using multiple diagnostic procedures may not be cost-effective and clearly can lead to conflicts in resource management when attempting to reduce schistosomiasis in endemic areas . Given that CCA tests do not require a stool sample and have greater capabilities to detect low-intensity infections than KK , implementation of CCA diagnostics could be the best approach for rapid screening during ongoing monitoring programmes . However , the problem of interpretation for CCA tests still remains [56] , although a recent systematic modelling paper comparing KK with CCA results from many different countries and endemic levels of infection indicates the relative comparative results of these two assays [27] . Despite the minimal training required for CCA testing , approaches to classify different trace results can be inconsistent [47 , 56] . Nevertheless , as previously reported for Burundi [53] , comparisons of the KK , CCA and CAA assays by latent class analysis indicate that at least half of trace results are estimated to be true positives . Analysis of the CCA datasets in our study delivered quite different inferences . The estimated number of 5 to 9 year-old boys currently harbouring infection varied by an order of magnitude , a large difference that could be confusing to decision-makers . It should also be noted that even CCA with trace as positive tests are known to miss some confirmed infections [56] , suggesting that our projections of burden in Rwanda could still be conservative . Because many nations where Schistosoma parasites are endemic do not have adequate funds for blanket treatment , this variation in prevalence estimates has important ramifications for the decision-making process . WHO guidelines are used around the world for designing mass drug administration strategies to reduce intestinal helminth infection rates in endemic nations [11 , 33 , 59] . Current guidelines for reducing schistosomiasis suggest that the prevalence in the at-risk school population should determine the number of interventions to use over the course of a child’s primary school years [41] . For example , areas with estimated prevalence >50% should receive treatment on an annual basis , while areas with prevalence <10% should be treat each child twice during their primary school years [41] . In light of our study , decisions about whether areas are high-risk ( including many endemic clusters identified using the CCA with trace positive analysis ) or low-risk ( covering most of the country when considering the other two analyses ) can lead to dramatic differences in the overall cost of treatment across diagnostic methods . Based on our findings and on previous work suggesting a high sensitivity of CCA tests [25 , 47 , 57] , we suggest treatment should be focused on areas that were identified by the CCA with trace as positive procedure as high-risk . This seems a useful approach to ensure adequate coverage of areas that likely exhibit high prevalence , high average intensity of infection and a relatively large number of infected schoolchildren . Here , our modelling identifies districts around the capital region and along the Western and Northern borders of the country ( consisting of mountain highlands , the Virunga volcano range , and Lake Kivu [31] ) as harbouring high S . mansoni burdens . These regions are some of the most heavily populated in the country [32 , 51] , and our projections indicate they contain high densities of at-risk populations . Indeed , using the less conservative CCA with trace as positive test , we estimate that prevalence of S . mansoni reaches >50% among schoolchildren in some of these districts . Targeting these areas will likely be the most cost-effective intervention approach for reducing prevalence and associated morbidity , as programs targeting areas with high transmission risk are expected to be more efficient reduction measures for battling schistosomiasis [10 , 59] . In addition to mass drug administration , additional measures should ensure improved access to clean water and environmental measures to control snail abundances and reduce transmission [59 , 60] . With malnutrition and diarrhea presenting as two of the most common causes of hospital-based child mortality in Rwanda [34] , population densities and lack of adequate sanitation likely play strong roles in driving the observed spatial variation in S . mansoni infection rates . Schistosoma parasites maintain high transmission rates in regions where overcrowding and poor sanitation coincide [61] . For example in Rwanda’s capital city Kigali , where we identified an endemic cluster of high S . mansoni infection risk , construction of adequate sanitation facilities has not kept pace with rapid population expansion in recent years [62] . Instead , many people reside in high-density temporary slums where access to freshwater is limited . However , the issue of poor sanitation is not restricted to urbanised areas . Pit latrines , which facilitate the spread of infectious diseases through environmental contamination , are the most common toilet facilities , while defecation in fields or rivers is also commonplace [63] . Poverty contributes to these poor sanitation practices , as low-income communities are often located in marsh or swamp lands skirting urban centres in Rwanda [62] . In these areas , densities of intermediate snail hosts may be high , leading to high transmission forces . Female S . mansoni worms can produce hundreds of eggs per day [64] . When sanitation rates are poor and burdens are high , ecological risk factors that influence vegetation or water properties , both of which impact parasite survival and/or infectivity , become especially important . The widespread availability of satellite imagery has played a key role in identifying ecological correlates of geographical distributions and infection rates for an incredible diversity of pathogens [29 , 65–69] . For human helminth parasites , numerous geostatistical analyses have delineated spatial clusters of high infection risk , further indicating a strong role of environmental forces [29 , 65 , 70 , 71] . In our case , we identified LST and NDVI as important predictors of S . mansoni infection probability and spatial clustering . Temperature of the land surface is a key predictor of population dynamics for intermediate snail hosts , while low temperatures can impede the development of Schistosoma parasites within snails [43] . Vegetation indices could reflect distributions of habitats that are suitable for snails , while both variables in tandem may influence vegetation or soil properties that determine the survival of parasite stages in human excreta ( Schistosoma eggs that release miracidia ) or the infectivity of water-borne stages that penetrate human skin ( cercariae ) [4 , 61] . Identifying key drivers of infection risk using remotely sensed variables presents a major advantage in efforts to provide continuously updated high-resolution projection maps [66 , 72–74] . We provide new insights into risk factors and the spatial distribution of S . mansoni infections in Rwanda . However , our study has some weaknesses that should not be ignored . Our dataset did not consider whether infection with other intestinal parasites might have influenced risk of S . mansoni infection . Parasite co-infections are ubiquitous , and there is mounting evidence indicating that biotic parasite associations can have marked influences infection risk and/or disease progression [70 , 71 , 75–79] . In addition , remote-sensed variables such as those used in our study come with their own levels of uncertainty , though these are commonly ignored when producing raster maps [80 , 81] . Moreover , our projection maps of at-risk population densities used population estimates from the UN population database . These estimates may not be entirely accurate , as data on the proportion of persons within our target age group overlaps a number of UN categories . Further uncertainty in our estimates could result from our approach to calculate population sizes using the UNDP average annual rate of population change . This average rate may not reflect spatio-temporal variation in population changes in Rwanda . Finally , while school-based surveys are the primary method of choice for mapping intestinal parasite infections , estimates of infections in adults would provide useful additional information to gain better insights into population-level risk factors [82] . We provide high-resolution predictions of spatial heterogeneity in S . mansoni infection prevalence in Rwandan schoolchildren . Together with our identification of risk factors and data-driven projections of current burdens in at-risk populations , these results can be leveraged to make informed decisions about mass drug treatment regimes . Treatment decisions based on mapping and modelling approaches such as ours could be useful for managers deciding between sustained morbidity control or moving toward elimination [21] . Ongoing monitoring and use of continuously updated geostatistical models will be essential for designing intestinal parasite mitigation programmes and evaluating their efficacy [66 , 72–74] . Nevertheless , we highlight important discrepancies in spatial disease projections that rely on different diagnostic procedures . Greater emphasis is needed to develop standardized guidelines for classifying CCA trace results , as our risk maps yielded very different conclusions about areas in need of treatment when considering traces as positive or negative . We hope that our research provides a platform to help mitigate Schistosoma infection burdens and associated morbidity in the tropical and subtropical regions . | Schistosomiasis control efforts rely on rapid diagnostic tests to generate maps of disease prevalence . This is so that high-risk areas can be identified and provided with treatments . A range of tests are available , yet it is unclear how their differing results can inform disease mitigation . This study compared the results of diagnostic methods for uncovering areas at risk of Schistosoma mansoni infection in Rwanda . A national survey of Rwandan schoolchildren used two detection methods: a test detecting a schistosome antigen in urine ( CCA ) and a test to detect parasite eggs in stool ( KK ) . We divided the CCA test into two datasets , as there is large uncertainty when interpreting its reading . We found that these three datasets all tell different stories about the distribution of S . mansoni in Rwanda . While all tests found similar high-risk areas where prevalence reaches 50% , such as Northern and Western regions , their overall messages are mixed . Some urine tests find areas that are high-risk , while stool tests in the same area may consider it low-risk . This makes it difficult to design budgets for treatment programs , as it is unclear where resources should go . More research and analyses are needed to determine how these tests can be used as tools for schistosomiasis risk mapping . Furthermore , the interpretations of mapping outcomes will also likely rest on national decisions regarding programmatic goals . | [
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"neglec... | 2019 | Mapping Schistosoma mansoni endemicity in Rwanda: a critical assessment of geographical disparities arising from circulating cathodic antigen versus Kato-Katz diagnostics |
Prions induce lethal neurodegeneration and consist of PrPSc , an aggregated conformer of the cellular prion protein PrPC . Antibody-derived ligands to the globular domain of PrPC ( collectively termed GDL ) are also neurotoxic . Here we show that GDL and prion infections activate the same pathways . Firstly , both GDL and prion infection of cerebellar organotypic cultured slices ( COCS ) induced the production of reactive oxygen species ( ROS ) . Accordingly , ROS scavenging , which counteracts GDL toxicity in vitro and in vivo , prolonged the lifespan of prion-infected mice and protected prion-infected COCS from neurodegeneration . Instead , neither glutamate receptor antagonists nor inhibitors of endoplasmic reticulum calcium channels abolished neurotoxicity in either model . Secondly , antibodies against the flexible tail ( FT ) of PrPC reduced neurotoxicity in both GDL-exposed and prion-infected COCS , suggesting that the FT executes toxicity in both paradigms . Thirdly , the PERK pathway of the unfolded protein response was activated in both models . Finally , 80% of transcriptionally downregulated genes overlapped between prion-infected and GDL-treated COCS . We conclude that GDL mimic the interaction of PrPSc with PrPC , thereby triggering the downstream events characteristic of prion infection .
Prion diseases are lethal infectious diseases that propagate through the conversion of the cellular prion protein ( PrPC ) into a pathological conformer , the scrapie-associated prion protein ( PrPSc ) [1] . Neuronal expression of PrPC is required to mediate the neurotoxicity of PrPSc [2] and possibly also of other protein aggregates [3] , yet the pathways leading to neurotoxicity are largely unknown . While caspase activation , autophagy , and Ca2+ dysregulation have been shown to occur after prion infections [4 , 5] , ablation of Bax and caspase-12 , or overexpression of Bcl-2 , does not delay incubation time of prion-infected animals [6 , 7] . Induction of autophagy , despite enhancing PrPSc clearance in vitro and in vivo , did not prolong survival time of prion-infected mice [8] . Furthermore , excessive unfolded protein responses ( UPR ) in the endoplasmic reticulum ( ER ) plays a significant role in the pathogenesis of prion and other neurodegenerative diseases [9 , 10] , yet the biochemical events emanating from prion replication and leading to UPR induction are unknown , and it is unclear how extracellular aggregates can trigger pathology in a subcellular compartment to which they have no direct access . Prion infection of cerebellar organotypic cultured slices ( COCS ) has proven to be an extraordinarily faithful and tractable model of prion disease . Prion-infected COCS replicate all salient biochemical , histological , and pathophysiological events which occur during prion infections in vivo , including PrPC-dependent prion replication [11 , 12] , neuroinflammation with proliferation of microglia and astrogliosis , spongiosis , and neuronal cell loss . In prion-infected COCS , calpain inhibition confers neuroprotection without reducing prion replication , suggesting that calpains are involved in neurotoxicity [13] . We have reported that exposure to antibody-derived anti-PrP ligands ( full-length antibodies , F ( ab ) 1 fragments thereof , and recombinant single-chain miniantibodies ) targeting the globular domain ( GD ) of PrPC [14] induces rapid cerebellar granular cell ( CGC ) degeneration in COCS and in live mice . Since this toxic effect was also attenuated by calpain inhibitors [15] , we wondered whether the two triggers of PrP-dependent cell death , GDL and prions , might induce similar neurotoxic cascades . Here we report that antibodies against the flexible tail ( FT ) of PrPC , which prevent GD ligand ( GDL ) toxicity in COCS [15] , also counteracted neurotoxicity in prion-infected COCS , suggesting a role for the FT in both models . Furthermore , GDL treatment and prion infection triggered similar intracellular cascades including PERK activation [9] and reactive oxygen species ( ROS ) production . Also , a comparative analysis of transcription in prion-infected vs . GDL-exposed COCS showed extensive similarities between these two paradigms of PrP-related toxicity . We conclude that prions and GDL share downstream pathways of toxicity , and that in both instances the FT is the main molecular effector of prion-mediated toxicity .
Rapid neurotoxicity is elicited in COCS and in vivo by several monoclonal antibodies , single-chain variable fragments ( scFv ) , and F ( ab ) 1 , and F ( ab ) 2 fragments directed against the globular domain of PrPC [15] . We collectively termed these reagents “globular domain ligands” ( GDL ) . In all of the experiments described below , we used the POM1 holoantibody ( 67nM ) as a validated paradigm of GDL-associated toxicity . Also , we have previously reported that neurodegeneration and prion replication similarly occur in COCS exposed to the three prion strains , RML , 22L , and 139A [13] . Here , we used RML infection as an extensively characterized paradigm of prion infection . Prion infection of COCS from tga20 transgenic mice overexpressing PrPC [16] elicited toxicity more rapidly than in wild-type COCS [13] , and was used for all experiments except when otherwise indicated . As controls , pooled mouse immunoglobulins ( IgG ) and non-infectious brain homogenate ( NBH ) were used . First , we compared the progression of neurodegeneration in GDL-exposure vs . prion infection of COCS by measuring the area positive for neuronal-nuclear antigen ( NeuN ) within the CGC layer , and by counting cells stained by propidium iodide ( PI ) . The NeuN+ area was used to estimate COCS viability , while the density of PI+ cells correlated with the intensity of ongoing damage . A previously published time-course experiment [15] was repeated including additional time points . PI+ cells peaked at 3 days post-exposure ( dpe ) ( S1A Fig . ) and decreased around 7–10 dpe in GDL-treated COCS . Also , significant loss of NeuN+ granule cells was detectable at 3 dpe ( Fig . 1A ) . In prion-infected COCS , we observed a peak of PI+ cells at 38 days post infection ( dpi ) ( S1B Fig . ) and significant neuronal cell loss at 45 dpi ( Fig . 1B ) . ROS , particularly superoxide , are causally involved in GDL toxicity [15] . We therefore asked whether prion infection resulted in ROS production , and whether ROS scavenging might be beneficial . We measured ROS production in live GDL-treated and RML-infected COCS by fluorescent recording of dihydroethidium ( DHE ) oxidation products [17] . GDL-treated COCS were treated with DHE at various time points between 1 h and 10 days after POM1 exposure ( Fig . 1C ) . Enhanced fluorescence from DHE oxidation products was observed at 4 h ( 67 nM ) . Exposure to a fivefold higher POM1 concentration ( 335nM ) resulted in toxicity even after 1 h . Significantly increased fluorescence was observed in prion-infected COCS ( Fig . 1D , RML “+” ) starting at 25 dpi and reached a peak at 38 dpi , but not in COCS exposed to non-infectious brain homogenate ( RML “-” ) . Consistently with what we found in GDL-exposed tga20 COCS , we observed significant ROS production , measured by DHE incorporation , in GDL-exposed COCS from wild-type ( Bl/6 ) mice at 7 and 14 dpe ( S2A Fig . ) . This result provides further validation for our view that prion related pathologies show very similar characteristics in wild-type and tga20-derived tissues . ROS generation was also measured by lucigenin conversion , which detects superoxide anion radicals [18] . COCS exposed to GDL displayed increased lucigenin conversion [15] , which was quenched by diphenylene iodonium ( DPI ) , an inhibitor of ROS-producing electron transporters including NADPH oxidases ( NOX ) [15] . Similarly , we observed elevated lucigenin conversion in prion-infected COCS at 42 dpi , indicating a strong increase in superoxide production . Furthermore , addition of DPI quenched ROS production in prion-infected COCS ( Fig . 1E ) . We also measured ROS production in vivo using DHE . Terminally sick RML-infected mice were injected intraperitoneally with DHE , and DHE oxidation products were detected in brain homogenates . Forebrains and cerebella of prion-infected mice showed higher levels of fluorescence than NBH-inoculated control mice ( Fig . 1F ) . If the superoxide burst in prion-infected COCS is a direct consequence of prion infection , interference with prion replication should reduce ROS production . We therefore subjected prion-infected COCS to a panel of compounds that had previously been found to antagonize prion replication , including pentosan polysulfate ( PPS ) , congo red ( CR ) , and amphotericin B ( Amph ) . Prion-induced ROS production was reversed by treatment with PPS , CR , and Amph ( Fig . 1G lower half ) . Hence , ROS production is a general feature of prion toxicity downstream of prion replication . PPS , CR , and Amph may be effective because they intercalate with prions , or because they activate neuroprotective pathways independently of their interactions with PrPSc . We therefore tested the effects of PPS , CR , and Amph on GDL-treated COCS . We found that ROS production was not reduced ( Fig . 1G , upper half ) and neurodegeneration was not prevented ( Fig . 1H ) , whereas PPS , CR , Amph counteracted neurotoxicity in prion-infected COCS [13] , with PPS being protective for at least 55 dpi ( Fig . 1I ) . We conclude that the prionostatic properties of these compounds , rather than any off-target effects , were indeed the proximal reason for ROS suppression . Analogously to what we observed in GDL-exposed COCS , the ROS scavengers ascorbate and N-acetyl cysteine ( NaC ) completely prevented prion neurotoxicity in COCS ( Fig . 2A ) , although neither compound affected prion titers ( Fig . 2B ) . Furthermore , ascorbate did not affect PrPSc accumulation , total PrP levels , or processing of PrPC into the C1 fragment in prion-infected COCS . Only the C2 fragment was decreased ( S3A–S3D Fig . ) . As previously shown for GDL toxicity , the membrane-impermeable antioxidant isoascorbate and the superoxide dismutase mimetic MnTBAP conferred protection against prion toxicity , suggesting that the relevant ROS species are extracellular in both instances ( Fig . 2A ) . In contrast , the nitric oxide synthase inhibitor 1400W was ineffective in both prion-infected ( Fig . 2A ) and GDL-exposed COCS [15] . These data indicate that the ROS moiety instrumental to prion-induced neurodegeneration is superoxide , rather than nitric oxide , in both models . We then investigated whether ascorbate would be neuroprotective over protracted periods of time . RML-infected COCS were treated with ascorbate and harvested at various times between 45–53 dpi . Remarkably , ascorbate significantly reduced neurodegeneration of RML-infected COCS for ≥53 dpi ( Fig . 2C ) . Finally , we asked whether antioxidants might be protective against prion-induced neurotoxicity in vivo . For this , we administered the enterically activated antioxidant , acetylated hydroxy tyrosol ( AcHyT , 2g l-1 added to drinking water ) [19] , to tga20 transgenic mice . AcHyT was previously shown to block the toxicity of GDL in vivo [15] . Tga20 mice pretreated with AcHyT for 7 days were intracerebrally infected with 22L prions ( 30μl , diluted 10–2 ) and treatment with AcHyT was continued until mice reached the criteria for termination of the experiment . Treated animals showed a modest , but significant , life extension ( Fig . 2D ) . Hence , AcHyT is protective in vivo against the toxicity of both prions and GDL . We have previously shown that calpain inhibitors , but not caspase inhibitors , prevent cell death in GDL-exposed [15] and RML-infected COCS [13] ( Fig . 2A ) . In order to test whether ROS signaling occurs upstream of calpain activation , we studied the effects of antioxidants on the catabolism of fodrin , which is specifically cleaved by calpains into fragments of 145 and 150 KDa . This cleavage was blocked by calpain inhibition [13] yet was unaffected by antioxidant treatment in both RML-infected and GDL-exposed COCS , indicating that ROS production is triggered by events that are dependent on ( “downstream” of ) calpain activation ( Fig . 2E , F ) . This hierarchical sequence may not be unique to PrP-related toxicity , and other calpain activators may plausibly also induce ROS . Excitotoxicity is a potent ROS inducer [17] , and PrPC can modulate NMDA and voltage-gated calcium channels [20 , 21] . We therefore investigated if inhibitors of NMDA and AMPA/kainate ionotropic glutamate receptors , or of a mitochondrial membrane permeability transition pore , could protect COCS against GDL or prion neurotoxicity . However , none of the inhibitors were protective in either model ( Fig . 2A ) . Also , inhibiting ryanodine receptor-mediated calcium release from the endoplasmic reticulum ( ER ) with Dantrolene , was not protective ( Fig . 2A ) . None of the tested compounds were inherently toxic , as the viability of IgG-treated or NBH- exposed tga20 COCS were unaffected ( S4 Fig . ) . High-affinity ligands to the FT of PrPC such as the POM2 antibody [14] are not only innocuous , but counteract the toxicity of GDL . Moreover , interstitial FT deletions prevent GDL toxicity in vitro and in vivo , indicating that the FT is required to execute GDL toxicity [15] . To determine whether the FT also mediates toxicity in prion infection , we treated prion-infected COCS with the POM2 antibody , which recognizes the octapeptide repeats of the FT . POM2 prevented prion-mediated neurodegeneration in tga20 COCS , whereas equimolar amounts of IgG had no beneficial effect ( Fig . 3A ) . We determined prion titers by the scrapie cell-assay in end-point format ( SCEPA; [22 , 23] , Fig . 3B ) , which measures the minimal concentration that still can infect the cells and is currently the most precise measurement of infectivity in vitro . Crucially , prion titers were not significantly affected . This finding disproves the possibility that neuroprotection was caused by reduced infectivity , and suggests that POM2 acted specifically on prion neurotoxicity by interfering with events triggered by the encounter of prions with their target cells . Western blots of PK-digested samples showed that POM2 treatment led to the appearance of PrP-immunoreactive higher-molecular weight bands ( Fig . 3C ) , possibly representing SDS-stable PrPSc oligomers concomitant with reduced immunoreactivity in the 27–30 kDa range . The total PK-resistant PrP immunoreactivity was determined by densitometric quantification of the entire lane , and was found to be similar to that of samples that had not been exposed to POM2 . We conclude that POM2 induced a shift in the distribution of PrPSc moieties without affecting its overall quantity . This interpretation is congruent with the results of prion titer determinations ( Fig . 3B ) . Since ER stress has previously been shown to be involved in prion disease [9 , 10] , we examined the levels of phosphorylated PERK ( p-PERK ) , phosphorylated eIF2α ( p-eIF2α ) , and ATF4 in both paradigms of PrPC-dependent neurotoxicity . We found a trend towards increased levels of p-PERK , as well as significantly increased p-eIF2α and ATF4 in RML-infected COCS at 42 dpi ( Fig . 4A ) , confirming the activation of the unfolded protein response in prion infections . Surprisingly , we found that POM1-exposed COCS also showed increased p-PERK , p-eIF2α , and ATF4 at 3 dpe ( Fig . 4B ) . To further explore this phenomenon , COCS prepared from wild-type mice were exposed to POM1 for 7 and 14 days ( S2B–S2C Fig . ) . At 7 dpe there was a trend towards increased p-PERK and p-eIF2α levels , whereas ATF4 was unchanged . At 14dpe we found significantly increased levels of p-eIF2α and ATF4 , suggesting again an involvement of the PERK pathway as observed in the tga20 COCS . This suggests that signals emanating from GDLs can propagate to the ER and initiate a response similar to that seen in prion infections . The transcriptional changes occurring in COCS infected with prions and exposed to GDL were studied by microarray hybridization . Genes were considered to be differentially expressed if they exhibited a fold change of ≥ 2 ( p value < 0 . 01 ) between RML and NBH ( prion infection paradigm ) or between POM1 and IgG ( GDL exposure paradigm ) . Upregulated and downregulated genes were compared at various time points ( Fig . 5A; S1–S2 Tables ) . To account for the different velocity of neurodegeneration between the two models , we compared transcriptional profiles at the time at which NeuN staining loss became significant ( 3 dpe for GDL vs . 45 dpi for prion infection ) . The largest overlap of transcriptionally altered genes was found when GDL-treated COCS at 3 dpe were compared to prion-infected COCS at 45 dpi . At these time points , COCS shared 38% of all upregulated genes ( Fig . 5B left; S3 Table ) and 80% of all downregulated genes ( Fig . 5B right ) . At the peak of ongoing cell death in both models ( 3 dpe for GDL vs . 38 dpi for prion infection; S1A–S1B Fig . , measured by PI incorporation ) , we found that 38 . 4% ( 15/39 ) of upregulated genes were identical . Only one of these fifteen genes , Fosb , has been annotated as possibly involved in the signaling initiated by activated ROS [24] . The remaining 14 genes have been assigned to various cellular pathways , but we failed to identify an overrepresentation of any specific pathway . The analysis of individual genes , followed by the compilation of a list of candidates using arbitrary cut-off criteria ( typically fold-change and p values ) may not reveal biologically important effects on pathways . For example , a modest yet concerted increase in the activity of several genes feeding into the same pathway may be more consequential that a strong increase of a single member gene . We therefore set out to evaluate microarray data as predefined gene sets that could be assigned to certain pathways . Gene set enrichment analysis ( GSEA ) is an important approach to the analysis of coordinate expression changes at a pathway level [25] . Specifically , we applied this method to our microarray data in order to specifically investigate whether the genes constituting the TNF-ROS-CASP3 pathway are significantly regulated in a coordinated manner in POM1 and RML-exposed COCS . Indeed , we found using GSEA , that the TNF-ROS-CASP3 pathway indeed was significantly regulated in both POM1-exposed COCS after 3d ( p = 0 . 037 ) and RML-exposed COCS after 38d ( p = 0 . 03 ) and after 45d ( p = 0 . 026 ) . This result shows that in both paradigms genes belonging to the same ROS-dependent pathway are activated upon exposure . Only 3 genes were downregulated at 38 dpi , one of which was downregulated at 3 dpe in GDL-exposed COCS . The top 40 upregulated pathways at each time point were identified using GeneGo MetaCore software . When comparing POM1 at 3 dpe to prion infection at 45dpi , there was an overlap of 19 pathways ( 47 . 5% ) , while 9 out of the top 10 active pathways at 45dpi RML were present in the top 40 of POM1 7 dpe ( S4 Table ) . When genes in POM1-treated COCS at different time points were compared with 45 dpi prion-infected COCS , the correlation of genes increased with time and reached a plateau at 7 dpe POM1 , with a correlation coefficient close to 0 . 8 ( Fig . 5C ) . We then examined the involvement of pathways from the GeneGo MetaCore database that had been described to be activated upon prion infection , such as the ER stress response [9] , ERK inhibition [26 , 27] , autophagy [28] , CCL2 signaling [29] , and TNF-ROS-casp3 [29 , 30] . These pathways were activated in POM1-treated COCS in a pattern that strongly correlated with RML-infected COCS at 45dpi ( correlation value between 0 . 8–0 . 9 ) . Scatter plots and heat maps of the genes involved in the five signaling pathways ( S5A–S5E Fig . ; S6 Fig . ) support this view . To validate the regulation of genes in the microarray data , we performed nanostring analysis for 40 genes on the same RNA preparation that was used in the microarray analysis . Differential expression of the selected genes at various time points in prion-infected and GDL-exposed COCS ( S5 Table ) confirmed the results of the microarray analysis .
Using multiple paradigms in organotypic cultures and in vivo , we show that the toxic antibody POM1 induces largely overlapping pathogenetic cascades as bona fide prion infections . Not only were all strategies preventing GDL-induced neurodegeneration ( such as calpain inhibition , ROS scavenging and FT binding ) found to be neuroprotective against prions , but compounds neuroprotective against other kinds of insult ( such as caspase inhibitors and glutamate antagonists ) were ineffective against both GDL and prions . Moreover , the results of transcriptomic analyses are compatible with the contention of a large overlap in the downstream effectors of both pathways . Besides highlighting the commonalities between GDL and prion-related neurodegeneration ( S7 Fig . ) , these observations set both conditions apart from other types of neurodegenerative conditions . Treatment of prion-infected COCS with antioxidants did not interfere with the aggregation of PK-resistant material , as was previously shown for calpain inhibitors [13] . This adds to the evidence that ROS scavengers and calpain inhibitors mitigate toxicity by interfering with events triggered by prion replication . A plausible model of pathogenesis predicates that toxicity is triggered by binding of either GDL or PrPSc to the globular domain of PrPC . Since inhibitors of prion replication decreased ROS production , but did not protect from GDL toxicity and did not reduce ROS production ( Fig . 1G ) , we conclude that ROS production is downstream of both prion replication and GDL binding . The modest therapeutic effect of the antioxidative therapy with AcHyt in vivo is not unexpected , since their involvement occurs downstream of both prion replication and calpain activation , and suggests the existence of additional pathways of toxicity that remain operational even after scavenging ROS . How can GDL execute such a faithful molecular mimicry of prion infection ? We favor the hypothesis that GDL and PrPSc share the same docking site on cellular PrPC . Engagement of the latter site enacts a long-range allosteric transition of the FT , which in turn triggers the toxic cascade . The above scenario cannot be tested directly because of the technological barriers still hampering structural studies of PrPSc , yet it is at least compatible with the structure of the POM1:PrPC complex , as determined by X-ray crystallography [31 , 32] . Solforosi et al [33] claimed that anti-PrP antibodies induced toxicity by crosslinking PrPC , as F ( ab ) 1 fragments were innocuous in their study . However the monovalent scFv and F ( ab ) 1 fragments of antibody POM1 lead to toxicity in vitro and in vivo [15] . This refutes clustering of PrPC as a cause of toxicity in the present study . Thus far , quests for anti-prion therapeutics have been rare and mostly unsuccessful . Two crucial reasons are the hazards associated with prion infectivity and the dearth of rapid , validated models of prion-induced toxicity . The validation of GDL as prion mimetics will help identify novel nodes in the pathogenetic cascades leading to neurodegeneration , and it is likely that some of these nodes may represent druggable targets . We also identified differences between the pathogenesis of GDL exposure and that of prion infections . Firstly and most glaringly , the kinetics of GDL-induced neurodegeneration ( days ) is much faster than that of experimental prion infections ( months ) . Secondly , although GDL function as a prion mimetic , they differ from bona fide prions by not inducing the classical misfolding and aggregation of PrP , by failing to induce deposition of protease-resistant PrP , and most crucially by being non-infectious . Thirdly , compounds that interfere with prion replication , such as pentosan polysulfate , do not alter the toxicity caused by GDL . All of these observations are compatible with the interpretation that GDL , while not leading to the generation of PrPSc , trigger the same signaling pathway as prion infections . The different speed of disease development may be taken to suggest that GDL exposure and prion infections are fundamentally dissimilar . In our view , however , this does not contradict the hypothesis that these two models share pathogenetic pathways . Prion infection is initiated by trace amounts of prions within brain homogenates , with the PrPSc concentration only gradually increasing upon infection of a progressively larger numbers of host cells . The prion isolate used for a standard slice culture infection contains 7 . 9*106 ID50 in 10 μl [12] . Antibodies in slice culture experiments were used at 67 nM in 1 ml of medium , which corresponds to 4 . 0*1013 molecules . We conclude that , in the case of the antibodies , the exposure to the bioactive principle exceeds that of prions by ca . 7 logs . This calculation is conservative since it disregards that prion inocula were removed after exposure , and that large prion aggregates are unlikely to efficiently penetrate tissues . Hence the bioactive principle in antibody preparations exceeds that in prion infections by several orders of magnitude , which yields—in our view—a highly plausible explanation for the difference in the kinetics of neurodegeneration . Finally , recent evidence suggested the involvement of the unfolded protein response in prion-induced cell death in vivo [9] . Here , we confirm its involvement in RML and GDL-induced cell death in COCS . All of the above suggests that GDL-induced neurodegeneration represents a phenocopy of bona fide prion infections . If this conjecture is correct , targeted manipulations of the FT may be beneficial against neurotoxicity in prion infections . Indeed , we found that binding of the FT by antibodies was neuroprotective to prion-infected slice cultures , yet did not appreciably reduce prion titers—indicating selective suppression of the cytotoxic events downstream of prion replication . Therefore , binding of the FT could modify the course of the disease by uncoupling prion replication from prion toxicity . This hypothesis remains to be validated . Since the GDL-induced toxicity model closely mimics multiple aspects of prion-induced neurotoxicity of prion-induced neurotoxicity , it seems reasonable to utilize GDLs for phenotypic screens aimed at identifying potential antiprion therapeutics . While confirmatory counterscreens will still require proof of efficacy against infectious prions , we posit that GDL toxicity may form the basis of convenient high-throughput and non-biohazardous assays of chemical and biological libraries .
All compounds were purchased from Sigma/Aldrich unless otherwise stated . Prnpo/o;tga20+/+ ( tga20 ) mice were on a mixed 129Sv/BL6 background [16 , 34] . C57BL/6 mice were used as a wild-type mouse strain . 10-week old tga20 mice were administered acetylated hydroxy tyrosol in drinking water ad libitum ( 2 g l-1 with an approximate intake of 8 ml daily ) . After 7 days of treatment , mice were anesthetized and intracerebrally inoculated with the 22L prion strain ( 30μl of 1% homogenate into the temporal cortex ) . Prion-inoculated animals were examined every second day and euthanized upon reaching pre-specified criteria for the terminal stage of disease . All prion-inoculated mice developed typical signs of scrapie and prion infection was confirmed in all cases by western blotting for protease-resistant PrPSc with the anti-PrP antibody POM1 ( S8 Fig . ) [14] . Cultured organotypic cerebellar slices were prepared as previously described [11] . Briefly , cerebella from 10–12 day old pups were cut into 350 μm sections and kept in Gey’s balanced salt solution ( GBSS ) ( NaCl 8 g l–1 , KCl 0 . 37 g l–1 , Na2HPO4 0 . 12 g l–1 , CaCl2 2H2O 0 . 22 g l–1 , KH2PO4 0 . 09 g l–1 , MgSO4 7H2O 0 . 07 g l–1 , MgCl2 6H2O 0 . 210 g l–1 , NaHCO3 0 . 227 g l–1 ) supplemented with the glutamate receptor antagonist kynurenic acid ( 1 mM ) at 4°C . Six to ten slices were then plated per Millicell-CM Biopore PTFE membrane insert ( Millipore ) and residual buffer was removed before placing the inserts into a cell culture plate containing “slice-culture medium” ( 50% vol/vol MEM , 25% vol/vol basal medium Eagle and 25% vol/vol horse serum supplemented with 0 . 65% glucose ( w/vol ) , penicillin/streptomycin and glutamax ( Invitrogen ) ) . Culture medium was exchanged thrice weekly and tissue cultures were kept in a humidified cell culture incubator set to 37°C with 5% CO2 . Antibody treatment and prion inoculations were performed as previously described [11 , 15 , 35] . Briefly , for antibody experiments , POM1 was spiked into the medium 10–14 days post-culturing , a time point at which COCS had recovered from acute phenomena associated with tissue dissection . Fresh POM1 was provided at every medium change . Cultures were harvested for biochemical analyses or fixed for immunocytochemical analyses at different time points . For prion experiments , immediately after dissection , free-floating sections were incubated with infectious brain homogenates for 1 h at 4°C . Sections were then washed twice in 6 ml GBSSK , and 6–10 slices were transferred onto a 6-well Millicell-CM Biopore PTFE membrane insert ( Millipore ) . Residual buffer was removed and inserts were placed into a 6-well culture plate and incubated in standard slice culture medium . POM2 treatment ( 335nM ) was initiated after plating and re-supplied at every medium exchange . For antibody experiments , drug treatment was initiated at the time of antibody addition ( 10–14 days post-culturing ) , whereas for prion experiments , drug treatment was started at 21 dpi when PrPSc is detectable in the cultures . Drugs were re-supplied at every medium change . As a control , the toxicity of each compound was tested in parallel in IgG-treated slices and NBH-inoculated slices . The drugs and concentrations used were ( + ) -5-methyl-10 , 11-dihydro-5H-dibenzo[a , d] cyclohepten-5 , 10-imine maleate ( MK-801 , 20 μM ) , 6-cyano-7-nitroquinoxaline-2 , 3-dione ( CNQX , 20 μM ) , cyclosporine A ( 1 μM ) , ascorbate ( 1 . 5 mM ) , isoascorbate ( 1 . 5mM ) , N- ( 3-methyl-5-sulfamoyl-1 , 3 , 4-tiadiazol-2-ylidine ) acetamide ( methazolamide , 10 μM ) , MnTBAP ( 100 μM ) , benzyloxycarbonyl-Val-Ala-Asp ( OMe ) fluoromethylketone ( zVAD-fmk , 40 μM ) , diphenyleneiodonium chloride ( DPI , 5 μM ) , N- ( [3- ( Aminomethyl ) phenyl]methyl ) - ethanimidamide dihydrochloride ( 1400W , 20 μM ) , N-benzyloxycarbonyl-L-leucylnorleucinal ( calpeptin , 20 μM ) , N-acetylcystein ( NaC , 1 mM ) , ( 2S , 3S ) -trans-epoxysuccinyl-L-leucylamido-3-methylbutane ethyl ester ( E64d , 15 mM , Bachem ) , 1-[ ( 5- ( p-Nitrophenyl ) furfurylidene ) amino]-hydantoin sodium salt ( Dantrolene , 10 μM ) . A summary table of the used tool compounds and their biological targets are reported in S6 Table . The drugs and concentrations used for anti-prion compounds were pentosan polysulphate ( PPS , 300 ng ml-1 , generously provided by Bene Pharmachem ) , Congo red ( 1 mg ml-1 ) , and amphotericin B ( 4 . 5 mg ml-1 ) . Inserts containing the slices were transferred to new plates containing PBS for washing ( twice ) and tissue was then scraped off the membrane using 10 μl per slice of lysis buffer ( 0 . 5% sodium deoxycholate ( DOC ) , 0 . 5% Nonidet P-40 ( NP-40 ) supplemented with complete mini protease inhibitor cocktail ( Roche ) and PhosphoStop ( Roche ) in PBS ) . The harvested tissue was homogenized by trituration using a 30G syringe and protein concentrations were measured using the bicinchoninic acid assay ( Pierce ) . Samples were mixed with loading buffer ( NuPAGE , Invitrogen ) and heated at 95°C for 5 min . Equal volumes were loaded ( 10 μg proteins per lane ) and separated on a 12% Bis-Tris polyacrylamide gel or for higher molecular weight proteins , on a 4–12% gradient gel ( NuPAGE , Invitrogen ) , and transferred onto a nitrocellulose membrane . These membranes were blocked with 5% w/vol Topblock ( Fluka ) in TBS-T ( Tris-buffered saline supplemented with Tween20 ( 150 mM NaCl , 10 mM Tris HCl , 0 . 05% Tween 20 ( vol/vol ) ) for 1 h and incubated with primary antibodies diluted in 1% Topblock in TBS-T at 4°C overnight . After 4 washes of 15 minutes each with TBS-T , membranes were incubated with secondary antibody diluted in 1% Top Block in TBS-T for 1 h at RT . Primary mouse monoclonal antibodies used were: POM1 mouse IgG1 antibody raised against PrPC ( anti-PrPC; 200 ng ml–1 ) , anti-α-fodrin ( AA6 , 100 ng ml-1 , Millipore ) , anti-GAPDH ( 200 ng ml-1 , Millipore ) , anti-actin ( 200 ng ml-1 , Chemicon ) and anti-calnexin ( 1:3000 , Enzo Life Sciences ) . Secondary antibodies were horseradish peroxidase ( HRP ) -conjugated rabbit anti–mouse IgG1 ( 1:10 , 000 , Zymed ) , and goat anti–rabbit IgG1 ( 1:10 , 000 , Zymed ) . The following rabbit monoclonal antibodies were used: anti-phospho PERK ( Cell Signal 3179S ) , anti-PERK ( Cell Signal 3192S ) , anti-phospho eIf2α ( Cell Signal 9721S ) , anti-eIf2α ( Cell Signal 9722S ) , and anti-ATF4 ( Cell Signal 11815S ) . Blots were developed using SuperSignal West Pico chemiluminescent substrate ( Pierce ) and signals were detected using the VersaDoc system ( model 3000 , Bio-Rad ) or Fuji . Quantification of band intensities was performed using Quantity One 4 . 5 . 2 software ( Biorad ) . For specific detection of PrPSc , 20 μg of protein were digested with 25 μg ml-1 proteinase K in 20 μl final volume of digestion buffer ( 0 . 5% wt/vol sodium deoxycholate and 0 . 5% vol/vol Nonidet P-40 in PBS ) for 30 min at 37°C [11] . Loading buffer was added and samples were boiled at 95°C for 5 min to inactivate PK . PNGase F treatment was performed using a commercially available kit , according to the manufacturer’s protocol ( New England Biolabs ) . In brief , 10 μg of proteins was treated with 2 μl denaturation buffer in a 20 μl sample volume and incubated for 15 min at 95°C . A reaction mixture containing 2 . 6 μl G7 , 2 . 6 μl NP-40 ( 10% ) and 0 . 5 μl PNGase was added to the samples and incubated for 2h at 37°C . Samples were then boiled in presence of loading dye , and subjected to western blot analyses . For immunofluorescence staining , organotypic slices were rinsed twice in PBS and fixed in 4% formalin overnight at 4°C . After washing , membrane inserts were incubated in blocking buffer ( 0 . 05% vol/vol Triton X-100 and 3% vol/vol goat serum in PBS ) for 1 h and incubated with primary antibodies diluted in blocking buffer at 4°C for 3 days . The primary antibodies and concentrations used were mouse anti-Neuronal Nuclei ( NeuN , 1 μg ml-1 , Serotec ) , and directly conjugated mouse anti-NeuN-Alexa488 ( 0 . 5 μg ml-1 , Millipore ) . The primary antibodies were detected using Alexa-conjugated secondary antibodies ( 3 μg ml–1 , Molecular Probes ) . Membrane inserts were washed four times with PBS and the counterstaining agent 4 , 6-diamidino-2-phenylindole ( DAPI ) ( 1 μg ml–1 ) was added during the third washing step . Membranes were cut and mounted with fluorescent mounting medium ( Dako ) on a glass slide . Images were taken at identical exposure times with a fluorescence microscope ( BX-61 , Olympus ) equipped with a cooled black/white CCD camera using a 4x objective . Morphometric analyses were performed to quantify the area of immunoreactivity using image analysis software analySIS vs5 . 0 . For PI incorporation , slices were rinsed with PBS and incubated for 30 min with PI ( 5 μg ml-1 ) . Live images were recorded at 5x magnification using a fluorescent microscope ( Axiovert 200 ) equipped with a cooled CCD camera using a 5x objective and processed using image analysis software analySIS vs5 . 0 . The lucigenin conversion assay was carried out at room temperature ( RT ) . Inserts containing 5–10 slices each were washed in PBS and lysed with a 30G syringe in Krebs-Ringer solution supplemented with complete mini protease inhibitor cocktail ( Roche ) . 50 μl of tissue lysate was transferred to a 96-well white microplate containing 175 μl assay solution and 0 . 25 μl lucigenin ( 10 mM ) per well . Background measurements were performed using a chemiluminescence reader prior to the addition of 50 μl NADPH ( 1 mM ) to each well . Subsequently , the NADPH-dependent signal was read and subtracted . Data are presented as relative light unit mg-1 total protein ( each bar: average of 4 inserts ± s . d . ) . For DHE conversion measurements , slices were inoculated , incubated for 40 dpi , and washed twice in GBSS . They were then incubated in GBSS containing DHE ( 10 μg ml-1 ) . After 20 minutes of incubation at RT , 3 images/slice were recorded by live fluorescence microscopy using Axiovert 200 equipped with a cooled CCD camera and using a 10x objective . Three images were recorded per slice in three individual folia of the cerebellum . Fluorescence of DHE oxidation products was assessed by morphometry using constant thresholds . In vivo assessment of ROS production followed the protocol described by Murakami et al [36] . Thirty minutes prior to euthanasia , mice were injected intraperitoneally with 200 μl DHE , and brain tissue was homogenized in 50 mM KH2PO4 , 1 mM EGTA , and 150 mM sucrose . Fluorescence of DHE oxidation products was measured in 250 μl of 2% ( w/v ) homogenates using a fluorimeter with Ex/Em 485/585nm and a cutoff of 570 . Relative fluorescence units were normalized to protein concentration . Prion-susceptible neuroblastoma cells ( subclone N2aPK1 ) [22 , 23] were exposed to 300 μl cerebellar slice homogenates , with 6 replicates per dilution , in 96-well plates for 3 days . Cells were subsequently split three times 1:10 every 3 days . After the cells reached confluence , 25’000 cells from each well were filtered onto the membrane of ELISPOT plates , treated with PK ( 0 . 5 μg ml–1 for 90 min at 37°C ) , denatured , and infected ( PrPSc ) cells were detected by immunocytochemistry using alkaline phosphatase-conjugated POM1 , mouse anti-PrP , and an alkaline phosphatase-conjugated substrate kit ( Bio-Rad ) . We performed serial ten-fold dilutions of experimental samples in cell culture medium containing healthy mouse brain homogenate . Scrapie-susceptible PK1 cells were then exposed to dilutions of experimental samples ranging from 10–4 to 10–7 ( corresponding to homogenate with a protein concentration of 10 μg ml-1 to 0 . 01 μg ml-1 ) , or to a 10-fold dilution of RML or healthy mouse brain homogenate . Samples were quantified in endpoint format by counting positive wells according to established methods [22 , 23] . One-way ANOVA with Tukey’s post-hoc test for multi-column comparison , or Dunnett’s post-hoc test for comparison of all columns to a control column , were used for statistical analysis of experiments involving the comparison of three or more samples . Paired Student’s t-test was used for comparing two samples . Results are displayed as the average of replicates ± s . d . COCS were exposed to RML/NBH or POM1/IgG for various time points; for each time point and treatment , four cell culture inserts ( n = 4 ) with 10 slices were used . RNA was extracted from 10 slices per insert using TRIZOL reagent ( Invitrogen , USA ) and purified with RNeasy columns ( Qiagen , USA ) . Quality was assessed using BioAnalyzer ( Agilent US ) . Labeled cDNA was fragmented and hybridized to GeneChip Mouse Genome 430 2 . 0 Array ( Affymetrix , USA ) which contains 45 000 probe sets . The data was analyzed with R/Bioconductor . Preprocessing and normalization was done using the RMA algorithm [37] and differential expression was assessed using the limma [26] package . The nCounter Analysis system has been introduced previously [38] . Briefly , for each gene of interest , two sequence-specific probes are designed . The probes are complementary to a 100-base region of the target mRNA . The first probe is covalently linked to an oligonucleotide containing biotin ( capture probe ) , and the second probe is covalently linked to a color-coded molecular tag that provided the signal ( reporter probe ) . Forty-nine probe pairs for test genes and control genes were contained in the nCounter CodeSet . All mouse experiments were carried out according to Swiss law and conducted under the approval of the Animal Experimentation Committee of the Canton of Zurich ( permits 200/2007 , 90/2013 and 130/2008 ) . The animal care and protocol guidelines were obtained from http://www . blv . admin . ch/themen/tierschutz/index . html ? lang=en and strictly adhered by the experimenters and animal facility at the institution where the experiments were performed . | Prion diseases are a group of infectious , invariably fatal neurodegenerative diseases . Progress in developing therapeutics is slow , partly because animal models of prion diseases require stringent biosafety and are very slow . We recently found that treatment of cerebellar slices with antibodies targeting the globular domain ( GD ligands ) of the prion protein ( PrP ) is neurotoxic . Here we compared this model to prion infection , and describe striking similarities . Both models involved the production of reactive oxygen species , and antioxidants could reverse the toxicity in cerebellar slices and even prolong the survival time of prion-infected mice . Antibodies targeting the flexible tail of PrP that prevent toxicity of GD ligands reduced the toxicity induced by prions . Endoplasmic reticulum stress , which is involved in prion toxicity , is also found in GD-ligand induced neurotoxicity . Finally , changes of gene expression were similar in both models . We conclude that prion infection and GD ligands use converging neurotoxic pathways . Because GD ligands induce toxicity within days rather than months and do not pose biosafety hazards , they may represent a powerful tool for furthering our understanding of prion pathogenesis and also for the discovery of antiprion drugs . | [
"Abstract",
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"Methods"
] | [] | 2015 | Prion Infections and Anti-PrP Antibodies Trigger Converging Neurotoxic Pathways |
Ivermectin-based mass drug administration ( MDA ) programs have achieved remarkable success towards the elimination of onchocerciasis and lymphatic filariasis . However , their full implementation has been hindered in Central Africa by the occurrence of ivermectin-related severe adverse events ( SAEs ) in a subset of individuals with high circulating levels of Loa loa microfilariae . Extending MDA to areas with coincident L . loa infection is problematic , and inexpensive point-of-care tests for L . loa are acutely needed . Herein , we present a lateral flow assay ( LFA ) to identify subjects with a serological response to Ll-SXP-1 , a specific and validated marker of L . loa . The test was evaluated on serum samples from patients infected with L . loa ( n = 109 ) and other helminths ( n = 204 ) , as well as on uninfected controls ( n = 77 ) . When read with the naked eye , the test was 94% sensitive for L . loa infection and was 100% specific when sera from healthy endemic and non-endemic controls or from those with S . stercoralis infections were used as the comparators . When sera of patients with O . volvulus , W . bancrofti , or M . perstans were used as the comparators , the specificity of the LFA was 82% , 87% , and 88% , respectively . A companion smartphone reader allowed measurement of the test line intensities and establishment of cutoff values . With a cutoff of 600 Units , the assay sensitivity decreased to 71% , but the specificity increased to 96% for O . volvulus , 100% for W . bancrofti , and 100% for M . perstans-infected individuals . The LFA may find applications in refining the current maps of L . loa prevalence , which are needed to eliminate onchocerciasis and lymphatic filariasis from the African continent .
Loiasis , also known as African eye-worm disease , is a vector-borne parasitic infection caused by Loa loa , a filarial worm endemic to Central and West Africa [1] . Epidemiological data collected from 11 African countries indicates that at least 10 million people are infected [2] . In certain communities , the prevalence of loiasis is astounding , with over 40% of the population displaying microfilariae [3] . L . loa is transmitted by daytime biting flies of the genus Chrysops during a blood meal . The fly injects into the human host infective larvae ( L3 development stage ) that develop over time into adult worms . These then mate to produce microfilariae ( mf ) that circulate in peripheral blood [1 , 4] . The major clinical manifestations of loiasis are Calabar swellings ( evanescent episodic angioedema ) and the subconjunctival migration of the adult worm ( eye-worm ) . Less specific manifestations include urticaria , pruritus , myalgias , and arthralgia [5] . Moreover , L . loa infection can cause renal , cardiac , pulmonary and neurological diseases [6] and a recent study found L . loa infection to be associated with a decreased life expectancy [7] . Despite this , loiasis is still considered a benign disease and does not appear on the World Health Organization’s official list of Neglected Tropical Diseases [6] . Loiasis is a major public health issue because of its geographic overlap with onchocerciasis and lymphatic filariasis [8] . The international community has deployed intense efforts to eliminate these two diseases through vector control and mass drug administration ( MDA ) programs . Over 600 million doses of ivermectin ( Mectizan ) are distributed annually , as monotherapy against onchocerciasis , and in combination with albendazole or diethylcarbamazine against lymphatic filariasis [9] . Yet , ivermectin can lead to serious and occasionally fatal adverse neurological reactions in people infected with L . loa . The severe adverse events ( SAEs ) occur when the L . loa microfilaremia exceeds 20 , 000–30 , 000 mf/mL . These SAEs are thought to result from mf dying within the vessels of the central nervous system and from the ensuing eosinophil-rich inflammatory response , a process that can result in encephalopathy [10 , 11] . The initial signs of encephalopathy –confusion , agitation , lethargy , dysarthria , mutism , and urinary incontinence– appear 2 to 3 days post-dosage and can progress into coma and , eventually , death [12] . While in L . loa co-endemic areas , bancroftian filariasis can be addressed with albendazole alone [9] , there are no chemotherapeutic agents other than ivermectin available for MDA against onchocerciasis [13] . Thus , loiasis poses serious ethical and logistic difficulties to onchocerciasis elimination programs . The current guidelines of the Mectizan Expert Committee [12] allow ivermectin-based MDA to proceed in regions of Loa co-incidence , but only if the prevalence of onchocerciasis exceeds 40% based on the presence of O . volvulus microfilariae in skin snips , or 20% based on the presence of palpable nodules in adult males . Even so , a system of pharmacovigilance must be in place to intercept post-ivermectin SAEs . Otherwise , a more demanding test-and- ( not ) -treat intervention strategy must be implemented , where every person in the community must be tested for Loa microfilaremia to determine if he or she can receive ivermectin . Point-of-care tests for loiasis are needed to define more precisely which individuals and which communities are eligible to receive ivermectin . While broad L . loa prevalence maps exist [2] , more granular maps may help decide which communities can be safely included in MDA programs and which ones should be approached with a more labor-intensive test-and- ( not ) -treat approach . Substantial efforts of data collection , statistical analysis , and modelling are currently underway to examine if one can define a limit of Loa prevalence under which ivermectin MDA would be safe and ethical [14] . Definitive diagnosis of loiasis can be done by the identification of the adult worm in the eye or after its removal from under the skin or by morphological identification of the mf in blood smears , but these are low throughput methods inadequate for mapping purposes . Molecular methods such as loop-mediated isothermal amplification ( LAMP ) [15 , 16] and quantitative PCR ( qPCR ) [17] assays are credible alternatives to microscopy-based techniques since they combine a high degree of sensitivity and specificity with high throughput capabilities . However , molecular methods remain impractical for rapid testing at the point-of-care and are relatively expensive . Proteomic and immunological analyses of L . loa infected human samples have identified L . loa specific biomarkers . Of these , the L . loa protein LOAG_16297 has been introduced as a promising biomarker for future antigen-based tests , but it has not yet been applied for point-of-care testing [18] . Finally , a portable smartphone-based microscope ( LoaScope ) has been developed to simplify and accelerate the counting of L . loa microfilariae at the point-of-care [19] . Additionally , there are well-established immunoassays [20] [21] that detect circulating antibodies specific for the Ll-SXP-1 gene product . Ll-SXP-1 ( GenBank accession number: EFO21235 . 1 ) is a 168 amino acid protein of unknown function expressed by all stages of the L . loa parasite . Orthologs of the Ll-SXP-1 gene have been identified in the genome of O . volvulus ( Ov17 ) , W . bancrofti ( Wb-SXP-1 ) [22–25] , and B . malayi ( Bm14 , also known as BmM14 ) [26 , 27] , which display a 51–53% sequence identity to Ll-SXP-1 ( S1 Table ) . The M . perstans genome has not been sequenced yet . An ELISA assay configured to detect total IgG to Ll-SXP-1 was 67% sensitive and 81% specific when patients infected with other filarial diseases were used as comparators [20] . When the test was restricted to detecting only the IgG4 isotype , the sensitivity decreased to 47% but the specificity against other filariae increased to 99% [20] . Similarly , a different type of immunoassay format ( LIPS ) was configured to detect either total IgG or IgG4 . These LIPS assays dramatically increased the sensitivity ( 93–100% ) but at a loss of specificity ( 78–81% ) , even in the IgG4 variant [21] ( S2 Table ) . Herein , we adapt the validated Ll-SXP-1 methodology to a simple and inexpensive LFA to assess exposure to L . loa .
The article reports test results on human sera . All samples were collected from subjects as part of registered protocols approved by the Institutional Review Boards of the National Institute of Allergy and Infectious Diseases , National Institutes of Health , collected under NCT00001230 , NCT00342576 , or 92-I-0155 ( inactive ) . Some samples were collected as part of a large international field project approved by their respective governments . Written informed consent was obtained from all subjects . The Loa Antibody Rapid Test contains a test strip within a plastic cassette , which has a window and a single sample port . The test strip consists of four abutting components: a blood-filter ( Ahlstrom , Alpharetta , GA ) , where the sample is deposited , and which prevents erythrocytes from migrating to the rest of the test strip , a fiberglass pad ( Ahlstrom ) in which reporter nanoparticles are dried together with other reagents in a sugar matrix , a nitrocellulose strip containing the test and control lines ( EMD Millipore , Billerica , MA ) , and an absorbent pad to wick excess moisture ( Ahlstrom ) . The Loa Antibody Rapid Test features novel reporter nanoparticles consisting of a 20 nm thick gold shell encapsulating a spherical 110 nm silica core ( nanoComposix , San Diego , CA ) . The optical properties of the particles can be modulated by varying the shell thickness . The nanoshells employed in the Loa Antibody Rapid Test are blue-to-black and have a per-particle extinction coefficient 35 times higher than that of red 40 nm gold commonly employed in other commercial LFAs . Consequently , they appear darker to the human eye even when 35 times more diluted . This translates into an increase in analytical sensitivity of 2–10 fold , depending on the exact assay . The low-density silica interior decreases the overall density of the particles so that they are easily re-suspended in water and can flow unimpeded through the LFA membrane . The Loa Antibody Rapid Test is , to our knowledge , the first LFA to incorporate gold nanoshells . The Loa Antibody Rapid Test has a “bridged” design , with recombinant Ll-SXP-1 localized both at the surface of the gold nanoshells and at the test line . To be consistent with previous work [20] , a 148-amino acid partial sequence of Ll-SXP-1 was used ( GenBank accession no: AAG09181 . 1 ) . The design leverages the bivalency of antibodies . When an IgG antibody specific for Ll-SXP-1 is present , one of its Fab portions can bind the reporter nanoparticle while the other can be captured by the test line , thus leading to an accumulation of nanoparticles at the test line , and therefore to a visual signal . This design can , at least in theory , detect any antibody irrespectively of its isotype . For procedural control purposes , the Loa Antibody Rapid Test also contains nanoparticles conjugated to an anti-fluorescein antibody and a control line of fluorescein-BSA . Thus , if the eluent is applied properly , a control line will always be formed , indicating that the test has developed properly . The assay is run by laying the device flat ( e . g . on a table ) . Next , 5 μL of serum , plasma , or whole blood are placed in the port by means of a calibrated micropipette , followed by 2 drops of eluent ( 52 μL ) . The assay is a single-port design and sample and eluent are added to the same port . The assay is read after 20 minutes and readout remains valid for up to 1 hour , provided that the test strip remains wet during that time . If the assay is deliberately left to dry overnight , it should be re-wetted with 1 drop of eluent ( 26 μL ) before being read . In experiments where the Loa infected sample was diluted with negative serum , delipidized serum from uninfected North American individuals was utilized ( ConeBio , Seguin , TX ) . All testing was performed at ambient temperature and humidity ( 22°C , 40–55% relative humidity ) . The intensities of the test and control lines were quantified with a HRDR-200 smartphone-based chromatographic test reader ( Cellmic , Los Angeles , CA ) . The reader was programmed using Cellmic’s Test Developer Software ( TDS ) V3 . 7 . 0_160420 NK . The raw output values were obtained by integrating the Area Under the Peak ( AUP ) of zone intensities within a 10%-width security margin around each zone . The raw values are expressed as reader units ( RU ) derived from the calculated AUP . Test results were exported from the reader to Microsoft Excel using Cellmic’s Test Explorer Software ( TES ) . Each test strip was visually validated for potential physical shifts in TES and further numerically analyzed in Microsoft Excel . Well-characterized pools of sera were used to optimize the LFA and to test reproducibility . The final device was tested in a blinded fashion using individual serum samples from patients with documented patent L . loa infection from Cameroon , Gabon , Benin , and the Central African Republic ( n = 109 ) , W . bancrofti infection from India and the Cook Islands ( n = 49 ) , O . volvulus infection from Ecuador , Guatemala and Ghana ( n = 99 ) , M . perstans infection from an onchocerciasis-negative area of Mali ( n = 16 ) , and S . stercoralis from South America and Southeast Asia ( n = 40 ) . Additional control sera were used from healthy controls from Loa-non-endemic regions of Africa ( Mali , Ghana n = 28 ) and from North America who had never traveled outside North America ( n = 49 ) . The parasitological diagnosis of all filarial infections was made based on the demonstration of mf in the blood ( for L . loa , W . bancrofti , and M . perstans ) , in the skin ( for O . volvulus ) , or the detection of larvae in stool samples ( S . stercoralis ) . For the few amicrofilaremic individuals with L . loa , a definitive diagnosis was made based on standardized criteria: presence of an eyeworm or Calabar swelling in individuals with a relevant exposure history [5] . All data were analyzed using GraphPad Prism ( version 7 . 0 ) software . Groups of variables were analyzed for statistically significant differences using the Mann-Whitney U test . Correlations between variables were analyzed using the non-parametric 1-tail Spearman rank correlation test . Sensitivity and specificity values were calculated using Fisher’s exact test , and their 95% confidence intervals were determined by the Brown-Wilson method .
The analytical sensitivity of the Loa Antibody Rapid Test was assessed as per the General Procedure with pooled L . loa sera , either undiluted or serially diluted with negative serum from uninfected North American individuals . The signal was measured after 20 minutes with the Cellmic smartphone reader . When tested with undiluted pooled L . loa sera , the assay gave a sharp test line ( 1113 RUs ) , comparable in visual intensity to the control line ( Fig 1 ) . The signal remained sharp after a 5-fold and 10-fold dilution ( 914 and 890 RUs , respectively ) . Upon further dilutions of the test sample , the test line intensity gradually decreased . At a 100-fold dilution , the signal was clearly visible but weaker ( 447 RUs ) . The limit of eye detection was reached at an ~ 800-fold dilution ( 100 RUs ) . The pool of L . loa sera was tested at two different dilutions ( 10- and 100-fold ) . Five microliters were deposited on the assay , followed by 2 drops ( 52 μL ) of eluent . The test line developed rapidly and was clearly visible within 2 minutes . The signal increased over time , was half-developed after 5 minutes , and reached a plateau after 20 minutes ( Fig 2 ) . A single device was run with the pool of L . loa sera ( 5 μL ) for 30 min , and the same test line was measured 25 consecutive times with the reader . The mean value and standard deviation of the 25 reads were 1110 ±7 RUs , corresponding to a coefficient of variation CV = 0 . 7% ( Table 1 ) . The experiment was repeated using 5 μL of the same pooled L . loa serum sample , diluted either 10-fold or 100-fold with negative human serum . The mean signal decreased , while the standard deviation remained at 8–10 RUs , leading to CV values of 1 . 2–1 . 7% . It can be concluded that the reader gives highly reproducible readouts . Having established that the reader gives highly reproducible results , we next evaluated the reproducibility of cassettes coming from a single manufacturing lot . Ten cassettes were randomly selected and tested with 5 μL of pooled L . loa sera , either undiluted , diluted 10-fold , or diluted 100-fold with negative serum prior to application . The standard deviations were in the range of 69–76 RUs , corresponding to CV values in the 6–19% range ( Table 2 ) . Furthermore , the control lines were tightly grouped with a median value of 1321 RUs ( S1 Fig ) . The Loa Antibody Rapid Test was evaluated at the National Institutes of Health in the Laboratory of Parasitic Diseases using a set of cryopreserved human sera . For logistic reasons , the tests were let dry at the end of the run and were rewetted before scoring . The drying/rewetting process decreases the test line intensity by up to 20% but still gives reproducible and interpretable results . Fig 3 summarizes the clinical data . Most samples of sera from those with L . loa infection gave sharp signals , with a median value of 845 RUs . Onchocerciasis samples cross-reacted to a small degree with Ll-SXP-1 but there was a clear differentiation in the RUs between the two groups ( P value < 0 . 0001 in a Mann-Whitney U Test ) . The onchocerciasis group gave substantially weaker signals and a median value of 21 RUs—either not detectable or barely detectable with the naked eye . Similarly , the bancroftian filariasis samples partially cross-reacted with the L . loa samples , but were even weaker with a median value of 10 RUs ( undetectable by the naked eye , P < 0 . 0001 ) . M . perstans samples gave even weaker signals , with a median value of 3 . 5 RU ( P < 0 . 0001 ) . Strongyloides samples as well as endemic and non-endemic normal controls were all negative by eye ( P < 0 . 0001 ) . When read with the naked eye , the test was 94% sensitive for L . loa . The specificity was 82% vs . O . volvulus , 84% vs . W . bancrofti , 88% vs . M . perstans , and 100% vs . S . stercoralis , endemic normal , and non-endemic normal samples ( Table 3 ) . The LFA reader offers the remarkable advantage of establishing an objective cutoff value . By adjusting the cutoff value , the assay results can be tuned to modulate the sensitivity and specificity to the needs of the end-users ( Table 3 ) . A cutoff of 100 RUs is just above what can be detected by the unaided eye and provides results similar to the visual scoring: 88% sensitivity , 100% specificity when compared to normal , uninfected sera , and 83–88% specificity towards W . bancrofti , and M . perstans . With a cutoff of 200 RUs , the sensitivity is 84% and the specificity towards the other filariae is in the 89–94% range . By increasing the cutoff to 600 RUs , the sensitivity decreases to 71% , but the specificity towards other filarial species increases to 96–100% . Receiver Operating Characteristic ( ROC ) curves ( Fig 4 and S2 Fig ) allow to examine in more detail the effect of the cutoff on the sensitivity and specificity . Of the 109 L . loa infected patients tested , 62 had known mf counts , including 26 amicrofilaremic patients . The mf levels of the 62 individuals with available microfilaremia data were plotted against the quantitative data reported by the LFA reader ( Fig 5 ) . When including all 62 data points , a 1-tail Spearman analysis revealed only a marginal correlation ( r = 0 . 36 , p = 0 . 0018 ) between test line intensity and microfilaremia . When restricting the analysis to the 36 people with circulating mf , the 1-tail Spearman analysis did not show a statistically significant correlation between the two variables ( r = 0 . 16 , p = 0 . 18 ) . Of the 26 amicrofilaremic patients , 24 ( 92% ) were positive in the LFA when read visually and had wide range of responses when quantified , from 0 to 1133 RUs ( Fig 5 ) .
GenBank Accession Numbers: B . malayi antigen , partial ( Bm14 ) AAA67319 . 1; L . loa SXP-1: EFO21235 . 1; O . volvulus Ov17: AAA18283 . 1 . ; W . bancrofti SXP antigen , partial: AAC70783 . 1 . | Loiasis affects over 10 million people in sub-Saharan Africa , and there are no commercial assays to detect Loa loa infection . New diagnostics for L . loa are urgently needed for two different purposes . First , although L . loa is generally a relatively asymptomatic infection , it has been associated with serious renal , cardiac , and neurological complications . Second , L . loa infection represents a major obstacle to the MDA-based elimination of river blindness and , to a lesser extent , of lymphatic filariasis . The programs to control and eliminate these parasites rely on mass administrations of ivermectin , a drug that has been associated with neurologic adverse events and sometimes death in patients with high levels of L . loa microfilariae . Herein , we present a novel lateral flow assay for L . loa infection . It is hoped that this test will help refine the current maps of loiasis , which will in turn allow optimization of programmatic decisions in the fight against O . volvulus and W . bancrofti , and ultimately against L . loa itself . | [
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"onchocerc... | 2017 | A novel rapid test for detecting antibody responses to Loa loa infections |
CD8+ T lymphocytes play an important role in controlling infections by intracellular pathogens . Chemokines and their receptors are crucial for the migration of CD8+ T-lymphocytes , which are the main IFNγ producers and cytotoxic effectors cells . Although the participation of chemokine ligands and receptors has been largely explored in viral infection , much less is known in infection by Trypanosoma cruzi , the causative agent of Chagas disease . After T . cruzi infection , CXCR3 chemokine receptor is highly expressed on the surface of CD8+ T-lymphocytes . Here , we hypothesized that CXCR3 is a key molecule for migration of parasite-specific CD8+ T-cells towards infected tissues , where they may play their effector activities . Using a model of induction of resistance to highly susceptible A/Sn mice using an ASP2-carrying DNA/adenovirus prime-boost strategy , we showed that CXCR3 expression was upregulated on CD8+ T-cells , which selectively migrated towards its ligands CXCL9 and CXCL10 . Anti-CXCR3 administration reversed the vaccine-induced resistance to T . cruzi infection in a way associated with hampered cytotoxic activity and increased proapoptotic markers on the H2KK-restricted TEWETGQI-specific CD8+ T-cells . Furthermore , CXCR3 receptor critically guided TEWETGQI-specific effector CD8+ T-cells to the infected heart tissue that express CXCL9 and CXCL10 . Overall , our study pointed CXCR3 and its ligands as key molecules to drive T . cruzi-specific effector CD8+ T-cells into the infected heart tissue . The unveiling of the process driving cell migration and colonization of infected tissues by pathogen-specific effector T-cells is a crucial requirement to the development of vaccine strategies .
The causative agent of Chagas disease Trypanosoma cruzi is an intracellular parasite that infects a variety of cells of the mammalian host [1 , 2] . The activation of adaptive immune response occurs by recruiting T lymphocytes to the infection sites after the presentation of trypomastigote/amastigote-related proteins via MHC-I or MHC-II [3 , 4] . CD8+ T lymphocytes are the cells primarily responsible for controlling intracellular pathogens such as T . cruzi [5–7] . Their relevance to the control of T . cruzi infection was demonstrated during the infection of CD8-deficient mice , or by the blockade of this molecule using monoclonal antibodies; in both cases , animals did not survive to infection [8] . The multiple antiparasitic mechanisms mediated by these cells include secretion of cytokines and direct cytotoxicity against infected cells [9 , 10] . The importance of the immune response mediated by CD8+ T lymphocytes , which promote resistance to T . cruzi infection , has led several groups to investigate different vaccine strategies [11] . Our group has been studying the prime-boost protocol that uses plasmid vector for priming and a replication-defective human adenovirus type 5 ( AdHu5 vector ) [9 , 12] for boosting , both containing an insertion of the amastigote surface protein 2 ( ASP2 ) gene ASP2 . That immunization protocol can induce a strong CD8-mediated response able to protect the highly susceptible A/Sn mice to experimental T . cruzi infection [13 , 14] . Recently , we have shown that more than proliferative response , the specific CD8+ T-cells need to recirculate to exert protection against infection in A/Sn mice [9 , 13] . Chemokine molecules are small chemotactic molecules responsible for the guidance of leukocyte migration during homeostasis and inflammation [15] . In addition to cell migration , chemokines acting as costimulatory molecules involved in T-lymphocytes activation , differentiation and proliferation [16 , 17] . Pro-inflammatory chemokines are induced by infection with different pathogens and molecular inflammatory stimuli [18] . Chemokines expression are induced by an IFN-γ- and TNF-enriched Th1-type immune response triggered by infection with intracellular pathogens [19 , 20] such as T . cruzi [21–23] . Naive T cells differentiate into cytokine-producing cells such as IFN-γ , IL-2 and TNF; this differentiation occurs through the expression of interleukin IL-12 and the T-bet transcription factor [24] . Differentiated effector T cells express high levels of the CXC-chemokine receptor CXCR3 , whereas its ligands CXCL10 ( IP-10 ) , CXCL11 , and CXCL9 ( MIG ) are produced by antigen presenting cells present in the infected tissues [25] . The role of CXCR3 receptor and the migration of effector T lymphocytes during Th1 type responses have already been demonstrated in a murine model infected by the protozoan Toxoplasma gondii . This receptor was highly expressed on CD4+ T cells and was responsible for the migration of T lymphocytes to the intestine , enabling the control of parasite load and tissue damage , and consequently the survival of infected mice [26] . In addition to cell migration , chemokine receptors such as CXCR3 affect the differentiation of T lymphocytes . Indeed , recently published studies have shown that the absence of CXCR3 favors the differentiation of memory effector CD8+ T cells [27 , 28] . Considering that CXCL10 and CXCL9 are expressed in heart tissue of acute and chronically T . cruzi-infected mice presenting a CD8+ T-cell-enriched myocarditis [21 , 29] , here we hypothesized that CXCR3 is a key molecule for migration of specific CD8+ T-cells towards infected tissues . Using a model of prime-boost immunization in highly susceptible to T . cruzi infection A/Sn mice , we analyzed the role of CXCR3 receptor present on pathogen-specific CD8+ T-cells migration , compartmentalization and effector functions . Further , we used an anti-CXCR3 blocking antibody as a tool to interfere in the migration process of CD8+ T-cells and analyzed susceptibility to infection , migration pattern , tissue colonization and effector activity . Therefore , we aimed to shed light on the importance of CXCR3-driven cell migration , and its role to protection and tissue injury in T . cruzi infected hosts . This knowledge may contribute to the strategies of vaccine development against intracellular pathogens .
This study was carried out in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the Brazilian National Council of Animal Experimentation ( http://www . cobea . org . br ) . The protocol was approved by the Ethical Committee for Animal Experimentation at the Federal University of Sao Paulo ( Id # CEP 7559051115 ) . Eight-weeks-old female mice , A/Sn , C57BL/6 or CD8-deficient mice ( cd8-/- ) , were purchased from the Federal University of São Paulo ( CEDEME ) . CCR2 deficient mice ( ccr2-/- ) were kindly supplied by Dr . João Santana , Ribeirão Preto School of Medicine-FMPR . Blood trypomastigotes of Y strain of T . cruzi were maintained by weekly passages in A/Sn mice at the Xenodiagnosis Laboratory of Dante Pazzenese Cardiology Institute . For in vivo experiments , each mouse was inoculated with 150 ( A/Sn ) or 104 trypomastigotes forms from blood ( C57BL/6 ) diluted in 0 . 2 mL PBS and administered subcutaneously ( s . c . ) at the base of the tail . Parasitemia was determined by the examination of 5 μL of blood , and parasites were counted with a light microscope . Heterologous prime-boost immunization protocol with plasmid pIgSPCl . 9 and the human replication-defective adenovirus type 5 containing the ASP2 gene , as described previously [12 , 30] , was used . Briefly , the immunization consists of a dose of plasmid DNA ( 100 μg ) as a prime ( pcDNA3 control or pIgSPClone9 ) and three weeks later , mice were boosted with 2x108 plaque-forming units ( pfu ) of the adenoviral vectors Adβ-gal or AdASP2 . Both injections were performed via intramuscular route ( Tibialis anterior muscle ) . After 15 days of boosting mice were infected with T . cruzi . Blocking monoclonal antibodies anti-CXCR3 ( clone CXCR3-173 , BioXcell ) , anti-CCL2 ( clone 2H5 , BioXcell ) and isotype control antibody Rat IgG2a ( clone 2A3 , BioXcell ) , were administered via i . p route on the same day of infection and every 48 hours until 20 days after infection . The quantity of antibodies administered was 250 μg of mAb/mouse . The dose was the same used in previously studies [31] . The groups were divided as shown below: TEWETGQI immunodominant peptide described earlier [32] , was synthesized by GenScript ( Piscataway , New Jersey ) and used for in vitro and ex vivo stimulation of splenocytes . The multimer H2KK-TEWETGQI ( Immudex Copenhagen , Denmark ) was used for specific CD8+ T cell detection . Hearts and spleens from βgal+T . cruzi , ASP2+T . cruzi and ASP2+αCXCR3+T . cruzi were used for DNA extraction . The DNA extraction , the specific primers for a satellite DNA region of the parasite ( T . cruzi ) and the qPCR reaction using TaqMan Universal Master Mix II with UNG were adapted from Piron and colleagues [33] . Briefly , 1x106 responder cells from spleen were incubated with 3x105 antigen-presenting cells in complete medium ( 1% NEAA , 1% L-glutamine , 1% vitamins and 1% pyruvate , 0 , 1% 2-ME , 10% FBS ( HyClone ) , 20 U/mL mouse recombinant IL-2 ( SIGMA ) and on a plate previously coated with capture antibody those cells were incubated in the presence or absence of 10 μM of peptide TEWETGQI . After 24 hours the plates were washed with PBS and PBS-Tween 20 ( 0 . 05% Tween ) . Each well received 2 μg/mL of biotinylated anti-mouse monoclonal antibody ( clone XMG1 . 2 , Pharmingen ) . The plates were incubated with streptavidin-peroxidase ( BD ) and developed by adding peroxidase substrate ( 50mM Tris-HCl , pH 7 . 5 , containing 1 mg/ml DAB and 1 μL/ml 30% hydrogen peroxide , both from SIGMA ) . The number of IFN-γ-producing cells was determined using a stereoscope . Two million cells from spleen were treated with ACK buffer ( NH4Cl , 0 . 15 M; KHCO3 , 10 mM; Na2-EDTA 0 . 1 mM; pH = 7 . 4 ) . Both spleen and heart cells were stained with H2Kk-TEWETGQI multimer for 10 minutes at RT . The splenocytes cell surface was stained for 30 min at 4°C . The following antibodies were used for surface staining: anti-CD3 APCcy7 ( clone 145-2C11 , BD ) , anti-CD8 PERCP or anti-CD8 PACIFIC BLUE ( clone 53–67 , BD ) , anti-CD11a FITC ( clone 2D7 , BD ) , anti-CD11c APCcy7 ( clone HL3 , BD ) , anti-CD44 FITC ( clone IM7 , BD ) , anti-CD62L PE ( clone MEL-14 , BD ) , anti-CXCR3 PERCP/Cy5 . 5 ( clone 173 , BioLegend ) , anti-CD27 FITC ( clone LG3A10 , BD ) , anti-CD4 PEcy7 ( clone RM4-5 , BD ) anti-KLRG1 FITC ( clone 2F1 , eBioscience ) , anti-CD49d PEcy7 ( clone R1-2 , BD ) , anti-CD69 PERCP ( clone H1 . 2F3 , BD ) , anti-CD43 PEcy7 ( 1B11 , BioLegend ) , anti-CD95 PEcy7 ( clone JO2 , BD ) , anti-CD25 FITC ( clone LG3A10 , BD ) , anti-CD127 PE ( clone SB/199 , BD ) , anti-CD122 FITC ( clone TM-β1 , BD ) , anti-CD38 PE ( clone 90 , BD ) , anti-β7 PERCP ( clone FIB27 , BioLegend ) , anti-CD31 FITC ( clone MEC 13 . 3 , BD ) , anti-CD272 PE ( clone 8F4 , eBioscience ) , anti-PD-1 FITC ( clone J43 , eBioscience ) , anti-CTLA-4 PE ( clone UC10-4B9 , eBioscience ) , and anti-CCR7 PE ( clone 4B12 , BD ) . For annexin V and 7-AAD assays , 2x106 of spleen cells were labeled with multimer , subsequently , the cells were stained according to the Annexin-PE Kit protocol ( BD Pharmingen ) . To detect IFN-γ , TNF or granzyme B by intracellular staining , 2x106 cells/mL in cell culture medium containing CD107a FITC antibody ( clone 1D4B , BD ) , anti-CD28 ( clone 37 . 51 , BD ) , BD Golgi-Plug ( 1 μL/mL ) and monensin ( 5 μg/mL ) were incubated in presence or absence of 10 μM of peptide TEWETGQI , no longer than 12 hours in V-bottom 96-well plates with a final volume of 200 μL at 37°C and containing 5% CO2 . Cells were washed and stained for surface markers with anti-CD8 PERCP antibody ( clone 53–6 . 7 , BD ) on ice for 30 min . Cells were then double washed in buffer containing PBS , 0 . 5% BSA , and 2 mM EDTA , fixed and permeabilized with BD perm/wash buffer . After the double wash procedure with BD perm/wash buffer , cells were stained for intracellular markers using APC-labeled anti-IFN-γ ( clone XMG1 . 2 , BD ) , PE-labeled anti-TNF ( clone MP6-XT22 , BD ) and PE-labeled anti-granzyme B ( clone GB11 , Invitrogen ) for 20 minutes on ice . Finally , cells were washed twice with BD perm/wash buffer and fixed in 1% PBS-paraformaldehyde . At least 700 , 000 cells were acquired on a BD FACS Canto II flow cytometer and then analyzed with FlowJo . For isolating lymphocytes in the heart , we used the protocol described by Gutierrez and colleagues [34] . Briefly , hearts collected from 5 mice at day 20 dpi were minced , pooled , and incubated for 1h at 37°C with RPMI 1640 , supplemented with NaHCO3 , penicillin-streptomycin gentamicin , and 0 . 05 g/mL of liberase blendzyme CI ( Roche , Basel , Switzerland ) . The tissues were processed in Medimachine ( BD Biosciences ) with phosphate buffered saline ( PBS ) containing 0 . 01% bovine serum albumin ( BSA ) . After tissue digestion and washes the lymphocytes were isolated by Ficoll gradient ( Sigma ) . On the same day of infection mice were treated with 2 mg of BrdU ( 5-bromo-2'-deoxiuridine , SIGMA ) via i . p route and every 48 hours , until 20 days after challenge . Then , 2x106 splenocytes were stained with H2Kk-TEWETGQI multimer; BrdU staining was performed according to the BrdU-FITC Kit protocol ( BD Pharmingen ) . At least 700 , 000 cells were acquired on a BD FACS Canto II flow cytometer and analyzed with FlowJo 8 . 7 . Splenocytes from βgal+T . cruzi , ASP2+T . cruzi , and ASP2+αCXCR3+T . cruzi were stained with 1 , 25 μM of carboxyfluorescein diacetate succinimidyl diester ( CFSE; Molecular Probes , Eugene , OR , USA ) , stimulated with TEWETGQI peptide , and incubated during 6 days at 37°C . Following , splenocytes were stained with H2Kk-TEWETGQI multimer and the percentage of CFSE dilution was analyzed . At least 700 , 000 cells were acquired on a BD FACS Canto II flow cytometer and analyzed with FlowJo 8 . 7 . We used the protocol described by Silverio et al [10] . Briefly , splenocytes collected from naive A/Sn mice were treated with ACK buffer to lyse the red blood cells . Those cells were divided into two populations and were labeled with the fluorogenic dye CFSE ( Molecular Probes , Eugene , OR , USA ) at a final concentration of 10 μM ( CFSEhigh ) or 1 μM ( CFSElow ) . CFSEhigh cells were coated with 2 . 5 μM of the TEWETGQI ASP2 peptide for 40 minutes at 37°C . CFSElow cells remained uncoated . Subsequently , CFSEhigh cells were washed and mixed with equal numbers of CFSElow cells before intravenous injection ( 2x107 cells per mouse ) into recipient mice . Spleen cells from the recipient mice were collected at 20 hours after adoptive cell transfer and fixed with 1 . 0% paraformaldehyde . At least 100 , 000 cells were acquired on a BD FACS Canto II flow cytometer and analyzed with FlowJo 8 . 7 . The percentage of specific lysis was determined using the following formula: %lysis=1− ( %CFSEhighinfected/%CFSElowinfected ) ( %CFSEhighnaive/%CFSElownaive ) x100 . Total RNA from hearts of naïve , βgal+T . cruzi , ASP2+T . cruzi and ASP2+αCXCR3+T . cruzi groups , was extracted by using TRIzol and complementary DNA prepared using SuperScript IV VILO ( Applied Biosystems ) . Quantitative PCR was performed with TaqMan Universal Master Mix II ( Applied Biosystems ) using a StepOne thermocycler ( Applied Biosystems ) . We used a customized plate—TaqMan Array 96-well Mouse Chemokines Plate targets genes . Hearts were fixed in 10% formalin , and then dehydrated , embedded in paraffin blocks , and sectioned in microtome . Staining was obtained with hematoxylin and eosin , and the number of amastigotes nests was quantified using a light microscope with 40x objective lens . Overall , 25 fields/group were counted . For immunohistochemistry the mice’s hearts were removed and frozen in Tissue-Tek O . C . T ( Sakura Fineteck ) . The blocks were sectioned in cryostat ( 7 μm thickness ) and then fixed in ice-cold acetone for 15 minutes . The samples were stained with 20 μg of the biotinylated anti-CD8 antibody ( clone 53–6 . 7 , RD systems ) for 12 hours . After incubation , samples were labeled with streptavidin Alexa Fluor 488 ( Thermo Fischer ) at the concentration of 0 . 5 mg/mL , diluted 1:100 for 1 hour at room temperature . The DAPI ( 4' , 6-diamidino-2-phenylindole , Sigma ) dye was used for labeling the cell nucleus , the concentration used was 5 mg/mL . The images were acquired in Confocal Leica TCS SP8 CARS microscope from Institute of Pharmacology and Molecular Biology ( INFAR ) . The images were obtained using the 63x objective and processed in ImageJ software . Mice’s serum was collected on days 0 , 6 , 8 , 10 , 12 and 14 after infection in order to quantify the ligands of CXCR3 , IP-10 ( CXCL10 ) , MIG ( CXCL9 ) , also , MCP-1 ( CCL2 ) and RANTES ( CCL5 ) . The quantification was performed according to the MCYTOMAG-70K Kit protocol ( Merck Millipore ) . Luminex xMAP in the Institute of Pharmacology and Molecular Biology ( INFAR ) was used to read the plates . CD8+T cells from spleens of βgal+T . cruzi , ASP2+T . cruzi , and ASP2+αCXCR3+T . cruzi groups were purified using CD8a+ T cell isolation kit ( Miltenyi ) and labeled with 10 μM of CFSE . 1x106 CD8+ T cells were transferred via i . v . route to infected CD8 deficient mice ( day 6 of infection ) and 6 days afterwards , the number of CD8+ CFSE cells on recipient mice’s hearts were analyzed by fluorescent microscopy . CD8+ T-cells from mice were purified using a negative selection kit ( Miltenyi Biotec ) . A transwell microplate ( Corning ) with 5μm membrane pore was used to carry out the migration assay . For each condition tested , lower chambers of transwell were filled with 600 μL in the absence or presence of 100ng/mL CXCL9 , CXC10 and/or CXCL11 ( RD systems ) . CD8+ T-cells ( 5x104 in 300 μL ) were deposited in the upper chamber of transwell and incubated for 3h at 37°C . CD8+ T-cells were harvested from the lower chamber and counted using cytometer . The migration index was calculated through the ratio of cells that migrated in the presence of medium and ligands . Parasitemia , number of IFN-γ-producing cells ( ELISpot ) , and absolute number of CD8+ T-cells were compared by analysis of unidirectional variance ( ANOVA ) ; subsequently , the Tukey’s HSD test was used ( http://vassarstats . net/ ) . The survival rate was compare using the Log-rank test using GraphPad Prism 7 . The expression of molecules was compared using MFI ( Mean Fluorescence Intensity ) , and the naive group MFI was taken as the baseline . MFI was determined by the FlowJo software ( version 9 . 9 ) . The Kaplan-Meier method was employed to compare survival rates of the studied groups . All statistical tests were performed with GraphPad Prism 5 . 0 ( La Jolla , CA , USA ) . Differences were considered statistically significant when P < 0 . 05 .
To investigate whether T lymphocytes expressed CXCR3 receptor on T cells surface after immunization and/or infection with T . cruzi , splenic parasite antigen-specific CD8+ and activated CD4+ T-cells of A/Sn mice were labeled on day 20 after infection . The dot-plot graphs show the frequency of specific CD8+ T cells , gated as positive for H2KK-TEWETGQI ( Fig 1A ) . In infected group , immunized with the control DNA/adenovirus encoding the βgal ( βgal+T . cruzi group ) , the frequency of H2KK-restricted TEWETGQI-specific CD8+ T-cells was lower ( Q2: 0 . 49% ) when compared to that found in mice immunized with DNA/adenovirus encoding the ASP-2 ( Q2: 5 . 91% ) and further infected with T . cruzi ( ASP2+T . cruzi ) , as shown in Fig 1A . Also , during the infection , the Mean of Fluorescence Intensity ( MFI ) of CXCR3 receptor was higher in βgal+T . cruzi than in ASP2+T . cruzi group ( Fig 1B ) . When CD44high and CD62Llow activated CD4+ T-cells were gated ( Fig 1C ) , we observed that differently in specific CD8+ T cells , CXCR3 expression was higher expressed and similar in both experimental groups ( βgal+T . cruzi and ASP2+T . cruzi ) ( Fig 1D ) . In addition to enhanced CXCR3 expression , we evaluated the concentrations of the CXCR3 ligands IP-10/CXCL10 and MIG/CXCL9 in the serum of mice at days 0 , 6 , 8 , 10 , 12 , and 14 after infection . As shown in Fig 1E and 1F , the concentrations of CXCL9 and CXCL10 increased on day 10 after challenge in both groups , βgal+T . cruzi and ASP2+T . cruzi and reaching the maximum concentration on day 14 after infection . Importantly , the levels of IP-10 and MIG were higher in the serum of mice of the group βgal+T . cruzi when compared to the ASP2+T . cruzi group . We also measured the levels of the chemokines CCL2/MCP-1 and CCL5/RANTES , but no differences were observed in those chemokine levels when compared to those found in the serum of naïve group ( S1A and S1B Fig ) . Interestingly , purified CD8+ T cells from spleen of ASP2+T . cruzi mice group had higher migration index after chemotaxis induced by the recombinant proteins CXCL9 and CXCL10 , when compared to cells harvested from mice of βgal+T . cruzi group ( Fig 1G ) . No significant migration was detected under stimulation with CXCL11 , supporting the selective effect of CXCL9 and CXCL10 to induce ex vivo chemotaxis of CD8+ T-cells . These results showed that CXCR3 is highly expressed on T cell surface as well as CXCR3 ligands ( CXCL9 and CXCL10 ) , especially in the infected group; however , the immunized group’s CD8+ T cells showed more migration capacity after stimulation with CXCL9 and CXCL10 recombinant proteins . Since we have previously shown that the recirculation of CD8+ T lymphocytes was more important than their proliferative response to control T . cruzi infection [13] , we evaluated which chemokine receptors could be important to drive the migration and to the effector functions of ASP2-specific CD8+ T-cells after vaccination of highly susceptible A/Sn mouse lineage [9] challenged with the virulent T . cruzi Y strain . In order to analyze that , immunized and infected mice were treated with chemokine-specific blocking monoclonal antibodies to the Th1-related chemokines CXCR3 and CCL2 . On the same day of challenge with the Y strain infection , A/Sn mice were treated with the anti-CXCR3 or anti-CCL2 monoclonal antibodies . This procedure was repeated every 48 hours until day 20 after infection . We observed that the treatment with anti-CCL2 antibody had no impact on the protective effect of ASP2 vaccination , as parasitemia levels remained lower compared to the ASP2+T . cruzi group , whereas , as expected , higher parasitemia levels were observed in mice of group βgal+T . cruzi ( Fig 2A ) . Further , all mice from untreated and anti-CCL2-injected ASP2+T . cruzi groups survived , while mice from βgal+T . cruzi group succumbed to infection ( Fig 2B ) . To approach the participation of CCR2 , which has as ligands CCL2 and other CC-chemokines [35] , we used CCR2-deficient ( ccr2-/- ) mice . As previously described [36] , T . cruzi-infected CCR2-deficient mice died due to infection , while wild-type resistant C57BL/6 mice survived . However , all CCR2-deficient mice immunized with the DNA/adenovirus ASP2 vaccine survived after to be challenged with T . cruzi ( S2A and S2B Fig ) . After anti-CXCR3 administration into ASP2-vaccinated and challenged mice , we observed a trend in parasitemia increase only on day 12 after infection , when the peak of parasitemia was noticed , when compared to the immunized and isotype-treated control group ( ASP2+T . cruzi ) , as shown in Fig 2C . At 20 days after infection , the quantification of parasite load in spleen by real time qPCR supported that trend in the treated group , showing that the number of parasites in the spleen of anti-CXCR3-treated vaccinated and challenged mice ( ASP2+αCXCR3+T . cruzi group ) was similar to the βgal+T . cruzi group and it contrasted with the low parasite load found in the spleen of mice of the isotype-treated ASP2+T . cruzi group ( Fig 2D ) . The survival rate was followed for a 45-day period after infection and all mice from the ASP2+αCXCR3+T . cruzi group died due to infection while 100% of mice of the ASP2+T . cruzi group survived ( Fig 2E ) . Taken together , these data indicate that the CXC-chemokine CXCR3 is important to control parasite dissemination and mice survival after challenge of ASP2-vaccinated mice . Next , we analyzed the number of antigen-specific CD8+ T-cells after the treatment with anti-CXCR3 antibody . To perform that , we measured the number of specific CD8+ T-cells in spleen using the H-2Kk-restricted TEWETGQI multimer , characterized as an immunodominant epitope of the ASP2 protein in A/Sn mice [3] . As expected , after immunization and infection , the frequency of TEWETGQI-specific CD8+ T-cells was higher in mice of ASP2+T . cruzi group than in mice of βgal+T . cruzi control group . After treatment with anti-CXCR3 , we observed a decrease in the frequency of TEWETGQI-specific CD8+ T-cells in the anti-CXCR3 treated group , but no statistical differences in absolute numbers of TEWETGQI-specific CD8+ T-cells were observed in ASP2+αCXCR3+T . cruzi group when compared to the ASP2+T . cruzi group ( Fig 3A and 3B ) , suggesting that the treatment with anti-CXCR3 antibody did not influence in the number of TEWETGQI-specific CD8+ T-cells in the A/Sn mice’s spleen . To investigate whether anti-CXCR3 treatment affected the polyfunctionality and cytokines production by TEWETGQI-specific CD8+ T-cells , we performed an Intracellular Staining assay ( ICS ) to measure the percentage of epitope-specific CD8+ T-cells producing IFN-γ and TNF cytokines as well as the degranulation marker CD107a molecule ( LAMP-1 ) , an indirect indicator of cytotoxicity activity , after ex vivo stimulation with TEWETGQI peptide . The gate strategy used to evaluate the polyfunctionality of TEWETGQI-specific CD8+ T-cells is in S3A and S3B Fig . After immunization and infection ( ASP2+T . cruzi ) , the number of splenic polyfunctional ( IFN-γ+TNF+CD107a+ ) TEWETGQI-specific CD8+ T-cells increased ( 5 . 17 ± 0 . 68 ) , when compared to βgal+T . cruzi control group ( 3 . 55 ± 1 . 19 ) ( Fig 3C ) . Also , we observed that the treatment with anti-CXCR3 did not alter the frequency of polyfunctional TEWETGQI-specific CD8+ T-cells ( 4 . 25 ± 1 . 82 ) in comparison to the isotype-treated ASP2+T . cruzi group ( Fig 3C ) . Using the ELISpot assay to detect IFN-γ-secreting cells , we observed that the number of IFN-γ-producing CD8+ T-cells in βgal+T . cruzi group was lower than in the immunized and infected groups ( Fig 3D ) . In addition , the number of IFN-γ-producing CD8+ T-cells decreased in ASP2+αCXCR3+T . cruzi when compared to ASP2+T . cruzi group . Collectively , these data provide evidence that the polyfunctionality capacity of TEWETGQI-specific CD8+ T-cells , characterized by the capacity of producing cytokines and degranulation at the same time , was not altered after anti-CXCR3 administration . Previously , we have described that TEWETGQI-specific CD8+ T-cells generated by prime-boost heterologous immunization are effectors ( TE ) , characterized by the CD44high , CD11ahigh , CD62Llow , CD127low , and KLRG-1high phenotype [12] . These cells play a crucial role in the control of infection by producing cytokines and killing the target cells by direct cytotoxicity [9] . Here , we evaluated whether anti-CXCR3 treatment affects the function-linked phenotypes of TEWETGQI-specific CD8+ T-cells in the spleen . In order to analyze that , TEWETGQI-specific CD8+ T-cells were labeled with tetramer and markers associated with cell activation and differentiation . Overall , we observed that anti-CXCR3 treatment did not alter the phenotype of TEWETGQI-specific CD8+ T-cells when compared to the isotype-treated ASP2+T . cruzi group . Indeed , TEWETGQI-specific CD8+ T-cells from the ASP2+αCXCR3+T . cruzi group had effector phenotype characterized as CD44high , CD11ahigh , CD62Llow and KLRG-1high , comparable to the epitope-specific CD8+ T-cells found in the ASP2+T . cruzi group ( S4 Fig ) . Interestingly , we observed that the expression of the CD95 molecule was increased in the specific CD8+ T cells from spleen of ASP2+αCXCR3+T . cruzi group , when compared to the βgal+T . cruzi and ASP2+T . cruzi groups ( Fig 4A and 4B ) . Previously , our group showed that the reason of a suboptimal CD8+ T-cell response profile during infection with T . cruzi was associated with an upregulation of CD95 expression and a proapoptotic phenotype , that was reversible with ASP2 vaccination which prevented that phenotyping observed only during infection [37] . Taking into account those findings , we evaluated the proapoptotic phenotyping by labeling specific CD8+ T cells with annexin V and 7-AAD molecules . We observed in ASP2+αCXCR3+T . cruzi group an increase in annexin V levels when compared to the βgal+T . cruzi and ASP2+T . cruzi groups , however , the percentage of cells expressing 7-AAD was similar in all groups ( Fig 4C ) , indicating that anti-CXCR3 treatment increased the apoptotic phenotype in specific CD8+ T cells , but not necrosis . Next , we assessed the proliferative response of the TEWETGQI-specific CD8+ T-cells in vivo by BrdU incorporation assay and by CFSE-labeling after ex-vivo re-stimulation with TEWETGQI peptide . The number of epitope-specific CD8+ T-cells that incorporated BrdU was similar in all infected groups ( Fig 4D ) . Similar results were also observed in ex vivo CFSE-labeled cell proliferation assay ( Fig 4E ) . Together , these results suggest that anti-CXCR3 treatment of vaccinated and challenged mice increased the proapoptotic phenotype of TEWETGQI-specific CD8+ T-cells in the spleen . One of the effector functions of the CD8+ T-cells is to kill infected cells by direct cytotoxicity , which is crucial for controlling infection by T . cruzi [9] . Here , we evaluated the cytotoxicity activity of TEWETGQI-specific CD8+ T-cells after treatment with anti-CXCR3 antibody after immunization and infection . The cytotoxicity assay was performed using transference of 1x107 CFSElow ( not pulsed ) and CFSEhigh ( pulsed with TEWETGQI peptide ) to experimental groups . After 12 hours , the percentage of CFSEhigh lysis was measured . We demonstrated that the percentage of cytotoxicity in immunized mice treated with the anti-CXCR3 blocking antibody ( ASP2+αCXCR3 ) decreased when compared to isotype-treated ASP2-immunized mice ( Fig 5A and 5B ) . After infection , however , no differences were observed in the cytotoxicity activity of CD8+ T-cells in the spleen of mice from βgal+T . cruzi , ASP2+T . cruzi , and ASP2+αCXCR3+T . cruzi experimental groups ( Fig 5C ) . Moreover , granzyme B production by TEWETGQI-specific CD8+ T-cells was similar in these three experimental groups ( Fig 5D ) . Overall , the CXC-chemokine receptor CXCR3 indicates to be important to the cytotoxicity activity of TEWETGQI-specific CD8+ T-cells generated after prime-boost immunization protocol in A/Sn mice . Having shown the high expression of CXCR3 chemokine receptor in TEWETGQI-specific CD8+ T-cells , we evaluated the expression of CXCR3 ligands in heart , as well as other molecules involved in cell migration ( CC-chemokines and their receptors and cell adhesion molecules ) . In heart of naïve mice , all genes had low expression , except CXCL12 gene that was downregulated in infected groups . In general , we observed that in infected heart of mice from βgal+T . cruzi group only CXCL12 and CXCR5 were low expressed , while the other genes were highly expressed , including CXCR3 ligands such as: CXCL11 , CXCL10 and CXCL9 . In ASP2+T . cruzi experimental group , we observed a low expression of inflammatory cell migration genes , whereas in heart of mice from ASP2+αCXCR3+T . cruzi group , CXCR3 ligands CXCL10 and CXCL9 were high expressed , as well as CCR2 and CXCR5 ( Fig 6A ) . These results suggest that CXCR3 ligands , CXCL10 and CXCL9 were selectively high expressed in heart of infected mice , supporting that vaccination prevented the expression of most of the genes involved in cell migration here studied . T . cruzi infects the cardiac tissue [38] triggering an inflammatory response associated with tissue injury , leading to cardiomyopathy in 30% of the infected patients in the chronic phase of Chagas disease [11 , 39] . Thus , we evaluated the migration of CD8+ T-cells to heart after anti-CXCR3 treatment . For that propose , CFSE-labeled CD8+ T-cells obtained from βgal+T . cruzi , ASP2+T . cruzi , or ASP2+αCXCR3+T . cruzi groups were transferred to groups of CD8-deficient mice ( cd8-/- ) as shown in the experimental scheme in Fig 7A . The number of CFSE+CD8+ T-cells was quantified , and we observed a statistical decreased in the number of CFSE+CD8+ T-cells that migrated in the heart tissue of CD8-deficient mice who received CD8+ T-cells from ASP2+αCXCR3+T . cruzi mice , when compared to the recipient mice that received cells from the ASP2+T . cruzi donors ( Fig 7B and 7C ) . To endorse these results , we measured parasite burden and migration of TEWETGQI-specific CD8+ T-cells into the heart , after vaccination , challenge and anti-CXCR3 antibody administration . Firstly , we quantified the number of amastigote nests in the heart tissue by HE ( hematoxylin and eosin ) staining , and we observed that both βgal+T . cruzi and ASP2+αCXCR3+T . cruzi experimental groups had higher number of amastigote nests when compared to the ASP2+T . cruzi group ( Fig 8A and 8B ) . Also , we estimated the parasite load using qPCR , and again both βgal+T . cruzi and ASP2+αCXCR3+T . cruzi groups had an increased number of parasites in heart tissue when compared to the ASP2+T . cruzi group ( Fig 8C ) . Considering the results described above and the increased numbers of parasite nests seen in the heart after treatment with anti-CXCR3 antibody , we evaluated whether TEWETGQI-specific CD8+ T-cells migrate into the heart tissue after anti-CXCR3 treatment . For that propose , we purified parasite-specific CD8+ T-cells from cardiac tissue using a pool of dissociated hearts ( n = 5 mice/group ) and those cells were labeled with the H-2Kk-restricted TEWETGQI multimer . Curiously , the frequency of TEWETGQI-specific CD8+ T-cells decreased in the heart tissue of ASP2+αCXCR3+T . cruzi group when compared to ASP2+T . cruzi group ( Fig 8D and 8E ) , whereas the βgal+T . cruzi group had the lowest frequency of TEWETGQI-specific CD8+ T-cells . Additionally , we quantified the number of CD8+ T-cells in heart using confocal microscopy . Again , anti-CXCR3 decreased the number of CD8+ T cells in the heart ( Fig 8F and 8G ) . Altogether , these results show that CXCR3 guides TEWETGQI-specific CD8+ T-cells toward the T . cruzi-infected heart tissue , and these cells play an important role controlling the infection .
The recirculation of T lymphocytes into infected and , frequently , injured sites is essential for controlling infection by T . cruzi [13] . As chemokine receptors are pivotal for T-cell migration , we hypothesized that CXCR3 receptor might play an important role in parasite-specific CD8+ T-cells migration into infected tissues after immunization and challenge by T . cruzi . Firstly , we evaluated CCR2 and CXCR3 role during immunization and infection and both CXCR3 and CCR2 receptors are highly expressed in the heart of T . cruzi infected mice [22] . Other studies using the Colombian strain of T . cruzi have shown that CCR2-deficiency leads to increase in parasitemia [36] . The CC-chemokine receptor CCR2 is responsible for monocytes migration during the inflammation [40] , being CCL2 ( MCP-1 ) its main ligand . However , in our experiments the treatment with anti-CCL2 did not impact in parasitemia or survival rate . As CCR2-deficient mice were high susceptible and CCR2 has other ligands than CCL2 [41] , we immunized CCR2-deficient mice , and all vaccinated mice survived to the challenge with T . cruzi infection . Moreover , after anti-CXCR3 treatment , all mice had an increased parasitemia and burden of tissue parasitism , and died due to infection , showing that CXCR3 , but not CCR2 , had a pivotal role in T . cruzi resistance . The role of CXCR3 in the resistance against infections by virus and other pathogens has been shown [42 , 26] , reinforcing that CXCR3 is essential to control infection by intracellular pathogens . CXCR3 is highly expressed in murine Th-1 CD4+ and CD8+ T-cells [43] , and the CXC-chemokine receptor CXCR3 plays a role in the regulation of leukocyte migration into inflammatory sites in mice and human [44] . Here , we have shown that CXC-chemokine receptor CXCR3 is more highly expressed on TEWETGQI-specific CD8+ cells of T . cruzi challenged mice than in ASP2 immunized animals; however , the expression on effector CD4+ T-cells was similar between the groups . In addition , we found increased levels of ligands CXCL9 and CXCL10 in the serum of those mice . Although specific CD8+ T cells infected expressed higher levels of CXCR3 on cell surface , CD8+ T-cells from the immunized group had a higher migration index compared to specific CD8+ T cells generated only by infection , after the ex vivo stimulation with CXCL9 and CXCL10 , but not with CXCL11 . These three ligands are all induced by IFN-γ [45] , but are differently expressed [46] and that may explain the differential role played by the CXC-chemokine receptor CXCR3 in several diseases [47] . Concerning the in vitro high migration capacity of CD8+ T cells of the immunized group , CXCR3 low expression in those cells may be explained because specific CD8+CXCR3+ cells from the spleen migrated to the non-lymphoid peripheral tissue , for example , the heart tissue . We observed a higher number of specific CD8+ T cells in the immunized group compared to the infected group . Another explanation might be that CXCR3 receptor from the immunized group is more responsive to CXCR3 ligands and the receptor is activated and internalized [48] , which decreases the number of cells positive for CXCR3 receptor . Additionally , we evaluated the effector function of the TEWETGQI-specific CD8+ T-cells after anti-CXCR3 antibody administration . We observed that these parasite-specific CD8+ T-cells present in the spleen can release cytokines in the ELISpot assay , in which we observed a decrease in the number of IFN-γ producing cells . However , in ICS assay , the percentage of IFN-γ CD8+ producing cells was similar in the ASP2 immunized group , indicating that the decrease was due to a technique variation . In addition , TEWETGQI-specific CD8+ T-cells after anti-CXCR3 antibody administration showed proliferative response . Similar results were observed during infection by virus and during anti-CXCR3 treatment [42 , 49–50] . However , during autoimmune diseases and infection by Leishmania major , CXCR3 is important for cytokine production and proliferation by CD8+ T-cells [51–53] . In addition to cytokine production , we evaluated the cytotoxicity of these TEWETGQI-specific CD8+ T-cells and during infection these cells show high cytotoxicity [32]; therefore , we decided to perform the analyzes in parasite-specific CD8+ T-cells generated only by immunization because during the infection the cells are very cytotoxic and it is difficult observed differences among the groups [3] . Our results showed that the treatment with anti-CXCR3 also decreased cytotoxicity of TEWETGQI-specific CD8+ T-cells in ASP2 immunized mice , corroborating the results observed by Thapa and colleagues [54] . Unlike this study , however , we did not observe a decrease in granzyme B production by these TEWETGQI-specific CD8+ T-cells . The decreased cytotoxicity activity may be explained because the CXC chemokine receptor CXCR3 is important to the contact between infected target cells and specific CD8+ T-cells [50] . The role of CXCR3 in the differentiation of CD8+ T-cells in memory subtypes has been shown in other studies [28] . The receptor CXCR3 is important for the intranodal positioning of T-cells and Th cell polarization [55] and facilitates CD8+ T-cell differentiation into short-lived effector cells and memory generation [27] . The TEWETGQI-specific CD8+ T-cells generated by heterologous immunization and challenge by T . cruzi infection are effector cells characterized by the expression of these molecules and levels: CD11ahigh , CD62Llow , CD44high and CD127low and KLRG1high [12] . The treatment with anti-CXCR3 did not alter the effector phenotype of the TEWETGQI-specific CD8+ T-cells but increased the levels of CD95 expression on cell surface of those cells . Previously , our group showed that TEWETGQI-specific CD8+ T-cells generated by immunization had lower CD95 expression when compared to cells generated after infection [37] . As CD95 is a cell death-promoting molecule [56] , we analyzed the apoptosis in TEWETGQI-specific CD8+ T-cells and we observed an increase in annexin V expression , suggesting that anti-CXCR3 treatment increased the proapoptotic phenotype of TEWETGQI-specific CD8+ T-cells . The protection of cell death during immunization with ASP2 ensures that TEWETGQI-specific CD8+ T-cells trigger the effector function and control parasites replication . We have also demonstrated that CXCR3 molecule expression protected TEWETGQI-specific CD8+ T-cells from cell death . CXCR3 receptor is also essential for CD8+ T-cell migration after immunization and , particularly , for parasite-specific CD8+ T-cell migration into the heart tissue after immunization and challenge with T . cruzi infection . Indeed , after anti-CXCR3 treatment , we observed a reduced number of CD8+ T-cells infiltrating the heart tissue . Consistently with the reduced number of CD8+ T-cells in the heart tissue of anti-CXCR3-treated mice , we found a significant increase in the number of amastigote nests and parasite load in the heart tissue of these mice . Furthermore , we demonstrated that several chemokines genes in infected mice hearts were highly expressed , indicating a high inflammation/migration to heart tissue . The high expression of CCL5/RANTES , CCL3/MIP-1a , CCL4/MIP-1b , CCL2/MCP-1 and the CXC chemokines CXCL10/IP-10 and CXCL9/MIG mRNA also have been detected in the heart tissue of acutely and chronically T . cruzi-infected mice [29] . The high expression of chemokines genes in the infected group did not guarantee a high migration of specific CD8+ T cells . Studies have shown that a pro-inflammatory environment in the heart tissue is sufficient to activate autoreactive T cells and cause cardiomyopathy during Chagas disease [57] . Immunization with ASP2 prevents the expression of most of the analyzed chemokines; however , expression of CXCR3 ligands CXCL9 and CXCL10 was observed in two animals . Also , both chemokines were detected in the mice’s serum , suggesting that parasite-specific CD8+ T-cells expressing CXCR3 can be attracted to the heart tissue . In fact , the number of TEWETGQI-specific CD8+ T-cells in the ASP2 immunized heart tissue is higher than in the infected group . In addition , in the ASP2 immunized group , the number of amastigote nests and parasite burden is lower than in the infected mice group , suggesting that the higher number of TEWETGQI-specific CD8+ T cells participate in the infection control . After anti-CXCR3 administration , we observed a high expression of CXCR3 ligands , which may be explained for the competition between anti-CXCR3 and the ligands to CXCR3 ligation , resulting in CXCR3 ligands accumulation . The importance of CXCR3 in T cells migration has been demonstrated in several studies and shown that anti-CXCR3 treatment is effective at preventing acute and chronic heart rejection after transplantation [58] . Although previous studies have shown CXCR3 role in the migration of effector lymphocytes involved in the control of viral , protozoan and bacterial infection [49–60] , our study reveals for the first time that CXCR3 receptor is pivotal for the migration and positioning of pathogen-specific CD8+ T-cells directly involved in the clearance of T . cruzi after the prime-boost immunization and challenge . Therefore , our data support that prime-boost vaccination protocol was effective in the selective CXC-chemokine-mediated CXCR3-driven activation , migration and positioning in a target tissue that is drastically affected during the chronic phase of T . cruzi infection . Moreover , our work places CXCR3 as a powerful molecule able to address specific cell to target tissue of infection and , therefore , to be included as a key requirement for design of vaccines against intracellular pathogens . The potential use of chemokines receptor as an adjuvant in vaccines strategies has been demonstrated in the dengue model [61] . In Chagas disease , CXCR3 receptor may be used to guide specific CD8+ T cells to the heart and prevent cell death . Consequently , it might control parasites replication . In general , we have demonstrated that anti-CXCR3 treatment increased the susceptibility of immunized A/Sn mice , which died very quickly due to infection . Moreover , specific CD8+ T-cells decreased the migration into the heart tissue , and those cells displayed a pro-apoptotic profile . Taken together , those results show that CXCR3 has a critical role in the protective immune response and understanding its migratory role might support the development of vaccines against intracellular parasites such as Trypanosoma cruzi . | Chemokine receptors and cell adhesion molecules are essential for T lymphocytes migration into infected tissues . Previously , our group demonstrated that CXCR3 receptor was highly expressed on specific CD8+ T-cells surface after immunization and infection by T . cruzi . Also , recirculation of specific CD8+ T-cells was more important than proliferation to control the infection by T cruzi . As CD8+ T lymphocytes are responsible for controlling T . cruzi infection by releasing IFN-γ or by direct cytotoxicity against infected target cells , our aim was to analyze the role of the chemokine receptor CXCR3 in the migration of specific CD8+ T-cells towards infected tissues . Our results revealed that intervention on CXCR3 by administration of a blocking anti-CXCR3 antibody decreased CD8+ T-cell migration , hampering the access of parasite-specific effector cell into the heart tissue of mice infected by T . cruzi . Therefore , to induce the appropriate migration footmarks is crucial for drive the pathogen-specific effector to sites of infection and , therefore , to clarify this requirement is a crucial strategy for vaccine development . | [
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"cor... | 2019 | CXCR3 chemokine receptor guides Trypanosoma cruzi-specific T-cells triggered by DNA/adenovirus ASP2 vaccine to heart tissue after challenge |
In many biological systems , the interactions that describe the coupling between different units in a genetic network are nonlinear and stochastic . We study the interplay between stochasticity and nonlinearity using the responses of Chinese hamster ovary ( CHO ) mammalian cells to different temperature shocks . The experimental data show that the mean value response of a cell population can be described by a mathematical expression ( empirical law ) which is valid for a large range of heat shock conditions . A nonlinear stochastic theoretical model was developed that explains the empirical law for the mean response . Moreover , the theoretical model predicts a specific biological probability distribution of responses for a cell population . The prediction was experimentally confirmed by measurements at the single-cell level . The computational approach can be used to study other nonlinear stochastic biological phenomena .
Complex biological systems are built out of a huge number of components . These components are diverse: DNA sequence elements , mRNA , transcription factors , etc . The concentration of each component changes over time . One way to understand the functions of a complex biological system is to construct a quantitative model of the interactions present in the system . These interactions are usually nonlinear in terms of the concentrations of the components that participate in the interaction process . For example , the concentration of a dimer is proportional to the product of the concentrations of the molecules that dimerise . Besides being nonlinear , the interactions are also stochastic . The production process of a molecule is not deterministic , and it is governed by a probability rate of production . In what follows , a nonlinear stochastic model for the response to heat shocks in CHO mammalian cells will be developed . Heat stress is just one example of the many ways a molecular system can be perturbed . From a general perspective , the structure of a molecular system is uncovered by imposing different perturbations ( input signals ) on the system under study , and then the responses of the system ( output signals ) are measured . From the experimental collection of pairs of input–output signals , laws that describe the system can be uncovered . This is the fundamental idea in Systems and Synthetic Biology [1–5] and has long proved to be successful in the field of electronics . The input signals are applied through the use of signal generators [6–8] . An input signal that is easy to manipulate is a heat pulse , the parameters to change being the pulse temperature and its duration . Members of the stress protein family such as the heat shock protein 70 ( HSP70 ) are highly responsive to temperature variations . This protein is a molecular chaperone and is a critical component of a complex genetic network that enables the organism to respond to deleterious effects of stress [9–11] . Since Hsp70 is thus an important regulator in a complex system , our goal was to find if it is possible to develop a mathematical model of the regulation of its expression in mammalian cells exposed to heat shock . Our specific objectives were 1 ) determine an equation representing the average expression of Hsp70 over time in a cell population after an initial heat shock , 2 ) determine how the physical parameters of heat shock ( temperature and duration ) influence the parameters of this equation , and 3 ) determine the mathematical model that describes the expression of Hsp70 at the single-cell level . We first describe the process of inferring the mathematical model from the experimental data . Then a mathematical study of the model will follow .
To acquire the experimental data , we elected to use a system using a reporter gene where the expression of the green fluorescent protein ( GFP ) is under the control of the promoter region of the mouse Hsp70 gene . The GFP reporter proved useful for quantitative analysis [12] and was used before in connection with Hsp70 in different biological systems [13–17] . The Hsp70-GFP fusion gene was integrated into a plasmid and transfected in Chinese hamster ovary ( CHO ) cells . Stable transfectants were selected for their low level of basal expression of GFP and their capacity to upregulate GFP effectively and homogenously after exposure to heat shock . Flow cytometry was used to make precise quantitative measurements of the fluorescence of a large cell population . Since the quality of the experimental data was critical to the feasibility of the mathematical analysis , steps were taken to minimize sample-to-sample and experiment-to-experiment variability and to maintain the experimental noise to a minimum . To that effect , temperature and time were tightly controlled for heat shocks , the cells were treated as a batch in a single tube for each condition ( combination of temperature and time ) , and aliquots were taken at each time point . All samples were fixed for at least 24 h before analysis by flow cytometry so that changes of fluorescence due to fixation would not be a factor , and all the samples from the same experiment were analyzed at the same time . Flow cytometry was chosen for analysis because it allows a very accurate quantitative measurement of the fluorescence of a large number of events , independently of the actual size of the sample . Within the same experiment and between experiments , the same instruments settings were used for the flow cytometer , and at least 1 × 104 cells were analyzed per sample . Detailed protocols and experimental conditions are available in the Materials and Methods section . First , we will follow a description of the time course of the mean response to a heat shock . At elevated temperatures ( 39 °C to 47 °C ) , the heat shock promoter HSP70 is active and GFP starts to be synthesized . The input signals were chosen in the form of a pulse at a temperature ( T ) and duration in time ( D ) ( Figure 1A ) . In the first experiment , the dynamic response of GFP after a heat pulse at 42 °C for 30 min was monitored by taking samples each 30 min for 18 h . Before and immediately after the heat shock , the GFP intensity remains at approximately the same level; this phenomenon was observed in all subsequent experiments . The fold induction of GFP with respect to a reference ( GFP0 ) was then determined: The reference is the first measured sample away from the end of the heat shock ( 30 min after the shock in Figure 1A ) . Our finding is that the logarithm of the fold induction of GFP follows an exponential saturation trajectory ( Figure 1B ) , with tight confidence bounds for the estimated parameters and tight prediction bounds for nonsimultaneous observations . The tight prediction bounds appear even when almost half of the data is not used during fitting ( Figure 1B ) . The time t is measured relative to the reference time t0 . The initial fold induction at t = 0 ( or equivalent t0 after the end of heat shock ) is 1 . This value of 1 for the initial fold induction is consistent with the entire time evolution if a fit with the expression will give a value for parameter very close to the value for parameter a . Theoretically , must be equal with a to have a fold induction of 1 at t = 0 . The result of the fit ( Figure 1B ) shows this consistency . From now on we will take . The empirical law for the response of the cells to the heat pulse can be thus cast into the form: The same law appeared in repeated measurements of pulses at 42 °C for 30 min duration ( unpublished data ) . Parameter b describes the quickness of the response . As b increases , the saturation value of the response is reached in less time . Parameter a specifies the saturation value of the response . The plateau reached by the fold induction is ea and thus grows exponentially with parameter a . These findings suggest that the same law is valid for other heat shock pulses , parameters a and b being dependent on the heat pulse height T and its duration D ( Figure 1C ) . To find the range of validity for the empirical law , measurements were taken for the responses to heat shocks at various heat pulse parameters T and D in a series of three experiments that partially overlapped Figure 2 . The law was again present in all responses for temperatures between 41 . 5 °C and 42 . 5 °C , ( examples selected in Figure 3A , fit 3 , 4 ) . For lower temperature ( 39 . 5 °C to 40 . 5 °C ) , the law was valid , but with poor 95% confidence intervals for estimated parameters a and b , as in Figure 3A , fit 1 , 2 ( the activity of the Hsp70 promoter was low ) . At high temperatures or long durations ( Figure 3B ) , the double exponential law still explains the main characteristic of the stress response and is valid after a few hours from the end of the heat shock . In the following , a theoretical model will be developed to explain the experimentally discovered law . The exponential accumulation of the GFP shows that the derivative with respect to time of the mean GFP is proportional with itself: There must be thus a molecular process , described by the exponential term abe−bt , which controls the heat shock response . This theoretical suggestion is confirmed by previous studies of the heat shock system which revealed that the accumulation and subsequent degradation of the heat shock transcription factor 1 ( HSF1 ) regulates Hsp70 [18–22] . Experimental results [18] show that HSF1 activation is characterized by a rapid and transient increase in hsp70 transcription which parallels the kinetics of HSF1–DNA binding and inducible phosphorylation . This rapid increase in HSF1–DNA binding activity reaches a maximal level and thereafter attenuates to a low level . This rapid increase in activity followed by attenuation will form the starting point for our theoretical model . An activation–accumulation two-component model will be developed as a minimal theoretical description of the empirical law . The “activation” variable ( X1 ) represents the first phase of the heat shock response and includes components like HSF1–DNA binding activity . X1 will increase during the duration of the heat shock and then , after the shock , will decrease with a lifetime proportional to parameter b ( Figure 4 ) . The “accumulation” variable ( X2 ) includes the products of transcription and translation . This second variable , at low levels before the shock , will gain momentum after the shock . To connect the model with the experimental data , the GFP will be considered to be proportional with X2 . The speed of accumulation of X2 , that is , dX2/dt , will be proportional to the product X1X2 . Immediately after the shock , X1 has a big value ( the activation is high ) , and thus the speed of X2 is high ( the accumulation is in full thrust ) . This will trigger an initial fast accumulation of GFP , which is proportional with X2 . Later on , the activity X1 disappears , nullifying the product X1X2 and thus the speed of X2 . The process is then terminated ( the accumulation stops ) ( Figure 4 ) . The empirical law follows directly as a solution of the activation–accumulation system of equations: with b and c as some constants . Indeed , given the initial conditions X1 ( 0 ) and X2 ( 0 ) at a zero time reference t0 = 0 , the solution to this system of differential equations is With the notation the empirical law follows from X2 ( t ) : The theoretical model contains two parameters: b and c . Parameter b is directly accessible to experimental measurements , whereas parameter c is not; however , the product cX1 ( 0 ) which equals the product of a and b can be measured . It is interesting to notice that the above time evolution can be re-expressed as a conservation law which is independent of any reference time . For any two time points t1 and t2 , the following holds At this point , there is no more information in the activation–accumulation description above than is in the empirical law . However , one can search for more information hidden in the above two-component description by turning attention to the full data available , not only to the mean value of GFP . For each sampled time , the full data available consists of measured GFP levels for at least 10 , 000 single cells . These 10 , 000 single-cell measurements are typically distributed as in Figure 5 . There is a long tail at high values of GFP . This biological variation in response to the stress is explained by turning the deterministic two-component system into a stochastic two-component system [6 , 7] . The stochastic description must be completely enforced by ideas behind the deterministic two-component system . The stochastic model is simple . X1 is the mean value of a stochastic activation variable which will be denoted by q1 , X1 = 〈q1〉 . After the heat shock , q1 will decrease with a probabilistic transition rate bq1 . The activation–accumulation stochastic model is based on the same relation as before ( compare bq1 with bX1 ) , but now it describes the probabilistic transition rate and not a deterministic speed of attenuation . By the same token , X2 is the mean value of q2 and its probabilistic accumulation rate is cq1q2 . One notices that the transition probability rate cq1q2 is nonlinear in the variables q1 and q2 . The stochastic two-component description is thus a mirror image of the deterministic two-component system . However , the probabilistic system is more powerful as it predicts that the histograms of GFP ( proportional with q2 ) obtained from the flow cytometry measurements follow a Gamma distribution with GFP ≡ x . This prediction is confirmed experimentally ( Figure 5 ) . The fact that the levels of proteins in gene networks tend to follow a Gamma distribution , which is a continuum version of a discrete negative-binomial distribution , was presented in [23 , 24] . The papers [23 , 24] develop theoretical models describing the steady-state distribution of protein concentration in live cells . Our interest lies in the non–steady-state behavior of these distributions . Namely , the aim is to find the time evolution of the parameters that characterize these distributions . The entire time evolution of the distributions is presented in Figure 6 . The distributions become wider as time passes . The experimental data reveal that parameter ρ remains constant in time and only θ changes . These experimental findings are theoretically explained in detail in the section Analysis of the Theoretical Model . What follows summarizes the theoretical conclusions that are useful in understanding the experimental results of Figures 5 and 6 . The probability distribution for the discrete molecule number q2 , predicted by the stochastic activation–accumulation model , is the negative-binomial distribution . This distribution appeared in earlier theoretical studies of genetic networks [23 , 24] and in physics [25 , 26] . The GFP intensity is proportional with q2 and appears in measurements as a decimal number and not as a pure integer . Thus , to describe the probability distribution of the GFP intensity , a continuous version of the discrete negative-binomial distribution is necessary . This continuous version is the Gamma distribution observed experimentally in Figures 5 and 6 . The physical interpretation of parameter ρ will now be discussed . At initial time t0 , immediately after the heat shock , there will be at least one cell from the entire cell population which contains the minimum number of molecules q2 . Denote this number by N0 . As the time passes , the molecule number q2 will grow , following the described stochastic process . However , there is a nonzero probability , though extremely small , that the process of accumulation in one cell does not start even after 24 h . This can happen in one of those cells that contain the minimum number of molecules q2 at the initial time t0 . Thus , at any later time t > t0 , the lowest possible number of molecules q2 in a cell is N0 as it was at the initial time t0 . It can be shown ( see the section Analysis of the Theoretical Model ) that ρ = N0 . This explains the time independence of the experimental values of ρ; it also gives a physical meaning to ρ as being proportional to the minimum number of GFP molecules in a cell . Parameter θ contains the time evolution of the stochastic accumulation of the GFP molecules . This evolution can be again expressed as a time conservation property valid between any two time points t1 and t2 . The above relation Equation 10 contains parameters a and b and can be used to check the consistency of the model . Using the data from Figure 6 , it follows that a = 3 . 159 with a 95% confidence interval ( 3 . 074 , 3 . 244 ) and b = 0 . 2572 with a 95% confidence interval ( 0 . 2358 , 0 . 2785 ) . From the mean value for GFP , it results that a = 2 . 423 with a 95% confidence interval ( 2 . 351 , 2 . 496 ) and b = 0 . 2579 with a 95% confidence interval ( 0 . 2344 , 0 . 2814 ) . Parameter a is sensitive to the estimation procedure , a phenomenon connected with the fact that parameter ρ is not perfectly constant but decreases a bit with time . The mean value of the Gamma distribution is ρθ . For a perfectly constant ρ , the estimated value for a would be the same using either the θ values or the ρθ data . Contrary to parameter a , parameter b is independent of the way it is estimated , and the estimation is highly reliable . To further check the reality of the Gamma distribution for heat shock response , a comparison of the Gamma fit with the lognormal fit is presented in Figure 7 . The lognormal was chosen because it can be viewed as a result of many random multiplicative biological processes . A loglikelihood ratio less than 1 favors the Gamma distribution against the lognormal . Moreover , at 37 °C the Gamma distribution is not a good fit ( loglikelihood ratio is bigger than 1 ) as it should be because the promoter is not active . The law is useful in making predictions for the fold induction to many other heat shock pulses . For a heat pulse of a given temperature and duration , parameters a and b can be read out from Figure 8 . The constant level contours were inferred from the experimental data . The level patterns differ; parameter a increases monotonically with the temperature and duration of the heat pulse ( Figure 8A ) , while the levels of parameter b form an unstable saddle shape pattern ( Figure 8B ) . The conclusion of this section will be rephrased using a control theory perspective . The end result of this paper is an input–output relation for the response of the CHO cells to heat shocks , together with a theoretical model that explains it . The input signals are pulses of a precise time duration D and temperature height T . The output measured signals are the GFP intensity . The input–output relation is given by the time-dependent probability density for GFP intensity with Parameters a and b are functions of the input signal , that is a = a ( T , D ) and b = b ( T , D ) . The dependence of parameters a and b on temperature T and duration D is given by the contour plots of Figure 8 . The functional forms of a = a ( T , D ) and b = b ( T , D ) is a consequence of biological phenomena that take place during the heat shock . We do not have a theoretical model for the phenomena that take place during the heat shock . To explain the time evolution of the output variable ( GFP intensity ) , we developed a coarse-grained model for the heat shock response . This coarse-grained model is valid for the biological phenomena that takes place after the end of the heat shock . The model predicts the existence of a molecular factor that controls the GFP accumulation ( variable q1 ) . We associated this theoretical factor with the heat shock factor HSF1-DNA binding activity . The theoretical model is based on an activation variable q1 and an accumulation variable q2 . The state of this two-component model is thus ( q1 , q2 ) , and any pair of positive integer numbers can be a possible state . The main goal is to find the mean value and standard deviation for the activation and accumulation variable , respectively . These quantities will be obtained from the equation for the probability P ( q1 , q2 , t ) that the system is in the state ( q1 , q2 ) at the time t . The equation for P ( q1 , q2 , t ) depends on the multitude of transitions which can change a state ( q1 , q2 ) . The experimental results suggest that two possible transitions change the state ( q1 , q2 ) . One transition represents the decreasing of the activation variable from q1 to q1 − 1 . On the state ( q1 , q2 ) , this attenuation appears as ( q1 , q2 ) → ( q1 − 1 , q2 ) , with an unaffected accumulation variable q2 . The second transition will describe the accumulation of the accumulation variable from q2 to q2 + 1 . On the state ( q1 , q2 ) , this accumulation appears as ( q1 , q2 ) → ( q1 , q2 + 1 ) , with the activation variable q1 now being unaffected . A notation for the transition direction can be introduced: ɛ−1 = ( −1 , 0 ) . The degradation transition can thus be written as ( q1 , q2 ) → ( q1 , q2 ) + ɛ−1 . The negative sign in the index −1 is just a reminder of the fact that the transition reduces the number of molecules; the 1 in the subscript tells us that the transition is on the first variable . Likewise , the accumulation transition can be expressed as ( q1 , q2 ) → ( q1 , q2 ) + ɛ2 and ɛ2 = ( 0 , 1 ) . The index 2 is positive ( accumulation ) and is associated with the second component . To find the probability P ( q1 , q2 , t ) , the transition probabilities per unit time are needed . The experiment suggests we use as the transition probability rate for the attenuation of the activation component , and as the transition probability rate for the increasing of the accumulation component . The stochastic model can be represented with the help of a molecular diagram [7] ( Figure 9 ) . The components q1 and q2 are represented by ovals and the transitions by squares . The lines that start from the center of a transition square represent the sign of that transition and point to the component on which the transition acts . The transition ɛ−1 is negative , so the line ends in a bar and acts on q1 . The transition ɛ2 is positive and so the line ends with an arrow; it acts on q2 . The lines that stop on the edges of the transition squares represent the transition probability rates . The line that starts from q1 and ends on ɛ−1 represents the transition probability rate bq1 . In other words , the transition ɛ−1 is controlled by q1 . The lines that start on q1 and q2 and merge together to end on ɛ2 represent the product cq1q2 , ( the merging point represents the mathematical operation of taking the product ) . At this point , the theoretical model is fixed and what comes next is a sequence of computations to extract information out of it . This information will be compared with the experimental results . Given the transition rates , the equation for the probability P ( q1 , q2 , t ) is given by the following equation [7 , 25] . The above equation for P ( q1 , q2 , t ) is not easy to solve . We will use the method outlined in [6 , 7] and work with the function X ( z1 , z2 , t ) defined by The equation for the function X ( z1 , z2 , t ) is a consequence of the equation for P ( q1 , q2 , t ) : The goal is to find the time variation of the mean value and standard deviation for the activation and accumulation variable: 〈q1〉 , 〈q2〉 , , , 〈q1 , q2〉 , etc . Here 〈〉 is a notation for the mean value with respect to the probability distribution P ( q1 , q2 , t ) . From X ( z1 , z2 , t ) , the above mean values can be obtained by taking partial derivatives of X ( z1 , z2 , t ) at z1 =1 , z2 = 1 . These partial derivatives are actually the factorial cumulants of the probability distribution P ( q1 , q2 , t ) . In what follows , the sign =: means that the right side is introduced as a notation . The equations for X1 ( t ) , X2 ( t ) , X11 ( t ) , and higher factorial cumulants result from the equation for X ( z1 , z2 , t ) : The activation–accumulation model being nonlinear , the equations for the factorial cumulants cannot be reduced to a finite system of equations , unless some approximation technique is employed . All third-order cumulants were discarded to obtain the above system of equations . In [7] it was shown , using simulations , that the effect of discarding higher-order factorial cumulants is negligible . The finite system thus obtained contains X1 , X2 , X12 , X11 , and X22 as variables . Although it can be solved for X1 and X2 , we found that the influence of the correlation term X12 is small and cannot be experimentally detected in the GFP response . Taken thus , X12 = 0 , and the system of equations is reduced to: The solution to X22 from the four-equation system is with k a constant determined from the initial value X2 ( t0 ) at some time t0 after the heat shock . The solution can be restated in terms of the variance , Var , of the variable q2 . The transformation from the factorial cumulants to Var is And , thus , remembering that the mean value of q2 is X22 , it follows that Such a relation between Var and Mean is satisfied by the negative-binomial distribution , a point to which we will return later . Employing the general procedure , we continue to solve the system of equations for X1 , X2 , X11 , and X22 . However , for the case of negligible X12 , the stochastic process is decoupled in two stochastic processes , each of which is exactly solvable . It is thus useful to solve directly for the probability distribution of q2 at this point . The transition probability rate for the first stochastic process ( for the activation component q1 ) is the same as before: . For the second one , it changes from to ( the coupling between q1 and q2 is through the mean value of q1 now ) . This simplifies the problem of finding the distribution of q2 . Denote the mean value of cq1 with g ( t ) , which acts actually like a signal generator on q2 [6 , 7] . The time variation of g ( t ) from the first equation in Equation 20 is so the stochastic process for q2 now has an accumulation transition rate The origin of time , t = 0 , is taken at the end of the heat shock , so X1 ( 0 ) represents the mean value of the activation variable at the end of the heat shock . The probability P ( q2 , t ) to have q2 number of molecules at time t can be found from the master equation for this process To find the solution , an initial condition P ( q2 , t0 ) must be specified . The time t = t0 is some time taken after the heat shock pulse ( t0 > 0 ) , when the effects of the shock start to be detectable; it can be , for example , 30 min or 2 h after the pulse . The probability distribution P ( q2 , t0 ) can be obtained , in principle , from the experimental values of GFP since GFP = fq2 . There is an obstacle though: the proportionality factor f is unknown . The factor f converts the number of molecules q2 into the laser intensity which is the output of the flow cytometry machine . The conversion from the molecule numbers to the laser intensity can be more complicated than the proportionality relation GFP = fq2 . For example , a background B can change the relation into: GFP = fq2 + B . We measured the GFP in regular CHO cells ( no HFP70-GFP construct ) and found that the background B is about 50 times less than the minimum intensity of GFP in the transfected CHO cells . The settings of the flow cytometry instrument were set in a linear response range , and thus we will use the scaling relation GFP = fq2 to connect the flow cytometry readings with the number of molecules . To conclude this initial condition discussion , in a perfect setting we would know the scaling factor f and then get P ( q2 , t0 ) from the measured data . Because the scaling factor f is unknown , the problem will be solved in two steps . The first step in choosing P ( q2 , t0 ) is based on a simple assumption: all cells have the same number of molecules q2 = N at the time t = t0 . That is P ( q2 , t0 ) = δ ( q2 , N ) where δ is the Kronecker delta function . The solution to Equation 26 with this initial condition is Here q2 can take only values greater than N , q2 = N , N + 1 , ··· . This distribution appeared in the study of cosmic rays [26] , and in the context of protein production was presented in [23] . In terms of the variable x = q2 − N , it is known as the negative-binomial distribution , with interpretations that are not connected with the present problem . The number N also represents the minimum possible number of molecules q2 in any cell . This physical interpretation of N will be helpful in what follows . The variable p ( t ) in the distribution is time-dependent , since the signal generator g ( t ) acts on q2: The mean and variance for q2 are from which follows Equation 23 Although the assumption that all the cells contain the same number of molecules at t = t0 is unreal , it produces a valuable outcome . The negative-binomial distribution implies a Gamma distribution for the GFP intensity ( through the scaling relation GFP = fq2 ) , a fact to be discussed shortly . Because the Gamma distribution is a good fit for the experimental data , we conclude that the negative-binomial is the correct solution for the distribution of the accumulation variable q2 . The second step in choosing the probability distribution P ( q2 , t0 ) will be guided by the experimental results . The experimental results show that the biological system passes through a chain of events from an unknown distribution of GFP before the heat shock , to a Gamma distribution at some time t0 after the heat shock ( 2 h , for example ) . Also , the experiment shows that the distribution of GFP is Gamma at later times t > t0 . In other words , the distribution of q2 becomes a negative-binomial at some time t0 after the heat shock and then afterward remains negative-binomial . These experimental observations are mathematically explained by showing that a solution to Equation 26 with a negative-binomial distribution at t0 remains negative-binomial for all later times t > t0 . Indeed , the solution to Equation 26 with a negative-binomial initial condition is which is a negative-binomial at all times t > t0 . The number N0 is the minimum number of molecules q2 to be found in a cell at t0 and also at all later times t > t0 ( because q2 cannot decrease ) . The time evolution of the mean 〈q2〉 is and represents , using Equation 24 , the same empirical law ( Equation 8 ) as before . To conclude , the dynamical system is such that once the cells enter into a negative-binomial distribution at some time after the heat shock , the distribution remains negative-binomial at later times . As the time passes , all the distributions will have the same parameter N0 but different parameters p ( t ) . To connect the theory with the experimental results , the probability distribution for the GFP intensity is needed . This distribution is the continuum limit of the distribution for q2 . It is a well-known fact that the continuum limit of a negative-binomial distribution is the Gamma distribution . This continuum limit is presented here in order to find parameters ρ and θ , which can be experimentally measured . The change from the integer variable q2 to the real variable fq2 is simple if advantage is taken of the fact that the common parameter N0 is a small number . Parameter N0 is less than any possible molecule number q2 present in the system after the time t0 , q2 ≫ N0 . Then , writing for simplicity p ( t ) as p , In the last step , we used the approximation 1 − y ≅ e−y for small values of y . To go from the discrete variable q2 to the continuous variable GFP , we write the above relation as an equation for the probability density with Δq2 = 1; then scale to GFP , ( GFP = f q2 ) . The probability density P℘ for GFP is then This is a Gamma distribution for GFP ≡ x with From Equation 24 and 28 , we get The mean value of the Gamma distribution is ρθ from which the empirical law Equation 8 follows .
The way the material is organized and presented in this paper is an outcome of a series of guiding principles imposed upon the project . These guiding principles were formulated to keep in balance the experimental data with both the mathematical and biological models . The guiding principles are: 1 ) start from experimental measurements and discover an empirical law from data using signal generators as input into the system; 2 ) build a simple mathematical model with as few parameters as possible to explain the empirical law; 3 ) check the mathematical model using additional experimental information; 4 ) use a general mathematical technique , likely to be applied to other experimental designs; 5 ) keep the biological model and the mathematical model to a level of complexity commensurate with the richness of the experimental data These guiding principles filtered out other possible presentation formats . For example , the fifth principle will prevent the development of a complex mathematical model built on a complex biological model , although many molecules involved in the heat shock response are known . One outcome of the strategy outlined above is the discovery of a new variable , q1 , brought about by a mathematical necessity from the empirical law . The behavior of this variable matches the behavior of the HSF1-DNA binding activity , experimentally described in [18] . In other words the empirical law predicts the existence of a heat shock factor , a molecule on which we did not take any measurements . This heat shock factor is well-known , but our point is that in other experimental settings a mathematical analysis of an empirical law can suggest the existence of an unknown molecule . In this respect , the aim of finding empirical laws from experimental data has biological significance . From a different perspective , an empirical law can be useful for calibration or classification purposes . For example , the heat shock responses can be classified using two parameters , a and b . Reproducibility of experiments can be checked by measuring parameter b which proved to be reproducible and reliable . Comparisons between different heat shock experiments can be done in terms of parameters a and b . At a deeper level , the double exponential law and the activation–accumulation model need to be extended by simultaneously measuring the GFP production and the HSF1 activity . Following a series of modelling and data acquisition , more and more molecules can be reliably added into a quantitative description of the heat shock response . Narrowing the discussion from general views to the specifics of this project , a natural question arises: why would cells evolve such a double exponential response ? We can only speculate and say that cells need a very fast response immediately after the shock . Moreover , cells cannot bear for a long time such a fast exponential accumulation , so this initial exponential growth must be stopped . A compromise between these two requirements is the double exponential law for the mean heat shock response . Such a law permits a fast response immediately after the stress , controlled by parameter a and a flexibility in the duration of the response , controlled by parameter b . Such a response is easily implemented by a heat shock factor with an exponentially diminishing activity . We believe that this type of response is present in many other biological systems and thus has a wide range of applicability . Another aspect to be noted is the time evolution of the stochastic process that describes the heat shock response . Not only the time evolution of the mean value can be mathematically modelled , but also the time evolution of the probability distribution . The time evolution of GFP distribution can be well-explained by a negative-binomial with a time-dependent parameter . This behavior is obtained by neglecting the statistical correlation between the activation and the accumulation variable in the stochastic activation–accumulation model . It will be interesting to reach a level of experimental accuracy at which the statistical correlation becomes detectable , and then measure the deviation of the probability distributions from the negative-binomial . From a mathematical point of view , we choose to work with the discrete master equation because it is simple to relate it to a biological model . The transition probability rates can be easily connected with biological phenomena at the molecular level . The ease of building the model is counterweighed by the difficulty of solving the discrete master equation . To overcome this difficulty , we employ the method outlined in [7] , which uses the factorial cumulants as time-dependent variables . The biological significance of the approach can be also expressed using a control theory perspective . The structure of an unknown physical system is uncovered by perturbing the system with a series of input signals . The response to these perturbations is measured as output signals . Then the mathematical relation between the input and the output signals constitutes a model for the system . As much as possible , this theoretical model must also incorporate the molecular components of the system . The activation–accumulation model belongs to the category of input–output models . It is possible that other biological systems can be described by other simple models . A classification of molecular networks can thus be devised using their input–output functional relation . Moreover , decomposing the biological system in subsystems , there is a hope that global properties of each subsystem can also be described by a coarse-grained model . In this way , a hierarchy of models can be built to explain more and more details of a complex system .
A 5 . 3-kilobase DNA containing promoter and 5′-untranslated region of the mouse hsp70 . 1gene was subcloned from a lambda phage clone carrying an hsp70 . 1 gene identified by genomic library screening ( Stratagene ) using a human hsp70 . 1 cDNA as a probe . A cDNA coding for the GFP with a polyA signal from SV40 large T antigen gene was engineered to fuse to the start codon ( ATG ) of the hsp70 . 1 gene . The chimera gene was inserted into a pSP72 vector containing a hygromycin resistance gene in order to select for stable transfectants . CHO-K1 cells ( ATCC ) were grown in MEM-alpha ( Cellgro ) containing penicillin , streptomycin , and amphotericin ( Cellgro ) and complemented with 10% FBS ( Gemini Bio-Products ) . Cells were transfected by lipofection using Lipofectamine ( Invitrogen ) as previously described . After 10 d of selection in hygromycin ( 500 μg/mL ) , single-cell clones were derived by limiting dilution . The screening was performed by epifluorescence ( Nikon TE2000E ) , and clones with a low basal fluorescence intensity were selected and amplified for additional testing by flow cytometry . One clone with a low basal expression of GFP and the capacity to effectively and homogenously upregulate the expression of GFP after being submitted to heat shock ( 42 °C , 30 min ) was selected to conduct all the subsequent experiments . The cells were detached with trypsin and allowed to recover in suspension in complete growth medium for 3 to 4 h at 1 × 106 cells/mL at 37 °C in a CO2 incubator . The cells were then aliquoted in 50 mL conical tubes , one for each experimental condition ( temperature and duration of heat shock ) . Up to five different temperatures were tested simultaneously , one water-bath being used for each temperature . The temperature of each water-bath was accurately monitored with a precision Hg thermometer ( accuracy ±0 . 1 °C ) . Then the cells were centrifuged , the medium was aspirated , and the heat was initiated by resuspending the cell pellet quickly at 5 × 105 cells/mL in a medium prewarmed at the temperature selected for the heat shock . The tube was then placed in the same water-bath for the remainder of the heat shock , after which the tube was placed in ice-cold water and agitated for the amount of time that had previously been determined to be necessary to bring the temperature back to 37 °C ( from 2 to 14 s ) . The tube containing the cells was then placed in a waterbath set at 37 °C . From that point on , samples were taken every 30 min or every 2 h for up to 26 h . In all experiments , a control where the cells were kept at 37 °C for the whole time was included . The exact duration of each heat shock was monitored with a stopwatch . This protocol allowed a very strict control over the amount of input applied to the cells . The cells were kept in suspension in the 50 mL tubes in a CO2 incubator at 37 °C for the rest of the experiment . At each time point , 1 mL of cell suspension was removed from each tube and placed in a 5 mL tube . The cells were centrifuged for 2 min at 300 g , the supernatant was aspirated , and the cell pellet was resuspended in 500 μL of fixation solution ( PBS containing 1% paraformaldehyde ) and kept at room temperature and in the dark until analysis . Since fixation can decrease the fluorescence intensity of GFP , the samples were analyzed at least 24 h after collection of the last time point , so that the duration of fixation would not introduce any artifact . The samples were analyzed by flow cytometry on an LSR II ( Becton-Dickinson ) equipped with a 488 nm solid state laser . The performance of the system was routinely checked with fluorescent beads ( 8-peak beads , Shero Rainbow , Spherotech ) , and the same instrument settings were used in all experiments , yielding almost identical fluorescence intensities every time for the cells kept at 37 °C . The cells were gated based on their forward scatter ( FSC ) and side scatter ( SSC ) , and the same gate was used for all the samples . The fluorescence of each cell was measured based on the area of the corresponding pulse . The data were analyzed with the Diva software ( Becton-Dickinson ) for the mean fluorescence . The flow cytometry binary FCS files were converted to an ASCII text format with FCSExtract utility ( Stowers Institute for Medical Research ) . The data were consequently analyzed with cftool and dfittool from MATLAB ( MathWorks ) . The time evolution of the mean GFP expressed with respect to a reference initial time t0 = 0 is The above time evolution can be reexpressed as a conservation law which is independent of any reference time . For any two time points t1 and t2 we have Taking thus a time reference t0 we get The form Equation 40 was used to estimate parameters a and b for medium and low heat shocks . For strong shocks we need to modify the estimation procedure . The reason for this modification is explained below . As the promoter is activated by increasing temperature pulses , 41 . 5 °C to 43 . 5 °C , the Gamma distribution becomes a better description of the biological variation ( Figure 7 ) . However , for strong shocks , when the temperature approaches 44 . 5 °C and the duration of the pulse is high ( 30 min ) , the empirical law changes ( Figures 7 and 3B ) . In the first hours after the shock , the response for a shock at 44 . 5 °C for 30 min is slower in comparison with a shock at 44 . 5 °C for 15 min . To account for this initial slow response , the experimental data for strong shocks call for a modification to the empirical law , valid at low and moderate shocks . For strong shocks , the modified empirical law that fit well the experimental mean response value is , where h ( t ) = 1 – ξ + ξe−ηt . A few hours after the heat shock , when the effect of the exponential e−ηt is negligible and the slow response ended , the cell responds again with the same pattern found for low and moderate shocks . The response at strong shocks can also be explained with the help of the activation–accumulation two-component model , by the following scenario . At the beginning of the heat shock , the activation component X1 will start to accumulate irrespective of how strong the heat shock will be . A cell does not know at the beginning of the heat shock about the duration of the shock . For a high temperature , if the duration of the shock is too long , after an initial accumulation , the activation component X1 will drop to low values . At the end of a strong shock , the activation component X1 will thus have low values . This is contrary to the case of moderate shocks , when at the end of the shock X1 has high values ( Figure 4 ) . This effect was observed experimentally in HeLa cells exposed to a 42 °C heat shock for 4 h [18] . The HSF1-DNA binding activity reaches its maximal level after 60 min and then attenuates to low levels at the end of the heat shock [18] . For strong shocks then , the activity X1 will accumulate again after the shock . Because X1 accumulates after the end of a strong shock , the speed of X1 is no longer described by d ( X1 ) /dt = −bX1 in this time interval . Then , a few hours after the shock , it reaches a maximum value , from which it will decrease in the subsequent hours following d ( X1 ) /dt = −bX1 . The accumulation of X1 after the shock is responsible for the slow response in the first hours . The decrease of X1 , which follows , imposes a response similar with the one observed at low and moderate shocks . The mathematical model for strong shocks during the time period when X1 decreases ( 5–6 h after the shock ) is the same with the model for moderate shocks , d ( X1 ) /dt = −bX1 and d ( X2 ) /dt = cX1 X2 . . After the slow response ends , the empirical law again explains the GFP trend . In view of the above discussion , for strong shocks the mean GFP is given by a modification of Equation 40: Similar to Equation 42 , to estimate parameters a , b , ξ , η for strong shocks , we used | The structure of an unknown biological system is uncovered by experimentally perturbing the system with a series of input signals . The response to these perturbations is measured as output signals . Then , the mathematical relation between the input and the output signals constitutes a model for the system . As a result , a classification of biological molecular networks can be devised using their input–output functional relation . This article studies the input–output functional form for the response to heat shocks in mammalian cells . The Chinese hamster ovary ( CHO ) mammalian cells were perturbed with a series of heat pulses of precise duration and temperature . The experimental data , taken at the single-cell level , revealed a simple and precise mathematical law for the time evolution of the heat shock response . Parameters of the mathematical law can be experimentally measured and can be used by heat shock biologists to classify the heat shock response in different experimental conditions . Since the response to heat shock is the outcome of a transcriptional factor control , it is highly probable that the empirical law is valid for other biological systems . The mathematical model explains not only the mean value of the response but also the time evolution of its probability distribution in a cell population . | [
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] | [
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] | 2007 | Heat Shock Response in CHO Mammalian Cells Is Controlled by a Nonlinear Stochastic Process |
Retinoblastoma ( Rb ) , the most common pediatric intraocular neoplasm , results from inactivation of both alleles of the RB1 tumor suppressor gene . The second allele is most commonly lost , as demonstrated by loss of heterozygosity studies . RB1 germline carriers usually develop bilateral tumors , but some Rb families display low penetrance and variable expressivity . In order to decipher the underlying mechanisms , 23 unrelated low penetrance pedigrees segregating the common c . 1981C>T/p . Arg661Trp mutation and other low penetrance mutations were studied . In families segregating the c . 1981C>T mutation , we demonstrated , for the first time , a correlation between the gender of the transmitting carrier and penetrance , as evidenced by Fisher’s exact test: the probability of being unaffected is 90 . 3% and 32 . 5% when the mutation is inherited from the mother and the father , respectively ( p-value = 7 . 10−7 ) . Interestingly , a similar correlation was observed in families segregating other low penetrance alleles . Consequently , we investigated the putative involvement of an imprinted , modifier gene in low penetrance Rb . We first ruled out a MED4-driven mechanism by MED4 methylation and expression analyses . We then focused on the differentially methylated CpG85 island located in intron 2 of RB1 and showing parent-of-origin-specific DNA methylation . This differential methylation promotes expression of the maternal c . 1981C>T allele . We propose that the maternally inherited c . 1981C>T/p . Arg661Trp allele retains sufficient tumor suppressor activity to prevent retinoblastoma development . In contrast , when the mutation is paternally transmitted , the low residual activity would mimic a null mutation and subsequently lead to retinoblastoma . This implies that the c . 1981C>T mutation is not deleterious per se but needs to be destabilized in order to reach pRb haploinsufficiency and initiate tumorigenesis . We suggest that this phenomenon might be a general mechanism to explain phenotypic differences in low penetrance Rb families .
Retinoblastoma ( Rb ) is the most common pediatric intraocular neoplasm and occurs in 1 of every 15 , 000 births . It results from the biallelic inactivation of the RB1 tumor suppressor gene , located on 13q14 [1] . RB1 encodes the nuclear phosphoprotein pRB , which plays a prominent role during the G1/S phase transition[2] . In tumors , both RB1 alleles can be inactivated via diverse mechanisms including point mutations , large rearrangements , promoter hypermethylation and , most frequently , loss of the second allele demonstrated by loss of heterozygosity studies . In non-hereditary retinoblastoma , both RB1 mutations are somatic and occur in the same retinal cell that develops into a tumor . In contrast , in hereditary retinoblastoma , germline mutation of one allele is associated with predisposition to Rb , while the second mutation on the other allele is somatic , usually acquired during early childhood . Non-hereditary retinoblastomas are usually unilateral ( one eye affected ) with a median age at diagnosis of 2 years , whereas hereditary cases are usually bilateral ( both eyes affected ) with a median age at diagnosis of 1 year and an increased risk for second tumors . Familial hereditary Rb is defined as two or more carriers of an RB1 germline gene mutation in a family and represents 10% of all retinoblastomas . Predisposition to Rb is transmitted as an autosomal dominant trait with almost complete penetrance ( over 90% ) and germline carriers usually develop bilateral or multifocal tumors . However , some Rb families display low penetrance ( unaffected carriers ) and variable expressivity ( carriers develop bilateral , unilateral Rb or even benign retinomas ) . Deciphering the mechanisms underlying low penetrance ( LP ) Rb is of utmost importance , as it will impact the clinical management of these families and furthers our understanding of Rb as a disease . The well-known c . 1981C>T / p . Arg661Trp low penetrance mutation in exon 20 of RB1 results in a mutant pRb that is partially inactivated [3 , 4] which may explain the reduced severity observed . However , why this would be the case in some family members and not in others remains unclear . Based on the collection of large families , we have demonstrated , that in the context of c . 1981C>T/p . Arg661Trp low penetrance , a parent-of-origin effect impacts on Rb phenotype . When the mutation is inherited from the paternal side , offspring are retinoblastoma-prone . In contrast , when the mutation is inherited from the maternal side , offspring mostly remain unaffected . Based on these observations , the involvement of a putative modifier , imprinted gene should be considered . Two alternative hypotheses were tested . Firstly , we searched for a possible involvement of the MED4 gene , located in the flanking centromeric region of RB1 , as we have recently demonstrated that MED4 expression is required for Rb development [5] . We postulated maternal imprinting for MED4 , which results in monoallelic expression from the paternal allele . As a result , when the RB1 c . 1981C>T/p . Arg661Trp mutation is inherited from the mother , loss of the contralateral paternal allele in the tumor would switch off MED4 expression and prevent retinoblastoma development in the context of a low penetrance mutation . Secondly , we focused on a differentially methylated CpG island showing parent-of-origin-specific DNA methylation at the RB1 gene and located in RB1 intron 2 ( called CpG85 hereafter ) [6 , 7] . Differential methylation of CpG85 skews RB1 expression in favor of the maternal allele [6] . Our results on a series of germline , tumor DNAs and RNAs did not support any involvement of MED4 in the low penetrance phenotype , but confirmed the differentially methylated status of RB1 CpG85 . It was therefore concluded that overexpressed maternally inherited p . Arg661Trp alleles retain sufficient tumor suppressor activity to prevent Rb development . On the other hand , when the mutation is paternally transmitted , the low residual activity would mimic a null mutation , leading to haploinsufficiency and Rb development .
We reviewed the records of 49 pedigrees from Institut Curie with a family history of Rb . Thirty-four of these families segregated high penetrance mutations and 15 families segregated low penetrance mutations . Eight low penetrance families derived from the literature were also found by PubMed search and were added to the study ( Table 1 ) . All first generation carriers were excluded to avoid any bias in DER calculation ( Disease Eye Ratio , see “Patients and Methods” section ) . The parental origin of the c . 1981C>T/p . Arg661Trp mutant allele was documented in 71 of the 85 carriers . In this series of 71 carriers , 31 and 40 received the mutant allele from their mother and father , respectively . Twenty-eight carriers who received the mutant allele from their mother remained unaffected ( 28/31 , 90 . 3% ) , and only 3 developed Rb ( 3/31 , 9 . 7% ) . In contrast , 13 carriers who received the mutant allele from their father remained unaffected ( 13/40 , 32 . 5% ) and 27 developed Rb ( 27/40 , 67 . 5% ) . Consequently , inheriting the c . 1981C>T/p . Arg661Trp mutation from the maternal side significantly prevented Rb development ( p-value = 7 . 10−7 , Fisher’s exact test ) . In other words , the probability of being unaffected when the mutation is inherited from the maternal side is 90 . 3% versus only 32 . 5% when the mutation is inherited from the paternal side . We then looked for a similar disequilibrium in families segregating non-p . Arg661Trp low penetrance mutant alleles ( see Table 1 ) . To avoid any bias , families F14 and F15 segregating the c . 607+1 G>T mutation were excluded from analysis since a parent of origin effect was previously described [13] . The parental origin of the mutant alleles was documented in 58 of the 82 remaining carriers . Seventeen carriers received the mutation from their mother and 41 received the mutation from their father . Thirteen carriers who received the mutant allele from their mother were unaffected ( 13/17 , 76 . 4% ) and 4 developed Rb ( 4/17 , 23 . 6% ) . Eighteen carriers who received the mutation from their father were unaffected ( 18/41 , 43 . 9% ) and 23 developed Rb ( 23/41 , 56 . 1% ) . Fisher’s exact test demonstrated a disequilibrium between the gender of the transmitting carrier parent and penetrance ( p-value = 0 . 041 ) . Lastly , families segregating high penetrance mutations displayed no such correlation , as all 54 mutation carriers of known parental origin developed retinoblastoma , regardless of the gender of the transmitting carrier . As previously described , no preferential transmission of mutant or normal alleles from carrier fathers or mothers was observed [17] . These results unambiguously demonstrate that , in the context of low penetrance Rb , a parent-of-origin effect impacts on Rb phenotype .
Deciphering the molecular basis of low penetrance retinoblastoma is of utmost importance for both researchers and clinicians , as it will shed light on retinoblastoma development , allow prognostic assessment in low penetrance families , and promote optimal genetic counseling and ophthalmological surveillance . In this study , we have identified , for the first time , a parent-of-origin effect in families segregating the c . 1981C>T/p . Arg661Trp mutation . In these families , the probabilities of being unaffected for germline carriers were 90 . 3% and 32 . 5% when the mutation was inherited from the maternal and paternal side , respectively . Interestingly , a similar correlation was observed in families segregating other low penetrance alleles , albeit to a lesser extent: probabilities of being unaffected were 76 . 5% and 43 . 9% when the mutation was inherited from the maternal and paternal side , respectively . This finding echoes the maternal protective effect previously described in 2 families ( F14 and F15 in this paper ) in association with the c . 607+1G>T low penetrance mutation [13] . Restoration of the maternal truncated transcript or mutation at an imprinted locus in cis were proposed to explain this observation . Our own results on a large number of pedigrees segregating a distinct low penetrance mutation rule out the first hypothesis , but support the second hypothesis . We have recently shown that retinoblastoma RB1 -/- cells cannot survive in the absence of MED4 , both in vitro and in orthotopic xenograft models in vivo , therefore identifying MED4 as a survival gene in retinoblastoma [5] . Consequently , we considered a MED4-driven general mechanism to explain low penetrance retinoblastoma . We postulated a parent-of-origin regulation of MED4 that would be able to skew MED4 expression in favor of the maternal allele . As a result , when the p . Arg661Trp mutation is inherited from the mother , loss of the contralateral paternal allele would dramatically decrease MED4 expression and prevent retinoblastoma development in the context of a low penetrance mutation . However , methylation and expression studies both ruled out this mechanism to explain the parent-of-origin effect observed in p . Arg661Trp pedigrees . A recent study demonstrated RB1 imprinting by a differentially-methylated-region ( DMR ) at CpG85 in RB1 intron 2 . In humans , this DMR is methylated on the maternal allele and remains unmethylated on the paternal allele . Consequently , CpG85 acts as a weak promoter for an alternative , paternally expressed , RB1 transcript ( RB1-E2B ) that competes with the main RB1 transcript . This transcriptional interference skews RB1 expression in favor of the maternal allele [6 , 18] . In line with this previous report , our SNAPshot analyses targeting the c . 1981C>T/p . Arg661Trp mutation demonstrated higher expression of the maternal RB1 allele . Our results also demonstrated that , when this mutation is inherited from the maternal side , offspring mostly remain unaffected . Although counter-intuitive , this means that a high level of the c . 1981C>T/p . Arg661Trp mutant allele would protect from retinoblastoma . A plausible explanation lies in the residual biochemical properties of p . Arg661Trp mutants , which lack E2F pocket protein-binding activity but retain E2F-independent tumor suppressor function and the wild-type ability to partially suppress colony growth of RB ( - ) cells and induce parameters of cell differentiation [19] . More broadly , an E2F-independent paradigm of tumor suppression is being developed for RB1[20] . Lastly , a study showed that certain LP alleles ( p . Arg661Trp included ) retain greater functional activity than expected , which is why additional cooperating events are needed to block this residual activity [21] . The competing RB1-E2B transcript that lowers RB1 regular transcript on the paternal allele might constitute this additional event in low penetrance Rb families . Consequently , when the father transmits the mutation , the residual pRb activity is too low to prevent the development of Rb in the cell . The low residual activity would mimic a null mutation , leading to genomic instability and Rb development . This also means that the c . 1981C>T/p . Arg661Trp mutation is not deleterious per se but needs to be destabilized in order to reach pRb haploinsufficiency and initiate genomic instability and tumorigenesis [22 , 23] . Although our results on low penetrance families segregating other LP alleles reached borderline significance ( p = 0 . 041 ) , we propose this hypothesis as a general mechanism to explain disease occurrence in the context of low penetrance Rb . Intriguingly , we have also reported , for the first time , a hypermethylated , deregulated RB1 imprint in Rb tumors . Hypermethylation of CpG85 inhibits RB1-E2B transcription , therefore enhancing RB1 main transcript expression . A plausible explanation would be that this loss of imprinting at the CpG85 locus might be used by tumor cells to attempt to increase the expression of pRB and thus restore its tumor suppressor activity . Overall , we demonstrated that a parent-of-origin effect is involved in low penetrance Rb families segregating the c . 1981C>T/p . Arg661Trp mutation of RB1 and propose this phenomenon as a general mechanism to explain phenotypic differences in low penetrance Rb families .
All patients have given written informed consent during genetic counselling sessions . The study was approved by the Groupe Thématique Transverse ( GTT ) “retinoblastome” of Institut Curie medical center ( 2013–2310 ) . Institut Curie is the national referral center for retinoblastoma in France . Diagnosis of Rb is established on the basis of examinations by an ophthalmologist and histopathological criteria when treatment involves enucleation . All Rb patients are offered genetic counseling and RB1 gene mutation analysis in constitutional and tumor DNA . When a germline mutation is found , molecular testing is extended to relatives . Individual written consent for genetic analysis was obtained from all participating patients or their legal guardians . The study was approved by our local ethic committee and retinoblastoma board . In our series of 1 , 210 consecutively ascertained cases , we surveyed 49 pedigrees with a family history of Rb . Seven of the low penetrance families have been previously published in part[11] . We included family members for which the mutational status was ascertained by RB1 analysis and obligate carriers when a DNA sample was not available . Relatives underwent routine fundus examination to look for the presence of retinomas ( retinal scars ) . Since it has been described that retinoma develops after homozygous loss of RB1[24] , individuals with retinoma were considered to be affected . Obligate carriers with normal fundus examination were considered to be non-penetrant or unaffected . Mutational mosaicism is known to explain the variable expressivity and penetrance in Rb patients[25] . Consequently , we excluded all first-generation carriers of a germline mutation displaying unilateral Rb or remaining unaffected , since retinal mosaicism could not be excluded in these patients . Clinical features included disease status ( affected / unaffected ) and diseased-eye ratio ( DER ) . The DER is defined as the ratio of the sum of the eyes affected by tumors to the number of mutation carriers in a family . It provides a useful combination of penetrance and expressivity . Families with a DER ≥ 1 . 5 are considered to display complete penetrance . Families with a DER ≤ 1 are designated as LP[8] . Fisher’s exact test was performed using R statistical software v3 . 0 . 2 on i ) 10 p . Arg661Trp families ( 6 from our series and 4 from the literature [8 , 9 , 10] ) , ii ) 13 non-p . Arg661Trp low penetrance families ( 9 from our series and 4 from the literature [11 , 12 , 14 , 15 , 16] , iii ) 34 high penetrance families from our series . | Complex genotype-phenotype correlations lead to clinically and emotionally difficult situations . Improved understanding of these correlations is of utmost importance in medical genetics . Low penetrance retinoblastoma families segregating the c . 1981C>T / p . Arg661Trp mutation are a good model as germline carriers develop bilateral , unilateral retinoblastoma , benign retinomas or remain unaffected . The c . 1981C>T mutation results in a mutant pRb protein that is partially inactivated which may explain the reduced severity observed . However it is still unclear why this would be the case in some family members and not in others . We have demonstrated a parent-of -origin effect in c . 1981C>T / p . Arg661Trp pedigrees and have concluded that overexpressed maternally inherited p . Arg661Trp alleles retain sufficient tumor suppressor activity to prevent Rb development . This might be a general phenomenon driving low penetrance retinoblastoma . Our findings shed light on genotype-phenotype correlations in low penetrance retinoblastoma and are of special relevance for genetic counselling . | [
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"py... | 2016 | A Parent-of-Origin Effect Impacts the Phenotype in Low Penetrance Retinoblastoma Families Segregating the c.1981C>T/p.Arg661Trp Mutation of RB1 |
A fundamental goal of microbial ecology is to understand what determines the diversity , stability , and structure of microbial ecosystems . The microbial context poses special conceptual challenges because of the strong mutual influences between the microbes and their chemical environment through the consumption and production of metabolites . By analyzing a generalized consumer resource model that explicitly includes cross-feeding , stochastic colonization , and thermodynamics , we show that complex microbial communities generically exhibit a transition as a function of available energy fluxes from a “resource-limited” regime where community structure and stability is shaped by energetic and metabolic considerations to a diverse regime where the dominant force shaping microbial communities is the overlap between species’ consumption preferences . These two regimes have distinct species abundance patterns , different functional profiles , and respond differently to environmental perturbations . Our model reproduces large-scale ecological patterns observed across multiple experimental settings such as nestedness and differential beta diversity patterns along energy gradients . We discuss the experimental implications of our results and possible connections with disorder-induced phase transitions in statistical physics .
Microbial communities inhabit every corner of our planet , from our own nutrient-rich guts to the remote depths of the ocean floor . Different environments harbor very different levels of microbial diversity: in some samples of non-saline water at mild temperature and pH , nearly 3 , 000 coexisting types of bacteria can be detected , whereas at ambient temperatures warmer than 40° C , most cataloged samples contain fewer than 100 distinct variants [1] . The functional structure of these communities is also highly variable , with functional traits often reflecting the environment in which the communities are found [1 , 2] . A central goal of microbial community ecology is to understand how these variations in diversity , stability and functional structure [3] arise from an interplay of environmental factors such as energy and resource availability [4 , 5] and ecological processes such as competition [6–9] and stochastic colonization [10–13] . This endeavor is complicated by the fact that microbes dramatically modify their abiotic environments through consumption and secretion of organic and inorganic compounds . This happens on a global scale , as in the Great Oxidation Event two billion years ago [14 , 15] , and also on smaller scales relevant to agriculture , industry and medicine . In this sense , every microbe is an “ecosystem engineer” [16] . Metabolic modeling and experiments suggests that metabolically mediated syntrophic interactions should be a generic feature of microbial ecology [17–19] and that complex microbial communities can self-organize even in constant environments with no spatial structure or predation [17 , 20] . For these reasons , there has been significant interest in developing new models for community assembly suited to the microbial setting [21–25] . Here , we present a statistical physics-inspired consumer resource model for microbial community assembly that builds upon the simple model introduced in [17] and explicitly includes energetic fluxes , stochastic colonization , syntrophy , and resource competition . We focus on modeling complex communities with many species and metabolites . By necessity , any mathematical model of such a large , diverse ecosystem will contain thousands of parameters that are hard to measure . To circumvent this problem , we take a statistical physics approach where all consumer preferences and metabolic parameters are drawn from random distributions . This approach to modeling complex systems has its root in the pioneering work of Wigner on the spectrum of heavy nuclei [26] and was adapted by May to ecological settings [27] . Recently , there has been a renewed interest in using these ideas to understand complex systems in both many-body physics ( reviewed in [28] ) and community assembly [12 , 17 , 25 , 29–35] . The key insight underlying this approach is that generic and reproducible large-scale patterns observed across multiple settings likely reflect typical properties , rather than fine tuned features of any particular realization or community . Consistent with this idea , it was recently shown that a generalized consumer resource model with random parameters can reproduce many of the patterns observed in experiments where natural communities were grown in synthetic minimal environments [17] . In this paper , we ask how varying the energy flux into an ecosystem and the amount of cross-feeding affects microbial community assembly . We find that the resulting communities generically fall into two distinct regimes , characterized by qualitative differences in their community-level metabolic networks , functional structures , responses to environmental perturbations , and large-scale biodiversity patterns . We show our model predictions are consistent with data from the Tara Oceans database [36] and the Earth Microbiome Project [1] , and propose feasible experimental tests using synthetic communities .
The starting point for our analysis is a new model that adapts MacArthur’s Consumer Resource Model [7] to the microbial context by including energetics , stochastic colonization , and the exchange and consumption of metabolites . We consider the population dynamics of S species of consumers ( e . g . , microbes ) competing for M types of substitutable resources . We are interested in large , diverse ecosystems where S , M ≫ 1 . A schematic summarizing our model is shown in Fig 1 . A natural setting for considering substitutable resources is when all essential biomass components are supplied in excess , and the limiting factor for growth is the supply of usable energy . In this context , one only needs to keep track of resources from which energy can be harvested . All other nutrients are included implicitly , under the assumption that some of the energy budget is used to import whatever materials are required for growth and reproduction . Terminal waste products from which no more energy can be extracted are likewise treated implicitly , and are not included among the M resource types . In our model , the rate at which an individual of species i harvests energy from resource α depends on the resource concentration Rα as well as on the consumer’s vector of resource preferences ciα through the expression: J i α in = w α σ ( c i α R α ) , ( 1 ) where σ ( x ) encodes the functional response and has units of mass/time , while wα is the energy density of resource α with units of energy/mass . In the microbial context the consumer preferences ciα can be interpreted as expression levels of transporters for each of the resources . In the main text , we focus on Type-I responses where σ ( x ) = x , and we set wα = 1 for all α , but most of our results still hold when σ ( x ) is a Monod function or the wα are randomly sampled , as shown in Section 3 of S1 Text . We model leakage and secretion by letting a fraction lα of this imported energy return to the environment , so that the power available to the cell for sustaining growth is equal to J i grow = ∑ α ( 1 - l α ) J i α in . ( 2 ) This parameterization guarantees that the community does not spontaneously generate usable energy in violation of the Second Law of Thermodynamics . We assume that a fixed quantity mi of power per cell is required for maintenance of a steady population of species i , and that the per-capita growth rate is proportional to the remaining energy flux , with proportionality constant gi . In typical experimental conditions , cell death is negligible , and mi is the energy harvest required for the replication rate to keep up with the dilution rate . Under these assumptions , the time-evolution of the population size Ni of species i can be modeled using the equation d N i d t = g i N i [ J i grow - m i ] . ( 3 ) The leaked energy flux J i out = ∑ αl α J i α in from each cell of species i is partitioned among the M possible resource types via the biochemical pathways operating within the cell . We assume that all species share a similar core metabolism , encoded in a matrix Dβα . Each element of Dβα specifies the fraction of leaked energy from resource α that is released in the form of resource β ( note that by definition , ∑β Dβα = 1 ) . Thus , in our model the resources that are excreted into the environment are intimately coupled to the resources a cell is consuming . The outgoing energy flux contained in metabolite β is given by J i β out = w β ν i β out = ∑ α D β α l α J i α in . ( 4 ) The dynamics of the resource concentrations depend on the incoming and outgoing mass fluxes ν i α in = σ ( c i α R α ) and ν i α out , which are related to the energy fluxes via the energy densities wα . In terms of these quantities , we have d R α d t= h α + ∑ j N j ( ν j α out - ν j α in ) , ( 5 ) with hα encoding the dynamics of externally supplied resources . In this manuscript , we focus on the case where the microbial communities are grown in a chemostat with a single externally supplied resource α = 0 ( Fig 1 ) . In this case , the resource dynamics can be described by choosing h α = κ α - τ R - 1 R α , with all the κα set to zero except for κ0 . These equations for Ni and Rα , along with the expressions for J i α in and J i α out , completely specify the ecological dynamics of the model . This model has been implemented in a freely available open-source Python package “Community Simulator . ” The package can be downloaded from https://github . com/Emergent-Behaviors-in-Biology/community-simulator .
Our numerical simulations display a transition between two qualitatively different community structures as we vary the externally supplied energy flux w0κ0 and the leakage/syntrophy l . In the “thermodynamic limit” of M , S → ∞ , the communities exhibit signatures of a phase transition analogous to those found in disordered systems in physics ( see Discussion and S1 Text Section 5 ) . Fig 2 shows the effect of this transition on community diversity at our chosen finite values of S and M . At low levels of energy flux or syntrophy , the diversity is severely limited by resource availability . In the limit of high supplied energy flux and high leakage , a maximally diverse regime is obtained , where the number of surviving species is limited only by the similarity between consumption profiles within the regional species pool , in accordance with classical niche-packing theory [7] as we will discuss below . The difference between the two regimes is most apparent from the perspective of the energy flux networks . Because our model explicitly accounts for the flow of energy from one resource type into another , we can compute all the steady-state fluxes and represent them graphically , as shown in Fig 3 for some representative examples . Each node in this network is a resource type , and each directed edge represents the steady-state flux Jβα of energy conversion from resource α to resource β , mediated by one or more syntrophic consumers: J β α= ∑ i N i J i β α out = D β α l α ∑ i N i w α c i α R α . ( 6 ) The resource-limited regime produces a unidirectional flow of energy , which is converted from the externally supplied resource type into an orderly succession of secreted resources . For the sparse metabolic matrix shown in the top row of Fig 3 , most resource types also have extremely small incoming flux vectors in this regime , with magnitudes less than 1% the size of the largest flux in the network . The diverse regime displays a qualitatively different structure , where all resources have significant incoming fluxes ( regardless of the choice of Dαβ ) , and the large number of loops in the network makes it impossible to put the resource types into any definite order . In S10 Fig . , we plot the fraction of samples from Fig 2 whose ( pruned ) flux networks are free of cycles , and confirm that this observation is generic . The dramatic contrast between the community-level metabolism of the two regimes affects many other global features of the ecosystem , which we will explore in the following sections . To better understand the behavior of consumers in the two regimes , we examined the functional traits of members of typical communities in each one . In the resource-limited regime , many surviving species derive most of their energy directly from the externally supplied resource ( Fig 4A ) . In the diverse regime , by contrast , only a minority of the steady-state community members can consume this resource at all , and even these species receive most of their energy from a diverse array of metabolic byproducts ( Fig 4B ) . We quantified this observation using the Simpson Diversity M i eff of the incoming resource flux vectors J i α in , which measures the effective number of resources consumed by each species , and is closely related to the inverse participation ratio in statistical physics . The Simpson Diversity is defined by Mieff=[ ∑α ( JiαinJiin ) 2 ]−1 , ( 7 ) where J i in = ∑ αJ i α in is the total incoming energy flux for each cell of this species . M i eff approaches 1 for species that obtain the bulk of their energy from a single resource type and approaches M when all resource types are consumed equally . In the resource-limited regime , the distribution of these values is sharply peaked around 2 . In the diverse regime , the peak is located around 10 , which is the average number of resources with high transporter expression in our binary sampling scheme for ciα . This shows that most community members in the diverse regime utilize multiple energy sources , with the incoming flux spread evenly over all resource types they are capable of consuming . Another important property of microbial ecosystems is how they respond to environmental perturbations . Previous theoretical studies have shown that sufficiently diverse communities can “pin” the resource concentrations in their local environment to fixed values , which are independent of the magnitude of externally supplied fluxes [21 , 38 , 39] . In these studies , resource pinning occurs only when the community saturates the diversity bound imposed by the principal of competitive exclusion , i . e . when the number of coexisting species is at least as large as the number of resource types . Such maximally diverse communities typically require fine-tuning of the resource utilization profiles or imposition of universal efficiency tradeoffs in cellular metabolism . In our stochastically assembled communities , the diversity is always much lower than the number of resource types , so we hypothesized that the resource concentrations should not be pinned . To test this idea , we measured the response of the steady-state concentrations R ¯ α to changes in external supply rates κα , in terms of the “resource susceptibilities” ∂ R ¯ α / ∂ κ α plotted in Fig 4D [34] . Our hypothesis was valid in the resource-limited regime , where many resource susceptibilities are comparable to the susceptibility in the empty chemostat ∂ R ¯ α / ∂ κ α = τ R = 1 . But in the diverse regime , we were surprised to find that the susceptibilities are 100 times smaller than this maximum value . This suggests that resource pinning may be a generic phenomenon , observable in real ecosystems when the energy supply is sufficiently large . In the diverse regime , the number of coexisting species ( “richness” ) is not limited by energy availability or by access to secreted metabolites , but is still much less than the maximal value of M = 100 set by the competitive exclusion principle [8] , even though almost all M resource types are present at non-negligible levels ( as shown in S11 Fig . ) . We hypothesized that the diversity in this regime is limited by the degree of similarity between consumption preferences of members of the regional species pool . This can be quantified in terms of the niche overlap [9 , 40] , whose average value in a large regional pool is given by: 〈 ρ i j 〉 ≡ 〈 ∑ αc i α c j α ∑ αc i α 2 ∑ αc j α 2 〉 = 〈 c i α 〉 2 〈 c i α 2 〉 . ( 8 ) Fig 5 shows how the richness varies as a function of 〈ρij〉 . In the diverse regime the mean richness decreases approximately linearly with increasing overlap . The richness of the resource-limited regime , on the other hand , has only a very weak dependence on the niche overlap . These results suggest that the distribution of consumption preferences in the regional pool is the primary driver of community assembly in the diverse regime . Importantly , non-zero niche overlap limits the number of coexisting species well below the upper bound imposed by the competitive exclusion principle . Our aim in developing this model is to identify and understand generic patterns in community structure , that are independent of particular biological details . In large-scale surveys of natural communities , subject to many sources of noise and environmental heterogeneity , one expects that only sufficiently generic patterns will be detectable . The simplest observable to examine in such survey data is the list of species that are present or absent in each sample . We obtained these presence/absence vectors from the simulations of Fig 2 , and found that when we sorted species by prevalence ( rows in Fig 6A ) and samples by richness ( columns in Fig 6A ) , the community composition generically exhibited a nested structure—less diverse communities tended to be subsets of more diverse communities [41 , 42] . We quantified this result using an established nestedness metric , as described in S1 Text and S7 Fig . , and found that the actual nestedness exceeds the mean value for a randomized null model by more than 100 standard deviations . This suggests that nested structures may generically emerge in community assembly through the interplay of stochastic colonization , competition , and environmental filtering . Next , we asked if we large-scale beta-diversity patterns could be used to distinguish the resource-limited and diverse regimes . We initialized 200 new communities with 100 randomly chosen members from the full regional species pool and simulated these communities to steady state in both the resource-limited and diverse regimes ( see S1 Text Section 2B for details ) . This sub-sampling of the full regional species pools mimics the effect of stochastic colonization , where a different random subset of species seeds each community . To better understand beta-diversity signatures in the two regimes , we performed a Principal Component Analysis ( PCA ) on community composition and projected the data onto the first two principal components , as shown in Fig 6B–6D . In the resource-limited regime , the communities form distinct clusters that are distinguished by different highly abundant species . This suggests that harsh environments only allow a few species from the regional pool to rise to dominance , and that these dominant species induce clustering of communities . Such “enterotype”-like behavior is a common feature observed in many microbial settings [43] . In contrast , the diverse regime exhibited neither well-defined clusters nor dominant , highly abundant species . The preceding results suggest that the resource-limited and diverse regimes can be distinguished using beta-diversity patterns . Rigorous testing of this prediction is beyond the scope of the present work . But as an illustration of the kind of data we hope to explain , we examined the natural gradient of solar energy supply in the Tara Oceans survey , which collected microbial community samples from a range of depths across the world’s oceans [36] . Explicitly including light as an energy source would require some modification to the structure of the model equations , but we expect that the large-scale features of sufficiently diverse ecosystems should not be sensitive to changes involving just one resource . We analyzed the 16S OTU composition of tropical ocean communities for all 30 sea-surface samples , where solar energy is plentiful , and all 13 samples from the deep-sea mesopelagic zone where energy fluxes are limited . We projected these composition vectors onto their first two principal components as in Fig 6 above , and plot the results in Fig 7 . The sea surface data superficially resembles our diverse regime , with a relatively uniform distribution of possible community compositions . In contrast , the Mesopelagic Zone is similar to our resource-limited regime: the dominance of the most abundant species is much more pronounced , and the compositions appear to cluster into four discrete types . While these results are consistent with our model predictions , the number of samples at each depth is still too small to draw any definitive conclusions about clustering . As mentioned above , our model also gives a natural explanation for the nestedness in the Earth Microbiome Project community composition data [1] , suggesting that it may be a natural byproduct of complex microbial communities shaped by competition , environmental heterogeneity , and stochastic colonization . To test how generic this feature is , we plotted presence/absence community compositions of all samples from the Tara Oceans dataset , sorting samples by richness and OTU’s ( “species” ) by prevalence . Each sample contains thousands of low-abundance OTU’s , which can obscure ecological patterns through their susceptibility to sequencing noise and transient immigration . We therefore imposed a 0 . 5% relative abundance threshold for an OTU to count as “present . ” The resulting pattern in Fig 7 is qualitatively similar to our simulations ( Fig 6D ) , and to the phylum-level data of the Earth Microbiome Project [1] , with the region below the diagonal significantly less populated than the region above the diagonal ( although the signal is much weaker ) . In S1 Text Section 4 and S7 Fig . , we quantify the nestedness using the same metric employed in the Earth Microbiome Project analysis [1 , 44] , and show that the score is significantly higher than the mean scores from two standard null models .
Advances in sequencing technology have opened new horizons for the study of microbial ecology , generating massive amounts of data on the composition of both natural and synthetic communities . But the complexity of these systems make it difficult to extract robust general principles suitable for guiding medical and industrial applications . Numerical simulations provide a powerful tool for addressing this problem . By rapidly iterating numerical experiments under a variety of modeling choices with random parameters , one can identify robust patterns and use the resulting insights to guide targeted experiments . Following this strategy , we developed a thermodynamic consumer resource model that explicitly includes energetic fluxes and metabolically mediated cross-feeding and competition . Using this model , we identified two qualitatively distinct regimes as we varied the amount of energy supplied to ecosystem and the fraction of energy leaked back into the environment: a low diversity “resource-limited” regime and a “diverse” regime . The structure of the resource-limited regime is strongly constrained by species- and community-level environmental filtering . Each community is dominated by a handful of species , making the community properties sensitive to the idiosyncratic characteristics of these species and susceptible to environmental fluctuations . In the diverse regime , communities exhibit more universal features because they substantially engineer their environments . In particular , the concentrations of resources at steady state are more narrowly distributed and insensitive to perturbations in the external supply rates . Moreover , each species draws its energy roughly equally from all resources , rather than subsisting on the externally supplied resource as in the resource-limited regime . The emergence of environmental engineering from this community-scale model makes it a valuable tool for testing and refining existing conceptual frameworks employed by empirical biologists [45] . A major limitation of the dominant paradigms for evolution and ecology from the last century is the implicit assumption of a constant environment [46] . The generalized Lotka-Volterra model , for example , remains a standard lens for reasoning about ecological dynamics , both quantitatively and qualitatively [47–49] . It assumes that the dynamics emerge from the sum of pairwise interactions among species , and that the sign and strength of these interactions are intrinsic properties of the species . This can be a good assumption in some circumstances [47 , 48] , but fails to accurately describe the behavior of simple models that explicitly account for the state of the environment [50] . Our work provides a starting point for determining the conditions under which pairwise models will generically succeed or fail in describing the behavior of large ecosystems . Our model complements other recent efforts at understanding microbial community ecology . Taillefumier et al . proposed a similar model of metabolite exchange , and focused on the case where the number of resource types M is equal to 3 [21] . In this case , repeated invasion attempts from a large regional species pool produced optimal combinations of metabolic strategies . Goyal et al . examined the opposite limit , with M = 5 , 000 , but allowed each species to consume only one type of resource [22] . This generated communities with a tree-like metabolic structure , where each species depends directly on another species to generate its unique food source . In our model , the large number of resource types ( M = 100 in the current study ) makes spontaneous strategy optimization extremely unlikely . And our generic protocol for sampling the metabolic matrix Dαβ allows a variety of community-level energy flux topologies to emerge , as illustrated in Fig 3 , which can sometimes be quite different from the tree networks of Goyal et al . The absence of highly specialized metabolic structure in our model makes it especially well-suited for interpreting patterns in large-scale sequence-based datasets such as the Earth Microbiome Project [1] . Our model predictions can also be directly tested using experiments with natural communities in synthetic laboratory environments [17 , 51] . Our model predicts that beta-diversity patterns and community-level metabolic networks can be significantly altered by increasing the ecosystem’s energy supply , inducing a transition from the resource-limited to the diverse regime . In the experimental set-up of [51] , this can be done by directly adding chitinase enzymes to the sludge reactor to increase the degradation of chitin-based organic particles on which the ocean-derived microbial communities subsist . One could then look for shifts in the resulting diversity patterns , and observe any changes in the topology of the metabolic flux network using isotope labeling . In this work we have largely confined ourselves to studying steady-state properties of well-mixed microbial communities . Microbial communities often exhibit complex temporal dynamics with well-defined successions [51–53] . It will be interesting to explore these dynamical phenomena using our model . It is also well established that spatial structure can give rise to new ecological phenomena [54 , 55] and an important area of future work will be to better explore the role of space in microbial community assembly . Finally , we have obtained strong numerical evidence that the two regimes are separated by a phase transition , which is likely closely related to disorder-induced phase transitions in statistical physics [32] . In Supporting Text Section 5 , we examine the steady-state richness in the three examples of Fig 2 under increasing values of M from M = 40 to M = 560 . We find that the richness is proportional to M in the diverse regime , but scales sub-linearly with M in both examples from the resource-limited regime . In the M → ∞ limit , therefore , we expect to find a sharp line between the regimes , with the ratio of the richness to M vanishing on the resource-limited side . But we do not yet know the exact location of this boundary , or the critical exponents describing the behavior of the system near the transition . | The diversity , stability and functional structure of microbial communities have dramatic effects on the health of humans and of ecosystems . The complexity of these communities has so far precluded the development of a general predictive model that would capture the dependence of these features on environmental conditions . We confronted this challenge by constructing a flexible simulation framework , and randomly sampling parameters under a variety of modeling assumptions to identify generic patterns . We found two qualitatively distinct regimes of community structure , which reproduce observed patterns of biodiversity , and make new predictions about stability and function . | [
"Abstract",
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"biodiversity",... | 2019 | Available energy fluxes drive a transition in the diversity, stability, and functional structure of microbial communities |
In northern Ethiopia the prevalence of visceral leishmaniasis is steadily rising posing an increasing public health concern . In order to develop effective control strategies on the transmission of the disease it is important to generate knowledge on the epidemiological determinants of the infection . We conducted a cross-sectional survey on children 4–15 years of age using a multi staged stratified cluster sampling on high incidence sub-districts of Amhara regional state , Ethiopia . The survey included a socio-demographic , health and dietary questionnaire , and anthropometric measurements . We performed rK39-ICT and DAT serological tests in order to detect anti-Leishmania antibodies and carried out Leishmanin Skin Test ( LST ) using L . major antigen . Logistic regression models were used . Of the 565 children surveyed 56 children were positive to infection ( 9 . 9% ) . The individual variables that showed a positive association with infection were increasing age , being male and sleeping outside [adjusted odds ratios ( 95% CI ) : 1 . 15 ( 1 . 03 , 1 . 29 ) , 2 . 56 ( 1 . 19 , 5 . 48 ) and 2 . 21 ( 1 . 03 , 4 . 71 ) respectively] and in relation to the household: past history of VL in the family , living in a straw roofed house and if the family owned sheep [adjusted OR ( 95% CI ) : 2 . 92 ( 1 . 25 , 6 . 81 ) , 2 . 71 ( 1 . 21 , 6 . 07 ) and 4 . 16 ( 1 . 41 , 12 . 31 ) respectively] . A behavioural pattern like sleeping outside is determinant in the transmission of the infection in this area . Protective measures should be implemented against this identified risk activity . Results also suggest a geographical clustering and a household focalization of the infection . The behaviour of the vector in the area needs to be clarified in order to establish the role of domestic animals and house materials in the transmission of the infection .
Visceral leishmaniasis ( VL ) or kala-azar is a neglected vector-borne parasitic disease that manifests with irregular bouts of fever , substantial weight loss , weakness , hepatosplenomegaly and pancytopenia , and that is fatal if left untreated [1] . It has an estimated annual incidence of 500 000 clinical cases with 50 000 associated deaths and 2 357 000 disability-adjusted life years lost [2] . It is mainly concentrated in few major foci and the East African Leishmania donovani focus is the second largest , with the highest incidence in Ethiopia and the Sudan [2] . VL is caused by protozoan parasites of the L . donovani species complex transmitted to human and animal hosts by the bite of phlebotomine sand flies . It has already been determined that large numbers of individuals in endemic areas are infected with the parasite but do not develop any signs or symptoms of the disease . The reported ratio of asymptomatic infections to VL clinical cases varies widely from 4∶1 in Kenya [3] to 50∶1 in Spain [4] . This variation is presumed to reflect differences in parasite virulence and host population characteristics , and may also depend on the study designs and on the tests used to define asymptomatic infection [1] . The methods more widely used in order to assess asymptomatic infection in the field are a ) serological assays that detect anti-Leishmania antibodies based either on the direct agglutination test ( DAT ) or the rK39-immunochromatographic test ( rK39-ICT ) and b ) Leishmanin Skin Test ( LST ) that measures cell-mediated immunity against Leishmania [5] , [6] . It is important to generate knowledge on the factors associated with asymptomatic infection for the optimal design and implementation of prevention and control strategies of VL , as asymptomatically infected individuals can harbor latent parasite and may act as reservoirs for new infection or become ill if immunosuppression occurs [7] , [8] . In northern Ethiopia , the prevalence of VL is steadily rising posing an increasing public health concern . The region has recently experienced epidemics in previously unaffected areas [2] . In 2005 , a kala-azar outbreak occurred in the district of Libo Kemkem in Amhara regional state , described by Alvar et al [9] . A case control study was conducted there in 2007 to evaluate the risk factors associated with the clinical form of the disease [10] . As it has been previously stated , the epidemiological determinants of clinical VL and sub clinical infection are not necessarily the same [11] but both are of interest to better understand the transmission of the disease . Thus , the aim of this study is to describe the factors associated with asymptomatic Leishmania infection among the villages with high incidence of VL in Libo Kemkem and Fogera in order to complement the already existing information on VL transmission in the area and help the Amhara regional health authorities to develop effective strategies to control the transmission of the disease .
The study was conducted during May–July 2009 in the districts ( weredas ) of Libo Kemkem and Fogera ( Amhara regional state , Ethiopia ) , see Figure 1 and Figure 2 . These are adjacent districts most affected by the outbreak of VL that occurred in 2005 [9] . In 2009 , the population numbered 198 374 and 226 595 in Libo Kemkem and Fogera , respectively . The economic status of the population is uniformly low . The districts are located in a black cotton clay soil flat plain ( 1800–2000 meters a . s . l . ) . Human activities related to intensive cultivation of teff , maize , beans , oilseeds , rice and cotton , have reduced the natural vegetation to scattered clumps of acacia trees . Most of the area is flooded during the rainy season ( July–September ) and dried up during the dry season ( November–March ) , resulting in deep cracks in the soil surface , which could turn into breeding sites for the putative vector Phlebotomus orientalis [12] , [13] . The study was carried out within the framework of a UBS Optimus Foundation funded project called Visceral Leishmaniasis and Malnutrition in Amhara State , Ethiopia , which among its specific objectives aimed to characterize nutritional , immunological , and parasitological aspects of the school age children population in the districts of Fogera and Libo Kemkem . Sample size was calculated according to project goals using an expected malnutrition prevalence of 20% and applying a design effect of 2 . Population sampling was carried out by a multi-staged cluster survey . Primary sampling units were sub-districts ( kebeles ) with high incidence of VL according to the 2008 register of the Addis Zemen VL Treatment Centre: Bura , Yifag Akababi and Agita from Libo Kemkem and Sifatra and Rib Gebriel from Fogera . Secondary sampling units were randomly selected villages ( gotts ) in each of the selected sub-districts . Third sampling units were randomly selected households in each of the villages . All children with reported age between 4 and 15 years living in the selected household at the time of the survey , and with no previous history of VL were included in the study , as long as they were asymptomatic ( absence of VL symptoms: fever for >2 weeks , in combination with either enlargement of spleen and/or liver , or weight loss ) . A blood sample was taken from the selected children in order to detect anti-Leishmania antibodies . The rK39-ICT ( Kalazar Detect Rapid Test , InBios International Inc . , USA ) was performed following the manufacturers' instructions . DAT with freeze-dried antigen ( ITMA-DAT/VL , Prince Leopold Institute of Tropical Medicine , Antwerp , Belgium ) was performed on blood-impregnated filter paper following the screening method according to the manufacturer's protocol . Titers ≥1∶3200 were considered positive . Leishmanin Skin Test was carried out using L . major antigen ( Leishmanin batch 123-2; Pasteur Institute , Iran ) . The test was read 48 hours later by the ballpoint pen method . An induration with an average of two perpendiculars ≥5 mm was considered as positive . All children were measured and weighed according to standard World Health Organization ( WHO ) procedures [14] . Wasting was defined as Body Mass Index ( BMI ) for age Z score ( BAZ ) <−2 , and stunting as Height for Age Z score ( HAZ ) <−2 according to the 2006 WHO Growth Standards for children ≤5 years and to the 2007 WHO Growth Reference for children >5 years respectively [15] . Care providers of the children were interviewed by trained health professionals using standardized questionnaires that included questions on demographics , household characteristics , child health , dietary habits and VL prevention behaviours . The questionnaires used were pretested and translated into Amharic , the local language . The primary outcome of interest was Leishmania “asymptomatic infection” defined as a positive result in rK39-ICT , DAT or LST and the absence of VL signs and symptoms ( fever for >2 weeks , in combination with either enlargement of spleen and/or liver , or weight loss ) . The serological tests ( rK39-ICT and DAT ) and the LST measure different types of immune response and are thus not likely to produce the same results . Therefore we created two secondary outcomes: a ) Seropositive: positive to rK39-ICT and/or DAT irrespective of the LST result and b ) LST Positive: positive to LST irrespective of the serostatus . We attempted to describe the factors associated with “asymptomatic infection” and then to differentiate the factors associated with the seropositivity and LST positivity by making independent analysis for the three outcomes described above . Since more than one child was sampled per household , the non-independence of children from the same household had to be taken into account . Therefore , potential risk factors were evaluated by odds ratios ( OR ) using random effects logistic regression with households defined as the group variable . To describe the amount of aggregation existing in VL asymptomatic infection within household units , the percentage of explained variance attributed ( rho ) was estimated in the adjusted models . Socioeconomic , behavioural , nutritional and dietary variables were assessed in univariate and multivariate analysis ( listed in Table S1 and Table S2 ) . Variables associated with each of the outcomes of interest at the p<0 . 10 level in the univariate analysis ( univariate random effects logistic regression ) were included in the multivariate regression procedure ( multivariate random effects logistic regression ) . The final model was obtained by using a manual backward stepwise procedure . Variables with a p-value ≤0 . 05 were retained in the model . Age and sex , considered biologically relevant , were kept in the model independently of their level of association . Final multivariate models included all variables for which adjusted estimates are presented . A p value less than 0 . 05 was considered statistically significant . Data analysis was performed using AnthroPlus v1 . 02 ( WHO , Geneva , Switzerland ) , SPSS version 18 . 0 ( SPSS Inc . , Chicago , Illinois , USA ) and STATA version 11 . 0 ( StataCorp LP , College Station , Texas , USA ) . The study was approved by the ethical advisory boards of Instituto de Salud Carlos III in Spain and the Armauer Hansen Research Institute and the Ethiopian National Ethical Review Committee in Ethiopia . Support letters were obtained from the Amhara regional state and the district Health Bureaus . All parents/guardians gave written informed consent prior to the enrolment of their children in the study . Assent was also obtained from children ≥11 years of age .
Table 2 and Table 3 summarize the individual and household characteristics that showed significant association in the univariate analysis with “asymptomatic infection” , seropositivity and LST positivity as defined in the Material and Methods section . The individual factors that showed a positive association with “asymptomatic infection” were: increasing age , male sex , sleeping outside , cattle herding and decreasing BAZ . In relation to household conditions an increasing number of people living in the household , having a past history of VL in the family , and owning sheep showed a direct and significant association . Living in a house with straw roof versus corrugated iron roof showed a direct association close to significance ( 1 . 92 [0 . 92 , 4 . 03] , p = 0 . 08 ) . Increasing age and being male were the only two individual variables that showed a positive and significant association with seropositivity . Cattle herding showed a positive and close to significance relationship ( p = 0 . 06 ) . In terms of household variables only if someone in the family had had VL in the past was directly and significantly associated with it . Owning sheep showed a positive but not significant association ( p = 0 . 07 ) . The individual variables that showed a direct association with LST positivity were the same as those for “asymptomatic infection” , except for BAZ . The use of bed net by a child , although not statistically significant suggested an inverse association ( p = 0 . 050 ) . In terms of household conditions , increasing number of people in the family and owning sheep showed a positive but not significant association ( p = 0 . 07 and p = 0 . 09 respectively ) . Table 4 shows the results of the multivariate logistic regression for “asymptomatic infection” , seropositivity” and LST positivity . The individual variables that kept in the model positively associated with “asymptomatic infection” after adjustment were: increasing age ( per year ) , being male and sleeping outside at any time of the year [OR ( 95% CI ) : 1 . 15 ( 1 . 03 , 1 . 29 ) , 2 . 56 ( 1 . 19 , 5 . 48 ) and 2 . 21 ( 1 . 03 , 4 . 71 ) respectively] . The household characteristics that remained positively associated with this same outcome after adjustment were: past history of VL in the family , living in a straw roofed house and if the family owned sheep [OR ( 95% CI ) : 2 . 92 ( 1 . 25 , 6 . 81 ) , 2 . 71 ( 1 . 21 , 6 . 07 ) and 4 . 16 ( 1 . 41 , 12 . 31 ) respectively] . Being male and past history of VL in the family were the only variables that kept direct and significant association with seropositivity after adjustment [OR ( 95% CI ) : 3 . 55 ( 1 . 31 , 9 . 63 ) , and 4 . 67 ( 1 . 59 , 13 . 75 ) respectively] . And increasing age and sleeping outside were the only factors positively and significantly associated with LST after adjustment [OR ( 95% CI ) : 1 . 19 ( 1 . 02 , 1 . 40 ) and 5 . 51 ( 1 . 77 , 17 . 20 ) respectively] . A significant level of aggregation within household units was found for the three outcomes analyzed , being strongest in the case of seropositivity . “Asymptomatic infection” ( rho = 32% , 95%CI: 11 to 65 , p = 0 . 012 ) , seropositivity ( rho = 44% , 95% CI: 18 to 73 , p = 0 . 004 ) and LST positivity ( rho = 40% , 95% CI: 13 to 76 , p = 0 . 022 ) . No significant association was found between any of the outcomes analysed and stunting; the number of meals consumed or consumption of animal source food products by the child the day before the survey; number of children in the household; age , sex , or education of the head of the household; wall construction material and condition , household electricity , radio or land owning , the existence of an animal shed , animal dung or a termite mound near the house , if the household owned dogs , cattle or chicken , the number of cattle , chicken or sheep owned by the house; the number of bed nets in the household or the house spraying status .
The prevalence of asymptomatic infection found in our study sample as well as the factors associated with it , differed depending on the outcome variable used for the analysis . The discordances observed between serology and LST have been discussed elsewhere [7] , [16]–[18] . The last LST screening in the area was conducted in 2005 as part of the outbreak assessment , and the prevalence of LST positivity was considerably higher than in our study , 34% for men and 26% for women [9] . The differences in design may account for this marked difference , as the study by Alvar et al was carried out in three villages reported to be highly affected ( all belonging to Bura sub-district ) and a fourth one selected from Shina sub-district but only a few kilometres away from Bura . Also , the cited study was conducted in a population with a different age distribution ( age range; 0 . 7–60 years ) with more than 50% of the sample being 15 years or older . Seventy per cent of the LST positive cases found in that study belonged to this older age group . Finally , the treatment interventions carried out in the area in the time period between the two studies could have reduced the transmission . A similar observation , a reduction of LST positivity in one year period from 30 . 1% to 17 . 3% , has been documented in an L . donovani focus of south Ethiopia [17] . The strong variation in the prevalence of asymptomatic infection among clusters highly endemic for VL is congruent with the spatial clustering observed in other studies of asymptomatic infection [19] , [20] and of clinical VL cases [21] , [22] . Notably , Bura , the kebele where the 2005 outbreak started , has maintained the highest prevalence ever since [9] . The increase in asymptomatic infection rate with age observed in our study area is also consistent with an endemic focus of VL , in spite of the low VL incidence situation reached after the outbreak [23] , [24] . The permanence of LST reactivity is thought to be a consequence of cumulative past exposure , thus prevalence typically rises with age [25] . The positive association between Leishmania infection and older age , as well as with male sex , has also been related to activities like cattle herding or sleeping outside , that imply an increased potential exposure to the sand fly vector , and that are culturally specific to male adolescents and male adults [19] , [26] . Our results would support this hypothesis , as cattle herding and sleeping outside were also identified in our study population as risk activities for asymptomatic infection and had previously been identified as risk factors for VL in South Ethiopia [27] and North Ethiopia ( in our study area ) as well [10] . The greater exposure to sand flies when herding livestock can be associated with the staying outside at dusk and dawn when the sand flies are supposed to be active [28] and also with an increased proximity to acacia trees . Acacia-Balanites forest growing on black cotton soils have been described as specific habitats with abundance of Phlebotomus orientalis [29] . Other studies have described the risk for humans to contract the infection by intruding into this type of environment [30] . Resting under acacia trees was identified as a risk factor for VL in our study area [10] and among our surveyed population 82% of the herder children reported resting under acacia trees while herding . However it is important to highlight that in the adjusted analysis only sleeping outside remained significant suggesting that this behaviour is associated with infection independently of the cattle herding activity . Poor nutritional status has been associated with a higher risk of developing visceral leishmaniasis in other studies [31]–[34] although to the best of our knowledge , an association with asymptomatic infection has not yet been described . In our findings a better nutritional status ( increasing BAZ ) appeared as protector for asymptomatic infection but only in the unadjusted analysis , so we can not conclude there is association between nutritional status , measured by anthropometry , and asymptomatic infection in our study population . The use of bed net appeared to be protective for LST positivity and the global “asymptomatic infection” outcome , but did not reach a significant association , which is in agreement with other studies in relation to asymptomatic infection [16] , [35] . The protective effect of bed net use towards visceral leishmaniasis remains unclear , with variable results depending on the setting and study [11] , [36] . The net conditions , nature of utilization and impregnation status were not assessed in our survey , and this can account for the lack of statistical significance found in our results . A previous case of VL within the household appeared strongly associated with seropositivity and maintained the association with the global “asymptomatic infection” outcome . Other studies have also identified living close to a previous case of VL as a risk factor for L . donovani asymptomatic infection [3] or for the clinical form of the disease [35] , [37] , [38] suggesting the importance of the house as a micro focus in the spread of the disease . The significant amount of aggregation within the households of the three outcomes analysed in this study would further support this hypothesis . This may be related to the ecologic location of the household , although there have been studies that have failed to relate house or surrounding ecological characteristics with it [3] , [39] . This house focalization may also be related to genetics or to the possibility of a domestic or peri-domestic transmission . It is important to highlight that the increased likelihood of asymptomatic infection among children with a past VL case in the family remained significant only for seropositivity and not for LST positivity , in concordance with findings of Bern et al in Bangladesh [35] . In one study conducted in Kenya , it was found that the association between LST positivity and previous VL cases in the family was significant only for women and young children , suggesting that women were exposed in and around the house and males , in addition , exposed elsewhere [40] . We tested this hypothesis by conducting separate analyses for male and female populations but results did not vary ( data not shown ) . The theory of transmission within the household is only a supposition as the existence of a domestic reservoir has not yet been well substantiated in Ethiopia . Furthermore , most reports regarding P . orientalis point out that the vector is rarely encountered inside the houses [41] , [42] . However in an entomological study conducted in eastern Sudan , it was reported that 75% of the P . orientalis captured were found indoors [43] indicating that some populations of the vector are more adapted to domestic habitats . This might be due to variations in construction materials used in building houses or to other microclimatic conditions [29] . The high altitude ( 1800–2000 mts ) of Libo Kemkem and Fogera makes the ecoclimatic conditions rather unique for what is known about sand fly ecology . Therefore there is an urgent need to identify and understand the behaviour of sand flies in the area in order to come up with consistent conclusions . Living in a straw roofed house versus an iron thatched one was the only house characteristic associated with asymptomatic infection . It could be related to socioeconomic status or to the potential of straw roofs to provide resting places for the sand fly that would increase its survival and abundance . Mud-type houses have been identified as risk factors for VL or asymptomatic infection before and have been associated with better living conditions or with the vector preference for mud crack walls for breeding and resting [22] , [27] , [38] , [44] . However , regarding P . orientalis more studies are needed , as the few extant studies in the literature point out to an exophagic behaviour of the vector , ill suited with this hypothesis [41] . In relation to domestic animals the only significant association found was with owning sheep . The positive correlation of disease and the presence of sheep has already been described [19] , [22] , and has been explained by the greater biomass and the accumulation of animal dung that may be attractive to the sand flies , drawing the vectors into closer association with humans . However , the number of sheep , the presence of other livestock , or animal dung near the house did not show a significant association in our study . On the other hand , sheep herding can be associated to an increased contact to Acacia trees due to the fact that sheep are fed on Acacia fruits and leaves [45] . Our personal observation during surveys was that herders shake Acacia trees in order to make fruits fall , thus disturbing the suspected vector habitat and increasing the probabilities of being bitten . One important limitation of our study is its cross sectional nature , which limits the making of causal inferences between the analysed factors and the infection . However , we believe the results are of interest in order to contribute to the existing knowledge in the area , and in order to support future analytical studies . Our conclusion is that sleeping outside and selected housing factors were associated with higher rates of asymptomatic infection and our recommendation is that the behaviour of P . orientalis , the putative vector in the area should be further studied in order to clarify the role of domestic animals in the transmission cycle and in order to propose possible entomological interventions . | Visceral leishmaniasis is a vector borne disease that can be fatal if left untreated . Its prevalence is steadily rising in northern Ethiopia posing a public health challenge in the region . We conducted a study on the factors associated to asymptomatic infection in Libo Kemkem and Fogera , Amhara regional state , where little is known about Leishmania transmission . Sleeping outside was identified as a risk activity so measures towards it are recommended . Our results also showed a geographical clustering and a household focalization of the infection although the reasons behind it are not clearly understood . More entomological studies are needed in order to clarify the vecto's behaviour in the area . Individuals living in houses that owned sheep were more likely to be infected but no association was found with other domestic animals like cattle chicken or dogs . These results add up to the debate found in the literature regarding the role of domestic animals in the transmission of Leishmania in different regions of the world . No specific recommendation should be given until the exact role of the domestic animal in the transmission cycle is clearly understood . | [
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"disease... | 2012 | Factors Associated with Leishmania Asymptomatic Infection: Results from a Cross-Sectional Survey in Highland Northern Ethiopia |
CD36 is a platelet membrane glycoprotein whose engagement with oxidized low-density lipoprotein ( oxLDL ) results in platelet activation . The CD36 gene has been associated with platelet count , platelet volume , as well as lipid levels and CVD risk by genome-wide association studies . Platelet CD36 expression levels have been shown to be associated with both the platelet oxLDL response and an elevated risk of thrombo-embolism . Several genomic variants have been identified as associated with platelet CD36 levels , however none have been conclusively demonstrated to be causative . We screened 81 expression quantitative trait loci ( eQTL ) single nucleotide polymorphisms ( SNPs ) associated with platelet CD36 expression by a Massively Parallel Reporter Assay ( MPRA ) and analyzed the results with a novel Bayesian statistical method . Ten eQTLs located 13kb to 55kb upstream of the CD36 transcriptional start site of transcript ENST00000309881 and 49kb to 92kb upstream of transcript ENST00000447544 , demonstrated significant transcription shifts between their minor and major allele in the MPRA assay . Of these , rs2366739 and rs1194196 , separated by only 20bp , were confirmed by luciferase assay to alter transcriptional regulation . In addition , electromobility shift assays demonstrated differential DNA:protein complex formation between the two alleles of this locus . Furthermore , deletion of the genomic locus by CRISPR/Cas9 in K562 and Meg-01 cells results in upregulation of CD36 transcription . These data indicate that we have identified a variant that regulates expression of CD36 , which in turn affects platelet function . To assess the clinical relevance of our findings we used the PhenoScanner tool , which aggregates large scale GWAS findings; the results reinforce the clinical relevance of our variants and the utility of the MPRA assay . The study demonstrates a generalizable paradigm for functional testing of genetic variants to inform mechanistic studies , support patient management and develop precision therapies .
Cardiovascular disease ( CVD ) remains the number one cause of death globally [1] . Myocardial infarctions ( MI ) are acute events in CVD which are frequently the proximal causes of death or severe disability which are the result of platelet-rich thrombi [2] . Genome wide association studies ( GWASs ) have identified numerous common genetic variants associated with the risk of CVD and platelet function parameters , but these variants are usually not causative due to the resolution of the genotyping platforms used and genetic linkage . One of the genes identified by GWAS as associated with platelet count , lipid levels . and CVD is the platelet oxidized LDL ( oxLDL ) receptor , CD36 [3–5] . CD36 is a transmembrane protein belonging to the class B scavenger receptor family expressed in platelets and variety of other cells [6–8] . It binds to many ligands such as oxidized phospholipids ( oxPL ) and oxidized low-density lipoprotein ( oxLDL ) long-chain fatty acids [9] . In platelets , CD36 interaction with oxLDL and thrombospondin-1 ( TSP1 ) triggers MAP and Src family kinase dependent signaling events leading to platelet activation , [10 , 11] which also lead to increase in P-selectin expression and αIIbβ3 activation [10] . Deletion of CD36 in mice fed a high fat diet results in attenuation of the pro-thrombotic state and platelet hyper-activity [10] . CD36 deficiencies have been identified which result in increased risk of cardiomyopathy , hyperlipidemia and insulin resistance [12–15] . In type I deficiency , monocytes and platelets lack CD36 expression , whereas in type II only platelets lack CD36 expression . CD36 deficiency is more frequent in black and Asian populations . Our platelet transcriptomic data also show that platelet CD36 RNA levels are lower in the black population and in women [16 , 17] . The molecular mechanisms behind CD36 deficiency have been attributed to variants causing defects in protein maturation or frameshift , resulting in an absence of protein [14 , 18] . Among subjects without CD36 deficiency , there is a wide range of platelet CD36 surface expression and the level of CD36 correlated with reactivity to oxLDL [19] . Many genetic variants have already been reported to be associated with platelet CD36 expression , however , these variants span a large linked genomic area and no functional analysis has been carried out [19 , 20] . We have previously reported platelet expression Quantitative Trait Loci ( eQTLs ) that associate single nucleotide polymorphisms ( SNPs ) with platelet RNA levels , indicating genetic variability effecting gene expression [21] . CD36 is one of the 612 platelet-expressed RNAs whose abundance has significant genotypic associations . 81 eQTL SNPs located within a +/- 100kb window of the CD36 gene are associated with platelet CD36 mRNA levels at a significance of P<1x10-6 , spanning a range of 118kb . We hypothesized that a parallel screening method would be more efficient and cost-effective to identify causal variants instead of a one-at-a-time approach . We used a massively parallel reporter assay ( MPRA ) to screen the 81 platelet eQTLs associated with CD36 mRNA . We developed new statistical methods for MPRA analysis , and we were able to identify rs2366739 and rs1194196 as functional variants that alter transcriptional regulation . We further tested these MPRA-functional variants , showing significant transcription shift between the reference and alternate alleles by luciferase assays , electromobility shift assays ( EMSA ) and using CRISPR/Cas edited stable cell lines . Finally , we used the Phenoscaner GWAS aggregation tool to reinforce the clinical relevance of our functional variants . Using these approaches , we have identified genetic variants that modulate platelet CD36 expression and have clinical associations .
We have previously published the results of a cis-eQTL analysis of platelet gene expression [21] . SNPs found to be associated with platelet CD36 mRNA expression are indicated by diamonds on the Manhattan plot in Fig 1 . Ghosh et al . have also looked for associations between CD36 SNPs and CD36 protein expression [19] . SNPs identified in that report are indicated in Fig 1 by squares , and SNPs that were identified both by our eQTL study and Ghosh et al . are indicated by upside-down triangles . Several CD36 SNPs have been identified in GWAS studies to associate with platelet count or volume . The GWAS-identified SNPS rs6961069 , rs13236689 , rs2177616 , and rs11764390 are also platelet CD36 eQTLs and are indicated by triangles in Fig 1 [4 , 22 , 23] . rs139761834 ( Fig 1 , circle ) was identified by GWAS but not by eQTL analysis [23] . The genomic region containing these variants encompasses the 5’ end of the CD36 gene and upstream sequence and is highly linked as indicated by the linkage disequilibrium plot in the bottom panel of Fig 1 . Given that most data on CD36 deficiency and expression has been obtained from Japanese subjects , D’ values were calculated using the 1000 Genomes JPT population . This strong linkage makes identification of the functional variant difficult , and therefore functional analysis requires experimental testing of individual SNPs . The large genomic span and the number of CD36 phenotype-linked variants necessitated a highly parallel approach for functional testing . We generated a library of plasmids in which a unique 10bp barcodes located downstream to a luciferase cassette were transcribed under the control of a 150bp genomic fragment containing a CD36 platelet eQTL SNP . Each allele of each variant is associated with 40 unique barcodes in order to give high statistical power for detecting variant function despite variation in the NGS outputs . Successful conduction of a MPRA experiment requires high transfection efficiency to allow for sufficient expression of barcode diversity . We compared the RNA-seq gene expression profiles of several hematopoietic cell lines ( derived from ArrayExpress ( https://www . ebi . ac . uk/arrayexpress/ ) accession number E-MTAB-4101 ) to RNA-Seq data from cultured megakaryocytes ( derived from Blueprint Epigenome Data [24] ) . All comparisons were significant at P<0 . 0001 and the Spearman correlation coefficient ranged from 0 . 658 to 0 . 720 ( Table 1 ) . We ultimately chose to utilize K562 cells due to their myelogenous origin , transfection efficiency , the comparable expression profile similarity to other cell lines and megakaryocytes , and their prior successful use in MPRA experiments [25] . Transcription activity driven by each variant was then measured by quantifying RNA barcodes output after they have been “normalized” or jointly modeled against the plasmid DNA library barcode inputs . An overview of MPRA protocol is presented in Fig 2 . We employed two statistical methods to analyze the result of the MPRA: a traditional method that involves computing variant activities defined by a ratio transformation of mRNA to DNA input and a second Bayesian method . The traditional method normalizes the counts for sample depth , removes barcodes with low representation in the plasmid library , and computes the activity as log ( mRNADNA ) of each barcode in each allele in each transfection , and then uses a t-test and false discovery rate correction to compare the mean activity levels of alleles for each SNP . This approach yields 14 hits with Q < . 05 , including nine of the 10 controls ( Table 2; Fig 3A and S1 Fig ) and five CD36 SNPs: rs2366739 , rs940542 , rs1093831 , rs11464747 , and rs6467258 ( Table 2; Fig 3B and S1 Fig ) . MPRA activities can occasionally defy the normality assumption underlying the t-test , [26] so we also employed the non-parametric Mann-Whitney U-test , under the same frequentist methodologic paradigm as the t-test approach . Analyzing the transcription activity level with a U-test revealed an additional four significant variants , rs1194196 , rs6961069 , rs819456 , and rs819457 ( Table 2; Fig 3C and S1 Fig ) . We sought to avoid two statistical limitations that lead to information and power loss in the MPRA experiment using the traditional analysis approach . First , transforming the data with a ratio removes the ability to model systematic effects of the DNA and RNA libraries . Second , discarding barcodes with low or 0 counts discards data that may be informative . Therefore , we also employed a Bayesian count model of the data generating process that models the NGS reads of each barcode observed from sequencing the plasmid library and from each transfection experiment as arising from coupled negative binomial distributions . The means of the negative binomial distributions are proportional to the depth of the sequencing of each sample and , in the case of RNA samples , the mean of the barcode’s DNA read count . Empirical gamma priors on the negative binomial parameters were estimated marginally across all SNPs in the assay . The log difference in the depth- and DNA-normalized RNA means gives a quantity comparable to the difference in mean activity ( i . e . the ratios ) analyzed under the t-test-based method . Thus , this model provides a posterior on transcription shift for each SNP after directly accounting for more sources of variation and more data from the MPRA experiment than the traditional approach . We identify a SNP in question as a functional hit if a 95% credible interval for the posterior distribution of the transcription shift excludes 0 . This process yields 19 hits , including the same nine of the ten controls and ten CD36 SNPs , the nine listed above plus an additional variant , rs1093833 ( Table 2; Fig 3D and S1 Fig ) that was not identified by the frequentist approaches . As shown in Fig 1 , ( MPRA positive hits indicated by X’s ) these SNPs are in high LD with one another , indicating close physical proximity in what is likely the regulatory region of the CD36 gene . The complete analysis results of the tested MPRA variants and controls is given in S1 and S2 Tables . To verify the transcription shifts identified by the MPRA , we tested three of the controls , the two most significant MPRA hits by t-test ( rs2366739 and rs940542 ) , the additional two most significant MPRA hits identified by U-test ( rs1193196 and rs819456 ) , and the additional significant MPRA hit identified by Bayesian analysis ( rs1093833 ) by reporter assay . Reporter plasmids containing reference or alternate alleles of the eQTLs were transfected into K562 cells and assayed after 48 hours for luciferase and β-gal expression . We first investigated the activity of each control sequence ( ALAS2-1 , 2 and 3 ) containing original or disrupted GATA1 binding site . As predicted and shown previously the sequences with original binding site exhibited more enhancer like activity by luciferase expression than the sequence with disrupted ( Alt ) binding site ( Fig 4A ) [25] . Because eQTLs rs2366739 and rs1194196 are within 21 base pairs of each other and in high linkage disequilibrium we constructed single oligos which contains either reference ( T-A for rs2366739-rs1194196 ) or alternate alleles ( C-T ) for both eQTLs . These genotypes account for 96% of the observed haplotypes from all populations . Out of the five tested constructs , rs819456 and rs2366739-rs1194196 showed significant transcriptional difference between their reference vs alternate allele as depicted by the luciferase levels ( Fig 4B ) . The rs2366739-rs1194196 results are in agreement with our platelet eQTL data and whole blood eQTL data from Jansen et al . that indicate that the ‘C’ allele of rs2366739 is associated with lower levels of CD36 mRNA ( Fig 4C ) [21 , 27] . Overall expression from the rs819456 constructs was higher than other constructs but the direction of the difference between alleles ( higher in the reference , Fig 4B ) was opposite to that of the MPRA results ( lower in the reference ( Fig 3B ) ) . Finally , to test the transcriptional activity in a system more closely related to megakaryocytes , we repeated the luciferase assay of the rs2366739-rs1194196 construct in Meg-01 chronic myelogenous leukemia cells . In this system , the difference in transcriptional potency between the two alleles was consistent with the results in K562 cells showing an approximate 20% reduction in transcription between the two alleles ( Fig 4D ) . rs2366739 has been described as an CD36 eQTL not just in our platelet data but in whole blood data from Võsa et al . ( P = 1 . 3 x 10−267 ) [28] . In addition rs2366739 has been associated with DNA methylation levels ( P = 6 . 51 x 10−81 ) [29] . These results in addition to the high significance and directional agreement of the rs2366739-rs1194196 luciferase and MPRA results lead us to pursue the rs2366739-rs1194196 locus in further tests . One of the mechanisms by which gene expression is regulated is the binding of transcription factors to regulatory elements . To test if the difference in transcription between TA and CT alleles of the rs2366739-rs1194196 constructs is due to alteration in transcription factor binding affinity , we performed an electrophoretic mobility shift assay ( EMSA ) to compare binding of K562 nuclear extracts to probes derived from the two different haplotypes . The results show formation of a DNA:protein complex with twice as much affinity to the TA genotype probe than to the CT genotype probe ( Fig 5 ) . To confirm the locus containing rs2366739 and rs1194196 regulates CD36 expression , we generated K562 cell lines with deletion of 573 basepairs containing this region using CRISPR/Cas9 . The deletion was confirmed with PCR comparing clones transfected with sgRNAs to those transfected with vectors with no sgRNA ( Fig 6A , lane C ) . Clones labeled WT do not contain a deletion whereas clones labeled KO were successfully altered . To determine the effect of this deletion on CD36 RNA expression , CD36 transcript levels were measured by qRT-PCR . In the cells with the rs2366739-rs1194196 locus removed , CD36 mRNA was ~13 times greater than the clones with the region intact ( Fig 6C ) . We also analyzed the effect of this deletion in Meg-01 cells . We were only able to obtain clones containing heterozygous knockouts ( Fig 6B ) . However , like in K562 cells , this resulted in a ~39-fold increase in CD36 mRNA levels ( Fig 6C ) . This supports the evidence that this genomic region identified by MPRA regulated expression of the CD36 gene . To assess the clinical relevance of our findings we used the PhenoScanner tool , which aggregates large scale GWAS findings . We re-identified the rs2366739 variant in the CD36 associations and we found it to be strongly associated with platelet volume and count but not with phenotypes unrelated to platelet activity . These results reinforce the clinical relevance of our variants and the utility of the MPRA assay .
The expression of CD36 has been actively studied since the identification of a deficiency in healthy Japanese and US donors [30] . CD36 deficiency has been divided into two types: Type I in which neither platelets nor monocytes express surface CD36 and Type II in which only platelets lack expression [31] . Lack of CD36 leads to numerous cellular phenotypes including defective uptake of long chain fatty acids by the myocardium[32 , 33] and altered lipid profiles [34 , 35] . Lack of CD36 has also been associated with altered foam cell formation in both humans and mice [36 , 37] . Even in non-deficient patients a wide range of CD36 expression has been observed and this variation has been associated with the platelet response to oxLDL [19 , 38] . Five genetic causes of type I deficiency have been identified , two of which lead to alterations in post-translation modification or surface trafficking , the other three which lead to frame-shift mutations [18 , 39–41] . The basis of type II deficiency remains unclear . Mechanisms behind the broad range of non-deficient expression has been explored previously . For example Ghosh et al . previously identified a number of SNPs that are associated with platelet CD36 levels and Masuda explored surface levels in individuals heterozygous for the deficiency mutations mentioned above [19 , 38] . However , given the tightly linked nature of the locus ( Fig 1 ) , neither of these studies identified functional variants . Our data presented here represents the first comprehensive analysis and testing of genetic variants associated with CD36 mRNA expression . We tested 81 variants associated with platelet CD36 mRNA levels , some of which overlap with variants previously associated with surface levels , by MPRA . Of these variants , rs2366739 and rs1194196 , which are within 21 base pairs of each other , were identified by MPRA and validated by ( 1 ) altering expression of a linked reporter gene , ( 2 ) altering protein binding in a gel-shift assay , and ( 3 ) altering endogenous CD36 expression when the locus containing these variants was deleted by genome editing . Importantly , rs2366739 has previously been associated with both platelet count ( P = 9 . 13 x 10−10 ) and platelet volume ( P = 5 . 27 x 10−11 ) [22] . Taken together , we found that the MPRA analysis refined the region of CD36 responsible for gene expression and within this region the MPRA distinguished specific GWAS hits for platelet-associated phenotypes . This result emphasizes the utility of the MPRA to clarify and refine association analyses in highly linked regions . The analysis methods employed for our CD36 MPRA are another important contribution of this work . We applied t- and U-tests that have been employed in prior MPRA studies , but we also introduced a new and more comprehensive Bayesian approach . Our new method recapitulates the findings of the prior methods , but also identifies a variant that was missed by the prior approaches . A key advantage of our new statistical method is a generative stochastic model that probabilistically accounts for the discrete nature of NGS count data as well as sources of variation in the MPRA experiment without having to discard zero counts . S4 Fig shows a Kruschke diagram of the generative process considered by the model . The sources of variation addressed include variation in the barcode abundances in the cDNA library as well as other factors . Furthermore , the use of empirical priors provides estimate shrinkage; noisy parameter estimates are shrunken towards more moderate levels observed throughout the rest of the assay . This process helps eliminate false positives without the heavy statistical burden of multiple testing correction procedures like false discovery rates . We have previously studied the statistical power of MPRA experiments using the standard approaches [26] . Although the prior methods were at least partially successful to analyze MPRA data , our Bayesian model appears both practical and more powerful . Therefore , our paper demonstrates effective statistical improvements to analysis of MPRA studies . This approach may be particularly important in larger scale genome wide MPRA studies , and more work is warranted to improve the cost-effectiveness as well as the discovery potential of MPRA assays . One of the weaknesses of this study is that we have been unable to identify the DNA-binding protein factor whose binding is altered by the variants . The rs2366739-rs1194196 is located in a genomic locus that contains ChIP-Seq signals for Histone H3K27 acetylation and is in a DNA hypersensitive region in primary and cultured hematopoietic stem cells . [42] However ChIP-Seq data of specific transcription factors in CD34 cells and megakaryocytes is limited and we have not been able to identify a sequence-specific factor bound to the region . We have analyzed the sequence using the transcription factor binding prediction algorithm JASPAR [43] and found predictions for the well-studied megakaryocytic transcription factors GATA1/2/3 and Gfi1/Gfi1b on the TA haplotype but not CT . [44 , 45] Interestingly these two transcription factor families , GATA and Gfi1 , have opposite functions; GATA factors are transcriptional activators while Gfi1 and Gfi1b are transcriptional repressors . This suggests that these two factors may regulate CD36 expression in a complex manner that is affected by genotype . The dual nucleotide changes assayed in Figs 4 and 5 indicate that the TA haplotype results in higher transcriptional activity and an enhancement of protein binding , suggesting that a positive regulatory factor is more readily bound to the TA haplotype . However , deletion of the locus resulted in enhanced CD36 expression in both K562 and Meg-01 cells , suggesting a negative regulatory activity also exists . There are differences between these experiments which can contribute to understanding our observations: The luciferase and EMSA experiments are performed in vitro using 70bp of genomic sequence surrounding rs2366739- rs1194196 , either by itself as an EMSA probe or cloned into a luciferase vector . The genomic deletion is a 573bp deletion of DNA in a genomic chromatin context . In the genomic context , the locus is located 56 kbp and 92 kbp from the two transcriptional start sites of CD36 . In the plasmid context , the transcription start site is immediately downstream from the cloned fragment . We hypothesize that additional negative regulatory factors bind to genomic DNA , outside the limited context used in MPRA and the 70bp fragment tested by luciferase and EMSA ( S2 Fig ) . Therefore , in experimental conditions containing only the 70bp region , a positive regulatory factor determines transcriptional/binding activity . But in the genomic context , deletion of the 573bp fragment results in the loss of both positive and negative factors , resulting in a net increase in transcription , perhaps driven by enhancers more proximal to the promoter . More work is required to further investigate this hypothesis . Currently , more human genetic studies are moving beyond associations of genotypes with phenotypes to seeking the molecular mechanisms behind the variants responsible for the observed traits . Mechanistic understanding of genetic variants will provide better understanding of the observed physiology , allow for more precise biomarkers , and identify potential new therapeutic targets . Given the large number of variants potentially associated with a trait in highly linked genomic regions such as CD36 , high-throughput methods are necessary to efficiently test and identify functional polymorphisms in an unbiased manner . Our identification of the genetic locus responsible for inter-individual variation in non-deficient CD36 expression opens new areas of investigation into the link between this locus and platelet function , serum lipid levels , and atherosclerosis .
K562 and Meg-01 cells were obtained from the American Tissue Culture Collection ( ATCC ) K562 ( CCL-243 ) and Meg-01 ( CRL-2021 ) cells from ATCC were maintained in RPMI 1640 media ( Invitrogen , CA 10-040-cv ) containing penicillin-streptomycin and 10% FBS . The MPRA design was based on the method previously published ( A graphical summary is presented in Fig 2 ) [46] . To design the CD36 MPRA library , we used a p-value threshold of p < 1x10-6 to select the expression quantitative trait loci ( eQTLs ) most highly associated with CD36 expression in the PRAX study surrounded by 150bp of hg38 genomic context [21] . After discarding 5 eQTLs that contained digestion sites for restriction enzymes used in the library preparation in their genomic context , this yielded a set of 81 CD36 SNPs to assay . We also included 10 SNPs previously identified in the literature as directly affecting ALAS2 , HBG2 , PKRRE , and URUOS expression as a set of positive controls ( S3 Table ) [47 , 48] . We synthesized 40 oligonucleotide replicates per allele ( Agilent , Santa Clara , CA ) , each uniquely tagged with inert 10bp barcodes which followed the design criteria stipulated in Melnikov et al . [49] . The library of oligonucleotides was amplified using emulsion PCR and the primers 5’-TGCTAAGGCCTAACTGGCCAG-3’ and 5’-CTCGGCGGCCAAGTATTCAT-3’ which also added additional sequence containing SfiI restriction enzyme sites to each end . After each oligo was directionally cloned into pMPRA1 ( Addgene , Cambridge , MA ) using the SfiI sites , a minimal promoter and luciferase cassette derived from pNL3 . 2 ( Promega , Madison , WI ) was inserted in between the genomic sequences and the barcode using KpnI and XbaI sites . This library of plasmids was transfected into K562 cells and then RNA was harvested 48 hours later . After reverse transcription with a polyT primer , three separate amplifications of the cDNA were performed to generate RNA sequencing libraries . The barcodes contained in the MPRA plasmid library were subjected to two separate amplifications to generate DNA sequencing libraries . RNA and plasmid barcode expression was quantified by next generation sequencing on an Illumina MiSeq in the Children’s Hospital of Philadelphia sequencing core . After extraction from the fastq files , barcodes with a quality of Q>30 at every base was counted . RNA barcode counts were analyzed in conjunction with the DNA barcode counts to control for variances in barcode abundances introduced by library generation . Quality control data concerning the sequencing libraries are presented in S4 Table and Fig 7 and S3 Fig . Both frequentist ( t-tests and U-tests ) and Bayesian analyses were applied to identify variants that caused alterations to transcription activity by use of RNA-to-DNA ratios to examine allelic differences . Analysis of the barcode counts proceeds by computing the MPRA activity of each barcode as the log-ratio of the depth-normalized RNA counts to depth-normalized DNA counts and each variant’s corresponding “transcription shift” . The transcription shift of a variant is defined as the difference in activity between the alternate and reference alleles . The application of traditional frequentist tests to MPRA activities has been previously described [25 , 26] . The novel Bayesian analysis models the barcode count data using negative binomial distributions with empirical gamma priors ( Fig 8 ) , this analysis method provides greater sensitivity than traditional methods while retaining specificity . We designed and ordered oligonucleotides ( IDT-DNA , Coralville , IA ) containing the candidate MPRA-functional SNPs and 40bp of flanking genomic sequence ( S5 Table ) . The amplified sequence was inserted into nano-luciferase containing plasmid pNL3 . 2 ( Promega , Madison , WI ) using HindIII and XhoI ( ThermoFisher , Waltham , MA ) restriction sites . The sequence was confirmed by sequencing . Three independent preparations of reporter plasmids and β-gal expression plasmids were cotransfected in K562 cells or Meg-01 cells and luciferase assay was carried out after 48 hours using Nanoglo luciferase kit ( Promega ) and normalized to ß-gal expression measured using assay reagent ( ThermoFisher ) . Nuclear extracts from K562 cells were isolated using the NE-PER Nuclear and Cytoplasmic Extraction Kit ( ThermoFisher ) . 70 base pair sequences containing either the reference alleles for rs2366739 and rs1194196 ( referred to as TA ) or alternate alleles ( referred to as CT ) were amplified by PCR using MPRA plasmid library as template . Digoxigenin ( DIG ) labeled nucleotides ( Roche , Basel , Switzerland ) were used to create amplified sequences with DIG labeled base pairs . The sequences were purified by agarose gel electrophoresis and the QIAEX II Gel Extraction Kit ( Qiagen , Hilden , Germany ) . 10μg of nuclear extract was incubated with DIG labeled probes in buffer containing 10% glycerol , 20 mM HEPES , 30 mM KCl , 30 mM NaCl , 3 mM MgCl2 , 1 mM DTT . 1 μg of Poly dI-dC was added to reduce nonspecific binding . The reaction was carried out for 30 mins on ice . The sample was mixed with 10X orange loading dye ( Licor , Lincoln , NE ) and loaded on 6% acrylamide gel and ran for 4–5 hours with 0 . 5% TBE buffer . The DNA-protein complex was transferred on positively charged Biodyne nylon membrane ( Pall Industries , Fort Washington , NY ) using 0 . 5% TBE for 45 minutes . The membrane was incubated in blocking solution for 30 mins at RT , followed by Anti-Digoxigenin-AP antibody containing blocking solution for 30 mins at RT . The membrane was then washed twice for 15 minutes each using washing solution , visualized using chemiluminescence , and quantified . To generate genomic deletion mutants , the CRISPR/Cas9 system was used as previously reported [50] . Two guide RNAs ( sgRNA ) flanking 573 base pairs containing rs2366739 and rs1194196 were designed ( IDT DNA ) . The design of sgRNA pairs for targeting and prediction of off-target sites were based on online tools: CRISPR Design ( http://crispr . mit . edu/ ) and CRISPOR ( http://www . crispor . org ) [51] . Two guide RNAs , 5'-TACCCCCATTGTATCTATCTAGG-3’ and 5'- CTACAGTAAATACACTTGTCAGG -3’ were used to delete the 573 basepair region . Pairs of complementary DNA oligos ( IDTDNA , Coralville , IA ) were individually phosphorylated with T4 polynucleotide kinase ( NEB , Ipswitch , MA ) and then annealed . Each DNA oligo duplex had 5' overhangs ( forward: ACCG , reverse: AAAC ) designed to be directly cloned into the BbsI or BsaI-digested and dephosphorylated AIO-GFP ( Cas9 ) vector using the Quick Ligation Kit ( NEB ) . The first and second sgRNA was cloned into the BbsI and BsaI sites , respectively , and confirmed by colony PCR and sequencing . The plasmid was transfected in K562 using Lipofectamine2000 ( ThermoFisher ) or Meg-01 with Nucleofection . ( Lonza , Basel , Switzerland ) . After 24 hours , the GFP positive cells were sorted by flow cytometry and individually seeded in a 96 well plate . Single colonies were expanded further and a cell line was established from a single clone . Deletion was confirmed by PCR and sequencing . Total RNA was isolated using Trizol Reagent ( ThermoFisher ) . 3μg total RNA was used for first strand cDNA synthesis with the SuperScript III First-Strand Synthesis System ( ThermoFisher ) . To evaluate relative expression levels of mRNAs , we performed qRT-PCR with the Power SYBR Green PCR master mix ( Life Technologies , Carlsbad , CA ) normalized to Actin . We carried out real time PCR reaction and analyses in 384-well optical reaction plates using the CFX384 instrument ( Bio-Rad , Hercules , CA ) . | Platelets are anucleate cells that are best known as regulators of vascular hemostasis and thrombosis but also play important roles in cancer , angiogenesis , and inflammation . CD36 is a platelet surface marker that can activate platelet in response to oxidized low density lipoprotein ( oxLDL ) . CD36 has been associated with numerous cardiovascular traits in human including blood lipid levels , platelet count , and cardiovascular disease prevalence in human genetic studies . Human variability in platelet CD36 levels are associated with the platelet response to oxLDL . However , the genetic mechanisms responsible for the variability of CD36 levels are unknown . We examined 81 genetic variants associated with CD36 levels for functionality using a high-throughput assay . Of the ten variants that were identified in that assay , one doublet , rs2366739 and rs1194196 , were confirmed using additional molecular and cellular assays . Deletion of the genomic region containing rs2366739 and rs1194196 resulted in overexpression of CD36 in a cell culture system . This finding indicates a control locus which can serve as a potential target in modulating CD36 expression and altering platelet function in cardiovascular disease . | [
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"platel... | 2019 | Functionalization of CD36 cardiovascular disease and expression associated variants by interdisciplinary high throughput analysis |
Systemic lupus erythematosus ( SLE ) is a genetically complex disease with heterogeneous clinical manifestations . Recent studies have greatly expanded the number of established SLE risk alleles , but the distribution of multiple risk alleles in cases versus controls and their relationship to subphenotypes have not been studied . We studied 22 SLE susceptibility polymorphisms with previous genome-wide evidence of association ( p<5×10−8 ) in 1919 SLE cases from 9 independent Caucasian SLE case series and 4813 independent controls . The mean number of risk alleles in cases was 15 . 1 ( SD 3 . 1 ) while the mean in controls was 13 . 1 ( SD 2 . 8 ) , with trend p = 4×10−128 . We defined a genetic risk score ( GRS ) for SLE as the number of risk alleles with each weighted by the SLE risk odds ratio ( OR ) . The OR for high-low GRS tertiles , adjusted for intra-European ancestry , sex , and parent study , was 4 . 4 ( 95% CI 3 . 8–5 . 1 ) . We studied associations of individual SNPs and the GRS with clinical manifestations for the cases: age at diagnosis , the 11 American College of Rheumatology classification criteria , and double-stranded DNA antibody ( anti-dsDNA ) production . Six subphenotypes were significantly associated with the GRS , most notably anti-dsDNA ( ORhigh-low = 2 . 36 , p = 9e−9 ) , the immunologic criterion ( ORhigh-low = 2 . 23 , p = 3e−7 ) , and age at diagnosis ( ORhigh-low = 1 . 45 , p = 0 . 0060 ) . Finally , we developed a subphenotype-specific GRS ( sub-GRS ) for each phenotype with more power to detect cumulative genetic associations . The sub-GRS was more strongly associated than any single SNP effect for 5 subphenotypes ( the above plus hematologic disorder and oral ulcers ) , while single loci are more significantly associated with renal disease ( HLA-DRB1 , OR = 1 . 37 , 95% CI 1 . 14–1 . 64 ) and arthritis ( ITGAM , OR = 0 . 72 , 95% CI 0 . 59–0 . 88 ) . We did not observe significant associations for other subphenotypes , for individual loci or the sub-GRS . Thus our analysis categorizes SLE subphenotypes into three groups: those having cumulative , single , and no known genetic association with respect to the currently established SLE risk loci .
Systemic lupus erythematosus ( SLE ) is a debilitating autoimmune disease affecting multiple organ systems and characterized by the production of multiple autoantibodies . It is genetically complex , with an estimated sibling risk ratio s of 8–29 and heritability greater than 66% [1] . It is also an extremely heterogeneous disease , with patients meeting any 4 out of 11 American College of Rheumatology ( ACR ) criteria – which include such disparate manifestations as renal disease , arthritis , hematologic disorders , and skin manifestations – classified as having SLE . As these disparate manifestations have great impact on the disease course , understanding their specific genetic etiology is of prime importance . Until 2008 , only a handful of genetic loci affecting SLE susceptibility had been identified and reproduced ( e . g . HLA-DRB1 , FcγR2A , PTPN22 , IRF5 , STAT4 ) via candidate-gene studies [2] . The advent of genome-wide single nucleotide polymorphism ( SNP ) genotyping technology and subsequent recent genome-wide association studies ( GWAS ) have greatly expanded the number of established SLE risk alleles [3]–[7] to over twenty; most are located in immune-related pathways such as antigen presentation , B- and T-cell receptor signaling , and interferon signaling [2] . Furthermore , few relationships between SLE clinical manifestations and individual risk alleles have been reported , such as the STAT4 gene variant rs7574865 with production of antibodies to double-stranded DNA ( anti-dsDNA ) and age at diagnosis [8] and the association between anti-dsDNA production and the HLA-DRB1 *1501 ( DR2 ) allele [9] . However , the distribution of multiple risk alleles in affected and unaffected individuals and the relationship of this distribution to clinical manifestations of SLE have not been studied . Recent studies have begun to characterize cumulative associations of multiple risk alleles for other diseases using a variety of techniques [10]–[12] . In this work , twenty-two genetic variants with p<5×10−8 in recent studies [6] were chosen for a composite genetic risk score ( GRS ) for SLE . We investigated the risk alleles and GRS with two goals: first to further characterize SLE susceptibility , and then to investigate relationships with SLE subphenotypes – namely the 11 American College of Rheumatology ( ACR ) classification criteria [13] , [14] , anti-dsDNA production ( a subset of the ACR immunologic criterion ) , and age at diagnosis . Our access to a large SLE case collection with clinical and genetic data provided an opportunity to analyze the risk alleles and subphenotypes comprehensively , both as individual alleles and with the genetic risk scores .
A total of 1919 SLE cases and 4813 healthy controls obtained from two SLE GWAS ( referred to as “parent studies” ) were analyzed . Subjects by parent study and source are shown in Table S1 . Parent study 1 contained 1295 cases and 3334 controls genotyped on the Illumina 550K panel as part of an SLE GWAS [3] including 1722 controls from iControlDB ( Illumina , www . illumina . com ) . Parent study 2 contained 624 cases and an additional 337 non-overlapping controls genotyped on the Illumina 317K panel as part of a SLEGEN Consortium GWAS [4] , with missing 550K SNPs imputed ( see Methods ) . As many controls were removed from parent study 2 due to overlap with parent study 1 , we added an additional 1142 healthy controls from the breast cancer study conducted by CGEMS ( Cancer Genetics Markers of Susceptibility , cgems . cancer . gov ) [15] genotyped on the Illumina 550K to the parent study 2 dataset . Twenty-two established SLE risk SNPs with reported genome-wide levels of significance ( p<5×10−8 ) in at least one study are shown in Table 1 , along with their adjusted OR for the cohorts studied here . Associations ranged from OR = 1 . 94 ( 95% CI 1 . 75–2 . 16 , p = 9×10−34 ) for the HLA-DR3 tag SNP to OR = 0 . 92 ( 95% CI 0 . 84–1 . 00 , p = 0 . 055 ) for BANK1 . We also examined all possible 2×2 interactions of the 22 risk alleles in both SLE cases versus controls and in case-only analyses for each subphenotype . No combination was significant using a false discovery rate ( FDR ) [16] threshold of 5% to account for multiple testing of 222 combinations . For the case-control analysis , the most significant interactions were rs1801274-rs6445975 ( FCγR2A -PXK , unadjusted p = 0 . 0022 ) and rs2187668-rs10488631 ( HLA-DR3-IRF5 , adjusted p = 0 . 0043 ) . In subphenotype associations , the most significant interactions were rs2431099-rs2187668 ( PTTG1-HLA-DR3 , unadjusted p = 0 . 0015 ) for photosensitivity and rs2327832-rs2248932 ( TNFAIP3-BLK , unadjusted p = 0 . 0029 ) for anti-dsDNA production . The twenty-two established risk variants were used for two genetic risk measures: a simple count of the number of risk alleles , and a composite genetic risk score ( GRS ) , defined as the summation of SLE risk alleles with each weighted by its SLE odds ratio ( OR ) . Figure 1A shows the distribution of the number of risk alleles in cases versus controls; the mean in cases was 15 . 1 ( SD 3 . 1 ) while the mean in controls was 13 . 1 ( SD 2 . 8 ) , with a trend p = 4×10−128 . Figure 1B shows the density of the continuous GRS score , with mean of 18 . 8 ( SD 4 . 0 ) in cases and 16 . 2 ( SD 3 . 6 ) in controls . The SLE OR , adjusted for intra-European ancestry , sex , and parent study , for high-low GRS tertiles was 4 . 4 ( 95% CI 3 . 8–5 . 1 ) . Figure 2 shows adjusted ORs for intervals of the GRS compared to a GRS range of 15–17 . 5 . For example , the OR for SLE having GRS>25 versus the reference group was 8 . 9 ( 95% CI 5 . 9–13 . 2 ) , while the OR for SLE having GRS<10 was 0 . 29 ( 95% CI 0 . 17–0 . 48 ) . We used receiver operating characteristic ( ROC ) curves to compare the GRS versus the number of risk alleles as predictors of SLE . The GRS was a significantly better predictor: the area under the curve ( AUC ) for the GRS was 68 . 9% ( 95% CI 67 . 5%–70 . 3% ) versus 67 . 9% ( 95% CI 66 . 4%–69 . 3% ) for the number of risk alleles , p = 3×10−14 . As expected , many SLE subphenotypes were significantly correlated , shown in Table S2 . The strongest is between anti-dsDNA production and the immunologic disorder classification criterion ( r = 0 . 62 ) , as anti-dsDNA is one of many antibodies that fulfill the immunologic criterion . Correlation between anti-dsDNA production and renal disease ( r = 0 . 26 ) and between malar rash and photosensitivity ( r = 0 . 18 ) is also observed . Many of the classification criteria have an inverse association with age at diagnosis , with renal disease showing the strongest inverse correlation ( r = −0 . 27 ) . Individually , several risk alleles were associated with SLE subphenotypes . Table 2 shows those that were significant at an FDR level of 5% . As reported previously [8] , the STAT4 SNP rs7574865 was associated with anti-dsDNA antibody production and early age at diagnosis . We also observed associations between the HLA-DR3 tagging allele and anti-dsDNA production ( OR = 1 . 37 , 95% CI 1 . 14–1 . 65 ) , as well as renal disorder ( OR = 1 . 37 , 95% CI 1 . 14–1 . 64 ) . In addition , we observed significant associations for anti-dsDNA production with ITGAM ( OR = 1 . 32 , 95% CI 1 . 09–1 . 59 ) and UBE2L3 ( OR = 1 . 31 , 95% CI 1 . 09–1 . 56 ) , arthritis with ITGAM ( OR = 0 . 72 , 95% CI 0 . 59–0 . 88 ) , and immunologic disorder with KIAA1542 ( OR = 0 . 79 , 95% CI 0 . 68–0 . 92 ) and UHRF1BP1 ( OR = 1 . 25 , 1 . 08 = 1 . 44 ) , with OR<1 indicating protective effects of the minor allele . Next , we considered associations between subphenotypes and cumulative risk alleles . Six subphenotypes were associated with the number of risk alleles ( not shown ) and the GRS at p<0 . 05 , as shown in Table 3 for the GRS as a continuous score and as a comparison between the highest and lowest tertiles . For all of these subphenotypes , the GRS was slightly more strongly associated than the number of risk alleles ( not shown ) . The strongest associations were between the continuous GRS and anti-dsDNA production ( p = 9×10−12 ) , immunologic disorder ( p = 4×10−9 ) , and age at diagnosis ( continuous , p = 9×10−7 ) . Corresponding ORs for high-low GRS tertiles , respectively , were ORanti-dsDNA = 2 . 36 ( 95% CI 1 . 76–3 . 16 , p = 9e−9 ) , ORimmunologic = 2 . 23 ( 1 . 64–3 . 03 , p = 3e−7 ) , and ORage = −2 . 68 ( −4 . 42–0 . 94 , p = 0 . 0026 ) . For the dichotomized age at diagnosis<34 years , ORage34 = 1 . 45 ( 1 . 11–1 . 90 , p = 0 . 0060 ) . Figure 1C and 1E shows the distribution of the number of risk alleles in anti-dsDNA positive versus negative SLE subjects and high versus low tertiles of age at diagnosis , respectively . Figure 1D and 1F shows the corresponding density curves for the GRS . We tested these associations both with observations dropped for missing disease duration and on the full dataset using multiple imputation ( see Methods ) with very similar results ( Table S3 ) . However , since the SLE risk alleles include SNPs which may not be associated with subphenotypes , or may have different effect sizes than for SLE susceptibility , the number of risk alleles and the GRS may be under-powered to detect cumulative associations with subphenotypes . To more fully address the question of which subphenotypes have evidence of association with cumulative SLE risk alleles , we used a discovery-replication approach to develop a subphenotype-specific genetic risk score , sub-GRS , for each subphenotype ( see Methods ) containing a subset of the SLE risk alleles , weighted by the subphenotype odds ratio in parent study 1 . The number of SNPs was chosen to optimize the association with the subphenotype , in contrast to the GRS which contains all SLE risk SNPs regardless of the subphenotype associations . Table 4 shows association results for those sub-GRS that have replication p< 0 . 1 in parent study 2 and ORs in the same direction . ORs are standardized for comparison since the differing number of SNPs and different weights cause each sub-GRS to be on a different scale . Note that all of these subphenotypes were also significantly associated with the SLE GRS , indicating that we did not miss any cumulative associations when testing the SLE GRS . Note that for renal disease , the sub-GRS contained only a single SNP , showing that the top SNP ( tagging the HLA-DR3 allele ) was more significant than cumulative effects with additional risk alleles . For arthritis , although ITGAM was associated with arthritis in the joint data ( FDR p = 0 . 038 in Table 2 ) and the discovery set ( unadjusted p = 0 . 00056 ) , ITGAM and the sub-GRS had p>0 . 1 in the replication set . Finally , we considered the predictive capability of the sub-GRS and GRS for associated subphenotypes . We compared ROC curves for four predictive models for each of the six subphenotypes as shown in Table 5 . When adding the sub-GRS ( model 4 ) to a model containing only ( commonly-available clinical data ) disease duration and sex ( model 1 ) , the area under the ROC curve was significantly improved ( p<0 . 05 ) for all of these subphenotypes except renal disease . It was also significantly better than adding only the top single-locus association ( model 2 ) . When comparing model 4 to a model containing sex , disease duration , and the SLE GRS , it was only significantly better ( p = 0 . 020 ) for anti-dsDNA production . Figure 3 shows the ROC curves for these four models for anti-dsDNA production .
In a large collection of SLE cases and controls , we investigated the relationship between 22 risk alleles , considered individually and as cumulative genetic risk scores , with SLE susceptibility and specific SLE manifestations . It is important to understand the etiology of SLE subphenotypes , since different subphenotypes of SLE have differential morbidity and mortality , and appear likely to have different underlying etiologies as well . We believe that a more clear understanding of which , if any , genes affect each subphenotype may help lead to a better understanding of SLE disease mechanisms . We defined a genetic risk score , the GRS , as a summation of SLE risk alleles with each allele unit multiplied by the SLE OR for that allele . This is similar to the weighted “wGRS” defined by Karlson et al [11] for rheumatoid arthritis , except that we use the OR directly rather than its logarithm to be on a scale more similar to the number of risk alleles; the use of 22 risk alleles in both is coincidental . While the number of risk alleles is more intuitive and easier to visualize , the GRS has a wider range and variance and a stronger correlation with SLE susceptibility and subphenotypes . When applied to subphenotypes , the GRS may lose power due to unassociated or improperly weighted SNPs . For this reason we also modeled subphenotype-specific genetic risk scores ( sub-GRS ) with subsets of SNPs determined using a discovery-replication approach . While the association of these scores in our overall dataset was likely to be inflated since a substantial subset of the data was used to determine the ranking and weighting of the composite SNPs , the odds ratios in our replication set were similar or slightly higher than for the SLE GRS . It should be noted that many of the SLE risk alleles were discovered using subjects in our study; thus our odds ratios may be an overestimate of the actual odds ratios ( “winner's curse” ) resulting in over-weighting in the GRS for some SNPs . On the other hand , it is likely that many of these SNPs are not the causal variants but markers in LD . In that case , their effect sizes for SLE susceptibility and/or subphenotype associations would be underestimated , causing the GRS and/or sub-GRS scores to be underweighted and under-associated . Also , in some cases we were not able to use directly-genotyped SNPs at exactly the risk locus previously identified in the literature . Three SNPs were imputed in the SLEGEN dataset ( Illumina 317K versus 550K , see Table S1 ) , and for 6 SNPs we used a proxy . Use of proxy and/or imputed SNPs may have given us lower power to detect associations if those SNPs were not as accurate or highly associated; however we believe accuracy was assured by high thresholds for imputation inclusion ( see Methods ) and proxy SNP selection ( r2≥0 . 8 ) . Also , while multiple signals have been implicated in the TNFAIP3 region [5] , [17] , we were only able to include one locus with a suitable match in our data . Another potential limitation of the GRS is lack of modeling interactions between SNPs . We tested for all 2×2 interactions between the 22 SNPs in our data with no results being significant after multiple-testing correction; however we may have lacked the statistical power to detect such interactions given our sample size . Our analyses used HLA-DRB1 tagging SNPs for the DRB1*0301 ( DR3 ) and DRB1*1501 ( DR2 ) alleles rather than direct HLA-DRB1 genotyping data . Our resulting ORs were lower than those in the literature and therefore may underestimate the GRS . We performed sensitivity analyses with a subset of our cases having 4-digit HLA-DRB1 typing ( n = 716 ) and a subset of controls having mixed 2- and 4-digit typing ( n = 1414 ) . Removing ambiguous 2-digit types , there was 98 . 9% agreement of the DR3 classification ( as 0/1/2 alleles ) and 98 . 2% agreement for DR2 . We were not able to assess case-control ORs using this data due to the differential typing; however we tested our DR3 associations with anti-dsDNA production and renal subphenotypes , and observed nearly identical ORs and significance compared to the tag SNPs using the same subset of subjects ( data not shown ) . We have shown that a subset of SLE clinical manifestations – immunological disorder including anti-dsDNA production , renal disease , age at diagnosis , hematologic disorder , and oral ulcers – are strongly associated with the number of risk alleles and the GRS . For most of these , the GRS was much more highly associated than any single locus , with the exception of renal disease and the HLA-DRB1 *0301 ( DR3 ) allele , which is stronger than the GRS signal ( and equivalent to the sub-GRS as it had only a single allele ) . For arthritis , there was no association with the GRS , but there is evidence for a protective effect of the ITGAM locus . For other manifestations , such as malar rash and serositis , there were no significant associations with either the GRS , sub-GRS , or with single loci . This led to our categorization of SLE manifestations into those that are: a ) influenced by cumulative effects of multiple known genes , b ) influenced primarily by a single gene out of the currently-established risk loci , and c ) thus far not appearing to be strongly influenced by genetics ( Figure 4 ) . Anti-nuclear antibody production was not included in this characterization as it was present in almost all SLE patients ( 95 . 9% of our subjects , Table S4 ) ; it is also possible that some associations were not evident due to lack of power for less-frequent manifestations , such as discoid rash and neurologic disorder . Strengths of this study include the large sample size and availability of clinical data for the SLE cases . Although there are potential issues of differing clinical evaluation at different sites and comprehensive follow-up after DNA collection , we expect the standardized ACR criteria to be highly consistent; furthermore we expect that any misclassification would be random with respect to genotype and therefore bias our results towards the null . One related issue was the large number of cases lacking data for disease duration . In general , we took a conservative approach and did not include observations that did not have disease duration information when disease duration was found to be associated with subphenotypes; for a subset of analyses , we also utilized single and/or multiple imputation on the entire dataset and observed similar results . A limitation of this and most other recent studies of SLE genetics is that it contains only subjects of European ancestry , and primarily northern European . The GRS was strongly associated with the first principal component of whole-genome SNPs , which reflects ancestry along the northwest-to-southeast European cline . This is likely to be at least somewhat if not largely due to the fact that these risk alleles have been discovered using mostly subjects of northern European ancestry , and additional risk alleles for other populations have yet to be discovered . While the GRS was very highly associated with SLE susceptibility , the predictive capability was somewhat modest ( AUC for ROC curve 68 . 9% ) . For subphenotypes associated with the GRS and sub-GRS , these scores significantly improve prediction over disease duration and gender , but the AUC for these subphenotypes is even more modest ( 56 . 0%–65 . 7% ) . For renal disease , the GRS did not improve prediction over clinical variables . It will be very interesting to see how such measures will be improved as we obtain additional information on SLE risk . In particular we anticipate that new susceptibility loci will be found as non-northern-Europeans are studied in greater detail . We also anticipate that the locations of current risk loci will be determined more precisely with regional fine mapping , re-sequencing , and functional studies .
Prior to merging , individual datasets were filtered for individuals with<90% genotyping and SNPs with<90% genotyping , minor allele frequency ( MAF ) <1% , or HWE p-value<0 . 00001 . SNPs in the 550K but not the 317K platform were imputed in the parent study 2 ( SLEGEN ) dataset using IMPUTE [18] , retaining SNPs with >90% confidence , >90% concordance in two test datasets ( 500 cases and 500 controls from parent study 1 with known genotypes removed ) , and >90% imputed genotype rate . In the final merged dataset of genotyped and imputed SNPs , SNPs were again filtered for >90% genotyping ( using typed or imputed values ) . From this dataset , SLE risk SNPs or their proxies were obtained . Out of 22 loci selected for inclusion based on p<5×10−8 in a previous study [6] , 16 were directly genotyped in all of our subjects . Three SNPs were imputed in the SLEGEN dataset , and a proxy SNP ( r2>0 . 8 ) was found for 6 SNPs using the HapMap ( http://www . hapmap . org ) CEU population ( with one overlap , a proxy SNP imputed in the SLEGEN dataset ) . Imputed and proxy SNPs are shown in Table S5 . Principal components analysis using EIGENSTRAT [19] was performed using the above merged dataset of directly genotyped SNPs , with SNPs having at least 90% genotyping ( thus on both the 317K and 550K platforms ) . SNPs in regions of known high LD ( chr 5: 44–51 . 5 Mb , chr 6: 25–33 . 5 Mb , chr 8: 8–12 Mb , chr 11: 45–57 Mb , and chr 17: 40–43 Mb ) were removed prior to analysis . Individuals with values more than 6 standard deviations away from the mean of any of the first 10 PCs ( n = 21 ) were considered genetic outliers and were removed . Four PCs were used for ancestry adjustment , based on leveling off of the PCA scree plot and due to significant differences between cases and controls for the first 4 PCs . The GRS was defined as the number of risk alleles at each locus multiplied by the OR for SLE susceptibility in our dataset . For example , two STAT4 risk alleles contribute 2*1 . 5 = 3 to the GRS . For a protective SNP , the risk alleles are the major alleles . Since not counting sporadic missing data would underestimate the number of risk alleles , the GRS , and the sub-GRS , we used best-guess imputed missing genotypes ( using IMPUTE version 2 ) for these calculations . The GRS was analyzed both continuously and by comparing the highest and lowest tertiles to aid in interpretation , with comparison of tertiles being a compromise between more extreme tails of the distribution ( having less power ) and dichotomizing ( having less differentiation ) . Subphenotypes and covariates studied are shown in Table S4 . In each study , subphenotype status was confirmed by chart review . Autoantibody status was determined by chart review and/or serologic testing; subjects were considered auto-antibody positive if there was any positive test indicated in the reviewed medical records or serologic tests . Negative status required that at least one negative test be documented and no positive tests . Positive anti-dsDNA status is a subset of the immunologic criteria; other qualifiers are anti-Sm antibodies or the presence of anti-phospholipid antibodies . Where appropriate , e . g . logistic regression and bar graphs , the age at diagnosis was dichotomized into high-low halves or split into tertiles . For regression , in addition to the ancestry principal components described above , additional covariates were sex , disease duration , and study ( two parent studies or eight sources , see Table S1 ) . All subphenotypes were heterogeneous by study source ( data not shown ) . We first looked at the adjusted association between each outcome and the continuous GRS ( Table S3 ) . As we have a high percentage of missing data for disease duration ( 18 . 5% , see Table S4 ) , adjustment was done two ways: a ) using only the subset of subjects having disease duration , and b ) using multiple imputation of the missing disease duration values . Multiple imputation was performed using Stata ICE [20] with predictive matching . Covariates age at diagnosis , study source , and sex were used in the imputation . Differences in results using these methods were very slight for subphenotypes associated with the GRS . We used actual data without imputation in subsequent GRS analyses . For the sub-GRS computations ( below ) , we used single imputation based on the same variables as above . In subphenotype associations , the SLE GRS may have less power than a risk score which utilizes the SNPs and effect sizes appropriate for that subphenotype . Thus we also tested a subphenotype-specific sub-GRS for each subphenotype , defined via a discovery-replication approach . First , for each subphenotype we used the associations in parent study 1 ( the “discovery” study for this analysis ) to determine the rank and OR of each risk SNP association with the subphenotype . Then a series of 22 candidate sub-GRS ( n ) scores were computed incrementally adding in the OR weights by rank , where n is the number of SNPs included . ( The first candidate sub-GRS ( 1 ) is equal to the top SNP weights , the second candidate sub-GRS ( 2 ) adds in the second SNP weights , and so on ) . The associations in the discovery set for the resulting sub-GRS ( n ) candidates are shown in Figure 5; p-values are for the likelihood ratio test of differences between models with the sub-GRS ( n ) plus covariates versus a model with only covariates . This method can accumulate random associations as well , as illustrated for comparison purposes by sample “null” subphenotypes with 50–50 random associations ( highest and lowest associations out of ten samples are shown ) ; hence the importance of a discovery-replication approach . Finally the peak association sub-GRS ( n ) candidate for the replication and discovery sets with the minimum number of SNPs was used as the final sub-GRS for each subphenotype; this assumes that post-peak SNPs in either set are likely to be false positive associations . Stata 9 . 2 [21] was used for regressions and ROC curve analyses . Plink [22] was used for quality control filters , regressions and tests for 2×2 interactions . HelixTree SVS Version 7 . 2 . 3 ( www . goldenhelix . com ) was used for likelihood-ratio tests of logistic regressions of the sub-GRS ( n ) series . The R programming environment [23] Version 2 . 11 . 1 was used for GRS density curves . | Systemic lupus erythematosus is a chronic disabling autoimmune disease , most commonly striking women in their thirties or forties . It can cause a wide variety of clinical manifestations , including kidney disease , arthritis , and skin disorders . Prognosis varies greatly depending on these clinical features , with kidney disease and related characteristics leading to greater morbidity and mortality . It is also complex genetically; while lupus runs in families , genes increase one's risk for lupus but do not fully determine the outcome . The interactions of multiple genes and/or interactions between genes and environmental factors may cause lupus , but the causes and disease pathways of this very heterogeneous disease are not well understood . By examining relationships between the presence of multiple lupus risk genes , lupus susceptibility , and clinical manifestations , we hope to better understand how lupus is triggered and by what biological pathways it progresses . We show in this work that certain clinical manifestations of lupus are highly associated with cumulative genetic variations , i . e . multiple risk alleles , while others are associated with a single variation or none at all . | [
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"g... | 2011 | Risk Alleles for Systemic Lupus Erythematosus in a Large Case-Control Collection and Associations with Clinical Subphenotypes |
The phytopathogenic bacterium Xanthomonas campestris pv . vesicatoria ( Xcv ) requires type III effector proteins ( T3Es ) for virulence . After translocation into the host cell , T3Es are thought to interact with components of host immunity to suppress defence responses . XopJ is a T3E protein from Xcv that interferes with plant immune responses; however , its host cellular target is unknown . Here we show that XopJ interacts with the proteasomal subunit RPT6 in yeast and in planta to inhibit proteasome activity . A C235A mutation within the catalytic triad of XopJ as well as a G2A exchange within the N-terminal myristoylation motif abolishes the ability of XopJ to inhibit the proteasome . Xcv ΔxopJ mutants are impaired in growth and display accelerated symptom development including tissue necrosis on susceptible pepper leaves . Application of the proteasome inhibitor MG132 restored the ability of the Xcv ΔxopJ to attenuate the development of leaf necrosis . The XopJ dependent delay of tissue degeneration correlates with reduced levels of salicylic acid ( SA ) and changes in defence- and senescence-associated gene expression . Necrosis upon infection with Xcv ΔxopJ was greatly reduced in pepper plants with reduced expression of NPR1 , a central regulator of SA responses , demonstrating the involvement of SA-signalling in the development of XopJ dependent phenotypes . Our results suggest that XopJ-mediated inhibition of the proteasome interferes with SA-dependent defence response to attenuate onset of necrosis and to alter host transcription . A central role of the proteasome in plant defence is discussed .
Plants have to protect themselves from a plethora of microbial enemies . In a first layer of defence , conserved microbial molecules called PAMPs/MAMPs ( pathogen/microbe-associated molecular patterns ) are recognized on the cell surface which then leads to the induction of a number of defence responses , including the generation of reactive oxygen species , the initiation of MAP kinase signalling , PR-gene expression , and callose depositions at the cell wall [1] . Collectively , these responses are sufficient to prevent multiplication and spread of a broad range of potential pathogens and mostly result in PTI ( PAMP-triggered immunity ) . To overcome this barrier many gram-negative plant pathogenic bacteria have acquired a highly conserved type III secretion system ( T3SS ) which enables them to inject so called type III effector proteins ( T3Es ) into the plant cell . These T3Es are targeted to a number of cellular compartments where they influence host cellular processes to promote pathogen multiplication and disease [2] , [3] . Many T3Es are enzymes ( e . g . phosphotransferases , phospholyases , proteases , E3 ligases , and acetyltransferases ) , while others have no obvious enzymatic activity or act as transcription factors . The picture that emerges from research in the past few years is that the majority of T3Es acts to suppress basal defence responses and innate immunity by interfering with e . g . defence signal transduction , vesicle trafficking , gene expression , and RNA metabolism [2]–[5] . However , the exact mechanism by which they accomplish their function remains unknown for most of T3Es identified to date . In response to defence suppression by T3Es , plants have acquired the ability to recognize specific effector proteins through resistance ( R ) proteins . In this second layer of defence effector recognition results in an effective immune response which is often accompanied by rapid , localized cell death , termed the hypersensitive response ( HR ) , eventually restricting bacterial spread and leading to effector triggered immunity ( ETI ) [6] . One of the most diverse and widely distributed families of T3Es is the YopJ family of cysteine proteases/acetyltransferases [7]–[9] . Members of this large family of T3Es are found among both plant and animal pathogens as well as plant symbionts and a characteristic feature of these proteins is their catalytic triad consisting of the amino acids histidine , glutamic/aspartic acid , and a cysteine . YopJ from Yersinia pestis , the archetypal member of this effector family , has been shown to possess acetyltransferase activity . During infection of mammalian cells YopJ inhibits MAP kinase signalling by acetylating a serine or threonine within the activation loop of MKK6 , preventing the phosphorylation of theses residues and thereby blocking signal transduction [10] . However , other experiments have demonstrated de-sumoylating and de-ubiquitinating activity for YopJ [11]–[13] although direct targets of these protease activities remain to be determined . More than 10 YopJ homologues have been identified in plant pathogenic bacteria including Pseudomonas ( HopZ-family ) , Ralstonia ( PopP1 and PopP2 ) , Erwinia ( ORFB ) , and Xanthomonas ( AvrRxv , AvrXv4 , AvrBsT and XopJ ) species as well as the plant symbiont Rhizobium ( Y4LO ) [7]–[9] . HopZ1a from P . syringae has recently been shown to target GmHID1 ( 2- hydroxyisoflavone dehydratase ) , an enzyme involved in the biosynthesis of isoflavones in soybean . The interaction between the effector protein and GmHID1 leads to the degradation of the enzyme which eventually suppresses the synthesis of the defence compound diazedin and leads to enhanced bacterial multiplication [14] . The mechanism by which HopZ1a causes degradation of GmHID1 is currently unknown . Although it requires an intact catalytic triad , no biochemical activity of HopZ1a could be demonstrated . In another study , Lee et al . [15] could recently show that HopZ1a possess acetyltransferase activity that is activated by the eukaryotic factor phytic acid ( inositolhexakisphosphate ) . HopZ1a was able to acetylate itself and tubulin . In plant cells , HopZ1a causes a dramatic decrease in microtubule networks , disrupts the plant secretory pathway and suppresses cell wall-mediated defense [15] . Another T3E with demonstrated acetyltransferase activity is PopP2 from Ralstonia solanacearum [16] . The effector autoacetylates on a particular lysine residue that is conserved among all members of the YopJ family and has also been described as being required for HopZ1a acetyltransferase activity [15] . Although PopP2's acetyltransferase activity is required for proper recognition by the cognate RRS1-R R protein its acetylation target during virulence is currently unknown [16] . XopJ is one of the YopJ-family members present in a number of Xanthomonas campestris pv . vesicatoria ( Xcv ) strains [17] , [18] . XopJ is attached to the plasma membrane of plant cells through a myristoylation motif and has been shown to block protein secretion [19] , [20] . Moreover , transgenic expression of XopJ in Arabidopsis suppressed callose deposition elicited by an avirulent bacteria indicating that the effector interferes with cell wall – associated defense responses [19] . Mutants with an alanine replacement of the catalytic cysteine residue ( C235A ) are abrogated in the virulence function of XopJ , indicating that the cellular functions of XopJ are accomplished through its enzymatic activity [19] . However , neither the cellular target ( s ) nor the biochemical activity of XopJ has been determined so far . Aim of the present study was to gain insights into the molecular function of XopJ through the identification of potential target proteins . Our results show that XopJ interacts with RPT6 a subunit of the 19S regulatory particle within the 26S proteasome to inhibit proteasome activity . This prevents accumulation of the defence phytohormone salicylic acid ( SA ) and attenuates SA mediated symptom development as well as pathogen-induced senescence .
In order to identify potential XopJ target proteins in plant cells , yeast two-hybrid screens were conducted with XopJ as a bait and an Arabidopsis and tobacco cDNA library , respectively , as a prey . Neither Arabidopsis nor tobacco is a host plant for Xcv; however , we have previously established that XopJ inhibits basal defence responses in both species [19] . Therefore , it appears highly likely that XopJ targets are conserved in different plants irrespective of their susceptibility towards Xcv . One protein identified as an interaction partner of XopJ in both libraries was RPT6 ( Figure 1 ) . RPT6 ( regulatory particle ATPase 6 ) is one of six ATPases of the 19S regulatory particle of the 26S proteasome involved in the degradation of ubiquitinated substrates [21] . The six RPT subunits form a ring that consumes ATP to facilitate substrate unfolding and channel opening , which is required for translocation of substrates from the 19S regulatory particle into the proteolytic 20S core particle of the proteasome [22] . The Arabidopsis genome encodes two RPT6 genes ( RPT6a , At5g19990 and RPT6b , At5g20000 ) which are directly arranged in tandem and expression of both genes is supported by cDNAs ( www . arabidopsis . org ) . Both protein sequences share 97% identity with each other ( Figure S1 ) ; however , screening the Arabidopsis two-hybrid library recovered only RPT6a as an in XopJ interacting protein and thus the ability of RPT6b to bind XopJ was investigated in a direct interaction assay in yeast . As shown in Figure 1 pair wise transformation of BD-XopJ and AD-AtRPT6b did also result in activation of reporter genes indicating that XopJ/RPT6 interaction is not specific for AtRPT6a . The RPT6 protein sequence is highly conserved across phylogeny with 81 to 82% identity between Arabidopsis RPT6a and RPT6 from human and 70% identity between the RPT6 sequences from Arabidopsis and yeast ( Figure S1 ) . In order to assess whether XopJ could interact with RPT6 from another phylum , we tested its interaction with RPT6 from yeast using the two-hybrid system . The results showed that no interaction between the two proteins in yeast occurred ( Figure 1 ) . In addition , a XopJ C235A mutant in the conserved catalytic triad lost its ability to interact with RPT6 in yeast ( Figure 1 ) , indicating that the biochemical activity of XopJ might be required for its interaction with RPT6 in yeast . Sequence identity between RPT6 from N . tabacum and the orthologous protein from the Xcv host plant pepper ( Capsicum annuum ) is 98% ( Figure S1B ) and a yeast two-hybrid analysis revealed binding of XopJ to the pepper RTP6 protein ( Figure 1 ) . Thus , RPT6 could represent a potential XopJ target protein during a compatible interaction of Xcv with pepper . However , given the high degree of sequence identity between the tobacco and pepper RTP6 we reasoned that further functional analysis of the XopJ/RPT6 interaction could be carried out with the tobacco NtRPT6 . Next , the subcellular localization of NtRPT6 was examined to determine whether it overlaps with that of XopJ in plant cells . Colocalization of both proteins would indicate that these proteins could interact in planta . The green fluorescent protein ( GFP ) was fused to the C-terminus of NtRPT6 and the fusion protein was expressed together with a XopJ-mCherry fusion protein , in leaves of N . benthamiana using Agrobacterium-infiltration . The fluorescence pattern was investigated using confocal laser scanning microscopy 48 h after infiltration . NtRPT6-GFP fluorescence was present at the plasma membrane ( PM ) and in the cortical cytoplasm ( Figure 2A ) . XopJ was previously reported to localize to the PM involving N-myristoylation [19] , [20] . Colocalization of NtRPT6-GFP with XopJ-mCherry revealed partially overlapping fluorescence patterns at the PM , indicating that both proteins could interact in vivo ( Figure 2A ) . To confirm the interaction of XopJ and NtRPT6 in planta , bimolecular fluorescence complementation ( BiFC ) assays were performed in N . benthamiana using transient expression via particle bombardment . XopJ and NtRPT6 were fused with the non-fluorescent N-terminal part of the yellow fluorescent protein ( YFPN ) and the C-terminal part of YFP ( YFPC ) at their C-termini , respectively . Homodimerization of cytosolic fructose-1 , 6-bisphosphatase in the cytosol served as a positive control ( Figure S2 ) . A combination of FBPase-YFPN with NtRPT6-YFPC or FBPase-YFPc with NtRPT6-YFPN induced no fluorescence ( Figure S2 ) . By contrast , strong YFP fluorescence was observed when a combination of XopJ-YFPN with NtRPT6-YFPC was expressed , demonstrating that XopJ/NtRPT6 interact in plant cells ( Figure 2B ) . In accordance with a PM localization of XopJ , the YFP signal in XopJ/NtRPT6 BiFC experiments appeared to be confined to the PM as no fluorescence surrounding the chloroplasts could be detected which would be indicative for a cytosolic localization of the XopJ/NtRPT6 interaction ( Figure 2B ) . To further substantiate this finding a GFP-pull down assay was performed . To this end NtRPT6-GFP was transiently co-expressed with XopJ-myc in leaves of N . benthamiana using Agro-infiltration . Forty-eight hours after infiltration GFP-tagged NtRPT6 was pulled down from total leaf extracts using GFP-trap beads and the precipitate was subjected to western blot analysis with anti-GFP and anti-myc antibodies , respectively . As shown in Figure 2C NtRPT6-GFP was able to co-precipitate XopJ-myc which is indicative for an interaction between the two proteins in planta . Previous results demonstrated that XopJ requires an intact catalytic triad and a functional myristoylation motif , respectively , to inhibit basal defence responses [19] . To further investigate structural requirements for the XopJ/NtRPT6 interaction in planta , a co-immunoprecipitation experiment was performed using the XopJ ( C235A ) mutant variety as well as the XopJ ( G2A ) variant . The results revealed that both mutant proteins retained their ability to interact with NtRPT6 in a pull-down experiment ( Figure 2C ) suggesting that biological activity and myristoylation , respectively , are per se not required for XopJ to interact with RPT6 in planta . To exclude that the interaction between XopJ and RPT6 is mediated by a third eukaryotic protein an in vitro pull-down assay was performed . To this end , recombinant glutathione S-transferase ( GST ) tagged NtRPT6 was incubated with maltose-binding protein ( MBP ) tagged XopJ . A subsequent western blot revealed that GST-NtRPT6 was pulled down together with MBP-XopJ , demonstrating a direct physical interaction of both proteins which does not require additional factors ( Figure 2D ) . MBP alone was not able to pull down GST-RPT6 and GST-RPT6 was not able to bind to the amylose matrix indicating specificity of the in vitro interaction ( Figure 2D ) . After having established that XopJ and RPT6 interact in plant cells we next sought to investigate whether this interaction exerts any effect on overall proteasome activity in plants . To this end , the proteasome activity was monitored using a fluorogenic peptide ( Suc-LLVY-AMC ) which is a substrate for the chymotrypsin-like activity of the proteasome . This substrate has been shown to be split by the 26S proteolytic complex , whereas the 20S proteasome , which is not involved in the degradation of ubiquitinated proteins , is known to have no activity for the peptide breakdown [23] . As shown in Figure 3A , transient expression of XopJ-myc in leaves of N . benthamiana led to a reduction in proteasome activity of approximately 40% as compared to leaves infiltrated with the empty vector control . Mutation of the catalytic triad in XopJ ( C235A ) as well as a mutation in the myristoylation site in the XopJ ( G2A ) variant abolished the inhibitory effect on proteasome activity although both proteins were expressed to comparable levels as wild-type XopJ ( Fig 3A ) . This indicates that XopJ requires an intact catalytic triad and proper localization to the PM to affect proteasome activity . Furthermore , an unrelated T3E from Xcv , XopB , did not inhibit proteasome activity upon transient expression ( Figure S3 ) , indicating that inhibition of the proteasome is not a general feature of type III effectors . Previous reports suggest that Suc-LLVY-AMC could also be cleaved by cysteine proteases in addition to serving as a substrate for the proteasome [24] . To rule out that XopJ inhibits cysteine proteases , the proteasome activity assay was performed in the presence or absence of the broad spectrum cysteine protease inhibitor E64 . As shown in Figure 3B , E64 caused a reduction of Suc-LLVY-AMC cleaving activity of approximately 10% in extracts prepared from control leaves as well as in extracts prepared from N . benthamiana leaves transiently expressing XopJ . Thus , the inhibitory effect of XopJ on the proteasome activity is not affected by the addition of E64 . In turn , when extracts from control leaves were assayed in the presence of the potent proteasome inhibitor MG132 Suc-LLVY-AMC cleaving activity was reduced by approximately 85% indicating a high degree of specificity of the assay ( Figure 3B ) . XopJ was not able to inhibit proteasome activity any further than what was observed in the presence of MG132 ( Figure 3B ) . These data strongly suggest that XopJ specifically inhibits the chymotrypsin-like activity of the proteasome and not cysteine proteases in general . To determine whether the reduced proteasome activity would lead to the accumulation of ubiquinated proteins a western blot using an anti-ubiquitin antibody was performed on total protein extracts from leaves transiently expressing XopJ-myc or the XopJ ( C235A ) -myc and XopJ ( G2A ) -myc variants , respectively . As shown in Figure 3C , a high-molecular weight smear diagnostic for the accumulation of non-degraded poly-ubiquinated proteins was visible in extracts from XopJ-myc expressing leaves . Although there is some variation in staining intensity , expression of the mutated XopJ variants did not cause a comparable accumulation of ubiquitin-decorated proteins ( Figure 3C ) . This is in line with the observation that these proteins do not affect proteasome activity upon transient expression . The results obtained thus far indicate that XopJ and RPT6 interact in yeast and when transiently expressed in leaves of N . benthamiana . This interaction somehow leads to a reduction in proteasome activity interfering with the turnover of ubiquinated proteins . Thus , the question arises as to whether XopJ has a similar effect when translocated in a type III dependent manner during a compatible interaction and how this could contribute to bacterial virulence . It has previously been shown that an Xcv mutant strain of XopJ was not affected in bacterial growth and symptom formation on susceptible plants , indicating subtle contributions to bacterial virulence or functional redundancy [17] . The mutant strain analyzed in that study contained a frameshift mutation in xopJ . In the present study , we constructed a xopJ null mutant ( designated Xcv ΔxopJ ) in Xcv strain 85–10 by deleting 880 nt within the XopJ coding region by homologous recombination . To re-assess the contribution of XopJ to bacterial multiplication , susceptible pepper plants were infiltrated with the Xcv ΔxopJ strain and with the Xcv wild type control ( each carrying the broad host range vector pBBR1 MCS-5 [25] that was subsequently used for complementation ) at a bacterial titer of 105 cfu/ml . Xcv ΔxopJ multiplication was slightly but significantly reduced as compared to the control at 6 dpi ( days post infection ) and 8 dpi ( Figure 4A ) . Xcv ΔxopJ strains carrying the broad host vector pBBR1 MCS-5 containing the xopJ ORF tagged with HA to facilitate immunological detection [Xcv ΔxopJ ( xopJ-HA ) ] exhibited wild-type growth at 6 dpi and 8 dpi ( Figure 4A ) . This indicates that XopJ is required for maximal Xcv growth in susceptible pepper leaves at the late stages of infection . Measurement of the overall leaf proteasome activity three days after infection provides evidence that Xcv wild-type causes a significant induction of proteasome activity ( Figure 4B ) . The rise in activity was significantly higher with Xcv ΔxopJ ( vector ) and also significantly induced compared to leaves infected with Xcv ΔxopJ ( XopJ-HA ) or Xcv ( vector ) , indicating that XopJ is necessary to dampen the proteasome activity in vivo ( Fig . 4B ) . Pepper plants infected with Xcv ΔhrpF , a T3SS deficient mutant that is not able suppress basal defence responses , displayed elevated proteasome activity 3 dpi , suggesting that the proteasome activity is induced during basal defence ( Fig . 4B ) . These data demonstrate that XopJ is able to reduce proteasome activity after translocation by a virulent Xcv in a type III dependent manner . Given the fact that the in planta growth as a measure for virulence was affected in a Xcv ΔxopJ mutant strain at late stages of infection we searched for XopJ phenotypes that could provide a link between effector function and virulence activity . To this end we assessed phenotype development and symptom production after infection of susceptible pepper plants with a high bacterial titre ( 108 cfu/ml ) of the Xcv ΔxopJ mutant as compared to the wild type strain . Leaves inoculated with the Xcv ΔxopJ deletion strain developed necrotic lesions 3 dpi while those infected with the Xcv ( vector ) strain remained symptomless at the same time point ( Figure 5A ) . However , 5 dpi a similar degree of necrotic lesions observed for Xcv ( vector ) infected leaves as in the Xcv ΔxopJ mutant at 3 dpi ( Figure S5 ) . This suggests that a deletion of XopJ affects the kinetics of symptom development during infection by inhibiting the onset of necrosis . Introduction of XopJ ( G2A-HA ) and ( C235A-HA ) constructs into the Xcv ΔxopJ null mutant did not abolish necrosis induction , suggesting that a functional XopJ is necessary and sufficient to suppress development of necrosis in pepper ( Figure 5A ) . Proper expression of all XopJ variants was verified by western blotting using the HA-tag ( Figure 5B ) . The timing of tissue necrosis is slow compared with the rapid , localized hypersensitive cell death response characteristic of R protein–mediated defences in resistant hosts . Therefore , the necrotic phenotype observed in leaves infected with the Xcv ΔxopJ strain rather reflects normal but accelerated symptom development associated with later stages of disease [26] . To strengthen the idea that XopJ suppresses the onset of necrosis , we performed an in planta mixed-inoculum experiment by first infiltrating Xcv ΔxopJ harbouring the XopJ-HA construct into pepper and , with a time shift of three hours , Xcv ΔxopJ . As shown in Figure S6 , cell death was not induced in this mixed-inoculum experiment , indicating that XopJ suppresses necrosis in the Xcv-pepper interaction . To characterize the suppression of cell death by XopJ in more detail , plant cell death was monitored by trypan blue staining of the infected tissue . Trypan blue is a vital stain that specifically stains dead cells but is not absorbed by cells with intact plasma membranes [27] . Xcv ( vector ) , ΔxopJ ( vector ) and the XopJ-complemented strains were inoculated into leaves of pepper plants . Samples from infected leaf tissue were collected 3 dpi , stained with trypan blue and analyzed by transmission light microscopy . In contrast to untreated leaf material that remained unstained , almost all cells were stained by trypan blue in tissue infected with Xcv ΔxopJ null mutant ( Figure 5C ) . In leaves inoculated with Xcv harbouring the empty vector or Xcv ΔxopJ ( XopJ-HA ) , only a few cells were stained , whereas Xcv ΔxopJ XopJ ( G2A-HA ) and ( C235A-HA ) strains displayed enhanced staining ( Figure 5C ) . In summary , this result is in accordance with the macroscopically observed phenotype caused by the different Xcv strains on pepper leaves , summarized in Figure 5D . The disease index demonstrates that the phenotypes caused by the different Xcv strains consistently occur in a population of 20 individual pepper ECW plants , e . g . , Xcv strains lacking XopJ induced tissue necrosis in 90% of infected pepper plants ( Figure 5D ) . In order to quantify cell death elicitation by the different Xcv strains , we determined ion leakage induced by all strains . Cell death is often preceded by an enhanced ion leakage in dying cells due to membrane damage and thus provides a quantitative measure of cell death-associated phenotypes . As expected for an ongoing cell death , conductivity significantly increased at 3 dpi in samples infiltrated with Xcv ΔxopJ , Xcv ΔxopJ XopJ ( G2A-HA ) and ( C235A-HA ) in comparison to Xcv ( vector ) and Xcv ΔxopJ ( XopJ-HA ) , which is in agreement with the observed phenotypes ( Figure 5E ) . Thus , in susceptible pepper leaves , XopJ action does promote Xcv multiplication by slowing down the rate of secondary symptom development such as tissue necrosis . Given that XopJ prevents necrosis and depletes proteasome activity during a compatible interaction of Xcv with pepper , we sought to investigate whether both events during infection are connected with each other . To this end a pharmacological approach to determine whether the inhibition of the proteasome activity could account for XopJ-mediated suppression of cell death was taken . When Xcv ΔxopJ was co-infiltrated with the well-characterized proteasome inhibitor , MG132 ( 100 µM in 1% ethanol ) , less necrotic lesions compared to control treatment could be observed , indicative for a complementation of the loss of XopJ by MG132 ( Figure 6A ) . Ion leakage measurements were also consistent with the observed phenotype , as leaves co-infiltrated with Xcv ΔxopJ and MG132 exhibited significantly reduced conductivity compared to the control treatment and being similar to Xcv WT induced ion leakage ( Figure 6B ) . Thus , we conclude that MG132 can phenocopy XopJ function leading to the suppression of cell death . Taken together , these findings suggest a connection between inhibition of the proteasome by XopJ and its ability to prevent cell death induction during disease development . It has previously been shown that tissue necrosis associated with the secondary phase of Xcv infection of tomato leaves is dependent on the phytohormone salicylic acid ( SA ) [26] . Furthermore , experiments by Kim et al . [28] suggest that the Xcv effector XopD is able to suppress SA responses and plant immunity providing a paradigm for a Xcv T3E that interferes with hormonal defence . This finding prompted us to investigate whether XopJ could influence SA levels in infected pepper plants . To this end , SA pools ( free and conjugated SA ) were quantified in susceptible pepper plants 2 and 3 dpi infected with a high titre of Xcv ( 108 cfu/ml ) . By two and 3 dpi , leaves inoculated with Xcv ΔxopJ had approximately two-fold more free and total SA than leaves infected with Xcv wildtype ( Figure 7 ) . Complementation of Xcv ΔxopJ with XopJ resulted in SA levels comparable to Xcv WT infected leaves . The decrease in the pool of SA hence indicates that XopJ significantly diminishes the magnitude of SA accumulation in Xcv infected pepper plants ( Figure 7 ) . If the function of XopJ is to inhibit symptom development through interference with SA accumulation , then application of SA to wild type Xcv infected pepper leaves may mimic the phenotype of an Xcv ΔxopJ deletion mutant . Indeed , when Xcv wild type infected pepper leaves were sprayed with 5 mM SA 2 dpi necrotic lesions developed 3 dpi that were comparable to those observed on Xcv ΔxopJ infected leaves at the same time point without SA treatment ( Figure S7 ) . Thus , Xcv infected tissue remains sensitive to exogenously applied SA even in the presence of XopJ . After having established that XopJ negatively affects SA levels during infection , we next used quantitative real-time RT-PCR ( qPCR ) to investigate whether SA-dependent gene expression is impaired in plants infected with Xcv lacking XopJ . Thus , we monitored the impact of Xcv ΔxopJ infection in comparison to Xcv WT infection on the mRNA levels of the SA marker genes CaBPR1 ( basic PR1 protein ) CaPR-Q ( chitinase ) and CaSAR82A ( SAR8 . 2 ) ( [29]–[31] . The mRNA levels of all three SA-inducible marker genes were significantly elevated in pepper leaves infected with Xcv ΔxopJ 3 dpi when compared to leaves infected with Xcv wild type bacteria ( Figure 8A ) . This is consistent with the notion that XopJ leads to reduced SA pools during infection that then leads to an altered SA-dependent gene expression in pepper . Pathogen infection has previously been shown accelerate the onset of leaf senescence and evidence suggests that this is at least in part mediated by SA signalling [28] , [32] , [33] . Based on the phenotype of pepper leaves infected with the Xcv ΔxopJ strain we hypothesized that XopJ could delay senescence-associated processes during infection . Thus , qPCR was used to analyze mRNA levels of genes whose expression levels significantly change during age- and pathogen- induced senescence . Three genes were analyzed: CaSENU4 encodes a pathogenesis-related protein 1b1 that is induced in response to aging and SA [34] , [35] . CaSGR ( STAYGREEN ) and CaCab-1b ( chlorophyll binding protein ) are senescence markers because their expression has been shown to decrease during senescence in tomato leaves [28] , [35] , [36] . As shown in Figure 8B transcripts of CaSGR and CaCab-1b were significantly down regulated in tissue infected with Xcv ΔxopJ , compared to Xcv WT infection , while mRNA levels of CaSENU4 were significantly up-regulated , indicating that pepper leaves display accelerated senescence when infected with a Xcv ΔxopJ strain as compared to Xcv wild type infected leaves . Thus , XopJ seems to suppress senescence-associated gene expression likely to delay symptom development and tissue necrosis during later stages of infection . Since XopJ is required to suppress cell death correlating with reduced proteasome activity and decreased SA levels , we sought to investigate whether SA would have an influence on proteasome activity and gene expression of the proteasome subunit RPT6 . To test this , pepper and N . benthamiana leaves were sprayed with 5 mM SA and the transcript abundance of RPT6 in response to SA was determined . Transcript levels of CaRPT6 and NbRPT6 were significantly elevated about threefold 3 h after SA treatment ( Figure 9A ) . We then determined whether the proteasome activity is also induced after SA treatment . Measurements revealed that proteasome activity is significantly induced by SA , up to 40% in pepper and up to 130% in N . benthamiana , having a peak at 6 h after SA application ( Figure 9B ) . These data demonstrate that elevated proteasome activities and up-regulation of RPT6 gene expression occurs in response to activation of the SA signalling pathway . Since SA levels increase during a compatible interaction of Xcv with pepper , we next analysed RPT6 gene expression during infection . To this end , we monitored RPT6 mRNA levels in pepper leaves infiltrated with 1 mM MgCl2 , Xcv and Xcv ΔxopJ ( 108 cfu/ml ) . At 3 dpi Xcv WT significantly elevated RPT6 gene expression in comparison to MgCl2 ( Figure S8 ) . Intriguingly , the increase in transcript abundance was even higher in Xcv ΔxopJ infected pepper tissue displaying a significant difference in comparison to Xcv-infected tissue . As RPT6 is an SA inducible gene ( Figure 9A ) and plants infected with Xcv ΔxopJ display significantly higher SA pools than Xcv WT infected pepper leaves ( Figure 7 ) , we conclude that RPT6 gene expression during infection depends on the phytohormone SA . In an approach to provide more direct evidence for a connection between XopJ-mediated perturbations of the proteasome and SA-signalling , we used virus-induced gene silencing ( VIGS ) in pepper with Tobacco rattle virus ( TRV ) , followed by infection with different Xcv strains . NPR1 is a key positive regulator of SA-mediated defence responses notably by activating transcription of a battery of genes in response to rising SA-levels [37] . To investigate the involvement of SA-signalling via NPR1 pepper seedlings were infiltrated with a mixture of A . tumefaciens strains of pTRV1 ( CaMV 35S-driven TRV RNA1 ) and pTRV2-NPR1 ( TRV RNA2 containing the target sequence ) , or pTRV2-GFPsil ( serving as a control for infection symptoms ) . Three weeks after TRV inoculation , silencing of the target gene was confirmed by qRT-PCR ( Figure 10A ) . Subsequently , plants were infiltrated with either Xcv , Xcv ΔxopJ or Xcv ΔxopJ ( XopJ-HA ) . At 3 dpi silencing of NPR1 gene expression prevented development of host cell necrosis in leaves infected with the Xcv strain lacking XopJ while pTRV2-GFPsil leaves were necrotic ( Figure 10B ) . The fact that XopJ-dependent necrosis does not occur in plants defective in NPR1 expression suggests a direct involvement of SA-signalling in XopJ-dependent phenotype development . As previously observed measurement of the proteasome activity 3 dpi in pTRV2-GFPsil plants revealed increased activity in Xcv and Xcv ΔxopJ infected leaves as compared to the mock-infiltrated control with a more pronounced rise in Xcv ΔxopJ infected leaves confirming the inhibitory effect of XopJ on the proteasome during infection ( Figure 10C ) . By contrast , in plants silenced for NPR1 expression the proteasome activity was only slightly increased as compared to the mock-infected control with a significantly lower rise than in pTRV2-GFPsil plants ( Figure 10C ) . This shows that plants impaired in SA signalling are unable to induce proteasome activity upon infection and opens the possibility that activation of the proteasome by SA could be mediated through NPR1 . Although an important role of the ubiquitin-proteasome system during the regulation of plant immune responses is increasingly recognized , a direct link between proteasome activity and basal defence is not firmly established [38] . Effectors inhibit basal defence at different levels such as PAMP-signalling , transcription and translation of defence related genes or vesicle trafficking and cell wall associated defence responses . Thus , we first attempted to narrow down the level on which XopJ could interfere with PTI . To determine the effect of XopJ on PAMP signalling we investigated MAPK activation followed by flg22 treatment in seedlings of transgenic Arabidopsis plants expressing XopJ under control of the ethanol-inducible promoter [19] . Ethanol-induced seedlings were treated with flg22 and MAPK activation was monitored using the phospho-p44/p42 antibody that specifically recognizes the active phosphorylated MAPK form . Western blot analysis revealed that ethanol-induced XopJ plants displayed no difference in MAPK activation in response to flg22 treatment as compared to non-induced alc-XopJ control plants ( Figure S8A ) . Measurement of the proteasome activity in these plants showed a clear reduction in alc-XopJ plants after induction with ethanol ( Figure S8B ) . Thus , XopJ flg22 induced MAPK signalling in Arabidopsis seems not to be affected by a XopJ mediated reduction in proteasome activity . In a more direct attempt to study the involvement RPT6/proteasome function in basal defence we performed ( VIGS ) to reduce RPT6 mRNA levels in pepper plants . However , two to three weeks after infection with the TRV silencing constructs tissues of RPT6 silenced plants began to collapse and the plants died shortly after ( Figure S9 ) . The lethal phenotype of RPT6-VIGS plant precludes further genetic analysis of RPT6 function during defence but highlights the essential function of this proteasome subunit for cell viability . We thus decided to follow a pharmacological approach using the specific proteasome inhibitor MG132 to study the impact of reduced proteasome activity on basal defence responses . XopJ has previously been shown to inhibit secretion of a secGFP reporter . In addition , ethanol-inducible XopJ expression in leaves of transgenic Arabidopsis strongly compromises in the ability to deposit callose associated with papillae , a hallmark of cell wall–associated defence , in response to inoculation with the nonpathogenic P . syringae pv . tomato DC3000 hrcC mutant [19] . In order to investigate whether the same effects could be mediated by inhibition of the proteasome , N . benthamiana leaves transiently expressing secGFP were infiltrated with MG132 and analyzed for GFP fluorescence using confocal microscopy . As a consequence of a secretory block , coexpression of secGFP with Sp2 or XopJ-myc in leaves of N . benthamiana plants led to the expected increase in secGFP fluorescence , forming an intracellular ER-like pattern of fluorescence ( Figure 11B and C ) . When plants transiently expressing secGFP were infiltrated with 100 µM MG132 and subjected to confocal microscopy one hour after the treatment detection of ER-like GFP fluorescence indicated that GFP secretion into the apoplast was impaired ( Figure 11E ) . At a higher MG132 concentration ( 300 µM ) fast moving punctuate structures became visible that could represent some sort of vesicles ( Figure 11D ) . Taken together , these data indicate that manipulation of the proteasome function by inhibition through MG132 affects protein secretion , which opens the possibility that XopJ acts on secretion in a similar manner . However , the experiments described here do not show that MG132 and XopJ necessarily act in the same way to inhibit secretion . To further explore the effects of proteasome inhibition on basal defence responses , callose deposition was analyzed , after flg22 challenge in the presence or absence of MG132 . Six hours after treatment with flg22 plants infiltrated with MG132 exhibited significantly reduced callose deposits ( Figure 11F and G ) , indicating that the inhibition of the proteasome could interfere with cell-wall associated defence in Arabidopsis .
Type III effector proteins delivered into the host cell by plant-pathogenic bacteria collectively suppress host defence responses to promote virulence and pathogen spread . However , specific host cellular targets have been identified for only a few T3Es and the majority seems to interfere with defence signalling [2] , [3] . We have previously shown that the Xcv T3E XopJ is able suppress protein secretion and callose deposition when transiently expressed in leaves of N . benthamiana or after inducible expression in Arabidopsis , respectively , and thus this effector apparently can interfere with cell wall-based basal defence [19] . In the present study we identified the 26S proteasome subunit RPT6 as a potential virulence target of XopJ in plant cells . We demonstrated that XopJ interacts with RPT6 from different plant species in yeast and in planta . Furthermore , wild type XopJ inhibits proteasome activity , reduces accumulation of SA , and attenuates the onset of necrosis and pathogen-induced senescence during infection of susceptible pepper plants with Xcv . The 26S proteasome is an essential multicatalytic protease complex for the degradation of regulatory proteins that have been marked for destruction by ubiquitin ( Ub ) . The ubiquitin/proteasome system ( UPS ) plays a central role in the degradation of short-lived and regulatory proteins important for a variety of cellular processes [21] , [39] . It consists of two multisubunit protein complexes: the 20S proteolytic core protease ( CP ) and the 19S regulatory particle ( RP ) that is composed of 17 subunits . The CP functions as a nonspecific ATP and Ub-independent protease that forms a cylindrical structure composed of four heptameric rings while the RP caps one or both ends of the CP and confers ATP dependence and poly-Ub recognition to the proteasome . The RP is composed of a ring of six triple A ( AAA+ ) ATPases ( RPT1-6 ) that covers the opening to the CP and probably assists in target unfolding , the RP non ATPases ( RPNs ) 10 and 13 are Ub receptors , and RPN11 is a deubiquitylating enzyme ( DUB ) that helps to release bound Ub [21] . Arabidopsis mutants compromised in individual proteasome subunits often display severe developmental defects or even show embryo lethality , confirming the importance of the UPS for overall plant fitness [40] . During the past few years , a growing body of evidence has indicated that the UPS is not only implicated in crucial cellular survival mechanisms , but also plays a central role in plant defence during PTI as well as during ETI [38] , [41] . For example , several E3 ligases have been shown to be required for the development of HR in Cf-9 mediated resistance in response to the fungal avirulence protein Avr9 in tobacco [42] . Furthermore , RING-finger E3 ubiquitin ligases in Arabidopsis are involved in RPM1- and RPS2-mediated elicitation of the HR [43] and Arabidopsis PUB17 ( an U box E3 ligase ) knockout plants are compromised in RPS4-mediated resistance against Pseudomonas syringae pv . tomato containing avirulence genes AvrB and AvrRPS4 [44] . The U-box E3 ligases PUB22 , 23 , and 24 have been demonstrated to negative regulate PTI responses in Arabidopsis [45] . In contrast , a number of bacterial T3Es have been shown to exploit the host cell UPS for instance by acting as E3 ligases , such as AvrPtoB [46] , [47] , or by otherwise promoting ubiquitination of target proteins in order to suppress plant defence , like HopM1 [48] . However , proteasomal subunits have yet not been identified as direct targets of T3Es in plants . Recently , it has been shown that P . syringae pv . syringae strain B728a secretes a small non-ribosomal peptide called syringolin A ( SylA ) which acts as an inhibitor of the host cell proteasome [24] . A SylA deficient strain caused reduced symptom development on susceptible bean plants suggesting that SylA contributes to bacterial virulence . Thus , the proteasome appears to represent a valid target for T3Es to promote bacterial virulence . Because of its central role in numerous regulatory pathways , inhibition of the proteasome by bacterial effector molecules can be expected to elicit pleiotropic responses and it is not obvious how the pathogen would benefit from these . The analysis of Arabidopsis mutants compromised in certain subunits of the proteasome suggests that the proteasome contributes to basal defence responses . An Arabidopsis rpn1a mutant displayed enhanced susceptibility toward virulent and avirulent P . syringae strains as well as to the biotrophic fungal pathogen Golovinomyces cichoracearum while no effect on virulence could be observed upon infection of mutant plants with Botrytis cinerea , a necrotroph [49] . This led to the suggestion that RPN1a is involved in resistance against biotrophic pathogens , but not necrotrophic pathogens . From a number of additional Arabidopsis proteasome subunit mutants tested only those affected in RPT2a and RPN8a function fully suppressed edr2-mediated powdery mildew resistance indicating that the different proteasome subunits might have distinct roles in mediating plant defence responses [49] . RPT6 knock-out alleles in Arabidopsis have thus far not been described; however , our own experiments show that suppression of RPT6 expression by VIGS in pepper is lethal to the plants . This precludes a genetic analysis of RPT6 function in this system but it implies that RPT6 is essential for proper proteasome function and thus constitutes a valid target for T3Es to interfere with proteasome activity . In contrast to a previous study [17] we could show that a Xcv xopJ deletion mutant was slightly but significantly reduced in bacterial growth in a compatible interaction with pepper plants . Thus , the question arises as to how a XopJ-mediated inhibition of the proteasome contributes to bacterial virulence . Measurement of overall proteasome activity in Xcv infected pepper leaves revealed a significant induction in proteasome activity that was even higher upon infection with an Xcv ΔxopJ deletion strain . On the one hand this indicates that XopJ indeed contributes to suppression of proteasome activity during infection , confirming the findings from transient expression of XopJ , while on the other hand infection with virulent Xcv per se appears to induce the proteasome most likely as a consequence of slightly elevated SA levels in the course of induced defence . This is further corroborated by the fact that infection of pepper with a Xcv ΔhrpF mutant , which lacks a functional T3SS and thus is not able to suppress basal defence responses , causes induction of the proteasome comparable to that seen upon Xcv ΔxopJ infection . Thus , induction of proteasome activity might be a component of basal defence . However , it could also be possible that Xcv translocates T3Es that require and thus induce proteasome activity for their virulence function as it has been shown for effectors from a range of other bacterial pathogens [50] . A recent publication suggests that XopL of Xcv exhibits E3 ubiquitin ligase activity in planta and is able to subvert plant immunity [51] . Hence , XopL virulence function would rely on a functional proteasome . This apparent contradiction can be resolved if UPS-related T3Es would act spatially separated from XopJ . The in planta BiFC analysis indicates that the interaction between XopJ and RPT6 occurs at or close to the PM . The proteasome is assumed to be distributed between the cytosol and the nucleus of the cell; however , proteomics studies imply that RPT2 can be myristoylated [52] , [53] and thus could target a subset of 26S particles to the PM where they might serve a specialized function . Along that line , it has been shown that a RPT2a G2A mutant was able to rescue most but not all of the phenotypic functions of RPT2a [54] . Xcv can be considered as a hemibiotrophic pathogen that exhibits characteristics of both biotrophs and necrotrophs , depending on the stages of its life cycle . In the early stages of infection , Xcv requires living host tissue to thrive and multiply . Thus , host programmed cell death has been suggested to constitute an effective way to mount an efficient defence response towards a pathogen in the biotrophic phase while the bacterium would need to repress this reaction in order to allow disease progression . Leaves infected with an Xcv ΔxopJ deletion strain developed necrotic lesions as early as 3 dpi while Xcv wild type infected leaves appeared asymptotic at this time point . This suggests that XopJ acts to prevent host cell death during the biotrophic phase of infection . Given the fact that an Xcv ΔxopJ deletion strain is slightly impaired in bacterial multiplication during infection of susceptible pepper plants it seems that the XopJ mediated delay in the development of tissue necrosis is required for full pathogen growth in pepper . A similar role has been proposed for XopD during the compatible interaction of Xcv with tomato [28] . XopD alters the kinetics of leaf chlorosis and necrosis without affecting the number or rate of appearance of necrotic lesions and it furthermore acts as a tolerance factor to increase the ability of the host to cope with bacterial colonization . Interestingly , it appears that XopD is not required for full virulence of Xcv on pepper and it has been suggested that another T3E could play a functionally redundant role in pepper and thus might mask XopD action [28] . Future studies using a xopD/xopJ double mutant could shed further light on a functionally redundant role of these two T3Es . In tomato , there are two stages of disease symptom development during infection with Xcv [26] , [55] . The primary response consists of localized lesions , which is followed by a secondary phase of chlorosis and necrosis spreading out from the primary sites of infection . It has been shown that the infection of tomato with virulent Xcv was associated with a substantial increase in SA levels . The analysis of transgenic tomato plants deficient in the accumulation of SA indicates that this secondary phase of Xcv-induced disease is SA dependent as these plants did not develop tissue necrosis [26] . The infection experiments of pepper with a XopJ deficient Xcv strain presented in this study show that XopJ is necessary to prevent SA accumulation and SA associated signalling during infection and the suppression of tissue necrosis by XopJ is likely a consequence of reduced SA signalling . The fact that XopJ alters the abundance of SA marker genes as well as of genes involved in development of leaf senescence provides further evidence for a role of XopJ in the suppression of SA-dependent host responses . Due to its role in triggering host programmed cell death SA is considered to be a central regulator of defence against biotrophic and hemi-biotrophic pathogens [56] . However , Arabidopsis basal defence responses such as bacterial-induced stomatal closure and callose deposition at the cell wall are at least in part also SA dependent [57] , [58] . Consequently , several T3Es from virulent bacteria target the SA pathway to promote pathogenesis . For example , the P . syringae effector HopI1 localizes to chloroplasts where it suppresses SA accumulation [59] . The defense-suppressive activity of HopI1 depends on its interaction with the plant stress chaperone HEAT SHOCK PROTEIN 70 ( HSP70 ) , which is thought to possess a defence-promoting function [60] . In addition , hopPtoM and avrE genes of P . syringae were found to encode suppressors of these SA-dependent basal defense responses , such as callose deposition [58] . Kim et al . [28] could show that during infection of tomato with Xcv XopD functions as a transcriptional repressor , resulting in the suppression of SA-induced defence responses that otherwise would limit Xcv growth . However , in a more recent study the same authors could show that XopD affects ethylene signalling and the suppression of SA responses might rather be a secondary effect [61] . Thus far none of the T3Es affecting SA signalling has been functionally associated with the proteasome and there is still a possibility that inhibition of SA responses by XopJ is an indirect effect through interference with upstream processes . Strikingly , the SylA peptide secreted by P . syringae pv . syringae strain B728a was shown to inhibit stomatal innate immunity in bean and Arabidopsis through inhibition of the proteasome [62] . Further analysis revealed that stomatal closure in response to infection was dependent on an intact SA signalling pathway . Thus , it appears likely that XopJ suppresses SA signalling and the development of tissue necrosis by inhibition of the proteasome through its interaction with RPT6 . Additional support for a role of the proteasome in SA mediated defence response is provided by the finding that Arabidopsis rpn1a , as well as rpt2a and rpn8a mutants accumulated significant lower SA levels than wild type upon infection with virulent Pto DC3000 [49] . It is currently unclear how inhibition of the proteasome by XopJ could affect SA accumulation and signalling . The most parsimonious explanation is that XopJ would inhibit the proteasomal turnover of a negative regulator of SA synthesis or signalling . The master regulator of SA responses in plants NPR1 ( nonepxressor of pathogenesis-related ( PR ) genes ) , a transcriptional co-activator , must be turned over in its phosphorylated form by the proteasome to activate SA responsive genes [63] . Inhibition of the proteasome by XopJ could prevent NPR1 turnover and thus downstream SA responses . However , our results indicate that XopJ interacts with RPT6 close to or at the PM while proteasomal turnover of NPR1 occurs within the nucleus [63] . On the other hand it is currently unknown whether XopJ only inhibits a subpopulation of the proteasome at the PM or whether proteasome complexes in other cellular locations would also be affected . Alternatively , other components of SA signalling could be dependent on proteasomal turnover at the PM . Recently it could be shown that the PM localized RING E3 ubiquitin ligase CaRING1 is required for SA accumulation and induction of SA responsive marker genes in pepper [64] . The observation that the loss of XopJ could be mimicked by external SA application onto wild type Xcv infected pepper leaves might argue for an intact SA signalling which is just not triggered due to too low internal SA levels . In this scenario XopJ would rather interfere with SA synthesis than with signalling . However , VIGS of NPR1 expression in pepper abrogates early tissue necrosis upon infection with Xcv ΔxopJ demonstrating the necessity of a functional SA signalling pathway for this type of host cell death to occur . Although this observation does not necessarily imply that proteasome suppression by XopJ directly interferes with NPR1 function it strongly suggests that XopJ acts to inhibit SA mediated defence responses . Our data also indicate that SA induces RPT6 transcription as well as overall proteasome activity suggesting a positive feedback mechanism to amplify the proteasome dependent induction of SA synthesis or signalling . In Arabidopsis , SA treatment led to the induction of RPN1a expression [49] and spraying plants with benzothidiazole ( BTH ) to induce SA signalling results in increased activity of the proteasome [65] . Pepper plants with reduced expression of NPR1 did not show an increase in proteasome activity upon infection with either Xcv wild type or the Xcv ΔxopJ mutant indicating that the regulation of proteasome activity during defence is at least partly mediated through NPR1 . This is in line with the observation that induction of proteasome activity upon BTH treatment is abolished in an Arabidopsis npr1 knock-out mutant [65] . It is currently not known whether the SA-mediated increase in proteasome activity in pepper is solely due to an increase in gene expression or whether post-translational mechanisms might also contribute to activation . We have previously shown that XopJ inhibits cell wall – associated defence responses such as protein secretion and callose deposition [19] . We could mimic the inhibitory effect of XopJ on secretion of a GFP reporter by applying the proteasome inhibitor MG132 to leaves . It is currently unknown whether proteasome activity is directly required for secretion or whether proteasome inhibition acts indirectly for instance by interference with SA which has been shown to control expression of secretory pathway genes [66] . Treatment of Arabidopsis leaves with MG132 also prevented callose deposition upon challenge with flg22 indicating that proper proteasome function is also required for this type of defence response . These results open the possibility that the previously observed effects of XopJ on protein secretion and callose deposition could well be mediated by the ability of XopJ to inhibit the proteasome . How then does XopJ act mechanistically to inhibit the proteasome ? Several members of the YopJ-like effector family posses acetyltransferase activity [10] , [15] , [16] , [67] . Although the trans-acetylation substrate for these T3Es has not been identified in all cases they have been shown to autoacetylate most likely on a conserved lysine residue [15] , [16] . Although this lysine residue is also present in XopJ [K300; 16] we could neither demonstrate autoacetylation of XopJ nor acetyltransferase activity using recombinant E . coli produced XopJ in the presence of 14C-acetyl CoA with RTP6 as a bona fide substrate ( data not shown ) . It has recently been shown that HopZ1a from P . syringae requires phytic acid as a cofactor for its full acetyltransferase activity [15] . Phytic acid has been previously shown to activate the acetyltransferase activities of YopJ and AvrA , both highly divergent homologs of HopZ1a from animal pathogens [67] and thus might represent a general activator for these effectors . However , in case of XopJ also the addition of phytic acid to the assay did not lead to any detectable acetyltransferase activity ( data not shown ) . HopZ1a as well as AvrBsT from Xcv have weak cysteine protease activities in vitro [9] , [68] . Whether XopJ could act as a protease to mediate destabilization of RPT6 will be subject of future studies . While in yeast a C235A mutation of XopJ abolished its ability to interact with RPT6 the XopJ ( C235A ) mutant is still able to interact with RPT6 in planta although it is no longer able to inhibit the proteasome . This discrepancy in binding of the XopJ ( C235A ) mutant to RPT6 in the two experimental systems is currently unresolved but could reflect differences in sensitivity between the two methods . In addition , we currently cannot exclude the C235A mutation affects protein level or other properties of the protein in yeast which in turn could also affect interaction with RPT6 . Taken together , however , our results strongly argue for an enzymatic activity of XopJ of whatever kind this might be and it appears likely that the effector requires an as yet unknown host cell factor or a host cell mediated posttranslational modification for activation . In conclusion , we have shown that XopJ interacts with the proteasomal subunit RPT6 to inhibit proteasome activity . XopJ represses SA-mediated defence responses and counteracts development of tissue damage during a compatible interaction of Xcv with pepper providing a growth advantage to the bacterium at late stages of infection . Prolonged host cell viability through inhibition of the proteasome is likely to enhance nutrient availability and could also support pathogen spread from the initial site of infection . Future studies will have to reveal the biochemical activity of XopJ and further establish the connection of proteasome activity with SA signalling on the molecular level .
Pepper ( Capsicum annuum cv . Early Cal Wonder ( ECW ) ) and tobacco plants ( Nicotiana benthamiana ) were grown in soil in a greenhouse with daily watering , and subjected to a 16 h light :8 h dark cycle ( 25°C : 21°C ) at 300 µmol m−2 s−1 light and 75% relative humidity . Xcv infections and bacterial growth assays were performed as described previously [69] . Yeast two-hybrid techniques were performed according to the yeast protocols handbook and the Matchmaker GAL4 Two-hybrid System 3 manual ( both Clontech , Heidelberg , Germany ) using the yeast reporter strains AH109 and Y187 . The entire XopJ coding region was amplified by PCR using the primers listed in Table S1 and inserted in the pGBT-9 vector generating a fusion between the GAL4 DNA-binding domain ( BD ) . The yeast strain Y187 carrying the BD-XopJ construct was mated with AH109 cells pre-transformed with either a two-hybrid library from Arabidopsis inflorescence [70] ( kindly provided by the Arabidopsis Biological Resource Center ) or with a library derived from tobacco ( Nicotiana tabacum ) source leaves [71] . Diploid cells were selected on medium lacking Leu , Trp , and His supplemented with 4 mM 3-aminotriazole . Cells growing on selective medium were further tested for activity of the lacZ reportergene using filter lift assays . Library plasmids from his3/lacZ positive clones were isolated from yeast cells and transformed into E . coli before sequencing of the cDNA inserts . Direct interaction of two proteins was investigated by cotransformation of the respective plasmids in the yeast strain AH109 , followed by selection of transformants on medium lacking Leu and Trp at 30°C for 3 days and subsequent transfer to medium lacking Leu , Trp and His for growth selection and lacZ activity testing of interacting clones . For the generation of the AtRPT6b , ScRPT6 and CaRPT6 activation domain fusions the respective coding region was amplified by PCR using the primers listed in Table S1 , inserted into the vector pGAD424 ( Clontech ) and sequence verified . Site directed mutagenesis of XopJ constructs was carried out using the Quick-change site directed mutagenesis kit ( Stratagene , Heidelberg , Germany ) employing primers listed in Table S1 online . All base changes were verified by sequencing . Construction of binary vectors expressing XopJ and its mutant variants XopJG2A and C235A was described previously [19] . The NtRPT6-GFP construct was assembled by amplifying the entire coding region from tobacco cDNA using the primers listed in Table S1 . The resulting PCR fragment was inserted in the pENTR-D/TOPO ( Invitrogen ) and subsequently recombined into pK7WGF2 [72] using L/R-Clonase ( Invitrogen ) . Entry clones of XopJ and NtRPT6 comprising the entire coding region of each cDNA were used in a L/R-reaction with a Gateway-System ( Invitrogen , Karlsruhe , Germany ) compatible version of the BiFC vectors pUC-SPYNE and pUC-SPYCE , respectively [73] . Constructs were delivered into leaf cells of tobacco by particle bombardment using a Bio-Rad PDS – 1000 He particle delivery system according to the manufacturer's instructions . The BiFC-induced fluorescence was detected by confocal laser scanning microscopy on a Leica TCS SP5II after 24 h of incubation at 22°C in the dark . For infiltration of N . benthamiana leaves , A . tumefaciens C58C1 was infiltrated into the abaxial air space of 4- to 6-week-old plants , using a needleless 2-ml syringe . Agrobacteria were cultivated overnight at 28°C in the presence of appropriate antibiotics . The cultures were harvested by centrifugation , and the pellet was resuspended in sterile water to a final optical density at ( OD600 ) of 1 . 0 . The cells were used for the infiltration directly after resuspension . Infiltrated plants were further cultivated in the greenhouse daily watering , and subjected to a 16 h light: 8 h dark cycle ( 25°C : 21°C ) at 300 µmol m−2 s−1 light and 75% relative humidity . Leaf material was homogenized in sodium-dodecyl sulphate-polyacrylamide gel electrophoresis ( SDS-PAGE ) loading buffer ( 100 mM Tris-HCl , pH 6 . 8; 9% β-mercapto ethanol , 40% glycerol , 0 . 0005% bromophenol blue , 4% SDS ) and , after heating for 10 min at 95°C , subjected to gelectrophoresis . Separated proteins were transferred onto nitrocellulose membrane ( Porablot , Machery und Nagel , Düren , Germany ) . Proteins were detected by either an anti-HA antibody ( Sigma ) , anti-myc antibody ( Santa Cruz Biotechnology ) , anti-GFP antibody ( Roche ) , or anti-ubiquitin antibody ( Agrisera ) via chemiluminescence ( GE Healthcare ) . To generate deletions of xopJ , a fragment ranging from position −67 to +147 relative to the ATG and another fragment comprising −96 to +74 relative to the stopp codon of the XopJ coding region were amplified from genomic DNA of Xcv 85-10 by PCR using oligonucleotides harboring appropriate restriction sites ( Table S1 ) . Both fragments were fused by PCR resulting in an internal deletion fragment . The fragment was subsequently cloned into suicide vector pOK1 [74] using BamHI and SalI restriction sites . The resulting constructs were conjugated into Xcv strain 85-10 , and mutants were selected by PCR . Proteasome activity in crude plant extracts was determined spectrofluorometrically using the fluorogenic substrate suc-LLVY-NH-AMC ( Sigma ) according to Reinheckel et al . [75] . In brief , four leaf discs with a diameter of 0 . 7 cm each were harvested and frozen in liquid nitrogen . The leaf material was ground in 200 µl extraction buffer [50 mM HEPES-KOH , pH 7 . 2 , 2 mM ATP , 2 mM DTT , 250 mM sucrose] . After centrifugation the protein concentration of the supernatant was adjusted to 1 mg/ml with extraction buffer . 50 µg of total protein was mixed with 220 µl proteolysis buffer [100 mM HEPES-KOH , pH 7 , 8 , 5 mM MgCl2 , 10 mM KCl , 2 mM ATP] . The reaction was started after 5 min at 30°C by addition 0 , 2 mM suc-LLVY-AMC . Released amino-methyl-coumarin ( AMC ) was measured every two minutes between t0 and t120 min using a fluorescence spectrophotometer ( FLX800 , BioTek ) , with an excitation wavelength of 360 nm and an emission wavelength of 460 nm . Proteasome activity was calculated from the linear slope of the emission curve and is expressed as fluorescence units per minute ( RFU min−1 ) or in percentage relative to controls , respectively . GFP-pull down assays were carried out according to Schwessinger et al . [76] with slight modifications . Approximately 1 g of leaf material was ground to fine powder in liquid nitrogen and 5 ml extraction buffer [50 mM Tris-HCl pH 7 . 5; 150 mM NaCl; 10% glycerol; 10 mM DTT; 10 mM EDTA; 1 mM NaF; 1 mM Na2MoO4 . 2H2O; 1% ( w/v ) PVPP; 1% ( v/v ) P9599 protease inhibitor cocktail ( Sigma ) ; 1% ( v/v ) NP-40] added . Samples were cleared by centrifugation at 16 . 000×g for 15 min at 4°C and adjusted to 2 mg/ml total protein concentration . Immunoprecipitation was performed on 1 . 5 ml total protein by adding 20 µl GFPTrap-M beads ( Chromotek ) and incubation at 4°C for 3–4 h . Beads were washed 4 times with TBS containing 0 . 5% ( v/v ) NP-40 , immunoprecipitates eluted with 30 µl 2× SDS loading buffer and heating at 70°C for 10 min . For electrolyte leakage experiments , triplicates of 1 . 76 cm2 infected leaf material were taken at indicated time points . Leaf discs were placed on the bottom of a 15 ml tube . 8 ml of deionized water was added to each tube . After 24 h of incubation in a rotary shaker at 4°C , conductivity was determined with a conductometer . To measure maximum conductivity of the entire sample , conductivity was determined after boiling the samples for 30 min [77] . To visualize dying cells , leaves were detached and submerged in lactophenol-trypan blue solution ( 0 . 03% trypan blue , 33% [w/v] lactic acid , 33% water-saturated phenol , and 33% glycerol ) . Samples were incubated at 99°C for 1 min followed by incubation at room temperature for 24 h , washed in chloral hydrate solution ( 2 . 5 g mL−1 ) to reduce background staining , and photographed using a Leica MZLIII stereomicroscope ( Leica Microsystems ) . Total RNA was isolated from leaf material and then treated with RNAse-free DNase ( Fermentas ) to degrade any remaining DNA . First strand cDNA synthesis was performed from 2 µg of total RNA using a random hexamer using Revert-Aid reverse transcriptase ( Fermentas ) . For quantitative realtime RT-PCR , the cDNAs were amplified using Brilliant II SYBR Green QPCR Mastermix ( Stratagene ) in an MX3000P real-time PCR instrument ( Stratagene ) . PCR was optimized , and reactions were performed in triplicate . The transcript level was standardized based on cDNA amplification of Actin as a reference . Fold induction values of target genes were calculated with the ΔΔCP equation according to Pfaffl [78] . Statistical analysis was performed using a two tailed Student's t-test . Primers used for RT-PCR and quantitative real-time PCR , respectively , are listed in Table S1 . Free SA and SA glucoside were extracted and analyzed as described [79] . Six-week-old Arabidopsis Col-0 plants were infiltrated with a mixture of 1 µM flg22+1%EtOH or 100 µM MG132 if not otherwise stated . Leaf tissue was harvested 6 hpi and cleared of pigments by treatment with Lactophenol ( 95% EtOH: 5% Lactophenol ) . After staining of leaf material with aniline blue solution ( 0 . 01% aniline blue in 0 . 15M K2HPO4 , pH 9 . 5 ) , leaves were examined with a Leica DMR microscope . The number of callose deposits was determined on four microscopic views taken from four independent leaves . The callose assays reported here were performed two times with similar results . VIGS was performed as described previously [69] . Briefly , Agrobacterium strains with the pTRV1 vector and with pTRV2-GFPsil , PYL279-RPT6 and pTRV2-NPR1 [80] ( OD 600 = 1 . 0 ) were mixed in a 1∶1 ratio , respectively , and the mixture was infiltrated into cotyledons of 2-week-old pepper plants using a 1-mL sterile syringe without a needle . The Agrobacterium-inoculated pepper plants were grown in the green house at 20°C/16°C in the dark for 56 h with 45% relative humidity , and then transferred to a 16 h light :8 h dark cycle ( 25°C : 21°C ) at 300 µmol m−2 s−1 light and 75% relative humidity . Recombinant proteins from Escherichia coli lysates were immobilized on amylose resins ( New England Biolabs ) , incubated for 1 h at 4°C with purified GST-RPT6 , eluted , and analyzed by immunoblotting using either anti-GST antibody ( Sigma ) or anti-MBP antibody ( NEB ) . For callose deposition , plants were co-infiltrated with 1 µM flg22+1% EtOH or 100 µM MG132 . For the analysis of secretion , 100 or 300 µM MG132 or 1% EtOH was infiltrated to plants transiently expressing secGFP 44 hpi . At 46 hpi plants were analysed under the CLSM . For MG132 treatment of pepper leaves , plants were first infiltrated with Xcv strains . Inoculated areas were then infiltrated with 100 µM MG132 or 1% EtOH at 2 dpi . Leaves were photographed 3 dpi . Sequence data from this article can be found in the Arabidopsis Genome Initiative or GenBank/EMBL databases under following accession numbers: At5g19990 ( AtRPT6a ) ; At5g20000 ( AtRPT6b ) ; JX965405 ( NtRPT6 ) ; JX965404 ( CaRPT6 ) ; EHN02423 . 1 ( ScRPT6 ) . Accession numbers of proteins used for sequence alignments can be found in the legend of the respective figures . | Many bacteria that are pathogens for mammals , insects or plants use a specialized apparatus called the type III secretion system to inject a diverse set of effector proteins into the cytoplasm of their eukaryotic host cells in order to alter cellular processes in favour of the pathogen's lifestyle . However , direct cellular targets have been identified for only a few effector proteins and the elucidation of their mode of action is of fundamental interest for the understanding of bacterial virulence strategies . The effector XopJ from the phytopathogen Xanthomonas campestris pv . vesicatoria ( Xcv ) , the causal agent of bacterial spot disease on tomato and pepper plants , belongs to the YopJ-superfamily of effector proteins . Members of this family are found among plant and animal pathogens , as well as plant symbionts . We show here that within plant cells XopJ targets the proteasomal subunit RPT6 to suppress host proteasome activity and thus protein turnover . In pepper leaves , this leads to reduced accumulation of the defence hormone salicylic acid ( SA ) and also attenuates SA-mediated defence responses such as tissue degeneration and defence gene expression . XopJ from Xcv is the first example of a bacterial effector protein targeting the host proteasome and our results also suggest a central role of the proteasome in plant immunity . | [
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] | 2013 | The Xanthomonas campestris Type III Effector XopJ Targets the Host Cell Proteasome to Suppress Salicylic-Acid Mediated Plant Defence |
Protein kinases play critical roles in learning and memory and in long term potentiation ( LTP ) , a form of synaptic plasticity . The induction of late-phase LTP ( L-LTP ) in the CA1 region of the hippocampus requires several kinases , including CaMKII and PKA , which are activated by calcium-dependent signaling processes and other intracellular signaling pathways . The requirement for PKA is limited to L-LTP induced using spaced stimuli , but not massed stimuli . To investigate this temporal sensitivity of PKA , a computational biochemical model of L-LTP induction in CA1 pyramidal neurons was developed . The model describes the interactions of calcium and cAMP signaling pathways and is based on published biochemical measurements of two key synaptic signaling molecules , PKA and CaMKII . The model is stimulated using four 100 Hz tetani separated by 3 sec ( massed ) or 300 sec ( spaced ) , identical to experimental L-LTP induction protocols . Simulations show that spaced stimulation activates more PKA than massed stimulation , and makes a key experimental prediction , that L-LTP is PKA-dependent for intervals larger than 60 sec . Experimental measurements of L-LTP demonstrate that intervals of 80 sec , but not 40 sec , produce PKA-dependent L-LTP , thereby confirming the model prediction . Examination of CaMKII reveals that its temporal sensitivity is opposite that of PKA , suggesting that PKA is required after spaced stimulation to compensate for a decrease in CaMKII . In addition to explaining the temporal sensitivity of PKA , these simulations suggest that the use of several kinases for memory storage allows each to respond optimally to different temporal patterns .
Synaptic plasticity , the activity-dependent change in the strength of neuronal connections , is a cellular mechanism proposed to underlie memory storage . One type of synaptic plasticity is long term potentiation ( LTP ) , which typically is induced by brief periods of high-frequency synaptic stimulation . LTP displays physiological properties suggestive of information storage and has been found in all excitatory pathways in the hippocampus , as well as other brain regions . Late-phase LTP ( L-LTP ) is induced by 4 trains of stimulation separated by either 3–20 sec ( massed ) or 300–600 sec ( spaced ) , lasts more than 3 hours , and requires protein synthesis [1] . Interestingly , the temporal spacing between successive trains regulates the PKA-dependence of L-LTP [2] , [3] . A spaced protocol ( using a 300 sec inter-train interval ) requires PKA , whereas massed protocols ( using 20 sec and 3 sec intervals ) induce L-LTP that is independent of PKA . The mechanisms underlying this temporal sensitivity of PKA dependence are not understood . PKA is composed of two regulatory subunits bound to two catalytic subunits that form a tetrameric holoenzyme . Sequential and co-operative binding of four cAMP to these regulatory subunits results in the release of two catalytic subunits [4] , [5] . In the hippocampus , cAMP is produced by adenylyl cyclase types 1 and 8 , which are activated by calcium and Gsα coupled receptors [6] . Consistent with this pathway of reactions leading to PKA , activation of dopaminergic and glutamatergic pathways is required for the induction of L-LTP in hippocampal CA1 pyramidal neurons [7]–[11] . NMDA receptor activation also leads to stimulation of the calcium sensitive isoform of adenylyl cyclase [12] . Because the induction of L-LTP involves complex networks of intracellular signaling pathways , computational models have been developed to gain an understanding of LTP [13]–[17] . Several of these studies , which specify the model using ordinary differential equations , explain the requirement for high frequency stimulation ( e . g . 100 Hz for LTP ) versus low frequency stimulation ( e . g . 1 Hz for long term depression ) in terms of the characteristics of CaMKII [18]–[21] . Even though PKA has been incorporated in some of these models , PKA activation is typically described using simplified algebraic equations [21]–[23] . These models do not include the role of dopamine or β-adrenergic receptors in PKA activation nor adequately describe the temporal dynamics of PKA activation . Consequently , these models do not evaluate the temporal sensitivity of PKA , and cannot accurately explain why PKA is required for spaced stimulation . In contrast , several models by Bhalla [24] , [25] include not only the signaling pathways leading to PKA activation , but also those for mitogen activated protein kinase ( MAPK ) activation . However , Bhalla did not explore the role of dopamine or PKA in late-phase LTP , and we have utilized more recent experimental data to update several of the reactions , especially those involved in PKA activation . To evaluate the biochemical mechanisms underlying the temporal sensitivity of PKA dependence of L-LTP and the role of dopamine , we developed a single compartment model of postsynaptic signaling pathways underlying L- LTP in CA1 pyramidal neurons of the hippocampus . Reaction rates and pathways are based on published biochemical measurements . Simulations explore the mechanisms underlying temporal sensitivity of LTP to PKA and complementary experiments test the model predictions of the critical temporal interval separating PKA-dependent and PKA-independent LTP .
Simulation results show that the activation of PKA is greater with spaced as compared to massed stimulation ( Fig 2A1 ) . These results are consistent with experimental results [3] showing that PKA is required for spaced , but not massed stimulation . The cumulative activity of PKA with spaced stimulation ( 2321 nM-sec ) is 60% greater than with massed stimulation ( 1455 nM-sec ) . Although the massed protocol produces a higher peak PKA activity , it is not 4 times higher than the peak produced from a single spaced train of stimulation because of sub-linear summation: the PKA peak activity for massed stimulation is only 1 . 4 times higher than the peak activity in response to spaced stimulation ( Fig 2A2 ) . Subsequent trains do not increase the peak activity of PKA , but do contribute to cumulative PKA activity over time by linear summation; therefore more PKA activity is available with spaced stimuli . Simulations are repeated for a range of inter-train intervals to further explore the temporal sensitivity of PKA dependence . Fig 2C shows that cumulative PKA activity increases with temporal interval , with a time constant , τ , of 8 . 5 sec . PKA activity reaches 95% of maximal value within 3 time constant , i . e . , at 25 . 5 sec . This temporal sensitivity is not observed if peak activity is evaluated . Activity at a single time point , such as 10 minutes after stimulation , is often used to compare with experimental measurements that measure enzyme activity at a single time point . Nonetheless , cumulative activity better indicates the ability of an enzyme to act on downstream targets . Using single time point measures of activity may explain why a previous study did not observe temporal sensitivity of PKA . This increase in PKA activity with increasing inter-train interval can partly explain the mechanism of temporal sensitivity of PKA dependence of L-LTP , but the other part of the explanation is likely a deficit in some other molecule , such as CaMKII , which is known to be sensitive to higher frequency stimuli and plays a major role in LTP . Thus , levels of phosphorylated CaMKII were examined for 3 sec and 300 sec inter-train intervals to assess whether PKA dependence was related to a decline in phosphorylated CaMKII with longer inter-train intervals . This peak was evaluated because experiments suggest that phosphoCaMKII anchors at the post-synaptic density ( PSD ) and is not accessible to dephosphorylation by protein phosphatase 1 [28] . This would imply that activity would be proportional to peak value , and the resulting slow decay of phosphoCaMKII precludes a reasonable calculation of the area under the curve . Fig 2B shows that peak activity of phosphorylated CaMKII with 300 sec intervals is lower than with 3 sec intervals , which is opposite to the temporal sensitivity of PKA , suggesting that PKA activity is compensating for a frequency-dependent deficit in CaMKII . To further compare the CaMKII temporal sensitivity with the PKA temporal sensitivity , Fig 2C explores the phosphorylated activity of CaMKII for a range of inter-train intervals . PhosphoCaMKII decreases as temporal interval increases ( beyond 3 sec ) , in agreement with experiments [29] . The time constant of this decrease is 20 . 8 sec , and phosphoCaMKII drops to 95% of its peak value with a 62 sec inter-train interval . The sum of ( normalized ) phosphoCaMKII and PKA activity is independent of interval for all but the very shortest intervals suggesting that PKA is required for spaced stimulation to compensate for a decrease in CaMKII . This result leads to the prediction that PKA will be required for inter-train intervals greater than ∼62 sec . The prediction that PKA is required for intervals greater than ∼62 sec was tested by inducing L-LTP at Schaffer collateral-CA1 synapses in mouse hippocampal slices using 4 trains of high frequency stimulation , with either 40 sec or 80 sec inter-train intervals , in the presence of either KT5720 or vehicle as control . As shown in Fig 3A , LTP induced by stimulation trains delivered at 80 sec inter-train intervals was attenuated in KT5720-treated slices compared to vehicle controls . At 120 min after LTP induction , the average fEPSP slopes were significantly different: 196±11% for vehicle-treated slices and 112±7% for KT5720-treated slices ( Mann-Whitney U test , p<0 . 05 ) . This demonstrates that LTP induced by 4 trains of high frequency stimulation delivered at 80 sec inter-train intervals requires PKA . In contrast , fEPSP slopes are not significantly different between KT5720 and control slices using 40 sec inter-train intervals ( Fig 3B ) . At 120 min after LTP induction , the average fEPSP slopes were 167±14% for vehicle-treated slices and 167±13% for KT5720-treated slices ( Mann-Whitney U test , p>0 . 05 ) . This indicates that LTP stimulated by 4 trains of high frequency stimulation delivered at 40 sec inter-train interval is PKA-independent . These results , and previous experimental results on PKA dependence [3] , are summarized in Fig 3C , which demonstrates that L-LTP induced with temporal intervals of 3 sec to 40 sec are PKA-independent , whereas L-LTP induced by temporal intervals of 80 sec and 300 sec are PKA-dependent . These experiments support the model prediction , thus verifying the model and its explanation of mechanisms underlying PKA dependence . In the hippocampus , adenylyl cyclase type 1 is synergistically activated by both calcium-calmodulin and dopamine , which is released during 100 Hz stimulation [30] from fibers innervating hippocampal area CA1 [31] . Further support for the role of dopamine is provided by experiments that show that L-LTP induced using a 10–12 min inter-train interval is reduced when dopamine receptors are blocked [8] , [30] , [32] . Thus , simulations were repeated with the dopamine receptor blocked , to evaluate the contribution of dopamine to L-LTP . Fig 4 shows that cumulative PKA activity is reduced significantly with both massed and spaced stimulation intervals when dopamine receptor function is blocked . The PKA activity for a 300 sec inter-train interval with no dopamine is similar to the PKA activity for the 3 sec inter-train interval with dopamine present , suggesting that L-LTP induction with spaced stimuli requires the higher PKA produced by spaced stimuli . Though the lack of dopamine reduces PKA activity for the 3 sec inter-train interval , this is not functionally significant because L-LTP with massed stimulation is PKA-independent . In other words , a 300 sec inter-train interval activates insufficient quantities of CaMKII , and additional dopamine stimulated PKA activity is required for the 300 sec interval only . Stimulation with a 3 sec interval activates sufficient CaMKII , and thus , the model predicts that blocking dopamine receptors would not block L-LTP for this interval . The sensitivity of cumulative PKA activity to different temporal intervals follows that of adenylyl cyclase ( Fig 5A ) and cAMP ( Fig 5B ) . The first 100 Hz train produces a 600 nM increase in adenylyl cyclase activity from binding to calmodulin and Gsα ( Fig 5A2 ) . With the massed protocol , the second 100 Hz train only produces an additional 300 nM increase in adenylyl cyclase activity , because free adenylyl cyclase is depleted with massed trains to a significant degree . More than 80% of unbound adenylyl cyclase 1 is available for activation by the first train of stimulation ( Fig 5C ) ; unbound adenylyl cyclase 1 decreases by 20% for massed ( Fig 5C1 ) , but remains at more than 80% for spaced stimulation ( Fig 5C2 ) . Calmodulin , which activates adenylyl cyclase 1 , also exhibits a small degree of depletion , in part because it binds to other molecules , such as protein phosphatase 2B and phosphodiesterase 1B , with extremely high affinity . Thus , subsequent stimulation trains produce smaller increments in activated adenylyl cyclase for massed , but not for spaced stimulation . These lower adenylyl cyclase activity increments result in lower cAMP increments with subsequent trains using massed stimulation: 300 nM for the first train and 150 nM for the second train ( Fig 5B2 ) ; thus the total cAMP produced from four trains of stimulation is less than four times the cAMP produced for one train . Note that the temporal pattern of cAMP , which decays within 40 sec to basal levels , agrees with measurements using a fluorescent Epac-1 probe [33] , [34] , verifying this aspect of the model . Therefore , the activation of PKA is greater with spaced as compared to massed stimulation because adenylyl cyclase activity is greater with spaced as compared to massed stimulation . PKA is important in LTP because it phosphorylates AMPA receptors and inhibitor-1 , as well as other plasticity related proteins [35]–[38] , not all of which have been identified . Because rates of AMPA receptor phosphorylation have not been directly measured , we chose to evaluate the effect of PKA activity on a different target , namely inhibitor-1 . Furthermore , inhibition of protein phosphatase 1 by phosphorylated inhibitor-1 will enhance phosphorylation of many PKA targets via inhibition of dephosphorylation . Thus , examination of the phosphorylation state of inhibitor-1 in these simulations both represents the ability of PKA to phosphorylate downstream targets , and also indicates whether free protein phosphatase 1 will be sensitive to temporal interval . As seen in Fig 6A , the amount of phosphorylated inhibitor-1 is 50% greater for spaced than massed stimulation . Similar to that observed with PKA activity , the peak value is higher for massed stimuli , but total phosphorylated inhibitor-1 is greater for spaced stimuli . This shows that the temporal sensitivity of PKA activity propagates to downstream targets . The phosphorylated inhibitor-1 binds to protein phosphatase 1 with high affinity , inhibiting its activity . Thus , the 50% increase in phosphorylated inhibitor-1 produces a 50% decrease in protein phosphatase 1 ( Fig 6B ) . This suggests that the enhanced activity of PKA with spaced stimulation will suppress protein phosphatase 1 activity , reinforcing the phosphorylation of plasticity related proteins . To test whether the enhanced inhibitor-1 phosphorylation increased CaMKII phosphorylation , simulations were repeated with PKA phosphorylation of inhibitor-1 blocked . The decrease in CaMKII phosphorylation was small ( Fig S2A ) , suggesting other mechanisms to enhance PKA activity are important ( discussed below ) . To investigate the robustness of results ( i . e . , whether the results are sensitive to variation in parameters ) , simulations are repeated using parameter values 2 to 10 times larger or smaller than the control values , for parameters that are least constrained by biochemical data . For instance , though the quantity of PKA has been estimated to be 1 . 2 µM in brain tissue , assuming the protein distributes in 70% of intercellular space [39] , the existence of localized pools of PKA suggest that the effective quantity of this enzyme in the synapse could be higher than the estimated quantity . Similar arguments can be made for protein phosphatase 1 . Thus , simulations are repeated using both higher and lower quantities of PKA , protein phosphatase 1 , protein phosphatase 2B , as well as Ca2+ influx . As shown in Fig S3 , the main results from this model are qualitatively robust . Though the PKA activity increases when enzyme quantities are increased , spaced stimulation still produces ∼60% more total activity than massed stimulation ( Fig S3A ) . The quantity of protein phosphatase 1 has no effect on PKA activity , but does modify the decay rate of phosphoCaMKII . Regardless of protein phosphatase 1 quantity or dephosphorylation rate , spaced stimulation produces lower phosphorylated CaMKII than massed stimulation ( Fig S3B ) . Peak Ca2+ has a different effect on phosphoCaMKII: it changes the peak value with no change in decay , and no change in frequency sensitivity ( Fig S3D ) . PKA was minimally affected by variation of peak Ca2+ ( Fig S3C ) . A recent FRET imaging experiment suggests that CaMKII activity in spines is transient in response to synaptic stimulation [40] . Thus , additional simulations evaluated whether the results are sensitive to persistence of CaMKII . Transient phosphoCaMKII was produced by allowing protein phosphatase 1 to dephosphorylate the calmodulin bound form of phosphoCaMKII ( Fig S2A ) . Using this more transient phosphoCaMKII in simulations , CaMKII activity is quantified as area under the curve ( instead of peak ) . Fig S2B shows that area under the curve increases for PKA and decreases for phosphoCaMKII with increasing inter-train interval , the latter with a time constant of 17 . 8 sec – close to the time constant for the persistent model of CaMKII . Thus , the prediction that PKA is required to compensate for a decrease in phosphoCaMKII is robust to this variation in CaMKII dynamics .
To better understand the complex intracellular signaling networks underlying the temporal sensitivity of PKA dependence of L-LTP , we developed a computational model of the calcium and cAMP signaling pathways involved in PKA and CaMKII activation in hippocampal CA1 neurons . The model is based on published biochemical measurements of many key signaling molecules , most notably PKA and CaMKII . Simulations of four trains of 100 Hz stimuli separated by 300 sec or 3 sec revealed that spaced stimulation activates more PKA and less CaMKII than massed stimulation . Thus , PKA activity may be required for spaced stimulation because more of it is active , and less phosphoCaMKII is available . Simulations were repeated for a range of inter-train intervals , to further explore the PKA dependence of L-LTP induction . PKA activity increases exponentially with increasing inter-train interval , compensating for the decrease in phosphoCaMKII with increasing inter-train interval . The time constant of phosphoCaMKII decrease was 20 . 8 sec; thus , the model predicts that L-LTP induced with an inter-train interval greater than 62 sec ( 3τ ) will be dependent on PKA , and L-LTP induced with an interval less than 62 sec will be independent of PKA . Experiments confirm this prediction , showing that a 40 sec inter-train interval is PKA-independent and an 80 sec inter-train interval requires PKA . The temporal sensitivity of PKA differs from that in a previously published model [29] mainly due to the different method of quantifying PKA activity . The present study measured cumulative PKA activity as area under the curve and found an increase with temporal interval . In the previously published model , PKA activity was quantified as the peak activity at 600 sec after the last tetanus , to compare with experimental measurements which also measured activity at 600 sec after the last tetanus . In that study , PKA peak activity did not exhibit temporal sensitivity , and thus could not explain the temporal sensitivity of PKA dependence of LTP . To compare the present model results with that previous model , PKA activity was quantified as activity at 600 sec after the last tetanus . Using this quantification , temporal sensitivity of PKA activation in the present model is minimal , in agreement with Ajay and Bhalla [29] . Nonetheless , cumulative activity is a better measure of the ability of a kinase to phosphorylate downstream substrates such as AMPA receptors or inhibitor-1 , because cumulative activity is proportional to average enzyme activity over the time course of the enzyme . With regards to CaMKII activity , both cumulative , when CaMKII phosphorylation is transient , and peak when CaMKII phosphorylation is persistent , were good predictors of the critical inter-train interval . Another PKA-dependent form of L-LTP is induced by theta-burst stimuli [41] , which uses short bursts of 100 Hz stimulation ( e . g . , 4 pulses ) repeated at 200 msec intervals . A typical experimental induction protocol uses fifteen repetitions of 4 bursts yielding 60 pulses total , far less than provided with 4 bursts of 100 Hz . Model simulations show that both CaMKII and PKA are lower with this stimulation due to the lower number of pulses . These simulations of post-synaptic mechanisms cannot explain the PKA-dependence of theta-burst L-LTP because theta-burst L-LTP involves pre-synaptic mechanisms [42] . In our model , activated PKA is represented as the cumulative quantity of the free catalytic subunit . Although stimulation produces about a 60% increase in free catalytic subunit , the peak quantity of free catalytic subunit is relatively small ( less than 50 nM for massed stimulation and less than 35 nM for spaced stimulation ) . This may suggest that the quantity of free catalytic subunit would be insufficient for the PKA-dependent L-LTP ( i . e . , both the increase in inhibitor-1 phosphorylation , and the inhibition in CaMKII dephosphorylation were small ) , especially given the number of PKA targets . The small quantity of PKA free catalytic subunit produced is due to the high affinity ( 9 nM ) of the regulatory subunit for the catalytic subunit even when all four cAMP molecules are bound . One possible solution to the low quantity of PKA catalytic subunit is that the cAMP-saturated holoenzyme is catalytically active toward its substrates . Binding of four cAMP to the linker region of the regulatory subunit causes a conformational change , exposing the catalytic site without complete dissociation [43] , [44] . The L-LTP induction paradigms produce a significant amount of cAMP-saturated holoenzyme ( twice as much as free catalytic subunit ) . If this form is active , the quantity of active PKA would be three times higher . In addition , the actions of anchoring also increase local PKA activity in the synapse . A kinase anchoring proteins ( AKAPs ) bind to the regulatory subunit of the PKA holoenzyme [45] . By tethering the PKA holoenzyme near a preferred substrate at a particular subcellular location , a small number of molecules could produce significant phosphorylation of its substrate . In support of this concept , experiment shows that hippocampal synaptic plasticity requires not only PKA activation , but also the activation of an appropriately anchored pool of PKA [42] , [46] . As previously mentioned , the conceptual model of CaMKII activation predicts a positive feedback loop in which increased phosphorylation leads to an increased rate of subsequent phosphorylation . Therefore , subsequent stimulus trains should produce increasing increments in CaMKII activity . Similar to other single compartment models [19] , [20] , [47] , this positive feedback response is not observed in the model unless additional calmodulin is provided ( Fig S4A ) . Calmodulin binds with high affinity to protein phosphatase 2B and phosphodiesterase 1B , and with intermediate affinity to adenylyl cyclase as well as CaMKII . This binding causes a decrease in Ca4-calmodulin with subsequent trains due to competition for calmodulin between the CaMKII pathway and other pathways . Calmodulin is a diffusible protein; thus , in a dendritic spine free calmodulin would diffuse into the spine from the dendrite to replace the bound calmodulin . In addition , neurogranin is a calmodulin binding protein that releases calmodulin upon Ca2+ stimulation; in essence neurogranin acts as a calmodulin reservoir [48]–[50] . Simulations in which additional calmodulin is provided yields a frequency sensitivity of phosphoCaMKII that agrees with experimental measurements [29] . Not only CaMKII , but also PKA activation is limited by free available calmodulin , since the predominant adenylyl cyclases ( 1/8 ) in hippocampus are activated by calmodulin . Calmodulin depletion results in decreasing increments of adenylyl cyclase activity , cAMP production , and PKA activation with massed stimulation , causing sublinear summation . Providing additional calmodulin reduces the degree of sublinear summation , though the limited quantity of adenylyl cyclase 1 and adenylyl cyclase 8 also contributes to sublinear summation . Thus , as illustrated in Fig S4B , the incorporation of additional calmodulin does not change the main result , namely that PKA cumulative activity is higher with spaced stimulation . One way in which LTP is expressed post-synaptically is as enhanced phosphorylation of AMPA receptors leading to insertion of new AMPA receptors . The phosphorylation state of AMPA receptors depends on the balance of kinases and phosphatases including PKA , CaMKII and protein phosphatase 1 [51]–[53] . Active PKA directly phosphorylates the AMPA receptor GluR1 subunit at Ser845 , enhancing AMPA channel function [54] and leading to increased AMPA channel expression . PKA indirectly governs the dephosphorylation activity of protein phosphatase 1 by phosphorylating inhibitor-1 with very high affinity allowing it to bind protein phosphatase 1 . Other substrates of PKA are implicated in hippocampal synaptic plasticity , including phosphodiesterase type 4D3 and inositol triphosphate receptor channels [55] , [56] . AMPA channel phosphorylation modulates expression of LTP , but transcription and translation are required for L-LTP [57] . A target of phosphorylation by active PKA involved in transcription is the cAMP Response Element Binding Protein ( CREB ) in the nucleus . Phosphorylated CREB increases activation of transcription and protein translation . Members of the mitogen activated protein kinase ( MAPK ) family are targets of PKA that plays a role in transcription , translation , and synaptic plasticity [58] . One member of the MAPK family is extracellular signal-regulated kinase type II , which is phosphorylated by several signaling pathway kinases , such as PKA and also CaMKII through synGAP [59] , [60] . Ajay and Bhalla [29] demonstrate that both extracellular signal-regulated kinase type II activity and the magnitude of LTP induction are maximal using inter-train intervals of 300–600 sec; in this context , our results suggest that part of the temporal dependence of extracellular signal-regulated kinase type II is due to PKA . Yet another target of PKA involved in maintenance of LTP is the atypical protein kinase C , type Mζ , which is phosphorylated at a site of convergence of both PKA and CaMKII [61] . Thus , our hypothesis that the combination of CaMKII plus PKA is critical for L-LTP is consistent with several of these target proteins whose activity integrates multiple kinases . Additional evidence suggests that PKA is critical for synaptic tagging [46] , [62] , [63] , which provides the synaptic specificity important for information processing . The synaptic tag theory proposes that L-LTP associated gene products can only be captured and utilized at synapses that have been tagged by previous activity [64] . Both CaMKII and PKA have been implicated in phosphorylation of an unidentified synaptic substrate , which appears necessary to set a tag at activated synapses to allow capture of plasticity factors ( i . e . CRE-driven gene products , newly synthesized AMPA receptors or mRNAs ) . One possibility is that phosphorylation of the tag can be provided by either CaMKII , PKA , or both , depending on the temporal interval of stimulation . To further evaluate L-LTP , it will be necessary to include some of these signaling events downstream of PKA , such as activation of extracellular signal-regulated kinase type II . Furthermore , anchoring of proteins in spines , communication with the larger dendrites , and other spatial details all suggest that single compartment models are not sufficiently accurate . Thus , multi-compartmental models will be critical for evaluating issues such as the distribution of synaptic inputs underlying the spread of biochemical signals from synapses to dendrites [25] or the diffusion of biochemical signals between spines [65] . For example , preliminary simulations using a multi-compartmental stochastic model suggest that localization of dopamine receptors and PKA leads to larger phosphorylation of inhibitor-1 , and inhibition of protein phosphatase 1 , as experimentally observed [35] . Given the complexity of non-linear interactions among signaling pathways , simulations using these novel multi-compartmental models promise to enhance understanding of the mechanisms underlying synaptic plasticity .
All research with animals was consistent with NIH guidelines and approved by the IACUC at the University of Pennsylvania . The single compartment , computational model , illustrated in Fig 1A , consists of signaling pathways known to underlie synaptic plasticity in hippocampal CA1 pyramidal neurons . Calcium influx through the NMDA receptor leads to calcium-calmodulin activation of adenylyl cyclase types 1 and 8 [66] , phosphodiesterase type 1B , protein phosphatase 2B ( PP2B or calcineurin ) and CaMKII . In addition , CA1 is innervated by dopamine fibers[67] , and dopamine type D1/D5 receptors , coupled to Gsα , are expressed in CA1[68] . Dopamine levels increase in response to 100 Hz stimulation [30] , leading to enhanced adenylyl cyclase ( type 1 ) activity [69] , [70] , and increases in cAMP , which activate PKA [71] , [72] . The phosphorylation of inhibitor-1 by PKA transforms inhibitor-1 into a potent inhibitor of protein phosphatase 1 [73] , [74] , thereby decreasing CaMKII dephosphorylation . Though not included in the model , the phosphorylation state of the AMPA receptor is controlled by CaMKII , PKA and protein phosphatase 1 [75] , [76] . All reactions in the model are listed in Tables 1 and 2 and are described as bimolecular chemical reactions or as enzymatic reactions except for PKA ( described below ) and CaMKII reactions ( Text S1 ) . A set of rate equations is constructed to describe the biochemical reactions of the model's pathways . These rate equations are nonlinear ordinary differential equations with concentrations of chemical species as variables . Equations are derived assuming all reactions are in a single compartment and the number of molecules is sufficient for mass action kinetics , as follows: For a bimolecular chemical reaction: ( 1 ) in which substrates , A and B , are consumed to create products , C and D , the rate of reaction is represented by a differential equation of the form ( 2 ) where kf and kb are the forward and backward rate constants of the reaction , and Kd = kf /kb is the affinity . For an enzyme-catalyzed reaction: ( 3 ) where E , S , ES and P denote enzyme , substrate , enzyme-substrate complex and product , the rate of production of P , d[P]/dt , is given by: ( 4 ) For enzymatic reactions kcat defining the last , catalytic step , is the rate at which product appears , and the affinity Km is defined as . When kb is not known explicitly , kb is defined as 4 times kcat [14] . PKA ( cAMP-dependent protein kinase ) is activated by the cooperative binding [77] of cAMP to two tandem cAMP-binding sites ( called A and B sites ) on each of the two regulatory subunits . The binding of four cAMP leads to the dissociation of the active catalytic subunits , allowing them to phosphorylate their protein targets [4] . In the model pairs of cAMP bind with first order kinetics as measured by the fraction of free catalytic subunit as a function of cAMP concentration [78] , [79] . The affinity of site A relative to the affinity of site B is obtained from Herberg et al . [77] , [80] . Keeping this ratio , the affinity of these sites was adjusted to match the overall affinity of the holoenzyme [72] ( Fig S1A ) . The only exception to the single compartment approximation is that additional calmodulin was provided to prevent calmodulin from decreasing significantly during stimulation . Calmodulin is a diffusible protein , thus in a dendritic spine , free calmodulin would diffuse into the spine from the dendrite to replace the bound calmodulin . In addition , neurogranin is a calmodulin binding protein that releases calmodulin upon Ca2+ stimulation; in essence neurogranin acts as a calmodulin reservoir [48]–[50] . The increase in calmodulin was made proportional to the difference between initial calmodulin and free calmodulin . The rationale is that without additional calmodulin , subsequent stimulation trains produce a smaller increment in phosphoCaMKII ( 1st: 166 nM , 4th: 154 nM ) , which is inconsistent with the positive feedback loop implicit in a widely accepted conceptual model of CaMKII activation [81] , [82] . With added calmodulin , increased phosphorylation leads to an increased rate of subsequent phosphorylation since phosphorylated CaMKII has higher activity than calmodulin-bound unphosphorylated CaMKII ( Fig S4A ) . Rate constants used in this model were obtained from the biochemical literature and are tabulated with their reactions in Tables 1 and 2 . The differential equations are programmed in XPPAUT and run under the Linux operating system . The model is freely available for download from ModelDB: http://senselab . med . yale . edu/senselab/modeldb/ Simulations used the numerical integration method called “stiff” with a time step of 0 . 01 sec . To understand how L-LTP dependence on PKA is sensitive to temporal interval , simulations were performed using stimulation paradigms identical to the experimental paradigms typically used to induce L-LTP . Thus , we simulated four trains of 100 Hz stimulation for a duration of 1 sec ( Fig 1B ) , delivered either 3 sec apart ( massed ) or 300 sec apart ( spaced ) , and compared these two simulation “groups” with a control simulation run without induction stimuli . The total number stimulation pulses may modify the activation of PKA or CaMKII; therefore , they were held constant for these simulations [3] , [83] . Each stimulation pulse triggered a transient elevation in intracellular calcium concentration ( Fig 1B ) , similar to experimental observations [84] , [85] of the response to synaptic activation of the NMDA receptors . Stimulation at 100 Hz frequency results in accumulation of calcium ( Fig 1C ) [86] because individual transients do not completely decay . Each train of stimulation was accompanied by an increase in dopamine concentration , as if released from dopaminergic synaptic terminals . The amplitude of the dopamine pulse ( Fig 1C ) is based on Rice and Cragg [87] . The simulation was run for a period of 3000 seconds following stimulation . Hippocampal slices were prepared from wild type mice as described previously [9] . Extracellular field excitatory postsynaptic potentials ( fEPSPs ) were recorded with a glass microelectrode positioned in stratum radiatum of area CA1 . Evoked fEPSPs were elicited by stimulation of the Schaeffer collateral fibers with an extracellular bipolar nickel-chromium electrode . The stimulation intensity was adjusted to give fEPSP amplitudes that were approximately 40% of maximal fEPSP sizes . Control “baseline” responses were elicited once per minute at this intensity . The stimulation protocol was applied by delivering four trains ( 100 Hz , each of 1sec duration ) with either 40 sec or 80 sec inter-train intervals in either pretreated KT5720 hippocampal slices or control ( Vehicle ) slices . KT5720 ( Biomol ) , an inhibitor of catalytic subunits of PKA [88] , was dissolved in DMSO and diluted in ACSF to a final perfusate concentration of 1 µM ( 0 . 1% DMSO ) , the control slices were pretreated with 0 . 1% DMSO vehicle , which had no effect on basal fEPSPs . KT5720 or vehicle was delivered for 30 minutes , from 15 minutes before , until 15 minutes after LTP induction . Data analysis was performed using Statistica 7 . 1 software ( Statsoft , Inc . , Tulsa , OK ) . Electrophysiological data from LTP recordings were analyzed by nonparametric tests because the analyses of repetitive recordings over long durations do not allow the use of parametric tests [89] . The initial slope of the fEPSP at each time point was analyzed . The Mann-Whitney U test was used to compare between two groups . Differences were considered statistically significant when p<0 . 05 . | The hippocampus is a part of the cerebral cortex intimately involved in learning and memory behavior . A common cellular model of learning is a long lasting form of long term potentiation ( L-LTP ) in the hippocampus , because it shares several characteristics with learning . For example , both learning and long term potentiation exhibit sensitivity to temporal patterns of synaptic inputs and share common intracellular events such as activation of specific intracellular signaling pathways . Therefore , understanding the pivotal molecules in the intracellular signaling pathways underlying temporal sensitivity of L-LTP in the hippocampus may illuminate mechanisms underlying learning . We developed a computational model to evaluate whether the signaling pathways leading to activation of the two critical enzymes: protein kinase A and calcium-calmodulin-dependent kinase II are sufficient to explain the experimentally observed temporal sensitivity . Indeed , the simulations demonstrate that these enzymes exhibit different temporal sensitivities , and make a key experimental prediction , that L-LTP is dependent on protein kinase A for intervals larger than 60 sec . Measurements of hippocampal L-LTP confirm this prediction , demonstrating the value of a systems biology approach to computational neuroscience . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] | [
"computational",
"biology/computational",
"neuroscience"
] | 2010 | Temporal Sensitivity of Protein Kinase A Activation in Late-Phase Long Term Potentiation |
Neuronal computations strongly depend on inhibitory interactions . One such example occurs at the first retinal synapse , where horizontal cells inhibit photoreceptors . This interaction generates the center/surround organization of bipolar cell receptive fields and is crucial for contrast enhancement . Despite its essential role in vision , the underlying synaptic mechanism has puzzled the neuroscience community for decades . Two competing hypotheses are currently considered: an ephaptic and a proton-mediated mechanism . Here we show that horizontal cells feed back to photoreceptors via an unexpected synthesis of the two . The first one is a very fast ephaptic mechanism that has no synaptic delay , making it one of the fastest inhibitory synapses known . The second one is a relatively slow ( τ≈200 ms ) , highly intriguing mechanism . It depends on ATP release via Pannexin 1 channels located on horizontal cell dendrites invaginating the cone synaptic terminal . The ecto-ATPase NTPDase1 hydrolyses extracellular ATP to AMP , phosphate groups , and protons . The phosphate groups and protons form a pH buffer with a pKa of 7 . 2 , which keeps the pH in the synaptic cleft relatively acidic . This inhibits the cone Ca2+ channels and consequently reduces the glutamate release by the cones . When horizontal cells hyperpolarize , the pannexin 1 channels decrease their conductance , the ATP release decreases , and the formation of the pH buffer reduces . The resulting alkalization in the synaptic cleft consequently increases cone glutamate release . Surprisingly , the hydrolysis of ATP instead of ATP itself mediates the synaptic modulation . Our results not only solve longstanding issues regarding horizontal cell to photoreceptor feedback , they also demonstrate a new form of synaptic modulation . Because pannexin 1 channels and ecto-ATPases are strongly expressed in the nervous system and pannexin 1 function is implicated in synaptic plasticity , we anticipate that this novel form of synaptic modulation may be a widespread phenomenon .
Natural scenes contain a large amount of redundant information both in space and time . For optimal coding of the visual scene , most of these redundancies need to be removed . The inhibitory interaction between horizontal cells ( HCs ) and cones is the first step in this process . HCs estimate the global properties of the stimulus . This information is subtracted from the local information sampled by the cones . The result is a strong reduction of redundant information in the cone output signal . In order to reduce spatial redundancies , this feedback mechanism needs to be very fast . If this were not the case , the surround of the bipolar cell receptive field would lag the center for moving stimuli . In contrast , to reduce temporal redundancies , the inhibition needs to be very slow; otherwise , long-lasting activity would not be removed selectively . In this article we show that these two seemingly incompatible requirements are merged into a feedback mechanism that consists of a very fast ephaptic component and a very slow component that modulates the synaptic efficiency by changing the pH buffering in the synaptic cleft of cones . Cones project to HCs that are strongly coupled to each other electrically and provide negative feedback to the cones . Hyperpolarization of HCs by light shifts the activation potential of the presynaptic Ca2+ current ( ICa ) in cones to more negative potentials [1]–[5] , leading to a larger ICa . This increases the Ca2+ concentration in the cone synaptic terminal so more glutamate is released . This modulation is not mediated by GABA [1] , [3] . Two hypotheses have been put forward to account for the modulation of ICa: an ephaptic mechanism [6]–[8] and a proton-mediated mechanism [4] , [9] , [10] . The ephaptic feedback mechanism depends on connexin ( Cx ) hemichannels and possibly pannexin 1 ( Panx1 ) channels expressed at the tips of HC dendrites [6] , [7] , [11] , [12] . These channels form large pores in the cell membrane , leading to an inward current . Given the finite resistance of the synaptic cleft , this inward current creates a slight negativity in the synaptic cleft . This negativity is sensed by the voltage-gated Ca channels of the cones as a slight depolarization of the cone membrane potential . HC hyperpolarization will increase the inward current through the Cx hemichannels , thus increasing the negativity in the synaptic cleft . This will be visible as an inward current in voltage clamped cones , reflecting a shift of ICa to more negative potentials . A major unresolved issue with the ephaptic feedback hypothesis is that it predicts a very fast feedback signal , whereas other studies indicate a relatively slow process [13] , [14] . The proton-mediated feedback hypothesis is based on the pH sensitivity of ICa [15] . The activation potential of ICa shifts to more positive potentials in an acidic condition and to more negative potentials in an alkaline condition . To test the proton-mediated feedback hypothesis , Hirasawa and Kaneko [4] added 10 mM HEPES to the medium to reduce pH changes in the synaptic cleft and were able to show that the feedback-induced shift of ICa was reduced and sometimes even absent . They suggested that hyperpolarized HCs take up protons , which leads to an alkalization of the synaptic cleft . However , these experiments were not conclusive as more recent research found that 20 mM HEPES also induced a number of nonspecific effects , such as intracellular acidification and a direct inhibition of Cx hemichannels [16] . Moreover , the mechanism responsible for the proposed changes in proton concentration in the synaptic cleft has not yet been identified . The aim of this article is to determine the synaptic mechanisms underlying lateral inhibition in the vertebrate outer retina . We show that the negative feedback pathway from HCs to cones is a synthesis of an ephaptic feedback mechanism and a proton-mediated mechanism . The ephaptic mechanism is one of the fastest inhibitory systems known and is especially suitable for spatial redundancy reduction in a dynamic scene . The proton-mediated mechanism depends on extracellular hydrolysis of ATP . HCs release ATP via Panx1 channels located on their dendritic tips that invaginate the synaptic terminals of cones . Ecto-ATPases hydrolyze ATP , which generates protons and a phosphate pH buffer , leading to an acidification of the synaptic cleft that inhibits ICa . This pathway is very slow ( time constant of about 200 ms ) and does not involve purinergic or adenosine receptors . It is especially suitable for reducing temporal redundancies . Our findings not only resolve the longstanding controversy about the mechanism of negative feedback from HCs to cones , they also demonstrate a novel mechanism of synaptic modulation involving ATP released from Panx1 channels .
In zebrafish , the Cx hemichannels at the tips of the HC dendrites are formed by Cx55 . 5 . Zebrafish lacking this Cx ( Cx55 . 5−/− mutant ) have reduced feedback from HCs to cones [7] . Figure 1C shows feedback responses measured in cones of wild-type ( WT , black ) and Cx55 . 5−/− mutant ( red ) zebrafish . The feedback-induced current was reduced by 48±11% in the Cx55 . 5−/− mutant zebrafish ( n = 22 ) compared to WT ( n = 25 ) . To quantify the contribution of both feedback components , double exponential functions were fitted through the feedback responses . Although the time constants of both components were independent of the genotype ( Figure 1D ) , the amplitude of the fast feedback component was reduced in Cx55 . 5−/− mutants such that the fast and slow feedback components now equally contributed to the feedback response . The amplitude of the slow feedback component in Cx55 . 5−/− mutants ( 1 . 62±0 . 39 pA; n = 9 ) did not differ significantly from WT ( 1 . 87±0 . 39 pA; n = 13; p = 0 . 67 ) , illustrating that the reduction of feedback in the Cx55 . 5−/− mutant can be fully accounted for by the reduction of the fast feedback component . These experiments show that the fast component depends on Cx55 . 5 , whereas the slow component does not . Previously we have shown that carbenoxolone , a Cx antagonist , blocks light-induced feedback responses in cones completely [6] . Interestingly , carbenoxolone is also a potent blocker of Panx1 channels [11] . Could Panx1 channels mediate the slow component of feedback ? Panx1 channels are open at the resting membrane potential of HCs ( −35 mV ) , reduce their conductance with hyperpolarization [11] , [20] , [21] , and are modulated by intracellular Ca2+ [11] , [22] . Figure 2A shows that Panx1-IR ( green ) was present as punctated labeling in the outer plexiform layer ( OPL ) , suggesting Panx1 channels were localized at the tips of HC dendrites , which invaginate the cone's synaptic terminals [11] . Immuno-electron microscopy confirms this location . Panx1 labeling ( black dots ) was found in lateral elements flanking the synaptic ribbons ( R ) ( Figure 2B and C ) . Next we determined whether Panx1 channels were active in HCs . Goldfish HCs were dissociated according to a modified protocol of Dowling et al . [23] , [24] ( Figure 3A ) . Such a preparation consists of about 90% of HCs , and it has been used previously to quantify GABA release by HCs [24] . Probenecid is a specific inhibitor of Panx1 channels that does not block Cx hemichannels [25] ( see also Figure S3A ) . Whole-cell voltage clamp experiments on these dissociated HCs show that 500 µM probenecid blocks a current in the physiological membrane potential range with similar properties as previously described for Panx1 channels [11] , [20] , [21] ( Figure 3B; black , control; red , probenecid; green , probenecid blocked current ) . On average probenecid reduced the whole-cell current statistically significant amounts at positive and negative potentials and in the physiological range ( n = 6; asterisk means p<0 . 05 ) . In three of the six cells , where stable recordings could be maintained , partial recovery was obtained . Similar results were obtained by application of another specific Panx1 blocker , 20 µM BB FCF ( Figure S3B ) [26] . The Panx1-mediated current was small , most likely because most of the Panx1 channels will have been lost during the dissociation process , as Panx1 is preferentially expressed at the tips of the HC dendrites . Panx1 channels have been shown to mediate ATP release in many cell types [27] , [28] . Can HCs release ATP upon depolarization ? A luciferin–luciferase ATP detection assay was used to measure changes in the ATP release from the dissociated HCs . Bioluminescence was measured using a luminometer . After obtaining a baseline value , HCs were depolarized with 50 µM AMPA and the ATP concentration in the medium increased by 11 . 5±2 . 5% . The subsequent addition of 100 µM probenecid decreased the ATP concentration to 6 . 8±2 . 8% below the baseline value ( n = 74; p<0 . 001 ) . These data show that upon depolarization HCs release ATP via Panx1 channels ( Figure 3C ) . Finally , we determined whether Panx1 channels are active under physiological conditions . Panx1 channels mediate a current with a reversal potential more positive than the dark resting membrane potential of HCs [28] , suggesting that these channels keep the HCs slightly depolarized and that their closure should cause HCs to hyperpolarize . We found that this was indeed the case . Inhibiting Panx1 channels with 500 µM probenecid hyperpolarized HCs on average −8 . 2±1 . 8 mV ( n = 9 ) . HCs are part of a closed feedback loop with cones . Hyperpolarization of HCs will lead to an increase in feedback , leading to more glutamate release by the cones , which limits the extent to which HCs will hyperpolarize . To isolate the effect of Panx1 on the HC membrane potential , we opened this closed loop by applying 28 mM HEPES , which is known to inhibit feedback substantially [4] , [10] , [16] . When feedback was inhibited in this way , HCs hyperpolarized significantly more when 500 µM probenecid was applied , compared to its application while feedback was intact ( −19 . 2±2 . 7 mV; n = 9; p = 0 . 0047 ) . These experiments confirm that HCs express Panx1 channels that are functional at physiological membrane potentials . It has been suggested that HCs take up protons upon hyperpolarization and that the resulting increase in pH modulates the ICa of cones [4] . Extensive evidence indicates that feedback is inhibited by HEPES [4] , [10] , [16] . Could ATP be involved in modulating the pH in the synaptic cleft ? ATP can be hydrolyzed to ADP and AMP by ecto-ATPases . These reactions generate protons and phosphate groups , which constitute a phosphate pH buffer with a pKa of 7 . 2 . Therefore , ATP released by HCs might lead to an acidification of the synaptic cleft relative to the extrasynaptic medium ( 7 . 6–7 . 8 ) and an increase in the pH buffer capacity of the synaptic cleft . This leads to an inhibition of ICa of the cones . Upon hyperpolarization of HCs , Panx1 channels will reduce their conductance and the release of ATP will decrease , resulting in a drop of the pH buffer capacity and an alkalization of the synaptic cleft . The inhibition of ICa will be relieved . This hypothesis depends on three critical aspects: ( 1 ) release of ATP , ( 2 ) hydrolysis of ATP , and ( 3 ) changes in pH and pH buffer capacity in the synaptic cleft . The dependence of the slow component of feedback on these three aspects was tested next . Panx1 channels were inhibited with 500 µM probenecid , and feedback responses in cones were measured . Figure 4A shows mean responses ( control , black; probenecid , red ) . Examples of the responses of individual cells are given in Figure S4A ( wash , green ) . In the presence of probenecid , the amplitude of feedback responses reduced by 26±8% ( n = 9; p = 0 . 0009 ) and the shape of the response became more square ( Figure 4A and I ) . The slow component of feedback often reduced to such an extent that a two exponential fit could not be performed reliably . After application of probenecid , a single exponential function fitted the response significantly better than a double exponential function in seven of the nine cells tested , whereas this was the case for only one cell in the control condition . Therefore , to quantify the reduction of the slow component , we determined the difference in amplitude measured at 160 ms and 460 ms after stimulus onset ( see Materials and Methods ) . Application of probenecid resulted in a 51±10% reduction of the slow component ( n = 9; p = 0 . 003 ) ( Figure 4A and J ) . Figures 4E and S4A show that these effects were reversible . To test whether the slow component of feedback was dependent on ATP , we applied 100 µM ATP , a concentration that does not block Panx1 channels [20] , and measured feedback responses . The amplitude of the feedback response reduced by 21±5% ( n = 6; p = 0 . 009 ) ( Figures 4B , I and S4B ) and became squarer in shape . The size of the slow component reduced by 67±15% ( n = 6; p = 0 . 036 ) ( Figure 4B and J ) and recovered after washing out the drug ( Figures 4F and S4B ) . These experiments indicate that ATP is able to modulate the slow component of feedback . ATP hydrolysis by ecto-ATPases should lead to acidification . First we tested whether ecto-nucleoside triphosphate diphosphohydrolase ( NTPDase1 ) was present in the cone synaptic cleft . Figure 2D shows NTDPase1-IR ( green ) in horseshoe-shaped structures in the OPL , at a similar localization as the Panx1-IR shown in Figure 2A . Double labeling of anti-NTPDase1 with an antibody against GluR2 , the glutamate receptor expressed at the HC dendrites , resulted in complete overlap ( Figure 2E ) . This shows that NTPDase1 is expressed at the tips of HC dendrites . Because NTPDase1 is a protein with two membrane spanning domains with its catalytic domain located extracellularly , these experiments show that enzymes that hydrolyze extracellular ATP are present within the synaptic complex of cones , allowing for the synthesis of protons and a phosphate buffer and thus acidification of the synaptic cleft . ATP hydrolysis eventually leads to the formation of adenosine . Adenosine deaminase ( ADA ) is the enzyme that extracellularly degrades adenosine to inosine . Figure 2F shows ADA-IR in similar horseshoe-shaped structures in the OPL , as was found for NTDPase1-IR . Double labeling with an antibody against the glutamate receptor GluR2 shows strong co-localization ( Figure 2G ) , suggesting that ADA is also expressed on the HC dendrites invaginating the cone synaptic terminal . These two enzymes allow for effective hydrolyzation of ATP in the synaptic cleft . Is the hydrolysis of ATP an essential step in the feedback pathway ? Blocking NTPDase1 with 50 µM ARL67156 , a specific blocker of NTPDases [29] , made the feedback response more square and reduced the amplitude of the slow component of feedback ( 49±20%; n = 7; p = 0 . 045 ) ( Figures 4C , J and S4C ) . This effect was reversible ( Figures 4G and S4C ) . Contrary to the effect seen when ATP was applied , the amplitude of the total feedback response did not decrease but may even have increased ( 113±10%; n = 7; p = 0 . 23 ) ( Figure 4I ) . This experiment shows that the hydrolysis of ATP is involved in the generation of the slow component of feedback . Finally , we tested whether the slow component of feedback depends on the pH gradient between the synaptic ( pH 7 . 2 ) and the extrasynaptic ( pH 7 . 6 ) compartments . We decreased the pH of the Ringer's solution by changing the ratio of CO2 and O2 , with which the Ringer's solution was gassed . This might cause two changes: the pH gradient is reduced and the pH in the synaptic cleft might reduce . Figures 4D , J and S4D show that the slow component was reduced by acidifying the extrasynaptic compartment ( 35±6%; n = 6; p = 0 . 010 ) . This effect was reversible ( Figures 4H and S4D ) . The feedback amplitude was reduced by 29±8% ( n = 6; p = 0 . 017 ) ( Figure 4D and I ) . The pharmacological manipulations we applied are expected to change the pH and the pH buffer capacity in the synaptic cleft . Barnes and Bui [15] showed that pH modulates the activation potential of ICa of cones . Therefore , it is expected that the half activation potential of ICa will have shifted in the various pharmacological conditions used in this study . According to the proposed hypothesis , ATP should acidify the synaptic cleft , whereas ARL67156 alkalizes it , predicting that ICa will shift to more positive potentials in ATP and to more negative potentials in the ARL67156 . Indeed this was found . Application of ATP shifted the activation of ICa 0 . 8±0 . 3 mV ( n = 8; p = 0 . 027 ) to more positive potentials , whereas ARL67156 shifted the activation of ICa −1 . 4±0 . 4 mV ( n = 8; p = 0 . 013 ) to more negative potentials ( Figure 4K ) . Consistent with these results is that acidifying the extracellular medium also leads to acidification of the synaptic cleft and thus to a shift of the activation potential of ICa to positive potentials ( 2 . 0±0 . 3 mV; n = 5; p = 0 . 002 ) . Interestingly , application of probenecid did not lead to a significant shift of ICa ( −0 . 7±0 . 7 mV; n = 9; p = 0 . 34 ) . It has been suggested the vacuolar H+-ATPase ( V-ATPase ) in the HC plasma membrane is involved in mediating negative feedback from HCS to cones [30] . However , no direct effects of blocking V-ATPase on the feedback-induced modulation of ICa in cones have been published . To see whether negative feedback indeed depends on the activity of V-ATPase , we applied the specific V-ATPase blocker bafilomycin A1 ( BFA1 ) . BFA1 did not significantly affect either the total feedback amplitude ( 113±11%; n = 8; p = 0 . 27 ) or the slow component ( 138±22%; n = 8; p = 0 . 14 ) of the feedback response , making it unlikely that V-ATPase is involved in feedback-induced modulation of the cone ICa within the physiological range . It is expected that negative feedback from HCs to cones will affect the kinetic properties of HCs . HC responses consist of a fast hyperpolarization followed by a slow rollback response ( Figure 5A , left trace , arrow ) . It has been suggested that the HC rollback response correlates , at least partly , with negative feedback from HCs to cones [13] , [31] , [32] . However , some caution is warranted , as the rollback response is also influenced by many other processes , such as the transient nature of the cone response [33] , [34] and voltage-gated currents [35] , [36] in HCs . Because the rollback response is relatively slow , the slow component of feedback might be influenced most by the slow component . First , we tested whether the rollback response depended on the pH gradient in the synaptic cleft . Figure 5D shows that changing the pH of the extrasynaptic medium from 7 . 6 to 7 . 2 hyperpolarized HCs ( −9 . 1±1 . 1 mV; n = 4 ) . In all four cells tested , the rollback response reduced but did not disappear completely and recovered after returning to pH 7 . 6 ( Figure 5A; black , control; red , pH 7 . 2; green , wash ) . This shows that the HC rollback response depends on the pH gradient in the synaptic cleft just as the slow component of feedback does ( Figures 4D , H , J and S4E ) . Next we tested if application of 500 µM probenecid would also reduce the rollback response . Application of probenecid hyperpolarized the HC membrane potential ( Figure 5D ) , and even though there was a high degree of variability in the rollback responses , it was reduced in 10 out of 18 HCs ( Figure 5B; black , control; red , probenecid; green , wash ) . However , the rollback response never completely disappeared . Note that this result resembles the effect of probenecid on the slow component of feedback , which only reduced by about 45% but never disappeared completely ( Figure 4J ) . This is to be expected as probenecid is only a partial blocker of Panx1 channels [37] . Furthermore , because probenecid does not affect Cx hemichannels , feedback via Cx hemichannels is still present . This might account for the remaining rollback response in HCs . To test this , we determined the effect of probenecid in conditions when a major part of feedback was blocked by 28 mM HEPES . HEPES most likely has two effects on the feedback system . It inhibits the proton-mediated feedback by buffering the pH in the synaptic cleft , and it leads to the closure of Cx hemichannels [16] . When 28 mM HEPES was present in the medium , applying probenecid hyperpolarized HCs significantly more ( Figure 5D ) and no sign of rollback could be seen ( Figure 5C; black , HEPES; red , HEPES+probenecid; green , HEPES ) . This result indicates that feedback is blocked ( almost ) completely in this condition . These experiments indicate that the rollback response depends , at least partly , on the slow feedback component . In many systems ATP released from Panx1 channels activates purinergic receptors [38] . Some evidence exists for expression of P2X [39] and P2Y [40] receptors on photoreceptors . Activation of P2X receptors by ATP should induce a nonspecific cation current [41] . Whole-cell IV relations were constructed for cones in control conditions and when 100 µM ATP ( n = 5 ) ( Figure 6A ) or 50 µM ARL67156 ( n = 5 ) ( Figure 6B ) was added to the bath solution . Neither ATP nor ARL67156 appeared to modulate a cation conductance , making it unlikely that ATP acted directly on a P2X receptor . The data presented in Figure 4 also show that purinergic receptors are unlikely to be involved in mediating negative feedback from HCs to cones . Either applying ATP or blocking NTPDase1 with ARL67156 will increase the ATP concentration . If ATP affected feedback by modulating photoreceptor purinergic receptors , ATP and ARL67156 would have had similar effects . Although both ATP and ARL67156 reduced the slow component of feedback , the shift of ICa and the size of the total feedback response moved in opposite directions ( Figure 4I , J , and K ) . This implies that ATP hydrolysis and not ATP itself exerts an effect on the slow component of feedback . In addition , A2 receptors have been suggested to modulate photoreceptor function [42]–[44] . We excluded a possible role for adenosine by measuring feedback in the presence of the specific A2 receptor blocker , ZM 241385 , at a similar concentration as used by Stella and co-workers ( Figure 6C ) [42]–[44] . In this condition , neither the feedback amplitude nor its kinetics were affected ( p>0 . 2; n = 4 ) , indicating that A2 receptors do not mediate feedback .
Figure 7 summarizes the proposed mechanism of negative feedback from HCs to cones . Glutamate receptors , Cx hemichannels , and Panx1 channels are expressed in the postsynaptic HC membrane . Voltage-gated Ca channels are expressed on the presynaptic cone membrane . In the dark , HCs and cones rest at about −35 mV . As ICa in cones is activated at that potential , cones release glutamate and HC glutamate receptors are activated , depolarizing HCs . Glutamate-gated channels , Cx hemichannels , and Panx1 channels are open in this condition and current flows into the HC . Because the extracellular space has a finite resistance , this current makes the potential deep in the synaptic cleft slightly negative . This is sensed by the voltage-gated Ca channels in the presynaptic membrane of the cones as a slight depolarization . The effect will be that the activation potential of ICa has shifted to more negative potentials relative to the cone's overall membrane potential [6] , [7] , [45] . At the same time , ATP is released via Panx1 channels . ATP is hydrolyzed to ADP , AMP , and eventually to adenosine by ecto-ATPases . This hydrolysis leads to an acidification of the synaptic cleft and the formation of a phosphate pH buffer ( pKa of phosphate buffer is 7 . 2 ) . Acidification of the synaptic cleft inhibits the cone ICa [15] and shifts its activation potential to more positive potentials . Interestingly , the ephaptic mechanism shifts the activation potential of ICa to more negative potentials , while the Panx1/ATP-mediated mechanism shifts it to more positive potentials . These two opposing mechanisms together set the activation potential of ICa in the dark ( Figure 7C , black line ) . Hyperpolarization of HCs due to surround stimulation will have two effects on the system . First , the current flowing through the Cx hemichannels , the Panx1 channels , and the glutamate-gated channels will increase . This increases the negativity of the synaptic cleft , shifting ICa to more negative potentials ( Figure 7C , red line ) . This process is as fast as the change in HC membrane potential and does not have a synaptic delay . In due time , the Panx1 channels will reduce their conductance and the release of ATP will diminish . Gradually the proton concentration and the pH buffer capacity in the synaptic cleft reduce , and the resulting alkalization disinhibits ICa . As a consequence , ICa increases and its activation potential shifts to even more negative potentials ( Figure 7C , blue line ) . This process is the slow feedback component and has a time constant of about 200 ms . The form of synaptic modulation we propose here is novel as it exerts its actions by regulating the local pH buffer capacity . Changing the pH buffer capacity consequentially changes the pH in the synaptic cleft . The feedback-induced pH change in the synaptic cleft is therefore indirect . This has an enormous advantage over direct modulation of the proton concentration in the synaptic cleft in an unbuffered system . To illustrate this , we calculated the number of protons involved in a feedback response . The maximal feedback-induced shift of ICa is about 9 mV [16] , and a pH change of 0 . 1 units shifts ICa by 1 mV [15] . Here we show that about 35% of the total feedback current in cones is pH-mediated . This implies that the slow component of feedback is responsible for about 3 mV of the shift of ICa , which translates to a pH change in the synaptic cleft of about 0 . 3 pH units . Vandenbranden [46] estimated that the volume of the extracellular space within the synaptic terminal of goldfish cones is 0 . 88 µm3 . Given these numbers , a 0 . 3 pH unit change in the pH in the synaptic cleft would involve the movement of about 19 protons from the total pool of around 38 free protons . In an unbuffered system , this would produce an unreliable noisy signal . However , the phosphate buffer is most likely present in the range of hundreds of µM , making the number of free protons a well-controlled statistical parameter . On the other hand , if the synaptic pH was strongly buffered by static pH buffers , proton-mediated feedback would be largely inefficient . Any pH change induced by HC hyperpolarization would be counteracted by the activity of the static pH buffers . This suggests that changing the pH buffer capacity is possibly the only way proton-mediated synaptic transmission can work . In this way , a pH-signaling mechanism can be highly reliable and noise free . In the dark , cones continuously release glutamate . Because glutamate and protons are co-released by the cones , this would lead to an acidification of the synaptic cleft in the dark and an alkalization in the light . Negative feedback leads to an increase in glutamate release and hence an increase in proton release as well—that is , an acidification . The opposite is found , suggesting that the pH near the Ca channels in the synaptic cleft depends more on HC activity than on cone activity . This is highly unexpected as glutamate is released continuously very close to the Ca channels of the cones . The reason why the pH in the synaptic cleft depends more on HC activity than on cone activity might be that the pH in the synaptic cleft is set by the pH buffer capacity , which is modulated by HCs , and not directly by proton release or uptake . Noise reduction is of great importance for an optimally performing visual system . The feedback pathway from HCs to cones modulates the output of the photoreceptors . Any noise added at this level of the visual system will considerably decrease the visual performance of the whole visual system . In later processing stages , noise can be lowered by convergence and by distributing the signals over various parallel channels . Such options are not available for the photoreceptors . Both feedback mechanisms we describe here have low noise properties; for instance , neither of them depends on vesicular release of neurotransmitters or activation of postsynaptic receptors . This unusual feedback synapse thus seems to be optimally adapted for its function in the outer retina . Wang et al . [14] studied feedback-induced pH changes in the synaptic cleft of zebrafish cones using a fluorescent method . They found that HC depolarization leads to acidification of the synaptic cleft . The time course ( τ∼200 ms ) of this pH change is remarkably similar to the time course of the second feedback component ( τs = 189±25 ms ) we find . Also , the size of the pH change they describe is very similar to the pH change we predict . In other words , the results of Wang et al . [14] are fully consistent with our experimental data . Wang et al . [14] did not find the fast component of feedback we have described here . However , they solely used fluorescent measurements to study pH changes in the synaptic cleft . As such , these types of experiments would be unable to detect the fast feedback component we describe , as it is mediated by an ephaptic mechanism and not by a pH-dependent mechanism . Wang et al . [14] suggested that the pH changes are mainly due to V-ATPase activity because they could inhibit the feedback-induced pH changes in the synaptic cleft with BFA1 . We tested the effect of BFA1 on light-induced feedback responses measured in the cones and found that neither the fast nor slow feedback component was affected by BFA1 . These results indicate that light-induced feedback does not depend on V-ATPase activity . This discrepancy may relate to the transgenic approach Wang et al . [14] used . They studied pH changes in the synaptic cleft in a transgenic zebrafish line that expressed Na channels ( FaNaChannels ) in HCs . To depolarize the HCs , FMRFamide , an agonist for the FaNaChannels , was applied . Because the reversal potential for sodium is very positive , it is highly likely that HCs in their experiments were depolarized to potentials far outside their physiological operating range . The HC membrane potentials might even have become positive during the depolarization , which is a very unphysiological condition . We show that under physiological conditions BFA1 does not significantly affect feedback , making it unlikely that V-ATPase has a role in negative feedback from HCs to cones . The question arises as to why two feedback mechanisms are present in the outer retina instead of one . To reduce spatial redundancies in the visual scene , the mean activity of all cones within the large receptive field of HCs is subtracted from the output of individual cones . If this process was not extremely fast , the surround of BC receptive fields would lag the center when responding to moving stimuli . Conversely , reducing temporal redundancies requires a slow mechanism so that lasting activity can be subtracted from the cone output . The feedback system we present here fulfills these requirements . The ephaptic feedback mechanism is extremely fast and will be prominently involved in reducing spatial redundancies . The Panx1/ATP-mediated mechanism is especially suitable for reducing temporal redundancies . As the slow component of feedback can only contribute when relatively static stimuli are used , it will not compromise the fast spatial redundancy reduction via the ephaptic feedback mechanism . In a first order approximation it is expected that inhibiting the slow component of feedback will always reduce the amplitude of feedback . However , this is not necessarily the case . For example , enhancing the amount of pH buffer experimentally by application of ATP will keep the pH in the synaptic cleft low and so ICa remains inhibited . Because the pH in the cleft no longer depends on HC hyperpolarization , the slow component of feedback is lost and the total feedback response becomes smaller . In contrast , when the formation of the pH buffer is prevented by ARL67156 , the pH in the synaptic cleft is again no longer dependent on HC hyperpolarization , but now the pH is high and ICa disinhibited . Because of this larger ICa , the total feedback responses will increase , even though the slow component is lost . Indeed this is what was found experimentally ( Figure 4B and C ) . One would also expect that probenecid and ARL67156 would affect the feedback amplitude similarly , as both drugs decrease the pH buffer concentration in the synaptic cleft . However , this was not the case as probenecid decreased the total feedback response amplitude , whereas ARL67156 did not ( Figure 4A , C , and J ) . The difference between probenecid and ARL67156 application is that probenecid also modulates the conductance of the Panx1 channels , whereas ARL67156 does not . This suggests that Panx1 channels also participate in the ephaptic component of negative feedback together with Cx hemichannels [7] , [11] , [12] and glutamate-gated channels [47] . Reducing the Panx1 conductance will affect both the fast and the slow feedback component , whereas application of ARL67156 only affects the slow component . Blocking the ephaptic part of feedback will lead to a shift of the activation potential of ICa to more positive potentials , whereas inhibiting the ATP release leads to alkalization and thus a shift to more negative potentials . The overall effect of inhibiting Panx1 channels will therefore depend on the relative strength of both effects . Our data show that application of probenecid indeed does not significantly shift ICa , indicating that both Panx1-mediated feedback signals affect ICa equally but in opposite directions ( Figure 4K ) . Why does probenecid have a greater effect on the HC membrane potential when the feedback is blocked with 28 mM HEPES ? The cone-HC system is a closed loop . Glutamate release by cones sets the membrane potential of HCs ( feedforward signal ) , whereas feedback from HC to cones determines the amount of glutamate released by the cones . In other words , the feedforward signal from cones to HCs is kept in its working range by the feedback signal from HCs to cones . They keep each other balanced . Therefore , it is expected that when feedback is blocked completely , ICa is no longer kept in its working range and cones stop releasing glutamate . Indeed this happens when feedback is blocked by carbenoxolone [6] . Carbenoxolone completely blocks feedback by closing both the Cx hemichannels and Panx1 channels . This causes a large shift of the activation potential of ICa to more positive potentials , which induces a strong reduction of the glutamate release by cones and hyperpolarization of HCs . Because cones no longer release glutamate , HC light responses are lost . The fact that a high concentration of HEPES does not strongly hyperpolarize HCs or completely block their light responses suggests that HEPES does not block feedback completely . This was confirmed by Fahrenfort et al . [16] , who showed that 10 mM HEPES or more reduces feedback to about 40% of its maximum . The consequence is that in the presence of 28 mM HEPES , the remaining part of feedback can keep the cone-HC system in its working range and HC light responses remain ( Figure 5C ) . When the ephaptic Panx1/ATP-mediated feedback component is inhibited as well by adding probenecid in the presence of HEPES , the cone-HC system can no longer remain in its working range . The cones stop releasing glutamate and HCs hyperpolarize strongly and lose their light responses . On the other hand , applying probenecid in the absence of HEPES has only a relatively minor effect on the HC membrane potential , as in this condition the Cx-hemichannel-mediated feedback pathway will not be affected and can keep the cone output in its working range and HC light responses remain present . Stella and co-workers [42]–[44] report that adenosine decreased ICa in cones via an A2 receptor interaction . In this article we showed that the slow component of feedback did not depend on this pathway . In fact , we found no effect at all on the feedback responses of cones when adenosine receptors were blocked . This disparity may have occurred as a result of the different experimental conditions used . We used relatively light-adapted goldfish or zebrafish retinas , whereas Stella and co-workers [42]–[44] worked with salamander retinas that were dark-adapted , a condition where adenosine signaling might be most prominent [48] . Furthermore , at present there is no direct evidence for the expression of adenosine receptors in the cone synaptic terminal , whereas expression is found in the inner retina [48]–[51] . It is possible that the effects seen by Stella and co-workers [42]–[44] are mediated by activation of A2 receptors in the inner retina affecting the outer retina via , for instance , interplexiform cells . Are the feedback mechanisms we describe here also present in other vertebrates , or are they specific for fish ? There is general agreement that in all vertebrates , ranging from salamander and fish to mice and primates , negative feedback from HCs modulates the ICa of cones [1]–[5] . In zebrafish , knocking out the hemichannel forming Cxs ( Cx55 . 5 ) leads to a severe reduction of feedback from HCs to cones [7] . Interestingly , the rollback response remained intact [7] . Similarly , the HC rollback response is unaffected in mice when the HC-specific Cx ( Cx57 ) is knocked out [52] . This led the authors to conclude that there was no Cx-hemichannel-mediated ephaptic feedback in mice . However , because the ephaptic feedback component is very fast and most likely does not contribute strongly to the rollback response in HCs , the conclusion that ephaptic feedback does not occur in mice might be premature . In the present study , we show that the rollback response in HCs , at least partly , depends on the slow Panx1/ATP-mediated component of feedback . Similar to zebrafish and goldfish , mice also express Panx1 channels at the HC dendrites [12] . It is therefore likely that in mice the slow component of feedback is also mediated by Panx1 and ATP . It is tempting to speculate that both mechanisms are present in all vertebrates but in different ratios and that this ratio reflects a species' visual capability and needs . In some animals , the ephaptic component might be the largest , whereas in others the Panx1/ATP component might dominate . For example , as the spatiotemporal correlation function of natural scenes is inseparable [53] , faster temporal signals received by the retina of species like mice with low visual acuity will be limited under normal conditions . In animals such as these , the slow Panx1/ATP component of feedback may dominate as their retina has less need to manage the faster temporal aspects of the scene . On the other hand , in animals strongly depending on vision , such as zebrafish and goldfish , the fast component might be dominating . Whether the ratios of the two feedback mechanisms indeed correlate with the visual performance of the various animals is an intriguing question that awaits further study . Could the Panx1/ATP mechanism presented here also function outside the retina ? In the central nervous system , Panx1 and NTPDase1 are both abundantly present and their localization is concentrated in synapses [54]–[56] . This suggests that the Panx1/ATP system described in this article might also occur in other brain regions . The hippocampus is one region where Panx1 expression levels are high , and recently it was suggested that Panx1 channels are involved in synaptic plasticity stabilization in that brain area , although the underlying mechanism has not been clarified [57] . As NMDA receptors are very sensitive to changes in pH [58] , the proposed Panx1/ATP system may also be acting as a modulator of synaptic strength in the hippocampus and other brain regions . Panx1 is also expressed in astrocytes and astrocytes are known to release ATP [27] . Processes of astrocytes and pre- and postsynaptic structures of neurons form a tripartite synapse . Astrocytes play an active role in such a complex; they modulate the signal flow between pre- and postsynaptic cells and in that way influence the neuronal network properties [59] . This modulation depends on the intracellular Ca2+ concentration in the astrocytes . Because Panx1 channels are gated by intracellular Ca2+ , and because any voltage-gated channel , such as the presynaptic voltage-gated Ca channels , is pH sensitive due to pH-induced changes in surface charge , astrocytes might modulate the synaptic efficiency by changing the pH buffering in the synaptic cleft utilizing the Panx1/ATP system described in this article . Furthermore , because both Panx1 and NTPDase1 are also coexpressed in other organs like the kidneys and heart [21] , [55] , [60] , similar extracellular pH modulation systems might also modulate cellular activity in nonneuronal tissues .
All animal experiments were carried out under the responsibility of the ethical committee of the Royal Netherlands Academy of Arts and Sciences acting in accordance with the European Communities Council Directive of November 24 , 1986 ( 86/609/EEC ) . Goldfish , Carassius auratus , or zebrafish , Danio rerio , were euthanized and the eyes enucleated . Wild-type and Cx55 . 5 mutant zebrafish ( C54X , hu1795 , ZFIN ID: ZDB-ALT-110920-1 ) , all in a TL background , were used . For the isolated retina preparation , control Ringer solution contained ( in mM ) 102 . 0 NaCl , 2 . 6 KCl , 1 . 0 MgCl2 , 1 . 0 CaCl2 , 28 . 0 NaHCO3 , 5 . 0 glucose , and 0 . 1 picrotoxin and was continuously gassed with 2 . 5% CO2 and 97 . 5% O2 to yield a pH of 7 . 6 . HEPES Ringer solution contained ( in mM ) 102 . 0 NaCl , 2 . 6 KCl , 1 . 0 MgCl2 , 1 . 0 CaCl2 , 28 . 0 HEPES , 5 . 0 glucose , and 0 . 1 picrotoxin , and the pH was set to 7 . 6 with NaOH . The pipette solution contained ( in mM ) 85 K-gluconate , 21 KCl , 1 MgCl2 , 0 . 1 CaCl2 , 1 EGTA , 10 HEPES , 10 ATP-K2 , 1 GTP-Na3 , 20 phosphocreatine-Na2 , 50 units ml−1 creatine phosphokinase , adjusted with NaOH to pH 7 . 3 , and resulting in a ECl of −50 mV when used in conjunction with the Ringer solution . All chemicals were supplied by Sigma-Aldrich ( Zwijndrecht , the Netherlands ) , except for Papain ( Worthington Biochemical Company , Lakewood , NJ ) and ARL67156 and ZM241385 ( Tocris Biosciences , Bristol , UK ) . For the electrophysiological experiments with dissociated HC , the following solutions were used . The control Ringer solution contained ( in mM ) 110 NaCl , 5 KCl , 10 CsCl , 2 . 5 CaCl2 , 2 MgCl2 , 10 HEPES , 10 Glucose , pH 7 . 8 . Intracellular recording solution contained ( in mM ) 10 NaCl , 120 CsCl , 5 CaCl2 ( free 100 µM ) , 5 EGTA , 10 HEPES , 2 ATP-Mg , pH 7 . 4 . Concentrations of the drugs used are indicated in the legends . HCs of goldfish were isolated using an optimized version of the procedure originally described by Dowling et al . [23] and optimized by Ayoub and Lam [24] . Retinas were dissected as described above . The isolated retinas were placed in a solution of L-15 containing 5 mg/ml papain ( Worthington , no . 3126 ) . They were incubated at room temperature for 35 min while being shaken at a low frequency . Subsequently , the retinas were washed in DMEM+Glutamax ( GIBCO , no . 61965 ) containing 10% fetal bovine serum ( GIBCO , no . 10270 ) to inactivate the papain . Then the retinas were washed in L-15 and finally placed in a tube containing 3 ml L-15 . The retinas were mechanically dissociated by trituration using a wide plastic Pasteur pipette first and a narrower fire polished glass pipette for later fractions . For each new fraction , the cells were allowed to settle for a minute before the lower heavier section was transferred to a new tube . The fractions containing an HC concentration of 85% or higher were used for luminescence measurements . ATP bioluminescence was measured using the ATP Bioluminescence Assay Kit CLS II purchased from Roche . Luciferase luminescence was measured with a Varioscan Flash ( Thermo Scientific ) using luminometry . After obtaining a baseline measure , 50 µM AMPA was added and subsequently 100 µM probenecid . A 20 µm white light spot ( 0 log ) was focused via a 60× water immersion objective on the cone outer segment and a 4 , 500 µm “full field” white spot ( −1 . 5 log ) projected through the microscope condenser . The light stimulator consisted of two homemade LED stimulators based on a three-wavelength high-intensity LED ( Atlas , Lamina Ceramics Inc . , Westhampton , NJ ) . The peak wavelengths of the LEDs were 624 , 525 , and 465 nm , respectively , with bandwidths smaller than 25 nm . An optical feedback loop ensured linearity . The output of the LEDs was coupled to the microscope via light guides . White light consisted of an equal quantal output of the three LEDs . 0 log intensity was 8 . 5×1015 quanta m−2 s−1 . The full-field light onset responses of the negative feedback measurements were fitted with a single exponential: ( 1 ) and if possible with a double exponential function: ( 2 ) To test which of the two models described the raw data best , an F test comparing the sum of squares of residuals of each fit was performed . Often the slow component of feedback present in control conditions was reduced by our pharmacological manipulation to such a level that the onset of the feedback current could no longer be fitted accurately by a double exponential function . In order to quantify the effect of the various compounds used on the slow component of feedback , the average amplitudes were determined for 40 ms stretches of the feedback current centered at 160 ms and 460 ms after response onset , and the difference was calculated . This difference was taken as the amplitude of the slow component of feedback . The amplitude of the slow component in the pharmacological condition ( B ) was divided by the amplitude of the slow component in the control condition ( A ) , yielding the reduction ratio . The activation curve of ICa was derived by leak subtracting the IV relation using the linear part of the IV relation between −80 and −60 mV [16] . The half activation potential was then determined by fitting a Boltzmann relation ( Eq . 3 ) through the leak subtracted IV relations: ( 3 ) where V is the membrane voltage , is the midpoint , and m is the slope factor . This was done for each cell in both control ( C ) and experimental ( E ) conditions and the shift in the half activation potential calculated as K ( E ) minus K ( C ) . Immunohistochemical procedures were similar to published methods [7] , [16] . The Panx1 antibody was raised against the zebrafish sequence and characterized by Prochnow et al . [11] . The primary antibody against NTPDase1 was raised in rabbit to the corresponding amino acid sequence 102–130 of human NTPDase1 ( GIYLTDCMERAREVIPRSQHQETPVYLGA ) . It was obtained from CHUQ ( www . ectonucleotidases-ab . com ) and characterized by Ricattie et al . [61] . The ADA ( AB176 ) and GluR2 antibodies were purchased from Chemicon International ( Temecula , CA ) . The ADA rabbit polyclonal antibody was raised against calf spleen ADA . The GluR2 ( MAB397 ) mouse monoclonal ( clone 6C4 ) antibody was raised against a recombinant fusion protein TrpE–GluR2 ( N-terminal portion , amino acids 175–430 of rat GluR2 ) . Secondary antibodies , goat–anti-mouse Alexa 488 , and goat–anti-rabbit Cy3 were purchased from the Jackson Immuno Research Lab ( West Grove , PA ) . For light microscopical ( LM ) purposes , 10-µm-thick sections were made and stored at −20°C . Sections were first preincubated in 2% Normal Goat Serum ( NGS ) for 30 min , then incubated with primary antibodies for 24–48 h , followed by 35 min of incubation with secondary antibodies at 37°C . The 0 . 25 µm optically sectioning was performed with Zeiss CLSM meta confocal microscope ( Zeiss , Germany ) . For electron microscopical ( EM ) purposes , 40-µm-thick sections were incubated with the primary antibody in PB for 48 h , then rinsed before being incubated with rabbit peroxidase antiperoxidase ( PAP ) for 2 h , rinsed , and then developed in a 2 , 2′-diaminobenzidine ( DAB ) solution containing 0 , 03% H2O2 for 4 min . Afterwards the gold substitute silver peroxidase method [62] was performed; sections were fixed in sodium cacodylate buffer ( pH 7 . 4 ) containing 1% Osmium tetra oxide and 1 . 5% potassium ferricyanide . Sections were then dehydrated and embedded in Epoxy resin , ultrathin sections made and examined with a FEI Tecnai 12 electron microscope . All data are presented as mean ± sem unless otherwise stated . Significance was tested using a two-tailed t test on paired or independent group means as appropriate . | At the first retinal synapse , specific cells—horizontal cells ( HCs ) —inhibit photoreceptors and help to organize the receptive fields of another retinal cell type , bipolar cells . This synaptic interaction is crucial for visual contrast enhancement . Here we show that horizontal cells feed back to photoreceptors via a very fast ephaptic mechanism and a relatively slow mechanism . The slow mechanism requires ATP release via Pannexin 1 ( Panx1 ) channels that are located on HC dendrites near the site where photoreceptors release the neurotransmitter glutamate to HCs and bipolar cells . The released ATP is hydrolyzed to produce AMP , phosphate groups , and protons; these phosphates and protons form a pH buffer , which acidifies the synaptic cleft . This slow acidification inhibits presynaptic calcium channels and consequently reduces the neurotransmitter release of photoreceptors . This demonstrates a new way in which ATP release can be involved in synaptic modulation . Surprisingly , the action of ATP is not purinergic but is mediated via changes in the pH buffer capacity in the synaptic cleft . Given the broad expression of Panx1 channels in the nervous system and the suggestion that Panx1 function underlies stabilization of synaptic plasticity and is needed for learning , we anticipate that this mechanism will be more widespread than just occurring at the first retinal synapse . | [
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"meth... | 2014 | Extracellular ATP Hydrolysis Inhibits Synaptic Transmission by Increasing pH Buffering in the Synaptic Cleft |
It is crucial to determine whether rapid eye movement ( REM ) sleep and slow-wave sleep ( SWS ) ( or non-REM sleep ) , identified in most mammals and birds , also exist in lizards , as they share a common ancestor with these groups . Recently , a study in the bearded dragon ( P . vitticeps ) reported states analogous to REM and SWS alternating in a surprisingly regular 80-s period , suggesting a common origin of the two sleep states across amniotes . We first confirmed these results in the bearded dragon with deep brain recordings and electro-oculogram ( EOG ) recordings . Then , to confirm a common origin and more finely characterize sleep in lizards , we developed a multiparametric approach in the tegu lizard , a species never recorded to date . We recorded EOG , electromyogram ( EMG ) , heart rate , and local field potentials ( LFPs ) and included data on arousal thresholds , sleep deprivation , and pharmacological treatments with fluoxetine , a serotonin reuptake blocker that suppresses REM sleep in mammals . As in the bearded dragon , we demonstrate the existence of two sleep states in tegu lizards . However , no clear periodicity is apparent . The first sleep state ( S1 sleep ) showed high-amplitude isolated sharp waves , and the second sleep state ( S2 sleep ) displayed 15-Hz oscillations , isolated ocular movements , and a decrease in heart rate variability and muscle tone compared to S1 . Fluoxetine treatment induced a significant decrease in S2 quantities and in the number of sharp waves in S1 . Because S2 sleep is characterized by the presence of ocular movements and is inhibited by a serotonin reuptake inhibitor , as is REM sleep in birds and mammals , it might be analogous to this state . However , S2 displays a type of oscillation never previously reported and does not display a desynchronized electroencephalogram ( EEG ) as is observed in the bearded dragons , mammals , and birds . This suggests that the phenotype of sleep states and possibly their role can differ even between closely related species . Finally , our results suggest a common origin of two sleep states in amniotes . Yet , they also highlight a diversity of sleep phenotypes across lizards , demonstrating that the evolution of sleep states is more complex than previously thought .
Based on the 1913 behavioral definition [1] , sleep is characterized by sustained immobility , a species-specific sleep posture and location , and a high arousal threshold . In addition , it displays a circadian distribution and is homeostatically regulated . Based on these criteria , it has been shown that sleep occurs in all animals , from the simplest organisms to the most complex ones [2–5] . Such ubiquity of sleep indicates that it constitutes a fundamental need for all living organisms . In the 50s , two distinct sleep states were described in humans and cats [6 , 7] . The first sleep state is slow-wave sleep ( SWS ) , also known as non-rapid eye movement ( REM ) sleep or quiet sleep . This state is characterized in mammals by the occurrence of cortical high-amplitude slow delta waves ( 0 . 5–4 Hz ) [8] , hippocampal sharp-wave ripple ( hSWP-R ) complexes [9 , 10] , and spindle oscillations [11 , 12] . During SWS , physiological processes are reduced , including heart rate , body temperature , eye movements , and muscle tone . In sharp contrast , the active sleep state named REM or paradoxical sleep [7]—commonly associated with dreaming in humans—is characterized by REM and cortical desynchronization like the awake state , but without muscle tone [6 , 7] . REM sleep and SWS are also characterized by a high arousal threshold . During REM sleep , in contrast to SWS , thermoregulation processes including shivering , piloerection , and sweating are abolished [13] , brain temperature increases , and the heart and breathing rates become irregular [14] . Finally , toe , tail , limb , and whisker movements occur phasically ( muscle twitches ) during REM sleep [15] . SWS and REM sleep have been unequivocally identified to date only in terrestrial mammals and birds [4] ( Fig 1A ) . Since these species are homeotherms , it has often been proposed that the two sleep states evolved together with homeothermia [16] . However , the poikilothermic nonavian reptiles , including lizards and snakes , turtles , and crocodiles share a common ancestor with mammals and birds . Squamates ( lizards and snakes ) are the group that shares the most ancestral features with the common ancestor of birds and nonavian reptiles ( Fig 1A ) . Therefore , to retrace the evolution of the two sleep states , studying species in this group is essential . Despite its importance in understanding the evolutionary origins of these sleep states , less than 40 studies , mostly from the 70s , have been devoted to the study of sleep in nonavian reptiles [4 , 17 , 18] . Of them , 16 were dedicated to squamates , with only seven articles including more than three recorded animals [19–25] . In addition , these studies were performed in only six species , all belonging to the infraorder Iguania . They revealed that this lizard family displays behavioral sleep during the night , including a specific posture and , when examined , a high arousal threshold and a homeostatic response to sleep deprivation . The sleep period was often described as one large bout during the night . During the day , periods of activity intersected long phases of quiet wake ( QW ) . Sleep was also reported to be associated with a decrease of the heart and respiratory rates . Regarding the presence of one or multiple sleep states in lizards , the existence of a REM-like sleep state was already suggested in 1966 [19] , mainly based on the presence of eye movements during sleep periods . However , these older studies failed to convince , and no consensus was obtained because of limitations in methodology , recording conditions , and the absence of replication [18] . However , in 2016 , Shein-Idelson and colleagues provided convincing evidence for the existence of two electrophysiological sleep states [22] in a species never previously recorded for this purpose , the bearded dragon ( Pogona vitticeps ) . The authors observed—specifically during the night , when the animal was lying on the floor of the cage with its eyes closed—a very regular alternation of periods characterized by the occurrence of “slow waves” and periods characterized by local field potential ( LFP ) desynchronization , similar to those observed during the awake state and associated with isolated eye movements . The authors concluded that both SWS and REM sleep exist in this species with a very rhythmic periodicity . However , such a periodicity , as regular as clockwork , is quite surprising and had never been reported before in either other nonavian reptiles or in mammals and birds . Moreover , muscle tone , motor automatism , heart rate , and arousal threshold evaluation were missing to unequivocally demonstrate that the state identified as REM sleep did not correspond to short periods of awakening also known to be characterized by desynchronized electroencephalogram ( EEG ) and eye movements . Therefore , we decided to replicate the experiments of Shein-Idelson and colleagues [22] and to compare these data with data for another species of lizard from a different family to test the generality of these findings . We replicated data on one bearded dragon ( P . vitticeps ) ( Fig 1B ) and developed a multiparametric approach to examine sleep in the Argentine tegu lizard , S . merianae ( Fig 1B ) . We chose this species as it belongs to the Lacertoidea family , for which sleep has never been recorded with the exception of three studies focusing on circadian rhythms [26–28] . Furthermore , this predatory species displays an active foraging life style , an omnivorous diet , and high cognitive abilities , with one of the highest encephalization quotients across squamates [29] . Consequently , it may have larger quantities of sleep and more specifically REM sleep than other lizards [30] . Six subadult Argentine tegus ( S . merianae ) were studied . We recorded LFPs by means of 35-μm–diameter tungsten electrodes implanted at different depths in four forebrain regions . We simultaneously recorded the nuchal electromyogram ( EMG ) , the electro-oculogram ( EOG ) , and the electrocardiogram ( ECG ) using a wireless system . All the animals were video monitored for 24 h a day with four near-infrared cameras . As brain LFP amplitudes and frequencies covary with temperature [31] , we performed all the experiments at a constant temperature . Therefore , baseline conditions , the arousal threshold , and the effect of 9 h of sleep deprivation by means of gentle handling were recorded at 28 °C ( body temperature ) . Finally , systemic injections of fluoxetine—a serotonin reuptake inhibitor known to suppress REM sleep in mammals [32 , 33]—were performed at two different concentrations .
The signals obtained from tungsten electrodes implanted in the dorsoventricular ridge ( DVR ) of a bearded dragon—a forebrain structure proposed to be homologous to the mammalian isocortex , the amygdala , and/or the claustral complex [34–37]—revealed different patterns across vigilance states ( Fig 1C ) . During the dark period , the bearded dragon displays a stereotypical posture , with the head lying on the floor in a specific location of the terrarium . This posture was never seen during the light period , as the animal always had its head up from the floor . During this period , two electrophysiological phases with distinct frequency content coexisted ( Fig 1C and 1D ) . The first electrophysiological sleep state , rich in δ ( 0 . 5–4 Hz ) frequencies , was characterized by a signal containing one to two slow negative high-amplitude sharp waves ( HShWs ) per second , lasting around 100–200 ms with an amplitude of 500 mV . The second electrophysiological sleep state contained frequencies in the β ( 11–30 Hz ) band , an oscillatory pattern that looked like the awake one ( Fig 1C ) . The δ/β power ratio and the autocorrelation of the signal revealed a very regular alternance between periods with δ and periods with β ( Fig 1E ) . The periodicity of these cycles was around 90 s . Finally , the extraction of the occurrences of the eye movements from the EOG showed that the second electrophysiological sleep state contained more ocular movements than the first one . Eye movements were mainly isolated and appeared mostly at the beginning of S2 ( Fig 1F ) . Our results obtained for one animal confirm the results reported by Shein-Idelson and colleagues . However , the same recordings and analysis performed on the Argentine tegu revealed different electrophysiological patterns ( Fig 1C ) . Indeed , even if two electrophysiological sleep states could be detected during the night resting phase ( Fig 1D ) , S1 did not contain slow negative HShWs as observed in the bearded dragon , and S2 differed from the awake activity , as an oscillation around 15 Hz dominates this phase . Finally , the autocorrelation analysis suggested no periodicity of the δ/β power ratio ( Fig 1G ) . As the same protocol was performed on these two lizard species , and as it revealed such different results , we decided to characterize sleep in greater detail in the Argentine tegu and developed a multiparameter approach as described below . During the light period , the tegus remained outside of their shelter and displayed short periods of active behavior , with head movements , locomotion , drinking , and feeding intersected by periods of immobility ( quiet wake , QW ) where animals were lying on the floor , eyes closed , head down with the four limbs spread apart . We observed that all animals entered their shelter 1 h ( 19 h 11 ± 27 min ) before the onset of darkness ( Fig 2A ) . Next , they curled up and kept their eyes closed and stayed in their shelter until 2 h after light onset ( 10 h 10 ± 23 min ) . During this phase , repositioning and movements of the head , limbs , toes , or whole body rarely occurred , and the eyes remained mostly closed . We also observed rare tongue flicking with the head slightly up and the eyes closed . To objectively demonstrate that the animals were sleeping , we then measured for each hour the percentage of stimulations that induces an arousal and the associated number of eye movements and the heart rate . Between 6 PM and 10 AM , the percentage of time spent in the shelter was significantly higher than between 10 AM and 6 PM , while the number of stimuli that induced an awakening was significantly lower ( p < 0 . 01 ) . In addition , the number of eye movements and the heart rate tended to decrease during the night ( p = 0 . 0556 ) ( Fig 2A , 2C and 2D ) . In line with the behavioral definition of sleep , these results strongly suggest that the animals are awake between 10 AM and 6 PM and are sleeping between 6 PM and 10 AM . We then developed a custom script based on the number of eye movements ( Fig 2F ) and the muscle activity ( S1 Fig ) to automatically score sleep behavior ( SB ) , QW , and active wake ( AW ) ( Fig 2E ) . We compared the periods of time spent in the shelter with SB periods scored with our algorithm and obtained 87% of correct assignments , a sensitivity of 0 . 91 , and a specificity of 0 . 87 ( S1 Table ) . Using such automatic scoring , we measured the percentage of time spent in each state over 24 h: 6 . 4 ± 1% ( AW ) , 29 ± 2% ( QW ) , and 64 . 6 ± 2% ( SB ) , with a mean bout duration of 0 . 5 ± 0 . 1 min ( AW ) , 2 . 6 ± 0 . 2 min ( QW ) , and 18 . 3 ± 1 . 6 min ( SB ) . Baseline recordings of LFPs were made during 24 h at 28°C in the DVR , the rostral medial cortex ( rMC ) and caudal medial cortex ( cMC ) —homologous to the mammalian hippocampus [38]—and the nucleus sphericus ( NS ) , a vomeronasal region [39] caudal to the DVR ( Fig 3D and 3C ) . A 3D reconstruction of the coordinates of the brain structures and of the skull was made for each animal using in vivo MRI and computed tomography ( CT ) scans ( Fig 3A ) in order to accurately implant the targeted structures ( Fig 3C and 3D ) . Bundles of 35-μm tungsten electrodes ( Fig 3B ) were implanted in these structures . The electrode positions were verified using a postimplantation CT scan merged with the preimplantation MRI and CT scans and postmortem histology ( Fig 3C ) . The bundles consisted of four to eight electrodes covering 1 , 500 μm dorsoventrally ( S2 Fig ) . In addition to the LFPs , we also recorded the EMG of the deep nuchal muscles , the EOG of both eyes , and the heart rate ( Fig 3E ) . During AW , a significantly higher muscle tone ( p < 0 . 001 ) , a higher number of eye movements ( p < 0 . 001 ) , and a higher heart rate ( p < 0 . 001 ) were recorded compared to QW and SB ( S1 Video ) . In addition , the LFP spectral power during AW was dominated by low frequencies ( around 5 Hz ) ( Fig 3E and 3F ) . When comparing QW and SB , no significant difference was seen in muscle tone and heart rate variability . However , the heart rate significantly decreased during SB compared to QW ( 29 . 4 ± 2 . 6 versus 40 . 32 ± 1 . 2 bpm , p < 0 . 001 ) . The LFPs in all regions showed a high diversity of patterns during all states and no obvious modifications of the mean power spectrum ( Fig 3E and 3F; S1 and S2 Videos ) except a small peak around 15 Hz during SB compared to QW in the DVR and rMC electrodes ( Fig 3F ) . A large peak around 20 Hz was also clearly visible during all states , primarily in the NS ( Fig 3F ) . In agreement with the power spectrum analysis , we observed on the raw signal ( Fig 4A ) as well as on the time/frequency representation ( Fig 4B , S2 Video ) the phasic occurrence during SB of oscillations at a frequency of 15 Hz . We first selected for each animal the electrode showing the highest power of this 15-Hz frequency during SB using an unsupervised method ( S3 and S4 Figs ) . We then performed a hierarchical clustering of the SB signals based on the correlations between each 3-s–window power spectrum for each animal . This revealed the existence of two clusters of sleep ( Fig 4C ) . These two clusters define two electrophysiologically distinct sleep periods: S1 periods not showing any predominant oscillation and S2 periods characterized by the presence of an oscillation around 15 Hz ( Fig 4D ) . Based on the mean power spectra of S1 and S2 computed for each animal , we extracted a power ratio ( S2 detection ratio; S2R ) to automatically detect the periods with 15-Hz oscillations ( S2R = [10–22 Hz]/[ ( 4–10 Hz ) + ( 22–28 Hz ) ] ) ( Fig 4E ) . Periods displaying 15-Hz oscillations mostly occurred during sleep ( 83 . 4 ± 2% ) , although some were observed during QW ( 16 . 4 ± 2% ) . They were nearly absent during AW ( 0 . 09 ± 0 . 05% ) ( Fig 4F ) . The oscillations had a peak frequency of 15 . 3 ± 0 . 03 Hz and lasted on average 4 . 3 ± 0 . 1 s ( but some episodes lasted 1 to 32 ± 2 . 3 s ) . They occurred 4 . 6 ± 0 . 1 times per min ( 2 , 229 . 6 ± 260 bouts over 24 h ) without a regular periodicity , with an average individual variability of 3 . 4 oscillations per min ranging between 0 . 02 and 16 . SB periods with these oscillations ( S2 ) constituted 17 . 2 ± 2 . 3% of the total sleep time . No change in the power and the frequency of the oscillations was detected across the night . S2 periods occur preferentially at the beginning ( 18 . 9 ± 0 . 9% ) and at the end ( 18 . 4 ± 2 . 4% ) rather than in the middle ( 13 ± 1 . 7% , p = 0 . 0139 and p = 0 . 0287 , respectively ) of the night ( Fig 4G and 4H ) . Further , S2 was associated with a lower heart rate ( p = 0 . 0079 , mean value: S1 , 28 . 39 bpm; S2 , 29 . 15 bpm; S1–S2 , −0 . 24 bpm ) , lower heart rate variability ( p = 0 . 0079 , mean value: S1 , 2 . 2 bpm; S2 , 1 . 79 bpm; S1–S2 , −0 . 41 bpm ) , a small but significant decrease in muscle tone ( p = 0 . 0079 , mean value: S1 , 3 . 92 μV; S2 , 3 . 77 μV; S1–S2 , −0 . 15 μV ) , and an increase of the number of eye movements compared to S1 sleep periods ( p = 0 . 0079 , mean value: S1 , 9 . 31 min−1; S2 , 13 . 13 min−1; S1–S2 , 3 . 82 min−1 ) ( Fig 4I ) . Finally , the mean power spectra analysis revealed that the 15-Hz oscillations occurring during S2 were present in all regions except the NS ( Fig 4J ) . HShWs were observed on LFPs from all structures ( Fig 5A ) . They were extracted automatically from LFP signals using a spike-sorter algorithm [40] ( Fig 5B and 5C ) . The HShWs displayed a mean amplitude of 635 ± 124 μV and lasted less than 50 ms ( Fig 5C ) . They were significantly more numerous in the middle of the night between 0 AM and 3 AM ( 1 . 1 ± 0 . 2 ) than during the first ( 0 . 5 ± 0 . 1 ) and last 3 h of sleep ( 0 . 54 ± 0 . 1 ) ( p < 0 . 001 ) ( Fig 5B and 5D ) . They appeared mostly during S1 periods ( 72 . 8% ) , although some were visible during S2 ( 14 . 4% ) and QW ( 5% ) ( Fig 5E and 5F ) . To determine whether sleep homeostasis is present in lizards , 9 h gentle-handling sleep deprivation was performed between 7 PM and 4 AM ( Fig 6A ) . During this sleep deprivation , the SB quantities ( S1 + S2 ) were reduced significantly by 84 . 7 ± 4 . 8% compared to baseline conditions ( Fig 6A and 6C ) ( p = 0 . 0006 for S1 and p = 0 . 0012 for S2 ) . During sleep deprivation , the number of HShWs significantly decreased ( Fig 6D and 6E ) ( p = 0 . 0216 ) . After sleep deprivation , a significant increase of SB ( Fig 6B; increase of SB: 8 . 96 ± 2 . 18% ) occurred during the following 24 h compared to the baseline ( p = 0 . 0302 ) . The recovery of sleep was only significant for S1 ( Fig 6B and 6C ) ( p = 0 . 0245 ) . The density of HShWs during SB was significantly increased during the 24 h following the sleep deprivation compared to the baseline condition ( Fig 6F and 6G ) . We then tested the effect of fluoxetine on the occurrence of the 15-Hz–oscillation periods defined as S2 and HShWs to determine whether they showed similarities with mammalian REM sleep and hippocampal sharp waves , respectively . Indeed , it has been shown that both REM sleep in mammals and birds [32 , 33 , 41] and in vitro hippocampal sharp waves are inhibited by serotonin reuptake inhibitors [42] . We injected fluoxetine [43 , 44] at two concentrations ( 10 mg/kg and 60 mg/kg ) and a saline solution as a control ( Fig 7 ) . Control injection of saline did not induce any effect on the total percentage of SB , the number of SB episodes , or their duration compared to baseline ( p > 0 . 05 ) . The lower concentration of fluoxetine did not affect the total amount of AW , QW , and S1 ( Fig 7A and 7B ) ( p > 0 . 05 ) . Nevertheless , SB episodes ( S1 + S2 ) were interrupted by short awakenings compared to baseline , inducing a significant decrease of their mean duration ( 10 mg/kg and 60 mg/kg , p = 0 . 0366 and p = 0 . 0255 , respectively ) and a significant increase in the number of SB episodes ( 10 mg/kg and 60 mg/kg , p = 0 . 0106 and p = 0 . 0325 , respectively ) . Regarding the specific effect on the 15-Hz oscillations , their quantities were not significantly decreased with 10 mg/kg of fluoxetine in contrast to 60 mg/kg , strongly suggesting that the state of S2 is dramatically reduced ( Fig 7A and 7B ) ( p = 0 . 0096 ) . Regarding the effect on the HShW density ( Fig 7C , 7D , 7E and 7F ) , both doses tended to reduce it during the 24 h after injection , but it was only significant for 60 mg/kg .
Our results demonstrate the existence of two different sleep states in the tegu and the bearded dragon , sharing features with mammalian and bird REM sleep and SWS . The existence of an REM-like sleep state in a lizard suggests that homeothermic animals are not the only ones to show two sleep states . However , even if some nonavian reptiles display two sleep states , the ancestral or convergent origin of these states remains unclear . In fact , too few studies have been conducted in nonavian reptiles to fully conclude that a REM-like sleep state did not appear convergently . Moreover , around 75% of the studies on turtles and almost all of the studies on crocodiles ( both groups being closely related to birds ) did not report two sleep states . Whether the two sleep states originated at the base of the amniote tree or before also remains to be determined by means of new studies of sleep in other nonavian reptiles as well as amphibians and fish . Deciphering the origin of the two sleep states is complicated , and the further we move away from mammals and the classical definition of sleep , the more difficult it will be to identify homologies . More than providing additional evidence for a reptilian REM-like sleep state , our results reveal the true diversity in sleep phenotypes , a diversity that should be explored through integrated and complementary approaches without an underlying biased definition based on mammalian studies . Indeed , even in mammals and birds , experiments on basal species show that those states could be mixed [62 , 63] . Maybe the question should not be whether nonavian reptiles show REM sleep and SWS , but how did these states appear and evolve along the different branches of the amniote tree .
All experiments were conducted according to the 3R principles in animal experimentation and in accordance with the European Community Council Directive for the use of research animals ( 2010/63/EEC; https://eur-lex . europa . eu/legal-content/EN/TXT/ ? uri=CELEX:32010L0063 ) . Protocols and procedures used were approved by the local ethics committee for animal experimentation of the university Lyon 1 ( No . BH2012-43 ) . We report data on one bearded dragon ( P . vitticeps ) and six Argentine tegus ( S . merianae ) , five males and one female ( #2 ) , with an age of 2 y ( ± 0 . 5 ) , 3 ± 0 . 7 kg . All tegus were bought from official breeders and were maintained individually in a 4-m-square area ( 2 m × 2 m ) . The bearded dragon was maintained and recorded in a smaller terrarium ( 90 cm length , 50 cm width , 40 cm height ) . The tegus were fed dead mice two to three times a week , and the bearded dragon was fed crickets and vegetables twice weekly . Water was provided ad libitum . Prior to experiments , animals were maintained under a 12 h:12 h light/dark cycle in a room maintained at 25 °C with a hot spot at 45 °C available between 11 AM and 6 PM . Six infrared ( 850 nm ) panels ( Viewpoint SA ) were always on . A shelter transparent to infrared wavelengths was used to monitor the animals during the dark phase . All the experiments were conducted in a room at 25 °C after at least 2 days of habituation . A custom floor heating regulated at 30 °C was used for the tegu . The nuchal temperature was measured for one animal of each species thanks to a micro thermistor implanted in the nuchal muscles . The nuchal temperature measured in one animal was around 28 °C for the tegu and 25 °C for the bearded dragon . Prior to the surgery , two 100-μm diameter holes were drilled under anesthesia ( cf . surgery part ) in the anterior and posterior part of the parietal bone . These holes served as references during electrode implantation . MRI imaging was carried out on a 3T GEHC MR750 System using an 8-channel wrist coil . The head of the lizard was placed at the center of the coil . After a three-plane localizer , two 3D high-spatial–resolution magnetic resonance imaging ( HR-MRI ) acquisition sequences were performed in the coronal plane . For both HR-MRI acquisitions , similar parameters were used: 59 . 2-mm slab thickness with 100 × 80 mm2 field of view ( FOV ) , 148 × 448 × 384 acquisition matrix size , and a 592 × 1 , 024 × 768 reconstruction matrix leading to a slice thickness of 100 μm with an in-plane pixel of 97 × 97 μm2 . First , a T1-weighted FSGGR sequence with 30 ° flip angle , 29 . 4 ms TR , 10 . 1 ms TE , and ±7 . 8k Hz receiver bandwidth with 22’15” scan time was performed . Second , a FIESTA-C sequence with 70 ° flip angle , 10 . 8 ms TR , 3 . 6 ms TE , and ±41 . 7 kHz receiver bandwidth with 12’45” scan time was performed . A few days later , a CT scan was performed to image the skull . The experiments were done on an NVEON system ( Siemens ) , with a tension of 80 kV , a current of 500 μA , and an exposure time of 900 ms with 720 steps . The reconstruction of the final volume permits us to obtain a voxel size of 55 . 62 μm3 in the three dimensions . The two modalities ( MRI and CT scan ) were realigned by choosing at least 10 common landmarks and using a principal component analysis method for realignment ( Avizo v7 . 0 . 1 ) . Next , landmarks were put on the MRI slices at the targeted electrode positions . A custom script ( Matlab r2016b; The MathWorks , Natick , MA , USA ) was used to transform the targeted landmarks into the reference frame defined by the holes drilled on the skull . The coordinates obtained were those used for the surgery . This procedure was used for all animals of both species . One week after the surgery , a second CT scan was performed in order to check the electrode positions by realigning the last CT scan to the two presurgical images . Under surgical anesthesia ( cf . surgery ) and after an electrocoagulation lesioning ( 2 s , 0 . 5 mA ) , animals were perfused transcardially [64] with a 400-ml Ringer-Lactate solution ( Braun Medical , France ) followed by a 2 , 000-ml 4% paraformaldehyde fixative solution , with a perfusion pump ( Gilson , France ) set at a 55 ml/min rate . Brains were removed and postfixed for 2 d at 4 °C in the same solution . Brains were included in paraffin ( LEICA ASP300 , Germany ) and mounted ( Myr EC 350–2 , Spain ) , and 7-μm slices were cut with a microtome ( Leica RM2245 , Germany ) for histochemical processing . One slice out of every seven was kept . The Nissl staining was done for the bearded dragon and tegus #2 , #3 , #4 , #5 , and #6 . The paraffin was removed from each slice with two 4-min baths of methylcylohexane , then two 4-min baths of 100% alcohol , followed by a 4-min bath of water . The Nissl stain was performed by putting the slices successively into the following baths: 2 min water , 4 min Cresyl Violet acetate ( 1 g/L ) ( Sigma Aldrich , St . Louis , MO , USA ) , 1 min alcohol 75% , 30 s alcohol 95% , 15 min alcohol 15% , 5 s alcohol 100% , 5 s alcohol 100% , 2 min OTTIX ( MM France , France ) . Then slices were digitalized ( Zeiss Axioscan Z1 , Germany ) with a 5X Fluar ( ON 0 . 25 ) lens . The animals were anesthetized with a mixture of ketamine ( 66 to 100 mg/kg ) and medetomidine ( 100 to 200 μg/kg ) at 19 °C injected intramuscularly and equally distributed in the four limbs [65] . After every 6 h , reinjections of half the previous dose were performed . Reflexes and respiratory rate were checked throughout the surgery . During surgery , two stainless steel electrodes were inserted bilaterally in the intercostal muscles for measuring heart rate , and two others were also implanted in the neck muscles to assess muscle tone . For the tegus and the bearded dragon , two other electrodes , gold plated at the tip , were positioned behind each eye , under the eyelid , to record eye movements . The tegus were also implanted with three to four bundles of six 35-μm diameter tungsten electrodes in different brain regions ( DVR , NS , rMC , and/or cMC ) . Only the DVR was implanted with this kind of bundle during the bearded dragon surgery . One screw was fixed on the skull between the two eyes for signal referencing for the tegu . The reference was inserted on the most caudal part of the parietal bone for the bearded dragon . To do so , lizards were placed in an adapted stereotactic frame . All wires were then connected to a head connector ( EIB-36-PTB Neuralynx ) , which was secured over the skull using acrylic Superbond ( Sun Medical Co . ) . Next , dental Paladur cement ( Heraeus Kuzler ) was applied around the head connector to protect all the wires and the connector . The behavior of the animal was monitored with four cameras ( Dragonfly2 DR2-HIBW , PointGrey ) equipped with a band-pass filter in the near-infrared wavelength . One camera was recording the full area , and the three others were dedicated to the animal shelter . The videos were recorded 24 h a day ( VPCore2 , Viewpoint ) , and the actimetry , which is the number of pixels changing more than 14 gray levels between two successive images , was evaluated online for each camera . The arousal threshold was evaluated for the Argentine tegus . A microrotor was fixed over the head of the animal for at least 4 d . The microrotor was programmed with a custom device to rotate at the maximum power for 5 s every hour to avoid any habituation . When the rotor was activated , an LED light was on . Using the four videos , any signs of awakening ( like an eye opening or a leg or head movement ) after a stimulation was recorded , as well as the latency thereof . The percentage of awakening after stimulation was evaluated for each hour for each animal . The mean percentage was then calculated for five animals ( Fig 2A ) . For the tegus , the electrophysiological signals from at least 22 tungsten electrodes into the brain—two ECG , two EMG , two EOG , and in some animals , a screw EEG—were recorded wirelessly ( TBSI W32 ) . A custom battery ( 3 , 000 mAh ) for recording at least 4 d without changing the battery was used and fixed over the back of the animal with tape . The amplification of the system was 1 , 000× . The digitalization was performed using a DAQ card ( National Instruments USB 6363 ) with a custom script ( Matlab r2016b ) . The data were sampled first at 20 kHz , low-pass filtered at 500 Hz , and subsampled at 2 kHz online . The videos were synchronized with an output TTL to trig the start and the stop of each video . For the bearded dragon , the DVR LFP was recorded with eight tungsten electrodes at different depth ( −4 to −2 mm below the skull , at 1 . 28 mm caudal to the anterior part of the pineal hole , and 1 . 94 mm lateral ) . Two EOGs were also recorded . The signals were recorded thanks to a custom wireless recording device at 128 Hz and to a custom Matlab script . The sleep deprivation was performed on the Argentine tegu by gentle handling without changing the light cycle from 7 PM to 4 AM . The shelter was removed from the area , and when the animal displayed a sign of sleep ( mostly closing the eyes ) , the experimenter woke up the animal by pulling a rope attached to the animal’s tail . After deprivation , the animal was left for at least 24 h without any human intervention . The sleep deprivation was performed on four animals , and the recordings started during the baseline and ended at least 24 h after the recovery . Twelve ml of fluoxetine ( 10 and 60 mg/kg; Interchim , France ) or saline ( vehicle ) solutions were randomly injected intraperitoneally at 4 PM in the tegus . Animals were recorded for at least 48 h after injections . Each injection was spaced at least 2 d apart for NaCl and 3 d after the fluoxetine injections . All the electrophysiological signals of the tegus were filtered with a zero phase-shift low-pass filter ( cutoff frequency 100 Hz , order 2 ) and subsampled at 250 Hz before any other treatments . Next , the electrophysiological signals , the actimetry , and the video were imported into a custom software program ( SlipAnalysis , developed under Matlab r2016b ) . An empty hypnogram was then created . The hypnogram was then manually filled per 5 s from the video with two states: animal inside the shelter or animal outside the shelter . All the analyses performed were also done with custom scripts ( Matlab r2016b ) . For the Argentine tegus , differential EOG calculated from the subtraction between the two EOGs was filtered with a low-pass filter ( Fc 10 Hz , order 10 ) . Then , the maximal value of the redressed signal was evaluated every second . Eye movement occurrence and duration were extracted by taking any part of the signal higher than 30 μV . Next , every epoch of the hypnogram during which the interval between eye movements was higher than 30 s was scored as SB . The other epochs were considered as QW . The episodes of SB spaced by less than 2 min were merged , and those lasting less than 2 min were removed . A differential EMG calculated from the subtraction between two EMGs was filtered with a high-pass filter ( Fc 10 Hz , order 10 ) and the absolute value of the Hilbert transform was calculated . An average filter with a 0 . 5-s window was applied , and the mean value was evaluated for every 1 s bout . AW was scored when the processed EMG value was above 20 μV . Every episode lasting less than 5 s was ignored , and episodes spaced by less than 5 s were merged ( Fig 2D and S1 Fig ) . For the baseline experiments , the episodes scored as SB in the automated hypnograms were compared with the “shelter scoring” ( S1 Table ) . A mean correct rate of 0 . 873 was obtained on the six animals , with a mean sensitivity of 0 . 911 and a mean specificity of 0 . 874 . At least 22 electrodes were implanted in three to four regions in each tegu . In order to remove electrodes that were likely in the cerebral spinal fluid ( CSF ) , we computed the mean power spectrum density ( MPSD ) into the 0 . 5–45 Hz band . For all animals , based on the imaging ( MRI and postsurgery CT scan ) , we labeled the electrodes that were in the CSF and those in the brain . A threshold was obtained by computing the mean plus one standard deviation from all MPSD of the CSF electrodes . Every electrode with MPSD below the threshold was removed from the analyses and considered as being in the CSF ( S2 Fig ) . In order to choose the best electrode to extract the S2 states , we computed the MPSD during the episodes scored as SB . An interpolated spectrum was computed by removing the 10–20 Hz band and keeping the value in the 5–10 Hz and 20–25 Hz bands ( S3A–S3F Fig ) . A spline interpolation was used to evaluate this interpolated spectrum . By this means , one electrode was chosen per animal by taking the electrode with the maximal ratio between the interpolated and the real spectrum into the 10–20 Hz band . Animal two was removed from the S2 and HShW analysis because none of its electrodes had a ratio higher than 0 . 5% . As only the DVR was recorded , we choose the electrode with the highest amplitude for the bearded dragon . We used the methodology of Shein-Idelson and colleagues [22] . From the baseline experiments , between 9 PM and 2 AM , the signal of the chosen electrode was whitened with an autoregressive algorithm . A multitaper power spectrum between 0 . 5 and 30 Hz was computed for each 3-s epoch scored as SB ( windows 3 s , bandwidth 1 Hz , 5 tapers [66] ) . Each power spectrum was normalized by the mean power spectrum . A correlation matrix of these power spectra was calculated . Then , a hierarchical clustering with two clusters was realized based on a Euclidian distance of the correlation and using a Ward linkage ( Figs 1D and 4C ) . A mean normalized power spectrum per animal was then calculated for each cluster ( Figs 1D and 4D ) . For Fig 1 , we used the ratio used by Shein-Idelson and colleagues ( δ/β , [0 . 5–4 Hz]/[11–30 Hz] ) . For our detailed analysis on tegus , we detected the peak of each power spectrum of the state of maximum power in the 10–20 Hz band and the crossing frequency between the two normalized power spectra in order to extract the band power ratio that maximizes the cluster detection . Based on the means of these values , we defined S2R , which is the mean power of the 10–22 Hz band divided by the sum of the 4–10 Hz and the 22–28 Hz bands ( S2R = [10–22 Hz]/[ ( 4–10 Hz ) + ( 22–28 Hz ) ] ) . This ratio was calculated for the 24-h baseline of each animal on the chosen whitened electrode . A threshold was defined as the mean plus one standard deviation ( Fig 3E ) . Every part of the signal above that threshold was considered as S2 . If the S2 episodes were separated by less than 2 s , they were merged , and the episodes lasting less than 2 s were removed . The autocorrelation of Figs 1E , 1G and 4C was computed as described in Shein-Idelson and colleagues . The heart rate was extracted from the ECG electrode previously filtered with a high-pass filter ( Fc 10 Hz , order 10 ) . A peak detection was performed ( threshold 100 μV , min interval between peak 0 . 7 s ) . The instantaneous heart rate was then computed by measuring the interval between peaks . The muscle tone was extracted from differential EMGs filtered with a high-pass filter ( Fc 10 Hz , order 10 ) . The muscle tone is the absolute value of the Hilbert transform of the signal was filtered with a mean filter ( windows 0 . 5 s ) . The eye movement density was calculated from the EOG channels . The signal was filtered with a low-pass filter ( Fc 10 Hz , order 10 ) . Each part of the signal above 30 μV was considered as an eye movement . The density of eye movements corresponds to the number of eye movements occurring per min per state . Fig 1F , representing the phase histogram of the eye movements of the bearded dragon , was obtained by detecting the δ and β periods . The δ/β ratio was evaluated . Each δ period was extracted when the ratio was higher than the average and β periods when the ratio was lower than the average . Each cycle of δ–β periods was normalized between 0 and 2 π radians . The distribution of the occurrence of the ocular movements was evaluated relatively to this cycle . For the tegus , the HShW extraction was performed on all channels that were not considered as being in the CSF . The HShW detection algorithm was adapted from the spike-detection algorithm described by Quiroga and colleagues [40] . The HShWs were detected without any filter applied to the data . The threshold used was 10 times the signal-to-noise ratio , and 50 ms before and after the peak of the HShW was used for the waveform averaging . The channels kept for the analysis ( baseline , sleep deprivation , and pharmacology ) were the channels with the cleanest mean waveforms . The HShW density was evaluated by dividing the number of HShWs during a state by the duration of that state . All the statistics were performed using Matlab . Wilcoxon signed-rank tests were used for single comparisons between mean parameters per state ( Figs 2B , 2C , 2D , 4I , 6A , 6B , 6E , 6F and 6G ) . For multiple conditions with balanced designs , an analysis of variance with two factors ( ANOVA2 ) was used followed by post hoc analysis using Fisher’s least significant difference procedure ( Figs 4F , 4H , 5D , 5E , 5F , 7A , 7B , 7D and 7F ) . Each three-hour period data presented in Fig 4H were calculated , for each animal , by averaging 3 consecutive values from the sequential data of Fig 4G . For unbalanced designs , Kruskal-Wallis tests were performed and followed by post hoc analysis using Fisher’s least significant difference procedure . For the ANOVA , the normality of the data was tested with a Lilliefors test . When data were not normal , a Gaussian normalization centered on 0 with a variability of 0 . 2 was applied before any statistical test . The homoscedasticity was verified when needed using a Bartlett’s test . A difference was considered significant if the p-value was lower than 0 . 05 ( * for p < 0 . 05 , ** for p < 0 . 001 , *** for p < 0 . 0001 ) . All data are expressed as means ± standard error of the mean . | Until recently , the general understanding about sleep was that only mammals and birds show two sleep states: slow-wave sleep and rapid eye movement ( REM ) sleep . Consequently , it was thought that these two states appeared independently in these warm-blooded animals . However , a recent paper reported the presence of these two states in the bearded dragon lizard ( Pogona vitticeps ) , suggesting that these two states arose with the common ancestor of mammals , birds , and reptiles . We confirmed the presence of two sleep states in the bearded dragon and compared its sleep with that of another lizard , the Argentine tegu ( Salvator merianae ) . Our results show that both lizard species have two sleep states with similarities to the two sleep states observed in mammals and birds . Additionally , our study of behavioral and physiological parameters as well as the brain activity associated with sleep in these lizards allowed us to also show important differences between these two species of lizards and between lizards , birds , and mammals . Our findings indicate that sleep in lizards is more complex than previously thought and raise further questions about the nature , function , and evolution of these two sleep states . | [
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"electrophysiology... | 2018 | Partial homologies between sleep states in lizards, mammals, and birds suggest a complex evolution of sleep states in amniotes |
The influence of genetic ancestry on Trypanosoma cruzi infection and Chagas disease outcomes is unknown . We used 370 , 539 Single Nucleotide Polymorphisms ( SNPs ) to examine the association between individual proportions of African , European and Native American genomic ancestry with T . cruzi infection and related outcomes in 1 , 341 participants ( aged ≥ 60 years ) of the Bambui ( Brazil ) population-based cohort study of aging . Potential confounding variables included sociodemographic characteristics and an array of health measures . The prevalence of T . cruzi infection was 37 . 5% and 56 . 3% of those infected had a major ECG abnormality . Baseline T . cruzi infection was correlated with higher levels of African and Native American ancestry , which in turn were strongly associated with poor socioeconomic circumstances . Cardiomyopathy in infected persons was not significantly associated with African or Native American ancestry levels . Infected persons with a major ECG abnormality were at increased risk of 15-year mortality relative to their counterparts with no such abnormalities ( adjusted hazard ratio = 1 . 80; 95% 1 . 41 , 2 . 32 ) . African and Native American ancestry levels had no significant effect modifying this association . Our findings indicate that African and Native American ancestry have no influence on the presence of major ECG abnormalities and had no influence on the ability of an ECG abnormality to predict mortality in older people infected with T . cruzi . In contrast , our results revealed a strong and independent association between prevalent T . cruzi infection and higher levels of African and Native American ancestry . Whether this association is a consequence of genetic background or differential exposure to infection remains to be determined .
Chagas disease ( ChD ) , which is caused by the protozoan Trypanosoma cruzi , affects approximately 5 . 7 million people in 21 Latin American countries [1] . ChD is known as a neglected tropical disease and is an emerging issue in North America and Europe [2–5] . ChD is autochthonous in South and Central America but T . cruzi infection has spread to other regions of the world primarily due to immigration of infected persons [2] , although there has been evidence of some locally-occurring infections in the United States [3] . Currently , at least 300 , 000 persons with T . cruzi infection live in the US [4] and at least 80 , 000 in Europe [5] . The disease is costly to individuals and society with estimates of over USD 100 million spent on treatments and over USD 800 million in lost productivity each year [6] . Up to one third of those infected with ChD may develop chronic heart abnormalities and other complications of which Chagas cardiomyopathy is the most severe and life-threatening form [7] . The presence of major electrocardiogram ( ECG ) abnormalities ( a diagnostic measure of Chagas cardiomyopathy ) doubles the risk for mortality in T . cruzi-infected elderly populations [8] . The influence of African and/or Native American ancestry on T . cruzi infection and/or ChD outcomes is unknown . The existence of an association is plausible for at least two reasons: first , familial aggregation of T . cruzi seropositivity and ECG abnormalities have been found in highly endemic areas , suggesting that genetic variation may play a role in susceptibility to infection as well as disease progression [9 , 10]; second , an earlier publication , using ethnoracial self-classification , reported greater prevalence of ECG abnormalities among Black middle-aged adults relative to their White counterparts [11] . Latin America is one of the most ethnoracially heterogeneous regions of the world [12] , and Brazil is the largest and the most populous ChD endemic country in the region . The current Brazilian population’s genetic makeup is the product of admixture between Amerindians , Europeans colonizers or immigrants , and African slaves [13] . Brazil received nearly 4 million slaves from Africa , about seven times more than the United States [14] . Thus , the Brazilian population provides an opportunity to assess the relationship between T . cruzi infection and its complications with genetic ancestry in admixed populations . The Bambui-Epigen Cohort Study of Aging is conducted in a well-defined population of older Brazilian adults living in a formerly ChD endemic area [15] . We examined for the first time the association between genome-wide proportions of genomic ancestry with T . cruzi infection and cardiomyopathy , taking into account an array of socioeconomic and health indicators that could confound such an association . Additionally , we examined whether genomic ancestry affects the prognostic value of major ECG abnormalities for 15-year mortality in T . cruzi-infected individuals .
The Bambui cohort study of aging is ongoing in Bambuí , a city of approximately 15 , 000 inhabitants in the state of Minas Gerais in Southeast Brazil , which is one of the oldest known endemic areas for ChD [16–18] . Detailed information on this cohort can be found elsewhere [15] . Briefly , the population eligible for the cohort consisted of all residents aged 60 years and over on 1 January 1997 ( 92% of the 1 , 742 inhabitants in this age group participated ) . Most participants had some degree of admixture between African , European and Native American genomic ancestry [19 , 20] . T . cruzi infection status was assessed by means of three different assays performed concurrently: a hemagglutination assay ( Biolab Merieux SA , Rio de Janeiro , Brazil ) and two enzyme-linked immunosorbent assays ( Abbott Laboratories , Inc . , North Chicago , Illinois; and Wiener Laboratories , Rosario , Argentina ) . Infection with T . cruzi was defined by seropositivity in all of the three examinations; seventeen persons had discordant results among the assays and were excluded from the analysis . As far as we could determine , none of the cohort participants had a history of use of antitrypanosomal medications , and none of the seropositive subjects reported such treatment over the ensuing decade during annual follow-up visits . Thus , the use of antitrypanosomal therapy was not considered in the present analysis . In addition , no cohort participant had received a cardiac transplant . At the baseline examination , a digitally recorded 12-lead ECG ( Hewlett Packard MI700A ) reading was obtained at rest . ECGs were analyzed at the ECG Reading Center ( EPICARE , Wake Forest University ) and classified using the Minnesota Code ( MC ) criteria [21 , 22] . Major ECG abnormalities were defined by the presence of at least one of the following: old ( MC 1 . 1 . x or 1 . 2 . x ) or possible myocardial infarction ( 1 . 3 . x and 4 . 1 . x , 4 . 2 , 5 . 1 , or 5 . 2 ) , complete intraventricular blocks ( MC 7 . 1 , 7 . 2 , 7 . 4 , or 7 . 8 ) , frequent supraventricular or ventricular premature beats ( MC 8 . 1 . x , except 8 . 1 . 4 ) , major isolated ST segment or T-wave abnormalities ( MC 4 . 1 . x , 4 . 2 , 5 . 1 or 5 . 2 ) , atrial fibrillation or flutter or supraventricular tachycardia ( MC 8 . 3 . x . or 8 . 4 . 2 ) , other major arrhythmias ( MC 8 . 2 . x , except 8 . 2 . 1 ) , major atrioventricular conduction abnormalities or pacemaker use ( MC 6 . 1 , 6 . 2 . x , 6 . 4 , 6 . 8 , 8 . 6 . 1 or 8 . 6 . 2 ) , major QTi prolongation ( >115% ) and left ventricular hypertrophy ( LVH ) ( MC 3 . 1 together with [4 . 1 . x , 4 . 2 , 5 . 1 , or 5 . 2] ) . Further details can be seen elsewhere [8] . Cohort participants were genotyped with the Omni 2 . 5M array ( Illumina , San Diego , California ) [13] . We performed ancestry inferences using the model-based method [23] , implemented in the Admixture software . First , we used 370 , 539 SNPs to estimate for each individual African , European and Native American tri-hybrid ancestry proportions , using 266 African , 262 European and 93 Native American individuals from public datasets as parental populations [13] . Further , we inferred a kinship coefficient for each pair of individuals , using the software Reap [24] , conditioning on tri-hybrid individual admixture proportions . We used complex networks to identify families from the matrix of pair-wise kinship coefficients [13] . In this approach , pairs of individuals ( i . e . families ) are related if they have a kinship coefficient >0 . 1 ( first and second-degree relatives ) . Given that Brazilians with African ancestry generally have a high proportion of East African genetic markers ( as opposed to markers of West African origin ) , relative to African Americans and those from the Caribbean [13 , 25 , 26] , we used 331 , 790 SNPs and the reference dataset “U” [13] to further divide total African ancestry into its two components: a Western-African/non Bantu and an Eastern African/Bantu , hereafter called Western African and Eastern African , respectively . The fact that many Bambuí residents are related could affect high-resolution inferences of biogeographic ancestry ( such as West- and East-African ) with the Admixture software . To overcome this limitation , we performed separate Admixture runs to infer West- and East- African ancestry components , avoiding the presence of related individuals in the same run . Further details on how genetic and ancestry analyses of the Bambui cohort population were performed can be found elsewhere [13 , 27] . Deaths that occurred between study enrollment in 1997 and December 31 , 2011 , were included in the present analysis . Deaths were reported by next of kin during the annual follow-up interview and verified through the Brazilian mortality information system . Death certificates were obtained for 95 . 7% of the participants who died . Deaths from any cause were considered in this analysis . Potential confounding variables included baseline sociodemographic characteristics ( age , sex , schooling , household income and father’s occupation ) and health measures ( current smoking , hypertension , diabetes , coronary heart disease , C-reactive protein and non-HDL cholesterol level ) . We categorized schooling into incomplete primary school ( <4 years ) and complete primary and higher ( 4 years and more ) . We categorized monthly household income per capita into equal or superior to the median value ( median = 1 . 5 Brazilian minimum wages or USD 180 in 1997 ) . Occupation of the study participant’s father ( as informed by cohort members ) was categorized into urban workers , landowners , manual rural workers and unknown . Current smokers were persons who had smoked at least 100 cigarettes during their lifetime and who still smoke . Body mass index ( BMI ) was defined as weight ( in kg ) divided by height ( in meters ) squared . Hypertension was defined by mean ( two out of three measures ) systolic blood pressure of ≥140 mmHg and/or diastolic pressure of ≥90 mmHg and/or treatment [28] . Diabetes mellitus was defined by fasting blood glucose ≥126mg/dL and/or treatment [29] . Coronary heart disease was defined by prior medical diagnosis of myocardial infarction and/or symptoms of angina pectoris [30] . High sensitivity C-Reactive Protein was measured by the CRP immunonephelometric method ( BNII , Dade Behring , Marburg , Germany ) . Blood fasting glucose and cholesterol were determined by using standard enzymatic methods ( Merck , Darmstadt , Germany ) . Non-HDL cholesterol was defined by total cholesterol level minus HDL cholesterol . Unadjusted analyses were based on Pearson´s chi square , oneway ANOVA and Kruskall Wallis tests to examine differences across frequencies , means and medians , respectively . Individual proportions of genomic ancestries were expressed as medians or divided into quintiles . Prevalence ratios ( PR ) estimated by multivariable Poisson regression [31] were computed to examine associations between ( i ) genomic ancestry in quintiles and T . cruzi infection and ( ii ) genome ancestry in quintiles and major ECG abnormality among persons infected with T . cruzi . Further , we used Cox proportional hazard models to implement an analysis restricted to persons infected with T . cruzi to assess the influence of each category of genomic ancestry on the risk of major ECG abnormalities and subsequent mortality . The above-mentioned statistical analyses were based on two models . First , prevalence and hazard ratios were adjusted for age ( continuous ) , sex , smoking , hypertension , diabetes , coronary heart disease ( all dichotomous variables ) plus body mass index , log-transformed C-reactive protein and non-HDL cholesterol ( as continuous measures ) . We then added schooling , monthly household income per capita , and father’s occupation to the previous models . Because 913 participants were first- or second-degree relatives , and excluding them would lead to loss of power and possible selection bias , we kept all related individuals in our analyses and used robust variance estimators in multivariate models to correct results for clustering by family structure . Finally , we examined separately the significance of the effect of multiplicative interactions between sex and genomic ancestry on each outcome by means of cross-product terms in Poisson and Cox proportional hazards regression models , respectively . Since there was no evidence of interaction with sex , the analyses were carried out for both men and women with sex included as a covariate . Separate analyses were performed for African , Native American and European genomic ancestries and further for Western African sub continental ancestry . Statistical analyses were conducted using STATA 13 . 0 statistical software ( Stata Corporation , College Station ) . The Bambui cohort study of aging was approved by the Institutional Review Board of the Oswaldo Cruz Foundation , Rio de Janeiro , Brazil . Genotyping was approved by Brazil’s national research ethics committee , as part of the Epigen-Brazil protocol ( CONEP , resolution 15895 ) . Written informed consent was obtained from all participants at baseline and at all follow-up interviews .
Of the 1 , 606 baseline cohort participants , 1 , 343 had complete information for all study variables and were included in the current analysis . As shown in Table 1 , the prevalence of T . cruzi infection was 37 . 6% ( n = 505 ) . At baseline , the mean age of participants was 68 . 8 years , 61 . 2% were women , and low schooling level ( <4 years ) largely predominated ( 64 . 1% ) . The median proportions of African , Native American and European genomic ancestries were 9 . 6% , 5 . 4% and 83 . 8% , respectively . The median proportion of Western African sub-continental ancestry relative to total African ancestry was 63 . 9% ( complementarily , the corresponding value for Eastern African ancestry was 36 . 1% ) . T . cruzi infected participants had significantly higher median individual proportions of African and Native American ancestries and significantly lower median European genomic ancestry . Other baseline characteristics of the study participants , by T . cruzi infection status , are presented in Table 1 . Table 2 presents median individual proportions of African , Native American and European genomic ancestries by baseline characteristics . Median African and Native American genomic ancestries were significantly higher ( and European ancestry was significantly lower ) among those with lower schooling and income levels , those whose fathers were manual workers or had an unknown occupation , as well as those with any major ECG abnormality or previous coronary heart disease . Median African ancestry was lower in those aged 69 years and over and in those with BMI under 25 kg/m2 . No significant associations with genomic ancestry were found for other study variables . Associations between the different genomic ancestries and T . cruzi infection are shown in Table 3 . There was a graded positive univariate association between T . cruzi infection with the proportion of African and Native American ancestry , and a graded negative relationship with a greater proportion of European ancestry ( p<0 . 001 for all ) . After adjustments for age , sex and health measures , persons at the intermediate and highest quintiles of African and Native American ancestry were significantly more likely to be infected with T . cruzi relative to their counterparts in the lowest quintiles . After further adjustments for socioeconomic indicators ( schooling , income and father’s occupation ) these associations were attenuated , but remained largely significant ( PR = 1 . 38; 95% CI 1 . 07 , 1 . 79 and PR = 1 . 74; 95% CI 1 . 37 , 2 . 35 for those at the intermediate and highest quintiles of African ancestry , respectively , and PR = 1 . 54; 95% CI 1 . 19 , 1 . 99 for those at the highest quintile of Native American ancestry ) . The opposite trend was found for European ancestry ( PR = 0 . 73; 95% CI 0 . 63 , 0 . 85 and PR = 0 . 54; 95%CI 0 . 41 , 0 . 70 , respectively ) . Among those infected , 56 . 4% had at least one major ECG abnormality ( 31 . 7% among the non-infected ) . As shown in Table 4 , in the bivariate analysis , a major ECG abnormality among infected persons was not found to be significantly ( p>0 . 05 ) associated with African , Native American or European ancestry levels . This absence of association remained in analyses adjusted for age , sex and health measures , as well as in analyses further adjusted for socioeconomic indicators . Over a 15 year follow-up period , 683 participants died and 109 ( 8 . 1% ) were lost to follow-up , leading to 14 , 680 person-years ( pyrs ) of observations ( 5 , 251 pyrs among the infected ) . The death rate was 46 . 4 per 1 , 000 pyrs ( 56 . 2 and 40 . 9 per 1 , 000 pyrs among T . cruzi infected and non-infected , respectively ) . As shown in Table 5 , persons infected with T . cruzi with any major ECG abnormality were at significantly increased risk of death , compared to their counterparts with no such abnormalities , independent of age , sex and other health measures ( HR = 1 . 83; 95% CI 1 . 44 , 2 . 34 ) . Further adjustments for socioeconomic indicators had little impact on this association ( HR = 1 . 78; 95% CI 1 . 39 , 2 . 28 ) . The association was consistent across different levels of African , Native American and European genomic ancestries . We found no evidence of statistically significant multiplicative interactions between African , Native American and European genome ancestry levels and major ECG abnormalities on mortality ( p>0 . 05 for all ) . As shown in Table 6 , a statistically significant association between Western African proportion and T . cruzi infection was found in bivariate analysis , but the association lost significance after adjustments for socio demographic characteristics and health measures . Furthermore , we did not find any evidence of an association between the above mentioned ancestry levels and the presence of major ECG abnormalities among people infected with T . cruzi in either univariate or multivariate analyses ( p>0 . 05 for both ) . Finally , as previous observed for global African ancestry , levels of Western African ancestry did not modify the association between a major ECG abnormality and subsequent mortality among infected subjects ( p value for interactions >0 . 05 ) .
The key findings of the current study are: first , T . cruzi infection was strongly correlated with both African and Native American ancestry—and conversely showed a negative correlation with European ancestry—and this association had a graded effect; second , cardiomyopathy in infected persons was not associated with either African or Native American or European ancestry levels; third , genomic ancestry had no significant effect modification on the prognostic value of major ECG abnormalities for mortality in T . cruzi infected older adults; fourth , Western African sub continental origin was not associated with either T . cruzi infection or related outcomes . The above-mentioned findings were independent of an array of sociodemographic and biological confounders . The association between T . cruzi infection and higher levels of African and Native American ancestry may result from genetic influence on susceptibility and/or greater exposure to infection in these groups during the life course . Our study population was born before 1940 , and this cohort has experienced dramatic political and social changes during their lifetimes . Brazil has transitioned from a low-income , primarily rural country in the mid-1950s , to one of the largest economies in the world , with 84% of the population living in urban areas by 2010 [32 , 33] . Chagas disease is related to poor socio-economic circumstances , mostly in early life . In endemic areas , the main source of infection is a bloodsucking triatomine insect that colonizes poor households . Most individuals in these areas acquire the infection before they reach 20 years of age [34] . Further , ethnoracial disparities in Brazil are remarkable . Persons of African origin are more likely to have lower income and education , to experience race-based discrimination , and to report worse health outcomes [14 , 35] . Native Americans experience sustained marginalization [36] . Our results are in agreement with these observations , revealing higher levels of African and Native American ancestry in those with lower schooling and family income levels , as well as those whose fathers were rural workers or had an unknown occupation ( which suggests a less prestigious occupational category ) . T . cruzi infection followed this trend , with higher prevalence associated with worse current ( measured by income ) and worse early socioeconomic circumstances ( educational attainment and father’s occupation ) . However , the association between higher levels of African and Native American ancestry with T . cruzi infection was attenuated , but still remained largely significant after adjustments for socioeconomic indicators , suggesting a possible independent effect of genomic ancestry . Despite this finding , it is important to emphasize that although we control for several important measures of current and early socioeconomic circumstances , they cannot completely account for the complexity of unfavorable trajectories of persons with higher levels of African and Native American ancestry in Brazilian society [14] . Thus , we cannot exclude the possibility that residual confounding may still account for the association between higher levels of African and Native American ancestry and prevalent T . cruzi infection in our analysis . The fact that analyses of subsequent complications ( cardiomyopathy ) showed no association with genomic ancestry further tempers any inference regarding a causal relationship between genetic ancestry and increased vulnerability to T . cruzi . Chronic Chagas cardiomyopathy is the most clinically relevant manifestation of the disease . It manifests as heart failure , arrhythmia , heart block , thromboembolism , stroke and sudden death [7 , 16] . The pathogenesis of chronic chagasic cardiomyopathy is not completely understood [37] , but inflammation caused by persistent parasitism of the heart tissue appears to play an important role [38 , 39] . Additionally , a recent genome-wide study ( GWAS ) identified suggestive single nucleotide polymorphisms ( SNPs ) that may impact the risk of progression to cardiomyopathy in seropositive persons [37] . Electrocardiography has been considered an important tool in the management of ChD patients [7] . Information on ECG findings among the elderly infected with ChD is scant , and very few studies in middle-aged or older adults have used core-lab readings using classifications developed by the internationally accepted Minnesota Code [8] . A previous study in the Bambui cohort showed that any major ECG abnormality ( classified by the Minnesota Code ) was strongly and independently associated with increased risk for 10-year mortality among T . cruzi infected older adults [8] . The results of the current analysis , based on an extended 15 year-follow-up , are in agreement with these findings . Additionally , we found no evidence of an association between African and Native American ancestries and major ECG abnormalities among T . cruzi infected persons . The absence of an association was consistent in bivariate analyses as well as those adjusted for an array of potential confounding factors . Furthermore , African , Native American and European ancestry showed no significant interactions affecting the ability of major ECG abnormalities to predict subsequent mortality . Strengths of this study include the large population-based cohort followed for an extended period , and minimal loss of participants to follow-up . Another major strength is the use of genome-wide measures of ancestry . Genomic ancestry does not change over time , while ethnoracial self-classification is prone to misclassification—particularly in admixed populations [14 , 19] . Another strength is the inclusion of several biological and non-biological risk factors in our analysis . However , one cannot exclude the possibility that there may be additional unmeasured factors , including unknown genetic factors that confound our results . The current study is , to our knowledge , the first investigation on the influence of African , Native American and European genomic ancestry on T . cruzi infection and related outcomes . Our findings indicate that African and Native American ancestry have no influence on the presence of major ECG abnormalities and had no influence on the ability of an ECG abnormality in predicting mortality in older people infected with T . cruzi . In contrast , our results revealed a strong positive association between prevalent T . cruzi infection with higher levels of African and Native American ancestry . Whether this association is a consequence of genetic background , differential exposure to infection , or a combination of both factors , remains to be determined . | Chagas disease ( ChD ) , which is caused by the protozoan Trypanosoma cruzi , affects approximately 8 million people worldwide . ChD is known as a neglected tropical disease . The disease is endemic in South and Central American countries , and is an emerging issue in North America and Europe . This study examined , for the first time , the association between genomic ancestry and T . cruzi infection , Chagasic cardiomyopathy and its ability to predict long term mortality . Our results show that persons with higher levels of African and Native American ancestries ( and the reverse for European ancestry ) are more likely to be infected with T . cruzi . However , genomic ancestry had no effect on either Chagasic cardiomyopathy or on its ability to predict mortality . Whether the association between T . cruzi infection and genomic ancestry is a consequence of genetic susceptibility or differential exposure to infection due to poor socioeconomic circumstances over the life course , remains to be determined . | [
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... | 2016 | Genomic African and Native American Ancestry and Chagas Disease: The Bambui (Brazil) Epigen Cohort Study of Aging |
A recently characterized calmodulin-like protein is an endogenous RNA silencing suppressor that suppresses sense-RNA induced post-transcriptional gene silencing ( S-PTGS ) and enhances virus infection , but the mechanism underlying calmodulin-like protein-mediated S-PTGS suppression is obscure . Here , we show that a calmodulin-like protein from Nicotiana benthamiana ( NbCaM ) interacts with Suppressor of Gene Silencing 3 ( NbSGS3 ) . Deletion analyses showed that domains essential for the interaction between NbSGS3 and NbCaM are also required for the subcellular localization of NbSGS3 and NbCaM suppressor activity . Overexpression of NbCaM reduced the number of NbSGS3-associated granules by degrading NbSGS3 protein accumulation in the cytoplasm . This NbCaM-mediated NbSGS3 degradation was sensitive to the autophagy inhibitors 3-methyladenine and E64d , and was compromised when key autophagy genes of the phosphatidylinositol 3-kinase ( PI3K ) complex were knocked down . Meanwhile , silencing of key autophagy genes within the PI3K complex inhibited geminivirus infection . Taken together these data suggest that NbCaM acts as a suppressor of RNA silencing by degrading NbSGS3 through the autophagy pathway .
Post transcriptional gene silencing ( PTGS ) is an important RNA interference ( RNAi ) -based defense mechanism against foreign nucleic acid invasion and is involved in silencing a wide range of endogenous genes in plants . PTGS is triggered by double-stranded RNAs ( dsRNAs ) , which are cleaved into 21- to 24- nucleotide ( nt ) small interfering RNA ( siRNA ) duplexes by Dicer-like ( DCL ) endoribonucleases . Subsequently , the siRNAs are loaded into an RNA-induced silencing complex ( RISC ) , which contains an RNaseH-like Argonaute ( AGO ) enzyme , and one strand of the siRNA duplex is used to guide AGO to cleave homologous RNAs for degradation [1 , 2] . In plants , overexpressed transgene transcripts , viral RNAs or their cleavage products can serve as the substrates for RNA-dependent RNA polymerases ( e . g . RDR6 ) for conversion of single-stranded RNAs ( ssRNAs ) to dsRNAs , which further produce secondary siRNA molecules through DCL cleavage [3] . Therefore , RDR6 plays a key role in the sense RNA-induced PTGS ( S-PTGS ) pathway , the synthesis of trans-acting small-interfering RNA ( ta-siRNAs ) , and anti-viral silencing pathways [4–6] . Recently , many reports have shown that RDR6-deficient plants ( e . g . Nicotiana benthamiana ) are more susceptible to infection by some positive-sense single-stranded RNA viruses , viroids and DNA viruses [7–10] , strongly supporting the role of RDR6 in the host antiviral response . In these processes , a plant-specific RNA binding protein , Suppressor of Gene Silencing 3 ( SGS3 ) , functions together with RDR6 as a chaperone protein [4–6] . Arabidopsis SGS3 ( AtSGS3 ) contains a zinc finger ( ZF ) , rice gene X and SGS3 ( XS ) , and coiled-coil ( CC ) domain . Among these , the XS and CC domains are involved in RNA binding and homodimer formation , respectively , and both are required for normal AtSGS3 localization and function in the synthesis of ta-siRNAs in plants [11–13] . Previous studies have suggested that AtSGS3 binds and stabilizes RNA templates during initiation of Arabidopsis RDR6 ( AtRDR6 ) -mediated dsRNA synthesis [14] , and AtSGS3 and AtRDR6 co-localize in certain cytoplasmic granules called SGS3/RDR6-bodies [13] . However , whether SGS3 from N . benthamiana plays a similar chaperone role with NbRDR6 is still obscure . PTGS is an elaborately regulated process targeted against viral infection . However , most plant viruses have evolved viral suppressors of RNA silencing ( VSRs ) to counteract host antiviral silencing activity . Various VSRs have been identified in almost all plant virus genera , but they exhibit no obvious sequence similarities and interact with RNA-silencing pathways in multiple ways [15] . Recent reports show that several components of the Arabidopsis cytoplasmic exoribonuclease complex participated in mRNA quality control and mRNA processing , including FIERY1 , XRN2 , XRN3 , XRN4 , EIN5 and SKI2 , which can also function as repressors of PTGS [16–18] . Moreover , impairing nonsense-mediated decay , deadenylation or exosome activity enhances S-PTGS in Arabidopsis , which requires the host RDR6 and SGS3 proteins for conversion of ssRNAs into dsRNAs to trigger PTGS [19] . Those endogenous RNA suppressors derived from mRNA decay pathways competed for SGS3/RDR6 RNA substrates to repress RNA silencing , suggesting the crucial role of SGS3/RDR6 in the endogenous RNA silencing pathway . A calmodulin-like protein from Nicotiana tabacum ( NtCaM ) has been identified as an endogenous RNA silencing suppressor which interacts with the helper component-proteinase ( HC-Pro ) of a potyvirus [20] . However , follow-up work showed that NtCaM interacts with and directs degradation of several dsRNA binding VSRs likely through the autophagy-like protein degradation pathway , revealing a contradictory function for NtCaM in antiviral defense [21] . Nevertheless , a growing body of evidence published recently by different laboratories supports a role for the calmodulin-like protein as an S-PTGS suppressor [10 , 22–24] . In the case of geminivirus infections , calmodulin-like protein from N . benthamiana ( NbCaM ) was up-regulated by Tomato yellow leaf curl China betasatellite ( TYLCCNB ) -encoded βC1 upon virus infection . Up-regulation of NbCaM by βC1 suppressed RNA silencing by repressing expression of RDR6 to promote viral infection [10] . Moreover , overexpression of Arabidopsis calmodulin-like protein 39 ( AtCaM39 ) leads to increased susceptibility to infection by Tomato golden mosaic virus ( TGMV ) [22] . These studies indicate that calmodulin-like proteins are hijacked by plant viruses ( at least geminiviruses , if not all ) to counterattack the host defense response . However , the precise mechanism of calmodulin-like protein-mediated S-PTGS suppression is yet to be understood . Autophagy is thought to be a nonspecific , bulk degradation process by which eukaryotic cells recycle intracellular components , such as protein aggregates and organelles [25] . There are at least three types of autophagy: macroautophagy , microautophagy and chaperone-mediated autophagy [26] . Macroautophagy ( hereafter referred to as autophagy ) is the major type of autophagy , and it occurs when cytoplasmic constituents are engulfed by double-membrane vesicles termed autophagosome and subsequently delivered to the vacuoles for breakdown and turnover in plants [27] . Autophagy is evolutionarily conserved from yeast to plants , and most of the essential components have been identified and characterized in plants through comparison to their homologs in yeast [26 , 28–30] . Among these autophagy-related genes ( ATGs ) , Beclin1 forms a complex with PI3K/VPS34 , the class III phosphatidylinositol 3-kinase , as a first step in the initiation of autophagy , recruits other proteins to the complex and is required for autophagosome formation [26 , 31] . Autophagy has also been shown to be important for anti-viral defense . In Drosophila , ATGs protect against Vesicular stomatitis virus ( VSV ) infection , and disruption of ATG5 , ATG8 , and ATG18 is associated with increased VSV RNA replication resulting in increased animal lethality [32] . Autophagy has also been reported to participate in antiviral defense in mammalian systems . For example , ATG5 is essential to protect mice against lethal infection of the mouse central nervous system by Sindbis virus [33] . Not surprisingly , viruses have developed strategies to subvert or use autophagy for their own benefit . For example , autophagy proteins are proviral factors that favor initiation of Hepatitis C virus infection and are required for translation of incoming viral RNA [34 , 35] . In plants , deficiency in ATGs compromises plant vitality and disease resistance [29 , 36 , 37] . For example , N-gene mediated resistance against Tobacco mosaic virus ( TMV ) is dependent on autophagy genes , and plants deficient in the autophagy genes , Beclin1 , PI3K/VPS34 , ATG3 , and ATG7 , exhibit an unrestricted hypersensitive response ( HR ) in response to pathogen infection [29] . However , Arabidopsis mutant atg2-2 and several other ATG mutants , including atg5 , atg7 and atg10 , exhibit enhanced resistance to powdery mildew and dramatic mildew-induced cell death [38] , providing new insights into the role of autophagy in disease resistance and cell death . A recent report showed that autophagy is possibly involved in the RNA silencing suppressor activity of P0 , as P0-mediated degradation of AGO1 can be blocked by autophagy inhibitors [39] . Therefore , there is a question of whether autophagy is involved in the suppressor activity of NbCaM or in geminivirus infection . In this study , we show that NbCaM interacts with SGS3 from N . benthamiana ( NbSGS3 ) , but not with NbRDR6 . Furthermore , we found that NbCaM induces degradation of NbSGS3 by interacting with ATG factors , and silencing of ATG genes inhibits NbCaM-mediated NbSGS3 degradation and promotes resistance to infection by the geminivirus Tomato yellow leaf curl China virus ( TYLCCNV ) and its betasatellite ( TYLCCNB ) . Together with previous results , these findings suggest that the endogenous RNA silencing suppressor NbCaM regulates RNA silencing and promotes geminivirus infection by repressing NbRDR6 expression and promoting degradation of NbSGS3 , most likely via the autophagy pathway .
NbCaM suppresses sense RNA-induced PTGS and enhances geminivirus infection in N . benthamiana , similar to results observed when expression of AtSGS3 and AtRDR6 in Arabidopsis is reduced [4–6] . To explore the molecular mechanism of NbCaM-mediated suppression of RNA silencing and augmentation of geminivirus infection , potential interactions among NbCaM , NbSGS3 and NbRDR6 were analyzed initially using yeast two-hybrid ( Y2H ) assays . An expressed sequence tag ( EST ) for the NbSGS3 sequence was identified by aligning tobacco NtSGS3 and tomato SlSGS3 sequences ( obtained from the GenBank database ) . Primers were designed to amplify the full-length coding sequence and the full-length gene encoding NbSGS3 was cloned from N . benthamiana . Sequence analysis revealed that the NbSGS3 open reading frame ( ORF ) contains 1908 nucleotides ( nt ) ( GenBank accession number: KJ190939 ) . Co-transformants of NbCaM cloned as a fusion with the GAL4 activation domain ( AD-NbCaM ) and NbSGS3 as a fusion with the GAL4 DNA binding domain ( BD-NbSGS3 ) were plated on different selective media to detect activation of the reporter genes , HIS3 and ADE2 . Yeast transformants containing AD-NbCaM and BD-NbSGS3 were able to grow on SD/Leu-Trp-His selection plates with 5 mM 3-amino-1 , 2 , 4-triazole ( 3-AT ) , whereas yeast transformants carrying AD-NbCaM with empty vector ( AD-NbCaM + BD ) or BD-NbSGS3 with empty vector ( BD-NbSGS3 + BD ) were unable to proliferate ( Fig 1A ) . Furthermore , yeast transformants containing AD-NbCaM and BD-NbRDR6 showed no interaction between the proteins tested ( Fig 1B ) . In addition , yeast transformants containing AD-NbRDR6 and BD-NbSGS3 or AD-NbSGS3 and BD-NbSGS3 also grew on the selection plates ( S1A and S1B Fig ) , consistent with an interaction between SGS3 and RDR6 and self-interaction of SGS3 , which was observed for AtSGS3 and AtRDR6 [12 , 13] . Expression of NbCaM , NbSGS3 and NbRDR6 proteins was verified by Western blot ( S1C–S1F Fig ) . The interaction between NbCaM , NbSGS3 and NbRDR6 was further investigated by bimolecular fluorescence complementation ( BiFC ) in leaves from transgenic N . benthamiana plants which expressed H2B-RFP as a nuclear marker . In this assay , NbCaM , NbSGS3 and NbRDR6 were fused to the N ( 2YN ) and C-terminal ( 2YC ) fragments of yellow fluorescent protein ( YFP ) , generating the constructs 2YN-NbCaM , 2YC-NbCaM , 2YN-NbSGS3 , 2YC-NbSGS3 , 2YN-NbRDR6 and 2YC-NbRDR6 . Pairwise expression of 2YN-NbCaM and 2YC-NbSGS3 , 2YC-NbCaM and 2YN-NbSGS3 , 2YN-NbRDR6 and 2YC-NbSGS3 , and 2YC-NbRDR6 and 2YN-NbSGS3 by agroinfiltration resulted in a clear YFP fluorescence signal in the cytoplasm of agroinfiltrated cells at 48 hours post infiltration ( hpi ) ( Fig 1C ) . While no YFP fluorescence was observed when 2YN-NbCaM and 2YC-NbRDR6 or 2YC-NbCaM and 2YN-NbRDR6 were co-expressed together ( Fig 1D and S2 Fig ) . The movement protein P3N-PIPO from Turnip mosaic virus ( TuMV ) [40] was used as a negative control , we found there was no YFP fluorescence in the pairwise expression of 2YN-NbSGS3 and 2YC-P3N-PIPO or 2YC-NbSGS3 and 2YN-P3N-PIPO ( Fig 1D and S2 Fig ) . These results demonstrate that NbCaM specifically interacts with NbSGS3 in both yeast and plant cells . In Arabidopsis thaliana , efficient RNA silencing requires RDR6 and its double-stranded RNA ( dsRNA ) -binding partner , SGS3 to amplify secondary siRNAs which allow plants to mount an effective defense response against transgene-induced aberrant RNAs or virus infection [4–6] . To better understand the role of NbCaM in the S-PTGS pathway and the potential effect of NbCaM on the function of NbSGS3 , the sequence and biological features of NbSGS3 were analyzed . NbSGS3 cDNA encodes a 635-amino acid ( aa ) protein , with a structure similar to AtSGS3 and contains a zinc finger domain ( ZF ) , a rice gene X and SGS3 domain ( XS ) , and two coiled-coil domains ( 2*CC ) ( Fig 2A ) . A phylogenetic tree was constructed to compare the evolutionary relationships among SGS3 orthologs in tobacco ( NtSGS3 ) , tomato ( SlSGS3 ) and Arabidopsis ( AtSGS3 ) ( Fig 2B ) . NbSGS3 is clustered with NtSGS3 and SlSGS3 and is distant from AtSGS3 , sharing 94% , 82% and 51% aa identity with NtSGS3 , SlSGS3 and AtSGS3 , respectively . To determine the expression pattern of NbSGS3 , reverse transcription real-time quantitative PCR ( RT-qPCR ) was performed using total RNA isolated from different N . benthamiana tissues as template . NbSGS3 expression levels were very similar among different tissues , with the exception that the expression level in flower was higher than that detected in root tissues ( Fig 2C , p<0 . 01 ) . To examine the subcellular localization of NbSGS3 , a green ( GFP ) or red ( RFP ) fluorescent protein reporter was fused to its C-terminus ( NbSGS3:GFP or NbSGS3:RFP ) under control of the Cauliflower mosaic virus ( CaMV ) 35S promoter . GFP or NbSGS3:GFP was transiently expressed in leaves of transgenic H2B-RFP N . benthamiana plants , and GFP fluorescence was examined in agroinfiltrated transgenic leaves at 48 hpi by confocal microscopy . Fluorescence in plants expressing GFP alone was observed in both the cytoplasm and nucleus , whereas fluorescence from NbSGS3:GFP was localized to granular-like structures in the cytoplasm ( Fig 2D ) . These granular-like structures were also observed in N . benthamiana protoplasts ( S3A Fig ) . Similar granular-like structures were also observed when a YFP was fused to the N terminus of NbSGS3 ( YFP:NbSGS3 , S3B Fig ) . A previous study reported that AtSGS3 localized to cytoplasmic granules , termed SGS3/RDR6-bodies [13] . To check whether NbSGS3 also localizes to SGS3/RDR6-bodies , NbRDR6:GFP and NbSGS3:RFP were co-expressed in wild type ( Wt ) N . benthamiana . As shown in Fig 2D , NbRDR6 alone formed irregular granules along the edge of the cell ( the third line ) , but NbRDR6:GFP co-localized with NbSGS3:RFP to the cytoplasmic granules ( the fourth line ) . In addition , we also examined whether NbSGS3 granules are related to cellular organelles , including chloroplasts , mitochondria , golgi bodies or peroxisomes , but no co-localization was found ( S3A Fig and S4 Fig ) . To map the protein domains required for the interaction between NbCaM and NbSGS3 , three deletion mutants for NbSGS3 and four deletion mutants for NbCaM were constructed ( Fig 3A and 3B ) . Mutants NbCaM-dX , NbCaM-dEFI , NbCaM-dEFII and NbCaM-dEFIV lacking the N-terminal 50 aa of an unknown domain , or the first , second and fourth Ca2+ binding EF-hand domain , respectively , were cloned into the plant BiFC vector 2YN [41] . Mutants NbSGS3-dZF , NbSGS3-dXS and NbSGS3-d2*CC , which lack the zinc finger , rice gene X and SGS3 domain , and two coiled-coil domains , respectively , were generated and cloned into the plant BiFC vector 2YC [41] . BiFC assays were performed using 2YN- and 2YC-tagged mutant proteins in transgenic H2B-RFP N . benthamiana plants . NbCaM deletion mutants NbCaM-dEFI and NbCaM-dEFII were unable to interact with NbSGS3 , and NbSGS3 deletion mutants NbSGS3-dZF and NbSGS3-d2*CC failed to interact with NbCaM ( Fig 3C ) . These results suggest that the EFI and EFII domains of NbCaM and the ZF and CC domains of NbSGS3 are essential for the interaction between NbSGS3 and NbCaM . Localization of SGS3 to SGS3/RDR6-bodies is one of its basic features [13] . To investigate whether the domains essential for the interaction between NbCaM and NbSGS3 are also important for localization of NbSGS3 , three deletion mutants of NbSGS3 were fused with GFP at their C-termini . Typical localization patterns of the deletion mutants and wild type NbSGS3:GFP ( NbSGS3-Wt:GFP ) are shown in Fig 3D . Expression of these proteins was verified by Western blot analyses ( Fig 3E ) . In contrast to the granule localization of NbSGS3-Wt:GFP and the NbSGS3-dXS:GFP mutant , the NbSGS3-dZF:GFP or NbSGS3-d2*CC:GFP mutant exhibited no obvious granule localization ( Fig 3D ) . These results suggest that the ZF and the 2* CC domains are important for localization of NbSGS3 to the granules . We next tested whether domains essential for the interaction between NbCaM and NbSGS3 are also required for the PTGS suppressor activity of NbCaM . N . benthamiana leaves were co-infiltrated with agrobacteria harboring either an empty vector ( Vec ) , 35S:NbCaM-dX ( dX ) , 35S:NbCaM-dEFI ( dEFI ) , 35S:NbCaM-dEFII ( dEFII ) , 35S:NbCaM-dEFIV ( dEFIV ) or 35S:NbCaM ( wild type NbCaM , Wt ) , together with 35S:GFP plus 35S:FP to trigger PTGS . Weak GFP fluorescence was observed in tissues co-infiltrated with empty vector , 35S:NbCaM-dEFI or 35S:NbCaM-dEFII together with 35S:GFP +35S:FP at 5 dpi . In contrast , strong fluorescence was evident in infiltrated patches where 35S:GFP +35S:FP were co-expressed with 35S:NbCaM-dX , 35S:NbCaM-dEFIV or 35S:NbCaM ( Fig 3F ) . GFP fluorescence in infiltrated leaf patches was confirmed by the presence of GFP mRNA and protein , and expression of Wt or mutant forms of NbCaM was validated by the presence of NbCaM mRNA ( Fig 3G ) . These results demonstrate that domains within NbCaM that are essential for the interaction with NbSGS3 are also indispensable for NbCaM suppressor activity . It has been reported that the correct localization of SGS3 is important for its biological function [13] . To determine whether NbCaM affects the localization pattern of NbSGS3 , GFP and NbSGS3:GFP fusion proteins were expressed alone or co-expressed with either empty vector ( Vec ) or Myc:NbCaM in N . benthamiana leaves . The distribution of GFP was very similar between tissue expressing GFP alone , or when co-expressing empty vector or Myc:NbCaM ( Fig 4A ) . The NbSGS3:GFP fusion protein formed granules in the cytoplasm when it was expressed alone or together with empty vector . However , when NbSGS3:GFP was co-expressed with Myc:NbCaM , the number of NbSGS3:GFP granules was greatly decreased as compared to plants expressing NbSGS3:GFP alone or in conjunction with empty vector ( Fig 4A and 4B ) . To further determine whether the weak fluorescence of NbSGS3:GFP in plants co-expressing Myc:NbCaM was due to decreased NbSGS3:GFP levels , Western blot analysis was performed to determine the accumulation of NbSGS3:GFP . As expected , levels of NbSGS3 decreased ~2-fold when co-expressed with Myc:NbCaM as compared to empty vector ( Fig 4C ) . To exclude the possible influence of the tag , Myc:NbSGS3 was also expressed alone , or co-expressed with GFP or NbCaM:GFP . Protein and mRNA levels of Myc:NbSGS3 remained constant when expressed alone or together with GFP . In samples overexpressing NbCaM:GFP , no obvious changes in Myc:NbSGS3 mRNA were observed , but the amount of NbSGS3 protein was largely reduced ( Fig 4D ) . It is worth mentioning that the NbCaM protein level was also reduced ~2-fold when co-expressed with NbSGS3 as compared to NbCaM alone ( Fig 4C and 4D ) . These results suggest that overexpression of NbCaM leads to reduced NbSGS3 protein accumulation , and that both may be targeted for degradation after they form a complex . A recent study showed that NtCaM is sensitive to 3-methyladenine ( 3-MA ) and E64d , inhibitors of the autophagy pathway , and NtCaM seems to mediate degradation of VSRs [21] . To determine whether NbCaM-mediated degradation of NbSGS3 protein occurs via autophagy or other protein degradation systems , the sensitivity of NbCaM or NbSGS3 to 3-MA and E64d , two chemical inhibitors of autophagy , was tested . N . benthamiana leaves were agroinfiltrated with GFP , NbCaM:GFP or NbSGS3:GFP followed by infiltration of DMSO ( control ) , 3-MA ( 10 mM ) or E64d ( 100 uM ) after 32 hours . Samples were collected from leaves after an additional 16 h incubation . No obvious changes in GFP , NbCaM:GFP and NbSGS3:GFP protein levels were observed in DMSO , 3-MA or E64d treated samples ( S5 Fig ) . These results suggest that inhibition of autophagy did not affect accumulation of NbCaM or NbSGS3 when expressed alone . Similarly , the 26S proteasome inhibitor MG132 did not have an observable impact on the accumulation of NbCaM or NbSGS3 ( S6 Fig ) . We next co-expressed Myc:NbSGS3 with GFP or Myc:NbSGS3 with NbCaM:GFP in plants treated with DMSO or 3-MA using different concentrations of Agrobacterium tumefaciens cultures carrying GFP or NbCaM:GFP and assessed protein levels by Western blot . Levels of GFP and Myc:NbSGS3 protein did not appear to change when co-expressed or when expressed in the presence of DMSO or 3-MA ( Fig 5A ) . However , both Myc:NbSGS3 and NbCaM:GFP protein accumulated to higher levels in 3-MA treated plants as compared to DMSO treated plants ( Fig 5B ) . The E64d had a similar role with 3-MA on the accumulation of NbSGS3:GFP when it was co-expressed with Myc:NbCaM ( S7 Fig ) . These results suggest that NbCaM and NbSGS3 are most likely degraded by autophagy in plant cells . To confirm this assumption , we used YFP-tagged N . benthamiana ATG8a ( YFP-ATG8a ) as an autophagosome marker to monitor autophagy [36 , 42–45] . In Wt or 35S:NbCaM transgenic N . benthamiana plants , we observed a low number of punctate YFP fluorescent structures ( Fig 5C ) . However , when NbSGS3 was transiently over-expressed in 35S:NbCaM transgenic N . benthamiana plants via infiltration with TO:NbSGS3 , there was a 3 to 4-fold increase in the punctate fluorescent structures , likely representing pre-autophagosome or autophagosome structures ( Fig 5C and 5D ) . To check if NbSGS3 has any effects on YFP-ATG8a accumulation , YFP-ATG8a accumulation levels were compared by Western blot between co-expression of NbSGS3 with YFP-ATG8a or with empty vector and result showed that YFP-ATG8a accumulation level were similar between the two treatments ( S8 Fig ) , indicating that NbSGS3 has no negative effect on YFP-ATG8a accumulation . To further assess induction of autophagy when NbCaM and NbSGS3 are co-expressed , transmission electron microscopy ( TEM ) was used to monitor autophagic activity . Co-expression of NbCaM and NbSGS3 induced a 4-fold greater number of double-membrane structures typical of autophagosomes in the cytoplasm , as compared to expression of NbSGS3 or NbCaM alone ( Fig 5E and 5F ) . Taken together , these results indicate that NbCaM and NbSGS3 are likely degraded by autophagy after they form a complex . To further understand the involvement of autophagy in NbCaM-mediated NbSGS3 degradation , the phosphatidylinositol 3-kinase ( PI3K ) complex containing Beclin1/VPS30/ATG6 , PI3K/VPS34 and VPS15 , which form phagophore to initiate autophagy [31] , were analyzed . Predicted cDNA and protein sequences for Beclin1 , PI3K , and VPS15 were identified in N . benthamiana ( https://solgenomics . net/tools/blast/ ) through sequence similarity to homologs in A . thaliana and N . tabacum [29 , 46 , 47] . Partial-length cDNA sequences were isolated using N . benthamiana cDNA and cloned into a Tobacco rattle virus ( TRV ) -based VIGS vector . N . benthamiana seedlings were agroinfiltrated with recombinant TRV vectors carrying partial fragments of NbBeclin1 , NbPI3K and NbVPS15 , respectively to induce silencing of each gene . Silencing of these genes in N . benthamiana plants did not result in any distinct developmental defects in systemic leaves ( S9A Fig ) , when compared to TRV-GUS-infected plants ( negative controls ) . At 14 dpi , in plants infiltrated with ATG-silencing vectors , mRNA levels of each ATG were reduced by approximately 80% as compared to negative controls ( infiltrated with TRV-GUS or mock ) ( S9B Fig ) . Newly formed upper leaves in ATG-silenced , TRV-GUS-treated or mock plants ( no TRV infection ) were infiltrated with NbSGS3:GFP and empty vector ( Vec ) or NbSGS3:GFP and Myc:NbCaM at 21 dpi . Two days later , the newly infiltrated leaf tissue was examined by confocal microscopy to compare the fluorescence strength of NbSGS3:GFP . Western blot analysis was performed to determine levels of NbSGS3:GFP . In mock or TRV-GUS-treated plants , overexpression of NbCaM decreased the fluorescence intensity of NbSGS3:GFP ( S10 Fig ) and reduced the accumulation of NbSGS3:GFP 3-fold ( Fig 6A ) . Silencing either Beclin1 , PI3K or VPS15 blocked degradation of NbSGS3 as determined by reduced levels of NbSGS3:GFP protein in infiltrated leaf patches ( Fig 6A ) . These results demonstrate that the autophagy genes Beclin1 , PI3K and VPS15 , which constitute the PI3K complex , are required for NbCaM-mediated degradation of NbSGS3 . TYLCCNB-encoded βC1 up-regulates NbCaM to suppress RNA silencing and promote viral infection [10] . Given that NbSGS3 has an important role in defense against geminiviral infection and NbCaM-mediated NbSGS3 degradation appears to be dependent on the autophagy pathway , we next examined whether ATGs were also involved in geminivirus infection . Plants silenced for NbBeclin1 , NbPI3K or NbVPS15 at 7 dpi were inoculated with equal amounts of TYLCCNV and its betasatellite ( 10Aβ ) and symptoms induced by 10Aβ in mock , TRV-GUS-treated or ATGs-silenced plants were observed . Infection induced by 10Aβ in TRV-GUS-treated plants showed leaf curling symptoms similar to those observed in mock plants at 14 dpi . In contrast , NbBeclin1 , NbPI3K or NbVPS15-silenced plants developed much milder symptoms with reduced leaf curling ( Fig 6B ) . In agreement with these observations , Southern blot analysis of viral genomic DNA levels indicated almost undetectable amounts of viral DNA accumulation of both helper virus ( 10A ) and betasatellite ( 10β ) in NbBeclin1 , NbPI3K or NbVPS15-silenced plants ( Fig 6C ) . qPCR analysis of 10A and 10β DNA levels in the upper emerged infected leaves also showed a significant reduction in viral DNA levels in NbBeclin1 , NbVPS15 or NbPI3K-silenced plants as compared to TRV-GUS-treated or mock plants ( Fig 6D ) . These findings suggest that the PI3K complex is necessary for maximal symptom development and viral DNA accumulation , consistent with their role in the degradation of NbSGS3 . To determine whether these observations extend to geminivirus that lacks an associated betasatellite , mock , TRV-GUS-treated or ATGs-silenced plants were also inoculated with equal amounts of TYLCCNV alone ( 10A ) . No obvious viral symptom and viral DNA accumulation difference were observed in among mock , TRV-GUS-treated , and NbBeclin1 , NbPI3K or NbVPS15-silenced plants at 14 dpi ( Fig 6E and 6F ) . Similarly , the deficiency of NbBeclin1 , NbPI3K or NbVPS15 also had no obvious effect on the infectivity and viral DNA accumulations of Tomato leaf curl Yunnan virus ( TLCYnV ) and Tobacco curly shoot virus ( TbCSV ) without betasatellite ( S11 Fig ) . These data indicate that the proviral role of autophagy in geminivirus biology depends on the presence of betasatellite .
In plants , RNA silencing is a major defense mechanism against foreign genes or viral invasion [2 , 3] . As a counter defensive strategy , plant viruses have evolved VSRs as potent molecular weapons to counteract antiviral RNA silencing by interacting with key components of the cellular RNA silencing pathway , such as binding long or short dsRNA duplex , interacting with or disrupting AGOs , DCLs , RDRs and their functional partners , or interfering with the assembly of RISC [1 , 15] . The function of calmodulin-like protein is still in dispute and its suppression mechanism is not clear . To help clarify the mechanism by which calmodulin-like protein suppresses RNA silencing , we showed that NbCaM interacts with NbSGS3 in the Y2H and BiFC systems , but not with NbRDR6 ( Fig 1 ) . AtSGS3 localizes to cytoplasmic granules ( SGS3/RDR6-bodies ) , where RDR6-mediated dsRNA synthesis is thought to occur [13] . NbSGS3 also localizes to SGS3/RDR6-bodies , along with NbRDR6 ( Fig 2D ) , indicating that SGS3/RDR6-bodies are likely conserved among different plant species . However , the domains that are necessary for localization of NbSGS3 and AtSGS3 appear to be different . We showed that the ZF and CC domains are required for NbSGS3:GFP localization , but the XS and CC domains are necessary for AtSGS3:GFP localization [13] . As the partner of RDR6 , SGS3 can bind the 5’ overhang of dsRNAs and may prevent degradation of these dsRNAs , alter their localization , and/or recruit them as templates for dsRNA synthesis process [11 , 14 , 48] . Therefore , it is not surprising that SGS3 is targeted by several VSRs , including the V2 protein of Tomato yellow leaf curl virus ( TYLCV ) [49] , p2 of Rice stripe virus ( RSV ) [50] , the VPg protein of Potato virus A ( PVA ) [51] , TGBp1 of Planta goasiatica mosaic virus ( PlAMV ) [52] . Our data showed that NbSGS3 is also a target of the endogenous RNA silencing suppressor , NbCaM . First , NbCaM interacted with NbSGS3 in yeast and in planta ( Fig 1 ) . Second , deletion mutants lacking the EFI and EFII domains lost the ability to interact with NbSGS3 , and failed to suppress GFP-induced S-PTGS ( Fig 3F and 3G ) . Finally , overexpression of NbCaM led to a reduced accumulation of NbSGS3 in granules and promoted its degradation ( Fig 4 ) . Our data also demonstrate that the interaction between NbCaM and NbSGS3 is required for the suppressor activity of NbCaM . Meanwhile , the ZF and CC domains of NbSGS3 , which are necessary for localization to the SGS3/RDR6-bodies , are also required for the interaction with NbCaM . This suggests that these two domains play an important role in inducing RNA silencing . Autophagy has been reported to play a central role in several physiological and developmental responses in plants , such as nutrient recycling , seed development and germination , nitrogen or carbon deprivation [44 , 45 , 53 , 54] , and plant immunity and programmed cell death [29 , 55] . A recent study showed that NtCaM could mediate degradation of the dsRNA binding VSR 2b via the autophagy-like protein degradation pathway [21] . We found that overexpression of NbCaM induced degradation/reduction of NbSGS3 when co-expressed ( Fig 4 ) . Inhibition of autophagy ( 3-MA or E64d , S5 Fig ) or the 26S proteasome ( S6 Fig ) did not have obvious effects on the accumulation of GFP , NbCaM:GFP or NbSGS3:GFP , when expressed alone . In contrast , 3-MA-treatment blocked degradation of both NbCaM and NbSGS3 , when co-expressed and led to an increase in the level of their corresponding proteins ( Fig 5A and 5B ) . This phenomenon suggests that individual expression of either NbCaM or NbSGS3 does not trigger autophagy-mediated degradation , but that interaction between NbCaM and NbSGS3 activates the autophagy system , possibly via recruitment of some ATG proteins . Indeed , degradation was blocked when NbBeclin1 , NbPI3K or NbVPS15 , which constitute the PI3K complex , was silenced . In addition , when NbBeclin1 , NbPI3K or NbVPS15 was knocked-down , TYLCCNV and TYLCCNB ( 10Aβ ) was unable to infect plants efficiently , showing very mild viral symptoms and almost undetectable viral DNA levels ( Fig 6A–6D ) , suggesting a necessary role for the PI3K complex in viral replication and systemic infection . It is worthy to note that the knock-down of NbBeclin1 , NbPI3K or NbVPS15 has no effect on the infection of this geminivirus that lacks an associated betasatellite ( 10A ) ( Fig 6E and 6F ) . These data indicate that the proviral role of autophagy in geminivirus biology depends on the presence of betasatellite , which is consistent with the fact that 10Aβ not 10A significantly up-regulates NbCaM expression and induces severe symptoms [10 , 62] . Similarly , the other two geminiviruses in the absence of betasatellite showed no obvious differences in their infectivity in mock and ATGs-silenced plants ( S11 Fig ) . Therefore , it seems that geminiviruses that lack an associated betasatellite fail to utilize autophagy factors to defend NbRDR6/NbSGS3-dependent resistance . RDR6 and SGS3 play important roles in RNA silencing , and their expression can be effectively fine-tuned . For NbCaM to be an effective negative regulator of RNA silencing , it needs to repress both NbRDR6 and NbSGS3 . In support of this , our previous study showed that NbCaM suppressed NbRDR6 mRNA levels [10] . Plant calmodulin-like proteins can directly bind to DNA and function as transcription factors ( TF ) to activate or suppress a target gene’s expression [56] . For example , an Arabidopsis calmodulin-binding transcription factor CAMTA3 functions as a suppressor of defense response and can activate gene expression by directly binding to promoters of suppressed genes or suppressing gene expression by activating expression of a repressor [57] . We found that NbCaM could activate expression of a reporter gene in yeast cells ( S12 Fig ) , which indicates that NbCaM may also function as a TF . It is therefore possible that NbCaM suppresses NbRDR6 via binding to a promoter element and repressing its expression . However , further study is necessary to determine the mechanism of NbCaM suppression of NbRDR6 expression . Together with previous studies , we conclude that the cellular suppressor NbCaM not only suppresses NbRDR6 transcription , but also interacts with the RNA silencing component NbSGS3 and mediates its degradation by recruiting autophagy factors . Geminivirus betasatellite appears to utilize NbCaM in suppression of plant antiviral defenses , which leads to successful viral infection and multiplication ( Fig 7 ) .
N . benthamiana seedlings were placed in soil and incubated in an insect-free growth chamber at 25°C and 60% relative humidity under a 16 h light/8 h dark photoperiod . The transgenic H2B-RFP line was gift of Michael M . Goodin ( University of Kentucky , USA ) . The tobacco NtSGS3 and tomato SlSGS3 sequences were used to identify orthologous sequences from available N . benthamiana ESTs . BLAST searches revealed high homology between SGS3 from tobacco and N . benthamiana ( https://blast . ncbi . nlm . nih . gov/Blast . cgi ? CMD=Web&PAGE_TYPE=BlastHome ) . Primers designed to anneal to conserved sequences in the 5' and 3' untranslated regions of tobacco SGS3 were used to amplify the coding region of N . benthamiana SGS3 by reverse transcription PCR ( RT-PCR ) . Amplification with primer pairs NbSGS3-cds-F/NbSGS3-cds-R yielded a specific product of approximately 1900-bp , which was cloned into pMD18-T ( TaKaRa , Dalian , China ) and then sequenced . Detailed primer information is given in S1 Table . The full-length gene of NbSGS3 was deposited in GenBank under the accession number KJ190939 . The full-length NbSGS3 was amplified using primer pair NbSGS3-F/NbSGS3-R and cloned into the binary vectors pCHF3-Flag , pCHF3-GFP or pCHF3-RFP between the BamHI and SalI sites . The resulting plasmids ( pCHF3-35S-NbSGS3:Flag , pCHF3-35S-NbSGS3:GFP or pCHF3-35S-NbSGS3:RFP ) were used for overexpression in transgenic plants or transient agroinfiltration assays using the CaMV 35S promoter . NbSGS3 was introduced into the 2YN or 2YC BiFC vectors between the PacI and AscI sites to generate 2YN-NbSGS3 or 2YC-NbSGS3 for BiFC analysis . Mutants of NbSGS3 were generated by overlapping PCR [58] , using the corresponding primer pairs given in S1 Table and cloned into the 2YN , 2YC and pCHF3-GFP vectors . To construct a TRV-based recombinant VIGS vector containing NbBeclin1 , NbPI3K or NbVPS15 , a partial fragment of each gene was generated by PCR amplification using the respective primer pair and cloned into the pTRV2 vector ( a kind gift of Yule Liu ) [59] using the restriction enzyme sites listed in S1 Table . The coding sequence of NbCaM was amplified by PCR from N . benthamiana and introduced into the vectors pCHF3-Flag , pCHF3-GFP , 2YN or 2YC using the primers and restriction enzyme sites listed in S1 Table . pCHF3-based vectors were used for transient expression of NbCaM in N . benthamiana leaves . Construction of NbCaM mutants by overlapping PCR was similar to that described for NbSGS3 mutants [58] , using the corresponding primers described in S1 Table . For the pCHF3-NbRDR6:GFP construct , the coding sequence of NbRDR6 was amplified by PCR from N . benthamiana and introduced into pCHF3-GFP between the SmaI and SalI sites using the corresponding primers described in S1 Table . For 2YN-NbRDR6 or 2YC-NbRDR6 , the NbRDR6 coding sequence was introduced into the 2YN or 2YC BiFC vectors between the PacI and AscI sites . 2YN-P3N-PIPO and 2YC-P3N-PIPO have been described previously [40] . The pBA-Flag-Myc4:NbSGS3 ( Myc4:NbSGS3 ) , pEarleygate104:NbSGS3 ( YFP:NbSGS3 ) , pEarleygate101:NbSGS3 ( NbSGS3:YFP ) , pBA-Flag-Myc4:NbCaM ( Myc4:NbCaM ) or pEarleygate104:NbATG8a ( YFP:NbATG8a ) construct was generated using gateway technology ( Invitrogen , Burlington , Ontario , Canada ) with the corresponding primer pairs given in S1 Table . GenBank accession numbers for the genes analyzed in this study are as follows: NbSGS3 ( KJ190939 ) , NtSGS3 ( NM_001325691 ) , SlSGS3 ( NM_001247782 ) , AtSGS3 ( NM_122263 ) , NbRDR6 ( AY722008 ) , NbBeclin1 ( AY701316 ) , NbPI3K ( AY701317 ) , NbVPS15 ( KU561371 ) and NbATG8a ( KX120976 ) . Two-hybrid screen experiments to assess the different interactions between NbCaM , NbSGS3 and NbRDR6 in yeast were performed as described previously [60] . For BiFC and subcellular localization experiments fluorescence were examined in epidermal cells of 1–2 cm2 leaf explants by confocal microscopy ( Leica TCS SP5 , Mannheim , Germany ) from 36 h to 72 h post infiltration as described [60] . For geminivirus agroinoculation , equal volumes of individual A . tumefaciens cultures at an OD600 of 1 were mixed prior to inoculations . Infectious virus clones , including TYLCCNV ( pBinPLUS-Y10-1 . 7A ) , TYLCCNV/TYLCCNB ( pBinPLUS-Y10-1 . 7A+Y10β ) , TbCSV ( pBinPLUS-Y35-1 . 9A ) and TLCYnV ( pBinPLUS-Y194-1 . 4A ) have been described previously [61–63] . Agrobacterium cultures carrying infectious virus clone ( s ) were infiltrated into N . benthamiana leaves and inoculated plants were photographed with a Canon 400D digital camera at different time periods . For the TRV-VIGS assay , Agrobacterium cultures harboring pTRV1 and pTRV2-VIGS ( TRV2-GUS , TRV2-NbBeclin1 , TRV2-NbPI3K or TRV2-NbVPS15 ) were resuspended in infiltration buffer ( 10 mM MgCl2 , 10 mM MES ( pH5 . 6 ) , and 100 μM acetosyringone ) and mixed at a 1:1 ratio . After a 3 h incubation at room temperature , the mixed Agrobacterium cultures were infiltrated into leaves of N . benthamiana plants at the 5–6 leaf stage . A silenced phenotype appeared in the upper leaves at 2 weeks post infiltration . Total DNA was extracted from infected plants using the CTAB method [64] , and DNA blot hybridization performed to assess viral DNA accumulation essentially as described [65] . Total DNA electrophoresed through agarose gels was stained with ethidium bromide to ensure equal loading . After denaturation and neutralization , total DNA was transferred to Hybond N+ nylon membranes ( GE Healthcare , Pittsburgh , PA , USA ) by capillary transfer . Membranes were hybridized at 45°C to specific probes labeled with digoxigenin ( Roche Diagnostics , Rotkreuz , Switzerland ) . Viral DNA levels were determined by qPCR using specific primers ( S1 Table ) and normalized to 25S RNA as an internal genomic DNA control [66] . Total RNA was isolated from virus-infected plants and different plant organs using Trizol reagent ( Invitrogen , Carlsbad , CA , USA ) . For RT-qPCR analysis , 1 μg total RNA was firstly treated with DNase I , and then the first strand cDNA was synthesized from the treated RNA by using Oligo ( dT ) 12-18 primer and SuperScript III reverse transcriptase ( Invitrogen ) following the recommended protocol . All primer information used in RT-PCR was given in S1 Table , and the specific primer pairs for qRT-PCR were designed by Primer Premier 5 software [10] . Total protein was extracted from infiltrated leaf patches as described previously [67] . Immunoblotting was performed with primary mouse monoclonal or rabbit polyclonal antibodies , followed by goat anti-mouse or anti-rabbit secondary antibody conjugated to horseradish peroxidase ( Bio-Rad , Hercules , CA , USA ) . The GFP polyclonal antibody was obtained from Abcam ( Massachusetts , US ) , and the Myc monoclonal antibody was obtained from Sigma ( Los Angeles , CA , USA ) . Blotted membranes were washed thoroughly and visualized using chemiluminescence according to the manufacturer’s protocol ( ECL; GE Healthcare ) . PBS buffer containing 2% DMSO ( control ) or an equal volume of DMSO with 10 mM 3-MA and 100 uM E64d ( Sigma ) for inhibition of autophagy , or 100 μM MG132 ( Sigma ) for inhibition of the 26S proteasome was infiltrated into leaves 16 h before samples were collected . For TEM observation , detailed information has been described previously [46] . Vec and NbSGS3 , or NbCaM , or NbSGS3 +Vec or NbSGS3 +NbCaM -infiltrated leaves pretreated with 10 mM 3-MA for 8 h , and then were cut into small pieces ( 1 mm × 4 mm ) . The sampled tissues were fixed in 2 . 5% glutaraldehyde and 1% osmium tetroxide ( both in 100 mM phosphate buffer ( PB ) , pH 7 . 0 ) . The samples were then post-fixed in OsO4 , dehydrated in ethanol , and then embedded in Epon 812 resin as instructed by the manufacture ( SPI-EM , Division of Structure Probe , Inc . , West Chester , USA ) . Ultrathin sections ( 70 nm ) were cut with a diamond knife from the embedded tissues using the Ultracut E Ultramicrotome ( Reichart-Jung , Vienna , Austria ) and were collected on 3-mm copper ( mesh ) grids , and then stained with uranyl acetate and lead citrate before final examination under an electron microscope , Model JEM-1230 . | Post-transcriptional gene silencing ( PTGS ) is an elaborately regulated process for defense against virus infection in plants . To achieve effective infection , a betasatellite molecule associated with geminivirus induced high levels of an endogenous RNA silencing suppressor , calmodulin-like protein ( CaM ) , to counter host defenses . However , although CaM is one of the first identified cellular suppressors of RNA silencing , the mechanism of PTGS suppression is still poorly understood . This study demonstrates that CaM interacts with and degrades Suppressor of Gene Silencing 3 ( SGS3 ) in Nicotiana benthamiana . We found that domains essential for the interaction between NbSGS3 and NbCaM are also required for the subcellular localization of NbSGS3 and for NbCaM suppressor activity . Moreover , NbCaM mediated NbSGS3 protein degradation can be blocked using the autophagy inhibitors 3-methyladenine and E64d , and by knock-down of key autophagy-related genes within the phosphatidylinositol 3-kinase ( PI3K ) complex . Silencing of the PI3K complex also inhibited geminivirus infection , which is consistent with autophagy playing an important role in RNA silencing suppression pathway and geminivirus infection . | [
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"... | 2017 | A calmodulin-like protein suppresses RNA silencing and promotes geminivirus infection by degrading SGS3 via the autophagy pathway in Nicotiana benthamiana |
Advances in large-scale analysis of human genomic variability provide unprecedented opportunities to study the genetic basis of susceptibility to infectious agents . We report here the use of an in vitro system for the identification of a locus on HSA8q24 . 3 associated with cellular susceptibility to HIV-1 . This locus was mapped through quantitative linkage analysis using cell lines from multigeneration families , validated in vitro , and followed up by two independent association studies in HIV-positive individuals . Single nucleotide polymorphism rs2572886 , which is associated with cellular susceptibility to HIV-1 in lymphoblastoid B cells and in primary T cells , was also associated with accelerated disease progression in one of two cohorts of HIV-1–infected patients . Biological analysis suggests a role of the rs2572886 region in the regulation of the LY6 family of glycosyl-phosphatidyl-inositol ( GPI ) –anchored proteins . Genetic analysis of in vitro cellular phenotypes provides an attractive approach for the discovery of susceptibility loci to infectious agents .
Some individuals do not become infected to the HIV-1 virus despite repeated exposures , and among those that do , there is marked variation in the clinical course and progression to AIDS [1] . Although a number of host genetic determinants of susceptibility to HIV-1 have been identified through the analysis of candidate genes—most notably CCR5 Δ32 and HLA alleles—only a fraction of the observed phenotypic variation can be explained by variation at these loci [2 , 3] . Thus , there is a considerable interest in applying unbiased methods such as whole-genome analysis for the identification of novel susceptibility loci to human pathogens [1] . This hunt is , however , plagued by numerous confounding factors such as the lack of ascertainment of informative patient cohorts and difficulties to control for the variability of the infectious agent . Whole-genome mapping for viral susceptibility has been reported in mice for the murine adenovirus type 1 [4] , and in mosquitoes for the dengue-2 virus [5] . Recently , the first genomewide association analysis for determinants of host control of HIV-1 in humans has been completed [6] . Whole-genome scans can also be performed through the analysis of family data using linkage analysis , an approach widely used to map monogenic disorders [7 , 8] . The need for family-based data has limited the use of this approach in the HIV-1 field because of the rarity , beyond instances of vertical transmission , of multi-case family infections . Studies of host genetic susceptibility to HIV-1 are also confounded by differences in virulence of the infecting viral strain [1] . To circumvent these limitations , we established an in vitro system to address the genetic control of cellular susceptibility to HIV-1 using cell lines from multi-generation families [9 , 10] . We used families from the Centre d'Etude du Polymorphisme Humain ( CEPH ) resource ( up to four grandparents and an average of eight children per family ) , consisting of Epstein-Barr virus ( EBV ) –immortalized lymphoblastoid B cell lines ( LCL ) . CEPH LCLs have been extensively genotyped , and the data are publicly available ( http://snpdata . cshl . edu/population_studies/linkage_maps// ) . CEPH LCLs were previously used to identify genomic loci influencing sodium–lithium counter transport [11] , natural variation in gene expression [12–15] , transcriptional response to ionizing radiation [16] , susceptibility to chemotherapy [17] , and the relative impact of nucleotide and copy number variation on gene expression [18 , 19] . We hypothesized that CEPH LCLs could allow genome-wide investigation of interindividual variation of cellular susceptibility to infection with an isogenic virus , under standardized conditions and a controlled environment .
We designed the study to progress through consecutive steps including: ( i ) the identification by linkage and association of candidate markers associated with in vitro cellular susceptibility to an HIV-1-based vector , ( ii ) in vivo validation of candidate polymorphisms in humans infected with HIV , ( iii ) investigation of potential biological mechanisms ( Figure 1 ) . Since B cells are not a natural target of HIV-1 , we established the conditions for efficient transduction of lymphoblasts with a VSV . G ( vesicular stomatitis virus G protein ) -pseudotyped HIV-1–based vector ( HIV . GFP ) . We first assessed to what extent immortalized B cells reflect the behavior of CD4+ T cells by transducing purified CD4+ T cells and EBV-immortalized B cells , from the same 11 Caucasian healthy blood donors , with the same HIV . GFP . We used the green fluorescent protein ( GFP ) transgene expression as a reporter for permissiveness to lentiviral infection . We observed a significant correlation ( Pearson r2 = 0 . 56 , p = 0 . 007 ) between the level of transduction of CD4+ T cells and B lymphoblastoid cells for the same individuals ( Figure S1 ) . Thus , we hypothesized that transduction of B cells can capture a significant proportion of interindividual variation of post-entry events in the HIV-1 life cycle ( reverse transcription , integration , transcription , and translation ) . Additional validation of the assay established the intra- and interday reproducibility of the transduction phenotype in CEPH LCLs , and ruled out an influence of potential confounders such as EBV copies per cell and the level of expression of the EBV-transforming protein LMP1 ( unpublished data ) . To determine whether variation in cellular susceptibility to the HIV . GFP virus has a genetic component we estimated heritability ( h2 , i . e . , the proportion of variance attributable to additive genetic factors ) in five CEPH pedigrees ( 76 individuals ) . In parallel , we also scored eight additional traits unrelated to HIV susceptibility ( EBV copy number , EBV LMP1 oncogene CD11a , CD19 , CD21 , CD23 , CD39 , CD54 ) . We observed a significant heritability of the HIV susceptibility trait ( h2 = 0 . 54 , p = 1 . 6 ×10−6 ) , as well as for most of the other traits , with h2 values in the same range as those reported for gene expression variation traits [20] ( Figure S2 ) . In view of these significant heritability results , we extended the analyses to 15 CEPH pedigrees ( 198 individuals ) for the lentiviral cellular permissiveness trait ( Figure S2 ) , and we selected the expression of the endogenous cell surface marker CD39 ( EBV receptor ) , and of the EBV-encoded LMP1 protein as additional study phenotypes . To identify genomic loci that contribute to the variation in cellular permissiveness to HIV . GFP , we performed a quantitative genome-wide linkage analysis using a panel of 2 , 600 SNP markers with an effective resolution of 3 . 9 cM . Calculations were performed using the variance components analysis option from Merlin [21] . A region on HSA8q24 ( marker rs1398296 ) showed the highest multipoint linkage score ( logarithm of the odds [LOD] = 2 . 89 , p = 1 . 3 × 10−04; Figure 2A ) . To determine the significance of this finding , we performed 500 simulations in which genotypes were randomized but the phenotype was kept constant , so as to preserve the heritability of the trait , the marker density , and the missing data patterns [22] . The distribution of maximum LOD scores of the simulations revealed that the observed HIV . GFP linkage peak is significant on a genome-wide basis at the 95% significance level ( Figure 2A ) . In order to independently confirm and fine-map the linkage analysis result , we assayed LCLs from 56 unrelated CEPH individuals that have been genotyped at a high density in the frame of the HapMap project [23] . The association analysis was performed using 521 tag SNPs in a 3-Mb region centered on the initial linkage assignment . A single SNP , rs2572886G>A , was strongly associated with HIV . GFP permissiveness ( p = 1 . 8 × 10−5 ) , and statistical significance was maintained after Bonferroni correction for multiple testing and permutation analysis ( n = 10 , 000 ) ( Figure 2B ) . Allele A of marker rs2572886 is associated with an average 1 . 4-fold increase in susceptibility to the HIV . GFP in LCLs from unrelated individuals , p = 0 . 001 ( Figure 2C ) . Similar steps were taken for the secondary study phenotypes unrelated to lentiviral cellular susceptibility , which led to the precise identification ( by linkage and followed by association ) of a region involved in cis-regulation of CD39 expression ( Figure S2 ) . In contrast , no locus was identified affecting LMP1 expression , suggesting a more complex control of this trait by multiple genes . Because observations were all made on B cells , we next assessed the potential role of rs2572886 as a susceptibility factor for HIV-1 infection in CD4+ T cells . We genotyped the SNP in a collection of purified CD4+ T cells obtained from 128 Caucasian healthy blood donors . CD4+ T cells were infected with a replicating HIV-1 , and permissiveness was assessed by p24 antigen production [3] . A significant association was again obtained for SNP rs2572886 and cellular susceptibility to HIV-1 on this independent sample ( p = 0 . 019 ) using a biological system that more closely resembles the in vivo situation . Consistent with the results of transduction of B cells with a HIV-1–based vector , in CD4+ T cells , the allele A of marker rs2572886 is associated with a 1 . 6-fold increase in susceptibility to infectious HIV-1 virus than CD4+ T cells of noncarriers , as assessed in a 7-d replication kinetics analysis ( Figure 2D ) . The size effect associated with rs2572886 in vitro is comparable to that identified for other genetic variants influencing the HIV life cycle [3] . Since the previous results were obtained from in vitro assays , we set out to assess the potential association of rs2572886 with disease progression in HIV-1 infected individuals . The rs2572886 SNP has a minor allele frequency of 7% in Caucasians ( Utah CEPH individuals ) , 19% in West Africans ( Yoruba Hapmap sample ) , and 23% in Asians ( Han Chinese and Japanese , HapMap sample ) . We genotyped 805 individuals recruited in the frame of the genetic project of the Swiss HIV Cohort Study ( http://www . shcs . ch ) who provided informed consent . These patients contributed consecutive CD4+ T cell data ( n = 4 , 999 measurements ) and viremia ( n = 1 , 926 measurements ) over an average follow-up period of 7 y in the absence of anti-retroviral drug treatment . The rs2572886A allele was associated with greater viral load , and faster progression of immunosuppression , as defined by the slope of CD4+ T cells depletion over time ( Figure 3A and 3B ) . Individuals homozygous for the minor allele variant ( n = 7 ) exhibited , as a group , a faster disease progression , but no conclusions can be made with such a small sample size . The same trends were also present in the incident cohort of 259 individuals identified within a 1-y interval of seroconversion ( Figure 3C and 3D ) , although the limited numbers precluded significant association . These results are consistent with the in vitro data , since the A allele , which was associated with higher susceptibility of infection in the cellular systems , was associated with greater viral load and faster progression in vivo . As an additional validation step , we genotyped a second independent cohort including 189 individuals with a precise date of seroconversion ( Figure 3E and 3F ) , which was collected in the context of a whole-genome association analysis [6] . No association was detected in this cohort; however , the power to detect association in a sample of this size is estimated to be around 25% . These patients were recruited by eight different cohorts , while the original results were established using Swiss HIV cohort data . When pooling the discovery incident subcohort and the validation cohort , the association of rs2572886 on both the CD4 and viral load did not reach significance despite the increased number of samples to 448 . However , the combined sample is far from homogeneous . Thus this association should be considered as suggestive at this point . . The association results should be discussed in the frame of the recently published genome-wide association analysis of host determinants of viral setpoint [6] . First , the marker identified in the current study , rs2572886 , is neither present nor tagged by the Illumina HumanHap550 BeadChip used in the paper by Fellay et al . [6] . In addition , the design and premises of the genome-wide association and those of the genome scan reported herein are different: ( i ) the manuscript by Fellay et al . led to the identification of acquired/innate immunity loci ( in major histocompatibility complex [MHC] ) that cannot be captured in a cellular assay that investigates the viral life cycle; ( ii ) the study design in the paper by Fellay was powered to detect only very strong and sufficiently common genetic determinants; ( iii ) the standardized infection conditions and the study endpoint ( expression of a reporter ) that were used in the current study are very different from the conditions encountered in a population of HIV-infected individuals . It is through the nature of these profound study design differences that we aimed at generating complementary information to that provided by the genome-wide association analyses . To provide a reference parameter that would allow comparison with genetic variants identified in other studies , we estimated the proportion of variation explained by rs2572886 and compared it to the contribution of CCR5 Δ32 in the same study population . Including CCR5 Δ32 into the model increased the proportion of variation explained by 1 . 9% for the CD4 cell count and 0 . 4% for the viral load . For rs2572886A , the estimates were 0 . 8% and 1% , respectively . For comparison , age at infection contributed to an increase in the proportion of variation explained of 1 . 4% for the CD4 cell count and 0 . 05% for the viral load , whereas the increase was 3% and 3 . 1% , respectively , for gender . These values are comparable to estimates indicated in the literature for various genetic variants influencing HIV pathogenesis [24] , although direct comparisons are difficult due to different study designs . In contrast , the proportion of variation explained by rs2572886 or CCR5 Δ32 is considerable smaller than that for the genetic determinants reported in the study by Fellay et al . , reflecting the fact that this genome-wide association study was powered to detect strong genetic effects . Thus , HCP5 and HLA-C variants explained 9 . 6% and 6 . 5% of the total variation in viral load , respectively , and an SNP near the RNF39 and ZNRD1 genes explained 5 . 8% of the total variation in disease progression [6] . The rs2572886 SNP is located in a nonconserved intergenic region on the telomeric end of Chromosome 8q ( Figure S4 ) . It is flanked on both sides by genes of the LY6/uPAR family ( Figure S3 ) . The LY6 genes are characterized by conserved cysteine-rich domains with specific disulfide bonding patterns but with little homology ( 20%–30% amino acid conservation among family members ) ; members are either glycosyl-phosphatidyl-inositol ( GPI ) –anchored cell-surface receptors or secreted cytotoxins . Eight genes are located at 8q24 . 3: LY6K , SLURP1 , LYPD2 , LYNX1 , LY6D , GML , LY6E , and LY6H . The functions of the encoded proteins are diverse but not well understood [25] . None has been associated with HIV-1 in the past , although the LY6H gene was reported to be up-regulated upon HIV infection [26] . A related protein of the LY6/uPAR family , the urokinase-type plasminogen activator receptor , coded by a gene in Chromosome 19 , has been reported up-regulated in HIV-infected individuals , and proposed to participate in the innate immunity to HIV-1 through an interferon ( IFN ) -like mechanism [27 , 28] . The SNP rs2572886 is located in a recombination hot spot between two linkage disequilibrium blocks . We resequenced the surrounding region ( ∼ 13 kb ) in 30 chromosomes to identify additional SNPs in linkage disequilibrium with rs2572886 that might point toward a biological function . Although two closely positioned SNPs—rs12546765 and rs12546801—were associated with rs2572886 in this limited resequencing dataset , they are not found in linkage disequilibrium in HapMap ( pairwise r2 = 0 . 03 ) . The region ( ∼1 kb ) where rs2572886 is located is only present once in the human genome . We downloaded the homologous region of chimpanzee and Rhesus macaque and sequenced it in seven additional primates ( bonobo , gorilla , orang-utan , nomascus gibbon , siamang gibbon , baboon , and African green monkey ) . rs2572886G>A was particularly variable among primates , with “G” representing the ancestral nucleotide in Old World monkeys , “A” the ancestral residue in hominoids , and “T” in gibbons . To identify candidate genes that could be functionally related to the rs2572886 SNP , we performed quantitative 3C ( chromatin conformation capture ) [29] , with the goal of detecting potential chromatin interactions between the SNP region and neighboring genes . We tested 11 regions by Taqman real-time PCR , spanning a distance of 190 kb surrounding the SNP . We focused primarily on the upstream areas ( promoters ) of genes in the locus . Results from cross-linked cells were compared to randomly ligated BAC DNA from the same region to correct for interassay differences and potential ligation biases . As expected , we observed a high level of enrichment with a region located 3 . 1 kb from the SNP ( positive control ) due to random chromatin interactions that have been reported to occur between regions separated by less than 5 kb [30] . The trend for enrichment rapidly decreased with increasing distance . Interestingly , we detected higher than background peaks of enrichment on the upstream areas of two genes—LY6D and LYPD2 ( Figure 4 ) —suggesting that these are good candidates for functional interaction with the associated SNP . There are no apparent interactions between the SNP and the nearby GML promoter , despite its relative proximity ( 12 kb ) in comparison to the LY6D ( 35 kb ) and LYPD2 ( 70 kb ) genes . We prioritized the following proteins for additional biological assessment: LY6D and LYPD2 on the basis of chromatin conformation capture analysis , SLURP1 based on its unique status of secreted protein , and GML because of the proximity to the genetic marker . First , we overexpressed each of the four proteins from several vector backgrounds in 293T and HeLa cells to assess whether this would influence transduction by HIV . GFP . No significant changes in cellular infectivity were detected upon overexpression in these cell lines ( Table S1 ) . In general , all eight genes of the LY6/uPAR family show detectable , but very low levels of expression as assessed by quantitative RT-PCR ( unpublished ) ; this precludes gene expression variation analysis to determine whether the genotype at rs2572886 correlates with expression levels of nearby genes . LY6D and LYPD2 , which showed relatively higher expression levels , were silenced in HeLa cells by small interfering RNA ( siRNA ) . Silencing with three different siRNA was successful for LY6D and suboptimal for LY6PD2 . After transduction with HIV . GFP , we observed minor modifications in rates of cellular infection ( Table S1 ) . These findings are interesting , but given the cell type used and the harsh treatment of the cells , they are not conclusive enough to make a functional link for these genes . Overall , the biological basis for a role the LY6/uPAR family of proteins in HIV-1 cellular susceptibility remains elusive after this first line of biological screening . Additional analyses will be required to convincingly demonstrate a role for these proteins in the HIV life cycle . In summary , by using a multi-step procedure involving a whole-genome linkage scan followed by association studies , we identified a locus on HSA8q24 that influences cellular susceptibility to HIV-1 , and possibly progression of HIV-1 infection in vivo . Although the initial findings were based on transduction of transformed B lymphoblastoid cells with a HIV-1–based vector , subsequent experiments first on primary CD4+ T cells infected with replicating HIV , and second on a cohort of untreated HIV patients , supported the initial observations of association . In addition , although quantitative 3C data suggest a possible participation of genes of the LY6/uPAR family , further work is required to decipher the biological mechanism underlying this association .
Members of the LY6/uPAR family—LY6D ( GenBank NM_003695 ) , LYPD2 ( NM_205545 ) , GML ( NM_002066 , SC303114; OriGene ) , Lynx1c ( NM_177457 ) , Slurp1 ( NM_020427 ) , and Slurp2 ( NM_177458 ) —were amplified by RT-PCR from RNA extracted from human cell lines ( HeLa or 293T ) , and cloned into pCI-neo . LY6D and LYPD2 were tagged C-terminally with an HA tag . 293T cells were cultivated in Dulbecco's modified Eagle Medium ( DMEM; Invitrogen ) supplemented with 10% heat-inactivated fetal bovine serum ( FBS ) and 50 μg/ml gentamycin . 293T cells ( 3 × 106 cells ) were cotransfected with 20 μg total of DNA ( empty pCI vector + increasing amounts of pCI vector containing the gene of interest ) using the calcium phosphate technique . Twelve hours post-transfection , cells were washed and 300 , 000 cells were seeded in six-well plates and incubated further for 36 h to allow the expression of the gene of interest before HIV-based vector infection . EBV-transformed B cell lines were obtained from the CEPH collection through the Coriell Institute for Medical Research ( http://locus . umdnj . edu/nigms/ceph/ceph . html ) . Cells were cultivated in RPMI 1640/Glutamax-I medium ( Invitrogen ) supplemented with 15% fetal calf serum ( FCS , Inotech ) . They were maintained by replacing half medium twice a week . Pedigrees studied were numbers 102 , 884 , 1328 , 1331 , 1332 , 1333 , 1334 , 1340 , 1341 , 1345 , 1346 , 1347 , 1362 , 1408 , and 13292 . Cells from 11 white healthy blood donors were used to isolate CD4+ T cells by using anti-CD4 magnetic beads ( Miltenyi Biotech ) . Cells were cultured in RPMI1640/Glutamax-I medium supplemented with 20% FCS , 20 U/ml human interleukin-2 ( IL-2 , Roche ) and 50 μg/ml gentamicin ( Invitrogen ) following stimulation with phytohemagglutinin ( PHA ) at 2 mg/ml for 2 d [31] . The CD4-negative cell fraction was exposed to EBV containing supernatant from a B95–8 cell line according to current protocols [32] . To produce HIV-based vector particles ( HIV . GFP ) , 293T cells ( 3 × 106 cells ) were cotransfected with four plasmids using the calcium phosphate method . Plasmids encoded the VSV-G pantropic envelope ( pMD . G ) , the Gag and Pol proteins ( pCMVΔR8 . 92 ) , Rev ( pRSV-Rev ) , and the fourth plasmid encoded the HIV vector segment carrying GFP as the reporter transgene under the control of the CMV promoter ( pWPTS-GFP ) ( kind gifts from D . Trono , EPFL , Lausanne , Switzerland; see http://rd . plos . org/pbio . 0060032 . 1 for vector details ) . Forty-eight hours after transfection , the supernatant was collected , centrifuged to pellet cellular debris and filtered through 0 . 45-μm filters . Viral particles were concentrated by centrifugation through a 100-kDa cut-off membrane ( Centricon Plus-70; Millipore AG ) . Transduction of CEPH cells and of the B cells of healthy blood donors ( 0 . 5 × 104 cells in 96 wells ) was performed by spinoculation with HIV-based particles for 3 h at 1500g and 22 °C . After 72 h , cells were harvested and expression of GFP protein was monitored by fluorescence activated cell sorting ( FACS ) analysis with mock transduced cells as control . This was performed twice in triplicate at 1-wk intervals . Similarly , transfected 293T cells ( in six-well plates ) were infected with HIV-based particles ( 25 ng p24 equivalent ) in the presence of 10 μg/ml DEAE-dextran in 1 ml D-10 for 5 h . Culture medium was replaced and cells were incubated for 24 h before FACS analysis of GFP expression . Typically , 20%–30% of GFP+ cells were obtained for controls . Healthy blood donors' CD4+ T cells ( 106 cells ) were infected with NL4-3BaL virus ( 1 , 000 pg of p24 antigen ) in a 1-ml final volume for 2 h at 37 °C in 5% CO2 . Cells were washed and cultured for 7 d . Virus-containing supernatant was harvested , and p24 antigen production was monitored by an enzyme-linked immunosorbent assay ( ELISA ) ( Abbott ) . For cell surface molecule staining , 105 CEPH cells were washed , resuspended in PBS/0 . 5% BSA ( Sigma ) and incubated with primary monoclonal antibodies ( mAbs ) or isotypes for 15 min at room temperature ( RT ) . Primary mAbs were : anti-CD11a ( Dako , MHM24 ) , -CD19 ( Dako , HD37 ) , -CD21 ( Dako , 1F8 ) , -CD23 ( Dako , MHM6 ) , -CD39 ( Serotec , A1 ) , -CD54 ( Dako , 6 . 5B5 ) , and the negative control was mouse IgG1FITC ( Dako , X0927 ) . All mAbs were used at 1/50 , except CD19 used at 1/20 . For intracellular staining , CEPH cells were washed and resuspended in cytofix/cytoperm solution ( Becton Dickinson ) for 20 min at 4 °C . After two washes with permwash , cells were resuspended in permwash with primary anti-LMP1 ( 1/50 , S12 , a gift from S . Rothenberger ) or negative control antibody mouse IgG2a ( 1/50 , Dako ) , for 15 min , at RT . After washes , cells were incubated in permwash with secondary anti-mouse PE ( 1/30 , Dako ) . After wash , cells were fixed ( CellFix , Becton Dickinson ) and analyzed using a FACSCalibur system for 10 , 000 events . Positive events were defined as a fluorescence level superior to that of isotypic control . Determination of EBV copy number was carried out by real-time PCR by using specific probes as described [33] . Heritability calculations ( h2 ) were performed using the “polygenicscreen” command from the SOLAR software [34] . SNP genotyping data , consisting of 2 , 688 autosomal SNPs were downloaded from the SNP Consortium database ( http://snpdata . cshl . edu/population_studies/linkage_maps/ ) [35] . Multipoint linkage with the SNP map was performed using Merlin [36] with the –VC option , after Mendelian inconsistencies ( PEDCHECK ) [37] and unlikely genotypes ( PEDWIPE ) [38] were removed . To calculate the empirical significance of the linkage results , we performed 500 simulations for each quantitative trait using the –simulate command from Merlin with different seed numbers . We extracted the highest result from each simulation to build significance distributions . All simulations were performed using a cluster of 32 HP/Intel Itanium 2 based servers at the Vital-IT Center ( http://www . vital-it . ch/ ) . Association analysis of quantitative phenotypes ( % of GFP-positive cells and / mean fluorescence intensity ( MFI ) of CD39 ) , and corrections for multiple testing were performed using the PLINK software ( http://pngu . mgh . harvard . edu/~purcell/plink/anal . shtml ) . Genotypes were downloaded from the HapMap project URL ( http://www . hapmap . org/cgi-perl/gbrowse/gbrowse/hapmap/ ) , HapMap public release number 19 . Data from both incident ( patients identified during primary infection or who have had a negative and positive test for HIV infection within a narrow time interval , 1 y in this study , in which case the date of infection is estimated as the mid-point ) , as well as data from prevalent cases ( i . e . , individuals already HIV-seropositive by the time they entered the study , unknown date of infection ) were analysed longitudinally by modeling the CD4 T cell count and HIV-1 RNA marker's trajectories over time for the different genotype groups . The analysis was conducted using population-averaged marginal modeling [39] , because the focus of the study was to investigate the effect of specific genetic factors on disease progression at the population level . In a marginal model , the mean regression function is modeled independently from the variance–covariances matrix . We used fractional polynomials to assess the best-fitting functional form . The viral load ( log scale ) and the CD4 ( square root scale ) trajectories post seroconversion were linear and appeared stationary . Therefore , linear functions of time , along with interactions with polymorphisms and covariables ( age at infection and gender ) were considered . The impact of genotype on slope and intercept was assessed using Wald test , and the proportion of explained variation was assessed [40] . A multivariate distribution was fitted to the data by score-like methods ( generalized estimating equations ) [41] . The correlation structure was assumed to be well represented by an autoregressive process of order 1 . To limit the impact of frailty selection , only the data for the first eight years since seroconversion were considered . The analysis was repeated considering , in turn , only the incident , prevalent , and both cohorts . Subanalyses were also performed considering the Caucasian group only . For the prevalent cases , an estimate of the unknown date of infection was obtained using the markers data and defining for each patient an infection window based on his or her last negative and first positive available HIV tests . The date of infection was then imputed using a methodology that extends published methods [42 , 43] to accommodate multiple marker measurements per individual ( P . Taffe and M . May , unpulished data , and [44] . A second incident cohort , recruiting individuals from various European countries , was used to validate results obtained from the analysis of the incident cohort recruited within the Swiss HIV Cohort study . Statistical analyses were conducted using SAS version 9 . 1 for Windows , as well as STATA 9 . 2 . The region ( ∼1 kb ) around the candidate marker was resequenced by using forward primer SG2000 ( 5′-AGTTCATACCCCTTTGCCAGGTTG ) and reverse primer SG2001 ( 5′-GAAGCCTTACCTGCTTCCTGCC ) , and forward primer SG1829 ( 5′-TTCCCTGAGCTTGCAGGACTC ) and reverse primer SG1853 ( 5′-CTCTACACACCTACCTTGCTGGGA ) to generate overlapping PCR products . Sequences have been submitted to GeneBank for bonobo ( EU340888 , Pan paniscus ) , gorilla ( EU340889 , Gorilla gorilla ) , bornean orang-utan ( EU340890 , Pongo pygmaeus ) , nomascus ( EU340891 , Hylobates leucogenys ) , siamang ( EU340892 , Hylobates syndactylus ) , baboon ( EU340893 Papio hamadryas ) , and African green monkey ( EU340894 , Cercopithecus [chlorocebus] aethiops ) . Approximately 107 stimulated expanded primary CD4+ T cells [31] were crosslinked in their media for 10 min at RT with 1% formaldehyde ( v/v ) . Crosslinking was quenched with 125 mM glycine prior to two successive washes with 1xPBS . Pelleted cells were resuspended into 5-ml ice-cold lysis buffer ( 10mM Tris HCl , pH 8 . 0 , 10 mM NaCl , 0 . 2% ( v/v ) NP-40 ) complemented with protease inhibitors ( Complete , Roche ) and 0 . 5 mM PMSF . Lysis of the cells was allowed to proceed for 10 min on ice with mild shaking . Nuclei were recovered by centrifugation ( 600g for 5 min at 4 °C ) and resuspended into 500-μl 1 . 2xDpnII restriction buffer ( NEB ) . Nuclei were lysed with 0 . 3% ( v/v ) SDS for 60 min at 37 °C . SDS was sequestered with 2% ( v/v ) Triton X-100 for another 60 min at 37 °C . Chromatin was subsequently restricted overnight at 37 °C with 500 U DpnII ( NEB ) in a final reaction volume of 600 μl . After heat inactivation of the restriction enzyme ( 10 min at 65 °C ) , chromatin was dialyzed ( Slide-A-Lyzer , Pierce ) for 1 h against 1 . 5 l of water at RT and transferred into 7 ml ligation reaction mix ( 50 mM Tris HCl , pH 8 . 0 , 10 mM MgCl2 , 0 . 5mg/ml BSA , 10mM β-mercapto-ethanol , 0 . 5 mM ATP and 400 U T4 DNA ligase ( NEB ) . The ligation reaction was performed for 4 h at 16 °C followed by another 30 min at RT . Crosslinking was heat-reversed and proteins were degraded ( 300 μg proteinase K ) overnight at 65 °C in a hybridization oven . DNA was purified by phenol/chloroform/isoamyl alcohol [25:24:1 ( v/v ) ] extraction , precipitated with isopropanol , and washed with ethanol 70% . DNA was subsequently resuspended with 200 μl 1xTE pH 8 . 0 and treated with 50 μg RNaseA for 30 min at 37 °C . Finally , DNA was extracted with 1 volume phenol/chloroform/isoamyl alcohol [25:24:1 ( v/v ) ] , ethanol precipitated , and resuspended into 100 μl 1xTE pH 8 . 0 . Cross-linking was independently performed on four CD4+ lines derived from different individuals , two of whom ( 2 and 4 ) were heterozygous for rs2572886 . For quantitative Taqman PCR , we designed 11 assays comprising the PCR primers and a dual-labeled probe sitting at the predicted DpnII junction between the target and bait regions ( primer and probe sequences are available upon request ) . Reactions were set up using a Biomek 2000 robot ( Beckman ) , in a 10-μl volume in 384-well plates . Three replicates per assay per sample were performed . PCRs were run in an ABI 7900 Sequence Detection System ( Applied Biosystems ) with the following conditions: 50 °C for 2 min , 95 °C for 10min , and 50 cycles of 95 °C 15 s/60 °C for 1 min . Each reaction contained 300 nM of each primer and 250 nM of probe . For the 3C samples , approximately 200 ng of DNA was used per well , and for the BAC ( digested – randomly ligated ) samples , 10 ng of DNA was used . Normalization for each assay was performed using the values obtained from BAC experiment ( all assays are expected to give the same result , given that the naked BAC was fully digested and re-ligated , and all ligation combinations are expected to be present equimolarly ) . Enrichment was calculated with respect to the most centromeric probes , which showed very low levels of interaction . Note in Press: Recently , Brass et al [45] identified through a siRNA screen over 250 HIV-dependency factors . Among these there were three members of the LY6/uPAR family ( GML , LY6D , and LYPD4 ) . This new evidence provides independent support for a biological role of the LY6/uPAR family in HIV-1 pathogenesis . | Individuals differ in their susceptibility to the HIV-1 virus , and the determinants of susceptibility are encoded in the human genome . Genetic variants influencing this trait have been identified by investigating candidate genes thought likely to be involved in HIV-1 pathogenesis or by whole-genome association studies , which type more than 500 , 000 genetic variants per individual ( genome-wide association studies ) to see which ones associate with susceptibility . We have addressed the issue of identification of new genetic variants influencing susceptibility to HIV-1 by a novel strategy based on the in vitro infection of cells . For this , immortalized B lymphocytes from 15 families ( 198 cell lines ) were infected by a HIV-based vector . Differences in cellular susceptibility to infection—a genetic trait—could be mapped to a precise region on Chromosome 8 , suggesting a role of the LY6 family of GPI-anchored proteins in HIV-1 infection . Genetic analysis of in vitro standardized cellular phenotypes provides a new approach to the discovery of the basis of genetic susceptibility to infectious agents . | [
"Abstract",
"Introduction",
"Results/Discussion",
"Materials",
"and",
"Methods"
] | [
"infectious",
"diseases",
"genetics",
"and",
"genomics"
] | 2008 | In Vitro Whole-Genome Analysis Identifies a Susceptibility Locus for HIV-1 |
With only ∼3 , 000 wild individuals surviving restricted to just 7% of their historical range , tigers are now a globally threatened species . Therefore , conservation efforts must prioritize regions that harbor more tigers , as well try to capture most of the remaining genetic variation and habitat diversity . Only such prioritization based on demographic , genetic , and ecological considerations can ensure species recovery and retention of evolutionary flexibility in the face of ongoing global changes . Although scientific understanding of ecological and demographic aspects of extant wild tiger populations has improved recently , little is known about their genetic composition and variability . We sampled 73 individual tigers from 28 reserves spread across a diversity of habitats in the Indian subcontinent to obtain 1 , 263 bp of mitochondrial DNA and 10 microsatellite loci . Our analyses reveals that Indian tigers retain more than half of the extant genetic diversity in the species . Coalescent simulations attribute this high genetic diversity to a historically large population size of about 58 , 200 tigers for peninsular India south of the Gangetic plains . Furthermore , our analyses indicate a precipitous , possibly human-induced population crash ∼200 years ago in India , which is in concordance with historical records . Our results suggest that only 1 . 7% ( with an upper limit of 13% and a lower limit of 0 . 2% ) of tiger numbers in historical times remain now . In the global conservation context our results suggest that , based on genetic , demographic , and ecological considerations , the Indian subcontinent holds the key to global survival and recovery of wild tigers .
As top predators , large carnivores strongly shape ecological interactions in biological communities , thus playing a critical role in maintaining their structure and diversity [1] , [2] . However , during historical times , increased anthropogenic impacts have driven range collapses and population declines in many large carnivores , thereby engendering significant efforts at species recovery . These efforts have typically aimed at increasing local population sizes and enhancing connectivity between populations using available demographic , ecological and genetic information for the species [3]–[5] . Integration of such datasets is critical for prioritizing conservation efforts . The tiger ( Panthera tigris ) typifies large carnivores severely threatened by historical anthropogenic impacts . Wild tigers historically occurred across 70 degrees of latitude and 100 degrees of longitude , spanning 30 present-day nations ranging from Armenia to Indonesia , the Russian Far East to the Southern tip of India [6] , [7] . This range encompassed a variety of habitats , including taiga and boreal forests , tropical evergreen , moist and dry deciduous forests , alluvial grasslands and mangroves . Historical times have seen a dramatic range collapse of 93% for wild tigers due to habitat loss , prey depletion and direct hunting [7] . Current global estimates of wild tiger populations range from 3000–3500 individuals [7] , [8] . The Indian subcontinent is estimated to harbor about 2000 tigers [9] , or about 60% of the global wild population , although it retains only an estimated 8–25% of remaining global habitat [7] , [9] , [10] . These data emphasize the importance of Indian tigers for future species recovery from a demographic perspective . Ecology and population dynamics of tigers in the Indian subcontinent has been reasonably well studied [11] , [12] , as has been their spatial distribution and habitat diversity [9] , [10] . However , the genetic make up and diversity of Indian wild tiger populations have not been examined in a global context . Limited phylogeographic studies [13] , [14] reveal only moderate levels of variation within Indian tigers , in spite of more than half of the global population and the most varied habitat conditions occurring in this region . In order to adequately assess genetic variability of extant Indian tigers , it is critical to obtain as many genetic samples as possible from the varied , disjunct and fragmented tiger habitats . However , because wild tigers are endangered , elusive and difficult to capture , it is difficult to invasively collect sufficient samples such as blood or tissue . We overcome this problem by using genetic samples non-invasively collected from tiger scats to assess genetic variation , phylogeography and demographic history of tigers in the Indian subcontinent . In this paper we investigate ( 1 ) the proportion of global tiger genetic variation harboured by tigers in the Indian subcontinent and ( 2 ) the demographic history of tigers in the Indian subcontinent , with a synthesis based on historical population sizes and recent human impacts . We address these questions using 1 . 26 kb of mitochondrial DNA and 10 microsatellite loci surveyed in 73 individual tigers from 28 different populations , and compare our results to published data from 68 tigers outside the Indian subcontinent .
Our sampling strategy concentrated on tiger populations living in varied habitats throughout the Indian subcontinent . Using 71 ( Table S1 ) non-invasively collected fecal samples and two tissue samples from across the Indian subcontinent , we investigated genetic variability of Indian tigers using mtDNA and microsatellite loci . Our results reveal that Indian tigers have much higher genetic variation than wild tigers elsewhere . For mitochondrial DNA , 76% of all tiger genetic variability ( 32 out of 42 haplotypes ) is found within the Indian subcontinent ( Figure 1A ) . These results are robust to differences in sample size ( 67 within India versus 57 outside India ) . Re-sampling simulations reveal that if only 57 Indian tigers were sampled , we would expect between 18 and 25 haplotypes , much higher than the observed 10 haplotypes . Similarly , five microsatellite loci reveal higher average number of alleles ( Table 1 ) , allelic size range ( Table 1 ) and heterozygosity ( Table 1 ) in Indian subcontinent tigers compared to tigers from the rest of the world . Additionally , the program STRUCTURE [15] ( based on five loci ) illustrates that Indian tigers retain high allelic richness and varied ancestry ( Figure 1B ) . Thus both markers and several analyses suggest higher genetic variability within the Indian subcontinent compared to any other subspecies , as well as all compared to all tiger subspecies outside the Indian subcontinent ( Figure 1 , Table 1 ) . Viewed alone , this higher genetic variability observed within the Indian subcontinent is concordant with India being the geographic source for tigers . However , fossil evidence suggests that the tiger evolved in southern China [16] . Phylogenetic and phylogeographic data [13] suggest the genetic antiquity of the Indochinese tigers ( very limited samples from South China tigers ) , and that Indian tigers are of relatively recent origin . Coalescent-based two population models ( LAMARC [17]; Indian subcontinent tigers versus Indochinese tigers ) based on both mitochondrial DNA and microsatellite data ( based on five loci ) estimate significantly higher immigration into the Indian subcontinent [MLEmtDNA ( maximum likelihood estimate ) = 185 . 8 ( 44 . 72 , 486 . 63 ) ; MLEmicrosats = 36 . 82 ( 31 . 17 , 40 . 40 ) ] compared to emigration [MLEmtDNA = 0 . 19 ( 0 . 000001 , 59 . 84 ) ; MLEmicrosats = 13 . 77 ( 11 . 31 , 15 . 32 ) ] out of the subcontinent . Although not conclusive , these independent lines of evidence suggest that Indian tigers are not ancestral to the species . The higher genetic diversity of Indian tigers could be explained by higher effective population size , due to ( 1 ) high levels of population differentiation between tiger populations within the subcontinent due to habitat variability and past fragmentation and/or ( 2 ) high historic abundance of tigers in the Indian subcontinent . We investigated the impacts of population differentiation on our results . We divided our samples into those roughly from the North , Central and South of the Indian subcontinent . Our results reveal a strong signature of population structure for mitochondrial DNA ( Table 2 ) , especially between the North and the Central and Southern region . On the other hand , pairwise Fst values ( Table 2 ) for microsatellite data are low . Although the structure plot ( Figure 1B ) reveals varied ancestry , there is no clear partition of ancestry between regions . We estimated historical effective population size for Indian tigers . Our mitochondrial DNA data suggest population expansion within the Indian subcontinent ( Fu's F = −26 . 33 ( p = 0 . 000 ) ; LAMARC: MLE of g = 2859 . 7 ( 2092 . 67 , 5549 . 68 ) , indicating growth ) . In contrast , the microsatellite data from the same populations indicate population decline ( M ratio 0 . 35 ( s . d . 0 . 08 ) , BOTTLENECK [18]: 7 to all of the10 loci with heterozygote excess depending on the mutational model , LAMARC ( based on 10 loci ) : MLE of g = −20 . 87 ( −24 . 29 , −17 . 09 ) , indicating population decline ) . Tests for selective neutrality of the tiger mitochondrial genome revealed evidence for negative selection on the cytochrome b gene ( dN/dS within species = 1 . 9 , between species = 0 . 09 , p = 0 . 00002 ) . Because of negative selection , mitochondrial genetic variation may result in underestimates of historical population size . Given that tigers from Central and Southern India do not reveal strong subdivision ( low and non-significant pairwise Fst's for both mitochondrial and microsatellite DNA ) , we investigate the demographic history of tigers in this region that we refer to as peninsular India ( including the states of Madhya Pradesh , Chattisgarh , Maharastra , Karnataka , Tamil Nadu , Andhra Pradesh and Kerala ) using coalescent simulations [19] , [20] . Models including linear and exponential decline ( Table S5 and Table S6 , Figure S4 and Figure S5 ) revealed that the current effective size is about one tenth of the historical effective size , indicating that the Indian subcontinent has lost about 90% of its tigers ( Figure 2 ) . As these models do not allow us to investigate the absolute historical effective size as well as the timing of decline , we also used the Storz and Beaumont method to explore recent population decline . Results reveal a strong signal of population decline ( 91 . 4% decline , Figure 2 ) , which potentially occurred around 200 years before present . We investigated the sensitivity of our results on demographic history to the number of genetic loci . Coalescent simulations that included 5 wild caught tigers ( data from 13 ) genotyped at 30 microsatellite loci also revealed a very similar extent and timing of demographic decline ( Figure S3 ) . Further , using genetic data from tigers across the Indian subcontinent resulted in similar extent of population decline ( Figure S2 ) . Our sensitivity analyses re-iterate that the extent of demographic decline and its timing are robust to population structure as well as increased genetic data .
An assessment of genetic variation for tigers reveals tigers in the Indian subcontinent retain more than 60% of the genetic variability of the species . In this study , we have taken extreme care to sample Indian tigers in a spatially exhaustive way . However , our results are also conditional on adequate sampling of tiger variation outside the India . Future studies might also include additional sampling of wild tigers outside the Indian subcontinent . Additionally , data from captive tigers of known origin could also be used to investigate discrepancies in genetic variation . Indian subcontinent tigers could retain higher genetic variation not only because they had high historical population size but also because other tiger subspecies declined more severely in the recent past . Single population models in LAMARC for Indochinese tigers using the microsatellite data also exhibit a signature of recent population decline ( MLE of g = −0 . 881825 ( −1 . 29 , −0 . 560142 ) ) , although lower than the estimated decline for Indian tigers . We also quantified the timing and extent of demographic decline , and simulations revealed a relatively recent decline ( 158 years ago , Figure S6 , Figure S7 , and Figure S8 ) of about the same magnitude ( 90% ) as for Central and South Indian tigers . However , the median ancestral effective size for Indochinese tigers was much lower than that of the Indian tigers in central and south India ( 23 , 280 ) . The higher ancestral effective size explains the higher genetic variation among extant Indian tigers inspite of recent , human induced decline . Data from mitochondrial DNA potentially reveal a signal of demographic expansion , while microsatellite data reveal a signal of a recent population decline . The strong population differentiation for mitochondrial DNA ( Table 2 ) could also result in the observed , expansion-like pattern [21] and the resultant high mitochondrial genetic diversity in this part of the species' range . Our genetic data in combination with a series of simulation models suggests that prior to historical human impacts , the genetic effective population size for tigers from peninsular India was between 2 , 964 and 151 , 008 , with a median value of 23 , 280 . Converting this effective population size into a population size suggests that between 7 , 412 and 377 , 520 , with a median of 58 , 202 ( using Ne/N = 0 . 4 [22] , where Ne is the effective population size and N is the census size ) adult wild tigers inhabited peninsular India prior to these human impacts . Given the recent census estimate of around 1 , 000 adult tigers in peninsular India [9] , this corresponds to a median decline of approximately 98% over the last 200 years . Major demographic declines are evidenced by historical hunting records ( based on bounty killings ) during the Colonial rule , which suggest that over 80 , 000 tigers were hunted for bounties between 1875 and 1925 [23] across the Indian subcontinent . These data potentially indicate an even higher historical population size for tigers than do our results . However , the demographic decline we detect is in the face of high potential annual growth rates [12] , suggesting that hunted individuals far exceeded 57 , 000 ( 98% of the ancestral effective size ) , even in peninsular India . Accounting for population growth rates suggests that our genetic results might be in concordance with historical hunting records . Our estimates of the decline are linked to the assumed Ne/N ratio of 0 . 4 [22] . Empirical estimates for mammals suggest a median Ne/N of 0 . 6 [24] while theoretical estimates suggest Ne/N of 0 . 5 [25] . These estimates would reduce the decline to 97 . 4% and 97 . 8% respectively . Alternatively , Ne/N values lower than 0 . 4 would accentuate the decline scenario we propose . It is known that in the last ∼600 years , two major historical events [23] affected tiger populations across the Indian subcontinent: the intrusion and political control of India by Mughal' warriors who were known for their advanced hunting technologies , and subsequently , the establishment of the British Empire , which promoted widespread use of fire-arms , modern technologies and encouraged mass hunting of tigers for bounty and sport . Our results estimate the median timing of decline to 200 years ago , overlapping with the extensive bounty killings , which started around 130 years ago under colonial rule [23] . Historical records indicate that tigers were systematically hunted from Mughal times ( around 500 years ago , [23] ) and the subsequent colonial rule additionally encouraged bounty-hunting ( initially in eastern India ) from about 1777 ( 231 years ago ) [23] . It is possible that tiger population declines started during the Mughal empire and accelerating over the last 150 years during colonial rule . The analytical approaches we use in this paper explore relatively simple scenarios of decline . However , additional historical genetic data from trophy or bounty hunted tiger skins might allow investigate as to whether rates of decline in tiger populations have increased relatively recently . Finally , our estimates of the timing of decline are based on an assumed 5-year generation time for tigers [22] . A higher generation time ( say 6 years ) would result in a younger estimated timing of decline , while a lower generation time would result in an older estimated timing of decline . The differences between the observed patterns of population differentiation between mitochondrial and nuclear markers could be because of the lower effective size for mitochondrial DNA [26] , [27] or due to interactions between mode of inheritance and sex-biased dispersal . Female tigers have smaller home ranges than males , with daughters inheriting the home range of their mothers [28] . This would result in strong population subdivision for maternally inherited mitochondrial DNA . On the other hand , biparentally inherited nuclear ( microsatellite ) data are consistent with expectations for a large carnivore species that exhibits long-range dispersal movements [28] . Discordant patterns for population differentiation between mitochondrial and nuclear DNA are common for mammals with female philopatry and male-biased dispersal [29] . It is interesting that population subdivision between Southern and Central India is not significant for both mitochondrial and nuclear DNA , suggesting dispersal through a wide range of habitat types as well as relatively recent fragmentation of the formerly contiguous tiger habitats in peninsular India . Our results are important for global tiger conservation because they suggest that Indian tiger populations are critical for species recovery . However , because tiger habitats in India are often small , disjunct and fragmented , conservation options are limited . Ecological studies [7] , [10] , [12] have identified a few protected landscapes in India with high tiger densities and potential connectivity . Conservation efforts must prioritize these tiger populations in larger landscapes like the Western Ghats , Central India and the alluvial flood plains in the Himalayan foot hills that support high potential tiger densities , and relatively larger populations . Genetic diversity retains the history of a species [30] , [31] , and is vital for survival and future adaptation to changes [32] . Although it is possible that other tiger populations outside of India harboured increased genetic variation in the past , our results show that currently Indian tiger retain the majority of the species' genetic variation . This suggests subspecies-based conservation criteria are inappropriate . Despite having experienced recent demographic declines , extensive habitat loss , extant Indian wild tigers retain 76% of the mitochondrial diversity and 63% of the species' nuclear genetic diversity and are adapted to a greater diversity of habitats [7] , [12] . They are thus critically important from demographic , evolutionary and ecological perspectives for future survival and recovery of the species . More than a billion people , afflicted by poverty and yet experiencing rapid economic growth live in India . That Indian tigers have managed to retain their genetic diversity in the face of such high anthropogenic pressure provides some hope for species survival in the future .
Samples were opportunistically collected from wild individuals living inside protected areas and national parks spanning all over India . We collected 71 fecal samples and two tissue samples from most of the tiger habitat in India . Tissue samples were collected from poached animals with permissions . All samples were collected in sterile vials and preserved in absolute alcohol until processed . To avoid the effects of inbreeding in our analyses , samples were collected spatially far apart within a protected area ( at least 15 km apart ) . DNA extraction and species identification was performed by methods explained in Mukherjee et al . [33] . Sampling information is provided in supplementary material ( Table S1 ) . We generated mitochondrial DNA data for 54 samples and STR data for 58 samples . In addition to the samples collected in this study , we used genetic data from all tiger subspecies ( Indo-Chinese , Malayan , Sumatran and Siberian , in addition to Indian tigers ) from Luo et al . [13] . All genetic data for tigers outside the Indian subcontinent ( as presented in Figure 1 ) are from Luo et al . [13] . We only considered data from tigers of known wild origin . A total of 57 tiger mitochondrial DNA and 68 STR data have been used for comparison in this study . We designed tiger-specific mitochondrial DNA primers . Polymorphic regions were ascertained using tiger mitochondrial sequences across all subspecies based on Luo et al . [13] ( Figure S1 ) . These primers were then standardized for fecal DNA samples . A total of nine primer sets were designed , and used to amplify1263 bp from Indian tiger fecal samples . Primers sequences are presented in supplementary information ( Table S2 ) . We selected ten felid-specific microsatellite loci based on PCR success rate , amplicon size , number of alleles and the level of observed heterozygosity ( Hobs ) in Indian tigers ( Table S3 ) . All samples were genotyped at this panel of nine dinucleotide and one tetranucleotide microsatellite locus described initially in the domestic cat [34] . The mitochondrial regions were amplified in 10 µl volume reactions , cleaned by Exo-Sap mixture ( NEB ) and sequenced from both ends on an ABI 3100XL capillary sequencer . To monitor possible contamination , PCR blanks were included in all experiments . Amplification for all the microsatellite loci was done using a multiplex approach . A modified multiple tube approach , combined with a quality index approval was used for data quality management to account for the varying quality and quantity of DNA obtained from non-invasive sources . The complete genotyping process was repeated three times for all samples , and only those loci with quality index ≥0 . 75 were included in the analysis [35] . Genetic diversity statistics , population growth indicators ( Fu's F , Tajima's D ) and genetic difference ( Fst ) were calculated using ARLEQUIN 3 . 1 [36] , assuming two populations of tigers ( Indian subspecies and all other subspecies ) . To avoid the effects of related individuals in our analyses , we used STR data from 39 representative samples from all the areas sampled . For intra-population diversity statistics , samples were divided into Northern India ( n = 10 ) , Central India ( n = 11 ) and Southern India ( n = 18 ) . Tests for selective neutrality were performed using DNASP 4 . 0 [37] . A statistical parsimony network based on 1263 bp mtDNA sequences of all the tiger subspecies was created using NETWORK ( Fluxus Technology Ltd . ) . Two-population models were explored to estimate migration rate with the mitochondrial DNA and STR data with coalescent analysis program LAMARC and were based on genetic data from five common microsatellite loci . | Tiger range and numbers have collapsed globally despite substantial conservation efforts . Genetic data quantifying variation from 73 wild tigers in 28 reserves in the Indian subcontinent suggests historically high numbers for tigers , and simulations reveal a signature of a 200-year-old , possibly human-induced decline . Simulations suggest that only 1 . 7% of historical tiger numbers now persist in peninsular Indian . Our data also reveal that tigers of the Indian subcontinent retain most of the species' genetic diversity , besides this region harbouring maximum diversity of tiger habitats . Overall , the Indian subcontinent appears to be a global hotspot holding the key to any future recovery of wild tigers from both an ecological and genetic perspective . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [
"evolutionary",
"biology",
"ecology/population",
"ecology",
"ecology/conservation",
"and",
"restoration",
"ecology",
"genetics",
"and",
"genomics/population",
"genetics"
] | 2009 | Why the Indian Subcontinent Holds the Key to Global Tiger Recovery |
A central challenge in sensory neuroscience involves understanding how neural circuits shape computations across cascaded cell layers . Here we attempt to reconstruct the response properties of experimentally unobserved neurons in the interior of a multilayered neural circuit , using cascaded linear-nonlinear ( LN-LN ) models . We combine non-smooth regularization with proximal consensus algorithms to overcome difficulties in fitting such models that arise from the high dimensionality of their parameter space . We apply this framework to retinal ganglion cell processing , learning LN-LN models of retinal circuitry consisting of thousands of parameters , using 40 minutes of responses to white noise . Our models demonstrate a 53% improvement in predicting ganglion cell spikes over classical linear-nonlinear ( LN ) models . Internal nonlinear subunits of the model match properties of retinal bipolar cells in both receptive field structure and number . Subunits have consistently high thresholds , supressing all but a small fraction of inputs , leading to sparse activity patterns in which only one subunit drives ganglion cell spiking at any time . From the model’s parameters , we predict that the removal of visual redundancies through stimulus decorrelation across space , a central tenet of efficient coding theory , originates primarily from bipolar cell synapses . Furthermore , the composite nonlinear computation performed by retinal circuitry corresponds to a boolean OR function applied to bipolar cell feature detectors . Our methods are statistically and computationally efficient , enabling us to rapidly learn hierarchical non-linear models as well as efficiently compute widely used descriptive statistics such as the spike triggered average ( STA ) and covariance ( STC ) for high dimensional stimuli . This general computational framework may aid in extracting principles of nonlinear hierarchical sensory processing across diverse modalities from limited data .
Computational models of neural responses to sensory stimuli have played a central role in addressing fundamental questions about the nervous system , including how sensory stimuli are encoded and represented , the mechanisms that generate such a neural code , and the theoretical principles governing both the sensory code and underlying mechanisms . These models often begin with a statistical description of the stimuli that precede a neural response such as the spike-triggered average ( STA ) [1 , 2] or covariance ( STC ) [3–8] . These statistical measures characterize to some extent the set of effective stimuli that drive a response , but do not necessarily reveal how these statistical properties relate to cellular mechanisms or neural pathways . Going beyond descriptive statistics , an explicit representation of the neural code can be obtained by building a model to predict neural responses to sensory stimuli . A classic approach involves a single stage of spatiotemporal filtering and a time-independent or static nonlinearity; these models include linear-nonlinear ( LN ) models with single or multiple pathways [1 , 9–11] or generalized linear models ( GLMs ) with spike history feedback [12 , 13] . However , these models do not directly map onto circuit anatomy and function . As a result , the interpretation of such phenomenological models , as well as how they precisely relate to underlying cellular mechanisms , remains unclear . Ideally , one would like to generate more biologically interpretable models of sensory circuits , in which sub-components of the model map in a one-to-one fashion onto cellular components of neurobiological circuits [14] . For example , model components such as spatiotemporal filtering , thresholding , and summation are readily mapped onto photoreceptor or membrane voltage dynamics , synaptic and spiking thresholds , and dendritic pooling , respectively . A critical aspect of sensory circuits is that they operate in a hierarchical fashion in which sensory signals propagate through multiple nonlinear cell layers [15–17] . Fitting models that capture this widespread structure using neural data recorded from one layer of a circuit in response to controlled stimuli raises significant statistical and computational challenges [18–22] . A key issue is the high dimensionality of both stimulus and parameter space , as well as the existence of hidden , unobserved neurons in intermediate cell layers . The high dimensionality of parameter space can necessitate prohibitively large amounts of data and computational time required to accurately fit the model . One approach to address these difficulties is to incorporate prior knowledge about the structure and components of circuits to constrain the model [11 , 21 , 23–25] . Although prior knowledge of the exact network architecture and sequence of nonlinear transformations would greatly constrain the number of possible circuit solutions , such prior knowledge is typically minimal for most neural circuits . In this work , we learn hierarchical nonlinear models from recordings of ganglion cells in the salamander retina , with the goal of building more interpretable models . In particular , we focus on models with two stages of linear-nonlinear processing ( LN-LN models ) , analogous to the specific cell layers the retina . LN-LN models have been previously proposed to describe cascaded nonlinear computation in sensory pathways such as in V1 [11 , 21] and retina [18 , 22 , 23 , 26 , 27] ( we elaborate on differences across these studies and our work below ) . In the retina , it has been proposed that there is a nonlinear transformation between bipolar and ganglion cells , however , building models that capture these nonlinearities has been a challenge due to the issues described above . Here , we find that with appropriate regularization , we are able to learn LN-LN models from recordings of ganglion cells alone that are both more accurate and more interpretable than their LN counterparts . In particular , inferred LN-LN model subunits quantitatively match properties of bipolar cells in the retina . Moreover , although the focus of this paper is on LN-LN models , we demonstrate that the algorithms we use to fit them are also useful in directly learning the STA and STC eigenvectors using very little data . Further analysis of our learned LN-LN models reveals novel insights into retinal function , namely that: transmission between every subunit and ganglion cell pair is well described by a high threshold expansive nonlinearity ( suppressing all but a small fraction of inputs ) , bipolar cell terminals are sparsely active , visual inputs are most decorrelated at the subunit layer , pre-synaptic to ganglion cells , and finally the composite computation performed by the retinal ganglion cell output corresponds to a boolean OR function of bipolar cell feature detectors . Collectively , these results shed light on the nature of hierarchical nonlinear computation in the retina . Our computational framework is general , however , and we hope it will aid in providing insights into hierarchical nonlinear computations across the nervous system . The retina is a classic system for exploring the relationship between quantitative encoding models and measurements of neurobiological circuit properties [28 , 29] . Signals in the retina flow from photoreceptors through populations of horizontal , bipolar , and amacrine cells before reaching the ganglion cell layer . To characterize this complex multilayered circuitry , many studies utilize descriptive statistics such as the spike-triggered average , interpreted as the average feature encoded by a ganglion cell [1–3] . Responses are often then modeled using a linear-nonlinear ( LN ) framework ( schematized in Fig 1A ) . A major reason for the widespread adoption of LN models is their high level of tractability; learning their parameters can be accomplished by solving a simple convex optimization problem [2] , or alternatively , estimated using straightforward reverse correlation analyses [1] . However , LN models have two major drawbacks: it is difficult to map them onto biophysical mechanisms in retinal circuitry , and they do not accurately describe ganglion cell responses across diverse stimuli . Regarding mechanisms , the spatiotemporal linear filter of the LN model is typically interpreted as mapping onto the aggregate sequential mechanisms of phototransduction , signal filtering and transmission through bipolar and amacrine cell pathways , and summation at the ganglion cell , while the nonlinearity is mapped onto the spiking threshold of ganglion cells . Regarding accuracy , while previous studies have found that these simple models can , for some neurons , capture most of the variance of the responses to low-resolution spatiotemporal white noise [9 , 12 , 20] , they do not describe responses to stimuli with more structure such as natural scenes [13 , 30–33] . A likely reason for these drawbacks are the nonlinearities within the retina . There can be strong rectification of signals that occurs pre-synaptic to ganglion cells [15 , 34–36] , breaking the assumption of composite linearity in the pathway from photoreceptors just up to the ganglion cell spiking threshold [17] . Indeed , nonlinear spatial integration within ganglion cell receptive fields was first described in the cat retina [37] in Y-type ganglion cells . A hypothetical model for this computation was proposed as a cascade of two layers of linear-nonlinear operations ( LN-LN ) [26 , 27] . If one keeps the mean luminance constant , avoiding light adaptation in photoreceptors , the first major nonlinearity is thought to lie at the presynaptic terminal of the bipolar to ganglion cell synapse . Ganglion cells pool over multiple bipolar cell inputs , each of which can be approximated as linear-nonlinear components , termed subunits of the ganglion cell . Due to the roughly linear integration [9] that occurs at bipolar cells , we ( computationally ) distill mechanisms in photoreceptors and inhibitory horizontal cells into a single spatiotemporal filter with positive and negative elements that gives rise to bipolar cell signals . The second LN layer corresponds to summation or pooling across multiple subunits at the ganglion cell soma , followed by a spiking threshold . The subunit nonlinearities in these models have been shown to underlie many retinal computations including latency encoding [29] , object motion sensitivity [38] , and sensitivity to fine spatial structure ( such as edges ) in natural scenes [35] . Fig 1 shows a schematic of the LN-LN cascade and its mapping onto retinal anatomy . Functionally , these models with multiple nonlinear pathways both provide a more accurate description of ganglion cell responses and are more amenable to interpretation . Early work on characterizing these multiple pathways motivated the use of the significant eigenvectors of the spike-triggered covariance ( STC ) matrix as the set of features that drives a cell , focusing on low-dimensional full field flicker stimuli [10 , 39] to reduce the amount of data required for accurately estimating these eigenvectors . Significant STC eigenvectors will span the same linear subspace as the true biological filters that make up the pathways feeding onto a ganglion cell [3 , 40–42] . However , the precise relationship between these eigenvectors ( which obey a biologically implausible orthogonality constraint ) and the individual spatiotemporal filtering properties intrinsic to multiple parallel pathways in a neural circuit remains unclear . Instead , we take the approach of directly fitting a hierarchical , nonlinear , neural model , enabling us to jointly learn a set of non-orthogonal , biophysically plausible set of pathway filters , as well as an arbitrary , flexible nonlinearity for each pathway . Much recent and complementary work on fitting such models make simplifying assumptions in order to make model fitting tractable . For example , assuming the subunits are shifted copies of a template results in models with a single convolutional subunit filter [21 , 23 , 24] . However , this obscures individual variability in the spatiotemporal filters of subunits of the same type across visual space , which has been shown to be functionally important in increasing retinal resolution [43] . Another common assumption is that the subunit nonlinearities have a particular form , such as quadratic [11 , 25] or sigmoidal [44] . Fitting multi-layered models with convolutional filters and fixed nonlinearities has also been successfully used to describe retinal responses to natural scenes [32 , 33] , although this work maximizes predictive accuracy at the expense of a one-to-one mapping of model components onto retinal circuit elements . Finally , other work focuses on particular ganglion cell types with a small number of inputs [22] , constrains the input stimulus to a low-dimensional subspace ( such as two halves of the receptive field [45] ) , or constrains the coefficients of receptive fields to be non-negative [46] , thus discarding known properties of the inhibitory surround . Our approach is most similar to MacFarland et . al . [18] , who formulate LN-LN models for describing nonlinearities in sensory pathways . Their model formulation uses spatiotemporal filters and smooth parameterized nonlinearities with an additional sparsity regularization penalty on the filters ( encouraging filters to contain few non-zero elements ) , fit using gradient descent . They demonstrate that these methods recover the parameters of a simulated model cell with two subunit pathways . Our work differs technically in the types of regularization penalties we apply and our use of high-dimensional spatiotemporal stimuli , and scientifically in our focus on gaining insight into the nonlinear computations underlying spatiotemporal processing in the retina . In this work , we do not make assumptions about or place restrictions on the number or tiling of subunit filters , the shapes of the subunit nonlinearities , the sign of receptive field elements , or the stimulus dimensionality . We additionally use a low-rank regularization penalty , that encourages approximately spatiotemporally separable filters [47 , 48] , a property that is common to receptive fields in a wide variety of sensory systems . In order to fit these models , we use methods based on proximal consensus algorithms ( described in Methods ) . These allow us to use this prior knowledge about model parameters to not only fit hierarchical nonlinear models , but also perform spike-triggered analyses using much less data than otherwise required .
Our LN-LN model architecture ( schematized in Fig 1 ) follows previous work [18] . The stimulus is first passed through a set of LN subunits . Each subunit filter is a spatiotemporal stimulus filter , constrained to have unit norm . The subunit nonlinearity is parameterized using a set of basis functions ( Gaussian bumps ) that tile the input space [12 , 20] ( see Methods ) . This parameterization is flexible enough that we could learn , for each individual subunit , any smooth nonlinearity that can be expressed as a linear combination of our basis functions . The second LN layer pools subunits through weighted summation , followed by a spiking nonlinearity that we model using a parameterized soft rectifying function r ( x ) = g log ( 1 + ex−θ ) . Here g is an overall gain , and θ is a threshold . The full set of parameters for the model consists of the spatiotemporal subunit filters , the subunit nonlinearity parameters , and the gain and threshold of the final nonlinearity . Here we examine , in more detail , quantitative properties of learned LN-LN models that can be compared to physiological properties of the retina . We find that model subunits quantitatively resemble bipolar cells in terms of receptive field properties and number , and that these intermediate subunits consistently have high-threshold nonlinearities . We now turn from a quantitative analysis of the physiological properties of the retina , described above , to their implications in terms of the computational function of the retina in processing visual stimuli . In particular , in the next two sub-sections we predict that the dominant contribution to stimulus decorrelation in efficient coding theory occurs at the bipolar cell synaptic threshold , and that the composite function computed by a retinal ganglion cell corresponds to a logical OR of its bipolar cell inputs . Given a mathematical model of a multilayered neural circuit , we can connect the pathways in such models back to descriptive statistics , namely , spike-triggered statistics such as the spike-triggered average ( STA ) and covariance ( STC ) . That is , we can show that the STA and the STC eigenvectors of a general LN-LN model are linear combinations its pathway filters ( see Methods and [64] ) . Therefore , we expect certain types of structure in said pathways to persist after the linear combination , assuming the number of pathways is small relative to the stimulus dimension . This immediately suggests that the same proximal algorithms and regularization terms we used to fit LN-LN models can be used to regularize the STA and the STC eigenvectors directly ( for situations where one is interested in the descriptive statistics , but not the full encoding model ) . To illustrate the benefits of the regularization terms used to fit the LN-LN models , we apply these penalties to perform regularized spike-triggered analysis . We formulate optimization problems for regularizing the spike-triggered average and covariance which only require access to the un-regularized estimates ( see Methods ) . This is useful for the situation where working with the full spike-triggered ensemble or raw dataset is prohibitive due to computational time or memory constraints . Fig 9A compares a regularized spike-triggered average with the raw , un-regularized STA for an example recorded ganglion cell in response to a 1-D spatiotemporal white noise stimulus . For long recordings , the regularized STA closely matches the raw STA , while for short recordings the regularized STA has less high frequency noise and retains much of the structure observed if the STA had been estimated using more data . Fig 9B shows the held-out performance of the regularized STA for an example cell across different regularization weights , scanned over a broad range , demonstrating that performance is largely insensitive to the strengths of the weights of the ℓ1 and nuclear norm penalty functions . Thus regularization weights need not be fine tuned to achieve superior performance . We further quantified the performance of the regularized STA by using it as the linear filter of an LN model , and found that with regularization , about 5 minutes of recording was sufficient to achieve the performance ( on held-out data ) obtained through 40 minutes of recording without regularization ( Fig 9C ) . Fig 10 demonstrates the improvement in our ability to estimate the relevant subspace spanned by significant STC eigenvectors , both in terms of the qualitative improvement in eigenvectors for an example cell ( Fig 10A ) and quantified across the population ( Fig 10B ) . In Fig 10A , we show the top regularized STC eigenvectors for different values of the nuclear norm ( γ* ) and ℓ1-norm ( γ1 ) regularization penalties ( Eq 11 in Methods and Table 1 ) . We score the performance of the STC subspace in Fig 10B in terms of how well stimuli , after projection onto the subspace , can be used to predict spikes , by computing the subspace overlap ( defined in Methods ) between the raw or regularized STC subspace and the best fit LN-LN subspace . This quantity ranges between zero for orthogonal subspaces and one for overlapping subspaces . Since the LN-LN subspace is the best subspace found by the LN-LN model for predicting spiking , a large subspace overlap between the regularized STC and LN-LN subspaces indicates the ability of regularized STC to find stimulus subspaces predictive of neural firing without actually fitting a model of the neuron . With appropriate regularization , one can recover the best predictive subspace using about 10 minutes of data; without regularization , one requires 40 minutes of data to recover a subspace with comparative predictive accuracy . Note that even for the full length of this experiment ( 40 minutes ) , regularization still improves our regularized STC estimate . Thus , we find the subspace spanned by regularized STC eigenvectors becomes very similar to the subspace obtained from the filters in an LN-LN model , as predicted by our theoretical analysis .
In summary , we combine proximal algorithms with non-smooth regularization terms to model stimulus driven neural processing in circuits with multiple parallel , hierarchical nonlinear pathways using limited experimental data . We found that models employing two stages of linear and nonlinear computation , namely LN-LN models , demonstrated a robust improvement over the classical standard of LN models at predicting responses to white noise across a population of ganglion cells . Beyond performance considerations alone , the gross architecture of the LN-LN model maps directly onto the hierarchical , cascaded , anatomy of the retina , thereby enabling the possibility that we can generate quantitative hypotheses about neural signal propagation and computation in the unobserved interior of the retina simply by examining the structure of our model’s interior . Since learning our model only requires measurements of the inputs and outputs to the retinal circuit , this approach is tantamount to the computational reconstruction of unobserved hidden layers of a neural circuit . The advantage of applying this method in the retina is that we can experimentally validate aspects of this computational reconstruction procedure . Indeed , using intracellular recordings of bipolar cells , we found that our learned subunits matched properties of bipolar cells , both in terms of their receptive field center-surround structure , and in terms of the approximate number of bipolar cells connected to a ganglion-cell . However care must be taken not to directly identify the learned subunits in our model with bipolar cells in the retina . Instead , they should be thought of as functional subunits that reflect the combined contribution of not only bipolar cells , but also horizontal cells and amacrine cells that sculpt the composite response of retinal ganglion cells to stimuli . Nevertheless , the correspondence between subunits and bipolar cell RFs ( which are also shaped by horizontal cells ) , suggests that even for Gaussian white noise stimuli , it is important to learn functional subunits that loosely correspond to the composite effect that bipolar cells and associated circuitry have on ganglion-cell responses . The interior of our models also reveal several functional principles underlying retinal processing . First , all subunits across all cells had strikingly consistent nonlinearities corresponding to monotonically increasing threshold-like functions with very high thresholds . This inferred biophysical property yields several important consequences for neural signal processing in the inner retina . First , it predicts that subunit activation patterns are sparse across the ensemble of stimuli , with typically only one subunit actively contributing to any given ganglion cell spike . Second , it predicts that the dominant source of stimulus decorrelation , a central tenet of efficient coding theory , has its mechanistic origin at the first strongly nonlinear processing stage of the retina , namely in the synapse from bipolar cells to ganglion cells . Third , it implies that the composite function computed by individual retinal ganglion cells corresponds to a Boolean OR function of bipolar cell feature detectors . Taken together , the proximal algorithms framework provides a unified way to both estimate hierarchical nonlinear models of sensory processing and compute spike-triggered statistics using limited data . When applied to the retina , these techniques recover aspects of the interior of the retina without requiring direct measurements of retinal interneurons . Moreover , by identifying candidate mechanisms for cascaded nonlinear computation in retinal circuitry , our results provide a higher resolution view of retinal processing compared to classic LN models , thereby setting the stage for the next generation of efficient coding theories that may provide a normative explanation for such processing . For example , considerations of efficient coding have been employed to explain aspects of the linear filter [65] and nonlinearity [61] of retinal ganglion cells when viewed through the coarse lens of an LN model . An important direction for future research would be the extension of these basic theories to more sophisticated ones that can explain the higher resolution view of retinal processing uncovered by our learned LN-LN models . Principles that underlie such theories of LN-LN processing might include subthreshold noise rejection [66 , 67] , sensitivity to higher order statistical structure in natural scenes , and energy efficiency [63] . Indeed the ability to extract these models from data in both a statistically and computationally efficient manner constitutes an important step in the genesis and validation of such a theory . Another phenomenon robustly observed in the retina is adaptation to the luminance and contrast of the visual scene . Adaptation is thought to be a critical component of the retinal response to natural scenes [30] , and a promising direction for extensions of our work would be to include luminance and contrast adaptation in subunit models . Luminance adaptation ( adapting to the mean light intensity ) is mediated by photoreceptor cells , and could be modeled by prepending a simple photoreceptor model ( e . g . [68] ) to an LN-LN model . There are two major sites of contrast adaptation , at the bipolar-to-ganglion cell synapse [69 , 70] and at the spiking mechanism of ganglion cells [69 , 71] . Extending the simple thresholding nonlinearities in our model with a dynamical model of adaptation ( e . g . [19] ) is a first step towards understanding the interaction between nonlinear subunits and adaptation . While our work utilized white noise stimuli , the methods do not require any particular form of stimulus and will thus generalize to other stimulus distributions . In particular , stimuli that differentially activate subunits will be the most effective at differentiating LN and LN-LN models . Stimuli with coarse spatial resolution will not differentially activate subunits within the receptive field , thus are a poor choice for studying nonlinear spatial integration . However , fine textures as present in natural stimuli , are very likely to activate these nonlinear mechanisms in the retina , and thus are a critical component for understanding vision in the context of ethologically relevant stimuli . The computational motifs identified by LN-LN models are likely to generalize across different species because they rely on a few key properties . For example , our predictions about the primary source of decorrelation in the retina rely on three features of the underlying circuitry identified by LN-LN models: ( a ) bipolar cell receptive fields are smaller than those of ganglion cells , ( b ) bipolar cell receptive field centers are largely non-overlapping , and ( c ) bipolar cell synapses have high thresholds . In addition , the logical OR combination of features relies on high thresholds and bipolar receptive fields that are ( largely ) non-overlapping . These properties ( high threshold subunits with smaller , non-overlapping receptive fields ) are common across multiple species . Beyond the retina , multiple stages of cascaded nonlinear computation constitutes a ubiquitous motif in the structure and function of neural circuits . The tools we have applied here to elucidate hierarchical nonlinear processing in the retina are similarly applicable across neural systems more generally . Thus we hope our work provides mathematical and computational tools for efficiently extracting and analyzing both informative descriptive statistics and hierarchical nonlinear models across many different sensory modalities , brain regions , and stimulus ensembles , thereby furthering our understanding of general principles underlying nonlinear neural computation .
This study was performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health , and the Stanford institutional animal care and use committee ( IACUC ) protocol ( 11619 ) . Experimental data was collected from the tiger salamander retina using a multi-electrode array ( Multi-Channel Systems ) , as described elsewhere [9] . Isolated ganglion cells were identified using custom spike sorting software . The stimulus used was a 100 Hz white noise bars stimulus , where the luminance of each bar was drawn independently from a Gaussian distribution . Spatially , the stimulus spanned approximately 2 . 8 mm on the retina ( 50 bars at 55 . 5 μm / bar ) . Intracellular recordings were performed as described elsewhere [72] . Off bipolar cells were identified by their flash response , receptive field size , and level in the retina . Data were analyzed using the pyret package [73] . The experimental data , as well as general purpose code to fit hierarchical LN-LN models and perform regularized STA and STC analysis , are available at https://github . com/baccuslab/inferring-hidden-structure-retinal-circuits . In this section , we specify the mathematical formulation of our LN-LN models . The model takes a spatiotemporal stimulus , represented as a vector x , and generates a predicted firing rate , r ( x ) . First , the stimulus is projected onto a number of subunit filters . The number of subunits is a hyper-parameter of the model , chosen through cross validation ( we repeatedly fit models with increasing numbers of subunits until held-out performance on a validation set decreases ) . If we have k subunits , then the stimulus is projected onto each of the k filters: wi for i = 1 , … , k . These projections are then passed through separate subunit nonlinearities . The nonlinearities are parameterized using a set of Gaussian basis functions ( or bumps ) that tile the relevant input space [12 , 20] . This parameterization enforces smoothness of the nonlinearity . We typically use p = 30 evenly spaced Gaussian bumps that tile the range spanned by the projection of the stimulus onto the linear filter ( results were not sensitive to the number of bumps over a range of 10–30 bumps ) . For example , a nonlinearity h ( u ) is parameterized as h ( u ) = ∑ j = 1 p a j ϕ j ( u ) = ∑ j = 1 p a j ϕ ( u - Δ j ) , where ϕ is the basis function , e . g . ϕ ( x ) = exp ( −x2 ) , Δj indicates the spacing between the basis functions , p is the number of bases used , and aj is a weight on that particular basis function . Since the basis functions and spacings are fixed beforehand , the only free parameters are the aj’s . For subunit i , the corresponding nonlinearity has a set of weights aij for j = 1 , … , p . The output of the k subunits is then summed and passed through a final nonlinearity . This final nonlinearity is parameterized as a soft rectifying function r ( x ) = g log ( 1 + ex−θ ) , with two parameters: g is an overall gain and θ is the threshold . The full LN-LN model is then given by: r ( x ) = g log ( 1 + exp [ ( ∑ i = 1 k ∑ j = 1 p a i ϕ ( w i T x - Δ j ) ) - θ ] ) , where the parameters to optimize are the subunit filters wi for i = 1 , … , k , subunit nonlinearity weights aij for j = 1 , … , p , and final nonlinearity parameters θ and g . We optimize the parameters using a maximum likelihood objective assuming a Poisson noise model for spiking . Rather than optimize all of the parameters simultaneously , we alternate between optimizing blocks of parameters ( joint optimization using gradient descent was prone to getting stuck at solutions that were less accurate ) . That is , we alternate between optimizing three blocks of parameters: the subunit filters wi , the subunit nonlinearities aij , and the final nonlinearity parameterized by θ and g . We optimize each block of parameters by minimizing the negative log-likelihood of the data plus any regularization terms using proximal algorithms . The subunit filters are the only parameters with regularization penalties ( the nuclear norm applied to the filter reshaped as a spatiotemporal matrix and the ℓ1 norm ) , to encourage space-time separability and sparseness of the filters . The proximal operator for each of these regularization penalties is given in Table 1 , and the proximal operator for the log-likelihood term ( which does not have a closed-form solution ) is solved using gradient descent . In addition , after optimizing the block of parameters corresponding to the subunit filters , we rescale them to have unit norm before continuing the alternating minimization scheme . This ensures that the distribution of input to the nonlinearities spans the same range , and gets rid of an ambiguity between the scale of the subunit filters and the scale of the domain of the subunit nonlinearity . We find that the parameters converge after several rounds of alternating minimization , and are robust with respect to random initialization of the parameters . The framework of proximal algorithms allows us to efficiently optimize functions with non-smooth terms . The name proximal comes from the fact that these algorithms utilize the proximal operator ( defined below ) as subroutines or steps in the optimization algorithm . For brevity , we skip the derivation of these algorithms , instead referring the reader to the more thorough treatment by Parikh and Boyd [74] or Polson et al . [75] . The proximal operator for a function ϕ given a starting point v is defined as: P ϕ ( v ) = argmin x [ ϕ ( x ) + ρ 2 ∥ x - v ∥ 2 2 ] . ( 1 ) The proximal operator is a mapping from a starting point v to a new point x that tries to minimize the function ϕ ( x ) ( first term above ) but stays close to the starting point v ( second term ) , where the parameter ρ trades off between these two objectives . The proximal operator is a building block that we will use to create more complicated algorithms . We will take advantage of the fact that for many functions ϕ of interest to us , we can analytically compute their proximal operators , thus making these operators a computationally cheap building block . We used these building blocks to solve optimization problems involving the sum of a number of simpler terms: min x ∑ i = 1 k ϕ i ( x ) ( 2 ) where in our application the ϕi’s represent either a model fitting objective ( e . g . a log-likelihood ) or different regularization penalties on the parameters , x . For example , for learning the parameters of a linear filter in an LN model , the objective consists of a log-likelihood f ( x ) along with regularization penalties that impose prior beliefs about the filter , x . We focus on two main penalties . Sparsity , which encodes the belief that many filter coefficients are zero , is penalized by the ℓ1-norm ( ϕ1 ( x ) = ‖x‖1 ) . Additionally , spatiotemporal filters are often approximately space-time separable ( they are well modeled as the outer product of a few spatial and temporal factors ) . We encoded this penalty by the nuclear norm , ℓ* , which encourages the parameters x , when reshaped to form a spatiotemporal matrix , to be a low-rank matrix ( the nuclear norm ℓ* of a matrix is simply the sum of its singular values ) . Another natural penalty would be one that encourages the parameters to be smooth in space and/or time , which could be accomplished by applying an ℓ1 or ℓ2 penalty to the spatial or temporal differences in parameters . As shown below , these types of penalties are easy to incorporate into the proximal algorithm framework . Other commonly used regularization penalties , and their corresponding proximal operators , are listed in Table 1 . The proximal consensus algorithm is an iterative algorithm for solving ( 2 ) that takes a series of proximal operator steps . It first creates a copy of the variable x for each term ϕi in the objective . The algorithm proceeds by alternating between taking proximal steps for each function ϕi using that variable copy xi , and then enforcing all of the different variable copies to agree ( reach consensus ) by averaging them . The algorithm is: x i k + 1 = P ϕ i ( x ¯ k - u i k ) x ¯ k + 1 = 1 k ∑ i = 1 k x i u i k + 1 = u i k + x i k + 1 - x ¯ k + 1 , where i indexes each of the terms in the objective function , xi is a copy of the variable , x ¯ is the average of the variable copies , and ui is a dual variable that can be thought of as keeping a running average of the error between each variable copy and the average . Intuitively , we can think of each variable copy xi as trying to minimize a single term ϕi in the objective , and the average , or consensus x ¯ forces the different copies to agree . After convergence , each copy xi will be close to the mean value x ¯ , which is the set of parameters that minimizes the original composite objective . This algorithm has a number of desirable properties . First , the updates for each term xi can be carried out in parallel , therefore allowing for speedups when run on a cluster or multi-core computer . Second , it converges even when terms in the objective are non-differentiable . Due to the repeated application of the proximal operator , this algorithm works best when the terms ϕi have proximal operators that are easy to compute . This is exactly the case for the regularization terms described above: for the ℓ1 norm , the proximal operator corresponds to soft thresholding of the parameters . For the nuclear norm , the proximal operator corresponds to soft thresholding of the singular values of parameters reshaped as a matrix . Occasionally , the proximal operator may not have a closed form solution . In this case , the proximal step can be carried out through gradient based optimization of ( 1 ) directly . This is the case for some log-likelihoods , such as the log-likelihood of a particular firing rate under Poisson spiking . In this case , gradient step based optimization of ( 1 ) often dominates the computational cost of the algorithm . As many methods for fitting neural models involve gradient step updates on the log-likelihood , such methods can then be augmented with additional regularization terms with no appreciable effect on runtime , by using proximal consensus algorithms for optimization . Our code for solving formulating and solving optimization problems using proximal algorithms is provided online at https://github . com/ganguli-lab/proxalgs . Here , we derive the relationship between the pathways of any differentiable encoding model and spike-triggered statistics under Gaussian noise stimulation . We represent a visual stimulus as an N dimensional vector x . We view a functional neural model as an arbitrary nonlinear function r = f ( x ) , over N dimensional stimulus space , where r determines the probability that the neuron fires in a small time window following a stimulus x: r ( x ) = p ( spike ∣ x ) . The derivation will show how the STA is related to the gradient of the model ∇r ( x ) , and the STC is related to the Hessian , ∇2r ( x ) . The STA and STC are the mean and covariance , respectively , of the spike-triggered stimulus ensemble , which reflects the collection of stimuli preceding each spike [3] . This distribution over stimuli , conditioned on a spike occurring , can be expressed via Bayes rule , p ( x ∣ spike ) = p ( spike ∣ x ) p ( x ) p ( spike ) , ( 3 ) where p ( x ) is the prior distribution over stimuli and p ( spike ) is the average firing probability over all stimuli . Here , we assume a white noise stimulus distribution , in which each component of x is chosen independently from a Gaussian distribution with zero mean and unit variance . The STA and STC are given by x STA = E p ( x ∣ s p i k e ) [ x ] ( 4 ) C STC = E p ( x ∣ s p i k e ) [ x x T ] - ( x STA ) ( x STA ) T ( 5 ) Focusing first on the STA: x STA = ∫ x p ( x ∣ spike ) d x = 1 μ ∫ x r ( x ) p ( x ) d x = 1 μ E p ( x ) [ x r ( x ) ] = 1 μ E p ( x ) [ ∇ r ( x ) ] , ( 6 ) where μ = p ( spike ) is the overall probability of spiking . The last step in the derivation uses Stein’s lemma , which states that E [ x f ( x ) ] = E [ ∇ f ( x ) ] if the expectation is taken over a multivariate Gaussian distribution with identity covariance matrix , corresponding to our white noise stimulus assumption . This calculation thus yields the simple statement that the spike-triggered average is proportional to the gradient ( or gain ) of the response function , averaged over the input distribution [64] . Applying Stein’s lemma again yields an expression for the STC matrix: C STC = ∫ x x T p ( x ∣ spike ) d x - ( x STA ) ( x STA ) T = 1 μ ∫ x x T r ( x ) p ( x ) d x - ( x STA ) ( x STA ) T = 1 μ E p ( x ) [ x x T r ( x ) ] - ( x STA ) ( x STA ) T = 1 μ E p ( x ) [ ∇ 2 r ( x ) ] - ( x STA ) ( x STA ) T ( 7 ) Intuitively , these results state that the STA is related to the slope ( first derivative ) and the STC is related to the Hessian curvature ( matrix of second derivatives ) of the multi-dimensional nonlinear response function r ( x ) . For example , consider a linear-nonlinear model r = f ( wT x ) which has the following gradient: ∇r ( x ) = f′ ( wT x ) w and Hessian: ∇2r ( x ) = f″ ( wT x ) wwT . Plugging these expressions into Eqs ( 6 ) and ( 7 ) reveals that the STA is proportional to w and the STC is proportional to wwT . Therefore , we recover the known result [2] that the STA of the LN model is proportional to the linear filter , and there will be one significant direction in the STC , which is also proportional to the linear filter ( with mild assumptions on the nonlinearity , f , to ensure that slope and curvature terms in ( 6 ) and ( 7 ) are non-zero ) . We can extend this to the case of a multilayered circuit with k pathways , each of which first filters the stimulus with a filter w1 … wk . Regardless of how these pathways are then combined , we can write this circuit computation as r = f ( WT x ) where W is a matrix whose columns are the k pathway filters , and f is a k-dimensional time-independent ( static ) nonlinear function . We can think of the k dimensional vector u = WT x as the activity pattern across each of the k pathways before any nonlinearity . The gradient for such a model is ∇r ( x ) = WT∇f ( u ) , where ∇f ( u ) is the gradient of the k-dimensional nonlinearity . Using Eq ( 6 ) , the STA is then a linear combination of the pathway filters: x STA = 1 μ ∑ i = 1 k α i w i , where the weights are given by α i = E p ( x ) [ ∂ u i r ( u ) ] , and correspond to the average sensitivity , or slope of the neural response r with respect to changes in the activity of the ith filter . The Hessian for the multilayered model is ∇2r ( x ) = W∇2fWT , where ∇2f is the k-by-k matrix of second derivatives of the k-dimensional nonlinearity f ( u ) . From Eq ( 7 ) , the STC is then given by: C STC = 1 μ 2 W H W T , ( 8 ) where the k-by-k matrix H is: H = μ E [ ∇ 2 f ( u ) ] - E [ ∇ f ( u ) ] E [ ∇ f ( u ) ] T . This expression implies that nontrivial directions in the column space of CSTC correspond to ( span the same space as ) the column space of W . Therefore , the significant eigenvectors of the STC matrix will be linear combinations of the k pathway filters , and the number of significant eigenvectors is at most k . Note that Eqs ( 6 ) and ( 7 ) are valid for any differentiable model , including those with more than two layers , divisive interactions , feedback , and so on . We quantify the overlap between two subspaces as the average of the cosine of the principal ( or canonical ) angles between the subspaces . The principal angles between two subspaces X ∈ R n × p and Y ∈ R n × q generalize the idea of angles between vectors . Here we describe a pair of p and q dimensional subspaces in n dimensional space as the span of the columns of the matrices X and Y . Assuming without loss of generality that p ≤ q , then we have p principal angles θ1 , … , θp that are defined recursively for k = 1 , … , p as: cos θ k = max x ∈ X max y ∈ Y x T y = x kT y k , subject to the constraints that the vectors are unit vectors ( xT x = yT y = 1 ) and are orthogonal to the previously identified vectors ( x jTx = 0 , y jTy = 0 for j = 1 , 2 , … , k − 1 ) . That is , the first principal angle is found by identifying a unit vector within each subspace such that the correlation , or dot product , between these vectors ( these are known as the principal vectors ) is maximized . This principal angle is then the inverse cosine of the dot product . Each subsequent principal angle is found by performing the same maximization but restricting each new pair of vectors to be orthogonal to the previous principal vectors in each subspace . The principal angles can be efficiently computed via the QR decomposition [78] . We define subspace overlap as the average of the cosine of the principal angles , 1 p ∑ k = 1 p cos θ k . This quantity is at most 1 ( for two subspaces that span the same space ) , and at least 0 ( for two orthogonal subspaces that share no common directions ) . | Computation in neural circuits arises from the cascaded processing of inputs through multiple cell layers . Each of these cell layers performs operations such as filtering and thresholding in order to shape a circuit’s output . It remains a challenge to describe both the computations and the mechanisms that mediate them given limited data recorded from a neural circuit . A standard approach to describing circuit computation involves building quantitative encoding models that predict the circuit response given its input , but these often fail to map in an interpretable way onto mechanisms within the circuit . In this work , we build two layer linear-nonlinear cascade models ( LN-LN ) in order to describe how the retinal output is shaped by nonlinear mechanisms in the inner retina . We find that these LN-LN models , fit to ganglion cell recordings alone , identify filters and nonlinearities that are readily mapped onto individual circuit components inside the retina , namely bipolar cells and the bipolar-to-ganglion cell synaptic threshold . This work demonstrates how combining simple prior knowledge of circuit properties with partial experimental recordings of a neural circuit’s output can yield interpretable models of the entire circuit computation , including parts of the circuit that are hidden or not directly observed in neural recordings . | [
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"ganglion... | 2018 | Inferring hidden structure in multilayered neural circuits |
Certain environmental microorganisms can cause severe human infections , even in the absence of an obvious requirement for transition through an animal host for replication ( “accidental virulence” ) . To understand this process , we compared eleven isolate genomes of Burkholderia pseudomallei ( Bp ) , a tropical soil microbe and causative agent of the human and animal disease melioidosis . We found evidence for the existence of several new genes in the Bp reference genome , identifying 282 novel genes supported by at least two independent lines of supporting evidence ( mRNA transcripts , database homologs , and presence of ribosomal binding sites ) and 81 novel genes supported by all three lines . Within the Bp core genome , 211 genes exhibited significant levels of positive selection ( 4 . 5% ) , distributed across many cellular pathways including carbohydrate and secondary metabolism . Functional experiments revealed that certain positively selected genes might enhance mammalian virulence by interacting with host cellular pathways or utilizing host nutrients . Evolutionary modifications improving Bp environmental fitness may thus have indirectly facilitated the ability of Bp to colonize and survive in mammalian hosts . These findings improve our understanding of the pathogenesis of melioidosis , and establish Bp as a model system for studying the genetics of accidental virulence .
Burkholderia pseudomallei ( Bp ) , the causative agent of the often-fatal disease melioidosis , represents one of the most complex bacterial genomes sequenced to date [1] . Comprising two circular chromosomes with a combined length of 7 . 2 Mb , the Bp genome contains an estimated ∼5800 genes involved in a myriad of functions , allowing microbial survival in extreme environments and virulence in diverse host species including humans , gorillas , pigs , and fish [2]–[3] . Epidemiological and genetic evidence suggests that Bp is likely an ‘accidental pathogen’ , in that adaptations incurred by Bp in its natural environmental reservoir ( soil ) may have indirectly contributed to its ability to colonize a mammalian host [4]–[7] . Understanding the genetic basis of these environmental adaptations may thus provide important insights into the pathogenesis of melioidosis , and shed light on how environmental microorganisms are able to acquire novel traits enhancing their ability to cause opportunistic disease . The evolutionary success of Bp as a thriving soil microbe suggests that most Bp strains are likely to possess a common repertoire of genes ( the Bp core genome , or BpCG ) regulating survival and fitness in this highly competitive environmental niche . Specific selective pressures encountered in soil , such as evading phagocytosis by amoebae [8] or ingestion by nematodes [9] might further enhance Bp environmental fitness by inducing modifications in BpCG genes , and some of these modifications might also contribute indirectly to mammalian virulence . Indeed , many classical virulence genes such as adhesins , fimbrae , exopolysaccharides and Type III secretion ( TTS ) systems are part of the BpCG [7] , suggesting a plausible link between the BpCG and mammalian pathogenicity . Currently , little is known regarding the extent of genetic variation in the Bp core genome ( BpCG ) and whether BpCG variations might underlie potential virulence phenotypes . In this study , we undertook a comprehensive qualitative and quantitative survey of the BpCG across a panel of eleven Bp genomes , comprising nine independently derived strains , and two related strain pairs isolated from human patients at primary infection and disease relapse . We found evidence for the presence of several new genes in the Bp genome , and discovered a sizeable degree of genetic variation in BpCG genes . We identified over two hundred BpCG genes with signatures of positive selection , likely reflecting the activity of multiple distinct environmental pressures . Finally , we provide experimental evidence that some of these positively selected genes may have indirectly contributed to Bp pathogenesis in mammals , by facilitating interactions with host cellular pathways or the use of host nutrients .
We analyzed whole-genome sequences from eleven Bp strains , comprising ten clinical isolates from four countries ( Australia , Thailand , Singapore , and Vietnam ) and one soil isolate ( S13 ) from Singapore . To achieve maximal genetic diversity , we elected to analyze all Bp strains regardless of their source of isolation ( clinical or environmental ) . Notably , environmental Bp isolates have also been shown to exhibit high levels of virulence in animal models [10] . Among the clinical isolates , strain pairs 1106a–1106b and 1710a–1710b were isolated from the same patients during either primary infection or disease relapse ( Table S1 ) . Reflecting the genetic diversity in this panel , the Bp isolates belong to different multi-locus subtypes ( MLST ) with an overall MLST allele/subtype ratio of 2 . 67 , markedly higher than the allele/subtype ratio of the general Bp population ( 0 . 43 , as of Jan 2009 ) . Ten genomes were sequenced by conventional Sanger based shotgun methods ( coverage range 7 . 75x – 11 . 4x ) , while strain Bp 22 was sequenced using next-generation instrumentation ( GS20-454 , average read length 100 bp , 20× coverage ) followed by de novo assembly using a custom 454 large-insert paired-end sequencing protocol ( CN and YR , manuscript in prep ) . The genome sequences were uniformly annotated by a FGENESB gene prediction pipeline [11] , and predicted protein-coding regions , tRNAs , rRNAs , and potential promoters , terminators and operons were identified . Predicted genes were comprehensively annotated against known proteins in the NR , COG , KEGG and STRING databases ( details in Methods ) . All genomes revealed similar benchmark data such as genome size , GC content , and numbers of predicted genes ( Table 1 ) . Both chromosomes ( 1 and 2 ) were highly syntenic across the Bp genomes ( Figure 1 [12]–[13] and Figure S1 ) . No evidence for inter-chromosomal exchange of genetic material across the two chromosomes was observed . We identified three large-scale inversions of 1 . 6 Mb , 1 . 2 Mb and 880 Kb on Chromosome 1 , largely flanked either by rRNAs , tRNAs , or inverted protein units ( Text S1 ) . The 1 . 2 Mb inversion was observed in two strains , 1655 and Pasteur 52237 , hailing from distinct geographic origins ( Australia and Vietnam ) and belonging to unrelated MLSTs , suggesting that this rearrangement may have independently occurred at least twice during Bp genome evolution . The other two inversions were only observed in single strains ( 406e and K96243 ) , however it is worth noting that K96243 represents the original Bp reference genome described in 2004 [1] . Our comparative analysis allowed us to revisit the original 2004 genome analysis with updated annotation protocols . Our annotation pipeline identified 6332 protein coding genes in Bp K96243 ( Datasets S1 and S2 ) , a considerably higher number ( ∼10% ) than the 5855 genes originally described [1] . The vast majority ( 90% ) of genes , however , were commonly identified in both annotation pipelines ( Figure 2A ) , indicating that differences in the two annotation sets are likely due to subtle differences in the prediction algorithms used [14]–[15] ( FGENESB vs GeneMark/Glimmer ) . Deciding to investigate these previously unreported genes , we sought to distinguish between likely bona-fide new genes and those arising due to computational over-prediction ( false positives ) . We manually curated a set of 519 novel predicted genes exhibiting non-overlapping start-stop boundaries to the previously reported genes ( see Figure 2B for an example ) , and subjected the 519 putative novel genes to three independent lines of analysis ( mRNA transcript information , homology to previously reported genes , and presence of ribosomal binding sites , RBSs ) . First , using whole genome tiling microarrays covering the entire non-repetitive Bp K96243 genome , we identified transcription units from Bp cultures isolated from six distinct growth conditions ( see Methods , [16] ) . Confirming the accuracy of the microarray , many mRNA transcripts were tightly associated with the boundaries of previously-identified genes ( Figure S2 ) . Of the 519 novel genes , we found that 280 ( 53% ) were associated with discrete mRNA transcripts . 178 novel genes exhibited mRNA transcripts in at least 1 out of 6 different growth conditions , indicating that they are differentially-regulated ( Figure 2C ) , while the remaining 102 were constitutively expressed across the six conditions . The presence of several novel gene transcripts was also directly confirmed by targeted RT-PCR assays ( Figure S3 ) . To investigate if any of the novel genes might correspond to non-coding RNAs ( ncRNAs ) , we used Rfam , a public database of non-coding RNA families [17] , to identify ncRNAs in the BpK96243 reference genome . Of 82 small ncRNAs identified by Rfam analysis , 8 ncRNAs corresponded to the novel genes . Second , using matching criteria similar to other studies [18]–[19] ( see Methods , [20] ) , approximately 46% of the novel genes ( 239 ) were associated with at least one other matching protein in the COG , KEGG , STRING and NR databases ( Figure 2D , [21] ) . 138 novel genes had matching proteins previously observed in other Bp strains , and 97 novel genes had matches to other Burkholderia species . A small fraction ( ∼1% ) exhibited homology to other non-Burkholderia species ( eg Xanthomonas oryzae pv . oryzae MAFF , Sodalis glossinidius str morsitans ) . Third , using the RBSfinder program [22]–[24] , we checked the novel genes for the presence of ribosome binding sites ( RBS ) . The ability of RBSfinder to detect true RBSs in the Bp genome was confirmed by benchmarking the numbers of RBS predictions using previously-identified Bp genes against a set of background randomized sequences [25]–[26] ( Text S2 ) . Of the 519 novel genes , we identified high-confidence RBSs in 309 genes ( 59 . 5% ) , without requiring alteration of the predicted gene start/stop coordinates . Combining these three lines of supporting evidence ( mRNA transcripts , database matches , presence of RBS ) , we identified 282 novel genes supported by two lines of evidence ( “dual evidence genes” ) , and 81 novel genes supported by all three lines ( Table S2 ) . A comparison of compositional features ( length , G+C content , CAI , hydrophobicity [27] ) between the 282 dual evidence genes and 5728 protein-coding genes from the original 2004 annotation revealed striking differences in gene length between the sets ( average gene length 98±56 aa vs 348±307 aa between novel and 2004 genes , p = 1 . 23×10−304 ) ( Figure 2E ) . Significant differences in G+C content , CAI , and hydrophobicity were also observed ( eg G+C content 0 . 63±0 . 1 vs 0 . 68±0 . 05 , p = 9 . 69×10−17 ) ( Table S3 ) . Interestingly , some of these latter compositional differences might be indirectly related due to the short lengths of the novel genes , as significant G+C content , CAI , and hydrophobicity differences were also observed when a set of “short length” genes from the original annotation ( <200 aa ) were compared against the entire 5728 set ( Table S3 ) . Because compositional differences can often influence gene prediction accuracy [28]–[29] , it is possible that some of these differences might have contributed to the novel genes being missed in the original annotation . To facilitate integration with existing genome features , we assigned identities to the 282 novel genes based on their proximity to existing genes ( eg BPSL2192 . 1 ) ( Table S2 ) . We also investigated the 120 genes missed in the current gene prediction analysis but identified by the previous 2004 genome annotation ( Table S4 ) . Of these 120 genes , 87 genes ( 73% ) were categorized either as “doubtful CDs” , “gene remnants” , or “pseudogenes” in the original 2004 annotation , indicating that these genes were likely regarded as ambiguous in the previous annotation as well . Of the remaining 33 genes , 21 genes encode hypothetical proteins while another 6 appear to have bacteriophage origins that may contain coding signals distinct from the rest of the Bp genome . The ambiguous nature for three-quarters of these genes , coupled with presence of atypical coding signals , provides the most likely explanation for their failure to be detected by the current automated prediction pipeline . The availability of multiple Bp genomes also permitted the analysis of pseudogene dynamics within a species . Of 26 previously-described pseudo-genes in Bp K96243 [1] , at least 6 were ‘resurrected’ in >6 other Bp genomes . For example , the BPSL2828 pseudo-gene exhibits a premature truncation due to a stop codon at position 107 ( TGG → TGA ) . This mutation , however , was only observed in Bp K96243 and Bp Pasteur 52237; while the other 9 Bp genomes had an extended gene sequence to position 147 ( Figure S4 ) . The differential presence of multiple pseudogenes across the Bp strains suggests that pseudogene formation in Bp is likely to be an active and highly dynamic process , consistent with its role as a recently evolved pathogen . An analysis of gene orthologs across the Bp genomes identified a BpCG of 4908 genes present in all 11 strains ( Figure 3A , [30] ) , with slight variations in individual genomes due to the presence of gene duplications and paralogs ( range 5049–5139 genes ) . Similar core genome estimates were obtained when the analysis was confined to the nine independently derived isolates ( Figure S5 ) . We confirmed the robustness of this BpCG estimate using the method of Tettelin et al [31] . An evolutionary comparison of the BpCG against two closely related Burkholderia species with highly distinct niches - B . mallei ATCC23344 ( Bm ) , a intracellular pathogen specific to horses [32] , and B . thailandensis E264 ( Bt ) , a non pathogenic , environmental bacterium [33]–[34] , defined a common set of ∼3616 genes found in all three species ( Figure 3C ) . 270 out of 335 genes are common to Bp and Bm with no orthologs in Bt , while 641 out of 769 genes are common to Bp and Bt with no ortholog in Bm . Besides the core genes , gene accumulation curves also project the global gene repertoire of Bp ( the Bp pangenome ) to be ∼7 , 500 genes ( Figure 3B ) , a number close to 1 . 5x the size of the Bp core genome . A detailed analysis of the Bp pangenome will be described elsewhere . To survey the landscape of genetic variation in Bp , we focused on a high quality ortholog set of 4673 BpCG genes ( one orthologous gene per genome with >50% sequence similarity , each member exhibiting positional conservation to every other member , and excluding paralogs ) . We catalogued single-nucleotide polymorphisms ( SNPs ) and insertion/deletion sequences ( indels ) in the BpCG . Each Bp strain exhibited an average of ∼8594 SNPs compared to the K96243 reference genome , resulting in an overall SNP/Kb frequency of ∼2 . 0 for BpCG genes , while indels account for 0 . 1% and 0 . 3% of the total genetic variation in chromosomes 1 and 2 respectively . We confirmed the reliability of the genetic variation data by several methods . First , we confirmed by targeted resequencing >100 randomly-selected SNPs and 25 randomly-selected indels ( data not shown ) . Second , 83% of identified SNPs are either ( a ) recurrently observed across multiple genomes ( Table S5 ) [35] , or ( b ) observed in Bp genomes of particularly high sequence quality ( 1106a , 1710b , 22 , K96243 and 406e ) ( Table S5 ) . Third , the SNP distributions are entirely consistent with geographic models in that strains with the highest levels of genetic variation compared to K96243 were observed in isolates from Australia , the most geographically distant locale ( Figure 4A ) . This is consistent with previous proposals that strains from Australia are genetically distinct from their Asian counterparts [36] and form an ancestral population [35] . The existence of a deep genetic distinction between the South East Asian and Australian strains was further supported by phylogenetic analysis of 14 , 544 shared orthologous SNPs across 23 Bp genomes ( including the genomes analyzed in this study ) , and also by an MLST population structure analysis involving >1800 Bp strains ( 647 sequence types ) ( Figure S6 ) . Among the clinical isolates , strain pairs 1106a–1106b and 1710a–1710b were isolated from the same patients during either primary infection or disease relapse , with intervening periods of approximately three years ( Table S1 ) . Surprisingly , a comparison of the primary and relapse strain genomes in both pairs failed to reveal a significant number of newly acquired mutations in relapsed strains ( 4 variants in 1106a vs 1106b , 6 variants in 1710a vs 1710b , none recurrent between both pairs ) ( Table S6 ) . This lack of genetic variation between the primary and relapsed strains suggests that the former may have remained dormant in the human host during this intervening period , supporting the notion that that the Bp genome is likely to exhibit a high degree of stability during in vivo infection and persistence . To assess the functional implications of BpCG variation , we divided the BpCG SNPs into subsets predicted to cause either synonymous ( Ks ) or nonsynonymous ( Ka ) nucleotide substitutions . The Ks rate was similar between Bp Chr 1 and 2 , indicating comparable levels of background genetic diversity between the two chromosomes . However , the Ka rate of Chr 2 was significantly higher than Chr 1 ( P = 2 . 42×10−21 , unpaired t-test , under a one-ratio model ( M0 ) assuming a constant Ka/Ks ratio , Figure 4B ) , indicating that BpCG genes on Chr 2 are experiencing a higher degree of functional substitution than Chr 1 . These chromosomal differences support the model of Holden et al [1] that Chr 1 of Bp represents the ancestral chromosome , with genes primarily related to housekeeping functions while Chr 2 contains genes involved in accessory functions and secondary adaptation . We identified BpCG genes with signatures of positive selection using established methods [37]–[39] ( Figure S7 and Methods , [40] ) . A maximum likelihood analyses was performed on each Bp core gene to detect coding sequence sites displaying features of differential selective pressure ( positive selection ) using two different likelihood ratio ( LR ) models ( M1a-M2a , or M7-M8 ) . Out of 4673 genes , Model M1a-M2a was significant for 212 genes , while model M7 -M8 test was significant for 239 genes ( Ka/Ks>1; ∼2% FDR; P<0 . 001 , LR Test ) . In total , 211 genes were commonly identified by both models as being positively selected ( Table S7 ) . Consistent with these 211 genes exhibiting above-background rates of functional variation ( median Ka/Ks = 60 . 07 and P<0 . 001 , LR Test ) , the average Ks value of the 211 positively selected genes was similar to the Ks value of non-PS genes ( Ks = 0 . 2 for PS and non-PS genes , p = 0 . 56 ) , while in contrast , Ka , the rate of non-synonymous substitution was 3 times greater in the positively-selected genes compared to genes under neutral selection ( p = 0 . 5×10−5 , t-test ) . The Ka/Ks value of the positively selected genes was also markedly higher compared to seven housekeeping genes typically used in MLST analysis ( ace , gltB , gmhD , lepA , lipA , narK and ndh ) ( P<0 . 001 , LR Test ) . A significantly greater fraction of positively-selected genes were identified on Chr 2 than Chr 1 ( P = 0 . 006 , χ2 test , 10000 simulations ) . These observations suggest that a significant proportion of the Bp core genome ( ∼4 . 5% ) may be under positive selection . We investigated whether the elevated Ka/Ks rate of the 211 positively selected genes might be due to mutation or recombination between the genomes in this strain panel . All 4673 core genome alignments were tested for the potential presence of recombination using two different methods ( GENECONV [41] , and the Pairwise Homoplasy Index ( Phi ) ) [42] . Combining both methods , 56 out of 4673 core genes were identified as exhibiting a recombination signature . Of these 56 , only 3 belong to the 211 positively selected genes , indicating that only a relatively minor component of the 211 genes are associated with a recombination signature . We also assessed rho/theta , the recombination/mutation ratio , of the Bp genomes analyzed in this study [43] . Using the Clonalframe algorithm [43] , an inspection of 4294032 variation sites estimated rho/theta to be 0 . 012–0 . 015 ( 95% credibility region ) for Chr 1 and 0 . 015–0 . 019 for Chr 2 respectively . This low value suggests that mutation rather than recombination appears to be the predominant evolutionary process explaining the patterns of genetic variation observed in the current panel of Bp strains . Consistent with the BpCG responding to multiple selective pressures , the positively selected genes were widely dispersed across a wide variety of functions , including metabolic processes , membrane functions , signal transduction , and gene expression regulation ( Table 2 ) . A functional category analysis subsequently revealed that positively selected genes in the Bp core genome were significantly enriched in COG categories related to secondary metabolism ( P = 0 . 036 ) and carbohydrate metabolism ( P = 0 . 01 , binomial test after correction for multiple hypotheses ) ( Figure 4C ) , highlighting these two metabolic pathways as major processes experiencing selective pressure . We were intrigued by the possibility that the positively selected genes , while overtly responding to environmental pressures encountered by Bp in soil , might indirectly facilitate the colonization of mammalian hosts . Supporting this notion , the positively selected genes were significantly enriched in genes previously identified as putative virulence-related genes [1] ( 20 genes , P = 0 . 019 , based on 10 , 000 empirical permutations ) . For example , one representative class of virulence-related genes are Type IV pili ( TFP ) , which are bacterial surface proteins implicated in multiple cellular processes , including motility , cell adhesion , microcolony formation , and virulence [44] . Of eight previously identified TFP loci in Bp K96243 [45] , positively selected genes were associated with three TFP loci ( TFP2 , TFP4 and TFP7 ) , with the TFP4 Type IVA minor pilin locus containing two positively selected genes ( BPSL2754 pilW and BPSL2755 pilV ) . To evaluate if TFP4 might be involved in mammalian virulence , we generated isogenic Bp mutant strains deleted in the TFP4 locus , and tested the virulence of TFP4 deletion strains in a BALB/c mouse intranasal infection assay [46] . TFP4 deleted strains exhibited significantly reduced virulence compared to parental Bp K96243 wild-type controls ( p = 0 . 048 , Mantel-Haenszel log-rank test , Figure 5A ) , supporting a role for Type IV minor pilin activity in murine virulence . These results suggest that a subset of positively selected genes in Bp may influence virulence in mammals . To further explore if other positively selected genes might conceivably provide traits facilitating successful mammalian infection , we then investigated two other features typically associated with successful intracellular human pathogens - a ) the ability to interact with host cellular processes , and b ) the ability to utilize host metabolites as nutrients . Previous studies have shown that many microbial pathogens can alter host cytoskeletons and cell morphology during infection , using proteins such as TTS factors to induce actin stress fibers , lamellipodia , and filapodia [46]–[48] . To examine the role of positive selection in this process , we curated a list of ten positively selected genes , either related to TTS biology ( BPSS1552 ) or present in Bp and Bm ( both pathogenic species ) but absent from Bt ( non-pathogenic ) ( Table S8 ) . We cloned and expressed these ten genes in Hela cells , and examined the transfected cells for cytoskeletal perturbations . As a positive control , we also included BopE ( BPSS1525 ) , a TTS effector protein capable of inducing actin rearrangements [49] . Nine of the positively selected genes were successfully expressed in Hela cells but did not induce any significant differences in actin morphology compared to vector controls ( eg BPSS0415 , Figure 5B ) . In contrast , cells transfected with BPSL1057F1 , a hypothetical protein and one of the novel genes identified in this study , exhibited a marked increase in actin stress fiber formation in the majority ( 60% ) of transfected cells , with phenotypes very similar to BopE transfection ( Figure 5B and 5C ) . Protein analysis of BPSL1057F1 revealed the presence of a twin-arginine signal peptide sequence , often found in proteins exported into an extra-cellular environment [50] . These results suggest that some positively selected genes in Bp may provide Bp with the potential to interact with host cellular pathways . We also analyzed the list of positively selected genes for potential genes involved in host metabolite catabolism . Of metabolites linked to the 10 positively selected secondary metabolism genes , we focused on taurine ( 2-aminoethanesulfonate ) , since taurine is an amino acid found at high levels in potential mammalian hosts in muscles , bile , and white blood cells , but absent or present at only trace levels in bacteria and plants [51] . Supporting the notion that Bp has developed an ability to metabolize taurine , the taurine dixoygenase gene BPSS0161 ( tauD ) exhibited a significant degree of positive selection across the eleven Bp genomes ( P<0 . 001 , Ka/Ks = 57 . 6 , EC 1 . 14 . 11 . 17 ) . Prompted by this finding , we further explored the role of taurine metabolism genes in Bp and discovered a previously-unreported species-specific expansion of additional tauD gene members in Bp . Specifically , compared to Bt or Bm which have three tauD genes on Chr 2 , the Bp Chr 2 genomes harbor eight-nine tauD genes , a three-fold expansion ( Figure 5D [52]–[53] , also on Chr 2 ) . The Bp tauD genes all share the same tauD pfam family domain ( PF02668 ) but otherwise exhibit low sequence similarity between each other ( average nucleotide homology of 36% ) , arguing against this expansion occurring by gene duplication . Instead , sequence analysis suggests that many of the Bp tauD genes were likely acquired by lateral gene transfer . For example , BPSS0665 , another tauD gene , is localized to genomic island 14 ( GI14 ) , a region of codon bias deviation and atypical % GC content ( Figure S8 ) . Intriguingly , despite exhibiting many features of mobile elements , GI14 has been previously shown to be consistently present across a large panel of natural Bp isolates in contrast to other GIs [7] ( Figure S8 ) . It is possible that a selective requirement for maintaining levels of tauD activity might have contributed to GI14 behaving as a conserved feature of the Bp genome . In other bacterial species , tauD is required to metabolize taurine as a sulphur source [54]–[55] . Experimental assays comparing the growth Bp and Bt strains confirmed that Bp also exhibits a significantly enhanced ability to efficiently utilize taurine as a sulphur source compared to Bt ( p = 0 . 002 , Figure 5E ) . The ability of Bp to metabolize taurine for sulphur utilization is specific , as Bp was unable to use taurine as an alternative carbon or nitrogen source , activities which are not mediated by tauD ( Figure S8 ) . Finally , to investigate the molecular response of Bp to taurine , we generated whole-genome transcriptome profiles of Bp exposed to high levels of taurine ( 250 uM ) . Here , the taurine concentrations used were based on previous reports studying taurine metabolism in E . coli [54]–[55] . Compared to Bp grown in standard laboratory media , taurine-exposed Bp exhibited transcriptional up-regulation of ∼280 genes , of which 40% ( 126 genes ) have been previously associated with pathogenicity , host–cell interaction , or survival in diverse and challenging environments [1] . Specific examples of taurine-regulated genes implicated in virulence included several flagella gene clusters ( BPSL0024-BPSL0032 , BPSL0224-BPSL0236 , BPSL0266-BPSL0282 , BPSL3288- BPSL3330 ) [56] , siderophore biosynthesis and iron metabolism genes ( BPSL1771- BPSL1787 , BPSS0239- BPSS0244 , BPSS0581- BPSS0588 ) [57] , and fimbrae/pili ( BPSL2026- BPSL2031 , BPSS1593- BPSS1605 ) [45] ( Figure 5F , Table S9A and S9B ) . Taken collectively , these findings suggest that altered taurine metabolism likely mediated by tauD may represent a species-specific adaptation of Bp that may have also facilitated its ability to survive in infected mammalian hosts [58] .
In this , the first nucleotide-scale comparative analysis of multiple Bp genomes , we expanded the known gene repertoire of Bp , defined the BpCG , and described the extent of genetic variation in BpCG genes . We identified a set of genes exhibiting positive selection , and examined how such variations can impact genomic organization and structure . Our results suggest that a significant proportion of the BpCG may be experiencing functional selection , and that a large aspect of this selection involves the modification of preexisting metabolic circuits related to carbohydrate and secondary metabolism . Importantly , we also provide evidence that a subset of these genes may have also facilitated the ability of Bp to interact with mammalian hosts , either structurally or nutritionally . In our analysis , we have proposed that many of the genetic alterations observed in the positively selected genes were primarily driven by environmental pressures outside the human or mammalian host . Nevertheless , if Bp undergoes cryptic cycling through normal humans or other potential mammalian hosts , such as livestock or wild cattle [59] , it remains possible that certain survival and virulence traits were directly selected for in mammals . In melioidosis-endemic NE Thailand , the majority of healthy individuals have antibodies to Bp by the age of 4 years , indicating constant exposure to the bacterium that may occur by inoculation , inhalation or ingestion [4] . Within such hosts , Bp might spend periods of time being exposed to the mammalian immune response and various physiologic traits . Subsequent return to the environment in a viable state , through skin desquamation or in urine and stool , could also lead to the selection of factors that promote survival in vivo . However , because we a ) consider the mammalian host to be a relatively minor component of Bp ecology , b ) such cryptic cycling through mammalian hosts has yet to be documented , and c ) the lack of genetic variation between the primary and relapsed strains suggests that the Bp genome is likely to exhibit a high degree of stability during mammalian infection , we argue that this scenario is , on balance , possible but less likely . A large proportion of Bp genes are still unannotated or poorly characterized , raising the need for systematic approaches to link discrete sets of Bp genes to their specific biological and cellular functions . The genomic identification of these positively selected genes should facilitate the process of targeted experimentation to elucidate the pathogenesis of melioidosis . The prioritization of candidate genes for targeted experimentation is particularly relevant for Bp due to its classification as a potential biothreat agent . Under international biosafety regulations , Bp research is typically conducted in high containment ( Category 3 ) facilities and limited to highly focused projects [60] ( http://www . selectagents . gov/ ) . Finally , it is worth noting that the ability of this approach to uncover candidate host interaction genes and pathways from a genome as complex as Bp suggests that similar approaches should prove equally fruitful in elucidating novel aspects of biology in other recently emergent pathogens as well .
This research was approved by the Genome Institute of Singapore Institutional Review Board . All animal experimentation was conducted at DSTL ( Defence Science and Technology Laboratory ) in the United Kingdom ( UK ) under Animal ( Scientific Procedures ) Act 1986 . Bp genes were predicted using FGENESB [http://linux1 . softberry . com/berry . phtml ? topic=fgenesb&group=help&subgroup=gfindb ( Softberry ) ] . tRNA genes were identified using tRNAScan-SE [20] , and rRNA genes by sequence conservation ( blastn , e-value threshold: 1e-08 ) . Operons were identified based on a ) distances between genes , b ) likelihood of neighboring genes also appearing in other bacterial genomes as neighbors , and c ) locations of predicted promoters and terminators . Genes were annotated against the NR , COG , KEGG and STRING [www . ncbi . nlm . nih . gov ( NR ) ; www . ncbi . nlm . nih . gov/COG ( COG ) ; www . genome . jp/kegg ( KEGG ) ; http://string . embl . de/ ( STRING ) ] databases using the following criteria: i ) BLASTP e-value threshold of <1e-10; ii ) percent identify threshold of >60% , and iii ) a percentage coverage threshold of 80% . These criteria were used based on previous studies [18]–[19] . Ribosome binding sites ( RBSs ) were identified using RBSfinder [22]–[24] . Notably , the consensus RBS sequences between E . coli and Bp are similar [25]–[26] . Non-coding RNAs were identified using the Rfam database [17] . CodonW ( http://codonw . sourceforge . net/ ) was used to identify codon adaptation indexes ( CAI ) , Kyte and Doolittle scales of hydrophobicity [27] , GC percentages and gene lengths . Multiple whole-genome alignments were performed using Mauve 2 . 2 . 0 [61] . Bp K96243 cultures were isolated from six conditions: Luria-Bertani broth ( mid-logarithmic , early stationary and late stationary phases , conditions 1–3 ) , minimal media ( mid-log and early stationary , conditions 4–5 ) , or exposure to 1x PBS solution ( condition 6 ) . Bacterial mRNAs were profiled on a high-density Bp tiling array representing both strands of the Bp K96243 genome ( 7 . 2 Mb ) ( Nimblegen ) ( 50-mers , 15-base overlap ) . All transcriptome profiles are the average of 2 biological replicates . Three distinct criteria were employed to consider a novel gene as “expressed” . First , an “expressed” novel gene was required to exhibit a minimum of 3 consecutive array probes with fluorescence intensities above the array median intensity . Second , for genes covered by more than five array probes , the combined pseudo-median expression value of the novel gene was assessed using the SIGN Test , a statistical method previously used to measure the transcriptional activity of genes using tiling microarrays [16] . Only novel genes passing the SIGN test were considered as “expressed” ( p<0 . 05 ) . Third , short novel genes covered by less than five probes that did not qualify for the SIGN Test were manually curated to confirm the presence of contiguous expression signals for each gene . For analyses of differential gene expression , ratios of normalized probe signals were computed . Probe identities with more than 2-fold up-regulation or down-regulation were matched to Bp gene identities . Genes that have 50% or more probes showing at least 2-fold up-regulation or down-regulation were taken as differentially expressed between the conditions compared . Gene orthologs across the Bp genomes were determined using OrthoMCL [62] . An all-against-all BLASTp [63] was performed , followed by a reciprocal BLAST to define putative ortholog pairs or recent paralogs ( genes within the same genome that are reciprocally more similar to each other than any sequence from another genome ) . Reciprocal BLASTp values were converted to a normalized similarity matrix that was analyzed by the Markov Cluster algorithm MCL to define ortholog clusters . OrthoMCL was run with a BLAST e-value cut-off of 1e-5 , and an inflation parameter of 1 . 5 . The OrthoMCL output was used to construct tables of shared orthologs and strain-specific genes . Orthologs exhibiting positional conservation across the Bp genomes were aligned at the DNA level with ClustalW [21] and manually confirmed . SNAP . pl was used to calculate the number of synonymous vs . non-synonymous base substitutions ( Nei and Gojobori method ) for all pairwise comparisons of ortholog sequences [40] . Ambiguous codons or codons with insertions were excluded from the tally of compared codons . Base-substitutions were also manually inspected to remove from consideration substitutions indirectly caused by upstream frame-shifts . GENECONV [41] was used to identify recombination breakpoints , and genes exhibiting a recombination signature were fragmented at the predicted breakpoints . The recombination sub-fragments ( total 152 sub-fragments ) were individually applied to the PHYLIP pipeline to infer maximum parsimony trees . The core gene alignments were also tested for the presence of recombination using the Pairwise Homoplasy Index ( Phi ) as implemented in the HYPHY package ( 100000 permutations , cutoff at ∼1% FDR ) [42] . ClonalFrame version 1 . 1 was used to compute rho/theta , the recombination/mutation ratio [43] . Protein sequences were aligned using ClustalW ( ‘ktuple’ ⇒ 2 and ‘matrix’ ⇒ ‘BLOSUM’ ) . PAL2NAL [64] Perl scripts were used to convert the multiple sequence protein alignments and corresponding DNA sequences into codon alignments . Maximum parsimony ( MP ) trees were generated using PHYLIP ( ‘dnapars’ module ) using default values ( http://evolution . genetics . washington . edu/phylip . html ) . Codon alignments and MP trees were analyzed by PAML 4 . 0 [38] to calculate Ka/Ks ( or ω ) ratios and test different evolutionary models . The following nested models were used: M1a-M2a and M7-M8 [39] . A likelihood ratio test was used to compare model M2a with M1a , and model M8 with M7 , at a significance cutoff of ∼2% FDR [38] . The nested model M0 ( one-ratio ) -M3 ( discrete ) was also used to confirm heterogeneity of Ka/Ks in the cohort of positively selected genes [65] . Isogenic unmarked mutant Bp strains carrying a 3 . 7 kb deletion of the TFP4 gene cluster were generated as previously described in Boddey et al . , 2006 [66] . Briefly , a TFP4 ( BPSL2749-BPSL2755 ) targeting vector was constructed and conjugated into Bp K96243 . Integrants were selected on chloramphenicol plates ( 100 ug/ml ) and confirmed by PCR . Merodiploid integrants were then cultured without selection and plated onto medium lacking sodium chloride but containing 15% sucrose to enrich for colonies carrying a deleted chromosomal locus . Bp TFP4 mutants were confirmed both by PCR and Southern blotting . Virulence of wild-type and mutant Bp strains were assessed using an intranasal BALB/c mouse model as previously described [45] . Briefly , groups of six age-matched BALB/c female mice were anesthetized and infected intranasally with 10-fold dilutions ( 101–106 ) of either wild-type Bp K96243 or TFP5 deletion strains grown overnight at 37degC with shaking . Mice were recovered and survival was recorded for up to 51 days . The survival data was analyzed using the Mantel-Haenszel log rank test in GraphPad Prism 4 or by Regression with Life Data in MIniTAB v13 . 0 , using a significance threshold of α = 0 . 05 . Positively selected genes were PCR-amplified from Bp genomic DNA and subcloned into Vivid Colors®pcDNA® 6 . 2/N-EmGFP-GW/TOPO® mammalian expression vectors ( Invitrogen ) . Hela cells were transfected using Gene Juice ( Novagen ) , and cultured for 24 h after tranfection . Cells were fixed in 3 . 7% paraformaldehyde/PBS ( pH 7 . 0 ) . After washing and preincubation , cells were stained with Alexa Flour 555 phalloidin ( Invitrogen ) and DAPI ( Sigma-Aldrich ) . Stained cells were visualized using a confocal Zeiss LSM 150 inverted laser scanning microscope and analyzed using Zeiss LSM Image Browser software ( Carl Zeiss , Oberkochen , Germany ) . 2 Bp and 2 Bt strains ( Bp K96243 , Bp 22 , Bt ATCC700388 and Bt E305 ) were cultured in modified M63 media , or media supplemented with 250 µM taurine or 250 µM Na2SO4 . Cultures were grown at 37°C , 150 rpm and OD600 readings were taken every 2 hrs for 72 hrs . To study differential gene expression , Bp K96243 was cultured in modified M63 medium with 250 µM taurine at 37°C , 150 rpm for 48 hrs to reach stationary phase . The expression profile obtained was compared with that obtained for Bp K96243 cultured in LB at stationary phase . All transcriptome profiles are the average of 2 biological replicates . | With recent advances in genomics now permitting the systematic comparison of dozens , if not hundreds , of closely related bacterial strains , the opportunity arises for developing novel approaches to identify the complete repertoire of molecular factors governing interactions between hosts and pathogens . We explored these approaches using the model system Burkholderia pseudomallei ( Bp ) , a Gram-negative bacterium that causes the tropical disease melioidosis . At 7 . 2 Mb , the Bp genome represents one of the most complex bacterial genomes sequenced to date . In this study , we present the first nucleotide-resolution comparative analysis of a panel of sequenced Bp strains . We identified a novel panel of genes demonstrating “positive selection” , referring to functional adaptations related to survival in soil , the natural reservoir of Bp . We propose a model and provide functional evidence that some of these genes may also have indirectly facilitated the ability of Bp to colonize and infect a mammalian host . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] | [
"infectious",
"diseases",
"computational",
"biology/genomics"
] | 2010 | A Genomic Survey of Positive Selection in Burkholderia pseudomallei Provides Insights into the Evolution of Accidental Virulence |
High content image-based screening was developed as an approach to test a protease inhibitor small molecule library for antiviral activity against Rift Valley fever virus ( RVFV ) and to determine their mechanism of action . RVFV is the causative agent of severe disease of humans and animals throughout Africa and the Arabian Peninsula . Of the 849 compounds screened , 34 compounds exhibited ≥50% inhibition against RVFV . All of the hit compounds could be classified into 4 distinct groups based on their unique chemical backbone . Some of the compounds also showed broad antiviral activity against several highly pathogenic RNA viruses including Ebola , Marburg , Venezuela equine encephalitis , and Lassa viruses . Four hit compounds ( C795-0925 , D011-2120 , F694-1532 and G202-0362 ) , which were most active against RVFV and showed broad-spectrum antiviral activity , were selected for further evaluation for their cytotoxicity , dose response profile , and mode of action using classical virological methods and high-content imaging analysis . Time-of-addition assays in RVFV infections suggested that D011-2120 and G202-0362 targeted virus egress , while C795-0925 and F694-1532 inhibited virus replication . We showed that D011-2120 exhibited its antiviral effects by blocking microtubule polymerization , thereby disrupting the Golgi complex and inhibiting viral trafficking to the plasma membrane during virus egress . While G202-0362 also affected virus egress , it appears to do so by a different mechanism , namely by blocking virus budding from the trans Golgi . F694-1532 inhibited viral replication , but also appeared to inhibit overall cellular gene expression . However , G202-0362 and C795-0925 did not alter any of the morphological features that we examined and thus may prove to be good candidates for antiviral drug development . Overall this work demonstrates that high-content image analysis can be used to screen chemical libraries for new antivirals and to determine their mechanism of action and any possible deleterious effects on host cellular biology .
Many RNA viruses are highly pathogenic to humans and can cause hemorrhagic fever and/or encephalitis . Among these , Rift Valley fever virus ( RVFV ) , a member of the genus Phlebovirus ( family Bunyaviridae ) , causes Rift Valley fever ( RVF ) that severely affects human and livestock throughout Africa and the Arabian Peninsula [1] , [2] . In humans , RVF is characterized by a flu-like illness that occasionally progresses to hemorrhagic fever , encephalitis , or ocular disease with a significant death rate [3] . In ruminants , RVF is characterized by a high rate of abortion in pregnant females ( 80–100% ) , as well as high mortality in younger animals [4] . RVF is a mosquito-borne disease transmitted by the bite of various species of mosquitoes or through direct contact with infected animals [5] , [6] . Similar to RVFV , Lake Victoria marburgvirus ( MARV ) , Zaire ebolavirus ( ZEBOV ) , Lassa virus ( LASV ) and Venezuelan equine encephalomyelitis virus ( VEEV ) are highly pathogenic viruses and classified as National Institute of Allergy and Infectious Disease ( NIAID ) category A priority pathogens . Marburgviruses and ebolaviruses , members of the family Filoviridae , as well as LASV , members of the family Arenaviridae , cause severe hemorrhagic fevers in humans and nonhuman primates with extraordinarily high case-fatality rates ( reviewed in [7] , [8] ) . VEEV , an alpha virus and member of Togaviridae family , causes severe encephalitis in horses and humans ( reviewed in [9] ) . RVFV , as with other highly pathogenic RNA viruses , including EBOV , MARV , VEEV and LASV , cause severe disease in many developing countries that already suffer from fragile economies and health care infrastructures . There is currently no U . S . Food and Drug Administration ( FDA ) approved therapeutic or prophylactic treatments for any of these agents , thus there is an urgent need for research to develop effective new drugs and vaccines to combat these diseases . Recent advancements in high content image ( HCI ) -based screening ( HCS ) technologies have contributed greatly to increasing the efficiency of the drug discovery process . HCS utilizes automated high-speed , high-resolution microscopy and image analysis to measure morphological changes in the cells in a quantitative and high-throughput manner [10] . Most importantly , HCI-based analysis enables simultaneous measurement of multiple features of cellular biology that are relevant to therapeutic and cytotoxic characteristics of potential antiviral compounds . As a result , HCI-based analyses not only allows for rapid screening of compounds , but can provide early insights into their cytotoxicity and mode of action , thereby facilitating the decision-making processes that govern the progression from a candidate compound to a successful antiviral drug . RVFV is an enveloped spherical virus with containing a has a tri-segmented , single-stranded RNA genome , which encodes for the RNA-dependent RNA polymerase ( RdRp ) , envelope glycoproteins ( Gn/Gc ) , nucelocapsid proteins ( N ) and non-structural proteins including NSs and NSm [11] . Virus entry into cells is mediated by the binding of the envelope glycoproteins ( Gn/Gc ) to an unknown cell surface receptor which mediates virus endocytosis . Acidification of the virus-containing endocytotic vesicle promotes virus-host membrane fusion and results in the release of the encapsidated genome and RdRp into the cytoplasm , where transcription and replication of the viral genome occurs [12] . The glycoproteins Gn and Gc form a heteromeric complex and localize in steady-state to the Golgi apparatus due to a Golgi localization signal on Gn [6] , [10] , [13] . Multiple interactions between the glycoporteins , the encapsidated viral genome , and remaining structural proteins are believed to cause a change in membrane curvature leading to virus budding into the Golgi lumen [14]–[16] . Although the exact mechanism is not known , based on knowledge from other bunyaviruses , it is possible that the release of the virus-filled vesicles from the Golgi and its subsequent fusion with cell plasma membrane , releases mature virions into extracellular medium . During the past two years , small molecule libraries containing compounds related to currently marketed drugs with known targets; mostly targeting kinases , phosphatases , or G protein coupled receptors; have been used with high throughput or HCI-based screening for antiviral drug discovery [17]–[19] . However these studies in which HCI analysis was used primarily focused on assay development and optimization specifically for determining the antiviral activity of the compounds and were not applied for the determination of the compound's mechanism of action [18] , [19] . Proteases constitute one of the largest drug target enzyme families , and their promise has been demonstrated by several successful drugs on the market , including the angiotensin converting enzyme inhibitors and anti-HIV protease inhibitors ( reviewed in [20] ) . Many other drugs targeting key proteases involved in various diseases are predicted to reach the market in near future . Despite their success as drugs in the marketplace , to our knowledge , no studies using a protease inhibitor library and HCI-based analysis to screen for their antiviral activities have been previously reported . Here we describe the development and application of HCS to test a protease inhibitor library of 849 small molecules for antiviral activity against multiple pathogenic RNA viruses and to determine their mechanism of action for RVFV .
HeLa , Vero and Vero E6 cells were obtained from the American Type Culture Collection ( ATCC ) and maintained in Dulbecco's Modified Eagle Medium ( Life Technologies , USA ) supplemented with 10% fetal bovine serum ( FBS , Life Technologies , USA ) . Human small airway epithelial cells ( HSAECs ) ( Lonza , USA ) were maintained under humidified conditions at 37°C , 5% CO2 in Ham's F12 medium supplemented with nonessential amino acids , pyruvate , β-mercaptoethanol and 10% fetal calf serum ( FCS ) . RVFV strains ZH548/MP-12 ( MP-12 ) and ZH501 were obtained from The Salk Institute's Government Services Division and from Dr . Michael Turell ( USAMRIID ) , respectively . RVFV strain MP12 was derived from a virulent strain of RVFV ( ZH548 ) and is highly attenuated in its virulence due to several nucleotide mutations in its genome , however , it retains its sensitivity to IFN-α [16] , [21] and can be handled safety under biosafety level ( BSL ) -2 laboratory conditions . ZH501 is the wild-type strain of RVFV and is fully virulent , requiring to be handled under BSL-3 laboratory conditions . VEEV ( 1CSH3 ) , LASV ( Josiah ) , EBOV ( Zaire ) and MARV ( Ci67 ) were obtained from the USAMRIID collection and were propagated in Vero cells . Virus-containing supernatant was clarified by centrifugation at 12 , 000×g for 30 min prior to storage at −80°C . All virus stock titers were determined by plaque assay on Vero E6 cells as previously described [22] . Work with infectious filoviruses or arenaviruses were performed under BSL-4 laboratory conditions . RVFV ZH501 and VEEV infections were performed in a BSL-3 lab , and RVFV MP12 infections were performed under BSL-2 conditions . HeLa cells were infected with virus at the indicated MOIs . Inocula were removed after 1 h , unless stated otherwise , washed one time with 1× PBS , and replaced with the same amount of fresh medium . Infection was allowed to proceed for a specific duration of time , as indicated for each experiment . At the end of the incubation time , culture supernatants were collect to determine the virus yield by plaque assay . Alternatively , virus-infected cells were fixed in 10% neutral buffered Formalin ( Sigma ) for 3 days for BSL-3/4 viruses or 15 min for BSL-2 viruses . ChemDiv was the source of the Serine/Cysteine Protease ( SCP ) inhibitor library used in this study . ChemDiv built the library using a variety of computational programs to qualify a small molecule as a potential SCP ligand ( reviewed in [23] ) . Basically , their method applied a set of pre-selected descriptors for encoding the molecular structures , and a trained neural network to qualify the molecules as potential SCP ligands . The molecular requirements were profiled by using available databases of active SCP and non-SCP-active agents . The library was composed of 849 compounds in a 96-well plate format and was used in both primary and secondary screening assays . For subsequent mechanism of action studies , compounds were reordered ( ChemDiv , USA ) at least three different times and tested independently to ensure consistency across batches . Reference reagents included human interferon-α2a ( IFN-α ) ( PBL Interferon Source , USA ) , ribavirin ( Sigma ) , Brefeldin A ( cat # B-7450 , Life Technologies ) and Nocodazole ( cat # M1404 , Sigma ) . All compounds from the ChemDiv protease inhibitor library and ribavirin were prepared in 100% dimethyl sulfoxide ( DMSO , Sigma-Aldrich , USA ) at 8 mM stock solution and stored at −20°C . IFN-α was prepared in Dulbecco's phosphate-buffered saline ( DPBS , Sigma-Aldrich , USA ) containing 5% FBS . An immunofluorescence assay ( IFA ) was used to visualize RVFV-infected cells . Briefly , cells were fixed with Formalin ( 10% ) for 15 min at room temperature . To permeabilize cells , Formalin-fixed cells were treated with 0 . 1% ( v/v ) Triton-X 100 for 15 min at room temperature . RVFV-infected cells were by visualized by staining with 4D4 mAb prepared in blocking buffer containing 3% BSA/PBS . The mAb 4D4 binds to the Gn portion of the RVFV glycoprotein and was purified from the hybridomas at USAMRIID . The following antibodies , R3-1D8-1-1a , 1A4A-1 , 6D8-1 , MBG II 9G4-1 and L52-161-6 were used to detect , RVFV nucleocapsid ( N ) , VEE envelope 2 ( E2 ) protein , EBOV glycoprotein ( GP ) , MARV GP and Lassa virus GP , respectively . Antibodies for cellular protein detection including Histone 3 phospho Serine 10 ( cat #9710; Cell Signalling ) , alpha-Tubulin ( cat #T9026; Sigma ) and Alexa Fluor 488 phalloidin ( cat # A12379; Life Technologies ) were used at 1∶1000 dilution according to vendors' specifications . Cell nuclei and cytoplasm were labeled with Hoechst 33342 ( Life Technologies , USA ) and HCS CellMask Red or Deep Red ( Life Technologies , USA ) , respectively , at a 1∶10 , 000 dilution . Golgi apparatus was visualized using CellLight Golgi-GFP ( Life Technologies , USA ) , a modified baculovirus expressing a fusion construct of a Golgi marker and green florescent protein . Alexa 488-conjugated goat anti-mouse secondary antibody , Alexa 568-conjugated goat anti-rabbit antibody or Alexa 647-conjugated goat anti-rabbit ( 1∶1 , 000; Life Technologies , USA ) were used to visualize primary antibodies . The ChemDiv protease inhibitor library was screened against RVFV strain MP12 at 20 µM in 0 . 5% ( v/v ) DMSO . Screening was performed in triplicates wells of a 96-well plate . HeLa cells were treated with compound for 2 h prior to virus infection . After virus infection , cells were washed with PBS 1× , and media containing the compound was added back to the cells and remained for the duration of the infection ( 24 h ) . To test the potential broad-spectrum antiviral activity of the primary hit compounds , HeLa cells were treated with the compounds in the same way as in the primary screen and infected with multiple RNA viruses as described below . The multiplicity of infection ( MOI ) and duration of infection for each virus were optimized to achieve an infection rate of 40–60% and were as follows: RVFV ZH501 ( MOI = 1 for 24 h ) , EBOV ( MOI = 3 for 48 h ) , MARV ( MOI = 3 for 48 h ) , LASV ( MO1 = 1 for 24 h ) , and VEEV ( MOI = 0 . 5 for 20 h ) . Mock-infected HeLa cells were considered as negative controls , and wells in which the cells were infected with virus , but treated with 0 . 5% DMSO were considered as positive controls . Compound activity based on percent inhibition and cell toxicity was assessed by IFA and image analysis as described below . Data were plotted in Excel to generate a heat map using “color scales” in the conditional format menu . Scatter plot distribution was generated using TIBCO Spotfire 4 . 5 . 0 ( TIBCO Software , USA ) . Confocal images were collected using a Leica TCS-SP5 confocal/multiphoton microscope . High-content quantitative imaging data were acquired and analyzed on an Opera confocal reader ( model 3842 [Quadruple Excitation High Sensitivity] or model 5025; PerkinElmer ) at two exposures using a 10× air objective or 40× water objective . Analyses of the images were accomplished within the Opera or Columbus environment using standard Acapella scripts . The statistical reliability of the RVFV MP12 infection was evaluated by calculating for the Z′-factor using the formula: 1−[ ( 3σp+3σn ) /|μp−μn| ) ] , where μp , σp , and μn , σn are the mean ( μ ) and standard deviations ( σ ) of both positive ( p ) and negative ( n ) controls [20] . The mock-infected and RVFV-infected HeLa cells were used as negative and positive controls , respectively . Percentages of infected cells were normalized with mock-infected and RVFV-infected cells which were considered as 100% , and the values obtained were subtracted from 100 to determine the percent infection inhibition . The same formula was used for all percent infection inhibition calculations unless specified differently . For primary screening , Z′-factor ≥0 . 5 was used to validate the results of the assay . The hit ( i . e . , a compound that demonstrates inhibition of virus infection ) selection criteria for the primary screening was set at ≥50% inhibition of RVFV infection . Dose response curve analysis was used to confirm hit compound activity against RVFV , VEEV , EBOV , MARV and LASV . Briefly , HeLa cells were seeded at a concentration of 2×104 cells per well in a 96-well plate . After an overnight incubation at 37°C , hit compounds and references compounds , except for IFN-α , were tested in a 10-point dose-response curve ( 2-fold serial dilution from 200 µM ) assay . IFN-α , was used as reference only in RVFV infections . The assay was performed in the same manner as the primary screening assay described above . Cells subjected to IFN-α were incubated with media containing serial dilutions ( 2-fold from 3000 units/mL ) of IFN-α for 16 h ( or overnight ) prior to the start of virus infection . Two hours post-infection , cells were washed ( one time with 1× PBS ) and fresh medium was added back . At the end of virus incubation , cells were fixed and subjected to IFA to visualize the corresponding viral antigen expression as described in the secondary screen above . Each concentration of the hit compound was tested in triplicate . Percent infection inhibition was determined normalizing the percentage of infected cells in compound treated cells with mock treated ( 0 . 5% DMSO ) and virus infected cells . Data generated from the image analysis of the dose response curve assay were plotted and analyzed using the non-linear regression formula: log ( inhibitor ) vs . response –variable slope ( 4 parameters ) in GraphPad Prism 6 . The EC50 , defined as the effective concentration resulting in a 50% inhibition of virus infection , was used to evaluate compound activity . Compound toxicity was determined by normalizing cell number of compound treated+virus-infected cells with mock treated ( 0 . 5% DMSO ) +virus-infected cells , which were considered as 100% . The CC50 value , defined as the compound concentration resulting in a 50% reduction in cell viability ( based on normalized data ) compared with mock infection was used to evaluate cell toxicity . The relative effectiveness of the compound is defined in terms of its selectivity index ( SI ) , a value that indicates the relationship between the compound's effective and toxic concentrations , and is calculated as: SI = CC50/EC50 . It is therefore desirable for a compound to have a high SI value , indicating maximum antiviral activity and minimal cell toxicity . HeLa cells at a concentration of 2×104 cells per well in a 96-well plate were either mock-infected or treated with compound 2 h prior to infection ( pre ) , concurrent with virus infection ( 0 h ) , or at various time points post-infection as indicated in the experiment . Cells were infected with RVFV strain MP12 at an MOI of 10 for 1 h at 4°C . After the 1 h incubation , cells were washed one time with 1× PBS to remove unattached virus and incubated at 37°C with complete media for the duration of the experiment . After 13 h , cells were fixed in 10% Formalin and immunostained to detect viral G protein expression . Experiments were performed in triplicate and the average ( ± standard deviation ) of three independent experiments is shown . RVFV RNA yields were determined by Quantitative RT-PCR ( qRT-PCR ) using TaqMan-based probe sequences as previously described [24] . In brief , total RNA from supernatants or cells were prepared using a MagMax 96 RNA extraction kit ( Life Technologies ) or RNeasy Plus minikit ( Qiagen ) respectively following manufacturer's instructions . Purified RNA was then measured with a Quant-IT RiboGreen RNA assay kit ( Life Technologies ) of which fifty nanograms of RNA was used in the assays . qRT-PCR assays were then performed on an ABI Prism 7900HT sequence detection system with an RNA UltraSense one-step kit ( Life Technologies ) and TaqMan probes ( Applied Biosystems ) according to the manufacturers' instructions . Serial 10-fold dilutions of the assayed virus ( 102 to 107 copies ) were used as standards . The viral RNA levels from cell extracts was normalized with the PPIB housekeeping gene . Four wells of a 96 well plate were used to generate one data point and the experiment was done in triplicates . Relative expression levels were determined using the comparative threshold cycle ( CT ) method [25] . A HeLa cell line stably expressing RVFV Gn-Gc polyprotein , referred as HeLa-G was made by transfecting HeLa cells with the expression vector pCAGGS containing the open reading frame of RVFV Gn and Gc genes ( kindly provided by Dr . Shinji Makino [26] ) and an empty pcDNA3 . 1 vector expressing a neomycin selection marker at a 8∶1 ratio followed by selection using Geneticin ( G418; Life Technologies , USA ) , an analog of neomycin sulfate , at a concentration of 400 µg/mL . Isolated clones expressing RVFV Gn protein were verified by IFA and western blots analysis . RVFV-Gn localized to Golgi complex and serves as a Golgi marker . Thus HeLa-G cells were used to quantify changes in Golgi phenotype . HeLa-G cells were seeded at 1×104 the day before the experiment . Cells were mock treated or treated with hit compounds for 12 h , with the exception of IFN-α2a , in which cells were treated overnight prior to start of the experiment . Following treatment , cells were fixed in 10% Formalin , permeabilized with 0 . 1% Triton-X-100 and immunostained to detect Gn protein expression . Subsequently cells were also stained with Hoechst for nuclear detection . Images were acquired on Opera using 20× air objective , and the images were analyzed with Columbus High Content Imaging software . Individual cells were segmented based on the Hoechst nuclear stain using the “Find Nuclei” building block and using “Select Cell Region” building block , a ring region of 15 pixel width was then created around the individual nuclei that was further masked to classify them as cells . A common boundary was drawn connecting the individual Golgi stacks appearing as spots and spaced less than 2 pixels apart to create a “Golgi mask . ” Subsequently , the area of the Golgi mask was evaluated and only those with surface area ≥100 pixels were considered as “intact Golgi . ” Percent Golgi was determined by normalizing “Golgi number” per field with the “number of nuclei” in the same field , and the resulting values were then normalized with vehicle control ( 0 . 5% DMSO ) treated cells . The values obtained were plotted and analyzed using the non-linear regression formula: log ( inhibitor ) vs . response-variable slope ( 4 parameters ) in GraphPad Prism 6 . The GC50 was defined as the effective concentration resulting in a 50% reduction in Golgi numbers . HeLa cells were either mock treated ( 0 . 5% DMSO ) or treated with BFA ( 50 ng/mL ) for 15 min or nocodazole ( 33 µM ) for 5 h or D011-2120 ( 50 µM ) for 4 h and fixed in 10% Formalin , permeabilized with 0 . 1% Triton-X-100 , and immunostained with tubulin antibody . Subsequently , cells were stained with nuclear Hoechst ( 33342 ) dye and Deep red ( Cell mask ) . Images were acquired on an Opera System using a 40× air objective and exported to Columbus High Content Imaging and Analysis Software . Individual cells were segmented based on the Hoechst nuclear stain using the “Find Nuclei” building block and the cell mask deep red stain using “Select Cell Region . ” To quantify tubulin phenotype , texture analysis was performed using the Columbus software and the “SER Features” method . The “SER Features” method analyzes the occurrence of typical patters in the intensity structure of an image . The “Ridge Value” was selected as this feature showed the most difference in the intensity pattern of mock-treated vs . nocodazole-treated cells . The ridge values were collected from 4 fields and 3 wells for each condition , and the values were normalized with control treated cells , which were considered as 100% .
HeLa cells were considered the optimal cell line to use for assay development as the cells are permissive to RVFV infection , are the optimal size for image analysis , possess a functional interferon response , and they are relatively easy to grow . Selection criteria for the appropriate cell seeding density included having a sufficiently high number of cells but with enough spatial distribution for proper identification during image acquisition . After testing various seeding densities of HeLa cells , the seeding density of 2×104 cells per well was selected as minimal variations among replicates were noted without compromising proper segmentation of cells ( data not shown ) . RVFV infection in HeLa cells was visualized by IFA detection of the RVFV Gn protein using the 4D4 mAb and confocal imaging using the Evotec Technologies High-Throughput Cell Analyzer Opera ( Fig . 1A ) . Expression of this protein on the cell surface is indicative of virus egress from the infected cell . For the RVFV infection , a MOI of 1 . 0 and incubation time of 24 h was used since it achieved an infection rate of ∼60% and allowed multiple rounds of virus replication that facilitated the screening of active compounds that target different stages of virus life cycle . Finally , the RVFV infected cells were classified as those cells having G signal within the defined boundaries of a cell and greater than a pre-defined threshold level . Several additional parameters ( ∼50; data not shown ) were acquired from the images , some of which include the nuclear and cytoplasmic intensities of the G signal , nuclear size and nuclear intensities . However , for the screening purposes described in this section , only cell number and the infected cell number was used to determine the percentage of infected cells . The Z′-factor was evaluated to test the robustness of the assay in the 96-well plate format . Figure 1B shows a representation of the validation process done for the RVFV infection in HeLa cells . Cells were dispensed in a 96-well plate and half ( 48 wells ) were mock-infected ( 0 . 5% DMSO only ) while the other half were infected with RVFV . Mock-infected wells were considered as negative controls , while RVFV-infected wells as positive controls . After the viral infection period and IFA , image analysis of the acquired images revealed the infection percentage , cell number based on cell nuclei detected , and other pre-defined parameters . The Z′-factor was calculated using average and standard deviations of the percent infection of the positive and negative controls as described in methods section [27] . The experiment was performed in triplicate on three separate days , and the calculated Z′-factor was 0 . 62 . A Z′-factor ≥0 . 5 indicates a statistically reliable separation between positive and negative controls . A total of 849 compounds from ChemDiv protease inhibitor library were used for antiviral screening . The library was screened at 20 µM concentration against RVFV and primary hits were selected based on the criteria: ≥50% inhibition and ≥50% cell number compared to positive controls . Figure 2 shows a scatter plot of the primary screening data where percent infected cells were normalized with mock-treated RVFV-infected cells to determine the percent infection inhibition ( see methods ) . Thirteen separate master compound plates were used and are represented as separate colors in Figure 2 . Many of the hit compounds clustered together on the scatter plot since the compounds were grouped together on the plate by primary chemical structure . Sixty-one compounds were initially selected as primary hits ( exhibiting ≥50% inhibition ) , although we suspected some of these may be due to edge well effects . Upon repeat screening , the compounds with suspected edge well effects proved not to be active and were eliminated from subsequent analysis . Thus , a total of 34 compounds ( 4 . 0% ) exhibited ≥50% inhibition against RVFV ( shown above the black horizontal line at 50% infection inhibition in Figure 2 ) . In order to determine if the primary hits had broad-spectrum activity against other highly pathogenic RNA viruses , they were further screened against multiple viruses , including EBOV , MARV , VEEV , LASV , and the virulent RVFV ZH501 strain , in addition to MP12 . Figure 3A shows the generated heat map of percent virus infection inhibition and percent cell viability . As can be seen in the heat map , most of the compounds had varying degrees of activity across the multiple RNA viruses tested . The 34 primary hit compounds were classified into four distinct groups based on their primary chemical structure as shown in brackets in Figure 3A . Four compounds , each comprising a unique primary chemical structure ( Fig . 3B ) , were selected based on activity against three or more of the viruses tested ( Fig . 3A ) . All other primary hit compounds were chemical analogs of these four compounds . These compounds were selected for further study to determine their EC50 , CC50 , SI , and mechanism of action against RVFV . Antiviral activities of the four hit compounds against RVFV were determined by dose response curve analysis in HeLa cells . The EC50 , CC50 and SI were determined for the four compounds and two reference compounds , ribavirin and IFN-α2a , known inhibitors of RVFV . Figure 3C shows the dose response curve analysis of the four hit compounds and two reference compounds , with percent infection normalized against RVFV-infected HeLa cells . All compounds tested showed inhibition of RVFV-infected HeLa cells in a dose-dependent manner ( Fig . 3C ) . Furthermore , all compounds tested had a SI of greater than 1 , indicating that the virus inhibitory effects were apparent before the cytotoxic effects appeared . G202-0362 had the lowest effective dose ( EC50 = 13 . 6 µM ) , and significantly , appeared to have no toxic effects on the HeLa cells at the concentration used in the experiment ( Table 1 ) . C795-0925 had a similar effective dose ( EC50 = 14 . 4 µM ) , albeit the compound was more toxic to cells ( CC50 = 56 . 7 µM ) compared to G202-0362 . D011-2120 had the highest effective dose ( EC50 = 61 . 5 µM ) and consequently the lowest SI ( 1 . 5 ) ( Table 1 ) . The effective doses of ribavirin and IFN-α inhibited RVFV were consistent with what has been reported in the literature [17] , [28] , [29] . In order to examine the potential that the inhibitory effects of these compounds were due to an artifact of using a cancer cell line ( HeLa ) , we repeated the screens of these four compounds and references compounds against RVFV-infected human small airway epithelial ( SAEC ) cells , a primary cell line derived normal human lung tissue . The effective doses of all the compounds , except for IFN-α2a , were similar to those observed in HeLa cells ( Table 1 ) . IFN-α was approximately 10-fold less effective against RVFV infection in SAEC compared to in HeLa cells . IFN-α has several targets in mammalian cells and therefore , although highly effective , is not an ideal model to compare with other drugs . Interestingly for C795-0925 , while the EC50 was comparable between the two cell lines , the compound was less toxic to SAEC ( CC50 = 110 . 6 µM ) . The hit compounds' potency against other pathogenic viruses including VEEV , EBOV , MARV and LASV were further evaluated by does response analysis ( Table 2 ) and compared to ribavirin's antiviral activity . In VEEV infections , all 4 compounds were more potent than ribavirin ( a broad spectrum antiviral agent ) while C795-0925 was most potent among all with EC50 = 10 . 2 µM . G202-0362 was most potent in filoviruses EBOV and MARV with EC50 = 16 µM and 34 µM respectively and more potent than ribavirin . However , in LASV infections , ribavirin was most effective compared to all 4 compounds . Collectively , these data show that these compounds were effective against more than one virus . RVFV infection follows an ordered sequence of steps that can be visualized using IFA for the early nucleocapsid ( N ) and late glycoprotein ( Gn ) expression in infected cells [28] . Compounds targeting any stage of the viral life cycle should alter either the kinetics or localization of viral protein expression . Thus we used time-of-addition ( ToA ) assays , adding compounds at various time points before or after virus infection , combined with HCI analysis to determine at which stage of the viral life cycle the compound is acting . To examine the kinetics of N , Gn , and cell surface exposed Gn ( referred to as S-Gn ) expression , HeLa cells were infected with RVFV MP12 virus ( time = 0 h ) , and the percent of cells expressing N , Gn , and S-Gn were determined by IFA at 4 , 6 , 8 , 10 , and 12 h post-infection ( PI ) . N protein expression was apparent at 4 h PI and steadily increased throughout the 12 h infection cycle , at which time approximately 70% of the cells expressed the protein ( Fig . 4A ) . Gn expression was first apparent at 8 h PI and steadily increased throughout the infection cycle to a peak of approximately 40% of the cells expression the protein at 12 h PI . Cell surface exposed Gn ( S-Gn ) protein expression is indicative of virus egress . Consistent with this , S-Gn was first apparent at 10 h PI and peaked at 12 h PI in approximately 25% of the cells ( Fig . 4A ) and corresponds to one round of replication of the RVFV life cycle [28] . Release of virus into the extracellular medium was further confirmed by quantitative PCR analysis ( Q-PCR ) and plaque assay ( data not shown ) . Compounds targeting virus entry or virus replication will show aberrant kinetics in the cytoplasmic expression of N and Gn . Alternatively , if the compound only targets virus egress then changes in the kinetics of S-Gn expression , and not cytoplasmic Gn or N expression , should be observed . Therefore , the kinetics of viral N , Gn , and S-Gn expression in the presence of compound was examined . The percentage of cells expressing N , Gn or S-Gn upon compound treatment was normalized with mock treated and infected cells , which was considered as 100% ( Fig . 4B ) . Treatment with all compounds significantly reduced the expression of S-Gn by 70–100% , indicative reduction of infectious virus getting to the cell surface . However , treatment with F694-1532 and C795-0925 also significantly reduced expression of N and Gn , suggesting these compounds exhibited their effects earlier in the virus life cycle . While treatment with D011-2120 and G202-0362 reduced S-Gn expression approximately 90% , they had only minor effect ( ∼10% reduction ) on N and Gn expression ( Fig . 4B ) . These data suggest that D011-2120 and G202-0362 are targeting virus egress , while F695-1532 and C795-0925 may be targeting steps earlier in the virus life cycle . To further define the stage of the viral life cycle the compounds are acting , compounds were added either 2 h prior to infection ( −2 h ) , at the time of infection ( 0 h ) , or 2 h post-infection ( 2 h ) . Acid conditions ( pH<5 . 0 ) inside the endocytosed virus-containing vesicles are necessary to promote virus-host membrane fusion [12] , [28] . Thus , we used NH4Cl ( 20 mM ) as a control as it targets the last stage of the virus entry pathway by neutralizing the pH inside the acidic compartments within the cell . Figure 4C shows that NH4Cl inhibited RVFV infection when cells were treated at early time points ( −2 h or 0 h ) , but not at the later time point ( 2 h ) , consistent with its role as an entry inhibitor . Conversely , levels of virus inhibition with each of the four hit compounds added 2 h PI were similar to levels of inhibition when the compounds were added at −2 h or 0 h . ( Fig . 4C ) . These data suggest that the observed inhibitory effects of the four hit compounds were not due to a block in the virus entry pathway . In order to examine how the compounds affect subsequent stages of the virus life cycle , compounds were added to virus-infected HeLa cells at 2 , 4 , 6 , 8 , 9 , 10 , 11 , 12 , or 12 . 5 h PI and the percentage of infected cells were evaluated at 13 h PI using IFA for S-Gn expression , which is indicative of virus egress . More than 50% of infection was rescued when F694-1532 or C795-0925 were added at 8 h or 9 h PI respectively ( Fig . 4D , marked with red arrows ) , which suggested that compounds mostly targeted viral RNA replication or viral protein expression . Not surprisingly , D011-2120 and G202-0362 , which appeared to target virus egress , did not recover restriction until late stages ( >10 h for 50% infection recovery ) . Collectively these data suggested that C795-0925 and F694-1532 targeted viral RNA transcription or protein synthesis and not virus entry or egress , while D011-2120 and G202-0362 targeted egress . To further confirm these observations , viral RNA levels were evaluated to determine compound mediated effects on RVFV life cycle as described below . The compound mediated effect on virus replication was determined by measuring the amount of viral RNA that accumulated inside infected cells or in their supernatants at the end of one life cycle . The viral RNA in the supernatants is a measure of virus egress . Cells were mock- treated or incubated with any of the four hit compounds beginning 2 hours prior to the start of infection . Twelve hours post-infection , the cell extracts or supernatants were collected separately , and the viral RNA levels were evaluated by qRT-PCR . The RNA levels in compound-treated cells were normalized with mock-treated cells to calculate the relative change in RNA levels ( Fig . 4E ) . Alternatively , in the duplicate experiment , cells were subjected to IFA of Gn and S-Gn protein expression . HCI was then applied to evaluate the percentage of cells expressing Gn or S-Gn , and the relative change was calculated . ( Fig . 4E ) . As expected , D011-2120 and G202-0362 treatments that targeted virus egress resulted in low levels of 9% and 28% , respectively of viral RNA accumulation in the supernatants as compared to 75% and 95% , respectively inside the cells . In contrast , viral RNA levels inside the cells and in the supernatants were similar for cells treated with C795-025 and F694-1532 . In addition , these data corroborated with the viral protein expression levels inside cells ( Gn ) or on the surface of cells ( S-Gn ) . Collectively , these data suggest that C795-0925 and F694-1532 targeted viral RNA transcription or protein synthesis , and not virus entry or egress , while D011-2120 and G202-0362 targeted egress . HCI was further applied to understand the mode of action as described below . RVFV envelope glycoproteins localize to the Golgi complex and mediate virion assembly and budding into the Golgi lumen [13] , [14] , [30] . Subsequently , based on similarities with other bunyaviruses , it is believed that virus egress occurs by the fusion of the virion-containing Golgi vesicles with the cellular plasma membrane . Because D011-2120 and G202-0362 appeared to target virus egress , HCA was applied to determine if the virus trafficking from the Golgi complex to plasma membrane was affected . Golgi complex was visualized by transducing cells overnight with baculovirus expressing fusion construct of a Golgi marker and green florescent protein ( GFP ) . RVFV G expression in cytoplasm is detectable by 10 h PI ( Fig . 4A ) and therefore this time point was used to interrogate any potential compound-mediated changes in G localization within the Golgi complex of infected cells . At 10 h PI , cells treated with 0 . 5% DMSO alone displayed a bright G signal localized to one side of the nucleus , which is consistent with the location of the Golgi complex ( Fig . 5A–B ) . A portion of the G protein co-localized with Golgi as evidenced by the bright yellow staining when the images were overlaid ( Fig . 5C ) . Furthermore , numerous G stained spots ( Fig . 5B–C ) , presumably virus containing Golgi vesicles were found in the cytoplasm ( marked with white arrow ) . G202-0362 treated cells , similar to DMSO treated cells , expressed G that co-localized with Golgi apparatus ( Fig . 5D–F ) . However the numerous G stained spots in the cytoplasm that were observed in DMSO treated cells were not observed . Therefore it is possible that G202-0362 is targeting virus assembly , virus budding into Golgi lumen or the subsequent release of the virus containing Golgi vesicle into the cytoplasm . On the contrary , D011-2120 treated virus-infected cells resulted in Golgi dispersion ( Fig . 5G–I ) . G remained localized with the disrupted Golgi . The effects of compounds on Golgi and G protein localization were compared to that of two well-known Golgi-disrupting compounds , nocodazole and brefeldin A ( BFA ) . Nocodazole is a microtubule-disrupting agent and induces a slow dispersal of the juxtanuclear Golgi to peripheral sites [31] ( Fig . 5J–L ) , while BFA causes a rapid disassembly and redistribution of the Golgi into the endoplasmic reticulum ( ER ) [32] , ( Fig . 5M–O ) . D011-2120 and nocodazole had same effect on Golgi dispersion ( compare Fig . 5I and 5L ) suggesting a common mechanism of action . These results suggest that D011-2120 , exerts its antiviral activity by disrupting the Golgi complex in a manner similar to nocodazole , but distinct from BFA . We further developed HCI analysis to quantify alterations in Golgi structures , to estimate GC50 values ( effective concentration of compound that disrupts 50% of the Golgi complexes ) of D011-2120 targeting the Golgi , and to screen other compounds that may also target the Golgi . HCI-based analysis was developed to quantify changes in Golgi phenotype . For this , a HeLa cell line that stably expresses RVFV Gn was generated ( HeLa-G ) . In the absence of viral RNP complex , Gn remains in the Golgi ( [14] and reviewed in [33] ) and therefore IFA of Gn served as a Golgi marker . IFA showed specificity in the localization of RVFV Gn with Golgi marker ( Fig . 6A ) . Images of Gn stained HeLa-G that were mock-treated or treated with D011-2120 were used further for the development of HCI-based assay for cellular Golgi distribution . Figure 6B shows the individual steps that allowed successful segmentation of nuclei ( I ) , cells ( II ) and the Golgi complex ( III ) . The image analysis was applied such that the intact juxtanuclear Golgi appeared as one “intact Golgi” ( see methods ) . Figure 6B–IV ( see insert ) shows a red boundary generated by image analysis to classify “intact Golgi . ” D011-2120 treated cells showed Golgi staining as numerous spots dispersed throughout the cytoplasm , which was disqualified as ‘Intact Golgi” by image analysis program ( Fig . 6B–V , see insert ) . This image analysis was further applied to determine how the hit compounds modulated Golgi phenotype in HeLa-G cells that were treated with increasing concentrations of the hit compounds or the reference compounds Ribavirin or IFN-α ( Fig . 6C ) . Several features of the Golgi complex were generated , including “Golgi number” and “Golgi area” per well , and a heat map thus generated shows a clear reduction in Golgi “number” or “area” in wells with higher concentration of D011-2120 . The “Golgi number” parameter was further used to determine the GC50 values by dose response curve analysis ( Fig . 6D ) , which were compared to the compounds' EC50 as shown in Table 3 . The GC50 value for D011-2120 was less than half that of its EC50 value . The ratio of GC50 to EC50 was further calculated and was determined to be 0 . 62 . A ratio of less than 1 suggests that the compound's antiviral activity is related to its ability to disrupt the Golgi complex . Other compounds had lower GC50 values , but when compared to their EC50 , none of their GC50/EC50 ratios were below 1 ( Table 3 ) . Surprisingly , F694-1532 treated cells also resulted in a decrease in Golgi numbers . However , further analysis showed that this compound inhibited expression of Gn or any other exogenously introduced gene such as GFP , but did not disrupt Golgi phenotype ( data not shown ) . Because of the similarities observed in Golgi staining patterns in cells treated with D011-2120 and cells treated with nocodazole , we hypothesized that they are both acting by a similar biochemical mechanism . It is well-known that nocodazole exerts its effects by inhibiting polymerization of microtubules [34] , which are made up of linear polymers of tubulin that undergo continual assembly and disassembly to form a dynamic filamentous microtubule network within cells . Thus , we reasoned that D011-2120 may also be acting to inhibit this process . To test this , the kinetics of Golgi complex dispersion in HeLa cells exposed to either vehicle control ( 0 . 5% DMSO ) , D011-2120 , nocodazole , or BFA were examined by live cell imaging . Our previous data indicated that a 4 h exposure to both D011-2120 and nocodazole was optimal for cells to exhibit the Golgi dispersion phenotype ( data not shown ) . Thus , HeLa cells infected with MP12 virus for one life cycle ( 12 h ) and treated with D011-2120 or Nocodazole during the last 4 h of infection or with BFA during the last 15 min of infection . Tubulin was visualized by IFA . As expected , treatment with either the vehicle control ( 0 . 5% DMSO ) or BFA showed predominantly filamentous microtubule network ( Fig . 7A ) . In contrast , cells treated with either nocodazole or D011-2120 showed diffused pattern of tubulin staining ( Fig . 7A ) . To further quantify tubulin phenotypic changes , HeLa cells in a 96-well plate were treated with D011-2120 or reference compounds for 4 h and immunostained with tubulin antibody . The images were further subjected to HCA to quantify the changes in the pattern of microtubule organization using the “Ridge Value” of the patternanalysis program ( Columbus Software ) . The “ridge” feature best distinguished the filamentous pattern in control cells from the diffused staining of tubulin in the compound treated cells ( Fig . 7B ) . The ridge value for cells treated with D011-2120 was similar to cells treated with nocodazole , which were approximately half that of cells treated with BFA or mock-treated ( Fig . 7B ) . Because the separation of chromosomes requires functional spindle fibers that are made of microtubules , microtubule depolymerizing agents , such as nocodazole , are known to arrest cells in the G2/M phase of the cell cycle [35] . To determine if D011-2120 induces mitotic arrest in treated HeLa cells , cells were treated with various concentrations of the compound and immunostained to detect the expression of phosphorylated histone 3 at serine number 10 ( H3-pS10 ) , a known marker of cells undergoing mitosis and that is associated with chromatin condensation [36] . As compared to mock-treated ( 0 . 5% DMSO ) cells , there was a significant increase in the number of cells expressing H3-pS10 when cells were treated for 24 h with 25 µM of D011-2120 or 3 . 3 µM nocodazole ( Fig . 8A ) . Furthermore , the effect was dose dependent with the number of cells expressing H3-pS10 increasing with increasing concentration of D011-2120 up to 25 µM ( Fig . 8B ) . Concentrations above this amount were toxic to the cells . Taken together , these data suggest that D011-2120 acts by depolymerizing microtubules resulting in mitotic arrest .
RVFV , along with VEEV , MARV , EBOV and LASV all cause serious disease in humans and animals ( RVFV and VEEV ) . As such , they are classified by NIAID as category A priority pathogens with bioterrorism potential . In addition to being highly virulent , there is currently no FDA approved antivirals to treat any of them . In this study , we applied HCI-based analysis as a screening tool to discover novel compounds with antiviral activity against these highly pathogenic viruses and to elucidate their mode of action . Image-based high-throughput screening of potential antiviral compounds is an extremely effective drug discovery tool as it can not only determine antiviral activity , but can also measure many aspects of the viral life cycle and virus interaction with multiple host cellular components . However , many potential antiviral compounds could be targeting a cellular component that is essential for normal functioning of host cells . It is at this juncture that HCI-based screening has promise over traditional high-throughput screening assays . The sophisticated image analysis in HCS offers more information including intensity of expression , localization and pattern of expression ( i . e . , texture ) of the fluorescent target . Since viral infection follows a specific sequence of viral gene expression , any changes in the kinetics of viral protein expression patterns can provide useful insights into the stage of the virus life cycle targeted by the compound . This information can , therefore , be helpful in forming a hypothesis regarding which specific virus-host protein interaction ( s ) the compounds are acting on . To discover novel compounds with broad spectrum antiviral activity , the strain MP12 of RVFV served as a model system for primary screening . This attenuated strain was previously shown to faithfully recapitulate the replication properties of wildtype RVFV [15] and unlike the wildtype virus , can be handled safely under BSL-2 laboratory conditions . Thus , we used MP12 virus-infected cells to set the optimal system parameters , which included cell type , cell number , duration and multiplicity of infection , to achieve a statistically reliable high-throughput screening assay with a Z′-factor of 0 . 62 ( Fig . 1B ) . Basic features such as cell number and infected cell number were used to determine the “percentage of infected cells . ” Several additional parameters such as size of cell and nucleus were also acquired that provided additional information to determine if the compound were toxic to cells was acquired ( data not shown ) but were not used in this study . Using these optimized conditions , a focused small molecule library of 840 serine/cysteine protease inhibitors from ChemDiv were screened against MP12 RVFV infection in HeLa cells . Primary screening of the protease inhibitor library yielded 34 primary hits ( Fig . 2 ) , which could all be classified as one of four chemical structures ( Fig . 3B ) . Interestingly , none of these four chemical scaffolds had been previously reported to possess antiviral activity . The 34 primary hits were further screened against the fully virulent RVFV ZH501 strain , VEEV , LASV , EBOV and MARV . These viruses represent four different viral families and thus would give us some indication if the hit compounds were broadly active . Many of the hit compounds were broadly active against all the viruses tested , albeit with different efficiencies . For example , compound C795-0925 had the highest activity against RVFV and VEEV , but exhibited moderate antiviral activity against EBOV , MARV , or LASV . Similarly , compound D011-2120 had high activity against EBOV , MARV , and VEEV , but moderate activity against RVFV or LASV ( Fig . 3A ) . One compound from each chemical scaffold that showed broad spectrum antiviral activity ( active against at least three of the viruses tested ) were chosen for further study using a dose response curve assay against RVFV . Three of the four hit compounds had EC50 values that were below that of ribavirin , a drug commonly used to treat infections due to RNA viruses . To examine whether the compound's activities were specific to HeLa , we also tested them in the primary cell line SAEC . All of the hit compounds had activities similar in these cells as compared to those seen in HeLa cells; however , compound C795-0925 was less toxic in SAEC ( CC50 56 . 7 µM in HeLa compared to 110 . 6 µM in SAEC ) . The virus life cycle is an orchestrated series of specific steps that include virus entry , viral RNA replication , transcription , followed by viral protein expression , and finally the assembly of the viral structural proteins and egress out of the cell . To determine the specific stage of virus life cycle targeted by the compounds , we first evaluated the kinetics of RVFV N , Gn and S-Gn expression ( Fig . 4A ) [28] . Cells treated with C795-0925and F694-1532 exhibited decreased levels of expression of the viral proteins N and Gn . In contrast , cells treated with D011-2120 and G202-0362 showed normal expression levels of N and Gn , similar to that seen in mock-treated virus infected cells . As expected , cells treated with C795-0925and F694-1532 also exhibited significantly reduced levels of surface expressed Gn ( S-Gn ) , as fewer virions were being made during treatment with these compounds , thus fewer virions were getting to the cell surface . However , with compounds D011-2120 and G202-0362 , cells exhibited normal levels of N and Gn , but greatly reduced levels of S-Gn , suggesting the inhibition was at a more downstream point in the viral life cycle , such as virus assembly or egress . Thus , we used time-of-addition assays to determine at which stage these compounds were acting . Since none of the compounds inhibited virus infection when added at the time of infection or 2 h prior to infection , we concluded that the compounds are not having an effect on virus entry ( Fig . 4C ) . When time of compound addition was extended to 12 . 5 h PI , results suggest that D011-2120 and G202-0362 were affecting virus egress; whereas , C795-0925and F694-1532 were affecting viral RNA replication . We were further interested in using HCI-based analysis to define the mechanism of action used by D011-2120 and G202-0362 to inhibit virus egress . RVFV glycoproteins localize to the Golgi , promote virus assembly , and bud into the Golgi lumen [14] , [33] . Based on studies with other bunyaviruses , it is speculated that virus egress results from the budding of these virus-containing vesicles from the Golgi , trafficking through the cytoplasm , and their subsequent fusion with the plasma membrane , releasing the virus into the extracellular environment [15] , [30] , [33] . This is consistent with our data showing strong Gn staining in the Golgi at early time points ( data not shown ) and diffuse punctate stain throughout the cytoplasm at later time points ( i . e . , 10 h PI ) ( Fig . 5B ) . Presumably this represents RVFV-containing vesicles released from the Golgi and making their way to the cell surface as has been described for other bunyaviruses [22] , [33] . These vesicles were not observed in cells stably expressing Gn alone ( Fig . 6A ) , further supporting this idea . Given our observations , we wanted to determine if either G202-0362 or D011-2120 ( compounds earlier shown to effect egress ) affected viral trafficking from the Golgi to the cell surface . Interestingly , cells treated with G202-0362 showed Gn localized to the Golgi , but no virus could be seen in vesicles in the cytoplasm , suggesting that this compound was blocking the virus budding from Golgi and subsequent trafficking to the cell surface ( Fig . 5 ) . In contrast , D011-2120 appeared to completely disrupt the Golgi in a manner similar to nocodazole ( i . e . , by depolymerizing microtubules ) , as evidenced by co-localization of the Golgi marker , 1 , 4-galactosyltransferase , and Gn in a staining pattern similar to that seen with nocodazole ( Fig . 5G–L ) . These data suggested that D011-2120 , but not G202-0362 , may be acting by disrupting cellular microtubules . Because we were interested in further defining the phenotypic alterations in the Golgi caused by treatment with D011-2120 , we developed a HCI-based assay for this purpose . An algorithm using Columbus software was built that allowed classification of normal juxtanuclear Golgi complex from stacks of Golgi dispersed throughout the cytoplasm ( Fig . 5B ) . The algorithm was applied to determine the potency of the compounds to determine the concentration of compound that gives 50% reduction in Golgi numbers ( termed GC50 ) ( Table 3 ) . When these values were compared to EC50 values , it was evident that D011-2021 antiviral activity was related to its Golgi disruptive properties . Its GC50 was 38 . 2 µM , which was significantly lower than its EC50 ( 61 . 5 µM ) . Interestingly , while F694-1532 exhibited a relatively low GC50 ( 35 . 3 µM ) , it was still higher than its EC50 ( 20 µM ) . Likewise , as expected , F694-1532 and G202-0362 GC50 values were higher than their corresponding EC50 values , confirming that they also do not possess Golgi disruptive properties . We also examined the %GNL , which is the lowest percentage of Golgi number achievable at the compound's highest concentration . D011-2120 had the lowest %GNL further suggesting this compound was an active Golgi disruptor . Because the staining pattern of cells treated with D011-2120 was similar to that seen with nocodazole treatment ( Fig . 5 ) , we hypothesized that D011-2120 was acting by a mechanism similar to that of nocodazole ( i . e . , depolymerization of microtubules ) . Because spindle fibers , which are made of microtubules , are an essential component involved in mitosis , and subsequently , cell division , a consequence of microtubule depolymerization is mitotic arrest . Consistent with the idea that D011-2120 exerts its effect by microtubule depolymerization , we showed that cells treated with this compound undergo mitotic arrest ( Fig . 8A ) . Collectively , our data suggest that the antiviral action of D011-2120 is by depolymerizing microtubules which disrupted virus trafficking of virions from the Golgi to the cell membrane during virus egress in RVFV infection . Microtubulin plays an important role in the life cycle of many viruses supporting virus entry , RNA replication , assembly and or egress ( reviewed in [37] ) ) . The specific stage of the virus life cycle that is critically dependent on microtubulin defers between viruses and therefore it is possible that D011-2120 targeted virus entry or replication but not egress of other RNA viruses . Moreover microtubulin depolymerization induces mitotic arrest , and reduces cell viability in cells which can impair virus growth . This is apparent in the SI values of ≤1 . 2 derived from D011-2120 treatments in VEEV , EBOV , MARV or LASV infections , which meant that the compounds antiviral action could be due to compromised cell viability . G202-0362 also affected virus egress , but it appears to do so by a different mechanism to that of D011-2120 , namely by blocking virus budding from the trans Golgi . F694-1532 inhibits viral replication by an as yet unknown mechanism . This compound , however , also appeared to inhibit overall cellular gene expression and formed aggregates in the cell . Thus , while D011-2120 and F694-1532 may prove to have utility in treating other diseases , such as certain types of cancer , they are not attractive candidates for antiviral therapeutics . G202-0362 blocked virus budding from the Golgi , but did not disrupt the Golgi and did not alter any of the morphological features that we examined , including changes in cytoskeleton organization , cell or nucleus size , or Golgi or endoplasmic reticulum structure ( data not shown ) . Moreover , this compound had no observable effects on cell division in uninfected cells at the highest concentration tested ( 200 µM ) . In addition this compound was effective against filoviruses and VEEV Likewise C795-0925 was highly effective against VEEV with EC50 = 10 . 2 µM and SI = 6 . 2 . Thus , these two compounds may prove to be good candidates for antiviral drug development . In this study , we showed how HCI-based analysis could be used to screen for antiviral compounds effective against RVFV or other highly pathogenic RNA viruses and determine their mechanism of action . | Rift Valley fever ( RVF ) is an arthropod-borne viral zoonosis that occurs in large parts of sub-Saharan and North Africa and in 2000 emerged outside the African continent for the first time , raising concerns that it could further expand its geographical range . The disease in humans can result in encephalitis or hemorrhagic fever and in ruminants often results in abortion in pregnant females . Due to the lack of a licensed and commercially available vaccine , efforts to discover effective antiviral drugs are underway . Drug discovery using high content image-based screening is an effective tool that has been successfully used to identify new drugs . In this study , we developed an image-based assay to identify compounds active against RVF virus and other highly pathogenic human viruses . We demonstrated the usefulness of our image-based high content assay in identifying potential RVF antivirals by screening a small subset of chemical compounds for inhibition of RVF virus in a human cell line ( HeLa ) and partially characterized their mechanism of action within infected cells . The methods we developed in this study will be useful in discovering new effective drugs to combat Rift Valley fever . | [
"Abstract",
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] | 2014 | High Content Image-Based Screening of a Protease Inhibitor Library Reveals Compounds Broadly Active against Rift Valley Fever Virus and Other Highly Pathogenic RNA Viruses |
Antigenic variation plays a vital role in the pathogenesis of many infectious bacteria and protozoa including Borrelia burgdorferi , the causative agent of Lyme disease . VlsE , a 35 kDa surface-exposed lipoprotein , undergoes antigenic variation during B . burgdorferi infection of mammalian hosts , and is believed to be a critical mechanism by which the spirochetes evade immune clearance . Random , segmental recombination between the expressed vlsE gene and adjacent vls silent cassettes generates a large number of different VlsE variants within the infected host . Although the occurrence and importance of vlsE sequence variation is well established , little is known about the biological mechanism of vlsE recombination . To identify factors important in antigenic variation and vlsE recombination , we screened transposon mutants of genes known to be involved in DNA recombination and repair for their effects on infectivity and vlsE recombination . Several mutants , including those in BB0023 ( ruvA ) , BB0022 ( ruvB ) , BB0797 ( mutS ) , and BB0098 ( mutS-II ) , showed reduced infectivity in immunocompetent C3H/HeN mice . Mutants in ruvA and ruvB exhibited greatly reduced rates of vlsE recombination in C3H/HeN mice , as determined by restriction fragment polymorphism ( RFLP ) screening and DNA sequence analysis . In severe combined immunodeficiency ( C3H/scid ) mice , the ruvA mutant retained full infectivity; however , all recovered clones retained the ‘parental’ vlsE sequence , consistent with low rates of vlsE recombination . These results suggest that the reduced infectivity of ruvA and ruvB mutants is the result of ineffective vlsE recombination and underscores the important role that vlsE recombination plays in immune evasion . Based on functional studies in other organisms , the RuvAB complex of B . burgdorferi may promote branch migration of Holliday junctions during vlsE recombination . Our findings are consistent with those in the accompanying article by Dresser et al . , and together these studies provide the first examples of trans-acting factors involved in vlsE recombination .
Lyme borreliosis is a multi-stage , systemic disease caused by members of the spirochete genus Borrelia , including Borrelia burgdorferi in North America and Borrelia afzelii , Borrelia garinii , and B . burgdorferi in Eurasia [1] . Spirochetes are transmitted to mammalian and avian hosts via the bite of hard-bodied ticks of Ixodes genus [2] and disseminate widely throughout the body in the first weeks of infection . If untreated in early stages , chronic and debilitating disease can develop in the skin , joints , heart , and central nervous system [1] . Infected individuals develop an active immune response to the pathogen yet are unable to clear the infection . A common mechanism of immune evasion is antigenic variation , a process by which pathogens alter surface exposed antigenic proteins [3] , [4] . The resulting variant organisms are immunologically distinct from parental strains and thereby gain a selective advantage over individuals that retain parental antigenic determinants . Bacteria that undergo antigenic variation often cause long term or repeated infections . Examples of such bacteria include Neisseria gonorrhoeae , Neisseria meningitidis , Borrelia hermsii , Treponema pallidum , Campylobacter jejuni , Mycoplasma synoviae , Mycoplasma pulmonis , and Anaplasma marginale . Lyme disease Borrelia possess the vls ( Variable Major Protein ( VMP ) -like sequence ) system , a robust antigenic variation mechanism involving DNA recombination at the locus that expresses the surface exposed lipoprotein VlsE [5] , [6] , [7] , [8] , [9] . The vls locus consists of the vlsE expression site and a contiguous array of 15 vls silent cassettes , which have homology to the central region of the expression site . Gene conversion events involving replacement of regions of the vlsE expression site cassette with segments of the silent cassettes occur continuously during mouse infection , resulting in a myriad of vlsE sequence variants in each infected animal [10] , [11] . Within each cassette , there are six variable regions ( VRs ) that display considerable sequence diversity , interspersed with six relatively invariant regions ( IRs ) . The structure of the VlsE polypeptide is predominated by alpha helices that are believed to be important in maintaining protein structure [12] . The variable regions form random coils on the membrane distal surface of the protein , the region most likely to be exposed to the host immune system . VlsE variants have different epitopes when compared with parental VlsE1 polypeptide [10] , [13] , indicating that sequence changes in vlsE result in true antigenic variation . In the B . burgdorferi strain B31 , the vls locus is located near the telomere of the linear plasmid lp28-1 [10] . Loss of lp28-1 in B . burgdorferi B31 is associated with an intermediate infectivity phenotype in immunocompetent mice , in which infection lasts for less than 3 weeks and is largely restricted to joint tissue [14] , [15] , [16] , [17] . Spirochetes lacking lp28-1 are able to survive and cause disease at all tissue sites in severe combined immunodeficiency ( SCID ) mice [17] , [18] , indicating that one or more gene products encoded on lp28-1 play an important protective role against adaptive immunity . Bankhead and Chaconas [19] recently demonstrated that the vls locus is the important mediator of infectivity in lp28-1 . Deletion of the locus by telomere-mediated truncation resulted in an intermediate infectivity phenotype similar to that displayed by B . burgdorferi lacking lp28-1 , while deletion of the other end of the plasmid had no detectable effect on infectivity . The mechanisms that regulate vlsE recombination and expression are not well understood . vlsE recombination events have not been detected in ticks , during in vitro culture , or in dialysis membrane chambers embedded in rats , suggesting that non-dialyzable host components play a role in initiation of recombination [20] , [21] , [22] , [23] . In contrast , vlsE recombination is detectable within 4 days of mouse inoculation , and appears to occur throughout the course of mammalian infection [22] , [24] . Approximately 50% of recovered spirochetes have recombined vlsE sequences during the first 7 days of mouse infection; by four weeks , no organisms with parental vlsE sequence can be recovered [11] , [22] . In immunodeficient SCID mice , spirochetes with the parental vlsE disappear more gradually , indicating that the adaptive immune response is required for the rapid elimination of organisms expressing the parental VlsE [11] . Although analyses of vlsE transcription levels during mammalian infection have yielded variable results , immunoblot analysis indicates that VlsE protein expression is dramatically upregulated during mouse or rabbit infection [25] , [26] . Genes involved in DNA recombination and repair have been found to play a role in antigenic variation in other bacteria . For example , in Neisseria gonorrhoeae , pilin antigenic variation requires several trans-acting factors in the RecF-like recombination pathway , including RecA , RecX , RecJ , RecO , RecQ , and RecR [27] , [28] , [29] as well as RecG and a functional RuvABC complex [30] . However , in B . burgdorferi no genes have been yet identified that play a role in recombination within vlsE , although recA has been shown to be dispensable [31] . To identify proteins that play a role in vlsE recombination , we screened transposon mutants of DNA recombination and repair genes for infectivity and vlsE recombination . We found that mutants in the genes encoding the Holliday junction helicase polypeptides RuvA and RuvB were compromised in their ability to undergo vlsE recombination and displayed a reduced infectivity phenotype . In SCID mice , ruvA mutants retained full infectivity . vlsE sequences recovered from SCID mice were identical to parental vlsE sequence , suggesting that the failure to undergo vlsE recombination was a critical factor in the reduced infectivity phenotype . Furthermore , ruvA mutants had no increase in sensitivity to DNA damage . Nearly identical results were obtained in the accompanying article by Dresser et al . [32] .
For this study , 9 transposon insertion mutants representing 7 different genes whose homologues are known to be involved in DNA recombination and repair in other bacteria were selected from a large Signature Tagged Mutagenesis ( STM ) panel to screen for their effect on infectivity and vlsE recombination ( Table 1 ) . Independent mutants from two of the genes were included to test the possible role of different insertion sites on infectivity and vlsE recombination . T05P01C02 and T10P01D06 are independent mutants of BB0797 with insertion ratios of 0 . 73 and 0 . 97 respectively . ( The insertion ratio represents the relative position of the transposon insertion in a coding sequence , with the entire coding sequence having a value of 1 . 0 ) . Likewise , T08P01E02 and T11P01F09 are independent mutants from gene BBE29 with insertion ratios of 0 . 33 and 0 . 30 . Each mutant was injected in 5 mice and skin biopsies were taken at days 7 and 14 after inoculation and cultured for B . burgdorferi . Mice were sacrificed on day 28 of infection , and samples taken from skin , tibiotarsal joint , heart , and bladder were cultured to recover infectious organisms . B . burgdorferi maintained in in vitro culture sometimes lose plasmids that are not required for in vitro growth but may be required for infectivity . Therefore , the plasmid content of each mutant was determined and compared with that of the parental clone 5A18NP1 . Circular plasmid cp9 was found to be missing in two mutants ( T11P01A01 and T11P01F09 ) and lp21 is lacking in T10P01D09 . However , previous studies have shown that neither cp9 nor lp21 are essential for infection of mice [14] , [15] . As in previous studies , the parental strain 5A18NP1 was recovered from 29 of 30 tissue samples on days 7 , 14 , and 28 post inoculation [33] . Three of the nine DNA repair mutants tested ( T11P01A01 , T03TC051 , and T05P01C02 ) exhibited reduced infectivity and one ( MG065 ) lost infectivity in immunocompetent mice ( Table 2 ) . One of the mutS mutants ( T05P01C02 ) displayed a reduced infectivity phenotype , whereas the other mutant ( T10P01D06 ) had normal infectivity . The insertion site for the highly infectious mutant was very close to the end of the coding sequence ( 0 . 97 ) , so this mutant may express a functional product . ruvA ( T11P01A01 ) and ruvB ( T03TC051 ) mutants both exhibited intermediate infectivity patterns . While 5/5 skin cultures were positive for both mutants at day 7 post inoculation , by 2 weeks no skin cultures were spirochete positive , and at 4 weeks only 6 of 20 and 10 of 16 tissue sites were culture positive for the ruvA and ruvB mutants , respectively . We also examined the growth rates of the ruvA and ruvB mutants in vitro . Both mutants had growth kinetics very similar to that of the parental strain 5A18NP1 ( data not shown ) , indicating that the reduced infectivity phenotype observed for the mutants was not due to a growth defect . Restriction fragment length polymorphism ( RFLP ) was used to estimate the extent of vlsE variation in recovered organisms . Amplicons corresponding to the vlsE cassette region were generated by PCR from uncloned cultures and digested with HphI . This restriction enzyme recognizes a 4-bp sequence that occurs with varying frequency as a result of vlsE recombination . The vlsE cassette region of 5A18NP1 , the parental strain used in this study , has a single HphI site near one end ( Figure 1A ) . As expected , cultures from mice inoculated with 5A18NP1 displayed significant RFLP variability that increased over the course of infection , as indicated by multiple bands or the presence of a smear in the HphI-digested samples ( Figure 1A ) . In contrast , the ruvA and ruvB mutant cultures ( Figure 1B and 1C ) had vlsE RFLP patterns that were either unchanged or had relatively few bands without smearing , indicating that few vlsE variants had been generated during the course of infection . The other putative DNA recombination and repair mutants had complex vlsE RFLP patterns , indicating that a variety of vlsE variants had been generated during infection and that vlsE recombination likely had occurred normally ( data not shown ) . ruvA and ruvB have been reported to be part of a larger operon containing two additional genes ( Figure S1A ) , queA ( BB0021 , S-adenosylmethionine:tRNA ribosyltransferase-isomerase ) and pfpB ( BB0020 , diphosphate-fructose-6-phosphate 1-phosphotransferase ) [34] . To determine whether expression of other genes in the operon might be disturbed by the transposon insertion , we performed RT-PCR on RNA samples from the parental strain 5A18NP1 and the ruvA mutant T11P01A01 . Primer pair 1 generates a PCR fragment from within the ruvA coding region that crosses the transposon insertion site . As expected , this fragment can be generated using RNA from the parental strain , but not using RNA from the ruvA mutant , or RNA untreated with reverse transcriptase ( Figure S1B ) . However , RT-PCR products spanning regions of both ruvB and queA were generated from both strains using primer pair 3 and 4 ( Figure S1B ) . In the ruvA mutant T11P01A01 , the transposon is inserted such that a ‘read-through’ transcript could possibly be generated from the flgBP::aacC1 cassette within the transposable element . To test that possibility we used primer pair 2 , which generates a PCR fragment corresponding to the ruvA coding sequence downstream of the transposon insertion site . A product could be generated from both strains ( Figure S1B ) , suggesting that ‘read-through’ may be occurring from either the transposon or the native promoter . Thus , we conclude that T11P01A01 is defective in expression of ruvA , but that transcription of ruvB , queA and pfpB is occurring . However , we cannot rule out the possibility of polar effects resulting from changes in the levels of expression of ruvB , queA and pfpB . To further examine the effects of ruvA disruption on infectivity and vlsE recombination , a more detailed analysis of infectivity was performed ( Table 3 ) . Groups of ten immunocompetent C3H/HeN mice and ten C3H/scid mice were each inoculated with 105 organisms of either the T11P01A01 ( the ruvA mutant ) , or the parental clone 5A18NP1 . Mice were also inoculated with the previously characterized lp28-1− clone 5A8 [15] as a negative control . Groups of 5 mice were sacrificed at days 14 and 28 post inoculation . Samples of ear , tibiotarsal joint , heart , and bladder were collected for recovery of spirochetes . As expected , the positive control clone 5A18NP1 was fully infectious in both mice strains; spirochetes were isolated from all sites at day 14 and day 28 post inoculation ( Table 3 ) . The lp28-1− clone 5A8 exhibited the expected intermediate infectivity phenotype . In normal mice inoculated with 5A8 , spirochetes were recovered from only three joint cultures at day 14 , and no organisms could be recovered by day 28 post inoculation . However , all tissue sites were infected in C3H/scid mice inoculated with 5A8 . The ruvA mutant exhibited an infectivity phenotype similar to that of lp28-1− B . burgdorferi at day 14 , but resulted in some positive cultures at day 28 post inoculation ( Table 3 ) . In C3H/HeN mice infected with the ruvA mutant , only 3 joint cultures of 20 possible cultures were positive for spirochetes at day 14 post inoculation , whereas 20 of 20 cultures were positive in the C3H/scid mouse group . At day 28 , the ruvA mutant was recovered from 2/5 ear , 2/5 tibiotarsal joint , 2/5 heart , and 1/5 bladder cultures in immunocompetent mice , while again all cultures were positive in the C3H/scid mouse group . These results indicate that the ruvA mutant is significantly impaired in infectivity compared to the parental strain; it is not , however , as severely compromised as the strain lacking lp28-1 . We also tested the ability of B . burgdorferi carrying the ruvA or ruvB mutation to survive in ticks . I . scapularis nymphs were inoculated with the ruvA mutant T11P01A01 , the ruvB mutant T03TC051 , or the parental strain 5A18NP1 by capillary feeding . Ticks were held for 21–25 days and cultured for B . burgdorferi either before or immediately after feeding on 3 C3H/HeN mice . B . burgdorferi were readily detected in both fed and unfed ticks , as determined by direct fluorescent antibody ( DFA ) staining and culture ( Table 4 ) . This result indicates that the ruvA and ruvB mutations do not abrogate the ability of B . burgdorferi to survive in ticks . In addition , the mutant spirochetes were able to multiply upon tick feeding ( Table 4 ) . Fewer spirochetes were recovered from fed ticks carrying the ruvB mutant as compared to the ruvA mutant or the parental strain , but enough spirochetes were present in fed ticks to expect a mouse infection to result . However , tissues collected 4 weeks post tick inoculation with the ruvA or ruvB mutants were consistently culture negative ( Table 4 ) . The failure to recover organisms from any cultures derived from tick-inoculated mice ( as compared to the sporadically positive cultures from needle-inoculated animals; Table 2 ) may be due to the lower number of organisms delivered during tick inoculation as compared to needle inoculation , coupled with the decreased survival of ruvA or ruvB mutants in immunocompetent mice at 28 days post inoculation ( Table 2 ) . Spirochetes recovered from infected mice were isolated by colony formation , and the vlsE cassette region sequences of the resulting clones were determined by PCR amplification and sequencing to examine the effect of ruvA or ruvB mutation on vlsE recombination . For the ruvA mutant T11P01A01 , a total of 382 vlsE sequences were analyzed , comprising sequences from both immunocompetent and SCID mice , at three time points and from four tissues . For the ruvB mutant T03TC051 , a total of 62 clones isolated from C3H/HeN mice were sequenced , including 22 obtained from skin cultures 7 days post inoculation , and 40 clones from joint , heart , bladder and skin cultures 28 days after inoculation . The overall pattern of vlsE recombination observed is depicted in Figure 2 . For each mouse group and time point , it was determined whether the recovered clones retained the parental vlsE sequence , had a unique vlsE sequence , or shared the same vlsE variant sequence when compared to other clones from the same animal ( ‘vlsE sequences with siblings’ ) . It has been determined previously that vlsE variation is not detectable during in vitro culture [22]; therefore all inoculated organisms initially contained the parental vlsE sequence . As observed in prior studies with B . burgdorferi B31 clones , the parental strain 5A18NP1 underwent rapid vlsE recombination in both C3H/HeN and C3H/scid mouse hosts . By 14 days post inoculation , 0/59 clones from C3H/HeN mice had retained the parental sequence . Clones with unique vlsE cassette region sequences predominated after 7 days , although a surprisingly high proportion of sibling variants was observed in C3H/HeN mice inoculated with 5A18NP1 ( Figure 2 , Table S1 ) . At 14 and 28 days post inoculation , no clones with the parental vlsE sequence were detected . A similar pattern was observed during infection of C3H/scid mice , although the dilution of parental sequence clones occurred at a slower rate; 19/76 clones ( 25% ) still had the parental sequence on day 14 . However , even in C3H/scid mice no clones with the parental vlsE sequence were recovered at day 28 post inoculation . In contrast , sequence analysis demonstrated that very little vlsE sequence variation occurred during infection of mice with the ruvA mutant T11P01A11 ( Figure 2 , Table S1 ) . In immunocompetent mice , only clones with the parental sequence were recovered up to 14 days post inoculation . By day 28 very few ( 3 of 114 , 3% ) of the clones retained the parental sequence; however , the remaining clones were quite restricted in terms of sequence variation , with each animal possessing only 1 or 2 variant types . Surprisingly , only parental sequence clones were recovered from C3H/scid mice on days 14 and 28 post inoculation , indicating that clones that had not undergone vlsE variation predominated in the absence of immune selection . The ruvB mutant T03TC051 also exhibited reduced vlsE sequence variation during infection of C3H/HeN mice ( Figure 2 , Table S1 ) . The differences between sequence variation in 5A18NP1 and T11P01A01 are further illustrated in Figure 3 . Sequence diversity among the clones isolated at day 28 post inoculation from C3H/HeN mice was analyzed using phylogenetic tree software . The 63 clones from infection with 5A18NP1 were from joint , heart , bladder , and ear tissues of a single mouse , whereas the 114 clones for T11P01A01 were from the 12 culture-positive samples from 6 different mice . With clone 5A18NP1 , 31/63 ( 49% ) of the clones characterized possessed unique vlsE sequences; the remaining clones were variant siblings that were isolated from the same mouse tissue . Moreover , closely related sequences were often isolated from the same tissue ( Figure 3A , brackets ) , indicating that vlsE sequences in sibling clones were diverging within those tissues . For the ruvA mutant T11P01A11 , only eight different vlsE sequences could be detected among the 114 clones examined in the 6 mice , and no more than two different sequences were found in any one animal ( Figure 3B ) . Moreover , clones with the same sequence were often found in more than one tissue site ( Figure 3B , brackets ) . Three clones that retained the parental vlsE sequence were also isolated . These results provide further evidence that the ruvA mutant is severely compromised in its ability to undergo vlsE recombination . The sequences of 17 bp direct repeats at the 5′ and 3′ ends of vlsE central cassette were examined in all of the vlsE sequences recovered from ruvA mutants . No changes were identified indicating that vlsE recombination was not perturbed in the ruvA mutants due to instability of the direct repeats during mouse infection and/or vlsE recombination . In E . coli and other organisms , ruvA and ruvB act in concert to promote DNA branch migration . Therefore , we also examined the effects of ruvB mutation on vlsE sequence variation in C3H/HeN mice . As shown in Figures 2 and S3 and in Table S1 , the ruvB mutant T03TC051 exhibited reduced vlsE recombination rates similar to those observed for the ruvA mutant . No vlsE variants were observed at 7 days post inoculation . On day 28 , the vlsE cassette region sequences of 12 to 14 clones from each of three mice were determined . Each animal was found to have only 1 to 3 vlsE variant sequences , and 5 clones with the parental vlsE sequence were isolated from Animal 3 ( Figure S3 ) . Only one clone with a unique vlsE variant sequence was identified ( 1/40 , 2 . 5% ) . There were subsets of clones with the same vlsE variant sequence , consistent with the outgrowth of siblings of rare vlsE variants ( Figures 2 and S3 ) . Thus the ruvB mutant T03TC051 had an infectivity and vlsE variation phenotype that was quite similar to that observed for the ruvA mutant T11P01A01 . The non-parental vlsE variants recovered 28 days post infection with the ruvA and ruvB mutants were analyzed to determine the length , location and silent cassette source of the recombination events ( Figure 4 , Figure S2 ) . Each sequence was aligned with parental vlsE sequence , codon formatted and analyzed using a semi-automated analysis program [11] . The program compares each codon to parental and silent vls sequences and depicts the result ( identity or no identity ) as colored bars with each silent cassette assigned a unique color . Dark regions represent the sequence changes that may have resulted by recombination with that silent cassette . The lighter colored regions are contiguous codons that match both parental and silent cassette sequences and thus represent the possible boundaries of a recombination event . The most likely recombination events are presented in Figure 4; a more detailed presentation showing all silent cassettes potentially involved in the recombination events is shown in Figure S2 . Variants recovered from infections with 5A18NP1 at day 28 of infection are usually difficult to assign to a single silent cassette with confidence and appear to have undergone multiple recombination events ( [4] and data not shown ) . For example , the simplest explanation for the variant recovered from a mouse infected with 5A18NP1 ( Figure 4 , first panel ) appears to involve multiple recombinations of varied lengths with 6 different silent cassettes . In contrast , the results obtained with the ruvA and ruvB mutants were consistent with the occurrence of relatively rare and elongated vlsE recombination events ( Figure 4 ) . This pattern is exemplified by the vlsE sequence recovered from animal 1 , which likely represents a single recombination event with vls5 spanning almost the entire cassette region . Although many silent cassettes have sequence identity to the variant residues , vls5 represents the only continuous match over the entire region ( Figure S2 ) . One variant ( animal 2 ) is predicted to have undergone untemplated changes ( not matching any vlsE silent cassette ) in VR-I followed by an intermittent recombination event with vls2 . Several of the recombination events found in the ruvA mutant appear to be intermittent , i . e . the recombination events were discontinuous over the length of the cassette , alternating between the template cassette and vlsE1 . This intermittent recombination has been previously observed in vlsE recombination [11] . In addition , we noted that all recombination events from ruvA mutants included variable regions IV through VI . This bias is not observed with the parental strain [4] . Equally striking is length of the recombination events observed in the ruvA mutant . Coutte et al . [11] analyzed 126 clones that had undergone a single recombination event and identified the minimum and maximum predicted lengths of recombination . The majority of these clones ( 55% ) had minimum recombination lengths of 1–5 nucleotides and only 28% had minimum recombination lengths of >15 nucleotides . The variants obtained from ruvA mutant infections , however , had a median minimum recombination length of 168 bp ( range 91 to 479 bp ) , and a median maximum recombination length of 269 bp ( range 111 to 546 bp ) . Another unusual feature of the recombination events seen in the ruvA mutant is the distribution of silent cassette usage . Only 3 silent cassettes , vls2 , vls4 , and vls5 were used in the seven templated variants . vls4 and vls5 were each used twice . vls2 , the silent gene most proximal to the expression cassette has been observed to be used very rarely in infections with wild type B . burgdorferi , yet we observed it in three of seven templated ruvA variants . These results suggest that the normal mechanism of silent template selection may be perturbed in ruvA mutants . The vlsE sequences derived from infection with the ruvB mutant displayed similar features to those from the ruvA mutant ( Figures 4 and S2 ) . Most sequences were the result of single recombination events and used few vls silent cassette templates . The recombinations observed were unusually long , with a median minimum recombination length of 151 bp ( range 119 to 389 bp ) and an average maximum length of 179 bp ( range 151 to 561 bp ) . Recombination events always included most of the 3′ end of the recombination cassette; however , these recombinations did not always include VR6 , as observed for the recombination events derived from ruvA mutants . To determine whether mice infected with the ruvA and ruvB mutants developed a robust antibody response to VlsE , we performed ELISAs on serum from infected animals . We found that serum from animals infected with the ruvA or ruvB mutants displayed more variable antibody responses to VlsE than animals infected with the parental B . burgdorferi strain ( data not shown ) . Some animals displayed similar reactivity to sera from animals infected with parental strain while others displayed lower anti-VlsE activity . However , low anti-VlsE titers did not necessarily correlate with positive B . burgdorferi cultures from harvested organs . It is speculated that low quantities of anti-VlsE antibodies in some mice may correspond to early clearance of B . burgdorferi , thus resulting in a limited stimulation of the immune response against Borrelia antigens , including VlsE . In an attempt to fully demonstrate the role of ruvA in vlsE sequence variation and infectivity , we complemented the ruvA mutant T11P01A01 with the shuttle vector pKFSS1 [35] containing either ruvA alone , ruvAruvB , or ruvAruvBqueApfpB ( the four genes in the predicted operon; Figure S1 ) . A 264-bp region upstream of ruvA predicted to include the transcriptional promoter was included in all three constructs . The integrity of the resulting plasmids was confirmed by sequencing the inserts , and transformation of T11P01A01 was demonstrated by streptomycin selection followed by PCR using one primer specific for the pKFSS1 vector sequence and one primer corresponding to the B . burgdorferi DNA insert . Groups of three mice were each inoculated intradermally ( 105 organisms/mouse ) with one of two clones containing each complementation construct , yielding 3×6 = 18 mice inoculated with complemented lones . The two control groups ( 3 mice each ) were inoculated with positive control 5A18NP1 and the non-complemented ruvA mutant T11P01A01 . All strains yielded positive cultures from each of 3 skin sites taken distant from the inoculation site on day 7 , indicating that the infection was successful in each case . Six representative day 7 cultures were tested for the presence of the complementing plasmids by PCR , and yielded the expected amplicons . All cultures except those from 5A18NP1-inoculated mice were negative on day 14 post inoculation , and on day 28 the proportions of positive clones for the complemented clones were similar to that obtained for the ruvA mutant T11P01A01 ( data not shown ) . In addition , 17 complemented clones isolated on day 7 post inoculation were examined for vlsE recombination , and none exhibited vlsE sequence changes; this result was similar to what had been observed previously with uncomplemented ruvA mutant clones at this time point ( Figure 2 , Table S1 ) . Therefore attempts to restore infectivity and vlsE sequence variation to wild type levels by complementation have thus far been unsuccessful . In many microorganisms , ruvA is important in the repair of DNA damage resulting from UV irradiation or chemical mutagens . To assess the role of B . burgdorferi ruvA in DNA repair we monitored the survival of the ruvA mutant T11P01A01 subjected to DNA damaging conditions . Log phase cultures were irradiated with increasing doses of UV ( 254nm ) light , and cultured to determine spirochete survival by colony counting . Figure 5A shows the results of a representative experiment . The parental strain 5A18NP1 , and ruvA mutants had a similar number of colonies surviving at all UV doses , indicating that ruvA mutants do not have increased sensitivity to UV irradiation . Mitomycin C causes DNA damage by crosslinking complementary DNA strands at CpG sequences and is a commonly used reagent to examine the cellular response to DNA damage . To determine the sensitivity of the ruvA mutants to mitomycin C we assessed the viability of the ruvA mutant T11P01A11 and the parental strain 5A18NP1 after 14 hours exposure to increasing doses of mitomycin C . Treated cultures were plated and the number of colonies visible after 2–3 weeks incubation was used to assess spirochete survival . Figure 5B shows the survival of B . burgdorferi colonies after exposure to varied concentrations of mitomycin C . We observed no differences in survival between the ruvA mutant and the parental strain 5A18NP1 .
We conducted a genetic screen for trans-acting factors involved in vlsE antigenic variation in B . burgdorferi . Of the seven genes examined in this screen , four exhibited diverse PCR-RFLP patterns of vlsE , indicating that the inactivated genes are not centrally involved in vlsE recombination in C3H/HeN mice . Mutant MG065 in BB0098 ( annotated as a recombination and DNA strand exchange inhibitor and as mutS-II in other organisms ) was not recovered from inoculated mice , and thus could not be evaluated for vlsE variation . Two of the remaining transposon mutants , which had disruptions in the B . burgdorferi orthologs of the Holliday junction helicase genes ruvA and ruvB , had reduced vlsE recombination . The only other mutant that exhibited reduced infectivity and PCR-RFLP diversity was a mutS mutant , T05P01C02 . A second mutS mutant , T10P01D06 , had an insertion site near the end of the gene ( insertion ratio 0 . 97 ) ; this clone had normal infectivity and RFLP results , indicating that a functional product is likely produced . The possible role of mutS in vlsE recombination will be investigated further in a separate study . The predicted proteins encoded by the B . burgdorferi BB0023 and BB0022 open reading frames have a high degree of homology with the Holliday junction helicase proteins RuvA and RuvB , respectively , of other organisms . In Escherichia coli , the 22-kDa protein RuvA specifically targets RuvB to the Holliday junctions [36] , [37] , and the combined action of RuvAB results in branch migration during homologous recombination [38] . The 19-kDa RuvC resolvase cleaves the Holliday junction and is required for resolution of Holliday junctions in E . coli [39] . No homolog of RuvC has been identified in Lyme disease Borrelia , although RuvC orthologs have been identified in other spirochetes including the relapsing fever organism B . turicatae , T . pallidum , T . denticola and L . interrogans . Aravind et al . has proposed that a family of predicted LE exonucleases may substitute for RuvC in B . burgdorferi [40] . In addition to their role in recombination , E . coli ruv mutants exhibit defects in DNA repair such as increased sensitivity to UV light and mitomycin C [41] , [42] . The infectivity phenotypes of the ruvA mutant T11P01A01 and the ruvB mutant T03TC051 resemble those of B . burgdorferi strains that lack lp28-1 [14] , [15] , [17] , [18] or the vls locus [19] , although some differences exist . As shown in Tables 2 and 3 , the ruvA and ruvB mutants exhibited lower culture positivity than the parental strain 5A18NP1 in immunocompetent C3H/HeN mice . The ruvA mutant culture positivity pattern was the same as the lp28-1− clone 5A8 on day 14 post inoculation in C3H/HeN mice , with only joint specimens yielding positive cultures ( Table 3 ) ; however , 7/20 cultures in diverse tissues were positive for the ruvA mutant at day 28 post inoculation , as compared to a lack of positive cultures in the 5A8-inoculated animals . The ability of some ruvA− organisms to survive is most likely due to the ability to express VlsE and to undergo limited vlsE recombination . The ruvA mutant and the lp28-1− clone 5A8 is able to infect all tissues in C3H/scid mice , as has been observed previously with lp28-1− strains and clones in which the vls locus was deleted from lp28-1 by telomere-mediated plasmid truncation [19] . Thus mutation of ruvA results in reduced ability to survive in the presence of the adaptive immune system , perhaps due to antibody responses against invariant or limited variation forms of VlsE . We also tested the ability of B . burgdorferi carrying ruvA or ruvB mutations to survive in ticks . B . burgdorferi were readily recovered from both fed and unfed ticks suggesting that the ruvA and ruvB mutations do not abrogate the ability of B . burgdorferi to survive in ticks . However , the mutant spirochetes did not establish infection in C3H/HeN mice following tick inoculation ( Table 4 ) . These data suggest that the lack of detectable organisms at day 28 post mouse inoculation ( Table 4 ) was due to the effects of ruvA and ruvB mutations on survival in mice rather than poor replication in ticks or transmission from ticks to mammals . The failure to recover organisms in cultures derived from mouse inoculation via ticks may be due to the relatively low number of organisms delivered during tick inoculation as compared to the 105 Borrelia per mouse used in the needle inoculation studies . The reduced ability of the ruvA mutant T11P01A01 to undergo vlsE recombination is illustrated in Figures 3 , 4 , and S3 . Figure 3 shows that vlsE variants were not detected on days 7 and 14 in C3H/HeN mice inoculated with the ruvA mutant; while vlsE variants are predominant on day 28 , only one or two variant clones are detected in each mouse ( Figures 4 and 5 ) . Remarkably , no vlsE variants were detected at any time point following infection of C3H/scid mice with the ruvA mutant , whereas all of the clones examined at 28 days post inoculation were variants when C3H/scid mice were inoculated with the parental 5A18NP1 strain . Combining the reduced culture positivity results with the decreased vlsE variant diversity observed with the ruvA mutant , the following is evident: 1 ) inactivation of ruvA results in reduction of vlsE recombination rates , resulting in only a few variants in C3H/HeN mice and the lack of detected variants in C3H/scid mice; and 2 ) in C3H/HeN mice , the few clones that have undergone vlsE recombination are able to survive after the anti-VlsE response is activated , whereas nearly all of the parental clones are eliminated by day 28 post inoculation . The types of recombination events observed in the ruvA mutant were also quite different than those observed in wild-type B . burgdorferi . The average length of observed recombination events was an order of magnitude larger than in wild type clones . Moreover , most of the predicted recombination events observed in the ruvA mutant also appeared to represent intermittent recombination events , with regions of recombination interrupted by stretches of the unchanged , parental vlsE sequence ( Figure 5 ) . Finally , vls2 , vls4 , and vls5 were the only silent cassettes utilized in the ruvA mutant . The ruvB mutant also exhibited a limited repertoire of silent cassette usage ( cassettes 2 , 3 , 4 , 5 , and 8 ) . Taken together , these results may indicate that the recombination process is different in the ruvA mutant than in wild-type organisms; i . e . , the observed changes could involve a different , underlying recombination mechanism other than the as yet cryptic , vlsE-specific process that appears to be induced during mammalian infection . We found that sensitivity of B . burgdorferi to UV radiation and mitomycin C exposure was not affected by ruvA mutation . In other bacteria such as E . coli , deficiencies in RuvA , RuvB , or RuvC result in increased sensitivity to DNA-damaging agents , including UV irradiation and mitomycin C [43] . UV irradiation causes intra-strand thymine dimers in DNA , and the damage is repaired by RecA-mediated SOS response [44] . Mitomycin C exposure induces inter-strand cross-link in DNA , and an extended SOS response is needed to repair the damaged DNA [45] . Induction of genes encoding DNA repair enzymes during the SOS response is one of the most important DNA repair system in bacteria [46] . However , the B . burgdorferi genome does not encode a homolog of the SOS response repressor LexA , and SOS boxes ( LexA binding sites in promoter regions ) are not present upstream of recA and other genes that comprise the SOS regulon [47] . Also , expression of recA is not induced following UV exposure [48] . Thus B . burgdorferi appears to lack an SOS regulon . As an obligate parasite , B . burgdorferi is never exposed directly to UV light , and thus may have lost its ability to upregulate genes involved in the repair of DNA damage caused by radiation and other agents . Thus far , our attempts to restore full infectivity and vlsE recombination through complementation with ruvA in the shuttle vector pKFSS1 have been unsuccessful . In addition , we have also tried using constructs containing ruvAruvB and ruvAruvBqueApfpB , in case the transposon insertion in ruvA has some polar effect on the expression of downstream genes . A 264-bp region upstream of ruvA was used in all of these constructs; it is presumed to contain the promoter , although the region lacks a strong consensus promoter sequence ( e . g . −35 and −10 sequences with the proper spacing ) . BB0024 , the gene upstream of ruvA , is oriented in the opposite direction , indicating that ruvA is the first gene in the operon . Dresser et al . [49] have also been unsuccessful in trans complementing ruvA and ruvB mutants obtained by allelic exchange . The ruvA and ruvB mutants obtained by our laboratory and by Dresser et al . [49] were derived independently by different means ( transposon mutagenesis and gene disruption by allelic exchange ) , yet have nearly identical phenotypes . Thus it is likely that the lack of complementation observed in these studies is due to technical complications , as has been commonly observed in genetic studies involving infectious B . burgdorferi . We will continue our efforts to complement the ruvA and ruvB mutants in an attempt to fulfill the ‘molecular Koch's postulates’ on the roles of these genes in infectivity in immunocompetent mice and in vlsE recombination . The current study along with those by Liveris et al . [31] and Dresser et al . [32] provide some insight into the mechanism of recombination in the vls antigenic variation system . The central role of RuvAB indicates that heteroduplex formation with branch migration is important in this process . The lack of a requirement for RecA [31] , [32] is surprising . RecA provides two important functions in other microorganisms: ATP-dependent formation of RecA-single-stranded DNA nucleoprotein filaments that facilitate the homologous base pairing during heteroduplex formation [50]; and cleavage of LexA to activate the SOS response through its activity as a co-protease when bound to single-stranded DNA . As indicated above , B . burgdorferi lacks a recognizable LexA ortholog , so the latter function is likely to be unimportant ( although co-protease activity is present in B . burgdorferi RecA ) . Liveris et al . [31] state that the apparent lack of effect of recA mutation on vlsE recombination indicates that homologous recombination mechanisms are not involved in this process . However , ‘templated’ vlsE sequence changes ( those involving incorporation of silent cassette sequences ) consistently occur at the same position as the optimal alignment between the silent cassette and vlsE; i . e . , the observed vls silent cassette/vlsE recombinations are always homologous , and never nonhomologous [11] . vlsE recombination is induced during mammalian infection; it is possible that factor ( s ) that bind specifically to vls sequences and promote strand invasion and heteroduplex formation may be expressed under these conditions and hence fulfill a RecA-like ( but site-specific ) role . Such factor ( s ) have not been identified to date . Once a heteroduplex is formed , RuvAB may promote the migration of the heteroduplex branch point , thus extending the region of strand exchange . In a set of 126 vlsE variants that appeared to contain a single recombination event [11] , the putative minimal recombination events ranged from 1 nt to 349 nt , with a median value of less than 5 nt . This result indicates that the strand replacement process is often interrupted quite soon after its initiation . The observed range of sequence identity between donor and recipient sequences flanking the region of sequence change was from 0 nt to 88 nt , with ( remarkably ) as little as 6 nt on one side or the other [11] . It is currently unknown whether the role of the RuvAB migrase is to promote heteroduplex formation in these regions of sequence identity ( thus nucleating the strand exchange event ) , or whether it is also able to ‘drive’ the strand pairing through regions of sequence differences . Gene conversion has been described as the predominant mechanism in other bacterial and protozoal antigenic variation systems , including those of relapsing fever Borrelia ( e . g . B . hermsii ) , Neisseria gonorrhoeae , Anaplasma marginale , Trypanosoma cruzi , and Babesia bovis [51] , [52] , [53] , [54] . Lyme disease and relapsing fever Borrelia are closely related , and VlsE and the variable large protein ( Vlp ) antigenic variation proteins have some sequence similarity . However , in B . hermsii the gene conversion events result from homologous recombination within well-demarcated upstream homology sequences ( UHS ) and downstream homology sequences ( DHS ) , resulting in replacement of nearly the entire expression site gene with a silent gene sequence [53] , [55]; therefore it is different from the vls system both in terms of mechanism and gene conversion outcome . The N . gonorrhoeae pilE system , the A . marginale MSP2 , and the B . bovis VESA1a systems each involve segmental gene conversion events utilizing multiple silent gene copies to produce highly variable pilin or surface protein sequences . The pilE system is dependent upon RecA and other recombination system proteins that are not required for vlsE recombination , as described in detail by Dresser et al . [32] . In A . marginale , the gene conversion event is almost always ‘anchored’ in a conserved region flanking the hypervariable region [56] . The mechanisms of B . bovis VESA1a recombination are not well characterized , but are likely to involve eukaryote-specific elements that will differ considerably from those present in the prokaryote B . burgdorferi . Thus , based on current knowledge , the vls system may represent a unique gene conversion process that is mechanistically dissimilar to other known antigenic variation systems .
All procedures involving mice conducted at the University of Texas Health Science Center at Houston were reviewed and approved by the Animal Welfare Committee of that institution . All mouse studies conducted at the Tulane National Primate Research Center were reviewed and approved by its Institutional Animal Care and Use Committee ( IACUC ) . The transformable , infectious Borrelia burgdorferi B31 clone 5A18NP1 was used for generation of all mutants . 5A18NP1 is a genetically modified clone in which plasmids lp28-4 and lp56 are missing and BBE02 , encoding a putative restriction-modification enzyme , has been disrupted [33] . Borrelia burgdorferi B31 clone 5A8 , containing all plasmids except lp28-1 , was isolated previously from the low-passage strain B31 [15] , [57] and was used as negative control in mouse inoculation experiments . All strains used in this study had undergone no more than two subcultures since clone isolation prior to infectivity studies . B . burgdorferi were grown at 34°C in 3% CO2 in Barbour-Stoenner-Kelly II ( BSK-II ) medium supplemented with appropriate antibiotics as described previously [58] . The in vitro growth rates of the ruvA and ruvB mutants and the parental strain 5A18 NP1 were determined by daily quantitation of organisms in triplicate cultures by dark-field microscopy . E . coli TOP10 , a DH5α™-derived strain obtained from Invitrogen Corporation ( Carlsbad , CA , USA ) , was used for the preparation of plasmids for electroporation into B . burgdorferi . Genes putatively involved DNA recombination and repair were inactivated by transposon mediated mutagenesis as part of a transposon signature tagged mutagenesis ( STM ) study on-going in the laboratory . This study will be described in detail in another publication ( Lin , T . , L . Gao , C . Zhang , E . Odeh , and Norris , S . J . , manuscript in preparation ) . Briefly , twelve independent mutant libraries , each having a unique 7 bp sequence tag , were created using modified versions of the suicide plasmid pMarGentKan . This plasmid was graciously provided by Dr . P . E . Stewart ( Rocky Mountain Laboratories , National Institutes of Health , Hamilton , MN ) and is a modified version of pMarGent [59] in which a kanamycin resistance cassette ( flaB::aph1 ) was inserted in the ‘backbone’ of the vector , outside the himar1-based transposable element and a flgB:aacC1 gene is inserted within the transposable element ( P . E . Stewart , unpublished data ) . After insertion of unique sequence tags into pMarGentKan , 5 µg of each plasmid was electroporated into B . burgdorferi B31 using a modification of previously described methods [59] , [60] . The transformants were incubated in BSK-II medium without antibiotics for recovery overnight hours and plated in solid BSK-II media with 200 µg/ml of kanamycin and 40 µg/ml of gentamicin as described previously [57] . Colonies were selected and cultured in liquid BSK-II medium until mid-log phase prior to addition of 15% ( v/v ) glycerol and storage at −70°C . The transposon insertion site was determined by restriction digestion of the Borrelia genomic DNA , plasmid rescue in E . coli , and sequencing as described previously [59] . Properties of the transposon mutants selected for this study are shown in Table 1 . The plasmid profiles of DNA recombination and repair mutants were determined by a microtiter plate-based PCR method as previously described [15] or by a multiplex PCR scheme followed by detection using Luminex® FlexMAP™ technology . The Luminex® procedure will be described in detail in another article ( S . J . Norris , J . K . Howell , E . Odeh , T . Lin , and D . G . Edmondson , manuscript in preparation ) . Briefly , multiplex PCR reactions were performed to amplify plasmid-specific regions . The resultant PCR reactions were treated with exonuclease I and shrimp alkaline phosphatase ( Exo/SAP , U . S . Biologicals ) to remove excess nucleotides and primers , and then subjected to allele specific primer extension ( ASPE ) in the presence of biotin-dCTP using primers specific for individual plasmid products . The 5′ end of the ASPE primers contains an xTAG® universal tag sequence and the 3′ end of the ASPE primers contains the plasmid-specific sequences . The 5′ universal tag sequence was hybridized to the complementary anti-tag sequence coupled to a particular xMAP® bead set and biotin labeled DNA was detected with PhycoLink® Streptavidin-R-Phycoerythrin ( SAPE ) . Detection and analysis was carried out using the Luminex® 200™ System ( Luminex Corporation , Austin , TX ) , and samples were scored as plasmid positive or negative based on the median fluorescence intensity values for each probe set . Clones with transposon insertions in DNA recombination and repair genes were tested individually for infectivity in 4-week-old C3H/HeNHsd ( wild type ) by needle inoculation ( Table 1 ) . Mutant clones , the parental strain 5A18NP1 , and clone 5A8 were cultured to mid-log phase , and groups of 4–5 mice were inoculated with 1×105 organisms subcutaneously at the base of the tail as described previously [57] . Skin biopsies were collected aseptically at day 4 , 7 , 14 post inoculation . The mice were sacrificed at day 28 post inoculation , and skin , tibiotarsal joint , heart , and urinary bladder were collected . The tissue specimens were cultured in 6 ml BSK II medium containing kanamycin and gentamicin at 34°C in 3% CO2 . The cultures were checked for spirochetes by dark-field microscopy at 2 and 4 weeks , and positive cultures were diluted and subsurface plated in 0 . 7% solid BSKII –agarose medium to isolate individual colonies . For selected mutants , similar studies were performed in 5-week-old , female C3H . C-Prkdĉscid/ICRSmnHsd SCID mice ( Harlan , Indianapolis , IN ) . For clarity , this mouse strain is referred to as C3H/scid in this article . Anti-VlsE responses were assessed by ELISA as described previously [61] . B . burgdorferi mutant and wild-type strains were grown in BSK-II medium that was supplemented with 6% rabbit serum ( Pel-Freez Biologicals ) and 45 . 4 µg/ml rifampicin , 193 µg/ml phosphomycin , 0 . 25 µg/ml amphotericin , 200 µg/ml kanamycin ( all from Sigma-Aldrich ) . Gentamicin ( Gibco ) at 50 µg/ml was added to the mutant strain cultures only . Ixodes scapularis nymphal ticks from the Tulane National Primate Research Center tick colony were capillary fed with culture medium that contained the ruvA mutant , ruvB mutant , or the 5A18NP1 wild type B . burgdorferi , each at a concentration of about 9×107 cells/ml . Capillary feeding was performed by a procedure described previously [20] . Ticks were then allowed to rest for 21 to 25 days in a humidified environment at 22°C . Ten flat ( unfed ) nymphs from each group were surface disinfected and crushed in 30 µl of sterile PBS . Half of this volume was cultured in 5 ml of BSK II medium , supplemented with antibiotics as above , for a total of 12 weeks , and monitored weekly after the second week . . The remaining half was distributed on microscope slides for quantitation of spirochetes ( see below ) . The remaining flat ticks were placed on mice . Three 8–10 week-old C3H/HeN female mice were used for each B . burgdorferi strain , and each mouse received 10–12 nymphs . Engorged ( fed ) ticks ( about 75% of the initial number ) were collected within 6 days , and cleaned , crushed , and cultured or prepared for DFA as described above . All of the mice were euthanized 4 weeks after the ticks had dropped off , and heart , bladder , one ear , and one tibiotarsal joint were collected from each animal . In each case , half of the organ sample was snap frozen in liquid nitrogen and stored and the other half was placed in culture for 8 weeks . A direct fluorescent antibody ( DFA ) assay was performed to evaluate survival of each B . burgdorferi strain in ticks as described previously [62] . Briefly , tick smears from flat and fed ticks ( see above ) were air-dried on glass slides , acetone fixed and stored at −20°C until DFA examination . Slides were incubated with 40 µl of a 1∶10 dilution of fluorescein-labeled anti-Borrelia species antibody ( Kirkegaard & Perry Laboratories ( Gaithersburg , MD ) ) for 30 minutes at 37°C . Following incubation , the slides were washed in phosphate-buffered saline and examined by fluorescence microscopy ( magnification , 600X ) . For unfed ticks and for each spirochetal strain , spirochetes in 10 microscope fields were counted in each of 10 ticks per strain . For fed ticks , between 5 and 10 fields were counted in 24–26 ticks per strain . The mean number of spirochetes per field and the standard deviations are presented in Table 4 . Statistical significance ( p<0 . 05 ) was assessed by ANOVA . As a screen for vlsE sequence variation , cultures obtained from mouse infections were subjected to vlsE cassette region amplification followed by RFLP analysis . Five µl of unpurified culture was used as the DNA template . The vlsE expression cassette was amplified by using primers 4066 and 4120 [6] and the Phusion™ High-Fidelity DNA Polymerase ( Finnzymes , Inc . Woburn , Massachusetts , USA ) . PCR reactions were performed in volumes of 50 µl containing 10 µl of 5× HF buffer with 7 . 5 mM MgCl2 , 1 µl of 10 mM dNTPs , 1 µl of 25 mM primers , and 1 U of Phusion™ High-Fidelity DNA Polymerase . PCR reactions were performed in a Eppendorf Mastercycler® thermocycler ( Foster City , California , USA ) , using the following conditions; 98°C for 2 min followed by 30 cycles of 1 ) denaturation at 98°C for 10 sec , 2 ) annealing at 61°C for 20 sec , and 3 ) extension at 72°C for 45 sec and a final extension at 72°C for 10 min . For RFLP analysis , 10 µl of PCR product was digested with 2 . 5 U of the restriction endonuclease HphI ( New England BioLabs , Ipswich , MA ) for 2 hrs at 37°C in 10×NEBuffer 4 . The digests were separated in a 2% ( w/v ) agarose gel at a 100V constant voltage for 1 . 5 hrs in the presence of ethidium bromide . The Hi-Lo™ DNA marker ( Bionexus , Oakland , CA ) was used as a molecular size marker . Gels were imaged with UV light illumination . For sequence determination , the PCR products from individual clones were amplified as described above , purified using the Qiaquick® PCR purification kit ( Qiagen ) , and sequenced on both strands at the High-Throughput Genomics Unit ( Department of Genome Sciences , University of Washington , Seattle ) , using the same primers used for PCR amplification . Each DNA sequence was compared with their corresponding chromatographs and the parental vlsE sequence to verify the quality and accuracy of the sequence data . The sequence of the vlsE cassette region of clone 5A18NP1 ( GenBank GQ369288 ) is identical to that of B . burgdorferi B31-5A3 , from which the vlsE sequence ( U76405 ) was derived initially [6] . All B . burgdorferi clones and the GenBank numbers corresponding to their vlsE cassette region sequences are listed in Table S3 . For simplicity , the clone names refer to all clones resulting from T11P01A01 infection as ruvA1 and all T03TC051 derivatives as ruvB1 . All clones resulting from infection with the parental clone are given the prefix 5A18NP1 . The clone names ( e . g . RuvA1SD14M1S2 ) are in the following format: infecting strain name; S indicates C3H/scid mice ( all others are C3H/HeN mice ) ; D7 , D14 or D28 = 7 , 14 or 28 days post inoculation; mouse number ( M1 , M2 , etc . ) ; S , E , J , H , B = skin , ear , tibiotarsal joint , heart , and bladder , respectively; and the clone number from that tissue . The clone numbers and their GenBank accession numbers are also provided at the website http://www . uth . tmc . edu/pathology/borrelia/ . vlsE sequence analysis of variants was performed as described previously [11] . The output of this Excel®/Visual Basic-based program is a color-coded map of possible vlsE recombination events , as shown in Figure 4 and Figure S2 . The minimum and maximum deduced regions of recombination were determined by analyzing the longest contiguous recombination event in the variant sequence . The relationships among clones with different vlsE sequences were displayed graphically as phylogenetic trees . Phylogenetic trees were constructed using the online phylogenetic program Phylogeny . fr [63] , based on the aligned parental and variant vlsE sequences . The ruvA mutant T11P01A01 and the parental strain 5A18NP1 were tested for UV sensitivity using a modification of the method described by Miller , et al . Cultures were grown to a density of 1×107 organisms/ml . The spirochetes were centrifuged and resuspended in phosphate buffered saline ( PBS ) at a concentration of 1×108 organisms/ml , and 0 . 1 ml of the suspensions was rapidly aliquoted into 24-well plates . The bacteria were irradiated with UV light ( 254 nm ) using a Spectrolinker XL-1000 UV cross-linker ( Spectronics , Westbury , N . Y . ) at doses of 0 , 3 . 0 , 4 . 5 , 6 . 0 , 7 . 5 and 9 . 0 mJ/cm2 . The UV treated bacteria were protected from room light , diluted in BSK-II and cultured in BSK-II plates in duplicate or triplicate , at a concentration of 100 organisms per plate . The colonies were counted after 2 weeks incubation . For determination of mitomycin C sensitivity , fresh cultures of Borrelia were grown to mid-log phase and diluted to a density of 1×107 organisms/ml . Mitomycin C ( Sigma-Aldrich , St . Louis , MO ) was added to 1 ml cultures at final concentrations of 0 , 15 , 30 , 60 , 120 , 240 , 480 , 960 , 2000 , and 4000 ng/ml , and the cultures were incubated at 34°C in 3% CO2 . The concentration of motile spirochetes was determined by dark-field microscopy at 2 , 4 , 6 , 8 , 12 , 16 , and 24 hours . At 14 hours , the cultures were serially diluted in BSK-II to obtain concentrations 1000 cells/ml , and 0 . 1 ml portions of each dilution were cultured in BSKII plates with antibiotics as described above . Each culture was plated in duplicate and incubated 7–10 days at 34°C . Mitomycin C sensitivity was measured by counting the surviving colonies . Untreated cells grown in an identical manner served as controls . RNA was isolated from B . burgdorferi using RNA-Bee® ( Tel-Test , Inc . , Friendswood , Texas ) . Borrelia cultures were grown to a concentration of approximately 5×107 organisms/ml . Spirochetes from 1 ml of culture were sedimented by centrifugation and resuspended in 1 ml of RNA-Bee® , and RNA isolation was carried out as per manufacturer's instructions . The resulting RNA was quantitated by UV spectroscopy , checked visually on an agarose gel , and then treated with DNase I ( RNase-free , New England Biolabs ) following the manufacturer's suggested procedure . Reverse transcription was performed using 200 ng of RNA and primers specific to the ruvA operon following the two-step protocol found in the Enhanced Avian HS RT-PCR kit from Sigma-Aldrich . Subsequent PCR reactions used two µl of the resultant cDNA , 25 µM of specific primers and 2X PCR mix from New England Biolabs . Primer sequences and reaction conditions are shown in Table S2 . | Lyme disease is the most prevalent tick-borne infection in North America and Eurasia . It is caused by the bacterium Borrelia burgdorferi and is transmitted to humans via the bite of infected ticks . These spirochetes can cause both acute and chronic infection and inflammation of the skin , joints , heart , and central nervous system . The persistence of infection despite the presence of an active immune response is dependent upon antigenic variation of VlsE , a 35 kDa surface-exposed lipoprotein . A large number of different VlsE variants are present in the host simultaneously and are generated by recombination of the vlsE gene with adjacent vls silent cassettes . To try to identify factors important in vlsE recombination and immune evasion , we selected mutants in genes involved in DNA recombination and repair and screened them for infectivity and vlsE recombination . Mutants in genes encoding RuvA and RuvB ( which act together to promote the exchange of strands between two different DNA molecules ) had reduced infectivity and greatly diminished vlsE recombination . In immunodeficient mice , ruvA mutants retained full infectivity , and no vlsE recombination was detected . Our findings reinforce the importance of vlsE variation in immune evasion and persistent infection . | [
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... | 2009 | Central Role of the Holliday Junction Helicase RuvAB in vlsE Recombination and Infectivity of Borrelia burgdorferi |
The bacterial stringent response , triggered by nutritional deprivation , causes an accumulation of the signaling nucleotides pppGpp and ppGpp . We characterize the replication arrest that occurs during the stringent response in Escherichia coli . Wild type cells undergo a RelA-dependent arrest after treatment with serine hydroxamate to contain an integer number of chromosomes and a replication origin-to-terminus ratio of 1 . The growth rate prior to starvation determines the number of chromosomes upon arrest . Nucleoids of these cells are decondensed; in the absence of the ability to synthesize ppGpp , nucleoids become highly condensed , similar to that seen after treatment with the translational inhibitor chloramphenicol . After induction of the stringent response , while regions corresponding to the origins of replication segregate , the termini remain colocalized in wild-type cells . In contrast , cells arrested by rifampicin and cephalexin do not show colocalized termini , suggesting that the stringent response arrests chromosome segregation at a specific point . Release from starvation causes rapid nucleoid reorganization , chromosome segregation , and resumption of replication . Arrest of replication and inhibition of colony formation by ppGpp accumulation is relieved in seqA and dam mutants , although other aspects of the stringent response appear to be intact . We propose that DNA methylation and SeqA binding to non-origin loci is necessary to enforce a full stringent arrest , affecting both initiation of replication and chromosome segregation . This is the first indication that bacterial chromosome segregation , whose mechanism is not understood , is a step that may be regulated in response to environmental conditions .
Bacterial cells encounter varied environmental stresses and make appropriate adjustments to ensure survival . One such stress is amino acid starvation , which triggers physiological reprogramming known as the “stringent response” . Signaling of the stringent response is achieved by accumulation of effector nucleotides , guanosine tetra- and pentaphosphate ppGpp and pppGpp ( reviewed in [1] ) , with the former the predominant and more stable of the two species . Two enzymes , RelA and SpoT , control the levels of ppGpp: RelA ( PSI , or ppGpp synthetase I ) synthesizes ppGpp in response to uncharged tRNA , the consequence of amino acid starvation; SpoT ( PSII ) possesses weak synthetase activity and is the sole hydrolase for ppGpp degradation . The stringent response is RelA-dependent and is the most well-studied of stress responses signaled by ppGpp ( reviewed in [1] ) . RelA associates with the ribosome and is triggered to produce ppGpp when the ribosome stalls with an uncharged tRNA in the acceptor site . This causes a dramatic alteration in gene expression , including the reduction of rRNA synthesis and increased transcription of amino acid biosynthesis genes [2] . These changes result from direct binding of ppGpp to RNA polymerase , aided by the transcription factor , DksA [3] , [4] . Although it has been reported that ppGpp accumulation promotes arrest of replication , in addition to the well-studied transcriptional changes , the mechanism of the cell cycle arrest remains unclear [5] , [6] and is the subject of our investigation . The cell cycle of E . coli under low nutrient conditions is similar to that of eukaryotic cells , with a period prior to initiation of replication ( “B period” , equivalent to eukaryotic G1 ) , a period with ongoing DNA synthesis ( “C period” , equivalent to S phase ) and a period after completion of replication but before cell division ( “D period” , equivalent to eukaryotic G2 phase ) . In medium rich in nutrients , E . coli cell cycle is accelerated such that it becomes faster than the time necessary to replicate the entire chromosome; under this circumstance , replication cycles overlap and cells are born with partially replicated chromosomes , whose replication was initiated in its mother or even grandmother [7] . In E . coli , replication initiates at the oriC locus and proceeds bidirectionally to completion within the terminator region , ter [8] . Replication initiation is tightly controlled by the AAA+ ATPase , DnaA [9] . Binding to oriC followed by loading of the DnaB helicase depends on levels of DnaA-ATP [9] , correlated with achievement of a critical cell mass [10]–[12] . Firing of sister origins occurs in synchrony , such that cells contain 1 , 2 , 4 , 8 , 16 , etc . copies of the oriC locus . “Sequestration” , the binding of SeqA to a hemimethylated origin is a component of initiation control [13]–[15] . SeqA binds newly replicated , hemimethylated GATC sequences throughout the entire genome [16] , [17] . Within oriC , SeqA binding prolongs its hemimethylated status and blocks DnaA-origin interaction until the region becomes fully methylated by Dam methyltransferase [13] , [18] , [19] . This contributes to the “eclipse period” , the time within a cell cycle when reinitiation is actively prevented [20] , which is defective in mutants lacking SeqA and Dam [15] , [21]–[23] . In addition , SeqA is implicated in chromosome segregation and nucleoid organization [24] , [25] . In the absence of SeqA , DNA becomes more negatively supercoiled and nucleoids appear more decondensed [15] , [26] , [27] . Immunofluorescence microscopy of SeqA and GFP-tagged SeqA reveals foci colocalized with the replisome , consistent with SeqA binding to hemimethylated DNA as it emerges from the replication fork [24] , [25] , [28]–[30] . Under conditions of fast growth with overlapping replication cycles , SeqA promotes the colocalization of sister origins in E . coli , in a manner independent of sequestration at oriC [31] . SeqA overexpression also interferes with chromosome segregation [32] . It has been reported that stringent response in E . coli promotes replication arrest via inhibition of initiation [33]–[36] . Phase and fluorescent microscopy show that cells experience a reduction in cell size and contain a single nucleoid at mid-cell after ppGpp accumulation [34] . Initial reports showed limited replication at oriC after stringent onset [36] and later studies revealed that cells have a significant reduction , though not a complete block , in septum formation and cell division [34] . We reexamine replication arrest induced by the stringent response using flow cytometric techniques and implicate SeqA as a contributor to this arrest . Our studies reveal that under the stringent response , cells appear to complete replication and arrest at an integer DNA content corresponding to their pre-arrest growth conditions . This arrest appears to be dependent on RelA-dependent ppGpp synthesis . Stringent cells always contain one decondensed nucleoid; in relA mutants that fail to arrest , nucleoid compaction is apparent , similar to that seen upon treatment of cells with the translational inhibitor , chloramphenicol . Although marker frequency analysis shows that the ratio of oriC to ter is 1 after stringent arrest , visualization of oriC and ter by ParB-GFP binding shows that sister loci at the termini remain colocalized , whereas the oriC loci have separated . Stringent cell cycle arrest is dependent on SeqA and Dam , in a manner that is only partly dependent on GATC sites near the origin .
To determine the extent of DNA replication in populations of Escherichia coli K12 cells growing in defined media , we used flow cytometry for DNA content using the stain PicoGreen ( Invitrogen ) . We examined DNA content in cells at different growth rates , with and without treatment with serine hydroxamate , a derivative of serine that acts as a competitive inhibitor of seryl-tRNA synthetase , eliciting the stringent response [37] . This was compared to cells incubated with rifampicin and cephalexin , so-called “run-out” conditions that are used routinely to judge cell cycle status of E . coli . These antibiotics block initiation of replication and cell division , respectively; under this regimen , ongoing replication forks are completed and cells arrest in the D period . Under run-out conditions , the DNA content reflects the number of oriC loci in the cell at the time of treatment . With no treatment , there is a broad distribution of cellular DNA content , indicative of DNA replication , asynchronous in the population ( Figure 1 ) . After treatment with rifampicin and cephalexin , replication is completed and cells assume an integer DNA content reflective of the growth rate . In low glucose medium , the majority of cells appear to be replicating and arrest at 2N DNA content after run-out; a subpopulation appears not to have initiated DNA replication at the time of rifampicin and cephalexin treatment and arrest at 1N . In higher glucose minimal medium , the cell cycle is accelerated such all cells appear to be replicating . Some arrest after run-out as 2N but a proportion of cells have initiated a second round of replication prior to completion of the first and arrest at 4N . In high glucose with casamino acids ( CAA ) , all cells have initiated a second round , some with a third round , and arrest after run-out as a mixture of 4N and 8N cells . In each growth medium , treatment with serine hydroxamate to induce the stringent response for 1 . 5 hr caused the population to assume an integer DNA content , similar to treatment with rifampicin and cephalexin , indicating an inhibition of cell cycle progression and DNA replication . In each case , the integer DNA content at stringent arrest was somewhat lower than that seen with rifampicin and cephalexin treatment . This indicates that some stringent arrested cells undergo cell division after cessation of replication . Although some stringent cells may arrest in D period ( after completion of replication and prior to division , G2-like ) as do rifampicin and cephalexin-treated cells , there is a preference for stringent arrest in B period ( after division but prior to replication re-initiation , G1-like ) . Under the fastest growth condition , we examined relA mutants , defective in ppGpp production elicited by serine hydroxamate . Mutants in relA were noticeably impaired for arrest after serine hydroxamate treatment and the cellular DNA content of the population was broadly distributed , indicative of ongoing replication ( Figure 2A ) . In the presence of rifampicin and cephalexin , relA mutants assumed integer DNA content similar to wild-type cells , but with slightly more 8N relative to 4 N peaks . This finding confirms our expectation that ppGpp production by RelA is required for cell cycle arrest during the stringent response . We also examined wild-type cells in which the stringent response was induced by high levels of a catalytically active truncated RelA fragment , RelA′ . Overexpression of RelA′ causes ppGpp production , independent of idle ribosomes [38] . This method has the advantage of ppGpp accumulation independent of ribosome signaling and which is not accompanied by translational stalling . This allows us to distinguish ppGpp-specific effects from those associated indirectly with starvation or translation inhibition . If ppGpp accumulation is sufficient to induce cell cycle arrest , we would expect DNA profiles from pRelA′ induced cells to resemble those after treatment with serine hydroxamate . Indeed , cell cycle arrest and integer chromosome number was apparent by flow cytometry in IPTG-induced pRelA′ cells as compared to non-induced cells ( Figure 2B ) . This confirms that accumulation of ppGpp , rather than inhibition of translation or starvation itself , is responsible for the arrest . We did note that the integer chromosome number after RelA′ overexpression was somewhat lower , with a more predominant 2N peak , and more asynchronous , with a strong 6N peak , than that seen for serine hydroxamate . This may be a consequence of higher ppGpp levels induced by RelA′ overexpression . Because of the implication of the DNA binding protein SeqA in control of both chromosome initiation and segregation , we tested ΔseqA mutants for DNA content after induction of the stringent response . We found them to be virtually blind to serine hydroxamate treatment ( Figure 2A ) and DNA profiles resemble untreated cells . As has been noted previously [15] , [39] , [40] , seqA mutants are also unable to assume integer DNA content after run-out with rifampicin and cephalexin , potentially because initiation is no longer sensitive to rifampicin or because ongoing forks fail to proceed to completion . The former explanation is suggested by the fact that the mean DNA content per cell in the seqA mutant cell population appears to increase substantially even after rifampicin/cephalexin treatment , as compared to untreated cells . SeqA binds preferentially to GATC sites hemi-methylated by Dam ( DNA adenine methylase ) over unmethylated sites [20] and therefore we also tested dam mutants , which are expected to resemble seqA defective strains . We observed strains lacking Dam methylase showed a stringent cell cycle arrest defect similar to ΔseqA strains ( Figure 2A ) . As seqA , dam mutants show no “run-out” after treatment with rifampicin and cephalexin ( Figure 2A ) , although average cellular DNA content increases , suggesting rifampicin-resistant replication . Because of SeqA's preference for hemi-methylated sites , Dam-overproducing cells also perturb SeqA binding to GATC sequences and cause defects in initiation control . Overproduction of Dam causes rapid conversion of hemimethylated DNA to fully methylated DNA , decreasing SeqA's ability to bind to these sites [13] . We would therefore expect Dam-overexpressing cells to exhibit defects in stringent cell cycle arrest , similar to seqA and dam mutants . To test this , we engineered otherwise wild-type cells to overexpress Dam from an arabinose-inducible promoter . This strain exhibited cell cycle arrest after treatment with serine hydroxamate when grown in the presence of glucose but failed to shift DNA content fully to an integer amount when Dam was induced by arabinose ( Figure 2C ) . There was , however , evidence of a slight 2N peak in Dam-induced wild-type cells: this may represent a subpopulation that arrests replication because Dam levels are not sufficiently high or because they have lost the plasmid . After treatment with rifampicin and cephalexin , glucose-grown cells were primarily 2N and 4N whereas many arabinose-grown , Dam-overexpressing cells failed to assume integer DNA content . As seqA and dam mutants , Dam-overexpressing cells may exhibit rifampicin-resistant replication initiation that prevents “run-out” to integer DNA content . DNA content is notably higher in seqA mutant strains due to loss of initiation restraint and subsequent over-replication [15] . To test whether the tendency to overinitiate obscured a functional stringent arrest in ΔseqA cells , we used a genetic suppressor of seqA in dnaA . The hypomorphic dnaA ( Sx ) allele lowers the frequency of initiation at cold-temperatures and suppresses the overinitiation property of ΔseqA mutants at its permissive temperature [40] , [41] . We confirmed that dnaA ( Sx ) itself does not influence stringent cell cycle arrest . dnaA ( Sx ) cells displayed a stringent arrest after treatment with serine hydroxamate as indicated by a shift to an integer number of chromosomes , similar to run-out conditions ( Figure 2A ) . When combined with the dnaA ( Sx ) allele , ΔseqA cells maintain a DNA content similar to wild-type cells in the absence of any treatment ( Figure 2A ) . The dnaA ( Sx ) ΔseqA mutant did not successfully arrest after treatment with serine hydroxamate , although DNA content remained within the range that was comparable to arrested wild-type cells . This suggests that failed stringent arrest in ΔseqA cells is due to a lack of SeqA function and is not an indirect consequence of hyper-initiation or excessive DNA content . SeqA appears to have two distinct functions: it binds to hemimethylated DNA sites at the origin and , somewhat more transiently , to newly replicated DNA throughout the chromosome . To distinguish between the origin and other sites of SeqA binding , we examined DNA content after stringent arrest in an oriCm3 strain , which is specifically defective in oriC sequestration . oriCm3 strains have eight of the GATC sequences within oriC converted to GTTC , causing a decreased affinity for SeqA , asynchronous replication , shortened eclipse periods and asymmetric cell division , equivalent to strains lacking SeqA altogether [39] . These mutations should not affect SeqA binding to hemi-methylated DNA revealed after replication of other regions of the chromosome . Flow cytometry of oriCm3 cells shows a modest increase in DNA content , presumably due to hyperinitiation caused by defective origin sequestration . After treatment with serine hydroxamate , the DNA content indicates that stringent arrest is partially intact in the oriCm3 strain , with a prominent 4N arrest peak . This suggests that there is a critical role of SeqA in enforcing the stringent response by interactions to DNA sites outside the origin . Mutants in oriCm3 , like those in dam and seqA , showed poor run-out to integer chromosomal content after treatment with rifampicin and cephalexin . To examine segregation patterns of specific locations of the chromosome , we used strains that contain a parS sequence inserted adjacent to the origin or to the terminus . The parS sequence provides a binding site for the plasmid-expressed fusion protein , GFP-ParB , to allow visualization of the locus of interest [42] . To enhance GFP fluorescence , these experiments were performed at lower temperature , 34° , and flow cytometry was performed on these cultures in parallel to discern their cell cycle status . For growth in minimal medium plus casamino acids at 34° , examination of oriC and ter foci via ParB-GFP showed that stringently-arrested wild-type cells have two or four distinct oriC foci ( Figure 3A and 3B ) . However , the number of visible ter foci was one or two , half that seen for oriC and similar to that seen for untreated cells . Marker frequency analysis by quantitative Southern blots for oriC and ter showed that with no treatment , the oriC to ter ratio was 2 . 5 ( Figure 3C ) , indicating that replication was ongoing . After induction of the stringent response , the oriC/ter ratio in wild-type cells was 1 . 0 ( Figure 3C ) , indicating that replication was complete . In contrast , relA mutant cells retained an oriC/ter ratio of greater than 2 , even after serine hydroxamate treatment ( Figure 3C ) . In similar analysis , the oriC/ter ratio of dnaA ( Sx ) seqA mutant cells was 2 . 8 before treatment and 2 . 7 after serine hydroxamate , confirming that replication is ongoing after induction of the stringent response in these strains . The 2∶1 ratio of oriC to ter foci after serine hydroxamate treatment of wild-type cells , despite the fact that the chromosome appears to have completely duplicated from the marker frequency analysis , suggests that ter loci remain colocalized after replication . In contrast , colocalization of ter was not observed in wild-type cells arrested in the cell cycle by rifampicin and cephalexin: under these conditions the number of ter foci are equivalent to those seen for oriC ( Figure 3A and 3B ) . This confirms that colocalization of ter seen during the stringent response is not likely to be a simple artifact of the ParB-GFP visualization system . Rather , there appears to be a distinct chromosome organization pattern enforced by the stringent response , and it is unlike that seen with other types of cell cycle inhibitors . We examined the nucleoid morphology of stringent cells by DAPI-staining and fluorescence microscopy . Untreated wild-type cells growing in minimal CAA medium showed 1 or 2 nucleoids and had apparent signs of division and chromosome segregation ( Figure 4A , left panel ) . DNA-free zones of the cytoplasm were apparent . After treatment with serine hydroxamate , signs of cell division were absent and all cells contained one nucleoid ( Figure 4A , middle panel ) . The nucleoids appear decondensed , filling nearly the entire cell volume . This was quite different from cells treated with the translation inhibitor chloramphenicol , with a single , very condensed nucleoid structure at midcell ( Figure 4A , right panel ) , consistent with previous reports [43] . From the observation of chloramphenicol-collapsed nucleoids , it has been argued that translation and anchoring of membrane proteins is required to extend the nucleoid throughout the cytoplasm . Despite a potential down-regulation of translation induced by serine hydroxamate , the nucleoid remained surprisingly decondensed , even more so than untreated cells . The decondensed nucleoid was not just a consequence of serine hydroxamate treatment: we saw similar appearance in cells in which the stringent response had been induced by pRelA′ overexpression ( Figure 4B ) . We also examined nucleoid morphology in ΔrelA strains ( Figure 4A ) . Untreated ΔrelA nucleoids appear similar to wild-type; however , when treated with serine hydroxamate , nucleoids in ΔrelA cells have a condensed appearance , similar to cells treated with chloramphenicol . This may indicate that the absence of capacity to synthesize ppGpp causes a collapse in translational capacity upon serine hydroxamate treatment , reflected in nucleoid appearance . Or , it could mean that ppGpp induces some active nucleoid decondensation process that is absent in relA strains . Interestingly , mutants in seqA , despite their failure to arrest replication , appeared to retain the decondensed nucleoid character of wild-type cells after serine hydroxamate treatment . Although this is difficult to see in seqA strains because of their excessive DNA content , nucleoid decondensation after serine hydroxamate is also apparent in dnaA ( Sx ) seqA strains that have more normal DNA content per cell . This may indicate that seqA affects only a subset of the responses to ppGpp ( see below ) . Mutants in oriCm3 also exhibited nucleoid decondensation similar to wild-type cells after serine hydroxamate treatment . We wondered how cell cycle patterns would be reset after release from arrest . Would cells resume replication in a pattern similar to that prior to arrest ? Or would cells be obligated to segregate each chromosome , divide and initiate replication from 1N progeny ? To examine this , after 90 minutes of stringent arrest induced by serine hydroxamate , wild-type cells in minimal M9 Glucose CAA medium were washed and allowed to resume growth . DNA content was followed over time by flow cytometry and nucleoid appearance was monitored by DAPI staining ( Figure 5A and 5B ) . As early as 15 minutes after release , some signs of nucleoid segregation were apparent . Segregation of two nucleoids appeared first at midcell; later segregation at the ¼ positions to form 4 nucleoids was detected . We think this reflects sequential and ordered segregation of chromosomes: sister-chromosome pairs held in cohesion segregate first , followed by separation of sisters ( see schematic in Figure 5C ) . From 15 to 30 minutes , DNA content in the entire population appeared to increase , concomitant with nucleoid condensation and segregation . Therefore , cells appear to assume DNA content equivalent to conditions before the arrest , suggesting that replication patterns are reset quickly upon release . Growth is inhibited in wild-type Escherichia coli cells with elevated ppGpp levels and they are unable to form colonies [44] . We wondered whether this is a consequence of cell cycle arrest induced by the stringent response and , moreover , if the stringent cell cycle arrest defects in Δdam and ΔseqA would permit colony formation during chronic ppGpp production . Wild type , ΔseqA , Δdam , and oriCm3 cells containing the IPTG-inducible pALS13 plasmid producing truncated RelA′ , were grown on M9 minimal CAA ampicillin plates containing various concentrations of IPTG . A control plasmid , pALS14 , contains a truncated 1 . 2 kb fragment of RelA that has no enzymatic activity [38] . Colony formation in wild-type cells was severely inhibited by induction of RelA′ ( Table 1 ) but not with the nonfunctional RelA- protein . Similar inhibition of plating was obtained by induction of pALS10 , expressing wild-type RelA+ ( data not shown ) . ΔseqA and Δdam cells , however , maintained the ability to form some colonies in the presence of elevated ppGpp concentrations , with plating efficiencies dramatically elevated , over 1000-fold , in the presence of IPTG ( Table 1 , and data not shown ) . On the other hand , oriCm3 cells had only a modestly increased plating efficiency of about 10-fold . This is consistent with our flow cytometric results and suggests that an origin compromised for SeqA interaction has only a partial defect in the stringent cell cycle arrest , considerably less severe than strains lacking all SeqA function or Dam methylase . Cells that successfully formed colonies under stringent response induction in ΔseqA or Δdam genetic backgrounds were no more resistant than the original population upon rechallenge with IPTG ( data not shown ) , indicating that no heritable change arising during growth , which is a special concern for dam mutator strains , had allowed them to escape preferentially . The inability of cells to form colonies under constitutive ppGpp accumulation appears to be , in part , a consequence of cell cycle arrest . We do note that the rescue of plating by seqA and dam is not 100% , indicating that transcriptional reprogramming , translational inhibition or other aspects of the stringent response , which remain intact in seqA and dam mutants ( see below ) , may also be inhibitory to growth and division . One possible explanation for the inability of Δdam and ΔseqA strains to arrest cell cycle during the stringent response is that production of ppGpp , or its ability to interact with RNA polymerase , for some reason , is defective . To investigate this , we examined ppGpp production directly by 32P-phosphate labeling and separation of nucleotides by thin-layer chromatography ( Figure 6A and 6B ) . The more slowly-migrating form corresponding to ppGpp was apparent in wild-type , seqA , dam and oriCm3 strains after treatment with serine hydroxamate; this was not seen for relA strains . Another characteristic of stringent control in wild type cells is the reduction of stable RNA synthesis [44] . Uridine uptake is also reduced by induction of the stringent response [45] . By pulsing cells with [3H]-uridine , treated with or without serine hydroxamate , we examined the amount of newly labeled rRNA synthesis over time ( Figure 6C ) . Wild-type cells treated with serine hydroxamate display a decrease in labeled rRNA compared to untreated cultures . ΔrelA cells , defective in stringent control , maintain labeled rRNA production at high levels , blind to treatment with serine hydroxamate . Like wild-type , ΔseqA and Δdam cells showed reduced labeled rRNA after serine hydroxamate addition . Because the latter experiment reflects both down-regulation of rRNA synthesis , as well as reduction in uridine uptake , we also examined pulse-labeling of rRNA with inorganic phosphate , relative to total levels as determined by ethidium bromide staining , which should be more reflective of rRNA synthesis . Labeling of rRNA decreased over 2-fold after treatment with serine hydroxamate in wild-type cells and 15-fold in ΔseqA mutant cells; incorporation of 32P into rRNA was not strongly affected by serine hydroxamate treatment in relA mutants that fail to synthesize ppGpp . These experiments suggest that seqA and dam mutants have no defect in production of ppGpp or other aspects of the stringent response , including transcriptional down-regulation of rRNA synthesis and possibly uridine uptake , and therefore are specifically impaired in cell cycle response to ppGpp .
Previous results suggested that initiation of replication is blocked when ppGpp levels are high and that elongation of replication continues to completion after ppGpp accumulation [34]–[36] . Our findings confirm this and suggest that chromosome segregation is an additional point of stringent regulation . Stringent cells arrest with unsegregated nucleoids with colocalized termini . This is consistent with reports showing that cell division , though not completely inhibited , does not likely proceed until each cell has 1 chromosome [34] . Stringent cell cycle arrest points differ between Escherichia coli and Bacillus subtilis . B . subtilis arrests replication elongation by ppGpp inhibition of primase activity [47] . It is unclear why E . coli does not perform this C-period ( “intra-S phase”-like ) arrest , although it remains possible that elongation is slower in stringent cells or punctuated with stalling events . We also do not know the threshold levels of ppGpp or starvation that elicit replication arrest in the two organisms . It remains possible that elongation arrest in E . coli could occur under more stringent conditions or occurs in a subpopulation of cells , obscured by arrest in B and D periods . During the stringent response in E . coli , GTP levels do not fall more than 50% [46]; in contrast , Bacillus subtilis experiences a drop in GTP concomitant with ppGpp accumulation and its stringent response may be an indirect consequence of depletion of GTP pools [48] . For this reason , E . coli may respond more sensitively to ppGpp , enabling it to complete replication before collapse of nucleotide pools that would stall replication . E . coli and its relatives are unique in their acquisition of adenine methylation and SeqA function , perhaps allowing an extra level of control of replication and chromosome segregation , lacking in other bacteria . The origin region is particularly rich in GATC sites and SeqA binding to these sites is relatively long-lived , up to 1/3 of the cell cycle , when the sites remain hemimethylated [18] , [23] . Using a mutant in many of the GATC sites near the origin , oriCm3 [39] , we addressed the role of the methylation pattern of oriC during the stringent response . Our data indicates that in this mutant stringent arrest is partially intact . Some arrest , as judged by flow cytometry for DNA content , was seen in this mutant upon serine hydroxamate treatment . During chronic exposure to ppGpp , this mutation relieved inhibition of colony formation only modestly , approximately 10-fold , relative to wild-type strains . This was in contrast to the ΔseqA strain , in which no evidence of replication arrest was apparent and which was 1 , 000-fold more efficient in colony formation during chronic exposure to ppGpp . It is possible that the oriCm3 mutation only produces a partial loss of SeqA binding to the origin , although the first characterization of this mutant suggests that loss of sequestration at oriC is complete [39] . A recent study [31] shows that transient colocalization of sister origins in cells with overlapping replication cycles depends on SeqA in a manner that is not affected by oriCm3 but dependent on the property of SeqA for self-aggregation . It may be this mode of SeqA binding that is required for stringent arrest . This study provides new evidence that late stages of chromosome replication or chromosome segregation can be regulated in response to environmental conditions . The nature of this arrest is intriguing and suggests possible mechanisms . We observed segregated oriC regions marked by GFP-ParB but only one half the predicted number of ter regions . In contrast , after cell cycle arrest by rifampicin and cephalexin , the number of observed ter foci is equivalent to those of oriC . Loss of ter cohesion may be a prerequisite for chromosome segregation and a point of regulation by the stringent response . Interestingly , the nature of stringent arrest of chromosome segregation is very similar to the arrest seen in cells depleted of the GTPase ObgE , which is required for chromosome segregation and survival after treatment with replication inhibitors [49] , [50] . Both the Bacillus subtilis Obg and E . coli ObgE bind ppGpp ( [51]; Persky and Lovett , unpublished results ) ; E . coli Obg ( also known as CgtA ) interacts with ppGpp synthetase/hydrolase SpoT [52] and CgtA may regulate SpoT hydrolase activity in Vibrio cholerae [53] . One possibility is that Obg controls ppGpp levels; alternatively , Obg may be required to license cell cycle progression in a manner that is inhibited by ppGpp binding . Replication and chromosome segregation are concurrent processes in growing E . coli cells and loci segregate as they are duplicated . In some studies [54] , [55] , there appears to be a delay of segregation of ter relative to other regions of the chromosome , suggesting that there could be special factors that control its segregation . The 2∶1 ratio of oriC to ter foci may suggest a post-replication cohesion , either because regions near ter have not fully duplicated or because fully-replicated sister chromosomes are held together by DNA or protein linkages . Although the marker frequency analysis showing a 1∶1 oriC/ter ratio appears to support the latter explanation , we cannot rule out the possibility that short or heterogeneous unreplicated sequences in the ter region after ppGpp accumulation escape our detection . In any case , this “cohesion” may assist in the organization of chromosome segregation that will occur when cells are released from arrest with multiple chromosomes . We observed a rapid segregation of 4 nucleoids upon release , concomitant with nucleoid compaction , with segregation occurring first at midcell and later at the quarter position . Cohesion at the termini ( Figure 5C ) may restrain segregation of recent sister chromosomes until all others have segregated , a means of enforcing sequential patterns of segregation . In vitro , SeqA wraps DNA , producing positive supercoiling and can form cooperative self-aggregates [56] . This aggregative property , specifically altered in seqA N-terminal mutants , is implicated in the formation of visible foci colocalized to the replication fork and for promoting organization of the origin [31] , [57] . The effects exerted by SeqA in origin-proximal cohesion could act in the same manner at the termini to promote their cohesion . We do note that , as ter is the last region to be replicated , its hemimethylated GATC sites should be bound by SeqA prior to segregation , giving the opportunity for SeqA to control separation and segregation of this region of the chromosome . Chromosome cohesion by prolonged binding during ppGpp accumulation could , in turn , signal a block to cell division . Alternatively , apparent cohesion of sister chromosome could be mediated by DNA topological links . SeqA interacts with Topoisomerase IV , with the potential to modulate decatenation of the replicated chromosomes [58] . In vitro , at moderate levels of SeqA , decatenation and relaxation by Topo IV is stimulated by specific recruitment of the enzyme . At high levels , SeqA promotes catenane formation by Topo IV by promoting intermolecular aggregates . In either case , an increased probability of intertwined , catenated chromosomes upon induction of the stringent response could explain failure of the terminus regions of the chromosome to segregate after replication . Although our genetic analysis places SeqA and Dam in the cell cycle aspect of the stringent response , the direct connection between ppGpp , changes in the transcriptional program and modulation of SeqA or Dam methylase activity remains to be elucidated . Neither SeqA nor Dam bind guanine nucleotides; therefore some factor responsive to ppGpp is implicated in their control . An obvious candidate is RNA polymerase . Although transcription is required to initiate replication ( and is therefore blocked by the RNA polymerase inhibitor , rifampicin ) , the mechanism of this control is still obscure , since promoter activity at oriC is not required for initiation under normal conditions [59] . We note that many of the strains defective in stringent control of replication , such as seqA , dam , oriCm3 and dam overexpressors , may also exhibit rifampicin-resistant replication , as evident in run-out experiments , suggesting some connection between the two phenomena . An attractive model is that transcription sensitive to ppGpp may be required to reverse inhibitory effects of SeqA on replication initiation and chromosome segregation . This could be because SeqA binding blocks some DNA site required for cell cycle progression , with the act of transcription of this locus directly reversing this . Or alternatively , ppGpp-sensitive transcription of some unknown gene may be required to dissociate SeqA . Previous reports have shown that DnaA expression decreases during the stringent response [35] . Although this may play some role in stringent control of replication initiation , this alone appears unlikely to mediate all stringent response effects on cell cycle . We were not able to suppress seqA defects in stringent arrest by dnaA mutants with reduced initiation efficiency . Moreover , DnaA is unlikely to directly influence chromosome segregation arrest during the stringent response . Nonetheless , it is possible that multiple mechanisms of cell cycle control , such as the DnaA levels and the regulatory inactivation of DnaA ( RIDA ) , cooperate to control cell cycle in response to ppGpp .
Escherichia coli K-12 strains ( Table 2 ) were grown at 30°C , 34°C , 37°C as previously described on Luria-Bertani ( LB ) medium , consisting of 1% Bacto Tryptone , 0 . 5% yeast extract , 0 . 5% sodium chloride and , for plates , 1 . 5% agar or in M9 minimal medium ( 48 mM Na2HPO4-7H2O , 22 mM KH2PO4 , 8 . 5 mM NaCl , 19 mM NH4Cl , 2 mM MgSO4 and 0 . 1 mM CalCl2 ) with 0 . 2% glucose , 0 . 4% glucose , or 0 . 4% arabinose , and 0 . 2% casamino acids with 1 . 5% agar for plates . For P1 transductions and phage lysates , cultures were grown in LCG , LB medium supplemented with 1% glucose with an additional 2 mM calcium chloride; for plates , 1% agar was added . Antibiotics were used in the following concentrations: ampicillin ( Ap ) , 100 µg/ml; kanamycin ( Km ) , 60 µg/ml; tetracycline ( Tc ) and chloramphenicol ( Cm ) , 15 µg/ml . Isogenic strains in MG1655 were constructed by P1 vira transduction . Cultures employed M9 minimal media described above with the addition of 1 mg/ml DL-Serine hydroxamate ( Sigma ) or , in the case of strains harboring pALS13 ( pRelA′ ) , 1 mM isopropyl β-D-1-thiogalactopyranoside IPTG for 1 . 5 hrs . Addition was made in early logarithmic growth of the culture , at OD600 of ∼0 . 2 . Experiments examining chloramphenicol-induced translational inhibition were performed with the addition of 300 µg/ml chloramphenicol for 1 . 5 hrs . Release from DL-serine hydroxamate was accomplished by centrifugation of the treated culture and resuspension of the cell pellet in an equal volume of fresh medium without the drug . For experiments employing radioactive inorganic phosphate labeling , MOPS-buffered minimal medium was used ( 50 mM MOPS pH 7 . 2 , 43 mM NaCl , 93 mM NH4Cl 1 mM MgSO4 , 3 . 6 µM FeSO4-7H2O , 0 . 12 mM CaCl2 and either 2 . 2 mM or 0 . 4 mM KH2PO4 ) . DNA content per cell was determined as described [49] . Briefly , 1 ml of culture was fixed in 9 mls of 70% ethanol and stored at 4°C until staining . For staining , fixed cultures were resuspended in 1 ml phosphate-buffered saline ( PBS ) pH 7 . 4 . The samples were incubated with 100 µl PicoGreen dye ( Invitrogen ) , diluted in 1∶100 in 25% DMSO for 3 hr at room temperature , and then further diluted with an additional 1 ml PBS containing PicoGreen ( 1∶1000 ) . Cultures were analyzed by using a FACSCalibur flow cytometer and FloJo 6 . 4 . 1 software . As a control for chromosome number , a stationary phase wild type culture and an isogenic dnaA46 strain , temperature sensitive for replication initiation , was analyzed similarly after 3 hr of growth at 42°C . Overnight cultures were inoculated into fresh medium at a dilution of 1∶100 and grown with aeration for 3 hours . Nucleoid staining was performed as previously described [28] . For DAPI staining alone , cultures were fixed in 3∶1 methanol acetic acid . 10–20 µl of cells was placed on poly-L-lysine hydrobromide ( 1 mg/ml ) -coated slides and air-dried . Cells were washed 3 times with 1× Phosphate-Buffered-Saline ( PBS [pH 7 . 4] ) and allowed to air dry . Cells were then stained with 10 µl of 10 µg/ml DAPI ( 4′ , 6′ diamido-2-phenylindole ) for 10 min and washed three times with PBS and mounted in 1 mg/ml p-phenylenediamine 90% glycerol in PBS , mounted with 5 µl VectaShield mounting medium and analyzed as described below . Living cells harboring pALA2705 ( ParB-GFP ) were grown at 34°C without supplementation of isopropyl β-D-1-thiogalactopyranoside ( IPTG ) to induce synthesis of the GFP fusions . A suspension of growing cells was added to a 2% agarose pad ( MP Biomedicals , Inc ) and covered with a cover slip over the residual media . Slides were analyzed with an Olympus BX51 microscope equipped with a RGB liquid crystal color filter . Images were acquired with a Qimaging Retiga Exi camera by using the manufacturer's software . Foci counts were obtained using Openlab Darkroom imaging software ( Improvision , Coventry , United Kingdom ) and edited with Openlab and Adobe Photoshop Elements 4 . 0 . Cells were grown to exponential growth phase in M9 0 . 4% glucose CAA medium . Samples were taken and chromosomal DNA was extracted using the MasterPure DNA Purification Kit ( Epicentre ) . Restriction digest and preparation of the probe were done as described previously [60] . Briefly , the chromosomal DNA was triple digested with EcoRI , HindIII , and EcoRV and the fragments were separated on a 1 . 0% agarose gel . The DNA was vacuum-transferred to a nylon membrane ( Amersham ) . The membrane was prehybridized with BSA for more than 1 h at 65°C and hybridized overnight at 65°C with 32P a-dATP . The probe consisted of two DNA fragments that anneal to the chromosomal regions gidA ( 84 . 3 min ) , and relB ( 34 . 8 min ) . The DNA fragments were labeled using Random Primer Labeling ( Molecular Cloning ) . After hybridization , the membrane was washed with 0 . 21 M Na2HPO4 ( pH 7 . 3 ) / 6% SDS / 0 . 85 mM EDTA 3× for 10 minutes at 25°C followed by 2× for 5 minutes at 65°C . The membrane was exposed on a Phophoimaging screen ( Molecular Dynamics ) and scanned on a Bio–Rad Molecular Imager FX ( Bio-Rad ) . Analysis of bands was carried out using Quantity One imaging software ( Bio-Rad ) . Normalization of the bands was accomplished using genomic DNA from dnaA46 that was grown at the non-permissive temperature for 2 h . Overnight cultures grown in M9 CAA media were diluted 1∶100 in fresh media and grown to an OD600∼0 . 3 . 10-fold serially diluted cultures were plated on M9 minimal media plates containing ampicillin and 100 µM IPTG . Total colony numbers were determined by plating on M9 ampicillin medium without IPTG . Colonies were counted after 48 hours of growth at 37°C . The number of independent cultures , as indicated in figure legends , was determined on at least three different days . Overnight cultures were diluted 1/50 in M9 CAA media and grown to an O . D . 600∼0 . 2 . Where indicated , cells were treated with serine hydroxamate . Pulse labeling was initiated by the addition of 20 µCi of [3H] uridine per 2 ml of culture . Uracil was added to 0 . 9 mg/ml after a ten minute pulse . Total RNA was extracted from 0 . 5 ml by the RNAeasy kit ( Qiagen ) . Purified RNA was resuspended in RNase free water and stored at −20°C . Approximately 1 µg of RNA sample was analyzed by electrophoresis in a 1% non-denaturing agarose gel . After electrophoresis , the gel was photographed under UV light . Amount of rRNA was determined by band intensity of the 16S , 23S , and unprocessed rRNA bands in the image using Quantity Oneâ imaging software ( Bio-Rad ) . To determine the amount of [3H] labeled rRNA , corresponding rRNA bands were cut out from the gel , dissolved , and analyzed in a scintillation counter . Normalization was achieved by dividing the obtained cpm by the volume of rRNA band intensity . Overnight cultures grown in MOPS pH 7 . 2 medium containing 2 mM phosphate ( KH2PO4 ) and 0 . 2% casamino acids were diluted 1∶100 into MOPS medium containing 0 . 4 mM phosphate and 0 . 2% casamino acids . Treated samples received 1 mg/ml SHX before the addition of [32P]H3PO4 to a final concentration of 200 µCi/ml when the culture OD600 reached ∼0 . 05 . Total RNA was isolated after 15 minutes of incubation with [32P]H3PO4 . RNA was isolated using the RiboPure Bacteria Kit from Ambion according to the manufacturer's instructions . Total RNA was electrophoresed on a native agarose gel and stained with ethidium bromide . rRNA bands were visualized and quantified by UV- light induced fluorescence using Quantity One software ( Bio-Rad ) . RNA was then transferred to a nylon membrane ( Amersham ) using the Vacuum Blotter 785 ( Bio-Rad ) . The amount of radiolabeled rRNA was determined by autoradiography and quantified using MolecularImager FX PhosphorImager and Quantity One software ( Bio-Rad ) . Amount of radiolabeled rRNA was normalized to the amount of RNA observed by UV-light induced fluorescence . ( p ) ppGpp measurements were performed as previously described [61] . Overnight cultures grown in MOPS minimal medium containing 0 . 4% Glucose 2 mM phosphate ( KH2PO4 ) and 0 . 2% casamino acids were diluted 1∶100 into the same MOPS medium except containing 0 . 4 mM phosphate . [32P]H3PO4 was added to a final concentration of 100 µCi/ml when the OD600 reached ∼0 . 05 and cultures grew for an additional 3 hours before the first sample was taken . SHX was added at time 0 , and samples were isolated every ten minutes by mixing 100 µl of culture with an equal volume of 13 M formic acid and chilling on dry ice . The samples were subjected to two rounds of freezing and thawing before microcentrifugation at 14 , 000 rpm for 2 minutes to remove cellular debris . 6 µl of supernatant were spotted onto 20×20 cm polyethyleneimine cellulose on polyester TLC plates ( Sigma ) in 1 . 5 KH2PO4 ( pH 3 . 4 ) for 2 h . After chromatography , nucleotides were visualized by autoradiography and quantified with a MolecularImager FX PhosphorImager and Quantity One software ( Bio-Rad ) . Unlabeled GDP and GTP were spotted on the plates as markers and visualized after chromatography by UV light-induced fluorescence . The identities of the labeled ( p ) ppGpp were inferred from their positions in the chromatograph relative to the origin and GTP . ( p ) ppGpp levels are normalized to levels of GTP observed in the same sample . | Management of cell growth and division in response to environmental conditions is important for all cells . In bacteria , nutritional downturns are signaled by accumulation of the nucleotide ppGpp . Amino acid starvation causes a programmed change in transcription , known as the “stringent response”; ppGpp also causes an arrest of cell cycle in bacteria , whose mechanism has not been thoroughly investigated . Here , we show that E . coli cells , when the stringent response is in effect , complete chromosomal replication but do not initiate new rounds and arrest with an integer number of chromosomes . The number of chromosomes corresponds to the growth rate prior to arrest . In polyploid arrested cells , the chromosomal regions at which replication initiates are segregated , whereas the termini regions remain colocalized . The E . coli chromosome remains decondensed and unsegregated during arrest and rapidly resumes replication and segregation , concomitant with chromosome condensation , upon release . The protein SeqA , a DNA binding protein and negative regulator of replication , is necessary for enforcing this arrest . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [
"microbiology/microbial",
"growth",
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"development",
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"and",
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] | 2008 | The Stringent Response and Cell Cycle Arrest in Escherichia coli |
Sound waveforms convey information largely via amplitude modulations ( AM ) . A large body of experimental evidence has provided support for a modulation ( bandpass ) filterbank . Details of this model have varied over time partly reflecting different experimental conditions and diverse datasets from distinct task strategies , contributing uncertainty to the bandwidth measurements and leaving important issues unresolved . We adopt here a solely data-driven measurement approach in which we first demonstrate how different models can be subsumed within a common ‘cascade’ framework , and then proceed to characterize the cascade via system identification analysis using a single stimulus/task specification and hence stable task rules largely unconstrained by any model or parameters . Observers were required to detect a brief change in level superimposed onto random level changes that served as AM noise; the relationship between trial-by-trial noisy fluctuations and corresponding human responses enables targeted identification of distinct cascade elements . The resulting measurements exhibit a dynamic complex picture in which human perception of auditory modulations appears adaptive in nature , evolving from an initial lowpass to bandpass modes ( with broad tuning , Q∼1 ) following repeated stimulus exposure .
Natural sounds carry salient amplitude modulations ( AM ) essential for successful interpretation of auditory landscapes and robust source identification [1–5] . The human auditory system is exquisitely sensitive to relatively slow AM cues , prompting extensive investigation of this ability over several decades [6 , 7] . Recent success in modeling recognition of environmental sound textures [8] , speech [9–11] and music material [12–14] has now prompted the need to consolidate the exact nature of modulation filtering [15–18] . Early measurements of sensitivity across AM rates seemed consistent with low-pass characteristics ( running average over time ) as envisaged by the ‘linear envelope detector’ ( LED ) model [6 , 19 , 20] . However , this class of experiments often posed interpretational challenges . For example , under some stimulus and experimental conditions only parts of the dataset conformed to low-pass characteristics [6 , 15 , 21–23] but not others [16 , 24 , 25] . Plausible accounts of these apparent inconsistencies involved shifts in task strategies and/or decision statistics [15 , 21] , whereby listeners would rely on different cues under conditions associated with different portions of the dataset and/or subtle stimulus alterations [26–28] . Strategy shifts of this kind are relatively common [29] ( e . g . off-frequency listening [30] ) . Therefore , our first goal was to assess the extent to which endogenous adaptive strategies can influence the measurements of the modulation filter when no stimulus and/or task-related factors are concomitantly modified . Specifically , we sought to adopt a single stable measurement approach throughout ( the reverse correlation method ) , reasoning that systematic changes in the subjects’ detection strategies would be unveiled as a dynamic evolution of the filter estimates during the experimental session [31–33] . The shortcomings of the low-pass AM filter model have since spurred development of alternative models which augmented it with , for example , an autocorrelation stage [34] , or the current dominant framework of the modulation filterbank ( MFB ) [16 , 35] . This latter model consists of a low-pass filter ( up to 2 . 5 Hz ) and a bank of band-pass filters spanning the ∼5–100 Hz range . Thanks to its increased sophistication and flexibility , the MFB is able to account for a wide range of psychophysical [16 , 24 , 36–39] and physiological [35 , 40–42] results . Nevertheless , there remain several important details of these hypothesized filters that have not been adequately constrained by available data . For instance , filter tuning ( Q-value ) has often been assumed to measure ∼2 [35] , yet other studies have indicated a significantly lower value ( <1 ) [25] . Furthermore , another study set out to test the ability of the modulation filter bank model to account for dependence of AM envelope detection on the nature of the carrier . It reported that the model significantly underestimated the detrimental effects of carrier periodicity on modulation detection , a finding that has cast a shadow of uncertainty on certain aspects of the filterbank model [34] . Another unexplained finding concerns the lack of persistent low-level adaptive effects in these postulated filters [18] , suggesting that they are more dynamic and likely more susceptible to cognitive control ( e . g . by the details of the measurement task [43] ) . With specific relation to psychoacoustical literature using decision weights [44] ( a technique related to the reverse correlation approach used here ) , the bandpass signatures expected of the MFB model are not directly evident through previous filter estimates [45–48] ( we return to this issue in Discussion ) . Consequently , the second goal of the present study is to measure these bandpass filters in an unconstrained manner to allow for data-driven conclusions that are largely independent of model specifics . To do so , we relied on a combination of powerful system identification tools and AM-tailored stimulus perturbations that enabled us to describe a more dynamic picture of the underlying process encompassing both LED and MFB modes of operation . Our findings largely confirm the three critical questions we sought to address: ( 1 ) the measured bandpass channels undergo characteristic changes to reflect listeners’ strategy shifts from using a combination of loudness and spectral-profile cues ( both existing in the presented stimuli ) in the early part of the experiment , to relying primarily on the spectral-profile cue during later phases; ( 2 ) the Q-values associated with these channels are ∼1 , although this characteristic is itself subject to recalibration as assessed by our measurement task and analysis; and ( 3 ) the modulation filter bank ( augmented by a low-pass characteristic with a low cut-off [35] ) remains the most parsimonious model for auditory modulation processing .
Ethics approval was obtained from the College Ethics Review Board ( CERB ) at Aberdeen University ( http://www . abdn . ac . uk/clsm/working-here/cerb . php ) . All listeners gave written informed consent . The auditory stimuli ( delivered binaurally via Sennheiser HD202 headphones ) were specifically designed to encode task-relevant AM modulations into the envelope of the acoustic signal in a manner suitable for experimental characterization using psychophysical reverse correlation [49] , and their parameters were specified to lie in the perceptually salient range for AM processing ( <30 Hz ) . The 300-ms carrier was a segment of white noise ( 5 kHz bandwidth , 10 kHz sampling rate ) that was generated once at the beginning of each block and identically replicated throughout the entire block; on any given block , no variability/perturbation was therefore introduced by the fine temporal structure of the stimulus ( see further below and S6 Fig for additional analyses demonstrating that carrier-induced AM deviations had no impact on our results ) . Stimulus perturbation was instead applied to the overall amplitude of the carrier in a stepwise fashion: the stimulus waveform was subdivided into 9 temporal segments ( each lasting ∼30-ms ) and the amplitude of each segment was controlled independently [46] . In the absence of an applied increment/decrement ( signal ) , a given segment was assigned a fixed baseline level ( indicated by leading and trailing ends of red line in Fig 1A ) of ∼62 dB SPL . The ‘increment’ signal was generated by increasing the amplitude of the central segment within the stimulus waveform ( peak of red line in Fig 1A ) to ∼68 dB SPL ( we use ∼ because the exact values were tailored to each listener to target individual threshold performance and therefore differed across listeners ) ; the temporal scale of this modulation was chosen to match ecologically relevant AM cues [1 , 50] , and its AM pulse-like specification was chosen to ease application of analytical/theoretical results dependent on signal shape [51] . The target signal was then added to a noise waveform generated by applying a random Gaussian-distributed increment/decrement to the overall amplitude of each segment , independently for different segments ( Fig 1C ) ; the resulting signal+noise trace ( Fig 1E ) was presented together with a noise-only trace on every trial , and listeners were asked to detect the former in a two-interval-forced-choice ( 2IFC ) protocol . The jitter introduced by the noisy modulation was approximately ±2 . 2 dB standard deviation around baseline level . In a separate series of experiments we asked the same listeners to detect a signal defined by a decrement ( rather than an increment ) in the amplitude of the central segment ( Fig 1B ) from a baseline level of ∼68 dB to ∼62 dB . Some previous studies on AM minimized the role of loudness cues by roving the absolute levels of individual stimuli [44 , 52]; we deliberately avoided this manipulation because it amplifies the role of gain control [53] , a nonlinear effect that may have compromised interpretation of the nonlinear kernels [51 , 54]: roving stimuli span a wide level range for the purpose of rendering overall absolute level ineffective as a cue for performing discrimination , however they also require listeners to factor out overall level via gain control ( or analogous mechanisms ) to compute relative filter outputs; this dynamic nonlinear operation is difficult to incorporate into the cascade models that form the theoretical underpinnings of the present study [51 , 58] , potentially complicating kernel analysis beyond the level of interpretability afforded by analyses like those favoured here that do not involve parameter fitting . Following their response ( via button press ) , auditory feedback ( correct/incorrect ) was provided immediately; the next trial automatically initiated after a 1-second delay . At the end of each block , listeners received an auditory summary ( via an automated system based on segments of human voice ) detailing the total number of collected trials and the percentage of correct responses on the last block as well as averaged across all blocks . We tested 10 listeners , all naive except author EJ ( indicated by square symbol in all Figures ) , with ages 28±9 years ( mean±SD across listeners ) . Listeners were initially familiarized with the task during preliminary training sessions consisting of ∼20 trials without noise . They were presented with noiseless versions of both signal+noise and noise-only stimuli , preceded by explicit verbal indication of whether they would hear the former or the latter . They were then asked to indicate the signal+noise interval and provided with trial-by-trial feedback ( correct/incorrect ) . After this preliminary phase , we adjusted noise levels individually to target optimal threshold regimes for the deployment of reverse correlation [55] ( S1 Fig ) . Percent correct was 74%±6% ( increment detection , 5 . 5k±2 . 8k trials per listener ) and 76%±7% ( decrement detection , 3 . 6k±3 . 3k trials per listener ) . We successfully minimized response bias across listeners ( S1B Fig ) ; this is particularly important when attempting nonlinear system identification to avoid bias-induced modulations within nonlinear kernels: in the presence of bias , 2nd order kernels ( see below for detailed description/definition ) may contain modulations that do not reflect the structure of the perceptual machinery preceding the binary behavioural decision , but are instead produced by the nonlinear nature of the conversion from decision variable to binary output which , in general , is not relevant for characterizing the perceptual machinery itself as it is protocol-specific [51] ( i . e . it depends on the arbitrary way in which listeners are asked to express their percept , whether via binary choice ( ‘yes’/‘no’ , ‘present’/‘absent’ ) or rating scale , for example ) . Internal noise was within the expected range for human psychophysics [56] ( S1C Fig ) , indicating that listeners adopted a robust task strategy , as also evidenced by the relatively high absolute efficiency ( within the normal range for detection [57] and much higher than observed for other auditory tasks [58] , see S1D Fig ) . All aspects of performance metric analysis indicate that 1 ) listeners performed the above-detailed tasks in a stable and efficient manner , with no discernible difference in overall performance metrics between increment and decrement experiments ( data points fall around diagonal unity line in S1 Fig ) ; 2 ) our protocols successfully established optimal conditions for the application of behavioural reverse correlation [49 , 51 , 56] . The modulation filtering models are referred to as LED/MFB models . They are normally implemented as illustrated in Fig 2 . For the purpose of examining how these models relate to our protocols , we treat the incoming stimulus as defined in AM space ( i . e . as a 9-element vector where individual entries indicate the amplitude of each segment ) because this is the stimulus subspace within which input noise was applied ( see Fig 1 ) ; in other words , cochlear filtering ( top in Fig 2 ) is reduced by our stimulus generation protocols , because noise is applied not to the fine structure of the stimulus waveform but to its AM profile . The LED involves application of a low-pass filter [6] to the ( modulation ) envelope , while the MFB applies primarily band-pass filtering [16] . This front-end stage is illustrated in Fig 2A and 2B for LED and MFB respectively . With reference to the 9-element input vector where each entry refers to a different time point , this filtering stage consists of convolution between this input vector and a temporal impulse response L1 . We represent the filter frequency characteristics in Fig 2 ( blue ) because they are easier to interpret as lowpass/bandpass , but our L1 estimates are initially recovered as temporal impulse responses ( Fig 3B ) because they are obtained via direct reverse-correlation of the input stimulus ( defined across time ) . The output from the L1 layer ( which is itself a function of time ) is then passed onto a decision stage that generates a psychophysical response ( red rectangle in Fig 2 ) . The details of how this stage operates are still unclear [15 , 21] . We can describe the sequence of operations carried out by LED/MFB models using the same general cascade , as illustrated in Fig 2C . In this formulation , the LED/MFB filters correspond to different characteristics for the first filtering stage L1 . Subsequent decision stages are approximated by a combined nonlinear-linear operation ( red outlines in Fig 2C ) . For example , if read-out involves energy extraction from the temporal output returned by L1 , N corresponds to squaring and L2 to sum over time . Similar approximations can be adopted for root-mean-square and MAX rules [51 , 58] . The two filters L1 and L2 are referred to as the cascade filters . Our goal is to estimate their structure via the psychophysical kernels we can measure from data ( see below ) ; this is achieved by exploiting a set of analytical tools that establish important connections between cascade filters and psychophysical kernels [59] . Psychophysical kernels are used as compact descriptors of stimulus properties that impact listeners’ decisions in simple detection/discrimination tasks [51 , 60] . The most effective approach to an intuitive understanding of the 1st order kernel is to think of the underlying perceptual process as a matched template that assigns a set of weights to different elements of the stimulus , sums across all elements , and finally converts this weighted sum into a binary decision of the kind ‘I saw the target’ or ‘I did not see it’ [49 , 61] . For this model , the psychophysical 1st order kernel ( computed as described below ) is an image of the template [49 , 60]: it details the perceptual impact associated with different portions of the auditory waveform . It also does not matter whether the kernel is computed from noise modulations associated with the target or not: in both cases , it will reflect the template associated with the model outlined above , if this model provides an adequate account of the perceptual process [49 , 60] . There are many conditions , however , when the 1st order kernel does not retain the intuitively transparent interpretation proposed above , e . g . in the presence of a nonlinear transformation between the stimulus and the response such as a dependence on the power or correlational structure of the stimulus [62 , 63] . In order to extract useful information about the underlying process , it then becomes necessary to study higher-order descriptors such as the 2nd or 3rd order kernels [64] , requiring more data and elaborate models . For example , the 2nd order kernel is useful if we suspect that the perceptual process assigns a set of weights to all possible pairwise interactions between different elements of the stimulus , e . g . between the amplitudes of the first and the second segments of the auditory waveform , or between the amplitudes of the first and third segments , and so on . These interaction terms would provide additional information about the stimulus properties that affect listeners’ choices beyond the description afforded by the 1st order kernels [51 , 59 , 64] . To compute 1st and 2nd order kernels , we denote the AM noise modulation applied on the target-present ( q = 1 ) or target-absent ( q = 0 ) interval of a trial to which listeners responded correctly ( r = 1 ) or incorrectly ( r = 0 ) by the 9-element vector n[q , r] . The first-order target-present psychophysical kernels ( i . e . those obtained only from noise trials containing the target ) were computed as p 1 [ 1 ] = avg ( n [ 1 , 1 ] ) - avg ( n [ 1 , 0 ] ) where avg ( . ) is used to indicate average across trials of the specified type [49]; the target-absent kernels were p 1 [ 0 ] = avg ( n [ 0 , 0 ] ) - avg ( n [ 0 , 1 ] ) . The second-order psychophysical kernels were similarly computed as p2 = cov ( n[1 , 1] ) + cov ( n[0 , 0] ) − cov ( n[1 , 0] ) − cov ( n[0 , 1] ) where cov ( . ) indicates covariance across trials . Please see [51 , 60] for further details of these methods . Cascade filters and psychophysical kernels are different classes of objects . Cascade filters are filtering components of a hypothesized cascade model; for the L1NL2 cascade described previously , they cannot be estimated directly from data via simple rules . They can , however , be estimated indirectly via the psychophysical kernels . Psychophysical kernels are data descriptors computed directly from the raw data using simple rules ( see above ) ; in this sense , they are not dissimilar from simply computing a summary statistic ( e . g . mean or median ) from a dataset . Their estimation is robust and does not depend on any assumed underlying model . If a model is assumed , the kernels can then be used to characterize specific components of the model . For example , the LN model is widely adopted for this type of application [49]; in its psychophysical variant , this model reduces to template matching for the L stage [51] , i . e . inner product between the input stimulus and the L template [65–67] . Under this model , the first-order psychophysical kernel returns a scaled image of the template L [60] , allowing for direct transparent estimation of the linear filtering stage . For the purpose of our study the LN model is inapplicable as it predicts [49 , 51 , 58 , 68 , 69] that perceptual kernels derived from noise modulations associated with signal+noise stimuli ( ‘target-present’ ) must match those derived from noise-only stimuli ( ‘target-absent’ ) . This property is a consequence of the linear nature of the L stage , combined with the classic reverse-correlation result that the static nonlinear N stage is bypassed by the kernel estimation procedure [60 , 70 , 71] . The response of L to signal+noise is simply the sum of its response to signal plus its response to noise , effectively decoupling the noise-driven response from that associated with the signal . The filter perturbation associated with the noise element is therefore statistically analogous between signal+noise and noise-only stimuli , leading to equivalent kernel estimates [68 , 69] . This prediction is not born out by the results in S2A and S2B Fig which show that target-absent and target-present first-order kernels respectively are markedly different ( compare not only the shape of the traces , but also the scaling of ordinate between S2A and S2B Fig; see also [72] and S7A Fig ) . This finding is consistent with the expectation that the underlying mechanism would more likely conform to cascade models including additional filters , e . g . the L1NL2 cascade in Fig 2C ( see more below ) ; because this cascade does not belong to the LN family of models , it does not predict that target-present and target-absent 1st order kernels should match but rather that ( in general ) they should differ [51] , as we observe . Under the L1NL2 cascade model , the connection between filter components ( L1/L2 ) and psychophysical kernels ( p 1 [ 1 ]/p 1 [ 0 ]/p2 ) is provided by the following three theoretical results ( #1-2 pertaining to L1 , #3 pertaining primarily to L2 ) . Result #1: target-present first-order kernels ( Fig 3A ) return an approximate image of L1 autocorrelation [51]; we can exploit this result to study the characteristics of L1 , with the cautionary note that the relationship between p 1 [ 1 ] and L1 involves other terms besides L1 autocorrelation and that the relative contribution of these terms depends on stimulus SNR [51] . Result #2: L1 can also be estimated from second-order kernels by exploiting the established result that the first row ( or column ) of the second-order kernel ( black and red rectangles in S2C and S2D Fig , replotted as traces in Fig 3B ) returns an approximate image of L1 [51 , 59 , 64] . This is the approach typically adopted for solving L1NL2 cascades [59 , 64]; we conform to this practice by relying primarily on these L1 estimates here . We can cross-check the consistency of L1 estimates returned by these two approaches: if we take the autocorrelation of the trace in Fig 3B and plot it in the inset to Fig 3A , it should resemble the trace in Fig 3A . This prediction is well realized by data ( see also S2B and S2E Fig ) , thus lending further support to the applicability of the associated analytical tools to the present context . We can also estimate L2 by relying on the additional result ( #3 ) that target-absent first-order psychophysical kernels ( S2A Fig ) return the cross-correlation between L1 and L2 , as detailed in [51 , 73] . We can then deconvolve the L1 estimates ( obtained as described above ) out of target-absent first-order kernels to obtain estimates for L2 . The additional deconvolution step involved in deriving L2 partly justifies the noisiness associated with the aggregate estimate in Fig 2D ( shading shows ±1 SEM; this is compounded by computing the power spectrum from time-based filter estimates before combining them across listeners , who naturally displayed a significant degree of individual variability ) . Notice that all our conclusions are based on quantitative analysis of individual listener data ( Figs 4 , 5B–5D and 5F ) ; aggregate estimates are shown for visualization purposes only . In practice , L1/L2 estimates will be distorted images of the kernels associated with theoretical accounts of L1NL2 cascades due to analytical approximations [51 , 73] and the highly nonlinear properties of AM extraction [16] , but the qualitative nature of their filtering characteristics ( whether low- , high- or band-pass ) is preserved in the presence of these distortions ( as we have verified via Monte Carlo simulations of full-scale models explicitly encompassing all stages from cochlear filtering to binary choice; see S5 Fig for a diagrammatic representation of one such simulation ) . We computed the power spectrum w of each L1 and L2 estimate and gauged its band-pass characteristics using four parameter-free metrics; because target-present kernels ( Fig 3A ) approximate L1 autocorrelation , the corresponding power spectrum was obtained via Fourier transform [74] . The spectral centroid ( Fig 4A ) was f • w ^ where f is the vector of sampled spatial frequencies and w ^ was obtained by normalizing w to sum 1 . The ratio between spectral centroid and SD of w ^ provides a surrogate index of band-pass characteristics for bell-shaped w ^; the transition value from low-pass to high-pass ( marked by vertical dashed line in Fig 4B ) corresponds to a uniform spectrum , for which the centroid/SD ratio is 8 / 2 given the sampling rate used here . To establish a link with existing literature , in Fig 4B we plot this quantity in units of Q , the mean/width ratio for a rectangular shape; the conversion is obtained by approximating an assumed Gaussian shape with a rectangle of equivalent full-width at half-height ( FWHH ) [7] , for which the conversion factor is FWHH = SD × 2 2 log ( 2 ) . AC/DC energy log-ratio ( Fig 4C ) was log[w ( f > 0 ) /w ( 0 ) ] where w ( 0 ) is power at frequency 0 ( DC ) and w ( f > 0 ) is all remaining power in the spectrum . Spectral slope ( Fig 4D ) was the correlation coefficient of w across f . The composite band-pass index in Fig 5D consisted of paired comparisons between ‘early’ and ‘late’ estimates of Q , AC/DC energy log-ratio and spectral slope; because Q is always positive the comparison involved log-ratios , while AC/DC energy log-ratios and spectral slopes ( can be negative ) were compared via subtraction . Increment and decrement experiments were often run in alternate fashion across sessions ( although they were never mixed within the same session/day ) ; for exposure-related analyses ( Fig 5 ) , they were combined following sign inversion for noise modulations from decrement experiments to align them with the increment data . We restricted our analysis to the smallest number of trials collected by any listener ( 3 . 5k ) to make the analysis comparable across listeners ( 35k trials contributed to Fig 5 ) . We split this initial period of data collection into ‘early’ and ‘late’ epochs by assigning the first 1750 trials to the former and the second 1750 trials to the latter . For the 10-epoch analysis ( Fig 5E and 5F ) we split the same period into 10 epochs of 350 trials each . Centroid drift ( x axis in Fig 5F ) is the correlation coefficient of centroid versus logarithm of epoch number . We logged epoch number before computing correlation because the semilogarithmic representation corresponded to an excellent linear fit of the aggregate data in Fig 5E ( see solid gray lines ) . We averaged noise amplitude ( as specified by the 9-element vector n detailed above ) and used it as proxy for the noise-induced DC perturbation of each stimulus . We then took the difference in noise DC content between the two stimuli presented on each trial , and computed the biserial correlation coefficient between this differential DC content and the binary response returned by listeners ( S4B Fig ) . We applied the above calculation only to the noise component of each stimulus ( without target signal ) because , when the signal is included , DC content is almost invariably greater for the stimulus containing the target signal; given that listeners performed above chance ( i . e . their response was correlated with target presence ) , it is trivial that we should find a correlation ( which we do find in all instances ) between differential target-driven DC content and behavioural response . We therefore focused on the behavioural component of the response that was specifically driven by trial-to-trial random fluctuations of DC content ( i . e . those induced by the noise ) , rather than the expected correlation with target presence . We estimated stimulus task-relevant modulation for different centroid values by extracting the AM content of signal+noise and noise-only stimulus waveforms via a bank of 1-octave AM filters centred at 2 , 4 , 8 , 16 and 32 Hz , plus a lowpass filter with a cut-off at ∼1 . 5 Hz ( approximating a DC-driven loudness estimator ) . Each simulation returned the difference between the AM content of the two traces over 1000 trials , and the average of 100 simulations is plotted in Fig 5E ( orange shading; see [38] for related results ) . S5 Fig illustrates this procedure for 1 simulation ( see caption for details of individual panels ) . We also wished to verify that the slight amplitude deviations introduced by the randomly generated carrier ( which was refreshed from block to block , see above ) did not affect our calculations based on the notional AM perturbations specified before application of the carrier to generate the stimulus waveform . To this end , we applied the following energy-based recalibration to the stimulus samples in our dataset: each waveform as it was delivered to the listener was split into 9 segments , and RMS ( root-mean-square ) was computed from each segment to obtain a proxy AM vector equivalent to the 9-element vector specified by our amplitude modulation protocol . We then applied the same kernel estimation procedures used with the pre-specified noise samples to these RMS-corrected samples . The resulting kernel estimates are plotted in S6 Fig , where it can be seen that they demonstrate the same characteristics as obtained before RMS recalibration .
Data from reverse correlation experiments are almost invariably interpreted with relation to a cascade that only incorporates one linear filter L1 applied via template-matching , followed by a threshold conversion to binary decision [49] . However , as discussed in Materials and Methods , this linear-nonlinear ( LN ) class of models is inadequate for our dataset ( we return to this point in Discussion ) . Instead , we adopt the more general and highly successful linear-nonlinear-linear ( L1NL2 ) cascade [64] which , in its most general formulation , serves as a functional approximator of wide applicability [75 , 76] ( notice that the L1 linear stage in the L1NL2 cascade involves convolution , not template matching; see Materials and Methods for further details ) . Qualitative inspection of the second-order kernels associated with the experiments described here appears consistent with this class of models [51 , 64] ( as discussed in Materials and Methods and demonstrated in S2C and S2D Fig ) . Both LED and MFB can be cast in the form of L1NL2 cascades as illustrated in Fig 2 . The only difference between the two models lies in the characteristics of the L1 stage ( blue in Fig 2 ) : low-pass for LED [6] ( Fig 2A ) , primarily band-pass for MFB [16] ( Fig 2B ) . Subsequent stages depend on relatively arbitrary choices of read-out rules [21] , but in general they can all be approximated by the combination of a static nonlinearity ( N ) and a subsequent linear stage ( L2 ) . Established techniques in nonlinear system identification [59 , 64] , combined with idiosyncratic features of their psychophysical variants [51] , can be exploited to derive estimates for both L1 and L2 from first-order and second-order psychophysical kernels like those shown in Figs 3 and S2 ( see Materials and Methods for a more detailed description of the connection between model components L1/L2 and psychophysical kernels ) . Within the framework outlined above , L1 and L2 can be thought of as ‘front-end’ and ‘read-out’ filters . L1 is the component of primary interest for this study , as it supports the distinction between LED and MFB as being associated with low-pass versus band-pass characteristics respectively ( see next section for discussion of recent variants of the MFB model incorporating a lowpass filter [35] ) . Estimates of this filter are depicted in Fig 3A and 3B ( the black trace in A is an estimate of the filter autocorrelation , see Materials and Methods ) . They show that L1 presents band-pass characteristics with Q∼1 centred around 8 Hz ( thus favouring the MFB model overall ) . This band-pass property is not an artefactual distortion induced by the target signal , because it is preserved when estimates are obtained from target-absent noise modulations alone ( inset to Fig 3B ) . As we demonstrate in later sections of this study , it is also an evolving characteristic that may not be present at all stages of stimulus exposure . We quantify this band-pass finding using four different metrics ( Fig 4; see Materials and Methods ) . In all cases , L1 estimate distributions ( solid histograms in Fig 4B–4D ) fall within the highpass/band-pass range , while L2 estimate distributions ( open histograms ) fall within the low-pass range ( the latter result points to a late temporal integration window of 50–100 ms consistent with independent estimates from previous studies [21] ) . More specifically , spectral centroids ( Fig 4A ) for L1 are larger than for L2 ( p<10−5 , unpaired two-tailed Wilcoxon test ) ; Q values ( Fig 4B ) for L1 ( but not L2 ) are significantly larger ( p<10−5 , two-tailed Wilcoxon test ) than expected for a uniform spectrum ( indicated by dashed lines in Fig 4B ) ; the AC/DC energy ratio ( Fig 4C ) is larger than 0 ( p<10−5 ) for L1 ( indicative of band-pass/highpass characteristics ) and smaller than 0 for L2 ( p<0 . 05 ) ; the spectral slope ( Fig 4D ) is positive for L1 ( p<10−4 ) but negative for L2 ( p<0 . 01 ) . It is also noteworthy that results were comparable between datasets from increment detection and decrement detection ( y axis ) : there was no statistically significant difference ( at p>0 . 05 ) for any metric and for either L1 or L2 ( data points scatter around solid unity lines in S3 Fig ) . Such convergence of independent datasets indirectly validates our estimation procedure and suggests that increments and decrements may be processed by the same perceptual mechanism ( as also indicated by the similarity in performance metrics , see S1 Fig ) . The overall conclusion from the above analyses is that the L1 filter is band-pass; therefore , AM processing resembles the characteristics of the MFB more than the LED model . This conclusion is not the product of fitting either model to the data: it is based on non-parametric characterization of the front-end filter associated with a general framework cascade that encompasses both models ( Fig 2 ) . All estimates described above were obtained by pooling trials across the entire data collection period undertaken by each listener , spanning several sessions on different days . The characteristics of the perceptual process may have undergone substantial modifications over this extended period , particularly considering that listeners received trial-by-trial feedback and were therefore encouraged to optimize their strategy . To investigate this possibility we defined early versus late epochs for data collection ( see Materials and Methods for definition ) . The L1 estimates associated with the two epochs differed: only the ‘late’ estimate ( black in Fig 5A ) exhibited band-pass characteristics . In contrast , the ‘early’ estimate ( green in Fig 5A ) was closer to low-pass ( see also AM frequency plots within inset ) . Similar exposure-mediated changes in kernel structure have been previously reported in the vision literature [31 , 32]; Fig 5 offers the first demonstration for auditory processing . The above result is supported by metric analysis of individual listener data: Q estimates ( x axis in Fig 5B ) are significantly larger ( at p<0 . 01 ) than the lowpass/highpass cut-off point ( orange vertical dashed line ) for the late epoch ( black ) , but not for the early epoch ( green ) . We further probed this result with paired data analysis by computing a composite shift index for band-pass characteristics from early to late in each condition and each listener ( see Materials and Methods ) ; the resulting distribution ( orange in Fig 5D ) was significantly shifted away from 0 ( p<10−4 ) in the direction of greater band-pass for the late epoch . This shift in band-pass value was accompanied by a significant shift in filter centroid ( Fig 5C ) . Although more elaborate interpretations are possible , a parsimonious view of our measurements suggests that the shift involved an adjustment of the same underlying filter population , rather than ad-hoc neural assembly of a new filter bank: the ‘late’ dataset overlaps with the ‘early’ dataset in Q-centroid space , only restricted to a smaller region ( compare black and green ovals in Fig 5B ) . When we compare the Q/centroid ranges spanned by the two epochs , we find that the lower percentile boundary ( 5% ) shifts from 0 . 27 ( early ) to 0 . 44 ( late ) for Q and 2 . 7 to 5 . 1 for centroid , but the higher percentile boundary ( 95% ) remains virtually unchanged at 1 . 5 ( Q ) and 10 Hz ( centroid ) . A different but equivalent way of conceptualizing this result is to describe the early-late shift as reflecting differential weighting of two discrimination strategies: one relying on loudness , the other on the spectral shape of the modulation frequencies ( temporal profile ) , both driven by valid cues for performing the task ( see below for further discussion of this point ) . In the early phase , the two strategies would coexist and support discrimination to a roughly equal extent; in the late phase , the temporal profile strategy would play a more prominent role . The above interpretation is consistent with an additional analysis where we estimated coupling between listeners’ choices and the differential DC content ( proxy for loudness ) of the noise samples presented on those same trials ( see Materials and Methods ) . In the early phase , we found that correlation values across listeners were significantly different than 0 ( data points in S4B Fig fall to the right of the vertical dashed line at p<0 . 02 ) , indicating that the behavioural choices made by listeners were at least partly driven by stimulus loudness . In the late phase , correlation values did not demonstrate a significant shift away from 0 ( data points in S4B Fig scatter around the horizontal dashed line at p<0 . 23 ) , indicating that loudness did not play a significant role in driving behaviour during later phases of data collection . The filter bank proposed by recent versions of the MFB model [35] , encompassing a lowpass filter in the very low modulation range and bandpass filters at higher modulation rates , could accommodate our results when combined with appropriate weighting profiles . In this sense , our data provide support for a mixed lowpass/bandpass version of the MFB model combined with a flexible read-out stage that may undergo internally driven retuning . The lowpass filter recovered by our protocols should not be confounded with the processing stage preceding the filterbank in early formulations of the MFB model [39]; this stage does consist of a lowpass filter , but with a much higher cut-off frequency of 150 Hz . The lowpass filter of interest for the present discussion is therefore best viewed as a subcomponent of the filter-bank itself operating in the very low frequency range , rather than a separate earlier stage extending to the high frequency range . To gain better insight into the temporal evolution of the exposure-mediated effects , we obtained centroid estimates across 10 different epochs of data collection . Centroid estimates drifted exponentially towards higher values ( Fig 5E ) matching closely the estimated modulation content of the stimulus ( indicated by orange shading , see Materials and Methods and S5 Fig ) , and this effect was surprisingly robust across listeners: even though drift ( see Materials and Methods for definition ) returned a noisy measurement for individual listeners ( see 95% confidence intervals in Fig 5F ) , it was consistently positive ( symbols fall to the right of vertical line in Fig 5F ) so that the overall trend across listeners was highly significant ( p<0 . 005 ) . The above-detailed modifications of filter structure were associated with only mild improvements of absolute efficiency in some listeners ( S4A Fig ) . This apparent decoupling between filter estimates and performance metrics is a well-documented finding in relation to various perceptual phenomena [77–79] including learning [33] . Direct coupling is theoretically expected only for LN models [80] which are not applicable to our experiments as pointed out earlier; therefore , the estimated filters cannot be transparently linked to discrimination performance . Even if they were , there are at least two reasons why one may not expect to see performance differences . First , learning effects on AM discrimination are small and difficult to expose ( often requiring >100 listeners , see [81] ) . Second , successful discrimination in our task was supported by both lowpass and bandpass stimulus power ( see two peaks in S5I Fig ) ; in this respect our protocol differs from the equally valid ones adopted by previous studies ( e . g . [82] ) with the specific goal of excluding loudness cues ( see Materials and Methods for clarifications as to why we deliberately avoided a stimulus design that would invalidate loudness cues ) . Because filter structure shifted between these two equivalent sources of task-related information ( see above ) , discrimination performance may well remain unchanged even though supported by different regions of AM frequency . Prompted by the above results , we re-analyzed data from a prior published study [58] to determine whether similar effects could be exposed for an independent dataset collected using substantially different stimulus/task designs . At the time when this dataset was published , the exposure-mediated effects reported in the present study were not known . We converted perceptual filters from the previous study into a format comparable with the one adopted here and applied the same analysis; as demonstrated in S7 Fig , we obtained remarkably similar results , including lowpass-to-bandpass retuning during the first ∼4K trials .
This study represents the first targeted application of psychophysical reverse correlation to AM processing . Although related tools have been applied successfully in auditory neuroscience [83] and psychoacoustics ( see [84] and [85] for the case of spectral processing and [48] for an application to a loudness illusion ) , they have not addressed the specific case of modulation perception [86] , possibly due to multiple challenges associated with this question . First , there is the critical issue of which stimulus dimension should be perturbed by the noisy process in order to provide meaningful and feasible leverage for tapping into the mechanisms responsible for analyzing AM signals . Adding acoustic white-noise is inappropriate , partly because the envelope fluctuations it induces are difficult to control and exercise adequately , and partly because the dimensionality of the space needing characterization is impractically large to measure [86] . Second , there is the question of whether the analytical toolkit associated with reverse correlation is sufficiently flexible to accommodate both LED and MFB: in the vast majority of its applications , reverse correlation is tightly coupled with the assumption of the linear-nonlinear ( LN ) cascade [49 , 87] . Neither LED nor MFB can be correctly approximated by this model ( and our data fail to comply with its basic prediction that target-present first-order kernels must match corresponding target-absent estimates , compare black versus orange traces in Fig 3A ) , requiring more elaborate analytical tools . To overcome these challenges , we exploited techniques from nonlinear system identification analysis [59] where the coupling between input noise and output response is used not only to compute linear descriptors of the sensory process [55 , 85 , 87] , but also nonlinear ( second-order ) descriptors that afford the opportunity to characterize more complex cascades than LN [64] . In particular , these additional tools can effectively constrain linear-nonlinear-linear ( LNL ) cascades [51] to which both LED and MFB likely conform when formulated with reference to the stimulus dimension perturbed in the experiments described here ( Fig 2 ) . By combining these system identification tools with AM-tailored stimulus perturbations , we gained sufficient insight into the perceptual process to constrain its properties via data-driven characterization . To appreciate the significance of the analysis adopted here , it is instructive to consider first-order filter estimates from target-absent noise modulations alone ( orange trace in Fig 3A ) . This measurement is similar to the decision weight profiles reported by loudness studies [44–48] , including evidence for a primacy effect ( larger weights during early phase of the stimulus [47] , see orange trace in Fig 3A ) , and is often regarded as a more appropriate description of the filtering process [88 , 89]; more importantly , these measurements ( from previous studies as well as our own ) present lowpass characteristics , with no evidence of bandpass AM filtering . Signatures of bandpass processing are exposed specifically by second-order kernels ( Fig 3B ) . Indeed , when the dataset from [48] is re-analyzed using the nonlinear tools described here , bandpass filtering becomes evident at the level of second-order kernels in the presence of decisively lowpass first-order kernels [90] ( see [91 , 92] for related examples from the vision literature ) . A further enabling factor in the experiments reported here is the stability of task rules and impenetrability of cognitive introspection . Specifically , listeners in these experiments carried out the same task throughout data collection and it is extremely unlikely that from one trial to the next they could explicitly monitor all small deviations introduced by the noisy process and introspect cognitively on those to reach a decision . They therefore operated under relatively stable conditions ( except for potential intrinsic changes in adaptive state ) , allowing us to confidently treat our dataset as reflecting the properties of the same perceptual machinery throughout [31 , 32] ( even though specific parameters within that machinery may change with exposure ) . These advantages carry the cost of unusually large data mass ( for this study we collected ∼100k trials ) , restricting our investigation to only a limited ecologically relevant portion ( 3–12 Hz ) of the system’s operating regime , however they allow us to exclude stimulus-driven alterations . More specifically , previous literature has shown that auditory perceptual templates depend not only on signal spectrotemporal structure [26] but also on signal intensity [27] ( see [92–94] for related results in the vision literature ) . Furthermore , strategy shifts not dissimilar from those we report here can be triggered by simple stimulus modifications such as signal-masker asynchrony [28] . It is therefore critical to use stable task rules and a statistically invariant stimulus throughout ( as we have done in this study ) if one is to ascribe spontaneous filter changes to the perceptual system alone . Over the past decades , evidence in favour of LED/MFB models [7 , 20] has been interpreted in the light of fitting procedures around specified computational implementations and often requiring ad-hoc adjustments for different datasets , weakening the associated conclusions regarding the applicability of one model over the other . Our approach did not favour any specific model , nor did it involve explicit implementation of those or other computational schemes . At the same time , it enabled model selection while retaining close proximity with data structure . These methods uncovered a more complex picture than initially suggested by the LED/MFB dichotomy . Although the low-pass/band-pass distinction retains its descriptive power in relation to our dataset , the underlying mechanism displays dynamic adaptive properties that potentially depend on various factors , most notably learning-mediated plasticity [95–99] ( see also expectation effects on AM processing [29] ) . This raises the possibility that previous diverse interpretations of the results ( with respect to lowpass versus bandpass filtering ) may in fact both provide adequate representations of the underlying process , albeit under different learning states [18] . For example , long-term release from adaptation of postulated bandpass filters [18] may need to be re-interpreted in the context of exposure-mediated reweighting across the filter bank , rather than evidence against low-level adaptation within the MFB ( as originally hypothesized in [18] ) . This interpretation may be verified/falsified using the tools developed and validated in this study . A further unresolved issue concerning the LED/MFB distinction pertains to the specific Q value associated with AM filtering . It was originally hypothesized that the filterbank associated with the MFB exhibits slightly different Q’s for low versus high modulation rates [16]: above ∼10 Hz , filters would span a bandwidth that increased with center frequency; below ∼10 Hz , bandwidth would remain roughly constant regardless of center frequency . Our dataset presents sufficient variability of estimated central spectroid to span the 3–10 Hz range ( y axis in Fig 5B ) , allowing us to test the latter hypothesis directly . We find that the hypothesized trend is well supported by data: if filter bandwidth is relatively independent of center frequency , the ratio between center frequency and bandwidth ( Q ) should scale with center frequency; consistent with this prediction , we measured a strong correlation between spectral centroid and Q for both early ( r = 0 . 89 , p<10−7 ) and late ( r = 0 . 9 , p<10−6 ) epochs ( see tilted ovals in Fig 5B ) . However , the specific values hypothesized for bandwidth ( Q≈2; [16] ) are higher than suggested by relevant studies ( Q≈1; [24 , 25] ) and by some of the values we measured in this study ( Fig 4B ) . Our results indicate that , even when restricted to comparable regions of AM rates , aggregate Q values may span a 0 . 3–1 . 7 range depending on the degree of recalibration undergone by the system via exposure/learning ( see data scatter across x axis in Fig 5B ) , consistent with the latest estimates [24 , 25] but substantially lower than the values employed by recent modelling work [35 , 39] . To what extent do our results depend on the stimulus parameters and task specifications selected for this study ? As explained earlier , we were constrained in our ability to test a wide range of configurations , however we did perform measurements using increment as well as decrement target signals . The spectral profile of task-relevant stimulus information is substantially different between these two configurations: in the increment case , the useful bandpass region lies between 8 and 20 Hz ( S5I Fig ) , while the decrement configuration mostly targets the 4–8 Hz region ( S5J Fig ) . As for the lowpass ( loudness ) cue , it required opposite read-out rules for the two configurations ( target signal is louder in the increment configuration , and softer in the decrement configuration; see peaks of opposite signs in the lowpass region of S5I and S5J Fig ) . Despite these differences in the stimulus , we observed no difference between increment and decrement estimates of bandpass tuning ( S2 and S3 Figs ) , and we found no correlation/relationship between the exposure-mediated effects ( Fig 5E and 5F ) and the relative exposure to increment versus decrement signals . Furthermore , the very fact that these characteristics ( both centroid and Q values , Fig 5B–5D ) changed with exposure in the face of an unchanging stimulus indicates that they are not solely driven by stimulus specification . This is not to say that our estimates are completely decoupled from the chosen stimulus/task parameters: by requiring observers to detect a specific signal , we are implicitly prompting them to calibrate their available perceptual resources in relation to the assigned task and signal [92 , 94]; for example it is conceivable that , in extreme cases such as detection of very narrow AM pulses with a broad modulation spectrum , the measured filters may become broader reflecting stimulus characteristics [93] . However , beyond the inevitable structure imposed by task instructions and signal specification on listeners’ selection of perceptual resources , our measurements appear to reflect properties that are instrinsic to the perceptual process and informative of its inherent characteristics . Finally , targeted re-analysis of an earlier published dataset [58] exposed structure entirely consistent with the results reported here ( S7 Fig ) , providing strong validation of our findings: due to numerous design differences between the two studies , it is not trivially expected that we should find similar overall characteristics . In summary , the experimental approach adopted in this study has enabled us to examine outstanding issues in the AM processing literature from a different perspective , and clarify important aspects of this phenomenon , enabled by a set of tools that has not been previously applied with relation to this phenomenon . We have delineated the relationship between LED and MFB models within the context of a prominent theoretical cascade framework [100] , we have refined and further constrained previous estimates of channel selectivity for processing amplitude modulations , and we have demonstrated its spontaneous adaptive nature in the context of active listening tasks ( see also [31 , 32] ) . Further research and additional characterization will be necessary to establish the applicability of our findings across a wider range of tasks and determine the exact nature and functional purpose of exposure-dependent adaptive processes [101 , 102] . | Amplitude modulations are considered the key carriers of intelligible information in auditory signals , and consequently it is of significant interest to discover how they are neurally analyzed and perceptually encoded . A dominant model has emerged from extensive experimental and theoretical studies of this phenomenon . This model posits that amplitude modulations are parsed into channels of different temporal rates via a bank of bandpass filters . Using exclusively data driven approaches with minimal assumptions about the structure of the model , the picture that emerges is of an adaptive process . Initially , human listeners in these tasks perceive modulations as if through a lowpass filter with very low cutoff frequency , which gradually evolves to become a broadly tuned bandpass process at higher modulation frequencies , reflecting the modulations of the target stimuli . This surprising dynamic characteristic emphasizes the plastic nature of modulation analysis in sensory perception . | [
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"(mathemat... | 2016 | Dynamic Reweighting of Auditory Modulation Filters |
Intra-protein information is transmitted over distances via allosteric processes . This ubiquitous protein process allows for protein function changes due to ligand binding events . Understanding protein allostery is essential to understanding protein functions . In this study , allostery in the second PDZ domain ( PDZ2 ) in the human PTP1E protein is examined as model system to advance a recently developed rigid residue scan method combining with configurational entropy calculation and principal component analysis . The contributions from individual residues to whole-protein dynamics and allostery were systematically assessed via rigid body simulations of both unbound and ligand-bound states of the protein . The entropic contributions of individual residues to whole-protein dynamics were evaluated based on covariance-based correlation analysis of all simulations . The changes of overall protein entropy when individual residues being held rigid support that the rigidity/flexibility equilibrium in protein structure is governed by the La Châtelier’s principle of chemical equilibrium . Key residues of PDZ2 allostery were identified with good agreement with NMR studies of the same protein bound to the same peptide . On the other hand , the change of entropic contribution from each residue upon perturbation revealed intrinsic differences among all the residues . The quasi-harmonic and principal component analyses of simulations without rigid residue perturbation showed a coherent allosteric mode from unbound and bound states , respectively . The projection of simulations with rigid residue perturbation onto coherent allosteric modes demonstrated the intrinsic shifting of ensemble distributions supporting the population-shift theory of protein allostery . Overall , the study presented here provides a robust and systematic approach to estimate the contribution of individual residue internal motion to overall protein dynamics and allostery .
Allostery is the process by which signals are transmitted from distal ligand binding sites to functional sites in proteins . The concept of allostery originated from early attempts to explain the fact that the binding of oxygen molecules to hemoglobin deviates from the typical Michaelis-Menten kinetics model . [1–3] Following the term “allosteric” being coined and reviewed during early 60’s , [4 , 5] two protein allostery theories were proposed and referred to as the Monod−Wyman−Changeux ( MWC ) [6] and Koshland−Neḿethy−Filmer ( KNF ) [7] models . In these models , allostery theories were formed based on significant conformational changes of hemoglobin observed in crystallographic structures . In addition to hemoglobin , allostery with conformational change has been observed in other proteins such as aspartate transcarbamoylase , [8] insulin , [9] trypsin , [10] and caspases[11] . In these proteins , the binding signal is assumed to be transmitted through protein conformational change . Multiple allostery theories have evolved based on experimental and theoretical studies . [12–27] The classical “induced fit” model[28–30] fits well to protein conformational changes upon ligand binding observed in hemoglobin . [31] However , a more recent “population shift” model of protein allostery[32–35] is strongly supported by sophisticated NMR experiments . [36–38] In this model , no conformational changes can be detected throughout the process in which proteins carry out their functions . Instead , allostery-triggering events alter the distribution of the protein ensemble among distinctive sub-states . Many computational methods have been developed to delineate protein allosteric mechanisms in atomic detail and to facilitate development of allostery theories . Some methods are mainly based on protein tertiary structure comparison using topology or graph theory for analysis . [39–45] Some methods analyze energy-based residue-residue interactions to explore residue coupling . [46–50] Normal mode analysis ( NMA ) [51] is employed based on the elastic network model ( ENM ) [52 , 53] or the Gaussian network model ( GNM ) . [54] These models provide coarse-grained protein structure descriptions , which reduce the computational cost to probe the protein’s vibrational modes . Modes with low frequency and large magnitude presumably correspond to allosteric mechanisms . [55–58] Molecular dynamics ( MD ) simulation is the most widely used and direct means to simulate protein dynamics . Thus , it is frequently used with certain modifications to investigate protein allostery as a dynamical process . Ota and Agard proposed the MD-based anisotropic thermal diffusion ( ATD ) method to probe energy dissipation pathways in proteins . In this method , a single residue is heated in a protein at an extremely low temperature ( approximately 10K ) to probe energy dissipation pathways . [59] Sharp and Skinner developed a pump-probe MD method that perturbs protein dynamics by exerting oscillating forces on target residues . [60] Long-time MD simulations were carried out and subjected for further analysis to reveal protein allosteric effects in several other studies . [35 , 61–64] Deep understanding of protein allostery remains elusive despite the experimental and theoretical studies done thus far . More methodological development is needed to quantitatively evaluate the effect of individual amino acid residues on overall protein dynamics . Although mutagenesis studies can provide valuable information about the impact of changing specific residues on protein activity , systematically posing perturbation on individual residues provides an alternative way to probe the effect of the internal motions of specific residues on protein dynamics or to discover the function of individual residues without changing their chemical entity . Applying rigid constraints on selected degrees of freedom in protein structure has been implemented to probe protein allostery . [65–67] Alternatively , we recently developed a simulation method , referred to as rigid residue scan ( RRS ) , [68] to systematically probe the impact of each individual residue on overall protein dynamics through rigid body MD simulations using an efficient integrator . [69] In this study , the entropy calculation and principal component analysis are combined with the RRS method to evaluate the effects of internal motions from individual residues on overall protein dynamics as well as allostery upon ligand binding .
The all-atom RMSD for the unperturbed unbound and bound states ( without rigid residue perturbation ) of PDZ2 are shown in Fig 1 , which indicates that both structures are stable throughout the simulations . The RMSD plots of all RRS simulations are listed in S1 Table . In general , the RRS simulations are stable throughout the simulations , with the majority of the simulations having average RMSD under 2 Å ( Fig 2 ) . To assess the overall conformational change upon binding and rigid residue perturbation , averaged structures of PDZ2 were calculated for each simulation . Using the averaged structure of PDZ2 from unperturbed unbound simulation as reference structure , the all-atom RMSD of all other averaged structures were calculated and plotted in Fig 2 . For most of the RRS simulations , both unbound and bound , the average structures have RMSD between 1 . 5 and 2 . 0 Å , with very few exceptions . Entropy contributions from PDZ2 are estimated using the method[70 , 71] described in the Computational Methods section for all the unperturbed and rigid body perturbed simulations . The heat maps of cross-correlation matrices ( based on which the entropy was calculated ) are provided for all the simulations in S2 Table . Using the entropy of PDZ2 from unperturbed simulation of unbound state as reference , the relative entropies of PDZ2 ( ΔS ) from all the simulations are plotted in Fig 3 and listed in S3 Table . The ΔS are also sorted with ascending order and listed in S4 Table . For both unbound and bound states , the entropy of PDZ2 significantly increases for most of the RRS simulations . The changes of unbound PDZ2 entropy in rigid residue simulations comparing to unperturbed simulations vary from −0 . 100 to 0 . 254 kcal/ ( mol•K ) with average as 0 . 058 kcal/ ( mol•K ) and unsigned average as 0 . 066 kcal/ ( mol•K ) . For the bound state , the PDZ2 entropy differences in rigid residue simulations comparing to unperturbed simulation vary from −0 . 065 to 0 . 405 kcal/ ( mol•K ) with average as 0 . 060 kcal/ ( mol•K ) and unsigned average as 0 . 071 kcal/ ( mol•K ) . Overall , in 80 unbound and 68 bound RRS simulations , the ΔS of PDZ2 is positive . This is counterintuitive , because treating a residue as a rigid body removes the internal degrees of freedom of that residue and should reduce the overall entropy . Furthermore , we calculated the PDZ2 entropy difference between two states ( ΔΔS ) by subtracting the unbound state entropy from the bound state entropy with the same residue being held rigid ( Fig 4 and S3 and S4 Tables ) . The absolute ΔΔS values range from 0 . 001 to 0 . 341 kcal/ ( mol•K ) ( S4 Table ) . For the two unperturbed simulations , this difference is 0 . 016 kcal/ ( mol•K ) with a higher PDZ2 entropy from the bound state ( Residue 0 in S3 and S4 Tables ) . For the 11 residues being held rigid , the absolute ΔΔS is smaller than 0 . 016 kcal/ ( mol•K ) ( S4 Table ) . Seven among these 11 residues , D15 , T28 , V40 , T81 , R31 , L78 , L18 , were reported as important allosteric residues from an NMR study of PDZ2 bound to the RA-GEF-2 peptide ( Table 1 ) . [72] The error bar of PDZ2 entropy calculations was estimated for both unbound and bound states of PDZ2 in unperturbed simulations and seven RRS simulations ( Table 2 ) . For these simulations , the PDZ2 entropy was calculated based on seven sets of 30 ns ( total of 210 ns ) trajectories . The standard deviation ( σ ) and 85% Confidence Interval ( CI ) of each state is rather small , indicating the convergence of simulation within 30 ns of trajectories . The standard deviation ( σ ) and 85% CI of ΔΔS for unperturbed states are 0 . 037 and 0 . 039 kcal/ ( mol•K ) , respectively . It is noticeable that the errors of entropy calculations , although small when compared to the total entropy , are comparable to the differences between simulations . For the unbound state , total of 28 RRS simulations have ΔS smaller than the 85% CI of unperturbed unbound state . For the bound state , total of 53 RRS simulations have ΔS smaller than the corresponding 85% CI ( S3 Table ) . Among seven identified residues , there are three residues ( D15 , T28 , V40 ) with ΔS values higher than the 85% CI of corresponding unperturbed states . Although the cancelling of the error could improve the reliability of the analysis , these comparisons indicate that the uncertainty of calculated configurational entropies requires further improvement , for example by including anharmonicity and higher order correlations , to increase the reliability of the calculations . Velocity autocorrelation analysis was carried out for the unperturbed simulations and the seven RRS simulations listed in Table 2 to estimate the relaxation time in these simulations . Only one trajectory of each simulation was subjected to the analysis . All the selected simulations display a relaxation time around 20 ps ( S1 Fig ) , showing that RRS simulations have similar relaxation time to the unperturbed simulations . From each simulation , the entropy contribution of each residue to total protein entropy was evaluated . Such individual residue entropy contributions are plotted as heat maps for the RRS simulations of both unbound and bound states of PDZ2 ( Fig 5 ) . To make plots clear , the contribution from each individual residue in unperturbed simulations was used as reference in unbound and bound states , respectively . The response of each individual residue varies significantly . The most prominent features in both heat maps are the blue diagonal lines , reflecting the fact that the entropy contribution from each residue diminishes when that residue is held as a rigid body during the simulation . The most recognizable features besides blue diagonal lines are the horizontal lines in both heat maps , either in red or blue . These horizontal red or blue lines indicate that response from some residues to rigid body perturbation is consistent regardless which residue being held rigid in the perturbed simulations . To further illustrate this feature , the average entropic response from each residue in all RRS simulations was calculated and plotted in Fig 6 for the unbound and bound states , respectively . The average entropic responses are also listed in S5 Table and with descending order in S6 Table . The individual residue entropies were also normalized using the number of atoms in each residue following a previous study . [73] The normalized individual residue entropies are illustrated in S2 Fig and S3 Fig . The patterns described above remain the same with the normalized entropies , showing that the differences of residue responses are inherent to each residue and not scaled with residue size . The average entropic responses range between 0 . 0352 and −0 . 0167 kcal/ ( mol•K ) for the unbound state , and between 0 . 0183 and −0 . 0161 kcal/ ( mol•K ) for the bound state . Among the top ten residues with largest average entropic responses in the unbound state , seven residues , R31 , T28 , V61 , L18 , V26 , V22 , N27 , were among the 21 important allosteric residues reported in an NMR study of PDZ2 ( Table 1 ) . [72] However , for the bound state , only four residues , V22 , V85 , V61 , V26 , among top ten residues were reported as important allosteric residues from the same NMR study of PDZ2 ( Table 1 ) . [72] Noticeably , three residues , V22 , V61 , and V26 , are among the top ten residues of both unbound and bound states . Quasi-harmonic analysis was carried out for both unperturbed and RRS simulations . The distributions of density of states from quasi-harmonic analysis of unperturbed simulations are plotted for both unbound and bound states in Fig 7 . Obviously , the binding with the peptide does not significantly affect the distribution of density of states . Similarly , the rigid residue perturbation does not significantly affect the distribution of density of states either ( S4 Fig ) . We further carried out the PCA to evaluate the contribution of each quasi-harmonic mode to overall dynamics , and plotted accumulative contribution of these modes for both unperturbed unbound and bound states in Fig 8 . Low frequency modes significantly contribute to overall protein dynamics . For the unbound state , total of 83 modes with frequency under 18 . 7 cm−1 contribute 90% to the overall dynamics . For the bound state , total of 52 modes with frequency under 13 . 4 cm−1 contribute 90% to the overall dynamics . In both cases , translational and rotational modes are excluded . Because protein allostery is highly dynamical process that couples the dynamics of distal parts of the protein , it is logical to assume that mainly low frequency modes , which involve overall dynamics of proteins , play important roles in protein allostery . To identify significant low-frequency modes , PCA was carried out for the seven 30 ns trajectories as well as total 210 ns trajectories for the unperturbed unbound and bound states , respectively . For the unperturbed unbound state , the dot products were calculated between the five lowest frequency quasi-harmonic modes ( PC1 to PC5 ) of each 30 ns trajectory with the PC1 to PC5 modes from the whole 210 ns trajectory ( S7 Table ) . The same calculations were also carried out for the unperturbed bound state ( S7 Table ) . The unsigned averaged dot product of each mode is listed in Table 3 . Among five modes , only PC1 modes ( with the lowest frequency quasi-harmonic mode ) in both unperturbed unbound and bound states have significant overlap between each trajectory and overall trajectory . The overlaps for PC2 through PC5 are significantly less than PC1 ( Table 3 ) , indicating that these modes and all other modes with higher frequencies do not have physical significance . To further evaluate significance of PC1 modes in the unperturbed unbound state , the dot products among PC1 modes from seven 30 ns trajectories were calculated to produce a 7×7 matrix ( S8 Table ) . The absolute values of off-diagonal matrix elements range from 0 . 694 to 0 . 960 with unsigned average values ( standard deviation ) as 0 . 842 ( 0 . 078 ) . The similar analysis of the unperturbed bound state results in a matrix with absolute values of off-diagonal matrix elements range from 0 . 653 to 0 . 938 with average values ( standard deviation ) as 0 . 781 ( 0 . 089 ) ( S8 Table ) . It should be noted that PC1 modes from 210 ns trajectories of unperturbed unbound and bound states do not overlap significantly with each other ( with magnitude of dot product as −0 . 214 ) . Therefore , two PC1 modes from two states could serve as coherent allosteric modes revealing effect of PDZ2 upon ligand binding . The PC1 modes calculated using 210 ns trajectories of the unperturbed unbound and bound states are used for further analysis in this study . The simulations of unperturbed states are projected onto a 2D surface using two PC1 vectors from unperturbed states to illustrate the distribution of ensemble representing each state ( Fig 9 ) . Despite the close similarity between PDZ2 structures from unbound and bound states , the clear separation between two states on this 2D surface provides more insight into the allosteric difference between these states . The separation of two distributions on the 2D surface was represented by an average distance ( 0 . 734 ) between two attraction basins ( Fig 9 ) . All RRS simulations are also projected onto this 2D surface using the same two PC1 vectors to probe the impact of rigid residue perturbation on the distribution of ensemble on the same surface ( S9 Table ) . For all the RRS simulations , the separation between unbound and bound states distributions resembles the unperturbed states , suggesting that the allosteric effect triggered by ligand binding event is robust upon rigid residue perturbation . However , the average distance between two distributions varies significantly among RRS simulations ( Fig 10 , S10 Table and sorted values in S11 Table ) , revealing the different contribution from each residue in the protein allostery . It is notable that the distribution distances of RRS simulations when residues R31 , V40 , or L78—all identified as key allosteric residues in the NMR study [72]—being held rigid are significantly shorter than the one of unperturbed states .
Individual amino acid residues , which are basic building blocks for protein structures , and therefore serve as the main target for many residue based protein allostery analysis methods , [47 , 74–76] in which residue based interaction energy is the target for analysis . However , because protein allostery is mainly considered a dynamical process , it should be informative to investigate the internal dynamics of each individual residue and their impact on overall protein dynamics . Presumably , the internal degrees of freedom or dynamics of key allosteric residues should play unique roles in allostery with specific impact on overall protein dynamics . The RRS simulations combining with entropy analysis make it feasible to systematically evaluate the contribution from individual residue internal degrees of freedom to overall protein dynamics . Comparison between the unbound and bound states connects such contribution with protein allostery upon binding . Rigid body constraint , which effectively removes the internal degrees of freedom in residue , should theoretically reduce the disorder of the protein as well as the protein entropy . On the contrary , rigid residue constraints lead to the increase of PDZ2 entropies in most RRS simulations . This counterintuitive observation indicates that the internal dynamics of each individual residue in a well-folded protein cooperatively contribute to the overall protein dynamics . In a recent simulation study of protein structures , [77] it was also reported that rigidifying some of protein degrees of freedom often cause more flexibility in other parts and lead to increasing protein entropy . The basic La Châtelier’s principle in chemical equilibrium was referred to govern the rigidity/flexibility equilibrium in protein structure . [77] Seemingly , our observation of increasing protein entropies in rigid residue simulations also agrees with the La Châtelier’s principle . Without rigid body constraints , the binding with peptide leads to slight increase of PDZ2 entropy ( 0 . 016 kcal/ ( mol•K ) ) . This is also in agreement with that the RMSD of PDZ2 in bound state is slightly higher than the one of unbound state ( Fig 1 ) . For only 11 residues among 94 PDZ2 residues , the PDZ2 entropy difference between unbound and bound states from RRS simulations is smaller than 0 . 016 kcal/ ( mol•K ) . Seven among these 11 residues D15 , T28 , V40 , T81 , R31 , L78 , L18 ( Fig 11 ) , were recognized as important for PDZ2 allostery upon binding by the NMR study . [72] All seven residues displayed significant dynamical parameter change upon binding . Although the direct relationship between the present study and NMR study of PDZ2 is not obvious , the overlap between two studies are unlikely to be random coincident . It should not be overlooked that the uncertainty of calculated configurational entropies undermines the reliability of predictions based on these calculations . Nevertheless , the current development is only a small step towards deeper understanding of protein allostery in terms of configurational entropy change . Improvement of configurational entropy calculations by including anharmonicity and higher order correlations will be applied to increase the reliability of the calculations . The remaining residues were also identified by various computational studies as key allosteric residues . R79 was identified as one of “Hot Residues” for allostery in a study using ENM to probe PDZ2 allostery[58] as well as one of “nodes” to form an allostery communication network in another study using protein structure network model . [42] Both residues N14 and E90 were identified as part of an interacting cluster localized at the ligand binding pocket . [47] This strongly suggests that the RRS simulations could reveal the significance of internal dynamics of some key allosteric residues with regard to overall protein dynamics . L18 , as one of identified residues , when being held rigid , leads to the entropy increase of 0 . 045 kcal/ ( mol•K ) for unbound state and 0 . 031 kcal/ ( mol•K ) for bound state , which may be resulted from La Châtelier’s principle of protein rigidity/flexibility equilibrium . [77] However , this residue makes hydrophobic contact with the C-terminal valine of the binding peptide , which may counteract some of the entropy increasing effect . K13 , another key residue for PDZ domain for interaction with binding peptide , forms multiple hydrogen bonds with Gly82 , the backbone and side chain of Thr81 . When K13 being held rigid , the entropy of PDZ2 increases 0 . 013 kcal/ ( mol•K ) for unbound state and decreases 0 . 052 kcal/ ( mol•K ) for bound state . These observations indicate that in RRS , strong interactions between residues being held rigid and ligand may help to counteract the general trend of increasing entropy in rigid body simulations . Another informative analysis presented in this study is the response from each individual residue to perturbations on proteins . By its definition , the mechanism of protein allostery is to be elucidated at overall protein structure level . However , this should not prevent any attempt to evaluate general response of individual residues to external or internal perturbations . Using the estimate of entropic contribution from individual residue in each simulation , the intrinsic difference of response to perturbation from each residue is revealed . Residue R31 is a clear case in the unbound state . Regardless which residue being held rigid , the entropic contribution from R31 is higher than the value in the unperturbed unbound state . Coincidentally , R31 has also been identified based on overall protein entropy change and NMR study[72] discussed in the previous section . On the contrary , this positive entropic response from R31 is inhibited upon binding with the peptide ( Fig 5 and S3 and S4 Tables ) . Another six residues ( T28 , V61 , L18 , V26 , V22 , N27 ) also showed overwhelming positive response similar to R31 , and were also recognized in the NMR study of PDZ2 allostery ( Table 1 ) . The individual residue response pattern is significantly different in the bound state . Residues with consistent entropic response to rigid residue perturbations are very different from those in the unbound state . The observations that some residues display consistent response suggest that these residues are more sensitive to perturbations than other residues . The difference between unbound and bound states shows that the binding event inherently changes the sensitivity of each residue upon the perturbations , reflecting the very nature of protein allostery influenced by binding and perturbation events . Given the sheer number of modes generated from the quasi-harmonic analysis , one definitely suffers the risk of studying trivial and random patterns when focusing on only a few modes related to overall protein dynamics . However , the PCA analyses using multiple trajectories of unperturbed states clearly validate the physical significance of two PC1 modes from two states . The fact that two PC1 modes are virtually orthogonal to each other signifies the relevance between these two modes and protein allostery upon binding . The projection of RRS simulations onto these coherent allosteric modes support the entropy driven theory of protein allostery , [78 , 79] which explain the protein allostery phenomenon as shifting of ensemble distribution upon perturbation instead of significant conformational change observed in either crystallographic[31] or NMR studies . [80] The various distances between two states projecting on the coherent allosteric modes demonstrate the shift of protein ensemble distribution upon rigid residue perturbation , revealing detailed information about individual residue with regard to overall allostery . It is undeniable that the computational cost of the proposed method is exceptionally high compared to many other methods to elucidate protein allostery mechanisms . However , the current goal of our research is to develop an unbiased protocol to assess potential individual residue’s contribution towards overall protein dynamics and consequently allostery , with little or no a priori information about protein allosteric mechanisms . In the experiment , the most feasible way to probe the contribution of each individual residue to protein function is mutagenesis study . However , some knowledge of importance of residues is necessary for the mutagenesis study . Otherwise , all positions should be considered . In addition , it is somewhat arbitrary to choose what amino acids to which the wild type residues should be mutated . From the mutagenesis study , the perturbation added to protein contains two parts: removing the wild type residue and adding the mutated residue . These two parts are distinct but inseparable in the mutagenesis study . Without any a priori knowledge about relationship between protein sequence and allostery , one would mutate every residue to all other 19 natural amino acids to obtain the most comprehensive and unbiased evaluation of relationship between each residue and protein allostery . This is actually what has been done in an experimental study of allostery of another PDZ domain , in which total of 1577 mutants were generated for 83 out of 115 residues . [81] However the equivalent strategy could not be applied routinely to other proteins due to its obvious high cost . In addition to the exceedingly high cost of doing all possible mutations , the effects of removing the wild type residue and adding the mutated residue are still inseparable . One of the main advantages from the strategy presented in this study is that only the internal motion of each individual residue is removed , while the chemical content of the wild type residue is intact . This strategy provides a practical mean to investigate the intrinsic dynamical effect of each individual residue to overall protein dynamics . At this early stage , the RRS simulations were carried out for all residues for the sake of completion . Further improvement of the method is ongoing to significantly reduce the computational cost while keeping the confidence level of the results . In this study , we further developed a recently proposed RRS method through combination of configurational entropy calculation and PCA to systematically evaluate the contribution of internal degrees of freedom of individual residue to overall protein dynamics and potential allostery upon ligand binding . Through the changes of the entropy from whole protein upon rigid residue perturbation , key residues were recognized as those when being held as rigid bodies , the protein entropy difference between unbound and bound states is smaller than the entropy difference from unperturbed simulations . These key residues have good agreement with a previous NMR study of the same protein bound to the same peptide . [72] Entropic response from individual residue upon perturbations was also evaluated . In the unbound state simulations , residues generally displaying increased entropic contribution upon rigid residue perturbation are in good agreement with the same NMR study . [72] The different patterns of individual residue response in the unbound and bound states suggest that the binding event inherently changes the sensitivity of each residue upon the perturbations . PCA of unperturbed states of PDZ2 revealed two quasi-harmonic coherent allosteric modes , which are robust upon analysis of multiple trajectories of each state . The projection of RRS simulations onto coherent allosteric modes reveals the intrinsic shifting of ensemble distributions upon rigid residue perturbations , and supports the population-shift point of view about protein allostery . Overall , the combination of entropy calculation and PCA with the RRS method provides a systematic approach to estimate the individual residue contribution to protein dynamics as well as allostery . Further development is actively under development to reduce the computational cost with deeper understanding of the protein allostery .
The assessment of the role of individual residues in overall protein dynamics is carried out using rigid residue scan , a systematic simulation method developed in our group . [68] In the RRS method , rigid body constraints are applied to each residue in the target protein in separate simulations ( referred to as perturbed simulations ) . Thus , there are as many rigid body MD simulations ( perturbed simulations ) as there are residues comprising the target protein . The second PDZ domain ( PDZ2 ) from the human tyrosine phosphatase 1E ( hPTP1E ) is used as a test protein in this study to further develop the RRS method . The allosteric mechanisms of PDZ2 have been the subject of a number of studies with various residues identified as key allosteric residues . [42 , 47 , 61] Initial crystal structures for the unbound and bound states with RA-GEF2 peptide ( EQVSAV ) were obtained from the Protein Data Bank ( PDB ) with IDs 3LNX and 3LNY , respectively . [82] PDZ2 structures in both 3LNX and 3LNY contain 94 residues . For the residues with multiple copies in the PDB files , the first coordinate set was used to prepare the simulation systems . The structures from the PDB were processed with hydrogen atoms added and solvated in water ( TIP3P ) [83] with charge balancing ions of sodium and chlorine added . Additional ions were included to adjust the ionic strength in simulation cells to about 0 . 02 M . The system was then subjected to energy minimization with 200 steps of steepest descent and 9491 steps of adopted basis Newton-Raphson minimization , which yielded a total gradient of less than 0 . 001 kcal/ ( mol•Å ) . This was followed by an equilibration step that raised the temperature of the systems from 100 K to 300 K over 12 picoseconds ( ps ) . Then the systems were equilibrated via 10 nanosecond ( ns ) isothermal-isobaric ensemble ( NPT ) MD simulations at 300 K and 1 atm . The frame from the simulation trajectory with dimensions closest to the average dimension for the entire trajectory was selected . This set of coordinates and its corresponding velocities were used as the initial conditions for 34 ns canonical ensemble ( NVT ) Langevin MD simulations also at 300 K . The first 4 ns of each NVT simulation was treated as equilibrium , and therefore not included in the reported analysis . The NVT simulations consisted of normal MD simulations without rigid residue constraint for the unbound and bound PDZ2 ( referred as unperturbed simulations ) and the rigid residue scan over all 94 residues in PDZ2 . There are total of 190 simulations , including 188 rigid residue simulations and two unperturbed simulations of unbound and bound states of PDZ2 . Considering 30 ns of each NVT simulation for analysis , this work comprises 5 , 700 ns of simulation time . A 2 femtosecond ( fs ) simulation time step was used in all simulations . To estimate the error bar of the entropy calculations and validate coherent allosteric modes , additional 180 ns simulations were carried out for the unperturbed states and rigid residue simulations corresponding to seven residues ( 15 , 18 , 22 , 28 , 40 , 61 , and 81 ) . Each set of 180 ns simulations were carried out with three independent 60 ns trajectories for better sampling and shorter computing times . All simulations used cubic periodic boundary conditions , and electrostatic interactions were modeled using the particle mesh Ewald method . [84] All simulations were carried out using CHARMM version 38b1 and version 27 of the CHARMM force field . [85] | Allostery is a fundamental dynamics property of many proteins , and plays a critical role in protein functions . Despite extensive experimental and theoretical studies of protein allosteric mechanisms , the current understanding and predicting power of protein allostery are still limited . One of the main challenges in studying protein allostery is effectively narrowing down residues for further site-directed mutagenesis study . Our goal is to develop effective computational tools to systematically evaluate significance of individual residue in protein dynamics and allostery without any a priori knowledge about protein allosteric mechanism . In this study , we significantly enhanced a simulation protocol developed in our lab , rigid residue scan ( RRS ) , through combination of configurational entropy calculation , principal component analysis ( PCA ) , and projection of ensembles onto coherent allosteric modes . Detailed analysis of the impact of removing individual residue internal motions on overall protein dynamics led to identification of key allosteric residues . Our prediction of key allosteric residues has good agreement with experimental studies of an allosteric protein as a model system , which displays allostery through binding events . Interestingly , the entropy calculations suggest that the La Châtelier’s principle in chemical equilibrium may also govern the rigidity/flexibility equilibrium in protein structure , which is related to protein allostery . Our study has demonstrated these methods to be very valuable tools to effectively identify initial key residues for proteins with crystallographic structures and limited information of their allosteric mechanisms . | [
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"enzyme"... | 2016 | Rigid Residue Scan Simulations Systematically Reveal Residue Entropic Roles in Protein Allostery |
The oscillations of the somitogenesis clock are linked to the fundamental process of vertebrate embryo segmentation , yet little is known about their generation . In zebrafish , it has been proposed that Her proteins repress the transcription of their own mRNA . However , in its simplest form , this model is incompatible with the fact that morpholino knockdown of Her proteins can impair expression of their mRNA . Simple self-repression models also do not account for the spatiotemporal pattern of gene expression , with waves of gene expression shrinking as they propagate . Here we study computationally the networks generated by the wealth of dimerization possibilities amongst transcriptional repressors in the zebrafish somitogenesis clock . These networks can reproduce knockdown phenotypes , and strongly suggest the existence of a Her1–Her7 heterodimer , so far untested experimentally . The networks are the first reported to reproduce the spatiotemporal pattern of the zebrafish somitogenesis clock; they shed new light on the role of Her13 . 2 , the only known link between the somitogenesis clock and positional information in the paraxial mesoderm . The networks can also account for perturbations of the clock by manipulation of FGF signaling . Achieving an understanding of the interplay between clock oscillations and positional information is a crucial first step in the investigation of the segmentation mechanism .
A somitogenesis clock , linked to the vertebrate segmentation process , has been uncovered in mouse , chick , and zebrafish [1] . Genes involved show oscillatory expression in the presomitic mesoderm ( PSM ) and are mostly related to the Notch pathway in all three species . In zebrafish PSM , oscillatory genes include her1 and her7 , transcriptional repressors whose expression is thought to be enhanced by Notch signaling , and deltaC , which encodes a Notch ligand; expression of each of these three genes is necessary for correct oscillatory expression of all three [2 , 3] . The Her1 protein represses expression from its own promoter in a cell-culture assay [4] , and it has been proposed that self-repression of her genes could drive the somitogenesis clock [5–7] . Intriguingly , however , morpholino blocking of her1 or her7 mRNA translation can lead to downregulation of their transcription [2] , while a simple negative feedback loop would predict upregulation of transcription if the repressor protein cannot be translated . What is more , the significance of the requirement for Her13 . 2 , a cofactor for Her self-repression [4] , remains unexplored in mathematical models . Here we study computationally the properties of networks where Her proteins must dimerize to act as repressors . Networks are assessed both for compatibility with morpholino knockdown phenotypes and for correct reproduction of the collective creation of an oscillatory pattern in the PSM . Her13 . 2 is expressed in a posterior–anterior gradient in zebrafish PSM and heterodimerizes with Her1 to enhance Her1 autorepression [4] . Dimerization is a common feature of the basic helix loop helix family [8] , and in the following it is assumed that Her13 . 2 can heterodimerize with Her1 or Her7 , that Her1 and Her7 can also homodimerize or heterodimerize with each other , and that the resulting dimers repress expression of her1 , her7 , and deltaC . her1 and her7 share a common 12-kb promoter [2] , which contains nine copies of the consensus hairy binding site ( CACGCG [9] ) . In the model proposed here , depicted in Figure 1 , all dimer combinations between Her1 , Her7 , and Her13 . 2 compete for binding to these sites , and repress her1 and her7 transcription with strengths specific to each dimer combination . It is assumed that the deltaC promoter functions similarly to that of her1 and her7 , in agreement with closely overlapping expression patterns in the PSM [2 , 5 , 6 , 10 , 11]; this does not take into account some differences in expression patterns observed in deltaC mutants [3] . Delays are taken into account for mRNA transcription and export from the nucleus and for protein translation . None of the biochemical reaction rates has been determined experimentally . To investigate the behavior of the model , we therefore sampled values from extended , biologically realistic ranges . We screened for suitable oscillations , with at least a 5-fold difference between mRNA peak and basal levels ( see Methods for a full definition ) , and for reproduction of experimental results obtained by perturbation of the oscillatory machinery . Because mRNA and protein copy numbers often reach low absolute levels at the trough of their oscillatory cycle , the effect of internal noise was assayed using stochastic simulations , with the same parameter sets that were identified as providing suitable deterministic oscillations . Possible reactions in the system were the same in the deterministic and stochastic cases , but stochastic simulations considered all individual reaction events explicitly .
The model depicted in Figure 1 readily gives rise to single-cell oscillations with parameters sampled in the ranges detailed above . A parameter set was deemed robust if each parameter could be varied individually by 50% or more without disrupting oscillations . By this criterion , 50% of 300 randomly selected parameter sets were found to be robust . As a first step to identify parameter sets reproducing the morpholino-induced disruption of the spatiotemporal pattern of oscillation described in [2] , parameter sets were screened with single-cell simulations for downregulation of her1 and her7 mRNA when the Her1 or Her7 translation rates were divided by ten ( corresponding to 90% morpholino efficiency in blocking protein translation ) . Such parameter sets occurred at a low frequency ( see Figure 2 for a representative example ) . While general robustness of the model with these parameter sets was comparable with that in the general case ( 30% of parameter sets were found to be robust ) , the parameters with the strongest influence on the oscillation period were found to be strikingly different . Parameter sets leading to correct reproduction of the morpholino phenotypes also led to a very high sensitivity of the oscillation period to the degradation rate of the Her1–Her7 dimer ( and to a lower extent to various parameters describing its repressive activity ) : for 30% of identified parameter sets , variation of the Her1–Her7 degradation rate yielded a higher variation in period than variation of any parameter not related to delays of transcription and translation . In the general case , period-sensitivity to individual parameter variation was more even across parameters and highest for the her1 mRNA degradation rate . ( For 10% of identified parameter sets , variation of that degradation rate led to the highest period variation amongst parameters other than delays . ) This suggests a central role for a Her1–Her7 heterodimer , which can be tested experimentally . Examination of the parameter values leading to correct reproduction of the her1 and her7 morpholino knockdown phenotypes showed that the repression strength of the Her1–Her7 heterodimer was strongly biased towards lower values than that of other repressive dimers . This suggests that the mechanism by which Her1 and Her7 are required for their own expression is by Her1–Her7 heterodimers acting as a “protective” species: Her1–Her7 heterodimers repress her1 and her7 expression , but compete with other dimer combinations that repress expression more strongly . Parameter sets reproducing the her13 . 2 knockdown phenotype ( which consists of disrupted oscillations [4] ) were identified independently of those reproducing the her1 and her7 knockdown phenotypes and did not show any notable difference in period distribution . Of the parameter sets leading to correct reproduction of her1 and her7 knockdown phenotypes , 10% also led to disruption of the oscillations when her13 . 2 expression was knocked down ( see example in Figure 2 ) . We have so far addressed oscillations at the level of individual cells . One important feature of the somitogenesis clock is that waves of expression sweep from posterior PSM to anterior PSM and shrink in the process [10] . The spread of an intercellular signal is not necessary for the short-term maintenance of the oscillatory pattern in mouse and chick [21–23] , but it has been suggested that cellular oscillators can influence their neighbors [11 , 24–26] . In the case of the chick and mouse somitogenesis clocks , a gradient in the strength of intercellular coupling can lead to the formation of the correct collective pattern of oscillatory expression [24] . In those species , no molecular link is currently known between the oscillatory machinery and positional information in the PSM . However , Her13 . 2 provides such a link in the zebrafish clock [4] , which makes it possible to investigate the detail of the mechanism . To assess whether graded expression of her13 . 2 could prompt a linear chain of oscillators to form the correct collective pattern of oscillatory expression , a screen was carried out in which the dynamic structure of the PSM was reproduced by adding cells at regular intervals at the posterior end of the chain ( corresponding to convergent extension and ingression from the tailbud [27] ) and removing cells at the anterior end . ( Cells were removed continuously , rather than in blocks corresponding to somites , because the process of segmentation , which is controlled by poorly understood molecular mechanisms , is not the subject of this study . ) Each cell influenced its two anterior and posterior neighbors by providing them with the ligand Delta for Notch receptor activation , leading to increased her and deltaC transcription ( the dynamics of Notch signaling were not modeled explicitly ) . Expression of her13 . 2 mRNA was assumed to be high in posterior PSM and to drop sharply in anterior PSM [4]; the regulation of her13 . 2 by FGF-8 was not modelled explicitly . The rates of her13 . 2 mRNA decay and of cell addition at the anterior end set the length of the PSM , and therefore the number of oscillations each cell experienced while in the PSM ( that number was set to 12 , as can be estimated from [3 , 27 , 28] ) . A number of parameter sets were identified for which her and deltaC waves of expression swept from posterior to anterior , their width becoming restricted as they went along ( see Figure 3A–3C and Video S1 for a representative example ) . The number of stripes observable at any given time depends on parameter sets and spans the range observed experimentally ( from one in old embryos at specific phases , to up to three in younger embryos [10] ) ; it was not attempted to reproduce precisely the rate at which stripes decrease in length . Positional information provided by Her13 . 2 , as identified experimentally , is therefore sufficient to arrange oscillatory expression in the PSM in the correct pattern , within the framework of the model proposed here . To determine whether the role of Her13 . 2 is to modulate intercellular coupling or to act on individual oscillators , simulations were run with no intercellular coupling ( this was performed by abolishing DeltaC translation , or by replacing Notch signaling with fictitious autocrine signaling ) . For all parameters studied , it was found that intercellular coupling could be removed without destroying the spatiotemporal pattern . For some parameter sets , this loss of Notch needed to be compensated by an increase in the transcription rates of her1 and her7 . A shift in oscillatory phase and a slight change in the oscillatory period occur when her13 . 2 mRNA expression drops ( unpublished data ) ; this is sufficient to set up the spatiotemporal pattern . Note that this does not contradict the fact that Notch signaling is necessary for oscillations in vivo . The model studied here has parameter sets for which Notch signaling is required for individual cellular oscillations with the correct pattern ( by providing a sufficient level of her expression ) as well as for intercellular coupling . In addition , the model has parameter sets for which Notch is required for intercellular coupling only . The first set of parameters corresponds to the in vivo behavior of the oscillator ( such a parameter set was used to produce Figures 2–6 ) . In vivo , intercellular coupling through Notch signaling could have the additional role of setting up the very first waves of expression , which are not the object of this study . Even if intercellular coupling has no role in the establishment of the oscillatory pattern under the simplified conditions studied here , it could have a crucial role in synchronizing cells in vivo [11 , 29] . Perturbations were simulated by delaying a number of oscillators in the chain by 5 min . For some parameter sets , such perturbations were resorbed within a few rounds of oscillation ( see Figure 3D–3E and Video S1 at 50 min for an example ) . Synchronization was much stronger for cells located in posterior PSM than for cells in anterior PSM . This might be the basis for greater plasticity of posterior PSM as compared with anterior PSM , as observed in chick [30] . To further study the role of intercellular coupling in resistance to noise , the behavior of chains of oscillators in the presence of molecular noise was assessed as described above for individual oscillators . Due to the high computational and memory costs of simulating individual reaction events with delays for a system comprising more than 50 oscillators with 13 variables each , only a very small number of parameter sets could be studied . Nonetheless , parameter sets were identified for which the patterns of oscillation in stochastic simulations were as expected , close to the deterministic form ( Figure 4 and Video S2 ) . For such parameter sets , closely similar successive rounds of oscillation showed low variability between stochastic realizations . A stochastic simulation was run with disrupted coupling , with the same parameter set as used in Figure 3 . A few cells went noticeably out of synchrony with their neighbors , and local synchrony was generally not as strong as with coupling , but the global spatiotemporal pattern was not disrupted ( Figure 4D–4F and Video S3 ) . Thus , even though this parameter set leads to perturbation resorption in posterior PSM ( Figure 3D–3E ) , the molecular clock is sufficiently precise that this capacity is not required to maintain the spatiotemporal pattern with the molecular noise simulated here . Morpholino knockdown of her1 leads to residual her1 and her7 oscillations in posterior PSM and to defective stripe formation in anterior PSM [2] . Knockdown of her7 leads to expression of her1 throughout the PSM ( with no stripes ) and to posterior expression of her7 [2] . Detailed comparison of simulation data and experimental data is not possible because the latter is not quantitative , but most general features can be reproduced . Simulated knockdown of her1 or her7 on the parameter set used in Figure 3 showed residual oscillations in posterior PSM , with a high level of basal expression ( see Figure 5A–5B and Video S4 for the her1 knockdown , and Video S5 for the her7 knockdown ) . These residual oscillations were also present in anterior PSM , but no clear stripes of expression were formed , in agreement with experimental data . The simulations showed that her1 and her7 , with the biochemical parameters used , have essentially symmetrical roles . ( This is because many parameters for her7 were chosen to be the same as that of their her1 counterpart , to make the computational study tractable . ) Some asymmetry has been reported based on knockdown phenotypes [2]; for example , her1 knockdown leads to some her1 expression in anterior PSM , while her7 knockdown leads to loss of expression of her7 in anterior PSM . It is possible that some of this asymmetry stems from differences in mRNA in situ hybridization detection thresholds , which are unknown ( her7 could have a higher detection threshold than her1 ) . Simulated knockdown of her1 and her7 together showed upregulated expression in posterior PSM and a salt-and-pepper pattern in anterior PSM ( Figure 5C and Video S6 ) . This is consistent with experimental results showing generalized upregulation [5] . There was a slight discrepancy in that salt-and-pepper expression has been reported to occur throughout the PSM rather than specifically in anterior PSM [5]; this remains to be investigated . Strikingly , individual cells oscillated in the anterior PSM , even though the global pattern appeared constant . This brings computational confirmation to the hypothesis that a salt-and-pepper pattern can occur by desynchronization of cells , rather than by blocking of oscillations at different phases of the cycle in different cells [11] . In the double morphant , the clock started oscillating around the transition between posterior and anterior PSM . Because the oscillation period was roughly similar , the number of cycles experienced by cells in the PSM was about 50% lower than normal . Another way in which the spatiotemporal oscillatory pattern can be disrupted is by grafting FGF-8 coated beads . This leads to minimal disruptions of oscillations when the bead is adjacent to posterior PSM , but to anterior extension of waves in the anterior PSM [31] . Such grafting experiments were simulated by assuming that an ectopic stripe of high her13 . 2 mRNA expression is induced around the bead ( Figure 6 and Video S7 ) . When the bead was adjacent to posterior PSM , oscillations were not affected because the bead was assumed not to further increase her13 . 2 expression . When the bead reached anterior PSM , posterior oscillations were still unaffected , but anterior oscillations , if imaged at the right phase , could show anterior extension of a wave in anterior PSM .
Direct characterizations of molecular interactions in the zebrafish somitogenesis clock network are scarce . Many dimerization combinations remain untested , and potential binding sites on the her1–her7 and deltaC promoters remain unmapped . It would be a daunting task to test all possible molecular interactions and measure all biochemical reaction rates; the theoretical work presented here makes readily testable predictions and identifies select biochemical parameters of the network that are likely to have great impact on its behavior . The existence of Her1–Her7 heterodimerization is a key feature to explain her1 and her7 morpholino knockdown phenotypes , with Her1–Her7 dimers having a protective role by competing with other dimers that repress transcription more strongly . The half-life of the Her1–Her7 heterodimer is predicted to have an important influence on the period of oscillation . Interestingly , dimerization of clock proteins is a feature shared with mouse and chick somitogenesis clocks [32] . However , the mechanism in those two clocks seems to be very different in that Lunatic fringe—which potentiates Notch activation by its ligand Delta—oscillates along with other clock genes , and that a positive feedback loop is likely to drive the oscillations [24] . The models studied here were kept simple to make it easier to extract essential features . The cellular aspects could be expanded by taking into account cell cycling throughout the PSM [29] , blocking of mRNA transcription and protein translation in the mitotic phase of the cell cycle , possible cell mingling ( observed in chicken [33 , 34] ) , and the effect of coupling on a 2-D or 3-D set of oscillators ( rather than on a linear chain as in this study ) . It was assumed that the somitogenesis clock is already active in PSM progenitors ( this has been suggested for early oscillations in chick [35] , but does not seem to have been addressed in zebrafish ) ; it would also be possible to have the clock inactive in progenitors and kick-started when cells join the posterior PSM . The molecular networks could also be expanded by having different enhancers active in posterior and anterior PSM , as shown experimentally [2] . This study shows that the presence of such different enhancers is not a fundamental requirement of the somitogenesis clock , but it might allow finer reproduction of the spatiotemporal pattern of gene expression and of its disruption by morpholino knockdown . Such an extension of the model might also allow for a role of fused somites , a gene essential for somite formation [36] , whose activity is required for the propagation of expression waves into anterior PSM [6 , 10 , 37] . This study addressed the molecular mechanism of the somitogenesis clock oscillations . The mechanism by which the oscillations are read out to control mesoderm segmentation is not fully understood and is likely to be linked to the complex process of somite polarity establishment , most thoroughly studied in mouse [38] . Interestingly , out-of-phase oscillation of dimerization partners has been proposed as a mechanism to establish somite polarity [39]; however , the proteins considered in the present model do not oscillate out of phase . A model for segmentation based on reaction–diffusion of factors promoting anterior or posterior somite fate has also been proposed [40] , but the genes considered in the present model cannot be related to such factors in a straightforward fashion . A “clock and wavefront” model , first proposed by Cooke and Zeeman [41] , is most often invoked to explain segmentation . However , modifications of the original model [30 , 42] suppose that clock and FGF-8 wavefront are independent , which has previously been shown not to be the case ( [31]; see also Figure 4I in [30] ) . The present study details a molecular mechanism with strong experimental support by which FGF-8 interacts with the clock to regulate the spatiotemporal pattern of oscillation . This will in turn make it possible to investigate how clock and wavefront interact to regulate segmentation .
Deterministic oscillations were considered suitable if each interpeak distance in the course of the simulation fell between 10 min and 100 min , and if the amplitude of the peaks was sufficiently high , both in relative terms ( at least a 5-fold difference between minimal and maximal values ) and absolute terms ( at least 30 molecules at the peak value ) . Potentially spurious peaks arising within 10 min after a previous peak were discarded from the analysis . Both her1 and her7 mRNA oscillations were assayed , each was required to meet these criteria , and the number of peaks undergone by each could not differ by more than one ( so as to ensure roughly similar oscillation periods ) . Only her1 mRNA period oscillation was measured ( her1 and her7 play symmetrical roles in the models studied here ) , either as the distance between the last two peaks in a simulation run , so as to allow the system to have likely reached a limit cycle after the zero initial conditions used to start the simulation , or as the average of all distances between consecutive peaks in the simulation . The algorithm above requires the absence of monotonicity changes between major peaks . As a control , a different algorithm was also used: the autocorrelations of the her1 mRNA copy numbers through time were computed for increasing timeshifts starting from zero , and the period considered to be the first nonzero timeshift that produced a local maximum of the autocorrelation value . For deterministic simulations , the results were very close to that of the algorithm described above . Deterministic simulations were performed with an adaptive-stepsize , 4th-order Runge–Kutta–Fehlberg algorithm [43] implemented in a custom C++ program ( available on request ) . Numerical accuracy ( taking into account both absolute and relative accuracies [43] ) was set to 1% . Time points where derivatives are discontinuous ( because of delays or because of the introduction or removal of oscillators in a chain of coupled oscillators ) were forced to be part of the integration mesh . To speed up computations and ease RAM requirements , a subset of past solution values was stored , and delayed values required by the derivative function were linearly interpolated . To ascertain the accuracy of this method , a subset of results were compared with that obtained with a method providing 4th-order interpolation [44] , with storage of all past integration steps; no significant difference was observed . Stochastic simulations were implemented following the Gibson–Bruck algorithm [45] , with a custom C++ program ( available on request ) . Simulations were carried out on a set of PowerPC G5 iMacs , PowerPC G5 PowerMacs , and Intel Core Duo iMacs ( totaling about 16 processors ) , using GNU gcc 4 . 0 . 1 ( with optimization setting on fast ) and Intel icpc 9 . 1 as compilers , and on two SGI ALTIX 350 servers comprising a total of 32 Intel Itanium 2 processors and 64 GB of RAM , using gcc 3 . 2 . 3 ( with optimization setting on fast ) or icc 8 . 0 as compilers ( the ALTIX servers being essentially used for stochastic simulations of chains of oscillators ) . | Vertebrate embryos acquire a segmented structure along the anteroposterior axis . Segmentation is critical for patterning of other structures ( such as nerves , vertebrae , muscles , and blood vessels ) and occurs by the rhythmic separation of balls of cells , called somites , from the anterior end of their precursor tissue , called the presomitic mesoderm . These rhythmic events are associated with oscillatory gene expression in the presomitic mesoderm: waves of gene expression originate at the posterior end and spread anteriorly . When a wave reaches the anterior end , a pair of new somites detaches . The set of genes whose expression oscillates is termed the “somitogenesis clock . ” Even though the zebrafish somitogenesis clock has been the subject of intensive study , it is not clear how its oscillations are generated . It has been proposed that the mechanism involves a simple negative feedback loop , with proteins of the Her family periodically repressing their own expression . However , this is incompatible with some experimental results and does not explain how the spatiotemporal pattern of gene expression is generated . Here I propose a model—based on physical interactions between Her proteins—that is compatible with experimental results , and that explains how positional information is used to generate the spatiotemporal pattern of gene expression . | [
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] | 2007 | Repressor Dimerization in the Zebrafish Somitogenesis Clock |
The three-dimensional ( 3D ) structure of the genome is important for orchestration of gene expression and cell differentiation . While mapping genomes in 3D has for a long time been elusive , recent adaptations of high-throughput sequencing to chromosome conformation capture ( 3C ) techniques , allows for genome-wide structural characterization for the first time . However , reconstruction of "consensus" 3D genomes from 3C-based data is a challenging problem , since the data are aggregated over millions of cells . Recent single-cell adaptations to the 3C-technique , however , allow for non-aggregated structural assessment of genome structure , but data suffer from sparse and noisy interaction sampling . We present a manifold based optimization ( MBO ) approach for the reconstruction of 3D genome structure from chromosomal contact data . We show that MBO is able to reconstruct 3D structures based on the chromosomal contacts , imposing fewer structural violations than comparable methods . Additionally , MBO is suitable for efficient high-throughput reconstruction of large systems , such as entire genomes , allowing for comparative studies of genomic structure across cell-lines and different species .
Understanding genomes in three dimensions ( 3D ) is a fundamental problem in biology . Recently , the combination of chromosome conformation capture ( 3C ) methods with next-generation sequencing , such as 5C [1] , Hi-C [2] , TCC [3] , and GCC [4] , has enabled the study of contact frequencies across large genomic regions or entire genomes . These methods consist in crosslinking a large sample of cells followed by restriction enzyme digestion and ligation . Ligated DNA molecules are isolated , and sequenced using massively parallel paired-end sequencing . The end-result is typically a large matrix containing interaction ( ligation ) frequencies between all regions of the genome under study in the cell population . While such matrices can be visualized and analyzed directly [2] , determining the 3D structure corresponding to the interaction frequency matrix has been of steady increasing interest in the fields of computational biology and genomics . However , such 3D genome reconstruction is challenging due to the sparse and noisy nature of the data , the fact that the matrices typically contain aggregated interaction frequencies across millions of cells [5] , and the dynamic nature of chromatin [6] . These limitations constitute an obvious problem with respect to reconstructing a “consensus” 3D structure . Several approaches have been proposed to take into account the dynamic nature of chromatin and the aggregated nature of the data . Baù et al . [7] used the Integrative Modelling Platform ( IMP ) [8 , 9] and a Markov Chain Monte Carlo ( MCMC ) method to simulate a large set of 50 , 000 independent structural models from 5C data . A subset of the resulting structural ensemble consisting of the 10 , 000 structures with the best scores was then clustered , such that the different clusters arguably represent the variability of chromatin conformation in the population-averaged data . An MCMC approach for structural ensemble determination from 5C data was also utilized in a study by Rousseau et al . [10] , leading to a probabilistic model of the interaction frequency data . This allows for sampling from the posterior distribution of structures after a sufficient number of Monte Carlo steps . IMP has also been used to simulate an ensemble of 10 , 000 structures , that simultaneously encounter the restraints , assuming that the ensemble represents the dynamic nature of chromatin [3] . Another class of methods for identifying 3D chromatin structure from chromosomal contact data relies on reconstructing a “consensus” 3D structure from a ( possibly incomplete and noisy ) Euclidean distance matrix ( EDM ) consisting of pairwise distances ( in 3D ) between different regions in the genome . In general , this EDM is not known , but is typically estimated from the interaction frequency matrix . Given an EDM various optimization approaches that fall under the general topic of multidimensional scaling ( MDS ) ( see e . g . [11] for an overview ) can be used to find an optimal 3D structure . Methods based on MDS are often simpler and can handle larger problems , such as multiple chromosomes or single chromosomes on finer scales , than many of the more complex probability based methods . On the other hand , such methods often ignore the dynamic nature of chromatin and the aggregated nature of the Hi-C data . The most basic form of MDS is the so-called classical ( or metric ) MDS , where the optimal coordinate reconstruction from a given EDM is found directly by eigen decomposition of the so-called Gram matrix ( see Methods for details ) . An early application of classical MDS to determine 3D structure from chromosome contact data was presented by Dekker et al . [12] . In general , however , when the EDM has been inferred from interaction frequencies , the MDS approaches consider the reconstruction as a nonlinear and non-convex optimization problem using some iterative optimization method . For example , the EDM has been inferred by assuming simple transformations of genomic distances to Euclidean distances , and an iterative optimization method has been applied to reconstruct the coordinates best corresponding to the EDM [13 , 14] . Other optimization methods applied on MDS problems to find coordinates from incomplete distances exploit the rank constraints on the EDM ( or corresponding Gram matrix ) to find an optimal EDM for the relevant spatial dimension . One successful method in this respect is based on convex semidefinite programming [15 , 16] , which relaxes the problem to a convex optimization problem . These approaches are applicable to model 3D chromosome configurations [17]; however they cannot handle large problems , due to computational limitations . Technological improvements have also facilitated the reconstruction of 3D genome structures . In particular , adjustments to the Hi-C protocol have been introduced to enable identification of interactions between chromosome regions in single cells [18] . Single-cell Hi-C , however , inevitably suffers from sparse sampling of chromosomal interactions and a general lack of information on non-local distances between genomic regions with no mutual contacts . Nonetheless , mapped interactions are found in individual cells , potentially enabling a more robust determination of the underlying 3D structure [18] . One way to handle these limitations is to replace missing distances with their ‘shortest-path’ equivalence; that is , considering the existing ( observed ) entries in the EDM as weighted edges in a graph , and replacing each missing edge weight with the smallest possible sum of weights traversing the graph along the observed edges [19] . One drawback of completing the EDM with the shortest-path distances , however , may be that the imputed distances introduce noise which dominates over the more accurate local distances . An application of single-cell like contact maps coupled with missing-value imputation using the shortest-path method and classical MDS to find 3D coordinates , was recently proposed [20] . This approach offers an efficient way of establishing 3D genome structures . However , accuracy may be limited both by the noise introduced by the shortest-path procedure as well as from the limitations of the classical MDS approach . Another approach proven to be effective on many optimization problems relies on optimization on manifolds . The problem of finding optimal coordinates from an EDM can be formulated as an optimization problem on the manifold of the set of positive semidefinite matrices of fixed rank [21 , 22] . The Riemannian quotient geometry of the manifold can be exploited to yield efficient algorithms for the optimization problem [23] . However , this strategy has , to our knowledge , not been applied to 3D genome reconstruction in previous studies . In this paper , we show that the manifold based optimization ( MBO ) approach can be successfully applied to 3D genome reconstruction . MBO significantly outperforms the simpler methods based on classical MDS in terms of consistency with the original contact map and structural violations , while remaining sufficiently efficient to handle large-scale problems . Using both simulated and real single-cell Hi-C data , we show that , by combining the shortest-path derived distances with appropriate weights to reduce the influence of noise , MBO can efficiently reconstruct 3D structures consistent with the chromosome contact maps , despite the noisy and sparse nature of the data . Our implementation of the manifold optimization method is based on the Manopt software [24] that provides a Matlab interface for optimization on manifolds .
Given a matrix of interaction frequencies , typically from a Hi-C or single-cell Hi-C data set , we seek to reconstruct the corresponding 3D coordinates of the genome structure . In classical MDS ( CMDS ) , this reconstruction is performed by converting the contact frequencies into an EDM ( Fig 1B ) , and uses singular value decomposition for direct coordinate reconstruction . Crucially , such approaches assume that all Euclidean distances in the EDM are of equal importance and equally accurate . This is problematic , since it is known that short genomic distances are sampled much more frequently than long genomic distances . Also , in single-cell Hi-C , contacts are restricted to only two interactions per restriction fragment , for autosomal chromosome pairs , resulting in a large number of missing values . In our method , which relies on manifold based optimization ( MBO ) [22] , the low-rank property of the EDM , and the resulting redundancy in the distances , are exploited to infer the missing distances . We consider the completion of the EDM while simultaneously allowing for missing distances . We do this by combining the shortest-path completed distances with weights , such that imputed ( and typically long ) distances are weighted less in the subsequent optimization procedure ( Fig 1C ) . This allows for flexibility in the reconstruction of uncertain regions of the final 3D structure , while enforcing distances in more reliable sections of the structure . The Methods section provides an in-depth description of the full algorithm . As a first validation of the method , we have considered an in silico test case where a known chromosome structure was employed to test the ability of different methods to reconstruct the original structure from incomplete and noisy distance information . Here , MBO is compared to the classical MDS ( CMDS ) approach recently presented in Lesne et al . [20] , where the graph shortest-path method is utilized to replace missing distances . This method is generally known as Isomap [19] , while the adaptation to 3D genome reconstruction was named ShRec3D in Lesne et al . [20] . In the following we will refer to this method simply as CMDS . In addition , we present comparison with the ChromSDE method of Zhang et al . [17] , which is based on semidefinite programming and is significantly more computationally demanding than both the CMDS method and MBO . The structure considered in this validation is a 3D model of mouse haploid chromosome X generated from single-cell Hi-C data by Nagano et al . [18] . The 3D model represents chromosome X using a 50 kilo base pair ( kbp ) resolution . However , for the current test , the structure was re-sampled at 600 kbp , by taking the average spatial position of groups of bins , this due to the computational limitation of the ChromSDE method . Additionally , we evaluate different levels of noise ( σ ) , added to the final contact matrix , as well as different levels of contact scarcity ( see Methods section ) . The results from these tests are shown in Fig 2 . The data shows the structural similarity between original distances and reconstructed distances for the different methods , for different noise levels ( σ ) and ratios of missing distances . For the weakly noisy case ( Fig 2; σ = 0 . 1 ) MBO and ChromSDE still reconstruct structures more consistent with the orignal structure than CMDS . For the two cases with higher noise levels , however , MBO performs markedly better , and produces structures more similar to the original , compared to the two other methods ( Fig 2; σ = 0 . 5 and 1 . 0 ) . In the noiseless case ( σ = 0 ) both MBO and ChromSDE are able to reconstruct the original structure exactly as long as a sufficient number of the pair-wise distances are known . This would be expected for ChromSDE , since the semidefinite programming approach is convex in this case . That MBO also recovers the original coordinates exactly is not a priori obvious . Naturally , the ratio of distances needed for an exact reconstruction will vary with the size n of the problem . In fact , it has been shown that knowledge of m ≥ Cn6/5 r log n ( for some positive contant C ) random entries of an n × n matrix of rank r is sufficient for an exact completion of the matrix in most cases [25] . We inspected the ability of MBO to reconstruct the considered orignal structure when the missing distances approach this limit . The original structure can be exactly reconstructed with up to ∼ 90% missing data ( Fig 3A–3C ) . With 95% missing data , the structure is still similar to the original structure , with an RMSD of ∼ 610 nm . At levels of missing data above 98% , however , the structure collapses into a compact globule , due to missing interactions between distal bins ( Fig 3E–3F ) . To inspect this dependency further , we calculated the minimum ratio of observed distance values needed for complete reconstruction ( [1-ρ]<1e-10 ) and partial reconstruction ( [1-ρ]<0 . 1 ) ) , for a range of different sampled structures with varying number of bins ( n ) ( see Fig 3G ) . The required percentage of observed interactions is dependent on the total number of bins in the system considered . We compared the structures from Fig 3B–3F with these estimated curves , and indeed found that the compact globular structures correspond to a ratio of observed values crossing the boundary of partial reconstruction . Furthermore , we compared these curves to the sets of all chromosomes from the single-cell Hi-C data from [18] . As can be seen in Fig 3G , the datasets are distributed around the curve of partial reconstruction ( [1-ρ]<0 . 1 ) ) . This could indicate that the current single cell Hi-C data sets are generally too sparse for high confidence structure reconstruction . Note , however , that the single-cell Hi-C data for chromosome X ( cell 1 and cell 2 ) are between the partial and complete reconstruction curves , and are therefore likely to be among the more reliable data sets for structural reconstruction and method comparisons . Typical computation times for the methods considered in the validation performed above are shown in Fig 4 , as a function of the problem size n ( i . e . n is the number of bins in the reconstructed structure ) . As expected , CMDS ( excluding the shortest-path algorithm ) is fastest , while ChromSDE is slowest . Note , however , that MBO has the same asymptotic behavior as CMDS for large n . Further , when the input EDM has missing values , the shortest-path distances must be calculated before application of CMDS . Hence , for n larger than about 500 , MBO is actually the fastest of the three methods . In practice , using stringent settings , reconstruction of e . g . chromosome X using MBO at 50kbp resolution takes less than 5 minutes . Next , we examined the ability of MBO and CMDS to reconstruct contact maps for the full set of chromosomes , based on single-cell Hi-C data [18] . We therefore applied MBO and CMDS to all mouse chromosomes individually , for two different single cells ( named “cell 1” and “cell 2” in [18] ) , and evaluated the resulting structures . We evaluated and compared the ability of the methods to reconstruct structures with resulting contact maps consistent with the input data , by inspecting the percentage of contacts established in the reconstructed structure that were also present in the original contact map ( % correct contacts ) . Additionally , we evaluated the occurrence of structural inconsistencies in the inferred structures , i . e . the percentage of bins being too close to each other ( % min distance violation ) , and the percentage of consecutive bins that are too far away from each other ( % connectivity violation ) . See the Methods section for details . We started by considering chromosome X , where only one copy is present in the data . For chromosome X , we found that MBO was able to reconstruct the original contact map of the haploid X nearly completely ( both cases > 95% reconstructed ) . CMDS , on the other hand , was not able to reconstruct the contact matrix of chromosome X at more than ∼50–60% correct contacts ( Figs 5C and 6A ) . Similar results were found for all 10 individual cells from [18] ( see S1 Fig ) , even though the percentage of correct contacts was closer to 80% for some of the cells with the fewest number of input contacts ( cells 9 and 10 ) . Interestingly , for homologous chromosome pairs , where two chromosome copies are present , reconstruction was not as consistent with the input contact maps as for chromosome X , as only ∼20% of the contacts in the original maps could be reconstructed ( Fig 6A ) . In other words , the presence of two chromosomal copies affects the ability to reconstruct structures that reflect the original contact matrix . This indicates that the structures of the two homologous copies may contain mutually exclusive contacts , making full reconstruction of the contact maps difficult . We were interested in investigating the effect of having possibly mutually exclusive contact information from two separate chromosome X structures from cell 1 and cell 2 . We therefore randomly sampled 50 new datasets consisting of an equal number of contacts from the matrices from these two cells and inspected the ability of MBO to reconstruct structures corresponding to the resulting contact maps . As S2 Fig shows , the mixed datasets produce structures with a significantly lower percentage of correct contacts , and structures with higher connectivity violations . It should be noted that 3D reconstruction from mixed populations of contact data has no guarantee of reliably estimating a correct structure . For homologous chromosome pairs , MBO and CMDS performed similarly in terms of percentage of successfully established interactions ( Fig 6A ) . However , when looking at minimum distance violations ( chromosomal bins closer than 30 nm , Fig 6B , or violations of the connectivity of consecutive regions ( consecutive bins further away than 200 nm , Fig 6C ) , it is clear that MBO is more successful in positioning the regions in 3D , without imposing obvious violations . Since MBO , like most optimization strategies for structural reconstruction , is non-convex , optimized structures might depend on the random starting configuration of the optimization . We wanted to study this effect by running 100 independent optimizations of chromosome X using different random initialization of the starting configurations . We then calculated the root-mean-square deviation ( RMSD ) between the resulting superimposed structures , and found a high degree of similarity between all the 100 chromosome X structures , with an average RMSD of ∼ 322 nm , similar to what was reported in [18] . Furthermore , we clustered the RMSD values using hierarchical clustering , and the resulting clusters are visualized in Fig 7 . As the figure shows , 4–5 large clusters are found , where the structural similarity within the clusters is clearly higher than between clusters , probably reflecting different local optima in the cost function . By inspecting example structures within each of the clusters , overall the similarity between the structures is high . This indicates that the MBO method gives robust results , with similar structures regardless of starting configuration . Nevertheless , it is advisable to run several independent optimizations , to inspect whether the different local optima in the cost function represents disparate structures . In S3 Fig , the reconstructed 3D structure from chromosome 1 based on MBO is displayed . We note that , despite the presence of two copies , the reconstructed structure shows few structural violations , with minimum distance violation < 0 . 01% and connectivity violations below 10% . By performing 100 independent reconstructions , as for chromosome X , ( see S4 Fig ) , the average RMSD was found to be ∼ 262 nm . However , for chromosome 1 , the resulting clusters were not as clear as for chromosome X , possibly due to the two separate copies of chromosome 1 . For comparison reasons , we applied MBO using a weighting scheme where the shortest-path completed matrix was used directly without accompanying weights . In S5 Fig , the results from this analysis is shown . As the figure shows , using no weights results in a reduced fraction of correct contacts , and additionally , a higher fraction of connectivity violations . The latter point can be explained by considering that all genomic distances are weighted equally when no weights are used . However , when weights are used , as in the MBO method that we present here , short genomic distances will be weighted more , since these will typically contain more contact information . And as a result , connectivity violations will be reduced . All in all , we have shown that MBO reconstructs 3D structures consistent with the input chromosomal contact data , at the same computational speed as the popular CMDS approach . Additionally , MBO imposes fewer violations relating to the connectivity of the chain , as well as fewer violations from placing regions too close to each other . We have shown that MBO can be used for routine reconstruction of 3D structures from sparsely sampled data , such as single-cell Hi-C .
In contrast to methods such as MCMC and molecular dynamics , methods aiming at reconstructing a single consensus 3D structure can be utilized quickly and in a high-throughput fashion . One challenge with such approaches , however , has been the lack of possibilities for handling the sparse and noisy interaction frequency matrices in a flexible and robust way . In this paper , we have shown that combining weights with manifold based optimization ( MBO ) allows for reconstructing 3D structures of genomes , even when data are sparse and noisy , such as for single-cell Hi-C . We have shown that the weights allow for prioritization of interactions where information about spatial positioning is found , while allowing the remaining regions to be positioned in a consistent fashion . Specifically , by comparing the reconstructed and original contact maps , we have shown that the single copy of chromosome X in male mouse cells can be reconstructed in a fashion consistent with the input data . For homologous chromosome pairs , however , reconstruction was not complete , most likely due to considerable structural difference between the two chromosome copies . We note that it is also possible to run MBO on ensemble Hi-C datasets , since the weighing scheme is equally applicable in this case . However , the assumption of a consensus structure would in this case probably be less justifiable , due to the known inherent variability in chromosome interactions across cells in a large population . As chromosome conformation capture data are becoming increasingly available [26] , quick and robust methods for reconstructing chromosomal 3D structure from chromosomal interaction data , are needed . Additionally , for a complete understanding of the mechanisms involved in gene regulation , cell differentiation , DNA replication and repair , genome organization needs to be studied in its correct dimensions . Efficient and robust 3D genome reconstruction tools such as MBO , are likely to play an increasingly important role for such studies in the future .
A fundamental problem relevant for many applications in various disciplines is to find some coordinates , xi ∈ ℝr , i = 1 , ⋯ , n in an r-dimensional Euclidean space , given some information about the pair-wise distances between the points . The pairwise distances can be represented by the Euclidean distance matrix ( EDM ) , D ∈ ℝn×n , q D i j = | | x i - x j | | 2 , ( 1 ) which is an n × n matrix containing the squared distances between the n points . By construction the EDM is a symmetric matrix with zero diagonal and non-negative entries satisfying the triangle inequality D i j ≤ D i k + D k j . Note also that D is invariant to arbitrary rotations and translations of the set of coordinates xi . If the EDM is known exactly ( without noise or missing entries ) , the coordinates xi can be uniquely determined up to arbitrary rotations and translations by introducing the matrix B ∈ ℝn×n , B = - 1 2 ( I - 1 n e e T ) D ( I - 1 n e e T ) , ( 2 ) where I ∈ ℝn×n is the identity matrix and e ∈ ℝn is a vector of all ones . If D is a true EDM in an r dimensional space , B is a symmetric positive semidefinite matrix of rank r . That is , B has maximum r nonzero eigenvalues , and B = V Λ VT , where Λ ∈ ℝr×r is the diagonal matrix with the r nonzero eigenvalues of B on the diagonal , and V ∈ ℝn×r is the matrix with the r eigenvectors of B as its columns . It can then be shown that X = V Λ is an n × r matrix with the coordinates xi as its rows . It is easy to see that B = XXT , thus B contains the inner product of the coordinates and is often called the Gram matrix for the set of coordinate vectors . In many practical applications , however , the EDM may contain noisy and missing values . In this case , finding optimal coordinates xi must be treated as an optimization problem of finding coordinates that minimize some cost function based the known distances . If all pair-wise distances between points are known , but not necessarily accurately , one solution to the optimization problem is given in terms of classical multidimensional scaling ( CMDS ) . CMDS basically solves the optimization problem of finding a matrix B ^ that solves min B ^ ∈ 𝓢 + n ( r ) | | B ^ - B | | 2 , ( 3 ) where 𝓢 + n ( r ) is the set of positive semidefinite n × n matrices of rank r or less , and B is the matrix derived from the EDM by using Eq ( 2 ) . This problem has a closed-form solution in terms of the r largest eigenvalues and corresponding eigenvectors of B , namely B ^ = V Λ V T , where Λ is now the diagonal matrix with the r largest eigenvalues of B on the diagonal , and V is the matrix with the corresponding eigenvectors of B as its columns . Consequently , the corresponding coordinates are given by X ^ = V Λ . Obviously , if D is a true EDM for the relevant dimension r , there will be exactly r nonzero eigenvalues and the procedure reduces to the one described in the previous paragraph , and the coordinates are recovered exactly up to arbitrary rotations and translations . However , if D is not close to a true EDM , CMDS is often not robust since the nearest distances are measured through B rather than on D directly . A manifold based optimization approach for the completion of Euclidean distance matrices was recently presented in Mishra et al . [22] . They solved a minimization problem in the form min D ^ ∈ 𝓔 n ( r ) 1 2 | | H ⊙ ( D ^ - D ) | | 2 , ( 4 ) where 𝓔n ( r ) is the set of EDMs with embedding dimension r or less , H is a symmetric weight matrix with binary entries ( i . e . a matrix whose elements are either 0 or 1 ) and where ⊙ denotes the element-wise ( Hadamard ) product between matrices . For the application of this approach to the case of the 3D genome reconstruction we have applied a slightly more general framework where the weights are allowed to take any non-negative values ( not restricted to 0 and 1 ) . In addition , we choose to minimize the differences between the ordinary Euclidean distances rather than the squared distances used in Eq ( 4 ) . This choice is motivated by the fact that the longer genomic distances will be weighted less in the final optimization , and results in improved performance compared to using squared distances ( see S6 and S7 Figs ) . Thus , we consider the minimization problem min D ^ ∈ 𝓔 n ( r ) 1 2 | | H ⊙ ( D ^ - D ) | | 2 , ( 5 ) where square roots here and in the following denote the element-wise square root of the matrix . Following Mishra et al . [22] , Eq ( 5 ) can alternatively be formulated as an optimization problem on the set of positive semidefinite matrices with fixed rank , denoted 𝓢 +n ( r ) , by using the mapping from the set 𝓢 +n ( r ) to the set of EDMs 𝓔n ( r ) given by D = κ ( B ) = b e T + e b T - 2 B , ( 6 ) where b is the vector with the diagonal entries of B , i . e b = diag ( B ) = ( B ⊙ I ) e . As discussed above a positive semidefinite matrix of rank r admits the factorization B = XXT , where X ∈ ℝn×r and rank ( X ) = r . Thus , the cost function that we wish to minimize may be written f ( X ) = 1 2 | | H ⊙ ( κ ( X X T ) - D ) | | 2 . ( 7 ) Note that the X that minimizes Eq ( 7 ) is in fact the coordinates that we wish to find . To minimize Eq ( 7 ) we have implemented a solver for the optimization problem in Matlab using the Manopt toolbox [24] using the symfixedrankYYfactory ( n , r ) manifold , which provides the geometry for the manifold of n × n positive semidefinite matrices with rank r . Manopt includes a number of different solvers for the optimization problem . Here we will employ a trust-region solver which , unlike steepest descent , utilizes information about both the gradient and the Hessian of the cost function , and has been shown to have good convergence rates . The gradient of f ( X ) can be written grad f ( X ) = κ * ( H ( 2 ) ⊙ ( e e T - K ) ) X , ( 8 ) where H ( 2 ) = H ⊙ H is the matrix with the squared weights and the matrix K is the symmetric matrix with zero diagonal and off-diagonal entries given by K i j = D i j κ ( X X T ) i j , i ≠ j . ( 9 ) κ* ( B ) is the adjoint operator of κ defined by κ * ( B ) = 2 ( Diag ( B e ) - B ) , ( 10 ) where Diag ( v ) = ( veeT ) ⊙ I is the function that returns the n × n matrix with the n × 1 vector v on the diagonal and zeros elsewhere . In addition to the gradient the trust-region algorithm also requires the Hessian in a given direction U , Hess f ( X ) [U] . One can show that the Euclidean Hessian of f ( X ) takes the form Hess f ( X ) [ U ] = κ * ( H ( 2 ) ⊙ ( e e T - K ) ) U + 1 2 κ * ( H ( 2 ) ⊙ G ⊙ κ ( X U T + U X T ) ) X , ( 11 ) where G is the symmetric matrix with zero diagonal and off-diagonal entries G i j = D i j ( κ ( X X T ) i j ) 3 , i ≠ j . ( 12 ) The conversion from the Euclidean to the Riemannian Hessian , needed for the optimization algorithm , is performed internally in Manopt . For additional details about the manifold based algorithm , see [22 , 24] . From the known 3D structure . a true EDM was constructed containing the pair-wise squared distances between all the 600 kbp sized bins . To model the uncertainty and possible sparsity of distance information inferred from chromosomal contact data such as Hi-C , the original distance matrix was contaminated by adding random noise as well as randomly removing a given percentage of the distances . That is , from the original Euclidean distance matrix D ( containing the squared pair-wise distances ) , a noisy and incomplete set of distances δij is generated as δ i j = δ j i = D i j | 1 + σ ϵ i j | , for ( i , j ) ∈ 𝓝 ( 13 ) where ϵij are sampled randomly from a standard normal distribution and where 𝓝 is the set of entries ( i , j ) for which the distances are available . Tests were run for different values for the noise level σ and ratio of missing distances ( size of 𝓝 ) . The raw results from a single-cell Hi-C experiment typically lists a number of observed contacts between specific genome positions . From the raw results , the contacts were aggregated into equally spaced bins along the chromosomes . For the results presented here a bin size of 50 kbp was used . Then all observed contacts were assigned to their corresponding bins . In the case that multiple contacts fell into the same bin , the duplicate entries were ignored so that a binary contact matrix Cij was obtained for each chromosome . Hence , Cij = 1 represents a Hi-C contact between bins i and j , while Cij = 0 represents the absence of a contact . To use the MBO approach , the binary contact map must be converted into a distance matrix Dij . First a target distance dc is assigned to all bins with an observed Hi-C contact . Secondly , the connectivity along the chromosome is taken into account by assigning a distance dn to neighboring bins . Hence , as a first step the following matrix is constructed D i j = { d c if C i j = 1 , d n if C i j = 0 and | i - j | = 1 , 0 elsewhere . ( 14 ) Since the MBO method works also for incomplete distance matrices , the optimization could in principle be run directly on Eq ( 14 ) , letting the weights Hij be nonzero only for the nonzero entries of Dij . However , since only the local distances ( contacts and neighboring bins ) are known , a direct optimization of Eq ( 14 ) would lead to a very compact structure where all bins are located close together . Hence , for a consistent 3D structure some information about the large distances must be included . One possible method is to assign large distances and small weights to the non-interacting bins ( see e . g . [27 , 28] ) . The large distances will then act as a repulsive force and counteract the formation of a compact state . Another possibility is to apply the shortest-path method to fill the missing entries of the distance matrix . In this way the missing distances may take more realistic values since they are deduced directly from the known distances . However , these shortest path-distances still introduce noise that may seriously influence the result . Motivated by the fact that the shortest-path derived distances are more noisy than the ‘original’ contact-distances that we wish to satisfy , we have adopted a slightly more flexible approach where we combine the shortest-path completed matrix with weights so that the shortest-path inferred distances are weighted less in the optimization procedure . Thus , we first replace the zero entries in Dij with the shortest-path derived distances . We then introduce the weight matrix Hij whose elements are chosen to be inverse proportional to the number of edges traversed in the shortest path , i . e H i j = n i j − q where nij is the number of edges that is needed to connect node i and j . That is , the original distances will have weights equal to one , while the shortest-path derived distances will have smaller weights . The value q is a factor that specifies the relative magnitude of the weights for the non-observed edges compared to the observed ones , and was found by maximizing the percent correct contacts and minimizing distances violations ( see S8A Fig for an example ) . In our case this value was always found to be between 1 and 3 ( see S1 File ) , but in theory , for other data , the optimal value may be outside this range . Here , we have used a simple optimization scheme by trying out a range of values for q . This is likely sufficient in most cases , since the effect of using different values for q on the final structures is not very large . For example , on chromosome X for cell 1 , using a range of values of q between 0 and 3 , the structures all had RMSD<300nm compared to the structure with optimized q ( see S8B Fig ) . MBO is initialized by starting with a random initial configuration ( a random point on the manifold ) , and convergence is considered obtained if the cost function or the norm of the gradient drops below a small value ( 1e-20 and 1e-08 , respectively ) . After a successful convergence of the optimization algorithm the resulting coordinates xi are scaled to best agree with the original contact map . That is , we search for a scaling constant cl so that D ^ i j = ∣ ∣ c l x i − c l x j ∣ ∣ contains exactly nc pair-wise distances smaller than the contact distance dc , where nc is the number of contacts in the original contact matrix . Note that in the case of perfect agreement , the contact matrix derived from the coordinates cl xi will be identical to the original contact matrix , since the number of entries are the same . The optimal value for cl is found by a simple binary search method . The percent correct contacts was calculated by direct comparisons of original and reconstructed contact matrices . Minimum distance violations were defined as the percent fraction of pairwise distance below 30 nanometers . Connectivity violations were defined as the percent fraction of neighboring ( connected ) bins with a distance above 200 nanometers . In Eq 14 , dc = 60nm , dn = 120nm . MBO is implemented in Matlab , and is based on the Manopt software [24] . Code is freely available at http://folk . uio . no/jonaspau/mbo/ . | Understanding how the genome is folded in three-dimensional ( 3D ) space is crucial for unravelling the complex regulatory mechanisms underlying the differentiation and proliferation of cells . With recent high-throughput adaptations of chromosome conformation capture in techniques such as single-cell Hi-C , it is now possible to probe 3D information of chromosomes genome-wide . Such experiments , however , only provide sparse information about contacts between regions in the genome . We have developed a tool , based on manifold based optimization ( MBO ) , that reconstructs 3D structures from such contact information . We show that MBO allows for reconstruction of 3D genomes more consistent with the original contact map , and with fewer structural violations compared to other , related methods . Since MBO is also computationally fast , it can be used for high-throughput and large-scale 3D reconstruction of entire genomes . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] | [] | 2015 | Manifold Based Optimization for Single-Cell 3D Genome Reconstruction |
Vaccinia virus ( VACV ) , the prototype poxvirus , encodes numerous proteins that modulate the host response to infection . Two such proteins , B14 and A52 , act inside infected cells to inhibit activation of NF-κB , thereby blocking the production of pro-inflammatory cytokines . We have solved the crystal structures of A52 and B14 at 1 . 9 Å and 2 . 7 Å resolution , respectively . Strikingly , both these proteins adopt a Bcl-2–like fold despite sharing no significant sequence similarity with other viral or cellular Bcl-2–like proteins . Unlike cellular and viral Bcl-2–like proteins described previously , A52 and B14 lack a surface groove for binding BH3 peptides from pro-apoptotic Bcl-2–like proteins and they do not modulate apoptosis . Structure-based phylogenetic analysis of 32 cellular and viral Bcl-2–like protein structures reveals that A52 and B14 are more closely related to each other and to VACV N1 and myxoma virus M11 than they are to other viral or cellular Bcl-2–like proteins . This suggests that a progenitor poxvirus acquired a gene encoding a Bcl-2–like protein and , over the course of evolution , gene duplication events have allowed the virus to exploit this Bcl-2 scaffold for interfering with distinct host signalling pathways .
Vaccinia virus ( VACV ) , the smallpox vaccine , is the prototypic member of the Poxviridae; a family of large , double-stranded DNA viruses that replicate in the cytoplasm of host cells [1] . VACV strain Copenhagen was the first poxvirus to be sequenced and encodes about 200 genes [2] . The central portion of orthopoxvirus genomes ( ∼100 kb ) is highly conserved and contains genes essential for virus replication [3] . Genes located towards the termini are more variable and , although non-essential for virus replication , they affect VACV virulence , host range and modulation of the host immune system . These VACV immunomodulators can act either inside or outside infected cells [4] . Intracellular immunomodulators modulate apoptosis , the anti-viral activity of interferons , innate immune signalling and host gene transcription , whilst extracellular immunomodulators inhibit the action of complement , interferons , cytokines and chemokines [4]–[6] . Nuclear factor-κB ( NF-κB ) is a transcriptional complex that plays a central role in stimulating innate and adaptive immune responses to infection . Receptors for the pro-inflammatory cytokines interleukin ( IL ) -1 and tumour necrosis factor alpha ( TNFα ) activate signalling pathways leading to NF-κB activation [7] , [8] , as do Toll-like receptors ( TLRs ) , which recognise pathogen-associated molecular patterns such as in viral ( glyco ) proteins and nucleic acids [9] , [10] . NF-κB activation downstream of the IL-1 receptor and TLRs requires TNF-receptor-associated factor 6 ( TRAF6 ) and IL-1 receptor associated kinases ( IRAKs ) , while activation downstream of the TNF receptor requires TRAF2 [7] , [10] . These independent downstream signalling pathways converge at the IκB kinase ( IKK ) complex , a key regulator of signalling to NF-κB activation [7] . The importance of the immune response initiated by proteins under NF-κB transcriptional regulation upon virus infection is underscored by the fact that VACV encodes several proteins , A52 , A46 , B14 , K1 , N1 and M2 , which interfere with the intracellular signalling pathways that lead to the activation of NF-κB [11]–[16] . A52R is an immediate-early VACV gene [17] encoding a 23-kDa intracellular protein ( A52 ) that contributes to virus virulence [16] . A52 functions by inhibiting NF-κB activation [14] downstream of the IL-1 receptor and TLRs [18] via interactions with IRAK2 and TRAF6 [16] , [18] . While the precise molecular details of these interactions are unclear , the N-terminal death domain of IRAK2 is essential for binding A52 [16] , and a truncation mutant of A52 lacking the C-terminal 46 residues ( A52ΔC46 ) retains the ability to both bind IRAK2 and inhibit NF-κB activation [18] , [19] . Further , a peptide derived from A52 termed ‘P13’ , comprising residues 125–135 of A52 plus a nine-arginine cell-transducing sequence ( which promotes cellular internalisation of the peptide ) , inhibits TLR-mediated activation of NF-κB and shows promise as a potent anti-inflammatory therapeutic [20] . In addition to inhibiting NF-κB , A52 activates p38 MAP kinase and enhances the TLR4-induced production of IL-10 , a cytokine that inhibits inflammatory and cell-mediated immune responses . Activation of p38 MAP kinase is mediated by the direct binding of A52 to the TRAF domain of TRAF6 , and removal of the A52 C-terminal 46 residues abolishes the interaction with TRAF6 and subsequent activation of p38 MAP kinase [16] , [19] . VACV strain Western Reserve gene B14R is an immediate-early gene [17] , [21] that encodes a 17-kDa cytosolic protein ( B14 ) that contributes to VACV virulence [21] and inhibits the IKK complex [13] . The interaction of B14 with the IKK complex depends on the presence of IKKβ , and B14 bound to the IKK complex prevents phosphorylation of the IKKβ activation loop . Consequently , B14 inhibits the phosphorylation and subsequent ubiquitin-mediated degradation of IκBα , the inhibitor of NF-κB [13] . In this way , B14 blocks activation of NF-κB downstream of a variety of stimuli including TNFα , IL-1 , poly ( I∶C ) and phorbol myristate acetate [13] . While B14 and A52 share identifiable sequence similarity with each other , being members of a Pfam [22] protein family that also includes VACV proteins A46 , K7 , C6 and C16/B22 , they do not display significant sequence similarity to other cellular or viral proteins [14] , [15] , [21] , [23] . Protein structure is more strongly conserved during evolution than protein sequence [24] and determination of virus protein structures is a powerful tool for identifying previously undetermined functional and evolutionary relationships [25] . For example , the recent crystal structures of VACV N1 [26] , [27] and myxoma virus M11 [28] , [29] revealed that these proteins possess Bcl-2–like structures despite sharing no identifiable sequence similarity with the cellular Bcl-2 family of proteins . Members of the Bcl-2 family are small α-helical proteins that can be either pro- or anti-apoptotic and they regulate the release of pro-apoptotic molecules from mitochondria [30] . The structures of N1 and M11 both display conserved features important for anti-apoptotic Bcl-2 function; namely the presence of an elongated surface groove for binding α-helical motifs ( BH3 peptides ) of pro-apoptotic Bcl-2–like proteins and thereby antagonizing their function . Functional studies performed in light of these structure elucidations confirmed that N1 and M11 protect cells from apoptosis by binding to pro-apoptotic Bcl-2 family members such as Bid and Bax [26] , [29] , the affinity [27] , [28] and binding mode [29] being comparable to cellular anti-apoptotic Bcl-2 family proteins . The structural and functional similarity of the poxvirus and cellular Bcl-2–like proteins suggest that these viral proteins had a cellular origin , a common theme in poxviruses and other large DNA viruses [31]–[33] . To understand the mechanism of action and evolutionary origins of VACV A52 and B14 in more detail , we have solved their crystal structures at 1 . 9 Å and 2 . 7 Å resolution , respectively . We show that both proteins are Bcl-2 family members but lack a surface groove for binding BH3 peptides and , consonant with this , are not anti-apoptotic . Instead these proteins have acquired the ability to inhibit signalling pathways that activate NF-κB .
The structures of A52 and B14 were solved by multiple-wavelength anomalous dispersion ( MAD ) experiments performed upon crystals of selenomethionine ( SeMet ) -labelled protein ( Tables 1 & 2 ) . The structures of two independent crystal forms of an N-terminal truncated form of A52 comprising residues 37–190 ( A52ΔN36 ) were refined to 1 . 9 Å and 2 . 8 Å resolution with residuals R/Rfree = 0 . 177/0 . 215 and 0 . 181/0 . 192 , respectively , with residues 40–189 being observed in electron density maps in both crystal forms ( Figure 1A ) . Residue 190 and the first two residues of the polyHis purification tag were also visible in the low-resolution structure . Both crystal forms of A52 contain 2 molecules per asymmetric unit arranged as a dimer , the overall fold ( 0 . 32±0 . 07 Å root-mean-squared displacement [rmsd] over 150 Cα atoms ) and dimer interface being highly conserved ( Figure S1 ) . The structure of SeMet B14 was refined to 2 . 7 Å resolution with residuals R/Rfree = 0 . 223/0 . 244 , residues 8–149 being observed in the electron density ( Figure 1B ) . Four molecules of B14 are present in the crystallographic asymmetric unit , forming two dimers with highly conserved overall folds ( 0 . 11±0 . 02 Å rmsd over 142 Cα atoms ) and dimer interfaces ( Figure S1 ) . The structures of A52 and B14 are entirely α helical , both comprising seven α helices and adopting the Bcl-2–like fold ( Figure 1 ) . The Bcl-2–like folds of A52 and B14 are surprising given the low sequence similarity shared between A52 , B14 and other Bcl-2–like proteins ( Table 3 ) , and the structures contradict a previous suggestion that A52 would adopt a fold like Toll-like–IL-1 resistance ( TIR ) domains [14] . A structural similarity search using SSM [34] identified the closest relative of both A52 and B14 to be N1 ( Figure 1C ) , a VACV Bcl-2–like protein that inhibits apoptosis [26] , [27] and which has also been reported to inhibit signalling pathways leading to activation of NF-κB [35] . N1 , A52 and B14 all homodimerise both in crystallo and in vitro ( Figure S1 , [36] and data not shown ) . While the face of the structure involved in dimerisation is generally conserved across these proteins , the orientations of the two-fold rotation axes that relate the monomers differ by up to 57° ( Figure 2 ) . Despite being a cytosolic protein , and despite being purified and crystallised in the presence of the reducing agent β-mercaptoethanol , a single disulphide bond is observed in B14 between cysteine residues 15 and 46 , locking the N-terminal loop with the α1-α2 loop ( Figure 1B ) . There is no obvious functional role for this disulphide bond other than stabilising the structure of the protein . Residues 125–135 of A52 , which encompass the 11-residue ‘P13’ peptide sequence that in isolation can inhibit NF-κB activation [20] , form the surface loop between helices 4 and 5 . This is distal to the A52 dimerisation interface and is appreciably different in length , amino acid composition and conformation to the comparable loops in the other VACV Bcl-2–like proteins ( Figures 1 & 3 ) . It is a likely candidate for mediating the interaction with IRAK2 , although such identification awaits direct experimental confirmation . The final 46 residues , removed in the A52ΔC46 truncation mutant that abolished TRAF6 binding and the ability to stimulate p38 MAP kinase , comprise the final 6 residues of helix 5 and all of helices 6 and 7 . Given that helices 5 and 6 contribute to the central core of the protein , it is unclear whether this truncated protein would be stable and natively folded ( Figure 3 ) let alone whether it would dimerise like the native protein ( 900 Å2 of the 1 , 300 Å2 of surface area buried by the native dimer interface being abolished by the truncation ) . Further study is therefore required to identify the binding face of TRAF6 on the surface of A52 . The determination of the structures of VACV proteins B14 and A52 establishes that poxviruses encode a family of Bcl-2–like proteins that also includes VACV N1 and myxoma virus M11 . These proteins have been reported to have diverse functions including inhibition of apoptosis and interference with signalling from several stimuli leading to activation of NF-κB . We therefore undertook a direct comparison of the ability of these proteins to inhibit apoptosis in response to staurosporine or inhibit NF-κB activation in response to IL-1α or TNFα stimulation ( Figure 4A ) or over-expression of TRAF2 or TRAF6 ( Figure 4B ) . A52 , B14 and N1 all inhibit the activation of NF-κB to some degree in response to IL-1α or downstream of TRAF6 . However , only B14 is able to block signalling downstream of TNFα/TRAF2 . This is due to the ability of B14 to inhibit signalling from the IKK complex via its interaction with IKKβ: the nexus where IL-1 receptor , TNF receptor and TLR signalling pathways to NF-κB converge [13] . The ability of A52 to inhibit IL-1α– but not TNFα–induced signalling is consistent with previous findings [14] , [16] , whereas the inability of N1 to inhibit TNFα signalling is inconsistent with a prior report [35] . The mechanism by which N1 inhibits signalling downstream of IL-1α is unclear . However , given that N1 inhibits TRAF6-induced NF-κB activation but does not interact with the IKK complex [13] , contrary to previous suggestions [35] , it is likely that it acts at the level of TRAF6 or on downstream proteins in the pathway that precede the IKK complex . M11 did not inhibit either pathway , consistent with a primarily anti-apoptotic function during virus infection [29] . To test whether the N terminus of A52 , predicted to be unstructured and removed for crystallisation , is required for anti–NF-κB activity , full length A52 and the A52ΔN36 truncation were compared for their ability to block signalling induced by IL-1α ( Figure 4C ) . A52ΔN36 had a comparable inhibitory effect to the full-length protein , indicating that the N-terminal 36 residues are not necessary for the inhibitory action of A52 . Anti-apoptotic Bcl-2–like proteins inhibit apoptosis by binding the BH3 peptides of pro-apoptotic Bcl-2–like and BH3-only proteins in a hydrophobic groove on the surface of the anti-apoptotic protein [30] . While both N1 and M11 block mitochondrial apoptosis in cells treated with the pan-kinase inhibitor staurosporine ( Figures 5A & S2 ) , consistent with previous reports [26] , [29] , neither B14 nor A52 block apoptosis ( Figures 5A & S2 ) . Superposition of our structures onto that of myxoma virus M11 in complex with the BH3 peptide of Bak [29] reveals the hydrophobic BH3-peptide binding grooves are occluded in both A52 and B14 , but not in N1 ( Figure 5 ) . Residues 92–94 and 117–122 block the groove in A52 , the C-terminal ends of helices 2 and 4 being oriented closer to each other than in M11 , thereby narrowing the groove significantly , and the side chains of Q93 , F94 and Y118 pointing directly into and filling the groove . Equivalent residues ( 63–66 and 82–90 ) occlude the groove of B14 , helices 2 and 4 again being much closer to each other than in M11 and three side chains ( V64 , F65 and Y90 ) pointing directly into and blocking the groove . Bcl- xL and BHRF1 , two Bcl-2 family proteins that are able to bind BH3 peptides and thereby inhibit apoptosis , have restricted grooves that are ‘closed’ in the absence of bound BH3 peptide [37]–[39] . Movement of helices 3 and 4 widens the Bcl-xL groove to allow BH3-peptide binding [39] and , while a structure of BHRF1 in complex with a BH3 peptide is not available , it is likely that rearrangement of the loop between helices 4 and 5 would be required for BH3-peptide binding . In contrast , blockage of the BH3-peptide binding groove by residues at the C-terminal end of helix 2 is characteristic of A52 and B14 ( Figure 5D ) and we propose that it explains the inability of A52 and B14 to protect cells from apoptotic challenge . Interestingly , helix 2 of N1 has the same orientation as in A52 and B14 but is one turn shorter and thus doesn't occlude the BH3-peptide–binding groove ( Figure 5D ) . This is consistent with both the ability of N1 to inhibit apoptosis ( Figures 5A and S2 ) and suggests that N1 is an evolutionary ‘intermediate’ between the apoptosis-regulating Bcl-2–like proteins and those that inhibit NF-κB activation . To investigate the evolutionary relationship between A52 , B14 , N1 and other Bcl-2–like proteins further , a structure-based phylogenetic tree [25] was calculated using all-pairs pairwise structural superpositions of A52 , B14 and 30 representative cellular and viral Bcl-2–like proteins ( Figure 6 ) . Amongst the cellular Bcl-2–like proteins , orthologues are seen to cluster together , residing closer to each other on the tree than to paralogue structures from the same species . However , the poxvirus Bcl-2–like proteins are all more similar to each other than they are to cellular Bcl-2–like proteins despite their divergent functions . The closest viral relatives to the cellular Bcl-2–like proteins are the proteins from gamma herpes viruses ( EBV , KSHV and MHV-68 ) and M11 . These proteins bind pro-apoptotic BH3-peptides and are potent inhibitors of apoptosis [28] , [29] , [37] , [38] , [40] , [41] . More distantly related is N1 , which both inhibits apoptosis by binding BH3-peptides and interferes with NF-κB activation ( Figures 4 & 5 ) . The proteins most distinct from cellular Bcl-2–like proteins , A52 and B14 , lack a BH3-peptide binding groove and inhibit NF-κB activation rather than apoptosis ( Figure 5 ) . This is consistent with the hypothesis that an ancestral poxvirus acquired a gene encoding a Bcl-2–like protein from its host and over evolution this useful protein scaffold has been adapted to interfere with several different cellular signalling pathways [31]–[33] . As poxvirus and cellular Bcl-2–like proteins are of a similar size , convergence of separately-acquired cellular Bcl-2–like proteins to this common , minimal fold in the virus seems unlikely . Interestingly , the poxvirus Bcl-2–like proteins are more closely related to Bcl-2–like proteins from herpes viruses than they are to cellular Bcl-2–like proteins . This might imply either some elements of common ancestry of poxviruses and herpes viruses , independent acquisition of the same cellular Bcl-2–like protein by both virus families , or horizontal gene transfer between the viruses . While Bid lies closer to viral than cellular Bcl-2–like proteins , it is only distantly related to either group ( Tables 3 & S1 ) . Its position in the tree most likely arises from a form of ‘long-branch attraction’ [42] and does not reflect a close evolutionary relationship with viral Bcl-2–like proteins . We have now shown that three VACV proteins , N1 , A52 and B14 , all adopt the Bcl-2–like fold despite sharing little sequence identity and having different functions . A52 and B14 are both members of a protein family ( PF06225 ) that also includes VACV proteins A46 ( VACWR172 ) , C6 ( VACWR022 ) , C16/B22 and K7 ( VACWR039 ) ( Figure S3 ) [14] , [23] and it is likely that these proteins will also adopt a Bcl-2–like fold . Like B14 and A52 , A46 inhibits activation of NF-κB , although it does so by an independent mechanism , binding directly to the TIR domains of TLR4 and of the TLR-associated proteins MyD88 , TRIF , TRAM and Mal [14] , [15] . The sequence similarity shared between A52 , B14 and A46 make it likely that A46 will share the Bcl-2 fold , rather than the TIR fold as suggested previously [15] . The functions of C6 , C16/B22 and K7 are unknown , although peptides derived from C6 and C16/B22 are presented to CD8+ cells by MHC-I during VACV infection , confirming that these proteins are expressed [43] , [44] . [Note that C16/B22 is distinct from the vaccinia serpin-like serine protease inhibitor SPI-1 ( also known as B22 ) ] [45] , [46] . Temporal profiling of VACV gene expression during infection shows A52 , B14 , C6 and K7 to be immediate-early genes and A46 to be an early gene [15] , [17] , [21] , [36] . Genes expressed immediately after or early during infection are often associated with modulation of the host immune response [1] , [17] . Therefore , immediately after or early during infection poxviruses express a number of proteins that adopt the Bcl-2–like fold . While the precise roles of C6 , K7 and C16/B22 remain to be determined , it is evident that poxviruses have adapted the Bcl-2–like fold to interfere at multiple points along signalling pathways mediating the host immune response to viral infection . In summary , we have solved the structure of the VACV immunomodulatory proteins A52 and B14 . These proteins both adopt the Bcl-2–like fold , despite sharing little sequence identity with viral or cellular Bcl-2–like proteins . Neither A52 nor B14 inhibit apoptosis as they lack a hydrophobic surface groove capable of binding pro-apoptotic BH3 peptides . Further , A52 and B14 are representative members of a protein family that also includes VACV proteins K7 , C6 , A46 and C16/B22 , and it is likely that all these proteins will adopt a Bcl-2–like fold despite their varied functions . Structure-based phylogenetic analysis of viral and cellular Bcl-2–like proteins reveal that poxvirus Bcl-2–like proteins are more similar to each other than they are to cellular Bcl-2–like proteins , implying that these poxvirus Bcl-2–like proteins share a common evolutionary origin .
Full-length A52 and an N-terminal truncation lacking residues 1–36 ( A52ΔN36 ) were amplified from VACV Western Reserve ( WR ) cDNA using KOD HiFi DNA polymerase ( Novagen ) according to the manufacturer's instructions ( forward primer: 5′- AGGAGATATACCATGGACATAAAGATAGATATTAGTATTTCTGG-3′ , reverse primer: 5′-GTGATGGTGATGTTTTGACATTTCCACATATACTAGTCTATTC-3′ [A52] and forward primer: 5′-AGGAGATATACCATGACTGATGTTATCAAACCTGATTATCT-3′ , reverse primer: 5′-GTGATGGTGATGTTTTGACATTTCCACATATACTAGTCTATTC-3′ [A52ΔN36] ) . The genes were cloned into pOPINE ( adding a C-terminal Lys-His6 fusion tag ) by InFusion cloning [47] . Full-length B14 ( residues 1–149 ) was amplified by PCR from VACV WR cDNA using HiFi Taq DNA polymerase ( Geneaid ) with primers containing NdeI and EcoRI restriction sites respectively ( forward primer: 5′- GGAATTCCATATGACGGCCAACTTTAGTACC-3′ , reverse primer: 5′-CTCGAATTCTCATCAATTCATACGCCGGAA-3′; sequences encoding restriction sites are underlined ) . The PCR product was cloned into pET28a ( Promega ) cut with NdeI and EcoRI ( Roche ) using T4 DNA ligase ( Promega ) , the resultant plasmid encoding full-length B14 with an N-terminal His6 fusion tag . pCI-based expression plasmids for FLAG-tagged N1 and B14 were constructed as described previously [13] , [26] . Plasmids containing FLAG-tagged A52 , TRAF2 , TRAF6 , NF-κB luciferase reporter and pTK-Renilla luciferase internal control were gifts from Dr . Andrew Bowie ( Trinity College , Dublin , Ireland ) . FLAG-tagged M11 was a gift from Dr . David Huang ( The Walter and Eliza Hall Institute of Medical Research , Melbourne , Australia ) and Bcl-xL was provided by Professor Xin Lu ( Ludwig Institute for Cancer Research , London , United Kingdom ) . Relative protein expression levels were verified by immunoblotting using anti-FLAG or anti-Bcl-xL monoclonal antibodies . Both unlabelled and selenomethionine ( SeMet ) -labelled A52ΔN36 were overexpressed by autoinduction in E . coli Rosetta ( DE3 ) pLysS cells [48] and stored frozen ( −80°C ) until required . The final mass obtained for cells expressing SeMet-labelled A52ΔN36 ( 0 . 5 g/L ) was much lower than obtained for those expressing the unlabelled protein ( ∼10 g/L ) . SeMet-labelled B14 was expressed in E . coli B834 ( DE3 ) cells ( grown in the presence of 30 µg/mL kanamycin ) using SeMet medium ( Molecular Dimensions ) supplemented with 40 mg/L l-SeMet . Cultures were grown at 37°C to an optical density ( OD600 ) of 0 . 6 , cooled to 20°C and protein expression was induced by the addition of 1 mM isopropyl β-d-thiogalactopyranoside . Cells were harvested after 16 h incubation by centrifugation ( 5 , 500 g , 4°C , 20 min ) and the cell pellet was stored frozen ( −80°C ) until required . Thawed cells were resuspended in 50 mM Tris pH 7 . 5 , 500 mM NaCl , 20 mM imidazole , 0 . 2% v/v TWEEN-20 , supplemented with ∼5 mg hen egg-white lysozyme ( Sigma ) and 1 EDTA-free protease inhibitor tablet ( Roche ) , and incubated for 1 h at 20°C before being sonicated on ice for 5 min until the cells were lysed completely . The cell lysate was cleared by centrifugation ( 45 , 000 g , 8°C , 30 min ) and incubated with 1–2 mL of Ni Sepharose 6 Fast Flow beads ( GE Healthcare ) for 1 h at 4°C before being loaded into a disposable chromatography column ( BioRad ) . Beads were washed with 15 c . v . of 50 mM Tris pH 7 . 5 , 500 mM NaCl , 20–40 mM imidazole and the protein was eluted in 50 mM Tris pH 7 . 5 , 500 mM NaCl , 500 mM imidazole . Pooled fractions containing A52ΔN36 were diluted 10-fold in gel-filtration buffer ( 20 mM Tris-HCl pH 7 . 5 , 200 mM NaCl ) , concentrated and then applied to a Superdex 75 column ( GE Healthcare ) equilibrated in gel-filtration buffer . SDS-PAGE confirmed the purity ( >98% ) of the protein and mass-spectrometry confirmed both the identity of native A52ΔN36 and the percentage Se incorporation ( 100% ) of the SeMet-labelled protein ( data not shown ) . Cells were thawed , resuspended in 50 mM Tris pH 8 . 0 , 500 mM NaCl , 1 M non-detergent sulphobetaine 201 , 2% v/v Triton X-100 and 2 mM β-mercaptoethanol , cooled on ice and sonicated until the cells were lysed completely . Lysate was cleared by centrifugation ( 20 , 000 g , 4°C , 30 min ) and applied to a 5 mL Ni-Sepharose HiTrap affinity chromatography column ( GE Healthcare ) that had been equilibrated in binding buffer ( 30 mM imidazole , 500 mM NaCl , 20 mM Tris pH 7 . 9 , 2 mM β-mercaptoethanol ) . The column was washed with binding buffer ( 5 c . v . ) and eluted with an increasing gradient of imidazole ( 30–500 mM ) . Fractions containing B14 were pooled and applied to a Superdex 75 column ( GE Healthcare ) equilibrated in 50 mM Tris-HCl pH 8 . 5 , 150 mM NaCl , 2 mM β-mercaptoethanol . SDS-PAGE and mass-spectrometry confirmed the purity ( >98% ) and identity of the purified protein ( data not shown ) . The presence of β-mercaptoethanol throughout the purification was essential to prevent aggregation and precipitation of the protein . Purified A52ΔN36 and B14 were concentrated to 5 . 2–5 . 4 mg/mL and 3 . 2 mg/mL in 5 kDa MWCO ( Vivascience ) and 10 kDa MWCO ( Millipore ) microconcentrators , respectively . Initial screening of crystallisation conditions was performed at 21°C in 96-well plates with sitting drops ( 100 nL protein+100 nL reservoir ) equilibrated against 95 µL of reservoir solution [49] . For unlabelled and SeMet-labelled A52ΔN36 , initial crystallisation conditions were scaled up as hanging drops ( 1 µL protein+1 µL reservoir ) in 24-well Linbro-style plates equilibrated at 21°C against 500 µL reservoirs containing 15–21% w/v polyethylene glycol 3350 and 0 . 2–0 . 24 M tri-sodium citrate ( space group P21 ) or 22% w/v polyethylene glycol 3350 and 0 . 2 M sodium phosphate ( space group R3 ) , diffraction quality crystals appearing within 48 h . For B14 , initial crystallisation conditions were optimized by screening additives [49] and diffraction quality crystals were obtained in 48 h against reservoirs containing 0 . 2 M di-ammonium tartrate , 20% w/v polyethylene glycol 3350 , 0 . 4 M non-detergent sulphobetaine 201 and 2 mM β-mercaptoethanol . All crystals were cryoprotected by a quick pass through reservoir solution supplemented with 20% v/v glycerol before being flash-cryocooled in a cold ( 100 K ) stream of N2 gas . Diffraction data were collected at 100 K at the ESRF beamlines ID14-4 ( high resolution unlabelled A52 ) and BM14 ( SeMet-lebelled B14 and A52 ) and at Diamond beamline I03 ( low resolution unlabelled A52 ) . Diffraction data were processed with HKL2000 [50] ( Table 1 ) . The three wavelengths of the A52 MAD experiment were cross-scaled , the selenium sites were located , the selenium substructure was refined , and calculated phases were solvent-flattened with SHELXD [51] , SHARP [52] , DM [53] and SOLOMON [54] as implemented by the AutoSHARP structure solution pipeline [55] . The chain was traced using ARP/wARP [56] , 281 of the 304 residues in the final model being positioned automatically . For all structures , manual model manipulation was performed using COOT [57] . For B14 , the three wavelengths of the MAD experiment were cross-scaled and selenium sites were located using SHELXC and SHELXD as implemented in HKL2MAP [58] . Initial phases were calculated using SHARP [59] , solvent flattening was performed using RESOLVE [60] , and the backbone was traced manually . Initial structure refinement was performed using CNS [61] ( B14 ) or using REFMAC5 with phase restraints [62] ( A52 ) . The high-resolution structure of unlabelled A52 ( space group P21 ) was determined directly from the isomorphous structure solved by MAD analysis and the lower-resolution ( R3 ) structure by molecular replacement using PHASER [63] . Final refinement was performed using REFMAC5 ( high resolution A52 ) or phenix . refine [64] ( B14 and low-resolution A52 ) in consultation with the validation tools present in COOT and the MolProbity web server [57] , [65] . For B14 and the low-resolution structure of A52 , non-crystallographic symmetry restraints were used throughout the refinement . Atomic coordinates and structure factors have been deposited with the Protein Data Bank , accession IDs 2vvw ( high-resolution A52 ) , 2vvx ( low-resolution A52 ) and 2vvy ( B14 ) . The representative set of Bcl-2–like structures used for structure-based phylogenetic analysis were selected with the assistance of the SSM web server [34] . Gap-penalty–weighted pairwise superposition of all Bcl-2–like structures was performed using the program SHP [66] to maximise the sum of probabilities of equivalence between pairs of residues for the proteins being compared [67] . The total summed probability was converted into an estimate of the evolutionary distance using the expression: D = −log[ ( P-2 ) / ( <N>-2 ) ] , where D is the evolutionary distance , P is the sum of probabilities and <N> is the mean number of residues in the two molecules [25] . For crystal structures where more than two Bcl-2–like molecules were present in the asymmetric unit the most representative monomers as determined using the MCentral command of LSQMAN [68] was used for the analysis . For structures with two Bcl-2–like molecules per asymmetric unit ‘chain A’ was chosen arbitrarily . For NMR ensembles , the ‘core’ of the most representative member of the ensemble as determined by the OLDERADO server [69] was used . The tree representation was generated from the matrix of evolutionary distances using the programs FITCH and DRAWTREE , part of the PHYLIP package [70] , using default parameters . Cα rmsds , numbers of equivalent residues and evolutionary distances used to generate the phylogenetic tree are presented in Table S1 . Structure-based multiple sequence alignments were generated from superposed co-ordinate files ( see above ) with the “Match->Align” tool in UCSF Chimera [71] using default parameters . Interaction interfaces were analysed using the PISA web server [72] . Human embryonic kidney 293 ( HEK 293 ) cells ( 1×105 per well ) were seeded in 24-well plates and transfected with 250 ng of expression plasmid encoding either FLAG-tagged A52 , B14 , N1 , or M11 , together with 100 ng of NF-κB-luc reporter plasmid and 10 ng of pTK-Renilla luciferase internal control with FugeneHD ( Roche ) according to the manufacturer's instructions . For analysis of the function of the N terminus of A52 , cells were transfected with pOPINE vectors expressing either C-terminally His-tagged full-length A52 or A52ΔN36 ( described above ) , together with plasmids encoding the NF-κB reporter and Renilla internal control . The total amount of DNA ( 500 ng ) was kept constant by supplementation with pCI ( Promega ) or pOPINE . After overnight incubation , the transfected cells were simulated with 100 ng/ml of IL-1α or TNFα ( Peprotech ) for 8 h . Alternatively , cells were transfected with 200 ng of the A52 , B14 , N1 , or M11 expression alleles together with 190 ng TRAF2 or TRAF6 , 100 ng of NF-κB-luc reporter plasmid and 10 ng of pTK-Renilla luciferase internal control and were incubated for 24 h . Cells were harvested in passive lysis buffer ( Promega ) , and the relative stimulation of NF-κB activity was calculated by normalizing luciferase activity with Renilla luciferase intensity . In all cases , data shown are from one of two to four independent experiments with similar qualitative results . Data from experiments performed in triplicate are expressed as means±standard deviation . Apoptosis was measured as described previously [26] . Briefly , HeLa cells were transfected with expression vectors for FLAG-tagged A52 , B14 , N1 , M11 , untagged Bcl-xL or empty vector ( pCI ) together with a CD20 surface transfection marker using FugeneHD ( Roche ) . Cells were stimulated with 0 . 5–1 µM staurosporine for 1 h or left untreated as indicated . The level of apoptosis was assessed by measuring the change in mitochondrial potential ( Δψm ) using the potentiometric dye JC-1 . Cells were collected , washed in phosphate-buffered saline ( 10 mM phosphate pH 7 . 4 , 137 mM NaCl; PBS ) and stained with anti-CD20 APC antibody ( BD Pharmingen ) for 20 min on ice . Cells were then stained with 2 µM JC-1 dye ( Invitrogen ) for 30 min at 37 °C , washed in PBS , re-suspended in FACS buffer ( PBS with 2% v/v foetal calf serum ) and analyzed by flow cytometry ( FACScan; Becton Dickinson ) . Data was analysed using Summit software ( Dako ) . To assess relative protein expression levels , cells remaining after FACS analysis were collected and harvested in RIPA buffer [50 mM Tris-HCl pH 7 . 4 , 150 mM NaCl , 1% Triton v/v X-100 , 1% w/v sodium deoxycholate and 0 . 1% w/v SDS with protease inhibitor cocktail tablets ( Roche ) ] . Lysates were separated by SDS-PAGE ( 15% gel ) , transferred to nitrocellulose membranes and blotted for the presence of N1 , A52 , B14 , M11 using anti-FLAG monoclonal antibody ( Sigma ) or for Bcl-xL using an anti-Bcl-xL monoclonal antibody ( Cell Signalling Technologies ) . Equal protein loading was assessed using an anti-tubulin-α polyclonal antibody ( Chemicon ) . | Cells possess formidable defences against virus infection , but viruses have evolved sophisticated counter-measures to evade such defences . Vaccinia virus , the vaccine used to eradicate smallpox , has about 200 genes , and many of these encode proteins that help the virus evade the host's immune defences . This paper concerns the vaccinia virus proteins A52 and B14 , which block signalling pathways leading to the activation of the NF-κB transcription factor and thereby diminish the host immune response to infection . By solving the three-dimensional structures of A52 and B14 , we show that they closely resemble a family of cellular and viral proteins ( the Bcl-2 family ) that usually function to regulate apoptosis ( a process by which cells commit suicide , thereby stopping the replication of any viruses with which they are infected ) . However , neither A52 nor B14 regulate apoptosis . By comparing three-dimensional structures , we show that vaccinia virus Bcl-2–like proteins more closely resemble each other than they do other cellular or viral Bcl-2–like proteins . This suggests that an ancestor of vaccinia virus acquired a gene encoding a Bcl-2–like protein from its host and , over time , this gene has been copied and adapted for different functions within the virus . | [
"Abstract",
"Introduction",
"Results/Discussion",
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"Methods"
] | [
"virology/immune",
"evasion",
"virology/virus",
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"immunology/immune",
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] | 2008 | Vaccinia Virus Proteins A52 and B14 Share a Bcl-2–Like Fold but Have Evolved to Inhibit NF-κB rather than Apoptosis |
Tsetse flies ( Glossina spp . ) vector pathogenic African trypanosomes , which cause sleeping sickness in humans and nagana in domesticated animals . Additionally , tsetse harbors 3 maternally transmitted endosymbiotic bacteria that modulate their host's physiology . Tsetse is highly resistant to infection with trypanosomes , and this phenotype depends on multiple physiological factors at the time of challenge . These factors include host age , density of maternally-derived trypanolytic effector molecules present in the gut , and symbiont status during development . In this study , we investigated the molecular mechanisms that result in tsetse's resistance to trypanosomes . We found that following parasite challenge , young susceptible tsetse present a highly attenuated immune response . In contrast , mature refractory flies express higher levels of genes associated with humoral ( attacin and pgrp-lb ) and epithelial ( inducible nitric oxide synthase and dual oxidase ) immunity . Additionally , we discovered that tsetse must harbor its endogenous microbiome during intrauterine larval development in order to present a parasite refractory phenotype during adulthood . Interestingly , mature aposymbiotic flies ( GmmApo ) present a strong immune response earlier in the infection process than do WT flies that harbor symbiotic bacteria throughout their entire lifecycle . However , this early response fails to confer significant resistance to trypanosomes . GmmApo adults present a structurally compromised peritrophic matrix ( PM ) , which lines the fly midgut and serves as a physical barrier that separates luminal contents from immune responsive epithelial cells . We propose that the early immune response we observe in GmmApo flies following parasite challenge results from the premature exposure of gut epithelia to parasite-derived immunogens in the absence of a robust PM . Thus , tsetse's PM appears to regulate the timing of host immune induction following parasite challenge . Our results document a novel finding , which is the existence of a positive correlation between tsetse's larval microbiome and the integrity of the emerging adult PM gut immune barrier .
Tsetse flies ( Glossina spp . ) serve as the sole vector of protozoan African trypanosomes ( Trypanosoma brucei spp . ) , which are the causative agents of Human African trypanosomiasis ( HAT ) , or sleeping sickness , throughout most of sub-Saharan Africa . Additionally , parasites from this same species complex also infect domesticated animals , causing an economically devastating disease called nagana . During their lifecycle through mammalian and tsetse hosts , African trypanosomes undergo a genetically complex differentiation process . Once in the fly , stumpy form mammalian trypanosomes differentiate to become procyclics [1] , [2] . At this point most tsetse hosts can efficiently clear their infections [3] . In fact , despite the large number of infected animal reservoirs and high disease burden in Africa , relatively few tsetse flies ( <5% ) are able to successfully transmit trypanosomes to susceptible mammalian hosts [4] . Furthermore , even under ideal laboratory-based conditions , only a small proportion of adult flies are able to transmit parasites to a naïve host [4] , [5] . Several physiological factors have been identified that may contribute to tsetse's natural trypanosome refractory phenotype . These include fly age and nutritional status at the time of exposure to infectious trypanosomes [6]–[8] , antimicrobial peptides ( AMPs ) [9] , [10] , trypanosome-binding lectins [11] , [12] , gut-associated EP protein [13] , [14] , reactive oxygen species ( ROS ) [15] , [16] and parasite inhibitory peptidoglycan recognition protein LB ( PGRP-LB ) [17] , [18] . Many insects that transmit mammalian disease also house gut-associated microbes that modulate their vector competence [19]–[21] . In anopheline mosquitoes , malaria infection outcomes can be directly modulated by the host gut microbiome . For example , commensal bacteria ( Enterobacter spp . ) found naturally in the Anopheles gambiae midgut produce reactive oxygen species that directly inhibit Plasmodium development [22] . Alternatively , commensal fauna in the mosquito gut can indirectly regulate infection outcomes by boosting host immunity , which in turn detrimentally impacts pathogen transmission . This phenomenon was observed when malaria infection outcomes were observed in septic and aseptic adult A . gambiae flowing challenge with Plasmodium gametocytes . Specifically , adult mosquitoes that lacked their microbiome displayed an increased susceptibility to parasites , while their counterparts that housed endogenous bacteria were highly resistant [23] , [24] . These high infection outcomes were attributed to the absence of microbiome-induced anti-Plasmodium immune responses in aseptic mosquitoes . Tsetse flies harbor 3 distinct endosymbiotic bacteria that are intimately associated with their host's physiology . These symbionts , obligate Wigglesworthia , commensal Sodalis and parasitic Wolbachia , are maternally transmitted during tsetse's unique viviparous mode of reproduction [25] , [26] . Unlike mosquitoes , the gut microbiome of adult tsetse is dominated by Sodalis and Wigglesworthia [27] , which may be reflective of the fact that tsetse feeds exclusively on sterile vertebrate blood . In an effort to understand the immunological relationship between tsetse and its microbiome , our laboratory has developed fly lines that contain altered symbiont populations . These dysbiotic fly lines , designated GmmWgm− and GmmApo , either lack only obligate Wigglesworthia , or all of their symbiotic microbes , respectively , throughout their entire lifecycle . Trypanosome infection outcome experiments revealed that GmmWgm− individuals are significantly more susceptible to infection with trypanosomes than are their wild-type counterparts [17] , [28] . This susceptible phenotype was subsequently determined to result from the fact that Wigglesworthia-free adults posses less trypanocidal PGRP-LB than do their parasite refractory wild-type ( GmmWT ) counterparts [17] , [18] . Later studies revealed that both GmmWgm− and GmmApo individuals exhibit a highly irregular expression pattern of humoral and epithelial immunity-related genes and are unusually susceptible to hemocoelic infection with normally non-pathogenic E . coli K12 . Furthermore , GmmWgm− flies contained a markedly deplete population of cellular immunity-associated sessile and circulating phagocytic hemocytes , while this cell type was entirely absent from aposymbiotic counterparts [29] , [30] . To date no information exists regarding how GmmApo flies respond immunologically following challenge with pathogenic trypanosomes , or how this immune response subsequently influences infection outcomes . To further our understanding of the molecular mechanisms that underlie tsetse's parasite refractory phenotype , we investigated the relationship between fly age and symbiont status as they relate to host immunity and trypanosome infection outcome . We analyzed immunity-related gene expression in GmmWT teneral and mature adults , and mature GmmApo adults , following challenge with trypanosomes , and then correlated these data with the infection outcomes we observed in these distinct fly lines . Information obtained from our gene expression analysis also led to the discovery of what may be a novel mechanism that passively modulates tsetse's ability to detect , and thus subsequently respond to , immunogenic parasites . Our results provide further insights into how tsetse's endogenous symbionts regulate their host's immune response .
Previous studies suggest that host age and microbiome status modulate the ability of insect disease vectors to transmit mammalian pathogens [7] , [17] , [20] , [21] . In this study we set out to evaluate how these physiological parameters impact tsetse's ability to transmit pathogenic African trypanosomes . We began by investigating the relationship between tsetse age at the time of trypanosome challenge and subsequent infection outcomes . Previous studies have demonstrated that adult tsetse newly eclosed from their pupal case ( which is known as the teneral state ) are highly susceptible to infection with trypanosomes [6] , [7] . We confirmed that tsetse from our laboratory colony also exhibited the ‘teneral phenomenon’ by challenging adult flies with a parasite-infective blood meal one day post-eclosion from their pupal case . We found that 54% of teneral GmmWT adults harbored midgut trypanosome infections when their 1st blood meal contained infective parasites ( Table 1 ) . For comparative purposes , we found that only about 3% of mature ( challenged 8 days post-eclosion from their pupal case ) GmmWT individuals became infected with trypanosomes following the same challenge . These findings demonstrate that teneral flies from our colony are highly susceptible to infection with trypanosomes . We next investigated whether tsetse's microbiome influences fly susceptibility to trypanosomes . To do so we made use of a tsetse line , designated GmmApo ( Apo , aposymbiotic ) , that is devoid of all of its endogenous symbiotic microbes ( Figure S1A ) [28] , [31] . Mature GmmApo individuals were challenged with T . b . rhodesiense BSF trypanosomes to determine whether infection outcome correlated with the presence and composition of tsetse's microbiome . Following per os challenge with trypanosomes in their 4th blood meal , 58% of mature GmmApo adults had established trypanosomes infections in their gut ( Table 1 ) . Conversely , as indicated above , when age-matched GmmWT individuals were challenged with parasites in their 4th blood meal , only 3% of flies became infected . Our discovery that mature GmmWT adults are highly refractory to infection with trypanosomes , while their age-matched aposymbiotic counterparts ( GmmApo ) are highly susceptible , strongly implies that tsetse's microbiome modulates their host's ability to mount an effective immune response following challenge with parasites . More so , the fact that both Wigglesworthia-free ( GmmWgm−; these flies still house commensal Sodalis and parasitic Wolbachia ) [28] and GmmApo flies exhibit a similarly high susceptibility to infection with trypanosomes indicates that obligate Wigglesworthia , as opposed to Sodalis or Wolbachia , is the primary modulator of tsetse's immune response following challenge with pathogenic trypanosomes . In this study we found that mature adult GmmWgm− and GmmApo flies are highly susceptible to infection with trypanosomes , thus indicating that tsetse's symbionts contribute to their host's immune response against challenge with this parasite . To investigate whether tsetse's gut microbiome directly or indirectly modulates its host's immune response following challenge with pathogenic trypanosomes , we fed newly emerged GmmWT adults 3 blood meals supplemented with either ampicillin , to eliminate Sodalis from their gut , or tetracycline , which clears all endogenous microbes . Thus , these flies , which were designated GmmWT/Sgm− and GmmWT/Apo , respectively , underwent intrauterine larval development in the presence of their endogenous microbiome , but existed in a dysbiotic state as adults ( Figure S1B ) . Following the above-mentioned course of antibiotics GmmWT/Sgm− and GmmWT/Apo individuals were challenged with BSF trypanosomes . Fourteen days post-challenge we found that , similar to their mature GmmWT counterparts , only about 5% of GmmWT/Sgm− flies , and 7% of GmmWT/Apo flies , were infected with trypanosomes ( Table 2 ) . Our finding that mature GmmWT , GmmWT/Sgm− and GmmWT/Apo flies are similarly resistant to infection with trypanosomes suggests that microbes present in the adult gut do not directly produce effector molecules , or modulate host production of effector molecules , that directly kill trypanosomes . Instead , these data suggest that the presence of the symbionts during larval maturation primes tsetse's immune system so that it develops and functions properly during adulthood . We determined that teneral tsetse flies are more susceptible to infection with pathogenic trypanosomes than are their mature counterparts . Additionally , we found that tsetse must harbor obligate Wigglesworthia during intrauterine larval development in order to overcome challenge with infectious parasites during adulthood . In an effort to better understand the association between these distinct phenotypes and the differential infection outcomes observed , we monitored the expression of immunity-related genes at two physiologically relevant time points in teneral and mature GmmWT adults , and mature GmmApo adults , that were either unchallenged or challenged with trypanosomes . We chose 24 hours post-challenge ( hpc ) as the 1st time point to determine tsetse's initial response to the presence of trypanosomes in its gut . The 2nd time point , 3 days post-challenge ( dpc ) , was chosen because a bottlenecking event at this juncture dramatically reduces trypanosome viability in tsetse's gut [32] , [33] . Our prior studies demonstrated that the Imd pathway is involved in tsetse's defense against challenge with pathogenic trypanosomes [9] , [10] , [17] . Thus , to investigate if trypanosome challenge activated the Imd pathway in teneral and mature GmmWT adults , and mature GmmApo adults , we monitored expression patterns of the associated antimicrobial peptide ( AMP ) effector attacin , as well as two negative regulators , peptidoglycan recognition protein ( PGRP-LB ) and caudal , following parasite challenge . We also evaluated the role of Jak/stat signaling by monitoring the expression of domeless , which is the receptor for this pathway . Finally , as indicators of cellular and epithelial immune responses , we monitored the expression patterns of two thioester-containing proteins genes ( tep2 and tep4 ) , and dual oxidase ( DUOX ) and inducible nitric oxide synthase ( iNOS ) , respectively . In insects TEPs presumably function as pathogen-specific opsonins that bind to foreign microbes and promote their phagocytosis or encapsulation [34] , while DUOX and iNOS serve as signaling molecules that are involved in the production of reactive oxygen species and activation of humoral immune responses [35]–[37] . Expression patterns of the immunity-related genes identified above indicated that teneral GmmWT adults present a highly attenuated immune response following exposure to trypanosomes at both 24 hpc ( Figure 1A ) and 3 dpc ( Figure 1B ) . We argue that the immune system of teneral flies is relatively under-developed , and thus is capable of presenting only a weak response following challenge with trypanosomes . Interestingly , despite their weak immune response , ∼50% of teneral GmmWT adults are able to clear trypanosomes before they establish an infection in their host's gut . This finding suggests that the effectors we examined may be functional even at low concentrations and thus inhibited the establishment of infections in 50% of challenged flies . Furthermore , our data show that the expression of attacin , pgrp-lb and iNOS , all of which exhibit trypanocidal activity [38] , [16] , [18] , varies 4-fold among individual flies within the population we tested . Hence , individuals that express more of these immune molecules may be able to successfully clear their parasite infections while those with reduced levels can not . We next compared expression patterns of the same immunity-related genes in mature adult trypanosome-resistant GmmWT and trypanosome-susceptible GmmApo flies . We found that at 24 hpc GmmWT adults presented a latent immune response similar to that of their younger counterparts ( Figure 2A ) . However , by 3 dpc , the time at which parasite infections are typically beginning to clear [4] , genes that encode the AMPs Attacin and PGRP-LB , as well as those that encode the epithelial immunity-related molecules DUOX and iNOS , were expressed at significantly higher levels in mature trypanosome challenged adults compared to unchallenged GmmWT adults ( Figure 2B ) . These findings suggest that multiple immune pathways contribute to the parasite resistant phenotype presented by mature GmmWT adults . Interestingly , GmmApo flies responded differently to challenge with trypanosomes than did their WT counterparts . In this case expression levels of duox and inos , as well as the AMP attacin , were significantly higher at 24 hpc in challenged compared to unchallenged individuals ( Figure 3A ) . By 3 dpc these same genes ( as well as tep 4 ) were still significantly up-regulated in parasite challenged versus unchallenged individuals . However , their median expression levels were in relative decline , suggesting that the immune response of mature GmmApo adults was in remission at this time point ( Figure 3B ) . We hypothesize that the delayed immune activation exhibited by mature GmmWT adults following exposure to trypanosomes may reflect the fact that their gut epithelium is unable to detect immunogenic parasites until at least 24 hpc . In contrast , the relatively potent immune response presented by mature GmmApo adults early in the infection process ( 24 hpc ) suggests that the gut of these flies is able to detect the presence of parasites , and immune eliciting parasite-derived molecules , more promptly than that of their wild-type counterparts . Based on these findings we postulated that tsetse's symbionts regulate temporal aspects of the fly's ability to recognize the presence of pathogenic trypanosomes in their midgut . The midgut epithelia of most insects are separated from the gut lumen by a chitinous , sheath-like structure called the peritrophic matrix ( PM ) . Presumed functions of the insect PM include regulation of digestive processes via passive control of digestive enzyme movement into the gut lumen , protection of midgut epithelial cells from environmental toxins and mechanical damage caused by ingested food particles , and prevention or reduction in the severity of pathogen infections [39] , [40] . Unlike most insects , ‘higher’ Brachyceran flies , including tsetse and Drosophila , house a type II PM that is constitutively produced regardless of feeding status . In the case of tsetse , this structure is immature when teneral adults emerge from their puparium . However , within 96 hrs of emergence , adult tsetse present a fully formed PM [41] . The PM from mature WT tsetse can be removed by gently grasping the structure with fine forceps and teasing it out of microscopically dissected midguts . Interestingly , we have found that when this procedure is attempted with age-matched GmmApo adults , the PM is difficult to grasp and readily breaks apart . This finding suggests that the PM of GmmApo flies may be structurally modified . Our results from experiments described above indicate that teneral GmmWT adults , which lack a fully formed PM [41] , and mature GmmApo adults , are similarly susceptible to infection with trypanosomes ( Table 1 ) . Thus , we hypothesized that tsetse's microbiome may modulate PM formation , which in turn affects trypanosome infection outcomes in this fly . To address this question we histologically analyzed gut tissues from teneral GmmWT , and mature GmmWT , GmmApo , GmmWT/Sgm− and GmmWT/Apo adults . We observed that mature GmmWT , GmmWT/Sgm− and GmmWT/Apo adults have an intact PM , while this structure in age-matched GmmApo ( and teneral GmmWT ) adults is severely compromised or entirely absent ( Figure 4A ) . To further validate that tsetse's microbiome regulates the formation of its host PM , we fed teneral GmmWT adults , and mature GmmWT and GmmApo adults , a modified blood meal supplemented with FITC-labeled dextran molecules ( 500 kDa ) . This procedure allowed us to visualize structural integrity of the PM by monitoring the movement of dextran through midguts of treated individuals . Six hours post-feeding , we observed that dextran molecules were contained within the PM of mature GmmWT individuals . In contrast , an intact PM was absent from midguts of teneral GmmWT and mature GmmApo adults , and a diffuse pattern of dextran molecules was observed in contact with surrounding intestinal epithelial tissues ( Fig . 4B ) . Taken together , these finding indicate that tsetse's larval microbiome plays a role in the development of the adult PM . More so , young GmmWT and mature GmmApo adults may be unusually susceptible to trypanosome infection because they lack a fully developed PM .
In the present study we provide data that further our understanding of the factors that modulate tsetse's immune response following challenge with pathogenic African trypanosomes . Based on our collective experimental evidence , we have developed a model that suggests tsetse's symbionts indirectly modulate their host's ability to detect and immunologically respond to the presence of parasites in their gut ( Figure 5 ) . We found that trypanosome-susceptible teneral GmmWT flies exhibit attenuated expression of immunity-related genes following exposure to trypanosomes . In contrast , mature GmmWT flies exhibit a robust immune response , regardless of adult symbiont status , and are highly resistant to parasites . Additionally , we show that mature GmmApo flies , which are also susceptible to infection with parasites , exhibit robust expression of effector genes earlier in the infection process than do their refractory , age-matched GmmWT counterparts . We speculate that this untimely immune response , which appears inefficient to kill trypanosomes , may occur because mature GmmApo flies present a structurally compromised PM that permits rapid detection of parasite antigens following their entry into tsetse's gut . This novel finding demonstrates that a strong correlation exists between tsetse's larval microbiome and the integrity of the emerging adult PM . Additionally , our results indicate that this structure regulates the timing of tsetse immune induction following parasite challenge . Taken together these findings are indicative of the complex interplay that exists between tsetse's endogenous microbiome and active and passive innate immune mechanisms that influence trypanosome infection outcomes . In this study we determine that tsetse flies from our laboratory colony exhibit the ‘teneral phenomenon’ in that approximately 50% of individuals harbor midgut infections when their first adult blood meal contains infective trypanosomes . This relatively high infection prevalence we observed in teneral GmmWT adults could result from several factors . First , this population is represented by individuals that express significantly different levels of trypanolytic effectors . Those flies that produce less of these molecules may present the parasite-susceptible phenotype we observed in half of teneral individuals . The second factor may involve tsetse's PM , which is constitutively-secreted by the fly's proventriculus organ [39] . Adult flies emerge from their pupal case without a recognizable PM . At this juncture , regardless of feeding status , the matrix begins developing so that by 3–4 days post-eclosion it lines the fly's entire midgut [41] . A recent study demonstrated that trypanosome infection prevalence in tsetse's midgut was inversely related to the length of the fly's PM , as midgut infection rates were found to decrease as the time between pupal eclosion and trypanosome exposure increased [7] . The teneral flies we used for our infection study were collected over a 48 hr time frame post-emergence . Because these flies were not perfectly age-matched , the structural integrity of their PMs varied at the time of parasite challenge . Assuming that PM integrity interferes with trypanosome development in tsetse's gut , the population of trypanosome-infected teneral adults we observed may represent more recently emerged flies . Another contributory factor that may induce a parasite-susceptible phenotype in teneral adults involves maternally-derived trypanolytic immune effectors . One such molecule , PGRP-LB , is transferred to larval tsetse via female milk gland secretions . The quantity of PGRP-LB present in a teneral adult's gut positively correlates with the density of Wigglesworthia present in the milk gland tissue of their mother [18] . Thus , we propose that trypanosome-susceptible teneral adults inherit less PGRP-LB from their mothers than do their refractory counterparts . In contrast to teneral GmmWT adults , which exhibit a relatively ineffective immune response , mature adult tsetse employ a potent and multi-faceted active immune response following challenge with trypanosomes that likely accounts for their refractory phenotype . Immune gene expression data presented in this study indicates that attacin , pgrp-lb , duox and inos are significantly up-regulated in mature GmmWT adults following trypanosome challenge . A major component of this response involves induction of immunodeficiency ( Imd ) pathway-associated AMPs ( including Attacin ) . The importance of this pathway in trypanosome infection outcomes was demonstrated when AMP expression was stimulated via thoracic micro-injection with E . coli prior to per os inoculation with parasites . Tsetse that received this treatment were significantly more refractory to infection than were sham-injected controls [9] . More so , reverse genetic suppression of tsetse pgrp-lc and relish , which are components of Imd pathway , impeded induction of attacin and cecropin expression . This procedure led to an immuno-compromised phenotype characterized by a high prevalence of midgut trypanosome infections [10] , [17] . Tsetse's gut also presents an epithelial immune response that appears to alter trypanosome infection outcomes in this fly . Tsetse's alimentary canal contains a distinct organ , called the proventriculus , which serves as a junction between the fly's foregut and midgut . This organ is presumably immune-responsive in that it produces cytotoxic reactive oxygen species ( ROS ) , including nitric oxide and hydrogen peroxide , as well as Attacin and Defensin , upon microbial challenge [15] . ROS can exhibit direct anti-parasite activity , serve as signaling molecules that activate other immune pathways , and induce apoptotic cell death [37] , [42]–[44] . Interestingly , trypanosome cell death can be dramatically reduced in tsetse when flies are fed a diet supplemented with a range of antioxidants [17] . This finding implicates tsetse-produced ROS as a component of the fly's trypanocidal immune response . We found that mature GmmApo flies are significantly more susceptible to infection with trypanosomes than are age-matched WT individuals . Of note is our observation that parasitized GmmApo adults express significantly less pgrp-lb than do age-matched refractory GmmWT individuals . This finding corroborates those from a previous study , which demonstrated that Wigglesworthia-free tsetse express unusually low levels of this molecule and are highly susceptible to infection with this parasite [17] . Our data also indicate that GmmApo flies , like their refractory wild-type counterparts , up-regulate the expression of immunity-related genes ( attacin , duox , inos and tep4 ) following trypanosome challenge . However , the timing of this response occurs earlier in the infection process in GmmApo compared to GmmWT individuals . Trypanocidal effector molecules produced early in the infection process would become highly diluted in the large , potentially pH-unfavorable blood meal . Furthermore , following completion of a blood meal , tsetse rapidly excretes abundant fluid volumes via diuresis [45] , a process that would likely substantially decrease the quantity of soluble effector molecules present in the resulting trypanosome-containing blood bolus . Cumulatively , these conditions may account for the trypanosome-susceptible phenotype presented by mature GmmApo adults . The comparatively early robust expression of immunity-related genes observed in mature GmmApo adults led us to hypothesize that these flies have an altered ability to immunologically detect the presence of parasite-derived antigens . As a means of addressing this theory we investigated tsetse's PM , which separates the fly's gut lumen from surrounding epithelial cells . While this structure has been proposed to serve as a barrier that physically prevents trypanosome movement through tsetse's gut [46] , the genetic mechanisms that underlie PM-mediated parasite refractoriness in this fly have not been addressed . In fact , the first study to address the genetic association between the PM and host refractoriness to infection with an intestinal pathogen was recently performed using the fruit fly , Drosophila melanogaster [47] . In this case , Drosophila mutants that did not produce the protein Drosocrystallin ( dcy ) presented a PM that was approximately half as thick , and significantly more porous , than that found in wild-type flies . Interestingly , dcy mutants perished in unusually high numbers following per os inoculation with the entomopathogenic bacteria Pseudomonas entomophila and Serratia marcescens , as well as the pore-forming toxin Monalysin ( derived from P . entomophila ) . Furthermore , mutant flies expressed significantly more of the Imd pathway-associated AMP diptericin than did their wild-type counterparts following oral inoculation with P . entomophila . These observations led to the conclusion that Drosophila's PM influences host infection outcomes by modulating the fly's ability to detect the presence of pathogenic organisms and the toxins they produce . Results we present in the current study indicate that tsetse's PM serves a similar regulatory role in this fly . Specifically , we suggest that tsetse's PM influences the fly's ability to immunologically perceive and respond following challenge with parasites . When tsetse consumes an infective blood meal , stumpy BSF T . brucei parasites that are adapted for development in the fly midgut quickly differentiate to become procyclic forms ( the majority of incompetent slender form parasites perish ) . This process is marked by the complete replacement of the protein coat found on the trypanosome surface [3] , [48] . Thus , the early immune response presented by mature GmmApo flies may result from BSF trypanosomes , and shed surface coat molecules , having unimpeded access to immuno-reactive gut epithelia in the absence of an otherwise obstructive PM . In support of this theory , a previous study demonstrated that under normal conditions insect stage procyclic trypanosomes are not microscopically detectable in tsetse's ectoperitrophic space ( EPS , the area between the PM and midgut epithelial cells ) until 6 dpc [33] . Additionally , our results presented herein , and those from a previous study [9] , indicate that wild-type flies that are old enough to present a fully formed PM display virtually no increase in the expression of AMPs until at least 24 hpc with BSF trypanosomes . Taken together , these results suggest that tsetse's PM does not provide a physical barrier to the passage of the parasites from the gut lumen to EPS . Instead we speculate this structure serves as a passive immune barrier that regulates tsetse's ability to immunologically detect and respond to foreign microbes in its gut . In this context , tsetse's PM likely also reduces physical contact between environmentally-acquired microbes and immune-reactive gut epithelia . This function would increase tsetse's overall fitness by preventing the induction of energetically costly immune responses that result in decreased host fecundity [49] . The association between obligate Wigglesworthia and tsetse immune system development is well documented . Results from this study further emphasize the steadfast nature of this association by suggesting that tsetse must house Wigglesworthia during larval development in order to form a fully functional PM during adulthood . Interestingly , in other insects the PM serves not only as an immune barrier , but also a biochemical one that regulates digestive and reproductive processes [39] , [40] , [50] . Assuming tsetse's PM exhibits similarly diverse functional roles , interfering with the structure may be exploitable as a novel form of vector control that would operate in a redundant manner to reduce this insect's capacity to transmit deadly trypanosomes .
This work was carried out in strict accordance with the recommendations in the Office of Laboratory Animal Welfare at the National Institutes of Health and the Yale University Institutional Animal Care and Use Committee . The experimental protocol was reviewed and approved by the Yale University Institutional Animal Care and Use Committee ( Protocol 2011-07266 ) . Wild-type G . morsitans morsitans ( GmmWT ) were maintained in Yale's insectary at 24°C with 50–55% relative humidity . Throughout the manuscript , flies referred to as ‘teneral’ were unfed adults recently eclosed from their pupal case [7] , while those referred to as ‘mature’ were 8 days old and had received 3 blood meals . All flies used in this study were female . Several tsetse lines that harbored modified microbiomes were also generated for experimental use ( see Table S1 ) . The 1st , designated GmmApo , was derived from females treated with tetracycline ( 20 µg per ml of blood ) to clear their entire microbiome . Additionally , tetracycline-treated females also received a diet supplemented with yeast extract ( 1% w/v ) to rescue the sterile phenotype associated with the absence of Wigglesworthia [30] . Thus , GmmApo offspring developed in the absence of all symbiotic bacteria ( Figure S1A ) . Finally , 2 additional tsetse lines , designated GmmWT/Sgm− and GmmWT/Apo , were generated by feeding newly eclosed GmmWT adults 3 blood meals containing ampicillin ( 100 µg per ml of blood ) or tetracycline ( 80 µg per ml of blood ) , respectively . Thus , all of these flies underwent larval development in the presence of their complete microbiome . However , as adults , GmmWT/Sgm− individuals housed bacteriome-associated Wigglesworthia and intracellular Wolbachia ( but no Sodalis; Figure S1B ) while GmmWT/Apo individuals were devoid of all symbiotic microbes ( Figure S1B ) [30] . All flies received defibrinated bovine blood ( Hemostat Laboratories ) every 48 hours through an artificial membrane feeding system [51] . For trypanosome infection experiments , teneral GmmWT ( between 24–48 hrs . old ) adults received 2×106 infective bloodstream form ( BSF ) Trypanosoma brucei rhodesiense per ml of blood in their 1st meal . Mature GmmWT , GmmApo , GmmWT/Sgm− and GmmWT/Apo adults received 3 trypanosome-free ( but supplemented with antibiotics as indicated above ) blood meals followed by a 4th containing 2×106 BSF T . b . rhodesiense per ml of blood . Fourteen days post-trypanosome challenge , all flies were dissected and their midguts microscopically examined for the presence of parasite infections . Each experiment was repeated at least twice . Replicate data were combined when no significant difference in infection prevalence was observed between individual experiments . Immunity-related gene expression was quantified in teneral and mature GmmWT adults , and GmmApo adults , 1 and 3 days post-challenge ( dpc ) with trypanosomes . Sample preparation and quantitative real-time PCR ( qPCR ) were performed as described previously [30] . Amplification primers are listed in Table S2 . Quantitative measurements were performed on at least 4 biological samples ( specific samples sizes are indicated in respective figure legends ) in duplicate and results were normalized relative to tsetse's constitutively expressed β-tubulin gene ( determined from each corresponding sample ) . Fold-change data are represented as a fraction of average normalized gene expression levels in trypanosome-infected flies relative to expression levels in corresponding uninfected controls . Values are represented as the mean ( ±SEM ) . We sectioned and stained midgut tissues from mature GmmWT , GmmApo , GmmWT/Sgm− and GmmWT/Apo adults in an effort to visually confirm PM structural integrity in these fly lines . To do so we collected guts ( inclusive of the bacteriome through posterior midgut ) from 10 day old individuals ( n = 3 per tsetse treatment ) 3 days after they consumed their last blood meal . Tissues were immediately fixed in Carnoy's solution ( 60% EtOH , 30% chloroform , 10% glacial acetic acid ) , embedded in agar ( 1 . 5% ) , dehydrated and cleared through a zylene and EtOH series , and embedded in paraffin [52] . Serial 5 µM tissue sections were cut mid-way through each midgut tissue with a rotary microtome and mounted on poly-l-lysine-coated glass slides ( Richard-Allan Scientific ) . Prior to staining , slide-mounted samples were dewaxed through an additional zylene and EtOH series . Tissues were then stained with hematoxylin and eosin according to the manufacturer's protocol ( Poly Scientific ) , and hard-mounted using Permount mounting solution containing toluene . Finally , samples were visualized under DIC optics using a Zeiss Axio Observer Z1 inverted microscope equipped with a Hamamatsu camera . Dextran feeding assays were performed by employing a modified version of previously described protocols [47] , [53] . In brief , 500 kDa FITC-labeled dextran molecules ( Sigma ) were dissolved in a 2 . 5% sucrose solution and filtered using PD MiniTrap Sephadex G10 columns ( GE Healthcare ) . Tsetse ( n = 10 teneral and mature GmmWT , and mature GmmApo ) were inoculated with dextran by feeding flies a 2 . 5% sucrose solution containing 10% bovine blood and 10% filtered dextran molecules ( 1 mg/ml ) . Six hours post-feeding , midguts were dissected and FITC signal observed using a fluorescent dissecting microscope ( Zeiss Discovery ) equipped with a digital camera ( Zeiss AxioCam MRc 5 ) . Statistical significance of trypanosome infection outcomes between treatment groups , and treatment and control groups , was determined using Quantitative Parasitology 3 . 0 [54] . Statistical analysis of qPCR data was performed by Student's t test using Microsoft Excel software . | Tsetse flies serve as a host to many micro-organisms . Specifically , this fly houses beneficial endosymbiotic bacteria , and can also serve as a vector of pathogenic trypanosomes across much of sub-Saharan Africa . Although flies feed on parasite-infected reservoir hosts , only a small proportion ( 1–5% ) of individuals that acquire an infectious meal become infected and subsequently transmit disease to a naïve host . Several physiological factors , including tsetse's age , nutritional status and innate immune mechanisms , contribute to trypanosome infection outcomes in the fly . We demonstrate that tsetse's endogenous microbiome also impacts the fly's resistance to parasites . Specifically , we show that tsetse must harbor it's symbiotic bacteria during larval development in order to present a trypanosome-refractory phenotype during adulthood . These microbes appear to indirectly regulate the fly's ability to immunologically detect and respond to the presence of trypanosomes . One of the mechanisms by which these microbes regulate parasite transmission involves modulating the formation of a physical barrier ( called the ‘peritrophic matrix’ ) in their host's gut . Our findings are indicative of the complex functional association that exists between tsetse's symbiotic microbes and host immune mechanisms that regulate trypanosome infection outcomes . | [
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] | 2013 | Trypanosome Infection Establishment in the Tsetse Fly Gut Is Influenced by Microbiome-Regulated Host Immune Barriers |
Dengue fever is the most rapidly spreading mosquito-borne viral disease over the past 50 years , with a 30-fold increase in global incidence . Dengue vector control is a key component for the dengue control strategy , since no absolutely effective vaccine or drug is available yet . However , the rapid rise and spread of mosquito insecticide resistance have become major threats to the efficiency of insecticide-based vector control activities . Thus , innovative vector control tools are badly needed . This study aims to confirm the antivirus effectiveness of ivermectin on dengue virus type 2 ( DENV-2 ) in Aedes albopictus ( Skuse , 1894 ) , then to explore its potential use in the combating to the dengue epidemics . Aedes albopictus were first infected with DENV-2 in human whole blood , and at the fourth day after infectious blood feeding , they were divided into eight groups . Seven of them were held for six days with access to 0 , 2 , 4 , 8 , 16 , 32 and 64 ng/ml ivermectin , respectively , and the last one was set as a historical control group , which was stored at -80°C until being detected at the same time with the other groups . Each mosquito was detected using real-time fluorescent RT-PCR kit . DENV-2 RNA concentration ( copies/ml ) and infection rate in each group were compared . Both of quantitatively and qualitatively inhibiting effects of ivermectin have been detected in this study . Generally , DENV-2 replicated well in Aedes albopictus without ivermectin intervention , whose virus loads exhibited significantly higher when the mosquitoes were holding from 4 days to 10 days after infectious blood feeding . In contrast , with the treatment of ivermectin , the infection rate was reduced by as much as 49 . 63% . The regression equation between infection rates ( Y2 ) and ivermectin concentration log2 values ( X2 ) was obtained as Y2 = 91 . 41–7 . 21*X2 with R2 = 0 . 89 . Ivermectin can directly or indirectly inhibit DENV-2 multiplication in Aedes albopictus . Moreover , the actual concentration for application in zooprophylaxis needs to be confirmed in the further field trials .
Dengue fever is the most rapidly spreading mosquito-borne viral disease over the past 50 years , with a 30-fold increase in global incidence [1] . To reverse the growing trend , comprehensive technical strategies involving diagnosis and case management , integrated surveillance and outbreak preparedness , sustainable vector control and future vaccine implementation are necessary . Apart from the other technical elements , effective vector control is a critical component to achieve and sustain reduction of morbidity attribute to dengue . There are well-documented and various historical examples of dengue elimination or significant reduction through control of Aedes aegypti ( Linnaeus and Hasselquist , 1762 ) [2] . While bioassay demonstrates that resistance to organophosphates and pyrethroids are widespread in Aedes aegypti and Aedes albopictus [3–9] . Therefore , innovative vector control tools are badly needed for current control programs on dengue fever [1 , 10] . Many new tools in vector control have been developed , such as insecticide-treated materials [11–14] , lethal ovitraps [15 , 16] , spatial repellents [12 , 14] , genetically modified mosquitoes [17–19] , Wolbachia-infected Aedes spp . [20] , and so on . But effective tools able to block the transmission of dengue inside vector are still lacking . Therefore , we are trying to find an innovative avenue to inhibit dengue virus development inside Aedes mosquito in order to block the cycle of dengue transmission . Two significant progresses in the tools to block the transmission of dengue inside vector benefit from the advances in genetic engineering technology and molecular biology . One is the discovery of cytoplasmic incompatibility ( CI ) induced by the intracellular bacteria Wolbachia ( Hertig and Burt , 1924 ) , which has enhanced replacement in the control programs [21 , 22] . CI is a reproductive phenotype induced by bacterial endosymbionts in arthropods . Measured as a reduction in egg hatchability resulting from the crossing of uninfected females with bacteria-infected males , CI increases the frequency of bacteria-infected hosts by restricting the fertilization opportunities of uninfected hosts in populations [23] . Markedly reduced severity of dengue virus infection has been found in Aedes albopictus infected with Wolbachia [21 , 24] . The other one is the introduction of genetic-based strategies , which has the goal to eliminate or reduce mosquito densities below transmission threshold through population suppression or to establish mosquito populations that are refractory to the pathogen through population replacement and/or modification [25] . Genetically modified Aedes aegypti mosquitoes that activate the conserved antiviral JAK/STAT pathway in the fat body tissue have been developed , and the modified population inhibits infection with several dengue virus ( DENV ) serotypes [26] , but its use encounters regulatory barriers and public opposition in some countries . Few drugs have been tested to inhibit the virus transmission inside mosquito , although some drugs against dengue virus effectively in vitro have been reported , such as quercetin [27] , ivermectin [28–30] , dasatinib [31] , pyran naphthoquinones [32] , mycophenolic acid [33 , 34] , castanospermine [34] , deoxynojirimycin [35 , 36] . From these drugs , we choose ivermectin as an available compound for the investigation by considering following three facts: ( i ) ivermectin has been used for about 30 years for treatment of parasitic infections in human since 1988 [37] , and ivermectin mass drug administration ( MDA ) to humans has been suggested as a possible vector control method to reduce Plasmodium transmission [38–40]; ( ii ) ivermectin has the ability to target exophagic and exophilic vectors [40 , 41] with a different mode of action [42 , 43] from the currently used insecticides [44] , and then avoid known mosquito behavioral and physiological resistance mechanisms [45]; ( iii ) ivermectin is an inhibitor for the development of dengue virus in cells [28–30] . The purpose of this investigation is to further determine ivermectin efficacy against dengue virus type-2 ( DENV-2 ) in Aedes albopictus , and explore its potential application as an innovative vector control tool .
The study was approved by the ethical review committee of National Institute of Parasitic Diseases , Chinese Center for Disease Control and Prevention , and approval document number was 20160627 . Moreover , no specific permits were required for the described field studies . The studies did not involve endangered or protected species . C6/36 mosquito cell and BHK-21 cell lines , derived from Aedes albopictus and Baby Hamster Syrian Kidney respectively , were used in this study . The cell lines were maintained and propagated in Dulbecco’s Modified Eagle Medium ( DMEM ) ( Gibco by Life technologies , Australia ) containing 10% ( v/v ) fetal bovine serum ( FBS ) ( Gibco by Life technologies , Australia ) and 1% ( v/v ) Penicillin-Streptomycin ( Gibco by Life technologies , Australia ) . Cultured C6/36 was incubated at 28°C in 5% CO2 humidified chamber , and was passaged every 2~3 days . At the time of virus multiplication , the serum concentration was reduced to 2% and temperature was increased to 33°C . DENV-2 was propagated using C6/36 cell line and harvested after CPE presentation on day five post-infection . Supernatants containing DENV-2 were collected , centrifuged at 4 , 000 xg for 10 minutes to clear cellular debris , and then were stored at -80°C until further use . The titer of viral stocks was measured by TCID ( 50 ) % using serial dilutions of 101 to 106 of the viral stocks inoculated into BHK-21 cells . The viral titer was calculated according with Reed and Munch [46] . Cell lines and virus were kindly provided by Shenzhen Center for Disease Control and Prevention ( Shenzhen , China ) . Adult mosquitoes of Aedes albopictus were obtained from the National Institute of Parasitic Diseases at Chinese Center for Disease Control and Prevention based in Shanghai and were raised at 26±2°C , 60~80% relative humidity , and a 12:12 light: dark cycle . The larvae were raised on a diet of rat food . Adults were provided with 10% ( g/v ) sucrose solution . Adult mosquitoes aged between three and five days post emergence from larvae were used as experiment objects . The powdered ivermectin formulation was obtained from Sigma-Aldrich ( St . Louis , MO ) . Ivermectin was diluted in dimethyl sulfoxide ( DMSO ) to 10 mg/ml and aliquots were frozen at −20°C . Frozen aliquots of ivermectin were thawed and serially diluted in phosphate buffered saline ( PBS ) prior to addition to human whole blood heated to 37°C prior to mixing . 10 μl of varied concentrations of ivermectin in PBS were added to 990 μl of human whole blood meal to reach 0 , 2 , 4 , 8 , 16 , 32 and 64 ng/ml concentrations offered to mosquitoes . Aedes albopictus aged between three and five days post emergence from larvae were fed together with human whole blood containing the same titer of DENV-2 . After blood feeding , all fully engorged mosquitoes were gently transferred by aspiration to a new 3L cardboard cartons and held in an incubator at 26±2°C , 60~80% relative humidity , and a 12:12 light: dark cycle . Engorged mosquitoes were held for four days with access to human whole blood , and then were randomly divided into eight groups . Seven of them were held for six days with access to 0 , 2 , 4 , 8 , 16 , 32 and 64 ng/ml ivermectin , respectively , and the last one was set as a historical control group . The mosquitoes in the historical control group were stored at -80°C until being detected at the same time with mosquitoes in the other groups . In this way , one parallel control group ( 0ng/ml ) , one historical control group and six treatment groups were set . Three replicates were performed for each group/concentration , with at least 20 mosquitoes per replicate being analyzed . The human whole blood was obtained from Jiangxi International Travel Healthcare Center , which provided healthy physical examination for community . Mosquitoes treated as described above were collected , and DENV-2 RNA copies in each mosquito were detected by real-time RT-PCR at the same time , and the cycle threshold ( CT ) value of each mosquito was recorded . At least 60 mosquitoes were analyzed for each group . After being frozen to death at −20°C , each mosquito was collected in a grinding tube with 350 μl lysis buffer and then was fully grinded by tissue grinded instrument . The DENV-2 RNA was isolated with RNeasy plus Mini Kit ( 250 ) ( Qiagen , German ) , and quantitatively tested with the dengue virus 2 real-time fluorescent RT-PCR kit ( Shanghai ZJ Bio-Tech , China ) . The Master Mix volume for each reaction was pipetted as follows: super mix 18 μl , enzyme mix 1 μl , internal control 1 μl , extraction RNA 5 μl . PCR reaction conditions were: one cycle of 45°C for 10 minutes and 95°C for 15 minutes , then 40 cycles of 95°C for 15 seconds and 60°C for 60 seconds , fluorescence measured at 60°C . During the bioassay , the standard curve between CT values and DENV-2 RNA concentrations ( copies/ml ) was also detected as described previously [47] . The standard curve between CT values and DENV-2 RNA concentrations ( copies/ml ) was analyzed by linear correlation regression with regression equation and the DENV-2 RNA concentration ( copies/ml ) in each mosquito were calculated by the CT value according to the regression equation . All the DENV-2 RNA concentration ( copies/ml ) in each group were presented by the key parameters , including the median , 75th percentile ( P75 ) , 25th percentile ( P25 ) , maximum ( Max ) , minimum ( Min ) and inter-quartile range ( Q ) . For the DENV-2 RNA copies , the differences among the eight groups were analyzed by Kruskal-Wallis test ( K-W test ) , and then were further analyzed by the Turkey studentized range test to determine exactly which two groups had significant difference . According to the detection reagent protocol , when the CT value of mosquito was less than or equal to 40 . 00 , the mosquito was judged to be positive with DENV-2 , and the infection rate in each group was calculated . For the infection rates , Chi-squared test ( χ2 test ) was used to examine the statistical significances among the eight groups , and Duncan multiple range tests were used to determine pair-wise differences , and then linear correlation regression method was used to further analyze the correlation between the infection rates and ivermectin concentrations . P < 0 . 05 was considered to be significant .
The DENV-2 RNA concentration of positive control sample from the commercial kit was 10 , 000 , 000 copies/ml , which was serially diluted to 1 , 000 , 000 , 100 , 000 , 10 , 000 , 1 , 000 , 100 copies/ml . They were synchronously detected with mosquito samples . Three replicates were performed for each concentration . The relationship between CT values ( X1 ) and log10 values of DENV-2 RNA concentrations ( Y1 ) was expressed by the regression equation , which was obtained from the experimental data as Y1 = 12 . 70–0 . 28*X1 with R2 = 0 . 99 . Thus , we got the concentration of DENV-2 RNA in each mosquito by the standard curve . The infection rate in the mosquitoes fed with 0 ng/ml ivermectin ( parallel control group ) was 84 . 62% , which was not significantly higher than the infection rate ( 81 . 67% ) in the historical control group ( Table 1 ) . And the mosquitoes fed with 0 ng/ml ivermectin were of higher DENV-2 RNA concentrations than mosquitoes in historical control group ( Table 2 ) , verifying the multiplication of DENV-2 inside Aedes albopictus when they were raised from 4 days to 10 days post infectious blood feeding without ivermectin intervention . The average of infection rates in the seven groups treated with 0 , 2 , 4 , 8 , 16 , 32 and 64 ng/ml ivermectin from 4 to 10 days post ingesting infectious blood were 84 . 62% , 85 . 29% , 82 . 54% , 74 . 24% , 63 . 33% , 54 . 29% and 42 . 62% , respectively , And the average of infection rates in historical control group was 81 . 67% ( Table 1 ) . Compared with the parallel control group or historical control group , infection rates in the mosquitoes fed with 2 , 4 , 8 ng/ml ivermectin were not significantly lowered; while infection rates in the mosquitoes fed with 16 , 32 , 64 ng/ml ivermectin were much lower ( Table 1 ) , with infection rate being reduced by as much as 49 . 63% ( Fig 1 ) . The regression equation between infection rates ( Y2 ) and log2 values of ivermectin concentration ( X2 ) was obtained as Y2 = 91 . 41–7 . 21*X2 with R2 = 0 . 89 . ( Table 1 , Fig 2 ) . What might confuse us here was that infection rate ( 85 . 29% ) in mosquitoes fed with 2ng/ml ivermectin was seem to be higher than that in the historical control group ( 81 . 67% ) or parallel control group ( 84 . 62% ) , but this differences were meaningless for being without statistical significance . In this part of experiment , antivirus effectiveness on DENV-2 in Aedes albopictus was observed in the ivermectin treatment groups at certain concentration , and the more ivermectin mosquito ingested , the lower the infection rate was . Related parameters indicating the DENV-2 loads in mosquitoes , including Max , median , P75 , P25 , Min and Q in each group were presented in Table 2 . Compared with mosquitoes fed with 0 ng/ml ivermectin , mosquitoes fed with 2 , 4 , 8 ng/ml ivermectin carried the same level of DENV-2 RNA concentrations ( copies/ml ) , and mosquitoes fed with 16 , 32 , 64 ng/ml ivermectin exhibited much lower DENV-2 RNA concentrations ( copies/ml ) ( Table 2 ) , with Max , median , P75 and P25 of DENV-2 RNA concentrations ( copies/ml ) being reduced by up to 85 . 89% , 99 . 99% , 99 . 99% and 84 . 06% , respectively ( Fig 3 ) . On the other hand , compared with mosquitoes in historical control group , DENV-2 had well developed inside mosquitoes fed with 0 , 2 , 4 , or 8 ng/ml ivermectin showing significantly higher DENV-2 RNA concentrations ( copies/ml ) , and was effectively inhibited in mosquitoes fed with 16 , 32 , or 64 ng/ml ivermectin showing the same level of DENV-2 RNA concentrations ( copies/ml ) . The evidences confirmed the observation of antivirus effectiveness that virus loads in Aedes albopictus were statistically reduced by treatment of ivermectin when concentration of ivermectin was more than 16ng/ml . ( Table 2 )
In the past decades , dengue fever was a neglected vector-borne tropical disease , with few of control efforts to reduce the burden of the disease at national or international levels [1] . With more outbreaks occurred every year around the world [48–56] , people are being faced with the problem of difficulty in blocking the growing trend of dengue transmission [1] . Currently , it has been a consensus that vector control is a key component in the dengue control programs . However , the rapid rise and spread of insecticide resistance have become major threats to the efficiency of insecticide-based vector control activities [1 , 3–8] . It is an urgent need to develop innovative control tools for dengue vector control . It was our first try in the laboratory to find out whether ivermectin was able to effectively inhibit the DENV-2 multiplication in Aedes albopictus ( Tables 1 and 2 , Fig 2 ) . The results give us a hint that using ivermectin in some strategy ( e . g . zooprophylaxis [45] ) is potentially a new way to stop dengue epidemic through inhibiting DENV-2 in field Aedes mosquitoes . Interestingly , both of quantitatively and qualitatively inhibiting effects of ivermectin on DENV-2 have been detected in this study . Generally speaking , without ivermectin intervention , DENV-2 was well developed in Aedes albopictus , whose virus loads were significantly higher when the fully engorged mosquitoes were held from 4 to 10 days post infectious blood feeding ( Table 2 ) . In contrast , with the treatment of ivermectin , the infection rate and the median of DENV-2 RNA concentrations ( copies/ml ) were reduced by up to 49 . 63% and 99 . 99% ( Figs 1 and 3 ) . The linear correlation regression was established between concentration of ivermectin and infection rate of mosquitoes , and we found that 88 . 5% reduction of infection rate was attributed to the antivirus effectiveness of ivermectin ( Fig 2 ) . But the inhibiting effort of ivermectin on the virus in mosquitoes depended on the ivermectin dose , only when the ivermectin concentration was high enough ( e . g . over 16ng/ml ) can effectively inhibit DENV-2 inside Aedes albopictus . Thus , it is a new need to find out the exactly effective concentration of ivermectin per bite by mosquito as well as action mechanism of ivermectin in the future research , so as to guide its actual application in zooprophylaxis [45] . This study does not attempt to explore the action mechanism of ivermectin towards DENV-2 in Aedes albopictus . In our opinion , several potential reasons are leading to the inhibiting effect on any of the three aspects , namely virus , vector and natural microbiome of mosquitoes . Ivermectin is of a wide range of bioactivity [57] . It has been initially used in livestock or pets to kill parasites ( e . g . gastrointestinal and mite ) since 1981 . Subsequently , it was proved to be very effective in humankind for a variety of internal nematode infections ( e . g . Onchocerciasis ) [37] . The action mechanism is that ivermectin targets glutamate-gated chloride channels , which plays fundamental roles in nematodes and insects while not accessible in vertebrates , leading to flaccid paralysis [37] . Ivermectin may also interact with γ-aminobutyric acid-gated chloride channels [58] . Both of the two channels are absent in virus . The antiviral activity of ivermectin towards dengue virus had been reported repeatedly since 2012 [29 , 30] , and then was confirmed in 2016 [28] , but all of the researches were carried out in vitro . Considering the existed evidences , the antiviral mechanisms of ivermectin inhibiting DENV-2 in Aedes albopictus can be assumed from the following six aspects: ( i ) by targeting virus NS3 helicase activity [30]; ( ii ) by inhibiting nuclear import with respect to virus NS5 polymerase proteins [28]; ( iii ) by altering some aspects of the mosquito physiology , e . g . reducing the thickness of the peritrophic matrix in Aedes aegypti [59] , delaying blood ingesting in Anopheles gambiae [60]; ( iv ) by stimulating enhanced anti-pathogen innate immunity , e . g . helping the host’s own immune response being able to overcome the immature worms and so kill them [61]; ( v ) by interacting with glutamate-gated chloride channels or γ-aminobutyric acid-gated chloride channels in the mosquito , and then reducing the adaptability between mosquito and pathogen; ( vi ) by influencing the natural microbiome of mosquitoes , since the natural microbiome , like Wolbachia , is related with the DENV 2 infection in Aedes mosquitoes [21 , 22] . After all , these complex interactions between the pathogen and vector make it possible for ivermectin to have the function of antivirus inside Aedes mosquitoes . All of these potential reasons are worth more deep and overall follow-up study . Moreover , there are still some other effects remain poorly understood . It is unclear that how ivermectin exerts its effect on microfilariae infection in human [62] and P . falciparum in Anopheles gambiae ( Giles , 1902 ) [63] . Ivermectin can block the DENV 2 at any anatomical barrier , like midgut or salivary gland . It was a great pity that we did not study where virus was blocked , so we did not test the viral infection , dissemination and transmission rates , all of which are always different in the same group of mosquitoes . Infection of mosquitoes requires the navigation of several anatomical barriers ( e . g . the midgut and salivary glands barriers ) , and last is excreted into saliva for transmission to a new host . Escape from the midgut or colonization of the hemolymph does not necessarily guarantee the infection of the salivary glands . All of these barriers to productive infection of mosquitoes affect the transmission of viruses . Thus , transmission rate is always lower than viral infection rate . In this study , we just chose viral infection rates as an outcome measure . Maybe transmission rate is a more direct indicator to reflect the significance of ivermectin for the dengue control program in terms of blocking the dengue transmission . Anyway , the results showed that virus infection rates were significantly decreased by ivermectin ( Table 1 , Figs 1 and 2 ) , which could also largely illustrate the above-mentioned significance of ivermectin . As shown in Table 1 and Fig 1 , the virus infection rate in Aedes albopictus mosquitoes fed with 0ng/ml ivermectin was 84 . 62% ( 55/65 ) , which was only 42 . 62% ( 26/61 ) in the mosquitoes fed with 64ng/ml ivermectin . The reduction degree of virus infection rate in the treated mosquitoes was up to 49 . 63% , which meant that there were more negative mosquitoes without virus disseminating from midgut to salivary gland , or that there were less positive mosquitoes with virus transmitting from mosquitoes to a new host . In this sense , we concluded that ivermectin can be used as alternative tool for controlling dengue vectors . The results of our study may be quite meaningful for the dengue control program in terms of blocking the dengue transmission by using ivermectin . On one hand , the inhibiting effect on dengue virus in vivo means ivermectin which has been proved to be safety in human [64] has the potential to be developed as a drug for curing dengue patients . On the other hand , its antiviral effect inside the dengue vectors may lead to stopping the epidemics of dengue transmission in the field . Moreover , apart from the observed antivirus effect , ivermectin also is of insecticidal action [60 , 65 , 66] . For an example , about 32 . 22% ( 29/90 ) of mortality was observed in the mosquitoes fed with 64ng/ml ivermectin , which was much higher than 5 . 79% ( 4/69 ) of mortality in the mosquitoes fed with 0ng/ml ivermectin ( χ2 = 16 . 58 , df = 1 , P<0 . 0001 ) . Thus , it is an ideal drug for zooprophylaxis and endectocides [45] . Both of the strategies have been used in combating with malaria elimination [15 , 16 , 67] , and resulted in a decrease of malaria incidence and prevalence in Pakistan [67] . The data illuminates that these two strategies may be still suitable for the dengue control program . Because of the antivirus and insecticidal effect , ivermectin using in endectocides can not only kill a number of blood-sucking vectors , but also inhibit the development of the dengue virus in the survived vectors , playing an unexpected role in reversing dengue’s growing trend in the world . However , the exact antivirus effectiveness and eventually being used in blocking dengue transmission need to be further validated with field Aedes albopictus mosquitoes or even other three serotypes dengue virus . Moreover , the actual concentration for application in zooprophylaxis needs to be confirmed in the field trials . In conclusion , our study shows for the first time that ivermectin can directly or indirectly inhibit DENV-2 multiplication in Aedes albopictus . While the exact antivirus effectiveness and eventually being used in blocking dengue transmission need to be further validated in the field trials with field Aedes albopictus mosquitoes or even other three serotypes dengue virus . | Dengue fever is one of neglected vector-borne tropical diseases with a 30-fold increase in global incidence recently . In 2012 , World Health Organization set a goal to reduce dengue mortality by at least 50% by 2020 . Being faced with more challenges in the dengue control programs , such as the increase of dengue outbreaks , lacking absolutely effective vaccine , rise of vector insecticide resistance and so on; innovative vector control tools are urgently needed for current control programs on dengue fever . To find a new avenue in vector control , we for the first time assessed the inhibiting effectiveness of ivermectin on dengue virus type 2 ( DENV-2 ) inside Aedes mosquitoes . We found that about 80% Aedes albopictus mosquitoes were effectively infected with DENV-2 without treatment of ivermectin . But in the groups of ivermectin treatment , the infection rate of DENV-2 and the median of virus loads were significantly reduced by up to 49 . 63% and 99 . 99% , respectively . Both quantitatively and qualitatively inhibiting effects of ivermectin were detected . We found out that ivermectin was able to effectively inhibit the DENV-2 multiplication in Aedes albopictus , which may gave us a hint that using ivermectin in some control programs as a zooprophylaxis to block dengue epidemic through inhibiting DENV-2 in field Aedes mosquitoes . | [
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"diseases",... | 2018 | Antivirus effectiveness of ivermectin on dengue virus type 2 in Aedes albopictus |
Giardia duodenalis , originally regarded as a commensal organism , is the etiologic agent of giardiasis , a gastrointestinal disease of humans and animals . Giardiasis causes major public and veterinary health concerns worldwide . Transmission is either direct , through the faecal-oral route , or indirect , through ingestion of contaminated water or food . Genetic characterization of G . duodenalis isolates has revealed the existence of seven groups ( assemblages A to G ) which differ in their host distribution . Assemblages A and B are found in humans and in many other mammals , but the role of animals in the epidemiology of human infection is still unclear , despite the fact that the zoonotic potential of Giardia was recognised by the WHO some 30 years ago . Here , we performed an extensive genetic characterization of 978 human and 1440 animal isolates , which together comprise 3886 sequences from 4 genetic loci . The data were assembled into a molecular epidemiological database developed by a European network of public and veterinary health Institutions . Genotyping was performed at different levels of resolution ( single and multiple loci on the same dataset ) . The zoonotic potential of both assemblages A and B is evident when studied at the level of assemblages , sub-assemblages , and even at each single locus . However , when genotypes are defined using a multi-locus sequence typing scheme , only 2 multi-locus genotypes ( MLG ) of assemblage A and none of assemblage B appear to have a zoonotic potential . Surprisingly , mixtures of genotypes in individual isolates were repeatedly observed . Possible explanations are the uptake of genetically different Giardia cysts by a host , or subsequent infection of an already infected host , likely without overt symptoms , with a different Giardia species , which may cause disease . Other explanations for mixed genotypes , particularly for assemblage B , are substantial allelic sequence heterogeneity and/or genetic recombination . Although the zoonotic potential of G . duodenalis is evident , evidence on the contribution and frequency is ( still ) lacking . This newly developed molecular database has the potential to tackle intricate epidemiological questions concerning protozoan diseases .
Giardia is a genus of intestinal flagellates that infect a wide range of vertebrate hosts . The genus consists of six species , which are distinguished on the basis of the morphology and ultra-structure of their trophozoites [1] . Giardia duodenalis ( syn . G . intestinalis , G . lamblia ) is the only species found in humans , although it exhibits a wide host range being found in many other mammals . G . duodenalis is the etiological agent of giardiasis , a gastrointestinal infection in humans ranging from asymptomatic to severe diarrhea as well as chronic disease [2] . Giardiasis represents a major public health concern in both developing and developed countries [3] , [4] . The economic losses , both direct and indirect , caused by this widespread parasitic infection are considerable . Children are at most risk from the clinical consequences of G . duodenalis infection , particularly those in developing countries and living in disadvantaged community settings [5] . In population- and general practitioner-based studies in The Netherlands , G . duodenalis was identified as the most important gastrointestinal parasitic pathogen [6] , [7] . Paradoxically , the diagnosis of giardiasis is not routinely carried out , due to lack of awareness and the similarity of symptoms with other gastro-enteritis diseases . G . duodenalis is also of significant clinical and economic importance in livestock and pet animals [8]–[10] . Giardia has a simple life cycle comprising rapidly multiplying , non-invasive trophozoites on the mucosal surface of the small intestine , and the production of environmentally resistant cysts that are passed with the host faeces . Infectious cysts are transmitted by the faecal-oral route , either by direct contact or by ingestion of contaminated food or water [11] . Illness from this parasite arises through infection in two broad settings: outbreaks and ( sporadic ) endemic transmissions . Outbreaks are most frequently waterborne and caused by contamination of drinking water , although other transmission routes have been implicated as well [1] , [12] , [13] . One complicating factor is that the number of asymptomatic carriers , and their role in the spread of the infections , are not clear [6] , [7] , [12] , [14] . G . duodenalis can be considered as a species complex , whose members show little variation in their morphology , yet can be assigned to seven distinct assemblages ( A to G ) based on genetic analysis [15] . Assemblages A and B are responsible for human infection , and are also found in a wide range of mammals . The remaining assemblages show more restricted host ranges: C and D are found in canids , E in livestock , F in cats , and G in rodents [16] . Genetic characterization has been extensively used to assess the role of animals in the epidemiology of human infection and to develop tools for tracing sources of infection . However , the zoonotic potential of G . duodenalis is still under debate , particularly the role of domestic animals . Transmission may occur from animals to humans or from humans to animals . Alternatively , humans and animals may be infected with host-adapted genotypes only . For example , transmission of Giardia from beavers to humans via drinking water was postulated [17] , [18] . In endemic areas where humans and animals live closely together , transmission from human to animals or vice versa may occur [19] , [20] . Also , the existence of host-adapted Giardia genotypes has been reported [21] , [22] . Until now , the majority of molecular epidemiological studies have been based on the analysis of a single marker from a limited number of isolates . Furthermore , the genetic variability and the usefulness of the different loci in identifying genotypes have not been systematically evaluated . Finally , it remains unclear to what extent allelic sequence heterozygosity ( ASH ) and genetic exchanges contribute to the genetic variation found in Giardia [23] . In this study the zoonotic potential of G . duodenalis is investigated at different levels of resolution ( single and multiple loci on the same dataset ) . Zoonotic potential is defined here as a G . duodenalis genotype , which has been isolated from both human and animal , sources , and doesn't take into account other epidemiological parameters ( such as time and geographical origin ) . A European network of public and veterinary health Institutions from 9 European countries that focuses on zoonotic protozoan parasites ( the ZOOnotic Protozoa NETwork , ZOOPNET ) has been established ( Sprong et al . submitted ) as part of MedVetNet , a European network of excellence working for the prevention and control of zoonoses and food borne diseases . The aims of ZOOPNET were ( i ) to harmonize the methodology for the detection and control of Giardia and Cryptosporidium , ( ii ) to investigate the molecular epidemiology of these infections , and ( iii ) to study the role of animal sources in human disease . A molecular epidemiological database was built in the course of the project , currently containing information on 2476 Giardia isolates , which encompass 3886 sequences , and on 1024 Cryptosporidium isolates , for a total of 1664 sequences . The ZOOPNET-database differs from a representative ( e . g . Genbank ) or a genomic ( e . g . GiardaDB ) database [24] , as it aims to collect epidemiological data linked to a few molecular markers from as many field isolates as possible . A field isolate can be described best as a DNA sample isolated from a human , animal or environmental source . This implies that an isolate may contain more than one G . duodenalis species or genotypes . A part of the database is already publicly available ( https://hypocrates . rivm . nl/bnwww/MedVetNet/ ) . Currently , a more user-friendly web-based database which not only contains all the molecular epidemiological data used in this study , but also allows public and veterinary health researchers to BLAST their sequences in the database , to perform basis phylogenetic analysis and to submit their own data into the database . In the present study , the genetic diversity and geographic distribution of G . duodenalis of human and animal origin , and the potential for zoonotic transmission , were assessed by different molecular genotyping methods .
Giardia isolates of human and animal origin were collected by Public and Veterinary Health Institutions from the European countries represented in the network , as well as and from external research groups on a voluntary basis . Epidemiologic and molecular data were submitted using an Excel-based file , and form the basis of the information present in the database ( Sequences and data used for this study are available on request ) . Furthermore , Giardia sequences were retrieved from the Genbank database . A selection of these sequences was made using the same strategy as previously described [25] . For example , sequences that were too short to cover regions of variation within any given assemblage were used only for analysis at the level of that assemblage , but not at the level of sub-assemblage . In addition , when multiple , identical sequences from any given isolate were deposited in Genbank , only the longest available sequence was retrieved . Although Genbank sequences constitute ∼45% of the database , limited epidemiological data ( mainly country and source of isolation ) are available for those isolates . All molecular epidemiological data were stored and analysed in Bionumerics ( Version 5 . 10; Applied Math , Belgium ) . The contents of the database ( February 2009 ) are described in the supporting information ( Text S1 ) . All of the G . duodenalis sequences were derived from genomic DNA . Most of the sequences were obtained from direct sequencing ( occasionally cloned ) of PCR products amplified from faecal samples . The sequences of reference isolates originated from laboratory strains , which were grown previously in culture or passaged through suckling mice . Each isolate was characterized using one to four of the most commonly employed genetic markers , which corresponds to portions of the small subunit ribosomal DNA ( SSU-rDNA ) , beta-giardin ( BG ) , glutamate dehydrogenase ( GDH ) , and triose phosphate isomerase ( TPI ) genes [25] . All sequences were sorted into their different genes , assemblages , and sub-assemblages as well as alignments along the gene using previously defined references ( Text S1 ) . All of these markers , with the exception of the SSU-rDNA , have a high , though variable degree of genetic polymorphism [25] , and were used to define sub-assemblages and subtypes . Sequences that were too short , or that contain ambiguous nucleotides which prevent their assignment to specific assemblage were excluded from further analysis [25] . Subtyping at the GDH locus was complicated by the use of different primers that amplify different portions of the gene , with only a partial overlap . In order to minimize these transitivity dilemmas , cluster analysis for each locus was performed using Unweigthed Pair Group Method with Arithmetic mean ( UPGMA ) and “most identical matches” as first and secondary criterion , respectively . A secondary criterion will be applied if two equivalent solutions will emerge from the first criterion . The four markers used in this study are unlinked in the G . duodenalis genome , at least in the genome of assemblage A [22] , which is a prerequisite for a multi-locus sequence typing scheme . The following G . duodenalis isolates were used as references for multi-locus sequence typing: for assemblage A , sub-assemblage AI , the axenic strains WB , Portland 1 and Ad-1 [26] , [27]; for assemblage A , sub-assemblage AII , the axenic strains Bris-162 , Bris-136 and KC8 [28]; for assemblage A , sub-assemblage AIII the isolate ISSGdA614 [22]; for assemblage B , sub-assemblage BIII , the strains BAH12 and Ld18 [26] , [29]; and for assemblage B , sub-assemblage BIV , the strains Ad28 and Nij5 [26] , [29] .
The sequences from each of the four markers obtained from 2476 Giardia isolates were assigned to G . duodenalis assemblages A to G by comparison with previously defined reference strains ( Text S1 ) . The distribution of the assemblages within each source ( corresponds to host or host group ) was determined ( Table 1 ) . In humans ( n = 1658 ) , assemblage A ( 43% ) , B ( 56% ) and to a much lesser extent C ( 0 , 1% ) , D ( 0 , 2% ) , E ( 0 , 2% ) , and F ( 0 , 2% ) were found [32] , [33] . All of these assemblages were also found in animals . Thus , at this very low level of resolution assemblages A to F can be considered zoonotic . The relative host range of a specific assemblage is calculated as the distribution of the sources within each assemblage ( Table 2 ) . The presented calculation does not take the absolute numbers of the sources in a population ( e . g . number of cats compared to the number of humans in Europe ) and the prevalence of giardiasis of each source into account . Still , assemblages C and D were mainly found in dogs ( Table 2 ) , assemblage E in livestock , F in cats and G in rodents ( beavers and rats ) . These results are in agreement with previous findings [11] , [16] . Remarkably , the host distribution of assemblage B is predominantly human and to a much lesser extent wildlife and dog ( Table 2 ) . The host distribution of assemblage A is less restricted than B , where companion animals ( 29% ) livestock ( 27% ) and wildlife ( 22% ) have a comparable prevalence of assemblage A as in humans ( 19% ) . This result suggests that humans are the major source of assemblage B , but that domestic animals play a major role in the host range of assemblage A . For those isolates which were characterized at two or more loci ( n = 908 ) , the assignment to a specific assemblage obtained at one locus was inconsistent with that obtained at another locus in 13% of them ( Table 3 ) . Similar results have been reported in previous studies , using the same markers as those in the present study [20] , [25] , [34] . This finding was particularly frequent in isolates from dogs ( ∼34% ) where , depending on the markers used , isolates are typed as either host-adapted assemblages C and D , or as assemblage A and B ( Table 4 ) . Also in ∼12% of the human isolates ( n = 392 ) mixing of assemblages was observed between A and B . As sexual recombination between different assemblages has not been unequivocally demonstrated [23] , [35] , these cases are more likely to represent mixed infections . Sub-groups within assemblages A and B were originally defined by isoenzyme analysis of laboratory-adapted strains , and classified into AI and AII , BIII and BIV [28] . Importantly , other subgroups were observed in a more recent study also based on isoenzyme analysis , and some appear to be host specific [15] . DNA sequence analysis of a smaller number of these isolates confirmed the existence of these subgroups in assemblage A and B at different loci [15] . More recently , a third sub-assemblage within assemblage A ( referred to as AIII ) was identified , and appears to be specifically associated with wild hoofed animals [22] , [36] , [37] . The SSU-rDNA locus showed too little variability among assemblage A and B isolates to perform analysis at the sub-assemblage level , whereas sufficient genetic variation was observed at the other three loci [22] . In companion animals and in livestock infected with assemblage A , approximately three quarter of the sequences corresponded to sub-assemblage AI , and the remaining quarter to sub-assemblage AII ( Table 5 ) . The opposite was found in human isolates: approximately one quarter of the sequences was identified as sub-assemblage AI and three quarter as sub-assemblage AII . The AIII sub-assemblage was mostly found in wildlife , a few cows and in a single cat isolate , but never in humans . In human isolates with assemblage B , sub-assemblage BIII and BIV were found with a very similar frequency ( Table 6 ) . In some wild animals ( beaver , muskrat ) , sub-assemblage BIV was predominantly found . Monkeys and marine animals [22] , [38] , [39] , [40] , [41] , which together represent the majority of the category “others” , were both infected with sub-assemblage BIII and BIV . Thus , at this level of resolution , G . duodenalis sub-assemblage AI , AII , BIII and BIV are potentially zoonotic , whereas sub-assemblage AIII is found exclusively in animals . The geographic distribution of sub-assemblages AI and AII in humans and companion animals/livestock was compared . In companion animals/livestock infected with assemblage A , the majority was sub-assemblage AI , and the minority was sub-assemblage AII ( Table 7 ) . This distribution was found globally , suggesting that sub-assemblage AI has a preference for companion animals/livestock . Except for Asia and Australia , the opposite was found in humans: the majority was sub-assemblage AII , and the minority was sub-assemblage AI . These data show that the three G . duodenalis sub-assemblages A predominantly/preferentially cycle within defined hosts ( AI in livestock , AII in humans , AIII in wildlife ) , and that these cycles do not interact significantly . The geographic distribution of sub-assemblages BIII and BIV in humans showed marked differences between continents . In Africa , infection with G . duodenalis assemblage B , sub-assemblage BIII is more prevalent ( 81% ) than infection with sub-assemblage BIV ( 19% ) , whereas the opposite is found in North-America where 86% of infections are associated with sub-assemblage BIV , and only 14% with sub-assemblage BIII ( Table 8 ) . A more balanced distribution is found in Europe and Australia . The finding of a mixture of assemblages in a significant fraction of individual isolates prompted us to investigate whether this occurred at the level of sub-assemblages . In isolates analysed at two or more loci , sub-assemblage results obtained at the different loci were compared . Mixtures were found between AI and AII , and between AI and AIII . No mixtures were detected between AII and AIII . Within assemblage A , 5 . 4% of mixtures were observed between sub-assemblages AI and AII . Remarkably , mixtures between BIII and BIV characterized 30 . 3% of the isolates . Analysis of human isolates showed that an infection with AI alone occurs as often as an infection with a mixture of AI and AII ( Table 9 ) . A similar situation occurred with sub-assemblage BIII and BIV: an infection with BIV occurs as often as an infection with a mixture of BIII and BIV . Sequence heterogeneity was also observed within each sub-assemblage , and those genetic variants are referred here as subtypes . In order to determine the zoonotic potential at this level , subtypes were assigned to groups of sequences , on the basis of similarity [22] , [30] , [31] . Thus , sequences that differ for a single nucleotide difference defined two subtypes . For example , at the SSU-rDNA locus , 15 subtypes were found among assemblage A isolates ( Table 10 ) . Of these , 3 and 7 subtypes were exclusively found in humans or in animals , respectively , whereas 5 subtypes contained both human and animal isolates . Notably , these 5 subtypes correspond to 92% of the isolates ( humans and animals ) . Genetic variability at each of the other three loci defined several subtypes ( between 3 and 18 ) in both assemblages A and B , and , as subtypes comprises both human and animal isolates , it is possible to infer a zoonotic potential . Subtypes were also determined for assemblages C to F . The subtypes of assemblage C , D and E found in a few human isolates did not match any of the subtypes found in animals . However , several subtypes of assemblage F found in humans at the BG locus were identical to subtypes found in cats [32] . In order to increase the accuracy of genotyping of isolates at this level , subtypes from two or three loci were combined to define multi-locus genotypes ( MLGs ) . 41 sequences , which could not be unequivocally assigned at the level of assemblage , were excluded from the analysis . Combining SSU-rDNA and BG was possible for 33 isolates of assemblage A , and defined 11 MLGs ( Table 10 ) . With this combination only one MLG of assemblage A was potentially zoonotic . The combination of SSU-rDNA and BG for assemblage B also generated a single potentially zoonotic MLG out of 20 MLGs . This MLG was found in 3 out of 46 isolates of assemblage B . The same approach was used for all possible combinations of the 4 markers ( Table 10 ) . When using two markers , the number of potentially zoonotic subtypes and the percentage of corresponding isolates decreased significantly . Still , potential zoonotic subtypes of both assemblage A and B were found when using two markers . When subtypes from three loci are combined , two MLGs of assemblage A are potentially zoonotic , and none of assemblage B . These cases have been described before . In Italy , an isolate from a cat ( ISSGdA107 ) has a MLG belonging to sub-assemblage AII [22] . Human isolates from Belgium , Germany , The Netherlands , Italy , France , Nicaragua , and Australia , have the same MLG . The other case is based on two axenic strains that have a MLG belonging to sub-assemblage AI These two isolates , Portland and Ad-1 , were originally isolated from human patients in the USA and Australia , respectively [15] . Remarkably , the animal ( mostly cattle ) isolates having this MLG are from Canada , Italy and Sweden . There are several technical explanations for the relatively low number of zoonotic MLGs as defined using three loci . Most importantly , the number of isolates typed at this level is still relatively small compared to the number of subtypes defined . Furthermore , most MLGs are from human isolates , particularly for assemblage B . Indeed , for many animal isolates of assemblage A or B , only one or two markers were sequenced , and , in some cases , the mixture of zoonotic and non-zoonotic assemblages prevents an unambiguous identification of the MLGs . An alternative , but less accurate , approach for the identification of potential zoonotic MLGs is to combine the zoonotic information of subtypes of individual markers ( Table 10 , row 1–4 ) . Isolates with 3 markers ( BG , GDH and TPI ) were considered as potentially zoonotic when all three markers were found to be zoonotic individually . For assemblage A , 36% ( n = 101 ) of isolates with 3 markers was found to be zoonotic . For assemblage B , 4% ( n = 56 ) was potentially zoonotic ( Table 11 ) . The presence of heterogeneous sequencing profiles ( characterized by two overlapping nucleotide peaks at specific positions ) has been reported in several papers from different research groups [19] , [22] , [32] , [42] . Besides the quality of the sequencing reaction itself , two explanations can be given for the presence of those mixed profiles: allelic sequence heterozygosity ( ASH ) and mixed infections . Giardia has two diploid nuclei , which may accumulate specific mutations independently , and this generates ASH [23] . The fact that G . duodenalis isolates display a very low level of ASH , initially based on the analysis of few isolates and genetic loci [35] , [43] , has been confirmed by the analysis of the complete WB genome , a strain belonging to assemblage A , sub-assemblage AI [43] . Albeit limited by the small number of loci , and by the difficulty in distinguishing ASH from mixed infections , the data presented in Table 12 clearly shows that heterogeneous sequencing profiles occur much more often in isolates of assemblages B , C , and D than in those from assemblage A , E and F . The number of heterogeneous positions also varied among the loci analysed and the positions involved often coincide with polymorphic sites among different subtypes . The occurrence of ASH complicates the assignment of isolates to specific subtypes , especially for assemblage B . Therefore , the occurrence of zoonotic subtypes within assemblage B was tested after the exclusion of ambiguous nucleotides . The BG , GDH , and TPI sequences from a total of 117 assemblage B isolates ( 100 from humans , and 17 from animals ) were merged and clustered . No zoonotic subtypes were detected . When all isolates ( n = 199 ) typed with 2 markers ( BG-GDH , BG-TPI , or GDH-TPI ) were included in the analysis , 7% were compatible with zoonotic potential . Interestingly , these isolates were from zoo animals and a rabbit . A measure of the genetic diversity of a locus can be estimated by the number of subtypes corrected for the number of isolates . This was achieved by dividing the number of isolates without ambiguous nucleotides ( Table 13 ) by the number of subtypes . The lowest genetic variability was found at the SSU-rDNA locus . Although 15 subtypes were identified at SSU-rDNA for both assemblage A and B , sequence variation , no distinction could be made between sub-assemblages . Most of the sequence variation found at SSU-rDNA was caused by a minority of the isolates . The genetic variability of the other 3 markers varied only a little from each other . Remarkably , the genetic variability at each marker in assemblage A subtypes was ∼2-fold lower than that found in assemblage B subtypes . The genetic distance within assemblage A was higher than within assemblage B ( Table 13 ) . The multi-locus analysis of field isolates may not represent G . duodenalis genotypes as they could consist of a mixture of several G . duodenalis ( sub ) species . To identify multi-locus genotypes among isolates of assemblage A , the sequences of the BG , GDH , and TPI loci from isolates with matching assignment were merged , a multiple alignment was generated and trees were constructed using complete linkage . To increase the accuracy of the analysis , only multi-locus genotypes found in more than one isolate were selected . In total 9 MLGs were identified from 84 isolates for assemblage A ( Figure 1 ) . To evaluate the robustness of the inferred relationships within assemblage A , trees were also generated from each marker . The clustering generated from the individual markers was congruent with the clustering of multi-locus profile ( Table 14 ) . These analyses confirmed the existence of three monophyletic sub-assemblages at each marker . However , the sequence variation at each locus was too low to discriminate between the different subtypes within sub-assemblage AI and AII . For example , subtype AI-1 cannot be distinguished from AI-3 with GDH , and AI-1 is identical to AI-2 when using BG and TPI . Two genotypes were identified , AI-III , and AII-II , which contained both human and animals isolates , which is in agreement with the MLGs identified previously ( Table 10 ) . A similar analysis was performed for assemblage B isolates . In total 31 genotypes were identified from 65 isolates ( Figure 2 ) . The clustering generated from individual markers was able to discriminate sub-assemblage BIII from BIV , but with low bootstrap values , especially for BG . However , multi-locus genotyping of assemblage B was inconsistent with genotyping at the sub-assemblage level: significant mixing ( ∼30% ) of BIII and BIV was observed . In contrast to assemblage A , clustering from individual loci of assemblage B was incongruent with clustering of multiple loci ( Table 14 ) . These results are consistent with the multi-locus subtyping of isolates: In assemblage A , mixing is less frequently observed than in assemblage B ( Table 9 ) . Removal of the “mixed MLGs” from the genotyping analysis did not alter the outcome of the analysis significantly: The bootstrap values as well as the congruency remained low ( not shown ) . Compared to assemblage A , the MLG diversity ( number of genotypes ) of assemblage B is 4 times higher , but their genetic distance is two times lower , both at the level of individual markers and at the level of MLG ( Figures 1 and 2 ) .
Significant differences were found between the sub-assemblages AI , AII and AIII . Although sub-assemblages AI and AII are found in both humans and animals , sub-assemblage AI is preferentially found in livestock and pets whereas sub-assemblage AII is predominantly found in humans . Sub-assemblage AIII is almost exclusively found in wild hoofed animals , and is most likely a host-adapted genotype . Several potential zoonotic subtypes , which correspond to the majority of the isolates , were identified at the level of individual markers ( Table 10 ) . However , combining the subtype information of the available markers of individual isolates ( MLG ) resulted in only two potentially zoonotic genotypes within assemblage A . Thus , the most important conclusion is that analysis of single markers is inaccurate for molecular epidemiological studies . This finding is consistent with the phylogenetic analysis of assemblage A: the genetic variation found in individual markers is too low to allow discrimination of different genotypes ( Figure 1 ) . Conversely , many subtypes for assemblage A were identified for each marker ( Table 10: 15 for SSU-rDNA , 80 for BG , 40 for GDH , and 42 for TPI ) . Subtyping is based on similarity , and a single point mutation has been considered sufficient to describe a new subtype . For all markers it was found that only a minority of subtypes corresponded to the majority of isolates and that the majority of subtypes were found in only one or two isolates . Whether all these subtypes correspond to new genotypes or whether some of them will turn out to be ( sequence ) artifacts is unclear . The significance of all these subtypes will become clearer when more molecular epidemiological data are added to the database . From the six MLGs defined within assemblage A , two are potentially zoonotic . Genotype AI-3 consisted mostly of animal isolates and of a few human ( axenic ) isolates , whereas AII-2 consisted predominantly of human isolates and a single cat isolate . These findings are in agreement with the preferential distribution of AI and AII found at the level of sub-assemblages . Since the number of MLG isolates is relatively small , especially for pet isolates typed with three ( consistent ) markers , more genotypes with zoonotic potential may exist . The assumption is that genetically identical G . duodenalis found in both humans and animals , are zoonotic . Remarkably , the isolates having zoonotic potential were not epidemiologically linked ( i . e . same location , same study ) . These findings highlight the global distribution of these G . duodenalis genotypes , but provide little evidence for zoonotic transmission . The host distribution of assemblage B is predominantly human and to a much lesser extent wildlife and dog ( Table 2 ) . Assemblage B is also found regularly in ( captive ) non-human primates . They generally do not play significant roles in the life cycle of G . duodenalis , which involve humans . The abundance of assemblage B in ( captive ) non-human primates may be due exposure to human sources . Alternatively , assemblage B is well-adapted to infect primates . Genotyping of assemblage B was more problematic . The genetic diversity ( number of subtypes ) and the percentage of sequences with mixed templates ( ambiguous nucleotides ) were ∼2 , 5 and 4 times higher than for assemblage A , respectively . The mixing of the sub-assemblages BIII and BIV within isolates was ∼30% , which is 6 times more than the mixing observed between sub-assemblages AI and AII . Furthermore , the 119 field isolates of assemblage B with 3 markers ( BG , GDH , TPI ) consisted of 102 humans , 13 primates , 2 zoo animals , one guinea pig and one rabbit . Relevant animal sources , in particular dogs and marine animals [38] are present in the database , but are not typed with the 3 markers of assemblage B . Together , these factors hamper the precise assignment of isolates at the assemblage or subtype level . Typing with two but not with three markers resulted in the identification of a few potentially zoonotic MLGs . Alternative approaches , e . g . removal of ambiguous nucleotides or estimation of potential zoonotic MLGs by combining the zoonotic information from individual markers , resulted in the identification of potential zoonotic genotypes , which corresponded to only 4–7% of the isolates of assemblage B . All in all , no clear genotypes could be inferred for assemblage B , and no distinction between zoonotic and host-adapted genotypes could be made within assemblage B . Two principal mechanisms can explain the occurrence of ambiguous nucleotides and the inconsistent assignment of single isolates at the level of both assemblage and sub-assemblage: ( i ) “true” mixed infections; and ii ) allelic sequence heterozygosity ( ASH ) . The presence of more than one G . duodenalis type during a symptomatic infection has important implications for the etiology of giardiasis: it is unclear how humans and animals become infected with two or more G . duodenalis types . Subjects may be infected simultaneously with different Giardia assemblages ( or even subtypes ) , because of environmental mixing , for example in water . Alternatively , subjects are asymptomatically infected with one Giardia assemblage , but become ill/symptomatic from a second infection with another Giardia assemblage . The latter hypothesis is supported by the finding of asymptomatic subjects [6] , [7] , [12] , [14] . The occurrence of mixed infections has important epidemiological implications . Using only one marker for the assignment of isolates to specific ( sub ) -assemblages is not always reliable , as different markers can give different results . For example , isolates can be typed as “potentially zoonotic” with one marker , but as “host-adapted” with another . More reliable results are obtained when multiple markers are used for typing . On the other hand , “true” G . duodenalis genotypes are difficult to identify in mixed infections . Allelic sequence heterozygosity ( ASH ) is not unusual for diplomonads , which have two diploid nuclei , and replicate asexually [1] . Indeed , in asexual eukaryotes , the two allelic gene copies at a locus are expected to become highly divergent as a result of the independent accumulation of mutations in the absence of segregation ( Meselson's effect ) . Therefore , substantial genetic differences are expected to accumulate among the chromosome homologues in asexual organisms with a ploidy of two or higher [44] . However , the ASH found in the genome of G . duodenalis assemblage A is extremely low [43] , but the mechanism ( s ) responsible remained undetermined . Based on the presence of ambiguous nucleotides in sequences derived from PCR products , it is to be expected that the ASH is higher in assemblages B , C , and D than in assemblages A , E and F ( Table 11 ) . Recent studies have shown that G . duodenalis may be able to undergo sexual reproduction , a phenomenon that can influence ASH levels [35] , [45] . However , the frequency of recombination is not known , nor its impact on the etiology and epidemiology of giardiasis [11] , [23] . The ZOOPNET-database is the largest molecular epidemiological database of G . duodenalis to date . Still , the limitations of this unique database are apparent . Currently , the database contains a heterogeneous geographic- and incomplete source distribution of a “limited” set of isolates . Furthermore , each isolate is characterized by a small set of epidemiological data and limited sequence data . Our aim is to expand and improve the ZOOPNET database: since the content of the ZOOPNET database is accessible via internet , scientists can use these data for their own epidemiological studies . The web-based ZOOPNET-database will remain accessible , and its interface will be soon improved . Both veterinary and public health researchers are welcome to submit their molecular epidemiological data on G . duodenalis and Cryptosporidium to ZOOPNET . The web-based ZOOPNET-database has a flexible content and provides a powerful tool for new ( inter ) national studies on giardiasis ( and cryptosporidiosis ) . | Giardia duodenalis is a parasite causing a gastrointestinal disease in humans , pets , livestock , and wildlife . The role of animals in human disease is unclear , because Giardia from humans and animals is morphologically indistinguishable . An international consortium of both veterinary and public health institutions built a web-based database , where molecular and epidemiological data are combined . After extensive genetic characterization , the zoonotic potential of Giardia became evident , but data on frequency and role in epidemiology is ( still ) lacking . Surprisingly , mixtures of Giardia genotypes in individual hosts were frequently observed , and have important implications for the etiology of Giardiasis . Possible explanations are the uptake of mixtures of Giardia genotypes by one host , or subsequent infection of an already infected host , likely without overt symptoms , with a different Giardia species , which may cause disease . We demonstrated that collaborative , human and veterinary health integrated databases have the potential to tackle intricate epidemiological questions concerning parasitic diseases , as was demonstrated for G . duodenalis in the present study . | [
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"and... | 2009 | Identification of Zoonotic Genotypes of Giardia duodenalis |
Parasitic roundworm infections plague more than 2 billion people ( 1/3 of humanity ) and cause drastic losses in crops and livestock . New anthelmintic drugs are urgently needed as new drug resistance and environmental concerns arise . A “chokepoint reaction” is defined as a reaction that either consumes a unique substrate or produces a unique product . A chokepoint analysis provides a systematic method of identifying novel potential drug targets . Chokepoint enzymes were identified in the genomes of 10 nematode species , and the intersection and union of all chokepoint enzymes were found . By studying and experimentally testing available compounds known to target proteins orthologous to nematode chokepoint proteins in public databases , this study uncovers features of chokepoints that make them successful drug targets . Chemogenomic screening was performed on drug-like compounds from public drug databases to find existing compounds that target homologs of nematode chokepoints . The compounds were prioritized based on chemical properties frequently found in successful drugs and were experimentally tested using Caenorhabditis elegans . Several drugs that are already known anthelmintic drugs and novel candidate targets were identified . Seven of the compounds were tested in Caenorhabditis elegans and three yielded a detrimental phenotype . One of these three drug-like compounds , Perhexiline , also yielded a deleterious effect in Haemonchus contortus and Onchocerca lienalis , two nematodes with divergent forms of parasitism . Perhexiline , known to affect the fatty acid oxidation pathway in mammals , caused a reduction in oxygen consumption rates in C . elegans and genome-wide gene expression profiles provided an additional confirmation of its mode of action . Computational modeling of Perhexiline and its target provided structural insights regarding its binding mode and specificity . Our lists of prioritized drug targets and drug-like compounds have potential to expedite the discovery of new anthelmintic drugs with broad-spectrum efficacy .
Parasitic nematode ( roundworm ) infections impose an enormous burden of morbidity on humanity [1] , [2] . Only a few drugs are commonly used to treat nematode infections , creating a dangerous environment for the emergence of drug resistance . Currently , administering anthelmintic drugs on a yearly basis is necessary to break the infection cycle , but also causes drug resistance in parasites that infect human and animal populations [3] , [4] . Many of the drugs used to treat filarial infections , including diethylcarbamazine ( DEC ) , ivermectin , and albendazole , predominately kill nematodes in their microfilarial stage and have a much lower activity level in adult worms [5] . Plant parasitic nematodes have devastating effects on crops , costing $78 billion per year globally [6] . In addition to the possibility of the development of pesticide resistance in plant parasitic nematodes , there are also environmental concerns associated with them . For example , the United States is phasing out methyl bromide ( a highly effective pre-plant soil fumigant used on high-value crops ) due its ability to deplete ozone in the stratosphere [7] . Thus , there is a pressing need to develop new anthelmintic treatments and pesticides [1] that are highly efficient and environmentally safe . A systematic way of identifying new targets is by studying metabolic pathways , particularly chokepoint reactions within particular pathways . A “chokepoint reaction” is defined as a reaction that either consumes a unique substrate or produces a unique product ( Figure 1A & B; [8] ) . If the enzyme catalyzing a reaction that produces or consumes a unique compound can be inhibited , the entire pathway will be blocked , leading to accumulation of the unique substrate or the organism being starved of unique product [8] . The idea of chokepoints and essentiality is further supported by Palumbo et al [9] , which demonstrated that lethality corresponds to a lack of alternative pathways in a network that has been perturbed by a blocked enzyme . Chokepoint analyses have been used for drug target identification in several pathogenic organisms . In two different studies , chokepoint analyses were performed to determine novel drug targets for two parasites: the mitochondrial protist , Entamoeba histolytica [10] , and the protozoan parasite Plasmodium falciparum , which causes malaria [8] . Two additional studies have applied chokepoint analysis to find unique drug targets for Pseudomonas aeruginosa [11] ( a common bacterium that causes infections ) and Bacillus anthracis [12] ( the bacterium that causes anthrax ) . Another study which explored P . falciparum drug targets has evaluated the essentiality of a reaction in a pathway by deleting a reaction in silico and determining if the metabolic network could find an alternative pathway to get to the same endpoint [13] . A chokepoint analysis and the essentiality of a reaction have been combined to find antibacterial drug targets [14] . However , most of these studies have yielded a long list of chokepoints without any prioritization for testing . The number of nematodes sequenced has risen dramatically recently , with a total of 10 complete nematode genomes being published and around 30 in progress [15] , [16] . These newly sequenced genomes provide a unique opportunity to find new anthelmintic drug targets that may be broad-spectrum in nature . The set of 10 sequenced nematode genomes provides representatives from four of the five clades spanning the phylum Nematoda [17] including those that are free-living , and plant , animal , or human parasitic nematodes . In this study , we determine chokepoint reactions using the intersection in all 10 nematode-deduced proteomes ( the common/intersection to all ten studied nematodes , CommNem ) , as well as the complete set of chokepoints within the 10 deduced proteomes ( the union of all 10 nematode species , UniNem ) . We also isolate a group of chokepoints that are only found in a union of parasitic nematodes ( ParaNem ) . All other chokepoint analysis studies have only used a single organism in their analysis , making this pan-phylum analysis much more comprehensive than previous studies . The chokepoints from nematodes are compared to chokepoints in Drosophila melanogaster and Homo sapiens , in addition to the chokepoints found in the publicly available databases , KEGG Drug and DrugBank [18] , [19] . Further , targets of insecticides were also investigated . We confirm that chokepoints are meaningful drug targets by identifying chokepoint enzymes that are already known anthelmintic and insecticide targets through this method . Given the list of nematode chokepoints , we prioritize the list by evaluating specific criteria and compare the results to known drug targets from two publically available databases . In addition , we provide a list of enzymes involved in chokepoint reactions that have already known drug associations . Seven of these compounds ( referred to as “drug-like compounds” because while pharmacological properties were used to screen out compounds , not all of the compounds in those databases are approved drugs ) were experimentally tested in C . elegans and two parasitic nematodes . Three drug-like compounds elicited a deleterious phenotype in C . elegans , and one of these also yielded a deleterious phenotype in the two parasitic species , demonstrating that this prioritized list of drug-like compounds should be further studied for good candidates for repositioning and/or development as potential anthelmintic drugs . We present evidence that one of these drug-like compounds , Perhexiline , acts according to its predicted mode of action . Computational modeling suggested structural differences in the binding site that can be used to develop a more specific , efficacious drug .
The following list of nematode genomes was analyzed: Brugia malayi [20] , Caenorhabditis species from WormBase release WS240 ( Caenorhabditis brenneri , Caenorhabditis briggsae , Caenorhabditis elegans , Caenorhabditis japonicum , Caenorhabditis remanei ) , Meloidogyne hapla ( http://supfam . mrc-lmb . cam . ac . uk/SUPERFAMILY/cgi-bin/gen_list . cgi ? genome=wm; [21] ) , Meloidogyne incognita ( http://www . inra . fr/meloidogyne_incognita/g enomic_resources/downloads; [22] ) , Pristionchus pacificus ( http://pristionchus . org; [23] ) and Trichinella spiralis [24] . The Homo sapiens genome was downloaded from Ensembl ( Homo_sapiens . GRCh37 . 57 . pep . all . fa ) and Drosophilia melanogaster were downloaded from Flybase 5 . 26 ( http://flybase . org/static_pages/downloads/archivedata3 . html ) . The sequences of all the genomes had open reading frames discerned and then translated to protein for analysis ( henceforth referred to as ‘proteomes’ ) . Proteins with EC ( enzyme commission ) numbers associated with them were downloaded from KEGG version 58 [18] . WU-BLASTP ( wordmask-seg , hitdist = 40 , topcomboN = 1 , postsw ) was used to screen the proteomes for sequence similarity and find homology to proteins with an associated EC number and best match , scoring below 1e−10 . The intersection of ECs ( i . e . common ECs , “CommNem” ) and the union of ECs ( i . e . set of all nematode ECs , “UniNem” ) in the 10 nematode proteomes were parsed using PERL scripts developed in-house . Both KEGG Drug [18] and DrugBank [19] were used to identify potential drugs that bind to targets in the nematode proteomes , H . sapiens , and D . melanogaster . These databases contain some FDA approved compounds , as well as compounds that were known to interact with certain targets . The KEGG Drug and DrugBank databases used for analysis were downloaded on 4/14/2010 and 5/19/2010 , respectively . ECs were linking to targets using annotations from the KEGG Drug database . DrugBank contains the protein sequences of the targets , as well as their associated drugs . WU-BLASTP was used to screen the targets in DrugBank against the KEGG genes database to get an EC number annotation that matched within a cutoff score of 1e−10 or better . The EC number associated with the DrugBank target was then associated with the drug within DrugBank . The reaction database from KEGG v58 [18] was used to identify chokepoint reactions and corresponding chokepoint enzymes . Each reaction equation is listed as a separate reaction with a unique identifier under the ENTRY field . The KEGG reaction database also contains a file that lists the reactions within the reaction database as reversible or irreversible ( reaction_mapformula . lst – downloaded 6/21/2011 ) . The entire reaction was extracted from the KEGG reaction database by parsing the EQUATION field , and the reaction_mapformula . lst file was used to obtain the directionality of the reaction such that the reactions could be written with reactants on the left side and products on the right side . If the reaction was reversible , this was also noted in the file because products and reactants would be ambiguous . The reactions were placed into a [compound×reaction number] matrix by parsing an intermediate file that contained the directionality and all the products and reactants for the reaction within the matrix , −1 indicated the compound was consumed ( i . e . the compound was listed on the left side of the equation ) , +1 indicated the compound was produced ( i . e . the compound was listed on the right side of the equation ) , 2 indicated the reaction was reversible , and a zero indicated the compound did not take part in the reaction . To find the chokepoints , the matrix was parsed for compounds that were only produced or consumed in a single reaction . If a compound was produced or consumed in a single reaction , only a single 1 or −1 would be present across the entire compound row within the matrix . In some cases , a compound was uniquely produced or uniquely consumed , but was part of a reversible reaction ( i . e . two 2's would be present within a row ) . If this reaction was the only reaction in which the compound participated , this was also called a chokepoint . The chokepoint compounds were related to EC numbers using the ENZYME field in the reaction database . The EC numbers corresponding to proteins in the various genomes were mapped to KEGG metabolic pathways active in nematodes . Pathway categories that were not applicable such as photosynthesis , carbon fixation , reductive carboxylate cycle were excluded . The distribution of chokepoint targets and known drugs in metabolic pathways was compared to determine any potential enrichment using Fisher's Exact Test . Pathways in the KEGG reaction database ( v58 ) were enumerated . First , the KEGG reaction database was broken into separate reaction pathways based on the “PATHWAY” classification . There were 8121 entries in the reaction database , and 5638 had a PATHWAY classification . Only 142 unique reaction pathways were used; due to the large size and overlap with other pathways , rn00240 , rn00230 , rn01100 , rn01110 , and rn01120 were not used . For each of the different pathways , a separate [compound×reaction number] matrix was generated as described in the “Identifying Chokepoints” section above . The starting and ending nodes for reaction pathways were generated from this matrix by determining compounds that were consumed but not produced ( start nodes ) and produced but not consumed ( end nodes ) . Beginning with each of the start nodes , the compounds in all possible pathways were enumerated . The position of the chokepoint within the pathway was determined by the number of compounds in the pathway before the chokepoint , as well as the length of the entire pathway . Chokepoint enzymes were prioritized by assigning a point for meeting each of the following criteria , then ranked based on number of points: EST-based gene expression found in a parasitic stage for plant parasitic nematodes ( egg , J2 , J3 , J4 , adult ) and infective/parasitic stages for human and animal parasitic nematodes ( embryo , L3 , L4 , adults ) ; expressed in pharynx , intestine , neurons , muscle , or hypodermis [25] , [26] , [27] in C . elegans ( www . wormbase . org ) ; less than 30% sequence identity to H . sapiens over half the length of the sequence; chokepoint enzyme functioning in two or more pathways; chokepoint enzyme involved in nucleic acid metabolism; and chokepoint is a hydrolase based on their enrichment ( classification as EC 3 , enzyme commission number ) . This analysis was performed to determine if certain classes of enzymes were more likely to have drugs associated with them . This information was fed into the prioritization scheme . EST sequences sets for the 10 species were downloaded from Genbank on 7/16/2010: C . brenneri , C . briggsae , C . japonicum , M . hapla , M . incognita , T . spiralis , P . pacificus , B . malayi , and C . remanei . C . elegans EST sequences were downloaded from GenBank on 4/21/2010 . The tissue expression data from C . elegans was obtained from WormMart ( WS195 ) on 4/23/2010 . Proteins associated with ECs ( using KEGG ) were blast searched against protein targets in DrugBank as described above . The ECs from DrugBank were compared to CommNem and UniNem . Cheminformatic properties were obtained by running SMILES strings ( SMILES are strings of ASCII characters that describe a compound unambiguously ) extracted from DrugBank through the Cytoscape [28] plugin , ChemViz . To prioritize the drugs , drugs were given one point for meeting each of the following criteria: molecular weight ≤500 , 0<number of rotatable bonds ≤10 , hydrogen-bond donors ≤5 , hydrogen-bond acceptors ≤10 , logP≤5 [29] . This additional screen was done because the compounds in the drug database are not optimized for Lipinski's rules and thus may not have been “successful” drugs for the disease for which they were developed/tested . For a drug to be effective , it should have a long half-life , so a drug with half-life ≥60 minutes was rewarded with a point . Toxicity information is also important for future testing and therefore , a compound with any available toxicity information was given an additional point . The maximum attainable compound score was 7 . Drug-like compounds were also eliminated if placed in the dietary supplement , micronutrient , or vitamin categories by DrugBank , as various vitamins and amino acids were not desired . Nematode proteins were searched against sequences from DrugBank , and then parsed for sequences that had 50% or greater identity over 80% of sequence length . Only these targets were considered in the prioritized list . Compounds were obtained from the following sources: Perhexiline maleate ( 1 DB1074 is just perhexiline; CAS: 6724-53-4; P287320 ) from TRC; Carbidopa ( 2 DB00190; CAS: 28860-95-9; BML-EI265 ) and dopamine ( 4 DB00988; CAS: 62-37-1; BML-AC752 ) were ordered from Enzo Life Sciences dissolved in DMSO; LT00772250 ( Probenecid 5 DB01032; CAS: 57-66-9 ) , LT00255846 3 ( similar to DB00993; the DrugBank compound was not available , so a similar compound was ordered ) , LT00138053 ( 6 DB01033 ) , LTBB001666 ( 7 DB00548 ) were ordered from Ryan Scientific . Compounds formulated in 100% DMSO were tested in microtiter plates containing 50 µl nematode growth media , 1% E . coli and 20 L1 C . elegans . Five concentrations in 4-fold increments ( 0 . 078 , 0 . 3125 , 1 . 25 , 5 , and 20 ppm; ∼25 to 60 µM , depending on the molecular weight of the compound ) were tested , and the experiment was repeated twice and a final confirmation test , with the best result reported . The efficacy of a compound was determined based on the motility of the larvae as compared to average motility of control wells containing DMSO only at 48 hours post treatment ( by that time the larvae develop to L4's; screening is not performed at a later stage due to the way imaging is done , i . e . comparing exact numbers of parasites in every well ) . The motility was assessed using a camera-based imaging . The camera takes multiple images of a well and the changes in movement between the images are calculated . An absolute movement value is calculated for each well . On each test plate , multiple wells containing only DMSO are included as a control . The absolute movement value from these wells was averaged and then compared to the movement in the treatment wells . The percent reduction in motility is calculated by dividing the movement in the treatment well by the average movement of the DMSO wells . Controls were used on every plate and in every test ( data not shown ) . Movement was manually assessed at 72 hours post-treatment to determine if there were altered movements or morphological changes not detected by the imaging system . Compounds formulated in 100% DMSO were tested in microtiter plates containing 50 µl nematode media , fecal slurry and 20 L1 Haemonchus contortus . The experiment was repeated twice at five concentrations in 4-fold increments ( 0 . 078 , 0 . 3125 , 1 . 25 , 5 , and 20 µM ) . The efficacy of a compound was determined based on the motility of the larvae ( when the larvae have developed to L3's ) as compared to average motility of control wells containing DMSO only . A MIC90 value was calculated by determining the lowest dose at which there was a 90% reduction in motility as compared to the control wells . The motility was assessed using a camera-based imaging system as described in the C . elegans screen . Larval movement was manually assessed at 72 hours post-treatment to determine if there were altered movements or morphological changes not detected by the camera . Compounds were tested at two static doses of 50 µM and 12 . 5 µM in Onchocerca lienalis . Five microfilariae were added to each well of a 96-well microtitre plate . Larvae were assessed at 120 hours post-treatment and efficacy was determined by visually assessing the motility of the larvae in the treated wells as compared to control wells . While other stages for screening could also be used , our approach was implemented as an early indicator of activity . Progressing to advanced tests against relevant clinical stages should be the next step for future research . In particular , when working with filarial worms , having some filter for prioritizing compounds is helpful , since access to adult stages is often difficult . Real-time measurements of oxygen consumption rates ( OCR ) were made using an XF-24 Extracellular Flux Analyzer ( Seahorse Bioscience ) as previously described [30] . The real-time extracellular flux experiment was designed to evaluate whether Perhexiline decreases OCR via inhibiting mitochondrial carnitine palmitoyltransferase in C . elegans . The concentrations used ( 25–100 uM ) do not have any impact on the movement of the worms ( based on examination under the microscope ) , but do have an impact on the OCR . Synchronized young adult C . elegans were washed with M9 media and plated into XF-24 culture plates at approximately 100 worms/well . OCR measurements were recorded under basal conditions or in the presence of Perhexiline , Etomoxir ( Sigma ) and/or Ivermectin ( Sigma ) at various concentrations , over a period of 1 . 5 hours and 40 minutes . The significance of observed OCR differences was assessed using Student's t-test using GraphPad Prism Version 5 . The treated worms ( approximately 100 µl settled volume ) were washed in sterile PBS and resuspended in 100 µl TRIzol reagent ( Invitrogen ) . Samples were frozen with liquid nitrogen and homogenized . Following the homogenization , the worm/TRIzol powder was collected and allowed to thaw on ice . A further 0 . 2 volumes of chloroform were added into samples , and gently mixed , incubated at room temperature for 3 minutes , then centrifugated at 12 , 000× g for 15 minutes at 4°C . The upper aqueous phase was transferred to a fresh tube and RNA was precipitated by an additional 0 . 5 volumes of isopropanol followed by incubation at room temperature for 10 minutes . The mixture was then centrifuged at 12 , 000× g for 10 minutes at 4°C . The supernatant was discarded and the RNA pellet was washed with 500 µl of 75% ( v/v ) ethanol before centrifugation at 7 , 500× g for 5 minutes at 4°C . The supernatant was removed and the pellet air-dried . The RNA pellet was suspended in nuclease-free distilled water . The total RNA was treated with Ambion Turbo DNase ( Ambion/Applied Biosystems , Austin , TX ) . 1 ug of the DNAse treated total RNA went through polyA selection via the MicroPoly ( A ) Purist Kit according to the manufacturer's recommendations ( Ambion/Applied Biosystems , Austin , TX ) . 1 ng of the mRNA isolated was used as the template for cDNA library construction using the Ovation RNA-Seq version 2 kit according to the manufacturer's recommendations ( NuGEN Technologies , Inc . , San Carlos , CA ) . Non-normalized cDNA was used to construct Multiplexed Illumina paired end small fragment libraries according to the manufacturer's recommendations ( Illumina Inc , San Diego , CA ) , with the following exceptions: 1 ) 500 ng of cDNA was sheared using a Covaris S220 DNA Sonicator ( Covaris , INC . Woburn , MA ) to a size range between 200–400 bp . 2 ) Eight PCR reactions were amplified to enrich for proper adaptor ligated fragments and properly index the libraries . 3 ) The final size selection of the library was achieved by an AMPure paramagnetic bead ( Agencourt , Beckman Coulter Genomics , Beverly , MA ) cleanup targeting 300–500 bp . The concentration of the library was accurately determined through qPCR according to the manufacturer's protocol ( Kapa Biosystems , Inc , Woburn , MA ) to produce cluster counts appropriate for the Illumina platform . The HiSeq2000 Illumina platform was used to generate 100 bp sequences . Analytical processing of the Illumina short-reads was performed using in-house scripts . DUST was used to filter out regions of low compositional complexity and to convert them into N's [31] . An in-house script was used to remove N's , which discards reads without at least 60 bases of non-N sequence . Raw RNA-seq datasets are deposited at SRA ( accession numbers: Control - SRR868958 , IVM - SRR868932 , PER - SRR868957 , PER+ETO - SRS868939 , ETO - SRS868942 . ) . Gene expression for each sample was calculated by mapping the screened RNA-seq reads to the WS230 release of C . elegans using Tophat [32] ( version 1 . 3 . 1 ) , and calculating depth and breadth of coverage per gene using Refcov ( version 0 . 3 , http://gmt . genome . wustl . edu/gmt-refcov ) . Gene expression values were normalized using the depth of coverage per million reads ( DCPM ) per sample [33] . Expressed genes were subject to further differential expression analysis using EdgeR [34] ( false discovery rate <0 . 05 , dispersion value 0 . 01 ) , in order to identify genes differentially expressed in each treatment relative to the control sample . Hierarchical agglomerative clustering ( with “unweighted pair group method with arithmetic mean” , and Pearson correlation coefficient similarity settings in XLSTAT-Pro; version 2012 . 6 . 02 , Addinsoft , Inc . , Brooklyn , NY , USA ) was used to cluster samples based on the gene expression profiles across all genes , and to cluster all 1 , 908 genes upregulated in any of the four comparisons . Interproscan [35] , [36] was used to determine associations of genes to Gene Ontology ( GO ) terms [37] . Interproscan also identified predicted Interpro domains found in each gene . GO term enrichment among genes upregulated in each of the 4 samples was determined using a non-parametric binomial distribution test with a 0 . 05 p value cutoff for significance , after Benjamini-Hochberg false-discovery-rate ( FDR ) population correction for the total number of terms [38] . Only GO terms with at least 5 gene members in the C . elegans genome were included in the analysis ( 501 total ) . Perhexiline was downloaded from the DrugBank website as a mol file , then converted to a PDB file using OpenBabel [39] . The PDB file was optimized using Sybyl 7 . 3 [40] to minimize the Perhexiline structure . In AutoDockTools4 [41] , hydrogen atoms , followed by Gasteiger charges , were added , then the non-polar hydrogen atoms were merged . A docking box of 88×68×80 points in the x , y , and z dimensions , with a spacing of 0 . 375 Å , was used centered at 61 . 752 , 72 . 8001 , 52 . 0321 and all other parameters were default . The carnitine palmitoyltransferase-2 ( CPT-2 ) macromolecule was taken from the crystal structure of 2H4T [42] . Hydrogen atoms were added , followed by Kollman charges . Then , the non-polar hydrogens were merged on the macromolecule . The docking calculations utilized local search Lamarkian genetic algorithm in Autodock4 [41] using rigid side chains . A total of 250 genetic algorithm runs were done . The results were clustered using Autodock4 with the default parameters .
Our approach identifies chokepoint enzymes as targets of existing drugs or as novel drug targets ( Figure 1C ) . The intersection of nematode genomes ( CommNem ) yielded 487 proteins conserved among all nematode species studied , of which 169 are conserved chokepoint enzymes ( Figure 2 & Table S1 in Text S1 ) . The union of the nematode proteomes ( UniNem ) yielded 477 chokepoint enzymes ( Table S2 in Text S1 ) , of which 24 chokepoint enzymes were only found in parasitic worms ( ParaNem ) . The EC numbers and corresponding FASTA sequences for each of the species investigated can be found on Nematode . net [43] . In all cases , 34–35% of the proteome assigned with an EC number consists of chokepoints ( Figure S1 in Text S2 ) . The only chokepoint enzyme present in CommNem and not in H . sapiens is EC: 6 . 2 . 1 . 12 . However , 120 chokepoint enzymes from UniNem are not found in H . sapiens . A high overlap also exists between CommNem chokepoint enzymes and D . melanogaster , with only 5 of 169 in CommNem are not present in D . melanogaster ( EC: 1 . 8 . 4 . 2 , 2 . 4 . 2 . 8 , 5 . 3 . 2 . 1 , 2 . 7 . 1 . 149 , 3 . 6 . 1 . 14 ) . Some enzyme categories were enriched or depleted based on Fisher's Exact statistical test within the species relative to chokepoint enzymes in KEGG ( i . e . KEGGChoke ) , and all enzymes in the KEGG database ( i . e . AllKEGG ) ( Figure S2 in Text S2 ) . This analysis was performed to determine if certain types of enzymes were more likely to have drugs associated with them . This information was fed into the prioritization scheme . Oxidoreductases were significantly enriched in nematodes and KEGG Drug and DrugBank relative to KEGGChoke ( p<0 . 005 ) . The chokepoints within KEGG Drug and DrugBank were significantly enriched in hydrolase enzymes ( p<0 . 005 ) when compared to KEGGChoke ( all chokepoints in KEGG identified using our approach ) as well as AllKEGG ( all enzymes with assigned ECs within KEGG ) . Further , isomerases in DrugBank and KEGG Drug were significantly enriched relative to KEGGChoke . The abundances of enzymes in DrugBank and KEGG Drug significantly differ from KEGGChoke in 3 out of the 6 enzyme categories . There are 75 drugs in KEGG Drug that are classified as anthelmintic . Much research has also been done to design insecticides , therefore it is interesting to see that these insecticides also target chokepoint enzymes . The insecticides are shown in Table S3 in Text S1 , and the DrugBank compounds that are classified as antiparasitic are shown in Table S4 in Text S1 . The nearly complete overlap of CommNem and partial overlap of UniNem chokepoint enzymes with H . sapiens enzymes provide an excellent opportunity to reposition drugs used for other purposes in H . sapiens as anthelmintic drugs . If these drugs show some efficacy , subsequent optimization studies could be performed on these leads to make these drugs bind with higher affinity and specificity to the nematode protein . Out of the 169 chokepoints in CommNem , only 13 have a drug associated with them in KEGG Drug ( Table S5 in Text S1 and Table S6 in Text S1 ) . When considering UniNem , a total of 29 chokepoints have ECs associated with a drug in KEGG Drug ( Table S5 in Text S1 and Table S7 in Text S1 ) . Out of 446 enzymes involved in chokepoint reactions in H . sapiens , only 35 mapped to ECs associated with a drug in KEGG ( data not shown ) . Of the 977 enzymes in the D . melanogaster genome , 330 are chokepoint enzymes and of the 68 of those that mapped to the ECs in the KEGG Drug database 29 are considered chokepoint enzymes . There are 30 drugs in KEGG that have insecticide activity , but none have ECs associated with them . Only 97 enzymes within KEGG Drug have an EC assigned , of which 39 are associated with chokepoint reactions . Therefore , the UniNem , H . sapiens , and D . melanogaster proteins hit roughly 1/3 of targets with ECs assigned within KEGG Drug . DrugBank contains the sequences of targets to which the drugs bind , enabling more complete mapping of ECs to protein targets and subsequently to drug-like compounds . Within DrugBank , there are 4774 compounds , and 1289 targets were assigned EC numbers . DrugBank contains 504 enzymes that are involved in chokepoint reactions based on chokepoints derived from KEGG reactions . Based on the number of compounds , KEGG Drug has more compounds than DrugBank with 9447 compounds . However , DrugBank has many more compounds associated with ECs ( Figure S1 in Text S2 ) . Due to the large list of targets and compounds , the compounds were prioritized ( see Methods ) . Several of the compounds yielded the maximal compound score of 7 . A compound score cutoff of ≥6 was used to prioritize the top drugs that have potential to be repositioned or further optimized as nematode drugs ( Figure 3A , Table 1 ) . The compounds identified are drugs that are used to treat hypertension , angina , and Parkinson's disease , and have immunosuppressive and antimicrobial properties . The chokepoint enzymes were prioritized for the CommNem , UniNem , and ParaNem groups using a simple addition scoring function , with 7 being the maximum possible target score ( see Methods and Materials ) . The results for CommNem and UniNem are shown in Table 2 and ParaNem in Table S8 in Text S1 . The maximum target score obtained in CommNem and UniNem was 5 , and a cutoff of 4 was used . None of the enzymes in ParaNem met the maximum-target score criteria as well , with 5 being the highest target score attained; therefore a cutoff of 2 was used . The seven drug-like compounds prioritized based on our cut-off ( see Methods and Materials ) were experimentally screened in C . elegans ( Table 1 ) , and three yielded a phenotype . C . elegans exposed to drug-like compound 2 yielded a slow moving and twitchy phenotype , whereas 7 yielded a jerky , twitchy phenotype in 75% of the worms and 25% of the worms did not move after exposure to the compound . C . elegans exposed to drug-like compound 1 ( Perhexiline ) yielded a 50% reduction in motility phenotype at 47 . 3 µM ( 18 . 6 ppm ) , also showed slow movement and twitchy behavior at compound concentrations below the EC50 value . Importantly , Perhexiline ( 1 ) caused a 90% reduction in motility ( MIC90 ) at 20 µM in the blood-feeding nematode H . contortus , and 100% reduction in motility in the filarial nematode O . lienalis at 50 µM . Chemical structures of the drug-like compounds are shown in Figure 3A , dose-response curves for Perhexiline ( 1 ) are shown in Figure 3C & D , and videos of the effect of Perhexiline ( 1 ) on C . elegans and H . contortus and Carbidopa ( 2 ) and Azelaic acid ( 7 ) in C . elegans are shown in Supplementary Videos ( Video S1 , S2 , S3 , S4 , S5 , S6 , S7 , S8 ) . Carnitine palmitoyl transferases ( CPT ) are chokepoint enzymes with existing drugs , such as Perhexiline ( 1 ) , inhibiting the mammalian homologs . Two versions of the enzyme ( CPT-1 and CPT-2 ) play important roles in fatty acid metabolism in the mitochondria [44] . Inhibition of CPT leads to a decrease in oxygen consumption rate ( OCR ) in the mitochondria . Perhexiline ( drug-like compound 1 ) treatment in C . elegans led to a significant decrease in basal OCR in a dose-dependent manner ( Figure 5A ) . The effect of Perhexiline ( PER ) was equivalent to that of Etomoxir ( ETO ) , a known inhibitor of the mitochondrial outer membrane associated enzyme , CPT-1 , which acts with CPT-2 to regulate fatty acid oxidation [45] , [46] . The combination of Perhexiline and Etomoxir had an additive inhibitory effect of OCR that was greater than the effects measured with either drug alone ( Figure 5B ) . OCR was also measured in presence of PER , ETO , PER+ETO and compared to OCR in presence of Ivermectin ( IVM ) , a commercially available anthelminic used to treat nematode infections . IVM , which kills C . elegans at therapeutic concentrations through interference with nervous system function , provides a control for drug-induced toxicity that leads to phenotypic alterations such as paralysis that may indirectly affect oxygen consumption as measured by OCR . The dose response curve ( Figure 5C ) enabled identification of the 10 uM concentration as applicable for our comparison experiment ( see Methods ) . While the effect of PER , ETO and the additive inhibitory effect of OCR was confirmed by this experiment , the IVM had no significant inhibitory effect of OCR ( Figure 5D ) . Genome-wide gene expression profiling can be used to investigate if a transcriptional response to drugs carries signatures for drug mechanism of action . Drugs with related mechanisms of action are expected to have similar patterns of molecular functions significantly perturbed . RNAseq-based expression evidence was obtained for all C . elegans genes with 6–11% of the genes being differentially expressed among the four treatments ( Table S9 in Text S1 ) . On average 2–8% of genes were upregulated ( range 1 . 7% PER+ETO to 3 . 9% IVM ) and 5 . 3% were downregulated ( range 3 . 3% PER to 7 . 1% IVM ) . Comparison of genome-wide transcriptional responses to PER , ETO , PER+ETO and IVM showed that the transcriptional responses of C . elegans to PER and ETO are significantly closer than any of the two to IVM , confirmed by them being clustered together and having more enriched functions in common ( Figure 6A; Table S10 in Text S1 ) . The correlation of gene expression ( across the 1 , 908 differentially expressed genes ) between PER and ETO was 0 . 43 , compared to 0 . 09 between PER and IVM ( p<10−10 according to r-to-z Fisher test ) , showing that PER and ETO elicit a highly similar gene expression response to one another compared to the IVM treatment . PER and ETO cluster together since their targets ( CPT-1 and CPT-2 ) act together to regulate fatty acid oxidation . The difference among PER and ETO , among others , was reflected by a small gene expression cluster near the top of the heatmap ( Figure 6A ) , where we observed a group of genes downregulated in PER but upregulated in ETO . GO enrichment analysis on the genes related to this PER-specific downregulation pattern identified several enriched molecular functions ( flavin-containing monooxygenase activity-GO:0004499; flavin adenine dinucleotide binding-GO:0050660; carbohydrate binding-GO:0030246 and NADP binding-GO:0050661 ) and biological processes ( response to heat-GO:0009408; multicellular organismal development-GO:0007275 ) . GO enrichment analysis was performed independently on the upregulated gene sets of each of the four treatments . The number of GO categories enriched in each treatment are shown in Figure 6B , and the specific GO terms in each intersection of Figure 6B can be found in Table S10 in Text S1 . Two terms , one biological process ( response to heat-GO:0009408 ) and one cellular component ( peroxisome-GO:0005777 ) were enriched among genes upregulated in PER , ETO and PER+ETO , showing that both heat-responsive genes ( primarily HSP70 genes ) as well as genes related to peroxisome function were upregulated in all combinations of these treatments . Since CPT-1 is an initiating step in the translocation of long chain fatty acids across the mitochondrial membranes for beta-oxidation [44] , [47] and the peroxisome proliferator activated receptor α ( PPARα ) is a nuclear receptor which stimulates genes involved in mitochondrial fatty acid oxidation and increases expression of those modulating pyruvate oxidation , the observed enrichment of genes related to peroxisome related activity is not surprising . Among the 10 GO terms which were only enriched among the PER+ETO treatment ( but not in individual treatments ) were two biological process terms related to fatty acid processes ( fatty acid beta-oxidation-GO:0006635 and fatty acid metabolic process-GO:0006631 ) , biological functions that are directly related to the function of CPT-1 and CPT-2 . The rat structure of CPT-2 ( PDB ID: 2H4T ) was used for the docking of Perhexiline , since that is the only species with crystal structures available . One major low-energy cluster with a binding energy of −5 . 8 kcal/mol resulted and contained 226 of the 250 genetic algorithm runs . Using Autodock 4 [41] , Perhexiline was docked into the active site of CPT-2 [42] ( Figure 7 ) . The binding site of Perhexiline in CPT-2 does not overlap with the carnitine group in the ST-1326 ( bound CPT-2 inhibitor in PDB ID: 2FW3 ) based on the docking calculations , but overlaps more with the fatty acid chain . The major contacts that Perhexiline makes in its docked configuration include: P133 , F134 , M135 , F370 , H372 , D376 , G377 , V378 , L381 , S590 , G601 , and F602 . H372 is the catalytic residue ( Figure 7C ) . The amine group on Perhexiline makes a hydrogen bond with the backbone carbonyl group on D376 . Residues that differ between mammals and nematode include L335 , S445 , Q447 , V597 , S598 , L599 , A615 , W620 , C623 , N624 ( Figure 7B ) .
In this study , we report chokepoint reactions and enzymes that are common to all 10 studied species of nematodes , as well as chokepoint reactions and enzymes that encompass the union of the 10 nematode species . This study goes further than previous studies to try to understand features of chokepoint enzymes that are successful drugs targets , then uses available diverse information to prioritize the nematode chokepoint enzymes for those that are good drug candidates . Scoring high on the prioritized list are targets that are under investigation for treatment of parasites , indicating that the list contains reasonable targets that should be investigated further . In addition , KEGG Drug and DrugBank were examined for existing drugs that could be repositioned or optimized as anthelmintic drugs . Three of the seven compounds were experimentally tested and show efficacy in C . elegans , and one of these three ( Perhexiline ) shows efficacy in two nematode species with distinct modes of parasitism . A suggested mode of action was also outlined for Perhexiline . Computational modeling results suggest opportunities for higher affinity and specificity using this compound as a starting point . The list of prioritized drug targets and drug compounds has enormous potential for the development of new and urgently-needed anthelmintic drugs and pesticides . | The World Health Organization estimates that 2 . 9 million people are infected with parasitic roundworms , causing high-morbidity and mortality rates , developmental delays in children , and low productivity of affected individuals . The agricultural industry experiences drastic losses in crop and livestock due to parasitic worm infections . Therefore , there is an urgent need to identify new targets and drugs to fight parasitic nematode infection . This study identified metabolic chokepoint compounds that were either produced or consumed by a single reaction and elucidated the chokepoint enzyme that drives the reaction . If the enzyme that catalyzes that reaction is blocked , a toxic build-up of a compound or lack of compound necessary for subsequent reaction will occur , potentially causing adverse effects to the parasite organism . Compounds that target some of the chokepoint enzymes were tested in C . elegans and several compounds showed efficacy . One drug-like compound , Perhexiline , showed efficacy in two different parasitic worms and yielded expected physiological effects , indicating that this drug-like compound may have efficacy on a pan-phylum level through the predicted mode of action . The methodology to find and prioritize metabolic chokepoint targets and prioritize compounds could be applied to other parasites . | [
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] | [
"pesticides",
"medicine",
"infectious",
"diseases",
"veterinary",
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] | 2013 | Discovery of Anthelmintic Drug Targets and Drugs Using Chokepoints in Nematode Metabolic Pathways |
Genes underlying important phenotypic differences between Plasmodium species , the causative agents of malaria , are frequently found in only a subset of species and cluster at dynamically evolving subtelomeric regions of chromosomes . We hypothesized that chromosome-internal regions of Plasmodium genomes harbour additional species subset-specific genes that underlie differences in human pathogenicity , human-to-human transmissibility , and human virulence . We combined sequence similarity searches with synteny block analyses to identify species subset-specific genes in chromosome-internal regions of six published Plasmodium genomes , including Plasmodium falciparum , Plasmodium vivax , Plasmodium knowlesi , Plasmodium yoelii , Plasmodium berghei , and Plasmodium chabaudi . To improve comparative analysis , we first revised incorrectly annotated gene models using homology-based gene finders and examined putative subset-specific genes within syntenic contexts . Confirmed subset-specific genes were then analyzed for their role in biological pathways and examined for molecular functions using publicly available databases . We identified 16 genes that are well conserved in the three primate parasites but not found in rodent parasites , including three key enzymes of the thiamine ( vitamin B1 ) biosynthesis pathway . Thirteen genes were found to be present in both human parasites but absent in the monkey parasite P . knowlesi , including genes specifically upregulated in sporozoites or gametocytes that could be linked to parasite transmission success between humans . Furthermore , we propose 15 chromosome-internal P . falciparum-specific genes as new candidate genes underlying increased human virulence and detected a currently uncharacterized cluster of P . vivax-specific genes on chromosome 6 likely involved in erythrocyte invasion . In conclusion , Plasmodium species harbour many chromosome-internal differences in the form of protein-coding genes , some of which are potentially linked to human disease and thus promising leads for future laboratory research .
Malaria remains a serious health threat . Every year , more than 250 million people worldwide suffer from malaria and over one million people die as a consequence of the disease , mostly children in Africa under the age of five [1] . Malaria is an infectious disease caused by single-celled intracellular eukaryotic parasites of the genus Plasmodium that are transmitted by mosquitoes . Four species , Plasmodium falciparum , Plasmodium vivax , Plasmodium malariae and Plasmodium ovale , are traditionally recognized as human parasites . Other Plasmodium species are important model parasites in malaria research , including the primate malaria model Plasmodium knowlesi , which parasitizes macaque monkeys in the wild , as well as the three rodent malaria parasites Plasmodium berghei , Plasmodium yoelii , and Plasmodium chabaudi , which are natural parasites of thicket rats in central Africa . Plasmodium species that naturally infect humans , monkeys , and rodents differ in their ability to cause human disease . Firstly , laboratory experiments have shown that parasites of thicket rats are infectious to various other species of rodents but not primates [2] , [3] , suggesting that rodent parasites lack essential features required to parasitize primates , including humans . Secondly , the macaque monkey parasite P . knowlesi differs from the four human parasites in that it is not endemic in larger parts of the human population despite its known ability to infect also humans under natural conditions [4] . Recent epidemiological and entomological data suggest that human P . knowlesi malaria is an ancient zoonosis acquired from forest-dwelling macaque monkeys [5] . It is likely that P . knowlesi malaria fails to spread in human settlements and beyond because of the known inability of P . knowlesi to develop in domestic species of Anopheles [6] , [7] . However , concerns have been raised that with increased exposure of humans to P . knowlesi the parasite might eventually become epidemic in humans [4] , [5] . Thirdly , human malaria parasites differ greatly in human virulence . P . falciparum , which accounts for up to 90% of annual infections worldwide [1] , is the most virulent species and is responsible for almost all malarial deaths [8] . P . vivax , the major cause of human malaria outside Africa , rarely kills , although cases of lethal P . vivax malaria have been reported [9] . The more benign nature of P . vivax malaria in humans is commonly attributed to the inability of P . vivax-infected red blood cells to adhere to vascular endothelium and the preference of P . vivax to infect reticulocytes ( immature red blood cells ) , which naturally limits parasitaemia because reticulocytes account for only 1–2% of erythrocytes [10] , [11] . Finally , P . vivax and P . ovale , but not P . falciparum and P . malariae , can stay dormant in the liver as hypnozoites , which can cause relapses months or even years after the primary infection in the blood has been cleared [12] . Relapses are thought to be an evolutionary adaptation of the parasite to ensure transmission in more temperate climate zones where mosquitoes are not available throughout the year [11] . Recent genome sequencing of the two human malaria parasites P . falciparum [13] and P . vivax [14] , the macaque parasite P . knowlesi [15] , and the three rodent parasites P . yoelii [16] , P . berghei [17] , and P . chabaudi [17] provides an opportunity to identify the genetic basis of the aforementioned important phenotypic differences by means of comparative genomics . An important insight that has been gleaned from early comparative genomics analyses of Plasmodium genomes is that genes mediating parasite-host interactions are frequently restricted to a single Plasmodium species ( species-specific ) or restricted to a subset of Plasmodium species ( species subset-specific ) . Perhaps the best studied and clinically most relevant example is P . falciparum erythrocyte membrane protein 1 ( PfEMP1 ) , whose different isoforms are encoded by about 60 members of the P . falciparum-specific var gene family [13] , [18] . PfEMP1 proteins are expressed at the surface of infected red blood cells ( iRBC ) where they mediate adhesion to both uninfected erythrocytes and host endothelial cells . This causes a great deal of the severe clinical pathologies of P . falciparum malaria . PfEMP1 is therefore considered the prime virulence factor of P . falciparum malaria . Other important species- or species subset-specific gene families have been linked to host immune evasion , including the var and rif/stevor gene families in P . falciparum , vir in P . vivax , SICAvar and kir in P . knowlesi , and the cir/bir/yir family in rodent malaria parasites ( reviewed in [19] ) . Erythrocyte invasion is another critical molecular process at the parasite-host interface facilitated by species subset-specific gene family members , including duffy-binding like ( DBL ) and reticulocyte-binding-like ( RBL ) gene family members [14] as well as serine repeat antigens ( SERA ) and merozoite surface proteins ( MSPs ) , some of which are now leading targets in vaccine development ( reviewed in [20] , [21] ) . Comparative genomic studies also have shown that species- or species subset-specific genes in Plasmodium genomes are preferentially located at dynamically evolving subtelomeric regions of chromosomes that are completely devoid of synteny [14] , [16] , [22] , [23] . In contrast , non-subtelomeric or chromosome ‘core’ regions ( referred to as chromosome-internal regions in the following ) were found to be highly syntenic and to contain comparably few gene differences between species . Nevertheless , important species- and subset-specific genes have been described in chromosome-internal regions as well , including members of the aforementioned var , MSP , and SERA gene families in P . falciparum [13] , [16] , [23] as well as MSP and RAD genes in P . vivax [14] , the latter of which has been associated with P . vivax selectivity for young erythrocytes and/or immune evasion [24] . The P . knowlesi genome is particularly rich in chromosome-internal species- and subset-specific genes , which have been identified as surface antigens of the SICAvar and kir gene families , respectively [15] . The fact that parasite genes mediating parasite-host interactions are frequently restricted to a single or a subset of Plasmodium species suggests that the search for species subset-specific genes is a promising strategy to identify new candidate genes underlying host-specific adaptations of Plasmodium species , in particular adaptations to human hosts and anthropophilic mosquito vectors . Identification and characterization of such genes may hold the key for important insights into molecular processes contributing to human disease . For example , parasite-encoded molecular factors that can explain why P . falciparum , P . vivax , and P . knowlesi but not rodent malaria parasites are infectious to humans are currently unknown . The identification of such pathogenicity factors could lead to new strategies to treat malaria in humans . Similarly , genes allowing P . falciparum and P . vivax but not P . knowlesi to complete their life cycle in anthropophilic mosquito vectors have not been identified , although an understanding of the genetic basis of this difference in human transmission success could help to prevent future host switches from monkey to human and pave the way for new transmission blocking strategies . Regarding human virulence it is likely that P . falciparum contains additional virulence genes that await functional characterization . The identification of new virulence genes would enhance our understanding of virulence mechanisms and could lead to new therapeutic interventions to treat severe malaria in humans . Finally , an understanding of the molecular mechanism underlying P . vivax hypnozoite formation is currently entirely missing but urgently needed , because hypnozoites cannot be killed by most available antimalarial drugs and complicate malaria eradication efforts [11] . We hypothesize that chromosome-internal regions of Plasmodium genomes harbour currently unappreciated species differences in the form of protein-coding genes that contribute to human pathogenicity , human-mosquito-human transmissibility , and human virulence . Other than subtelomeric regions , which contain mostly large and readily identifiable species-specific gene families [17] , gene differences in chromosome-internal regions are currently largely unexplored [22] , [23] . The goal of this study was therefore to systematically identify and characterize species subset-specific genes in chromosome-internal regions of Plasmodium genomes . Although not all subset-specific genes are expected to be functional due to stochastic processes of gene birth-and-death , a recent study in Drosophila has shown that a significant fraction of genes that differ between species do have important phenotypic effects [25] . We focused on four specific comparisons . First , to identify genes possibly linked to human pathogenicity , we determined genes well conserved in the genomes of P . falciparum , P . vivax , and P . knowlesi but absent in rodent malaria parasites , P . chabaudi , P . berghei , and P . yoelii . Second , we identified genes possibly crucial for parasite transmission success between humans by looking for genes present in P . vivax and P . falciparum but absent in the macaque monkey parasite P . knowlesi . Third , we identified genes that possibly contribute to severe human malaria by looking for P . falciparum-specific genes comparing P . falciparum with its less virulent relative P . vivax . Finally , we identified genes that potentially define unique features of P . vivax malaria by looking for genes present in P . vivax but absent in other sequenced Plasmodium genomes . Each of these comparisons resulted in the identification of several species subset-specific genes , most of which with unknown function . We propose these genes as attractive starting points for follow-up experimental analyses to test predicted phenotypic associations and to further elucidate their functions .
Six published Plasmodium genomes sequenced to high coverage ( ranging from 4 to 14 . 5-fold coverage ) were selected for comparison , including the two clinically most important human parasites ( P . falciparum and P . vivax ) , one monkey parasite ( P . knowlesi ) , and three rodent parasites ( P . chabaudi , P . berghei , and P . yoelii ) ( Figure S1 ) . Preliminary examination of P . vivax and P . knowlesi gene models ( Text S1 ) indicated that many gene models in these two genomes are apparently missing or mispredicted . To facilitate comparative analysis , we therefore started our analysis by improving current P . vivax and P . knowlesi gene models with homology-based gene prediction programs , using validated P . falciparum gene models as queries ( see Materials and Methods ) . In total , we identified 53 and 19 new protein-coding genes and revised 165 and 116 existing gene models in P . vivax and P . knowlesi , respectively , including 31 split or merged genes ( Table S1 and Table S2 ) . Figure S2 shows four typical examples of improved gene models , including a novel gene , a split gene that was merged , a merged gene that was split , and an elongated gene model . Comparative analyses of the complete proteomes of P . falciparum , P . yoelii , P . berghei and P . chabaudi , and the improved proteomes of P . vivax and P . knowlesi using BLASTP and genBlastG ( see Materials and Methods ) identified 30 proteins well conserved in the three primate parasites ( percent identity ( PID ) of global protein sequence alignment ≥40 ) that are putatively absent in all three rodent parasites ( global PID≤15 ) ( Figure 1 ) . Examination of their identifiable syntenic genomic regions provided additional support for the absence of 16 of these putatively absent genes , i . e . no orthologous genes were found at the corresponding genomic positions in the rodent parasite genomes . Table 1 shows P . falciparum orthologs of these 16 putative primate parasite-specific genes together with their degree of conservation in P . vivax , functional annotations , and expression profiles ( see Table S9 for a list of the same genes but including graphical expression profiles ) . Among them are three key metabolic enzymes of the thiamine ( vitamin B1 ) biosynthesis pathway: PFL1920c ( hydroxyethylthiazole kinase , EC 2 . 7 . 1 . 50 ) , PFE1030c ( hydroxylmethylpyrimidine kinase , EC 2 . 7 . 1 . 49 ) , and PFF0680c ( thiamine-phosphate diphosphorylase , EC 2 . 5 . 1 . 3 ) . Together , these three genes catalyze essential steps in the de novo synthesis of vitamin B1 ( Figure 2 ) . With one exception in P . yoelii , which appears to be a gene relic that should be annotated as a pseudogene , orthologs of all three P . falciparum genes are absent from three independent syntenic positions in all three sequenced rodent pathogen genomes ( Figure 3 ) . This data strongly suggests that primate but not rodent malaria parasites are capable of synthesizing vitamin B1 de novo . Besides the three thiamine biosynthesis enzymes , Table 1 reveals additional enzyme-coding genes conserved in primate but absent in rodent malaria parasites . This includes an acid phosphatase ( PF14_0036 ) involved in riboflavin ( vitamin B2 ) metabolism [26] , [27] , a highly conserved putative IMP-specific 5′-nucleotidase ( PFL0305c ) that is involved in purine metabolism , an apicoplast phosphatidic acid phosphatase ( MAL8P1 . 202 ) catalyzing the production of diacylglycerol as part of the dolichol metabolism [26] , as well as two enzymes previously described as absent in rodent malaria parasites , including phosphoethanolamine N-methyltransferase ( MAL13P1 . 214 ) that plays a role in phospholipid metabolism [28] , and Jumonji domain containing protein ( MAL8P1 . 111 ) serving as one of two functionally distinct P . falciparum histone lysine demethylases [29] . Other functionally annotated proteins conserved in primate malaria parasites but absent in rodent malaria parasites include a putative nucleoside transporter ( PF14_0662 ) , a putative acyl-CoA N-acyltransferase ( PFI1220w ) specifically upregulated in gametocytes and sporozoites [30] , and a putative Ca++ chelating serine protease ( MAL7P1 . 339 ) . Taken together , the three primate parasites infectious to humans maintain a limited but conserved subset of genes that is absent in rodent malaria parasites , pointing towards new candidate pathogenicity genes required for parasitizing primate hosts , including humans . Further comparisons of the genomes of the three primate parasites P . falciparum , P . vivax , and P . knowlesi were performed using whole-genome synteny analysis . Synteny blocks were detected with OrthoCluster [31] based on our improved gene sets and orthology relationships predicted by Inparanoid ( see Materials and Methods ) . Because our goal was to identify parasite-specific genes in syntenic chromosome-internal regions , we focused on the detection of imperfect synteny blocks ( i . e . synteny blocks allowing for minor interruptions ) and non-nested synteny blocks ( i . e . synteny blocks not contained within larger synteny blocks due to one-to-many orthologous relationships ) [32] . Note that in the context of pairwise synteny analysis we refer to genes without predicted ortholog in the other species as parasite-specific and not species-specific , because some of these genes might have predicted orthologs in other species . Between the two human parasites P . falciparum and P . vivax ( Figure 4 and Table S3 ) , we identified 28 non-nested imperfect synteny blocks with a median size of 144 . 5 genes ( 563 . 7 kb ) that collectively cover 90% of protein-coding genes or 85% of the nuclear genome sequence . Between P . vivax and P . knowlesi ( Figure 5 and Table S3 ) , OrthoCluster identified 16 non-nested imperfect synteny blocks of median size 300 genes or 1 , 376 kb ( average of both genomes ) , each of them essentially spanning complete chromosomes with two exceptions on P . vivax chromosomes 3 and 4 ( Text S1 ) . OrthoCluster output files listing all detected synteny blocks and their genes are provided in Dataset S2 and Dataset S3 . A more detailed discussion of synteny block analysis results can be found in the Supporting Information ( Text S1 ) . To better characterize parasite-specific genes revealed by synteny block analysis , we define three different types of non-syntenic regions ( inset Figure 4 and Figure S3 ) . A subtelomeric region ( STR ) is defined as the genomic region from the most distal gene on a chromosome arm to the first syntenic gene that is part of an imperfect synteny block ( there are two such STRs on each chromosome ) . A synteny breakpoint region ( SBR ) is defined as a genomic region between imperfect synteny blocks . A synteny gap region ( SGR ) is defined as the genomic region that interrupts perfect synteny within imperfect synteny blocks due to the presence of one or more consecutive non-syntenic genes ( defined here either as parasite-specific genes that do not have a predicted ortholog in the compared species or as genes that do have a predicted ortholog in the compared species but not syntenic ) . Detected imperfect synteny blocks allowed us to examine chromosome-internal parasite-specific genes within their syntenic contexts ( Text S1 ) . In total , syntenic examination confirmed 117 of 388 ( 30% ) P . falciparum-specific genes and 173 of 388 ( 45% ) P . vivax-specific genes in chromosome-internal regions between P . falciparum and P . vivax ( Figure 6 ) . Between P . vivax and P . knowlesi , 139 of 281 ( 49% ) P . vivax-specific genes and 222 of 364 ( 61% ) P . knowlesi-specific genes were confirmed ( Figure 7 ) . Thus , depending on the comparison , SGRs and SBRs were found to contain 16–58% of the total number of parasite-specific genes in each species ( Text S1 and Table S6 ) , representing a considerable amount of the total parasite-specific gene content in each species . The gene content of these SGRs and SBRs is discussed in the following sections . Although P . vivax and P . knowlesi are phylogenetically much more closely related to each other than P . vivax is to P . falciparum ( Figure S1 and [33] ) , we identified 13 genes that are syntenic orthologs between P . vivax and P . falciparum but absent from syntenic regions in P . knowlesi ( Figure 7 , red slice ) . Indeed , orthologs of those genes were not found anywhere in the P . knowlesi genome , even after screening P . knowlesi genomic sequences with genBlastG to account for unannotated genes ( see Materials and Methods ) . Table 2 shows P . falciparum orthologs of these 13 genes together with their degree of conservation in P . vivax and gene expression data ( see Table S10 for a list of the same genes but including graphical expression profiles ) . Three genes ( PFA0380w , PF14_0236 , and PF10_0185 ) show no or only weak expression in the intraerythrocytic developmental cycle ( IDC ) and were found to be specifically upregulated in gametocytes or sporozoites [30] , which is consistent with the possibility that they may play a role in parasite development within the mosquito host and hence transmission success between humans . One of these three genes ( PFA0380w ) is annotated as putative serine/threonine kinase . NCBI BLASTP search with this gene revealed that it is much closer related to its P . vivax ortholog ( PVX_081395; E = 9e-66; PID = 54% ) than to any P . falciparum paralog ( best hit PF13_0258 ( TKL3 ) ; E = 0 . 008; PID = 48% ) , suggesting that the presence of this gene is of functional importance . Four genes in Table 2 ( MAL13P1 . 107 , MAL8P1 . 126 , PF14_0236 , and PFL0360c ) lack orthologs also in rodent malaria parasites and are thus potentially unique to human malaria parasites . Three of these genes show only weak expression in the intraerythrocytic developmental cycle ( IDC ) and two protein products were detected in sporozoites , again pointing towards a possible role of these genes in parasite development within the mosquito host . MAL13P1 . 107 shows sequence similarity ( BLASTP PID 30 , E = 2e-33 ) with the neighboring gene rhoptry protein 2 [34] , suggesting a function during host cell invasion . MAL8P1 . 126 is annotated as Deg2 chloroplast peptidases and is the sole P . falciparum member of clan PA [26] . NCBI BLASTP and TBLASTN searches revealed that MAL8P1 . 126 is conserved in other Apicomplexa species but not non-human malaria parasites , suggesting functional gene loss in non-human malaria parasites . It should be emphasized that a syntenic gene of MAL8P1 . 126 annotated as DegP-like serine protease 1 precursor is present in P . knowlesi ( PKH_011050 ) but much shorter ( 409 aa ) with very low sequence similarity to MAL8P1 . 126 ( global PID 8; BLASTP e = 6e-7 ) . Thus PKH_011050 is probably a non-functional pseudogene . The remaining two putative human malaria parasite-specific genes ( PF14_0236 and PFL0360c ) have no annotated function . Both contain a predicted zinc finger domain and PF14_0236 is predicted to be involved in antigenic variation [35] and PFL0360c shows similarity to a serine protease [36] . We found indications that P . knowlesi could lack a functional copy of telomeric repeat binding factor 1 ( TRF1 ) . Running GeneWise with TRF1 of P . falciparum ( PFI1216w ) against the syntenic region in P . knowlesi reveals only residual protein sequence similarity ( 24% global PID ) , which is well below the degree of conservation found with P . vivax ( 52% PID ) and probably indicative of recent gene inactivation in P . knowlesi . Both BLASTP and TBLASTN searches using PFI1216w as query against the complete P . knowlesi genome revealed the syntenic region of PFI1216w as best hit . Although almost certainly not linked to parasite transmission success , the potential absence of a fully functional copy of TRF1 in P . knowlesi is interesting , because it could offer an explanation for the presence of hundreds of variant surface antigens and telomeric repeats in chromosome-internal regions of the P . knowlesi genome ( see Discussion ) . Functions of the remaining genes shared by P . falciparum and P . vivax but absent in P . knowlesi ( Table 2 ) remain largely unknown . Notably , the 13 identified genes are statistically significantly enriched ( p = 0 . 0159 ) for genes whose expression is induced during the trophozoite stage ( 20 h post infection ) and peaks during the schizont stage ( 36 h post infection ) . It remains to be determined if these genes are therefore also functionally related . Looking at parasite-specific genes identified between the highly virulent parasite P . falciparum and the less virulent human parasite P . vivax , our analysis recovers many known human virulence genes in P . falciparum ( Figure 6 , bottom left ) . The largest fraction ( 26 genes , 22% ) of the 117 chromosome-internal P . falciparum-specific genes is annotated as chromosome-internal members of the var gene family , the prime virulence factors of P . falciparum [18] . GO term enrichment analysis with Ontologizer [37] reveals that the 117 P . falciparum-specific genes are statistically significantly enriched for GO biological processes pathogenesis ( GO:0009405; FDR-adjusted p-value = 9e-5 ) and adhesion to host ( GO:0044406; p = 0 . 02 ) , mostly because of the presence of these 26 var genes ( Table S7 ) . The two second largest subgroups of P . falciparum-specific genes are also involved in important pathogenic processes , including nine MSPs and 13 members of the rif/stevor gene family . Enriched GO terms associated with these genes include cell adhesion ( GO:0007155; p = 2e-25 ) and defense response ( GO:0006952; p = 3e-6 ) . More generally , we find P . falciparum-specific genes enriched for GO subcellular locations membrane ( GO:0016020; p = 4e-10 ) and host intracellular part ( GO:0033646; p = 8e-4 ) , indicating enrichment for proteins functional at the parasite-host interface . To identify novel candidate genes potentially linked to severe P . falciparum malaria , we removed known virulence genes and retained genes that contain features commonly associated with human virulence genes , including PEXEL motifs , signal peptides , or transmembrane domains . In addition , we retained P . falciparum-specific genes predicted to have virulence-associated functions based on gene co-expression or protein interaction data with known virulence genes ( ‘guilt-by-association’ principle ) [35] , [38] . Among the resulting 15 genes ( Table 3 and Table S11 ) we found two genes with annotated functions , including a putative apyrase ( PF14_0297 ) and a putative sugar transporter ( PFE1455w ) ( see Discussion ) . The remaining 13 genes are of unknown function . Four genes have predicted human virulence-associated functions based on gene co-expression or protein interaction data [35] , [38] , including evasion of host defense ( PF07_0107 ) , antigenic variation ( PFA0360c ) , biological adhesion ( PF10_0350 ) , and immune response ( PF10_0044 ) . PlasmoDB annotates another two genes with GO terms cell adhesion ( PF13_0071 ) and immune response ( MAL8P1 . 97 ) , respectively . Eleven genes carry a predicted signal peptide or transmembrane domain and thus potentially function at the parasite-host interface . One of them ( PF07_0107 ) carries an additional PEXEL motif and is thus a predicted erythrocyte surface or exported protein . Looking at RNA-seq expression data for genes with unknown function , all but two genes ( MAL8P1 . 97 and PF10_0044 ) have associated expression evidence during the intraerythrocytic developmental cycle ( IDC ) . Two genes ( PF07_0107 and PF13_0194 ) are constitutively expressed at high levels , one gene peaks at the trophozoite stage ( PF10_0350 ) , seven genes peak at the late trophozoite/early schizont stage , and one gene ( PFF0335c ) peaks during schizont development . Two genes ( PF10_0357 and PF10_0342 ) appear maximally expressed during the schizont-ring stage transition and co-localize with the MSP3 gene cluster on P . falciparum chromosome 10 , suggesting a function in erythrocyte invasion . Of the 173 identified P . vivax-specific genes compared to P . falciparum ( Figure 6 , bottom right ) , the largest group of genes with named gene products contains members of the previously mentioned RAD gene family ( 39 genes , 23% ) , followed by MSP3 genes ( 12 , 7% ) , and MSP7 genes ( 3 , 2% ) . Among genes with unannotated function ( 102 genes , 59% ) , we identified an interesting and currently uncharacterized P . vivax gene cluster of hypothetical proteins likely involved in erythrocyte invasion ( Figure 8 ) . This gene cluster is found on P . vivax chromosome 6 ( position 815 , 000 to 842 , 000 ) and contains eight single-exon genes located on the same strand . The syntenic genomic region in P . falciparum maps to the MSP3 gene cluster on chromosome 10 ( position 1 , 390 , 000 to 1 , 444 , 000 ) , which harbors 13 P . falciparum-specific single-exon genes also located on the same strand . The P . falciparum gene cluster consists of several known antigens and genes involved in erythrocyte invasion , including six members of the MSP3 gene family ( including MSP6 ) , the glutamate-rich protein ( GLURP ) as well as the S-antigen ( PF10_0343 ) and liver stage antigen 1 ( PF10_0356 ) . All but one of these genes ( PF10_0343 ) have no predicted ortholog in P . vivax . It is possible that the P . vivax genes in the syntenic gene cluster on chromosome 6 have a similar function as the P . falciparum-specific genes on chromosome 10 , which makes them prime candidate genes involved in erythrocyte invasion and interesting targets for further functional characterization . Three other lines of evidence support this conclusion . First , for all but one ( PVX_110955 ) of these eight P . vivax genes , top P . falciparum BLASTP hits fall into the syntenic P . falciparum gene cluster ( E-value≤0 . 05; PID≥28% ) . Second , all eight P . vivax genes carry a predicted signal peptide and are thus likely exported proteins . Third , four P . vivax genes ( PVX_110945 , PVX_088845 , PVX_099900 , and PVX_089440 ) peak in expression during the schizont-ring stage transition , which is typical for invasion-related proteins [24] . We identified only few chromosome-internal P . vivax-specific genes absent in both P . falciparum and P . knowlesi that could explain unique biological features of P . vivax malaria , in particular the formation of hypnozoites . After excluding questionable open reading frames , only six candidate genes remained ( see Materials and Methods ) . One gene ( PVX_099470 ) has an annotated function and is one of 25 WD domain , G-beta repeat domain containing proteins in P . vivax , all of which occur chromosome-internally . WD-repeat proteins are a large family of proteins found in all eukaryotes and are implicated in a variety of functions , ranging from signal transduction and transcription regulation to cell cycle control and apoptosis . Using PVX_099470 as query , GeneWise predicts a severely truncated syntenic pseudogene in P . knowlesi with high identity ( 56% PID ) , suggesting recent gene inactivation in P . knowlesi . The other five genes have unknown functions . Four genes ( PVX_089770 , PVX_097730 , PVX_110945 , and PVX_082710 ) localize to chromosome-internal RAD , MSP3 ( chromosome 10 ) , MSP3 ( chromosome 6 , putative ) , and MSP7 gene clusters , respectively , and are thus possibly functionally related to these gene families . The remaining gene ( PVX_003710 ) is a 154 aa single-exon gene with EST expression evidence but of unknown function .
In this study , we compared the genomes of six Plasmodium species and proposed several chromosome-internal genes as new candidate genes underlying medically important phenotypic differences , including human pathogenicity , human-mosquito-human transmissibility , and human virulence . Previous studies have shown that important molecular processes at the parasite-host interface , including cytoadherence [13] , [18] , immune evasion [19] , and erythrocyte invasion [20] , are typically mediated by species- or species subset-specific genes and that these genes cluster at subtelomeric regions of chromosomes . We hypothesized that human parasites harbor additional human virulence- and pathogenicity genes in chromosome-internal regions . Although we expect parasite virulence and pathogenicity to be primarily the result of gene gain or retention , another possibility not further explored here is that some virulence and pathogenicity is the consequence of adaptive gene loss , as observed in bacteria [39] . We identified 16 genes that are well conserved in the three primate parasites causing human disease but are not found in rodent parasites . Some of these genes could be determinants of primate ( and thus human ) pathogenicity ( Table 1 ) . Most of these 16 genes ( 9 genes ) have predicted OrthoMCL DB orthologs in other Alveolate species ( Table 1 ) , suggesting that gene loss in rodent malaria parasites caused these species differences . Multiple lines of evidence suggest that these 16 genes are indeed absent in rodent malaria parasite genomes . First , none of these genes has a predicted Inparanoid or OrthoMCL DB ortholog ( neither syntenic nor non-syntenic ) in any of the three closely related rodent malaria parasite genomes . Second , screening complete genomic sequences ( including the nearly complete chromosome-level assemblies of P . chabaudi and P . berghei available at PlasmoDB 7 . 1 ) with genBlastG did not identify these genes in any of the three rodent malaria parasite genomes . If these genes were present in rodent malaria genomes but mis- or unannotated , then we would expect genBlastG to find them , because all 16 P . falciparum genes are well conserved in P . vivax and P . knowlesi , which have a similar phylogenetic distance to P . falciparum as the three rodent parasites . Finally , syntenic genomic regions as determined by flanking orthologs are present in latest chromosome-level assemblies of P . berghei and P . chabaudi and are assembled without gaps , making it less likely that these genes are absent in rodent parasite genomes due to incomplete genome sequences or assemblies . In some cases as shown in Figure 3 , we even find evidence of residual sequence similarity in syntenic regions , which is best explained by ( recent ) gene loss in rodent malaria parasites . Thus our bioinformatics analysis strongly suggests that these 16 genes are not present in rodent malaria parasite genomes , but ultimate proof will require experimental studies . Among the 16 putative primate parasite-specific genes were several metabolic enzymes , including three key enzymes of the thiamine ( vitamin B1 ) biosynthesis pathway . This pathway has been proposed as attractive antimalarial drug target because of its absence in human hosts [40] , [41] . Our analysis suggests that primate but not rodent malaria parasites synthesize thiamine de novo and that rodent malaria parasites depend entirely on thiamine uptake from vertebrate and invertebrate hosts . Indeed , studies have shown that rodent malaria parasites have greatly impaired eryrthrocytic multiplication rates if thiamine is deliberately eliminated from the host [6] . Why particularly primate parasites engage in thiamine biosynthesis is an interesting question . One possibility is that , in primate hosts , thiamine salvage provides the parasite with only insufficient amounts of this essential coenzyme . A more speculative alternative is that thiamine production of the parasite provides the host with this essential enzyme during times when it is only insufficiently available in the host's diet . Interestingly , for all three P . falciparum thiamine enzymes , top BLASTP hits outside Plasmodium are found in bacteria , including Clostridium spp . as top hits in two of three cases ( data not shown ) . In Clostridium ljungdahlii , the three enzymes are located next to each other on the same strand and thus form a potential operon ( Figure S5 ) , compatible with the possibility that in the common ancestor of Plasmodium parasites thiamine biosynthesis was horizontally acquired from bacteria ( probably from the mitochondrial or apicoplast genome ) and subsequently lost in the common ancestor of rodent malaria parasites . Gene loss in rodent malaria parasites ( vs . gene gain in primate malaria parasites ) as the likely cause for this species-specific difference is supported by residual sequence similarity found in syntenic genomic regions of rodent parasite genomes ( Figure 3C ) . Comparing the two human parasites P . falciparum and P . vivax with the monkey parasite P . knowlesi , we identified 13 P . vivax genes that have a syntenic ortholog in P . falciparum but no predicted ortholog ( neither syntenic nor non-syntenic ) in P . knowlesi . The presence of such genes was unexpected because phylogenetically P . vivax is much more closely related to P . knowlesi than to P . falciparum ( Figure S1 and [33] ) . Unlike P . falciparum and P . vivax , P . knowlesi malaria in humans is not endemic in larger parts of the human population and is geographically restricted to forested areas in Malaysian Borneo and peninsular Malaysia [4] , [42] . This is most likely due to P . knowlesi's known inability to develop in Anopheles species that preferentially feed on humans [6] . We therefore hypothesize that these 13 genes shared by P . falciparum and P . vivax but absent in P . knowlesi may include genes that permit the entry and survival of parasites in anthropophilic human vectors . Consistent with this possibility , three of the 13 genes ( PF14_0236 , PFA0380w , and PF10_0185 ) show only weak expression during the IDC and are specifically up-regulated in sporozoites or gametocytes . Notably , four of the identified 13 genes lack orthologs also in rodent malaria parasites and thus could mediate functions specifically required to parasitize humans . The remaining nine genes have predicted orthologs in rodent malaria parasites and thus likely represent cases of gene loss in P . knowlesi . Further experimental characterization of these 13 genes is required to confirm a potential role in human transmission success . Eventually , these studies may lead to the development of new transmission blocking strategies or to new ideas how future host switches from monkey to human can be prevented . If the ambitious goal of malaria eradication is to be taken seriously [43] , a better understanding of molecular factors contributing to the parasite's ability to complete its life cycle in anthropophilic insect vectors is indispensable . Comparing the highly virulent human parasite P . falciparum with the less virulent human parasite P . vivax , we identified 117 chromosome-internal P . falciparum-specific genes , many of which have known virulence-associated functions ( Figure 6 ) . Subtracting genes with known virulence-associated functions , we identified a subset of 15 genes that we proposed as novel candidate genes potentially linked to severe human malaria ( Table 3 ) . Because most of these 15 genes are of unknown function and lack also identifiable orthologs in other species [44] , experimental analysis in P . falciparum will be required to elucidate their function and to confirm an association with human virulence . The two genes with annotated functions warrant further discussion . The first gene ( PF14_0297 ) is annotated as apyrase , which is a membrane-bound enzyme converting ATP to AMP . Apyrases are involved in purine metabolism [26] and , in mosquitoes , are expressed in salivary glands to inhibit blood clotting [45] . The presence of apyrase in P . falciparum but not in any other Plasmodium parasite ( best NCBI BLASTP hit was found in the human apicomplexan parasite Toxoplasma gondii ) points towards an increased requirement of this enzymatic function in P . falciparum . Apyrase has been proposed as possible target for antimicrobial therapies [46] , but our finding suggests that its use as antimalarial drug target would be limited to P . falciparum malaria . The second gene with annotated function ( PFE1455w ) is a putative Na+- or H+-driven sugar symporter of the GPH family [47] and one of currently six genes annotated with sugar transmembrane transporter activity in P . falciparum ( GeneDB; GO:0051119 ) . NCBI BLASTP and TBLASTN searches reveal homologs of PFE1455w in T . gondii ( TGME49_026020 ) and Neospora caninum ( NCLIV_046810 ) but not in any other Plasmodium species . Host-derived sugars are an essential nutrient of malaria parasites for intraerythrocytic development [48] . In the absence of gluconeogenesis in malaria parasites [13] additional sugar transporters in the membrane of infected erythrocytes likely allow for more efficient glucose uptake from the blood and thus for faster parasite growth , which can be seen as an adaption towards increased virulence of P . falciparum . Several biological features distinguish P . vivax from other sequenced Plasmodium species , including preference for reticulocytes and its ability to develop dormant hypnozoite forms in the liver that can cause relapses months or even years after primary infection . We hypothesized that genes present in P . vivax but absent in the other sequenced Plasmodium species are candidate genes underlying reticulocyte invasion and hypnozoite formation . We identified a currently uncharacterized chromosome-internal gene cluster on P . vivax chromosome 6 containing several P . vivax-specific genes putatively involved in erythrocyte invasion ( Figure 8 ) . Based on synteny , this gene cluster likely encodes for MSPs , including the currently missing P . vivax ortholog of P . falciparum MSP6 [14] . We expect that further characterization of this gene cluster will result in new insights into P . vivax-specific adaptations of erythrocyte invasion . Experimental analyses will be required to test this bioinformatics prediction . In contrast , our search for P . vivax-specific genes potentially linked to hypnozoite formation was largely unsuccessful , suggesting that hypnozoite formation has its roots in regulatory differences and is not primarily associated with protein-coding genes that are unique to P . vivax . One peculiarity of the P . knowlesi genome is that it has hundreds surface antigens spread all over its genome [15] , which we noticed also in our analysis ( Figure 7 , lower right ) . How P . knowlesi mobilized its once subtelomeric surface antigens and inserted them into chromosome-internal regions is an intriguing question , especially because this must have happened rather recently after the divergence from the common ancestor with P . vivax and because transposable elements that could have mediated rapid gene dispersal have not been identified in Plasmodium genomes [13] . Our finding that P . knowlesi might lack a fully functional copy of TRF1 could provide a possible explanation for this phenomenon . In mammalian cells , telomeric repeat binding factors play a pivotal role in protection and maintenance of telomeres [49] . Partial or complete loss of function of telomere repeat binding factor 1 in P . knowlesi could cause telomere instability , resulting in frequent DNA breakage events near telomeres whose subsequent repair causes broken subtelomeric fragments to be randomly inserted into the P . knowlesi genome . Such a mechanism would also explain why P . knowlesi harbors telomeric repeat sequences in chromosome-internal regions [15] . Further experimental work can now test this hypothesis and , if confirmed , investigate the important question if the loss-of-function allele of PFI1216w is a fixed wild type allele in the P . knowlesi population or a recently introduced mutation , perhaps only present in the sequenced laboratory strain of P . knowlesi .
Published chromosome-level assemblies for P . falciparum , P . vivax , and P . knowlesi were downloaded from PlasmoDB version 7 . 0 [36] ( http://plasmodb . org ) . P . chabaudi and P . berghei chromosome-level assemblies were available but unpublished . Therefore , older contig-level assemblies available at PlasmoDB ( version 5 . 5 ) were used for genome-wide comparisons . The P . yoelii contig-level assembly was also downloaded from PlasmoDB 5 . 5 . Annotated gene models ( GFF3 format ) were downloaded from PlasmoDB 7 . 0 ( P . falciparum , P . vivax , and P . knowlesi ) and PlasmoDB 5 . 5 ( P . yoelii , P . chabaudi , and P . berghei ) . If a gene had multiple isoforms , only longest isoforms ( = longest protein sequence ) were kept . Missing or incorrectly annotated gene models cause overestimates of genetic differences and , important for this study , false specific-specific genes . We therefore repaired the more obvious defects in P . vivax and P . knowlesi gene model annotations before genome comparisons . Using two homology-based gene predictors , including our own program genBlastG [50] and the widely used and well established program GeneWise [51] , an automated pipeline for genome-wide gene model improvement was implemented . Briefly , protein sequences of all protein-coding P . falciparum genes ( 5 , 317 genes , excluding pseudogenes and shorter isoforms ) were used as query to run both genBlastG and GeneWise against P . vivax and P . knowlesi genomes . To ensure the quality of predicted gene models , only predictions that encoded for protein sequences with high global sequence identity ( PID> = 60 ) with the query gene were kept . If multiple predictions overlapped by more than 5% of their coding exons , only the prediction with the highest PID was kept ( filtration step ) . We use global PID as a measure of sequence conservation because it better captures global similarity between two proteins as compared to for example the BLAST E-value , which measures local sequence similarity and is more prone to various biases , including sequence composition . In a subsequent merging step , predicted and existing gene models were merged into a hybrid gene set , retaining predictions that ( a ) did not overlap with existing gene models or ( b ) showed a PID improvement of at least 5% over overlapping existing gene models . As in the filtration step , existing and predicted gene modes were considered as overlapping if more than 5% of their coding exons overlapped . The hybrid gene set served as basis for all subsequent comparisons . A summary of improved gene models , including novel functional annotations predicted with InterProScan [52] , can be found in Table S1 ( P . vivax ) and Table S2 ( P . knowlesi ) . Novel and improved gene models for both P . vivax and P . knowlesi are provided in Dataset S1 ( GFF3 format ) . Because chromosome-level assemblies for rodent malaria parasites that became available with PlasmoDB 7 . 0 have not yet been published , we used older , contig-level assemblies ( PlasmoDB version 5 . 5 ) and a synteny-independent , BLAST-based approach for the initial genome-wide screening for species subset-specific genes . Briefly , complete proteomes of P . falciparum ( 5 , 317 proteins ) , P . vivax ( 5 , 156 ) , P . knowlesi ( 5 , 143 ) , and P . yoelii ( 7 , 802 ) were used as query to run both NCBI BLASTP ( version 2 . 2 . 21 ) [53] and genBlastG ( version 1 . 28 ) [50] against the other five proteomes and genomes , respectively ( including P . berghei and P . chabaudi ) . Top hits of both BLASTP and genBlastG were used to compute global PIDs with the query protein using ClustalW ( version 1 . 83; BLOSUM62; default parameters ) [54] . If the best BLASTP hit was different from the predicted Inparanoid ortholog then the global PID was also computed between query and Inparanoid ortholog . A query protein was considered as conserved in another genome if the maximum of these three PIDs was ≥40 and as absent if the maximum PID was ≤15 . In particular , P . falciparum genes were considered primate parasite-specific if conserved in P . vivax and P . knowlesi but not in P . berghei , P . chabaudi , and P . yoelii . The rather conservative margin between high and low PID ( 25 percent points ) was chosen to exclude insignificant PID differences due to fluctuating protein sequence conservation levels or imperfect gene models . Summarized results of this first initial screening are shown in Figure 1 . The complete gene list is provided in Table S8 . In a second step , P . falciparum orthologs of the 30 putative primate parasite-specific genes were inspected using the newer chromosome-level assemblies of P . chabaudi and P . berghei available at PlasmoDB 7 . 1 . We only kept P . falciparum genes for which ( a ) genBlastG failed to annotate a gene with a minimum global PID of 15 in the entire genome and ( b ) no gene was present at the expected syntenic region as defined by the position of flanking syntenic orthologs . Sixteen out of the initial 30 genes fulfilled these two criteria and are shown in Table 1 . The two-step process of first screening for putative primate parasite-specific genes against PlasmoDB 5 . 5 versions of rodent malaria parasite genomes and gene models then verifying the absence of candidate genes in PlasmoDB 7 . 1 was chosen because , in agreement with pre-publication data use policies , we restricted all genome-scale comparisons to officially published Plasmodium genomes . Furthermore , we made no efforts to improve rodent parasite gene models based on the now obsolete PlasmoDB 5 . 5 genome assemblies , because greatly improved P . chabaudi and P . berghei gene models became available with PlasmoDB 7 . 0 . It should be emphasized , however , that using the older PlasmoDB 5 . 5 rodent parasite genome sequences and gene models in the initial screening step did not affect our final results , because all final candidate genes in Table 1 have been verified to be also absent in PlasmoDB 7 . 1 . We used OrthoCluster [31] ( executable from Dec 17 , 2007 , downloaded from http://genome . sfu . ca/cgi-bin/orthoclusterdb/download ) , a program recently developed in our lab , for the gene-based identification of synteny blocks . As input OrthoCluster was provided with genome coordinates of protein-coding genes as well as with gene orthology relationships predicted by Inparanoid ( version 4 ) [55] . Synteny blocks ( both perfect and imperfect ) were required to have at least two pairs of orthologous genes , irrespective of genomic distance but constrained by the amount of allowed intervening genes . For perfect synteny blocks , we did not allow for any interruptions . For imperfect synteny blocks , we allowed for ≤40% out-map mismatches ( i . e . genes without predicted orthologs in the other genome ) and ≤10% in-map mismatches ( i . e . genes with , but non-syntenic orthologs in the other genome ) . These two thresholds were chosen after observing that further increasing the percentages did not result in larger imperfect synteny blocks ( Figure S4 ) . OrthoCluster was further run with the -rs parameter , which instructs OrthoCluster to report all genes not perfectly preserved in order and strandedness as mismatches . This allowed us to localize all genes for which synteny was not perfectly conserved and to examine the nature of those differences in detail . Synteny analysis was performed only on the 14 nuclear chromosomes excluding mitochondrial and apicoplast genomes . Imperfect synteny blocks were visualized using Circos ( version 0 . 52 ) [56] . Orthology prediction and synteny analysis was performed using our homology-improved gene models . To separate questionable differences from likely true genetic differences , we examined all parasite-specific genes in SGRs and SBRs . SGRs were examined in an automated manner using custom Perl scripts . The few SBRs were trickier to deal with due to ambiguous mapping locations in the other genome and were thus examined manually . Briefly , automated BLASTP and GeneWise homology searches were combined with manual visual inspections of non-syntenic regions in a genome browser . Non-random BLASTP sequence similarity ( E≤1e-4 and PID≥20 ) between two ‘syntenic’ parasite-specific genes of which both are flanked by syntenic orthologs was interpreted as evidence of likely orthologous genes missed by Inparanoid . We refer to these genes as positional orthologs . Furthermore , non-random GeneWise alignments ( bitscore ≥40 ) generated in syntenic regions using the putative parasite-specific gene as query are indicative of potentially split/merged genes or missing genes , depending on whether or not alignments overlap with existing gene models . Albeit due to limited sequence similarity GeneWise gene models produced in this step are not entirely reliable , we kept their protein translations for downstream proteomics analyses . In addition , we provide these tentative GeneWise gene models for further inspection ( Dataset S4 , GFF3 format ) . Gene structures ( gene length , location , number of exons ) were also visually examined to validate putative orthologs . We further excluded putative parasite-specific genes for which sequence gaps were present in syntenic regions of the respective other genome , because in this case one cannot reliably exclude the possibility that a syntenic ortholog is present but currently missing from the assembly . Genes shared by P . falciparum and P . vivax but absent in P . knowlesi ( Figure 7 and Table 2 ) were identified by taking all confirmed P . vivax-specific genes absent in P . knowlesi ( Figure 7 ) and then excluding all genes without predicted ortholog in P . falciparum , considering both Inparanoid orthologs and positional orthologs recovered from Figure 6 . In addition , we queried OrthoMCL DB [44] for the presence of orthologs of putative human parasite-specific genes in other species than P . falciparum and P . vivax . As a last step , we ran genBlastG with remaining P . falciparum genes against the entire P . knowlesi genome and retained only those candidates that either ( a ) did not produce a gene model with at least 15% PID and 80% query coverage or ( b ) produced such a gene model but it overlapped with a P . knowlesi gene that had a different known ortholog in P . falciparum . The resulting gene list is shown in Table 2 . Additional information shown in Table 2 is a compilation of data obtained from searching online databases with P . falciparum gene names and sequences , including PlasmoDB 7 . 1 [36] , GeneDB [57] , InterPro [52] , and NCBI nucleotide and protein archives . Starting with all genes in Figure 6 ( bottom left diagram ) categorized as ‘other , annotated function’ ( 15 genes ) and ‘ ( conserved or hypothetical ) protein , unknown function’ ( 42 genes ) , we excluded genes representing chromosome-internal members of previously described ( subtelomeric ) gene families ( 7 genes ) , genes part of gene families with known members in P . vivax ( 6 genes ) , genes without expression evidence or questionable open reading frames ( 9 genes ) , and genes where visual re-examination revealed the presence of a potential positional ortholog in P . vivax that did not meet our similarity threshold for automatic detection ( BLASTP E-value<1e-04; PID> = 20 ) . Of the remaining genes we only retained those with potential virulence-associated functions as predicted by ( a ) the presence of a PEXEL motif , a signal peptide , or a transmembrane domain , or ( b ) PlasmoDraft [35] or OPI [38] . We further queried OrthoMCL DB [44] for predicted orthologs in other species . One gene ( PF14_0708 ) was found to have a predicted ortholog in P . vivax , but was nevertheless retained in the final list because this gene is present as an extra copy in P . falciparum ( i . e . two genes in P . falciparum and one in P . vivax ) . As a last step , we ran genBlastG with remaining P . falciparum genes against the entire P . vivax genome and retained only those candidates that either ( a ) did not produce a gene model with at least 15% PID and 80% query coverage or ( b ) produced such a gene model but it overlapped with a P . vivax gene that had a different known ortholog in P . falciparum . The resulting gene list is shown in Table 3 . The complete , unfiltered list of all 117 identified chromosome-internal P . falciparum -specific genes is provided in Table S4 . As before , the additional information shown in Table 3 is a compilation of data obtained from searching online databases with P . falciparum gene names and sequences , including PlasmoDB 7 . 1 , GeneDB , InterPro , and NCBI nucleotide and protein archives . Sequence-independent predictions of virulence-associated functions were obtained from . To identify genes exclusively present in P . vivax , we overlapped the two P . vivax-specific gene sets of Figure 6 and Figure 7 , which resulted in 81 P . vivax-specific genes absent in both P . falciparum and P . knowlesi . We then excluded genes with named gene products ( RAD , MSP7 , MSP3 , SERA ) , which resulted in 38 chromosome-internal P . vivax-specific genes encoding for hypothetical proteins of unknown function ( Table S5 ) . Because median length of encoded protein sequences was short ( 116 aa ) , we suspected many false-positive gene predictions among those genes . We therefore further excluded all genes with one or more of the following characteristics: short open reading frames ( <100 aa ) ; EST evidence conflicting with the current gene model; coding sequence consisting mostly of low complexity regions or repeat sequences; and the presence of an overlapping gene on opposite strand . Excluding low-confidence ORFs and two other hypothetical genes located near subtelomeric regions resulted in five genes with a likely genuine ORF in chromosome-internal regions . | With more than 250 million infections and over a million deaths each year , malaria remains one of the most devastating infectious diseases worldwide . With the availability of complete genome sequences of both human and non-human Plasmodium parasites , the causative agents of malaria , it is now possible to use comparative genomics as a tool to look for genes that are present in some but not all Plasmodium species . Such species subset-specific genes possibly underlie important phenotypic differences between malaria parasites and could provide important clues for the development of new strategies to prevent and treat malaria in humans . In this study , we performed a comprehensive computational comparison of the published genomes of six Plasmodium species , including two human ( P . falciparum and P . vivax ) , one monkey ( P . knowlesi ) , and three rodent malaria parasites ( P . berghei , P . yoelii , and P . chabaudi ) . This comparison revealed many species subset-specific genes that are potentially linked to human pathogenicity , human-to-human transmissibility , and human virulence . These genes can now be examined further by targeted experimental analyses to test predicted phenotypic associations and to elucidate gene function . | [
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] | 2011 | Genome Comparison of Human and Non-Human Malaria Parasites Reveals Species Subset-Specific Genes Potentially Linked to Human Disease |
Regulated cell polarity is central to many cellular processes . We investigated the mechanisms that govern the rapid switching of cell polarity ( reversals ) during motility of the bacterium Myxococcus xanthus . Cellular reversals are mediated by pole-to-pole oscillations of motility proteins and the frequency of the oscillations is under the control of the Frz chemosensory system . However , the molecular mechanism that creates dynamic polarity remained to be characterized . In this work , we establish that polarization is regulated by the GTP cycle of a Ras-like GTPase , MglA . We initially sought an MglA regulator and purified a protein , MglB , which was found to activate GTP hydrolysis by MglA . Using live fluorescence microscopy , we show that MglA and MglB localize at opposite poles and oscillate oppositely when cells reverse . In absence of MglB , MglA-YFP accumulates at the lagging cell end , leading to a strikingly aberrant reversal cycle . Spatial control of MglA is achieved through the GAP activity of MglB because an MglA mutant that cannot hydrolyze GTP accumulates at the lagging cell end , despite the presence of MglB . Genetic and cell biological studies show that the MglA-GTP cycle controls dynamic polarity and the reversal switch . The study supports a model wherein a chemosensory signal transduction system ( Frz ) activates reversals by relieving a spatial inhibition at the back pole of the cells: reversals are allowed by Frz-activated switching of MglB to the opposite pole , allowing MglA-GTP to accumulate at the back of the cells and create the polarity switch . In summary , our results provide insight into how bacteria regulate their polarity dynamically , revealing unsuspected conserved regulations with eukaryots .
In living cells , environmental changes and cell-cell regulations require transient cellular processes relying on the ability of the cells to regulate their underlying ultrastructures dynamically . For example , during chemotaxis , eukaryotic cells sense and migrate towards a chemical gradient , which requires complex spatial regulation of actin cytoskeleton dynamics [1] . The cells use a directional sensing system as a compass to favor the formation of pseudopodia towards or away from a source of chemoattractrant or repellent [1] . In this process , the cell adopts a polarized morphology , to define a front and a rear to coordinate actin polymerization at the leading edge with contractile forces generated by myosin motors at the rear . The actin cytoskeleton and the membrane are rearranged by a complex signaling network involving Receptor/G-proteins and , centrally , small GTPases of the Ras superfamily [2] . For example , in leukocytes , or in the amoeba Dictyostelium discoidum , polarization is achieved by a complex interplay of multiple small GTP-binding proteins at the front and the rear involving Ras , Rac , Cdc42 , and Rho ( see [2] for a detailed review of these regulations ) . Owing to the small size of the bacterial cell , it is generally accepted that dynamic processes such as motility are regulated at the temporal rather than at the spatial level . For example , chemotaxis in liquid media relies on a temporal signal transduction cascade that switches the rotation of the flagellum [3] . However , one conspicuous example of dynamic cell polarization occurs during Myxococcus xanthus motility over solid surfaces ( gliding motility ) : rod-shaped myxococcus cells control their direction of movement by inverting their polarity , rapidly switching their leading pole into their lagging cell pole ( cellular reversal ) [4] . Cellular reversals are highly regulated and mutants with impaired reversal frequencies cannot accomplish complex multicellular behaviors such as predation [5] and the capacity to develop fruiting bodies [6] . Cellular reversals imply that the directionality of the motility machinery can be rapidly inverted . In Myxococcus , two motility engines power locomotion: the first motility engine , a type-IV pilus , polymerizes fibers at the leading cell pole , which act as “grappling hooks” as they extend and retract to pull the cell forward [7] . The pili constitute the so-called Social ( S ) -motility system because they are involved in the movement within large cell groups , presumably because they allow tight cell-cell interactions [8]; the second motility system is not as well characterized and involves dynamic eukaryotic-like focal adhesions and the secretion of a polysaccharidic slime [9] . This system is usually referred to as the Adventurous ( A ) -motility system because in contrast to the pili , it promotes the movement of single isolated cells [10] . Recently , ( A ) - and ( S ) -motility components have been tracked in live gliding cells by time lapse fluorescence microcopy using chimeric fluorescent reporter proteins . Core type-IV pilus sub-units were found to be pre-assembled at both cell poles , but some key subunits , the extension and retraction ATPases and the FrzS protein , shuttled from pole-to-pole and were only clustered at one pole , suggesting that reversals occur following completion of an active pilus machine at the leading cell pole [11] , [12] . Likewise , the A-motility focal adhesions , visualized by the AglZ-YFP protein , are assembled at the leading cell pole and are slowly moved to the rear where they are dispersed; at the time of reversal , the existing AglZ clusters are first dispersed and then reassembled from the new leading pole [13] . A-motility also involves proteins that accumulate and switch at the back of the cell ( RomR ) , showing that motility requires both a head and a tail [14] . The two motility systems must be coordinated not to counteract each other , meaning that their directionality must be switched together when the cell reverses . Consistent with this , FrzS ( S-motility ) and RomR ( A-motility ) have been shown to oscillate synchronously [14] . Synchronous pole-pole oscillations of proteins belonging to the ( A ) - and ( S ) -motility are regulated by the Frz chemotaxis-like system [12] , [13] , [14] . The Frz core components involve a cytosolic chemoreceptor-like protein FrzCD , its coupling protein FrzA , and a cognate histidine kinase FrzE [6] . Auto-phosphorylation of FrzE following receptor activation allows transfer of phosphoryl groups to the downstream response regulator FrzZ [15] , [16] . frz-null mutations decrease the cellular reversal frequency dramatically , whereas frz-gain of function mutations ( frzCDc ) increase the reversal frequency . Consistent with this , both classes of mutations respectively abolish or increase spatial oscillations of the ( A ) - and ( S ) -motility protein reporters [12] , [13] . It was suggested that the Frz system constitutes a biochemical oscillator to regulate a downstream spatial oscillator , thus acting as a molecular clock to finely tune the reversal frequency to the ever-changing environmental conditions [17] . However , proving this attractive hypothesis will require extended characterization of the regulation mechanism . How is the cell dynamically polarized to target motility proteins to opposite cell poles when cells reverse ? A likely candidate for such regulation is the MglA protein , a bacterial small G-protein of the Ras-superfamily [18] . Previously , it was shown that MglA interacts directly with FrzS and AglZ and that FrzS , AglZ , and RomR are mislocalized in an mglA mutant [14] , [18] , [19] . Assembly of the focal adhesion clusters specifically requires MglA to cooperate with the MreB actin cytoskeleton [18] . A difficulty is that MglA is required for the functionality of the motility engines themselves; thus , it could not be determined if MglA also has a role in directional control . In this work , we investigated the role of the MglA GTP cycle and found that MglA acts as a cornerstone to coordinate spatial assembly and activity of the motility engines . We found that the establishment of a dynamic polarity axis relies directly on the sequestration of the MglA GTP-bound form at the leading cell pole and characterized a novel GTPase Activating Protein responsible for this spatial regulation .
In eukaryotic cells , small G-proteins are critically regulated by Guanine nucleotide Exchange Factors ( GEFs ) and GTPase Activating Proteins ( GAPs ) [20] , [21] . We have previously established that MglA can hydrolyze GTP , albeit at very slow rates in vitro , suggesting that an MglA-regulator with GAP activity could exist [18] . Based on sequence conservation , extensive search of the Myxococcus genome did not reveal eukaryotic-like regulators . Yet MglA is co-expressed with MglB , the founder member of a family of proteins that contains a so-called roadblock domain [22] , [23] . The function of roadblock domains has not been demonstrated experimentally , but bioinformatics suggested that they might regulate the activity of a cognate NTPase [23] . Thus , MglB and MglB-like proteins could be prokaryotic regulators of bacterial small G-proteins such as MglA . To test this possibility , we purified recombinant MglA and MglB proteins to analyze in vitro whether MglB could act as a GAP for MglA ( Figure 1A ) . In vitro , MglA bound but did not significantly hydrolyze radio-labeled GTP ( Figure 1B and 1C ) . This result is consistent with previous results , showing that MglA hydrolyzed GTP at an extremely low rate in an enzyme-coupled assay [18] . In marked contrast , addition of MglB stimulated GTP hydrolysis by MglA in a dose-dependent manner ( Figure 1C ) . MglB alone did not bind radioactive GTP ( Figure 1B ) . Additionally , MglB was not found to affect GDP/GTP exchange on MglA: MglB stabilized the GTP bound form slightly ( like a classical G-protein effector , Figure 1B ) but did not modify the GDP off rate of MglA ( unpublished data ) . Thus , MglB is an MglA GAP , which functions by switching MglA-GTP to MglA-GDP . What is the function of MglB in vivo ? mglAB are encoded within a putative operon . In a previous work , deletion of mglB resulted in a dramatic reduction of the MglA levels , which precluded in-depth study of the function of MglB [24] . MglB was proposed to have a chaperone function for MglA explaining the observed lack of MglA stability [24] , yet the low levels of MglA expression could also have been due to polar effects of the mglB deletion . To test the function of mglB in vivo , we deleted the region encoding residues 10–159 of mglB ( MglB contains 159 residues ) . To show that this mglB deletion created no downstream polar effects on the expression of mglA , we successfully complemented the ΔmglB mutant by integrating another copy of mglB at an ectopic site on the Myxococcus chromosome ( the Mx8-phage attachment site , Figure 2A and Figure S1A ) . Likewise , deletion of mglA was fully complemented when mglA was expressed from the Mx8-phage attachment site ( Figure S1B ) . Western blots using anti-MglA and anti-MglB antibodies showed that MglA and MglB were produced stably in the ΔmglB and ΔmglA mutant , respectively ( Figure 2A ) . We conclude that MglA and MglB are stable independently from each other and that their respective functions can be studied with the deletion mutants . We tested the motility of the ΔmglB , ΔmglA , and ΔmglAB mutants in the hard ( testing both A- and S-motility ) and soft ( testing S-motility only ) agar assays . Swarming of the ΔmglB mutant was severely defective but detectable on both substrata ( Figure 2B ) . The ΔmglA and ΔmglAB mutants looked completely non-motile under all conditions , showing that mglA acts downstream from mglB ( Figure 2B ) . The motility defect of the ΔmglB mutant may be due to defects of the motility engines , aberrant directional control , or both . Time-lapse analysis of ΔmglB motile cells revealed that the cells moved with WT velocities ( unpublished data ) . Strikingly , the ΔmglB mutant displayed an altered reversal frequency and reversed their direction of movement more frequently than WT cells ( Figure 2C ) . Thus , MglB acts upstream from MglA and inhibits cellular reversals . The Frz pathway regulates the reversal frequency of Myxococcus cells [25] . We wondered where MglB acts in the pathway . We combined frzE-null ( kinase null ) and frzZ-null ( response-regulator null ) mutations with a ΔmglB deletion and scored the reversal frequency of the double mutants . Strikingly , the ΔmglB mutation restored reversals of both the ΔfrzZ and ΔfrzE mutants ( Figure 2C ) . The reversal frequency of the double mutants was significantly higher than the reversal frequency of WT cells yet remained slightly lower than the reversal frequency of the ΔmglB mutant ( Figure 2C ) . To confirm the epistastic relationship between mglB and frz , we also combined a frzCDc mutation ( a mutation that hyperactivates Frz signaling ) with the ΔmglB deletion . Both mutants hyper-reverse but they have significantly distinct reversal frequencies: the ΔmglB mutant has an average frequency of ∼10 rev . hour−1 , while the frzCDc has an average frequency of ∼40 rev . hour−1 ( Figure 2C ) . A frzCDc ΔmglB mutant reversed with frequencies that were indistinguishable from the ΔmglB mutant ( ∼10 rev . hour−1 ) , confirming that mglB acts downstream from the Frz-pathway . Agar swarming assays showed that the swarming pattern of the ΔfrzE ΔmglB was almost identical to the swarming pattern of the ΔmglB mutant , confirming that mglB acts downstream from the Frz pathway ( Figure S2 ) . To clarify whether the ΔmglB mutant is indeed distinct from the ΔfrzE ΔmglB mutant , we measured the average distances traveled by the cells between reversals ( Figure 2D ) . We found that the ΔfrzE ΔmglB mutant cells moved on average a distance corresponding to 4–5 cell lengths before they reversed ( versus ∼8 cell lengths for the WT , Figure 2D ) . On the contrary , the ΔmglB mutant cells almost systematically reversed after moving a distance corresponding to one cell length ( Figure 2D , see below ) . Taken together , these results suggest that the Frz pathway activates cellular reversals by relieving an inhibition that mglB exerts on mglA: low reversal frequencies in frz-null mutants can thus be explained by a failure to relieve MglB inhibition , a mechanism that depends on FrzZ . However , Frz must also be able to signal to MglA independently from MglB because Frz-dependent regulation ( albeit highly abnormal ) is still detected when the reversal frequency of ΔmglB mutant is compared to the reversal frequency of double ΔfrzE ΔmglB mutant ( see Discussion ) . This branching in the signaling pathway must occur downstream from FrzZ because ΔfrzZ ΔmglB mutants reverse with frequencies that are similar to the ΔfrzE ΔmglB ( Figure 2C ) . To further understand the role of MglB , we generated a functional MglB-YFP fusion to investigate MglB dynamics during the reversal cycle ( Figure S1 ) . A single MglB-YFP focus was observed at the lagging cell pole and this focus switched systematically to the new lagging pole when cells reversed ( Figures 3A , 3B , and S4A ) . Automated cross-correlation analysis confirmed that MglB oscillations are indeed coupled to cellular reversals ( Figure 3C ) . Introduction of the frzCDc allele led to hyper-oscillations of MglB-YFP ( Figure 3D and 3E ) whereas a frzE-null mutation abolished oscillations ( unpublished data ) , confirming that MglB is indeed regulated by Frz . Our genetic and biochemical evidence suggests that MglB inhibits reversals by activating GTP hydrolysis by MglA at the lagging cell pole . In a previous work , we constructed a partially functional MglA-YFP chimera: cells expressing MglA-YFP alone were motile but significantly impaired in their reversal frequency , precluding studies of MglA dynamics during the reversal cycle ( Figure S3 [18] ) . To monitor the dynamics of MglA-YFP in reversing cell , we expressed MglA-YFP in the presence of MglA . In these merodiploid cells , expression of MglA-YFP was not associated with detectable motility defects ( see Protocol S1 for details on the construction and Figure S3 ) . Thus , we conclude that MglA-YFP dynamics during reversal can be studied using the merodiploid system , which will be systematically used for the rest of this study . In a fluorescent time-lapse motility assay , MglA-YFP localized at the leading cell and within fixed internal clusters ( Figures 4A and S4B ) . MglA-YFP oscillated from pole to pole and was systematically redirected to the new leading pole at the time of reversal ( Figure 4A and 4B ) . Cross-correlation analysis also confirmed that MglAYFP oscillations are coupled with the reversal cycle ( Figure 4C ) . Thus , the localization of MglA-YFP is coupled to the reversal cycle . MglA-YFP dynamics were clearly regulated by the Frz pathway: in a ΔfrzE mutant oscillations of MglA-YFP were abolished ( unpublished data ) , while they were enhanced and correlated with increased cellular reversals in a frzCDc mutant ( Figures 4D and S5 ) , confirming that MglA is a downstream component of the reversal switching machinery . To monitor the dynamic behaviors of MglA and MglB simultaneously , we engineered merodiploid cells expressing both MglA-YFP and a functional MglB-mCherry . As expected from analysis of the individual fusions in WT and frz backgrounds , both proteins oscillated inversely and synchronously , switching to opposite poles when cells reversed ( Figure 4F and 4E ) . We then analyzed the dynamic localization of MglA-YFP in absence of MglB . In this mutant , MglA-YFP did not localize to one cell pole but localized to both cell poles: minor fluctuations in MglA-YFP fluorescence were observed over time , but these changes were rapid and transient and not obviously correlated with the timing of reversals ( Figure 5A and 5B ) . Thus , a function of MglB is to prevent MglA-YFP accumulation at the lagging pole , which seems to result in aberrant reversals . MglB could inhibit cellular reversals by catalyzing the transition from MglA-GTP to MglA-GDP at the lagging cell pole . The in vitro results show that MglA does not hydrolyze GTP significantly in absence of MglB; thus , MglA may be mostly GTP-bound in the mglB mutant . If so , a mutation that locks MglA in its GTP-bound form should mimic the mglB mutation . We designed an MglA mutant where Glutamine 82 is replaced by a Leucine , a mutation predicted to lock MglA in its GTP-bound state by inhibiting GTP hydrolysis ( Figure S6A , [26] ) . In vitro , MglAQ82L bound GTP stably like the WT MglA ( Figure S6B ) , but contrarily to WT MglA and as expected , addition of MglB failed to activate hydrolysis , showing that MglAQ82L cannot hydrolyze GTP ( Figure 1D ) . When expressed in vivo , MglAQ82L was found to be as stable as WT MglA ( Figure S7 ) . If MglB prevents MglA binding at the lagging pole through its GAP activity , MglAQ82L should localize at both cell poles despite the presence of MglB . As expected , an MglAQ82L-YFP chimera ( see Protocol S1 for details on this construction ) was mostly found at both cell poles and the cells reversed in the absence of MglAQ82L-YFP oscillations ( Figure 5C and 5D ) , similarly to MglA-YFP in the ΔmglB mutant ( Figure 5A and 5B ) . We conclude that the function of MglB is to catalyze the transition from MglA-GTP to MglA-GDP , preventing accumulation of MglA at the lagging cell pole and thus inhibiting reversal frequency . MglAQ82L expressing cells reversed with a reversal frequency that was almost identical to that of the mglB deletion mutant ( Figure 2C and 2D ) . In fact , similarly to the ΔmglB mutant , mglAQ82L cells almost systematically moved exactly the length of one cell body before they reversed ( Figure 2D ) . To confirm that reversals are regulated through the MglA GTP hydrolysis cycle , we measured the reversal frequencies of mglAQ82L ΔmglB and mglAQ82L ΔmglB ΔfrzE mutant cells . All mutants reversed with frequencies similar to the mglAQ82L ( Figure 2C ) showing that the MglA GTP switch is the final downstream output of the Frz MglB transduction pathway . Our results suggest that the MglA and MglB proteins define the polarity switch that controls cellular reversals . However , an outstanding question remains: Why are cells still reversing in absence of a GTP hydrolysis cycle ( for example in ΔmglB and mglAQ82L cells ) ? This seems paradoxical because a simple assumption was that in absence of dynamic polarization , the cells would be non-reversing rather than hyper-reversing . A clue , however , is that in all cases the cells reverse after they moved the distance of one cell length ( Figure 2D ) . Since single motile cells move essentially by A-motility , we analyzed AglZ-YFP dynamics in the mglAQ82L mutant . In WT cells , AglZ-YFP localizes at the leading pole and assembles within fixed adhesion clusters dispersed at the back of the cell ( Figure S8 and [13] ) . In the mglAQ82L mutant , AglZ-YFP was not significantly retained at the cell pole; instead , a major fluorescent cluster remained at a fixed position relative to the substratum at all times ( Figure 6A ) . Cells systematically reversed once the AglZ-YFP clusters accumulated at the lagging cell end ( Figure 6A ) . Comparable results were obtained in the mglB mutant ( unpublished data ) . Thus , AglZ-YFP no longer oscillates between poles in absence of the MglA GTP-cycle . Instead , we propose that the cells reverse because the A-motility system is intrinsically capable to switch its own directionality , for example , once key regulatory proteins such as AglZ accumulate at the lagging cell pole ( see Discussion ) . To confirm that the MglA GTP cycle is essential for dynamic cell polarity we also tracked the localization of the downstream S-motility protein FrzS-GFP in the mglAQ82L strain . Under our experimental conditions , single cells do not move by S-motility but S-motility proteins dynamics are still coupled to the directionality of A-motile cells [11] , [12] . For example , FrzS-GFP clusters at the leading cell pole and oscillates from pole to pole during the reversal cycle in wild type cells ( [12] and Figure S9A ) . In both the mglAQ82L and ΔmglB strains , FrzS-GFP localized to both cell poles but showed no detectable switching: fluorescence intensities fluctuated at the cell poles but these fluctuations did not correlate with the direction of movement ( Figure 6B , 6C and Figure S9B ) . Finally , we also looked at the dynamics of the RomR-GFP protein , which belongs to the A-motility system and binds at the lagging end , oscillating inversely and synchronously with FrzS and AglZ [14] . In absence of MglB , RomR-GFP was bipolar and showed no oscillation , confirming the lack of dynamic cell polarity ( Figure S10 ) . All together , these results show that MglA and MglB establish a polarity axis that drives programmed cellular reversals .
MglA-binding cues may in fact exist at both cell poles because MglA-GTP is bi-polar in absence of MglB regulation ( i . e . , MglAQ82L or MglA in the mglB mutant ) . However , these cues are not dynamically regulated because bi-polar MglA does not oscillate with the reversal cycle . Also , FrzS and RomR localize non-dynamically to one cell pole in absence of MglA [14] , [18] . Thus , targeting of motility proteins to the cell poles is probably wired into the cell cycle itself in a process similar to flagellar assembly at new division septa [30] , [31] . Conceptually , polar curvature itself may play a role in recognition because small G-proteins and their regulators can bind curved membranes [32] and several proteins have been shown to recognize curvature at the bacterial poles [33] , [34] . Several lines of evidence suggest that MglAB is the polarity generator that creates cellular reversals: ( i ) MglA acts downstream from the Frz pathway and switches systematically to the new leading pole . ( ii ) Expression of an MglA variant locked in its GTP-bound state is epistatic over Δfrz and ΔmglB mutations , showing that MglA is the most downstream component of the regulatory cascade that controls reversals . ( iii ) MglA interacts directly with FrzS and AglZ [18] , [19] and is essential for the dynamic localization of FrzS , AglZ , and RomR . ( iv ) The perturbations of the MglA GTP cycle affect dynamic polarity of MglA itself and creates aberrant dynamic behaviors of the downstream proteins FrzS , AglZ , and RomR . ( v ) MglA is a bona fide small G-protein , a class of essential polarity regulators in eukaryotic cells . The results suggest that MglB acts to sequester MglA-GTP at the leading cell pole where it would activate both motility systems , for example , by engaging FrzS and AglZ ( Figure 7A ) . Consistent with this , MglAQ82L-YFP , a GTP-locked mutant , accumulates at the lagging cell pole , despite the presence of MglB . MglB may also trigger dispersal of the focal adhesion clusters by inactivating cluster-associated MglA and preventing uncontrolled A-motility directional switches ( see below ) . Thus , a Frz-dependent mechanism could simply invert the polarity axis by switching MglB to the opposite cell pole ( Figure 7A ) . This model is attractive but still has a number of unresolved questions . How are MglA and MglB switched to generate reversals ? MglA- and MglB-YFP do not accumulate gradually at opposite poles but rather are rapidly relocated at the time of reversal ( within ∼30 s ) ( Figures 3B and 4B ) , arguing that a transient signal input triggers the switch . Interestingly , bursts of phosphorylated FrzZ are predicted by mathematical modeling [17] . If true , FrzZ may trigger re-localization of MglB to the opposite cell pole directly , potentially by inhibiting the MglB GAP activity . However , this scenario is probably over-simplistic: our results clearly point to the existence of additional MglA regulators: the “pendulum” motility of the ΔmglB mutant can be suppressed partially by deletion of either frzE or frzZ ( Figure 2D ) , suggesting the existence of an additional Frz-modulated regulator of MglA . frz suppression does not occur in cells expressing the MglA GTP-locked variant; thus , the suppression mechanism specifically occurs at the level of the MglA GTP cycle ( Figure 2C ) . In addition , MglA may be mostly in its GTP-bound form in the ΔmglB mutant because the reversal frequency and localization of MglA-YFP were very similar in the ΔmglB and mglAQ82L mutants . Thus , frz suppression of the ΔmglB mutant pendulum motion argues that the MglA GTP-cycle is somewhat restored in the double mutant ( albeit incompletely ) , for example because of an additional MglA GAP . Eukaryotic small G-proteins are often controlled through the balancing actions of GAPs and GEFs , each catalyzing opposite steps of the GTP switch [21] . A GEF may be necessary to switch MglA back to the GTP bound form after MglB activation of GTP hydrolysis , but MglA could also spontaneously switch back to the GTP-bound state if the GTP/GDP balance is favorable in the cell . Small GTPase regulation by bacterial proteins is common during pathogenesis where invasive bacteria inject effectors that mimic GAPs and GEFs directly into the host cell to disrupt small GTPase signaling [35] . However , none of these virulence factors are related to MglB and there is no evidence that they have a physiological function in bacteria that express them . Thus , MglB-like proteins are probably major regulators of bacterial small GTPases . How MglB activates GTP hydrolysis by MglA is an interesting question because MglB contains a widespread so-called LC7/roadblock domain [23] . LC7/roadblocks are ancient protein domains conserved in all three eukaryotic , prokaryotic , and archeal kingdoms , yet very little information is available about their function . It was suggested that the members of this family regulate NTPases because proteins that contain roadblock domains are almost invariably linked to an NTPase [23] . For example , the LC7 protein is a conserved component of the Dynein light chain and has an important regulatory role on the activity of this motor [36] . However , the lack of a simple biochemical system to test LC7 function has hampered our understanding of how these domains work . Thus , understanding how MglB regulates MglA at the molecular level is potentially of great significance to understand the function of a widely conserved protein domain . The oscillation dynamics of FrzS-GFP and RomR-GFP were abrogated in absence of the MglA-GTP cycle , suggesting that the MglAB proteins polarize the cell dynamically to regulate cellular reversals . Thus , we were surprised to find that the cells still reversed in absence of the MglA GTP-cycle . This was puzzling because the dynamics of RomR , an A-motility protein , are not coupled to the reversal cycle in the ΔmglB mutant . So how were these reversals generated if the cells are not dynamically polarized ? Figure 7B depicts a proposed mechanism . In absence of the MglA GTP switch , active engine units may be assembled at the cell pole and produce movement . When these units reach the lagging cell end , they are not disassembled because MglB cannot activate MglA-GTP hydrolysis within the complexes . Instead , we propose that a threshold is reached at the pole , activating a built-in capacity in the machinery to reverse its directionality and resume movement in the opposite direction . The cycle can thus be repeated endlessly resulting in the “pendulum” behavior . The term “pendulum gliding” was borrowed from studies on Plasmodium sporozoites ( apicomplexan parasites ) [37] . We previously discussed that A-motility may be analogous to Apicomplexan gliding motility because the parasites assemble focal adhesion complexes at their apical end and glide forward by moving these adhesions rearward in an actomyosin motorized process [13] , [38] . Strikingly , mutant sporozoites expressing a truncated version of the adhesion factor TRAP also move like a pendulum , most likely because they fail to relieve TRAP-dependent adhesions at their trailing end [37] . In Myxococcus , failure to relieve focal adhesions at the back of the cells could also trigger a switch to the opposite direction . Thus , a critical function of MglB is to suppress these periodic switches and allow the cell to move distances corresponding at least to several cell lengths before it reverses . The molecular basis for directional inversion needs investigation both in Plasmodium and Myxococcus . In a previous work , we showed that A-motility complexes require the bacterial MreB actin cytoskeleton and MglA , much like focal adhesion complexes that drive eukaryotic cell migration [18] . Thus , the mechanisms underlying Myxococcus motility are remarkably similar to the mechanisms that drive eukaryotic cell motility . In Dictyostelium discoidum , chemotaxis involves a complex arsenal of receptor-activated small GTPases and their cognate regulators [1] , [2] . In Myxococcus , polarity seems to be controlled by a single small G-protein switch that acts downstream of a chemotaxis-like signal transduction pathway . It is thus an ideal model system to dissect molecular regulations that may be extremely widespread . Finally , MglA and MglB homologues are also widespread in prokaryots [39] , many of which are not motile , suggesting that small GTPase switches also regulate multiple biological processes in bacteria , a field of research that has not received the attention it deserves .
See Table S1 for plasmids and Table S2 for strains and their mode of construction . Primer sequences and plasmid construction schemes are provided in Tables S3 and S4 . M . xanthus strains were grown at 32°C in CYE rich media as previously described [6] . Plasmids were introduced in M . xanthus by electroporation . Mutants and transformants were obtained by homologous recombination based on a previously reported method [6] . Complementation , expression of the fusion and mutant protein were all obtained after ectopic integration of the genes of interest at the Mx8-phage attachment site in appropriate deletion backgrounds ( Table S2 ) . For co-expression of both MglAQ82L and MglAQ82L-YFP , expression of MglAQ82L was additionally driven from the car locus , another ectopic site with the pCT2 system ( Table 1 in [40] ) . Both integration at Mx8att and car have no effect on cell motility [14] , [40] . For phenotypic assays , cells , at a concentration of 4×109 cfu ml−1 , were spotted on CF-agar plates or CYE plates containing an agar concentration of 1 . 5% , incubated at 32°C , and photographed after 48 h with an Olympus SZ61 binocular or a Nikon Eclipse ( model TE2000E ) microscope . MglA-His6 and His6-MglB were expressed from the expression vector pET28 ( a ) ( Novagen ) . Expression of the recombinant proteins was induced in both cases by growing cells at room temperature for 20 h in the presence of 0 . 5 mM IPTG ( isopropyl-h-d-thiogalactopyranoside ) . Cells were then harvested by centrifugation at 8 , 000 rpm for 10 min , resuspended in a buffer containing 50 mM NaH2PO4 pH 8 . 0 , 300 mM NaCl , 10 mM imidazol , and lysed with a French press . The lysates were centrifuged twice ( 18 , 000 rpm , 4°C , 30 min ) to remove debris prior to the purification . Supernatants were incubated with Nickel beads for 1 h at 4°C and the beads were collected and loaded into 5 ml HisTrap™ nickel columns ( GE Healthcare ) . The elution was performed by using a buffer containing 50 mM NaH2PO4 pH 8 . 0 , 300 mM NaCl , 250 mM imidazol , and for MglA , GDP 30 µM . Eluates were finally dialysed against a storage solution containing 50 mM NaH2PO4 pH 8 . 0 , 300 mM NaCl , 10% Glycerol , and for MglA , GDP 30 µM . Protein purity and stability was determined by a Bradford assay and SDS-PAGE . The recombinant proteins were used both to immunize rabbits and perform biochemical in vitro assays . Purified MglA , MglAQ82L , and MglB ( 1 µM final ) were incubated at 30°C with either 20 µM non-hydrolysable [35S]GTPγS or 15 µM γ[32P]GTP in 50 mM HEPES ( pH 7 . 5 ) , 100 mM KCl , 1 mM MgCl2 , 5 mM Pi , and 1 mM DTT . We found that , in solution , MglA is stabilized by addition of lipids; thus , all biochemical assays were conducted in the presence of 1 g/l Azolectin vesicles . Samples of 25 µl were filtered at the indicated times and radioactivity was counted [41] . The curves were obtained by fitting the data to the model y = Ao ( 1−e−kt ) with k = 0 . 29 min−1 for MglA alone and k = 0 . 12 min−1 for MglA in the presence of MglB . Purified MglA and MglAQ82L ( 1 µM final ) were loaded with 15 mM [γ-32P]GTP ( ∼1 , 400 cpm/pmoles ) in 50 mM HEPES ( pH 7 . 5 ) , 100 mM KCl , 1 mM MgCl2 , 5 mM Pi , 1 mM DTT , in the presence of 1 g/l Azolectin ( Sigma ) vesicles for 4 min at 30°C . The GTP hydrolysis was initiated by the addition of 1 µM ( unless otherwise stated ) of purified MglB . At the indicated times , aliquots of 25 µl were removed . 32Pi release was measured by the charcoal method [42] . Briefly , the 25 µl samples were added to 750 µl of 5% ( w/v ) charcoal ( 100–400 mesh , Sigma ) in 50 mM NaH2PO4 ( 4°C ) and vortexed . The charcoal was removed by centrifugation ( 5 min at 13 . 2 krpm ) and the amount of radioactivity present in the supernatant was determined by liquid scintillation counting . Western blotting was performed as previously described [40] with 1/10 , 000 dilutions of MglA or MglB antisera . Time lapse experiments were performed as previously described [43] . Microscopic analysis was performed using an automated and inverted epifluorescence microscope TE2000-E-PFS ( Nikon , France ) . The microscope is equipped with “The Perfect Focus System” ( PFS ) that automatically maintains focus so that the point of interest within a specimen is always kept in sharp focus at all times , in spite of any mechanical or thermal perturbations . Images were recorded with a CoolSNAP HQ 2 ( Roper Scientific , Roper Scientific SARL , France ) and a 40×/0 . 75 DLL “Plan-Apochromat” or a 100×/1 . 4 DLL objective . All fluorescence images were acquired with a minimal exposure time to minimize bleaching and phototoxicity effects . Cell tracking was performed automatically using a previously described macro under the METAMORPH software ( Molecular devices ) ; when appropriate , manual measurements were also performed to correct tracking errors with tools built into the software . Images were processed under both ImageJ 1 . 40g ( National Institute of Health , USA ) and METAMORPH . Cells ( n>100 ) were automatically segmented by successive morphological operations: h-dome extraction , gray-scale reconstruction , binary images , and morphological opening . To optimize segmentation , binary frames were sometimes corrected manually with appropriate tools built into the software . A binary mask was then used to perform integrated morphometric analysis and cell tracking . Cell tracking was performed following standard mathematical procedures already described in [43] . Computational scoring of cell reversals was obtained by tracking cells that showed clear directional changes , moving at least a 10th of their cellular length in the opposite direction . To correlate these reversals to changes in fluorescence at the cell poles , the cell poles were automatically detected using a custom automation script ( Visual Basic ) under Metamorph 7 . 5 ( Molecular Devices , Molecular Devices France , France ) . In this system , polar fluorescence inversions were systematically scored when the difference between the average grey intensity values of the poles became significantly different from the standard deviation of the average intensity value along the length of the cell . All selected cells were verified manually to ensure that the automatic process always scored actual reversals and polar fluorescence inversions . The cross-correlation coefficient ( Rxy ) between scored reversals and fluorescence pole-to-pole switchings for a time of delay ( m ) was calculated with the following equation:The maximum value is Rxy = 1 for a perfect correlation . The time lapse movies are composed of 30 s time frames due to illumination constraints ( toxicity and bleaching ) . In these conditions , a Rxy>0 . 5 for a time delay = 0 ( ±30 s ) means that the two events , fluorescence polar inversions ( x ( t ) ) and cellular reversals ( y ( t ) ) , are highly correlated . | Motile cells have evolved complex regulatory networks to respond to environmental cues and change their direction of movement appropriately . In this process , an arsenal of receptor-coupled small G-proteins acts as a cellular compass to dynamically polarize the leading edge and regulate the motility response . However , the precise mechanism of action of these G-proteins in controlling bacteria movement on solid surfaces has remained an enigma . We investigate this process in Gram negative Myxococcus xanthus cells . Surprisingly , we find that the Ras-like small G-protein MglA polarizes the cell by accumulating at the leading cell pole in its active GTP-bound form . This localization is dependent on MglB , a GTPase-activating protein that converts MglA to its inactive form specifically at the opposite , lagging cell pole . Furthermore , we show that a receptor-coupled signal transduction cascade can activate re-localization of MglA and MglB at opposite poles in a synchronous manner , resulting in inversion of the polarity axis and cell movement in the opposite direction . Thus , a simple , eukaryote-like signaling module also governs dynamic polarity mechanisms in bacteria , demonstrating broader conservation of these signaling systems than initially suspected . | [
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] | 2010 | A Bacterial Ras-Like Small GTP-Binding Protein and Its Cognate GAP Establish a Dynamic Spatial Polarity Axis to Control Directed Motility |
Metronidazole is the most commonly used drug for the treatment of giardiasis in humans . In spite of its therapeutic efficacy for giardiasis , low patient compliance , especially in children , side effects , and the emergence of metronidazole-resistant strains may restrict its use . Albendazole has been used to treat Giardia duodenalis infections in recent years . However , efficacy studies in vivo and in vitro have produced diverse results as to its effectiveness . A moderately benign side effect profile , combined with established efficacy against many helminths , renders it promising for treatment of giardiasis in humans . We performed a search in the PubMed , Scopus , EMBASE , the ISI Web of Science , LILIACS , and Cochrane Controlled Trials Register for trials published before February 2010 as well as in references of relevant research and review articles . Eight randomized clinical trials ( including 900 patients ) comparing the effectiveness of albendazole with that of metronidazole were included in meta-analysis . After extracting and validating the data , the pooled risk ratio ( RR ) was calculated using an inverse-variance random-effects model . Albendazole was found to be equally as effective as metronidazole in the treatment of giardiasis in humans ( RR 0 . 97; 95% CI , 0 . 93 , 1 . 01 ) . In addition , safety analysis suggested that patients treated with albendazole had a lower risk of adverse effects compared with those who received metronidazole ( RR 0 . 36; 95% CI , 0 . 10 , 1 . 34 ) , but limitations of the sample size precluded a definite conclusion . The effectiveness of albendazole , when given as a single dose of 400 mg/day for 5 days , was comparable to that of metronidazole . Patients treated with albendazole tended to have fewer side effects compared with those who took metronidazole . Given the safety , effectiveness , and low costs of albendazole , this drug could be potentially used as an alternative and/or a replacement for the existing metronidazole therapy protocols in the treatment of giardiasis in humans .
Giardiasis in humans , caused by the protozoan parasite Giardia duodenalis ( syn . G . lamblia , G . intestinalis ) , is a common parasitic disease [1] . The prevalence of infection is commonly between 2–5% in the developed world and 20–30% in the developing and underdeveloped countries [2] . Infection is initiated by ingestion of cysts in contaminated drinking water and/or contaminated food [1] . Ingested cysts release trophozoites which colonize and replicate in the small intestine of the new host . G . duodenalis does not invade the epithelial or deeper layers of the mucosa and propagation takes place on the epithelial surface [3] . The outcomes of Giardia infections vary significantly and the majority of infections are self-limiting . Clinical manifestations range from a relatively asymptomatic phase marked by mild nutrient malabsorption , to an ephemeral or persistent acute stage , with steatorrhea , intermittent diarrhea , vomiting , malabsorption syndrome and weight loss , or to a subacute chronic phase that can mimic gallbladder or peptic ulcer disease [4] , [5] . Infections in immunocompetent individuals are generally self-limited , suggesting the existence of effective host defense mechanisms against the parasite [6] . Different diagnostic methods are employed for the diagnosis of human giardiasis of which the most insensitive method , direct stool microscopy is used routinely in developing countries where the disease is endemic [5] , [7] . Existing chemotherapy protocols recommend that patients should be treated if the parasite is found , irrespective of the presence or absence of acute symptoms [8] . However , some investigators question the usefulness of chemotherapy in infected people in endemic areas due to the extremely high rate of reinfection , as high as 90% in some studies [9] , [10] . Treatment preferences vary among clinicians and in different locations . Several synthetic compounds ( including metronidazole and other nitroimidazole derivates such as albendazole , mebendazole , furazolidone , tinidazole , ornidazole ) are used in the treatment of giardiasis in humans . A single dose of tinidazole ( 2 . 0 g ) has been shown to have a clinical efficacy of 80–100% in different clinical trials [11] , [12] while the compliance is improved compared with other giardiasis treatments . However , the high cost of tinidazole may restrict its use in mass chemotherapy campaigns [13] in developing and underdeveloped countries ( e . g . $18 to $32 for a single-dose of 2 g for the treatment of trichomoniasis ) . The most widely used treatment protocols employ metronidazole given 3 times per day for 3–5 days [8] , [14] , [15] , [16] . Metronidazole is typically administered in doses of 250 mg 3 times a day for 5–7 days for adults and 15 mg/kg 3 times a day for 5–7 days in children . However , albendazole is typically given as a single dose of 400 mg/day for 3–5 days . In recent years , therapeutic failure of metronidazole , the first-line drug of choice in giardiasis in humans , has increasingly been reported from all around the world [17] . Metronidazole is prescribed widely for a wide range of non-parasitic infectious diseases; overusing metronidazole as a treatment option for parasitic infections may increase the chances of the development of clinically drug-resistant strains of Helicobacter pylori , an important cause of gastric cancer in humans [18] . Low compliance of patients with the current metronidazole therapy protocols , the emergence of the metronidazole-resistant strains of the parasite and other pathogens , and rapid reinfection of treated patients in the endemic areas are additional reasons for considering alternative therapies [19] . Treatment compliance is a key factor affecting the outcome of giardiasis . However , compliance has been neglected in the literature [20] , and is therefore not part of the current analysis . In one report on metronidazole use in patients with giardiasis , treatment compliance was extremely poor because of missed doses , spillage , inaccurate measuring implements , and poor adherence to the prescribed frequency and duration of medication [21] . Common adverse reactions frequently reported with metronidazole include metallic taste , nausea , vomiting , diarrhea , and epigastric discomfort [20] . Moreover , its activity against the host's normal intestinal microflora; its contraindication for children , pregnant and breastfeeding women; and its carcinogenic and tumorigenic properties in animal models make it less than optimal for widespread use [8] . Finding safer drugs with less toxicity and more effective therapeutic properties and developing novel protocols ( e . g fewer doses and shortened duration ) to maximize the effects of existing drugs are , therefore , crucial for the field . Albendazole has been used extensively for the treatment of a wide range of helminth parasites including hookworms , Ascaris lumbricoides , Trichuris trichiura , Echinococcus sp . [22] and Taenia sp . [23] with few side effects ( reviewed by Keiser and Utzinger [24] ) . The mechanism of action of albendazole differs from that of metronidazole . While metronidazole affects electron transport of the parasite [25] , it is believed that albendazole exerts its anti-giardial effects by interaction with tubulin of the Giardia cytoskeleton [26] . Albendazole also has overt giardiacidal activity in vitro [27] , as well as being able to resolve infections in a mouse model of G . duodenalis infection [19] , [26] . Using albendazole against giardiasis in humans could potentially augment mass treatment programs , which are part of helminth control campaigns , since most patients with Giardia are probably co-infected with other parasitic agents . Altogether , the evidence suggests that albendazole could be considered as a potential anti-giardial agent . Its lower toxicity , its relative insolubility and poor absorption from the gut , and its lack of significant effects on the intestinal microflora could make albendazole an ideal substitute for metronidazole . The aims of the current meta-analysis , therefore , were first to address the effectiveness and second to assess the safety of albendazole compared with metronidazole for the treatment of giardiasis in humans .
A literature search of the PubMed database ( 1966–February 2010 ) , Scopus , EMBASE , the Cochrane Controlled Trials Register ( issue 4 , 2009 ) , LILIACS and the ISI Web of Science for trials published before February 2010 was performed . The literature search used the following terms: “giardiasis” , “metronidazole” , and “albendazole . ” The abstracts of all selected articles were read to identify the potentially eligible articles . A manual search was performed systematically using the authors' reference files and reference lists from original communications , selected books and review articles [8] , [28] . Language restriction was not applied . The contents of abstracts or full-text manuscripts identified during our literature search were reviewed to determine whether they met the criteria for inclusion . For inclusion , a study had to allocate the study participants randomly to study groups ( a prospective randomized clinical trial ) . Included studies had to compare the effectiveness of albendazole with that of metronidazole in the treatment of giardiasis . Figure 1 summarizes the trial selection process . Our search identified twenty-nine articles for further consideration , of which only eight articles met the inclusion criteria . Major reasons for exclusion of studies were duplicate publications from which only one article was selected [29] , [30] , animal models of infections [19] , [26] , studies of veterinary importance [31] , studies in vitro [32] , single-arm studies with no randomized control groups [33] , studies lacking a comparison between the effectiveness of albendazole with metronidazole [34] , review articles [8] , [28] , studies with no clear randomization allocation procedure [35] , studies using albendazole and metronidazole analogues [36] as well as the studies showing the synergistic effects between albendazole and/or metronidazole with other drugs [37] , [38] . Conference proceedings and unpublished data were also not included . Included articles compared the effectiveness of albendazole with that of metronidazole in the treatment of giardiasis [29] , [39]–[45] . Together these articles followed 900 patients presenting with symptomatic and/or asymptomatic G . duodenalis infections . Among these 900 treated patients , 452 ( 50 . 2% ) individuals were treated with albendazole whereas 448 ( 49 . 8% ) received metronidazole . Data were extracted independently by two reviewers ( SSM and SMS ) from the eight randomized controlled trials [Table 1 and Table 2] . Discrepancies were resolved by discussion . Study characteristics recorded were as follows: 1 ) first author's name , year of publication and country of origin; 2 ) description of the population; 3 ) number of participants; 4 ) age and sex distribution of the participants; 5 ) number of participants in each arm; 6 ) clinical profile ( symptomatic , asymptomatic infections ) ; 7 ) the follow-up period; 8 ) the outcome measure; 9 ) study design; 10 ) type and dosage of the drugs; and 11 ) effectiveness range . The primary outcome measure was parasitological cure defined as the absence of parasites ( trophozoites and/or cysts ) in feces at the end of the treatment in at least two consecutive stool microscopy examinations . Parasitological cure was considered necessary in order to evaluate the effectiveness of the treatment . The secondary outcome measure , clinical cure , was defined as the global improvement of clinical symptoms , such as diarrhea , nausea/vomiting , transient abdominal pain and loss of appetite , at the end of the follow-up period . The quality of included reports was compared using the Jadad score which examines whether there is randomization , blinding , and information on dropouts/withdrawals from the study [46] . It also evaluates the appropriateness of randomization and blinding , if present . The quality scale ranges from 0 to 5 points with a low-quality report earning score of 2 or less . A study with a Jadad score ≥3 is considered to be of ample quality . The quality of parasitological diagnostic methods was assessed by the scoring system utilized by Zaat et al . [47] . This method evaluates whether techniques are sufficiently described and are adequate . Moreover , this method evaluates the reproducibility of the parasitological examinations and the level of inter-observer variation among methods [Table 3] . Three different methods were employed to perform sensitivity analysis of these trials . We first excluded the trial in which the parasitological method employed was not clearly described [45] . Second , the trials that utilized the most insensitive diagnostic methods , i . e . direct stool microscopy , alone were excluded [39] , [40] . Finally , we excluded a trial that used the most sensitive parasitological methods ( three methods at the same time ) [41] , and compared the results with the remaining trials which used two parasitological methods . We identified eight randomized , controlled trials that reported data on the comparison of the effectiveness of albendazole with metronidazole in the treatment of giardiasis in humans . The inconsistency across trials was calculated using the I2 statistic; results range between 0% ( i . e . , no observed heterogeneity ) and 100% [48] . High values reflect increasing heterogeneity . Publication bias was assessed by means of funnel plots [49] . Relative risks ( RRs ) were calculated for each study outcome separately based on information presented in articles ( i . e . the percentage of people exhibiting parasitological cure in both groups relative to the percentage of people continuing to shed cysts during the follow up period ) ; the pooled RRs and 95% confidence intervals ( CIs ) were estimated by using the inverse-variance random-effects method [50] . Although there is no standard description , an I2 statistic greater than 20% suggests heterogeneity while an I2 statistic greater than 50% usually is considered to represent significant heterogeneity [48] . The statistical package Review Manager Software 5 ( Cochrane Collaboration , Oxford , UK ) was used for analyzing the data .
Publication bias was examined using a funnel plot . Figure 3 plots the funnel plot of the treatment effects estimated from individual studies on the x-axis ( RR ) and the standard error of these estimates on y-axis ( S . E [log RR] ) . This analysis shows that the included studies were almost evenly distributed around the vertical axis , providing no evidence of publication bias . To explore further the possibility of heterogeneity due to the use of different outcome measures , we confined our analysis to trials which used the least sensitive methods to detect parasites and then to those that used the most sensitive methods ( three methods at the same time ) . Similarly , we performed an analysis restricted to those studies with clearly defined outcome measures . As seen in Table 4 , the overall estimates were equal and the confidence intervals were comparable among these restricted data sets , as well as with the combined meta-analysis values . In six studies , side effects related to therapy were absent or were less prominent in the patients receiving albendazole . Only in one study [43] were the reported side effects more evident in patients in the albendazole group compared with those in the metronidazole group ( 40 cases vs . 7 cases; P<0 . 005 ) . Overall , metallic taste and anorexia were the most commonly observed side effects in patients treated with metronidazole , while loose stools and abdominal pain were more frequent among patients receiving albendazole . Most side effects were transient and no trials were discontinued because of severe adverse effects . In Yereli et al . [41] , no side effects were reported in patients treated with either albendazole or metronidazole . The report by Rodríguez-García et al . [44] does not mention if treated children showed any side effects . In order to perform a safety analysis , the two latter studies were excluded from the analysis . Hall and Nahar [43] reported the adverse effects of a two-stage trial , and these were treated as a single trial . Considering all side effects together , 61 of 373 ( 16 . 3% ) patients treated with albendazole and 82 of 371 ( 22 . 1% ) of patients treated with metronidazole experienced at least a single side effect . The estimated summary RRs showed that individuals treated with albendazole had a lower risk of adverse effects ( RR 0 . 36 ) compared with those who took metronidazole , but with a wide confidence interval ( 95% CI , 0 . 10 , 1 . 34 ) that included the null value .
The major finding of this analysis is that when albendazole was given as a single dose of 400 mg/day for 5 days it was as effective as metronidazole in the treatment of giardiasis in humans . Additionally , albendazole had statistically the same safety profile as metronidazole . Metronidazole has been widely used to treat giardiasis in humans [10] , [38] , [51] , [52] , [53] , [54] , and often causes side effects such as nausea , metallic taste , dizziness and headache [8] . In addition , this drug is a known mutagen in bacteria [55] , [56] , it is genotoxic to human cells [57] , [58] and it has been shown to be carcinogenic in animal models [59] , [60] . However , there is no evidence showing metronidazole is also carcinogenic in humans [60] . Typically , metronidazole is administered in doses of 250 mg 3 times a day for 5–7 days for adults and 15 mg/kg 3 times a day for 5–7 days in children . Some clinicians tend to use single-dose regimens , while others like to administer higher dosages for an extended period of time . The latter is problematic in developing countries , as medications are frequently purchased in quantities which represent less than a single day's dose and effective therapies of short duration are preferable [61] . The need for an extended period of time for the treatment of giardiasis again may in part explain the frequent side effects associated with metronidazole therapy . Extended treatment with albendazole also appears to be more effective than shorter duration protocols . However , the once per day regimen would still be preferable to the three times per day required for metronidazole therapy . A further complication when using metronidazole therapy to treat giardiasis is that the consumption of alcohol should be avoided by patients during systemic metronidazole therapy and for at least 24 hours after completion of treatment [62] , [63] . Taking metronidazole and alcohol may result , rarely , in a disulfiram-like reaction ( nausea , vomiting , flushing , and tachycardia ) . It should be noted that the consumption of alcohol by patients was not monitored in any of the studies considered in the current meta-analysis . Alcohol uptake could potentially explain side effects in some patients receiving metronidazole . The lack of placebo-controlled trials makes it difficult to attribute the existence and severity of side effects to either of these two drugs . However , one study that did not meet our inclusion criteria suggested that patients receiving a placebo control presented with minimal side effects [10] . Together , these limitations can potentially restrict the use of metronidazole , in the treatment of giardiasis in humans . In the trials included in the current meta-analysis , only one study [39] clearly described the inclusion of both adults and children ( 2–53 yr ) , while other studies exclusively included either only adults [40] or only children [29] , [41] , [42] , [43] , [44] , [45] . The inclusion of different age-groups potentially allows us to assess the effectiveness of treatment and to ascertain the extent to which side effects occur in different age-groups . Similarly , including patients with diverse clinical presentations ( i . e . asymptomatic , symptomatic; acute , subacute , chronic ) in clinical trials could give us the opportunity to evaluate the effect ( s ) of a given chemotherapy agent/protocol on patients with different clinical manifestations . From the information presented in the articles , it seems that only three articles [41] , [42] , [44] included both symptomatic and asymptomatic patients , although the clinical status of patients who participated in the study of Hall and Nahar [43] and Dutta et al . [45] was not clear . Including patients from different age-groups and with different clinical presentations in future studies would allow investigators to analyze whether albendazole has a differential effect that correlates to the disease clinical profile and/or age of the patient . Our analysis suggests that the study designs typically used for evaluating these drugs could be improved . Open-label trials may be suitable for comparing two extremely similar treatments to verify which one is more effective . Only Alizadeh et al . [39] and Hall and Nahar [43] used an adequate protocol for concealing the treatment protocol while determining the parasitological outcome . The six other trials either did not specify or were insufficient in using blinded observers to determine the outcome . Since albendazole and metronidazole may produce certain side effects specific to each drug and since these two drugs may be available in different forms , the use of homogenous therapy regimens and/or using blinded studies may be warranted in future clinical trials . Several factors may influence the effectiveness of a particular therapy . Nutritional and physiological conditions such as pregnancy and immunodeficiency could potentially alter the effectiveness of a specific drug as shown for other parasitic diseases [64]–[67] . Individuals with “pre-existing” nutritional and physiological ( pregnant women ) complications were excluded in only two studies among those we have analyzed [40] , [45] . Dutta et al . [45] excluded children having grade I and II malnutrition , patients with acute febrile illness and those on long term drug therapy; while Karabay et al . [40] excluded pregnant women and patients with fever from the study . In future studies , it would be desirable to include only patients with no known nutritional , physiological or immunological problems . Resistance of G . duodenalis strains to metronidazole and other drugs has been reported both in vitro and in vivo [8] , [68] , [69] . Misra et al . [29] reported a 100% cure rate in groups treated with either metronidazole or albendazole , while the other seven reported an effectiveness of 72 . 7–100% for metronidazole and 77–97% for albendazole . At least part of the so-called “failure-to-treat” cases might be attributed to the presence of “drug-resistant” strains , a mechanism to which none of the studies referred as a potential reason for treatment failure . The use of different combinations of albendazole with other anti-parasitic agents in future studies may be desirable in order to minimize the risk of the emergence of drug-resistant strains . However , the design of placebo-controlled double blinded clinical trials may help us to better understand the most appropriate regimen ( s ) and the most suitable chemotherapy protocols . Some limitations in the current analysis should be considered before making definitive conclusions . First , the small number of trials and patients included in the current analysis ( 8 studies , 900 patients ) led to wide confidence intervals that rendered some of the results inconclusive [70] . Second , publication bias is constantly a potential pitfall in meta-analyses . While we did not try to trace unpublished data for the current meta-analysis , our analysis failed to detect any suggestion of such bias ( Figure 3 ) . Third , heterogeneity among studies is another potential limitation to our meta-analysis . It might be argued that differences in the methods used for measuring the outcome of treatment could result in differences in the reported parasitological cure rates , as some combined methods are more sensitive than others . As seen in Table 4 , the effect sizes remained fairly constant in these analyses , suggesting that heterogeneity due to diverse outcome measures probably did not adversely affect our analyses . Performing repeated microscopy-based stool examinations on at least two consecutive occasions is sensitive enough to detect up to 95% of infections [71][72] . This could potentially explain why we did not see any difference among studies employing diverse methods since all the studies required at least two consecutive negative stool examinations before considering the patients cured . The high rate of side effects from metronidazole therapy for giardiasis , combined with the global emergence of resistant strains , led us to consider the effectiveness of alternative treatments . This meta-analysis revealed that albendazole cures Giardia infections with the same effectiveness as metronidazole . However , we were not able to show conclusively , due to limitations of the sample size , that its toxicity profile is more favorable than metronidazole . Therefore , we conclude that larger , double-masked , randomized controlled trials of albendazole and metronidazole with uniform outcome measures are needed to shed light on this important clinical question . | Giardiasis is one of the most common intestinal protozoal infections worldwide . Although metronidazole is the most common drug used to treat giardiasis in humans , its use is associated with a variety of side effects . Poor compliance and the emergence of metronidazole-resistant strains may restrict use of the drug . Albendazole is an orally administered broad-spectrum anthelmintic agent . The use of albendazole has fewer side effects than metronidazole . The anthelmintic has been used against Giardia duodenalis both in vivo and in vitro with different results . However , the current meta-analysis assessed the effectiveness and safety of albendazole compared with metronidazole for the treatment of giardiasis in humans . After searching different databases , eight comparative randomized clinical trials , including 900 patients , met our criteria and were selected for the current meta-analysis . Results showed that albendazole was as effective as metronidazole for the treatment of giardiasis in humans and people receiving the drug tended to have fewer side effects compared with those who received metronidazole . Given the safety , effectiveness , and low costs of albendazole , this drug may be considered a potential alternative and/or a replacement for the existing widely used metronidazole in the treatment of giardiasis in humans . | [
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] | [
"infectious",
"diseases/protozoal",
"infections",
"microbiology/parasitology"
] | 2010 | A Meta-analysis of the Effectiveness of Albendazole Compared with Metronidazole as Treatments for Infections with Giardia duodenalis |
Leprosy reactions are a significant cause of morbidity in leprosy population . Erythema nodosum leprosum ( ENL ) is an immunological complication affecting approximately 50% of patients with lepromatous leprosy ( LL ) and 10% of borderline lepromatous ( BL ) leprosy . ENL is associated with clinical features such as skin lesions , neuritis , arthritis , dactylitis , eye inflammation , osteitis , orchitis , lymphadenitis and nephritis . ENL is treated mainly with corticosteroids and corticosteroids are often required for extended periods of time which may lead to serious adverse effects . High mortality rate and increased morbidity associated with corticosteroid treatment of ENL has been reported . For improved and evidence-based treatment of ENL , documenting the systems affected by ENL is important . We report here the clinical features of ENL in a cohort of patients with acute ENL who were recruited for a clinico-pathological study before and after prednisolone treatment . A case–control study was performed at ALERT hospital , Ethiopia . Forty-six LL patients with ENL and 31 non-reactional LL matched controls were enrolled to the study and followed for 28 weeks . Clinical features were systematically documented at three visits ( before , during and after predinsolone treatment of ENL cases ) using a specifically designed form . Skin biopsy samples were obtained from each patient before and after treatment and used for histopathological investigations to supplement the clinical data . Pain was the most common symptom reported ( 98% ) by patients with ENL . Eighty percent of them had reported skin pain and more than 70% had nerve and joint pain at enrolment . About 40% of the patients developed chronic ENL . Most individuals 95 . 7% had nodular skin lesions . Over half of patients with ENL had old nerve function impairment ( NFI ) while 13% had new NFI at enrolment . Facial and limb oedema were present in 60% patients . Regarding pathological findings before treatment , dermal neutrophilic infiltration was noted in 58 . 8% of patients with ENL compared to 14 . 3% in LL controls . Only 14 . 7% patients with ENL had evidence of vasculitis at enrolment . In our study , painful nodular skin lesions were present in all ENL patients . Only 58% patients had dermal polymorphonuclear cell infiltration showing that not all clinically confirmed ENL cases have neutrophilic infiltration in lesions . Very few patients had histological evidence of vasculitis . Many patients developed chronic ENL and these patients require inpatient corticosteroid treatment for extended periods which challenges the health service facility in resource poor settings , as well as the patient’s quality of life .
Leprosy is a disease caused by Mycobacterium leprae , an intracellular acid-fast bacillus[1] . It mainly infects the skin and peripheral nerves[2] . The disease manifests with a spectrum of clinical pictures ranging from the localized tuberculoid leprosy ( TT ) to the generalized lepromatous leprosy ( LL ) types forming the two poles of the five point spectrum [3] . Erythema nodosum leprosum ( ENL ) is an immune-mediated inflammatory complication affecting about 50% of patients with lepromatous leprosy ( LL ) and 10% of borderline lepromatous ( BL ) patients [4–6] . ENL can occur before , during or after successful completion multi-drug therapy ( MDT ) . The onset of ENL is acute , but it may pass into a chronic phase and can be recurrent [7] . ENL affects multiple organs and causes systemic illness [8] . It is clinically characterized by the occurrence of crops of tender skin lesions [9] . Histologically , neutrophils are considered the hall mark of ENL[10] . The histology of ENL lesions shows an intense perivascular infiltrate of neutrophils throughout the dermis and subcutis [10] . However , not all clinically confirmed ENL cases have neutrophilic infiltration in lesions[11] . The underlying immunologic mechanisms of ENL have not been fully understood . The hypothesis of ENL as an immune-complex mediated disease proposed in the 1960s has yet to be supported by definitive evidence . Granular deposits of immunoglobulin and complements in the dermis of ENL lesion has been found by using direct immunofluorescence techniques which were absent in non-reactional LL lesions [12–14] . However , some investigators have reported the presence of immunoglobulin and complement deposits in ENL lesions as well as in LL lesions [15–17] . The contribution of cell-mediated immunity in the pathogenesis of the disease has been suggested but not supported by definitive evidence[18] . Several studies [19–23] have reported increased percentage of CD4+ T-cells and reduced CD8+ T-cells with an increased CD4+/CD8+ ratio in patients with ENL compared to patients with non-reactional lepromatous leprosy . Other studies have however , also reported a reduced CD4+/CD8+ ratio and increased percentage of CD8+ T-cells in patients with ENL compared to patients with LL [24] . The inflammatory condition of ENL may cause significant morbidity and mortality if it is not treated on time . [25] . In Ethiopia , patients with ENL are treated with corticosteroids for several months or years . Many patients require high doses of prednisone to control inflammation which could lead to complications . A significant proportion of deaths associated with long-term use of these drugs has been reported [25] . Having awareness of the diverse clinical features of ENL is useful for the accurate diagnosis and successful management of the disease . However , there are only few prospective studies describing the clinical features and there relative frequencies in ENL . A cross-sectional international multicentre study of the clinical features of ENL including 292 patients in 7 countries has reported that a significant number of patients had extra-cutaneous pathology such as peripheral oedema , large joint arthritis , lymphadenitis , and orchitis [9] . We set up a case control follow up study to investigate the clinico-pathological features of ENL . We compared the clinical and histological features in patients with ENL reactions to matched uncomplicated non-reactional LL patient controls before and after prednisolone treatment of ENL cases . ENL patients have diverse clinical manifestations . Therefore , prospective documentation of the clinical manifestations of patients with ENL is useful for accurate diagnosis of ENL . Unlike previous cross-sectional studies , in the present study we obtained clinical data and clinical sample ( skin biopsy ) from cases ( ENL ) and controls ( LL ) before , during and after treatment . The controls were matched with cases with respect to age , sex and duration of leprosy diagnosis . Hence , the present findings are more informative and show the dynamics of clinical features of ENL before and after treatment .
Informed written consent for blood and skin biopsies were obtained from patients following approval of the study by the Institutional Ethical Committee of London School of Hygiene and Tropical Medicine , UK , ( #6391 ) , AHRI/ALERT Ethics review committee , Ethiopia ( P032/12 ) and the National Research Ethics Review Committee , Ethiopia ( #310/450/06 ) . A case control study was conducted between December , 2013 and October , 2015 at All Africa Leprosy and , Tuberculosis Rehabilitation and Training Centre ( ALERT ) Hospital , Ethiopia . This is the main leprosy specialized hospital in Ethiopia . Hence , it is an ideal hospital to obtain referred leprosy patients from all regions in the country . Children below 18 years old , adults above 65 years old , pregnant and lactating mothers , patients with other clinical forms of leprosy ( TT , BT , BB , BL and T1R ) were excluded from the study . Forty-six untreated patients with ENL and 31 LL controls were enrolled into the study and followed for 28 weeks . The controls were age and sex matched with cases ( ENL ) . ENL was clinically diagnosed when a patient with LL leprosy had painful crops of tender cutaneous erythematous skin lesions [5] . Lepromatous leprosy was clinically diagnosed when a patient had widely disseminated nodular lesions with ill-defined borders and BI above 2 [7] . New ENL was defined as the occurrence of ENL for the first time in a patient with LL . The nature of ENL was defined as acute for a single episode lasting less than 24 weeks while on corticosteroids treatment , recurrent if a patient experienced a second or subsequent episode of ENL occurring 28 days or more after stopping treatment for ENL and chronic if occurring for 24 weeks or more during which a patient required ENL treatment either continuously or where any treatment free period had been 27 days or less [7] . Clinical data were collected using a standard form that had been developed by the Erythema Nodosum Leprosum International STudy ( ENLIST ) group . Demographic , clinical and laboratory data were recorded including evidence of any nerve function impairment ( NFI ) using voluntary muscle and Semmes-Weinstein monofilament sensory testing . Nerve function impairment ( NFI ) was defined as clinically detectable impairment of sensory or motor nerve function . New NFI was defined as NFI present for less than six months[26] . The bacterial Index ( BI ) at leprosy diagnosis was obtained for all recruited patients . BI at ENL reaction was also obtained at enrolment . Six millimetre skin biopsies were obtained from each ENL case before and on 24th week after prednisolone treatment of ENL cases . Similarly , 6mm biopsy was obtained during enrolment and on the 24th week of recruitment from matched non-reactional LL controls . Biopsies were taken from the active erythematous new skin lesions in all patients with ENL and from nodular LL lesions . Biopsies were obtained from the same area for cases and control . Biopsies were stored in 10% formalin until processed . Sections were stained with Haematoxylin and Eosin stain and examined by two histopathologists independently . The pathologists were not aware of the clinical diagnosis . Bacterial index ( BI ) was obtained for each patient as a routine investigation . When a polymorphonuclear neutrophilic infiltrate on the background of a macrophage granuloma accompanied by oedema and often with evidence of vasculitis and/or panniculitis was seen , the sample was classified as ENL . The presence of macrophage and foam cell collections with numerous bacilli interspersed with sparse number of lymphocytes in histological sections was defined as LL [27] . The anonymised clinical and Histopathology data were entered into an Excel database and analysed using Stata 14 version 2 and SPSS 23 version 1 Statistical Software . Depending on the nature of the variable and the normality of the data , either parametric or non-parametric analysis was used . Categorical variables were analysed by non-parametric methods and normally distributed numerical variables with parametric methods . Whenever mean is used for comparison , data presentation has followed the form of mean ± standard error of the mean ( SE ) . The level for statistical significance was set at α = 5% with 95% confidence interval .
Clinical data were obtained on 77 patients ( 46 LL patients with ENL reactions and 31 non-reactional LL patients ) at recruitment ( Table 1 ) . The male to female ratio was 2:1 with a median age of 27 . 5 [range: 18–56] years in patients with ENL and nearly 3:1 with a median age of 25 . 0 [range: 18–60] years in patients with non-reactional LL controls . The age range of females in both groups was relatively narrow ( 18–35 years ) compared to males ( 18–60 ) . More than half of the patients with ENL had previously been treated with MDT . Half of the patients with ENL had acute ENL at the time of enrolment with mean BI 3 . 9 ±0 . 205 SE ( standard error ) . Recurrent ENL cases had the highest mean BI ( 4 . 9 ±0 . 409 SE ) at leprosy diagnosis whereas acute and chronic cases had comparable mean bacterial index ( BI ) ( Table 1 ) . Pain was the most common symptom reported by patients with ENL . Ninety-eight percent of the patients with ENL had pain at enrolment . About 80% of the patients with ENL had reported skin pain and more than 70% had nerve and joint pain during enrolment . Other pain sites reported include bone , digits , eyes , muscles , lymph nodes and testes ( Fig 1 ) . Fever was reported by 31 ( 71 . 7% ) patients with ENL . Sixteen ( 34 . 8% ) patients with ENL reported depression and 47 . 8% nasal stuffiness . Other reported symptoms included peripheral oedema , insomnia , anorexia , weight loss , joint swelling and malaise ( Fig 2 ) . About 96% individuals had nodular cutaneous lesions , about two-third had subcutaneous nodules and a quarter of patients had scar . While one-third of the patients had ulcerated lesions , only 4% had necrotic lesions . Eight patients ( 17 . 3% ) had vesicles , bullae or pustular lesions ( Fig 3 ) . In most patients with ENL ( 73 . 9% ) , the number of skin lesions recorded at the time of enrolment was between 11 to 50 . Few patients had five or less skin lesions . Almost all patients ( 97 . 8% ) had skin lesions on the upper limbs . Many patients also had skin lesions on the lower limbs ( 95 . 7% ) or on the head and neck ( 63 . 0% ) . Half of the patients reported reduced nerve sensation . Paraesthesia and hyperaesthesia were reported by 13% and 23 . 9% of patients respectively ( Table 2 ) . More than half ( 52 . 2% ) of patients with ENL had old nerve function impairment ( NFI ) while 13% had new NFI at the time of enrolment . Facial oedema was reported in 56 . 5% of the patients with ENL and nearly half ( 47 . 8% ) of the patients had oedema on their lower limbs . Other organs involved in the patients with ENL were small joint arthritis ( 28 . 3% ) , large joint arthritis ( 15 . 2% ) , conjunctivitis ( 4 . 3% ) , lagophthalmos ( 2 . 2% ) , scleritis ( 8 . 7% ) , lymph node ( 15 . 2% ) and dactylitis ( 2 . 2% ) ( Table 2 ) . Paraffin- embedded sections of skin biopsy samples from ENL and LL lesions were examined by a histopathologist ( Fig 4 ) . Neutrophils infiltration was noted more ENL lesions ( 58 . 9% ) than LL lesions ( 14 . 3% ) before treatment ( P = 0 . 004 ) . Lymphocytes infiltration was recorded in all ENL and LL lesions . Foamy histiocytes were more frequently seen in LL lesions ( 95 . 3% ) than in ENL lesions ( 85 . 3% ) although the difference was not statistically significant at enrolment . After 24 weeks treatment of ENL , the percentage of foamy histiocytes was significantly decreased in ENL cases ( 42 . 2% ) compared to LL cases ( 85 . 7% ) ( p = 0 . 001 ) . Panniculitis was diagnosed in 62 . 5% of lesions from patients with ENL reactions . After 24 weeks of ENL treatment , neutrophils infiltration was noted in 5 biopsies from patients with ENL reactions , lymphocytes infiltration was seen in 20 biopsies of patients with ENL ( Table 3 ) .
The number of male patients with ENL recruited to the study was twice the number of female patients and similar to a five-year retrospective data ( 2008–2013 ) which showed the number of male to female ratio to be 1 . 7:1 [7] . In our study , the median age for male and female patients with ENL was 28 . 0 and 26 . 7 years respectively . Both male and female patients with ENL were relatively older than the LL patient controls ( median age: male = 26 years , female = 21 years ) . The slight difference in median age between the two groups could be explained by natural the course of the disease . Patients usually develop ENL reaction after having either LL or BL clinical forms for some time . Interestingly , the age range of females in both groups was relatively narrow ( 18–35 years ) compared to males ( 18–60 years ) indicating that either younger females are more likely to have access to health institutions for various reasons than older females in low-income countries where health facilities are relatively inadequate[28] or ENL is relatively common among younger females of child bearing age due to various biological reasons [29–31] . Our data confirm that a significant proportion of cases had chronic ENL ( 39% ) . This implies that these patients require , in our setting , corticosteroid treatment for extended periods , often at high doses… But high doses of corticosteroids do not always control the inflammation and also pose life-threatening risks for patients [9 , 32 , 33] . Chronic ENL cases are a burden to referral hospitals in these resource poor settings . as well as to their communities . A study in rural India has shown that families with at least one ENL case incur loss of more than 40% of total household income compared to families without ENL case due to out of pocket expenditure for treatment-seeking ( direct cost ) and loss of income resulting from reduced productivity ( earning potential ) of household members ( indirect cost ) . This implies that households affected by ENL face significant economic burden and are at risk of being pushed further into poverty [34] . In this study , several cutaneous manifestations of ENL were documented highlighting the heterogeneous nature of ENL clinical manifestation . Pain was was a symptom reported by 98% of the patients . Most patients had skin pain ( 80 . 4% ) , nerve pain ( 73 . 9% ) , joint pain ( 71 . 7% ) and bone pain ( 69 . 2% ) . The most frequent site of pain due to ENL in our study was the skin which is explained by the fact that 95% of patients with ENL had skin lesions . Our finding is in agreement with a previous report [7] . Bone pain was reported in two-third of our study patients which is higher than the previous report [7] . The difference between the two studies is likely due to the retrospective nature of the previous study which was not reliant on case note recording unlike the current study . The nerve function impairment ( NFI ) was reported in 65% of our study patients , which was higher than the 51 . 3% NFI in six countries as reported by Walker et al [35] . Among the 65% of patients reporting NFI , 80% of them had old NFI . This highlights the prevalence of NFI in patients with ENL the high risk of developing permanent disability . A study by Santos Santos , de Mendonça Neto [36] , in northern Brazil had identified NFI and leprosy reactions as the main risk factors associated with the development of disability in leprosy patients . The same authors reported that NFI was strongly associated with physical disability in children under 15 [37] . In our study , 50% of patients with ENL had WHO disability grade-1 ( G1D ) while 4 . 3% had Grade- 2 disability ( G2D ) . The proportion of grade 2 disability was lower than the national figure ( 10 . 2% ) in 2014 [38] . Histopathologically , neutrophil infiltration was noted in 58 . 8% of patients with ENL compared to 14 . 3% in LL controls before treatment . This confirms that a neutrophilic infiltration cannot be used as the sole histological marker for ENL The absence of neutrophil infiltration has been reported in 36% of ENL skin lesions in Pakistani patients who had classical signs and symptoms of ENL[11] . Similarly , a cross-sectional study on the histological features of leprosy reactions in Indian patients by Sarita , Muhammed [39] showed that 43% ENL skin lesions did not have histological evidence of neutrophil infiltration . Our findings agree with these two studies . Previous studies by others [40–42] , reported finding neutrophil infiltration in all ENL lesions . The varying reports of neutrophil infiltration in ENL lesions could be attributed to several factors . If the definition of ENL includes the presence of neutrophils in the case definition then all cases will have it , as did Aldhe et al who investigated the presence of cellular neutrophil infiltration on histologically confirmed ENL cases [42] . Delay between the onset of reaction and the timing of obtaining the biopsy in those without neutrophilic infiltrate , as dermal oedema may be missed in older reactional lesions could cause these differences . Discordance between pathologists and standard operating procedures ( SOPs ) of slide preparations are also potential areas that should be further investigated to evaluate their impact on the findings of neutrophil infiltration in tissue sections . Previous reports suggested vasculitis as part of ENL reaction commonly seen in Indian patients [43] , only 5 ( 14 . 7% ) of our patients had evidence of vasculitis . Similar observations had been made by Sarita et al and Adhe et al [39 , 44] . Inclusion of a large number of patients with ENL and LL controls was one of the strengths of this study . The other strength of the study had been that clinical data were obtained from each patient three times unlike the previous cross-sectional studies . A weakness of the study is that there may have been biased recruitment because of the need to have good follow–up of patients . In conclusion , we have shown that skin , nerve and joint pain are the most common clinical symptoms reported in patients with ENL . These clinical conditions are usually difficult to manage with corticosteroids at referral Hospitals . Most of our patients with ENL then developed chronic ENL and these patients require in patient corticosteroid treatment for extended periods which challenges the health service facility in resource poor settings . More than half of the patients with ENL had old NFI which indicates that these patients are at a higher risk of developing permanent disability . Hence , better attention to care and NFI needed in these patients . | Leprosy reactions ( Type 1 and 2 ) are important causes of nerve damage and illness . Erythema Nodosum Leprosum ( ENL ) also called type 2 reactions is a severe multisystem immune-mediated complication of borderline and lepromatous leprosy . ENL causes high morbidity and mortality and usually requires urgent medical attention . ENL can occur before , during , or after completion of MDT . The diagnosis and treatment of ENL is largely based on clinical symptoms . However , the clinical symptoms are heterogeneous and may vary from patient to patient . Although thalidomide is an effective drug for ENL treatment , it is not available in many leprosy endemic countries including Ethiopia . In spite of its adverse effects , in many endemic countries corticosteroid is the only available drug for ENL treatment , usually being used for prolonged periods . Therefore , alternative and effective drugs are required to reduce the burden of ENL . To establish which drugs will be effective in the treatment of ENL it is necessary to have a clear picture of the clinical and histological features of the disease . We systematically documented these features of ENL and compared them with matched non-reactional LL controls . Thus , the findings will help to develop better ENL diagnosis and treatment options . | [
"Abstract",
"Introduction",
"Materials",
"and",
"methods",
"Results",
"Discussion"
] | [
"blood",
"cells",
"inflammatory",
"diseases",
"rheumatology",
"medicine",
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"immune",
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"geographical",
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"invas... | 2017 | Clinico-pathological features of erythema nodosum leprosum: A case-control study at ALERT hospital, Ethiopia |
Analyses of circulating metabolites in large prospective epidemiological studies could lead to improved prediction and better biological understanding of coronary heart disease ( CHD ) . We performed a mass spectrometry-based non-targeted metabolomics study for association with incident CHD events in 1 , 028 individuals ( 131 events; 10 y . median follow-up ) with validation in 1 , 670 individuals ( 282 events; 3 . 9 y . median follow-up ) . Four metabolites were replicated and independent of main cardiovascular risk factors [lysophosphatidylcholine 18∶1 ( hazard ratio [HR] per standard deviation [SD] increment = 0 . 77 , P-value<0 . 001 ) , lysophosphatidylcholine 18∶2 ( HR = 0 . 81 , P-value<0 . 001 ) , monoglyceride 18∶2 ( MG 18∶2; HR = 1 . 18 , P-value = 0 . 011 ) and sphingomyelin 28∶1 ( HR = 0 . 85 , P-value = 0 . 015 ) ] . Together they contributed to moderate improvements in discrimination and re-classification in addition to traditional risk factors ( C-statistic: 0 . 76 vs . 0 . 75; NRI: 9 . 2% ) . MG 18∶2 was associated with CHD independently of triglycerides . Lysophosphatidylcholines were negatively associated with body mass index , C-reactive protein and with less evidence of subclinical cardiovascular disease in additional 970 participants; a reverse pattern was observed for MG 18∶2 . MG 18∶2 showed an enrichment ( P-value = 0 . 002 ) of significant associations with CHD-associated SNPs ( P-value = 1 . 2×10−7 for association with rs964184 in the ZNF259/APOA5 region ) and a weak , but positive causal effect ( odds ratio = 1 . 05 per SD increment in MG 18∶2 , P-value = 0 . 05 ) on CHD , as suggested by Mendelian randomization analysis . In conclusion , we identified four lipid-related metabolites with evidence for clinical utility , as well as a causal role in CHD development .
Advances in high-throughput technologies can fuel discovery of novel biomarkers for early detection and prevention of coronary heart disease ( CHD ) . Metabolomic profiling , or metabolomics , provides a holistic signature of biochemical activities in humans by detecting and quantifying low-weight molecules ( <1 , 500 Da ) . Integration of genetic information and metabolomics data can generate new hypotheses regarding underlying pathophysiological processes [1] . Moreover , targeted metabolomics studies have identified several associations between metabolites and cardiovascular disease ( CVD ) risk [2] , [3] highlighting the importance of metabolic pathways in the development of atherosclerosis . The primary aim of our study was to identify novel CHD biomarkers by performing non-targeted metabolomics profiling in 3 , 668 individuals free of CHD at baseline from three population-based prospective cohort studies . Our secondary aims were to delineate the underlying biological mechanisms and to evaluate clinical utility , as well as potential causal effects for those metabolites showing strong evidence of association . For these purposes , we analyzed associations with measures of oxidative stress , inflammation and subclinical CVD , as well as integrated metabolomics and genetics data .
In this study of 3 , 668 participants from three prospective population-based cohorts , we investigated the association of circulating metabolites measured by liquid chromatography coupled mass spectrometry with incident CHD . In our discovery cohort , 32 metabolites were associated with CHD , of which 84% showed a directionally consistent association with CHD in our validation cohort . In multivariable analyses adjusted for main cardiovascular risk factors , three metabolites remained associated with CHD . In a targeted LysoPC analysis , we detected one additional significant association resulting in a total of four metabolites associated with CHD independently of main cardiovascular risk factors: LysoPC 18∶1 , LysoPC 18∶2 , MG 18∶2 and SM 28∶1 . These biomarkers moderately improved risk reclassification beyond traditional risk factors , when commonly used risk categories were considered . Lysophosphatidylcholines were negatively associated with BMI , markers of inflammations and subclinical cardiovascular disease , while a reverse pattern was observed for MG 18∶2 . We found evidences for a causal effect of MG 18∶2 on CHD independently of triglycerides levels . Finally , we uncovered several genome-wide significant SNPs and suggestive signals for association with LysoPCs , some of which have not been previously observed . We observed a strong positive association between MG 18∶2 and CHD . The majority of circulating monoglycerides are released by the action of lipoprotein lipase and hepatic lipase , which catalyze the hydrolysis of triglycerides to provide non-esterified fatty acids and monoglycerides for tissue utilization [10] . Monoglycerides are further converted into free fatty acids and glycerol by monoglyceride lipase . Within the intestinal wall , monoglycerides are used to resynthesize diglycerides and triglycerides via monoacylglycerol pathway before being transported in lymph to the liver . Several observations suggest an involvement of MG 18∶2 in the pathogenesis of CHD . First , MG 18∶2 is central in the synthesis and breakdown of triglycerides and a causal effect of plasma triglyceride levels on CHD risk have recently been supported by a large Mendelian randomization analysis [11] . Although highly correlated , when both MG 18∶2 and triglycerides were included in the same model , both showed independent significant associations with CHD . Moreover , when separately added to a model with main cardiovascular risk factors , MG 18∶2 was a better predictor of CHD than triglycerides . Second , MG 18∶2 was associated with higher levels of cardiovascular risk factors and markers of subclinical CVD and oxidative stress . Third , Mendelian randomization analysis suggested a weak , but positive causal effect of MG 18∶2 on CHD risk . Several SNPs reported for association with CHD remained associated with MG 18∶2 ( in the PCSK9 , HHIPL1 , PLG , ApoE/ApoC1 , COL4A1/COL4A2 regions , P-values<0 . 05 ) , even after adjustment for main cardiovascular risk factors . We observed a strong age-dependent association between LysoPC 18∶2 , LysoPC 18∶1 and CHD risk , with stronger inverse association in older individuals . These LysoPC species were further characterized to be associated with higher HDL-C and total cholesterol levels , and lower BMI and markers of subclinical CVD . Moreover , they were highly correlated , suggesting shared biological mechanisms . LysoPCs are mostly derived from phosphatidylcholines ( PC ) and several mechanisms contribute to their formation . A large component of LysoPC in plasma is derived from PC by the glycoprotein lecithin cholesterol acyltransferase ( LCAT ) . Another well-known mechanism of LysoPC production , which mainly takes place in tissues , is via PC hydrolysis by the action of secretory PLA2 family [4] . Although higher levels of LysoPCs have been observed during the oxidative modification of LDL-C that accompanies their conversion to atherogenic particles , it has also been shown that LysoPCs produced by a PLA2-like activity of Paraoxanase 1 contributes to the inhibition of macrophage biosynthesis and that they consequently reduce cellular cholesterol accumulation and atherogenesis [12] . LysoPC are also produced by endothelial lipase and hepatic lipase [13] . Hepatic lipase , which is also involved in triglyceride hydrolysis , is mainly responsible of the production of unsaturated LysoPCs [14] , [15] . Although LysoPCs are commonly seen as pro-inflammatory and pro-atherogenic metabolites [16] , recent population-based studies have suggested a protective effect of LysoPCs on cardiovascular risk . In a study of type 2 diabetes , LysoPC 18∶2 was found to be inversely associated with incident diabetes and impaired glucose tolerance [17] . Fernandez and colleagues found an inverse association of LysoPC 16∶0 and LysoPC 20∶4 with incident CVD and reduced intima media thickness [18] . More recently , Stegemann and colleagues [19] found an inverse association between several LysoPC species and incident CHD . Our study confirms and extends these previous findings . Using a Mendelian randomization approach , we suggest that the observed association between LysoPCs and incident CHD are likely to not be causal . Our study has several strengths . To our knowledge , this is the largest study investigating the metabolome in relation to incident CHD . Mass spectrometry-based metabolomics is extremely sensitive and allows detection of more metabolites than nuclear magnetic resonance-based methods [20] . We validated our findings using an independent population , with a different blood collection method , blood partition ( serum instead of plasma ) and age range . At the cost of augmented heterogeneity , this approach has the advantage to increase the generalizability of our findings . All three study samples were longitudinal and we have studied incident events decreasing the risk of reverse causation or selection bias as an explanation to our observations . We performed extensive characterization of underlying biological mechanisms , clinical utility , and potential causal effects for those metabolites showing strong evidence of association . We also acknowledge several limitations of our study . First , we used a non-targeted approach , meaning that every ion detected by mass spectrometry was treated as a separate variable , increasing the multiple-testing burden . We have previously shown that this approach does not affect the FDR point estimate , but might increase its variability [21] . However , this method is advantageous because it does not rely on pre-annotation and allows inclusion of unknown metabolites in the analyses ( which subsequently can be identified using targeted methods ) . Moreover , we used a single analytical platform ( liquid chromatography-mass spectrometry ) ; the integration of multiple analytical platforms is a way of increasing the number of detectable metabolites . Second , non-targeted metabolomics is subject to co-elution of metabolites , ion suppression and imprecision in metabolites quantification , since each value assigned to the metabolic feature can only be interpreted as mass ion intensity . However , we do not have reason to believe that such biases would systematically affect CHD cases , since our outcome is measured prospectively and metabolomic profiling performed in a blinded fashion . Moreover , each sample has been analyzed in non-consecutive randomized duplicates , which minimize the risk of systematic biases . Third , the use of 15% FDR in the discovery phase is larger than in some other studies , but is justified by the high degree of correlation in the data , due to the existence of multiple metabolic features for a single metabolite . Moreover , metabolites were replicated ( P-value<0 . 05 ) in an independent study sample . To evaluate if our replication strategy was sufficient to minimize the number of false positives , we estimated the expected false discovery rate in the replication sample ( TwinGene ) [22] . This was calculated as 0 . 23% ( S1 Text ) , meaning that only 0 . 23% of metabolites replicating at P<0 . 05 are expected to be false positives , suggesting that our two-tier approach correctly control the number of false positives . Finally , as our study samples consist of middle-aged to elderly individuals of Northern European decent , the generalizability to other ethnicities and younger age groups is unknown . In conclusion , in the largest study of the metabolome in relation to incident CHD to date , we identified lysophosphatidylcholines 18∶1 , 18∶2 , monoglyceride 18∶2 and sphingomyelin 28∶1 as risk factors of coronary heart disease and suggested a causal effect for monoglyceride 18∶2 on CHD . Future experiments should mainly focus on determining the mechanisms by which these metabolites of lipid metabolism might be involved in pathogenesis of coronary heart disease .
We performed metabolomic profiling of blood samples from three studies: TwinGene , ULSAM and PIVUS . An overview of the study design is illustrated in Fig . 1 , and a detailed description of each study is given in the S1 Text . In brief , TwinGene is a longitudinal sub-study of 12 , 591 individuals ( 55% women ) from the Swedish Twin Register [23] . For the purpose of metabolomic profiling , we designed a case-cohort of incident CHD events and a matched sub-cohort ( controls ) stratified on age and sex [24] . In the final analysis we included serum samples from 1 , 670 unrelated individuals . The Uppsala Longitudinal Study of Adult Men [25] ( ULSAM; http://www2 . pubcare . uu . se/ULSAM/ ) is an ongoing , longitudinal , epidemiologic study of men born between 1920 and 1924 in Uppsala County , Sweden . In the final analysis , we included plasma samples from 1 , 028 individuals investigated at 70 years of age . The Prospective Investigation of the Vasculature in Uppsala Seniors [26] ( PIVUS; http://www . medsci . uu . se/pivus/ ) is a population-based study of 70-year old individuals living in Uppsala . In the final analysis , we included serum samples from 970 individuals . Incident CHD cases were defined as hospitalization or death with a primary diagnosis for acute myocardial infarction or unstable angina . This information was collected by linking the personal identity numbers from TwinGene and ULSAM participants with the Swedish National In-Patient Register and the Cause of Death Register up to the 31th December 2010 , which comprise the end of follow-up of the present study . Laboratory procedures for metabolomics have been previously described [21] , [27] and are detailed in the S1 Text . Briefly , metabolomic profiling was performed on Acquity UPLC coupled to a Xevo G2 Q-TOFMS ( Waters Corporation , Milford , USA ) with an atmospheric electrospray interface operating in positive ion mode . Non-consecutive duplicate sample aliquots of 1 µL were injected onto a Acquity UPLC BEH C8 analytical column . Mass analysis was performed in the full scan mode ( m/z 50–1200 ) . Genotyping arrays used in each study are described in the S1 Text . All the samples underwent the same quality control ( QC ) and imputation of polymorphic 1000 genome CEU SNPs ( Phase I , version 3 ) performed using IMPUTE2 . Methods for measuring the 21 biological markers and imaging features in PIVUS have been previously described [28]–[30] . Raw data were processed using XCMS software [31] . Procedures to perform non-targeted metabolomics in large-population studies have been previously described by our group [21]; the code has been made publically available at https://github . com/andgan/metabolomics_pipeline . Metabolic feature detection , alignment , grouping , imputation and normalization were performed separately for each study ( S1 Text ) . Each feature is characterized by a specific mass-to-charge ratio ( m/z ) and retention time . A single metabolite is normally represented by more than one feature . Indiscriminant ( id ) MS and idMS/MS spectra were generated for all the significant features [27] . Those with highly similar spectra , strong correlation and similar retention time were deemed to be from the same metabolite . We used the spectra to identify the corresponding metabolite . Four approaches were considered , in agreement with what has been suggested by the Metabolomics Standard Initiative ( MSI ) [32] and as described in the S1 Text . In ULSAM , we tested the association between each feature and incident CHD using a Cox proportional hazards model adjusted by age at baseline . We restricted our analysis to a 10-year follow-up since most biological markers experience a decreasing association with longer follow-up due to regression dilution bias . To evaluate the proportional hazard assumption we obtained , for each feature , a P-value from the Schoenfeld residual-based test; we did not detect any significant deviation from the proportionality assumption after correcting for multiple testing . Features that were significantly associated with CHD in ULSAM at 15% false discovery rate ( FDR ) level were taken forward for replication in TwinGene . In TwinGene , we fitted Cox models adjusted for age and sex , and re-weighted for the inverse of the sampling probability using the Borgan “Estimator II” [24] . Features with P-value<0 . 05 in TwinGene and showed association with consistent direction were considered as replicated . In the multivariable analysis , we studied the association between replicated features and CHD adjusting for main cardiovascular risk factors ( sex , age , systolic blood pressure , BMI , current smoking , antihypertensive treatment , LDL-C , HDL-C , natural logarithm-transformed triglycerides and prevalent diabetes ) . Association analyses between metabolic features and markers of oxidative stress , inflammation and subclinical CVD in PIVUS was performed using linear regression adjusted only for age and sex , and for the same cardiovascular risk factors described above . In TwinGene , reclassification measures ( NRI , see S1 Text for additional details ) were calculated using a 10% and 20% threshold for a 10-year risk of event , as often done in previous literature [33] . The genome-wide association study ( GWAS ) analyses were performed in PLINK adjusting for age , sex ( where feasible ) and first three principal components; results were meta-analyzed using fixed effects inverse-variance weighted meta-analysis in METAL . Instrumental variables for the Mendelian randomization analysis were constructed using the GWAS results and tested for association with CHD using the results from the CARDIOoGRAMplusC4D consortium [9] . Criteria for exclusion of pleiotropic SNPs and additional methodological information can be found in the S1 Text . All participants gave informed written consent and the Ethics Committees of Karolinska Institutet or Uppsala University approved the respective study protocol . | Non-targeted metabolomic profiling of large population-based studies has become feasible only in the past 1–2 years and this hypothesis-free exploration of the metabolome holds a great potential to fuel the discovery of novel biomarkers for coronary heart disease ( CHD ) . Such biomarkers are not only important for risk stratification and treatment decisions , but can also improve understanding of cardiovascular disease pathophysiology to identify new drug targets . In this study , we investigated the metabolic profiles of more than 3 , 600 individuals from three population-based studies , and discovered four metabolites that are consistently associated with incident CHD . We integrate genetic and metabolomic analysis to delineate the underlying biological mechanisms and evaluate potential causal effects of the novel biomarkers . Specifically , we found one metabolite to be strongly associated with single nucleotides polymorphisms previously reported for association with CHD , and consistent with a potential causal role in CHD development , as suggested by Mendelian randomization analysis . | [
"Abstract",
"Introduction",
"Discussion",
"Materials",
"and",
"Methods"
] | [
"metabolism",
"biochemistry",
"biology",
"and",
"life",
"sciences",
"metabolomics"
] | 2014 | Large-scale Metabolomic Profiling Identifies Novel Biomarkers for Incident Coronary Heart Disease |
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